GENIUS Olympiad 

Let's build a better future together.

GENIUS Olympiad is an international high school project competition about environmental issues. It is founded and organized by Terra Science and Education and hosted by the Rochester Institute of Technology. GENIUS Olympiad will host projects in five general disciplines with an environmental focus.  

" Unless someone like you cares a whole awful lot, nothing is going to get better. It's not. " Dr. Seuss, The Lorax 

GENIUS Science creates innovative solutions to environmental problems using science and engineering.

GENIUS Creative Writing calls the public to take action on environmental problems and solutions using writing.  

GENIUS Business raises awareness of environmental values and social responsibility with novel green business plans. 

GENIUS Robotics provides students an understanding at the role of engineering and research on environment.

GENIUS Art heightens the public concern for environmental problems and solutions through artistic expression.

GENIUS Music motivates society to make positive change by pulling at the auditory heart strings through performance.  

GENIUS Short Film promotes behavioral changes regarding global issues through the lens and action of cameras.

GENIUS Coding allows students to use their coding skills and algorithmic knowledge to solve environmental issues.

Awardees are Announced

Congratulations to all participants and awardees!! For the awardee list   Click Here

Finalists are Announced

You should follow the detailed instructions provided on the finalist list page to prepare your presentation videos and registration. The deadline for registration, payments, and submitting presentation videos is May 15th.   Read More

Applications Deadline April 18!

GENIUS Olympiad 2022 applications will end on April 18 11.59 US EST. Finalist projects will be anounced by May 5th. Finalist project must submit a presentation video by May 15 for Virtual Judging.   Read More

Applications for GENIUS 2023 are now open

GENIUS Olympiad 2023 will be held in-person this year! We are accepting applications now.   Apply Now

Applications Starts on November 10

GENIUS Olympiad 2023 will be held in-person this year! Applications will start on November 10.   Read More

New Category: GENIUS CODING!!

GENIUS Olympiad offers a new category, GENIUS Coding, that allows students to use their coding skills to solve environmental issues. Students are expected to use Python programming to develop algorithms for problems given by GENIUS Olympiad. Read More

Organizing Country Based GENIUS Olympiad

Be a GENIUS Olympiad partner in your country: GENIUS Olympiad is looking to allow organizations to hold country-based Genius Olympiad fairs in their own country or region. If your organization is interested, please fill out our interest form as the first step in initiating communication about a partner fair. Read More

International Journal  

We invite all participants and all other high school researchers to publish with  International Journal of High School Research , a peer-reviewed journal, which is published by GENIUS Olympiad.   Read More

RIT SCHOLARSHIP PACKAGE

As one of the top 50 universities in the US, RIT encourages students to apply to RIT and take advantage of the GENIUS Olympiad scholarship. Please click read more to print the RIT-GENIUS Olympiad Scholarship letter. RIT will confirm your status with GENIUS Olympiad after you applied for RIT. Read More

GENIUS Olympiad Ukraine  

We are excited to announce our first country-based GENIUS Olympiad aggreement with Junior Academy of Sciences of Ukraine (JASU) under the auspices of UNESCO within the patronage of the Ministry of Education and Sciences of Ukraine. Read More

RIT Hosting GENIUS 2022

The Rochester Institute of Technology will host GENIUS Olympiad 2022.   Read More

RIT Special Hotel Offer

RIT Inn offers a special program for those who would like to stay in a hotel setting rather than college housing. Special rate for their newly renovated hotel with access to the pool, airport shuttles, and shuttles to campus. You need to make your own registration with the hotel if you choose to stay at RIT Inn. Read More

New Trip Option

Participants can choose SixFlags/NYCity as their trip option and spend one whole day at Six Flags. Read More

Application Process

Submit application, march 8  ,  11:59 pm us est .

$50 application fee per project.

 Deadline for US/EU fairs is April 17.

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Finalists Announced

Check full list of finalists

GENIUS finalist status can be checked in the application system

Participant Registration

 deadline: may 1.

$425 participation fee per participant

Request Visa Letters

April 3 - may 1.

Payment must be made before visa letters can be requested within the application system.

Trip & Travel Registration

April 3 - may 10.

NYC, DC , Boston, SixFlags trips 

Enter travel information for the team.

GENIUS Finals

Make sure to read Finalist Guide, and send us an email for questions.  

GENIUS Optional Trips

Cancelled for 2022.

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DC & NY Trips

3 Night or 4 Night Options: Spend 1 day in DC and 1 or 2 days in NYC.  

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DC & NY & IVY

6 Nights: After DC & NY trip, visit IVY colleges in NY and Boston. 

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DC & NY &  Six Flags   

4 Nights: Spend 1 day in DC,  1 day in NYC and 1 Day in Great Adventure.

Useful Links

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Video, Poster and Logos

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Finalist Guide and Rules

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Yearly / Daily Event Schedule

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Inter. Fair, Niagara Falls

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Finalists & Awards

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Judges, Sponsors, Host

Applicant Countries

The number of applicant countries for GENIUS Olympiad 2020 is .

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Multimedia Links

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GENIUS Logo

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GENIUS Poster

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GENIUS Video

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GENIUS Video Channel

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RIT Video Channel

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RIT Student Life

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Finalist Guide

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COMPLIMENTARY GENIUS OLYMPIAD EVENTS AND ACTIVITIES

The following attractions and activities will take place during GENIUS Olympiad as part of the regular program without a fee . You will learn and have fun during these activities.

Niagara Falls Trip

As part of GENIUS Olympiad, you will experience Niagara Falls State Park’s rushing torrents, spectacular scenery and one-of-a-kind attractions while letting your excitement flow as freely as the waters. Transportation to Niagara Falls (1.5 hrs travel) and a boxed lunch will be provided by the GENIUS Olympiad. All participants will be dropped at a shopping mall on the way back to campus.

  • You may walk right up to the base of Niagara Falls during the Cave of the Winds tour
  • You may take the the Maid of the Mist® boat ride (Tickets will be provided by GENIUS Olympiad as part of your registration.)
  • You may visit the aquarium and as well as a cinematic explanation of the formation of Niagara falls at the movie theater (both are fee-based).

GENIUS International Culture Fair

GENIUS International Fair is the place where students from all around the world get together to experience a wide variety of ethnic and cultural food, music, and dance. The purpose of the international fair is to provide an opportunity to all participants to promote and share their culture and country. Each country and state will be provided with table space to have displays and promotional items to promote their culture.

In addition, participants will be given an opportunity to perform ethnic and cultural music and dance. The international fair is a fun place to share, enjoy, learn, and make new friendships. Finalists will receive an email about registering stage performance (dance, singing, etc) ahead of time. On-the-spot performance requests may be denied due to time restrictions.

We encourage every group to bring cultural items to display as well as small gifts to exchange with others. Those who will perform will receive a small gift from GENIUS Olympiad.

RIT Open House

RIT Open House provides an opportunity to learn about college applications, financial aid, personal statement preparation, as well as one-on-one meetings with various departments and programs at RIT. You will receive in depth information about the programs and application process you are interested in.

Thank you for applying to GENIUS Olympiad 2020 and 2021. GENIUS Olympiad will host around 1,245 projects presented by around 2000 students this year.

  • Our finalist list posted below is the most accurate list, rather than the project status within the application system.
  • Those who appear on the list but do not have Finalist status within the application system should contact us via email as soon as possible.
  • If your name is on the finalist list, please follow the What is next section on this page.
  • We should note that the quality of the projects submitted has been increased significantly compared to previous years and we are very proud of all applicants for their work and effort.We also kept our acceptance rate the same as previuos years. Projects are reviewed out of 5 points by multiple reviewers and projects scored 3.1 and higher selected as finalist.
  • Please note that it is our policy not to send individual responses to those who are not selected as finalists. We are sorry about this, but our finalists will need a great deal of support at this time, and we do not have the staff to provide feedback on individual projects and their results.

GENIUS 2020-2021 Facts:

  • 2,481 projects were submitted, 1,245 projects were accepted (50% acceptance rate)
  • The number of projects submitted from the United States was 879 (35% of submitted projects)
  • The country where the most number of projects were submitted: South Korea with 261 projects, Ukraine with 115 projects, Kyrgyzstan with 112, Tajikistan with 92 projects, and Jordan with 75 projects)
  • The high school which submitted the most projects are Junior Academy of Science, Ukraine (82 projects), Jubille Schools, Jordan (50 projects),Wellspring Saigon International Bilingual School, Viet Nam (44 Projects), Seoul International School, South Korea (42 Projects), Lyceum for Gifted Students, Tajikistan (38 Projects),Yahya Kemal College, Macedonia (34 Projects), Pawling High Schools, U.S. NY, (31 projects), Complixo Escolar Privado International, Angola (30 projects).
  • The number of countries where the projects were submitted: 85
  • The number of US States where the projects were submitted: 42
  • The number of accepted Science projects: 679 out of 1,311 submissions (51% acceptance rate)
  • The number of accepted Art projects: 270 out of 567 submissions (48% acceptance rate)
  • The number of accepted Short Film projects: 60 out of 127 submissions (47% acceptance rate)
  • The number of accepted Creative Writing projects: 136 out of 287 submissions (47% acceptance rate)
  • The number of accepted Robotics projects: Will not be held this year.
  • The number of accepted Music projects: 31 out of 56 submissions (55% acceptance rate)
  • The number of accepted Business projects: 68 out of 134 submissions (50% acceptance rate)

WHAT IS NEXT? PLEASE FOLLOW THE STEPS!

  • If you do not see your project status as a finalist in the application system, but you have been announced as a finalist, please contact us via email at [email protected]
  • Login to the system and click on Participant Tab, and Add all participants who will attend the event, including teachers, parents, siblings, even they will stay in a hotel. Supervisor information can be different from what was submitted during the application process.
  • Login to the system and click on Participant Tab, and Add all student participants who will present.
  • Pay the listed participation fee ($20) in order to complete your registration. Please see the rules for fees.
  • International applicants: All information must be entered correctly.  Visa letters are sent to the whole group and you will apply for visas as a group. You will request B1 visas. You MUST make the participation fee payment in order to receive a visa letter. 
  • Fill out the travel information when you have purchased your tickets.  
  • Fill out the Trip information (optional) if you would like to attend one of the Boston/NYC/DC trips. We have a bus service from JFK Airport: One-way bus services from JFK airport (NY) to RIT University is $75. 
  • Click on the "Presentations" tab in the application system and provide your presentation video YouTube link. Follow the instructions in the virtual presentation guidelines below for your presentation.

Virtual Presentation Guidelines

  • For all of your finalist projects, you must submit a YouTube link for your presentations. For each project, you must submit single video link. Our system accepts only videos shared through YouTube.
  • For team projects, the registered participants must present their project together. All materials in your presentation must be sized and aligned to make the content readable and viewable by the judges. The presenter(speaker) video must be aligned to the top right corner throughout your presentation.
  • You need to create a presentation video that will allow you to efficiently describe your work, challenges you have faced, techniques that you have used, and possible future work/improvements if applicable. Your presentation must include a statement to explain your project's connection to the environmental issues which can be broadly defined. All presentations must start with the following introduction: "I am FirstName LastName and I am from YourState/Country".
  • Science: Your presentation video must include a full screen presentation (e.g. PowerPoint, Prezi) along with the speaker's video. e.g. You can use Zoom and record your presentation with the presenter video. Your presentation video should not exceed 12 minutes.
  • Art: Your presentation video must include a full screen image of your art project along with the speaker's video. e.g. You can use Zoom and record your presentation with the presenter video. In addition to item 3, your presentation should also elaborate on interpretation (artist statement) of your art work. Your presentation video should not exceed 9 minutes.
  • Short Film: You must submit a single presentation video which combines your film and 3 minutes presentation. In addition to item 3, your presentation should also elaborate on interpretation (artist statement) of your art work. Your combined video should not exceed 9 minutes.
  • Music: You must submit a single presentation video which includes your live performance recording and explanation of your work's relation to environment in additional 3 minutes. e.g. You can use Zoom and record your presentation with the presenter video. In addition to item 3, your presentation should also elaborate on interpretation (artist statement) of your music work. Your presentation video should not exceed 9 minutes.
  • Business: Your presentation video must include a full screen presentation (e.g. PowerPoint, Prezi) along with the speaker's video. e.g. You can use Zoom and record your presentation with the presenter video. Your presentation video should not exceed 12 minutes.
  • Creative Writing: Your presentation video must include a full screen view of your writing project along with the speaker's video while reading your writing piece. e.g. You can use Zoom and record your presentation with the presenter video. Your presentation video should not exceed 9 minutes.
  • In your YouTube account click on "Create" and "upload videos" button and select your video.
  • In "Details" tab, enter your video title as "Project Id - Project Title".
  • In "Visibility" tab, you must select "Unlisted" for "Save or Publish" options.
  • When you save the video, copy the provided link and submit it on this page for your project.

FINALIST LIST WILL BE ANNOUNCED ON THIS PAGE.

CATEGORY AWARDS

  • Top Grand Gold Award: To the top one project in each category: A Grant Certificate, a gold medal, and an award will be given. 
  • Gold Medal: To top 10 % of the participants: A Gold Certificate and a gold medal.
  • Silver Medal: To top 90-70% of the participants: A Silver Certificate and a silver medal.
  • Bronze Medal: To top 70-50% of the participants. A Bronze Certificate and a bronze medal.
  • Honorable Mention: To top 50-20% of the participants. A certificate will be given to all Honorable Mention winners.

Electronic gifts will be given as an award at different levels. Students have to pick up their awards during the ceremony. GENIUS Olympiad will NOT ship any awards. Each student can present only one project and may receive only one award. Awards are given only those who attend the event because the presentation is also part of the judging.

Certificates and medals will be mailed to each awardee student. Each awardee must submit their home address to receive their certificates and medals. Awards are given only those who register and submit a presentation for judging. Those who take part in the preparation of a project but could not attend the event may not get any awards or certificates. 

SPECIAL AWARDS

GENIUS Supervisor Award: The supervisor which consistently participates in GENIUS Olympiad with multiple HIGH-Quality projects over the years.

GENIUS Most Applicant School Award: The school which submits the most number of projects in this year

GENIUS Most Successful School Award:  The school which has the most number of SUCESSFULL (based on awards received) of projects in this year

GENIUS Scholarship Certificate: All eligible GENIUS participants may receive RIT University Scholarship based on the set criteria on the GENIUS Scholarship Certificate, which will be given gold, silver, and bronze winners.

RIT University Acceptance: Among those who are interviewed, RIT University will provide conditional acceptance letters. 

RIT SCHOLARSHIPS

  • Gold Medal $20,000 renewable scholarship
  • Silver Medal $18,000 renewable scholarship
  • Bronze Medal $15,000 renewable scholarship
  • Honorable Mention $14,000 renewable scholarship
  • Participant $12,000 renewable scholarship
  • Finalist $10,000 renewable scholarship

All scholarships are renewable and contingent on the participant being admitted to RIT through the admissions process. Students are eligible only for one level of the scholarship award. Please note that this program is only eligible to international students.RIT has several existing merit scholarship programs for domestic students. You can learn more at RIT financial aid.

All GENIUS Olympiad students who are interested in to apply for studying at RIT should contact Paul Keller at [email protected] with questions. RIT is honored to be partnered with Genius Olympiad and its talented students.

Thanks to all of our participants in GENIUS Olympiad.

All participants were selected and deserved recognition. We hope that all students and supervisors went back home with something learned or experienced at GENIUS Olympiad to have a life long impact. 

All grand gold, silver, and bronze winners in the science category should submit their research to International Journal of High School Research to get it peer-reviewed and published. For more information to submit: IJHighschoolResearch.org

GENIUS OLYMPIAD 2020-2021 AWARDEES WILL BE ANNOUNCED ON THIS PAGE AFTER THE AWARD CEREMONY.

We are proud to announce that we have managed to host 816 projects and 1021 students through our virtual fair. 631 projects have been awarded to medals or certificates based on our award distribution policy on "Awards" tab.

  • Grand, Gold, Silver and Bronze Medals and their certificates will be sent to the account holder's registered address in our application system under "Schools" tab. PLEASE MAKE SURE THE REGISTERED ADDRESS IS ACCURATE BY JUNE 20th. The medals and certificates will be mailed after June 21st. GENIUS Olympiad is not responsible for lost or returned items due to incorrect address information.
  • Honorable Mention and participation certificates will be available to download from our application system under "Participants" tab and will not be mailed to your address.
  • Please note that it is our policy not to send individual responses to those who are not received any awards. All judging session information is confidential and any detail information will not be provided.
  • We should note that the quality of the projects submitted has been increased significantly compared to previous years and we are very proud of all applicants for their work and effort. Projects are judged by 5-10 judges depending on the project discipline. Awardee list is created based on the average score of all judgings for each project.

All grand, gold, silver, and bronze winners in the science category should submit their research to International Journal of High School Research to get it peer-reviewed and published. For more information to submit: IJHighschoolResearch.org

GENIUS 2021 AWARDEES

GENIUS Olympiad will allow you to interact with amazing students from more than 80 countries with array of experiences and skills. 

  • Anyone with a passion for environmental issues and a BS degree in related discipline or relevant experience (STEM, Music, Film, Art, Business) may serve as a judge for the GENIUS Olympiad Projects in related categories.
  • If you would like to volunteer for GENIUS Olympiad as a judge, please register using our judge registration link .
  • Volunteering as a judge requires at least three hours of your time. Judging in 2021 will be asynchronous online using our website and can be completed anytime between May 15 nd June 1.
  • $25 Amazon Gift Card will be provided for judges for their time.
  • We have an online judging tool which can be used trough tablets and smart-phones. We expect you to bring your smart device, however, we will also lend a tablet for those who need one for judging purposes. Paper judging forms will be available for those who prefer.
  • GENIUS Science and Art projects will be judged by 6-7 individual judges.
  • GENIUS Film, Music, and Business projects are judged as a group by 6-10 judges. 

REGISTER AS A JUDGE

Judges are expected to.

  • listen to every student's presentation for five minutes
  • evaluate the presentation's organization and content
  • ask several questions according to the judging criteria
  • provide feedback about the poster design, content, scientific method, data management, and student's presentation to promote future improvement
  • rate the student on all the questions listed under the six categories using ONLINE judging form

Judging Sessions  

  • There are two judging sessions: morning session (9.30-12.00) and afternoon session (1-3.30 pm).
  • Lunch and refreshments will be provided during judging sessions. 
  • Music projects will be judged only during the afternoon session at RIT Campus. 
  • Parking is free on campus.

Why Sponsor?

  • GENIUS Olympiad actively recruits participants from 1700 selected schools and organizations in the United States and around the world.
  • GENIUS Olympiad receives applications from 1500 students who work with 300-400 teachers and parents.
  • GENIUS Olympiad website receives more than 65,000 unique users from 110+ countries and 45 states and spends 3 minutes on average.
  • GENIUS Olympiad and RIT host 1300 high achieving and motivated high school students who are destined to be influential in the future worldwide and in the nation.
  • In addition to the global reach, New York State residents are well represented, accounting for 400-500 participants. New York residents in attendance are highly educated; interested in educational activities; interested in environmental issues and/or international events.
  • GENIUS Olympiad and RIT create 3-5 press releases prior to the event, all of which include the names of main sponsors.
  • Social media is an important channel for our global reach and therefore GENIUS is extremely active on both Instagram, Facebook and Twitter. This strategy includes repeated mentions of sponsor companies and their involvement.
  • GENIUS Olympiad events and programs will be announced through NPR affiliates. 

Your donation will be TAX-DEDUCTIBLE. Please write your check payable to ‘Terra Science and Education” a 501.c.3  organization, with Genius Olympiad noted.  835 West Genesee St, Syracuse NY 13204

The GENIUS Sponsorship Levels and Benefits:

Platinum sponsorship ($20,000).

  • Address opportunity by your Company representative during opening or closing ceremony,
  • Your name and corporate logo displayed on all pages of the GENIUS Olympiad website,
  • Distribution of corporate promotional material in the "GENIUS Welcome bag"
  • Your company’s signage/banner in the Exhibit Hall during GENIUS Olympiad
  • Exhibit table space during opening reception and international fair, which are open to general public
  • Mentioning company name within press releases as the supporter of the event
  • A one-page advertisement in the Official Event Guide, distributed to participants and general public during opening reception.
  • Certificates with your company logo presented to 10 gold medal winners
  • Recognition and presentation of your company’s support at the Awards Ceremony

Gold Sponsorship ($10,000)

  • Your name and corporate logo displayed on the front page and sponsors’ page of the GENIUS Olympiad website,
  • Exhibit table space during opening reception which is open to general public
  • A half-page advertisement in the Official Event Guide, distributed to participants and general public during opening reception.
  • Certificates with your company logo presented to 10 silver medal winners
  • Recognition of your company’s support at the Awards Ceremony

Silver Sponsorship ($5,000)

  • Your name and corporate logo displayed on the sponsors’ page of the GENIUS Olympiad website
  • A one-quarter-page advertisement in the Official Event Guide, distributed to participants and general public during opening reception.
  • Certificates with your company logo presented to 10 bronze medal winners

Bronze Sponsorship ($2,500)

  • Logo print in the Official Event Guide, distributed to participants and general public during opening reception.

Special Sponsorship ($500)

GENIUS Olympiad is hosted at Rochester Institute of Technology university campus (see the picture and map below for exact location), located in Rochester, New York, USA. Participants will have safe and fun experience at RIT, which is one of the leading universities in design, engineering, arts, and more. For more information about RIT University, please scroll down.

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Airport: The nearest major transportation center is Greater Rochester Airport, which is 10 minutes away from the campus. GENIUS Olympiad will have scheduled pick-up/drop services from this airport (please check schedule or finalist guide for further information).

Participants arriving at any location other than Greater Rochester Airport must arrange their own transportation to RIT campus. Those who will attend optional GENIUS trips after the Olympiad can register to be picked at JFK airport in New York City if they are dropped at the same location after the trips (please read finalist guide/trips for further information about this option).

BY CAR, ROCHESTER IS: 90 minutes to Syracuse 80 minutes to Niagara Falls/Buffalo 3 hours to Toronto, Canada 6 hours to New York City (JFK), Boston, or Philadelphia 7 hours to Washington D.C.

For more information about RIT Campus and programs, visit: http://www.RIT.edu

At RIT, we are always on to something amazing.

Rochester Institute of Technology: Founded in 1829, Rochester Institute of Technology is a diverse and collaborative community of engaged, socially conscious, and intellectually curious minds. Through creativity and innovation, and an intentional blending of technology, the arts and design, we provide exceptional individuals with a wide range of academic opportunities, including a leading research program and an internationally recognized education for deaf and hard-of-hearing students.

Beyond its main campus in Rochester, New York, RIT has international campuses in China, Croatia, Dubai, and Kosovo. And with nearly 19,000 students and more than 135,000 graduates from all 50 states and over 100 nations, RIT is driving progress in industries and communities around the world. RIT is a top 100 national research university. RIT offers 8 doctoral (Ph.D.) programs in astrophysical sciences and technology, color science, computing and information sciences, imaging science, engineering, mathematical modeling, microsystems engineering, and sustainability; 77 master’s programs, including, Master of Architecture (M.Arch.), Master of Business Administration (MBA), Master of Engineering (ME), Master of Fine Arts (MFA), Master of Science (MS), and Master of Science for Teachers (MST); and 85 undergraduate degree programs, including Bachelor of Fine Arts (BFA) and Bachelor of Science (BS).

Academic programs include Art, Design, Architecture, Business, Communications, Digital Media, Computing and Information Sciences, Engineering, Environmental Studies, Game Design and Development, Health Professionals and Health Sciences, Photography, Film, Animation, and all STEM areas, such as Biology, Chemistry, Material Sciences, etc. In addition, RIT has more than 300 student clubs and organizations which provides a vibrant and social campus life, which is also part of the learning experience at RIT.

According to U.S. News & World Report, RIT is: Ranked 104th in the “National Universities” category Ranked 56th in the engineering programs (2022) Ranked 74th in the business programs (2022) Ranked 54th in the computer science programs, 28th in cybersecurity, and 6th in game design programs (2022) Ranked among top 15 universities recognized for excellent co-operative learning and internship programs Ranked 52th among “best value schools”

According to Princeton Review, RIT is: Ranked fourth nationally for “Top Schools for Video Game Design; Undergraduate (2022)”

According to College Factual, the college rankings data provider for USA Today College Guide 2018, RIT is: Ranked fifth in computer software and application Ranked seventh in computer and information sciences Ranked ninth in engineering-related fields Ranked 10th in management information systems Ranked 10th in design and applied arts Ranked 17th in film, video and photographic arts Ranked 42nd for criminal justice

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Calculate for all schools, your chance of acceptance.

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  • 25 Science Research Competitions for High Schoolers

What’s Covered:

  • Why Should You Enter a Science Research Competition?
  • How Do Science Research Competitions Affect My Admissions Chances?

Participating in a science research competition as a high schooler can not only allow you to explore one of your passions, but also make you a more competitive candidate during the college admissions process. There’s a wide variety of science research competitions designed for high schoolers, including the high-profile contests listed below. 

Why Should You Enter a Science Research Competition? 

Entering a science research competition demonstrates that you take initiative and that you care about academics beyond the grades in your courses, both of which are qualities that colleges appreciate in prospective students. 

Participation in competitions is already a strong extracurricular activity that’s likely to make your application more memorable, and successes—like making the finals or winning—can open additional doors, to scholarships or even research programs with professors once you get to college.

If competition isn’t really your thing, another way to showcase your initiative and skills is to work on an independent research paper. There are a number of ways to do independent research, including working with a high school teacher, reaching out to local professors, or taking part in a structured research program.  

For example, the Lumiere Research Scholar Program is one type of structured research program tailored for high school students. In the program, you work one-on-one with a researcher on an independent research project. The program is run by researchers from Harvard and helps create the structure for you to get started quickly doing your own research. Many of Lumiere’s alums have used their research in the structured program to then apply to research competitions like ISEF.  

Whether you participate in a structured program first or dive right into a competition, engaging in research allows you to deepen your understanding of one of your interests, while simultaneously boosting your profile for college admissions. 

25 Science Research Competitions for High Schoolers 

1. american academy of neurology neuroscience research prize.

Grades: 9-12

Type: National 

The American Academy of Neurology (AAN) Neuroscience Research Prize competition challenges students to investigate problems regarding the brain or nervous system. The competition is only open to individual students—group projects are ineligible. Teachers are encouraged to provide guidance and support; however, they should allow students to demonstrate their own creativity. 

Winners receive a monetary prize and the chance to present their projects at the AAN Annual Meeting.

2. NCF-Envirothon

Type: State, National, and International

Envirothon is North America’s largest environmental education competition, with more than 25,000 students participating in the multi-level competition each year. Student teams are first challenged at state-level competitions, with the winners moving on to face top teams from across the globe at the annual international competition. 

The international competition is a six-day event held in a different location each summer—for example, on an open range of the American West one year, and at a coastal community in eastern Canada the next. Participants have the chance to win thousands of dollars in scholarships.

3. Regeneron International Science and Engineering Fair (ISEF)

Type: Local, Regional, and International

The Regeneron ISEF is the world’s largest international pre-college STEM competition—high school students representing all 50 states and more than 70 countries, regions, and territories, take part. Students showcase independent research and compete across 22 categories for awards ranging from $500 to $75,000.

This is not a group-based competition—individual students enroll in local school science fairs before advancing to upper-level competitions in hopes of reaching the national stage. 

4. National Science Bowl

Type: National

Hosted by the Department of Energy in Washington, D.C., the National Science Bowl is a highly publicized competition that tests students’ knowledge in all areas of science and mathematics, including biology, chemistry, earth science, physics, energy, and math. Students compete in teams of four (plus an alternate) and have a teacher who serves as an advisor. 

The National Science Bowl is one of the largest science competitions in the country—roughly 344,000 students have participated in it throughout its 34-year history.

5. National Science Olympiad

Type: State and National 

One of the nation’s premier STEM competitions, the National Science Olympiad is the pinnacle of achievement for the country’s top Science Olympiad teams. Teams compete annually for the opportunity to win prizes and scholarships, including a one-time $10,000 Science Olympiad Founders’ Scholarship. About 6,000 teams compete each year, beginning at the regional level in hopes of reaching the national competition.

6. Regeneron Science Talent Search (STS)

Established in 1942 and hosted by the Society for Science, the Regeneron Science Talent Search is considered the nation’s most prestigious high school science research competition. The competition tasks young scientists with presenting their original research before a panel of nationally recognized professional scientists.

Of the roughly 1,800 entrants, 300 Regeneron STS scholars are selected—they and their schools are awarded $2,000 each. From that pool of scholars, 40 finalists are then identified to receive an all-expenses-paid trip to Washington, D.C., where they compete for an additional $1.8 million in awards, with a top prize of $250,000.

7. Stockholm Junior Water Prize

Type: Regional, State, National, and International 

In this competition, students from around the world seek to address the current and future water challenges facing the world. Competition for the Stockholm Junior Water Prize occurs on four levels: regional, state, national, and international. 

  • Regional winners receive a certificate and a nomination to compete in the state competition.
  • State winners receive a medal and an all-expenses-paid trip to compete in the national competition.
  • National winners receive a trophy, a $10,000 scholarship, and an all-expenses-paid trip to the international competition in Stockholm, Sweden.
  • International winners receive a crystal trophy and a $15,000 scholarship, along with a $5,000 award for their school.

In order to participate, students begin to research and develop a practical project proposal either individually or with a group.  

8. TOPSS Competition for High School Psychology Students

To participate in this competition, students must submit a video (up to 3 minutes long) that demonstrates an interest in and understanding of a topic in psychology that they think could benefit their local community and improve lives. Students must utilize at least one peer-reviewed research study on their topic, and must include a closing slide citing their source(s). Up to three winners are chosen to receive a $300 scholarship.

9. Junior Science and Humanities Symposium (JSHS) National Competition

Type: Regional and National

The Junior Science and Humanities Symposium National Competition is one of the country’s longest-running STEM competitions—participants submit and present scientific research papers, and compete for military-sponsored undergraduate scholarships. 

The JSHS national competition is designed to emulate a professional symposium. Research projects are organized into categories such as Environmental Science, Engineering and Technology, and Medicine and Health. After competing regionally, about 250 students are chosen to attend an annual symposium to showcase their work.

10. MIT THINK Scholars Program

In the fall of each year, students who have thoroughly explored the background of a potential research project and are looking to get it off the ground can present their proposals to a group of undergraduate students at MIT . If selected, students will be able to carry out their project, while receiving up to $1,000 in funding. They’ll also be invited to a four-day, all-expenses paid trip to MIT’s campus. 

Finalists participate in weekly mentorship meetings and will have the opportunity to present their findings to MIT students and faculty at the end of the program.

11. Conrad Challenge

Teams of two to five students are tasked with designing and detailing project proposals to tackle various problems in categories such as Aerospace & Aviation, Health & Nutrition, Cyber-Technology & Security, and Energy & Environment. In doing so, they will identify problems in the world and come up with feasible and innovative solutions, while working with judges and mentors along the way. 

Finalists will be selected from the competing teams and invited to the Innovation Summit in Houston, where they will pitch their projects to judges and potentially receive numerous prizes and awards, ranging from scholarships to professional networking opportunities.

12. USA Biolympiad Competition

Type: National and International

Students will undergo multiple rounds of testing that will eventually pinpoint 20 finalists—out of nearly 10,000 students annually—for selection into a residential training program to represent the USA in the International Biology Olympiad. This is one of the most prestigious and difficult competitions for high school scientists–it is the ultimate test for students devoted to the future of biology.

13. Davidson Fellows Scholarship

While not exclusive to STEM, the Davidson Fellows program offers various major scholarships for students interested in careers in sciences—scholarship categories include Science, Technology, and Mathematics. The program requires students to submit significant work that is recognized as meaningful and has the potential to make a positive contribution to society. 

Scholarships range from $10,000 to $50,000.

14. Destination Imagination

Type: Regional, State, National, International 

Destination Imagination is another worldwide competition that covers a variety of subjects, but it specializes in science-based challenges. Students will form teams and choose from a list of different challenges to compete in, in categories such as Technical, Scientific, and Engineering.

Students will solve these challenges and present their solutions in regional competitions. Regional winners will move on to statewide competitions before being invited to the Global Finals, where students from 36 states, 7 Canadian provinces, and 24 countries compete for awards.

15. Breakthrough Junior Challenge

For students looking for a more creative, unconventional competition, the Breakthrough Junior Challenge tasks students with creating a short two-minute video in which they explain a complex scientific concept and demonstrate how it works in practice.

Winning applicants will need to demonstrate immense creativity and deep understanding of complex scientific concepts. Rest assured, the prize is worth the difficulty, with awards including a $250,000 college scholarship, a $100,000 grant to the winner’s school for the development of a science lab, and a $50,000 award to a teacher of the winner’s choosing.

16. Biotechnology Institute BioGENEius Challenge

Type: State and National

Students from across the country are invited to participate in the Biotechnology Institute’s BioGENEius Challenge, where they’re able to complete a project in the category of Healthcare, Sustainability, or Environment. Their project must be extensive, and produce concrete results, and they will then compete in either a local or a virtual “At-Large” competition, with other student competitors from around the world.

17. Genes in Space

Grades: 7-12

For students interested in the science of space and its overlap with our current understanding of the human genome, this competition combines the two worlds by tasking students with designing a DNA experiment that addresses challenges in space exploration and travel.

Finalists receive mentorship from Harvard and MIT scientists and present their proposals to win the grand prize. The Genes in Space winner will travel to the Kennedy Space Center to see their experiment launched into space, and actually conducted on the International Space Station.

18. Odyssey of the Mind

Type: Regional, State, and International

Students form teams to compete in a variety of STEM-based challenges during this global problem-solving competition, which culminates in the World Finals. Challenges change annually and can range from designing vehicles to building small structures that can support hundreds of pounds. These challenges are designed to encourage creativity in the performative and presentational elements of competition.

19. U.S. National Chemistry Olympiad

Type: Regional, National, International

Students interested in chemistry can participate in the USNCO, in which they’ll take rigorous exams to prove their skills in the field. Top test-takers will be selected to attend a prestigious Study Camp, where they’ll compete for the chance to represent the U.S. at the International Chemistry Olympiad. Interested students can contact their local coordinator, who can be found through the program’s website.

20. ArcGIS Online Competition

Type: Regional, State, and National

This competition tasks high schoolers with conducting a research project connected to their home state, and eventually presenting their data in an ArcGIS StoryMap. This is a multi-level competition–participants compete at the school, state, and national level as they pursue top honors.

21. AAPT High School Physics Photo Contest

Type: International

This unique international competition is presented by the American Association of Physics Teachers (AAPT) and challenges students to create visual illustrations of natural and contrived phenomena, along with a written analysis of what the images are demonstrating. More than 1,000 students take part in this competition annually.

22. DNA Day Essay Contest

This annual competition asks high schoolers from around the globe to examine, question, and reflect on important topics in genetics. The essay can be no longer than 750 words and the prompt changes yearly. First place takes home $1,000, second place $600, and third place $400.

23. The Biomimicry Institute: Youth Design Challenge

Through this science competition, students are introduced to biomimicry—an interdisciplinary approach to science and environmental literacy. Students work as teams with an adult coach to search for bio-inspired ideas to solve real-world problems in support of a healthier planet.

24. TEAMS (Tests of Engineering Aptitude, Mathematics, and Science)

During this aptly named competition, students must work in teams to apply their knowledge of math and science to real-world engineering challenges. The three-part, themed competition includes design/build, multiple choice, and essay components, and the theme changes annually. 

Beyond the chance to win an award, participants build valuable, broadly applicable skills like teamwork, collaboration, communication, and critical thinking.

25. Eye on the Future Teen Video Contest

While not a research competition per se, aspiring scientists will want to look into this science-related competition. Participants are tasked with creating a video between 30 seconds and three minutes long, either on their own or in teams of up to three members. Students compete in three categories: science in your world, science in the field or lab, and science in the future. 

Winners receive a $2,000 cash prize and a paid trip for them and a parent or guardian to visit the National Institute of Health in Bethesda, Maryland. 

How Do Science Research Competitions Affect My Admissions Chances? 

The influence your participation in science research competitions can have on your college admissions varies—considerations such as how well you performed and the prestige of the event factor into how admissions officers view the competition. That being said, the four tiers of extracurricular activities provide a good general guide for understanding how colleges view your activities outside the classroom.

The most esteemed and well-known science research competitions are organized into Tiers 1 and 2. Extracurricular activities in these categories are extremely rare, demonstrate exceptional achievement, and hold considerable sway with admissions officers. Tiers 3 and 4 are reserved for more modest accomplishments—like winning a regional (rather than a national) competition—and carry less weight at colleges than their higher-tiered counterparts. 

Generally, participation in a science research competition will be considered at least a Tier 2 activity. As stated before, this varies depending on the competition and your performance. For example, being a finalist or winner in something like the Regeneron Science Talent Search or the International Biology Olympiad—prestigious national and international competitions—is very likely to be considered a Tier 1 achievement. 

However, lower-tiered extracurriculars are still valuable, as they show colleges a more well-rounded picture of you as a student, and highlight your desire to pursue your interests outside of school. 

Curious how your participation in science research competitions affects your odds of college admissions? Collegevine can help. Our free chancing calculator uses factors like grades, test scores, and extracurricular activities—like science research competitions— to calculate your chances of getting into hundreds of colleges across the country! You can even use the information provided to identify where you can improve your college profile and ultimately bolster your odds of getting into your dream school. 

Disclaimer: This post includes content sponsored by Lumiere Education.

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Dr. Jane Goodall, DBE, speaks at the ClimateScience Olympiad 2021 Awards Ceremony at UN Climate Summit, Glasgow.

100,000 students, 190 countries self.__wrap_n=self.__wrap_n||(self.CSS&&CSS.supports("text-wrap","balance")?1:2);self.__wrap_b=(e,n,t)=>{t=t||document.querySelector(`[data-br="${e}"]`);let r=t.parentElement,o=f=>t.style.maxWidth=f+"px";t.style.maxWidth="";let c=r.clientWidth,a=r.clientHeight,s=c/2-.25,i=c+.5,p;if(c){for(o(s),s=Math.max(t.scrollWidth,s);s+1 {self.__wrap_b(0,+t.dataset.brr,t)})).observe(r):process.env.NODE_ENV==="development"&&console.warn("The browser you are using does not support the ResizeObserver API. Please consider add polyfill for this API to avoid potential layout shifts or upgrade your browser. Read more: https://github.com/shuding/react-wrap-balancer#browser-support-information"))};self.__wrap_n!=1&&self.__wrap_b("undefined",1)

Dr. Jane Goodall, DBE, speaks at the ClimateScience Olympiad 2021 Awards Ceremony at UN Climate Summit, Glasgow.

Jane Goodall

“Empowering young people is what I’ve been all about for so long, beginning our roots and shoots program, back in 1991, with 12 high school students. […] Young people, such as those who are here today, such as all of you who took part in this competition.”

Dr. Jane Goodall, DBE, ClimateScience Olympiad Finals Ceremony, COP26 Glasgow.

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10 Environmental Science Competitions for High School Students

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By Eric Eng

A forestry student working outside

Environmental science competitions for high school students serve as a platform to showcase skills in tackling global ecological challenges. Among high school students top environmental science competitions, two standout events are the Action for Nature International Young Eco-Hero Awards and the 4-H Wildlife Habitat Evaluation Program.

1. Action for Nature International Young Eco-Hero Awards

  • Location: This is a global competition open to young environmentalists from all around the world.
  • Registration Fee: none
  • Important date: February 28, 2024.
  • Eligibility: Open to youth aged 8 to 16, the competition seeks participants who have initiated and executed a project concerning environmental health, advocacy, research, or protection of the natural world.

The Action for Nature International Young Eco-Hero Awards recognize and reward the innovative environmental projects of young individuals. Winners receive cash prizes, certificates, and public recognition, encouraging them to continue their efforts in environmental conservation.

Asian woman travel and camping alone at natural park

In the Action for Nature International Young Eco-Hero Awards, considerable emphasis is placed on the duration and sustainability of participants’ environmental projects, with a preference for those that span over two years or are ongoing. The judging panel evaluates each project based on a comprehensive set of criteria. These include the originality of the idea, the challenges faced during its implementation, and the project’s organizational structure.

Additionally, the time committed to the project, its capacity to influence and educate others, the effective utilization of external resources, the level of achievement in meeting set objectives, and, importantly, the project’s overall environmental impact are key factors in the decision-making process. This holistic approach in assessing each project ensures a fair and comprehensive evaluation of the young participants’ contributions to environmental conservation.

2. 4-H Wildlife Habitat Evaluation Program

  • Location: This program is held in various states across the United States, including competitions at Iowa State University and Garvan Woodland Gardens in Hot Springs, Arkansas.
  • Registration Fee: The registration fee can vary by state
  • Important dates: Important dates vary by state (For example, in Iowa, the state competition is scheduled for May 18, 2024, with registration opening on April 10, 2024. The Wildlife Habitat Education Program ( WHEP ) State Contest is set for April 27, 2024 in Arkansas. Other states may have different dates for their respective competitions.)
  • Eligibility: The program is open to youth in grades 3 to one-year post-high school, categorized into Junior, Intermediate, and Senior divisions based on age.

The 4-H Wildlife Habitat Evaluation Program provides a hands-on environmental education experience focused on wildlife and fisheries habitat management. It involves learning about wildlife habitats, judging their quality, and understanding management practices, culminating in an annual competition where teams present their wildlife knowledge.

Pretty young girls having outdoor science lesson exploring nature

In the diverse landscape of the 4-H Wildlife Habitat Evaluation Program, each state competition is tailored with specific themes or focal areas, reflecting the unique ecological characteristics of the region. For example, the 2024 Arkansas state contest zeroes in on Urban Wildlife Identification, spotlighting species endemic to the Eastern Deciduous Forest and Wetland ecoregions. This thematic approach enriches the learning experience, offering participants a nuanced understanding of local biodiversity.

Many resources are available to aid their preparation, including detailed manuals and practice materials. These resources equip participants with the necessary knowledge and skills, ensuring they are well-prepared for the intricate nuances of their state’s specific environmental context.

3. Envirothon

  • Location: The Envirothon hosts competitions across the United States, Canada, China, and Singapore, culminating in an annual international event.
  • Important dates: July 28 to August 3.
  • Registration Fee: The registration fee details vary by state and region. Teams should consult their local Envirothon coordinators for specific fee information.
  • Eligibility: High school students in grades 9-12 or 14-19 can participate. Each team has five students and must have a designated coach or teacher.

The Envirothon competition challenges students in aquatic ecology, forestry, soils and land use, wildlife, and current environmental issues. Incorporating STEM principles, it offers a dynamic platform for students to develop critical thinking skills and devise inventive solutions to complex environmental and natural resource issues. Participants are encouraged to work collaboratively, promoting team-building and leadership skills.

Side view at multi-ethnic group of students using laptop while studying in college

Envirothon also serves as an educational journey, equipping students with environmental knowledge and conservation of natural resources through academic study and outdoor experiences. It aims to inspire action in local communities and instill a lifelong commitment to environmental stewardship and sustainability. The competition’s structure involves hands-on learning and outdoor field experiences, making it a comprehensive educational endeavor for young environmental enthusiasts.

4. National Ocean Sciences Bowl

  • Location: Held in various regions across the United States.
  • Registration Fee: Information specific to the registration fee is not universally specified and may vary by region.
  • Important Dates: Regional competitions have varying dates; the national finals’ specific dates are typically announced post-regional rounds.
  • Eligibility: High school students are eligible to participate in the NOSB.

The National Ocean Sciences Bowl is an academic competition that immerses high school students in the expansive world of oceanography. It offers an in-depth exploration of the oceanic environment, covering many topics including biology, chemistry, physics, and geology . The competition consists of quiz-bowl-style rounds, testing students’ knowledge and understanding of ocean sciences.

aerial view of a coast

Not only does the NOSB provide a rigorous academic challenge, but it also cultivates an appreciation for marine science and promotes environmental stewardship. By participating in this competition, students gain valuable experience in scientific research and inquiry, setting a strong foundation for future careers in environmental science and related fields.

5. Shell Eco-marathon

  • Location: Hosts regional events across the Americas, Europe and Africa, Asia-Pacific, and the Middle East.
  • Registration Fee: Specific details about the registration fee for the 2024 competition are unspecified.
  • Important Dates: Vary by region and specific competition.
  • Eligibility: Students who design, build, and test ultra-energy-efficient vehicles can participate.

The Shell Eco-marathon is a unique competition that challenges student teams to design, build, and test energy-efficient vehicles. It emphasizes innovation and sustainability in automotive engineering, pushing the boundaries of fuel efficiency. The competition includes two vehicle classes – Prototype and UrbanConcept, and three energy categories – battery-electric, hydrogen fuel cell, and internal combustion engine.

construction managers working together

This competition is an extraordinary educational experience, allowing students to apply their engineering and scientific knowledge in a practical, environmentally-focused context. It encourages creative problem-solving, teamwork, and a deeper understanding of energy efficiency and sustainable transportation technologies. Students contribute to the global conversation on energy sustainability and environmental responsibility through the Shell Eco-marathon.

6. River of Words Art and Poetry Contest

  • Location: International
  • Registration Fee: Not specified
  • Important Dates: Submission deadline – February 29, 2024
  • Eligibility: Students from kindergarten to 12th grade, ages 5 to 19, enrolled in school​.

Open internationally, the River of Words Art and Poetry Contest fosters a global platform for youth to showcase their talents and environmental insights. The contest’s inclusivity and global reach allow students from diverse backgrounds to share their unique interpretations and relationships with nature.

The Adroit Prizes for Poetry and Prose

With a submission deadline typically set in early spring, the contest aligns with the academic calendar, allowing educators to integrate it into their environmental science or art curriculums. This approach enhances students’ understanding of environmental issues and cultivates their artistic skills, making it a multifaceted educational experience.

The impact of the River of Words Contest extends beyond the realm of traditional environmental science competitions. Bridging the gap between science and the arts empowers young individuals to explore and creatively communicate environmental themes.

7. Earthwatch Student Challenge Awards

  • Location: Varies by expedition
  • Registration Fee: Scholarships available
  • Important Dates: Not specified for 2024
  • Eligibility: Secondary school students; specific requirements vary by expedition​​.

The Earthwatch Student Challenge Awards hold a prestigious position among the top environmental science competitions for high school students. This program stands out for its unique approach to environmental education, combining hands-on scientific research with real-world conservation efforts.

A student holding a model of the earth

Offered to secondary school students, these awards provide an opportunity to engage in environmental science and conservation research expeditions, working alongside professional scientists. This immersive experience allows students to contribute directly to important environmental research, enhancing their understanding of ecological issues while practically applying their classroom learning.

8. The Gloria Barron Prize for Young Heroes

  • Location: U.S.A. or Canada
  • Important Dates: Application deadline – April 15, 2024
  • Eligibility: Ages 8-18, permanent residents of the U.S.A. or Canada, currently working on an inspiring service project, or have done so within the past 12 months​.

The Gloria Barron Prize for Young Heroes is a distinctive and prestigious honor within the scope of top environmental science competitions for high school students. Established to celebrate young, public-spirited individuals across North America, this prize recognizes and supports young leaders who have significantly impacted people, their communities, and the environment.

Students cleaning up the beach, volunteers collecting the waste on the coast line

The prize stands out for its focus on young individuals actively working on inspiring service projects, demonstrating commitment and leadership in addressing societal and environmental issues. Each year, the Barron Prize honors 25 outstanding young leaders between the ages of 8 and 18, offering them a substantial award to support and extend their service projects and educational goals.

9. President’s Environmental Youth Awards

  • Location: United States
  • Important Dates: Application deadline – January 15, 2024
  • Eligibility: Students in grades K-12 in the United States​​​​

The President’s Environmental Youth Awards (PEYA) are a significant highlight among top environmental science competitions for high school students. This prestigious program, organized by the U.S. Environmental Protection Agency (EPA), recognizes outstanding environmental stewardship projects by K-12 students across the United States.

Some students are doing some community service.

The awards showcase and honor the innovative efforts of young environmentalists in promoting environmental awareness and community involvement. Each year, the PEYA celebrates students who have demonstrated creativity and initiative in projects addressing various environmental topics, including climate change, recycling, and sustainability.

10. Stockholm Junior Water Prize

  • Location: U.S. National Competition in Golden, Colorado; International Competition in Stockholm, Sweden
  • State Competition entry deadline – April 15, 2024
  • National Competition – June 22-24, 2024
  • International Competition – August 23-27, 2024
  • Eligibility: High school students in grades 9-12, aged 15 by August 1 of the competition year, who have conducted a water-related science project​​​.

The Stockholm Junior Water Prize (SJWP) is prominent among high school students’ top environmental science competitions, emphasizing the critical issue of water science. This globally recognized award, founded in 1997, celebrates high school students who engage in innovative water-related research projects.

Biologists testing water of natural river

Open to students in grades 9-12 who have reached the age of 15 by August 1 of the competition year, SJWP encourages in-depth exploration of water quality, water resources management, and water and wastewater treatment.

The competition comprises several levels, starting from regional, moving to state, then national, and finally, the international stage. Each level of the competition acknowledges the students’ contributions to water research, with the national winner receiving a $10,000 scholarship, a trophy, and an all-expenses-paid trip to participate in the International Competition during World Water Week in Stockholm, Sweden.

Top environmental science competitions for high school students are more than just contests; they are incubators for the next generation of environmental innovation and conservation leaders. These platforms showcase youthful brilliance and cultivate a profound comprehension of ecological complexities. They are nurturing grounds where theoretical knowledge meets practical application, encouraging the integration of cutting-edge technology in environmental solutions.

As these competitions evolve, they promise to shape a cadre of informed, skilled, and passionate environmental scientists and advocates. These young minds are being prepared to confront and solve the most pressing environmental issues of our era.

The drive, imagination, and commitment exhibited in these competitions ignite hope and pave the way for a future where sustainability and environmental consciousness are at the forefront. Through these competitions, we are witnessing the emergence of environmental stewards who will drive the change towards a more sustainable, ecologically balanced world.

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15 Research Competitions for High School Students

Students benefit from participating in research competitions in a variety of ways, including learning how to present their findings and gaining experience in an important field of their interest. Competitions are not only a strong extracurricular activity, but reaching the finals can also help students earn college scholarships. Being a significant achievement, it may even open opportunities, such as laying the groundwork for a career in research and helping one land an internship.

It also aids them in becoming competitive candidates for college admissions by demonstrating students' intellectual prowess and capacity to work on a rigorous project, either individually or as part of a team. Even if they don't win or place in the competition, students can use their participation to demonstrate what they have learned about their chosen academic field and how they have explored their passion for the discipline.

In this post, we have compiled a list of 15 well-respected research competitions that are sure to boost your high school profile.

Here are 15 Research Competitions for High School Students:

1. Regeneron Science Talent Search

This talent hunt, which began in 1942 as a program of the Society for Science & the Public (the Society), is widely regarded as the nation's most renowned high school science research competition. Young scientists present their original findings to a panel of nationally recognized professional scientists as part of the competition. 300 Regeneron STS scholars are chosen from 1,800 applicants, and they and their schools are each granted $2,000. From the group of scholars, forty finalists are chosen, who get an all-expenses-paid trip to Washington, D.C., and compete for another $1.8 million in prizes, including a top prize of $250,000.

2. MIT THINK Scholars Program

Most research competitions require participants to have already completed the project, but the THINK program is different in that students only need to have completed background research for a project in the science, technology, or engineering fields before applying. Those whose projects are selected receive $1,000 funding and mentorship from MIT students. They also get a paid trip to MIT's campus to meet professors in their field of research, tour labs, and attend MIT's xFair. Students in grades 9th to 12th are eligible.

3. Google Science Fair

Students aged 13 to 18 submit science research ideas to be judged by a panel of scientists and experts in this competition. At various levels, victors are rewarded generous scholarships, cool gear, and unique opportunities such as internships. Past projects include battery-free lighting and wearable sensors to improve the safety of Alzheimer's patients.

environment research paper competition

4. AAN Neuroscience Research Prize

The nervous system/brain is the center of this competition, with students investigating and solving problems linked to it. Students do their own neuroscience research, which is evaluated based on its relevance to neuroscience, originality, data interpretation, and research reports. The competition is open to students in grades 9 through 12, and only individual entries are accepted.

5. Odyssey of the Mind

This challenge encourages high school students to think outside the box by identifying problems and developing innovative solutions. After a school or community group purchases membership, they qualify for the competition, which takes place at the regional, state, and national levels. The competition is open to students from grades 9th to 12th. 6. International BioGENEius Challenge

Recognizing outstanding research in biotechnology, this challenge gives students the opportunity to win cash awards for their work. Finalists present their research before a panel of expert biotech judges. Students receive the unique opportunity of being able to meet top industry professionals and gain valuable advice and insight on their projects.

7. Davidson Fellows

Students 18 and under who have completed a project in one of several subjects, including STEM, are eligible for the Davidson Fellows Scholarship, which awards $50,000, $25,000, and $10,000 scholarships. It's a prestigious and competitive scholarship to obtain, and the projects the recipients generate are frequently on par with those produced by college graduates. Research projects should "contribute a work that is acknowledged as an extraordinary accomplishment by experts in the field and has the potential to benefit society."

8. ExploraVision

The Toshiba/NSTA ExploraVision initiative is a competition for students to improve their STEM skills. Participants research a current technology and then envision what it will look like in 20 years, including development processes, benefits and drawbacks, and challenges. Students work in groups of 2-4 with the help of a teacher who serves as a mentor.

9. Regeneron International Science and Engineering Fair (Regeneron ISEF)

As the premier science fair in the United States, Regeneron ISEF is one of the best-known high school science competitions. Even ranking within the top 100 is enough to help one's university application stand out.

Unlike Regeneron STS, students can't apply directly to the ISEF. Instead, they have to first participate in a regional science fair. Doing well there helps the student qualify for the next ISEF rounds. Key factors for winning include innovation and originality. To show originality for the ISEF, students need to tackle a problem that's interesting to the scientific community. It is important to have a good overview of academic science literature in the field that one's project is in, and it helps to have a professional academic scientist or engineer as a mentor.

environment research paper competition

10. Stemanities Research Competition

A national competition, this event invites students in their freshman, sophomore, junior, or senior year to conduct research in STEM and the humanities to develop a more sophisticated understanding of a topic. Stemanities is sponsored by the Institute for Biomedical Sciences, and finalists are invited to La Jolla, California to present their work and compete for monetary awards.

11. Destination ImagiNation

For students who have a penchant for problem solving, Destination ImagiNation helps one refine their critical thinking skills. An international competition for students in kindergarten through college, Destination ImagiNation teaches life skills while encouraging imagination, through problem solving, creativity, and research. In this competition, students work in groups of five to seven to develop solutions to Team Challenges.

12. Stockholm Junior Water Prize

Students compete in this competition to provide solutions to the world's present and future water problems. State winners receive a medal and an all-expenses-paid travel to the national competition at The Ohio State University. Previous winning themes at the state level include "Protecting the Aquatic Environment from Household Microfibers" and "Optimizing Straw Mulch Use in Agriculture." A $10,000 scholarship and a free ticket to the international competition in Stockholm, Sweden are awarded to the national winner. The international winner receives a prize of $15,000 for themselves and $5,000 for their school.

13. TOPPS Competition for High School Psychology Students

Students write a 3,000-word essay on a specific topic, using peer-reviewed psychological research. "Non-human animals in psychology" was the research theme for 2019. Four winners are selected for a prize of $250. Students from grades 9th to 12th are eligible to compete.

14. Clean Tech Competition

Students must identify a problem with our natural world and resource consumption that they wish to address, develop a sustainable solution, and submit a research paper to the judges as part of the Clean Tech Competition research and design challenge. There are no topic restrictions; entrants must just have one goal: to develop a long-term solution to an environmental problem.

Each team should consist of one to three students who must be between the ages of 15 and 18 at the time of submission. Following the submission of papers, the top 10 teams from the worldwide pool will be chosen to compete in the virtual global finals. They'll submit their research and prototypes to the judges and win cash awards, with the winning team receiving continued mentorship from an expert in their field.

15. Junior Science and Humanities Symposium

This scholarship competition encourages students to pursue research in the fields of science, engineering, technology, or mathematics. Students can submit their original research findings in front of a judging panel and their peers at the symposia. Furthermore, attending regional or national symposia provides students with a variety of opportunities, such as seminars, panel discussions, career exploration, research lab visits, and networking events.

How to select which research competition to participate in:

While the above list includes a number of prestigious competitions, it is definitely not exhaustive in nature. If you don't find one that fits what you're looking for, it is encouraged to find one that does, with careful research! Be sure to use your judgment when considering unknown competitions, and only select those that have ample information about them transparently available. Be sure to also look out for competitions that charge unnecessarily high fees to participate.

Typically, older and national competitions are better known and have a larger chance of standing out on college applications. It is also important to remember that a cash prize may not be the only criteria to decide on what competition is worth participating in. Several competitions also give out other benefits to winners, such as mentorships and invitations to conferences, each of which are equally important as a stepping stone in a student's research career aspirations.

Additionally, you can also work on independent research in AI to present at these competitions, through Veritas AI's Fellowship Program!

Veritas AI focuses on providing high school students who are passionate about the field of AI a suitable environment to explore their interests. The programs include collaborative learning, project development, and 1-on-1 mentorship.  

These programs are designed and run by Harvard graduate students and alumni and you can expect a great, fulfilling educational experience. Students are expected to have a basic understanding of Python or are recommended to complete the AI scholars program before pursuing the fellowship. 

The   AI Fellowship  program will have students pursue their own independent AI research project. Students work on their own individual research projects over a period of 12-15 weeks and can opt to combine AI with any other field of interest. In the past, students have worked on research papers in the field of AI & medicine, AI & finance, AI & environmental science, AI & education, and more! You can find examples of previous projects   here . 

Location : Virtual

$1,790 for the 10-week AI Scholars program

$4,900 for the 12-15 week AI Fellowship 

$4,700 for both

Need-based financial aid is available. You can apply   here . 

Application deadline : On a rolling basis. Applications for fall cohort have closed September 3, 2023. 

Program dates : Various according to the cohort

Program selectivity : Moderately selective

Eligibility : Ambitious high school students located anywhere in the world. AI Fellowship applicants should either have completed the AI Scholars program or exhibit past experience with AI concepts or Python.

Application Requirements: Online application form, answers to a few questions pertaining to the students background & coding experience, math courses, and areas of interest. 

One other option – Lumiere Research Scholar Program

If you are interested in a selective, structured research program, consider applying to the Lumiere Research Scholar Program , a selective online high school program for students founded by Harvard and Oxford researchers. The program pairs you with a full-time researcher to develop your own independent research project, in any discipline of your choice. Last year over 1500 students applied to 500 slots in the research program! You can find the  application form   here .

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The 11 Best High School Science Competitions

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Love science and want to show off your skills? High school science competitions are a great way to do that! But which competitions will impress colleges the most? We've gathered information on 11 of the best science competitions for high school students. Look over the descriptions that seem most interesting to you, then keep reading to learn everything you need to do to make them stand out on your college applications.

11 Best Science Competitions for High School Students

Below are overviews of 11 of the best science competitions for high school students. For each one, we state which grades are eligible, whether it's an individual or group competition, and whether it's a research-based project or an exam-based competition. We then give a brief overview of what you can expect as a participant in the competition.

AAN Neuroscience Research Prize

  • Grades Eligible: 9-12
  • Individual or Group: Individual
  • Research or Exam: Research

Students in this competition focus on researching and solving problems related to the nervous system/brain. If you decide to compete for this prize, you'll submit your own research on neuroscience, which will be judged on relevance to neuroscience, creativity, interpretation of data, and research reports.

Biology Olympiad

  • Research or Exam: Exam

The USA Biology Olympiad (USABO) is one of the more memorization-heavy olympiads, and much of it, especially in early rounds, involves recalling the text of Campbell Biology in a timed fashion. As you progress further, there will be lab components and short-answer questions. For the hands-on portion, you need to be skilled at following memorized procedures. Nearly 10,000 high school students participate in the Biology Olympiad each year. Students take timed exams and those with the highest scores proceed to the next round. As long as your school is registered, you can sign up for the USABO open exam. If you score within the top 10%, you'll move on to the semifinals, and potentially the national and international competition.

Chemistry Olympiad

The U.S. National Chemistry Olympiad (USNCO) is similar to the Biology Olympiad in that they're both exams widely open to high school students, and, if you score high enough, you'll keep advancing to more challenging rounds. However, the Chemistry Olympiad does include more of a lab component than the Biology Olympiad. Any high school student can compete in a local Chemistry Olympiad competition, and students are then nominated for subsequent competitions based on their scores. Local competition exams are all multiple choice, while subsequent competitions include short/long answer questions and labs.

Conrad Challenge

  • Grades Eligible: Ages 13-18
  • Individual or Group: Group

The Conrad Challenge is a competition that challenges teenagers to think outside the box and create solutions to address local or global problems. Students work on teams of 2-5 (along with an adult coach) to create a product or service in one of the following categories: Aerospace & Aviation, Cyber-Technology & Security, Energy & Environment, Health & Nutrition, Transforming Education Through Technology, Smoke-Free World: Eliminating & Reducing Teen Vaping, and Smoke-Free World: Repurposed Farmlands & Tobacco Crops.

Like other high school science research competitions, there are multiple rounds competitors can advance to, and those that reach the Innovation Summit level are invited to present their project to a panel of expert judges at the Kennedy Space Center.

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Davidson Fellows

  • Grades Eligible: Anyone 18 or younger is eligible

The Davidson Fellows Scholarship awards $50,000, $25,000 and $10,000 scholarships to students 18 or younger who have completed a project in one of several fields, including STEM. It's both a prestigious and competitive scholarship to win, and the projects the winners produce are often at the level of college-graduate research projects. Research projects should "contribute a work that is recognized as an outstanding accomplishment by experts in the field and has the potential to benefit society."

Envirothon is a competition designed to promote environmental education in schools. Competitions are held during the school year, with the national competition held each summer. Students compete in teams of five to answer questions, do lab work, and give an oral presentation. There are five testing categories: aquatic ecology, forestry, soils/land use, wildlife, and a current environmental issue that changes yearly.

ExploraVision

  • Grades Eligible: K-12

The Toshiba/NSTA ExploraVision program is a competition designed to build STEM skills in students. Participants research a current technology of their choice then envision what that technology will look like in 20 years, including development steps, pros and cons, and challenges. Students work in groups of 2-4, along with a teacher as a mentor.

MIT THINK Scholars Program

  • Individual or Group: Mostly individual, although groups of two are allowed

Most research competitions require participants to have already completed the project, but the THINK program is different in that students only need to have completed background research for a project in the science, technology, or engineering fields before applying. Those whose projects are selected receive $1,000 funding and mentorship from MIT students. They also get a paid trip to MIT's campus to meet professors in their field of research, tour labs, attend MIT's xFair.

National Science Bowl

  • Grades Eligible: 6-12

The National Science Bowl is one of the oldest and best-known science competitions, having been around since 1991. Students compete in groups of four (along with a coach and an alternate member) to verbally answer questions in all areas of math and science. Thousands of students compete each year, and you need to be able to answer questions quickly to do well. There are local, regional, and national competitions, and questions are designed to be at a college freshman level of knowledge.

Regeneron International Science and Engineering Fair (Regeneron ISEF)

  • Individual or Group: Either (groups can have up to three members)

Regeneron ISEF (formerly Intel ISEF) is one of the most prestigious science fairs for high school students. In fact, it's the premier science fair in the United States and one of the best-known high school science competitions. If you rank within the top 100, that's enough to help your application stand out even for Ivy League schools, and if you win the entire competition, you get a $75,000 prize!

You can't apply directly to the ISEF. Instead, you have to start out first in a regional science fair . If you do well in that, you can advance to the next ISEF rounds. Key factors for winning include being innovative and original. To show originality for the ISEF, you need to tackle a problem that's interesting to the scientific community. Since few high school students have a good overview of the academic science literature, it's important for any student to have a professional academic scientist or engineer as their mentor. This will ensure that you work on a problem the field considers important.

Science Olympiad

  • Individual or Group: Either
  • Research or Exam: Mix

We've written an in-depth guide on how to excel at Science Olympiad , but here's a brief overview. Schools that compete in Science Olympiad have a team made up of 15 members. Each member typically participates in three or four events. There are 23 events, some of which are "study" events where you learn about a specific topic and are tested on it, and others are "building" events that are hands-on and require you to design something (a plane, bridge, protein model, etc.). The events are varied and cover topics such as human biology, geology, and circuits. You'll be scored for each of your events, and those scores are combined into a team score. There are regional, state, and national competitions each year.

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What to Look for in High School Science Research Competitions

The above list certainly doesn't include every science competition for high schoolers, and if you don't find one that quite fits what you're looking for, feel free to do some additional research of your own. However, use judgement when considering unknown competitions, especially if they are new or you can't find much information about them beyond a website or their social media. Also be wary of those that charge large fees to participate.

Quality science competitions will have a clear and detailed website that explains what the competition is, who is eligible, how you can participate, and who you can contact to learn more. It's not required for them to be backed by an academic or government entity (such as the Department of Energy) or a well-known corporation (such as Toshiba), but having that name recognition can help solidify their legitimacy.

Additionally, older competitions, and those that are national (rather than just local or regional) typically are better known and can stand out more on college applications. While some competitions offer significant prize money, just because a certain competition has smaller/no prizes doesn't mean they're not worth your time. Winners may receive other benefits, such as mentorship or invitations to conferences where they can network.

If you're ever unsure about a science competition, ask your science teacher or guidance counselor about it; they often know a lot about these things and can advise you if you should participate or focus your efforts elsewhere.

How to Include High School Science Competitions in College Applications

Participating in a high school science competition can be a strong asset to your college applications, especially if you plan on majoring in a STEM field. Colleges like to see passion and commitment to your future field of study, and participating in a science competition shows them you have both the skills and motivation to pursue science outside of the classroom. To make your participation as impressive as possible, use the following tips:

#1: Make Clear the Time You Put In

The more time you commit to something the stronger it looks to colleges because it shows dedication and a strong work ethic. So, instead of just listing the science competitions you participated in, be sure to include how long you prepared for the competition and what you were doing. Use numbers whenever possible, for example: "Studied chemistry and biochemistry topics 5-10 hours a week for four semesters" or "spent 25 hours researching biotech innovations, 20 hours contacting and meeting with biotech experts to gather advice and feedback, 60 hours designing prototype…" The more specific and detailed you are, the more colleges will understand how much work you've put into it.

#2: Connect It to Your Spike

Your " spike " is what we call your overarching passion/interest/career goal. For example, your spike might be being a great basketball player, creating a blog with thousands of followers, conducting engineering research, etc. The stronger your spike, the more impressive you are to colleges because you'll show talent, dedication, and passion that will likely continue in college.

If your spike at all relates to STEM, then you want to connect these science competitions to it however you can. Say you want to be a doctor, and your spike is an interest in human biology. If you competed on Science Olympiad, you'd want to be sure to mention any events you were on that related to human biology, mentoring you got from medical professionals, etc. Keep connecting it back to your spike to make your participation in high school science research competitions even stronger.

#3: Highlight Any Initiative You Took

Colleges love it when applicants show initiative because it indicates leadership qualities, aptitude, and motivation. Be sure to make clear any initiative you took with the project. This could include setting up a team, getting your school to participate in a competition it previously didn't have a program for, contacting mentors, designing research protocols, etc. If you came up with the idea on your own and followed through, make sure it shows up on your application!

#4: Don't Feel Like You Had to Win for It to Count

Many science competitions for high school students have thousands of competitors, and only a tiny fraction of those participants will end up winning a prize. However, that doesn't mean they're the only people with a strong extracurricular to add to their applications. Preparing for a competition takes time, skill, and a strong work ethic, all qualities that colleges appreciate. So if you work hard to prepare for a competition, be sure to still include it on your applications, even if you don't end up placing.

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What's Next?

Do you love science? Check out our guide to learn which science classes you should take in high school .

Interested in math competitions, too? Check out our article on the 12 best math competitions for high school students .

Want to learn about other impressive extracurricular activities? Read our guide to see four examples of outstanding extracurriculars that are sure to impress colleges .

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Christine graduated from Michigan State University with degrees in Environmental Biology and Geography and received her Master's from Duke University. In high school she scored in the 99th percentile on the SAT and was named a National Merit Finalist. She has taught English and biology in several countries.

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  • Published: 12 July 2024

The nature of the last universal common ancestor and its impact on the early Earth system

  • Edmund R. R. Moody   ORCID: orcid.org/0000-0002-8785-5006 1 ,
  • Sandra Álvarez-Carretero   ORCID: orcid.org/0000-0002-9508-6286 1 ,
  • Tara A. Mahendrarajah   ORCID: orcid.org/0000-0001-7032-6581 2 ,
  • James W. Clark 3 ,
  • Holly C. Betts 1 ,
  • Nina Dombrowski   ORCID: orcid.org/0000-0003-1917-2577 2 ,
  • Lénárd L. Szánthó   ORCID: orcid.org/0000-0003-3363-2488 4 , 5 , 6 ,
  • Richard A. Boyle 7 ,
  • Stuart Daines 7 ,
  • Xi Chen   ORCID: orcid.org/0000-0001-7098-607X 8 ,
  • Nick Lane   ORCID: orcid.org/0000-0002-5433-3973 9 ,
  • Ziheng Yang   ORCID: orcid.org/0000-0003-3351-7981 9 ,
  • Graham A. Shields   ORCID: orcid.org/0000-0002-7828-3966 8 ,
  • Gergely J. Szöllősi 5 , 6 , 10 ,
  • Anja Spang   ORCID: orcid.org/0000-0002-6518-8556 2 , 11 ,
  • Davide Pisani   ORCID: orcid.org/0000-0003-0949-6682 1 , 12 ,
  • Tom A. Williams   ORCID: orcid.org/0000-0003-1072-0223 12 ,
  • Timothy M. Lenton   ORCID: orcid.org/0000-0002-6725-7498 7 &
  • Philip C. J. Donoghue   ORCID: orcid.org/0000-0003-3116-7463 1  

Nature Ecology & Evolution ( 2024 ) Cite this article

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  • Microbial genetics
  • Molecular evolution
  • Phylogenetics

The nature of the last universal common ancestor (LUCA), its age and its impact on the Earth system have been the subject of vigorous debate across diverse disciplines, often based on disparate data and methods. Age estimates for LUCA are usually based on the fossil record, varying with every reinterpretation. The nature of LUCA’s metabolism has proven equally contentious, with some attributing all core metabolisms to LUCA, whereas others reconstruct a simpler life form dependent on geochemistry. Here we infer that LUCA lived ~4.2 Ga (4.09–4.33 Ga) through divergence time analysis of pre-LUCA gene duplicates, calibrated using microbial fossils and isotope records under a new cross-bracing implementation. Phylogenetic reconciliation suggests that LUCA had a genome of at least 2.5 Mb (2.49–2.99 Mb), encoding around 2,600 proteins, comparable to modern prokaryotes. Our results suggest LUCA was a prokaryote-grade anaerobic acetogen that possessed an early immune system. Although LUCA is sometimes perceived as living in isolation, we infer LUCA to have been part of an established ecological system. The metabolism of LUCA would have provided a niche for other microbial community members and hydrogen recycling by atmospheric photochemistry could have supported a modestly productive early ecosystem.

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The common ancestry of all extant cellular life is evidenced by the universal genetic code, machinery for protein synthesis, shared chirality of the almost-universal set of 20 amino acids and use of ATP as a common energy currency 1 . The last universal common ancestor (LUCA) is the node on the tree of life from which the fundamental prokaryotic domains (Archaea and Bacteria) diverge. As such, our understanding of LUCA impacts our understanding of the early evolution of life on Earth. Was LUCA a simple or complex organism? What kind of environment did it inhabit and when? Previous estimates of LUCA are in conflict either due to conceptual disagreement about what LUCA is 2 or as a result of different methodological approaches and data 3 , 4 , 5 , 6 , 7 , 8 , 9 . Published analyses differ in their inferences of LUCA’s genome, from conservative estimates of 80 orthologous proteins 10 up to 1,529 different potential gene families 4 . Interpretations range from little beyond an information-processing and metabolic core 6 through to a prokaryote-grade organism with much of the gene repertoire of modern Archaea and Bacteria 8 , recently reviewed in ref. 7 . Here we use molecular clock methodology, horizontal gene-transfer-aware phylogenetic reconciliation and existing biogeochemical models to address questions about LUCA’s age, gene content, metabolism and impact on the early Earth system.

Estimating the age of LUCA

Life’s evolutionary timescale is typically calibrated to the oldest fossil occurrences. However, the veracity of fossil discoveries from the early Archaean period has been contested 11 , 12 . Relaxed Bayesian node-calibrated molecular clock approaches provide a means of integrating the sparse fossil and geochemical record of early life with the information provided by molecular data; however, constraining LUCA’s age is challenging due to limited prokaryote fossil calibrations and the uncertainty in their placement on the phylogeny. Molecular clock estimates of LUCA 13 , 14 , 15 have relied on conserved universal single-copy marker genes within phylogenies for which LUCA represented the root. Dating the root of a tree is difficult because errors propagate from the tips to the root of the dated phylogeny and information is not available to estimate the rate of evolution for the branch incident on the root node. Therefore, we analysed genes that duplicated before LUCA with two (or more) copies in LUCA’s genome 16 . The root in these gene trees represents this duplication preceding LUCA, whereas LUCA is represented by two descendant nodes. Use of these universal paralogues also has the advantage that the same calibrations can be applied at least twice. After duplication, the same species divergences are represented on both sides of the gene tree 17 , 18 and thus can be assumed to have the same age. This considerably reduces the uncertainty when genetic distance (branch length) is resolved into absolute time and rate. When a shared node is assigned a fossil calibration, such cross-bracing also serves to double the number of calibrations on the phylogeny, improving divergence time estimates. We calibrated our molecular clock analyses using 13 calibrations (see ‘Fossil calibrations’ in Supplementary Information ). The calibration on the root of the tree of life is of particular importance. Some previous studies have placed a younger maximum constraint on the age of LUCA based on the assumption that life could not have survived Late Heavy Bombardment (LHB) (~3.7–3.9 billion years ago (Ga)) 19 . However, the LHB hypothesis is extrapolated and scaled from the Moon’s impact record, the interpretation of which has been questioned in terms of the intensity, duration and even the veracity of an LHB episode 20 , 21 , 22 , 23 . Thus, the LHB hypothesis should not be considered a credible maximum constraint on the age of LUCA. We used soft-uniform bounds, with the maximum-age bound based on the time of the Moon-forming impact (4,510 million years ago (Ma) ± 10 Myr), which would have effectively sterilized Earth’s precursors, Tellus and Theia 13 . Our minimum bound on the age of LUCA is based on low δ 98 Mo isotope values indicative of Mn oxidation compatible with oxygenic photosynthesis and, therefore, total-group Oxyphotobacteria in the Mozaan Group, Pongola Supergroup, South Africa 24 , 25 , dated minimally to 2,954 Ma ± 9 Myr (ref. 26 ).

Our estimates for the age of LUCA are inferred with a concatenated and a partitioned dataset, both consisting of five pre-LUCA paralogues: catalytic and non-catalytic subunits from ATP synthases, elongation factor Tu and G, signal recognition protein and signal recognition particle receptor, tyrosyl-tRNA and tryptophanyl-tRNA synthetases, and leucyl- and valyl-tRNA synthetases 27 . Marginal densities (commonly referred to as effective priors) fall within calibration densities (that is, user-specified priors) when topologically adjacent calibrations do not overlap temporally, but may differ when they overlap, to ensure the relative age relationships between ancestor-descendant nodes. We consider the marginal densities a reasonable interpretation of the calibration evidence given the phylogeny; we are not attempting to test the hypothesis that the fossil record is an accurate temporal archive of evolutionary history because it is not 28 . The duplicated LUCA node age estimates we obtained under the autocorrelated rates (geometric Brownian motion (GBM)) 29 , 30 and independent-rates log-normal (ILN) 31 , 32 relaxed-clock models with our partitioned dataset (GBM, 4.18–4.33 Ga; ILN, 4.09–4.32 Ga; Fig. 1 ) fall within our composite age estimate for LUCA ranging from 3.94 Ga to 4.52 Ga, comparable to previous studies 13 , 18 , 33 . Dating analyses based on single genes, or concatenations that excluded each gene in turn, returned compatible timescales (Extended Data Figs. 1 and 2 and ‘Additional methods’ in Methods ).

figure 1

Our results suggest that LUCA lived around 4.2 Ga, with a 95% confidence interval spanning 4.09–4.33 Ga under the ILN relaxed-clock model (orange) and 4.18–4.33 Ga under the GBM relaxed-clock model (teal). Under a cross-bracing approach, nodes corresponding to the same species divergences (that is, mirrored nodes) have the same posterior time densities. This figure shows the corresponding posterior time densities of the mirrored nodes for the last universal, archaeal, bacterial and eukaryotic common ancestors (LUCA, LACA, LBCA and LECA, respectively); the last common ancestor of the mitochondrial lineage (Mito-LECA); and the last plastid-bearing common ancestor (LPCA). Purple stars indicate nodes calibrated with fossils. Arc, Archaea; Bac, Bacteria; Euk, Eukarya.

LUCA’s physiology

To estimate the physiology of LUCA, we first inferred an updated microbial phylogeny from 57 phylogenetic marker genes (see ‘Universal marker genes’ in Methods ) on 700 genomes, comprising 350 Archaea and 350 Bacteria 15 . This tree was in good agreement with recent phylogenies of the archaeal and bacterial domains of life 34 , 35 . For example, the TACK 36 and Asgard clades of Archaea 37 , 38 , 39 and Gracilicutes within Bacteria 40 , 41 were recovered as monophyletic. However, the analysis was equivocal as to the phylogenetic placement of the Patescibacteria (CPR) 42 and DPANN 43 , which are two small-genome lineages that have been difficult to place in trees. Approximately unbiased 44 tests could not distinguish the placement of these clades, neither at the root of their respective domains nor in derived positions, with CPR sister to Chloroflexota (as reported recently in refs. 35 , 41 , 45 ) and DPANN sister to Euryarchaeota. To account for this phylogenetic uncertainty, we performed LUCA reconstructions on two trees: our maximum likelihood (ML) tree (topology 1; Extended Data Fig. 3 ) and a tree in which CPR were placed as the sister of Chloroflexota, with DPANN sister to all other Archaea (topology 2; Extended Data Fig. 4 ). In both cases, the gene families mapped to LUCA were very similar (correlation of LUCA presence probabilities (PP), r  = 0.6720275, P  < 2.2 × 10 − 16 ). We discuss the results on the tree with topology 2 and discuss the residual differences in Supplementary Information , ‘Topology 1’ (Supplementary Data 1 ).

We used the probabilistic gene- and species-tree reconciliation algorithm ALE 46 to infer the evolution of gene family trees for each sampled entry in the KEGG Orthology (KO) database 47 on our species tree. ALE infers the history of gene duplications, transfers and losses based on a comparison between a distribution of bootstrapped gene trees and the reference species tree, allowing us to estimate the probability that the gene family was present at a node in the tree 35 , 48 , 49 . This reconciliation approach has several advantages for drawing inferences about LUCA. Most gene families have experienced gene transfer since the time of LUCA 50 , 51 and so explicitly modelling transfers enables us to include many more gene families in the analysis than has been possible using previous approaches. As the analysis is probabilistic, we can also account for uncertainty in gene family origins and evolutionary history by averaging over different scenarios using the reconciliation model. Using this approach, we estimated the probability that each KEGG gene family (KO) was present in LUCA and then used the resulting probabilities to construct a hypothetical model of LUCA’s gene content, metabolic potential (Fig. 2 ) and environmental context (Fig. 3 ). Using the KEGG annotation is beneficial because it allows us to connect our inferences to curated functional annotations; however, it has the drawback that some widespread gene families that were likely present in LUCA are divided into multiple KO families that individually appear to be restricted to particular taxonomic groups and inferred to have arisen later. To account for this limitation, we also performed an analysis of COG (Clusters of Orthologous Genes) 52 gene families, which correspond to more coarse-grained functional annotations (Supplementary Data 2 ).

figure 2

In black: enzymes and metabolic pathways inferred to be present in LUCA with at least PP = 0.75, with sampling in both prokaryotic domains. In grey: those inferred in our least-stringent threshold of PP = 0.50. The analysis supports the presence of a complete WLP and an almost complete TCA cycle across multiple confidence thresholds. Metabolic maps derived from KEGG 47 database through iPath 109 . GPI, glycosylphosphatidylinositol; DDT, 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane.

figure 3

a , A representation of LUCA based on our ancestral gene content reconstruction. Gene names in black have been inferred to be present in LUCA under the most-stringent threshold (PP = 0.75, sampled in both domains); those in grey are present at the least-stringent threshold (PP = 0.50, without a requirement for presence in both domains). b , LUCA in the context of the tree of life. Branches on the tree of life that have left sampled descendants today are coloured black, those that have left no sampled descendants are in grey. As the common ancestor of extant cellular life, LUCA is the oldest node that can be reconstructed using phylogenetic methods. It would have shared the early Earth with other lineages (highlighted in teal) that have left no descendants among sampled cellular life today. However, these lineages may have left a trace in modern organisms by transferring genes into the sampled tree of life (red lines) before their extinction. c , LUCA’s chemoautotrophic metabolism probably relied on gas exchange with the immediate environment to achieve organic carbon (C org ) fixation via acetogenesis and it may also have run the metabolism in reverse. d , LUCA within the context of an early ecosystem. The CO 2 and H 2 that fuelled LUCA’s plausibly acetogenic metabolism could have come from both geochemical and biotic inputs. The organic matter and acetate that LUCA produced could have created a niche for other metabolisms, including ones that recycled CO 2 and H 2 (as in modern sediments). e , LUCA in an Earth system context. Acetogenic LUCA could have been a key part of both surface and deep (chemo)autotrophic ecosystems, powered by H 2 . If methanogens were also present, hydrogen would be released as CH 4 to the atmosphere, converted to H 2 by photochemistry and thus recycled back to the surface ecosystem, boosting its productivity. Ferm., fermentation.

Genome size and cellular features

By using modern prokaryotic genomes as training data, we used a predictive model to estimate the genome size and the number of protein families encoded by LUCA based on the relationship between the number of KEGG gene families and the total number of proteins encoded by modern prokaryote genomes (Extended Data Figs. 5 and 6 ). On the basis of the PPs for KEGG KO gene families, we identified a conservative subset of 399 KOs that were likely to be present in LUCA, with PPs ≥0.75, and found in both Archaea and Bacteria (Supplementary Data 1 ); these families form the basis of our metabolic reconstruction. However, by integrating over the inferred PPs of all KO gene families, including those with low probabilities, we also estimate LUCA’s genome size. Our predictive model estimates a genome size of 2.75 Mb (2.49–2.99 Mb) encoding 2,657 (2,451–2,855) proteins ( Methods ). Although we can estimate the number of genes in LUCA’s genome, it is more difficult to identify the specific gene families that might have already been present in LUCA based on the genomes of modern Archaea and Bacteria. It is likely that the modern version of the pathways would be considered incomplete based on LUCA’s gene content through subsequent evolutionary changes. We should therefore expect reconstructions of metabolic pathways to be incomplete due to this phylogenetic noise and other limitations of the analysis pipeline. For example, when looking at genes and pathways that can uncontroversially be mapped to LUCA, such as the ribosome and aminoacyl-tRNA synthetases for implementing the genetic code, we find that we map many (but not all) of the key components to LUCA (see ‘Notes’ in Supplementary Information ). We interpret this to mean that our reconstruction is probably incomplete but our interpretation of LUCA’s metabolism relies on our inference of pathways, not individual genes.

The inferred gene content of LUCA suggests it was an anaerobe as we do not find support for the presence of terminal oxidases (Supplementary Data 1 ). Instead we identified almost all genes encoding proteins of the archaeal (and most of the bacterial) versions of the Wood–Ljungdahl pathway (WLP) (PP > 0.7), indicating that LUCA had the potential for acetogenic growth and/or carbon fixation 53 , 54 , 55 (Supplementary Data 3 ). LUCA encoded some NiFe hydrogenase subunits ( K06281 , PP = 0.90; K14126 , PP = 0.92), which may have enabled growth on hydrogen (see ‘Notes’ in Supplementary Information ). Complexes involved in methanogenesis such as methyl-coenzyme M reductase and tetrahydromethanopterin S-methyltransferase were inferred to be absent, suggesting that LUCA was unlikely to function as a modern methanogen. We found strong support for some components of the TCA cycle (including subunits of oxoglutarate/2-oxoacid ferredoxin oxidoreductase ( K00175 and K00176 ), succinate dehydrogenase ( K00239 ) and homocitrate synthase ( K02594 )), although some steps are missing. LUCA was probably capable of gluconeogenesis/glycolysis in that we find support for most subunits of enzymes involved in these pathways (Supplementary Data 1 and 3 ). Considering the presence of the WLP, this may indicate that LUCA had the ability to grow organoheterotrophically and potentially also autotrophically. Gluconeogenesis would have been important in linking carbon fixation to nucleotide biosynthesis via the pentose phosphate pathway, most enzymes of which seem to be present in LUCA (see ‘Notes’ in Supplementary Information ). We found no evidence that LUCA was photosynthetic, with low PPs for almost all components of oxygenic and anoxygenic photosystems (Supplementary Data 3 ).

We find strong support for the presence of ATP synthase, specifically, the A ( K02117 , PP = 0.98) and B ( K02118 , PP = 0.94) subunit components of the hydrophilic V/A1 subunit, and the I (subunit a, K02123 , PP = 0.99) and K (subunit c, K02124 , PP = 0.82) subunits of the transmembrane V/A0 subunit. In addition, if we relax the sampling threshold, we also infer the presence of the F1-type β-subunit ( K02112 , PP = 0.94). This is consistent with many previous studies that have mapped ATP synthase subunits to LUCA 6 , 17 , 18 , 56 , 57 .

We obtain moderate support for the presence of pathways for assimilatory nitrate (ferredoxin-nitrate reductase, K00367 , PP = 0.69; ferredoxin-nitrite reductase, K00367 , PP = 0.53) and sulfate reduction (sulfate adenylyltransferase, K00957 , PP = 0.80, and K00958 , PP = 0.73; sulfite reductase, K00392 , PP = 0.82; phosphoadenosine phosphosulfate reductase, K00390 , PP = 0.56), probably to fuel amino acid biosynthesis, for which we inferred the presence of 37 partially complete pathways.

We found support for the presence of 19 class 1 CRISPR–Cas effector protein families in the genome of LUCA, including types I and III (cas3, K07012 , PP = 0.80, and K07475 , PP = 0.74; cas10, K07016 , PP = 0.96, and K19076 , PP = 0.67; and cas7, K07061 , PP = 0.90, K09002 , PP = 0.84, K19075 , PP = 0.97, K19115 , PP = 0.98, and K19140 , PP = 0.80). The absence of Cas1 and Cas2 may suggest LUCA encoded an early Cas system with the means to deliver an RNA-based immune response by cutting (Cas6/Cas3) and binding (CSM/Cas10) RNA, but lacking the full immune-system-site CRISPR. This supports the idea that the effector stage of CRISPR–Cas immunity evolved from RNA sensing for signal transduction, based on the similarities in RNA binding modules of the proteins 58 . This is consistent with the idea that cellular life was already involved in an arms race with viruses at the time of LUCA 59 , 60 . Our results indicate that an early Cas system was an ancestral immune system of extant cellular life.

Altogether, our metabolic reconstructions suggest that LUCA was a relatively complex organism, similar to extant Archaea and Bacteria 6 , 7 . On the basis of ancient duplications of the Sec and ATP synthase genes before LUCA, along with high PPs for key components of those systems, membrane-bound ATP synthase subunits, genes involved in peptidoglycan synthesis ( mraY , K01000 ; murC , K01924 ) and the cytoskeletal actin-like protein, MreB ( K03569 ) (Supplementary Data 3 ), it is highly likely that LUCA possessed the core cellular apparatus of modern prokaryotic life. This might include the basic constituents of a phospholipid membrane, although our analysis did not conclusively establish its composition. In particular, we recovered the following enzymes involved in the synthesis of ether and ester lipids, (alkyldihydroxyacetonephosphate synthase, glycerol 3-phosphate and glycerol 1-phosphate) and components of the mevalonate pathway (mevalonate 5-phosphate dehydratase (PP = 0.84), hydroxymethylglutaryl-CoA reductase (PP = 0.52), mevalonate kinase (PP = 0.51) and hydroxymethylglutaryl-CoA synthase (PP = 0.51)).

Compared with previous estimates of LUCA’s gene content, we find 81 overlapping COG gene families with the consensus dataset of ref. 7 and 69 overlapping KOs with the dataset of ref. 6 . Key points of agreement between previous studies include the presence of signal recognition particle protein, ffh (COG0541, K03106 ) 7 used in the targeting and delivery of proteins for the plasma membrane, a high number of aminoacyl-tRNA synthetases for amino acid synthesis and glycolysis/gluconeogenesis enzymes.

Ref. 6 inferred LUCA to be a thermophilic anaerobic autotroph using the WLP for carbon fixation based on the presence of a single enzyme (CODH), and similarly suggested that LUCA was capable of nitrogen fixation using a nitrogenase. Our reconstruction agrees with ref. 6 that LUCA was an anaerobic autotroph using the WLP for carbon fixation, but we infer the presence of a much more complete WLP than that previously obtained. We did not find strong evidence for nitrogenase or nitrogen fixation, and the reconstruction was not definitive with respect to the optimal growth environment of LUCA.

We used a probabilistic approach to reconstruct LUCA—that is, we estimated the probability with which each gene family was present in LUCA based on a model of how gene families evolve along an overarching species tree. This approach differs from analyses of phylogenetic presence–absence profiles 3 , 4 , 9 or those that used filtering criteria (such as broadly distributed or highly vertically evolving families) to define a high-confidence subset of modern genes that might have been present in LUCA. Our reconstruction maps many more genes to LUCA—albeit each with lower probability—than previous analyses 8 and yields an estimate of LUCA’s genome size that is within the range of modern prokaryotes. The result is an incomplete picture of a cellular organism that was prokaryote grade rather than progenotic 2 and that, similarly to prokaryotes today, probably existed as part of an ecosystem. As the common ancestor of sampled, extant prokaryotic life, LUCA is the oldest node on the species tree that we can reconstruct via phylogenomics but, as Fig. 3 illustrates, it was already the product of a highly innovative period in evolutionary history during which most of the core components of cells were established. By definition, we cannot reconstruct LUCA’s contemporaries using phylogenomics but we can propose hypotheses about their physiologies based on the reconstructed LUCA whose features immediately suggest the potential for interactions with other prokaryotic metabolisms.

LUCA’s environment, ecosystem and Earth system context

The inference that LUCA used the WLP helps constrain the environment and ecology in which it could have lived. Modern acetogens can grow autotrophically on H 2 (and CO 2 ) or heterotrophically on a wide range of alternative electron donors including alcohols, sugars and carboxylic acids 55 . This metabolic flexibility is key to their modern ecological success. Acetogenesis, whether autotrophic or heterotrophic, has a low energy yield and growth efficiency (although use of the reductive acetyl-CoA pathway for both energy production and biosynthesis reduces the energy cost of biosynthesis). This would be consistent with an energy-limited early biosphere 61 .

If LUCA functioned as an organoheterotrophic acetogen, it was necessarily part of an ecosystem containing autotrophs providing a source of organic compounds (because the abiotic source flux of organic molecules was minimal on the early Earth). Alternatively, if LUCA functioned as a chemoautotrophic acetogen it could (in principle) have lived independently off an abiotic source of H 2 (and CO 2 ). However, it is implausible that LUCA would have existed in isolation as the by-products of its chemoautotrophic metabolism would have created a niche for a consortium of other metabolisms (as in modern sediments) (Fig. 3d ). This would include the potential for LUCA itself to grow as an organoheterotroph.

A chemoautotrophic acetogenic LUCA could have occupied two major potential habitats (Fig. 3e ): the first is the deep ocean where hydrothermal vents and serpentinization of sea-floor provided a source of H 2 (ref. 62 ). Consistent with this, we find support for the presence of reverse gyrase (PP = 0.97), a hallmark enzyme of hyperthermophilic prokaryotes 6 , 63 , 64 , 65 , which would not be expected if early life existed at the ocean surface (although the evolution of reverse gyrase is complex 63 ; see ‘Reverse gyrase’ in Supplementary Information ). The second habitat is the ocean surface where the atmosphere would have provided a source of H 2 derived from volcanoes and metamorphism. Indeed, we detected the presence of spore photoproduct lyase (COG1533, K03716 , PP = 0.88) that in extant organisms repairs methylene-bridged thymine dimers occurring in spore DNA as a result of damage induced through ultraviolet (UV) radiation 66 , 67 . However, this gene family also occurs in modern taxa that neither form endospores nor dwell in environments where they are likely to accrue UV damage to their DNA and so is not an exclusive hallmark of environments exposed to UV. Previous studies often favoured a deep-ocean environment for LUCA as early life would have been better protected there from an episode of LHB. However, if the LHB was less intense than initially proposed 20 , 22 , or just a sampling artefact 21 , these arguments weaken. Another possibility may be that LUCA inhabited a shallow hydrothermal vent or a hot spring.

Hydrogen fluxes in these ecosystems could have been several times higher on the early Earth (with its greater internal heat source) than today. Volcanism today produces ~1 × 10 12  mol H 2  yr −1 and serpentinization produces ~0.4 × 10 12  mol H 2  yr − 1 . With the present H 2 flux and the known scaling of the H 2 escape rate to space, an abiotic atmospheric concentration of H 2 of ~150 ppmv is predicted 68 . Chemoautotrophic acetogens would have locally drawn down the concentration of H 2 (in either surface or deep niche) but their low growth efficiency would ensure H 2 (and CO 2 ) remained available. This and the organic matter and acetate produced would have created niches for other metabolisms, including methanogenesis (Fig. 3d ).

On the basis of thermodynamic considerations, CH 4 and CO 2 are expected to be the eventual metabolic end products of the resulting ecosystem, with a small fraction of the initial hydrogen consumption buried as organic matter. The resulting flux of CH 4 to the atmosphere would fuel photochemical H 2 regeneration and associated productivity in the surface ocean (Fig. 3e ). Existing models suggest the resulting global H 2 recycling system is highly effective, such that the supply flux of H 2 to the surface could have exceeded the volcanic input of H 2 to the atmosphere by at least an order of magnitude, in turn implying that the productivity of such a biosphere was boosted by a comparable factor 69 . Photochemical recycling to CO would also have supported a surface niche for organisms consuming CO (ref. 69 ).

In deep-ocean habitats, there could be some localized recycling of electrons (Fig. 3d ) but a quantitative loss of highly insoluble H 2 and CH 4 to the atmosphere and minimal return after photochemical conversion of CH 4 to H 2 means global recycling to depth would be minimal (Fig. 3e ). Hence the surface environment for LUCA could have become dominant (albeit recycling of the resulting organic matter could be spread through ocean depth; ‘Deep heterotrophic ecosystem’ in Fig. 3e ). The global net primary productivity of an early chemoautotrophic biosphere including acetogenic LUCA and methanogens could have been of order ~1 × 10 12 to 7 × 10 12  mol C yr − 1 (~3 orders of magnitude less than today) 69 .

The nutrient supply (for example, N) required to support such a biosphere would need to balance that lost in the burial flux of organic matter. Earth surface redox balance dictates that hydrogen loss to space and burial of electrons/hydrogen must together balance input of electrons/hydrogen. Considering contemporary H 2 inputs, and the above estimate of net primary productivity, this suggests a maximum burial flux in the order of ~10 12  mol C yr − 1 , which, with contemporary stoichiometry (C:N ratio of ~7) could demand >10 11  mol N yr − 1 . Lightning would have provided a source of nitrite and nitrate 70 , consistent with LUCA’s inferred pathways of nitrite and (possibly) nitrate reduction. However, it would only have been of the order 3 × 10 9  mol N yr − 1 (ref. 71 ). Instead, in a global hydrogen-recycling system, HCN from photochemistry higher in the atmosphere, deposited and hydrolysed to ammonia in water, would have increased available nitrogen supply by orders of magnitude toward ~3 × 10 12  mol N yr − 1 (refs. 71 , 72 ). This HCN pathway is consistent with the anomalously light nitrogen isotopic composition of the earliest plausible biogenic matter of 3.8–3.7 Ga (ref. 73 ), although that considerably postdates our inferred age of LUCA. These considerations suggest that the proposed LUCA biosphere (Fig. 3e ) would have been energy or hydrogen limited not nitrogen limited.

Conclusions

By treating gene presence probabilistically, our reconstruction maps many more genes (2,657) to LUCA than previous analyses and results in an estimate of LUCA’s genome size (2.75 Mb) that is within the range of modern prokaryotes. The result is a picture of a cellular organism that was prokaryote grade rather than progenotic 2 and that probably existed as a component of an ecosystem, using the WLP for acetogenic growth and carbon fixation. We cannot use phylogenetics to reconstruct other members of this early ecosystem but we can infer their physiologies based on the metabolic inputs and outputs of LUCA. How evolution proceeded from the origin of life to early communities at the time of LUCA remains an open question, but the inferred age of LUCA (~4.2 Ga) compared with the origin of the Earth and Moon suggests that the process required a surprisingly short interval of geologic time.

Universal marker genes

A list of 298 markers were identified by creating a non-redundant list of markers used in previous studies on archaeal and bacterial phylogenies 10 , 35 , 38 , 74 , 75 , 76 , 77 , 78 , 79 . These markers were mapped to the corresponding COG, arCOG and TIGRFAM profile to identify which profile is best suited to extract proteins from taxa of interest. To evaluate whether the markers cover all archaeal and bacterial diversity, proteins from a set of 574 archaeal and 3,020 bacterial genomes were searched against the COG, arCOG and TIGRFAM databases using hmmsearch (v.3.1b2; settings, hmmsearch–tblout output–domtblout–notextw) 52 , 80 , 81 , 82 . Only hits with an e-value less than or equal to 1 × 10 −5 were investigated further and for each protein the best hit was determined based on the e-value (expect value) and bit-score. Results from all database searches were merged based on the protein identifiers and the table was subsetted to only include hits against the 298 markers of interest. On the basis of this table we calculated whether the markers occurred in Archaea, Bacteria or both Archaea and Bacteria. Markers were only included if they were present in at least 50% of taxa and contained less than 10% of duplications, leaving a set of 265 markers. Sequences for each marker were aligned using MAFFT L-INS-i v.7.407 (ref. 83 ) for markers with less than 1,000 sequences or MAFFT 84 for those with more than 1,000 sequences (setting, –reorder) 84 and sequences were trimmed using BMGE 85 , set for amino acids, a BLOcks SUbstitution Matrix 30 similarity matrix, with a entropy score of 0.5 (v.1.12; settings, -t AA -m BLOSUM30 -h 0.5). Single gene trees were generated with IQ-TREE 2 (ref. 86 ), using the LG substitution matrix, with ten-profile mixture models, four CPUs, with 1,000 ultrafast bootstraps optimized by nearest neighbour interchange written to a file retaining branch lengths (v.2.1.2; settings, -m LG + C10 + F + R -nt 4 -wbtl -bb 1,000 -bnni). These single gene trees were investigated for archaeal and bacterial monophyly and the presence of paralogues. Markers that failed these tests were not included in further analyses, leaving a set of 59 markers (3 arCOGs, 46 COGs and 10 TIGRFAMs) suited for phylogenies containing both Archaea and Bacteria (Supplementary Data 4 ).

Marker gene sequence selection

To limit selecting distant paralogues and false positives, we used a bidirectional or reciprocal approach to identify the sequences corresponding to the 59 single-copy markers. In the first inspection (query 1), the 350 archaeal and 350 bacterial reference genomes were queried against all arCOG HMM (hidden Markov model) profiles (All_Arcogs_2018.hmm), all COG HMM profiles (NCBI_COGs_Oct2020.hmm) and all TIGRFAM HMM profiles (TIGRFAMs_15.0_HMM.LIB) using a custom script built on hmmsearch: hmmsearchTable <genomes.faa> <database.hmm> -E 1 × 10 −5 >HMMscan_Output_e5 (HMMER v.3.3.2) 87 . HMM profiles corresponding to the 59 single-copy marker genes (Supplementary Data 4 ) were extracted from each query and the best-hit sequences were identified based on the e-value and bit-score. We used the same custom hmmsearchTable script and conditions (see above) in the second inspection (query 2) to query the best-hit sequences identified above against the full COG HMM database (NCBI_COGs_Oct2020.hmm). Results were parsed and the COG family assigned in query 2 was compared with the COG family assigned to sequences based on the marker gene identity (Supplementary Data 4 ). Sequence hits were validated using the matching COG identifier, resulting in 353 mismatches (that is, COG family in query 1 does not match COG family in query 2) that were removed from the working set of marker gene sequences. These sequences were aligned using MAFFT L-INS-i 83 and then trimmed using BMGE 85 with a BLOSUM30 matrix. Individual gene trees were inferred under ML using IQ-TREE 2 (ref. 86 ) with model fitting, including both the default homologous substitution models and the following complex heterogeneous substitution models (LG substitution matrices with 10–60-profile mixture models, with empirical base frequencies and a discrete gamma model with four categories accounting for rate heterogeneity across sites): LG + C60 + F + G, LG + C50 + F + G, LG + C40 + F + G, LG + C30 + F + G, LG + C20 + F + G and LG + C10 + F + G, with 10,000 ultrafast bootstraps and 10 independent runs to avoid local optima. These 59 gene trees were manually inspected and curated over multiple rounds. Any horizontal gene transfer events, paralogous genes or sequences that violated domain monophyly were removed and two genes (arCOG01561, tuf ; COG0442, ProS ) were dropped at this stage due to the high number of transfer events, resulting in 57 single-copy orthologues for further tree inference.

Species-tree inference

These 57 orthologous sequences were concatenated and ML trees were inferred after three independent runs with IQ-TREE 2 (ref. 86 ) using the same model fitting and bootstrap settings as described above. The tree with the highest log-likelihood of the three runs was chosen as the ML species tree (topology 1). To test the effect of removing the CPR bacteria, we removed all CPR bacteria from the alignment before inferring a species tree (same parameters as above). We also performed approximately unbiased 44 tree topology tests (with IQ-TREE 2 (ref. 86 ), using LG + C20 + F + G) when testing the significance of constraining the species-tree topology (ML tree; Supplementary Fig. 1 ) to have a DPANN clade as sister to all other Archaea (same parameters as above but with a minimally constrained topology with monophyletic Archaea and DPANN sister to other Archaea present in a polytomy (Supplementary Fig. 2 )) and testing a constraint of CPR to be sister to Chloroflexi (Supplementary Fig. 3 ), and a combination of both the DPANN and CPR constraints (topology 2); these were tested against the ML topology, both using the normal 20 amino acid alignments and also with Susko–Roger recoding 88 .

Gene families

For the 700 representative species 15 , gene family clustering was performed using EGGNOGMAPPER v.2 (ref. 89 ), with the following parameters: using the DIAMOND 90 search, a query cover of 50% and an e-value threshold of 0.0000001. Gene families were collated using their KEGG 47 identifier, resulting in 9,365 gene families. These gene families were then aligned using MAFFT 84 v.7.5 with default settings and trimmed using BMGE 85 (with the same settings as above). Five independent sets of ML trees were then inferred using IQ-TREE 2 (ref. 86 ), using LG + F + G, with 1,000 ultrafast bootstrap replicates. We also performed a COG-based clustering analysis in which COGs were assigned based on the modal COG identifier annotated for each KEGG gene family based on the results from EGGNOGMAPPER v.2 (ref. 89 ). These gene families were aligned, trimmed and one set of gene trees (with 1,000 ultrafast bootstrap replicates) was inferred using the same parameters as described above for the KEGG gene families.

Reconciliations

The five sets of bootstrap distributions were converted into ALE files, using ALEobserve, and reconciled against topology 1 and topology 2 using ALEml_undated 91 with the fraction missing for each genome included (where available). Gene family root origination rates were optimized for each COG functional category as previously described 35 and families were categorized into four different groups based on the probability of being present in the LUCA node in the tree. The most-stringent category was that with sampling above 1% in both domains and a PP ≥ 0.75, another category was with PP ≥ 0.75 with no sampling requirement, another with PP ≥ 0.5 with the sampling requirement; the least stringent was PP ≥ 0.5 with no sampling requirement. We used the median probability at the root from across the five runs to avoid potential biases from failed runs in the mean and to account for variation across bootstrap distributions (see Supplementary Fig. 4 for distributions of the inferred ratio of duplications, transfers and losses for all gene families across all tips in the species tree; see Supplementary Data 5 for the inferred duplications, transfers and losses ratios for LUCA, the last bacterial common ancestor and the last archaeal common ancestor).

Metabolic pathway analysis

Metabolic pathways for gene families mapped to the LUCA node were inferred using the KEGG 47 website GUI and metabolic completeness for individual modules was estimated with Anvi’o 92 (anvi-estimate-metabolism), with pathwise completeness.

Additional testing

We tested for the effects of model complexity on reconciliation by using posterior mean site frequency LG + C20 + F + G across three independent runs in comparison with 3 LG + F + G independent runs. We also performed a 10% subsampling of the species trees and gene family alignments across two independent runs for two different subsamples, one with and one without the presence of Asgard archaea. We also tested the likelihood of the gene families under a bacterial root (between Terrabacteria and Gracilicutes) using reconciliations of the gene families under a species-tree topology rooted as such.

Fossil calibrations

On the basis of well-established geological events and the fossil record, we modelled 13 uniform densities to constrain the maximum and minimum ages of various nodes in our phylogeny. We constrained the bounds of the uniform densities to be either hard (no tail probability is allowed after the age constraint) or soft (a 2.5% tail probability is allowed after the age constraint) depending on the interpretation of the fossil record ( Supplementary Information ). Nodes that refer to the same duplication event are identified by MCMCtree as cross-braced (that is, one is chosen as the ‘driver’ node, the rest are ‘mirrored’ nodes). In other words, the sampling during the Markov chain Monte Carlo (MCMC) for cross-braced nodes is not independent: the same posterior time density is inferred for matching mirror–driver nodes (see ‘Additional methods’ for details on our cross-bracing approach).

Timetree inference analyses

Timetree inference with the program MCMCtree (PAML v.4.10.7 (ref. 93 )) proceeded under both the GBM and ILN relaxed-clock models. We specified a vague rate prior with the shape parameter equal to 2 and the scale parameter equal to 2.5: Γ(2, 2.5). This gamma distribution is meant to account for the uncertainty on our estimate for the mean evolutionary rate, ~0.81 substitutions per site per time unit, which we calculated by dividing the tree height of our best-scoring ML tree ( Supplementary Information ) into the estimated mean root age of our phylogeny (that is, 4.520 Ga, time unit = 10 9 years; see ‘Fossil calibrations’ in Supplementary Information for justifications on used calibrations). Given that we are estimating very deep divergences, the molecular clock may be seriously violated. Therefore, we applied a very diffuse gamma prior on the rate variation parameter ( σ 2 ), Γ(1, 10), so that it is centred around σ 2  = 0.1. To incorporate our uncertainty regarding the tree shape, we specified a uniform kernel density for the birth–death sampling process by setting the birth and death processes to 1, λ  (per-lineage birth rate) =  μ  (per-lineage death rate) = 1, and the sampling frequency to ρ  (sampling fraction) = 0.1. Our main analysis consisted of inferring the timetree for the partitioned dataset under both the GBM and the ILN relaxed-clock models in which nodes that correspond to the same divergences are cross-braced (that is, hereby referred to as cross-bracing A). In addition, we ran 10 additional inference analyses to benchmark the effect that partitioning, cross-bracing and relaxed-clock models can have on species divergence time estimation: (1) GBM + concatenated alignment + cross-bracing A, (2) GBM + concatenated alignment + cross-bracing B (only nodes that correspond to the same divergences for which there are fossil constraints are cross-braced), (3) GBM + concatenated alignment + without cross-bracing, (4) GBM + partitioned alignment + cross-bracing B, (5) GBM + partitioned alignment + without cross-bracing, (6) ILN + concatenated alignment + cross-bracing A, (7) ILN + concatenated alignment + cross-bracing B, (8) ILN + concatenated alignment + without cross-bracing, (9) ILN + partitioned alignment + cross-bracing B, and (10) ILN + partitioned alignment + without cross-bracing. Lastly, we used (1) individual gene alignments, (2) a leave-one-out strategy (rate prior changed for alignments without ATP and Leu , Γ(2, 2.2), and without Tyr , Γ(2, 2.3), but was Γ(2, 2.5) for the rest; see ‘Additional methods’), and (3) a more complex substitution model 94 to assess their impact on timetree inference. Refer to ‘Additional methods’ for details on how we parsed the dataset we used for timetree inference analyses, ran PAML programs CODEML and MCMCtree to approximate the likelihood calculation 95 , and carried out the MCMC diagnostics for the results obtained under each of the previously mentioned scenarios.

We simulated 100 samples of ‘KEGG genomes’ based on the probabilities of each of the (7,467) gene families being present in LUCA using the random.rand function in numpy 96 . The mean number of KEGG gene families was 1,298.25, the 95% HPD (highest posterior density) minimum was 1,255 and the maximum was 1,340. To infer the relationship between the number of KEGG KO gene families encoded by a genome, the number of proteins and the genome size, we used LOESS (locally estimated scatter-plot smoothing) regression to estimate the relationship between the number of KOs and (1) the number of protein-coding genes and (2) the genome size for the 700 prokaryotic genomes used in the LUCA reconstruction. To ensure that our inference of genome size is robust to uncertainty in the number of paralogues that can be expected to have been present in LUCA, we used the presence of probability for each of these KEGG KO gene families rather than the estimated copy number. We used the predict function to estimate the protein-coding genes and genome size of LUCA using these models and the simulated gene contents encoded with 95% confidence intervals.

Additional methods

Cross-bracing approach implemented in mcmctree.

The PAML program MCMCtree was implemented to allow for the analysis of duplicated genes or proteins so that some nodes in the tree corresponding to the same speciation events in different paralogues share the same age. We used the tree topology depicted in Supplementary Fig. 5 to explain how users can label driver or mirror nodes (more on these terms below) so that the program identifies them as sharing the same speciation events. The tree topology shown in Supplementary Fig. 5 can be written in Newick format as:

(((A1,A2),A3),((B1,B2),B3));

In this example, A and B are paralogues and the corresponding tips labelled as A1–A3 and B1–B3 represent different species. Node r represents a duplication event, whereas other nodes are speciation events. If we want to constrain the same speciation events to have the same age (that is, Supplementary Fig. 5 , see labels a and b (that is, A1–A2 ancestor and B1–B2 ancestor, respectively) and labels v and b (that is, A1–A2–A3 ancestor and B1–B2–B3 ancestor, respectively), we use node labels in the format #1, #2, and so on to identify such nodes:

(((A1, A2) #1, A3) #2, ((B1, B2) [#1 B{0.2, 0.4}], B3) #2) 'B(0.9,1.1)';

Node a and node b are assigned the same label (#1) and so they share the same age ( t ): t a  =  t b . Similarly, node u and node v have the same age: t u  =  t v . The former nodes are further constrained by a soft-bound calibration based on the fossil record or geological evidence: 0.2 <  t a  =  t b  < 0.4. The latter, however, does not have fossil constraints and thus the only restriction imposed is that both t u and t v are equal. Finally, there is another soft-bound calibration on the root age: 0.9 <  t r  < 1.1.

Among the nodes on the tree with the same label (for example, those nodes labelled with #1 and those with #2 in our example), one is chosen as the driver node, whereas the others are mirror nodes. If calibration information is provided on one of the shared nodes (for example, nodes a and b in Supplementary Fig. 5 ), the same information therefore applies to all shared nodes. If calibration information is provided on multiple shared nodes, that information has to be the same (for example, you could not constrain node a with a different calibration used to constrain node b in Supplementary Fig. 5 ). The time prior (or the prior on all node ages on the tree) is constructed by using a density at the root of the tree, which is specified by the user (for example, 'B(0.9,1.1)' in our example, which has a minimum of 0.9 and a maximum of 1.1). The ages of all non-calibrated nodes are given by the uniform density. This time prior is similar to that used by ref. 29 . The parameters in the birth–death sampling process ( λ , μ , ρ ; specified using the option BDparas in the control file that executes MCMCtree) are ignored. It is noteworthy that more than two nodes can have the same label but one node cannot have two or more labels. In addition, the prior on rates does not distinguish between speciation and duplication events. The implemented cross-bracing approach can only be enabled if option duplication = 1 is included in the control file. By default, this option is set to 0 and users are not required to include it in the control file (that is, the default option is duplication = 0 ).

Timetree inference

Data parsing.

Eight paralogues were initially selected based on previous work showing a likely duplication event before LUCA: the amino- and carboxy-terminal regions from carbamoyl phosphate synthetase, aspartate and ornithine transcarbamoylases, histidine biosynthesis genes A and F , catalytic and non-catalytic subunits from ATP synthase ( ATP ), elongation factor Tu and G ( EF ), signal recognition protein and signal recognition particle receptor ( SRP ), tyrosyl-tRNA and tryptophanyl-tRNA synthetases ( Tyr ), and leucyl- and valyl-tRNA synthetases ( Leu ) 27 . Gene families were identified using BLASTp 97 . Sequences were downloaded from NCBI 98 , aligned with MUSCLE 99 and trimmed with TrimAl 100 (-strict). Individual gene trees were inferred under the LG + C20 + F + G substitution model implemented in IQ-TREE 2 (ref. 86 ). These trees were manually inspected and curated to remove non-homologous sequences, horizontal gene transfers, exceptionally short or long sequences and extremely long branches. Recent paralogues or taxa of inconsistent and/or uncertain placement inferred with RogueNaRok 101 were also removed. Independent verification of an archaeal or bacterial deep split was achieved using minimal ancestor deviation 102 . This filtering process resulted in the five pairs of paralogous gene families 27 ( ATP , EF , SRP , Tyr and Leu ) that we used to estimate the origination time of LUCA. The alignment used for timetree inference consisted of 246 species, with the majority of taxa having at least two copies (for some eukaryotes, they may be represented by plastid, mitochondrial and nuclear sequences).

To assess the impact that partitioning can have on divergence time estimates, we ran our inference analyses with both a concatenated and a partitioned alignment (that is, gene partitioning scheme). We used PAML v.4.10.7 (programs CODEML and MCMCtree) for all divergence time estimation analyses. Given that a fixed tree topology is required for timetree inference with MCMCtree, we inferred the best-scoring ML tree with IQ-TREE 2 under the LG + C20 + F + G4 (ref. 103 ) model following our previous phylogenetic analyses. We then modified the resulting inferred tree topology following consensus views of species-level relationships 34 , 35 , 104 , which we calibrated with the available fossil calibrations (see below). In addition, we ran three sensitivity tests: timetree inference (1) with each gene alignment separately, (2) under a leave-one-out strategy in which each gene alignment was iteratively removed from the concatenated dataset (for example, remove gene ATP but keep genes EF , Leu , SRP and Tyr concatenated in a unique alignment block; apply the same procedure for each gene family), and (3) using the vector of branch lengths, the gradient vector and the Hessian matrix estimated under a complex substitution model (bsinBV method described in ref. 94 ) with the concatenated dataset used for our core analyses. Four of the gene alignments generated for the leave-one-out strategy had gap-only sequences, these were removed when re-inferring the branch lengths under the LG + C20 + F + G4 model (that is, without ATP , 241 species; without EF , 236 species; without Leu , 243 species; without Tyr , 244 species). We used these trees to set the rate prior used for timetree inference for those alignments not including ATP , EF , Leu or Tyr , respectively. The β value (scale parameter) for the rate prior used when analysing alignments without ATP , Leu and Tyr changed minimally but we updated the corresponding rate priors accordingly (see above). When not including SRP , the alignment did not have any sequences removed (that is, 246 species). All alignments were analysed with the same rate prior, Γ(2, 2.5), except for the three previously mentioned alignments.

Approximating the likelihood calculation during timetree inference using PAML programs

Before timetree inference, we ran the CODEML program to infer the branch lengths of the fixed tree topology, the gradient (first derivative of the likelihood function) and the Hessian matrix (second derivative of the likelihood function); the vectors and matrix are required to approximate the likelihood function in the dating program MCMCtree 95 , an approach that substantially reduces computational time 105 . Given that CODEML does not implement the CAT (Bayesian mixture model for across-site heterogeneity) model, we ran our analyses under the closest available substitution model: LG + F + G4 (model = 3). We calculated the aforementioned vectors and matrix for each of the five gene alignments (that is, required for the partitioned alignment), for the concatenated alignment and for the concatenated alignments used for the leave-one-out strategy; the resulting values are written out in an output file called rst2. We appended the rst2 files generated for each of the five individual alignments in the same order the alignment blocks appear in the partitioned alignment file (for example, the first alignment block corresponds to the ATP gene alignment, and thus the first rst2 block will be the one generated when analysing the ATP gene alignment with CODEML). We named this file in_5parts.BV. There is only one rst2 output file for the concatenated alignments, which we renamed in.BV (main concatenated alignment and concatenated alignments under leave-one-out strategy). When analysing each gene alignment separately, we renamed the rst2 files generated for each gene alignment as in.BV.

MCMC diagnostics

All the chains that we ran with MCMCtree for each type of analysis underwent a protocol of MCMC diagnostics consisting of the following steps: (1) flagging and removal of problematic chains; (2) generating convergence plots before and after chain filtering; (3) using the samples collected by those chains that passed the filters (that is, assumed to have converged to the same target distribution) to summarize the results; (4) assessing chain efficiency and convergence by calculating statistics such as R-hat, tail-ESS and bulk-ESS (in-house wrapper function calling Rstan functions, Rstan v.2.21.7; https://mc-stan.org/rstan/ ); and (5) generating the timetrees for each type of analysis with confidence intervals and high-posterior densities to show the uncertainty surrounding the estimated divergence times. Tail-ESS is a diagnostic tool that we used to assess the sampling efficiency in the tails of the posterior distributions of all estimated divergence times, which corresponds to the minimum of the effective sample sizes for quantiles 2.5% and 97.5%. To assess the sampling efficiency in the bulk of the posterior distributions of all estimated divergence, we used bulk-ESS, which uses rank-normalized draws. Note that if tail-ESS and bulk-ESS values are larger than 100, the chains are assumed to have been efficient and reliable parameter estimates (that is, divergence times in our case). R-hat is a convergence diagnostic measure that we used to compare between- and within-chain divergence time estimates to assess chain mixing. If R-hat values are larger than 1.05, between- and within-chain estimates do not agree and thus mixing has been poor. Lastly, we assessed the impact that truncation may have on the estimated divergence times by running MCMCtree when sampling from the prior (that is, the same settings specified above but without using sequence data, which set the prior distribution to be the target distribution during the MCMC). To summarize the samples collected during this analysis, we carried out the same MCMC diagnostics procedure previously mentioned. Supplementary Fig. 6 shows our calibration densities (commonly referred to as user-specified priors, see justifications for used calibrations above) versus the marginal densities (also known as effective priors) that MCMCtree infers when building the joint prior (that is, a prior built without sequence data that considers age constraints specified by the user, the birth–death with sampling process to infer the time densities for the uncalibrated nodes, the rate priors, and so on). We provide all our results for these quality-control checks in our GitHub repository ( https://github.com/sabifo4/LUCA-divtimes ) and in Extended Data Fig. 1 , Supplementary Figs. 7 – 10 and Supplementary Data 6 . Data, figures and tables used and/or generated following a step-by-step tutorial are detailed in the GitHub repository for each inference analysis.

Additional sensitivity analyses

We compared the divergence times we estimated with the concatenated dataset under the calibration strategy cross-bracing A with those inferred (1) for each gene, (2) for gene alignments analysed under a leave-one-out strategy, and (3) for the main concatenated dataset but when using the vector of branch lengths, the gradient vector and the Hessian matrix estimated under a more complex substitution model 94 . The results are summarized in Extended Data Fig. 2 and Supplementary Data 7 and 8 . The same pattern regarding the calibration densities and marginal densities when the tree topology was pruned (that is, see above for details on the leave-one-out strategy) was observed, and thus no additional figures have been generated. As for our main analyses, the results for these additional sensitivity analyses can be found on our GitHub repository ( https://github.com/sabifo4/LUCA-divtimes ).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

All data required to interpret, verify and extend the research in this article can be found at our figshare repository at https://doi.org/10.6084/m9.figshare.24428659 (ref. 106 ) for the reconciliation and phylogenomic analyses and GitHub at https://github.com/sabifo4/LUCA-divtimes (ref. 107 ) for the molecular clock analyses. Additional data are available at the University of Bristol data repository, data.bris, at https://doi.org/10.5523/bris.405xnm7ei36d2cj65nrirg3ip (ref. 108 ).

Code availability

All code relating to the dating analysis can be found on GitHub at https://github.com/sabifo4/LUCA-divtimes (ref. 107 ), and other custom scripts can be found in our figshare repository at https://doi.org/10.6084/m9.figshare.24428659 (ref. 106 ).

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Acknowledgements

Our research is funded by the John Templeton Foundation (62220 to P.C.J.D., N.L., T.M.L., D.P., G.A.S., T.A.W. and Z.Y.; the opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation), Biotechnology and Biological Sciences Research Council (BB/T012773/1 to P.C.J.D. and Z.Y.; BB/T012951/1 to Z.Y.), by the European Research Council under the European Union’s Horizon 2020 research and innovation programme (947317 ASymbEL to A.S.; 714774, GENECLOCKS to G.J.S.), Leverhulme Trust (RF-2022-167 to P.C.J.D.), Gordon and Betty Moore Foundation (GBMF9741 to T.A.W., D.P., P.C.J.D., A.S. and G.J.S.; GBMF9346 to A.S.), Royal Society (University Research Fellowship (URF) to T.A.W.), the Simons Foundation (735929LPI to A.S.) and the University of Bristol (University Research Fellowship (URF) to D.P.).

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Edmund R. R. Moody, Sandra Álvarez-Carretero, Holly C. Betts, Davide Pisani & Philip C. J. Donoghue

Department of Marine Microbiology and Biogeochemistry, NIOZ, Royal Netherlands Institute for Sea Research, Den Burg, The Netherlands

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Milner Centre for Evolution, Department of Life Sciences, University of Bath, Bath, UK

James W. Clark

Department of Biological Physics, Eötvös University, Budapest, Hungary

Lénárd L. Szánthó

MTA-ELTE ‘Lendulet’ Evolutionary Genomics Research Group, Budapest, Hungary

Lénárd L. Szánthó & Gergely J. Szöllősi

Institute of Evolution, HUN-REN Center for Ecological Research, Budapest, Hungary

Global Systems Institute, University of Exeter, Exeter, UK

Richard A. Boyle, Stuart Daines & Timothy M. Lenton

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Xi Chen & Graham A. Shields

Department of Genetics, Evolution and Environment, University College London, London, UK

Nick Lane & Ziheng Yang

Model-Based Evolutionary Genomics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan

Gergely J. Szöllősi

Department of Evolutionary & Population Biology, Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, The Netherlands

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Contributions

The project was conceived and designed by P.C.J.D., T.M.L., D.P., G.J.S., A.S. and T.A.W. Dating analyses were performed by H.C.B., J.W.C., S.Á.-C., P.J.C.D. and E.R.R.M. T.A.M., N.D. and E.R.R.M. performed single-copy orthologue analysis for species-tree inference. L.L.S., G.J.S., T.A.W. and E.R.R.M. performed reconciliation analysis. E.R.R.M. performed homologous gene family annotation, sequence, alignment, gene tree inference and sensitivity tests. E.R.R.M., A.S. and T.A.W. performed metabolic analysis and interpretation. T.M.L., S.D. and R.A.B. provided biogeochemical interpretation. E.R.R.M., T.M.L., A.S., T.A.W., D.P. and P.J.C.D. drafted the article to which all authors (including X.C., N.L., Z.Y. and G.A.S.) contributed.

Corresponding authors

Correspondence to Edmund R. R. Moody , Davide Pisani , Tom A. Williams , Timothy M. Lenton or Philip C. J. Donoghue .

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Extended data

Extended data fig. 1 comparison of the mean divergence times and confidence intervals estimated for the two duplicates of luca under each timetree inference analysis..

Black dots refer to estimated mean divergence times for analyses without cross-bracing, stars are used to identify those under cross-bracing and triangles for estimated upper and lower confidence intervals. Straight lines are used to link mean divergence time estimates across the various inference analyses we carried out, while dashed lines are used to link the estimated confidence intervals. The node label for the driver node is “248”, while it is “368” for the mirror node, as shown in the title of each graph. Coloured stars and triangles are used to identify which LUCA time estimates were inferred under the same cross-braced analysis for the driver-mirror nodes (that is, equal time and CI estimates). Black dots and triangles are used to identify those inferred when cross-bracing was not enabled (that is, different time and CI estimates). -Abbreviations. “GBM”: Geometric Brownian motion relaxed-clock model; “ILN”: Independent-rate log-normal relaxed-clock model; “conc, cb” dots/triangles: results under cross-bracing A when the concatenated dataset was analysed under GBM (red) and ILN (blue); “conc, fosscb”: results under cross-bracing B when the concatenated dataset was analysed under GBM (orange) and ILN (cyan); “part, cb” dots/triangles: results under cross-bracing A when the partitioned dataset was analysed under GBM (pink) and ILN (purple); “part, fosscb”: results under cross-bracing B when the concatenated dataset was analysed under GBM (light green) and ILN (grey); black dots and triangles: results when cross-bracing was not enabled for both concatenated and partitioned datasets.

Extended Data Fig. 2 Comparison of the posterior time estimates and confidence intervals for the two duplicates of LUCA inferred under the main calibration strategy cross-bracing A with the concatenated dataset and with the datasets for the three additional sensitivity analyses.

Dots refer to estimated mean divergence times and triangles to estimated 2.5% and 97.5% quantiles. Straight lines are used to link the mean divergence times estimated in the same analysis under the two different relaxed-clock models (GBM and ILN). Labels in the x axis are informative about the clock model under which the analysis ran and the type of analysis we carried (see abbreviations below). Coloured dots are used to identify which time estimates were inferred when using the same dataset and strategy under GBM and ILN, while triangles refer to the corresponding upper and lower quantiles for the 95% confidence interval. -Abbreviations. “GBM”: Geometric Brownian motion relaxed-clock model; “ILN”: Independent-rate log-normal relaxed-clock model; “main-conc”: results obtained with the concatenated dataset analysed in our main analyses under cross-bracing A; “ATP/EF/Leu/SRP/Tyr”: results obtained when using each gene alignment separately; “noATP/noEF/noLeu/noSRP/noTyr”: results obtained when using concatenated alignments without the gene alignment mentioned in the label as per the “leave-one-out” strategy; “main-bsinbv”: results obtained with the concatenated dataset analysed in our main analyses when using branch lengths, Hessian, and gradient calculated under a more complex substitution model to infer divergence times.

Extended Data Fig. 3 Maximum Likelihood species tree.

The Maximum Likelihood tree inferred across three independent runs, under the best fitting model (according to BIC: LG + F + G + C60) from a concatenation of 57 orthologous proteins, support values are from 10,000 ultrafast bootstraps. Referred to as topology I in the main text. Tips coloured according to taxonomy: Euryarchaeota (teal), DPANN (purple), Asgardarchaeota (cyan), TACK (blue), Gracilicutes (orange), Terrabacteria (red), DST (brown), CPR (green).

Extended Data Fig. 4 Maximum Likelihood tree for focal reconciliation analysis.

Maximum Likelihood tree (topology II in the main text), where DPANN is constrained to be sister to all other Archaea, and CPR is sister to Chloroflexi. Tips coloured according to taxonomy: Euryarchaeota (teal), DPANN (purple), Asgardarchaeota (cyan), TACK (blue), Gracilicutes (orange), Terrabacteria (red), DST (brown), CPR (green). AU topology test, P = 0.517, this is a one-sided statistical test.

Extended Data Fig. 5 The relationship between the number of KO gene families encoded on a genome and its size.

LOESS regression of the number of KOs per sampled genome against the genome size in megabases. We used the inferred relationship for modern prokaryotes to estimate LUCA’s genome size based on reconstructed KO gene family content, as described in the main text. Shaded area represents the 95% confidence interval.

Extended Data Fig. 6 The relationship between the number of KO gene families encoded on a genome and the total number of protein-coding genes.

LOESS regression of the number of KOs per sampled genome against the number of proteins encoded for per sampled genome. We used the inferred relationship for modern prokaryotes to estimate the total number of protein-coding genes encoded by LUCA based on reconstructed KO gene family content, as described in the main text. Shaded area represents the 95% confidence interval.

Supplementary information

Supplementary information.

Supplementary Notes and Figs. 1–10.

Reporting Summary

Peer review file, supplementary data 1.

This table contains the results of the reconciliations for each gene family. KEGG_ko is the KEGG orthology ID; arc_domain_prop is the proportion of the sampled Archaea; bac_domain_prop is the proportion of the sampled bacteria; gene refers to gene name, description and enzyme code; map refers to the different KEGG maps of which this KEGG gene family is a component; pathway is a text description of the metabolic pathways of which these genes are a component; alignment_length refers to the length of the alignment in amino acids; highest_COG_cat refers to the number of sequences placed in the most frequent COG category; difference_1st_and_2nd is the difference between the most frequent COG category and the second most frequent COG category; categories is the number of different COG categories assigned to this KEGG gene family; COG_freq is the proportion of the sequences placed in the most frequent COG category; COG_cat is the most frequent COG functional category; Archaea is the number of archaeal sequences sampled in the gene family; Bacteria is the number of bacterial sequences sampled in the gene family; alternative_COGs is the number of alternative COG gene families assigned across this KEGG orthologous gene family; COG_perc is the proportion of the most frequent COG ID assigned to this KEGG gene family; COG is the COG ID of the most frequenty COG assigned to this gene family; COG_NAME is the description of the most frequent COG ID assigned to this gene family; COG_TAG is the symbol associated with the most frequent COG gene familiy; sequences is the total number of sequences assigned to this gene family; Arc_prop is the proportion of Archaea that make up this gene family; Bac_prop is the proportion of Bacteria that make up this gene family; constrained_median is the median probability (PP) that this gene was present in LUCA from our reconciliation under the focal constrained tree search across the 5 independent bootstrap distribution reconciliations; ML_median is the median PP of the gene family being present in LUCA with gene tree bootstrap distributions against the ML species-tree topology across the 15 independent bootstrap distribution reconciliations; MEAN_OF_MEDIANS is the mean value across the constrained and ML PP results; RANGE_OF_MEDIANS is the range of the PPs for the constrained and ML topology PPs for LUCA; Probable_and_sampling_threshold_met is our most stringent category of gene families inferred in LUCA with 0.75 + PP and a sampling requirement of 1% met in both Archaea and Bacteria; Possible_and_sampling_threshold_met is a threshold of 0.50 + PP and sampling both domains; probable is simply 0.75 + PP; and possible is 0.50 + PP.

Supplementary Data 2

PP for COGs. This table contains the results for the reconciliations of COG-based gene family clustering against the constrained focal species-tree topology. Columns are named similarly to Supplementary Data 1 but each row is a different COG family. The column Modal_KEGG_ko refers to the most frequent KEGG gene family in which a given COG is found; sequences_in_modal_KEGG refers to the number of sequences in the most frequent KEGG gene family.

Supplementary Data 3

Module completeness. Estimated pathway completeness for KEGG metabolic modules (with a completeness greater than zero in at least one confidence threshold) using Anvi’o’s stepwise pathway completeness 48 . Module_name is the name of the module; module_category is the broader category into which the module falls; module_subcategory is a more specific category; possible_anvio includes the gene families with a median PP ≥ 0.50; probable_anvio related to gene families PP ≥ 0.75; and _ws refers to the sampling requirement being met (presence in at least 1% of the sampled Archaea and Bacteria).

Supplementary Data 4

Marker gene metadata for all markers checked during marker gene curation, including the initial 59 single-copy marker genes used in species-tree inference (see Methods ). Data include marker gene set provenance, marker gene name, marker gene description, presence in different marker gene sets 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , and presence in Archaea and Bacteria. When available, marker genes are matched with their arCOG, TIGR, and COG ID and their respective occurrence across different taxonomic sets is quantified.

Supplementary Data 5

The ratio of duplications, transfers and losses in relation to the total number of copies for the deep ancestral nodes: the LUCA, archaeal (LACA) and bacterial (LBCA) common ancestors, and the average (mean) and 95th percentile.

Supplementary Data 6

Spreadsheet containing a list of the estimated divergence times for all timetree inferences carried out and the corresponding results of the MCMC diagnostics. Tabs Divtimes_GBM-allnodes and Divtimes_ILN-allnodes represent a list of the estimated divergence times (Ma) for all nodes under the 12 inference analyses we ran under GBM and ILN, respectively. Tabs Divtimes_GBM-highlighted and Divtimes_ILN-highlighted represent a list of the estimated divergence times (Ma) for selected nodes ordered according to their mirrored nodes under the 12 inference analyses we ran under GBM and ILN, respectively. Each of the tabs MCMCdiagn_prior, MCMCdiagn_postGBM and MCMCdiagn_postILN contains the statistical results of the MCMC diagnostics we ran for each inference analysis. Note that, despite the analyses carried out when sampling from the prior could have only been done three times (that is, data are not used, and thus only once under each calibration strategy was enough), we repeated them with each dataset regardless. In other words, results for (1) ‘concatenated + cross-bracing A’ and ‘partitioned + cross-bracing A’; (2) ‘concatenated + without cross-bracing’ and ‘partitioned + without cross-bracing’; and (3) ‘concatenated + cross-bracing B’ and ‘partitioned + cross-bracing B’ would be equivalent, respectively. For tabs 1–4, part represents partitioned dataset; conc, concatenated dataset; cb, cross-bracing A; notcb, without cross-bracing; fosscb, cross-bracing B; mean_t, mean posterior time estimate; 2.5%q, 2.5% quantile of the posterior time density for a given node; and 97.5%q, 97.5% quantile of the posterior time density for a given node. For tabs 5–7, med. num. samples collected per chain represents median of the total amount of samples collected per chain; min. num. samples collected per chain, minimum number of samples collected per chain; max. num. samples collected per chain, minimum number of samples collected per chain; num. samples used to calculate stats, number of samples collected by all chains that passed the filters that were used to calculate the tail-ESS, bulk-ESS and R-hat values. For tail-ESS, we report the median, minimum, and maximum tail-ESS values; all larger than 100 as required for assuming reliable parameter estimates. For bulk-ESS, we report the median, minimum and maximum bulk-ESS values; all larger than 100 as required for assuming reliable parameter estimates. For R-hat, minimum and maximum values reported, all smaller than 1.05 as required to assume good mixing.

Supplementary Data 7

Spreadsheet containing a list of the posterior time estimates for LUCA obtained under the main calibration strategy cross-bracing A with the concatenated dataset and with the datasets for the three additional sensitivity analyses. The first column ‘label’ contains the node number for both the driver and mirror nodes for LUCA (the latter includes the term -dup in the label). Columns mean_t, 2.5%q, and 97.5%q refer to the estimated mean divergence times, and the 2.5%/97.5% quantiles of the posterior time density for the corresponding node. Main-conc, refers to results obtained with the concatenated dataset analysed in our main analyses under cross-bracing A; ATP/EF/Leu/SRP/Tyr, results obtained when using each gene alignment separately; noATP/noEF/noLeu/noSRP/noTyr, results obtained when using concatenated alignments without the gene alignment mentioned in the label as per the leave-one-out strategy; main-bsinbv, results obtained with the concatenated dataset analysed in our main analyses when using branch lengths, Hessian and gradient calculated under a more complex substitution model to infer divergence times.

Supplementary Data 8

Spreadsheet containing a list of the estimated divergence times for all timetree inferences carried out for the sensitivity analyses and the corresponding results for the MCMC diagnostics. Tabs Divtimes_GBM-allnodes and Divtimes_ILN-allnodes represent a list of the estimated divergence times (Ma) for all nodes under the 11 inference analyses we ran under GBM and ILN when testing the impact on divergence times estimation when (1) analysing each gene alignment individually, (2) following a leave-one-out strategy, and (3) using the branch lengths, Hessian and gradient estimated under a more complex model for timetree inference (bsinBV approach). Tabs Divtimes_GBM-highlighted and Divtimes_ILN-highlighted represent a list of the estimated divergence times (Ma) for selected nodes ordered according to their mirrored nodes we ran under GBM and ILN for the sensitivity analyses (we also included the results with the main concatenated dataset for reference). Each of tabs MCMCdiagn_prior, MCMCdiagn_postGBM and MCMCdiagn_postILN contains the statistical results of the MCMC diagnostics we ran for the sensitivity analyses. Note that, despite the analyses carried out when sampling from the prior could have only been done once for each different tree topology (that is, data are not used, only topological changes may affect the resulting marginal densities), we ran them with each dataset regardless as part of our pipeline. For tabs 1–4, main-conc represents results obtained with the concatenated dataset analysed in our main analyses under cross-bracing A; ATP/EF/Leu/SRP/Tyr, results obtained when using each gene alignment separately; noATP/noEF/noLeu/noSRP/noTyr, results obtained when using concatenated alignments without the gene alignment mentioned in the label as per the leave-one-out strategy; main-bsinbv, results obtained with the concatenated dataset analysed in our main analyses when using branch lengths, Hessian and gradient calculated under a more complex substitution model to infer divergence times; mean_t, mean posterior time estimate; 2.5%q, 2.5% quantile of the posterior time density for a given node; and 97.5%q, 97.5% quantile of the posterior time density for a given node. For tabs 5–7, med. num. samples collected per chain represents the median of the total amount of samples collected per chain; min. num. samples collected per chain, minimum number of samples collected per chain; max. num. samples collected per chain, minimum number of samples collected per chain; num. samples used to calculate stats, number of samples collected by all chains that passed the filters that were used to calculate the tail-ESS, bulk-ESS and R-hat values. For tail-ESS, we report the median, minimum and maximum tail-ESS values; all larger than 100 as required for assuming reliable parameter estimates. For bulk-ESS, we report the median, minimum and maximum bulk-ESS values; all larger than 100 as required for assuming reliable parameter estimates. For R-hat, minimum and maximum values are reported, all smaller than 1.05 as required to assume good mixing.

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Moody, E.R.R., Álvarez-Carretero, S., Mahendrarajah, T.A. et al. The nature of the last universal common ancestor and its impact on the early Earth system. Nat Ecol Evol (2024). https://doi.org/10.1038/s41559-024-02461-1

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The science competitions your students can enter this year

By Emma Molloy

Discover STEM-themed competitions for you and your students to enter in this academic year

A digital artwork showing an atom next to a trophy

Source: © Shutterstock

Learn about the fantastic array of science competitions your students can enter – so you can sign up as soon as possible

There is a great range of science competitions out there that your students can enter. Competitions come in all shapes and sizes, including essay writing, photography and video competitions, and can be local or national events.

Besides the array of downloadable materials you can make use of in your lessons, as homework or part of a science club, the benefits of taking part include learning how to work in a team, grasping how lessons apply to real-world problems, and there could even be some extra cash to bag!

You can jump straight to the lists of science-writing competitions , or more arty competitions (such as photography and drawing prizes), or simply read on to discover what’s open to you and your students this academic year.

These competitions have been ordered by closing date. Listing a competition does not serve as an endorsement by the RSC.  Last updated: 16 May 2024.

Cambridge Chemistry Challenge

Age: 19 or younger

Registration opens: now

Closes:  1 June 2024

This competition — aimed at Year 12 students but available to younger students — is designed to stretch and challenge students beyond the curriculum interested in chemistry and is excellent experience for anyone considering chemistry for further study.

Students sit a 90-minute written paper under exam conditions in school, which is sent out to schools in advance. Mark schemes are available to teachers, and for schools submitting more than five scripts, these should be marked by the teacher. Scripts of students scoring over 50% are then submitted. Students who perform well receive a certificate and the best performers are invited to join a residential camp at the University of Cambridge at the end of August

The website contains lots of past papers and mark schemes, which are a valuable resource for teachers. Full details are on the  website .

Science meets art

If you have some students who would be hooked by the artistic side of science, check out these competitions:

  • RSB Photography competition (open to all ages; opens March 2024; £500 top prize for under 18s)
  • RSB Nancy Rothwell Award for specimen drawing (ages 7–18; open March–July 2024; prizes include set of drawing pencils and small cash prizes for students and schools)
  • Science Without Borders challenge is an artwork competition with a focus on ocean conservation. The 2024 theme is ‘hidden wonders of the deep’ (ages 11–19; closes 4 March 2024; maximum prize of $500)
  • British Science Week poster competition ; this year’s theme will be ‘time’ (ages 3–14; closes March 2024)
  • RPS Woman Science Photographer of the Year is open to women of all ages and backgrounds (open and under 18s; closing date TBC but expected March 2024)
  • Minds Underground Competitions ; Minds Underground run a number of essay competitions each year covering a variety of STEM and other topics (all ages; closing dates vary but 2024 questions will be released January 2024, see website for full details)

UKBC Intermediate Biology Olympiad

Age: Students in first year of 16+ education

Registration opens: now open

Competition dates: 5–12 June 2024

This international, annual competition is open to students in the first year of post-16 education in the UK. The competition consists of a one-hour multiple choice paper that is taken online under formal exam conditions. Questions cover topics students will be familiar with alongside some new concepts to test their problem-solving skills and understanding of core principals.

Practice papers are available to print to help students prepare. The competition is free to enter for UK schools and participants receive an e-certificate that recognises their level of achievement.

Find more information, including registering your school to take part, on the  UKBC website .

Science writing competitions

Numerous essays competitions run each year covering all aspects and areas of STEM. Below is just a selection of some of the competitions out there. Entries into science writing competitions make great additions to UCAS applications, and they get students thinking about science, too.

  • The  Oxford Scientist  Schools’ Science Writing Competition  (700-word essay that teachers submit; ages 15–18; deadline 10 July 2024; prize includes being published in the magazine and feedback).
  • Newnham College, Camb ridge (2000-word academic essay; age 16–18 women at state school only; deadline 8 July 2024; winners receive up to £400 to split with their school). Teachers can sign up to mailing lists now to hear more about this essay competition and other events from the college.

IET Faraday Challenge

Registration opens: January 2024 for the 2024–2025 season

Closes: July 2024

Faraday Challenges  are cross-curricular STEM activity days for UK schools run by the Institution of Engineering and Technology. This annual competition draws on students’ practical science and engineering skills, asking them to work in teams to solve real-world engineering problems and think creatively. Schools can host Challenge Days and invite teams from local schools to join them or apply to join a day at another school. Planning for these events starts early, so plenty of time to get organised for the day.

Teams should be made up of six students aged 12–13 years old (England and Wales Year 8, Scotland S1/S2, Northern Ireland Year 9). Schools may host a challenge day themselves or attend one hosted at another school.

Students win prizes for themselves and a trophy for their school. There is also a national league table and the top teams from across the UK go through to the national final, with the chance to win a cash prize of up to £1000 for their school. Plus, by taking part students will also meet the criteria for achieving a CREST Discovery Award.

If you are not able to enter into the main competition, there is also the opportunity for students to take part in the  Virtual Faraday Challenge  open to anyone aged 7–15.

Local to Newcastle?

Newcastle Secondary School SciFair  is a university-run secondary school science fair for students from state schools across Newcastle. Sci-Fair is a whole day event that will take place during British Science Week. Students can get the opportunity to present their models, posters or PowerPoint presentations about a scientific topic of their choosing. SciFair is open to ages 11–16. There are multiple prizes to be won on the day to recognise student’s efforts. Spaces are limited capacity, so students should wait for their projects to be approved before starting work.

EMBL Art and Science Project

Age: 14–18 Participation deadline: 31 August 2024

Discover the world of proteins with the European Molecular Biology Laboratory, and create an artwork inspired by what you’ve learned. Cash prizes of up to €100.

Visit the website to find out more. 

Deadlines passed:

Stockholm uk junior water prize.

Submissions open: 29 Feb 2024

Submission deadline: 13 May 2024

This prize challenges young people in STEM to develop innovative yet practical solutions to the global water crisis. Entrants decide on a topic or problem that they want to investigate and undertake background research and experimental work before submitting a full written report.

Students whose reports are shortlisted get to present their work virtually to the judges. The winning UK entry receives £1,000 cash prize and a fully funded trip to represent the UK and their school at the Stockholm Junior Water Prize competition in Sweden in August and be in with a chance to win the international grand prize of US$15,000!

Learn more on the  website .

UKBC Biology Challenge

Competition dates: 1–17 May 2024

The Biology Challenge is a fun, annual competition open to students aged 13–15 in the UK. The challenge compromises of two, 25-minute, multiple-choice papers, and students need to complete both papers to be considered for an award category.

The questions set cover the school curriculum, but also caters to budding biologists whose knowledge has been enhanced by reading books and magazines, watching natural history programmes and taking a keen interest in all things biology.

Practice papers are available to help students prepare. The competition is free to enter for UK schools and participants receive an e-certificate that recognises their category of achievement.

Find more information and register your school to take part on the  Biology Challenge website .

BIEA Youth STEAM Competition

Registration opens:  October 2023

Closes: April 2024 for first-round submissions

The  BIEA Youth STEAM Competition  asks students to use their creativity to come up with ideas for a more sustainable future based on a specific theme. The theme for 2024 has yet to be announced, but the theme for 2023 was “developing solutions for sustainable cities”. Students research, design and present their solution, including a written report.

Students can enter as individuals or in teams of up to five members and schools can enter more than one team. There are lots of competition categories to cover all age groups. Submissions are expected to be accepted from January 2024 and the international final to be in July 2024. Learn more on the competition  website .

Royal College of Science Union (RCSU) Science Challenge

Registration opens:  1 March 2024

Closes: 26 April 2024

Imperial College London’s RCSU Science Challenge is all about science communication – requiring students to demonstrate their skills in debate and reasoning and teach the public about science and its consequences. Questions on a given theme are set by eminent scientists – who even read the shortlisted entries, so there’s a real chance students’ work will be seen by world-leading academics. This year’s theme is Hidden depth.

Students can answer one of the questions in either written or video form of up to 1000 words or three minutes, 30 seconds, respectively. Winners receive cash prizes, plus there are non-cash prizes for the runners up.

Shortlisted candidates will be invited to the grand final on 21 June 2024 at the Royal Institution, where they will deliver a short presentation. Find more information about taking part on the  challenge website .

Unsung Heroes of Science video competition

Close s: 30 April 2024

The International  Unsung Heroes of Science video competition   from Hertford College, University of Oxford is open to all 16–18 students. Entrants are tasked with making a two-minute video sharing the story of a scientist whose contributions were overlooked. Entries can be submitted by individuals or in teams of up to three.

The competition website also has lesson plans and links to videos of previous unsung heros, which are great resources for teachers to inspire their students.

British Science Week poster competition

Age: 3–14 Registration opened: January 2024 Closes: March 2024

British Science Week will run from 8–17 March. Alongside numerous activities and events across the country, there will be a themed poster competition – and this year’s theme will is ‘time’.

Entrants can explore a wide range of ideas covered by the broad theme. Judges are on the look out for an innovative angle or creative interpretation of the theme; clear, accurate and informative content; and effective, engaging communication. This competition is a great way for students to practise their communication skills. There are numerous prizes up for grabs that cover all age categories.

Entrants can be teams or individuals from any organisation, although schools are limited to five entries. Find out more on the  website , including activity packs and other resources to make the most of British Science Week.

Big Bang Young Scientists and Engineers Competition

Age: 11–18 Registration opens:  October 2023 Closes: 27 March 2024

The Big Bang Competition  is open to young people aged 11 to 18 in state-funded education or who are home educated or who enter as part of a community group. Private school participants can get involved as part of a collaboration with state-school peers.

Participants complete project-based work, focusing on investigation, discovery and use of scientific methods. Students choose their own STEM topic and work to submit their project as a written report or short video. The possibilities are endless!

Students can include their involvement in the competition in their extracurricular activities on UCAS forms and personal statements and have a chance of winning a range of awards and cash prizes.

Find out how to get started and get inspired with past projects on the  Big Bang website .

MathWorks Math Modeling challenge

Age: 16–19 (England and Wales only) Registration opens:  November 2023 Closes: 24 February 2024

The  M3 Challenge  is an internet-based applied maths competition that inspires participants to pursue STEM education and careers. Working in teams of three to five students, participants have 14 consecutive hours to solve an open-ended maths-modelling problem based around a real issue during the challenge weekend, 1–4 March 2024.

The problem typically has a socially conscious theme – equity, the environment, conservation or recycling, energy use, health, and other topics that young people care about. The challenge gives students the opportunity to use maths modelling processes to represent, analyse, make predictions and otherwise provide insight into real-world phenomena. For example, 2023’s problem centred around modelling the impacts of e-bikes to better understand if they are likely to become part of a global, more sustainable energy plan.

Numerous free  resources , including modelling and coding handbooks, videos and sample problems are available to help teams prepare for the event.

The competition’s final presentation and awards ceremony event is held in New York City in late April – an all-expense paid experience for the finalist teams. These top teams will be awarded scholarships toward the pursuit of higher education, with members of the overall winning team receiving $20,000 (»£16,000).

For rules, resources and to register, visit the competition  website .

The Cambridge Upper Secondary Science Competition

Age: 16–18 Registration opens: now Closes:  30 September 2023 and 31 March 2024

The  Cambridge Upper Secondary Science Competition , run by Cambridge Assessment, is an exciting extra-curricular activity for teams of aspiring scientists who are studying with the Cambridge IGCSE or O Level science programmes.

Teams of three to six students choose a topic and work on a scientific investigation over 20–25 hours. The competition encourages investigations with some practical or community relevance and an eye on sustainability.

Projects may involve laboratory work and should include creative and collaborative working, critical thinking and reflection. Students should be given the opportunity to present their results to a wider audience, perhaps at a science fair or other school event.

Teachers provide initial project evaluations and the best are put forward for consideration by a panel of experts. The winning team receives a certificate and is featured on the competition website. The competition runs twice a year, so keep abreast of all the dates  on the website .

TeenTech Awards 

Age: 11–16 Registration opens: now Closes:  March 2024 for first-round submissions

The  TeenTech Awards  encourage students to see how they might apply science and technology to real-world problems across several different categories, from food and retail through the future of transport to wearable technology. Students identify an opportunity or a problem, suggest a solution and research the market.

Students can work in teams of up to three people and there are lots of award categories. All submitted projects receive feedback and a bronze, silver or gold award. The event is well supported with training sessions for teachers and students, so everyone knows what to expect and what the judges will be looking for!

The best projects go forward to the TeenTech Awards Final for judging and the winning school in each category will receive a cash prize. The final is expected to take place in London in June 2024.

Schools’ Analyst

Age: 16–17 Registration opens: soon Closes: 23 February 2024

The  Schools’ Analyst Competition  is returning to schools in 2024. Run collaboratively by the Analytical Chemistry Trust Fund and the Royal Society of Chemistry, this event allows students to expand their chemistry knowledge and skills through practical analytical experiments. Students must be in Year 12 (England, Wales, NI)/S5 (Scotland)/5th Year (Ireland).

Schools and colleges register their interest to host a heat and, if randomly selected, can now enter up to 25 teams of three students to compete to be crowned the overall school winner. Each winning school team will then compete within their region to find regional winners. Regional winners receive a cash prize for themselves and their school.

Register your school  to take part by 23 February 2024. To take part, students only need access to standard school laboratory equipment and some consumables (a bursary is available for those who need it).

Equipment boxes are sent to 400 entrants, selected at random, and delivered in advance of the event. Results must be submitted by 17 May in Ireland (to ensure schools have the chance to award winners before the summer holidays) and 14 June elsewhere.

Slingshot Challenge

Age: 13–18 Registration opens: now Closes: 1 February 2024

The  Slingshot Challenge  is run by National Geographic and is an exciting opportunity for students to get involved with the global programme. Students can enter in teams of up to six. Individual entries are welcomed although all entries are expected to involve collaboration with peers, stakeholders, and/or marginalized communities.

Students work to prepare a short, 1-minute video, from topics with an environmental focus. Training sessions for teachers and resource/tool kits are available from the website and the providers can offer feedback and technical support ahead of official submissions.

Videos are expected to put forward compelling, evidence-based information and be engaging for the audience. A small number of motivating prizes are awarded each year to the student of up to $10,000.

For full details see the  Slingshot Challenge website .

UK Chemistry Olympiad 

Age: 16–18 (recommended) Registration opens: September 2023 Closes: January 2024

Run by the RSC, the  UK Chemistry Olympiad  is designed to challenge and inspire older secondary-school students, by encouraging them to push themselves, boost their critical problem-solving skills and test their knowledge in real-world situations.  Explore past papers  to get an idea of the types of questions involved.

There are three rounds that culminate with the prestigious  International Chemistry Olympiad , which will take place this year in Riyadh, Saudi Arabia. Round 1, a written test taken in your school, is scheduled to take place on 25 January 2024. Students then receive bronze, silver or gold certificates depending on their scores. Up to 30 students will then be selected to move on to the second round – a training weekend at the University of Nottingham. Four students will then be chosen to represent the UK in the international competition from 21–30 July 2024.

To get started, register your school or college. Do this and find out more information about preparing on the  Olympiad homepage .

Top of the Bench

Age: 14–16 Registration opens: soon Closes: January 2024

Top of the Bench  (TOTB) is an annual practical chemistry competition that has been running for over 20 years. It’s a long-standing favourite for students and teachers, and provides an opportunity for students to put their teamwork and practical skills to the test.

Regional heats are led by  RSC local sections  between October and January. The winning team from each heat progresses to the national final, held in the spring at a UK university (where there is also a session for teachers to explore resources and classroom ideas with one of the RSC’s education coordinators).

First prize is awarded to the best overall school performance, with five teams receiving runners up prizes. The Jacqui Clee Award is also awarded each year to the student who makes an outstanding individual contribution.

Teams must consist of four students: two from year 9/S2; one from year 10/S3; one from year 11/S4.

Find more information including past papers and how to apply on the  TOTB homepage .

Imperial College Science & Innovation Competition

Age:  4–adult Registration opens:  September  2023 Closes:  15 December 2023

The  Science & Innovation Competition , run by the Faculty of Natural Sciences at Imperial College, aims to motivate primary and secondary-aged children to engage with science, to encourage them to work as part of a team and engage in fun activities. Adults are also welcome to enter.

Teams of two to four people are asked to develop a new and innovative scientific solution to help achieve one of the  United Nation’s Global Goals for Sustainable Development . To enter, teams need to create a five-minute film that describes the science behind their idea. Finalists are invited to take part in an event during spring 2024 at Imperial College, London (date to be confirmed). Learn more on the  website .

Global essay competition: Young voices in the chemical sciences for sustainability

Age: 35 and under  Registration opens: now Closes: 31 March 2023

An  annual essay competition  on the role of the chemical sciences in sustainability, organised by the International Organization for Chemical Sciences in Development (IOCD) in collaboration with the Royal Society of Chemistry (RSC). The competition is open globally to entrants under 35 years of age. The theme for the 2023 competition is: How can the chemical sciences lead the stewardship of the Earth’s element resources?

Essays will be grouped into seven regions for shortlisting and selection of winners, based on the entrant’s country of normal residence. Each regional winner will receive a prize of US$500 and their entries will be published in  RSC Sustainability . The shortlisted essays will be collected in an annual compendium,  Young voices in the chemical sciences for sustainability , available on the IOCD’s website. Individual shortlisted entries will also be featured from time to time on IOCD’s website.

Essays will be judged on how well they highlight the importance of scientific approaches grounded in the chemical sciences for solving sustainability challenges. Entrants should take a broad, global perspective, and reflect on the intersection of science, society and policy aspects, rather than describing a particular scientific advance in great technical detail. Essays must not exceed 1500 words of body copy.

Cambridge Chemistry Race

Age: 16–18 Registration opens: Mon 5 December 2022 Closes: February 2023

In the  Cambridge Chemistry Race , teams of 3–5 students solve as many theoretical problems as they can over the course of two hours – ranging from easy riddles to tasks of A-level difficulty and complex chemical problems.

Once a team has solved a question, the examiner verifies their answer and hands them the next question. Points are awarded based on the number of successful attempts. Whoever gets the most points wins!

Students are allowed to use a calculator, books, notes, and printed literature. The challenge aims to test problem-solving skills and chemical understanding rather than knowledge. Explore past questions and solutions  here  to get an idea of what’s in store.

Schools may only enter one team each and places are first come first served.

The competition is run in collaboration with the University of Cambridge’s Department of Chemistry. This year, it is joined by the University of Oxford too, so students may compete in either city. The competition will take place on Saturday 4 February 2023. Learn more on the  competition website .

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Competition Law Research Paper Topics

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This page presents a comprehensive exploration of competition law research paper topics , designed to assist law students in their pursuit of academic excellence. As competition law continues to play a critical role in regulating market dynamics, students often face the challenge of choosing compelling research topics that reflect the evolving complexities of this field. Here, we highlight the diverse range of competition law research paper topics covered in this page, encompassing anti-competitive agreements, abuse of dominant market position, mergers and acquisitions, intellectual property issues, digital markets, international antitrust enforcement, consumer protection, public policy implications, and emerging issues in the digital era. Through this curated list of topics, students will gain insights into the multifaceted dimensions of competition law, fostering critical thinking and the ability to address real-world challenges in an ever-changing legal landscape. Whether investigating the intersection of competition law and technology or exploring the impact of global trade on market competition, this page aims to empower students with an array of research paper ideas to embark on their scholarly endeavors in competition law.

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Anti-competitive Agreements:

  • The Role of Cartels in Market Manipulation: Case Studies and Impact on Consumers
  • Horizontal vs. Vertical Agreements: Analyzing the Distinctions and Legal Implications
  • Price Fixing and Collusion: Assessing the Challenges of Detecting and Prosecuting Anti-competitive Conduct
  • Leniency Programs: Evaluating the Effectiveness in Combating Cartels and Encouraging Cooperation
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  • Technology Cartels and the Digital Age: Investigating Anti-competitive Practices in Tech Markets
  • Intellectual Property and Competition: Antitrust Implications of Patent Pools and Cross-Licensing Agreements
  • Compliance Mechanisms for Agreements: Promoting Ethical Business Practices and Preventing Collusion
  • Bundling and Tying Arrangements: Analyzing the Impact on Market Entry and Consumer Choice
  • Antitrust Enforcement in the Pharmaceutical Industry: Addressing Market Distortions and Access to Medicine.

Abuse of Dominant Market Position:

  • Monopolization and Market Power: Analyzing the Criteria for Identifying Dominant Firms
  • Predatory Pricing and Market Entry Barriers: Evaluating the Impact on Competitors and Consumers
  • Exclusionary Practices by Tech Giants: The Intersection of Dominance and Digital Markets
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  • Refusal to Deal and Essential Inputs: Assessing the Role of Dominant Entities in Supply Chains
  • Intellectual Property and Dominant Firms: Exploring the Intersection of Competition Law and Patents
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  • Monopoly Regulation in Developing Economies: Promoting Fair Competition and Economic Growth.

Mergers and Acquisitions:

  • Merger Control Thresholds: The Balance between Market Concentration and Facilitating Business Transactions
  • Failing Firm Defense: Evaluating the Criteria for Allowing Mergers in Distressed Companies
  • Killer Acquisitions: Assessing the Impact of Acquiring Potential Competitors on Innovation
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  • Remedies in Merger Control: Evaluating the Effectiveness of Divestitures and Behavioral Conditions
  • Merger Waves and Economic Cycles: Examining the Relationship between M&A Activities and Market Performance
  • Merger Notification Procedures: Streamlining the Review Process and Ensuring Effective Decision-Making.

Intellectual Property and Competition Law:

  • Standard-Essential Patents and FRAND Commitments: Balancing Innovation Incentives and Access to Essential Technologies
  • Patent Thickets and Competition: Addressing Patent Pools and Overlapping Rights
  • Intellectual Property Rights and Market Power: Antitrust Scrutiny of Dominant Firms with Strong IP Portfolios
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  • Copyright Licensing and Competition: The Interface between Copyright and Market Competition
  • Big Data and Antitrust: The Impact of Data Dominance on Market Concentration and Consumer Choice
  • Digital Rights Management and Competition Law: Striking a Balance between Copyright Protection and Market Access
  • Antitrust Enforcement in the Digital Media Industry: Implications for Content Creators and Distribution Platforms
  • Innovation and Market Dominance: The Interaction between Patent Protection and Competition Law.

Competition Law and Digital Markets:

  • Big Tech and Platform Dominance: Investigating the Role of Technology Giants in Shaping Digital Markets
  • Data Privacy and Antitrust: Analyzing the Relationship between Consumer Data and Market Power
  • Online Platforms and Self-Preferencing: The Legal Boundaries of Fair Competition in E-Commerce
  • Algorithmic Collusion: Detecting and Addressing Collusive Behavior in Automated Systems
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International Antitrust Enforcement:

  • Extraterritorial Application of Competition Law: The Legal Challenges and Global Cooperation Efforts
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  • Regional Competition Agreements: Assessing the Role of Regional Bodies in Promoting Cross-Border Competition
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  • Antitrust in the Digital Silk Road: The Impact of China’s Belt and Road Initiative on Global Markets
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  • Price Discrimination and Consumer Welfare: Analyzing the Impact on Vulnerable Populations
  • Online Consumer Rights in Digital Markets: Ensuring Fair Practices and Redress Mechanisms
  • Competition Law and Healthcare: Addressing Market Concentration and Access to Medicine
  • Financial Services and Market Regulation: Consumer Protection in the Banking Sector
  • Consumer Data and Privacy in the Digital Age: The Intersection of Consumer Protection and Data Dominance
  • Unfair Competition Practices: Analyzing the Role of Unfair Competition in Restraining Market Access and Consumer Choice
  • Product Safety and Market Competition: Balancing Innovation and Consumer Welfare
  • Consumer Empowerment and Market Information: The Impact of Market Transparency on Consumer Decision-Making
  • Competition Law Remedies for Consumer Harm: Evaluating the Effectiveness of Compensation Mechanisms.

Public Policy and Competition Law:

  • Antitrust and Innovation: The Interplay between Market Competition and Technological Advancements
  • Competition Policy and Economic Development: The Role of Antitrust in Fostering Economic Growth
  • Political Influence and Market Concentration: Analyzing the Impact of Lobbying on Antitrust Regulation
  • Market Regulation in Times of Crisis: Addressing Competition Challenges during Economic Downturns
  • National Security and Competition Law: Balancing National Interests and Open Markets
  • Market Power and Income Inequality: The Socioeconomic Implications of Market Concentration
  • Technology Transfer and National Interest: Assessing the Role of Competition Law in Safeguarding Innovation
  • Corporate Social Responsibility and Market Dominance: Examining Ethical Business Practices and Market Influence
  • Environmental Sustainability and Competition Law: The Relationship between Competition and Green Business Practices
  • Digital Sovereignty and Market Control: Navigating the Challenges of Global Technology Regulation.

Emerging Issues in the Digital Era:

  • Artificial Intelligence and Antitrust: The Challenges of Addressing Algorithmic Collusion
  • Blockchain Technology and Market Competition: The Potential of Decentralized Markets
  • Data Monopolies and Market Distortion: Antitrust Implications in Data-Driven Economies
  • Internet of Things and Market Dominance: The Intersection of Connected Devices and Competition Law
  • Virtual Markets and Market Power: Analyzing the Antitrust Impact of Virtual Goods and Services
  • Privacy Regulation and Competition Law: The Balancing Act between Data Protection and Market Competition
  • Digital Disinformation and Competition Law: Addressing Misinformation and Consumer Manipulation
  • Competition Law Enforcement in the Gig Economy: The Challenges of Regulating Flexible Work Arrangements
  • Smart Cities and Antitrust: The Impact of Technological Urbanization on Market Concentration
  • Cybersecurity and Market Competition: The Role of Antitrust in Protecting Against Cyber Threats.

Case Studies in Competition Law:

  • Microsoft Antitrust Case: Analyzing the Legacy of the U.S. v. Microsoft Corp. Case
  • Google Antitrust Cases: Assessing the EU’s Multiple Investigations into Google’s Market Dominance
  • Apple vs. Epic Games: The Antitrust Battle over App Store Policies and Market Access
  • Qualcomm vs. FTC: The Antitrust Litigation over Qualcomm’s Licensing Practices
  • Intel Antitrust Case: Examining the European Commission’s Decision on Intel’s Market Dominance
  • Amazon and Antitrust: Investigating Amazon’s Role as a Dominant E-Commerce Platform
  • Facebook and Market Dominance: The Antitrust Scrutiny of Social Media Platforms
  • Standard Oil and the Origins of Antitrust: A Historical Perspective on Competition Regulation
  • Uber and Antitrust: Addressing the Competition Challenges in the Ride-Hailing Industry
  • Visa and Mastercard Antitrust Cases: Analyzing the Legal Battle over Credit Card Network Fees.

In conclusion, this comprehensive list of competition law research paper topics offers a diverse and extensive range of areas for exploration in the dynamic field of antitrust regulation and market competition. From examining the implications of anti-competitive agreements to navigating the challenges of regulating digital markets, students will find ample opportunities to delve into complex legal issues and contribute to the ongoing evolution of competition law. By exploring these thought-provoking topics, students can enhance their critical thinking skills, develop a deeper understanding of legal complexities, and contribute to the advancement of competition law jurisprudence. This carefully curated collection aims to empower law students in their academic pursuits and inspire them to undertake impactful research in the realm of competition law.

Competition Law: Exploring the Range of Research Paper Topics

Competition law, also known as antitrust law in some jurisdictions, is a crucial area of legal study that aims to promote fair competition and prevent anti-competitive practices in the marketplace. It plays a vital role in maintaining a level playing field for businesses, safeguarding consumer interests, and fostering economic efficiency. As students of law venture into the realm of competition law, they are presented with a vast and ever-evolving landscape of legal issues to explore and analyze. This section delves into the multifaceted world of competition law research paper topics, highlighting key areas of interest and offering valuable insights to inspire law students in their academic pursuits.

The Evolution of Competition Law

To begin our exploration, it is essential to understand the historical development of competition law. Students can investigate the origins of antitrust regulation, examining landmark cases and legislative milestones that have shaped the field over time. They can explore how competition law has evolved to adapt to new economic challenges and technological advancements, such as the impact of globalization and the digital era on market competition.

Theoretical Perspectives in Competition Law

Competition law draws upon various economic theories to justify its existence and guide its application. Students can delve into different theoretical perspectives, such as the Chicago School of thought, the Harvard School, and the Post-Chicago School, and critically analyze their implications for antitrust policy and enforcement. This area of research allows students to explore the tensions between economic efficiency and consumer welfare, as well as the role of competition authorities in balancing competing objectives.

Comparative Analysis of Competition Laws

Conducting a comparative study of competition laws across different jurisdictions provides an enriching research opportunity. Students can compare and contrast the legal frameworks, enforcement approaches, and policy objectives of various countries, shedding light on the diversity of approaches to competition regulation and identifying potential areas of harmonization or cooperation in the global context.

Market Definition and Dominance Assessment

Defining relevant markets and assessing market dominance are critical steps in competition law analysis. Research papers in this area can explore the methodologies used by competition authorities to define markets, measure market power, and identify dominant firms. Students can examine the challenges of market definition in emerging sectors, such as digital markets and technology-driven industries.

Anti-competitive Agreements

The prohibition of anti-competitive agreements lies at the core of competition law. Students can investigate the different types of agreements, such as cartels, price-fixing arrangements, and bid-rigging, and explore the legal and economic consequences of such collusive practices. Research papers may delve into leniency programs, the role of whistleblowers, and the use of technology in detecting and prosecuting anti-competitive agreements.

Abuse of Dominant Market Position

Analyzing cases of market dominance and abuse is an area of significant interest in competition law research. Students can examine the factors that contribute to market power, such as barriers to entry, network effects, and economies of scale, and explore how dominant firms may engage in exclusionary conduct to maintain or strengthen their position in the market. This research can include the examination of cases involving monopolization, predatory pricing, and refusal to deal.

Merger Control and Consolidation

Mergers and acquisitions have the potential to impact market competition significantly. Research papers in this area can focus on the effectiveness of merger control regulations in preventing anti-competitive consolidation, the role of economic analysis in merger reviews, and the challenges of regulating cross-border mergers. Students can explore the factors considered by competition authorities when evaluating the competitive effects of mergers and the design of remedies to address potential anti-competitive concerns.

Competition Law Enforcement in the Digital Age

As the world becomes increasingly digitalized, competition law faces new challenges in addressing the unique issues arising in the digital marketplace. Students can investigate the role of competition law in regulating online platforms, data-driven markets, and the use of algorithms. They may examine the complexities of applying traditional competition principles to the digital economy and consider the role of big data, artificial intelligence, and machine learning in competition enforcement.

Sector-Specific Competition Law

Competition law is often tailored to address specific industries or sectors. Students can explore sector-specific competition regulations, such as competition law in the healthcare industry, telecommunications, financial services, or energy markets. This research allows for an in-depth examination of the particular challenges and policy objectives that arise in different sectors and how competition law can be adapted to address sector-specific issues.

Competition Policy and Public Interest Considerations

Competition law enforcement is not only about promoting efficiency and consumer welfare but also involves considerations of public interest and broader societal objectives. Students can delve into the interface between competition law and public policy, examining cases where competition enforcement has been influenced by non-economic concerns, such as environmental protection, access to essential services, or cultural preservation.

The realm of competition law research offers a vast landscape of compelling topics that reflect the intricacies of market regulation, antitrust enforcement, and consumer protection. As law students engage in exploring these research paper topics, they embark on a journey to understand the complexities and significance of competition law in shaping the competitive dynamics of modern economies. Through their scholarly pursuits, students not only contribute to the academic discourse but also play a crucial role in advancing the field of competition law and its impact on society and economic welfare.

How to Choose Competition Law Research Paper Topics

Selecting a research paper topic is a crucial step in the academic journey of law students. The field of competition law offers a diverse range of fascinating and relevant issues for exploration, making the process of choosing the right research topic both exciting and challenging. This section provides valuable insights and practical tips to help students navigate the process of selecting compelling and well-defined competition law research paper topics that align with their interests, expertise, and academic goals.

  • Identify Your Area of Interest : Begin by identifying your area of interest within the broad scope of competition law. Are you intrigued by antitrust enforcement in the digital economy, mergers and acquisitions, or the economic implications of market dominance? By narrowing down your interests, you can focus on specific topics that resonate with your passion for the subject.
  • Conduct Preliminary Research : Before finalizing your research topic, conduct preliminary research to familiarize yourself with recent developments and emerging trends in competition law. Stay updated with landmark cases, policy changes, and academic publications in the field. This background research will help you identify gaps in the existing literature and potential areas for further exploration.
  • Define Your Research Objectives : Clearly define your research objectives and the specific questions you aim to answer in your paper. Are you seeking to analyze the effectiveness of certain competition law regulations, explore the impact of market consolidation, or evaluate the role of competition enforcement in specific industries? Having well-defined research objectives will guide your selection of a focused and relevant topic.
  • Analyze the Legal Framework : Competition law operates within a legal framework that varies across jurisdictions. If you are interested in conducting a comparative analysis, choose a topic that allows for a meaningful comparison of competition laws in different countries. Understanding the legal context is essential for framing your research question and methodology.
  • Consider Practical Implications : Assess the practical implications of your chosen research topic. How does your research contribute to the ongoing discourse on competition law? Is there potential for your findings to inform competition policy or impact the enforcement practices of competition authorities? Topics with practical significance can add value to your research and demonstrate its relevance in the real world.
  • Consult with Faculty and Peers : Engage in discussions with your faculty members and peers to seek their input and feedback on potential research topics. Collaborating with others can provide new perspectives, help refine your ideas, and ensure that your research aligns with academic standards and expectations.
  • Access to Data and Resources : Consider the availability of data and resources relevant to your research topic. Access to comprehensive data and credible sources can significantly enhance the quality and depth of your research. Ensure that you have access to the necessary legal texts, court decisions, economic data, and academic literature to support your analysis.
  • Timeliness and Relevance : Choose a research topic that is timely and relevant to the current state of competition law. Topics that address emerging issues, recent court decisions, or changes in regulatory approaches can attract greater interest from readers and contribute to ongoing debates in the field.
  • Originality and Contribution : Strive for originality in your research topic and aim to make a unique contribution to the field of competition law. Avoid topics that have been extensively covered or lack novelty. Consider how your research can fill gaps in existing literature or offer fresh perspectives on well-known issues.
  • Stay Open to Exploration : Finally, remain open to exploring new ideas and adjusting your research focus as you delve deeper into the literature. As you progress in your research journey, new insights may lead you to refine your research question or explore related areas that enrich your paper.

Selecting the right competition law research paper topic is a critical step in producing a compelling and impactful academic work. By identifying your interests, conducting thorough research, defining your objectives, and considering practical implications, you can narrow down your choices and choose a topic that aligns with your academic goals and contributes meaningfully to the field of competition law. Remember to seek guidance from faculty and peers, access credible resources, and stay open to exploration as you embark on your research journey.

How to Write a Competition Law Research Paper

Writing a competition law research paper requires a systematic approach that combines legal analysis, economic insights, and critical thinking. As law students delve into the complexities of competition law, they must effectively communicate their findings and arguments in a well-structured and coherent manner. This section provides valuable guidance on how to write a compelling competition law research paper, from planning and conducting research to structuring the paper and presenting the analysis effectively.

  • Define Your Research Question : At the outset, clearly define your research question or thesis statement. Your research question should be specific, focused, and aligned with the objectives of your study. It serves as the guiding compass throughout the writing process and ensures that your paper remains cohesive and on track.
  • Conduct Thorough Research : Competition law research papers require a comprehensive examination of legal texts, court decisions, academic literature, and economic data. Conduct thorough research using authoritative sources to gather relevant information, legal precedents, and empirical evidence to support your arguments.
  • Create an Outline : Before diving into writing, create a detailed outline that outlines the structure of your paper. An outline helps organize your thoughts, provides a logical flow to your arguments, and ensures that you cover all essential aspects of your research.
  • Introduction : The introduction should provide context for your research topic, present the research question, and outline the scope and objectives of your paper. Engage your readers with a compelling opening and highlight the significance of your research in the context of competition law.
  • Literature Review : Conduct a thorough literature review to situate your research within the existing body of scholarship on competition law. Identify key theories, legal principles, and economic concepts that inform your research and highlight any gaps in the literature that your paper aims to address.
  • Legal Analysis : Present a detailed legal analysis of the relevant competition law principles, statutes, and court decisions that are central to your research question. Analyze how these legal frameworks apply to the specific issues or cases you are examining. Use clear and precise legal language while supporting your analysis with authoritative sources.
  • Economic Analysis : If your research involves economic aspects, provide an economic analysis that complements your legal analysis. Integrate economic concepts, such as market power, consumer welfare, and efficiency, into your arguments. Use empirical data, economic models, and economic theory to support your findings.
  • Case Studies : Consider incorporating case studies or real-world examples to illustrate your arguments and demonstrate how competition law principles are applied in practice. Case studies provide valuable insights and strengthen the practical relevance of your research.
  • Antitrust Policy Implications : Discuss the policy implications of your research findings. Consider how your analysis informs antitrust policy, enforcement practices, and potential legislative reforms. Offer practical recommendations for policymakers and competition authorities based on your research.
  • Conclusion : In the conclusion, restate your research question and summarize the main findings of your paper. Emphasize the significance of your research and its contribution to the field of competition law. Discuss any limitations of your study and propose areas for further research.
  • Citations and References : Ensure that you use proper citations and references throughout your paper to acknowledge the sources of your information and ideas. Follow the appropriate citation style, such as APA, MLA, or Chicago, as required by your academic institution.
  • Review and Revise : Writing a competition law research paper is an iterative process. After completing the first draft, review your paper for clarity, coherence, and consistency. Revise your arguments, strengthen your analysis, and ensure that your paper adheres to academic standards.
  • Seek Feedback : Seek feedback from professors, mentors, or peers to get valuable insights and suggestions for improvement. Feedback from others can help refine your arguments, clarify your writing, and enhance the overall quality of your research paper.

Writing a competition law research paper requires a rigorous approach that integrates legal analysis, economic insights, and scholarly research. By defining a clear research question, conducting thorough research, and structuring your paper effectively, you can craft a compelling and impactful research paper that contributes to the vibrant field of competition law. Through careful writing and presentation of your analysis, you can convey your expertise, critical thinking, and understanding of complex legal issues to your readers.

iResearchNet’s Custom Research Paper Writing Services

At iResearchNet, we understand the challenges that law students face when tasked with writing a competition law research paper. The field of competition law is dynamic and complex, requiring a deep understanding of legal principles, economic theories, and real-world applications. We recognize the importance of producing high-quality research papers that not only meet academic standards but also contribute to the advancement of competition law knowledge. To support students in their academic journey, we offer custom competition law research paper writing services that cater to their unique needs and requirements.

  • Expert Degree-Holding Writers : At iResearchNet, we pride ourselves on having a team of expert writers who possess advanced degrees in law and related fields. Our writers are well-versed in competition law and have a keen understanding of legal principles and economic concepts. With their expertise, they can deliver comprehensive and well-researched papers that meet the highest academic standards.
  • Custom Written Works : We believe in providing personalized solutions to our clients. Each competition law research paper is custom written based on the specific requirements and instructions provided by the student. Our writers conduct thorough research, analyze legal and economic aspects, and craft original papers that address the unique research questions and objectives of each client.
  • In-Depth Research : Competition law research papers require in-depth research and analysis. Our writers have access to extensive academic databases, legal texts, court decisions, and economic data, enabling them to gather credible and relevant information for each paper. We ensure that our research papers are comprehensive, well-supported, and up-to-date.
  • Custom Formatting : Academic formatting is a crucial aspect of research papers. Our writers are proficient in various citation styles, including APA, MLA, Chicago/Turabian, and Harvard. They meticulously adhere to the specified formatting guidelines, ensuring that each paper is presented professionally and in accordance with the academic requirements.
  • Top Quality : At iResearchNet, we prioritize quality above all else. Our dedicated quality assurance team reviews each research paper to ensure accuracy, coherence, and adherence to the client’s instructions. We aim to deliver research papers that demonstrate thorough analysis, critical thinking, and a deep understanding of competition law.
  • Customized Solutions : We understand that each competition law research paper is unique, requiring individualized attention and focus. Our writers work closely with clients to understand their research objectives, preferences, and specific areas of interest. This collaborative approach allows us to deliver customized solutions that align with each student’s academic goals.
  • Flexible Pricing : We offer competitive and transparent pricing for our custom competition law research paper writing services. Our pricing model is designed to accommodate students with varying budget constraints. We believe in providing value for money by offering high-quality research papers at affordable rates.
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Don’t even study it: Geoengineering research hits societal roadblocks

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  • As climate change accelerates, some scientists are calling for more field research into solar geoengineering concepts. However, these ideas are running into opposition from other researchers, some governments and the public.
  • A series of recent setbacks has put solar geoengineering research on the back foot, attempting to figure out a way to navigate the opposition.
  • Proponents of field research say it would help humanity better understand the potential and problems with solar geoengineering, while opponents argue that there are too many risks and it could take our eye off the ball: cutting carbon emissions.
  • The debate has spilled into the international arena, pitting nations that support greater research against those that would like to see a solar geoengineering non-use agreement.

This is Part Two of a two-part story. Find Part One here.

In April, researchers from the University of Washington sprayed sea salt particles into the air off the California coast in the nation’s first field test of this solar geoengineering concept.

The idea: When certain types of aerosol particles, whether natural or synthetic pollutants, enter clouds, they cause them to brighten. Brighter clouds reflect more sunlight away from Earth, leading to localized cooling. Put into practice on a large scale, solar engineering could potentially offset rapidly worsening climate change impacts.

The experiment was tiny: The team would spray sea salts for short periods each day for four months from the deck of the USS Hornet, a decommissioned aircraft carrier docked in Alameda, California, to understand how the particles moved in the air.

But public blowback was huge: Within two months of the experiment’s start, local officials voted unanimously to halt it, citing the project’s lack of transparency, despite city consultants determining that the research wouldn’t impact wildlife or human health.

“This is the pitchfork brigades run amok,” says Wake Smith, a climate researcher who lectures at Yale University. “This involved spraying seawater into the air over the sea, mimicking the action of waves. It’s hard to conceive a more harmless experiment. The Luddites are back.”

A beach along the Californian coastline.

To study, or not to study

The public outcry in Alameda is indicative of several recent battles lost by scientists trying to research solar geoengineering through small-scale field experiments.

Meanwhile, a growing number of scientists are urgently calling for research and funding into geoengineering. They’re not arguing for deployment, but point to escalating emissions and worsening climate change impacts, as a key reason to consider other tools, however controversial , to combat the problem.

But not all scientists agree. Some criticize geoengineering as a dangerous distraction, arguing it takes the onus off the vital need for drastic emissions cuts, while putting humanity on a precarious path, risking dependence on a totally untried technology with potentially unforeseen results.

The debate has not only hit individual experiments and projects, but even international meetings, such as at the February 2024 gathering of the United Nations Environment Assembly, where Switzerland, backed by the U.S., Saudi Arabia, Canada and Japan, tussled with African nations in an attempt to move forward on an expert panel to assess the benefits and risks of solar geoengineering. Switzerland did not prevail.

“I think the best way forward is to just take this option off the table, to stop these debates, and to support a non-use agreement on solar geoengineering,” says Frank Biermann, a social science researcher at the Global Sustainability Governance at Utrecht University in the Netherlands.

Paul Goddard doesn’t agree. A researcher studying how solar geoengineering could slow melting in Antarctica, Goddard says he doesn’t understand the opposition, as it “is potentially removing a great tool in the toolbox against climate change.”

As a result of this heated dispute, those wanting more field research to better understand solar geoengineering options are running into roadblocks and issues of societal acceptance. But at the same time, a shift in the other direction is happening, with a rising number of researchers and policymakers starting to take solar geoengineering seriously.

Penguins on ice in Antarctica.

Is solar geoengineering becoming less taboo?

Before he started researching geoengineering, Goddard says he thought there was “no way in heck” we should deploy such extreme technology. But now that he’s steeped himself in the science of its potential benefits, he’s not only changed his tune, but seen changes of heart among other scientists.

“I think it’s becoming less taboo [because] people are looking for methods that can help with the climate crisis,” Goddard says.

Specifically, he’s supportive of researching a solar geoengineering technique known as stratospheric aerosol injection (SAI), which would release small particulates, likely sulfates, from planes into the stratosphere at about 20,000 meters (66,000 feet) to block out a tiny percentage of sunlight and slow the heating of the planet to some degree.

Among researchers and policymakers, SAI is arguably the most popular of numerous geoengineering schemes due to the belief it would work — it mimics the globally cooling effect of large volcanic eruptions — and its relatively low cost.

David Keith, a professor in the Department of the Geophysical Sciences at the University of Chicago, who’s worked in the field far longer than most, definitely sees a geoengineering sea change coming. “There was … extremely little work on solar geoengineering in the ’90s and the early part of the 2000s. I was one of the few people doing anything. Not the only one, but one of the few,” he says, adding that in the scientific community back then, researchers warned him that it would “hurt your career.”

“That’s definitely changed,” Keith says. “The last few years, there’s been much more attention. There’s been high-level policy attention.”

U.S. government interest is arguably where the biggest shift is occurring. In 2022, the Biden administration called for a five-year research plan into SAI.

It’s also recently come to light that the Environmental Defense Fund, a U.S.-based NGO, is planning to study SAI. The group, one of the biggest environmental NGOs in the nation, brought in $255 million in 2023 . Likewise, the Union of Concerned Scientists and the Natural Resources Defense Council have come out in favor of field research.

Research backers now include wealthy proponents like Bill Gates and Mike Schroepfer , formerly of Meta. As with the scientists, these funders are talking only about research at this point, not deployment.

There’s a downside to these proponents, Biermann says. The extensive support coming mostly from the U.S. government, and U.S. entrepreneurs, financiers and NGOs, has caused those in other parts of the world to be wary of equity issues surrounding geoengineering. It “makes many people quite suspicious.”

As geoengineering becomes less taboo in some circles, opposition rises elsewhere. Biermann, for example, is one of the initiators of an open letter signed by 500 experts and endorsed by 2,000 civil society groups calling for a global geoengineering non-use agreement.

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Field research permissions

In March, Harvard University shut down a solar geoengineering experiment known as the Stratospheric Controlled Perturbation Experiment, or SCoPEx. A brainchild of David Keith (now with the University of Chicago) and Frank Keutsch, the experiment never got off the ground. It would have used high-altitude balloons to deliver small particles into the stratosphere, then measure how well they reflected sunlight.

SCoPEx ran into trouble in 2021 when the Saami Indigenous group discovered that the project was planning to use balloons above their traditional lands in Sweden. After a protest, the Saami were able to get the planned experiment canceled.

“Harvard proposed an utterly exquisite governance structure sitting atop a teency-weency science experiment,” Smith says. “In the end, the governance superstructure crushed the pitiful little experiment.”

Keith notes that Harvard only canceled this particular experiment; the university hasn’t said it would stop geoengineering research altogether. However, what happened there is emblematic of how difficult conducing a geoengineering field experiment has become.

The non-use agreement, supported by Biermann and others, doesn’t propose a total ban on solar geoengineering research. But if implemented, it would “ban outdoor experiments” and disallow the use of public funds for geoengineering research. The signers are also against any geoengineering technology development, patenting, or the qualification of any geoengineering project for carbon offsetting.

“We believe that outdoor experimentation doesn’t add much to general knowledge, but leads to [geoengineering] technology development,” Biermann says, adding this is what the signers oppose.

“It’s really a ‘non-research agreement,’” Smith counters. “I don’t see how one can reasonably say, ‘We don’t know much about it, but we know it would be bad.’ We can only know that after doing the research.”

Biermann, though, says supporters of the non-use agreement are not “Luddites … We are scientists.” However, he adds, “Our societies [get to] decide that certain activities and technologies should be banned … So far, chemical weapons, biological weapons, human cloning, Antarctic mining, deep seabed mining, antipersonnel landmines, and a couple of other activities are not allowed. That’s for a good reason. You can’t sit in the United States of America and have a chemical weapons factory in your backyard.”

Those arguing in support of expanded field research say it will help the world better understand both the potential and drawbacks of geoengineering. They also point out that a research ban won’t prevent a nation from deploying the technology. Keith notes that when it comes to SAI, a nation could deploy a major project without doing further research, dubbing this “One of the good or bad, terrifying things about [SAI].”

There are no global policies in place to legally prevent such a deployment. A country, or even a large corporation, without further study, could start sending planes with aerosol payloads into the stratosphere tomorrow and hope for the best. But, of course, researchers argue, it would be far better to have an extensive understanding of the technology before launching it at scale.

Shadow Image of a Plane Flying during Sunset

Debate erupts in the international arena

A heated geoengineering discussion has arisen internationally over going forward with geoengineering research, largely between nations of the Global North (mostly supporting it) and the Global South (largely opposing it).

Last year, at the African Ministerial Conference on the Environment, African nations signed on to a text calling for “the need for a global governance mechanism for non-use of solar radiation management.” The call was seen as a victory for those wanting to slow or stop field research and curb consideration of SAI.

Then, in February, at the most recent United Nations Environment Assembly, Switzerland proposed the creation of an expert group to look into SAI. The motion was fiercely fought by African countries that instead called for an SAI “non-use agreement,” preventing future utilization of the technology, according to Climate Home News . A letter by the African delegation complained of “efforts to use Africa to justify use of this dangerous technology.”

In the end, neither group triumphed. Switzerland tabled its proposal, and a non-use agreement made no headway. The meeting ended in a stalemate, enforcing the status quo, which allows SAI research, but not large-scale deployment.

“What has happened so far is mixed comments from climate negotiators,” Keith says. “My hope is that these calls trigger more robust debates rooted in the Global South.”

But Biermann says the writing is on the wall: “Researchers make the argument that they do [geoengineering work] for the Global South and for the ‘global poor’ — but those who make these arguments should think very carefully about the fact that African governments don’t want solar geoengineering.”

Of course, the Global South isn’t a monolith. For example, a poll of students in Japan, Australia, the Philippines and India on their geoengineering views found that a higher percentage of those from the Philippines and India were open to geoengineering. Notably, students in those two countries also said they believe outcomes from climate change will be worse and more likely to affect them personally.

“We feel like it’s a moral responsibility and an ethical responsibility to at least look at every possible option, not necessarily to do anything yet, but if we don’t even look at them, then we are tying our hands behind our back,” says Brad Ack, the CEO of Ocean Visions, a nonprofit organization currently investigating and evaluating geoengineering ideas.

Graph showing the baseline radiative forcing under three different Representative Concentration Pathway scenarios

A future without a choice?

Geoengineering research, whether or not to do it, has become a political fight, one that likely portends far larger political battles down the road over deployment.

“It’s a political struggle of course, and there are people who have a lot of money; there’s a well-funded pro-SRM [solar radiation management] lobbying community in the United States and they’re doing their thing. They’re lobbying, they have money, we don’t have money,” Biermann says. “It’s a bit like David and Goliath.”

But true to the David and Goliath story, it often seems like David is winning. In case after case, the side against geoengineering has halted field experiments. Biermann says one of the problems with geoengineering research is that it often excludes social and governance issues from the equation. Those supporting geoengineering field research “are presumably natural scientists, so they have not been much involved in thinking about the political economy, the political ecology, and the governance challenges that come with [this new technology],” he says.

For his part, Biermann says he doesn’t believe any of the world’s current institutions would be up to deploying geoengineering in a just way.

“It will be hard for SAI to move forward until there are some full-throated advocates calling for it to countervail the full-throated opponents,” Smith says. “There is only so far that research can go without substantial public support.”

But Smith and others who want more field research say eventually the terrors of climate change will make this question moot. It’s hard to imagine a non-use agreement stopping a nation from moving forward if millions of its citizens are uprooted or dying from extreme heat.

“Those disputing [solar geoengineering] do overplay risks, but more importantly, they underplay [the] risks of runaway climate change in the absence of solar [geoengineering],” Smith says. “They are implicitly comparing today’s climate to engineered climate, and saying, ‘I want today’s climate, not franken-climate!’ Well, so do I, but that won’t be the choice we will confront.”

Banner image: Put into practice on a large scale, solar engineering could potentially offset rapidly worsening climate change impacts — but there are a variety of potential risks. Image via Pexels (Public domain).

Related audio from Mongabay’s podcast: Author Elizabeth Kolbert discusses the pitfalls of geoengineering and other proposed solutions to ecological challenges, listen here:

Biermann, F., & Gupta, A. (2024). A paradigm shift? African countries call for the non-use of solar geoengineering at UN Environment Assembly. PLOS Climate , 3 (5), e0000413. doi: 10.1371/journal.pclm.0000413

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To wipe or to wash? The use of toilet papers | Consumed

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Toilet paper: Environmentally impactful, but alternatives are rolling out

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Consumed: Unmasking the environmental impact of tires

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Getting the bread: What’s the environmental impact of wheat?

Consumed traces the life cycle of a variety of common consumer products from their origins, across supply chains, and waste streams. The circular economy is an attempt to lessen the pace and impact of consumption through efforts to reduce demand for raw materials by recycling wastes, improve the reusability/durability of products to limit pollution, and […]

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Apparel Industry Leaks Millions of Tons of Plastic Into Environment Each Year, Study Finds

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A new study finds that waste from the global apparel industry is leaking millions of tons of plastic into the environment each year – an overlooked pollution source which may be getting worse over time.

The findings are detailed in a recent study from North Carolina State University researchers, which found that global apparel consumption resulted in over 20 million tons of plastic waste in 2019. Around 40% of that waste may have been improperly managed and become environmental pollution, a process known as “plastic leakage.”

Textile waste was divided between two sources; clothing made from synthetic materials like polyester, nylon and acrylic, and clothing made from cotton and other natural fibers. Researchers looked at plastic waste generated across an apparel product’s “value chain,” which refers to the entire lifecycle of a product – including, for example, not only the piece of apparel itself, but the plastics used to wrap it.

“We analyzed data on imports, exports and apparel production in countries all over the world,” said Richard Venditti, professor of paper science and engineering at NC State and co-author of the study. “Then we compared that to existing global information on different stages of the apparel value chain to estimate how much plastic leaks into the environment at each of those points.

“Much of the plastic waste that leaks into the environment comes from clothes that are thrown away, especially synthetic apparel,” Venditti said. “There is also waste from manufacturing, packaging and even from tire abrasion during transport, as well as microplastics which get pulled into the water when we wash our clothes.”

Researchers found that synthetic apparel was by far the largest source of plastic waste. The synthetic value chain accounted for 18 million tons of waste in 2019, making up 89% of all plastic waste from the global apparel industry that year. Of that, researchers estimated that around 8.3 million tons may have leaked into the environment.

Meanwhile, cotton clothing accounted for 1.9 million tons of plastic waste, with the final 0.31 million tons coming from fibers other than synthetic textiles or cotton. As opposed to the end-of-life plastic waste created by discarded synthetic apparel, plastic waste from cotton and other fibers came almost entirely from the plastic used in packaging.

Researchers found that where apparel was sold is not necessarily where plastic waste leaks into the environment. For apparel originally sold in high-income countries like the United States, Japan and many others, most of the resulting pollution happened in lower-income countries where these pieces of clothing might be sold in the secondary market.

This finding points to a major concern with how people in higher-income countries consume apparel.

“What we’re seeing is that in countries like the United States, we have a ‘fast fashion’ culture where we buy a lot of clothes and don’t keep them for very long,” Venditti said. “When we discard those clothes, they either go into landfills or, more often, they end up in thrift stores. Some of the clothes that go to these stores are sold in the U.S., but often they end up going to other countries that do not have waste management systems robust enough to handle that kind of volume. That is where you end up with a large amount of plastic leaking into the environment.”

The study concludes that significant changes in the apparel sector need to be made to move the industry toward a more circular framework, where materials are recycled and do not become waste. The study also recommends increasing the use of renewable, non-synthetic textiles.

The paper, “The global apparel industry is a significant yet overlooked source of plastic leakage” appears in the open-access journal Nature Communications . The paper’s corresponding author is Anna Kounina of Quantis. Co-authors include Jesse Daystar, Sophie Chalumeau, Jon Devine, Roland Geyer, Steven T. Pires, Shreya Uday Sonar and Julien Boucher.

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Research Paper Competition

Team Research Papers are allowed again this year, with up to three members on the team. A research paper consists of student or team Investigative Research, which is the written presentation of your investigation and experimentation. Research papers are only allowed for students in 6th-12th grade competing in the middle school/senior high fair. Scientific thought and procedures will receive major credit in the judging. All submitted Southern MN Regional Science & Engineering Fair research papers are read prior to the regional fair by Minnesota State University, Mankato Faculty. The top papers will then compete at the Regional Science Fair with an oral presentation.

Southern MN Regional Science and Engineering Fair follows the same rules and guidelines as The National Junior Science and Humanities Symposium.

Junior Science and Humanities Symposium Core Rules of Competition

Length of Paper

The paper should be a minimum of 5-6 pages and a maximum of 20 pages, including appendices and references. The cover page does NOT count towards the 20 page maximum. Please use: Times or Times New Roman for your font, single spaced and keyed in 10 or 12 point font, with 1-inch margins.

The cover page states the student's name, school name and address, title of the research, grade in school, name of the advisor and category of the research. Make your title concise but also descriptive. Your title should indicate the nature of your research, not the entire content. The best titles are usually ten (10) words or less. The cover page is not part of the 20 page maximum.

An abstract of no more than 250 words must be included before the title page.

Papers will be judged solely on this year's work. Be sure that it is clear to the judges what this year's work is.

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Environmental Preferences, Competition, and Firms’ R&D Choices

Working Paper Figure w26921

Firms in automobile-related businesses whose consumers are environmentally focused are more inclined to develop sustainable technologies, particularly in markets defined by higher levels of competition.

C onsumers’ environmental preferences, in conjunction with the level of market competition, affect firms’ decisions to invest in environmentally friendly innovations, according to findings reported in Environmental Preferences and Technological Choices: Is Market Competition Clean or Dirty? (NBER Working Paper 26921 ), a study by Philippe Aghion , Roland Bénabou , Ralf Martin , and Alexandra Roulet .

The researchers hypothesize that consumers care about the environmental footprint of products they buy, and that firms consider these preferences when choosing how much to invest in research and development on “clean” or “dirty” innovations. They then use data on patents, consumers’ environmental preferences, and product-competition levels in the automotive industry for over 8,500 firms in 42 countries between 1998 and 2012 to evaluate how companies respond to changing consumer sentiments.

They find that firms catering to more environmentally focused consumers, measured as a weighted average of support for pro-environment positions in the markets in which the firms sell their products, appear to reallocate their resources toward developing sustainable technologies. The share of dirty-technology patents declines for these firms. They also find that the relationship between consumer preferences and firms’ investments in clean technology is stronger in markets defined by higher levels of competition.

The researchers note that the link between competition and green investment is a priori ambiguous. High levels of competition could result in less environmentally friendly practices if firms attempt to keep prices low, but they could also incentivize companies to invest in green technology as a means of differentiating their products. Both effects may be present; the researchers find that the latter effect prevails.

For firms exposed to more sustainability minded consumers, the growth rate of clean patents is 14 percent higher than the growth rate for dirty patents; that difference jumps to 17 percent in more competitive markets. To put these numbers in context, the researchers compare the effects to the impact of a significant hike in fuel prices. They find that realistic increases in environmentally friendly attitudes and product competition — shifts on par with historical trends — would have the same impact on firms’ investments in clean technology as a 40 percent jump in fuel prices.

The findings suggest that consumer preferences for different types of products can have a meaningful impact on firms’ R&D decisions under some conditions. While each individual consumer’s choice to “buy green” may not have a large effect on pollution, an environmentally focused consumer class can alter firms’ willingness to invest in R&D directed toward environmentally friendly products, particularly in competitive markets.

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Does public environmental concern cause pollution transfer? Evidence from Chinese firms' off-site investments

  • Wang, Zhiwei
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  • Zhang, Xianfeng

The power of public environmental concern cannot be ignored. It is vital in promoting environmental legislation, corporate social responsibility, and sustainable development. Existing studies have discussed the positive governance effects of public environmental concern on environmental quality but have neglected the issue of environmental inequality due to pollution transfer resulting from differences in public environmental concern. We used the data from the off-site investment of Chinese heavy polluting firms to reveal the impact of public environmental concern on pollution transfer. Our research revealed that (1) Public environmental concern causes polluting firms to transfer out, thus generating the pollution transfer phenomenon. (2) Public environmental concern can cause pollution transfer through increased environmental penalties. From the perspective of external environmental incentives, market competition, market potential, and government environmental concern strengthen the positive influence of public environmental concern on pollution transfer. In terms of the intrinsic motivation of firms, risk-taking capacity, green innovation ability, and asset-stranding risk weaken the positive influence of public environmental concern on pollution transfer. (3) The public environmental concern is also characterized by "grasping the large and letting go of the small". Public environmental concern remarkably induces pollution transfer when firms' environmental awareness is low and local government officials' political incentives are high. These findings help policymakers to place greater emphasis on the power of public concern. Moreover, they can further improve the pluralistic governance structure of environmental regulation.

  • Public environmental concern;
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The power of competition: Effects of social motivation on attention, sustained physical effort, and learning

Competition has often been implicated as a means to improve effort-based learning and attention. Two experiments examined the effects of competition on effort and memory. In Experiment 1, participants completed a physical effort task in which they were rewarded for winning an overall percentage, or for winning a competition they believed was against another player. In Experiment 2, participants completed a memory task in which they were rewarded for remembering an overall percentage of shapes, or more shapes than a “competitor.” We found that, in the physical effort task, participants demonstrated faster reaction times (RTs)—a previous indicator of increased attention—in the competitive environment. Moreover, individual differences predicted the salience of competition’s effect. Furthermore, male participants showed faster RTs and greater sustained effort as a result of a competitive environment, suggesting that males may be more affected by competition in physical effort tasks. However, in Experiment 2, participants remembered fewer shapes when competing, and later recalled less of these shapes during a post-test, suggesting that competition was harmful in our memory task. The different results from these two experiments suggest that competition can improve attention in a physical effort task, yet caution the use of competition in memory tasks.

Introduction

Social motivation has been defined as a drive for a particular goal based on a social influence ( Hogg and Abrams, 1990 ). Although research has examined correlative relationships between competition and learning ( Dweck and Leggett, 1988 ; Zimmerman, 1989 ; Oldfather and Dahl, 1994 ; Wentzel, 1999 ), few studies have examined how the presence of a competitor directly influences motivation, effort, and memory. In Burguillo (2010) found that implementing competition-based games in a classroom improved course performance. One might therefore assume that competition may directly improve some aspect of the memory process; yet, it is unclear whether competition directly affects attention, effort, or memory.

Recent research has shown that the presence of a competitor can increase physical effort over both short ( Le Bouc and Pessiglione, 2013 ) and long durations ( Kilduff, 2014 ). Competitiveness has also been shown to increase physical motivation, such as motivation to practice a sport ( Frederick-Recascino and Schuster-Smith, 2003 ). A better understanding of how competition improves performance may help shed light on how to improve cognitive performance (e.g., memory in the classroom). For example, if the presence of a competitor affected attention, we may expect to see an effect at encoding, since attention is one of many necessary components for accurate encoding ( Craik et al., 1996 ; Anderson et al., 2000 ; Fernandes and Moscovitch, 2000 ). However, if the presence of a competitor is affecting memory retention, we may expect a difference regarding long-term memory, but not short-term memory. Furthermore, competition could affect components of memory without affecting attention at all.

There may also be individual differences in the magnitude and direction of competition’s effect on performance. Individual differences exist in a variety of domains, especially those involving motivation ( Duckworth et al., 2007 ; Maddi et al., 2012 ). For example, previous research has found that individual differences in normative goals—i.e., wanting to perform better than others ( Grant and Dweck, 2003 )—have been shown to predict performance on ostensibly difficult tasks ( Swanson and Tricomi, 2014 ), suggesting that individual differences may be at play when examining competition’s effect on effort, attention, and memory. Also, competition may affect elements of effort and elements of memory in different ways. For example, if competition does indeed have an effect on attention, competition could have a varying effect depending on attentional load. In accordance with the Yerkes and Dodson (1908) law, one might expect that competition may improve performance in situations requiring a low attention load, but not in learning environments requiring high attentional load.

Additionally, research has yet to examine the potential social stigma associated with competition, or in other words, whether being competitive is viewed as a negative personality trait. Moreover, previous research regarding illusory superiority has found that individuals tend to rate themselves as having significantly more positive personality traits than the rest of the population, including traits such as trustworthiness, honesty, good-humor, and patience ( Hoorens, 1995 ). Furthermore, previous research has found that the majority of individuals rate themselves as significantly less likely to act selfishly than the rest of the general population ( Pronin et al., 2002 ), as well as drive better ( Horswill et al., 2004 ) than the rest of the general population. Since individuals tend to have unrealistically positive reflections of themselves, participants may tend to rate themselves as having less competitive behaviors—if competitive behavior is viewed as a socially negative trait—in order to continue to view themselves in a positively-skewed light.

Experiment 1 examined the effect of social motivation on a physical effort task. Experiment 2 examined the effect that the presence of a competitor can have on working memory and long-term memory. We hoped to gain insight regarding competition’s effect on effort, attention, and memory, as well as individual differences in competitive performance and the likely possibility of a social desirability bias regarding competitive habits.

Experiment 1

Experiment 1 examined whether competition affects physical effort. Specifically, we wondered if competition would affect sustained effort on an isolated, simple physical task, or if competition affects some other mechanism necessary for successful performance regarding physical effort, such as attentional control. Le Bouc and Pessiglione (2013) found that, when participants believed they were competing, they increased physical effort, suggesting that social factors often increase motivation. However, research has yet to parse the mechanisms at play in social motivation and physical effort. For example, does competition increase effort at the attentional level, or does the presence of a competitor increase sustained effort over time? Previous research has suggested that reaction times (RTs) are indicative of an individual’s level of selective attention ( Eason et al., 1969 ; Stuss et al., 1989 ; Prinzmetal et al., 2005 ), while sustained press rates have been regularly implicated as a means for measuring sustained effort over time ( Maatsch et al., 1954 ; Treadway et al., 2009 ). We also wanted to examine the possibility of individual differences in physical effort in the presence of a competitor, and the possibility of gender differences in the saliency of social motivation.

Participants

One hundred and twenty-nine undergraduates from Rutgers University’s Newark campus participated in the study, which was approved by the Rutgers IRB. Participants received course credit for their participation, and were told upon arriving they would be eligible to earn $1–3 in bonus money in addition to course credit. Participants entered the lab and were introduced to a fellow “participant” they would later be interacting with—a same or opposite sex confederate. After obtaining written informed consent from the participant, the experimenter brought the confederate into a testing room and waited for about 5 min, the expected time for the confederate to complete the practice session of the task. Participants then completed a practice version of the task, the actual task, and a battery of surveys, including demographic information. After completing the surveys, participants were probed about whether or not they believed they were actually competing against another individual and if they believed the confederate was a real participant. Then, participants were debriefed about the confederate and real purpose of the task. Seven participants were removed for not believing the manipulation, and two participants were removed for failing to complete the task in its entirety. Analyses were thus performed on the remaining 120 participants.

Effort Bar Task

Participants completed an effort bar task in the form of a computerized carnival water gun game. Participants saw a fixation cross with a 3–7 s jitter, then were required to press the “x” key to move the effort bar (in this case, in the form of a “water tube”). If participants pressed the “x” key before the water tube appeared, the jitter reset. Participants were required to press between a randomly generated requirement of 5 and 30 times to fill the effort bar in order to win the trial. Participants had to press at an average rate of 150 ms to fill the tube with water in time to win the round, with an extra 350 ms to account for the expected first press time. This time amount was decided due to the results of a pilot study that found that participants had an average first press of 350 ms and press rate (excluding the first press) of one press per 150 ms. Titrating the task at this rate led to the expectation that participants would win an average of 50% of trials. We analyzed participants’ first press RTs as a measure of their attention to the task ( Eason et al., 1969 ; Stuss et al., 1989 ; Prinzmetal et al., 2005 ), as well as their sustained press rate over the span of the task, which provided us a measure of sustained effort ( Maatsch et al., 1954 ; Treadway et al., 2009 ).

“Self” condition

In the “self” condition, participants were told they were playing against the clock, and that if they could win 2/3 of the games (trials) played in this round, they would be granted $1 in addition to their course credit. There were 100 trials per condition (200 trials total). Participants were given immediate feedback after each trial as to whether they won, and were immediately told at the end of each self and each competition condition if they won the bonus money. Conditions were counterbalanced across participants to prevent order effects.

“Competition” condition

In the competition condition, participants were told they were playing against the other “participant” they met earlier (again, a confederate), and would be granted an additional $1 if they could beat their competitor in more of the games. At the end of each game, they were told whether they or the other player won the game, and were told who won the bonus at the end of each self and each competition condition. If participants won 2/3 of the games in a particular condition, they were granted the bonus. Each participant completed both conditions, and conditions were counterbalanced across participants to account for possible order effects. Task depiction is illustrated in Figure ​ Figure1 1 .

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Experiment 1 task depiction. Participants saw a preparation screen (Slide 1) for 2 s, then a fixation jittered for 1.5–3 s (Slide 2). Participants pressed the x key repeatedly when they saw the effort bar appear; time was varied by the number of required presses (Slide 3). Participants were told if they filled the effort bar in time (Slide 4) and were given feedback regarding their performance (Slide 5).

We administered several surveys to investigate potential individual differences and their relationship to task performance.

Hypercompetitive Attitude Scale (HAS)

The HAS examines individual differences in general hypercompetitive attitude ( Ryckman et al., 1990 ). The HAS asks participants to reflect on habits and traits that may be associated with a competitive personality (e.g., “I can’t stand to lose an argument.”).

Personal Development Competitive Attitude Scale (PDCAS)

The PDCAS examines if individuals regard competition as a means of improving personal development ( Ryckman et al., 1996 ) The PDCAS reflects on preference for situations in which competition may improve their performance (e.g., “I enjoy competition because it gives me a chance to discover my abilities.”).

Marlow-Crowne Social Desirability Scale (SDS)

We included the SDS ( Crowne and Marlowe, 1960 ) to measure possible bias in responding, whether it be because participants have unrealistic representations of their own traits, or because of a desire to please the experimenter. This questionnaire examines the extent to which a subject may positively skew their survey responses to represent themselves in a positive manner, and requires a “true or false” response to items such as “I am always courteous, even to people who are disagreeable.” The SDS has been previously used to detect the tendency of participants to have unrealistically positive representations of their own traits ( Zerbe and Paulhus, 1987 ; Paulhus, 1991 ; DiMenichi and Richmond, 2015 ). Because Ryckman et al. (1990) found that HAS was also correlated with high aggression, we were unsure whether participants would be likely to admit the extent of their competitive natures. Furthermore, research has yet to examine whether or not individuals view competition as a negative personality trait, and a correlation with the HAS and SDS would suggest this.

Main analyses

A within-subjects t -test examined differences between the first-press RTs in the self condition and the first-press RTs in competition condition. A within-subjects t -test also examined differences between the sustained press-rates in the self condition and the sustained press-rates in the competition condition.

Individual differences analyses

Pearson correlations examined the relationship between trait competitive tendencies (HAS and PDCAS), first-press RTs, and sustained press-rates from the competition condition and the self condition. Pearson correlations also examined relationships between survey scores and scores on the SDS in order to examine possible biases in participants’ responding, as well as if competitive habits are viewed as a socially-negative trait. We used a Bonferroni corrected significance threshold of p = 0.017 (0.05/3 scales) and interpreted correlations with p -values between 0.018 and 0.05 with caution.

Gender differences analyses

Between-subjects t -tests examined gender differences in performance and on the survey measures (HAS, PDCAS, and SDS) used in our experiment. Two-way analyses of variance (ANOVAs) also examined the effects of the factors gender and confederate gender on competitive first-press RT (first-press RT in the competition condition minus the first-press RT in the self condition) and competitive press rate (press rate in the competition condition minus the press rate in the self condition). Within-subject t -tests for each group individually also examined differences in performance across conditions (30 participants per group).

Results and Discussion

A paired-samples t -test revealed that participants’ first presses—i.e., immediate RTs on the task—were significantly faster in the competition condition ( M = 339.43 ms, SD = 72.96) than in the self condition [ M = 352.89, SD = 86.84; t (119) = –2.62, p = 0.010, Cohen’s d = 0.24], suggesting that participants demonstrated greater attentional focus on the task when they believed they were competing against another participant (Figure ​ (Figure2). 2 ). There were no other significant findings regarding press rate, score, and condition, suggesting that competition affected attentional focus on the task, but not sustained physical effort over time.

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Results from Experiment 1. Participants’ first press reaction times (RTs) were significantly faster in the competition condition than the self condition. Error bars reflect standard errors of the means. *Significant at p < 0 .05.

Scores on the SDS were significantly negatively correlated with scores on the HAS ( r = –0.367, p < 0.001), suggesting that overt competition may be implicitly viewed as a negative personal quality by most individuals. There was no significant relationship between scores on the SDS and scores on the PDCAS, suggesting that the PDCAS may be immune to participants’ tendencies to paint themselves in a positively-skewed manner. Scores on the PDCAS were significantly correlated with faster RTs of the first press in competition condition ( r = –0.239, p = 0.008), suggesting that individuals who view competition as a means for personal development may have greater attentional focus in the presence of a competitor. However, there was no significant relationship between scores on the PDCAS and first press RT in the self condition, which is consistent with the idea that competitive personality traits should not affect performance in an environment with no competition.

Men also scored significantly higher on the PDCAS ( M = 51.59, SD = 9.65) than women [ M = 46.62, SD = 11.68; t (118) = 2.53, p = 0.012, Cohen’s d = 0.46], suggesting that men may view competition as a greater motivation for improving skills pertaining to personal development. Additionally, male participants demonstrated significantly faster first press RTs in the competition condition than female participants’ first press RTs in the competition condition [male M = 323.23, SD = 71.44; female M = 335.09, SD = 71.53; t (118) = –2.44, p = 0.016, Cohen’s d = 0.17] Furthermore, male participants also had faster sustained press rates in the competition condition ( M = 128.36, SD = 16.01) when compared to females participants’ press rates in the competition condition [ M = 138.26, SD = 11.98; t (118) = –3.84, p < 0.001, Cohen’s d = 0.70]. However, there were no significant gender differences involving first press RT in the self condition or press rate in the self condition. Furthermore, when examining male participants’ sustained press rate performance, there was no significant difference between press rate in the competition and self conditions. See Figure ​ Figure3 3 for gender difference results across conditions. A two-way ANOVA with the factors participant gender and confederate gender did not reveal a significant main effect of confederate gender [ F (3) = 0.48, p = 0.695] or interaction of gender by confederate gender [ F (42) = 0.63, p = 0.825 Cohen’s d = 0.08] on competitive first-press RTs. Also, a two-way ANOVA with the factors participant gender and confederate gender did not reveal a significant main effect of confederate gender [ F (3) = 0.75, p = 0.528] or interaction of gender by confederate gender [ F (42) = 1.25, p = 0.209, Cohen’s d = 0.10] on competitive press rate. Overall, these findings suggest that men were significantly more socially motivated in the presence of another competitor, at least in terms of attention in a physical effort task.

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Gender differences from Experiment 1. Males had significantly faster first press reaction times and significantly faster press rates in the competition condition compared to female’s first press reaction times and press rates in the competition condition. However, there was no significant gender difference in the self condition. Error bars reflect standard errors of the means.

Our findings from Experiment 1 suggest that competition had an effect on participants’ attention to our task. We did not find a significant relationship between competition and sustained physical effort in our task, suggesting that competition may have a more cloudy relationship with physical effort than our task was able to provide. Furthermore, our results suggest that there are predictable individual differences in competition’s influence on attention, although reflection on these individual differences may be vulnerable to a bias of individuals to paint themselves in an overly positive light, whether implicitly or explicitly (e.g., due to task-demand characteristics or the presence of an experimenter). Also, our findings show that men’s attention on a physical effort task may be more influenced by the presence of a competitor than women’s.

Experiment 2

Because Experiment 1 found that competition increased attention, Experiment 2 examined whether the presence of a competitor enhanced working memory as well as memory retention, mechanisms that both rely heavily on attention. Specifically, we examined whether competition would inspire greater performance on a memory task and, if so, what mechanisms are responsible.

One hundred and twenty-four undergraduates from Rutgers University’s Newark campus participated in the study, which was approved by the Rutgers IRB. Participants received course credit for their participation, and were told upon arriving they would be eligible to earn $1–3 in bonus money in addition to course credit. Experiment 2 followed the same laboratory format as Experiment 1: upon entering the lab, participants were introduced to another “participant” they would later be interacting with—a same or opposite sex confederate. After obtaining written informed consent from the participant, the experimenter brought the confederate into a testing room and waited for about 5 min, the expected time for the confederate to complete the practice session of the task. Participants then completed a practice version of the task, the actual task, a surprise recall task, and a battery of surveys, including demographic information. After completing the surveys, participants were probed for task believability and debriefed about the confederate and real purpose of the task. Four participants were removed from the sample for not believing that the confederate was a participant. Analyses were performed on the remaining 120 participants (60 females).

Working Memory Task

Our working memory task was adapted from ( Redick et al., 2012 ). Participants decided if a matrix was symmetrical or not, and then were presented with a line drawing of an abnormal shape, along with a number (1 through 3). See Figure ​ Figure4 4 for task depiction. They were asked to memorize the association between the shape and the number. Novel shapes were taken from Endo et al.’s (2001) Novel Shape database. After three different matrices and shapes were shown, participants were shown a recall screen with the shapes from the trial, and asked to recall the numbers associated with the shapes they were just shown. Each condition contained 12 rounds with 18 novel shapes randomly assigned to each condition, and each round was shown twice because of a later recall task. Each participant completed both conditions, and shapes in the “self” condition were not repeated in the “competition” condition (and vice versa ). Conditions were counterbalanced across participants to prevent order effects, and shapes in each condition were counterbalanced across participants, in case shapes in one condition were somehow more difficult than shapes in another condition.

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Experiment 2 task depiction. (A) Participants were shown a matrix for 2 s (Slide 1) and asked to decide if the shape was symmetrical (Slide 2). Participants were then shown a novel shape paired with a number (1, 2, or 3) for 2 s, and were asked to memorize this association (Slide 3). After three rounds (of Slides 1–3), participants were asked to recall the numbers associated with the shapes. (B) Subjects were given immediate feedback for 6 s regarding their performance on the previous round. In the self condition (left), subjects were informed about how many shapes they recalled correctly. After a 2 s delay, they also saw the number of symmetry errors they made on this trial, and the total percentage of symmetry problems answered correctly throughout the condition (top right corner—subjects were required to answer at least 85% of symmetry problems correctly in order to receive the monetary bonus). In the competition condition (right), subjects were also given feedback about the number of shapes their “opponent” remembered correctly—a randomly generated number from 0 to 3. After a 2 s delay, they were also given feedback about their symmetry performance.

In the self condition, participants were given feedback about their performance directly after the recall screen: they were told how many shapes they recalled correctly out of three, as well as how many symmetry problems they answered correctly. They were also given the running total percentage of correct symmetry problems for the entire condition. Participants viewed feedback for 6 s after each round, and were told that if they could remember a total average of 2/3 shapes across all rounds for this condition, they would be given a $1 bonus in addition to their course credit. They were also told that in order to receive the bonus, they were required to complete the task with a symmetry matrix accuracy of at least 85%. Inclusion of the symmetry task also allowed us to examine if effort on the task varied across conditions, since this section of the task did not have a memory component.

In the competition condition, after each recall screen, participants were given feedback about how many shapes they correctly recalled out of three, as well as feedback about their “competitor’s” performance. Competitor performance was randomly generated out of 3, and averaged out to be 2/3 across the entire condition, making the task goal equivalent across both the self and competition conditions. After a 2 s delay, participants were also given feedback about symmetry matrices errors for the round. This delay was issued in order to present the same amount of information across conditions, therefore making cognitive load on working memory more equal across conditions. Total recall viewing time was 6 s after each round. Participants were told if they could recall more associations than the other participant on the most rounds—as well have a symmetry matrix accuracy of at least 85%—they would get a $1 bonus at the end of the condition. Condition feedback is depicted in Figure ​ Figure1B 1B .

Recall task

In a surprise recall task that followed the working memory task, participants were again asked to recall each number associated with each shape. Shape order was randomized to prevent order effects.

A within-subjects t -test examined differences between the number of shapes remembered in the self condition and the number of shapes remembered in competition condition of the working memory task. A within-subjects t -test also examined whether there were differences in subsequent memory between the two conditions, i.e., whether there were differences between the number of shapes originally learned in the self condition and the number of shapes originally learned in the competition condition that were correctly recalled on the surprise recall posttest. To compare any differences in immediate attention across conditions, a within-subjects t -test examined RT to the first symmetry problem between the two conditions. We also subtracted each participant’s total number of shapes remembered during the self condition of the working memory task from their total number of shapes remembered during the competition condition of the working memory task, and deemed this score each participant’s “competitive performance score.” A positive number would indicate better performance on the competition condition of our task. We also repeated the process for post-test scores. A linear regression examined if competitive performance scores predicted competitive recall scores, in order to examine if recall scores on the post-test were the result of learning during the working memory task. If there was no significant relationship between competitive performance scores and competitive recall scores, we would assume that competition increased effort on our task, but not immediate long-term memory. Self scores were subtracted from competition scores in order to account for general memory ability on the task.

Pearson correlations (Bonferroni corrected for multiple comparisons, α = 0.017) examined the relationship between trait competitive tendencies (HAS and PDCAS) and working memory scores from the competition condition and self condition, as well as recall scores. Pearson correlations also examined relationships between survey scores and scores on the SDS in order to examine possible biases in participants’ responding, as well as if competitive habits are viewed as a socially-negative trait. A partial Pearson correlation also examined relationships between trait competitive tendencies and performance while controlling for scores on the SDS.

Between-subjects t -tests examined gender differences in performance, recall, and on the survey measures (HAS, PDCAS, and SDS) used in our experiment. Two-way ANOVAs also examined the effect of the factors gender and confederate gender on competitive performance and competitive recall scores. Furthermore, within-subject t -tests for each group individually examined differences in performance across conditions (30 participants per group). Partial Pearson correlations controlling for SDS also examined the relationship between trait competitive tendencies (HAS and PDCAS) and working memory scores from the competition condition, self condition, and recall conditions in order to examine if the presence of a same- or opposite-sex confederate is salient enough to override state tendencies.

A paired-samples t -test revealed that participants performed significantly better in the self condition ( M = 28.78, SD = 6.87) than the competition condition [ M = 26.72, SD = 6.24; t (119) = 3.85, p < 0.001, Cohen’s d = 0.31] during the working memory task. There was no significant difference between symmetry error rates across conditions, as well as no significant difference in RT to the first symmetry problem across conditions, suggesting that competition did not affect participants’ expended effort on the task, but specifically affected working memory performance. Furthermore, a paired-samples t -test revealed that participants later recalled more shapes on the post-test learned in the self condition ( M = 10.61, SD = 4.40) than in the competition condition [ M = 8.76, SD = 3.34; t (119) = 4.06, p < 0.001, Cohen’s d = 0.37]. A linear regression revealed that competitive performance scores significantly predicted competitive recall scores [β = 0.25, t (119) = 3.34, p = 0.005], and competitive performance scores also explained a significant proportion of variance in competitive recall post-test scores [ R 2 = 0.09, F (1,118) = 11.15, p = 0.001], suggesting that recall scores on the post-test were the result of learning during the working memory task. If there was not a significant relationship between competitive performance scores and competitive recall scores, we would assume that competition increased effort on our task, but not immediate long-term memory.

A Pearson correlation on our survey data revealed a marginally significantly positive association between scores on the PDCAS and performance in the competition condition ( r = 0.17, p = 0.061), but not in the self condition. Because scores on the SDS were again relatively high in our sample—participants answered an average of 55.25% of questions in a “socially desirable” manner—we conducted a partial correlation that revealed that, when controlling for SDS, PDCAS scores were marginally significantly associated with performance during the competition condition ( r = 0.18, p = 0.048). However, after adjusting for multiple comparisons, this finding was no longer significant.

As predicted, SDS scores were again significantly negatively correlated with scores on the HAS ( r = –0.367, p < 0.001), replicating our findings from Experiment 1 and again suggesting that our participants’ self-reflections of their own competitive habits may be skewed. Since HAS contains questions pertaining to direct competitive tendencies, overt competitiveness may be considered a negative personality trait by most individuals. Furthermore, although HAS scores were significantly associated with PDCAS scores ( r = 0.304, p < 0.001), PDCAS scores were not significantly associated with SDS scores, again suggesting that competition as a means for personal development may be viewed more positively than overt competitive behavior and beliefs.

Although the men in our sample again scored significantly higher on the PDCAS ( M = 56.03, SD = 13.26) than women [ M = 49.27, SD = 14.76; t (118) = 2.87, p = 0.005, Cohen’s d = 0.48], there were no significant differences regarding gender and task performance or recall. We also examined the results with respect to the gender of the confederates. A two-way ANOVA with the factors participant gender and confederate gender did not reveal a significant main effect of confederate gender [ F (3) = 1.48, p = 0.229] or an interaction of gender by confederate gender [ F (42) = 1.09, p = 0.735, Cohen’s d = 0.36] on competitive performance scores, nor did a two-way ANOVA with the factors participant gender and confederate gender reveal a significant main effect of confederate gender [ F (3) = 2.28, p = 0.088] or an interaction of gender by confederate gender [ F (42) = 1.73, p = 0.066, Cohen’s d = 0.45] on competitive recall scores. Furthermore, pair-wise t -tests revealed that neither men nor women who competed against male confederates showed any significant difference in self vs. competitive performance. Yet, male participants who competed against female confederates performed significantly worse [ t (29) = 3.54, p = 0.001, Cohen’s d = 0.65] and female participants who competed against female confederates performed marginally significantly worse [females: t (29) = 1.91, p = 0.066, Cohen’s d = 0.35] while they believed they were competing than when they were not competing. Furthermore, both male and females participants who competed against female confederates later recalled significantly fewer shapes learned in the competition condition [males: t (29) = 3.38, p = 0.002, Cohen’s d = 0.62; females: t (29) = 3.00, p = 0.006, Cohen’s d = 0.55]. All groups contained equal n ’s of 30 participants in each group. Although one could suggest that a significant difference among participants who believed they were competing against females may have resulted because these participants were exerting less effort against female competitors, there were no significant group differences regarding symmetry errors, suggesting that effort on the task was equal across groups, while memory on the task was hindered in those participants who faced female competitors. Details regarding group differences are depicted in Figure ​ Figure5 5 .

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Results of Experiment 2. (A) Participants remembered significantly more shapes during the task in the “self” condition than the “competition” condition. (B) Participants later recalled more shapes learned in the “self” condition than the “competition” condition. (C) “Competitive performance scores” (score on “self” condition subtracted from score on “competition” condition) significantly predicted “competitive recall scores” (shapes from the “self” condition successfully recalled on the post-test subtracted from shapes from the “competition” condition successfully recalled), suggesting that our working memory task produced significant immediate long-term learning. In this graph, a positive score signifies more competitive score. Error bars reflect standard errors of the means.

When controlling for social desirability bias, scores on the PDCAS were significantly positively correlated with performance in the competition condition (but not the self condition) for female participants who believed they were competing against female confederates ( r = 0.49, p = 0.009). This suggests that the more these participants viewed competition as a way to improve their skills, the better they performed in a competitive environment. However, given the small sample of female participants who competed against female confederates ( n = 30), this finding may be very speculative. Furthermore, although one would then expect the PDCAS to be correlated with the number of shapes recalled from the competition condition, this finding was not significant. However, competitive performance scores (score during self condition subtracted from the score during the competition condition) did not predict competitive recall scores for females who believed they were competing against other females, suggesting that, although competition may increase performance for individuals who prefer competition as a means of improving performance, competitive performance does not very often translate to an increase in immediate long-term memory.

Overall, our results suggest that competition hindered working memory performance and immediate long-term memory for most groups in our task. The finding that competition may hinder memory is surprising; one explanation for this finding could be that the presence of a competitor could invoke high anxiety among participants, and high levels of anxiety have been shown to decrease working ( Darke, 1988 ; Ashcraft and Kirk, 2001 ; Miller and Bichsel, 2004 ) and long-term memory ( Rosenfeld, 1978 ; Cassady, 2004 ; Miller and Bichsel, 2004 ). Specifically, research has found that adolescents raised in high normative goal environments report the highest rates of competitive anxiety ( White, 1998 ), which may lead to decrements in performance.

Perhaps even more unanticipated is that the finding that the presence of a female competitor, but not a male, was most likely to hinder performance on our memory task. An alternative explanation for this finding would be that participants exerted less effort on the task because of the presence of a female competitor. However, because there was no significant difference involving gender, competition condition, and symmetry errors, these results suggest that the presence of a female competitor is more likely to be hindering processes involved in working memory—and subsequently, the processes necessary for encoding, as evident by the results of our recall task. Furthermore, we found significant differences between conditions for participants who believed they were competing against female confederates, but there was no significant interaction of gender by confederate gender. This may suggest that all participants may have reduced performance in the competition condition in a similar fashion (see Figure ​ Figure6), 6 ), and therefore not produced an interaction of gender by confederate gender.

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Gender differences in Experiment 2. Male and female participants performed worse in and recalled fewer shapes at post-test when they believed they were competing against female competitors. There were no significant differences for participants who believed they were competing again male competitors. Error bars reflect standard errors of the means.

Moreover, disparities in subjective reward could affect the memory processes required for learning, such as attention: succeeding in a competitive learning environment could feel subjectively more rewarding than succeeding in an individualist learning environment, and therefore distract participants’ attention, thereby disrupting working and long-term memory.

General Discussion

Competition, attention, and memory.

Our results support the notion that a competitive environment can affect memory and effort. In Experiment 1, we examined the effect of competition on attention and effort; we found that the presence of a competitor increased attention on a physical effort task. However, we did not find that competition increased sustained effort on our task—just as competition did not affect the effort portion of Experiment 2 (symmetry matrices). This result could have occurred for a number of reasons: first, since RTs tend to be viewed as an implicit marker of motivation ( Glaser and Knowles, 2008 ), perhaps competition affects effort on an implicit, rather than explicit, level, especially since our survey results suggest that participants tend to view overt competitive behavior as a negative trait. Second, perhaps competition is only salient enough to increase immediate attention in a laboratory setting, and not sustained physical effort on a task over time. More likely, however, competition may only affect performance on a physical effort task in an environment where competitors compete side-by-side, which did not occur in our task. Furthermore, Kilduff (2014) has found that competition tends to increase physical effort on a gross physical effort task (i.e., running a race). Nonetheless, the finding that competition may increase attention has crucial real-world applications for education and the workplace.

In Experiment 2, we examined the effects of the presence of a competitor on memory. Participants in our sample performed best on our working memory task in a non-competitive environment, and also learned more in a non-competitive environment, as demonstrated by their performance on a later recall test. These results could have occurred for a number of reasons. First, competition could be viewed as an anxiety-provoking threat for most participants: previous research has suggested that high levels of anxiety could have a negative effect on both working memory ability ( Darke, 1988 ; Ashcraft and Kirk, 2001 ; Miller and Bichsel, 2004 ; Owens et al., 2012 ) and on learning ( Rosenfeld, 1978 ; Cassady, 2004 ; Miller and Bichsel, 2004 ; Einsel and Turk, 2011 ). We would expect that, if participants viewed their competitor as a threat, this would indeed hinder performance, as was seen in our results. These findings were even stronger in our results regarding recall, suggesting that for most individuals, competition actually hinders memory. Furthermore, our sample consisted of students already at the undergraduate level of education, who may already be acclimated to cooperating with other students in academic settings (as opposed to competing). Since our sample consisted of U.S. undergraduate students—as opposed to students from a country such as Japan, in which competitive learning environments are common ( Heine et al., 2001 )—perhaps our participants were not adjusted to learning in a competitive environment. Competitive learning environments may have led to improvements in countries which have taught this way from an early age, suggesting that a competitive learning environment may be too novel for someone already at a higher level of education ( Sanders, 1987 ; Smith, 1992 ).

Although competition improved initial RT in Experiment 1, the presence of a competitor hindered both working memory and immediate long-term memory in Experiment 2. Since attention is likely to increase both working memory ( Awh et al., 2006 ; Berryhill et al., 2011 ) and learning ( Nissen and Bullemer, 1987 ; Cohen et al., 1990 ; Gottlieb, 2012 ), why did this finding occur? It is possible that the difficulty of the task was responsible for this paradox: Experiment 1 featured a simple, button press task that required minimal effort. However, the multi-faceted task from Experiment 2 required more effort to succeed, and since greater emotional arousal may hinder performance and motivation on a very difficult task ( Yerkes and Dodson, 1908 ; Watters et al., 1997 ; Diamond et al., 2007 ), it may be that the presence of a competitor was anxiety-provoking enough to hinder working memory performance and immediate long-term memory. In fact, previous research has found that RT tends to be faster after an increase in arousal, whereas executive tasks such as those necessary for successful working memory tend to benefit from a decrease in arousal ( Luft et al., 2009 ). Furthermore, since competitive performance scores significantly predicted competitive recall scores, it may be that anxiety affected memory at the encoding phase—as opposed to affecting retention or retrieval.

An alternative explanation lies in the reward literature, as previous research has found that receiving rewards for a task can sometimes hinder performance, learning, and memory ( Spence, 1970 ; McGraw and McCullers, 1974 ; Mobbs et al., 2009 ; Chib et al., 2012 ). Perhaps succeeding in a competitive learning environment was subjectively more rewarding than succeeding in an individualist setting, despite objective rewards remaining the same across conditions. If succeeding in a competitive learning environment is subjectively more rewarding than succeeding in an individualist setting, competition may be more likely to distract participants—similarly to “choking under pressure” ( Baumeister, 1984 ; Beilock and Carr, 2001 , 2005 ; Ramirez et al., 2013 ). This explanation may be why competition negatively affecting working memory and immediate long-term memory on our task. There also may individual differences in preferences for competitive learning environments. In future research, it would be valuable to discern participants’ preference for the competition condition, as this information may provide insight as to the possible distractibility of competition and memory.

Individual and Gender Differences

In Experiment 1, we found that the PDCAS predicted how competitive an individual was at an effort bar task. In Experiment 2, the PDCAS predicted how competitive an individual was in a memory task, although this finding did not remain significant after correcting for multiple comparisons. Competitiveness in a learning setting is likely to be contingent on more factors than can be grasped from one survey measure. Furthermore, we found that men scored significantly higher on the PDCAS, suggesting that men may value competition as a means for improving personal development more than women. Men also exhibited a more competitive performance in our physical effort task in Experiment 1, in line with recent research that suggests men tend to both prefer and perform better in competitive physical environments more so than women ( Gneezy et al., 2009 ; Niederle and Vesterlund, 2011 ). However, men did not outperform women in our repeated memory task in Experiment 2. Competition may affect performance on memory tasks differently than competition traditionally affects effort and attention. Furthermore, since previous studies [such as Gneezy et al. (2009) ] have typically utilized effort tasks to compare preference for competitive environments, future research studies may want to further examine gender differences in preference for competition in memory tasks specifically, since these are typically utilized in educational settings.

We also found high rates of social desirability in our sample, which was negatively correlated with the HAS—but not the PDCAS—suggesting that the PDCAS may be a superior survey measure when tapping an individual’s true trait competitive habits and preferences. Furthermore, because the HAS contains blatant questions regarding competition, its negative correlation with social desirability may suggest that competition may be viewed as a negative personality trait by most individuals.

In Experiment 2, we found significant differences in performance on a memory task when a participant believed they were competing against a female participant. However, this result was not the case in Experiment 1 in a physical effort task. Although some research has found that females tend to excel at tasks involving episodic memory ( Herlitz et al., 1997 ; Davis, 1999 ) and object identification memory tasks ( Voyer et al., 2007 ), which were strong skills necessary to succeed at the type of task used in Experiment 2, whether this gender advantage was known by our participants remains unknown. Research suggests that increased attention drawn to one’s own performance can result in performance decrements or “choking under pressure” ( Baumeister, 1984 ; Beilock and Carr, 2001 , 2005 ; Ramirez et al., 2013 ), so the presence of a female competitor may increase pressure in a learning environment if participants have had previous experience with an object identification memory tasks and a female rivals, such as in a classroom learning setting. Yet, it is unclear whether the performance differences we found among participants who believed they were competing against female competitors were due to increased pressure due to the presence of a female competitor, or the opposite view: that females did not appear to be strong opponents in a learning setting, so they did not cause their competitors to devote more attentional resources to the task. However, although we found significant differences between conditions for participants who believed they were competing against female confederates, there was no significant interaction of gender by confederate gender, suggesting that all participants may have reduced performance in the competition condition.

Limitations

It may be difficult to generalize our experiment to competition and memory in a real-world sense. Our task in Experiment 1 examined how social motivation’s effect on a simple physical effort task, but competition may affect gross physical effort (e.g., running, team sports, etc.) on a more complex level. Additionally, our task from Experiment 2 was a specific, short memory task that did not offer any realistic long-term gains. Future research should include a longer period before administering a recall task, as a longer delay before recall would more realistically illustrate how learning occurs in a classroom setting. Furthermore, although individual preferences in competition were obtained, individual differences in intrinsic vs. extrinsic reward preference were not accounted for, and an additional sum of a few dollars may not have been enough motivation for some individuals to increase performance. Future research should examine how competition may influence long-term memory in a true educational setting.

Because our study examined the effect of competition on memory in two tasks that also featured gains and losses, our findings may have been driven by the effect of gains and losses on attention and performance, moderated by the saliency of a competitor. Since previous research has suggested that losses can increase both attention and performance ( Yechiam and Hochman, 2013 ), future research studies should attempt to distinguish whether or not competition merely moderates this affect, especially since most competitive learning environments incorporate some type of gains and losses, such as in educational settings.

In sum, our research suggests that social motivation—specifically, competition—can have strong effects on attention and memory, although significant individual and gender differences exist. Competition in a physical effort setting may increase attention, while the presence of a competitor may have detrimental effects on memory and performance. These findings present strong implications for education, the workplace, and other real-world settings involving social interaction.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Zana J Hanini, Joe Melon, and Tanasia Hall for their help as experimenters. We would also like to thank Holly Sullivan Toole with design of the effort bar task, and James Bradley, Frank Nick, Ahmet Ceceli, Christina Bejjani, Samantha DePasque Swanson, Jamil Bhanji, Onaisa Rizki, Kiranmayee Kurimella, and Stuti Prajapati for their help as confederates. This work was supported by a grant from the National Science Foundation (BCS 1150708) awarded to ET.

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Home » Student Opportunities » Contests for Students

Contests for Students

The IEEE offers many opportunities for students to win contests for outstanding performance in a variety of areas. Students, here you will be able to search for opportunities to receive recognition and prizes for your innovative thinking and hard work.

Sponsors, here you can have the opportunity to recognize some of the best and brightest young engineering minds while taking the opportunity to reinforce your organization’s dedication to the support of the next generation of IEEE leaders.

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Organizer:  IEEE Women in Engineering

Description: To bridge the gender gap and promote gender diversity, IEEE Women-in-Engineering (WIE) is organizing a story contest. The winners‘ stories will be plotted in the format of Manga comics, which will be socialized with the community through IEEE WIE Newsletter and website. The Manga plots will be available not only to the IEEE members, but also used as a tool to engage young generations particularly girls through IEEE WIE 1000+ Affinity Groups globally. The aim of the contest is to encourage the younger generation, particularly girls, to consider a career in STEM and work towards it. The story can be either fiction or non-fic

Eligibility: Please apply as an individual or as a group. At least one representative must be an IEEE member/IEEE student member.

Description: For this competition, student will design, analyze and optimize an additively manufactured heat sink to cool a constant heat flux power electronics module subject to free convection. The student teams that are evaluated as having the most effective, unique designs will have an opportunity to test their designs using the additive manufacturing facilities at GE and state-of-the-art test equipment at Oregon State University. These student groups will also present their work at the 2023 ITherm Conference.

Eligibility: Teams of up to eight undergrad and graduate students.

Organizer: IEEE Antennas and Propagation Society (AP-S)

Description: Design and build reconfigurable intelligent surfaces. The top 6 teams will receive travel funds to attend the IEEE Antennas and Propagation Symposium in Portland, Oregon, USA, July 23–28, 2023 to demonstrate their working systems. 1st, 2nd, and 3rd place winners will be announced at the 2023 IEEE AP-S Awards Presentation at the conference and will receive cash awards of US $1,500, $750, and $250, respectively.

Eligibility: The team should consist of 2 to 5 students, with at least 50% being undergraduate students. For a 5-year Bachelor-cum- Master degree program, students in years 1 to 3 are considered undergraduates. Each team should be advised by one professional mentor who is a member of the IEEE AP-S, but the work needs to be done primarily by the students. No student or mentor should be involved in more than one team.

Organizer: IEEE Computer Society

Description: Encourages students to develop excellence in their communication skills and achievement in the field of computer science.

Eligibility: All IEEE student members. There will be one award for undergraduates and a second for graduate students

Organizer: IEEE Women in Engineering

Description: The IEEE Women in Engineering (WIE) Student Branch Affinity Group of the Year Awards are given annually to one IEEE WIE Student Branch Affinity Group and one IEEE WIE Student Affinity Group that have shown outstanding leadership and initiative in organizing activities.

Organizer: IEEE WIE

Description: The IEEE Women in Engineering (WIE) Affinity Group of the Year Award is given annually to one IEEE WIE Affinity Group that has shown outstanding leadership and initiative in organizing activities. The award is based on programs that took place during the period of 1 January to 31 December of the preceding year.

Description: The purpose of this award is to recognize an undergraduate/graduate student member of IEEE Women in Engineering (WIE) who has overcome barriers to pursue engineering and/or who has made a personal impact in their community through their dedication and involvement in projects or activities directed toward fulfilling one or more of the IEEE WIE goals and objectives.

Eligibility: An IEEE Student Member or Graduate Student Member as of the submission deadline A member of IEEE WIE for at least two consecutive (2) years Must not be a past recipient of the IEEE Women in Engineering Inspiring Student Member of the Year Award

Description: The purpose of this award is to recognize a professional member of IEEE Women in Engineering (WIE) who has made an outstanding contribution to IEEE WIE, their community, and the engineering community, through their dedication and involvement in projects or activities directed toward fulfilling one or more of the IEEE WIE goals and objectives.

Eligibility: An IEEE Member grade or higher A professional member of IEEE WIE for at least two (2) years A professional working in industry/academia for greater than five (5) years Must not be a past recipient of the IEEE Women in Engineering Inspiring Member of the Year Award

Organizer: Region 9 SAC

Description: Exemplary Student Affinity Group will be considered those who demonstrate that they have good management of the institution’s internal and external resources and, mainly, effectively promote the theme of their affinity group through projects and activities. In addition, groups must have quality documentation, which can be used for the continuity of the group’s culture and dissemination of knowledge of good practices and ideas.

Description: If your organizational unit has carried out any innovative activity, which stands out among other activities within the Region, whether it had a correct organization, good audience, won a prize, generated funds and resources for the Branch or managed to have agreements with other universities, companies or institutions, is an excellent candidate to be chosen as a case of success!

Eligibility: • They have updated president and advisor / advisor information at IEEE vTools Officer Reporting; • They are active (have at least 10 members for Branches and 5 for Chapters / Affinity Groups). • Have submitted the 2020 student branch report. In addition, only activities carried out during the period of August 2019 until June 2020 will be considered. Each organizational unit can send just 1 (one) success case.

Description: Will be considered to be exemplary those Student Technical Chapters that prove to have a good internal and external resources management and, mainly, effectively promote their Society area of study through projects and activities. In addition, these chapters should have quality documentation that can be useful for the group continuity and to share good practices knowledge and ideas.

Description: The photo contest IEEE R9 is a fun way to show love by the institute through the activities that the Student Branches have done is through photographic records. Therefore, the photography contest of IEEE Region 9, in which all those registered images, related to IEEE can be a basis for the promotion of the Institute among the different branches, sections, advice or at the global level.

Description: The International Future Energy Challenge (IFEC) is an international student competition for innovation, conservation, and effective use of electrical energy.The competition is sponsored by the Industry Applications Society (IAS), Power & Energy Society (PES), Power Electronics Society (PELS), and Power Sources Manufacturers Association (PSMA).

Eligibility: The competition is open to college and university student teams from recognized engineering programs in any location. Participation is on a proposal basis.

Organizer: HRL Laboratories, LLC, IEEE Photonics Society and APS Division of Laser Science.

Description: This competition was established in 2008 in memory of Theodore Maiman and in acknowledgement of his amazing invention, the first working laser, and his other outstanding contributions to optics and photonics. The program recognizes student innovation, research excellence and presentation skills in the areas of laser technology and electro-optics, and is endowed by HRL Laboratories, LLC, IEEE Photonics Society and APS Division of Laser Science.

Eligibility: undergraduate or graduate student of an educational institution of collegiate grade who is devoting more than half-time to studies within the institution at the time the paper was written.

Description: Autonomous underwater robotics is an exciting challenge in engineering, which participants get to experience at SAUVC. The competition is great learning ground for participants to experience the challenges of AUV system engineering and develop skills in the related fields of mechanical, electrical and software engineering.

Description: The NOSB is an academic competition and program that addresses a national gap in environmental and earth sciences in public education by introducing high school students to and engaging them in ocean science, preparing them for ocean science-related and other STEM careers, and helping them become knowledgeable citizens and environmental stewards.

Organizer: The IEEE Nuclear and Plasma Sciences Society (NPSS)

Description: For outstanding student poster or oral papers as desired by each of the technical committees of NPSS that organizes a conference. The purpose of these awards is to encourage both outstanding student contributions and greater student participation as principal or sole authors of papers as well as to acknowledge the importance of student contributions to the fields embraced by the NPSS.

Eligibility: Any student who is the principal or sole author/researcher and the presenter of either a poster or oral paper at any IEEE NPSS conference that has chosen to provide outstanding student awards, and who has been identified as an eligible student author, will be eligible. If there is a tie, preference will be given 1) to IEEE NPSS members; 2) to IEEE members; or 3) to non-IEEE members.

Organizer: IEEE Geoscience and Remote Sensing Society

Description: This prestigious academic competition, founded by the University of Queensland, is designed to enhance students’ research communication and presentation skills by challenging them to describe their thesis topic in just three minutes to a general audience using one static slide.

Eligibility: To participate, simply submit a 3-minute video describing your research and thesis topic to a video platform like YouTube or TikTok. or through a private URL accessible only by the evaluation committee. Your video will be evaluated in the first round based on presentation skills (40%), scientific quality (40%) and originality (20%) of the topic presented.

Organizer: The IEEE Microwave Theory and Techniques Society

Description: The MTT-Sat Challenge is a worldwide competition for teams of undergraduate and graduate students to design and build radio frequency (RF) and microwave hardware for small satellites. The most promising designs will undergo space environmental qualification testing and will be incorporated in a cubesat, which will be launched into orbit (in case MTT-Sat Challenge secures enough funding and a participation in cubesat projects). The main goal of the MTT-Sat Challenge is to advance space RF and microwave education, inspire students to pursue science and engineering education and careers, and prepare tomorrow’s leaders with the interdisciplinary teamwork skills, which are necessary for success. The MTT-Sat Challenge is managed by the IEEE Microwave Theory & Techniques Society (IEEE MTT-S) with additional experts and advisors in the field.

Eligibility: undergraduate and graduate students

Organizer: sponsored by the Technical Committees of the MTT

Description: The competition encourages students to employ creative problem solving and gain practical design experience by developing a circuit, or system to address a problem stated in the competition rules while following specified constraints. The students will bring their designs to the competition where they perform measurements and compete against other student teams. The winning teams are awarded cash prizes and recognized at the IMS student luncheon awards. In the IMS 2020 SDC we have 12 different competitions spanning a wide range of topics from power amplifier design to spectral sensing radios. Links to descriptions and rules for each competition rules are below.Winning teams are awarded cash prizes and a chance to publish their designs in the IEEE Microwave Magazine.

Organizer: jointly promoted and organized by IEEE Instrumentation and Measurement Society (IMS), IEEE Engineering in Medicine and Biology Society (EMBS) and IEEE Sensors Council (SC) and is sponsored by STMicroelectronics

Description: The IEEE International Contest of Sensors and Measurement Systems is jointly promoted and organized by IEEE Instrumentation and Measurement Society (IMS), IEEE Engineering in Medicine and Biology Society (EMBS) and IEEE Sensors Council (SC) and is sponsored by STMicroelectronics who will provide one SensorTile.box® to each team admitted to the competition. This multisensory device will be the common technology platform of the contest. Those willing to participate will have to submit a proposal, will have to develop their application at their University laboratories and attend one of the scheduled live demonstration sessions co-located with international conferences in the areas of sensors and instrumentation and measurement. For each demonstration event, two awards will be assigned (1st and 2nd place) for the best “Sensors and Measurement Systems” application.

Eligibility: teams of Ph.D., Master and advanced undergraduates (particularly those in fast-track, dual BS/MS, Master programs) students

Organizer: Industrial Electronics Society Awards and Honor Committee (IES A&H Committee).

Description: To recognize the student best paper in The Industrial Electronics Society publications and to encourage the student or graduate student author to contribute further in the field of industrial electronics.

Eligibility: Author(s) of papers in the Industrial Electronics Society publications during the year specified for the award, where the first author must be a student or a graduate student IEEE member. Must be student or graduate student member of the IEEE.

Description: The GRSS Student Prize Paper Award was established to recognize the best student paper(s) presented at the IEEE International Geoscience and Remote Sensing Symposium (IGARSS). It is believed that early recognition of an outstanding paper will encourage the student to strive for greater and continued contributions to the Geoscience and Remote Sensing profession. The award shall be considered annually. These awards go to the 2nd and 3rd place students. For the 1st place student award refer to the Mikio Takagi Student Prize.

Eligibility: The (first) author(s) must:

  • contribute more than 60% of the content of the presented paper (if the contribution is less than 60%, the paper is not suitable for a student paper competition and can be submitted to the normal track),
  • be a student,
  • be under 33 years of age,
  • be a candidate for a graduate degree (PhD students included),
  • be an IEEE member,
  • publish the paper in the IGARSS digest,
  • be registered at IGARSS,
  • personally present the paper at IGARSS, and
  • be present at the IGARSS banquet to receive the award

Multiple eligible authors are allowed. An ineligible co-author, or an advisor, must verify on university letterhead that the candidate is a student, under 33 years of age, a candidate for a graduate degree, and an IEEE member on the submittal date of the paper. Eligibility and Selection process shall comply with procedures and regulation established in IEEE and Society governing documents, particularly with IEEE Policy 4.4 on Awards Limitations.

Organiser: Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) and the Technical University of Munich Description: The Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) and the Technical University of Munich, aims to promote research in large-scale land cover mapping from globally available multimodal satellite data. The task is to train a machine learning model for global land cover mapping based on weakly annotated samples. The 2020 IEEE GRSS Data Fusion Contest consists of two challenge tracks: Eligibility: The Contest is open not only to IEEE members but to everyone, with the goal of promoting innovation and benchmarking in analyzing multi-source big earth observation data.

Organizer: IEEE Engineering in Medicine & Biology Society, in connection with the Annual International EMB Conference

Description: Annually the IEEE Engineering in Medicine & Biology Society, in connection with the Annual International EMB Conference, sponsors a Student Paper Competition (SPC).

Eligibility: an active member of the IEEE Engineering in Medicine & Biology Society at a Student Grade; Graduate Student Member or Undergraduate Student Member

Organizer: IEEE Aerospace and Electronic Systems Society

Description: The Radar Challenge is a new event co-hosted with radar conferences that enables participants to experience the magic of radar in a personal, tangible and experiential way—offering an opportunity to create and “see” invisible radar waves interacting with their environment. The event will host an unknown target scene that participants will then sense and decipher using their self-engineered “home-brew” radar. The goal is to build a community of radar builders that collectively explore the art of the possible in making “COTS-based” radars.

Description: The Radar Challenge is a series of events co-hosted with radar conferences that enable participants to experience the magic of radar in a personal, tangible and experiential way. ​ The events invigorate participants to experiment with their self-engineered “home-brew” radar, low-cost commercial-off-the-shelf RF sensors, and publicly available radar datasets. The goal is to build a community of radar engineers that collectively explore the art of the possible for a new generation of radars by creating and experimenting with prototype radars.

Organiser: IEEE Computational Intelligence Society

Organizer: Region 10 SAC

Description: The IEEE Region 10 Student Branch Website Contest is designed to encourage student volunteers to fully utilize the power of the Internet for keeping members informed about the local activities and opportunities to participate. A well-maintained website with ease of navigation can be a great source of timely information and an appealing showcase for the local IEEE activities. IEEE Region 10 Student Activities Committee annually conducts a website contest and the Student Branches under the Sections of Region 10 are invited to submit entries of their websites.

Eligibility: IEEE Student Branches in Region 10

Description: The IEEE Region 10 Student Activities Committee recognizes the importance of research and dissemination of the findings for the The IEEE Region 10 Student Activities Committee recognizes the importance of research and dissemination of the findings for the advancement of science and technology. Researching, writing, and presenting a paper provides students with invaluable early experience in communicating ideas related to their professional fields. The contest offers IEEE Student members an opportunity to exercise and improve both written and verbal communication skills.

Eligibility: Open to all IEEE Student Members with basic degrees in electrical engineering, electronics, computer science or any other fields of interest of an IEEE Society, and are currently enrolled in a postgraduate course at a recognized educational institute. The contest is open only to IEEE Student Members in Region 10. The papers may be on any engineering subject in the field of interest of IEEE (within the scope of IEEE transactions).

Description: The IEEE Region 10 Student Activities Committee recognizes the importance of communication skills for fresh graduates as throughout their engineering career, they are constantly called upon to communicate ideas to others. The contest offers IEEE student members an opportunity to exercise and improve both verbal communication and presentation skills in a concise manner suitable for wider audience. The contest provides students with invaluable early experience in communicating ideas related to their professional field via electronic media.

Eligibility: Open to all IEEE Student Members who currently enrolled or graduated within the last six months for degrees in electrical engineering, electronics, computer science or any other field of interest of an IEEE Society. The contest is open only to IEEE Student Members in Region 10. The project video may be on any engineering subject in the field of interest of IEEE (within the scope of IEEE transactions).

Organizer: Region 8

Description: The IEEE Region 8 Student Paper Contest (SPC) started in 1967, only four years after IEEE R8 was formed. The SPC was an initiative of the second R8 Director, Jean Lebel. The first SPC was held in Lausanne, Switzerland in conjunction with the IEEE R8 Committee Meeting. Since then, it has been held every year without exception, and it is one of the main technical activities in Region 8. By organizing the Student Paper Contest, the IEEE Region 8 Student Activities Committee recognizes the importance of student research and the dissemination of their results and findings.

Description: In 1983, the Lance Stafford Larson Award was established by the Larson family in memorial for their son, who died in an electrical accident while an undergraduate at the University of Maryland. The Larson family, which includes IEEE Past President Robert Larson, created this award to encourage students to develop excellence in their communication skills and to motivate students toward achievement in the field of Computer Science.

One award of $500 is given each year to the first-place winner. First, second, and third place winners also receive a certificate of commendation. The prize is awarded to the best paper. In the case of multiple authors, the prize will be divided among the student authors.

Organizer: Partnered with IEEE RAS

Description: RoboCup is arranged with the intention to use RoboCup as a vehicle to promote robotics and AI research, by offering a publicly appealing, but formidable challenge. One of the effective ways to promote science and engineering research is to set a challenging long term goal. When the accomplishment of such a goal has signifRoboCup is an international scientific initiative with the goal to advance the state of the art of intelligent robots. When established in 1997, the original mission was to field a team of robots capable of winning against the human soccer World Cup champions by 2050. While that mission remains, RoboCup has since expanded into other relevant application domains based on the needs of modern society. Today, RoboCup covers the themes of robot soccer, personal service robotics in living spaces, manipulation and manufacturing at work, and rescue robotics. In addition, RoboCupJunior is a project-oriented educational initiative that sponsors local, regional, and international robotic events for young students. It is designed to introduce RoboCup to primary and secondary school children.

Description: This year’s challenge will be based on a study recently published in Cancer Cell by the ProCan team (Gonçalves et al., 2022). The study aimed to generate a comprehensive pan-cancer proteomic map of human cell lines to aid in the discovery of cancer biomarkers and the development of new cancer treatments. The main challenge will be to create an integrated overview of cell-type / tissue-type / cancer-type distributions of both single proteins as well as protein categories. There will also be a re-design challenge connected to the improvement of the representation/interaction strategies used for one of the figures in the paper.

Organizer: IEEE VIS 2020

Description: The 2020 IEEE SciVis Contest is dedicated to create novel approaches or state of the art visualizations to assist domain scientists to better understand the complex transport mechanisms of eddies in the Red Sea under uncertainty.

Description: The MATE competition challenges K-12, community college, and university students from all over the world to design and build ROVs to tackle missions modeled after scenarios from the ocean workplace. Eligibility: Pre-University Students

Organiser: IEEE IAS Eligibility: Open for all

Organiser: IEEE IAS Eligibility: At least one member of the team should be an IAS, IEEE member.

Description: The IEEE Xplore® Challenge for Researchers is open to academics, research scholars, and engineers from select areas, who are from universities, corporations, and government institutions and who have a subscription to IEEE Xplore, and are at least eighteen (18) years of age at the time of entry. The respondents with the highest quiz scores will be entered into a drawing to win one of several prizes.

Eligibility: All academics, research scholars, and engineers from Pakistan, Brazil, Asia, or Mexico, who are from universities, corporations, and government institutions who have a subscription to IEEE Xplore, and are at least eighteen (18) years of age at the time of entry.

Organizer: IEEE Oceanic Engineering Society

Description: Each year the IEEE Oceanic Engineering Society sponsors the Student Poster Competition at the spring and fall OCEANS Conferences. Cash awards for the winning posters and the travel, food, lodging, and registration expenses of all students participating in the competition are provided by OES.

Eligibility: Open for all

Organizer: IEEE Signal Processing Society

Description: The Signal Processing Cup (SP Cup) competition is held annually and encourages teams of students to work together to solve real-world problems using signal processing methods and techniques. Each year, three final teams are chosen to present their work during ICASSP to compete for the US$5,000 grand prize!

Eligibility: Each team participating should be composed of one faculty member or someone with a PhD degree employed by the university (the Supervisor), at most one graduate student (the Tutor), and at least three, but no more than ten undergraduate students. At least three of the undergraduate team members must hold either regular or student memberships of the IEEE Signal Processing Society. Undergraduate students who are in the first two years of their college studies, as well as high school students who are capable to contribute are welcome to participate in a team. A participant cannot be on more than one team.

Organiser : IEEE Circuits and Systems Society (CAS)

Description: The CASS Student Design Competition is a worldwide competition where undergraduate students will team with high school students. The teams should suggest and execute projects aimed at encouraging High School Students to study Electrical Engineering and related areas. The focus should be on finding a solution to a real-life problem based on circuits and systems.

Organizer: IEEE Communications Society

Description: The competition, Communication Technology Changing the World, recognizes students or teams of students who demonstrate the capacity to improve the lives of people through the application of communication technology and the development of projects that meet the needs of humanity.

Organizer: IEEE Computer Society Description: IEEEmadC (Mobile Applications Development Contest), is a 6-8 month competition which was initially focused to inspire student members in Europe, the Middle East, and Africa to develop mobile applications. It has escalated into a globally recognized competition.

Organizer: MGA Student Activities Committee Description: IEEEXtreme is a global challenge in which teams of IEEE Student members – advised and proctored by an IEEE member, and often supported by an IEEE Student Branch – compete in a 24-hour time span against each other to solve a set of programming problems.

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How to choose recycling mode between monopoly and competition by considering blockchain technology.

environment research paper competition

Share and Cite

Zhang, X.; Zheng, H.; Hang, T.; Meng, Q. How to Choose Recycling Mode between Monopoly and Competition by Considering Blockchain Technology? Sustainability 2024 , 16 , 6296. https://doi.org/10.3390/su16156296

Zhang X, Zheng H, Hang T, Meng Q. How to Choose Recycling Mode between Monopoly and Competition by Considering Blockchain Technology? Sustainability . 2024; 16(15):6296. https://doi.org/10.3390/su16156296

Zhang, Xuemei, Haodong Zheng, Tao Hang, and Qiang Meng. 2024. "How to Choose Recycling Mode between Monopoly and Competition by Considering Blockchain Technology?" Sustainability 16, no. 15: 6296. https://doi.org/10.3390/su16156296

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Competition →

environment research paper competition

  • 04 Jun 2024
  • Cold Call Podcast

How One Insurtech Firm Formulated a Strategy for Climate Change

The Insurtech firm Hippo was facing two big challenges related to climate change: major loss ratios and rate hikes. The company used technologically empowered services to create its competitive edge, along with providing smart home packages, targeting risk-friendly customers, and using data-driven pricing. But now CEO and president Rick McCathron needed to determine how the firm’s underwriting model could account for the effects of high-intensity weather events. Harvard Business School professor Lauren Cohen discusses how Hippo could adjust its strategy to survive a new era of unprecedented weather catastrophes in his case, “Hippo: Weathering the Storm of the Home Insurance Crisis.”

environment research paper competition

  • 29 Feb 2024

Beyond Goals: David Beckham's Playbook for Mobilizing Star Talent

Reach soccer's pinnacle. Become a global brand. Buy a team. Sign Lionel Messi. David Beckham makes success look as easy as his epic free kicks. But leveraging world-class talent takes discipline and deft decision-making, as case studies by Anita Elberse reveal. What could other businesses learn from his ascent?

environment research paper competition

  • 09 Jan 2024
  • In Practice

Harnessing AI: What Businesses Need to Know in ChatGPT’s Second Year

Companies across industries rushed to adopt ChatGPT last year, seeing its potential to streamline tasks formerly handled by people and vendors at much higher cost. As generative AI enters its next phase in 2024, what can leaders expect? Harvard Business School faculty members highlight four trends to watch.

environment research paper competition

  • 26 Sep 2023

The PGA Tour and LIV Golf Merger: Competition vs. Cooperation

On June 9, 2022, the first LIV Golf event teed off outside of London. The new tour offered players larger prizes, more flexibility, and ambitions to attract new fans to the sport. Immediately following the official start of that tournament, the PGA Tour announced that all 17 PGA Tour players participating in the LIV Golf event were suspended and ineligible to compete in PGA Tour events. Tensions between the two golf entities continued to rise, as more players “defected” to LIV. Eventually LIV Golf filed an antitrust lawsuit accusing the PGA Tour of anticompetitive practices, and the Department of Justice launched an investigation. Then, in a dramatic turn of events, LIV Golf and the PGA Tour announced that they were merging. Harvard Business School assistant professor Alexander MacKay discusses the competitive, antitrust, and regulatory issues at stake and whether or not the PGA Tour took the right actions in response to LIV Golf’s entry in his case, “LIV Golf.”

environment research paper competition

  • 19 Sep 2023

How Will the Tech Titans Behind ChatGPT, Bard, and LLaMA Make Money?

It seems like anything is possible with generative AI right now. But how will companies profit from those big ideas? Andy Wu breaks down the potentially painful tradeoffs that tech firms might face as artificial intelligence enters its next phase.

environment research paper competition

  • 29 Aug 2023

As Social Networks Get More Competitive, Which Ones Will Survive?

In early 2023, TikTok reached close to 1 billion users globally, placing it fourth behind the leading social networks: Facebook, YouTube, and Instagram. Meanwhile, competition in the market for videos had intensified. Can all four networks continue to attract audiences and creators? Felix Oberholzer-Gee discusses competition and imitation among social networks in his case “Hey, Insta & YouTube, Are You Watching TikTok?”

environment research paper competition

  • 07 Jun 2023

3 Ways to Gain a Competitive Advantage Now: Lessons from Amazon, Chipotle, and Facebook

Remember the Sony Librie? Some people considered it superior to Amazon's Kindle, but it didn't end up the market leader. Rebecca Karp breaks down three methods that companies use to create more value than their rivals—an edge that can make all the difference.

environment research paper competition

  • 28 Feb 2023

Muhammad Ali: A Case Study in Purpose-Driven Decision Making

Muhammad Ali, born Cassius Marcellus Clay Jr., rose from a poor family in segregated Louisville, Kentucky to international fame, winning three heavyweight boxing titles and becoming a civil rights leader and role model for millions of people around the world. How did he do it? Early in his career, Ali’s creativity and hard work helped him overcome significant obstacles. Rather than letting his fear of flying keep him from competing in the 1960 Olympics, he traveled to Italy wearing a parachute -- and easily won the gold medal in boxing. When he returned to the U.S. as a gold medalist, Ali used his growing fame to bring attention to racism and humanitarian causes he supported, including his then-controversial decision to refuse to fight in the Vietnam War. Professor Robert Simons discusses how Ali made decisions throughout his life and career to leave a lasting impact on the world in his case, “Muhammad Ali: Changing the World.”

environment research paper competition

  • 21 Jun 2022

Free Isn’t Always Better: How Slack Holds Its Own Against Microsoft Teams

What will it take to win the collaboration app wars: massive scale or a loyal following? A case study by David Yoffie digs into the intense competition between Microsoft Teams and Salesforce's Slack.

environment research paper competition

  • 28 Apr 2022
  • Research & Ideas

Can You Buy Creativity in the Gig Economy?

It's possible, but creators need more of a stake. A study by Feng Zhu of 10,000 novels in the Chinese e-book market reveals how tying pay to performance can lead to new ideas.

environment research paper competition

  • 13 Apr 2021
  • Working Paper Summaries

Deregulation, Market Power, and Prices: Evidence from the Electricity Sector

Efforts to deregulate the US electricity sector beginning in the 1990s included market-based prices and restructuring measures to introduce competition. This paper argues that electricity prices increased after deregulation because of the presence of market power.

environment research paper competition

  • 07 Sep 2020

How to Help Small Businesses Survive COVID's Next Phase

For small businesses that have survived the coronavirus so far, what's next? Karen Mills outlines steps that business owners and government should take immediately. Open for comment; 0 Comments.

environment research paper competition

  • 03 Sep 2020

Why American Health Care Needs Its Own SEC

The United States needs a health care equivalent of the Securities and Exchange Commission to increase transparency and competition, argues Regina Herzlinger. Open for comment; 0 Comments.

  • 01 Jun 2020
  • What Do You Think?

Will Challenged Amazon Tweak Its Retail Model Post-Pandemic?

James Heskett's readers have little sympathy for Amazon's loss of market share during the pandemic. Has the organization lost its ability to learn? Open for comment; 0 Comments.

environment research paper competition

  • 21 Apr 2020

7 Successful Battle Strategies to Beat COVID-19

The Agile methodology used to speed complex software development is also helpful for managing decision-making in today's crisis environment, says Euvin Naidoo. Open for comment; 0 Comments.

environment research paper competition

  • 06 Apr 2020

Where Do Workers Go When the Robots Arrive?

Marco Tabellini and colleagues investigate where workers go after losing their jobs to automation and Chinese imports. Open for comment; 0 Comments.

  • 24 Mar 2020

Free Riding in Loan Approvals: Evidence From SME Lending in Peru

Using data from a large Peruvian bank trying to expand credit access to small and medium enterprises, this study shows that competing lenders use one another’s loan approvals as an input into their own approval process. Such “free riding” has great impact on market outcomes and might warrant policy intervention.

environment research paper competition

  • 17 Mar 2020

Is There a Winner in Huawei’s Digital Cold War with the US?

Bill Kirby discusses his case study of China-based Huawei’s growth and ultimate confrontation with the United States government, and China's response to the coronavirus. Open for comment; 0 Comments.

environment research paper competition

  • 09 Mar 2020

Warring Algorithms Could Be Driving Up Consumer Prices

Companies increasingly use software to conduct rapid price changes. Alexander MacKay explains why firms might benefit but consumers should be worried. Open for comment; 0 Comments.

  • 06 Mar 2020

Consumer Protection in an Online World: An Analysis of Occupational Licensing

This paper uses new data collected by a digital platform to study the role of occupational licensing laws on individual choices and market outcomes. Results suggest that more stringent licensing laws restrict competition but do not lead to improvements in customer satisfaction.

COMMENTS

  1. Home

    GENIUS Olympiad is an international high school project competition about environmental issues. It is founded and organized by Terra Science and Education and hosted by the Rochester Institute of Technology. GENIUS Olympiad will host projects in five general disciplines with an environmental focus. " Unless someone like you cares a whole awful ...

  2. 25 Science Research Competitions for High Schoolers

    The Regeneron ISEF is the world's largest international pre-college STEM competition—high school students representing all 50 states and more than 70 countries, regions, and territories, take part. Students showcase independent research and compete across 22 categories for awards ranging from $500 to $75,000.

  3. Your Gateway To The COP29

    We're always open to ambitious and motivated people to join our team! Mail [email protected] with how you'd like to help out. Join climate enthusiasts on a global stage to brainstorm climate solutions. Win a cash prize & a sponsored trip to COP29 in Azerbaijan.

  4. 10 Environmental Science Competitions for High School Students

    National Competition - June 22-24, 2024. International Competition - August 23-27, 2024. Eligibility: High school students in grades 9-12, aged 15 by August 1 of the competition year, who have conducted a water-related science project . The Stockholm Junior Water Prize (SJWP) is prominent among high school students' top environmental ...

  5. 2024 ASA ENVR Student Paper Competition

    The paper may consist of novel approaches to the analysis of environmental data, new methodology with a clear application to a statistical problem found within the environmental sciences, or an interesting application of statistics to environmental research. Awards: For the 2024 competition, ENVR anticipates awarding travel funding to the top ...

  6. 15 Research Competitions for High School Students

    Here are 15 Research Competitions for High School Students: 1. Regeneron Science Talent Search. This talent hunt, which began in 1942 as a program of the Society for Science & the Public (the Society), is widely regarded as the nation's most renowned high school science research competition.

  7. The 11 Best High School Science Competitions

    Research projects should "contribute a work that is recognized as an outstanding accomplishment by experts in the field and has the potential to benefit society." Envirothon . Grades Eligible: 9-12; Individual or Group: Group; Research or Exam: Exam; Envirothon is a competition designed to promote environmental education in schools.

  8. The Best Environmental Competitions for Students.

    World of 7 Billion Competition: this featured challenge in the ICS environmental competitions database helps students take the first steps into global change-making by researching challenges associated with global population change, and creating a video describing their solution to the problem. Check it out today.

  9. Student Paper Competition

    Description. The Section on Statistics in the Environment (ENVR) sponsors a student paper competition on the topic of environmental statistics. Papers may consist of novel approaches to the analysis of environmental data, new methodology with a clear application to an environmental statistical issue, or application of statistics to ...

  10. The nature of the last universal common ancestor and its impact on the

    Integration of phylogenetics, comparative genomics and palaeobiological approaches suggests that the last universal common ancestor lived about 4.2 billion years ago and was a complex prokaryote ...

  11. 25 Science Competitions for High School Students in 2023

    1. Davidson Fellows. The Davidson Institute offers $50,000, $25,000, and $10,000 scholarships every year to high-achieving students, 18 years old or younger. To apply, students a project they have completed in science, technology, engineering, mathematics, literature, music, or philosophy, along with completed evaluations by their nominators. 2.

  12. Science competitions your students can enter in 2023

    Age: 13-15. Registration opens: now open. Competition dates: 1-17 May 2024. The Biology Challenge is a fun, annual competition open to students aged 13-15 in the UK. The challenge compromises of two, 25-minute, multiple-choice papers, and students need to complete both papers to be considered for an award category.

  13. Competitions

    Categories: Architecture, Community Service, Environment, Real Estate, Urban Planning. Follow. View Details. Aerial Drone Competition. Ages: Middle School, High School. Categories: Engineering, Robotics, STEM. Follow. View Details ... The Institute of Competition Sciences (ICS) was founded in 2012 to help transform learning into an exciting ...

  14. Ignited competition: Impact of bioactive extracellular compounds on

    Plant, Cell & Environment is an ecology journal analysing the ways plants respond to their environment including biological, physiological and ecological factors. Abstract Prevalent interactions among marine phytoplankton triggered by long-range climatic stressors are well-known environmental disturbers of community structure.

  15. Sustainability

    Supply chain green technology collaborative innovation is an important means for enterprises to improve the greenness of their products. This paper takes supply chain green technology innovation collaboration as the research object and constructs a stochastic differential game model, which not only provides reference for enterprises to choose the optimal type of technology innovation by ...

  16. Environmental regulation under sequential competition

    While environmental policy leads both firms to reduce their output, i.e., q 1 C ( t C) < q 1 C ( 0) and q 2 C ( t C) < q 2 C ( 0), the regulator keeps firm 1's output advantage unaffected, which originates from its cost advantage alone. As a result, Δ C ≡ Δ q N R, C − Δ q R, C = 0 for all parameters.

  17. Writing Competitions for Law Students: Environmental Law

    Vermont Journal of Environmental Law White River Environmental Law Writing Competition. Papers should address a relevant topic in environmental law. American Bar Association Section of Environment, Energy, and Resources . Competition topic areas include "Air, Water, and Food," "Biodiversity," "Indigenous Law," and "Recycling." Submit by May 31 ...

  18. Competition Law Research Paper Topics

    100 Competition Law Research Paper Topics. Competition law is a dynamic and multifaceted field that addresses various issues related to market competition, monopolies, consumer welfare, and economic efficiency. As law students delve into this intricate domain, they often encounter the challenge of selecting compelling research paper topics that ...

  19. Don't even study it: Geoengineering research hits societal roadblocks

    The debate has not only hit individual experiments and projects, but even international meetings, such as at the February 2024 gathering of the United Nations Environment Assembly, where ...

  20. Apparel Industry Leaks Millions of Tons of Plastic Into Environment

    "Then we compared that to existing global information on different stages of the apparel value chain to estimate how much plastic leaks into the environment at each of those points. "Much of the plastic waste that leaks into the environment comes from clothes that are thrown away, especially synthetic apparel," Venditti said.

  21. Research Paper Competition

    A research paper consists of student or team Investigative Research, which is the written presentation of your investigation and experimentation. Research papers are only allowed for students in 6th-12th grade competing in the middle school/senior high fair. Scientific thought and procedures will receive major credit in the judging.

  22. King's Speech 2024: background briefing notes

    Research and statistics. Reports, analysis and official statistics. Policy papers and consultations. Consultations and strategy. Transparency. Data, Freedom of Information releases and corporate ...

  23. Environmental Preferences, Competition, and Firms' R&D Choices

    The researchers hypothesize that consumers care about the environmental footprint of products they buy, and that firms consider these preferences when choosing how much to invest in research and development on "clean" or "dirty" innovations. They then use data on patents, consumers' environmental preferences, and product-competition ...

  24. Does public environmental concern cause pollution transfer? Evidence

    The power of public environmental concern cannot be ignored. It is vital in promoting environmental legislation, corporate social responsibility, and sustainable development. Existing studies have discussed the positive governance effects of public environmental concern on environmental quality but have neglected the issue of environmental inequality due to pollution transfer resulting from ...

  25. The power of competition: Effects of social motivation on attention

    Introduction. Social motivation has been defined as a drive for a particular goal based on a social influence (Hogg and Abrams, 1990).Although research has examined correlative relationships between competition and learning (Dweck and Leggett, 1988; Zimmerman, 1989; Oldfather and Dahl, 1994; Wentzel, 1999), few studies have examined how the presence of a competitor directly influences ...

  26. Contests for Students

    Description: For this competition, student will design, analyze and optimize an additively manufactured heat sink to cool a constant heat flux power electronics module subject to free convection. The student teams that are evaluated as having the most effective, unique designs will have an opportunity to test their designs using the additive manufacturing facilities at GE and state-of-the-art ...

  27. How to Choose Recycling Mode between Monopoly and Competition by ...

    Enterprises adopting a circular economy approach can effectively solve the severe situation of resources and the environment, and recycling is considered an effective means to solve environmental issues. Simultaneously, blockchain technology (BT) has been used to enhance product quality trust. However, there is limited literature on how to choose between monopolistic and competitive recycling ...

  28. The Competitive Effects of School Choice on Student Achievement: A

    We also found some evidence that the type of school-choice policy and student demographics moderated the effects of competition on student achievement. By examining whether school competition improves outcomes, our findings can inform decisions of state and local policymakers who have adopted or are considering adopting school-choice reforms.

  29. Competition: Articles, Research, & Case Studies on Competition- HBS

    by Alexander MacKay and Ignacia Mercadal. Efforts to deregulate the US electricity sector beginning in the 1990s included market-based prices and restructuring measures to introduce competition. This paper argues that electricity prices increased after deregulation because of the presence of market power. 07 Sep 2020.

  30. PDF The Effect of Competition on Moral Development: A ...

    Moral maturation requires a positive environment, competition which can often be achieved in an environment where competition is as minimal as possible and with values-rich lives (Akkaya, 2008 ò Erden & Akman, 2012 ò Öztürk, 2016). ... about the concept of "competition", the study group of the research was chosen by criterion sampling of