Global Air Pollution Prediction Challenge | bitgrit
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Global Air Pollution Prediction Challenge

Predicting Pollution for a Cleaner Tomorrow

bitgrit
85 days to go
76 Participants
170 Submissions
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Brief

Welcome to the Air Pollution Prediction Challenge!

Air pollution remains one of the world’s most pressing public-health threats, contributing to millions of premature deaths each year. Understanding and anticipating how pollution levels change across space and time is essential for issuing timely health warnings, shaping urban policy, and helping communities respond to environmental risks.

In this competition, your mission is simple: build a model that predicts future air pollution measurements as accurately as possible. You’ll work with historical observations and contextual data to forecast unseen conditions. Submissions are evaluated based on prediction accuracy, and top-performing models will rise to the top of the leaderboard. Join us in developing data-driven tools for a cleaner, healthier future.

Prizes
  • 1st Prize: $1,500
  • 2nd Prize: $1,000
  • 3rd Prize: $500
Timeline
  • Competition Starts: 2025-06-06
  • Competition Ends: 2025-09-05
  • Winners Announced (Subject to change based on submission results): 2025-09-30
Data Breakdown

Air Quality Prediction Challenge

Your challenge in this competition is to predict air pollution levels at specific locations and times using spatial and temporal features. Can you build a model that accurately predicts air quality based on geographic coordinates and time patterns? Let's find out!

Data Breakdown:

Downloadable file "air_pollution_dataset.zip" includes the following files:

train.csv: file to train your machine learning model.

test.csv: This is the file you're going to make predictions on with your trained model and create a submission file.

submission_example.csv: example of the format that the submission file needs to be in to be properly scored.

Data Dictionary

  • id: Unique identifier for each observation
  • latitude: Geographic latitude coordinate (anonymized with deterministic jitter)
  • longitude: Geographic longitude coordinate (anonymized with deterministic jitter)
  • day_of_year: Day of the year (1-365, captures seasonal patterns)
  • day_of_week: Day of the week (0=Monday, 6=Sunday)
  • hour: Hour of the day (0-23, captures daily pollution cycles)
  • month: Month of the year (1-12, captures seasonal variations)
  • pollution_value: Target variable. Pollution level in the air.

Important Notes:

The submission file should follow the same format as the example file (submission_format.csv). It should contain two columns: id and pollution_value. The pollution_value should be a numeric (float) prediction.Submissions are evaluated by Root Mean Square Error (RMSE) - specifically, exp(-RMSE/100), where 100 is a scaling factor.

Final competition results are based on the Private Leaderboard results, and the winner will be the user at the top of the Private Leaderboard.

This dataset represents real-world air quality measurements from monitoring stations worldwide, making accurate predictions valuable for environmental and public health applications.

The use of any external dataset is not allowed. Please abide by the rules.

FAQs
Who do I contact if I need help regarding a competition?
For any inquiries, please contact us at [email protected]
How will I know if I've won?
If you are one of the top three winners for this competition, we will email you with the final result and information about how to claim your reward.
How can I report a bug?
Please shoot us an email at [email protected] with details and a description of the bug you are facing, and if possible, please attach a screenshot of the bug itself.
If I win, how can I receive my reward?
Prizes will be paid by bank transfer. If for some reason you are not able to accept payment by bank transfer, please let us know and we will do our best to accommodate your needs as possible.
Rules

1. This competition is governed by the following Terms of Participation. Participants must agree to and comply with these Terms to participate.

2. Users can make a maximum number of 5 submissions per day. If users want to submit new files after making 5 submissions in a day, they will have to wait until the following day to do so. Please keep this in mind when uploading a submission file. Any attempt to circumvent stated limits will result in disqualification.

3. The use of external datasets is not allowed.

4. It is not allowed to upload the competition dataset to other websites. Users who do not comply with this rule will be disqualified.

5. A competition prize will be awarded after we have received, successfully executed, and confirmed the validity of both the code and the solution (See 6.). Once winners are announced and our team reaches out to them, the winners must provide the following by September 20, 2025 to be qualified as a competition winner and receive their prize:
    a. All source files required to preprocess the data
    b. All source files required to build, train and make predictions with the model using the processed data
    c. A requirements.txt (or equivalent) file indicating all the required libraries and their versions as needed
    d. A ReadMe file containing the following:
        • Clear and unambiguous instructions on how to reproduce the predictions from start to finish including data pre-processing, feature extraction, model training, and predictions generation
        • Environment details regarding where the model was developed and trained, including OS, memory (RAM), disk space, CPU/GPU used, and any required environment configurations required to execute the code
        • Clear answers to the following questions:
            - Which data files are being used?
            - How are these files processed?
            - What is the algorithm used and what are its main hyperparameters?
            - Any other comments considered relevant to understanding and using the model

6. The submitted solution should be able to generate exactly the same output that gives the corresponding score on the leaderboard. If the score obtained from the code is different from what’s shown on the leaderboard, the new score will be used for the final rankings unless a logical explanation is provided. Please make sure to set the seed or random_state etc. so we can obtain the same result from your code. 

7. The final submission has to be selected manually before the end of the competition (you can select up to 2), or else it will be selected automatically based on your highest public score.

8. In order to be eligible for the prize, the competition winner must agree to transfer to the Host and the relevant transferee of rights in such Competition all transferable rights, such as copyrights, rights to obtain patents and know-how, etc. in and to all analysis and prediction results, reports, analysis and prediction model, algorithm, source code and documentation for the model reproducibility, etc., and the Submissions contained in the Final Submissions.

9. Any prize awards are subject to eligibility verification and compliance with these Terms of Participation. All decisions of bitgrit will be final and binding on all matters relating to this Competition.

10. Payments to winners may be subject to local, state, federal and foreign tax reporting and withholding requirements.

11. If two or more participants have the same score on the leaderboard, the participant who submitted the winning file first will be considered the winner.

12. All submissions must be made individually; no teams are allowed in this competition. Users who do not comply with this rule will be immediately disqualified in the case that we find the same or very similar scores and/or uploaded solutions.

13. If you have any inquiries about this competition, please don’t hesitate to reach out to us at [email protected]

New Submission
Step 1
Upload or drop your file
Upload or drop your csv file here.
Your submission should be in .csv format.
Step 2
Description
Briefly describe your submission (400 characters or less)
5 submission(s) left

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