Solving air pollution mini-challenge

Analysis and Now Casting of Urban Air Pollution

Learning instruction: Please, read the task and follow the video introduction for challenge solving.

Task description

World Health Organization has worked to ensure that health-relevant indicators of household and ambient pollution exposure and disease burden are included in the formal system of SDG indicators. SDG targets of relevance to ambient and household air pollution include:

• SDG 3 – a substantial reduction in deaths and illnesses from air pollution;
• SDG 11 – to reduce the environmental impact of cities by improving air quality.

Report on SDG 11 contains data on annual air pollution in cities. Nonetheless, more granular data (for example, daily statistics) would be useful for urban citizens for the purpose of monitoring local situation as well as planning activities or travel trips.

Two variants of mini-challenge are available to choose from:

1. Finding dangerous pollution patterns. Analytics dashboard, visually summarizing historical tendencies of air pollution at a selected city. Solution should help to answer which months of the year and which days of the week have the largest levels of pollutants.
2. Analysis of historical patterns and forecasting pollution (for example, a week ahead). Analytics dashboard, allowing to make historical insights and forecast of air pollution at a selected city. Forecast should be obtained using multivariate model.

Participants should calculate Air Pollution Index (API) instead of Temperature-Humidity Index (THI).

API = MAX(PM10, PM2.5, NO2, O3, SO2, CO)

Final grade (100-point scale) composition:

• 40% = Moodle tests from learned topics with certainty-based marking (CBM);
• 20% = inside peer (team members) evaluation of a teamwork process result;
• 40% = outside peer (of other teams) evaluation of a mini-challenge solution.