PollutionMapper: Identifying Global Air Pollution Sources

Abstract

Air pollution adversely impacts public health. The National Capital Region (Delhi-NCR) is among the most polluted urban areas in the world. One component of air pollution is PM2.5, which accounts for around 80% of deaths due to air pollution. Solutions for lowering PM2.5 levels in Delhi have been ineffective due to their unscientific design. In this paper, we build a mixed-methods model that captures the interplay of various factors—geographical, chemical, meteorological—that contribute to the concentration of PM2.5. Using domain knowledge and KDE sampling from NASA’s GEOS-CF dataset, we identify the major sources of each of the seven constituents of PM2.5. From the 68 sources thus selected, we run the NOAA’s HYSPLIT wind dispersion model to track the movement of released particles to the sink, i.e., Delhi. Using the concentration of pollutants at the sources and by tracking their movement, we can predict the PM2.5 levels at the sink and identify polluting sources. Our model performed significantly better than the baseline fixed-effects model and captured seasonal variations in all seven constituents of PM2.5. It also uncovered the impact of polluting sources hundreds of kilometers away on the air of Delhi. Policymakers can use such a model to design data-driven policy interventions.