Pinpointing sources of pollution using citizen science and hyperlocal low-cost mobile source apportionment

Area of Science:

• Environmental Science
• Public Health
• Urban Planning

Background:

• Traditional air pollution source identification is costly and limited in scope.
• Existing monitoring networks often lack the spatiotemporal resolution to capture hyperlocal sources.
• Understanding local air quality impacts is crucial for public health in densely populated areas.

Purpose of the Study:

• To present a novel, cost-effective methodology for identifying and apportioning air pollution sources.
• To assess the contribution of local versus regional sources to air pollution in Birmingham, UK.
• To demonstrate the potential of citizen science in enhancing urban air quality monitoring.

Main Methods:

• Utilized mobile sensor measurements collected by citizen scientists during daily walks.
• Applied data analysis to pinpoint distinct pollution sources affecting local air quality in a high-density urban area.
• Compared contributions of regional and local sources for various particulate matter fractions (PM2.5, PM1, PM10), particle number, lung deposited surface area, and black carbon.

Main Results:

• Regional sources predominantly influenced PM2.5 and PM1 concentrations.
• Local sources were the main contributors to PM10.
• Traffic was the primary source for total particle number and lung deposited surface area of PM; black carbon was linked to urban background and local traffic.
• Hyperlocal sources, like traffic and construction, have a significant impact within a few hundred meters, affecting thousands in dense areas.

Conclusions:

• Citizen science-driven mobile monitoring offers a versatile and affordable alternative to traditional methods.
• This approach significantly enhances the spatiotemporal resolution of air quality data.
• Hyperlocal pollution sources, though short-range, pose a considerable risk to public health in urban environments.
• The study highlights limitations of current monitoring networks and proposes a more effective paradigm for understanding urban air quality.