Analysing Urban Air Pollution Using Low-Cost Methods and Community Science

Abstract

Rise in air pollution resulting in negative health externalities for humans has created an urgent need for cities and communities to monitor it regularly. At present we have insufficient ground passive and active monitoring networks in place which presents a huge challenge. Satellite imagery has been used extensively for such analysis, but its resolution and methodology present other challenges in estimating pollution burden. The objective of this study was to propose three low-cost methods to fill in the gaps that exist currently. First, EPA grade sensors were used in 11 cities across the U.S. to examine NO2. This is a simplistic way to assess the burden of air pollution in a region. However, this technique cannot be applied to fine scale analysis, which resulted in the next two components of this research study. Second, a citizen science network was established on the east side of Indianapolis, IN who hosted 32 Ogawa passive sensors to examine NO2 and O3 at a finer scale. These low-cost passive sensors, not requiring power, and very little maintenance, have historically tracked very closely with Federal Reference Monitors. Third, a low-cost PurpleAir PA-II-SD active sensors measuring PM2.5 were housed with the citizen scientists identified above. This data was uploaded via Wi-Fi and available via a crowd sourced site established by PurpleAir. These data sets were analyzed to examine the burden of air pollution. The second and third research studies enabled granular analyses utilizing citizen science, tree canopy data, and traffic data, thus accommodating some of the present limitations. Advancement in low-cost sensor technology, along with ease of use and maintenance, presents an opportunity for not just communities, but cities to take charge of some of these analyses to help them examine health equity impacts on their citizens because of air pollution.