Real-time source apportionment of fine particle inorganic and organic constituents at an urban site in Delhi city: An IoT-based approach

Abstract

An Internet of things (IoT) based real-time source apportionment methodology of PM2.5 aerosol was developed and demonstrated for an urban site in Delhi city, India. A dashboard was designed and developed to display in real-time the data from low-cost PM sensors, PM2.5 chemical speciation monitors data, and source apportionment results using a chemical mass balance (CMB) algorithm performed on an IoT platform. Ten source profiles were used in CMB modeling for the urban site of Delhi. Major contributing source categories were identified as biomass burning, soil dust, vehicle, coal combustion, waste burning, industries, and secondary aerosol. Biomass burning and secondary aerosol was a significant contributor in autumn and winter (23–30%), while soil dust exhibited highs during summer. The vehicle sources remained consistent over the year with an ∼8–12% contribution. Similarly, consistent seasonal contributions of waste burning, and industries were observed. Coal combustion was found to be a substantial contributor in Delhi during the monsoon and summer; primarily from regional power plants outside the Delhi region, and/or from smaller-scale industrial outfits in the vicinity of the Delhi region. Hourly resolved sources of fine particles were displayed in real-time on a customized dashboard. This is the first such demonstration of an IoT-based real-time source apportionment in India (and in many parts of the world). The approach developed could be a resource to identify and control emissions from local and regional sources in real-time, and actions to curtail air quality and health detriment in a scientifically sound manner.