Novel approaches to address air pollution using Activity data 

Abstract

Tackling air pollution and developing sustainable solutions in any region necessitates comprehensive local data, including air quality monitoring, emission inventories, and information on sources and activities contributing to air pollution. Addressing air pollution in these cities necessitates a multi-tiered approach at the regional, city, and neighborhood levels. However, obtaining air quality data at the neighborhood level is largely unavailable in developing countries like India. Relying on city or regional level data to comprehend the sources of air pollution at the neighborhood level is highly uncertain. To overcome this uncertainty and data scarcity, we designed some approaches at various levels which include air quality monitoring site selection, primary data collection to fill the gaps in secondary data, and high resolution (ward level) emission inventory.  The Clean Air Catalyst (CAC) program, led by the World Resources Institute (WRI) and Environmental Defense Fund (EDF), aims to build capacity for local air pollution solutions through source apportionment and emission inventory. To estimate emissions for the Central Indian city of Indore under the Clean Air Catalyst (CAC), we integrated available secondary data with a primary survey to address data gaps and validate the secondary information. Primary survey data, including household, industrial, and commercial energy consumption, as well as the number of employees in industries, was utilized to fill gaps in sectors such as households and industries. Secondary data sources, including time-use surveys, economic census, and the regular census, were employed for the household, construction, and eateries sectors. The Google Earth tool was employed to identify the locations of brick kilns in both Indore city and district. Additionally, secondhand car and bike seller databases were utilized to ascertain the age of vehicles and the type of fuel used in different vehicle categories. In sectors lacking available data, such as waste burning, a distance sampling approach was utilized to estimate the spatial frequency, volume, and composition of municipal solid waste (MSW) burning at the neighborhood and city scales. A similar method was applied to gather information about the fuel used and the types of eateries, aiding in estimating emissions from the eateries sector.   A novel methodology was used for air quality monitoring site selection for the Source apportionment study in the Indore city. The air monitoring site was selected using an integrated approach of secondary data, which along with meteorology, land use pattern, also include activity data, demography. The methodology was also validated using the modelling, satellite data, Aerosol optical depth (AOD), low-cost sensors (LCS), back trajectory.  The methodology employed in this study can be applied in cities where limited activity data from surveys are available. Utilizing activity data in monitoring site selection can reduce the uncertainty in air pollution source profiling discrepancies between source apportionment and emission inventory.