Air quality deterioration due to vehicular emissions in smaller Indian cities and rural areas remains unacknowledged, even though the situation is alarmingly similar to megacities. The resulting lack of knowledge on travel behavior and vehicle characteristics impacts accuracy of emission studies in these regions. This study uses a novel approach and appropriate primary and secondary data sets to allocate vehicular activities (vehicle population and vehicle kilometer travelled) and associated emissions at a high spatial resolution for estimation and dispersion analysis of vehicular exhaust and non-exhaust PM2.5 emission in an Indian urban-rural landscape. The study indicates that using approaches that do not allocate vehicles kilometers travelled to areas of their expected travel results in underestimating the percent share of PM2.5 emissions from rural roads and motorways while overestimating overall PM2.5 emissions. Particulate matter resuspension is the dominant form of PM2.5 emissions from the vehicular sector on all road types, constituting an even higher fraction on rural roads. Two-wheelers contribute a high fraction of PM2.5 emissions (exhaust and non-exhaust combined), followed by heavy commercial vehicles and four-wheelers on urban roads. Light commercial vehicles, especially agricultural tractors dominate these emissions on rural roads. PM2.5 hotspots are prevalent in urban areas, but several rural areas also experience heavy particulate matter concentrations. Thus, vehicle movement incorporation results in more accurate emission estimation, especially in an urban-rural landscape.
Keywords: Emission inventory; PM(2.5) emission; Particulate matter dispersion; Urban and rural air pollution; Vehicle trip simulation; Vehicular air pollution.
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