Bottom-up and top-down approaches for estimating road dust emission and correlating it with a receptor model results over a typical urban atmosphere of Indo Gangetic Plain

Abstract

To investigate the emission and concentration of PM10 and PM2.5-related road dust over Agra, a typical semi-arid urban atmosphere of the Indo Gangetic Plain (IGP), a fine-resolution emission inventory and receptor modeling-based source apportionment was undertaken for the year 2019. On-road, the silt load of Agra (7–55 g/m2 of the road) was found to be 10 to 50 times higher than that reported in advanced countries. The silt load over Agra varied widely depending on road conditions, long-range transport, and land-use pattern. Depending on the silt load, land-use and fleet averaged weight, the annual emission factor for road dust was estimated as 14.3 ± 3.2 (PM10) and 4.4 ± 1.4 (PM2.5) gm/VKT (vehicle kilometer travel). PM10 emission of road dust alone contributed 80 % (29 ± 6 t/d) to the total emission of PM10 and 68 % (9 ± 3 t/d) to PM2.5 of the city with the maximum emission being in industrial areas. Chemical analysis of ambient PM10, PM2.5, and road dust samples showed that the road dust was enriched with geogenic components and was in good agreement with the road dust profile identified from the positive matrix factorization receptor model. The model estimated contribution of road dust (summer and winter combined) to PM10 and PM2.5 ambient air levels was 28 % (67 μg/m3) and 23 % (27 μg/m3) respectively. Summer showed a larger road dust contribution than winter due to strong surface wind and dry road conditions. Results have revealed that the emissions and concentrations of road dust are closely interrelated with road conditions (silt load), land-use patterns, VKT, weight of the vehicles, and micrometeorological conditions. The large road dust emission in IGP cities requires better road conditions and traffic management to curb the emission.