Estimation of Enhancing Improvement for Ambient Air-Quality during Street Flushing and Sweeping

[[abstract]]This investigation addressed the source apportionment of aerosol particles using both the receptor and dispersion models. Factor analysis and chemical mass balance (CMB) models were two receptor modeling techniques employed to categorize the possible sources in Kaohsiung district. The ISCST3 dispersion model was also used to evaluate improvements in ambient-air quality. Factor analysis revealed that road sweeping resulted in a variation of approximately 10% in the compositions of TSP and PM10. The mass fractions of TSP explained by the CMB model were 60-70% before flushing, 35-37% after flushing, 71-83% before sweeping, and 80-120% after sweeping. The CMB method identified six possible sources of TSP as: combustion sources (53.2 ± 11.1%), street dust (12.4 ± 9.3%), nitrate (4.9 ± 1.2%), sulfate (2.9 ± 0.8%), sea salt (1.0 ± 0.3%), and gasoline cars (0.4 ± 0.6%). The simulation results of ISCST3 model showed that road flushing improved annual PM10 from 1.5-2.1% at the 11 monitoring stations operated around Kaohsiung City. After road flushing, the ratios and concentrations of TSP for street dust and combustion sources were reduced. For TSP, road sweeping increased the concentrations of street dust within 30 m downwind of the sampling sites (both sites located downwind at 5 and 30 meters); but reduced it at 200 m downwind. Factor analysis showed rates of street dust for TSP were lower than 28% before street sweeping; lower than 17% after street sweeping. The CMB model revealed that contributed rates of street dust for TSP were lower than 22% before street sweeping, and lower than 34% after street sweeping. The ISCST3 model showed air quality improvements for PM10 in urban areas were greater than in industrial areas. Moreover, the maximum improvement in the annual mean PM10 was around 2 μg/m3