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Volume 6, No. 4, December 2006, Pages 380-396 PDF(252 KB)  
doi: null   

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

Tai-Yi Yu1, Yu-Chun Chiang2, Chung-Shin Yuan3, Chung-Hsuang Hung4

1 Ming Chuan University, Department of Risk Management and Insurance, 250 Chun Shan N. Rd. Sec. 5, Taipei 111, Taiwan
2 Yuan Ze University, Department of Mechanical Engineering, 135 Yuan-Tung Rd., Chung-Li, Taoyuan 320, Taiwan
3 National Sun Yat-Sen University, Graduate Institute of Environmental Engineering, 70 Lien-hai Rd., Kaohsiung 804, Taiwan
4 National Kaohsiung First University of Science & Tech., Department of Safety Health and Environmental Engineering, 2 Juoyue Rd., Kaohsiung 811, Taiwan




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.



Keywords: Road flushing and sweeping; Factor analysis; Receptor modeling; ISCST3 model.



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