Author/Authors :
Lung، نويسنده , , Shih-Chun Candice and Hsiao، نويسنده , , Pao-Kuei and Wen، نويسنده , , Tzu-Yao and Liu، نويسنده , , Chun-Hu and Fu، نويسنده , , Chi Betsy and Cheng، نويسنده , , Yu-Ting، نويسنده ,
Abstract :
Asian residential communities are usually dotted with various spot pollution sources (SPS), such as restaurants, temples, and home factories, with traffic arteries passing through, resulting in higher intra-urban pollution variability compared with their western counterparts. Thus, it is important to characterize spatial variability of pollutant levels in order to assess accurately residentsʹ exposures in their communities. The objectives of this study are to assess the actual pollutant levels and variability within an Asian urban area and to evaluate the influence of vehicle emission and various SPS on the exposure levels within communities. Real-time monitoring was conducted for a total of 123 locations for particulate matter (PM) and CO in Taipei metropolitan, Taiwan. The mean concentrations for PM1, PM2.5, PM10, and CO are 29.8 ± 22.7, 36.0 ± 25.5, 61.9 ± 35.0 μg m−3 and 4.0 ± 2.5 ppm, respectively. The mean values of PM1/PM2.5 and PM2.5/PM10 are 0.80 ± 0.10 and 0.57 ± 0.15, respectively. PM and CO levels at locations near SPS could be increased by 3.5–4.9 times compared with those at background locations. Regression results show that restaurants contribute significantly 6.18, 6.33, 7.27 μg m−3, and 1.64 ppm to community PM1, PM2.5, PM10, and CO levels, respectively; while the contribution from temples are 13.2, 15.1, and 17.2 μg m−3 for PM1, PM2.5 and PM10, respectively. Additionally, construction sites elevate nearby PM10 levels by 14.2 μg m−3. At bus stops and intersections, vehicle emissions increased PM1 and PM2.5 levels by 5 μg m−3. These results demonstrate significant contribution of community sources to air pollution, and thus the importance of assessing intra-community variability in Asian cities for air pollution and health studies. The methodology used is applicable to other Asian countries with similar features.
Keywords :
Asian cooking emission , Temple emission , Traffic emission , Community air pollution , Aerosol size distribution