Variability of intra-urban exposure to particulate matter and CO from Asian-type community pollution sources

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 residents' 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.

[1]  John D. Spengler,et al.  Characterizing local traffic contributions to particulate air pollution in street canyons using mobile monitoring techniques , 2011 .

[2]  Sharad Gokhale,et al.  Evaluating effects of traffic and vehicle characteristics on vehicular emissions near traffic intersections , 2009 .

[3]  Feifei Liu,et al.  Predictors of intra-community variation in air quality , 2012, Journal of Exposure Science and Environmental Epidemiology.

[4]  Ari B. Friedman,et al.  Spatial and temporal patterns of particulate matter sources and pollution in four communities in Accra, Ghana. , 2012, The Science of the total environment.

[5]  Shih-Chun Candice Lung,et al.  Residents' particle exposures in six different communities in Taiwan. , 2007, The Science of the total environment.

[6]  John D. Spengler,et al.  Modeling Spatial Patterns of Traffic-Related Air Pollutants in Complex Urban Terrain , 2011, Environmental health perspectives.

[7]  Christoph Schneider,et al.  Mobile measurements and regression modeling of the spatial particulate matter variability in an urban area. , 2012, The Science of the total environment.

[8]  R. Burnett,et al.  Spatial Analysis of Air Pollution and Mortality in Los Angeles , 2005, Epidemiology.

[9]  S. Lung,et al.  Generation rates and emission factors of particulate matter and particle-bound polycyclic aromatic hydrocarbons of incense sticks. , 2003, Chemosphere.

[10]  C. Liao,et al.  Heavy incense burning in temples promotes exposure risk from airborne PMs and carcinogenic PAHs. , 2006, The Science of the total environment.

[11]  Jiming Hao,et al.  Air pollutants in rural homes in Guizhou, China - Concentrations, speciation, and size distribution , 2010 .

[12]  Kiros Berhane,et al.  Childhood Incident Asthma and Traffic-Related Air Pollution at Home and School , 2010, Environmental health perspectives.

[13]  W James Gauderman,et al.  Childhood Asthma and Exposure to Traffic and Nitrogen Dioxide , 2005, Epidemiology.

[14]  S. Lung,et al.  Inequality of Asian-type neighborhood environmental quality in communities with different urbanization levels , 2014 .

[15]  Bert Brunekreef,et al.  Air pollution from traffic and the development of respiratory infections and asthmatic and allergic symptoms in children. , 2002, American journal of respiratory and critical care medicine.

[16]  Ari B. Friedman,et al.  Within-Neighborhood Patterns and Sources of Particle Pollution: Mobile Monitoring and Geographic Information System Analysis in Four Communities in Accra, Ghana , 2010, Environmental health perspectives.

[17]  Chih-Da Wu,et al.  Applying GIS and fine-resolution digital terrain models to assess three-dimensional population distribution under traffic impacts , 2012, Journal of Exposure Science and Environmental Epidemiology.

[18]  S. Lung,et al.  Worshippers’ Exposure to Particulate Matter in Two Temples in Taiwan , 2003, Journal of the Air & Waste Management Association.