摘要
Hourly PM2.5 concentrations were observed simultaneously at a cities-cluster comprising 10 cities/towns in Hebei province in China from July 1 to 31, 2008. Among the 10 cities/towns, Baoding showed the high- est average concentration level （161.57μg/m3） and Yanjiao exhibited the lowest （99.35 μg/m3 ）. These observed data were also studied using the joint potential source contribution function with 24-h and 72-h backward trajectories, to identify more clearly the local and countrywide-scale long-range transport sources. For the local sources, three important influential areas were found, whereas five important influential areas were defined for long-range transport sources. Spatial characteristics of PM2.5 were determined by multivariate statistical analyses. Soil dust, coal combustion, and vehicle emissions might be the potential contributors in these areas. The results of a hierarchical cluster analysis for back trajectory endpoints and PM2.s concentrations datasets show that the spatial characteristics of PM2.5 in the cities-cluster were influenced not only by local sources, but also by long-range transport sources. Different cities in the cities-cluster obtained different weighted contributions from local or long-range transport sources. Cangzhou, Shijiazhuang, and Baoding are near the source areas in the south of Hebei province, whereas Zhuozhou, Yangfang, Yanjiao, Xianghe, and Langfang are close to the sources areas near Beijing and Tianjin.
Hourly PM2.5 concentrations were observed simultaneously at a cities-cluster comprising 10 cities/towns in Hebei province in China from July 1 to 31, 2008. Among the 10 cities/towns, Baoding showed the high- est average concentration level （161.57μg/m3） and Yanjiao exhibited the lowest （99.35 μg/m3 ）. These observed data were also studied using the joint potential source contribution function with 24-h and 72-h backward trajectories, to identify more clearly the local and countrywide-scale long-range transport sources. For the local sources, three important influential areas were found, whereas five important influential areas were defined for long-range transport sources. Spatial characteristics of PM2.5 were determined by multivariate statistical analyses. Soil dust, coal combustion, and vehicle emissions might be the potential contributors in these areas. The results of a hierarchical cluster analysis for back trajectory endpoints and PM2.s concentrations datasets show that the spatial characteristics of PM2.5 in the cities-cluster were influenced not only by local sources, but also by long-range transport sources. Different cities in the cities-cluster obtained different weighted contributions from local or long-range transport sources. Cangzhou, Shijiazhuang, and Baoding are near the source areas in the south of Hebei province, whereas Zhuozhou, Yangfang, Yanjiao, Xianghe, and Langfang are close to the sources areas near Beijing and Tianjin.
基金
supported by the "Strategic Priority Research Program (B)" of the Chinese Academy of Sciences (XDB05030103)
the National Natural Science Foundation of China (71103098 and 21207070)
the Fundamental Research Funds for the Central Universities and the Combined Laboratory of the Tianjin Meteorological Bureau
