Response surface modeling-based source contribution analysis and VOC emission control policy assessment in a typical ozone-polluted urban Shunde,China

To develop a sound ozone（O_3） pollution control strategy,it is important to well understand and characterize the source contribution due to the complex chemical and physical formation processes of O_3.Using the ＂Shunde＂ city as a pilot summer case study,we apply an innovative response surface modeling（RSM） methodology based on the Community Multi-Scale Air Quality（CMAQ） modeling simulations to identify the O_3 regime and provide dynamic analysis of the precursor contributions to effectively assess the O_3 impacts of volatile organic compound（VOC） control strategy.Our results show that Shunde is a typical VOC-limited urban O_3 polluted city.The ＂Jiangmen＂ city,as the main upper wind area during July 2014,its VOCs and nitrogen oxides（NO_x） emissions make up the largest contribution（9.06%）.On the contrary,the contribution from local（Shunde） emission is lowest（6.35%） among the seven neighbor regions.The local VOCs industrial source emission has the largest contribution comparing to other precursor emission sectors in Shunde.The results of dynamic source contribution analysis further show that the local NO_x control could slightly increase the ground O_3 under low（10.00%） and medium（40.00%）reduction ratios,while it could start to turn positive to decrease ground O_3 under the high NO_x abatement ratio（75.00%）.The real-time assessment of O_3 impacts from VOCs control strategies in Pearl River Delta（PRD） shows that the joint regional VOCs emission control policy will effectively reduce the ground O_3 concentration in Shunde.

Local and long-range transport influences on PM_(2.5) at a cities-cluster in northern China,during summer 2008

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.