Search

PM 2.5 in Shijiazhuang was collected from October 15, 2018 to January 31, 2019, and selected toxic elements were measured. Five typical haze episodes were chosen to analyze the health risks and critical risk sources. Toxic elements during the haze episodes accounted for 0.33% of PM 2.5 mass. Non-cancer risk of toxic elements for children was 1.8 times higher than that for adults during the haze episodes, while cancer risk for adults was 2.5 times higher than that for children; cancer and non-cancer risks were primarily attributable to As and Mn, respectively. Health risks of toxic elements increased during the growth and stable periods of haze episodes. Non-cancer and cancer risks of toxic elements during the haze stable periods were higher than other haze stages, and higher for children than for adults during the stable period. Mn was the largest contributor to non-cancer risk during different haze stages, while As was the largest contributor to cancer risk. Crustal dust, vehicle emissions, and industrial emissions were critical sources of cancer risk during the clean-air periods; while vehicle emissions, coal combustion, and crustal dust were key sources of cancer risk during the haze episodes. Cancer risks of crustal dust and vehicle emissions during the haze episodes were 2.0 and 1.7 times higher than those in the clean-air periods. Non-cancer risks from emission sources were not found during different periods. Cancer risks of biomass burning and coal combustion increased rapidly during the haze growth period, while that of coal combustion decreased sharply during the dissipation period. Vehicle emissions, crustal dust, and coal combustion were significant cancer risk sources during different haze stages, cancer risk of each source was the highest during the stable period. Southern Hebei, Northern and central Shaanxi were potential risk regions that affected the health of both adults and children in Shijiazhuang. [Display omitted] • The highest health risk come from As and Mn during the haze episodes. • Health risks of toxic elements during the haze stable period were the highest. • Vehicle and coal combustion were critical cancer risk sources in the haze episodes. • Cancer risk of crustal dust in haze episodes was 2.0 times that in clean-air periods. [ABSTRACT FROM AUTHOR]

With the intensification of Chinese source control of air pollution, there is an urgent need for refined and rapid source apportionment techniques. A refined source apportionment method was constructed based on an off-line sampling dataset using a receptor model coupled with a source-oriented model, and the method was implemented in Shijiazhuang during the heating period. The refined results for source apportionment mainly included temporal, spatial, and source-category refinement data. The results indicated that the mean concentration of PM 2.5 during the heating period was 96 μg/m3. Organic carbon (OC) and NO 3 − were found to be the dominant species of PM 2.5 during the study. A high correlation was detected between elemental carbon (EC) and NO 3 − on polluted days, which was suggestive of the stagnant condition that accumulates EC and nitrate simultaneously. Secondary particle formation greatly promoted the occurrence of haze events. Secondary sources (34.9%), vehicle exhaust (18.6%), coal combustion (20.0%), industrial emissions (9.2%), crustal dust (9.7%), and biomass burning (7.6%) were the major sources during the heating period. The contributions of secondary sources and vehicle exhaust increased on polluted days, while those of coal combustion, industrial emissions and crustal dust decreased significantly. The contribution percentage of secondary sources from the southeast direction was basically the highest, while those of vehicle exhaust from the northwest or southeast directions were relatively higher as well, likely due to the distribution of traffic arteries. Based on the refined results for the source-category assessment, we found that the heating boilers (17.0%), non-road mobile (13.8%), diesel vehicles (10.4%), residential combustion (6.7%), road dust (5.5%), and architectural material industry (4.9%) were the major contributors to PM 2.5. There was some uncertainty in the distribution proportions of the refined results, which were derived based on the emission inventory and the results of CALPUFF model. • A refined source apportionment method for ambient PM 2.5 was constructed. • Contributions of secondary sources and vehicle exhaust increased on polluted days. • Heating boilers, non-road mobile, and diesel vehicles were major contributors. [ABSTRACT FROM AUTHOR]