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Volume 18, issue 3 | Copyright

Special issue: Regional transport and transformation of air pollution in...

Atmos. Chem. Phys., 18, 2049-2064, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 13 Feb 2018

Research article | 13 Feb 2018

High-resolution sampling and analysis of ambient particulate matter in the Pearl River Delta region of southern China: source apportionment and health risk implications

Shengzhen Zhou1,2, Perry K. Davy3, Minjuan Huang1, Jingbo Duan4, Xuemei Wang1,5, Qi Fan1, Ming Chang5, Yiming Liu1, Weihua Chen1, Shanju Xie6, Travis Ancelet3, and William J. Trompetter3 Shengzhen Zhou et al.
  • 1School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, 510275, China
  • 2Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou 510275, China
  • 3National Isotope Centre, Institute of Geological and Nuclear Sciences, 30 Gracefield Road, P.O. Box 31312, Lower Hutt, New Zealand
  • 4Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, 350 Shu Shan Hu Road, Hefei, Anhui 230031, China
  • 5Institute for Environment and Climate Research, Jinan University, Guangzhou, China
  • 6Auckland Council, Auckland, New Zealand

Abstract. Hazardous air pollutants, such as trace elements in particulate matter (PM), are known or highly suspected to cause detrimental effects on human health. To understand the sources and associated risks of PM to human health, hourly time-integrated major trace elements in size-segregated coarse (PM2.5–10) and fine (PM2.5) particulate matter were collected at the industrial city of Foshan in the Pearl River Delta region, China. Receptor modeling of the data set by positive matrix factorization (PMF) was used to identify six sources contributing to PM2.5 and PM10 concentrations at the site. Dominant sources included industrial coal combustion, secondary inorganic aerosol, motor vehicles and construction dust along with two intermittent sources (biomass combustion and marine aerosol). The biomass combustion source was found to be a significant contributor to peak PM2.5 episodes along with motor vehicles and industrial coal combustion. Conditional probability function (CPF) analysis was applied to estimate the source locations using the PMF-resolved source contribution coupled with the surface wind direction data. Health exposure risk of hazardous trace elements (Pb, As, Si, Cr, Mn and Ni) and source-specific values were estimated. The total hazard quotient (HQ) of PM2.5 was 2.09, higher than the acceptable limit (HQ =1). The total carcinogenic risk (CR) was 3.37 × 10−3 for PM2.5, which was 3 times higher than the least stringent limit (1.0 × 10−4). Among the selected trace elements, As and Pb posed the highest non-carcinogenic and carcinogenic risks to human health, respectively. In addition, our results show that the industrial coal combustion source is the dominant non-carcinogenic and carcinogenic risk contributor, highlighting the need for stringent control of this source. This study provides new insight for policy makers to prioritize sources in air quality management and health risk reduction.

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We collected hourly samples of PM2.5 and PM2.5–10 at an industrial city in the PRD, China. The samples were analyzed for black carbon and elemental compositions. Receptor modeling of the dataset by positive matrix factorization was used to identify PM sources. Human health exposure risks to the selected trace elements in PM released from the specific sources were estimated. The source–risk apportionment method helps decision makers to manage air quality more effectively.
We collected hourly samples of PM2.5 and PM2.5–10 at an industrial city in the PRD, China. The...