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

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 (PM_2.5–10) and fine (PM_2.5) 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 PM_2.5 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 PM_2.5 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 PM_2.5 was 2.09, higher than the acceptable limit (HQ = 1). The total carcinogenic risk (CR) was 3.37 × 10⁻³ for PM_2.5, 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