A novel method to analyze the spatial distribution and potential sources of pollutant combinations in the soil of Beijing urban parks. (1st September 2021) - Liu, Qiyuan; Wu, Yihang; Zhou, Yongzhang; Li, Xingyuan; Yang, Shuhui; Chen, Yixiang; Qu, Yajing; Ma, Jin
Abstract: Organic and inorganic pollutants are often co-sedimentary in soils and have the same sources in the urban environment. The identification of the sources and distribution of combined pollutants is a basic step in risk management. In this study, the levels of polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) were measured in urban park soils in Beijing. Bivariate local Moran's I and positive matrix factorization (PMF) source apportionment were used to identify the spatial clustering patterns and potential sources of PAHs and HMs, as well as to ultimately define a pollution risk control area. The results revealed an obvious clustered distribution of PAHs and HMs in the park soils. High-high areas were defined as sites containing a complex mixture of pollutants, which were mainly located in the center and north of Beijing. High-low and low-high areas were located outside the city center but had the potential for combined pollution, and therefore require continuous attention. Bivariate local indicators of spatial association (LISA) enabled a more accurate analyses of the mechanism controlling the spatial distribution of PAH and HM combinations in urban parks. The source apportionment indicated that industrial and traffic emissions were the most important sources of the pollutant combinations in urban parks, with traffic emissions accounting for most of the pollution. Graphical abstract: Image 1 Highlights: PAHs and heavy metals were co-sedimentary in urban park soils of Beijing. An obvious clustered distribution of combined PAHs and HMs was observed. Hot spots of high PAHs and high heavy metals mainly occurred in the city center. Traffic emissions are important conjoint sources of PAHs and heavy metals. LISA is a useful tool to identify spatial clustering patterns of PAHs and HMs.