Health risk assessment based on source identification of heavy metals: A case study of Beiyun River, China

Abstract

Long-term retention and accumulation of heavy metals in rivers pose a great threat to the stability of ecosystems and human health. In this study, Beiyun River was taken as the example to quantitatively identify pollution sources and assess the pollution source-oriented health risk. A total of 8 heavy metals (Mn, Ni, Pb, Zn, As, Cr, Cd, and Cu) in Beiyun River were measured. Ordinary kriging (OK) and inverse distance weight (IDW) methods were used to predict the distribution of heavy metals. The results showed that the OK method is more accurate, and heavy metal pollution in the midstream and downstream is much more serious than that in the upstream. Principal component analysis-multiple linear regressions (PCA-MLR) and positive matrix factorization (PMF) methods were used to quantitatively identify pollution sources. The coefficient of determination (R2) of PMF is closer to 1, and the analyzed pollution source is more refined. Furthermore, the result of source identification was imported into the health risk assessment to calculate the hazard index (HI) and carcinogenic risk (CR) of various pollution sources. The results showed that the HI and CR of As and Ni to local residents were serious in the Beiyun River. Industrial activities (23.0%) are considered to be the largest contribution of heavy metals in Beiyun River, followed by traffic source (17%), agricultural source (16%), and atmospheric deposition (16%). The source-oriented risk assessment indicated that the largest contribution of HI and CR is agricultural source in the Beiyun River, followed by industrial activities. This study provides a "target" for the precise control of pollution sources, which is of great significance for improving the fine management of the water environment in the basin.