Mercury (Hg) has always been a research hot spot because of its high toxicity. This study conducted in farmland near rare earth mining area and traffic facilities, which considered multiple pollution sources innovatively. It not only analyzed Hg spatial characteristics using inverse distance weighting and self-organizing map (SOM), but also assessed its pollution risk by potential ecological risk index (Er) as well as geoaccumulation index (Igeo), and identified the pollution sources with positive matrix factorization. The results showed that there was no heavy Hg pollution in most farmland, while a few sampling sites with Hg pollution were close to highway, railway station and petrol station in Xinfeng or in the farmland of Anyuan, which were divided into the cluster with highest Hg concentration in SOM. The vehicle exhaust emission and pesticide as well as fertilizer additions significantly contributed to the local Hg pollution. Besides, there was moderate pollution and high ecological risk in Anyuan assessed by Igeo and Er, respectively. In contrast, Xinfeng had the moderate and considerable ecological risks in a larger scale. The enriched Hg might harmed not only the nearby ecological environment, but also the human health when it entered human body through food chain. The three factors that contributed to mercury concentration in this area according to positive matrix factorization were natural source, traffic source and agricultural source, respectively. This study about Hg pollution in the typical area would provide scientific evidence for the particular treatment of Hg pollution from various pollution sources like traffic source, agricultural source, etc.
Keywords: Mercury pollution; Positive matrix factorization; Risk assessment; Self-organizing map; Source identification.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.