Antimony, beryllium, cobalt, and vanadium in urban park soils in Beijing: Machine learning-based source identification and health risk-based soil environmental criteria

Abstract

The pollution situation of antimony (Sb), beryllium (Be), cobalt (Co), and vanadium (V) is poorly understood, although they are widely used in daily life and production processes. Moreover, threshold levels (“soil environmental criteria”, SEC) for these pollutants are lacking in China, which impedes effective soil quality management. This study explored pollution characteristics for park soils in urban area of Beijing, China at first. Then multivariate statistical analysis and machine learning model were used to identify the main sources of pollutants. Additionally, probabilistic health risk and SEC were studied to assess the risks of pollutants and manage soil pollutants. The results revealed that the overall pollution levels of Be, Co, Sb, and V were low, but Be and Sb were enriched to varying degrees. Source apportionment showed that Sb (85.5%) was mainly derived from fuel combustion and industrial legacy, Co (66.7%) and V (82.5%) from natural processes, and Be from the natural background (39.3%) and anthropogenic sources (53.8%). Risk assessment indicated that the pollutants' carcinogenic and noncarcinogenic risks were negligible. Exposure frequency and soil ingestion rate were the most important parameters affecting health risks. The SEC of Be, Co, Sb, and V were 31, 39.7, 41.3, and 348 mg/kg, respectively, all of which are higher than the corresponding soil quality standards in China, indicating that current soil quality standards may be too conservative for urban park land. This study provides a reference for the management of soil pollutants in Beijing's urban parks, and the formulation of soil environmental quality standards.