Identification priority source of soil heavy metals pollution based on source-specific ecological and human health risk analysis in a typical smelting and mining region of South China

Abstract

An in-depth understanding of the ecological and health risks posed by heavy metals originating from various pollution sources is critical for foresighted soil-quality management. Based on 220 grid samples (2 × 2 km) analyzed for eight heavy metals (Cd, Hg, As, Pb, Cr, Ni, Cu, and Zn) in the Chenshui (CS) watershed of Hunan Province, China, we applied an integrated approach for identifying and apportioning pollution sources of soil heavy metals and exploring their source-specific pollution risks. This approach consists of three sequential steps: (1) source identification by combining the positive matrix factorization model with geostatistical analysis; (2) quantification of ecological, carcinogenic, and non-carcinogenic risks in a source-specific manner; (3) prioritization of sources in a holistic manner, considering both ecological risks and human health risks. Cd (68.0%) and Hg (13.3%) dominated the ecological risk in terms of ecological risk index; As dominated the non-carcinogenic health risk in terms of total hazard index (THI; adults: 84.8%, children: 84.7%) and the carcinogenic health risk in terms of total carcinogenic risk index (TCRI; adults: 69.0%, children: 68.8%). Among three exposure routes, oral ingestion (89.4-95.2%) was the predominant route for both adults and children. Compared with adults (THI = 0.41, TCRI = 7.01E-05), children (THI = 2.81, TCRI = 1.22E-04) had greater non-carcinogenic and carcinogenic risks. Four sources (F1-4) were identified for the CS watershed: atmospheric deposition related to coal-burning and traffic emissions (F1, 18.0%), natural sources from parent materials (F2, 34.3%), non-ferrous mining and smelting industry (F3, 37.9%), and historical arsenic-related activity (F4, 9.8%). The F3 source contributed the largest (45.2%) to the ecological risks, and the F4 source was the predominant contributor to non-carcinogenic (52.4%) and carcinogenic (64.6%) risks. The results highlight the importance of considering legacy As pollution from abandoned industries when developing risk reduction strategies in this region. The proposed methodology for source and risk identification and apportionment formulates the multidimensional concerns of pollution and the various associated risks into a tangible decision-making process to support soil pollution control.

Keywords: Legacy Arsenic pollution; Positive matrix factorization; Risk quantification; Source apportionment.