<p>In agricultural basins, the dissolved heavy metal(loid)s (DHMs) are usually derived from diverse sources, including natural processes, agricultural inputs, and non-agricultural human activities. Assessing the potential human health risks posed by DHMs and quantifying the contributions of these sources to DHMs are essential for effective water environment management in agricultural basins. This study took an agricultural basin of Chongqing, China as a case study. Eight DHMs (Cr, Mn, Ni, Cu, Zn, As, Cd, Pb) of river water at 42 sampling sites were investigated. Results showed that while non-carcinogenic health risks from all DHMs were within acceptable levels, arsenic (As) posed a potentially high carcinogenic risk (CR) to both children and adults, with mean CR values exceeding 1.00E-04. Source apportionment using absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models identified three and five potential sources of DHMs, respectively. Despite it is a basin dominated by agricultural land use, industrial activities were the largest contributor to DHMs, accounting for 29.45% of the total, followed by traffic emissions (22.88%), natural sources (19.45%), agricultural activities (15.16%), and mixed agricultural-industrial sources (13.08%). The PMF model demonstrated greater reliability for DHMs source analysis compared to the APCS-MLR model in this study. These findings can provide scientific support for the sustainable and effective management of water environments in agricultural basins affected by complex pollution sources.</p> Graphical Abstract <p></p>

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Health Risk Assessment and Source Identification of Dissolved Heavy Metal(loid)s in an Agricultural Basin of Chongqing, China

  • Xian Cheng,
  • Yue Mu

摘要

In agricultural basins, the dissolved heavy metal(loid)s (DHMs) are usually derived from diverse sources, including natural processes, agricultural inputs, and non-agricultural human activities. Assessing the potential human health risks posed by DHMs and quantifying the contributions of these sources to DHMs are essential for effective water environment management in agricultural basins. This study took an agricultural basin of Chongqing, China as a case study. Eight DHMs (Cr, Mn, Ni, Cu, Zn, As, Cd, Pb) of river water at 42 sampling sites were investigated. Results showed that while non-carcinogenic health risks from all DHMs were within acceptable levels, arsenic (As) posed a potentially high carcinogenic risk (CR) to both children and adults, with mean CR values exceeding 1.00E-04. Source apportionment using absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models identified three and five potential sources of DHMs, respectively. Despite it is a basin dominated by agricultural land use, industrial activities were the largest contributor to DHMs, accounting for 29.45% of the total, followed by traffic emissions (22.88%), natural sources (19.45%), agricultural activities (15.16%), and mixed agricultural-industrial sources (13.08%). The PMF model demonstrated greater reliability for DHMs source analysis compared to the APCS-MLR model in this study. These findings can provide scientific support for the sustainable and effective management of water environments in agricultural basins affected by complex pollution sources.

Graphical Abstract