Soil type data provide new methods and insights for heavy metal pollution assessment and driving factors analysis

Zhou，Wentao1; Li，Zhen2; Liu，Yunjia1; Shen，Chongyang1; Tang，Huaizhi1; Huang，Yuanfang1

2024-12-05

10.1016/j.jhazmat.2024.135868

Journal of Hazardous Materials   影响因子和分区

0304-3894

1873-3336

Assessing heavy metal pollution and understanding the driving factors are crucial for monitoring and managing soil pollution. This study developed two modified assessment methods (NIPI and NECI) based on soil type-specific background values and pollution indices, and combined them with the receptor model to evaluate pollution status. Additionally, a structural equation model was used to analyze the driving factors of soil heavy metal pollution. Results showed that the average NIPI and NECI were 1.48 and 0.92, respectively, indicating a low pollution risk level. In some areas, Cd and Hg were the primary heavy metals contributing to pollution risk, with their highest average concentrations exceeding soil type-specific background values by 2.06 and 2.04 times, respectively. Additionally, in black soils, meadow soils, and chernozems, heavy metals primarily originated from natural sources, accounting for 48.92 %, 45.98 %, and 45.58 %, respectively. In aeolian soils, agricultural sources were predominant, contributing 43.38 %. Soil pH and organic matter were key soil properties affecting NECI and NIPI, with direct effects of 0.36 and −0.19, respectively. This study aims to provide new methods and insights for the comprehensive assessment and driving factors analysis of soil heavy metal pollution, with the goal of enhancing pollution monitoring and reducing risk.

Nemerow index Risk assessment Soil environmental capacity Source apportionment Structural equation model

英语

其他

2-s2.0-85204899909

Scopus

1.College of Land Science and Technology,China Agricultural University,Beijing,100193,China
2.School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Zhou，Wentao,Li，Zhen,Liu，Yunjia,et al. Soil type data provide new methods and insights for heavy metal pollution assessment and driving factors analysis[J]. Journal of Hazardous Materials,2024,480.

Zhou，Wentao,Li，Zhen,Liu，Yunjia,Shen，Chongyang,Tang，Huaizhi,&Huang，Yuanfang.(2024).Soil type data provide new methods and insights for heavy metal pollution assessment and driving factors analysis.Journal of Hazardous Materials,480.

Zhou，Wentao,et al."Soil type data provide new methods and insights for heavy metal pollution assessment and driving factors analysis".Journal of Hazardous Materials 480(2024).