Quantitative assessment of ecological risk from pollution source based on geostatistical analysis and APCS-MLR model

被引:2
|
作者
Liu H. [1 ]
Ma J. [1 ]
Taj R. [3 ]
Xu M. [4 ]
Lou F. [4 ]
Liu W. [1 ]
Xu Y. [1 ]
Xu J. [1 ]
Xu Y. [1 ]
Liu D. [1 ]
机构
[1] F University, Zhejiang, Hangzhou
[2] Institute of Chemical Sciences, University of Peshawar, Peshawar
[3] Chengbang Ecoenvironment Co., Ltd., Hangzhou
[4] State Key Laboratory of Subtropical Silviculture, Key Laboratory of Soil Contamination Bioremediation of Zhejiang Province
[5] F University, Zhejiang, Hangzhou
关键词
APCS-MLR; Geostatistical analysis; Heavy metal; Pollution sources;
D O I
10.1007/s11356-024-33258-1
中图分类号
学科分类号
摘要
The safety of human health and agricultural production depends on the quality of farmland soil. Risk assessment of heavy metal pollution sources could effectively reduce the hazard of soil pollution from various sources. This study has identified and quantitatively analyzed pollution sources with geostatistical analysis and the APCS-MLR model. The potential ecological risk index was combined with the APCS-MLR model which has quantitatively calculated the source contribution. The results revealed that As, Cr, Cd, Pb, Zn, and Cu were enriched in soil. Geostatistical analysis and the APCS-MLR model have apportioned four pollution sources. The Mn and Ni were attributed to natural sources; As and Cr were from agricultural activities; Cu and Zn were originated from natural sources; Cd and Pb were derived from atmospheric deposition. Atmospheric deposition and agricultural activities were the largest contributors to ecological risk of heavy metals in soil, which accounted for 56.21% and 36.01% respectively. Atmospheric deposition and agricultural activities are classified as priority sources of pollution. The combination of source analysis receptor model and risk assessment is an effective method to quantify source contribution. This study has quantified the ecological risks of soil heavy metals from different sources, which will provide a reliable method for the identification of primary harmfulness sources of pollution for future studies. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
引用
收藏
页码:34953 / 34961
页数:8
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