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A joint method to quantify source contributions of heavy metals to ecological and human health risks in oasis farmland soil
Author(s) -
Tian Jing,
Guan Qingyu,
Shao Wenyan,
Liu Zhan,
Ma Yunrui,
Li Huichun,
Sun Yunfan
Publication year - 2021
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.1002/saj2.20287
Subject(s) - environmental science , pollution , apportionment , risk assessment , health risk assessment , human health , nonpoint source pollution , coal , risk analysis (engineering) , environmental health , environmental protection , environmental engineering , ecology , waste management , computer science , business , engineering , biology , medicine , computer security , political science , law
Source identification and risk assessment of heavy metals are ongoing hot topics in current research, but few studies have been performed on the linkage mechanism between them. In the past, the amount of heavy metals discharged was the identification criterion for high‐risk source but failed to consider different toxicity of heavy metals in the risk level of each pollution source. Therefore, it is impossible to accurately determine high‐risk pollution source. For this situation, this study introduced a risk assessment model based on the source apportionment model, which can quantitatively analyze the source‐based risk. Meanwhile, pollution assessment indexes and a risk assessment model were applied to evaluate the levels of pollution and risk of heavy metals, showing that lead (Pb) caused relatively serious pollution and arsenic (As) generated the highest ecological risk and noncarcinogenic risk. Positive matrix factorization (PMF) model identified and quantified the sources of heavy metals (coal‐related activities source, mixed source of mining and traffic emissions, industrial activity source, agricultural source related to the application of agrochemicals) with the corresponding contributions of 42, 30, 26, and 2%, respectively. Then PMF was combined with potential ecological risk index and human health risk assessment model to quantify the risk from pollution sources, indicating that the coal‐related activities source was the largest pollution source (31–36%) that caused human health risks, while the mixed source of mining and transportation emissions posed the greatest threat (29%) to the ecosystem health. Therefore, both sources should be identified as the priority pollution sources.