砷
环境科学
土壤科学
生态学
生物
化学
有机化学
作者
Yihang Huang,Naichi Zhang,Zixuan Ge,Chen Lv,Linfang Zhu,Changfeng Ding,Cun Liu,Pei-Qin Peng,Tongliang Wu,Yujun Wang
出处
期刊:Eco-environment & health
[Elsevier BV]
日期:2024-03-12
卷期号:3 (2): 238-246
被引量:9
标识
DOI:10.1016/j.eehl.2024.02.007
摘要
The establishment of ecological risk thresholds for arsenic (As) plays a pivotal role in developing soil conservation strategies. However, despite many studies regarding the toxicological profile of As, such thresholds varying by diverse soil properties have rarely been established. This study aims to address this gap by compiling and critically examining an extensive dataset of As toxicity data sourced from existing literature. Furthermore, to augment the existing information, experimental studies on As toxicity focusing on barley root elongation were carried out across various soil types. The As concentrations varied from 12.01 to 437.25 mg/kg for the effective concentrations that inhibited 10% of barley root growth (EC10). The present study employed a machine learning approach to investigate the complex associations between the toxicity thresholds of As and diverse soil properties. The results revealed that Mn-/Fe-ox and clay content emerged as the most influential factors in predicting the EC10 contribution. Additionally, by employing a species sensitivity distribution (SSD) model and toxicity data from 21 different species, the hazardous concentration for x% of species (HCx) was calculated for four representative soil scenarios. The HC5 values for acidic, neutral, alkaline, and alkaline calcareous soils were 80, 47, 40, and 28 mg/kg, respectively. This study establishes an evidence-based methodology for deriving soil-specific guidance concerning As toxicity thresholds.
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