Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
National Urban Environmental Pollution Control Engineering Research Center, Beijing Municipal Research Institute of Environmental Protection, Beijing, 100037, China.
Ecotoxicol Environ Saf. 2020 May;194:110418. doi: 10.1016/j.ecoenv.2020.110418. Epub 2020 Mar 6.
The increasing accumulation of zinc (Zn) in agricultural soils has led to the need to assess the potential risk of this element for terrestrial organisms. However, the soil ecological criteria in agricultural soil as a function of soil properties have been sparsely reported. In the present study, we derived the ecological criteria (expressed as predicted no effect concentration (PNEC)) for Zn in soils, based on ecotoxicity data for 19 terrestrial species in Chinese soils, the effect of soil properties on Zn ecotoxicity, differences in species sensitivity, and differences between laboratory and realistic field conditions. First, all ecotoxicity data of Zn for terrestrial organisms in Chinese soils were collected and filtered with given criteria to obtain reliable database. Second, the ecotoxicity data were normalized using Zn ecotoxicity predictive models to eliminate the effect of soil properties on Zn ecotoxicity, and corrected with leaching and aging factors to minimize the differences in Zn ecotoxicity under laboratory and field conditions. Then, species sensitivity distribution (SSD) curves were generated with a Burr Ⅲ function based on corrected ecotoxicity data. The concentration of Zn in soil that provides ecological safety for (100 - x)% of species (HC), was calculated from the SSD curve and HC was used for estimation of PNEC. Finally, we developed the predictive models for HC by quantifying the relationship between the Zn HC and soil properties. Results showed that soil pH was the most crucial factor affecting Zn HC values, with HC values varying from 38.3 mg/kg in an acidic soil to 263.3 mg/kg in an alkaline calcareous soil. Both the two-factor (soil pH and OC) and the three-factor (soil pH, OC and CEC) models predicted HC values well, with determination coefficients (R) of 0.941-0.959 and 0.978-0.982, respectively. This study provides a scientific and reliable basis for the improvement of ecological risk assessment and the establishment of soil environmental quality standards.
农业土壤中锌（Zn）的积累量不断增加，这使得评估该元素对陆地生物的潜在风险变得尤为重要。然而，关于农业土壤中土壤特性与土壤生态标准之间的关系的研究还很少。在本研究中，我们基于中国土壤中 19 种陆地物种的生态毒性数据、土壤特性对 Zn 生态毒性的影响、物种敏感性差异以及实验室和实际田间条件的差异，推导了土壤中 Zn 的生态标准（以预测无效应浓度 (PNEC) 表示）。首先，我们收集并筛选了所有中国土壤中 Zn 对陆地生物的生态毒性数据，以获得可靠的数据库。其次，我们使用 Zn 生态毒性预测模型对生态毒性数据进行归一化，以消除土壤特性对 Zn 生态毒性的影响，并通过淋溶和老化因子进行校正，以最小化实验室和田间条件下 Zn 生态毒性的差异。然后，我们基于修正后的生态毒性数据，使用 Burr Ⅲ 函数生成物种敏感性分布（SSD）曲线。从 SSD 曲线中计算出土壤中能为（100-x）%的物种提供生态安全的 Zn 浓度（HC），并将 HC 用于 PNEC 的估算。最后，我们通过量化 Zn HC 与土壤特性之间的关系，建立了 HC 的预测模型。结果表明，土壤 pH 是影响 Zn HC 值的最关键因素，HC 值从酸性土壤中的 38.3 mg/kg 变化到碱性钙质土壤中的 263.3 mg/kg。土壤 pH 和 OC 的双因素模型和土壤 pH、OC 和 CEC 的三因素模型均能很好地预测 HC 值，决定系数（R）分别为 0.941-0.959 和 0.978-0.982。本研究为改进生态风险评估和制定土壤环境质量标准提供了科学可靠的依据。
