Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China.
Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China.
Environ Pollut. 2018 Sep;240:184-190. doi: 10.1016/j.envpol.2018.04.118. Epub 2018 May 4.
Spatial uncertainty information of the environmental risk of soil heavy metal is crucial for precise environmental management. This study first compared three geostatistical methods for spatial simulation of soil Copper (Cu) in a peri-urban agriculture area of Wuhan city, China, that are sequential Gaussian co-simulation (CoSGS) with auxiliary in-situ portable X-ray fluorescence (PXRF) data (CoSGS_in-situ), CoSGS with auxiliary ex-situ PXRF data (CoSGS_ex-situ), and sequential Gaussian simulation without auxiliary data (SGS). Then, the environmental risk of soil Cu was assessed based on the joint thresholds of soil Cu and soil pH in the Chinese soil environmental quality standards II. The geostatistical simulated realizations of soil Cu and soil pH were used to calculate the probabilities of exceeding the joint thresholds. Validation showed that CoSGS_ex-situ is slightly better than CoSGS_in-situ in the performance of both E-type estimates (i.e., mathematical expectation estimates) and uncertainty modelling of soil Cu, and SGS is the worst. The spatial uncertainty information of both soil Cu and soil pH was transferred to the environmental risk map through the corresponding geostatistical simulated realizations. The areas with higher probabilities of exceeding the joint thresholds mainly located in the northwest and southwest of the study area. It is concluded that CoSGS_ex-situ and CoSGS_in-situ were more cost-effective than the traditional SGS in the spatial simulation of soil Cu, and the simulated realizations of soil Cu and soil pH provide a solution to the spatial assessment of the probabilities of exceeding the joint thresholds.
土壤重金属环境风险的空间不确定性信息对于精确的环境管理至关重要。本研究首先比较了三种地统计学方法，用于模拟中国武汉市城郊农业区土壤铜的空间分布，分别是带有原位便携式 X 射线荧光（PXRF）数据辅助的序贯高斯协同模拟（CoSGS_in-situ）、带有异位 PXRF 数据辅助的 CoSGS（CoSGS_ex-situ）和无辅助数据的序贯高斯模拟（SGS）。然后，基于中国土壤环境质量标准 II 中土壤铜和土壤 pH 的联合阈值，评估了土壤铜的环境风险。利用土壤铜和土壤 pH 的联合阈值，计算了超过联合阈值的概率。验证表明，CoSGS_ex-situ 在土壤铜的 E 型估计（即数学期望估计）和不确定性建模方面的性能略优于 CoSGS_in-situ，而 SGS 则表现最差。土壤铜和土壤 pH 的空间不确定性信息通过相应的地统计学模拟实现被转化为环境风险图。超过联合阈值概率较高的区域主要分布在研究区的西北部和西南部。结论是，与传统的 SGS 相比，CoSGS_ex-situ 和 CoSGS_in-situ 在土壤铜的空间模拟中更具成本效益，土壤铜和土壤 pH 的模拟实现为超过联合阈值的概率的空间评估提供了一种解决方案。
