Spatial uncertainty assessment of the environmental risk of soil copper using auxiliary portable X-ray fluorescence spectrometry data and soil pH.

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.