A joint standard-exceeding risk assessment of multiple pollutants based on robust geostatistics with categorical land-use type data: A case study of soil nitrogen and phosphorus

被引:5
作者
Chen, Jian [2 ,3 ]
Qu, Mingkai [1 ,3 ]
Wang, Yan [1 ]
Huang, Biao [1 ,3 ]
Zhao, Yongcun [2 ,3 ]
机构
[1] Chinese Acad Sci, Inst Soil Sci, Key Lab Soil Environm & Pollut Remediat, Nanjing 210008, Peoples R China
[2] Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
Soil available nitrogen; Soil available phosphorus; Robust sequential Gaussian simulation with land-use types; Spatial uncertainty; Joint standard-exceeding probability; Joint regulation of multiple soil pollutants; SEQUENTIAL GAUSSIAN SIMULATION; YANGTZE-RIVER DELTA; SPATIAL UNCERTAINTY; ENVIRONMENTAL RISK; HEAVY-METALS; VARIOGRAM; ESTIMATORS; POLLUTION; AREAS; CONTAMINATION;
D O I
10.1016/j.envpol.2022.118901
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Joint standard-exceeding risk and its spatial uncertainty of soil available nitrogen (AN) and available phosphorus (AP) under the specific constraints are essential for guiding the joint regulation of pollutants but were rarely considered by previous studies. Moreover, traditionally-used spatial simulation models are not only non-robust but also ignoring valuable categorical information (e.g., land-use types), which may hinder the acquisition of high-precision spatial simulation results. This study first established optimally robust semi-variogram estimators to identify the spatial outliers of soil AN and AP in Jintan County, China. Then, robust sequential Gaussian simulation (RSGS) with land-use types (RSGS-LU) was proposed and further compared with RSGS, SGS-LU, and SGS in the spatial simulation accuracy. Last, a joint standard-exceeding probability model under the specific constraints was proposed, and the corresponding high-risk areas were delineated for the joint regulation of soil AN and AP. Results showed that: (i) 23 and 17 spatial outliers were identified for soil AN and AP, respectively; (ii) removing outliers or combining land-use types could improve the spatial simulation accuracy of soil AN and AP; (iii) RSGS-LU generated the highest spatial simulation accuracy for both soil AN and AP; (iv) the area with the joint standard-exceeding (AP > 30 mg kg(-1) boolean OR AN > 130 mg kg(-1)) probability >75% accounted for 9.98% of the county's area; (iv) the area with the joint standard-exceeding (AP > 30 mg kg(-1) boolean AND AN > 130 mg kg(-1)) probability >75% accounted for 2.29% of the county's area. It is concluded that RSGS-LU and joint standard-exceeding probability model under the specific constraints could provide more accurate and flexible spatial decision support for the joint regulation of soil AN and AP at a regional scale. Moreover, the methods recommended in this study also provide valuable tools for the joint standard-exceeding risk assessment of other multiple soil pollutants.
引用
收藏
页数:9
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