Correcting correlation quality of portable X-ray fluorescence to better map heavy metal contamination by spatial co-kriging interpolation

Manying Zhao; Zengsiche Chen; Can Qian; Yuxin Zhao; Ya Xu; Yuqiang Liu

doi:10.1016/j.ecoenv.2024.115962

Correcting correlation quality of portable X-ray fluorescence to better map heavy metal contamination by spatial co-kriging interpolation

Ecotoxicol Environ Saf. 2024 Feb:271:115962. doi: 10.1016/j.ecoenv.2024.115962. Epub 2024 Jan 17.

Authors

Manying Zhao¹, Zengsiche Chen², Can Qian³, Yuxin Zhao⁴, Ya Xu⁵, Yuqiang Liu³

Affiliations

¹ State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Hazardous Waste Identification and Risk Control, Beijing 100012, China; School of Municipal and Environmental Engineering, Jilin Jianzhu University, Changchun 130000, China.
² Solid Waste and Chemicals Management Center, Ministry of Ecology and Environment, Beijing 100029, China.
³ State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Hazardous Waste Identification and Risk Control, Beijing 100012, China.
⁴ School of Municipal and Environmental Engineering, Jilin Jianzhu University, Changchun 130000, China.
⁵ State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Hazardous Waste Identification and Risk Control, Beijing 100012, China. Electronic address: xuya@craes.org.cn.

PMID: 38237394
DOI: 10.1016/j.ecoenv.2024.115962

Abstract

High-precision mapping based on portable X-ray fluorescence (PXRF) data is currently being studied extensively; however, owing to poor correlation with soil metal concentration, the original PXRF data directly used for co-kriging interpolation (CKI) cannot accurately map contaminated sites with heterogeneous concentrations. Therefore, this study selected a landfill-contaminated site for research, explored the best correlation mode between PXRF variants and actual heavy metal concentration, analyzed the impact of improving the correlation model on the CKI of the spatial distribution of heavy metals, and explored the most appropriate CKI mode and point density. The results showed the following: (1) After nonlinear transformation, the correlation model between PXRF and the actual concentration was significantly improved, and the correlation coefficients of five heavy metals increased from 0.214-0.232 to 0.936-0.986. (2) The introduction of corrected PXRF data significantly improves the accuracy of CKI. Compared with the original PXRF co-kriging interpolation (OP-CKI), the ME of the corrected PXRF co-kriging interpolation (CP-CKI) for Zn, Pb, and Cu decreased by 78.2 %, 45.5 %, and 65.3 %, respectively. In terms of the spatial distribution of heavy metal pollutant concentrations, CP-CKI effectively improved the influence of local anomalous high-value points on the interpolation accuracy. (3) When the sample density measured by inductively coupled plasma mass spectrometry (ICP-MS) was less than 4 boreholes/hm², CKI accuracy decreased significantly, indicating that the sample density should not be less than a certain threshold during CKI. (4) When the sample density measured by PXRF exceeded 7 boreholes/hm², the mean error and root mean square error of CKI continued to decrease, suggesting that the introduction of enough sample density measured by PXRF can effectively improve the accuracy of CKI.

Keywords: High-accuracy mapping; Non-destructive detection; Pollution distribution; Site survey.

MeSH terms

Environmental Monitoring / methods
Metals, Heavy* / analysis
Soil / chemistry
Soil Pollutants* / analysis
Spatial Analysis
Spectrometry, X-Ray Emission / methods
X-Rays

Substances

Soil Pollutants
Metals, Heavy
Soil