Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Soil Sampling
2.2. Samples Analyses
2.2.1. ICP-AES
2.2.2. PXRF
2.3. Pollution Assessment
2.4. Geostatistics Models
2.4.1. Ordinary Kriging (OK)
2.4.2. Co-Ordinary Kriging (COK)
2.4.3. Getis-Ord Index
2.4.4. Multi-Variables Indicator Kriging (MVIK)
- Define indicator codes for target variables:
- The MVIK is the weighted results of several univariate indicator krigings:
3. Results and Discussion
3.1. Summary of PXRF and ICP-AES Measurements
3.2. Assessment of Soil Heavy Metals Pollution Status
3.3. Spatial Modeling of Soil PTEs Based on Secondary Variables from Predicted Value of PXRF
3.3.1. Spatial Pattern of Soil Heavy Metals Content
3.3.2. Model Accuracy
3.3.3. Hotspots of Soil Heavy Metals Pollution
3.4. Multi-Heavy Metals Pollution Risk in Study Area
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Statistics | Method | MEAN | SD | MIN | MAX | CV% | SBC1 | SBC2 |
---|---|---|---|---|---|---|---|---|
pH | 5.8 | 1.1 | 3.8 | 8.01 | 18.9 | |||
Cd | ICP-AES | 0.37 | 0.24 | 0.1 | 1.53 | 64.81 | 0.07 | 0.097 |
PXRF | 0.41 | 0.2 | 0.15 | 1.6 | 48.65 | |||
As | ICP-AES | 12.59 | 6.77 | 2.36 | 35.39 | 53.73 | 9.2 | 11.2 |
PXRF | 12.73 | 5.11 | 1.69 | 25.68 | 40.17 | |||
Pb | ICP-AES | 22.68 | 14.64 | 3.59 | 97.24 | 64.53 | 23.7 | 26 |
PXRF | 22.59 | 10.12 | 5.63 | 62.01 | 44.79 | |||
Cr | ICP-AES | 43.79 | 16.86 | 13.1 | 87.32 | 38.5 | 52.9 | 61 |
PXRF | 43.86 | 13.64 | 6.14 | 85.34 | 31.1 | |||
Ni | ICP-AES | 20.31 | 8.27 | 5.62 | 38.02 | 40.74 | 24.6 | 26.9 |
PXRF | 21.18 | 8.01 | 0.86 | 52.03 | 37.8 |
Element | ||||||
---|---|---|---|---|---|---|
As | Sample Number | 93 | 4 | 0 | 0 | 0 |
Percentage | 95.88% | 4.12% | 0 | 0 | 0 | |
Cd | Sample Number | 64 | 28 | 2 | 3 | 0 |
Percentage | 65.98% | 28.86% | 2.06% | 3.09% | 0 | |
Cr | Sample Number | 97 | 0 | 0 | 0 | 0 |
Percentage | 100% | 0 | 0 | 0 | 0 | |
Pb | Sample Number | 96 | 1 | 0 | 0 | 0 |
Percentage | 98.97% | 1.03% | 0 | 0 | 0 | |
Ni | Sample Number | 97 | 0 | 0 | 0 | 0 |
Percentage | 100% | 0 | 0 | 0 | 0 |
Pollution Grade | Count | Proportion |
---|---|---|
Safety | 52 | 53.61% |
Alert | 27 | 27.84% |
Slight pollution | 15 | 15.46% |
Moderate pollution | 2 | 2.06% |
Severe pollution | 1 | 1.03% |
Element | R2 | Concordance | RMSE | |
---|---|---|---|---|
Cr | OK | 0.706 | 0.83 | 8.76 |
COK XRF | 0.714 | 0.83 | 8.70 | |
Differences (%) | +1.13% | 0 | −0.68% | |
Pb | OK | 0.456 | 0.655 | 8.60 |
COK XRF | 0.514 | 0.696 | 8.21 | |
Differences (%) | +12.72% | +4.66% | −4.54% | |
Cd | OK | 0.624 | 0.766 | 0.13 |
COK XRF | 0.687 | 0.818 | 0.12 | |
Differences (%) | +10.10% | +6.79% | −7.70% | |
As | OK | 0.450 | 0.65 | 4.75 |
COK XRF | 0.480 | 0.67 | 4.64 | |
Differences (%) | +6.67% | +3.08% | −2.32% | |
Ni | OK | 0.715 | 0.84 | 4.64 |
COK XRF | 0.722 | 0.84 | 4.63 | |
Differences (%) | +0.98% | 0 | +0.22% |
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Xia, F.; Hu, B.; Shao, S.; Xu, D.; Zhou, Y.; Zhou, Y.; Huang, M.; Li, Y.; Chen, S.; Shi, Z. Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China. Int. J. Environ. Res. Public Health 2019, 16, 2694. https://doi.org/10.3390/ijerph16152694
Xia F, Hu B, Shao S, Xu D, Zhou Y, Zhou Y, Huang M, Li Y, Chen S, Shi Z. Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China. International Journal of Environmental Research and Public Health. 2019; 16(15):2694. https://doi.org/10.3390/ijerph16152694
Chicago/Turabian StyleXia, Fang, Bifeng Hu, Shuai Shao, Dongyun Xu, Yue Zhou, Yin Zhou, Mingxiang Huang, Yan Li, Songchao Chen, and Zhou Shi. 2019. "Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China" International Journal of Environmental Research and Public Health 16, no. 15: 2694. https://doi.org/10.3390/ijerph16152694