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. 2021 Feb 15;271:116310. doi: 10.1016/j.envpol.2020.116310. Epub 2020 Dec 17.
There must be some uncertainty in the remediation areas delineated based on limited sample points, and resampling in the high-uncertainty areas is particularly necessary. In situ field portable X-ray fluorescence spectrometry (FPXRF), a rapid and cheap analysis method for soil heavy metals, is strongly affected by many spatially non-stationary soil factors. This study first delineated the high-uncertainty area (threshold-exceeding probabilities (P) between 30% and 70%) of soil Pb based on the 1000 realizations produced by sequential Gaussian simulation (SGS) with 93 ICP-MS Pb concentrations measured in a peri-urban agriculture area, China. Next, in situ FPXRF was used to increase sample density in this high-uncertainty area. Then, robust geographically weighted regression (RGWR) was used to correct the in situ FPXRF Pb, and the correction accuracies of RGWR, basic GWR, and traditionally-used ordinary least squares regression (OLSR) were compared. Finally, to explore the best way to combine these corrected in situ FPXRF concentrations in delineating the remediation area, we compared the following spatial simulation methods: basic SGS, sequential Gaussian co-simulation (CoSGS) with the RGWR-corrected in situ FPXRF Pb as auxiliary soft data (CoSGS-CorFPXRF), and SGS with the RGWR-corrected in situ FPXRF Pb as part of hard data (SGS-CorFPXRF). Results showed that (i) RGWR produced higher correction accuracy (RI = 71.5%) than GWR (RI = 59.68%) and OLSR (RI = 25.58%) for the in situ FPXRF Pb; (ii) SGS-CorFPXRF produced less uncertainty (G = 0.97) than CoSGS-CorFPXRF (G = 0.95) and SGS (G = 0.91) in the spatial simulation; (iii) High-uncertainty area (30%<P<70%) was reduced from 36.55% to 8.7% of the whole study area. It is concluded that the recommended methods are cost-effective to reduce the uncertainty in delineating the remediation areas of soil heavy metals.
基于有限的采样点，划定的补救区域必然存在一定的不确定性，因此在高不确定性区域进行重新采样尤为必要。现场便携式 X 射线荧光光谱法（FPXRF）是一种快速、廉价的土壤重金属分析方法，但受许多空间非平稳土壤因素的强烈影响。本研究首先基于序贯高斯模拟（SGS）生成的 1000 个实现，划定了中国城郊农业区土壤 Pb 的高不确定性区域（超标概率（P）在 30%至 70%之间），该区域共测量了 93 个电感耦合等离子体质谱（ICP-MS）Pb 浓度。然后，在高不确定性区域使用现场 FPXRF 增加采样密度。然后，使用稳健地理加权回归（RGWR）校正现场 FPXRF Pb，比较了 RGWR、基本地理加权回归（GWR）和传统的普通最小二乘回归（OLSR）的校正精度。最后，为了探索在划定补救区域中结合这些校正后的现场 FPXRF 浓度的最佳方法，我们比较了以下空间模拟方法：基本 SGS、与 RGWR 校正后的现场 FPXRF Pb 一起进行序贯高斯协同模拟（CoSGS）的辅助软数据（CoSGS-CorFPXRF），以及将 RGWR 校正后的现场 FPXRF Pb 作为部分硬数据的 SGS（SGS-CorFPXRF）。结果表明：（i）与 GWR（RI=59.68%）和 OLSR（RI=25.58%）相比，RGWR 对现场 FPXRF Pb 的校正精度更高（RI=71.5%）；（ii）在空间模拟中，SGS-CorFPXRF 的不确定性（G=0.97）小于 CoSGS-CorFPXRF（G=0.95）和 SGS（G=0.91）；（iii）高不确定性区域（30%<P<70%）从整个研究区域的 36.55%减少到 8.7%。综上所述，推荐的方法可以有效地降低划定土壤重金属补救区域的不确定性，具有成本效益。
