Zhaocong Fu

Nanjing University of Information Science and Technology

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Chunfa Wu

Fujian Normal University

Ying Teng

Chinese Academy of Sciences

Wenjie Ren

Henan University of Technology

Taoran Shi

Nanjing University of Information Science and Technology

Shaopo Deng

Nanjing Institute of Environmental Sciences

Fenfang Lin

Nanjing University of Information Science and Technology

Shouyuan Gu

Nanjing University of Information Science and Technology

Yang Huang

Hebei University of Technology

Yongming Luo

Institute of Soil Science

Ling Zhao

Shanghai University of Traditional Chinese Medicine

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Chinese Academy of Sciences

Institute of Soil Science

University of Chinese Academy of Sciences

Nanjing University of Information Science and Technology

Fudan University

Ministry of Natural Resources

Zhejiang University

Shanghai Jiao Tong University

Yantai Institute of Coastal Zone Research

Nanjing Institute of Environmental Sciences

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Would it Be Better for Subarea Prediction of Heavy Metal Concentration in Soils Via Proximal Sensor Data Fusion?

Taoran Shi Zhaocong Fu Fenfang Lin Shouyuan Gu Yongming Luo

Heavy metal (HM) contamination in soil necessitates effective methods to diagnose suspected contaminated areas and control rehabilitation processes. The synergistic use of proximal sensors demonstrates significant potential for rapid detection via accurate surveys of soil HM pollution at large scales and high sampling densities, and necessitates the selection of appropriate data mining and modeling methods for early diagnosis of soil pollution. The aim of this study is to evaluate the performance of a subarea model based on geographically partitioned and global models based on high-precision energy dispersive X-ray fluorescence (HD-XRF) and visible near-infrared (vis-NIR) spectra using a random forest model for predicting soil Cu and Pb concentrations. A total of 166 soil samples are acquired from a contaminated plot in Baiyin, Gansu Province, China. The soil samples are subjected to HM analysis and proximal sensor scanning in a laboratory. Vis-NIR spectral data are preprocessed using the Savitzky Golay (SG) and first-order derivative with Savitzky Golay (SGFD) methods. The results show that for predicting Cu and Pb concentrations in soil, the subarea models performs better than the global models in terms of quantitative prediction, based solely on individual HD-XRF data. For the subarea and global models, the R2 values are 0.961 and 0.981, respectively; the RMSE values are 27.8 and 79.6, respectively; and the RPD values are 4.96 and 7.38, respectively. However, making use of the random forest algorithm trained with data fusion obtained from the HD-XRF and vis-NIR sensors, the global model achieves the best predictions for Cu and Pb concentrations via HD-XRF + vis-NIR (SGFD) and HD-XRF + vis-NIR (SG), respectively. The results will provide a new perspective for modeling approaches to rapidly invert HM concentrations based on proximal sensor data fusion within a large scope of the study area.

Sensor Fusion

10.2139/ssrn.4510792

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Risk control effectiveness of phosphorus-containing passivators on Cd-contaminated agricultural soils to be strictly controlled

Journal of Soils and Sediments (2022)

Chunfa Wu JinLu Zhang Yu Zhang Shaopo Deng Chong Wang

Topsoil

10.1007/s11368-022-03240-w

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Citations (1)

SHIMEN市周辺の農地土壌における重金属汚染と健康リスク評価【JST・京大機械翻訳】

Turang (2016)

Yang Min Ying Teng Wenjie Ren Huang Yang Defu Xu

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Pollution and Health Risk Assessment of Heavy Metals in Agricultural Soil Around Shimen Realgar Mine

Turang (2016)

Yang Min Ying Teng Wenjie Ren Yang Huang Defu Xu

Realgar

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Effect of Different Washing Solutions on Soil Enzyme Activity and Microbial Community in Agricultural Soil Severely Contaminated With Cadmium

Research Square (Research Square) (2021)

Yu Zhang Chunfa Wu Shaopo Deng Jinlu Zhang Jinyu Hou

Abstract Soil enzyme activities and microbial communities have a good response to the remediation effect of heavy metal-contaminated soils. To evaluate the effect of three commonly used washing agents, ferric chloride (FC), ethylenediamine-tetra- methylenephosphonic acid (EDTMP) and ethylenediamine tetraacetic acid (EDTA) on soil enzyme activities and microbial community in cadmium (Cd)- contaminated agricultural soil collected around the mining area. The soil enzyme activities, microbial community, chemical forms of Cd and some physicochemical properties of the soil washed with different washing solutions were determined after two months incubation. The results showed that the three washing solutions had moderate removal efficiencies (22.83%-37.56%) for Cd in the tested soil and the breakdown product of EDTMP has a certain stabilizing effect on Cd. The geometric mean and the integrated total enzyme activity index showed that soil washing with FC and EDTA were more beneficial to the restoration of biochemical functions than that with EDTMP. The relative abundance of Gemmatimonadetes in the soil washed with EDTA was significantly higher than that with FC and EDTMP. The relative abundance of Firmicutes in the soil washed with EDTMP was significantly increased, and the relative abundance of Bacteroidetes in the soil washed with FC was significantly decreased. Pearson correlation analysis and redundancy analysis (RDA) indicated that the three washing solutions affected soil enzyme activities and microbial community by altering soil nutrient, total Cd concentration and Cd fractions in soils.

10.21203/rs.3.rs-1063888/v1

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Would it be better for partition prediction of heavy metal concentration in soils based on the fusion of XRF and Vis-NIR data?

The Science of The Total Environment (2023)

Taoran Shi Zhaocong Fu Xuhua Miao Fenfang Lin Jianyuan Ma

Soil test

10.1016/j.scitotenv.2023.168381

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Human health risk assessment of heavy metals in the soil–Panax notoginseng system in Yunnan province, China

Human and Ecological Risk Assessment An International Journal (2018)

Yang Huang Ying Teng Ning Zhang Zhaocong Fu Wenjie Ren

In this study, a total of 69 topsoil samples and 10 Panax notoginseng samples from Yunnan Province were collected and the concentrations of As, Cd, Cu, Hg, Ni, Pb and Zn in all the samples were determined. The hazard index (HI), total carcinogenic risk (TCR) and estimated daily intake (EDI) of heavy metals were calculated to assess the health risk of P. notoginseng growers and consumers. The average concentrations of As, Cd, Cu, Hg, Ni, Pb and Zn in P. notoginseng planting soils are 43.6, 0.55, 50.8, 0.30, 73.4, 58.2, and 161 mg/kg, respectively. The average Nemerow integrated pollution index of heavy metals in soils is 1.8, indicating that the P. notoginseng planting soils are slightly polluted by those heavy metals. The average HI value is 1.29 and the TCR value of As is above the threshold value, suggesting that As pollution in soil has adverse impact on local growers' health. P. notoginseng is polluted by Cd, As and Pb. 39.1% of estimated daily intakes of As for P. notoginseng consumers through leaf consumption exceeding its permitted daily exposure dosages, suggesting that there is a potential health risk for P. notoginseng consumers to consume P. notoginseng leaves.

Panax notoginseng

Topsoil

10.1080/10807039.2017.1411782

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Pesticide residues in soils planted with Panax notoginseng in south China, and their relationships in Panax notoginseng and soil

Ecotoxicology and Environmental Safety (2020)

Ling Zhao Yan Li Wenjie Ren Yang Huang Xiaomi Wang

Panax notoginseng

Procymidone

Chlorothalonil

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