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Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution

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Listed:
  • Bifeng Hu
  • Songchao Chen
  • Jie Hu
  • Fang Xia
  • Junfeng Xu
  • Yan Li
  • Zhou Shi

Abstract

Rapid heavy metal soil surveys at large scale with high sampling density could not be conducted with traditional laboratory physical and chemical analyses because of the high cost, low efficiency and heavy workload involved. This study explored a rapid approach to assess heavy metals contamination in 301 farmland soils from Fuyang in Zhejiang Province, in the southern Yangtze River Delta, China, using portable proximal soil sensors. Portable X-ray fluorescence spectroscopy (PXRF) was used to determine soil heavy metals total concentrations while soil pH was predicted by portable visible-near infrared spectroscopy (PVNIR). Zn, Cu and Pb were successfully predicted by PXRF (R2 >0.90 and RPD >2.50) while As and Ni were predicted with less accuracy (R2

Suggested Citation

  • Bifeng Hu & Songchao Chen & Jie Hu & Fang Xia & Junfeng Xu & Yan Li & Zhou Shi, 2017. "Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.
  • Handle: RePEc:plo:pone00:0172438
    DOI: 10.1371/journal.pone.0172438
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    Citations

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    Cited by:

    1. Bifeng Hu & Ruiying Zhao & Songchao Chen & Yue Zhou & Bin Jin & Yan Li & Zhou Shi, 2018. "Heavy Metal Pollution Delineation Based on Uncertainty in a Coastal Industrial City in the Yangtze River Delta, China," IJERPH, MDPI, vol. 15(4), pages 1-13, April.
    2. Modian Xie & Hongyi Li & Youwei Zhu & Jie Xue & Qihao You & Bin Jin & Zhou Shi, 2021. "Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China," Land, MDPI, vol. 10(6), pages 1-17, May.
    3. Fang Xia & Bifeng Hu & Shuai Shao & Dongyun Xu & Yue Zhou & Yin Zhou & Mingxiang Huang & Yan Li & Songchao Chen & 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," IJERPH, MDPI, vol. 16(15), pages 1-15, July.
    4. Mohammad Nishat Akhtar & Abdurrahman Javid Shaikh & Ambareen Khan & Habib Awais & Elmi Abu Bakar & Abdul Rahim Othman, 2021. "Smart Sensing with Edge Computing in Precision Agriculture for Soil Assessment and Heavy Metal Monitoring: A Review," Agriculture, MDPI, vol. 11(6), pages 1-37, May.
    5. Xiaolin Jia & Yi Fang & Bifeng Hu & Baobao Yu & Yin Zhou, 2023. "Development of Soil Fertility Index Using Machine Learning and Visible-Near-Infrared Spectroscopy," Land, MDPI, vol. 12(12), pages 1-13, December.
    6. Yan Zha & Lin Zhao & Tianxin Niu & Erkui Yue & Xianbo Wang & Jiang Shi, 2023. "Multi-Target Element-Based Screening of Maize Varieties with Low Accumulation of Heavy Metals (HMs) and Metalloids: Uptake, Transport, and Health Risks," Agriculture, MDPI, vol. 13(6), pages 1-15, May.
    7. Shuai Shao & Bifeng Hu & Zhiyi Fu & Jiayu Wang & Ge Lou & Yue Zhou & Bin Jin & Yan Li & Zhou Shi, 2018. "Source Identification and Apportionment of Trace Elements in Soils in the Yangtze River Delta, China," IJERPH, MDPI, vol. 15(6), pages 1-14, June.
    8. Bifeng Hu & Xiaolin Jia & Jie Hu & Dongyun Xu & Fang Xia & Yan Li, 2017. "Assessment of Heavy Metal Pollution and Health Risks in the Soil-Plant-Human System in the Yangtze River Delta, China," IJERPH, MDPI, vol. 14(9), pages 1-18, September.
    9. Ioana Andreea Petrean & Valer Micle & Marin Șenilă, 2023. "Investigation of Sterile Mining Dumps Resulting from Ore Exploitation and Processing in Maramures County, Romania," Land, MDPI, vol. 12(2), pages 1-21, February.
    10. Ioana Andreea Petrean & Valer Micle & Ioana Monica Sur & Marin Șenilă, 2023. "Characterization of Sterile Mining Dumps by the ICP-OES Analytical Method: A Case Study from Baia Mare Mining Area (Maramures, Romania)," Sustainability, MDPI, vol. 15(2), pages 1-14, January.

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