title: Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution.
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 <0.75 and RPD <1.40). The pH values were well predicted by PVNIR. Classification of heavy metals contamination grades in farmland soils was conducted based on previous results; the Kappa coefficient was 0.87, which showed that the combination of PXRF and PVNIR was an effective and rapid method to determine the degree of pollution with soil heavy metals. This study provides a new approach to assess soil heavy metals pollution; this method will facilitate large-scale surveys of soil heavy metal pollution.
authors.affiliation: Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou, China.
authors.forename: Bifeng
authors.initials: B
authors.lastname: Hu
authors.affiliation: INRA, InfoSol Unit, Ardon, Orléans, France.|UMR SAS, INRA, AGROCAMPUS OUEST, Rennes, France.
authors.forename: Songchao
authors.initials: S
authors.lastname: Chen
authors.affiliation: Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Hu
authors.affiliation: Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou, China.
authors.forename: Fang
authors.initials: F
authors.lastname: Xia
authors.affiliation: College of Science, Hangzhou Normal University, Hangzhou, China.
authors.forename: Junfeng
authors.initials: J
authors.lastname: Xu
authors.affiliation: Institute of Land Science and Property Management, School of Public Affairs, Zhejiang University, Hangzhou, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Li
authors.affiliation: Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou, China.
authors.forename: Zhou
authors.initials: Z
authors.lastname: Shi
mesh_terms: D000383:Agriculture; D002681:China; D004784:Environmental Monitoring; D004787:Environmental Pollution / Q000032:analysis*; D006801:Humans; D019216:Metals, Heavy / Q000737:chemistry / Q000302:isolation & purification*; D045483:Rivers; D012989:Soil Pollutants / Q000737:chemistry / Q000302:isolation & purification*; D013052:Spectrometry, X-Ray Emission / Q000379:methods; D013055:Spectrophotometry, Infrared / Q000379:methods
chemical_list: D019216:Metals, Heavy; D012989:Soil Pollutants