Determination of Cr, Zn, As and Pb in Soil by X-Ray Fluorescence Spectrometry Based on a Partial Least Square Regression Model
Soil samples were collected from five provinces over China, includ-ing Beijing, Xinjiang, Heilongjiang, Yunnan, and Jiangsu. Heavy metal Cr, Zn, Pb and As in soils were analyzed by a portable X-ray fluorescence spectrometry (XRF). For predicating metal concentration in soils, a partial least square regression model (PLSR) was established. After crosscalibration, the correlation coefficients for validation (R) of value predicted by PLSR model against that measured by AAS and AFS for Cr, Zn, Pb and As was 0.984, 0.929, 0.979, and 0.958, square error of validation (SEP)was 108 mg kg﹣1, 117 mg kg﹣1, 116 mg kg1, and 167 mg kg﹣1 for metals concentration from about 100 to 1500 mg kg﹣1, and the relative square error of validation(RSEP) was about 14.5 ％, 15.6 ％, 14.9 ％, and 21.0 ％. These results indicated XRF based on PLSR model could be applied for determination of Cr, Zn, Pb and As in soil, and would be an ef-fective tool for rapid, quantitative monitoring of metal contamination.
Heavy metal Soil Partial least square regression X-ray fluores-cence spectrometry
Anxiang Lu Xiangyang Qin Jihua Wang Jiang Sun Dazhou Zhu Ligang Pan
Beijing Research Center for Agri-food Testing and Farmland Monitoring, Beijing, China Nation Enginee Nation Engineering Research Center for Information Technology in Agriculture,Beijing, China Beijing Municipal Station of Agro-Environmental Monitoring, Beijing, China Beijing Research Center for Agri-food Testing and Farmland Monitoring, Beijing, China
国际会议
南昌
英文
563-568
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）