Environ Sci Pollut Res (2014) 21:7698–7707 DOI 10.1007/s11356-014-2726-x
RESEARCH ARTICLE
Positive matrix factorization as source apportionment of soil lead and cadmium around a battery plant (Changxing County, China) Jian-long Xue & Yu-you Zhi & Li-ping Yang & Jia-chun Shi & Ling-zao Zeng & Lao-sheng Wu
Received: 3 December 2013 / Accepted: 28 February 2014 / Published online: 14 March 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Chemical compositions of soil samples are multivariate in nature and provide datasets suitable for the application of multivariate factor analytical techniques. One of the analytical techniques, the positive matrix factorization (PMF), uses a weighted least square by fitting the data matrix to determine the weights of the sources based on the error estimates of each data point. In this research, PMF was employed to apportion the sources of heavy metals in 104 soil samples taken within a 1-km radius of a lead battery plant contaminated site in Changxing County, Zhejiang Province, China. The site is heavily contaminated with high concentrations of lead (Pb) and cadmium (Cd). PMF successfully partitioned the variances into sources related to soil background, agronomic practices, and the lead battery plants combined with a geostatistical approach. It was estimated that the lead battery plants and the agronomic practices contributed 55.37 and 29.28 %, respectively, for soil Pb of the total source. Soil Cd mainly came from the lead battery plants (65.92 %), followed by the agronomic practices (21.65 %), and soil parent materials (12.43 %). This research indicates that PMF combined with geostatistics is a useful tool for source identification and apportionment.
Keywords Heavy metal pollution . Anthropogenic influences . Source apportionment . Spatial variation . Receptor model Responsible editor: Michael Matthies J.
RESEARCH ARTICLE
Positive matrix factorization as source apportionment of soil lead and cadmium around a battery plant (Changxing County, China) Jian-long Xue & Yu-you Zhi & Li-ping Yang & Jia-chun Shi & Ling-zao Zeng & Lao-sheng Wu
Received: 3 December 2013 / Accepted: 28 February 2014 / Published online: 14 March 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Chemical compositions of soil samples are multivariate in nature and provide datasets suitable for the application of multivariate factor analytical techniques. One of the analytical techniques, the positive matrix factorization (PMF), uses a weighted least square by fitting the data matrix to determine the weights of the sources based on the error estimates of each data point. In this research, PMF was employed to apportion the sources of heavy metals in 104 soil samples taken within a 1-km radius of a lead battery plant contaminated site in Changxing County, Zhejiang Province, China. The site is heavily contaminated with high concentrations of lead (Pb) and cadmium (Cd). PMF successfully partitioned the variances into sources related to soil background, agronomic practices, and the lead battery plants combined with a geostatistical approach. It was estimated that the lead battery plants and the agronomic practices contributed 55.37 and 29.28 %, respectively, for soil Pb of the total source. Soil Cd mainly came from the lead battery plants (65.92 %), followed by the agronomic practices (21.65 %), and soil parent materials (12.43 %). This research indicates that PMF combined with geostatistics is a useful tool for source identification and apportionment.
Keywords Heavy metal pollution . Anthropogenic influences . Source apportionment . Spatial variation . Receptor model Responsible editor: Michael Matthies J.
