Contamination characteristics and source apportionment of trace metals in soils around Miyun Reservoir.

Abstract

Due to their toxicity and bioaccumulation, trace metals in soils can result in a wide range of toxic effects on animals, plants, microbes, and even humans. Recognizing the contamination characteristics of soil metals and especially apportioning their potential sources are the necessary preconditions for pollution prevention and control. Over the past decades, several receptor models have been developed for source apportionment. Among them, positive matrix factorization (PMF) has gained popularity and was recommended by the US Environmental Protection Agency as a general modeling tool. In this study, an extended chemometrics model, multivariate curve resolution-alternating least squares based on maximum likelihood principal component analysis (MCR-ALS/MLPCA), was proposed for source apportionment of soil metals and applied to identify the potential sources of trace metals in soils around Miyun Reservoir. Similar to PMF, the MCR-ALS/MLPCA model can incorporate measurement error information and non-negativity constraints in its calculation procedures. Model validation with synthetic dataset suggested that the MCR-ALS/MLPCA could extract acceptable recovered source profiles even considering relatively larger error levels. When applying to identify the sources of trace metals in soils around Miyun Reservoir, the MCR-ALS/MLPCA model obtained the highly similar profiles with PMF. On the other hand, the assessment results of contamination status showed that the soils around reservoir were polluted by trace metals in slightly moderate degree but potentially posed acceptable risks to the public. Mining activities, fertilizers and agrochemicals, and atmospheric deposition were identified as the potential anthropogenic sources with contributions of 24.8, 14.6, and 13.3%, respectively. In order to protect the drinking water source of Beijing, special attention should be paid to the metal inputs to soils from mining and agricultural activities.