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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. [ABSTRACT FROM AUTHOR]

Heavy metals (HMs) in lake sediments have aroused long-term attention due to their persistent threat to the lake ecosystems. Study into the pollution characteristics and potential sources of HMs in lakes, especially those heavily influenced by human activities, can give some insights to prevent and control the environmental risks of HMs. Lake Tai is the China's third largest freshwater lake but has been a drastic example of water pollution in recent decades. Here, we systematically investigated the characterization of pollution, risk and sources of HMs in the sediments of Lake Tai and its surrounding soils using several methods and tools. Specifically, a total of 46 sediments and 578 soils were collected from the study area, and geochemical approaches (geo-accumulation index and enrichment factor) and pollution indexes were jointly used to reveal the contamination characteristics of HMs. Meanwhile, the potential ecological risk index and probabilistic model of health risk assessment were employed to understand the environmental risk of HMs. Further, absolute principle component score-multiple linear regression and positive matrix factorization models were comparatively applied to apportion the sources of HMs. Results showed that various metals including Cd, Cr, As, Hg, Pb, and Cu appeared contamination level in varying degrees both in the sediments and soils. In particular, Cd, As and Hg were identified as the significant contaminants and presented moderate ecological risk. As a whole, the health risk levels of metals were acceptable. Source apportionment suggested that industrial discharge, agricultural activities, atmospheric deposition and natural source were the potential origins of HMs in this area. Among them, anthropogenic activities were the largest dominator of HMs with contribution of >75%. The study will advance our knowledge on HMs in lake and its surrounding soils and provide reference for policy maker to design migration strategies for protecting the lake ecosystems. Unlabelled Image • Contamination risk and sources of HMs in the sediments of Lake Tai were studied. • Cd, As and Hg were recognized as the significant contaminants. • Contamination risk of HMs in the sediments of Lake Tai was higher than surrounding soils. • Anthropogenic activities were the largest dominator of HMs with contributions of >75%. [ABSTRACT FROM AUTHOR]

Identifying the contamination characteristics of trace metals in river and targeting their corresponding potential contamination sources and source-specific ecological risk are of very importance for putting forward effective river environment protection strategies. Here, a detailed investigation was conducted to recognize the contamination and ecological risk characteristics of trace metals in Le'an River. To attain this objective, a PMF-SSD model (Positive Matrix Factorization-Species Sensitivity Distribution) was proposed to evaluate the ecological risk of trace metals in Le'an River. The positive matrix factorization (PMF) was employed to identify the potential source of trace metals in surface water and their corresponding contributions. The ecological risks of the sources were quantitatively calculated by PMF-SSD. In addition, the spatial dissimilarity analysis of the source contribution distributions was also conducted in this study. Results showed that the water environment in Jiangxi were considerably contaminated by trace metals (Cd, Cr, Co, Al, Mn, Cu, Zn and Ni). The concentrations of these trace metals in surface water demonstrated significant spatial variations and the ecological risk lay in high level. Mining activities were identified as the main anthropogenic sources, which should to be strictly regulated. • A source-oriented ecological risk assessment model was proposed. • The Zn, Cu and Fe were identified as priority trace metals for water ecological risk control. • The concentrations of these trace metals in surface water demonstrated significant spatial variations. • The copper production activities are the largest contributor of ecological risk source in Le'an River. [ABSTRACT FROM AUTHOR]

Here, a new integrated methodology framework has been proposed for source apportionment and source-oriented risk evaluation, and applied to identify the characteristics, sources and health risks of PAHs in the soils of a typical cold region in Northeastern China. To this end, a large-scale data set containing 1780 soil samples and 16 priority PAHs has been collected from the study area. Two advanced receptor models, positive matrix factorization (PMF) and multivariate curve resolution-weighted alternating least-squares (MCR-WALS), have been comparatively employed to apportion the pollution sources of soil PAHs, with the help of a set of modified literature PAH source fingerprints. Further, the apportionment results have been incorporated into a probabilistic incremental lifetime cancer risk model for assessing the source-specific health risk of soil PAHs. Notably, the PMF and MCR-WALS models have apportioned essentially same results. The coal combustion and gasoline engine are identified as the main contributors of soil PAHs, with contributions of 57.9–58.1% and 25.2–22.2%, respectively. The health risks posed by PAHs in the soils are negligible for both adult and children; relatively, source-oriented risk assessment shows coal combustions make the largest contribution to the total risk of PAHs (56.1%), followed by gasoline engine (22.5%) and coke oven (21.4%). [Display omitted] • A new integrated framework has been proposed for characterizing sources and risks of PAHs. • Apportionment results have been used for assessing source-specific health risk of PAHs. • The MCR-WALS model has apportioned essentially same results with PMF. • Coal combustion, gasoline engine and coke oven are the main pollution sources of PAHs. • Coal combustion has made the largest contribution to the total risk of PAHs (56.1%). [ABSTRACT FROM AUTHOR]