A PMF-SSD based approach for the source apportionment and source-specific ecological risk assessment of Le'an river in Jiangxi Province, China.

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 sustainability assessment-based methodology for the prioritization of contaminated site risk management options.

Contaminated site management is a multiple objective decision-making that generally involves different factors, such as performance of technology, environmental effects, cost, and social influence. In this study, we developed a sustainability assessment-based methodology for the prioritization of contaminated site risk management options. We integrate remediation sustainable assessment and redevelopment sustainable assessment in one framework and allow the optimization of indicators. The framework started with the definition of site management type, then investigating site characterization, screening indicators, quantifying of indicator, selecting assessment model, selecting primary options, assessment with uncertainty analysis, and determining of preferred options. To demonstrate the utility of the framework, results are presented in a contaminate site in southwest China for two risk management decisions, site remediation and site redevelopment. We used different approaches to evaluate the stability and robustness of assessment results, including Monte Carlo simulation, scenario analysis, and sensitivity analysis. The demonstration showed that attention has to be paid to the proper description of the site, the principles of the procedure, and the decision criteria.