Search

Environmental assessment and decision making is complex leading to uncertainty due to multiple criteria involved with uncertain information. Uncertainty is an unavoidable and inevitable element of any environmental evaluation process. The published literatures rarely include the studies on uncertain data with variable fuzzy reliabilities. This research has proposed an environmental evaluation framework based on Dempster–Shafer theory and Z-numbers. Of which a new notion of the utility of fuzzy number is proposed to generate the basic probability assignment of Z-numbers. The framework can effectively aggregate uncertain data with different fuzzy reliabilities to obtain a comprehensive evaluation measure. The proposed model has been applied to two case studies to illustrate the proposed framework and show its effectiveness in environmental evaluations. Results show that the proposed framework can improve the previous methods with comparability considering the reliability of information using Z-numbers. The proposed method is more flexible comparing with previous work.

The City of White Rock, Canada has been facing challenges of elevated concentrations of arsenic and manganese in its drinking water supply. A pilot water treatment study was conducted to explore effective contaminant removal solutions for human health risk mitigation. The arsenic and manganese removal performance of four treatment processes, including ozonation-manganese greensand filtration (OSF), OSF-iron-based granular media adsorption (OSFIA), the Burgess Iron Removal Method (BIRM), and BIRM-iron-based granular media adsorption (BIA) were evaluated. The non-cancer health risks and the incremental lifetime cancer risks (ILCR) posed by arsenic in different water sources were also assessed. The results show that OSFIA treatment achieved the highest arsenic and manganese removal. An average arsenic removal rate of 68.5% (initial concentration = 9.3 μg/L) was observed using OSFIA during two months of treatment, while manganese (initial concentration = 133.9 μg/L) can be completely removed. The arsenic removal was mainly be attributed to the adsorption of iron-based granular media. The mean values of non-cancer health risks of arsenic exposure due to oral intake of treated water were identified to be lower than the critical threshold for different age groups. In addition, the probability of critical ILCR occurrence can be greatly reduced. Based on the results from the pilot study, OSFIA was selected to construct a full-scale water treatment plant. Arsenic and manganese concentrations in the effluent from the plant can be reduced to a low-to-undetectable level, achieving negligible health risks to the residents of the city.

•A three-stage approach was developed to establish ESG criteria and metrics•A forensic review of industrially applied ESG risk assessment tools was performed•>60 experts were recruited to establish the importance of ESG criteria and metrics•Environmental component was identified as relatively more important•Developments and a roadmap to integrate ESG into mainstream finance was proposed.