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• W2900474733 startingPage "1071" @default.
• W2900474733 abstract "Excessive organic emissions measured as chemical oxygen demand (COD) have caused serious regional water pollution i.e. the widespread malodorous black rivers in China. Assessing the optimum treatment strategies is generally a complicated work involving sophisticated trade-offs across regional improvement and global sustainability. Life cycle assessment (LCA) is a promising tool to support such trade-offs, but it appears difficult to comprehensively reflect the direct impact of high-COD wastewater. This is because, the current LCA framework only highlights the effect of nutrients as a representative eutrophication indicator. To address this issue, this study extends the LCA framework by defining a new COD category to characterize the oxygen-depleting processes associated with development of characterization factors and models. By combining water quality model, the modeling scheme is shown capable of converting dynamic effects of COD on the receiving water into the spatially differentiated impact-assessment results. Upon a descriptive case, we also illustrate that the modeling scheme can construct different environmental situations by varying the embedded variables. This enables the refined investigations of the paradigm shift in wastewater treatment, which contributes to the avoidance of one-size-fits-all solution identified without considerations of environmental sustainability. Last, we discuss the ways to further refining the modeling scheme to make it applicable in more cases of water pollution." @default.
• W2900474733 created "2018-11-29" @default.
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• W2900474733 date "2019-03-01" @default.
• W2900474733 modified "2023-10-13" @default.
• W2900474733 title "Modeling the oxygen-depleting potential and spatially differentiated effect of sewage organics in life cycle assessment for wastewater management" @default.
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• W2900474733 doi "https://doi.org/10.1016/j.scitotenv.2018.11.203" @default.
• W2900474733 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30577101" @default.
• W2900474733 hasPublicationYear "2019" @default.
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