The general objective for this paper is to reveal the dynamic relationships between the rapid economic development, water pollution and the subsequent waste-load allocation in different economic sectors through a case-study in Shenzhen City, South China. Two-objective analysis model was employed based on the input-output table for Shenzhen with the full consideration of various constraints in local area. The improved Tchebycheff procedure was used for obtaining the solutions. The predictions were made on economic development and pollutants from wastewater in different sectors and different planning years. The present study allows for the consideration of the economic structural adjustment. It is found that the current situation of economic structure is generally good and is subject to further adjustment in Shenzhen, although it has undergone the rapid development in the past 18 years. When the maximum Gross Domestic Production and the minimum Chemical Oxygen Demand are chosen as the two objectives subject to other constraints, the harmonized results indicated a scheme that claims substantial reduction of polluting effluences in Shenzhen while closely keeping the economic growth rate as planned. 相似文献
Environmental Science and Pollution Research - Coal-based mercury pollution from power plants has received increasing attention. In a previous study, high iron and calcium coal ash (HICCA) was... 相似文献
Coastal rivers contributed the majority of anthropogenic nitrogen (N) loads to coastal waters, often resulting in eutrophication and hypoxia zones. Accurate N source identification is critical for optimizing coastal river N pollution control strategies. Based on a 2-year seasonal record of dual stable isotopes (\({\updelta}^{15}\mathrm{N}-{\mathrm{NO}}_3^{\hbox{-} }\) and \({\updelta}^{18}\mathrm{O}-{\mathrm{NO}}_3^{\hbox{-} }\)) and water quality parameters, this study combined the dual stable isotope-based MixSIAR model and the absolute principal component score-multiple linear regression (APCS-MLR) model to elucidate N dynamics and sources in two coastal rivers of Hangzhou Bay. Water quality/trophic level indices indicated light-to-moderate eutrophication status for the studied rivers. Spatio-temporal variability of water quality was associated with seasonal agricultural, aquaculture, and domestic activities, as well as the seasonal precipitation pattern. The APCS-MLR model identified soil + domestic wastewater (69.5%) and aquaculture tailwater (22.2%) as the major nitrogen pollution sources. The dual stable isotope-based MixSIAR model identified soil N, aquaculture tailwater, domestic wastewater, and atmospheric deposition N contributions of 35.3 ±21.1%, 29.7 ±17.2%, 27.9 ±14.5%, and 7.2 ±11.4% to riverine \({\mathrm{NO}}_3^{\hbox{-} }\) in the Cao’e River (CER) and 34.4 ±21.3%, 29.5 ±17.2%, 27.4 ±14.7%, and 8.7 ±12.8% in the Jiantang River (JTR), respectively. The APCS-MLR model and the dual stable isotope-based MixSIAR model showed consistent results for riverine N source identification. Combining these two methods for riverine N source identifications effectively distinguished the mix-source components from the APCS-MLR method and alleviated the high cost of stable isotope analysis, thereby providing reliable N source apportionment results with low requirements for water quality sampling and isotope analysis costs. This study highlights the importance of soil N management and aquaculture tailwater treatment in coastal river N pollution control.
