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The focus of the this work is to develop mesoporous silica and amine modified sand loaded with iron (Fe) and copper (Cu) species from electroplating wastewater for a further removal of phosphorus (P) from wastewater. First, it is shown that Fe or Cu supported sand adsorbent can effectively remove phosphorus (P) from aqueous solutions. The influence of pH, initial ion concentration (C 0 ), contact time (t) on the adsorption of P by both sand adsorbents was studied. The maximum adsorption efficiency at room temperature reached 98% for the Fe-supported adsorbent under conditions of pH = 4, C 0  = 25 mg/L, t = 180min and 96.3% for the Cu-supported sand under conditions of pH = 2, C 0  = 5 mg/L, t = 120min respectively. The kinetics of P adsorption by the Fe or Cu supported sands followed the pseudo second-order kinetic model, while the adsorption isotherms fitted the Langmuir model. Based on the above results, an iron and copper co-supported sand adsorbent was prepared successfully by encapsulating Fe and Cu from a copper electroplating wastewater. In the meantime, Cu in the electroplating wastewater was reduced from 222 to 0.12 mg/L. This wastewater derived sand-based adsorbent had the same efficiency as the Fe-supported sand adsorbent. It was used to remove P from aqueous solution until the residual P in solution met China National Standard of WastewaterEmission. By this way, a dual approach to synergistically purify both anions and cations polluted wastewaters is developed. [ABSTRACT FROM AUTHOR]

Strategies based on virtual water have become a controversial measure to alleviate pressure on the water resource in regions with scarce water. Advocates of this approach highlight its potentially low cost and high efficiency, whereas opponents criticize its over-simplification and neglect of important factors other than water. Detailed analysis of the strategy's effects on water use and socioeconomic development is essential to fully understand the strengths and weaknesses of the strategy, and to support its reasonable and scientific implementation. In the present study, we defined three virtual water strategy scenarios (i.e., reduce agricultural production, increase agricultural imports, and reduce production and increase imports simultaneously) and developed a computable general equilibrium model to simulate the effects of the scenarios. We chose China's Bohai Bay area, a rapidly developing region with scarce water, for a case study. We found that the virtual water strategy was a double-edged sword: it improved water conservation (water use decreased by 3.6%, 6.9%, and 3.2% under the three scenarios, respectively), but had negative effects on economic development, employment, and economic welfare. The scenario that only increased agricultural imports had the greatest negative impact on socioeconomic development, whereas the scenario that simultaneously decreased production and increased imports most effectively balanced the economic development and water conservation requirements. • The virtual water strategy (VWS) exerts negative effects on economic systems. • VWS produces tradeoffs between water conservation and economic development. • The dual-policy strategy could achieve a better tradeoff. [ABSTRACT FROM AUTHOR]

Carbon taxation has long been proposed to mitigate carbon emissions. Carbon tax rate determination and tax revenue recycling are two key steps to achieve a double dividend under carbon taxation. However, few research has sought to optimize the allocation proportion of tax revenue to various categories of taxpayers (households, enterprises, sectors, etc.), or to optimize the two steps synchronously based on nonlinear optimization methods. In this study, a computable general equilibrium model was established to explore the influence of carbon tax rate and tax revenue recycling shares on the economy and on carbon emissions. Meanwhile, a nonlinear optimization model was proposed, for optimizing both steps of carbon taxation synchronously, as well as for promoting GDP and CO 2 emission reduction. The Bohai Bay area, a typical area with enormous carbon emissions in China, was adopted as the study case for this research. The results showed that the optimized taxation scheme could lead to lower carbon emissions and greater economic growth, i.e., a strong double dividend was obtained. The optimized taxation scheme could lead to both cleaner air and cleaner energy and industrial structures while still promoting economic growth. • CGE model is used for effect analysis under different taxation schemes. • Carbon tax rate and revenue recycling are optimized synchronously. • Lower CO 2 emissions can be achieved without economic decline. [ABSTRACT FROM AUTHOR]

Energy and water are closely related resources, so environmental tax policies for energy resources will also influence the use of water resources. Different environmental tax policies have different emphases. However, few research has compared their effects on the energy – water nexus. In the present study, we considered two commonly used environmental tax policies to regulate energy use (energy and carbon taxes), and established a dynamic computable general equilibrium model to compare the comprehensive impacts of different tax types and intensities on the energy – water nexus. In addition to the direct-use nexus (direct water and energy consumption), we also considered the embodied-use nexus (energy-related water consumption and water-related energy consumption) and the hybrid-use nexus (hybrid water and energy consumption). Besides, both the effects of tax rates and time spans are simulated simultaneously. China was adopted as a case study. For the direct-use nexus, both taxes would increase the proportion of direct water consumption versus direct energy consumption. The average differences in the proportion change rates between the two taxes were 3.8, 7.8, and 9.7% for the low, medium, and high tax intensities, respectively. For the embodied-use nexus, the carbon tax could increase the proportion of energy-related water consumption versus water-related energy consumption. The average differences in the proportion change rates between the two taxes were 4.4, 8.4, and 10.2% for the low, medium, and high tax intensities, respectively. For the hybrid-use nexus, the effects of the taxes were similar to those for the direct-use nexus. • A dynamic CGE model is used for effect analysis under different taxes. • The effects of energy and carbon taxes on energy–water nexus are compared. • The direct-use, embodied-use and hybrid-use nexus are analyzed simultaneously. • The combined effects are simulated under different tax rates and time spans. [ABSTRACT FROM AUTHOR]

Inflow forecast is an important input for reservoir operation. Due to limited forecast techniques, the inflow forecast always has uncertainties (usually in the form of forecast errors). Handling inflow forecast uncertainties effectively is important for optimizing reservoir operation. The magnitude of this uncertainty depends on both the forecast lead times and the hydrological periods (i.e., wet season vs. dry season). Two-stage Bayesian stochastic dynamic programming (TBSDP) is an effective way to address the forecast uncertainties. However, current TBSDP methods pay more attention to the uncertainty differences caused by forecast lead times, neglecting the uncertainty differences in wet and dry seasons. Starting with a TBSDP model, we proposed a new two-stage and two-period version of the model (TTBSDP), which can not only consider the forecast uncertainty differences caused by forecast lead times, but also separately accounts for forecast uncertainty in wet and dry seasons. Because dealing separately with the uncertainties in the two periods increases the computational complexity, we further explored the conditions under which degree of forecast uncertainties this separation is necessary. We compared our new model's results (in terms of cumulative annual power generation) with the previous Bayesian stochastic dynamic programming models. With increasing forecast uncertainty in the first stage of the overall forecast horizon (in the wet season), the TTBSDP model produced superior results at higher uncertainty, with the most stable performance (the smallest variation of cumulative annual power generation when the forecast uncertainty coefficient increases). The proposed new model is benefit for hydropower operations when the magnitude of forecast uncertainty in the wet seasons is large. • A two-stage and two-period Bayesian stochastic dynamic programming model was developed. • The new model dealt separately with forecast uncertainties not only in two stages but also in two hydrological periods. • The TTBSDP model produced superior results at higher uncertainty, with the smallest variation of power generation. [ABSTRACT FROM AUTHOR]