Environmental Science and Pollution Research - The existing literature on the environmental Kuznets curve (EKC) fails to investigate the spatial attribute of the “pollution halo” effect... 相似文献
Waste cutting emulsions are difficult to treat efficiently owing to their complex composition and stable emulsified structure. As an important treatment method for emulsions, chemical demulsification is faced with challenges such as low flocs–water separation rates and high sludge production. Hence, in this study, Fe3O4 magnetic nanoparticles (MNPs) were used to enhance chemical demulsification performance for treating waste cutting emulsions under a magnetic field. The addition of MNPs significantly decreased the time required to attain sludge–water separation and sludge compression equilibrium, from 210 to 20 min. In addition, the volume percentage of sludge produced at the equilibrium state was reduced from 45% to 10%. This excellent flocculation–separation performance was stable over a pH range of 3–11. The magnetization of the flocculants and oil droplets to form a flocculant–MNP–oil droplet composite, and the magnetic transfer of the composite were two key processes that enhanced the separation of cutting emulsions. Specifically, the interactions among MNPs, flocculants, and oil droplets were important in the magnetization process, which was controlled by the structures and properties of the three components. Under the magnetic field, the magnetized flocculant–MNP–oil droplet composites were considerably accelerated and separated from water, and the sludge was simultaneously compressed. Thus, this study expands the applicability of magnetic separation techniques in the treatment of complex waste cutting emulsions. 相似文献
Both China’s national subsidy policies for plug-in electric vehicles (PEVs) purchasers and passenger cars corporate average fuel consumption and new vehicle credit regulation (dual-credit policy) favor long-range 300+ km battery electric vehicles (BEVs) and 80+ km plug-in hybrid electric vehicles (PHEVs). However, these electric vehicles tend to have lower energy efficiency and higher purchase and operation costs. Vehicle with larger batteries can also be less equitable because the subsidies are often provided to more expensive vehicles and wealthier owners. This study takes advantage of a novel dataset of daily driving data from 39,854 conventional gasoline vehicles in Beijing and 4999 PHEVs in Shanghai to determine the optimal range of BEVs and PHEVs within their respective cities. We simulate a model to explore ranges with which PEVs emit less GHGs than that of a baseline hybrid and conventional gasoline vehicle while ensuring that all daily travel demands are met. Our findings indicate that in both cities, the optimal ranges to balance cost and travel demand for BEVs are 350 km or less and for PHEVs are 60 km or less in Beijing and 80 km or less in Shanghai. We also find that to minimize carbon dioxide (CO2) emissions, the ranges are even lower 10 km in Beijing and 30 km in Shanghai. Our study suggests that instead of encouraging long-range PEVs, governments should subsidize PEV models with shorter ranges. Parallel efforts should also be made to both increase renewable energy over fossil fuels and expand charging facilities. Although individual mobility demand varies, the government could reduce occasional long-distance driving by subsidizing alternative transportation choices. Providing week-long driving trials to consumers before their purchases may help decrease the demand of very long range PEVs by alleviating the range anxiety through a learning process.