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The aim of this study was to investigate the influence of chemical leaching on permeability and Cd removal from fine-grained polluted soils. Column leaching experiments were conducted using two types of soils (i.e., artificially Cd-polluted loam and historically polluted silty loam). Chemical agents of CaCl2, FeCl3, citric acid, EDTA, rhamnolipid, and deionized water were used to leach Cd from the soils. Results showed that organic agents reduced permeability of both soils, and FeCl3 reduced permeability of loam soil, compared with inorganic agents and deionized water. Entrapment and deposition of colloids generated from the organic agents and FeCl3 treatments reduced the soil permeability. The peak Cd effluence from the artificially polluted loam columns was retarded. For the artificially polluted soils treated with EDTA and the historically polluted soils with FeCl3, Cd precipitates were observed at the bottom after chemical leaching. When Cd was associated with large colloid particles, the reduction of soil permeability caused Cd accumulation in deeper soil. In addition, the slow process of disintegration of soil clay during chemical leaching might result in the retardation of peak Cd effluence. These results suggest the need for caution when using chemical-leaching agents for Cd removal in fine-grained soils.
相似文献In recent 2 years, the incidence of influenza showed a slight upward trend in Guangxi; therefore, some joint actions should be done to help preventing and controlling this disease. The factors analysis of affecting influenza and early prediction of influenza incidence may help policy-making so as to take effective measures to prevent and control influenza. In this study, we used the cross correlation function (CCF) to analyze the effect of climate indicators on influenza incidence, ARIMA and ARIMAX (autoregressive integrated moving average model with exogenous input variables) model methods to do predictive analysis of influenza incidence. The results of CCF analysis showed that climate indicators (PM2.5, PM10, SO2, CO, NO2, O3, average temperature, maximum temperature, minimum temperature, average relative humidity, and sunshine duration) had significant effects on the incidence of influenza. People need to take good precautions in the days of severe air pollution and keep warm in cold weather to prevent influenza. We found that the ARIMAX (1,0,1)(0,0,1)12 with NO2 model has good predictive performance, which can be used to predict the influenza incidence in Guangxi, and the predicted incidence may be useful in developing early warning systems and providing important evidence for influenza control policy-making and public health intervention.
相似文献The optimal allocation of sediment resources needs to balance three objectives including ecological, economic, and social benefits so as to realize sustainable development of sediment resources. This study aims to apply fuzzy programming and bargaining approaches to solve the problem of optimal allocation of sediment resources. Firstly, Pareto-optimal solutions of multi-objective optimization were introduced, and the multi-objective optimal allocation model of sediment resources and fuzzy programming model was constructed. Then, from the perspective of multiplayer cooperation, the optimal allocation model of sediment resources was transformed into a game model by using Nash bargaining, and Nash bargaining solution was obtained as the optimal equilibrium strategy. Finally, the influence of different disagreement utility points and bargaining weights on the results was discussed, and the results of Nash bargaining and fuzzy programming methods were compared and analyzed. Results corroborate that Nash bargaining can achieve the cooperative optimization of multiple objectives with competitive relationship and obtain satisfactory scheme. Disagreement utility points and bargaining weights have a certain impact on the optimization results. The solution of fuzzy programming is close to that of Nash bargaining, which provides different ideas for multi-objective optimization problem.
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