With the increasingly serious problem of surface water environmental safety, it is of great significance to study the changing trend of reservoir water quality, and it is necessary to establish a water quality prediction and early warning system for the management and maintenance of water resources. Aiming at the problem of water quality prediction in reservoirs, a CA-NARX algorithm is designed, which combines the improved dynamic clustering algorithm with the idea of machine learning and the forward dynamic regression neural network. The improved dynamic clustering algorithm is used to classify the eutrophication degree of waterbodies according to the total phosphorus and total nitrogen content. Considering four meteorological factors, air temperature, water temperature, water surface evaporation, and rainfall, synthetically for each water quality condition, the total phosphorus and total nitrogen in the waterbody are forecasted by an improved forward NARX dynamic regression neural network. Based on this, the CA-NARX prediction algorithm can realize short period water quality prediction. Compared with the traditional support vector regression machine model, improved GA-BP neural network, and exponential smoothing method, the CA-NARX model has the least prediction error.
China will set up a national carbon emissions trading market by the end of 2017, which is initially open to individual investors from the initial market for business and institutional investors. In this article, the main influencing factors and mechanism of individual participation in carbon trading market are studied by establishing multiple linear regression model. The study found that age, education level, length of account opening time, and risk attitude are the main factors influencing the participation of individual investors. Environmental awareness and environmental impact are less affected; information transparency and transaction risk also have an impact on the degree of individual investor participation; investment experience does not affect the participation of individual investors in the carbon trading market. 相似文献
Environmental Science and Pollution Research - Waste electrical and electronic equipment (WEEE) contains both toxic and valuable materials. Due to rapid development of information and communication... 相似文献
The farmland irrigation with the sewage is a common and better pathway to save the resource of groundwater in Northern China. The investigation was conducted in the farmland along the Fuhe River to explore characteristics of heavy metals in soils and grains of wheat and maize from a long-term sewage-irrigated area of Baoding region. The results showed that the topsoil with long-term sewage irrigation accumulated more Cd, Pb, and Hg compared with that of soil irrigated with groundwater and their corresponding natural background values. Cd concentrations in 48% of sewage-irrigated soil samples exceeded the Chinese safety limitation at 0.6 mg/kg, but less Cd accumulated in crop grains and did not pose the potential health risk. On the contrary, Pb levels in soils irrigated with sewage were lower than the safety limitation but Pb concentrations in 24% of wheat grain samples exceeded the Chinese national safety limit. Long-term sewage irrigation did not increase As, Cr, and Ni concentrations in soils or crop grains. The target hazard quotient (THQ) of heavy metals in edible grains of crops was selected to assess their risk to human health. Total THQ values were higher than 1.0 for the wheat samples from sewage-irrigated area and both sewage-irrigated and smelter-impacted areas, and As is the main contributor to the total THQ and posed the potential risk to human health. Therefore, the accumulation of Cd, Pb, Hg, and As in soils and crops in sewage-irrigated area should be monitored continuously to ensure food safety and security.
