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Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake China

机译:工业化与环境保护对环境污染的影响-以太湖为例

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摘要

In order to quantitatively study the effect of environmental protection in China since the twenty-first century and the environmental pollution projected for the next ten years (under the model of extensive economic development), this paper establishes a Bayesian regulation back propagation neural network (BRBPNN) to analyze the typical pollutants (i.e., cadmium (Cd) and benzopyrene (BaP)) for Taihu Lake, a typical Chinese freshwater lake. For the periods 1950–2003 and 1950–2015, the neural network model estimated the BaP concentration for the database with Nash-Sutcliffe model efficiency (NS) = 0.99 and 0.99 and root-mean-square error (RMSE) = 3.1 and 9.3 for the total database and the Cd concentration for the database with NS = 0.93 and 0.98 and RMSE = 45.4 and 65.7 for the total database, respectively. In the model of extensive economic development, the concentration of pollutants in the sediments of Taihu reached the maximum value at the end of the twentieth century and early twenty-first century, and there was an inflection point. After the early twenty-first century, the concentration of pollutants was controlled under various environmental policies and measures. In 2015, the environmental protection ratio of Cd and BaP reached 52% and 89%, respectively. Without environmental protection measures, the concentrations of Cd and BaP obtained from the neural network model is projected to reach 2015.5 μg kg−1 and 407.8 ng g−1, respectively, in 2030. Based on the results of this study, the Chinese government will need to invest more money and energy to clean up the environment.
机译:为了定量研究二十一世纪以来中国环境保护的影响以及未来十年预计的环境污染(在广泛的经济发展模式下),本文建立了贝叶斯规则反向传播神经网络(BRBPNN) )分析典型的中国淡水湖太湖的典型污染物(例如镉(Cd)和苯并re(BaP))。在1950-2003年和1950-2015年期间,神经网络模型估计数据库的BaP浓度,Nash-Sutcliffe模型效率(NS)= 0.99和0.99,均方根误差(RMSE)= 3.1和9.3数据库的总数据库和Cd浓度分别为NS = 0.93和0.98,RMSE = 45.4和65.7。在广泛的经济发展模式中,太湖沉积物中的污染物浓度在20世纪末和21世纪初达到最大值,并出现了拐点。在二十一世纪初之后,污染物的浓度受到各种环境政策和措施的控制。 2015年,Cd和BaP的环保率分别达到52%和89%。如果不采取环境保护措施,从神经网络模型获得的Cd和BaP浓度预计在2015年分别达到2015.5μgkg -1 和407.8 ng g -1 。 2030年。根据这项研究的结果,中国政府将需要投入更多的资金和能源来清洁环境。

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