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

Abstract

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.

Trends in the impact of socioeconomic developments on polycyclic aromatic hydrocarbon concentrations in Dianchi Lake

“…To improve the generalization ability of the ANN model, a regularization method was employed, with the objective function F given by (Bui et al 2012;Li et al 2018):…”

Based on the Current Level of Economic Development, Predict PAHs Concentration in Sediment of Dianchi Lake in Southwest China From 2021 to 2030

“…To improve the generalization ability of the artificial neural network model, a regularization method was used, with the objective function F as follows (Bui, 2012;Li et al, 2018):…”

“…Some previous studies have used artificial neural networks to investigate the concentration of pollutants in lake sediments or soils (Anagu et al 2009, Buszewski and Kowalkowski 2006, Jia et al, 2018, Liuet al, 2010, Sari 2012, Shiet al 2015. An artificial neural network can detect the complex nonlinear relationship between the independent and dependent variables (Wösten et al 2001).…”

Dual-Source Optimization of the “Diverting Water from the Yangtze River to Tai Lake (DWYRTL)” Project Based on the Euler Method

“…In order to further compare the simulated water levels with the measured values, this study uses three model evaluation methods, namely, average relative error (MRE), root mean square error (RMSE), and correlation coefficient analysis (R 2 ). e evaluation process involves an error and correlation analysis of the measured values (M) and simulated values (S) with the following formulations [30]:…”