Suchergebnisse

AbstractThis article expands the study of smart growth from urban space to urban–rural regions based on land use. It analyses smart land use in urban–rural regions. The study sets up an integrated measure indicator system of smart land use in urban–rural regions, which consisted of three subsystems: land amount controls, land form compactness, and land use efficiency. As a case study, the system was used to measure the smart land use in the Pukou District of Nanjing City, an area with intensive urbanization in the Yangtze River Delta of China. The results show that smart land use in the investigated area is increasing year by year, but it remains to be further improved. The integrated measure indicator system of smart land use in urban–rural regions is effective for measuring the level and status of regional smart land use.

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.