We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Study on the influence of industrial structure optimization on water environment and economy: A case study of Changzhou city
Summary
Researchers used an EE-SBM-DEA model to classify industries in Changzhou city by environmental performance and then simulated industrial restructuring using coupled 0-D and MIKE11 hydrodynamic models, finding that optimising the industrial structure could increase water environment capacity for key pollutants including COD, total nitrogen, and total phosphorus in overloaded canals.
Economic development and large amounts of industrial production have led to environmental deterioration. The assessment and prediction of water environment capacity (WEC) are crucial supports for water quality target management. Therefore, this study aims to improve WEC via changes in the industrial structure and to analyze the economic changes. For this purpose, the economic efficiency (EE), water use efficiency (WUE), and water treatment efficiency (WTE) are estimated by the EE–SBM (slack-based measure)–DEA (data envelopment analysis) model. Based on the proposed model, the industry is divided into three types: green enterprises, yellow enterprises, and red enterprises. Yellow enterprises and red enterprises are the major supervision subjects, and the spatial distribution of different environmental risks is identified. The WECs of the main canals are analyzed based on dynamic changes in the industrial structure by integrating the 0-D and MIKE11 models. The results showed that after adjusting the industrial structure, the maximum added values of the WEC of chemical oxygen demand (COD), total nitrogen (TN), ammonia nitrogen (NH 3 –N), and total phosphorus (TP) are 1,744.66 t/a, 536.14 t/a, 24.81 t/a, and 4.16 t/a, respectively. The results show that the canals (R40, R41, R20, R19, and R17) are overloaded with pollutants and indicate that TN is included as a water environment quality assessment target. Furthermore, after the optimization of the industrial structure, the loss of industrial output value is 174.44 million yuan, and the added value of the environmental economy is 232.12 million yuan. The findings provide important technical support for achieving industrial upgrading and sustainable development.
Sign in to start a discussion.
More Papers Like This
Early Warning and Joint Regulation of Water Quantity and Quality in the Daqing River Basin
Researchers developed a dynamic water quantity and quality simulation model for the Daqing River Basin in China, finding that reducing ammonia-nitrogen emissions by 38–85% and maintaining minimum base flows could bring the river's water quality up to standard under extreme flood scenarios.
Exploring the spatiotemporal effects of urban scale and urban vitality on S&D balance in the Yangtze River Delta, China from 2015 to 2025
Researchers analyzed how city growth and economic activity affect the balance between what ecosystems provide (like clean water and clean air) and what people demand in China's Yangtze River Delta, finding that larger urban areas strain this balance while targeted development strategies can help certain regions maintain healthier ecosystems.
The Research on the Influence of Population Agglomeration on Environmental Pollution under the Background of Industrial Upgrading
This study examines how population concentration in cities affects environmental pollution levels, particularly in the context of industrial upgrading in China. Population density and industrial activity are major drivers of plastic waste generation, which is closely linked to microplastic contamination of urban waterways.
Simulation of Water Quality in a River Network with Time-Varying Lateral Inflows and Pollutants
Researchers improved a mathematical model for non-point source pollutant transport in urban river networks by converting the lateral outflow term in the Saint-Venant equations from a constant to a time-varying flow process with linear increase and exponential decay. Applied to Maozhou River Basin, the improved model achieved NSE values of 0.805 and 0.851 for hydrodynamic and water quality simulation, respectively.
The Role of Land Use Transition on Industrial Pollution Reduction in the Context of Innovation-Driven: The Case of 30 Provinces in China
This study analyzed data from 30 Chinese provinces to examine how land use transitions associated with urbanization affect industrial pollution levels, finding that innovation-driven development strategies can decouple economic growth from pollution under certain land use conditions.