Analysis of the Environmental Sustainability of a Megacity through a Cobenefits Indicator System—The Case of Shanghai

City-level synergy and co-benefits of mitigating CO2 emissions and air pollution in China

Synergistic control of carbon emissions and pollutant concentrations can efficiently tackle climate change and air pollution. The synergistic performance and co-benefits yielded by controlling these factors are urgent and critical issues in China. Accordingly, a comprehensive indicator for assessing synergistic performance is pioneered, and co-benefits of mitigating CO2 and PM2.5 in Chinese cities are evaluated. Chinese synergistic performance is dominated by CO2 variations. In 2015-2020, multiple northeastern, central, southern, and eastern cities exhibited synergistic effects by greatly reducing CO2 emissions. The synergistic performance thereafter leads to co-benefits through environmental and economic feedbacks. The CO2 and PM2.5 controls in Northeast Chinese cities feature the most profound co-benefits of approximate 4800 CNY per capita, with each contributing 72 % and 28 %, respectively, to this total. The findings provide intercity synergistic performance and scientific support for policymaking.

Study on the Co-Benefits of Air Pollution Control and Carbon Reduction in the Yellow River Basin: An Assessment Based on a Spatial Econometric Model

To assess the green and low-carbon development of the Yellow River Basin (YRB) in China, this study utilizes an evaluation index system based on the framework of driving force, pressure, state, impacts, response, and management, and it measured the comprehensive scores of the co-benefits of carbon reduction and air pollution control in the YRB. The global Moran index was used to analyze the spatial correlation characteristics of co-benefits, and a generalized spatial measurement model was constructed to demonstrate their spatial spillover effects. The results show that the co-benefits steadily increased every year. The co-benefits had a significant positive spatial correlation and showed a development trend of “up–down–up”. According to the spillover effect test, the economic development level, education level, and intensity of environmental regulations had significant positive effects, while the level of urbanization and foreign investment had significant negative effects. Considering these results and the aim of promoting green and low-carbon development, clear detection of the spatial spillover characteristics of the co-benefits should be prioritized, followed by an understanding of the spatial transmission mechanism of carbon and air pollutant emission and transfer. Policy recommendations are also proposed including upgrading industrial structure, focusing on the development of modern services and high-tech industry, and strictly implementing the industrial environment access system.

Construction and Evaluation of the Integrated Perception Ecological Environment Indicator (IPEEI) Based on the DPSIR Framework for Smart Sustainable Cities

Ecological environment evaluation is of great significance to achieve the Sustainable Development Goals (SDGs) and promote the harmonious development of economy, society, and environment. To evaluate environmental SDGs, single environmental indicators have been analyzed at national or large regional scale in some literature, while the urban integrated environment is ignored. Therefore, it is necessary to systematically and quantically evaluate the sustainability of ecological environment integrating the water, soil, and air environment at the urban scale. This study aims to construct the Integrated Perception Ecological Environment Indicator (IPEEI) based on the Driver-Pressure-State-Impact-Response (DPSIR) framework to solve the above-mentioned problems. The IPEEI model was proposed based on the three-level association mechanism of the Domain-Theme-Element, and the DPSIR framework conforming to the relevant standards for indicator determination. Moreover, the multi-dimensional, multi-thematic, and multi-urban quantitative evaluations were conducted using the entropy weight method, and the comprehensive evaluation grades by the Jenks natural breaks classification method of the geospatial analysis. Nine cities in the Wuhan Metropolitan Area were selected as the experimental areas. The results were consistent with the Ecological Index and local government’s planning and measures, which demonstrated that IPEEI can be effectively verified and applied for the evaluation of urban ecological environment sustainability.