Construction of Urban Environmental Performance Evaluation System Based on Multivariate System Theory and Comparative Analysis: A Case Study of Chengdu-Chongqing Twin Cities, China

Based on the related environmental data of Chengdu and Chongqing from 2011 to 2020, this paper constructs a multivariate environment performance evaluation system, combines the self-built indicator system determination criteria and rules, evaluates and compares the environmental performance of Chengdu and Chongqing, and also discusses the impact of COVID-19 on urban environmental performance. The research results show that the overall environmental performance increased from 2011 to 2020, but there are differences between different subsystems, mainly manifested in the best water environment performance, followed by air environment and solid waste; moreover, the noise environment maintains a relatively stable level. By comparing the average levels of various subsystems of the Chengdu-Chongqing dual cities from 2011 to 2020, it can be seen that Chengdu City has better environmental performance in air environment and solid waste, while Chongqing City has better environmental performance in the water environment and noise environment. In addition, this paper also found that the impact of the epidemic on urban environmental performance mainly comes from the impact on the air environment. At present, the overall environmental performance of the two places has shown a trend of environmentally coordinated development. In the future, Chengdu and Chongqing should further optimize and improve their relatively weak environmental subsystems, deepen the joint action mechanism between the two places, and build a green and high-quality development economic circle for the Chengdu-Chongqing twin cities.

[1]  Dong Han,et al.  Investigation on the spatial and temporal patterns of coupling sustainable development posture and economic development in World Natural Heritage Sites: A case study of Jiuzhaigou, China , 2023, Ecological Indicators.

[2]  Yi Xiao,et al.  Coordination of industrial structure and eco-efficiency in ecologically fragile areas: A case study of the Loess Plateau, China. , 2023, Journal of environmental management.

[3]  Yi Xiao,et al.  Assessing spatial–temporal evolution and key factors of urban livability in arid zone: The case study of the Loess Plateau, China , 2022, Ecological Indicators.

[4]  Yi Xiao,et al.  Investigation on spatial and temporal variation of coupling coordination between socioeconomic and ecological environment: A case study of the Loess Plateau, China , 2022, Ecological Indicators.

[5]  Li Peng,et al.  Response and multiscenario simulation of trade-offs/synergies among ecosystem services to the Grain to Green Program: a case study of the Chengdu-Chongqing urban agglomeration, China , 2022, Environmental Science and Pollution Research.

[6]  Huang Huang,et al.  Towards the Coupling Coordination Relationship between Economic Growth Quality and Environmental Regulation: An Empirical Case Study of China , 2021, Discrete Dynamics in Nature and Society.

[7]  Zujiang Luo,et al.  Suitability evaluation system for the shallow geothermal energy implementation in region by Entropy Weight Method and TOPSIS method , 2021, Renewable Energy.

[8]  Liuna Geng,et al.  How and when higher climate change risk perception promotes less climate change inaction , 2021, Journal of Cleaner Production.

[9]  Peng Huang,et al.  Ecological vulnerability assessment based on AHP-PSR method and analysis of its single parameter sensitivity and spatial autocorrelation for ecological protection – A case of Weifang City, China , 2021 .

[10]  Dayong Zhang,et al.  Demand for green finance: Resolving financing constraints on green innovation in China , 2021 .

[11]  Zongjun Wang,et al.  How environmental regulations affect corporate innovation? The coupling mechanism of mandatory rules and voluntary management , 2021 .

[12]  Xiao Yi,et al.  Does economic development bring more livability? Evidence from Jiangsu Province, China , 2021 .

[13]  Yunna Wu,et al.  A decision framework of low-speed wind farm projects in hilly areas based on DEMATEL-entropy-TODIM method from the sustainability perspective: A case in China , 2020 .

[14]  Claudia Eckert,et al.  A review of fuzzy AHP methods for decision-making with subjective judgements , 2020, Expert Syst. Appl..

[15]  F. Zwiers,et al.  Changes in Annual Extremes of Daily Temperature and Precipitation in CMIP6 Models , 2020, Journal of Climate.

[16]  C. Zang,et al.  A comprehensive evaluation of the eco-carrying capacity and green economy in the Guangdong-Hong Kong-Macao Greater Bay Area, China , 2020 .

[17]  Pengyu Chen,et al.  Effects of the entropy weight on TOPSIS , 2020, Expert Syst. Appl..

[18]  Huibin Du,et al.  Spatial spillover effects of environmental regulations on air pollution: Evidence from urban agglomerations in China. , 2020, Journal of environmental management.

[19]  Gengyuan Liu,et al.  Urban ecological transition: The practice of ecological civilization construction in China. , 2020, The Science of the total environment.

[20]  Yunna Wu,et al.  Data-driven configuration optimization of an off-grid wind/PV/hydrogen system based on modified NSGA-II and CRITIC-TOPSIS , 2020 .

[21]  Kuishuang Feng,et al.  Strategizing the relation between urbanization and air pollution: Empirical evidence from global countries , 2020 .

[22]  Longwu Liang,et al.  The effect of urbanization on environmental pollution in rapidly developing urban agglomerations , 2019, Journal of Cleaner Production.

[23]  Ioannou Konstantinos,et al.  A Decision Support System methodology for selecting wind farm installation locations using AHP and TOPSIS: Case study in Eastern Macedonia and Thrace region, Greece , 2019, Energy Policy.

[24]  Zifeng Liang,et al.  Improvement of Eco-Efficiency in China: A Comparison of Mandatory and Hybrid Environmental Policy Instruments , 2018, International journal of environmental research and public health.

[25]  Yong Deng,et al.  Evidential Supplier Selection Based on DEMATEL and Game Theory , 2018, Int. J. Fuzzy Syst..

[26]  Volker Mauerhofer,et al.  Behavioral patterns of environmental performance evaluation programs. , 2016, Journal of environmental management.

[27]  J. Rezaei.  Best-worst multi-criteria decision-making method , 2015 .

[28]  Will Steffen,et al.  An integrated framework for sustainable development goals , 2014 .

[29]  Ramesh P. Singh,et al.  Comparison of ground based indices (API and AQI) with satellite based aerosol products. , 2014, The Science of the total environment.

[30]  Osman Taylan,et al.  Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies , 2014, Appl. Soft Comput..

[31]  Ru-Jen Lin.  Using fuzzy DEMATEL to evaluate the green supply chain management practices , 2013 .

[32]  B. Pradhan,et al.  Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran , 2012, Natural Hazards.

[33]  H. Levrel,et al.  OECD pressure–state–response indicators for managing biodiversity: a realistic perspective for a French biosphere reserve , 2009, Biodiversity and Conservation.

[34]  Jing Wu,et al.  Index system of urban resource and environment carrying capacity based on ecological civilization , 2018 .

[35]  Chandra Prakash Garg,et al.  An integrated framework for sustainable supplier selection and evaluation in supply chains , 2017 .

[36]  Svatava Janoušková,et al.  Sustainable Development Goals: A need for relevant indicators , 2016 .

[37]  K. Mori,et al.  Review of sustainability indices and indicators: Towards a new City Sustainability Index (CSI) , 2012 .