Urban and industrial environmental pollution control in China: An analysis of capital input, efficiency and influencing factors

Guo, Ke; Cao, Yuequn; Wang, Zongfang; Li, Zhengyang

doi:10.1016/j.jenvman.2022.115198

Cited by 50 publications

(17 citation statements)

References 49 publications

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“…Even within the advanced economic urban agglomerations, it is still dominated by the export of laborintensive products, heavy industry and heavy pollution. This industry structure limits industrial optimization and causes environmental pressures [56]. More notably, greening in urban built-up areas does not make a positive contribution to the EE of the four major urban agglomerations.…”

Section: Discussionmentioning

confidence: 99%

Eco-Efficiency of the Urban Agglomerations: Spatiotemporal Characteristics and Determinations

Xue

Wang

Zhang

et al. 2023

Land

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Attaining optimal eco-efficiency is of paramount importance in promoting the sustainable and harmonious development of the economy and environment within urban agglomerations. Firstly, this paper utilizes the Super-SBM model with undesirable output to measure the eco-efficiency (EE) of 64 cities in the Beijing–Tianjin–Hebei metropolitan region (BTHMR), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Chengdu–Chongqing Economic Zone (CCEZ) from 2006 to 2019. Secondly, this study puts forth a novel and comprehensive index system aimed at evaluating the urbanization efficiency and sheds light on the spatiotemporal changes in EE and urbanization efficiency. Finally, the STIRPAT model is used to examine the influencing factors of EE and to investigate the correlation between EE and urbanization efficiency. The study found that the overall EE of the four typical urban agglomerations is high, but the trend varies with a decrease of about 12.9% from 2006 to 2019. The mean EE is in the order of CCEZ > PRD > BTHMR > YRD, with mean values of 0.941, 0.909, 0.842, and 0.732, respectively. The level of science and technology and the urbanization efficiency have a significant positive impact on EE, while population, industrial structure, FDI, and greening level have an inhibitory effect on urban eco-efficiency. Based on the results, policy suggestions such as paying attention to regional heterogeneity and giving full play to the government’s macro-regulatory role in shaping the economic and industrial structure are proposed to serve as a guide for the coordinated development of urban agglomerations under the Dual Carbon Target.

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Section: Discussionmentioning

confidence: 99%

Eco-Efficiency of the Urban Agglomerations: Spatiotemporal Characteristics and Determinations

Xue

Wang

Zhang

et al. 2023

Land

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“…This research emphasizes the essential need for sustainable solutions by placing DFM in the context of China's growing urbanization and environmental issues, as illustrated by the historical "high investment, high energy consumption, and high emissions" growth model [1,2]. The Chinese government's focus on pollution control and green development, as evidenced by policies emanating from significant national directives [61,62] and the alarming statistics on air quality levels in urban centers [63], serves a pertinent backdrop for our study. The "Data Elements Action Plan" for 2024-2026, published jointly by the China Data Bureau and 17 other departments, identifies the use of data elements to facilitate green and lowcarbon production processes as a critical goal.…”

Section: Theoretical Implicationsmentioning

confidence: 99%

Digital Transformation and Urban Green Development: Evidence from China’s Data Factor Marketization

Li,

Du,

Yan

et al. 2024

Sustainability

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Data are the core element of digital transformation. Data factor marketization (DFM) is critical in the process of digital transformation, which promotes urban green development. This paper analyzes the role of digitization in urban environmental sustainability. We investigate the effects of DFM on environmental pollution (EP) using a difference-in-differences approach and data from 283 cities in China from 2006 to 2019. The findings reveal that cities implementing DFM demonstrate an average reduction in EP of 2.67%. The mechanism behind DFM lowering EP involves fostering green innovation, increasing public awareness of environmental issues, attracting IT professionals, optimizing the industrial structure, and enhancing digital finance capabilities. Large cities, cities in the south, and those not primarily dependent on natural resources exhibit a more pronounced reduction in EP through DFM. Implementing policies related to digital infrastructure and enhancing the protection of urban intellectual property rights further amplifies the effect of DFM in reducing pollution. Additionally, this effect exhibits spatial spillover effects. This study contributes to the existing literature by (1) demonstrating DFM’s role in improving urban environmental quality in China through digital technology and market mechanisms, thereby aligning economic growth with ecological sustainability; (2) emphasizing the importance of public engagement in environmental stewardship through increased awareness and community participation in policymaking, as well as fostering social inclusion and ecological conservation; (3) emphasizing spatial spillover effects, the importance of inter-city collaboration in environmental policies, and advocating for comprehensive strategies to achieve broader environmental improvements across urban areas.

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“…The increase of greenhouse gases such as carbon dioxide, comes more from the combustion of fossil energy in addition to the natural production. Core explanatory variables: (1) Formal environmental regulation (ER): Ratio of investment in industrial pollution treatment to GDP (Guo et al, 2022); (2) Informal environmental regulation (FER): Informal environmental regulation mainly refers to the restriction of the media, public participation and public opinion on environmental governance. Composite index based on per capita income, population density and human capital (Hao and Peng, 2017).…”

Section: Threshold Regression Modelmentioning

confidence: 99%

Research on the impacts of dual environmental regulation on regional carbon emissions under the goal of carbon neutrality-the intermediary role of green technology innovation

Dong

Zhong

Liu

et al. 2022

Front. Environ. Sci.

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As an important means to promote regional low-carbon development, environmental regulation has great theoretical and practical significance for achieving the goal of carbon-neutral development in China. Based on the panel data of 30 provinces and cities in China from 2005 to 2019, this paper first uses the intermediary effect model to analyze the impact of the implementation of environmental regulation policies on regional carbon emissions, discusses the relationship between environmental regulation, green technology innovation and carbon emissions, and further uses the threshold effect model to discuss the nonlinear relationship between environmental regulation and regional carbon emissions. The results show that: the improvement of formal and informal environmental regulation can play a role in “forced emission reduction”; Green technology innovation plays a complete intermediary role in the impact of environmental regulation on regional carbon emissions; At the same time, the impact of formal and informal environmental regulation on regional carbon emissions has a threshold effect. Among them, formal environmental regulation has a double threshold effect, the threshold values are 0.429 and 0.502 respectively, while informal environmental regulation has a single threshold effect, the threshold value is 1.803. The results of heterogeneity analysis show that there are obvious differences in the implementation effects of environmental regulation policies under different economic development levels and industrialization development stages. Therefore, we should pay attention to the mutual promotion effect of different types of environmental regulation, strengthen the collaborative emission reduction of environmental regulation and green technology innovation, and improve the level of regional green technology innovation, so as to better promote the realization of regional carbon neutrality goals.

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Urban and industrial environmental pollution control in China: An analysis of capital input, efficiency and influencing factors

Cited by 50 publications

References 49 publications

Eco-Efficiency of the Urban Agglomerations: Spatiotemporal Characteristics and Determinations

Eco-Efficiency of the Urban Agglomerations: Spatiotemporal Characteristics and Determinations

Digital Transformation and Urban Green Development: Evidence from China’s Data Factor Marketization

Research on the impacts of dual environmental regulation on regional carbon emissions under the goal of carbon neutrality-the intermediary role of green technology innovation

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