Improvement Of Ecological Efficiency Research Articles

Can industrial collaborative agglomeration drive the regional ecological efficiency improvement to fulfill COP26 requirements?

COP26 provided a roadmap to world leaders for taking policy measure for the climate change effects mitigation. In this regard, policy makers of major countries devoted their overwhelming support. Similarly, to achieve the targets of COP26, the role of industrial and energy sector critically important. In this paper, we have developed a new energy saving path to meet COP26 requirements through the industrial collaborative agglomeration index (ICAI) model which is constructed by taking location entropy of single industrial agglomeration as the basis. The super undesirable SBM (SUSBM) model is constructed to measure regional ecological efficiency (EE). Results show great differences in ICAI among the 3 regions and 11 provinces. Industrial collaborative agglomeration level of the upstream region shows fluctuation upward trend, while that of midstream and downstream regions shows fluctuation downward trend. The EE in downstream region is highest. The impact of ICAI on EE is significant and shows as a U-shaped curve. The increasing of proportion of the secondary industry in the industrial structure and increasing of per capita energy consumption inhibit the improvement of EE. The high proportion of non-state-owned economy in the economic system, the strengthening of environmental regulation intensity, and the improvement of economic development level and push technological innovation are conducive to the improvement of regional EE.

Environmental Regulation Promotes Eco-Efficiency through Industrial Transfer: Evidence from the Yangtze River Economic Belt in China.

How does environmental regulation affect ecological efficiency? What is the role of industrial transfer in the mechanism of action? Relations and interactions between the three determine economic quality when ecological performance is concerned. Empirical studies in this paper are based on samples from the Yangtze River economic belt in China, which contributes nearly half of China’s GDP. By measuring environmental regulation, industrial transfer, and ecological efficiency, data and indexes are prepared for investigating the driving mechanism of environmental regulation and illustrating of the role of industrial transfer. By applying the Markov process to model industrial transfer between regions, the dynamic of transfer is simulated and facilitates further study on the effects of industrial transfer. Finally, this paper concludes that by targeting on the improvement of ecological efficiency, environmental regulation releases its utility through industrial transfer. The highlights include three aspects. Theoretically, it illustrates the driving mechanism of improving the eco-efficiency by environmental regulation. Technically, it pioneers a methodology for describing the regional industrial transfer by modeling it with a Markov process. Practically, the conclusion supplies insights into the inherent law of sustainable development for policy makers.

Spatial-Temporal Pattern and Influencing Factors of Ecological Efficiency in Zhejiang-Based on Super-SBM Method.

The traditional meaning of ecological efficiency generally considers only the ratio of economic output to environmental input. This paper expands the meaning and the evaluation system of ecological efficiency from the perspective of improving people’s livelihoods. Not only are the discharge of wastewater, waste gas, and solid waste included in the undesired output, but the output index also takes full account of the overall development of the economy, innovation, society and the environment from the perspective of high-quality development. Under the assumption of variable returns to scale, a super-efficiency slack-based measure model based on the undesirable output and Malmquist index is introduced to measure the spatial and temporal variation of ecological efficiency of Zhejiang Province in China, and the panel Tobit method is used to study the key factors affecting ecological efficiency. The results include the four following findings: (1) In the past 12 years, the ecological efficiency of Zhejiang Province has steadily increased, except in 2019 and 2020, when seven cities in Zhejiang Province experienced a decline or near stagnation due to the impact of the economic slowdown and the COVID-19 epidemic. (2) The ecological efficiency of Zhejiang demonstrates a severe regional imbalance, showing a high level in the northeast and a low level in the southwest. (3) Malmquist index analysis shows that the improvement of ecological efficiency in Zhejiang Province has shifted from mainly relying on the dual drivers of pure technical efficiency and scale efficiency in the early stage to relying on technological progress in the later stage. (4) Tobit regression analysis shows that industrialization structure, Theil index, and traffic activity have a significant positive effect on ecological efficiency.

Dynamic Measurement Analysis of Urban Innovation Ability and Ecological Efficiency in China

To establish the evaluation index system of urbanization innovation level and ecological efficiency, the entropy method is applied to measure the comprehensive index of urbanization innovation level and ecological efficiency, the VAR model is established, and empirical measurement is used to study the internal relationship and dynamic development between urbanization innovation level and ecological efficiency. The empirical results show the following: (1) The overall development of the innovation level in 30 cities in China is uneven, there is a large gap between the urban innovation level in backwards areas and economically developed areas, and there is a certain coupling effect between the urban innovation level and ecological efficiency. (2) There is a long-term dynamic equilibrium relationship between the urban innovation level and ecological efficiency, which will exert certain pressure on the ecological environment in the process of urbanization. However, the continuous improvement of urbanization will have a positive impact on the improvement of the ecological environment. (3) The improvement of ecological efficiency will also promote the improvement of the urban innovation level. Therefore, this paper puts forwards policy suggestions to promote the harmonious development of urbanization and the ecological environment and provides a reference for realizing the balanced development of urbanization and ecological efficiency in China.

Spatial Interaction Spillover Effects between Digital Financial Technology and Urban Ecological Efficiency in China: An Empirical Study Based on Spatial Simultaneous Equations.

As a core component of the digital economy, digital financial technology has a complex interactive and interdependent relationship with ecological efficiency. From the holistic spatial interaction perspective, this paper uses spatial simultaneous equations and generalized spatial three-stage least squares (GS3SLS) to analyze the spatial interaction spillovers between digital financial technology and urban ecological efficiency based on data from 284 Cities in China from 2008 to 2018. The results show that: (1) Digital financial technology and urban ecological efficiency promote each other, and the latter is relatively dominant. (2) Both digital financial technology and urban ecological efficiency have significant spatial spillover effects. (3) Digital financial technology in surrounding cities has a restraining effect on local ecological efficiency, and the improvement of ecological efficiency in surrounding cities has a siphon effect on local digital financial technology. (4) There is spatial and period heterogeneity in the intensity of the spatial interaction spillover effect between the two. With resources and environment increasingly becoming rigid constraints on economic growth, these findings help identify new drivers of regional ecological efficiency and promote the coordinated development of digital finance and green ecology.

Evaluation of ecological efficiency of resource exhausted cities — a case study of Jilin old industrial base

Based on DEA theory and window analysis method, this paper empirically measures the ecological efficiency of six resource exhausted cities in Jilin old industrial base from 2012 to 2017, and investigates their regional differences and dynamic evolution characteristics. The results show that: in the sample period, the overall ecological efficiency of Jilin old industrial base is low, but fluctuates slightly; the difference between different urban areas is obvious, while the industrial structure and low level of science and technology inhibit the improvement of ecological efficiency.

Evaluating green development level of nine cities within the Pearl River Delta, China

Due to the uncertainties resulted from environmental changes, the importance of green development has been paid increasingly attention in the world. However, our knowledge of the green development level of nine cities in the Pearl River Delta (PRD), China, was still limited. Therefore, this study, based on the analysis on the connotation of green development, employed multi-level evaluation method and entropy method to develop the urban green development evaluation index system from five aspects, including enhancement of living environment, treatment and utilization of pollutant, improvement of ecological efficiency, optimization of economic growth and development of innovative potential. This evaluation index system was further applied to evaluate the green development level of nine cities within PRD. Results showed that significant difference in green development level occurred among cities within PRD. Green development level in Shenzhen, Zhuhai, Guangzhou was relatively higher than that in other cities, with the advantages in improvement of ecological efficiency and optimization of economic growth. Green development level in Zhongshan, Dongguan, Huizhou, Foshan averaged in PRD, while Jiangmen and Zhaoqing had a delayed green development level because of their irrational economic structures and extensive growth patterns though these two cities possessed good ecological environment endowments. In the future, it is necessary for PRD to formulate specific and targeted policies and measures to further upgrade energy structure, transform industrial structure, improve public transportation, enhance forestry carbon sink, and eventually construct low-carbon circular industrial system and development pattern.

Research on the Differences of Ecological Efficiency of Low-carbon M&A among Enterprises under the Education of Ecological Civilization

Environmental education has a substantial impact on the behavior and performance of mergers and acquisitions. Low-carbon M&A is a new mode of mergers and acquisitions under the education of ecological civilization. This paper first analyses the improvement of ecological efficiency of low-carbon M&A in different regions and industries in China, but there are significant differences in the improvement of environmental efficiency in different regions and industries. The higher efficiency industries are mainly distributed in the capital-intensive industries, followed by labor-intensive industries, while the resource intensive industries are the lowest. The cleaner production industries are significantly higher than the pollution intensive industries. The main reason is that there are significant industrial differences in environmental education, energy structure and low-carbon technology. Regional environmental efficiency is higher in the Yangtze River Delta, followed by the Pearl River Delta, the Circum-Bohai-Sea Region, the worst. The main reason is that there are regional differences in environmental education investment, resource endowment, government intervention, marketization level, environmental policy and ecological civilization education system. Increasing investment in environmental education is one of the key means of improving ecological performance.