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Background: The progress of green credit in China is accelerating, but its development is uneven and insufficient in different regions. And whether the issuance of green credit can effectively promote the improvement of the environment and economy is not well understood. Objective: Previous research has found that green credit promotes economic growth through improvement of the industrial structure and green technological innovation. However, these studies have not considered the positive externality of environmental improvement even though environmental improvement and economic growth are requirements of the sustainable development concept. Methods: We use the chain-mediated model to estimate the impact of green credit issuance on the economic growth of different provinces since the large-scale implementation of green credit in China with data from 2008 to 2016. Results and conclusion: This paper shows that the issuance of green credit can improve labor supply rather than labor productivity through the improvement of air quality to achieve regional economic growth. Such a chain-mediated path is different from the economic growth caused by industrial structural adjustment and green technology innovation. At the national level, every 1% increase in green credit issuance relative to industrial loans will increase the per capita gross domestic product (GDP) by approximately 4.6 yuan, or 0.012%, through air quality and labor supply, accounting for 2.875% of the total effect. Heterogeneity analysis indicates that due to regional industrial structure differences and diminishing marginal effects, the impact of green credit is stronger in the western region than in the eastern and central regions. For every 1% increase in the proportion of green credit issuance relative to industrial loans, the per capita GDP growth achieved through the chain-mediated path is approximately 30.17 yuan in the western region, approximately 6.6 times greater than that at the national level. Within a 95% confidence interval of 5000 bootstrap samples, this path is found to be true, and the chain-mediated effect accounts for approximately 12.96% of the total indirect effect. Limitations: The limitation of this paper is the measurement of green credit. Although green credit has a large volume, it remains underdeveloped, and there is a lack of perfect indicators. Most existing studies have adopted only alternative or reverse indicators to measure the issuance of green credit. For example, this paper takes the interest expenditure of six high-energy-consuming enterprises as the reverse indicator, which may to a certain extent lead to the overestimation of the issuance of green credit and its impact on the environment and economy. Future research can accurately explore the performance of green credit on the basis of its mature development. [ABSTRACT FROM AUTHOR]

Air pollution control is crucial for promoting the modernization of governance systems and efficiency. To address the subjective contrived factors and errors in the gross domestic product (GDP) data in traditional statistical almanacs, our study aims to construct a panel data model of 287 prefecture-level cities for the period from 1998-2016 (using objective nighttime light data). We also used government work report words related to environmental regulation to characterize the constraints of government environmental regulations. For this purpose, we used instrumental variables (to explore the relationship and interaction between air pollution and economic growth) and a model setting, with which we carried out regression analysis and robustness tests; the findings were validated using a transmission mechanism hypothesis. We found that that economic growth and air pollution positively influence each other and government environmental regulations significantly reduce air pollution. We also found that to achieve high economic development, environmental pollution must be controlled to avoid further damage to human and material capital. Furthermore, government environmental regulations can help improve the environmental comfort level and economic development quality. [ABSTRACT FROM AUTHOR]

India and China are the biggest developing economies in the world apart from being the most populous nations. The population of China is expected to increase over 1.4 billion by 2050, and India may over take China and become the most populous nation at around 1.6 billion populace. These two nations are home to about 40 % of the total population in the world. Apart from this, India and China have attained remarkable success in the economic growth denoted by higher gross domestic product (GDP). The two nations together contribute about one-fifth of the world GDP. This paper discusses about the changes in the energy consumption pattern of developing countries like China and India aiming towards the sustainable development. Furthermore, this paper also analyses the most important drivers adding to the ecological problems, and gives a further glance at the ecological impacts of these in India and China. Over the last 50-60 years we have been emitting carbon dioxide at an accelerated pace. This has had an effect on the carbon dioxide concentration and other GHG gas concentrations, in the atmosphere. The paper also discusses about the effect of pollutants like NOx, SOx, Particulate matter and Mercury on the environment. [ABSTRACT FROM AUTHOR]

Most of China's resource-based cities are recently threatened by the problems of environmental pollution, resource depletion, and even economic recession. There is an urgent need for these cities to decouple economic growth from environmental degradation through improving resource utilization efficiency and eco-efficiency. This paper quantitatively evaluates the decoupling trends between GDP and environmental damage in major Chinese resource-based cities using big data. To explore the decoupling trends in the development of 115 resource-based cities in China, we develops a model to evaluate the eco-efficiency between economic growth and environmental pollution. Industrial pollutants are used as indicators of environmental degradation and GDP as an index for economic growth. This study finds diverse decoupling levels among the cities and that nearly one-third are developing unsustainably. The cities have encountered serious environmental problems due to past economic policies which have encouraged extensive GDP growth for the past 4 decades. This study demonstrates that the urban development and environmental protection of Chinese resource-based cities are not on a good path. It will be more difficult for the cities with quicker GDP growth to achieve a satisfactory decoupling trend. Therefore, there is an urgent need for industries to undertake resource-conserving and environmental protection measures, and, particularly, endorse technology innovation and the green economy. In order to achieve an overall balanced decoupling in China's resource-based cities, it is essential for local governments to encourage environmentally friendly behaviors and enhance eco-efficiency when developing the country's economy. Finally, the findings illustrate significant unbalanced decoupling levels across Chinese resource-based cities. [ABSTRACT FROM AUTHOR]

Guangdong has become the province with the second largest energy consumption and the largest gross domestic product in China. Studying the energy intensity to realise the sustainable development goal of Guangdong is important. Numerous studies on energy intensity hold a common assumption that regions are spatially independent from a static and macro perspective of the country, which may not always be the case. This study focuses on investigating the spatial aggregation and determinants of Guangdong's energy intensity using the panel data on city level from 2005 to 2016 from a spatial perspective. A novel approach based on the Global Moran-Index (Moran's I) and Durbin model was proposed to deal with the dilemma. From the analytical results, the findings are as follows: (1) Guangdong's energy intensity indicates a strong spatial correlation and clear spatial agglomeration characteristics; (2) Economic growth is the most important influential factor of energy intensity in Guangdong, whereas foreign direct investment has the least impact; (3) The spillover effect of technological progress is significant and can effectively reduce regional energy intensity. Moreover, the study provides references for the implementation of enhancing energy utilisation efficiency. • Spatial correlation and aggregation of energy intensity among cities are confirmed. • Economic growth is the most important factor driving energy intensity. • The direct effect and the overall effect of FDI on energy intensity are opposite. • Technology spillover has been proved to promote regional sustainable development. [ABSTRACT FROM AUTHOR]

In recent years, the correlation between economic growth and environmental pollution has become noticeably contentious in China, which is experiencing the process of transitions in various social and economic sectors, for example, slowing economic growth, reformations to industrial and capital structure, ongoing urbanization, aggravated aging population and a series of environmental challenges, which are also known as a "New Normal" era in the 2010s. In the present study, a test is conducted on the non-linear relationship between economy and environment, which are represented as real GDP (Gross Domestic Product) per capita and carbon emissions per capita, respectively. Based on the data of a non-dynamic panel that covers 30 Chinese provinces from 2001 to 2016, the threshold regression model is applied with fixed effects to understand how the mentioned transitions impact on such relationship as structural breaks, in particular since its "New Normal" era. In brief, according to the estimation results, economic growth with a sustained high level of investment in technology (e.g., Northwest and Southwest China) and environmental protection activities are of empirical significance to cutting down on carbon emissions in China. Moreover, given the emissions reduction during China's economic growth, "Economically significant provinces" concentrated in East China (e.g., Beijing, Tianjin, Shanghai, Jiangsu and Shandong in the present study) ought to develop and transfer their energy structure in a more renewable manner. In the meantime, "Energy abundant provinces" located in inland China are supposed to develop clean mining technology and strengthen their construction of energy delivery channel, which complies with an efficient market mechanism for cross-regional transaction in renewable energy from the perspective of sustainability. [ABSTRACT FROM AUTHOR]

There is a significant challenge in resource management: the perceived trade-off between economic growth and ecosystem conservation. In this study, we integrate a variety of quantitative research methods and models, such as the ecosystem service value (ESV), interval parameter planning (IPP), Dyna-CLUE, and Monte Carlo methods, in an attempt to balance the ESV and economic benefits. The highest system benefits can be obtained, and uncertainty in the ecosystem assessment is considered. Taking the Pearl River Delta as the study area, the results show that when the GDP growth rate is less than 6%, the ESV in 2025 will be higher than the ESV in 2017. An interval approach (upper and lower bounds) is used. For a scenario with a 5% GDP growth rate, the ESV is RMB¥ [1.85, 20.79] × 109, which is more than the ESV of the scenario with a 9% GDP growth rate. When the GDP growth rates are 5% and 9%, the proportions of forestland are [61.5%, 61.7%] and [58%, 58.2%], respectively. Furthermore, spatialization was performed using the Dyna-CLUE model. In 2025, the simulated area of farmland is larger in some small regions with 9% GDP growth rate than it is in regions with 5% GDP growth rate, thus achieving a balance between occupation and compensation of regional farmland. By comparing ecosystem planning under different GDP growth rates, an optimized land-use allocation method can help decision makers balance system benefits and ecological risks, which can provide multiple options and specific locations for decision. Image 1 • A model was built to balance ecosystem services (ES) and economic benefits. • An evaluation system was built to assess the ESV in the lower and upper bounds. • Spatial differences in both ESV and land-use efficiency are considered. • An interval parameter planning (IPP) method and Dyna-CLUE model are integrated. • Decision makers are supported to balance system benefits and ecological risks. [ABSTRACT FROM AUTHOR]

Shi, L.Y., 2020. Changes of industrial structure and economic growth in coastal regions of China: A threshold panel model based study. In: Qiu, Y.; Zhu, H., and Fang, X. (eds.), Current Advancements in Marine and Coastal Research for Technological and Sociological Applications. Journal of Coastal Research, Special Issue No. 107, pp. 278-282. Coconut Creek (Florida), ISSN 0749-0208. Based on 53 coastal cities in China, this paper empirically tests the threshold effect of industrial structure changes on economic growth by establishing threshold panel model. The results show that the rationalization of industrial structure can significantly promote coastal economic growth, but after the real per capita GDP crosses a higher threshold, the driving force becomes weak. The upgrading of industrial structure has a significant negative impact on coastal economic growth within the range of smaller real per capita GDP. However, when the real per capita GDP is higher than a certain threshold, the upgrading of industrial structure can promote coastal economic growth weakly but significantly. In addition, the higher the level of industrial structure upgrading, the stronger the driving force of industrial structure rationalization for coastal economic growth. On the other hand, the effect of industrial structure upgrading on coastal economic growth is negative but not significant when the rationalization of industrial structure is high. However, industrial structure upgrading strongly and significantly slow down coastal economic growth when the rationalization of industrial structure is low. [ABSTRACT FROM AUTHOR]

This study looks at the global trajectory of the relationship between GDP (gross domestic product) and CO2 (carbon dioxide) emission in the time-series, comparative, and transitional point of view (from Y1992 to Y2014). It sets up a measurement framework and compares thirty-seven countries (thirty-six OECD countries and China) through the fuzzy-set ideal type analysis while focusing on the comparative and relational types. This research found that economic growth (GDP) and environmental problems (CO2 emissions) are tied together in a very solid path-dependent relationship. Particularly, the analysis of comparisons among OECD countries and China shows that the relationship between GDP and CO2 emissions is very firmly coupled, unlike the previous non-combination of one-dimensional statistics that are based on the environmental Kuznets curve (EKC) hypothesis. In short, it draws out and highlights the research implications that the existing conventions regarding the relationship between sustained economic growth and GHG (greenhouse gas) emissions reductions are ill-founded at the international comparative level. This paper reiterates the importance of relevant regulatory policies in order to reduce the harmful external effects of GHG and a need for policy measures to solve the problem in the long term. [ABSTRACT FROM AUTHOR]