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China's extensive economic growth has been accompanied with high levels of pollution, and excessive energy consumption has brought serious pollution problems. The use of financial resources to regulate green production modes and encourage high‐quality economic development has become a major focus in academia. At the same time, growth enterprise market (GEM) enterprises, which mainly operate in technology‐intensive industries, are assumed to have a simulating effect on regional innovation. Therefore, this paper utilizes the capital return differences of 4437 listed companies and 920 GEM companies based in 30 provinces of China from 2008 to 2018 to quantitatively analyze the levels of financial misallocation. With two‐stage regression method, the direct effect of financial misallocation on regional green total factor energy efficiency (GTFEE) and the indirect impact observed when taking regional innovation as an intermediary variable are discussed. Furthermore, dynamic threshold panel regression and heterogeneity analysis are used to verify the above nonlinear relationship. The empirical findings indicate that financial misallocation enhances innovation capability and further restrains GTFEE. With an improved degree of marketization and environmental regulation, the inhibitory effect of financial misallocation on GTFEE is more significant. [ABSTRACT FROM AUTHOR]

This paper uses China's provincial border counties as samples to explore the role played by administrative boundaries in uneven regional economic development. The results indicate that the gap between provincial border counties and other regions is increasing and that economic diffusion to provincial border counties from developed regions is extremely weak. Moreover, provincial border counties have become economically backward. A regression analysis model that includes certain novel factors that are likely to influence economic growth confirms the significant effects of government intervention and administrative boundaries on economic growth in provincial border counties. This paper concludes that administrative boundaries' effects should be nullified by limiting preferential development policies and implementing policies that instead help provincial border counties engage in sustainable development. [ABSTRACT FROM AUTHOR]

Along with the rapid urbanization and economic development, the Yangtze River Middle‐Reach urban agglomeration (YRMR) has suffered from increasingly serious environmental problems. Characterizing the long‐term dynamics of aerosol optical depth (AOD) in YRMR is of important significance for scientific control of aerosol pollutants over this region. Previously, numerous researches have analysed the temporal and spatial characteristics of AOD in different regions through statistical values of AOD time series or using trend analysis methods based on linear regression models. It is challenging to approximate nonlinear trends and identify change points of AOD time series. This paper proposed a new methodology for investigating the dynamics of AOD over the YRMR region on a monthly basis by using the Terra MODIS Collection 6.1 Level 2 aerosol products (MOD04_L2) during 2001–2017. A three‐dimensional spatio‐temporal interpolation method was used to generate gap‐filled monthly AOD maps, and then a generic Bayesian time series decomposition algorithm was applied to analyse the trends and change points of monthly AOD time series. The results showed that the areas with high AOD values were mainly located in the core cities and the connecting belts. Strong positive AOD anomalies had been observed during 2006–2011, whereas the positive anomalies were typically intermingled with negative anomalies and it indicated that the evolution patterns of AOD for different regions were different and influenced by fluctuations. Trend analysis of the monthly mean AOD values indicated that AOD in YRMR increased first, then fluctuated, and finally decreased. Although it was difficult to separate the increasing and fluctuating periods from each other due to the fluctuation, the decreasing trend after 2011 was significant, and a significant drop of AOD had been observed since 2014. Long‐term AOD variations were closely related to national policies, and the results could provide useful references for regional environmental assessment and decision‐making. [ABSTRACT FROM AUTHOR]

Given the rapid development within China, the inequality of available water resources has been increasingly of interest. Current methods for assessing water stress are inadequate for province-scale rapid monitoring. A more responsive indicator at a finer scale is needed to understand the distribution of water stress in China. This paper selected Defense Meteorological Satellite Program Operational Line-scan System night-time stable lights as a proxy for water stress at the province level in China from 2004 to 2012, as night-time lights are closely linked with population density, electricity consumption and other social, economic and environmental indicators associated with water stress. The linear regression results showed the intensity of night-time lights can serve as a predictive tool to assess water stress across provinces with an R2 from 0.797 to 0.854. The model worked especially well in some regions, such as East China, North China and South West China. Nonetheless, confounding factors interfered with the predictive relationship, including population density, level of economic development, natural resource endowment and industrial structures, etc. The model was not greatly improved by building a multi-variable linear regression including agricultural and industrial indicators. A straightforward predictor of water stress using remotely sensed data was developed. [ABSTRACT FROM AUTHOR]

Rapid economic growth is usually accompanied by rising air pollution in China, especially in the economically developed regions. Beijing is the capital of China, which is selected as a study case in this article. The aim of this study is to authenticate if the Environmental Kuznets curve (EKC) hypothesis exists between air pollution and economic growth in Beijing over the period of 1990-2013, and to understand the driving factors of the air pollution by utilizing the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. To avoid the multicollinearity of the driving factors, ridge regression is utilized. CO2, SO2 and dust emissions are served as the air pollution indicators. Results show that, both CO2 and SO2 emissions, contribute to an agreement to the EKC hypothesis, while dust emissions do not. Besides, the turning point of SO2 emissions has already achieved in 1999, whereas that of CO2 emissions will be achieved in 2026. Population, urbanization, and industry structure are introduced into the STIRPAT model. In the STIRPAT model, CO2, SO2 and dust emissions all follow the EKC hypothesis, while only SO2 emissions achieved the turning point in 2006, nevertheless, that of CO2 and dust emissions will be achieved in 2023 and 2070, respectively. Population, urbanization, and industry structure factors all contribute a positive impact on CO2 emissions. However, the three factors all exert negative influence on the SO2 and dust emissions. Finally, policies on addressing air pollution problems in Beijing have been discussed. [ABSTRACT FROM AUTHOR]