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Nowadays, public health issues are increasingly in the spotlight, and the role played by foreign direct investment (FDI) cannot be ignored, especially in developing countries. Scholars have discussed the influencing mechanism of FDI on public health from both positive and negative aspects, but there is little literature focused on the impact of FDI’s green technology spillovers. This paper explores the impact of spontaneous green technology progress induced by FDI, i.e., FDI’s green technology spillover effect, on the public health status of China. It constructs a theoretical model based on the cost discovery theory and uses the Global Malmquist–Luenberger Method to calculate the green technology spillover index; then, it empirically researches the impact of this spillover effect on public health based on the Grossman health product function, using Chinese provincial data from 2007 to 2019. After a series of robustness tests, this paper also discusses the regional heterogeneity and the influencing mechanism. The main conclusions are as follows: Firstly, there is a significant negative correlation between FDI’s green technology spillover and infant mortality, indicating that the spillover effect significantly promotes China’s public health. Secondly, the results of regional heterogeneity show that the spillover effect of green technology presents a decreasing trend from east to west regions. The threshold effect test results also show that, when the level of economic development is extremely low or exceeds a specific threshold, FDI’s green technology spillover will have a positive impact on public health. Finally, FDI’s green technology spillover improves public health by controlling environmental pollution and optimizing industrial activities, but it does not worsen public health by increasing income inequality. The conclusions of this paper provide empirical support and policy suggestions for rationally and effectively utilizing FDI to promote China’s public health in the future.

As a responsible country, China should take on heavy responsibility of energy conservation and emission reduction, and it is an inevitable choice for China to develop high-tech industries and improve the innovation efficiency of high-tech industries in order to alleviate the current environmental pressure. Therefore, this paper takes the panel data of 30 provinces in China from 2005 to 2016 as the research sample, on the basis of using DEA Global-Malmquist index to measure the innovation efficiency of high-tech industries, it constructs three spatial weight matrices, by including spatial geography, spatial economic geography nesting and innovation, and then it uses Spatial Durbin Model to empirically analyze the effect of innovation efficiency of high-tech industry on CO2 emissions in China from spatial perspective. The results indicate: firstly, in China, CO2 emissions gradually increase from 2006 to 2012, however, some provinces have declined after 2012. And CO2 emissions present a descending trend from eastern coastal area to central and western region. Secondly, affected by “warning effect”, CO2 emissions show a significant negative spatial spillover effect. Thirdly, the overall level of innovation efficiency of high-tech industries in China is not high, and its impact on CO2 emissions is not a simple linear relationship, but shows an “inverted N–shaped” curvilinear relation, and its decomposition index EC and TC also have similar characteristics. Obviously, the research in this paper provides a necessary theoretical support for China and some emerging developing countries to rational formulating and effective implementing the energy conservation and emission reduction policies.

A sustainable financial and economic system is the need of the hour, especially in the context of a deteriorating environment. Environment quality is very important for healthy labour life, contributing to economic growth more effectively. China is one of the largest economies in the world, which is the residency of 18.47% of total humans on planet earth. Keeping environment is a major policy concern; this study investigates the relationship between environmental quality and economic growth in the presence of human capita and renewable energy use. The study uses the data for the time period of 1995–2017. While conducting nonparametric tests, the study applied QMMR regression approach to hand the issues of cross-sectional heterogeneities and endogeneity simultaneously. The study found that GDP is positively associated with carbon emissions throughout all the quantiles. Foreign trade is showing mixed results, most probably due to changes in trade patterns, and a hidden heterogeneity across provinces in China.

Achieving carbon-neutrality has become a global agenda following the ratification of the Paris Agreement. For the developing countries, in particular, attaining a low-carbon economy is particularly important since these economies are predominantly fossil-fuel dependent, to which Bangladesh is no exception. Therefore, this study specifically aimed at evaluating the environmental impacts associated with energy consumption and other key macroeconomic variables in the context of Bangladesh over the 1975-2016 period. As opposed to the conventional practice of using carbon dioxide emissions to proxy environmental quality, this study makes a novel attempt to use the carbon footprints to measure environmental welfare in Bangldesh. The outcomes from this study are expected to facilitate the carbon-neutrality objective of Bangladesh and, therefore, enable the nation to comply with its commitments concerning the attainment of the targets enlisted under the Paris Agreement and the United Nations Sustainable Development Goals declarations. The econometric analysis involved the application of methods that are suitable for handling the structural break issues in the data. The overall findings from empirical exercises reveal that aggregate energy consumption, fossil fuel consumption, and natural gas consumption boost the carbon footprint figures of Bangladesh. In contrast, nonfossil fuel consumption and hydroelectricity consumption are witnessed to abate the carbon footprint levels. Besides, economic growth and international trade are also evidenced to further increase the carbon footprints. Hence, these findings suggest that a clean energy transition within the Bangladesh economy can be the panacea to the nation's persitently aggravating environmental hardships. Furthermore, the causality analysis confirmed the presence of unidirectional causalities stemming from total energy consumption, fossil fuel consumption, natural gas consumption, hydroelectricity consumption, economic growth, and international trade to the carbon footprints. On the other hand, nonfossil fuel consumption is found to be bidirectionally associated with carbon footprints. In line with these aforementioned findings, several key policy suggestions are put forward regarding the facilitation of the carbon-neutrality agenda in Bangladesh.

Abstract Cities are the major contributors to energy consumption and CO2 emissions, as well as being leading innovators and implementers of policy measures in climate change mitigation. Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is an agglomeration of cities put forward by China to strengthen international cooperation among “Belt and Road” countries and promote low-carbon, inclusive, coordinated and sustainable development. Few studies have discussed the emission characteristics of GBA cities. This study, for the first time, compiles emission inventories of 11 GBA cities and their surroundings based on IPCC territorial emission accounting approach, which are consistent and comparable with the national and provincial inventories. Results show that (a) total emissions increased from 426 Mt in 2000 to 610 Mt in 2016, while emissions of GBA cities increased rapidly by 6.9% over 2000–2011 and peaked in 2014 (334 Mt); (b) raw coal and diesel oil are the top two emitters by energy type, while energy production sector and tertiary industry are the top two largest sectors; (c) GBA cities take the lead in low-carbon development, emitted 4% of total national emissions and contributed 13% of national GDP with less than a third of national emission intensities and less than three-quarters of national per capita emissions; (d) Macao, Shenzhen and Hong Kong have the top three lowest emission intensity in the country; (e) most of GBA cities are experiencing the shift from an industrial economy to a service economy, while Hong Kong, Shenzhen, Foshan and Huizhou reached their peak emissions and Guangzhou, Dongguan and Jiangmen remained decreasing emission tendencies; (g) for those coal-dominate or energy-production cities (i.e. Zhuhai, Zhongshan, Zhaoqing, Maoming, Yangjiang, Shanwei, Shaoguan and Zhanjiang) in mid-term industrialization, total emissions experienced soaring increases. The emission inventories provide robust, self-consistent, transparent and comparable data support for identifying spatial–temporal emission characteristics, developing low-carbon policies, monitoring mitigation progress in GBA cities as well as further emissions-related studies at a city-level. The low-carbon roadmaps designed for GBA cities and their surroundings also provide a benchmark for other developing countries/cities to adapting changing climate and achieve sustainable development.

The electric universal service policy, which has been implemented for many years in China, aims to meet the basic electricity demands of rural residents. Electricity consumption can facilitate the daily life of rural residents, such as lighting and cooking, which are necessary to their well-being. In practice, the well-being of rural residents due to electricity consumption is influenced by many factors. Therefore, to improve the well-being of rural residents, it is quite necessary to identify and optimize the significant factors that make the electric universal service policy play its prescribed role as well as possible. In this paper, the significant factors influencing rural residents’ well-being obtained from electricity consumption were identified and discussed by employing the Ordered Probit model. The results indicate that: (1) there are six significant factors, of which ‘educational level’, ‘health condition’, ‘each person income of a family per month’, and ‘service time of household appliances’ play positive roles in rural residents’ well-being, while ‘average power interruption times’ and ‘monthly electric charges’ have negative impacts; (2) for significant factors with positive roles, ‘educational level’ and ‘health condition’ show larger marginal effects on rural residents’ well-being; and (3) for significant factors with negative impacts, ‘average power interruption times’ has the greatest marginal effect. Finally, policy implications are proposed for improving rural residents’ well-being, which can also contribute to the effective implementation of the electric universal service policy in China.

Abstract The development of the regional economy in China is unbalanced. Interregional "carbon leakage" and "carbon transfer" have a significant impact on the realization of carbon emission mitigation targets and the allocation of responsibility. Using China's interregional input-output tables and the corresponding carbon emission data for 2007 and 2010, this paper proposes an interregional Ghosh input-output model and estimates the amount of interprovincial carbon emission transfer from the supply-side perspective. We find that the main direction of supply-side carbon emission transfer is from resource-intensive provinces in the central and western regions to developed provinces in the eastern coastal regions. Further analysis shows that the transfer is mainly concentrated in the production and distribution of electricity and heat, nonmetallic mineral products, and basic metals, whose carbon emissions account for approximately 70% of all sectors’ carbon emissions. The differences between the supply side and the demand side of China's provinces are mainly reflected in the transfer out of carbon emissions.

With the deepening of the concept of sustainable development, a green economy has become the primary goal of urban development. Therefore, to improve the sustainability and far-reaching development of the urban economy, this work first discusses the concept of sustainable development. Second, the concept of a “green economy” is discussed. Lastly, based on the concept of green economic development, this work studies carbon emissions in Hebei Province, China, and discusses the impact of carbon emissions on the urban economy. On this basis, the impact of carbon intensity and CO2 emissions on economic growth is analyzed by establishing an endogenous growth model and state-space model, thereby revealing the importance of carbon emissions to the economic development of Hebei Province. In the analysis process, sensitivity analysis and a robustness test are also used to verify the reliability and robustness of the model results. Finally, this work summarizes the research conclusions and puts forward relevant policy suggestions, which provide a reference for developing a green economy in Hebei Province. The results reveal that from 1999 to 2020, the average output elasticity of labor, capital, and CO2 in Hebei Province are 0.4002, 0.3057, and 0.2941, respectively. This shows that carbon emissions are essential to Hebei’s economic growth. In other words, Hebei’s economic development mainly depends on enterprises with high carbon emissions. Additionally, in the optimistic case, Hebei’s potential output growth rate will show a downward trend, but will soon rise. This indicates that even under strict carbon emission control, Hebei’s economic growth rate will still pick up based on the support of high-tech. This work not only provides a reference for the development of Hebei’s green economic system, but also contributes to the sustainable development of the urban economy in the future.