Emission accounting and drivers in Central Asian countries.

Emerging countries are at the frontier of climate change actions, and carbon emissions accounting provides a quantifiable measure of the environmental impact of economic activities, which allows for comparisons of emissions across different entities. However, currently there is no study covering detailed emissions inventories for emerging countries in Central Asian. This paper compiles detailed and accurate carbon emissions inventories in several Central Asian countries (i.e., Kazakhstan, Kyrgyzstan, Pakistan, Palestine, Tajikistan, and Uzbekistan) during the period 2010-2020. Using the IPCC administrative territorial approach, we for the first time compile their emissions inventories in 47 economic sectors and five energy categories. Moreover, we also investigate decoupling status based on Tapio decoupling model and examine emissions driving factors based on the index decomposition analysis method. The primary results illustrate that carbon emissions in Central Asian countries are increasing with huge differences. Decoupling results highlight that most of the sample countries still need more effort to decouple the economy and emissions except that Pakistan achieves an ideal strong decoupling state. The results of the decomposition indicate that the economy and population both raise emissions, while energy intensity and carbon intensity are negative drivers in some countries. We propose practical policy implications for decarbonization and energy transition roadmap in Central Asian countries.

Toward China's green growth through boosting energy transition: the role of energy efficiency.

The primary purpose of this study is to quantitatively evaluate whether low-carbon energy transition has achieved preliminary progress in facilitating China's green evolution of economy following the provincial dataset. Besides, how improved energy efficiency moderates the influence of energy transition on green growth and the mediation effects are also quantitatively explored. The primary findings insist that low carbonization energy transition is positively associated with green growth, a finding detected by a series of sensitivity checks. Besides, the reciprocal actions between adjusting energy structure and raising energy productivity can effectively strengthen their roles in promoting green growth. In addition, boosting clean energy transition plays an indirect role in green growth by enhancing energy productivity while directly facilitating green growth. Following the three outcomes, this study puts forward some policy implications on enhancing governmental supervision, promoting clean energy evolution, and upgrading ecological protection technologies.

How natural disasters affect carbon emissions: the global case.

The outbreak of the COVID-19 pandemic has once again made the impacts of natural disasters a hot topic in academia. The environmental impacts of natural disasters, however, remain unsettled in the existing literature. This study aims to investigate the impact of natural disasters on CO2 emissions. For this purpose, we employ a panel dataset covering 138 countries over the period 1990-2018 and two dynamic panel estimation methods. Then, considering the differences in CO2 emissions across various countries, we run a panel quantile regression to examine the asymmetry in the nexus between natural disasters and CO2 emissions. We also discuss the mediating effects of energy consumption between natural disasters and CO2 emissions. After conducting a series of robustness checks, we confirm that our results are stable and convincing. The empirical results indicate that natural disasters significantly reduce CO2 emissions. Nevertheless, the impact of natural disasters on CO2 emissions is asymmetric across different quantiles of CO2 emissions. Furthermore, the technology level serves as an important moderating factor between natural disasters and CO2 emissions. The mediating effect results reveal that natural disasters not only directly reduce CO2 emissions but also indirectly promote carbon reduction by restraining energy consumption. Finally, several policy implications are provided to reduce CO2 emissions and the damage caused by natural disasters.

Assessing the impact of trade openness on CO2 emissions: Evidence from China-Japan-ROK FTA countries.

After signing the Regional Comprehensive Economic Partnership trade agreement, China became a proposed signatory to another important trilateral free-trade agreement - the China-Japan-South Korea Free Trade Agreement. In the context of the agreement, we explore the potential effect and internal influencing mechanism of trade openness on this region's carbon emissions from 1970 to 2019. We further detect the impact of the agreement by splitting the full sample into two subsamples, one subperiod before the agreement was signed and the other after it was signed. Then we separately analyze the impacts of imports and exports on carbon emissions and find that: (i) Trade openness positively affects the greenhouse effect, and the signing of the agreement can reduce the promotion effect of trade openness on carbon emissions; (ii) imports contribute to increased carbon emissions while exports significantly reduce carbon emissions in a country; and (iii) expanding trade openness not only directly affects carbon emissions directly, but also has indirect impacts by affecting three main effects (i.e., scale effect, technical effect, and structure effect). Finally, several important policy suggestions are provided to mitigate the greenhouse effect and promote high-quality trade openness.

Does national air quality monitoring reduce local air pollution? The case of PM2.5 for China.

Fine particulate matter (PM2.5) has become a major pressing challenge for China and remains a concern of its central government. This paper draws on a natural experiment generated by the National Ambient Air Quality Monitoring Network (NAAQMN) program in China to explore whether national air quality monitoring reduces local air pollution. In this study, we use a city-level dataset for 4200 Chinese cities covering 2001-2015 and a difference-in-differences (DID) assessment design to assess the impact of the NAAQMN program on local PM2.5 emissions in China. The results suggest that the NAAQMN program significantly reduces the local PM2.5 concentrations by 1.325 mg/m3, and each additional NAAQMN program will cause a decrease of 0.154 mg/m3 in the local PM2.5 concentrations. Furthermore, we determine the heterogeneous impacts of the NAAQMN program on local PM2.5 emission levels through the local government leaders' characteristics, PM2.5 emission levels, and economic development levels. In addition, a mediation effect is found between the NAAQMN program and local PM2.5 emissions through the efficiency of environmental governance. The Chinese government should continue to promote the implementation of the NAAQMN program by promoting the NAAQMN program to the county and rural areas as well as adding the sites of the NAAQMN program in the existing cities. Also, during the process of promoting the NAAQMN program, sufficient differentiation in policies should be developed for different cities.

How does technological innovation mitigate CO2 emissions in OECD countries? Heterogeneous analysis using panel quantile regression.

To verify how does the development of technological innovation effectively mitigate carbon dioxide (CO2) emissions in Organization for Economic Co-operation and Development (OECD) countries, this study first investigates the direct impacts and moderating effects of technological innovation, measured by the development of patents on CO2 emissions by employing a balanced panel dataset for 35 OECD countries covering 1996-2015. Also, to examine the potential heterogeneity and asymmetry, the panel quantile regression approach is utilized. The empirical results indicate that technological innovation directly reduces CO2 emissions; however, this impact is significantly heterogeneous and asymmetric across quantiles. Furthermore, through analyzing the influencing mechanism, the technological innovation affects the impacts of economic growth and renewable energy through its moderating effects. Moreover, the moderating effects of technological innovation is also heterogenous. Accordingly, the main contribution of this study is that the potential heterogeneity and asymmetry of both the direct impact and moderating effect of technological innovation on CO2 emissions in OECD countries are systematically analyzed by employing the panel quantile regression approach.

Decoupling and decomposition analysis of investments and CO2 emissions in information and communication technology sector.

Organization of Economic Cooperation and Development (OECD) economies are facing a substantial increase in the information and communication technology (ICT) investments in the context of rapid spread of the Coronavirus Disease-2019 (COVID-2019) pandemic and constraints of emissions reduction. However, the mechanism of the impact of ICT investments on carbon dioxide is still unclear. Therefore, by employing the decoupling-factor model and Generalized Divisia Index Method, we explore the decoupling states of ICT investments and emission intensity, and the driving factors of ICT investments' scale, intensity, structure, and efficiency effects on carbon emissions in 20 OECD economies between 2000 and 2018. The results indicate that the number of economies with an ideal state of strong decoupling rose to nine between 2009 and 2018 compared to no economies between 2000 and 2009. The emission intensity of ICT investments contributes to a significant increase of carbon emissions, and the structure and efficiency of ICT investments always restrain the growth of carbon emissions. Significant emissions changes caused by the driving factors are shown in many economies before and after the crisis, reflecting the differences in the strategic choices of ICT investments and the impact on emissions due to the crisis such as the COVID-2019 pandemic. And policy implications for energy and carbon dioxide mitigation strategies in the post-COVID-2019 era are also provided.

The greenhouse effect of the agriculture-economic growth-renewable energy nexus: Evidence from G20 countries.

Agriculture is the world's second largest greenhouse gas (GHG) emitter due to the use of fossil fuel-based fertilizers, agricultural machinery, and the burning of biomass. Meanwhile, the Group of Twenty (G20) countries, which include the world's top three agricultural markets, have a significant impact on world agricultural development. This study is the first attempt to examine the effects of the agriculture-economic growth-renewable energy nexus on carbon dioxide (CO2) emissions within the framework of the environmental Kuznets curve (EKC) in a panel of 19 nations of the G20 countries from 1990 to 2014. To do so, panel data unit root tests, cointegration tests, and the panel fully modified ordinary least squares (FMOLS) estimator are used. The main findings are as follows: (1) Panel data unit root and cointegration tests confirm the existence of a long-run relationship among the selected variables, (2) agriculture significantly increases CO2 emissions in the full sample and the developing economies of the G20, while renewable energy consumption reduces the CO2 emissions in the full sample and the developed economies of the G20, (3) the EKC indeed exists in the full sample and developed economies, while economic growth only exerts a positive impact on CO2 emissions for developing economies, indicating that the peak of CO2 emissions for developing economies has not yet been reached, and (4) varied causality links exist among the variables across the different income levels of the G20 countries. Based on the above findings, to suppress the greenhouse effect, the G20 countries' policymakers should not only promote the development of sustainable agriculture, but also stimulate renewable energy consumption, especially in developing economies.

Driving forces and mitigation potential of global CO2 emissions from 1980 through 2030: Evidence from countries with different income levels.

To mitigate global carbon dioxide (CO2) emissions in an effective manner, it is essential to identify the driving forces and estimate the reduction potential of changes to CO2 emissions. Using an extended logarithmic mean Divisia index (LMDI) method, this study decomposes the changes in global emissions between 1980 and 2015 with consideration of different income levels; it also reports on scenario analysis of the global emissions reduction potential up to the year 2030 to explore feasible mitigation pathways. The results suggest that the key driving force responsible for promoting global emissions from 1980 through 2015 is income, while energy intensity is the most significant factor in inhibiting global emissions. Furthermore, the countries with the largest reductions in global emissions are mainly upper-middle-income (UMI) countries. The key driving forces of emissions changes in countries with different income levels offer mixed results. In addition, the forecast results indicate that the future emissions reduction potential across the globe is significant and that UMI countries offer the greatest emissions mitigation potential. Finally, this study provides several targeted policy suggestions for reducing emissions across the globe.

What drives environmental degradation? Evidence from 14 Sub-Saharan African countries.

Although Sub-Saharan Africa (SSA) countries make less environmental pollution compared with other regions, the notably increasing economic growth and accelerating process of urbanization have resulted in the increase of energy needs and, thus, lead to environmental degradation. To empirically investigate the determinants of environmental degradation by accounting for the significant roles played by economic growth, non-renewable and renewable energy consumption, and urbanization, a balanced panel dataset of 14 SSA countries over 1990-2014 is utilized. Also, the ecological footprint (EF), considered a more comprehensive indicator, is used as a proxy of environmental degradation. The results confirm strong cross-sectional dependence within the SSA countries. The Augmented Mean Group (AMG) estimator indicates that economic growth, non-renewable energy consumption, and urbanization exert positive effects on the EF in the SSA countries, while renewable energy consumption plays a negative role in the EF. Moreover, bidirectional long-run causality runs among economic growth, non-renewable consumption, urbanization, and the EF; in contrast, unidirectional causality is found to run from renewable energy consumption to the EF. Therefore, for the SSA countries, the upgrading of industrial structure and further improvement of renewable energy are needed. In addition, urbanization plays a crucial role in contributing to environmental degradation and requires immediate policy response in the SSA countries.

What is the probability of achieving the carbon dioxide emission targets of the Paris Agreement? Evidence from the top ten emitters.

This study predicts the probabilities of achieving the carbon dioxide (CO2) emission targets set by the Paris Agreement and the Intended Nationally Determined Contribution (INDC) of the top ten CO2 emitters (TTCE). The TTCE are China, USA, India, Russia, Japan, Germany, South Korea, Iran, Saudi Arabia and Indonesia based on their emission trends over 1991-2015 period. The methods of trend extrapolation and back propagation (BP) neural networks are used in this paper to overcome the weakness of multiple linear regression (MLR) and the assumptions of the environmental Kuznets curve (EKC). The results show that the model performs well and has high predictive accuracy. The volume of the CO2 emissions by the TTCE in 2030 is predicted to increase by 26.5-36.5%, compared with 2005. According to different trends of economic growth, energy consumption, and changes in share of renewable energy, the results show that China, India and Russia will achieve their INDC targets in some scenarios, whereas there will be a shortfall in achieving targets by USA, Japan, Germany, and South Korea. In particular, the carbon reduction situations of Saudi Arabia, Iran and Indonesia are quite severe. Moreover, the results show that there is no common trend that can be used as a suitable benchmark for every country for the implementation of carbon reductions targets of the Paris Agreement and their INDC goals. Finally, there are signs of improvement of the equality of carbon emissions based on the analysis of the Gini coefficient.

CO2 emissions, natural gas and renewables, economic growth: Assessing the evidence from China.

This study aims to test the environmental Kuznets curve (EKC) for carbon dioxide (CO2) emissions in China by developing a new framework based on the suggestion of Narayan and Narayan (2010). The dynamic effect of natural gas and renewable energy consumption on CO2 emissions is also analyzed. Considering the structural break observed in the sample, a series of econometric techniques allowing for structural breaks is utilized for the period 1965-2016. The empirical results confirm the existence of the EKC for CO2 emissions in China. Furthermore, in both the long-run and the short-run, the beneficial effects of natural gas and renewables on CO2 emission reduction are observable. In addition, the mitigation effect of natural gas on CO2 emissions will be weakened over time, while renewables will become progressively more important. Finally, policy suggestions are highlighted not only for mitigating CO2 emissions, but also for promoting growth in the natural gas and renewable energy industries.