Carbon neutrality challenges in Belt and Road countries: what factors can contribute to CO2 emissions mitigation?

How do income inequality, poverty and industry 4.0 affect environmental pollution in South Asia: New insights from quantile regression

While many factors have been studied as potential causes of environmental degradation, the impact of poverty and inequality has been largely overlooked in the research. The Sustainable Development Goals are aligned with the intersection of poverty, inequality, and the environment. In addition, most previous research has used carbon dioxide (CO2) emissions as a surrogate for pollution. These gaps are filled by this study, which uses ecological footprint (a comprehensive measure of pollution) and CO2 emissions to examine the effects of income disparity and poverty on environmental pollution in 13 nations. Dynamic panel Quantile regression methods are used in this study because of their resilience to various econometric problems that can crop up during the estimate process. The empirical results reveal that the whole panel's carbon emissions and ecological footprint rise when income disparity and poverty exist. When the panel is subdivided, however, we see that income inequality reduces carbon emissions and environmental footprint for the wealthy but has the opposite effect on the middle class. While high-income households see no impact from poverty on their carbon emissions, middle-income households see an increase in both. Overall, the results of this study suggest that income disparity and poverty are major factors in ecological degradation. Therefore, initiatives to reduce environmental degradation should pay sufficient attention to poverty and inequality to achieve ecological sustainability.

Green process innovation, green product innovation, leverage, and corporate financial performance; evidence from system GMM

Natural resource usage has produced various environmental challenges. Green process innovation has been considered a viable option that can help both industry and society. This study investigates the impact of green process innovation and green product innovation on corporate financial performance. We based our findings on a sample of 280 listed non-financial firms operating in South Asia. Information was gathered from firms' annual and CSR reports from 2012 to 2022. This study's data was analyzed using a two-step dynamic panel system GMM, correlation analysis, multicollinearity diagnostic tests, and descriptive statistics. Corporate financial performance is measured with ROA, ROE and Tobin's Q. Overall findings of the study show that green innovation has a significant positive impact on all measures of financial performance. Investing in the innovation of green products and green process can assist businesses in avoiding environmental concerns and regulatory penalties, while also assisting them in establishing new market prospects and achieving new levels of success with their green products. In addition, developing products that are friendly to the environment is tightly connected to expanding green competencies, promoting a company's green image, and improving the company's financial performance. Particularly useful for policymakers in developing countries, the study's findings can be used to introduce paradigm-shifting legislation and penalties that speed up business adoption of green process innovation.

Dynamic nonlinear CO2 emission effects of urbanization routes in the eight most populous countries

A dynamic STIRPAT model used in the current study is based on panel data from the eight most populous countries from 1975 to 2020, revealing the nonlinear effects of urbanization routes (percentage of total urbanization, percentage of small cities and percentage of large cities) on carbon dioxide (CO2) emissions. Using "Dynamic Display Unrelated Regression (DSUR)" and "Fully Modified Ordinary Least Squares (FMOLS)" regressions, the outcomes reflect that percentage of total urbanization and percentage of small cities have an incremental influence on carbon dioxide emissions. However, square percentage of small cities and square percentage of total urbanization have significant adverse effects on carbon dioxide (CO2) emissions. The positive relationship between the percentage of small cities, percentage of total urbanization and CO2 emissions and the negative relationship between the square percentage of small cities, square percentage of total urbanization and CO2 emissions legitimize the inverted U-shaped EKC hypothesis. The impact of the percentage of large cities on carbon dioxide emissions is significantly negative, while the impact of the square percentage of large cities on carbon dioxide emissions is significantly positive, validating a U-shaped EKC hypothesis. The incremental effect of percentage of small cities and percentage of total urbanization on long-term environmental degradation can provide support for ecological modernization theory. Energy intensity, Gross Domestic Product (GDP), industrial growth and transport infrastructure stimulate long-term CO2 emissions. Country-level findings from the AMG estimator support a U-shaped link between the percentage of small cities and CO2 emissions for each country in the entire panel except the United States. In addition, the Dumitrescu and Hulin causality tests yield a two-way causality between emission of carbon dioxide and squared percentage of total urbanization, between the percentage of the large cities and emission of carbon dioxide, and between energy intensity and emission of carbon dioxide. This study proposes renewable energy options and green city-friendly technologies to improve the environmental quality of urban areas.

Synergistic effect of combating air pollutants and carbon emissions in the Yangtze River Delta of China: spatial and temporal divergence analysis and key influencing factors

Synergizing the reduction of air pollutants and carbon emissions (APCE) has become a critical tactic alternative to address the issue of climate change. Taking the Yangtze River Delta (YRD) region of China as a case study, this paper explores the spatial and temporal distribution pattern of the coupling coordination degree (CCD) of combating APCE from 2011 to 2022, analyzes the dynamic change in CCD using the convergence test, and investigates the key factors affecting CCD via the Tobit regression model. The results show that (1) from 2011 to 2022, the air pollutants (AP) and CO2 emission (CE) in the YRD region decrease at the annual rate of 10.32% and 0.85%, respectively; (2) the CCD of reducing APCE in the YRD presents a W-shaped fluctuation before 2016 and then steps into a steady increase status after 2016; (3) the order of CCD in four provincial-level units by 2022 is Shanghai > Zhejiang > Jiangsu > Anhui. The proportion of cities where the CCD of reducing APCE enters the high-coordination period has reached 87.8%; and (4) the Tobit regression results affirm that economic growth, industrial structure, and green technological innovation exacerbate the CCD of combating APCE, while opening-up level mitigates it. The findings offer policymakers valuable insights into the importance of pursuing collaborative governance over APCE and ensuring sustainable development.

A bibliometric analysis of carbon neutrality: Research hotspots and future directions

Global attention has shifted in recent years to climate change and global warming. The international community has set the objective of carbon neutrality to address the climate crisis. Carbon neutrality has drawn significant attention as a crucial step in the fight against climate change, with individual nations having established their carbon neutrality targets. This paper aims to use bibliometric analysis to investigate research hotspots and trends in carbon neutrality research, and accesses the literature through the Web of Science (WoS) core database and undertakes an in-depth examination of 909 publications linked to carbon neutrality around the world using Vosviewer and Bibliometrix software. According to the findings, the number of carbon neutrality publications has increased dramatically in recent years. There are also notable differences in carbon neutrality research across countries and regions. China and the US are the primary drivers and leaders of carbon neutrality research, and developing countries have relatively little carbon neutrality research. Research has concentrated on carbon neutrality's practical, technical, policy, and economic aspects, as well as renewable energy sources, carbon conversion technologies, and carbon capture and storage technologies are also research hotspots. The paper also outlines opportunities for the advancement of carbon neutrality research in the future, including how it might be further integrated with Artificial intelligence (AI) and the metaverse, and how to attack the difficulties and uncertainties faced by the post-epidemic rebound. This study aids in understanding the current state of the field of carbon neutrality research and can be used to guide future studies.

Toward carbon neutrality: a bibliometric analysis of technological innovation and global emission reductions

In the context of global carbon neutrality, climate change mitigation and response has become a top priority. Currently, countries around the world are setting emission reduction targets or are already involved in carbon-neutral actions, with technological innovation becoming the key to global emission reduction. Therefore, a systematic review of the literature related to technology innovation and emission reduction in response to carbon-neutral actions for climate change is conducted. A global bibliometric visualization analysis is presented using CiteSpace and VOSviewer software. This study visualizes the basic relationship between global emission reduction and technology-related literature under the carbon neutrality target and analyzes and discusses the spatial distribution and hotspot trends of the co-author network and knowledge base. The results show that (1) the trend of the number of relevant studies can be divided into two phases before and after, and starts to increase gradually after 2020. (2) The structural relationship of the author- and institution-based cooperative networks is relatively loose, and the main cooperative networks, mainly by countries, are initially formed by the key contributions of developed and emerging economies. (3) Relevant research hotspots are reflected in multiple perspectives such as investment, management, and policy, in addition to emission reduction targets and technological innovation itself. The causal relationship between relevant research and economic and political dimensions has become an important driving factor for research development. Especially in the paradigm shift phase, there are research characteristics of human intervention and specific actions. (4) In terms of future trends, research involving policy management, methodological efficiency, and systemic models will become important research paths in the future by matching the supply of actions to real needs.

Does excessive energy utilization and expansion of urbanization increase carbon dioxide emission in Belt and Road economies?

The phenomenal increase in global temperature and variation in climate change are the replications of nature, alarming governments to limit the emissions of greenhouse gases (GHGs) and adopt green innovation and environmental-friendly clean and green technologies. In this paper, we empirically investigate whether there are any changes in excessive consumption of energy from conventional sources, expansion of urbanization, carbon dioxide (CO₂) emissions, and economic growth in six different regions, namely, East Asia (EA), South Asia (SA), Southeast Asia (SEA), Central Asia (CA), Eastern Europe (EE), and the Middle East and North Africa (MENA), under the Belt and Road Initiatives of panel data over the period of 1985 to 2017. The empirical methods include a panel co-integration check, heterogeneity test, panel Granger causality test, pooled mean group (PMG), and augmented mean group (AMG). To verify the outcomes, robustness tests were carried out using the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) approaches. Our results confirm that CO₂ emissions are primarily influenced by excessive utilization of conventional energy, economic growth, and expansion of urbanization. The findings confirm the co-integrating relationships among the variables in all six regions. Moreover, the panel causality analysis identified a bidirectional causal relationship between energy consumption, economic growth, urbanization, and CO₂ emissions. While these results can play an instrumental role in formulating CO₂ emission policies among our selected countries, our research can also assist policymakers and governments in other developing countries implement important policy initiatives. In this regard, the findings suggest that the current environment-related polices of Belt and Road Initiatives (BRI) do not efficiently tackle CO₂ emissions. In order to achieve the CO₂ emission degradation objective, the Belt and Road countries should restructure their environment-related policies by limiting the consumption of conventional energy and expansion of urbanization. The adaptation and establishment of such a panoramic policy program can assist emerging economies to acquire consolidated and environmentally sustainable economic growth.

Consumption of energy from conventional sources a challenge to the green environment: evaluating the role of energy imports, and energy intensity in Australia

Conventional energy consumption such as coal, natural gas, and oil is a source of deteriorating environmental sustainability as well as a severe challenge to the green environment. The present paper explores the nexus between CO₂ emissions, energy imports, energy intensity, and power generation from renewable and non-renewable energies from 1990 to 2021 in Australia. Based on the ARDL model, the findings reveal that energy imports and power generation from non-renewable energy sources show an adverse effect on the green environment. A 1% increase in conventional energy imports leads to an 11% increase in CO₂ emissions. Similarly, a 1% increase in energy generation from conventional sources will increase CO₂ emissions by 45%. On the other hand, lower energy intensity and power generation from renewable sources reveal a positive effect on environmental quality. A 1% increase in energy intensity will decrease CO₂ emissions by 92% while energy generation from non-conventional sources by 15%. Most interestingly, energy intensity reveals the foremost position among all the selected variables to decarbonize and effectively transform conventional energy to clean and green energy production and utilization. The robustness test outcomes confirm the results of the empirical output. Furthermore, this study suggests that governments and policymakers should focus on the adaptation of lower energy intensity for the purpose to reduce CO₂ emissions and promote a clean and green environment. Finally, power generation from renewable energy sources plays an inevitable role which ultimately helps environmentally sustainability in Australia.