Influence Carbon Emissions Research Articles

How much financing China needs to achieve carbon peak and carbon neutrality goals?

China requires financial support to achieve its dual‑carbon goals, the carbon emission peak and neutrality. However, currently, there lack of systematic estimation of the amount and structure of finance needed to achieve these goals. This paper attempts to fill the research gap by constructing a simultaneous equations model that characterizes the five core channels that finance contributes to carbon emission. Cointegration estimation, suitable for long-term forecasting, was used to estimate the amount of finance required for carbon emission paths planned by the International Energy Agency (2021) for China to achieve dual‑carbon goals. Finally, the finance structure was estimated using the Bootstrap method. We found that first, estimations of the simultaneous equations model perform better than the existing single equation models. Second, finance influences carbon emissions through economic development, employment (industry) structure, foreign direct investment, energy structure, and energy technology. There are long-run equilibrium relations between these variables. Third, the financing required for the dual‑carbon goals will increase from 2021 and grow at a relatively stable rate higher than history. The earlier carbon neutrality, the more financing is needed. Financing expansion to achieve the emissions peak before 2030 is small, but achieving carbon neutrality before 2060 is challenging. Fourth, the finance structures ranked by their shares in the total amount are indirect financing, other financings, direct financing, and shadow banking. The future paths of these financings have different fluctuation patterns due to their varied embedded risks.

Determinants of Carbon Emission Disclosure in Non-Financial Companies Listed on IDX

According to a report by the Climate Transparency organization, Indonesia is in a critical situation. The organization states that the Indonesian government is not taking adequate steps to meet the Paris Agreement's target of limiting global temperature rise to 1.5°C. As the world's fifth-largest carbon emitter, Indonesia requires concrete actions to reduce its carbon emissions. One approach is to enhance the responsibility and accountability of companies in carbon-intensive industries to disclose their emissions. This study aims to identify the factors influencing carbon emission disclosure. The research uses a population of non-financial sector companies listed on the Indonesia Stock Exchange (IDX) for the period 2021-2023, with 52 samples selected through purposive sampling. Multiple linear regression analysis is applied in this study to examine the relationship between the independent variables and the dependent variable. The results show that firm size affects carbon emission disclosure, while leverage and managerial ownership do not impact carbon emission disclosure.

Understanding the Social Determinants of Household Carbon Emissions for Carbon Mitigation Policies: The Case of Mersin, Turkey

Households are the main consumer-side source of carbon emissions. In Europe, consumer-based CO2 consumption per capita fell from 10.8 tons to 7.8 tons between 1990 and 2022, but in Turkey, the same data showed a rise from 4 tons to 5 tons. Strategies to reduce carbon emissions have recently shifted their focus from the production side to the consumption side. However, because different social segments have varying levels of price sensitivity and differing levels of necessity regarding consuming different items, a simple tax policy only targeting the consumption side is doomed to fail. This has prompted a discussion of the factors influencing carbon emissions on the consumption side and how those factors affect the amount of emissions. This study aims to identify the social determinants affecting household carbon emission levels and to demonstrate that such differences play an important role in effective and efficient carbon emission reduction strategies. In this case study, an appropriate testing method was used to test whether there are significant differences in dependent variables (carbon emissions) between categories of independent variables (the social determinants of households). As our literature review demonstrates, the social determinants of households and the local context were found to have an impact on carbon emissions in the case study. Nevertheless, we found that the degree of association lessens when the relationship between the dependent variables and the independent variables is re-evaluated while controlling for income level. Consequently, it may be concluded that the primary element influencing carbon emissions is income. In our field study, on the other hand, poverty stood out as another important factor affecting the level of carbon emissions. Poverty affects total household carbon emissions in two different ways, causing both carbon-intensive consumer goods and household appliances with low energy efficiency to be preferred because they are cheap to purchase. Therefore, the fight against poverty should be recognized as an important component of carbon reduction policies in Turkey, and the issue of environmental justice should not be ignored, because we know that 30% of the population was living in poverty (compared to the other 70% receiving the national median income) in 2022.

Analysis of the Measurement of Transportation Carbon Emissions and the Emission Reduction Path in the Yangtze River Economic Belt under the Background of “Dual Carbon” Goals

Carbon emissions from the Yangtze River Economic Belt are an important element of China’s carbon emission endeavor, and a study of its emission reduction pathway can provide a reference for the country’s overall management of carbon emission reduction. From the perspective of energy consumption, this paper uses the carbon emission factor method to estimate the carbon emissions of the transportation industry in the Yangtze River Economic Belt during 2006–2020, based on the extended STIRPAT model, considering the influence of seven factors, i.e., population size, urbanization rate, GDP per capita, transportation added value, energy structure, energy intensity, and transportation intensity, on carbon emissions. Based on these factors, a scenario analysis, combined with a forecasting model, is used to predict the peak carbon performance of the transportation industry under different development scenarios. The results show that the overall carbon emissions of transportation in the YEB from 2006 to 2020 show a fluctuating upward trend, and the downstream carbon emissions are significantly higher than those in other regions. The main factors influencing carbon emissions from transportation in different upstream, midstream, and downstream regions vary, with both population and economic factors contributing to carbon emissions, while technical factors affect them differently. There are significant differences in the peak carbon performance of transportation under different development scenarios, and the government should take effective measures to work towards achieving the goals of the low-carbon or enhanced low-carbon scenarios.

Research on the carbon reduction effect of regional industrial transfer in China -- based on the perspective of factor flow

Industrial transfer plays a crucial role in regional carbon reduction efforts in China. This study conducted a systematic analysis of the carbon reduction impact of industrial transfer, focusing on factor flow, and performed empirical tests using Chinese provincial data from 2003 to 2019 with a spatial regression model. The key findings are as follows: (1) Industrial transfer significantly influences carbon emissions, with varying effects depending on the factor flow. Capital and technology flows contribute to carbon emission reduction, while labor flow generally has a negligible impact. (2) Over time, the environmental impact of capital and technology flows intensifies, whereas the influence of labor flow diminishes. (3) Regional variations exist in the impact of industrial transfer on carbon emissions based on the factor flow perspective.

Investigation into Spatial and Temporal Differences in Carbon Emissions and Driving Factors in the Pearl River Delta: The Perspective of Urbanization

Urbanization is a significant indicator of city progress, and as urbanization advances, carbon emissions exhibit an increasing trend that must not be disregarded. Therefore, it is imperative to thoroughly examine the spatial and temporal variations as well as the factors influencing carbon emissions during the urbanization process. In this paper, based on the 2009–2019 PRD region, carbon emissions are measured from energy consumption, industrial production process, solid waste, and wastewater according to the IPCC coefficients, and spatial and spatial differences in carbon emissions are combined with spatial analysis and the drivers analyzed using the gray correlation scale. The results show that: (1) The total carbon emissions in the PRD region have been increasing over the study period, and the distribution of total carbon emissions shows a pattern of “strong in the east and weak in the west”, with energy consumption accounting for the highest proportion of carbon emissions. (2) The global Moran Index of carbon emissions in the PRD has been decreasing, with low and low clustering concentrated in Shaoguan and Zhaoqing, high and high clustering concentrated in Dongguan and Shenzhen, and low and high clustering concentrated in Shenzhen and Guangzhou, with cold spots mainly concentrated in Zhaoqing and hot spots mainly distributed in Guangzhou, Shenzhen, and Dongguan. (3) The degree of economic growth has a substantial influence on carbon emissions in the PRD cities, and the influence of technical advancement has intensified. Guangzhou City is propelled by low-carbon regulations that have a more equitable influence on all elements. Zhuhai City has a more significant influence on energy intensity, while Foshan City has a more noticeable decrease in the effect of foreign investment. To address the issue of carbon emissions, the government should establish appropriate rules to regulate carbon emissions in areas with high emissions, foster collaborative efforts across cities, and encourage the growth of environmentally friendly enterprises.

The Impact of Urban Construction Land Expansion on Carbon Emissions from the Perspective of the Yangtze River Delta Integration, China

Regional integration plays a pivotal role in the socio-economic advancement of various global regions and is closely linked with the expansion of construction land. This expansion is a major contributor to urban carbon emissions. Utilizing a geographical regression discontinuity design (GRDD), this paper estimates the impact of urban construction land expansion on carbon emissions and explores the underlying mechanisms within the regional integration process of the Yangtze River Delta (YRD), China. The findings reveal that urban construction land expansion significantly influences carbon emissions, displaying an inverted “U”-shaped pattern. Furthermore, this expansion affects carbon emissions through the transformation of industrial structures, shifts in consumption patterns, and enhancements in scientific and technological investments. Our findings span the performance of the Yangtze River Delta from its early development stages to a relatively mature phase. This paper also partially reveals how the Yangtze River Delta, with both megacities and large- to medium-sized cities, manages urban construction land expansion during the integration process and strives for low-carbon emissions reduction. These results can provide green growth recommendations that balance socio-economic development, low-carbon emissions, and social equity not only for other urban agglomerations in China but also for similar regions in other developing countries by altering construction land utilization patterns.

The asymmetric effect of global value chain on environmental quality: Implications for environmental management

This study examines the dynamic relationship between global value chain integration, and carbon emissions, in 57 developing economies from 2000 to 2018. Our results show a multipart link between GVC involvement and carbon emissions. Specifically, forward participation, which involves domestic content in foreign exports, offers the potential to reduce emissions, whereas backward participation, defined by foreign content in domestic exports, typically increases emissions. This imbalance draws attention to the dual nature of using mineral resources, which can contribute to and mitigate environmental damage depending on the extent of GVC engagement. The NARDL model employed in the study also reveals the dynamic and nonlinear responses of carbon emissions to variations in the utilization of mineral resources within GVCs. Our findings show that positive shocks to mineral resources use within GVCs negatively influence carbon emissions, while adverse shocks have less impact. The results have significant policy implications, indicating that developing nations should prioritize environmental sustainability while planning their GVC participation. This entails promoting value-added mining resource use initiatives and pushing for strict environmental regulations in GVCs. Our results also highlight the significance of implementing customized measures to mitigate economic activity's asymmetric and nonlinear impacts on environmental quality. It enlightens policymakers in developing nations on balancing environmental conservation and economic growth in a global economy that is becoming more interconnected.

Analysis of factors influencing carbon emissions in the evolution of road electrification in Beijing

Analysis of factors influencing carbon emissions in the evolution of road electrification in Beijing

The Dynamics of Energy-Related Carbon Emissions and Their Influencing Factors in the Yangtze River Delta, China

Chinese cities are pursuing an energy transition to decouple energy-related carbon emissions (ERCEs) from economic growth. Despite numerous studies focusing on the factors influencing carbon emissions, few have quantitatively analyzed their respective contribution rates, thus leaving a gap in effectively guiding policies. This study took 16 cities in the Yangtze River Delta (YRD) as the study area. The decoupling between ERCEs and economic growth was analyzed during 2000–2020, and the contribution rates of different factors were explored. The results showed that the total ERCEs increased from 413.40 million to 1265.86 million tons during 2000–2020, increasing by over three times. Coal and oil were the dominant energy sources in most cities, but natural gas consumption increased from 0.15% to 5.96%. Moreover, 14 cities showed a decoupling status, indicating a certain win–win situation between economic growth and ERCE reduction. Economic growth greatly increased ERCEs, with its contribution rate ranging from 114.65% to 493.27% during 2000–2020. On the contrary, energy structure and energy intensity both contributed to reducing ERCEs in most cities, and their maximum contribution rates reached −32.29% and −449.13%, respectively, which were the main forces for the win–win situation. Finally, carbon reduction proposals are put forward, which provide theoretical support for achieving the “Double Carbon” goal in the YRD.

Modelling the factors influencing carbon efficiency of consumer choice to promote energy-efficient vehicles

This study investigates the main factors influencing carbon emissions from Four Wheel Passenger Vehicles (FWPVs) in Sri Lanka, an emerging economy where the transport sector contributes 12 % of total emissions. Pioneering a new methodology, we integrate System Dynamics (SD) modeling and decomposition analysis to comprehensively map the factors affecting fuel efficiency for the first time in Sri Lanka. Employing the additive Logarithmic Mean Divisia Index (LMDI I), we analyze a comprehensive time series dataset covering all petrol, diesel, and electric-powered FWPVs registered between 2015 and 2019. Our study delves into significant drivers of CO2 emissions, including population dynamics, vehicle ownership trends, annual travel distances, fuel types, engine capacities, and technological advancements. Additionally, we quantify the impact of fiscal policies on FWPV emissions, revealing a surge in emissions in 2018 and 2019 driven by consumer preferences for high-capacity vehicles. Our findings offer critical insights for crafting effective policies to promote energy-efficient vehicles and mitigate carbon emissions in the transport sector, emphasizing the importance of targeted fiscal measures. By imposing taxes on high-capacity vehicles and incentivizing the adoption of low-emission options through tax variations and renewable energy incentives, policymakers can influence consumer behavior and drive significant emission reductions. Our study underscores the need for ongoing monitoring and evaluation of fiscal policies to refine existing measures and accelerate the transition towards a sustainable, low-carbon transportation sector in Sri Lanka.

Study on the Evolution of Spatial and Temporal Patterns of Carbon Emissions and Influencing Factors in China

Abstract: Industrialization has increased global carbon emissions, necessitating effective climate change mitigation measures. China, the most populous developing nation, faces the challenge of strategizing emissions to meet national carbon neutrality objectives. However, research on specific regions’ carbon emissions drivers and causal factors is limited, particularly across prefectural-level cities. This study estimates the spatial and temporal patterns of carbon emissions across China’s prefectural cities and utilizes both OLS regression and stepwise regression models to analyze the impact of various factors influencing carbon emissions in these cities. Results reveal the following: (1) The country’s overall 20-year carbon emissions continue to grow from 3020.29 Mt in 2001 to 9169.74 Mt in 2020, with an average annual growth rate of 5.71%; the eastern region has seen a gradual deceleration in emissions, whereas the western region continues to experience an increase. Carbon emissions in cities within each subregion consistently rise. (2) Carbon emissions in Chinese prefectural-level cities exhibit strong spatial autocorrelation and clustering (Z > 1.96, p < 0.05), with hot spots primarily in the eastern coastal areas and cold spots in the northwest to southwest regions. (3) Economic and demographic factors significantly increase carbon emissions, while climate and urbanization effects are more complex and variable. Economic growth and population increase are the most significant influencing factors, but regional variances exist in carbon emissions determinants in subregional prefectural cities. These insights provide valuable insights into national emission dynamics at the prefectural level, providing a theoretical basis for enhancing carbon emission strategies across various jurisdictions.

CARBON EMISSIONS DISCLOSURE IN INDONESIA: THE IMPACT OF INSTITUTIONAL OWNERSHIP

This research aims to determine the effect of institutional ownership on carbon emissions disclosure, with leverage, number of top executives, company age, company size, and profitability as control variables. The sample in the research was non-financial companies listed on the Indonesia Stock Exchange, but during the research, several companies were eliminated due to incomplete data from 2018-2022. After statistical analysis and modelling, this research found that institutional ownership influences carbon emissions disclosure. In addition, control variables that influence carbon emissions disclosure are the number of top executives, company age, and company size. So the results of this research are in line with the proposed hypothesis. Although this research is limited in the available sample size because not all companies disclose carbon emissions, its novelty lies in the fact that disclosing carbon emissions for all non-financial companies in Indonesia is still an interesting topic to research related to the issue of climate change and global warming.

Does Economic Complexity Influence Carbon Emissions? Evidence from Next Eleven Countries

Abstract Research Purpose The study examines the effect of economic complexity on carbon dioxide emissions in the Next 11 countries with the view to validate or refute the economic complexity-Kuznets curve (EcKC) between 1995 and 2019. The Next 11 countries include Bangladesh, Egypt, Indonesia, Iran, Mexico, Nigeria, Pakistan, Philippines, South Korea, Turkey, and Vietnam. Design/Methodology/Approach Two econometric methods, correlated Panel standard error (PCSE) and feasible generalized least squares (FGLS) estimating techniques, are used to achieve the objectives of the study. Findings The estimates from the FGLS approach are consistent with that of the PCSE approach. The results from both techniques show that economic complexity increases carbon emissions in the Next 11 countries. Also, from the EcKC, the study invalidates the hypothesis and supports a positive monotonic linear relationship between economic complexity and carbon emissions, which also means the “pollution haven hypothesis”. Originality/Value/Practical Implications The study examines whether the environmental Kuznets curve (EKC) in the Next 11 countries is valid or not. To do this, the current study is different from earlier studies in that it uses economic complexity—that is, the economic complexity-Kuznets Curve (ECKC)—instead of GDP. This is explained by the fact that environmental issues should involve the development of more advanced commodities rather than just raising an economy's GDP productivity. And most of the countries in the Next 11 countries are currently shifting their economies to produce more complex goods.

Can financial development affect environmental quality in the presence of economic uncertainty and informal activities? Exploring the linkages in the middle-income countries

PurposeThe significance of this research lies in providing an understanding of how economic conditions, including financial development, informal economic activities and economic uncertainty, influence carbon emissions and tries to offer valuable insights for policymakers to promote sustainable development.Design/methodology/approachThe Panel-ARDL method is employed for a group of 30 developing countries from 1990 to 2018. This study analyzes the data obtained from the World bank, International Monetary Fund and World Uncertainty databases.FindingsBased on the empirical results of the extended model, an increase in GDP and energy intensity is associated with an 83 and 14% increase in carbon emissions, respectively. Conversely, a 1% increase in financial development and economic uncertainty is linked to significant decrease in carbon emissions (about 47 and 23%, respectively). Finally, an increase in the informal economy can lead to a negligible yet significant decrease in carbon emissions. These results reveal that financial development plays an effective role in reducing CO2 emissions. Moreover, while economic uncertainty and informal economy are among unfavorable economic conditions, they contribute in CO2 reduction.Practical implicationsTherefore, fostering financial development and addressing economic uncertainty are crucial for mitigating carbon emissions, while the impact of informal economy on emissions, though present, is relatively negligible. Accordingly, policies to control uncertainty and reduce the informal economy should be accompanied by environmental policies to avoid increase in emissions.Originality/valueThe originality of this paper lies in its focus on fundamental changes in the economic environment such as financial development, economic uncertainty, and informal activities as determinants of carbon emissions. This perspective opens up new avenues for understanding the intricate relationship between carbon emissions and economic factors, offering unique insights previously unexplored in the literature.

Environmental, social and governance assets and diversity scores: exploring their relationship to carbon emissions in global companies

PurposeThe interconnected challenges of climate change and social inclusivity have placed unprecedented pressure on businesses to adopt responsible practices. While previous research has explored the individual impacts of environmental, social, and governance (ESG) performance and diversity initiatives, there remains a dearth of comprehensive investigations into how these factors collectively influence carbon emission scores. Drawing on the legitimacy theory, we explore whether ESG and diversity scores predict global companies' carbon emission scores. As concerns about the environmental impact of businesses grow, understanding the relationships between ESG performance, diversity management, and carbon emissions becomes imperative for sustainable corporate practices.Design/methodology/approachThe primary dataset for this study includes 1,268 worldwide firm-year data for 2021. The sample is subjected to missing data examination as a component of the filtration process. Data preprocessing is performed before machine learning analysis, including verifying missing data. Our research resulted in the final sample, which includes 627 worldwide firm data from 2021. Data regarding all publicly traded companies was obtained from Refinitiv Eikon.FindingsOur findings showed that corporate carbon emission performance in global corporations is influenced by ESG performance and total diversity score.Originality/valueFirms involve in ESG as well as diversity practices to be able to achieve sustainable success. Yet, the forecasting of carbon emissions based on ESG scores and diversity scores remains inadequately established due to conflicting findings and enigmas prevalent in the literature.

Climate governance and carbon emission disclosure

PurposeThe purpose of this study is to shed light on the influence of climate governance on carbon emission disclosure.Design/methodology/approachThis study is based on S&P BSE 500 Indian firms over six years, i.e. from 2016–2017 to 2021–2022. The panel regression has been used to determine the association between climate governance and carbon emission disclosure.FindingsThe results of this study suggest that climate governance exerts a significant influence on corporate carbon emission disclosure. Moreover, results corroborate that climate governance elements such as the environment committee, carbon strategy and environment management system are critical contributors to carbon emission disclosure.Practical implicationsThis study adds to the emerging literature on climate change, carbon emission disclosure, corporate governance and climate governance.Social implicationsThis work provides valuable insights to corporate managers and policymakers as the study concludes that climate governance enhances firms’ carbon emission disclosure.Originality/valueEarlier literature has examined the influence of corporate governance on carbon emission disclosure. However, this study extends to the corporate governance literature by providing novel insights into how integrating climate governance elements into corporate governance can influence carbon emission disclosure. Moreover, to the best of the authors’ knowledge, this study is the first to explore the association between climate governance and carbon emission disclosure in the Indian context.

Research on the impact of ESG performance on carbon emissions from the perspective of green credit

Utilizing panel data from 30 Chinese provinces, this research examines the non-linear relationship between regional environmental, social, and governance (ESG) performance and carbon emissions (CE) from the viewpoint of green credit. The study reveals a single threshold effect between ESG performance and CE, with green credit acting as the threshold variable. When the amount of green credit in a region exceeds the threshold, the growth rate of CE in that region begins to decline with higher ESG scores. Furthermore, green credit acts as a catalyst, playing a negative moderating role between ESG performance and CE, validated by both threshold regression and fixed effects models on panel data. Green credit indirectly influences carbon emissions by supporting green innovation, thus facilitating the transition to a greener economic development framework. Lastly, regional disparities are found in the moderating influence of green credit between ESG performance and CE. In regions with high ESG performance, the moderating impact of green credit is smaller, while in regions with low ESG performance, the effect is more significant. The research findings offer theoretical backing for policymakers regarding the efficacy of ESG in achieving carbon neutrality objectives, and offer valuable strategic recommendations for the diversified formulation of green credit strategies on both national and provincial scales. Regional heterogeneity test results provide valuable support for formulating policies that encourage green credit in provinces with low ESG performance.

The Effect of Built Environment on Carbon Emission from Travel Behavior in the City center of Surabaya

Climate change is currently demanding attention due to global warming caused by increased Greenhouse Gas (GHG) emissions from the land transportation sector. The built environment is one of the factors that can influence non-motorized travel and emissions production. The built environment is identified using the 3D component approach (Density, Diversity, Design). The City center of Surabaya area is one of the Central Business Districts (CBDs) that is not exempt from emission issues and has the potential to decrease emissions through environmental arrangement scenarios. This research investigates the correlation between the 3D components and carbon emission production using the method of correlation analysis and multiple linear regression. The analysis results show a significant correlation between carbon emission production and the travel behavior of the city center of the Surabaya area community. Travel behavior variables influencing carbon emission production are household income, vehicles ownership, and travel distance. Furthermore, the study results indicate a significant relationship between travel behavior and the 3D components, as well as a significant association between the 3D components and carbon emission production. The 3D components that affect carbon emission production are population density, land use mix index, and pedestrian pathway density.

Decoding enterprise digital transformation: External oversight and carbon emission reduction performance

Enterprise digital transformation (EDT) is a strategic initiative that provides robust support for optimising resource allocation, fosters business innovation, and significantly impacts ecological environment to increase financial performance. This study re-examines the substantial contributions of EDT to climate change mitigation. Drawing on data from Chinese A-share listed companies from 2010 to 2021, we investigated the changes and mechanisms influencing carbon emissions reduction performance (CERP) of enterprises undergoing digital transformation. The empirical results indicate that EDT actively contributes to enhancing the CERP of enterprises, with a more pronounced effect observed in non-polluting industries, state-owned enterprises, and manufacturing companies. Furthermore, empirical findings from mechanism tests reveal that EDT effectively improves the CERP by driving green technological innovation, strengthening industry chain connections, and enhancing capacity utilisation. Finally, within external oversight groups, particularly in government and investor supervision, the enhancement of enterprise CERP is more significant, highlighting the crucial role of external oversight in the EDT process.