Affect Carbon Dioxide Emissions Research Articles

Impact of Urbanization on Carbon Dioxide Emissions—Evidence from 136 Countries and Regions

Urbanization affects economic production activities and energy demand, as well as lifestyle and consumption behavior, affecting carbon dioxide emissions. This study constructs the System Generalized Method of Moments (Sys-GMM) model of the impact of urbanization rate on carbon dioxide emissions based on panel data of 136 countries and regions in the world from 1990 to 2020, grounded on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. This study found that (1) there is a negative relationship between urbanization rate and CO2 emissions from 1990 to 2020. (2) The impact of the urbanization rate on CO2 emissions is heterogeneous. An increase in urbanization rate in non-OECD countries significantly reduces CO2 emissions, while the effect is not significant in OECD countries. (3) The carbon intensity of fossil energy consumption moderates the relationship between urbanization rate and CO2 emissions, weakening the effect of urbanization rate on CO2 emissions. Based on these findings, policy recommendations such as promoting urbanization and increasing the regulation and control of fossil energy carbon intensity are proposed.

Pathway to Decarbonization Through Industrial Energy Efficiency: Micro and Macro Perspectives from Compressed Air Usage

Energy audits directly provided the industrial sector with reduced energy costs and avoided emissions. Still, they also lead to far-reaching indirect and induced local, regional, and national benefits. This paper aims to present the techno-economic-environmental analysis to achieve decarbonization through implementing industrial energy efficiency at micro and macro levels. An integrated techno-economic-environmental methodology is developed. Case studies of micro-level carbon reduction efforts through industrial energy efficiency technologies are presented. The broader macroeconomic and environmental effects of technology on society are analyzed using data from 206 energy audits of industrial compressed air systems conducted over 13 years. The impacts show that energy-efficient improvements lead to direct cost savings for manufacturers, boost economic activity across sectors, and affect carbon dioxide emissions both short-term and long-term in the region. Given their extensive benefits, energy audits significantly influence policymaking. We devised a methodology to link micro-level energy audit data with macroeconomic and environmental analyses to quantify these cascading benefits. The economic scenario analysis shows that $228 M has been saved from direct industrial energy savings from implementing all compressed air recommendations in the studied periods and the region. In addition, the investment made through manufacturers would create 2,025 jobs and $383 M annually, cascading regional economic impacts. The environmental analysis shows that the regional manufacturers have directly avoided about 2.8 M metric tons of carbon dioxide emissions.

The relationship between urbanization, energy consumption, economic growth, and carbon dioxide emissions in middle eastern countries: Saudi Arabia, Jordan and Egypt

The Middle East region is a strategic driver of the global economy. However, ensuring environmental sustainability in the context of rapid urban and economic changes remains a major challenge for most Middle Eastern countries. Although researchers have widely examined factors affecting carbon dioxide emissions (CO2), little attention has been paid to the Middle Eastern countries. This study uses an ARDL model to examine the nexus between urbanization, energy consumption, economic growth, and CO2 emissions for three Middle Eastern countries, (Saudi Arabia, Egypt and Jordan) based on panel data for the period from 1990 to 2023. Findings reveal that urbanization has had no significant impact on CO2 emissions in Egypt; this is not in line with the findings for Saudi Arabia and Jordan, where urbanization has reduced CO2 emissions in the long- and short-run, indicating that urban policies are well matched with environmental goals in both countries. However, empirical results indicate that energy consumption has had a positive effect on CO2 emissions in the long- and short-run in all three countries and economic growth has also had a positive impact on CO2 emissions. The fact that economic growth has been unable to mitigate CO2 emissions indicates a mismatch between economic policies and environmental goals. This article suggests a series of valuable insights for policymakers to reduce CO2 emissions.

The gender and culture effect on the CO2 emission empirical analysis.

In recent years, the world has been facing severe challenges from climate change and environmental issues, with carbon dioxide emissions being considered one of the main driving factors. Many studies have proven that activities in various industries and fields have a significant impact on carbon dioxide emissions. However, few studies have explored the impact of gender on carbon dioxide emissions. This study aims to explore the potential impact of gender diversity on carbon dioxide emissions in the boards of directors of developed and emerging market enterprises. In addition, we also analyzed how board cultural diversity affects carbon dioxide emissions. We searched two European indices provided by Morgan Stanley Capital International (MSCI) from the Bloomberg database and conducted empirical analysis. We selected the MSCI index and MSCI emerging market index from 2010 to 2019 as samples and thoroughly cleaned up the data by removing any observations containing missing information on any variables. Statistical methods such as t-test, ordinary least squares, panel data analysis, regression analysis, and robustness testing were used for statistical analysis. At the same time, differential testing was conducted on sensitive and non-sensitive sectors, and the average representation of female boards in sensitive industries was low. The research results show that the proportion of female members on a company's board of directors is negatively correlated with carbon dioxide emissions. This discovery is consistent with the legitimacy theory advocating for gender equality and environmental sustainability, emphasizing the importance of gender diversity in reducing greenhouse gas emissions. However, agency theory suggests that diversity may lead to internal conflicts within a company, leading to agency costs and information asymmetry. The research results show a negative correlation between board cultural diversity and carbon dioxide emissions, indicating the potential challenge of board cultural diversity. This study provides important insights for decision-makers and managers, not only inspiring corporate social responsibility and environmental policy formulation, but also of great significance for academic research in the field of climate change. Our research findings help deepen our understanding of the factors that affect carbon dioxide emissions in different sectors and countries, while also expanding the research field between gender diversity, cultural diversity, and environmental sustainability. Although this study still needs to be further expanded and deepened, it provides useful insights into the relationship between board gender and cultural diversity and carbon dioxide emissions.

Rescheduling Multiproduct Delivery Planning With Digital Technologies for Smart Mobility and Sustainability Goals

In this article, we study a load-dependent vehicle routing problem (LDVRP) to devise a delivery plan for vehicles carrying various types of products (with different quality and rejection rates) to deliver at the lowest cost and environmental impact. Therefore, this study develops a multidepot, multiproduct, multivehicle model considering the demands of customers, rejection rates of products, predefined time windows, speed limits, and extra waiting time. To manage the complexity of such a system, digital technologies support the decisions since the systems’ conditions are dynamic and vary in an uncontrollable way. For example, unexpected changes in traffic require the support of digital technologies to properly handle a full rescheduling by changing both the vehicles’ speed and the waiting time. In terms of sustainability aspects, these decision variables affect carbon dioxide emissions, customers’ satisfaction, and delivery costs. The proposed model will be discussed mathematically and solved using a Genetic Algorithm. Finally, different numerical examples reveal how smart mobility sets the proper decisions and solves the tradeoffs emerging from the analysis of environmental, social, and economic sustainability.

How does new energy demonstration city pilot policy affect carbon dioxide emissions? Evidence from a quasi-natural experiment in China

Energy transition policies are of great significance in adjusting the structure of energy supply and demand and coping with climate change. The new energy demonstration city pilot (NEDCP) policy, as an important pilot project in China's energy transition process, lacks a scientific assessment of the carbon reduction effect of the NEDCP policy and an in-depth explanation of the mechanism of the NEDCP. Based on panel data of 209 Chinese cities at the prefectural and higher levels from 2007 to 2019, this study takes the NEDCP policy as a quasi-natural experiment, using a difference-in-differences model combined with firm-level data to identify the impact of the NEDCP policy on urban carbon dioxide (CO2) emissions. This study analyzes the impact of heterogeneity of urban characteristics on the policy effect from multiple perspectives, and further investigates its mechanism. The conclusions are shown in the following aspects. (1) The implementation of the NEDCP policy decreases urban CO2 emissions significantly. Meanwhile, a series of robustness tests, including the instrumental variables method, propensity score matching difference-in-differences method, placebo test, exclusion of policy interference test, and machine learning method, support this conclusion. (2) The NEDCP policy achieves carbon reduction effects mainly through scale and structure effects. (3) The results of the heterogeneity test show that the NEDCP policy is more effective in cities with higher administrative levels, energy-demanding cities, cities in the southeast of Hu-line, and cities with a higher degree of nationalization. Therefore, the Chinese government should summarize the implementation experience of the NEDCP policy and expand its scope of application. The evaluation of the NEDCP policy in China has important reference value for the energy transition of other developing countries.

Industrial carbon emission forecasting considering external factors based on linear and machine learning models

Accurate forecasting of carbon emissions has become a critical task for the government to formulate effective policies and sustainable development. However, previous studies have mainly focused on large-scale carbon emissions forecasting, while urban-level carbon emission forecasting is equally important but rarely covered. In this study, we propose a novel carbon emission forecasting framework combining linear and machine learning models that considers both time dynamics and external influences. To improve the accuracy and explanatory power of the proposed model, we first introduce twelve initial influencing factors by considering the urban development, economic development, industrial energy consumption, and demographic factors. And then Lasso regression algorithm is adopted to filter out the indicators with poor predictive power. Finally, a combined prediction model by integrating Autoregressive Integrated Moving Average (ARIMA) and Support Vector Regression (SVR) models is established to capture linear and nonlinear features, respectively. The simulation results show that compared with benchmark models, the proposed model indicates stronger prediction performance with a Mean Absolute Percentage Error (MAPE) of 0.096 and a R-squared (R2) of 97.5%. In addition, six future development scenarios, including carbon emission projections for industrial growth and environmental protection factors, are also performed in this study to provide recommendations for carbon emission reduction programmers and related policy formulation. In conclusion, the forecasting framework proposed in this research can help to identify the key factors affecting carbon dioxide emissions and provide a quantitative reference for carbon dioxide emission reduction.

Heterogeneous effects of battery storage deployment strategies on decarbonization of provincial power systems in China

Battery storage is critical for integrating variable renewable generation, yet how the location, scale, and timing of storage deployment affect system costs and carbon dioxide (CO2) emissions is uncertain. We improve a power system model, SWITCH-China, to examine three nationally uniform battery deployment strategies (Renewable-connected, Grid-connected, and Demand-side) and a heterogeneous battery deployment strategy where each province is allowed to utilize any of the three battery strategies. Here, we find that the heterogeneous strategy always provides the lowest system costs among all four strategies, where provinces with abundant renewable resources dominantly adopt Renewable-connected batteries while those with limited renewables dominantly adopt Demand-side batteries. However, which strategy achieves the lowest CO2 emissions depends on carbon prices. The Renewable-connected strategy achieves the lowest CO2 emissions when carbon prices are relatively low, and the heterogeneous strategy results in the lowest CO2 emissions only at extremely high carbon prices.

Do Environmental Taxes Affect Carbon Dioxide Emissions in OECD Countries? Evidence from the Dynamic Panel Threshold Model

The latest decades have been marked by rapid climate change and global warming due to the release of greenhouse gas emissions into the atmosphere. Environmental taxes have emerged as a cost-effective way to tackle environmental degradation. However, the effectiveness of environmental taxes in reducing pollution remains a topic of ongoing debate. The purpose of this paper is to examine empirically the effects of various environmental tax categories (energy, pollution, resource and transport) on CO2 emissions in 34 OECD countries between 1995 and 2019. The dynamic panel threshold regression developed by Seo and Shin (2016) is implemented to assess whether the impact of environmental taxes on CO2 emissions depends on a given threshold level. The locally weighted scatterplot smoothing analysis provides evidence for a nonlinear association between environmental taxes and CO2 emissions. The analysis indicates the existence of one significant threshold and two regimes (lower and upper) for all environmental tax categories. The dynamic panel threshold regression reveals that the total environmental tax, energy tax and pollution tax reduce CO2 emissions in the upper regime, i.e., once a given threshold level is reached. The threshold levels are 3.002% of GDP for the total environmental tax, 1.991% for the energy tax and 0.377% for the pollution tax. Furthermore, implementing taxes on resource utilization may be effective but with limited environmental effects. Based on the research results, it is recommended that countries in the OECD implement specific environmental taxes to reduce greenhouse gas emissions.

Impact of globalisation, remittances and human capital on environmental quality: Evidence from landlocked African countries

AbstractStudying environmental quality is essential for promoting sustainable development and ensuring a healthy and prosperous future for all, as it directly affects human health, well‐being, and quality of life. This paper looks at how globalisation, remittances, human capital, foreign direct investment, and financial growth affect carbon dioxide emissions in landlocked African countries from 1980 to 2018. The study looks at the elasticities between study factors by using second‐generation tests, as well as Continuously‐updated and Fully Modified (Cup‐FM) and Continuously‐updated and Bias‐Corrected (Cup‐BC) tests. The results show that remittances, human capital, natural resources, and income growth all make the environment worse by increasing CO2 emissions, whilst globalisation, foreign direct investment, and financial development all make it better by reducing emissions. The panel causality analysis shows that there are two ways in which transfers and CO2 emissions cause each other, but only one way in which CO2 emissions cause globalisation. Globalisation should be implemented sustainably to avoid irreversible long‐term environmental impacts that deprive future generations of the chance to prosper or maintain their quality of life. It should also empower people and reduce inequality in landlocked countries.

How are green finance, carbon emissions, and energy resources related in Asian sub-regions?

In this research, by employing the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework, for the case studies of five Asian regions and data from 2010 to 2021, the impacts of green finance and renewable resource deployment on CO2 emissions are evaluated. The results confirmed that the effect of green financial development and expansion of renewable energies on carbon dioxide emissions does not have the same pattern in Asia. In Central and South Asia, the development of green finance, patents, and the expansion of renewable energies do not significantly affect carbon dioxide emissions. In contrast, in East Asia, green financial development, exploitation of renewable energies, and patents will reduce carbon dioxide emissions in the short and long term. Accelerating the operationalization of ongoing green projects, promoting FinTech green financing tools, increasing green facilities, implementing tax exemptions, and supporting green research and development are suggested as effective practical policies.

Exploring the roles of green finance and environmental regulations on CO2es: defining the roles of social and economic globalization in the next eleven nations

Achieving sustainable environmental growth and preventing further environmental degradation are challenging goals for policymakers. This study looks at environmental laws and green finance's role in fostering a more sustainable environment. The literature still needs to empirically or theoretically investigate how environmental laws and green financing affect carbon dioxide (CO2) emissions, particularly when combined with moderating factors such as social and economic globalization. As a result, this study investigates how environmental laws and green funding can help the N-11 nations cut their CO2 emissions. Our research uses empirical data from a group of the N-11 nations that span the years 2000 to 2019. To handle issues with panel data analysis, such as cross-sectional dependence and slope heterogeneity, we use advanced panel approaches (CIPS and CADF unit root and cointegration test and cross-sectional augmented ARDL). This research demonstrates that green financing (GFI) and environmental laws (ENV) have a negative but significant effect on CO2 emissions. While social globalization moderates the causal relationship between energy consumption and GDP while negatively and significantly causing GFI and ENV with CO2 emissions among the N-11 countries, economic growth has had a positive and significant effect on CO2 emissions in the N-11 countries. According to our research, nations could achieve the SDG-7 and SDG-13 goals if they adopted green financial and environmental policies.

Factors Affecting Carbon Dioxide Emissions Embodied in Trade

Factors Affecting Carbon Dioxide Emissions Embodied in Trade

How varying population ageing, urbanisation, and institutional quality affect carbon dioxide emissions in South Asia: macro-level evidence

How varying population ageing, urbanisation, and institutional quality affect carbon dioxide emissions in South Asia: macro-level evidence

The effect of transport services and ICTs on carbon dioxide emissions in South Africa.

The rising trend in carbon dioxide emissions has implications on economic livelihoods through global warming and climate change. Attaining lower carbon dioxide emissions is therefore crucial for the realization of the sustainable development goals. South Africa happens to be one of the leading countries in ICT and transport infrastructure in the sub-Saharan African region. Oppossing arguments on how ICT and tranport services affect carbon dioxide emissions exist. However, their effects on the rising trend in carbon emissions in the country has not received much empirical attention. The study analyses the role ICTs and the transportation sector play in the carbon dioxide emissions of South Africa. Regression analysis of data for the 1989–2018 period shows mobile adoption, internet usage, and telephone usage increases carbon dioxide emissions while transportation services in the country helps reduce carbon dioxide emissions. Income positively affects carbon dioxide emissions while urbanization has negative effects. Implications from the findings include the urgent need to have electricity that power ICT devices and equipment be generated from renewable and sustainable sources rather than from heavy polluting sources.

The estimation of the carbon dioxide emission and driving factors in China based on machine learning methods

Global warming can be reduced and the ecological environment can be enhanced by reducing carbon dioxide emissions. Therefore, it is imperative to determine how to calculate urban carbon dioxide emissions. Besides, as the country with the largest carbon dioxide emissions, exploring the influencing factors of carbon dioxide emissions is conducive to providing support for emission reduction actions. In the first place, the paper makes use of China's provincial carbon dioxide emissions data and nighttime light data to build an inversion model from 2000 to 2019 that calculates carbon emission data for prefecture-level cities. Furthermore, this paper employs machine learning methods such as decision tree and random forest to determine the factors affecting carbon dioxide emissions. The main conclusion is that carbon dioxide emissions are highest in the eastern regions with higher economic development. Additionally, cities which are dependent on resources to develop have higher carbon dioxide emissions and a rising trend. Factors such as gross domestic production, financial general budget revenue and foreign investment can influence carbon dioxide emissions. According to the random forest results, the feature importance of GDP, financial general budget revenue and foreign investment is 0.45, 0.12 and 0.08, respectively. Accordingly, different regions cannot ignore carbon dioxide emissions when developing their economies. As the growth rate of emissions has slowed in recent years in part due to government policies, China's ongoing implementation of low-carbon transformation must continue to be implemented, including low-carbon city pilot programs, carbon trading markets, etc. As well, areas with serious carbon dioxide emissions, such as Shanghai, Tianjin, and Chongqing, should be prioritized as areas for low-carbon economic development.

How does export composition improvement affect carbon dioxide emissions in BRI countries? The mediating role of industrial structure upgrading and the moderating role of intellectual property protection.

Climate change, caused by carbon dioxide (CO2) emissions, has become increasingly severe and is a serious constraint on the sustainable development of the global economy. Economists are aware of the close relationship between export trade and the growth of CO2 emissions, especially for the Belt and Road Initiative countries that are experiencing economic growth and transformation. Extant literature also agrees that the composition of the export basket is one of the crucial factors influencing CO2 emissions, but the mechanisms by which changes in the export basket affect carbon emissions from a sustainable production perspective remain unexplored. Based on international trade theory, this study examines how shifts in production patterns affect subsequent CO2 emissions through the lens of exogenously driven changes in the composition of a country's exports, with the consideration of the mediating role of industrial structure upgrading and the moderating role of intellectual property protection simultaneously. The results reveal that export composition improvement contributes to carbon reduction, and industrial structure upgrading plays a significant mediating role in the export composition improvement for carbon reduction. Intellectual property protection moderates the relationship between export composition improvement and industrial structure upgrading. The mediating effect of export composition improvement affecting carbon emissions reduction through industrial structure upgrading is also moderated by intellectual property protection.

Can renewable energy investment reduce carbon dioxide emissions? Evidence from scale and structure

Many countries have invested a lot in renewable energy to reach “carbon neutrality”. However, whether renewable energy investment effectively reduces carbon dioxide emissions still needs to be verified systematically. This paper examines the impact of renewable energy investment on carbon dioxide emissions by considering both scale and structure. It uses data from 13 countries that have made large investments in renewable energy from 2010 to 2019. A parallel multiple mediator model is used to analyze the impact of renewable energy investment scale on carbon dioxide emissions, in which multiplier effect, technique effect, and structure effect are identified as mediation effects. A chain multiple mediator model and a parallel multiple mediator model are integrated to identify the effect of renewable energy investment structure on carbon dioxide emissions, in which allocation effect is also considered. It concludes that, on the whole, increasing renewable energy investment scale can increase carbon dioxide emissions. Specifically, increasing renewable energy investment scale can indirectly reduce carbon dioxide emissions through the technique effect and increase carbon dioxide emissions through the multiplier effect. However, the structure effect on carbon dioxide emissions caused by renewable energy investment scale is not significant. Moreover, increasing the proportional investment in wind energy can reduce carbon dioxide emissions. Meanwhile, increasing the proportional investment in solar energy and bioenergy can increase carbon dioxide emissions. This paper also finds that increasing the proportional investment in renewable hydropower does not significantly affect carbon dioxide emissions.

Is Geopolitical Risk Powerful Enough to Affect Carbon Dioxide Emissions? Evidence from China

Escalating geopolitical factors are closely related to climate warming, but researchers have not fully considered this. Therefore, the purpose of this study is to explore the interaction between geopolitical risk (GPR) and carbon dioxide (CO2) in China. This paper uses the recently developed GPR index and a bootstrap Granger rolling-window estimation. Empirical results spanning different subsamples reveal a two-way causal relationship between GPR and CO2. GPR transforms energy consumption and economic activities through trade disputes, military deployments and energy issues, which have a complex impact on CO2 emissions. Oppositely, CO2 emissions affect GPR through changes in international cooperation and shaping of geopolitical systems. In view of these empirical results, we put forward several policy recommendations. The Chinese government can effectively consider GPR to control CO2 emissions by increasing green investment and signing environmental contracts. Enterprises must focus on research and development (R&D) and investment in new energy innovations. In addition, international organizations can be a useful tool for monitoring decarbonization policies and resolving conflicts between countries.

The nexus between remittances, natural resources, technological innovation, economic growth, and environmental sustainability in Pakistan.

Globally, the issues about sustainable development are on the increase. Moreover, these issues are rising every day in Pakistan, as remittances are increasing, technology innovation is ambiguous, natural resources are degraded, and economic expansion might pose serious challenges to the environment. Thus, this research looks at how remittances, natural resources, technological innovation, and economic growth affect carbon dioxide (CO2) emissions in Pakistan by controlling energy consumption and urbanization from 1990 to 2019. The Bayer and Hanck test of combined cointegration discloses a cointegration between remittances, natural resources, technological innovations, economic growth, and CO2 emissions. Moreover, the autoregressive distributive lag model (ARDL) proposes a significant positive association between remittances and CO2 emissions in the long run, indicating that the increase in remittances distresses the environmental performance of Pakistan. Our study confirms that natural resources decrease CO2 emissions while technological advancement, economic progress, energy use, and urbanization increase CO2 emissions. In addition, the results of robustness checks by employing fully modified ordinary least squares and dynamic ordinary least squares are parallel to the conclusions of ARDL estimations. Furthermore, the frequency causality test results show that remittances, natural resources, technological innovation, economic growth, energy use, and urbanization cause CO2 emissions at different frequencies. Therefore, to achieve the sustainable development goals, appropriate policy repercussions can be developed toward advanced and environmentally sustainable sources of energy.