Nexus between energy use, industrialization, forest area, and carbon dioxide emissions: New insights from Russia

Nexus between carbon emissions, economic growth, renewable energy use, urbanization, industrialization, technological innovation, and forest area towards achieving environmental sustainability in Bangladesh

The dynamic nexus between economic growth, renewable energy use, urbanization, industrialization, tourism, agricultural productivity, forest area, and carbon dioxide emissions in the Philippines

Global climate change caused by greenhouse gasses (GHGs), particularly carbon dioxide (CO2) emissions, poses incomparable threats to the environment, development, and sustainability. This research investigates the potential of economic growth, renewable energy use, and forested area toward achieving environmental sustainability in Malaysia by reducing CO2 emissions. Time series data from 1990 to 2019 were utilized by applying the Dynamic Ordinary Least Squares (DOLS) method. The empirical findings show that the coefficient of economic growth is positive and significant, indicating a 1% increase in economic growth is related to a 0.78% rise in CO2 emissions. In addition, the coefficient of renewable energy use is negative but not significant, suggesting that increasing renewable energy use by 1% is associated with CO2 emissions reduction by 0.10%. Finally, the coefficient of forested area is negative and significant, implying that increasing forested area by 1% is linked with a 3.86% reduction in CO2 emissions. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test was utilized to capture the causal relationship between the variables. The empirical outcomes reveal that economic growth deteriorates the environmental quality in Malaysia while enhanced renewable energy use and forested area can reduce Malaysia's carbon emissions. This study put forward policy recommendations for a low-carbon economy, promoting renewable energy, and sustainable forest management which could help to achieve environmental sustainability through emission reduction in Malaysia.

Global climate change caused by Greenhouse Gases (GHGs), particularly carbon dioxide (CO2) emissions, poses incomparable threats to the environment, development and sustainability. Vietnam is experiencing continuous economic growth and agricultural advancement, which causes higher energy consumption and CO2 emissions. Understanding Vietnam’s sensitivity to climate change is becoming more crucial for governments trying to reconcile climate change mitigation and sustainable development. Analyzing pollution-development trade-offs can help minimize environmental degradation in Vietnam. Therefore, the present study empirically investigated the nexus between economic growth, energy use, agricultural added value and CO2 emissions in Vietnam. To investigate the short-run and long-run relationships between the variables, this study employed the autoregressive distributed lag (ARDL) technique and the Vector Error Correction Model (VECM) using the time series data from 1984 to 2020 for Vietnam. The empirical findings indicated that economic growth and energy use trigger environmental degradation by increasing CO2 emissions, whereas enhancing agricultural added value improves Vietnam’s environmental quality by reducing CO2 emissions in both the long-run and short-run. The estimated results are robust compared with alternative estimators such as dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). This research contributes to the existing literature by shedding light on the potential of agricultural added value to reduce emissions in Vietnam and provides policy recommendations in areas of low-carbon economy, promoting renewable energy, and sustainable agriculture that can reduce CO2 emissions in Vietnam.

This study investigated the dynamic effects of economic growth, renewable energy consumption, urbanization, industrialization, tourism, agricultural productivity, and forest area on carbon dioxide (CO2) emissions in Chile. Using the dynamic ordinary least squares (DOLS) approach, time series data from 1990 to 2020 were analyzed. A 1% increase in economic growth, urbanization, industrialization, and tourism will increase Chile's CO2 emissions by 0.62%, 0.24%, 0.15%, and 0.1%, respectively. Additionally, a 1% increase in renewable energy consumption, agricultural production, and forest area may lead to CO2 emission reductions of 0.55%, 0.20%, and 0.98%, respectively. The estimated outcomes are insensitive to alternative estimators such as fully modified ordinary least squares (FMOLS) and canonical cointegrating regression (CCR). In order to ensure environmental sustainability through emission reductions, this article recommends policies on low-carbon economies, renewable energy consumption, sustainable urbanization, green industrialization, eco-friendly tourism, climate-smart agriculture, and sustainable forest management.

BackgroundInternational awareness of the impact of global warming and climate change is increasing. Developing countries face the task of achieving sustainable economic growth while also improving the efficiency of their energy consumption. The E7 countries (Brazil, India, Indonesia, Mexico, People’s Republic of China, Russia, and Turkey) are all highly concerned with the promotion of carbon-emission-reduction strategies.MethodsThis research uses a bootstrap autoregressive distributed lag (ARDL) bound test with structural breaks to examine the cointegration and causality relations between economic growth, energy consumption, and carbon dioxide (CO2) emissions in the E7 countries.ResultsThere is no cointegration between economic growth, energy consumption, and CO2 emissions for People’s Republic of China, Indonesia, Mexico, and Turkey. Evidence of cointegration is found for Brazil when CO2 emissions are the dependent variable and for India and Russia when energy consumption is the dependent variable. For all of the E7 countries except Indonesia, short-run Granger causality was found to exist from energy consumption to CO2 emissions and from economic growth to CO2 emissions for Brazil, India, Mexico, and People’s Republic of China. Short-run Granger causality was also found from economic growth to energy consumption for Brazil, India, Indonesia, Mexico, and People’s Republic of China, and from CO2 emissions to energy consumption for all E7 countries.ConclusionsThe results consistently show that energy consumption is the main cause of CO2 emissions, which has led to the emergence of global warming problems. Increases in CO2 emissions compel the E7 countries to develop sound policies on energy consumption and environmental pollution.

The main objective of this research was to test the effect of oil prices, renewable and non-renewable energy consumption, and economic growth on Turkey’s carbon emissions by using three co-integration tests, namely, the newly-developed bootstrap autoregressive distributed lag (ARDL) testing technique as proposed by (McNown et al., 2018); the new approach involving the Bayer–Hanck (2013) combined co-integration test; and the H-J (2008) co-integration technique, which induces two dates of structural breaks. The autoregressive distributed lag model (ARDL), dynamic ordinary least squares (DOLS), canonical cointegrating regression (CCR), and fully modified ordinary least square (FMOLS) approaches were utilized to test the long-run interaction between the examined variables. The Granger causality (GC) analysis was utilized to investigate the direction of causality among the variables. The long-run coefficients of ARDL, DOLS, CCR, and FMOLS showed that the oil prices had a negative influence on CO2 emissions in Turkey in the long run. Furthermore, the findings demonstrate that non-renewable energy, which includes oil, natural gas, and coal, increased CO2 emissions. In contrast, renewable energy can decrease the environmental pollution. These empirical findings can be attributed to the fact that Turkey is heavily dependent on imported oil; more than 50% of the energy requirement has been supplied by imports. Hence, oil price fluctuations have severe effects on the economic performance in Turkey, which in turn affects energy consumption and the level of carbon emissions. The study suggests that the rate of imported oil in Turkey must be decreased by finding more renewable energy sources for the energy supply formula to avoid any undesirable effects of oil price fluctuations on the CO2 emissions, and also to achieve sustainable development.

Azerbaijan signed the Paris Agreement in 2016 and committed to cut greenhouse gas (GHG) emissions by 35% in 2030. Meanwhile, natural gas has been vital component in the total energy mix of Azerbaijan economy and accounted for almost 65% of the total energy consumption. In the overall electricity mix, natural gas-fired power plants generate 93% of the country’s electricity. Since global energy consumption is responsible for 73% of human-caused greenhouse-gas emissions, and CO2 makes up more than 74% of the total, this study investigates possible mitigation effects of the natural gas consumption on CO2 emissions for Azerbaijan. Author employed several cointegration methodologies, namely Bound testing Autoregressive Distributed Lag (ARDL) approach, Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Structural Time Series model (STSM). Author of this paper found that when the share of natural gas increases 1 percent in the total energy mix, CO2 emission per capita decreases approximately 0.14 percent as a result of the ARDL, FMOLS, and DOLS models. All three models provide cointegration between the share of natural gas in the total energy mix and reduction in CO2 emissions.

Renewable energy utilization, green finance and agricultural land expansion in China

This study aims to examine the relationship between CO2 emissions, forest area, and GDP in each South Asian Association for Regional Cooperation (SAARC) country. This study uses a panel dataset that spans South Asian countries from 1990 to 2020 for econometric analysis. The Fully Modified Least Squares (FMOLS) method adds annual forested area to the regression model. The study results show that India, Nepal, Pakistan, and Sri Lanka must prioritize decoupling CO2 emissions from economic growth, as their strong correlation shows significant environmental costs of development. Although Bangladesh, Bhutan, and the Maldives are in a slightly better position, they need strategies to manage emissions as they progress economically. The study once again revealed a relationship between a 1% increase in GDP and a 0.68% rise in CO2 emissions, whereas a 1% increase in forest area led to a slightly higher 0.79% rise in CO2 over the period. The hypotheses testing results confirm a positive correlation between economic growth and carbon dioxide emissions in SAARC countries, indicating that emissions rise as economies expand. Additionally, a negative relationship was found between forest area and carbon dioxide emissions, where larger forest coverage is linked to lower emissions. The conclusion is that an increase in forest area is associated with a relatively small increase in CO2 emissions, indicating that the relationship between forest area and CO2 emissions is less pronounced compared to GDP.

Achieving sustainable environmental quality has become a critical global issue, necessitating the reduction of carbon dioxide (CO2) emissions and greenhouse gas (GHG) emissions to mitigate environmental pollution. Hydropower energy has the potential to play a significant role in this effort by providing a clean, renewable energy source that can help reduce reliance on fossil fuels and decrease CO2 emissions. This study examines the dynamic impact of hydropower energy consumption, economic growth, capital, and labor on Indonesia's CO2 emissions from 1990 to 2020. Applying the Autoregressive Distributed Lag (ARDL) method, the findings demonstrate that hydropower energy consumption has a negative effect on CO2 emissions in both the short and long term, indicating that increasing hydropower energy consumption leads to a reduction in CO2 emissions. Conversely, labor exhibits a positive influence on CO2 emissions in both the short and long term, suggesting that a rise in labor contributes to higher levels of CO2 emissions in Indonesia. Furthermore, the Granger causality analysis reveals a bidirectional relationship between CO2 emissions and hydropower energy consumption. The robustness of ARDL results is confirmed through additional tests using Fully-Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regressions (CCR) methods. The findings underscore the importance of promoting sustainable hydropower energy for effective environmental management in Indonesia. Policymakers should prioritize investments in sustainable hydropower infrastructure, encourage the adoption of energy-efficient technologies, and develop a skilled workforce to mitigate the environmental impact of increased labor force participation.

This study examines the short- and long-run impacts of economic growth and unemployment (SDG 8), energy consumption (SDG 7) and income inequality (SDG 10) on CO2 emissions in South Africa over the period 1980-2012 to establish potential synergy/trade-off to achieve these goals. We use the autoregressive distributed lag (ARDL) approach to cointegration technique. Our results show that the promotion of economic growth (SDG 8) as well as the reduction in energy consumption/increase in energy efficiency (SDG 7) can be achieved in synergy with the reduction of CO2 emissions (SDG 13). On the other hand, our results suggest a trade-off between reducing unemployment rate or achieving productive employment and decent work (SGD 8) and mitigating CO2 emissions (SDG 13). Neither a synergy nor trade-off (neutral relationship) is found between the reduction of income inequality (SDG 10) and the reduction of CO2 emissions (SDG 13). Our findings highlight the importance of mainstreaming SDG’s policy interactions to achieve sustainable development goals, while also stressing the potential for South Africa to achieve low-carbon development should economic growth be decoupled from carbon-intensive energy use through policies that promote access and effective use of clean energy. The transition to clean energy is therefore emphasized and relevant factors underpinning such as transition should be explored further. 
 
 Highlights
 
 
 This study examines the short- and long-run impacts of economic growth and unemployment (SDG 8), energy consumption (SDG 7) and income inequality (SDG 10) on CO2 emissions in South Africa 
 The autoregressive distributed lag approach to cointegration is employed
 A synergy is established between the promotion of economic growth (SDG 8) and the reduction of CO2 emissions (SDG 13), and between the reduction in energy consumption/increase in energy efficiency (SDG 7) and the reduction of CO2 emissions (SDG 13)
 A trade-off is confirmed between reducing unemployment rate or achieving productive employment and decent work (SDG 8) and mitigating CO2 emissions (SDG 13)
 A neutral relationship is found between the reduction of income inequality (SDG 10) and the reduction of CO2 emissions (SDG 13)
 Policymakers need to mainstream SDG’s policy interactions to achieve sustainable development goals
 
 
 South Africa can achieve low-carbon development should economic growth be decoupled from carbon-intensive energy use through policies that promote access and effective use of clean energy

Global climate change caused by Greenhouse gases (GHGs), particularly carbon dioxide (CO2) emissions, poses incomparable threats to the environment, development, and sustainability. This research investigates the potential of economic growth, renewable energy use, and technological innovation to achieve environmental sustainability by reducing CO2 emissions in Bangladesh. Time series data from 1980 to 2019 were utilized by applying the autoregressive distributed lag (ARDL) bounds testing approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The DOLS estimate findings show that the long-run coefficient of economic growth is positive and significant with CO2 emissions, indicating a 1% increase in economic growth is related to a 1.3% rise in CO2 emissions. Furthermore, the coefficient of renewable energy use is negative and significant, which indicates that increasing renewable energy use by 1% is associated with CO2 emissions reduction by 0.15% in the long run. In addition, the estimated long-run coefficient of technological innovation is negative but not significant, implying that a 1% increase in technological innovation results in a 0.07% reduction in CO2 emissions. The empirical findings reveal that economic growth increases CO2 emissions in Bangladesh while increased renewable energy use and technological innovation help to achieve environmental sustainability by reducing CO2 emissions. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test is utilized to capture the causal linkage between the variables. This article provides policy recommendations aimed at a low-carbon economy, promoting renewable energy use, and financing technological advancement, to achieve emission reduction and environmental sustainability in Bangladesh.

The intricate relationship between economic growth, environmental quality, and energy consumption has been extensively debated and studied on a global scale. The impacts of ecological quality on economic growth have been observed to be both positive and negative, particularly about human health as a result of pollutant emissions. It is essential to examine the compatibility between economic growth and environmental improvement, particularly through the reduction of emissions. This study aimed to investigate the connection between economic growth in forested areas and the corresponding impact on carbon dioxide (CO2) emissions in Nepal (Rose and Fisher, 1970). The analysis utilized time series data from 1990 to 2020, employing the dynamic ordinary least squares (DOLS) method. The DOLS results demonstrated a positive and statistically significant relationship between economic growth and CO2 emissions (Shafik and Bandyopadhyay, 1992). Specifically, an increase of Rs. 10 million in gross domestic product (GDP) corresponded to a 0.6112 kiloton increase in CO2 emissions. In contrast, the long‐term coefficient for forested areas exhibited a substantial association, indicating that a reduction of one square kilometer of forested area (deforestation) resulted in an increase of 68.37 kilotons in CO2 emissions in Nepal. These findings accentuate the divergent effects of economic progress and deforestation on carbon emissions in Nepal, with GDP growth contributing to a greater increase in emissions. Therefore, the implementation of effective strategies and economic measures, such as afforestation and reforestation, forest protection, sustainable forest management, and mechanisms like REDD+ (reducing emissions from deforestation and forest degradation plus), can play a vital role in mitigating carbon emissions while simultaneously addressing deforestation and ensuring long‐term economic progress in Nepal.

Global climate change, driven predominantly by carbon dioxide (CO2) emissions, poses one of the most critical challenges to sustainability in the 21st century. As Türkiye continues to pursue economic expansion and agricultural development, the resulting rise in energy consumption has led to a substantial increase in CO2 emissions. Given Türkiye’s position as the world’s 17th largest economy and its ranking as the 15th highest CO2 emitter, understanding the country’s exposure to climate risks is essential for informing policy efforts aimed at sustainable development. This study investigates the dynamic interplay between CO2 emissions and their primary determinants in Türkiye, offering empirical insights into the pathways through which these factors influence environmental sustainability. Utilizing a 34-year time series and the Autoregressive Distributed Lag (ARDL) model, the findings reveal that both economic growth and energy consumption contribute significantly to rising CO2 emissions, thereby exacerbating environmental degradation. Conversely, an increase in agricultural value added is associated with a reduction in CO2 emissions, highlighting its potential role in improving environmental quality. The results underscore the urgent need for a comprehensive legal and institutional framework that supports technological innovation and accelerates the transition toward a low-carbon economy in Türkiye.