How to bend down the environmental Kuznets curve: the significance of biomass energy.

Summary Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways.

This paper employs the K-Nearest Neighbor (k-NN) algorithm to examine the relationship between electricity generation—using renewable and non-renewable energy sources—and carbon dioxide (CO₂) emissions. The model achieved strong predictive accuracy, with a mean squared error (MSE) of 134.9 and an R² value of 0.915. Two analytical approaches were applied: the first included both renewable and non-renewable energy sources to determine the largest contribution of each energy source, and the second excluded non-renewable sources to assess the relative importance of different types of renewable energy. In the first approach, fossil fuel-fired electricity generation contributed 98.04% of the impact on carbon dioxide emissions, confirming its dominant role in increasing global carbon emissions. Renewable energy sources, however, had limited contributions: solar (1.16%), wind (0.71%), hydropower (0.09%), and bioenergy showed a negligible impact. In the second approach—excluding fossil fuels—renewable energy sources gained relative importance, with wind energy emerging as the most influential factor in the model (80.24%), followed by solar (10.92%), and hydropower (8.84%). Bioenergy remained insignificant in both models. The study concludes that fossil fuel–based electricity generation remains the principal driver of CO₂ emissions globally. though, among renewable sources, wind energy exhibits the greatest potential for reducing emissions when fossil fuels are excluded, highlighting its strategic importance in future clean energy transitions. The findings confirm the need for global energy policies that prioritize expanding renewable energy infrastructure, particularly solar and hydropower, while phasing out reliance on fossil fuels. countries should focus on stimulating investment in clean energy, developing efficiency-enhancing technologies, and expanding renewable energy generation to achieve long-term carbon reduction and environmental sustainability while maintaining economic growth.

The Environmental Kuznets Curve (EKC) hypothesis advocates a reversed U-shaped association between different pollutants and per capita income. EKC postulates that speedy growth certainly results in environmental degradation due to glut use of natural resources and emission of pollutants. The study used carbon dioxide (CO2) emissions, economic growth, energy consumption, and the annual growth rate of population to investigate the EKC hypothesis in India and China for the period of 1971–2013. Furthermore, to explore the long-run and short-run relationship among competing variables, the autoregressive distributed lag model (ARDL) is used. Granger causality test is used to investigate the long-run and short-run causality between variables under study. The results support the EKC hypothesis in India and China, in both long-run and short-run, and inverse U-shaped association is found between CO2 emission and economic growth. Unidirectional causality seen in both countries in terms of economic growth and CO2 emissions. In addition, the coefficient of economic growth in a short-run model provides the evidence that there has been a gradual decline in environmental degradation (downward sloping of EKC) and the quality of the environment is gradually improving in China. Based on the findings, the study suggests that environmental policymakers, especially in India, should seriously address the issue of CO2 emissions as it has a tendency to move faster in the coming years.

The economic development and environmental sustainability nexus have long been a fiercely debated issue. Researchers have widely acknowledged the environmental Kuznets curve (EKC) hypothesis when evaluating this relationship. Recently, an emerging strand of research examined the EKC through the lens of the Economic Complexity Index (ECoI) as a broader measure of economic development. However, empirical evidence of the index’s environmental impact is still limited. Despite its growing prominence, no prior research has been conducted in the Gulf Cooperation Council (GCC) using the ECoI, particularly in the EKC context. Furthermore, research comparing the ECoI differentiated impacts on Ecological Footprint and Carbon Dioxide (CO2) emissions is largely lacking. Extending on this line of research, our investigation intends to ascertain the influence of ECoI, income, globalization as well as non-renewable energy consumption on two dominant environmental pressure metrics: CO2 emissions and ecological footprint per capita (EFpc) within the EKC hypothesis context in six GCC countries during 1995–2018. To this end, Pedroni’s cointegration approach was conducted to examine the long-term association between variables; cointegration coefficients were analyzed using Dynamic and Fully modified OLS. Our investigation indicates the emergence of an inverted U-shaped link between ECoI and environmental sustainability in the GCC region for both CO2 emissions and EFpc. Furthermore, according to the individual country analysis, our findings demonstrate that the EKC hypothesis is sensitive to both the environmental degradation indicator used and the country analyzed; such that the quadratic link incorporating ECoI is confirmed for Saudi Arabia, Bahrain, United Arab Emirates, and Kuwait when EFpc is employed. In comparison, it holds for Kuwait, Oman, and Qatar when CO2 emissions are used. Moreover, the findings show that income per capita and non-renewables consumption significantly harm environmental sustainability, however, in terms of EFpc only. In contrast, through its three sub-dimensions, globalization contributes to the environmental burden by increasing both EFpc and CO2 emissions. These conclusions emphasize the economic complexity’s dominant role in mitigating environmental pollution in GCC beyond a certain threshold. Finally, the paper reaches a concise set of implications. Among the foremost, the GCC nations could enhance their environmental sustainability by diversifying their energy sources and increasing reliance on renewable sources, encouraging investment in carbon-reduction technologies, converting their economy from energy-intensive to technology-intensive, as well as imposing strict environmental laws to enable globalization to improve environmental quality.

Analyzing the effects of real income and biomass energy consumption on carbon dioxide (CO2) emissions: Empirical evidence from the panel of biomass-consuming countries

The objective of this study is to explore the influence of the real income (GDP), renewable energy consumption and non-renewable energy consumption on carbon dioxide (CO2) emissions for the United States of America (USA) in the environmental Kuznets curve (EKC) model for the period 1980-2014. The Zivot-Andrews unit root test with a structural break and the Clemente-Montanes-Reyes unit root test with a structural break report that the analyzed variables become stationary at first-differences. The Gregory-Hansen cointegration test with a structural break and the bounds testing for cointegration in the presence of a structural break show CO2 emissions, the real income, the quadratic real income, renewable and non-renewable energy consumption are cointegrated. The long-run estimates obtained from the ARDL model indicate that increases in renewable energy consumption mitigate environmental degradation whereas increases in non-renewable energy consumption contribute to CO2 emissions. In addition, the EKC hypothesis is not valid for the USA. Since we use time-series econometric approaches that account for structural break in the data, findings of this study are robust, reliable and accurate. The US government is advised to put more weights on renewable sources in energy mix, to support and encourage the use and adoption of renewable energy and clean technologies, and to increase the public awareness of renewable energy for lower levels of emissions.

Hydrogen farm concept: A Perspective for Turkey

Air pollution, global greenhouse gases (GHG), water pollution and water resources degradation are among the most serious environmental concerns that encounter the Qatar country. In nowadays, it is commonly known that the effects of environment degradation exceed its direct negative impacts on climate changes to cover its impacts on Human health, nation livelihood and cultural integrity. So, we advocate that understanding and determining factors explaining environmental degradation remain an important question of research. Moreover, by determining factors that explain environment degradation, policymakers, researchers and international institutions can help on recommending the adequate economic policies that can improve the environment quality and the live standing of inhabitants. In the empirical literature, the Environmental Kuznets Curve (EKC) is the most powerful tool used to investigate the relationship between environment degradation and some macroeconomics and financial variables. Following the EKC hypothesis, the relationship between economic growth and environment degradation is inverted-U shaped. From the economic perspective, this means that initially economic growth increases environment degradation and then declines it after a threshold point of income per capita. More specifically, at initial level of economic growth, an increase in income is linked with an increase in energy consumption that raises environment degradation. After reaching a critical level of income, the spending on environment protection is increased, and hence environment degradation tend to decrease. From an econometrical or statistical perspectives, the EKC hypothesis have been firstly tested using the basic EKC equation which relies the environment degradation proxy to the real GDP and to a nonlinear term of the real GDP (the squared real GDP). If the EKC hypothesis holds then the real GDP and the squared real GDP have respectively a positive and negative signs. This EKC hypothesis has been firstly introduced by Kuznets (1955) when examining the relationship between economic growth and income inequality which shows that this relationship is inverted U-shaped. Grossman and Krueger (1995) are the first to examine this relationship between environment degradation and economic growth in their seminal paper published on the Quarterly Journal of Economics. They found that this relationship is inverted U-shaped which validates the EKC hypothesis. Empirically, until now no consensus has been reached about the true nature of the relation between real GDP and environment degradation. Evidence for the EKC hypothesis is very mixed. Overall, the results seem to depend in many factors including the specification, the pollutants and the econometrics technique used. First, empirical studies show that the results in term of positive and negative relationships as well as in term of magnitude differ significantly for the same country depend on the specification studied, linear, quadratic or cubic. Moreover, the inclusion of other factors in the right hand of the regression such as urbanization, trade openness, financial development and political stability have a significant impact on the magnitude of the income per capita variables coefficients. Second, the results differ significantly following the environment degradation proxy used. For instance, Horvath (1997) and Holtz-Eakin and Selden (1995) suggest that the use of global pollutants leads to continuously rise the levels of environment degradation or to a high levels of income per capita turning point, see also Esteve and Tamarit (2011). Third, the results also seem to depend in the econometric approach employed. In this paper, we investigate the case of the Qatar economy for several reasons. First, Qatar 2030 vision has given a high importance to questions related to air pollution, climate change and their impacts on economic sustainability. Second, the rapid increase of economic growth of the Qatar economy in the last two decades has been accompanied with an increase in energy consumption, urbanization and international trade. These factors are among the most important factors largely used in theoretical and empirical literature to explain environment degradation. Third, following the world health organization (WHO), local air pollution levels in Qatar has frequently exceeded recommended levels and are more time higher than the international standards. In fact, compared to the WHO's standards for PM10 for the 24-hour average and for the annual average concentration of 50 ug/m 3 and 20 ug/m 3 the Qatar's national air quality standards are far from these values. For instance, the values for PM10 is around 150 ug/m 3 for 24 hours average concentration and to 50 ug/m 3 for the annual average concentration. The data set used in this paper consists on macroeconomics and financial data, including CO 2 emissions, ecological foot print, real GDP per capita, energy use, urbanization, financial development and openness trade, to investigate the EKC hypothesis for the Qatar economy. All the dataset except the ecological foot print variable are collected from the world Bank's development indicators (WDI). The ecological footprint data is obtained from the National Footprint Accounts (NFAs) of the Global Footprint Network. This variable is employed as second proxy of environment quality measures. This data set used is a quarterly data and covers the period 1975Q1 to 2007Q4 for variables used for ecological footprint equation and covers the periods 1980Q1 to 2010Q4 for the CO 2 emissions equations variables. This paper contributes to the empirical literature of the EKC hypothesis in many ways. First, to our knowledge this paper is the first to consider the case of the Qatar economy as a single country to test the EKC hypothesis as well as the different directions of causality between variables. Second, in addition to the CO 2 emissions largely employed in the empirical literature, in this paper we employ also the ecological footprint as a new proxy of environmental degradation. Third, we use recent development of cointegration approach with structural breaks which is also rarely used for the case of EKC hypothesis. As tests of cointegration with shifts in the cointegration vector, we use the Gregory and Hansen (1996), Hatemi-J (2008) and to investigate the causal relationship between all variables using standard Granger causality tests. Fourth, to our knowledge this paper is the first study that uses Markov Switching Equilibrium Correction Model with shifts in both the intercept and the income per capita coefficient for the long run relationship between environment degradation and its key determinants. The empirical findings of this paper are useful for Qatari policymakers and especially for the ministry of environment of the Qatar government. Moreover, economic implications and economic policy are proposed and discussed. [1] P.O.Box: 2713-Doha-Qatar. Email: lcharfeddine@qu.edu.qa. Office: (+974) 4403-7764(+974) 4403-7764, Fax: (+974) 4403-5081. 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Background: The provision of energy services is a vital component of the energy system. This is often considered emission-intensive and at same time, highly vulnerable to climate change conditions. This forms the fundamental objective of this thesis, poised to examine technoeconomic and environmental implications of policy intervention, targeted at cushioning impacts of climate change on the energy system. Aims: Four research queries are central to this work: (1) Review literature on impacts of CVC (2) Estimate influence of seasonal climatic and socioeconomic factors on energy demand in Australia; (3) Model dynamic interactions between energy policies and climate variability and change (CVC and (4) Identify least-cost combination of electricity generation technologies and effective emissions reduction policies under climate change conditions in Australia. Methods: A systematic scoping review method was first applied to identify consistent pattern of CV&C impacts on the energy system, while spotting research gaps in studies that met the inclusion criteria. Databases consisting of Scopus and Web of Science were searched, and snowballing references in published studies was adopted. Data was collated and summarised to identify the characteristic features of the studies, consistent pattern of CV&C impacts, and locate research gaps to be filled by this study. The second study applied an autoregressive distributed lag (ARDL) model to estimate temperature sensitive electricity demand in Australia. Estimates were used with projected temperatures from global climate models (GCMs) to simulate future electricity demand under climate change scenarios. The study further accounted for uncertainties in electricity demand forecasting under climate change conditions, in relation to energy efficiency improvement, renewable energy adoption and electricity price volatility. The estimates from the ARDL model and projections from GCMs were used for energy system simulation using the Long-range Energy Alternative and Planning (LEAP) system. It considered climate induced energy demand in the residential and commercial sector, alongside linking the non-climate sensitive sector with energy supply sector. This model was vital to justifying policy options under investigation. Further, LEAP modelling analysis was extended by identifying effective emission reduction policies considering CV&C impacts. Here, the Open Source Energy Modelling System (OSeMOSYS) was used for optimisation analysis to identify least-cost combination of electricity generation technologies and GHG emission reduction policies. Whereas, in the third and final study, cost-benefit analysis and estimation of long run marginal cost of electricity were conducted, while decomposition analysis of GHGs were analysed in the third study alone. Data used in the ARDL model included socioeconomic data which includes gross state product, as well as population and electricity prices from 1990-2016. The LEAP and OSeMOSYS model as used, was dated to 2014 as the base year, while several technological (power plant characteristics, household technologies), economic (energy prices, economic growth, carbon price) and environmental (emission factors, emission reduction target) variables were used to develop Australia's energy model. Results: The literature search generated 5,062 articles in which 176 studies met the inclusion criteria for the final literature review. Australian studies were scarce compared to other developed countries. Also, just few articles made attempt to examine decarbonisation under climate change. The ARDL model estimates and GCMs simulation of future electricity demand under CV&C show that Australia had an upward sloping climate-response functions, resulting to an increase in electricity demand. However, the researcher identified an annual increase in projected electricity demand for states and territory in Australia, which calls for the need to scale up RET. The LEAP model results showed substantial impacts on energy demand, as well as impacts on power sector efficiency. Under the BAU scenario, CV&C will result in an increase in energy demand by 72 PJ and 150 PJ in the residential and commercial sectors, respectively. Induced temperature enlarges the non-climate BAU demand, which will increase threefold before 2050. Under the non-climate BAU, there is an expansion of installed capacity to 81.8 GW generating 524.6 TWh. Due to CV&C impacts, power output declines by 59 TWh and 157 TWh in Representative Concentration Pathways (RCP) 4.5 and 8.5 climate scenarios. This leads to an increase in generation costs by 10% from the base year, but a decrease in sales revenue by 8% and 21% in RCP 4.5 and RCP 8.5, respectively. The LEAP-OSeMOSYS model suggests renewables and battery storage systems as least-cost option. However, the configuration varied across Australia. Carbon tax policy was observed to be effective in reducing Australia's emission and foster huge economic benefits when compared to the current emission reduction target policy in the country. Also, renewable energy technologies increase electricity sales and decrease fuel cost better than fossil fuel dominated scenarios. Conclusions: Data from this study reveals that seasonal electricity demand in Australia will be influenced by warmer temperatures. Also, the study identified the possibility of winter peaking which is somewhat higher than summer peak demand in some states located in the southern regions of Australia. However, winter peaking is projected to decline by mid-century across the RCPs, while summer peak load is projected to increase, thereby, causing power companies to expand their generation capacity which may become underutilised. Owing to increase in cooling requirements up to 2050, policy uncertainties analysis recommend renewables to match an increasing future electricity demand. The energy model indicates that ignoring the influence of CV&C may result in severe economic implications which range from increased demand, higher fuel cost, loss in revenue from decreased power output, as well as increased environmental externalities. The study concludes that policy options to reduce energy demand and GHG emissions under climate change may be expensive on the short-run, though, may likely secure long-run benefits in cost savings and emission reductions. It is envisaged that this could provide power sector management with initiatives that could be used to overcome cost ineffectiveness of short-term cost. The modelling results makes a case for renewable energy in Australia as lower demand for energy and increased electricity generation from renewable energy source presents a win-win case for Australia.

Kicking the Oil Addiction

Abstract. This research paper conducts a comprehensive analysis of the complex relationship between CO2 emissions and economic factors, specifically investigating the Environmental Kuznets Curve (EKC) theory in Malaysia. Using data from 1991 to 2020, the study applies the Autoregressive Distributed Lag (ARDL) modelling approach developed by Pesaran et al. (2001). The results demonstrate a significant long-term connection between Gross Domestic Product (GDP), trade, and carbon emissions, indicating that economic development plays a crucial role in influencing Malaysia's carbon footprint. Additionally, the inclusion of institutional quality in the model adds another layer of complexity, highlighting the multifaceted nature of the relationship between economic progress and environmental outcomes. Furthermore, examining short-term dynamics using the ARDL model reveals diverse effects over time for variables such as renewable energy and institutional quality, providing a more nuanced understanding of these relationships. These detailed insights are essential for policymakers dealing with the challenges of promoting economic progress while ensuring environmental sustainability. The findings contribute to a deeper understanding of the interplay between economic variables and CO2 emissions, offering valuable guidance for policymakers striving to strike a balance between economic growth and environmental conservation in Malaysia. Keywords: Malaysia, autoregressive distributed lag (ardl) modelling, environmental kuznets curve (ekc), carbon dioxide (co2) emissions, gross domestic product (gdp), renewable energy (ren), institutional quality (iq), trade (tr)

This study investigates the presence of environmental kuznets curve (EKC) for green house gases (GHG) measured by CO2 emission in Malaysia for the period 1970 to 2011. The study also examines the potential of the renewable source of energy to contain GHG. The long-run significant positive coefficient of GDP indicates that the GHG are increasing with economic growth while the insignificant coefficient on GDP square rejects the EKC transition. These results indicate a high GDP level for the EKC turning point for Malaysia. Therefore, it can be stated that only economic growth cannot reverse the environmental degradation in Malaysia. The government should have to come up with some policy measures to achieve CO2 emission reduction targets that Malaysia has pledged to achieve in Paris Submit (2015). The renewable energy production is found to have significant negative effect on CO2 emission. So government should focus on the renewable source of energy production and should frame a special policy for renewable energy production.

The achievement of economic growth is equally important as environmental sustainability. Economic growth is considered capable of enhancing the overall welfare of society. However, there is a sacrifice stemming from economic growth in the form of negative external impacts. Therefore, the objective of this study is to examine the Environmental Kuznets Curve (EKC) hypothesis in Indonesia and India. The EKC hypothesis connects economic growth with CO2 emissions. The Autoregressive Distributed Lag (ARDL) model is employed to assess both the long-term and short-term impacts of economic growth on CO2 emissions in Indonesia and India. Additionally, the study seeks to comprehend the applicability of the Environmental Kuznets Curve (EKC) hypothesis in these countries over the period of 1965-2021. The research findings indicate that economic growth has a significant impact on CO2 emissions in the short term, but this influence is not sustained in the long term in Indonesia. In contrast, in India, economic growth does not exhibit a significant effect on CO2 emissions in the short term, but it does have a notable impact in the long term. This implies that Indonesia does not align with the Environmental Kuznets Curve (EKC) hypothesis in the long term, while India is anticipated to adhere to the EKC hypothesis in the future.

Nexus between selected macroeconomic variables and carbon emission in Kenya

Our pioneer study is aimed at investigating the role of the service sector in affecting sustainable environment in Pakistan. Using time series data over 1971–2014 and applying an autoregressive distributive lag (ARDL) model with structural break analysis, we establish a long-term equilibrium relationship of carbon dioxide (CO2) emissions with energy consumption, income level, services and trade openness. Our findings support a service-induced environmental Kuznets curve (EKC) hypothesis in Pakistan. The income level sharply raises environmental degradation at the early stage; however, after reaching a certain threshold, it improves environmental quality but at a lower rate. There exists an inverted U-shaped nexus between services and CO2 emissions, which implies that the service sector is less energy-intensive in terms of mitigating pollution in Pakistan. Moreover, the energy consumption has an inverted U-shaped effect on carbon emissions, which implies energy efficiencies and adoption of renewable energy has reduced pollution in the long run. The trade openness increases CO2 emissions in both the short term and long term. The quadratic term of income level has a negatively inelastic impact on CO2 emissions, which implies a very slow rate of improvement in environmental quality. On the other hand, the quadratic term of services shows a highly elastic impact on pollution, which induces the EKC hypothesis. Our robustness checks such as fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (OLS), and Toda and Yamamoto (TY) causality tests further confirm the existence of the service-induced EKC hypothesis in Pakistan. Moreover, there exists a unidirectional causality from energy consumption to CO2 emissions, a bidirectional causal relationship between economic growth and CO2 emissions, and a unidirectional causal linkage between services and CO2 emissions. Lastly, we discuss certain policy implications for designing appropriate environmental and energy policies to mitigate the pollution in Pakistan.