Does energy intensity contribute to CO2 emissions? A trivariate analysis in selected African countries

The present study investigates the dynamic relationship between energy intensity and CO₂ emissions by incorporating economic growth in environment CO₂ emissions function using data of Sub Saharan African countries. For this purpose, we applied panel cointegration to examine the long run relationship between the series. We employed the VECM Granger causality to test the direction of causality amid the variables.At panel level, our results validate the existence of cointegration among the series. The long run panel results show that energy intensity has positive and statistically significant impact on CO₂ emissions. There is also positive and negative link of non-linear and linear terms of real GDP per capita with CO₂ emissions supporting the presence of environmental Kuznets curve (EKC). The causality analysis reveals the bidirectional causality between economic growth and CO₂ emissions while energy intensity Granger causes economic growth and hence CO₂ emissions, while across the individual countries, the results differ. This paper opens up new insights for policy makers to design comprehensive economic, energy and environmental policy for sustainable long run economic growth.     

CO2, economic growth,and energy consumption in China's provinces: Investigating the spatiotemporal and econometric characteristics of China's CO2 emissions

This study addresses the spatiotemporal variations at play in China's CO₂ emissions, based on an estimation of emission levels in the period 1995–2012 and an provincial analysis of the relationship of CO₂ emissions to economic growth and energy consumption. Using a series of econometric models and data on the combustion of fossil fuels and cement manufacturing, the study first estimated CO₂ emission levels during the study period, exploring their spatiotemporal pattern. The results indicate that both China's total and its per capita CO₂ emissions have increased significantly over the study period, with both measures evidencing a similar evolution (albeit one that is characterized by noticeable regional discrepancies at the provincial level and which displays properties of convergence). From a geographical perspective, we found both total and per capita CO₂ emissionsto be higher in China's eastern region than in the country's central and western regions. Panel data analysis was subsequently undertaken in order to quantify the dynamic casual relationship between economic growth, energy consumption, and CO₂ emissions. The empirical results indicated that the variables were in fact cointegrated and exhibited a long-run positive relationship. The results of further Granger causality tests indicated the existence of a bidirectional positive causality between economic growth and energy consumption, as well as between energy consumption and CO₂ emissions, and a unidirectional positive causality running from economic growth to CO₂ emissions. The findings of this study suggest that China is, in the long run, dependent on carbon energy consumption for its rapid economic growth, a dependency which is the cause of considerable increases in CO₂ emissions. China should therefore make greater efforts to develop low-carbon technologies and renewable energy, and improve energy efficiency in order to reduce emissions and achieve green economic growth.     

The renewable energy-growth nexus with carbon emissions and technological innovation: Evidence from the Nordic countries

Despite the fact that previous studies have extensively investigated the renewable energy-growth nexus, those studies have not considered the role of technological innovation. This study examines the relationship between renewable energy consumption, technological innovation, economic growth, and CO₂ emissions in the four Nordic countries by constructing a vector autoregression (VAR) model. On the basis of a modified version of the Granger non-causality test, the results show a unidirectional causality running from renewable energy to CO₂ emissions for Denmark and Finland and a bidirectional causality between these variables for Sweden and Norway. The findings also indicate a unidirectional causality running from technological innovation to renewable energy and from growth to renewable energy for the four Nordic countries. The results could not confirm any causality from renewable energy to growth. Three policy implications are offered: (i) renewable energy improves environmental well-being, (ii) the Nordic countries have very low energy intensities and high energy efficiencies, and (iii) technological innovation plays an effective role in the renewable energy-growth nexus.     

Testing environmental Kuznets curve hypothesis: The role of renewable and non-renewable energy consumption and trade in OECD countries

This paper investigates the causal relationships between per capita CO₂ emissions, gross domestic product (GDP), renewable and non-renewable energy consumption, and international trade for a panel of 25 OECD countries over the period 1980–2010. Short-run Granger causality tests show the existence of bidirectional causality between: renewable energy consumption and imports, renewable and non-renewable energy consumption, non-renewable energy and trade (exports or imports); and unidirectional causality running from: exports to renewable energy, trade to CO₂ emissions, output to renewable energy. There are also long-run bidirectional causalities between all our considered variables. Our long-run fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimates show that the inverted U-shaped environmental Kuznets curve (EKC) hypothesis is verified for this sample of OECD countries. They also show that increasing non-renewable energy increases CO₂ emissions. Interestingly, increasing trade or renewable energy reduces CO₂ emissions. According to these results, more trade and more use of renewable energy are efficient strategies to combat global warming in these countries.     

Change in cereal production caused by climate change in Malaysia

This study attempts to estimate the effects of climate change variables, such as average temperature, CO₂ emissions and average rainfall, on cereal production in Malaysia from 1969 to 2018. After preliminary tests on time series data, we employed a novel autoregressive distributed lag (ARDL) method known as the dynamic ARDL simulations technique. The results showed that a long-run co-integration relationship exists between cereal production and climatic and non-climatic factors. All climate variables have a negative impact on cereal yield, while energy consumption and cultivated land have a positive effect on cereal yield in the short- and long-run. Granger causality analyses also showed that a unidirectional causality link exists between rainfall and temperature with cereal production and between CO₂ emissions and cereal production. Energy consumption, as a proxy for technology, has a one-way Granger cause with cereal production. The results of the dynamic ARDL simulations suggest that cereal yield was most sensitive to CO₂ emissions, rainfall and temperature. In the long run, a 1% increase in temperature is associated with a 2.87% and 3.52% decrease in general and predicted estimates of cereal production, respectively. The dynamic ARDL simulations methodology provides a better understanding of the variability of cereal production in Malaysia as a result of climate change.     

Spatiotemporal Characteristics,Determinants and Scenario Analysis of CO2 Emissions in China Using Provincial Panel Data

This paper empirically investigated the spatiotemporal variations, influencing factors and future emission trends of China’s CO₂ emissions based on a provincial panel data set. A series of panel econometric models were used taking the period 1995–2011 into consideration. The results indicated that CO₂ emissions in China increased over time, and were characterized by noticeable regional discrepancies; in addition, CO₂ emissions also exhibited properties of spatial dependence and convergence. Factors such as population scale, economic level and urbanization level exerted a positive influence on CO₂ emissions. Conversely, energy intensity was identified as having a negative influence on CO₂ emissions. In addition, the significance of the relationship between CO₂ emissions and the four variables varied across the provinces based on their scale of economic development. Scenario simulations further showed that the scenario of middle economic growth, middle population increase, low urbanization growth, and high technology improvement (here referred to as Scenario BTU), constitutes the best development model for China to realize the future sustainable development. Based on these empirical findings, we also provide a number of policy recommendations with respect to the future mitigation of CO₂ emissions.     

能源活动CO2排放不同核算方法比较和减排策略选择

能源活动CO₂排放是温室气体排放的最重要部分,这部分CO₂排放量的核算是温室气体清单编制和减排方案制定的关键和基础。采用直接法、电热终端法和隐含终端法核算了2009年中国能源消费的CO₂排放量,对不同核算法的CO₂排放部门分布、部门排放强度进行了比较,明确不同核算方法的差异和适用范围。采用电热终端法的核算结果定量分析了各产业部门和工业行业的经济增长和排放强度变化对中国能源活动CO₂排放增长的影响。结果表明,中国2009年隐含终端CO₂排放量为65.6亿t,略高于直接和电热终端CO₂排放量62.2亿t。3种核算方法的CO₂排放部门分布和排放强度有明显的差异:电、热力生产与供应业的直接排放占比为45.2%,而电热终端CO₂排放仅占4.5%;制造业的直接法、电热终端法和隐含终端法核算的CO₂排放占比分别为35.3% 、61.1%和65.5%,是终端能源消费CO₂排放最主要的部门;制造业、电热力生产与供应业和交通运输业的电热终端CO₂排放强度分别为2.166、1.72和1.622 t CO₂/万元GDP,是排放强度较高的部门。在产业部门中,制造业的色金属冶炼及压延加工业、非金属矿物制品业等5个行业以9.8%的经济增长贡献,排放了52.4%的CO₂,是产业结构调整、技术和工程减排的重点;服务业以7.2%的CO₂排放,贡献了38.4%的经济增长,应作为中国低碳经济优先发展的产业。     

Does globalization impede environmental quality in India?

Using annual data for the period 1970–2012, the study explores the relationship between globalization and CO₂ emissions by incorporating energy consumption, financial development and economic growth in CO₂ emission function for India. It applies Lee and Strazicich (2013) unit root test for examining the stationary properties of variables in presence of structural breaks and employs the cointegration method proposed by Bayer and Hanck (2013) to test the long-run relationships in the model. The robustness s of cointegration result from the latter model was further verified with the application of the ARDL bounds testing approach to cointegration proposed by Pesaran et al. (2001). After confirming the existence of conitegration, the overall long run estimates of the estimation of carbon emission model points out that acceleration in the process of globalization (measured in its three dimensions – economic, social and political globalizations) and energy consumption result in increasing CO₂ emissions, along with the contribution of economic development and financial development toward the deterioration of the environmental quality by raising CO₂ emissions over the long-run. This finding validates the holding of environmental Kuznets curve (EKC) hypothesis for the Indian context.     

The impact of trade openness on global carbon dioxide emissions: Evidence from the top ten emitters among developing countries

This study aims to analyze the relationship between carbon dioxide (CO₂) emissions, trade openness, real income and energy consumption in the top ten CO₂ emitters among the developing countries; namely China, India, South Korea, Brazil, Mexico, Indonesia, South Africa, Turkey, Thailand and Malaysia over the period of 1971–2011. In addition, the possible presence of the EKC hypothesis is investigated for the analyzed countries. The Zivot–Andrews unit root test with structural break, the bounds testing for cointegration in the presence of structural break and the VECM Granger causality method are employed. The empirical results indicate that (i) the analyzed variables are co-integrated for Thailand, Turkey, India, Brazil, China, Indonesia and Korea, (ii) real income, energy consumption and trade openness are the main determinants of carbon emissions in the long run, (iii) there exists a number of causal relations between the analyzed variables, (iv) the EKC hypothesis is validated for Turkey, India, China and Korea. Robust policy implications can be derived from this study since the estimated models pass several diagnostic and stability tests.     

Environmental Kuznets Curve hypothesis and the role of globalization in selected African countries

The present study incorporates globalization and energy intensity into the CO₂ emissions function and investigates the presence of Environmental Kuznets Curve (EKC) in 19 African countries for the time period of 1971–2012. We have applied the ARDL bounds testing approach for cointegration to examine the long run relationship in the variables. Our results confirmed the presence of cointegration between the series in Africa, Algeria, Angola, Cameroon, Congo Republic, Ghana, Kenya, Libya, Morocco, Nigeria, South Africa, Sudan, Tanzania, Togo, Tunisia, Zambia and Zimbabwe. The results indicated the positive effect of energy intensity on CO₂ emissions in Africa, Algeria, Angola, Cameroon, Congo Republic, Ghana, Kenya, Libya, Morocco, Nigeria, South Africa, Sudan, Togo, and Tunisia while energy intensity declines CO₂ emissions in the case of Zambia and Zimbabwe. Globalization decreases CO₂ emissions in Africa, Angola, Cameroon, Congo Republic, Egypt, Kenya, Libya, Tunisia and Zambia but increases CO₂ emissions in Ghana, Morocco, South Africa, Sudan and Tanzania. The EKC exists in Africa, Algeria, Cameroon, Congo Republic, Morocco, Tunisia and Zambia but U-shaped relationship is found between economic growth and CO₂ emissions in Sudan and Tanzania.     

Environmental Kuznets curve for CO2 emissions in China: A spatial panel data approach

Different from previous studies which mainly focused on conventional estimation techniques, this paper examines the CO₂ EKC hypothesis of China using a spatial panel data model to avoid the coefficient estimation error covering the period of 1997–2012. Furthermore, a comparative analysis of the turning points between the non-spatial panel model and spatial panel model is conducted. The results show that the relationship between economic growth and CO₂ emissions shapes as an inverted-N trajectory. Spatial spillovers effects are confirmed to affect the shape of the CO₂ environmental Kuznets curve. There exists an apparent block distribution in spatial structure of China's provincial CO₂ emissions. Specifically, CO₂ emissions have a relatively sharp increase from the eastern regions to the central and the western regions of China. It has also been found that urbanization and coal combustion are main factors on increasing CO₂ emissions. While the trade openness contributes to slight decrease in CO₂ emissions. The government should make targeted carbon-reduction policies for CO₂ emission reduction.     

The linkages between deforestation,energy and growth for environmental degradation in Pakistan

This study explores the validation of the Environmental Kuznets Curve (EKC) hypothesis for Pakistan using time series data from 1980–2013 with deforestation as an indicator (dependent variable) for environmental degradation, and four independent variables (economic growth, energy consumption, trade openness, and population) were also examined. The Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration and the VECM–Granger causality test were applied. The results confirmed the existence of cointegration among the variables both in long- and short-run paths. However, the diminishing negative impact of economic growth on deforestation in the long-run confirms the EKC hypothesis for deforestation in Pakistan. Moreover, economic growth and energy consumption Granger cause deforestation. A bidirectional causal effect is detected between economic growth and energy consumption, however, in the long-run, economic growth and trade openness Granger cause energy consumption. This study was designed with several significant tests to ensure the reliability of results for policy use and to contribute to future studies on the environment-growth-energy nexus.     

CO2 emissions and urbanization correlation in China based on threshold analysis

Urbanization and CO₂ emissions trends are driven by worldwide economic development. Studies indicate a direct correlation between urbanization and CO₂ emissions increases with both stimulating and inhibiting factors exhibited in the urbanization process and with periodic and regional characteristics exhibited with CO₂ emission. The relationship between urbanization and CO₂ emissions specifically in China from 1979 to 2013 is researched in this paper The novel points of this paper lies in utilizing a threshold mode to test periodic characteristics and analysis by regions. Results verify the effect of urbanization on CO₂ emissions as: (1) emissions increase when threshold point 0.43 was surpassed; (2) emissions increase as residential income increases; (3) coefficients of urbanization on emissions increase initially and then decrease as a factor of increasing industry percentage in overall GDP; (4) patterns of threshold points vary geographically.     

辽宁省能源消费和碳排放与经济增长的关系

在广泛收集资料的基础上,对辽宁省的能源利用效率、能源消费强度与经济增长的关系进行探索,其目的为辽宁省的节能与CO2减排及经济的快速发展提供科学依据。结果表明:辽宁整体单位GDP能耗高出全国水平52%—70%,第二产业单位GDP能耗是第三产业的5.67—8.41倍,第一产业的7.2—9.0倍;辽宁能源利用率只有全国平均水平的60%左右,第二产业能源利用效率只有第一产业的11.89%,第三产业的12.60%;GDP年增长速率大于能源消费量年增长速率,能源投入增加促进了国民生产总值的提高,但是经济增长并不是完全依赖能源消费的增长;能源消费量与经济增长的关系,呈现出"N型"曲线特征,随着GDP的增加,能源消费量出现反复上升和下降过程,辽宁省能源消费和经济增长关系没有达到长期的均衡性,尚处于非平衡的发展阶段。     

Relationships among carbon emissions,economic growth,energy consumption and population growth: Testing Environmental Kuznets Curve hypothesis for Brazil,China, India and Indonesia

This study examines the impacts of income, energy consumption and population growth on CO₂ emissions by employing an annual time series data for the period 1970–2012 for India, Indonesia, China, and Brazil. The study used the Autoregressive Distributed Lag (ARDL) bounds test approach considering both the linear and non-linear assumptions for related time series data for the top CO₂ emitter emerging countries in both the short run and long run. The results show that CO₂ emissions have increased statistically significantly with increases in income and energy consumption in all four countries. While the relationship between CO₂ emissions and population growth was found to be statistically significant for India and Brazil, it has been statistically insignificant for China and Indonesia in both the short run and long run. Also, empirical observations from the testing of environmental Kuznets curve (EKC) hypothesis imply that in the cases of Brazil, China and Indonesia, CO₂ emissions will decrease over the time when income increases. So based on the EKC findings, it can be argued that these three countries should not take any actions or policies, which might have conservative impacts on income, in order to reduce their CO₂ emissions. But in the case of India, where CO₂ emissions and income were found to have a positive relationship, an increase in income over the time will not reduce CO₂ emissions in the country.     

Decoupling environmental pressure from economic growth on city level: The Case Study of Chongqing in China

As cities represent the microcosms of global environmental change, it is very important for the global sustainable development by decoupling environmental pressure from economic growth on city level. In this paper, the municipality of Chongqing in China is employed as a case to show whether the decoupling of environmental pressures from economic growth has occurred in cities undergoing rapid economic growth; what is the level of decoupling; and what causes the observed degree of decoupling. Results show the following. (1) During the period of 1999–2010, decoupling from economic growth has been absolute for the emissions of SO₂, soot, and waste water, while it has been relative for total energy consumption, emissions of CO₂ and solid waste. (2) Compared with the period 2000–2005, decoupling level improved for all the six environmental pressures in the period 2005–2010. (3) Compared with China and other three municipalities of China, the overall decoupling level of Chongqing is above China’s average while below those of Beijing and Shanghai. (4) During the period 1999–2000, technological change was the dominate factor for decoupling Chongqing’s environmental pressure from economic growth, as it contributed 131.4%, 134.6%, 99.9%, 97.7%, 104.5% and 54.9% to the decoupling of total energy consumption, emissions of CO₂, SO₂, soot, waste water and solid waste, respectively; while economic structural change had very tiny effect to the decoupling of emissions of soot and SO₂, and it even had negative effect to that of total energy consumption, and emissions of CO₂ and waste water. Based on the above observations, we explain the difference in decoupling levels for different environmental pressures and suggest approaches for policy-makers on further promoting decoupling environmental pressure from economic growth.     

Decoupling Analysis of the Environmental Mountain—with Case Studies from China

The resource‐development trajectory of developed countries after the Industrial Revolution of the eighteenth and nineteenth centuries can be portrayed as an “environmental mountain” (EM). It is important for developing countries to decouple their resource use from economic growth and tunnel through the EM. In this study, we embedded the decoupling indicators for resource use and waste emissions into EM curves to quantify China's progress in tunneling through the EM over a specific time period. Five case studies regarding the conditions required for decoupling energy consumption, crude steel production, cement production, CO₂ emissions, and SO₂ emissions from economic growth in China were conducted. The results indicated that during 1985–2010 the trajectories of energy consumption, and CO₂ and SO₂ emissions in China met the requirements for tunneling through the EM, but the trajectories of cement and steel production did not. Based on these results, suggestions regarding China's environmental policies are provided to enable the country to tunnel through the EM.     

Examining the impact factors of urban residential energy consumption and CO2 emissions in China – Evidence from city-level data

Rapid urbanization has exerted substantial pressure on China’s energy system and contributed to climate change. To find the key drivers of urban residential energy consumption and CO₂ emissions, this paper uses an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that employs city-level data to examine the influences of population scale, income level, population compactness and price on house-based residential energy consumption, energy-related CO₂ emissions and private vehicle ownership. The empirical results indicate that factors such as population scale, affluence, and population compactness can lead to increases in residential energy consumption and CO₂ emissions. In terms of transportation, income and population scale positively drive the growth of private vehicle ownership, while the fuel price negatively influences private vehicle ownership. Moreover, population scale is the most important factor in residential energy consumption and CO₂ emissions. Finally, policy recommendations are suggested for China’s urban development strategy and urban design and to encourage technology innovations that reduce residential energy consumption and CO₂ emissions.     

Estimating the environmental Kuznets curve for Spain by considering fuel oil prices (1874–2011)

We perform a structural analysis on an environmental Kuznets curve (EKC) for Spain by exploiting long time series (1874–2011) and by using real oil prices as an indicator of variations in fuel energy consumption. This empirical strategy allows us to both, capture the effect of the most pollutant energy on carbon dioxide (CO₂) emissions and, at the same time, preclude potential endogeneity problems derived from the direct inclusion of fuel consumption in econometric specification. Knowing the extent to which oil prices affect CO₂ emissions has a straightforward application for environmental policy. The dynamics estimates of the long and short-term relationships among CO₂, economic growth and oil prices are built through an autoregressive distributed lag (ARDL) model. Our test results support the EKC hypothesis. Moreover, real oil prices are clearly revealed as a valuable indicator of pollutant energy consumption.     

我国典型城市化石能源消费CO2排放及其影响因素比较研究

城市是化石能源消费和CO_2排放的主要区域。分析典型城市化石能源消费CO_2排放特征,明确不同城市CO_2排放动态及主要影响因素的差异,是开展城市减排行动的重要科学依据。采用IPCC推荐方法及中国的排放参数核算11个典型城市2006—2015年间化石能源消费产生的CO_2排放量。根据各城市经济发展和CO_2排放特征将之分为四类:经济高度发达城市(北京、上海、广州)、高碳排放城市(重庆、乌鲁木齐、唐山)、低排放低增长城市(哈尔滨、呼和浩特和大庆)和低排放高增长城市(贵阳、合肥),并运用对数平均迪氏指数法(Logarithmic Mean Divisia Index,即LMDI分解法)对比分析了四类城市CO_2排放量的影响因素。结果表明:(1)研究期内大部分城市CO_2排放总量有所增加,仅北京和广州呈下降趋势,工业部门CO_2排放在城市排放总量及其变化中占据主导地位;四类城市的人均CO_2排放量表现出与排放总量相似的变化趋势;CO_2排放强度整体上表现为经济高度发达城市(均值为0.88 t CO_2/万元)低排放低增长城市(均值为2.82 t CO_2/万元)低排放高增长城市(均值为3.05 t CO_2/万元)高碳排放城市(均值为6.62 t CO_2/万元)。(2)在城市CO_2排放的影响因素中,经济发展和人口规模均是4类城市CO_2排放增长的促进因素,但经济发展效应的累积贡献值大于人口规模效应;能源强度降低是4类城市CO_2排放最主要的抑制因素,且经济高度发达和高碳排放城市的抑制作用强于其他两类城市;对第三产业GDP年平均增速高于第二产业的6个城市来说,产业结构是CO_2排放的抑制因素;能源结构的变化仅对煤炭消费比重较低且降幅较大的北京和广州的CO_2排放是抑制作用,累积贡献值分别为-21.73Mt和-0.03Mt,而对其他城市,特别是高碳排放城市的CO_2排放具有明显的促进作用。