Carbon emissions, energy consumption and economic growth in Zimbabwe: investigating the existence of the environmental Kuznets curve within a developing economy context

This article examines the short- and long-run association among carbon emissions, energy consumption and economic growth through deploying the environmental Kuznets curve (EKC) using combined (aggregated) and separated (disaggregated) energy consumption data for Zimbabwe from 1980 to 2014. The ARDL bounds tests and Johansen cointegration tests found long-run relationships among the variables. In the long-run, total energy consumption and primary coal consumption produce statistically significant positive relationships with carbon emissions. However, petroleum consumption demonstrates a statistically significant negative association with carbon emissions. The results show the validity of the EKC in total energy and primary coal consumption in the long-run but are invalid for petroleum consumption. In the short run, the findings reveal that total energy, primary coal and petroleum consumption have statistically significant positive relationships with carbon emissions. Furthermore, in the short run, the EKC is evident in petroleum consumption but invalid in both total energy and primary coal consumption. The short- and long-run Granger causality tests results based on the VECM are also discussed. The article concludes that, if carbon emissions are to be reduced in developing economies, alternative energy sources in the form of green technologies should be adopted as substitutes for coal and petroleum.

This article examined the relationships involving carbon emissions, economic growth and energy consumption by employing the environmental Kuznets curve (EKC) in South Africa from 1980 to 2014. The auto regressive distributed lag approach and Johansen cointegration tests proved that the variables are cointegrated. The article findings show that combined (total energy consumption) and hydrocarbon gas and petroleum consumption demonstrates evidence of EKC in the long‐run. Other separated data (primary coal, secondary coal, and electricity consumption) show no evidence of the EKC in the long‐run. Primary coal, secondary coal, electricity and hydrocarbon gas consumption develop positive and statistically significant relationships with carbon emissions in the long‐run but the case of total energy and petroleum consumption was negative and statistically significant. The short‐run results illustrate that combined (total energy consumption) and hydrocarbon gas consumption indicate evidence of EKC. Other separated data (primary coal, secondary coal, electricity, and petroleum consumption) show no evidence of the EKC in the short‐run. Short‐run results also indicated that total energy, primary coal, secondary coal, and electricity consumption report positive and statistically significant relationship with carbon emissions but hydrocarbon gas and petroleum consumption indicate positive but insignificant associations. Granger causality test based on vector error correction method (VECM) are also presented to ascertain causality. © 2018 American Institute of Chemical Engineers Environ Prog, 38: 30–46, 2019 Highlights The EKC hypothesis was examined in South Africa by employing energy combined and separated data. The EKC is supported in energy combined data in both short and long‐run but varies in separated data. Primary coal, secondary coal, electricity and hydrocarbon gas consumption develop positive and statistically significant relationships with carbon emissions in the long‐run. Total energy and petroleum consumption generate negative and statistically significant associations with carbon emissions in the long‐run. Total energy, primary coal, secondary coal and electricity show positive and statistically significant relationship with carbon emissions in the short‐run. Hydrocarbon gas and petroleum consumption indicate positive but insignificant association with carbon emissions in the short‐run. Granger causality tests based on VECM are also discussed.

Carbon emissions, energy consumption and economic growth: An aggregate and disaggregate analysis of the Indian economy

This paper examines the environmental Kuznets curve (EKC) relationship between energy consumption and economic growth in upper-middle-income regions of China with the panel data of 21 provinces from 2000 to 2017. The influence mechanism of socio-economic factors on the EKC of these regions is also detected. The results show that the energy consumption EKC fitting map in these regions conforms to the classical environmental Kuznets curve, which is an inverted “N” type, and the inflection point is ahead and more accurate after adding spatial effects. The direct effect of energy consumption has delayed the inflection point, indicating that the level of industrialization, urbanization, and population density have a significant impact on EKC. At the same time, it is found that the level of industrialization and population density have a positive relationship with energy consumption, while the level of urbanization has a negative correlation with energy consumption. The spatial spillover effect of the indirect effects of total energy consumption, coal consumption, and crude oil consumption shows that the level of industrialization has a significant and negative link with EKC. The increase in the level of industrialization will affect the total energy consumption of neighboring areas and the consumption of coal and crude oil.

With the rapid development of economy, energy demand is increasing in Hebei. Therefore, prediction of energy consumption and structure in Hebei province has importance of actual meaning significance. In this paper, total energy, coal, oil and natural gas consumption data are selected in Hebei province between 2001 and 2013. First, energy consumption and structure in Hebei province are analyzed. Second, GM(1,1)forecast model is established. Then, according to the established forecast model, energy consumption and structure between 2014 and 2021 in Hebei province is predicted. Last, related suggestions on energy optimization are put forward. The results are expected to provide important scientific basis for energy utilization and planning in Hebei province. Introduction Grey prediction is a method that can predict the systems containing uncertainties. To find the laws of system changes, original data is generating processed by identifying development trend of dissimilarity degree between system factors. Thus, data sequence with high regularity is generated. And then the corresponding differential equation model is established to predict future development trend of things. GM (1,1) prediction model with a variable and first-order differential is an important model of grey prediction. It is commonly used in energy and environment prediction because this model requires less modeling information, operates easily, forecasts precisely and is easy to test. In this paper, total energy, coal, oil and natural gas consumption data in Hebei province between 2001 and 2013 are selected as original sequence. GM (1, 1) model is constructed to predict energy consumption and structure in following 20 years in Hebei province. It hopes to provide reference and scientific basis for energy development strategy and the establishment of energy planning in Hebei. Analysis of energy consumption and structure in Hebei province The energy data in Hebei province between 2000 and 2012 are from China energy statistical yearbook. In this paper, all the energy consumption data have been converted into standard coal and the unit is ten thousand tons of standard coal. Table one shows the energy consumption and consumption structure in Hebei province. As shown in table 1, the total energy consumption in Hebei province seems to be increasing annually from 2000 to 2012 and its average annual growth rate is 7.95%. However, the speed of total energy consumption growth is different during the period and it has periodic growth characteristic. From the table, we can see that the growth speed is rapid from 2001 to 2007. Energy consumption structure in Hebei province is basically stable in recent years because of restriction on resources endowment and consumption structure of energy relying mainly on coal cannot be changed. Coal accounts for about 90 percent in energy consumption before 2011, but oil, gas and electricity such clean energy consumption occupies 10 percent of the total energy consumption. This shows that there is no variety in energy consumption structure in Hebei province and energy consumption has many defects. It depends heavily on coal which is non-renewable International Conference on Computational Science and Engineering (ICCSE 2015) © 2015. The authors Published by Atlantis Press 34 energy, so the renewable clean energy strengthened the large market demand, and the development of solar energy utilization technology has a broad prospect. Table.1 Energy consumption and consumption structure in Hebei province Year Total energy consumption Coal Oil Natural gas Electric power Total Proportion Total Proportion Total Proportion Total Proportion 2001 11195.71 10181.38 90.94 914.69 8.17 94.04 0.84 5.60 0.05 2002 12114.29 11125.76 91.84 898.88 7.42 84.80 0.70 4.85 0.04 2003 13404.53 12214.21 91.12 1092.47 8.15 93.83 0.70 4.02 0.03 2004 15297.89 14193.38 92.78 992.83 6.49 100.97 0.66 10.71 0.07 2005 17347.79 15810.78 91.14 1389.56 8.01 130.11 0.75 17.35 0.1

Energy consumption and economic growth: Evidence from China at both aggregated and disaggregated levels

Environmental awareness and its relation to the development of economy has garnered increased attention in recent years. Researchers, over the years, have argued that sustainable development warrants for minimizing environmental degradation since one depends on the other. This study analyzes the relationship between environmental degradation (carbon emission taken as proxy for degradation), economic growth, total energy consumption and industrial production index growth in Bangladesh from year 1998 to 2013. This study uses Vector Autoregression (VAR) Model and variance decomposition of VAR to analyze the effect of these variables on carbon emission and vice-versa. The findings of VAR model suggest that industrial production and GDP per capita has significant relationship with carbon emission. Further analysis through variance decomposition shows carbon emission has consistent impact on industrial production over time, whereas, industrial production has high impact on emission in the short run which fades in the long run which is consistent with Environmental Kuznets Curve (EKC) hypothesis. Carbon emission rising along with GDP per capita and at the same time having low impact in the long run on industrial index indicates there may be other sources of pollution introduced with the rise in income of the economy over time.

The causal link between energy and output growth: Evidence from Markov switching Granger causality

PDF HTML阅读 XML下载 导出引用 引用提醒 我国城市发展与能源碳排放关系的面板数据分析 DOI: 10.5846/stxb201911292591 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学重点基金项目（71533005）；国家重点研发项目（2017YFF0207303） The impact of urbanization on carbon emissions: Analysis of panel data from 158 cities in China Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:城市化与城市能耗及其碳排放密切相关，城市发展过程中的人口城市化进程和产业总量与结构调整都是能源碳排放变化的主要驱动因素。以2006-2015年全国158个地级城市的面板数据为基础，从总量变化趋势和空间变化趋势两个角度分析了研究期内的我国城市发展特征及能源碳排放特征；并利用面板计量分析方法研究了城市发展因素对城市总能耗、总能耗碳排放、单位能耗碳排放量的驱动特征。结果表明：城市化每提升0.095%，总能耗上升1%。虽然城市总能耗及能耗碳排放在降低，但是单位能耗碳排放在增加；第二产业和第三产业发展对总能耗及能耗碳排放的驱动作用大；城市第三产业的发展有利于能源结构优化调整等；并基于研究发现给出一些政策建议。 Abstract:Urbanization is closely related to urban energy consumption and associated carbon emissions. The process of population urbanization and industrial structure adjustment in urban development are the main drivers of changes in carbon emissions. Based on the panel data of 158 prefecture-level cities in China from 2006 to 2015, this study analyzes the urban development characteristics and energy carbon emission characteristics of China from total volume and spatial variation. The study uses panel measurement to analyze the driving characteristics of urban development factors on total urban energy consumption, total carbon emissions, and carbon emissions per unit energy consumption. The results show that for every 0.095% increase in urbanization, the total energy consumption increases by 1%. Although the total urban energy consumption and carbon emissions are decreasing, the carbon emissions per unit energy consumption are increasing. The total energy consumption of secondary and tertiary industries is also increasing. The development of tertiary industries in the city is beneficial for the optimization and adjustment of the energy structure. Based on the findings, some policy suggestions are proposed. 参考文献 相似文献 引证文献

In recent years, China's economic development has attracted worldwide attention, but economic growth has been at the expense of the excessive consumption of energy.Per unit of GDP's energy consumption in China is not only much higher than the United States, Japan and other developed countries that are far higher than the world average.On basis of simple analysis on the cause of excessive energy consumption in our country, this paper uses the econometrics method to study the various factors in the economic growth and how they affect the level of the energy consumption.Finally, this paper puts forward the proposal of optimize the industrial structure in our country, as well as development of new energy and so on.Only in this way can we at the same time in the guarantee of our country's economic growth and reduce energy consumption, which improve the effect of energy efficiency achieved particularly remarkable.

In this study, the relationship between total energy consumption and carbon dioxide (CO2) emissions is measured in the Environmental Kuznets Curve (EKC) framework. Based on the data in Turkey between the years of 1960-2015, the relationship is analyzed for long term through ARDL-bounds test. In this context, CO2 emissions, gross domestic product per capita, total energy consumption and some other related variables such as capital, labor, openness and population are considered. In the long-run equilibrium CO2 emissions and energy use appear to be both output elastic where the results indicate that output is a significant determinant of emissions and energy use. In accordance with these results of the inverted U-shaped relationships of both emissions–income and energy consumption–income imply that both environmental damage and energy consumption firstly increase with income, then stabilize, and eventually decline. Various policy recommendations about the estimated income elasticity of carbon emissions and energy consumption are presented with additional analyses of adverse effects. The overall results indicates that EKC is valid, besides, energy conservation policies and controlling CO2 emissions, are likely to have adverse effect on the real output growth of Turkey.

This study looked into causality relationship between energy consumption and economic growth in Zimbabwe using time series data spanning from 1980 to 2011. Four views explaining the causality relationship between energy consumption and economic growth include the growth hypothesis, conservation hypothesis, feedback hypothesis and the neutrality hypothesis. Whilst the growth hypothesis argues that energy consumption promotes economic growth, conservation hypothesis says that it is in fact economic growth that drives energy consumption. The feedback hypothesis argues that both energy consumption and economic growth promote each other whilst according to the neutrality hypothesis, no causality relationship exist between the two variables either in the short or long run. Using the bi-variate causality test framework, this study failed to establish any direct causality relationship between energy consumption and economic growth. However, the results imply the existence of an indirect bi-directional causality relationship between the two variables. The study therefore recommends Zimbabwe authorities not only to scale up investment into energy generation capacity improvement infrastructure but also address indirect factors like employment, human capital development, financial market development, and government consumption, among others in order to boost sustainable economic growth.

Energy consumption carbon emission factor method was used to analyze the carbon emission evolution of industrial energy consumption in Hunan Province with collected data on industrial energy consumption in 2000-2012. Results had shown that Hunan province industry’s carbon emission keep increasing in 2000-2012. There is a highly correlation between the total coal consumption and carbon emission of industrial energy carbon emission. Industrial energy consumption structure plays a decisive role in carbon emission. Industrial economic growth at the expense of high energy consumption in 2000-2005 has changed. Industrial carbon intensity has a fluctuated downward trend from 2005 to 2012. From the perspective of carbon emission per industrial output and industrial energy consumption structure, there is a large potential for carbon emission control in Hunan industrial energy consumption. Therefore, the main way to control carbon emission of industrial energy consumption in Hunan Province is to optimize the energy structure, reasonable adjustment of industry structure, improve energy technical level, proper control the growth of energy consumption.

Diverse factors may have an impact in carbon dioxide (CO2) emissions; thus, three main contributors, energy consumption, gross domestic product (GDP) and an exergy indicator are examined in this work. This study explores the relationship between economic growth and energy consumption by means of the hypothesis postulated for the Environmental Kuznets Curve (EKC). Panel data for ten countries, from 1971 to 2014 have been studied. Despite a wide gamma of research on the EKC, the role of an exergy variable has not been tested to find the EKC; for this reason, exergy analysis is proposed. Exergy analyses were performed to propose an exergetic indicator as a control variable and a comparative empirical study is developed to study a multivariable framework with the aim to detect correlations between them. High correlation between CO2, GDP, energy consumption, energy intensity and trade openness are observed, on the other hand not statistically significant values for trade openness and energy intensity. The results do not support the EKC hypothesis, however exergy intensity opens the door for future research once it proves to be a useful control variable. Exergy provides opportunities to analyze and implement energy and environmental policies in these countries, with the possibility to link exergy efficiencies and the use of renewables.

Compared to general public and residential buildings, large public buildings are often difficult to construct and have a long construction period, creating greater construction energy consumption and carbon emissions on the one hand, while generating a large amount and many types of difficult-to-track process data on the other. As such, it is difficult to measure carbon emissions and analyze various influencing factors. By realizing the simple calculation of energy consumption and carbon emissions, as well as discerning the degree of influence of various factors based on the results of influencing factors research, it is of considerable practical significance to propose energy savings and emission reductions in a targeted manner. In view of the above, this work aimed to establish a more practical calculation method to measure energy consumption and carbon emissions in the construction of large public buildings, as well as to identify the multiple influencing factors related to energy consumption and carbon emissions during the construction process. To demonstrate the practicality of our approach, quantitative calculations are carried out for a new terminal building in a certain place and from the perspective of sustainable urban construction; thus, the driving factors of the traditional STIRPAT model are extended to seven. Based on the calculation results, a modified STIRPAT model is used to analyze the comparative study of impact factors, such as population and construction machinery performance, on energy consumption and carbon emission intensity. The results show the following: (1) The energy consumption value per square meter of this terminal building is 3.43 kgce/m2, and the average carbon emission per square meter is about 13.88 kgCO2/m2, which is much larger than the national average of 6.96 kgCO2/m2, and (2) the type of energy used in the construction process has the greatest degree of influence on energy consumption and carbon emission, and the local GDP, population factor, construction machinery performance specifications, and shift usage also show a positive correlation with the growth of total energy consumption and carbon emissions. Moreover, while the government’s continuous investment in energy conservation and environmental protection has reduced the total energy consumption and carbon emissions in construction, there is still considerable room for improvement. Finally, according to the results, we provide theoretical references and constructive suggestions for the low-carbon construction of large public buildings in the construction stage. Thus, the results of our study will allow policy makers to formulate appropriate policies.