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.     

Economic growth,electricity consumption,urbanization and environmental degradation relationship in United Arab Emirates

The present study explores the relationship between economic growth, electricity consumption, urbanization and environmental degradation in case of United Arab Emirates (UAE). The study covers the quarter frequency data over the period of 1975–2011. We have applied the ARDL bounds testing approach to examine the long run relationship between the variables in the presence of structural breaks. The VECM Granger causality is applied to investigate the direction of causal relationship between the variables. Our empirical exercise reported the existence of cointegration among the series. Further, we found an inverted U-shaped relationship between economic growth and CO₂ emissions i.e. economic growth raises energy emissions initially and declines it after a threshold point of income per capita (EKC exists). Electricity consumption declines CO₂ emissions. The relationship between urbanization and CO₂ emissions is positive. Exports seem to improve the environmental quality by lowering CO₂ emissions. The causality analysis validates the feedback effect between CO₂ emissions and electricity consumption. Economic growth and urbanization Granger cause CO₂ emissions.     

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.     

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.     

Do nuclear and renewable energy improve the environment? Empirical evidence from the United States

The central focus of this article is to assess the dynamic effects of nuclear and renewable energy consumption on CO₂ emissions, for a given level of income and energy consumption. We apply an autoregressive distributed lag (ARDL) approach to cointegration to U.S. data from 1960 to 2010. We find that nuclear energy consumption indeed reduces CO₂ emissions in both the short- and long-run, while renewable energy consumption does only in the short-run. We also find that income increases CO₂ emissions in the long-run after showing the environmental Kuznets curve (EKC) initially in the short-run. Finally, energy consumption is found to have a negative impact on reducing CO₂ emissions in the short- and long-run.     

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.     

Testing Environmental Kuznets Curve hypothesis in Asian countries

The aim of this study is to test the Environmental Kuznet Curve (EKC) hypothesis for 14 Asian countries spanning the period 1990–2011. We focused on how both income and policies in these countries affect the income–emissions (environment) relationship. The GMM methodology using panel data is employed in a multivariate framework to test the EKC hypothesis. The multivariate framework includes: CO₂ emissions, GDP per capita, population density, land, industry shares in GDP, and four indicators that measure the quality of institutions. In terms of the presence of an inverted U-shape association between emissions and income per capita, the estimates have the expected signs and are statistically significant, yielding empirical support to the presence of an Environmental Kuznets Curve hypothesis.     

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.     

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.     

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.     

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.     

A Comparative Study of Environmental Impacts of Two Delivery Systems in the Business‐to‐Customer Book Retail Sector

China has the highest carbon dioxide (CO₂) emissions in the world. In China, logistics accounts for a significant portion of the total energy use and CO₂ emissions in business‐to‐customer (B2C) retailing. This study focuses on the environmental impacts of B2C delivery in China, focusing on the book retail industry. Mathematical models are proposed based on the practical operations of the “e‐commerce networked delivery” (END) system and the “sustainable networked delivery” (SND) system. The energy consumption and CO₂ emissions per book are then determined and compared for the two systems. Furthermore, we contrast the findings with those of similar studies conducted for other countries and provide explanations for the differences. The results show that (1) in general, in China, the SND system is better than the END system in terms of environmental impacts; (2) the END system in China generates fewer environmental impacts than those in the United States and the United Kingdom, while the SND system in China has greater environmental impacts than that in the United States; and (3) the wide use of vehicles such as electric bicycles that have low energy consumption rates contributes to the reduction of environmental impacts per book in both the END and SND systems in China. The limitations of the study and suggestions for future research are also discussed.     

Estimating 20‐year land‐use change and derived CO2 emissions associated with crops,pasture and forestry in Brazil and each of its 27 states

Land‐use change (LUC) in Brazil has important implications on global climate change, ecosystem services and biodiversity, and agricultural expansion plays a critical role in this process. Concerns over these issues have led to the need for estimating the magnitude and impacts associated with that, which are increasingly reported in the environmental assessment of products. Currently, there is an extensive debate on which methods are more appropriate for estimating LUC and related emissions and regionalized estimates are lacking for Brazil, which is a world leader in agricultural production (e.g. food, fibres and bioenergy). We developed a method for estimating scenarios of past 20‐year LUC and derived CO₂ emission rates associated with 64 crops, pasture and forestry in Brazil as whole and in each of its 27 states, based on time‐series statistics and in accordance with most used carbon‐footprinting standards. The scenarios adopted provide a range between minimum and maximum rates of CO₂ emissions from LUC according to different possibilities of land‐use transitions, which can have large impacts in the results. Specificities of Brazil, like multiple cropping and highly heterogeneous carbon stocks, are also addressed. The highest CO₂ emission rates are observed in the Amazon biome states and crops with the highest rates are those that have undergone expansion in this region. Some states and crops showing large agricultural areas have low emissions associated, especially in southern and eastern Brazil. Native carbon stocks and time of agricultural expansion are the most decisive factors to the patterns of emissions. Some implications on LUC estimation methods and standards and on agri‐environmental policies are discussed.     

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.     

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 hard choice for alternative biofuels to diesel in Brazil

This paper selects biofuel scenarios to substitute diesel in Brazil based on oil reserves increase, diesel imports, CO₂ emissions, crops agronomic yields, byproducts marketing and social impacts. This hard task still considers that agricultural practices in developing countries have large social impacts. Brazil presents high consumption of diesel oil in transport; low agronomic yield of traditional vegetable oil crops, which demand large cultivation areas contrasting with microalgae and palm oils which present high productivity. Concerning technologies, thermal cracking and transesterification of vegetable oils present a difficult economic situation related to vegetable oils price, food competition and glycerin market; BTL technology, meaning thermal gasification of biomass to liquids, faces problems related to low density of biomaterials and low viscosity of synthetic biodiesel produced. Biorefinery algal integrated systems and co-solvent technology to introduce up to 8% of ethanol into diesel seem to be feasible routes to reduce diesel consumption.     

Decoupling Analysis of Four Selected Countries

We examine decoupling conditions of domestic extraction of materials, energy use, and sulfur dioxide (SO₂) emissions from gross domestic product (GDP) for two BRIC (Brazil, Russia, India and China) countries (i.e., China and Russia) and two Organisation for Economic Co‐operation and Development (OECD) countries (Japan and the United States) during 2000–2007, using a pair of decoupling indicators for resource use (D_r) and waste emissions (D_e) and the decoupling chart, which can distinguish between absolute decoupling, relative decoupling, and non‐decoupling. We find that (1) during 2000–2007, decoupling between environmental indicators and GDP was higher in the two OECD countries as compared with the two BRIC countries. The key reason is that these countries were in different development stages with different economic growth rates. (2) Changes in environmental policies can significantly influence the degree of decoupling in a country. (3) China, Japan, and the United States were more successful in decoupling SO₂ emissions from GDP than in decoupling material and energy use from GDP. The main reason is that, unlike resource use, waste emissions (e.g., SO₂ emissions) can be reduced by effective end‐of‐pipe treatment. (4) The decoupling indicator is different from the changing rate of resource use and waste emissions. If two countries have different GDP growth rates, even though they may have similar values using the decoupling indicator, they may show different rates of change for resource use and waste emissions.     

Global Warming: Predicting OPEC Carbon Dioxide Emissions from Petroleum Consumption Using Neural Network and Hybrid Cuckoo Search Algorithm

Background

Global warming is attracting attention from policy makers due to its impacts such as floods, extreme weather, increases in temperature by 0.7°C, heat waves, storms, etc. These disasters result in loss of human life and billions of dollars in property. Global warming is believed to be caused by the emissions of greenhouse gases due to human activities including the emissions of carbon dioxide (CO₂) from petroleum consumption. Limitations of the previous methods of predicting CO₂ emissions and lack of work on the prediction of the Organization of the Petroleum Exporting Countries (OPEC) CO₂ emissions from petroleum consumption have motivated this research.

Methods/Findings

The OPEC CO₂ emissions data were collected from the Energy Information Administration. Artificial Neural Network (ANN) adaptability and performance motivated its choice for this study. To improve effectiveness of the ANN, the cuckoo search algorithm was hybridised with accelerated particle swarm optimisation for training the ANN to build a model for the prediction of OPEC CO₂ emissions. The proposed model predicts OPEC CO₂ emissions for 3, 6, 9, 12 and 16 years with an improved accuracy and speed over the state-of-the-art methods.

Conclusion

An accurate prediction of OPEC CO₂ emissions can serve as a reference point for propagating the reorganisation of economic development in OPEC member countries with the view of reducing CO₂ emissions to Kyoto benchmarks—hence, reducing global warming. The policy implications are discussed in the paper.     

Can carbon emissions from tropical deforestation drop by 50% in 5 years?

Halving carbon emissions from tropical deforestation by 2020 could help bring the international community closer to the agreed goal of <2 degree increase in global average temperature change and is consistent with a target set last year by the governments, corporations, indigenous peoples' organizations and non‐governmental organizations that signed the New York Declaration on Forests (NYDF). We assemble and refine a robust dataset to establish a 2001–2013 benchmark for average annual carbon emissions from gross tropical deforestation at 2.270 Gt CO₂ yr^?1. Brazil did not sign the NYDF, yet from 2001 to 2013, Brazil ranks first for both carbon emissions from gross tropical deforestation and reductions in those emissions – its share of the total declined from a peak of 69% in 2003 to a low of 20% in 2012. Indonesia, an NYDF signatory, is the second highest emitter, peaking in 2012 at 0.362 Gt CO₂ yr^?1 before declining to 0.205 Gt CO₂ yr^?1 in 2013. The other 14 NYDF tropical country signatories were responsible for a combined average of 0.317 Gt CO₂ yr^?1, while the other 86 tropical country non‐signatories were responsible for a combined average of 0.688 Gt CO₂ yr^?1. We outline two scenarios for achieving the 50% emission reduction target by 2020, both emphasizing the critical role of Brazil and the need to reverse the trends of increasing carbon emissions from gross tropical deforestation in many other tropical countries that, from 2001 to 2013, have largely offset Brazil's reductions. Achieving the target will therefore be challenging, even though it is in the self‐interest of the international community. Conserving rather than cutting down tropical forests requires shifting economic development away from a dependence on natural resource depletion toward recognition of the dependence of human societies on the natural capital that tropical forests represent and the goods and services they provide.