(searched for: doi:10.3390/su6021037)
Environmental Science and Pollution Research, Volume 28, pp 16690-16706; https://doi.org/10.1007/s11356-020-12199-5
Environmental Kuznets curve (EKC) is a statistical tool to examine the cointegration and causality nexus between economic growth and carbon emissions. The EKC is widely used in energy and environmental economics studies. Although a large number of researchers have analyzed the EKC by applying different statistical models, some review work has been summarized to draw a pictorial view of extending studies in this research field. However, still, the macroscopic overview needs to be considered. Therefore, this study aims to contribute to the literature for finding a new pathway for further research employing, and to facilitate this research, scientometric analysis is carried out by feature in CiteSpace. The dataset was screened and found 2384 records out of 59,225 Web of Science (WoS) references, and the records for the timespan 1999–2019 was used to visualize the knowledge map and outcome of the scientific enterprise. The visualization results reveal the most influencing studies, institutions, authors, countries, keywords, and category cloud, in the research field of EKC. This article reveals that the research on EKC in alignment with green and sustainable technology science requires more attention. Further, this article would help authors and publishers make their decisions for the research of EKC and planning for future perspectives to contribute to academic development and applied methodology.
OPEC Energy Review, Volume 44, pp 511-534; https://doi.org/10.1111/opec.12192
This study examines the relationships between the environmental pollution, energy use and economic growth of countries around the world using secondary sources of 44 countries collected from the World Energy Outlook 2019. Cointegration tests with sophisticated econometric panel models and autoregressive distributed lag models were used to measure the relationship between the above variables ranging from 1990 to 2018. Our study’s empirical model finds that high energy usage improves a country’s economic position but at the cost of environmental pollution (carbon dioxide emissions). It also observes that countries in the European Union, the Commonwealth of Independent States, and North and Latin American across the Pacific region support the hypothesis of an inverted N‐shaped environmental Kuznets curve. However, the situation in Asia and Africa suggests the N‐shaped environmental Kuznets curve hypothesis, which indicates that these countries experience ups and downs in their environmental quality all the time and their environmental quality is substandard at any point in time. Those countries that show both long‐term and short‐term relationships among these three factors must adopt environmental safety measures such as renewable energy sources and green concepts to reduce their levels of carbon dioxide emissions and increase their environmental quality.
Environment, Development and Sustainability, Volume 23, pp 9336-9351; https://doi.org/10.1007/s10668-020-01027-y
A close association prevails among energy consumption, energy prices, and income levels. This association has implications for the growth of an economy. Hence, incorporating energy consumption properties in an economy is crucial for policy design purposes especially in the case of energy-exporting countries of the Gulf Cooperation Council (GCC). This paper studies the correlates of energy consumption with an emphasis on shocks in crude oil prices, changes in GDP per capita, carbon dioxide emissions, trade, population growth, and other key indicators using a panel of GCC countries over 30 years of data period (1985–2014). The study provides direct evidence of the oil price shocks and energy consumption using a static panel (POLS and FE) and dynamic panel (system-GMM) estimation technique. The finding shows that oil price shocks affect energy consumption negatively. The greatest positive effect on energy consumption is observed with an increase in GDP per capita, as a percent increase in it increases energy consumption by 0.65 percent. It is followed by trade openness which increases energy consumption by 0.14 percent. While the greatest negative effect on energy consumption is observed by a rise in oil prices, as a percent increase in oil prices reduces energy consumption by approximately 0.22 percent. The study also finds that higher energy consumption increases carbon dioxide emissions as energy consumption is growing with population growth. Thus, it is important to upscale the adoption of renewable energy sources, adopt energy-efficient technologies, reduce energy subsidies, and practice demand-side management.
Energies, Volume 13; https://doi.org/10.3390/en13184731
This article describes the results of a study of Ecuador’s energy status, using the system dynamics methodology to model supply, demand and CO2 emissions scenarios for the year 2030. Primary energy production increased in the different projected scenarios, with oil as the most important source of energy. The increase observed in final energy consumption was mainly associated with the transport and industry sectors. A reduction in energy intensity was projected for the different scenarios, which could be associated with the projected economic growth. The results obtained were used to build a proposal for energy policies aimed at mitigating emissions. The proposed changes to the national energy matrix could be the factors that will contribute most to the achievement of carbon emission reductions projected by the different scenarios; changes in the energy matrix are mainly associated with the development of projects to replace fossil fuels with renewable energies, mainly hydropower.
Sustainability, Volume 12; https://doi.org/10.3390/su12010020
Climate change and global warming are related to the demand for energy, energy efficiency, and CO2 emissions. In this research, in order to project the trends in final energy demand, energy intensity, and CO2 emission production in Ecuador during a period between 2000 and 2030, a model has been developed based on the dynamics of the systems supported by Vensim simulation models. The energy matrix of Ecuador has changed in recent years, giving more importance to hydropower. It is conclusive that, if industrialized country policies or trends on the use of renewable energy and energy efficiency were applied, the production of CO2 emissions by 2030 in Ecuador would reach 42,191.4 KTCO2, a value well below the 75,182.6 KTCO2 that would be seen if the current conditions are maintained. In the same way, by 2030, energy intensity would be reduced to 54% compared to the beginning of the simulation period.
Renewable Energy, Volume 145, pp 1949-1956; https://doi.org/10.1016/j.renene.2019.07.098
Cellulose liquefaction in supercritical ethanol with 2,2,6,6-Tetramethylpiperidinooxy (TEMPO) was carried out in a stainless autoclave. The influence of process parameters on bio-oil (BO) and platform chemicals, mainly including the dosage of TEMPO, reaction temperature and reaction time, were investigated. Characterization of liquefaction products was explored by fourier transform infrared (FTIR) and gas chromatography-mass spectrometry analysis (GC-MS). The maximum yield of BO (57.98%) was obtained from cellulose liquefaction at 320 °C, 4 g TEMPO and moderate time of 60 min. It showed that the conversion rate and yield of BO was significantly improved by 46.14% and 31.87% due to temperature and TEMPO respectively. The relative contents of dominant platform chemicals in bio-oil were as follows approximately: ketones > esters > alkanes > alcohols > acids. The total yields of ketones enhanced markedly (from 20.00 to 41.83%) with the increasing of TEMPO. The results showed that TEMPO catalyst under appropriate reaction conditions improved the selectivity of platform chemicals with carbonyl, which had an obvious contribution on the converting of ketones.
Economia Politica, Volume 36, pp 695-729; https://doi.org/10.1007/s40888-019-00159-3
This study explores the relationship between greenhouse gas (GHG) emissions, financial development and disaggregated energy consumption among the top 10 countries with the highest CO2 emissions (Canada, China, Germany, India, Iran, Japan, Korea Republic, Russia, UK and US). The study uses panel data for the period 1990–2014 within a multivariate framework. The econometric techniques of cross-sectional dependence unit root test, panel co-integration (Levine, Lin and Chun; Breitung; Im, Pesaran and Shin; Fisher-Augmented Dickey Fuller and Fisher-Phillips Perrron) tests, fully modified ordinary least squares (FMOLS) and Dumitrescu and Hurlin Granger causality tests are applied for the unit root test, co-integration, estimation of long-run coefficients as well as inference on the causal relationship respectively. Pesaran’s cross-sectional unit root test shows that variables are integrated of the first order. Pedroni’s heterogeneous panel co-integration tests reveal a long-run equilibrium relationship between the dependent and independent variables. The Granger-causality results indicate both short-run and long-run causality among renewable, fossil fuel energy and financial development and GHG emissions. The results’ findings have important policy implications for environmental quality, and thus, GHG emissions’ reduction using a higher percentage of energy from renewable energy. In addition, there is need for countries to increase financial support on renewable energy infrastructure construction as well as transformation of fossil fuel energy utilization.
Economic Modelling, Volume 84, pp 203-213; https://doi.org/10.1016/j.econmod.2019.04.010
The interdependence among energy consumption, economic growth and environmental degradation has become an important public policy priority among OECD countries. Yet, the related literature provides conflicting results when describing the dynamic nature of such a relationship and the way it affects countries' development path. Using a sample of 35 OECD countries over the period 2000–2014, we find that economic growth and energy consumption patterns contribute to the enhancement of countries' environmental performance levels. In contrast to a large stream of empirical research, our findings highlight that countries' economic development path and their energy consumption patterns have started to align with their environmental policies. The results are robust since we utilize different aspects of countries' environmental degradation such as carbon dioxide emissions, ecological footprints and countries' environmental performance levels. Finally, the analysis of the dynamic interrelations among countries' energy consumption, economic growth and environmental degradation levels, reveals the necessity to promote sustainable development through a coexistence rather than through a trade-off mechanism.
Published: 4 November 2018
Inventive Computation and Information Technologies pp 3-9; https://doi.org/10.1007/978-3-030-00102-5_1
Conference: International Conference Project “The future of the Global Financial System: Downfall of Harmony”, 13 April 2018 - 14 April 2018, Larnaca, Cyprus
The purpose of the work is to study the peculiarities of integration processes and their influence on economy of the agro-industrial complex of various models of economic systems. The authors use the method of regression analysis for determining the dominating type of integration (internal or external), calculate the values of regression indicators, and determine the type if influence of integration processes on economy of the agro-industrial complex (positive or negative influence). For determining the dominating type of integration, dynamics of the values of the corresponding indicators are studied. The indicator of internal integration is the index of intensity of competition in domestic sectorial markets according to the World Economic Forum. The indicator of external integration is the index of economic globalization according to the KOF. The level of development of economy of the AIC is evaluated on the basis of the index of food production according to the World Bank. The data are studied in dynamics of three years: from 2015 to 2017 by the example of the countries that correspond to various distinguished models of economic systems. As a result, it is concluded that various models of economic systems are influenced differently by internal and external integration. The authors substantiate the necessity for mandatory accounting of the influence of integration processes during management of development of the AIC economy. For that, the proprietary mechanism of management of integration processes in the interests of stimulating the development of the AIC economy from positions of various models of economic systems is created.
Journal of Environmental Management, Volume 230, pp 474-487; https://doi.org/10.1016/j.jenvman.2018.09.065
The environmental and resource issues that accompany rapid economic growth have attracted the attention of the government and the public. Multiple non-linear and complicated interactions exist between the economy, resource and environment subsystem. Accordingly, understanding the operating mechanism of the economy–resource–environment (ERE) system and evaluating its coordination level are of immense significance for sustainable urban development. This study uses system dynamics (SD) to build a dynamic model of the ERE system. Furthermore, a coupling coordination degree model (CCDM) that focuses on the coordination of the ERE system is established using data from 2000 to 2015 for Wuhan City, China. Four typical scenarios (i.e., current, economy, resource and environment scenarios) are designed and simulated by the constructed SD model. Coordination assessment results based on the CCDM show that the coordination of the economy scenario performs the worst, the environment scenario performs best in the short term and the resource scenario is considerably effective for the coordinated development of the urban ERE system in the long term. We suggest that improvements in the energy structure and the natural environment are prior choices for sustainable urban development.
Environmental Science and Pollution Research, Volume 25, pp 533-540; https://doi.org/10.1007/s11356-017-0436-x
This study examines causal relationship between urbanization and coal consumption. By taking Shanxi Province, China, as a typical case area, a multivariate path analysis model is used to seek for the key driving factors of coal consumption throughout its urbanization during the period of 1978 to 2014. The result indicates that the key factors are urban household disposable income and residential area per capita, which are closely related to urban construction and household lifestyle. It is expected that the study may inform better policies on coal consumption reduction and energy structure improvement.
Sustainability, Volume 9; https://doi.org/10.3390/su9101727
The sustainable development of an economic-energy-environment (3E) system has received increasing attention by the government because it both determines national development and individuals’ health at the macro and micro level. In this paper, we synthetically consider various important factors based on analysis of the existing literature and use system dynamics (SD) to establish models of sustainable development of a 3E system. The model not only clearly shows the complex logical relationship between the factors but also reveals the process of the 3E system. In addition, the paper provides a case study of the Beijing-Tianjin-Hebei region in China by using a scenario analysis method. The models proposed in this paper can facilitate an understanding of the sustainable development pattern of a 3E coordination system and help to provide references for policy-making institutions. The results show that the long-term development of the Beijing-Tianjin-Hebei region’s 3E system is not sustainable, but it can be changed through the adjustment of the energy structure and an increase in investment in environmental protection, which can improve the environmental quality and ensure continuous growth rather than excessive growth of energy consumption and the gross domestic product (GDP).
Environmental Science and Pollution Research, Volume 24, pp 14163-14175; https://doi.org/10.1007/s11356-017-8980-y
As the largest developing country in the world, China has witnessed fast-paced urbanization over the past three decades with rapid economic growth. In fact, urbanization has been not only shown to promote economic growth and improve the livelihood of people but also can increase demands of regional logistics. Therefore, a better understanding of the relationship between urbanization and regional logistics is important for China’s future sustainable development. The development of urban residential area and heterogeneous, modern society as well regional logistics are running two abreast. The regional logistics can promote the development of new-type urbanization jointly by promoting industrial concentration and logistics demand, enhancing the residents’ quality of life and improving the infrastructure and logistics technology. In this paper, the index system and evaluation model for evaluating the development of regional logistics and the new-type urbanization are constructed. Further, the econometric analysis is utilized such as correlation analysis, co-integration test, and error correction model to explore relationships of the new-type urbanization development and regional logistics development in Liaoning Province. The results showed that there was a long-term stable equilibrium relationship between the new-type urbanization and regional logistics. The findings have important implications for Chinese policymakers that on the path towards a sustainable urbanization and regional reverse, this must be taken into consideration. The paper concludes providing some strategies that might be helpful to the policymakers in formulating development policies for sustainable urbanization.
Renewable and Sustainable Energy Reviews, Volume 69, pp 1129-1146; https://doi.org/10.1016/j.rser.2016.09.113
Energies, Volume 10; https://doi.org/10.3390/en10010093
China has become the world’s largest carbon dioxide (CO2) emitter. Sectoral production activities promote economic development while also adding considerably to national CO2 emissions. Due to their different sectoral structures, each region shows different levels of economic development and CO2 emissions. The Chinese government hopes to achieve the dual objectives of economic growth and CO2 emissions reduction by encouraging those sectors that have high economic influence and low environmental influence. Based on the above background, this study constructed an inter-regional sectoral economic influence coefficient (REIC) and a CO2 emissions influence coefficient (RCIC) based on the basic multi-regional input-output (MRIO) model to analyse the economy-carbon nexus of 17 sectors in 30 regions in China in 2010. The results showed that most Chinese sectors and regions had low CO2 emissions influences in 2010. However, some sectors showed negative environmental influences. Specifically, the mining-related sectors showed high CO2 emissions influence with low economic influence. It is encouraging that some light industry and high-end equipment manufacturing sectors had low CO2 emissions influence with high economic influence. For regions, geographic location and past preferential policies are the most important factors influencing local economic growth and CO2 emissions reduction. Most inland regions have low economic influence with high or low CO2 emissions influence. Meanwhile, most coastal regions showed high economic influence with low CO2 emissions influence. Finally, we propose some policy implications for sectors and regions.
Ecological Indicators, Volume 69, pp 184-195; https://doi.org/10.1016/j.ecolind.2016.04.022
Sustainability, Volume 8; https://doi.org/10.3390/su8090874
This paper uses an autoregressive distributed lag model (ARDL) to examine the dynamic impact of non-fossil energy consumption on carbon dioxide (CO2) emissions in China for a given level of economic growth, trade openness, and energy usage between 1965 and 2014. The results suggest that the variables are in a long-run equilibrium. ARDL estimation indicates that consumption of non-fossil energy plays a crucial role in curbing CO2 emissions in the long run but not in the short term. The results also suggest that, in both the long and short term, energy consumption and trade openness have a negative impact on the reduction of CO2 emissions, while gross domestic product (GDP) per capita increases CO2 emissions only in the short term. Finally, the Granger causality test indicates a bidirectional causality between CO2 emissions and energy consumption. In addition, this study suggests that non-fossil energy is an effective solution to mitigate CO2 emissions, providing useful information for policy-makers wishing to reduce atmospheric CO2.
Sustainability, Volume 8; https://doi.org/10.3390/su8070642
China’s heating industry is a coal-fired industry with serious environmental issues. CO2 emissions from the heating industry accounted for an average 6.1% of China’s carbon emissions during 1985–2010. The potential for reducing emissions in China’s heating industry is evaluated by co-integration analysis and scenario analysis. The results demonstrate that there is a long-run equilibrium relationship among CO2 emissions and the influencing factors, including energy intensity, industrial scale, labor productivity, and energy productivity. Monte Carlo technique is adopted for risk analysis. It is found that the CO2 emissions reduction potential of the heating industry will be 26.7 million tons of coal equivalent (Mtce) in 2020 and 64.8 Mtce in 2025 under the moderate scenario, compared with 50.6 Mtce in 2020 and 122.1 Mtce in 2025 under the advanced scenario. Policy suggestions are provided accordingly.
Sustainability, Volume 7, pp 15570-15592; https://doi.org/10.3390/su71115570
Urban air pollution is one of the most visible environmental problems to have accompanied China’s rapid urbanization. Based on emission inventory data from 2014, gathered from 289 cities, we used Global and Local Moran’s I to measure the spatial autorrelation of Air Quality Index (AQI) values at the city level, and employed Ordinary Least Squares (OLS), Spatial Lag Model (SAR), and Geographically Weighted Regression (GWR) to quantitatively estimate the comprehensive impact and spatial variations of China’s urbanization process on air quality. The results show that a significant spatial dependence and heterogeneity existed in AQI values. Regression models revealed urbanization has played an important negative role in determining air quality in Chinese cities. The population, urbanization rate, automobile density, and the proportion of secondary industry were all found to have had a significant influence over air quality. Per capita Gross Domestic Product (GDP) and the scale of urban land use, however, failed the significance test at 10% level. The GWR model performed better than global models and the results of GWR modeling show that the relationship between urbanization and air quality was not constant in space. Further, the local parameter estimates suggest significant spatial variation in the impacts of various urbanization factors on air quality.
Environmental Science and Pollution Research, Volume 22, pp 19773-19785; https://doi.org/10.1007/s11356-015-5185-0
This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975–2013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions.
Sustainability, Volume 7, pp 5609-5627; https://doi.org/10.3390/su7055609
As the largest developing country in the world, with rapid economic growth, China has witnessed fast-paced urbanization development over the past three decades. In fact, urbanization has been shown to promote economic growth and improve the livelihood of people, but it can also increase energy consumption and further generate energy crisis. Therefore, a better understanding of the relationship between urbanization, economic growth and energy consumption is important for China’s future sustainable development. This paper empirically investigates the long-term equilibrium relationships, temporal dynamic relationships and causal relationships between urbanization, economic growth and energy consumption in China. Econometric models are utilized taking the period 1980–2012 into consideration. Cointegration tests indicate that the variables are found to be of I(1) and cointegrated. Further, vector error-correction model (VECM) indicates that when the short-term fluctuations deviate from the long-term equilibrium, the current changes of energy consumption could eliminate 9.74% non-equilibrium error of the last period, putting back the situation to the equilibrium state through a reverse adjustment. Impulse response analysis intuitively portrays the destabilized changes of the variables in response to some external shocks. However, the impact of energy consumption shock on urbanization and the impact of urbanization on economic growth seem to be rather marginal. Moreover, Granger causality results reveal that there is a bi-directional Granger causal relationship between energy consumption and economic growth, and unidirectional causality running from urbanization to energy consumption and economic growth to urbanization. The findings have important implications for Chinese policymakers that on the path towards a sustainable society, the effects of urbanization and economic growth on energy consumption must be taken into consideration.
Sustainability, Volume 7, pp 75-95; https://doi.org/10.3390/su7010075
Spurred by the increasingly serious air pollution problem, the Chinese government has launched a series of policies to put forward specific measures of power structure adjustment and the control objectives of air pollution and coal consumption. Other policies pointed out that the coal resources regional blockades will be broken by improving transportation networks and constructing new logistics nodes. Thermal power takes the largest part of China’s total installed power generation capacity, so these policies will undoubtedly impact thermal coal supply chain member enterprises. Based on the actual situation in China, this paper figures out how the member enterprises adjust their business decisions to satisfy the requirements of air pollution prevention and control policies by establishing system dynamic models of policy impact transfer. These dynamic analyses can help coal enterprises and thermal power enterprises do strategic environmental assessments and find directions of sustainable development. Furthermore, the policy simulated results of this paper provide the Chinese government with suggestions for policy-making to make sure that the energy conservation and emission reduction policies and sustainable energy policies can work more efficiently.