scholarly journals The Role of Renewables in a Low-Carbon Society: Evidence from a Multivariate Panel Data Analysis at the EU Level

2019 ◽  
Vol 11 (19) ◽  
pp. 5260 ◽  
Author(s):  
Mihail Busu
Keyword(s):  
Panel Data ◽  
Population Growth ◽  
Co2 Emissions ◽  
Carbon Emission ◽  
Linear Regression Analysis ◽  
Biofuel Production ◽  
Total Carbon ◽  
Low Carbon ◽  
Eu Countries ◽  
The Impact

Low carbon emission has a major positive impact on our society. Due to the importance of reducing carbon emission levels, factors that contribute significantly towards reducing carbon emission levels have attracted the interest of academics and researchers in the field. In this paper, the author develops a multiple linear regression analysis to examine the relationship between renewable energy consumption, biofuel production, resources productivity, bioenergy productivity, the level of urbanization and population and their impact on total carbon dioxide (CO2) emissions. Data was collected from the European Statistical Office (EUROSTAT) and four statistical hypotheses were validated through a regression model with panel data using the statistical software EViews 11. The study was conducted for 27 European Union (EU) countries during 2008 to 2017. The author’s findings indicate that renewables have a direct and positive influence on the levels of CO2 emissions, as opposed to population growth and urbanization. These findings suggest that public policy should be directed towards increasing the use of renewables in EU countries, while the level of urbanization and the population growth add more restrictions in the modelling equation of the impact on CO2 emissions.

scholarly journals Impact of Population Aging on Carbon Emission in China: A Panel Data Analysis

2018 ◽  
Vol 10 (7) ◽  
pp. 2458 ◽  
Author(s):  
Weidong Li ◽  
Xin Qi ◽  
Xiaojun Zhao
Keyword(s):  
Panel Data ◽  
Carbon Emission ◽  
Population Aging ◽  
Panel Data Analysis ◽  
Negative Relationship ◽  
Modern Society ◽  
Eastern Region ◽  
Low Carbon ◽  
Stirpat Model ◽  
The Impact

The impact of population structure on carbon emission has always been a key area of research in modern society. In this paper, we propose a new expanded STIRPAT model and panel co-integration method to analyze the relationship between population aging and carbon emission, based on the provincial panel data in China from 1999 to 2014. Empirical results show that there exists a significant inverted U-shaped curve between the population aging and carbon emission. There also exist regional discrepancies, where the impact of the population aging on carbon emission in the eastern region is significantly positive. By contrast, a negative relationship arises in the central and western regions. Finally, several suggestions for low carbon development are provided.

scholarly journals Spatio-Temporal Effects of Multi-Dimensional Urbanization on Carbon Emission Efficiency: Analysis Based on Panel Data of 283 Cities in China

2021 ◽  
Vol 18 (23) ◽  
pp. 12712
Author(s):  
Zhanhang Zhou ◽  
Linjian Cao ◽  
Kuokuo Zhao ◽  
Dongliang Li ◽  
Ci Ding
Keyword(s):  
Panel Data ◽  
Spatial Heterogeneity ◽  
Carbon Emission ◽  
Negative Impact ◽  
Low Carbon ◽  
Promoting Effect ◽  
Gradual Improvement ◽  
Emission Efficiency ◽  
Spatio Temporal ◽  
The Impact

Under the influence of complex urbanization, improving the carbon emission efficiency (CEE) plays an important role in the construction of low-carbon cities in China. Based on the panel data of 283 prefectural-level cities in China from 2005 to 2017, this study evaluated the CEE by the US-SBM model, and explored the spatial agglomeration evolution characteristics of CEE from static and dynamic perspectives by integrating ESDA and Spatial Markov Chains. Then, the spatial heterogeneity of the impacts of multi-dimensional urbanization on CEE were analyzed by using the Geographically and Temporally Weighted Regression (GTWR). The results show that: (1) with the evolution of time, the CEE has a trend of gradual improvement, but the average is 0.4693; (2) from the perspective of spatial static agglomeration, the “hot spots” of CEE mainly concentrated in Shandong Peninsula, Pearl River Delta, and Chengdu-Chongqing urban agglomeration; The dynamic evolution of CEE gradually forms the phenomenon of “club convergence”; (3) urbanization of different dimensions shows spatial heterogeneity to CEE. The impact of economic urbanization in northern cities on CEE shows an inverted “U” shape, and the negative impact of spatial urbanization on CEE appears in the northwest and resource-based cities around Bohai Sea. Population and social urbanization have a positive promoting effect on CEE after 2010. These findings may help China to improve the level of CEE at the city level and provide a reference for low-carbon decision-making.

scholarly journals Carbon Emission Estimation of Assembled Composite Concrete Beams during Construction

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1810
Author(s):  
Kaitong Xu ◽  
Haibo Kang ◽  
Wei Wang ◽  
Ping Jiang ◽  
Na Li
Keyword(s):  
Life Cycle ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Composite Beams ◽  
Total Carbon ◽  
Construction Process ◽  
Low Carbon ◽  
Carbon Emission Reduction ◽  
The Government

At present, the issue of carbon emissions from buildings has become a hot topic, and carbon emission reduction is also becoming a political and economic contest for countries. As a result, the government and researchers have gradually begun to attach great importance to the industrialization of low-carbon and energy-saving buildings. The rise of prefabricated buildings has promoted a major transformation of the construction methods in the construction industry, which is conducive to reducing the consumption of resources and energy, and of great significance in promoting the low-carbon emission reduction of industrial buildings. This article mainly studies the calculation model for carbon emissions of the three-stage life cycle of component production, logistics transportation, and on-site installation in the whole construction process of composite beams for prefabricated buildings. The construction of CG-2 composite beams in Fujian province, China, was taken as the example. Based on the life cycle assessment method, carbon emissions from the actual construction process of composite beams were evaluated, and that generated by the composite beam components during the transportation stage by using diesel, gasoline, and electric energy consumption methods were compared in detail. The results show that (1) the carbon emissions generated by composite beams during the production stage were relatively high, accounting for 80.8% of the total carbon emissions, while during the transport stage and installation stage, they only accounted for 7.6% and 11.6%, respectively; and (2) during the transportation stage with three different energy-consuming trucks, the carbon emissions from diesel fuel trucks were higher, reaching 186.05 kg, followed by gasoline trucks, which generated about 115.68 kg; electric trucks produced the lowest, only 12.24 kg.

scholarly journals Carbon Emission Governance Zones at the County Level to Promote Sustainable Development

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 197
Author(s):  
He Zhang ◽  
Jingyi Peng ◽  
Dahlia Yu ◽  
Lie You ◽  
Rui Wang
Keyword(s):  
Sustainable Development ◽  
Carbon Emission ◽  
Total Carbon ◽  
Small Scale ◽  
County Level ◽  
Low Carbon ◽  
High Carbon ◽  
Governance System ◽  
Medium Carbon ◽  
Indicator Evaluation

Low-carbon governance at the county level has been an important issue for sustainable development due to the large contributions to carbon emission. However, the experiences of carbon emission governance at the county level are lacking. This paper discusses 5 carbon emission governance zones for 1753 counties. The zoning is formed according to a differentiated zoning method based on a multi-indicator evaluation to judge if the governance had better focus and had formulated a differentiated carbon emission governance system. According to zoning results, there is 1 high-carbon governance zone, 2 medium-carbon governance zones, and 2 low-carbon zones. The extensive high-carbon governance zone and medium-carbon zones are key governance areas, in which the counties are mainly located in the northern plain areas and southeast coastal areas and have contributed 51.88% of total carbon emissions. This paper proposes differentiated governance standards for each indicator of the 5 zones. The differentiated zoning method mentioned in this paper can be applied to other governance issues of small-scale regions.

scholarly journals Analyzing the Renewable Energy and CO2 Emission Levels Nexus at an EU Level: A Panel Data Regression Approach

Processes ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 130
Author(s):  
Mihail Busu ◽  
Alexandra Catalina Nedelcu
Keyword(s):  
Renewable Energy ◽  
Panel Data ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Negative Impact ◽  
National Level ◽  
Renewable Energy Consumption ◽  
Urbanization Level ◽  
Carbon Dioxide Co2 ◽  
The Impact

In the past decades, carbon dioxide (CO2) emissions have become an important issue for many researchers and policy makers. The focus of scientists and experts in the area is mainly on lowering the CO2 emission levels. In this article, panel data is analyzed with an econometric model, to estimate the impact of renewable energy, biofuels, bioenergy efficiency, population, and urbanization level on CO2 emissions in European Union (EU) countries. Our results underline the fact that urbanization level has a negative impact on increasing CO2 emissions, while biofuels, bioenergy production, and renewable energy consumption have positive and direct impacts on reducing CO2 emissions. Moreover, population growth and urbanization level are negatively correlated with CO2 emission levels. The authors’ findings suggest that the public policies at the national level must encourage the consumption of renewable energy and biofuels in the EU, while population and urbanization level should come along with more restrictions on CO2 emissions.

scholarly journals Analysis of total carbon emission of the logistics industry in Guangdong and solutions to emission reduction

2021 ◽  
Vol 245 ◽  
pp. 01020
Author(s):  
Aixia Xu ◽  
Xiaoyong Yang
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Utilization ◽  
Total Carbon ◽  
Utilization Rate ◽  
Low Carbon ◽  
Logistics Industry ◽  
Direct Energy ◽  
Reduce Emissions

The input-output method is employed in this study to measure the total carbon emission of the logistics industry in Guangdong. The findings revealed that the carbon emission of direct energy consumption of the logistics industry in Guangdong is far above the actual carbon emissions, the second and third industries play a significant role in carbon emission of indirect energy consumption in the logistics industry in Guangdong. To reduce energy consumption and carbon emissions in Guangdong, it is not only important to control the carbon emissions in the logistics industry, but strengthen carbon emission detection in relevant industries, improve the energy utilization rate and reduce emissions in other industries, and move towards low-carbon sustainable development.

scholarly journals Does Emission Trading Improve Carbon Emission Efficiency of China’s Iron and Steel Industry? An Exploration Using a DEA-SBM and Difference-In-Differences Approach

2021 ◽  
Author(s):  
Xiping Wang ◽  
Sujing Wang
Keyword(s):  
Steel Industry ◽  
Carbon Emission ◽  
Emission Trading ◽  
Energy Structure ◽  
Iron And Steel Industry ◽  
Low Carbon ◽  
Difference In Differences ◽  
Iron And Steel ◽  
Emission Efficiency ◽  
The Impact

Abstract As an effective tool of carbon emission reduction, emission trading has been widely used in many countries. Since 2013, China implemented carbon emission trading in seven provinces and cities, with iron and steel industry included in the first batch of pilot industries. This study attempts to explore the policy effect of emission trading on iron and steel industry in order to provide data and theoretical support for the low-carbon development of iron and steel industry as well as the optimization of carbon market. With panel data of China’s 29 provinces from 2006 to 2017, this study adopted a DEA-SBM model to measure carbon emission efficiency of China’s iron and steel industry (CEI) and a difference-in-differences (DID) method to explore the impact of emission trading on CEI. Moreover, regional heterogeneity and influencing mechanisms were further investigated, respectively. The results indicate that: (1) China's emission trading has a significant and sustained effect on carbon abatement of iron and steel industry, increasing the annual average CEI by 12.6% in pilot provinces. (2) The policy effects are heterogeneous across diverse regions. Higher impacts are found in the western and eastern regions, whereas the central region is not significant. (3) Emission trading improves CEI by stimulating technology innovation, reducing energy intensity, and adjusting energy structure. (4) Economic level and industrial structure are negatively related to CEI, while environmental governance and openness degree have no obvious impacts. Finally, according to the results and conclusions, some specific suggestions are proposed.

scholarly journals Spatial cluster and Heterogeneity Research on Energy-Related Carbon Emissions in Districts and Counties of Guangdong Province

2019 ◽  
Vol 79 ◽  
pp. 03019
Author(s):  
Wenxiu Wang ◽  
Shangjun Ke ◽  
Daiqing Zhao ◽  
Guotian Cai
Keyword(s):  
Spatial Autocorrelation ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Guangdong Province ◽  
Total Carbon ◽  
Low Carbon ◽  
Cluster Area ◽  
Reduce Emissions ◽  
Global Spatial Autocorrelation ◽  
High Cluster

Energy-related carbon emissions in districts and counties of Guangdong province from 2005 to 2016 are researched based on spatial econometrics method in this article, and significance cluster area and heterogeneity area are precise pinpointed. Conclusions are as follows: (1) total carbon emissions and per capita carbon emissions exist significance global spatial autocorrelation in the year 2005-2016, and formed significance high-high cluster area in districts and counties of Guangzhou city, Shenzhen city and Dongguan city. It also formed three significance low-low cluster areas in districts and counties of eastern, western and northern of Guangdong province. Low-high heterogeneity area and high -low heterogeneity area often appears in the scope of high-high cluster area and low-low cluster area. (2)Carbon emission intensity not exist significance global spatial autocorrelation, but exist significance cluster area and heterogeneity area in the ecological development areas of eastern, western and northern of Guangdong province. In the end, the paper puts forward the regional and detailed policy recommendations for efficient carbon emission reduction for each cluster type region: carbon high-high cluster areas are priority reduce emissions area, heighten energy saving technology and optimize industrial structure are two grippers to reduce emissions. Low - low carbon emissions concentrated area in western of Guangdong should primarily develop high and new technology industry. Low low carbon emissions concentrated areas and high - high carbon emissions intensity concentrated area for eastern and northern of Guangdong province should try hard to wins ecological compensation at the same time focus on developing ecological tourism.

scholarly journals PERTUMBUHAN PENDUDUK, INFLASI DAN KORUPSI: ANALISIS EMPIRIS ENVIRONMENTAL KUZNETS CURVE (EKC) DI KAWASAN ASEAN PERIODE 2002-2016

2019 ◽  
Vol 1 (3) ◽  
pp. 71
Author(s):  
Muhammad Fajri Setia Trianto ◽  
Evi Yulia Purwanti
Keyword(s):  
Economic Growth ◽  
Population Growth ◽  
Co2 Emissions ◽  
Environmental Kuznets Curve ◽  
Secondary Data ◽  
Gdp Per Capita ◽  
Environmental Damage ◽  
Kuznets Curve ◽  
Per Capita ◽  
The Impact

The economy that continues to grow has the impact of environmental damage. This study aims to prove empirically the Environmental Kuznets Curve (EKC) hypothesis by analyzing the relationship of economic growth with environmental damage as measured by GDP per capita, and CO2 emissions. The data used are secondary data in the form of data on GDP per capita, CO2 emissions, population growth, inflation, and control of corruption in 10 countries in the ASEAN region in 2002-2016. Data analysis using the Fixed Effect model. The results show that there is a relationship between economic growth and environmental damage that forms an inverted U curve. Economic growth will initially have a positive effect on environmental damage so that at a point of economic growth negatively affects environmental damage. By adding control variables: population growth, inflation and corruption, inflation and corruption positively impact environmental damage, while population negatively affect environmental damage.

scholarly journals Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction

2019 ◽  
Vol 11 (16) ◽  
pp. 4387 ◽  
Author(s):  
Lin ◽  
Zhang ◽  
Wang ◽  
Yang ◽  
Shi ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Carbon Tax ◽  
Search Algorithm ◽  
Urban Traffic ◽  
Low Carbon ◽  
Carbon Emission Reduction ◽  
Urban Distribution ◽  
The Impact

The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the basis of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution routes with and without carbon emissions cost are constructed. Fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit.

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