scholarly journals Impact of Green Innovation Efficiency on Carbon Emission Reduction in the Guangdong-Hong Kong-Macao GBA

2021 ◽  
Vol 13 (23) ◽  
pp. 13450
Author(s):  
Lingming Chen ◽  
Congjia Huo
Keyword(s):  
Hong Kong ◽  
Linear Relationship ◽  
Spatial Correlation ◽  
Carbon Emissions ◽  
Emission Intensity ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Green Innovation ◽  
Carbon Emission Reduction ◽  
Carbon Emission Intensity

Climate change has become a global issue of general concern to human society. It is not only an environmental issue, but also a development issue. As the second largest economy in the world, China has adhered to its commitments in the Paris Agreement and formulated a series of autonomous action targets. In this context, scholars have done a lot of research focusing on carbon emission reduction, but have neglected the spatial correlation of carbon emission, and lack of research on carbon emission reduction in urban agglomerations. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has been at the forefront of China in terms of economy, politics, ecology, and civilization by taking advantage of the “one country, two systems” policy. This article innovatively proposes that there is a non-linear relationship between the efficiency of green innovation and the carbon emission intensity of the Guangdong-Hong Kong-Macao GBA, and has passed quantitative verification. Based on the panel data of the Guangdong-Hong Kong-Macao GBA from 2009 to 2019, we used the super-efficiency slacks-based measure (SBM) model to measure the efficiency of green innovation. We used the global Moran index and Theil index to discuss the spatial correlation of carbon emissions and regional differences in carbon emission intensity in the Guangdong-Hong Kong-Macao GBA, respectively. Then, we used the threshold model to verify the nonlinear relationship between the efficiency of green innovation and the intensity of carbon emissions in the Guangdong-Hong Kong-Macao GBA. The results of the study found that the green innovation efficiency of the Guangdong-Hong Kong-Macao GBA is increasing overall, carbon emissions have a certain spatial correlation, and the correlation is low overall. The impact of green innovation efficiency on carbon emission intensity has a non-linear relationship and there is an “inverted U” pattern between the two, and there is an inflection point in green innovation efficiency. Based on this, this article proposes carbon emission reduction measures within a reasonable range, and looks forward to future research directions and complement the research deficiencies.

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 The Changes of Carbon Emission in China’s Industrial Sectors from 2002 to 2010: A Structural Decomposition Analysis and Input-Output Subsystem

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Guoxing Zhang ◽  
Mingxing Liu
Keyword(s):  
Carbon Emissions ◽  
Emission Intensity ◽  
Carbon Emission ◽  
Decomposition Analysis ◽  
Final Demand ◽  
Good Effect ◽  
Input Output ◽  
Carbon Emission Intensity ◽  
Industrial Sectors ◽  
Three Components

Based on 2002–2010 comparable price input-output tables, this paper first calculates the carbon emissions of China’s industrial sectors with three components by input-output subsystems; next, we decompose the three components into effect of carbon emission intensity, effect of social technology, and effect of final demand separately by structure decomposition analysis; at last, we analyze the contribution of every effect to the total emissions by sectors, thus finding the key sectors and key factors which induce the changes of carbon emissions in China’s industrial sectors. Our results show that in the latest 8 years five departments have gotten the greatest increase in the changes of carbon emissions compare with other departments and the effect of final demand is the key factor leading to the increase of industrial total carbon emissions. The decomposed effects show a decrease in carbon emission due to the changes of carbon emission intensity between 2002 and 2010 compensated by an increase in carbon emissions caused by the rise in final demand of industrial sectors. And social technological changes on the reduction of carbon emissions did not play a very good effect and need further improvement.

scholarly journals Optimal Decisions for Two Risk-Averse Competitive Manufacturers under the Cap-and-Trade Policy and Uncertain Demand

2020 ◽  
Vol 17 (3) ◽  
pp. 1010 ◽  
Author(s):  
Hongxia Sun ◽  
Jie Yang ◽  
Yang Zhong
Keyword(s):  
Decision Making ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Reduction Rate ◽  
Risk Averse ◽  
Cap And Trade ◽  
Carbon Emission Reduction ◽  
Optimal Decisions ◽  
The Government

With the increasingly serious problem of environmental pollution, reducing carbon emissions has become an urgent task for all countries. The cap-and-trade (C&T) policy has gained international recognition and has been adopted by several countries. In this paper, considering the uncertainty of market demand, we discuss the carbon emission reduction and price policies of two risk-averse competitive manufacturers under the C&T policy. The two manufacturers have two competitive behaviors: simultaneous decision making and sequential decision making. Two models were constructed for these behaviors. The optimal decisions, carbon emission reduction rate, and price were obtained from these two models. Furthermore, in this paper the effects of some key parameters on the optimal decision are discussed, and some managerial insights are obtained. The results show that the lower the manufacturers’ risk aversion level is, the higher their carbon emission reduction rate and utilities. As the carbon quota increases, the manufacturers’ optimal carbon reduction rate and utilities increase. Considering consumers’ environmental awareness, it is more beneficial for the government to reduce the carbon quota and motivate manufacturers’ internal enthusiasm for emission reduction. The government can, through macro control of the market, make carbon trading prices increase appropriately and encourage manufacturers to reduce carbon emissions.

scholarly journals Multi-Perspective Influence Mechanism Analysis and Multi-Scenario Prediction of Carbon Emissions——A Case of the Yangtze River Delta, China

2019 ◽  
Vol 118 ◽  
pp. 04014
Author(s):  
Tao Yi ◽  
Mohan Qiu ◽  
Zhengang Zhang ◽  
Song Mu ◽  
Yu Tian
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Yangtze River ◽  
Carbon Emission ◽  
Yangtze River Delta ◽  
Mechanism Analysis ◽  
The Yangtze River ◽  
Carbon Emission Reduction ◽  
Influence Mechanism ◽  
The Yangtze River Delta

Under the mandatory push of meeting carbon emission reduction commitments proposed in the Paris Agreement, the analysis on the peaking time of China’s carbon emissions deserves enough attention. This paper focuses on the peaking times of total carbon emissions (TCE) and carbon emission intensity (CEI) in the Yangtze River Delta (YRD). According to the development of carbon emissions in YRD and related targets in the 13th Five-Year Plan, the peaking times of TCE and CEI in different scenarios are predicted based on the influence mechanism analysis of carbon emissions in YRD from the perspective of energy, economy and society. Considering the development characteristics of China at this stage, this paper introduces several new indicators such as full-time equivalent of research and development (R&D) personnel and investment in environmental pollution control. Based on the study results, several policy recommendations are put forward to fulfil China’s carbon emission reduction commitments.

scholarly journals Exploring Potential Pathways toward Energy-Related Carbon Emission Reduction in Heavy Industrial Regions of China: An Input–Output Approach

2020 ◽  
Vol 12 (5) ◽  
pp. 2148 ◽  
Author(s):  
Jingyao Peng ◽  
Yidi Sun ◽  
Junnian Song ◽  
Wei Yang
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Emission Intensity ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Input Output ◽  
Carbon Emission Reduction ◽  
Industrial Regions ◽  
Co2 Emission Intensity

It is a very urgent issue to reduce energy-related carbon emissions in China. The three northeastern provinces (Heilongjiang (HLJ), Jilin (JL), and Liaoning (LN)) are typical heavy industrial regions in China, playing an important role in the national carbon emission reduction target. In this study, we analyzed the energy consumption, carbon dioxide (CO2) emissions, and CO2 emission intensity of each sector in the three regions, and we compared them with the national level and those of China’s most developed province Guangdong (GD). Then, based on an input–output (I–O) framework, linkage analysis of production and CO2 emission from sector–system and sector–sector dimensions was conducted. The results showed that the three regions accounted for about 1/10 of China’s energy consumption and 1/6 of China’s CO2 emissions in 2012. In addition, the level of energy structure, CO2 emission intensity, and sectoral structure lagged behind China’s average level, much lower than those for GD. According to the sectoral characteristics of each region and unified backward/forward linkages of production and CO2 emissions, we divided sectoral clusters into those whose development was to be encouraged and those whose development was to be restricted. The results of this paper could provide policy–makers with reference to exploring potential pathways toward energy-related carbon emission reduction in heavy industrial regions.

scholarly journals Carbon Emission Reduction Strategy for Energy Users in China

2020 ◽  
Vol 12 (16) ◽  
pp. 6498 ◽  
Author(s):  
Fuquan Zhao ◽  
Feiqi Liu ◽  
Han Hao ◽  
Zongwei Liu
Keyword(s):  
Renewable Energy ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Current Status ◽  
Chinese Government ◽  
Carbon Trading ◽  
Levelized Cost Of Electricity ◽  
Carbon Emission Reduction ◽  
The Cost

The Chinese government has made a commitment to control carbon emissions, and the deployment of renewable energy power generation is considered as an effective solution. In recent years, great effort has been exerted to support the development of renewable energy in China. While, due to fiscal pressures and changes in management policies, related subsidies are diminishing now and energy users are asked to pay for the cost. Regulations about carbon cap and renewable energy consumptions are issued to transfer the responsibility of consuming renewable energy and reducing carbon emissions to energy consumers. A national carbon trading system is set up in China and is under its growth stage. Therefore, this study lists the factors that should be considered by the energy users, analyzes the levelized cost of electricity generated by renewable energy in four cities in China, Beijing, Shanghai, Guangzhou, Wuhan, and compares the results with current carbon prices. Based on the research, under the current status, it is still more cost-efficient for enterprises to buy carbon credits than introduce renewable energies, and great differences among cities are shown due to different natural conditions. Besides, with diminishing subsidies and development of the carbon trading market, the carbon price will gradually reflect the actual value and carbon emission reduction costs will become an important part of enterprise expenditure. In the long term, enterprises should link more factors to carbon emissions, like social responsibility and brand image, instead of only the cost.

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.

scholarly journals Crop Production and Agricultural Carbon Emissions: Relationship Diagnosis and Decomposition Analysis

2021 ◽  
Vol 18 (15) ◽  
pp. 8219
Author(s):  
Jianli Sui ◽  
Wenqiang Lv
Keyword(s):  
Economic Growth ◽  
Agricultural Economic ◽  
Carbon Emissions ◽  
Emission Intensity ◽  
Crop Production ◽  
Carbon Emission ◽  
Decomposition Analysis ◽  
Lmdi Method ◽  
Carbon Emission Intensity ◽  
Decoupling Analysis

Modern agriculture contributes significantly to greenhouse gas emissions, and agriculture has become the second biggest source of carbon emissions in China. In this context, it is necessary for China to study the nexus of agricultural economic growth and carbon emissions. Taking Jilin province as an example, this paper applied the environmental Kuznets curve (EKC) hypothesis and a decoupling analysis to examine the relationship between crop production and agricultural carbon emissions during 2000–2018, and it further provided a decomposition analysis of the changes in agricultural carbon emissions using the log mean Divisia index (LMDI) method. The results were as follows: (1) Based on the results of CO2 EKC estimation, an N-shaped EKC was found; in particular, the upward trend in agricultural carbon emissions has not changed recently. (2) According to the results of the decoupling analysis, expansive coupling occurred for 9 years, which was followed by weak decoupling for 5 years, and strong decoupling and strong coupling occurred for 2 years each. There was no stable evolutionary path from coupling to decoupling, and this has remained true recently. (3) We used the LMDI method to decompose the driving factors of agricultural carbon emissions into four factors: the agricultural carbon emission intensity effect, structure effect, economic effect, and labor force effect. From a policymaking perspective, we integrated the results of both the EKC and the decoupling analysis and conducted a detailed decomposition analysis, focusing on several key time points. Agricultural economic growth was found to have played a significant role on many occasions in the increase in agricultural carbon emissions, while agricultural carbon emission intensity was important to the decline in agricultural carbon emissions. Specifically, the four factors’ driving direction in the context of agricultural carbon emissions was not stable. We also found that the change in agricultural carbon emissions was affected more by economic policy than by environmental policy. Finally, we put forward policy suggestions for low-carbon agricultural development in Jilin province.

scholarly journals A Study on The Driving Factors and Spatial Spillover of Carbon Emission Intensity in The Yangtze River Economic Belt under Double Control Action

2019 ◽  
Vol 16 (22) ◽  
pp. 4452 ◽  
Author(s):  
Xuhui Ding ◽  
Zhongyao Cai ◽  
Qianqian Xiao ◽  
Suhui Gao
Keyword(s):  
Technological Innovation ◽  
Emission Intensity ◽  
Emission Reduction ◽  
Yangtze River ◽  
Carbon Emission ◽  
Spillover Effects ◽  
The Yangtze River ◽  
Low Carbon ◽  
Spatial Spillover ◽  
Carbon Emission Intensity

It is greatly important to promote low-carbon green transformations in China, for implementing the emission reduction commitments and global climate governance. However, understanding the spatial spillover effects of carbon emissions will help the government achieve this goal. This paper selects the carbon-emission intensity panel data of 11 provinces in the Yangtze River Economic Belt from 2004 to 2016. Then, this paper uses the Global Moran’s I to explore the spatial distribution characteristics and spatial correlation of carbon emission intensity. Furthermore, this paper constructs a spatial econometric model to empirically test the driving path and spillover effects of relevant factors. The results show that there is a significant positive correlation with the provincial carbon intensity in the Yangtze River Economic Belt, but this trend is weakening. The provinces of Jiangsu, Zhejiang, and Shanghai are High–High agglomerations, while the provinces of Yunnan and Guizhou are Low–Low agglomerations. Economic development, technological innovation, and foreign direct investion (FDI) have positive effects on the reduction of carbon emissions, while industrialization has a negative effect on it. There is also a significant positive spatial spillover effect of the industrialization level and technological innovation level. The spatial spillover effects of FDI and economic development on carbon emission intensity fail to pass a significance test. Therefore, it is necessary to promote cross-regional low-carbon development, accelerate the R&D of energy-saving and emission-reduction technologies, actively enhance the transformation and upgrade industrial structures, and optimize the opening up of the region and the patterns of industrial transfer.

scholarly journals Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective

2020 ◽  
Vol 12 (19) ◽  
pp. 8097
Author(s):  
Li-Ming Xue ◽  
Shuo Meng ◽  
Jia-Xing Wang ◽  
Lei Liu ◽  
Zhi-Xue Zheng
Keyword(s):  
Spatial Econometrics ◽  
Emission Intensity ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Spillover Effect ◽  
Influential Factors ◽  
Energy Structure ◽  
Driving Mechanism ◽  
Emission Mitigation ◽  
Carbon Emission Intensity

Emission reduction strategies based on provinces are key for China to mitigate its carbon emission intensity (CEI). As such, it is valuable to analyze the driving mechanism of CEI from a provincial view, and to explore a coordinated emission mitigation mechanism. Based on spatial econometrics, this study conducts a spatial-temporal effect analysis on CEI, and constructs a Spatial Durbin Model on the Panel data (SDPM) of CEI and its eight influential factors: GDP, urbanization rate (URB), industrial structure (INS), energy structure (ENS), energy intensity (ENI), technological innovation (TEL), openness level (OPL), and foreign direct investment (FDI). The main findings are as follows: (1) overall, there is a significant and upward trend of the spatial autocorrelation of CEI on 30 provinces in China. (2) The spatial spillover effect of CEI is positive, with a coefficient of 0.083. (3) The direct effects of ENI, ENS and TEL are significantly positive in descending order, while INS and GDP are significantly negative. The indirect effects of URB and ENS are significantly positive, while GDP, ENI, OPL and FDI are significantly negative in descending order. Economic and energy-related emission reduction measures are still crucial to the achievement of CEI reduction targets for provinces in China.

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