scholarly journals Driving Factor Analysis of Carbon Emissions in China’s Power Sector for Low-Carbon Economy

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Dan Yan ◽  
Yalin Lei ◽  
Li Li
Keyword(s):  
Power Generation ◽  
Carbon Emissions ◽  
Electricity Consumption ◽  
Least Squares Regression ◽  
Low Carbon ◽  
Power Sector ◽  
Stirpat Model ◽  
Coal Consumption ◽  
Low Carbon Economy ◽  
Generation Structure

The largest percentage of China’s total coal consumption is used for coal-fired power generation, which has resulted in the power sector becoming China’s largest carbon emissions emitter. Most of the previous studies concerning the driving factors of carbon emissions changes lacked considerations of different socioeconomic factors. This study examines the impacts of eight factors from different aspects on carbon emissions within power sector from 1981 to 2013 by using the extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model; in addition, the regression coefficients are effectively determined by a partial least squares regression (PLS) method. The empirical results show that (1) the degree of influence of various factors from strong to weak is urbanization level (UL) > technology level (T1) > population (P) > GDP per capita (A) > line loss (T2) > power generation structure (T3) > energy intensity (T4) > industry structure (IS); (2) economic activity is no longer the most important contributing factor; the strong correlation between electricity consumption and economic growth is weakening; and (3) the coal consumption rate of power generation had the most obvious inhibitory effect, indicating that technological progress is still a vital means of achieving emissions reductions.

scholarly journals The Moderating Effect of R&D Investment on Income and Carbon Emissions in China: Direct and Spatial Spillover Insights

2019 ◽  
Vol 11 (5) ◽  
pp. 1235 ◽  
Author(s):  
Shaozhou Qi ◽  
Huarong Peng ◽  
Xiujie Tan
Keyword(s):  
Carbon Emissions ◽  
Knowledge Spillovers ◽  
Positive Impact ◽  
Positive Influence ◽  
Moderating Effect ◽  
Low Carbon ◽  
Coal Consumption ◽  
Spatial Spillover ◽  
Low Carbon Economy ◽  
D Investment

R&D investment plays a great role in achieving China’s low-carbon economy goals, which has a moderating effect on the relationship between income and carbon emissions. Furthermore, such a moderating effect may have spatial differences, given the possible spatial dependence of carbon emissions. Therefore, this paper explores the direct and spatial spillover moderating effects of R&D investment by adopting the panel spatial Durbin model and data of 30 provinces in China during 1998–2015. The empirical results firstly indicate that R&D investment moderates the positive impact of income on local carbon emissions for both the non-spatial and spatial model, and that more R&D investment can make carbon emissions reach the turning point earlier. Secondly, R&D investment in the local province increases the positive influence of local income on neighboring carbon emissions, which mainly results from the transfer effect of carbon emissions rather than the knowledge spillovers effect. The results are indicated to be robust by three types of robustness analyses. Finally, FDI and patents are the main constrained forces of local and neighboring carbon emissions; coal consumption is the main driver of local carbon emissions.

scholarly journals Decomposition and Forecasting of CO2 Emissions in China’s Power Sector Based on STIRPAT Model with Selected PLS Model and a Novel Hybrid PLS-Grey-Markov Model

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2985 ◽  
Author(s):  
Herui Cui ◽  
Ruirui Wu ◽  
Tian Zhao
Keyword(s):  
Markov Model ◽  
Co2 Emissions ◽  
Ridge Regression ◽  
Back Propagation ◽  
Partial Least Square ◽  
Least Square ◽  
Low Carbon ◽  
Power Sector ◽  
Stirpat Model ◽  
Generation Structure

China faces significant challenges related to global warming caused by CO2 emissions, and the power industry is a large CO2 emitter. The decomposition and accurate forecasting of CO2 emissions in China’s power sector are thus crucial for low-carbon outcomes. This paper selects seven socio-economic and technological drivers related to the power sector, and decomposes CO2 emissions based on two models: the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) model and the partial least square (PLS) model. Distinguished from previous research, our study first compares the effects of eliminating the multicollinearity of the PLS model with stepwise regression and ridge regression, finding that PLS is superior. Further, the decomposition results show the factors’ absolute elasticity coefficients are population (2.58) > line loss rate (1.112) > GDP per capita (0.669) > generation structure (0.522) > the urbanization level (0.512) > electricity intensity (0.310) > industrial structure (0.060). Meanwhile, a novel hybrid PLS-Grey-Markov model is proposed, and is verified to have better precision for the CO2 emissions of the power sector compared to the selected models, such as ridge regression-Grey-Markov, PLS-Grey-Markov, PLS-Grey and PLS-BP (Back propagation neutral network model). The forecast results suggest that CO2 emissions of the power sector will increase to 5102.9 Mt by 2025. Consequently, policy recommendations are proposed to achieve low-carbon development in aspects of population, technology, and economy.

scholarly journals Life Cycle Energy Consumption and Carbon Dioxide Emissions of Agricultural Residue Feedstock for Bioenergy

2021 ◽  
Vol 11 (5) ◽  
pp. 2009
Author(s):  
Valerii Havrysh ◽  
Antonina Kalinichenko ◽  
Anna Brzozowska ◽  
Jan Stebila
Keyword(s):  
Carbon Dioxide ◽  
Power Generation ◽  
Life Cycle ◽  
Carbon Dioxide Emissions ◽  
Crop Production ◽  
Agricultural Residues ◽  
Environmental Indicators ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Energy Inputs

The depletion of fossil fuels and climate change concerns are drivers for the development and expansion of bioenergy. Promoting biomass is vital to move civilization toward a low-carbon economy. To meet European Union targets, it is required to increase the use of agricultural residues (including straw) for power generation. Using agricultural residues without accounting for their energy consumed and carbon dioxide emissions distorts the energy and environmental balance, and their analysis is the purpose of this study. In this paper, a life cycle analysis method is applied. The allocation of carbon dioxide emissions and energy inputs in the crop production by allocating between a product (grain) and a byproduct (straw) is modeled. Selected crop yield and the residue-to-crop ratio impact on the above indicators are investigated. We reveal that straw formation can consume between 30% and 70% of the total energy inputs and, therefore, emits relative carbon dioxide emissions. For cereal crops, this energy can be up to 40% of the lower heating value of straw. Energy and environmental indicators of a straw return-to-field technology and straw power generation systems are examined.

Carbon Efficient Supply Chain Management: Literature Review with Extensions

2013 ◽  
Vol 291-294 ◽  
pp. 1407-1412 ◽  
Author(s):  
Liang Jie Xia ◽  
Dao Zhi Zhao ◽  
Bai Yun Yuan
Keyword(s):  
Supply Chain ◽  
Carbon Emissions ◽  
Optimization Theory ◽  
Production Optimization ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Chain Operation ◽  
Market Economy System ◽  
Supply Chain Operation ◽  
Carbon Economy

In low carbon economy, carbon emissions permit has become a kind of resource; in the market economy system, new economic relations between enterprises have appeared, these characteristics make enterprise operation cost structure and profiting pattern changed. The paper reviews the previous literature on carbon footprint, production optimization theory individual enterprise and supply chain operation management with carbon emissions constraints. Then the paper put forward four worth further research directions: Carbon emission cost distribution and scientific measurement in supply chain; supply chain operation based on consumer behavior in Low Carbon Economy Era; optimizing the allocation of carbon emissions permit in supply chain; Dynamic Multi-period operation optimization of carbon efficient supply chain.

Study on Power Generation Expansion Planning Model Based on NOx Total Emission Control and Low Carbon Economy Effect

2013 ◽  
Vol 830 ◽  
pp. 439-443 ◽  
Author(s):  
Yu Li ◽  
Chao Ci Li
Keyword(s):  
Power Generation ◽  
Energy Saving ◽  
Emission Reduction ◽  
Emission Control ◽  
Total Emission ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Generation Expansion ◽  
Total Emission Control ◽  
Carbon Economy

Acid rain and greenhouse effect are the major air pollution problems in China, and the goals for the total emission control of NOx and total energy consumption control begin to move forward in the 12th five-year plan. NOx emission reduction and energy saving of coal-fired power plants are still put in a strategic position. Accordingly, it is of great significance to carry out power planning work, considering effect of NOx emission index and energy saving on power industry. In this study, a mixed 0-1 integer linear power generation expansion model based on total emission control of NOx and low carbon economy effect is developed for the first time, which can be used for studying the change of power structure, confirming the releasing emissions of NOx from power system for development and reducing energy consumption by total amount control of power coal consumption and CO2 emission growth rate. The model is applied to the power system in Heilongjiang province and the results indicate that the proposed model not only can meet the requirement of power generation expansion management, but also can help the power industry clear the economic impact of NOx emission reduction on self-development and achieve the energy saving target.

scholarly journals Carbon Emissions Constrained Energy Planning for Aluminum Products

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2753
Author(s):  
Rok Gomilšek ◽  
Lidija Čuček ◽  
Marko Homšak ◽  
Raymond R. Tan ◽  
Zdravko Kravanja
Keyword(s):  
Energy Source ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Electricity Consumption ◽  
Primary Aluminum ◽  
Energy Planning ◽  
Low Carbon ◽  
Gas Emissions

The production of primary aluminum is an energy-intensive industry which produces large amounts of direct and indirect greenhouse gas emissions, especially from electricity consumption. Carbon Emissions Constrained Energy Planning proved to be an efficient tool for reducing energy-related greenhouse gas emissions. This study focuses on energy planning constrained by CO2 emissions and determines the required amount of CO2 emissions from electricity sources in order to meet specified CO2 emission benchmark. The study is demonstrated on and applied to specific aluminum products, aluminum slugs and aluminum evaporator panels. Three different approaches of energy planning are considered: (i) an insight-based, graphical targeting approach, (ii) an algebraic targeting approach of cascade analysis, and (iii) an optimization-based approach, using a transportation model. The results of the three approaches show that approximately 2.15 MWh of fossil energy source should be replaced with a zero-carbon or 2.22 MWh with a low-carbon energy source to satisfy the benchmark of CO2 emissions to produce 1 t of aluminum slug; however, this substitution results in higher costs. This study is the first of its kind demonstrated on and applied to specific aluminum products, and represents a step forward in the development of more sustainable practices in this field.

Study on Different Capacity of Photovoltaic Power Generation Project Compares

2012 ◽  
Vol 608-609 ◽  
pp. 160-163
Author(s):  
Kai Bin Wang ◽  
Rong Jin Liang ◽  
Zi Hua Xu ◽  
Zun Yi Ren
Keyword(s):  
Power Generation ◽  
Development Trend ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Investment Projects ◽  
Emerging Industries ◽  
Photovoltaic Power ◽  
Development And Utilization ◽  
The Development Trend

Development and utilization of solar and other renewable resources is the development trend on energy. Belong to one of the national industrial policy to support the strategic emerging industries to optimize the power structure, Energy conservation, environmental protection, the development of low-carbon economy has a positive effect. Different monolithic capacity of photovoltaic power generation project, in construction investment, the basic difference between the little and then be able to estimate the construction of photovoltaic power generation project investment, preliminary determination of investment projects in economic rationality.

Coal power contradicts China’s climate change goals

2020 ◽  
Keyword(s):  
Carbon Emissions ◽  
Power Plants ◽  
Low Carbon ◽  
Coal Consumption ◽  
Content Type ◽  
Time Investment ◽  
Generating Capacity ◽  
Economic Stimulus ◽  
The Government ◽  
Financial Losses

Subject Energy policy in China. Significance China has resumed the construction of large numbers of coal-fired power plants, despite a massive excess of generating capacity. At the same time, investment in non-fossil fuel capacity is also still underway and the government continues to deploy low-carbon policies. Impacts Coal consumption and carbon emissions will rise further, raising doubts over the achievability of peak emissions by 2030. Despite a modest economic stimulus, large excess generating capacity will persist, as will financial losses for generating companies. The economic stimulus will boost coal use in heavy industry as well as air pollution and carbon emissions in the short-term. The financial losses of the coal-fired generators will grow; bankruptcies will be avoided through enforced consolidation and plant closures.

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