scholarly journals Scenario Analysis on Energy Consumption and CO2 Emissions Reduction Potential in Building Heating Sector at Community Level

2019 ◽  
Vol 11 (19) ◽  
pp. 5392 ◽  
Author(s):  
Chuan Tian ◽  
Guohui Feng ◽  
Shuai Li ◽  
Fuqiang Xu
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Population Data ◽  
Driving Factors ◽  
Policy Implications ◽  
Energy Planning ◽  
Emissions Reduction ◽  
Energy Structure ◽  
Baseline Scenario

Energy consumption and carbon emissions of building heating are increasing rapidly. Taking Liaobin coastal economic zone as an example, two scenarios are built to analyze the potential of energy consumption and CO2 emissions reduction from the aspects of laws, regulations, policies and planning. The baseline scenario refers to the traditional way of energy planning and the community energy planning scenario seeks to apply community energy planning within the zone. Energy consumption and CO2 emission are forecast in two scenarios with the driving factors including GDP growth, changes in population size, energy structure adjustment, energy technology progress, and increase of energy efficiency. To improve accuracy of future GDP and population data prediction, an ARIMA (Autoregressive Integrated Moving Average model) (1,1,1) model is introduced into GDP prediction and a logistics model is introduced into population prediction. Results show that compared with the baseline scenario, energy consumption levels in the community energy planning scenario are reduced by 140% and CO2 emission levels are reduced by 45%; the short-term and long-term driving factors are analyzed. Policy implications are given for energy conservation and environmental protection.

scholarly journals Exploring the Driving Forces and Reduction Potential of Industrial Energy-Related CO2 Emissions during 2001–2030: A Case Study for Henan Province, China

2019 ◽  
Vol 11 (4) ◽  
pp. 1176 ◽  
Author(s):  
Lei Liu ◽  
Ke Wang ◽  
Shanshan Wang ◽  
Ruiqin Zhang ◽  
Xiaoyan Tang
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Driving Forces ◽  
Henan Province ◽  
Policy Implications ◽  
Energy Structure ◽  
Annual Growth Rate ◽  
Industrial Emissions ◽  
Economic Output ◽  
Industrial Energy

In China, the industrial sector is the main contributor to economic development and CO2 emissions, especially for the developing regional provinces. This study employs the Logarithmic Mean Divisia Index (LMDI) approach to decompose industrial energy-related CO2 emission into eight factors during 2001–2015 for Henan Province. Furthermore, the future CO2 emissions under different scenarios (Business as Usual (BAU), Efficiency Improvement (EI), Structural Optimization (SO), R&D Input (RD), and Comprehensive Policy (CP) scenarios) over 2016–2030 are projected. The results indicate that among these factors, the economic output, R&D intensity, investment intensity, and energy structure are the drivers for increasing CO2 emissions over the entire period, with the contribution of 293, 83, 80, and 1% of the total CO2 emissions changes, respectively. Conversely, the energy intensity, R&D efficiency, and industrial internal structure can decrease CO2 emissions with contributions of –86, –163, and –108% to the changes, respectively. Under the five scenarios, CO2 emissions in 2030 will reach 1222, 1079, 793, 987, and 638 Mt with an annual growth rate of 4.7%, 3.8%, 1.8%, 3.3%, and 0.4%, respectively. In particular, the CO2 emission peak for SO and CP scenarios is observed before 2030. Finally, some policy implications are suggested to further mitigate industrial emissions.

scholarly journals Pulp and Paper Industry: Decarbonisation Technology Assessment to Reach CO2 Neutral Emissions—An Austrian Case Study

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1161
Author(s):  
Maedeh Rahnama Mobarakeh ◽  
Miguel Santos Silva ◽  
Thomas Kienberger
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Manufacturing Industry ◽  
Paper Industry ◽  
Heat Pumps ◽  
Pulp And Paper ◽  
Low Carbon ◽  
Co2 Emission Reduction

The pulp and paper (P&P) sector is a dynamic manufacturing industry and plays an essential role in the Austrian economy. However, the sector, which consumes about 20 TWh of final energy, is responsible for 7% of Austria’s industrial CO2 emissions. This study, intending to assess the potential for improving energy efficiency and reducing emissions in the Austrian context in the P&P sector, uses a bottom-up approach model. The model is applied to analyze the energy consumption (heat and electricity) and CO2 emissions in the main processes, related to the P&P production from virgin or recycled fibers. Afterward, technological options to reduce energy consumption and fossil CO2 emissions for P&P production are investigated, and various low-carbon technologies are applied to the model. For each of the selected technologies, the potential of emission reduction and energy savings up to 2050 is estimated. Finally, a series of low-carbon technology-based scenarios are developed and evaluated. These scenarios’ content is based on the improvement potential associated with the various processes of different paper grades. The results reveal that the investigated technologies applied in the production process (chemical pulping and paper drying) have a minor impact on CO2 emission reduction (maximum 10% due to applying an impulse dryer). In contrast, steam supply electrification, by replacing fossil fuel boilers with direct heat supply (such as commercial electric boilers or heat pumps), enables reducing emissions by up to 75%. This means that the goal of 100% CO2 emission reduction by 2050 cannot be reached with one method alone. Consequently, a combination of technologies, particularly with the electrification of the steam supply, along with the use of carbon-free electricity generated by renewable energy, appears to be essential.

scholarly journals The Regional Inequity of CO2 Emissions per Capita in China

2017 ◽  
Vol 9 (7) ◽  
pp. 228 ◽  
Author(s):  
Ting Liu ◽  
Wenqing Pan
Keyword(s):  
Co2 Emissions ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Theil Index ◽  
Energy Structure ◽  
Co2 Emission Reduction ◽  
Index Method ◽  
Per Capita

This paper combines Theil index method with factor decomposition technique to analyze China eight regions’ inequality of CO2 emissions per capita, and discuss energy structure, energy intensity, industrial structure, and per capita output’s impacts on inequality. This research shows that: (1) The trend of China regional carbon inequality is in the opposite direction to the per capita CO2 emission level. Namely, as the per capita CO2 emission levels rise, regional carbon inequality decreases, and vice versa. (2) Per capita output factor reduces regional carbon inequality, whereas energy structure factor and energy intensity factor increase the inequality. (3) More developed areas can reduce the carbon inequality by improving the energy structure, whereas the divergence of energy intensity in less developed areas has increased to expand the carbon inequity. Thus, when designing CO2 emission reduction targets, policy makers should consider regional differences in economic development level and energy efficiency, and refer to the main influencing factors. At the same time, upgrading industrial structure and upgrading energy technologies should be combined to meet the targets of economic growth and CO2 emission reduction.

scholarly journals Spatio-Temporal Analysis of CO2 Emission Driving Force in Various Provinces in China Using the Extended STIRPAT-GWR Model

2021 ◽  
Author(s):  
Yulin Zhang
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Temporal Analysis ◽  
Energy Structure ◽  
High Effect ◽  
Northern Regions ◽  
Spatio Temporal ◽  
Gwr Model

To fill the shortcomings of traditional research that ignores the driver’s own spatial characteristics and provide a theoretical support to formulate suitable emission reduction policies in different regions across China. In this pursuit, based on the panel data of provincial CO2 emission in 2007, 2012, and 2017, the present study employed the extended environmental impact assessment model (STIRPAT-GWR model) to study the effect of population, energy intensity, energy structure, urbanization and industrial structure on the CO2 emissions in 29 provinces across China. The empirical results show that the effect of drivers on the CO2 emissions exhibited significant variations among the different provinces. The effect of population in the southwest region was significantly lower than that of the central and eastern regions. Provinces with stronger energy intensity effects were concentrated in the central and western regions. The effect of energy structure in the eastern and northern regions was relatively strong, and gradually weakened towards the southeast region. The areas with high urbanization effect were concentrated in the central and the eastern regions. Furthermore, significant changes were observed in the high-effect regions of the industrial structure in 2017. The high-effect area showed a migration from the northwest and northeast regions in 2007 and 2012, respectively, to the southwest and southeast regions in 2017. Urbanization showed the strongest effect on the CO2 emissions, followed by population and energy intensity, and the weakest effect was exhibited by the energy and industrial structure. Thus, the effects of population and energy structure showed a downward trend, in contrary to the effect of urbanization on the CO2 emissions in China.

scholarly journals CO2 Emissions, Energy Consumption, and Economic Growth: New Evidence in the ASEAN Countries

2019 ◽  
Vol 12 (3) ◽  
pp. 145 ◽  
Author(s):  
Vo ◽  
Vo ◽  
Le
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Granger Causality ◽  
Co2 Emissions ◽  
Causal Effect ◽  
The Philippines ◽  
Policy Implications ◽  
Renewable Energy Consumption ◽  
Long Run

The members of the Association of Southeast Asian Nations (ASEAN) have made several attempts to adopt renewable energy targets given the economic, energy-related, environmental challenges faced by the governments, policy makers, and stakeholders. However, previous studies have focused limited attention on the role of renewable energy when testing the dynamic link between CO2 emissions, energy consumption and renewable energy consumption. As such, this study is conducted to test a common hypothesis regarding a long-run environmental Kuznets curve (EKC). The paper also investigates the causal link between carbon dioxide (CO2) emissions, energy consumption, renewable energy, population growth, and economic growth for countries in the region. Using various time-series econometrics approaches, our analysis covers five ASEAN members (including Indonesia, Myanmar, Malaysia, the Philippines, and Thailand) for the 1971–2014 period where required data are available. Our results reveal no long-run relationship among the variables of interest in the Philippines and Thailand, but a relationship does exist in Indonesia, Myanmar, and Malaysia. The EKC hypothesis is observed in Myanmar but not in Indonesia and Malaysia. Also, Granger causality among these important variables varies considerably across the selected countries. No Granger causality among carbon emissions, energy consumption, and renewable energy consumption is reported in Malaysia, the Philippines, and Thailand. Indonesia experiences a unidirectional causal effect from economic growth to renewable energy consumption in both short and long run and from economic growth to CO2 emissions and energy consumption. Interestingly, only Myanmar has a unidirectional effect from GDP growth, energy consumption, and population to the adoption of renewable energy. Policy implications have emerged based on the findings achieved from this study for each country in the ASEAN region.

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 Driving Factor Analysis and Forecasting of CO2 Emissions from Power Output in China Using Scenario Analysis and CSCWOA-ELM Method

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2709 ◽  
Author(s):  
Weijun Wang ◽  
Weisong Peng ◽  
Jiaming Xu ◽  
Ran Zhang ◽  
Yaxuan Zhao
Keyword(s):  
Co2 Emissions ◽  
Influencing Factors ◽  
Power Output ◽  
Policy Implications ◽  
Emissions Reduction ◽  
Development Scenarios ◽  
Learning Machine ◽  
Set Up ◽  
Grey Relational ◽  
Average Contribution

With power consumption increasing in China, the CO2 emissions from electricity pose a serious threat to the environment. Therefore, it is of great significance to explore the influencing factors of power CO2 emissions, which is conducive to sustainable economic development. Taking the characteristics of power generation, transmission and consumption into consideration, the grey relational analysis method (GRA) is adopted to select 11 influencing factors, which are further converted into 5 main factors by hierarchical clustering analysis (HCA). According to the possible variation tendency of each factor, 48 development scenarios are set up from 2018–2025, and then an extreme learning machine optimized by whale algorithm based on chaotic sine cosine operator (CSCWOA-ELM) is established to predict the power CO2 emissions respectively. The results show that gross domestic product (GDP) has the greatest impact on the CO2 emissions from power output, of which the average contribution rate is 1.28%. Similarly, power structure and living consumption level also have an enormous influence, with average contribution rates over 0.6%. Eventually, the analysis made in this study can provide valuable policy implications for power CO2 emissions reduction, which can be regarded as a reference for China’s 14th Five-Year development plan in the future.

scholarly journals Analysis of China’s Carbon Emissions Base on Carbon Flow in Four Main Sectors: 2000–2013

2017 ◽  
Author(s):  
Xin Li ◽  
Xiandan Cui ◽  
Minxi Wang
Keyword(s):  
Co2 Emissions ◽  
Carbon Emissions ◽  
Carbon Flow ◽  
Emissions Reduction ◽  
Energy Structure ◽  
Low Carbon ◽  
Coal Consumption ◽  
Co2 Intensity ◽  
Secondary Industry ◽  
The Government

Reducing carbon emissions is a major ways to achieving green development and sustainability for China’s future. This paper elaborates the detailed feature of China's carbon flow for 2013 with the carbon flow chart and gives changing characteristics of China's CO2 flow from the viewpoint of sector and energy during 2000 and 2013. The results show that (1) during 2000 to 2013, China's CO2 emissions with the approximately growth portion of 9% annually, while the CO2 intensity of China diminishes at different rates. (2) The CO2 emissions from secondary industry are prominent from the perspective of four main sectors accounting for 83.5%. The manufacturing play an important part in the secondary industry with 45%. In which the "smelting and pressing of metal" takes up a large percentage as about 50% in manufacturing. (3) The CO2 emissions produced by coal consumption is keep dominant in energy-related emissions with a contribution of 65%, while it will decrease in the future. (4) From the aspect of sector, the CO2 emissions mainly come from the "electricity and heating" sector and the "smelting and pressing of metals" sub-sector. While it is essential and urgent to propose concrete recommendations for CO2 emissions mitigation. Firstly, the progression of creative technology is inevitable and undeniable. Secondly, the government should make different CO2 emissions reduction policies among different sectors. For example, the process emission plays an important role in "non-metallic mineral" while in "smelting and manufacturing of metals" it is energy. Thirdly, the country can change the energy structure and promote renewable energy for powering by wind or other low-carbon energy. Besides it, the coke oven gas can be a feasible substitution. Finally, policy maker should be aware of the emissions from residents have been growing in a fast rate. It is effective to involve the public in the activity of energy conservation and carbon emissions reduction such as reducing the times of personal transportation.

Decomposition analysis of energy-related CO2 emissions in South Africa

2015 ◽  
Vol 26 (1) ◽  
pp. 67-73 ◽  
Author(s):  
Ming Zhang ◽  
Shuang Dai ◽  
Yan Song
Keyword(s):  
South Africa ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Driving Forces ◽  
Dominant Role ◽  
Decomposition Analysis ◽  
Structure Effect ◽  
Energy Structure ◽  
Index Method ◽  
Intensity Effect

South Africa has become one of the most developing countries in the world, and its economic growth has occurred along with rising energy-related CO2 emission levels. A deeper understanding of the driving forces governing energy-related CO2 emissions is very important in formulating future policies. The LMDI (Log Mean Divisia Index) method is used to analyse the contribution of the factors which influence energy-related CO2 emissions in South Africa over the period 1993-2011. The main conclusions drawn from the present study may be summarized as follows: the energy intensity effect plays the dominant role in decreasing of CO2 emission, followed by fossil energy structure effect and renewable energy structure effect; the economic activity is a critical factor in the growth of energy-related CO2 emission in South Africa.

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