CO2 Emissions from China’s Power Industry: Scenarios and Policies for 13th Five-Year Plan

Sun, Wei; Meng, Ming; He, Youjun; Hong, Chang

doi:10.3390/en9100825

Cited by 20 publications

(12 citation statements)

References 23 publications

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“…A stream of literature follows the STIRPAT model in the estimations. For example, Sun et al [30] investigated the determinants of CO 2 emissions from the power sector of China. They found the two most important factors which may help in pollution reduction that are electricity production with low carbon technology and economic activities.…”

Section: Literature Reviewmentioning

confidence: 99%

Financial Market Development and Pollution Nexus in Saudi Arabia: Asymmetrical Analysis

Mahmood

Alrasheed

Furqan³

2018

Energies

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The study is aimed to scrutinize the presence of Environmental Kuznets Curve (EKC) hypothesis in Saudi Arabia by analyzing a period of 1971-2014. Asymmetrical impacts of Financial Market Development (FMD) and energy consumption per capita have also been tested on CO 2 emissions per capita. The estimates buoyed the long and short-run relationships in the hypothesized model, and EKC is found to be true in terms of the relationship between income and pollution. Asymmetrical effects of FMD in the long run and asymmetrical effects of energy consumption per capita in the long and short run are presented on the CO 2 emissions per capita. A decreasing FMD is found responsible for environmental degradation, and decreasing energy consumption per capita is found helpful in controlling CO 2 emissions. The tested effect of the financial crisis is found insignificant on CO 2 emissions.

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Section: Literature Reviewmentioning

confidence: 99%

Financial Market Development and Pollution Nexus in Saudi Arabia: Asymmetrical Analysis

Mahmood

Alrasheed

Furqan³

2018

Energies

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“…Drivers influencing CO 2 emissions are classified under four headings. The first is population, represented by total population or urbanization level in earlier literature, which are found to be the contributory drivers of CO 2 emissions [27][28][29][30][41][42][43][44]. The second is affluence, usually reflected by gross domestic product (GDP) per capita.…”

Section: Stirpat Modelmentioning

confidence: 99%

“…In terms of China's power generation industry, Zhang [27] identified the determinants of CO 2 emissions change of the power sector in Beijing-Tianjin-Hebei region, and showed that the production sector's electricity intensity remains a critical factor for achieving CO 2 emission reductions. Sun et al [28] used a scenario analysis approach to estimate the CO 2 emissions in China's power industry for diverse scenarios, and derived policy implications based on the extended STIRPAT model. Wen et al [29] explored drivers of CO 2 emissions in China's power sector based on ridge regression and proposed related policy measures.…”

Section: Introductionmentioning

confidence: 99%

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

Cui

Zhao

2018

Energies

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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.

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“…where A (1) and A (2) is the first and the second alternatives ranked by Q i . m is the number of evaluation alternatives…”

Section: Linguistic Variables Tfnsmentioning

confidence: 99%

Evaluating the Comprehensive Performance of Demand Response for Commercial Customers by Applying Combination Weighting Techniques and Fuzzy VIKOR Approach

Dong¹,

Huo²,

Liu³

et al. 2017

Sustainability

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Abstract:In order to guarantee the sustainability of power industries, demand response is widely developed in China with the improvement of power markets. Massive potential flexible resources in the commercial sector are valuable to carry out continuous demand response programs. This paper presented a hybrid framework to evaluate the performance of such programs. Considering that assessment processes involve multiple decisions for massive criteria under fuzzy conditions, we proposed a fuzzy multi-criteria decision making model to evaluate the performance of commercial demand response based on the concepts of a fuzzy Vlsekriterijumska Optimizacijia I Kompromisno Resenje method and a L2-metric distance. The weighting determination process in the model was modified by integrating subjective opinions and objective information according to a fuzzy Analytic Hierarchy Process and Criteria Importance Through Intercriteria Correlation methods. Then a comprehensive evaluation index system for demand response performance was established by using a fuzzy Delphi method based on experts' opinions, including the five aspects of economy, society, technology, environment and management. Finally, the practicality of the proposed hybrid framework was verified through an empirical analysis of five such programs in Chinese commercial buildings. Their comprehensive performances were ranked effectively. Sub-criteria affiliated with society and environment should be more attention than the other evaluation criteria based on experts' judgments and objective information. Moreover, a set of sensitivity analyses were performed to confirm the robustness and effectiveness of the proposed framework and the evaluation results. The study findings can offer references for the improvement of demand response and relevant policy formulation.

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CO2 Emissions from China’s Power Industry: Scenarios and Policies for 13th Five-Year Plan

Cited by 20 publications

References 23 publications

Financial Market Development and Pollution Nexus in Saudi Arabia: Asymmetrical Analysis

Financial Market Development and Pollution Nexus in Saudi Arabia: Asymmetrical Analysis

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

Evaluating the Comprehensive Performance of Demand Response for Commercial Customers by Applying Combination Weighting Techniques and Fuzzy VIKOR Approach

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