CO2 emissions from China’s power sector at the provincial level: Consumption versus production perspectives

Lindner, Steve; Liu, Zhu; Guan, Dabo; Geng, Yong; Li, Xin

doi:10.1016/j.rser.2012.10.050

Cited by 124 publications

(49 citation statements)

References 37 publications

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“…Stricter regulations of the Beijing power sector will tend to increase the import of electricity if similar actions are not taken in Inner Mongolia. Given this connection, the most cost-effective means of reducing emissions from the Inner Mongolia power sector might not only be deploying new generation technologies there but also energy conservation in Beijing, as well as facilitating technological cooperation between the two regions Lindner et al, 2013). In this regard, effective and cost-effective management of air quality may therefore require policies that cover the entire supply chain, which in turn will depend upon quantitative understanding of emission transport between producers and consumers.…”

Section: H Y Zhao Et Al: Assessment Of China's Virtual Air Pollutimentioning

confidence: 99%

Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory

et al. 2015

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Abstract. Substantial anthropogenic emissions from China have resulted in serious air pollution, and this has generated considerable academic and public concern. The physical transport of air pollutants in the atmosphere has been extensively investigated; however, understanding the mechanisms how the pollutant was transferred through economic and trade activities remains a challenge. For the first time, we quantified and tracked China's air pollutant emission flows embodied in interprovincial trade, using a multiregional input-output model framework. Trade relative emissions for four key air pollutants (primary fine particle matter, sulfur dioxide, nitrogen oxides and non-methane volatile organic compounds) were assessed for 2007 in each Chinese province. We found that emissions were significantly redistributed among provinces owing to interprovincial trade. Large amounts of emissions were embodied in the imports of eastern regions from northern and central regions, and these were determined by differences in regional economic status and environmental policy. It is suggested that measures should be introduced to reduce air pollution by integrating cross-regional consumers and producers within national agreements to encourage efficiency improvement in the supply chain and optimize consumption structure internationally. The consumption-based air pollutant emission inventory developed in this work can be further used to attribute pollution to various economic activities and final demand types with the aid of air quality models.

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Section: H Y Zhao Et Al: Assessment Of China's Virtual Air Pollutimentioning

confidence: 99%

Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory

et al. 2015

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show abstract

“…It means that the regression model is not suitable to capture the fluctuation increasing trend without constant growth rate in our work. The forecasting performance of GM (1,1) for all sample data is better than the regression model since the errors of the GM (1, 1) model are lower; and it shows better performance for the training data than the testing data. The errors of BP are almost the highest, which indicates this model is the worst one, except for the regression model.…”

Section: Overall Accuracy Comparison For All Sample Datamentioning

confidence: 96%

“…LSSVM maps the input vector i x to a higher dimensional feature space, using a nonlinear kernel function   φ  , shown as Equation (1). Through Equation (1), the nonlinear estimation in original space can be transformed into linear function estimation in feature space:…”

Section: Least Squares Support Vector Machine (Lssvm)mentioning

confidence: 99%

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Forecasting Fossil Fuel Energy Consumption for Power Generation Using QHSA-Based LSSVM Model

Sun

Hong

2015

Energies

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Accurate forecasting of fossil fuel energy consumption for power generation is important and fundamental for rational power energy planning in the electricity industry. The least squares support vector machine (LSSVM) is a powerful methodology for solving nonlinear forecasting issues with small samples. The key point is how to determine the appropriate parameters which have great effect on the performance of LSSVM model. In this paper, a novel hybrid quantum harmony search algorithm-based LSSVM (QHSA-LSSVM) energy forecasting model is proposed. The QHSA which combines the quantum computation theory and harmony search algorithm is applied to searching the optimal values of σ and C in LSSVM model to enhance the learning and generalization ability. The case study on annual fossil fuel energy consumption for power generation in China shows that the proposed model outperforms other four comparative models, namely regression, grey model (1, 1) (GM (1, 1)), back propagation (BP) and LSSVM, in terms of prediction accuracy and forecasting risk.

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“…Das Input-Output-Modell ermöglicht außerdem nicht nur die direkten, in Österreich anfallenden CO 2 -Emissionen abzuschätzen, sondern auch -soweit die schwierig zu erhaltende Kohlenstoffintensität der Importe nach Herkunftsland bekannt ist -entlang der gesamten Wertschöpfungskette (dem Lebenszyklus der Produkte und Dienstleistungen folgend), jene indirekten "grauen", durch Konsum von aus dem Ausland importierten Vorleistungen und Produkten induzierten Emissionen annähernd zu quantifizieren. Dabei kann man jedoch eine Einheit "importierter" Emissionen (also: eingebettet in eingeführte Güter) nicht einfach mit einem Ausstoß einer Einheit von Emissionen in die Atmosphäre gleichsetzen (Peters und Hertwich, 2008;Lindner et al, 2013;Jakob et al, 2014;Steininger et al, 2014). .…”

Section: Einleitung Introductionunclassified

Kapitel 6: Transformationspfade

Stagl¹,

Schulz²,

Köppl³

et al. 2014

Österreichischer Sachstandsbericht Klimawandel 2014

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CO2 emissions from China’s power sector at the provincial level: Consumption versus production perspectives

Cited by 124 publications

References 37 publications

Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory

Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory

Forecasting Fossil Fuel Energy Consumption for Power Generation Using QHSA-Based LSSVM Model

Kapitel 6: Transformationspfade

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