2015
DOI: 10.1016/j.apenergy.2015.01.018
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Reducing China’s road transport sector CO2 emissions to 2050: Technologies, costs and decomposition analysis

Abstract: 1 This model is based in Microsoft Excel and does not contain any macros or specific visual basic code. *Manuscript Click here to download Manuscript: China transport paper 10th December 2014.docx Click here to view linked References

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Cited by 148 publications
(54 citation statements)
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“…A major determinant will be the size and composition of China's vehicle stock. However, projections of the future vehicle stock vary enormously as there are so many relevant supply and demand side variables; the sector will be the subject of both disruptive technological innovation and strong policy intervention over the coming decade and beyond, making forecasting difficult (see Gambhir et al, 2015). China has targeted an expansion of its share of gas in PEC to 10% by 2020 (State Council, 2014), which looks feasible (see Green and Stern 2015, p. 37).…”
Section: Energy Supplymentioning
confidence: 99%
“…A major determinant will be the size and composition of China's vehicle stock. However, projections of the future vehicle stock vary enormously as there are so many relevant supply and demand side variables; the sector will be the subject of both disruptive technological innovation and strong policy intervention over the coming decade and beyond, making forecasting difficult (see Gambhir et al, 2015). China has targeted an expansion of its share of gas in PEC to 10% by 2020 (State Council, 2014), which looks feasible (see Green and Stern 2015, p. 37).…”
Section: Energy Supplymentioning
confidence: 99%
“…FCV from a number of previous investigations [17]- [19]. The total emission in this study was calculated based on the estimated fuel demand [19], [20] as well as total mileage by the add-on module for exhaust and non-exhaust emissions [21]. Although the total mileage between COPERT outputs and the add-on module remained the same, the fuel demand varied due to changes in vehicle technologies in different scenarios.…”
Section: Methodological Frameworkmentioning
confidence: 99%
“…The addon module estimated energy consumption for a wide range of PC categories using fuel efficacy uplift multipliers for alternative PC technologies e.g. FCV from a number of previous investigations [17]- [19]. The total emission in this study was calculated based on the estimated fuel demand [19], [20] as well as total mileage by the add-on module for exhaust and non-exhaust emissions [21].…”
Section: Methodological Frameworkmentioning
confidence: 99%
“…The technological details relevant to efficiency improvement and vehicle technologies are considered with various degrees of technology categories, along with the suitability of the county such as infrastructure and economy condition. In this study, the share constraints of mitigation actions in the CMs scenario is designed and analysed in both countries, which considered technologies have been obtained from [5] , [16], [17] and [18]. The average GDP growth rate during 2010-2030 is 4.11% and 5.92% for Thailand and Laos respectively, and during 2031-2050 is 2.70% and 4.30%.…”
Section: Transport Demand Modellingmentioning
confidence: 99%