Emissions reduction potential analysis of road transportation
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Abstract:
At the 2009 United Nations Climate Change Conference in Copenhagen,China announced its target of CO2 emission reduction,that is,by 2020 the amount of CO2 emission per output unit will drop by 40% ~45% compared to that in 2005.The target will be incorporated into China’s long term socio-economic planning.Globally,the transport sector is the largest source of CO2 emissions.Exploring road transportation energy consumption and the abatement opportunities for road transportation is of great significance for low-carbon economy research,and also for the emission reduction target.Based on the existing literature and research,in this article,we outline four major potential ways of emissions reduction on road transportation,which are:(1) give priority to the development of public transportation;(2) give priority to the development of small output volume automobiles;(3) reduce the automobile energy consumption per kilometer;(4) strictly control the automobile pollutant emission standard.With these four potential ways,the article uses the emission calculation model and scenario analysis method to estimate the reduction potential of road transportation carbon emission in 2015 and 2020.Calculation results show that: under low,middle and high scenarios,China will reduce the CO2emission by 21.83,18.91 and 18.81 million tons in 2015 respectively.Up to 2020,the emission amount will achieve 71.48,55.45,and 40.55 million tons respectively.Lastly,according to the development reality of China,the paper puts forward the corresponding policy recommendations in relation to emission reduction of road transportation on the basis of the above findings.Keywords:
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In recent years, emissions from the road transportation industry in China have been increasing rapidly. To evaluate the reduction potential of greenhouse gas and pollutant emissions of the industry in China, its emission inventory was calculated and scenario analysis was created for the period between 2012 and 2030 in this paper. Based on the Long-range Energy Alternatives Planning System (LEAP) model, the development of China’s road transportation industry in two scenarios (the business-as-usual (BAU) scenario and the comprehensive-mitigation (CM) scenario) was simulated. In the Comprehensive Mitigation scenario, there are nine various measures which include Fuel Economy Standards, Auto Emission Standards, Energy-saving Technology, Tax Policy, Eco-driving, Logistics Informatization, Vehicle Liquidation, Electric Vehicles, and Alternative Fuels. The cumulative energy and emission reductions of these specific measures were evaluated. Our results demonstrate that China’s road transportation produced 881 million metric tons of CO2 and emitted 1420 thousand tons of CO, 2150 thousand tons of NOx, 148 thousand tons of PM10, and 745 thousand tons of HC in 2012. The reduction potential is quite large, and road freight transportation is the key mitigation subsector, accounting for 85%–92% of the total emission. For energy conservation and carbon emission mitigation, logistics informatization is the most effective method, potentially reducing 1.80 billion tons of coal equivalent and 3.83 billion tons of CO2 from 2012 to 2030. In terms of air pollutant emission mitigation, the auto emission standards measure performs best with respect to NOx, PM10, and HC emission mitigation, and logistic informatization measure is the best in CO emission reduction. In order to maximize the mitigation potential of China’s road transportation industry, the government needs to implement various measures in a timely and strict fashion.
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Abstract The annual growth rate of CO 2 emissions from China's transportation sector exceeded the growth rate of emissions from the whole society, making transportation the third‐largest CO 2 emissions sector after the industrial and household consumption sectors in China. This paper is intended to project CO 2 emissions in China's transportation sector from 2010 to 2020 and to assess the effectiveness of possible reduction measures. A detailed bottom‐up model has been developed and four scenarios have been designed to describe the future development of the sector. The results indicate that under the business as usual (BAU) scenario, emissions would increase by 58%, reaching 1.38 billion tCO 2 by 2020. Reduction potentials ranged from 96 to 515 million tCO 2 under different scenarios. Road transportation alone accounted for more than 80% of total emissions on average, making it a key target for CO 2 mitigation actions. Application of conventional transportation technology, together with accelerating the development of new‐energy technologies, was the most effective and contributed to more than 70% of reductions. These measures combined with traffic mode shifts in consumption patterns will lead to the sustainable and effective development of China's transportation sector. In addition, to avoid a rebound in transport fuel demand, policies combination is suggested. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd.
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The increasing vehicle usage has brought about a sharp increase in greenhouse gas (GHG) emissions of vehicles, which brings severe challenges to the sustainable development of road transportation in Chinese counties. Low-carbon transportation planning is an essential strategy for carbon control from the source of carbon emissions and is crucial to the full transition to a low-carbon future. For transportation planning designers, a quick and accurate estimation of carbon emissions under different transportation planning schemes is a prerequisite to determine the optimal low-carbon transportation development plan. To address this issue, a novel prediction method of hourly GHG emissions over the urban roads network was constructed in this paper. A case study was conducted in Changxing county, and the results indicate the effectiveness of our proposed method. Furthermore, we applied the same approach to 30 other counties in China to analyze the influencing factors of emissions from urban road networks in Chinese counties. The analysis results indicate that the urban road mileage and arterial road ratio are the two most important factors affecting road network GHG emissions in road traffic planning process. Moreover, the method was employed to derive peak hour emission coefficients that can be used to quickly estimate daily or annual GHG emissions. The peak hour emission of CO2, CH4, and N2O accounts for approximately 9–10%, 8.5–10.5%, 5.5–7.5% of daily emissions, respectively. It is expected that the findings from this study would be helpful for establishing effective carbon control strategies in the transportation planning stage to reduce road traffic GHG emissions in counties.
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