Historic and future trends of vehicle emissions in Beijing, 1998–2020: A policy assessment for the most stringent vehicle emission control program in China

Zhang, Shaojun; Wu, Ye; Li, Mengliang; Ge, Yunshan; Bin, Liang; Xu, Yueyun; Zhou, Yu; Liu, Huan; Fu, Lixin; Hao, Jiming

doi:10.1016/j.atmosenv.2013.12.002

Cited by 167 publications

(85 citation statements)

References 38 publications

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“…Results from the three parts were summed to yield the total provincial emission amounts in 2015. Emission factors for VOCs used were derived from lab tests, field tests and literature review (MEP, 2015;Zhang et al, 2014;Liu et al, 2015). The IVOC emission calculation was similar to that of the VOCs, while only the tailpipe exhaust for non-GMs was taken into consideration.…”

Section: Vehicular Emission Data and Estimationmentioning

confidence: 99%

An updated emission inventory of vehicular VOCs and IVOCs in China

et al. 2017

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Abstract. Currently, the emission inventory of vehicular volatile organic compounds (VOCs) is one of those with the largest errors and uncertainties due to suboptimal estimation methods and the lack of first-hand basic data. In this study, an updated speciated emission inventory of VOCs and an estimation of intermediate-volatility organic compounds (IVOCs) from vehicles in China at the provincial level for the year of 2015 are developed based on a set of state-of-the-art methods and an abundance of local measurement data. Activity data for light-duty vehicles are derived from trajectories of more than 70 000 cars for 1 year. The annual mileage of trucks are calculated from reported data by more than 2 million trucks in China. The emission profiles are updated using measurement data. Vehicular tailpipe emissions (VTEs) and four types of vehicular evaporation emissions (VEEs), including refueling, hot soak, diurnal and running loss, are taken into account. Results show that the total vehicular VOC emissions in China are 4.21 Tg (with a 95 % confidence interval range from 2.90 to 6.54 Tg) and the IVOC emissions are 200.37 Gg in 2015. VTEs are still the predominant contributor, while VEEs are responsible for 39.20 % of VOC emissions. The control of VEEs is yet to be optimized in China. Among VTEs, passenger vehicles emissions have the largest share (49.86 %), followed by trucks (28.15 %) and motorcycles (21.99 %). Among VEEs, running loss is the largest contributor (81.05 %). For both VTEs and VEEs, Guangdong, Shandong and Jiangsu province are three of the highest, with a respective contribution of 10.66, 8.85 and 6.54 % to the total amounts of VOCs from vehicles. 97 VOC species are analyzed in this VOC emission inventory. i-Pentane, toluene and formaldehyde are found to be the most abundant species in China's vehicular VOC emissions. The estimated IVOCs are another "inconvenient truth", concluding that precursor emissions for secondary organic aerosol (SOA) from vehicles are much larger than previously estimated.

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Section: Vehicular Emission Data and Estimationmentioning

confidence: 99%

An updated emission inventory of vehicular VOCs and IVOCs in China

et al. 2017

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“…China implemented China-IV (Chinese emission standards in the fourth phase) for light-duty vehicles in 2011 and for heavy-duty trucks in 2013 [35]. According to this developmental trend, this study assumes that China will implement China-V in 2017 and implement China-VI (which is equivalent to Euro-VI) in 2020.…”

Section: Auto Emission Standardsmentioning

confidence: 99%

“…In the paper, we have set the parameters of the above scenarios based on considerations of previous results and Chinese medium-and long-term planning [26,[32][33][34][35][36][37][38][39][40][41][42][43][44][45]. The parameters of the above scenarios are shown in Table 2.…”

Section: Alternative Fuelsmentioning

confidence: 99%

Inventory and Policy Reduction Potential of Greenhouse Gas and Pollutant Emissions of Road Transportation Industry in China

Bao

et al. 2016

Sustainability

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Abstract: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 CO 2 and emitted 1420 thousand tons of CO, 2150 thousand tons of NO x , 148 thousand tons of PM 10 , 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 CO 2 from 2012 to 2030. In terms of air pollutant emission mitigation, the auto emission standards measure performs best with respect to NO x , PM 10 , 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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“…They vary in several factors such as the vehicle type under study, urban structure, testing conditions and technologies, and the time of study, which correspond to the emission standards in place. Focusing on vehicle emissions, number of vehicles and emission standards, some studies also provide future trends of on-road vehicle emissions in China (Hao, Liu, Zhao, Li, & Hang, 2015;Wang, Fu, & Bi, 2011;Wu et al, 2017;Zhang, Wu, Wu et al, 2014).…”

mentioning

confidence: 99%

“…In response, the national government implemented stringent vehicle emission standards. Several studies have focused on evaluation of the emission factors of various vehicle types in Chinese cities over the past decade Huo et al, 2012;Liu, He, Lents, Wang, & Tolvett, 2009;Wang, Westerdahl, Wu, Pan, & Zhang, 2011;Wang et al, 2012;Wu et al, 2012;Zhang, Wu, Liu et al, 2014;Zhang, Wu, Wu et al, 2014;Zheng et al, 2015;Zhou, Wu, Zhang, Fu, & Hao, 2014). They vary in several factors such as the vehicle type under study, urban structure, testing conditions and technologies, and the time of study, which correspond to the emission standards in place.…”

mentioning

confidence: 99%

Investigating the Potential of Ridesharing to Reduce Vehicle Emissions

Jalali

Koohi-Fayegh

El-Khatib

et al. 2017

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As urban populations grow, cities need new strategies to maintain a good standard of living while enhancing services and infrastructure development. A key area for improving city operations and spatial layout is the transportation of people and goods. While conventional transportation systems (i.e., fossil fuel based) are struggling to serve mobility needs for growing populations, they also represent serious environmental threats. Alternative-fuel vehicles can reduce emissions that contribute to local air pollution and greenhouse gases as mobility needs grow. However, even if alternative-powered vehicles were widely employed, road congestion would still increase. This paper investigates ridesharing as a mobility option to reduce emissions (carbon, particulates and ozone) while accommodating growing transportation needs and reducing overall congestion. The potential of ridesharing to reduce carbon emissions from personal vehicles in Changsha, China, is examined by reviewing mobility patterns of approximately 8,900 privately-owned vehicles over two months. Big data analytics identify ridesharing potential among these drivers by grouping vehicles by their trajectory similarity. The approach includes five steps: data preprocessing, trip recognition, feature vector creation, similarity measurement and clustering. Potential reductions in vehicle emissions through ridesharing among a specific group of drivers are calculated and discussed. While the quantitative results of this analysis are specific to the population of Changsha, they provide useful insights for the potential of ridesharing to reduce vehicle emissions and the congestion expected to grow with mobility needs. Within the study area, ridesharing has the potential to reduce total kilometers driven by about 24% assuming a maximum distance between trips less than 10 kilometers, and schedule time less than 60 minutes. For a more conservative maximum trip distance of 2 kilometers and passenger schedule time of less than 40 minutes, the reductions in traveled kilometers could translate to the equivalent of approximately 4.0 tons CO 2 emission reductions daily.

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Historic and future trends of vehicle emissions in Beijing, 1998–2020: A policy assessment for the most stringent vehicle emission control program in China

Cited by 167 publications

References 38 publications

An updated emission inventory of vehicular VOCs and IVOCs in China

An updated emission inventory of vehicular VOCs and IVOCs in China

Inventory and Policy Reduction Potential of Greenhouse Gas and Pollutant Emissions of Road Transportation Industry in China

Investigating the Potential of Ridesharing to Reduce Vehicle Emissions

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