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PM2.5 emissions from different types of heavy-duty truck: a case study and meta-analysis of the Beijing-Tianjin-Hebei region

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Abstract

Beijing-Tianjin-Hebei (BTH) region in China is affected seriously by the hazy weather that has a large impact on human health. PM2.5 is one of the most important reasons for hazy weather. Understanding the PM2.5 emission characteristics from different types of heavy-duty trucks (HDTs) is valuable in policies and regulations to improve urban air quality and mitigate vehicle emission in China. The investigation and analysis on HDT population and PM2.5 emission in BTH region are carried out. The results show that the population and PM2.5 emission of HDTs in BTH has risen for the last four consecutive years, from 404 thousand and 1795 tons in 2012 to 551 thousand and 2303 tons in 2015. The PM2.5 emission from HDTs in Hebei is about 10 times more than that of Beijing and 9 times more than that of Tianjin. The proportion of natural gas HDTs is about 5%; however, its PM2.5 emission only accounts for 0.94% in 2015, which indicates the utilization of HDTs powered by natural gas facilitate PM2.5 mitigation more than diesel in BTH. The tractor and pickup trucks are the main source of PM2.5 emission from different types of HDT, while special and dump trucks are relatively clean. This study has provided insights for management method and policy-making of vehicle in terms of environmental demand.

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References

  • Askin AC, Barter GE, West TH, Manley DK (2015) The heavy-duty vehicle future in the United States: a parametric analysis of technology and policy tradeoffs. Energy Policy 81:1–13

    Article  Google Scholar 

  • Beevers SD, Westmoreland E, Jong MCD, Williams ML, Carslaw DC (2012) Trends in NOx and NO2 emissions from road traffic in Great Britain. Atmos Environ 54:107–116

    Article  CAS  Google Scholar 

  • Bishop GA, Hottor RR, Stedman DH (2015) On-road heavy-duty vehicle emissions monitoring system. Environ. Sci. Technol 49:1639–1645

    Article  CAS  Google Scholar 

  • Cai H, Xie SD (2007) Estimation of vehicular emission inventories in China from 1980 to 2005. Atmos Environ 41:8963–8979

    Article  CAS  Google Scholar 

  • Camuzeaux JR, Alvarez RA, Brooks SA, Browne JB, Sterner T (2015) Influence of methane emissions and vehicle efficiency on the climate implications of heavy-duty natural gas vehicles. Environ. Sci. Technol 49:6402–6410

    Article  CAS  Google Scholar 

  • Cao XY, Yao ZL, Shen XB, Ye Y, Jiang X (2016) On-road emission characteristics of VOCs from light-duty gasoline vehicles in Beijing, China. Atmos Environ 124:146–155

    Article  CAS  Google Scholar 

  • Chen CH et al (2007) On-road emission characteristics of heavy-duty diesel vehicles in Shanghai. Atmos Environ 41:5334–5344

    Article  CAS  Google Scholar 

  • Cheng SY, Lang JL, Zhou Y, Han LH, Wang G, Chen DS (2013) A new monitoring-simulation-source apportionment approach for investigating the vehicular emission contribution to the PM2.5 pollution in Beijing, China. Atmos Environ 79:308–316

    Article  CAS  Google Scholar 

  • Curran SJ, Wagner RM, Graves RL, Keller M, Green JB (2014) Well-to-wheel analysis of direct and indirect use of natural gas in passenger vehicles. Energy 75:194–203

    Article  Google Scholar 

  • Ehsan B, Vahid H (2016) Development of hot exhaust emission factors for Iranian-made euro-2 certified light-duty vehicles. Environ. Sci. Technol 50:279–284

    Article  Google Scholar 

  • Ekström M, Sjödin AK (2004) Evaluation of the COPERT III emission model with on road optical remote sensing measurements. Atmos Environ 38:6631–6641

    Article  Google Scholar 

  • Fan SB (2011) Tail-pipe emission characteristics from on-road vehicles in Beijing. Environmental Science and Management 36(4):28–31 (in Chinese)

    CAS  Google Scholar 

  • Fann N, Lamson AD, Anenberg SC, Wesson K, Risley D, Hubbell BJ (2012) Estimating the national public health burden associated with exposure to ambient PM2.5 and ozone. Risk Anal 32:81–95

    Article  Google Scholar 

  • Henschel SS et al (2015) Trends of nitrogen oxides in ambient air in nine European cities between 1999 and 2010. Atmos Environ 117:234–241

    Article  CAS  Google Scholar 

  • Huo H, Yao ZL, Zhang YZ, Shen XB, Zhang Q, He KB (2012) On-board measurements of emissions from diesel trucks in five cities in China. Atmos Environ 54:159–167

    Article  CAS  Google Scholar 

  • José MB, José M et al (2004) Estimation of road transportation emissions in Spain from 1988 to 1999 using COPERT III program. Atmos Environ 38:715–724

    Article  Google Scholar 

  • Khan M, Yasmin T (2014) Development of natural gas as a vehicular fuel in Pakistan: issues and prospects. Journal of Natural Gas Science and Engineering 17:99–109

    Article  Google Scholar 

  • Li J, Li YY, Wang QY (2014) Total amount characteristics of regional vehicular emissions and pollutant reduction allocation. China Population Resources and Environment 24(8):141–148 (in Chinese with English abstract)

    Google Scholar 

  • Liang JL, Cheng SY, Wei W, Zhou Y, Wei X, Chen DS (2012) A study on the trends of vehicular emissions in the Beijing-Tianjin-Hebei (BTH) region, China. Atmos Environ 62:605–614

    Article  Google Scholar 

  • Liang JL, Cheng SY, Zhou Y, Zhang YL, Wang G (2014) Air pollutant emissions from on-road vehicles in China, 1999–2011. Sci Total Environ 496:1–10

    Article  Google Scholar 

  • Lv BL, Zhang B, Bai YQ (2016) A systematic analysis of PM2.5 in Beijing and its sources from 2000 to 2012. Atmos Environ 124:98–108

    Article  CAS  Google Scholar 

  • Ministry of Environmental Protection of China. China vehicle emission control annual report 2010. Available at http://www.vecc-mep.org.cn/index/20101110nianbao.pdf, 2010. (accessed April 2011).

  • Nesamani KS (2010) Estimation of automobile emissions and control strategies in India. Sci Total Environ 408:1800–1811

    Article  CAS  Google Scholar 

  • Pramila G, Dhirendra M, Anikender K (2013) Vehicular emission inventory of criteria pollutants in Delhi. SpringerPlus 2:216

    Article  Google Scholar 

  • Puttipong C, Panida T, Kamphol P, Pornphimol W, Bundit L (2015) Low carbon transportation in Thailand: CO2 mitigtion strategy in 2050. Chunark et al. SpringerPlus 4:618. doi:10.1186/s40064-015-1388-6

    Article  Google Scholar 

  • Querol X et al (2014) 2001–2012 trends on air quality in Spain. Sci Total Environ 490:957–969

    Article  CAS  Google Scholar 

  • Shen W, Han WJ, Wallington TJ (2014a) Current and future greenhouse gas emissions associated with electricity generation in China: implications for electric vehicles. Environ Sci Technol 48:7069–7075

    Article  CAS  Google Scholar 

  • Shen XB, Yao ZL, Huo H, He KB, Zhang YZ, Liu H, Ye Y (2014b) PM2.5 emissions from light-duty gasoline vehicles in Beijing, China. Sci Total Environ 487:521–527

    Article  CAS  Google Scholar 

  • Sun SD, Jiang W, Gao WD (2016) Vehicle emission trends and spatial distribution in Shandong province, China, from 2000 to 2014. Atmos Environ 147:190–199

    Article  CAS  Google Scholar 

  • Tamayao MAM, Michalek JJ, Hendrickson C, Azevedo IML (2015) Regional variability and uncertainty of electric vehicle life cycle CO2 emissions across the United States. Environ Sci Technol 49:8844–8855

    Article  CAS  Google Scholar 

  • Wang H, Chen C, Huang C, Fu L (2008) On-road vehicle emission inventory and its uncertainty analysis for Shanghai, China. Sci Total Environ 398:60–67

    Article  CAS  Google Scholar 

  • Wang HK, Fu LX, Zhou Y, Du X, Ge WH (2010) Trends in vehicular emissions in China’s mega cities from 1995 to 2005. Environ Pollut 158:394–400

    Article  CAS  Google Scholar 

  • Wen W, Cheng SY, Chen XF, Wang G, Li S, Wang XQ, Liu XY (2016) Impact of emission control on PM2.5 and the chemical composition change in Beijing-Tianjin-Hebei during the APEC summit 2014. Environ Sci Pollut Res 23:4509–4521

    Article  CAS  Google Scholar 

  • Wu BB, Shen XB, Cao XY, Zhang W, Wu H, Yao ZL (2015a) Carbonaceous composition of PM2.5 emitted from on-road China III diesel trucks in Beijing, China. Atmos Environ 116:216–224

    Article  CAS  Google Scholar 

  • Wu XM, Zhang SJ, Wu Y, Li ZH, Zhou Y, Fu LX, Hao JM (2015b) Real-world emissions and fuel consumption of diesel buses and trucks in Macao: from on-road measurement to policy implications. Atmos Environ 120:393–403

    Article  CAS  Google Scholar 

  • Wu RR, Bo Y, Li J, Li LY, Li YQ, Xie SD (2016) Method to establish the emission inventory of anthropogenic volatile organic compounds in China and its application in the period 2008–2012. Atmos Environ 127:244–254

    Article  CAS  Google Scholar 

  • Xing Y et al (2016) The characteristics of greenhouse gas emissions from heavy-duty trucks in the Beijing-Tianjin-Hebei (BTH) region in China. Atmosphere 7(9):121

    Article  Google Scholar 

  • Yan F et al (2011) Global emission projections of particulate matter (PM): I. Exhaust emissions from on-road vehicles. Atmos Environ 45:4830–4844

    Article  CAS  Google Scholar 

  • Zhang SJ et al (2014) Historic and future trends of vehicle emissions in Beijing, 1998–2020: a policy assessment for the most stringent vehicle emission control program in China. Atmos Environ 89:216–229

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the National Nature Science Foundation of China under Grant 51404024 for financial support.

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Authors and Affiliations

  1. Dongling School of Economics and Management, University of Science and Technology Beijing, Beijing, China

    Liying Song & Xiaoxia Huang

  2. School of Civil and Environmental Engineering, University of Science and Technology Beijing, Beijing, China

    Hongqing Song, Jingyi Lin & Mingxu Yu

  3. China Automotive Technology and Research Center Beijing Operations, Beijing, China

    Cheng Wang, Yu Guan & Xing Wang

  4. The International Council on Clean Transportation, Washington, D.C., USA

    Li Du

Authors
  1. Liying Song
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  2. Hongqing Song
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  3. Jingyi Lin
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  4. Cheng Wang
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  5. Mingxu Yu
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  6. Xiaoxia Huang
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  7. Yu Guan
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  8. Xing Wang
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  9. Li Du
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Correspondence to Hongqing Song.

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Responsible editor: Philippe Garrigues

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Song, L., Song, H., Lin, J. et al. PM2.5 emissions from different types of heavy-duty truck: a case study and meta-analysis of the Beijing-Tianjin-Hebei region. Environ Sci Pollut Res 24, 11206–11214 (2017). https://doi.org/10.1007/s11356-017-8755-5

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  • DOI: https://doi.org/10.1007/s11356-017-8755-5

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