Skip to main content

Advertisement

Log in

Emission inventory estimation of an intercity bus terminal

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Intercity bus terminals are hotspots of air pollution due to concentrated activities of diesel buses. In order to evaluate the bus terminals’ impact on air quality, it is necessary to estimate the associated mobile emission inventories. Since the vehicles’ operating condition at the bus terminal varies significantly, conventional calculation of the emissions based on average emission factors suffers the loss of accuracy. In this study, we examined a typical intercity bus terminal—the Southern City Bus Station of Xi’an, China—using a multi-scale emission model—(US EPA’s MOVES model)—to quantity the vehicle emission inventory. A representative operating cycle for buses within the station is constructed. The emission inventory was then estimated using detailed inputs including vehicle ages, operating speeds, operating schedules, and operating mode distribution, as well as meteorological data (temperature and humidity). Five functional areas (bus yard, platforms, disembarking area, bus travel routes within the station, and bus entrance/exit routes) at the terminal were identified, and the bus operation cycle was established using the micro-trip cycle construction method. Results of our case study showed that switching to compressed natural gas (CNG) from diesel fuel could reduce PM2.5 and CO emissions by 85.64 and 6.21 %, respectively, in the microenvironment of the bus terminal. When CNG is used, tail pipe exhaust PM2.5 emission is significantly reduced, even less than brake wear PM2.5. The estimated bus operating cycles can also offer researchers and policy makers important information for emission evaluation in the planning and design of any typical intercity bus terminals of a similar scale.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Alam, A., & Hatzopoulou, M. (2014). Reducing transit bus emissions: alternative fuels or traffic operations? Atmospheric Environment, 89, 129–139.

    Article  CAS  Google Scholar 

  • Andre, M. (2004). The ARTEMIS European driving cycles for measuring car pollutant emissions. Science of the Total Environment, 73, 334–335.

    Google Scholar 

  • Beardsley, M. (2004). MOVES fleet and activity inputs: 1999 base year. Presented at the CRC On-road Emissions Workshop, San Diego, California.

  • Cheng, Y. H., Chang, H. P., & Hsieh, C. J. (2011). Short-term exposure to PM10, PM2.5, ultrafine particles and CO2 for passengers at an intercity bus terminal. Atmospheric Environment, 45, 2034–2042.

    Article  CAS  Google Scholar 

  • Corfa, E., Maury, F., Segers, P., Fresneau, A., & Albergel, A. (2004). Short-range evaluation of air pollution near bus and railway stations. Science of the Total Environment, 334-335, 223–230.

    Article  CAS  Google Scholar 

  • Hung, W. T., Tam, K. M., Lee, C. P., Chan, L. Y., & Cheung, C. S. (2005). Comparison of driving characteristics in cities of Pearl River Delta, China. Atmospheric Environment, 39, 615–625.

    Article  CAS  Google Scholar 

  • Goyal, P., & Sidhartha (2003). Present scenario of air quality in Delhi: a case study of CNG implementation. Atmospheric Environment, 37, 5423–5431.

    Article  Google Scholar 

  • Kuo, C. Y., Chien, P. S., Kuo, W. C., Wei, C. T., & Rau, J. Y. (2013). Comparison of polycyclic aromatic hydrocarbon emissions on gasoline- and diesel-dominated routes. Environmental Monitoring and Assessment, 185, 5749–5761.

    Article  CAS  Google Scholar 

  • Lin, J., & Niemeier, D. (2003). Estimating regional air quality vehicle emission inventories: constructing robust driving cycles. Transportation Science, 37, 330–346.

    Article  Google Scholar 

  • Liu, H. B., Chen, X. H., Wang, Y. Q., & Han, S. (2013). Vehicle emission and near-road air quality modeling in Shanghai, China, based on taxi GPS data and MOVES revised emission inventory. Transportation Research Record: Journal of the Transportation Research Board, 2340, 38–48.

    Article  Google Scholar 

  • Qiu, Z. W., Li, X. X., Hao, Y. Z., Deng, S. X. (2016). Potential of diesel emissions reduction strategies in Xi’an, China. Clean Technologies and Environmental Policy, 11 April 2016 (First online).

  • Sandhu, G. S., Frey, H. C., Bartelt-Hunt, S., & Jones, E. (2014). In-use measurement of the activity, fuel use, and emissions of front-load refuse trucks. Atmospheric Environment, 92, 557–565.

    Article  CAS  Google Scholar 

  • Silverman, D. T., Samanic, C. M., Lubin, J. H., Blair, A. E., Stewart, P. A., Vermeulen, R., et al. (2012). The diesel exhaust in miners study: a nested case-control study of lung cancer and diesel exhaust. Journal of the National Cancer Institute, 104, 855–868.

    Article  CAS  Google Scholar 

  • Smit, R., Ntziachristos, L., & Boulter, P. (2010). Validation of road vehicle and traffic emission models—a review and meta-analysis. Atmospheric Environment, 44, 2943–2953.

    Article  CAS  Google Scholar 

  • Suresh, P., Sharad, G., & Aloke, K. G. (2009). Evaluating effects of traffic and vehicle characteristics on vehicular emissions near traffic intersections. Transportation Research Part D, 14, 180–196.

    Article  Google Scholar 

  • US EPA. (US Environmental Protection Agency) (2012). Motor vehicle emission simulator (MOVES) user guide for MOVES2010b. Report EPA-420-B-12-001b. Office of Transportation and Air Quality.

  • Vallamsundar, S., & Lin, J. (2012). MOVES and AERMOD used for PM2.5 conformity hot spot air quality modeling. Transportation Research Record: Journal of the Transportation Research Board, 2270, 39–48.

    Article  Google Scholar 

  • Wang, X., & Gao, H. O. (2011). Exposure to fine particle mass and number concentrations in urban transportation environments of New York City. Transportation Research Part D, 16, 384–391.

    Article  Google Scholar 

  • Wang, L., Jayaratne, E. R., Morawska, L., Heuff, D., & Mengersen, K. (2010). Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station. Atmospheric Environment, 44, 3269–3277.

    Article  CAS  Google Scholar 

  • Wang, L., Morawska, L., Jayaratne, E. R., Mengersen, K., & Heuff, D. (2011). Characteristics of airborne particles and the factors affecting them at bus stations. Atmospheric Environment, 45, 611–620.

    Article  CAS  Google Scholar 

  • Wang, X., Yin, H., Ge, Y., Yu, L., Xu, Z., Yu, C., et al. (2013). On-vehicle emission measurement of a light-duty diesel van at various speeds at high altitude. Atmospheric Environment, 81, 263–269.

    Article  CAS  Google Scholar 

  • Xie, Y., Chowdhury, M., Bhavsar, P., & Zhou, Y. (2012). An integrated modeling approach for facilitating emission estimations of alternative fueled vehicles. Transportation Research Part D, 17, 15–20.

    Article  Google Scholar 

  • Yao, Z., Wei, H., Perugu, H., Liu, H., & Li, Z. (2014). Sensitivity analysis of project level MOVES running emission rates for light and heavy duty vehicles. Journal of Traffic and Transportation Engineering (English Edition), 1, 81–96.

    Article  Google Scholar 

Download references

Acknowledgments

This study was supported by the Fundamental Research Funds for the Central Universities (No. 310822152006, 310822151024), National Natural Science Foundation of China under Projects #51478045, Science and Technology Project of Ministry of Housing and Urban-rural Development of the People’s Republic of China (No. 2016-K2-032), and Innovation Project of Science and Technology in Shaanxi Province, China (No. 2012KTZB03-01-04). Author H. Oliver Gao acknowledges partial support from the National Natural Science Foundation of China under Projects #71428001.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhaowen Qiu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qiu, Z., Li, X., Hao, Y. et al. Emission inventory estimation of an intercity bus terminal. Environ Monit Assess 188, 367 (2016). https://doi.org/10.1007/s10661-016-5370-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-016-5370-8

Keywords

Navigation