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Marginal Effects and Spatial Variations of the Impact of the Built Environment on Taxis’ Pollutant Emissions in Chengdu, China

Author

Listed:
  • Guanwei Zhao

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

  • Zeyu Pan

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

  • Muzhuang Yang

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

Abstract

Understanding the impact of the urban built environment on taxis’ emissions is crucial for sustainable transportation. However, the marginal effects and spatial heterogeneity of this impact is worth noting. To this end, we calculated the taxis’ emissions on weekdays and weekends in Chengdu, China, and investigated the impact of the built environment on taxis’ emissions by applying multi-source data and several spatial regression models. The results showed that the taxis’ daily emissions on weekdays were higher than the emissions on weekends. The time heterogeneity of hourly taxis’ emissions was not significant, while the spatial heterogeneity of taxis’ emissions was significant. Except the HHI, the selected built environment variables both had a significant positive effect on taxis’ emissions on the global scale. There was a marginal effect of some built environment variables on taxis’ emissions, such as the density of bus stops and population density. The former exhibited an inhibitory effect on taxis’ emissions only when it was greater than 9 stops/km 2 , while the latter showed an inhibitory effect only in the range between 16,000 people/km 2 and 22,000 people/km 2 . There were some spatial variations in the effects of built environment factors on taxis’ emissions, with HHI, road density, and accommodation service facilities density showing the most significant variation. The marginal effect and spatial variation of the impact needs to be considered when developing strategies to reduce taxis’ pollutant emissions.

Suggested Citation

  • Guanwei Zhao & Zeyu Pan & Muzhuang Yang, 2022. "Marginal Effects and Spatial Variations of the Impact of the Built Environment on Taxis’ Pollutant Emissions in Chengdu, China," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16962-:d:1006243
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    References listed on IDEAS

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    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Zhou, Guanghui & Chung, William & Zhang, Xiliang, 2013. "A study of carbon dioxide emissions performance of China's transport sector," Energy, Elsevier, vol. 50(C), pages 302-314.
    3. Modarres, Ali, 2013. "Commuting and energy consumption: toward an equitable transportation policy," Journal of Transport Geography, Elsevier, vol. 33(C), pages 240-249.
    4. Brand, Christian & Goodman, Anna & Rutter, Harry & Song, Yena & Ogilvie, David, 2013. "Associations of individual, household and environmental characteristics with carbon dioxide emissions from motorised passenger travel," Applied Energy, Elsevier, vol. 104(C), pages 158-169.
    5. Mark R. Stevens, 2017. "Response to Commentaries on “Does Compact Development Make People Drive Less?”," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(2), pages 151-158, April.
    6. Mark R. Stevens, 2017. "Does Compact Development Make People Drive Less?," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 7-18, January.
    7. Jinlei Zhang & Feng Chen & Zijia Wang & Rui Wang & Shunwei Shi, 2018. "Spatiotemporal Patterns of Carbon Emissions and Taxi Travel Using GPS Data in Beijing," Energies, MDPI, vol. 11(3), pages 1-22, February.
    8. Wenyue Yang & Shaojian Wang & Xiaoming Zhao, 2018. "Measuring the Direct and Indirect Effects of Neighborhood-Built Environments on Travel-related CO 2 Emissions: A Structural Equation Modeling Approach," Sustainability, MDPI, vol. 10(5), pages 1-14, April.
    9. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    10. Gyo-Eon Shim & Sung-Mo Rhee & Kun-Hyuck Ahn & Sung-Bong Chung, 2006. "The relationship between the characteristics of transportation energy consumption and urban form," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 40(2), pages 351-367, June.
    11. Chuan Ding & Yaowu Wang & Binglei Xie & Chao Liu, 2014. "Understanding the Role of Built Environment in Reducing Vehicle Miles Traveled Accounting for Spatial Heterogeneity," Sustainability, MDPI, vol. 6(2), pages 1-13, January.
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