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An Integrated Environmental Indicator for Urban Transportation Systems: Description and Application

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  • Maria La Gennusa

    (Dipartimento di Energia, ingegneria dell'Informazione e modelli Matematici (DEIM), Polytechnic School, University of Palermo, Viale delle Scienze, Ed. 9, 90128 Palermo, Italy)

  • Patrizia Ferrante

    (Dipartimento di Energia, ingegneria dell'Informazione e modelli Matematici (DEIM), Polytechnic School, University of Palermo, Viale delle Scienze, Ed. 9, 90128 Palermo, Italy
    These authors contributed equally to this work.)

  • Barbara Lo Casto

    (Dipartimento di Energia, ingegneria dell'Informazione e modelli Matematici (DEIM), Polytechnic School, University of Palermo, Viale delle Scienze, Ed. 9, 90128 Palermo, Italy
    These authors contributed equally to this work.)

  • Gianfranco Rizzo

    (Dipartimento di Energia, ingegneria dell'Informazione e modelli Matematici (DEIM), Polytechnic School, University of Palermo, Viale delle Scienze, Ed. 9, 90128 Palermo, Italy
    These authors contributed equally to this work.)

Abstract

A simplified version of the ecological footprint method is proposed for assessing the environmental performances of urban transportation systems. The method, starting from the knowledge of the composition of the running vehicular fleet, is here applied to a southern Italian province. It represents a synthetic indicator of the environmental pressure exerted by the system also matching the pollutant emissions with the carrying capacity of the site. Particularly, the forested area needed to absorb the CO 2 emissions of the system is compared with the total forested area of the province. The results of the case-study indicates the yearly maximum distance that each vehicle of the fleet can cover in order for their emissions to be absorbed by the surrounding forested area. Specifically, if all cars of the fleet would travel for 10,000 km/year, 97% of the forested area would be involved. Thanks to its features, this indicator can be usefully adopted for ranking different transportation options. Therefore, it could allow local administrations to environmentally hierarchize alternative plans concerning urban transportation choices.

Suggested Citation

  • Maria La Gennusa & Patrizia Ferrante & Barbara Lo Casto & Gianfranco Rizzo, 2015. "An Integrated Environmental Indicator for Urban Transportation Systems: Description and Application," Energies, MDPI, vol. 8(10), pages 1-19, October.
  • Handle: RePEc:gam:jeners:v:8:y:2015:i:10:p:11076-11094:d:56787
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    References listed on IDEAS

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    1. Gössling, Stefan & Cohen, Scott, 2014. "Why sustainable transport policies will fail: EU climate policy in the light of transport taboos," Journal of Transport Geography, Elsevier, vol. 39(C), pages 197-207.
    2. Amekudzi, Adjo A. & Jotin Khisty, C. & Khayesi, Meleckidzedeck, 2009. "Using the sustainability footprint model to assess development impacts of transportation systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 339-348, May.
    3. Dongquan He & Fei Meng & Michael Q. Wang & Kebin He, 2011. "Impacts of Urban Transportation Mode Split on CO 2 Emissions in Jinan, China," Energies, MDPI, vol. 4(4), pages 1-15, April.
    4. Brett Williams & Elliot Martin & Timothy Lipman & Daniel Kammen, 2011. "Plug-in-Hybrid Vehicle Use, Energy Consumption, and Greenhouse Emissions: An Analysis of Household Vehicle Placements in Northern California," Energies, MDPI, vol. 4(3), pages 1-23, March.
    5. Marco Guerrieri & Ferdinando Corriere & Gianfranco Rizzo & Barbara Lo Casto & Gianluca Scaccianoce, 2015. "Improving the Sustainability of Transportation: Environmental and Functional Benefits of Right Turn By-Pass Lanes at Roundabouts," Sustainability, MDPI, vol. 7(5), pages 1-19, May.
    6. Timothy Waring & Mario Teisl & Eva Manandhar & Mark Anderson, 2014. "On the Travel Emissions of Sustainability Science Research," Sustainability, MDPI, vol. 6(5), pages 1-18, May.
    7. repec:cdl:itsrrp:qt6xt6d5jv is not listed on IDEAS
    8. Morten Simonsen & Hans Jakob Walnum, 2011. "Energy Chain Analysis of Passenger Car Transport," Energies, MDPI, vol. 4(2), pages 1-28, February.
    9. Cheng Gong & Shiwen Zhang & Feng Zhang & Jianguo Jiang & Xinheng Wang, 2014. "An Integrated Energy-Efficient Operation Methodology for Metro Systems Based on a Real Case of Shanghai Metro Line One," Energies, MDPI, vol. 7(11), pages 1-25, November.
    10. Nuwong Chollacoop & Peerawat Saisirirat & Tuenjai Fukuda & Atsushi Fukuda, 2011. "Scenario Analyses of Road Transport Energy Demand: A Case Study of Ethanol as a Diesel Substitute in Thailand," Energies, MDPI, vol. 4(1), pages 1-18, January.
    11. Paul Minett & John Pearce, 2011. "Estimating the Energy Consumption Impact of Casual Carpooling," Energies, MDPI, vol. 4(1), pages 1-14, January.
    12. Elliot Martin & Susan Shaheen, 2011. "The Impact of Carsharing on Public Transit and Non-Motorized Travel: An Exploration of North American Carsharing Survey Data," Energies, MDPI, vol. 4(11), pages 1-21, November.
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