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Life-cycle Environmental Inventory of Passenger Transportation in the United States

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  • Chester, Mikhail V

Abstract

Energy use and emission factors for passenger transportation modes typically ignore the total environmental inventory which includes vehicle non-operational components (e.g., vehicle manufacturing and maintenance), infrastructure components, and fuel production components from design through end-of-life processes. A life-cycle inventory for each mode is necessary to appropriately address and attribute the transportation sector’s energy and emissions impacts to reduction goals instead of allowing tailpipe emissions to act as indicators of total system performance. The contributions of U.S. passenger transportation modes to national energy and emissions inventories account for roughly 20% of U.S. totals, mostly attributed to gasoline consumption. Furthermore, world consumption of primary energy amounted to 490 EJ in 2005 with the U.S. responsible for 110 EJ, or 21% of the total. This means that passenger transportation in the U.S. accounts for roughly 5% of global primary energy consumption annually. With a predominant fossil fuel energy base, the impacts of U.S. passenger transportation have strong implications for global energy consumption, U.S. energy security, and climate change. Furthermore, criteria air pollutant emissions from transportation (passenger and freight) are also significant, accounting for 78% of national CO, 58% of NOX, 36% of VOCs, 9% of PM2.5, 2.6% of PM10, and 4.5% of SO2 emissions. These emissions often occur near population centers and can cause adverse direct human health effects as well as other impacts such as ground-level ozone formation and acid deposition. To appropriately mitigate environmental impacts from transportation, it is necessary for decision makers to consider the life-cycle energy consumption and emissions associated with each mode. A life-cycle energy, greenhouse gas, and criteria air pollutant emissions inventory is created for the passenger transportation modes of automobiles, urban buses, heavy rail transit, light rail transit, and aircraft in the U.S. Each mode’s inventory includes an assessment of vehicles, infrastructure, and fuel components. For each component, analysis is performed for material extraction through use and maintenance in both direct and indirect (supply chain) processes. For each mode’s life-cycle components, energy inputs and emission outputs are determined. Energy inputs include electricity and petroleum-based fuels. Emission outputs include greenhouse gases (CO2, CH4, and N2O) and criteria pollutants (CO, SO2, NOX, VOCs, and PM). The inputs and outputs are normalized by vehicle lifetime, vehicle mile traveled, and passenger mile traveled. A consistent system boundary is applied to all modal inventories which captures the entire life-cycle, except for end-of-life. For each modal life-cycle component, both direct and indirect processes are included if possible. A hybrid life-cycle assessment approach is used to estimate the components in the inventories. We find that life-cycle energy inputs and emission outputs increase significantly compared to the vehicle operational phase. Life-cycle energy consumption is 39-56% larger than vehicle operation for autos, 38% for buses, 93-160% for rail, and 19-24% for air systems per passenger mile traveled. Life-cycle greenhouse gas emissions are 47-65% larger than vehicle operation for autos, 43% for buses, 39-150% for rail, and 24-31% for air systems per passenger mile traveled. The energy and greenhouse gas increases are primarily due to vehicle manufacturing and maintenance, infrastructure construction, and fuel production. For criteria air pollutants, life-cycle components often dominate total emissions and can be a magnitude larger than operational counterparts. Per passenger mile traveled, total SO2 emissions (between 350 and 460 mg) are 19-27 times larger than operational emissions as a result of electricity generation in vehicle manufacturing, infrastructure construction, and fuel production. NOX emissions increase 50-73% for automobiles, 24% for buses, 13-1300% for rail, and 19-24% for aircraft. Non-tailpipe VOCs are 27-40% of total automobile, 71-95% of rail, and 51-81% of air total emissions. Infrastructure and parking construction are major components of total PM10 emissions resulting in total emissions over three times larger than operational emissions for autos and even larger for many rail systems and aircraft (the major contributor being emissions from hot-mix asphalt plants and concrete production). Infrastructure construction and operation as well as vehicle manufacturing increase total CO emissions by 5-17 times from tailpipe performance for rail and 3-9 times for air. A case study comparing the environmental performance of metropolitan regions is presented as an application of the inventory results. The San Francisco Bay Area, Chicago, and New York City are evaluated capturing passenger transportation life-cycle energy inputs and greenhouse gas and criteria air pollutant emissions. The regions are compared between off-peak and peak travel as well as personal and public transit. Additionally, healthcare externalities are computed from vehicle emissions. It is estimated that life-cycle energy varies from 6.3 MJ/PMT in the Bay Area to 5.7 MJ/PMT in Chicago and 5.3 MJ/PMT in New York for an average trip. Life-cycle GHG emissions range from 480 g C02e/PMT in the Bay Area to 440 g C02e/PMT for Chicago and 410 g C02e/PMT in New York. CAP emissions vary depending on the pollutant with differences as large as 25% between regions. Life-cycle CAP emissions are between 11% and 380% larger than their operational counterparts. Peak travel, with typical higher riderships, does not necessarily environmentally outperform off-peak travel due to the large share of auto PMT and less than ideal operating conditions during congestion. The social costs of travel range from 51 cent (in 2007 cents) per auto passenger per trip during peak in New York to 6 cents per public transit passenger per trip during peak hours in the Bay Area and New York. Average personal transit costs are around 30 cents while public transit ranges from 28 cents to 41 cents. This dissertation was completed with Professor Arpad Horvath serving as the advisor. This document supercedes the University of California, Berkeley, Center for Future Urban Transport papers, vwp-2007-7 and vwp-2008-2. Additional project information can be found at http://www.sustainable-transportation.com.

Suggested Citation

  • Chester, Mikhail V, 2008. "Life-cycle Environmental Inventory of Passenger Transportation in the United States," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7n29n303, Institute of Transportation Studies, UC Berkeley.
  • Handle: RePEc:cdl:itsrrp:qt7n29n303
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    1. Jariyasunant, Jerald & Abou-Zeid, Maya & Carrel, Andre & Ekambaram, Venkatesan & Gaker, David & Sengupta, Raja & Walker, Joan L., 2013. "Quantified Traveler: Travel Feedback Meets the Cloud to Change Behavior," University of California Transportation Center, Working Papers qt2dh952gj, University of California Transportation Center.
    2. Sofiia Miliutenko & Ingeborg Kluts & Kristina Lundberg & Susanna Toller & Helge Brattebø & Harpa Birgisdóttir & José Potting, 2014. "Consideration Of Life Cycle Energy Use And Greenhouse Gas Emissions In Road Infrastructure Planning Processes: Examples Of Sweden, Norway, Denmark And The Netherlands," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1-26.
    3. Jariyasunant, Jerald & Carrel, Andre & Ekambaram, Venkatesan & Gaker, David & Sengupta, Raja & Walker, Joan L., 2012. "The Quantified Traveler: Changing transport behavior with personalized travel data feedback," University of California Transportation Center, Working Papers qt3047k0dw, University of California Transportation Center.
    4. Michael Minn, 2019. "Contested Power: American Long-Distance Passenger Rail and the Ambiguities of Energy Intensity Analysis," Sustainability, MDPI, vol. 11(4), pages 1-20, February.
    5. Simon Robertson, 2013. "High-speed rail's potential for the reduction of carbon dioxide emissions from short haul aviation: a longitudinal study of modal substitution from an energy generation and renewable energy perspectiv," Transportation Planning and Technology, Taylor & Francis Journals, vol. 36(5), pages 395-412, July.
    6. Ryerson, Megan S., 2010. "Optimal Intercity Transportation Services with Heterogeneous Demand and Variable Fuel Price," University of California Transportation Center, Working Papers qt8696z26t, University of California Transportation Center.
    7. Tiago Ramos da Silva & Bruna Moura & Helena Monteiro, 2023. "Life Cycle Assessment of Current Portuguese Railway and Future Decarbonization Scenarios," Sustainability, MDPI, vol. 15(14), pages 1-15, July.
    8. Ali Azhar Butt & John Harvey & Arash Saboori & Maryam Ostovar & Manuel Bejarano & Navneet Garg, 2020. "Decision Support in Selecting Airfield Pavement Design Alternatives Using Life Cycle Assessment: Case Study of Nashville Airport," Sustainability, MDPI, vol. 13(1), pages 1-19, December.
    9. Kristoffer W. Lie & Trym A. Synnevåg & Jacob J. Lamb & Kristian M. Lien, 2021. "The Carbon Footprint of Electrified City Buses: A Case Study in Trondheim, Norway," Energies, MDPI, vol. 14(3), pages 1-21, February.
    10. Christian Spreafico & Davide Russo, 2020. "Exploiting the Scientific Literature for Performing Life Cycle Assessment about Transportation," Sustainability, MDPI, vol. 12(18), pages 1-24, September.
    11. Antonia Rahn & Kai Wicke & Gerko Wende, 2022. "Using Discrete-Event Simulation for a Holistic Aircraft Life Cycle Assessment," Sustainability, MDPI, vol. 14(17), pages 1-31, August.
    12. Jariyasunant, Jerald & Carrel, Andre & Ekambaram, Venkatesan & Gaker, DJ & Kote, Thejovardhana & Sengupta, Raja & Walker, Joan L., 2011. "The Quantified Traveler: Using personal travel data to promote sustainable transport behavior," University of California Transportation Center, Working Papers qt9jg0p1rj, University of California Transportation Center.
    13. Wojciech SZYMALSKI, 2021. "Energy And Co 2 Emission Intensities Of Various Modes Of Passenger Transport In Warsaw," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 16(2), pages 131-140, June.
    14. Rohacs, Jozsef & Rohacs, Daniel, 2020. "Energy coefficients for comparison of aircraft supported by different propulsion systems," Energy, Elsevier, vol. 191(C).
    15. Jariyasunant, Jerald & Carrel, Andre & Ekambaram, Venkatesan & Gaker, DJ & Kote, Thejovardhana & Sengupta, Raja & Walker, Joan L., 2011. "The Quantified Traveler: Using personal travel data to promote sustainable transport behavior," University of California Transportation Center, Working Papers qt678537sx, University of California Transportation Center.
    16. Peng Du & Antony Wood & Brent Stephens, 2016. "Empirical Operational Energy Analysis of Downtown High-Rise vs. Suburban Low-Rise Lifestyles: A Chicago Case Study," Energies, MDPI, vol. 9(6), pages 1-27, June.
    17. Rajib Sinha & Lars E. Olsson & Björn Frostell, 2019. "Sustainable Personal Transport Modes in a Life Cycle Perspective—Public or Private?," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
    18. Ana María Arbeláez Vélez & Andrius Plepys, 2021. "Car Sharing as a Strategy to Address GHG Emissions in the Transport System: Evaluation of Effects of Car Sharing in Amsterdam," Sustainability, MDPI, vol. 13(4), pages 1-15, February.
    19. Levon Amatuni & Juudit Ottelin & Bernhard Steubing & Jos'e Mogollon, 2019. "Does car sharing reduce greenhouse gas emissions? Life cycle assessment of the modal shift and lifetime shift rebound effects," Papers 1910.11570, arXiv.org.

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