TY - JOUR
T1 - Impact assessment of future fleet compositions in vehicle emissions in urban areas
T2 - A methodological framework and a case study
AU - Nisyrios, Emmanouil
AU - Soares Amorim, Marco Raul
AU - Cantelmo, Guido
AU - Gkiotsalitis, Konstantinos
AU - Antoniou, Constantinos
N1 - Publisher Copyright:
© 2024 World Conference on Transport Research Society
PY - 2024/12
Y1 - 2024/12
N2 - This study explores the impact of emerging vehicle technologies on direct urban traffic emissions. It investigates emission reduction potential from shifts in fleet compositions and modal choices, especially considering climate change. To achieve this, three key research areas are explored for historical, current, and future scenarios (up to 2050): mode choice, emission factors for different vehicle categories, and diverse vehicle propulsion technologies. The estimation of the modal split is pivotal, developing a methodology utilizing Stated Preference survey data, discrete choice modeling, Monte Carlo simulations, and macroscopic traffic simulations. Future scenarios derive from the reference year's modal split, and emission factors and fleet compositions are predetermined via an extensive literature review, aiding the assessment of their respective emissions. A subsequent sensitivity analysis identifies the impact of specific parameters on emissions, guiding future research focus. Study results underscore differences in greenhouse gas emissions and primary air pollutants between base and future scenarios.
AB - This study explores the impact of emerging vehicle technologies on direct urban traffic emissions. It investigates emission reduction potential from shifts in fleet compositions and modal choices, especially considering climate change. To achieve this, three key research areas are explored for historical, current, and future scenarios (up to 2050): mode choice, emission factors for different vehicle categories, and diverse vehicle propulsion technologies. The estimation of the modal split is pivotal, developing a methodology utilizing Stated Preference survey data, discrete choice modeling, Monte Carlo simulations, and macroscopic traffic simulations. Future scenarios derive from the reference year's modal split, and emission factors and fleet compositions are predetermined via an extensive literature review, aiding the assessment of their respective emissions. A subsequent sensitivity analysis identifies the impact of specific parameters on emissions, guiding future research focus. Study results underscore differences in greenhouse gas emissions and primary air pollutants between base and future scenarios.
KW - Air pollutants
KW - Discrete choice model
KW - Fleet composition
KW - Greenhouse gases
KW - Macroscopic traffic simulation
KW - Monte Carlo simulation
UR - http://www.scopus.com/inward/record.url?scp=85202754053&partnerID=8YFLogxK
U2 - 10.1016/j.cstp.2024.101285
DO - 10.1016/j.cstp.2024.101285
M3 - Article
AN - SCOPUS:85202754053
SN - 2213-624X
VL - 18
JO - Case Studies on Transport Policy
JF - Case Studies on Transport Policy
M1 - 101285
ER -