A multi-paradigm approach to system dynamics modeling of intercity transportation

Lewe, Jung-Ho; Hivin, Ludovic F.; Mavris, Dimitri N.

doi:10.1016/j.tre.2014.09.011

Cited by 40 publications

(20 citation statements)

References 34 publications

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“…The two most common approaches to construct transport subsystems to estimate energy consumption and emissions from urban passenger transport are: (1) using vehicle fleet, vehicle kilometer travelled (VKT), fuel economy, and emission rates (Cheng et al, 2015;Egilmez and Tatari, 2012) and (2) using number of trips by each mode (modal share), driving distance, energy consumption per trip by each mode and emission rates (Lewe et al, 2014;Xue Liu et al, 2015). In this study, the second approach is used in constructing the transport subsystem.…”

Section: Transport Subsystemmentioning

confidence: 99%

“…Since then, numerous studies have proposed and applied SD models for various purposes in the field (Shepherd, 2014). These studies vary extensively focusing on different aspects of transportation such as alternative fuel vehicles (Kwon, 2012;Onat et al, 2016;Stepp et al, 2009;Struben and Sterman, 2008), effect of resource allocation policies on urban transport diversity (Feng and Hsieh, 2009), linkage of transport development and land use (Shen et al, 2009), evaluating applications on traffic safety policy (Goh and Love, 2012), urban traffic and its parking related states (Cao and Menendez, 2015), air passenger demand forecasting (Suryani et al, 2010), impacts of rail transit system on metropolitan regions (Yang et al, 2014), highway sustainability (Egilmez and Tatari, 2012), intercity transportation (Han and Hayashi, 2008;Lewe et al, 2014), congestion pricing scheme (Liu et al, 2010;Sabounchi et al, 2014), and traffic congestion and air pollution linkage (Armah et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Impact assessment of supply-side and demand-side policies on energy consumption and CO2 emissions from urban passenger transportation: The case of Istanbul

Batur

Bayram

Кочкодан

2019

Journal of Cleaner Production

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The transportation sector accounts for about a quarter of global energy consumption and energy-related carbon emissions. To design and realize sustainable urban transportation, it is vital to understand and analyze interactions between a set of dynamic factors that shape transportation patterns, behaviors, and impacts. To this end, this study aims to develop a systems dynamics (SD) model for Istanbul, Turkey to simulate its urban motorized passenger transport system for analyzing numerous policies under different scenarios and assessing their potential effects in reducing energy consumption and CO2 emissions in the upcoming years. The constructed SD model includes four subsystems: population, household disposable income, transport, and energy and CO2 emissions. Based on historical data (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) and model validation processes, the energy consumption and the associated CO2 emissions from motorized passenger transport are forecasted for the following scenarios. The first one is business as usual scenario (BAU) which is designed to show how energy use and the associated CO2 emissions would evolve over time with the current development plans. The second and third scenarios constitute supply management measures (SMM) which consider different levels of improvements in the fuel economy of the vehicle fleet and reduced carbon emission intensity in electricity generation through increased share of renewable energy use. The fourth and fifth scenarios consider travel demand management (TDM) policies that include different levels of transport cost increase, and trip length reduction. Finally, the last two scenarios include integrated scenarios that are composed of the SMM and TDM options. In detail, compared to the BAU scenario, integrated scenario considers (1) a 10% improvement in the fuel economy of the vehicles, (2) a 10% reduction in the emission intensity of electricity generation, (3) a 30% increase in the transportation cost, and (4) a 15% reduction in the trip lengths. Under the BAU scenario, the SD model shows that energy consumption per capita from passenger trips will increase from 183 liters of oil equivalent in 2016 to 315 liters of oil equivalent in 2025 while the associated CO2 emissions per capita will increase from 460 kg in 2016 to 807 kg in 2025. To combat this dramatic growth, the findings indicate that the ambitious integrated scenario achieves the lowest energy consumption and CO2 emissions by offering a 33.5% expected reduction in total energy consumption and a 32.8% expected reduction in total CO2 emissions. Highlights • Development of system dynamics model for Istanbul passenger transport network• Several supply-side, demand-side, and integrated policy scenarios are generated using cost, emission, and trip-related parameters• Policies are evaluated based on transport energy consumption and CO2 emissions for Istanbul until 2025.• Integrated policies perform the best and lead to nearly one-third of energy and carbon...

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Section: Transport Subsystemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact assessment of supply-side and demand-side policies on energy consumption and CO2 emissions from urban passenger transportation: The case of Istanbul

Batur

Bayram

Кочкодан

2019

Journal of Cleaner Production

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show abstract

“…A dynamic model that captures the interrelationships between parts of the system is a valuable tool for exploring transport systems (Abbas and Bell 1994). It is therefore unsurprising that system dynamics, designed as it is to make order from complexity (Forrester 1961), has been widely used in wide ranging transport research (Shepherd 2014) including aviation (Sgouridis et al 2011), land transport (Struben and Sterman 2008), and multimodal travel (Leve et al 2014). Abbas and Bell (1994) argued that SD modelling is particularly useful for ''1.…”

Section: Applications Of System Dynamics Modelling To Transportmentioning

confidence: 99%

Exploring stability and change in transport systems: combining Delphi and system dynamics approaches

Rees¹,

Stephenson

Hopkins

et al. 2016

Transportation

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Transport is a vast and complex socio-technical system, and despite a clear need to reduce dependence on fossil fuels due to undesirable environmental impacts, it is largely locked into business-as-usual. Systems approaches are a useful way to help make sense of multiple competing influences which may be simultaneously driving change and supporting the status quo. This paper applies qualitative system dynamics modelling to help interpret the results of a Delphi study into global transport transitions, involving 22 international experts in various aspects of transport. The main contribution of the paper is its exploration of the use of system dynamics (SD) modelling to interpret the Delphi findings. SD modelling was used to reveal and elucidate the causal arguments put forward by the expert panel about the factors driving business-as-usual, the factors creating barriers to more sustainable transport systems, and the drivers of change. The SD model is used to explore and expose the key causal patterns at play, and how these interact to both support and hinder change. The resulting model shows the complex, interdependent dynamics involved in supporting the status quo. Even at the relatively high level of analysis reported here, the model is useful in revealing interdependencies between parts of the system, where change in one part may well have knock-on effects elsewhere in the system. In particular the model reveals the strong reinforcing loops that act to minimise the impact of change drivers and thus retain the dominance of automobility. The result is a system that is highly dependent on the continued existence of key reinforcements such as policies that subsidise fossil fuels. From a methodological perspective, the outcomes of the Delphi study provided a rich source of qualitative material which was highly suitable for developing a system dynamics model.

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“…Calibration is performed using Mi, through the adjustment of the rate of change of the stock of passengers, which changes based on the change in attractiveness of each mode over time. Mode choice is determined using the attractiveness of each mode of transportation, similar to a logit model (more details can be found in Lewe et al, 2014a). The attractiveness depends on the time and cost of each mode of transportation for a given type of trip.…”

Section: Quantifying Radiative Forcing Efficienciesmentioning

confidence: 99%

“…The use of a hybrid method enables two different approaches (top down and bottom up) to be used complementally. It allows for a better understanding of the complexity of the multimodal transportation system (Lewe et al, 2014a). Some issues such as capacity constraint or transportation policies are better handled with a top down approach, whereas other emerging behavior can only be captured with a bottom up approach.…”

Section: Quantifying Radiative Forcing Efficienciesmentioning

confidence: 99%

Regional climate impact of aerosols emitted by transportation modes and potential effects of policies on demand and emissions

Hivin

Pfaender

Mavris

2015

Transportation Research Part D: Transport and Environment

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A multi-paradigm approach to system dynamics modeling of intercity transportation

Cited by 40 publications

References 34 publications

Impact assessment of supply-side and demand-side policies on energy consumption and CO2 emissions from urban passenger transportation: The case of Istanbul

Impact assessment of supply-side and demand-side policies on energy consumption and CO2 emissions from urban passenger transportation: The case of Istanbul

Exploring stability and change in transport systems: combining Delphi and system dynamics approaches

Regional climate impact of aerosols emitted by transportation modes and potential effects of policies on demand and emissions

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