scholarly journals Are There Environmental Benefits from Driving Electric Vehicles? The Importance of Local Factors

2016 ◽  
Vol 106 (12) ◽  
pp. 3700-3729 ◽  
Author(s):  
Stephen P. Holland ◽  
Erin T. Mansur ◽  
Nicholas Z. Muller ◽  
Andrew J. Yates
Keyword(s):  
Air Pollution ◽  
Discrete Choice ◽  
Electric Vehicles ◽  
Choice Model ◽  
Environmental Benefits ◽  
Environmental Externalities ◽  
Deadweight Loss ◽  
Local Factors ◽  
Vehicle Purchase ◽  
Air Pollution Model

We combine a theoretical discrete-choice model of vehicle purchases, an econometric analysis of electricity emissions, and the AP2 air pollution model to estimate the geographic variation in the environmental benefits from driving electric vehicles. The second-best electric vehicle purchase subsidy ranges from $2,785 in California to −$4,964 in North Dakota, with a mean of −$1,095. Ninety percent of local environmental externalities from driving electric vehicles in one state are exported to others, implying they may be subsidized locally, even when the environmental benefits are negative overall. Geographically differentiated subsidies can reduce deadweight loss, but only modestly. (JEL D12, D62, H23, L62, Q53, Q54, R11)

scholarly journals A Charging Location Choice Model for Plug-In Hybrid Electric Vehicle Users

2019 ◽  
Vol 11 (20) ◽  
pp. 5761 ◽  
Author(s):  
Bolong Yun ◽  
Daniel (Jian) Sun ◽  
Yingjie Zhang ◽  
Siwen Deng ◽  
Jing Xiong
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Choice Model ◽  
Environmental Benefits ◽  
The Public ◽  
Home Based ◽  
Hybrid Electric ◽  
Charging Stations ◽  
The Relationship

Electric vehicles (EVs) are promising alternatives to replace traditional gasoline vehicles. The relationship between available charging stations and electric vehicles has to be precisely coordinated to facilitate the increasing promotion and usage of EVs. This paper aims to investigate the choice of the charging location with global positioning system (GPS) trajectories of 700 Plug-in Hybrid Electric Vehicle (PHEV) users as well as the charging facility data in Shanghai. First, the recharge accessibility of each PHEV user was investigated, and 9% rely solely on public charging networks. Then, we explored the relationship between fuel consumption and the average distance between charging to analyze the environmental benefits of PHEVs. It was found that 16% PHEVs are similar to EVs, and 9% whose drivers rely solely on public charging stations are similar to internal combustion engine (ICE) vehicles. PHEV users were divided into four types based on the actual recharge access: home and workplace-based user (private + workplace + public), the home-based user (private + public), the workplace-based user (workplace + public), and the public-based user (public). Models were developed to identify and compare the factors that influence PHEV user’s charging location choices (home, workplace, and public stations). The modeling and results interpretation were carried out for all PHEV users, home and workplace-based users, home-based users, and workplace-based users, respectively. The estimation results demonstrated that PHEV users tended to charge at home or workplace rather than public charging stations. Charging price, charging price tariff, the initial state of charge (SOC), dwell time, charging power, the density and size of public charging stations, the total number of public charging, vehicle kilometer travel (VKT) of the current trip and current day are the main predictors when choosing the charging location. Findings of this study may provide new insights into the operational strategies of the public charging station as well as the deployment of public charging facilities in urban cities.

Dynamic Household Vehicle Decision Modeling Considering Plug-In Electric Vehicles

2018 ◽  
Vol 2672 (49) ◽  
pp. 91-100
Author(s):  
Fatemeh Nazari ◽  
Abolfazl (Kouros) Mohammadian ◽  
Thomas Stephens
Keyword(s):  
Decision Making ◽  
Electric Vehicles ◽  
Choice Model ◽  
Cost Savings ◽  
Critical Factor ◽  
Capital Cost ◽  
Environmental Benefits ◽  
Data Set ◽  
Vehicle Type ◽  
Upper Level

Plug-in electric vehicles (PEVs) offer alternatives to traditional vehicles that rely on petroleum-based fuels. While PEV customers can enjoy significant reductions in fuel costs, they incur a larger capital cost than users of traditional vehicles because PEV technology is still maturing. Therefore, consumers adopting PEVs face a trade-off between fuel cost savings with environmental benefits and extra capital cost. It is thus crucial for policy makers and PEV manufacturers to understand people’s vehicle decision-making process while considering their socio-economic and travel pattern characteristics as well as the built-environment factors. This paper presents a connected, two-stage, dynamic model of PEV adoption and vehicle-transaction decision-making. Two connected nested logit (NL) models are estimated. The upper level is a two-level NL model to predict choice of vehicle type between four fuel types: gasoline, diesel, hybrid gasoline–electric, and PEV. The lower level is an NL model of vehicle-transaction choice which accommodates four transaction decisions of buy, trade, dispose, and do nothing, while accounting for the log-sum from the vehicle-type choice model, and is estimated using two waves of a panel data set. We find that households with higher levels of income and education are more likely to adopt a PEV. We also found that primarily decision makers take into account the accessibility to charging stations as a critical factor in choosing PEVs.

scholarly journals The Electric Vehicle Transition and the Economics of Banning Gasoline Vehicles

2021 ◽  
Vol 13 (3) ◽  
pp. 316-344
Author(s):  
Stephen P. Holland ◽  
Erin T. Mansur ◽  
Andrew J. Yates
Keyword(s):  
Electric Vehicle ◽  
Dynamic Model ◽  
Electric Vehicles ◽  
Deadweight Loss ◽  
Gasoline Vehicles ◽  
The Us ◽  
Vehicle Production ◽  
Personal Transportation ◽  
Vehicle Purchase ◽  
Unique Potential

Electric vehicles have a unique potential to transform personal transportation. We analyze this transition with a dynamic model capturing falling costs of electric vehicles, decreasing pollution from electricity, and increasing vehicle substitutability. Our calibration to the US market shows a transition from gasoline vehicles is not optimal at current substitutability: a gasoline vehicle production ban would have large deadweight loss. At higher substitutability, a ban can reduce deadweight loss from vehicle mix and adoption timing inefficiencies. A cumulative gasoline vehicle production quota has smaller deadweight loss, and an electric vehicle purchase subsidy is more robust to regulator misperceptions about substitutability. (JEL H23, L51, L62, L94, Q53)

The Impact of Zoning and Built Environment Characteristics on Transit, Biking, and Walking

2019 ◽  
Vol 11 (1) ◽  
pp. 108-129
Author(s):  
Andrew G. Mueller ◽  
Daniel J. Trujillo
Keyword(s):  
Land Use ◽  
Built Environment ◽  
Discrete Choice ◽  
Travel Behavior ◽  
Choice Model ◽  
Mode Choice ◽  
Land Use Regulation ◽  
Policy Action ◽  
Development Goals ◽  
The Impact

This study furthers existing research on the link between the built environment and travel behavior, particularly mode choice (auto, transit, biking, walking). While researchers have studied built environment characteristics and their impact on mode choice, none have attempted to measure the impact of zoning on travel behavior. By testing the impact of land use regulation in the form of zoning restrictions on travel behavior, this study expands the literature by incorporating an additional variable that can be changed through public policy action and may help cities promote sustainable real estate development goals. Using a unique, high-resolution travel survey dataset from Denver, Colorado, we develop a multinomial discrete choice model that addresses unobserved travel preferences by incorporating sociodemographic, built environment, and land use restriction variables. The results suggest that zoning can be tailored by cities to encourage reductions in auto usage, furthering sustainability goals in transportation.

Air Passengers’ Preferences for Aviation Voluntary Carbon Offsetting: A Co-benefits Perspective

2021 ◽  
pp. 004728752110303
Author(s):  
Beile Zhang ◽  
Brent W. Ritchie ◽  
Judith Mair ◽  
Sally Driml
Keyword(s):  
Discrete Choice ◽  
Latent Class ◽  
Choice Model ◽  
Choice Modeling ◽  
Positive Outcomes ◽  
Market Segments ◽  
Discrete Choice Modeling ◽  
Educational Benefits ◽  
Carbon Offsetting ◽  
Simple Reduction

Co-benefits are positive outcomes from voluntary carbon offsetting (VCO) programs beyond simple reduction in carbon emissions, which include biodiversity, air quality, economic, health, and educational benefits. Given the rates of aviation VCOs remain at less than 10%, this study investigated air passengers’ preferences for co-benefits as well as certification, location, and cost of VCO programs. Using discrete choice modeling, this study shows that aviation VCO programs with higher levels of co-benefits, particularly biodiversity and health benefits, are preferred by air passengers and confirms a preference for domestically based and certified VCO programs. The latent class choice model identified three classes with different preferences for VCO program attributes and demographic characteristics. The results of this study contribute to the knowledge of VCO co-benefits and imply that airlines should take note of this preference for biodiversity and health co-benefits when designing VCO programs and differentiate between market segments to increase the uptake of VCOs.

scholarly journals Electric Vehicles in Jordan: Challenges and Limitations

2021 ◽  
Vol 13 (6) ◽  
pp. 3199
Author(s):  
Laith Shalalfeh ◽  
Ashraf AlShalalfeh ◽  
Khaled Alkaradsheh ◽  
Mahmoud Alhamarneh ◽  
Ahmad Bashaireh
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Distribution Systems ◽  
Environmental Benefits ◽  
System Stability ◽  
Loading Conditions ◽  
Stability Margins ◽  
High Penetration ◽  
Node Distribution ◽  
The Impact

An increasing number of electric vehicles (EVs) are replacing gasoline vehicles in the automobile market due to the economic and environmental benefits. The high penetration of EVs is one of the main challenges in the future smart grid. As a result of EV charging, an excessive overloading is expected in different elements of the power system, especially at the distribution level. In this paper, we evaluate the impact of EVs on the distribution system under three loading conditions (light, intermediate, and full). For each case, we estimate the maximum number of EVs that can be charged simultaneously before reaching different system limitations, including the undervoltage, overcurrent, and transformer capacity limit. Finally, we use the 19-node distribution system to study these limitations under different loading conditions. The 19-node system is one of the typical distribution systems in Jordan. Our work estimates the upper limit of the possible EV penetration before reaching the system stability margins.

scholarly journals Pre-calibration of a Discrete Choice Model and Evaluation of Cycling Mobility for Île-de-France

2021 ◽  
Vol 184 ◽  
pp. 172-177
Author(s):  
Guoxi Feng ◽  
Maxime Jean ◽  
Alexandre Chasse ◽  
Sebastian Hörl
Keyword(s):  
Discrete Choice ◽  
Choice Model ◽  
Discrete Choice Model
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