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Ev Friendly Cities: A Comparison of Policy and Infrastructure in Sixteen Global Cities.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Ev Friendly Cities: A Comparison of Policy and Infrastructure in Sixteen Global Cities./
作者:
Haque Suravi, Romana .
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
121 p.
附註:
Source: Masters Abstracts International, Volume: 83-02.
Contained By:
Masters Abstracts International83-02.
標題:
Urban planning. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28547267
ISBN:
9798535506746
Ev Friendly Cities: A Comparison of Policy and Infrastructure in Sixteen Global Cities.
Haque Suravi, Romana .
Ev Friendly Cities: A Comparison of Policy and Infrastructure in Sixteen Global Cities.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 121 p.
Source: Masters Abstracts International, Volume: 83-02.
Thesis (Master)--University of Washington, 2021.
This item must not be sold to any third party vendors.
Electric vehicles, one of the emerging modes of transportation, are at the forefront of sustainable mobility. In the past years, there has been a rapid rise in EVs, both as private and public transportation modes. Private users are influenced by multiple factors while choosing electric cars as their travel modes. Among them, policy and infrastructure are deemed to be the main influencers globally. These policies and infrastructures vary in different cities. However, there is a lack of research dealing with what parts of the policy and infrastructure are actually most effective in EV adoption. This research presents a descriptive and quantitative evaluation as well as statistical analysis to identify the most effective policies and infrastructure components in electric car adoption as a personal transportation mode in sixteen selected cities; Seattle, Los Angeles, San Francisco, San Jose, New York, Oslo, Bergen, London, Amsterdam, Stockholm, Berlin, Munich, Paris, Shenzhen, Beijing and Tokyo. The cities are evaluated based on total electric vehicles on road, EVs on household level and electrification ratio of the registered cars in conjunction with household median income. Policy level incentives like electrification target, parking, toll, and lane access benefits along with tax rebates, subsidies and other monetary incentives as part of the total cost of ownership are also observed. Total number of public and residential charging points as well as the EV supply equipment program are analyzed as part of EV infrastructure preparedness on city level. Among the sample cities, Norway is the pioneer in the electric car integration into their passenger car market. All the sample cities have active Zero Energy Vehicle mandates and incentives for electric vehicles. Through secondary data collection via various online resources and statistical observation with help of the existing literature, this study found high correlation between EV ownership and incentives. Multilinear Regression Analysis model predicted 0.53% increase in passenger electrification with every $100 incentive increase. The environmental conditions of the sample cities are also evaluated to observe the impact of mass EV adoption in the overall improvement in CO2 emission reduction. At the end of this paper, this research proposes some policies to improve the EV adoption challenges present in the sample cities as well as the cities aiming to turn towards this sustainable mode in the future.
ISBN: 9798535506746Subjects--Topical Terms:
2122922
Urban planning.
Subjects--Index Terms:
Electric vehicle
Ev Friendly Cities: A Comparison of Policy and Infrastructure in Sixteen Global Cities.
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Electric vehicles, one of the emerging modes of transportation, are at the forefront of sustainable mobility. In the past years, there has been a rapid rise in EVs, both as private and public transportation modes. Private users are influenced by multiple factors while choosing electric cars as their travel modes. Among them, policy and infrastructure are deemed to be the main influencers globally. These policies and infrastructures vary in different cities. However, there is a lack of research dealing with what parts of the policy and infrastructure are actually most effective in EV adoption. This research presents a descriptive and quantitative evaluation as well as statistical analysis to identify the most effective policies and infrastructure components in electric car adoption as a personal transportation mode in sixteen selected cities; Seattle, Los Angeles, San Francisco, San Jose, New York, Oslo, Bergen, London, Amsterdam, Stockholm, Berlin, Munich, Paris, Shenzhen, Beijing and Tokyo. The cities are evaluated based on total electric vehicles on road, EVs on household level and electrification ratio of the registered cars in conjunction with household median income. Policy level incentives like electrification target, parking, toll, and lane access benefits along with tax rebates, subsidies and other monetary incentives as part of the total cost of ownership are also observed. Total number of public and residential charging points as well as the EV supply equipment program are analyzed as part of EV infrastructure preparedness on city level. Among the sample cities, Norway is the pioneer in the electric car integration into their passenger car market. All the sample cities have active Zero Energy Vehicle mandates and incentives for electric vehicles. Through secondary data collection via various online resources and statistical observation with help of the existing literature, this study found high correlation between EV ownership and incentives. Multilinear Regression Analysis model predicted 0.53% increase in passenger electrification with every $100 incentive increase. The environmental conditions of the sample cities are also evaluated to observe the impact of mass EV adoption in the overall improvement in CO2 emission reduction. At the end of this paper, this research proposes some policies to improve the EV adoption challenges present in the sample cities as well as the cities aiming to turn towards this sustainable mode in the future.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28547267
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