ZIP-CodeLevel Drivers of EV Adoption in Washington: Socioeconomics, Urbanization, and Charger Proximity (20202025)

Electric vehicles (EVs) offer lower noise and zero tailpipe emissions compared to traditional internal combustion engine (ICE) vehicles. This study quantifies EV adoption across Washington State using ZIP-codelevel data from 20202025. Multivariable linear regressions relate the monthly change in EV share to socioeconomic factors, urbanization, family structure, and the roll-out of public charging infrastructure. Results indicate that adoption growth is positively associated with higher per-capita income, higher educational attainment, greater urbanization, and larger average family size. Proximity to infrastructure matters: the number of newly built local stations (020 miles) is positively associated with adoption growth, whereas a higher number of newly built distant stations (30 miles) correlates negatively, consistent with rurality and limited access. By providing a comprehensive ZIP-codelevel analysis, the study addresses aggregation bias common in county-level work and reveals localized patterns that broader geographies can obscure. The findings offer policy-relevant evidence for charger siting and for targeting incentives.

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Publication Details

Journal
Applied and Computational Engineering
Published
2025-09-09
DOI
https://doi.org/10.54254/2755-2721/2025.ast26989
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

ZIP-CodeLevel Drivers of EV Adoption in Washington: Socioeconomics, Urbanization, and Charger Proximity (20202025)

Yifei Wang, Ling Jin, Ying Xiong
Applied and Computational Engineering
Electric Vehicles and Infrastructure
article

ZIP-CodeLevel Drivers of EV Adoption in Washington: Socioeconomics, Urbanization, and Charger Proximity (20202025)

Yifei Wang, Ling Jin, Ying Xiong
article en

Abstract

Electric vehicles (EVs) offer lower noise and zero tailpipe emissions compared to traditional internal combustion engine (ICE) vehicles. This study quantifies EV adoption across Washington State using ZIP-codelevel data from 20202025. Multivariable linear regressions relate the monthly change in EV share to socioeconomic factors, urbanization, family structure, and the roll-out of public charging infrastructure. Results indicate that adoption growth is positively associated with higher per-capita income, higher educational attainment, greater urbanization, and larger average family size. Proximity to infrastructure matters: the number of newly built local stations (020 miles) is positively associated with adoption growth, whereas a higher number of newly built distant stations (30 miles) correlates negatively, consistent with rurality and limited access. By providing a comprehensive ZIP-codelevel analysis, the study addresses aggregation bias common in county-level work and reveals localized patterns that broader geographies can obscure. The findings offer policy-relevant evidence for charger siting and for targeting incentives.

Applied and Computational EngineeringVol. 197(1)
University of Electronic Science and Technology of China (CN), University of Toronto (CA), Raffles Institution (SG)
Openalex Percentile: Top 76%
Electric Vehicles and Infrastructure
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ZIP-CodeLevel Drivers of EV Adoption in Washington: Socioeconomics, Urbanization, and Charger Proximity (20202025) — Yifei Wang, Ling Jin, et al. · Applied and Computational Engineering (2025) | TGRS Research Map | TGRS