Policy pathways to electric vehicle adoption in Chile, a scenario-based analysis of economic and environmental outcomes
チリにおける電気自動車普及への政策経路：経済・環境アウトカムのシナリオ分析 (AI 翻訳)
César Arancibia, Magdalena Jensen, Richard Riffo Sandoval, Lorena Pradenas
🤖 gxceed AI 要約
日本語
本研究は、チリの電気自動車（EV）普及がもたらす経済・環境影響を、2025～2050年の3つの政策シナリオ（持続可能、保守的、非持続可能）で評価。機械学習モデルを用いて、補助金・充電インフラ拡充により2035年にEV販売100%達成可能とし、CO2排出28%削減、従来車比で年間コスト18%低減を示した。寒冷地でも再エネ主電源でEVの優位性を確認。
English
This study evaluates the economic and environmental impacts of electric vehicle (EV) adoption in Chile under three policy scenarios (sustainable, conservative, non-sustainable) from 2025 to 2050. Using machine learning models, it finds that aggressive subsidies and charging infrastructure expansion could achieve 100% EV sales by 2035, reducing transportation CO2 emissions by 28% and annual costs by 18% compared to conventional vehicles, even with a 25% energy penalty from cold climate heating, given Chile's renewable-dominated grid.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本はEV普及で世界に後れを取っているが、本論文は再エネ比率の高い国での政策設計の参考になる。特に、補助金と充電インフラの同時展開の重要性を示す点は、日本のEV戦略にも示唆を与える。
In the global GX context
As global EV adoption accelerates, this paper provides a rare scenario-based analysis for an emerging economy with abundant renewables and lithium resources. It offers insights for countries designing integrated policy packages (subsidies + infrastructure) and highlights how renewable grids can support electrification with minimal generation capacity increase.
👥 読者別の含意
🔬研究者:Provides a robust integrated modeling framework (ML + policy scenarios) for EV adoption assessment in emerging markets, useful for comparative studies.
🏢実務担当者:Demonstrates the cost competitiveness of EVs under supportive policies, relevant for corporate fleet transition planning in countries with high renewable penetration.
🏛政策担当者:Offers evidence that strong policy intervention can achieve rapid EV adoption while cutting emissions and consumer costs, with implications for subsidy design and infrastructure investment.
📄 Abstract（原文）
Purpose This study evaluates the economic and environmental impacts of electric vehicle adoption in Chile, examining how different policy scenarios could influence battery electric vehicle market penetration, energy demand, emissions and consumer costs through 2050. The research addresses the critical need to understand the viability of electromobility in an emerging market with unique characteristics, including abundant lithium resources and a renewable-dominated energy matrix. Design/methodology/approach Three scenarios (sustainable, conservative and non-sustainable) for 2025–2050 were developed using machine learning models (Extreme Gradient Boosting regression and ExtraTrees) and international subsidy frameworks adapted to Chilean conditions, with Gross Domestic Product-adjusted factors. The methodology integrates vehicle demand projections, energy consumption calculations accounting for Chile's cold climate heating requirements, emissions analysis considering the national energy mix and lithium extraction impacts, and cost assessments for consumers. Findings Aggressive policy intervention (25% purchase subsidies and expanded charging infrastructure) could achieve 100% battery electric vehicle sales by 2035, reducing transportation carbon dioxide emissions by 28%. Chile's renewable-dominated grid can support full electrification with only 4% of national generation capacity. Despite a 25% energy penalty from heating in cold climates, conventional vehicles produce 184% higher emissions than battery electric vehicles and annual costs are 18% lower under supportive policies. Originality/value This represents the first systemic scenario-based electric vehicle adoption analysis specifically adapted to Chilean conditions, quantifying the impact of cold climate on electric vehicle efficiency and developing an integrated modelling approach for policy impact assessment in emerging markets with renewable energy advantages.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1108/meq-09-2025-0635first seen 2026-06-25 04:37:28
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