This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 41–60 of 378 papers
Black J.
An ex post policy evaluation of urban transport decarbonization toward net-zero emissions in Canberra, ACT, Australia. It examines how effectively implemented transport policies delivered actual emission reductions. Details are limited with…
Aleksander Jagiełło, Agnieszka Szmelter-Jarosz, Marcin Wołek
A case study of a Polish bus operator analyzes electrification processes using ARIS software and assigns KPIs to subprocesses like fleet development, charging infrastructure, and renewable energy generation. It presents a governance model l…
Xiaofan Wei, Zhe Zhang, Chao Li +2
This study estimates the maximum carbon reduction achievable through shared on-demand transit (ODT) using integer linear programming and multi-passenger optimization, then applies XGBoost with SHAP to link reductions to built-environment ch…
Yehui Li, Xueyuan Cui, Chongqing Kang +2
The authors turn on-board EV chargers into intelligent agents for distributed vehicle-grid coordination under tight hardware constraints. On a hardware-in-the-loop platform, their framework cuts memory use by 96.1% and communication overhea…
Tingjie Ba, Hongyi Zeng, Wanjun Wu +2
This study proposes a low-carbon coordinated dispatch framework for source–grid–load–storage systems that uses a time-varying carbon emission responsibility factor (CERF) as a guidance signal instead of electricity prices. A pre-dispatch st…
Raza, Kashif, ', Виктория, Hosen, Md Sazzad
This study characterizes prismatic NMC(631) EV cells using incremental capacity analysis (ICA) and electrochemical impedance spectroscopy (EIS) across three temperatures and varied cycling conditions. Cells cycled at 45°C suffered catastrop…
Jiayu Ni, Yanbo Che, Yingshu Liu +1
This study enhances a dynamic Bass diffusion model by integrating a social network effect factor that captures interpersonal information diffusion in EV adoption. Validated on historical EV ownership data from Beijing, the model forecasts m…
Abhi Mondal
This mixed-methods study examines how customized financial products—green auto loans, flexible leasing, battery subscriptions, usage-based financing, green bonds, and EV-specific insurance—affect consumer decisions and EV adoption. Findings…
Yuchen Liu, Stefan Pfenninger-Lee, Tosiyuki Nakaegawa +1
Simulating rooftop PV coupled with EV batteries across 5,000 global grid cells using hourly meteorology and climate-driven demand, the authors find PV-EV systems can meet up to 84% of annual building and mobility electricity demand. Self-su…
Yongliang Luo, Worawat Sa-Ngiamvibool, Supannika Wattana +1
A LEAP bottom-up model calibrated to 2024 statistics compares four Guangxi transport pathways to 2060. BAU peaks at 48.0 Mt around 2036 and stays at 37.4 Mt in 2060, while policy pathways peak by 2027 and reach 11.7–21.5 Mt (42–69% below BA…
Ebrahimi M.
This study analyzes how electrifying heavy-duty trucks affects greenhouse gas emissions in Ontario, Canada. It assesses the decarbonization potential of freight electrification at a regional scale, offering evidence on transport-sector emis…
Qian C.
A study assessing greenhouse gas emissions linked to electric vehicle adoption in Hong Kong. It examines the environmental impact of EV development, likely accounting for the local power mix and transport system. The work tests whether EV t…
Sumeet Kishore, Rahul Kumar Mahato, Nitesh Kumar Thakur +5
This study compares diesel and battery-electric haul trucks under similar surface-mine conditions, covering fuel/electricity use, CO2 emissions, OPEX, maintenance, life-cycle costs, NPV and payback. Electric trucks cut annual emissions by ~…
Wu R.
This work optimizes EV charging schedules to jointly minimize electricity cost and greenhouse gas emissions. It leverages time-varying power prices and grid emission factors through smart charging timing. Grid load and renewable integration…
yunus furuncu
Using IEA Global EV Data 2024, this study applies a Gaussian Mixture Model to 31 countries across EV sales share, stock share, and public charging infrastructure. It identifies three clusters—Early, Advanced, and Frontier Transition Economi…
Selma Elmgren, Carlos Lopes
The Swedish Energy Agency proposes a consumer label for passenger cars and light commercial vehicles to support electrification. It adopts a single colour scale based on in-use energy efficiency, avoiding practical difficulties of well-to-w…
Parth Patel
This PRISMA-based systematic review synthesizes 2018–2026 literature on multi-energy microgrids for EV charging across three domains: hybrid AC/DC converter topologies and constant-power-load stability control; V2X flexibility services with…
Egle Norgren, Jelena Stankevičienė
This paper compares renewable energy deployment in road transport across Finland and the Baltic States (Estonia, Latvia, Lithuania) from 2010–2024. Despite shared EU obligations, Finland reached a 20.3% RES share in transport by 2024 with s…
Muneer Nusir, Sahar Mohammad Al Mashaqbeh, Sadeq Damrah +1
This qualitative study assesses policy factors for EV adoption in Jordan through interviews with 12 experts from government, academia, and industry. It proposes the ISEVA framework integrating five variables—safety compliance, infrastructur…
Arahim Zuniga, Kristen E. Brown, Ivonne Santiago
A study analyzing least-cost decarbonization pathways for US light-duty vehicles and electricity generation. It integrates transport electrification with power-sector decarbonization to identify cost-efficient transition routes. Details are…
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