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For instance, Europe is embracing the shift to zero-emission mobility. The ''fit for 55 packages'' proposed by the European Green Deal aims to reduce at least 55% of GHG emissions by 2030 compared to 1990 levels7. One of the document that is part of ''fit for 55'' is the Alternative Fuels Infrastructure Regulation (AFIR)8 that is centred in the development of electric mobility. AFIR defines targets for minimum installed capacity in public charging stations that should be higher than 1.0 kW per per battery electric vehicle (BEV) and 0.66 KW per plug-in hybrid electric vehicle (PHEV). Considering the abovementioned, almost all internal combustion engine (ICE) vehicle sales are expected to be banned in Europe by 20359.
Considering the most recent data, Global EV sales more than doubled, driven by policy attention. It represents a global EV sales share of 8.57%, which accounts for 6.6 million units. Also, this stands current for over 16.4 million of BEVs (68%) and PHEVs (32%) on the roads. China and Europe lead the EV market, accounting for 85% of the global fleet, followed by the United States10.
Some scenarios in the literature cover different approaches to predict the future of electric mobility and sometimes consider hurdle factors like consumer behaviour in the trajectory. These range from machine-learning tools and diffusion models, which can be subdivided into stochastic and population models12. While the stochastic models are based on consumers'' preferences considering the purchase decision, the population models consider the market diffusion curve or different growth rate scenarios. Nevertheless, both are less accurate for long-term predictions than the statistical model13,14.
Furthermore, the datasets described in this study include an EV forecast concerning the stock, sales, electricity demand, and the number of public charging points in the World, Europe, Portugal, Denmark, Greece, and Slovenia. The analysis is performed by growth scenarios on a five-year increment to 2050. Further, the scenarios presented in this study, if not obtained from available sources, the values for some years have been applied to the regression model, and estimated assumptions are used. Figure 1 illustrates the main steps approached for EV demand projections.
Schematic method approach.
EV Forecast is based on existing production forecasts mainly from reports by public entities and consultants, which considers market and policy targets aiming to achieve carbon neutrality for different time horizons in the context of EV4EU member countries (Portugal, Denmark, Greece and Slovenia) and worldwide. In terms of analysis, these countries are interesting due to the cultural differences, relative position in Europe and the stage of adoption of electric vehicles.
Several reports have presented projections regarding the evolution of EVs, considering diverse aspects as follows. The input data and sources used are publicly available and described in Table 4. the data have been collected, organized and computed based on existing references. Values not available in the references have been computed using Eqs. (1) and (2).
The input data sourced from the available literature is descrived in the following paragraphs. The missing values regarding EV evolution scenarios were obtained by interpolation function for different time horizons. Figure 2 shows one EV scenario built in the case of worldwide.
IEA3 addresses three scenarios until 2030: (i) Announced pledge Scenario (IEA-APS) based on climate policy pledges up to 2030 and driven by the economic and technological development in the coming years impacting the EV market. (ii) Staded Policies Scenario (IEA-SPS) embraces current policy plans up to 2030. (iii) Net Zero Emissions by 2050 Scenario (IEA-NZE) considering the main energy-related targets of the united nations'' sustainable development goals (SDGs).
Bloomberg4 assesses three scenarios by 2050: (i) Economic Transition Scenario (BBG-ETS) driven by the economic and technological development in the coming years impacting the EV market; (ii) Net Zero Scenario (BBG-NZS) analyses the main path to zero-emission in the transport sector and considers the economy a decisive factor for achieving carbon neutrality by 2050.
IRENA5,15 presents three scenarios: (i) 1.5°C scenario (IRN-PRT) pathway to reach the 1.5°C targets of the Paris Agreement through six technological avenues comprising electrification of the sectors, increasing renewable energy generation and improvements in energy efficiency in the context of the energy transition. (ii) Planned Energy Scenario (IRN-PES) is based on the energy plans established by governments besides other policy targets in this field. (iii) Transforming Energy Scenario (TES) proposes an ambitious scenario considering renewable source penetration and energy efficiency improvements.
Global EV evolution Scenarios. (a) Global EV Stock scenarios. (b) Global EV sale scenarios. (c) Global EV electricity demand scenarios. (d) Global EV charging point scenarios.
Different assumptions were considered, and interpolation was applied for missing values in some years. The results were adjusted for each geo-zone of Europe in order to obtain a fair comparison between projections. Furthermore, constant car stock(333.3 million) and new car registrations (14.5 million/year) are assumed for values obtained from percentage sales until 2050.
Virta16 analyses two scenarios, "Low estimates" (VRTLOW) and "High estimates" (VRT-HGH). Both differ from each other mainly by the deployment of "EVs romaning around Europe" (EU-28).
Fraunhofer17 proposes a scenario (FRH-SCN) from EV sales that could reach 100% share in (EU-28+NO+IS+CH) and sales growth fitting the S-shaped diffusion curve adjusted on the baseline of Norwegian EV sales.
Eureletric18 in association with EY analyses the increasing penetration of EVs in Europe (EU-28+NO+CH) based on the charging infrastructure considering the impact on the electricity grid. It also considers the key participation of industry leaders in the evolution of EVs from market experience.
European Alternative Fuels Observatory (EAFO)19 Following three scenarios for 2050 in (EU-28): (i) ZEV Base Case (EFO-ZBV) considers a medium adoption of zero-emission vehicles (ZEV); (ii) PHEV Bridging (EFO-PHV) assumes a significant increase in the market share of PHEVs around 2030. (iii) ZEV leader (EFO-ZLD) is based on the high adoption of ZEV.
Strategy&20 reports the (SPC-SCN) scenario based on the declining global car stock of over 11% driven by car-sharing adoption in (EU-27+NO+GBR+CH).
Strategy& in partnership with European Association of Automotive Suppliers21 (CLEPA) presents three scenarios for 2040 in (EU-28 + EFTA): (i) "Mixed-technology scenario" (CLP-MTS) based on the government recovery post-COVID, consider a 50% reduction of CO2 emissions from 2020 to 2030.; (ii) "EV-only scenario" (CLP-EVS) addresses the projections by STEP in IEA10, fit for 55 package7 and incentives for EV adoption and charging infrastructure development.; (iii) "Radical scenario" (CLP-RAD) takes into account a total 100% reduction in CO2 emissions by 2030.
ElementEnergy22 covers two scenarios for 2050 that consider price parity a critical factor for EV adoption in (EU-28 + EFTA). (i) "Baseline" (ELM-BAS) assumes price parity will be reached in 2030 only for passenger cars; (ii) "2028 Purchase price parity" (ELM-PPP) goes further and considers price parity to be achieved in 2030 for all segments.
ChargeUp23 presents three scenarios following different shares of charging infrastructure deployment in (EU-27). Further, it takes into account the EV adoption based on current policies and EV strategies of the leading European automotive industries, production forecasts of market intelligence companies and some assumptions: (i) ChargeUP-minimum (CHU-MIN) set a minimum number of charging point stations; (ii) ChargeUP-AC station (CHU-ACS) assumes a high share of AC charging points; (iii) ChargeUP-higher share (CHU-HPS) also considers a high share (45% instead of 35% in the CHU-MIN scenario).
Transport & Environment24 discusses the scenario (TeE-SCN) in (EU-27), emphasising the impact on the development of charging infrastructure in Europe with increasing EV stock to reach the European target of 100% ZEV registration for passenger cars and vans until 2035.
International Council on Clean Transportation (ICCT)25 analyses the evolution of EV stock by the scenario (ICT-SCN) in (EU-27) until 2030 based on the goal of reaching 100% ZEV sales by 2030 through the roadmap model26.
Regarding the EV evolution scenarios in Greece are based on four uptake scenarios covering market and policy decisions on projections as described:
NECP uptake27 scenario uses the targets set by the Greek authorities'' National Energy and Climate Plan (NECP) as a constant.
2030 ban uptake28 scenario is based on a recent decision by the Greek authorities that bans all new internal combustion engine (ICE) car (non-PHEVs) sales by 2030.
C-curve uptake scenario is determined based on the corresponding mathematical model and uses fitting on past data (from 2015 to 2021) to project the likely uptake of new BEVs and PHEVs.
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