Establishing robust charging infrastructure is crucial for electric vehicle (EV) adoption. This study addresses the lack of systematic literature reviews examining the global charging infrastructure research landscape with a comprehensive review of English literature published between 2017 and 2023. We screened 12237 records, and analyzed 137 peer-reviewed and 31 grey literature studies. Findings reveal a mean and median public charging demand of 135 and 23 EVs/charger respectively – that is, a much more efficient utilization of chargers than the current public charging global average (10 EVs/charger). The differences are explained by aggregation of charging strategies – fast and super-fast charging can support 5 to 10 times as many vehicles per charger – but also a wide range of assumption used across studies, apparently deviating from actual deployment. We also identify a need for more forward-looking research given evolving technologies and policy ambitions. Further research is necessary for underrepresented regions like Africa and Latin America, and different vehicle types, such as heavy and light-duty commercial vehicles. Recommendations to the research community, policymakers, and practitioners include exploring complementary metrics beyond the widely used EVs/charger and addressing ambiguous charging definitions.

In this paper we show that OpenAI's Large Language Model (LLM) GPT perform remarkably well when used for title and abstract eligibility screening of scientific articles and within a (systematic) literature review workflow. We evaluated GPT on screening data from a systematic review study on electric vehicle charging infrastructure demand with almost 12,000 records using the same eligibility criteria as human screeners. We tested 3 different versions of this model that were tasked to distinguishing between relevant and irrelevant content by responding with a relevance probability between 0 and 1. For the latest GPT-4 model (tested in November 2023) and probability cutoff 0.5 the recall rate is 100%, meaning no relevant papers were missed and using this mode for screening would have saved 50% of the time that would otherwise be spent on manual screening. Experimenting with a higher cut of threshold can save more time. With threshold chosen so that recall is still above 95% for GPT-4 (where up to 5% of relevant papers might be missed), the model could save 75% of the time spent on manual screening. If automation technologies can replicate manual screening by human experts with effectiveness, accuracy, and precision, the work and cost savings are significant. Furthermore, the value of a comprehensive list of relevant literature, rather quickly available at the start of a research project, is hard to understate. However, as this study only evaluated the performance on one systematic review and one prompt, we caution that more test and methodological development is needed, and outline the next steps to properly evaluate rigor and effectiveness of LLMs for eligibility screening.

Electromobility has gained momentum in the last years following the efforts to reduce transportation-related emissions. In this context, efficient charging infrastructure is vital to foster the expansion of electric vehicles. This paper presents a standardized framework for micro-scale analysis of potential charging locations for electric buses aiming at easing the analysis process and promoting the expansion of electric buses. The framework is tailor-made for the Municipality of Stockholm and tested in two city-centre public transport hubs, namely Odenplan and Slussen. However, the framework can be used in other locations by implementing minimum changes. Connecting charging stations to the power grid is identified as the main drawback in city-centre locations due to their high impact on the grid. Lack of available capacity at nearby connection points results in long distance connections, reaching up to 1 km in some cases. Such connections impact the overall cost of electrification directly, as they may account for up to 63% of the total cost. Although other issues regarding space availability and operational efficiency also need to be addressed, such as the lack of enough dwell time to charge the batteries, the framework proves the suitability of these inner-city locations as charging points.

This paper focuses on the potential impact of various options for decarbonization of public bus transport in Stockholm, with particular attention to electrification. An optimization model is used to locate electric bus chargers and to estimate the associated carbon emissions, using a life cycle perspective and various implementation scenarios. Emissions associated with fuels and batteries of electric powertrains are considered to be the two main factors affecting carbon emissions. The results show that, although higher battery capacities could help electrify more routes of the city's bus network, this does not necessarily lead to a reduction of the total emissions. The results show the lowest life cycle emissions occurring when electric buses use batteries with a capacity of 120 kWh. The fuel choices significantly influence the environmental impact of a bus network. For example, the use of electricity is a better choice than first generation biofuels from a carbon emission perspective. However, the use of second -generation biofuels, such as Hydrotreated Vegetable Oil (HVO), can directly compete with the Nordic electricity mix. Among all fuel options, certified renewable electricity has the lowest impact. The analysis also shows that electrification could be beneficial for reduction of local pollutants in the Stockholm inner city; however, the local emissions of public transport are much lower than emissions from private transport.

This study provides a comparative assessment of carbon-pricing instruments for the Mexican electricity sector, contrasting a carbon tax with an emissions trading scheme (ETS). The assessment is performed in terms of economic impacts and political feasibility. Model-based scenarios considering different price and quantity levels are analyzed on Balmorel-MX, a cost optimization bottom-up model of the Mexican electricity system. The political feasibility is evaluated using an online survey and interviews with representatives of relevant stakeholder groups. The assessment suggests that an ETS is the most appropriate instrument for the Mexican case. We recommend to set the cap as 31% abatement in relation to a baseline, which is suggested to be 102 MtCO2 by 2030, given the business-as-usual baseline used as reference by the Mexican government (202 MtCO2) is found to leave cost-effective abatement potential untapped. An emission trading system with such design has higher cost-efficiency and lower distributional effects than a carbon tax at equivalent ambition level (15 USD/tCO2). The political feasibility analysis confirms the assessment, as it is in line with the priorities of the stakeholder groups, allows earmarking carbon revenue and avoids exempting natural gas from carbon pricing.

Electrification of public bus transport services is currently being explored in various demonstration projects around the world. The objective of this paper is to (i) gather insights from electric bus demonstration projects with a focus on charging technologies (conductive, inductive) and strategies (slow, fast); and explore the role these factors may play as upscaling of electric bus deployment is considered. The focus is on the Nordic region. A survey with stakeholders involved with electric bus demonstration projects is performed for understanding the benefits and drawbacks of each solution, and identifying the main themes emerging from project implementation and upscaling. Advantages of the conductive charging include the maturity of the technology and its higher maximum charging power compared to currently available inductive alternatives. On the other hand, inductive technology entails other benefits, such as the lack of moving parts which could reduce the maintenance costs for infrastructure, as well as minimal visibility of the equipment. The main issues likely to impact the upscaling of electric bus use are related to the maturity, cost-effectiveness, compatibility, and charging efficiency of the available technologies.

This thesis addresses the challenge of road transport electrification using a systems approach for the particular context of Stockholm’s public transport system. The objective is to identify the benefits of large-scale bus electrification on energy efficiency and greenhouse gas emissions, as well as the cost and planning considerations required for achieving such a shift. Quantitative and qualitative methods are deployed for answering the research questions, including the development and use of an optimisation model, survey research, and interviews. 

The results of the optimisation model developed for this thesis show that an optimal system configuration is obtained with a combination of electricity and biodiesel. The high energy efficiency of electric buses would lead to a significant reduction of energy consumption in Stockholm, even if not all bus routes in the network are electrified. Although larger battery capacities could support the electrification of more bus routes, this does not necessarily lead to lower environmental impact. In any case, electricity from renewable sources should be used to maximise emission reductions. 

The results also show that the annual costs necessary to invest in electric buses can be balanced by lower fuel costs. An effective utilisation of the charging infrastructure is of high priority in order to justify the costs of the required investments. The model results confirm the benefits of creating a dense initial network of charging stations in the inner city’s public transport hubs, which would facilitate the electrification of multiple routes and high infrastructure utilisation at lower costs. 

The survey and interviews with stakeholders indicate that multiple issues affect the choice of charging technology, not just costs. Compatibility, reliability, bus dwell time, as well as weather conditions and visual impact are some of the additional aspects taken into account. The introduction of electricity tax exemption for electric buses, the expansion of the electric bus premium to include private stakeholders, as well as the expansion of infrastructure investment subsidy programmes are among the policy instruments suggested for assisting a faster introduction of electric buses into Stockholm’s public transport system. 

Although the focus is on Stockholm, the conclusions of this work can be applicable to other cities in Sweden and around the world, which also face the challenge of making public transport a more sustainable option.

This study analyses the impact of the rising availability of steel scrap on the future steel production up to the year 2100 and implications for steel production capacity planning. Steel production processes are energy, resource, and emission intensive, but there are significant variations due to different production routes, product mixes, and processes. This analysis is based on the development of steel demand, using the Steel Optimization Model, which provides a region-detailed representation of technologies, energy and material flows, and trade activities. It is linked to the Scrap Availability Assessment Model which estimates the theoretical steel scrap availability. Aggregated crude steel production is estimated to evolve into an almost balanced split by 2050 between the primary production route using iron ore in the blast oven furnace and the secondary route using mostly steel scrap in the electric arc furnace. By 2060, the share of secondary steel production will exceed the share of primary steel production globally. The results also estimate a global increase in scrap use from 611 Mtonnes in 2015 to 1500 Mtonnes in 2050, with the highest growth being for post-consumer scrap. In 2050, almost 50% of post-consumer scrap is expected to be traded, with the main exporter being China and major importing regions being Africa, India, and other developing Asian countries. The results provide valuable insights on scrap availability and capacity development at the regional level for producers contemplating new investments. Regional availability, quality, and trade patterns of scrap will influence production route choices, possibly in favor of secondary routes. Also, policy instruments such as carbon taxation may affect investment choices and favor more energy-efficient and less carbon-intensive emerging technologies.

Urban regions account for 64% of global primary energy use and 70% of carbon emissions. For that reason, options to decarbonize urban environments are receiving increasing attention. In this context, public transport shall play a key role in decarbonizing urban road transport. One efficient way to achieve that is shifting towards clean fuels and modern electric buses, an option that is already under implementation in several cities around the world. In this paper, the basis for developing a dynamic optimization model for establishing charging infrastructure for electric buses is presented, using Stockholm, Sweden, as a case study. The model places constraints depending on the bus stop type (end or middle stop) which affects the time available for charging at each particular location. It also identifies the optimal technology type for the buses: conductive or inductive. In addition, the electric buses compete with buses run on biogas or biodiesel. In this paper, we present the results of a cost minimization scenario with constraints placed on the available charging time and power, differentiated between end stops and major public transport hubs. The mean charging time is 7.33 minutes, with a standard deviation of 4.78 minutes for all bus stops. The inner city bus routes require less charging time, which ranges on average at around 3 minutes. The installation of chargers at the locations proposed in the model would require scheduling adjustments and careful planning for the density of charging occasions.