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on Transport Economics |
| By: | Putra Farrel Azhar |
| Abstract: | To achieve the federal goal to make half of all new vehicles sold in the U.S. in 2030 zero-emissions vehicles, the U.S. Department of Transportation's (DOT) Federal Highway Administration (FHWA) has employed the National Electric Vehicle Infrastructure (NEVI) Formula Program, which aims to promote an interconnected network of publicly accessible electric vehicle (EV) charging stations. By analyzing panel data on a subset of U.S. counties, this paper examines the relationship between different classes of EV charging stations and plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs). Through an instrumental approach to identify potential endogeneity, this study suggests that public charging stations and the implications of the NEVI Formula Program might not provide the optimistic benefit expected in achieving the federal goal. This finding indicates the need to reevaluate current strategies and explore additional incentives to enhance EV adoption and the effectiveness of public charging infrastructure. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.03608 |
| By: | Ramadoss, Trisha; Tal, Gil |
| Abstract: | To meet zero-emission vehicle targets, people will have to adopt electric vehicles and convert their entire fleets. In the United States and California, most households own two or more vehicles; most of these households will need to switch their traditional vehicles for plug-in electric vehicles (PEVs). However, most of the research on PEV adoption has focused on people acquiring their first PEV. This work is the first to examine households’ decision to maintain at least two PEVs in their household fleets. Utilizing a multi-year survey of PEV adopters between 2012 and 2020, 3, 039 respondents who acquired a vehicle after obtaining an initial PEV are identified. Respondents are divided in two groups: those who reverted to an internal combustion engine vehicle (Single PEV) and those who added an additional PEV (Multi PEV). Modelling the groups using binary logistic regression, several factors that differentiate Single from Multi PEV households are identified. Compared to Single PEV, Multi PEV households are more likely to have owned previous PEVs, live in detached single-family homes with solar, own an SUV prior to their initial PEV, purchase a Tesla for their initial PEV, and use the initial PEV for commuting. View the NCST Project Webpage |
| Keywords: | Social and Behavioral Sciences, Electric vehicles, synthetic population, EV adoption, electric vehicle market |
| Date: | 2024–10–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt6pg9w6sc |
| By: | Simmons, Richard; Weed, Caleb; Rodgers, Michael |
| Abstract: | The EVALUATE (Electric Vehicle Assessment and Leveraging of Unified models toward AbatemenT of Emissions) project (Phases I and II) develops a rigorous methodology involving a high-fidelity system of systems model (i.e., vehicle powertrain, EV charging profiles and grid dispatch datasets) for the purpose of forecasting the emissions outputs of a class of vehicles and use cases. Phase I findings explored urban trips by households that operate light duty vehicles (LDVs) for daily personal use. Phase II, presented here, focuses on a series of targeted case studies that extend prior work from LDVs operated by individuals to service-oriented vehicles operated by small and medium businesses. Vehicles used in the present study are representative of public service fleets including the following: pickup trucks, vans, Medium Duty (MD) delivery vehicles, and refuse trucks. In one of the study’s simulations for a MD use case where a specific marginal grid generating resource is identified on an hourly basis as the grid’s means of supplying a particular EV charging event, estimated CO2 emissions could be as much as 42% lower than a conventional gasoline vehicle, or as much as 24% higher than a conventional gasoline vehicle. This large variance is purely a function of when and how quickly the vehicle is recharged, and upstream grid factors. This study reveals key insights: (1) Higher temporal resolution is important to develop more accurate estimates of EV CO2 emissions. Along with this, EV charge management is imperative for all use cases, and has profound implications on infrastructure and emissions; (2) Hybrid Electric Vehicles (HEVs) often performed as well as EVs in contemporary simulations on the basis of emissions benefits, suggesting that consideration of an array of vehicle technologies is important; (3) There is a growing need to focus on higher rate EV charging applications (e.g., DCFC), and related implications on grid demands and energy storage, as proxied by large vehicle batteries; and (4) The trend toward increasing electrification of the transportation sector will continue in conjunction with electrification across other sectors (e.g., buildings, data centers, industry). As such, associated cross-sector planning and study of concomitant emissions must be considered in context of other grid trends. Primary contributions of this effort are the development of new methodologies, integration of sub-system models and independent data sources, and decision support tools that estimate the environmental impacts of vehicle electrification. The study’s methodologies and use cases can enhance understanding and scale-up in additional EV-grid applications, sectors and regions. View the NCST Project Webpage |
| Keywords: | Engineering, Social and Behavioral Sciences, Electric vehicles, low carbon transportation, emissions, CO2, EV charging, marginal emissions, electric grid |
| Date: | 2024–12–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt0js485bz |
| By: | Simmons, Richard; Weed, Caleb; Rodgers, Michael |
| Abstract: | This research explores electric vehicle (EV) and grid interactions with a focus on CO2 emissions for future scenarios where EVs comprise growing market shares (e.g., 10% of the overall fleet mix). A major contribution of this effort has been to develop a methodology that integrates sub-system models and datasets that have previously stood alone, namely models and data that characterize: vehicle energy consumption, travel demands, vehicle charging, and temporal emission profiles associated with electric power generation dispatch. This convergence research helps quantify the relative emissions of light duty vehicle use and charging during various times of day to enable comparison of EV modes against one another and against conventional vehicle baselines. An initial use case involving light duty commuter and recharging scenarios has been explored as a means of validating and tuning the methodology. Under certain simulated scenarios, observed marginal emissions can be as much as 20% lower in the overnight hours compared to marginal CO2 emissions experienced during an identical charging event during the daytime. This study also confirms that marginal CO2 assumptions generally yield higher CO2 impacts than identical simulations that assume weighted average emissions. This variance is broad, ranging from 22% less to 97% greater, depending on a host of case-sensitive factors. These findings suggest that it will be essential to coordinate charging schedules and consider upstream grid implications in order to reduce the environmental impacts of EVs. By quantifying technical parameters related to both the magnitude and the range of possible emissions impacts, the study’s findings can be useful for education and awareness by all EV users, and will help decision-makers consider the importance of emission rate assumptions and the temporal granularity of the tools and data. More specifically, stakeholders should be incentivized to charge when marginal emissions are lowest whenever possible. This idea also has important implications about the location, type, cost and ownership models for tomorrow’s charging infrastructure. Translating and operationalizing this type of guidance will require some combination of education, access to rigorous and clear decision-support tools, signals between stakeholders (e.g., utilities and consumers), and behavioral change. View the NCST Project Webpage |
| Keywords: | Engineering, Social and Behavioral Sciences, Electric vehicles, low carbon transportation, emissions, CO2, EV charging, marginal emissions, electric grid |
| Date: | 2024–12–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt9kh490xz |
| By: | Martinez, Natalie; Guarino, Jenny |
| Abstract: | Our project was largely inspired by the report Decarcerating Transportation - a Mobility Justice Framework, by the Anti-Police Terror Project. This report gives background on the link between transportation and the criminal legal system and the negative repercussions especially for communities of color. It also provides a roadmap with concrete policy recommendations for localities to take on the task of decarcerating transportation, with the goals of removing police from public transit and traffic enforcement, universalizing accessibility to public transportation, and ending punitive systems involving fines and fees that further exacerbate financial insecurities of marginalized communities. |
| Keywords: | Social and Behavioral Sciences |
| Date: | 2024–12–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt1bc5c16h |
| By: | Daniel Thiel (Université Sorbonne Paris Nord, CEPN - Centre d'Economie de l'Université Paris Nord - CNRS - Centre National de la Recherche Scientifique - Université Sorbonne Paris Nord); Erick Leroux (Université Sorbonne Paris Nord, CEPN - Centre d'Economie de l'Université Paris Nord - CNRS - Centre National de la Recherche Scientifique - Université Sorbonne Paris Nord); Emmanuel Labarbe (UBM - Université Bordeaux Montaigne, D2iA - Dynamiques, Interactions, Interculturalité Asiatiques - ULR - La Rochelle Université - UBM - Université Bordeaux Montaigne, MICA - Médiation, Information, Communication, Art - UBM - Université Bordeaux Montaigne) |
| Abstract: | In order to reduce overtourism and traffic congestion, local authorities may have to divert recreational vehicle traffic to off-site service areas. The problem that will arise is how best to accommodate different types of users with opposing preferences in the same area, some wanting to be as close as possible to the major site to be visited, others seeking peace and quiet. We have represented their specific attitudes using a two-stage decision-making process via a conjunctive model followed by a compensatory model. We then propose to model three strategies, seeking either to optimise customer attractiveness, or profit, or space occupation, in order to define a location, capacity and price for this shared area. Using a realistic data set, the results show that economic performance follows a concave curve as a function of the population mix. Moreover, only the strategy of maximising attractiveness suggests always mixing users in the same area. |
| Keywords: | overtourism recreational vehicles service areas optimisation heterogeneous preferences, overtourism, recreational vehicles, service areas, optimisation, heterogeneous preferences |
| Date: | 2023–11–27 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04811280 |
| By: | Zarei, Ali; Kim, Changmo; Butt, Ali Azhar; Wu, Rongzong; Lea, Jeremy David; Erdahl, Jessica; Nassiri, Somayeh |
| Abstract: | Between 2017 and 2018, California experienced a series of four devastating fires, including the Camp and Carr Fires, which ranked among the most destructive fires in U.S. history. During these fires, roads were critical in the evacuation, rescue operations, goods transportation, and access to critical services. Additionally, postfire, road infrastructure became crucial for removing hazardous and nonhazardous waste from fire-affected areas to major landfills and recycling facilities. Despite the significance of pavements in this process, previous studies have not quantitatively assessed the potential damage caused to pavements by the additional trucks used in debris removal operations. This research aimed to address this knowledge gap by collecting precise traffic data for the routes taken to waste management facilities, including data on the number of trips involved in debris transportation. The traffic information was then utilized to calculate changes in equivalent single axle loads and traffic index values for pavement design. Pavement structures were obtained from the available core database. Pavement simulation results showed that of the nine studied highways, only one exhibited a reduction in cracking life of about 2 years. However, Skyway, the main artery in the town of Paradise, demonstrated a significantly accelerated fatigue cracking failure by 14.3 years. A sensitivity analysis of fire intensity showed other highway sections that were structurally adequate could be affected by larger fires. The presented methodology could be used in traffic planning as part of debris management operations to avoid vulnerable pavement sections. |
| Keywords: | Engineering |
| Date: | 2024–10–23 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt8hx274h3 |
| By: | Zhiyuan Liang (Beijing Jiaotong University); Vincent A.C. van den Berg (Vrije Universiteit Amsterdam and Tinbergen Institute); Vincent Erik T. Verhoef (Vrije Universiteit Amsterdam and Tinbergen Institute); Vincent Yacan Wang (Beijing Jiaotong University) |
| Abstract: | This study studies nudging information as a strategy that can complement or substitute externality pricing, by influencing commuter behavior through awareness of the health and environmental impacts of their choices. We develop a bi-modal model with road and metro commuters, with bottleneck congestion on the road and dynamic crowding congestion in the metro. The model further incorporates health costs and environmental externalities, particularly for road commuters. When commuters are homogeneous, our findings indicate that nudging information generates positive welfare effects except in scenarios with extremely high crowding effects in the metro system. Moreover, nudging information can consistently complement flat road tolls by integrating information and toll schemes to enhance the system’s social welfare impact. By adding heterogeneity in environmental preferences, car types, and income, the study further highlights that the effectiveness of such strategies depends on the varied behavioral responses from diverse individuals. Even when the crowding effect is relatively small with heterogeneity, nudging information may result in negative welfare effects by causing welfare-reducing swaps in road commuters’ departure patterns; in such cases, it fails to complement flat tolls effectively. |
| Keywords: | Congestion; Emissions; Nudging information; Bi-modal; Heterogeneity |
| JEL: | D8 L91 Q53 |
| Date: | 2024–12–31 |
| URL: | https://d.repec.org/n?u=RePEc:tin:wpaper:20240081 |
| By: | Jaller, Miguel; Thorne, James H.; Rivera-Royero, Daniel; Whitney, Jason; Hu, Alexander Kenichi; Saha, Ayush |
| Abstract: | This project examines multi-hazard risks and the performance of emergency evacuation routes in California using spatial synthesis, mapping, modeling, and performance analysis techniques. It enhances evacuation planning by analyzing road networks under natural hazard scenarios. Key tasks included: 1. Collecting and organizing evacuation route data for 190 cities, revealing that only 23 had comprehensive GIS maps, highlighting gaps in current planning. 2. Assessing road network performance under various hazards for 450 cities, identifying high-risk areas, and classifying cities based on risk levels and concentration. 3. Analyzing evacuation routes during the 2018 Camp and Thomas fires, using mathematical modeling and Omniscape to assess bottlenecks and evacuation efficiency. 4. Evaluating evacuation route performance for different population segments and proposing improvements, including using public transit for future wildfire evacuations. The findings provide actionable insights for improving emergency evacuation strategies in the state. View the NCST Project Webpage |
| Keywords: | Engineering, Social and Behavioral Sciences, Risk, resilience, wildfire, multi-hazard, evacuation, California, spatial index |
| Date: | 2024–12–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt72f801mf |
| By: | Stathis Devves; Angelos Alamanos; Phoebe Koundouri |
| Abstract: | The terrestrial transportation sector, including passengers, buses, and trains, is becoming an increasingly complex field in terms of decarbonization, requiring science-driven, data-based solutions to address its energy and emissions challenges effectively. Greece exemplifies these challenges, as its transportation sector has been slow in transitioning towards decarbonization, despite the country's commitments. Factors such as dependence on conventional fuels, infrastructure inefficiencies, and policy gaps exacerbate the situation, highlighting the urgent need for comprehensive modeling and assessment tools. This research presents a detailed assessment of Greece's transportation sector, focusing on energy demand and associated greenhouse gas (GHG) emissions, per use and per fuel type. Leveraging the Low-Emission-Analysis Platform (LEAP) model, we analyze the sector's fuel mix across various uses at a national scale, marking, to the best of our knowledge, the first such effort for Greece. The model is tested under Shared Socioeconomic Pathways (SSPs) scenarios: SSP1 (sustainability-focused), SSP2 (moderate progress), and SSP5 (fossil-fueled development), projected to 2050. Our findings reveal critical insights into how different decarbonization pathways could reshape Greece's transportation sector. The key outcomes discussed include variations in energy consumption, emission trajectories, and the feasibility of achieving national and EU decarbonization targets under diverse socio-economic conditions. This work aims to support policymakers in designing robust, forward-looking transportation strategies aligned with sustainability objectives. |
| Keywords: | Transportation Decarbonization, LEAP Modeling, Energy Demand Analysis, Greenhouse Gas Emissions, Shared Socioeconomic Pathways (SSPs), Greece |
| Date: | 2025–01–14 |
| URL: | https://d.repec.org/n?u=RePEc:aue:wpaper:2515 |
| By: | Taylor Jaworski; Erik O. Kimbrough; Nicole Saito |
| Abstract: | We propose a new measure of cultural distance based on differences in the composition of first names and church denominations between locations. We use a gravity equation to estimate the elasticity of migration flows with respect to the two components of cultural distance as well as a standard measure of travel costs via the transportation network in the United States between 1850 and 1870. Our findings indicate a modest role for cultural distance relative to travel costs in explaining migration flows. We construct migration costs that reflect the distinct contributions of cultural distance and travel costs, and use an economic geography model of migration to quantify their effects. Travel costs are substantially more important than cultural distance for aggregate welfare. Nevertheless, we provide evidence that the components of cultural distance play a role in shaping of how many people move and their final destinations. |
| JEL: | N0 N71 N91 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33192 |
| By: | Cunneen-Franco, Morgan; Schroer, Lisa; Villaseñor, Esteban |
| Abstract: | Our work revealed that the current status quo may be dangerous for people living in the Berkeley Hills. As the City considers upzoning single-family residential districts in the Berkeley Hills, impeded emergency response access, hindered evacuation, and traffic violence have the potential to compound existing risk. To address these challenges, a diverse set of infrastructure and policy prescriptions should be implemented. |
| Keywords: | Social and Behavioral Sciences |
| Date: | 2024–12–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt71b7z80t |
| By: | Mauricio S. de Carvalho; Patrícia C. Melo; Bruno T. Rocha; Isabel Proença; João de Abreu e Silva |
| Abstract: | This paper investigates the causal effects of road accessibility, measured by market potential, on firm births in Portuguese municipalities between 1991 and 2016, a period marked by significant road improvements. We address the endogeneity of market potential by employing instrumental variables within Poisson Pseudo-maximum Likelihood estimates with fixed effects, which we refer to as “non-local time-variant historical instruments”. Our estimated elasticities for firm births range from 1.6 to 1.9 for the 1-year interval and 1.2 to 1.3 for the 5-year interval. Additionally, we find a greater positive effect on firm births when excluding the metropolitan areas of Lisbon and Porto, which is indicative evidence of a heterogeneous spatial effect. We also find that the impact of the enlarged market potential is heterogeneous across sectors. Our results are robust to changes in model specification and the usage of alternative measures of the instruments. |
| Keywords: | road investment; firm births; market potential; Poisson Pseudo-maximum; Likelihood; instrumental variables. |
| JEL: | O18 R39 R49 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:ise:remwps:wp03642025 |
| By: | Lydia Papadaki; Olympia Nisiforou; Angelos Alamanos; Phoebe Koundouri |
| Abstract: | As the need for more environmentally friendly and energy-efficient operations becomes increasingly urgent, shipping - Shipping, despite being a carbon-efficient mode of transport - faces mounting pressure to adapt. The growing awareness of climate change and its impacts has led to a push for the decarbonisation of maritime transport, an industry responsible for approximately 3% of global greenhouse gas emissions. With international trade largely dependent on shipping, ensuring that maritime operations become more sustainable is essential for achieving broader global climate targets. This transition towards sustainability is especially crucial because of the sector's worldwide magnitude, which is growing in tandem with the surging shipping demand. The industry must fulfil these demands while substantially minimising its environmental impact... Alongside the increase in shipping demand, the transition to net-zero necessitates more environmental restrictions, which are expressed through policies (e.g., Emissions Trading Systems - ETS, etc.). Through a brief review of these new mandates, this paper provides a general overview of the main methods and simulation and optimisation models that have been proposed so far for analysing sustainable shipping scenarios, combining techno-economic and environmental parameters. These models combine techno-economic and environmental parameters to offer a comprehensive understanding of potential pathways for decarbonisation. Optimisation models considering technical shipping, fuels and costs, alternative fuels, transition rates, and various 'what-if' or policy scenarios, have been largely used to provide guidance to policymakers with respect to shipping decarbonisation. Herein, different case studies and scales are considered, in order to provide a more holistic picture of the techno-economic and environmental optimisation modelling approaches in maritime operations. Finally, different scenarios examined by these models are discussed, including different modelling cases related to the economic prices of various parameters, shipping demand, the stringency of environmental policies, and more. The findings of this research provide valuable insights for policymakers, shipping industry stakeholders, and researchers as they explore different models, and develop strategies to balance the need for increased shipping capacity with the imperative of environmental sustainability. |
| Keywords: | Shipping, Sustainable maritime operations, Fleet Optimization, Environmental regulations, Techno-economic analysis, Modelling scenarios |
| Date: | 2025–01–14 |
| URL: | https://d.repec.org/n?u=RePEc:aue:wpaper:2511 |
| By: | Dou, Liyu (School of Economics, Singapore Management University); KASTL, Jakub (Department of Economics, Princeton University, NBER and CEPR); LAZAREV, John (Stern Economics, New York University) |
| Abstract: | We develop a framework for quantifying delay propagation in airline networks that combines structural modeling and machine learning methods together to estimate causal objects of interest. Using a large comprehensive data set on actual delays and a model-selection algorithm (elastic net) we estimate a weighted directed graph of delay propagation for each major airline in the US and derive conditions under which the estimates of the propagation coefficients are causal. We use these estimates to decompose the airline performance into “luck” and “ability.” We find that luck may explain about 38% of the performance difference between Delta and American in our data. We further use these estimates to describe how network topology and other airline network characteristics (such as aircraft fleet heterogeneity) affect the expected delays. |
| Keywords: | Airline Networks; Shock Propagation; Elastic Net |
| JEL: | C50 L14 L93 |
| Date: | 2025–09–01 |
| URL: | https://d.repec.org/n?u=RePEc:ris:smuesw:2024_014 |
| By: | Beata Wo\'zniak-J\k{e}chorek; S{\l}awomir Ku\'zmar; David Bole |
| Abstract: | The main goal of this paper is to assess the likelihood of office workers relocating to the suburbs due to work-from-home opportunities and the key factors influencing these preferences. Our study focuses on Poland, a country with different cultural individualism at work, which can impact work-from-home preferences and, indirectly, home relocation desires. Given the methodological limitations of official data on remote work practices in Poland, we conducted an original survey, gathering primary data from a nationally representative sample of office workers living in cities with populations exceeding 100, 000. To investigate the factors shaping employees' preferences for suburban relocation driven by remote work, we utilized logistic regression to analyze the effects of socio-economic and employment characteristics, commuting experiences, and reported changes in work productivity. Our findings reveal that age, mode of commuting, perceived changes in work productivity, and sector ownership are significant determinants, strongly affecting home relocation preferences in response to work-from-home opportunities. These results align with previous research, typically based on data from countries with different cultural frameworks and more developed work-from-home practices. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.07459 |
| By: | Dakshina G. De Silva; Benjamin Rosa |
| Abstract: | We study highway procurement in Texas during the Great Recession and stimulus period, finding increased competition with more bidders and lower bids. We argue that the recession reduced opportunity costs, in part due to a slump in private-sector construction. We evaluate costs and efficiency by developing methods to estimate an empirical auction model tailored for public bidding and demonstrate that contracts became more efficient and less costly. A counterfactual analysis confirms that infrastructure procurement during recessions not only stimulates the economy but also enables the government to complete necessary projects at lower costs. |
| JEL: | D44 H57 H71 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33299 |
| By: | Olympia Nisiforou; Angelos Alamanos; Jorge Andres Garcia; Lydia Papadaki; Phoebe Koundouri |
| Abstract: | The maritime industry is undergoing significant transformation as it grapples with the need for more sustainable shipping practices. This transition involves a shift in fuel preferences, with traditional high-polluting fuels being phased out in favour of cleaner, more sustainable alternatives. The sector is also contending with increasingly stringent environmental regulations, particularly regarding the reduction of greenhouse gas (GHG) emissions. These regulatory demands, coupled with the already complex techno-economic considerations for optimizing shipping operations, present a set of multifaceted challenges that require comprehensive and integrated solutions. In response to these challenges, the Global Climate Hub (GCH) - an initiative under the United Nations Sustainable Development Solutions Network (UN SDSN) - has been actively developing models that offer sustainable pathways for all economic sectors, including the shipping industry. This paper presents such a model: MaritimeGCH, a free, open-source, and comprehensive tool (optimization model) designed to tackle the diverse challenges associated with maritime fleet management. It has been developed in Python, and there can be different variations, depending on the problem being studied and its scale. MaritimeGCH integrates a range of factors, including techno-economic, fuels, environmental, and operational elements, into a single, unified model. It also incorporates recent European environmental policies and penalties, offering a tool that is detailed, flexible, and adaptable to various scales. The model's optimization framework is tailored specifically for maritime challenges, balancing the need for economic efficiencystriving for environmental sustainability. The paper first describes the optimization logic applied to maritime problems, followed by a detailed mathematical breakdown of the MaritimeGCH model. Finally, the model's utility for policy-relevant scenario analysis is discussed. By making MaritimeGCH publicly available, the GCH aims to encourage the broader application of the model while fostering continuous improvements. The model offers significant potential for helping the maritime industry navigate its path toward sustainability while balancing economic and environmental goals in an increasingly complex regulatory landscape. |
| Keywords: | MaritimeGCH, Global Climate Hub, Fleet Optimization, Shipping, Sustainable maritime operations, Environmental regulations, Techno-economic analysis |
| Date: | 2025–01–14 |
| URL: | https://d.repec.org/n?u=RePEc:aue:wpaper:2512 |