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There is a growing consensus that moving to a low carbon future within the transport sector will require a substantial shift away from fossil fuels toward more sustainable means of transport. A particular emphasis has been given t...
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There is a growing consensus that moving to a low carbon future within the transport sector will require a substantial shift away from fossil fuels toward more sustainable means of transport. A particular emphasis has been given to battery electric vehicles (BEV) and plug in hybrid electric vehicles (PHEV), with many nations investing in improving their charging infrastructure and incentivising electric vehicle purchasing through offering grant schemes and tax relief to consumers. Despite these incentives, the uptake of BEVs and PHEVs has been low, while some countries, such as Ireland and Denmark, are in the process of removing the tax relief currently in place. This initial retraction has already been met with a fall in sales of BEVs and PHEVs, which is expected to continue decreasing as these incentives are further reduced. This study develops a socio-economic consumer choice model of the private transport sector based off national empirical data for Ireland and Denmark to analyse the long-term effects of these subsidy retractions, and to further analyse the policy measures and associated cost of moving toward a low carbon private transport sector.
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Hydrogen delivery is a critical contributor to the cost, energy use and emissions associated with hydrogen pathways involving central plant production. The choice of the lowest-cost delivery mode (compressed gas trucks, cryogenic ...
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Hydrogen delivery is a critical contributor to the cost, energy use and emissions associated with hydrogen pathways involving central plant production. The choice of the lowest-cost delivery mode (compressed gas trucks, cryogenic liquid trucks or gas pipelines) will depend upon specific geographic and market characteristics (e.g. city population and radius, population density, size and number of refueling stations and market penetration of fuel cell vehicles). We developed models to characterize delivery distances and to estimate costs, emissions and energy use from various parts of the delivery chain (e.g. compression or liquefaction, delivery and refueling stations). Results show that compressed gas truck delivery is ideal for small stations and very low demand, liquid delivery is ideal for long distance delivery and moderate demand and pipeline delivery is ideal for dense areas with large hydrogen demand.
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A future hydrogen economy would interact with and influence the electricity grid in numerous ways. This paper presents several concepts for understanding a hydrogen economy in the context of the co-evolution with the electricity s...
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A future hydrogen economy would interact with and influence the electricity grid in numerous ways. This paper presents several concepts for understanding a hydrogen economy in the context of the co-evolution with the electricity sector and lays out some of the opportunities and challenges. H_2 and electricity are complementary energy carriers that have distinct characteristics, which lead to more or less utility in different applications. Despite their differences, it is possible to understand a future hydrogen economy using some of the same techniques as electricity system analysis. Hydrogen pathways will lead to additional electric demands that will influence the structure, operation and emissions in the electric sector. Examples of convergence between these sectors include a number of options for H_2 and electricity co-production and interconversion.
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This paper investigates the potential for making deep cuts in US transportation greenhouse gas (GHG) emissions in the long-term (50-80% below 1990 levels by 2050). Scenarios are used to envision how such a significant decarbonizat...
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This paper investigates the potential for making deep cuts in US transportation greenhouse gas (GHG) emissions in the long-term (50-80% below 1990 levels by 2050). Scenarios are used to envision how such a significant decarbonization might be achieved through the application of advanced vehicle technologies and fuels, and various options for behavioral change. A Kaya framework that decomposes GHG emissions into the product of four major drivers is used to analyze emissions and mitigation options. In contrast to most previous studies, a relatively simple, easily adaptable modeling methodology is used which can incorporate insights from other modeling studies and organize them in a way that is easy for policymakers to understand. Also, a wider range of transportation subsectors is considered here-light- and heavy-duty vehicles, aviation, rail, marine, agriculture, off-road, and construction. This analysis investigates scenarios with multiple options (increased efficiency, lower-carbon fuels, and travel demand management) across the various subsectors and confirms the notion that there are no "silver bullet" strategies for making deep cuts in transport GHGs. If substantial emission reductions are to be made, considerable action is needed on all fronts, and no subsectors can be ignored. Light-duty vehicles offer the greatest potential for emission reductions; however, while deep reductions in other subsectors are also possible, there are more limitations in the types of fuels and propulsion systems that can be used. In all cases travel demand management strategies are critical; deep emission cuts will not likely be possible without slowing growth in travel demand across all modes. Even though these scenarios represent only a small subset of the potential futures in which deep reductions might be achieved, they provide a sense of the magnitude of changes required in our transportation system and the need for early and aggressive action if long-term targets are to be met.
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Hydrogen infrastructure costs will vary by region as geographic characteristics and feedstocks differ. This paper proposes a method for optimizing regional hydrogen infrastructure deployment by combining detailed spatial data in a...
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Hydrogen infrastructure costs will vary by region as geographic characteristics and feedstocks differ. This paper proposes a method for optimizing regional hydrogen infrastructure deployment by combining detailed spatial data in a geographic information system (GIS) with a technoeconomic model of hydrogen infrastructure components. The method is applied to a case study in Ohio in which coal-based hydrogen infrastructure with carbon capture and storage (CCS) is modeled for two distribution modes at several steady-state hydrogen vehicle market penetration levels. The paper identifies the optimal infrastructure design at each market penetration as well as the costs, CO_2 emissions, and energy use associated with each infrastructure pathway. The results indicate that aggregating infrastructure at the regional-scale yields lower levelized costs of hydrogen than at the city-level at a given market penetration level, and centralized production with pipeline distribution is the favored pathway even at low market penetration. Based upon the hydrogen infrastructure designs evaluated in this paper, coal-based hydrogen production with CCS can significantly reduce transportation-related CO_2 emissions at a relatively low infrastructure cost and levelized fuel cost.
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This paper describes the development and use of a hydrogen infrastructure optimization model using the TIMES modeling framework, H2TIMES, to analyze hydrogen development in California to 2050. H2TIMES is a quasi-spatial model that...
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This paper describes the development and use of a hydrogen infrastructure optimization model using the TIMES modeling framework, H2TIMES, to analyze hydrogen development in California to 2050. H2TIMES is a quasi-spatial model that develops the infrastructure to supply hydrogen fuel in order to meet demand in eight separate California regions in a least cost manner subject to various resource, technology and policy constraints. A Base case, with a suite of hydrogen policies now in effect or proposed in California (renewable hydrogen mandate, fuel carbon intensity constraint and prohibition on using coal without carbon capture and sequestration) leads to hydrogen fuel with significant reductions in carbon intensity (85% below gasoline on an efficiency-adjusted basis, 75% below on a raw energy basis) and competitive hydrogen costs (～$4.00/kg in 2025-2050). A number of sensitivity scenarios investigate the cost and emissions implications of altering policy constraints, technology and resource availability, and modeling decisions. The availability of biomass for hydrogen production and carbon capture and sequestration are two critical factors for achieving low-cost and low-emission hydrogen.
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California's target for reducing economy-wide greenhouse gas (GHG) emissions is 80% below 1990 levels by 2050. We develop transition scenarios for meeting this goal in California's transportation sector, with focus on light-duty v...
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California's target for reducing economy-wide greenhouse gas (GHG) emissions is 80% below 1990 levels by 2050. We develop transition scenarios for meeting this goal in California's transportation sector, with focus on light-duty vehicles (LDVs). We explore four questions: (1) what options are available to reduce transportation sector GHG emissions 80% below 1990 levels by 2050; (2) how rapidly would transitions in LDV markets, fuels, and travel behaviors need to occur over the next 40 years; (3) how do intermediate policy goals relate to different transition pathways; (4) how would rates of technological change and market adoption between 2010 and 2050 impact cumulative GHG emissions? We develop four LDV transition scenarios to meet the 80in50 target through a combination of travel demand reduction, fuel economy improvements, and low-carbon fuel supply, subject to restrictions on trajectories of technological change, potential market adoption of new vehicles and fuels, and resource availability. These scenarios exhibit several common themes: electrification of LDVs, rapid improvements in vehicle efficiency, and future fuels with less than half the carbon intensity of current gasoline and diesel. Availability of low-carbon biofuels and the level of travel demand reduction are "swing factors" that influence the degree of LDV electrification required.
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The CA-TIMES optimization model of the California Energy System (v1.5) is used to understand how California can meet the 2050 targets for greenhouse gas (GHG) emissions (80% below 1990 levels). This model represents energy supply ...
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The CA-TIMES optimization model of the California Energy System (v1.5) is used to understand how California can meet the 2050 targets for greenhouse gas (GHG) emissions (80% below 1990 levels). This model represents energy supply and demand sectors in California and simulates the technology and resource requirements needed to meet projected energy service demands. The model includes assumptions on policy constraints, as well as technology and resource costs and availability. Multiple scenarios are developed to analyze the changes and investments in low-carbon electricity generation, alternative fuels and advanced vehicles in transportation, resource utilization, and efficiency improvements across many sectors. Results show that major energy transformations are needed but that achieving the 80% reduction goal for California is possible at reasonable average carbon reduction cost ($9 to $124/tonne CO_2e at 4% discount rate) relative to a baseline scenario. Availability of low-carbon resources such as nuclear power, carbon capture and sequestration (CCS), biofuels, wind and solar generation, and demand reduction all serve to lower the mitigation costs, but CCS is a key technology for achieving the lowest mitigation costs.
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This paper explores how Plug-in Hybrid Vehicles (PHEVs) may reduce source-to-wheel Greenhouse Gas (GHG) emissions from passenger vehicles. The two primary advances are the incorporation of (1) explicit measures of consumer interes...
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This paper explores how Plug-in Hybrid Vehicles (PHEVs) may reduce source-to-wheel Greenhouse Gas (GHG) emissions from passenger vehicles. The two primary advances are the incorporation of (1) explicit measures of consumer interest in and potential use of different types of PHEVs and (2) a model of the California electricity grid capable of differentiating hourly and seasonal GHG emissions by generation source. We construct PHEV emissions scenarios to address inherent relationships between vehicle design, driving and recharging behaviors, seasonal and time-of-day variation in GHG-intensity of electricity, and total GHG emissions. A sample of 877 California new vehicle buyers provide data on driving, time of day recharge access, and PHEV design interests. The elicited data differ substantially from the assumptions used in previous analyses. We construct electricity demand profiles scaled to one million PHEVs and input them into an hourly California electricity supply model to simulate GHG emissions. Compared to conventional vehicles, consumer-designed PHEVs cut marginal (incremental) GHG emissions by more than one-third in current California energy scenarios and by one-quarter in future energy scenarios-reductions similar to those simulated for all-electric PHEV designs. Across the emissions scenarios, long-term GHG reductions depends on reducing the carbon intensity of the grid.
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California aims to reduce greenhouse gas (GHG) emissions to 40% below 1990 levels by 2030. We compare six energy models that have played various roles in informing the state policymakers in setting climate policy goals and targets...
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California aims to reduce greenhouse gas (GHG) emissions to 40% below 1990 levels by 2030. We compare six energy models that have played various roles in informing the state policymakers in setting climate policy goals and targets. These models adopt a range of modeling structures, including stockturnover back-casting models, a least-cost optimization model, macroeconomic/macro-econometric models, and an electricity dispatch model. Results from these models provide useful insights in terms of the transformations in the energy system required, including efficiency improvements in cars, trucks, and buildings, electrification of end-uses, low- or zero-carbon electricity and fuels, aggressive adoptions of zero-emission vehicles (ZEVs), demand reduction, and large reductions of non-energy GHG emissions. Some of these studies also suggest that the direct economic costs can be fairly modest or even generate net savings, while the indirect macroeconomic benefits are large, as shifts in employment and capital investments could have higher economic returns than conventional energy expenditures. These models, however, often assume perfect markets, perfect competition, and zero transaction costs. They also do not provide specific policy guidance on how these transformative changes can be achieved. Greater emphasis on modeling uncertainty, consumer behaviors, heterogeneity of impacts, and spatial modeling would further enhance policymakers' ability to design more effective and targeted policies. This paper presents an example of how policymakers, energy system modelers and stakeholders interact and work together to develop and evaluate long-term state climate policy targets. Even though this paper focuses on California, the process of dialogue and interactions, modeling results, and lessons learned can be generally adopted across different regions and scales.
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