GREET Model Research Articles

Integration of non-fuel coproducts into the GREET model.

The life-cycle greenhouse gas (GHG) emissions of alternative fuels that are capable of replacing conventional, petroleum-derived gasoline and diesel continue to be scrutinized for policy implementation. These alternative fuel technologies can also produce a number of value-adding nonfuel coproducts that require thorough and rigorous assessment in order to achieve an accurate life-cycle GHG emissions value. By using the gas to liquids (GTL) diesel pathway as a proxy for other alternative fuel pathways with coproducts, this paper examines how integration of coproduct analysis using the substitution method is possible within the existing framework and functionality of the GREET model. Using this approach, a GREET-compatible external tool was developed to calculate the life-cycle inventory of GTL coproducts to determine the life-cycle GHG emissions of GTL diesel using the substitution method. In addition to having built-in regional scenarios, this tool allows the user the flexibility to configure a given GTL product slate and to calculate the life-cycle GHG emissions of GTL diesel based on a given product composition. Using this protocol, the life-cycle GHG emissions of GTL diesel can range from 71.7 to 95.7 gCO2e/MJ on a well to wheel basis, with the range in carbon intensity being dependent on the mix of coproducts. These results highlight a weakly understood relationship between fuel and chemical products in LCA models. The coproduct integration approach described herein could potentially be incorporated into fuel LCA models, such as GREET, to allow users to further understand the potential environmental benefits of alternative fuel pathways, such as GTL.

Energy and environmental life-cycle assessment of passenger car electrification based on Beijing driving patterns

This paper examines the energy and environmental benefits within the whole life cycle shifting from traditional gasoline vehicles to electrified advanced vehicles under regional real-world driving behaviors. The advance vehicles focus on family passenger cars and include battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), and hybrid electric vehicles (HEVs). The GREET (greenhouse gases, regulated emissions, and energy use in transportation) model is adopted with regional circumstances modifications, especially the UF (utility factors) of PHEVs. The results show that the electrified vehicles offer great benefits concerning energy consumption, greenhouse gas (GHG) emissions as well as urban Particulate Matter 2.5 (PM2.5) emissions. Compared to conventional gasoline vehicles, the life-cycle total energy reduction for advance vehicles is 51% to 57%. There is little difference on energy reduction among the HEVs, PHEVs and BEVs, with the energy mix shifting from petroleum to coal for the stronger electrification. The reductions of GHG emissions are 57% for HEV, 54% to 48% for PHEVs with 10 miles to 40 miles CD range, and 40% for BEV. The life-cycle and local PM2.5 emissions are discussed separately. The life-cycle PM2.5 emissions increase with vehicle electrification and reach a maximum for the BEV which are 5% higher than the conventional vehicle (CV). However, electric vehicles can shift PM2.5 emissions from vehicle operation to upstream operations and help mitigate PM2.5 emissions in urban areas. The local emissions of PHEVs and BEVs can be reduced by 37% to 81% and 100% compared with CVs.

Impact of Updated Material Production Data in the GREET Life Cycle Model

SummaryThe Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model developed by Argonne National Laboratory quantifies the life cycle energy consumption and air emissions resulting from the production and use of light‐duty vehicles in the United States. GREET is comprised of two components: GREET 1 represents the fuel cycle of various energy carriers, including automotive fuels, and GREET 2 represents the vehicle cycle, which accounts for the production of vehicles and their constituent materials. The GREET model was updated in 2012 and now includes higher‐resolution material processing and transformation data. This study evaluated how model updates influence material and vehicle life cycle results. First, new primary energy demand and greenhouse gas (GHG) emissions results from GREET 2 for steel, aluminum, and plastics resins are compared herein with those from the previous version of the model as well as industrial results. A part of the comparison is a discussion about causes of differences between results. Included in this discussion is an assessment of the impact of the new material production data on vehicle life cycle results for conventional internal combustion engine (ICE) vehicles by comparing the energy and GHG emission values in the updated and previous versions of GREET 2. Finally, results from a sensitivity analysis are presented for identifying life cycle parameters that most affect vehicle life cycle estimates.

Well-to-wheel analysis on greenhouse gas emission and energy use with natural gas in Korea

In Korea, natural gas is widely used as city gas, fuel for electricity generation, and fuel for transportation (e.g., city bus). However, the environmental impact associated with the use of natural gas in Korea has not been paid much attention to. In this study, well-to-wheel (WTW) analysis on the greenhouse gas (GHG) emissions and energy uses associated with natural gas in Korea was performed by considering every step from feedstock recovery to final use in the vehicle operation. The raw data used in the analysis were mainly provided by Korean natural gas industry and related associations. The additional information, especially for the processes in foreign countries, was also collected by literature survey. We adopted the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model as a base WTW analysis tool, which was developed by the U.S. Argonne National Laboratory. However, the WTW analysis on natural gas in Korea is far different from that of the U.S, because ~99 % of natural gas used in Korea is imported from the oversea countries in the form of liquefied natural gas (LNG). For this reason, detailed parameters in GREET were changed for Korean situation, and especially, significant modifications were made on liquefaction, LNG transportation and storage, and re-gasification processes. As a result of the analysis, the well-to-pump GHG emissions of city gas and compressed natural gas are calculated as 25,717–30,178 and 28,903–33,422 g CO2 eq./GJFianl_fuel, respectively. The WTW GHG emission of compressed-natural-gas-fueled city bus is calculated as 1,348–1,417 g CO2 eq./km. These values are relatively larger than those of the U.S., because most of the natural gas used in the U.S. is transported by pipeline in a gaseous state, which typically takes less energy and associated GHG emissions, as compared to the import of LNG in Korea. Finally, sensitivity analysis is performed on the parameters, which have either range of values among various sources or uncertainties due to lack of accurate information. The results show that further investigation on three parameters, i.e., CO2 venting during natural gas processing, CH4 leakage in Korea, and CH4 leakage during recovery process, would be helpful to further improve overall accuracy of the analysis.

Microalgae to biofuels lifecycle assessment — Multiple pathway evaluation

A variety of researchers have constructed and presented lifecycle assessments of the microalgae-to-biofuel process, however, inconsistencies in system boundary definitions and high-level process modeling have led to a wide range of results. This study integrates engineering process models validated through experimental and modeling research to perform an environmental assessment of four microalgae-to-biofuel production scenarios leveraging the Argonne National Laboratory GREET model. The baseline scenario consists of a down flow open pond growth system, three phase de-watering step (settling, dissolved air flotation, and a centrifuge), hexane extraction and nutrient recovery using anaerobic digestion. The net energy ratio (NER), defined as energy consumed over the produced energy, and greenhouse gases (GHG) for the baseline scenario are 0.7MJMJ−1 and −41.7gCO2-eqMJ−1 respectively. Three alternative scenarios are also evaluated: 1) Improved microalgal productivity, 2) supercritical CO2 extraction, and 3) no nutrient recycle. This research shows that supercritical CO2 extraction is neither currently energetically- nor environmentally favorable and that nutrient recycle plays an integral role in achieving favorable NER and GHGs. The study highlights on the systems level, two findings related to the NER; 1) the NER is minimally impacted with increased productivity and 2) increasing microalgae lipid content detrimentally affects the NER which is attributed to the reduction in the total energy that can be captured by the anaerobic digester.

Life cycle assessment of the production of hydrogen and transportation fuels from corn stover via fast pyrolysis

This life cycle assessment evaluates and quantifies the environmental impacts of the production of hydrogen and transportation fuels from the fast pyrolysis and upgrading of corn stover. Input data for this analysis come from Aspen Plus modeling, a GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model database and a US Life Cycle Inventory Database. SimaPro 7.3 software is employed to estimate the environmental impacts. The results indicate that the net fossil energy input is 0.25 MJ and 0.23 MJ per km traveled for a light-duty vehicle fueled by gasoline and diesel fuel, respectively. Bio-oil production requires the largest fossil energy input. The net global warming potential (GWP) is 0.037 kg CO2eq and 0.015 kg CO2eq per km traveled for a vehicle fueled by gasoline and diesel fuel, respectively. Vehicle operations contribute up to 33% of the total positive GWP, which is the largest greenhouse gas footprint of all the unit processes. The net GWPs in this study are 88% and 94% lower than for petroleum-based gasoline and diesel fuel (2005 baseline), respectively. Biomass transportation has the largest impact on ozone depletion among all of the unit processes. Sensitivity analysis shows that fuel economy, transportation fuel yield, bio-oil yield, and electricity consumption are the key factors that influence greenhouse gas emissions.

Lifecycle performance assessment of fuel cell/battery electric vehicles

This paper has performed an assessment of lifecycle (as known as well-to-wheels, WTW) greenhouse gas (GHG) emissions and energy consumption of a fuel cell vehicle (FCV). The simulation tool MATLAB/Simulink is employed to examine the real-time behaviors of an FCV, which are used to determine the energy efficiency and the fuel economy of the FCV. Then, the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model is used to analyze the fuel-cycle energy consumption and GHG emissions for hydrogen fuels. Three potential pathways of hydrogen production for FCV application are examined, namely, steam reforming of natural gas, water electrolysis using grid electricity, and water electrolysis using photovoltaic (PV) electricity, respectively. Results show that the FCV has the maximum system efficiency of 60%, which occurs at about 25% of the maximum net system power. In addition, the FCVs fueled with PV electrolysis hydrogen could reduce about 99.2% energy consumption and 46.6% GHG emissions as compared to the conventional gasoline vehicles (GVs). However, the lifecycle energy consumption and GHG emissions of the FCVs fueled with grid-electrolysis hydrogen are 35% and 52.8% respectively higher than those of the conventional GVs. As compared to the grid-based battery electric vehicles (BEVs), the FCVs fueled with reforming hydrogen from natural gas are about 79.0% and 66.4% in the lifecycle energy consumption and GHG emissions, respectively.

Coal-based synthetic natural gas (SNG): A solution to China’s energy security and CO2 reduction?

Considering natural gas (NG) to be the most promising low-carbon option for the energy industry, large state owned companies in China have established numerous coal-based synthetic natural gas (SNG) projects. The objective of this paper is to use a system approach to evaluate coal-derived SNG in terms of life-cycle energy efficiency and CO2 emissions. This project examined main applications of the SNG and developed a model that can be used for evaluating energy efficiency and CO2 emissions of various fuel pathway systems. The model development started with the GREET model, and added the SNG module and an end-use equipment module. The database was constructed with Chinese data. The analyses show when the SNG are used for cooking, power generation, steam production for heating and industry, life-cycle energies are 20–108% higher than all competitive pathways, with a similar rate of increase in life-cycle CO2 emissions. When a compressed natural gas (CNG) car uses the SNG, life-cycle CO2 emission will increase by 150–190% compared to the baseline gasoline car and by 140–210% compared to an electric car powered by electricity from coal-fired power plants. The life-cycle CO2 emission of SNG-powered city bus will be 220–270% higher than that of traditional diesel city bus. The gap between SNG-powered buses and new hybrid diesel buses will be even larger—life-cycle CO2 emission of the former being around 4 times of that of the latter. It is concluded that the SNG will not accomplish the tasks of both energy conservation and CO2 reduction.

Life cycle analysis of hydrogen – A well-to-wheels analysis for Portugal

A life cycle analysis of hydrogen is presented involving several processes of H2 production. The main goal was to adapt the GREET 1.8c model in order to represent the European reality and more specifically the Portuguese energy sector. GEMIS model was used in order to obtain energy consumption and pollutant emissions related to the production of photovoltaic panels and wind towers, since GREET model consider zero emissions in renewable technologies. The integration between these two models generated MACV2H2 model that was calibrated.The main conclusions from a Well-To-Wheel (WTW) analysis are that wind energy is the best way to produce hydrogen, and its application in Fuel Cell Vehicles (FCV) presents less 85% of greenhouse gases emissions (GHGs) when compared with the gasoline vehicle. In the opposite situation, the FCV with hydrogen from electrolysis using the Portuguese electricity grid presents an increase of 43% on GHGs.

Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use

Globally, bioethanol is the largest volume biofuel used in the transportation sector, with corn-based ethanol production occurring mostly in the US and sugarcane-based ethanol production occurring mostly in Brazil. Advances in technology and the resulting improved productivity in corn and sugarcane farming and ethanol conversion, together with biofuel policies, have contributed to the significant expansion of ethanol production in the past 20 years. These improvements have increased the energy and greenhouse gas (GHG) benefits of using bioethanol as opposed to using petroleum gasoline. This article presents results from our most recently updated simulations of energy use and GHG emissions that result from using bioethanol made from several feedstocks. The results were generated with the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model. In particular, based on a consistent and systematic model platform, we estimate life-cycle energy consumption and GHG emissions from using ethanol produced from five feedstocks: corn, sugarcane, corn stover, switchgrass and miscanthus. We quantitatively address the impacts of a few critical factors that affect life-cycle GHG emissions from bioethanol. Even when the highly debated land use change GHG emissions are included, changing from corn to sugarcane and then to cellulosic biomass helps to significantly increase the reductions in energy use and GHG emissions from using bioethanol. Relative to petroleum gasoline, ethanol from corn, sugarcane, corn stover, switchgrass and miscanthus can reduce life-cycle GHG emissions by 19–48%, 40–62%, 90–103%, 77–97% and 101–115%, respectively. Similar trends have been found with regard to fossil energy benefits for the five bioethanol pathways.

A Spatially and Temporally Explicit Life Cycle Inventory of Air Pollutants from Gasoline and Ethanol in the United States

The environmental health impacts of transportation depend in part on where and when emissions occur during fuel production and combustion. Here we describe spatially and temporally explicit life cycle inventories (LCI) of air pollutants from gasoline, ethanol derived from corn grain, and ethanol from corn stover. Previous modeling for the U.S. by Argonne National Laboratory (GREET: Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) suggested that life cycle emissions are generally higher for ethanol from corn grain or corn stover than for gasoline. Our results show that for ethanol, emissions are concentrated in the Midwestern "Corn Belt". We find that life cycle emissions from ethanol exhibit different temporal patterns than from gasoline, reflecting seasonal aspects of farming activities. Enhanced chemical speciation beyond current GREET model capabilities is also described. Life cycle fine particulate matter emissions are higher for ethanol from corn grain than for ethanol from corn stover; for black carbon, the reverse holds. Overall, our results add to existing state-of-the-science transportation fuel LCI by providing spatial and temporal disaggregation and enhanced chemical speciation, thereby offering greater understanding of the impacts of transportation fuels on human health and opening the door to advanced air dispersion modeling of fuel life cycles.

Evolving a Cleaner Grid: Uses of Natural Gas in Transportation

Achieving greenhouse gas emissions reduction goals from the transportation sector will be a monumental challenge. Various alternative vehicle technologies such as plug-in hybrids, battery and fuel cell electric vehicles offer the promise of sharply reducing end use emissions. However, when considering the full fuel cycle, it is clear that a dramatically cleaner electricity grid will also be necessary if we ever hope to meet ambitious long-term reduction goals. To demonstrate the importance of achieving this dramatically cleaner grid, our analysis implements Argonne National Laboratory’s GREET model and the latest Annual Energy Outlook data to evaluate the relative merit of various alternative vehicles on a well-to-wheel basis while taking into account projections for the evolution of the U.S. electricity supply. Fortunately, significant progress is now underway to transform the electricity sector. The emergence of substantial supplies of shale gas, at low cost and substantial abundance, has dramatically reshaped the energy landscape. There are multiple pathways for this abundant supply of natural gas to help reduce the transportation sector emissions footprint, whether through greater utilization in highly efficient natural gas combined-cycle electricity generators, direct use in compressed natural gas vehicles, or steam reformation to provide hydrogen for fuel cell vehicles. Greater reliance on high efficiency natural gas combined cycle generators, combined with the steady expansion of renewable generation and energy efficiency, is providing a critical alternative to continued reliance on dirty, legacy generators. This emerging new clean power paradigm can multiply the benefits of more rapid growth in electric drive vehicles.

Marginal Analysis of the HFCVs Industrialization: Commercialization Scale and the CO<sub>2</sub> Emission Reduction

Focus on the hydrogen fuel cell vehicle industrialization barriers, the paper applies the marginal analysis into the CO2emission reduction of the HFCV. Based on the outputs of the GREET model, the CO2emission reduction amount of the HFCVs, the CO2emissions amount of HFCVs and the scale of the HFCV are calculated separately. Then we build the formulas of the above variables so that the marginal curve of the CO2emission reduction and the commercialization scale of HFCVs are mapped. The conclusion shows the marginal analyze could play a useful role in the CO2emission reduction estimation of the HFCV industrialization.

The impact of dry matter loss during herbaceous biomass storage on net greenhouse gas emissions from biofuels production

Abstract Life cycle inventory models of greenhouse gas emissions from biofuel production have become tightly integrated into government mandates and other policies to encourage biofuel production. Current models do not include life cycle impacts of biomass storage or reflect current literature on emissions from soil and biomass decomposition. In this study, the GREET model framework was used to determine net greenhouse gas emissions during ethanol production from corn and switchgrass via three biomass storage systems: wet ensiling of whole corn, and indoor and outdoor dry bale storage of corn stover and switchgrass. Dry matter losses during storage were estimated from the literature and used to modify GREET inventory analysis. Results showed that biomass stability is a key parameter affecting fuel production per farmed hectare and life cycle greenhouse gas emissions. Corn silage may generate 5358 L/ha of ethanol at 26.5 g CO2 eq/MJ, relative to 5654 L/ha at 52.3 g CO2 eq/MJ from combined corn stover and conventional grain corn ethanol production, or 3919 L/ha at 21.3 g CO2 eq/MJ from switchgrass. Dry matter losses can increase net emissions by 3–25% (ensiling), 5–53% (bales outdoors), or 1–12% (bales indoors), decreasing the net GHG reduction of ethanol over gasoline by up to 10.9%. Greater understanding of biomass storage losses and greenhouse gas fluxes during storage is necessary to accurately assess biomass storage options to ensure that the design of biomass supply logistics systems meet GHG reduction mandates for biofuel production.

Hybrid Electric and Battery Electric City Buses Benefit Analysis Based on Lifecycle Cost and Emission

This paper took hybrid electric bus and battery electric bus as research subjects, built lifecycle cost model based on purchase cost and using cost, calculated well-to-wheel carbon dioxide emission based on GREET model, analyzed current situation and foreground of new energy buses compared with conventional diesel bus. The results shows hybrid electric bus has advantages on cost and emission in the coming decade. While lifecycle cost of battery electric bus is too high today, and the cost in the future depends on battery technology development.

Assessment of Fuel-Cycle Energy Use and Greenhouse Gas Emissions for Fischer−Tropsch Diesel from Coal and Cellulosic Biomass

This study expands and uses the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model to assess the effects of carbon capture and storage (CCS) technology and cellulosic biomass and coal cofeeding in Fischer-Tropsch (FT) plants on energy use and greenhouse gas (GHG) emissions of FT diesel (FTD). To demonstrate the influence of the coproduct credit methods on FTD life-cycle analysis (LCA) results, two allocation methods based on the energy value and the market revenue of different products and a hybrid method are employed. With the energy-based allocation method, fossil energy use of FTD is less than that of petroleum diesel, and GHG emissions of FTD could be close to zero or even less than zero with CCS when forest residue accounts for 55% or more of the total dry mass input to FTD plants. Without CCS, GHG emissions are reduced to a level equivalent to that from petroleum diesel plants when forest residue accounts for 61% of the total dry mass input. Moreover, we show that coproduct method selection is crucial for LCA results of FTD when a large amount of coproducts is produced.

Study on whole-life cycle automotive manufacturing industry CO2 emission accounting method and Application in Chongqing

Low carbon economy has become a worldwide trend, many countries are seeking low carbon means to achieve environmentallyfriendly economy growth. However, various Greenhouse gases species in different industries, as well as various detection technology development levels in different countries lead to different carbon emissions accounting results eventually. So the accurate micro-level accounting on carbon dioxide emission is difficult to achieve while in the mean time, it is the basis for subsequent scenario analysis, which plays a crucial role in carbon pricing and carbon credits market promotion. That's why the regional carbon dioxide emission accounting is a hot issue in low-carbon economy. Nowadays, automotive manufacturing industry has become a big fuel consumer in China and an important source of air pollution. So an accounting method focused on carbon dioxide emission in Chinese automotive industry is essential and practical significant. This paper proposed a whole-life cycle carbon emissions methodology to account carbon dioxide emission in Chinese automotive manufacturing industry, which is based on GREET and MOBILE model. And then the feasibility is verified through application in the automotive industry in Chongqing, China.

Net Energy and Greenhouse Gas Emission Evaluation of Biodiesel Derived from Microalgae

Biofuels derived from microalgae have the potential to replace petroleum fuel and first-generation biofuel, but the efficacy with which sustainability goals can be achieved is dependent on the lifecycle impacts of the microalgae-to-biofuel process. This study proposes a detailed, industrial-scale engineering model for the species Nannochloropsis using a photobioreactor architecture. This process level model is integrated with a lifecycle energy and greenhouse gas emission analysis compatible with the methods and boundaries of the Argonne National Laboratory GREET model, thereby ensuring comparability to preexisting fuel-cycle assessments. Results are used to evaluate the net energy ratio (NER) and net greenhouse gas emissions (GHGs) of microalgae biodiesel in comparison to petroleum diesel and soybean-based biodiesel with a boundary equivalent to "well-to-pump". The resulting NER of the microalgae biodiesel process is 0.93 MJ of energy consumed per MJ of energy produced. In terms of net GHGs, microalgae-based biofuels avoids 75 g of CO(2)-equivalent emissions per MJ of energy produced. The scalability of the consumables and products of the proposed microalgae-to-biofuels processes are assessed in the context of 150 billion liters (40 billion gallons) of annual production.

Life cycle greenhouse gases, energy and cost assessment of automobiles using magnesium from Chinese Pidgeon process

Magnesium (Mg) has a great potential to reduce vehicle weight, fuel consumption, and greenhouse gas emissions. The Chinese Mg industry has developed rapidly since the 1990s. The output of Mg reached 700,000 tons in 2006, accounting for more than 70% of global Mg production. Most of Mg is produced in China through the Pidgeon process that has an intensive energy usage and generates a large amount of greenhouse gas (GHG) emissions, which may offset the potential advantage of using Mg parts in automobiles. It is critical to quantify the energy usage and GHG emissions through entire life cycle when the Mg are applied to automobiles. It is also essential to evaluate cost implications of the Mg parts application in automobiles and ensure it to be cost competitive. The objectives of this study are (1) Build a life cycle inventory (LCI) of Mg produced by Pidgeon process; (2) Establish an LCA model that can evaluate GHG emissions and energy usage for the Mg automotive application; (3) Estimate the cost implications of the Mg parts application in automobiles. An Mg LCI was built based on interviews and surveys and the GREET model was adapt for this study. The results indicated that, for each kilogram of Mg produced by Pidgeon process, GHG emissions and energy usage would be 27 kg CO 2eq and 280 MJ, which are five times higher than steel production. Replacing steel with 82 kg Mg on a base automobile would lower curb weight by 5.7%, but only reduce life cycle GHG emissions and energy usage by 0.8% and 1.3%. Scenario analyses indicated that potential reduction of life cycle GHG emissions and energy usage could reach to 15%, if secondary weight saving and a smaller engine were included. Cost analyses also show 18% reduction when the additional weight saving and a smaller displacement engine were included, under a 100,000 km driving distance and gasoline price at $1.0/l.

Diversification in the driveway: mean-variance optimization for greenhouse gas emissions reduction from the next generation of vehicles

Modern portfolio theory is applied to the problem of selecting which vehicle technologies and fuels to use in the next generation of vehicles. Selecting vehicles with the lowest lifetime cost is complicated by the fact that future prices are uncertain, just as selecting securities for an investment portfolio is complicated by the fact that future returns are uncertain. A quadratic program is developed based on modern portfolio theory, with the objective of minimizing the expected lifetime cost of the “vehicle portfolio”. Constraints limit greenhouse gas emissions, as well as the variance of the cost. A case study is performed for light-duty passenger vehicles in the United States, drawing emissions and usage data from the US Environmental Protection Agency's MOVES and Department of Energy's GREET models, among other sources. Four vehicle technologies are considered: conventional gasoline, conventional diesel, grid-independent (non-plug-in) gasoline-electric hybrid, and flex fuel using E85. Results indicate that much of the uncertainty surrounding cost stems from fuel price fluctuations, and that fuel efficient vehicles can lower cost variance. Hybrids exhibit the lowest cost variances of the technologies considered, making them an arguably financially conservative choice.