An Approach to Study Impact of Public Policy, Exogenous Variables, and Vehicle Design on Greenhouse Gas Emission

The aim of this paper is to study the impact of public government policies, fuel cell cost, and battery cost on greenhouse gas (GHG) emissions in the US transportation sector. The model includes a government model and an enterprise model. To examine the effect on GHG emissions that fuel cell and battery cost has, the optimization model includes public policy, fuel cell and battery cost, and a market mix focusing on the GHG effects of four different types of vehicles, 1) gasoline-based 2) gasoline-electric hybrid or alternative-fuel vehicles (AFVs), 3) battery-electric (BEVs) and 4) fuel-cell vehicles (FCVs). The public policies taken into consideration are infrastructure investments for hydrogen fueling stations and subsidies for purchasing AFVs. For each selection of public policy, fuel cell cost and battery cost in the government model, the enterprise model finds the optimum vehicle design that maximizes profit and updates the market mix, from which the government model can estimate GHG emissions. This paper demonstrates the model using FCV design as an illustrative example.

Evaluating automobile fuel/propulsion system technologies

Alternative-fuel-vehicle policy interactions increase U.S. greenhouse gas emissions

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Driving a sustainable road transportation transformation

Plug-in hybrid electric vehicles (PHEVs) have potential to reduce greenhouse gas (GHG) emissions in the U.S. light-duty vehicle fleet. GHG emissions from PHEVs and other vehicles depend on both vehicle design and driver behavior. We pose a twice-differentiable, factorable mixed-integer nonlinear programming model utilizing vehicle physics simulation, battery degradation data, and U.S. driving data to determine optimal vehicle design and allocation for minimizing lifecycle greenhouse gas (GHG) emissions. The resulting nonconvex optimization problem is solved using a convexification-based branch-and-reduce algorithm, which achieves global solutions. In contrast, a randomized multistart approach with local search algorithms finds global solutions in 59% of trials for the two-vehicle case and 18% of trials for the three-vehicle case. Results indicate that minimum GHG emissions is achieved with a mix of PHEVs sized for around 35 miles of electric travel. Larger battery packs allow longer travel on electric power, but additional battery production and weight result in higher GHG emissions, unless significant grid decarbonization is achieved. PHEVs offer a nearly 50% reduction in life cycle GHG emissions relative to equivalent conventional vehicles and about 5% improvement over ordinary hybrid electric vehicles. Optimal allocation of different vehicles to different drivers turns out to be of second order importance for minimizing net life cycle GHGs.

Plug-in hybrid electric vehicle (PHEV) technology has the potential to help address economic, environmental, and national security concerns in the United States by reducing operating cost, greenhouse gas (GHG) emissions and petroleum consumption from the transportation sector. However, the net effects of PHEVs depend critically on vehicle design, battery technology, and charging frequency. To examine these implications, we develop an integrated optimization model utilizing vehicle physics simulation, battery degradation data, and U.S. driving data to determine optimal vehicle design and allocation of vehicles to drivers for minimum life cycle cost, GHG emissions, and petroleum consumption. We find that, while PHEVs with large battery capacity minimize petroleum consumption, a mix of PHEVs sized for 25–40 miles of electric travel produces the greatest reduction in lifecycle GHG emissions. At today’s average US energy prices, battery pack cost must fall below $460/kWh (below $300/kWh for a 10% discount rate) for PHEVs to be cost competitive with ordinary hybrid electric vehicles (HEVs). Carbon allowance prices have marginal impact on optimal design or allocation of PHEVs even at $100/tonne. We find that the maximum battery swing should be utilized to achieve minimum life cycle cost, GHGs, and petroleum consumption. Increased swing enables greater all-electric range (AER) to be achieved with smaller battery packs, improving cost competitiveness of PHEVs. Hence, existing policies that subsidize battery cost for PHEVs would likely be better tied to AER, rather than total battery capacity.

This study investigates emission impacts of introducing inexpensive and efficient electric vehicles into the US light duty vehicle (LDV) sector. Scenarios are explored using the ANSWER-MARKAL model with a modified version of the Environmental Protection Agency's (EPA) 9-region database. Modified cost and performance projections for LDV technologies are adapted from the National Research Council (2013) optimistic case. Under our optimistic scenario (OPT) we find 15% and 47% adoption of battery electric vehicles (BEVs) in 2030 and 2050, respectively. In contrast, gasoline vehicles (ICEVs) remain dominant through 2050 in the EPA reference case (BAU). Compared to BAU, OPT gives 16% and 36% reductions in LDV greenhouse gas (GHG) emissions for 2030 and 2050, respectively, corresponding to 5% and 9% reductions in economy-wide emissions. Total nitrogen oxides, volatile organic compounds, and SO2 emissions are similar in the two scenarios due to intersectoral shifts. Moderate, economy-wide GHG fees have little effect on GHG emissions from the LDV sector but are more effective in the electricity sector. In the OPT scenario, estimated well-to-wheels GHG emissions from full-size BEVs with 100-mile range are 62 gCO2-e mi-1 in 2050, while those from full-size ICEVs are 121 gCO2-e mi-1.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Lifecycle performance assessment of fuel cell/battery electric vehicles

Parker Hannifin invests in new production plant in Chennai, India

Greenhouse gas emissions of conventional and alternative vehicles: Predictions based on energy policy analysis in South Korea

Analysis of policies to reduce oil consumption and greenhouse-gas emissions from the US transportation sector

Transportation in the United States is the leading sector for greenhouse gas (GHG) emissions, with its contributions increasing over the years. To achieve the US goal of net-zero emissions in 2050, the Federal Highway Administration has launched several programs to set goals and strategies for reducing the emissions in the transportation sector. Flexible pavements, an integral part of the transportation system, contribute significantly to the sector’s carbon footprint. This study investigates the carbon reduction strategies of various states (Florida, Illinois, New York, Pennsylvania, New Jersey, Massachusetts, California, Texas, South Dakota, and Alaska). In addition, life cycle assessments (LCAs) were conducted to quantify the contribution of asphalt concrete pavements toward the states’ goals. The LCA results, calculated for a lane-mile of pavement, considered materials, construction, maintenance, rehabilitation, and use stages. The results showed that the New Jersey pavement section had the highest energy consumption over its life cycle, while Illinois had the lowest. In addition, the maintenance and use stages accounted for a significant portion of the overall GHG emissions, contributing an average of 92% of the total energy consumed. These impacts were primarily influenced by the pavement’s condition, specifically its roughness and volume of vehicles traveling on it. While current transportation emission reduction strategies focus on curtailing on-road vehicles emissions, this study highlights the significant contributions of pavement structures to overall GHG emissions.

Taking Stock of Strategies on Climate Change and the Way Forward: A Strategic Climate Change Framework for Australia