Electrification of Transit Buses in the United States Reduces Greenhouse Gas Emissions.

The transportation sector is the largest emitter of greenhouse gas emissions (GHGs) in the United States. Increased use of public transit and electrification of public transit could help reduce these emissions. The electrification of public transit systems could also reduce air pollutant emissions in densely populated areas, where air pollution disproportionally burdens vulnerable communities with high health impacts and associated social costs. We analyze the life cycle emissions of transit buses powered by electricity, diesel, gasoline, and compressed natural gas and model GHGs and air pollutants mitigated for a transition to a fully electric U.S. public transit bus fleet using transit agency-level data. The electrification of the U.S. bus fleet would reduce several conventional air pollutants and has the potential to reduce transit bus GHGs by 33-65% within the next 14 years depending on how quickly the transition is made and how quickly the electricity grid decarbonizes. A levelized cost of driving analysis shows that with falling capital costs and an increase in annual passenger-kilometers of battery electric buses, the technology could reach levelized cost parity with diesel buses when electric bus capital costs fall below about $670 000 per bus.

Expert assessments of the cost and expected future performance of proton exchange membrane fuel cells for vehicles.

Despite decades of development, proton exchange membrane fuel cells (PEMFCs) still lack wide market acceptance in vehicles. To understand the expected trajectories of PEMFC attributes that influence adoption, we conducted an expert elicitation assessment of the current and expected future cost and performance of automotive PEMFCs. We elicited 39 experts' assessments of PEMFC system cost, stack durability, and stack power density under a hypothetical, large-scale production scenario. Experts assessed the median 2017 automotive cost to be $75/kW, stack durability to be 4,000 hours, and stack power density to be 2.5 kW/L. However, experts ranged widely in their assessments. Experts' 2017 best cost assessments ranged from $40 to $500/kW, durability assessments ranged from 1,200 to 12,000 hours, and power density assessments ranged from 0.5 to 4 kW/L. Most respondents expected the 2020 cost to fall short of the 2020 target of the US Department of Energy (DOE). However, most respondents anticipated that the DOE's ultimate target of $30/kW would be met by 2050 and a power density of 3 kW/L would be achieved by 2035. Fifteen experts thought that the DOE's ultimate durability target of 8,000 hours would be met by 2050. In general, experts identified high Pt group metal loading as the most significant barrier to reducing cost. Recommended research and development (R&D) funding was allocated to "catalysts and electrodes," followed in decreasing amount by "fuel cell performance and durability," "membranes and electrolytes," and "testing and technical assessment." Our results could be used to inform public and private R&D decisions and technology roadmaps.

Air Pollution, Greenhouse Gas, and Traffic Externality Benefits and Costs of Shifting Private Vehicle Travel to Ridesourcing Services.

On-demand ridesourcing services from transportation network companies (TNCs), such as Uber and Lyft, have reshaped urban travel and changed externality costs from vehicle emissions, congestion, crashes, and noise. To quantify these changes, we simulate replacing private vehicle travel with TNCs in six U.S. cities. On average, we find a 50-60% decline in air pollutant emission externalities from NOx, PM2.5, and VOCs due to avoided "cold starts" and relatively newer, lower-emitting TNC vehicles. However, increased vehicle travel from deadheading creates a ∼20% increase in fuel consumption and associated greenhouse gas emissions and a ∼60% increase in external costs from congestion, crashes, and noise. Overall, shifting private travel to TNCs increases external costs by 30-35% (adding 32-37 ¢ of external costs per trip, on average). This change in externalities increases threefold when TNCs displace transit or active transport, drops by 16-17% when TNC vehicles are zero-emission electric, and potentially results in reduced externalities when TNC rides are pooled.

Hydrogen Storage for Fuel Cell Electric Vehicles: Expert Elicitation and a Levelized Cost of Driving Model.

A cost-effective and compact hydrogen storage system could advance fuel cell electric vehicles (FCEVs). Today's commercial FCEVs incorporate storage that is projected to be heavier, larger, and costlier than targets set by the U.S. Driving Research and Innovation for Vehicle efficiency and Energy sustainability Partnership (U.S. DRIVE). To inform research and development (R&D), we elicited 31 experts' assessments of expected future costs and capacities of storage systems. Experts suggested that systems would approach U.S. DRIVE's ultimate capacity targets but fall short of cost targets at a high production volume. The 2035 and 2050 median costs anticipated by experts were $13.5 and $10.53/kWhH2, gravimetric capacities of 5.2 and 5.6 wt %, and volumetric capacities of 0.93 and 1.33 kWhH2/L, respectively. To meet U.S. DRIVE's targets, experts recommended allocating the majority of government hydrogen storage R&D funding to materials development. Furthermore, we incorporated experts' cost assessments into a levelized cost of driving model. Given technical and fuel price uncertainty, FCEV costs ranged from $0.38 to $0.45/mile ($0.24-$0.28/km) in 2020, $0.30 to $0.33/mile ($0.19-$0.21/km) in 2035-2050, and $0.27 to $0.31/mile ($0.17-$0.19/km) in 2050. Depending on fuel, electricity, and battery prices, our findings suggest that FCEVs could compete with conventional and alternative fuel vehicles by 2035.

Environmental and Economic Trade-Offs of City Vehicle Fleet Electrification and Photovoltaic Installation in the U.S. PJM Interconnection.

Several cities are considering both photovoltaic (PV) generation and electric vehicles (EVs). A city evaluating a transition to an EV fleet has different decision criteria than private actors. This paper conducts a life cycle assessment and cost-benefit analysis for city vehicle fleet electrification decisions, using Pittsburgh, PA as a case study. The analysis includes several electric-grid scenarios and assesses the installation of distributed PV at city-owned parking facilities. Costs were included while comparing vehicle options, as were the emissions and externality costs of GHGs, SO2, and NOx from direct and upstream effects. For the vehicles under consideration for Pittsburgh's fleet, BEVs were always found to have lower GHG emissions than Hybrids. Lowering external costs with fleet electrification, however, was found to be dependent on a rapid transition to a cleaner grid. A peak capacity of about 6000 kW of PV is possible on Pittsburgh city-owned parking facilities. This capacity would produce greater than 30 times the yearly energy needs of the city's municipal vehicle fleet. However, the PV canopy structures over parking spaces potentially make systems costs prohibitive. This study provides a method for cities, counties, and other stakeholders to evaluate the potential benefits and costs of EVs and PV generation.

A mathematical model to plan for long-term effects of water conservation choices on dry weather wastewater flows and concentrations.

In many cities, sewer systems are experiencing conditions that are significantly different from those for which they were designed. Factors such as water conservation efforts, changes in population, and efforts to reduce infiltration are altering the quantity and quality of sewage. These changes may affect the ability of sewers to maintain self-cleansing velocities, which are crucial to avoiding solids settling and corrosion issues. Further, such changes may alter the timeline for expected wastewater plant expansion. The present work proposes a method for predicting average annual dry weather wastewater flow, as well as pollutant load and concentration over time. The method takes into account potential declines in per person wastewater production due to water conservation and reuse practices, as well as other potential changes such as shifts in population, transformations in industrial wastewater production, and variations in dry weather infiltration. Results show that the amount of dry weather infiltration will play a large role in whether or not conservation will affect self-cleansing velocities or plant expansions. Conservation is most beneficial to systems with high levels of dry weather infiltration since plant expansion could be avoided; and most detrimental to systems with low levels of infiltration since low flow conditions could lead to settling and corrosion in the sewer. Furthermore, the rate of implementation of conservation efforts influences when impacts to the system would occur. Utility planners will be able to use this method to predict treatment plant upgrade and expansion needs more accurately as well as to assess the relative value of utility-based maintenance activities and conservation practices.

Life cycle greenhouse gas emissions from U.S. liquefied natural gas exports: implications for end uses.

This study analyzes how incremental U.S. liquefied natural gas (LNG) exports affect global greenhouse gas (GHG) emissions. We find that exported U.S. LNG has mean precombustion emissions of 37 g CO2-equiv/MJ when regasified in Europe and Asia. Shipping emissions of LNG exported from U.S. ports to Asian and European markets account for only 3.5-5.5% of precombustion life cycle emissions, hence shipping distance is not a major driver of GHGs. A scenario-based analysis addressing how potential end uses (electricity and industrial heating) and displacement of existing fuels (coal and Russian natural gas) affect GHG emissions shows the mean emissions for electricity generation using U.S. exported LNG were 655 g CO2-equiv/kWh (with a 90% confidence interval of 562-770), an 11% increase over U.S. natural gas electricity generation. Mean emissions from industrial heating were 104 g CO2-equiv/MJ (90% CI: 87-123). By displacing coal, LNG saves 550 g CO2-equiv per kWh of electricity and 20 g per MJ of heat. LNG saves GHGs under upstream fugitive emissions rates up to 9% and 5% for electricity and heating, respectively. GHG reductions were found if Russian pipeline natural gas was displaced for electricity and heating use regardless of GWP, as long as U.S. fugitive emission rates remain below the estimated 5-7% rate of Russian gas. However, from a country specific carbon accounting perspective, there is an imbalance in accrued social costs and benefits. Assuming a mean social cost of carbon of $49/metric ton, mean global savings from U.S. LNG displacement of coal for electricity generation are $1.50 per thousand cubic feet (Mcf) of gaseous natural gas exported as LNG ($.028/kWh). Conversely, the U.S. carbon cost of exporting the LNG is $1.80/Mcf ($.013/kWh), or $0.50-$5.50/Mcf across the range of potential discount rates. This spatial shift in embodied carbon emissions is important to consider in national interest estimates for LNG exports.

Valuation of plug-in vehicle life-cycle air emissions and oil displacement benefits.

We assess the economic value of life-cycle air emissions and oil consumption from conventional vehicles, hybrid-electric vehicles (HEVs), plug-in hybrid-electric vehicles (PHEVs), and battery electric vehicles in the US. We find that plug-in vehicles may reduce or increase externality costs relative to grid-independent HEVs, depending largely on greenhouse gas and SO(2) emissions produced during vehicle charging and battery manufacturing. However, even if future marginal damages from emissions of battery and electricity production drop dramatically, the damage reduction potential of plug-in vehicles remains small compared to ownership cost. As such, to offer a socially efficient approach to emissions and oil consumption reduction, lifetime cost of plug-in vehicles must be competitive with HEVs. Current subsidies intended to encourage sales of plug-in vehicles with large capacity battery packs exceed our externality estimates considerably, and taxes that optimally correct for externality damages would not close the gap in ownership cost. In contrast, HEVs and PHEVs with small battery packs reduce externality damages at low (or no) additional cost over their lifetime. Although large battery packs allow vehicles to travel longer distances using electricity instead of gasoline, large packs are more expensive, heavier, and more emissions intensive to produce, with lower utilization factors, greater charging infrastructure requirements, and life-cycle implications that are more sensitive to uncertain, time-sensitive, and location-specific factors. To reduce air emission and oil dependency impacts from passenger vehicles, strategies to promote adoption of HEVs and PHEVs with small battery packs offer more social benefits per dollar spent.

Drinking Water Utility-Level Understanding of Climate Change Effects to System Reliability.

Climate change hazards, including increased temperatures, drought, sea level rise, extreme precipitation, wildfires, and changes in freeze-thaw cycles, are expected to degrade drinking water utility system infrastructure and decrease the reliability of water provision. To assess how drinking water utility manager perceptions of these risks affect utility planning, 60 semistructured interviews were conducted with utilities of various sizes, source water supplies, and United States geographical regions. This study analyzes these interviews (1) to evaluate which climate hazards are of primary concern to drinking water managers, (2) to develop a mental model framework for assessing utility-level understanding of climate change risks to system reliability, and (3) to examine the status of current water utility adaptation planning. The results show that concern and awareness of climate hazard risks vary geographically and are grounded in historical exposure; some participants do not believe climate change will influence their system's overall reliability. When considering climate change risks, utility managers tend to focus on effects to water supply and infrastructure, as opposed to changes in operations and maintenance, water quality, or business functions. Most surveyed utilities do not have comprehensive climate adaptation plans despite federal and professional recommendations. The range of beliefs and actions concerning climate adaptation planning indicates that utilities need directed guidance, and policymakers should consider including climate hazards and projections as part of required utility risk and resilience assessments.

Potentials for sustainable transportation in cities to alleviate climate change impacts.

Reducing greenhouse gas emissions (GHG) is an important social goal to mitigate climate change. A common mitigation paradigm is to consider strategy "wedges" that can be applied to different activities to achieve desired GHG reductions. In this policy analysis piece, we consider a wide range of possible strategies to reduce light-duty vehicle GHG emissions, including fuel and vehicle options, low carbon and renewable power, travel demand management and land use changes. We conclude that no one strategy will be sufficient to meet GHG emissions reduction goals to avoid climate change. However, many of these changes have positive combinatorial effects, so the best strategy is to pursue combinations of transportation GHG reduction strategies to meet reduction goals. Agencies need to broaden their agendas to incorporate such combination in their planning.

Drone flight data reveal energy and greenhouse gas emissions savings for very small package delivery.

Uncrewed aerial vehicles (UAVs) for last-mile deliveries will affect the energy productivity of delivery and require new methods to understand energy consumption and greenhouse gas (GHG) emissions. We combine empirical testing of 188 quadcopter flights across a range of speeds with a first-principles analysis to develop a usable energy model and a machine-learning algorithm to assess energy across takeoff, cruise, and landing. Our model shows that an electric quadcopter drone with a very small package (0.5 kg) would consume approximately 0.08 MJ/km and result in 70 g of CO2e per package in the United States. We compare drone delivery with other vehicles and show that energy per package delivered by drones (0.33 MJ/package) can be up to 94% lower than conventional transportation modes, with only electric cargo bicycles providing lower GHGs/package. Our open model and coefficients can assist stakeholders in understanding and improving the sustainability of small package delivery.

The impact of Uber and Lyft on vehicle ownership, fuel economy, and transit across U.S. cities.

We estimate the effects of transportation network companies (TNCs) Uber and Lyft on vehicle ownership, fleet average fuel economy, and transit use in U.S. urban areas using a set of difference-in-difference propensity score-weighted regression models that exploit staggered market entry across the U.S. from 2011 to 2017. We find evidence that TNC entry into urban areas causes an average 0.7% increase in vehicle registrations with significant heterogeneity in these effects across urban areas: TNC entry produces larger vehicle ownership increases in urban areas with higher initial ownership (car-dependent cities) and in urban areas with lower population growth (where TNC-induced vehicle adoption outpaces population growth). We also find no statistically significant average effect of TNC entry on fuel economy or transit use but find evidence of heterogeneity in these effects across urban areas, including larger transit ridership reductions after TNC entry in areas with higher income and more childless households.

In-flight positional and energy use data set of a DJI Matrice 100 quadcopter for small package delivery.

We autonomously directed a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or "drone" to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, were varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones.

Net-societal and net-private benefits of some existing vehicle crash avoidance technologies.

Most light-duty vehicle crashes occur due to human error. Many of these crashes could be avoided or made less severe with the aid of crash avoidance technologies. These technologies can assist the driver in maintaining control of the vehicle when a possibly dangerous situation arises by issuing alerts to the driver and in a few cases, responding to the situation itself. This paper estimates the societal and private benefits and costs associated with three crash avoidance technologies, blind-spot monitoring, lane departure warning, and forward-collision warning, for all light duty passenger vehicles in the U.S. for the year 2015. The three technologies could collectively prevent up to 1.6 million crashes each year including 7200 fatal crashes. In this paper, the authors estimated the net-societal benefits to the overall society from avoiding the cost of the crashes while also estimating the private share of those benefits that are directly affecting the crash victims. For the first generation warning systems, net-societal benefits and net-private benefits are positive. Moreover, the newer generation of improved warning systems and active braking should make net benefits even more advantageous.

Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery.

The use of automated, unmanned aerial vehicles (drones) to deliver commercial packages is poised to become a new industry, significantly shifting energy use in the freight sector. Here we find the current practical range of multi-copters to be about 4 km with current battery technology, requiring a new network of urban warehouses or waystations as support. We show that, although drones consume less energy per package-km than delivery trucks, the additional warehouse energy required and the longer distances traveled by drones per package greatly increase the life-cycle impacts. Still, in most cases examined, the impacts of package delivery by small drone are lower than ground-based delivery. Results suggest that, if carefully deployed, drone-based delivery could reduce greenhouse gas emissions and energy use in the freight sector. To realize the environmental benefits of drone delivery, regulators and firms should focus on minimizing extra warehousing and limiting the size of drones.

Author Correction: Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery.

In the original version of this Article, the first sentence of the sixth paragraph of the "Comparing emissions" section, the Results originally incorrectly read as 'In the base case, delivery of a small (0.5 kg) package with the small quadrotor drone has lower impacts than delivery by diesel truck, ranging from a 59% reduction in GHGs in California, to a 17% reduction in Missouri'. The correct version states '54%' instead of '59%' and '23%' instead of '17%'.The fourth sentence of the same paragraph originally incorrectly read as 'In the base case, delivery of a medium-sized (8 kg) package has 17% lower GHGs than delivery by truck in California, is about equivalent to delivery trucks for the U.S. average electricity mix, but has 77% higher GHGs than truck delivery in Missouri, which has a carbon-intensive electricity grid'. The correct version states 'In the base case, delivery of a medium-sized (8 kg) package has 9% lower GHGs than delivery by truck in California, is about 24% higher than delivery trucks for the U.S. average electricity mix, and has 50% higher GHGs than truck delivery in Missouri, which has a carbon-intensive electricity grid.The last sentence of the seventh paragraph of the same section originally incorrectly read as 'Because of the importance of electricity used to power the octocopter, charging with low-carbon electricity of 200 g GHG/kWh can reduce delivered package GHGs by 34% compared to diesel trucks'. The correct version states '37%' instead of '34%'.These errors have been corrected in both the PDF and HTML versions of the Article.

Cost and benefit estimates of partially-automated vehicle collision avoidance technologies.

Many light-duty vehicle crashes occur due to human error and distracted driving. Partially-automated crash avoidance features offer the potential to reduce the frequency and severity of vehicle crashes that occur due to distracted driving and/or human error by assisting in maintaining control of the vehicle or issuing alerts if a potentially dangerous situation is detected. This paper evaluates the benefits and costs of fleet-wide deployment of blind spot monitoring, lane departure warning, and forward collision warning crash avoidance systems within the US light-duty vehicle fleet. The three crash avoidance technologies could collectively prevent or reduce the severity of as many as 1.3 million U.S. crashes a year including 133,000 injury crashes and 10,100 fatal crashes. For this paper we made two estimates of potential benefits in the United States: (1) the upper bound fleet-wide technology diffusion benefits by assuming all relevant crashes are avoided and (2) the lower bound fleet-wide benefits of the three technologies based on observed insurance data. The latter represents a lower bound as technology is improved over time and cost reduced with scale economies and technology improvement. All three technologies could collectively provide a lower bound annual benefit of about $18 billion if equipped on all light-duty vehicles. With 2015 pricing of safety options, the total annual costs to equip all light-duty vehicles with the three technologies would be about $13 billion, resulting in an annual net benefit of about $4 billion or a $20 per vehicle net benefit. By assuming all relevant crashes are avoided, the total upper bound annual net benefit from all three technologies combined is about $202 billion or an $861 per vehicle net benefit, at current technology costs. The technologies we are exploring in this paper represent an early form of vehicle automation and a positive net benefit suggests the fleet-wide adoption of these technologies would be beneficial from an economic and social perspective.

Life cycle assessment and grid electricity: what do we know and what can we know?

The generation and distribution of electricity comprises nearly 40% of U.S. CO(2), emissions, as well as large shares of SO(2), NO(x), small particulates, and other toxins. Thus, correctly accounting for these electricity-related environmental releases is of great importance in life cycle assessment of products and processes. Unfortunately, there is no agreed-upon protocol for accounting for the environmental emissions associated with electricity, as well as significant uncertainty in the estimates. Here, we explore the limits of current knowledge about grid electricity in LCA and carbon footprinting for the U.S. electrical grid, and show that differences in standards, protocols, and reporting organizations can lead to important differences in estimates of CO(2) SO(2), and NO(x) emissions factors. We find a considerable divergence in published values for grid emissions factor in the U.S. We discuss the implications of this divergence and list recommendations for a standardized approach to accounting for air pollution emissions in life cycle assessment and policy analyses in a world with incomplete and uncertain information.

Life cycle assessment of greenhouse gas emissions from plug-in hybrid vehicles: implications for policy.

Plug-in hybrid electric vehicles (PHEVs), which use electricity from the grid to power a portion of travel, could play a role in reducing greenhouse gas (GHG) emissions from the transport sector. However, meaningful GHG emissions reductions with PHEVs are conditional on low-carbon electricity sources. We assess life cycle GHG emissions from PHEVs and find that they reduce GHG emissions by 32% compared to conventional vehicles, but have small reductions compared to traditional hybrids. Batteries are an important component of PHEVs, and GHGs associated with lithium-ion battery materials and production account for 2-5% of life cycle emissions from PHEVs. We consider cellulosic ethanol use and various carbon intensities of electricity. The reduced liquid fuel requirements of PHEVs could leverage limited cellulosic ethanol resources. Electricity generation infrastructure is long-lived, and technology decisions within the next decade about electricity supplies in the power sector will affectthe potential for large GHG emissions reductions with PHEVs for several decades.