Search

Abstract Air pollution from motor vehicles, electricity-generating plants, industry, and other sources can harm human health, injure crops and forests, damage building materials, and impair visibility. Economists sometimes analyze the social cost of these impacts, in order to illuminate tradeoffs, compare alternatives, and promote efficient use of scarce resource. In this paper, we compare estimates of the health and visibility costs of air pollution derived from a meta-hedonic price analysis, with an estimate of health costs derived from a damage-function analysis and an estimate of the visibility cost derived from contingent valuation. We find that the meta-hedonic price analysis produces an estimate of the health cost that lies at the low end of the range of damage-function estimates. This is consistent with hypotheses that on the one hand, hedonic price analysis does not capture all of the health costs of air pollution (because individuals may not be fully informed about all of the health effects), and that on the other hand, the value of mortality used in the high-end damage function estimates is too high. The analysis of the visibility cost of air pollution derived from a meta-hedonic price analysis produces an estimate that is essentially identical to an independent estimate based on contingent valuation. This close agreement lends some credence to the estimates. We then apply the meta hedonic-price model to estimate the visibility cost per kilogram of motor vehicle emissions.

Regulators, policy analysts, automobile manufacturers, environmental groups, and others are debating the merits of policies regarding the development and use of battery-powered electric vehicles (BPEVs). At the crux of this debate is lifecycle cost: the annualized initial vehicle cost, plus annual operating and maintenance costs, plus battery replacement costs. To address this issue of cost, we have developed a detailed model of the performance, energy use, manufacturing costs, retail costs, and lifecycle cost of electric vehicles and comparable gasoline internal-combustion engine vehicles (ICEVs). This effort is an improvement over most previous studies of electric vehicle costs because instead of assuming important parameter values for such variables as vehicle efficiency and battery costs, we model these values in detail. We find that in order for electric vehicles to be cost-competitive with gasoline ICEVs, batteries must have a lower manufacturing cost, and a longer life, than the best lithium-ion and nickel-metal hydride batteries we modeled. We believe that it is most important to reduce the battery manufacturing cost to $100/kWh or less, attain a cycle life of 1200 or more and a calendar life of 12 years or more, and aim for a specific energy of around 100 Wh/kg.

Greenhouse gas emissions in developing countries are increasing most rapidly in the transportation sector. Even people with low incomes are meeting their need for mobility, and projected income growth over the next two decades suggests that many more will acquire personal modes of transportation. How this will affect the earth's climate is a great concern.In Delhi, India, transportation sector greenhouse gas emissions are expected to soar. There are policy and technology choices that could significantly lower the emissions growth rate while increasing mobility, improving air quality, reducing traffic congestion, and lowering transport and energy costs. To realize these benefits, vision, leadership, and political will must be brought to bear. Delhi has high vehicle ownership rates for the city's income level, increasing congestion, poor air quality, poor safety conditions, and insufficient coordination among the responsible government institutions. Travelers in Delhi desire transportation services, reflected by the increasing numbers of inexpensive but highly polluting scooters and motorcycles.This report creates two scenarios of greenhouse gas emissions from Delhi's transportation sector in 2020. It finds:•Greenhouse gas emissions quadruple in the high-GHG, or business-as-usual, scenario; but only double in the low scenario.•Transportation policies are readily available that will not only slow emissions growth, but also significantly improve local environmental, economic, and social conditions.•Improved technology would maximize the efficiency of automobiles, buses, and other modes of transportation and could play a key role in reducing emission increases.•Keeping many travel mode options available – including minicars and new efficient scooters and motorcycles – will help individuals at various income levels meet their mobility needs.•The time to act is now. The issues facing Delhi represent opportunities for improvement, but the longer authorities wait to address transportation inefficiencies, the more difficult and expensive it will be to produce a positive outcome.

The design and lifecycle cost model designs a motor vehicle to meet range and performance requirements specified by the modeler, and then calculates the initial retail cost and total lifecycle cost of the designed vehicle. The model can be used to investigate the relationship between the lifecycle cost -- the total cost of vehicle ownership and operation over the life of the vehicle -- and important parameters in the design and use of the vehicle.

The effects of ozone air pollution on the agricultural sector are an important environmental challenge facing policy makers. Most studies of the economic impact of air pollution on agriculture have found that a 25% reduction in ambient ozone would provide benefits of at least $1-2 billion annually in the United States. This paper extends existing research by estimating the benefits of a reduction in emissions from a major source of ozone formation: motor-vehicle emissions. An agricultural production model is combined with an analysis of motor-vehicle emissions and air quality to estimate the impacts of emissions from six different motor-vehicle classes, at both the regional and national level. The benefits to the agricultural sector from completely eliminating ozone precursor emissions from motor vehicles ranges between $3·5 and $6·1 billion annually.

This report is the first in a series of 20 that attempt to document the social cost of motor-vehicle use in the United States. The author suggests that beyond the hundreds of billions of dollars American drivers spend on vehicles, maintenance, fuel, tires, insurance, parking, tolls, registration and other items, there are a number of other costs to society. Those costs are bundled in the prices of non-transportation goods and services, such as “free” parking at a shopping mall, the costs of police protection, the judicial and legal system, the prison system, the protection of oil supplies, etc. In addition, there are the social costs of air pollution, pain and suffering due to accidents, and travel time. In the summary of costs of motor-vehicle use he provides a low and high cost, as well as low and high percentage of total for six categories.

Personal non-monetary costs are those unpriced costs of motor-vehicle use that a person imposes on herself as a result of her decision to travel. The largest personal costs of motor-vehicle use are personal travel time in uncongested conditions and the risk of getting into an accident that involves nobody else or would have happened regardless of the actions of others.

Personal non-monetary costs are those unpriced costs of motor-vehicle use that a person imposes on herself as a result of her decision to travel. The largest personal costs of motor-vehicle use are personal travel time in uncongested conditions and the risk of getting into an accident that revolves nobody else or would have happened regardless of the actions of others.

Over the past five years, analysts and policymakers have become increasingly interested in the “full social cost” of motor vehicle use. Not surprisingly, there is little agreement about how to estimate the social cost or why, with the result that estimates and interpretations can diverge tremendously. In this situation, policymakers and others who wish to apply estimates of the social cost of motor vehicle use might find it useful to have most of the major estimates summarized and evaluated in one place. Toward this end, we review the purpose, scope, and conclusions of most of the recent major U.S. studies, and summarize the cost estimates by individual category. We also assess the level of detail of each major cost estimate in the studies.

Every year, Americans drivers spend hundreds of billions of dollars on highway transportation. They pay for vehicles, maintenance, repair, fuel, lubricants, tires, parts, insurance, parking, tolls, registration, fees, and other items. These expenditures buy Americans considerable personal mobility and economic productivity.

Over the past five years, analysts and policy makers have become increasingly interested in the full social cost of motor-vehicle use. Researchers have performed social-cost analyses for a variety reasons, and have used them in a variety of ways, to support a wide range of policy positions. Some researchers have used social-cost analyses to argue that motor vehicles and gasoline are terrifically underpriced, while others have used them to downplay the need for drastic policy intervention in the transportation sector. In any case, social-cost analyses excite considerable interest, if only because nearly all of us use motor vehicles.

The use of energy accounts for a major fraction of all anthropogenic emissions of greenhouse gases (IPCC, 1995) , and in most industrialized countries the use of transportation fuels and electricity accounts for a major fraction of all energy-related emissions. In the transportation sector alone, emissions of carbon dioxide (CO2) from the production and use of motor-vehicle fuels account for as much as 30% of CO2 emissions from the use of all fossil fuels (DeLuchi, 1991). The production and use of fuels for transportation and electricity also results in emissions of other greenhouse gases, including methane (CH4) and nitrous oxide (N2O). In light of this, and in the face of growing concern about global climate change, analysts have started to evaluated energy strategies for their potential impact on global climate (EIA, 1991a; IEA, 1989; OTA, 1990; Victor, 1992).

In many urban areas, noise is a serious problem. Noise disturbs sleep, disrupts activities, hinders work, impedes learning, and causes stress (Linster, 1990). Indeed, surveys often find that noise is the most common disturbance in the home (Organization for Economic Cooperation and Development [OECD], 1988). And motor vehicles usually are the primary source of that noise (OECD, 1988)1.Noise is a prominent enough problem that it measurably affects the value of homes. Econometric or “hedonic” price analyses measure this effect by estimating the sales price of a house as a function of a number of important characteristics, including the ambient noise level or distance from a major noise source (Nelson, 1978; Hall and Welland, 1987; O’Byrne et al., 1985). If such an analysis does not omit important determinants of sales price, it can tell us how much an additional decibel of noise (above a certain threshold) reduces the value of a home2. This $/decibel measure, multiplied by the average value of homes, the number of homes exposed to noise above a threshold, and the amount of motor-vehicle noise above a threshold, will tell us the external “damage cost” of motor-vehicle noise in and around the home. The cost of noise in and around the home then can be scaled by the ratio of time spent in all activities affected by motor-vehicle noise to time spent in or around the home, to produce the total external damage cost of motor-vehicle noise.In this report, we present such a model of the total external damage cost of direct motor-vehicle noise in the U. S.3. We find that the external damage cost of direct motor-vehicle noise could range from as little as $100 million per year to approximately $40 billion per year (1990 data, 1991$), although we believe that the cost is not likely to exceed $5 billion. In sensitivity analyses presented at the end of the report, we show that this wide range is due primarily to uncertainty regarding the cost of noise per decibel above a threshold, the interest rate, the amount of noise attenuation due to ground cover and intervening structures, the threshold level below which damages are assumed to be zero, the density of housing alongside roads, average traffic speeds, and the cost of noise outside of the home.

In our analysis of the social cost of motor-vehicle use, many of our data sources, methods, and estimates of cost apply in the first instance to all classes of motor vehicles. For example, we are given, or can estimate from primary data, the following:- total government expenditures on the highways- the air-pollution damage cost of emissions from gasoline service stations- the air-pollution damage cost of emissions of PM10 from re-entrained road dust- highway-patrol expenditures- the cost of garages and parking spaces- the cost of oil spills, per barrel of oilAll of these costs pertain to all motor vehicles: all autos, trucks, and buses. Although it can be interesting to estimate the cost of all motor-vehicle use, it typically will be more useful to estimate the cost of different classes of vehicles or of different fuel types, because analysts, policy makers, and regulators typically are interested in specific classes of vehicles, and specific fuels, rather than all motor-vehicles as a group. (For example, pollution regulations are set for individual classes of vehicles, not for all motor vehicles as a class.) Thus, it is useful to carry the analysis of total social cost a step further, and take a cost that initially applies to all motor-vehicles and apportion it to specific vehicle and fuel classes. This report develops such “allocation factors,” which can be used to apportion or disaggregate a total cost to specific vehicle and fuel classes.

Motor vehicles and their related emission sources, such as petroleum refineries, emit many different kinds of air pollutants, which affect human health in a variety of ways. These health effects create a large economic cost to society. In this report, we estimate the social cost of many of the health effects of motor-vehicle air pollution.The relationship between changes in emissions related to motor-vehicle use and changes in health welfare (measured in dollars) can be modeled in three steps: 1) relate changes in emissions to changes in air quality; 2) relate changes in air quality to changes in physical health effects; and 3) relate changes in physical health effects to changes in economic welfare. We have made a detailed model of this sort to estimate the cost of the health effects of motor-vehicle air pollution1.We estimate the human-health cost of motor-vehicle air pollution in the entire U.S., in urban areas of the U.S., in rural areas of the U.S., and in 11 major metropolitan statistical areas (MSAs): Boston, Denver, Houston, Los Angeles, Minneapolis, New York, Philadelphia, Phoenix, St. Lotus, Spokane, and Washington D.C. We consider six types of motor vehicles: light-duty gasoline and diesel vehicles, light-duty gasoline and diesel trucks, and heavy-duty gasoline and diesel trucks. We estimate the number and type of health effects, and the monetized value of these effects, including total dollar costs, dollar costs per vehicle-mile of travel, and dollar costs per kg of pollutant emitted. Finally, we include an analysis of the three main sources of the costs: direct emissions from motor vehicles, emissions of road-dust particulate matter, and "upstream" emissions from gasoline stations, refineries, vehicle manufacturing, and so on.

In this Report, we explain how we model the contribution of motor-vehicles and other emissions sources to ambient air pollution.

Particles and gases in the atmosphere scatter and absorb light, and thereby reduce visibility (Watson and Chow, 1994; Richards et al., 1990; Ozkaynak et al., 1985). Although natural sources of particles, such as volcanoes, can significantly degrade visibility, it generally is true that “when visibility is poor...most particles are found to be of human origin, from sources such as power plants, vehicle exhaust, biomass burning, suspended dust, and industrial activities” (Watson and Chow, 1994, p.244). Poor visibility diminishes the enjoyment of scenic vistas and makes travel hazardous1. Statistical analyses of property values (discussed below) reveal that people are willing to pay extra for houses in areas with good visibility and air quality.The particles that are most efficient at scattering light are roughly the same size as the wavelength of visible light -- about 0.5 µm (Watson and Chow, 1994; Richards et al., 1990; Ozkaynak et al., 1985). Because most particles emitted by the combustion of diesel fuel, and some particles of re-entrained road dust, are 0.5 µm ± 0.4 µm, emissions related to motor-vehicle use can significantly degrade visibility. In support of this, Trijonis (1984) has estimated that direct emissions from heavy-duty diesel vehicles in California cause 10% to 20% of the light extinction.In this report, we review some of the literature on the cost of visibility, and then develop our own estimate of the cost. For our own estimate, we select a simple hedonic model, from the meta-analysis of Smith and Huang (1995), of the relationship between the asset value of homes, levels of total suspended particulate matter (TSP), and per- capita income. Because the hedonic price of TSP undoubtedly comprises the price of visibility (as well as the price of other effects of TSP, such as bad health), and because we can relate TSP emissions to visibility, we can use this hedonic model to estimate the visibility cost of TSP emissions. Specifically, we will apply this hedonic meta-model to estimate the visibility cost of all anthropogenic TSP pollution, and of motor-vehicle TSP pollution, in every county in the U. S. in 1990.

In this Report, we seek to answer the question: “If the U.S. highway transportation sector did not use oil, how much would the U.S. Federal government reduce its military commitment in the Persian Gulf?” The analysis goes in four parts.First, we explain that the U.S. protects its “oil interests” in the Persian Gulf primarily to prevent supply disruptions and sudden price rises and the attendant macroeconomic problems. We cite evidence (including statements by the Joint Chiefs of Staff) that the U.S. Congress and the military do indeed plan and budget military operations for the Persian Gulf on account of U.S. oil interests there. We review and rebut arguments that the U.S. has other interests in the region substantially more important than those related to oil.Second, we review the best available estimates of the amount of that the U.S. military spends to protect U .S. interests in the Persian Gulf. As part of the review we address the difficult questions of how to allocate joint costs to particular programs.Third, we consider whether any of the economic assistance granted to countries of the Middle East is related to U.S. oil interests in the region. We show that most of this assistance goes to Israel and Egypt, and probably is not motivated by a desire to protect U.S. oil interests in nearby Arab countries.Finally, we work from our estimate of the cost of defending all U.S. interests in the Persian Gulf towards an estimate of the military cost of using oil in highway transportation. This proceeds in several steps: i) estimate how much military expenditure would be foregone if there were no oil in the Persian Gulf region; ii) estimate how much would be foregone if the U.S. did not produce or consume oil from the Persian Gulf, but other countries still did; iii) estimate how much would be foregone if U.S. producers had investments in the Gulf, but the U.S. did not consume Persian Gulf oil; iv) and lastly, estimate how much would be foregone if motor vehicles in the U.S. did not use oil, but other sectors still did and the U.S. (and other countries) still produced and consumed oil from the Gulf. This last is the bottom line of our analysis. Our analysis of these steps generally is illustrative, not rigorously quantitative. In the end, we estimate that if U.S. motor vehicles did not use petroleum, the U.S. would reduce its defense expenditures in the long run by roughly $1 to 10 billion dollars per year.

The detrimental effects of ambient ozone on crops, even at relatively low concentrations, are well-established (Thompson et al., 1976; Heck and Brandt, 1977; Heck et al., 1982; Environmental Protection Agency, 1984; California Air Resources Board, 1987; Olszyk et al., 1988a, 1988b; Heagle et al., 1986; McCool et al., 1986, Ashmore, 1991). Ozone enters plant leaves through the stomatal openings in the leaf surface and then produces byproducts that reduce the efficiency of photosynthesis (CARB, 1987). Research suggests that ozone, either alone or in combination with nitrogen dioxide and sulfur dioxide, may be responsible for up to 90 percent of U.S. crop losses resulting from air pollution (Heck et al., 1982). In an effort to address this problem, the Clean Air Act and its amendments include air pollution damages to vegetation as one of the criteria by which secondary national ambient air quality standards are evaluated (Adams et al., 1984).There is, of course, an economic cost associated with this reduced productivity. In this paper we use a formal model of agricultural production and demand to estimate the cost of crop damage1 due to all anthropogenic ozone air pollution, and to ozone air pollution attributable to motor-vehicle use in the U. S. in 1990.

I arrived here at the UC Transportation Center just nine months ago. A former lawyer and aspiring writer, I had only a layman's knowledge of transportation systems, mostly based on my personal experiences. Growing up in Hilo, Hawaii, I thought traffic jams meant having to circle the parking lot twice to find a space. No one worried about ozone or took cars in for smog checks. Every desirable destination - shopping malls, movie theaters, beaches, even downtown - was within a few minutes' drive.

Policy makers in transportation often make investment decisions involving hundreds of millions of dollars. Typically they evaluate a wide range of alternatives -- from expanding highway capacity to managing existing demand to building a new rail line -- with respect to a broad array of seemingly incommensurable criteria. In theory, a policy maker can evaluate alternatives by cost-benefit analysis, in which one quantifies and monetizes all of the costs and benefits to society, and picks the alternative that yields the greatest net present-value of benefits. In this report, we quantify a key component of the social-cost part of cost-benefit analysis: emissions of air pollutants from different transportation modes.

Hydrogen is an especially attractive transportation fuel. It is the least polluting fuel available, and can be produced anywhere there is water and a clean source of electricity. A fuel cycle in which hydrogen is produced by solar-electrolysis of water, or by gasification of renewably grown biomass, and then used in a fuel-cell powered electric-motor vehicle (FCEV), would produce little or no local, regional, or global pollution.Hydrogen FCEVs would combine the best features of battery-powered electric vehicles (BPEVs) -- zero emissions, high efficiency, quiet operation and long life -- with the long range and fast refueling time of internal-combustion-engine vehicles (ICEVs). If fuel-cell technology develops as hoped, then hydrogen FCEVs will be a significant advance over both hydrogen ICEVs and solar BPEVs: they will be cleaner and more efficient than hydrogen ICEVs, have a much shorter refueling time than BPEVs, and have a lower lufecycle cost than both. Solar-hydrogen fuel-cell vehicles would be general-purpose zero-emission vehicles, and could be an important component of strategy for reducing dependence on imported oil, mitigating global warming, and improving urban air quality, at an acceptable cost.

--We analyze the impact of the use of electric vehicles (EVs) energy consumption in general and petroleum consumption in particular. The analysis is conducted for sub-compact cars, small vans, and large vans for the years 1995 and 2010. We compare per-mile primary energy consumption of EVs and gasoline internal combustion engine vehicles (ICEVs), for each of four primary energy sources: petroleum, coal, natural gas, and biomass. When petroleum, natural gas, or biomass is the primary energy source, EVs with current technology will consume more energy per mile than ICEVs, but EVs with advanced technology will consume less. If coal is the primary energy source, both current- and advanced-technology EVs will consume less energy per mile than ICEVs. We find that the magnitude of petroleum displacement by EVs depends mainly on the amount of petroleum used for electricity generation. In many areas of the U.S., EVs will reduce per-mile petroleum use by over 90%, because the vast majority of electricity is generated from non-petroleum fuels. In areas where a relatively large portion of electricity is generated from petroleum (such as New York), EVs will reduce per-mile petroleum use 65%.