Lester B. Lave’s research while affiliated with Carnegie Mellon University and other places

Turbocharged direct injection (TDI) diesel and hybridized electric gasoline (HEV) vehicles provide higher fuel economy, but have higher manufacturing costs and sell at higher prices than conventional gasoline vehicles. All other attributes being equal, rational consumers expect to recover this price premium in fuel savings over the vehicle lifetime. Since many owners sell their vehicle after three to five years, resale prices should also reflect fuel savings. Here, we employ data from used vehicle auctions in 2008–2009 for paired alternative and conventional vehicles to compare the difference in resale prices to the expected fuel savings and the five-year cost of ownership expressed as the net present value (NPV). To estimate resale prices,we group the auction data by season and by year. We then correct for accumulated odometer mileage, which accounts for most of the variability in prices. At five years, higher fuel economy vehicles retain a higher proportion of their initial price than conventional options. The ratio of the resale value to the initial purchase price increases at higher fuel prices. For the paired HEV – conventional passenger vehicles, the difference in resale prices approximates the expected future fuel savings. The price difference for TDI diesel–gasoline pairs exceeds the fuel savings; other attributes such as performance or prestige may account for this difference. Regardless of the mechanism, the fuel savings and higher resale values compensate for the price premium for the TDI diesel and HEV options.

There is growing interest in reducing energy use and emissions of carbon dioxide from the residential sector by deploying cost-effectiveness energy efficiency measures. However, there is still large uncertainty about the magnitude of the reductions that could be achieved by pursuing different energy efficiency measures across the nation. Using detailed estimates of the current inventory and performance of major appliances in U.S. homes, we model the cost, energy and CO2 emissions reduction if they were replaced with alternatives that consume less energy or emit less CO2. We explore trade-offs between reducing CO2, reducing primary or final energy, or electricity consumption. We explore switching between electricity and direct fuel use, and among fuels. The trade-offs between different energy efficiency policy goals, as well as the environmental metrics used, are important but have been largely unexplored by previous energy modelers and policy-makers. We find that overnight replacement of the full stock of major residential appliances sets an upper bound of just over 710x106 tonnes/year of CO2 or a 56% reduction from baseline residential emissions. However, a policy designed instead to minimize primary energy consumption instead of CO2 emissions will achieve a 48% reduction in annual carbon dioxide emissions from the nine largest energy consuming residential end-uses. Thus, we explore the uncertainty regarding the main assumptions and different policy goals in a detailed sensitivity analysis.

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.

Inês Azevedo is Assistant Research Professor in the Department of Engineering and Public Policy at Carnegie Mellon University and Executive Director of the Center for Climate and Energy Decision Making sponsored by NSF. Her research interests lie at the intersection of environmental, technical, and economic issues, such as how to address the challenge of climate change and to move towards a more sustainable energy system. Dr. Azevedo received a B.Sc. and M.Sc. in Environmental Engineering and an M.Sc. in Engineering Policy and Management of Technology from the Instituto Superior Técnico in Lisbon, Portugal. She received a Ph.D. in Engineering and Public Policy from Carnegie Mellon.

We explore the optimal size of the transmission line from distant wind farms, modeling the tradeoff between transmission cost and benefit from delivered wind power. We also examine the benefit of connecting a second wind farm, requiring additional transmission, in order to increase output smoothness. Since a wind farm has a low capacity factor, the transmission line would not be heavily loaded, on average; depending on the time profile of generation, for wind farms with capacity factor of 29-34%, profit is maximized for a line that is about 3/4 of the nameplate capacity of the wind farm. Although wind generation is inexpensive at a good site, transmitting wind power over 1600Â km (about the distance from Wyoming to Los Angeles) doubles the delivered cost of power. As the price for power rises, the optimal capacity of transmission increases. Connecting wind farms lowers delivered cost when the wind farms are close, despite the high correlation of output over time. Imposing a penalty for failing to deliver minimum contracted supply leads to connecting more distant wind farms.

Generators installed for backup power during blackouts could help satisfy peak electricity demand; however, many are diesel generators with nonnegligible air emissions that may damage air quality and human health. The full (private and social) cost of using diesel generators with and without emission control retrofits for fine particulate matter (PM2.5) and nitrogen oxides (NOx) were compared with a new natural gas turbine peaking plant. Lower private costs were found for the backup generators because the capital costs are mostly ascribed to reliability. To estimate the social costs from air quality, the changes in ambient concentrations of ozone (O3) and PM2.5 were modeled using the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) chemical transport model. These air quality changes were translated to their equivalent human health effects using concentration-response functions and then into dollars using estimates of "willingness-to-pay" to avoid ill health. As a case study, 1000 MW of backup generation operating for 12 hr/day for 6 days in each of four eastern U.S. cities (Atlanta, Chicago, Dallas, and New York) was modeled. In all cities, modeled PM2.5 concentrations increased (up to 5 microg/m3) due mainly to primary emissions. Smaller increases and decreases were observed for secondary PM2.5 with more variation between cities. Increases in NOx, emissions resulted in significant nitrate formation (up to 1 microg/m3) in Atlanta and Chicago. The NOx emissions also caused O3 decreases in the urban centers and increases in the surrounding areas. For PM2.5, a social cost of approximately $2/kWh was calculated for uncontrolled diesel generators in highly populated cities but was under 10 cent/kWh with PM2.5 and NOx controls. On a full cost basis, it was found that properly controlled diesel generators are cost-effective for meeting peak electricity demand. The authors recommend NOx and PM2.5 controls.