Inês L. Azevedo

The Transition to Solid-State Lighting

Lighting constitutes more than 20% of total U.S. electricity consumption, a similar fraction in the European Union, and an even higher fraction in many developing countries. Because many current lighting technologies are highly inefficient, improved technologies for lighting hold great potential for energy savings and for reducing associated greenhouse gas emissions. Solid-state lighting shows great promise as a source of efficient, affordable, color-balanced white light. Indeed, assuming market discount rates, engineering-economic analysis demonstrates that white solid-state lighting already has a lower levelized annual cost (LAC) than incandescent bulbs. The LAC for white solid-state lighting will be lower than that of the most efficient fluorescent bulbs by the end of this decade. However, a large literature indicates that households do not make their decisions in terms of simple expected economic value. After a review of the technology, we compare the electricity consumption, carbon emissions, and cost-effectiveness of current lighting technologies, accounting for expected performance evolution through 2015. We then simulate the lighting electricity consumption and implicit greenhouse gases emissions for the U.S. residential and commercial sectors through 2015 under different policy scenarios: voluntary solid-state lighting adoption, implementation of lighting standards in new construction, and rebate programs or equivalent subsidies. Finally, we provide a measure of cost-effectiveness for solid-state lighting in the context of other climate change abatement policies.

Marginal Emissions Factors for the U.S. Electricity System

There is growing interest in reducing emissions from electricity generation in the United States (U.S.). Renewable energy, energy efficiency, and energy conservation are all commonly suggested solutions. Both supply- and demand-side interventions will displace energy-and emissions-from conventional generators. Marginal emissions factors (MEFs) give a consistent metric for assessing the avoided emissions resulting from such interventions. This paper presents the first systematic calculation of MEFs for the U.S. electricity system. Using regressions of hourly generation and emissions data from 2006 through 2011, we estimate regional MEFs for CO(2), NO(x), and SO(2), as well as the share of marginal generation from coal-, gas-, and oil-fired generators. Trends in MEFs with respect to system load, time of day, and month are explored. We compare marginal and average emissions factors (AEFs), finding that AEFs may grossly misestimate the avoided emissions resulting from an intervention. We find significant regional differences in the emissions benefits of avoiding one megawatt-hour of electricity: compared to the West, an equivalent energy efficiency measure in the Midwest is expected to avoid roughly 70% more CO(2), 12 times more SO(2), and 3 times more NO(x) emissions.

Regional variations in the health, environmental, and climate benefits of wind and solar generation

When wind or solar energy displace conventional generation, the reduction in emissions varies dramatically across the United States. Although the Southwest has the greatest solar resource, a solar panel in New Jersey displaces significantly more sulfur dioxide, nitrogen oxides, and particulate matter than a panel in Arizona, resulting in 15 times more health and environmental benefits. A wind turbine in West Virginia displaces twice as much carbon dioxide as the same turbine in California. Depending on location, we estimate that the combined health, environmental, and climate benefits from wind or solar range from

Regional Variability and Uncertainty of Electric Vehicle Life Cycle CO2 Emissions across the United States

10/MWh to

Expert assessments of the cost of light water small modular reactors

100/MWh, and the sites with the highest energy output do not yield the greatest social benefits in many cases. We estimate that the social benefits from existing wind farms are roughly 60% higher than the cost of the Production Tax Credit, an important federal subsidy for wind energy. However, that same investment could achieve greater health, environmental, and climate benefits if it were differentiated by region.

Comparison of Life Cycle Greenhouse Gases from Natural Gas Pathways for Medium and Heavy-Duty Vehicles

We characterize regionally specific life cycle CO2 emissions per mile traveled for plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) across the United States under alternative assumptions for regional electricity emission factors, regional boundaries, and charging schemes. We find that estimates based on marginal vs average grid emission factors differ by as much as 50% (using National Electricity Reliability Commission (NERC) regional boundaries). Use of state boundaries versus NERC region boundaries results in estimates that differ by as much as 120% for the same location (using average emission factors). We argue that consumption-based marginal emission factors are conceptually appropriate for evaluating the emissions implications of policies that increase electric vehicle sales or use in a region. We also examine generation-based marginal emission factors to assess robustness. Using these two estimates of NERC region marginal emission factors, we find the following: (1) delayed charging (i.e., starting at midnight) leads to higher emissions in most cases due largely to increased coal in the marginal generation mix at night; (2) the Chevrolet Volt has higher expected life cycle emissions than the Toyota Prius hybrid electric vehicle (the most efficient U.S. gasoline vehicle) across the U.S. in nearly all scenarios; (3) the Nissan Leaf BEV has lower life cycle emissions than the Prius in the western U.S. and in Texas, but the Prius has lower emissions in the northern Midwest regardless of assumed charging scheme and marginal emissions estimation method; (4) in other regions the lowest emitting vehicle depends on charge timing and emission factor estimation assumptions.

Effect of regional grid mix, driving patterns and climate on the comparative carbon footprint of gasoline and plug-in electric vehicles in the United States

Analysts and decision makers frequently want estimates of the cost of technologies that have yet to be developed or deployed. Small modular reactors (SMRs), which could become part of a portfolio of carbon-free energy sources, are one such technology. Existing estimates of likely SMR costs rely on problematic top-down approaches or bottom-up assessments that are proprietary. When done properly, expert elicitations can complement these approaches. We developed detailed technical descriptions of two SMR designs and then conduced elicitation interviews in which we obtained probabilistic judgments from 16 experts who are involved in, or have access to, engineering-economic assessments of SMR projects. Here, we report estimates of the overnight cost and construction duration for five reactor-deployment scenarios that involve a large reactor and two light water SMRs. Consistent with the uncertainty introduced by past cost overruns and construction delays, median estimates of the cost of new large plants vary by more than a factor of 2.5. Expert judgments about likely SMR costs display an even wider range. Median estimates for a 45 megawatts-electric (MWe) SMR range from

Towards demand-side solutions for mitigating climate change

4,000 to

Changing the Renewable Fuel Standard to a Renewable Material Standard: Bioethylene Case Study

16,300/kWe and from

Known unknowns: indirect energy effects of information and communication technology

3,200 to