The resources available for managing wildfire risk are insufficient and ultimately finite, while the risk of catastrophic fires is enormous and growing. Prioritization of responses is thus critical, but the basis for comparing the costs and societal benefits of alternative investments in wildfire mitigation is inadequate. Here, we assess and compare the costs of landscape-scale fuel treatment in California to the benefits of avoided destruction of property and smoke-related health impacts, and identify areas where the net benefits are greatest statewide. We find that re-prioritizing treatment areas could increase net benefits by a factor of more than 6.5 relative to historical treatments, with average net benefits in the top decile of areas (i.e., 28,000 km2) of >$220k per km2 (as compared to an estimated $90k per km2 of past treatments). By integrating physical, epidemiological, and economic methods, our results reveal large opportunities for improving the cost-effectiveness of fuel treatments, and demonstrate a general framework that can be applied by land managers in all wildfire-prone areas.

In late December 1973, the United States enacted what some would come to call “the pitbull of environmental laws.” In the 50 years since, the formidable regulatory teeth of the Endangered Species Act (ESA) have been credited with considerable successes, obliging agencies to draw upon the best available science to protect species and habitats. Yet human pressures continue to push the planet toward extinctions on a massive scale. With that prospect looming, and with scientific understanding ever changing, Science invited experts to discuss how the ESA has evolved and what its future might hold. —Brad Wible

Climate-induced extreme weather conditions make electricity infrastructure more vulnerable. They increase the risk of power-line-ignited wildfires which can, in turn, jeopardize electric power delivery. Here, leveraging machine learning, we show that lower-income communities in California not only have lower fractions of power distribution lines undergrounded, but overhead lines and poles in their neighbourhoods are also more vulnerable to wildfires. Should they bear the cost of undergrounding fire-prone lines themselves, they would have to pay a disproportionately higher cost per household. We propose a cost allocation scheme with an income threshold below which the cost is borne by utility-wide ratepayers and above which the cost is borne locally. This scheme can not only minimize the average of undergrounding costs per household as a share of income, but also homogenize such cost–income ratios across communities. Our research demonstrates the opportunity to appropriately integrate existing policies to make electricity infrastructure affordable, equitable and reliable amidst climate change. Extreme weather conditions threaten electricity infrastructure. A new study finds that lower-income communities in California have fewer power distribution lines undergrounded and more vulnerable overhead lines and poles in their neighbourhoods.

The increasing frequency of severe wildfires demands a shift in landscape management to mitigate their consequences. The role of managed, low-intensity fire as a driver of beneficial fuel treatment in fire-adapted ecosystems has drawn interest in both scientific and policy venues. Using a synthetic control approach to analyze 20 years of satellite-based fire activity data across 124,186 square kilometers of forests in California, we provide evidence that low-intensity fires substantially reduce the risk of future high-intensity fires. In conifer forests, the risk of high-intensity fire is reduced by 64.0% [95% confidence interval (CI): 41.2 to 77.9%] in areas recently burned at low intensity relative to comparable unburned areas, and protective effects last for at least 6 years (lower bound of one-sided 95% CI: 6 years). These findings support a policy transition from fire suppression to restoration, through increased use of prescribed fire, cultural burning, and managed wildfire, of a presuppression and precolonial fire regime in California.

Carbon offsets allow greenhouse gas emitters to comply with an emissions cap by paying others outside of the capped sectors to reduce emissions. The first major carbon offset programme, the United Nations' Clean Development Mechanism (CDM), has been criticized for generating a large number of credits from projects that do not actually reduce emissions. Following the controversial CDM experience, California pioneered a second-generation compliance offset programme that shifts the focus of quality control from assessments of individual projects to the development of offset protocols, which define project type-specific eligibility criteria and methods for estimating emissions reductions. We assess the ability of California's 'standardized approach' to mitigate the risk of over-crediting greenhouse gas reductions by reviewing the development of two California offset protocols - Mine Methane Capture and Rice Cultivation. We examine the regulator's treatment of three sources of over-crediting under the CDM: non-additional projects, inflated counterfactual baseline scenarios, and perverse incentives that inadvertently increase emissions. We find that the standardized approach offers the ability to reduce, but not eliminate, the risk of over-crediting. This requires careful protocol-scale analysis, conservative methods for estimating reductions, ongoing monitoring of programme outcomes, and restricting participation to project types with manageable levels of uncertainty in emission reductions. However, several of these elements are missing from California's regime, and even best practices result in significant uncertainty in true emission reductions. Relying on carbon offsets to lower compliance costs risks lessening total emission reductions and increases uncertainty in whether an emissions target has been met. Key policy insights Substantial and ongoing oversight by offset programme administrators is needed to contain uncertainty and avoid over-crediting. California's Mine Methane Capture Protocol may have influenced federal decisions not to regulate methane emissions from coal mines on federally-owned lands. Government priorities and methodological choices drive outcomes in carbon pricing policies with large offset programmes, contrary to the common perception that these policies delegate decision-making to private actors. Offsets are better understood as a way for regulated emitters to invest in an incentive programme that achieves difficult-to-estimate emission reductions, than as accurately quantified tons of reductions.

The advent of distributed energy technologies, most notably, distributed solar energy, poses a competitive threat to the electric utility industry. Here I provide a comprehensive assessment of the U.S. electric utility industry's regulatory response to this threat over the past three years. Electric utilities across the United States are asking their Public Utility Commissions for changes in rate structures that, depending on their details, may either reduce cross-subsidies to distributed energy resources or may be erecting much higher barriers to entry for innovative energy technologies and business models. Usually, a utility's actions are exempt from antitrust scrutiny under the State Action Immunity and Filed Rate doctrines. I argue that in the case of the utility response to distributed energy, this may not be the case. Because the risk exists, both electric utilities and their overseeing commissions need to make much greater efforts to evaluate the competitive impacts of changes in rates - a consideration that is largely absent from the proceedings to date. By doing so, they will both ensure that society’s interest in a cleaner, more innovative, more productive energy sector is protected and at the same time minimize their own risks of liability under the antitrust statutes.

We present a new method that enables users of the federal government's flagship energy policy model (NEMS) to dynamically estimate the direct energy expenditure impacts of climate policy across U.S. household incomes and census regions. Our approach combines NEMS output with detailed household expenditure data from the Consumer Expenditure Survey, improving on static methods that assess policy impacts by assuming household energy demand remains unchanged under emissions pricing scenarios. To illustrate our method, we evaluate a recent carbon fee-and-dividend proposal introduced in the U.S. Senate, the Climate Protection Act of 2013 (S. 332). Our analysis indicates this bill, if enacted, would have cut CO2 emissions from energy by 17% below 2005 levels by 2020 at a gross cost of less than 0.5% of GDP, while offering rebates sufficient to offset increased direct energy expenditures for typical households making less than $120,000 per year and average households in all regions of the United States.

This Article examines the consequences of a previously unrecognized difference between pollutant cap-and-trade schemes and pollution taxes. Implementation of cap-and-trade relies on a forecast of future emissions, while implementation of a pollution tax does not. Realistic policy designs using either regulatory instrument almost always involve a phase-in over time to avoid economic disruption. Cap-and-trade accomplishes this phase-in via a limit on emissions that falls gradually below the forecast of future pollutant emissions. Emissions taxation accomplishes the same via a gradually increasing levy on pollution. Because of the administrative complexity of establishing an emissions trading market, cap-and-trade programs typically require between three and five years lead time before imposing obligations on emitters. In this Article, I present new evidence showing that forecast error over this timeframe for United States energy- related carbon dioxide emissions from the Department of Energy’s energy model—the model used for policy design by Congress and EPA—is biased and imprecise to such a degree as to make its use impractical. The forecasted emissions are insufficiently accurate to allow for creation of a reliable or predictable market signal to incentivize emission reductions. By contrast, carbon taxes, because they do not depend upon a baseline emissions forecast, create a relatively clear level of policy stringency. This difference matters because policies that end up weaker than intended face low odds for strengthening, while those that end up stronger than intended are likely to be weakened. The political asymmetry combined with actual model forecast errors leads to bias in favor of suboptimal, weak, policies for cap-and-trade. This is a serious concern if, as is usually the case, a cap is set based on political bargaining rather than on an optimal balancing of abatement costs and avoided climate damage. By contrast, the same model bias would lead to more environmentally effective than forecast carbon taxes but without the political consequences created by price volatility, were such programs to be implemented in the United States. Thus, while theory tells us that cap-and-trade and carbon taxes can be equivalent, imperfect information leads to suboptimal environmental performance of emissions trading, relative to carbon taxation policies. Policymakers should weigh these practical, information-related concerns when considering approaches to controlling emissions of greenhouse gases.

Key elements of EPA's Clean Power Plan rely on forecasted electricity sales from the National Energy Modeling System (NEMS), but NEMS has consistently over-projected electricity sales. An analysis of the model's bias as applied by EPA raises concerns about the stringency of the proposed emissions targets.

Complex energy modeling is increasingly central to the development of electricity sector regulations, and perhaps increasingly necessary. But environmental agencies need to remain vigilant to avoid vulnerabilities created when models designed for broad energy system projections are repurposed for the design of detailed pollution control policies. All models are false, some are useful, and by implication, some are misused. Looking beyond the current proposal, it is critical that legislators and environmental regulators recognize the limitations of energy models w they employ them to design fut pollution control programs. H ere, we express concern about the way the Environmental Protection Age uses the National Energy Modeling System (NEMS) in design of the Clean Power Pla We also suggest strategies for fostering policy integrity throu a period of deep uncertainty in U.S. electricity system. Now, more than at any time in the p century, it appears possible th from both technological and Michael Wara is an Associate Professor of Law and the Justin M. Roach, Jr. Faculty Scholar at Stanford Law School. His research and teaching focuses on environmental and energy law with an emphasis on climate and electricity policy. He holds a J.D. from Stanford Law School and a Ph.D. in Ocean Sciences from the University of California, Santa Cruz.

The U.S. Environmental Protection Agency (EPA) is exercising its authority under section 111(d) of the Clean Air Act to limit U.S. greenhouse gas (GHG) emissions from existing stationary sources, beginning with carbon dioxide (CO2) emissions from fossil-fuel fired electric generating units (EGUs, power plants, or covered sources). This comment examines the extent to which EPA’s proposed rule for existing power plants (the EPA proposal) and its existing regulations would allow states to comply with their obligations under 111(d) by adopting and enforcing carbon excise taxes. We find that although states can adopt carbon taxes to comply with 111(d) rules, EPA has inadvertently restricted how states can design their policies, precluding some of the most straightforward approaches. Accordingly, we recommend amendments that would give full flexibility to states to design policies as they see fit, provided those policies are enforceable and will achieve the applicable emissions guidelines.

The world needs a new approach to achieving international progress on climate change. Despite prodigious diplomatic efforts over two decades aimed at limiting emissions of climate change pollutants, relatively little in the way of effective global governance has been achieved. In Part 1, I argue that this is due to a narrow legal, economic, and political focus on the hardest part of the climate change problem – energy related carbon dioxide emissions. Part 2 explains key scientific developments over the past two decades and how these have reshaped the scientific view of human impacts on climate. Studies aimed at resolving the remaining uncertainties in climate projections have resulted in a dramatically improved understanding of the importance of short-lived climate pollutants in causing current and medium-term climate change. In Part 3, I argue that such a shift in focus to short-lived climate pollutants could produce more effective outcomes. In Part 4, I provide an account of how short-lived climate pollutants might form a path toward more comprehensive international greenhouse gas limits in the future. In the long run, a multilateral agreement limiting energy related carbon emissions is essential to avoiding the worst impacts of climate change. But simply repeating the failed strategies of the last twenty years is unlikely to accomplish that end. This article aims to provide a plausible path forward to deep cooperation that is consistent with current scientific knowledge, technical ability, and international law and relations theory.