Near-Term Pathways for Achieving Forest and Agricultural Greenhouse Gas Mitigation in the U.S.

U.S. forests and agriculture present unique opportunities to mitigate greenhouse gas (GHG) emissions. U.S. forests currently remove a large amount of carbon dioxide from the atmosphere each year and store it as a terrestrial carbon sink, a trend that is projected to continue, although at a decreasing rate over time. Agriculture is and will continue to be a net source of GHGs. To encourage additional mitigation, analyses suggest addressing forest loss, forest aging, wildfire, and encouraging greater forest growth. In agriculture, analyses suggest addressing animal operation methane emissions and nitrous oxide from fertilizer use. Absent new targeted policies to encourage mitigation practices such as these, existing programs may need to be better leveraged for GHG mitigation, even if that is not their explicit objective. Leveraging existing programs requires coordinated outreach efforts to ensure that practices are not cross-purposed. Development of standards and verification practices is also necessary to ensure desirable outcomes. Finally, greater mitigation may be possible by maximizing the effectiveness of voluntary efforts from private and non-governmental organizations, and not necessarily the implementation of new policies. This conclusion represents a departure from traditional commentary on the subject, but arguably represents a more realistic path forward to achieving climate mitigation objectives in the near-term

Mitig Adapt Strateg Glob Change DOI 10.1007/s11027-011-9306-x ORIGINAL ARTICLE Managing dependencies in forest offset projects: toward a more complete evaluation of reversal risk

Abstract Although forest carbon offsets can play an important role in the implementation of comprehensive climate policy, they also face an inherent risk of reversal. If such risks are positively correlated across projects, it can affect the integrity of larger project portfolios and potentially the entire offsets program. Here, we discuss three types of risks that could affect forest offsets—fat tails, micro-correlation, and tail dependence—and provide examples of how they could present themselves in a forest offset context. Given these potential dependencies, we suggest several new risk management approaches that take into account dependencies in reversal risk across projects and which could help guard the climate integrity of an offsets program. We also argue that data collection be included as an integral part of any offsets program so that disturbance-related dependencies may be identified and managed as early and to the greatest extent possible. Keywords Carbon offsets. Climate policy. Forestry. Natural disturbance. Risk 1 Forest offset risk and management Recent years have witnessed rapid growth in voluntary carbon markets and increased discussion of economy-wide limits on greenhouse gas (GHG) emissions. Emerging as a central component of both are carbon offsets, defined broadly as reductions in GHG emissions or increases in carbon storage produced by one entity to compensate for emissions from another. Because the ultimate objective of climate policy is to reduce globa

Managing dependencies in forest offset projects: toward a more complete evaluation of reversal risk

Carbon offsets, Climate policy, Forestry, Natural disturbance, Risk,

Leveraging open-source tools for collaborative macro-energy system modeling efforts

The authors are founding team members of a new effort to develop an Open Energy Outlook for the United States. The effort aims to apply best practices of policy-focused energy system modeling, ensure transparency, build a networked community, and work toward a common purpose: examining possible US energy system futures to inform energy and climate policy efforts. Individual author biographies can be found on the project website: https://openenergyoutlook.org/. DeCarolis et al. articulate the benefits of forming collaborative teams with a wide array of disciplinary and domain expertise to conduct analysis with macro-energy system models. Open-source models, tools, and datasets underpin such efforts by enabling transparency, accessibility, and replicability among team members and with the broader modeling community