Climate Policy

A comparison of cost-containment instruments for US carbon reduction policies

A cap-and-trade program, as is used in the European Trading Scheme, is currently the most widely discussed method in the US for reducing greenhouse gases. A basic cap-and-trade program operates by mandating a fixed level of emissions for a given period, issuing permits, and then allowing a market for those permits to develop. The resulting market price for emissions permits, and hence the economic impacts of the chosen policy, can only be estimated in advance with a high degree of uncertainty. Many of the current US cap-and-trade proposals contain provisions for cost-containment instruments which reduce the possible range of emissions prices. This paper analyzes the relative effectiveness of three such cost-containment instruments, including a safety valve, an intensity target, and banking and borrowing. The results presented rely on two computable general equilibrium models developed at the Massachusetts Institute of Technology, and show the predicted performance of these instruments under a simulated range of economic outcomes.

A Contemporary Carbon Balance for the Northeast Region of the United States

Development of regional policies to reduce net emissions of carbon dioxide (CO2) would benefit from the quantification of the major components of the region’s carbon balance fossil fuel CO2 emissions and net fluxes between land ecosystems and the atmosphere. Through spatially detailed inventories of fossil fuel CO2 emissions and a terrestrial biogeochemistry model, we produce the first estimate of regional carbon balance for the Northeast United States between 2001 and 2005. Our analysis reveals that the region was a net carbon source of 259 Tg C/yr over this period. Carbon sequestration by land ecosystems across the region, mainly forests, compensated for about 6% of the region’s fossil fuel emissions. Actions that reduce fossil fuel CO2 emissions are key to improving the region’s carbon balance. Careful management of forested lands will be required to protect their role as a net carbon sink and a provider of important ecosystem services such as water purification, erosion control, wildlife habitat and diversity, and scenic landscapes.

© 2013 American Chemical Society

A framework for modeling uncertainty in regional climate change

In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States (US) associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework are the emissions projections, global climate system parameters, natural variability and model structural uncertainty. The modeling framework revolves around the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model with an Earth System Model of Intermediate Complexity (EMIC) (with a two-dimensional zonal-mean atmosphere). Regional climate change over the US is obtained through a two-pronged approach. First, we use the IGSMCAM framework, which links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Second, we use a pattern-scaling method that extends the IGSM zonal mean based on climate change patterns from various climate models. Results show that the range of annual mean temperature changes are mainly driven by policy choices and the range of climate sensitivity considered. Meanwhile, the four sources of uncertainty contribute more equally to end-of-century precipitation changes, with natural variability dominating until 2050. For the set of scenarios used in this study, the choice of policy is the largest driver of uncertainty, defined as the range of warming and changes in precipitation, in future projections of climate change over the US.

© 2014 Springer Science+Business Media

A Framework for Modeling Uncertainty in Regional Climate Change

In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the US associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework are the emissions projections (using different climate policies), climate system parameters (represented by different values of climate sensitivity and net aerosol forcing), natural variability (by perturbing initial conditions) and structural uncertainty (using different climate models). The modeling framework revolves around the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model with an intermediate complexity earth system model (with a two-dimensional zonal-mean atmosphere). Regional climate change over the US is obtained through a two-pronged approach. First, we use the IGSM-CAM framework which links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Secondly, we use a pattern-scaling method that extends the IGSM zonal mean based on climate change patterns from various climate models. Results show that uncertainty in temperature changes are mainly driven by policy choices and the range of climate sensitivity considered. Meanwhile, the four sources of uncertainty contribute more equally to precipitation changes, with natural variability having a large impact in the first part of the 21st century. Overall, the choice of policy is the largest driver of uncertainty in future projections of climate change over the US.

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