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An Integrated Assessment Framework for Uncertainty Studies in Global and Regional Climate Change: The IGSM-CAM

This paper describes an integrated assessment framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the IGSM-CAM incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from uncertainties intrinsic to the economic model, from parametric uncertainty to uncertainty in future climate policies. Another major feature is the flexibility to vary key climate parameters controlling the climate response: climate sensitivity, net aerosol forcing and ocean heat uptake rate. Thus, the IGSM-CAM is a computationally efficient framework to explore the uncertainty in future global and regional climate change due to uncertainty in the climate response and projected emissions. This study further presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent by 2100) and three sets of climate parameters. The chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change. As such, this study presents new estimates of the 90% probability interval of regional climate change for different emissions scenarios. These results underscore the large uncertainty in regional climate change resulting from uncertainty in climate parameters and emissions, and the statistical uncertainty due to natural variability.

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap – but display similar size – over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

© 2013 the authors

An Integrated Assessment of Air Pollutant Abatement Opportunities in a Computable General Equilibrium Framework

Air pollution and anthropogenic greenhouse gas emission reduction policies are desirable to reduce smog, tropospheric concentrations of ozone precursors, acid rain, and other adverse effects on human health, the environment, and the economy. While reduction of both air pollution and greenhouse gas emissions is often attained through economic instruments such as taxes, caps, and other regulation, emission controls in both developed and developing countries often achieves reduction through policies that target air pollution and greenhouse gases separately. However, because the emissions of both air pollution and greenhouse gases are often intrinsically linked to the same sources, any attempt to design policies to optimally achieve desired reduction goals must consider the complex socioeconomic interactions that produce both kinds of emissions as they collectively react to regulatory constraints.

Integrated assessment models have often been used as tools to inform policy design by representing the interactions between technology, economics, policy, and the environment within a self-contained framework. Many contemporary integrated assessment models consider emissions of greenhouse gases while others also consider air pollution emissions. While greenhouse gas reduction opportunities are often represented endogenously in the models through the availability of backstop technologies such as carbon capture and storage or by shifts away from carbon intensive to less carbon intensive production, representation of air pollutant reduction has largely been represented within integrated assessment models exogenously based on empirically observed trends. By treating air pollution reduction opportunities exogenously, such models are unable to represent many key considerations important to policy design including the true economic impact of air pollutant reduction policy, the impact such policies may have on the market penetration of backstop energy production technologies, and the ancillary co-benefits of air pollution policy on greenhouse gas emission reduction.

To overcome current limitations imposed by exogenous representation of air pollution abatement, I develop a new method for representing air pollutant abatement opportunities endogenously within an integrated assessment model designed using a computable general equilibrium (CGE) framework. CGE models are often used to simulate macroeconomic activity based on microeconomic theory and are well suited for emission policy analysis because of their ability to represent the interactions between multiple economic regions and sectors, to connect emission sources to economic activity, and to accommodate a large 3 degree of technological detail not captured by other macroeconomic models. Using this new method, I demonstrate how the parameters needed to represent the abatement opportunities are derived from engineering data on specific abatement technologies available within each economic sector and for distinct fuel types as air pollution is largely generated through the combustion of hydrocarbon fuels. With both the methodology and parameterization established, I represent sulfur dioxide and nitrous oxide abatement opportunities in the MIT Emissions Prediction and Policy Analysis (EPPA) model and compare model results with previous representations of air quality pollutant reduction methodologies based on exogenous trends. An example of how the model predicts co-benefits for CO2 reduction and policy costs in China is then presented. Overall, the new model demonstrates the ability to fully capture important effects relevant to policy design not captured in integrated assessment models where air pollution abatement is exogenously represented.

An Integrated Assessment of China's Wind Energy Potential

Computable general equilibrium (CGE) models seeking to evaluate the impacts of electricity policy face difficulties incorporating detail on the variable nature of renewable energy resources. To improve the accuracy of modeling renewable energy and climate policies, detailed scientific and engineering data are used to inform the parameterization of wind electricity in a new regional CGE model of China. Wind power density (WPD) in China is constructed using boundary layer flux data from the Modern Era Retrospective-analysis for Research and Applications (MERRA) dataset with a 0.5° latitude by 0.67° longitude spatial resolution. Wind resource data are used to generate production cost functions for wind at the provincial level for both onshore and offshore, incorporating technological parameters and geographical constraints. By using these updated wind production cost data to parameterize the wind electricity option in a CGE model, an illustrative policy analysis of the current feed-in tariff (FIT) for onshore wind electricity is performed. Assuming a generous penetration rate, no grid integration cost and no interprovincial interconnection, we find that the economic potential of wind exceeds China’s 2020 wind target by a large margin. Our analysis shows how wind electricity resource can be differentiated based on location and quality in a CGE model and then applied to analyze climate and energy policies.

An interim evaluation of sulfur dioxide emissions trading

This paper summarizes recent empirical research on compliance costs and strategies and on permit market performance under the U.S. acid rain program, the first large-scale, long-term program to use tradeable emissions permits to control pollution. An efficient market for emissions permits developed in a few years, and this program more than achieved its early goals on time, and it cost less than had been projected. Because of expectation errors, however, investment was excessive, and permit prices substantially understate abatement costs. The tradeable permits approach has worked well, but it is not a miracle cure for environmental problems. Coauthors are Paul L. Joskow, A. Denny Ellerman, Juan Pablo Montero, and Elizabeth M. Bailey. Copyright 1998 by American Economic Association.

Copyright American Economic Association 

An Issue of Permanence: Assessing the Effectiveness of Temporary Carbon Storage

In this paper, we present a method to quantify the effectiveness of carbon mitigation options taking into account the "permanence" of the emissions reduction. While the issue of permanence is most commonly associated with a "leaky" carbon sequestration reservoir, we argue that this is an issue that applies to just about all carbon mitigation options. The appropriate formulation of this problem is to ask 'what is the value of temporary storage?' Valuing temporary storage can be represented as a familiar economic problem, with explicitly stated assumptions about carbon prices and the discount rate. To illustrate the methodology, we calculate the sequestration effectiveness for injecting CO2 at various depths in the ocean. Analysis is performed for three limiting carbon price assumptions: constant carbon prices (assumes constant marginal damages), carbon prices rise at the discount rate (assumes efficient allocation of a cumulative emissions cap without a backstop technology), and carbon prices first rise at the discount rate but become constant after a given time (assumes introduction of a backstop technology). Our results show that the value of relatively deep ocean carbon sequestration can be nearly equivalent to permanent sequestration if marginal damages (i.e., carbon prices) remain constant or if there is a backstop technology that caps the abatement cost in the not too distant future. On the other hand, if climate damages are such as to require a fixed cumulative emissions limit and there is no backstop, then a storage option with even very slow leakage has limited value relative to a permanent storage option.

An Ongoing Observational Study of Greenhouse Gas Emissions in the Greater Boston Area

Observations of greenhouse gas (GHG) concentrations and their relationship to atmospheric conditions in major cities are an important component of current efforts to understand the effects of urbanization on anthropogenic sources of GHGs. One-minute CO2 mixing ratio measurements in the city of Cambridge, MA have been determined from air samples collected from an intake mounted at on the roof of MIT’s Green building (99.0 m) since July 3, 2012. Atmospheric CO2 concentrations are governed by a diurnal cycle with July hourly average mixing ratios ranging from a minimum of 390.22 ± 9.22 ppm at 4:00PM to a maximum of 412.89 ± 16.78 ppm at 6:00AM. Occasional plume events, with mixing ratios exceeding 500 ppm, are seen in preliminary records especially in the morning hours (6:00AM-12:00PM). Small CO2 detectors also have been deployed at other locations on MIT’s campus to determine CO2 mixing ratios to within 30 ppm at different elevations. These detectors provide a cost effective way to determine the spatial extent of plume events. To assess overall levels of GHGs in the Boston area, corresponding CO and N2O concentrations, obtained with a continuous wave, quantum cascade tunable infrared laser absorption spectrometer are used to determine source signatures during plume events. The potential exists to establish a baseline diurnal signal in the CO and N2O records similar to that of CO2 in the ongoing measurements. Further analyses will look to determine the existence and extent of an urban GHG dome over the city of Boston. Some unique source signatures are identified on the basis of their characteristic N2O-CO-CO2 ratios; this information will be used to evaluate the location of significant anthropogenic sources of GHGs in conjunction with wind direction and traffic flow data. Preliminary N2O/CO2 ratios, averaged over six hour periods, fall between (7.31 ± 0.31)*10-4 in the morning (6:00AM-12:00PM) and (8.34 ± 0.13)*10-4 in the evening (6:00PM – 12:00AM) are slightly higher than Jimenez et al.’s mixed traffic ratio ((12.8 ±0.3)*10-5 ) and Farmulari et al.’s urban emission ratio ((2.5)*10-4) from Edinburgh, Scotland. In further analysis, CO/CO2 and N2O/CO ratios will also be considered. While diurnal cycles in GHG levels are largely attributed to changes in temperature and planetary boundary layer (PBL) height, the geographical variation and significance of high frequency plume events will be evaluated in the context of the urban CO2 budget.

An Open Letter to Congress from U.S. Scientists on Climate Change and Recently Stolen Emails

Leading U.S. scientists with substantial expertise on climate change and its impacts on natural ecosystems, our built environment and human well-being, assure policy makers and the public of the integrity of the underlying scientific research and the need for urgent action to reduce heat-trapping emissions. In recent weeks, opponents of taking action on climate change have misrepresented both the content and the significance of stolen emails to obscure public understanding of climate science and the scientific process.

In this open letter to Congress, the scientists seek to set the record straight: The body of evidence that human activity is the dominant cause of global warming is overwhelming. The content of the stolen emails has no impact whatsoever on our overall understanding that human activity is driving dangerous levels of global warming. The scientific process depends on open access to methodology, data, and a rigorous peer-review process. The robust exchange of ideas in the peer-reviewed literature regarding climate science is evidence of the high degree of integrity in this process.
 

 

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