Learning from global emissions scenarios

Scenarios of global greenhouse gas emissions have played a key role in climate change analysis for over twenty years. Currently, several research communities are organizing to undertake a new round of scenario development in the lead-up to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). To help inform this process, we assess a number of past efforts to develop and learn from sets of global greenhouse gas emissions scenarios. We conclude that while emissions scenario exercises have likely had substantial benefits for participating modeling teams and produced insights from individual models, learning from the exercises taken as a whole has been more limited. Model comparison exercises have typically focused on the production of large numbers of scenarios while investing little in assessing the results or the production process, perhaps on the assumption that later assessment efforts could play this role. However, much of this assessment potential remains untapped. Efforts such as scenario-related chapters of IPCC reports have been most informative when they have gone to extra lengths to carry out more specific comparison exercises, but in general these assessments do not have the remit or resources to carry out the kind of detailed analysis of scenario results necessary for drawing the most useful conclusions. We recommend that scenario comparison exercises build-in time and resources for assessing scenario results in more detail at the time when they are produced, that these exercises focus on more specific questions to improve the prospects for learning, and that additional scenario assessments are carried out separately from production exercises. We also discuss the obstacles to better assessment that might exist, and how they might be overcome. Finally, we recommend that future work include much greater emphasis on understanding how scenarios are actually used, as a guide to improving scenario production

Projecting U.S. Household Changes with a New Household Model

Anticipating changes in number, size, and composition of households is an important element of many issues of social concern. To facilitate continued progress in these areas, an efficient household projection model with moderate data requirements, manageable complexity, explicit accounting for the effects of demographic events, and output that includes the most important household characteristics is needed. None of the existing modelling approaches meets all these needs. This study proposes a new type of headship rate model that projects changes in age- and size-specific headship rates by accounting for the effect of changes in population age structure, changes in the age structure of household heads, and the effect of demographic events. We compare model results to historical data on the last 100 years of experience in the United United States, and to results from a projection over the next 100 years using the dynamic household model ProFamy. Results show that the new model is a substantial improvement over the commonly used constant headship rate approach. A simplified version of the model that does not require projecting the effect of changes in demographic events on headship rates appears to produce reasonably accurate projections of the composition of the population by household size and age of the household head

Household Projections for Rural and Urban Areas of Major Regions of the World

Demographic dynamics are important drivers of environmental change, including effects on climate through energy and land use that lead to emissions of greenhouse gases. These dynamics include changes to population size, age structure, and urbanization, as well as changes in household living arrangements. Population and household projections are therefore essential for investigating potential future demographic effects, but no long-term, global projections exist that simultaneously describe consistent outcomes for population, urbanization, and households. We therefore develop a new set of population/household projections for nine world regions. The projections are based partly on existing population and urbanization projections, partly on new multi-state projections for China and India, and on a new household projection using age-, size-, and urban/rural-specific headship rates. We discuss principle results that foresee future aging, urbanization, and trends toward smaller household sizes

Linking Mid-century Concentration Targets to Long-Term Climate Change Outcomes

We present a framework that could inform the choice of an interim (mid-21st century) target in the making of climate mitigation policy. The idea of interim targets for greenhouse gas concentration has been proposed previously as a way to bridge short- and long-term climate targets, address concerns about the rate of temperature change, and provide guidance in planning for energy infrastructure while scientific understanding improves and long-term climate goals are negotiated. Our analysis relates a wide range of mid-century equivalent CO2 (eCO2) concentrations to rates of temperature increase as well as total long-term temperature increases, accounts for uncertainties in the carbon cycle and the climate response (including climate sensitivity, ocean diffusivity, and aerosol forcing), and provides a rough measure of the economic feasibility of different emissions pathways. Our results show, for example, that for a roughly 50% likelihood of limiting long-term warming to 20C above the pre-industrial level, and with the constraint that global emissions should not have to be reduced by more than 2.5%/year, the mid-century concentration needs to remain below about 470 ppm eCO2 (including only the Kyoto gases and defined relative to a year 2000 baseline). For a roughly 83% likelihood of achieving the same temperature goal, the mid-century target needs to be about 440 ppm. These targets require that emissions between 2010 and 2050 average to approximately the current level and the 1990 level, respectively. Our framework illustrates how delay in emissions reductions in the near term forecloses options in the long term. Finally, we demonstrate how near-term reductions of CO2 from a particular source, deforestation, can significantly facilitate the achievement of long-term temperature goals

Production Data for the Population-Environment-Technology (PET) Model

This report describes the production data serving as an input to the Population-Environment-Technology (PET) model (Dalton and Goulder, 2001; Dalton et al., 2008). The PET model is a multi-sector, multi-region computable general equilibrium model of the global economy. We describe the procedures used to develop regional production data for the model. GTAP (Global Trade Analysis Project) represents the major production data source. The document explains the structure of the data and the modifications we make to it, including modifications to the treatment of trade, physical energy quantities, and household consumption