The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).The Emissions Prediction and Policy Analysis (EPPA) model is the part of the MIT Integrated Global Systems Model (IGSM) that represents the human systems. EPPA is a recursive-dynamic multi-regional general equilibrium model of the world economy, which is built on the GTAP dataset and additional data for the greenhouse gas and urban gas emissions. It is designed to develop projections of economic growth and anthropogenic emissions of greenhouse related gases and aerosols. The main purpose of this report is to provide documentation of a new version of EPPA, EPPA version 4. In comparison with EPPA3, it includes greater regional and sectoral detail, a wider range of advanced energy supply technologies, improved capability to represent a variety of different and more realistic climate policies, and enhanced treatment of physical stocks and flows of energy, emissions, and land use to facilitate linkage with the earth system components of the IGSM. Reconsideration of important parameters and assumptions led to some revisions in reference projections of GDP and greenhouse gas emissions. In EPPA4 the global economy grows by 12.5 times from 2000 to 2100 (2.5% per year) compared with an increase of 10.7 times (2.4% per year) in EPPA3. This is one of the important revisions that led to an increase in CO2 emissions to 25.7 GtC in 2100, up from 23 GtC in 2100 projected by EPPA3. There is considerable uncertainty in such projections because of uncertainty in various driving forces. To illustrate this uncertainty we consider scenarios where the global GDP grows 0.5% faster (slower) than the reference rate, and these scenarios result in CO2 emissions in 2100 of 34 (17) GtC. A sample greenhouse gas policy scenario that puts the world economy on a path toward stabilization of atmospheric CO2 at 550 ppmv is also simulated to illustrate the response of EPPA4 to a policy constraint.This research was supported by the U.S Department of Energy, U.S. Environmental Protection Agency, U.S. National Science Foundation, U.S. National Aeronautics and Space Administration, U.S. National Oceanographic and Atmospheric Administration; and the Industry and Foundation Sponsors of the MIT Joint Program on the Science and Policy of Global Change: Alstom Power (France), American Electric Power (USA), BP p.l.c. (UK/USA), Chevron Corporation (USA), CONCAWE (Belgium), DaimlerChrysler AG (Germany), Duke Energy (USA), J-Power (Japan), Electric Power Research Institute (USA), Electricité de France, ExxonMobil Corporation (USA), Ford Motor Company (USA), General Motors (USA), Murphy Oil Corporation (USA), Oglethorpe Power Corporation (USA), RWE Power (Germany), Shell Petroleum (Netherlands/UK), Southern Company (USA), Statoil ASA (Norway), Tennessee Valley Authority (USA), Tokyo Electric Power Company (Japan), Total (France), G. Unger Vetlesen Foundation (USA)

Global Health and Economic Impacts of Future Ozone Pollution

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).We assess the human health and economic impacts of projected 2000-2050 changes in ozone pollution using the MIT Emissions Prediction and Policy Analysis-Health Effects (EPPA-HE) model, in combination with results from the GEOS-Chem global tropospheric chemistry model that simulated climate and chemistry effects of IPCC SRES emissions. We use EPPA to assess the human health damages (including acute mortality and morbidity outcomes) caused by ozone pollution and quantify their economic impacts in sixteen world regions. We compare the costs of ozone pollution under scenarios with 2000 and 2050 ozone precursor and greenhouse gas emissions (SRES A1B scenario). We estimate that health costs due to global ozone pollution above pre-industrial levels by 2050 will be $580 billion (year 2000$) and that acute mortalities will exceed 2 million. We find that previous methodologies underestimate costs of air pollution by more than a third because they do not take into account the long-term, compounding effects of health costs. The economic effects of emissions changes far exceed the influence of climate alone.United States Department of Energy, Office of Science (BER) grants DE-FG02-94ER61937 and DE-FG02-93ER61677, the United States Environmental Protection Agency grant EPA-XA-83344601-0, and the industrial and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change

Energy-economy interactions in small developing countries.

This report is addressed at modelling energy-economy interactions in small developing countries, those with populations less than 20 million or so and where neither the industrial or energy sectors are dominant. The overall objectives of the research were to learn more about how energy-economy interactions can be usefully modelled for policy purposes, to compare the pros and cons of alternative methods which have been used previously, and to test the feasibility of utilizing simple general equilibrium models by constructing an illustrative model for Sri Lanka.Various approaches to energy policy analysis--project evaluation, technology assessment, energy sector assessment, macro simulation models, economy-wide optimization models, and computable general equilibrium models-- are surveyed and critically reviewed. A major deficiency of all but the latter two is their failure to account for the important two-way interactions between energy and the rest of the economy which are common in developing countries.The latter models are general in scope and can include the important energy-economy relationships. Since the computable general equilibrium models are somewhat easier to formulate and solve, they seen most appropriate for the type of countries under consideration. These types of models can analyze a large number of interrelated issues such as: the impact of energy costs and prices on aggregate growth and its sectoral composition; the relationship between energy imports, investment rates, and the balance of payments; the scope for substitution between energy and other factors of substitution; and the effect of energy prices on income distribution and employment.The Sri Lanka model is meant to illustrate how a simple computable general equilibrium model focussing on these issues can be built rather quickly in a situation with substantial data limitations. The model was constructed with data from existing sources, supplemented by some minimal econometric estimation, and was designed to run on a personal computer.The model includes eleven sectors: (1) paddy and other annual agricultural crops; (2) tree crops; (3) industry; (4) transportation: (5) housing; (6) services; (7) refined petroleum products; (8) electricity; (9) non-competing imports; (10) crude oil: and (11) traditional fuels. Prices determine factor allocations, production, and final demands. Trade flows are adjusted to ensure that total supply equals total usage. For the tradable goods, prices are exogenous. Electricity prices also are set by government policy. The model calculates prices for transportation and housing which insure supply/demand equilibrium for these non-traded sectors. The model is "closed" by specifying a rule for relating aggregate investment and the balance of payments deficit to national income (GDP). In some cases, the trade deficit is fixed in terms of GDP, and in others aggregate investment is fixed as a share of national income.Starting from a base year of 1983, the model simulates developments through 1989. Several alternative solutions are discussed to demonstrate how parametric changes can show the sensitivity of key variables to changes in prices, economic policy, and the external environment.Supported by the Office of Energy of the U.S. Agency for International Development