U.S. National Communication: Projections and Effects of Policies and Measures United States Delegation UNFCCC Workshop on National Communications from Annex I Parties, Bonn, Germany 28 February – 2 March, 2001

Overview Process underlying the preparation of the U.S. projections Modeling for projections and the effects of P&Ms Reporting then and now -- how issues are being addressed Conclusions

Preparation Process Federal interagency collaboration on program estimates and future projections –Energy, Environment, Transport, Agriculture, State –Interaction with interagency P&Ms Team –Oversight by White House, Budget Office Choice of methodology that we plan to use Data collection Modeling runs Interagency expert and public stakeholder review

Energy Sector: Use of MARKAL-MACRO Model as an Integrating Framework  A bottom-up approach is adopted to first map programs to P&Ms, then from P&Ms to technology characteristics, demand for energy services, and consumer hurdle rate, and finally to reductions in energy consumption and carbon emissions.  The effects of programs on energy consumption and carbon emissions are estimated using capital stock turn over rate and improvement in energy efficiency attributable to these programs.

Technology Characteristics Energy Sources Used Efficiency Costs (Capital and O&M) Availability Energy Source Data Cost Availability Energy Demands By Sector Other Assumptions Long-Term Discount Rate System Reserve Requirements Other Constraints Max. CO 2 Emissions by Time Period Dynamic LP Optimization with Macro Economic Feedback Technology Mix for Each Time Period That Satisfies Energy Demand Given System Constraints MARKAL-Macro Technology Choice

Other Greenhouse Gases Other GHG estimates use combination of top- down projections of activities and detailed bottom-up analysis of measures –vintaging model for synthetic gases (HFC, PFC, SF 6 ) –discrete spreadsheet models for CH 4, N 2 O –rely on projections of activities for key variables e.g. coal production, area under cultivation, livestock populations

Carbon Sequestration Carbon sequestration projections based on the latest Resource Planning Act Assessment (USDA/Forest Service, 2000) Model consists of area-change, timber market, and inventory projection components Implemented policies and measures are already addressed within the projections Action-specific estimates of benefits will be developed exogenously

Mapping of Programs to P&Ms and Technology-specific Model Parameters Examples of Implemented Programs: Energy Star, Motor Challenge, Renewable Energy Commercialization, etc... Policy and Measures: Economic, Fiscal, Voluntary/negotiated programs, Regulatory, Information, Education, Research, Other Model Parameters: Capital cost, Efficiency, O&M cost, Consumer hurdle rate, Penetration rate, Commercial date, Demand for energy services

What do modelers of projections and effects need from P&M experts?  Policy and Measure Summary Information for 2001 CAR  For “policy effects” analysis, we need data on performance characteristics, capital stock in 1990, 1995, and 2000, market penetration assumptions, and average lifespan.  For “projections” analysis, we will be using  Data on capital costs, fixed O&M costs, variable O&M costs, performance characteristics, commercialization date, average lifespan, and consumer hurdle rate; and/or  Estimates of market penetration, average intensity improvements, and emerging market share of high efficiency technologies as Energy Star products  Guidance for information collection has been sent to all Federal agencies

Reporting then and now: How Issues are being Addressed 2 nd national communication reporting issues –failure to provide projections by sector and by gas –no projection of emissions related to bunker fuels –more sensitivity analysis on “with measures” projections

Reporting then and now Issues being addressed in preparations for 3 rd national communication –Significantly changed economic profile –Quality assurance, transparency –Address uncertainties affecting emission projections (e.g., energy prices, elect. demand growth, etc.)

Significant Changes in Economic Drivers and Impacts

Conclusions Approach used encourages interaction between P&M experts and modelers Modeling effort is reflective of intent of P&Ms Quality assurance is explicitly addressed because modeling focuses on how policies influence specific technologies, and how improved program impacts might affect modeling assumptions –Promotes transparency in modeling process –Consistency in characterization of P&M effects across different policies –Assumptions regarding a P&M or multiple P&M influences on any given technology are logically tracked via model’s accounting framework

For More Information Projections Team: John Conti (USDOE) & Skip Laitner (USEPA), co-leads for the Projections Analysis; and Phil Tseng (USDOE, MARKAL expert) P&Ms Team: Kathleen Hogan (USEPA) & Mary Beth Zimmerman (USDOE), co-leads on P&Ms Analysis Coordination: Reid Harvey, USEPA Tel: