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CEF JK short

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Published on March 21, 2008

Author: Cajetano

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Costs of reducing carbon emissions in the U.S.: Some recent results:  Costs of reducing carbon emissions in the U.S.: Some recent results Jonathan Koomey, Ph.D. Lawrence Berkeley National Laboratory JGKoomey@lbl.gov, 510/486-5974, http://enduse.lbl.gov/ To download the report discussed here, go to http://www.ornl.gov/ORNL/Energy_Eff/CEF.htm To download the talk, http://enduse.lbl.gov/shareddata/CEF.JK.short.ppt Presented in San Francisco, CA at AAAS February 20, 2001 Environmental Energy Technologies SUMMARY OF TALK:  SUMMARY OF TALK Context on assessing GHG mitigation costs Background on Clean Energy Futures (CEF) study & methodology Energy and carbon results Economic results Conclusions ECONOMICS OF CLIMATE CHANGE MITIGATION HOTLY DEBATED:  ECONOMICS OF CLIMATE CHANGE MITIGATION HOTLY DEBATED Many respected institutions on both sides of the heated discussion, BUT There is some common ground: Some successful policies both save money and reduce pollution The real debate is over how many of such policies actually exist and how successful they will be if scaled up. THE ECONOMIST’S STATEMENT:  THE ECONOMIST’S STATEMENT On February 13, 1997, two thousand economists, including 6 Nobel Laureates, declared: Economic studies have found that there are many potential policies to reduce greenhouse-gas emissions for which the total benefits outweigh the total costs. For the United States in particular, sound economic analysis shows that there are policy options that would slow climate change without harming American living standards, and these measures may in fact improve U.S. productivity in the longer run. AT THE CORE OF THE DEBATE:  AT THE CORE OF THE DEBATE Are there $20 bills on the sidewalk? Most economists say no, on theoretical grounds, because someone would have picked them up already Some economists and most engineers, physicists, and business practitioners say yes, on empirical grounds (they see the opportunities with their own eyes). Ultimately an empirical question. BACKGROUND:  BACKGROUND The previous “5-lab Study”: Scenarios of U.S. Carbon Reductions (1997) was influential, but was criticized because it did not explicitly identify technologies, programs, and policies; treat fuel price interactions; or incorporate macroeconomic impacts of an emissions trading system. CEF was undertaken to address these key criticisms. BACKGROUND (Continued):  BACKGROUND (Continued) The Clean Energy Futures (CEF) Study Initiated by the U.S. Department of Energy in Nov. 1998. Goal: to identify and analyze policies that promote efficient and clean energy technologies to reduce carbon emissions and improve oil security and air quality Published in Nov. 2000 Slide8:  LABORATORY TEAM LEADS Study Design/Integration Marilyn Brown, ORNL Mark Levine, LBNL Walter Short, NREL Buildings Jon Koomey, LBNL Andrew Nicholls, PNNL Transportation David Greene, ORNL Steve Plotkin, ANL Electricity Stan Hadley, ORNL Walter Short, NREL ANL = Argonne National Laboratory (ANL) LBNL = Lawrence Berkeley National Laboratory (LBNL) NREL = National Renewable Energy Laboratory (NREL) ORNL = Oak Ridge National Laboratory (ORNL) PNNL = Pacific Northwest National Laboratory (PNNL) NEMS Modeling/ Economic Integration Jon Koomey, LBNL Marilyn Brown, ORNL Macro-Economic Modeling Alan Sanstad, LBNL Gale Boyd, ANL Industry Lynn Price, LBNL Ernst Worrell, LBNL METHODOLOGY: DIFFERENT MODELING APPROACHES:  METHODOLOGY: DIFFERENT MODELING APPROACHES Top down/econometric Bottom-up/engineering-economic Hybrids (like CEF-NEMS) N.B., All methods susceptible to the inappropriate use of historically-based parameters to model futures that are quite different from the business-as-usual case. METHODOLOGY (CONTINUED):  METHODOLOGY (CONTINUED) Analyze and compile latest technology data by sector and end-use. Define scenarios in detail, relying on program experience and judgment. Change decision parameters and technology costs in CEF-NEMS to reflect the scenarios. Run the CEF-NEMS model and associated spreadsheets to capture fuel-price feedbacks and direct cost impacts. Analyze second-order impacts of emissions trading using latest literature. TWO SCENARIOS:  TWO SCENARIOS (1) Moderate Scenario: relatively non-intrusive, no-regrets or low-cost policies. assumes some shift in political will & public opinion excludes fiscal policies that involve taxing energy (2) Advanced Scenario: more vigorous policies. assumes a nationwide sense of urgency includes a domestic carbon trading system with assumed permit price of $50/tC. Defined by policies that reflect increased levels of national commitment to energy and environmental goals. The scenarios are not forecasts or recommendations; they are possible pathways to a cleaner energy future. KEY POLICIES- ADVANCED SCENARIO*:  KEY POLICIES- ADVANCED SCENARIO* *The scenarios are defined by approximately 50 policies. These 10 are the most important ones in the Advanced scenario. Each policy is specified in terms of magnitude and timing (e.g., “431 kWh/year dishwasher standard implemented in 2010”). Enhanced R&D is estimated to improve technologies in all sectors. :  Enhanced R&D is estimated to improve technologies in all sectors. Slide14:  RESULTS: ENERGY USE Efficiency RD&D policies Advanced Scenario (~20% reduction in 2020) Energy Use (in Quads) RESULTS: ENERGY SOURCES:  RESULTS: ENERGY SOURCES Slide16:  RESULTS: CARBON EMISSIONS Need for R&D delays impacts on transportation, but by 2020 emission reductions are large. Electric sector policies account for a third of the carbon reductions in the Advanced scenario. Slide17:  Moderate Scenario Advanced Scenario THE ECONOMICS: Energy bill savings exceed investment costs, and the gap grows over time. Slide18:  RESULTS: DIRECT COSTS IN 2010 (units: Billions US $/year) (units: Billions US $/year) THE ECONOMICS:  THE ECONOMICS Based on data from EMF 16 and worst case assumptions (no smart revenue recycling of advanced case carbon trading fees), indirect macroeconomic costs are in the same range as net direct benefits. Important transition impacts and dislocations could still be produced in the advanced case (e.g., reduced coal and railroad employment). “Green” industries could grow significantly (e.g., wind, agriculture, and energy efficiency). CONCLUSIONS:  CONCLUSIONS Smart public policies can significantly reduce not only carbon dioxide emissions, but also local air pollution, petroleum dependence, and inefficiencies in energy production and use. RD&D, voluntary programs, efficiency standards, and other non-price policies play a critical role in the realization of these scenarios. The overall economic benefits of these policies appear to be comparable to their overall costs. EXTRAS (JUST IN CASE):  EXTRAS (JUST IN CASE) If energy efficiency is such a good idea, why don’t people do it anyway?:  If energy efficiency is such a good idea, why don’t people do it anyway? Engineering-economic analysis Engineering-economic analysis plus transaction costs Results with policy or program that reduces transaction costs Source: Adapted from Katrin Ostertag Transaction costs of raising energy efficiency. Working paper, May 1999. Presented at the IEA International Workshop on Technologies to Reduce Greenhouse Gas Emissions: Engineering-Economic Analyses of Conserved Energy and Carbon. Washington, DC. 5-7 May 1999. This example assumes that the energy efficient technology delivers the exact same service as the standard technology. Slide23:  Buildings Voluntary programs and equipment standards are the key policy mechanisms in this sector. Many small end-uses (“other”) are large contributors to total carbon savings. Lighting is also important. Residential Commercial Industry:  Industry Key Policies: Voluntary programs (technology demonstrations, energy audits, financial incentives), voluntary agreements between government and industry, and doubling cost-shared federal R&D. Key Crosscutting Technologies: Combined heat and power, preventive maintenance, pollution prevention, waste recycling, process control, stream distribution, motor and drive system improvements. Numerous subsector-specific technologies play a role. Industry:  Industry Cement, iron & steel, and other energy-intensive industries save the most energy. Pulp and paper industry reduces its carbon emissions by 41% in the Advanced scenario. Slide26:  Industry: Combined Heat and Power BAU New Capacity:  4 GW by 2010  9 GW by 2020 Advanced Scenario New Capacity:  29 GW by 2010  76 GW by 2020 In 2020, this saves:  2.4 quads of energy  40 MtC of emissions Transportation:  Transportation KEY POLICIES: Doubling cost-shared federal R&D is critical to achieving a greater degree of technological success Voluntary commitments by vehicle manufacturers to fuel economy goals Pay-at-the-pump insurance fees Domestic carbon trading system Transportation Technologies:  Transportation Technologies Turbo-charged direct injection (TDI) diesels and hydrogen fuel cell vehicles play a major role by 2020. Sales of New Vehicles (in 1,000s) Transportation Efficiency Technologies:  Transportation Efficiency Technologies Passenger Car MPG Improvements (Advanced Scenario) Gasoline Engine Technology Only, Year 2020 (28.6 to 44.1 MPG, or 8.2 to 5.3 l/100 km) Electricity:  Electricity Key Policies: domestic carbon trading system, restructuring of the electricity industry, production tax credit for non-hydro renewable energy, and R&D. Key Technologies: natural gas combined cycle plants, wind power, nuclear relicensing, biomass, and geothermal. Slide31:  Total Generation by Fuel (TWh) Slide32:  Non-Hydro Renewable Electric Generation in the Advanced Scenario (TWh) Standby power for TVs:  Standby power for TVs Source: Karen Rosen, LBNL, May 1999, KBRosen@lbl.gov Share of units measured Industrial Sector Voluntary Agreements by Companies:  Industrial Sector Voluntary Agreements by Companies Market Imperfections: Efficient Magnetic Ballast Market Shares:  Market Imperfections: Efficient Magnetic Ballast Market Shares Market Imperfections: Real IRRs for Efficient Magnetic Ballasts:  Market Imperfections: Real IRRs for Efficient Magnetic Ballasts Based on market data in the US commercial sector (circa 1989),

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