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Assessment of Environmental Benefits (AEB) Modeling System A coupled energy-air quality modeling system for describing air quality impact of energy efficiency. Fifth Annual CMAS Conference Chapel Hill, NC October 16-18, 2006 Session 5: Regulatory Modeling Studies.

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slide1

Assessment of Environmental Benefits (AEB) Modeling System

    • A coupled energy-air quality modeling system for describing air quality impact of energy efficiency

Fifth Annual CMAS Conference

Chapel Hill, NC

October 16-18, 2006

Session 5: Regulatory Modeling Studies

Principal Investigator Bob Imhoff

bob.imhoff@baronams.com

assessment of environmental benefits modeling system aeb objective
Assessment of Environmental Benefits Modeling System (AEB) Objective
  • Get SIP Credit for Air Quality Benefits of Energy Efficiency Technologies:
  • How do we make the case?
    • Link together accepted models using new S/W tools and new methods
      • ORCED = Oak Ridge Competitive Electricity Dispatch model (Stan Hadley, ORNL)
      • SMOKE
      • CMAQ
  • Follow USEPA Guidance of August 5, 2004 to ensure emission reductions will be: Quantifiable, Surplus, Enforceable, Permanent
slide4

Source Domain for CMAQ Sensitivity Analyses

Southern + TVA + VACAR subregions; that portion of SERC that most closely resembles VISTAS

cmaq modeling scenarios
CMAQ modeling scenarios

Future base case: VISTAS OTW 2018 F4

Modeling time period: 1 year

Met data: 2002 (VISTAS)

Grid resolution: 36 km

slide12

“Power-gen Pictogram” originated by Stan Hadley of ORNL,

developer of the ORCED power dispatch model

results so2 reductions joint action
Results – SO2 Reductions, joint action

Coordinated EE implementation improves NC-only results by 35% from 43k tons to 58k tons

results 2018 reductions at current costs
Results – 2018 Reductions at Current Costs

Market rates for Allowances from Evolution Markets, Inc. at

http://www.evomarkets.com/emissions/index.php?xp1=so2 and

http://www.evomarkets.com/emissions/index.php?xp1=sipnox

results 2018 reductions at projected cost
Results – 2018 Reductions at Projected Cost

Beyond 300k Annual Tons

SO2 Reduction: $5,000/ton*

NOx Allowance: $5,000/ton**

*according to recent analysis by G. Stella of Alpine Geophysics, SO2 reductions costs increase exponentially beyond 300k tons reduced

**approximate value indicated for 2018 by EIA in AEO2005

results 2018 reductions conservative projection of costs and demand impact
Results – 2018 Reductions, Conservative Projection of Costs and Demand Impact

SO2 Reduction: $2,115/ton*

NOx Allowance: $3,000/ton**

*average of per ton cost for annual reductions less than 300k tons (data from analysis by G. Stella of Alpine Geophysics)

**approximately mid-way between present day trade value and projection by EIA for 2018

conclusion linkage between energy modeling and air quality modeling with aeb
Conclusion: Linkage Between Energy Modeling and Air Quality Modeling with AEB

SM

Sensitivity Matrix captures the intelligence of CMAQ modeling runs with pollutant-specific, gridded, hourly sensitivity factors.

Expresses the modeled sensitivity of emissions and the ambient air in response to changes in power demand

Principal benefit: states’ tool for characterizing emissions and air quality benefits from EERE technologies / programs.

acknowledgments
Acknowledgments
  • Bob Imhoff (BAMS),Principal Investigator
  • Jerry Condrey (BAMS), software tool development
  • Stan Hadley (ORNL), demand projections and power dispatch modeling
  • Ted Smith (BAMS), server side development (output products)
  • Joe Brownsmith (UNCA), EUI development
  • Dr. Saswati Datta (BAMS), data analysis
  • Jesse O’Neal (BAMS) project management and outreach
  • Marilyn Brown and Barbara Ashdown (ORNL), project directors

Questions and comments to: Bob Imhoff

Baron Advanced Meteorological Systems (BAMS)

bob.imhoff@baronams.com