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Our modeling framework integrates

This study examines the economic benefits of reduced ozone damage to Eastern US forests resulting from the EPA's Heavy Duty Engine/Diesel Fuel Final Rule. Integrated modeling techniques are used to estimate the commercial forest productivity benefits using atmospheric chemistry, biology, and economics. The results show significant economic gains from reducing NOx emissions.

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Our modeling framework integrates

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  1. Integrated Forestry Ozone Regulatory Modeling System (InFORMS)Economic Benefits of Reduced Ozone Damage to Eastern US Forests Resulting from US EPA’s Heavy Duty Engine/Diesel Fuel Final Rule& Brief Discussion of Forestry Aesthetics Bryan Hubbell,1 Patricia Koman,1 John Laurence,2 Brian Heninger,3 Andrea Petro,4 John Mills,5 and Richard Haynes 5, Yewah Lau1 Presented by Linda M. Chappell Ph.D.1

  2. 1US Environmental Protection Agency, Office of Air Quality Planning and Standards, Innovative Strategies and Economics Group, Research Triangle Park, NC 27711 • 2US Environmental Protection Agency, Office of Research and Development, NHEERL, Western Ecology Division, Corvallis, Oregon 97330 and Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, 14853 • 3US Environmental Protection Agency, National Center for Environmental Economics, 1200 Pennsylvania Ave, Washington, DC 20460 • 4Indiana University, School of Public and Environmental Affairs, 1315 E. 10th Street, Bloomington, IN 47405 • 5US Forest Service, Pacific Northwest Research Station, 1221 SW Yamhill, Suite 200, Portland, OR 97208 • For More Information: www.epa.gov/otaq/diesel.htm or ww.fs.fed.us/pnw/serv/rpa/model.htm

  3. The US EPA finalized the Heavy Duty Engine/Diesel Fuel rule in December 2000. The NOx emissions reductions from this rule contribute to a constellation of beneficial ecosystem effects related to forest health. • We focused on commercial forest productivity benefits of reduced ozone damage to Eastern U.S. forests that will result from reductions in NOx emissions when the policy is fully phased in. • For commercial forestry, well-developed techniques are available to estimate biological and market changes independently; however,this is the first time we have integrated them as we have here in theIntegrated Forestry Ozone Regulatory Modeling System (InFORMS).

  4. Our modeling framework integrates • Atmospheric Chemistry: modeled future ozone concentrations from Urban Airshed Model (UAM-V); • Biology: species-specific concentration-response functions estimated from TREGRO model simulations and USDA’s Forest Inventory Analysis data; and • Economics: modeled by the Timber Assessment Market Model (TAMM)/Aggregated Timberland Assessment System (ATLAS). • Annual benefits= sum of the annualized present value of the stream of benefits (change in consumer and producer surplus) over a 30 year period plus the annualized present value of additional accumulated forest inventories.

  5. Air Quality Inputs Biological Inputs Model: TREGRO Scope:6 Species in 6 Eastern regions at county level Metric: Relative Stem Biomass Loss Concentration-Response functions Model: UAM-V Scope: Eastern US at county level Metric: SUM06 in 2030 for base case and HD Engine/Diesel Fuel control scenario County-level Growth Adjustment Factors by Species Multi-Stage Weighting Process (1) Assign weights based on county-level species-specific biomass estimates (2) Aggregate county data to TAMM/ATLAS Regions by species (3) Aggregate species to ATLAS forest types within TAMM/ATLAS Regions. Economic Modeling Model: TAMM/ATLAS Scope: National with Eastern O3 changes only; assumes no change in West or Canada Metric: Net Present Value of changes in producer and consumer surplus and value of stumpage inventory from 2020 to 2050

  6. Air Quality Inputs: UAM-V • US EPA’s Urban Airshed Model • Predicting county-level year-round ozone concentrations • Eastern domain only • In year 2030 with and without the HD Engine/ Diesel Fuel rule • Policy fully implemented in 2030 with truck fleet turn-over • Ozone season (May – September) using eVNA to interpolate data

  7. Air Quality Inputs: UAM-V

  8. Biological Inputs: TREGRO • Using TREGRO-derived region-specific functions relating biomass loss to changes in ozone in 6 species • Black Cherry • Loblolly Pine • Red Oak • Red Spruce • Sugar Maple • Tulip Poplar

  9. Biological Inputs: TREGRO Zones

  10. Multi-Stage Weighting Process + TREGRO Function To set up the economic model we must know what portion of the ATLAS forest inventory is affected by ozone changes from the policy (for the species and areas we are able to quantify). ozone Growth County X ATLAS Regions and Forest Types (e.g., Lowland hardwood)

  11. Multi-Stage Weighting Process • Analytical Steps: • Assign weights based on county-level species-specific biomass estimates • Aggregate county data to TAMM/ATLAS regions by species • Aggregate species to ATLAS forest types within TAMM/ATLAS regions

  12. Change in Growth Adjustment Factors (x 10-6)

  13. Economic Modeling: TAMM/ATLAS • TAMM evaluates timber production and market changes • Spatial model of solidwood and timber inventory in US • Timber price, quantity • Net change in consumer and producer surplus and change in value of accumulated inventories • Area for further research and analysis

  14. Research Needs for Economic Benefits Analysis Air Quality Inputs Biological Inputs Additional species parameterized; extrapolations to other species* Stand-level interactions (Zelig) Western tree inventories Non-timber related values Western US air quality changes Model performance in rural/remote settings Canadian air quality changes Multi-year modeling Economic Modeling Ability to model long time horizons and sensitivities to assumptions Comparison with Forest and Agricultural Sector Optimization Model (FASOM) in which long-term trends may be changed and the Subregional Timber Supply Model (STSM) that may be better able to handle marginal impacts *See next slide

  15. Additional Species Parameterized • Ponderosa Pine, Red Maple, American Basswood, Chestnut Oak, White Ash, and White Fir • Enhances coverage of marketable species in the US

  16. Forestry Aesthetics • Air pollution can cause a range of visual injuries to forest (discoloration of leaves to extensive defoliation and death of trees). • Pollutants that may cause visual forestry symptoms include tropospheric ozone, sulfur dioxide, hydrogen sulfide (other pollutants include mineral acids, heavy metal such as lead and mercury, nitrogen oxides, ammonia, peroxyacetyl nitrate, chlorides, and ethylene). • Evidence indicates people value forest aesthetics and change outdoor recreational behavior according to the quality of forest health

  17. Limited Analysis • Benefits & Cost of the Clean Air Act 1990 to 2010 evaluates this category of benefits as an illustrative calculation. • Research needs include: • Natural science component of assessment (trends in forest health, links between forest health and air pollution, and dose-response relationships) • Economic valuation studies • Long-term monitoring networks that are capable of linking causal agent(s) to forestry aesthetics

  18. Progress has occurred in the area of commercial forestry benefit assessments! Much work is required to assess economic aesthetic forestry benefits with any degree of specificity! Conclusions

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