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David Parrish - NOAA Aeronomy Laboratory

Today:. Review “Section 6.4: Evaluation of the strengths and weaknesses of current inventories and models.”. Please feel free to provide critiques and feedback!!!. Preview of NARSTO Emission Inventory Assessment. David Parrish - NOAA Aeronomy Laboratory.

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David Parrish - NOAA Aeronomy Laboratory

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  1. Today: • Review “Section 6.4: Evaluation of the strengths and weaknesses of current inventories and models.” • Please feel free to provide critiques and feedback!!! Preview of NARSTO Emission Inventory Assessment David Parrish - NOAA Aeronomy Laboratory EMIS Meeting, Portsmouth NH, August 3, 2004

  2. NARSTO Emission Inventory Assessment 1.0 Introduction 2.0 Overview of Emissions Inventories Provide an emissions inventory primer for decision makers 3.0 Vision for Future North American Emission Inventory Programs Set the target: define where we need to be in future years. 4.0 North American Emission Inventories List what currently exists 5.0 Inventory Tools Describe how are inventories constructed 6.0 Strengths and Weaknesses of Current Inventories and Models: Sensitivities, Uncertainties, and Applicability Describe how to evaluate Provide an evaluation of important sectors 7.0 Evolving Tools for Determining Emissions Describe advanced methods and methodologies 8.0 Roadmap for Future Emission Inventory Application and Development

  3. Emission Inventory Development Starting Point for EI Regional/State/Local/Tribe/Provincial Improvements EI Applications Measurement Methods Field Testing and Sampling Emissions Processor Local Activity Levels & Variables Emission Factors and Models Forecasting Preliminary EI for Base 20xx States and Other Stakeholders Improved EI for Base Year 20xx Databases for Source Activity Levels Speciation Factors Defaults for Emissions Related Variables Temporal Factors Factor and Model Improvements Spatial Factors Point and Non Point Source Data Growth Factors Tests, Evaluations and Reviews

  4. Emission Inventory Development Starting Point for EI Regional/State/Local/Tribe/Provincial Improvements EI Applications Measurement Methods Field Testing and Sampling Emissions Processor Local Activity Levels & Variables Emission Factors and Models Forecasting Preliminary EI for Base 20xx States and Other Stakeholders Improved EI for Base Year 20xx Databases for Source Activity Levels Speciation Factors Defaults for Emissions Related Variables Temporal Factors Factor and Model Improvements Spatial Factors Point and Non Point Source Data Growth Factors Tests, Evaluations and Reviews

  5. 2000 = MOBILE 5 2003 = MOBILE 6 Evaluations of Road Transport Emissions: History of temporal trends of road transport emissions in NEI • U.S. EPA emissions estimates have • changed drastically. Danger Sign!! • Most recent emissions estimates are • uncertain by at least ~10% for VOC • and NOx and ~50% for CO. • For 1985 the 2003 estimate is higher than • previous estimates by factors of up to 1.35, • 1.6 and 2.5 for NOx, VOC, and CO

  6. Evaluations of Road Transport Emissions: Temporal trend of CO emissions in NEI compared to ambient levels • Trends in 2003 Report agree well • with trend of ambient levels, • but not 2000 Repoprt. - 4.2 %/yr • Exception is latest 2 years. Urban • Rural U.S. CO levels have also • decreased, but at a rate of • only about 3%/yr. • [Hallock-Waters et al., GRL, • 26, 2861-2864, 1999] - 4.4 %/yr - 2.7 %/yr • No information regarding the • accuracy of the absolute • emissions. 2000 = MOBILE 5 2003 = MOBILE 6

  7. Evaluations of Road Transport Emissions: Temporal trend of CO/NOx ratio in NEI compared to ambient ratios Neither Trends Report captures rapid decrease in CO/NOx ratios. Neither Trends Report matches recent low observed CO/NOx ratios, and 2003 is worse than 2000. Disagreement a factor > 2 by 2000. Current U.S. emissions estimates are too high for CO, and/or too low for NOx. (Parrish et al.,JGR, 107, 4140, doi:10.1029/2001JD000720, 2002)

  8. Evaluations of Road Transport Emissions: Comparison of fuel-based and mileage-based emissions estimates Nashville 1995 Road Transport Sources Fuel-based emissions agree with ambient CO/NOx MOBILE 5B emissions vs. Fuel-based in 1995: VOC agree well. NOx agree well, but not partitioning CO ≈ 40% high MOBILE 6 emissions (2003 Trends Report) would degrade CO comparison (Harley et al., JGR, 106, 3559-3567, 2001) EPA equivalent to 2000 Trends Report

  9. Conclusions: CO emissions in the 2003 Trends Report are over estimated by a factor of 2 for 1990-2001 (worse lately). NOx emissions are within 20% of the 2003 Trends Report values for all years after 1993, but are increasing rather than decreasing. Interestingly, the inferred NOx temporal trend closely follows the increasing trend of the first 5 years of the 1990s in the 2000 Trends Report. Evaluations of Road Transport Emissions: Reconciliation of estimated emissions with ambient measurements Assumptions: CO emissions trend assumed to be - 5.1 %/yr (1990-2000 temporal trend of ambient CO levels). CO to NOx emission ratio trend assumed to be - 8.8 %/yr (temporal trend for L.A. Nashville). 1995 NOx emissions from the 2000 Trends Report are assumed to be accurate.

  10. Evaluations of Road Transport Emissions: Reconciliation of estimated emissions with ambient measurements Conclusions: No substantial inconsistencies have been identified in the VOC emissions. VOC emissions trend for 1990-2000 (2003 Trends Report) is - 5.7 %/yr, very close to - 5.1 %/yr trend of ambient CO levels. VOC emissions do not increase recently as CO.

  11. Evaluations of Road Transport Emissions: Evaluation of VOC speciation Assumptions: Benzene & acetylene: • are from road transport • react slowly in the atmosphere - • ambient benzene to acetylene ratio • reflects emission ratio Conclusions: Benzene / acetylene ratio: Mean Benzene/Acetylene Ratio • exhibits long-term trends in response • to VOC emission control measures • The inventory values are a factor of • 3 to 4 higher than ambient, and • trends do not agree. • There is a critical need for a re- • evaluation of the VOC speciation • in the NEI.

  12. Evaluations of Power Plant Emissions: Nearly 50 plume studies on over 30 CEMS-equipped power plants (1995, 1997, 1999, 2000, and 2002). Flux ratios agree on average within estimated uncertainty of ambient determinations (± 10%). There are occasional significant discrepancies.

  13. Evaluations of Power Plant Emissions: Absolute NOx, SO2 and CO2 fluxes agree with CEMS data within the estimated uncertainty (±20% for optimum conditions). There are occasional significant discrepancies. emission tabulated / flux measured Conclusions: CEMS data are accurate CEMS data are accurately integrated into the NEI CO emissions can be more than a factor 10 higher than inventoried.

  14. Evaluation of Emissions from Texas Petrochemical Facilities Inventory alkene emissions are low by the following factors: Sweeny Freeport Choc. Bayou Ethene: 72 60 25 Propene67 70 40 Coincident, highly elevated levels of NOx and reactive VOCs lead to rapid formation of high O3 levels. Models using inventoried emissions of VOCs fail. (Ryerson et.al.,JGR, 108, 4249, doi:10.1029/2002JD003070, 2003)

  15. Inverse modeling application to ammonia emission inventory Compared to emission inventory, inverse modeling showed: • Showed 40% lower average annual emissions with strong seasonal cycle. • Dramatic improvement in aerosol nitrate simulation (not included in inverse optimization) PM2.5 source apportionment from chemical mass balance compared to the emission inventory in Denver, CO Compared to emission inventory, CMB showed: • Showed nearly twice the fractional contribution from fugitive dust emissions. • Did not include cold start gasoline vehicle exhaust, which makes a substantial contribution in the CMB analysis. • Underrepresented high emitter (i.e. poorly-maintained) gasoline vehicles.

  16. Recommendations Challenge inventories with ambient measurements. (Appropriate sites, measurement techniques, data analysis.) Increase interaction and feedback between inventory and measurement folks. Conclusions “Top down” tests do provide valuable evaluations of current inventories. It is not yet possible to develop “bottom up” inventories that are accurate enough for many scientific uses without support of direct measurements (e.g. CEMS) Still, “bottom up” inventories are indispensable

  17. Global CO Emissions Inventory Enigmas: Compared to U.S., Western Europe emits factor of 2 less with 40% more population.Lifestyle! Western Europe emissions decreasing significantly while U.S. emissions nearly constant? Road transportation emissions in U.S.: ≈ 2/3 of total. Really increasing?

  18. ≈ 86% increase in vehicle miles traveled 1975-1998 “National Vehicle Emissions Policies and Practices and Declining US Carbon Monoxide-Related Mortality”, J.A. Mott et al., J. Amer. Med. Assoc., 288, 988-995, 2002.≈ 12,000 deaths avoided in U.S. “Everyone knows” that CO emissions have decreased dramatically over the last couple of decades Death rates from CO Poisoning

  19. U.S. National CO Emissions Inventory Enigmas: U.S. EPA emissions estimates have changed drastically. Danger Sign!! Looking at history of current estimates gives impression of increasing emissions. (Road Transport Sources)

  20. U.S. National CO Emissions Inventory Enigmas: U.S. EPA emissions estimates have changed drastically. Danger Sign!! Looking at history of current estimates gives impression of increasing emissions. EDGAR EDGAR inventory may be affected by this changing of models (Road Transport Sources)

  21. CO to NOx Ratio in Urban Vehicle Exhaust Ambient CO and NOy correlate well during morning rush hour. Ambient measurements characterize CO/NOy emission ratio in vehicle exhaust.

  22. CO to NOx automotive exhaustemission ratios • Ratio of CO to NOx in vehicle exhaust • has decreased dramatically at these • two sites from 1989 to 1999.

  23. National inventory does not • accurately reflect observed • decrease. (National Air Pollutant Emission Trends, 2000) Comparison to Emission Inventories • Colorado inventory does • reflect Boulder decrease. CO to NOx Ratio • VOC emissions parallel • CO emissions. • The character of urban • photochemistry must have • changed as well. (Colorado Department of Public Health and Environment)

  24. Emissions ratios: from near-field aircraft transects in mixed layer

  25. Emissions ratios: from near-field aircraft transects in mixed layer

  26. Emissions ratios: from near-field aircraft transects in mixed layer

  27. Emissions ratios: from near-field aircraft transects in mixed layer slopes from multiple transects vary by ±2% combined instrumental uncertainties typ. ± 10% provides an exacting test of inventory ratios

  28. Absolute emission rates:calculate flux across plume transect White et al., Science, 194, 187-189, 1976.

  29. Absolute emission rates:calculate flux across plume transect Thomas Hill plant Randolph County, MO July 7, 1999 20 km/1.5 hrs downwind Estimated uncertainty of ±20% in flux calculation under optimal conditions

  30. Application to CO emissions from power plants: Power plant combustion is carefully monitored for maximum efficiency; most power plants emit undetectable amounts of CO, most of the time Martin Lake (TX) Monticello (TX) expected slopes, from inventory ratios Three out of four lignite-coal-fueled power plants showed substantially enhanced CO emissions, up to factors of 30 greater than inventory values; also observed in bituminous- and gas-fired electric utility power plants. J. Environ. Monit., 5, 35-39 (2003)

  31. Application to petrochemical industrial emissions: Houston, TX Compare measured (alkene/NOx) to inventory (alkene/NOx) • Electra NOx and VOC measurements accurate to ±10% • 2000 PSDB inventory NOx data are accurate to ± 30% • any larger discrepancies in (alkene/NOx) comparison attributed to errors in the alkene emissions inventory

  32. Application to petrochemical industrial emissions: Houston, TX Inventory alkene emissions are low by the following factors: Sweeny Freeport Choc. Bayou Ethene: 72 60 25 Propene67 70 40 (JGR, 108(D8), 4249, doi:10.1029/2002JD003070, 2003)

  33. Nashville and Boulder are representative

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