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Modeling Ozone in the Eastern U. S

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1 Modeling Ozone in the Eastern U. S
Modeling Ozone in the Eastern U.S. using a Fuel-Based Mobile Source Emissions Inventory Brian McDonald1,2, Stuart McKeen1,2, Yuyan Cui1,2, Ravan Ahmadov1,3, Si-Wan Kim1,2, Gregory Frost2, Ilana Pollack1,2, Thomas Ryerson1,2, John Holloway1,2, Martin Graus1,2, Carsten Warneke1,2, Joost de Gouw1,2, Jennifer Kaiser4, Frank Keutsch4, Thomas Hanisco5, Glenn Wolfe5,6, Michael Trainer2 CIRES, Univ. of Colorado, Boulder, CO Chemical Sciences Division, NOAA ESRL, Boulder, CO Global Sciences Division, NOAA ESRL, Boulder, CO Dept. of Chemistry, Univ. of Wisconsin, Madison, WI Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard, Greenbelt, MD Joint Center for Earth Systems Technology, Univ. of Maryland-Baltimore, Baltimore, MD Acknowledgments: NASA ROSES ACMAP and NOAA’s High Performance Computing Program. 2017 CMAS Conference

2 Recent Studies Suggest Overestimate in NEI 2011 NOx Emissions
Year Region Measurement Findings 2011 Baltimore/DC Aircraft (DISCOVER-AQ) Mobile sources overestimated by 50-70% [Anderson et al., Atmos. Environ. 2014]

3 Recent Studies Suggest Overestimate in NEI 2011 NOx Emissions
Year Region Measurement Findings 2011 Baltimore/DC Aircraft (DISCOVER-AQ) Mobile sources overestimated by 50-70% [Anderson et al., Atmos. Environ. 2014] 2013 Southeast (SEAC4RS) Reduce mobile and industrial sources by 30-60% [Travis et al., Atmos. Chem. Phys. 2016]

4 Recent Studies Suggest Overestimate in NEI 2011 NOx Emissions
Year Region Measurement Findings 2011 Baltimore/DC Aircraft (DISCOVER-AQ) Mobile sources overestimated by 50-70% [Anderson et al., Atmos. Environ. 2014] 2013 Southeast (SEAC4RS) Reduce mobile and industrial sources by 30-60% [Travis et al., Atmos. Chem. Phys. 2016] Urban Texas Satellite Inversion Reduce mobile, area, point sources by 30-60% [Souri et al., Atmos. Env. 2016]

5 Recent Studies Suggest Overestimate in NEI 2011 NOx Emissions
Year Region Measurement Findings 2011 Baltimore/DC Aircraft (DISCOVER-AQ) Mobile sources overestimated by 50-70% [Anderson et al., Atmos. Environ. 2014] 2013 Southeast (SEAC4RS) Reduce mobile and industrial sources by 30-60% [Travis et al., Atmos. Chem. Phys. 2016] Urban Texas Satellite Inversion Reduce mobile, area, point sources by 30-60% [Souri et al., Atmos. Env. 2016] Reduce total anthropogenic emissions by 14% [Li et al., Atmos. Chem. Phys. Disc. 2017]

6 Research Objectives Assess “Bottom-Up” Mobile Source Emissions
Focus on NOx, but CO and VOCs can also be assessed Construct fuel-based inventory and compare with EPA MOVES2014 Perform “Top-Down” Model Evaluation Evaluate emissions with aircraft- and ground-based measurements during Southeast Nexus (SENEX) Study in 2013 (3) Test sensitivity of ground-level O3 to mobile source NOx and biogenic VOC emissions

7 Trends in U.S. Mobile Source Activity (Fuel Use)
Emissions = Activity (kg fuel) x Emission Factor (g/kg fuel) Fuel estimates based on FHWA and EIA surveys Similar to fuel use reported in MOVES2014 Fuel Use (t/d) Year

8 Long-Term Trends in On-Road NOx Emission Factors
Emissions = Activity (kg fuel) x Emission Factor (g/kg fuel) NOx EF (g/kg fuel) Year

9 Long-Term Trends in On-Road NOx Emission Factors
Emissions = Activity (kg fuel) x Emission Factor (g/kg fuel) Diesel EF within ~20% NOx EF (g/kg fuel) Gasoline EF high by factor of ~2 MOVES EF are default values Year

10 NOx Emissions by Mobile Source Category (FIVE vs. MOVES)
Consistent with literature Anderson et al., Atmos. Env Travis et al., Atmos. Chem. Phys. 2016

11 WRF-Chem Modeling for Southeast Nexus (SENEX) Study
Model run from 6/1 – 7/15 in 2013 WRF-Chem Model v3.7 12 km x 12 km 61 vertical layers ECMWF-Era-Interim RACM_ESRL Chemistry Static Chemical B.C. Emission Cases: NEI * BEIS ISO NEI * BEIS ISO FIVE * BEIS ISO FIVE * BEIS ISO

12 Revise Mobile Source Emissions Only (NEI11 → FIVE13)
Total U.S. NOx emissions decreases by ~15%

13 Model Evaluation of NOx Emissions in Urban Plumes
Atlanta (SEARCH site) Nashville (P-3 aircraft) NEI11 Obs NEI11 Obs

14 Model Evaluation of NOx Emissions in Urban Plumes
Atlanta (SEARCH site) Nashville (P-3 aircraft) FIVE13 NEI11 Obs NEI11 Obs FIVE13

15 Model Evaluation of NOy and O3 across Southeastern U.S.
Emissions Case NOy (ppb) O3 (ppb) P-3 Obs. NEI * BEIS ISO NEI * BEIS ISO FIVE * BEIS ISO FIVE * BEIS ISO 2.1 2.9 (+43%) 2.8 (+34%) 2.5 (+21%) 2.3 (+13%) 47 56 (+9) 54 (+7) 53 (+6) 50 (+3) Emissions Case NOy (ppb) O3 (ppb) P-3 Obs. 2.1 47 Emissions Case NOy (ppb) O3 (ppb) P-3 Obs. NEI * BEIS ISO NEI * BEIS ISO 2.1 2.9 (+43%) 2.8 (+34%) 47 56 (+9) 54 (+7)

16 Evaluation of Model O3 with AQ Monitoring Sites (NEI 2011)
Model bias = 1220 days Bias in summer 2013 mean daily 8-h maximum modeled with NEI 2011 vs. AQS data

17 Improvement in Model O3 when Reducing Mobile Source NOx
FIVE is worse   FIVE is better Model bias = 1220 days Bias in summer 2013 mean daily 8-h maximum modeled with NEI 2011 vs. AQS data

18 Evaluation of Model on High Ozone Days (>70 ppb)
FIVE is worse   FIVE is better Bias in summer 2013 O3 exceedance days (>70 ppb) modeled with NEI 2011 vs. AQS data

19 High Ozone Days Sensitive to Mobile Source NOx
Episode 100 NEI11 No. of Sites (>70 ppb) FIVE13 50 Obs 6/1 6/11 6/21 7/1 7/11

20 Summary NOx overestimate seen in model, and partially explained by biases in mobile source emissions Biggest discrepancies found in the on-road gasoline sector Suggest reducing mobile source NOx emissions by 20-30% to be consistent with roadside studies and ambient measurements of NOy In Eastern U.S., ozone sensitive to mobile source NOx Small changes in transportation NOx → significant effects on high O3 days

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