NO X emissions, isoprene oxidation pathways, and implications for surface ozone in the Southeast United States

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(Katie) Travis CMAS 216: 1/26/16 Co-authors: D. J. Jacob, J. A.

M. Yantosca, M. P. Sulprizio, A. M. Thompson, P. O. Wennberg, J.

Dibb, S. R. Hall, K. Ullmann, G. M. Wolfe, I. B. Pollack, J.

Zhou This work was supported by the NASA Earth Science Division

9176161- awarded by the US Environmental Protection Agency

1 NO X emissions, isoprene oxidation pathways, and implications for surface ozone in the Southeast United States Katherine (Katie) Travis CMAS 216: 1/26/16 Co-authors: D. J. Jacob, J. A. Fisher, P. S. Kim, E. A. Marais, L. Zhu, K. Yu, C. C. Miller, R. M. Yantosca, M. P. Sulprizio, A. M. Thompson, P. O. Wennberg, J. D. Crounse, J. M. St. Clair, R. C. Cohen, J. L. Laughner, J. E. Dibb, S. R. Hall, K. Ullmann, G. M. Wolfe, I. B. Pollack, J. Peischl, J. A. Neuman, and X. Zhou This work was supported by the NASA Earth Science Division and by STAR Fellowship Assistance Agreement no awarded by the US Environmental Protection Agency (EPA). It has not been formally reviewed by EPA. The views expressed in this presentation are solely those of the authors.

2 The Southeast US Is One of the Most Difficult Regions to Model for Surface Ozone Monthly Mean Surface O 3 CASTNET Observations Multi-model Mean Fiore et al, Blame has included isoprene chemistry, isoprene emissions, dry deposition etc.

SEAC 4 RS (Aug-Sep 213) Provided an Unprecedented Dataset to Investigate Air Quality in the Southeast US SEAC 4 RS Flight Tracks from DC8 Aircraft Data Used for this Study

3 SEAC 4 RS (Aug-Sep 213) Provided an Unprecedented Dataset to Investigate Air Quality in the Southeast US SEAC 4 RS Flight Tracks from DC8 Aircraft Data Used for this Study Include: Thomas Ryerson, NOAA: NO y, NO, NO 2, O 3 Ron Cohen, Berkeley: NO 2 Paul Wennberg, Caltech: isoprene oxidation products Jack Dibb, UNH: HNO 3 Sam Hall, NCAR: J-values

GEOS-Chem Incorporates State-of-the-Science Understanding of O 3 -NO x -VOC Chemistry.25 o x.3125 o resolution over North America. Emissions: Biogenic from MEGAN (Guenther et al., 212).

4 GEOS-Chem Incorporates State-of-the-Science Understanding of O 3 -NO x -VOC Chemistry.25 o x.3125 o resolution over North America. Emissions: Biogenic from MEGAN (Guenther et al., 212). See Zhu et al, 216 (ACPD) Soil NO x from Hudman et al (212). Lightning NO x according to Murray et al. (212). Anthropogenic emissions from EPA s NEI 211v1. Chemistry: Chemistry from Mao et al. (213). With bromine chemistry (Parrella et al., 212). Improved treatment of low- and high- NO x pathways to incorporate recent lab studies. Physical processes: Faster deposition of isoprene oxidation products (Nguyen et al, 215). 1 4

5 NO x and Ozone are Overestimated in the Original GEOS-Chem Simulation 12 1 Fertilizer, 13 Altitude, km DC8 GEOS-Chem Original NO Fires, 5 Soil, 34 Industry, 61 Mobile, NO X, ppb O 3, ppb PBL is 6% too high for NO x and 12ppb too high for ozone. SEAC 4 RS PI Jack Dibb: HNO 3, Thomas Ryerson: O 3, NO, NO 2 Power Plants, 37 NEI11v1 (Gg N)

Reducing NEI11v1 by 5% Improves Agreement with

Altitude, km 1 8 6 4 2 DC8 GEOS-Chem Original

Mobile, 43 Power Plants, 37..2.4.6.8 NO X, ppb.

ppb SEAC 4 RS PI Jack Dibb: HNO 3 Thomas

NEI mobile NO x is overestimated Castellanos

Brioude et al, 213; Anderson et al, 214.

6 Reducing NEI11v1 by 5% Improves Agreement with SEAC 4 RS NO y and O 3 12 Fertilizer, 13 Altitude, km DC8 GEOS-Chem Original NO x Emissions Soil, 31 Fires, 5 Industry, 24 Mobile, 43 Power Plants, NO X, ppb HNO 3 +NO 3 -, ppb O 3, ppb SEAC 4 RS PI Jack Dibb: HNO 3 Thomas Ryerson: O 3, NO, NO 2 Many studies find that NEI mobile NO x is overestimated Castellanos et al, 211; Fujita et al, 212; Yu et al, 212; Brioude et al, 213; Anderson et al, 214. We scale NEI11v1 by 5% by reducing industry and mobile NO x by 6%.

7 NO x and O 3 Concentrations Below 1.5 km NO and O Concentrations Below 1.5 km x 3 Spatial Variability Shows No Significant Biases NO x, ppb NO, ppb x Observed NO x Observed O 3 Observed NO x Observed O 3 O 3, ppb O, ppb 3 r=.71 Model NO x x Model O 3 3 Mean model bias for ozone is +2 ppb, 9% for NO x SEAC 4 RS PI Thomas Ryerson: O 3, NO, NO 2

Simulation with Scaled NO x Successfully Captures 12 Isoprene Oxidation Pathways From SEAC 4 RS X 3 3 12 12 1 1 1 Altitude, km 8 6 4 2 High NOx pathway 8 6 4 2 DC8 GEOS-Chem Original NO x 8 6 4 2 2

8 Simulation with Scaled NO x Successfully Captures 12 Isoprene Oxidation Pathways From SEAC 4 RS X Altitude, km High NOx pathway DC8 GEOS-Chem Original NO x ISOPN, ppt ISOPOOH, ppt HPALD, ppt ISOPRENE + OH à RO 2 Isom. ISOPN HPALD ISOPOOH SEAC 4 RS PI Paul Wennberg: ISOPN, ISOPOOH, HPALD See Fisher et al, 216 (ACP) for more on ISOPN

54% 26% 1 8 6 4 2 % ISOPO 2 +HO 2 5 4 3 2 1 % ISOPO 2 Isomerization

9 4 o N % ISOPO 2 +NO Reductions in NO x Have a Smaller Impact Due to Spatial Segregation of Emissions 35 o N 3 o N 4 o N 35 o N 3 o N 4 o N 54% 26% % ISOPO 2 +HO % ISOPO 2 Isomerization More details in: Yu, K. et al, ACP (216) 35 o N 3 o N 9 o W 8 o W 15%

10 We Add New Constraints on NO x Using Measurements of Deposition NO 2 + OH + Mà HNO 3 NO x = NO + NO 2 Very soluble H +,NO 3 - What Goes Up Must Come Down Dry deposition of HNO 3 Wet deposition of NO 3 - Measured during Southern Oxidant and Aerosol Study June-July 213 Measured by the National Atmospheric Deposition Program

Wet Deposition Supports National Scaling of NEI11 US Nitrate Wet Deposition August-September 213.

11 Wet Deposition Supports National Scaling of NEI11 US Nitrate Wet Deposition August-September Nitrate ((kg N ha -1 month -1 ) Nitrate (kg N h a 1 month 1 ) Modeled (kg N h a 1 month 1 ) Model (kg N ha -1 month -1 ) Reduced NO x (Bias = 7%) Original NO x (Bias = 63%) Southeast US: Bias = 8%, r=.71 CONUS: Bias =7%, r=.76 Observations (kg N ha -1 month -1 )

12 Ozone Production Efficiency (OPE) Provides Constraint on Efficiency of Ozone Formation 1 OPE, Altitude < 1.5km OPE, Altitud 8 O X = O 3 + NO 2, ppb 6 4 Southeast US 2 SEAC 4 RS:[O x ] = [NO z ], r =.7 GEOS-Chem:[O x ] = [NO z ], r = NO z, ppb SEAC 4 RS:[O x ] = 1 2 Without scaling, OPE = 14.7 which means ozone would be produced less efficiently than observed.

13 How well can we constrain US NO x emissions with OMI NO 2? OMI NO 2 (BEHR) OMI NO 2 (NASA v2.1) 2 Observed (BEHR) Aug-Sep 213 data with GEOS-Chem shape factors 1E15 molec/cm 2 > GEOS-Chem with reduced NO x emissions -18% vs. BEHR -11% vs. NASA Observed (NASA) GEOS-Chem BEHR: % _ NASA: % _ Low bias in GEOS-Chem is due to upper troposphere, not surface emissions With original NEI emissions, Bias = %

14 Free/upper troposphere makes major contribution to OMI NO 2 tropospheric column in summer Mean SEAC 4 RS NO 2 profiles 25-4% of column 65-8% of column Mean NO/NO 2 ratio GEOS-Chem low bias in upper troposphere is caused by NO/NO 2 chemistry; insufficient convection of HO x precursors HCHO and CH 3 OOH? [NO]/[NO2] k7/(k5[o3]) O3, HO2, RO2 NO ¾¾¾ ¾¾¾¾¾ ¾ hn NO Current OMI retrievals may have large AMF errors 2 SEAC 4 RS PI Thomas Ryerson: NO 2 Ron Cohen: NO 2

15 Discrepancy Remains Between Surface & Upper PBL O Median Ozonesonde Ozone Vertical Profile Below 1.5km Altitude, km Altitude, km 1..5 Ozonesonde GEOS-Chem 4ppb CASTNET O 3, ppb O 3, ppb 48ppb GEOS-Chem PI. Anne Thompson MDA8 Remaining uncertainties are potential O 3 sinks and boundary layer mixing. O 3

16 Conclusions NEI11v1 for NO x is biased high across the US by as much as a factor of 2. Emissions from industrial and mobile sources must be 3-6% lower than NEI values. Evidence for this comes from (1) SEAC 4 RS observations of NO x and its oxidation products, (2) NADP network observations of nitrate wet deposition fluxes. The OPE in the boundary layer is well reproduced. There may be large errors in satellite NO 2 columns due to the presence of upper tropospheric NO 2. Observations show departure from photochemical steady-state. MDA8 surface ozone is still biased against the CASTNET observations by approximately 8ppb. Travis, K. R., Jacob, D. J. et al. Why do models overestimate surface ozone in the Southeast United States?, ACP, 216 (in press). ktravis@fas.harvard.edu

17 Additional Papers from SEAC 4 RS Organic nitrates: Fisher, J. A. et al.: Organic nitrate chemistry and its implications for nitrogen budgets in an isoprene- and monoterpene-rich atmosphere: constraints from aircraft (SEAC 4 RS) and groundbased (SOAS) observations in the Southeast US, Atmos. Chem. Phys., 16, , doi:1.5194/acp , 216. Formaldehyde: Zhu, L. et al.: Observing atmospheric formaldehyde (HCHO) from space: validation and intercomparison of six retrievals from four satellites (OMI, GOME2A, GOME2B, OMPS) with SEAC 4 RS aircraft observations over the Southeast US, Atmos. Chem. Phys. Discuss., doi:1.5194/acp , in review, 216. Aerosols: Kim, P. S., Jacob, D. J. et al.: Sources, seasonality, and trends of southeast US aerosol: an integrated analysis of surface, aircraft, and satellite observations with the GEOS-Chem chemical transport model, Atmos. Chem. Phys., 15, , doi:1.5194/acp , 215. SOA: Marais, E. A. et al.: Aqueous-phase mechanism for secondary organic aerosol formation from isoprene: application to the southeast United States and co-benefit of SO 2 emission controls, Atmos. Chem. Phys., 16, , doi:1.5194/acp , 216. Model Resolution: Yu, K. et al.: Sensitivity to grid resolution in the ability of a chemical transport model to simulate observed oxidant chemistry under high-isoprene conditions, Atmos. Chem. Phys., 16, , doi:1.5194/acp , 216

Jenny A. Fisher et al. Correspondence to: Jenny A. Fisher

Jenny A. Fisher et al. Correspondence to: Jenny A. Fisher Supplement of Atmos. Chem. Phys., 6, 5969 599, 6 http://www.atmos-chem-phys.net/6/5969/6/ doi:.59/acp-6-5969-6-supplement Author(s) 6. CC Attribution. License. Supplement of Organic nitrate chemistry and