Controls on O 3 and SOA production in wildfire plumes (and how to model them)

Transcription

1 Controls on O 3 and SOA production in wildfire plumes (and how to model them) M. J. Alvarado 1, D. A. Jaffe 2, C. R. Lonsdale 1, N. L. Wigder 2, P. Baylon 2, R. J. Yokelson 3, K. Travis 4, E. V. Fischer 5, and J. C Lin 6 1 Atmospheric and Environmental Research (AER) 2 University of Washington-Bothell 3 University of Montana 4 Harvard University 5 Colorado State University 6 University of Utah Western Air Quality Modeling Workshop May 13, 2015 Atmopsheric and Environmental Research, Inc., Government sponsorship acknowledged. 1

2 Outline Mt. Bachelor (MBO) Fire Observations Modeling the Near Source Chemistry of Smoke Plumes Improving the Representation of Near Source and Downwind Smoke Plume Chemistry in Air Quality Models 2

3 O3 in wildfires seen at MBO 13 of 32 plumes ( ) had enhanced O3 O3/ CO = (Wigder et al., AE, 2013) Review of Jaffe & Wigder, AE, 2012, found majority of studies reported enhanced O3 but with large variability O3/ CO = MCE (CO2/[CO+CO2]) and fuel N (0.2 4%) are major controls on O3

4 O 3 in wildfires seen at MBO: Role of NO x 5 O 3 (in ppbv) >20 fire plumes at MBO in Even when O 3 / CO is low, O 3 may still be significant. Negative correlation between O 3 / CO and NO x / NO y shows that photochemical age is a primary determinant of O 3 production. Fig. from Baylon et al., 2014 ( increasing age)

5 MCE Explains Variability in Downwind Fire OA Downwind fire plumes (1-2 days) at MBO from Low MCE: more smoldering r = 0.93 High MCE: more flaming Scattering is a function of fine PM mass, fine PM mostly organic (~90%). Negative correlation between scattering (σ sp ) and MCE due to: 1) Greater aerosol emission at low MCE 2) Greater SOA formation at low MCE due to greater emissions of oxygenated VOCs Wigder et al., 2015

6 PM (and OA) Enhancement ( PM 1 / CO) vs. Age (a) Initial emissions (b) Near Source (c) Downwind Wigder et al., 2013 (Atm. Env.)

7 Outline Mt. Bachelor (MBO) Downwind Fire Observations Modeling the Near Source Chemistry of Smoke Plumes Improving the Representation of Near Source and Downwind Smoke Plume Chemistry in Air Quality Models 7

8 Modeling Near Source Chemistry With ASP ASP (Alvarado and Prinn, 2009) models the formation of O 3 and SOA in smoke plumes. Gas-phase chemistry o C 4 gases follow Leeds Master Chemical Mechanism v3.2 (Saunders et al., 2003). o Other organic gases follow RACM2 (Goliff et al., 2013). Inorganic aerosol thermodynamics OA thermodynamics using the Volatility Basis Set (VBS) (Robinson et al., 2007). Evolution of the aerosol size distribution and optical properties. ASP can be run as a box model, or as a subroutine within 3D models (Alvarado et al., 2009). 8

9 ASP slightly overestimates O 3 and PAN Williams Fire (Akagi et al., 2012) MCE = 0.93, NMOC/NO x = 20 mol C/mol N ΔO 3 /ΔCO ΔPAN/ΔCO 2 Smoke Age (hr) Smoke Age (hr) Fast, Medium, and Slow Dilution Rates Solid = In Plume, Dashed = Top of Plume, Dotted = Bottom of Plume Alvarado et al., ACPD,

10 Need slow OH reaction rate and/or fragmentation to explain low OA downwind Organic Aerosol (OA) Enhancement Ratios at hr k OH = cm 3 /s o HC8 in RACM2: 1.1x10-11 cm 3 /s k OH = cm 3 /s+ 50% RO 2 frag o Formation of Acetic Acid? Observations k OH = 0 cm 3 /s k OH = , x100 less vol k OH = , x10 less vol k OH = , x10 less vol k OH = , x10 less vol, 0.5 frag. k OH = , x10 less vol, 0.5 frag., HO x /NO x Chem. ΔOA/ΔCO 2 (g/g) Alvarado et al., ACPD,

11 Acetic acid formation consistent with formation by RO 2 fragmentation k OH = cm 3 /s k OH = cm 3 /s frag ΔCH 3 COOH/ΔCO ΔCH 3 COOH/ΔCO Smoke Age (hr) Smoke Age (hr) Alvarado et al., ACPD,

12 Outline Mt. Bachelor (MBO) Downwind Fire Observations Modeling the Near Source Chemistry of Smoke Plumes Improving the Representation of Near Source and Downwind Smoke Plume Chemistry in Air Quality Models 12

13 Conceptual Model of Smoke Chemistry (a) Initial Emissions (t = 0 10 min.) NMOC/NO x f(mce, Fuel N) 13

14 NMOC/NO x Data (e.g., Akagi et al., 2011) Models generally use fixed MCE and EFs for each biome (boreal forest, etc.), ignoring variability MCE hard to determine globally from satellite More data needed on fuel N content OMI studies of Mebust and Cohen, 2013, 2014 Many NMOCs in smoke are unidentified Progress is being made (e.g., PTR-ToF-MS study of Stockwell et al., 2015; 2D GC-MS study of Hatch et al., 2015) Speciation of NMOCs in model may be inappropriate for fires (C. Wiedynmyer of NCAR working on this) 14

15 Conceptual Model of Smoke Chemistry (b) Near Source (t = 10 min. 6 hr.) Major Controls: Dilution, NMOC/NO x, T, Rad NO x limited O 3 production NO x reacts to make ANs, PNs, HNO 3, NO 3(p) Organic aerosols (OA) o Evaporate due to dilution and T o Can grow due to oxidation of NMOCs Plume smaller than global model grid o Need sub grid scale parameterization 15

16 Using ASP to Build a Sub-grid Scale Parameterization for GEOS-Chem Followed approach used by Vinken et al. (2011) for ship plumes Initial emissions taken from Akagi et al. (2011) We used ASP to build look-up tables of OA/ CO, O 3 / CO, PAN/ CO, etc. versus smoke age Look-up table includes dependence on biome, temperature, solar zenith angle (SZA), and other fire and meteorological parameters 16

17 Example: O 3 Formation Savanna/Grasslands (MCE = 0.95, NMOC/NO x = 10) Boreal Forest (MCE = 0.88, NMOC/NO x = 100) ΔO 3 /ΔCO (mol/mol) ΔO 3 /ΔCO (mol/mol) Smoke Age (hr) Smoke Age (hr) 17

18 Example: NO y Partitioning Savanna/Grasslands (MCE = 0.95, NMOC/NO x = 10) Boreal Forest (MCE = 0.88, NMOC/NO x = 100) (% NO y ) NO x (% NO y ) PAN Smoke Age (hr) Smoke Age (hr) 18

19 Conceptual Model of Smoke Chemistry (c) Downwind (t = 6 hr. 10 days) Major Controls: Transport, Dilution, NMOC/NO x, T, Radiation Potential for more O 3 production Remaining NO x PAN decomposition Mixing with other NO x sources OA continue to oxidize, grow, and/or evaporate 19

20 Tests of Parameterization in GEOS-Chem August 31 st, 2013 (SEAC 4 RS) O 3 PAN Standard QFED emissions plus NO y emitted as 40% NO, 40% PAN, and 20% HNO 3 above 30 N (Alvarado et al., 2010) ASP QFED emissions plus ASP parameterization (Lonsdale et al., in prep) 20

21 Summary Clear evidence from MBO and other studies that many, but not all, plumes make significant O 3 and SOA. MCE, fuel N, age, dilution, T, radiation, and transport are all important controls on O 3 and SOA formation. Air quality models need improved treatments of: Initial NMOC and NO x emissions Near source and downwind chemistry. ASP model, with reasonable SVOC chemistry, can simulate OA, O 3, OH, and NO x observations from the Williams Fire. Parameterizations could improve model representation of near source chemistry. 21

22 Acknowledgements ASP modeling work funded by NSF grant AGS Sampling of the Williams fire was funded by NSF grants ATM and ATM , and by SERDP projects SI-1648 and SI Improvements to ASP aerosol optical properties funded by NASA ACMAP grant NNX11AN72G. 22

23 Conceptual Model of Smoke Chemistry (b) Near Source (t = 10 min. 6 hr.) (c) Downwind (t = 6 hr. 10 days) (a) Initial Emissions (t = 0 10 min.) 23