DYNAMO: DYnamic Inputs of Natural Conditions for Air Quality MOdels - PowerPoint PPT Presentation

DYNAMO: DYnamic Inputs of Natural Conditions for Air Quality MOdels AQAST Year 3 Tiger Team Daniel Cohan, Loretta Mickley, Richard McNider, Arastoo Pour Biazar, Bryan Duncan

Key Additional Participants in DYNAMO Air Quality Management partners: • EPA: Jesse Bash, Pat Dolwick, Chris Misenis – 2011 CMAQ CONUS simulation • Texas Commission on Environmental Quality: Mark Estes • California Air Resources Board: Jeremy Avise Students: Ben Lash (Rice), Erin Chavez Figueroa (Rice), and Lulu Shen (Harvard) Postdoc: Dr. Rui Zhang (Rice)

DYNAMO Objectives • Stratospheric ozone : Satellite-based daily varying columns, to replace weekly averages – Impacts on tropospheric photochemistry • Clouds & Radiation: GOES-based clouds for photolysis rates and photosynthetically active radiation (PAR) – Impacts on biogenic VOC, ozone, and PM • Soil NO : Implement & extend BDSNP scheme – Impacts on NO 2 columns, ozone, and PM • Provide data on EPA’s RSIG • Review paper : Satellite-based inputs of natural conditions for regulatory modeling

Daily stratospheric ozone columns Total ozone from OMI • Motivation: DU – Synoptic variability in stratospheric ozone (Hudson et al., 2003) – Models interpolate from weekly or monthly averages – Impact on tropospheric OMI-MLS ozone over Chicago, 2005 UV & photochemistry?? daily values • Satellite observations: – Large daily variability in ozone columns in winter and spring 30-day moving avg Images prepared by Lulu Shen and Loretta Mickley using data from Wargan et al., 2014

Impacts of daily varying stratospheric ozone columns on tropospheric oxidants GEOS-Chem simulation Daily variability: Summer over Chicago for 2005 Difference from 30-day moving average for: Strat ozone column • JO 3 photolysis • MDA8 ozone • OH • Conclusion: Little impact on peak summer ozone • Impacts in other seasons?? Image prepared by Lulu Shen and Loretta Mickley

Satellite-based clouds: Impact on PAR Pinker (UMD) Satellite PAR << WRF PAR for July 2007 Satellite PAR (Pinker UMD) WRF PAR Initial evaluation of UAH satellite PAR data for September 2013 showed (Satellite PAR < WRF PAR), but less difference and more +/- (See Rui Zhang (Rice) poster)

Satellite-based radiation better matches SURFRAD monitors Solar Insolation from: • Satellite (Pinker UMD) • SURFRAD observations • WRF simulation UMD satellite data far outperform WRF, correct over-prediction bias UAH satellite-based data slightly outperform WRF for Sept. 2013 (results from preliminary check before screening & refining data) OBS(W/m 2 ) SIM(W/m 2 ) R RMSE(W/m 2 ) NMB (%) NME(%) PAR(WRF) 90 120 0.90 74 36.8 47.8 PAR(UAH) 90 117 0.92 70 32.3 44.4

Impact of UAH satellite PAR on emissions (Rui Zhang et al. poster, for Sept. 2013 simulation) Base Emissions from MEGAN Satellite (UAH) minus WRF Isoprene Mono- terpenes

Improved Soil NO Emissions Scheme • Berkeley Dalhousie Soil NO Parameterization (BDSNP) – Introduced by Hudman et al. 2012; In GEOS-Chem • Ben Lash (Rice) implemented in CMAQ (inline biogenics) – Providing to EPA (J. Bash) for upcoming CMAQ release – Also shared with UMD and other interested parties • Base-level emissions factors for each land cover category based on Steinkamp and Lawrence 2011 • Fertilizer and N deposition add N to soil reservoir • Meteorology influences emissions – Soil moisture and T from land surface model, instead of rainfall and air T – Pulse of emissions when rain follows dry period

BDSNP >> Y&L for Soil NO Emissions (Change in NO emissions per cell for Aug. 2005) BDSNP ~ 2x Y&L soil NO. Also, very different spatial & temporal patterns and responses to meteorology -- Can’t just scale Y&L.

∆24 -hr ozone due to BDSNP vs. Y&L (shown for August 2005 CMAQ, BDSNP – Y&L)

Over-predictions of Lamsal NO 2 columns (shown for August 2005) Spatial pattern does not correspond to soil emissions, so other factors likely drive CMAQ over-prediction of satellite-observed NO 2 in this case. Needs further investigation.

Potential Extensions of BDSNP Soil NO • EPIC dynamic fertilizer to replace Potter et al. 2010 • More evaluations vs. ambient & satellite NO 2 • Offline version of BDSNP for direct creation of soil NO emissions using WRF or other meteorology data – Requires assumptions about N-deposition • Add soil emissions of HONO (Su et al. 2011) • Ultimate goal: More mechanistic model to simulate soil emissions of all N compounds (NO, NH 3 , HONO, N 2 O, etc.) – Could a mechanistic model simulate responses of these emissions to agricultural control strategies??

Preliminary Findings and Recommendations • Daily-varying stratospheric ozone columns – Finding: Little impact on summertime MDA8 ozone – Recommendation: Investigate impacts on winter & spring photochemistry • Satellite-based clouds, solar radiation, J-values & PAR – Finding: Satellites can correct WRF over-predictions of PAR • Need further refinement and evaluation of UAH data – Recommendation: Investigate joint influences of satellite-based clouds on BVOC emissions and photochemistry • Soil NO scheme – Finding: BDSNP much higher than Y&L, and with very different spatio-temporal patterns, for soil NO emissions – Recommendations: (1) Include in next CMAQ release; (2) More evaluation with observations; (3) Extend to EPIC dynamic fertilizer inputs, offline inventory creation, and multi-pollutant emissions