Preliminary ResultsCMAQ and CMAQ-AIM with SAPRC99 Gail Tonnesen, Chao-Jung Chien, Bo Wang, UC Riverside Max Zhang, Tony Wexler, UC Davis Ralph Morris, Steven Lau, Bongyoung KooENVIRON International Corporation T.W. Tesche, Dennis McNally and Greg StellaAlpine Geophysics RPO Meeting, Denver, CO, May 25, 2004
CMAQ-AIM • Aerosol Inorganic Module (AIM) Clegg et al. • CMAQ-AIM uses simplified AIM thermodynamics to reduce computation cost. • Sectional aerosol algorithm (9 sections). • Uses SAPRC99 gas chemistry.
SOA in CMAQ-AIM • Simplified SOA speciation: uses 1 anthropogenic and 1 biogenic SOA. • Dynamic gas-particle partitioning:
NaCl Thermodynamics • Forms coarse mass NaNO3 • Should give reduced fine NO3 in CMAQ-AIM • CMAQ includes Sea salt species but chemistry is not yet implemented in ISORROPIA. • CMAQ-AIM includes sea salt.
Sea Salt Emissions • Used EPA code for sea salt emissions: • Only represented open ocean emissions. • Added new code to represent surf zone emissions. • Simple approximations of surf zone area: • 100 m width • If cell is between 20 and 80% water use cell full length as coast.
CMAQ-AIM Evaluation • CMAQ-AIM is still under development. • Initial Comparison of CMAQ-AIM to CMAQ was presented to VISTAS February 2004. • More recent results still being analyzed
SO4 (IMPROVE); CMAQ-AIM vs. CMAQ US (FB, -14% vs. -2%) Vistas States (FB, -30% vs.-15%)
CMAQ-AIM Summary • CMAQ-AIM tends to have lower predictions larger negative bias compared to CMAQ • Should we look at the size bins that are being included in PM2.5? • Does CMAQ-AIM have some SO4 and NO3 mass in larger size bins? • Still need to look at sea salt for recent simulation.
Comparison and Diagnostic Evaluation of Air Quality Models for Particulate Matter: CAMx, CMAQ, CMAQ-MADRID Zion Wang, Chao-Jung Chien and Gail Tonnesen University of California, Riverside Eladio M. Knipping and Naresh Kumar EPRI
Modeling Episode • Southern Oxidant Study (SOS) • June 29 to July 10, 1999 • Meteorology processed from MM5 Simulations • MCIP2.2: CMAQ, CMAQ-MADRID • mm5camx: CAMx • Emissions files courtesy of TVA • Simulation • 32-km horizontal resolution without nesting • Sensitivity Simulation • Increase ammonia emissions by 50% across-the-board
Summary of EPRI Study No single model is the “performance winner”. • All models over-estimated aerosol sulfate concentrations. CAMx showed a higher tendency to over-estimate aerosol sulfate concentration across a wide region of the domain compared to CMAQ and CMAQ-MADRID. • CMAQ under-estimated aerosol nitrate concentrations by a factor of ~2.5, whereas CMAQ-MADRID and CAMx over-estimated nitrate by a factor of ~3. However, CAMx exhibited a higher propensity to over-estimate nitrate in the southeast than CMAQ-MADRID. • All models under-estimated organic mass. However, CMAQ predicted the least organic mass of all three model • The models responded differently to changes in ammonia emissions.