- Количество слайдов: 28
Simulating diurnal changes of speciated particulate matter in Atlanta, Georgia using CMAQ Yongtao Hu, Jaemeen Baek, Bo Yan, Rodney Weber, Sangil Lee, Evan Cobb, Amy Sullivan, Armistead G. Russell School of Civil and Environmental Engineering and School of Earth and Atmospheric Sciences, Georgia Institute of Technology CMAS conference, October 18 th, 2006 Acknowledgements: Eric S. Edgerton and John Jansen ARA and Southern Company
Speciated particulate matter monitored at two sites in Georgia Tech's campus, 500 m away from each other
Measurements at neighboring sites HYW and ROF • Frequency: twice per day of 12 -hr average compositions of PM 2. 5 for daytime (10 am~10 pm) and nighttime (10 pm~10 am). • Items: ions, EC/OC, organic compounds and metals. • Periods: Jun. 15~18, 2006 and Jan. 19~26, 2006. • Findings: Compare two sites: ROF is cleaner; SO 4 and NH 4: no significant difference; NO 3: ROF is higher, but both very low; EC and OC: HYW is significantly higher. Compare day and night: Higher percentage of OC at night; Higher percentage of SO 4 during day.
Other PM 2. 5 composition monitors in Atlanta Met - 56 km 1. 3 -km Grid - 56 km -
Sampling frequency • SEARCH stations: JST and YRK, hourly composition of PM 2. 5, as well as daily 24 -hr averages • ASACA stations: FTM, TUC, SDK, YGP, daily 24 -hr average composition of PM 2. 5 • STN site: South De Kalb (same location as SDK), every third day 24 -hr average composition of PM 2. 5
Questions: Can CMAQ capture the observed gradient of the EC/OC concentration at the two closely neighboring sites? Can CMAQ capture the observed diurnal changes of PM 2. 5 and its components?
Objectives of this work • Simulating PM 2. 5 speciation using CMAQ at very fine scale. • Characterize emissions from freeway. • Compare fine scale CMAQ results to observations using detailed speciation of organics and metals (just have EC/OC and ions for now). Next to freeway, nearby (500 m), 2 km away, within the region. • Mutual calibration with receptor modeling results. • Reconcile differences: Improve emission characterization, emissions distributions, dispersion, etc.
CMAQ v 4. 5 simulation • Four nesting domains down to 1. 3 -km resolution. • Thirteen vertical layers, first layer ~18 meters. • Simulating summer episode currently: June 12 -20, 2005. • SAPRC 99 mechanism plus aero 4 module. • MM 5 and SMOKE provide meteorology and emission rate fields. • OSU land surface model plus 4 DDA (only for 36 -km and 12 -km grids) used in MM 5. • VISTAS 2002 emissions inventory projected to 2005, CEM data used for EGU sources.
Brute force sensitivity simulations 20 sensitivity runs sensitivity fields = air quality fields basecase - air quality fields reduced case
Modeling Domains 1. 3 -km 4 -km 12 -km 36 -km
Basecase 1. 3 -km Grid Emissions NOx PEC CO POA
Simulated Spatial Distributions on 1. 3 -km Grid (basecase) O 3 SO 4 NO 3 OC NH 4 EC
First Concern: Is 1. 3 -km grid performance worse than coarse grid?
MM 5 Performance: 1. 3 -km grid vs. other resolutions Compare with TDL hourly surface observations
CMAQ Performance: 1. 3 -km grid vs. other resolution Compare with Network measurements from: AIRNOW, STN, CASTNet (O 3 only), IMPROVE, SEARCH and ASACA
Further Concern: Is PM 2. 5 performance becoming worse when compared to measurements in higher temporal resolution?
1. 3 -km grid PM 2. 5 performance Compare with 24 -, 12 - and 1 -hr measurements, respectively
Limited EC/OC gradient was captured between HYW and ROF HIGHWAY ROOF
EC Sensitivity results show a higher contribution from traffic emissions at HIWAY HIGHWAY Non-road EC Mobile EC ROOF Non-road EC Mobile EC
Diurnal Changes: captured OK for SO 4, NH 4 and EC, not OK for OC Jefferson Street (urban) Yorkville (rural)
OC performance: diurnal change Jefferson Street (urban) Yorkville (rural)
OC Sensitivity: does it make sense? Jefferson Street (urban) OAVOC OAPOA NPOA MPOA FPOA DPOA BVOC Yorkville (rural) OAVOC OAPOA NPOA MNOX FPOA DPOA BVOC
Estimate Secondary OC from OC measurements ROOF When EC was well reproduced Assume Pri OCobs = Pri OCsim, then, we have SOAobs = OCobs - Pri. OCsim Yorkville Secondary OC was not captured by CMAQ, both mechanism and precursor emissions need improvements.
Summary • Performance of 1. 3 -km grid is as good as other resolutions. This is encouraging. • Limited EC/OC gradient was captured at neighboring sites. Link-base VMT is necessary to allocate the mobile emissions more accurately. • Utilize modeled primary OC to split SOA from observed OC. With uncertainty. • OC diurnal change was not captured. SOA prediction needs to be improved. Problems are from both mechanism and precursor emissions.
4 -km grid PM 2. 5 performance Compare with 24 -, 12 - and 1 -hr measurements, respectively
SO 4 performance