Comparison of photochemical

Transcription

1 Comparison of photochemical modeling for California by U.S. EPA and the California ARB James T. Kelly and Kirk R. Baker Office of Air Quality Planning & Standards, U.S. Environmental Protection Agency Chenxia Cai, Jeremy C. Avise, and Ajith Kaduwela Air Quality Planning and Science Division, California Air Resources Board (CARB) John B. Nowak 1 3, J. Andrew Neuman 1,2, Owen R. Cooper 1,2, Eric J. Williams 1,2, Brian Lerner 1,2, Barry Lefer 4, and Joost A. de Gouw 1,2 1 Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder 2 Chemical Sciences Division, National Oceanic and Atmospheric Administration 3 Now at Aerodyne 4 Earth and Atmospheric Sciences Department, University of Houston 1

2 Background Multiple areas of California do not attain federal standards for PM 2.5 and ozone CARB conducts modeling of these areas to support State Implementation Plans U.S. EPA conducts modeling of these areas to support national rules (e.g., Regulatory Impact Analyses) Air quality modeling for California is challenging; improved capabilities for SIPs and RIAs are desirable Here, we improve characterization of U.S. EPA and CARB modeling platforms by evaluating them against routine and field study measurements PM 2.5 Nonattainment O 3 Nonattainment 2

3 Today s Topics 1. Ammonium nitrate o Ammonia emissions o Nitrate at Riverside monitor in South Coast Air Basin (SoCAB) 2. Ozone o Impact of boundary conditions o Episode in eastern SoCAB o Response to weekday weekend NOx emission changes 3

4 Air Quality Modeling Category U.S. EPA CARB Period 4May 30 June May 30 June 2010 AQ model CMAQv5.0.2 CMAQv5.0.2 Resolution 4 km horizontal 34 vertical layers 4 km horizontal, 30 vertical layers Meteorology WRFv3.4, ACM2 PBL WRFv3.4, YSU PBL Gas chemistry CB05TU SAPRC07 Boundary conditions GEOS Chem MOZART Anthro. emissions NEI08v2 CARB 2012 Biogenic emissions BEISv3.14 MEGANv2.04 w/ ARB updates 4

5 Allocation of NH 3 Emissions EPA * and CARB emission totals are similar (left) but spatial allocations differ in SJV (above left) Peak mixing ratios from aircraft (above right) support CARB s point source allocation for large SJV sources ** *EPA NH 3 emissions based on NEI08v2 **DISCOVER AQ SJV 2013 dataset (not shown) also suggests a pointsource character for large SJV NH 3 emissions sources 5

6 Nitrate in Riverside 24 hr Average NO 3 Ammonium nitrate is often elevated in Riverside Dairy Riverside EPA and CARB nitrate predictions are correlated w/ obs but too low in Riverside Ammonia emissions from upwind dairy facilities are important for nitrate formation in Riverside Ports Relative magnitude of NH 3 mixing ratio is shown along P3 track * *Adapted from Nowak et al., GRL,

7 NH 3 and HNO 3 for P3 Flights NH 3, Modeled Observed HNO 3, Modeled Observed NH 3 is underpredicted and HNO 3 is overpredicted downwind of Chino dairies near Riverside (red diamond) 7

8 Western Boundary Ozone BC s for EPA 36 km outer domain Consistent with isentropes and northwesterlies Differences in BC s generally have small impact on overall statistics at surface monitors Figures on right are based on 4 km EPA CMAQ simulations with GEOS Chem and MOZART BC s 8

9 Ozonesondes Median ± Interquartile Range Point Reyes Point Sur Joshua Tree Median is underpredicted < ~6 km and overpredicted 6 10 km (upper left) Capture some day to day variability (left) Aloft O 3 is low during June stagnation episode (left) 9

10 Fontana SB Rubidoux Ozone in Eastern SoCAB *EPA modeling in this slide is based on the SAPRC07 mechanism and MOZART BC s. Note that SAPRC07 predicts higher O3 here than CB05 in part due to the faster OH+NO 2 in CB05 (JPL, 2003) than S07 (Mollner et al., 2010) Episode peaks are underpredicted more by EPA than CARB (above) EPA and CARB inventories have similar VOC to NOx ratios (left) Differences in meteorology may be the cause of differences in ozone predictions 10

11 Weekend to Weekday * Ratios Average MDA8 Ozone Ratios Fractional change in NOx emissions (weekend/weekday) is similar for EPA and CARB (above left) Models capture enhanced weekend ozone in urban core (red colors, above) Gradient in weekend effect from urban to downwind areas is weaker for CARB than EPA simulation *Weekend: Saturday and Sunday; weekday: Tuesday and Wednesday **Based on cells in top 20% of weekday NOx emissions; a few CARB outliers clipped 11

12 Preliminary Conclusions Despite differences in inputs, U.S. EPA and CARB simulations often have similar characteristics o Good correlations with observations; underpredict peak O 3 and NO 3 during SoCAB episode 2011 EPA National Modeling Improvements in bottom up NH 3 emissions inventories and spatial allocations could improve nitrate predictions in SoCAB Differences in EPA and CARB ozone predictions may be driven by differences in meteorology, since we have controlled for other factors to some degree o Ozone is not underpredicted at eastern SoCAB sites in 2011 EPA national modeling (upper right) 12

13 Future Work Compare EPA and CARB modeling platforms for a wintertime PM 2.5 episode in San Joaquin Valley to complement the springtime CalNex comparison in SoCAB 2013 DISCOVER AQ field campaign in SJV is an ideal episode to compare EPA and CARB wintertime PM 2.5 modeling * See Baker and Kelly poster for more details on EPA s preliminary DISCOVER AQ modeling 13