Improving air quality analysis through closer integration of observations & models Greg Carmichael, Scott Spak Air quality management contacts: Joe Hoch, Wisconsin DNR Matthew Johnson, Iowa DNR Donna Kenski, LADCO

1.Model skill for fine particle concentrations during wintertime episodes: how to improve? 2.AQ-WX feedbacks for both AQ & WX 3.Uncertainties & error attribution in derived policy metrics: met? ICs/BCs? model? 4.Value in assimilating remote sensing for AQ atmospheric composition land surface meteorology individual vs. synergistic effects? Motivations Applied science for AQ decision support Forecasting for AQ decision support 4.Daily resource for AQ managers 5.Public benchmark data archive to inform planning & forecasters 6.Integrated forecasting— support products for transportation, energy production, hazards 7.Demonstrated need for urban- scale nowcasting tools to support local public health response to urban air quality events

1.W126 monthly index, June-July km CONUS western US 12 km 2.Estimate background contributions Compare contributions from NA biomass burning emissions by turning off FINN & RAQMS BB emissions Compare contributions from transported background (model boundary) by perturbing RAQMS and GEOS-Chem BCs for O 3 & precursors: CO, NO, NO 2, NO 3, HNO 3, HNO 4, PAN, N 2 O 5 Evaluate W16 metric suitability and uncertainties for policy applications Assessing the Ozone Secondary Standard with the STEM adjoint & TES assimilation Huang et al. (2012). Impacts of transported background pollutants on summertime Western US air quality: model evaluation, sensitivity analysis and data assimilation, ACPD, 12, 1–73.

Model horizontal/vertical resolution & BC uncertainties strongly affect W126 value...

5 … and affect W126 adjoint sensitivities almost as strongly as local precursors

extrapolated from sensitivities to 75% perturbations in BCs Transported Background O 3 in the adjoint of a regional CTM Huang et al. (2012). Impacts of transported background pollutants on summertime Western US air quality: model evaluation, sensitivity analysis and data assimilation, ACPD, 12, 1–73.

LADCO Winter Nitrate Study: Phase II 7 How does interactive snow affect winter PM2.5 episodes? Most effective local & regional emissions control? NH3 During episodes, meteorology sensitivity >= emissions sensitivity Urban impacts of local (100 km, 250 km) NOx & NH 3 controls >60% of regional total CSAPR enhances effectiveness of regional NOx controls, nearly neutral to NH 3

air quality -PM2.5 & ozone -NAAQS exceedances -Background aerosol-climate effects carbon cycle renewable energy road conditions floods, agriculture Integrated forecast goals Toward 4DVAR in high resolution coupled Earth System modeling for prediction, process studies, climate, decision support, and policy applications:

Iowa City Landfill Fire acres burn, beginning 5/26 ~1 million shredded tires Uncontrolled tire fires (EPA, 1997) -40+ species of concern -35,000x more mutagenic than coal- fired power plants Immediate state & federal activity -Whole air samples, GC/MS (IA SHL) -Regional HYSPLIT dispersion (NOAA NWS) -MODIS visible (IA National Guard) -Fire containment & treatment (US EPA) Limited decision support response for air quality & public health

5/30 1 st AERMOD forecast 3DVAR IMAPP MODIS L2 DB 35 vertical levels in WRF-Chem 100 m x 100 m National Elevation Dataset

Interdisciplinary rapid response 3 intensive sampling platforms 11 Betsy Stone (Chemistry) PM2.5 mass and speciation 40+ organics Charles Stanier (CBE, IIHR) <1 Hz SO 2, CO, CO 2 Ultrafine Particle Counter (CPC) Scanning Mobility Particle Sizer ( µ m) Aerosol Particle Sizer ( µm) Weather station Tom Peters (Public Health) Grimm Optical Particle Counter ( µm) Portable black carbon monitor Tom Schnell (CoE Operator Performance) HUMVEE with power for all instruments

Plume chasing: 150+ µg/m 3 urban toxic PM 2.5 source 12 Landfill fire 0.8 km 1.8 km 2.7 km Sampling points during plume chase on June minute average concentrations of 157 µ g/m 3 PM at plume 0.8 km, 34 µg/m 3 PM 2.7 km.

13 APS PM (µg/m 3 ) Estimated PM 2.5 emissions rate: 10 ± 3 µg/m 2 /s ~5 g/s 5/31 WRF-Chem + AERMOD + obs -> Background PM 2.5 /CO/SO 2 + landfill emissions ~4 µg/m 3 per ppb SO2 APS PM (µg/m 3 )SO2 (ppb) Iowa City SO2

6/1 60hr weekend forecast to Johnson County Public Health using US EPA recommended metrics

16 APS PM (µg/m 3 ) Verification: Increment within 3 µg/m 3 AQS monitor 11.5 km east hit 77 µg/m 3

Learning from this event: on-demand decision support products 17 AQAST + Johnson County + Iowa DNR Guidelines & toolkit for state/local public health response to urban fires & toxic releases New decision support features in AQAST forecast AERMOD meteorology inputs web portal Rapid response capacity for the next year: urban AERMOD + WRF-Chem background Urban exposure & health modeling/monitoring

Recent synergistic highlights Santiago, Chile: daily operational WRF-Chem PM 10 /PM 2.5 forecast WRF-Chem aerosol-cloud assimilation MODIS cloud optical depth retrievals alter droplet concentration and effective radius AOD + COD constrain aerosols throughout scenes Improving parcel-level urban renewable energy estimates with NASA cloud retrievals 18 P. Saide et al. (2011). Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model, Atmospheric Environment, doi: /j.atmosenv P. Saide et al. (2012). Seeing aerosol through clouds: assimilating submicron aerosols from satellite cloud retrievals, PNAS, in press.

Year 2 Plans Aerosol RF in 72-hour operational forecast system Disaggregate AQ impacts from assimilation fields Publish maps & data download online Extendto custom AQ management products Evaluateand refine configuration ImplementAERMOD rapid response capability Supportyour tiger team activities