US aerosols: observation from space, interactions with climate Daniel J. Jacob and funding from NASA, EPRI, EPA with Easan E. Drury, Loretta J. Mickley, Eric M. Leibensperger, Amos Tai

IMPORTANCE OF ATMOSPHERIC AEROSOLS Public health Visibility Ocean fertilization Chemistry Climate forcing Cloud formation

number area volume AEROSOL CHARACTERISTICS Typical size distribution (Seinfeld and Pandis, 1998) Chemical composition of PM 2.5 (NARSTO, 2004) sulfate (coal combustion) nitrate (fossil fuel combustion) ammonium (agriculture) black carbon (combustion) organic carbon (combustion, vegetation) soil other PM 2.5 (EPA std.)

SATELLITE OBSERVATIONS OF TROPOSPHERIC COMPOSITION: The NASA “A-Train” Satellites Surface sites Models aircraft, ships, sondes, lidars a revolution over the past decade Integrated observing system Principal tropospheric species measured from space: Ozone, NO 2, formaldehyde, BrO, glyoxal CO, CO 2, methane Aerosols, SO 2

HOW TO OBSERVE AEROSOLS FROM SPACE? EARTH Solar occultation (SAGE, POAM…) Pros: high S/N, vertical profiling Cons: sparse sampling, cloud interference, low horizontal resolution Active system (CALIPSO…) Pro: vertical profiling Con: sparse sampling, low S/N Pro: horiz. resolution Con: daytime only, no vertical resolution Solar back-scatter (MODIS, MISR…) laser pulse Surface

Aerosol observation from space by solar backscatter Pollution off U.S. east coastDust off West Africa California fire plumes Relatively easy to do qualitatively for thick plumes over ocean… I   I   I (  )exp[-AOD] …but difficult quantitatively! Fundamental quantity is aerosol optical depth (AOD) aerosol scattering, absorption Measured top-of-atmosphere reflectance = f (AOD, aerosol properties, surface reflectance, air scattering, gas absorption, Sun-satellite geometry)

Aerosol optical depths (AODs) measured from space Jan 2001 – Oct 2002 operational data MODIS (c004) return time 2x/day; nadir view known positive bias over land MISR 9-day return time; multi-angle view better but much sparser van Donkelaar et al. [2006] 550 nm AODs

MODIS AEROSOL RETRIEVAL OVER LAND SURFACE 0.47  m 0.65  m 2.13  m Operational retrieval:  Use top-of-atmosphere (TOA) reflectance at 2.13  m (transparent atmosphere) to derive surface reflectance  Assume fixed 0.47/2.13 and 0.65/2.13 surface reflectance ratios to derive atmospheric reflectances at 0.47 and 0.65  m by subtraction  Assume generic aerosol optical properties to convert atmospheric reflectance to AOD Our improved retrieval:  Derive local values of 0.47/2.13 and 0.65/2.13 surface reflectance ratios from statistics of low-aerosol scenes  Use local aerosol column information from the GEOS-Chem chemical transport model to convert atmospheric reflectance to AOD TOA reflectance Drury et al. (JGR in press)

GEOS-Chem CHEMICAL TRANSPORT MODEL (geos-chem.org) Global model of atmospheric composition driven by NASA/GEOS assimilated meteorological data with 0.5 o x0.625 o (~50 km) resolution Simulates coupled oxidant-aerosol chemistry for sulfate-nitrate ammonium organic aerosol black carbon aerosol dust (4 size classes) sea salt (2 size classes) on 2 o x2.5 o grid Size distributions and optical properties for different aerosol types are specified

TESTING THE MODIS AEROSOL RETRIEVAL USING ICARTT AIRCRAFT DATA OVER US (Jul-Aug 2004) EASTERN U.S. EPA AQS/IMPROVE surface networks: mass concentrations NASA AERONET surface network: AODs NASA, NOAA, DOE aircraft: speciated mass concentrations, microphysical & optical properties MODIS satellite instrument: TOA reflectance GEOS-Chem model evaluate MODIS local surface reflectance and ratio synthetic TOA reflectance = f(AOD,…) fit AODs Drury et al. [JGR in press] NASA DC-8

ORGANIC AEROSOL IN ICARTT Standard reversible SOA (Pankow/Seinfeld): Dicarbonyl SOA (Liggio/Fu): Water-soluble organic carbon (WSOC) measured on NOAA P-3 IMPROVE measurements of organic carbon Fu et al. (AE, 2009) Two mechanisms for formation of secondary organic aerosol (SOA):

AEROSOL OPTICAL PROPERTIES IN ICARTT Single-scattering albedo = fraction of aerosol extinction due to scattering AERONET standard model assumption (GADs) improved fit (this work) Drury et al., JGR in press

AEOSOL OPTICAL DEPTHS (0.47  m), JUL-AUG 2004 Drury et al., JGR in press c005 is current MODIS operational data; statistics are relative to AERONET data in circles Beyond improving on the operational products, our MODIS retrieval enables quantitative comparison to model results (consistent aerosol optical properties); indicates model underestimate in Southeast US, likely due to organic aerosol bias=+2% r = 0.84 bias=-21% r = 0.82 bias=-15% r = 0.87

Can we use AODs measured from space as proxy for PM 2.5 ? MODIS PM 2.5 (this work) EPA AQS surface network data Infer PM 2.5 from AOD by MODIS captures general observed patterns in PM 2.5 but is 50% higher than observed. Could reflect Clear-sky bias Time-of-day bias Model error in vertical aerosol distribution Drury et al., JGR in press

RADIATIVE FORCING OF CLIMATE BY AEROSOLS But this aerosol radiative forcing is very inhomogeneous: what are the regional climate consequences? Anthropogenic aerosols may have offset more than half of global greenhouse warming from 1750 to present IPCC (2007) Leibensperger et al., in prep. Aerosol direct radiative forcing

CLIMATE IMPLICATIONS OF US AIR QUALITY POLICY today US sulfur emissions are decreasing rapidly: what are the regional climate impacts? Radiative forcing of US anthropogenic aerosols is small globally but important regionally Leibensperger et al., in prep.

CALCULATING THE CLIMATE RESPONSE FROM SHUTTING DOWN U.S. AEROSOL Mickley et al. (AE, submitted) Consider two scenarios: Control: aerosol optical depths fixed at 1990s levels. Sensitivity: U.S. aerosol optical depths set to zero (radiative forcing of about +2 W m -2 over US) Conduct ensemble of 3 simulations for each scenario. GISS GCM Use NASA/GISS general circulation model (GCM)

Removing aerosols over US causes o C annual mean warming in the East warming due to greenhouse gases Additional warming due to zeroing of aerosols over the US. Temperature ( o C) No-US-aerosols case Control, with US aerosols Mickley et al. [AE, submitted] Additional effects include increased summer heatwaves (1-2 o C warming) and increased precipitation in the East

EFFECT OF CLIMATE CHANGE ON SURFACE AIR QUALITY Ozone PM (aerosol) Stagnation Temperature Mixing depth Precipitation Cloud cover Relative humidity Expected effect of 21 st century climate change = = ? ? = ? ? Jacob and Winner, AE 2009 ?

EFFECT OF FUTURE CLIMATE CHANGE ON US AIR QUALITY Northeast Midwest California Texas Southeast change of 8-h daily max ozone in summer, keeping anthropogenic emissions constant ppb Models show consistent increase of ozone, mainly driven by temperature Results from six coupled GCM-CTM simulations Weaver et al. [BAMS, 2010] …but model results for aerosols show no such consistency, including in sign. How can we progress?

OBSERVED AEROSOL CORRELATION WITH METEOROLOGICAL VARIABLES Multilinear regression model fit to deseasonalized EPA/AQS data for PM2.5 (total and speciated) R 2 fit mostly precipitation mostly temperature and stagnation Tai et al. [AE, submitted]

PM 2.5 CORRELATION WITH METEOROLOGICAL VARIABLES Tai et al. [AE, submitted]

TEMPERATURE COEFFICIENTS FOR SPECIATED PM 2.5 Tai et al. [AE, submitted]

IMPORTANCE OF MID-LATITUDES CYCLONES IN AIR POLLUTION METEOROLOGY Clean air sweeps behind cold front Cold fronts from mid-latitude cyclones are the principal ventilation process for U.S. Midwest/Northeast, western Europe, China GCMs show decrease + N shift of cyclones from 21 st -century climate change; already seen in climatological data

CORRELATIONS AND TRENDS OF POLLUTION EPISODES AND CYCLONES IN NORTHEAST U.S. # pollution episode days (O 3 >80 ppb) and # cyclones tracking across SE Canada in summer observations Cyclone track Strong correlation; cyclone frequency is predictor of pollution episode frequency decrease in cyclone frequency would imply a corresponding degradation of air quality if emissions had remained constant Expected # of > 80 ppb days in Northeast dropped from 30 in 1980 to 10 in 2006, but would have dropped to zero by 2001 in absence of cyclone trend! Leibensperger et al. [ACP2008] # cyclones # episodes

EFFECT OF INCREASED STAGNATION ON PM 2.5 Difference in PM 2.5 between stagnant days (wind < 8 m s -1, 500 hPa wind <13 m s -1, no precipitation) and non-stagnant days, data PM 2.5 is expected to be highly sensitive to Increasing stagnation in future climate Tai et al. [AE, submitted]