Emerging issues in air quality Daniel J. Jacob with Lin Zhang, Raluca Ellis, Fabien Paulot, Eloise Marais, Qiaoqiao Wang, Kevin Wecht, Alex Turner, Helen Amos, Hannah Horowitz and Anne Perring, Joshua Schwartz, David Fahey (NOAA), Cui Ge, Jun Wang (U. Nebraska), David Streets (Argonne) Support from BP, NASA, NSF

4 th -highest annual maximum of daily 8-h average ozone, Current standard: 75 ppb Proposed standard: ppb

Long-term surface ozone trend Trend in 95 th percentile, June-August Cooper et al. [2012] Decrease in eastern US driven by NO x emission controls; Increase or flat in Intermountain West

4 th -highest annual maximum for daily 8-h average ozone, Intermountain West: The next ozone frontier! High elevation, arid terrain → high ozone background Current standard: 75 ppb Proposed standard: ppb

High background and stratospheric intrusions in Intermountain West Most surface ozone in Intermountain West originates from outside N America Highest ozone events (>80 ppb) due to stratospheric filaments, cannot be reproduced in models (stretched-flow numerical diffusion) Have to be careful with definition of stratospheric influence 2007 Zhang et al., in prep. STST O 3 produced in stratosphere Two definitions of stratospheric influence on tropospheric ozone: O 3 transported from stratosphere tropopause Ozone at Gothic, Colorado (2,900m) Observed GEOS-Chem N Am background Strat (transported) Strat (produced)

Wildfire plumes alone do not drive high-ozone events No evidence of high-ozone events from fire plumes unless mixed with pollution Models generate excessive ozone because they don’t account for emissions of highly reactive VOCs that lock up NO x as PAN in the plume – a difficult problem! Fires can still contribute to background ozone through PAN decomposition Glacier NP, 2007: model has high O 3 in fire plumes, observations show none Organic aerosol (OC) correlates with western US fires but not ozone OC (IMPROVE) Ozone (CASTNet) Zhang et al., in prep. Observed GEOS-Chem  wildfires

N deposition at US national parks: critical load exceedances Ellis et al. [2013] More deposition is expected to originate from ammonia in future Critical loads are 3-5 kg N ha -1 a -1 depending on ecosystem NO x NH 3 Present and future (RCP) US emissions Future exceedances driven by ammonia emissions Ellis et al. [submitted] RCP2.6

Optimizing NH 3 emissions by adjoint inversion of NH 4 + wet deposition flux data NADP data (circles) and GEOS-Chem model after adjoint inversion April: fertilizer July: livestock kgN ha -1 month -1 Error correlation between NH 4 + wet deposition flux (F) and precipitation (P) obtained by GEOS-Chem simulations with GEOS-4 vs. GEOS-5 meteorology: P GEOS5 /P GEOS4 F GEOS5 /F GEOS4 0.6 power dependence Paulot et al. [submitted]

Optimized ammonia emissions … and new MASAGE bottom-up ammonia emission inventory US EU E Asia x 0.5 crops livestock other anthro natural (China) Paulot et al. [submitted]

N deposition from agriculture is a global pollution problem Annual mean agricultural ammonia emissions from MASAGE ( ) 63% are from countries outside the US, European Union, and China Paulot et al. [submitted]

Contribution of US food export to PM (NH 4 NO 3 ) air pollution MASAGE NH 3 emissions from food export wheat  PM due to food export (GEOS-Chem) annual Economic implications by state ($ per capita): Paulot et al., in prep beef corn

Next frontier for air pollution: Nigeria OMI formaldehyde MISR SCIA aerosol (AOD) NO 2 HCHO glyoxal methane Population: 270 million (+2.6% a -1 ) GDP: $273 billion (+7% a -1 ) – oil! Most natural gas is flared >80% of domestic energy from biofuel, waste Lagos Port Harcourt An unusual mix of very high VOCs, low NO x – What will happen as infrastructure develops? Marais et al., in prep. gas flaring! molecules cm -2

Multimodel intercomparison and comparison to observations Multimodel intercomparisons and comparisons to observations Koch et al. [2009], Schwarz et al. [2010] ARCTAS (Arctic spring) BC, ng kg -1 TC4 (Costa Rica, summer) Observed Models Models differ by order of magnitude between themselves and with observations Large overestimates of observations over oceans, upper troposphere Discrepancy must be driven by model errors in scavenging Large model errors for black carbon (BC) aerosol in remote air Pressure, hPa obs models 60-80N obs models 20S-20N Pressure, hPa HIPPO over Pacific (Jan) BC, ng kg -1 Ensemble of AeroCom models

Global BC simulation in GEOS-Chem Source (2009): 4.9 Tg a -1 fuel Tg a -1 open fires Lifetime: 4.2 days NMB= -27% NMB= -12% NMB= 6.6% Observations (circles) and model (background) surface networks AERONET BC AAOD NMB= -32% Aircraft profiles in continental/outflow regions HIPPO (US) Arctic (ARCTAS) Asian outflow (A-FORCR) US (HIPPO) observed model Successful simulation in source regions and outflow Wang et al., in prep

HIPPO BC curtains across the Central Pacific, Minima in deep tropics Model doesn’t capture low tail, is also too high at N mid-latitudes; median bias is factor of 2, mean column bias is +48% Wang et al., in prep Observations by Perring et al. (in prep.) Observed Model PDF PDF, (mg m -3 STP) -1

BC top-of-atmosphere direct radiative forcing (DRF) Emission Tg C a -1 Global load (mg m -2 ) [% above 5 km] BC AAOD x100 Forcing efficiency (W m -2 /AAOD) Direct radiative forcing (W m -2 ) This work [8.7%] ( ) AeroCom [2006] 7.8 ± ± 0.08 [21±11%] 0.22± ± ± 0.07 Chung et al. [2012] Bond et al. [2013] In our work, BC above 5 km contributes 30% of global DRF and BC over the oceans contributes 24%; these contributions would be higher in other models with less efficient scavenging. We find that BC radiative forcing is much less than previously estimated; need to better understand BC in free/remote troposphere! Wang et al., in prep

Constraints on US methane emissions from SCIAMACHY data ppb SCIA CH 4 column mixing ratio, Jul-Aug 2004 Adjoint inversion with EDGAR v4.2 (anthropogenic), Kaplan (wetlands) as priors Focus on INTEX-A mission period to validate SCIAMACHY data and inversion Adjoint inversion scaling factors Wecht et al. [in prep] Total US anthropogenic emissions (Tg a -1 ) EDGAR v EPA 28.3 This work 32.7

Methane from GOSAT: preliminary adjoint inversion GOSAT data for CalNex period (May-Jul 10) Scaling factors to EDGAR inventory GOSAT data show consistency with SCIAMACHY for constraining livestock and wetland sources, but also discrepancies The data are sparse; now applying a Gaussian Mixture Model to optimally reduce the state vector for the inversion Turner et al. [in progress] Can we monitor from space the evolving source from oil & gas?

Biogeochemical cycle of mercury Hg(0) Hg(II) particulate Hg burial SEDIMENTS uplift volcanoes erosion oxidation Hg(0)Hg(II) reduction biological uptake ANTHROPOGENIC PERTURBATION: fuel combustion mining ATMOSPHERE OCEAN/SOIL VOLATILE WATER-SOLUBLE (months)lifetime ~6 months

History of global anthropogenic Hg emissions Large past (legacy) contribution from N. American and European emissions; Asian dominance is a recent phenomenon Streets et al., 2011

Global source contributions to Hg in present-day surface ocean Human activity has increased 7x the Hg content of the surface ocean Half of this human influence is from pre-1950 emissions N America, Europe and Asia share similar responsibilities for anthropogenic Hg in present-day surface ocean Amos et al., in press Europe Asia N America S America former USSR ROW pre-1850 natural emissions from biogeochemical box model constrained with GEOS-Chem fluxes

Disposal of Hg in commercial products: a missing component of the Hg biogeochemical cycle? Global production of commercial Hg peaked in 1970 Horowitz et al., in prep Commercial Hg enters environment upon use or disposal; much larger source than inadvertent emission Could explain observed atmospheric decrease of Hg(0) over past two decades Environmental release from commercial products dwarfs current emission estimates

TEMPO geostationary UV/Vis satellite instrument selected in November 2012 for 2018/2019 launch PI: Kelly Chance, Harvard-Smithsonian Monitoring of tropospheric ozone (2 levels), aerosols, NO 2, SO 2, formaldehyde, glyoxal with 1-hour temporal resolution, 4-km spatial resoution To be part of a geostationary constellation with other sensors observing Europe and East Asia TEMPO Sentinel-4 GEMS Next frontier in satellite observations of atmospheric composition!