Global isoprene sources and chemistry constraints from atmospheric
Global isoprene sources and chemistry: constraints from atmospheric observations Daniel J. Jacob with Emily Fischer, Fabien Paulot, Lei Zhu, Eloïse Marais, Chris Miller and funding from NASA, HUCE
Volatile organic compounds (VOCs) in the atmosphere: carbon oxidation chain • sources of organic aerosol • sources/sinks of oxidants (ozone, OH) O 3 Increasing functionality & cleavage h OH + products NO 2 carbonyl NO VOC OH RO 2 organic peroxy radical h OH R’O 2 organic aerosol HO 2 ROOH OH, h products organic peroxide biosphere combustion industry deposition EARTH SURFACE
Volatile organic compounds (VOCs) in the atmosphere: effect on nitrogen cycle Reservoirs for long-range transport of NOx Long-range atmospheric transport CH 3 C(O)OO lightning NOx peroxyacetylnitrate (PAN) NOx RO 2 N fixation OH other organic nitrates hours combustion OH HNO 3 deposition EARTH SURFACE deposition
Why is isoprene such an important VOC? 1. Large emission: Global emission, Tg C a-1 600 400 200 ng c as s bu rn i ni Bi om ro po ge An th O th e rb io sp he re e op re n Is M et ha ne 0 2. Oxidation generates suite of volatile reactive products: OH Isoprene ~1 h multistep • Formaldehyde • Other carbonyls • Dicarbonyls • Peroxides • Epoxides • Isoprene nitrates
Contribution of isoprene to PAN from GEOS-Chem global 3 -D chemical transport model January July Anthropogenic Open fires Isoprene Other biogenic VOCs Emily Fischer, Harvard %
Sensitivity of nitrogen deposition to isoprene emission Sensitivity for Cayuhoga National Park (Ohio) computed with the GEOS-Chem adjoint of local NOx emission) Local isoprene emission suppresses N deposition, upwind emission increases it Fabien Paulot, Harvard
Estimating isoprene emissions: bottom-up and top-down approaches Atmospheric observations Isoprene Bottom-up estimate from plant model: EISOP = f(plant type, phenology, LAI, T, PAR, water stress, …) oxidation products Top-down estimate from Inversion of chemical transport model: EISOP = f(atmospheric concentrations, transport, chemistry) Ecosystem observations
Observing isoprene oxidation products from space: formaldehyde (HCHO) and glyoxal (CHOCHO) GOME (1995 -2001), SCIAMACHY (2002 -2012), OMI (2004 -), GOME-2 (2006 -) instruments l 1 Scattering by atmosphere and Earth surface l 2 HCHO CHOCHO HCHO or CHOCHO absorption spectrum l 1 l 2 • Spectral fitting yields “slant” columns of HCHO, CHOCHO along light path • Air mass factor from radiative transfer model converts slant to vertical columns Annual mean vertical columns from GOME-2, 2007 -2008 HCHO CHOCHO
Relating HCHO columns to VOC emission VOCi oxidation yield yi HCHO h (340 nm), OH k ~ 0. 5 h-1 Emission Ei displacement In absence of horizontal wind, mass balance for HCHO column HCHO: Local linear relationship between HCHO column and E but wind smears this relationship depending on VOC lifetime wrt HCHO production: HCHO Isoprene a-pinene methanol detection limit VOCsource 100 km Distance downwind HCHO is mainly sensitive to isoprene emission with smearing ~ 10 -100 km
Past use of HCHO vs. EISOP relationship over US to constrain isoprene emission with OMI data OMI HCHO (Jun-Aug 2006) GEOS-Chem local relationship between HCHO column and isoprene emission OMI-constrained isoprene emission Model slope (2400 s) agrees with INTEX-A vertical profiles (2300), PROPHET Michigan site (2100) Palmer et al. [2003, 2006}, Millet et al. [2006, 2008]
Temperature dominates variability of EISOP seen by OMI can’t pick up any other variable from multivariate correlations, case studies HCHO column, Correlation of monthly mean HCHO with air T Jun-Aug 2005 NE Texas, JJA 2005 -2008 Exponential fit MEGAN 2006 2007 285 290 295 300 K Daily data in Southeast US binned by air temperature turnover at 307 K 2008 1 5 10 15 1015 molecules cm-2 290 295 300 305 310 K Lei Zhu, Harvard
After 2009 it’s curtains for OMI …but GOME-2 provides consistent continuity GOME-2 HCHO, 2007 OMI GOME-2 vs. OMI correlation monthly data in SE US JJA 2007 -2008 June July slope = 0. 91 r 2 = 0. 82 August nadir pixel OMI GOME-2 time 13 x 24 km 2 13: 30 40 x 80 km 2 9: 30 Lei Zhu, Harvard
Using OMI HCHO to constrain isoprene emissions in Africa OMI annual mean HCHO slant columns 2005 -2009 • Observed HCHO distribution over Africa points to sources from (1) biosphere, (2) open fires, (3) oil and gas industry • Africa accounts for 20% of global biogenic isoprene emissions in MEGAN inventory…but based on little in situ data Marais et al. , in press MODIS leaf area index 1015 molecules cm-2 MODIS fire counts Aug-Sep Earth lights AATSR gas flares
Isolating biogenic HCHO in the OMI data • Exclude open fire (and dust) influence using MODIS fire counts, OMI absorbing aerosol optical depth • Exclude oil/gas industry influence using AATSR gas flare product HCHO slant column original data HCHO vertical column biogenic only air mass factor HCHO biogenic vertical column; 8 -day product with 1 ox 1 o resolution Marais et al. , in press 1015 molecules cm-2
Pathways for HCHO formation from isoprene oxidation standard GEOS-Chem mechanism MVK NO high-NOx OH low-NOx RO 2 firs Peeters t-ge ner atio n Isomerization C 1, 5 -shift h formaldehyde HO 2 OH MACR OH ROOH OH -IEPOX Paulot • high-NOx branch (RO 2+NO) yields fast HCHO as 1 st generation product • low-NOx branch (RO 2+HO 2 ) yields slower HCHO, depletes OH More recently proposed low-NOx pathways regenerate OH, produce HCHO: Epoxydiols [Paulot et al. , 2009] Isomerization [Peeters and Muller, 2010]
Time-dependent HCHO yield from isoprene oxidation DSMACC box model calculations aging/smearing Yield is sensitive to NOx , not so much to mechanism except at very low NOx Marais et al. , in press
Boundary layer NOx levels over Africa Annual NO 2 tropospheric columns, fire influences excluded Satellite observations Model % isoprene RO 2 reacting with NO (GEOS-Chem, July) boundary layer • Boundary layer NOx over Africa is typically 0. 1 -1 ppbv • Expect NOx dependence of HCHO yield, moderate smearing Marais et al. , in press
Testing HCHO-isoprene smearing with AMMA aircraft data Flight tracks (Jul-Aug 2006) and MODIS leaf area index OMI HCHO Latitudinal profiles below 1 km WIND • HCHO tracks isoprene with only ~50 km smearing • But NOx measured in AMMA was relatively high (mean 0. 3 ppb) Marais et al. , in press
OMI HCHO column Testing HCHO-isoprene smearing in longitudinal transect across Congo: 1015 molecules cm-2 high isoprene and low NOx WIND July Smearing produces“shadow” region 200 -300 km downwind of rainforest shadow Marais et al. , in press
Relationship between HCHO column and isoprene emission Model sensitivity S of HCHO column (Δ HCHO) to isoprene emission (ΔEISOP) as function of tropospheric NO 2 column ( NO 2) Standard Paulot • Use S = Δ HCHO / ΔEISOP for local OMI NO 2 to derive isoprene emission • Exclude “shadow” regions on basis of anomalously high S values Marais et al. , in press
Error analysis on inferring EISOP from satellite HCHO data Estimated errors (8 -day data, 1 o x 1 o resolution) 20% (spectral fitting) Slant HCHO column 20% (clouds, vertical distribution, albedo) Vertical HCHO column 15% (chemical mechanism) 25 -60% (smearing) 15% (NO 2 column) Isoprene emission • Total error: 40% (high-NOx ), 40 -90% (low-NOx ). Can be reduced by averaging • Smearing is dominant error component. Need to resolve transport! Marais et al. , in press
Comparison of OMI isoprene emissions to MEGAN Isoprene emission (12 -15 local time annual mean, 2006) MEGAN is too low for equatorial forest, too high for savanna Marais et al. , in press
2005 -2009 monthly variability of isoprene emission for evergreen broadleaf forest of central Africa EISOP , temperature AVHRR EISOP , LAI • Variability is small and weakly correlated to temperature and LAI • Need to address uncertainty in meteorological and LAI products! Eloïse Marais, Harvard
2005 -2009 monthly variability of isoprene emission in open deciduous broadleaf forest of s. Africa EISOP , temperature AVHRR Jan EISOP , LAI Jan • May-Sept dry season; LAI drops below 1 in Aug, driving EISOP down • Sept-Nov increase in LAI (greening) causes spike in EISOP • Wet season cloudiness causes T to decrease after Nov, driving EISOP down even though LAI continues to increase • Suggests saturation of EISOP when LAI exceeds 1. 5 Eloïse Marais, Harvard
Glyoxal from space as additional constraint on VOC sources GOME-2 • Operational data available from SCIAMACHY, GOME-2 • OMI retrieval in progress (Chris Miller, Harvard) GEOS-Chem • Glyoxal sources in GEOS-Chem: 55% isoprene, 24% acetylene, 7% aromatics, 8% fire emission, 2% monoterpenes • Glyoxal lifetime ~1 h (photolysis) Chris Miller, Harvard
Does glyoxal provide information complementary to HCHO? Glyoxal columns (Jun-Aug 2007) Glyoxal/HCHO column ratio GOME-2 GEOSChem GOME-2 shows variability in glyoxal/HCHO ratio that GEOS-Chem doesn’t capture Chris Miller, Harvard
Glyoxal production from isoprene Dibble isomerization first-generation Observed fast production with 2 -3% yield [Galloway 2011] – Dibble isomerization? Chris Miller, Harvard
Measured isoprene GEOS-Chem with EISOP /2 Tower data from CABINEX, northern Michigan (Jul-Aug 09) Glyoxal Observations by Frank Keutsch Pathways for glyoxal formation Dibble OH-aldehydes Dibble isomerization is dominant model pathway for glyoxal formation Chris Miller, Harvard
Vision for the future: ecosystem monitoring Adjoint inversion of isoprene emission using geostationary satellite observations of HCHO and glyoxal boundary layer mixing (~1 h) HCHO, glyoxal measurement (x, t) 1 -km chemical transport model Wind inverse model Emission E( x’, t’) • Geostationary observation diurnal information, higher precision daily data GEMS (Korea), 2017; Sentinel-4 (Europe), 2019; GEO-CAPE (US), 2020+ • Adjoint inversion solve smearing problem, allow isoprene emission monitoring need to properly represent chemistry-transport coupling on scales of PBL mixing
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