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Lei Zhu and Daniel J. Jacob

Detection of anthropogenic formaldehyde over North America by oversampling of OMI data: Implications for TEMPO. Lei Zhu and Daniel J. Jacob. HCHO observations from space constrain emissions of highly reactive volatile organic compounds (HRVOCs). h  , OH. oxidation. HRVOCs. HCHO.

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Lei Zhu and Daniel J. Jacob

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  1. Detection of anthropogenic formaldehyde over North Americaby oversampling of OMI data: Implications for TEMPO Lei Zhu and Daniel J. Jacob

  2. HCHO observations from space constrain emissionsof highly reactive volatile organic compounds (HRVOCs) h , OH oxidation HRVOCs HCHO ~ 2 hours and funding from NASA ACMAP OMI HCHO columns Jan 2006 Jul 2006 < 1 day T.P. Kurosu anthropogenic biogenic pyrogenic

  3. OMI formaldehyde 2005-2009 Nigerian air pollution revealed by satellite • Population: 170 million (+3% a-1) • GDP: $270 billion (+7% a-1) – oil! • Most natural gas is flared • >80% of domestic energy from biofuel, waste An unusual mix of very high VOCs, low NOx – What will happen as infrastructure develops? gas flaring! TES 825 hPa ozone DJF 1015 molecules cm-2 aerosol (AOD) NO2 HCHO glyoxal methane Lagos Port Harcourt SCIA MISR Marais et al., 2014

  4. Detection of anthropogenic HRVOCs from HCHO over US has been elusive: elevated HCHO is mainly from isoprene h , OH oxidation HCHO OMI satellite observations of formaldehyde (HCHO) columns, Jun-Aug 2006 2 hours Millet et al. [2008] 1 hour isoprene

  5. Using non-growing season to avoid isoprene interference doesn’t work – HCHO observations are then below detection limit GOME data [Abbot et al., 2003] • HCHO detection in winter hampered by • low sun angles • low PBL heights • slow chemistry Detection limit (for 1-month average)

  6. Problem is that US urban/industrial plumes are small and localized • OMI monthly detection limit of 5x1015 molecules cm-2 ≡ 1 ppb HCHO in 2 km PBL • HCHO ~ 10 ppb observed in cores of urban/industrial plumes but not on scale of OMI pixels (13x24 km2 nadir) Solve problem by oversampling: achieve spatial resolution finer than pixel size by temporal averaging Day 3 Day 2 Day 1 Apply to OMI HCHO May-Aug 2005-2008 retrieval on 2x2 km2 grid, 24 km smoothing

  7. Oversampled OMI HCHO over eastern Texas (May-Aug 2005-2008) vegetation prevailing wind Isoprene in green Large AHRVOC point sources in black

  8. Lack of temperature dependence of HCHO in Houston urban coresupports anthropogenic attribution exp[0.11T]

  9. Using OMI HCHO to quantify Houston AHRVOC emissions Integrate HCHO enhancement over area of Houston plume HCHO source = 260 ± 110 kmol h-1 • = HCHO column • o = background column Consistent with S = 240 ± 90 kmol h-1 from TEXAQS [Parrish et al., 2012] Compare to EPA AHRVOC inventory (NEI 05) Background o EPA inventory is factor of 5.5 ± 2.4 too low

  10. Implications for TEMPO • TEMPO should perform much better than OMI in detecting AHRVOC emissions • Detecting AHRVOC emissions from oil/gas fields is of particular interest; OMI is marginal, TEMPO has promise. • Staggering TEMPO pixels from day to day would allow oversampling but that does not seem necessary • Observed diurnal variation of urban/industrial plumes will constrain primary vs. secondary HCHO sources

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