[Show abstract][Hide abstract] ABSTRACT: OMI HCHO is validated over the continental US (CONUS), and used to analyze regional sources in Northeast Asia (NA) and Southeast Asia (SA). OMI HCHO Version 2.0 data show unrealistic trends, which prompted the production of a corrected OMI HCHO data set. EOF and SVD are utilized to compare the spatial and temporal variability between OMI HCHO against GOME and SCIAMACHY, and against GEOS-Chem. CONUS HCHO chemistry is well studied; its concentrations are greatest in the southeastern US with annual cycle maximums corresponding to the summer vegetation. The corrected OMI HCHO agrees with this understanding as well as with the other sensors measurements and has no unrealistic trends. In NA the annual cycle is super-posed by extremely large concentrations in polluted mega-cities. The other sensors generally agree with NA's OMI HCHO regional distribution, but megacity signal is not seen in GEOS-Chem. Our study supports the findings proposed by others that the emission inventory used in GEOS-Chem significantly underestimates anthropogenic influence on HCHO emission over megacities. The persistent mega-city signal is also present in SA. In SA the spatial and temporal patterns of OMI HCHO show a maximum in the dry season. The patterns are in remarkably good agreement with fire counts, which illustrates that the variability of HCHO over SA is strongly influenced by biomass burning. The corrected OMI HCHO data has realistic trends, conforms to well-known sources over CONUS, and has shown a stationary large concentration over polluted Asian mega-cities, and a widespread biomass burning in SA.
Science of The Total Environment 05/2014; 490C:93-105. · 3.16 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We use a 2005-2009 record of isoprene emissions over Africa derived from OMI satellite observations of formaldehyde (HCHO) to better understand the factors controlling isoprene emission on the scale of the continent and evaluate the impact of isoprene emissions on atmospheric composition in Africa. OMI-derived isoprene emissions show large seasonality over savannas driven by temperature and leaf area index (LAI), and much weaker seasonality over equatorial forests driven by temperature. The commonly used MEGAN (version 2.1) global isoprene emission model reproduces this seasonality but is biased high, particularly for equatorial forests, when compared to OMI and relaxed-eddy accumulation measurements. Isoprene emissions in MEGAN are computed as the product of an emission factor Eo, LAI, and activity factors dependent on environmental variables. We use the OMI-derived emissions to provide improved estimates of Eo that are in good agreement with direct leaf measurements from field campaigns (r = 0.55, bias = -19%). The largest downward corrections to MEGAN Eo values are for equatorial forests and semi-arid environments, and this is consistent with latitudinal transects of isoprene over West Africa from the AMMA aircraft campaign. Total emission of isoprene in Africa is estimated to be 77 Tg C a-1, compared to 104 Tg C a-1 in MEGAN. Simulations with the GEOS-Chem oxidant-aerosol model suggest that isoprene emissions increase mean surface ozone in West Africa by up to 8 ppbv, and particulate matter by up to 1.5 μg m-3, due to coupling with anthropogenic influences.
Atmospheric Chemistry and Physics 02/2014; 14(5). · 5.51 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Future geostationary satellite observations of tropospheric ozone aim to improve monitoring of surface ozone air quality. However, ozone retrievals from space have limited sensitivity in the lower troposphere (boundary layer). Data assimilation in a chemical transport model can propagate the information from the satellite observations to provide useful constraints on surface ozone. This may be aided by correlated satellite observations of carbon monoxide (CO), for which boundary layer sensitivity is easier to achieve. We examine the potential of concurrent geostationary observations of ozone and CO to improve constraints on surface ozone air quality through exploitation of ozone–CO model error correlations in a joint data assimilation framework. The hypothesis is that model transport errors diagnosed for CO provide information on corresponding errors in ozone. A paired-model analysis of ozone–CO error correlations in the boundary layer over North America in summer indicates positive error correlations in continental outflow but negative regional-scale error correlations over land, the latter reflecting opposite sensitivities of ozone and CO to boundary layer depth. Aircraft observations from the ICARTT campaign are consistent with this pattern but also indicate strong positive error correlations in fine-scale pollution plumes. We develop a joint ozone–CO data assimilation system and apply it to a regional-scale Observing System Simulation Experiment (OSSE) of the planned NASA GEO-CAPE geostationary mission over North America. We find substantial benefit from joint ozone–CO data assimilation in informing US ozone air quality if the instrument sensitivity for CO in the boundary layer is greater than that for ozone. A high-quality geostationary measurement of CO could potentially relax the requirements for boundary layer sensitivity of the ozone measurement. This is contingent on accurate characterization of ozone–CO error correlations. A finer-resolution data assimilation system resolving the urban scale would need to account for the change in sign of the ozone–CO error correlations between urban pollution plumes and the regional atmosphere.
[Show abstract][Hide abstract] ABSTRACT: The accuracy of total ozone computed from the Smithsonian Astrophysical Observatory (SAO) optimal estimation (OE) ozone profile algorithm (SOE) applied to the Ozone Monitoring Instrument (OMI) is assessed through comparisons with ground-based Brewer spectrometer measurements from 2005 to 2008. We also make comparisons with the three OMI operational ozone products, derived from the NASA Total Ozone Mapping Spectrometer (TOMS), KNMI Differential Optical Absorption Spectroscopy (DOAS), and KNMI OE (KOE) algorithms. Excellent agreement is observed between SAO and Brewer, with a mean difference of less than ±1% at most individual stations. The KNMI OE algorithm systematically overestimates Brewer total ozone by 2% at low/mid latitudes and 5% at high latitudes while the TOMS and DOAS algorithms underestimate it by ~1.65% on average. Standard deviations of ~1.8% are found for both SOE and TOMS, but DOAS and KOE have scatters of 2.2% and 2.6%, respectively. The stability of the SOE algorithm is found to have insignificant dependence on viewing geometry, cloud parameters, total ozone column. In comparison, the KOE differences to Brewer values are significantly correlated with solar and viewing zenith angles, with a significant deviation depending on cloud parameters and total ozone amount. The TOMS algorithm exhibits similar stability to SOE with respect to viewing geometry and total column ozone, but stronger cloud parameter dependence. The dependence of DOAS on the algorithmic variables is marginal compared to KOE, but distinct compared to the SOE and TOMS algorithms. Comparisons of All four OMI products with Brewer show no apparent long-term drift but a seasonally affected feature, especially for KOE and TOMS. The substantial differences in the KOE vs. SOE algorithm performance cannot be sufficiently explained by the use of soft calibration (in SOE) and the use of different a priori error covariance matrix, but other algorithm details cause larger fitting residuals by a factor of 2-3 for KOE.
[Show abstract][Hide abstract] ABSTRACT: Ozone is a tropospheric pollutant and plays a key role in determining the air quality that affects human wellbeing. In this study, we compare the capability of two hypothetical grating spectrometers onboard a geostationary (GEO) satellite to sense ozone in the lowermost troposphere (surface and the 0-1 km column). We consider one week during the Northern Hemisphere summer simulated by a chemical transport model, and use the two GEO instrument configurations to measure ozone concentration (1) in the thermal infrared (GEO TIR) and (2) in the thermal infrared and the visible (GEO TIR+VIS). These configurations are compared against each other, and also against an ozone reference state and a priori ozone information. In a first approximation, we assume clear sky conditions neglecting the influence of aerosols and clouds. A number of statistical tests are used to assess the performance of the two GEO configurations. We consider land and sea pixels and whether differences between the two in the performance are significant. Results show that the GEO TIR+VIS configuration provides a better representation of the ozone field both for surface ozone and the 0-1 km ozone column during the daytime especially over land.
[Show abstract][Hide abstract] ABSTRACT: OMI HCHO is validated over the continental US (CONUS), and used to analyze regional sources in Northeast Asia (NA) and Southeast Asia (SA). OMI HCHO Version 2.0 data show unrealistic trends, which prompted the production of a corrected OMI HCHO data set. EOF and SVD are utilized to compare the spatial and temporal variability between OMI HCHO against GOME and SCIAMACHY, and against GEOS-Chem. CONUS HCHO chemistry is well studied; its concentrations are greatest in the southeastern US with annual cycle maximums corresponding to the summer vegetation. The corrected OMI HCHO agrees with this understanding as well as with the other sensors measurements and has no unrealistic trends. In NA the annual cycle is super-posed by extremely large concentrations in polluted mega-cities. The other sensors generally agree with NA’s OMI HCHO regional distribution, but megacity signal is not seen in GEOS-Chem. Our study supports the findings proposed by others that the emission inventory used in GEOS-Chem significantly underestimates anthropogenic influence on HCHO emission over megacities. The persistent mega-city signal is also present in SA. In SA the spatial and temporal patterns of OMI HCHO show a maximum in the dry season. The patterns are in remarkably good agreement with fire counts, which illustrates that the variability of HCHO over SA is strongly influenced by biomass burning. The corrected OMI HCHO data has realistic trends, conforms to well-known sources over CONUS, and has shown a stationary large concentration over polluted Asian mega-cities, and a widespread biomass burning in SA.
Science of The Total Environment 01/2014; 490:93–105. · 3.16 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Nigeria has a high population density and large fossil fuel resources but very poorly managed energy infrastructure. Satellite observations of formaldehyde (HCHO) and glyoxal (CHOCHO) reveal very large sources of anthropogenic nonmethane volatile organic compounds (NMVOCs) from the Lagos megacity and oil/gas operations in the Niger Delta. This is supported by aircraft observations over Lagos and satellite observations of methane in the Niger Delta. Satellite observations of carbon monoxide (CO) and nitrogen dioxide (NO2) show large seasonal emissions from open fires in December-February (DJF). Ventilation of central Nigeria is severely restricted at that time of year, leading to very poor ozone air quality as observed from aircraft (MOZAIC) and satellite (TES). Simulations with the GEOS-Chem chemical transport model (CTM) suggest that maximum daily 8-h average (MDA8) ozone exceeds 70 ppbv over the region on a seasonal mean basis, with significant contributions from both open fires (15-20 ppbv) and fuel/industrial emissions (7-9 ppbv). The already severe ozone pollution in Nigeria could worsen in the future as a result of demographic and economic growth, although this would be offset by a decrease in open fires.
[Show abstract][Hide abstract] ABSTRACT: There are distinct spectral features of water vapor in the wavelength range covered by the Ozone Monitoring Instrument (OMI) visible channel. Although these features are much weaker than those at longer wavelengths, they can be exploited to retrieve useful information about water vapor. They have an advantage in that their small optical depth leads to fairly simple interpretation as measurements of the total water vapor column density. We have used the Smithsonian Astrophysical Observatory (SAO)'s OMI operational retrieval algorithm to derive the Slant Column Density (SCD) of water vapor from OMI measurements using the 430-480 nm spectral region after extensive optimization of retrieval windows and parameters. The Air Mass Factor (AMF) is calculated using look-up tables of scattering weights and monthly mean water vapor profiles from the GEOS-5 assimilation products. We convert from SCD to Vertical Column Density (VCD) using the AMF and generate associated retrieval averaging kernels and shape factors. Our standard water vapor product has a median SCD of ~ 1.3 × 1023 molecule cm-2 and a median relative uncertainty of ~ 11% in the tropics, about a factor of 2 better than that from a similar OMI algorithm but using narrower retrieval window. The corresponding median VCD is ~ 1.2 × 1023 molecule cm-2. We have also explored the sensitivities to various parameters and compared our results with those from the Moderate-resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic NETwork (AERONET).
[Show abstract][Hide abstract] ABSTRACT: We present and discuss the Smithsonian Astrophysical Observatory (SAO) formaldehyde (H2CO) retrieval algorithm for the Ozone Monitoring Instrument (OMI) which is the operational retrieval for NASA OMI H2CO. The version of the algorithm described here includes relevant changes with respect to the operational one, including differences in the reference spectra for H2CO, the fit of O2-O2 collisional complex, updates in the high resolution solar reference spectrum, the use of a model reference sector over the remote Pacific Ocean to normalize the retrievals, an updated Air Mass Factor (AMF) calculation scheme, and the inclusion of scattering weights and vertical H2CO profile in the level 2 products. The theoretical basis of the retrieval is discussed in detail. Typical values for retrieved vertical columns are between 4 × 1015 and 4 × 1016 molecules cm-2 with typical fitting uncertainties ranging between 40% and 100%. In high concentration regions the errors are usually reduced to 30%. The detection limit is estimated at 3 × 1015 molecules cm-2. These updated retrievals are compared with previous ones.
[Show abstract][Hide abstract] ABSTRACT: We compare three datasets of high-resolution O3 cross
sections and evaluate the effects of using these cross sections on
O3 profile retrievals from OMI UV (270–330 nm)
measurements. These O3 cross sections include
Brion–Daumont–Malicet (BDM), Bass–Paur (BP) and a new
dataset measured by Serdyuchenko et al. (SGWCB), which is made from
measurements at more temperatures and in a wider temperature range than
BDM and BP, 193–293 K. Relative to the BDM dataset, the SGWCB data
have systematic biases of ‑2 to +4% for 260–340 nm, and the
BP data have smaller biases of 1–2% below 315 nm but larger spiky
biases of up to ±6% at longer wavelengths. These datasets show
distinctly different temperature dependences. Using different cross
sections can significantly affect atmospheric retrievals. Using SGWCB
data leads to retrieval failure for almost half of the OMI spatial
pixels, producing large negative ozone values that cannot be handled by
radiative transfer models and using BP data leads to large fitting
residuals over 310–330 nm. Relative to the BDM retrievals, total
ozone retrieved using original SGWCB data (with linear temperature
interpolation/extrapolation) typically shows negative biases of
5–10 DU; retrieved tropospheric ozone column generally shows
negative biases of 5–10 DU and 5–20 DU for parameterized and
original SGWCB data, respectively. Compared to BDM retrievals, ozone
profiles retrieved with BP/SGWCB data on average show large
altitude-dependent oscillating differences of up to ±20–40%
biases below ~20 km with almost opposite bias patterns. Validation with
ozonesonde observations demonstrates that the BDM retrievals agree well
with ozonesondes, to typically within 10%, while both BP and SGWCB
retrievals consistently show large altitude-dependent biases of up to
±20–70% below 20 km. Therefore, we recommend using the BDM
dataset for ozone profile retrievals from UV measurements. Its improved
performance is likely due to its better characterization of temperature
dependence in the Hartley and Huggins bands.
Journal of Quantitative Spectroscopy and Radiative Transfer 11/2013; · 2.38 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This paper describes the status of the 2012 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2008 and its updates during the intervening years. The HITRAN molecular absorption compilation is comprised of six major components structured into folders that are freely accessible on the internet. These folders consist of the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, ultraviolet spectroscopic parameters, aerosol indices of refraction, collision-induced absorption data, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, and validity. Molecules and isotopologues have been added that address the issues of atmospheres beyond the Earth. Also discussed is a new initiative that casts HITRAN into a relational database format that offers many advantages over the long-standing sequential text-based structure that has existed since the initial release of HITRAN in the early 1970s.
Journal of Quantitative Spectroscopy and Radiative Transfer 11/2013; 130:4-50. · 2.38 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We present a new multispectral approach for observing lowermost
tropospheric ozone from space by synergism of atmospheric radiances in
the thermal infrared (TIR) observed by IASI and earth reflectances in
the ultraviolet (UV) measured by GOME-2. Both instruments are onboard
the series of MetOp satellites (in orbit since 2006 and expected until
2022) and their scanning capabilities offer global coverage every day,
with a relatively fine ground pixel resolution (12-km-diameter pixels
spaced by 25 km for IASI at nadir). Our technique uses
altitude-dependent Tikhonov-Phillips-type constraints, which optimize
sensitivity to lower tropospheric ozone. It integrates the VLIDORT and
KOPRA radiative transfer codes for simulating UV reflectance and TIR
radiance, respectively. We have used our method to analyse real
observations over Europe during an ozone pollution episode in the summer
of 2009. The results show that the multispectral synergism of IASI (TIR)
and GOME-2 (UV) enables the observation of the spatial distribution of
ozone plumes in the lowermost troposphere (LMT, from the surface up to 3
km a.s.l., above sea level), in good quantitative agreement with the
CHIMERE regional chemistry-transport model. When high ozone
concentrations extend vertically above 3 km a.s.l., they are similarly
observed over land by both the multispectral and IASI retrievals. On the
other hand, ozone plumes located below 3 km a.s.l. are only clearly
depicted by the multispectral retrieval (both over land and over ocean).
This is achieved by a clear enhancement of sensitivity to ozone in the
lowest atmospheric layers. The multispectral sensitivity in the LMT
peaks at 2 to 2.5 km a.s.l. over land, while sensitivity for IASI or
GOME-2 only peaks at 3 to 4 km a.s.l. at lowest (above the LMT). The
degrees of freedom for the multispectral retrieval increase by 40% (21%)
with respect to IASI only retrievals for atmospheric partial columns up
to 3 km a.s.l. (6 km a.s.l.). Validations with ozonesondes show that our
synergetic approach for combining IASI (TIR) and GOME-2 (UV)
measurements retrieves lowermost tropospheric ozone with a mean bias of
2% and a precision of 16%, when smoothing by the retrieval vertical
sensitivity (1% mean bias and 24% precision for direct comparisons).
Atmospheric Chemistry and Physics 10/2013; 13:9675-9693. · 4.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Retrievals of sulfur dioxide (SO2) from space-based spectrometers are in a relatively early stage of development. Factors such as interference between ozone and SO2 in the retrieval algorithms often lead to errors in the retrieved values. Measurements from the Ozone Monitoring Instrument (OMI), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), and Global Ozone Monitoring Experiment -2 (GOME-2) satellite sensors, aver-aged over a period of several years, were used to identify locations with elevated SO2 values and estimate their emission levels. About 30 such locations, detectable by all three sensors and linked to volcanic and anthropogenic sources, were found, after applying low- and high- spatial fre-quency filtration designed to reduce noise and bias and to enhance weak signals to SO2 data from each instrument. Quantitatively, the mean amount of SO2 in the vicinity of the sources, estimated from the three instruments is in general agreement. However a better spatial resolution of OMI makes it possible for this instrument to detect smaller sources and with more details compared to the other two instruments. Over some regions of China, SCIAMACHY and GOME-2 data show mean SO2 values that are almost 1.5 times higher than those from OMI but the suggested spatial filtration technique largely reconciles these differences.
Journal of Geophysical Research Atmospheres 10/2013; 118(2013-10):11399-11418. · 3.44 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: TEMPO was selected in 2012 by NASA as the first Earth Venture
Instrument, for launch circa 2018. It will measure atmospheric pollution
for greater North America from space using ultraviolet and visible
spectroscopy. TEMPO measures from Mexico City to the Canadian tar sands,
and from the Atlantic to the Pacific, hourly and at high spatial
resolution (~2 km N/S×4.5 km E/W at 36.5°N, 100°W). TEMPO
provides a tropospheric measurement suite that includes the key elements
of tropospheric air pollution chemistry. Measurements are from
geostationary (GEO) orbit, to capture the inherent high variability in
the diurnal cycle of emissions and chemistry. The small product spatial
footprint resolves pollution sources at sub-urban scale. Together, this
temporal and spatial resolution improves emission inventories, monitors
population exposure, and enables effective emission-control strategies.
TEMPO takes advantage of a commercial GEO host spacecraft to provide a
modest cost mission that measures the spectra required to retrieve
O3, NO2, SO2, H2CO,
C2H2O2, H2O, aerosols, cloud
parameters, and UVB radiation. TEMPO thus measures the major elements,
directly or by proxy, in the tropospheric O3 chemistry cycle.
Multi-spectral observations provide sensitivity to O3 in the
lowermost troposphere, substantially reducing uncertainty in air quality
predictions. TEMPO quantifies and tracks the evolution of aerosol
loading. It provides near-real-time air quality products that will be
made widely, publicly available. TEMPO will launch at a prime time to be
the North American component of the global geostationary constellation
of pollution monitoring together with European Sentinel-4 and Korean
[Show abstract][Hide abstract] ABSTRACT: We use formaldehyde (HCHO) vertical column measurements from the Scanning
Imaging Absorption spectrometer for Atmospheric Chartography (SCIAMACHY) and
Ozone Monitoring Instrument (OMI), and a nested-grid version of the GEOS-Chem
chemistry transport model, to infer an ensemble of top-down isoprene emission estimates from tropical South America during 2006, using different model configurations and assumptions in the HCHO air-mass factor (AMF) calculation. Scenes affected by biomass burning are removed on a daily basis using fire count observations, and we use the local model sensitivity to identify locations where the impact of spatial smearing is small, though this comprises spatial coverage over the region. We find that the use of the HCHO column data more tightly constrains the ensemble isoprene emission range from
27–61 Tg C to 31–38 Tg C for SCIAMACHY, and 45–104 Tg C to 28–38 Tg C for OMI.
Median uncertainties of the top-down emissions are about 60–260% for SCIAMACHY,
and 10–90% for OMI. We find that the inferred emissions are most sensitive to uncertainties in cloud fraction and cloud top pressure (differences of ˙10%), the a priori
isoprene emissions (˙20%), and the HCHO vertical column retrieval (˙30%).
Construction of continuous top-down emission maps generally improves GEOS-Chem’s
simulation of HCHO columns over the region, with respect to both the SCIAMACHY
and OMI data. However, if local time top-down emissions are scaled to monthly mean
values, the annual emission inferred from SCIAMACHY are nearly twice those from
OMI. This difference cannot be explained by the different sampling of the sensors or
uncertainties in the AMF calculation.
Journal of Geophysical Research: Atmospheres. 06/2013; 118:n/a-n/a.
[Show abstract][Hide abstract] ABSTRACT: We present a global data set of free tropospheric ozone-CO correlations
with 2° × 2.5° spatial resolution from the Ozone
Monitoring Instrument (OMI) and Atmospheric Infrared Sounder (AIRS)
satellite instruments for each season of 2008. OMI and AIRS have near
daily global coverage of ozone and CO respectively and observe
coincident scenes with similar vertical sensitivities. The resulting
ozone-CO correlations are highly statistically significant (positive or
negative) in most regions of the world, and are less noisy than previous
satellite-based studies that used sparser data. We interpret the
observed ozone-CO correlations with the GEOS-Chem chemical transport
model to infer constraints on ozone sources. Driving GEOS-Chem with
different meteorological fields generally shows consistent ozone-CO
correlation patterns, except in some tropical regions where the
correlations are strongly sensitive to model transport error associated
with deep convection. GEOS-Chem reproduces the general structure of the
observed ozone-CO correlations and regression slopes
(dO3/dCO), although there are some large regional
discrepancies. We examine the model sensitivity of dO3/dCO to
different ozone sources (combustion, biosphere, stratosphere, and
lightning NOx) by correlating the ozone change from that
source to CO from the standard simulation. The model reproduces the
observed positive dO3/dCO in the extratropical Northern
Hemisphere in spring-summer, driven by combustion sources. Stratospheric
influence there is also associated with a positive dO3/dCO
because of the interweaving of stratospheric downwelling with
continental outflow. The well-known ozone maximum over the tropical
South Atlantic is associated with negative dO3/dCO in the
observations; this feature is reproduced in GEOS-Chem and supports a
dominant contribution from lightning to the ozone maximum. A~major model
discrepancy is found over the Northeast Pacific in summer-fall where
dO3/dCO is positive in the observations but negative in the
model, for all ozone sources. We suggest that this reflects a model
overestimate of lightning at northern mid-latitudes combined with an
underestimate of the East Asian CO source.
Atmospheric Chemistry and Physics 04/2013; 13(4):8901-8937. · 4.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Elevated levels of formaldehyde (HCHO) in Nigeria, as observed using the
Ozone Monitoring Instrument, indicate a large source of anthropogenic
volatile organic compounds (VOCs). We isolate an anthropogenic signal of
HCHO by removing the biomass burning and biogenic signal. We use
space-based observations of gas flare hotspots, carbon monoxide,
methane, nitrogen dioxide and glyoxal to identify emission source
locations - city centers (Lagos, Abuja, Port Harcourt); Niger Delta
petroleum and natural gas extraction; and intense biofuel use in
populous rural regions. GEOS-Chem underestimates anthropogenic HCHO in
Nigeria and we use aircraft observations of VOCs made over Lagos during
the AMMA campaign (Jul-Aug 2006) and SCIAMACHY methane observations over
the Niger Delta to address this discrepancy. After updating GEOS-Chem
VOC emissions in Nigeria we find that local emissions increase surface
ozone north of the Nigerian coastline (persistent onshore winds) and
ozone and peroxyacetyl nitrate in the free troposphere stretching from
the Gulf of Guinea to the east coast of South America (monsoonal
convection and advection along a branch of the African Easterly Jet).
[Show abstract][Hide abstract] ABSTRACT: Lightning is a particularly significant NOx source in the middle and upper troposphere where it affects tropospheric chemistry and ozone. Because the version-4 Community Multiscale Air Quality Modeling System (CMAQ) does not account for NOx emission from lightning, it underpredicts NOx above the mixed layer. In this study, the National Lightning Detection Network™ (NLDN) lightning data are applied to the CMAQ model to simulate the influence of lightning-produced NOx (LNOx) on upper tropospheric NOx and subsequent ozone concentration. Using reasonable values for salient parameters (detection efficiency ∼95%, cloud flash to ground flash ratio ∼3, LNOx production rate ∼500 mol N per flash), the NLDN ground flashes are converted into total lightning NOx amount and then vertically distributed on 39 CMAQ model layers according to a vertical-distribution profile of lightning N mass. This LNOx contributes 27% of the total NOx emission during 15 July ∼7 September 2006. This additional NOx reduces the low-bias of simulated tropospheric O3 columns with respect to OMI tropospheric O3 columns from 10 to 5%. Although the model prediction of ozone in upper troposphere improves by ∼20 ppbv due to lightning-produced NOx above the southeastern and eastern U.S.A., the improved ozone prediction is still ∼20–25 ppbv lower than ozonesonde measurements.