Seasonal and interannual variability of North American isoprene emissions as determined by formaldehyde column measurements from space

Formaldehyde (HCHO) columns measured from space by solar UV backscatter allow mapping of reactive hydrocarbon emissions. The principal contributor to these emissions during the growing season is the biogenic hydrocarbon isoprene, which is of great importance for driving regional and global tropospheric chemistry. We present seven years (1995-2001) of HCHO column data for North America from the Global Ozone Monitoring Experiment (GOME), and show that the general seasonal and interannual variability of these data is consistent with knowledge of isoprene emission. There are some significant regional discrepancies with the seasonal patterns predicted from current isoprene emission models, and we suggest that these may reflect flaws in the models. The interannual variability of HCHO columns observed by GOME appears to follow the interannual variability of surface temperature, as expected from current isoprene emission models

Spatial Distribution of Isoprene Emissions from North America Derived from Dormaldehyde Column Measurements by the OMI Satellite Sensor

Space-borne formaldehyde (HCHO) column measurements from the Ozone Monitoring Instrument (OMI), with 13 × 24 km2 nadir footprint and daily global coverage, provide new constraints on the spatial distribution of biogenic isoprene emission from North America. OMI HCHO columns for June-August 2006 are consistent with measurements from the earlier GOME satellite sensor (1996–2001) but OMI is 2–14% lower. The spatial distribution of OMI HCHO columns follows that of isoprene emission; anthropogenic hydrocarbon emissions are undetectable except in Houston. We develop updated relationships between HCHO columns and isoprene emission from a chemical transport model (GEOS-Chem), and use these to infer top-down constraints on isoprene emissions from the OMI data. We compare the OMI-derived emissions to a state-of-science bottom-up isoprene emission inventory (MEGAN) driven by two land cover databases, and use the results to optimize the MEGAN emission factors (EFs) for broadleaf trees (the main isoprene source). The OMI-derived isoprene emissions in North America (June–August 2006) with 1° × 1° resolution are spatially consistent with MEGAN (R2 = 0.48–0.68) but are lower (by 4–25% on average). MEGAN overestimates emissions in the Ozarks and the Upper South. A better fit to OMI (R2 = 0.73) is obtained in MEGAN by using a uniform isoprene EF from broadleaf trees rather than variable EFs. Thus MEGAN may overestimate emissions in areas where it specifies particularly high EFs. Within-canopy isoprene oxidation may also lead to significant differences between the effective isoprene emission to the atmosphere seen by OMI and the actual isoprene emission determined by MEGAN.Earth and Planetary SciencesEngineering and Applied Science

Air mass factor formulation for spectroscopic measurements from satellites: Application to formaldehyde retrievals from the Global Ozone Monitoring Experiment

Abstract. We present a new formulation for the air mass factor (AMF) to convert slant column measurements of optically thin atmospheric species from space into total vertical columns. Because of atmospheric scattering, the AMF depends on the vertical distribution of the species. We formulate the AMF as the integral of the relative vertical distribution (shape factor) of the species over the depth of the atmosphere, weighted by altitudedependent coefficients (scattering weights) computed independently from a radiative transfer model. The scattering weights are readily tabulated, and one can then obtain the AMF for any observation scene by using shape factors from a three dimensional (3-D) atmospheric chemistry model for the period of observation. This approach subsequently allows objective evaluation of the 3-D model with the observed vertical columns, since the shape factor and the vertical column in the model represent two independent pieces of information. We demonstrate the AMF method by using slant column measurements of formaldehyde at 346 nm from the Global Ozone Monitoring Experiment satellite instrument over North America during July 1996. Shape factors are computed with the Global Earth Observing System CHEMistry (GEOS-CHEM) global 3-D model and are checked for consistency with the few available aircraft measurements. Scattering weights increase by an order of magnitude from the surface to the upper troposphere. The AMFs are typically 20-40 % less over continents than over the oceans and are approximately half the values calculated in the absence of scattering. Model-induced errors in the AMF are estimated to be • 10%. The GEOS-CHEM model captures 50 % and 60 % of the variances in the observed slant and vertical columns, respectively. Comparison of the simulated and observed vertical columns allows assessment of model bias. 1

Mapping isoprene emissions over North America using formaldehyde column observations from space

[1] We present a methodology for deriving emissions of volatile organic compounds (VOC) using space-based column observations of formaldehyde (HCHO) and apply it to data from the Global Ozone Monitoring Experiment (GOME) satellite instrument over North America during July 1996. The HCHO column is related to local VOC emissions, with a spatial smearing that increases with the VOC lifetime. Isoprene is the dominant HCHO precursor over North America in summer, and its lifetime ('1 hour) is sufficiently short that the smearing can be neglected. We use the Goddard Earth Observing System global 3-D model of tropospheric chemistry (GEOS-CHEM) to derive the relationship between isoprene emissions and HCHO columns over North America and use these relationships to convert the GOME HCHO columns to isoprene emissions. We also use the GEOS-CHEM model as an intermediary to validate the GOME HCHO column measurements by comparison with in situ observations. The GEOS-CHEM model including the Global Emissions Inventory Activity (GEIA) isoprene emission inventory provides a good simulation of both the GOME data (r 2 = 0.69, n = 756, bias = +11%) and the in situ summertime HCHO measurements over North America (r 2 = 0.47, n = 10, bias = À3%). The GOME observations show high values over regions of known high isoprene emissions and a day-to-day variability that is consistent with the temperature dependence of isoprene emission. Isoprene emissions inferred from the GOME data are 20% less than GEIA on average over North America and twice those from the U.S. EPA Biogenic Emissions Inventory System (BEIS2) inventory. The GOME isoprene inventory when implemented in the GEOS-CHEM model provides a better simulation of the HCHO in situ measurements than either GEIA or BEIS2 (r 2 = 0.71, n = 10, bias = À10%)

First Directly Retrieved Global Distribution of Tropospheric Column Ozone from GOME: Comparison with the GEOS-CHEM Model

We present the first directly retrieved global distribution of tropospheric column ozone from Global Ozone Monitoring Experiment (GOME) ultraviolet measurements during December 1996 to November 1997. The retrievals clearly show signals due to convection, biomass burning, stratospheric influence, pollution, and transport. They are capable of capturing the spatiotemporal evolution of tropospheric column ozone in response to regional or short time-scale events such as the 1997–1998 El Niño event and a 10–20 DU change within a few days. The global distribution of tropospheric column ozone displays the well-known wave-1 pattern in the tropics, nearly zonal bands of enhanced tropospheric column ozone of 36–48 DU at 20°S–30°S during the austral spring and at 25°N–45°N during the boreal spring and summer, low tropospheric column ozone of 33 DU at some northern high-latitudes during the spring. Simulation from a chemical transport model corroborates most of the above structures, with small biases of <±5 DU and consistent seasonal cycles in most regions, especially in the southern hemisphere. However, significant positive biases of 5–20 DU occur in some northern tropical and subtropical regions such as the Middle East during summer. Comparison of GOME with monthly-averaged Measurement of Ozone and Water Vapor by Airbus in-service Aircraft (MOZAIC) tropospheric column ozone for these regions usually shows good consistency within 1σ standard deviations and retrieval uncertainties. Some biases can be accounted for by inadequate sensitivity to lower tropospheric ozone, the different spatiotemporal sampling and the spatiotemporal variations in tropospheric column ozone.Earth and Planetary SciencesEngineering and Applied Science

Satellite observations of formaldehyde over North America from GOME

Formaldehyde (HCHO) is an important indicator of tropospheric hydrocarbon emissions and photochemical activity. We present HCHO observations over North America for July 1996 from the GOME instrument on-board the ESA ERS-2 satellite. Slant columns are determined to < 4 × 1015 molecules cm−2 sensitivity by directly fitting GOME radiance measurements. These show a distinct enhancement over the southeastern United States, consistent with a large regional source from oxidation of non-methane hydrocarbons including in particular isoprene. Conversion of slant to vertical columns is done by combining species vertical distribution information from the GEOS-CHEM 3-D tropospheric chemistry and transport model with scattering weights from the Smithsonian Astrophysical Observatory LIDORT multiple scattering radiative transfer model. The results demonstrate the ability to measure HCHO from space in typical continental atmospheres, and imply that space-based measurements of HCHO may provide valuable information on emission fluxes of reactive hydrocarbons.Engineering and Applied Science

Can a “state of the art” chemistry transport model simulate Amazonian tropospheric chemistry?

We present an evaluation of a nested high-resolution Goddard Earth Observing System (GEOS)-Chem chemistry transport model simulation of tropospheric chemistry over tropical South America. The model has been constrained with two isoprene emission inventories: (1) the canopy-scale Model of Emissions of Gases and Aerosols from Nature (MEGAN) and (2) a leaf-scale algorithm coupled to the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model, and the model has been run using two different chemical mechanisms that contain alternative treatments of isoprene photo-oxidation. Large differences of up to 100 Tg C yr^(−1) exist between the isoprene emissions predicted by each inventory, with MEGAN emissions generally higher. Based on our simulations we estimate that tropical South America (30–85°W, 14°N–25°S) contributes about 15–35% of total global isoprene emissions. We have quantified the model sensitivity to changes in isoprene emissions, chemistry, boundary layer mixing, and soil NO_x emissions using ground-based and airborne observations. We find GEOS-Chem has difficulty reproducing several observed chemical species; typically hydroxyl concentrations are underestimated, whilst mixing ratios of isoprene and its oxidation products are overestimated. The magnitude of model formaldehyde (HCHO) columns are most sensitive to the choice of chemical mechanism and isoprene emission inventory. We find GEOS-Chem exhibits a significant positive bias (10–100%) when compared with HCHO columns from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI) for the study year 2006. Simulations that use the more detailed chemical mechanism and/or lowest isoprene emissions provide the best agreement to the satellite data, since they result in lower-HCHO columns

An improved retrieval of tropospheric nitrogen dioxide from GOME

We present a retrieval of tropospheric nitrogen dioxide (NO2) columns from the Global Ozone Monitoring Experiment (GOME) satellite instrument that improves in several ways over previous retrievals, especially in the accounting of Rayleigh and cloud scattering. Slant columns, which are directly fitted without low-pass filtering or spectral smoothing, are corrected for an artificial offset likely induced by spectral structure on the diffuser plate of the GOME instrument. The stratospheric column is determined from NO2 columns over the remote Pacific Ocean to minimize contamination from tropospheric NO2. The air mass factor (AMF) used to convert slant columns to vertical columns is calculated from the integral of the relative vertical NO2 distribution from a global 3-D model of tropospheric chemistry driven by assimilated meteorological data (Global Earth Observing System (GEOS)-CHEM), weighted by altitude-dependent scattering weights computed with a radiative transfer model (Linearized Discrete Ordinate Radiative Transfer), using local surface albedos determined from GOME observations at NO2 wavelengths. The AMF calculation accounts for cloud scattering using cloud fraction, cloud top pressure, and cloud optical thickness from a cloud retrieval algorithm (GOME Cloud Retrieval Algorithm). Over continental regions with high surface emissions, clouds decrease the AMF by 20–30% relative to clear sky. GOME is almost twice as sensitive to tropospheric NO2 columns over ocean than over land. Comparison of the retrieved tropospheric NO2 columns for July 1996 with GEOS-CHEM values tests both the retrieval and the nitrogen oxide radical (NOx) emissions inventories used in GEOS-CHEM. Retrieved tropospheric NO2 columns over the United States, where NOx emissions are particularly well known, are within 18% of GEOS-CHEM columns and are strongly spatially correlated (r = 0.78, n = 288, p < 0.005). Retrieved columns show more NO2 than GEOS-CHEM columns over the Transvaal region of South Africa and industrial regions of the northeast United States and Europe. They are lower over Houston, India, eastern Asia, and the biomass burning region of central Africa, possibly because of biases from absorbing aerosols.Engineering and Applied Science

OCO-3 early mission operations and initial (vEarly) XCO₂ and SIF retrievals

NASA's Orbiting Carbon Observatory-3 (OCO-3) was installed on the International Space Station (ISS) on 10 May 2019. OCO-3 combines the flight spare spectrometer from the Orbiting Carbon Observatory-2 (OCO-2) mission, which has been in operation since 2014, with a new Pointing Mirror Assembly (PMA) that facilitates observations of non-nadir targets from the nadir-oriented ISS platform. The PMA is a new feature of OCO-3, which is being used to collect data in all science modes, including nadir (ND), sun-glint (GL), target (TG), and the new snapshot area mapping (SAM) mode. This work provides an initial assessment of the OCO-3 instrument and algorithm performance, highlighting results from the first 8 months of operations spanning August 2019 through March 2020. During the In-Orbit Checkout (IOC) phase, critical systems such as power and cooling were verified, after which the OCO-3 spectrometer and PMA were subjected to a series of rigorous tests. First light of the OCO-3 spectrometer was on 26 June 2019, with full science operations beginning on 6 August 2019. The OCO-3 spectrometer on-orbit performance is consistent with that seen during preflight testing. Signal to noise ratios are in the expected range needed for high quality retrievals of the column-averaged carbon dioxide (CO₂) dry-air mole fraction (XCO₂) and solar-induced chlorophyll fluorescence (SIF), which will be used to help quantify and constrain the global carbon cycle. The first public release of OCO-3 Level 2 (L2) data products, called “vEarly”, is being distributed by NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC). The intent of the vEarly product is to evaluate early mission performance, facilitate comparisons with OCO-2 products, and identify key areas to improve for the next data release. The vEarly XCO2 exhibits a root-mean-squared-error (RMSE) of ≃ 1, 1, 2 ppm versus a truth proxy for nadir-land, TG&SAM, and glint-water observations, respectively. The vEarly SIF shows a correlation with OCO-2 measurements of >0.9 for highly coincident soundings. Overall, the Level 2 SIF and XCO₂ products look very promising, with performance comparable to OCO-2. A follow-on version of the OCO-3 L2 product containing a number of refinements, e.g., instrument calibration, pointing accuracy, and retrieval algorithm tuning, is anticipated by early in 2021