K. Chance

Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, United States

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Publications (342)525.21 Total impact

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    Atmospheric Measurement Techniques 01/2015; 8(1):19-32. DOI:10.5194/amt-8-19-2015 · 3.21 Impact Factor
  • Atmospheric Chemistry and Physics 01/2015; 15(2):2013-2054. DOI:10.5194/acpd-15-2013-2015 · 4.88 Impact Factor
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    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.
    Atmospheric Environment 12/2014; 99:32-40. DOI:10.1016/j.atmosenv.2014.09.055 · 3.06 Impact Factor
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    ABSTRACT: We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (High-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEO-CAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O-2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the synergic use of two future geostationary satellites, GOES-R (Geostationary Operational Environmental Satellite R-series) and TEMPO (Tropospheric Emissions: Monitoring of Pollution). Strong synergy between GEOS-R and TEMPO are found especially in their characterization of surface bi-directional reflectance, and thereby, can potentially improve the AOD retrieval to the accuracy required by GEO-CAPE.
    Journal of Quantitative Spectroscopy and Radiative Transfer 10/2014; 146:510-528. DOI:10.1016/j.jqsrt.2014.03.020 · 2.29 Impact Factor
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    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. DOI:10.1016/j.scitotenv.2014.04.108 · 3.16 Impact Factor
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    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). DOI:10.5194/acpd-14-6951-2014 · 5.51 Impact Factor
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    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.
    Atmospheric Environment 02/2014; 84:254–261. DOI:10.1016/j.atmosenv.2013.11.048 · 3.06 Impact Factor
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    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.
    Atmospheric Chemistry and Physics 01/2014; 14(3). DOI:10.5194/acpd-14-4051-2014 · 4.88 Impact Factor
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    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.
    01/2014; 7(2). DOI:10.5194/amtd-7-1645-2014
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    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
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    ABSTRACT: We present an algorithm for the retrieval of glyoxal from backscattered solar radiation, and apply it to spectra measured by the Ozone Monitoring Instrument (OMI). The algorithm is based on direct spectrum fitting, and adopts a two-step fitting routine to account for liquid water absorption. Previous studies have shown that glyoxal retrieval algorithms are highly sensitive to the position of the spectral fit window. This dependence was systematically tested on real and simulated OMI spectra. We find that a combination of errors resulting from uncertainties in reference cross sections and spectral features associated with the Ring effect are consistent with the fit-window dependence observed in real spectra. This implies an optimal fitting window of 435-461 nm, consistent with previous satellite glyoxal retrievals. The results from the retrieval of simulated spectra also support previous findings that have suggested that glyoxal is sensitive to NO2 cross-section temperature. The retrieval window limits of the liquid water retrieval are also tested. A retrieval window 385-470 nm reduces interference with strong spectral features associated with sand. We show that cross-track dependent offsets (stripes) present in OMI can be corrected using offsets derived from retrieved slant columns over the Sahara, and apply the correction to OMI data. Average glyoxal columns are on average lower than those of previous studies likely owing to the choice of reference sector for offset correction. OMI VCDs (vertical column densities) are lower compared to other satellites over the tropics and Asia during the monsoon season, suggesting that the new retrieval is less sensitive to water vapour abundance. Consequently we do not see significant glyoxal enhancements over tropical oceans. OMI-derived glyoxal-to-formaldehyde ratios over biogenic and anthropogenic source regions are consistent with surface observations.
    Atmospheric Measurement Techniques 01/2014; 7(11):3891-3907. DOI:10.5194/amt-7-3891-2014 · 3.21 Impact Factor
  • Atmospheric Measurement Techniques 01/2014; 7(2):11415-11437. DOI:10.5194/amtd-7-11415-2014 · 3.21 Impact Factor
  • 01/2014; 7(6):6065-6112. DOI:10.5194/amtd-7-6065-2014
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    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.
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    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).
    Atmospheric Measurement Techniques 12/2013; 7(1). DOI:10.5194/amtd-7-541-2014 · 3.21 Impact Factor
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    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.
    12/2013; 7(1). DOI:10.5194/amtd-7-1-2014
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    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. DOI:10.1016/j.jqsrt.2013.07.002 · 2.29 Impact Factor
  • Cheng Liu, Xiong Liu, Kelly Chance
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    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; 130:365-372. DOI:10.1016/j.jqsrt.2013.06.006 · 2.29 Impact Factor

Publication Stats

11k Citations
525.21 Total Impact Points

Institutions

  • 1970–2014
    • Harvard-Smithsonian Center for Astrophysics
      • • Division of Atomic and Molecular Physics
      • • Division of Optical and Infrared Astronomy
      • • Smithsonian Astrophysical Observatory
      Cambridge, Massachusetts, United States
  • 1999
    • Universität Bremen
      • Institute of Environmental Physics
      Bremen, Bremen, Germany
  • 1994
    • University of Florence
      Florens, Tuscany, Italy
  • 1993
    • Macalester College
      • Department of Chemistry
      Saint Paul, Minnesota, United States
  • 1987–1991
    • University of Oregon
      • Department of Physics
      Eugene, Oregon, United States
  • 1415
    • The University of Edinburgh
      • School of GeoSciences
      Edinburgh, SCT, United Kingdom