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  1. Article ; Online: Air quality impacts of COVID-19 lockdown measures detected from space using high spatial resolution observations of multiple trace gases from Sentinel-5P/TROPOMI

    P. F. Levelt / D. C. Stein Zweers / I. Aben / M. Bauwens / T. Borsdorff / I. De Smedt / H. J. Eskes / C. Lerot / D. G. Loyola / F. Romahn / T. Stavrakou / N. Theys / M. Van Roozendael / J. P. Veefkind / T. Verhoelst

    Atmospheric Chemistry and Physics, Vol 22, Pp 10319-

    2022  Volume 10351

    Abstract: The aim of this paper is to highlight how TROPOspheric Monitoring Instrument (TROPOMI) trace gas data can best be used and interpreted to understand event-based impacts on air quality from regional to city scales around the globe. For this study, we ... ...

    Abstract The aim of this paper is to highlight how TROPOspheric Monitoring Instrument (TROPOMI) trace gas data can best be used and interpreted to understand event-based impacts on air quality from regional to city scales around the globe. For this study, we present the observed changes in the atmospheric column amounts of five trace gases (NO 2 , SO 2 , CO, HCHO, and CHOCHO) detected by the Sentinel-5P TROPOMI instrument and driven by reductions in anthropogenic emissions due to COVID-19 lockdown measures in 2020. We report clear COVID-19-related decreases in TROPOMI NO 2 column amounts on all continents. For megacities, reductions in column amounts of tropospheric NO 2 range between 14 % and 63 %. For China and India, supported by NO 2 observations, where the primary source of anthropogenic SO 2 is coal-fired power generation, we were able to detect sector-specific emission changes using the SO 2 data. For HCHO and CHOCHO, we consistently observe anthropogenic changes in 2-week-averaged column amounts over China and India during the early phases of the lockdown periods. That these variations over such a short timescale are detectable from space is due to the high resolution and improved sensitivity of the TROPOMI instrument. For CO, we observe a small reduction over China, which is in concert with the other trace gas reductions observed during lockdown; however, large interannual differences prevent firm conclusions from being drawn. The joint analysis of COVID-19-lockdown-driven reductions in satellite-observed trace gas column amounts using the latest operational and scientific retrieval techniques for five species concomitantly is unprecedented. However, the meteorologically and seasonally driven variability of the five trace gases does not allow for drawing fully quantitative conclusions on the reduction in anthropogenic emissions based on TROPOMI observations alone. We anticipate that in future the combined use of inverse modeling techniques with the high spatial resolution data from S5P/TROPOMI for all observed ...
    Keywords Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 550 ; 520
    Language English
    Publishing date 2022-08-01T00:00:00Z
    Publisher Copernicus Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Characterization of errors in satellite-based HCHO ∕ NO 2 tropospheric column ratios with respect to chemistry, column-to-PBL translation, spatial representation, and retrieval uncertainties

    A. H. Souri / M. S. Johnson / G. M. Wolfe / J. H. Crawford / A. Fried / A. Wisthaler / W. H. Brune / D. R. Blake / A. J. Weinheimer / T. Verhoelst / S. Compernolle / G. Pinardi / C. Vigouroux / B. Langerock / S. Choi / L. Lamsal / L. Zhu / S. Sun / R. C. Cohen /
    K.-E. Min / C. Cho / S. Philip / X. Liu / K. Chance

    Atmospheric Chemistry and Physics, Vol 23, Pp 1963-

    2023  Volume 1986

    Abstract: The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2 ) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios ...

    Abstract The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2 ) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO 2 + RO 2 ( LRO x ) to the chemical loss of NO x ( LNO x ). Subsequently, we challenge the predictive power of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M11" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><mi mathvariant="normal">HCHO</mi><mo>/</mo><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">2</mn></msub></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="61pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="fb4bbb49a750a7ba45a0035537902178"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-1963-2023-ie00004.svg" width="61pt" height="14pt" src="acp-23-1963-2023-ie00004.png"/></svg:svg> ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to <math xmlns="http://www.w3.org/1998/Math/MathML" id="M12" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msub><mi ...<br />
    Keywords Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 511
    Language English
    Publishing date 2023-02-01T00:00:00Z
    Publisher Copernicus Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Validation of Aura-OMI QA4ECV NO 2 climate data records with ground-based DOAS networks

    S. Compernolle / T. Verhoelst / G. Pinardi / J. Granville / D. Hubert / A. Keppens / S. Niemeijer / B. Rino / A. Bais / S. Beirle / F. Boersma / J. P. Burrows / I. De Smedt / H. Eskes / F. Goutail / F. Hendrick / A. Lorente / A. Pazmino / A. Piters /
    E. Peters / J.-P. Pommereau / J. Remmers / A. Richter / J. van Geffen / M. Van Roozendael / T. Wagner / J.-C. Lambert

    Atmospheric Chemistry and Physics, Vol 20, Pp 8017-

    the role of measurement and comparison uncertainties

    2020  Volume 8045

    Abstract: The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO 2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC ...

    Abstract The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO 2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC (Network for the Detection of Atmospheric Composition Change) zenith-scattered light differential optical absorption spectroscopy (ZSL-DOAS) and multi-axis DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCDs have a small bias of ∼0.2 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow class="unit"><mi mathvariant="normal">Pmolec</mi><mo>.</mo><mspace linebreak="nobreak" width="0.125em"/><msup><mi mathvariant="normal">cm</mi><mrow><mo>-</mo><mn mathvariant="normal">2</mn></mrow></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="68pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="9bf84fbb0d1fee5cffd95a29110132fd"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-8017-2020-ie00001.svg" width="68pt" height="13pt" src="acp-20-8017-2020-ie00001.png"/></svg:svg> (5 %–10 %) and a dispersion of 0.2 to 1 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M6" display="inline" overflow="scroll" dspmath="mathml"><mrow class="unit"><mi mathvariant="normal">Pmolec</mi><mo>.</mo><mspace width="0.125em" linebreak="nobreak"/><msup><mi mathvariant="normal">cm</mi><mrow><mo>-</mo><mn mathvariant="normal">2</mn></mrow></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="68pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="f5188a8b62cdfcb0685e32f124f9c195"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-8017-2020-ie00002.svg" width="68pt" height="13pt" src="acp-20-8017-2020-ie00002.png"/></svg:svg> with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few peta molecules per square centimetre ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow class="unit"><mi mathvariant="normal">Pmolec</mi><mo>.</mo><mspace linebreak="nobreak" width="0.125em"/><msup><mi mathvariant="normal">cm</mi><mrow><mo>-</mo><mn mathvariant="normal">2</mn></mrow></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="68pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="f48b4429877e14d03a7b6b9b57b33a52"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-8017-2020-ie00003.svg" width="68pt" height="13pt" src="acp-20-8017-2020-ie00003.png"/></svg:svg> ) up to −10 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M9" display="inline" overflow="scroll" dspmath="mathml"><mrow class="unit"><mi mathvariant="normal">Pmolec</mi><mo>.</mo><mspace width="0.125em" linebreak="nobreak"/><msup><mi mathvariant="normal">cm</mi><mrow><mo>-</mo><mn mathvariant="normal">2</mn></mrow></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="68pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="d9ae270deaf6403bcbfe9d8827ea49b8"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-8017-2020-ie00004.svg" width="68pt" height="13pt" src="acp-20-8017-2020-ie00004.png"/></svg:svg> ( −40 %) in one extreme high-pollution case. The QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data ( −1 to −4 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M13" display="inline" overflow="scroll" dspmath="mathml"><mrow class="unit"><mi mathvariant="normal">Pmolec</mi><mo>.</mo><mspace width="0.125em" linebreak="nobreak"/><msup><mi mathvariant="normal">cm</mi><mrow><mo>-</mo><mn mathvariant="normal">2</mn></mrow></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="68pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="b823a4bfb031009c7e02c1eeffe1cc2b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-8017-2020-ie00005.svg" width="68pt" height="13pt" src="acp-20-8017-2020-ie00005.png"/></svg:svg> ), which is a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite measurements and ground-based data greatly exceed the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and the difference in vertical smoothing and a priori profile assumptions.
    Keywords Physics ; QC1-999 ; Chemistry ; QD1-999
    Language English
    Publishing date 2020-07-01T00:00:00Z
    Publisher Copernicus Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS)

    Laeng, A / A. Dudhia / A. Keppens / B.M. Dinelli / C. Zehner / D. Hubert / G. Stiller / J.-C. Lambert / K.A. Walker / L. Froidevaux / M. Kiefer / P. Raspollini / T. Verhoelst / T. von Clarmann / U. Grabowski / V. Sofieva

    Remote sensing of environment. 2015 June 01, v. 162

    2015  

    Abstract: The MIPAS spectrometer onboard the Envisat platform observed infrared emission from the Earth's limb between 2002 and 2012. It recorded high-resolution spectra during day and night, from pole to pole and between 6 and 70km altitude in the nominal ... ...

    Abstract The MIPAS spectrometer onboard the Envisat platform observed infrared emission from the Earth's limb between 2002 and 2012. It recorded high-resolution spectra during day and night, from pole to pole and between 6 and 70km altitude in the nominal measurement mode or up to 170km in special measurement modes, producing daily more than 1000 vertical profiles of various trace gases. The operational Level-2 data are processed by ESA/DLR but there exist three other, independent research Level-2 processors that are hosted by ISAC-CNR/University of Bologna, Oxford University, and KIT IMK/IAA. All four Level-2 processors rely on the same Level-1b data provided by ESA but their retrieval schemes differ. As part of ESA's Ozone Climate Change Initiative project, an intercomparison of the four MIPAS processors took place, in which vertical ozone profiles retrieved by these four processors from MIPAS nominal mode measurements were compared for 2007 and 2008. We present the results of this comparison exercise, which consisted of five parts: an information content study of the vertical averaging kernels, an intercomparison of zonal seasonal means and spreads, a determination of biases through comparison to ozonesonde and lidar measurements, a comparison to other satellite records (bias estimation and precision assessment with respect to ACE-FTS and Aura-MLS data), and a geophysical validation of the provided error bars using MIPAS–MIPAS collocations.The four processors demonstrate similar performance. All processors use the same Level-1b data from ESA, apply global fits, and use microwindows instead of the full spectrum. The main differences in the processing schemes include the choice of microwindows, the regularization approach, the treatment of negative retrieved values, and the cloud detection threshold. The different regularization schemes lead to a different trade-off between noise and resolution, but without a clear average advantage for any particular data set. The vertical resolution is typically 3–5km and the single profile precision is about 2–3%. In the middle and upper stratosphere, at 25–45km, all four MIPAS processors clearly show a high bias of 2 to 5% relative to all reference instruments. The similarity of the structure and magnitude of the bias among the MIPAS data sets indicates that the bias is most likely linked to the use of microwindows of the MIPAS AB band. The satellite intercomparisons show furthermore that for the KIT dataset, the onset of the high bias starts at a somewhat higher altitude (only above 35km) than for the other three datasets. This is likely due to the more restrictive use of the AB band by the KIT processor, which comes at the cost of a coarser vertical resolution near the ozone volume mixing ratio (vmr) peak. In the troposphere, the Level-2 algorithms that suppress negative ozone values in the iterative retrieval process produce a larger positive bias than the algorithm that does not follow such a strategy. Our main conclusion is that the four MIPAS processors are more similar to each other than to any other reference instrument. This indicates that the observed biases are very likely instrument-related.
    Keywords algorithms ; altitude ; climate change ; data collection ; detection limit ; gases ; geophysics ; indole acetic acid ; interferometers ; lidar ; mixing ; ozone ; remote sensing ; satellites ; seeds ; spectrometers ; stratosphere ; troposphere
    Language English
    Dates of publication 2015-0601
    Size p. 316-343.
    Publishing place Elsevier Inc.
    Document type Article
    ZDB-ID 431483-9
    ISSN 0034-4257
    ISSN 0034-4257
    DOI 10.1016/j.rse.2014.12.013
    Database NAL-Catalogue (AGRICOLA)

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  5. Article ; Online: Round-robin evaluation of nadir ozone profile retrievals

    A. Keppens / J.-C. Lambert / J. Granville / G. Miles / R. Siddans / J. C. A. van Peet / R. J. van der A / D. Hubert / T. Verhoelst / A. Delcloo / S. Godin-Beekmann / R. Kivi / R. Stübi / C. Zehner

    Atmospheric Measurement Techniques Discussions, Vol 7, Iss 11, Pp 11481-

    methodology and application to MetOp-A GOME-2

    2014  Volume 11546

    Abstract: A methodology for the round-robin evaluation and geophysical validation of ozone profile data retrieved from nadir UV backscatter satellite measurements is detailed and discussed, consisting of dataset content studies, information content studies, co- ... ...

    Abstract A methodology for the round-robin evaluation and geophysical validation of ozone profile data retrieved from nadir UV backscatter satellite measurements is detailed and discussed, consisting of dataset content studies, information content studies, co-location studies, and comparisons with reference measurements. Within ESA's Climate Change Initiative on ozone (Ozone_cci project), the proposed round-robin procedure is applied to two nadir ozone profile datasets retrieved at KNMI and RAL, using their respective OPERA v1.26 and RAL v2.1 optimal estimation algorithms, from MetOp-A GOME-2 measurements taken in 2008. The ground-based comparisons use ozonesonde and lidar profiles as reference data, acquired by the Network for the Detection of Atmospheric Composition Change (NDACC), Southern Hemisphere Additional Ozonesonde programme (SHADOZ), and other stations of WMO's Global Atmosphere Watch. This direct illustration highlights practical issues that inevitably emerge from discrepancies in e.g. profile representation and vertical smoothing, for which different recipes are investigated and discussed. Several approaches for information content quantification, vertical resolution estimation, and reference profile resampling are compared and applied as well. The paper concludes with compliance estimates of the two GOME-2 ozone profile datasets with user requirements from GCOS and from climate modellers.
    Keywords Meteorology. Climatology ; QC851-999 ; Physics ; QC1-999 ; Science ; Q ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Earthwork. Foundations ; TA715-787
    Subject code 290
    Language English
    Publishing date 2014-11-01T00:00:00Z
    Publisher Copernicus Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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