An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe

An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe

<p>Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km <span class="inline-formula">×</span> 3....

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Autores principales: S. Liu, P. Valks, G. Pinardi, J. Xu, K. L. Chan, A. Argyrouli, R. Lutz, S. Beirle, E. Khorsandi, F. Baier, V. Huijnen, A. Bais, S. Donner, S. Dörner, M. Gratsea, F. Hendrick, D. Karagkiozidis, K. Lange, A. J. M. Piters, J. Remmers, A. Richter, M. Van Roozendael, T. Wagner, M. Wenig, D. G. Loyola
Formato: article
Lenguaje:EN
Publicado: Copernicus Publications 2021
Materias:
Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
Acceso en línea:https://doaj.org/article/25c54614be3d4a66bf7603d6aac8a46e
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id oai:doaj.org-article:25c54614be3d4a66bf7603d6aac8a46e
record_format dspace
institution DOAJ
collection DOAJ
language EN
topic Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
spellingShingle Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
S. Liu
S. Liu
P. Valks
G. Pinardi
J. Xu
J. Xu
K. L. Chan
A. Argyrouli
A. Argyrouli
R. Lutz
S. Beirle
E. Khorsandi
F. Baier
V. Huijnen
A. Bais
S. Donner
S. Dörner
M. Gratsea
F. Hendrick
D. Karagkiozidis
K. Lange
A. J. M. Piters
J. Remmers
A. Richter
M. Van Roozendael
T. Wagner
M. Wenig
D. G. Loyola
An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe
description <p>Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km <span class="inline-formula">×</span> 3.5 km (7 km <span class="inline-formula">×</span> 3.5 km before 6 August 2019). The DLR nitrogen dioxide (<span class="inline-formula">NO<sub>2</sub></span>) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric <span class="inline-formula">NO<sub>2</sub></span> retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric <span class="inline-formula">NO<sub>2</sub></span> on the viewing geometry by up to <span class="inline-formula">2×10<sup>14</sup></span> molec./cm<span class="inline-formula"><sup>2</sup></span>. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is <span class="inline-formula">3.5×10<sup>14</sup></span> molec./cm<span class="inline-formula"><sup>2</sup></span> in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric <span class="inline-formula">NO<sub>2</sub></span> at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured.</p> <p><span id="page7298"/>For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori <span class="inline-formula">NO<sub>2</sub></span> profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors.</p> <p>For the error analysis, the tropospheric AMF uncertainty, which is the largest source of <span class="inline-formula">NO<sub>2</sub></span> uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric <span class="inline-formula">NO<sub>2</sub></span> column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric <span class="inline-formula">NO<sub>2</sub></span> data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from <span class="inline-formula">−</span>55.3 % to <span class="inline-formula">−</span>34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to <span class="inline-formula">∼</span> <span class="inline-formula">−</span>20 %.</p>
format article
author S. Liu
S. Liu
P. Valks
G. Pinardi
J. Xu
J. Xu
K. L. Chan
A. Argyrouli
A. Argyrouli
R. Lutz
S. Beirle
E. Khorsandi
F. Baier
V. Huijnen
A. Bais
S. Donner
S. Dörner
M. Gratsea
F. Hendrick
D. Karagkiozidis
K. Lange
A. J. M. Piters
J. Remmers
A. Richter
M. Van Roozendael
T. Wagner
M. Wenig
D. G. Loyola
author_facet S. Liu
S. Liu
P. Valks
G. Pinardi
J. Xu
J. Xu
K. L. Chan
A. Argyrouli
A. Argyrouli
R. Lutz
S. Beirle
E. Khorsandi
F. Baier
V. Huijnen
A. Bais
S. Donner
S. Dörner
M. Gratsea
F. Hendrick
D. Karagkiozidis
K. Lange
A. J. M. Piters
J. Remmers
A. Richter
M. Van Roozendael
T. Wagner
M. Wenig
D. G. Loyola
author_sort S. Liu
title An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe
title_short An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe
title_full An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe
title_fullStr An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe
title_full_unstemmed An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe
title_sort improved tropomi tropospheric no<sub>2</sub> research product over europe
publisher Copernicus Publications
publishDate 2021
url https://doaj.org/article/25c54614be3d4a66bf7603d6aac8a46e
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spelling oai:doaj.org-article:25c54614be3d4a66bf7603d6aac8a46e2021-11-22T09:00:59ZAn improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe10.5194/amt-14-7297-20211867-13811867-8548https://doaj.org/article/25c54614be3d4a66bf7603d6aac8a46e2021-11-01T00:00:00Zhttps://amt.copernicus.org/articles/14/7297/2021/amt-14-7297-2021.pdfhttps://doaj.org/toc/1867-1381https://doaj.org/toc/1867-8548<p>Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km <span class="inline-formula">×</span> 3.5 km (7 km <span class="inline-formula">×</span> 3.5 km before 6 August 2019). The DLR nitrogen dioxide (<span class="inline-formula">NO<sub>2</sub></span>) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric <span class="inline-formula">NO<sub>2</sub></span> retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric <span class="inline-formula">NO<sub>2</sub></span> on the viewing geometry by up to <span class="inline-formula">2×10<sup>14</sup></span> molec./cm<span class="inline-formula"><sup>2</sup></span>. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is <span class="inline-formula">3.5×10<sup>14</sup></span> molec./cm<span class="inline-formula"><sup>2</sup></span> in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric <span class="inline-formula">NO<sub>2</sub></span> at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured.</p> <p><span id="page7298"/>For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori <span class="inline-formula">NO<sub>2</sub></span> profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors.</p> <p>For the error analysis, the tropospheric AMF uncertainty, which is the largest source of <span class="inline-formula">NO<sub>2</sub></span> uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric <span class="inline-formula">NO<sub>2</sub></span> column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric <span class="inline-formula">NO<sub>2</sub></span> data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from <span class="inline-formula">−</span>55.3 % to <span class="inline-formula">−</span>34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to <span class="inline-formula">∼</span> <span class="inline-formula">−</span>20 %.</p>S. LiuS. LiuP. ValksG. PinardiJ. XuJ. XuK. L. ChanA. ArgyrouliA. ArgyrouliR. LutzS. BeirleE. KhorsandiF. BaierV. HuijnenA. BaisS. DonnerS. DörnerM. GratseaF. HendrickD. KaragkiozidisK. LangeA. J. M. PitersJ. RemmersA. RichterM. Van RoozendaelT. WagnerM. WenigD. G. LoyolaCopernicus PublicationsarticleEnvironmental engineeringTA170-171Earthwork. FoundationsTA715-787ENAtmospheric Measurement Techniques, Vol 14, Pp 7297-7327 (2021)

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