Publication in AMT journal of “Minimizing aerosol effects on the OMI tropospheric NO2 retrieval – An improved use of the 477 nm O2-O2 band and an estimation of the aerosol correction uncertainty”

Our last research paper focused on the challenging topics of aerosol layer height (ALH) retrieval from hyperspectral visible measurements, aerosol correction, and tropospheric NO2 retrieval from satellite sensors like OMI was published in the Atmospheric Measurement Techniques (AMT) journal. This work relies on the activities achieved during the last months of my thesis research with my colleagues of the Geoscience and Remote Sensing (GRS) department of TU Delft and KNMI: Dr. J. Pepijn Veefkind, Dr. Johan de Haan, Dr. Piet Stammess, and Prof. Dr. Pieternel  F. Levelt.

This paper is based on the last developments we published during 2016, 2017, and 2018. During these years, not only the OMI cloud algorithm was improved (Veefkind et al., 2016), but also an OMI aerosol layer height (and optical thickness) neural network algorithm was developed (Chimot et al., 2017, 2018). This time, we directly evaluate the impacts of these developments to correct of aerosol absorption and scattering effects in the visible spectral range in view of retrieving tropospheric NO2, an important trace gas affecting air quality in urban and industrialised areas.

What are the main conclusions? Aerosol correction on tropospheric NO2 retrieval from OMI has been greatly improving the last 2-3 years for UV-Vis air quality satellites. Notably thanks to the updated effective cloud retrievals. But also there is a clear potential from the ALH based on the 477 nm O2-O2 band. However, the decision for the future processors is not necessarily easy to take: accuracy vs. radiance closure budget are clearly competing.

Gotten curious? See more information here.

I greatly thank my co-authors from the Netherlands for this very interesting work! This paper closes the loop of my whole research work achieved during the last 4 years with the Geoscience and Remote Sensing (GRS) department of TU Delft and KNMI.

f04
Average maps of MODIS AOD(550nm), OMI DOMINO NNvO2 and differences after applying the implicit (with OMCLDO2-New) or explicit (with NNMODIS,SSA=0.95) aerosol correction over China in summertime (June–July–August) 2006–2007. (a) MODIS AOD(550nm), (b) OMI DOMINO NNvO2, (c) OMI NNvO2 differences due to changes between OMCLDO2-New and DOMINO implicit aerosol corrections, (d) NNvO2 differences between explicit aerosol correction based on the NNMODIS,SSA=0.95 aerosol parameters (i.e. aerosol forward model assuming SSA = 0.95, MODIS AOD(550 nm) and retrieved ALH) and implicit aerosol correction implemented in DOMINO.

Improving aerosol correction of OMI tropospheric NO2 over China, based on a CALIOP climatology – Happy to co-author the work of Liu et al. (2019)!

screenshot 2019-01-03 at 22.25.42
Seasonal spatial distribution of tropospheric NO2 VCD in 2012 for (a) POMINO v1.1, (b) POMINO, and (c) their relative difference.

A very nice work by Mengyao Liu et al. (2019), from Peking University in Beijing, China, has just been published in the Atmospheric Measurement Techniques (AMT) journal, on which I am co-author!

This study evaluated the possibility to improve OMI tropospheric NO2 retrieval over China by creating and exploiting an aerosol vertical profile climatology database from 9 years of CALIOP observations. Among other elements, it shows the potential benefits to use satellite observations in a synergistic way (OMIMODIS-CALIOP) and how to constrain better aerosol models in view of correcting aerosol scattering and absorption effects in UV-vis satellite measurements.

This notably leads to an update of the POMINO dataset from Lin et al. (2014, 2015).

 

More information?

Retrieving aerosol height and tropospheric NO2 from OMI – Ebook Thesis online!

PhDBook
Research Thesis book cover – Julien Chimot – July 2018

Almost 3 months ago, on 2018.09.10, I had the privilege to defend my research thesis at Delft University of Technology. A big moment after 4 years of intensive collaboration with my colleagues of the Geoscience & Remote Sensing Department and KNMI and in the presence of several friends and relatives. An very strict protocol to follow according to the Dutch rules and tradition.

My thesis book is now available online as an Ebook here! Feel free to have a look if you are interested by aerosol layer height retrieval, UV-Vis satellite measurements such as OMI, tropospheric NO2, air quality and climate observations. My main papers are concatenated there.

Enjoy the reading!

A new paper submitted – Minimizing aerosol effects on the OMI tropospheric NO2 retrieval – An improved use of the 477 nm O2-O2 band and an estimation of the aerosol correction uncertainty

We recently submitted a new paper in the Atmospheric Measurement Techniques (AMT) journal. This work relies on the activities achieved during the last months with my colleagues of the Geoscience and Remote Sensing (GRS) department of TU Delft and KNMI: Dr. J. Pepijn Veefkind, Dr. Johan de Haan, Dr. Piet Stammess, and Prof. Dr. Pieternel  F. Levelt.

This paper is based on the last developments we published during 2016, 2017, and 2018. During these years, not only the OMI cloud algorithm was improved (Veefkind et al., 2016), but also an OMI aerosol layer height (and optical thickness) neural network algorithm was developed (Chimot et al., 2017, 2018). This time, we directly evaluate the impacts of these developments to correct of aerosol absorption and scattering effects in the visible spectral range in view of retrieving tropospheric NO2, an important trace gas affecting air quality in urban and industrialised areas.

Gotten curious? See more information here.

I greatly thank my co-authors from the Netherlands for this very interesting work! This paper closes the loop of my whole research work achieved during the last 4 years with the Geoscience and Remote Sensing (GRS) department of TU Delft and KNMI.

All_NO2Diffs_OMCLDONew
Statistics of relative tropospheric NO2 VCD changes in (%) in 2006-2007, due to differences between the different explicit aerosol corrections and the implicit aerosol correction based on OMCLDO2-New: (a), and (b): China summertime (June-July-August), (c), and (d): China wintertime (December-January-February), (e), and (f): South America biomass burning season (August-September).

A new paper published on OMI aerosol layer height retrieval from the O2-O2 visible band and neural networks – Comparison with CALIOP aerosol spatial patterns

I am very glad to have a new paper recently published in the Atmospheric Measurement Techniques (AMT) journal. This paper relies on a research work achieved during the last months with my colleagues of the Geoscience and Remote Sensing (GRS) department of TU Delft and KNMI: Dr. J. Pepijn Veefkind, Dr. Tim Vlemmix, and Prof. Dr. Pieternel  F. Levelt.

This paper is based on the work of 2017, in which a neural network algorithm was developed for retrieving aerosol layer height (ALH) from the OMI O2-O2 visible measurements. This time, we directly compare our retrievals with CALIOP aerosol observations and evaluate the spatial patterns on several remarkable case studies including urban pollution, biomass burning events and a Saharan dust outbreak!

Gotten curious? See more information here.

I greatly thank my co-authors from the Netherlands for this very interesting work!

Research / Science Homepage – Already 1 year! Thanks!

More than 1 year ago, I decided to share a bit more my on-going scientific activities. At that time, I was mostly working on OMI, aerosol layer height and tropospheric NO2 retrievals with my great colleagues at the Geoscience and Remote Sensing department of TU Delft. Now, I am at EUMETSAT working on Sentinel-3.

In a world that is continuously evolving, and where it is very difficult to find adequate information about our environment and used observations, my only hope was to share some news about my  topics of interest (trace gases, aerosol, air quality, climate), get more reliable information and increase (if possible) my network. I must admit that I was initially a bit skeptical.

But the numbers that I have now somehow surprise me: 3091 visits last year from some 1147 visitors. Since January, already 1127 views from 550 visitors! This may look very little for some people. But for me, this is quite significant! I have no idea whether people really got interest in my work and/or website, or just found a bit by chance some of the webpages.

What is for sure not a coincidence: 96 people connected with me via Twitter, most of them / you that I don’t really know, and regularly exchanging scientific news with me. And about 56 posts posted alone or with some friends!

I don’t know who you are, and whether you found my HomePage by chance. But for all the scientific news and exciting exchanges that I have, thank you! In spite of my restricted time, I will keep updating this Homepage and my Twitter account on a more or less regular basis!

The Earth observation science journey, using satellites, continues!

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Towards new horizons!

 

 

Recent findings from OMI Aerosol Layer Height Neural Network at EGU 2018 by GRS – TU Delft and KNMI

Our research works achieved with my colleagues from Geoscience & Remote Sensing (GRS) – TU Delft, and KNMI, before my leaving, will be presented via a poster at EGU 2018. In particular, recent findings and the last publication on the retrieval of aerosol layer height (ALH) from the OMI 477 nm O2-O2 band and using the developed neural network algorithm will be shown

Don’t miss the poster presentation by Prof. Dr. Pieternel Levelt on Monday 09.04 17:30 – 19:00 in Hall X5 at board number X5.170!

EGU2018
Recent results of OMI Aerosol Layer Height Retrieval over East China by Chimot et al. (2018) (just accepted for publication in AMT).

More information?

  • Abstract EGU2018 “Aerosol layer height from OMI and neural network – Evaluation and possibility of a 13-year time series?” here
  • Our recent papers published on this topic here
  • My former research activities performed with GRS-TU Delft and KNMI here
  • Aerosol WebPage here