Hester Volten, Ellen Brinksma, Stijn Berkhout, Daan Swart, René van der Hoff, Hans Bergwerff, Pieternel Levelt, Gaia Pinardi, Michel Van Roozendael NO.

Slides:

Advertisements

Similar presentations

Martin G. Schultz, MPI Meteorology, Hamburg GEMS proposal preparation meeting, Reading, Dec 2003 GEMS RG Global reactive gases monitoring and forecast.

Advertisements

Page 1 Tropospheric NO 2 workshop, KNMI, De Bilt NL, Sept 2007M. Van Roozendael Tropospheric NO 2 from space: retrieval issues and perspectives for.

Application of Cloudnet data in the validation of SCIAMACHY cloud height products Ping Wang Piet Stammes KNMI, De Bilt, The Netherlands CESAR Science day,

Using a Radiative Transfer Model in Conjunction with UV-MFRSR Irradiance Data for Studying Aerosols in El Paso-Juarez Airshed by Richard Medina Calderón.

IUP Heidelberg – NDACC/NORS Meeting – July Aerosol Profiling during CINDI Udo Frieß Henk Klein Baltink Katrijn Clémer Udo Frieß Hitoshi Irie Tim.

And a head sensor on a sun tracker What is PANDORA? Pandora is a small spectrometer system, which we have been developing since We now have over.

N emissions and the changing landscape of air quality Rob Pinder US EPA Office of Research and Development Atmospheric Modeling & Analysis Division.

Task Group 3 AT2 workshop, 30 Sept – 1 Oct 2008 Task Group 3 Achievements and Prospects Ankie Piters, KNMI.

Atmospheric Measurements at Capel Dewi field station Prof. Geraint Vaughan.

1 Surface nitrogen dioxide concentrations inferred from Ozone Monitoring Instrument (OMI) rd GEOS-Chem USERS ` MEETING, Harvard University.

Ground-based validation of SCIAMACHY OL 3.0 Ozone Profile Data and Estimation of Altitude Shift.

Comparison of the aerosol extinction coefficient retrieved from MAX-DOAS measurements to in-situ measurements P. Zieger 1, K. Clemer 2, S. Yilmaz 3, R.

Validation of OMI UV products: results of two ground UV measurement campaigns in Austria P. Weihs 1, M. Blumthaler 2, H. E. Rieder 1,3,*, A. Kreuter 2,

Irie et al., Multi-component retrievals for MAX-DOAS, 2 nd CINDI workshop, Brussels, March 10-11, 2010 Multi-component vertical profile retrievals for.

High vertical resolution NO 2 -sonde data: Air quality monitoring and interpretation of satellite-based NO 2 measurements D. C. Stein Zweers, A.Piters,

Introduction A new methodology is developed for integrating complementary ground-based data sources to provide consistent ozone vertical distribution time.

1. The MPI MAX-DOAS inversion scheme 2. Cloud classification 3. Results: Aerosol OD: Correlation with AERONET Surface extinction: Correlation with Nephelometer.

G O D D A R D S P A C E F L I G H T C E N T E R Goddard Lidar Observatory for Winds (GLOW) Wind Profiling from the Howard University Beltsville Research.

EARLINET and Satellites: Partners for Aerosol Observations Matthias Wiegner Universität München Meteorologisches Institut (Satellites: spaceborne passive.

M. Van Roozendael, AMFIC Final Meeting, 23 Oct 2009, Beijing, China1 MAXDOAS measurements in Beijing M. Van Roozendael 1, K. Clémer 1, C. Fayt 1, C. Hermans.

1 Satellite data assimilation for air quality forecast 10/10/2006.

Air Quality Forecasting Bas Mijling Ronald van der A AMFIC Annual Meeting ● Beijing ● October 2008.

Ankie Piters Royal Netherlands Meteorological Institute Ministry of Infrastructure and Environment Measuring vertical profiles and tropospheric columns.

AMFIC third progress meeting MariLiza Koukouli & Dimitris Balis Laboratory of Atmospheric Physics Aristotle University of Thessaloniki.

SCIAMACHY satellite validation during the field campaigns CINDI and TRANSBROM Enno Peters, Folkard Wittrock, Andreas Richter, Mark Weber and John P. Burrows.

BIRA-IASB station report

Institute of Environmental Physics and Remote Sensing IUP/IFE-UB Physics/Electrical Engineering Department 1 Measurements.

National Institute for Public Health and the Environment The RIVM mobile lidar during the CINDI campaign Stijn Berkhout, René van der Hoff, Hans Bergwerff,

MELANIE FOLLETTE-COOK KEN PICKERING, PIUS LEE, RON COHEN, ALAN FRIED, ANDREW WEINHEIMER, JIM CRAWFORD, YUNHEE KIM, RICK SAYLOR IWAQFR NOVEMBER 30, 2011.

AMFIC final meeting LAP/Auth validation activities Dimitris Balis & MariLiza Koukouli Laboratory of Atmospheric Physics Aristotle University of Thessaloniki.

Assessment of SBUV Profile Algorithm Using High Vertical Resolution Sensors Assessment of SBUV Profile Algorithm Using High Vertical Resolution Sensors.

Retrieval of Ozone Profiles from GOME (and SCIAMACHY, and OMI, and GOME2 ) Roeland van Oss Ronald van der A and Johan de Haan, Robert Voors, Robert Spurr.

Air Quality Forecasting in China using a regional model Bas Mijling Ronald van der A Henk Eskes Hennie Kelder.

1 Inferring Ground-level Nitrogen Dioxide Concentrations from OMI Martin Steinbacher, Empa Edward Celarier, SGT Inc. Eric Bucsela, NASA GSFC.

Intercomparison of OMI NO 2 and HCHO air mass factor calculations: recommendations and best practices A. Lorente, S. Döerner, A. Hilboll, H. Yu and K.

Comparison of OMI NO 2 with Ground-based Direct Sun Measurements at NASA GSFC and JPL Table Mountain during Summer 2007 George H. Mount & Elena Spinei.

Air Pollution/Environmental Technology laboratory Initial results on OMI NO 2 Validation during CINDI A contribution to the BIRA Cindi Workshop Yipin Zhou,

Validation of OMI NO 2 data using ground-based spectrometric NO 2 measurements at Zvenigorod, Russia A.N. Gruzdev and A.S. Elokhov A.M. Obukhov Institute.

Plans to study horizontal NO 2 distribution Ankie Piters, Tim Vlemmix, KNMI data from: INTA, IUPB, JAMSTEC, KNMI, Leicester, NASA Objectives: –Satellite.

Henk Eskes, OMI meeting June 2006 OMI Nitrogen Dioxide: The KNMI Near-Real Time Product Henk Eskes, Pepijn Veefkind, Folkert Boersma, Ronald van.

Retrieval of Vertical Columns of Sulfur Dioxide from SCIAMACHY and OMI: Air Mass Factor Algorithm Development, Validation, and Error Analysis Chulkyu Lee.

C. Lerot 1, M. Koukouli 2, T. Danckaert 1, D. Balis 2, and M. Van Roozendael 1 1 BIRA-IASB, Belgium 2 LAP/AUTH, Greece S5P L2 Verification Meeting – 19-20/05/2015.

OMI Nitrogen Dioxide Validation Overview Ellen Brinksma & Edward Celarier with inputs from many others (AO, NASA, …)

1 Monitoring Tropospheric Ozone from Ozone Monitoring Instrument (OMI) Xiong Liu 1,2,3, Pawan K. Bhartia 3, Kelly Chance 2, Thomas P. Kurosu 2, Robert.

1 Examining Seasonal Variation of Space-based Tropospheric NO 2 Columns Lok Lamsal.

Tropospheric NO2 Ronald van der A, Michel Van Roozendael, Isabelle De Smedt, Ruud Dirksen, Folkert Boersma KNMI and BIRA-IASB Beijing, 23 October 2009.

OMI Validation using the Pandora Spectrometer System Jay Herman, Nader Abuhassan, Alexander Cede 1.Validation of OMI satellite data for Ozone is fairly.

AMFIC Progress Meeting, Barcelona, 24 June Space-nadir observations of formaldehyde, glyoxal and SO 2 columns with SCIAMACHY and GOME-2. Isabelle.

Page 1 Envisat Validation Workshop, ACVT-GBMCD, GOMOS O 3 (r) 12/12/2002 ACVT-GBMCD subgroup GOMOS ozone profiles, analysis of comparison with GMBCD datasets.

Evaluation of model simulations with satellite observed NO 2 columns and surface observations & Some new results from OMI N. Blond, LISA/KNMI P. van Velthoven,

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Requirement: Provide information to air quality decision makers and improve.

 Methodology  Comparison with others instruments  Impact of daily AMF  Conclusions Tropospheric NO 2 from SAOZ F. Goutail, A. Pazmino, A. Griesfeller,

MAXDOAS observations in Beijing G. Pinardi, K. Clémer, C. Hermans, C. Fayt, M. Van Roozendael BIRA-IASB Pucai Wang & Jianhui Bai IAP/CAS 24 June 2009,

EOS-AURA Science Team Meeting September 2009, Leiden Comparison of NO 2 profiles derived from MAX-DOAS measurements and model simulations.

TEMPO Validation Capabilities Pandora NO 2 Total and tropospheric columns of NO2 from direct sun measurements -> column along a narrow cone (0.5 o ), actual.

Validation of OMI and SCIAMACHY tropospheric NO 2 columns using DANDELIONS ground-based data J. Hains 1, H. Volten 2, F. Boersma 1, F. Wittrock 3, A. Richter.

First results of the aerosol profiling group IUP Heidelberg BIRA-IASB MPIC Mainz IUP Bremen JAMSTEC WSU KNMI NIWA Univ. Leicester PSI TNO RIVM KNMI.

Satellite Remote Sensing of the Air Quality Health Index Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Lok Lamsal, Dalhousie University.

ESA :DRAGON/ EU :AMFIC Air quality Monitoring and Forecasting In China Ronald van der A, KNMI Bas Mijling, KNMI Hennie Kelder KNMI, TUE DRAGON /AMFIC project.

Page 1 OMI ST Meeting #11, KNMI, De Bilt, The Netherlands, June 2006 Validation of OMI trace gas products Main contributors (this work): Michel Van.

MAX-DOAS observations of tropospheric aerosols and formaldehyde above China Tim Vlemmix Francois Hendrick Michel Van Roozendael Isabelle De Smedt Katrijn.

OMI Nitrogen Dioxide Workshop Ellen Brinksma, Folkert Boersma.

Latmos UPMC/CNRS - ILRC 2015

DOAS workshop 2015, Brussels, July 2015

Quantifying uncertainties of OMI NO2 data

Intercomparison of SCIAMACHY NO2, the Chimère air-quality model and

Huailin Chen, Bruce Gentry, Tulu Bacha, Belay Demoz, Demetrius Venable

Intercomparison of SCIAMACHY NO2, the Chimère air-quality model and

Diurnal Variation of Nitrogen Dioxide

Satellite data assimilation for air quality forecast

Presentation transcript:

Hester Volten, Ellen Brinksma, Stijn Berkhout, Daan Swart, René van der Hoff, Hans Bergwerff, Pieternel Levelt, Gaia Pinardi, Michel Van Roozendael NO 2 lidar profiles measured during the DANDELIONS validation campaign 2006

“How representative is an OMI measurement for surface concentrations?” DANDELIONS Sept – Objectives O 3 : total column and profile (sondes) tropospheric contribution NO 2 : lower tropospheric profile (lidar) total columns (focus: pollution) MAXDOAS intercomparison Aerosol:radiosondes, CIMEL, SPUV, aethalometer CESAR site (Cabauw, °N, 4.927°E) many continuous measurements full meteorological info at location 2007 research questions (for NO 2 ): 1)Shape of NO 2 profiles (and influence on OMINO2) for industrial area 2) Homogeneity of the NO 2 field Dutch Aerosol and Nitrogen Dioxide Experiments for vaLIdation of OMI and SCIAMACHY Cabauw industry Clean air CESAR industry

Participating Institutes and Instruments OMI, SCIAMACHY RIVMNO 2 lidar, NO 2 in-situ monitors, boundary layer lidar BIRA-IASBMAXDOAS, Mini MAXDOAS IUP HeidelbergMAXDOAS (three directions) IUP BremenMAXDOAS NASA-GSFC Direct Sun Instrument (Pandora) KNMI Mini MAXDOAS, ozone sondes, radio sondes TNOSun photometers, volatility system, aethalometer, nephelometer, etc. Nine validation days on Sept 8-13, Data publicly available on AVDC

The third dimension : NO 2 lidar – ground level to about 2.5 km NO 2 in-situ monitor - on the ground and at 200 m Mini MAXDOAS - on the mast (200m)

Mobile NO 2 Lidar telescope Rapid switching between two wavelengths

How to Measure a Profile 300 m

NO 2 Lidar Measurements during the DANDELIONS campaign NO 2 profiles during overpasses – seven different elevations 0.75, 1.5, 3, 6, 12, 24, 90 deg, 1 azimuth (39 degrees) Spatial variations – two azimuths (39 and -36 deg), 1 elevation (12 degrees) Time variations – 1 azimuth (39 degrees), 1 elevation (12 degrees), long time series EXAMPLE: 12 SEPTEMBER in-situ monitor comparison Mini MAXDOAS heterogeneity

Overview of all NO2 lidar measurements September 2006 Profile assumed in OMI retrieval concentration NO 2 (  g/m 3 ) Altitude (m) Profile shape influences OMI retrieval

OMI L4 tropospheric columns 12 September-polluted day

NO 2 lidar profile compares well with in-situ data

0,1,2,3,4,5,6,8,10, 12,14,16,20,25,30 -10,-8,-6,-4,-3,-2,-1 Example Mini MAXDOAS measurement High sensitivity to the vertical NO 2 distribution in the lowest 200 m Zenith Julian day

Boundary layer growth NO 2 layer below 200 m NO 2 layer above 200 m

NO 2 lidar profile compares badly with in-situ data OMI overpass 12:47 UT

Heterogeneity on 12 September NO 2 lidar - different azimuth angles elevation 12 deg

Heterogeneity on 12 September NO 2 lidar - time series elevation 12 deg

Lidar values smaller or the same as in-situ values No problem Problem !

Lidar versus in-situ NH 3 interference in-situ monitors? No solution: Error through NH3 interference cannot be larger than 6%

Conclusions We had a hugely successful DANDELIONS campaign in Data is available on AVDC. NO 2 lidar profile shapes differ quite a lot from OMI assumption Concentrations on clear and polluted days show large variations, from ~3 to ~50  g/m 3 Heterogeneity in space and time is sometimes very large In-situ data and lidar data do not always agree