differential optical absorption spectroscopy (doas) optical absorption spectroscopy (doas) studi...

Differential Optical Absorption Spectroscopy

(DOAS)Studi atmosferici e monitoraggio ambientale

gruppo Energy Transfer & Minor Gases in the Atmosphere

(ETAMGA)ISAC-Bologna

Presented by: Ivan Kostadinov

ISAC, [email protected]

ISAC Lecce, Nov 18, 2010

Alcuni protagonisti dell’ISAC nella DOAS

Giorgio Giovanelli

Ivan Kostadinov

Elisa Palazzi

Andrea Petritoli

Fabrizio Ravegnani

Samuele Masieri

Margerita PremudaDaniele Bortoli

Franco Evangelisti

Ubaldo Bonafè

Paolo Bonasoni

Nei anni sulla DOAS (sw & hw) anno lavorato


INDICE

• Metodologia DOAS

• Strumentazione

• Studi atmosferici

• Monitoraggio ambientale

• Integrazione dati satellitari, DOAS, modelistici

• Conclusioni

There are sophisticate physical and chemical processes leading to radiative

transfer of incoming at the top of the atmosphere solar radiation and

chemical conversion between large variety of atmospheric constituents. All

these processes appear part of continuously changing Earth’s climate

system. The interplay between physical and chemical processes is extended

through all the atmosphere. However during last two decades a spacial

attention is given to stratosphere and troposphere due to their key role

regarding ozone layed depletion and air quality


Ozone production

O2 + h O + O (<242nm)

O2 + O +M O3 + M*

O3 + h O2 + O > 200 nm

O3 and NO2 chemistry

Environmental aspects:

For example, there is the belief that the

production of biodiesel from renewable

sources, helping to reduce the negative

impact of human activities on climate,

while the cultivation of crops increase

the production of N2O, especially in soil

enriched with nitrogen.


In the stratosphere, about 5% of the nitrous oxide (N2O) is oxidised by

meta-stable oxygen atom O(1D)

N2O + O(1D) → 2NO (1)

while the rest either undergoes photolysis under short-wavelength by

solar UV radiation

N2O + h → N2+O (2)

or participates in other chemical reaction channels.

During the day NO2 is firmly involved in the ozone destruction catalytic

cycle

NO + O3 → NO2+O2 (3)

NO2 + O → NO+O2 (4)

The participation of NO2 in this catalytic scheme is terminated by its OH

oxidation:

NO2 +OH +M → HNO3+M (5)

while during the night it is converted into N2O5 according to:

NO3 +NO2 +M → N2O5+M (6)

This last reaction is preceded by

NO2 +O3 → NO3 + O2 (7)


Beer-Lambert law (also called the Beer-Lambert-Bouguer law)

I() = Io().exp(-s().N.L)

Io() - incoming radiation,

s() - absorption cross-section

L, - optical path and

Ni - mean concentration of the absorber.

DOAS / 1


er() = sr (). Nair extinction coeff. Rayleigh scattering ( ~ - 4 )

em() = sm (). Nair extinction coeff. Mie scattering ( ~ - n , n=1÷ 4 )

t () = s().NL optical depth

Extinction = Absorbing + Scattering

t () = ln (Io() / I()) = L [ s()N + er() + em() ]

In the atmosphere there are simultaneosly presented different

kind of absorbers => sumation

= L [ Ssi()Ni + er() + em() ]

DOAS / 2


Absorption cross sections

High frequency structures - imprints of gases

Subject of DOAS (Platt and Stutz, 2008)

s() = s hf() + s lf()

SO2

t() = s().N.L = (s hf() + s lf()) .N.L = s hf() .N.L + s lf().N.L

t() = t hf() + t lf()

DOAS / 3


Changed Optical Depth due to

changed absorber

concentartion N

(Optical path L =const)

To define relative optical depth (rod) smoothing

procedures

* Polynomial fit (commonly used n = 4÷7)

* Digital smoothing

* Fourier transform

DOD

rod

)()()( sss iii -=Differential Abs. Cross Section

Column

content

Differential

Optical

Depth

=

-

i

iii LNI

I

I

I.).(

ln

ln 00 s

Differential optical depth concept / аDOAS / 4

Known parameter

(measurable or modeled)Measured

quantity


t diff() = s().N.L

N = tdiff() .(s().L )-1

Differential optical depth concept / b

Case1: One absorber

Seeked parameter

Known parameter

Case 2: More gases with not interfering structured abs.cs.

Case 3: More gases with interfering abs.cs.

=i

iidiff LN .).()( st

Multiple linear regression analysis is adopted

to solve the “DOAS master equation”

in respect to concentrations Niof absorbers along the optical path L

DOAS / 5


Spectroscopic effects Atmospheric scattering Others

Spectra superposition

Shift & stretch

Aliasing problems

Temperature dependence

of the gas absorption

cross sections

Stray light

Instrumental polarization

properties

Filling–in of the

Fraunhofer lines

( Ring effect )

AMF calculations

Cloud effects

Differences of the

photochemistry rates

Effects caused by

dynamical factors

– transport

– intrusions

– etc.

Factors influencing zenith sky DOASDOAS / 6


Species Wavelength

Range

(nm)

Detection

ppt

Path length

(km)

SO2 290 - 310 17 0.2

CS2 320 - 340 500 5.0

NO 200 - 230 240 0.2

NO2 330 - 500 80 5.0

NO3 600 - 670 2 5.0

NH3 200 - 230 800 0.2

HNO2 330 - 380 40 5.0

O3 300 - 330 4000 5.0

CH2O 300 - 360 400 0.2

Benzene 250 - 290 200 2.0

p-Xylene 250 - 290 100 2.0

Benzaldehyde 250 - 290 40 2.0

Ethylbenzene 250 - 290 560 2.0

Styrene 250 - 290 122 2.0

Trimethylbenzene 250 - 290 600 2.0

A list of gases that can be detected with DOAS methodology

and the wavelength interval within which they can be identified.

DOAS / 7


Advantages:

• Broad band features like Rayleigh and Mie scattering can be omitted.

• No absolute calibration need

• High specificity due to broad band spectra

• High sensitivity due to long path-lengths

• Possible simultaneous measurements of atmospheric species

Disadvantages:

• Sensitive to atmospheric turbulence.

• Limited number of molecules.

• Rain, snow, fog and clouds make measurements impossible.

Advantages and Disadvantages DOAS / 8


La strumentazione DOAS, prima di essere messa in modalità

operativa in campo si sottopone ad una procedura di

calibrazione mediante l’utilizzo di una cella, che viene riempita

con miscele di un gas inerte (azoto) e quantità note del gas da

calibrare (ad esempio NO2, SO2, ecc.)

L’obiettivo delle calibrazioni è assicurare la qualità dei dati

ottenuti durante le campagne di misura in campo.

Cella da 1m per calibrazione degli strumenti

DOAS preso del laboratorio ISAC-CNR, Bologna

Calibrazione / aDOAS / 9


Analisi DOAS di concentrazioni note di gas inserite nella cella di calibrazione:

Calcolo delle sezioni d’urto assolute e confronto con letteratura:

L

I

I

I

I

Cdiff

ss

lnln~

00

s

-

=

L

I

I

s

C~

ln 0

=

s

Retta di calibrazione per

misure di NO2 ottenute per

lo spettrometro TropoGAS.

DOAS / 10 Calibrazione / b

DOAS / 11 Polarisation

Diffraction grating efficency

Spectrometer polarisation plane

& solar plane

Laboratory tests for deriving of spectarl

polarisation sensitivity of GASCOD

instrument:

X axis - wavelength

Y axis – angle between instr.pol. plane and

direction of polarisation of incoming

radiation

Z axis – arbitrary unitsISAC Lecce, Nov 18, 2010


…….

"To summaries: molecular scattering consists of Rayleigh

scattering and vibrational Raman scattering. The Rayleigh

scattering consists of rotational Raman lines and the central

Cabannes line. The Cabannes line is composed of the Brillion

doublet and the central Gross or Landau-Placzek line. Non of

above is completely coherent.

The term 'Rayleigh line' should never be used“ (Young, 1981)

DOAS / 12 Ring effect / a

The molecular-photon interaction is a sophisticate quantum-mechanical

process leading to spatial redistribution of incoming radiation:

Reflection (scattered radiation at the (-1).angle of incidence;

Scattering – radiation emmited by the scatter in any arbitrary direction

Back-scatering - radiation emmited by the scatter in the direction of

incoming radiation

Polarization of the zenith scattered radiation

• Aerosol

• Molecular

DOAS / 13 Ring effect / b



Rotational Raman Scattering

DOAS / 14 Ring effect / c

anti-Stoks and Stocks N2 spectrum


Atmospheric Slit FunctionKostadinov et al., 1997

High

resolution

solar spectrum

convolved with ASF

DOAS / 15 Ring effect / d


DOAS / 16 Ring effect / e

Example GASCOD/A4p NO2

Systematic Errors

PermanentAbsolute abs.c.s. interp.

esp 1%

Variablecross. sec. temp. dependa.,

multiple scatteringb,refractionb

esv 3%

es = esp + esv 3.16%

Retreival Errors

Inside and outsidevortex

er 5% (for ozone)

Random Errors

Albedo variationsc

( 0.3<albedo<0.9

era 3%

Measurement Error 6.63%

•a)Max Planck Institute of Chemistry, University of Essen and the Research Center Karlsruhe, ``UV / Vis Spectra of atmospheric

constituents'', supplied by ATMOS User Centre, http://auc.dfd.dlr.de/search/index.html.

•b)A. Sarkissian, H. K. Roscoe, D. Fish, ``Ozone measurements by zenith-sky spectrometers: an evaluation of errors in air-mass factors

calculated by radiative transfer models,'' J. Quant. Spectrosc. Radiat. Transfer, 54, 471-480, 1995

•c)Calculation performed with AMEFCO model

DOAS / 17 Error analysis



The Sun & Earth’s Atmosphere

Environoment

Pollu

tion o

ver B

olo

gna


Ground – based DOAS instruments

Since August 1993

Stratospheric NO2 a.m. and p.m profiles

Monte Cimone /1



NO2 profiles over MtC retrived through natural sun

scanning of the stratosphere during whilight period

a.m.

p.m.

Ground – based DOAS instruments Monte Cimone /2

scdi (,) = Li (,)Ci (l) WFi (,) dl

AMFCO RTM model

WF – weighting functions

Ci – concentration in i-th layer

– SZA

A. Petritoli‟, G. Giovanelli‟, I. Kostadinov‟** ,

F. Ravegnani‟, D. Bortoli‟, P. Bonasoni‟, F.

Evangelisti‟,

U. Bonafe‟, F. Calzolari‟

Petritoli et al., 2002


…….

,)()(),( *

,

-

= dtttfbafW ba

,1

,

-=

a

bt

aba

Wavelet transformation:

with

ψ - mother wavelet b- shift, a - dilatation.

-0.8

0

0.8

-4 0 4t

=

Real part

Imaginary

part of

Amplitude spectrum:

),( baW

b)W(a,

b)W(a,arctan

Phase spectrum:



Stratosheric NO2 responce to short-term Solar activity (27-days cycle)

Ca II K-line Index (05) provided by The Big Bear

Solar Observatory (BBSO) http://www.bbso.njit.edu/

have been used as a proxy of 27-days solar

rotational activity

Longer periodicities in the time series were

removed by subtraction of the 41-day moving

average. Additionally, the series were then

smoothed by a 7-day boxcar, which filtered out

the high frequency noise up to periods of about

7 days



Wavelet transform (WT) is calculated from the time series adopting of

Mexican hat mother wavelet ( simple real function and the calculation of

WT is comparatively fast.


Kostadinov et al., 2010


Cross-correlation functions of NO2 CaII-K index for three

27-day cycles within 01.10.2002 – 30.12.2002.



Non-linear regression based only on synthetic predictors (sine and cosine functions).

where Ci is the amplitude of the annual, semiannual, solar and QBO induced

oscillations, Ti are the respective periods and Pi the relative phases of the

cosine functions. In order to fit this synthetic NO2 time series to the measured

monthly time series we used CAnnual, PAnnual, CQBO, PQBO, CSolar, CSemiAnnual,

PSemiAnnual, and Const, as free parameters while the periods and the phase of

solar cycle are kept fixed at the expected values (the latter is due to the fact

the time series does not cover two full period of solar cycle (about 22 years)).

Levenberg-Marquardt algorithm has been applyed to minimize the difference

between NO2sl(t) and NO2sl,model(t) (called residuals) choosing the free

parameters as independent variables.

• Data quality Check-up is carried out before the trend analysis.

Stratospheric NO2 trends over MtC


y = -0.0416x + 1904.1

y = -0.0277x + 1439.4

y = -0.0257x + 1434.2

y = -0.0229x + 1375.6

y = -0.0092x + 885.4

y = -0.0069x + 850.46

y = -0.0039x + 719.86

y = -0.0074x + 805.2

y = -0.0141x + 1040.7

y = -0.02x + 1205.7

y = -0.0163x + 1013.1

y = -0.0214x + 1163.4

200

300

400

500

600

700

800

900

31/01/1993 28/10/1995 24/07/1998 19/04/2001 14/01/2004 10/10/2006 06/07/2009

Date

NO

2 s

cd

*1

014 m

ole

c/c

m2

Jan Feb March Apr May

June July Aug Sept Oct

Nov Dec Lineare (Jan) Lineare (Feb) Lineare (March)

Lineare (Apr) Lineare (May) Lineare (June) Lineare (July) Lineare (Aug)

Lineare (Sept) Lineare (Oct) Lineare (Nov) Lineare (Dec)


Column typesMt. Cimone

(% per decade)

Jungfraujoch

(%per decade)

a.m. p.m. a.m. p.m.

Slant column, SZA = 90°, polynomial fit -8±2 -11±2 -14±2 -11±2

Salnt column SZA = 88°, polynomial fit -10±3 -10±2

p.m. slant / a.m. slant -7±1


• Spring-summer

incresaing of NO2 @

18-27 km and 27-42 km

• AMF decreases if bulk

altitude decreasing

• Stratosheric –

Tropospheric Exchange

events @ MtC are more

frequent in winter period

Negative trend is more

prononced for winter months.Kostadinov et al., 2010

Former studies: Petritoli et al., 2010Mean monthly a.m. NO2 trendover Mt.Cimone at SZA=88°


Since August 1999

@ Stara Zagora,

NO2 SCD at Stara Zagora, filt. data

0

200

400

600

800

1000

1200

01/1/

1999

01/1/

2000

31/12

/2000

31/12

/2001

01/1/

2003

01/1/

2004

31/12

/2004

31/12

/2005

01/1/

2007

01/1/

2008

31/12

/2008

31/12

/2009

01/1/

2011

Data

NO

2 S

CD

, 1

01

4 m

o/c

m2

NO2 p.m., med. filt.

NO2 p.m., low pass filt.

NO2 a.m., med. filt.

NO2 a.m., low pass filt.

Data series

Planetary wave activities around the

polar vortex and tropospheric anti-

cyclon led to formation of mini-hole

in Southern Europe, detected at

Stara Zagora, Werner et al., 2005

SCIAMACHY NO2

data validation

Ground – based DOAS instruments Stara Zagora / 1


…….

Signatures of stratospheric NO2 response to 27-day solar rotational cycle


1Å Ca K II index

used as a proxy

of solar UV

output.



Wavelet analysis of stratospheric NO2 slant column. 12-month features,

corresponding to annual cycle are well pronounced


Since Oct 2005 @ Accra/Tema

• Stratospheric measurements

• Satellite data validations

• Environmental monitoring

Ground – based DOAS instruments GHANA / 1



NO2 O3

NO2 and O3 daily variations in Tema Oil Rafenery (Ghana)

during teast measuremnts



SO2 daily variations in Tema

Oil Rafenery (Ghana) during

teast measuremnts. Higher

concentration are well

prononced towards North .


GASCOD @ TNB

Ground – based DOAS instruments TNB / 1

NO2 a.m.

2001O3 a.m.

2001

NO2 p.m.

2001

NO2 a.m.

2002

NO2 p.m.

2002

NO2 a.m.

2003

O3 p.m.

2001

O3 a.m.

2002

O3 p.m.

2002

O3 a.m.

2003Bortoli et al., 2000

Aircraft measurements / 1

GASCOD-A/4p

ACILA Retrieval Methodology

• Spectrally resolved actinic flux

• J(NO2) evaluation


Cl + O3 ClO +O2

BrO + O3 BrO + O2

BrO + ClO Br + Cl +O2

BrO derived by GASCOD-A4pi

measurements TROCINOX / Envisat

campaign, Brasil, 15.02.2005




Under daytime conditions in the stratosphere several reactions:

NO2+ h NO + O

NO + O3 NO2+ O

NO + ClO NO2+ Cl

with a time scale from a few minutes @ 20 km to a few seconds @ 30km,

lead to fast interchanging, so photochemical steady-state equilibrium takes

place here.

NO2 /NO ratio is almost constant during the day, e.g. @19 km it is 0.68 ±0.17

NO2/ NO = { k2[O3] + k3[ClO] } / J(NO2)

20000.00 24000.00 28000.00 32000.00 36000.00UTC,s

0.00 500.00 1000.00 1500.00 2000.00 2500.00

Ozone, (ppbv)

0.00

0.50

1.00

1.50

NO

2 /

NO

ratio

0

5

10

15

20

alt,

km

0

500

1000

1500

2000

2500

Ozo

ne

, (p

pb

v)

NO2 /NO ratio (open symbols & upper

horizontal O3 x-axis), linearly fitted

(dashed line), O3 measured by FOZAN

and M55 Geophysica altitude, during the

flight of 14th October 2002, Forli, Italy.

k2[O3] dominating factor linear trend


A New Generation of DOAS Spectrometer has been developed.


Bortoli et al., 2010


Il modello di trasferimento radiativo (RTM) MOCRA

• Obiettivo: simulazione delle misure DOAS multi-asse per calcolare gli Air

Mass Factors (AMF) (Premuda et al, in press 2010)

• Equazioni da risolvere

-

-

---

--=

s

s

rr s

rr

srksdsrQsd

srksdrrI

0 0

0

exp,

exp,,

I è la radianza, è la sorgente esterna, Q è un termine di sorgente

interna (trascurabile nell‟UV e nel visibile), k è il coefficiente di estinzione.

L‟AMF è definito come dove I e I* sono i valori di radianza

in presenza e in assenza del gas considerato, rispettivamente, e δa è lo

spessore ottico verticale di assorbimento della specie gassosa

considerata.

In modo analogo si definisce il boxAMF, cioè l‟AMF relativo ad una

regione atmosferica di altezza limitata hb

,sr

a

II

AMF

-=*ln

b

g

bb

g

bbb

g

bd

Id

hdn

Id

hdVCD

dSCDAMF

s

ln1ln1=-==

AMF / 1


Superficie che definiscono la suddivisione geometrica dell‟atmosfera

utilizzata dal modello

a )b )

c )d )

Multi-region 3D spherical geometry: a) a set of three cones with the vertex at the Earth

centre; b) vertical half planes having the z axis as intersection line with azimuth angle ψi and ψj

defined in (x,y) plane; c) a horizontal section of a possible geometry with three cones and 5, 7

half planes for the second and third cone, respectively; d) a vertical section with three cones of

aperture θ1, θ2, θ3 and ground heights h1, h2 and h3.

L‟utilizzo di questa suddivisione geometrica consente di considerare diverse regioni,

ciascuna con diversa altezza del suolo e con il proprio profilo atmosferico, mediante

l‟uso di opportune librerie esterne di costanti fisiche (coefficienti d‟interazione e

funzioni di fase)

AMF / 2


Il calcolo dell‟AMF (o del boxAMF) viene effettuato simulando

contemporaneamente nell‟ambiente di riferimento e in un ambiente

perturbato (in assenza del gas in esame), secondo uno schema “backward

Monte Carlo” le interazioni dei fotoni con l‟atmosfera. I grafici seguenti sono

riportati a titolo di esempio.

20 30 40 50 60 70 80 90 100

0

2

4

6

8

10

12

14

16NO

2 AMF

AOD AMF

exact AMF

AM

F

SZA (°)

O3 AMF

20 30 40 50 60 70 80 90 100

0

2

4

6

8

10

12

14

16

AOD AMF

exact AMF

SZA (°)

Comparison between correct and approximated formulas for

O3 and NO2 AMFs (λ=310 nm)

boxAMF di NO2 per il caso di misure al lembo da

satellite per diverse linee di vista (λ=310 nm,

SZA=68°)

AMF / 3

GASCOD tmulti-input 295- 700 nm ;

TEC CCD ; SR 0.5 nm;

Both active and passive mode

Cruise Ships flow rate emission

evaluated by means of passive

DOAS instrument placed at the

end of the Giudecca channel

Environmental monitoring / 1

ijjiijiij senuzCLF cos)( ,, = Flow rate, g/s


LOS: 60°,70°,75°,80°,84°,87°,88°,89°

29/10/2006 fine meteo conditions



Vertical columns, Profiles and Mapping

NO2 and O3 vertical columns are anticorrelated (photochemistry)

Maps of SO2 around a

target chimney derived

by means of 2D

scanning

(30.06.2008).



RTM & Inversion Methods / 1

Measurements for 2D and 3D reconstructions of pollutants

distribution

TOGART model

(Tomographic retrieval of GASOCD observations based on the

Algebraic Reconstruction Technique)


SIMULATIONS

Flight altitude: 2000 m

Aircraft velocity: 50 m/s

Scanning angles: 16

Scans: 17

Angle between 2 scans: 8°

Hor: 293 m

Vert: 285 m

SZA: 30°

RTM & Inversion Methods / 2

Imaging UV-VIS spectrometer

• Passive DOAS (Differential Optical Absorption Spectroscopy)• Inversion methods

• Tomography

Spectral range: 295 ÷ 485nm ( simultaneously examined), Spectral resolution: 0.6 ÷ 0.8 nm

Spatial cannels: 32

Scientific Products: column content of NO2, O3, BrO, SO3 etc., 2D mapping, tomography, etc

Status: In development, laboratory tests of the diffraction grating

Developed @ CNR-ISAC (Bologna, Italy)

Weight: ~ Opt.Unit < 5kg ~ Elect Unit < 5kg

Volume: ~ 0.08 m3

Power consumption: < 350 W

n.b. all parameters To Be Confirmed

Satellite data validation

Gas concentration profiling

Air Quality

DOAS measurements

2D mapping, tomography

GASCOD-A / 2-3D


Target parameters:

Weight: Opt.Unit < 5kg Elect Unit < 5kg

Power consumption: < 350 W

Time sampling: 0.1 ÷ 10 s

Spectral resolution: 0.6 ÷ 0.8 nm

Laboratory tests of single chanells

Applications

Gas profiling

Gas Tomography

Satellite data validation

GASCOD-A / 2-3D

Specially designed

holographic

imaging grating

Imaging SpectrometerSpectral interval: 290 nm – 490 nm Input spatial optical chanells: up to 30

Measuring of diffuse solar radiance

Used for reconstarction of 2D e 3D spatial distribution of atmospheric minor gases (NO2, O3, BrO, etc. )

Data elaboration: DOAS (Differential Optical Absorption Specroscopy ) and Inversion Methods


An Italian Space Agency Pilot Project for

Monitoring, Forecasting and Planning

the Air Quality

www.quitsat.it

The experience of Italian research groups regarding air

quality and satellite observations were focalized into


QUITSAT is an Italian pilot project funded by the Italian Space Agency (ASI) and led by

Carlo Gavazzi Space (Prime Contractor) from 2006 to 2009, for developing a system

devoted to Air Quality (AQ) assessment through the fusion of observations coming from

polar and geostationary satellite sensors, ground-based data and CTM models

Project domain: Po valley area (Northern Italy)

The strategic objectives of QUITSAT Project were twofold:

• to promote in Italy the development of Earth Observation (EO) applications

(i.e. products and services based on satellite data)

• to study and implement application missions of pre-operational or operational type.

Therefore, the QUITSAT system was designed to:

• Explore the potential use of Earth Observation (EO) data.

• Fuse satellite data with ground-based remote sensing data from traditional technologies.

• Set up operational tools for Air Quality (AQ) management useful for decision makers.

• Take into account the Users role for priorities and requirements definition on AQ.


QUITSAT

Satellite Observations

•MODIS/EOS-Terra

•EOS-Aqua

•SCIAMACHY/Envisat

•SEVIR/MSG

•MOPITT/EOS/-Aura

Modelling

• Chem. Transp. 3D models (TCAM and CHIMERE)

• Stochastic and Deterministic Forecasting

• Integrated Assessment Mod. for AQ policies

Ground-Based Measurements

• Gas and PM in-situ sampling

• Sun–photometry and radiometry

• DOAS

• LIDAR

End User

• Requirements and System

Assessement provided by

Regional Italian EPA


Еstimation of near-surface NO2, HCHO, SO2, O3 concentrations

considering satellite and model data validated by means of ground-based

measurements

QM3 Product


SCIAMACHY/ENVISAT

[DOAS processor @ ISAC-CNR

(Petritoli et al., 2006)]

- NO2, O

3, HCHO, SO

2(tropospheric

column)

- resolution: 30km x 60km

-1 overpass / 3-6 days

- period: 2004

Earth Observations (EO)

OMI/AURA

provided by KNMI www.temis.nl

- NO2

(tropospheric column)

- resolution: 13km x 12km

- 1-2 overpass* / day

-period: field campaigns 2007-2008

QM3 Product


GAMES (Volta et al., 2006)

- vertical profiles of NO2, O

3, HCHO, SO

2etc.

- spatial grid: 10km x 10km

- hourly average

- photochemical model TCAM (Carnevale et al., 2008); meteo preprocessor

PROMETEO; emission processor POEMPM (Carnevale et al., 2008)

CTM

QM3 Product


The merging between satellite values and CTM simulations to get an improved ground

level NO2 concentration, is done according to the following steps:

i) the NO2 tropospheric column from satellite (CS) and its error (CS) are estimated using

DOAS technique;

ii) similar quantities are obtained from the GAMES model (CM and CM) by integrating

the vertical profile to get the tropospheric columns (the model vertical extension is up to

4km). All the CM whose central latitude and longitude match the satellite ground pixel

area are then averaged to get the final CM and CM is its variance.

iii) a corrected column (CC) is thus calculated using CM and CS according to the following

formula

CC is a weighted average between CM and CS where the respective errors are the

weights; a = 1/ CM , b = 1/ CS

iv) an average NO2 profile corresponding to the satellite ground pixel is calculated from

the model simulations and the respective column is scaled so to be equal to CC obtaining

then a corrected profile. The Ground Level concentration, thus Corrected, is considered

the final product (GLCNO2).

QM3 Product


Pixel SCIAMACHY

°° °° °

°

Stazioni ARPA

Pixel OMI

°° °°

Stazioni ARPA

GLC NO2 SCIAMACHY

GLC NO2(ug/m^3)

GLC NO2 da OMI

GLC NO2 (ug/m^3)

QM3 Product


B

A

Maps of (a) OMI NO2 tropospheric column amount; (b) GAMES NO2 ground level

concentration; (c) QM3 NO2 on March 13th 2008; and (d) QM3 NO2 averaged field in the

period from May 2007 to March 2008.

QM3 products, maps of ground-level gaseous concentrations


Improvement of the correlation (0.46 0.64) using QM3 product

(integrated satelliete and model data) instead model data.

QM3 Product

19 Feb 2008

NO2 ARPA vs. TCAM NO2 ARPA vs. QM3


Comparison DOAS-Long Path vs ARPA

QM3 Product C/V


Calculated partial tropospheric column is used to validate:

• modelled column over the stations. • Satellite tropospheric column (assumption: the main impact due to PBL, usually below 2 km in the stations area)

Mt. Cimone 44N, 10E, 2165 m a.s.l.

Bologna 44 N, 11E, 42 m a.s.l. - urban area

S.P.Capofiume 44 N, 11E, 10 m a.s.l. - rural area

NO2 (0-2 km) tropospheric column as a difference between two

DOAS measurements taken at different altitude.

QM3 Product C/V


Tropospheric NO2 vc (0-2 km)

derived from DOASV and

GAMES/TCAM February 2008.

Further improvements are

foresen:

e.g. 2D interpolation in order

to account NO2 horizontal

gradients (displacement of

DOAS station in respect the

center of the model pixel)

y = 1.3489x - 6E+15

R2 = 0.7293

1.0E+15

6.0E+15

1.1E+16

1.6E+16

2.1E+16

2.6E+16

1E+15 6E+15 1.1E+16 1.6E+16 2.1E+16 2.6E+16

TCAM NO2 tvc (molec/cm2)

DO

AS

N

O2 tvc

(m

ole

c/c

m2)

GAMES/TCAM profile is

integrated within the layer

defined by the diference of

altitudes of both DOAS stations

this risults in partial (0-2 km)

NO2 vertical column

QM3 Product C/V


2.00E+15

4.00E+15

6.00E+15

8.00E+15

1.00E+16

1.20E+16

1.40E+16

1.60E+16

1.80E+16

2.00E+16

12 12.5 13 13.5 14 14.5 15

Local time, h

NO

2 c

olo

na

tro

po

sf

(0-2

km

), m

ole

c/c

m2

7.58E15

6.68E15

OMI over-pass

t1

t2

Averagging of the ground-based data:

• t0 ± t1, t

0± t

2, ….. ?

• Symetry of the variations in respect to the satellite over-pass

QM3 Product C/V


Bologna

1.00E+13

5.01E+15

1.00E+16

1.50E+16

2.00E+16

2.50E+16

3.00E+16

3.50E+16

0 50 100 150 200 250 300

MaxDist, km

NO

2 tvc O

MI,

mo

lec/c

m2

04/02/2008

10/02/2008

16/02/2008

21/02/2008

24/02/2008

21/02/2008 Bologna station

Ferrara

1.00E+13

5.01E+15

1.00E+16

1.50E+16

2.00E+16

2.50E+16

3.00E+16

3.50E+16

0 50 100 150 200 250 300

Max Dist, km

NO

2 t

vc O

MI,

mo

lec/c

m2

04/02/2008

10/02/2008

21/02/2008

24/02/2008

16/02/2008

OMI

NO2 (0-2 km) in function of the

max distance (Dmax) between

selected DOAS station and the

most distant corner of the

satellite pixels for given range.

QM3 Product C/V

Decreasing of Dmax leads to

bad statistics: only very few

high resolution pixels remain

available.


Conclusions• Valuable expertise in the field of atmospheric studies:

- theory- instrumentation (ground-based, and aircraft deployments)- field facilities- data processing- modeling

•Satellite data validation ground-basedaircraft

•Environmental monitoring



References:Bortoli, D., et al., (2009). Ozone and nitrogen dioxide total columns and vertical distributions at the Italian Antarctic station during

1996-2008. In Rem. Sens. of Clouds and the Atmos. XIV, edited by Richard H. Picard, Klaus Schäfer, Adolfo Comeron, Evgueni

I. Kassianov, Christopher J. Mertens, Proceedings of SPIE Vol. 7475 (SPIE, Bellingham, WA 2009) 74751I.

Bortoli, D., et al., (2010). A new multipurpose UV-Vis spectrometer for air quality monitoring and climatic studies.

Int.J.Rem.Sens.Vol. 31, No. 3, 10 February 2010, 705–725

Carnevale C., et.al., (2008.). Design and validation of a multiphase 3D model to simulate tropospheric pollution. Science of The Total

Environment, 390, 166-176.

Giovanelli, G. et al., (1997). Performance of a diode array spectrometer in DOAS application. In: Spectroscopic Atmospheric

Monitoring Techniques. K.Schafer Eds. SPIE vol. 3106, 171-178.

Kostadinov, I., et al., (1997). Polarization and Ring Effects influences upon stratospheric DOAS measurements. Spectroscopic

Atmospheric Monitoring Tecniques. K.Schafer Eds. SPIE vol. 3106, 74-83.

Kostadinov, et al., (2010). The Solar Variability and its Impact on Atmospheric NO2 Slant Column Amount. 38th COSPAR Scientic

Assembly, 18 - 25 July 2010,Bremen, Germany, COSPAR paper number D21-0093-10.

Kostadinov et al (2010), Stratospheric NO2 trends over the high mountain „Ottavio Vittori‟ station, Italy. Int.J.Rem.Sensing, (in press).

Kostadinov et al (2010), The Solar Variability and its Impact on Atmospheric NO2 Slant Column Amount above Monte Comone. 38th

COSPAR Scientic Assembly, 18 - 25 July 2010.

Petritoli, A., et al., (2002). Tropospheric and Stratospheric NO2 Amount Deduced by Slant Column Measurements at Mt.Cimone

Station. Adv. Space Res. Vol. 29, No. 11, pp. 1691-1695.

Petritoli A., et al., (2004.) Study of the stratospheric NO2 trend at Mt. Cimone(44N, 11E), Italy: Evidence of the NAO Influence on the

Trace Gas Amount, poster, Quadrennial Ozone Symp. Kos, Greece, 1 - 8 June, 2004, ext. abs.abst. 422.doc:

http://www.qos2004.gr/.

Platt, U., and Stutz, J., (2008). Differential Optical Absorption Spectroscopy: Principles and Applications, Springer-Verlag, Berlin

Heidelberg, ISBN:978-3-540-21193-8. pp.1366–5901.

Premuda et al, (2009). A Monte Carlo simulation of radiative transfer in the atmosphere applied to ToTaL-DOAS" in Remote Sensing

of Clouds and the Atmosphere XIV, ed. Richard H. Picard, Klaus Schäfer, Adolfo Comeron, Evgueni I. Kassianov, Christopher

J. Mertens, Proceedings of SPIE Vol. 7475 (SPIE, Bellingham, WA 2009) 74751A.

Volta, M. and Finzi, G., GAMES, (2006). A comprehensive Gas Aerosol Modelling Evaluation System. Environ. Model. Software, 21,

587–594.

Werner, R., et al., (2006). NO2 column amount and total ozone in Stara Zagora (42°N, 25°E) and their response to the solar

rotational activity variation. Adv. Space Res., 37, 8, p. 1614-1620.

Young, A.T., (1981).Rayleigh scattering, App. Opt., v.20, pp.533-535.

http://www.qos2004.gr/








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