cope4bg2020.copernicus.bg

II-nd National Workshop with international participation under the EU Copernicus programme 28 July and 6 October2020, Online Seminar

S a t e l l i t e i n f o r m a t i o n d o w n s c a l e d t o u r b a n a i r q u a l i t y i n B u l g a r i a – r e s u l t s f r o m t h e S I D U A Q p r o j e c t

Emilia Georgieva & SIDUAQ team

National Institute of Meteorology and Hydrology Space Research and Technology Institute , BAS

S I D U A Q ( 2 0 1 8 - 2 0 2 0 ) – G o a l & O b j e c t i v e s

http://space.bas.bg/SIDUAQ/

Analysis of satellite data for aerosols & gases

Particulate Matter at surface inferred by TROPOMI – S5p aerosol data

Assimilation of sat. data in BG Chemical weather forecast system (BgCWFS)

Improvement of local AQ model for Plovdiv & downstream of BgCWFS results

Expert modules of LAQMS for AQ management

Use of satellite data for atmo-spheric chemistry for air quality (AQ) management in BG

(1st time in BG)

S I D U A Q – v a l u e a d d e d p r o d u c t s

Satellites MetOps, S-5p AQ forecast: BgCWFS AQ forecast: Plovdiv

AQ experts modules

PM, NO2, SO2: analysis at national & city level

A n a l y s i s o f s a t e l l i t e d a t a f o r A Q o v e r B G

Analysis of seasonal pollution (AAI, NO2, SO2, PM) for Bulgaria and selected cities based on :

MetOp A, B and C monthly data (2007 – 2019)

Terra & Aqua images (2004 – 2018)

Sentinel–5P (01.-03.2019)

Monthly AAI from MetOp A - Plovdiv

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-0.5

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July

August

September

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2007

2008

2009

2010

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2012

2013

2014

2015

Averaged

Montly AAI (MetOp A) – Plovdiv

Monthly NO2 from MetOp A - Sofia

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Janu

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ruary

March

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Averaged

NO2 VCD monthly for Sofia

D a t a b a s e s f o r A A I / A O D f r o m S e n t i n e l – 5 p s

Algorithm for creation of database of TROPOMI-AAI and AOD for Bulgaria

Empirical relation

AAI AOD;

toolbox in ArcGIS

C o n v e r s i o n o f A O D t o P M 1 0 & P M 2 . 5

Statistical and determenistic models created based on data from S5p-TROPOMI and ground stations in Bulgaria from Jun’18 till Aug’19

models tested for different meteorological conditions

E x a m p l e s - m a p s o f P M c o n c e n t r a t i o n s

PM2.5 Winter day 18.02.2019

PM2.5 Summer day 28.06.2018

At time of satellite overpass hour 11-12AM

S a t e l l i t e d a t a f o r a t m o s p h e r i c c h e m i s t r y

- GOME 2 instruments on MetopA, MetopB & MetopC satellites: -AAI aerosol absorbing index -Vertical column densities of NO2 and SO2

AOD from 3 satellites on 21.Aug17 overpass time over BG ̴09:00 UTC

AAI is converted into AOD (aerosol optical depth) ~ Aerosol mass concentration

D a t a a s s i m i l a t i o n i n t h e B G C h e m i c a l W e a t h e r S y s t e m a t N I M H ( B g C W F S )

• Assimilation in model domains EU (81 km), Balkan (27 km)

• AOD, VCD_NO2&SO2

• Approach based on correction factors at time of satellite overpass Assimilation algorithm – similar also for

VCD_NO2 and VCD_SO2

E f f e c t o f s a t d a t a a s s i m i l a t i o n o n m o d A O D

Diff AOD – mean AUG’17

2 runs of BgCWFS: mod ( no assim.) sat (with assim.)

Diff AOD - daily

Diff AOD: AODsat – AODmod

E f f e c t o f s a t d a t a a s s i m i l a t i o n o n P M 1 0

PM10 mod PM10 sat

AUGUST 2017

Domain averaged values:

•PM10 increase by 105%

•PM2.5 increase by 128%

•NO2 decrease by -2%

•SO2 increase by 104%

Monthly mean concentrations in µgm-3

E f f e c t o f s a t d a t a a s s i m i l a t i o n o n P M 1 0

PM10 mod PM10 sat AUGUST 2017

Domain averaged values:

•PM10 increase by 117% NO2 increase by < 1%

•PM2.5 increase by 130% SO2 increase by 92%

Monthly mean concentrations in µgm-3

V a l i d a t i o n o f B g C W F S f o r A u g u s t 2 0 1 7

PM10 – against surface observations

Plovdiv Sofia Kopitoto*

obs sat

SAT: Significant improvement for PM and SO2

L o c a l A Q s y s t e m f o r P l o v i d - M o d i f i c a t i o n s

Downscaling algorithms from BgCWFS (Δx=9km) to LAQMS Plovdiv region (Δx=1km) and Plovdiv city (Δx=250m): 24 met and 8 chemical parameters.

Bottom-up emission inventory:

household heating (450 question.)

traffic data (22 street segments).

V a l i d a t i o n o f L A Q M S f o r F e b r u a r y 2 0 1 9

Meteorological parameters : observed by 3 stations Plovdiv (AMS_mean)

BgCWFS 10m

BgCWFS 4m

Wind speed m/s Temperature °C

Mean FEB 2019: Better performance for Temperature than for wind

BgCWFSsat + LAQMS:

Leads to PM10 increase by ~ 11%

Decrease in the relative error on avg by 56%

V a l i d a t i o n o f L A Q M S f o r F e b r u a r y 2 0 1 9

Urban Background

Urban Traffic

PM10 comparison to data from 2 AQ stations 1. Kamentiza (background) 2. Trakia (traffic)

E x p e r t m o d u l e o f L A Q M S

LAQMS: calculates the contribution from different emission sectors: household heating, traffic, industry & total concentrations

PM10 from Household heating PM10 from Traffic

Maps: PM10, PM2.5, NO2, SO2, BaP

Emission sector contribution

Comparison to limit values (Air Quality Directive 2008)

Number of exceedances

L A Q M S – E x p e r t M o d u l e

D E M O v e r s i o n s o f t h e t w o m o d e l s y s t e m s

http://meteorology.meteo.bg/siduaq/index.html

• For the first time in BG satellite data were used for AQ modelling at national and local scale

• A modelling chain was created in pseudo-operational mode for accounting of sat data (AOD, VCD NO2_SO2) in pollutant concentrations for the city of Plovdiv

• The approach is transferrable to other cities, details on local emissions are required

• The models output is presented on an interface with appropriate information for AQ management at Municipality level

• First attempts are made towards linking satellite aerosol index to surface particulate matter concentrations in Bulgaria

K e y m e s s a g e s

• http://meteorology.meteo.bg/global-change/content-en-23-2.html

P u b l i c a t i o n s & l i n k s

http://www.space.bas.bg/SES/archive/SES

%202019_DOKLADI/contentsBG.html

http://space.bas.bg/SIDUAQ/index.html

http://meteorology.meteo.bg/siduaq/

• Financial support of SIDUAQ project: “Satellite Information Downscaled to Urban Air Quality in Bulgaria” funded by ESA and the Government of Bulgaria through ESA Contract No.4000124150/18/NL/SC

• Special thanks to providers of satellite data ( ESA, EUMETSAT and NASA /LANCE) and to CAMS for model results

A c k n o w l e d g e m e n t s

Thank you for the attention ! emilia.georgieva@meteo.bg