space Ronald van der A Bas Mijling Jieying Ding Overview NOx inversion from concentrations to emissions algorithm description of DECSO Results of NOx inversion for specific regions China Korea South Africa Middle East Europe ID: 634070
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Slide1
NOx emission estimates from space
Ronald van der A Bas Mijling Jieying Ding
Slide2
Overview
NOx inversion: from concentrations to emissionsalgorithm description of DECSO
Results of NOx inversion for specific regions:China, Korea, South Africa, Middle East, EuropeSlide3
From concentrations to emissionsKalman
Filter applied to emissions:State vector (x): gridded emissionsNOx emission model (M): persistencyObservations (y): NO2 concentrations of OMI or GOME-2
Model for NO2 concentrations (H): Chimere + Averaging Kernel + gridding
Sensitivity of concentrations to emission changes (H): isobaric trajectory analysisSlide4
Properties of DECSO
*
Regional emissions estimates at a resolution of 25
25
km
2
Relatively
fast: Only one run of the CTM needed per time step
Emission updates by
addition instead of scaling: enables
detection new hotspots / relocation existing
hotspots
Update of NOx-correlated pollutants (CO, PM, SO2
)
Full error estimation (
Kalman
filter)
*
D
aily
E
mission estimates
C
onstrained by
S
atellite
O
bservationsSlide5
Overview DECSO
(4) Emission
update
(3) Inverse with
Kalman Filter
(1) Forward model run
(2) Sensitivity calculation
Mijling and Van der A (2012),
Daily emission estimates from space
, J. Geophys. Res.Slide6
Current projects on emission estimates from spaceSlide7
MarcoPolo: Monitoring and Assessment of Regional air quality in China using space
ObservationsMarcoPolo project
funded by the EU. Objectives:Monitoring air quality from spaceImproved
air quality modelling and forecasting by:New emission inventory
Emission estimates from satellitesGIS info, MEIC experienceValidation Air quality studies
Dissemination of MarcoPolo end productsSlide8
Scope of GlobEmission
Within the GlobEmission project emission estimates derived from satellite
observations are developed. Main advantages:spatial
consistency and high temporal resolutionpointing out/identifying flaws in bottom-up inventories
monitoring of emission changes, trends & new spots
rapid availability to usersThey provide complimentary information to bottom-up emission inventories
DUE project in 2011-2016Slide9
Committed end users
European Environmental AgencyLATMOS, FranceSatellite Environment Center of the Chinese
Ministry of Environmental ProtectionIndian Institute of Tropical MeteorologySouth African National
Space Agency + South African Weather ServiceNational Institute for Environmental Studies,
JapanQatar Environmental & Energy Research Institute
Specific
user requirements
:
Species:
NOx
, CH
4
, CO, NMVOC, SO
2
,
PM, O
3
Accuracy: better than 30% - 80 %
Spatial resolution: 1 km - 50 km
Time resolution: daily – annual
Regional and GlobalSlide10
Regional emissionsSlide11
Emissions forEast AsiaSlide12
Changes w.r.t. to apriori NOx EmissionsSlide13
North vs South KoreaSlide14
NOx
emission trends in East Asia
Mijling et al., Atmos. Chem. Phys., 2013Slide15
NOx emission estimates by DECSO:
The monthly NOx emission estimates by DECSO in Nanjing for 2013 and
2014, and the monthly NOx emission of the MEIC inventory of 2010. The shade areas show the
natural variability (rms) of the mean NOx
emission estimates from DECSO.
Ding et al., Atmos. Chem. Phys., 2015
Decrease
25
%Slide16
Emissions forSouth AfricaSlide17
Emission hot spots in South AfricaSlide18
EDGAR v4.2 2008
DECSO + OMI 2009-2010
Highveld
NO
x
emissionsSlide19Slide20
Majuba power plantSlide21
Matimba power plantSlide22
Sasol company
oil from coalSlide23
Emissions for theMiddle EastSlide24
NO
2
hot spots in the Middle EastSlide25
NO
2
hot spots in the Middle EastSlide26
NO
2
hot spots in the Middle EastSlide27Slide28
Emissions for theEuropeSlide29
NOx emissions in Europe
Preliminary!
MACC-II Emissions December 2009
DECSO v3b + OMI, December 2009Slide30
Thank you for your attention
!
Emission data available on
www.globemission.eu