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13/06/2019
Adaptación de inventarios para modelización de la calidad del aire
Foro tecnológico. Bases científico técnicas para la mejora de la calidad del aire en España. Valencia, 11-13 Junio 2019
M. Guevara, Tena, C., Jorba, O., PérezGarcía-Pando, C.
Training and education
Monitoring
Interpretation
Modelling
Dissemination
https://www.nature.com/articles/d41586-018-06150-5
Training and education
Monitoring
Interpretation
Modelling
Dissemination
✓ Analysis of past events
✓ Forecast
✓ Support to planning andhealth impact studies
CALIOPE air quality systemProvides air quality information for the coming days and for the application of short term action plans for air quality managers.
Information is delivered using both
online or custom applications:
www.bsc.es/caliope
Smart city platform
Emissions requirements:
• Spatially distributed over a gridded domain
• Temporally resolved with (typically) an hourly resolution
• Mapped to the species defined in the atmospheric chemistry model (e.g. VOC, NOx)
Air quality modelling chain
Atmospheric chemistry
model
Meteorological model
Emissions
From global to local scales
Multi-scalemodels
• Global
• Regional
• Local
EMISSIONS: DIFFERENT NEEDS FOR DIFFERENT SCALES
Emission inputsNational emission inventories Gridded emission inventories Modelled emissions
X Not gridded (total national)
X Not hourly (annual)
X Not speciated
√ Gridded (fixed grid)
X Not hourly (annual, monthly)
X Not speciated
√ Gridded (any grid)
√ Hourly
√ Speciated
Emission processing systems:Adapt the emission data to the air quality model’s requirement
Emission models:Combine activity and
emission factors to estimate hourly, gridded emissions
HERMES: The high-Elective Resolution Modelling Emissions System
HERMES
(Baldasano et al., 2008)
HERMESv2
(Guevara et al., 2013)
HERMES-Mex
(Guevara et al., 2017)
HERMESv3
(Guevara et al., 2019)
Official Emission Dataset Spatial Allocation Vertical Allocation
Chemical Speciation Temporal Allocation
HERMES-Mex: An emission processing tool for Mexico
CMAQ ready emission data
HERMESv3
A python-based, open source and multiscale emission modelling framework that processes and estimates gas and aerosol emissions for
use in atmospheric chemistry models.
HERMESv3
A python-based, open source and multiscale emission modelling framework that processes and estimates gas and aerosol emissions for
use in atmospheric chemistry models.
global-regional module(HERMESv3_GR)
bottom-up module(HERMESv3_BU)
A processing system to calculateemissions through an automatic
combination of existing inventoriesand user defined vertical, temporal
and speciation profiles
An emission model to estimateemissions at the source level (e.g. road link) combining state-of-the-art bottom-up methods with local
activity and emission factors
Guevara et al. (2019a, GMD) Guevara et al. (2019b, in preparation)
HERMESv3_GR: global-regional module
• Combination of multiple up-to-date gridded emission inventories
• User defined destination working domain (multiple projections)
• Application of country-specific scaling and masking factors
• Temporal profiles per sector and pollutant
• Speciation profiles for multiple chemical mechanisms (CB05, RADM2, AERO5, AERO6)
• Outputs for multiple atmospheric chemistry models (CMAQ, WRF-Chem, MONARCH)
• Available at the BSC git repository: https://earth.bsc.es/gitlab/es/hermesv3_gr
HERMESv3_GR outputEmission data library
HERMESv3_GR: Spatial remappingUser defined destination working domain:• Conservative remapping (ESMF)• Multiple spatial resolutions• Multiple projections: regular lat-lon, rotated
lat-lon, mercator, lambert conformal conic
Rotated lat-lon(0.1*0.1 deg)
Lambert conformal conic
(4kmx4km)
Mercator(50kmx50km)
Regular lat-lon(1.4*1.0 deg)
HERMESv3_GR: Designing your experiment• Combination of multiple emission inventories• Application of country-specific scaling factors/masks
1
2
3
4
5
1 CAMS_REG_APv2.2.1
2 CAMS_REG_APv2.2.1 (EU)
3CAMS_REG_APv2.2.1 (EU) +
CAMS_GLOB_ANTv2.1 (rest)
4
CAMS_REG_APv2.2.1 (EU) +
CAMS_GLOB_ANTv2.1 (rest)
+ CAMS_GLOB_SHIPv1.1
5
CAMS_REG_APv2.2.1
(ESP*10, FRA*0.1) +
CAMS_GLOB_ANTv2.1 +
CAMS_GLOB_SHIPv1.1
HERMESv3_GR: Temporal distribution• Specific monthly, weekly and diurnal profiles per sector and pollutant• Use of gridded profiles (variation not uniform across the space)
0,0
1,0
2,0
3,0
4,0
1
30
59
88
11
7
14
6
17
5
20
4
23
3
26
2
29
1
32
0
34
9
Barcelona Oslo
0,0
1,0
2,0
3,0
4,0
5,0
1 2 3 4 5 6 7 8 9 10 11 12
Spain Germany
0,0
0,5
1,0
1,5
2,0
1 3 5 7 9 11 13 15 17 19 21 23
Barcelona Berlin
Monthly – NH3 fertilizers Daily – PM2.5 residential Hourly – NO2 traffic
HERMESv3_GR: Technical Implementation
1cpu: 1h20min 32cpu: 15min
Initialization Regrid Vertical Temporal Speciation WriteNoMore
sectors?
Yes
P_0 P_1 P_2 P_3
t0
t1
tn
t2
…
P_0 P_2 P_3
v0v1v2v3
vn
…
Test case:• Domain: Europe-North Africa-
Middle East (1021 x 721 cells)• Spatial resolution: 0.1x0.1deg• Vertical resolution: 48 layer• Emissions: TNO_MACC-iii (EU) +
HTAPv2 (others)• 24-h simulation
HERMESv3_GR: Code AvailabilityHERMESv3_GR code, test case and user guide available at BSC gitlab repository
https://earth.bsc.es/gitlab/es/hermesv3_gr
HERMESv3_BU: Bottom-up module
Criteria pollutants: NOx, CO, SO2, NMVOC, NH3, PM10, PM2.5
Greenhouse gases:CO2, CH4
HERMESv3_BU: Bottom-up module
HERMESv3_BU
Road transport
Exhaust
Non-exhaust
Point sources
Energy industry
Manufacturing industry
Agriculture
Fertilizers
Livestock
Crop operations
Residential Other mobile sources
Shipping in ports
Air traffic (LTO)
Agricultural machinery
Recreational boats
HERMESv3_BU: Input dataMore than 75% of the time spent building up an emission inventory is
devoted to compile and homogenise all the input data. There is a need to centralise all this information.
HERMESv3_BU: Road transportTraffic flow data (vehicle counts and speed)
Vehicle fleet composition
Emission factors (speed dependent)
Meteorological parameters
Temperature and precipitation to account for variation in evaporative/resuspension emissions
+ resuspension (Amato et al., 2011)
HERMESv3_BU: Fertilizers
Meteorology• Temperature• Wind speed• Growing Degree
DaysCultural techniques• N application rate• Crop calendars• Type of fertilizers• Type of application
Soil properties• PH• CEC
General information• Crop hectares• Land uses
0
20
40
60
80
100
120
1
19 37 55 73 91
10
9
12
7
145
16
3
18
1
19
9
21
7
23
5
25
3
27
1
28
9
30
7
32
5
34
3
36
1
t d
ay-1
Lleida
Barley Maize Wheat Others
0
20
40
60
80
100
120
1
19 37 55 73 91
10
9
12
7
14
5
16
3
18
1
19
9
21
7
235
25
3
27
1
28
9
30
7
32
5
34
3
36
1
t d
ay-1
South of Castilla Leon
Barley Maize Wheat Others
HERMESv3_BU: Livestock
Meteorology• Temperature• Wind speed
Cultural techniques• N excreta rate• TAN• Barn type• Storage type
General information• Number of animals
05
10152025303540455055
1
19 37 55 73 91
109
127
145
163
181
199
217
235
253
271
289
307
325
343
361
t d
ay-1
Murcia
Pigs Cattle Others
05
10152025303540455055
1
19 37 55 73 91
109
127
145
163
181
199
217
235
253
271
289
307
325
343
361
t d
ay-1
Galicia
Pigs Cattle Others
HERMESv3_BU: Other mobile sourcesShipping activities in ports Recreational boats in marinas
0,E+00
1,E+04
2,E+04
3,E+04
4,E+04
NOx SO2 CO NMVOC PM10 PM25
t /
year
Total annual emissions
Port activities Small Boats
HERMESv3_BU: Inter-comparisons
0,0E+00
1,0E+05
2,0E+05
3,0E+05
4,0E+05
5,0E+05
NOx CO NMVOC SOx NH3 PM10 PM2.5
Other stationary combustion [t/year]
HERMESv3 INESP 2015
0,0E+00
3,0E+04
6,0E+04
9,0E+04
1,2E+05
Aragon -Catalonia
Murcia
Total NH3 [t/year]
HERMESv3 IASIVan Damme et al. (2018, Nature)
Use of artificial intelligence to combine high resolution video-based traffic data with instantaneous emission models
Beyond the state-of-the art
0
100
200
300
400
500
0
10
20
30
40
50
60
20 40 60 80 100 120
NO
x (g
/h)
Spe
ed (
km/h
)Time (s)
speed PHEMlight
Beyond the state-of-the art
Use of GPS data from ships and data mining and machine learning techniques to assess very high resolution shipping emissions
THANK YOU!
www.bsc.es
HERMESv3 represents an effort to facilitate the use of emission inventories within the air quality modelling community
Next step: Engage and collaborate with key actors to develop a national emission tool that fulfils the needs of researchers, operational services,
administrations and companies
