Model assessment of B(a)P pollution:
results for new EMEP grid and preliminary
analysis for Spain
Alexey Gusev, Victor Shatalov, Olga Rozovskaya, Nadejda Vulyh
Meteorological Synthesizing Centre - East
Introduction
 Special session of Steering Body to EMEP (2016) on B(a)P and Wood burning
- uncertainties of emissions factors,
- PAH pollution levels and trends,
- contribution of residential wood combustion and biomass burning (AIRUSE project)
 Spatial and temporal trends of B(a)P pollution
- updated information on emissions and observed concentrations
 Progress in evaluation of B(a)P pollution
- transition of modelling to the New EMEP grid
 Case study on B(a)P pollution in Spain
- preliminary results
Observed B(a)P concentrations in EMEP region (2005-2014)
• Observed B(a)P concentrations indicate stabilization of pollution levels in recent
decade
• In 2014 at 33% of stations annual mean B(a)P air concentrations were above the
EU target level 1 ng/m3
BaP in air, ng m -3
2.5
2.0
1.5
1.0
0.5
EU target level
0.0
Mean levels of B(a)P in air measured at
background, suburban, and urban sites
EEA AirBase measurements of
B(a)P for 2014
PAH emissions in the EMEP countries (2005-2015)
PAH emissions by sectors
 Largest contribution from
Residential combustion
1400
Other
1000
 Most of sectors show decrease
(9% - 36%)
800
J_Waste
600
B_Industry
400
L_AgriOther
200
C_OtherStatComb
 Emission from Residential
combustion is almost stable
0
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
200
PAH emission, t / y
150
100
50
0
% change from 2005 to 2015
Italy
56 %
Hungary
32 %
Germany
9%
Romania
5%
Poland
-18 %
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
PAH emission, t/y
1200
Five countries with largest emissions from Residential combustion sector
DE
PL
IT
RO
HU
Progress in model assessment of B(a)P pollution:
transition to the New EMEP grid
New EMEP grid
(0.2°x0.2°)
Modelled vs measured BaP concentrations at
background EMEP sites (2014)
Old EMEP grid
(50x50km)
Modeled, ng m
-3
1
0.1
0.01
New grid
Old grid
0.001
0.001
0.01
0.1
1
Observed, ng m-3
Old grid
New grid
Bias
-20 %
-5 %
Correlation
0.73
0.73
Model assessment of B(a)P pollution in Spain:
comparison with national measurements
New EMEP grid
(0.2°x0.2°)
Modelled B(a)P concentrations vs. data
of national and EMEP sites in Spain (2014)
EMEP
sites
Modelled, ng m
-3
1
Overprediction
0.1
0.01
National sites
EMEP sites
0.001
0.001
0.01
0.1
1
Observed, ng m-3
For some of the sites in Spain the model
overestimate observed B(a)P concentrations
Case study on B(a)P pollution in Spain
Case study for B(a)P was recommended by the recent Steering Body to EMEP
Objective: Analysis of B(a)P pollution levels in Spain using EMEP fine resolution
modelling and national data (measurements and modelling results)
Country-specific study activities
 Modelling using national emissions and scenarios
 Verification of modelling results with EMEP and national measurements
 Analysis of pollution levels using GLEMOS and CHIMERE modelling results
 Sector-specific and source-receptor modelling using national emissions
Data for the analysis
 National emissions with 0.1x0.1 resolution (2013, 2014)
 National measurements of B(a)P, EBAS, AirBase
 Modelling results of EMEP GLEMOS and CHIMERE models
PAH emissions in Spain: recent inventories
National inventories of 2015, 2016, and 2017
 Sectoral distribution (GNFR)
 Temporal coverage: 1990-2015
 No speciation PAH emissions
 B(a)P emissions: fraction B(a)P/4PAHs is based on emissions of other EMEP countries
4 PAH emissions of Spain
4 PAH emission, t/y
250
2013 (15)
2013(16)
2013(17)
200
150
100
50
Spatial distribution of annual B(a)P
emission fluxes (0.1°x0.1°), g/km2/y
th
er
O
an
sp
or
t
b
om
F_
Ro
ad
Tr
C
_O
th
er
St
at
C
B_
In
du
st
ry
L_
Ag
riO
th
er
0
Sectoral PAH emissions in Spain:
sector L ~ 70%
Spatial distribution of B(a)P emissions of Spain (2014):
key source categories
Agriculture (L)
Residential combustion (C)
Industry (B)
Road Transport (F)
Emissions from field burning of agricultural residues dominate in southern areas
Monitoring of PAH pollution levels in Spain
Monitoring network for B(a)P: about 150 sites for period 2005-2016
Type of sites: background, suburban, urban, traffic, industrial
Measured B(a)P concentrations do not indicate elevated levels in southern areas
Locations of B(a)P monitoring sites (2014)
background rural
background suburban
background urban
industrial
traffic
Spatial distribution of annual B(a)P
emission fluxes (0.1°x0.1°), g/km2/yr
PAH emission data versus measured air concentrations
Annual PAH emission flux
2
PAH emission, g/km /y
500
400
300
200
100
0
PT ES PL BE BG CZ IT DE CH FR CY
Spatial distribution of annual B(a)P emission
fluxes in EMEP region, g/km2/y (2014)
 Average emission flux is among
highest
 Observed B(a)P concentrations are
among lowest
B(a)P in air, ng/m
3
6
Measured B(a)P concentrations
(2013, EEA AirBase)
5
4
3
2
1
0
PL
CZ BG
IT
DE FR
CH CY BE ES
Model runs with varying contribution of emissions
from agriculture
Scenarios of B(a)P emissions for model simulations
 Base case: official emission data for 2014
 Scenario 1: sector L decreased 2-fold (lower value of em. factor, EEA GuideBook)
 Scenario 2: sector L decreased 20-fold (average % in emissions of other EMEP countries)
Other
F 1%
4%
C
10%
B
18%
Scenario 2
Scenario 1
Base case
Other
1%
L
67%
F
6%
L
50%
Other
2%
F
11%
C
16%
B
27%
C
29%
L
8%
B
50%
Model evaluation of B(a)P pollution in Spain (2014)
Setup of model simulations
 Meteorological data for modelling: generated using WRF for 2014
 PAH emissions (incl B(a)P): for 2014 (spatial distribution based on 2013)
 Two nested domains: EMEP region, fine resolution domain over Spain (0.1°x0.1°)
 Boundary conditions: generated using modelling over EMEP region
Modelled B(a)P air concentrations in the EMEP region and in Spain for 2014,
base case model run
Model runs with varying contribution of emissions
from agriculture
Base case
Scenario 1
100
0.7
0.6
Correlation
80
Bias, %
Scenario 2
60
40
20
0.5
0.4
0.3
0.2
0.1
0
0.0
Base case
Scenario 1
Scenario 2
Base case
Scenario 1
Scenario 2
Assumption of lower emissions from agriculture (L) results in lower
bias and higher correlation with measurements
Modelling results against measurements of
background monitoring sites
Results of model run with decreased emission from agriculture (Scenario 2)
ES1799A (background urban)
0.8
BaP in air, ng m-3
Obs
Mod
0.6
0.4
0.2
10
9
12
9
8
11
8
8
8
7
6
5
5
4
3
2
1
1
0.0
ES1425A
Obs
1.0
Mod
0.8
0.6
0.4
0.2
12
11
9
10
Months
7
7
6
5
5
4
4
3
2
2
1
0.0
1
Modelled and observed B(a)P
air concentrations (2014)
BaP in air, ng m-3
1.2
Seasonal variations of B(a)P concentrations
Modelling results against measurements of
background monitoring sites
Results of model run with decreased emission from agriculture (Scenario 2)
ES1615A (background suburban)
BaP in air, ng m-3
0.5
Obs
Mod
0.4
0.3
0.2
0.1
10
11
12
12
10
11
11
12
10
9
8
8
7
7
6
6
5
4
3
1
0.0
ES1819A (background urban)
0.5
Mod
0.3
0.2
0.1
9
Months
9
8
8
7
6
6
5
4
4
3
0.0
1
Modelled and observed B(a)P
air concentrations (2014)
BaP in air, ng m-3
Obs
0.4
Seasonal variations of B(a)P concentrations
Modelling results against measurements of background
monitoring sites
Area with significant disagreement between observed and modelled B(a)P air
concentrations in North-eastern part of Spain
Modelled, ng m
-3
1
0.1
0.01
0.001
0.001
0.01
0.1
-3
Observed, ng m
Modelled and observed B(a)P air concentrations for 2014, (Scenario 2)
1
Modelling results against measurements of background
monitoring sites
Area with significant disagreement between observed and modelled B(a)P air
concentrations in North-eastern part of Spain
Overestimation in
Barcelona
Modelled, ng m
-3
1
0.1
0.01
Underestimation in
mountainous areas
0.001
0.001
0.01
0.1
-3
Observed, ng m
Modelled and observed B(a)P air concentrations for 2014, (Scenario 2)
1
B(a)P pollution levels in North-eastern Spain:
possible reasons of disagreement
1. Uncertainties in spatial distribution of emissions
 Negative correlation between measurements and total emissions as well as
emissions from Residential Combustion
Emission (sector C), kg/y
 Larger emissions from Res. Combustion are likely occurred in rural areas rather
than in Barcelona urban area (Viana et al., 2016; EEA Report)
50
40
30
20
10
0
0
0.5
Observed, ng m -3
Emission from Residential Combustion vs observed B(a)P concentrations
1
B(a)P pollution levels in North-eastern Spain:
possible reasons of disagreement
1. Uncertainties in spatial distribution of emissions
 Larger emissions from Res. Combustion are likely occurred in rural areas rather
than in Barcelona urban area (Viana et al., 2016; EEA Report)
 Experimental scenario with modified spatial allocation for sector C (Res.Comb.)
Original and modified spatial allocation of B(a)P emission fluxes
B(a)P pollution levels in North-eastern Spain:
possible reasons of disagreement
1. Uncertainties in spatial distribution of emissions
 Larger emissions from Res. Combustion are likely occurred in rural areas rather
than in Barcelona urban area (Viana et al., 2016; EEA Report)
 Experimental scenario with modified spatial allocation for sector C (Res.Comb.)
 Model simulations with altered spatial distribution of sector C (Res.Comb.) result
in better agreement with measurements in Barcelona
Modelled, ng m
-3
1
0.1
0.01
0.001
0.001
0.01
0.1
-3
Observed, ng m
Modelled and observed B(a)P air concentrations, 2014
1
B(a)P pollution levels in North-eastern Spain:
possible reasons of disagreement
2. Uncertainties due to modelling approach
 Insufficient spatial resolution
 Effects of specific meteorological and complex terrain conditions (inversions)
may not were captured well
Modelled, ng m
-3
1
0.1
0.01
0.001
0.001
0.01
0.1
1
-3
Observed, ng m
Modelled and observed B(a)P air concentrations, 2014
Further analysis using refined emissions and finer spatial resolution is needed
Concluding remarks and further activity

Modelling with emission scenarios indicated possible uncertainties in PAH emission
data of Spain

Refinement of PAH/BaP emissions of Spain is appreciated in co-operation with
national experts and CEIP/TFEIP

It is planned to perform analysis of factors affecting modelling results on B(a)P:
parameters of degradation and deposition processes

Evaluation of pollution using GLEMOS and CHIMERE modelling results

Analysis of modelling results using measurements of B(a)P air concentrations for
episodes, concentrations in vegetation, source apportionment studies, etc.

Model evaluation of source-receptor relationships and contributions of individual
sectors to B(a)P pollution

Preparation of final report in co-operation with national experts and publication of
results in peer-reviewed journal