Uncertainties of heavy metal pollution assessment
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Transcript of Uncertainties of heavy metal pollution assessment
TFMM & TFEIP Workshop, Dublin, 2007
Uncertainties of heavy metal pollution
assessmentOleg Travnikov
EMEP/MSC-E
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TFMM & TFEIP Workshop, Dublin, 2007
Outline
Sensitivity and uncertainty analysis
Models intercomparison
Model results vs. measurements
Back trajectory analysis
Emission reporting for model application
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TFMM & TFEIP Workshop, Dublin, 2007
Model sensitivity analysisPb and Cd total
depositionHg total deposition
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0.0 0.2 0.4 0.6 0.8 1.0
Anthropogenicemission
Natural and re-emission
Wind speed
Wetdeposition
Dry deposition
Aerosol size
Eddy diffusion
Boundaryconcentration
Cloud liquidwater content
Sensitivity coefficient
0.0 0.2 0.4 0.6 0.8 1.0
Boundary (GEM)
Anthrop. emission
Emission speciation
Natural and re-emission
Cloud water pH
Oxidation by O3 (gas)
Wet deposition
Dry deposition
Cloud LWC
Henry's constant Hg0
Oxidation by O3 (aq)
Boundary (TPM)
Oxidation by OH (gas)
Dry deposition (fog)
Dry deposition (GEM)
Aerosol solubility
Sensitivity coefficient
TFMM & TFEIP Workshop, Dublin, 2007
Model uncertainty
Lead and cadmium
0 20 40 60 80
Conc inair
Conc inprec
Totaldepos
Uncertainty, %
0 20 40 60 80
Conc inair
Conc inprec
Totaldepos
Uncertainty, %
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Uncertainty 30-40% Uncertainty 20-50%
Model intrinsic uncertainty without effect of emissions
Mercury
TFMM & TFEIP Workshop, Dublin, 2007
Review of MSC-E modelsWorkshop on review of MSC-E models on HMs and POPs (Moscow, 2005)
Purpose
to establish whether MSC-E models on HMs and POPs are state of the art and fit for the purpose of evaluating long-range transport of HMs and POPs.
Conclusions [ ECE/EB.AIR/GE.1/2006/4 ]
The model parameterization is appropriate for operational modelling of heavy metal concentration and deposition in Europe
HM depositions, concentrations and transboundary fluxes of HMs calculated by MSC-E model corresponded well with other transport models
Other models, such as the MSC-E model, underestimated air and precipitation concentrations of Pb and Cd when using official emission data
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Model intercomparison
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Cd air concentration (2000)
MSCE-HM
CMAQ
Comparison of MSCE-HM and CMAQ models for Pb and Cd
CMAQ (Community Multi-scale Air Quality model) – 3D chemical
transport model developed in US EPA
www.cmaq-model.org
Conditions of comparison: Anthropogenic emissions based on
official and ESPREME data Identical meteorological data for 2000 Similar initial and boundary conditions
TFMM & TFEIP Workshop, Dublin, 2007
Model intercomparison
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Annual mean Cd concentration in precipitation (2000)
based on ESPREME data
0.01 0.1
0.01
0.1
MSCE-HMCMAQ
Mod
el,
g/L
Observed, g/L
MSCE-HM = 0.62 ObsCMAQ = 0.68 Obs
30-40% underestimation
based on official data
0.01 0.1
0.01
0.1
MSCE-HMCMAQ
Mod
el,
g/L
Observed, g/L
MSCE-HM = 0.32 ObsCMAQ = 0.32 Obs
70% underestimation
TFMM & TFEIP Workshop, Dublin, 2007
Wind re-suspension of HMs
HM re-suspension scheme: Parameterization of mineral
dust suspension [Marticorena and Bergametti, 1995; Alfaro and
Gomes, 2001; Gomes et al., 2003]
Parameterization of sea salt aerosol production
[Monahan et al., 1986; Gong, 2003]
Detailed soil properties data [ISLSCP (Initiative II), http://islscp2.sesda.com]
Measured HM content in soil [FOREGS, Salminen et al., 2005]
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0
10
20
30
40
50
1990 1995 2000 2005T
ota
l em
issi
on
, kt/y
Re-suspension
Anthropogenic
Total emission and re-suspension of Pb in Europe
(1990-2005)
Contribution of Pb re-suspension: 20% in 1990, 60% in 2005
TFMM & TFEIP Workshop, Dublin, 2007
0.1 1 100.1
1
10
Mod
el,
g/L
Observed, g/L
Evaluation vs. observations
20-30% underestimation
Mod = 0.70 ObsCorr = 0.57
0.01 0.1
0.01
0.1
Mod
el,
g/L
Observed, g/L
Mod = 0.45 ObsCorr = 0.51
Lead
Annual mean concentration in precipitation based on official emissions data (2005)
Cadmium
30-50% underestimation
CdPb
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0.0
0.5
1.0
1.5
2.0
22
.04
.05
06
.05
.05
20
.05
.05
03
.06
.05
17
.06
.05
01
.07
.05
15
.07
.05
29
.07
.05
12
.08
.05
26
.08
.05
09
.09
.05
23
.09
.05
07
.10
.05
21
.10
.05
04
.11
.05
18
.11
.05
02
.12
.05
16
.12
.05
Air
con
cen
tra
tion
s, n
g/m
3
ObservedModelled (anthrop.+re-suspension)Modelled (anthrop.)
Analysis of discrepanciesDaily mean Cd concentration in air (2005)
Svratouch, Czech Republic (CZ1)
01.09.2005 06.11.2005
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0,00
0,05
0,10
0,15
0,20
Jan
Fe
b
Ma
r
Ap
r
Ma
y
Jun
Jul
Au
g
Se
p
Oct
No
v
De
c
Cd
co
nc.
in p
reci
pita
tion
, g
/ L
Modelled Observed
Neuglobsow, Germany (DE7)
0,00
0,05
0,10
0,15
0,20
Jan
Fe
b
Ma
r
Ap
r
Ma
y
Jun
Jul
Au
g
Se
p
Oct
No
v
De
c
Cd
co
nc.
in p
reci
pita
tion
, g
/ L
Modelled Observed
Kotinen, Finland (FI93)
Analysis of discrepanciesMonthly mean Cd concentration in precipitation
(2005)
Cd emissions in 2005
FI93
Density of back trajectoriesFebruary 2005
FI93
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0,00
0,05
0,10
0,15
0,20
Jan
Fe
b
Ma
r
Ap
r
Ma
y
Jun
Jul
Au
g
Se
p
Oct
No
v
De
c
Cd
co
nc.
in p
reci
pita
tion
, g
/ L
Modelled Observed
Kotinen, Finland (FI93)
Analysis of discrepanciesMonthly mean Cd concentration in precipitation
(2005)
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Cd emissions in 2005
FI93
FI93
March 2005
Density of back trajectories
TFMM & TFEIP Workshop, Dublin, 2007
2 10 502
10
50
SE14
Mod
el, n
g/L
Observed, ng/L
Hg
Mod = 0.78 Obs
0.5 1 2 40.5
1
2
4
PL5
Mod
el, n
g/m
3
Observed, ng/m3
Hg
Mod = 0.94 Obs
Evaluation vs. observationsHg concentration in air (2005)
Hg concentration in precipitation (2005)
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Zingst, Germany (DE9)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
01.0
1.05
15.0
1.05
29.0
1.05
12.0
2.05
26.0
2.05
12.0
3.05
26.0
3.05
09.0
4.05
23.0
4.05
07.0
5.05
21.0
5.05
04.0
6.05
18.0
6.05
02.0
7.05
16.0
7.05
30.0
7.05
13.0
8.05
27.0
8.05
10.0
9.05
24.0
9.05
08.1
0.05
22.1
0.05
05.1
1.05
19.1
1.05
03.1
2.05
17.1
2.05
31.1
2.05
Co
nc
en
tra
tio
n in
air
, ng
/m3 Observed Modelled
Westerland, Germany (DE1)
0
5
10
15
20
25
30
35
01.0
1.05
15.0
1.05
29.0
1.05
12.0
2.05
26.0
2.05
12.0
3.05
26.0
3.05
09.0
4.05
23.0
4.05
07.0
5.05
21.0
5.05
04.0
6.05
18.0
6.05
02.0
7.05
16.0
7.05
30.0
7.05
13.0
8.05
27.0
8.05
10.0
9.05
24.0
9.05
08.1
0.05
22.1
0.05
05.1
1.05
19.1
1.05
03.1
2.05
17.1
2.05
31.1
2.05
Co
nc
in p
rec
ipit
ati
on
, ng
/L Observed Modelled
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HM emissions reporting
Coverage of EMEP region with emission data for Pb (2005)
Reported Pb emission data for 2005:
Gridded data: 23 countries
Gridded sector data: 15 countries
National totals: 30 countries
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According to submission 2007
TFMM & TFEIP Workshop, Dublin, 2007
0
10
20
30
40
50
60
Germ
any
UK
Franc
eIta
ly
Spain
Poland
Russia
Ukrain
e
Tota
l em
issi
on
, t/y
Other
Waste Incineration
Metal Production
Fugitive Emissions from Solid Fuels
Agriculture/Forestry/Fishing
Residential
Commercial/Institutional
National Navigation
Road Transportation
Manufacturing Industries and Construction
Petroleum refining
Public Electricity and Heat Production
According to submission 2007
HM emissions by sectorsCd emissions in large European countries
(2005)
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Non-Party emission estimates
Comparison of official data with non-Party estimates of Pb emissions in 2000 (TNO,
ESPREME)Germany
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According to submission 2007
0
200
400
600
800
1000
EMEP TNO ESPREME
To
tal e
mis
sio
n, t
/y
Waste incineration
Road transport
Industrial processes
Industrial andresident.combustionPublic power
Germany
TFMM & TFEIP Workshop, Dublin, 2007
Emission uncertaintyEmissions data uncertainties reported by
countries (Pb)
Country Emission [t/y] Uncertainty
Austria 14 -52% +110%
Finland 24 -25% +26%
United Kingdom 118 -30% +40%
France 134 53%
Denmark 6 266%
Germany 107 ?
Russia 355 ?
Ukraine 195 ?
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Gaps of HM officially reported emissions data
Incomplete data on emission totals
Limited data on spatial distribution
No data on temporal variation
Scarce data on emission uncertainty
…
What data should be used to fill the gaps?
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Summary (1) Estimated intrinsic model uncertainty is 30-40% for Pb and
Cd and 20-50% for Hg
Modelling results are highly sensitive to emissions data for Pb and Cd and to boundary conditions for Hg
MSCE-HM and CMAQ models agree in underestimation of measurements (up to 70%) when officially reported emissions data is used
Assessment of wind re-suspension allows improve agreement between modelling results and measurements
Current model-to-measurement comparison demonstrates 20-30% underestimation for Pb and 30-50% underestimation for Cd. Modelling results for Hg well agree with observations
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Summary (2) Reported emission inventories for heavy metals are
incomplete and of limited value in terms of model applications
Procedure of the reported emission gaps filling is to be elaborated
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