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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Outline

Sensitivity and uncertainty analysis

Models intercomparison

Model results vs. measurements

Back trajectory analysis

Emission reporting for model application

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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


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


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


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


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


0.1 1 100.1

1

10

Mod

el,

g/L

Observed, g/L

Evaluation vs. observations


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


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


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


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


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


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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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


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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Documents

Uncertainties of heavy metal pollution assessment