EMEPTFMM Workshop on the review of the MSCE models on HMs and POPs 1314 October 2005, Moscow

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EMEP/TFMM Workshop on the review of the MSC-E
models on HMs and POPs 13-14 October 2005, Moscow
An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Torunn Berg, Knut Breivik, Wenche Aas, Stein
Manø, Jan Schaug, Hilde T. Uggerud Chemical
Co-ordinating Centre (CCC)Norwegian Institute
for Air Research (NILU)
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Outline

• Introduction
• Monitoring data as a tool for model
  parameterisation, evaluation and validation
• HMs
• EMEP data
• Additional data
• POPs
• EMEP data
• Additional sources of relevant monitoring data
• Scientific literature (examples)
• Other international monitoring efforts (UNEP)
• Summary

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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Monitoring data with respect to model
applicability

• Monitoring data may be used by modellers for
• Model parameterisation (e.g. definition of
  boundary conditions)
• Model evaluation / validation (for comparison of
  various features of model performance against
  real life)
• Monitoring data can be assessed in terms of model
  applicability on the basis of various features
• Spatial trends
• Temporal trends (annual, seasonal, diurnal)
• Speciation features (physical / chemical state)
• Absolute concentration levels
• Multimedia features (POPs and Hg)

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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy Metals EMEP data in 2003
65 sites, 23 co-located
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Mercury EMEP data in 2003
15 sites, 3 co-located (mainly OSPAR / CAMP or
AMAP)
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals EMEP data in 2003 (annual averages)
Pb (µg/l)
Pb (ng/m3)
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals EMEP data in 2003 (annual averages)
Cd (µg/l)
Cd (ng/m3)
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals EMEP data in 2003 (annual averages)
Hg (ng/l)
Hg (ng/m3)
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals EMEP data QA/QC

• 15 EMEP laboratories
• Pb, Cd, Cu, Zn, As, Cr, Ni
• 2 low conc. Samples
• 2 high conc. Samples repr.
• Southern Scandinavia and Central Europe

www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals EMEP data QA/QC
Average percent error (absolute) in low and high
conc. samples
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals EMEP data QA/QC
Median compared to expected values low conc.
samples
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals EMEP data QA/QC
Median compared to expected values high conc.
samples
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals Additional data Moss surveys
Years 1977 1985 1990 1995 2000 2005
Similar maps for Cd, Cr, Cu, Fe, Pb, Hg, Ni, V,
Zn
http//icpvegetation.ceh.ac.uk/metals_report_pdf.h
tm
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Heavy metals Additional data Moss surveys
Maps for Pb, Cd, As, Fe, Ni, V Year 1995
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Mercury Add. data Arctic Mercury Depletion
Events
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Mercury Add. data Arctic Mercury Depletion
Events
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Mercury Add. data Arctic Mercury Depletion
Events

• Spring campaign data from Alert, Ny-Ålesund,
  Barrow, Nord
• Summer campaign data from 2 cruises in the
  Arctic Sea
• (German 2004 and Swedish 2005)

Components measured GEM, RGM, Hg-P, total Hg and
methyl Hg in surface snow, Reemission data,
gradient data (within and above snow surface) DGM
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Mercury Add. data MOE and MAMCS
Wangberg et al. 2001 Atmospheric mercury
distribution in Northern Europe and in the
Mediterranean region. Atmos Environment 35,
3019-3025
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Mercury Add. data Med Oceanor
Sprovieri et al. 2001 Dynamic processes of
mercury and other trace contaminants in the
marine boundary layer of european seas - ELOISE
II Atmos Environment 37, 63-71
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Discussion Heavy metals

• EMEP particularly suited for model evaluation
  purposes
• Long-term and seasonal trends
• QA/QC addressed, sampling and analytical
  protocols are known
• Country involvement
• EMEP monitoring data still suffer from
• Limited spatial resolution
• Uncertainties
• Other studies complement EMEP data with
• Spatial and temporal patterns
• Additional media coverage

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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs EMEP data in 2003
12 sites, 6 co-located (mainly OSPAR / CAMP or
AMAP)
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs EMEP data in 2002 (annual averages)
SPCB7 (pg/m3)
Relative contribution of PCBs
South
North
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs EMEP data QA/QC

• 27 laboratories showed interest (21 submitted
  results)
• 19 PAHs and 14 Organochlorines (DDTs,
  Chlordanes, HCHs, HCB, PCBs)
• Round 1
• Two ampoules with PAHs (known and unknown
  concentrations)
• Two ampoules with OCs (known and unknown
  concentrations)
• Round 2
• Two real pooled hi-volume extracts (GFFs PUFs)

www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs EMEP data QA/QC
Round 1 Statistical overview for OCs
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs EMEP data QA/QC
Round 1 PCB-153 as an example
www.nilu.no/projects/ccc/reports.html
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs Additional data Passive air sampling
S29PCB

• Passive air samplers are suitable for evaluation
  of predicted spatial patterns in air
• Data reported for PCBs, PBDEs, HCHs, HCB, DDT,
  PAHs, PCNs (2002)
• Listen to the talk by Andy Sweetman in the POPs WG

Jaward et al 2004 Environ Sci Technol 38 34-41,
Jaward et al 2004 Environ Toxicol Chem 23
1355-1364
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs Additional data Precipitation (1980-2001)
Buijsman and Van Pul et al 2004 Water Air Soil
Pollut 150 59-71
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs Additional data Seasonal air
concentrations
Air concentrations of PCBs at 16 stations around
the Baltic Sea
Agrell et al 1999 Environ Sci Technol 33
1149-1156
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs Additional data Surface soil data

• Meijer et al reported on surface soil
  concentrations of PCBs in 191 soil samples from
  all over the world
• Suitable for evaluation of predicted spatial
  patterns in surface soil

Meijer et al 2003 Environ Sci Technol 37 667-672
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs Additional data Initiatives related to
UNEP
http//www.chem.unep.ch/gmn/GuidanceGPM.pdf /
GAPS Information kindly provided by Karla Pozo
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
POPs Additional data GAPS / UNEP

• Target OCPs (20 compounds)
• a-, ß-, ?-, d-HCHs
• aldrin, dieldrin, heptachlor, heptachlor epoxide
• cis-chlordane, trans-chlordane, trans-nonachlor,
• endosulfan I, endosulfan II, endosulfan sulphate,
  
• o,p-DDE p,p-DDE, o,p-DDD, p,p-DDD, o,p-DDT,
  p,p-DDT.
• Polychlorinated biphenyls (PCBs) (49 congeners).

GAPS Information kindly provided by Karla Pozo,
Environment Canada
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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Passive air sampling campaign for POPs (EMEP,
2006)

• Objectives
• To gain new insight into the spatial patterns of
  POPs in background air using a consistent
  sampling and analytical methodologies
• To evaluate limitations of the current EMEP
  measurement network with respect to spatial
  coverage
• To evaluate the use of passive air samplers as a
  complementary and cost efficient tool with
  respect to possible future monitoring strategies
  within EMEP
• To improve models by supporting model validation
  exercises at MSC/E (and beyond)
• Selected POPs Combustion-derived POPs (PAHs),
  Industrial chemicals (PCBs), Pesticides (HCHs,
  HCB), New POPs (PBDEs)
• Countries of the Eastern Europe, Caucasus and
  Central Asia (EECCA) are particularly welcome to
  take part in this exercise

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An evaluation of monitoring data for HMs and POPs
with emphasis on model applicability
Discussion - POPs

• EMEP data seem particularly suited for model
  evaluation purposes with respect to the
  atmospheric features governing the fate of POPs
• Hi-volume air samples (absolute concentration
  levels)
• Long-term and seasonal trends
• Congener/isomer patterns
• QA/QC addressed, sampling and analytical
  protocols are known
• Country involvement
• However, EMEP monitoring data still suffer from
• Limited spatial (and temporal) resolution
• Significant uncertainties
• Limited media coverage
• Other studies complement EMEP data with
• Spatial and temporal patterns
• Additional media coverage
• The UNEP Convention on POPs is likely to generate
  complementary monitoring data and knowledge of
  interest to EMEP.
• Interpretation of monitoring data from different
  sources (laboratories etc.) in the context of
  model evaluation must be done with caution
• A campaign using passive air samplers is planned
  for the EMEP network during the summer of 2006