Transcript Document

A HIGH RESOLUTION SPATIALLY EXPLICIT CONTINENTAL SCALE
MULTIMEDIA MODEL OF FATE AND TRANSPORT OF CHEMICALS
A.Pistocchi
D.Pennington
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Novel Methods for Integrated
Risk Assessment of Cumulative
Stressors in Europe
FP6
In the context of EC Environment
and Health Strategy
http://nomiracle.jrc.it
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NoMiracle Project
Commitment of DG-JRC for model development
• a novel multimedia fate and exposure model
with regionalised spatial resolutions at the
European level
• focus on improvements to the soil module by
using spatial data from the European Soils
Database
• various resolutions
• account for different temperate zones and
periods.
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FATE MAPPE
• FATE is an initiative aimed at providing crosscutting insights into the FAte of Chemicals in
Terrestrial and coastal ecosystems in Europe,
developed at the RWER Unit of EC- DG JRC,
Institute for Environment and Sustainability
• The acronym MAPPE stands for Multimedia
Assessment of Pollutant Pathways in Europe, and
is the Italian word to denote “maps”
• A GIS-based strategy for screening level modeling
of the fate and transport of chemicals over large
regions
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Coupling of environmental media
Atmosphere
Contaminant
Budget
sources
sources
Soil water budget
Erosion
Advection
Removal
Gas Abs+Deposition
Volatilization
Soil contaminant
budget
Stream network
+ lakes
Routing:
Stream network
+ lakes
loading
sources
Oceans
Removal
+ advection
Presentation at SETAC Europe 2005 - Lille
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FATE MAPPE
• The model accounts for the partitioning of
chemicals between phases, degradation,
advection through the different environmental
media (soil, inland water bodies, oceans, and
the atmosphere) and exchanges between
media due to atmospheric deposition,
volatilization and the contribution of soil
washoff to water discharges.
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FATE MAPPE
• The model is built in a geographic information
system (GIS) shell to manage data and to
perform simplified modeling through mapalgebraic and context analysis operators, such
as local drainage delineation, weighted
distance and zonal aggregation.
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FATE MAPPE
• This provides a spatially resolved multimedia
model suitable for the detailed simulation of
chemical concentrations from point and diffuse
sources of emissions for Europe.
• an efficient tool to compute concentrations from
emissions over large domains
• simplified conceptualization with limitations (e.g.
site-specific exposures to local sources).
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FATE MAPPE
• Spatial resolution is currently 1 km. The model
provides time dependent insights according generally
to monthly climatology. Landscape and climate
parameters required to perform calculations are
included as maps for model application. Among
distributed landscape and climate parameters, inland
water retention times, atmospheric advection and
deposition terms, soil properties and ocean
circulation have been defined based on specific
analyses.
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Algorithms
• Thanks to source receptor relations in space and
time, atmospheric modeling is performed through
map-overlaying of standard plumes generated
within the ADEPT model (Roemer et al., 2005)
• Soil: 1D approach
• Water-column processes in oceans: 1D approach
• Input to oceans from the river network:
penetration depth approach (exponential decay
following a weighted distance from the coast, no
directional modeling of plumes; calculations at the
level of ocean compartments individuated on the
basis of hydrodynamic patterns
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Emissions and receptors
• Emissions data that can be associated with
– e.g. agro-chemical use,
– population distribution,
– emission inventories such as the EEA’s EPER.
• Spatially resolved insights of ecosystem and
human exposure at a pan-European scale.
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Example 1 : 1,2-Dichloroethane
• Example fact sheet:
http://www.epa.gov/OGWDW/dwh/t-voc/12dichl.html
Assumptions:
Half life in air: 1 month
Half life in water: 10 hrs, mainly due to
volatilization
Degradation is negligible in water
Main multimedia mechanisms: volatilization,
advection
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Emissions to
water
(EPER points)
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The WATER_GIS
model (Pistocchi et al.,
2004) computes
concentrations along
the stream network and
lakes; volatilization is
included as a
mechanism of removal
from water and loading
to air.
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The results are spatially
resolved to the detail of
1 km along the stream
network
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The MAPPE_ADEPT
model computes
concentration in the
atmosphere depending
on volatilization from
surface waters.
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Example 2 - PCBs
• Degradation rates:
• Kair-water = 0.0153
• Kow = 2.E+6
• MW = 292
• Emissions:
EMEP data
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Koverall,
atmo., hr-1
(excluding
degradation)
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1.00E-05
kdry, diff
kdry, dep
6.63E-06
6.63E-06
6.63E-06
6.63E-06
6.63E-06
6.63E-06
1.00E-04
1.00E-03
kw et, diff
kw et, dep
kdry, tot
3.01E-02
kw et, tot
3.01E-02
2.31E-02
6.31E-03
3.46E-03
4.16E-03
6.36E-03
2.31E-02
soil, MQ
5.18E-05
4.21E-03
6.30E-03
3.51E-03
3.01E-02
2.31E-02
river, avg
9.96E-05
4.15E-03
3.45E-03
river, max
3.99E-05
1.68E-04
1.68E-04
6.37E-03
river, min
1.68E-04
1.68E-04
1.68E-04
3.02E-02
2.31E-02
lakes
1.68E-04
9.95E-05
3.51E-03
4.21E-03
6.31E-03
2.31E-02
3.01E-02
1.00E-01
3.99E-05
4.15E-03
1.00E-02
3.45E-03
removal rates from the atmosphere, hr-1
soil, SIMPLEBOX
1.00E+00
?
1.00E-06
ktot
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Ksoil, hr-1
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Kerosion,
hr-1
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Kvolat., hr-1
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Soil concentration
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The soil rates
?
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Deposition
to ocean,
g/km2/yr
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removal
rates from
the ocean,
hr-1: july
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Comparison with MSCE-POP
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Ocean
concentration
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Comparison with MSCE-POP highlights
that:
• Gas phase exchange plays a relevant role and
should be better parameterised for soil-air
interface
• Orders of magnitude are correct apart from the soil
compartment
– this is a common problem seen in many model
comparison exercises
• Patterns in ocean concentration are wrong:
– Importance of removal rate patterns over emissions
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Concentration to (potential) risk is a
trivial GIS overlay operation
Example: air C + pop.
density
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Forthcoming Applications
• Generic fate and transport modeling of widely
dispersed chemicals such as
– Pharmaceuticals and biocides (following pop.
Density)
– Pesticides (following agriculture)
• To obtain Indicators of “Chemical Density” of
Europe
– large-scale average trends
– hot spots
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Conclusions
• A screening-level tool that compares reasonably
with detailed, distributed model MSCE-POP, and
supports more detailed assessment (1km grid,
freshwater)
• Suitable for soft-computational applications
(concept of “chemical density” from given
pressure factors)
• Needs tuning with experimental evidence –
suitable for dialoguing btw. lab- and math-people
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Info
Info and this presentation on our web
sites:
dr Alberto Pistocchi European Commission
Joint Research Centre,
Institute for Environment and Sustainability (IES)
Rural, Water and Ecosystem Resources (RWER) Unit
Via E. Fermi 1, TP 460
I-21020 Ispra (VA), Italy Tel.: +39 0332 785591
e-mail [email protected]
http://ensure.jrc.it/
http://nomiracle.jrc.it
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