WEBFRAM 5: A risk assessment

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WEBFRAM 5 A risk assessment module for soil
invertebrates
Geoff Frampton University of Southampton
(UK) Joerg Roembke ECT Oekotoxikologie
(DE) Paul van den Brink Alterra Green World
Research (NL) Janeck Scott-Fordsmand NERI (DK)
Funded by
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WEBFRAM-5 Principal aim
To investigate whether the pesticide risk
assessment for below-ground invertebrates could
be improved by explicitly incorporating
variability and uncertainty into estimates of risk
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Soil invertebrates pesticide risk assessment
( 91 / 414 / EEC )
Standard higher-tier test ?
Testing
Earthworms
routine
yes
Collembola
optional
no
Enchytraeidae
optional
no
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WEBFRAM 5 Background
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Deterministic risk assessment scheme
toxicity
Risk based on
safety factor
exposure
Earthworms example
Risk measure
Safety factor
Lower tier acute
TER
10
Lower tier chronic
TER
5
Higher tier field
effects
none
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Deterministic risk assessment scheme
toxicity
Risk based on
safety factor
exposure
Appropriate as a worst-case screening tool
Simple to apply Harmonised calculations and
interpretation Applicable to small data sets
Safety factor represents uncertainty
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Deterministic risk assessment scheme
Principal criticisms
Ecological relevance unclear Does not use
all the available information Based on
untested assumptions Risk estimates lack
transparency Does not indicate - likelihood
of risk - degree of risk - certainty of the
risk estimate
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Potential benefits of incorporating uncertainty
in the risk assessment
Clarify how conservative the risk estimate
is Make better use of available
information Improve realism (i.e. ecological
relevance) Indicate certainty, likelihood, degree
of risk Improve transparency of risk estimation
Validate or refine assumptions Improve
efficiency (reduce unnecessary testing)
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Potential criticisms of incorporating uncertainty
in the risk assessment
Requires more data than deterministic
approach Statistical approaches more complex
Could introduce more assumptions May not
clarify risk if not communicated well
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WEBFRAM 5 Objectives
1. Acquire data (key step!)
2. Identify variables with adequately-supported
distributions
3. Use data distributions to describe variability
4. Incorporate descriptions of variability in
alternative version(s) of the risk assessment
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WEBFRAM 5 Database summary
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Data sources
Systematic search (literature, institutions,
colleagues)
gt 1000 relevant publications screened
gt 400 selected for data extraction
Data quality classes assigned after data
extraction
Lower tier
Higher tier
Research publications reports Regulatory data
in public domain Contract testing laboratory owned
82 17 1
100 0 0
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Below-ground invertebrates database
Lower tier (laboratory)
Higher tier (TME / field)
Active substances (a. s.) Species /
groups Effects data sets
257 70 1282
75 72 1029
a. s. with data for both tiers
45 (16)
a. s. with only one data set
108 (38)
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Soil invertebrate effects data pesticides with
gt 20 data sets
Carbendazim Copper Benomyl Dimethoate Pentachlorop
henol Parathion Carbofuran Diazinon Lindane Atrazi
ne Chloroacetamide Lambda-cyhalothrin Imidacloprid
Chlorpyrifos Carbaryl Halofenozide DNOC Bendiocar
b Malathion Thiophanate-methyl Phorate
Lower tier
Higher tier
Number of data sets
0
50
100
150
200
250
300
350
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Soil invertebrate effects data pesticides with
9 - 20 data sets
Lower tier
Higher tier
Number of data sets
0
2
4
6
8
10
12
14
16
18
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Distribution of pesticide effects data among soil
invertebrate groups
Lumbricidae Collembola Enchytraeidae Acari Coleopt
era Nematoda Isopoda Formicidae Diptera Araneae
Lower tier
Higher tier
Number of data sets
0
200
400
600
800
1000
1200
1400
17
Collembola species data lower tier
Folsomia candida Folsomia fimetaria Onychiurus
folsomi Isotoma viridis Onychiurus
armatus Proisotoma minuta Orchesella
cincta Sinella communis Collembolans
grouped Isotomidae Lepidocyrtus sp. Onychiurus
apuanicus Sinella caeca
Number of data sets
18
Enchytraeidae species data lower tier
Enchytraeus albidus
Cognettia sphagnetorum
Enchytraeus crypticus
Enchytraeus sp. indet.
Enchytraeus coronatus
Friderica ratzeli
Enchytraeus buchholzi
Number of data sets
19
Lumbricidae species data lower tier
Eisenia fetida Earthworms grouped Eisenia
andrei Lumbricus terrestris Aporrectodea
caliginosa Lumbricus rubellus Aporrectodea
tuberculata Allobophora chlorotica Dendrobaena
rubida Apporectodea longa Aporrectodea
rosea Octolasium lacteum Eisenia veneta
Number of data sets
0
100
200
300
400
500
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Data reliability checks
Following Klimisch et al. (1997) in Regulatory
Toxicology Pharmacology
Number

(1) Reliable without restriction
114
9
586
45
(2) Reliable with restrictions
(3) Not reliable
241
19
(4) Not assignable
351
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1292
100
Total
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WEBFRAM 5 Risk assessment approach
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Tiered risk assessment approach
Earlier steps are more strict / conservative than
later steps
Later steps are more realistic than earlier steps
Jumping to later steps is usually acceptable
Earlier steps usually require less effort than
later steps
The same type of concentration applies to all
steps
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Tiered risk assessment approach
Exposure model
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Tiered risk assessment approach (Boesten,
J.J.T.I.)
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Maximum carbendazim content in top 5cm soil (mg
a.i. / kg)
Fate model Ploughing No ploughing
Step 1 No loss 8.3 8.3
Step 2 Loss due to transformation and ploughing only, 5 oC 0.6 0.9
Step 3 PEARL calculations for a realistic worst-case scenario 0.4 0.5
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Tiered risk assessment approach
Effects model
Tier 1 Laboratory deterministic - a reasonable worst case estimate (present situation)
Tier 2 Laboratory probabilistic - a point estimate based on a distribution that indicates probability of the sensitivity
Tier 3 (Semi-)Field - a safe concentration based on (semi-)field experiments
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Tiered risk assessment approach
Effects model (top 5 cm soil) earthworms example
Tier 1 LC50 acute NOEC chronic OECD 207 guidance ISO 11268-2 (present situation)
Tier 2 HC5 From lower-tier species sensitivity distributions to incorporate inter-species variation
Tier 3 NOEC field From higher-tier semi-field or field experiments
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Tiered risk assessment approach
earthworms
Example carbendazim
Tier 1 (deterministic, acute)
OECD 207
Lower limit TER acute trigger (safety factor) 10
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Tiered risk assessment approach
earthworms
Example carbendazim
Tier 1 (deterministic, acute)
OECD 207
Lowest LC50 acute 3.9 mg a.i. / kg (EU SEEM
project 2002)
Typical application rate 250 g a.i. / ha,
equivalent to 0.418 mg a.i. / kg
Lower limit TER acute trigger (safety factor) 10
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Tiered risk assessment approach
earthworms
Example carbendazim
Tier 1 (deterministic, acute)
OECD 207
Lowest LC50 acute 3.9 mg a.i. / kg (EU SEEM
project 2002)
Typical application rate 250 g a.i. / ha,
equivalent to 0.418 mg a.i. / kg
RISK indicated
TER lt 10
Lower limit TER acute trigger (safety factor) 10
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Tiered risk assessment approach
earthworms
EU Terrestrial Guidance Document SANCO / 10329 /
2002
OECD 207
Requirement for chronic (reproduction) test if

• More than 6 applications (not fulfilled here)
• DT90 field gt 90 days (probably not fulfilled)
• TER acute lt 10 (fulfilled)

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Tiered risk assessment approach
earthworms
Example carbendazim
Tier 1 (deterministic, chronic)
OECD 207
PEC chronic Cumulative concentration In top 5cm
over 20 years, assuming no loss
Lower limit TER chronic trigger (safety factor)
5
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Tiered risk assessment approach
earthworms
Example carbendazim
Tier 1 (deterministic, chronic)
OECD 207
Lowest NOEC chronic 0.6 mg a.i. / kg (van
Gestel 1992)
PEC chronic Cumulative concentration In top 5cm
over 20 years, assuming no loss
PEC chronic 8.36 mg a.i. / kg
Lower limit TER chronic trigger (safety factor)
5
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Tiered risk assessment approach
earthworms
Example carbendazim
Tier 1 (deterministic, chronic)
OECD 207
Lowest NOEC chronic 0.6 mg a.i. / kg (van
Gestel 1992)
PEC chronic Cumulative concentration In top 5cm
over 20 years, assuming no loss
PEC chronic 8.36 mg a.i. / kg
RISK indicated
TER lt 5
Lower limit TER chronic trigger (safety factor)
5
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earthworms enchytraeids
Tiered risk assessment approach
Example carbendazim
Tier 2 (probabilistic)
An effect estimate based on the median HC5, in
this example derived from an array of individual
toxicity (NOEC) data for earthworms and
enchytraeids
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earthworms enchytraeids
Tiered risk assessment approach
Example carbendazim
Tier 2 (probabilistic)
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earthworms enchytraeids
Tiered risk assessment approach
Example carbendazim
Tier 2 (probabilistic)
Lowest PEC from step 2 of exposure model 0.6 mg
/ kg
TER refined 0.53 / 0.6 0.88
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earthworms enchytraeids
Tiered risk assessment approach
Example carbendazim
Tier 2 (probabilistic)
Lowest PEC from step 2 of exposure model 0.6 mg
/ kg
TER refined 0.53 / 0.6 0.88
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Tiered risk assessment approach
multiple species
Example carbendazim
Tier 3 (semi-field / field)
Higher-tier studies did not yield data suitable
for constructing distributions of sensitivities
An HC5 type approach therefore could not be
applied to the higher-tier data to estimate risk
Instead, the effect estimate (NOEC field) may be
determined from TME and field experiments that
simulate or represent realistic agroecological
conditions
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Higher-tier effects classes
(based on Brock et al. (2000) Alterra Report 88)
Class 1
No effect demonstrable
Class 2
Slight effect, transient
Class 3
Slight effect, long term Pronounced effect,
transient or long term
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Tiered risk assessment approach
multiple species
Example carbendazim
Tier 3 (semi-field / field)
61 data entries for Lumbricidae
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Tiered risk assessment approach
multiple species
Example carbendazim
Tier 3 (semi-field / field)
61 data entries for Lumbricidae
NOEC field 1.0 mg / kg
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Tiered risk assessment approach
multiple species
Example carbendazim
Tier 3 (semi-field / field)
61 data entries for Lumbricidae
NOEC field 1.0 mg / kg
Step 2 PECs
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Tiered risk assessment approach
multiple species
Example carbendazim
Tier 3 (semi-field / field)
61 data entries for Lumbricidae
NOEC field 1.0 mg / kg
Step 2 PECs
Step 3 PECs
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Project outputs
An internet-based risk assessment tool that
would enable stakeholders to input their own data
or use default examples to explore the impact on
risk estimates of incorporating uncertainty,
using
a species sensitivity distribution model to
calculate HC5 (or HCx) values for lower-tier data
a tiered exposure model
an interface to enable exposure and effects
estimates to be combined and plotted (where
appropriate) to indicate probability and
certainty of risk estimates
online guidance and links to other relevant risk
assessment resources
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Purpose of the internet resource
Optimise opportunities for interested parties to
explore alternative ways of estimating risk
Assist decision making at each risk assessment
tier
Provide feedback
Raise awareness of data availability issues and
limitations
Could be used as an educational and training
resource
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Conclusions
Opportunities to explicitly incorporate
uncertainty in the risk assessment are limited,
even for standard test species, due to a lack of
appropriate empirical data
However, the feasibility of incorporating
uncertainty can be illustrated for components of
the risk assessment scheme where data shortage is
least problematic
Data from the independent literature is biased
strongly towards standard test species, meaning
that few data are available to support
extrapolation to non-standard species
Further development of the database is
imperative, to enable advances in these research
areas