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A Comparison of Pesticide Environmental Risk Indicators for Agriculture. Thomas Greitens Esther Day. Ranking CHEMS 1 (USA) EIQ (USA) MATF (USA) PERI (Sweden). Predicted Environmental Concentration (PEC) EPRIP (Italy) EYP (The Netherlands) SyPEP (Belgium) SYNOPS (Germany).

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Presentation Transcript
risk indicator systems
Ranking

CHEMS 1 (USA)

EIQ (USA)

MATF (USA)

PERI (Sweden)

Predicted Environmental Concentration (PEC)

EPRIP (Italy)

EYP (The Netherlands)

SyPEP(Belgium)

SYNOPS (Germany)

Risk Indicator Systems
aft s research goals
AFT’s Research Goals
  • Evaluate usability of environmental risk indicators.
  • Analyze potential applicability at farm level.
  • Assess accuracy.
methodology
Methodology

Data Collection:

  • 2000-2001 application data, 4 FL fields, tomatoes and peppers
  • Soil samples
  • Weather data
  • Pesticide parameters
results
Results
  • Most models track reductions in potential risk consistently over time.
  • Some models are “outliers” but consistent with previous research.
usability
Usability
  • Ranking method simpler.
  • PEC method more data intensive, more complex

but

  • PEC also gives more complete picture of potential risk.
models soil and water
Models – Soil and Water
  • Some consider potential risk to soil
  • All consider potential risk to aquatic organisms.
  • Some calculate potential groundwater leaching.
  • Some consider potential risk to human health (e.g. cancer risks).
farmer applicability
Farmer Applicability

Models can be used to:

  • Analyze past and future applications
  • Obtain certification.
research concerns
Research Concerns
  • Absence of data
  • Adaptability of models?
  • Non-transferable standards (e.g. European drinking water standards)
synops as a separate model

SYNOPS as a Separate Model

Synoptisches Bewertungsmodell für PflanzenSchutzmittel

Federal Biological Research Centre for Agriculture and Forestry, Institute for Technology Assessment in Plant Protection

synops modules
SYNOPS Modules

SYNOPS Modules

  • SYNOPS calculates PEC over time in:
    • Soil
    • Surface water
    • Air
    • Bio-organisms (earthworms, fish, algae, daphnia)
    • Groundwater
risk potential to organisms
Risk Potential to Organisms
  • Acute: LD50 and LC50 of organisms and short term predicted concentration.
  • Chronic: based on NOEC of of organisms and long term predicted concentrations.
chronic fish
Chronic – Fish*

*all chemicals, one field

scale of synops
Scale of SYNOPS
  • SYNOPS lends itself to larger scale evaluation
  • Possible to expand from farm-level, homogeneous environmental conditions to larger, heterogeneous conditions.
validation of model
Validation of Model
  • ENVIROMAP project - German-South African collaboration.
  • Comparison between actual and predicted concentrations in orchards in the tributaries of the Lourens River catchment.
prediction vs measurement
Prediction vs. Measurement
  • Regression analysis: significant positive correlation (R2=0.95) between predicted and measured average runoff loads in the tributaries.
  • Basic drift deposition values proved accurate (R2=0.96) in predicting in-stream loads.

results indicate applicability to South African conditions.

conclusions
Conclusions

Models using:

  • Ranking method  know potential risk before application.
  • PEC method  know potential risk after application

therefore

Can be used by farmers to make strategic choices

  • Measure reductions achieved by IPM programs
  • Some models better reflect regional concerns

But…

  • Limited to pesticides, no nutrient impact assessment
future aft research
Future AFT Research
  • Further integrate models in the concept of IPM program evaluation and environmental risk assessment.