Terrestrial Field Dissipation TFD

1
Terrestrial Field Dissipation (TFD)

• A Case Study
• Mohammed A. Ruhman
• ruhman.mohammed_at_epa.gov
• Environmental Fate and Effects Division (EFED)
• Office of Pesticide Programs (OPP)
• The United States Environmental Protection Agency
  (USEPA)

2
Objectives

• Test the conceptual model approach using current
  TFD studies.
• Evaluate recent field dissipation studies for
  bias and completeness.
• Compare the actual behavior of the pesticide in
  the field with the predicted conceptual model.
• Suggest specific improvements for terrestrial
  field dissipation studies and identify areas
  needing further discussions.

3
Terrestrial Field Dissipation (TFD)

• TFD degradation movement.
• Function of (Pesticide Properties
  Site/Environmental Conditions).
• Confounded by
• Study design.
• Sampling method.
• Analytical methods.

4
Dissipation Pathways
Foliar Interception Dissipation
Spray Drift
Volatilization
Surface Runoff
Wash-off
Applied Pesticide
Plant Uptake
Lateral Flow
Sorption/ Retention
Transformations microbial chemical
Tile Drainage
Leaching
5
Topics of Discussion

• Definitions Data compilation and treatment.
• TFD data the application/dissipation periods.
• Trial sites.
• Tank-mix stability.
• Pesticide delivery zero time concentration
  (ztC).
• Sampling schemes.
• Handling of samples.
• Field-spiking and analytical bias.
• Lab trial specific conceptual model.
• Leaching.
• Routes of dissipation predicted versus
  determined.

6
Definitions / Data Compilation and Treatment
(Refer to Attachment to Summary Document)
7
Analysis of TFD data the application/dissipation
periods.
8
Trial Sites (US and Canada)
9
Tank-Mix Stability

• Tank-Mix Stability is a measure of change in
  pesticide concentration prior to and after
  application.
• Data reported for only three of six chemicals.
• Where multiple applications were applied, data
  was not provided for every tank mix.
• Data shows concentrations higher than expected
• Chemical H before after
• 15 4 higher in CA and OH trials,
  respectively
• Chemical M inconsistent
• 18 higher than expected in all trials
• Chemical J extremely variable
• 24-53 higher than expected in 4 trials

10
Tank-mix Stability

• Effect
• Introduction of bias.
• Use
• To correct residue?
• Suggestions for improvement
• Data should be collected for all sprays.
• Acceptable variations 10.
• In problem chemicals
• Continuous agitation during spraying.
• Collection of multiple samples to correspond to
  certain areas.
• Systematic sampling scheme.

11
Pesticide Delivery (Application Rates)
12
Pesticide Delivery (Verification)

• Objectives
• Did the equipment deliver the nominal rate
  nAR?
• Use
• aAR did the pesticide reach the target?
• vAR rvAR was the pesticide distributed evenly
  over the target?
• aAR vAR rvAR observe bias in pesticide
  distribution within each trial
• Findings
• Expressed in loss or gain data

13
Pesticide Delivery (Loss or Gain)

• Based on aAR
• Spray results were highly variable
• Liquid sprays up to 40 loss to 7 gain.
• Granule broadcasts up to 12 loss to 14
  gain.
• Data reported for only 60 of the
  sprays/broadcasts.
• Based on vAR/aAR (verification method)
• Spray results were highly variable
• Overall loss 23 (01-82), gain 7
  (04-32).
• Data reported for only 50 of the applications.

14
Pesticide Delivery (Loss or Gain)

• Based on rvAR/aAR or vAR (just before/after)
• Spray results were highly variable
• Overall loss 31 (03-90)
• Overall gain 34 (01-91)
• Data reported for 84 of the applications.
• In multiple applications data were not reported
  for all applications

15
Loss or Gain (Multiple Application)
16
Loss or Gain (Multiple Application)

• Based on found residue versus model EECs
  (expected environmental concentrations).
• Model EECs based on aerobic soil laboratory data.

17
Loss or Gain (Found Vs. Model EECs)
18
Loss or Gain (Found Vs. Model EECs)
19
Pesticide Delivery Zero Time Concentration
(ztCs) Data

• ztCs were determined for the top soil layer
• Single application cases only one value/trial.
• Multiple application cases a value for each
  application.
• Not all applications were sampled for multiple
  application.
• In one chemical no samples taken for the
  application period.
• Found ztCs confirmed presence of loss or gain

20
Analysis of Loss or Gain Data

• Effects of variable spray results
• Questionable application rate.
• Un-even distribution hot and cold spots.
• Create a good chance of missing one or more TFD
  processes.
• Use of data
• To clarify how much reached the target? How well
  it was distributed?
• To explain plant interception and drift.
• To correct the application rate (verification
  data).
• Contributing factors
• Tank-mix stability Volatilization Drift
  Chemical recovery/ determination procedure And
  accuracy of the verification procedure
• Plant cover and type of formulation used

21
Ground Cover Effects(Based on Loss Verified by
Soil Residue Data)
H
Chemical M
J
L
D
K
22
Formulation Effects
23
Suggestions for Improvement

• Verification method.
• Pre-tested before use in trials.
• Report/explain data.
• Use in correction of aAR to vAR.
• Soil residue verification method (based on
  rvAR).
• Use in interpreting plant-interception.
• Collect data to determine plant cover (IR
  imagery).
• Sample/analyze plants at various sampling
  intervals.
• Use verification method to verify drift.

24
Sampling Schemes

• Random and systematic core sampling.
• 9-16 samples within 94/566 days.
• 3-14 samples/two aerobic soil t½.
• 35" maximum depth sampled 48-60."
• 5-18 cores/plot or 74-10 m2/core.

25
Sampling Schemes

• 2" cores (top soil) 1-1.25 (lower depths).
• Composite/homogenized by depth.
• In multiple applications few samples during the
  AP.

26
Handling of Samples

• Storage Stability
• Frozen in the field, shipped, arrived and stored
  frozen in the laboratory.
• Maximum length of storage 481-767 days.
• Varied length of storage for samples within each
  trial.
• Some recoveries claimed to be acceptable were
  50-57 and 64-79.
• Storage stability often confirmed concurrently or
  after the fact.
• Effects
• Affect residue data.
• Suggestions for improvement
• Reduce storage length to minimum.
• Use the same storage time for all samples within
  a trial.
• Store TFD residue samples with field-spiked
  samples.
• Abide by a standard of acceptable minimum storage
  loss.

27
Field-spiking and Analytical Bias

• Field-spiking recoveries
• Fortification recoveries of field-spiked samples
  were used to correct residue data
• Examples of acceptable ranges were 927 929
  for C-H
• Example of unacceptable range was 24-213 for C-J
• Analytical recovery
• Use variation between replicates as a measure of
  analytical bias

28
Analytical Bias
M
L
D
H
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Topics of Discussion

• Definitions Data compilation and treatment
• TFD data the application/dissipation periods
• Trial sites.
• Tank-mix stability
• Pesticide delivery zero time concentration(ztC)
• Sampling schemes
• Handling of samples
• Field-spiking
• Lab trial specific conceptual model
• Leaching
• Routes of dissipation predicted versus determined

30
Laboratory Conceptual Model

• Formulate hypothesis of field dissipation based
  on laboratory data
• Hypothesis based on expected routes of
  dissipation covering
• Leaching availability/vulnerability
• Other routes volatilization, hydrolysis,
  photolysis, and bio-transformation
• Data were not available for evaluating
• Plant interception, wash-off, and uptake
• Run-off and erosion

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Laboratory Conceptual Model for the Case Study
Chemicals

• Statements on expected field leaching
• Availability for leaching
• All will be available for leaching except
  Chemical L
• (Based on solubility assuming soils containing
  25 water at field capacity).
• Vulnerability for leaching is expected to be
• Very high for chemicals K D
• High to medium (M) for chemicals L J and
• Medium for chemicals H M
• (based on Koc/mobility classes).

32
Laboratory Conceptual Model for the Case Study
Chemicals

• Statements on other routes of field dissipation
• Volatilization not important (based on vapor
  pressure lt10-8).
• Hydrolysis important in chemical M (acidic
  soils) and chemical D (alkaline soils).
• Photolysis important in chemical M J (based on
  t1/2/degradates)
• Bio-transformation important in all, except
  chemical K (based on t1/2/degradates as
  indicators).

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Mobility Predictions (Based on Koc)
Line of medium mobility (M)
Medium mobility line(M)
Medium (M) mobility line
Line of high mobility (H)
High Mobility Line(H)
High (H) mobility line
Line of (VH)
Very High (VH)
(VH) mobility line
34
Trial Specific Conceptual Model

• A modification of the laboratory conceptual
  model based on comparisons between trial and
  laboratory soils.
• Leaching Statements
• Modify based on WHC, expected Koc, water balance
  and soil permeability.
• For other processes
• Account for leaching by basing t1/2 on total
  residue.
• Expect change in TFD t1/2 based on
• Change in bound residue (O.C and clay types).
• Occurrence of other processes hydrolysis and/or
  photolysis (soil pH and availability of
  sunlight).
• Difference in soil viability between laboratory
  and field.

35
Trial Specific Conceptual Model

• Use
• During the planning stage to design TFD study
  capable of identifying/tracking/quantifying major
  routes of dissipation at chosen site(s).
• Hypothesis for the TFD study.
• Limitations
• Presence of data gaps necessary for establishing
  residue profile w/depth, water balance and soil
  WHC/permeability, and comparisons between lab and
  field soils.
• Suggestions for improvement
• Collect data for WHC, permeability, and water
  balance calculations.
• Use same extraction method as in the laboratory.
• Characterize/compare lab/field soils.

36
Topics of Discussion

• Definitions Data compilation and treatment
• TFD data the application/dissipation periods
• Trial sites.
• Tank-mix stability
• Pesticide delivery zero time concentration(ztC)
• Sampling schemes
• Handling of samples
• Field-spiking
• Lab trial specific conceptual model
• Leaching
• Routes of dissipation predicted versus determined

37
Field Leaching for the Case Study Chemicals

• Observed
• Where? At one M trial, two L trials, and all H
  J trials.
• Influences?
• Rainfall events.
• Depth of incorporation.
• High rainfall (equal to 30-year average).
• Not observed
• Where? Trials not stated above.
• Influences?
• Low solubility pesticide / low WHC soil
  (chemical L).
• Short t1/2 in relation to rainfall timing
  (chemicals M D).
• Low rainfall (less than the 30-year average).
• No data for Chemical K trials.

38
Field Leaching Profiles
1
0.5"
1
1
39
Field Leaching Profiles
5"
10
20
40
Field Leaching Profiles
5"
10
20
41
Topics of Discussion

• Definitions Data compilation and treatment
• TFD data the application/dissipation periods
• Trial sites.
• Tank-mix stability
• Pesticide delivery zero time concentration(ztC)
• Sampling schemes
• Handling of samples
• Field-spiking
• Lab trial specific conceptual model
• Leaching
• Routes of dissipation predicted versus determined

42
Routes of TFD Conceptual Model Versus Field
All are within the non-persistent class (Goring
et al 1975)
4
1
43
Routes of TFD Conceptual Model Vs. Field
44
Routes of TFD Conceptual Model Vs. Field
45
Routes of TFD Conceptual Model Vs. Field
All are within the non-persistent class
2.7
46
Routes of TFD Conceptual Model Versus Field
No leaching
47
Routes of TFD Conceptual Model Versus Field
No leaching
48
Routes of TFD Conceptual Model Vs. Field
2TFD t1/22 31 291
Highly persistent class
149
Moderately persistent class
49
Routes of TFD Conceptual Model Versus Field
50
Routes of TFD Conceptual Model Versus Field
All are within the the moderately persistent class
70
51
Routes of TFD Conceptual Model Versus Field
52
Routes of TFD Conceptual Model Vs. Field
180
Most are within the medium persistent class
Most are within the medium persistent class
69
53
Routes of TFD Conceptual Model Versus Field
54
Routes of TFD Conceptual Model Vs. Field
55
Routes of TFD Conceptual Model Versus Field
164
All are within the medium persistent Class
56
Routes of TFD Conceptual Model Versus Field
57
Conclusions

• TFD degradation movement
• Function of (Pesticide Properties
  Site/Environmental Conditions)
• Confounded by
• Study design
• Sampling method
• Analytical methods

58
Acknowledgments

• Mark Corbin
• Dana Spatz
• Nelson Thurman
• William Eckel
• Mah Shamim
• EFED Fate Technical Team
• PMRA