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Preliminary Findings of the Ecological Committee on FIFRA Risk Assessment Methods (ECOFRAM) : V. Aquatic Exposure Assessment

Paul Hendley (Zeneca Ag Products), James Baker (Iowa State Univ.), Lawrence Burns (EPA-ORD Athens), David Farrar (EPA OPP), Alan Hosmer (Novartis), David Jones (EPA OPP), Walton Low (USGS)

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Abstract

The Aquatic Exposure Subgroup has explored a variety of tools and approaches for clarifying uncertainty and incorporating probabilistic approaches into the assessment of aquatic exposure to pesticides. Reviews of the current risk assessment models and process have generated listings of factors for consideration. Reviews of sources of data and suggestions for enhancing the FIFRA Part 158 requirements for generating, calculating, reporting and expressing data important for modeling aquatic exposure are available. A logical tiered risk assessment process has been agreed with the aquatic effects workgroup (see Poster VII) and exposure related steps have been defined. Where possible, existing exposure models are suggested but, where necessary, improvements have been suggested. A practical tool (RADAR) has been developed to analyze EXAMS output to estimate the frequency and duration of peaks above a user specified threshold from a multiple year output sequence and estimating recovery intervals between high concentration "events". Recommendations are under development to further enhance aquatic exposure modeling and implement ECOFRAM concepts . Appropriate tools have been designed or defined.

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Tier 1 - Screening Exposure Estimates

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Tiering Concept Example

Diagram A

residue exposure profile in a river system
estimated using PRZM/EXAMS for Julian Days 100 to 200 across 6 years

The concept of a tiered approach to estimating aquatic exposure can be likened to drawing a rubber sheet down progressively over the "true exposure surface". For example, Diagram A shows the residue exposure profile in a river system estimated using PRZM/EXAMS for Julian Days 100 to 200 across 6 years (a full model run would typically be 365 days by 36 years).

Diagram B

what happens when such a highly conservative assumption is made - the default assumption (8 ppb) applies to
all cases with only the most extreme events exceeding the Tier 1 prediction. The
"sheet" reveals those most extreme events but masks the rest; almost no
information is available to characterize magnitude, duration or frequency of events

A Tier 1 prediction is required to be conservative and exceed predictions for the vast majority of anticipated events - Diagram B shows what happens when such a highly conservative assumption is made - the default assumption (8 ppb) applies to all cases with only the most extreme events exceeding the Tier 1 prediction. The "sheet" reveals those most extreme events but masks the rest; almost no information is available to characterize magnitude, duration or frequency of events.

Diagram C

shows that with progressively more sophisticated examination of the exposure (i.e. Tier 2) , the assessment more closely reflects reality and more detail on the exposure events becomes available

Diagram D

show that with progressively more sophisticated examination of the exposure (i.e.  3/4) , the assessment more closely reflects reality and more detail on the exposure events becomes available

Diagrams C & D show that with progressively more sophisticated examination of the exposure (i.e. Tier 2 and then 3/4) , the assessment more closely reflects reality and more detail on the exposure events becomes available. The "rubber sheet" conforms closely with more of the true exposure surface. A similar paradigm could apply to understanding regional or local spatial variation.

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Tiered Process Goal

ECOFRAM's aquatic exposure estimation tiers aim to improve understanding of:

Diagram E

the conceptual relationship of the tiers in terms of the distributions of values. Tier 1 is a single value at 90% of the Tier 2 prediction and Tiers 3/4 progress Tier 2 modeling towards reality by considering unexposed scenarios.  Ultimately, where needed, Tier 4's monitoring efforts can truly tie models to actual data.

Diagram E depicts the conceptual relationship of the tiers in terms of the distributions of values. Tier 1 is a single value at 90% of the Tier 2 prediction and Tiers 3/4 progress Tier 2 modeling towards reality by considering unexposed scenarios etc. Ultimately, where needed, Tier 4's monitoring efforts can truly tie models to actual data.

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Tier 2 - Exposure Characterization

Mark Russell (Dupont Ag Products), Mari Stavanja (Florida Bureau of Pesticides), Martin Williams (Waterborne Env. Inc.) and James Wolf (EPA OPP)

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Tier 3 - Tools to Refine Exposure

Purpose

Tier 3 refines Tier 2 exposure distribution predictions. The toolbox includes

Decisions

Exactly as Tier 2.

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Tier 4 - Major Conditional Monitoring or Mitigation Studies

Purpose

Tier 4 encompasses a further toolbox of approaches selected as needed to reduce uncertainty, incorporate additional variability or better represent reality. Will focus on settings shown in Tier 3 to have significant risk. Approaches include

Cost implications of these options are considerable so agreement is needed between EPA and Registrant under a conditional registration before Tier 4 can commence.

Decisions

Exactly as Tier 2.

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Example ECOFRAM Products

Idealized Expression of Exposure

Essential to express exposure assessments in highly specific terms to ensure clear communication with risk managers and aquatic toxicologists, e.g.

"33% (+/- 10%) of growing seasons experience events that exceed the 48 h Daphnia LC50 for at least 48 h without a subsequent recovery period of at least 21 days for pond in the MW adjacent to corn fields treated with one application of X at 1 lb./acre/season. It is believed that events below this level are unlikely to be of significant concern"

RADAR - Risk Assessment tool to evaluate Duration And Recovery.

RADAR has been developed to meet Tier 2 output goals (above) and process data from existing output from PRZM-EXAMS or MUSCRAT models. Examples are shown below. The table shows a summary of model output data for a stream, these results could be further evaluated to determine how many events met some user defined combination of concentration, duration & recovery period. The graph shows the annual maximum series for standard intervals matching toxicity studies.

Threshold Concn. No. of events % time over threshold Peak Concn. Avg. Concn. Duration (days) Inter-event Interval
MinMaxAvg MinMaxAvg MinMaxAvg MinMaxAvg
35630.6 36.317483.336.316079.3 1311389 205
70350.3 70.617410970.6160106 12111099371
104170.15 106174136106160131 1212432185765
13950.05 14917416014160156 12136432852020
17410.01 174174174174174174 111974097409740

Annual Maximum Series

the annual maximum series for standard  intervals matching toxicity studies

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