Pesticide Registration Evaluation Model (PREM

) for Surface W

ater Protection in California

Yuzhuo Luo, Ph.D.Research Scientist IV

Surface Water Protection Program

(SWPP)

California Department of Pesticide Regulation (CDPR)

Pesticide registration evaluation model (PREM

)

•The m

ain modeling tool for surface w

ater registration evaluation•

Historically, SW evaluations have been based on professional

judgment and experience

•A new

methodology has been developed and im

plemented in PREM

for m

ore consistent, transparent, and efficient evaluation•

The first version of PREM w

as released in 2012. It continues to evolve to better fit CA conditions w

ith increasing modeling capabilities

•The latest version: PREM

5

Model developm

ent•

Modeling fram

ework w

ith 2-stage evaluation processes

Version 2 (2012)

•Evaluation of urban pesticide uses

Version 3 (2014)

•Evaluation of pesticide degradates

•Exposure potentials to m

arine/estuarine organisms

Version 5 (2017)

•SW

PP continues to improve the m

odel's capabilities and specificity to California conditions: receiving w

ater body; indoor uses and w

astewater, etc.

Under

development

Scope and limitations

By pesticide use patterns:•

PREM is developed for production agriculture (both upland and

flooded), aquatic application, outdoor impervious surfaces

(residential, comm

ercial, right-of-way), adulticide

application, indoor uses (PO

TW scenario, under developm

ent)

•But N

OT for anti-fouling paint (AFP), inorganic com

pounds (silver, copper), and other biochem

ical and antimicrobial pesticides

Overview

of PREM evaluation process

Model input data

PREMRegistration

recomm

endations

�Product labels

�Chem

istry data *�

Eco-toxdata *

* DPR-accepted data only

�Support

�Conditionally support

�N

ot support�

Watch-listing, flagging etc.

Evaluation variables

Decision-making

flowchart

Functional modules

Graphical user interface

(GU

I)

Evaluation variables

VariablesInput param

etersApproaches

Soil-runoffpotential

Adsorption coefficient (KOC), Field

dissipation half-life, Water solubility

USDA W

IN-PST m

odel, modified by DPR

Aquatic persistence

Half-livesin w

ater and sediment

Criticalvalues of 30 and 100 days of half-lives

Aquatictoxicity

Acute aquatic toxicity(LC50 or EC50) for

sensitive species (fish & invertebrates)

USEPA classifications

Use pattern

Use pattern

High-risk usepatterns identified by DPR

Risk quotientChem

ical property, use pattern, labelrate, etc.

USEPA m

odels (PRZM, VVW

M, PFAM

)

Note: variables are presented as descriptive classification, e.g., high (H), low

(L), intermediate (M

)

6

Pesticide use pattern

•Pesticide use patterns w

ith high-risk potentials to surface water:

•Aquatic and rice pesticides

•U

rban/residential uses•

Crops with gravity irrigation

•W

inter rain season application•

Pre-emergent application

•Crops w

ith top acreages in California

•O

ther use patterns: low-risk potentials

Risk quotient (RQ)

•Evaluated for high-risk use patterns only

•EEC (estim

ated environmental concentration) = f(chem

ical property, use pattern, label rate)

•TOX

= the toxicity value (LC50 or EC50) for the most sensitive species

•RQ

is compared to the LO

C (level of concern)•

High RQ: >0.5

•Interm

ediate RQ: 0.1-0.5

TOX

EECRQ

EEC modeling

•Generally, based on the FIFRA

(Federal Insecticide, Fungicide, and Rodenticide Act) Tier-2 m

odeling framew

ork

Ref: EPA-HQ-O

PP-2015-0424-0036

EEC modeling

•Generally, based on the FIFRA

(Federal Insecticide, Fungicide, and Rodenticide Act) Tier-2 m

odeling framew

ork•

For applications to an aquatic site (e.g., rice pesticide), modeling for

the treated water body only

USEPA/O

PP 734S16002

EEC modeling: tools

•Sim

ulation engines (USEPA m

odels)•

Landscape simulation: PRZM

(Pesticide Root-Zone Model)

•In-w

ater simulation: VVW

M (Varying Volum

e Water M

odel), and PFAM

(Pesticide in Flooded Application Model)

•M

odeling scenarios•

USEPA scenarios for agricultural uses

•DPR scenario for urban outdoor uses

•DPR scenario for degradate

evaluation•

USEPA/DPR scenario for rice pesticides

•DPR scenario for dow

n-the-drain pesticides (under development)

•…

Decision-making flow

chart

Note: L=low, M

=intermediate, H=high, VH=very high

12

PREM Results

•Registration recom

mendations (for a product)

•Support registration

•Support conditional registration and request analytical m

ethods•

Do not support registration

•W

atch listing (for an active ingredient)•

Conditional registration: consider the A.I. as a candidate for surface water

monitoring, and w

atchits actual use am

ount and post-use risk•

Low-risk use pattern for the currently evaluated product: Flag the A.I. and

watch

it for new products and label am

endments

13

Graphical user interface

Chemical-specific data

Product-specific data

Specify the parent compound here

Specify the degradates to be modeled here

Input data

15

High-risk use patterns

16

Additional data by pesticide use pattern•

Urban use as an exam

ple

PREM O

utputs

18From

: PREM5 technical report

PREM applications

•Registration evaluations for 70+ pesticide products (as of Dec 2019)•

Risk assessment for fipronil(urban) and pyrethroids (urban and ag)

•Com

parison with U

SEPA/OPP residential settings in the ecological risk

assessment (ERA) for pyrethroids (EPA-HQ

-OPP-2010-0384-0045)

•Incorporation w

ith Best Managem

ent Practice (BMP) m

odeling•

Vegetative filter strip (VFS, completed)

•Vegetated drainage ditch (VDD, under developm

ent)

Summ

ary

•Surface w

ater evaluations with PREM

•Consistently &

reliably identify adverse risks of products to water quality &

aquatic life

•Avoid involved, costly &

protracted post-registration efforts to develop &

implem

ent mitigation or regulations

•Successful resolution betw

een DPR & registrants (data needs, label changes)

reinforces the usefulness & im

portance of SW registration evaluations &

PREM

•PREM

continually evolving for evermore realistic &

CA-centric predictions•

Eventually anyone could run model

PREM tim

eline

PREM w

ebsite

ww

w.cdpr.ca.gov/docs/em

on/surfwtr/sw

_models.htm

Thanks

Yuzhou Luo(916)445-2090Yuzhou.Luo@

cdpr.ca.gov

23