[Federal Register Volume 84, Number 57 (Monday, March 25, 2019)]
[Rules and Regulations]
[Pages 11208-11210]
[FR Doc No: 2019-05163]

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ENVIRONMENTAL PROTECTION AGENCY

40 CFR Part 52

[EPA-R09-OAR-2017-0728; FRL-9990-34-Region 9]

Approval and Promulgation of Air Quality State Implementation
Plans; California; Plumas County; Moderate Area Plan for the 2012 PM2.5
NAAQS

AGENCY: Environmental Protection Agency (EPA).

ACTION: Final rule.

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SUMMARY: The Environmental Protection Agency (EPA) is approving most
elements of state implementation plan (SIP) revisions submitted by
California to address Clean Air Act (CAA or ``Act'') requirements for
the 2012 annual fine particulate matter (PM2.5) national
ambient air quality standards (NAAQS or ``standards'') in the Plumas
County Moderate PM2.5 nonattainment area (``Portola
nonattainment area''). The SIP revisions are the ``Portola Fine
Particulate Matter (PM2.5) Attainment Plan'' submitted on
February 28, 2017, and the 2019 and 2022 transportation conformity
motor vehicle emission budgets (``budgets'') submitted on December 20,
2017. We refer to these submittals collectively as the ``Portola
PM2.5 Plan'' or ``Plan.'' The EPA is not taking action at
this time on the contingency measures in the Portola PM2.5
Plan.

DATES: This final rule is effective on April 24, 2019.

ADDRESSES: The EPA has established a docket for this action under
Docket ID No. EPA-R09-OAR-2017-0728. All documents in the docket are
listed on the https://www.regulations.gov website. Although listed in
the index, some information is not publicly available, e.g.,
Confidential Business Information (CBI) or other information whose
disclosure is restricted by statute. Certain other material, such as
copyrighted material, is not placed on the internet and will be
publicly available only in hard copy form. Publicly available docket
materials are available through https://www.regulations.gov, or please
contact the person identified in the FOR FURTHER INFORMATION CONTACT
section for additional availability information.

FOR FURTHER INFORMATION CONTACT: John Ungvarsky, EPA Region IX, (415)
972-3963<EMAIL_ADDRESS>
SUPPLEMENTARY INFORMATION: Throughout this document, ``we,'' ``us,''
and ``our'' refer to the EPA.

Table of Contents

I. Background
II. Public Comments and EPA Responses
III. Final Action
IV. Statutory and Executive Order Reviews

I. Background

    Epidemiological studies have shown statistically significant
correlations between elevated levels of PM2.5 (particulate
matter with a diameter of 2.5 microns or less) and premature mortality.
Other important health effects associated with PM2.5
exposure include aggravation of respiratory and cardiovascular disease,
changes in lung function, and increased respiratory symptoms.
Individuals particularly sensitive to PM2.5 exposure include
older adults, people with heart and lung disease, and children.\1\
PM2.5 can be emitted directly into the atmosphere as a solid
or liquid particle (``primary PM2.5'' or ``direct
PM2.5'') or can be formed in the atmosphere as a result of
various chemical reactions among precursor pollutants such as nitrogen
oxides, sulfur oxides, volatile organic compounds, and ammonia
(``secondary PM2.5'').\2\
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    \1\ 78 FR 3086, 3088 (January 15, 2013).
    \2\ 72 FR 20586, 20589 (April 25, 2007).
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    The EPA first established annual and 24-hour NAAQS for
PM2.5 on July 18, 1997.\3\ The annual standard was set at
15.0 micrograms per cubic meter ([micro]g/m\3\) based on a 3-year
average of annual mean PM2.5 concentrations, and the 24-hour
(daily) standard was set at 65 [micro]g/m\3\ based on the 3-year
average of the annual 98th percentile values of 24-hour
PM2.5 concentrations at each monitor within an area.\4\ On
October 17, 2006, the EPA revised the level of the 24-hour
PM2.5 NAAQS to 35 [micro]g/m\3\ based on a 3-year average of
the annual 98th percentile values of 24-hour concentrations.\5\ On
January 15, 2013, the EPA revised the annual standard to 12.0 [micro]g/
m\3\ based on a 3-year average of annual mean PM2.5
concentrations.\6\ We refer to this standard as the 2012
PM2.5 NAAQS.
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    \3\ 62 FR 38652. The initial NAAQS for PM2.5 included
annual standards of 15.0 [micro]g/m\3\ based on a 3-year average of
annual mean PM2.5 concentrations and 24-hour (daily)
standards of 65 [micro]g/m\3\ based on a 3-year average of 98th
percentile 24-hour concentrations (40 CFR 50.7).
    \4\ The primary and secondary standards were set at the same
level for both the 24-hour and the annual PM2.5
standards.
    \5\ 71 FR 61144.
    \6\ 78 FR 3086.
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    California submitted the Portola PM2.5 Plan to provide
for attainment of the 2012 PM2.5 NAAQS in the Portola
nonattainment area, which the EPA has designated and classified as
``Moderate'' nonattainment for these NAAQS.\7\ On December 18, 2018, we
proposed to approve the following elements of the Portola
PM2.5 Plan: The 2013 base year emissions inventories, the
reasonably available control measure/reasonably available control
technology (RACM/RACT) demonstration, the attainment demonstration, the
reasonable further progress demonstration, the quantitative milestones,
and the budgets for 2019 and 2021. We did not propose action on the
contingency measures in the Portola PM2.5 Plan.\8\
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    \7\ 80 FR 2206 (January 15, 2015).
    \8\ 83 FR 64774.
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    As part of the December 18, 2018 action, we proposed to find that
the collection of PM2.5 control requirements in the Portola
PM2.5 Plan implements all RACM/RACT for the control of
direct PM2.5 and to approve the PM2.5 RACM
demonstration in the Portola PM2.5 Plan as meeting the
requirements of CAA sections 172(c)(1) and 189(a)(1)(C) and 40 CFR
51.1009. The RACM/RACT measures in the Plan include the District's
enforceable commitment to implement the voluntary wood stove change-out
program, the City of Portola Wood Stove and Fireplace Ordinance, CARB's
mobile source program, the District's commitment to strengthen its open
burning measure, and other controls on sources in the nonattainment
area.
    We also proposed to find that the attainment demonstration in the
Portola PM2.5 Plan satisfies the requirements of sections
189(a)(1)(B) and 172(c)(1) of the CAA and 40 CFR 51.1011(a). In support
of this proposal, we found that the State used two acceptable modeling
techniques to demonstrate attainment of the 2012 PM2.5 NAAQS
in the Portola nonattainment area, and that the plan demonstrates
attainment as

expeditiously as practicable. We also found that the Portola
PM2.5 Plan provides a clear and convincing justification for
its extensive reliance on a voluntary wood stove change-out incentive
program as the primary strategy for attainment, and that all of the
control measures in the Plan, including the District's enforceable
commitment to implement the wood stove change-out program, together
ensure that projected emission reductions will occur in time to provide
for attainment of the 2012 PM2.5 NAAQS by the December 31,
2021 attainment date. Our December 18, 2018 proposed rule provides a
more detailed discussion of our evaluation of the Plan.\9\
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    \9\ Id.
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II. Public Comments and EPA Responses

    The EPA's proposed action provided a 30-day public comment period
that ended on January 17, 2019. We did not receive any comments during
this period.

III. Final Action

    Under CAA section 110(k)(3), the EPA is approving SIP revisions
submitted by California to address the Act's Moderate area planning
requirements for the 2012 PM2.5 NAAQS in the Portola
nonattainment area. Specifically, the EPA is approving the following
elements of the Portola PM2.5 Plan:
    1. The 2013 base year emissions inventories as meeting the
requirements of CAA section 172(c)(3);
    2. the reasonably available control measure/reasonably available
control technology demonstration as meeting the requirements of CAA
sections 172(c)(1) and 189(a)(1)(C);
    3. the attainment demonstration as meeting the requirements of CAA
sections 172(c)(1) and 189(a)(1)(B);
    4. the reasonable further progress demonstration as meeting the
requirements of CAA section 172(c)(2);
    5. the quantitative milestones as meeting the requirements of CAA
section 189(c); and
    6. the motor vehicle emissions budgets for 2019 and 2021, because
they are derived from approvable attainment and reasonable further
progress demonstrations and meet the requirements of CAA section 176(c)
and 40 CFR part 93, subpart A.
    The EPA is not taking action at this time on the contingency
measures or the post-attainment year (2022) budget in the Portola
PM2.5 Plan.

IV. Statutory and Executive Order Reviews

    Under the CAA, the Administrator is required to approve a SIP
submission that complies with the provisions of the Act and applicable
federal regulations. 42 U.S.C. 7410(k); 40 CFR 52.02(a). Thus, in
reviewing SIP submissions, the EPA's role is to approve state choices,
provided that they meet the criteria of the CAA. Accordingly, this
action merely approves State law as meeting federal requirements and
does not impose additional requirements beyond those imposed by State
law. For that reason, this action:
     Is not a ``significant regulatory action'' subject to
review by the Office of Management and Budget under Executive Orders
12866 (58 FR 51735, October 4, 1993) and 13563 (76 FR 3821, January 21,
2011);
     is not an Executive Order 13771 (82 FR 9339, February 2,
2017) regulatory action because SIP approvals are exempted under
Executive Order 12866;
     does not impose an information collection burden under the
provisions of the Paperwork Reduction Act (44 U.S.C. 3501 et seq.);
     is certified as not having a significant economic impact
on a substantial number of small entities under the Regulatory
Flexibility Act (5 U.S.C. 601 et seq.);
     does not contain any unfunded mandate or significantly or
uniquely affect small governments, as described in the Unfunded
Mandates Reform Act of 1995 (Pub. L. 104-4);
     does not have Federalism implications as specified in
Executive Order 13132 (64 FR 43255, August 10, 1999);
     is not an economically significant regulatory action based
on health or safety risks subject to Executive Order 13045 (62 FR
19885, April 23, 1997);
     is not a significant regulatory action subject to
Executive Order 13211 (66 FR 28355, May 22, 2001);
     is not subject to requirements of Section 12(d) of the
National Technology Transfer and Advancement Act of 1995 (15 U.S.C. 272
note) because application of those requirements would be inconsistent
with the CAA; and
     does not provide the EPA with the discretionary authority
to address disproportionate human health or environmental effects with
practical, appropriate, and legally permissible methods under Executive
Order 12898 (59 FR 7629, February 16, 1994).
    In addition, the SIP is not approved to apply on any Indian
reservation land or in any other area where the EPA or an Indian tribe
has demonstrated that a tribe has jurisdiction. In those areas of
Indian country, the rule does not have tribal implications and will not
impose substantial direct costs on tribal governments or preempt tribal
law as specified by Executive Order 13175 (65 FR 67249, November 9,
2000).
    The Congressional Review Act, 5 U.S.C. 801 et seq., as added by the
Small Business Regulatory Enforcement Fairness Act of 1996, generally
provides that before a rule may take effect, the agency promulgating
the rule must submit a rule report, which includes a copy of the rule,
to each House of the Congress and to the Comptroller General of the
United States. The EPA will submit a report containing this action and
other required information to the U.S. Senate, the U.S. House of
Representatives, and the Comptroller General of the United States prior
to publication of the rule in the Federal Register. A major rule cannot
take effect until 60 days after it is published in the Federal
Register. This action is not a ``major rule'' as defined by 5 U.S.C.
804(2).
    Under section 307(b)(1) of the Clean Air Act, petitions for
judicial review of this action must be filed in the United States Court
of Appeals for the appropriate circuit by May 24, 2019. Filing a
petition for reconsideration by the Administrator of this final rule
does not affect the finality of this action for the purposes of
judicial review nor does it extend the time within which a petition for
judicial review may be filed, and shall not postpone the effectiveness
of such rule or action. This action may not be challenged later in
proceedings to enforce its requirements. (See section 307(b)(2).)

List of Subjects in 40 CFR Part 52

    Environmental protection, Air pollution control, Ammonia,
Incorporation by reference, Intergovernmental relations, Oxides of
nitrogen, Particulate matter, Reporting and recordkeeping requirements,
Sulfur oxides, Volatile organic compounds.

    Authority:  42 U.S.C. 7401 et seq.

    Dated: February 20, 2019.
Deborah Jordan,
Acting Regional Administrator, Region IX.

    Part 52, chapter I, title 40 of the Code of Federal Regulations is
amended as follows:

PART 52--APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS

0
1. The authority citation for part 52 continues to read as follows:

    Authority: 42 U.S.C. 7401 et seq.

Subpart F--California

0
2. Section 52.220 is amended by adding paragraphs (c)(500)(ii) and
(c)(515) to read as follows:

Sec.  52.220  Identification of plan--in part.

* * * * *
    (c) * * *
    (500) * * *
    (ii) Additional materials. (A) Northern Sierra Air Quality
Management District.
    (1) The ``Portola Fine Particulate Matter (PM2.5)
Attainment Plan,'' adopted January 23, 2017, excluding subchapter V.G
(``Demonstrating Attainment of the 24-hour Standard''), subchapter VI.B
(``Contingency Measure''), and appendices.
    (2) [Reserved]
* * * * *
    (515) The following additional materials were submitted on December
20, 2017, by the Governor's designee.
    (i) [Reserved]
    (ii) Additional materials. (A) California Air Resources Board.
    (1) Resolution 17-28, ``Supplemental Transportation Conformity
Emissions Budgets for the Portola Fine Particulate Matter
(PM2.5) Attainment Plan,'' October 26, 2017, excluding the
2022 conformity budget.
    (2) [Reserved]
* * * * *
[FR Doc. 2019-05163 Filed 3-22-19; 8:45 am]
 BILLING CODE 6560-50-P


UNITED STATES ENVIRONMENTAL PROTECTION AGENCY WASHINGTON, D. C. 20460 OFFICE OF PREVENTION, PESTICIDES AND TOXIC SUBSTANCES PC Code: 035505 DP Barcode: D281404 MEMORANDUM March 11, 2002 SUBJECT: Drinking Water Reassessment for diuron and its degradates TO: Diana Locke Reregistration Actions Branch II Health Effects Division ( 7509C)

FROM: Ibrahim Abdel Saheb/ Agronomist Environmental Risk Branch II Environmental Fate and Effects Division ( 7507C)

PEER REVIEW: Sid Abel/ Environmental Scientist Environmental Risk Branch II Environmental Fate and Effects Division ( 7507C)

THRU: Tom Bailey, Branch Chief Environmental Risk Branch II Environmental Fate and Effects Division ( 7507C)

CONCLUSIONS This memorandum transmits re calculated estimated drinking water concentrations for use in the human health risk assessment. Griffin Label ( EPA Reg. No. 1812 362) was used to determine the estimated concentrations.

The Tier II screening models PRZM1 and EXAMS2 were rerun using the Index Reservoir and Percent Crop Area adjustment to 2 determine estimated surface water concentrations of diuron and its degradates dichlorophenylmethylurea ( DCPMU); dichlorophenylurea ( DCPU); 3,4 dichloraniline ( 3,4 DCA); and N'( 3 chlorophenyl) N Ndimethylurea ( mCPDMU). The Screening Concentration in Groundwater ( SCI GROW3) model was used to estimate groundwater concentrations for Diuron and its degradates. Modeling results are shown in Table 1.

Table 1. Estimated environmental concentrations in surface and groundwater for diuron and its degradates use on citrus.

Toxicity end point model EECs ( F g/ L) use( s) modeled PCA Diuron DCPMU DCPU 3,4 DCA mCPDMU one application of diuron on citrus @ 9.6 lb ai/ acre, ground application Default ( 0.87)

Surface water/ peak 613 130 5.80 0.08 136 Surface water/ 1 10 year average) 128 27.0 1.20 0.02 36.4 Surface water/ mean of annual values) 85.0 18.0 0.80 0.01 25.5 Groundwater/ ( peak and long term average) 6.5 2.50 0.1 2X10 4 1.38 The IR PCA modeling results indicate that diuron and its degradates have the potential to contaminate surface waters by runoff in areas with large amounts of annual rainfall. The degradate 3,4 DCA is commonly seen in surface water in areas with high diuron and propanil usage, however, EFED has received no guideline studies on the environmental fate and transport of 3,4 DCA or other degradate of diuron. EFED believes that additional studies are needed to fully understand both the fate and transport of these compounds in the environment.

Modeling results were higher than data from existing diuron surface water monitoring studies targeted to the pesticide use area. Modeling values where several orders of magnitude ( ranging from 9 100 times) higher than monitoring data.

Major degradates that were determined by HED to be of toxicological concern include: dichlorophenylmethylurea ( DCPMU), 3 dichlorophenylurea ( DCPU), 3,4 dichloroaniline ( 3,4 DCA), and N'( 3 chlorophenyl) N N dimethylurea ( mCPDMU)]. Because the EFED lacks complete environmental fate data ( such as the aerobic aquatic and anaerobic aquatic studies) on these degradates, this memorandum addresses the estimated environmental concentrations ( EEC's) for surface and groundwater based on half lives that were calculated on cumulative residues.

Usage map for diuron4 is attached.

Surface Water Monitoring The EFED has targeted, but, limited monitoring data on the concentrations of diuron and its degradates in surface water.

A study on the occurrence of cotton herbicides and insecticides in Playa lakes of the high plains of western Texas concluded that diuron was the major pesticide detected in water samples collected from 32 lakes with a mean concentration of 2.7 ppb. Diuron metabolites ( DCPMU, DCPU, and 3,4 DCA) were found in 71% of the samples analyzed. The mean concentrations of these metabolites were 0.45 ppb for DCPMU, 0.31 ppb for 3,4 DCA, and 0.2 ppb for DCPU5. In this study, water samples were taken within two days after diuron application to cotton in the region. Diuron usage on cotton in this part of the state reached an average of $ 1.379 lb ai/ mile2/ yr. Even though, the monitoring of diuron concentrations from use on Cotton in this part of the state is an example of a targeted study, the frequency of surface water sampling and the length of sampling period were insufficient to satisfy the temporal and spatial requirements for regulatory purposes. This study has limited use in a national assessment because we do not expect western Texas to be one of the most vulnerable use areas for runoff. However, because the samples were taken within two days after application, the results may represent a lower bound of possible peak concentrations that could occur in drinking water in that area.

The US Geological Survey ( USGS) National Water Quality Assessment Program ( NAWQA) collected 1420 surface water samples 4 from 62 agricultural stream sites during the period from 1992 1998. One to two samples was collected each month during periods when pesticide transport in the streams was expected to be low throughout the year. At most sites, the sampling frequency was increased to 1 to 3 samples per week during periods when elevated levels of pesticides were expected in the streams. Diuron was detected in 7.32% of the samples ( detection limit = 0.05 ppb) with concentration of 0.13 ppb in 95% of samples. Diuron maximum concentration was 13 ppb ( estimated concentration) 6.

Modeling Tier II surface water modeling was done using the Index Reservoir ( IR) and Percent Crop Area ( PCA) modifications to PRZM and EXAMS.

The index reservoir represents a potential vulnerable drinking water source from a specific area ( Illinois) with specific cropping patterns, weather, soils, and other factors.

The PCA is a generic watershed based adjustment factor which represent the portion of a watershed planted to a crop or crops and will be applied to pesticide concentrations estimated for the surface water component of the drinking water exposure assessment using PRZM/ EXAMS with the index reservoir scenario7.

The IR PCA PRZM/ EXAMS model use and fate input parameters for diuron and its degradates in surface water are shown in Tables 2 6. The IR PC PRZM/ EXAMS model input and output files for diuron and its degradates are shown in Appendix I. 5 Table 2: IR PC PRZM/ EXAMS input parameters for diuron.

Input variable Input value & calculations Source/ Quality of data Crop name citrus label ( EPA Reg. No. 1812 362).

application rate ( lb ai/ acre) 9.6 label ( EPA Reg. No. 1812 362).

Application efficiency 0.99 IR PC Guidance8 Spray drift fraction 0.064 IR PC Guidance Application method ground label ( EPA Reg. No. 1812 362).

DWRATE ( day 1) 0.0006 MRID# 41719303; Input parameters guidance8 DSRATE ( day 1) 0.0006 MRID# 41719303; Input parameters guidance Kd ( mL/ g) 14 MRID# 44490501; Input parameters guidance Henry ( atm. m3/ mole) 2.2X10 10 ( calculated) Product Chemistry chapter for HED RED, 2001.

KBACW ( h 1) 0.0003 Aerobic aquatic met. t ½ was multiplied by 3. MRID# 42260501. Input parameters guidance.

KBACS ( h 1) 0.002 aquatic met. t ½ was multiplied by 3. MRID# MRID# 42661901. Input parameters guidance.

KDP ( h 1) 0.0007 MRID# 41418805; Input parameters guidance.

KBH, KNH, KAH ( h 1) 0 ( stable) MRID# 41418804.

KPS ( mL/ g) 16.6 MRID# 44490501; Input parameters guidance. 6 MWT ( g/ mole) 233.1 The MERCK INDEX9 Solubility @ 25 0C ( ppm) 420 Product Chemistry chapter for HED RED, 2001; Input parameters guidance.

Vapor pressure ( torr) 2.0X10 7 Product Chemistry chapter for HED RED, 2001. 7 Table 3: IR PC PRZM/ EXAMS input parameters for DCPMU.

Input variable Input value & calculations Source/ Quality of data Crop name citrus label ( EPA Reg. No. 1812 362).

application rate ( lb ai/ acre) 2.03 label ( EPA Reg. No. 1812 362). An equivalent value based on maximum conversion of diuron to degradates and the molecular weight ratio adjustment.

Application efficiency 0.99 IR PC Guidance Spray drift fraction 0.064 IR PC Guidance Application method ground label ( EPA Reg. No. 1812 362).

DWRATE ( day 1) 0.0003 MRID# 41719303; Input parameters guidance8 DSRATE ( day 1) 0.0003 MRID# 41719303; Input parameters guidance Kd ( mL/ g) for diuron: 14 MRID# 44490501; Input parameters guidance Henry ( atm. m3/ mole) for diuron: 2.2X10 10 ( calculated) Product Chemistry chapter for HED RED, 2001.

KBACW ( h 1) for diuron: 0.0003 No aerobic aquatic data is available, diruon t ½ was multiplied by 3, MRID# 41719303. Input parameters guidance.

KBACS ( h 1) for diuron: 0.002 No anaerobic aquatic data is available, the anaerobic soil met. t ½ was multiplied by 0.5. MRID# 41418806. Input parameters guidance.

KDP ( h 1) for diuron: 0.0007 MRID# 41418805; Input parameters guidance.

KBH, KNH, KAH ( h 1) for diuron: 0 ( stable) MRID# 41418804.

KPS ( mL/ g) for diuron: 16.6 MRID# 44490501; Input parameters guidance.

MWT ( g/ mole) 219.1 The MERCK INDEX Solubility @ 25 0C ( ppm) for diuron: 420 Product Chemistry chapter for HED RED, 2001; Input parameters guidance. 8 Vapor pressure ( torr) for diuron: 2.0X10 7 Product Chemistry chapter for HED RED, 2001.

Table 4: IR PC PRZM/ EXAMS input parameters for DCPU.

Input variable Input value & calculations Source/ Quality of data Crop name citrus label ( EPA Reg. No. 1812 362).

application rate ( lb ai/ acre) 0.08 label ( EPA Reg. No. 1812 362). An equivalent value based on maximum conversion of diuron to degradates and the molecular weight ratio adjustment.

Application efficiency 0.99 IR PC Guidance Spray drift fraction 0.064 IR PC Guidance Application method ground label ( EPA Reg. No. 1812 362).

DWRATE ( day 1) 0.0003 MRID# 41719303; Input parameters guidance8 DSRATE ( day 1) 0.0003 MRID# 41719303; Input parameters guidance Kd ( mL/ g) for diuron: 14 MRID# 44490501; Input parameters guidance Henry ( atm. m3/ mole) for diuron: 2.2X10 10 ( calculated) Product Chemistry chapter for HED RED, 2001.

KBACW ( h 1) for diuron: 0.0003 No aerobic aquatic data is available, diruon t ½ was multiplied by 3, MRID# 41719303. Input parameters guidance.

KBACS ( h 1) for diuron: 0.002 No anaerobic aquatic data is available, the anaerobic soil met. t ½ was multiplied by 0.5. MRID# 41418806. Input parameters guidance.

KDP ( h 1) for diuron: 0.0007 MRID# 41418805; Input parameters guidance.

KBH, KNH, KAH ( h 1) for diuron: 0 ( stable) MRID# 41418804. 9 KPS ( mL/ g) for diuron: 16.6 MRID# 44490501; Input parameters guidance.

MWT ( g/ mole) 205.1 The MERCK INDEX Solubility @ 25 0C ( ppm) for diuron: 420 Product Chemistry chapter for HED RED, 2001; Input parameters guidance.

Vapor pressure ( torr) for diuron: 2.0X10 7 Product Chemistry chapter for HED RED, 2001.

Table 5: IR PC PRZM/ EXAMS input parameters for 3,4 DCA.

Input variable Input value & calculations Source/ Quality of data Crop name citrus label ( EPA Reg. No. 1812 362).

application rate ( lb ai/ acre) 0.0021 label ( EPA Reg. No. 1812 362). An equivalent value based on maximum conversion of diuron to degradates and the molecular weight ratio adjustment.

Application efficiency 0.99 IR PC Guidance7 Spray drift fraction 0.064 IR PC Guidance Application method ground label ( EPA Reg. No. 1812 362).

DWRATE ( day 1) 0.008 MRID# 41719303; Input parameters guidance8 DSRATE ( day 1) 0.008 MRID# 41538701; Input parameters guidance Kd ( mL/ g) for diuron: 14 MRID# 44490501; Input parameters guidance Henry ( atm. m3/ mole) for diuron: 2.2X10 10 ( calculated) Product Chemistry chapter for HED RED, 2001.

KBACW ( h 1) for diuron: 0.0003 No aerobic a q u a t i c d a t a i s available, diruon t ½ was multiplied by 3, MRID# 41719303. Input parameters guidance.

KBACS ( h 1) for diuron: 0.002 No anaerobic aquatic data is available, the anaerobic soil met. t ½ was multiplied by 0.5. MRID# 41418806. Input parameters guidance. 10 KDP ( h 1) for diuron: 0.0007 MRID# 41418805; Input parameters guidance.

KBH, KNH, KAH ( h 1) for diuron: 0 ( stable) MRID# 41418804.

KPS ( mL/ g) for diuron: 16.6 MRID# 44490501; Input parameters guidance.

MWT ( g/ mole) 162.1 The MERCK INDEX Solubility @ 25 0C ( ppm) for diuron: 420 Product Chemistry chapter for HED RED, 2001; Input parameters guidance.

Vapor pressure ( torr) for diuron: 2.0X10 7 Product Chemistry chapter for HED RED, 2001.

Table 6: IR PC PRZM/ EXAMS input parameters for mPDMU.

Input variable Input value & calculations Source/ Quality of data Crop name citrus label ( EPA Reg. No. 1812 362).

application rate ( lb ai/ acre) 2.04 label ( EPA Reg. No. 1812 362). An equivalent value based on maximum conversion of diuron to degradates and the molecular weight ratio adjustment.

Application efficiency 0.99 IR PC Guidance Spray drift fraction 0.064 IR PC Guidance Application method ground label ( EPA Reg. No. 1812 362).

DWRATE ( day 1) for diuron: 0.0006 MRID# 41719303; Input parameters guidance8 DSRATE ( day 1) for diuron: 0.0006 MRID# 41719303; Input parameters guidance Kd ( mL/ g) for diuron: 14 MRID# 44490501; Input parameters guidance Henry ( atm. m3/ mole) for diuron: 2.2X10 10 ( calculated) Product Chemistry chapter for HED RED, 2001.

KBACW ( h 1) 0.00008 MRID# 42661901. Input parameters guidance. 11 KBACS ( h 1) 0.00005 MRID# 42260501. Input parameters guidance.

KDP ( h 1) for diuron: 0.0007 MRID# 41418805; Input parameters guidance.

KBH, KNH, KAH ( h 1) for diuron: 0 ( stable) MRID# 41418804.

KPS ( mL/ g) for diuron: 16.6 MRID# 44490501; Input parameters guidance.

MWT ( g/ mole) 198.1 The MERCK INDEX Solubility @ 25 0C ( ppm) for diuron: 420 Product Chemistry chapter for HED RED, 2001; Input parameters guidance.

Vapor pressure ( torr) for diuron: 2.0X10 7 Product Chemistry chapter for HED RED, 2001.

Assumptions and Uncertainties7,10 Index Reservoir The index reservoir represents potential drinking water exposure from a specific area ( Illinois) with specific cropping patterns, weather, soils, and other factors. Use of the index reservoir for areas with different climates, crops, pesticides used, sources of water ( e. g. rivers instead of reservoirs, etc), and hydrogeology creates uncertainties. In general, because the index reservoir represents a fairly vulnerable watershed, the exposure estimated with the index reservoir will likely be higher than the actual exposure for most drinking water sources. However, the index reservoir is not a worst case scenario, communities that derive their drinking water from smaller bodies of water with minimal outflow, or with more runoff prone soils would likely get higher drinking water exposure than estimated using the index reservoir. Areas with a more humid climate that use a similar reservoir and cropping patterns may also get more pesticides in their drinking water than predicted using this scenario.

A single steady flow has been used to represent the flow through the reservoir. Discharge from the reservoir also removes chemical so this assumption will underestimate removal from the 12 reservoir during wet periods and overestimates removal during dry periods. This assumption can both underestimate or overestimate the concentration in the pond depending upon the annual precipitation pattern at the site.

The index reservoir scenario uses the characteristics of a single soil to represent the soil in the basin. In fact, soils can vary substantially across even small areas, and this variation is not reflected in these simulations.

The index reservoir scenario does not consider tile drainage. Areas that are prone to substantial runoff are often tile drained. Tile drainage contributes additional water and in some cases, additional pesticide loading to the reservoir. This may cause either an increase or decrease in the pesticide concentration in the reservoir. Tile drainage also causes the surface soil to dry out faster. This will reduce runoff of the pesticide into the reservoir. The watershed used as the model for the index reservoir ( Shipman City Lake) does not have tile drainage in the cropped areas.

EXAMS is unable to easily model spring and fall turnover. Turnover occurs when the temperature drops in the fall and the thermal stratification of the reservoir is removed. Turnover occurs again in the spring when the reservoir warms up. This results in complete mixing of the chemical through the water column at these times. Because of this inability, the Index Reservoir has been simulated without stratification. There is data to suggest that Shipman City Lake, upon which the Index Reservoir is based, does indeed stratify in the deepest parts of the lake at least in some years. This may result in both over and underestimation of the concentration in drinking water depending upon the time of the year and the depth the drinking water intake is drawing from.

Percent Crop Area Correction Factor The PCA is a watershed based modification. Implicit in its application is the assumption that currently used field scale models reflect basin scale processes consistently for all pesticides and uses. In other words, we assume that the large field simulated by the coupled PRZM and EXAMS models is a reasonable approximation of pesticide fate and transport within a watershed that contains a drinking water reservoir. If the 13 models fail to capture pertinent basin scale fate and transport processes consistently for all pesticides and all uses, the application of a factor that reduces the estimated concentrations predicted by modeling could, in some instances, result in inadvertently passing a chemical through the screen that may actually pose a risk. Some preliminary assessments made in the development of the PCA suggest that PRZM/ EXAMS may not be realistically capturing basin scale processes for all pesticides or for all uses. A preliminary survey of water assessments which compared screening model estimates to readily available monitoring data suggest uneven model results. In some instances, the screening model estimates are more than an order of magnitude greater than the highest concentrations reported in available monitoring data; in other instances, the model estimates are less than monitoring concentrations. Because of these concerns, the SAP recommended using the PCA only for " major" crops in the Midwest. For other crops, development of PCA's will depend on the availability of relevant monitoring data that could be used to evaluate the result of the PCA adjustment.

The spatial data used for the PCA came from readily available sources and have a number of inherent limitations:

° The size of the 8 digit HUC [ mean = 366,989 ha; range = 6.7 2,282,081 ha; n = 2,111] may not provide reasonable estimates of actual PCA's for smaller watersheds. The watersheds that drain into drinking water reservoirs are generally smaller than the 8 digit HUC and may be better represented by watersheds defined for drinking water intakes. ° The conversion of the county level data to watershed based percent crop areas assumes the distribution of the crops within a county is uniform and homogeneous throughout the county area. Distance between the treated fields and the water body is not addressed. ° The PCA's were generated using data from the 1992 Census of Agriculture. However, recent changes in the agriculture sector from farm bill legislation may significantly impact the distribution of crops throughout the country. The methods described in this report can rapidly be updated as more current agricultural crops data are obtained. The assumption that yearly changes in cropping patterns will cause minimal impact needs to be evaluated. 14 The PCA adjustment is only applicable to pesticides applied to agricultural crops. Contributions to surface waters from nonagricultural uses such as urban environments are not wellmodeled Currently, non agricultural uses are not included in the screening model assessments for drinking water.

The PCA does not consider percent crop treated because detailed pesticide usage data are extremely limited at this time. Detailed pesticide usage data are currently available for only a few states.

Groundwater Monitoring EFED has limited targeted monitoring data on the concentrations of diuron and its degradates in groundwater. Table 7 shows validated monitoring data for diuron that are available for the states of California ( CA), Florida ( FL), Georgia ( GA), and Texas ( TX).

Table 7. Groundwater monitoring data for diuron. Number of wells sampled ( number of wells with residues) 11.

State number of well range of conc. ( ppb) 15 CA 2010 ( 82) 0.05  3.95 FL 15385 ( 9) 1.18  5.37 GA 70 ( 67) 1.00  5.00 TX 31 ( 2) 0.01  0.02 According to the Ground Water Protection Section of the Florida Department of Environmental Protection12, ground water samples from wells collected between May/ 1990 and November/ 1997, showed diuron detections ranging from 0.94  12 ppb ( detection limit = 0.48 ppb). The arithmetic mean concentration was 2.44 ppb. Well water samples were collected from the following counties: Highlands, Jackson, Lake, Orange, and Polk. With the exception of the 12 ppb sample in Orange County, the majority of the detections were in Highlands County where citrus is grown. Diuron concentrations in Highlands County decreased with time to about 1 ppb but were detected every year. In Polk County, diuron concentrations show a seasonal pattern, with highest concentrations in the spring and lowest concentrations in the fall, but was not detected in all years.

The US Geological Survey ( USGS) National Water Quality Assessment Program ( NAWQA) 13 analyzed pesticide occurrence and concentrations for major aquifers and shallow ground water in agricultural areas ( detection limit = 0.05 ppb). Analysis of 2608 samples ( major aquifers study) showed diuron in 71% of the samples analyzed with a maximum concentration of 0.34 ppb. Maximum diuron concentration in 897 samples from shallow groundwater sites was 2.0 ppb, with diuron detected in only 1.23% of samples analyzed ( USGS, 1998). A major component of the sampling design in the NAWQA study was to target specific watersheds and shallow ground water areas that are influenced primarily by a single dominant land use( agricultural or urban) that is important in the particular area. The ground water data were primarily collected from a combination of production and monitoring wells. Ground water sampling sites were sampled for pesticides from a single snap shot in time.

Even though, the groundwater monitoring data collected by NAWQA are from sites considered typical for use areas, the frequency of sampling and the length of sampling period were not sufficient to represent the temporal and spatial requirements for regulatory purposes. 16 Major component of the sampling design in the NAWQA study was to target specific watersheds and shallow ground water areas that are influenced primarily by a single dominant land use( agricultural or urban) that is important in the particular area. The ground water data were primarily collected from a combination of production and monitoring wells. Ground water sites in the ground water data were sampled for pesticides from a single snap shot in time.

Modeling The SCI GROW model was used to estimate potential groundwater concentrations for diuron and its degradates.

Tables 8, and 9 show input parameters and output for SCI GROW modeling of diuron and its degradates, respectively.

Table 8. Input parameters for diuron and its degradates used in the SCI GROW model.

compound appl. rate ( lb ai/ acre) No. of appl. / year Aerobic soil t1/ 2 ( d) Koc ( mL/ g) Source/ Quality of data Diuron 9.6 1 372 468 label ( EPA Reg. No. 1812 362); MRID# 44490501; MRID# 41719303; Input parameters guideline ( Aug. 2000). Good data.

DCPMU 2.03* 1 770 468 label ( EPA Reg. No. 1812 362); MRID# 44490501; MRID# ; Input parameters guideline ( Aug. 2000). Good data.

DCPU 0.08* 1 770 468 label ( EPA Reg. No. 1812 362); MRID# 44490501; MRID# 41719303; Input parameters guideline ( Aug. 2000). Good data.

3,4 DCA 0.0021* 1 30 468 label ( EPA Reg. No. 1812 362); MRID# 44490501; MRID# 41719303; MRID# 41538701; Input parameters guideline ( Aug. 2000). Good data. 17 mCPDMU 2.04* 1 372 468 label ( EPA Reg. No. 1812 362); MRID# 44490501; MRID# 41719303; MRID# 42260501; Input parameters guideline ( Aug. 2000). Good data.

*: An equivalent value based on conversion of diuron to degradates.

Table 9. SCI GROW estimated environmental concentrations for diuron and its degradates in groundwater.

Toxicity end point model EECs ( F g/ L) use( s) modeled Diuron DCPMU DCPU 3,4 DCA mCPDMU one application of diuron on citrus @ 9.6 lb ai/ acre acute 6.5 2.50 0.09 0.0002 1.38 Chronic ( non cancer) 6.5 2.50 0.09 0.0002 1.38 Chronic ( cancer) 6.5 2.50 0.09 0.0002 1.38 The SCI GROW screening model developed by EFED indicates that diuron and its degradates concentrations are much less than those estimated for surface water. SCI GROW estimated concentrations of diuron do fall within the values from monitoring data shown in Table 8, but below some of the reported monitoring data. This means that SCI GROW could underestimate chemical concentrations in typical use areas when the pesticide is used at the maximum allowed label rate in areas with ground water exceptionally vulnerable to contamination such as Florida.

Limitations of the SCI GROW2 Analysis The SCI GROW model ( Screening Concentrations in Ground Water) is a model for estimating concentrations of pesticides in ground water under " maximum loading" conditions. SCI GROW provides a screening concentration, an estimate of likely ground water concentrations if the pesticide is used at the maximum allowed label rate in areas with ground water that is vulnerable to contamination. In most cases, a majority of the use area will have ground water that is less vulnerable to contamination than the areas used to derive the SCI GROW estimate. 18 References:

4. Carsel, R. F., J. C. Imhoff, P. R. Hummel, J. M. Cheplick and J. S. Donigian, Jr. 1997. PRZM 3, A Model for Predicting Pesticide and Nitrogen Fate in Crop Root and Unsaturated Soil Zones: Users Manual for Release 3.0; Environmental Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency, Athens, GA.

2. Burns, L. A. March 1997. Exposure Analysis Modeling System ( EXAMSII) Users Guide for Version 2.97.5, Environmental Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency, Athens, GA.

3. Barrett, M., 1997, Proposal For a Method to Determine Screening Concentration Estimates for Drinking Water Derived from Groundwater Studies, EFED/ OPP.

4. USGS. 1992. National Water Quality Assessment ( NWQA), Pesticides National Synthesis Project, Annual Use: Diuron.

5. Thurman, E. M., K. C. Bastian, and T. Mollhagen. Occurrence of cotton herbicides and insecticides in Playa lakes of the high plains of western Texas. [ Online]. Available at http:// toxics. usgs. gov/ pubs/ wri99 4018/ Volume2/ sectionC/ 2 403Thurman/ pdf/ 2403_ Thurman. pdf, May, 2001).

6. U. S GS. 1998. National Water Quality Assessment ( NWQA), Pesticides National Synthesis Project [ Online] at ( http:// ca. water. usgs. gov/ pnsp/ streamsum/ streamT1. html).

7. Effland, W., N. Thurman, I. Kennedy, R. D. Jones, J. Breithaupt, J. Lin, J. Carleton, L. Libel. R. Parker, and R. Matzner. 2000. " Guidance for use of the index Reservoir and Percent Crop Area Factor in drinking water exposure assessment s. Office of Pesticide Programs. 8. Guidance for Chemistry and Management Practice Input Parameters For Use in Modeling the Environmental Fate and Transport of Pesticides. Version 2. November 7, 2000. U. S. EPA Office of Pesticide Programs, Environmental Fate and Effects Division.

9. The Merck Index. 1989. An encyclopedia of chemicals, drugs, and biologicals. 11th ed. Rahway, N. J. p. 533. 19 10. Jones, R. D., S. W. Abel, W. Effland, R. Matzner, and R. Parker. 1998. " An Index Reservoir for Use in Assessing Drinking Water Exposures. Chapter IV in Proposed Methods for Basin Scale Estimation of Pesticide Concentrations in Flowing Water and Reservoirs for Tolerance Reassessment., presented to the FIFRA Science Advisory Panel, July 1998. http:// www. epa. gov/ pesticides/ SAP/ 1998/ index. htm.

11. U. S. EPA. 1992. Pesticides in Ground Water Database A compilation of Monitoring Studies: 1971  1991. Office of Prevention, Pesticides, and Toxic Substances, EPA 734 12 92 001. 12. Florida Department of Environmental Protection. 2001. Personal communication with Bryan Baker @ the Groundwater Protection Section ( 850/ 921 9435).

13. USGS. 1998. National Water Quality Assessment ( NWQA), Pesticides National Synthesis Project, [ Online] at http:// ca. water. usgs. gov/ pnsp/ allsum/# over.

APPENDIX I IR PCA PRZM/ EXAMS INPUT AND OUT PUT FILES FOR MODELING DIURON AND ITS DEGRADATES DIURON Metfile: met156a. met PRZM scenario: FLcitrusC. txt 20 EXAMS environment file: IRPRZM0. EXV Chemical Name: diuron Description Variable Name Value Units Comments Molecular weight mwt 233.1 g/ mol Henry's Law Const. henry 2.2e 10 atm m^ 3/ mol Vapor Pressure vapr 2e 7 torr Solubility sol 420 mg/ L Kd Kd 16.6 mg/ L Koc Koc mg/ L Photolysis half life kdp 43 days Half life Aerobic Aquatic Metabolism kbacw 99 days Halfife Anaerobic Aquatic Metabolism kbacs 15 days Halfife Aerobic Soil Metabolism asm 1116 days Halfife Hydrolysis: pH 7 0 days Half life Method: CAM 2 integer See PRZM manual Incorporation Depth: DEPI 0.1 cm Application Rate: TAPP 10.76 kg/ ha Application Efficiency: APPEFF 0.99 fraction Spray Drift DRFT 0.064 fraction of application rate applied to pond Application Date Date 1 Jul dd/ mm or dd/ mmm or dd mm or dd mmm Record 17: FILTRA IPSCND 1 UPTKF Record 18: PLVKRT PLDKRT FEXTRC 0.5 Flag for Index Res. Run IR IR Flag for runoff calc. RUNOFF total none or total( average of entire run)

OUTPUT FILE stored as diuron. out Chemical: diuron PRZM environment: FLcitrusC. txt EXAMS environment: IRPRZM0. EXV Metfile: met156a. met Water segment concentrations ( ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1948 458 439 399 333 289 123 21 1949 244 234 219 196 179 67.97 1950 325 311 281 260 237 100 1951 547 526 458 348 287 107 1952 912 873 735 540 448 187 1953 412 395 342 318 297 122 1954 528 506 472 352 316 117 1955 298 286 245 204 186 80.43 1956 373 358 318 255 215 78.67 1957 728 702 596 548 495 178 1958 249 242 219 187 182 74.4 1959 364 349 307 298 285 111 1960 721 691 641 512 422 148 1961 179 172 143 123 110 52.43 1962 315 302 270 223 194 82.85 1963 438 419 371 280 226 84.78 1964 698 669 561 433 385 146 1965 397 380 333 308 271 122 1966 248 238 205 172 154 73.71 1967 428 415 360 324 302 126 1968 328 315 286 227 213 91.01 1969 407 389 357 297 265 106 1970 284 271 232 166 135 55.88 1971 246 240 213 171 161 72.11 1972 372 360 318 277 249 89.16 1973 329 317 281 226 196 81.47 1974 321 308 265 207 175 64.67 1975 255 244 205 176 156 67.02 1976 421 408 351 274 244 101 1977 276 264 222 208 198 83.01 1978 80.59 78.02 71.26 63.29 53.82 29.89 1979 360 344 297 251 240 107 1980 407 394 359 329 292 113 1981 627 602 523 468 395 135 1982 159 154 140 116 99.89 51.04 1983 515 500 432 328 272 95.07 Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.02702 7 912 873 735 548 495 187 0.05405 4 728 702 641 540 448 178 0.08108 1 721 691 596 512 422 148 0.10810 8 698 669 561 468 395 146 0.13513 5 627 602 523 433 385 135 0.16216 2 547 526 472 352 316 126 22 0.18918 9 528 506 458 348 302 123 0.21621 6 515 500 432 333 297 122 0.24324 3 458 439 399 329 292 122 0.27027 438 419 371 328 289 117 0.29729 7 428 415 360 324 287 113 0.32432 4 421 408 359 318 285 111 0.35135 1 412 395 357 308 272 107 0.37837 8 407 394 351 298 271 107 0.40540 5 407 389 342 297 265 106 0.43243 2 397 380 333 280 249 101 0.45945 9 373 360 318 277 244 100 0.48648 6 372 358 318 274 240 95.07 0.51351 4 364 349 307 260 237 91.01 0.54054 1 360 344 297 255 226 89.16 0.56756 8 329 317 286 251 215 84.78 0.59459 5 328 315 281 227 213 83.01 0.62162 2 325 311 281 226 198 82.85 0.64864 9 321 308 270 223 196 81.47 0.67567 6 315 302 265 208 194 80.43 0.70270 3 298 286 245 207 186 78.67 0.72973 284 271 232 204 182 74.4 0.75675 7 276 264 222 196 179 73.71 0.78378 4 255 244 219 187 175 72.11 0.81081 1 249 242 219 176 161 67.97 0.83783 8 248 240 213 172 156 67.02 0.86486 5 246 238 205 171 154 64.67 0.89189 244 234 205 166 135 55.88 23 2 0.91891 9 179 172 143 123 110 52.43 0.94594 6 159 154 140 116 99.89 51.04 0.97297 3 80.59 78.02 71.26 63.29 53.82 29.89 0.1 704.9 675.6 571.5 481.2 403.1 146.6 Average of yearly average s: 97.9047 2 Inputs generaged by pe3. pl of 6 March 2002 DCPMU Metfile: met156a. met PRZM scenario: FLcitrusC. txt EXAMS environment file: IRPRZM0. EXV Chemical Name: dcpmu Description Variable Name Value Units Comments Molecular weight mwt 219.1 g/ mol Henry's Law Const. henry 2.2e 10 atm m^ 3/ mol Vapor Pressure vapr 2e 7 torr Solubility sol 420 mg/ L Kd Kd 16.6 mg/ L Koc Koc mg/ L Photolysis half life kdp 43 days Half life Aerobic Aquatic Metabolism kbacw 99 days Halfife Anaerobic Aquatic Metabolism kbacs 15 days Halfife Aerobic Soil Metabolism asm 2310 days Halfife Hydrolysis: pH 7 0 days Half life Method: CAM 2 integer See PRZM manual Incorporation Depth: DEPI 0.1 cm Application Rate: TAPP 2.27 kg/ ha Application Efficiency: APPEFF 1.0 fraction Spray Drift DRFT fraction of application rate applied to pond Application Date Date 1 Jul dd/ mm or dd/ mmm or dd mm or dd mmm Record 17: FILTRA IPSCND 1 UPTKF 24 Record 18: PLVKRT PLDKRT FEXTRC 0.5 Flag for Index Res. Run IR IR Flag for runoff calc. RUNOFF total none or total( average of entire run)

OUTPUT FILE stored as dcpmu. out Chemical: dcpmu PRZM environment: FLcitrusC. txt EXAMS environment: IRPRZM0. EXV Metfile: met156a. met Water segment concentrations ( ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1948 98.66 94.47 86.14 71.43 62.07 25.85 1949 52.57 50.36 47.23 41.74 38.15 14.1 1950 65.48 62.73 56.33 53.1 48.39 20.87 1951 112 108 94.2 71.78 59.43 22.21 1952 190 182 153 113 93.65 39.57 1953 86.07 82.4 71.37 67.13 62.65 25.77 1954 109 104 97.29 72.81 65.75 24.6 1955 61.27 58.75 50.38 42.24 38.76 16.73 1956 79.68 76.47 68.08 54.8 45.89 16.47 1957 151 146 124 115 104 37.61 1958 47.89 46.62 42.55 37.05 36.71 15.3 1959 77.23 74.06 64.7 61.96 59.14 23.24 1960 156 150 138 111 91.33 31.36 1961 37.01 35.41 29.57 25.48 23.04 10.73 1962 66.38 63.52 56.79 47.19 40.25 17.36 1963 94.8 90.73 80.33 60.6 48.85 17.88 1964 150 143 120 93.04 83.1 31.06 1965 84.8 81.22 71.32 66.26 58.58 25.91 1966 50.82 48.7 41.83 34.92 31.53 15.2 1967 89.44 86.86 75.16 67.12 63.03 26.42 1968 68.38 65.51 59.28 47.49 44.72 18.93 1969 84.68 80.99 74.32 60.54 54.31 22.22 1970 60.77 58.12 49.66 35.48 28.64 11.44 1971 52.31 50.95 45.14 35.63 32.93 15.03 1972 75.94 73.54 65.2 57.42 51.97 18.52 1973 69.77 67.2 59.36 47.76 40.62 16.85 1974 67.55 64.68 55.56 43.6 36.69 13.28 1975 49.32 47.27 39.71 34.91 31.21 13.79 25 1976 88.99 86.16 74.33 58.16 50.53 21.14 1977 58.23 55.76 46.95 42.43 40.52 17.26 1978 17.29 16.59 15.17 13.58 11.52 5.866 1979 74.95 71.73 61.05 52.07 50.36 22.71 1980 85.67 82.81 75.83 68.59 61.02 23.67 1981 134 128 112 100 84.85 28.61 1982 34.17 32.94 29.9 25.07 21.51 10.49 1983 108 105 90.37 68.84 57.3 19.84 Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.02702 7 190 182 153 115 104 39.57 0.05405 4 156 150 138 113 93.65 37.61 0.08108 1 151 146 124 111 91.33 31.36 0.10810 8 150 143 120 100 84.85 31.06 0.13513 5 134 128 112 93.04 83.1 28.61 0.16216 2 112 108 97.29 72.81 65.75 26.42 0.18918 9 109 105 94.2 71.78 63.03 25.91 0.21621 6 108 104 90.37 71.43 62.65 25.85 0.24324 3 98.66 94.47 86.14 68.84 62.07 25.77 0.27027 94.8 90.73 80.33 68.59 61.02 24.6 0.29729 7 89.44 86.86 75.83 67.13 59.43 23.67 0.32432 4 88.99 86.16 75.16 67.12 59.14 23.24 0.35135 1 86.07 82.81 74.33 66.26 58.58 22.71 0.37837 8 85.67 82.4 74.32 61.96 57.3 22.22 0.40540 5 84.8 81.22 71.37 60.6 54.31 22.21 0.43243 2 84.68 80.99 71.32 60.54 51.97 21.14 0.45945 9 79.68 76.47 68.08 58.16 50.53 20.87 0.48648 6 77.23 74.06 65.2 57.42 50.36 19.84 0.51351 4 75.94 73.54 64.7 54.8 48.85 18.93 0.54054 1 74.95 71.73 61.05 53.1 48.39 18.52 0.56756 69.77 67.2 59.36 52.07 45.89 17.88 26 8 0.59459 5 68.38 65.51 59.28 47.76 44.72 17.36 0.62162 2 67.55 64.68 56.79 47.49 40.62 17.26 0.64864 9 66.38 63.52 56.33 47.19 40.52 16.85 0.67567 6 65.48 62.73 55.56 43.6 40.25 16.73 0.70270 3 61.27 58.75 50.38 42.43 38.76 16.47 0.72973 60.77 58.12 49.66 42.24 38.15 15.3 0.75675 7 58.23 55.76 47.23 41.74 36.71 15.2 0.78378 4 52.57 50.95 46.95 37.05 36.69 15.03 0.81081 1 52.31 50.36 45.14 35.63 32.93 14.1 0.83783 8 50.82 48.7 42.55 35.48 31.53 13.79 0.86486 5 49.32 47.27 41.83 34.92 31.21 13.28 0.89189 2 47.89 46.62 39.71 34.91 28.64 11.44 0.91891 9 37.01 35.41 29.9 25.48 23.04 10.73 0.94594 6 34.17 32.94 29.57 25.07 21.51 10.49 0.97297 3 17.29 16.59 15.17 13.58 11.52 5.866 0.1 150.3 143.9 121.2 103.3 86.794 31.15 Average of yearly average s: 20.4968 3 Inputs generaged by pe3. pl of 6 March 2002 DCPU Metfile: met156a. met PRZM scenario: FLcitrusC. txt EXAMS environment file: IRPRZM0. EXV Chemical Name: dcpu Description Variable Name Value Units Comments Molecular weight mwt 205.1 g/ mol Henry's Law Const. henry 2.2e 10 atm m^ 3/ mol 27 Vapor Pressure vapr 2e 7 torr Solubility sol 420 mg/ L Kd Kd 16.6 mg/ L Koc Koc mg/ L Photolysis half life kdp 43 days Half life Aerobic Aquatic Metabolism kbacw 99 days Halfife Anaerobic Aquatic Metabolism kbacs 15 days Halfife Aerobic Soil Metabolism asm 2310 days Halfife Hydrolysis: pH 7 0 days Half life Method: CAM 2 integer See PRZM manual Incorporation Depth: DEPI 0.1 cm Application Rate: TAPP 0.1 kg/ ha Application Efficiency: APPEFF 0.99 fraction Spray Drift DRFT 0.064 fraction of application rate applied to pond Application Date Date 1 Jul dd/ mm or dd/ mmm or dd mm or dd mmm Record 17: FILTRA IPSCND 1 UPTKF Record 18: PLVKRT PLDKRT FEXTRC 0.5 Flag for Index Res. Run IR IR Flag for runoff calc. RUNOFF total none or total( average of entire run)

OUTPUT FILE stored as dcpu. out Chemical: dcpu PRZM environment: FLcitrusC. txt EXAMS environment: IRPRZM0. EXV Metfile: met156a. met Water segment concentrations ( ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1948 4.341 4.156 3.788 3.152 2.737 1.159 1949 2.323 2.225 2.086 1.859 1.696 0.6452 1950 3.028 2.901 2.615 2.426 2.211 0.9436 1951 5.097 4.896 4.27 3.244 2.681 1.001 1952 8.496 8.137 6.848 5.031 4.181 1.757 1953 3.864 3.7 3.201 2.989 2.797 1.155 1954 4.917 4.712 4.398 3.283 2.952 1.103 1955 2.802 2.686 2.304 1.917 1.749 0.7618 28 1956 3.531 3.389 3.014 2.421 2.036 0.7488 1957 6.785 6.544 5.558 5.115 4.627 1.672 1958 2.314 2.252 2.039 1.744 1.701 0.6986 1959 3.428 3.287 2.879 2.786 2.672 1.045 1960 6.844 6.562 6.078 4.858 4.006 1.398 1961 1.691 1.618 1.351 1.158 1.041 0.4973 1962 2.978 2.85 2.554 2.112 1.837 0.7889 1963 4.169 3.99 3.535 2.664 2.148 0.8094 1964 6.601 6.319 5.301 4.094 3.653 1.385 1965 3.751 3.593 3.153 2.919 2.579 1.162 1966 2.325 2.228 1.919 1.609 1.443 0.6956 1967 4.002 3.888 3.369 3.025 2.826 1.184 1968 3.078 2.949 2.677 2.135 2.002 0.8574 1969 3.802 3.636 3.34 2.77 2.47 0.9989 1970 2.694 2.577 2.202 1.572 1.279 0.5299 1971 2.334 2.274 2.013 1.615 1.525 0.6873 1972 3.471 3.36 2.972 2.594 2.337 0.8386 1973 3.106 2.991 2.647 2.132 1.842 0.7682 1974 3.024 2.896 2.497 1.953 1.653 0.6105 1975 2.37 2.272 1.908 1.645 1.458 0.6315 1976 3.961 3.836 3.307 2.585 2.295 0.9525 1977 2.598 2.487 2.095 1.944 1.858 0.7839 1978 0.7702 0.7457 0.6815 0.6067 0.5158 0.2854 1979 3.38 3.235 2.787 2.357 2.264 1.022 1980 3.819 3.693 3.375 3.084 2.736 1.065 1981 5.908 5.677 4.929 4.421 3.736 1.277 1982 1.519 1.464 1.33 1.112 0.954 0.487 1983 4.822 4.683 4.045 3.074 2.555 0.895 Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.02702 7 8.496 8.137 6.848 5.115 4.627 1.757 0.05405 4 6.844 6.562 6.078 5.031 4.181 1.672 0.08108 1 6.785 6.544 5.558 4.858 4.006 1.398 0.10810 8 6.601 6.319 5.301 4.421 3.736 1.385 0.13513 5 5.908 5.677 4.929 4.094 3.653 1.277 0.16216 2 5.097 4.896 4.398 3.283 2.952 1.184 0.18918 9 4.917 4.712 4.27 3.244 2.826 1.162 0.21621 6 4.822 4.683 4.045 3.152 2.797 1.159 0.24324 3 4.341 4.156 3.788 3.084 2.737 1.155 0.27027 4.169 3.99 3.535 3.074 2.736 1.103 0.29729 4.002 3.888 3.375 3.025 2.681 1.065 29 7 0.32432 4 3.961 3.836 3.369 2.989 2.672 1.045 0.35135 1 3.864 3.7 3.34 2.919 2.579 1.022 0.37837 8 3.819 3.693 3.307 2.786 2.555 1.001 0.40540 5 3.802 3.636 3.201 2.77 2.47 0.9989 0.43243 2 3.751 3.593 3.153 2.664 2.337 0.9525 0.45945 9 3.531 3.389 3.014 2.594 2.295 0.9436 0.48648 6 3.471 3.36 2.972 2.585 2.264 0.895 0.51351 4 3.428 3.287 2.879 2.426 2.211 0.8574 0.54054 1 3.38 3.235 2.787 2.421 2.148 0.8386 0.56756 8 3.106 2.991 2.677 2.357 2.036 0.8094 0.59459 5 3.078 2.949 2.647 2.135 2.002 0.7889 0.62162 2 3.028 2.901 2.615 2.132 1.858 0.7839 0.64864 9 3.024 2.896 2.554 2.112 1.842 0.7682 0.67567 6 2.978 2.85 2.497 1.953 1.837 0.7618 0.70270 3 2.802 2.686 2.304 1.944 1.749 0.7488 0.72973 2.694 2.577 2.202 1.917 1.701 0.6986 0.75675 7 2.598 2.487 2.095 1.859 1.696 0.6956 0.78378 4 2.37 2.274 2.086 1.744 1.653 0.6873 0.81081 1 2.334 2.272 2.039 1.645 1.525 0.6452 0.83783 8 2.325 2.252 2.013 1.615 1.458 0.6315 0.86486 5 2.323 2.228 1.919 1.609 1.443 0.6105 0.89189 2 2.314 2.225 1.908 1.572 1.279 0.5299 0.91891 9 1.691 1.618 1.351 1.158 1.041 0.4973 0.94594 6 1.519 1.464 1.33 1.112 0.954 0.487 0.97297 3 0.7702 0.7457 0.6815 0.6067 0.5158 0.2854 30 0.1 6.6562 6.3865 5.3781 4.5521 3.817 1.3889 Average of yearly average s: 0.92500 8 Inputs generaged by pe3. pl of 6 March 2002 3,4 DCA Metfile: met156a. met PRZM scenario: FLcitrusC. txt EXAMS environment file: IRPRZM0. EXV Chemical Name: dca Description Variable Name Value Units Comments Molecular weight mwt 162.1 g/ mol Henry's Law Const. henry 2.2e 10 atm m^ 3/ mol Vapor Pressure vapr 2e 7 torr Solubility sol 420 mg/ L Kd Kd 16.6 mg/ L Koc Koc mg/ L Photolysis half life kdp 43 days Half life Aerobic Aquatic Metabolism kbacw 99 days Halfife Anaerobic Aquatic Metabolism kbacs 15 days Halfife Aerobic Soil Metabolism asm 90 days Halfife Hydrolysis: pH 7 0 days Half life Method: CAM 2 integer See PRZM manual Incorporation Depth: DEPI 0.1 cm Application Rate: TAPP 0.002 kg/ ha Application Efficiency: APPEFF 0.99 fraction Spray Drift DRFT 0.064 fraction of application rate applied to pond Application Date Date 1 Jul dd/ mm or dd/ mmm or dd mm or dd mmm Record 17: FILTRA IPSCND 1 UPTKF Record 18: PLVKRT PLDKRT FEXTRC 0.5 Flag for Index Res. Run IR IR Flag for runoff calc. RUNOFF total none or total( average of entire run) 31 OUTPUT FILE stored as dca. out Chemical: dca PRZM environment: FLcitrusC. txt EXAMS environment: IRPRZM0. EXV Metfile: met156a. met Water segment concentrations ( ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1948 0.05604 0.05366 0.04829 0.04227 0.03963 0.0168 1949 0.03089 0.02958 0.02592 0.02395 0.02129 0.00817 3 1950 0.05756 0.05515 0.04984 0.04374 0.03919 0.01502 1951 0.09672 0.0929 0.08095 0.06067 0.04932 0.017 1952 0.1644 0.1574 0.1324 0.09597 0.07833 0.02836 1953 0.06428 0.06155 0.05301 0.04696 0.04327 0.01666 1954 0.09236 0.08852 0.08241 0.06076 0.05219 0.01781 1955 0.04656 0.04464 0.03827 0.03056 0.02708 0.01081 1956 0.04566 0.04381 0.03866 0.03018 0.02559 0.00917 1 1957 0.1277 0.1231 0.1044 0.09292 0.08181 0.02749 1958 0.04567 0.04444 0.04004 0.0329 0.03033 0.0114 1959 0.057 0.05464 0.04989 0.0482 0.04557 0.01655 1960 0.08523 0.08155 0.07637 0.06018 0.04928 0.0182 1961 0.02439 0.02334 0.01953 0.01617 0.01399 0.00638 1 1962 0.0442 0.04229 0.03808 0.03048 0.02707 0.0104 1963 0.04797 0.04591 0.04079 0.03042 0.0245 0.00919 1 1964 0.09001 0.08616 0.07222 0.05433 0.04661 0.01731 1965 0.05059 0.04846 0.04221 0.03648 0.03361 0.01446 1966 0.03934 0.0377 0.03273 0.02745 0.0245 0.01027 1967 0.07425 0.07121 0.06034 0.05366 0.04746 0.0183 1968 0.05082 0.04869 0.04465 0.03509 0.03231 0.01294 1969 0.06664 0.06374 0.05879 0.0512 0.04456 0.01598 1970 0.03314 0.0317 0.02711 0.0193 0.01614 0.00688 2 1971 0.03197 0.03116 0.02745 0.02341 0.02274 0.00911 9 1972 0.06228 0.06027 0.05307 0.04418 0.03849 0.01308 1973 0.04528 0.04358 0.039 0.0319 0.02889 0.01146 1974 0.04502 0.0431 0.03754 0.02884 0.02441 0.00876 1975 0.04604 0.04412 0.03707 0.03059 0.02631 0.00974 32 1 1976 0.06054 0.05868 0.0504 0.03859 0.03733 0.01404 1977 0.04515 0.04326 0.03783 0.03344 0.03137 0.01177 1978 0.00829 9 0.00802 4 0.00722 1 0.00610 1 0.00561 1 0.00330 2 1979 0.05574 0.05335 0.04676 0.03877 0.03518 0.01331 1980 0.06207 0.06011 0.05451 0.05188 0.04513 0.01648 1981 0.08621 0.08298 0.07184 0.06153 0.05135 0.01771 1982 0.01739 0.01674 0.01527 0.01226 0.01118 0.00578 5 1983 0.08038 0.07804 0.06737 0.05031 0.04114 0.01369 Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.02702 7 0.1644 0.1574 0.1324 0.09597 0.08181 0.02836 0.05405 4 0.1277 0.1231 0.1044 0.09292 0.07833 0.02749 0.08108 1 0.09672 0.0929 0.08241 0.06153 0.05219 0.0183 0.10810 8 0.09236 0.08852 0.08095 0.06076 0.05135 0.0182 0.13513 5 0.09001 0.08616 0.07637 0.06067 0.04932 0.01781 0.16216 2 0.08621 0.08298 0.07222 0.06018 0.04928 0.01771 0.18918 9 0.08523 0.08155 0.07184 0.05433 0.04746 0.01731 0.21621 6 0.08038 0.07804 0.06737 0.05366 0.04661 0.017 0.24324 3 0.07425 0.07121 0.06034 0.05188 0.04557 0.0168 0.27027 0.06664 0.06374 0.05879 0.0512 0.04513 0.01666 0.29729 7 0.06428 0.06155 0.05451 0.05031 0.04456 0.01655 0.32432 4 0.06228 0.06027 0.05307 0.0482 0.04327 0.01648 0.35135 1 0.06207 0.06011 0.05301 0.04696 0.04114 0.01598 0.37837 8 0.06054 0.05868 0.0504 0.04418 0.03963 0.01502 0.40540 5 0.05756 0.05515 0.04989 0.04374 0.03919 0.01446 0.43243 2 0.057 0.05464 0.04984 0.04227 0.03849 0.01404 0.45945 9 0.05604 0.05366 0.04829 0.03877 0.03733 0.01369 0.48648 6 0.05574 0.05335 0.04676 0.03859 0.03518 0.01331 0.51351 4 0.05082 0.04869 0.04465 0.03648 0.03361 0.01308 33 0.54054 1 0.05059 0.04846 0.04221 0.03509 0.03231 0.01294 0.56756 8 0.04797 0.04591 0.04079 0.03344 0.03137 0.01177 0.59459 5 0.04656 0.04464 0.04004 0.0329 0.03033 0.01146 0.62162 2 0.04604 0.04444 0.039 0.0319 0.02889 0.0114 0.64864 9 0.04567 0.04412 0.03866 0.03059 0.02708 0.01081 0.67567 6 0.04566 0.04381 0.03827 0.03056 0.02707 0.0104 0.70270 3 0.04528 0.04358 0.03808 0.03048 0.02631 0.01027 0.72973 0.04515 0.04326 0.03783 0.03042 0.02559 0.00974 1 0.75675 7 0.04502 0.0431 0.03754 0.03018 0.0245 0.00919 1 0.78378 4 0.0442 0.04229 0.03707 0.02884 0.0245 0.00917 1 0.81081 1 0.03934 0.0377 0.03273 0.02745 0.02441 0.00911 9 0.83783 8 0.03314 0.0317 0.02745 0.02395 0.02274 0.00876 0.86486 5 0.03197 0.03116 0.02711 0.02341 0.02129 0.00817 3 0.89189 2 0.03089 0.02958 0.02592 0.0193 0.01614 0.00688 2 0.91891 9 0.02439 0.02334 0.01953 0.01617 0.01399 0.00638 1 0.94594 6 0.01739 0.01674 0.01527 0.01226 0.01118 0.00578 5 0.97297 3 0.00829 9 0.00802 4 0.00722 1 0.00610 1 0.00561 1 0.00330 2 0.1 0.09366 8 0.08983 4 0.08138 8 0.06099 1 0.05160 2 0.01823 Average of yearly average s: 0.01343 9 Inputs generaged by pe3. pl of 6 March 2002 mCPDMU Metfile: met156a. met 34 PRZM scenario: FLcitrusC. txt EXAMS environment file: IRPRZM0. EXV Chemical Name: mcpdmu Description Variable Name Value Units Comments Molecular weight mwt 198.1 g/ mol Henry's Law Const. henry 2.2e 10 atm m^ 3/ mol Vapor Pressure vapr 2e 7 torr Solubility sol 420 mg/ L Kd Kd 16.6 mg/ L Koc Koc mg/ L Photolysis half life kdp 43 days Half life Aerobic Aquatic Metabolism kbacw 345 days Halfife Anaerobic Aquatic Metabolism kbacs 576 days Halfife Aerobic Soil Metabolism asm 1116 days Halfife Hydrolysis: pH 7 0 days Half life Method: CAM 2 integer See PRZM manual Incorporation Depth: DEPI 0.1 cm Application Rate: TAPP 2.28 kg/ ha Application Efficiency: APPEFF 0.99 fraction Spray Drift DRFT 0.064 fraction of application rate applied to pond Application Date Date 1 Jul dd/ mm or dd/ mmm or dd mm or dd mmm Record 17: FILTRA IPSCND 1 UPTKF Record 18: PLVKRT PLDKRT FEXTRC 0.5 Flag for Index Res. Run IR IR Flag for runoff calc. RUNOFF total none or total( average of entire run)

OUTPUT FILE stored as mcpdmu. out Chemical: mcpdmu PRZM environment: FLcitrusC. txt EXAMS environment: IRPRZM0. EXV Metfile: met156a. met Water segment concentrations 35 ( ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1948 111 108 102 86.4 78.22 33.14 1949 60.91 59.06 56.51 50.06 46.86 21.22 1950 76.32 74.87 66.68 65.08 61.07 29.53 1951 119 115 105 86.71 75.3 32.04 1952 195 190 168 135 118 54.72 1953 95.67 92.78 85.24 83.11 78.36 38.7 1954 118 114 109 88.57 82.88 35.84 1955 68.74 66.69 59.68 53.15 50.29 25.27 1956 83.6 81.27 75.69 65.67 57.19 23.27 1957 162 158 141 138 127 51.74 1958 59.05 57.28 52.13 48.45 48.39 24.67 1959 92.53 89.79 81.68 76.23 72.83 32.84 1960 171 166 153 132 113 42.44 1961 42.05 40.9 36.87 32.36 30.24 18.88 1962 74.52 72.24 65.92 58.63 51.84 24.17 1963 99.64 96.57 87.58 71.68 60.47 24.47 1964 154 150 132 111 102 41.51 1965 96.46 93.56 84.25 80.25 73.51 36.7 1966 59.13 57.35 51.49 44.58 41.52 23.24 1967 102 100 90.1 81.31 78.51 36.13 1968 78.5 76.13 70.05 60.24 58.09 28.19 1969 98.14 95.15 89.14 73.68 69.28 32.32 1970 65.69 63.67 56.86 44.59 37.25 18.31 1971 61.32 60.14 55.32 45.3 42.69 21.55 1972 82.3 79.84 73.47 68.58 64.48 26.28 1973 79.14 77.09 70.54 59.86 52.46 24.44 1974 73.61 71.37 63.83 53.37 46.59 19.75 1975 55.5 53.83 47.46 43.92 40.71 20.22 1976 98.21 95.81 86.64 72.98 64.27 29.55 1977 70.17 68.07 60.24 53.74 52.06 25.53 1978 21.38 20.81 18.84 17.6 15.52 10.4 1979 85.11 82.5 72.57 64.65 63.74 30.6 1980 99.32 96.8 91.78 82.6 76.45 33.65 1981 140 136 124 118 105 39.45 1982 39.57 38.59 35.96 31.95 28.43 17.34 1983 112 110 99.33 82.58 72.24 28.12 Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.02702 7 195 190 168 138 127 54.72 0.05405 4 171 166 153 135 118 51.74 0.08108 1 162 158 141 132 113 42.44 0.10810 8 154 150 132 118 105 41.51 36 0.13513 5 140 136 124 111 102 39.45 0.16216 2 119 115 109 88.57 82.88 38.7 0.18918 9 118 114 105 86.71 78.51 36.7 0.21621 6 112 110 102 86.4 78.36 36.13 0.24324 3 111 108 99.33 83.11 78.22 35.84 0.27027 102 100 91.78 82.6 76.45 33.65 0.29729 7 99.64 96.8 90.1 82.58 75.3 33.14 0.32432 4 99.32 96.57 89.14 81.31 73.51 32.84 0.35135 1 98.21 95.81 87.58 80.25 72.83 32.32 0.37837 8 98.14 95.15 86.64 76.23 72.24 32.04 0.40540 5 96.46 93.56 85.24 73.68 69.28 30.6 0.43243 2 95.67 92.78 84.25 72.98 64.48 29.55 0.45945 9 92.53 89.79 81.68 71.68 64.27 29.53 0.48648 6 85.11 82.5 75.69 68.58 63.74 28.19 0.51351 4 83.6 81.27 73.47 65.67 61.07 28.12 0.54054 1 82.3 79.84 72.57 65.08 60.47 26.28 0.56756 8 79.14 77.09 70.54 64.65 58.09 25.53 0.59459 5 78.5 76.13 70.05 60.24 57.19 25.27 0.62162 2 76.32 74.87 66.68 59.86 52.46 24.67 0.64864 9 74.52 72.24 65.92 58.63 52.06 24.47 0.67567 6 73.61 71.37 63.83 53.74 51.84 24.44 0.70270 3 70.17 68.07 60.24 53.37 50.29 24.17 0.72973 68.74 66.69 59.68 53.15 48.39 23.27 0.75675 7 65.69 63.67 56.86 50.06 46.86 23.24 0.78378 4 61.32 60.14 56.51 48.45 46.59 21.55 0.81081 1 60.91 59.06 55.32 45.3 42.69 21.22 0.83783 59.13 57.35 52.13 44.59 41.52 20.22 37 8 0.86486 5 59.05 57.28 51.49 44.58 40.71 19.75 0.89189 2 55.5 53.83 47.46 43.92 37.25 18.88 0.91891 9 42.05 40.9 36.87 32.36 30.24 18.31 0.94594 6 39.57 38.59 35.96 31.95 28.43 17.34 0.97297 3 21.38 20.81 18.84 17.6 15.52 10.4 0.1 156.4 152.4 134.7 122.2 107.4 41.789 Average of yearly average s: 29.3394 4 Inputs generaged by pe3. pl of 6 March 2002 APPENDIX II SCI GROW OUTPUT FILES FOE MODELING DIURON AND ITS DEGRADATES RUN No. 1 FOR diuron INPUT VALUES   APPL (#/ AC) APPL. URATE SOIL SOIL AEROBIC RATE NO. (#/ AC/ YR) KOC METABOLISM ( DAYS)

  38 9.600 1 9.600 468.0 372.0 GROUND WATER SCREENING CONCENTRATIONS IN PPB  6.521987  A= 367.000 B= 473.000 C= 2.565 D= 2.675 RILP= 3.399 F= . 168 G= .679 URATE= 9.600 GWSC= 6.521987 RUN No. 1 FOR DCPMU INPUT VALUES   APPL (#/ AC) APPL. URATE SOIL SOIL AEROBIC RATE NO. (#/ AC/ YR) KOC METABOLISM ( DAYS)

  2.030 1 2.030 468.0 770.0 GROUND WATER SCREENING CONCENTRATIONS IN PPB  2.497237  A= 765.000 B= 473.000 C= 2.884 D= 2.675 RILP= 3.821 F= .090 G= 1.230 URATE= 2.030 GWSC= 2.497237 RUN No. 2 FOR DCPU INPUT VALUES   39 APPL (#/ AC) APPL. URATE SOIL SOIL AEROBIC RATE NO. (#/ AC/ YR) KOC METABOLISM ( DAYS)

  .080 1 .080 468.0 770.0 GROUND WATER SCREENING CONCENTRATIONS IN PPB  .098413  A= 765.000 B= 473.000 C= 2.884 D= 2.675 RILP= 3.821 F= .090 G= 1.230 URATE= .080 GWSC= .098413 RUN No. 3 FOR 3,4 DCA INPUT VALUES   APPL (#/ AC) APPL. URATE SOIL SOIL AEROBIC RATE NO. (#/ AC/ YR) KOC METABOLISM ( DAYS)

  .002 1 .002 468.0 30.0 GROUND WATER SCREENING CONCENTRATIONS IN PPB  .000155  A= 25.000 B= 473.000 C= 1.398 D= 2.675 RILP= 1.852 F=  1.111 G= .077 URATE= .002 GWSC= .000155 RUN No. 4 FOR mCPDMU INPUT VALUES 40   APPL (#/ AC) APPL. URATE SOIL SOIL AEROBIC RATE NO. (#/ AC/ YR) KOC METABOLISM ( DAYS)

  2.04 1 2.04 468.0 372 GROUND WATER SCREENING CONCENTRATIONS IN PPB  1.3827  A= 110.000 B= 473.000 C= 2.041 D= 2.675 RILP= 2.705 F= . 591 G= .257 URATE= 1.120 GWSC= .287307