UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

WASHINGTON D.C., 20460 

OFFICE OF 

CHEMICAL SAFETY AND 

POLLUTION PREVENTION 

MEMORANDUM 

DATE: 

SUBJECT: 

FROM: 

THRU: 

TO: 

May 14,2013 

Addendum to the Problem Formulation for the Ecological Risk Assessment to be 

Conducted for the Registration Review of Atrazine. 

Amy Blankinship, Chemist n. J~t." f .Jj¥j/3 1 Frank T. Farruggia, Ph.D., Bi~ (.__;:/_ \._/ ~~ James Hetrick, Ph.D., Senior Advisor_J/MM41 Ct. f/e{!;; ~ Slt-r/3 r ¥ 3 

Environmental Risk Branch 3 . 

Environmental Fate and Effects Division (7507P) / j ~ s J'j ~)3 

Dana Spatz, Chi~~........::::, Rosanna Louie-JuZWI , L ~ ' 9Jv S/ J 

Environmental Risk Branch 3 V ~ J ~ 'l.Ot.3 

Environmental Fate and Effects Division (7507P) 

Monica Wait, Chemical Review Manager 

Patricia Parrott, Chief 

Risk Management and Implementation Branch 3 

Pesticide Re-Evaluation Division (7508P) 

This addendum and the attached problem formulation for atrazine, titled "Problem Formulation 

for the Reassessment of Ecological Risks from the Use of Atrazine," prepared for the June 12-15 

2012 FIFRA Scientific Advisory Panel (SAP or the Panel) meeting, together serve as the 

problem formulation for the ecological risk assessment to be conducted for the registration 

review of atrazine. The appendices to the June 2012 problem formulation document are not 

attached here but can be found in the SAP public docket at regulations.gov (EPA-HQ-OPP-2012-

0230). 

Functioning as the first stage of the risk assessment process for registration review, this problem 

formulation provides an overview of what is currently known about the environmental fate and 

ecological effects associated with atrazine and its degradates. It also describes the preliminary 

ecological risk hypothesis and analysis plan for evaluating and characterizing exposure and risk 

to non-target listed and non-listed species in support of the registration review of atrazine. 

Additionally, it describes the plan for evaluating and characterizing exposure from drinking 

' 

1 
2

water for the human health assessment. The database for environmental fate and transport, and 

ecological effects data for atrazine is sufficient for risk assessment such that no additional data 

are needed at this time. 

The purpose of this addendum is to address comments received from the SAP during the June 

12-15, 2012 meeting, and to provide an update on the ecological monitoring program being 

conducted by the registrant as a result of the 2003 atrazine Interim Reregistration Eligibility 

Decision. 

The 2012 SAP meeting on atrazine focused on three major topic areas: 

1. the evaluation of the atrazine amphibian toxicity data, 

2. the method for determining the level of concern for aquatic plant communities, and 

3. the development and implementation of methods for a quantitative interpretation of 

atrazine occurrence data in surface water. 

At this meeting, EPA scientists presented the state of knowledge concerning the ecological 

effects and exposure information for atrazine, and the proposed plan for analyzing the data and 

characterizing risks to non-target organisms, including plant community effects. The materials 

presented by the EPA and stakeholders, as well as meeting minutes and the SAP response to the 

charge questions, can be found in the public docket 

(http://www.regulations.gov/#!docketDetail;rpp=25;po=0;D=EPA-HQ-OPP-2012-0230) and the 

FIFRA SAP webpage (http://www.epa.gov/scipoly/sap/meetings/2012/061212meeting.html). 

While most of the SAP’s comments are addressed in the following pages, some of the 

recommendations will require additional time and investigation, and will be addressed prior to 

the completion of the registration review ecological risk assessment. 

 
3

Table of Contents 

Evaluation of the Atrazine Amphibian Toxicity Data .................................................................................... 5

Stakeholder Input Request ....................................................................................................................... 8

Weight of Evidence (meta‐analysis) Approach......................................................................................... 8

Stakeholder Input Requests.................................................................................................................... 11

Use of the Amphibian Toxicity Data Call‐In Study (DCI) to Evaluate Effects to Amphibians and

Recommended Additional Testing...................................................................................................... 11

Stakeholder Input Requests.................................................................................................................... 13

Other Atrazine Toxicity Topics Discussed at the June 2012 SAP ........................................................ 13

The Methodology for Determining the Levels of Concern for Atrazine ..................................................... 15

Criteria Used for Scoring the Mesocosm and Microcosm Studies.......................................................... 15

Concerns Regarding the Calculation of the CE‐LOC................................................................................ 16

Separate Lotic and Lentic Derived Studies and Use Only Lotic Test Systems (e.g., Artificial Streams,

Flow‐through Systems) for Evaluating Responses in Lotic Systems and Vice Versa. .........................16

Realistic Exposure Conditions and Cosm Study Duration to Best Represent Atrazine Exposure

Conditions in the Field. ....................................................................................................................... 17

Investigate Bias in Choice of Plant Species in Laboratory and Cosm Studies. ....................................18

Additional Cosm Study Reviews.............................................................................................................. 19

Panel Recommendations Regarding the Calculation of the CE‐LOC....................................................... 20

Evaluate the Uncertainties Inherent in the Available Cosm Dataset and Estimate the Robustness of

the Data to Estimate the CE‐LOC. ....................................................................................................... 20

Evaluate and Quantify the Cumulative Error in the CE‐LOC Estimation............................................. 20

Consideration for Additional Cosm Testing ............................................................................................ 20

The Panel’s recommendations for future cosm experiments included the following design elements:

............................................................................................................................................................20

Method for Determining Vulnerable Watersheds...................................................................................... 23

Development and Implementation of Methods for Quantitative Interpretation of Atrazine Occurrence

Data in Surface Water............................................................................................................................. 23

Proposed Approach for Estimating Atrazine Aquatic Exposure Concentrations in Surface Water........24

Atrazine Ecological Exposure Monitoring Program (AEEMP) ................................................................. 26

Background .........................................................................................................................................26

The Current Aquatic Ecosystem Level of Concern (CE‐LOC)............................................................... 28

Monitoring Results in Areas of Corn, Sorghum, and Sugarcane Production ......................................28
4

Considerations for Atrazine Risk Assessment..................................................................................... 33

Bias Factors.............................................................................................................................................33

Background .........................................................................................................................................33

Considerations for Atrazine Risk Assessment..................................................................................... 33

Strategy for Bias Factor Development and Implementation.................................................................. 36

Quantitative Modeling of Monitoring Data Section ............................................................................... 36

Background .........................................................................................................................................36

Considerations for Atrazine Risk Assessment..................................................................................... 37

Further Considerations for Registration Review..................................................................................... 38

Drinking Water Assessment.................................................................................................................... 38

Endocrine Disruptor Screening Program (EDSP)..................................................................................... 38

Endangered Species Assessments .......................................................................................................... 39

Preliminary Identification of Data Gaps.................................................................................................. 39

References ..............................................................................................................................................39

APPENDIX S‐1:.............................................................................................................................................45
5

Evaluation of the Atrazine Amphibian Toxicity Data

In the 2012 atrazine problem formulation, an evaluation of the large number of available 

amphibian studies from both the registrant and open literature (as of August 2011) was 

completed. Discussed was the process for evaluating the studies along with determinations 

(classification) of how each study may be utilized in a risk assessment (i.e., invalid (not to be 

used); qualitatively or quantitatively). The studies were grouped into general endpoint categories: 

survival, growth (mass and length), metamorphosis and development, immune response and 

infection, behavior modifications (e.g., feeding, locomotion, mating), biochemical or molecular 

alterations, and sexual development. Within a general category, the range of reported NOAECs 

and LOAECs was described along with each study classification. 

In addition to registrant-submitted studies, EPA scientists review pesticide studies from peerreviewed scientific journals and data from a wide variety of sources when they are available. In 

so doing, agency scientists identify hazards and characterize risks using the best data available 

for their review. For more information, see the Guidance for Identifying, Selecting and 

Evaluating Open Literature Studies at http://www.epa.gov/pesticides/science/literaturestudies.html. Prior to the 2012 SAP, most of the amphibian studies were previously reviewed by 

EPA and reported either in ecological risk assessments written for registration decisions, 

endangered species assessments for atrazine and/or in support of consultations with the FIFRA 

SAP. The 2012 SAP listed two amphibian studies not previously included in EPA’s review, 

(Paetow et al. 2012 & Bishop et al. 2010) that should also be given further consideration in 

evaluating potential risk to amphibians. The Panel also listed nine additional studies for other 

taxa that will be considered for the risk assessment (Table 1). 

Table 1. Additional Amphibian Studies Identified by the 2012 SAP 

No. Reference 

1 Baxter L.R., D.L. Moore, P.K. Sibley, K.R. Solomon, M.L. Hanson. 2011. Atrazine does not 

affect algal biomass or snail populations in microcosm communities at environmentally relevant 

concentrations. Environ Toxicol Chem 30: 1689-1696 

2 Belloni V., F. Dessi-Fulgheri, M. Zaccaroni, C.E. Di, A.G. De, E. Testai, et al. 2011. Early 

exposure to low doses of atrazine affects behavior in juvenile and adult CD1 mice. Toxicology 

279: 19-26 

3 Bishop C.A., S.L. Ashpole, A.M. Edwards, A.G. van, and J.E. Elliott. 2010. Hatching success 

and pesticide exposures in amphibians living in agricultural habitats of the South Okanagan 

Valley, British Columbia, Canada (2004-2006). Environ Toxicol Chem 29: 1593-1603 

4 Corvi M.M., K.A. Stanley, T.S. Peterson, M.L. Kent, S.W. Feist, J.K. La Du, et al. 2012. 

Investigating the impact of chronic atrazine exposure on sexual development in zebrafish. Birth 

Defects Res B Dev Reprod Toxicol. 

5 Cragin L.A., J.S. Kesner, A.M. Bachand, D.B. Barr, J.W. Meadows, E.F. Krieg, et al. 2011. 

Menstrual cycle characteristics and reproductive hormone levels in women exposed to atrazine in 

drinking water. Environ Res 111: 1293-1301 

6 Nascimento C.R., M.M. Souza, and C.B. Martinez. 2012. Copper and the herbicide atrazine 

impair the stress response of the freshwater fish Prochilodus lineatus. Comp Biochem Physiol C 
6

Toxicol Pharmacol 155: 456-461 

7 Paetow L.J., J.D. McLaughlin, R.I. Cue, B.D. Pauli, and D. J. Marcogliese. 2012. Effects of 

herbicides and the chytrid fungus Batrachochytrium dendrobatidis on the health of postmetamorphic northern leopard frogs (Lithobates pipiens). Ecotoxicol Environ Saf 80: 372-380 

8 Paulino M.G., M.M. Sakuragui, and M.N. Fernandes. 2012a. Effects of atrazine on the gill cells 

and ionic balance in a neotropical fish, Prochilodus lineatus. Chemosphere 86: 1-7. 

9 Paulino M.G., N.E. Souza, and M.N. Fernandes. 2012b. Subchronic exposure to atrazine induces 

biochemical and histopathological changes in the gills of a Neotropical freshwater fish, 

Prochilodus lineatus. Ecotoxicol Environ Saf 80: 6-13 

10 Shenoy K. 2012. Environmentally realistic exposure to the herbicide atrazine alters some 

sexually selected traits in male guppies. PLoS One 7: e30611 

11 Tillitt D.E., D.M. Papoulias, J.J. Whyte, and C.A. Richter . 2010. Atrazine reduces reproduction 

in fathead minnow (Pimephales promelas). Aquat. Toxicol. 99: 149-159 

The 2012 problem formulation identified test design elements that would contribute to some 

level of uncertainty in the ability to discern an exclusive causal relationship with atrazine. 

Studies were evaluated as a whole, and the overall level of confidence in the study results to 

identify the potential for atrazine-only effects was based on the number and type of uncertainties 

identified. 

According to the 2012 SAP Panel’s response to the charge question regarding the completeness 

of EPA’s identified test design elements, “in general, the Panel supported the use of the EPA’s 

test design elements (Section 7.2.b of the White Paper) for use in designing new studies ...to 

establish ‘cause and effect’ relationships...”. They further state that “many of these elements are 

what statisticians consider as properties of good experimental design prior to the initiation of a 

study”. However, the Panel did not wholly endorse EPA’s application of the test design elements 

to the existing compendium of available studies. 

The Panel further elaborated on the identified test design elements in terms of their influence on 

interpreting a causal relationship. The Panel did indicate that they agreed with the majority of the 

studies that the EPA labeled as ‘invalid’ (p. 35 of the Panel’s Response SAP report). Also, 

according to the Panel’s response “the EPA’s strict application of the test design elements to the 

published literature was flawed and many of the test design elements should be relaxed with the 

review of the published literature.” 

The test design elements outlined in the problem formulation are representative of OPP’s current 

guidance on evaluating open literature studies, as well as reflective of current ASTM and EPA 

OCSPP 850 guidelines for aquatic toxicology testing. Therefore, in moving forward, the test 

design elements outlined in the problem formulation are still anticipated to be applied to the 

previously published open literature data (this includes amphibian and non-amphibian data). 

While for each of the studies the departures from the specific test elements will be identified, the 

approach to evaluate potential effects to amphibians is anticipated to involve analyzing the data 

using a weight of evidence approach. The Panel provided feedback on the identified test design 

elements and this feedback will be considered when developing the list of test design elements 

(criteria) for this weight of evidence exercise. This is an alternative to the standard screening 
7

method of calculating a risk quotient (RQ) using the estimated exposure concentration and the 

most sensitive toxicity value from the studies that are considered acceptable for quantitative use 

and comparing the calculated value to the level of concern (LOC). However, even in using a 

weight of evidence approach, the potential uncertainties in each study will still be captured and 

considered in the overall evaluation. The objective of this approach is to be more inclusive of the 

available data, while still being cognizant of the potential issues within the dataset. 

In the evaluation of the available open literature amphibian toxicity data, one uncertainty that 

was discussed in the problem formulation was biological loading; a known key factor in the 

resulting water quality in a study. In the available open literature studies, loading was not 

commonly reported as mass per water volume, but rather as the number of tadpoles per volume 

of water, or sometimes as the number of tadpoles in a certain volume container without 

specifying the water volume. The recommended loading rate used in the evaluation of the 

amphibian data in the 2012 problem formulation was 1 tadpole/L or approximately 1 g/L. This 

loading was discussed at the 2003 SAP in which weight data on Xenopus laevis was used to 

support this recommended loading rate, as well as rates in ASTM guidelines. In the 2012 Panel’s 

response, they indicated that the best measure of adequate water quality and development is 

observing animals that are healthy and reach normal developmental size. For X. laevis, the 

expected developmental size and stage is well known under certain environmental conditions (as 

in the DCI study); however, the expected development for other species under certain conditions 

was not as easily determined. At the 2012 SAP meeting, weight data from the available open 

literature studies for different amphibian species were presented to better understand their 

potential weight ranges in comparison to X. laevis. In the following table, the reported weights 

generally reflect wet weight at completion of metamorphosis (Table 2). These values may be 

approximate as data were taken, in some cases, from summary graphs. Many species are 

approaching or exceeding 1 g; therefore, it may be assumed that the organisms reached 1 g at 

some point while undergoing metamorphosis in the study. Therefore, in the evaluation, it is 

assumed that the use of 1 tadpole/L was an appropriate measure by which to evaluate loading. 

Table 2. Wet weights of Different Amphibian Species at Completion of Metamorphosis 

Species Weight (g)/ organism Source 

Rana pipiens 2.5 2003 SAP (Hayes et al. 2002c) 

R. pipiens 0.83 Allran and Karasov 2000 

R. pipiens 2.2 Hayes et al. 2006 

R. clamitans 2 2003 SAP (Hecker et al. 2003) 

Litoria raniformis 0.9 Choung et al. 2011 

Hyla versicolor 0.5 LaFiandra et al. 2008 

Ambystoma barbouri 0.75 to 0.95 Rohr et al. 2011 

A. macrodactylum 0.85 Forson and Storfer 2006 

A. tigrinum 11-16 Larson et al. 1998 
8

Stakeholder Input Request 

The EPA is looking for information regarding what may constitute ‘normal development’ for 

different amphibian species under different environmental conditions. This information can be 

used to evaluate if environmental conditions described in the open literature studies were 

appropriate for proper development of different species. 

In terms of the one study that EPA classified as quantitative, published as Kloas et al. 2009 

(actually two studies conducted in parallel using the same protocol), the Panel stated that this 

study may be useful to answer whether atrazine affects gonadal development in a particular 

strain of Xenopus laevis, but is insufficient to make a global conclusion about atrazine effects on 

all amphibian species at concentrations below 100 μg/L. 

With regard to the amphibian portion of the problem formulation, the Panel made two overall 

recommendations. The Panel recommended a weight of evidence approach (e.g., a metaanalysis) and that “all studies should be considered explicitly in the risk assessment”. Secondly, 

the Panel recommended additional testing to include at least three North American (native) 

species of amphibians from three populations across the U.S. or the species’ range. This 

additional testing recommendation encompassed both laboratory and cosm studies. The EPA’s 

response to both of these recommendations is discussed below. 

Weight of Evidence (meta-analysis) Approach 

The Panel recommended that a weight of evidence approach (meta-analysis) be undertaken when 

evaluating the amphibian data, and that all data be considered explicitly in the risk assessment. 

However, few details on an appropriate weight of evidence approach were given. A reference for 

a meta-analysis evaluating a chemical’s potential for causing cancer was provided (Scott et al.

2011). The Panel also referenced the weight of evidence approach presented by the registrant at 

the meeting, but stated that it appeared to be flawed. Weight of evidence is a broad term that can 

refer to a process for characterizing the extent to which the available data support a hypothesis 

that an agent causes a particular effect (USEPA 2011).1 A weight of evidence analysis can be 

conducted qualitatively, quantitatively or a combination of the two. Weight of evidence reviews 

for atrazine toxicity have been previously published and a summary is presented in the problem 

formulation. Most of these papers analyze the data qualitatively (e.g., Rohr and McCoy 2010; 

Hayes et al. 2011). At the 2012 SAP meeting, an approach using a quantitative method (i.e., 

Solomon et al. 2012) was presented. Additionally, while not a strict weight of evidence method; 

Breton et al. (2009) presented a quantitative method for evaluating ecotoxicity studies for 

substances undergoing regulatory review in Canada. 

Previous weight of evidence reviews have explicitly incorporated the Hill criteria (Hill 1965) 

into their analyses to evaluate causality (Hayes et al. 2011; Solomon et al. 2008; Solomon et al. 

2012). There are nine criteria listed in the paper to establish causality: strength, consistency, 

                                                           

1

 http://www.regulations.gov/#!documentDetail;D=EPA-HQ-OPPT-2010-0877-0021 
9

specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy. 

Each of these criteria is further expanded upon in the Hill paper. These criteria should be 

incorporated in the weight of evidence approach used to evaluate the amphibian toxicity data. 

As mentioned previously, a weight of evidence may be done qualitatively or quantitatively. In 

evaluating the amphibian toxicity data for the risk assessment, the preferred path forward is to 

have an approach that is as robust and scientifically sound as possible, while being inclusive of 

all the available toxicity data. In a review by Balls et al. (2006), according to Horvath and 

Pewsner, a systematic review (weight of evidence) can be divided into six phases: 1) preparation 

of the systematic review, 2) systematic research of the primary literature, 3) selection of studies, 

4) assessment of quality, 5) analysis and synthesis of data, and 6) interpretation of data. 

Systematic reviews may include a statistical combination of studies (referred to as a metaanalysis), but it is not necessary1

. 

The meta-analysis approach is considered to be a more defined weight of evidence approach. 

The Cochrane Collaboration identifies meta-analysis as a two stage process with the first stage 

extracting data from individual studies and calculating its results and the second stage examining 

the appropriateness of calculating a pooled average result across the studies (which includes the 

process of weighting results) and reporting such results.2 The results are often presented in a 

forest plot. In a meta-analysis, the data can be analyzed using either a fixed effects or random 

effects model. The fixed model assumes the treatment effect is the same across studies, whereas 

the random effects model does not. There are assumptions and pros and cons to either model 

(Walker et al. 2008). 

As meta-analyses are quantitative, in many of these analyses, it is meant to increase the sample 

size and thus the power to study the effect of interest (Walker et al. 2008). The selection of 

studies to be included in the analysis is crucial and systematic steps such as eligibility or 

inclusion criteria are part of both systematic reviews and meta-analyses. In Walker et al. 2008, 

the reason for this process is to select studies that are as similar as possible to the identified 

criteria (e.g., study design, sample size, population studied), and when the dissimilarities 

between studies increases, it can decrease the appropriateness in pooling results to obtain an 

integrated conclusion. 

In the 2012 problem formulation evaluation of the amphibian studies, the data were grouped into 

identified categories as previously mentioned. However, within those broad categories, there 

were some variations in how the data were collected and presented. For example, there were 

different types of observed endpoints that were considered to be reflective of metamorphosis. 

While the majority of the endpoints represented time to metamorphosis or a comparison of 

metamorphic stage after a fixed exposure duration, a few studies represented metamorphic organ 

malformations. These types of endpoint variations were observed for all the identified categories. 

Given that similarity between studies is an important element when conducting a meta-analysis 

as it was described above, we conclude that the atrazine amphibian data should not be evaluated 

using a strict meta-analysis process in which studies are combined to obtain a cohesive result. 

                                                           

2 http://130.226.106.152/openlearning/html/mod3-2.htm (accessed February 13, 2013) 
10

However, the data may still be evaluated using a systematic review approach, which may involve 

quantitative steps. The weight of evidence approach chosen is anticipated to be an integrative 

and interpretive process. 

Considering the range of test designs and varying degrees of information provided in the 

amphibian studies, it is considered that the studies should not be weighed equally. In systematic 

reviews, weighting data may be done using sample size or based on the ‘quality’ of the studies 

using a pre-determined set of criteria. Assessment of the potential utility of the available studies 

in a risk assessment (data quality) was conducted in the 2012 problem formulation using a predetermined set of test design elements. Additionally, in the presentation by the registrant, 

quantitative weights were applied to the data. It is recognized that using a pre-determined set of 

criteria as defined by reviewer(s) can be subjective. 

In moving forward with a weight of evidence approach for atrazine amphibian data, we believe 

that applying weights to the data is important in the overall analysis process given the known 

uncertainties in the body of amphibian literature. This weighting process will be conducted using 

criteria from the test design elements that were referenced in the 2012 problem formulation, as 

well as from other sources such as the Hill criteria and the test design criteria described in the 

paper by Brenton et al. 2009. These elements are based on internationally recognized guidelines 

and procedures and should allow for a more consistent evaluation of the data. All of the available 

data will be subjected to this weighing exercise and included in the next steps in the weight of 

evidence approach. 

The potential for bias in a weight of evidence evaluation is a concern that is echoed in many 

review papers on the topic (e.g., Balls et al 2006; Walker et al. 2008; Spector and Thompson 

1991). In moving forward with a weight of evidence approach for atrazine, careful consideration 

of the potential for bias needs to be incorporated when developing a scientifically sound 

approach. In Walker et al. 2008, approaches to detecting bias are presented. The use of funnel 

plots may allow for the detection of possible bias in the identification and selection of studies (if 

the graph does not demonstrate a symmetrical funnel shape, then it suggests a possible bias). In 

addition, examining the heterogeneity in the studies (the degree of dissimilarity in the results 

between studies) can also be accomplished using a graph of the results. These techniques may be 

useful when evaluating the atrazine amphibian data. 

Given the nature of the data, we believe that it is not appropriate to analyze the data by pooling 

the results or by subjecting it to statistical analyses as described in the meta-analysis approach. 

However, the data do need to be integrated or displayed for interpretation. In the 2012 problem 

formulation and at the 2012 SAP meeting, the data were displayed in such way as to convey both 

the relative response as well as the confidence in the data for each study. Additionally, the 

presentation by the registrant at the meeting also graphically presented the data indicating the 

relative strength in an adverse outcome along with the strength of the methodology. It is 

anticipated that a method similar to the ones described will be used to report the results of the 

analysis. 
11

Atrazine was one of the chemicals in the first list of chemicals to undergo initial Tier I screening 

under the Endocrine Disruptor Screening Program.3

 The proposed weight of evidence approach 

for evaluation of a chemical incorporates the Hill criteria. Through this program, a weight of 

evidence analysis will be conducted for atrazine to evaluate ecological toxicity in a manner that 

takes into account all relevant scientific and technical information.4

Furthermore, while somewhat different than the weight of evidence approaches discussed above, 

there is another approach that may give insight into the potential for adverse effect from atrazine 

exposure. Adverse outcome pathways (AOPs) make inferences about molecular initiating events 

that ultimately lead to an adverse outcome, i.e., capable of affecting the survival, growth and 

reproduction. Development of AOPs is being conducted through the EDSP, which was built 

upon recommendations from a 2007 National Academy of Sciences report, Toxicity Testing in 

the 21st Century: A Vision and a Strategy.5 Through these efforts, it may be possible to establish 

robust and consistent information on a mode of action that then translates downstream to higher 

levels of biological organization to eventual adverse outcomes. 

In summary, it is proposed that evaluation of the atrazine amphibian data undergo a weight of 

evidence approach. However, given the nature of the reported data and endpoint variability, it is 

not recommended that the data be evaluated using a meta-analysis as it is described above. 

Rather, EPA proposes that the data be evaluated using a systematic review approach which 

includes: 1) identifying the question or hypothesis to test, 2) assembling the data, 3) assessment 

of data quality, 4) analysis of the data, and 5) interpretation of the data. It is envisioned that all 

available data will be collected and assessed for quality. Given that a rigorous statistical analysis 

of the data or pooling the data to achieve a unified response is not appropriate, one possible 

approach to data analysis is by plotting the data responses along with presenting a given weight 

or quality of each study. 

Stakeholder Input Requests 

While the EPA has presented a proposed path forward for evaluating the amphibian toxicity data, 

it is requesting feedback from stakeholders on this approach, as well as alternative scientifically 

sound approaches for evaluating the large set of toxicity data available for amphibians. 

Use of the Amphibian Toxicity Data Call-In Study (DCI) to Evaluate Effects to 

Amphibians and Recommended Additional Testing 

In the 2012 problem formulation, the EPA identified that the atrazine amphibian toxicity study 

that was submitted in response to the 2003 SAP on atrazine amphibian toxicity and resulted in a 

data call-in in 2004 was reliable for quantitative use to evaluate risk to amphibians (MRID 

                                                           

3 http://www.epa.gov/endo/pubs/prioritysetting/final_listfacts.htm (accessed February 13, 2013) 4 http://www.regulations.gov/#!documentDetail;D=EPA-HQ-OPPT-2010-0877-0021 (accessed February 13, 2013) 5 National Academy of Sciences. 2007 Toxicity Testing in the 21st Century: A Vision and a Strategy. Committee on Toxicity

Testing and Assessment of Environmental Agents, National Research Council ISBN: 0‐309‐10993‐0, 216 pages.
12

47046201-04 & 47153501, Hosmer et al. 2007 (registrant-submitted) and published as Kloas et 

al. 2009). While the Panel agreed that the study was useful in answering questions about atrazine 

toxicity on gonadal development in Xenopus laevis, they believed it was inadequate to make a 

global conclusion about atrazine effects on all amphibian species. The Panel recommended 

additional testing using three native species from three populations across the species’ range 

using multiple clutches (3) per population. The Panel also suggested conducting studies in 

parallel in multiple laboratories using the same protocol to evaluate concordance in the results. In 

another section of the Panel’s response (p 34 & 35), it referenced that additional laboratory and 

cosm studies on species other than X. laevis be conducted and included in the weight of evidence 

approach. At the request of the EPA, the Panel provided some information regarding culturing 

and testing of native amphibian species including: laboratories that have experience with North 

American amphibian species, and mesocosm detection power. They also discussed the impact of 

testing under more realistic environmental conditions on the ability to discern an effect and the 

quality of the data. 

At the 2003 SAP on potential developmental effects of atrazine on amphibians, the EPA asked 

the Panel if there were significant differences between X. laevis and a Rana species in terms of 

developmental processes. Some Panel members stated that there is little or no evidence to 

suggest significant differences in developmental pathways between the two species; however, 

some other members stated that there are significant differences in terms of timing of life cycle 

events such that concerns about differences could not be eliminated. The Panel was also asked to 

comment on what critical toxicokinetic processes should be considered for extrapolating X. 

laevis effects to Rana assuming that X. laevis and Rana were sufficiently concordant from a 

toxicodynamics perspective for developmental effects. The Panel was unaware of any 

pharmacokinetic studies with X. laevis or Rana pipiens that would allow for direct comparison 

for ADME; however, they stated that as X. laevis is fully aquatic and Rana is not, differences 

were anticipated, but their significance is uncertain. 

In the 2007 SAP meeting on atrazine’s potential to affect amphibian gonadal development, the 

EPA asked the Panel if the results obtained from the DCI study were sufficient to conclude that 

additional testing with indigenous species was not warranted. The Panel disagreed and noted one 

study (Glennemeir and Denver 2002) in which X. laevis and R. pipiens responded differently to 

stressors, as measured by whole body corticosterone. They also pointed to a study in which one 

ranid species appeared to be more susceptible to gonadal development than another ranid 

species. Furthermore, they provided a list of references on information on interspecies variation 

for amphibian species. 

The EPA appreciates all the feedback from the Panel on this issue. As an alternative to additional 

testing with native species, the EPA is anticipating examining further the potential differences in 

sensitivities with regard to biological and/or physiological factors between X. laevis and native 

species. A goal is to determine if a relationship(s) can be made across species to evaluate 

potential sensitivities. The EPA is interested in understanding if there are fundamental 

toxicodynamics and/or toxicokinetic differences between X. laevis and other native species of 

frogs such that it is expected to result in a markedly different response to a chemical such as 

atrazine. Targeted questions that might be asked include, are there differences in skin 

permeability between species and are there metabolic differences for a given biochemical 

pathway between the species? Xenopus laevis is a model test species for examining development 
13

toxicity of a chemical (ASTM FETAX), and is also a key model organism for biomedical 

research (National Xenopus Resource, Woods Hole, Massachusetts).6

 As such, information 

regarding physiological parameters and metabolic pathways for X. laevis may be available. 

Understanding, to the extent possible, ADME (administration; distribution; metabolism; 

excretion) and PBPK (physiologically-based pharmacokinetic) models for different species 

would be useful as it relates to potential atrazine exposure. The 2003 SAP panel was not aware 

of any pharmacokinetic studies with X. laevis or R. pipiens that would allow for direct 

comparison for uptake, metabolism or depuration; however, the EPA is interested if any studies 

now exist that may provide insight into those pathways. 

The development of AOPs, as described above for the EDSP program, based on the 2007 NAS 

report and the WoE framework from IPCS/ILSI documents7, includes the development of trying 

to establish linkages across species. The process, thus far, is to establish a mode of action, which 

then evaluates qualitative data for species to species sensitivity and, if available, to ultimately use 

quantitative data to examine species-to-species variability. This is being referred to as a 

“concordance analysis.” This involves establishing key events for a mode of action based on the 

Hill criteria, and then evaluating fundamental qualitative differences in the key events between 

species and ultimately evaluating quantitatively those differences. The approach being 

undertaken in this project may provide some utility in helping to develop a path forward when 

looking at potential differences between X. laevis and other amphibian species. 

The process to gather the type of information described above is anticipated to be conducted by 

searching the open literature for papers that may be useful in elucidating relevant pathways in 

amphibian species, as well as potential differences between them. As of now, open literature 

searches have focused on potential effects from exposure to atrazine specifically. However, for 

this exercise, the search will focus on broader basic physiological and biochemical parameters 

for amphibians. 

Stakeholder Input Requests 

The EPA is interested in obtaining information related to potential differences in sensitivities 

with regard to biological and/or physiological factors between X. laevis and native species. The 

EPA is interested in understanding if there are fundamental toxicodynamics and/or toxicokinetic 

differences between X. laevis and other native species of frogs such that it is expected to result in 

a markedly different response to a chemical such as atrazine. 

Other Atrazine Toxicity Topics Discussed at the June 2012 SAP 

While historically the focus of atrazine toxicity on amphibians has generally concentrated on 

sexual development, a number of studies reported the potential for atrazine to modify immune 

function and infection susceptibility in amphibians (Appendix C of the 2012 problem 

                                                           

6

 http://www.mbl.edu/xenopus/about/ 

7 http://www.ilsi.org and http://www.who.int/ipcs/methods/harmonization/index.html ; Meek et al. 2003; Seed et al. 2005; 

Sonich-Mullin et al. 2001; Boobis et al. 2006; Boobis et al. 2008
14

formulation). In the 2012 problem formulation, the EPA asserted that the research on these 

different hypotheses did not provide sufficient data to establish causal linkages among different 

levels of biological organization to result in adverse effects. Therefore, EPA concluded that a 

mode of action or adverse outcome pathway leading to effects on amphibian survival, growth or 

development could not yet be established. The 2012 SAP Panel agreed with the EPA’s 

conclusion that the existing data are insufficient to support or refute hypotheses that atrazine 

adversely affects immune function and infection susceptibility leading to adverse effects. 

However, the Panel did conclude that the information available was sufficient to conclude that 

there could be adverse effects, and recommended that the EPA further investigate this by 

engaging the scientific community to develop the necessary research protocols. 

As with other potential effects of atrazine exposure to non-target organism, the EPA will 

continue to monitor the open literature for studies on potential susceptibility and impacts of 

atrazine exposure on immune function for potential inclusion into the risk assessment. The 

results of these studies will be incorporated as appropriate. 

 

 
15

The Methodology for Determining the Levels of Concern for 

Atrazine 

Criteria Used for Scoring the Mesocosm and Microcosm Studies. 

The June 2012 SAP recommended that EPA publish the criteria used to score the mesocosm and 

microcosm studies. While this addendum will be the first formal publication of the criteria for 

scoring an endpoint in a cosm as an effect or no effect classification (described below), the 

committee of EPA scientists who reviewed the cosm studies followed the same basic principles 

discussed in Brock et al. 2000 and de Jong et al. 2008. Each endpoint was discussed and justified 

in a Data Evaluation Record (DER) for each study and is available to the public in the Federal 

Register Docket for Atrazine (http://www.regulations.gov/#!docketDetail;D=EPA-HQ-OPP2003-0367). The EPA scientists determined that an effect had occurred at a specific test 

concentration based on a statistically significant difference from the control or the magnitude and 

duration of the effect in the absence of a statistical analysis. The EPA scientific committee 

reviewing the cosm studies had further discussions about endpoints that were challenging to 

classify to determine the final endpoint classification through best professional judgment and 

scientific consensus. 

In the absence of statistical analysis, EPA used the following criteria to judge whether or not an 

effect was treatment-related: 

a. Professional judgment based decisions took into consideration the replication of 

treatment concentrations within the study, the type of endpoint, the variability in the 

response within and across test concentrations, the magnitude of the effect, and lastly, 

recovery. Generally, slight differences from the control were not considered effects in the 

absence of statistical analysis. However, in some cases, an endpoint may have been 

classified as an “Effect” when the magnitude could be considered as slight, but the 

difference from the control was statistically significant and persisted throughout the 

study. An effect was considered transient when recovery occurred quickly. However, it 

was not always possible to determine whether or not an effect was transient due to the 

study design and measurement schedule. Slight or transient effects were classified as a 

“No effect” for that test concentration. These effects would be considered as category 1 

or 2 under the Brock et al. (2000) and de Jong et al. (2008) methods. 

b. A pronounced effect did not require statistical significance for most endpoints (e.g.,

species composition, or chlorophyll A). In some cases a pronounced effect was reported; 

however, recovery of the measurement had occurred by the next measurement. Most 

pronounced effects reported did not recover by the end of the cosm experiment and were 

classified as an “Effect”. 

c. In the available cosm study dataset, recovery was only reported in a few of the studies. 

Graphics and data presented in each of the studies were used to qualitatively review if 

recovery had occurred; however, this was difficult to interpret in most studies. Recovery 

from the effects of atrazine and the development of resistance to the effects of atrazine in 
16

some vascular and non-vascular aquatic plant species have been reported in both single 

species studies and cosm experiments. However, reports of recovery were often based on 

differing interpretations. Additional uncertainty for recovery is that a single endpoint 

measurement (e.g., chlorophyll A) may show recovery, but other significant changes, 

such as community composition shifts, may have occurred in the study and were not 

documented or recovery was not observed. 

Concerns Regarding the Calculation of the CE-LOC 

The Panel identified a number of specific “issues to be considered” when evaluating cosm 

studies. 

Separate Lotic and Lentic Derived Studies and Use Only Lotic Test Systems (e.g., Artificial 

Streams, Flow-through Systems) for Evaluating Responses in Lotic Systems and Vice 

Versa. 

In response to this recommendation, EPA has conducted a review of the available cosm 

endpoints to see if there are major differences between lentic vs. lotic endpoint durations, 

concentrations or effect levels. The results indicate that there are very little differences between 

the lentic and lotic systems based on source communities, or study design (flow through or 

static). Figure 1 and Figure 2 illustrate the overlapping distribution the effects/no-effects 

endpoints based on these characteristics, and would be considered negligible. 

Figure 1. Cosm Study Endpoints Distinguished Based on Flowing, Static or Artificial 

Water Sources. 
17

Figure 2. Cosm Study Endpoints Distinguished Based on Flowing or Static Study Designs. 

Realistic Exposure Conditions and Cosm Study Duration to Best Represent Atrazine 

Exposure Conditions in the Field. 

The Panel recommended changes to the available cosm dataset, reducing the number of cosm 

endpoints to be included in the CE-LOC calculation. These recommendations included 

restricting the candidate cosm study endpoints to those within the typical concentration and 

duration window for atrazine. 

Based on the Atrazine Ecological Exposure Monitoring Program (AEEMP), EPA determined 

that a 240 day survey window would adequately represent the typical seasonal exposures of 

atrazine in the midwestern corn producing regions. Therefore this time frame will be used to 

limit the endpoints and chemographs from the cosm studies. The time restriction impacts 

endpoints 1, 2, 4, 5, 41, and 42 (Appendix A-1). These endpoints all originate from a series of 

multi-year experiments conducted at the University of Kansas from 1979-1991 (summarized in 

deNoyelles et al. 1982 and 1989). The effects noted in these studies were initially reported 

within the first few days to weeks following atrazine introduction into the mesocosms. However, 

as these effects were occurring throughout the study, these endpoints were not removed from the 

cosm endpoint database. 

The Panel’s recommendation to limit the endpoints to more realistic atrazine exposures, as 

identified from monitoring data, reduced the available cosm endpoint database. The peak non-
18

spill related concentration of atrazine in the natural environment is 237.5 ppb (excluding the 

value of 683.4 ppb, which is thought to be a result of a chemical spill; see Table 11 in problem 

formulation). EPA has decided to use 500 ppb (approximately 2X the measured peak value) to 

bound the upper concentration for inclusion in the analyses. This results in the removal of 11 

endpoints (Table 3). These implemented changes had negligible effect on the CE-LOC, 

changing the level from 4.23 μg/L to 4.38 μg/L. 

Table 3. Endpoints Removed from Available Cosm Endpoint Database Due to 

Restriction of Initial Endpoint Concentrations to Those Below 500 ppb. 

Endpoint 

Number 

Reference(s) Initial Test 

Concentration (μg/L) 

14 Stay et al., 1985 820 

15 Stay et al., 1985 3980 

19 Brockway et al., 1984 5000 

27 Johnson, 1986 1000 

29 Kosinski, 1984; Kosinski and Merkle, 1984 1000 

30 Kosinski, 1984; Kosinski and Merkle, 1984 10000 

33 Moorhead and Kosinski, 1986 1000 

37 Stay et al., 1989 1000 

38 Stay et al., 1989 5000 

45 Moorhead and Kosinski, 1986 10000 

97 Diana et al., 2000 2036 

Investigate Bias in Choice of Plant Species in Laboratory and Cosm Studies. 

The Panel expressed concern that the choice of photoautotrophic species used in laboratory and 

cosm experiments were chosen because most were easy to culture or obtain from commercial 

sources, and therefore, may represent resistant species. The Panel suggested that the EPA 

consider whether other species not in the database should be added. 

According to the cosm study reports that describe specific species included in the cosm 

experiments, there were approximately 150 species of photoautotrophs reported across the 

studies. This number is grossly underestimated because many of the studies only reported at 

higher taxonomic levels (e.g., Chlorphytes, Cyanophytes, Diatoms) but mention that hundreds of 

species were included in the cosm study (e.g., Pratt et al. 1988). Laboratory studies typically 

report the specific species tested. According to the available single species data, roughly 213 

species of photoautotrophs were studied. The combination of species represented in the cosms 

and laboratory testing represents the most comprehensive and broadly sampled herbicidal 

toxicity data for photoautotrophs. EPA believes that this diversity of taxa and aquatic plant 

communities represented in the laboratory studies and the cosm experiments is sufficient to 

establish a solid understanding of the toxicity of atrazine to single species and communities of 

aquatic photoautotrophs. 

 
19

Additional Cosm Study Reviews 

The Panel had concerns with the effects/no effects determinations for several cosm endpoints 

and proposed that several studies be removed from the endpoint dataset (Table 4). These studies 

and endpoints will be reevaluated prior to the risk assessment to consider their exclusion from 

the cosm endpoint dataset or reclassification as no effects. EPA’s justification and supporting 

evidence for currently including these endpoints and classifying the endpoints from these studies 

as effects are available in the data evaluation records (DER) for these studies 

(http://www.regulations.gov/#!docketDetail;D=EPA-HQ-OPP-2003-0367).

Table 4. Studies to be Re-reviewed Prior to the Risk Assessment. 

Endpoint Numbers Reference(s) Initial Test Concentrations (μg/L) 

58, 58b Lampert et al. (1989) 0.1, 1 

1, 2, 3, 4, 5, 41, 42, 

52 

deNoyelles et al. (1982), Carney and deNoyelles 

(1986), Dewey et al. 1986), Kettle et al. (1987), 

deNoyelles et al. (1989) 

20, 100, 200, 500 

22, 23, 24, 25 Detenbeck et al. (1996) 15, 25, 50, 79 

28, 44 Kosinski (1984) 10, 100 

83, 84 Sequin et al. (2001a) 2, 30 

85, 86 Sequin et al. (2001b) 2, 30 

87 Sequin et al. (2002) 30 

Prior to the risk assessment, an open literature search and review will be conducted to identify 

and evaluate any cosm studies testing atrazine toxicity that have not been previously considered. 

The cosm selection criteria and endpoint classification will follow the methods outlined in the 

problem formulation and as described above. At this time, several studies have been identified 

for future review (Table 5). 

Table 5. Studies Identified for Potential Inclusion of Endpoints for Cosm Dataset. 

Authors Title Publication Year 

Baxter LR;Moore 

DL;Sibley 

PK;Solomon 

KR;Hanson ML 

Atrazine does not Affect Algal Biomass or Snail 

Populations in Microcosm Communities at 

Environmentally Relevant Concentrations 

Environ. Toxicol. 

Chem.30(7): 1689-1696 

2011 

Hersh 

CM;Crumpton WG 

Atrazine Tolerance of Algae Isolated From Two 

Agricultural Streams 

Environ. Toxicol. 

Chem.8(4): 327-332 

1989 

Larsen 

DP;DeNoyelles F 

Jr;Stay 

F;Shiroyama T 

Comparisons of Single-Species, Microcosm and 

Experimental Pond Responses to Atrazine Exposure 

Environ. Toxicol. 

Chem.5(2): 179-190 

1986 

Lay JP;Muller 

A;Peichl L;Klein 

W;Korte F 

Long-Term Effects of the Herbicides Atrazine and 

Dichlobenil upon the Phytoplankton Density and 

Physico-chemical Conditions in Compartments of a 

Freshwater Pond 

Chemosphere13(7): 821-

832 

1984 

Murdock J.N; D.L. 

Wetzel 

 Macromolecular Response of Individual Algal Cells 

to Nutrient and Atrazine Mixtures within Biofilms. 

Microbial Ecology 2011 
20

Table 5. Studies Identified for Potential Inclusion of Endpoints for Cosm Dataset. 

Authors Title Publication Year 

Murdock J.N.; F.D. 

Shields; R.E. 

Lizotte 

Periphyton responses to nutrient and atrazine 

mixtures introduced through agricultural runoff 

Ecotoxicology 2012 

Pannard A;Le 

Rouzic B;Binet F 

Response of Phytoplankton Community to Low-Dose 

Atrazine Exposure Combined with Phosphorus 

Fluctuations 

Arch. Environ. Contam. 

Toxicol.57(1): 50-59 

2009 

Perschbacher 

PW;Ludwig 

GM;Edziyie R 

Effects of Atrazine Drift on Production Pond 

Plankton Communities and Water Quality Using 

Experimental Mesocosms 

J. World Aquacult. 

Soc.39(1): 126-130 

2008 

Knauer 

K;Leimgruber 

A;Hommen 

U;Knauert S 

Co-Tolerance of Phytoplankton Communities to 

Photosynthesis II Inhibitors 

Aquat. Toxicol.96(4): 256-

263 

2010 

Knauert S;Singer 

H;Hollender 

J;Knauer K 

Phytotoxicity of Atrazine, Isoproturon, and Diuron to 

Submersed Macrophytes in Outdoor Mesocosms 

Environ. Pollut.158(1): 

167-174 

2010 

Panel Recommendations Regarding the Calculation of the CE-LOC 

The Panel supported the overall methodology for calculating the Concentration Equivalent Level 

of Concern (CE-LOC); however, there were a few clarifications that they requested: 

Evaluate the Uncertainties Inherent in the Available Cosm Dataset and Estimate the 

Robustness of the Data to Estimate the CE-LOC. 

Methods such as bootstrapping or grouping data by exposure duration will be used to bound the 

uncertainties inherent in the cosm data. This will indicate the suitability of the available dataset 

for estimating a CE-LOC, and how large or small the dataset would need to be to adequately 

estimate a CE-LOC. 

Evaluate and Quantify the Cumulative Error in the CE-LOC Estimation. 

The aggregate error and assumptions in PATI, the estimation of the 50th percentile of the 

distribution of cosm effects data, and the final conversion to a concentration based value, will be 

assessed. An estimate of the cumulative error will be established for the CE-LOC. 

Consideration for Additional Cosm Testing 

The Panel’s recommendations for future cosm experiments included the following design 

elements: 

1) The cosm study should be designed to mimic natural field conditions and examine 

how scale, time, water flow, etc., relate to atrazine toxicity to the entire community. 
21

The size of the cosm and hydrologic regime should be correlated to the community of 

interest. 

2) The study should have suitable replication (3 or more replicates). 

3) Focused cosm studies to specifically address durations of exposure at 

environmentally relevant concentrations to support conclusion that the CE-LOC is 

protective of organisms in the aquatic community. 

4) A broad representation of plants and photoautotrophs representing the range of 

potential levels of sensitivity to anthropogenic stress should be included. 

5) A source of re-colonization, i.e., natural biologically active sediments, should be used 

in the study to allow for the development of more natural structural and functional 

components of the community. 

 

At this point in time, the EPA is not proposing to require the registrant to submit additional cosm 

studies prior to the risk assessment for atrazine. While the EPA will consider any new studies 

that are conducted and published prior to the risk assessment, we believe that the available cosm 

data set is representative of the natural communities that the CE-LOC is intended to protect, and 

the communities likely to receive the highest concentrations of atrazine under currently labeled 

use patterns. The evaluation of source water and cosm study design as discussed above, suggests 

that, based on the available data, there are minimal differences in the cosm endpoints when 

comparing lotic versus lentic sources. Based on the available monitoring data, the durations and 

exposures that the studies tested represent the typical time window and concentrations that are 

expected in lotic and lentic ecosystems. Furthermore, as described above, the diversity of 

photoautotrophs in the current set of cosm studies represents a broad diversity of organisms and 

communities. For these and other reasons, the cosm studies are considered to be suitable 

surrogates for the spectrum of sensitivities expected across photoautotrophs and aquatic plant 

communities. 

Lastly, the addition of endpoints from a cosm designed to straddle the CE-LOC will have 

minimal impact on the CE-LOC as it pertains to the number and distribution of exceeding 

streams and lakes across the atrazine use area. Any new cosm studies will be added to the 

endpoints already determined to be suitable for calculating the CE-LOC (see Appendix D), and 

would have equal weight in the calculation of the CE-LOC. Thus, it would be unlikely for the 

CE-LOC to be greatly impacted by the addition of these endpoints. 

As a test of the sensitivity of the CE-LOC to a study that would be aimed at spanning the CELOC and carried out for a 60-day duration, the following hypothetical data were constructed and 

added into the cosm endpoint database individually. The hypothetical test concentrations in all 

five tests were 50, 40, 30, 20, 10, 1 and 0.1 ug/L and concentrations were held constant for the 

duration of the hypothetical studies. Table 6 shows the CE-LOC results as an effect of changing 

the effect level from 30 to 0.1 ug/L in each hypothetical study. As shown in the table, the 

addition of each study individually to the available endpoints changes the CE-LOC. When 

comparing these results to a CE-LOC of 4 ug/L, the EPA believes that this CE-LOC represents a 
22

60-day average concentration that is protective of aquatic plant communities, and that the 

addition of more data will unlikely significantly change the CE-LOC. 

 

Table 6. Resulting CE-LOCs from the Addition of Single 

Hypothetical Test Endpoints. 

Hypothetical 

Study 

Effect Endpoints in Test CE-LOC 

(ug/L) 

A 50, 40, 30 5.4 

B 50, 40, 30, 20 5.0 

C 50, 40, 30, 20, 10 4.5 

D 50, 40, 30, 20, 10, 1 3.6 

E 50, 40, 30, 20, 10, 1, 0.1 2.7 
23

Method for Determining Vulnerable Watersheds 

Development and Implementation of Methods for Quantitative Interpretation 

of Atrazine Occurrence Data in Surface Water 

There are extensive surface water monitoring data from federal, state, and registrant-sponsored 

monitoring programs for atrazine. Uncertainties in monitoring data results may be attributed to 

sample frequency, sample location, sample timing, and sample method, among other factors. The 

net impact of these sampling variables can lead to underestimation of true atrazine 

concentrations. The purpose of this section of the addendum to the 2012 problem formulation is 

to put forth several possible approaches for predicting atrazine concentrations in monitored and 

non-monitored surface water and to address Panel comments on the development and 

implementation of bias factors. 

EPA has requested input from the Panel on the development of methods for quantitative 

interpretation of atrazine monitoring data for use in ecological and drinking water exposure 

assessment (USEPA 2009, 2010, 2011, and 2012). Various methods including bias factors, 

kriging, conditional simulation, and environmental fate modeling were considered as potential 

approaches to address uncertainties in estimating atrazine concentrations from monitoring data. 

Additionally, EPA has used various modeling approaches such as Watershed Regression for 

Pesticides (WARP) modeling for predicting vulnerability of watersheds for atrazine runoff 

(USEPA 2009). These methods represent a spectrum of tools available to allow for spatiallytemporally explicit prediction of atrazine concentrations. 

In the problem formulation phase, various tools and data, including environmental fate data, 

watershed vulnerability analysis tools, watershed surface water models, and monitoring data will 

be used to predict atrazine concentrations in surface water. These tools and data will be used in 

the analysis phase to predict atrazine concentrations in surface water. If the sampling site has a 

predicted concentration exceeding an aquatic exposure endpoint (CE-LOC) or the drinking water 

level of concern (LOC), these results will be communicated to risk managers for a decision on 

possible risk mitigation.
24

Figure 3. Proposed Flow Chart for Assessing Atrazine Concentrations in Monitored and 

Non-Monitored Surface Water in the Risk Assessment Framework 

Proposed Approach for Estimating Atrazine Aquatic Exposure 

Concentrations in Surface Water 

The proposed approach for assessing atrazine exposure provides a logical integration of available 

models and tools for quantitative prediction of atrazine concentrations in surface water. Key 

criteria for selection of various models and tools are as follows: 

A. Rigorous scientific peer review (i.e., FIFRA Scientific Advisory Panel); 

B. Employs a watershed-based approach consistent with atrazine ecological monitoring 

program; 

C. Prediction of spatially-temporal explicit atrazine concentrations; 

D. Prediction of atrazine exposure concentrations for risk assessment; and, 

E. Defined statistical probability for magnitude and frequency of atrazine occurrence. 

Using these criteria, the most logical approach for assessing atrazine exposure in surface water is 

to employ exposure modeling and bias factors for sites with monitoring data (
25

Figure 4). 
Figure 4. Proposed Decision Tree in Assessing Monitoring Data and Modeling Data for Aquatic Exposure Assessment for Atrazine. 
27

In order to be able to accurately predict atrazine concentrations in surface water, an approach that 

considers available monitoring data in concert with computer modeling is needed. There are 

extensive monitoring data for atrazine and its degradation products in surface water (USEPA 

2012). Although these monitoring data cover a large spatial and temporal range in the United 

States, the results are expected to underestimate actual atrazine concentrations due to inadequate 

sampling frequencies (USEPA 2009, 2010, 2011, 2012). The AEEMP provides extensive 

monitoring data for ranking watershed vulnerability to atrazine runoff according to watershed 

properties with known statistical confidence. 

A key aspect of this vulnerability assessment is determining whether a monitoring site of interest 

is included in the population of AEEMP monitoring sites. For monitoring sites not described in 

the population of AEEMP monitoring sites, the SAP recommended exploring the use of 

statistically-based bias factors to normalize atrazine monitoring data according to sampling 

frequency. The Panel also recommended considering other modeling approaches (USGS 

SEAWAVE and PRZM Hybrid Model) for predicting atrazine chemographs of daily 

concentrations from monitoring data. 

The ability to predict atrazine concentrations in non-monitored surface waters is another 

important component in assessing atrazine exposure. Although there are extensive surface water 

monitoring data for atrazine, these monitoring data represent only a small fraction of the stream 

miles in the United States. The atrazine runoff capability of some watersheds will be described 

using a watershed vulnerability assessment from AEEMP data. These data, however, may not be 

representative of all watersheds with atrazine use. For these sites, watershed-based exposure 

models are important tools for estimating atrazine concentrations. Several models for estimating 

atrazine concentrations in surface water have been presented over the years to the SAP (USEPA 

2009, 2010, 2011, 2012). Models considered include USGS WARP Model (Larson et al., 2004), 

USGS 2011 Corn Belt WARP Model (Stone and Gilliom, 2011), and PRZM-Hybrid Model (US 

EPA 2010, 2011, and 2012). The SAP recommended consideration of these models for 

estimation of atrazine exposure concentrations in non-monitored watersheds. 

Atrazine Ecological Exposure Monitoring Program (AEEMP)8

Background 

The 2003 Interim Reregistration Eligibility Decision for atrazine stipulated that the registrant 

conduct an atrazine ecological monitoring program (Atrazine Ecological Monitoring Program, 

2003). The primary objectives of the monitoring program were to: 

1. determine the number of watersheds identified in EPA’s vulnerability assessment that 

exceed the aquatic exposure trigger (CE-LOC) with known statistical confidence, 

2. assist in identifying vulnerable watersheds based on known watershed characteristics, 

and 

                                                           

8

 Syngenta refers to this monitoring program as the Atrazine Ecological Monitoring Program (AEMP). 
28

3. identify reliable watershed-dependent mitigation options for reducing atrazine 

exposure in aquatic environments. 

The AEEMP is primarily focused on flowing water in the Corn Belt; however, monitoring in 

static water bodies such as reservoirs, lakes, and ponds, in addition to sugarcane use areas, is also 

part of this exercise. The Syngenta Atrazine Monitoring Program (AMP), as well as historical 

data from the Novartis Voluntary Monitoring Program (VMP), will be used to assess the ability 

to predict vulnerability in static water. Additionally, targeted monitoring sites for freshwater and 

estuarine areas will be addressed through the selection of monitoring sites in sugarcane growing 

areas. 

Monitoring sites in the AEEMP were selected according to their watershed vulnerability. The 

watershed vulnerability assessment focused on watersheds at the HUC-10/11 scale in corn and 

sorghum use areas. The watersheds ranged in size from 40,000 to 250,000 acres. Three tiers of 

watersheds were selected to identify the vulnerable watersheds. 

The first tier consisted of approximately 10,000 HUC-10/11 watersheds with atrazine use areas 

overlapped corn or sorghum growing areas. From these watersheds, the atrazine use intensity on 

a county basis was calculated to estimate the mass of atrazine used (lbs a.i.) per county acre. 

The second tier of watersheds was selected because the atrazine use intensity was ≥ 0.25 lbs 

atrazine/county acre. The National USGS Watershed Regression for Pesticides model (National 

WARP) was used to estimate predicted atrazine concentration in the flowing surface water for 

each watershed with a use intensity of ≥ 0.25 lbs atrazine/county acre. Explanatory variables in 

the National WARP model include atrazine use intensity, rainfall erosivity factor (R-factor), soil 

erodibility (K-factor), watershed area, and Dunne overland flow. 

The third tier of watersheds was selected as the upper 20th percentile of watersheds according the 

WARP estimates. This process led to identification of a population of 1,172 watersheds as the 

most potentially vulnerable to atrazine loading. The watersheds were further divided into two 

categories. From these sites, 40 sites were selected to be probabilistically proportional to the 

atrazine use and spatially balanced across the corn and sorghum use area. 

The criteria for selection of water bodies in the selected watersheds were: 

1. water bodies have perennial flow; 

2. there is a high cropped area (≥ 50th percentile of crop area); 

3. there is a low urban use influence (≤10% percent urban area); 

4. the selected stream segment has a maximum drainage area (minimum drainage area 

of 9 mi2

 and maximum drainage area of 50 percent of HUC11); 

5. stream segment should have no adverse site characteristics (i.e., low corn agriculture 

area, low prevalence of herbicide-tolerant corn, no point sources such as pesticide 

distributors). 

Some of the uncertainties in the monitoring data analysis will be to account for interpolation of 

atrazine concentrations between 4-day sampling intervals, to estimate temporal variation of 

atrazine runoff from two-site years of sampling per site, to account for variability associated with 
29

sample collection, and to account for survey error (unbiased estimator of characteristic of 

interest). 

An additional watershed vulnerability analysis was conducted on AEEMP data from 2004-2007. 

This analysis showed that the presence of a shallow clay pan or low permeability horizon in the 

watershed soils is an important explanatory variable in estimating atrazine concentrations in 

surface water (USEPA 2009). This work led USGS to develop another regression equation, Corn 

Belt WARP, to refine prediction of atrazine concentrations in surface water (Stone and Gilliom, 

2011). Explanatory variables in the WARP CB model include atrazine use intensity, percentage 

of agricultural watershed area with a soil restrictive layer within the top 25 cm of the soil surface, 

total precipitation from May to June, percent of stream flow to Hortonian overland flow, 

watershed area, and percentage of watershed that is artificially tile drained. The WARP CB 

regression is based on monitoring data from IA, IL, IN, MN, SD, NE, KS, MS, OH, and WI. The 

WARP CB model provides more reliable prediction of atrazine concentrations than the National 

WARP model. 

The Current Aquatic Ecosystem Level of Concern (CE-LOC) 

The EPA is currently estimating the aquatic ecosystem level of concern as approximately 10 

parts per billion (ppb) for atrazine over a 60-day period. This estimate was developed using the 

PATI model described in EPA’s issue paper that we presented to the 2009 SAP, available at 

www.regulations.gov in docket number EPA-HQ-OPP-2009-0104-0006.

9

If a watershed shows levels of atrazine above this level of concern in any two years of 

monitoring, atrazine registrants must initiate watershed-based management activities in concert 

with state or local watershed programs to reduce atrazine exposure. These remedies will be 

consistent with the approaches used in the EPA Office of Water's Total Maximum Daily Load 

(TMDL) program but are enforceable under FIFRA through the 2003 Atrazine IRED and 

Memorandum of Agreement. 

Monitoring Results in Areas of Corn, Sorghum, and Sugarcane Production 

With regard to corn and sorghum producing areas, the AEEMP was designed to focus initially on 

flowing water bodies in the most vulnerable watersheds in the Midwest. Monitoring occurred 

over a two- to three-year period (2004 through 2006) in 40 watersheds, and certain sites have had 

additional monitoring conducted from 2007-2012. These initial 40 were selected to be 

representative of watersheds potentially vulnerable to atrazine runoff. 

The results of this survey informed EPA’s decision to sample an additional 25 sites across the 

Midwest. These sites were selected from the 455 most vulnerable watersheds identified in the 

vulnerability assessment that was presented to the 2007 SAP. The 25 sites as well as the 

remaining 430 watersheds share atrazine use and climate/geological characteristics with the most 

                                                           

9

 As described in the 2012 SAP documents and within this addendum, the CELOC will be updated for the upcoming 

risk assessment. 
30

vulnerable of the original 40 sites and thus were expected to be prone to atrazine runoff resulting 

in water concentrations that exceed EPA's levels of concern. The 2010, 2011, and 2012 

monitoring results for these new sites, as well as the existing sites, are presented below in Tables 

7 and 8 (Annual summaries for the AEEMP from 2004-2012 are found in Appendix S-1). 
31

Table 7. Summary of atrazine concentrations in corn/sorghum AEEMP sites from the past 3 years.

Sites decommissioned in 2012 are indicated with “NA”. Bolded values indicate an LOC exceedance.

Site ID Max 60‐day Avg. Value (μg/L)

2010 2011 2012

IA‐03 10.5 4.9 2.0

IA‐04 10.4 4.3 10.9

IA‐05 11.3 12.8 7.0

IL‐10 0.4 1.4 0.7

IL‐11 1.1 1.8 NA

IL‐12 6.9 4.6 5.6

IL‐13 0.7 1.4 NA

IL‐14 5.2 4.9 3.4

IL‐15 6.8 6.8 7.0

IL‐16 7.5 2.6 9.5

IL‐17 5.7 17.2 6.3

IN‐12 4.5 4.2 1.5

KS‐01 5.4 1.5 2.6

KS‐02 8.9 3.5 1.6

KS‐03 11.6 5.9 4.4

LA‐04 6.3 27.4 11.5

LA‐05 3.3 4.2 NA

MO‐01 5.1 4.5 1.4

MO‐02 8.4 6.6 1.8

MO‐04A 8.7 11.5 7.5

MO‐05 12.9 6.2 4.0

MO‐05B 12.3 8.3 5.6

MO‐06 6.3 6.9 3.7

MO‐07 20.2 14.6 11.9

MO‐08 14.5 14.1 11.2

NE‐04 34.7 3.4 2.4

NE‐05 8.1 2.3 1.0

NE‐09 6.2 1.2 4.9

OH‐05 2.0 1.4 1.9

OH‐06 3.8 5.9 5.2

TX‐01 13.5 3.0 15.6

TX‐02 3.7 0.2 3.3

 
32

Table 8.  Summary of atrazine concentrations in the remaining active Louisiana sugarcane

AEEMP sites from 2010‐2012. Bolded values indicate an LOC exceedance.

Site ID Year Max 60‐day Avg. Value (μg/L)

LA‐01 2010 9.5

2011 5.3

2012 2.2

LA‐03 2010 0.6

2011 0.8

2012 0.6

Based on these most recent monitoring results, there are six watersheds that have exceeded EPA’s 

published CE-LOC in at least 2 of the last three years. They are IA-04, IA-05, LA-04, MO-07, MO-08, 

and TX-01. These watersheds were selected from a statistically-based survey design and represent a 

larger number of vulnerable watersheds across the landscape. Figure 5 identifies the 455 vulnerable 

watersheds represented by the currently monitored watersheds, along with the locations of the 25 

corn/sorghum monitoring sites. 
33
34

Considerations for Atrazine Risk Assessment 

As highlighted in the AEEMP Subgroup Final Report, the reanalysis of monitoring data provides 

a feedback mechanism to reexamine the watershed properties contributing to vulnerability for 

atrazine runoff. 

An evaluation of the AEEMP indicated the presence of soil restrictive layer is an important 

watershed property controlling atrazine runoff. A revised watershed vulnerability analyses for 

selection of AEEMP index monitoring sites will be conducted to address the current toxicity 

endpoint (CE-LOC) for atrazine and the WARP CB model. This analysis is expected to change 

the geographic distribution of vulnerable watersheds in the Corn Belt region. This work will 

provide a more reliable identification of vulnerable watersheds for atrazine runoff. 

Bias Factors 

Background 

Pesticide concentrations from monitoring data are expected to be biased-low because of 

inadequate sampling frequency to capture the maximum pesticide concentrations (USEPA 2010). 

To address this situation, EPA evaluated several methods of data interpolation to allow 

prediction of daily concentrations from monitoring data (US EPA 2011). These methods 

included bias factors, kriging, conditional simulation, and exposure modeling. From these 

methods, the SAP recommended the development and application of bias factors to account for 

the underestimation of pesticide concentrations from monitoring data. 

The bias factor is a statistically-derived multiplicative factor to correct for underestimation of 

atrazine concentrations from monitoring data (US EPA 2011 and 2012). The bias factor is based 

on selection of the 5th percentile concentration from simulated stratified random sampling of 

monitoring data from the AEEMP index sites. The bias factor is estimated by dividing the actual 

atrazine concentration by the 5th percentile concentration from simulated stratified random 

sampling; and, there is 95% confidence the bias factor corrected concentration is equal to or less 

than the actual measured concentration. The AEEMP monitoring data were used to develop bias 

factors because of the high frequency sampling (daily to 4-day sampling intervals), high 

vulnerability of atrazine runoff at the monitoring sites, and multiple years of sampling (2004-

present). 

The implementation of bias factors is described in the attached problem formulation. The 

implementation strategy is based on developing regression equations for describing the 

relationship of sampling frequency and bias factor; an increase in bias factor with a decrease in 

sampling frequency (few samples). The regression equations, therefore, could be used to predict 

the appropriate bias factor for monitoring data based sampling frequency alone. 

Considerations for Atrazine Risk Assessment 

The Panel recommended that development and implementation of bias factors should consider 

the following issues, which will be addressed in the assessment: 

 
35

BIAS FACTORS SHOULD CONSIDER DIFFERENT WATERSHED CHARACTERISTICS

AEEMP and NWQRL monitoring data have been used to develop the bias factors. The 

watershed characteristics of the AEEMP index monitoring sites are representative of 

vulnerable watersheds for atrazine runoff in IN, KY, IL, IA, MO, NE, MN, TN, and LA. 

These watersheds have an average watershed area of 129 mile2 with a range of 8.2 to 333.9 

mile2. Twenty-seven of the 40 watersheds are headwater watersheds with no upstream 

surface flow contribution from the main stream channel from outside of the watershed. In 

contrast, the NWQRL are representative of large watersheds (range in watershed size) in 

Ohio. Additionally, the AMP monitoring data are also available to allow estimation of bias 

factors. Together, these monitoring data (AEEMP, NWQRL, and AMP) are expected to 

represent a range of watershed characteristics for estimation of bias factors. 

DEVELOPMENT OF BIAS FACTORS SHOULD BE REPRESENTATIVE OF WATERSHEDS WITH 

ATRAZINE USE. 

The watersheds from appropriate monitoring data (such as AEEMP, AMP, and NWQRL) 

will be evaluated using the revised watershed vulnerability assessment as detailed in the 

Atrazine Ecological Monitoring Program (AEEMP) section above. Bias factors will be 

assigned to appropriate watershed vulnerability classes to represent the range of watershed 

properties. 

BIAS FACTORS SHOULD BE BASED ON AN ADEQUATE NUMBER OF SITE-YEARS

Illustration of the development and implementation of bias factors, as presented in the FIFRA 

SAP in 2011 and 2012, was based on 2 to 8 monitoring site-years. The 2012 Panel 

recommended that an adequate number of site-years (50 to 100 site years) be considered to 

account for the variability in meteorological data (precipitation amounts and timing) and in 

agricultural management practices (crop rotations, pesticide application timing, etc.). 

The development of bias factors will be based on the maximum available site-years from 

appropriate watershed vulnerability classes as identified in the AEEMP, AMP, and NWQRL 

monitoring programs. 

BIAS FACTORS SHOULD REPRESENT DIFFERENT SAMPLING INTERVALS

Bias factors have been developed for daily, 4 day, 7 day, 14 day, and 28 sampling intervals. 

The 2012 Panel recommended that an adequate number of sampling intervals be developed 

to allow adequate prediction of bias factors using either a regression equation or categorical 

method. 

Bias factors will be developed with more sampling intervals to allow a more precise 

prediction of bias factors. 

BIAS FACTORS SHOULD BE DEVELOPED TO ACCOUNT FOR DIFFERENT SAMPLING STRATEGIES 

(STRATIFIED, STRATIFIED RANDOM, SYSTEMATIC, RANDOM) 

Sampling strategies are an important consideration in the development of bias factors. The 

development of bias factors has been based on the stratified, random sampling. This 
36

sampling strategy ignores the impact of autocorrelation (presence of dependence) of atrazine 

concentrations in time. The 2012 Panel recommended that bias factors be developed for 

various sampling strategies. 

Bias factors will be developed for both stratified random sampling and systematic sampling 

strategies. 

BIAS FACTORS SHOULD BE DEVELOPED ON ROBUST MONITORING DATA 

Bias factors have been developed on monitoring data from both AEEMP and NWQRL. 

These data are unique because they contain near daily monitoring data. Additionally, the 

AEEMP monitoring data represents both grab samples at 4-day sampling intervals and daily 

samples from continuous auto-samplers. The Panel recommended that bias factors be 

developed on the daily AEEMP data taken using auto-samplers (AEEMP 2009-present). 

These data would eliminate uncertainties associated with data interpolation of monitoring 

data. 

EPA will consider the Panel’s recommendation, bias factors will be developed using AEEMP 

monitoring data from AEEMP 2009 to present because these data were collected using 

autosamplers. Bias factor development will also consider monitoring data with model 

interpolated data (i.e., SEAWAVE-Q), stair step interpolation, and linear interpolation to 

assess the potential for development of bias factors from monitoring data with longer 

sampling frequencies. 

BIAS FACTORS SHOULD BE DEVELOPED FOR DIFFERENT HYDROLOGICAL CONDITIONS

Bias factors, as presented to FIFRA SAP in 2011 and 2012, were developed for flowing 

water bodies from AEEMP and NWQRL monitoring data. The implementation of bias factor 

was demonstrated by applying bias factors for flowing water bodies to other water bodies 

such as reservoirs, lakes, etc. The 2012 Panel recommended that watershed hydrology is an 

important consideration in developing and applying bias factors. 

Future bias factor development will be based on the watershed hydrology. The AEEMP and 

NWQRL will be used to develop bias factors for flowing water. The AMP monitoring data 

will be used to represent monitoring data from reservoirs. 

BIAS FACTORS SHOULD PROVIDE A SPECIFIC EXPOSURE ENDPOINT WITH KNOWN STATISTICAL 

CONFIDENCE IN MAGNITUDE AND FREQUENCY 

Bias factors, as presented in the FIFRA SAP in 2011 and 2012, were developed to capture 

the 95th percentile concentration at a single site-year. The Panel recommended that a clear 

statement on the statistical confidence of the magnitude and frequency of bias factor 

corrected monitoring data is needed. For context, the magnitude and frequency of exposure 

used in FIFRA and FQPA modeling is the 1 in 10 year exposure concentration. Although the 

bias factor provides statistical confidence on the magnitude on the bias factor- corrected 

concentration, it does not provide any statistical confidence on the return frequency. 

Because the AEEMP provides 8 years of monitoring data (2004-2012) at 40 sites with 

monitoring frequency of two years per site, the development of 1 in 10 year bias factor is not 
37

possible at this time. However, the AEEMP monitoring data may provide sufficient 

information to determine a 1 in 8 year return frequency if there is appropriate grouping of 

sites into watershed vulnerability classes. This approach will be evaluated using watershed 

vulnerability classifications as described in the Atrazine Ecological Monitoring Program 

(AEEMP) section above. 

Strategy for Bias Factor Development and Implementation 

Addressing the Panel comments on development and implementation of bias factors requires 

consideration of numerous variables including watershed vulnerability, watershed hydrology, 

sampling strategy, and data interpolation technique. Figure 6 provides a schematic to address the 

Panel’s recommendations on bias factor development and implementation. The key aspect of this 

schematic is that a single bias factor is not expected to be appropriate for national exposure 

because of variability in use patterns, meteorology, soils, etc. Therefore, the variables 

recommended by the Panel will be used to more develop and apply bias factors to monitoring 

data. 

Figure 6. Schematic of Variables to Be Considered in Developing and Applying Bias Factors to Monitoring 

Data 

Quantitative Modeling of Monitoring Data Section 

Background 

An important consideration in analyzing monitoring data is the requirement for data interpolation 

between measured concentrations. Several FIFRA SAPs have recommended consideration of 

various approaches for estimating daily atrazine concentrations from monitoring data including 

chemograph shape analysis, kriging, conditional simulation, and exposure modeling 

(SEAWAVE, PRZM-Hybrid) (US EPA 2010, 2011, and 2012). EPA conducted an analysis of 

kriging, conditional simulation, covariate modeling and exposure modeling using selected 

AEEMP data. EPA found that kriging and conditional simulation required at least 15 uncensored 

data sets in the 2 and 3rd quarter of the year to describe a seasonal chemograph of atrazine. 

Additionally, EPA investigated the use of covariates such as daily flow to predict atrazine 

concentrations in surface water at selected AEEMP sites. Because all these methods require a 

considerable amount of subjective judgment for fitting the monitoring data, they may not be 
38

compatible for large scale data analysis. The FIFRA SAP in 2011 recommended consideration of 

exposure modeling such as SEAWAVE and PRZM-Hybrid models as alternative tools for 

predicting daily concentrations from monitoring data. 

Considerations for Atrazine Risk Assessment 

EPA is investigating the SEAWAVE-Q model as a tool for predicting daily concentrations of 

atrazine concentrations at monitoring sites. The SEAWAVE-Q model has been used by USGS 

for trend analysis of pesticide monitoring data (Ryberg et al., 2010 and Sullivan et al., 2009). 

The minimum data requirement for the SEAWAVE-Q model is 3 years of monitoring data with 

8 detections per year. Currently, the USGS is preparing a standardized R Program Package for 

the SEAWAVE-Q model. EPA will be working with the USGS to beta test the R program 

SEAWAVE model. This beta-testing will provide an opportunity to understand the model and its 

potential application in pesticide exposure assessments. 

 
39

Further Considerations for Registration Review 

Drinking Water Assessment 

A new drinking water assessment will be conducted to support future human health dietary risk 

assessments of atrazine and will consider all currently registered uses. The new drinking water 

assessment will incorporate model estimates as well as available monitoring data of atrazine and 

any transformation products of toxicological concern that might be identified by the Health 

Effects Division in surface water and groundwater. The potential toxicity of atrazine 

transformation products will be considered in the drinking water assessment conducted during 

the Registration Review process. In addition, the triazine cumulative drinking water assessment 

will be updated if needed for registration review. 

Endocrine Disruptor Screening Program (EDSP) 

As required by FIFRA and FFDCA, EPA reviews numerous studies to assess potential adverse 

outcomes from exposure to chemicals. Collectively, these studies include acute, subchronic and 

chronic toxicity, including assessments of carcinogenicity, neurotoxicity, developmental, 

reproductive, and general or systemic toxicity. These studies include endpoints which may be 

susceptible to endocrine influence, including effects on endocrine target organ histopathology, 

organ weights, estrus cyclicity, sexual maturation, fertility, pregnancy rates, reproductive loss, 

and sex ratios in offspring. For ecological hazard assessments, EPA evaluates acute tests and 

chronic studies that assess growth, developmental and reproductive effects in different 

taxonomic groups. As part of its reregistration decision, EPA reviewed these data and selected 

the most sensitive endpoints for relevant risk assessment scenarios from the existing hazard 

database. However, as required by FFDCA section 408(p), atrazine is subject to the endocrine 

screening part of the Endocrine Disruptor Screening Program (EDSP). 

EPA has developed the EDSP to determine whether certain substances (including pesticide 

active and other ingredients) may have an effect in humans or wildlife similar to an effect 

produced by a “naturally occurring estrogen, or other such endocrine effects as the Administrator 

may designate.” The EDSP employs a two-tiered approach to making the statutorily required 

determinations. Tier 1 consists of a battery of 11 screening assays to identify the potential of a 

chemical substance to interact with the estrogen, androgen, or thyroid (E, A, or T) hormonal 

systems. Chemicals that go through Tier 1 screening and are found to have the potential to 

interact with E, A, or T hormonal systems will proceed to the next stage of the EDSP where EPA 

will determine which, if any, of the Tier 2 tests are necessary based on the available data. Tier 2 

testing is designed to identify any adverse endocrine-related effects caused by the substance, and 

establish a dose-response relationship between the dose and the E, A, or T effect. 

Under FFDCA section 408(p), EPA must screen all pesticide chemicals. Between October 2009 

and February 2010, EPA issued test orders/data call-ins for the first group of 67 chemicals, 

which contains 58 pesticide active ingredients and 9 inert ingredients. Atrazine was included on 

that list and has been issued an order to conduct the Tier 1 testing. Once all required Tier 1 and 

Tier 2 data have been received and reviewed, the endpoints and safety factors used for risk 

assessment purposes will be examined and a new risk assessment performed if necessary. For 

further information on the status of the EDSP, the policies and procedures, the list of 67 
40

chemicals, future lists, the test guidelines and the Tier 1 screening battery, please visit our 

website: http://www.epa.gov/endo/. 

Endangered Species Assessments 

Consistent with EPA’s responsibility under the Endangered Species Act (ESA), EPA will 

evaluate exposure and potential risks to federally listed threatened and/or endangered (listed) 

species from registered uses of pesticides in registration review. 

Preliminary Identification of Data Gaps 

The database for environmental fate and transport, and ecological effects for atrazine is sufficient 

for risk assessment. No additional data are needed at this time. 

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Stay, F.S., Larsen, D.P., Katko, A., and Rohm, C.M., (1985) Effects of Atrazine on Community 

Level Responses in Taub Microcosms. Validation and Predictability of Laboratory Methods for 

Assessing the Fate and Effects of Contaminants in Aquatic Ecosystems, ATSM STP 865, T.P. 

Boyle, Ed., American Society for Testing and Materials, Philadelphia, pp. 75-90 (MRID 

45087419). 

Stay, E.F., A. Katko, C.M. Rohm, M.A. Fix, and D.P. Larsen. (1989). The effects of atrazine on 

microcosms developed from four natural plankton communities. Arch. Environ. Contam. 

Toxicol. 18:866-875. (MRID 47543515). 

Stone, W.W. and Gilliom, R.J. (2011). Watershed regressions for pesticides (WARP) for 

predicting atrazine concentration in Corn Belt streams. U.S. Geological Survey Open-File Report 

2011-1141. 

Sullivan, D.J., Vecchia, A.V., Gilliom, R.J., and Martin, J.D. (2009). Trends in pesticide 

concentrations in corn-belt streams, 1996-2006. U.S. Geological Survey Scientific Investigations 

Report 2009-5132. 

Thurman, N., Costello, K., Frankenberry, M., Lin, J., Bradbury, S., Irene, S., Brady, D., 

Gabanski, L., Chemerys, R., Holdsworth, S., Well, D., Grevatt, P., Detenbeck, N., Olsen, T., 

Hendley, P., Hertl, P., and Harbourt, C. 2003. Atrazine Ecological Monitoring Program 

Subgroup Final Report: Recommendations for Monitoring Program. 

U.S. Environmental Protection Agency (USEPA). 2003. FIFRA Scientific Advisory Panel: A Set 

of Scientific Issues Being Considered by the Environmental Protection Agency Regarding: 

Potential Developmental Effects of Atrazine on Amphibians. June 17 - 20, 2003. Available at 

EPA-HQ-OPP-2003-0186. 

U.S. Environmental Protection Agency (USEPA). 2009. FIFRA Scientific Advisory Panel: A Set 

of Scientific Issues Being Considered by the Environmental Protection Agency Regarding:The 

Ecological Significance of Atrazine Effects on Primary Producers in Surface Water Streams in 

the Corn and Sorghum Growing Regions of the United States. May 12-15, 2009. 

U.S. Environmental Protection Agency (USEPA). 2010. FIFRA Scientific Advisory Panel: A Set 

of Scientific Issues Being Considered by the Environmental Protection Agency Regarding: ReEvaluation of Human Health Effects of Atrazine: Review of Experimental Animal and In Vitro 

Studies and Drinking Water Monitoring Frequency. April 26-29, 2010. 

U.S. Environmental Protection Agency (USEPA). 2011. FIFRA Scientific Advisory Panel: A Set 

of Scientific Issues Being Considered by the Environmental Protection Agency Regarding: ReEvaluation of Human Health Effects of Atrazine: Review of Non-Cancer Effects, Drinking 

Water Monitoring Frequency, and Cancer Epidemology. July 26-28, 2011. 
45

U.S. Environmental Protection Agency (USEPA). 2012. FIFRA Scientific Advisory Panel: A Set 

of Scientific Issues Being Considered by the Environmental Protection Agency Regarding: 

Problem Formulation for Reassessment of Ecological Risks from the Use of Atrazine. June 12 - 

14, 2012. 

U.S. Environmental Protection Agency (USEPA). 2007. ECOTOXicology Database. Office of 

Research and Development National Health and Environmental Effects Research Laboratory’s 

(NHEERL’s) Mid-Continent Ecology Division (MED). http://cfpub.epa.gov/ecotox/. 

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SCREENING PROGRAM Weight-of-Evidence: Evaluating Results of EDSP Tier 1 Screening to 

Identify the Need for Tier 2 Testing. Office of Chemical Safety and Pollution Prevention. 

Washington DC September 14, 2011. http://www.regulations.gov/#!documentDetail;D=EPAHQ-OPPT-2010-0877-0021

Walker, E., A.V. Hernandez, M.W. Kattan. 2008. Meta-analysis: its strengths and limitations. 

Cleveland Clinic J. Med. 75(6):431-439. 

 
46

APPENDIX S-1:

The following materials identify the location of each AEEMP monitoring site and provide the maximum

60‐day rolling average atrazine concentration for each site‐year.  

Figure S-1: Location of AEEMP monitoring sites. 
47

Table S‐1: Summary of AEEMP site‐year monitoring results organized

alphabetically by state. The orange column represents the

concentration to be compared to the CE‐LOC for each site‐year, and

exceeding site‐years have been indicated in the columns to the right.

Sites shaded green identify watersheds with primarily sugarcane, all

other sites are corn/sorghum watersheds. Some site‐years have been

broken out into Auto and Grab categories, this is based on the data

that was provided by the registrants and are considered as two

different sampling techniques and thus as separate values for that

site‐year. Note that many sites were only sampled two years and

were decommissioned, and some sites are nested within the same

watershed as others. Additionally, site MO‐01 was moved 200 feet

upstream in 2008 due to bridge work, the site was reported as MO‐

01N for 2008 and 2009, then was returned to the original location in

2010.

Site ID Year

Max 60‐day

Avg Value

(ppb)

Max Value

(ppb)

Exceeds 2009

CELOC (10

ppb)

FLORIDA

FL‐1A 2006 1.1 3.7   

FL‐1A 2007 0.8 2.9   

FL‐1A 2008 1.3 40.5   

FL‐1A 2009 1.4 10.7   

FL‐1B 2006 0.9 3.1   

FL‐1B 2007 1.0 2.5   

FL‐1B 2008 1.3 5.4   

FL‐1B 2009 1.0 1.5   

IOWA

IA‐01 2004 1.2 10.0   

IA‐01 2005 0.3 1.2   

IA‐02 2004 0.6 1.8   

IA‐02 2005 0.8 5.5   

IA‐03 2010 10.5 50.6 Exceeds

IA‐03 2011 4.9 39.8   

IA‐03 2012 2.0 17.8   

IA‐04 2010 10.4 73.4 Exceeds

IA‐04 2011 4.3 36.0   

IA‐04 2012 10.9 78.4 Exceeds

IA‐05 2010 11.3 74.2 Exceeds

IA‐05 2011 12.8 169.0 Exceeds

IA‐05 2012 7.0 33.5   

ILLINOIS

IL‐01 2004 2.5 13.2   
48

IL‐01 2005 0.2 0.6   

IL‐02 2004 1.5 4.9   

IL‐02 2005 0.7 2.9   

IL‐03 2005 0.6 5.6   

IL‐03 2006 0.3 2.5   

IL‐03 2007 0.5 1.4   

IL‐04 2005 0.5 2.8   

IL‐04 2006 1.7 11.5   

IL‐04 2007 1.0 6.8   

IL‐05 2004 2.0 22.1   

IL‐05 2005 0.3 1.8   

IL‐06 2004 0.5 2.2   

IL‐06 2005 0.2 0.2   

IL‐07 2004 2.4 21.8   

IL‐07 2005 0.5 2.3   

IL‐08 2005 1.8 5.6   

IL‐08 2006 4.4 33.1   

IL‐08Auto 2007 4.5 39.5   

IL‐08Grab 2007 6.6 42.8   

IL‐09 2004 4.6 13.3   

IL‐09 2005 2.3 16.0   

IL‐10 2010 0.4 5.0   

IL‐10 2011 1.4 11.5   

IL‐10 2012 0.7 5.4   

IL‐11Auto 2009 3.5 21.1   

IL‐11Grab 2009 3.5 19.5   

IL‐11 2010 1.1 5.5   

IL‐11 2011 1.8 26.1   

IL‐12 2010 6.9 29.1   

IL‐12 2011 4.6 58.9   

IL‐12 2012 5.6 60.7   

IL‐13 2010 0.7 4.4   

IL‐13 2011 1.4 8.7   

IL‐14 2010 5.2 34.2   

IL‐14 2011 4.9 44.2   

IL‐14 2012 3.4 36.3   

IL‐15 2010 6.8 63.7   

IL‐15 2011 6.8 50.2   

IL‐15 2012 7.0 71.9   

IL‐16 2010 7.5 36.7   

IL‐16 2011 2.6 14.7   

IL‐16 2012 9.5 73.7 Exceeds
49

IL‐17 2010 5.7 36.7   

IL‐17 2011 17.2 228.2 Exceeds

IL‐17 2012 6.3 39.4   

INDIANA

IN‐01 2004 2.4 8.6   

IN‐01 2005 0.7 4.4   

IN‐02 2004 2.8 9.3   

IN‐02 2005 3.0 20.3   

IN‐03 2005 2.3 7.6   

IN‐03 2006 3.9 16.9   

IN‐04 2004 6.3 78.1   

IN‐04 2005 1.4 8.8   

IN‐04 2006 2.2 10.2   

IN‐05 2004 7.0 28.9   

IN‐05 2005 4.1 17.3   

IN‐05 2006 7.5 41.3   

IN‐06Auto 2005 4.0 7.0   

IN‐06Grab 2005 1.0 7.2   

IN‐06Auto 2006 4.4 24.3   

IN‐06Grab 2006 1.9 9.4   

IN‐06Auto 2007 1.1 12.1   

IN‐06Grab 2007 0.5 4.1   

IN‐07 2005 3.9 22.6   

IN‐07 2006 2.0 10.5   

IN‐08 2005 2.8 21.1   

IN‐08 2006 4.4 20.7   

IN‐09Auto 2005 7.6 34.5   

IN‐09Grab 2005 1.7 9.4   

IN‐09Auto 2006 2.9 13.8   

IN‐09Grab 2006 1.2 8.3   

IN‐10 2005 2.8 12.4   

IN‐10 2006 3.6 16.4   

IN‐11A 2007 0.4 1.4   

IN‐11AAuto 2008 1.8 15.1   

IN‐11AGrab 2008 1.7 6.7   

IN‐11Auto 2005 19.6 237.5 Exceeds

IN‐11Grab 2005 16.2 208.8 Exceeds

IN‐11Auto 2006 5.2 15.9   

IN‐11Grab 2006 1.9 9.8   

IN‐11Auto 2007 0.5 3.0   

IN‐11Grab 2007 0.4 1.2   

IN‐11Auto 2008 2.0 27.1   
50

IN‐11GRAB 2008 1.5 3.7   

IN‐12 2010 4.5 32.3   

IN‐12 2011 4.2 34.8   

IN‐12 2012 1.5 10.7   

KANSAS

KS‐01 2010 5.4 35.9   

KS‐01 2011 1.5 10.1   

KS‐01 2012 2.6 19.3   

KS‐02 2010 8.9 58.9   

KS‐02 2011 3.5 24.1   

KS‐02 2012 1.6 10.6   

KS‐03 2010 11.6 68.9 Exceeds

KS‐03 2011 5.9 32.1   

KS‐03 2012 4.4 24.7   

LOUISIANNA

LA‐01 2005 7.6 79.7   

LA‐01 2006 2.3 24.0   

LA‐01 2007 12.7 44.9 Exceeds

LA‐01 2008 8.1 80.8   

LA‐01 2009 10.0 97.3 Exceeds

LA‐01 2010 9.5 44.7 Exceeds

LA‐01 2011 5.3 20.7   

LA‐01 2012 2.2 11.8   

LA‐02 2005 1.9 12.8   

LA‐02 2006 1.1 3.6   

LA‐02 2007 2.4 10.9   

LA‐02 2008 2.2 15.7   

LA‐02 2009 1.5 4.1   

LA‐03 2005 14.3 83.1 Exceeds

LA‐03 2006 3.7 18.6   

LA‐03 2007 3.0 13.5   

LA‐03 2008 6.3 49.0   

LA‐03 2009 2.1 23.2   

LA‐03 2010 0.6 3.4   

LA‐03 2011 0.8 2.2   

LA‐03 2012 0.6 3.1   

LA‐04 2010 6.3 32.9   

LA‐04 2011 27.4 167.4 Exceeds

LA‐04 2012 11.5 59.0 Exceeds

LA‐05 2010 3.3 8.0   

LA‐05 2011 4.2 16.7   

MINNESOTA
51

MN‐01‐Auto 2005 2.2 15.0   

MN‐01‐Grab 2005 0.8 5.9   

MN‐01 2006 0.2 0.2   

MISSOURI

MO‐01 2004 19.4 65.9 Exceeds

MO‐01 2005 25.7 182.8 Exceeds

MO‐01 2006 17.5 82.8 Exceeds

MO‐01Auto 2007 10.7 91.6 Exceeds

MO‐01Grab 2007 7.3 33.3   

MO‐01NAuto 2008 7.3 78.2   

MO‐01nGrab 2008 6.1 62.2   

MO‐01nAuto 2009 10.9 72.0 Exceeds

MO‐01nGrab 2009 11.5 73.0 Exceeds

MO‐01 2010 5.1 25.2   

MO‐01 2011 4.5 18.8   

MO‐01 2012 1.4 13.6   

MO‐01C 2010 9.7 139.4 Exceeds

MO‐01C 2011 5.8 29.9   

MO‐01D 2010 4.8 33.6   

MO‐01D 2011 6.1 27.5   

MO‐02 2004 16.8 53.8 Exceeds

MO‐02 2005 11.5 28.1 Exceeds

MO‐02 2006 15.4 43.2 Exceeds

MO‐02Auto 2007 3.3 13.8   

MO‐02Grab 2007 3.5 16.2   

MO‐02Auto 2008 5.2 36.4   

MO‐02Grab 2008 12.6 56.6 Exceeds

MO‐02Auto 2009 14.6 155.2 Exceeds

MO‐02Grab 2009 26.5 108.9 Exceeds

MO‐02 2010 8.4 31.0   

MO‐02 2011 6.6 40.7   

MO‐02 2012 1.8 8.7   

MO‐03 2004 8.4 59.0   

MO‐03 2005 5.5 12.3   

MO‐03Auto 2006 2.8 20.3   

MO‐03Grab 2006 1.5 3.9   

MO‐04Auto 2007 3.9 53.4   

MO‐04Grab 2007 7.8 65.7   

MO‐04AAuto 2008 11.4 144.7 Exceeds

MO‐04AGrab 2008 7.7 33.2   

MO‐04aAuto 2009 6.0 52.1   

MO‐04aGrab 2009 10.0 83.1 Exceeds
52

MO‐04A 2010 8.7 41.3   

MO‐04A 2011 11.5 88.9 Exceeds

MO‐04A 2012 7.5 48.8   

MO‐04BAuto 2007 3.9 22.8   

MO‐04BGrab 2007 6.1 43.0   

MO‐04BAuto 2008 3.2 33.6   

MO‐04BGrab 2008 6.0 31.0   

MO‐04bAuto 2009 5.3 23.9   

MO‐04bGrab 2009 7.4 22.7   

MO‐05Auto 2007 3.0 15.5   

MO‐05Grab 2007 5.7 21.1   

MO‐05Auto 2008 4.2 37.8   

MO‐05Grab 2008 9.8 34.7 Exceeds

MO‐05Auto 2009 8.5 42.6   

MO‐05Grab 2009 11.2 31.5 Exceeds

MO‐05 2010 12.9 84.2 Exceeds

MO‐05 2011 6.2 70.5   

MO‐05 2012 4.0 14.0   

MO‐05BAuto 2008 5.7 36.2   

MO‐05BGrab 2008 9.5 34.0 Exceeds

MO‐05BAuto 2009 14.0 67.6 Exceeds

MO‐05BGrab 2009 18.7 112.5 Exceeds

MO‐05B 2010 12.3 38.3 Exceeds

MO‐05B 2011 8.3 21.6   

MO‐05B 2012 5.6 26.0   

MO‐06 2010 6.3 44.6   

MO‐06 2011 6.9 102.4   

MO‐06 2012 3.7 48.0   

MO‐07 2010 20.2 92.5 Exceeds

MO‐07 2011 14.6 90.9 Exceeds

MO‐07N 2012 11.9 41.1 Exceeds

MO‐08 2010 14.5 69.7 Exceeds

MO‐08 2011 14.1 68.2 Exceeds

MO‐08 2012 11.2 66.3 Exceeds

NEBRASKA

NE‐01 2004 4.3 19.3   

NE‐01 2005 3.6 16.7   

NE‐02 2005 6.3 20.7   

NE‐02 2006 7.3 82.0   

NE‐03 2004 0.7 2.3   

NE‐03 2005 1.2 11.9   

NE‐04 2005 33.4 49.9 Exceeds
53

NE‐04Auto 2006 49.3 125.0 Exceeds

NE‐04Grab 2006 1.7 4.1   

NE‐04Auto 2008 20.8 147.7 Exceeds

NE‐04Grab 2008 18.5 69.0 Exceeds

NE‐04Auto 2009 4.8 38.2   

NE‐04Grab 2009 6.2 20.3   

NE‐04 2010 34.7 189.3 Exceeds

NE‐04 2011 3.4 13.0   

NE‐04 2012 2.4 8.4   

NE‐04UAuto 2008 18.8 116.0 Exceeds

NE‐04UGrab 2008 13.8 58.8 Exceeds

NE‐05 2005 16.5 49.9 Exceeds

NE‐05 2006 5.1 6.8   

NE‐05Auto 2008 6.1 58.6   

NE‐05Grab 2008 10.1 67.8 Exceeds

NE‐05Auto 2009 8.6 55.1   

NE‐05Grab 2009 10.2 31.8 Exceeds

NE‐05 2010 8.1 80.2   

NE‐05 2011 2.3 58.7   

NE‐05 2012 1.0 9.1   

NE‐06 2004 1.7 7.7   

NE‐06 2005 6.0 33.1   

NE‐06 2006 0.2 0.1   

NE‐07Auto 2008 2.7 13.8   

NE‐07Grab 2008 9.0 82.8   

NE‐07Auto 2009 3.1 19.7   

NE‐07Grab 2009 3.9 21.2   

NE‐07UAuto 2008 4.3 32.9   

NE‐07UGrab 2008 3.5 15.2   

NE‐08BAuto 2008 3.0 26.5   

NE‐08BGrab 2008 10.2 50.0 Exceeds

NE‐08BAuto 2009 6.2 38.8   

NE‐08BGrab 2009 0.8 4.0   

NE‐09 2010 6.2 35.9   

NE‐09 2011 1.2 4.8   

NE‐09 2012 4.9 17.2   

OHIO

OH‐01 2004 3.2 18.3   

OH‐01 2005 0.6 3.0   

OH‐02 2005 2.9 18.1   

OH‐02 2006 2.9 14.0   

OH‐02Auto 2007 1.2 9.6   
54

OH‐02Grab 2007 1.5 9.9   

OH‐03Auto 2004 1.4 7.4   

OH‐03Grab 2004 4.5 21.5   

OH‐03Auto 2005 5.6 18.8   

OH‐03Grab 2005 0.9 8.2   

OH‐04 2005 2.7 20.2   

OH‐04 2006 1.0 6.3   

OH‐05 2010 2.0 11.0   

OH‐05 2011 1.4 30.6   

OH‐05 2012 1.9 14.8   

OH‐06 2010 3.8 23.3   

OH‐06 2011 5.9 47.2   

OH‐06 2012 5.2 51.2   

TENNESSEE

TN‐01 2005 2.9 7.6   

TN‐01 2006 2.0 10.7   

TEXAS

TX‐01 2010 13.5 105.2 Exceeds

TX‐01 2011 3.0 6.4   

TX‐01 2012 15.6 133.9 Exceeds

TX‐02 2010 3.7 6.4   

TX‐02 2011 0.2 0.1   

TX‐02 2012 3.3 9.9   
MEETING OF THE FIFRA

SCIENTIFIC ADVISORY PANEL

ON THE

PROBLEM FORMULATION FOR THE ENVIRONMENTAL 

FATE AND ECOLOGICAL RISK ASSESSMENT FOR ATRAZINE

JUNE 12-15, 2012
2

Preamble 

 

This document is a preliminary problem formulation for atrazine to fulfill Registration Review 

requirements under FIFRA. In a problem formulation, available information, including stressor 

sources and characteristics, exposure, ecological effects on plants and animals (e.g., 

amphibians, fish, invertebrates, birds, and mammals), and characteristics of the ecosystem(s), is 

used to identify missing information and assessment endpoints and to develop a preliminary 

assessment of the problem. 

The document consists of two main sections. In the first section is background material on the 

regulatory history, use and usage, ecotoxicity data, environmental fate data, and environmental 

monitoring data for atrazine (Chapter I). These data serve as the foundational data for the risk 

assessment. This section also contains a critical review of published atrazine testing with 

amphibians (Chapter II).

The second section includes the analysis plan (Chapter III) for the risk assessment. This section 

also provides a detailed plan on the methods used to assess risk in light of information on 

use/usage, ecotoxicity data, and environmental fate data. A key aspect of this section is 

identifying and addressing uncertainties in the risk assessment. The topics are: 

 Chapter IV – The methodology for determining the level of concern for atrazine 

 Chapter V - A strategy for using the PATI-derived CE-LOC for identification of vulnerable 

watersheds 

Charge questions to the FIFRA SAP can be found in the relevant sections of Chapters I, II, IV, 

and V.
3

Table of Contents

CHAPTER I. ATRAZINE BACKGROUND, HISTORY, AND ECOTOXICOLOGICAL DATA .................... 6

1. Purpose ............................................................................................................................... 6

2. Regulatory Actions and History ......................................................................................... 6

2.1. Nature of Regulatory Action .........................................................................................6

2.2. Regulatory History, Mitigation of Ecological Risk, and Scientific Advisory Panel 

Reviews ..........................................................................................................................7

2.3. Endangered Species Assessments ..............................................................................13

3. Stressor Source and Distribution ..................................................................................... 13

3.1. Herbicidal Mechanism of Action.................................................................................13

3.2. Overview of Pesticide Use and Usage ........................................................................13

3.2.1. Agricultural Use Sites...............................................................................................14

3.2.2. Non-Agricultural Use Sites.......................................................................................15

3.2.3. Agricultural Usage Data ...........................................................................................15

4. Environmental Fate and Transport .................................................................................. 20

4.1. Physical and Chemical Properties ...............................................................................20

4.1.1. Environmental Fate Summary .................................................................................20

4.1.2. Degradation Products ..............................................................................................21

4.2. Surface Water Monitoring ..........................................................................................24

4.2.1. Monitoring Data Analysis ........................................................................................25

4.2.2. Ambient Surface Water Monitoring Programs .......................................................26

4.2.3. Finished Surface Source Drinking Water Monitoring Programs .............................28

4.2.4. Ground Water Monitoring Programs ......................................................................28

4.3. Atmospheric Monitoring .............................................................................................29

5. Stressors of Concern ......................................................................................................... 29

6. Evaluation of Atrazine Toxicity to Specific Taxa ....................................................................30

6.1. Toxicity to Plants .........................................................................................................31

6.1.1. Toxicity to Terrestrial Plants ....................................................................................31

6.1.2. Toxicity to Aquatic Non-Vascular Plants .................................................................34

6.1.3. Toxicity to Aquatic Vascular Plants .........................................................................42

6.1.4. Toxicity to Aquatic Plant Communities ...................................................................42

6.1.5. Biological Relevance: The Importance of Biodiversity and Plant Communities .....46

6.2. Effects to Animals ........................................................................................................50

6.2.1. Toxicity to Terrestrial Animals .................................................................................50

6.2.2. Effects to Aquatic Animals .......................................................................................53

CHAPTER II. THE EVALUATION OF AMPHIBIAN TOXICITY DATA ................................................ 60

7. Toxicity Data to Amphibians (aquatic-phase and terrestrial) ........................................ 62

7.1. History of Previous Amphibian SAPs ..........................................................................62

7.2. Test Design Elements ..................................................................................................62

7.3. Results of Evaluating Amphibian Test Design Elements ............................................67

7.4. Categorizing Amphibian Endpoints ............................................................................67
4

7.5. Evaluation of Overall Test Design Elements ...............................................................83

7.6. Other Evaluations – Published Literature Reviews ....................................................84

7.7. Evalution of Amphibian Studies and Adverse Outcome Pathways ...........................86

CHAPTER III. ANALYSIS PLAN ....................................................................................................... 87

8. Conceptual Model ............................................................................................................ 87

8.1. Risk Hypothesis ...........................................................................................................87

8.2. Conceptual Diagram ....................................................................................................88

9. Measures of Exposure .............................................................................................................91

10. Measures of Effect ..................................................................................................................93

11. Integration of Exposure and Effects .......................................................................................93

Chapter IV. METHODOLOGY FOR DETERMINING THE LEVELS OF CONCERN FOR ATRAZINE.....95

12. The Risk Quotient Method and Levels of Concern for Terrestrial Plants and Terrestrial 

and Aquatic Animals. ..................................................................................................95

13. The Method for Determining the Level of Concern for Aquatic Plant Communities ...........97

14. History of the Aquatic Plant Community LOC Methodology and the Effects on the LOC 

from Implementation of Suggestions by Scientific Advisory Panels. ........................... 111

14.1. A Synopsis of the Changes Incorporated into the Current Aquatic Plant 

Community LOC Methodology. ................................................................................111

14.2. Modifications to the Method for Determining the LOC for Aquatic Plant 

Communities (Based on the Suggestions from the 2009 SAP). ...............................112

14.3. Analyses of Driving Factors Affecting the CE-LOC ....................................................114

14.4. Uncertainty in the Calculation of the LOCPATI and CE-LOC .......................................118

CHAPTER V. METHOD FOR DETERMINING THE VULNERABLE WATERSHEDS .......................... 120

15. Identifying Watersheds without Available Monitoring Data. .............................................120

15.1. Identifying Watershed Criteria for Sites that Exceed the Aquatic Community 

LOC for Atrazine ........................................................................................................120

15.2. Factors Contributing to Watershed Vulnerability ....................................................120

15.3. Evaluating the Watershed Vulnerability Criteria .....................................................127

15.4. Further Evaluations of Watershed Criteria: The Cornbelt Watershed 

Regression for Pesticide (WARP) Model ..................................................................130

16. Method for Comparing Monitoring Data to the Aquatic Plant Community CE-LOC... 132

16.1. The Development of Bias Factors.............................................................................133

16.2. Translating Monitoring Data with the Bias Factor...................................................142

16.3. Results of Preliminary Review of Available National Monitoring Data..................143

16.4. Scope of National Aquatic Plant Communities Potentially Threatened by 

Atrazine Exposure. ....................................................................................................145

LITERATURE CITED ...................................................................................................................... 151
5

APPENDICES: 

A. SUPPORTING ENVIRONMENTAL FATE DATA 

B. SUPPORTING ECOLOGICAL TOXICITY DATA

C. OPEN LITERATURE REVIEW OF AMPHIBIAN DATA 

D. BIBLIOGRAPHY OF MICROCOSM AND MESOCOSM STUDIES AND CRITERIA USED TO SCREEN STUDIES FOR 

ANALYSIS OF ATRAZINE RISKS TO AQUATIC PLANT COMMUNITIES

E. PROPOSED METHODOLOGY FOR SPECIFYING ATRAZINE LEVELS OF CONCERN FOR PROTECTION OF PLANT 

COMMUNITIES IN FRESHWATER ECOSYSTEMS 

F. CRITIQUE OF SYNGENTA CORPORATION'S PROBABILISTIC IMPLEMENTATION OF CASMATZ FOR 

ECOLOGICAL RISK ASSESSMENT OF ATRAZINE 

G. ELECTRONIC FILES: 

a. THE PATI MODEL WORKING PROGRAM

b. MICROCOSM AND MESOCOSM AND ATRAZINE ECOLOGICAL EXPOSURE MONITORING PROGRAM 

INPUT FILES

c. PATI OUTPUT AND CE-LOC CALCULATION

d. MONITORING DATA PROCESSING MACRO FILE 

e. SUMMARY OF MONITORING DATA, INCLUDING LISTING OF WATER MONITORING SITES THAT 

EXCEED THE AQUATIC PLANT COMMUNITY LEVEL OF CONCERN 

f. BREAKDOWN OF SPECIES TESTED IN ECOTOXICITY STUDIES

g. LOG LINEAR 95% C.I. BIAS FACTOR SENSITIVITY ANALYSIS USING AEEMP MONITORING DATA

h. NAWQA MAP DATA: 60-DAY MAXIMUM AVERAGE 7 PPB EXCEEDERS

i. NAWQA MAP DATA: BIAS FACTOR ADJUSTED 4 PPB EXCEEDERS

j. NAWQA MAP DATA: BIAS FACTOR ADJUSTED 7 PPB EXCEEDERS

k. NAWQA MAP DATA: 60-DAY MAXIMUM AVERAGE 4 PPB EXCEEDERS

H. BIBLIOGRAPHY OF ECOTOX ACCEPTED PAPERS (2003-2011) 

I. BIBLIOGRAPHY OF ECOTOX REJECTED PAPERS (2003-2011) 

J. BIBLIOGRAPHY OF ECOTOX EXCLUDED PAPERS (2003-2011) 

K. BIAS FACTOR CALCULATIONS REGRESSION EQUATIONS

L. DEGRADATION PRODUCT STRUCTURES

M. REANALYSIS OF TOXICITY DATA FOR CONSTRUCTING PATI 

N. EVALUATION GUIDELINES FOR ECOLOGICAL TOXICITY DATA IN THE OPEN LITERATURE
6

CHAPTER I. ATRAZINE BACKGROUND, HISTORY, AND ECOTOXICOLOGICAL DATA 

1. Purpose 

Atrazine is currently registered as an herbicide in the U.S. to control annual broadleaf and grass 

weeds primarily in corn, sorghum, and sugarcane. In addition to food crops, atrazine is also 

used on a variety of non-food crops, forests, residential, commercial, and industrial lawn uses, 

golf course turf, recreational areas, and rights-of-way. It is one of the most widely used 

herbicides in North America (USEPA, 2003a). 

The purpose of this white paper (a problem formulation) is to provide an understanding of what 

is currently known about the environmental fate and ecological effects of atrazine, in 

relationship to its registered uses. An understanding of the environmental fate and ecological 

effects of atrazine will inform the risk assessment, which will be conducted for atrazine under 

EPA’s registration review program, and subsequently published for public comment. The 

atrazine risk assessment is scheduled for completion in 2017. 

This white paper will describe EPA’s plan for analyzing data relevant to atrazine and its 

degradates and for conducting the environmental fate and ecological risk assessment for 

atrazine’s registered uses. This document also contains charge questions to the Scientific 

Advisory Panel (SAP), and supporting reference materials.

2. Regulatory Actions and History 

2.1. Nature of Regulatory Action 

Under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), all pesticides intended 

for use in the United States must be registered (licensed) by the Environmental Protection 

Agency (EPA) before they can be sold or distributed in commerce. EPA will register a pesticide if 

scientific data provided by the registrant show that, when used according to label directions, it 

will not cause unreasonable adverse effects on human heath or the environment. In 1996, 

when FIFRA was amended by the Food Quality Protection Act, EPA was mandated to implement 

a program for the periodic review of pesticides (registration review) 

(http://www.epa.gov/oppsrrd1/registration_review/). The registration review program is 

intended to ensure that, as the ability to assess risk evolves and as policies and practices 

change, all registered pesticides continue to meet contemporary standards of health, safety, 

and product labeling and that their risks are adequately mitigated. 

As part of the implementation of the registration review program pursuant to Section 3(g) of 

the FIFRA, the EPA is intitiating its evaluation of atrazine to determine whether it continues to 
7

meet the statutory standard for no unreasonable adverse effects to human health and the 

environment based on current uses. 

2.2. Regulatory History, Mitigation of Ecological Risk, and Scientific Advisory Panel Reviews 

Atrazine was first registered by the United States Department of Agriculture (USDA) in 1958 as 

a broad spectrum residual herbicide. Atrazine is used both at plant and post-plant, and is 

primarily used in corn, sweet corn, sorghum, and sugarcane production. Additional uses include 

soybeans, wheat (stubble only), oats, macadamia nuts, guava, range grasses, conifer forests, 

Christmas tree farms, sod farms, ornamental grasses, ornamental plants, ornamental turf, 

residential lawns, schools, parks, playgrounds, athletic fields, roadsides, rights-of-ways, 

airfields, vacant lots, roadsides, lumber yards, agricultural buildings, industrial sites and storage 

sites.

EPA’s regulation of atrazine over the past three decades has focused on human and 

environmental exposures through water, the most significant exposures associated with 

atrazine’s agricultural and residential lawn uses. On November 10, 1983, EPA issued a 

Registration Standard for atrazine, which noted the EPA’s concerns regarding ground and 

surface water contamination (USEPA, 2003a). 

In the early 1990s, the registrant voluntarily instituted several risk reduction measures to 

address concerns raised about ground and surface water contamination by atrazine. In 1990, 

the following measures were undertaken to address groundwater exposures: 

 Reduction of the application rate for corn and sorghum to 3.0 pounds of active 

ingredient (lbs a.i.)/acre from 4.0 lbs a.i./acre. 

 Reduction of the maximum rate for non-cropland and total vegetation control to 10 lbs 

a.i./acre from 40 lbs a.i./acre. 

 Requirement that post-emergence applications to corn and sorghum be made before 

the corn and sorghum plants reach 12 inches in height. 

 Deletion of rangeland, proso millet, and pineapple uses. 

 Prohibition of chemigation (applying atrazine through irrigation systems). 

 Institution of a well-head protection plan requiring 50-foot setbacks around all wells for 

mixing, loading, or applying atrazine-containing products. 

 Institution of construction requirements for bulk storage facilities to prevent point 

source contamination from spills 

 Classification of all atrazine-containing products (except for the lawn care, turf, and 

conifer uses) as Restricted Use Pesticides (RUPs). 

In 1992, registrants undertook the following additional measures to address concerns about 

atrazine exposure in surface water: 

 Further reduction of the total seasonal application rates for corn and sorghum to 2.5 lbs 

a.i./acre per year. This rate includes a 1.5 lbs a.i./acre per year pre-emergence use and a 

1.0 lbs a.i./acre per year post-emergence use. 
8

 Deletion of all uses for total vegetation control in non-cropland. 

 Expansion of restricted use criteria. Expansion of the setback requirements, included 

following a 50-foot setback around surface water sources when workers are mixing and 

loading atrazine-containing products; a 66-foot application (ground and aerial) setback 

from points of entry where field surface water runoff enters surface water sources; and, 

a 200-foot application setback around lakes and reservoirs. 

In November 1994, EPA initiated a Special Review for the triazine pesticides (atrazine, simazine 

and cyanazine; USEPA, 1994) that focused on minimizing human exposure to atrazine from 

ground water and surface water. 

Further labeled use restrictions in 1996 reduced environmental exposure from tile-terraced 

fields containing standpipes, as follows: 

 Restrictions against application within 66 feet of standpipes. 

 Requirement that applications be incorporated to a depth of 2 to 3 inches. 

 Restrictions against application to no-till fields unless practicing high crop residue 

management. 

In January 2003, the EPA concluded its ecological risk assessment as part of the Interim 

Registration Eligibility Decision (IRED) for atrazine (USEPA, 2003a). This assessment was based 

on laboratory ecotoxicological data as well as microcosm and mesocosm (cosm) field studies 

found in publicly available literature, a substantial amount of monitoring data for freshwater 

streams, lakes, reservoirs, and estuarine areas, and incident reports of adverse effects on 

aquatic and terrestrial organisms associated with the use of atrazine. 

Based on this assessment, the January 2003 IRED concluded that atrazine concentrations in 

watersheds may cause significant changes in aquatic plant community structure and 

productivity; EPA considered this endpoint to be the most sensitive effect of concern. The IRED 

also established a framework for developing an aquatic ecosystem level of concern (LOC) to 

ensure that atrazine concentrations in watersheds will not cause these changes. By focusing on 

aquatic plant community structural and productivity changes, EPA intended to protect 

invertebrates, fish, and amphibians from the direct effects of atrazine as well as the effects that 

atrazine could have on the habitat and food sources of aquatic animals. The January 2003 IRED 

also established the need for additional data to (1) identify and evaluate water bodies in corn, 

sorghum, and sugarcane use areas where such changes in aquatic plant community structure 

and productivity were more likely to occur; and to (2) determine potential amphibian gonadal 

developmental responses to atrazine. 

To mitigate potential ecological risks to aquatic communities identified in the IRED, the EPA 

required atrazine registrants, in consultation with EPA, to develop a program under which the 

registrants monitor for atrazine concentrations and mitigate environmental exposures if EPA 

determines that mitigation is necessary. The program was intended to focus on impacts of 
9

atrazine use at the watershed level in accordance with existing state and federal water quality 

programs. This monitoring and mitigation program was also agreed upon in a 2003 

Memorandum of Agreement (MOA) between EPA and the atrazine registrants (USEPA, 2003b).

On October 31, 2003, EPA issued an addendum that updated the January 31, 2003 IRED (USEPA, 

2003c). This addendum described new scientific developments pertaining to monitoring of 

watersheds and potential effects of atrazine on endocrine-mediated pathways of amphibian 

gonadal development. As discussed in the October 2003 IRED, the EPA conducted an evaluation 

of the submitted studies regarding the potential effects of atrazine on amphibian gonadal 

development and presented its assessment in the form of a white paper for external peer 

review to a FIFRA Scientific Advisory Panel (SAP) in June 2003. In the white paper dated May 29, 

2003, the EPA summarized seventeen studies consisting of both open literature and registrantsubmitted laboratory and field studies involving both native and non-native species of frogs 

(USEPA, 2003d). The EPA concluded that none of the studies fully accounted for environmental 

and animal husbandry factors capable of influencing endpoints that the studies were 

attempting to measure. The EPA also concluded that the current lines-of-evidence did not show 

that atrazine produced consistent effects across a range of exposure concentrations and 

amphibian species tested. 

Based on this assessment, the EPA concluded and the SAP concurred that there was sufficient 

evidence to formulate a hypothesis that atrazine exposure may impact gonadal development in 

amphibians, but there were insufficient data to confirm or refute the hypothesis (USEPA, 

2003d). Because of the inconsistency and lack of reproducibility across studies and uncertainty 

in the nature of any dose-response relationship in the currently available data, the EPA 

determined that the data did not alter the conclusions reached in the January 2003 IRED 

regarding uncertainties related to atrazine’s potential effects on amphibians. The SAP, 

however, supported EPA in seeking additional data to reduce uncertainties regarding potential 

effects to amphibians. Subsequent data collection occurred following a multi-tiered process 

outlined in the EPA’s white paper to the SAP (USEPA, 2003d). These data were submitted, and a 

second SAP was held in 2007 to discuss results of these studies (USEPA, 2007a). These data 

suggested, and the SAP agreed, that gonadal development of larval Xenopus laevis was not 

affected by atrazine concentrations tested from 0.1 to 100 μg/L. Based on these data, EPA 

concluded that atrazine, using Xenopus laevis as a surrogate, does not consistently affect 

amphibian gonadal development. EPA acknowledged, however, that there is uncertainty in 

using Xenopus laevis to represent all amphibians. 

Since the October 2007 SAP on the potential effects of atrazine on amphibians, several other 

SAP meetings on atrazine have been held: 

 December 4-7, 2007: Interpretation of the Ecological Significance of Atrazine StreamWater Concentrations Using a Statistically-Designed Monitoring Program. 

 May 12-15, 2009: The Ecological Significance of Atrazine Effects on Primary Producers in 

Surface Water Streams in the Corn and Sorghum Growing Region of the United States. 
10

 November 3, 2009: Presentation of the Approach to Reevaluate Atrazine. 

 February 2 - 4, 2010: Incorporation of Epidemiology and Human Incident Data into 

Human Risk Assessment. 

 April 26-29, 2010: Re-Evaluation of Human Health Effects of Atrazine: Review of 

Experimental Animal and In Vitro Studies and Drinking Water Monitoring Frequency. 

 September 14-17, 2010: Re-Evaluation of Human Health Effects of Atrazine: Review of 

Non-Cancer Effects and Drinking Water Monitoring Frequency 

 July 26-29, 2011: Re-Evaluation of Human Health Effects of Atrazine: Review of Cancer 

Epidemiology, Non-cancer Experimental Animal and In Vitro Studies and Drinking Water 

Monitoring Frequency. 

These SAP meetings are discussed in more detail in the following paragraphs. 

In December 2007, another SAP was convened to address the potential for community-level 

effects to aquatic plants in Midwestern streams. In this SAP meeting, EPA discussed the 

preliminary development of an ecological LOC methodology and presented an analysis of the 

monitoring program using that methodology (USEPA 2007b). The LOC development included a 

summary of the underlying approach to relate effects from time variable real world exposure to 

aquatic plant community effects found in the cosm studies using the Comprehensive Aquatic 

Systems Model (CASMATZ1). The SAP document included a preliminary sensitivity analysis of 

CASMATZ1, results of the ecological stream monitoring study conducted from 2004 to 2006, and 

identification of watersheds that exceeded the CASMATZ1-based LOC with associated population 

statistics. 

Using a stratified, random statistical survey design EPA identified forty watersheds representing 

high atrazine use locations vulnerable to atrazine runoff (USEPA 2003c). Monitoring was 

conducted in these watersheds from 2004 to 2006 and is still occurring in select watersheds. 

During the December 2007 SAP meeting, EPA proposed a GIS-based approach for extrapolating 

results from these 40 watersheds to all watersheds where atrazine is used (USEPA, 2007b). 

The SAP issued its evaluation and recommendations on March 5, 2008 (USEPA, 2007b). In their 

report, the SAP concurred with the conceptual approach of using a community simulationbased model to relate time variable exposures to community-level effects data represented by 

the cosm data. The SAP recommended that the CASMATZ1 model should be revised with respect 

to parameterization, process formulation and functionality to more accurately model second 

and third order Midwest stream characteristics and that a more comprehensive sensitivity 

analysis should be conducted (USEPA, 2007b). The SAP also recommended that EPA determine 

the extent to which atrazine levels in water bodies exceed the aquatic community-level LOCs, 

including interpretation of the monitoring results and identification of chemographs that 

exceed the LOC, and the identification of the location of other watersheds with characteristics 

similar to those that exceeded the LOC in the monitoring study. 
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In May 2009, EPA again convened an SAP meeting, presenting new evaluations of the 

applicability of the revised CASM Atrazine model (CASMATZ2) to freshwater atrazine risk 

assessments for first- and second-order freshwater streams and provided reasons in support of 

its decision not to proceed with further development and application of this model (USEPA, 

2009a). A simpler alternative to the CASM-based approach, the Plant Assemblage Toxicity Index 

(PATI), was presented for relating atrazine surface water exposures to cosm effects data. Other 

related topics presented to the SAP included a revised assessment of cosm exposure profiles, a 

review of the literature and subsequent analysis of single-species toxicity tests to develop 

statistical estimates of Effects Concentrations (ECs) and Specific Growth Rate (SGR) parameters 

for major taxonomic groups, an update on the monitoring program results, interpretation of 

the surface water monitoring results with both the revised CASMATZ2 and the alternate PATI 

model, identification of the primary watershed characteristics driving atrazine exposure and a 

preliminary extrapolation of the results to the entire atrazine use area to identify other areas 

where atrazine exposures may exceed the LOC. The EPA Office of Water also provided an 

example of statistical alternatives for expressing the model results to develop a numeric aquatic 

life criterion for atrazine that integrates both concentrations and exposure durations of 

atrazine. 

The Panel agreed with the EPA decision to move to the PATI model for a first tier national 

approach, but also recommended using a refined CASMATZ2, the Hazard Criterion (HC5 or HC10) 

and/or species sensitivity distributions to compare LOC estimates from each (USEPA, 2009). The 

Panel further suggested that a refined CASMATZ2 could be used to further investigate those 

watersheds that exceed the LOC; however this would require a significant effort to incorporate 

site specific parameterization. The Panel concluded that the description of the selection criteria 

and scoring of the effects (Brock Scores method) in the cosm studies was inadequate and 

needed to be refined. 

EPA also presented to the 2009 SAP its watershed analysis to identify specific characteristics 

that distinguish watersheds with waters that frequently exceed the aquatic community LOC for 

atrazine and to use those characteristics to identify other similarly vulnerable watersheds. 

EPA’s analysis identified the presence of soils with shallow, drainage-restrictive layers in areas 

with atrazine use as a characteristic that distinguished monitoring sites exceeding the aquatic 

community LOC in multiple years from those sites that did not exceed the LOC during the 

sampling period (USEPA, 2007b, 2009). The 2009 SAP recommended using an effects index or 

concentration metric, rather than categorical LOC thresholds (i.e., exceeded the LOC in multiple 

years vs. did not exceed during the study) in order to take advantage of data from all 40 

Atrazine Ecological Exposure Monitoring Program sites (AEEMP1

; USEPA, 2009). The Panel 

encouraged the development of a “Cornbelt Watershed Regression for Pesticide (WARP) 

Model” and recommended considering additional data related to application (planting dates, 

timing of atrazine application), weather (rainfall intensity and duration), soils and hydrology 

 

1

 Syngenta refers to this monitoring program as the Atrazine Ecological Monitoring Program (AEMP). 
12

(runoff propensity index, composite curve numbers, watershed geometry), and management 

(riparian buffers/setback areas, tillage, conservation practices, etc.). 

In November 2009, EPA initiated a re-evaluation of atrazine to consider new research that had 

been published, as well as several years of atrazine drinking water monitoring data, to ensure 

that EPA’s regulatory decisions for atrazine continue to protect public health. To that end, EPA 

convened four SAPs from 2010 to 2011 focusing on the potential effects of atrazine on human 

health. New hazard and dose-response data reviewed during this re-evaluation suggested that 

a shorter duration of exposure may be appropriate for the toxicological endpoint of concern. 

Given the potential for a shorter duration of concern, EPA considered whether weekly or 

biweekly water monitoring would adequately characterize shorter durations of atrazine 

exposure in drinking water. In the April and September 2010 FIFRA SAP consultations on 

atrazine, EPA reviewed methods for designing monitoring studies to capture exposures of 

concern and approaches for analyzing and interpreting existing monitoring data and 

characterizing the uncertainties in those estimates for use in human health risk assessments 

(USEPA, 2010a and 2010b). The SAP commented that the toxicological exposure time frame of 

interest will define the importance of peaks and determine the most useful approaches both 

for designing a monitoring study and for evaluating the utility of existing monitoring studies 

(USEPA, 2010a). However, the SAP noted that, in light of uncertainty over a critical exposure 

period, ranging from a few days to a few weeks, the best course of action may be attempting 

“to capture the pattern of atrazine concentrations in the source water of each CWS based on 

the characteristics of that particular water system, as opposed to a one-size-fits-all approach” 

(USEPA, 2010b). 

Identifying monitoring sites and determining the sampling frequency require careful 

consideration to avoid underestimating true atrazine concentrations (USEPA, 2010b). A 

predictive model can be used to target sites that merit the most detailed monitoring and target 

the time periods when atrazine is most likely to be present (USEPA, 2010a and 2010b). The 

Panel recommended that the USEPA give thought to “using the simulation models and CWS 

characterizations as part of the monitoring process. In particular, it is feasible that models will 

eventually be accurate enough to provide predictions of atrazine concentrations in source 

waters to a CWS for the coming crop season. Instead of requiring a CWS to collect and analyze 

water samples in their output stream (drinking water) at some predefined frequency (e.g., daily 

or weekly in the case of some sites), it should be possible to use the models to facilitate 

targeting sampling to periods of time most likely to experience an exceedance” (USEPA, 2010b). 

To estimate exposures from monitoring data sampled at intervals, particularly where peak 

concentrations over shorter durations are important, the USEPA needs methods that can 

predict values that may be greater than those sampled (USEPA, 2010a). The SAP recommended 

combining regression-based models, such as the United States Geological Survey’s (USGS) 

Watershed Regression on Pesticides (WARP), with either a deterministic model or with a 

statistical approach using kriging or random-function models (USEPA, 2010b). 
13

In the July 2011 SAP, the EPA conducted an evaluation of methods for characterizing the 

uncertainties resulting from the existing AMP monitoring study design (USEPA, 2011a). 

Methods for addressing temporal uncertainty with monitoring data includes bias factors, 

kriging, conditional simulation, and mass balance modeling. The Panel concluded that temporal 

uncertainty in monitoring data could be addressed using bias factor or hybrid Pesticide Root 

Zone Model (PRZM) modeling approaches (USEPA, 2011a). 

2.3. Endangered Species Assessments 

On August 1, 2003, EPA released an assessment of the potential effects of atrazine to 26 listed 

Evolutionarily Significant Units (ESUs) of Pacific salmon and steelhead. In addition, as part of the 

Natural Resources Defense Council settlement agreement and second settlement agreement 

with the Center for Biological Diversity and Save Our Springs Alliance, several assessments have 

recently been conducted on the potential for atrazine to affect a number of listed species. 

These effects determinations, which are available on the web at www.epa.gov/espp, review 

atrazine’s potential direct and indirect effects. 

3. Stressor Source and Distribution 

Atrazine is mobile and persistent in the environment. The main routes of dissipation are 

microbial degradation under aerobic conditions, runoff, and leaching. Because of its persistence 

and mobility, atrazine will move into surface and ground water. This is confirmed by the 

widespread detections of atrazine in surface water and ground water. 

3.1. Herbicidal Mechanism of Action 

Triazine herbicides such as atrazine bind with a protein complex of the Photosystem II in 

chloroplast photosynthetic membranes (Schulz et al., 1990). The result is an inhibition in the 

transfer of electrons that in turn inhibits the formation and release of oxygen. An evaluation of 

the mode of action for atrazine in mammals was presented in an April 2010 SAP- “Re-Evaluation 

of Human Health Effects of Atrazine: Review of Experimental Animals and In vitro Studies and 

Drinking Water Monitoring Frequency” (USEPA, 2010a). Proposed modes of action for 

reproduction were presented and if conserved across species, may be applicable to other 

animals. 

 

3.2. Overview of Pesticide Use and Usage 

Information on use sites, formulations, application methods, and application timing in this 

section of the document has been obtained from various EPA sources, including databases such 
14

as OPPIN and the Label Use Information System (LUIS), and confirmed through a review of label 

information (USEPA, 2012a). 

3.2.1. Agricultural Use Sites 

Atrazine is a triazine herbicide first registered by USDA in 1958. It is currently registered as a 

restricted use pesticide only to be applied by certified applicators. Atrazine is registered for use 

against broadleaf and some grassy weeds in corn, sweet corn, sorghum, soybeans, sugarcane, 

wheat, oats, macadamia nuts, guava, and range grasses. Because application in wheat is to 

wheat stubble on fallow land following wheat harvests when the land is not cultivated, wheat is 

not considered the target crop. Application to range grasses is for the establishment of 

permanent grass cover on rangelands and pastures under USDA's Conservation Reserve 

Program (CRP in OK, NE, TX, and OR) and range/pastureland. Most of the atrazine applied to 

corn and sorghum is applied preemergence. 

Formulations: 

Atrazine is available in many formulations, including granular, wettable powder, water 

dispersible granules, emulsifiable concentrate, flowable concentrate, soluble concentrate, 

ready-to-use solution, and water soluble packs. 

Application Methods: 

Atrazine may be applied by groundboom sprayer, aircraft, tractor-drawn spreader, rights-ofway sprayer, low pressure handwand, backpack sprayer, lawn handgun, push-type spreader 

and belly grinder (hand-crank spreader). 

Application Timing on Crops with the Highest Use: 

Corn: Applications to corn are most often preemergence (mid-April through mid-May in the 

major corn-growing areas). Postemergence applications are most likely to occur up to the end 

of

June, until corn reaches 12" in height. There is some variability in timing based on geographical 

regions. 

Sorghum: Applications to sorghum are most often preemergence (mid-May to mid-July in the 

major sorghum-growing areas). Postemergence applications are most likely to occur up to the 

end of August. There is some variability in timing based on geographical regions. 

Sugarcane: Applications to sugarcane are usually at planting (fall), in the spring after 

emergence, and an additional postemergence application (often at layby). Since ratoon crops 

may face heavier weed pressure, additional applications are more likely in sugarcane ratoon 

crops. 
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3.2.2. Non-Agricultural Use Sites 

Atrazine is registered for use in conifer forests, Christmas tree farms, sod farms, ornamental 

grasses, ornamental plants, ornamental turf, outdoor residential, lawns mostly confined to 

Florida and the Southeast, schools, parks, playgrounds, and athletic fields. Atrazine can also be 

used on roadsides, rights-of-ways, airfields, vacant lots, roadsides, lumber yards, agricultural 

buildings, industrial sites and storage sites. The amound of atrazine applied to non-agricultural 

sites is not known. 

3.2.3. Agricultural Usage Data

Based on private market survey data from 2000-2010, agricultural usage averaged 

approximately 72 million pounds of active ingredient for 71 million acres, annually. 

Figure 1 presents atrazine agricultural usage in pounds of atrazine applied between 2000 and 

2010.

Figure 1. Atrazine Agricultural Usage (lbs ai Applied 2000-2010). Source: Proprietary Data 

(2000-2010). 

Screening Level Usage Analysis Data (2003-2010) 

Table 1 provides the most recent Screening Level Usage Analysis (SLUA), which was prepared in 

November, 2011 (USEPA, 2011b). The SLUA provides available estimates of pesticide usage data 

for atrazine on agricultural crops in the United States. The reported usage data in the SLUA are 

obtained from various sources and are merged, averaged and rounded so that the presented 

information is not proprietary, or business confidential. 
16

SLUA data sources include USDA-NASS (United States Department of Agriculture's National 

Agricultural Statistics Service) (2003-2010) and Private Pesticide Market Research (2003-2010). 

These results reflect amalgamated data developed by the EPA and are releasable to the public. 

Limitations to the data include the following: 

• Additional registered uses for certain crops may exist but are not included because the 

available surveys do not report usage (e.g., small acreage crops). 

• Lack of reported usage data for the pesticide on a crop does not imply zero usage. 

• Usage data on a particular site may be noted in data sources, but not quantified. In 

these instances, the site would not be reported in the SLUA. 

• Non-agricultural use sites (e.g., turf, post-harvest, mosquito control, etc.) are not 

reported in the SLUA. 

Some sites show use even though they are not on the label. This usage could be due to various 

factors, including, but not limited to data collection or reporting errors, or application errors. 

Table 1. Screening-Level Estimates of Agricultural Uses of Atrazine (2003-2010) (USEPA, 

2011b) 

Typical Use Patterns (2006-2010) 

For the more recent timeframe of 2006-2010, usage averaged approximately 66 million pounds 

a.i. for 67 million acres. Atrazine is typically applied at a rate of 0.3-2.3 lbs a.i./A, depending on 

the crop as shown in Table 2. (Proprietary Data, 2006-2010). 

In addition to the average application rate data, a rate distribution was generated to calculate 

an upper bound rate for each crop. The upper bound rate in this analysis is defined as the rate 
17

at which 90% (or as close to 90% as possible) of the acres treated with atrazine were treated at, 

or below that rate, as shown in Table 2. 

Table 2. Typical Use Patterns for Atrazine Used on Selected Crops (2006-2010). 

Top Crops and States with Highest Use (2006-2010) 

For 2006-2010, the top crop in terms of average annual pounds of active ingredient applied was 

corn (88%), followed by sorghum (8%), and sugarcane (2%) and sweet corn and fallow (1 % 

each). Spring and winter wheat stubble accounted for less than one percent of total pounds a.i. 

used during this period. 

As shown in Figure 2, between 2006-2010, the states with the most agricultural usage in terms 

of pounds a.i. applied were Illinois (17%), Iowa (11%), Nebraska (10%), Indiana and Kansas (9% 

each), followed by Missouri, Ohio, Texas, and Kentucky with less than 6% each. The "other" 

category includes 29 other states with Minnesota, Michigan and Wisconsin having the most 

usage among those states. 
18

Figure 2. States with the Highest Use (Percent of Total Pounds A.I. Applied) 2006-2010. 

National Mapping Data 

Another measure of usage is the use intensity. In this analysis, the use intensity is expressed as 

the pounds a.i. applied per acre of farmland. This differs from the application rate, which is 

expressed as the pounds a.i. applied per treated acre. Figure 3 is a map of agricultural pesticide 

usage at the Crop Reporting District (CRD) level that spatially represents atrazine use intensity 

in the US. As shown, areas such as Florida and the corn producing states (colored in red) have 

the highest use intensity. 

CRDs are districts created by USDA NASS which include aggregations of counties (USDA, 2010). 

Pesticide usage is displayed as average pounds (for the years 2006-2010) per 1,000 acres of 

farmland in a CRD to normalize for the variation in farmland between CRDs. Farmland acreage 

was obtained from USDA (2007). 

Usage is based on private market surveys of pesticide use in agriculture (Proprietary Data, 

2006- 

2010). The survey data are limited to the states that represent the top 80-90 percent of acreage 

for the individual crops; therefore, use may be occurring in regions outside the scope of the 

survey. CRDs showing no usage of pesticides may be due to either the lack of pesticide use in 

the region or non-participation in the agricultural surveys. In addition, across the years, there 

may be variations in the specific crops included in the CRD survey. This may result in a lower 

annual average for the CRD. 
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Figure 3. Atrazine Usage by Crop Reporting District (2006-2010).

3.2.4. Non-Agricultural Usage 

Information on non-agricultural usage in this section of the document has been obtained from 

available private market survey data from Kline & Co. The information provided on atrazine use 

in this section is for select non-agricultural use sites and does not represent all non-agricultural 

usage since data were not available for all non-agricultural use sites. 

Non-agricultural usage data for professional applications to turf and ornamentals are available 

for 2002, 2004, and 2006 (Table 3). Over this time period, there was a notable increase in use 

by lawn care operators and on golf courses, institutional turf, and turf farms (Kline & Co., 2002, 

2004, 2006). 
20

Table 3. Atrazine Select Non-Agricultural Usage (Pounds A.I.) (2002, 2004, 2006).

4. Environmental Fate and Transport 

4.1. Physical and Chemical Properties 

Atrazine physical and chemical properties are shown in Table 4. 

Table 4. Physical and Chemical Properties of Atrazine 

Physical/Chemical Property Units Value

CAS Reg. Number NA 1912-24-9

Chemical Formula NA C8H14ClN5

Physical State NA Powder

Color NA White

Melting Point 0C 175-177

Molecular Weight g/mole 215.69

Water Solubility@20°C mg/L 33

Vapor Pressure@ 20°C torr 3.0x10-7

Henrys Law Constant (calculated) atm-m

3 mole-1

2.6x10-9

Kow Unitless 501.18

4.1.1. Environmental Fate Summary 

Atrazine is mobile and persistent in the environment. The main routes of dissipation are 

microbial degradation under aerobic conditions, runoff, and leaching. Because of its persistence 

and mobility, atrazine will move into surface and ground water. This is confirmed by the 

widespread detections of atrazine in surface water and ground water. Summaries of the 

environmental fate data are shown in Appendix A. 

There is no evidence that atrazine degrades by abiotic hydrolysis at pH 5, 7, and 9 (MRID 

40431319). Photodegradation studies show a high variability in atrazine photodegradation 

rates. Atrazine is persistent to direct photodegradation in water (t1/2= 335 days) under natural 

sunlight (MRID 42089904; 40431320). Aqueous photodegradation products of atrazine include 

2-chloro-4-isoproylamino-6-amino-s-triazine(DEA),chlordiamino-s-triazine(DACT), and 2-chloro-
21

6-ethylamino-4-amino-s-triazine (DIA), 2-hydroxy-4-isopropylamino-6-amino-s-triazine (HA), 2-

hydroxy-6-ethylamino-4-amino-s-triazine (DIHA), and 2-hydroxy-4-isopropylamino-6-amino-striazine (DHEA). (Degradation product structures are presented in Appendix L). Similarly, 

atrazine is moderately persistent (t1/2= 12 to 45 days) to photodegradation on soil under natural 

light (MRID 40431320; 42089905). Soil photodegradation products of atrazine include DEA, 

DACT, and DIA. 

Atrazine is persistent (t1/2= 146 days) in aerobic mineral soils (MRID 40629303, MRID 40431321, 

MRID 42089906). Aerobic soil metabolism degradation products include DEA, DACT, DIA, HA, 

DIHA, DHEA. Atrazine is also persistent in anaerobic aquatic 

(t1/2 = 608 days) and anaerobic soil (t1/2= 159 days) environments (MRID 40431323, MRID 

40431321, MRID 42089906). Anaerobic degradation products of atrazine include DEA, DACT, 

DIA, HA, DIHA, DHEA. 

Soil sorption coefficients for atrazine are low (Kf= 0.427-2.00 (1/n=0.72-1.06). The average Koc= 

100.475 ml/g-OC; N=4) (MRID 40431324), which indicates a FAO mobility classification of 

mobile in soil. 

Field dissipation studies show atrazine dissipation is dependent on microbial-mediated 

degradation, runoff, and leaching. The half-life of atrazine in six field studies in CA, GA, and MN 

ranged from 12.75 to 261 days in corn planted soil and 38.52 to 261 days in fallow soil (MRID 

42165504; 42165505, 40431336, 42165506, 40431337, 42165507, 40431339, 42165508, 

40431339, 42165508, 40431338, 42165509). Microbial degradation is an important route of 

dissipation in the cited field studies. Although atrazine leaching or runoff is not clearly shown in 

the field studies, atrazine dissipation is dependent on runoff (Acc. Nos. 00023543, 00027118, 

00027124, 00027123, 00027119) and leaching (Spalding et al. 1980; Junk et al. 1980; Spalding 

et al. 1979). The half-life in four long-term field dissipation studies in MN and CA ranged from 

102-402 days (MRID 40431338, MRID 42089909, 40431336, 42089910, 40431339, 42089911, 

40431337, 42089912). Degradation products in the studies include HA, DEA, and DIA. 

Concentrations of atrazine and its degradation products DEA, HA, and DIA were detected with 

soil depth in long-term field dissipation studies. 

In forestry field studies in Oregon, atrazine was detected on leaf surfaces, leaf litter, and soil. 

The half-life of atrazine was 87 days for exposed soil, 13 days on foliage and 66 days in leaf litter 

(MRID 40431340, 42041405). 

4.1.2. Degradation Products 

Degradation products of atrazine are shown in Table 5. There are two major types of 

degradation products for atrazine. The first type of degradation products are formed through 

dealkylation of the amino groups. The second type of degradation products are formed through 

substitution of a chlorine by a hydroxy group. These degradation products can be formed 
22

through abiotic and microbial-mediated processes. Two of these degradation products, DIA and 

DACT, are also degradation products of simazine. In addition, DACT is also a degradation 

product of cyanazine. Structures of the degradation products are shown in Appendix L. 

Table 5. Chemical Names for Atrazine Degradation Products 

Common Name Chemical Name Chemical 

Formula CAS Reg No. Synonyms

Deisopropylatrazine 2-chloro-6-ethylamino-4-aminos-triazineC5H8ClN5 1002-28-9 CEAT/DIA/G-28279

Deethylatrazine 2-chloro-4-isopropylamino-6-

amino-s-triazine

C6H10ClN5 6190-54 CIAT/DEA/G-30033

Hydroxyatrazine 2-hydroxy-4-isopropylamino-6-

ethylamino-s-triazine

C8H15N5O 2163-80 OIET/HA/G-34048

Diadealkylatrazine chlordiamino-s-triazine C3H4ClN5 3397-62-4 CAAT/DACT/DDA/

GS-28273

Deisopropylhydroxyatra

zine

2-hydroxy-6-ethylamino-4-

amino-s-triazine

C5H9N5O 7313-54-4 OEAT/DIHA/GS17792

Deethylhydroxyatrazine 2-hydroxy-4-isopropylamino-6-

amino-s-triazine

C6H11N5O -------------- OIAT/DHEA/GS17794

Dethyl-atrazine (DEA; G-30033) and deisopropyl-atrazine (DIA; G-28279) were detected in all 

laboratory and field studies (Table 6); hydroxy-atrazine (HA; G-34048) was detected in all 

studies except for the photodegradation on soil study; and diaminochloro-atrazine (DACT; G28273) was detected in all studies except for the aquatic metabolism studies. Deethylhydroxyatrazine (DEHA; GS-17794) and deisopropylhydroxy-atrazine (DIHA; GS-17792) were also 

detected in the photodegradation in water, aerobic soil metabolism, and anaerobic soil 

metabolism studies. For studies limited to several months, the relative concentrations of the 

degradation products in soil were generally DEA>DIA>DACT~HA. 
23

Table 6. Identification of Atrazine Degradation Products in Environmental Fate Studies 

Study

Degradation 

Products

Maximum Percentage of 

Applied Atrazine References

Hydrolysis None None MRID 40431319

Photodegradation in 

Water 

DACT 15 MRID 42089904

DEA 16 MRID 00024328

DIA 5

DIHA 0.22

HA 1.19

DHEA 0.27

Photodegradation on 

Soil

DACT 18.3 MRID 40431320

DEA 14.5 MRID 42089905

DIA 7.9

Aerobic Soil 

Metabolism

DACT 0.317 MRID 40629303

DEA 4.18 MRID 42089906

DIA 1.61

DIHA 0.410

HA 4.20

DHEA 0.774

Anaerobic Soil 

Metabolism

DACT 0.3 MRID 40629303

DEA 2.1 MRID 42089906

DIA 0.74

DIHA 0.22

HA 1.22

DHEA 0.44

Anaerobic Aquatic 

Metabolism

DEA 4.7 MRID 40431323

DIA 1.4 MRID 46338702

HA 12.4

Aerobic Aquatic 

Metabolism

DEA 2.9 MRID 46338702

DIA 0.4

HA 14.8

The mobility of atrazine degradation products can range from low to high mobility in soil. The 

chloro-triazine degradation products are expected to exhibit higher mobility than the hydroxyltriazine degradation products because they have lower partition coefficients (Table 7). 

Table 7. Soil Sorption Coefficients for Atrazine Degradation Products 

Degradation 

Product Kf Kd Koc References

DACT 0.16-1.56 0.108-0.800 30.65-75.96

MRID 41257904

MRID 40431327

MRID 40431333

DIA 0.16-2.7 0.422-6.08 35.1-82.3

MRID 41257906

MRID 40431331

MRID 40431325

DEA 0.06-1.02 0.116-0.963 12.15-44.90

MRID 41257906

MRID 40431334

HA 1.98-389.6 1.643-8.165 38.50-155.34

MRID 41257902

MRID 40431332

MRID 40431326
24

4.2. Surface Water Monitoring 

Characteristics of representative monitoring programs for atrazine from 1975 to 2011 are 

shown in Table 8. Additional atrazine surface water monitoring data prior to 2003 has been 

previously analyzed in the USEPA IRED (2003b). As expected, the programs vary regarding their 

objective and monitoring strategy. Several of the programs such as the National Water-Quality 

Assessment Program (NAWQA), California Surface Water Monitoring Program (CSW), Iowa 

Ambient Monitoring Program, USGS-EPA Pilot Monitoring Program, Heidelberg University 

National Center of Water Quality (NCWQR) were developed to assess general pesticide 

occurrence in ambient surface water. In contrast, other monitoring programs such as the 

Nebraska State Surface Water Monitoring Program, Kansas State Surface Water Monitoring, 

Wisconsin State Surface Water Monitoring Program, Minnesota State Monitoring Program, 

Montana State Monitoring Program, and Syngenta Atrazine Ecological Monitoring Program 

(AMP), monitoring programs were targeted to atrazine use areas. These monitoring programs 

provide atrazine occurrence data from 1975-2011 (36 years) across 48 contiguous states. The 

number of sampling stations varied from six stations in NCWQR monitoring program to 2209 

sampling stations in the USGS-NAWQA monitoring program. 

Table 8. Characteristics of Representative Monitoring Programs for Atrazine and Its Degradation Products in 

Surface Water

Study

Number

of 

States

Number of 

Sampling 

Stations

Years Targeted 

Monitoring

Surface 

Water 

Type

Reported

LOD

(μg/L)

Degradates

Analyzed

NAWQA 48 2209 1991-2011 No Ambient ≤0.16 Yes

CSW 1 474 1991-2011 No Ambient ≤ 4.76 Yes

Iowa 1 175 2003-2006 No Ambient 0.05 No

Nebraska 1 232 2001-2006 Yes Ambient ≤ 0.3 No

Minnesota 1 9 1993-2007 Yes Ambient 0.05 No

Montana 1 25 2006-2008 Yes Ambient 0.0022 Yes

Kansas 

Streams 1 393 1977-2008 Yes Ambient <6.3 No

Kansas Lakes 1 284 1975-2008 Yes Ambient <6.3 No

Wisconsin 1 8 2008 Yes Ambient 0

1

No

USGS-EPA 

Reservoir 12 20 1999-2000 No

Ambient 

Finished <0.009 Yes

NCWQR 1 6 1983-2008 No Ambient 0

1

No

AEEMP 12 74 2004-2011 Yes Ambient <0.05 No

AMP 13 

250-Raw

204-Finish 2003-2011 Yes

Ambient 

Finished 0.05 Yes

PDP 26 61 2004-2009 No

Ambient 

Finished 0.0066 Yes

1-LOD was reported as zero in data. 

A key difference among the monitoring programs is the annual sampling frequency at each 

sampling station. Figure 4 provides a comparison of cumulative probability distributions of siteyear sampling frequencies among the monitoring programs. With the exception of the NCWQR 
25

monitoring program, the non-targeted atrazine monitoring programs had lower site-year 

sampling frequencies than the NCWQR. The 90th percentile annual sampling frequency for the 

non-targeted monitoring programs ranged from 2 to 147 days. The sampling frequency is an 

important consideration in quantitative interpretation of the pesticide concentrations from 

monitoring data as well as the development of reliable chemographs (USEPA, 2011a). 

Number Samples Per Site* Year

0 50 100 150 200 250

Cumulative Probability

0.0

0.2

0.4

0.6

0.8

1.0

USEPAUSGS

CA

IA 

KS-Stream

KS Lake 

NE

MN 

Heidleberg 

Figure 4. Distribution of Sampling Frequencies for Atrazine Surface Monitoring Programs 

4.2.1. Monitoring Data Analysis 

The monitoring data for atrazine and its degradation products were analyzed by site-year. 

This strategy was employed because pesticide occurrence is dependent on the spatiallydependent site conditions including pesticide use, agronomic practices, soil properties, 

meteorology, etc., as well as temporally-dependent conditions, including pesticide application 

timing and rainfall occurrence. Additionally, the site-year strategy provides a quantitative 

analysis of the data used in developing annual atrazine chemographs for the PATI model. An 

annual atrazine chemograph is generated by stair-step imputation between measured values 

for specific monitoring site-years. The chemograph, therefore, provides an annual daily time 

series of atrazine concentration, which can be used for calculating time-weighted mean 

concentrations. 

The monitoring data were analyzed using a macro in an Excel spreadsheet. The data were 

analyzed for site-year statistics, including number of samples, number of non-detections, 

arithmetic annual average concentration, time-weighted annual mean, maximum 60-day mean 

concentration, and annual maximum daily concentration. Time-weighted means were derived 
26

from a chemograph constructed on 365-day calendar year. A stair-stepping imputation was 

used between the measured values. The tails at the beginning and end of the site-year were 

assumed to equal the lowest detectable concentration in the NAWQA (0.16 μg/L) until the first 

or last measured value in the year. The lowest detection in NAWQA was used a conservative 

estimate of detectable concentrations of atrazine. Statistical analyses for atrazine were limited 

to site-years with 4 or more samples. This restriction was used because it is the minimum 

sampling frequency for assessing atrazine rolling average concentrations for Human Health 

Maximum Contaminant Levels. The descriptive statistics for degradation products of atrazine 

and atrazine residues in groundwater were described using detection frequency and maximum 

concentrations. 

4.2.2. Ambient Surface Water Monitoring Programs 

The atrazine monitoring data illustrates that the detection frequencies of atrazine 

concentrations in ambient water samples range from 0.28% to 94.32% (Table 9). For the 

purpose of the analysis, ambient surface water is defined as surface water from flowing water 

(rivers and streams), reservoirs, ponds, lakes, and ditches as well as raw surface source water 

from community water systems (CWS). As expected, the highest detection frequencies are 

associated with monitoring sites in corn production states such as Iowa, Nebraska, Minnesota, 

Ohio (NCWQR), and Kansas. The maximum daily concentration and annual average 

concentration of atrazine from all ambient surface water data are reported at 683.4 μg/L and 

31.80 μg/L, respectively. These concentrations are associated with a monitoring site in the 

Nebraska (Site ID SLB2TLSNDY60). 

Table 9. Descriptive Statistics of Atrazine Concentrations In Ambient Surface Water 

Monitoring Programs 

Monitoring 

Program

Detection 

Frequency

Maximum Daily 

Peak

Maximum

60 Day

Mean

Maximum

Time Weighted Annual 

Mean

% μg/L

NAWQA 82.51 201 54.3 11.63

CSW 0.28 5.3 1.8 0.3

Iowa 70.25 16.3 12 2.3

Nebraska 64.36 683.4 192 31.8

Minnesota 86.64 32 2.5 1.3

Montana 7.27a0.0022 NA NA

Kansas 57.71 105 61.8 11.2

Wisconsin 75.12 21.2 19.2 8.8

NCWQR 85.28 54.4 10.9 2.2

USGS-EPA 

Reservoir 84.77 11.6 6.1 1.9

AEEMP 94.32a237.5 49.3 8.2

AMP 88.21a227 39.9 9.6

PDP 75.57a4.2 2.8 1.1

a-Detection frequencies were not limited to site-years with 4 or more samples. 
27

Occurrence of atrazine degradation products were derived from the NAWQA, Atrazine 

Monitoring Program (AMP), USGS-EPA, California (CSW), Montana, and USDA Pesticide Data 

Program (PDP) monitoring programs. Because the AMP, USDA PDP, USGS-EPA monitoring 

programs are focused on pesticide concentrations in drinking water, raw water samples from 

these programs are used to represent occurrence patterns of the atrazine degradation products 

in ambient surface water. The chemical names for the atrazine degradation products are shown 

in Table 10. The monitoring data shows high detection frequencies of atrazine degradation 

products (DEA, DIA, DACT, DHEA, HA) in ambient surface water. The lowest detection 

frequencies of atrazine degradation products were found in the Montana Ambient Monitoring 

and California Surface Water- Ambient Water (CSW) program. This frequency is probably 

associated with lower atrazine use in these areas when compared to other monitoring 

programs. The maximum concentrations of atrazine degradation products decreased in the 

following order: DDA-DEA> DIA> ACT>OEIT>DHEA. The occurrence pattern is probably 

associated with the relative mobility of the chlorinated (DEA, DIA, DACT) and non-chlorinated 

(HA, DHEA) degradation products. The maximum occurrence concentrations of the degradation 

products are orders of magnitude lower than parent atrazine in ambient surface water. 

Table 10. Descriptive Statistics of Atrazine Degradation Products in Ambient Surface 

Source Water Monitoring Programs

Monitoring 

Program

Degradation 

Products N

Detection 

Frequency

Maximum 

Concentration

% μg/L

NAWQAAmbient WaterDEA 31830 69.03 10>

DIA 4360 38.62 4.44

DACT 1849 21.03 0.6249

DHEA 2 100 0.11

HA 17 11.76 0.3 

USGS-EPA 

Reservoir

DEA 383 78.85 0.577

HA 381 81.10 2.17

DIA 383 79.89 0.386

DACT 383 71.54 0.514

HA 381 81.10 2.17

AMP – Raw 

Water

DEA 27354 54.80 8.8

DIA 27357 37.73 4.79

DACT 27354 2.66 8.80

MontanaAmbient WaterDEA 55 0 NA

DIA 55 0 NA

HA 55 0 NA

CSW-Ambient 

Water

DEA 72 0 NA

DIA 751 0.399 0.021

DACT 466 2.36 0.672

PDP DEA 2104 66.40 1.078

DIA 2105 44.09 0.776

HA 927 68.40 0.48
28

4.2.3. Finished Surface Source Drinking Water Monitoring Programs 

Occurrence of atrazine and its degradation products in finished drinking water were derived 

from data in the AMP, USGS-EPA, and the USDA PDP monitoring programs (Table 11). The 

atrazine residue concentrations in drinking water are reported without consideration of water 

treatment processes. Activated carbon has been found to be the best available technology 

(BAT) to reduce atrazine concentrations in finished drinking water. Although the detection 

frequencies of atrazine residues in finished water are comparable to occurrence concentrations 

in ambient surface water, the maximum concentrations of atrazine and its degradation 

products in finished drinking water are generally lower than in ambient surface waters. 

Table 11. Descriptive Statistics of Atrazine and its Degradation Products in 

Finished Surface Source Water Monitoring Programs

Monitoring 

Program

Atrazine 

Residues N

Detection 

Frequency

Maximum 

Concentration

% μg/L

USGS-EPA 

Reservoir

Atrazine 225 82.22 1.94

DEA 224 74.55 0.267

DIA 225 64.89 0.178

DACT 225 62.66 0.0826

HA 224 81.25 1.79

AMP Atrazine 34215 76.06 59.57

DEA 26488 54.80 4.84

DIA 26488 37.73 2.61

DACT 20037 2.66 2.23

PDP Atrazine 2105 76.05 2.733

DEA 2105 62.57 0.865

DIA 2105 40.67 0.469

HA 929 68 0.37

4.2.4. Ground Water Monitoring Programs 

Occurrence of atrazine and it degradation products in groundwater were taken from the 

NAWQA, Montana State monitoring program, and the USDA PDP Program (Table 12). Although 

atrazine and its degradation products were detected in all the monitoring programs, the 

detection frequencies of atrazine residues in ground water were lower than ambient surface 

water. Additionally, the maximum concentration of atrazine (16.6 μg/L) in groundwater is 

substantially lower than maximum concentration detected in surface water (683.4 μg/L). As 

expected from laboratory mobility data, the more mobile chlorinated atrazine degradation 

products (DEA, DIA, DACT) were detected more frequently than the less mobile hydroxylsubstituted atrazine degradation products. 
29

Table 12. Descriptive Statistics of Atrazine Concentrations from 

Representative Ground Water Monitoring Programs

Monitoring 

Program

Atrazine 

Residues N

Detection 

Frequency

Maximum

Concentration

% μg/L

NAWQA Atrazine 13479 29.95 16.6

DEA 13410 32.78 2.6

DIA 2963 12.35 1.11

DACT 1754 8.20 0.7632

HA 52 9.62 0.81

DIHA 15 0 <0.025

PDP Atrazine 800 9.13 0.231

DEA 800 12.75 1.55

DIA 800 4.38 0.202

HA 800 11.13 0.255

DIHA 800 9 0.99

MT Atrazine 2120 13.39 0.98

DEA 1380 23 0.79

DIA 1381 7.09 2.2

DACT 154 35.71 1.3

DHEA 154 0 NA

HA 1376 8.21 2.5

DIHA 154 0 NA

4.3. Atmospheric Monitoring 

Atrazine has been detected in air, rain, snow, and fog samples (Majewski and Capel, 1995). 

Observed concentrations of atrazine range from 0.003 to 40 μg/L in rain, 0.000008 to 0.020 

μg/L in air, 0.270 to 0.820 μg/L in fog, and 0.02 to 0.03 μg/L in snow. These detections in air, 

rain, snow and fog were said to have been associated with atrazine use areas and application 

timing. 

5. Stressors of Concern 

The residues of concern in an assessment include the parent compound, and may also include 

any degradate(s) that are observed at significant levels (>10% by weight relative to parent from 

available degradation studies), and/or determined to be of toxicological concern. Previous 

ecological risk assessments for atrazine have evaluated potential degradate(s) for inclusion in 

the risk assessment (USEPA 2009b). Based on those analyses, parent atrazine will be 

considered the stressor of concern. This conclusion is based on either available degradate 

toxicity data indicating that it is less toxic than parent atrazine, or on the proportion of the 

degradates expected to be in the environment and available for exposure relative to atrazine. 

In this case, parent atrazine is expected to be protective for non-target organisms that may be 

exposed to the parent and any of its degradates (USEPA, 2009b). 
30

 

In its ecological risk assessments, the EPA does not routinely include a quantitative evaluation 

of mixtures of active ingredients, either those mixtures of multiple active ingredients in product 

formulations or those in the applicator’s tank. In the case of the product formulations of active 

ingredients (that is, a registered product containing more than one active ingredient), each 

active ingredient is subject to an individual risk assessment for regulatory decision regarding 

the active ingredient on a particular use site. Effects data are available for atrazine formulated 

products that contain more than one active ingredient (Appendix B; USEPA 2009b), and as such 

the data may be used qualitatively or quantitatively in accordance with the EPA’s Overview 

Document and the Services’ Evaluation Memorandum (USEPA 2004; USFWS/NMFS 2004). 

Available toxicity data for environmental mixtures of atrazine with other pesticides will be 

presented as part of the ecological risk assessment. It is expected that the toxic effect of 

atrazine, in combination with other pesticides used in the environment, is likely to be a function 

of many factors, including but not necessarily limited to: (1) the exposed species, (2) the cocontaminants in the mixture, (3) the ratio of atrazine and co-contaminant concentrations, (4) 

differences in the pattern and duration of exposure among contaminants, and (5) the 

differential effects of other physical/chemical characteristics of the receiving waters (e.g.

organic matter present in sediment and suspended water). Quantitatively predicting the 

combined effects of all these variables on mixture toxicity to any given taxa with confidence is 

beyond the capabilities of the available data and methodologies. However, a qualitative 

discussion of implications of the available pesticide mixture effects data on the confidence of 

risk assessment conclusions will be addressed as part of the uncertainty analysis.

6. Evaluation of Atrazine Toxicity to Specific Taxa 

Consistent with the process described in the Overview Document (USEPA 2004), the risk 

assessment for atrazine relies on a surrogate species approach. Toxicological data generated 

from surrogate test species, which are intended to be representative of broad taxonomic 

groups, are used to extrapolate the potential effects on a variety of species included under 

these taxonomic groupings. 

Acute and chronic toxicity data from single-species studies submitted by pesticide registrants 

along with the available open literature will be used to evaluate the potential direct and 

indirect effects of atrazine to aquatic and terrestrial species, including sublethal effects that can 

be directly linked to survival, growth, or fecundity. These data include toxicity on the technical 

grade active ingredient, degradates, and when available, formulated products (e.g., “Six-Pack” 

studies). The open literature studies are identified through EPA’s ECOTOXicology (ECOTOX 

2007c) database, which employs a literature search engine for locating chemical toxicity data 

for aquatic life, terrestrial plants, and wildlife. The evaluation of both sources of data may also 

provide insight into the direct and indirect effects of atrazine on biotic communities from loss 

of species that are sensitive to the chemical and from changes in structure and functional 

characteristics of the affected communities. Several ECOTOX runs have been conducted over 
31

the years prior to this problem formulation (2003, 2004, 2006, 2007, 2008, and 2011). 

However, if an additional ECOTOX search is conducted prior to the writing of the atrazine 

Registration Review risk assessment, this new information will also be evaluated for possible 

quantitative and/or qualitative data and when appropriate, will be included in the risk 

assessment in support of Registration Review. 

Assessment endpoints are defined as “explicit expressions of the actual environmental value 

that is to be protected” (USEPA 1992). Selection of the assessment endpoints is based on 

valued entities (e.g., birds, fish and aquatic plants), organisms important in the life cycle of 

ecological receptors, the primary constituent elements (PCEs) of designated critical habitat for 

listed species, the ecosystems potentially at risk (e.g., waterbodies, riparian vegetation, and 

upland and dispersal habitats), the migration pathways of atrazine (e.g., runoff, spray drift, 

etc.), and the routes by which ecological receptors are exposed to atrazine (e.g., direct contact, 

etc.).

As described in EPA’s Overview Document (USEPA, 2004), the assessment endpoints for 

pesticide risk assessments are growth, reproduction, and survival of species. For this 

assessment, evaluated taxa include aquatic-phase amphibians, freshwater and saltwater fish, 

freshwater and saltwater invertebrates, aquatic plants, birds (surrogate for terrestrial-phase 

amphibians), mammals, terrestrial invertebrates, and terrestrial plants. Acute (short-term 

exposure) and chronic (long-term exposure) toxicity information is characterized based on 

registrant-submitted studies and a comprehensive review of the open literature on atrazine and 

its degradates. 

A summary of the data to be used for quantitative and qualitative risk assessment for nontarget species and communities exposed to atrazine in aquatic and terrestrial habitats is 

provided in this section. See Appendix B for a complete list of submitted “Acceptable” and 

“Supplemental” studies).

6.1. Toxicity to Plants 

6.1.1. Toxicity to Terrestrial Plants 

Plant toxicity data from both registrant-submitted studies and studies in the scientific literature 

were reviewed for this assessment. Registrant-submitted studies are conducted under 

conditions and with species defined in EPA toxicity test guidelines. Sub-lethal endpoints such as 

plant growth, dry weight, and biomass are evaluated for both monocots and dicots, and effects 

are evaluated effects at both seedling emergence and vegetative life stages. A guideline study 

generally evaluates toxicity to ten crop species. A drawback to these tests is that they are 

conducted on herbaceous agricultural crop species only, and extrapolation of effects to other 

species, such as woody shrubs and trees and wild herbaceous species, contributes uncertainty 

to risk conclusions. Preliminary data (discussed below) suggests that sensitive woody plant 
32

species exist. However, since atrazine is labeled for use in forestry production effects to many 

types of trees are not expected at concentrations anticipated in the environment. 

Commercial crop species have been selectively bred and may be more or less resistant to 

particular stressors than wild herbs and forbs. The direction of this uncertainty for specific 

plants and stressors, including atrazine, is largely unknown. Homogenous test plant seed lots 

also lack the genetic variation that occurs in natural populations, so the range of effects seen 

from tests is likely to be smaller than would be expected from wild populations. 

Based on the results of the submitted terrestrial plant toxicity tests, it appears that emerged 

seedlings are more sensitive to atrazine via soil/root uptake exposure than emerged plants via 

foliar routes of exposure. However, all tested plants, with the exception of corn in the seedling 

emergence and vegetative vigor tests and ryegrass in the vegetative vigor test, exhibited 

adverse effects following exposure to atrazine. 

For Tier II seedling emergence, the most sensitive dicot is carrot and the most sensitive 

monocot is oat. EC25 values, on an equivalent application rate basis, for oats and carrots, which 

are based on a reduction in dry weight, are 0.003 and 0.004 lb a.i./A, respectively; NOAEC 

values for both species are 0.0025 lb a.i./A. Table 13 summarizes the most sensitive Tier II 

terrestrial plant seedling emergence toxicity data. 

For Tier II vegetative vigor studies, the most sensitive dicot is cucumber, and the most sensitive 

monocot is onion. In general, dicots appear to be more sensitive than monocots via foliar 

routes of exposure with all tested monocot species showing a significant reduction in dry 

weight at EC25 values ranging from 0.008 to 0.72 lb a.i./A. In contrast, two of the four tested 

monocots showed no effects from atrazine (corn and ryegrass), while EC25 values for oats and 

onion were 0.61 and 2.4 lb a.i./A, respectively. Table 14 summarizes the most sensitive 

terrestrial plant vegetative vigor toxicity data used to derive risk quotients in this assessment. 
33

 

Table 13. Nontarget Terrestrial Plant Seedling Emergence Toxicity (Tier II). Only endpoints in bold 

will be used quantitatively.

Surrogate Species % ai EC25 / NOAEC 

(lbs ai/A)

Endpoint 

Affected

MRID No. Study 

Classification Author/Year

Monocot - Corn 

(Zea mays)

97.7 > 4.0 / > 4.0 No effect 420414-03 Acceptable

Chetram 1989

Monocot - Oat 97.7 0.004 / 0.0025 red. in dry 

weight

420414-03 Acceptable

(Avena sativa) Chetram 1989

Monocot - Onion 97.7 0.009 / 0.005 red. in dry 

weight

420414-03 Acceptable

(Allium cepa) Chetram 1989

Monocot - Ryegrass 97.7 0.004 / 0.005 red. in dry 

weight

420414-03 Acceptable

(Lolium perenne) Chetram 1989

Dicot - Carrot 97.7 0.003 / 0.0025 red. in dry 

weight

420414-03 Acceptable

(Daucus carota) Chetram 1989

Dicot - Soybean 97.7 0.19 / 0.025 red. in dry 

weight

420414-03 Acceptable

(Glycine max) Chetram 1989

Dicot - Lettuce 97.7 0.005 / 0.005 red. in dry 

weight

420414-03 Acceptable

(Lactuca sativa) Chetram 1989

Dicot - Cabbage 97.7 0.014 / 0.01 red. in dry 

weight

420414-03 Acceptable

(Brassica oleracea alba) Chetram 1989

Dicot - Tomato 97.7 0.034 / 0.01 red. in dry 

weight

420414-03 Acceptable

(Solanum lycopersicum) Chetram 1989

Dicot - Cucumber 97.7 0.013 / 0.005 red. in dry 

weight

420414-03 Acceptable

(Cucumis sativus) Chetram 1989
34

Table 14. Nontarget Terrestrial Plant Vegetative Vigor Toxicity (Tier II). Only endpoints in bold will 

be used quantitatively.

Surrogate Species % ai EC25 / NOAEC Endpoint 

Affected

MRID No. Study 

Classification (lbs ai/A) Author/Year

Monocot - Corn 97.7 > 4.0 / > 4.0 No effect 420414-02 Acceptable

(Zea mays) Chetram 1989

Monocot - Oat 97.7 2.4 / 2.0 red. in dry 

weight

420414-02 Acceptable

(Avena sativa) Chetram 1989

Monocot - Onion 97.7 0.61 / 0.5 red. in dry 

weight

420414-02 Acceptable

(Allium cepa) Chetram 1989

Monocot - Ryegrass 97.7 > 4.0 / > 4.0 No effect 420414-02 Acceptable

(Lolium perenne) Chetram 1989

Dicot - Carrot 97.7 1.7 / 2.0 red. in 

plant 

height

420414-02 Acceptable

(Daucus carota) Chetram 1989

Dicot - Soybean 97.7 0.026 / 0.02 red. in dry 

weight

420414-02 Acceptable

(Glycine max) Chetram 1989

Dicot - Lettuce 97.7 0.33 / 0.25 red. in dry 

weight

420414-02 Acceptable

(Lactuca sativa) Chetram 1989

Dicot - Cabbage 97.7 0.014 / 0.005 red. in dry 

weight

420414-02 Acceptable

(Brassica oleracea alba) Chetram 1989

Dicot - Tomato 97.7 0.72 / 0.5 red. in 

plant 

height

420414-02 Acceptable

(Solanum lycopersicum) Chetram 1989

Dicot - Cucumber 97.7 0.008 / 0.005 red. in dry 

weight

420414-02 Acceptable

(Cucumis sativus) Chetram 1989

In addition, a report on the toxicity of atrazine to woody plants (Wall et al., 2006; MRID 

46870401) was reviewed by the EPA. A total of 35 species were tested at application rates 

ranging from 1.5 to 4.0 lbs a.i./A. Twenty-eight species exhibited either no or negligible 

phytotoxicity. Seven of 35 species exhibited >10% phytotoxicity. However, further examination 

of the data indicates that atrazine application was clearly associated with severe phytotoxicity 

in one species (Shrubby Althea). These data suggest that, although sensitive woody plants exist, 

atrazine exposure to most woody plant species at application rates of 1.5 to 4.0 lbs a.i./A is not 

expected to cause adverse effects. A summary of the available woody plant data is provided in 

Appendix B. 

 

6.1.2. Toxicity to Aquatic Non-Vascular Plants 

The following two toxicity sections (6.1.2 and 6.1.3) are organized based on the taxonomic 

groups shown in Figure 5 and are representative of closely related taxa. These sections are 

followed by Section 6.1.4, which describes the toxicity information available from microcosm 

and mesocosm studies, including the breadth of this diversity in the studies. Sections 6.1.2 and 
35

6.1.3 represent the toxicity to individual species, whereas Section 6.1.4 represents the toxicity 

of atrazine to the aquatic plant communities found in North America. Although the toxicity 

information is presented in separate sections (single species tests vs. cosm studies), the data 

represent the effects of atrazine on aquatic autotrophic species and communities of aquatic 

plants, and are considered of equal importance in the risk characterization. 

The category of “Aquatic Non-Vascular Plants” is representative of a broad diversity of 

unicellular and multicellular organisms. These include Eubacteria (e.g., blue-green algae), 

Archaeoplastida (e.g., red algae, glaucophytes, green algae, and aquatic bryophytes), 

Chromalveolates (e.g., aveolates, cryptomonads, dinoflagellates, diatoms, water molds, and 

brown algae), Excavates (e.g., euglena), and the Unikonts (e.g., fungi, and collared-flagellates) 

except the “Animals” lineage. 

Figure 5. The taxonomy followed in this problem formulation is based on the information 

available at the Tree of Life Web Project (http://tolweb.org/tree/) and is consistent with 

current understandings of the relationships between these taxa. 

Single-species aquatic plant toxicity studies will be used as the foundation for evaluating 

whether atrazine may affect primary production and diversity in aquatic ecosystems (see 
36

section 13 for further explaination). Numerous aquatic non-vascular plant toxicity studies have 

been submitted to EPA and/or have been published in the open literature (Appendix B; USEPA 

2007c). A summary of the most sensitive endpoints for freshwater non-vascular plants is 

provided below; Appendix B includes a more comprehensive list of the available data. The most 

sensitive single species data for aquatic non-vascular plants from either supplemental or 

acceptable studies (Table 15) will be used for risk characterization purposes only and will not be 

used for quantitative purposes in risk quotient calculation.
37

Table 15. Summary of the most sensitive aquatic non-vascular plant toxicity endpoints available from the registrant submitted studies and the open 

literature. 

Taxonomic Group

Number 

of 

Families 

Tested

Number 

of 

Genera 

Tested

Number 

of 

Species 

Tested

Minimum

ED/IC/EC50

Endpoint1

FW/SW 

and 

Duration2

Species and 

Effect Used for 

Reported 

Endpoint

Citation 

(MRID)

EUBACTERIA: CYANOBACTERIA:

(Blue-Green Algae)

5 14 29 EC50 <1 μg/L FW

7 days

Oscillatoria 

lutea

93% reduction 

of chlorophyll 

production

Torres and 

O'Flaherty 

1976 

(000235-44)

EUKARYOTES:

ARCHAEOPLASTIDA GREEN PLANTS: 

EMBRYOPHYTA: 

(Non-Vascular Land 

Plants)

1 1 1 EC50 < 2 

μg/L

FW

24 hrs

Fontinalis 

hypnoides

90% reduction 

in 

photosynthesis

Hoffman and 

Winkler 1990

EMBRYOPHYTA: 

(Vascular Land Plants)

21 30 42 EC50 = 0.001 

μg/L

FW

14 days

Elodea 

canadensis

50% reduction 

in biomass

McGregor et 

al. 2008

CHLOROPHYTA and 

STREPTOPHYTA3: 

(Green Algae)

16 26 34 EC50 < 1 

μg/L

FW

7 days

Stigeoclonium 

tenue

67% reduction 

in chlorophyll 

production

Torres and 

O'Flaherty 

1976 

(000235-44)

PRASINOPHYTA: 

(Prasinophytes)

2 3 4 IC50 = 14.2 

μg/L

LOAEC = 1.1 

μg/L

SW

4 hours

Nephroselmis 

pyriformis

50% 

photoinhibition

Magnussun et 

al. 2010
38

RHODOPHYTA: 

(Red Algae)

2 2 2 EC50 = 79 

μg/L

SW

72 hrs

Porphyridium 

cruentum

50% reduction 

in oxygen 

production

Mayer 1986 

(402284-01)

CHROMALVEOLATES HACROBIA: 

HAPTOPHYTA:

(Coccolithophorads)

2 2 2 EC50 = 30 

μg/L

SW 

72 hrs

Isochrysis 

galbana

50% growth 

inhibition

Debelius et al. 

2008

CRYPTOPHYTA: 

(Cryptomonads)

2 3 5 EC50 = 22.17 

μg/L

NOAEC < 

12.5 μg/L

SW

96 hrs.

Storeatula 

major

50% reduction 

in abundance

DeLorenzo et 

al. 2004

STRAMENOPILES: 

BACILLARIOPHYTA:

(DIATOMS)

17 22 46 EC50 = 19.4 

μg/L

SW

48 hrs.

Bellerochea 

polymorpha 

50% reduction 

in population 

growth

Walsh et al. 

1988

PHAEOPHYTA:

(Brown Algae)

1 1 2 LOAEC = 10 

μg/L

NOAEC < 1 

μg/L

SW

> 18 days

Laminaria 

hyperborea

growth 

reduction

Hopkin and 

Kain 1978

CHRYSOPHYTA:

(Golden Algae)

3 3 4 EC50 = 77 

μg/L

SW 

1 hr

Monochrysis 

lutheri

50% reduction 

in oxygen 

evolution

Hollister and 

Walsh 1973

XANTHOPHYTA:

(Yellow-Green Algae)

3 3 4 EC50 = 185 

μg/L

SW 

72 hrs

Nannochloropsis 

gaditana

50% total 

fluorescence 

inhibition

Debelius et al. 

2008

AVEOLATES:
39

PYRROPHYCOPHYTA 

(Dinoflagellates):

4 5 5 EC50 = 17.19 

μg/L

NOAEC < 

12.5 μg/L

SW

96 hrs.

Amphidinium 

operculatum

50% reduction 

in total 

biovolume

DeLorenzo et 

al. 2004

CILIOPHORA:

(Ciliates)

2 2 2 ED50 = 5.83 

μg/L

FW

24 hrs

Tetrahymena 

pyriformis

50% reduction 

in survival

Toth & 

Tomasovicova

1979

EXCAVATES EUGLENOZOA:

(Euglenoids)

1 1 1 496 μg/L FW

7 days

Euglena gracilis

50% inhibition 

of 

photosynthesis

ThuillierBruston et al. 

1996 

1

These endpoints were collected over different exposure periods. 

2

FW= fresh water, SW = salt water 

3

The Embryophytes are treated separately here. 
40

Eubacteria: Toxicity data from studies on Cyanobacteria (Cyanophyaceae) span three orders 

and include six species: the Oscillatoriales (Oscillatoria lutea), the Nostocales (Anabaena 

cylindrica; A.inaequalis; A. variabilis; A. flos-aquae), and the Chroococcales (Microcystis 

aeruginosa). The lower 95% confidence interval on the overall EC50 data in the ECOTOX 

database (as prepared for the Environmental Fate and Effects Division) is 13.6 μg/L. The most 

sensitive endpoint from these open literature data reports a 93% reduction in chlorophyll 

production at <1 μg/L in O. lutea in a 7-day study (Table 15). In another study (Stratton 1984) 

using A. inaequalis, the most sensitive endpoint was reduced biomass (measured as cell count) 

followed by reduced growth rate and lastly by reduced photosynthesis. This pattern of reduced 

biomass as the most sensitive measured endpoint was reflected in several other studies on 

cyanobacteria (Appendix B).

Archaeoplasida (Embryophyta): Under the broad category “Non-Vascular Aquatic Plants” the 

Bryophyta (mosses, liverworts and hornworts) are the only group that is represented (Table 

15). All other Embryophyta taxa are represented in either aquatic or terrestrial vascular plant 

sections of this problem formulation. The available toxicity data for bryophyta does not report 

an EC50; however, an EC90 of 2 μg/L is reported for the species Fontinalis hypnoides based on 

reduced photosynthesis (Hoffmann and Winkler 1990). This study also reports morphological 

effects to the structural composition of chloroplasts and leaf blade cellular structure at 2 and 10 

μg/L, respectively. 

Archaeoplasida (Chlorophyta and Streptophyta): This group of non-vascular plants is 

represented by 118 different studies in the toxicity literature, including 16 different families 

and and 34 species of both marine and freshwater environments (Table 15). The lower 95% 

confidence interval on the overall EC50 data in the ECOTOX database is 20.0 μg/L. The most 

sensitive endpoint for the freshwater toxicity tests is based on a 67% reduction in chlorophyll 

production in Stigeoclonium tenue at <1 μg/L (Torres and O’Flaherty 1976). The authors also 

tested Chlorella vulgaris and report a 50% reduction in chlorophyll production at 1 μg/L. In 

another study by Kish (2004), the author reports a NOAEC of 0.012 μg/L for Pithophora 

oedogonia based on total chlorophyll. In the saline aquatic systems, this group of 

Archaeoplasida is less sensitive than their counterparts in freshwater. The most sensitive 

chlorophyte was reported by DeLorenzo et al. (2004), who showed a 50% reduction in 

chlorophyll production at 11.87 μg/L during a 96 hour test on Ankistrodesmus sp. DeLorenzo et 

al. (2011) report that significant reductions in various endpoints occur in Dunaliella tertiolecta 

when exposed to atrazine (a single dose of 100 μg/L) at elevated salinity (40 ppt), higher 

temperature (35o C), and a combination of these factors than at typical conditions that were 

used in DeLorenzo et al. 2004. 

Archaeoplasida (Prasinophyta): This group of non-vascular plants is represented by 5 different 

studies in the toxicity literature, including 2 different families and 4 species (Table 15). The 

most sensitive endpoint for the freshwater toxicity is EC50 of 34.3 μg/L based on reduced 

photosynthesis (Podola and Melkonian 2005). The most sensitive endpoint for saltwater taxa is 

an IC50 of 14.2 μg/L, based on 50% photoinhibition (Magnussun et al. 2010). 
41

Archaeoplasida (Rhodophyta): The Rhodophyta (red algae) are represented in the toxicity 

literature by the Porphyridium cruentum (Bangiophyceae) (Table 15), which is the species from 

which the Japanese seaweed Nori is produced (Mayer 1986). This study reported a reduction in 

O2 production, which reflects the decline in photosynthetic activity, at an EC50 of 79 μg/L. The 

data suggest that the red algae may be less sensitive to atrazine than the other Arcaeoplastida 

groups. 

Chromalveolates (Hacrobia): These taxa are represented in the toxicological literature by 4 

different families and 7 species (Table 15). The most sensitive reported endpoints come from 

the DeLorenzo et al. (2004) study that reported an EC50 of 22.17 μg/L based on reduced 

abundance but also report effects at the lowest concentration tested (12.5 μg/L). Similarly, 

Debelius et al. (2008) reported a 50 % growth inhibition at 30 μg/L. 

Chromalveolates (Stramenopiles): The Stramenopiles are a highly diverse lineage of aquatic 

organisms that include diatoms, brown algae, golden-algae and yellow-green algae. They are 

represented by studies including 24 different families and 56 species of both marine and 

freshwater environments (Table 15). The available data suggests that these taxa have relatively 

similar toxicity to atrazine exposure. The most sensitive freshwater taxon, Phaeodactylum 

tricornutum, was reported to have a 50% inhibition of photosynthesis at 33.6 μg/L and effects 

at the lowest concentration tested, 4.5 μg/L (Magnussun et al. 2010). The most sensitive 

estuarine/marine taxon tested is a diatom with an EC50 of 19.4 μg/L based on population 

growth reduction (Walsh et al. 1988). In a study of atrazine toxicity to brown algae by Hopkin 

and Kain (1978), reproductive and sporophyte growth effects were reported at all 

concentrations tested (NOAEC < 1 μg/L). 

Chromalveolates (Aveolates): This diverse lineage of aquatic microorganisms is represented in 

the toxicological literature by 4 different families and 5 species (Table 4.2). The most sensitive 

reported EC50 is 17.19 μg/L (NOAEC < 12.5 μg/L) based on reduction of total biovolume 

(DeLorenzo et al. 2004). 

Chromalveolates (Ciliophora): Ciliates are represented in the toxicological literature by 5 

studies on two species from different families (Table 15). The most sensitive reported 

endpoints come from the Toth and Tomasovicova (1979) study that reported ~ 50 % reduction 

in survival at 5.83 μg/L. 

Excavates (Euglenozoa): The euglenoids are represented in the toxicological literature by only 

one study on Euglena gracilis (Table 15; Thuillier-Bruston et al. 1996). The authors report a 50% 

inhibition of photosynthesis at 496 μg/L. 

Unikonts (Amebozoa): The Unikonts are a lineage that includes fungi, amoebae, collaredflagellates and animals (Table 15). There are a great number of studies on animals, which are 

discussed in Section 6.2 of this problem formulation; however, only one aquatic single species 

test is available from the remainder of the Unikonts. This study on an amoeba reported an LD50

greater than 100 μg/L (Prescott and Olson 1977).
42

6.1.3. Toxicity to Aquatic Vascular Plants 

Archaeoplasida (Embryophyta): Single-species aquatic plant toxicity studies will be used as one 

of the measures of effect to evaluate whether atrazine may affect primary production and 

diversity in aquatic ecosystems. Numerous aquatic vascular plant toxicity studies have been 

submitted to EPA and/or have been published in the open literature. Appendix B includes a 

more comprehensive list of the available data. 

Freshwater vascular plants are as sensitive or more sensitive to atrazine as freshwater nonvascular plants, with the most sensitive vascular plant EC50 value of 0.001 μg/L, based on 

biomass reduction in Elodea (McGregor et al. 2008) (Table 15). The available estuarine/marine 

toxicity data for aquatic vascular plants show less sensitivity than from fresh water studies, 

with 50% mortality of Vallisneria Americana at 12 μg/L from a 47-day study (Correll & Wu 

1982). 

The most sensitive single species data for aquatic vascular plants from either supplemental or 

acceptable studies (Table 15) will be used for risk characterization purposes only and will not be 

used for quantitative purposes such as use in risk quotient calculation. 

6.1.4. Toxicity to Aquatic Plant Communities 

While reviewing this section, please consider the charge question below. 

SAP Question: 

 The cosms were comprised of natural communities of periphyton/phytoplankton; 

in some cases, vascular plants, invertebrates and vertebrates present in those 

communities were included in the study (Chapter I, Section 6.1.4). These sources 

were generally described as streams, lakes, reservoirs, and springs, and are 

considered to be representative of the structure and function of aquatic plant 

communities in such water bodies. Given the diversity of sources and the described 

communities, please comment on the extent to which these cosm studies taken 

together provide useful and reasonable physical models of the natural aquatic plant 

communities exposed to atrazine in the U.S. 

In addition to reviewing the toxicity data for individual species, the toxicity of atrazine to 

aquatic plant communities is evaluated. Concentrations of atrazine that affect plant 

productivity and community structure typically occur at levels lower than those that directly 

intoxicate fish and aquatic invertebrates. This focus is required to ensure that the atrazine 

concentrations in watersheds do not cause significant changes in aquatic plant community 

structure and productivity and thus put at risk the food chain and entire ecosystem integrity. In
43

this approach single-species plant toxicity data and cosm studies (Appendix D) will be used to 

determine what atrazine exposure patterns and concentrations are likely to result in adverse 

effects to aquatic plant communities. From these data, a LOC will be developed, which together 

with monitoring data can be used to identify watersheds where atrazine levels need to be 

mitigated consistent with the 2003 Memorandum of Agreement (USEPA 2003b) signed by the 

EPA and Syngenta. While the LOC is based on effects to aquatic plant communities by ensuring 

protection of primary producers, it is intended to provide protection for the entire aquatic 

ecosystem including fish, invertebrates, and amphibians. 

Potential effects of atrazine on plant communities have been evaluated using available cosm 

studies (Appendix D). Cosm studies conducted with atrazine provide measurements of primary 

productivity that incorporate the aggregate responses of multiple species in aquatic plant 

communities. Because plant species vary widely in their sensitivity to atrazine, the overall 

response of the plant community may be different from the responses of the individual species 

measured in laboratory toxicity tests. Cosm studies allow observation of population and 

community recovery from atrazine effects and of indirect effects on higher trophic levels. In 

addition, cosm studies, especially those conducted in outdoor systems, incorporate 

partitioning, degradation, and dissipation, factors that are not usually accounted for in 

laboratory toxicity studies, but that may influence the magnitude of ecological effects. 

The review of the cosm studies (Appendix D) included the establishment of criteria for 

selection. First, all studies were prescreened. The screen requires that: (1) treatments were 

exposed to only atrazine, and not mixtures or multi-active ingredients, (2) exposure 

concentrations were reported, (3) measured effects were specific to aquatic plant communities 

(defined as two or more species), and (4) the study was written in English. If any of these four 

criteria were not met the study was no longer considered for use. 

Studies that met the basic elements of the prescreen criteria were further screened using 

additional quality criteria. Criteria included basic elements such as use of controls and use of at 

least two replicates per treatment group. The accepted studies were then used as the basis for 

deriving the initial atrazine Level of Concern (LOC) (See Chapter III for complete details on the 

LOC Methodology). The acceptance criteria presented in Appendix D are intended to identify 

studies with confounding study design and performance elements to allow greater confidence 

in the study results. The criteria were derived using peer reviewed sources from U.S. EPA, 

SETAC (Society of Environmental Toxicology and Chemistry), and OECD (Organization for 

Economic Co-operation and Development) (Giddings et al. 1999; OECD, 2004; U.S. EPA, 2004). 

A total of 35 cosm studies were originally included in the 2003 IRED (USEPA 2003c), and an 

additional 38 cosm studies were identified in the May 2009 SAP for a total of 73 studies. After 

the prescreening and acceptance criteria were applied to the 73 studies, 31 of the original 35 

studies passed the screen and were presented in the IRED and 15 of the 38 studies 

recommended for consideration in the May 2009 SAP report (46 total studies). Citations of all 

73 cosm studies considered can be found in Appendix D. 
44

A total of 87 endpoints were used in the analysis to develop the level of concern for atrazine. 

These endpoints came from the 46 studies that passed the prescreening and acceptance 

criteria. Effects observed in the cosm studies included changes in aquatic plant biomass, 

chlorophyll a concentration, photosynthesis rate (14C uptake, oxygen production), and shifts in 

aquatic plant community structure (e.g. species composition and diversity) relative to a control. 

The durations of these studies ranged from a few weeks to several years at constant or variable 

and declining exposure concentrations ranging from 0.1 μg/L to 10,000 μg/L. Most of the 

studies focused on atrazine effects on phytoplankton, periphyton, and macrophytes; however, 

some also included measurements on animals. Although most studies did not provide the 

identity of the phytoplankton, periphyton or zooplankton, those that did report it showed that 

a great diversity of taxa were tested (Table 16). The numbers provided in Table 16 only reflect a 

subset of the microorganism diversity tested. Estimates from some studies suggest that there 

were 150-200 microorganism species present in a single mesocosm sourced from lake water 

(e.g., Pratt et al. 1988). It is assumed that these studies represent natural communities and the 

breadth of diversity found in North American freshwater environments. A summary of all cosm 

endpoints used in the analysis is presented in Appendix D. 
45

Table 16: The taxonomic distribution of reported species in COSM studies. See Figure 5 and discussion in Section 

6.1.2 for representatives of these taxonomic groups and relationships between them. These numbers represent 

only approximations of those taxa that were identified to genera and/or species. Appendix G.f. contains details on 

which COSM studies contained these taxa.

Taxonomic Group Genera Species

EUBACTERIA: CYANOBACTERIA:

(Blue-Green Algae)

14 27

EUKARYOTES

ARCHAEOPLASTIDA GREEN PLANTS:

EMBRYOPHYTA: 

(Non-Vascular Land Plants)

- -

EMBRYOPHYTA: (Vascular Land Plants) 11 20

CHLOROPHYTA and STREPTOPHYTA: 

(Green Algae)

43 86

PRASINOPHYTA: 

(Prasinophytes)

1 1

CHROMALVEOLATES HACROBIA: 

HAPTOPHYTA:

(Coccolithophorads)

2 4

CRYPTOPHYTA: 

(Cryptomonads)

4 13

STRAMENOPILES: 

BACILLARIOPHYTA:

(DIATOMS)

24 67

CHRYSOPHYTA:

(Golden Algae)

7 12

XANTHOPHYTA:

(Yellow-Green Algae)

2 2

AVEOLATES:

PYRROPHYCOPHYTA (Dinoflagellates): 4 4

EXCAVATES EUGLENOZOA:

(Euglenoids)

1 1

UNIKONTS FUNGI: 2 2

CHOANOFLAGELLIDA: 3 3

ANIMALS:

VERTEBRATES: 9 15

INVERTEBRATES: 137 196
46

Effects in the cosm studies were scored using a binary effect/no effect score. In previous 

analyses, the cosm studies were assigned Brock scores, which is a 5-point effects scoring 

system. A Brock score of 1 was assigned to studies that did not produce an effect and a Brock 

score of 5 was assigned to studies that produced clear effects without recovery for 56 days or 

more. Studies with Brock scores of 1 (no effect) or 2 (slight or transient effect) were 

distinguished from studies assigned 3 (clear effect with recovery) or higher for the LOC analysis. 

Functionally, the binary effects scoring is identical to the manner in which Brock scores were 

used (Brock scores of 1 and 2 were considered no effects and Brock scores of 3 or higher were 

considered to be effects). However, in response to recommendations by the 2009 SAP (USEPA 

2009a), all Brock scores were re-evaluated to ensure that each endpoint was categorized into 

the appropriate “effect” or “no effect” group. A binary effect/no effect system was considered 

to be more clear and transparent, which is the reason for adopting it for this analysis. 

Recovery from the effects of atrazine and the development of resistance to the effects of 

atrazine in some vascular and non-vascular aquatic plant species have been reported in both 

single species studies and cosm experiments and may add uncertainty to these findings. 

However, reports of recovery are often based on differing interpretations. For the purposes of 

this assessment, recovery is defined as a return to pre-exposure levels for the affected 

individual, population or community, not for a replacement population or community of more 

tolerant species. 

6.1.5. Biological Relevance: The Importance of Biodiversity and Plant Communities 

“Biological diversity can be defined as the variety of life and its processes. This definition 

encompasses genetic, species, assemblage, ecosystem and landscape levels of biological 

organization and it has structural, compositional and functional components” (Hughes & Noss 

1992). A recently published review of North American phytoplankton species richness (Stomp 

et al. 2011), based on the total number of species collected during surveys from 1973-1975 for 

the EPA National Eutrophication Survey, shows that phytoplankton diversity is greatest (Figure 

6) throughout the southeastern and isolated areas of the Midwest. This survey, while pointing 

out that there is higher phytoplankton diversity in the regions with atrazine use, does not 

answer critical questions regarding community structure, function and food web stability, nor 

does it address if the sampled lakes were previously exposed to atrazine or if the species 

present are known to be tolerant to atrazine. 
47

Figure 6. Geographical distribution of phytoplankton species richness across the continental 

United States (Stomp et al. 2011, reproduced with permission).

The complexity of species coexistence in phytoplankton communities is thought to be directly 

related to primary productivity (Leibold 1996), light availability (Huisman et al. 2004; Steinman 

1992; Hill et al. 1995), and nutrient supply ratios (e.g., Nitrogen:Phosphorus ratios, Tilman 

1982). Atrazine has the potential to affect all three of these factors and thus have a negative 

impact on the primary producers, their associated food webs, and overall ecosystem function 

and integrity. Negative impacts leading to instability or harm to the aquatic plant communities 

would impact aquatic and terrestrial species, which are supported by the aquatic plant 

communities for their growth, survival, and reproduction in a complex network of interactions. 

Decreased diversity may lead to increased nutrient and toxicant outflow to larger streams 

and lakes. 

Cardinale (2011) reported that in stream systems niche partitioning among species of algae can 

increase the uptake and storage of nitrate. His research also showed that more than 80% of 

increased cell densities in cultures were driven by niche complementarity in microcosms. 

Cardinale’s research provides “direct evidence that communities with more species take 

greater advantage of the niche opportunities in an environment and this allows diverse systems 

to capture a greater proportion of biologically available resources”. Cardinale also showed that 

when niche partitioning was removed or reduced to minimal levels, the periphyton 

communities collapsed to single species dominance. Cardinale attributes the niche partitioning 

in streams to specific algal characteristics that make them “best adapted” to specific habitats 

within the stream. “These adaptations were expressed only when environmental conditions 

were dynamic in space and or time and when heterogeneity provided ecological opportunities 

for species to coexist.” Some of the adaptations included sheer resistance for high flowing 

water, large filamentous algal dominance in slow moving waters, and increasing growth rate 

with habitat disturbance. 
48

This concept was also tested by Villeneueve et al. (2011) who concluded that increased 

turbulence led to more diversity in periphyton communities. Villeneueve et al. also found that 

the higher diversity periphyton communities were more sensitive to the tested pesticides 

(diuron and azoxystrobin) than less diverse communities. This is likely due to the 

interconnectivity of diversity and niche partitioning causing a more dramatic loss of species 

richness in higher diversity systems. The second factor to consider regarding low diversity 

systems is that they may be comprised of highly tolerant species that are less likely to be 

affected by the pesticide exposure, while a high diversity system would contain a much greater 

proportion of sensitive species. In low diversity systems made up of sensitive species, the effect 

could be great as well. These response phenomena have a potential to greatly impact food web 

stability. 

Food web stability is directly linked to diversity, number of trophic levels, and both top-down 

and bottom-up pressures. 

The aquatic food web is centered around and dependent upon aquatic plant communities 

(including all autotrophic organisms). These communities are the primary producers and 

provide sugar energy, lipids, as well as macro- and micronutrients to the herbivore taxa (e.g., 

insects, snails, fish, tadpoles, and waterfowl). In highly diverse and productive aquatic plant 

communities, high quality food is usually abundant, whereas in productive low diversity 

systems, there may be limited high quality food resources available to herbivores. 

The population sizes of the taxa comprising the primary producer community are greatly 

dependent on abiotic conditions (bottom-up pressure; e.g., light and nutrients) and the size and 

condition of the herbivore and predator communities (top-down pressure; e.g., snail 

populations). Steinman (1992) found that limitation of periphyton photosynthesis could be 

mitigated by increasing the levels of light. The effect of light limitation on productivity is well 

documented. For example, seasonal decreases in available light have been shown to lead to 

reduced productivity (Triska et al. 1983; Hill and Harvey 1990; Hill et al. 2001). The algae in the 

Hill et al. (1995) study were reported to adapt to the low light condition over time, but 

productivity was 4 times greater in high light conditions. The control of autotrophic 

communities by grazing pressure has also been a focus of research, and several studies show 

that the top-down pressures are most apparent in short food webs (i.e., producers and a single 

consumer; e.g., Steinman et al., 1987; McQueen et al., 1989; Steinman, 1992; Kurle and 

Cardinale, 2011). Steinman (1992) found that herbivore control was so complete that autotroph 

biomass could not respond to increases in the levels of light and that when grazing pressure 

was released, the controlling factors shifted back to abiotic factors (i.e., seasonality and light). 

Hill et al. (2001) found that nutrient concentrations (nitrate and phosphate) increased in 

streams after overstory leaf emergence, which they attributed to a “cascade of shade effects” 

through the reduction of primary producer communities, resulting in additional abiotic 

components available to the other portions of the ecosystem. Because herbivore growth 

increased almost linearly with increased light, reflecting food supply limitation at low light, the 

cascade of shade effects ultimately led to decreased herbivore densities. The effects of low-
49

light on the primary productivity of the system can be synergistic with the effects of herbivore 

grazing pressure. Higher grazing pressure also reduces algal communities and diversity and is 

more pronounced in low light conditions (e.g., Steinman, 1992; Hill et al., 1995), especially after 

shifts from higher light to lower light (i.e., herbivore populations would be higher due to 

increased food resources in the high light condition, and would demand the same energy input 

from the lower productivity of the low light condition). 

Other impacts on the food web come from another type of top-down pressure, the predatorherbivore interaction. Kurle and Cardinale (2011) report that higher diversity and productionto-biomass ratios in the autotrophic communities reduce the strength of trophic cascades. 

Therefore, in systems with high algal diversity, herbivores have a greater ability to evade or 

defend against predators, so that herbivore pressure on the primary producers is more even 

over time. However, low diversity systems have a propensity to have increased top-down 

pressure and would be more erratic in behavior and more prone to collapse when stressed 

(Steinman, 1992; Kurle and Cardinale, 2011). 

In addition to food, shelter, and reproduction, there are documented symbiotic relationships 

between algae and invertebrate and vertebrate species (e.g., Douglas, 2010; Oliver and Moon, 

2010; and Kerney, 2011). These symbiotic relationships present additional uncertainty 

regarding the impact of atrazine on these relationships. 

Importance of the Biological integrity of headwater streams, lakes, wetlands and estuaries: 

Meyer et al. (2007) summarize the importance of small streams and springs to the entire river 

system and discuss the ways they enhance the biological diversity of the entire river system. 

Headwater streams play a critical role in the export of food (e.g., drifting insects; benthic 

organisms, and emerging insects), they provide a filtration process which increases dissolved 

oxygen through photosynthetic output, reduces particulate matter (macrophytes), and provides 

critical nutrient transformations which increase downstream water quality. In addition to these 

exports, the larger river, lake, and reservoir organisms also depend on the headwaters for 

refuge (e.g., high flow events, thermal events, predation and competition) and rich feeding 

sites for spawning and nursery habitat (Meyer et al., 2007). While the study by Meyer et al.

(2007) was focused on the headwater stream, these same exports and downstream 

dependencies are common to lakes, wetlands and estuaries. 

The focus of the assessment endpoints presented in Section 6.1.4 is required to ensure that the 

atrazine concentrations in watersheds do not cause significant changes to the freshwater 

aquatic plant community (used as a surrogate for estuarine/marine plant communities) 

structure and productivity and thus put at risk the food chain and entire ecosystem health. 
50

6.2. Effects to Animals 

6.2.1. Toxicity to Terrestrial Animals 

6.2.1.1. Toxicity to Birds, Reptiles and Terrestrial Phase Amphibians 

Effects data for acute and chronic bird, terrestrial-phase amphibian, and reptile data, including 

data published in the open literature, are summarized in the following sections. Additional 

studies and details on the studies summarized below are included in Appendix B. As specified 

in the Overview Document, EPA uses birds as a surrogate for terrestrial-phase amphibians and 

reptiles when sufficient toxicity data for each specific taxonomic group are not available (U.S. 

EPA, 2004). 

6.2.1.1.a. Birds: Acute Exposure (Mortality) Studies 

The available data in birds suggest that atrazine is slightly toxic to avian species on an acute oral 

exposure basis. For parent atrazine, the lowest reported acute oral LD50 is 783 mg/kg-bw 

(bobwhite quail, Colinus virginianus) (MRID 00024721). The previous Data Evaluation Record 

(DER), which reported the study authors’ LD50 result, was recalculated using the current EFED 

methodology. In addition, as this study was conducted using 14-day old birds as oppose to 

typically adult birds. For an atrazine formulation in which the resulting LD50 values were >2,000 

mg/kg-bw (1520 mg a.i./kg), signs of poisoning in mallards (Anas platyrhynchos) first appeared 

1 hour after treatment and persisted up to 11 days ,and in ring-necked pheasants, (Phasianus 

colchicus), remission of signs of intoxication occurred by 5 days after treatment (U.S. EPA, 

2003a; MRID 001600-00). Signs of poisoning included weakness, hyper-excitability, ataxia, and 

tremors; weight loss also occurred in mallards. 

An acute oral toxicity study with passerines is not available for atrazine. 

Because all subacute avian LC50 values are greater than 5,000 mg/kg-diet, atrazine is 

categorized as practically non-toxic to avian species on a subacute dietary basis. In the subacute 

dietary study in mallard ducks (A. platyrhynchos), 30% mortality was observed at the highest 

test concentration of 5,000 mg/kg-diet (MRID 00022923); one mortality was observed in the 

Japanese quail (Coturnix japonica) study at 5,000 mg/kg-diet. The time to death was Day 3 for 

the one Japanese quail (C. japonica) and Day 5 for three mallard ducks (U.S. EPA, 2003a; MRID 

00022923 and 0002292; J. Spann at Patuxent Wildlife Center, 1999, personal communication). 

Four species of birds were tested in Hill et al., (1975) (MRID 00022923) study; however, control 

performance for the tests was not reported. In addition, the treated feed was not analyzed for 

stability. 
51

6.2.1.1.b. Birds: Chronic Exposure (Growth, Reproduction) Studies 

Reproduction studies in birds have reported effects at atrazine concentrations of 75 mg a.i./kgdiet and higher. Both northern bobwhite quail (C. virginianus) and mallard duck (A. 

platyrhnchos) reproduction studies were conducted using atrazine. Stability or homogeneity in 

the test feed was not analyzed for either study and therefore, there is uncertainty in the dietary 

exposure concentration. In the northern bobwhite study, the following endpoints were affected 

at 675 mg a.i./kg-diet: egg production and embryo viability, and a reduction in weight gain in 

the males (MRID 42547102). The number of cracked eggs in the control was about three times 

the typical value reported in the 850.2300 guideline. The NOAEC in the bobwhite study was 225 

mg a.i./kg-diet. In the mallard study, at a concentration of ≥225 mg a.i./kg-diet, there were 

effects on egg production; hatchability, male weight gain and food consumption were affected 

at 675 mg a.i./kg-diet (MRID 42527101). Hatchling weight was significant at all concentrations 

tested, 7.5-13% decrease at 75 to 675 mg a.i./kg-diet. 

6.2.1.1.c. Birds: Sublethal Effects 

Japanese quail (C. japonica) body weights (absolute) were reduced at atrazine concentrations of 

25 mg/kg-bw after receiving an oral daily dose of 35% (w/w) atrazine for 45 days (Hussain et al., 

2011; E153875). Feed consumption was reduced at concentrations of 50 mg/kg-bw. The name 

and type of formulation used in the study was not reported. 

6.2.1.2. Reptiles 

Limited data are available for reptiles, and there were no available data for terrestrial phase 

amphibians. 

Atrazine was tested on eggs of the red-eared slider turtle (Trachemys scripta elegans) and the 

American alligator (Alligator mississippiensis) to determine if atrazine produced endocrine 

effects on the sex of the young (Gross, 2001). The turtle and alligator eggs were placed in nests 

constructed of sphagnum moss treated with 0, 10, 50 100 and 500 μg/L for 10 days shortly after 

being laid. No adverse effects were found. Analysis of the embryonic fluids indicated that no 

atrazine was present in the eggs at the detection limit (0.5 μg/L) (MRID 455453-03 and 455453-

02). 

Two additional open literature studies in which snapping turtle (Chelydra serpentine) and 

alligator eggs (Alligator mississippiensis) were exposed to atrazine either via direct application 

or incubation in soil treated with atrazine were available (De Solla et al., 2006 and Crain et al., 

1999). In the snapping turtle study some males with testicular oocytes and females were 

produced in the atrazine-treated groups (3.3 – 3.7%), but not in the control group; however, no 

statistical differences were found among the treatment and control groups. For the alligator 

study, no differences in gonadal and reproductive tract histology or hepatic aromatase activity 
52

were observed in any of the atrazine-treated or control alligators. These studies are described 

further in Appendix B.

Toxicity data for terrestrial-phase amphibians are discussed in the amphibian section (Section 

7). 

6.2.1.3. Toxicity to Mammals 

Atrazine acute and chronic toxicity values for mammals are presented below. 

The mammalian LOAEL in reproduction toxicity studies was 500 mg/kg-diet based on significant 

reductions in adult rat body weight and adult food consumption (NOAEL 50 mg/kg-diet) (U.S. 

EPA, 2003a; MRID 40431303). 

6.2.1.3.a. Mammals: Acute Exposure (Mortality) Studies 

The acute oral LD50 value for parent atrazine in the rat (Rattus norvegicus) is 1,869 mg/kg-bw 

(MRID 00024709). 

6.2.1.3.b. Mammals: Reproduction Toxicity Studies 

Typically a 2-generation reproduction study is used to evaluate chronic toxicity to wild 

mammals and the study conducted using the rat (Rattus norvegicus) (MRID 40431303) 

described below has been used in previous evaluations; however, additional 

reproduction/developmental toxicity data are now available for atrazine (U.S. EPA, 2011a). The 

reviews for this available data will be evaluated to determine if there is additional relevant 

reproduction data for evaluating chronic risk to mammals. In the 2-generation reproduction 

study (MRID 40431303), technical grade atrazine was administered to rats (Rattus norvegicus) 

30/sex/dose) in the diet at concentrations of 0, 10, 50, and 500 mg/kg-diet. Parental body 

weights, body weight gain, and food consumption were statistically significantly reduced at the 

500 mg/kg-diet dose in both sexes and both generations throughout the study. Compared to 

controls, body weights for F0 males and females at 70 days into the study were decreased by 

12% and 15%, respectively, while F1 body weight for the same time period was decreased by 

15% and 13% for males and females, respectively. The only other parental effect, which may 

have been treatment related was a slight, but statistically significant increase in relative testes 

weight, occurring in both generations of the high dose. There did not appear to be any 

reproductive effects from compound exposure. Measured reproductive parameters from both 

generations did not appear to be altered in a dose-related manner. The LOAEL was 500 mg/kgdiet (39 mg/kg/day in males, 43 mg/kg/day in females) based on decreased body weights, body 

weight gains, and food consumption. The NOAEL was 50 mg/kg-diet (3.8 mg/kg/day in males, 

and 3.7 mg/kg/day in females). 
53

6.2.1.4. Toxicity to Terrestrial Invertebrates 

Atrazine is practically non-toxic to honey bees (Apis mellifera L.); the reported LD50 value is >97 

μg/bee with 5% mortality reported at the highest dose tested (MRID 00036935). Atrazine also 

did not cause adverse effects in fruit flies (Drosophila melanogaster), houseflies (Musca 

domestica), and mosquito larvae (Aedes aegypti) exposed to 15 μg/fly (Lichtenstein et al., 

1973). LC50 values in earthworms ranged from 273 to 926 ppm soil (Mosleh et al., 2003; Haque 

and Ebing, 1983). Atrazine did not produce statistically significant (p>0.05) adverse effects in 

studies on several beetle species at any level tested, which ranged from application rates of 

approximately 1 lb a.i./Acre to 8 lbs a.i./Acre (Kegel, 1989; Brust, 1990; Samsoe-Petersen, 

1995). 

The most sensitive terrestrial invertebrate species tested was the springtail (Onychiurus 

apuanicus and O. armatus). Exposure to O. apuanicus at 2.5 ppm resulted in 18% mortality, and 

exposure to O. armatus at 20 ppm resulted in 51% mortality (Mola et al., 1987); lower levels 

were not tested. These soil concentrations are associated with an application rate of 

approximately 1 lb a.i./Acre and 7 lbs a.i./Acre, respectively, assuming a soil density of 1.3 

grams/cm3 and a soil depth of 3 cm. Additional details for these studies may be found in 

Appendix B. 

6.2.2. Effects to Aquatic Animals 

A brief summary of submitted and open literature data considered relevant to the ecological 

risk assessment is presented below. Additional information is provided in Appendix B. 

6.2.2.1. Toxicity to Fish 

A summary of acute and chronic fish data, including data from the open literature, is provided 

in the following sections. Additional information is included in Appendix B. 

6.2.2.2. Acute Exposure (Mortality) Studies 

Atrazine toxicity has been evaluated in numerous fish species, and the results of these studies 

demonstrate a wide range of sensitivity. LC50 values range from 2,000 to 60,000 μg/L (2 mg/L 

to 60 mg/L (See Appendix B for additional details on these studies). Therefore, atrazine is 

classified as moderately to slightly toxic to fish on an acute basis. 
54

Parent Atrazine 

Freshwater Fish 

Acute toxicity data for freshwater fish are available for at least 8 different species. The most 

sensitive freshwater fish acute study is the rainbow trout with an 96-hour LC50 of 5,300 μg 

a.i./L, which appears to be based on nominal concentrations (MRID 43344901). The test 

solutions were renewed every 24 hours and the loading was calculated as 0.37 g/L. In this 

study, the fish exhibited a dose-response change in coloration (darkening) for 48 hours after 

test initiation (data not reported). Other than temperature, water quality parameters such as 

dissolved oxygen were not reported in this static study; the dilution water was aerated prior to 

dosing and was renewed every 24 hours. 

Estuarine/marine Fish 

Atrazine toxicity data have been submitted for two estuarine/marine fish species: sheepshead 

minnow and spot (Leiostomus xanthurus). A sheepshead study (MRID 45208303; 45227711; 

LC50 = 2,000 μg a.i./L) and the spot study (MRID 45202920; LC50 = 8,500 μg a.i./L) only reported 

the LC50 value with no summary mortality data reported. In addition, in the sheepshead study 

the fish were fed at 48-hours which the reviewer indicated that the fish were ca. 48 hours old 

at test initiation and withholding food for 96 hours was not appropriate. Another sheepshead 

minnow acute study reported an 96-hour LC50 of 13,400 μg a.i./L, based on measured 

concentrations (MRID 00024716). At concentrations of 4,600 μg a.i./L and greater, fish in this 

study exhibited sublethal effects such as loss of equilibrium, surfacing and extended abdomen. 

 Atrazine Formulations 

Toxicity studies using atrazine formulations are available for freshwater fish. The acute LC50

values range from 12,600 to 42,000 μg a.i./L and are classified as slightly toxic. Based on 

comparison of acute toxicity data for technical grade atrazine and formulated products of 

atrazine, it appears that freshwater fish are more sensitive to the TGAI. Acute studies with 

atrazine formulations for estuarine/marine fish were not available. 

6.2.2.3. Chronic Exposure (Growth/Reproduction) Studies 

Chronic freshwater fish toxicity studies will be used to assess potential effects to fish and 

aquatic phase amphibians via potential effects to growth and reproduction. Freshwater fish 

early life-stage and life-cycle studies, as well as early-life stage studies for estuarine/marine fish 

for atrazine are available and summarized in Appendix B. 
55

Freshwater Fish 

Several early life-stage (ELS) and life-cycle studies were available for freshwater fish using 

parent atrazine as well as ELS studies with atrazine formulations. For two of the ELS studies 

with rainbow trout (Oncorhynchus mykiss) and channel catfish (Ictalurus punctatus) the studies 

did examined an early life-stage however the study durations were too short to capture chronic 

exposure, with test durations of 27-d (4-d post hatch) and 8-d (4-d post hatch), respectively 

(MRID 45202902). Another ELS study was conducted with rainbow trout (86-d duration) with a 

reported NOAEC and LOAEC of 410 and 1,100 μg/L, respectively, based on delayed hatching and 

reduced weight (MRID 45208304). However, this study was conducted with the solvent 

dimethylsufoxide (DMSO) which can promote movement of chemicals across membranes. It 

also appears that only one replicate tank was used per concentration and if more were used, 

then variability within a treatment group was not reported. In the last available ELS study, 

zebrafish (Brachydanio rerio) were exposed for 35 days, and the reported NOAEC and LOAEC 

was 300 and 1,300 μg/L, respectively (MRID 45202908); raw data was not available. 

In addition to the ELS studies, there were several life-cycle fish studies conducted with atrazine. 

A 44-week study using brook trout (Salvelinus fontinalis) resulted in the most sensitive NOAEC, 

65 μg a.i./L based on growth (MRID 00024377). Upon reexamining this study for the problem 

formulation, several concerns with this study were identified: 1) it appears the study did not 

use a solvent control although DMSO was used in the atrazine concentrations; therefore, 

potential solvent effects could not be evaluated; 2) the use of DMSO is discouraged as it can 

promote movement across membranes; 3) following distribution to the test chambers, the fish 

were treated with malachite green and formalin (25 μg/L of formalin containing 3.7 g/L 

malachite green) to prevent further disease (disease was observed prior to distribution to the 

tanks when the fish were treated at that time); and 4) according to the authors, variability in 

the reproduction endpoint was highly variable which precluded the ability to ascribe statistical 

significance to treatment groups that appeared to have reduced values. This variability may 

have been potentially enhanced by the use of only two replicates during the reproduction 

phase. The other chronic studies reported in MRID 00024377, bluegill sunfish (Lepomis 

macrochirus) and fathead minnow (Pimephales promelas), also appeared to use DMSO without 

a solvent control. In the bluegill study, the percent survival in the F1 generation was 22% after 

30 days, and according to the authors the spawning was too sporadic to be conclusive. Control 

survival in the fathead minnow (Pimephales promelas)) after 30 days was 47-60%. Another 

chronic fathead minnow life-cycle study, MRID 42547103, resulted in a non-definitive NOAEC 

(<150 μ/L) as growth in the F1 generation was significantly lower in all treatment groups 

compared to the negative control. 

Short-term reproduction studies for freshwater fish were also available in which reproduction 

in adult fish was monitored for several weeks. These studies were conducted using mature 

actively-spawning fish to evaluate reproduction and did not capture exposure to embryo or 

larval stages. Adult fathead minnows (Pimephales promelas) were exposed to atrazine (5 and 

50μg/L) or 21-day with estradiol as a positive control (Brignole et al. 2004). While not 
56

statistically significant, the study authors reported a dose-dependent trend for percent 

embryos fertilized, male gonad-somatic index (GSI) and testicular maturity. 

A 30-d short-term reproduction study with fathead minnow using atrazine reported effects on 

reproduction (total number of eggs, and number of spawns) as well as alterations in ovarian 

maturation compared to the control (Tillitt et al., 2010). These adverse effects were reported at 

a concentration of ≥0.5 μg/L; however, an apparent threshold response was observed as similar 

results were obtained at 0.5 and 5.0 μg/L. The raw data for this study was provided, and this 

study will be evaluated for possible inclusion in the atrazine risk assessment. 

Estuarine/marine fish 

Two chronic toxicity tests with sheepshead minnow were available. The study with the most 

sensitive NOAEC was a 28 days post hatch early life-cycle study with a NOAEC value of 1,100 μg 

a.i./L based on growth; this study was classified as acceptable (MRID 46648203 and 46952604). 

6.2.2.3.a. Sublethal Effects and Additional Open Literature Information 

In addition to registrant-submitted studies, data from the open literature that reported

sublethal effect levels to freshwater fish were also evaluated. A number of open literature 

studies were reviewed as part of the 2003 IRED. The results of these studies, which showed

sublethal effects to olfaction, behavior, kidney histology, and tissue growth at atrazine 

concentrations ranging from 0.1 to 3,000 μg/L (Appendix B). In addition, the risk assessment for 

the California red-legged frog (CRLF) (U.S. EPA, 2009b) also identified open literature studies 

reporting sublethal effects. Prior to conducting the atrazine risk assessment for registration 

review, another open literature search may be completed (via ECOTOX) and additional studies 

reporting sublethal effects may be reviewed at that time. A summary of studies reviewed in 

CRLF assessment is presented below. 

The reported sublethal effects included a change in plasma vitellogenin in male and female 

rainbow trout and plasma testosterone in males at atrazine concentrations of ca. 50 μg/L (MRID 

45622304). Effects on fish behavior, including preference for the dark part of aquarium (MRID 

45204910), grouping behavior (MRID 45202914), as well as alterations in trout kidney histology 

(MRID 45202907) have been reported at atrazine concentrations of 5 μg/L. In salmon (Salmo 

salar), smolt gill physiology, represented by changes in Na-K-ATPase activity was altered at 2 

μg/L (Waring and Moore, 2004) with similar effects observed at 0.5 μg/L (Moore et al., 2007). 

Survival was evaluated after transfer to full salinity sea water (33 ‰) in Waring and Moore 

(2004). Atrazine exposure for 5 to 7 days in freshwater followed by transfer to full salinity sea 

water resulted in higher mortality at atrazine concentrations of 14 μg/L (14 % mortality) and 

higher mortality in one study at 1 μg/L (15 % mortality) and higher mortality in a separate 

experiment presented in the publication (no controls died; statistical significance was not 

indicated). The salinity used by Waring and Moore (2004) simulated full strength seawater (33 

%). 
57

Tierney et al. (2007) studied the effect of 30-minute exposure to atrazine on behavioral and 

neurophysiological responses of juvenile rainbow trout to an amino acid odorant (L-histidine at 

10-7 M, which had been shown to elicit an avoidance response in salmonids). Although the 

study authors concluded that L-histidine preference behavior was altered by atrazine at 

exposures > 1 μg/L, no significant decreases in preference behavior were observed at 1 μg/L, 

nor was a dose response relationship observed. Hyperactivity (measured as the number of 

times fish crossed the center line of the tank) was observed in trout exposed to 1 and 10 μg/L 

atrazine. In the study measuring neurophysiological responses following atrazine exposure, 

electro-olfactogram (EOG) response was significantly reduced (EOG measured changes in nasal 

epithelial voltage due to response of olfactory sensory neurons). 

Although these studies raise questions about the effects of atrazine on plasma steroid levels, 

behavior modifications, gill physiology, and endocrine-mediated functions in freshwater and 

anadromous fish, it is not possible to quantitatively link these sublethal effects to the selected 

assessment endpoints for the assessed species (i.e., survival, growth, and reproduction of 

individuals). Also, effects on survival, growth, or reproduction were not observed in the 

available life-cycle studies at concentrations that induced these reported sublethal effects. 

Further details on sublethal effects are provided in Appendix B. 

6.2.2.4. Toxicity to Aquatic Invertebrates 

A summary of acute and chronic freshwater invertebrate data, including data published in the 

open literature, is provided below in the following sections.

6.2.2.4.a. Acute Studies 

Atrazine toxicity has been evaluated in numerous aquatic invertebrate species, and the results 

of these studies demonstrate a wide range of sensitivity. Definitive EC/LC50 values range from 

48 to 30,000 μg/L (0.048 mg/L to 30 mg/L), with several other studies reporting non-definitive 

EC/LC50 values >4,900 to >100,000 μg/L (see Appendix B for additional details on these studies). 

Therefore, atrazine is classified as highly to slightly toxic to aquatic invertebrates on an acute 

basis. 

Parent Atrazine 

Freshwater Invertebrates 

There are many acute toxicity studies using atrazine for freshwater invertebrate species with a 

range of toxicity values. The acute LC/EC50 values range from 720 to greater than 30,000 μg 

a.i./L. For the available studies, while acute LC/EC50 values are reported, summary data for the 

controls and individual treatment groups are not reported. Therefore, verification of the 
58

reported LC/EC50 values could not be determined. Also, for some studies, details on the test 

design and/or environmental conditions were not well documented. The most sensitive value is 

for the midge, Chironomus tentans, with a 48-hour LC50 value of 720 μg a.i./L (MRID 00024377). 

A sediment toxicity test with whole sediment was available for Chironomus tentans (MRID 

45904002). The study was a 10-day static-renewal study using spiked sediment. The NOAEC and 

LOAEC, based on dry weight, was 24 and 60 mg a.i./kg based on mean measured sediment 

concentrations, respectively, and 4.0 and 21.5 mg a.i./L based on mean measured pore-water 

concentrations. 

Estuarine/marine Invertebrates 

As with the freshwater invertebrates, there are many acute toxicity tests available for 

estuarine/marine invertebrates, and like the freshwater invertebrate studies, the studies 

primarily only report LC/EC50 values with no documentation of test concentration toxicity data. 

The reported range of acute LC/EC50 values for estuarine-marine organisms range from 48 to 

13,300 μg/L, with several non-definitive endpoints. The most sensitive organism tested was the 

juvenile estuarine/marine shrimp, Neomysis integer (LC50 of 48 μg/L; Noppe et al. 2007); only 

the LC50 value was reported, so the results could not be confirmed and control mortality was 

unknown. 

A 10-d sediment toxicity test with the clam, Mercenaria mercenaria, was available in the open 

literature (Lawton et al. 2006; E89627). This study reported no effects on survival, mass and size 

at atrazine concentrations of ≤20,000 μg/kg, the highest concentration tested.

Formulations

Freshwater Invertebrates 

Two 48-hour acute toxicity studies with Daphnia for atrazine formulations (80WP and 40.8 4L) 

are available with acute LC50 values ranging from 36,500 to 49,000 μg/L and >31,000 μg a.i./L 

(MRID 42041401;45227712). These studies were conducted above the limit of solubility for 

atrazine (33 mg/L). Another study with Daphnia magna reported a 48-hour LC50 of >485,000 μg 

a.i./L using atrazine 500 (48.5% a.i.); the same study reported a 96-hour LC50 of 16,000 μg a.i./L 

for Hyallela azteca (Wan et al., 2006). An acute study with glochidia and juvenile stage 

freshwater mussels, Lampsilis siliquoidea, was conducted using Aatrex 4L (40.8% a.i.) (Bringolf 

et al., 2007; E99469). The reported 96-hour LC50 value for both stages was >30,000 μg/L (12,200 

μg a.i./L). The freshwater mussel, Utterbackia imbecillis, was tested using the formulation 

Atrazine 4L SA-50 (41% atrazine) under static conditions for 24 hours. The LC50 was estimated at 

241,000 μg/L (Conners and Black 2004; E74236) which is greater than the solubility of atrazine. 
59

Estuarine-marine Invertebrates 

There were several acute toxicity studies conducted with atrazine formulations for 

estuarine/marine invertebrates including eastern oyster (Crassostrea virginica), Pacific oyster 

(Crassostrea gigas), fiddler crab (Uca pugilator), and European brown shrimp (Crangon crangon) 

and cockle (Cardium edule). Several studies resulted in non-definitive values, LC50 >100 to 

>100,000 μg a.i./L (MRID 00024720; 45227728), while others resulted in definitive LC50 values, 

10,000 to 239,000 μg a.i./L (MRID 45227728; 00024395), of which some are above the solubility 

of atrazine. 

6.2.2.4.a. Chronic Exposure Studies 

Freshwater Invertebrates 

There are several chronic toxicity tests for freshwater invertebrates. The most sensitive chronic 

endpoint for freshwater invertebrates was based on a 30-day flow-through study on the scud, 

Gammarus fasciatus, with a NOAEC of 60 μg/L, based on growth of the second generation 

(MRID 00024377). As with the chronic freshwater fish, this study appeared to be conducted 

using the solvent DMSO with no concurrently tested solvent control. In addition, the control 

survival after 30 days was64-74%, and only one of the two replicates in the control reproduced. 

Results were available for freshwater invertebrate species (D. magna, C. tentans) from the 

same document, MRID 00024377; however, they all also appeared to use DMSO with no 

concurrent solvent control. The reported NOAEC and LOAEC for D. magna and C. tentans was 

140 and 250 μg a.i./L (based on reproduction and survival) and 120 and 230 μg a.i./L (based on 

reduced pupating and emergence), respectively. In the Daphnia magna test, control 

performance was an issue with only 61% survival after 15 days for the parental generation. 

Several other chronic toxicity studies were also available with NOAECs ranging from 200 to 

5,000 μg a.i./L, but toxicity data and/or methods were not reported; therefore the results could 

not be verified. 

Estuarine-marine Invertebrates 

The most sensitive chronic bioassay in estuarine-marine species was a 28-day study in mysid 

shrimp (Americamysis bahia) that reported a NOAEC of 80 μg/L based on a reduction in survival 

(MRID 45202920). However, toxicity data were not available for endpoint verification Thus, 

endpoint values are presented in a table with only the mean value and no standard error or 

deviations. In addition, while the report stated that the assay was conducted according to 

Nimmo et al. (1977), no explicate test duration was reported. Another mysid shrimp life-cycle 

study was available (MRID 46648202) with a reported NOAEC of 260 μg a.i./L, based on growth. 
60

CHAPTER II. THE EVALUATION OF AMPHIBIAN TOXICITY DATA 

While reviewing this section, please consider the charge questions below. 

SAP Questions: 

 Is the SAP aware of any other laboratory-based or field-based studies not included in 

this White Paper that should be considered?

EPA identified test design elements that could potentially confound the ability of a study to 

discern a causal relationship between exposure to atrazine and an effect on amphibians 

(Section 7.2). Based on consideration of those test design elements, EPA then evaluated 

the available amphibian data and assigned a classification (e.g., Quantitative, Qualitative 

(high, medium, and low level of confidence), and Invalid) to each study indicating EPA’s 

confidence in the study’s conclusions (Section 7.3 and Appendix C). The confidence in each 

study was based on an evaluation of the identified test design elements and resulting level 

of uncertainty in determining a direct causal relationship between atrazine and potential 

effects to amphibians. 

 Please comment on the completeness of EPA’s list of pertinent test design elements. 

Also, please comment on the degree to which these test design elements, singularly 

or in combination, would be expected to contribute towards confounding the test 

results. 

 Please comment on EPA’s conclusions about the level of confidence placed on each 

study’s results.

After evaluating all the available amphibian studies, one study was found to have accounted 

for all the identified test design elements (Question #2) and determined to be suitable for 

quantitative use in risk assessment for the endpoints of survival, growth and development 

(Section 7.3 and Appendix C). This study was required by an EPA Data Call-In (DCI) Notice 

following the recommendations from the 2003 SAP on atrazine and amphibians. The 

resulting study examined the effects of atrazine on Xenopus laevis at concentrations of 0.01 

to 100 μg/L at two different laboratories. Based on the 2007 SAP, the conclusion was, and 

there was agreement by the Panel, that the data from this study were robust and sufficient 

to conclude that exposure to atrazine at concentrations ranging from 0.01 to 100 μg/L had no 

effect on X. laevis development (which included survival, growth, metamorphosis and 

sexual development).

 Please comment on whether any new information has become available that leads 

to a different conclusion from the one which EPA reached in that the results of the 

DCI study were adequate to evaluate potential effects of atrazine exposure to 

amphibians.
61

 If such information is now available, please comment on how a threshold 

determination (a concentration that is expected to cause no effect) may be 

accomplished using the identified studies.

After evaluation of the available amphibian toxicity data, EPA concluded that the DCI study 

mentioned above was appropriate for quantitative use in a risk assessment for survival, 

growth and development. While the 2007 SAP Panel agreed that atrazine appeared to have 

no effect on X. laevis development at atrazine concentrations ranging from 0.01 to 100 

μg/L, they expressed concerns about the suitability of X. laevis as a surrogate for native 

species. Review of the available toxicity data utilizing indigenous species suggests that 

suitable protocols, including adequate husbandry methods in particular, that would enable 

EPA to quantify a toxicity endpoint representative of a clear and consistent response from 

atrazine for native species, may not exist. 

 Please comment on whether there are suitable methods for testing native 

amphibians with particular regard to husbandry and laboratory culturing conditions, 

consistent with the design elements recommended by the 2003 SAP. 

A number of studies report the potential for atrazine to modify immune function and 

infection susceptibility in amphibians (Appendix C). EPA believes the research on these 

different hypotheses does not provide sufficient data to establish causal linkages among 

different levels of biological organization to result in adverse effects. Therefore, EPA 

concluded that a mode of action or adverse outcome pathway leading to effects on 

amphibian survival, growth or development cannot be established at this time. 

 Please comment on whether the data in the existing database reasonably supports 

the hypotheses, or demonstrates that atrazine affects immune function and/or 

infection susceptibility leading to adverse effects on survival, growth or 

development; i.e., are there sufficient data to establish an adverse outcome 

pathway for atrazine effects on immune function? Please provide a rationale for the 

Panel’s position and discuss the associated strengths and weakness with the data 

supporting the rationale. 

 If the Panel concludes that the existing data are sufficient to formulate hypotheses 

that atrazine adversely affects immune function and infection susceptibility, but are 

not sufficient to test the hypotheses (refute or confirm), then please comment on 

specific study protocols that can be used to test these hypotheses with sufficient 

rigor to identify effects that can be directly and quantitatively attributed to adverse 

impacts on amphibian reproduction, growth and/or survival. 
62

7. Toxicity Data to Amphibians (aquatic-phase and terrestrial) 

If acute and chronic toxicity data are not available for aquatic-phase amphibians, the EPA relies 

on freshwater fish acute and chronic toxicity data as surrogates for aquatic-phase amphibians 

(U.S. EPA, 2004). Additionally, birds are used as surrogates for terrestrial-phase amphibians. To 

evaluate the potential for atrazine to affect amphibians in the environment, the Agency 

evaluated the available amphibian toxicity dataset. 

7.1. History of Previous Amphibian SAPs 

A large number of studies are available examining the potential effects of atrazine on 

amphibians. Many of these studies have been previously reviewed by OPP and reported in 

endangered species assessments for the compound and in ecological risk assessments written 

in support of registration decisions. Reviews of more recent literature on amphibians are 

contained in Appendix C. The current reviews were conducted on open literature papers that 

passed the U.S. EPA ECOTOX and OPP acceptability screening criteria (Appendix N). Previously, 

reviews of studies specific to the potential effects of atrazine on amphibian gonadal 

development were written in support of consultations with the FIFRA SAP. For the 2003 SAP on 

potential developmental effects of atrazine on amphibians, the Agency determined that 

existing data were sufficient to warrant further examination of atrazine effects on development 

(U.S. EPA, 2003d). The SAP concurred with a tiered testing approach proposed by EPA using the 

African clawed frog (Xenopus laevis) and indicated that X. laevis was a suitable surrogate test 

species for amphibians. In 2004, EPA issued a data call-in (DCI) to registrants for the study 

outlined in the first tier and at a 2007 SAP on the potential for atrazine to affect amphibian 

gonadal development, the results of the DCI study and evaluation of open literature data to 

date were presented (U.S. EPA, 2007a). The EPA concluded that based on available data, 

atrazine did not appear to produce consistent effects on amphibian development and that 

based on the tiered testing approach reviewed by the 2003 SAP, no further testing was needed. 

However, EPA indicated in 2007 that it would continue to monitor information as it becomes 

available. The SAP agreed that the study conducted in response to the DCI (which was 

comprised of two studies conducted in parallel) showed no effect to X. laevis on development 

from exposure to atrazine concentrations ranging from 0.01-100 ppb. The 2007 SAP Panel did, 

however, express concerns about the use of X. laevis to represent native species and the 

sensitivity of the strain of X. laevis used in the study. 

7.2. Test Design Elements 

Subsequent to the 2007 SAP, toxicity data on effects of atrazine for a variety of amphibian 

endpoints (e.g., metamorphosis, sexual development, immune response and infection 

susceptibility) have continued to be published in the open literature. At this time, attributing 

any clear dose-response for potential effects of atrazine on native species and terrestrialphase/reproductively mature amphibians remain as uncertainties. After a review of the 

available data for native species, adequate test methods, culturing in particular, have not been 
63

identified to reliably test hypotheses. Some of these uncertainties arise from confounding 

factors present with the available data in terms of the reported test design. As indicated in 

previous SAPs on atrazine and amphibians, there are many study design elements that if 

followed and reported, help to reduce uncertainty and allow for greater confidence in the 

ability to discern a cause and effect relationship with regards to atrazine exposures. These test 

design elements include: 

1. Sufficient replication to allow for adequate power to detect the desired difference from 

the control; 

2. Screening for potential contaminants/interferences in food and water sources; 

3. If the use of a solvent is required, the use of a recommended solvent at no more than 

the recommended maximum rate. Current ASTM and U.S. EPA OCSPP guidelines 

recommend that in chronic testing not to use more than 0.1mL solvent/L solution; 

dimethylsulfoxide (DMSO) is not currently a recommended solvent for chronic testing. 

In addition, the test would contain both a negative and a solvent control concurrently 

with the treatment groups, as previous historical knowledge and response to a solvent 

may not be indicative or representative of the response in the current study. This is 

particularly important for studies for which there is no standard, validated protocol or 

guideline; 

4. Measurement of the test chemical in both the control(s) and the treatment groups to 

relate potential effects to an exposure concentration and to check for potential 

contamination in the control(s); 

5. Test equipment (e.g., test vessels) that is constructed of recommended materials and 

avoids the use of materials (i.e., plastics) that may leach contaminants that may 

interfere with developmental endpoints; 

6. Loading that adheres to recommended rates to help ensure adequate water quality and 

development in addition to reporting the measured water quality parameters. If 

conducting a study under static or static-renewal conditions, it is particularly important 

to measure and report water quality elements such as ammonia levels to better ensure 

adequate environmental conditions. The renewal period may need to be shortened 

and/or the biological loading rate decreased in an effort to maintain water quality; 

7. The use of organisms from controlled environments in an effort to understand prior 

exposure history. This may include using laboratory-raised organisms (preferred) or 

organisms from outdoor sources in which information about potential contaminants is 

known; 

In addition to the test design elements described above, the resulting reported data need to be 

sufficient to enable the reviewer to understand and substantiate the study results or 

conclusions. Furthermore, care should be taken to avoid aberrant effects in controls that 

confound the ability to discern treatment related effects (e.g., high control mortality or high 

incidence of intersex especially when evaluating developmental endpoints). 

Overall, similar to findings from open literature reviews conducted in 2003 and again in 2007, 

many of the studies reported in the open literature since the 2007 SAP contain uncertainties 
64

and deficiencies in their methods and/or results and the results of any single study need to be 

considered within the context of its uncertainties and deficiencies. Common deficiencies or 

uncertainties reported in the current and previous SAP reviews of the open literature include, 

but are not limited to, lack of prior exposure history of the test organisms, potential 

interferences in food sources, biological loading rate, test vessel material, and solvent choice 

and concentration. These uncertainties can affect the environmental conditions and husbandry 

requirements of the test species and can confound the ability of a study to discriminate 

whether exposure to a compound results in a clear and reproducible response that is 

concentration dependent. In previous SAP white papers for evaluating effects of atrazine on 

amphibian development, each of the studies was evaluated with regard to the following 

parameters: 

1. experimental design, protocols and data quality assurance; 

2. strength of cause-effect and/or dose-response relationships; 

3. mechanistic plausibility; and, 

4. ecological relevancy of measured endpoints. 

In an effort to understand what uncertainties or potential confounding effects may be present 

in the current compendium of studies, test design elements that were expected to potentially 

confound test results were identified, many of which were used in the evaluations for the 

previous SAPs. In addition, uncertainties related to reporting of data/statistical results and 

aberrant effects in the control were also identified. Certain elements (e.g., control mortality) 

were deemed more influential in reducing the ability to evaluate causality, and, therefore, if a 

study contained one of these elements the study was classified as invalid. Each of the available 

studies was reviewed and a record of the critical design elements was maintained for each 

study. For field studies, excluding micro- or mesocosms, the body of available data was 

primarily evaluated in support of the 2003 and 2007 SAPs, of which the many reported 

uncertainties in those studies precluded the ability to provid conclusive evidence of an effect 

that can be consistently reproduced. Therefore, the focus of this current evaluation is on the 

laboratory and cosm studies. 

The identified test elements were as follows: 

A. A study was rejected as invalid, if the study had any of the following elements: 

1. Atrazine concentrations were not reported. Minimally, nominal test concentrations 

must be reported; ideally, the amount of test material applied and the exposure 

concentration in the water column should have been measured analytically at the 

start of exposure (t=0) and periodically throughout the study. 

2. The study did not provide sufficient replication (n=2). At least two replicates per 

treatment and controls must be included regardless of the statistical method used 

(e.g., regression, hypothesis testing). 
65

3. A control was not run concurrently with treatments. If the study used a solvent then 

either a solvent or a negative control must be run concurrently. 

4. Test chemical contamination of controls. 

5. Control mortality was greater than 30%. 

6. The use of an appropriate solvent control was greater than 0.05% (500 μL/L), which 

is the current maximum for acute static and static-renewal testing for ASTM and U.S. 

EPA OSCPP 890 and 850 guidelines. 

7. Sufficient data were not provided to enable the reviewer to 

understand/substantiate study results/conclusions. Statistical analysis of the data 

(univariate and/or multivariate), including numerical and/or graphical presentation 

of the results were not clearly described and presented. 

8. The presence of other stressors (physical, chemical, biological) in 

controls/treatments was at levels that would be expected to compromise the 

interpretation of atrazine (degradates) as the causal stressor. 

9. Aberrant effects in controls that confound ability to discern treatment related 

effects (e.g., high incidence of intersex or skewed sex ratio). 

B. If a study passed the screen above, further evaluation of the study was conducted. While 

the following test design elements would not immediately invalidate a study, one or more 

of these elements raises concerns about the ability to discern a cause-effect relationship 

with regards to atrazine.

1. When a solvent was used, both a negative and solvent control group was not used in 

the study.

2. If both solvent and negative controls were used and there was a significant 

difference between the control groups for an endpoint, i.e., there is a statistically 

significant solvent effect. 

3. The concentration of an appropriate solvent control was greater than 0.01% (100 

μL/L), which is the current recommended level for chronic aquatic testing for ASTM 

and U.S. EPA OSCP 890 and 850 guidelines. 

4. DMSO was used as a solvent (DMSO can promote movement of chemicals across 

membranes).

5. Plastic test vessels were used in the study (potential leaching of chemicals which 

may interfere with study). 

6. The study was not conducted using technical atrazine (e.g., a formulation (which 

may or may not contain more than one active ingredient) or an effluent). Exposure 

to the additional chemicals may influence the response and confound the ability to 

discern potential effects from exposure to atrazine alone. 
66

7. The loading rate was higher than recommended which may or may not be coupled 

with unreported or limited reporting of water quality parameters. One 

tadpole/L/day was the recommended rate discussed at 2007 SAP (also see Figure 3 

(pg 95) in 2003 SAP white paper for graph depicting the relationship between 

developmental stage and weight with further discussion on pg. 67); 1 g/L/day is the 

ASTM recommended loading rate for acute studies under flow-through conditions 

and is 0.5-0.8 g/L for acute static and renewal tests. For example, high loading rate 

(>one tadpole/L/day), coupled with an infrequent test solution renewal period (>48 

hours), along with no reporting of adequately maintained water quality raises 

uncertainties in the adequacy of environmental conditions in the study. However, 

the reviewer may be able to infer enough information about adequate water quality 

if certain design elements are reported and deemed appropriate. 

8. The study used organisms that were collected in the field where a complete prior 

exposure history is not known. While a study may indicate that organisms were 

collected from an area not known for agricultural use or that the area had been 

analyzed for some chemicals, it is difficult to account for all possible contaminants. 

After the test design elements were catalogued, an overall classification was assigned to each 

of the studies. If a study was not classified as invalid, it was classified as either “Qualitative” or 

“Quantitative” based on the screening process described above. There were three levels of 

Qualitative: lower, medium and higher levels of confidence. These subcategories were based 

on the number and type of uncertainties identified. For example, a combination of three 

elements that was evaluated included loading, reported water quality, and test solution 

renewal period. If a study contained limited information on water quality with a higher than 

recommended loading (i.e., >1 tadpole/L) along with a renewal period of greater than 48 hours 

then there may be a high level of uncertainty in the environmental water quality which could 

lead to significant confounding effects in the study, especially for growth and development. 

However, defining combinations where potential confounding effects could occur is not 

concrete and can vary for each test design. All possible combinations or situations in which 

compromised water quality may occur are difficult to predict; however, the combination 

described above was deemed to be one possible scenario. 

Overall, the test design elements described above were the basis for classifying a study. 

However, all the test design elements and results of each study were evaluated as a whole to 

determine the studies adequacies for inclusion into the evaluation of atrazine exposure and the 

potential for effects to amphibians. For example, if a study contained one or more elements 

that would introduce uncertainties about the plausibility of a cause-effect relationship, then the 

overall level of uncertainty of the study and its results was evaluated for its inclusion in a risk 

assessment. While the EPA recognizes that the overall classification of each study is subject to 

interpretation, the basis for the current classifications were general test design elements that 

are referenced in ASTM and EPA guidelines as well as from the previous amphibian SAPs that 
67

evaluated peer-reviewed amphibian studies. The test design elements identified above provide 

the foundation for a study in terms of potentially accounting for factors that may influence the 

study results. 

7.3. Results of Evaluating Amphibian Test Design Elements 

Of the 75 open literature studies reviewed, several uncertainties were observed in multiple 

studies. Measurement of atrazine in control solutions was not reported for 44 studies (59%) 

with uncertainty in seven others due to ambiguous wording regarding analytical 

measurements. Therefore, the failure to report/measure atrazine concentrations in control 

solutions is considered a substantial deficiency in a relatively large proportion of the amphibian 

studies. Because of the large number of studies that did not report this endpoint, this 

evaluation assumed that the test solutions were prepared and maintained correctly without 

cross contamination and that the source water did not contain atrazine as it can be filtered out 

using carbon. However, this is a significant assumption. 

Biological loading is a critical factor that can impact water quality, with dissolved oxygen and 

ammonia concentration being two important elements that are influenced by test organism 

loading (Hoke and Ankley, 2005). Biological loading rate in the available studies was not always 

reported in a mass/volume unit, but rather more commonly as number of tadpoles per volume 

or number per test vessel. In several studies (30 with 4 possibles) that tested tadpoles/larvae 

for longer than a week, the reported loading was higher than the value recommended by the 

2007 SAP (i.e., one tadpole/L). In addition, most of these studies had reported limited water 

quality information. Although temperature was the primary water quality parameter reported, 

few studies included information on other parameters such as ammonia. Therefore, there is 

uncertainty regarding whether there was adequate water quality for these studies especially for 

chronic exposures (early tadpole/larvae stage through metamorphosis). 

Finally, the collection of native amphibian species from the environment was common among 

the available studies. While some studies indicate that the organisms were collected from an 

area that is not known to be influenced or has low influence from agricultural activity (Williams 

and Semlitsch, 2010), other study authors did indicate that organisms were collected in areas 

that were presumed to have been influenced by agricultural activity (Rohr et al., 2003) or that 

they do not know the prior exposure history of the organisms (Brodkin et al., 2007). 

Nonetheless, it is difficult to account for all types of potential stressors, both chemical and 

biological, for wild-caught organisms. 

7.4. Categorizing Amphibian Endpoints 

Different categories of endpoints have been reported in the amphibian data with major 

endpoints being: survival, growth (mass and length), metamorphosis and development, 

immune response and infection, behavior modifications (e.g., feeding, locomotion, mating), 
68

biochemical or molecular alterations, and sexual development. These studies encompassed 

several different species of frogs, toads and salamanders, across different life stages. The 

majority of the studies evaluated the larval stage (aquatic phase) of the organism for some 

duration or until complete metamorphosis. 

In an effort to compare endpoints and study conditions, no observed adverse effect 

concentrations (NOAEC) and lowest observed adverse effect concentrations (LOAEC) were 

extracted from the available studies. These extracted endpoints were assigned to one of the 

categories defined above. Test concentrations above the reported LOAEC were not extracted 

as well as concentrations below the NOAEC (the next test level below the LOAEC). Only 

statistically significant endpoints were included in the review; therefore, near significant and/or 

trend data were excluded from consideration since there was no way to determine whether 

such measurements were significantly different from untreated animals. For several of the 

available laboratory studies, the number of atrazine concentrations tested was limited to one 

or two, thereby reducing the ability to definitively determine a NOAEC and LOAEC, or establish 

a dose-response relationship. Generally, chronic testing is not typically designed to establish a 

regression-based (e.g., ECx) toxicity value; for example, the test concentrations in a chronic test 

may be spaced far apart (such as a 10X factor as in the case of many of the available amphibian 

studies); therefore, the reported NOAEC value may not reflect the actual toxicity threshold for 

that organism. In addition, previous SAP white papers and other reviews of open literature 

data have acknowledged that for some of the published amphibian data, a non-monotonic 

response was observed (U.S. EPA, 2003d; U.S. EPA, 2007a; Rohr and McCoy 2010). Therefore, 

sometimes defining a NOAEC and LOAEC was confounded by an apparent lack of dose-response 

(i.e., significant effect reported at 10 μg/L but not at 25 μg/L). 

Studies that examined mixtures of more than one active ingredient chemical, of which atrazine 

was one of, are not considered in this evaluation as the ability to discriminate the influence 

from atrazine exposure alone could be confounded. However, if atrazine was tested as a 

formulation (with no other active ingredients), it was included in the analysis; although, it is 

recognized that one or more of the other ingredients (e.g., “inert” ingredients such as solvents 

or surfactants) in the formulation could also potentially influence the response(s) of the 

amphibians. Furthermore, nitrate was also added in some studies as an additional stressor and 

the results from these tests were also included (Sullivan and Spence, 2003). If more than one 

species was used in the study, individual effects for each species were identified and recorded. 

If more than one specific effect was observed for a general endpoint category (e.g., mass and 

snout-vent-length, and both growth endpoints were affected at 10 μg/L, then only one effect at 

10 μg/L for growth was recorded.) For the cosm studies, given that there was the potential for 

many different types of interactions that could occur simultaneously among test organisms that 

may result in direct or indirect effects, the potential variability within and between these cosm 

studies was considered to confound the ability to evaluate the relationship between reported 

results and test design elements when compared to laboratory studies. 

The assigned data were collated within a category in an effort to determine if there were 

patterns of observed effects across studies. Within a category, different species and life stages 
69

were combined, but could be further filtered to evaluate effects to a specific genera/species or 

life stage, if desired. Once studies were identified around a range of concentrations, study 

design elements and associated uncertainties within each study were then identified in an 

effort to determine if commonalities existed around similar atrazine concentrations (e.g., <100 

μg/L). 

The inclusion of all the studies, regardless of classification, may potentially mask the ability to 

observe a relationship between effects and test design elements. Therefore, studies classified 

as “Invalid” or “Qualitative with a lower level of confidence” were removed from the analysis. 

The remaining studies are presented in Table 17. 

These studies represent a small subset of the available studies, and some of the endpoints in 

the subset of studies were classified as “Invalid” for various reasons. As discussed above, the 

limited reported water quality coupled with higher than recommended loading and a longer 

renewal rate presents a high uncertainty in regards to the environmental conditions of the 

assays which may confound the results. Unfortunately, many of the available studies fit that 

description, along with other possible uncertainties, and therefore limit their utility in 

examining potential effects from atrazine. It should be noted that for seven of the 10 studies 

listed below, analytical measurements of atrazine in the control(s) and test vessel material were 

not explicitly reported. The results of the subset of studies are described below. 

In three studies, there was no effect on growth or time to metamorphosis at 25 μg/L and 100 

μg/L, and no effect on rate of development or growth at 30 μg/L, the highest concentrations 

tested (Choung et al., 2011; Kloas et al., 2009; Spolyarich et al., 2010). Two of those studies 

were tested using Australian species of frogs, Litoria raniformis (Choung et al., 2011) and 

Limnodynates tasmaniensis (Spolyarich et al. 2010) with the other species being Xenopus laevis

(Kloas et al., 2009). The relative sensitivity of the Australian species is not known, as a positive 

control, such as 17-β estradiol, was not conducted with either study. Another study report 

effects on metamorphosis with X. laevis with a decrease in metamorphic stage after a certain 

study duration (3-5 weeks) at 100 μg/L, the lowest concentration tested (Freeman and Rayburn, 

2005); no significant effect on mass was reported in the study. However, as time to 

metamorphosis was not determined in this study, the overall effect on metamorphosis is 

uncertain. In addition, since the study was terminated prior to metamorphosis, with 

presumably organisms at different developmental stages, it is unknown how each stage was 

accounted for when comparing tadpole mass between groups. Sex ratio and gonadal 

development were also reported to not be affected at 30 and 100 μg/L for L. tasmaniensis

(Spolyarich et al., 2010) and X. laevis (Kloas et al., 2009); the other studies did not evaluate sex 

ratio or gonadal development. However, observed effects on sex ratio need to be considered 

with respect to when the effect was measured in the life cycle of the organism as rate of 

gonadal development may not in sync with somatic development rate (metamorphosis). 

An effect on flow cytometric analysis (nuclei-whole body homogenized) meant to illustrate 

development stage was reported at exposure concentrations of 800 μg/L; however, this effect 

was not observed in all trials conducted at 800 μg/L (Freeman and Rayburn, 2005). 
70

For Bufo americanus, behavior (expressed as fear cues and overall activity) was not modified at 

196 μg/L (Rohr et al., 2009) and the toads did not have a preference for soil treated with 

atrazine or not at atrazine soil concentrations of 1430 μg/kg (Storrs Mendez et al., 2009). 

There were also four studies that examined acute toxicity to amphibian embryos and larvae 

from atrazine exposure (Birge et al. 1980; Howe et al. 1998; Morgan et al. 1996; Wan et al. 

2006). The resulting LC/EC50s were at relatively high atrazine concentrations; LC50 (mortality) 

concentrations were >7,000 μg/L. The lowest reported LC50 value was 410 μg/L for R. 

catesbeiana in which the LC50 was calculated using observed mortalities as well as 

abnormalities that were expected to result in mortality under natural conditions (Birge et al. 

1980). With the exception of Kloas et al. 2009, tatistical analyses for survival for the other 

studieswere not provided. Rather, an overall mortality/survival was generally reported as 

survival was generally high. 

Even though several studies were classified as Qualitative with a higher or medium level of 

confidence, there is only one study in which all identified test design elements were accounted 

for and reported, which was the X. laevis study, which was submitted by the registrant after the 

2003 SAP. The 2007 SAP concurred that there was no effect for X. laevis at concentrations of 

0.01-100 μg/L. While the SAP expressed concerns about the use of X. laevis as surrogate 

species, an evaluation of the available native species data suggests that husbandry issues may 

persist with native species as the overwhelming majority of available data reports using field 

collected organisms. 
71

Table 17. Study Design Elements and Results for Laboratory Amphibian Studies Conducted Using Atrazine, Classified as Quantitative 

or Qualitative (with lower level of uncertainty) 

Citation / 

ECOTOX(E)/ MRID

Species / 

Source / 

Exposure 

Period (stages 

& test 

duration)2

TS3/ 

% ai

Solvent 

(%)4/ 

NC/SC 

(Y/N); 

MA in 

CNT 

(Y/N/NS)5

Test 

vessel 

material6

Loading; 

Renewal 

Period7

Reported Results8 Indentified Uncertainties / Concerns and 

Classification

Endpoint NOEC

(μg/L)

LOEC 

(μg/L) Effect

Birge et al. 1980 / 

E6187

Rana. 

catesbeiana, R. 

pipiens, R. 

palustris, Bufo 

americanus / 

NS (purchased) 

/ E for 4 dph

F / 

80

NS / (Y 

unsure if 

NC or SC); 

NS

glass 50 -103 E 

/ 0.5L

Surv 4 

dph LC50

-- --

R. catesbeiana = 410 μg/L

R. pipiens = 7680

R. palustris = 17960

B. americanus >48000

LC50s were not based on mortality per se, but on 

abnormalities that would reportedly preclude 

survival under natural conditions; solvent (if used) 

was not identified as tested formulation suspect 

not; formulation used so uncertainty in source of 

toxicity

Qualitative – Higher level of confidence; however 

LC50 values are combination of both lethality and 

abnormal effects and formulation used

Choung et al. 

2011a / E153858 

Litoria

raniformis / Lab 

/ TP (G26) for 

10 wks

T/ 

>98

NA / 

(Y/NA); NS glass

10 TP 

/10L; 

2X/wk

Metam

Gro

Surv

25 (N)

25

--

>25

>25

--

Time to metamorphosis

Mass; SVL

Study indicated survival >97.5% for 

study; not explicitly reported in 

terms of NOEC/LOEC 

Limited reporting of potential contaminants in 

food and water; number of egg masses used not 

specified; measured ammonium (not NH3)

Qualitative-Higher level of confidence; however 

there is a lack of reported measurements in food 

 

Bold values were classified as ‘quantitative’ or ‘qualitative – medium or higher level of confidence’ 

2

 TP = tadpole; LV = larvae; M= metamorphorsis; E= embryo; G = gosner stage; NF=Nieuwkoop and Faber; SVL=snout-vent-length; A = adults; H = hatch; J = 

juvenile; if reported in study, developmental stage or some other identifier at test initiation is given, if not reported than designated as NS (not specified); dph = 

days post hatch 

3

 TS = Test substance; T = technical; F = formulation 

4

 NA = not applicable; NS = not specified; ACTN = acetone; EtOH= ethanol; DMSO=dimethylsulfoxide; MeOH=methanol; IPA = isopropyl alcohol 

5

 Negative Control (NC) and/or Solvent Control (SC) included in study design; MA in CNT = Measurable atrazine in control treatment group(s)- Yes (Y) or No 

(N) or Not Specified (NS) 

6

 The values reported represent loading reported as mass (g) or number of larvae/tadpoles in a volume of water (L). If loading was reported as number of 

larvae/tadpoles in a certain test vessel size but test solution volume was not reported, then this is presented # organisms in tank (volume reported if available) as 

actual loading could not be determined ; PE = polyethylene 

7 Water 

8

 Metam = metamorphosis; Gro = growth; Imm/Inf = immune system or infection; Bio/Mol = biochemical/Molecular; Sexdev = sexual development; 

Behav=behavioral; Surv = survival; N = nominal conc.; M = measured conc; NDR = not dose responsive (no significance at higher dose). 
72

Citation / 

ECOTOX(E)/ MRID

Species / 

Source / 

Exposure 

Period (stages 

& test 

duration)2

TS3/ 

% ai

Solvent 

(%)4/ 

NC/SC 

(Y/N); 

MA in 

CNT 

(Y/N/NS)5

Test 

vessel 

material6

Loading; 

Renewal 

Period7

Reported Results8 Indentified Uncertainties / Concerns and 

Classification

Endpoint NOEC

(μg/L)

LOEC 

(μg/L) Effect

water and number of egg masses

Freeman & 

Rayburn 2005 / 

E81459

X. laevis / 

Nasco/Xenopus 

Express / TP 

(varied NF40 to 

54) for 3-5 wks

T / 

98

NA / 

(Y/NA); 

NS9

NS NS; 

weekly

Metam

Gro

Bio/Mol

Surv

<100 (N)

800

Varied

--

100

>800

800

--

↓ metamorphic stage

Mass

↑ flow cytometric analysis meant to 

illustrate metemorphosis and 

development); results varied based 

on test 

% Mortality (0-16.7%) for different 

assays, reported as occurring 

randomly in treatments; mortality in 

terms of NOEC/LOEC not reported

Stats for flow cytometric conducted on CVs; 

uncertainty in weight analysis with regards to 

accounting for different stages of organisms; fill 

volume of test vessel (3L) not reported however 

water quality appears to be acceptable

Qualitative- Medium level of confidence for 

molecular endpoint due to analysis using CV and 

other reasons described for metamorphosis; 

Invalid for weight due to potential confounding 

factor; Qualitative –Higher –for metamorphosis 

stage; however, lack of analysis of atrazine in 

control

Howe et al 1998 / 

MRID 45202910

R. pipiens, B. 

americanus / F 

/ TP (G29 & 40) 

for 96 h

F / 

40.8

NA 

(Y/NA); N glass 20 TP / 15L 

Surv 96 hr 

LC50 -- --

R. pipiens (early stage) = 47600

R. pipiens (late stage) = 14500

B. americanus (early) = 26500

B. americanus (late) = 10700

Control survival not reported; no raw data; tested 

above water solubility

Qualitative – Medium level of confidence based 

on lack of control data and only LC50 values 

reported and testing above water solubility

Kloas 2009a / 

E112914

X. laevis / 

Xenopus I / TP 

(8 dpf) for 83 d 

T / 

NS

NA / 

(Y/NA); Y10 glass

<1 

g/L/day; 

7X/day

Metam

Gro

Sexdev

Surv

100 (N)

100

100

100

>100

>100

>100

>100

Time to metamorphosis

Mass; SVL>10011

Sex ratio; gonadal development

% Survival

Atrazine contamination of controls; marked 

fluctuations in water quality parameters; 

histological endpoint comparisons not made 

relative to amphibian reference

Quantitative based on fact that although 

deficiencies, study design and reporting were 

robust enough to properly evaluate results

Morgan 1996 / 

E63246

X. laevis / 

Xenopus I 

(adults) / E for 

F / 

40.8

NA / 

(Y/NA); 

NS12

plastic NS; 24 hr Metam

Surv --

11000 

or 1100 

(4488 

LC50 = 100000 or 126000 (40800 

or51408 ai)

EC50 (abnormalities) = 33000 or 

Limited water quality reported, test solution fill 

volume not reported; conducted above water 

solubility; formulation used so source of toxicity 

 

9

 Study reports that solutions measured from experimental tanks and atrazine concentrations were within expected range; however unsure if this included the 

control 

10 Atrazine detected in one out of 4 blocks of negative control tanks in one of the studies; it was excluded from analysis 

11 Significant decrease in female weight and SVL observed at 0.01, 1 and 25 for females only but not at 0.1 and 100 ppb in one of the two reported studies; No 

effect on wt and SVL reported in other study; EFED does not consider the differences in wt and SVL to be a concentration-dependent effect 

12 Test concentrations measured, but do not report results for control; unsure if analyzed 
73

Citation / 

ECOTOX(E)/ MRID

Species / 

Source / 

Exposure 

Period (stages 

& test 

duration)2

TS3/ 

% ai

Solvent 

(%)4/ 

NC/SC 

(Y/N); 

MA in 

CNT 

(Y/N/NS)5

Test 

vessel 

material6

Loading; 

Renewal 

Period7

Reported Results8 Indentified Uncertainties / Concerns and 

Classification

Endpoint NOEC

(μg/L)

LOEC 

(μg/L) Effect

96 hr or 448 

ai)

<8000 ( 13464 or 3264 ai) unknown

Qualitative – Medium level of confidence based 

on limited water quality reported 

Rohr et al. 2009 / 

E117315 

B. americanus / 

Field / LV (G25-

27) for 4 d

T/ 

99

ACTN 

(0.0002) / 

(N/Y); NS

NS

6 TP/0.5L 

(96hr) 

then 

1/3.5L; 

static

Behav

Surv

196 (M)

--

>196

--

Fear cues (predator and parasite); 

activity

Reported no effect on mortality with 

nearly 100% survival

No negative control (authors report no effect 

from solvent based on previous data); limited 

water quality reported

Qualitative-Higher level of confidence, however 

no negative control and limited water quality

Spolyarich et al. 

2010 / E153638

L.tasmaniensis 

/ Field / TP 

(G28) to G42 (4 

wks) 

T/ 

98

NA / 

(Y/NA); N glass 10 TP/10L; 2X/wk

Metam

Gro

Sexdev

Surv

30 (N)

30

30

--

>30

>30

>30

--

Rate of development

Length

Sex ratio; gonad development

Reported 2.3% mortality in test 

overall; mortality not reported in 

terms of NOAEC/LOAEC

Sex determination based on gross morphology; 

histology on male gonads only; Metamorphosis 

and length data analysis appear to be based using 

the individual frog as the experimental unit and 

not the tank as data in figures appears to be on 

pooled results of the three trials

Qualitative-Higher level of confidence as loading 

seemed within recommended levels, however, 

ammonia and nitrate concentrations not reported 

with a 2X/wk renewal period and field collected 

organisms (Sydney Australia suburb) so prior 

exposure history is unknown

Storrs Mendez et 

al. 2009/ E118898

B. americanus / 

Field / 

Metamorphs 

for 2 d 

T/ 

99.2

ACTN 

(NS)/ 

(NS/NS); 

NS

NS NA; NA

Behav

Surv

1430

μg/kg(N)

NS

>1430

NS

Soil choice preference (ATZ or no 

ATZ)

Limited reporting on control group preparationuncertainty regarding whether control contained 

solvent; uncertainty in measured conc. due to less 

than nominal and long storage time

Qualitative-Medium level of confidence based on 

limited reporting for control preparation 

Wan et al. 2006 / 

E89626

R. catesbeiana 

/Ward’s Natural 

Science / TP 

(10cm) for 96 

hr

T / 

98 & 

F / 

48.5

ACNT 

(NS); 

(Y/Y); NS 

(dilution 

water 

analysed)

glass 0.8 g/L; 

static Surv -- --

Technical

96 hr LC50 > 16000

Formulation

96 hr LC50 > 480000 (232800 ai)

Solvent concentration not reported; raw data not 

provided, control mortality not reported

Qualitative – Medium level of confidence based 

on lack of summary data and no reported solvent 

concentration
74

Given the small number of studies available after filtering the studies with a classification of 

“Invalid” or “Qualitative –Lower level of confidence”, a comparison of test design elements 

within an endpoint category is not really informative. Therefore, an effort was made to 

evaluate the breadth of toxicity values across all of the available studies identified in Appendix 

C regardless of whether further review of the study reported uncertainties that resulted in an 

“Quantitative”, “Qualitative (almost all studies were in this category) or “Invalid” classification. 

The results of this broader analysis are discussed below. 

Survival 

Available acute data for amphibians indicate that they are relatively insensitive to technical 

grade atrazine with acute LC50 values > 10,000 μg/L for juveniles and embryos (e.g., Howe et 

al.,1998). Teratogenic effects were also evaluated for amphibian embryos with EC50 values 

≥2,100 μg/L (Fort et al., 2004). The lowest acute value was reported by Birge et al. (1980) in 

which the reported 4 days post hatch LC50 for R. catesbeiana was 410 μg/L; this value 

represents both lethality as well as observed abnormalities expected to result in mortality 

under natural conditions. 

A wide range of sub-chronic or chronic survival results are available. No effects on survival have 

been reported at atrazine concentrations of up to and around 200 μg/L and above (400 μg/L) 

for several studies and species: X. laevis (Allran and Karasov, 2000 and Hayes et al., 2002); Hyla 

versicolor (LaFiandra et al.,2008); and A. barbouri (Rohr et al., 2003). Long term carry-over 

effects on survival for A. barbouri were reported at 4 μg/L, lowest concentration tested (Rohr et 

al.,(2006). In addition, chronic (32 days) atrazine exposure to four species of tadpole frogs 

including spring peepers (Pseudacris crucifer), American toads (Bufo americanus), green frogs 

(Rana clamitans), and wood frogs (Rana sylvatica) was studied at early (Gosner stages 25-27) 

and late (stages 29-36) developmental stages (Storrs and Kiesecker, 2004). For spring peepers, 

American toads and green frogs, survival was significant at the lowest concentration tested, 

2.84 μg/L; however, survival was not always significant at higher concentrations (25 and 64 

μg/L). In this study, atrazine was tested as a formulation (85.5% atrazine), therefore, there is 

uncertainty in if, and how, the inert ingredients may have influenced the toxicity. 

Metamorphosis 

Effects on metamorphosis were reported in 29 laboratory studies at concentrations ranging 

from 3 to 400 μg/L; acute studies such as those evaluated under the FETAX (frog embryo 

teratogenesis assay- Xenopus) protocol were not included. The distributions of the reported 

metamorphic NOAECs and LOAECs for the available studies along with their classification are 

presented in Figure 7 (distribution plotted used the Weibull method). The graphs are meant to 

serve as a qualitative representation of the range of reported effects and the corresponding 
75

study classification; the graphs are not intended to obtain a quantifiable percent value using 

the curve (e.g., 50% of studies are below this concentration). Some studies examined effects 

on more than one species concurrently using the same atrazine concentrations which resulted 

in the same reported NOAEC or LOAEC values for all or some of the tested species. The ability 

to visually discern each species on the distribution graph was considered desirable, so each 

species with the same NOAEC/LOAEC was ranked which skewed the percent distribution 

slightly. In addition, not every study reported had a definitive NOAEC and LOAEC (due to 

observed effects at all or none of the tested concentrations or use of only one test 

concentration); therefore, there is not an even number of data points between the NOAEC and 

LOAEC graphs. Seven studies reported effects at 100 μg/L or less: Koprivnikar, 2010; Coady et 

al., 2004; Rohr et al., 2004; Larson et al., 1998; Olivier and Moon, 2010; Brodeur et al., 2009 

and Freeman and Rayburn, 2005. Of the seven studies reporting effects on metamorphosis at 

100 μg/L or less, two were conducted with ranids (Rana pipiens and R. clamitans) and three 

were conducted with salamanders (Ambystoma tigrimum, A. barbouri, and A. maculatum); the 

other two were conducted with the frogs Rhinella arernarum and X. laevis. Effects included: 1) 

reduced developmental stage at test termination at 3 μg/L, only concentration available for 

analysis (Koprivnikar, 2010); 2) longer time to metamorphosis (Coady et al., 2004) at 11 but not 

28 μg/L; 3) decrease in time (day) of metamorphosis (presented as year standardized means) at 

40 μg/L but not at 4 μg/L (Rohr et al., 2004); 4) delayed metamorphosis at 81.8 μg/L (Larson et 

al., 1998); 5) decrease in time to metamorphic stage at 100 μg/L (Brodeur et al., 2009; Freeman 

and Rayburn, 2005); and 6) stage before death or hatch at 100 μg/L (Olivier and Moon, 2010). 

One reported common design element for these four studies is the use of a co-solvent. Ethanol 

was used in both of the ranid studies, and DMSO or acetone was used in the other studies. 

However, co-solvents such as ethanol and acetone were also used in other studies that did not 

report effects on metamorphosis at atrazine concentrations similar to the studies described 

above (Hayes et al., 2006b- NOAEC = 0.19 μg/L for R. pipiens; Storrs and Semlitsch, 2008-NOAEC 

= 30.4 μg/L for R. sphenocphala). 
76

 

Figure 7. Distribution of Metamorphic NOAECs and LOAECs and Study Classification 

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

100

0.1 1 1 0 100 1000 10000

Percent 

Metamorphosis NOAEC (ug/L)

Qualitative-High level of uncertainty

Qualitative-Lower level of uncertainty

Invalid

Quantiative

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

100

1 1 0 100 1000 10000

Percent

Metamorphosis LOEC (ug/L)
77

Growth 

Growth endpoints (e.g., mass and snout-vent-length (SVL)) were examined in 27 of the 

available laboratory studies. Many of the studies reported effects at or below 400 μg/L and 

examined both metamorphosis and growth (Figure 8). Both of these endpoints are frequently 

linked together (U.S. EPA, 2007a; Rohr and McCoy, 2010) as growth is reported in the context 

of metamorphosis. For the laboratory studies, adverse effects on growth were reported from 

0.19 μg/L to 800 μg/L (one study at 800 μg/L) with three laboratory studies reporting effects at 

less than 100 μg/L. In Hayes, et al. (2006b) an effect on R. pipiens growth (decreased mass and 

SVL), but not metamorphosis, was reported at 0.19 μg/L; however, Koprivnkiar (2010) reported 

both an effect on R. pipiens growth and metamorphosis at 3 μg/L (ca. 100% mortality reported 

at 300 μg/L). Reported decrease in mass for X. laevis at 20 μg/L (lowest concentration tested) 

was lower than the reported effect on metamorphosis (increase in time to metamorphosis) 

(LOEC >320 μg/L) for the same study (Sullivan and Spence, 2003). Studies also reported no 

effects on growth or metamorphosis at atrazine concentrations of 30 μg/L or less: 1.25 μg a.i./L 

for B. americanus, H. versicolor, and P. triseriata (Williams and Semlitsch, 2010). Several 

studies have reported no effects for growth around 20-30 μg/L, although they may have 

reported effects at higher concentrations, for example: Choung et al. (2011) reported a NOEC 

for growth and metamorphosis at 25 μg/L in Litoria raniformis; Zaya et al. (2011) reported a 

NOAEC for X. laevis growth at 25 μg/L with LOEC at 200 μg/L. 
78

Figure 8. Distribution of Growth NOAECs and LOAECs and Study Classification 

Sexual Development 

Many studies have been conducted that evaluate different aspects of sexual development (e.g., 

sex ratio, gonad development, other organs involved in reproduction) in amphibians. Effects on 

sexual development (i.e., change in sex ratio, increase in gonadal malformations (ovotestes), 

changes in larynxgeal muscles) were reported at atrazine concentrations of 50 μg/L or lower. 

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

1 1 0 100 1000 10000100000

Percent

Growth NOAEC (ug/L)

Invalid

Qualitative-Lower level of 

confidence

Qualitative-Higher level of 

confidence

Quantitative

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0.1 1 1 0 100 1000

Percent

Growth LOAEC (ug/L)

Invalid

Qualitative-Lower level of 

uncertainty
79

Seven out of eleven of these studies report effects on sex ratio and gonadal malformations at 

concentrations of 15 μg/L atrazine or lower. 

Effects on sex ratio were reported for atrazine concentrations ranging from 0.92 to 124 μg/L 

(Figure 9). However, observed effects on sex ratio need to be considered with respect to when 

the effect was measured in the life cycle of the organism. Many of the studies were conducted 

to metamorphosis; however, there is evidence that somatic development (metamorphosis) and 

gonadal maturation do not necessarily coincide, i.e., gonadal maturation occurs later in the life 

cycle (Storrs and Semlitsch, 2008) but this cited studies has uncertainties including test design 

and lack of reported water quality. 

Effects on gonadal development and morphological changes were examined in several studies. 

Gonadal effects such as observation of ovotestes, changes in testicular morphology, effects on 

gonadal somatic index compared to the controls were reported as well as changes in other 

organs used for reproduction or mating (e.g., larynx) were reported at atrazine concentrations 

ranging from 0.1 to 25 μg/L atrazine. Several of these studies were evaluated in the 2003 and 

2007 SAPs: Hayes et al. 2002, 2003, 2006a, 2010a; Tavera-Mendoza et al. 2002a and 2002b, 

Goleman et al. 2003; and Hecker et al., 2005b. While ethanol was used in only about half (5 out 

of 11) of the studies discussed above, these studies comprise the low end of the effects curve 

with effects ≤10 μg/L. However, no effect on sexual development were also reported at 

concentrations greater than the adverse effect concentrations described above (Spolyarich et 

al., 2010; Kloas et al., 2009a; LaFiandra et al., 2008). 
80

Figure 9. Distribution of Sexual Development NOAECs and LOAECs and Study Classification 

0

2 0

4 0

6 0

8 0

100

0.01 0.1 1 1 0 100 1000

Percent

Sexual development NOAEC (ug/L)

Invalid

Qualitative-Lower level of confidence

Qualitative-Higher level of confidence

Quantitative

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

100

0.1 1 1 0 100 1000

Percent

Sexual development LOAEC (ug/L)

Invalid Qualitative-Lower level of confidence
81

Biochemical and Molecular Endpoints 

Studies evaluating biochemical and/or molecular endpoints reported effects primarily at 

concentrations ≤ 500 μg/L. Many of the studies examined a diverse array of endocrine-related 

endpoints (e.g., aromatase, estradiol, and testosterone). Studies reported changes in a variety 

of biochemical endpoints (e.g., testosterone, estradiol, corticosteroid and thyroxine) at 

concentrations less than 100 μg/L: Coady et al., 2005; Hayes et al., 2010a, Hayes et al., 2002; 

and Larson et al., 1998. No effect on biochemical endpoints at concentrations of 25 μg/L and 

above were also reported (Kloas et al., 2009a; Oka et al., 2008; Hecker et al., 2005). However, 

there are uncertainties with all of these cited studies, except Kloas et al. 2009a, which limit the 

ability evaluate these endpoints. 

Again, cosolvent (ethanol or isopropyl alcohol) was used in several of the studies where effects 

≤25 μg/L were observed; other studies (e.g., Coady et al., 2005; Hecker et al., 2005a and 2005b; 

Villeanue et al., 2003) reported no effect on biochemical endpoints (e.g., estradiol, aromatase, 

testosterone) where no cosolvent was used. As there were diverse biochemical and molecular 

endpoints discussed and evaluated, a graph illustrating the NOAECs and LOAECs may not be 

very informative and misleading due to the varied endpoints. This is similar for the discussion 

on the immune system and behavior modifications. 

Immune System and Infection 

Several papers evaluated the potential effects of atrazine on the immune system and 

susceptibility to infection; several different immune response endpoints were examined in 

addition to susceptibility to infection. The majority of the studies evaluating the immune 

system report effects on ranids at or below 200 μg/L. Several studies reported effects at 30 

μg/L or less: Brodkin et al,. 2007 (decrease in number of phagocytic cells (at 0.01 μg/L) and a 

decrease in white blood cells and mean percentage of peritoneal phagocytic cells at 21 μg/L in 

adult R. pipien frogs); Houck and Sessions (2006) (reduction in the number of plaques 

representing antibody-secreting cells at 1 μg/L for adult R. pipiens); Forson and Stofer (2006) 

(decreased leukocyte levels (16 and 160 μg/L) and increased infections of Ambystoma tigrinum

virus (ATV) at 16 μg/L in tiger salamanders, Ambystoma tigrinum with a NOAEC of 1.6 μg/L 

reported; and Koprivnikar et al., 2007 (increase in intensity of infection in R. clamitans tadpoles 

at 30 μg/L). An increase in activated caspase3 immunopositive cells was reported at 400 μg/L, 

NOAEC of 200 μg/L in X. laevis (Zaya et al., 2011a). No effects on viral load was reported at 200 

μg/L in A. tigrinum (Kerby et al., 2009); 
82

Behavioral Modification 

There were some studies that evaluated behavioral aspects (e.g., feeding, locomotion, 

avoidance) of amphibians when exposed to atrazine concentrations of ≤400 μg/L. Suppressed 

mating behavior was reported at an atrazine concentration of 2.5μg/L in X. laevis (Hayes et. al. 

2010). In Goleman et al. (2003) abnormal swimming was observed in X. laevis tadpoles at 19.5 

μg/L atrazine with a reported NOAEC of 10.3 μg/L. Increased activity with decreased water 

conserving behavior (i.e., huddled, against side of dish, inactivity) was observed at 40 μg/L, but 

not at 4 μg/L, in adult A. barbouri salamanders (Rohr and Palmer, 2005). In Rohr et al. 2003 and 

2004, adverse behavior modification (increased activity after tapping on glass tank, and 

reduced shelter use was reported at 400 μg/L, but not 40 μg/L, for A. baarbouri. No effect on 

fear cues were reported for B. americanus at 196 μg/L (Rohr et al., 2009). 

One observation that occurred during the evaluation of all the studies was that the use of a cosolvent appeared to be a commonality. Therefore, an effort was made to determine whether 

there may be a relationship between the use of a co-solvent and whether a significant effect 

was reported. The numbers of laboratory studies that reported an effect on any endpoint as 

well as the number of studies that reported no observed effects were tallied relative to 

whether the study did or did not use a co-solvent (p>0.05, Chi-square test) (Figure 10). The 

results do not suggest that the use of a co-solvent is associated with whether or not the study 

demonstrated a significant effect. These results include observed effects that range from 0.1 

μg/L to 10,000 μg/L. 

. 

Figure 10. Number of studies that reported an overall effect or not along with use of a 

solvent 

18

22

7

6

0

5

10

15

20

25

no solvent solvent

effect

no effect
83

Cosm Studies 

While not included in the analysis described above, several cosm (micro and meso) studies that 

examined effects of atrazine on amphibians were available. Effects on the endpoints discussed 

above at concentrations of 100 μg/L or below, are discussed here. A summary of the cosm 

studies and the identified uncertainties associated with each study are presented in Appendix 

C. Metamorphosis was examined in the cosm studies. One cosm study reported reduced 

number of animals reaching metamorphosis at 0.1 μg/L; however, growth and age at 

metamorphosis were not affected (Langlois et al. 2010). No effect on metamorphosis was also 

reported for other cosm studies at concentrations from 6.4 to 197 μg/L (Relyea et al,. 2009; 

Rohr and Crumrine, 2005; and Du Preez et al., 2008). In the cosm studies, growth effects were 

observed around 200 μg/L for R. sphenocephala and B. americanus (Boone and James, 2003; 

Diana et al., 2000) except for Relyea (2009) who reported increased body weight for gray tree 

frogs (H. versicolor) treated with 6.4 μg/L, although time to metamorphosis was not affected. 

For behavioral modifications, the cosm study by Rohr and Crumrine (2005) reported a decrease 

in the percentage of R. sylvatic tadpole hiding and an increase in tadpole activity compared to 

the control at 50 μg/L. In another cosm study, Rohr et al. (2008) reported a decrease in 

melanomacrophages in R. pipiens and eosinophils with an increase in trematode cysts in R. 

palustris at an atrazine concentration of 117 μg/L. Survival was reported as significantly lower 

for R. pipiens but not for R. palustris, compared to control. A cosm study by Langlois et al.

(2010) reported a change in brain and tail biochemistry (changes in estrogen receptor-α and tail 

dio3 enzyme (involved in thyroid conversion)) in R. pipiens at an atrazine concentration of 1.8 

μg/L. In the cosm study by Langlois et al. (2010) a significant change in sex ratio was observed 

at 1.8 μg/L for R. pipiens. 

7.5. Evaluation of Overall Test Design Elements 

After compiling studies within one of the identified endpoints above, visually comparing specific 

study design elements (e.g., solvent use, tank vessel material) between the studies did not 

reveal any obvious relationship. Also, there does not appear to be a clear dose-response for 

any endpoint across species. Similar to the situation and range of uncertainties that the SAP 

was asked to evaluate in 2003, EPA has been unable to find any clear and consistent effects 

correlated to atrazine exposures across amphibian species, in spite of the large number of 

studies that purport that such effects exist. A major deficiency with the available amphibian 

data is the lack of an adequately standardized protocol for chronic amphibian testing, especially 

in regards to husbandry for native species. The available amphibian data represent a variety of 

methodologies that have various uncertainties, which limit the ability to discern effects from 

atrazine without confounding factors. The one study in which all of the identified test design 

elements were accounted for remains the one that was conducted in response to the DCI in 

2004 (which was comprised of two studies conducted in parallel at two different laboratories). 
84

This study did not demonstrate any consistent, concentration-dependent effects of atrazine on 

sexual development, metamorphosis, growth and survival of X. laevis at atrazine concentrations 

of 0.01 to 100 μg/L (referenced in 2007 SAP and in Kloas et al., 2009). The SAP in 2007 

expressed concern regarding the extent to which Xenopus can be considered representative of 

native species, while the SAP in 2003 could not identify any compelling reason why the species 

could not serve as a surrogate. Although a range of effects are noted in the open literature 

studies, the studies have internal inconsistencies (e.g., absence of a dose response, conflicting 

results) that make it difficult to generalize about any trends across studies. Previously 

identified uncertainties regarding the potential effects of atrazine on native species (e.g., R. 

pipiens) and potential effects of the compound on sexually mature adults or immune response 

have not been resolved through the available open literature. Therefore, at this time, EPA does 

not have additional data on amphibians that is sufficient and robust which alters its 

quantitative understanding of the potential toxicity of atrazine to this taxon. 

7.6. Other Evaluations – Published Literature Reviews 

The EPA is aware of previous attempts to investigate a relationship between atrazine exposure 

and adverse effects on amphibians as well as other taxa since the 2007 SAP (Rohr and McCoy, 

2010; Hayes et al., 2011; Solomon et al., 2008; Mann et al., 2009; Vandenberg et al., 2012; 

Bernanke and Köhler, 2008; Hayes et al., 2010). For an open literature paper to be considered 

for potential inclusion in a risk assessment, the paper is the primary source of the data (US EPA, 

2011). Therefore, while the references in the literature review paper may be extracted for 

screening for further potential review, the literature review papers themselves are typically not 

considered for further review. 

In the paper by Rohr and McCoy (2010), a similar binning exercise as the one described above 

was conducted. The authors made determinations about the inclusion/exclusion of data in 

their evaluation. Primary reasons for exclusion of this paper include inadequate reporting of 

statistical parameters or inappropriate analyses, and control contamination. These factors are 

very important in being able to infer causality. Their analysis included studies that showed 

trends and studies in which compounds other than atrazine were present (e.g., mixtures and 

agricultural sites). Evaluation of potential effects in this paper was done by tallying the number 

of studies that reported an effect and those that did not. This process gave equal weight to 

each represented study regardless of potential confounding factors beyond those that were 

considered in their analysis. The authors stated that for survival endpoints, their general 

conclusions from the studies are consistent with other reviews (Giddings et al.. 2005; Huber 

1993 and Solomon et al. 1996, 2008) in that there is no consistent published evidence that 

atrazine (at environmentally relevant concentrations) is directly toxic to fish or amphibians with 

some important exceptions (e.g., Alvarex and Fuiman 2005; Rohr et al.. 2006b, 2008c, Storrs 

and Kiesecker 2004). The study authors conclude that while there is much left to learn about 
85

atrazine effects, they identified several consistent effects of atrazine that must be considered 

when conducting a cost-benefit analysis. 

The review by Hayes et al.(2011) evaluated atrazine effects on demasculinization and 

feminization of male gonads across vertebrate classes including amphibians. This review 

examines the effects of atrazine on sexual development for different vertebrate classes 

applying the nine “Hill criteria.” The authors identify studies in which they believe support each 

of the nine criteria. The study authors state that the situation of atrazine as an endocrine 

disruptor which demasculinizes and feminizes male vertebrates meets all nine of the “Hill 

criteria”.

In the review by Solomon et al. (2008), a similar effort has described above was used in which 

the authors evaluated laboratory and field studies and assessed causality using procedures 

derived from Koch’s postulates and the Bradford-Hill guidelines. The authors state that they 

identified strengths and uncertainties, and some studies were omitted from their summary 

tables due to concerns about data quality. The authors report that on a weight of evidence 

analysis, the theory that atrazine at environmentally-relevant concentrations affect 

reproduction and/or reproductive development in fish, amphibians and reptiles is not 

supported by vast majority of observations. They further state that this conclusion holds for 

other theories (e.g., effects on biochemical endpoints, immune function, or parasitism). 

An examination of amphibians and agricultural chemicals was presented by Mann et al. (2009). 

Effects on amphibians, in addition to potential mechanisms of toxicity, from chemicals such as 

atrazine among others were discussed. Similar to the other reviews, the study authors 

identified studies that reported effects as well as reported no effects for various endpoints such 

as sexual development, metamorphosis, growth and immune response. The study authors 

argue that more emphasis needs to be placed on examining pesticide mixtures. 

A review by Vandenberg et al. (2012) on low-dose effects and nonmonotonic dose response 

included a discussion on atrazine exposure and sexual development. The study authors cite 

studies in which effects on sexual development were reported as well as studies that reported 

no effects. For amphibians, based on a weight-of-evidence (reported as taking together the 

results from the studies that reported effects along with one negative study), the study authors 

conclude that low-dose atrazine adversely affects sexual differentiation. 

A paper (Bernanke and Köhler 2008) on the impact to wildlife vertebrates from environmental 

chemicals included a discussion about atrazine. As before, the study authors discuss the impact 

of pesticides and cite studies which report effects to amphibians from atrazine exposure for 

several different endpoints such as survival, metamorphosis, behavior modifications, and sexual 

development. 
86

A paper on potential causes for amphibian declines (Hayes et al. 2010) cites studies that report 

effects from atrazine exposure on sexual development and behaviors, metamorphosis, uptake 

of atrazine and immune/infection response. 

Studies which serve as a foundation for the authors’ analysis/discussions have been previously 

reviewed by both EPA and FIFRA SAPs and determined to have limited confidence in the 

reported results. Similar to the analysis discussed in this document, these studies cannot 

reasonably be used to make inferences to refute or confirm the various hypotheses that have 

been developed regarding the potential effects of atrazine on amphibians. 

 

While some of the literature reviews discussed above comment on the exclusion of studies 

based on various factors, the EPA does not think that the extent of the exclusion criteria that 

appeared to be used in these reviews is robust enough to allow for equal comparison among 

the remaining filtered studies. It appears that the overall process (weight of evidence 

approach) used to evaluate the potential for atrazine to exert adverse effects on amphibians, 

after their exclusion process, is a tally system. Given that EPA has differing levels of confidence 

in these studies, EPA does not believe those procedures are adequate to capture the complex 

nature of the data and reach a weight-of-the-evidence determination about the hazards to 

amphibians. 

7.7. Evalution of Amphibian Studies and Adverse Outcome Pathways 

The available amphibian data suggest that the range of effects reported for amphibians 

exposed to atrazine vary considerably between species and that the majority of these 

measurement endpoints do not appear to exhibit a monotonic dose response. Effects on 

metamorphosis, growth and development as well as sexual development have been reported. 

Some of these endpoints are linked, such as size in regards to time to metamorphosis, and 

therefore significant differences for one endpoint may be autocorrelated to another effect 

endpoint. Many uncertainties and concerns in the conduct and results of the available 

amphibian data have been identified. Therefore, it is difficult to make definitive conclusions 

about the impact of atrazine at a given concentration. At this time, there is insufficient 

information or data on atrazine to make inferences about molecular initiating events that 

ultimately lead to an adverse outcome, i.e., capable of affecting the survival, growth and 

reproduction of amphibians, which is readily replicated and of sufficient rigor to enable its use 

in risk assessments. However, the EPA will continue to review data as they become available.
87

CHAPTER III. ANALYSIS PLAN 

8. Conceptual Model 

For a pesticide to pose an ecological risk, it must reach ecological receptors in biologically 

significant concentrations. An exposure pathway is the means by which a pesticide moves in the 

environment from a source to an ecological receptor. For an ecological pathway to be 

complete, it must have a source, a release mechanism, an environmental transport medium, a 

point of exposure for ecological receptors, and a feasible route of exposure. 

The conceptual model for atrazine provides a written description and visual representation of 

the predicted relationships between atrazine, potential routes of exposure, and the predicted 

effects for the assessment endpoint. A conceptual model consists of two major components: 

risk hypothesis and a conceptual diagram (USEPA, 1998).

Based on the submitted environmental fate data, atrazine is expected to leach to ground water 

and move to surface water through runoff and spray drift. 

Based on previous ecological risk assessments for atrazine, there is the potential for risk for 

federally listed threatened/endangered (hereafter referred to as “listed”) and non-listed birds, 

mammals, plants and aquatic species from labeled atrazine uses. Because of the potential risk 

for direct effects to taxa (both listed and non-listed) described above and in the previous 

assessments, listed species in all taxa may potentially be affected indirectly due to alterations in 

their habitat and prey items (e.g., food sources, shelter, and areas to reproduce). These 

preliminary conclusions are used to derive the risk hypothesis and conceptual diagram 

discussed below. 

8.1. Risk Hypothesis 

A risk hypothesis describes the predicted relationship among the stressor, exposure, and 

assessment endpoint response along with the rationale for their selection. For atrazine, the 

following ecological risk hypothesis is being employed for this ecological risk assessment: 

Based on the application methods, mode of action, fate and transport, and the 

sensitivity of non-target aquatic and terrestrial species, atrazine has the potential to 

reduce survival, reproduction, and/or growth in non-target terrestrial and aquatic 

organisms as well as negatively affect the structure, productivity, and function of 

aquatic plant communities when used in accordance with the current labels. These 

non-target organisms include listed and non-listed species. 
88

8.2. Conceptual Diagram 

The environmental fate properties of atrazine indicate that runoff, leaching, spray drift and 

direct spray represent potential transport mechanisms to aquatic and terrestrial habitats where 

non-target organisms may be exposed. Additional pathways are considered for the evaluation 

to identify other potential routes of exposure that may be of concern. These transport 

mechanisms (i.e., sources) are depicted in the conceptual diagrams below (Figure 11, Figure 12, 

and Figure 13) along with the receptors of concern and the potential attribute changes in the 

receptors from exposures to atrazine. 

Figure 11. Conceptual Model for Atrazine Effects on Aquatic Organisms. 
89

Figure 12. Conceptual Model for Atrazine Effects on Terrestrial Organisms. 
90

Figure 13. Conceptual Model for Atrazine Routes of Exposure for Terrestrial Animals. 

In order to address the risk hypothesis, the potential for adverse effects on the environment 

will be estimated. The use, environmental fate, and ecological effects of atrazine will be 

characterized and integrated to assess the risks. There are two distinct components to the 

effects analysis: one for risk to aquatic plants and aquatic plant communities, and the other to 

all other organisms. 

For all taxa not considered to be aquatic plants, in a screening level ecological risk assessment, 

risk characterization is based on a deterministic approach using the risk quotient (RQ) method 

which compares exposure over toxicity (USEPA 2004). For the toxicity value component, the 

lowest toxicity value (e.g., LC50 or NOAEC) that is deemed appropriate for quantitative use is 

chosen from the available atrazine toxicity dataset. 

The EPA’s process to determine the level of concern (LOC) for atrazine in aquatic ecosystems to 

protect aquatic organisms and the methodology used to identify watersheds that exceed this 

LOC are described below. A different treatment is given to aquatic plant effects than other taxa 
91

(i.e., the RQs) because, although aquatic plants are generally more sensitive than fish and 

aquatic invertebrates, the risk assessment endpoint is community structure/function rather 

than growth, reproduction, and survival of an individual species. The LOC methodology uses 

single-species plant toxicity data and microcosm/mesocosm (cosm) studies to determine what 

atrazine exposure patterns and concentrations can cause adverse effects on aquatic plant 

communities. Before these cosm effects can be applied, there is a need for a quantitative 

measure of the relative severity of different exposure time series needs to be developed to 

compare effects among different experimental ecosystem exposure and to extrapolate these to 

the field. 

The aquatic plant community LOC is derived to ensure that the atrazine concentrations in 

watersheds do not cause detrimental changes in aquatic plant community structure and 

productivity. While the LOC is based on effects to aquatic plant communities, by ensuring 

protection of primary producers, it is intended to provide protection for the entire aquatic 

ecosystem, including fish, invertebrates, and amphibians. 

This analysis plan will be revisited and may be revised depending upon a full review of the data 

available in the open literature and the information submitted by the public in response to the 

opening of the Registration Review docket. 

9. Measures of Exposure

In order to estimate risks of atrazine exposures in aquatic and terrestrial environments, all 

exposure modeling and resulting risk conclusions will be made based on maximum application 

rates for the currently registered uses as discussed in Section 3. Measures of exposure are 

based on aquatic and terrestrial models that estimate environmental concentrations of atrazine 

using maximum labeled application rates and application methods that have the greatest 

potential for off-site transport of the chemical. The models used to generate aquatic estimated 

environmental concentrations (EEC) are the Pesticide Root Zone Model (PRZM) coupled with 

the EXposure Analysis Model System (EXAMS). Model input values will be consistent with the 

most recent version of the Input Parameter guidance (current version 2.1). Additionally, 

measure of exposures, when possible, will be evaluated using monitoring data (Chapter IV). 

 PRZM (current version 3.12.3, June 2006) and EXAMS (current version 2.98.04.06, April 2005) 

are simulation models coupled with the graphical user interface, PE5 (PRZM EXAMS Model 

Shell; v5.0, November 2006), which incorporates the standard scenarios developed by EFED. 

The models generate daily exposures and 1-in-10-year EECs of atrazine that may occur over a 

30-year period in surface water bodies adjacent to pesticide application sites. PRZM simulates 

application, movement, and transformation of a pesticide on an agricultural field and the 

resultant pesticide loadings to a receiving water body via runoff, erosion, spray drift, and 

leaching. EXAMS simulates the fate of the pesticide and resulting concentrations in the 
92

receiving water body. Additional information on these models can be found at: 

http://www.epa.gov/oppefed1/models/water/models4.htm#surface_water 

The standard watershed geometry used for ecological pesticide assessments assumes 

application to a 10-hectare agricultural field that drains into an adjacent 1-hectare water body 

that is 2 meters deep (20,000 m3 volume) with no outlet. The composite model PRZM/EXAMS is 

used to estimate screening-level exposure of aquatic organisms to atrazine. The measure of 

exposure for aquatic species is the 1-in-10-year peak or rolling mean concentration. The 1-in10-year peak is used for estimating acute exposures of direct effects to aquatic organisms. The 

1-in-10-year 60-day mean is used for assessing the effects to fish and aquatic-phase amphibians 

from chronic exposure. The 1-in-10-year 21-day mean is used for assessing the effects on 

aquatic invertebrates from chronic exposure. Surface water monitoring data will also be 

considered in aquatic exposure assessment. 

The model used to produce terrestrial EECs on food items is T-REX, while the model used to 

derive EECs relevant to terrestrial and wetland plants is TerrPlant. Detailed information about 

the models T-REX and TerrPlant, can be found on the EPA’s website at 

http://www.epa.gov/pesticides/science/models_pg.htm#terrestrial. The AgDRIFT spray drift 

model (v2.01; May 2001; http://www.agdrift.com/AgDRIFt2/DownloadAgDrift2_0.htm) is used 

to assess exposures of organisms to atrazine deposited on terrestrial or aquatic habitats by 

spray drift. 

The Screening Imbibition Program (SIP v.1.0, Released June 15, 2010) was used to calculate an 

upper bound estimate of exposure to wildlife via drinking water using atrazine’s aquatic 

solubility limit (33 mg/L), and the most sensitive acute and chronic avian toxicity endpoints. 

Drinking water exposure alone was determined to be a potential pathway of concern for avian 

or mammalian species on a chronic basis but not on an acute basis. This pathway will be 

explored further with the development of SIP v.2.0 in the Ecological Risk Assessment for 

atrazine. Detailed information about the SIP v.1.0, as well as the tool, can be found on the EPA’s 

website at http://www.epa.gov/pesticides/science/models_pg.htm#terrestrial. 

The Screening Tool for Inhalation Risk (STIR v.1.0, November 19, 2010) was used to calculate an 

upper bound estimate of exposure to atrazine through inhalation. This calculation used 

atrazine’s vapor pressure (2.89 x 10-7 torr) and molecular weight (215.69 g/mole) for vapor 

phase exposure, the maximum application rate (4 lbs a.i./acre) and method of application for 

spray drift, and acute and chronic avian and mammalian toxicity values. Results of the model 

run indicated that inhalation exposure via spray drift and/or vapor-phase of atrazine alone did 

not appear to be a concern. Detailed information about STIR v.1.0, as well as the tool, can be 

found on the EPA’s website at:

http://www.epa.gov/pesticides/science/models_pg.htm#terrestrial. 
93

10. Measures of Effect

 

Ecological effects data are used as measures of direct and indirect effects to biological 

receptors. Data are obtained from registrant-submitted studies or from literature studies 

identified by ECOTOX (USEPA 2007c). The ECOTOX database provides more ecological effects 

data in an attempt to bridge existing data gaps, and is a source for locating single chemical 

toxicity data and potential chemical mixture toxicity data for aquatic life, terrestrial plants, and 

wildlife. ECOTOX was created and is maintained by the USEPA, Office of Research and 

Development, and the National Health and Environmental Effects Research Laboratory's MidContinent Ecology Division. 

Information on the potential effects of atrazine on non-target animals is also collected from the 

Ecological Incident Information System (EIIS; USEPA 2007d). The EIIS is a database containing 

adverse effects (typically mortality) reports on non-target organisms where such effects have 

been associated with the use of pesticides. 

Incidents reported in the aggregate incident reports and the Avian Incident Monitoring System 

(AIMS) will also be searched. AIMS is a database administered by the American Bird 

Conservancy (it was partially funded by the EPA). It contains publicly available data on reported 

avian incidents involving pesticides 

http://www.abcbirds.org/abcprograms/policy/toxins/aims/aims/login.cfm?CFID=139273599&CF

TOKEN=96183257

Where available, sub-lethal effects observed in both registrant-submitted and open literature 

studies will be evaluated qualitatively. Such effects may include behavioral changes such as 

lethargy and changes in coloration. Quantitative assessments of risks, though, are limited to 

those endpoints that can be directly linked to the EPA’s assessment endpoints of impaired 

survival, growth, and reproduction. 

11. Integration of Exposure and Effects

Risk characterization is the integration of exposure and ecological effect characterizations to 

determine the potential ecological risk from the use of atrazine and the likelihood of direct and 

indirect effects to non-target organisms in aquatic and terrestrial habitats. The exposure and 

effects data are integrated in order to evaluate potential adverse ecological effects on nontarget species. For the assessment of atrazine risks, the risk quotient (RQ) method is used to 

compare estimated exposure and measured single-species toxicity values. Acute and chronic 

EECs from are divided by acute and chronic single-species toxicity values. The resulting RQs are 

then compared to the EPA’s Levels of Concern (LOC) (USEPA 2004). In addition, the Agency will 

assess atrazine risk to aquatic plant communities, and thus all aquatic organisms, with an 

Agency developed method for determining the aquatic plant community LOC. EPA’s method is 
94

described below in Chapter IV. These criteria are used to indicate when atrazine’s use, as 

directed on the labels, has the potential to cause adverse direct or indirect effects to non-target 

organisms and communities. In addition, incident data from EIIS, aggregate incident reports, 

and AIMS will be considered as part of the risk characterization. 
95

Chapter IV. METHODOLOGY FOR DETERMINING THE LEVELS OF CONCERN FOR ATRAZINE. 

12. The Risk Quotient Method and Levels of Concern for Terrestrial Plants and Terrestrial and 

Aquatic Animals. 

The Risk Quotient Method is used to integrate the results of exposure and ecotoxicity data. For 

this method, Risk Quotients (RQs) are calculated by dividing exposure estimates by the acute 

and chronic ecotoxicity values (i.e., RQ = EXPOSURE/TOXICITY). These RQs are then compared 

to OPP's levels of concern (LOCs). These LOCs are criteria used by OPP to indicate potential risk 

to non-target organisms and the need to consider regulatory action. EFED has defined LOCs for 

acute risk, acute restricted use classification, acute and chronic risk to endangered species. Risk 

presumptions, along with the corresponding RQs and LOCs are summarized in Table 18. 
96

Table 18. Risk Presumptions and LOCs

Risk Presumption RQ LOC

Birds1

Acute Risk EEC/LC50 or LD50/sqft or LD50/day 0.5

Acute Restricted Use EEC/LC50 or LD50/sqft or LD50/day (or LD50 < 50 mg/kg) 0.2

Acute Endangered Species EEC/LC50 or LD50/sqft or LD50/day 0.1

Chronic Risk EEC/NOEC 1

Wild Mammals1

Acute Risk EEC/LC50 or LD50/sqft or LD50/day 0.5

Acute Restricted Use EEC/LC50 or LD50/sqft or LD50/day (or LD50 < 50 mg/kg) 0.2

Acute Endangered Species EEC/LC50 or LD50/sqft or LD50/day 0.1

Chronic Risk EEC/NOEC 1

Aquatic Animals2

Acute Risk EEC/LC50 or EC50 0.5

Acute Restricted Use EEC/LC50 or EC50 0.1

Acute Endangered Species EEC/LC50 or EC50 0.05

Chronic Risk EEC/NOEC 1

Terrestrial and Semi-Aquatic Plants 

Acute Risk EEC/EC25 1

Acute Endangered Species EEC/EC05 or NOEC 1

1

 LD50/sqft = (mg/sqft) / (LD50 * wt. of animal) 

 LD50/day = (mg of toxicant consumed/day) / (LD50 * wt. of animal) 

2

 EEC = (ppm or ppb) in water 
97

13. The Method for Determining the Level of Concern for Aquatic Plant Communities 

While reviewing this section, please consider the charge questions below. 

SAP Questions: 

 The Aquatic Plant Community CE-LOC methodology for atrazine is a four stage 

process that uses single-species plant toxicity data and cosm studies to discern 

atrazine concentrations and exposure durations that may cause adverse effects on 

aquatic plant communities. As a result, a CE-LOC for atrazine is developed which, 

together with monitoring data, can be used to identify watersheds where 

concentrations may result in adverse effects to aquatic plant community structure, 

function, and/or productivity. Please comment on the methodology EPA has used 

to derive the atrazine CE-LOC for aquatic plant communities, and in particular on 

EPA’s characterization of the uncertainties and assumptions in this methodology 

(Chapter IV, Sections 13 & 14). 

 The 2009 SAP recommended using an effects index or concentration metric, rather 

than categorical LOC thresholds in order to take advantage of data from Syngenta’s 

Atrazine Ecological Exposure Monitoring Program (AEEMP). At that time the LOC 

threshold for atrazine effects to plant communities was established at 10 μg/L for a 

60-day rolling average. The current analysis using the Plant Assemblage Toxicity 

Index (PATI) indicates the CE-LOC can range from 4 to 7 μg/L (Chapter IV, Section 

14.3 & 14.4). Please comment on this CE-LOC and whether it reasonably represents 

a range below which permanent or irreversible change in aquatic plant community 

structure, function, and/or productivity due to atrazine exposure would not be 

expected. 

 Based on previous analyses of the available ecotoxicity data, EPA concluded for 

atrazine that the level of concern for effects on aquatic plant communities (CE-LOC) 

was lower than the atrazine concentrations observed to produce significant direct 

or indirect effects on invertebrates, fish and amphibians. Given the current analysis 

of the ecotoxicity data (Chapter I, Section 6) and the Aquatic Plant Community LOC 

methodology, EPA continues to believe the original conclusion still holds true. 

Please comment on how well the available database supports EPA’s conclusion that 

the CE-LOC is lower than exposures that result in significant effects on the growth, 

survival and reproduction of aquatic animals. 
98

The Aquatic Plant Community LOC Methodology. 

The focus of this methodology is to determine a level of concern at which atrazine 

concentrations would negatively affect the productivity and composition of aquatic plant 

communities. LOC calculations are typically based on laboratory toxicity studies of individual 

species and calculated based on the RQs (See Section 12). With atrazine, the concern is the 

effect of atrazine on the individual species as well as effects to the whole community. Atrazine 

has been the subject of various microcosm and mesocosm (cosm) studies in which such effects 

have been documented (Appendix D). These studies serve as the foundation for identifying 

atrazine exposures that are detrimental to aquatic plant communities. However, the 

concentration and length of exposure varied markedly among these cosm studies. The lengths 

of the studies varied from one week to one year, and the concentrations remained constant or 

steadily declined over the exposure period. These studies demonstrate that there is a need to 

relate the concentration and length of exposure across all cosm studies and the effects they 

have on the cosm. 

The issue of comparing effects across different exposure time-series becomes even more 

important when trying to relate observed effects in cosms to expected effects in natural 

systems. Atrazine enters lakes, streams, and rivers primarily as a result of rainfall-driven runoff. 

This results in highly variable and episodic exposures that can be linked to rainfall distribution, 

atrazine application patterns, and geology (e.g. topography, and soil properties). Figure 14

provides examples of atrazine chemographs (graphs showing exposure levels over time, note 

different y-axis scales) measured in streams in the Midwestern U.S. (raw data available to the 

public at: EPA-HQ-OPP-2003-0367-0178, EPA-HQ-OPP-2003-0367-0205, and EPA-HQ-OPP-2003-

0367-0206). These highly variable exposures are markedly different from the exposures typical 

of laboratory toxicity tests and cosm studies, which have a defined duration (typically between 

6 and 60 days) and relatively constant or steadily declining concentrations. They also differ from 

the exposures expected in lakes and reservoirs, which tend to be more steady over time. There 

is thus a need for a method to quantify the relative toxic severity of different exposure time 

series in order to relate effects between different cosm exposures and to extrapolate effects 

from cosm exposures to field exposures. 
99

The primary goal is to be able to extrapolate the toxicity of different atrazine concentrations 

and length of exposure times from cosm studies to the concentrations and length of exposure 

occurring in the natural environment. It should be noted that the Comprehensive Aquatic 

Systems Model (CASM) was evaluated in the context of this goal; however, it was judged 

unsuitable for use on a national scale (Appendix F). Although CASM can have utility for certain 

site specific assessments, it was found to be too uncertain for the purpose here of a generic 

tool for the relative toxic impact of different exposure time series. Furthermore, risk 

characterizations using CASM provided no clear added value, differing negligibly from 

characterizations from much simpler methods, and involving uncertain and complex 

parameterization. As an alternative to CASM, EPA developed the Plant Assemblage Toxicity 

Index (PATI), which uses single-species aquatic plant toxicity data to estimate the relative 

severity of any atrazine concentration on an aquatic plant community. Additional tools such as 

species sensitivity distributions or the calculation of the 5th percentile hazard criterion (USEPA 

2012b), result in similar results of the methodology using PATI but do not account for the 

durations of exposure needed to assess risk to aquatic plant communities. 

The LOC methodology is a four stage process (Figure 15) that uses single-species plant toxicity 

data and cosm studies to discern what atrazine exposure patterns and concentrations can 

cause adverse effects on aquatic plant communities. With this methodology an LOC is 

Figure 14. Examples of atrazine exposure time-series for natural freshwater systems.
100

Stage 2: Use single species toxicity studies on 

aquatic plants to develop an average toxicity 

relationship (PATI relationship) representing the 

average % reduction in growth rate across all 

aquatic plants. The PATI distribution is used to 

calculate daily and cumulative PATI values for 

cosm studies (Stage 3a) and environmental 

monitoring data (Stage 4a).

Stage 1. Evaluate cosm data and categorize 

those showing effects versus those showing 

no effects.

Stage 4a. Determine daily PATI values for 

cosm chemographs and calculate a 60-day 

cumulative PATI value for each monitoring

chemograph. 

Stage 3a. Determine daily PATI values for 

cosm chemographs and calculate a 60-day 

cumulative PATI value for each cosm study.

Stage 3b. Set LOCPATI to distinguish 

accumulated PATI values associated with 

cosm studies that showed adverse effects 

from cosm studies that did not show adverse 

effects.

Stage 4c. Convert the LOCPATI into the 

Concentration Equivalent LOC.

Stage 4b. Identify the watersheds with 

monitoring chemographs that have 

accumulated PATI values that exceed the 

LOCPATI.

developed which, together with monitoring data, can be used to identify watersheds where 

atrazine levels may result in adverse effects to the aquatic plant community structure and 

function. 

Figure 15. The four-stage process to set an LOC for atrazine 

Stage 1: Summarize Toxic Effect to Communities Based on Microcosm and Mesocosm Studies. 

For atrazine, an extensive set of cosm studies have documented effects of atrazine on plant 

community structure and productivity (Appendix D). These tests can be used to decide what 

60-day cumulative value of PATI should be considered a LOC. In all, EPA is using 87 atrazine 

exposure values from 46 published articles on effects of atrazine on cosm systems (Figure 16). 

These 46 studies were selected from the larger pool of candidate studies because they met the 

established pre-screening and data quality criteria (Appendix D). The EPA reviewed each of the 

cosm studies that met the quality criteria in order to determine if atrazine-related effects were 

observed and at what atrazine concentration. Examples of atrazine-related effects observed in 
101

the cosm studies included reductions in aquatic plant biomass, concentration of chlorophyll A, 

rate of photosynthesis (14C uptake and oxygen production), and shifts in aquatic plant 

community structure (e.g., species composition and diversity) relative to a control. 

Stage 2: Summarize Toxic Effect Across An Aquatic Plant AssemblageBased on Single Species 

Toxicity Tests.

As noted above, a primary requirement for this methodology is to estimate the relative effects 

of different exposure time series on aquatic plant communities, in order to relate effects in 

different cosm exposures to each other and to extrapolate these effects to exposures in natural 

systems. PATI estimates such relative effects based on an aggregate of the toxicity 

relationships determined for individual aquatic plant species. This assemblage of test species is 

used as a surrogate for aquatic plant communities (only with regard to the relative effects of 

Figure 16. Effects of atrazine on experimental ecosystems as a function of exposure 

duration and average concentration. Squares denote adverse effects, open triangles no 

effects. 
102

different exposure time series). PATI is described and evaluated at length in Appendix E and is 

only summarized here (additional options and updates to PATI are provided in Appendix M). 

PATI represents an expansion of the Species Sensitivity Distribution (SSD) concept commonly 

used in aquatic risk assessments. SSDs summarize available toxicity tests as a statistical 

distribution of toxicity endpoints (e.g., EC50s – median effect concentrations) across different 

taxa (Table 19). PATI expands on this concept by, considering the entire toxicity relationship for 

plant taxa rather than the single level of effect embodied in EC50s and by determining the 

average effect across all taxa rather than focusing on a single taxon at a specific percentile in 

the SSD. PATI thus provides a more complete description of the reduction in productivity of an 

assemblage of plants and of the driving force for atrazine effects on aquatic plant communities. 

The toxicity relationship for each taxon is the relationship between the reduction in growth rate 

and the concentration of atrazine. For example in the middle panel of Figure 17, curve #1 

shows that as atrazine concentration increases, the percent of growth rate reduction also 

increases. With higher concentrations there is a reduction in the growth of the taxon (i.e., there 

is a toxic response). This curve represents the toxicity relationship for a single plant taxon. PATI 

assembles the toxicity relationships from many different taxa of plants and calculates the 

average toxicity relationship. This represents the average reduction in growth rate across all 

taxa and concentrations and is called the PATI relationship (Figure 17, lower panel). At 50 μg/L, 

the average effect (growth rate reduction) over all genera is 19%, providing the PATI value in 

the bottom panel (arrow). Thus, rather than just providing the percentage of taxa that have an 

EC50 below some concentration (e.g., 50 μg/L corresponds roughly to the 16th percentile on 

the SSD), PATI describes the percent reduction in plant production for the entire assemblage 

(weighting each taxon equally) (Appendix E). 

Table 19. Compiled data regarding atrazine toxicity to aquatic plants. All data pertain to the specific growth rate 

(SGR) of the plant. Compilation includes the EC50 for the SGR, a steepness measure, and the SGR of the control

(SGRc) under test conditions. Italicized EC50s denote values whose estimation required information on SGRc

and/or steepness from other studies.

Piecewise 

Linear Model

Sigmoidal 

Threshold 

Model

Logistic 

Model

Appendix D 

Report Values 

(Logistic)

Genus SGR 

EC50

Steep SGR 

EC50

Steep SGR 

EC50

Steep SGR 

EC50

Steep SGRC Reference

Ankistrodesmus

112.7 1.017 105.2 1.485 104.3 1.412 104 1.41 0.33 Burrell et al. 1985

138 127 124 119 Larsen et al. 1986

Chlamydomonas

421.7 0.516 386.8 0.677 378.3 0.652 378 0.65 Kallqvist and 

Romstad 1994

147 142 139 141 1.06 Schafer et al. 1993

78 71 70 67 Larsen et al. 1986
103

Table 19. Compiled data regarding atrazine toxicity to aquatic plants. All data pertain to the specific growth rate 

(SGR) of the plant. Compilation includes the EC50 for the SGR, a steepness measure, and the SGR of the control

(SGRc) under test conditions. Italicized EC50s denote values whose estimation required information on SGRc

and/or steepness from other studies.

Piecewise 

Linear Model

Sigmoidal 

Threshold 

Model

Logistic 

Model

Appendix D 

Report Values 

(Logistic)

Genus SGR 

EC50

Steep SGR 

EC50

Steep SGR 

EC50

Steep SGR 

EC50

Steep SGRC Reference

45 45 45 45 Hersh and 

Crumpton 1989

Chlorella

26.3 0.905 25.5 1.066 25.3 1.038 26 1.07 1.4-2.4 Faust et al. 1993

37 37 37 37 Hersh and 

Crumpton 1989

99.8 0.391 92.8 0.505 91.2 0.474 91 0.47 0.26 Burrell et al. 1985

645 592 580 557 Larsen et al. 1986

480 480 480 480 Stratton 1984

Scenedesmus

101 92 90 87 Larsen et al. 1986

300 300 300 300 Stratton 1984

39.1 0.662 39.2 0.729 38.9 0.716 39 0.73 Zagorc-Koncan 

1996

Selenastrum

164 0.491 164 0.752 164 0.792 164 0.79 1.80 Mayer et al. 1998

1.93 Radetski et al. 

1995

54.7 1.171 50.8 1.623 49.6 1.658 50 1.66 1.25 Caux et al. 1996

100 100 100 100 1.50 Versteeg 1990

134.5 0.533 130.2 0.656 130.7 0.617 131 0.62 1.75 Hoberg 1991A

70 70 70 70 Turbak et al. 1986

191.0 0.735 173.2 1.080 171.7 1.038 163 1.22 1.65 Roberts et al. 

1990

128.1 0.858 124.5 1.114 124.6 1.065 125 1.07 1.01 Gala and Giesy 

1990

110 0.656 110 0.906 110 0.900 110 0.90 Kallqvist and 

Romstad 1994

202.1 0.565 205.0 0.791 200.6 0.787 201 0.79 Kallqvist and 

Romstad 1994

231.4 0.691 237.9 1.026 236.4 1.012 236 1.01 van der Heever and 

Grobbelaar 1996
104

Table 19. Compiled data regarding atrazine toxicity to aquatic plants. All data pertain to the specific growth rate 

(SGR) of the plant. Compilation includes the EC50 for the SGR, a steepness measure, and the SGR of the control

(SGRc) under test conditions. Italicized EC50s denote values whose estimation required information on SGRc

and/or steepness from other studies.

Piecewise 

Linear Model

Sigmoidal 

Threshold 

Model

Logistic 

Model

Appendix D 

Report Values 

(Logistic)

Genus SGR 

EC50

Steep SGR 

EC50

Steep SGR 

EC50

Steep SGR 

EC50

Steep SGRC Reference

185.3 0.407 215.3 0.599 222.4 0.610 223 0.61 van der Heever and 

Grobbelaar 1997

104.4 1.302 101.7 1.694 101.1 1.610 101 1.61 0.97 Parrish 1978

90 83 81 78 Larsen et al. 1986

Stigeoclonium 367 336 330 317 Larsen et al. 1986

Ulothrix 184 169 166 159 Larsen et al. 1986

Cryptomonas 574.9 0.827 516.3 1.106 493.5 1.151 494 1.15 Kallqvist and 

Romstad 1994

Cyclotella

479.9 1.079 471.2 1.290 461.8 1.215 462 1.22 Kallqvist and 

Romstad 1994

102.9 0.615 102.1 0.721 100.2 0.674 100 0.67 Millie and Hersh 

1987

117.7 0.607 117.1 0.696 114.4 0.646 114 0.65 Millie and Hersh 

1987

236.2 0.922 224.9 1.031 225.2 0.996 225 1.00 Millie and Hersh 

1987

Navicula 217.8 0.919 216.6 1.104 216.7 1.080 217 1.08 1.03 Hughes et al. 1988

Anabaena

70 70 70 70 Stratton 1984

280 280 280 280 Stratton 1984

470 470 470 470 Stratton 1984

767.2 0.497 718.5 0.621 705.7 0.588 706 0.59 0.76 Hughes et al. 1988

317 294 292 286 Larsen et al. 1986

Microcystis

168.4 1.043 167.0 1.350 164.2 1.252 164 1.25 0.55 Parrish 1978

557.2 0.569 609.3 0.806 602.8 0.768 605 0.77 Kallqvist and 

Romstad 1994

Synechococcus 154.9 0.504 136.6 0.606 136.0 0.593 136 0.59 Kallqvist and 

Romstad 1994

Ceratophyllum 25.2 0.979 23.6 0.718 24.4 0.813 24 0.81 0.035 Fairchild et al. 

1998

Elodea 104.6 0.230 73.9 0.244 64.7 0.226 65 0.38 Forney and Davis 

1981
105

Table 19. Compiled data regarding atrazine toxicity to aquatic plants. All data pertain to the specific growth rate 

(SGR) of the plant. Compilation includes the EC50 for the SGR, a steepness measure, and the SGR of the control

(SGRc) under test conditions. Italicized EC50s denote values whose estimation required information on SGRc

and/or steepness from other studies.

Piecewise 

Linear Model

Sigmoidal 

Threshold 

Model

Logistic 

Model

Appendix D 

Report Values 

(Logistic)

Genus SGR 

EC50

Steep SGR 

EC50

Steep SGR 

EC50

Steep SGR 

EC50

Steep SGRC Reference

<38 <38 <38 <38 0.011 Fairchild et al. 

1998

141.6 0.348 199.6 0.532 203.6 0.519 204 0.52 0.088 Hoberg 2007

Hydrilla 151.0 0.440 118.4 0.604 111.0 0.630 118 0.99 Hinman 1989

Lemna

207.1 1.161 201.9 1.261 201.9 1.235 202 1.24 0.279F Hoberg 1991B

102.4 1.045 95.4 1.410 93.2 1.327 93 1.33 0.252W Hoberg 1993B

61.3 1.076 65.2 1.621 66.2 1.704 49 1.71 0.226W Hoberg 1993C

128.9 0.425 124.7 0.462 115.4 0.420 115 0.42 0.205F Fairchild et al. 

1998

225.8 0.886 222.7 1.190 224.2 1.142 224 1.14 0.225F Hughes et al 1988

102 97 95 95 Kirby and Sheehan 

1994

91.0 1.017 90.2 1.221 89.9 1.183 90 1.18 0.396W Desjardin 2003

Myriophyllum <150 <150 <150 <150 0.01? Fairchild et al. 

1998

Najas sp. 14.5 1.359 14.5 1.750 14.5 1.670 15 1.67 0.066 Fairchild et al. 

1998

Potamogeton 53.7 0.549 61.6 0.728 62.8 0.695 63 0.69 Forney and Davis 

1981

Vallisneria 141.5 0.355 153.9 0.436 140.7 0.401 141 0.40 Forney and Davis 

1981
106

In the LOC methodology, the PATI relationship is used to specify the average reduction in plant 

growth rate for each day (daily PATI value) in both the cosm studies and the chemographs 

available from environmental monitoring data. Because of the rapid recovery of growth rates 

after atrazine exposures (e.g., Abou-Waly et al., 1991, Desjardin et al. 2003), daily PATI values 

need not consider residual toxicity from exposures on previous days, but rather only the toxicity 

for the current day’s exposure. 

The cumulative effects of an exposure through time (i.e., the total toxic severity of an exposure 

time series) will take into account the total effect on the community. The EPA addresses this 

total effect by summing the daily PATI values to produce a “cumulative PATI value.” Such a 

Figure 17. Comparison of toxicity relationships for 20 plant genera (middle panel), the SSD 

of EC50s for these genera (top panel), and the plant assemblage toxicity index (bottom 

panel, PATI = the average of the curves in the middle panel) (from Erickson 2012). 
107

summation cannot be indefinite, but rather is limited to an "assessment period," and this limit 

must reflect judgments about cumulative effects and the duration of the available cosm data. 

Because atrazine exposure outside the assessment period is considered inconsequential by 

PATI, the assessment period needs to be long enough to encompass (a) exposures of 

significance to establishing LOCPATI from the cosms (Figure 16) and (b) effects expected from 

seasonal field exposures (e.g., Figure 14). However, it should not be any longer than necessary, 

in order to avoid uncertain inferences regarding (a) cumulative effects of low concentrations 

and (b) widely separated exposures that are independent regarding ecological effects. 

The 60-day assessment period was chosen because it would include all or almost all periods of 

significant exposure in the AEEMP monitoring data, and would also encompasses the duration 

of all but a few of the cosm studies. A few additional considerations regarding this period 

relative to the treatments in the cosm studies should be noted (Appendix E):

 It is slightly shorter than the longest cosm study treatment with no effect. If the 

assessment period is significantly shorter than treatments with no effect, this will underrepresent how substantial exposures could be without causing effects and thus be too 

restrictive. 

 For those treatments with effects, a shorter period will also be too restrictive by 

assuming that less exposure is needed to elicit effects than actually is involved (e.g., an 

effect observed over a 60-day exposure would be assumed to require less exposure 

than actually was required). This consideration does not pertain to the few cosms with 

extremely long durations, because they simply verify significant effects for high PATI 

values. For the LOC, the important treatments with effects are those whose exposures 

near to those without effects. 

 That 60-day exposure is longer than many cosm treatments with effects is not an issue, 

provided the effects from these shorter exposures will still be considered unacceptable 

from the perspective of this longer assessment period. For example, if a 30-day 

exposure showing effects had been monitored for another 30 days without exposure, 

the effects during the first 30 days would be considered unacceptable despite any 

recovery that occurred during the second 30 days). 

One drawback to assessment periods longer than 63 days is that there is limited data from 

cosm studies that extend beyond this duration. The Agency determined the 60-day assessment 

period was most representative of the available data because most cosm studies were in the 7-

63 day duration range, and the LOC values derived for the 60-day assessment period should be 

protective of the shorter time periods. 
108

Stage 3: Calculate a Level of Concern for Aquatic Plant Communities Based on the PATI 

Relationship and the COSM Studies. 

To establish an LOC for aquatic plant communities based on PATI, the first task is to calculate a 

cumulative PATI value for each cosm study. Daily PATI values for a cosm exposure are first 

calculated by applying the PATI relationship (e.g., Figure 17) to each day's concentration. The 

cumulative PATI value for the cosm exposure is then based on the 60-day period that has the 

greatest cumulative PATI value. For example if a cosm study has an atrazine concentration of 50

μg/L and that concentration is held constant, based on the PATI relationship (Figure 17) the 

daily PATI value is 19%, and the 60 day cumulative PATI is 1140%-days. After this cumulative 

value has been calculated for all of the cosm studies the values are then combined with the 

effects/no effects classifications determined in Stage 1. 

The relationship of the cosm studies cumulative PATI values to their effects/no effects 

classification(s) (see Figure 16 and Figure 18) (Appendix D) is used to specify the LOCPATI (the 

LOC in cumulative PATI values). Figure 15 provides a binary plot of cosm treatment effects/no 

effects determinations versus their calculated 60-d cumulative PATI values. The LOCPATI is set as 

the cumulative PATI value that corresponds to a 50 percent probability of an effect based on a 

logistic binary regression conducted to determine the probability relationship (Appendix E). In 

other words, at a PATI score of 130, there is a 50:50 chance of having adverse effects. EPA risk 

management determined a 50 percent cutoff due to a variety of factors including variability in 

sensitivities of the cosm studies, magnitude and duration of effects observed in the cosm 

studies, statistical uncertainty in the calculation of the LOCPATI and ecological relevance of 

observed effects in the cosm studies. This LOCPATI is expressed in PATI values and needs to be 

converted to a concentration-based LOC to be more easily used by the regulatory agencies. This 

conversion is discussed in Stage 4 below. 

 
109

Stage 4: Determine if Watersheds Exceed the Concentration Equivalent Level of Concern 

Based on the PATI Distribution and the Environmental Monitoring Data. 

The first task is to calculate a cumulative PATI value for each environmental monitoring site. A 

daily PATI value is calculated for each day of the study, by taking the concentration for each day 

and finding the corresponding PATI value from the PATI relationship (see Figure 17 for an 

example). After each day has been calculated the 60-day period that has the greatest 

cumulative PATI value is recorded. For example if an environmental monitoring site had an 

atrazine chemograph as shown in the top panel of Figure 19, based on the PATI relationship 

(Figure 17) the daily PATI value would be variable depending on the daily concentration, and 

the maximum 60-day cumulative PATI would be 150. The monitoring sites with cumulative PATI 

values greater than the LOCPATI would be predicted to cause adverse effects to the ecological 

communities in those lakes, streams or rivers. 

To assess whether the LOCPATI is exceeded in natural systems, the next step is to quantify the 

difference between each of the environmental monitoring sites and the LOCPATI. The cumulative 

PATI value from each monitoring site chemograph (e.g. 150) is divided by the LOCPATI (Figure 

18). This number is called the Effects Exceedance Factor (EEF), and is similar to risk quotient 

Figure 6. Cosm studies plotted as effect (closed triangle)/no-effect (open triangles) versus 

PATI fitted to a logistic relationship for the probability of an effect versus PATI, this 

probability being 50% when PATI equals 130. 

 

Figure 18. Cosm studies plotted as effect (closed triangle)/no-effect (open triangles) 

versus PATI fitted to a logistic relationship for the probability of an effect versus 

PATI, this probability being 50% when PATI equals 140.
110

methods in most EPA risk assessments as it identifies high- or low-risk situations (for examples 

visit: EPA Risk Characterization).

Figure 19. Typical atrazine exposure chemograph from monitoring data (top panel). The 

calculated daily PATI values and cumulative PATI value for a 60-day window for the example 

chemograph in the top panel. 

To more easily use this information the LOCPATI is converted into a concentration-based LOC 

called the Concentration Equivalent Level of Concern (CE-LOC). The CE-LOC is determined as the 

concentration at which the monitoring site cumulative PATI value is equal to the LOCPATI, or in 

other words, the EEF equals 1. In calculating this CE-LOC, EPA will use Syngenta’s monitoring 

data (AEEMP 2004-2011; 

http://www.epa.gov/opp00001/reregistration/atrazine/atrazine_update.htm). In Figure 20, the 

points represent AEEMP environmental monitoring sites (2004-2011), plotted by their average 

concentration for the chosen 60-day exposure window, and by their EEF. Additional calculations 

were carried out to determine the variability in CE-LOC values based on different 

analytical/statistical methods (these analyses are discussed further in Sections 14.3 and 14.4). 

A discussion of how the CE-LOC will be implemented is presented in Chapter V.

Cumulative PATI = 150 %-days
111

14. History of the Aquatic Plant Community LOC Methodology and the Effects on the LOC 

from Implementation of Suggestions by Scientific Advisory Panels. 

14.1. A Synopsis of the Changes Incorporated into the Current Aquatic Plant Community 

LOC Methodology. 

The EPA made the following revisions to the LOC approach based on recommendations made 

by the SAPs in 2007 and 2009: 

- Modifications to CASM after the 2007 review 

Figure 20. Plot of maximum 60-day average concentrations against the Effects 

Exceedance Factor (EEF) for the AEEMP Site Year Data (2004-2011). See Appendix 

G for further details on the regression results. Box plots along each axis describe the 

distribution of each variable.
112

- Critical evaluation of CASM and consideration of alternatives to CASM, 

- Re-evaluation the suitability of the original cosm endpoints based on peer-reviewed 

acceptance criteria (66 of the original 77 endpoints remained). 

- Re-classification of the endpoints from the 1-5 Brock score scale to an effect/no effect 

determination (5 of the original endpoints were re-classified from a Brock score of 2 

[treated as “no effect” in the analysis] to ”effect”

- Addition of one endpoint from one of the original cosm studies that was not previously 

included) 

- Incorporation of 20 additional cosm endpoints from new studies recommended by the 

SAP

- Change in the LOC method from balancing the absolute numbers of Type I/II errors to a 

logistic regression approach 

- Replacement of the assumed constant nominal atrazine concentration over the duration 

of the cosm study with time-variable atrazine concentrations 

14.2. Modifications to the Method for Determining the LOC for Aquatic Plant 

Communities (Based on the Suggestions from the 2009 SAP). 

New COSM Studies and Old COSM Reclassifications 

The original cosm data set was comprised of 35 studies and 77 endpoints for CASM 

development. The Agency evaluated 38 additional studies recommended by the 2009 SAP, and 

re-evaluated the 35 studies using a rigorous set of acceptance criteria (Appendix D). The new 

cosm study dataset now includes 46 studies and 87 endpoints (plotted in Figure 16). In this 

current cosm data set, the cosm effects were changed from the 5-tier Brock score to an effectno effect classification. Of the original cosm studies, 5 endpoints that were previously classified 

as the equivalent of “no effect” (Brock Score of 2) were reclassified as “effect” under the 

revised analysis. 

- Endpoint #51 (Brockway et al., 1984): the effects were based on a 25% reduction in 

phytoplankton oxygen production occurring the first day of a twelve-day study at 50 

μg/L. Recovery was not observed during the study period. 

- Endpoint #52 (deNoyelles et al., 1982, 1989): the effects were based on a 50% decline 

in 14C-uptake and 50% decline in phytoplankton biomass. All effects were statistically 

significant. Recovery of both 14C-uptake and biomass was not specified at this level, 

but assumed to be ≥3 weeks, given the lower magnitude of effect and recovery at the 

higher concentrations. 

- Endpoint #58 (Lampert et al., 1989): the effects were based on a 50% decrease in 

chlorophyll-a and oxygen saturation for the phytoplankton community at 1 μg/L in the 
113

18-day study. Reductions in oxygen may have been related to daphnid mortality; 

however, chlorophyll-a reductions were considered to be treatment related. Recovery 

was not observed. 

- Endpoint #59 (Pratt et al., 1988): the effects were based on 35% decrease in dissolved 

oxygen, slight reductions in magnesium and calcium levels for this 21-day study at 32 

μg/L. All effects were statistically significant. Recovery was not reported in the study. 

- Endpoint #60 (Pratt et al., 1988): the effects were based on a 35% decrease in 

dissolved oxygen, a 60% reduction in chlorophyll-a, and slight reductions in 

magnesium and calcium levels for this 21-day study at 110 μg/L. All effects, except 

chlorophyll-a reduction, were statistically significant. Recovery was not reported in the 

study. 

Changes to the calculation of the LOCPATI

The second suggestion from the 2009 SAP was to modify the way that cosm endpoints were 

used to estimate the LOCPATI. Instead of determining the LOCPATI as the PATI value at which a 

balance of absolute numbers of effect endpoints fall below and no effect endpoints fall above 

the value, which is problematic where the numbers of effect and no effect endpoints are 

unbalanced, the Agency now uses a probability of adverse effects (Appendix E). The 

relationship of the probability of effect in the cosms to the PATI value determined for each 

cosm exposure is determined using binary logistic regression. The LOCPATI is the point at which 

there is a 50% probability of an effect (Figure 18). 

Final calculation of the Concentration-Equivalent LOC 

The Agency uses the AEEMP monitoring sites (EPA-HQ-OPP-2003-0367-0206) and the LOCPATI to 

derive a single concentration-duration endpoint, the CE-LOC. The CE-LOC can be derived using a 

variety of methods and assessment periods. 

In investigatory studies of the effect of assessment period on the CE-LOC, the LOCPATI was 

calculated for 7, 14, 30, 60 and 90-day assessment periods (Table 20) using the 2011 

Cumulative PATI model and the full cosm dataset (Appendix D). The CE-LOC was calculated by 

conducting two linear regressions of the EEFs for each duration versus the maximum running 

average for each duration, one using all the data and one using only those points with 

0.5<EEF<2.0. The CE-LOC was estimated as the concentration on the regression line 

corresponding to EEF=1.0 (Table 20). At shorter assessment periods, 7 to 60 days, the linear 

regression was a poor fit of the data (i.e., missing the center of the distribution at EEF=1). The 

linear regression on only the 0.5<EEF<2.0 portion of the data set, resulted in a good fit of the 

data and was used to establish the CE-LOC. 
114

TABLE 20. Effect of averaging period and method of derivation on the percent of AEEMP 

site/years exceeding the CE-LOC. 

Averaging Period 7-Day 14-Day 30-Day 60-Day 90-Day

Cumulative PATI Value (%-days) 65.5 107.4 132.7 140.0 141.8

CE-LOC (μg/L) Linear Regression 

(Entire Data Set)

19.0 15.6 8.6 4.2 2.8

CE-LOC (μg/L) Linear Regression 

(0.5-2.0 EEF Range)

18.0 14.9 8.3 4.2 2.7

14.3. Analyses of Driving Factors Affecting the CE-LOC 

This section evaluates the relative impacts of recommendations made by the 2007 and 2009 

Scientific Advisory Panels (USEPA 2007b and USEPA 2009a) on the CE-LOC (Table 21). Based on 

the 2003 method, for the 60-day duration, the preliminary trigger was 17.5 μg/L. The direct 

comparison between the preliminary trigger and CE-LOC endpoints derived from PATI is 

problematic because a different set of cosm data, LOC approach, expanded set of field 

chemographs, and atrazine concentration profile, have been used. In addition, the CASM model 

used in that preliminary derivation has changed since 2003 based on SAP recommendations. 

Table 21. Comparison of effect of LOC methods, cosm exposure characterization, and cosm datasets on resulting 

60-day PATI model-derived LOCs and concentration-equivalent LOCs

LOC 

Method

Cosm Data Cosm 

Exposure

Changes LOCPATI CE-LOC

Old Original 77 Constant 

Nominal

2003 Preliminary NA 17.5a

LOC BASED ON 2007 SAP RECOMMENDATIONS

Old Original 77 Constant 

Nominal

Estimated change in LOC switching from 

preliminary version of CASM to updated 

version of CASM

NA 11.7b, c

Old Original 77 TimeVariableChanged representation of cosm atrazine 

concentrations from assumed nominal to 

actual concentrations over time

NA 7.2b, c

Old Original 77 Constant 

Nominal

Switched from CASM to PATI to derive 

the LOC after 2007 SAP 

recommendations for modifying CASM, 

additional sensitivity analyses

4.97 9.6

Old Original 77 TimeVariableChanged representation of cosm atrazine 

concentrations from assumed nominal to 

actual concentrations over time

4.24 8.1

LOC BASED ON 2009 SAP RECOMMENDATIONS

New Original 77 TimeVariableChanged LOC from balancing absolute 

numbers of Type I/II errors to logistic 

regression

4.15 7.9
115

Table 21. Comparison of effect of LOC methods, cosm exposure characterization, and cosm datasets on resulting 

60-day PATI model-derived LOCs and concentration-equivalent LOCs

LOC 

Method

Cosm Data Cosm 

Exposure

Changes LOCPATI CE-LOC

New Original 

screened reevaluated

TimeVariableScreened 77 original studies with new 

acceptance criteria: 

- Dropped 7 effects endpoints (6, 11, 12, 

16, 20, 21, 43)

- Dropped 4 no effects (55, 56, 57, 74)

Re-evaluated the 66 remaining original 

cosm endpoints that passed the new 

acceptance criteria (broken down in 

steps)

(a) Changed endpoint durations to match 

observed effect

4.55 8.7

(b) Changed 5 studies from no effect 

(original Brock score of 2) to effect (51, 

52, 58, 59, 60)

3.01 5.5

(c) Added a second endpoint from the 

Lambert study (58b)

2.89 5.3

New New 

Revised 

Cosm Set

TimeVariableAdded 20 endpoints from new cosm 

studies

2.33 4.2

LOC BASED ON MODIFICATIONS TO THE MODEL

New New 

Revised 

Cosm Set

TimeVariableChanged from an average PATI value to 

Cumulative PATI.

140.0 4.2

New Modified 

New Rev. 

Set

TimeVariableChanged 5 of original cosm endpoints 

from effect back to original no effect 

determination)

235.0 7.4

a

The 2003 concentration is not a CE-LOC, but a trigger concentration. 

b

For calculation of the CE-LOC when implementing the CASM model in the process, both the concentration and EEF 

were Log10 transformed. All subsequent regressions were conduced using linear regression of untransformed data. 

c

CASM was implemented with a logistic toxicity relationship for the intitial single species toxicity data to be 

consistent with the current version of PATI. The version of CASM presented to the 2007 SAP used a sigmoidalthreshold toxicity relationship. 

Effect of 2007 CASM Changes 

One consequence of the 2007 SAP was the recognition by all parties that the initial CASM 

model was unrealistic and needed modification. Changes were made that provided a more 

realistic depiction of a midwestern stream and this version was used for evaluations leading up 

to the 2009 SAP. To establish the impact of these changes on the difference between the CELOC and the preliminary screening value, the modified version of CASM used for the 2009 SAP 
116

was applied with the same cosm data and LOC method as the 2003 evaluations. These CASMbased LOCs were then applied to the same AEEMP data used for current CE-LOC derivations, in 

order to derive what the EEFs and CE-LOC would be for the modified version of CASM. This 

resulted in a CE-LOC of 11.7 μg/L, compared to the screening value of 17.5 μg/L. In other 

words, correcting only the deficiencies of the 2003/2007 CASM version and applying it to a 

more extensive and realistic set of field data than used in 2003 caused the CE-LOC to be 29% 

lower than the 2003 trigger. 

Change from assumed constant nominal to time-variable atrazine concentrations over the 

duration of the cosm study. 

The original analysis of cosm studies (for the 2003 preliminary trigger concentrations and the 

2007 SAP) assumed atrazine concentrations remained constant throughout the duration of the 

study. However, for a majority of the cosm data, atrazine concentrations declined throughout 

the study period. As part of the revisions leading up to the 2009 SAP, chemographs were 

developed for each cosm treatment (these chemographs were also reviewed by Syngenta's 

consultants). Using the modified CASM with these new time-variable chemographs, while still 

implementing the 2003 CE-LOC methodology, results in a CE-LOC of 7.2 μg/L (Table 21). A 

significant drop is to be expected because constant concentrations indicate a higher 

concentration was needed to cause effects in the cosms than was actually present. Again, by 

addressing only the changes recommended by the 2003 SAP, there is more than a two-fold 

difference between the preliminary trigger and the CE-LOC. This is before considering the 

switch to PATI, the change in the CE-LOC method, and changes in cosm data. The 2003 and 

2007 SAP evaluations presented in Table 21 were intended to be preliminary illustrations of 

methodology rather than providing assessment concentrations and were recognized at the time 

to require additional changes, so that this difference between the trigger and the CE-LOC is to 

be expected. 

Switch from CASM to PATI 

Based on the recommendations from the 2007 SAP, as an alternative to CASM, EPA developed 

PATI. PATI was developed after the change to the time-variable chemographs, however to 

compare to the earlier CE-LOCs, PATI was modified to use the constant concentration 

chemographs used in earlier versions of CASM. The resulting CE-LOC for comparison to the 

constant nominal concentration for CASM, explained in the earlier step, is 9.6 μg/L for PATI. 

This reflects the change from CASM to PATI. The resulting CE-LOC for the time variable 

concentrations is 8.1 μg/L, the same as the time variable CASM based value. 
117

Change the LOC determination approach from balancing Type I/II errors to logistic regression. 

The old LOC approach balanced the absolute number of effect endpoints that fell below the 

LOC with the number of no-effect endpoints above the LOC. However, because there are fewer 

no-effect endpoints in the cosm dataset, this allows for a higher percentage of no-effect 

endpoints above the LOC than effect endpoints below the LOC. The 2009 SAP expressed 

concern about the approach and recommended exploring alternative approaches. 

The new LOC approach is based on the relative probability of an adverse effect, linking the PATI 

index value with the 50th percent probability of an adverse effect. The change from the old 

(original) LOC approach to the logistic regression approach using the original cosm dataset (77 

cosm endpoints) resulted in the CE-LOC dropping from 8.1 to 7.9 μg/L. 

Re-evaluation of the original 77 cosm endpoints 

The 2009 SAP made several recommendations regarding the original set of cosm studies EPA 

used for the LOC determination, ranging from the Brock scoring effects determination to the 

suitability of some studies for use (based on a review Syngenta submitted to the docket for the 

2009 SAP). The re-evaluation included several steps, which have been broken out as separate 

increments in Table 21:

(a) The studies were screened against acceptance criteria based on number of controls, 

exposure, experimental design, statistical methods, and data interpretation (Appendix 

D). The re-evaluation resulted in 11 of the original 77 endpoints being dropped, which 

included 7 effects endpoints and 4 no effects endpoints. During the re-evaluation 

process, some endpoint durations from the original evaluation were revised to match 

the effects endpoints. Twenty-five durations were adjusted, with 15 effects durations 

increased and 10 effects durations decreased. This resulted in a net increase in the CELOC to 8.7 μg/L 

(b) The next sequential change was a change in the effects endpoint classification from 

the 1-5 Brock score to a binary effect (1) / no effect (0) score. This resulted in a change 

from no effect (Brock score 2) to effect for 5 of the original cosm endpoints (Appendix 

D): #51 (Brockway et al., 1984), #52 (deNoyelles et al., 1982, 1989), #58 (Lampert et al., 

1989), #59 and #60 (Pratt et al., 1988). The effective classification of the other 

endpoints remained unchanged. This resulted in the greatest change in the CE-LOC from 

8.7 μg/L to 5.5 μg/L 

(d) The re-review also resulted in adding an effects endpoint from the Lampert et al. 

(1989) study, identified at #58b, which showed an effect at a concentration of 0.1 μg/L, 

and resulted in a slight reduction in the CE-LOC from 5.5 to 5.3 μg/L (Appendix D).
118

Next to the revision in the CASM model recommended by the 2003 SAP, the re-evaluation of 

the cosm endpoints and, in particular, the re-classification of 5 of the studies from an original 

no-effect to effect (Appendix D), resulted in the greatest reduction in the CE-LOC. 

Incorporating additional endpoints from new cosm studies recommended by the 2009 SAP. 

The 2009 SAP provided EPA with a list of additional cosm studies that were not included in the 

original set of cosm studies. The Agency’s review of these studies, using the study acceptance 

criteria, added 15 new studies with a total of 20 new endpoints (13 effect endpoints, 7 no effect 

endpoints; Appendix D). The addition of the new cosm endpoints to the existing revised 

endpoints resulted in a change in the CE-LOC from 5.3 to 4.2 μg/L. 

Changed from an average PATI value to Cumulative PATI. 

The initial development of PATI as presented at the 2009 SAP used the average PATI value over 

the assessment period. The change to cumulative PATI better reflects the intent to describe 

cumulative effects. Because the effects index is intended to describe total toxic impact, the 

approach to address time is simply to sum the daily PATI values to provide a cumulative PATI. 

The summation units of this cumulative PATI are analogous to the ppb-days or, more familiarly, 

with degree-days used to describe the total heating or cooling impact of seasonal weather. A 

fundamental aspect of such a summation is that a certain reduction in growth over 1 d is 

treated as being of equal importance as half that reduction persisting for 2 d, a quarter of that 

reduction persisting for 4 d, etc. This summation cannot be continued indefinitely, but rather is 

limited here to a 60-day period. The change from an average PATI to the cumulative PATI does 

not change the EEFs or CE-LOC, because they are mathematically equivalent. 

14.4. Uncertainty in the Calculation of the LOCPATI and CE-LOC 

There are several calculations in the derivation of the CE-LOC that incorporate uncertainty into 

the final numbers. These include the the PATI relationship, the COSM classifications, the 

estimation of the 50th percentile of the effects/no effects distribution (binary logistic 

regression), and the final conversion to the CE-LOC. A discussion in of the the uncertainty based 

on the original toxicity data, as well as the assumptions made concerning using the average 

PATI relationship rather than the most or least sensitive taxonomic group for the PATI 

relationship is provided in Appendix E. 

The logistic PATI relationship may lead to heavy tails emphasizing greater effect at the tails than 

predicted from the toxicity data. To test the effects of this on the final CE-LOC two additional 
119

PATI relationships, piecewise-linear, and threshold sigmoidal, were calculated and the results 

were compared to the CE-LOC described above. The results indicated that the logistic toxicity 

relationship was more protective than either the sigmoidal-threshold (5.1 μg/L) or linear 

toxicity relatinonships (5.6 μg/L).

The LOC is presented as a range in concentrations due to the uncertainty involved in the 

classification of a few COSM endpoints. The reclassification of 5 of the cosm endpoints from 

“no effect” to “effect” had the largest impact on the CE-LOC, resulting in an approximate 40% 

reduction in the revised baseline 60-day CE-LOC. If the classification of 5 of those endpoints 

that were previously considered to be “no effect” were changed back to “no effect”, the CE-LOC 

would be 7.4 μg/L. Based on the results of these analyses EPA has determined the CE-LOC range 

to be between 4-7 μg/L. This means that those fresh water and estuarine/marine monitoring 

sites with a 60-day running average at or above 4 μg/L have atrazine concentrations that are 

above the lower bound of the CE-LOC, and that permanent or irreversible change in aquatic 

plant community structure, function, and/or productivity would be expected. 

The greatest uncertainty is surrounding the calculation of the 50th percentile (LOCPATI) of the 

binary logistic regression of effects/no-effects data (e.g., Figure 18). To investigate this, the 95th

confidence intervals (CI) around the LOCPATI for both the 4 μg/L and 7 μg/L results were 

calculated by multiplying the standard error, provided as output from the PATI software, from 

each of the analyses by 1.96 and finding the upper and lower CI by adding or subtracting from 

the respective LOCPATI. The upper and lower confidence intervals were divided by the LOCPATI to 

obtain an EEF for each of the upper and lower confidence intervals around the LOCPATI. The 

concentrations representing the upper and lower confidence intervals were then calculated 

using the linear regression equation for calculating the CE-LOC. This results in a 2-10 μg/L range 

of uncertainty around the 4 μg/L, and 3-15 μg/L for the 7 μg/L CE-LOC. 
120

CHAPTER V. METHOD FOR DETERMINING THE VULNERABLE WATERSHEDS 

15. Identifying Watersheds without Available Monitoring Data. 

15.1. Identifying Watershed Criteria for Sites that Exceed the Aquatic Community LOC for 

Atrazine

The Atrazine Ecological Exposure Monitoring Program (AEEMP) was a part of the data 

requirement imposed as a condition of reregistration for atrazine. Two objectives of the AEEMP 

were to (1) estimate the extent of watersheds in corn and sorghum areas with water bodies 

that exceed the atrazine CE-LOC for aquatic community effects, and (2) use watershed 

attributes to identify other watersheds where these higher atrazine exposure areas are likely to 

occur (USEPA 2003c). This section recaps the EPA’s 2009 analysis of watershed parameters 

characteristic of those watersheds that are most vulnerable to prolonged, elevated atrazine 

concentrations and describes future directions in watershed assessments for atrazine (USEPA 

2009a). It is important to note that the CE-LOC has changed since 2009, so the following 

analyses would need to be repeated with the current CE-LOC. 

15.2. Factors Contributing to Watershed Vulnerability 

The primary objective of the EPA’s 2007 watershed analysis was to identify those characteristics 

that distinguish watersheds with waters that frequently exceed the aquatic community CE-LOC 

for atrazine and to use those characteristics to identify other, similarly vulnerable watersheds. 

The AEEMP watershed properties were used to identified the presence of soils with shallow, 

drainage-restrictive layers in areas with atrazine use as a characteristic that distinguished 

monitoring sites that exceeded the aquatic community CE-LOC in multiple years (e.g., MO-01, 

MO-02, and NE-04) from those sites that did not exceeding the CE-LOC during the sampling 

period (USEPA, 2007b, and 2009a). In follow-up analyses, EPA evaluated a number of atrazine 

use, weather, soil, and hydrology properties reflective of runoff-prone conditions using both 

simple statistical comparisons and discriminate analyses. USEPA (2009a) provides a full list of 

watershed parameters that were considered and analyses conducted. 

For the 2009 SAP, US EPA used multivariate analyses to evaluate the importance of a variety of 

parameters to account for the variability in atrazine exposures among the AEEMP monitoring 

sites. Basic cluster analyses indicated that MO-01, MO-02, and NE-04 (3 sites that exceeded the 

CE-LOC in multiple years), as well as NE-05 and NE-07 (sites that exceeded the CE-LOC once) 

tended to group together based on soil factors. Discriminant analyses confirmed the 

importance of the percentage of soils with (1) a depth within 50 to 60 cm to a drainagerestrictive layer (defined by saturated hydraulic conductivity, Ksat, values of less than 1 to 1.25 

μm/s), (2) a high-to-very-high runoff potential, and/or (3) hydrologic group D soils in 
121

distinguishing sites that exceed the CE-LOC in multiple years. All three of these soil parameters 

reflect runoff-prone conditions in the watershed. 

Multivariate discriminant analysis showed the importance of weighting the percentage of 

watersheds with high runoff-prone soils, based on one of the three parameters described 

above, with the atrazine use intensity for the watershed (Figure 21). The first canonical model 

provided a sharp distinction between sites that exceed the CE-LOC in multiple years (in blue) 

and the remaining sites. The second canonical model provided some separation between the 

sites that exceeded the CE-LOC in 1 year (green) and the sites that did not exceed the CE-LOC 

during the monitoring study (red). 

Figure 21. Analysis of discriminating factors in distinguishing between sites that exceeded the

CE-LOC in multiple years (in blue), exceeded the CE-LOC once (green), and did not exceed the 

CE-LOC (red) 

The US EPA further evaluated these watershed characteristics to identify those that, singly or in 

combination, best provide a clear distinction between the 3 AEEMP sites that exceed the CELOC in multiple years and the 31 sites that did not exceed the CE-LOC during the sampling 

period (USEPA, 2009a). The percentage of the upstream catchments containing soils with 

shallow drainage-restrictive layers (as defined above) provided a clear separation between the 

- 1

0

1

2

3

4

5

6

7 Canonical2

LOC Below

LOC Exceeds One Year

LOC Exceeds Two or More Years

Rnof_HVH

HSG_D K100/50Use Kr050_25c

- 1 0 1 2 3 4 5 6 7 8 9 10 11

Canonical1
122

3 sites that exceeded the CE-LOC in multiple years and the 31 sites that did not exceed the CELOC during the study period (Figure 22). 

The red dashed lines in Figure 22 group the 40 AEEMP sites into those that exceeded the CELOC in 2 or more years (to the left of the first red line), 1 year (between the two red lines), or 0 

years (to the right of the second red line) during the study. The dark blue dotted line marks the 

lowest percentage of shallow, drainage restrictive soil layers among the watersheds that 

exceeded the CE-LOC in multiple years, while the yellow dotted line marks the highest 

percentage of shallow, drainage-restrictive soil layers among the watersheds that did not 

exceed the CE-LOC. Two of the six sites that exceeded the CE-LOC in 1 out of 3 years of the 

study (NE-05 and NE-07) were also above the upper threshold. 

Figure 22. Percent of upstream catchments containing soils with shallow (<60 cm), low-Ksat 

(<1.25 um/s) layers for the 40 AEEMP monitoring sites. See text for description of the 

meaning of the red, blue and yellow lines. 

Adjusting the fraction of the watershed with shallow, drainage restrictive layers by the atrazine 

use intensity improved the distinction between the 3 sites that exceeded the CE-LOC in multiple 

years and the remaining 37 sites (Figure 23).

0

10

20

30

40

50

60

70

80

90

100

MO-01MO-02

NE-04NE-07NE-05

IN-11

MO-03

IN-05

NE-02

IN-04

NE-06

IL-08IL-09

KY-02

IN-08

NE-01

OH-03

IN-03IN-07IN-10

OH-01

IN-09IN-02

TN-01

OH-02OH-04

IN-06

IL-01

IN-01

IL-07IL-05

KY-01

IL-04IL-02

IA-02IA-01

MN-01

NE-03

IL-06IL-03

Sites sorted by LOC, max 60-da concentration % of watershed with Ksat<1.25 w/in 60 cm (All land uses, all slopes)

54-73%
123

Figure 23: Atrazine use intensity adjusted percent of upstream catchment containing soils 

with shallow (<60 cm), low-Ksat (<1.25 um/s) layers for the 40 AEEMP monitoring sites. See 

the text for explaination of the red, blue and yellow lines. 

Figure 24 shows the areal extent of 1:100,000 scale National Hydrography Dataset (NHD+) 

catchments in the Midwestern US that meet the criteria shown in Figure 23. The dark red in the 

map represent catchments that have use-intensity adjusted percentages of drainage-restrictive 

soils greater than the upper threshold value (blue dashed line in Figure 23); the lighter red in 

the map represent catchments that have values between the upper and lower (yellow dashed 

line) threshold value. The NHD+ catchments are smaller than the catchment areas represented 

by the 40 AEEMP monitoring sites, which ranged from 9 to 64.5 mi2 (23 to 167 km2) in area. 

Waters are more likely to exceed the aquatic community CE-LOC for atrazine in areas where 

contiguous NHD+ catchments meet the vulnerability criteria than in areas where only isolated 

catchments exceed the CE-LOC. Thus, Figure 24 should be viewed as representing a maximum 

potential vulnerability area rather than the actual extent of vulnerable watersheds. As an 

illustration, Figure 28 identifies headwater streams that exceed EPA’s watershed vulnerability 

criteria (shown in blue and purple on the map) by beginning at the uppermost stream reach 

and continuing downstream until properties drop below the criteria. Thus, it excludes areas 

shown in Figure 24 that occur farther downstream and, when added into the larger drainage 

area, would be below the vulnerability criteria. 

While Syngenta also identified the presence of shallow, drainage-restrictive soil layers as a key 

attribute of watersheds that are most vulnerable to atrazine runoff, the available 

0

5

10

15

20

25

30

35

40

45

50

MO-01MO-02

NE-04NE-07NE-05

IN-11

MO-03

IN-05

NE-02

IN-04

NE-06

IL-08IL-09

KY-02

IN-08

NE-01

OH-03

IN-03IN-07IN-10

OH-01

IN-09IN-02

TN-01

OH-02OH-04

IN-06

IL-01

IN-01

IL-07IL-05

KY-01

IL-04IL-02

IA-02IA-01

MN-01

NE-03

IL-06IL-03

Sites sorted by LOC, max 60-da concentration

Use Intensity x % of watershed w/ Ksat<1.25 w/in 60 cm

(All land uses, all slopes)

22-29
124

documentation provided to the EPA focused primarily on the characteristics of MO-01 and MO02 in defining vulnerable watershed criteria (Miller et al., 2009; Prenger et al., 2009). Syngenta 

further narrowed the characteristics by stipulating that the soil conditions must be tied to the 

presence of slopes >2% under cropland, and used the percentage of corn or sorghum as an 

indicator of atrazine use intensity (Figure 25). 

Figure 24: NHD+ catchments in the Midwestern US meeting US EPA's watershed vulnerability 

criteria for atrazine. 
125

Figure 25: Registrant’s criteria for selecting watersheds similar to the AEEMP sites that 

exceeded the CE-LOC in multiple years. Source: Syngenta. 

Although Syngenta’s approach did not specifically attempt to distinguish between the AEEMP 

sites that exceeded the CE-LOC in multiple years and the sites that did not exceed the CE-LOC, 

the soil-slope-crop criteria, weighted by the fraction of the watershed in corn or sorghum, did 

distinguish between the two groups (Figure 26). However, the additional Pesticide Root Zone 

Model (PRZM) calculated atrazine flux – 90th percentile of 30 years of 30-day average atrazine 

flux – did not distinguish between AEEMP sites that exceed the CE-LOC in multiple years and 

sites that did not exceed the CE-LOC (Figure 27). Based on the 90th percentile of the 30-day 

average concentrations for the AEEMP watersheds, 15 of 31 sites that did not exceed the CELOC have PRZM values greater than the lowest of the sites exceeding in multiple years (Figure 

27).

Because PRZM does not specifically model the type of subsurface flow that may result from the 

shallow restrictive layers identified in the AEEMP sites and that exceeded the CE-LOC in 

multiple years, the US EPA would not expect the PRZM values to distinguish between the 

AEEMP sites. 
126

Figure 26: Percent of AEEMP watershed areas with soils that have a Ksat<1.25 um/s within 30 

cm of the surface on slopes >2% under cropland x % corn or sorghum (as a fraction). See the 

text for the description of the red, blue and yellow lines. 

0

1

2

3

4

5

6

7

8

9

10

MO-01MO-02

NE-04NE-07NE-05

IN-11

MO-03

IN-05

NE-02

IN-04

NE-06

IL-08IL-09

KY-02

IN-08

NE-01

OH-03

IN-03IN-07IN-10

OH-01

IN-09IN-02

TN-01

OH-02OH-04

IN-06

IL-01

IN-01

IL-07IL-05

KY-01

IL-04IL-02

IA-02IA-01

MN-01

NE-03

IL-06IL-03

Sites sorted by LOC, max 60-da concentration

%corn-sorghum x % watershed w/ Ksat<1.25 w/in 30 cm 

(Cropland only, slopes >2%)

1.4-2.7
127

Figure 27: 90th percentile of 30-day average PRZM atrazine flux concentrations calculated for 

the 40 AEEMP sites. See the text for the description of the red and blue lines. 

15.3. Evaluating the Watershed Vulnerability Criteria 

While EPA and Syngenta identified the presence of soils with shallow, drainage restrictive 

layers, differences in the ultimate watershed criteria have resulted in two sets of watershed 

criteria with different threshold values (see Table 22 below). The minimum threshold values 

listed in the table were identified by EPA based on a comparison of the sites that exceeded the 

CE-LOC in multiple years and the sites that did not exceed the CE-LOC during the study period. 

0

10

20

30

40

50

60

70

80

90

MO-01MO-02

NE-04NE-07NE-05

IN-11

MO-03

IN-05

NE-02

IN-04

NE-06

IL-08IL-09

KY-02

IN-08

NE-01

OH-03

IN-03IN-07IN-10

OH-01

IN-09IN-02

TN-01

OH-02OH-04

IN-06

IL-01

IN-01

IL-07IL-05

KY-01

IL-04IL-02

IA-02IA-01

MN-01

NE-03

IL-06IL-03

Sites sorted by LOC, max 60-da concentration

PRZM 30-day concentration, 90th percentile
128

Table 22 - Comparison of Watershed Criteria Used to Identify Sites that Exceed the CE-LOC in 

Multiple Years

Watershed Parameters EPA Criteria Syngenta Criteria 3

Drainage restriction / Ksat value < 1 μm/s 1<1.25 μm/s

Depth to drainage restrictive layer 50 / 60 cm 130 cm

Land use All land uses (entire 

watershed)

Cropland only

Slope No slope cutoff Slopes > 2%

Minimum % of watershed area 

meeting the threshold values

54-73% 25-6% 2

Adjustments to % area threshold x atrazine use intensity x % of corn or sorghum in the 

watershed x 90th %ile of the 30-day 

average PRZM concentration 3

Lower bound on threshold value 22 20.6 2

Upper bound on threshold value 29 21.3 2

1

 In the May 2009 SAP, EPA developed watershed criteria for drainage restrictive layers using 1 μm/s for 

the Ksat value and a depth of 50 cm. For this analysis, we used criteria of 1.25 μm/s and 60 cm because 

that coverage was already available for the entire atrazine use area. 

2

 The lower end of the threshold range represents the highest value found for any of the 31 monitoring 

sites that did not exceed the CE-LOC in any of the monitoring years. The upper end of the range 

represents the lowest value found for the 3 sites that exceeded the CE-LOC in multiple years. 

3

This is EPA’s reproduction of Syngenta’s documented criteria approach documented. While Syngenta 

passed the watersheds through three separate filters, EPA worked through a combination of watershed 

parameters identified by Syngenta in order to apply an upper and a lower bound on the threshold criteria. 

Consistent with the May 2009 FIFRA SAP recommendations (USEPA, 2009a) to evaluate both 

sets of criteria, this section details a methodology to evaluate the two approaches. Despite 

similarities in the basic vulnerability criteria, EPA’s and Syngenta’s watershed parameters often 

identify different areas as vulnerable (Figure 28). The map shows headwater watersheds similar 

in size to the AEEMP monitoring sites that either meet EPA’s vulnerability criteria (shown in 

blue), Syngenta’s criteria (in red), or both criteria (purple). While headwater watersheds 

meeting Syngenta’s criteria occur primarily in the upper Midwest, from Ohio to Nebraska and 

Kansas, the EPA’s criteria includes areas in southern Illinois (in a claypan area similar to that in 

northeastern Missouri where MO-01 and MO-02 occur) and in parts of Louisiana and Texas. 
129

Figure 28: Headwater watersheds that meet US EPA's (in blue), Syngenta's (red), or both 

(purple) watershed vulnerability criteria for atrazine. 

In order to better evaluate the differences between the two sets of criteria, the US EPA 

requested that Syngenta conduct an additional monitoring study that could be used to refine 

the vulnerability criteria. The EPA recommended that monitoring sites provide a statistical 

representation of headwater watersheds binned according to criteria (EPA or Syngenta) and 

range in threshold. The range is represented as between the lower and upper threshold, 

greater than the upper threshold, or a set less than the lower threshold could also be included). 

The main focus for additional monitoring was to evaluate the two criteria approaches (EPA’s 

watershed analysis vs Syngenta’s watershed analysis) used for identifying watersheds that are 

likely to exceed the CE-LOC in multiple sampling years. A secondary focus was to ensure a 

geographical representation of the sites, particularly in areas where the availability of 

monitoring data is limited. 
130

Ultimately, 25 sites were selected to represent either of the two criteria, including a set that 

met both. They selected sites to represent watersheds that either fell between the two 

threshold values or were greater than the upper threshold value. Monitoring began in the 

spring of 2010. The EPA will evaluate the results of the monitoring study once the third year of 

monitoring is completed and once Syngenta submits a full report, including the statistical 

sampling design, results of the monitoring, and a full set of watershed characteristics. The EPA 

anticipates receiving this report in time to evaluate it as a part of the registration review for 

atrazine. 

Additionally, the US EPA is currently evaluating other monitoring data sets from state 

monitoring programs and from the USGS NAWQA program. These monitoring data will provide 

the EPA with additional sites that can be used to evaluate the watershed vulnerability criteria. 

15.4. Further Evaluations of Watershed Criteria: The Cornbelt Watershed Regression for 

Pesticide (WARP) Model

The 2009 SAP recommended using an effects index or concentration metric, rather than 

categorical CE-LOC thresholds (i.e., exceeded the CE-LOC in multiple years vs. did not exceed 

during the study) in order to take advantage of data from all 40 AEEMP sites (USEPA 2009a). 

The Panel encouraged the development of a “Cornbelt Watershed Regression for Pesticide 

(WARP) Model” and recommended considering additional data related to application (planting 

dates, timing of atrazine application), weather (rainfall intensity and duration), soils and 

hydrology (runoff propensity index, composite curve numbers, watershed geometry), and 

management (riparian buffers/setback areas, tillage, conservation practices, etc.). Some of the 

recommended parameters can be collected on a national scale while others may only be 

available, if at all, on a local scale. Readily available parameters available throughout the 

atrazine use area are potentially useful in providing a national or regional atrazine vulnerability 

assessment that can be used to identify areas of likely concern for atrazine. Less readily 

available parameters may be useful for watershed-specific evaluations that attempt to more 

narrowly pinpoint the causes and sources of atrazine residues in water. 

 

The EPA has begun analyses that use time-averaged atrazine concentrations and a variety of 

watershed parameters which vary spatially (soil and hydrology parameters) as well as 

temporally (atrazine use, land use, rainfall), and which use parameters and monitoring results 

from individual years rather than multi-year averages. Such refinements may better identify the 

relative contributions of atrazine use patterns and rainfall on atrazine concentrations detected 

in the streams. 

The USGS recently developed and published a cornbelt WARP model (Stone and Gilliom 2011). 

The USGS evaluated how well a number of watershed characteristics (relating to pesticide use, 
131

land use, agricultural management practices, soil properties, physical watershed characteristics, 

weather characteristics, and hydrologic properties) predicted various maximum time-average 

(14, 21, 30, 60, and 90 day durations) and 95th percentile atrazine concentrations in streams in 

the Corn Belt region. Stone and Gilliom (2011) used 37 of the AEEMP sites (2004-2007 sample 

years), 5 Heidelberg University NCWQR sites, and 2 NAWQA sites for model development, and 

11 site/year combinations from the AEEMP and NCWQR and 10 sites from the Atrazine 

Monitoring Program for Community Water Systems 

(http://www.epa.gov/opp00001/reregistration/atrazine/atrazine_update.htm) for model 

evaluation. 

The following watershed parameters provided the best fit for predicting atrazine 

concentrations in the cornbelt WARP model: 

- Percentage of agricultural land with a soil-restrictive layer within the top 25 cm of the 

surface 

- Total precipitation (in mm) during May and June 

- Percentage of stream flow due to Hortonian overland flow 

- Watershed area (km2) 

- Percentage of watershed that is artificially drained 

- Atrazine use intensity (kg a.i. / watershed area in km2)

These parameters accounted for 53 to 62 percent of the variability in the atrazine 

concentration measurements in the model-development sites (Stone and Gilliom, 2011). As the 

US EPA moves into the registration review phase for atrazine, it will further evaluate the utility 

of using the cornbelt WARP model as a means of identifying watersheds that are most 

vulnerable for exceeding the aquatic community CE-LOC. 

The Cornbelt WARP model can be used to rank watersheds based on relative vulnerability 

based on estimated concentrations, similar to what EPA did to identify the original area of the 

most vulnerable watersheds to target for the AEEMP monitoring program (USEPA, 2009a). 

Because the model generates time-weighted concentrations (e.g., maximum 60-day average 

concentration in a year), it may also be useful in identifying watersheds that have a greater 

potential for exceeding the aquatic plant community level of concern concentration. The EPA 

will be evaluating its utility in this regard during registration review. 
132

16. Method for Comparing Monitoring Data to the Aquatic Plant Community CE-LOC 

While reviewing this section, please consider the charge questions below. 

SAP Questions: 

 Please comment on the strengths and limitations of EPA’s development and use of 

bias factors (Chapter V, Section 16.1) for addressing uncertainties in monitoring 

data. 

Prediction of bias factors is dependent on the selection of an appropriate model. EPA 

illustrated (Chapter V, Section 16.1) both categorical and regression methods for prediction 

of bias factors based solely on the number of samples taken in the 2nd and 3rd quarters of 

the year (April 1st to September 30th). 

 Please comment on EPA’s prediction of bias factors from monitoring data using 

categorical or regression method approaches. 

 Please comment on any additional methods for estimating bias factors that would 

be useful in this situation.

EPA illustrated (Chapter V, Section 16.1) both categorical and regression methods for

estimation of bias factors as a function of the sampling frequency of monitoring data. Stepwise regression analysis indicates that watershed size and average flow rate in the 2nd and 

3

rd quarters of the year are not significant variables for prediction of bias factors. However, 

the number of samples in the 2nd and 3rd quarters of the year was found to be a significant 

variable, accounting for 46% of the variation in the bias factor. 

 What other variables, if any, should be considered in the prediction of bias factors? 

 

EPA examined (Chapter V, Section 16.1) the performance of various regression equations to 

assess the failure percentage for identification of monitoring site-years with true maximum 

60-day average concentrations exceeding the CE-LOC for atrazine. This analysis showed 

that application of a bias factor, based on sample number during the 2nd and 3rd quarter of 

the year, substantially reduced the number of sites with underestimation of true maximum 

60-day means. 

 Given the EPA analysis, what other tests, if any, should be conducted to assess the 

performance of regression models for prediction of bias factors? 
133

16.1. The Development of Bias Factors 

Implementation of a PATI derived CE-LOC concentration requires addressing the uncertainty in 

capturing the true maximum 60 day mean concentration from monitoring programs of different 

designs. As discussed in the surface water monitoring section, sampling frequency among 

monitoring programs is variable. Sampling frequency, however, is an important consideration in 

the accurate estimation of pesticide concentrations in surface water. The 2011 FIFRA SAP 

recommended that the use of bias factors is an appropriate approach for addressing 

uncertainty in capturing true concentrations from monitoring data. This section provides an 

illustration of such an approach for the development of factors to address uncertainty in 

capturing the maximum 60 day mean from monitoring data. The bias factor serves as a 

protective multiplier of the actual concentration from monitoring data to account for 

uncertainty associated with sampling frequency. The general bias factor equation is as follows: 

Ŷ = X*BIAS FACTOR

Where: 

Ŷ =Estimated True Maximum 60 day average atrazine conc. 

X= Maximum 60 day rolling mean atrazine conc. obtained from monitoring data 

Bias Factor=True maximum 60 day rolling mean atrazine conc./Estimated 5th percentile 

maximum 60 day rolling average atrazine conc. 

The development of bias factors in this analysis is based on selected monitoring data from the 

AEEMP and NCWQR monitoring programs (Appendix G). Watershed characteristics and 

descriptive statistics of selected atrazine monitoring are shown in Table 26. The data were 

selected because they represent site-year chemographs with limited data infilling and long 

sampling periods (April 1st to September 17th). For this analysis, geographic and hydrologic 

properties were not used to discriminate the monitoring data. Missing data in each 

chemograph was infilled using a stair-step imputation between measured values. The measured 

atrazine concentration for each sampling day represents the highest measured value of the day, 

regardless of the monitoring method (grab vs autosample) or the number of samples taken 

within a given day. 
134

Table 23. Watershed Characteristics for Selected AEMP and NCWQR Monitoring Sites

Site Year

Watershed 

Area (acres)

Average Flow

(m3/sec)

Maximum

Peak

Maximum

60 day 

Average

μg/L

MO-05 2008 16192 0.3190 37.83 5.74

MO-05b 2008 116781 26.1526 36.83 7.04

MO-02 2009 18023 NR 155.20 16.83

MO-02 2008 18023 0.10074 56.60 7.57

MO-02 2007 18023 0.01920 16.18 3.46

MO-04a 2008 5382 0.8595 144.69 11.84

IN-11 2008 5780 1.3593 27.12 2.03

Sandusky 1995 800621 328.475 15.46 6.47

Bias factors were derived using a Monte Carlo sub-sampling process as presented to the 2011 

FIFRA SAP (FIFRA SAP, 2011). A similar approach was used by Syngenta to develop bias factors 

from AEEMP and NCWQR data (Mosquin et al. 2011). Each constructed chemograph was 

randomly subsampled 10,000 times using subsampling intervals of 4 days, 7 days, 14 days, and 

28 days. The sampling simulation was conducted using the Crystal Ball software programs 

(Crystal Ball® 2000 and Crystal Ball PredictorTM, 1999) starting with a common seed (Appendix 

G). For each sampling realization, a random value from the custom distribution of values within 

the designated time interval was selected to represent a value at each sampling interval within 

the chemograph. These selected concentrations were then used to construct simulated daily 

chemographs of atrazine concentrations using a linear interpolation. From a distribution of the 

10,000 simulated chemographs, the 5th percentile maximum 60 day rolling mean atrazine 

concentration was selected to derive the bias factor. Selection of the 5th percentile maximum 

60 day rolling mean atrazine concentration would provide development of protective bias 

factors. Protective factors would ensure that when applied the estimated 60 day maximum 

mean concentration would be equal to or higher than the true 60 day maximum mean 

concentration. The bias factor was calculated by dividing the true maximum value from the 

original chemograph by the 5th percentile maximum 60 day rolling mean atrazine concentration 

from the Monte Carlo simulation (Appendix G). 

Some uncertainties, limitations, and assumption in the development and application of the bias 

factor in this analysis are: 

 Random sampling is simulated for the 2nd and 3rd quarters of the year. It is anticipated 

that systematic sampling in the field or sampling around rainfall events would alter bias 

factor estimation. 
135

 Serial correlation of daily atrazine concentrations is not directly considered in the 

estimation of the bias factor. It is anticipated that serial correlation effects on bias 

factor estimation is dependent on sampling interval. 

 The extent of data infilling for the development of an annual chemograph is expected 

to impact the reliability of the bias factor estimation. In this analysis, AEEMP monitoring 

data were selected for their low infilling amount as well as long duration of monitoring 

during the 2nd and 3rd quarters. 

 Because the bias factors are based on monitoring data from the 2nd and 3rd quarters of 

the year, they are probably not applicable to monitoring sites with atrazine use in the 1st

and 4th quarters. 

 The bias factors in this analysis may not be representative of all atrazine use site-year 

combinations in the AEEMP and NCWQR monitoring data because they only represent 7 

site-years. 

 

The 60 day average monitoring bias factors for 4, 7, 14, and 28 day sampling intervals are 

shown in Table 24 (Appendix G). The minimum bias factor is 1. There is an inverse relationship 

between the calculated bias factor and sampling frequency; the bias factor and it variability 

increases with a decrease in sampling frequency or an increase in sampling interval (Figure 29). 

Similar results were found in a preliminary analysis of AEEMP and NCWQR monitoring data for 

different geographic areas and watershed sizes (Appendix G). Among the various monitoring 

sites presented in Table 24, the average bias factor for maximum 60 day mean atrazine 

concentrations is -1.79 for the 4-day sampling interval, -2.56 for the 7-day sampling interval, -

3.38 for the 14-day sampling interval, and -8.35 for the 28 day sampling interval. The bias 

factors are reported as negative numbers to represent the extent of underestimation from the 

true value. 
136

Table 24. Atrazine Monitoring Bias Factor for Predicting the Maximum 

60 day Average Concentration

Site

Sampling Interval

4 day 7 day 14 day 28 day

MO-05b 2008 -1.47 -2.02 -3.89 -7.91

MO-05 2008 -1.89 -3.48 -3.36 -4.67

MO-02 2008 -1.94 -2.64 -1.94 -7.81

MO-02 2009 -1.90 -2.36 -3.10 -8.50

MO-04a 2008 -2.41 -4.27 -6.80 -22.34

IN-11 2008 -1.13 -1.92 -2.57 -5.08

SANDUSKY 1995 -1.17 -1.21 -2.00 -2.13

Descriptive Statistics

Mean -1.79 -2.56 -3.38 -8.35

Median -1.89 -2.46 -3.23 -7.86

Maximum -2.41 -4.27 -6.80 -22.34

Minimum -1.13 -1.21 -1.94 -2.13

Number of Samples in 2nd and 3rd Quarter

0 10 20 30 40 50

Bias Factor

0

5

10

15

20

25

Bias Factor

0

5

10

15

20

25

MO-05b 2008 

 MO-05 2008 

 MO-02 2008 

MO-02 2009 

MO-04a 2005 

 IN-11 2008 

 SAND 1995 

Col 10 vs Col 11 

Figure 29. Relationship of Bias Factor and Sampling Frequency for Selected Watersheds from 

AEEMP and NCWQR Monitoring Programs. 
137

Selection and use of bias factors may be accomplished by using either a categorical or 

regression-based approach. The sample number was determined by dividing 180 days 

(representing the 2nd and 3rd quarters) by the sampling interval. For this analysis, the various 

approaches are not expected to represent all atrazine monitoring sites due to limited 

geographic and hydrologic variability in the test data. Forward stepwise multiple regression, 

however, indicate that watershed size and average flow are not significant variables (p< 0.45) 

for prediction of bias factors. In contrast, sample number was a significant variable (p<0.0029) 

for predicting bias factors. Therefore, the development of bias factors is based on the 

relationship of sample number and bias factor. 

A categorical approach would require the assignment of a unique bias factor for each sampling 

interval (Figure 30). Selection of the appropriate bias factor would assume the bias factor is 

fixed between the windows of sample intervals. For example, using an upper 95% confidence 

interval of the mean bias factors, a sampling frequency of 25 to 46 samples would be assigned a 

bias factor of 1.87(2); 12 to 26 samples would be assigned a bias factor of 2.94 (3); 7 to 13 

samples would be assigned a bias factor of 4.01(4); and ≤ 6 samples would be assigned a bias 

factor of 10.83 (11). The resolution of bias factor assignment is dependent on the number of 

different sampling intervals used in deriving bias factors; fewer sampling intervals would invoke 

more uncertainty in the deviation and selection of the bias factor. 

Number of Samples in 2nd and 3rd Quarter

10 20 30 40 50

Bias Factor

0

2

4

6

8

10

12

Figure 30. Categorical Designation of Upper 95% Confidence Limit of the Mean Bias Factor 

According to Sampling Frequency. 
138

Another approach for assignment of bias factors is the use of regression equations to describe 

the relationship between sample number and bias factor (Appendix K). The development of a 

regression model would be an important tool for estimating the true 60 day maximum annual 

mean from monitoring data with different sampling frequencies. This approach allows 

prediction of bias factors for a large number of sampling intervals. 

The first regression equation was derived using the SigmaPlot Regression Wizard (Version 11). 

This equation was selected to represent the relationship of bias factor and sample numbers in 

the 2nd and 3rd quarters. The best least-squares non-linear regression fit was a 4-parameter 

exponential decay model [y = 470.8251*exp (-0.0708*x) +-458.7698*exp(-0.0708*x); r2=0.3304; 

p<0.02] where y is the bias factor and x is the number of samples (

Figure 31). The upper 95% confidence interval of the regression[y =1383.0681*exp (-1.067*x) 

+11.6378*exp(-0.0425*x); r2=0.9993; p<0.0001)] was also fit and is presented on the graph the 

graph in red. 

Number of Samples

0 10 20 30 40 50

Bias Factor

0

5

10

15

20

25

Nonlinear Regression Equation

Upper 95th Percentile

Figure 31. Nonlinear Regression between Number of Samples and 60 Day Average Bias 

Factors 

A second approach was made by fitting the average bias factor against the number of samples 

in the 2nd and 3rd quarters. In this case, the best fitted equation was also a a 4-parameter 

exponential decay model [y= 170.5297*exp (-0.5580*x) + 4.1246*exp (-0.0186*x); r2=1.00 

](Figure 32). Although the variability in bias factors is removed using this approach, it may 

provide a useful predictor of the mean bias factor as a function of the number of samples in the 

2

nd and 3rd quarters. 
139

Number of Samples in 2nd and 3rd Quarter

0 10 20 30 40 50

Bias Factor

1

2

3

4

5

6

7

8

9

Figure 32. Nonlinear Regression of Number of Samples and the Mean 60 Day Average Bias 

Factor Across Watersheds (7 Site-Years) 

A third approach was conducted using a 1st order linear model on log-transformed bias factor 

values. The resulting log- linear equation is log y= 0.78616 -0.013729, (r2=0.4634, p<0.0001) (

Figure 33). The upper 95% confidence interval and prediction intervals for the bias factors are 

also presented. The regression model for the 95% confidence interval is log y = 0.946326366-

0.007773*X. 

 Number of Samples in the 2nd and 3rd Quarter

5 10 15 20 25 30 35 40 45

Log Bias Factor

0.1

1

10

100

Bias Factor 

95% Confidence Bounds

95% Prediction Interval

Figure 33. Relationship of Number of Samples and All Data 60 Day Average Bias Factor Across 

Watersheds 
140

As expected, the highest variability in bias factors is associated with the 28-day sampling 

frequency. This is not unexpected because infrequent sampling leads to a greater likelihood 

that the peak atrazine concentration will not be measured. This is an important consideration 

since the estimation of the true average pesticide concentrations is dependent on capturing the 

peak concentration (USEPA, 1998). However, the magnitude of bias factors also appears to be 

dependent on the shape of the chemograph (Figure 34). From our data analysis, the MO-04a 

2008 data had the highest estimated bias factors when compared to the other monitoring sites. 

Examination of the MO-04a 2008 chemograph shows it has fewer and sharper peaks when 

compared with the MO-05b 2008 and Sandusky 1995 chemographs. The sharpness and number 

of the chemograph peaks represents the measured temporal occurrence pattern. A similar 

observation was found in a preliminary analysis of other AEEMP and NCWQR monitoring data. 

Atrazine Concentration (ug/L)

0

20

40

60

80

100

120

140

160

Julian Day

100 120 140 160 180 200 220 240 260 280

Atrazine Concentration (ug/L)

0

10

20

30

40

50

60

3 4 5

Atrazine Concentration (ug/L)

0

10

20

30

40

50

60

A)

B)

C)
141

Figure 34. Difference in Chemograph Shapes and Height for Monitoring Site-Years Used for 

Development of Regression Equation: A.) MO-04a 2008; B) MO-05b 2008; and C) Sandusky 

1995. 

The predicted bias factors using the derived regression equations are shown in Table 25. As 

expected, each method provides some degree of over or underestimation of bias factor for a 

given sampling frequency. In general, the upper 95% confidence interval of the log-linear 

equation provided the most conservative estimates of bias factor at sampling frequencies less 

than 20 samples per 180 days. At sampling frequencies greater than 20 samples per 180 days, 

the upper 95% confidence interval of the non-linear equation provides more conservative 

estimates of bias factors. As discussed above, the greatest uncertainty in bias factor estimation 

is associated with the longest sampling intervals (28 days) or the fewest samples (6 samples in 

180 days). Therefore, the applicability of bias factor estimation may have defined limits 

according to sample frequency. The lowest bias factor is constrained to 1. The highest bias 

factor in this analysis is 22.34 at the 28 day sampling interval. As discussed, presumably the 

magnitude of the bias factor appears to be related to the sharpness and number of the peaks. 

Table 25. Estimated Bias Factors Using the Categorical and Regression-Based Estimation Methods.

Sampling 

Interval 

(Days)

Number 

of 

Samples 

Over 180 

Days

Categorical

Bias Factor

Average 

Non-Linear 

Bias Factor

Log 

Linear 

Bias 

Factor

Log Linear 

Bias Factor 

Upper 95% 

Confidence 

Interval

NonLinear 

Bias 

Factor

Non-Linear 

Bias Factor 

Upper 95% 

Confidence

Interval

4 45 1.87 1.79 1.55 3.95 1.00 1.72

7 26 2.94 2.56 2.79 5.58 1.95 3.90

10 18 2.94 2.96 3.53 6.40 3.37 5.42

14 13 4.01 3.38 4.13 7.02 4.85 6.74

20 9 4.01 4.61 4.65 7.52 6.37 8.03

28 6 10.83 8.38 5.02 7.88 7.65 10.30

To demonstrate the application of the bias factor approach using the regression equations, 190 

available AEEMP site-year data sets were sampled using 4, 7, 10, 14, 20 and 28 day fixed 

sampling intervals. The various regression equations were used to estimate the factors (Table 

12). Four chemographs were developed for each sampling interval by site-year combination. 

The chemographs were developed through systematic sampling at a fixed interval using the 

first 4 days of the monitoring interval as different starting dates. Each chemograph for the 

sampling interval-site-years was developed by stair-step imputation between sampled 

concentrations. The raw data and its summary for this performance analysis are provided in the 

Appendix G. 
142

The purpose of the bias factor adjustment is to address uncertainty in estimating the true 

maximum 60-day mean according to sample frequency over 180 days. This analysis illustrates 

that estimation of the unadjusted maximum 60 day mean from 4, 7, 10, 14, 20, and 28 at 

uniform sampling intervals underestimates the true maximum 60 day mean at 82 to 94% of the 

sites (Table 26). As expected, the application of bias factors to adjust the maximum 60 day 

mean resulted in substantially fewer underestimations of true maximum 60 day mean. The 

regression equation with the fewest underestimations of true maximum 60 day mean is the 

upper 95% confidence interval of the log-linear equation. 

Table 256. Percentage of the AEEMP site-years (N=190) that failed to meet or exceed the 

actual 60-day maximum running mean based on various sampling intervals. 

Sampling 

Interval 

(Days)

60-Day 

Maximum 

Running 

Average, 

Unadjusted

Average 

Non-Linear 

Bias Factor

Log 

Linear 

Bias 

Factor

Log Linear 

Bias Factor 

Upper 95% 

Confidence 

Interval

NonLinear 

Bias 

Factor

Non-Linear 

Bias Factor 

Upper 95% 

Confidence 

Interval

4 82 3 12 1 82 7

7 94 9 7 0 16 3

10 88 10 8 1 8 2

14 88 13 8 1 5 1

20 86 16 16 4 7 4

28 89 5 15 5 5 3

Bias factor estimation methods were evaluated to provide an illustration of various approaches 

for quantifying atrazine concentrations from monitoring programs with different sampling 

frequencies. In this case, the maximum 60 day mean concentration was used because it is the 

concentration CE-LOC derived from the PATI model. The bias factor adjusted maximum 60 day 

mean concentration from monitoring programs may be useful in identifying sites where 

additional monitoring may be required to assess potential ecological exposure from atrazine. 

16.2. Translating Monitoring Data with the Bias Factor 

The proposed method for determining whether a water body exceeds the Aquatic Plant 

Community LOC (CE-LOC), is as follows. The monitoring data for each year is collected and 

evaluated based on the following conditions: 

1) A total of at least 4 samples across the year are required to construct a chemograph 

and calculate a 60-day maximum running mean. 

a. Summary statistics for the site are calculated. 
143

b. A chemograph is constructed using a stair-stepping technique (linear 

interpolation preferred) with a minimum concentration of 0.16 μg/L (LOQ in 

the NAWQA Database) used as the concentration prior to the first 

measurement of the year, 

c. The final annual measurement within a single data set is carried over 4 days, 

then the concentration is dropped to 0.16 μg/L for the duration of the year, 

d. The maximum 60-day running mean is calculated from the chemograph. 

2) The available monitoring data with at minimum 6 samples in the 2nd and 3rd quarters 

are adjusted with the bias factor approach. 

a. Log Linear Bias Factor upper 95% confidence interval on the mean is used as 

a multiplier to correct the maximum 60-day running mean to what would be 

expected from daily sampling at these sites. 

3) Lastly the maximum 60-day running mean and the bias factor adjusted value are 

compared to the CE-LOC. 

16.3. Results of Preliminary Review of Available National Monitoring Data. 

Data Sources Evaluated as of 5/8/2012: 

2003-2011 Finished Water; 2003-2011 Raw Water; AEEMP; CA; Heidelberg 1; Heidelberg 

2; Heidelberg 3; Heidelberg 4; Heidelberg 5; Heidelberg 6; IA DNR 2003-2006; KS All 

Lakes and Wetland; KS Streams; KS WQ 2009-2011; MN MDA SW 2008-2011; MN MDA 

WQ 1993-2007; NAWQA; NE; PDP; WI 2008; WI 2009; WI 2010; WI 2011; USEPA 

Reservoir Data 1999-2000 (summary data provided in Appendix G) 

 Total number of site-year combinations meeting criteria: 6917 site-years 

Two general types of data were identified from the analysis of the available monitoring data, 

and were ranked based on the relative confidence in their results: 

Bias Factor Applicable Data: 

Sampling intervals 14 days or less (i.e., 12 or more samples for the 2nd and 3rd quarters 

combined) 

This temporal limitation to the 2nd and 3rd quarters was based on atrazine exposure typical 

in the AEEMP data. These data are considered of higher quality than are those with less 

frequent sampling. Bias factors for these datasets ranged from 3.36 to 7.13. 
144

 Total number of sites meeting the criteria for bias factor use: 3385 site-years 

 Total number of exceedances when bias factors are applied (4 μg/L): 2353 

site-years (70%) 

 Total number of exceedances when bias factors are applied (7 μg/L): 1886 

site-years (56%) 

Sampling intervals 28 days or less (i.e., 6 or more samples for the 2nd and 3rd quarters 

combined) 

This temporal limitation to the 2nd and 3rd quarters was based on atrazine exposure typical 

in the AEEMP data. These data are considered of less high quality than the previous set. Bias 

factors for these datasets ranged from 3.36 to 7.94. 

 Total number of sites meeting the criteria for bias factor use: 5124 site-years 

 Total number of exceedances when bias factors are applied (4 μg/L): 3125 

site-years (61%) 

 Total number of exceedances when bias factors are applied (7 μg/L): 2488 

site-years (49%) 

Unadjusted Data: 

All available data were also reviewed based on the 60-day maximum running mean 

concentration. This includes data with sampling intervals greater than 14 days during the 

2

nd and 3rd quarters (i.e., fewer than 12 samples for the 2nd and 3rd quarters combined) 

These data are considered for review but there is some uncertainty in the exceedances 

based on the infrequency of sampling. Because the bias factors were developed based on 

the AEEMP and Heidelberg data, their emphasis being on the 2nd and 3rd quarters, the 

applicability of the bias factor to data collected in other quarters is uncertain. 

 Total number of sites assessed: 6917 site-years 

 Total number of exceedances based on 60-Day maximum running mean 

 (4 μg/L): 779 (11%) 
145

 Total number of exceedances based on 60-Day maximum running mean 

(7 μg/L): 471 (7%) 

16.4. Scope of National Aquatic Plant Communities Potentially Threatened by Atrazine 

Exposure. 

The extent of the atrazine levels exceeding the Aquatic Plant Community CE-LOC (4 ppb) is 

reviewed in this section. According to the available monitoring data from Federal, State, Local 

and Registrant sources, the following states have exceedances of the CE-LOC (site specific 

details are reported in APPENDIX G): 

Based on 60-Day Running Means:

4 μg/L (21 States): AL, AR, FL, IA, IL, IN, KS, KY, LA, MD, MI, MO, MS, ND, NE, NJ, OH, 

TN, TX, VA, and WI 

7 μg/L (15 States): AL, AR, IA, IL, IN, KS, LA, MO, MS, NE, OH, TN, TX, VA, and WI 

Based on Bias Factor Adjusted Values, 28-day interval:

4 μg/L (30 States): AL, AR, CA, CO, FL, IA, IL, IN, KS, KY, LA, MD, MI, MN, MO, MS, NC, 

NE, NJ, NY, OH, OK, OR, PA, SD, TN, TX, VA, WA, and WI 

7 μg/L (27 States): AL, AR, CA, FL, IA, IL, IN, KS, KY, LA, MD, MI, MN, MO, MS, NC, NE, 

NJ, NY, OH, OR, PA, SD, TN, TX, VA, and WI 

An important limitation of the bias factor application used here is that those site-years with 

fewer than 6 samples gathered throughout the 2nd and 3rd quarters are not adjusted with the 

bias factor. Exceedances based on data collected in the 1st and 4th quarters provide additional 

insight into atrazine exposures outside of the primary application period for corn and sorghum 

crop areas and may reflect exceedances due to the other uses mentioned in Section 3.2 above 

or differences in use patterns due to the latitudinal gradient of seasonality. There were 14 

states (110 site-years) that had too few samples within the 2nd and 3rd quarters for bias factor 

adjustments but had 60-day running averages above the 4 μg/L CE-LOC, and 11 states (48 siteyears) above the 7 μg/L CE-LOC. 

The monitoring data can also be used to test the performance of the vulnerable areas analysis 

(Section 15.3) that was based on the analysis of the AEEMP watershed characteristics. In this 

review of the monitoring data, the data were parsed into two categories “Prior to 2006” and 
146

“2006-2011”. These categories were selected to also review the potential effects of the 

reduction in the maximum allowable annual pounds/acre, enforcement starting in 2006. 

The AEEMP monitoring sites in relation to the pounds of atrazine use per 1000 acres, the 

vulnerable areas analysis results, and the designated 303d atrazine impaired waterways are 

shown in Figure 35. What is reflected in the map regarding the vulnerability analysis (gold 

areas) is that exceedances are generally associated with the predicted areas. In addition, a 

number of states have identified atrazine related impairment to waterways. These impaired 

waterways reflect that atrazine exposures outside of the vulnerable areas analysis, and not 

associated with AEEMP monitoring sites, are also of concern. 

Figure 35. AEEMP monitoring program sites in relation to 303d atrazine impaired waterways 

(dark red areas), and the vulnerable areas (gold areas) identified through the methods 

discussed in Section 15. (The following 303d listings have not been mapped: ILC08_C33; 

ILC09_C09; ILC19_C19; ILCD01_CD01; ILCH01_CH02; ILJQ03_RJF; ILJQ03_RJG; ILN11_N11; 

ILN12_N12; ILNC07_NC07; ILNE05_NE05; ILOEB01_ROV; ILOIL01_ROT; ILOJ08_ROK; 

ILOZC01_SOC; ILROA_ROA; IL_SDH; IL_SDZO; IL_SOL) 

 
147

To further investigate the atrazine exposure outside of the AMP and AEEMP monitoring 

program, the EPA reviewed the available monitoring data in a spatial context. The next several 

figures show NAWQA monitoring sites that have exceeded the CE-LOC. The NAWQA data set 

was selected for an example here because they contain the GIS localities for all of the 

monitoring sites. The other available monitoring programs may also have GIS localities for each 

of the monitoring sites, however this information was not provided to the EPA at this time. 

The NAWQA sites that exceed the 4 μg/L and 7 μg/L CE-LOC based on the 60-day maximum 

running mean are shown in Figure 36 and Figure 37 respectively. The distribution of exceeding 

sites compared to the vulnerability analysis seems to identify vulnerable areas; however a 

number of sites fall outside of the identified vulnerable areas. These sites make sense in the 

context of the pounds of atrazine used per 1000 acres. The NAWQA data results in 36 sites 

exceeding the 4 μg/L CE-LOC and 5 sites exceeding 7 μg/L between 2006 and 2011, in 

comparison to 123 and 41 sites exceeding from 1992-2005, possibly reflecting the reduced 

runoff based on the rate reductions implemented in 2006. 

Figure 36. NAWQA monitoring sites that exceed the 4 μg/L CE-LOC based on the 60-day 

running average. 
148

Figure 37. NAWQA monitoring sites that exceed the 7 μg/L CE-LOC based on the 60-day 

running average. 

The NAWQA 4 μg/L and 7 μg/L CE-LOC exceedances based on the bias factor adjusted 60-day 

maximum running mean and a minimum of 6 samples across the 2nd and 3rd quarters are shown 

in Figure 38 and Figure 39. Based on this distribution of exceeding sites, the most predictive 

feature is the amount of atrazine used per 1000 acres. This reduced set of the NAWQA data 

results in 47 sites exceeding the 4 μg/L CE-LOC and 38 sites exceeding 7 μg/L between 2006 and 

2011, in comparison to 123 and 108 sites exceeding from 1992-2005, possibly reflecting the 

reduced runoff based on the rate reductions implemented in 2006. 
149

Figure 38. NAWQA monitoring sites that exceed the 4 μg/L CE-LOC based on the bias factor 

adjusted 60-day running average. Only those site-years with 6 or more samples in the 2nd and 

3

rd quarters were mapped. 
150

Figure 39. NAWQA monitoring sites that exceed the 7 μg/L CE-LOC based on the bias factor 

adjusted 60-day running average. Only those site-years with 6 or more samples in the 2nd and 

3

rd quarters were mapped. 

The implementation of the Aquatic Plant Community CE-LOC results in a picture of the national 

scope of atrazine exceedances and reflects that the 2009 vulnerability analysis identified 

watershed characteristics that were predictive but not entirely representative of the 

exceedances seen in the available monitoring data. These results indicate that those sites that 

have exceeded the CE-LOC would require additional monitoring to obtain data for, at minimum, 

a 14-day interval for the likely periods of atrazine runoff. These times of year will vary on a 

nationwide scale due to what crop is being treated and the seasonality of use (e.g., due to 

temperature). 
151

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