Modeling Pesticide Aquatic Exposures in California for Regulatory

Mar 26, 2019 - Abstract: The Imperial, Salinas, and Santa Maria valleys are the targeted ... Abstract: The overall goal of the Ecotoxicology Station i...
0 downloads 0 Views 2MB Size
Download PDF
Chapter 15

Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management Downloaded from pubs.acs.org by BETHEL UNIV on 04/01/19. For personal use only.

Modeling Pesticide Aquatic Exposures in California for Regulatory Purposes: Model Review and Scenario Assessment Yina Xie,* Yuzhou Luo, Nan Singhasemanon, and Kean S. Goh Environmental Monitoring Branch, California Department of Pesticide Regulation, P.O. Box 4015, Sacramento, California 95812-4015, United States *E-mail: [email protected].

To support the model development and refinement for pesticide registration evaluation in the California Department of Pesticide Regulation’s Surface Water Protection Program (CDPR/SWPP), three receiving water body models and the related modeling scenarios were reviewed and assessed for their capability of providing a worst-case representation of aquatic exposures to pesticides in California. Review of the modeling methodology showed that the Variable Volume Water Model (VVWM), developed by the U.S. Environmental Protection Agency (USEPA), was a promising tool for use by SWPP. We also confirmed that the USEPA pond scenario was appropriate for the regulatory aquatic modeling and risk assessment based on California conditions.

Introduction Applications of pesticides to croplands and urban areas can result in off-site movement of pesticides to an adjacent water body. The receiving water body model is developed to assess the risk of pesticide uses with regard to aquatic organisms. The model accounts for various physicochemical and microbial processes associated with the fate of pesticides in the receiving water body and predicts the estimated environmental concentrations (EECs) for pesticide exposure characterizations (1). An important use of the receiving water body model is to provide a conservative estimate of pesticide exposures for the aquatic © 2019 American Chemical Society

risk assessment in support of regulations (e.g., the screening-level ecological risk assessment for pesticide registration evaluation) (2). Typical models include: (i) the Variable Volume Water Model (VVWM), which was developed by the U.S. Environmental Protection Agency’s Office of Pesticide Programs (USEPA/OPP) (3) superseding the Exposure Analysis Modeling System (EXAMS) (4); (ii) the AGRO-2014 model, which was refined from the Canadian Environmental Modelling Centre’s (CEMC) AGRO modeling system (5–8) by the Stone Environmental Inc. (9) based on evaluations from the Federal Insecticide, Fungicide, and Rodenticide Act’s (FIFRA) Scientific Advisory Panel (SAP) (10); and (iii) the Toxic Substances in Surface Waters (TOXSWA) model, which was developed by Alterra, in cooperation with W!SL, the Wageningen Software Labs, in Wageningen, Netherlands (11) and adopted by the European Forum for the Coordination of Pesticide Fate Models and their Use (FOCUS) Workgroup. In order to assess aquatic risks for regulatory purposes, receiving water body models are typically used in conjunction with the Pesticide Root Zone Model (PRZM), a one-dimensional conceptual model that predicts pesticide loads from an adjacent field treated with pesticides (12). The Pesticide in Water Calculator (PWC) is a graphical user interface (GUI) that links the output of PRZM to VVWM (13). The PWC is the primary tool recommended by the USEPA for pesticide product registration evaluation and aquatic risk assessment in the United States. Similarly, a GUI called PA5 shell is available to link PRZM to AGRO-2014, providing an alternative approach for predicting aquatic exposures especially to hydrophobic pesticides such as pyrethroids (9). In addition to PRZM, FOCUSTOXSWA is also used in conjunction with other field-scale models such as the FOCUS drift calculator and the MACRO drainage model. The software interface, Surface Water Scenarios Help (SWASH) (14–16), is recommended by FOCUS for pesticide registration evaluation in the European Union (17, 18). Configuration of the receiving water body scenarios (e.g., the dimensions and physicochemical properties of the water body) is an important factor for determining model predictions. Properties of receiving water bodies vary from site to site. To ensure the regulations provide adequate protection, it is necessary to define a standard scenario that represents the worst-case aquatic exposures to pesticides. Several standard scenarios have been developed by the USEPA and FOCUS, for example, the USEPA pond (3, 4, 13) and the FOCUS pond, ditch, and stream (17, 18). These scenarios provide multiple water body configurations to support the regulatory aquatic risk assessment. The California Department of Pesticide Regulation’s Surface Water Protection Program (CDPR/SWPP) is improving their modeling system to better assess the aquatic risks of pesticide products submitted for registration in California. A receiving water body model that is configured to provide a worst-case representation of aquatic exposures to pesticides in California’s receiving water bodies would be a key component of this system. Currently, there is no systematic review of available receiving water body models or the associated modeling scenarios for pesticide assessments based on California conditions. This chapter captures SWPP’s derivation of a California-based receiving water body model for use in pesticide registration evaluation in SWPP. The chapter includes two parts: (i) a review of receiving water body models 292

that are designed to support pesticide registration evaluation (i.e., VVWM, AGRO-2014, and FOCUS-TOXSWA) and identify the appropriate model to be used by SWPP, and (ii) an assessment of receiving water body scenarios and their application to California conditions. VVWM version 1.02 (released on July 1, 2014), AGRO-2014 version 1.2 (released on May 29, 2015), and TOXSWA version 4.4.3 (the current version linked with FOCUS, i.e., FOCUS-TOXSWA) (19) are reviewed here.

Model Review Conceptual Model In VVWM, AGRO-2014, and FOCUS-TOXSWA, a receiving water body is commonly simulated as a two-compartment system consisting of water and sediment. Within a compartment, there are subcompartments. The water compartment contains pure water and sorbing media such as suspended solids (SS), dissolved organic carbon (DOC), and biota. The sediment compartment contains pore water and sorbing media such as benthic particles, benthic DOC, and benthic biota. Pore water, or sediment interstitial water, is the water that occupies the spaces between sediment particles and can be contaminated by chemical partitioning from surrounding sediments (20). Key processes associated with the fate of pesticides in the system are illustrated in Figure 1.

Figure 1. Schematic diagram of the conceptual model for pesticide fate in a receiving water body. In addition to the processes outlined in Figure 1, FOCUS-TOXSWA also considers pesticide transport with water flow in two directions—horizontally in the water compartment via advection and dispersion and vertically downwards 293

in pore water via advection, dispersion, and diffusion. A concentration gradient is calculated for each direction by using a coordinated segment system. The conceptual model in Figure 1 applies to each computational segment. Later in this chapter, “water compartment” and “sediment compartment” for FOCUS-TOXSWA will refer to the compartments in each segment. The VVWM and AGRO-2014, in contrast, assume that pesticides are uniformly distributed within each compartment. All three models commonly assume that instantaneous equilibrium of pesticides is established within a compartment (i.e., all material in each compartment is at thermodynamic equilibrium). This assumption is usually justified since chemical partitioning within a compartment is a relatively rapid process compared to the mass transfer between compartments (21). For FOCUS-TOXSWA, since it allows a concentration gradient in the flow direction, it also assumes that the water layer is ideally mixed in any wetted surface perpendicular to the flow direction. Modeling Methodology The three models are built on the principle of mass balance. The mass conservation equations (notated in differential equations in time for unsteady-state conditions) are formulated for both the water and sediment compartments. The VVWM and AGRO-2014 analytically solve the differential equations in a daily piecewise fashion, while the FOCUS-TOXSWA retains a numerical solution. Table 1 presents a schematic comparison of key processes involved in the models regarding mass balance of pesticide fluxes. Pesticides are delivered to the receiving water body via overland runoff and/or spray drift. The runoff inflow consists of water, SS, and pesticides in the dissolved and sorbed phases. System input of water, SS, and pesticides can be read from the PRZM output. The three models differ in the initial distribution of the inflow substances between the water and sediment compartments. In AGRO-2014 and FOCUS-TOXSWA, all inflow substances are delivered to the water compartment; whereas in VVWM, a fraction of sorbed pesticides is delivered directly to the sediment compartment. Pesticide mass transfer between the water and sediment compartments involves several mechanisms, including the dissolved pesticide exchange via diffusion and the sorbed pesticide exchange via sediment settling and resuspension. There are two different approaches to simulate the mass transfer between compartments. The AGRO-2014 and FOCUS-TOXSWA explicitly model the exchange mechanisms and compute the mass flux based on the individual mass transfer coefficients. One difference between the two models is that FOCUS-TOXSWA assumes sediment settling/resuspension is negligible and considers pesticide diffusion only, while AGRO-2014 simulates both processes. The assumption used by FOCUS-TOXSWA is only acceptable if the sediment settling/resuspension flux is negligibly small, which could be the case, for example, for sheltered, very slow-flowing ditches (22); otherwise, it would be problematic to disregard an essential process. The other approach is to model the mass transfer as a bulk process that includes all means of pesticide exchange 294

between the water and sediment compartments. This approach is adopted by VVWM with a bulk transfer described by a first-order, overall mass transfer coefficient. The necessary algorithm used by the three models for computing the mass transfer between compartments is demonstrated by Xie (23).

Table 1. Key Processes Considered in the Three Models

295

Pesticides adsorb to various media in the water (e.g., SS, DOC, and biota) and sediment (e.g., benthic particles, benthic DOC, and benthic biota) compartments. The VVWM considers a whole range of sorbing media, whereas AGRO-2014 only uses SS and benthic particles and FOCUS-TOXSWA only uses SS, aquatic biota, and benthic particles. In VVWM and AGRO-2014, the sorption process is described using a linear isotherm. In FOCUS-TOXSWA, pesticide sorption to SS and benthic particles is described using the non-linear, Freundlich equation, while sorption to biota is described using the linear isotherm. Pesticides dissipate in the water body through a variety of degradation processes, including photolysis, aqueous hydrolysis, aqueous metabolism, benthic hydrolysis, and benthic metabolism. The VVWM explicitly models these processes assuming that they follow first-order kinetics. It also assumes that benthic hydrolysis occurs at the same rate as aqueous hydrolysis and that the sorbed-phase metabolism occurs at the same rate as the aqueous-phase metabolism within a compartment. The AGRO-2014 and FOCUS-TOXSWA, in contrast, model the degradation mechanisms as a bulk process and use an overall rate coefficient to describe the combined effects of various degradation reactions in each compartment. Like VVWM, they assume that the processes follow first-order kinetics. The degradation rate constant is adjusted with the temperature of the modeled water body. A similar adjustment is also performed by VVWM for the metabolism rate constant. The temperature adjustment doubles the rate constant for every 10 °C rise in temperature and halves the rate for every 10 °C decrease. Both VVWM and FOCUS-TOXSWA (version 4.4.2 or higher) (24) are capable of simulating the formation and transformation of degradates in the water body. This feature, however, is not available in AGRO-2014, which is only able to handle the transport and fate of a degradate that enters the water body via inflow. The degradate formation scheme, supported by FOCUS-TOXSWA, consists of degradates formed in parallel, in sequence, or by a combination of both while the scheme supported by VVWM is less flexible and only consists of up to two degradates formed in sequence. Both models assume that the formation and transformation of degradates follow first-order kinetics. Since VVWM simulates each degradation mechanism individually, the rate constant for the transformation of the parent compound and the formation of the degradation products is defined separately for each mechanism. In FOCUS-TOXSWA, since the degradation is modeled as a bulk process, there is only one overall rate constant for all degradation reactions in a compartment. The theoretical background of the degradate simulation in FOCUS-TOXSWA and VVWM can be found in Adriaanse et al. (25) and Young (3), respectively. Volatilization is commonly simulated by the three models using first-order kinetics. The overall rate coefficient is determined as a function of Henry’s Law constant (H) and the liquid- and gas-phase resistances. In VVWM, H is approximated based on the vapor pressure, solubility, and molecular weight of the pesticide. The FOCUS-TOXSWA also considers the effect of water body temperature on vapor pressure and solubility. The AGRO-2014 simply uses the user-specified H. The liquid- and gas-phase resistances are assumed to be constant in AGRO-2014, whereas they vary in VVWM and FOCUS-TOXSWA 296

as a function of wind speed, temperature of water body, and pesticide molecular weight. Pesticides are removed from the system via outflow of water, SS, and other sorbing media. The three models differ in the way in which water outflow is determined. Both VVWM and FOCUS-TOXSWA can update the aqueous volume of water compartment as hydrologic conditions (e.g., runoff, precipitation, evaporation, and seepage in both models, and upstream inflow/incoming lateral flow in FOCUS-TOXSWA only) change during every simulation time step. In VVWM, the dynamic water volume varies between zero and a user-specified maximum level. The VVWM can also maintain a constant water volume thus offering three general options—variable volume with flowthrough, constant volume with flowthrough, and constant volume without flowthrough. Overflow, with hydrologic washout of pesticides, occurs if the flowthrough option is on and the newly calculated water volume exceeds the pre-defined constant or maximum level. The FOCUS-TOXSWA maintains a minimum water depth by installing a weir at the outflow end of the water body and updates the water depth based on the water conservation equations and the water depth-discharge relationships considering the impacts of weirs on flow (19). The AGRO-2014, in contrast, assumes a constant water volume with outflow rates equal to inflow rates. Precipitation is considered only for rain dissolution of pesticides but has no effect on water volume. Another major difference between the models is the way in which the concentration of SS in the water compartment is determined. In AGRO-2014, SS concentration is formulated as a dynamic variable that maintains a baseline level but elevates if excess sediments enter the system during runoff events. The excess SS will settle until the SS concentration returns to the baseline level. The model defines a term—the 90% sediment clearance time—to describe the settling of the excess SS and represent the residence time in the water compartment. With the sedimentation of excess SS, the mass transfer coefficients for sediment burial, settling, and resuspension are adjusted accordingly. In VVWM and FOCUS-TOXSWA, the concentration of SS is assumed to be invariant. However, due to the variable water volume, additional SS mass would be added to the system as the water volume increases. This portion of SS does not contain pesticides but will become available for sorption immediately resulting in redistribution of the pesticides in the water compartment. Consequently, the concentration of pesticides dissolved in pure water will decrease as a portion of pesticides adsorbs to additional SS. Pesticides sorbed to the benthic particles can also be removed via sediment burial (i.e., chemical burial in deep bed sediment). Both VVWM and AGRO-2014 include this process as one of the fates of pesticides in the sediment compartment. The FOCUS-TOXSWA, however, does not account for the sediment burial component.

297

Data Requirements and Availability Table 2 illustrates the comparison of key input parameters required by the three models to simulate processes described in the previous sections. The physicochemical properties and environmental fate (e-fate) of a pesticide make up an important group of input parameters. Some parameters are readily available per pesticide registration as required by the USEPA in 40 Code of Federal Regulations (CFR) Part 158. The CDPR has a data requirement substantially similar to the USEPA (26). For a model to be practical for registration evaluation, it is critical that the input data required by the model also be required by USEPA and readily submitted to the CDPR. Among the three models, VVWM is the only one that is well-suited to use the USEPA-required data. The other two models, in contrast, use additional data. Note that the USEPA only requires identification of major degradates (i.e., degradates formed at greater than or equal to 10% of the amount of the applied parent compound) upon registration. Physicochemical and e-fate data of degradates are not required. Another category of input parameter includes those associated with the mechanistic processes being modeled. The value of these parameters is usually suggested by model developers but can also be modified by users if needed. Parameters in this group mainly pertain to the mass transfer between the water and sediment compartments. The VVWM uses a generic mass transfer coefficient to govern this process. The term is empirically set on the order of 10-8 m s-1 for lakes, ponds, and other standing water bodies based on various sources, as suggested by model developers (3, 27). The AGRO-2014 requires several variables, whose value is suggested by model developers, but should be verified by users. This requires model users to have adequate knowledge and field information to parameterize the model. Similarly, FOCUS-TOXSWA requires users to verify the reference diffusion velocity.

298

Table 2. Comparison of Key Input Parameters Required by the Three Models

299

Model Selection for Pesticide Registration Evaluation in California The review of modeling methodology and data requirements identified features and limitations of the three models. The VVWM shows a promising capability of being a tool for pesticide registration evaluation as needed by SWPP. Compared to AGRO-2014 and FOCUS-TOXSWA, VVWM considers the most complete list of processes associated with the fate of pesticides in receiving water bodies and better represents degradation, sorption, and the formation and transformation of degradates. It also enables a practical, versatile approach to simulate the mass transfer between the water and sediment compartments and requires the least effort for model parameterization. Although a more explicit method is presented by AGRO-2014 to simulate the water-sediment mass transfer with the dynamic sedimentation scheme, this model also requires users to have adequate knowledge and field information (which is subject to data availability and can be highly uncertain and site-specific) to take advantage of this feature. It is worth pointing out that AGRO-2014 models the concentration of SS as a dynamic variable that varies as a function of excess SS in the water compartment. Alternatively, VVWM (and FOCUS-TOXSWA) assumes a constant SS concentration while providing the flexibility for users to change the value based on field conditions. The VVWM method is reasonable for regulatory purposes because: (i) for evaluation of pesticides with a low to intermediate partition coefficient, the assumption of constant SS concentration has little impact on model output since the partitioning to SS and other sorbing media is usually insignificant (3); and (ii) for evaluation of those with an extremely high partition coefficient, it is possible to improve the prediction of partitioning by varying the SS concentration and other relevant parameters (e.g., PRBEN in VVWM) without revising the model structure (28). Additionally, in terms of data requirements, VVWM is well-suited to use the pesticide physicochemical and e-fate data required by the USEPA for federal pesticide registration and readily available to the CDPR, while AGRO-2014 and FOCUS-TOXSWA require additional data.

Scenario Assessment Standard Receiving Water Body Scenarios The USEPA pond scenario, which was derived from agricultural ponds commonly observed in Georgia, is recommended by the USEPA/OPP as a standard scenario for aquatic risk assessments in the United States (3). The scenario assumes that a 10-ha field treated with pesticides empties into a 1-ha × 2-m static pond. Dimensions and physicochemical properties of the pond have been included in VVWM as default input values. The USEPA pond is also the default modeling scenario used in AGRO-2014. One exception is that, due to the dynamic sedimentation scheme, SS concentration in the pond is a dynamic variable with a baseline level of 30 mg L-1 instead of a constant. Similarly, there are three standard receiving water body scenarios proposed by FOCUS—the FOCUS pond, ditch, and stream. The FOCUS scenarios were developed based on common characteristics shared by various receiving water bodies in pre-selected 300

geographic sites in European countries (17, 18). The FOCUS pond assumes a circular 4,500-m2 field treated with pesticides draining into a 900-m2 × 1-m pond. The FOCUS ditch and stream is a 1-m × 100-m water body with average water depths of 0.3 and 0.3–0.5 m, respectively. The FOCUS ditch and stream scenarios also involve an upstream catchment, which contributes baseflow, runoff, drainage, and pesticides (if treated) to the receiving water body. Physicochemical properties of FOCUS water bodies are slightly different from that of the USEPA pond. As an example, for the USEPA pond and FOCUS water bodies, the concentrations of SS are 30 and 15 mg L-1, porosity values of bottom sediment are 0.5 and 0.6, bulk densities of bottom sediments are 1.35 and 0.8 kg L-1, and fractions of OC are 0.04 and 0.05, respectively. Application of the USEPA Pond to California In this assessment, we focus on the evaluation of the USEPA pond. This scenario has been widely used for aquatic risk assessment at national and regional scales in the United States. However, since it was developed based on areas where the conditions of receiving water bodies may substantially differ from those in California, it is important to evaluate its relevance to conditions in California and determine whether it is an appropriate scenario for use by SWPP for pesticide registration evaluation. For aquatic risk assessments, the scenario is typically used to configure the VVWM or EXAMS model, which (in conjunction with PRZM) provides predictions of EECs in the water column and benthic region on a daily basis for a 30-year (1961-1990) simulation. The relevance of the USEPA pond to California conditions can be assessed by comparing model results to monitoring data collected in California’s receiving water bodies. To ensure the protectiveness of the regulatory modeling, model results are intended to be conservative, with simulated EECs at the higher end of concentrations occurring in the real-world settings (29, 30). We followed the model evaluation criteria used by the USEPA (31) and SWPP (32) and considered model predictions to be relevant and applicable to California if the simulated peak EEC was reasonably greater than the maximum field measured concentration. Figure 2 shows a comparison of water column concentrations between model prediction and field measurement for 18 pesticides. Model results were mostly derived from the USEPA’s series studies for “Effects determination for the California red-legged frog and other California listed species (33),” which reported model predictions of EECs in the USEPA pond based on various California-specific pesticide application scenarios. The studies involved model results of more than 90 pesticides. Seventeen of these pesticides were selected by SWPP based on the priority ranking of use amount in California and their level of ecotoxicity (34, 35). Since the study did not evaluate imidacloprid, a highly used pesticide in California with high ecotoxicity, model results for this pesticide were derived separately from a USEPA risk assessment report, which reported simulated EECs based on a whole range of pesticide application scenarios in California and other states (36). The selected pesticides represented a wide range of physicochemical and e-fate properties. For each pesticide, the maximum for the predicted peak EECs over the evaluated pesticide application scenarios specific 301

to California was compared to the top three highest concentrations reported in the CDPR’s Surface Water Database from 1990–2017 (37).

Figure 2. Comparison between the model results based on the USEPA pond and the surface water monitoring data in California. References for the USEPA risk assessment: A = bifenthrin (38); B = deltamethrin (39); C = cyfluthrin (40); D = lambda-cyhalothrin (41); E = permethrin (42); F = trifluralin (43); G = imidacloprid (36); H = propargite (44); I = chlorpyrifos (45); J = oxyfluorfen (46); K = methomyl (47); L = malathion (48); M = simazine (49); N = oryzalin (50); O = carbaryl (51); P = bensulide (52, 53); Q = diazinon (54); R = diuron (55). As shown in Figure 2, the simulated peak water column EEC for most pesticides is greater than the top three monitoring concentrations in California (i.e., points are below the 1:1 line). For bifenthrin, deltamethrin, cyfluthrin, and permethrin, although the simulated peak EEC is significantly smaller than some of the top three highest concentrations, both the simulated and observed concentrations are above the solubility limit of the chemical (i.e., 0.014, 0.2, 2.32, and 5.5 µg/L, respectively). Note that due to the conservative configuration, it is possible that some model-predicted EECs may exceed the solubility limit. In these circumstances, the USEPA suggested that the modeled EEC should be adjusted to the limit of solubility and the exposure assessment should focus on concentrations in bed sediments (31). Among the four pesticides that have a predicted EEC above the limit of solubility, only bifenthrin and deltamethrin were reported to have peak EECs in sediment (on the organic carbon-, or OC- normalized basis), which were 39,200 and 93,800 µg/kg[OC], respectively. These totals were both greater than 302

the highest detected sediment concentrations in California—21,150 and 13,322 µg/kg[OC] for bifenthrin and deltamethrin, respectively. The comparison shows that peak EECs predicted based on the USEPA pond are generally above the highest measured concentrations in California, signifying that the USEPA pond was suitable for pesticide registration evaluation based on California conditions. Except for imidacloprid, exposures to other pesticides shown in Figure 2 were evaluated by using PRZM-EXAMS with the USEPA pond, rather than PRZM-VVWM. However, model testing shows that VVWM has an excellent compatibility with EXAMS when simulating static water bodies (e.g., the USEPA pond) (3). The EECs predicted from PRZM-EXAMS are thus comparative to those from PRZM-VVWM. The findings in Figure 2 are further confirmed by another study where the PRZM-VVWM with the USEPA pond was explicitly evaluated for its ability to generate a conservative representation of pesticide exposures in California (56). The study shows that the modeled EECs well capture the worst-case monitoring data observed in California’s agricultural receiving water bodies and confirms that the model results generated from PRZM-VVWM with the USEPA pond are protective for the regulatory screening-level exposure assessment in California’s agricultural settings.

Conclusions Modeling aquatic exposures to pesticides is an essential component of ecological risk assessment. The CDPR/SWPP is refining the modeling methodology for the aquatic risk assessment of pesticide products submitted for registration in California. One major refinement is to develop a receiving water body model that is configured to provide a conservative estimate of aquatic exposures to pesticides in California’s receiving water bodies. There are three receiving water body models that are specially designed for the regulatory aquatic risk assessment: VVWM, AGRO-2014, and FOCUS-TOXSWA. The conceptual model, modeling methodology, and data requirements of the three models were reviewed and compared with features and limitations of each model identified. SWPP concluded that VVWM was a promising tool for support of pesticide registration evaluation in California. The model thoroughly simulates processes associated with fates of pesticides in a receiving water body and is well-suited to use pesticide physicochemical and e-fate data that are currently required by the USEPA for pesticide registration and readily available to the CDPR. For aquatic risk assessments in evaluating pesticides for use registration, proper configuration of the receiving water body scenario is vital to ensure the scientific rigor and protectiveness required by regulations. It is critical to develop a standard receiving water body scenario that can represent the worst-case aquatic exposures to pesticides. The USEPA pond and FOCUS receiving water body scenarios (i.e., FOCUS pond, ditch, and stream) provide various ways to configure the receiving water body model. The USEPA pond, a scenario derived from Georgian farm ponds, and recommended by the USEPA as the standard scenario for the nationwide aquatic risk assessment in the United States, was evaluated to determine its relevance to California conditions. Modeled EECs predicted 303

by using the USEPA pond in PRZM-VVWM (or EXAMS) were reasonably greater than the worst-case concentrations measured in California’s receiving water bodies, indicating that model results were able to provide a worst-case yet realistic representation of pesticide aquatic exposures in California.

Acknowledgments The authors would like to acknowledge Xuyang Zhang and Xin Deng from the CDPR for valuable discussions and comments in the initialization and development of this study. We are grateful to Dirk Young (USEPA) for instructions on aquatic models. We also sincerely thank the editors and anonymous reviewers for critical reviews.

References 1.

Holvoet, K. M.; Seuntjens, P.; Vanrolleghem, P. A. Monitoring and modeling pesticide fate in surface waters at the catchment scale. Ecol. Modell. 2007, 209 (1), 53–64. 2. Williams, P. R.; Hubbell, B. J.; Weber, E.; Fehrenbacher, C.; Hrdy, D.; Zartarian, V. An overview of exposure assessment models used by the US Environmental Protection Agency. In Modelling of Pollutants in Complex Environmental Systems; Hanrahan, G., Ed.; 2010; Vol. 2, pp 61-131. 3. Young, D. F. The Variable Volume Water Model, Revision A (USEPA/OPP 734S16002); U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, 2016. 4. Burns, L. A. Exposure Analysis Modeling System (EXAMS) User Manual and System Documentation (US EPA/600/R-00/081); U.S. Environmental Protection Agency, Research Triangle Park, NC, 2000. 5. Arnot, J.; Gouin, T.; Mackay, D. Development and Application of Models of Chemical Fate in Canada: Practical Methods for Estimating Environmental Biodegradation Rates; Canadian Environmental Modelling Network, Trent University, Peterborough, Ontario, Canada, 2005. 6. Arnot, J. A.; Gobas, F. A. A food web bioaccumulation model for organic chemicals in aquatic ecosystems. Environ. Toxicol. Chem. 2004, 23 (10), 2343–2355. 7. CEMC. User’s Guide for CEMC_SFU_AGRO v1.2: The Combined Canadian Environmental Modelling Centre Water Quality Model and the Simon Fraser University Food Web Model; The Canadian Environmental Modelling Centre, Ontario, Canada, 2007. 8. Mackay, D. Multimedia Environmental Models: The Fugacity Approach; CRC Press, 2001. 9. Padilla, L. E.; Winchell, M. F.; Jackson, S. H. Evaluation of AGRO-2014 for predicting hydrophobic organic chemical concentrations in ponds. J. Environ. Qual. 2015, 44 (5), 1568–1578. 10. SAP A Set of Scientific Issues Being Considered by the Environmental Protection Agency Regarding Selected Issues Associated with the Risk 304

11.

12.

13. 14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

Assessment Process for Pesticides with Persistent, Bioaccumulative, and Toxic Characteristics; FIFRA Scientific Advisory Panel (SAP) Minutes No. 2009-01: Washington, DC, 2008. Adriaanse, P. Fate of Pesticides in Field Ditches: The TOXSWA Simulation Model; Report 90; DLO Winand Staring Centre for Integrated Land, Soil and Water Research. Wageningen, The Netherlands, 1996. Young, D. F.; Fry, M. M. PRZM5 A Model for Predicting Pesticide in Runoff, Erosion, and Leachate: User Manual; U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, 2014. Young, D. Pesticide in Water Calculator User Manual (version 1.52); U.S. Environmental Proteciton Agency, Washington, DC, 2015. Van den Berg, F.; Adriaanse, P. I.; Roller, J. A. t.; Vulto, V. C.; Groenwold, J. G. Surface WAter Scenarios Help (SWASH) Manual 2.1. User’s Guide Version 2; Werkdocument 83; Wageningen, The Netherlands, 2008. Roller, J. A. t.; Van den Berg, F.; Adriaanse, P. I. Surface WAter Scenarios Help (SWASH) Version 2.0. Technical Documentation Version 1.3; Alterrarapport 508; Wageningen, Alterra Green World Research, The Netherlands, 2003. Van den Berg, F.; Adriaanse, P. I.; Roller, J. A. t. Surface WAter Scenarios Help (SWASH) Version 2.0. User’s Guide Version 1.3; Alterra-rapport 507; Wageningen, Alterra Green World Research, The Netherlands, 2003. FOCUS Generic Guidance for FOCUS Surface Water Scenarios Version 1.4: Report of the FOCUS Working Group on Surface Water Scenarios; FOCUS Surface Water Scenarios Workgroup, Brussels, Belgium, 2015. Linders, J.; Adriaanse, P.; Allen, R.; Capri, E.; Gouy, V.; Hollis, J.; Jarvis, N.; Klein, M.; Lolos, P.; Maier, W. FOCUS Surface Water Scenarios in the EU Evaluation Process under 91/414/EEC; Sanco/4802/2001-rev vol 2; FOCUS, Brussels, Belgium, 2003. Adriaanse, P.; Beltman, W. Transient Water Flow in the TOXSWA Model (FOCUS) Versions: Concepts and Mathematical Description; Wettelijke Onderzoekstaken Natuur & Milieu, Wageningen, 2009. USEPA. Methods for Collection, Storage and Manipulation of Sediments for Chemical and Toxicological analyses: Technical Manual (EPA-823-B-01002); U.S. Environmental Protection Agency, Office of Water, Washington, DC, 2001. Mackay, D.; Joy, M.; Paterson, S. A Quantitative Water, Air, Sediment Interaction (QWASI) fugacity model for describing the fate of chemicals in lakes. Chemosphere 1983, 12 (7), 981–997. Adriaanse, P. I. Extended summary SCI pesticides group meeting ecotoxicology of organic compounds in the aquatic environment. Pestic. Sci. 1997, 49 (2), 210–212. Xie, Y. Report 293 Part I: Developing a California-Based Receiving Waterbody Model for Pesticide Product Registration Evaluation: Review of Model Theory; California Department of Pesticide Regulation, Sacramento, CA, 2016.

305

24. Beltman, W.; ter Horst, M.; Adriaanse, P.; de Jong, A.; Deneer, J. W. FOCUS-TOXSWA Manual 4.4. 2: User’s Guide Version 4; Wettelijke Onderzoekstaken Natuur & Milieu, Wageningen, 2014. 25. Adriaanse, P.; Beltman, W.; van den Berg, F. Metabolite Formation in Water and in Sediment in the TOXSWA Model: Theory and Procedure for the Upstream Catchment of FOCUS Streams; Alterra Wageningen UR, 2014. 26. CDPR. California Department of Pesticide Regulation The Pesticide Registration Branch Desk Manual; California Department of Pesticide Regulation, Sacramento, CA, 2013. 27. Luo, Y. Report 263: Review and Evaluation of Pesticide Modeling Approaches in Rice Paddies; California Department of Pesticide Regulation, Sacramento, CA, 2011. 28. USEPA. White Paper on Methods for Assessing Ecological Risks of Pesticides with Persistent, Bioaccumulative and Toxic Characteristics Submitted to the FIFRA Scientific Advisory Panel for Review and Comment (Rep. EPA-HQ-OPP-2008-0550-0003); U.S. Environmental Protection Agency Office of Pesticide Programs, Washington, DC, 2008. 29. Knäbel, A.; Stehle, S.; Schäfer, R. B.; Schulz, R. Regulatory FOCUS surface water models fail to predict insecticide concentrations in the field. Environ. Sci. Technol. 2012, 46 (15), 8397–8404. 30. USEPA. Evaluation and Use of Monitoring Data in Pesticide Aquatic Exposure Assessment; U.S. Environmental Protection Agency Office of Pesticide Programs, Washington, DC, 2014. 31. USEPA. Preliminary Comparative Environmental Fate and Ecological Risk Assessment for the Registration Review of Eight Synthetic Pyrethroids and the Pyrethrins (EPA-HQ-OPP-2010-0384-0045); U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, 2016. 32. Luo, Y. Methodology for Evaluating Pesticides for Surface Water Protection III. Module for Urban Scenario; California Department of Pesticide Regulation, Sacramento, CA, 2014. 33. USEPA. Effects Determinations for the California Red-Legged Frog and Other California Listed Species; U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, 2013. 34. Luo, Y.; Deng, X.; Budd, R.; Starner, K.; Ensminger, M. Methodology for Prioritizing Pesticides for Surface Water Monitoring in Agricultural and Urban Areas; California Department of Pesticide Regulation, Sacramento, CA, 2013. 35. Luo, Y.; Ensminger, M.; Budd, R.; Deng, X.; DaSilva, A. Methodology for Prioritizing Pesticides for Surface Water Monitoring in Agricultural and Urban Areas II: Refined Priority List; California Department of Pesticide Regulation, Sacramento, CA, 2014. 36. USEPA. Preliminary Aquatic Risk Assessment to Support the Registration Review of Imidacloprid (EPA-HQ-OPP-2008-0844-1086); U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, 2016. 37. CDPR Surface Water Monitoring Database. http://www.cdpr.ca.gov/docs/ emon/surfwtr/surfdata.htm accessed August 10, 2017). 306

38. USEPA. Effects Determination for Bifenthrin and the Bay Checkerspot Butterfly, Valley Elderberry Longhorn Beetle, California Tiger Salamander, Delta Smelt, California Clapper Rail, California Freshwater Shrimp, San Francisco Garter Snake, and Tidewater Goby; U.S. Environmental Protection Agency, Washington, DC, 2012. 39. USEPA. Effects Determination for Deltamethrin and the Bay Checkerspot Butterfly, Valley Elderberry Longhorn Beetle, California Tiger Salamander, Delta Smelt, California Clapper Rail, California Freshwater Shrimp, San Francisco Garter Snake, and Tidewater Goby; U.S. Environmental Protection Agency, Washington, DC, 2013. 40. USEPA. Effects Determination for Cyfluthrin and Beta-Cyfluthrin and the Federally Threatened Bay Checkerspot Butterfly, Valley Elderberry Longhorn Beetle, California Tiger Salamander, Central California Distinct Population Segment, and Delta Smelt, and the Federally Endangered California Clapper Rail, California Freshwater Shrimp, California Tiger Salamander, San Francisco Garter Snake, and Tidewater Goby; U.S. Environmental Protection Agency, Washington, DC, 2013. 41. USEPA. Effects Determination for Lambda-Cyhalothrin and the Bay Checkerspot Butterfly, Valley Elderberry Longhorn Beetle, California Tiger Salamander, Delta Smelt, California Clapper Rail, California Freshwater Shrimp, San Francisco Garter Snake, and Tidewater Goby; U.S. Environmental Protection Agency, Washington, DC, 2012. 42. USEPA. Risks of Permethrin Use to the Federally Threatened California Red-Legged Frog and Bay Checkerspot Butterfly, and the Federally Endangered California Clapper Rail, Salt Marsh Harvest Mouse, and San Francisco Garter Snake; U.S. Environmental Protection Agency, Washington, DC, 2008. 43. USEPA. Risks of Trifluralin Use to the Federally Listed California Red-Legged Frog, Delta Smelt, San Francisco Garter Snake and San Joaquin Kit Fox; U.S. Environmental Protection Agency, Washington, DC, 2009. 44. USEPA. Risks of Propargite Use to Federally Threatened California Red-Legged Frog; U.S. Environmental Protection Agency, Washington, DC, 2008. 45. USEPA. Risks of Chlorpyrifos Use to Federally Threatened and Endangered California Red-Legged Frog, California Tiger Salamander, San Francisco Garter Sanke, California Clapper Rail, Salt Marsh Harvest Mouse, Bay Checkerspot Butterfly, Valley Elderberry Longhorn Beetle, San Joaquin Kit Fox, California Freshwater Shrimp, and Delta Smelt; U.S. Environmental Protection Agency, Washington, DC, 2009. 46. USEPA. Risks of Oxyfluorfen Use to the Federally Threatened California Red-Legged Frog; U.S. Environmental Protection Agency, Washington, DC, 2008. 47. USEPA. Effects Determination for Methomyl and the Bay Checkerspot Butterfly, Valley Elderberry Longhorn Beetle, California Clapper Rail, California Freshwater Shrimp, California Tiger Salamander, San Francisco 307

48.

49. 50.

51. 52. 53.

54.

55. 56.

Garter Snake, Delta Smelt, and Tidewater Goby; U.S. Environmental Protection Agency, Washington, DC, 2012. USEPA. Risk of Malathion Use to the Federally Threatened Delta Smelt and California Tiger Salamander, Central California District Population Segment, and the Federally Endangered California Tiger Salamander; U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, 2010. USEPA. Risks of Simazine Use to Federally Threatened Delta Smelt; U.S. Environmental Protection Agency, Washington, DC, 2010. USEPA. Risks of Oryzalin Use to the Federally Threatened and Endangered California Tiger Salamander; U.S. Environmental Protection Agency, Washington, DC. 2010. USEPA. Risks of Carbaryl Use to Federally Threatened Delta Smelt; U.S. Environmental Protection Agency, Washington, DC, 2010. USEPA. Effects Determination for Bensulide and the California Red-Legged Frog U.S. Environmental Protection Agency, Washington, DC, 2007. USEPA. Effects Determination for Bensulide and the Bay Checkerspot Butterfly, California Clapper Rail, California Freshwater Shrimp, California Tiger Salamander, Delta Smelt, San Francisco Garter Snake, Tidewater Goby, and Valley Elderberry Longhorn Beetle; U.S. Environmental Protection Agency, Washington, DC, 2012. USEPA. Risks of Diazinon Use to Federally Threathened Delta Smelt and the Federally Endangered Tidewater Goby; U.S. Environmental Protection Agency, Washington, DC, 2012. USEPA. Risks of Diuron Use to Federally Threatened California Red-Legged Frog; U.S. Environmental Protection Agency, Washington, DC, 2009. Xie, Y.; Luo, Y.; Singhasemanon, N.; Goh, K. Regulatory modeling of pesticide aquatic exposures in California’s agricultural receiving waters. J. Environ. Qual. 2018, DOI: 10.2134/jeq2018.05.0198.

308