Recent Publications
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Abstract
Conceptually, imagine a vice where on one end there is demand for urban expansion (roads, buildings, industry/commerce, neighborhoods, etc.), on the other end there is societal demand for conservation (“listed” species protections, rewilding of farmlands, mitigations, etc.), and in the middle, being increasingly squeezed, exists the agricultural landscape of America. Conceptually, you can frame the shrinking land challenge. America’s farmland is shrinking while the urban landscape is expanding, and calls for preservation are growing increasingly louder. Land is finite, and once crops are converted to concrete the land is irrevocably changed. Technology has manifested an abundance of food; however, technology (e.g., genetically modified crops, pesticides, fertilizers, etc.) is also experiencing enhanced scrutiny as the frontier of agriculture inevitably converges with the aspirational boundaries of conservation. Unfortunately, few people are aware of the delicate policy intersection of food security, conservation, and population growth. Here we feature this conceptual challenge to provoke necessary discussion and debate.
Abstract
For pesticide registrations in the USA under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), as implemented by the United States Environ-mental Protection Agency, drinking water risk assess-ments for groundwater sources are based on standard scenario modeling concentration estimates. The con-ceptual model for the drinking water protection goals is defined in terms of (1) a rural well in or near a rela-tively high pesticide use area, a shallow well (4–10m); (2) long-term, single-station weather data; (3) soils characterized as highly leachable; (4) upper-end or sur-rogate, worst-case environmental fate parameters; and (5) maximum, annual use rates repeated every year. To date, monitoring data have not been quantitatively incorporated into FIFRA drinking water risk assessment; even though considerable, US national-scale temporal and spatial data for some chemistries exists. Investigations into drinking water monitoring data development have historically focused on single-source efforts that may not represent wide geographies and/or time periods, whereas Safe Drinking Water Act groundwater monitoring data are focused on a communitylevel scale rather than an individual, shallow, rural well. In the current case study, US national-scale, rural well data for the herbicide atrazine was collected, quality controlled, and combined into a single database from mixed sources (termed the atrazine rural well database) to (1) characterize differences between exposure estimates from standard EPA modeling approaches for specific characterization, (2) evaluate monitoring data toward direct use in US drinking water risk assessments to compliment or supersede standard modeling approaches to define risk, and (3) evaluate monitoring trends a function of time relative to label changes implemented as part of the registration review process. Of the 75,665 drinking water samples collected from groundwater, atrazine was only detected in 3185, a 4% detection rate.
Abstract
Inclusion of pesticide monitoring data in pesticide risk assessment is important yet challenging for several reasons, including infrequent or irregular data collection, disparate sources procedures and associated monitoring periods, and interpretation of the data itself in a policy context. These challenges alone, left unaddressed, will likely introduce unintentional and unforeseen risk assessment conclusions. While individual water quality monitoring programs report standard operating procedures and quality control practices for their own data, cross-checking data for duplicated data from one database to another does not routinely occur. Consequently, we developed a novel quality control and assurance methodology to identify errors and duplicated records toward creating an aggregated, single pesticide database toward use in ecological risk assessment. This methodology includes (1) standardization and reformatting practices, (2) data error and duplicate record identification protocols, (3) missing or inconsistent limit of detection and quantification reporting, and (4) site metadata scoring and ranking procedures to flag likely duplicate records. We applied this methodology to develop an aggregated (multiple-source), national-scale database for atrazine from a diverse set of surface water monitoring programs. The resultant database resolved and/or removed approximately 31% of the total ~ 385,000 records that were due to duplicated records. Identification of sample replicates was also developed. While the quality control and assurances methodologies developed in this work were applied to atrazine, they generally demonstrate how a properly constructed and aggregated single pesticide database would benefit from the methods described herein before use in subsequent statistical and data analysis or risk assessment.
Abstract
Tracer dyes are often used as surrogates to characterize pesticide spray drift and it is assumed that they accurately reflect analytical measurement of active ingredients; however, the validity of this assumption remains inconclusive. Consequently, the influence of measurement technique on the magnitude of deposition of spray drift was investigated using spray drift samples evaluated by traditional analytical techniques (HPLC–MS/MS) and fluorimetry (1,3,6,8-pyrene-tetra sulfonic acid tetrasodium salt dye tracer). The experiment was conducted in a low-speed wind tunnel under controlled meteorological conditions. The herbicide mesotrione was sprayed through three spray air induction nozzles (anvil deflector flat fan TTI11004; flat fan AI11004; flat fan AIXR11003). Spray drift deposition samples were collected using stainless steel discs pairs placed side by side in the center of the wind tunnel at distances of 5, 10, 20, 30, and 40 ft (1.5, 3.1, 6.1, 9.1, and 12.2 m) from the spray nozzle. The analytical technique determined pesticide concentration on one disc per pair, and the other was evaluated by fluorimetry. The experimental results, analyzed using the linear split-split plot model, revealed that median deposition concentrations were 15% higher using the tracer dye fluorescence method relative to the analytical method, potentially due in part to procedural recovery inefficiencies of the analytical method (the mean overall procedural recovery result and RSD was 87% ± 6.4% (n = 12). This relationship was consistent and held true for the three nozzle types at all distances within the wind tunnel. © 2021 Society of Chemical Industry.
Abstract
Inclusion of pesticide monitoring data in pesticide risk assessment is important yet challenging for several reasons, including infrequent or irregular data collection, disparate sources procedures and associated monitoring periods, and interpretation of the data itself in a policy context. These challenges alone, left unaddressed, will likely introduce unintentional and unforeseen risk assessment conclusions. While individual water quality monitoring programs report standard operating procedures and quality control practices for their own data, cross-checking data for duplicated data from one database to another does not routinely occur. Consequently, we developed a novel quality control and assurance methodology to identify errors and duplicated records toward creating an aggregated, single pesticide database toward use in ecological risk assessment. This methodology includes (1) standardization and reformatting practices, (2) data error and duplicate record identification protocols, (3) missing or inconsistent limit of detection and quantification reporting, and (4) site metadata scoring and ranking procedures to flag likely duplicate records. We applied this methodology to develop an aggregated (multiple-source), national-scale database for atrazine from a diverse set of surface water monitoring programs. The resultant database resolved and/or removed approximately 31% of the total ~ 385,000 records that were due to duplicated records. Identification of sample replicates was also developed. While the quality control and assurances methodologies developed in this work were applied to atrazine, they generally demonstrate how a properly constructed and aggregated single pesticide database would benefit from the methods described herein before use in subsequent statistical and data analysis or risk assessment.
Abstract
A field-scale, spray drift study with atrazine was conducted to simultaneously measure spray drift deposition, airborne interception and corresponding biological effects on two sensitive plant species (cucumber and lettuce). Applications of AAtrex 4L (atrazine) were made using ultra-coarse nozzles (TeeJet TTI11004) under worst-case drift potential conditions of bare soil and high wind speeds (i.e. >10 mph; >16 kph). This study was replicated 4 times, each with two parallel spray swaths (92.5 ft or 28 m per swath) perpendicular to wind direction. Within each replicate application, three sampling lines were used to measure drift deposition (using stainless-steel discs) at distances out to 400 ft (122 m), airborne interception (using stainless-steel rods) at distances out to 75 ft (23 m), and potential direct plant effects at 5, 15, 25, 35, and 45 ft (1.5, 4.6, 7.6, 10.7, and 13.7 m) from the downwind edge of the spray swath. Corresponding upwind control discs and plants were also included in each replicate. Each replicate application targeted steady wind speeds between 10 and 15 mph (16 and 24 kph) within a 30-degree angle of the downwind field orientation. On average, each 10% increase in distance from the spray zone resulted in approximately 14% less ground-deposited atrazine. Between 7 and 41× more atrazine mass was collected from vertical rods (airborne drift), compared to horizontally placed stainless-steel discs (ground deposition). Cucumber and lettuce plants exposed to spray drift were monitored for biological effects over 21 days post-application according to standard protocols. Endpoints of survival, weight (biomass), and shoot length were evaluated by comparing distance groups to up-wind controls. Overall, when trials were combined, the aggregate lowest observable effect distance (LOED) was 5-ft (1.5 m) and the aggregate no observable effects distance (NOED) was 15-ft (4.6 m), with cucumbers affected more than lettuce.