Wesley W. Stone

Pesticides in U.S. streams and rivers: occurrence and trends during 1992-2011.

During the 20 years from 1992 to 2011, pesticides were found at concentrations that exceeded aquatic-life benchmarks in many rivers and streams that drain agricultural, urban, and mixed-land use watersheds. Overall, the proportions of assessed streams with one or more pesticides that exceeded an aquatic-life benchmark were very similar between the two decades for agricultural (69% during 1992-2001 compared to 61% during 2002-2011) and mixed-land-use streams (45% compared to 46%). Urban streams, in contrast, increased from 53% during 1992-2011 to 90% during 2002-2011, largely because of fipronil and dichlorvos. The potential for adverse effects on aquatic life is likely greater than these results indicate because potentially important pesticide compounds were not included in the assessment. Human-health benchmarks were much less frequently exceeded, and during 2002-2011, only one agricultural stream and no urban or mixed-land-use streams exceeded human-health benchmarks for any of the measured pesticides. Widespread trends in pesticide concentrations, some downward and some upward, occurred in response to shifts in use patterns primarily driven by regulatory changes and introductions of new pesticides.

Pesticide Toxicity Index--a tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms.

Pesticide mixtures are common in streams with agricultural or urban influence in the watershed. The Pesticide Toxicity Index (PTI) is a screening tool to assess potential aquatic toxicity of complex pesticide mixtures by combining measures of pesticide exposure and acute toxicity in an additive toxic-unit model. The PTI is determined separately for fish, cladocerans, and benthic invertebrates. This study expands the number of pesticides and degradates included in previous editions of the PTI from 124 to 492 pesticides and degradates, and includes two types of PTI for use in different applications, depending on study objectives. The Median-PTI was calculated from median toxicity values for individual pesticides, so is robust to outliers and is appropriate for comparing relative potential toxicity among samples, sites, or pesticides. The Sensitive-PTI uses the 5th percentile of available toxicity values, so is a more sensitive screening-level indicator of potential toxicity. PTI predictions of toxicity in environmental samples were tested using data aggregated from published field studies that measured pesticide concentrations and toxicity to Ceriodaphnia dubia in ambient stream water. C. dubia survival was reduced to ≤50% of controls in 44% of samples with Median-PTI values of 0.1-1, and to 0% in 96% of samples with Median-PTI values >1. The PTI is a relative, but quantitative, indicator of potential toxicity that can be used to evaluate relationships between pesticide exposure and biological condition.

Estimated annual agricultural pesticide use for counties of the conterminous United States, 1992--2009

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Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States

Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro--ethyl--(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro--(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate that variability in the concentration of atrazine residues (atrazine plus DEA) in groundwater underlying agricultural areas is more strongly controlled by the history of atrazine use in relation to the timing of recharge (groundwater age) than by processes that control the dispersion, adsorption, or degradation of these compounds in the saturated zone. Current (1990s) atrazine use was found to be a weak explanatory variable, perhaps because it does not represent the use of atrazine at the time of recharge of the sampled groundwater and because the likelihood that these compounds will reach the water table is affected by other factors operating within the unsaturated zone, such as soil characteristics, artificial drainage, and water movement. Results show that only about 5% of agricultural areas have greater than a 10% probability of exceeding the USEPA maximum contaminant level of 3.0 μg L. These models are not developed for regulatory purposes but rather can be used to (i) identify areas of potential concern, (ii) provide conservative estimates of the concentrations of atrazine residues in deeper potential drinking water supplies, and (iii) set priorities among areas for future groundwater monitoring.

Watershed Regressions for Pesticides (WARP) Models for Predicting Stream Concentrations of Multiple Pesticides

Watershed Regressions for Pesticides for multiple pesticides (WARP-MP) are statistical models developed to predict concentration statistics for a wide range of pesticides in unmonitored streams. The WARP-MP models use the national atrazine WARP models in conjunction with an adjustment factor for each additional pesticide. The WARP-MP models perform best for pesticides with application timing and methods similar to those used with atrazine. For other pesticides, WARP-MP models tend to overpredict concentration statistics for the model development sites. For WARP and WARP-MP, the less-than-ideal sampling frequency for the model development sites leads to underestimation of the shorter-duration concentration; hence, the WARP models tend to underpredict 4- and 21-d maximum moving-average concentrations, with median errors ranging from 9 to 38% As a result of this sampling bias, pesticides that performed well with the model development sites are expected to have predictions that are biased low for these shorter-duration concentration statistics. The overprediction by WARP-MP apparent for some of the pesticides is variably offset by underestimation of the model development concentration statistics. Of the 112 pesticides used in the WARP-MP application to stream segments nationwide, 25 were predicted to have concentration statistics with a 50% or greater probability of exceeding one or more aquatic life benchmarks in one or more stream segments. Geographically, many of the modeled streams in the Corn Belt Region were predicted to have one or more pesticides that exceeded an aquatic life benchmark during 2009, indicating the potential vulnerability of streams in this region.

Regression models for explaining and predicting concentrations of organochlorine pesticides in fish from streams in the United States

Empirical regression models were developed for estimating concentrations of dieldrin, total chlordane, and total DDT in whole fish from U.S. streams. Models were based on pesticide concentrations measured in whole fish at 648 stream sites nationwide (1992-2001) as part of the U.S. Geological Surveys National Water Quality Assessment Program. Explanatory variables included fish lipid content, estimates (or surrogates) representing historical agricultural and urban sources, watershed characteristics, and geographic location. Models were developed using Tobit regression methods appropriate for data with censoring. Typically, the models explain approximately 50 to 70% of the variability in pesticide concentrations measured in whole fish. The models were used to predict pesticide concentrations in whole fish for streams nationwide using the U.S. Environmental Protection Agencys River Reach File 1 and to estimate the probability that whole-fish concentrations exceed benchmarks for protection of fish-eating wildlife. Predicted concentrations were highest for dieldrin in the Corn Belt, Texas, and scattered urban areas; for total chlordane in the Corn Belt, Texas, the Southeast, and urbanized Northeast; and for total DDT in the Southeast, Texas, California, and urban areas nationwide. The probability of exceeding wildlife benchmarks for dieldrin and chlordane was predicted to be low for most U.S. streams. The probability of exceeding wildlife benchmarks for total DDT is higher but varies depending on the fish taxon and on the benchmark used. Because the models in the present study are based on fish data collected during the 1990s and organochlorine pesticide residues in the environment continue to decline decades after their uses were discontinued, these models may overestimate present-day pesticide concentrations in fish.

Recovery data for surface water, groundwater and lab reagent samples analyzed by the USGS National Water Quality Laboratory schedule 2437, water years 2013-15

Analytical recovery is the concentration of an analyze measured in a water-quality sample expressed as a percentage of the known concentration added to the sample (Mueller and others, 2015). Analytical recovery (hereafter referred to as recovery ) can be used to understand method bias and variability and to assess the temporal changes in a method over time (Martin and others, 2009). This data set includes two tables: one table of field spike recovery data and one table of lab reagent spike recovery data. The table of field spike recovery data includes results from paired environmental and spike samples collected by the National Water Quality Program, National Water-Quality Assessment (NAWQA) Project in surface water and groundwater. These samples were collected as part of the NAWQA Project s National Water Quality Network: Rivers and Streams assessment, Regional Stream Quality Assessment studies and in multiple groundwater networks following standard practices (Mueller and others, 1997). This table includes environmental and spike water-quality sample data stored in the USGS National Water Information System (NWIS) database (https://dx.doi.org/10.5066/F7P55KJN). Concentrations of pesticides in spike samples, while stored in the NWIS database, are not publically available. The calculation of recovery based on these field sample data is outlined in Mueller and others (2015). Lab reagent spikes are pesticide-free reagent water spiked with a known concentration of pesticide. Lab reagent spikes are prepared in the lab and their recovery can be directly measured. The table of lab reagent spike data contains quality control sample information stored in the USGS National Water Quality Laboratory (NWQL) database. Both tables include fields for data-quality indicators that are described in the data processing steps of this metadata file. These tables were developed in order to support a USGS Scientific Investigations Report with the working title Considerations for the Preparation of Pesticide Data Analyzed with National Water Quality Laboratory Schedule 2437 Martin, J.D., Stone, W.W, Wydoski, D.S., and Sandstrom, M.W., 2009, Adjustment of pesticide concentrations for temporal changes in analytical recovery, 1992 2006: U.S. Geological Survey Scientific Investigations Report 2009 5189, 23 p. plus appendixes. Mueller, D.K., Schertz, T.L., Martin, J.D., and Sandstrom, M.W., 2015, Design, analysis, and interpretation of field quality-control data for water-sampling projects: U.S. Geological Survey Techniques and Methods, book 4, chap. C4, 54 p., https://dx.doi.org/10.3133/tm4C4. Mueller, D.K., Martin, J.D. and Lopes, T.J., 1997, Quality-Control Design for Surface-Water Sampling in the National Water-Quality Assessment Program: U.S. Geological Survey Open-File Report 97-223, 8 p. plus appendixes.

Corrigendum to “Pesticide Toxicity Index—A tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms” [Sci. Total Environ. 476–477 (2014) 144–157]

https://doi.org/10.1016/j.scitotenv.2013.12.088 Refers to: L.H. Nowell, J.E. Norman, P.W. Moran, J.D. Martin, W.W. Stone. Pesticide Toxicity Index—A tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms. Science of the Total Environment, Volume 476–477, 1 April 2014, Pages 144–157. The authors regret that in the above published article, an error appeared in one sentence of the text and is corrected below. In Section

Prediction of Pesticide Toxicity in Midwest Streams

The occurrence of pesticide mixtures is common in stream waters of the United States, and the impact of multiple compounds on aquatic organisms is not well understood. Watershed Regressions for Pesticides (WARP) models were developed to predict Pesticide Toxicity Index (PTI) values in unmonitored streams in the Midwest and are referred to as WARP-PTI models. The PTI is a tool for assessing the relative toxicity of pesticide mixtures to fish, benthic invertebrates, and cladocera in stream water. One hundred stream sites in the Midwest were sampled weekly in May through August 2013, and the highest calculated PTI for each site was used as the WARP-PTI model response variable. Watershed characteristics that represent pesticide sources and transport were used as the WARP-PTI model explanatory variables. Three WARP-PTI models-fish, benthic invertebrates, and cladocera-were developed that include watershed characteristics describing toxicity-weighted agricultural use intensity, land use, agricultural management practices, soil properties, precipitation, and hydrologic properties. The models explained between 41 and 48% of the variability in the measured PTI values. WARP-PTI model evaluation with independent data showed reasonable performance with no clear bias. The models were applied to streams in the Midwest to demonstrate extrapolation for a regional assessment to indicate vulnerable streams and to guide more intensive monitoring.