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William E. Asher

Publications and source records attributed to William E. Asher.

4 recordsLinked to original sources
USGS2020

Daily stream samples reveal highly complex pesticide occurrence and potential toxicity to aquatic life

Transient, acutely toxic concentrations of pesticides in streams can go undetected by fixed-interval sampling programs. Here we compare temporal patterns in occurrence of current-use pesticides in daily composite samples to those in weekly composite and weekly discrete samples of surface water from 14 small stream sites. Samples were collected over 10–14 weeks at 7 stream sites in each of the Midwestern and Southeastern United States. Samples were analyzed for over 200 pesticides and degradates by direct aqueous injection liquid chromatography with tandem mass spectrometry. Nearly 2 and 3 times as many unique pesticides were detected in daily samples as in weekly composite and weekly discrete samples, respectively. Based on exceedances of acute-invertebrate benchmarks (AIB) and(or) a Pesticide Toxicity Index (PTI) >1, potential acute-invertebrate toxicity was predicted at 11 of 14 sites from the results for daily composite samples, but was predicted for only 3 sites from weekly composites and for no sites from weekly discrete samples. Insecticides were responsible for most of the potential invertebrate toxicity, occurred transiently, and frequently were missed by the weekly discrete and composite samples. The number of days with benthic-invertebrate PTI ≥0.1 in daily composite samples was inversely related to Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness at the sites. The results of the study indicate that short-term, potentially toxic peaks in pesticides frequently are missed by weekly discrete sampling, and that such peaks may contribute to degradation of invertebrate community condition in small streams. Weekly composite samples underestimated maximum concentrations and potential acute-invertebrate toxicity, but to a lesser degree than weekly discrete samples, and provided a reasonable approximation of the 90th percentile total concentrations of herbicides, insecticides, and fungicides, suggesting that weekly composite sampling may be a compromise between assessment needs and cost.

Science of the Total Environment↗
USGS2006

StreamVOC - A deterministic source-apportionment model to estimate volatile organic compound concentrations in rivers and streams

This report documents the construction and verification of the model, StreamVOC, that estimates (1) the time- and position-dependent concentrations of volatile organic compounds (VOCs) in rivers and streams as well as (2) the source apportionment (SA) of those concentrations. The model considers how different types of sources and loss processes can act together to yield a given observed VOC concentration. Reasons for interest in the relative and absolute contributions of different sources to contaminant concentrations include the need to apportion: (1) the origins for an observed contamination, and (2) the associated human and ecosystem risks. For VOCs, sources of interest include the atmosphere (by absorption), as well as point and nonpoint inflows of VOC-containing water. Loss processes of interest include volatilization to the atmosphere, degradation, and outflows of VOC-containing water from the stream to local ground water. This report presents the details of StreamVOC and compares model output with measured concentrations for eight VOCs found in the Aberjona River at Winchester, Massachusetts. Input data for the model were obtained during a synoptic study of the stream system conducted July 11-13, 2001, as part of the National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey. The input data included a variety of basic stream characteristics (for example, flows, temperature, and VOC concentrations). The StreamVOC concentration results agreed moderately well with the measured concentration data for several VOCs and provided compound-dependent SA estimates as a function of longitudinal distance down the river. For many VOCs, the quality of the agreement between the model-simulated and measured concentrations could be improved by simple adjustments of the model input parameters. In general, this study illustrated: (1) the considerable difficulty of quantifying correctly the locations and magnitudes of ground-water-related sources of contamination in streams; and (2) that model-based estimates of stream VOC concentrations are likely to be most accurate when the major sources are point sources or tributaries where the spatial extent and magnitude of the sources are tightly constrained and easily determined.

Scientific Investigations Report↗
USGS2003

LakeVOC; A Deterministic Model to Estimate Volatile Organic Compound Concentrations in Reservoirs and Lakes

This report documents LakeVOC, a model to estimate volatile organic compound (VOC) concentrations in lakes and reservoirs. LakeVOC represents the lake or reservoir as a two-layer system and estimates VOC concentrations in both the epilimnion and hypolimnion. The air-water flux of a VOC is characterized in LakeVOC in terms of the two-film model of air-water exchange. LakeVOC solves the system of coupled differential equations for the VOC concentration in the epilimnion, the VOC concentration in the hypolimnion, the total mass of the VOC in the lake, the volume of the epilimnion, and the volume of the hypolimnion. A series of nine simulations were conducted to verify LakeVOC representation of mixing, dilution, and gas exchange characteristics in a hypothetical lake, and two additional estimates of lake volume and MTBE concentrations were done in an actual reservoir under environmental conditions. These 11 simulations showed that LakeVOC correctly handled mixing, dilution, and gas exchange. The model also adequately estimated VOC concentrations within the epilimnion in an actual reservoir with daily input parameters. As the parameter-input time scale increased (from daily to weekly to monthly, for example), the differences between the measured-averaged concentrations and the model-estimated concentrations generally increased, especially for the hypolimnion. This may be because as the time scale is increased from daily to weekly to monthly, the averaging of model inputs may cause a loss of detail in the model estimates.

Open-File Report↗