23 research outputs found

    Impacts of Future Climate Variability on Atrazine Accumulation and Transport in Corn Production Areas in the Midwestern United States

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    Atrazine is one of the most prevalent herbicides that has been widely applied to agricultural lands in the U.S. Understanding the transport and accumulation of atrazine in the subsurface under future climate scenarios is essential for future agriculture and water management. Here, we predict atrazine transport and accumulation under an intensive corn production land based on 20 projected global climate model (GCM) realizations, while considering uncertainties of transport parameters. Our study predicted continuous groundwater table declination and atrazine mass accumulation on the study site. We show that atrazine mass accumulation in corn production areas is subject to total precipitation in the atrazine application season, whereas atrazine plume movement is controlled by the sequence of annual precipitation. Atrazine mass transport and accumulation are more sensitive to climate variation on the field sites with low sorption and atrazine degradation rate. Under the extreme condition, the atrazine plume can migrate as far as five meters from the ground surface in only three years. While annual mean precipitation in the Midwestern U.S. is projected to increase in the future, groundwater vulnerability to atrazine and associated water quality impacts may rise in the U.S. Corn Belt, especially in sites with low atrazine degradation and sorption

    Data_Sheet_1_Extraction, analysis, and occurrence of per- and polyfluoroalkyl substances (PFAS) in wastewater and after municipal biosolids land application to determine agricultural loading.docx

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    Given the ubiquitous detection of per- and polyfluoroalkyl substances (PFAS) within numerous soil and water environmental compartments, there is a need for global understanding of current methodologies for extracting water, solids, polar organic chemical integrative samplers (POCIS), and plant tissue for these substances. This study provides details of several current extraction methods, demonstrates the use of POCIS in monitoring these compounds in a wastewater environment, and provides evidence of detectable levels of certain PFAS compounds within Midwestern municipalities and agroecosystems. Validated extraction procedures help characterize occurrence and release of 18 PFAS in a midwestern wastewater treatment plant (WWTP), surface water, runoff after land application of biosolids to agricultural test plots, infiltration into topsoil, and uptake by grain sorghum. Of the compounds measured, 14 PFAS were detected at least at one sampling site or type. The average total (Σ PFAS) dissolved phase time-weighted average (TWA) concentration in wastewater influent, effluent and in the upstream and downstream effluent mixing zone (EMZ) sites in the receiving stream, respectively, were 27.9, 132, 37.7, and 71.4 ng L−1. Long-chain PFAS dominated most of the aqueous compartments, and perfluoroalkyl acids (PFAAs) occurred in the WWTP and receiving surface waters. Total Σ14 PFAS measured in municipal biosolids applied to soils were 22.9 ng g−1 dw with long-chain PFAS comprising 77.5% of the cumulative PFAS mass. Perfluorooctanesulfonic acid (PFOS) was the most abundant compound detected in biosolids at the highest concentration (9.40 ng g−1 dw). Accumulation in WWTP biosolids was estimated to occur at a rate of 72.8 g day−1 dw based on the difference between influent and effluent time weighted average concentrations. PFAS were detected in both surface soil and runoff after land application of biosolids, but also in control plots consistent with background PFAS contamination. PFAS concentrations in surface runoff decreased over time from plots treated with biosolids. These results provide evidence of the introduction of PFAS to agroecosystems from wastewater effluent and land application of biosolids in the Midwest.</p

    sj-docx-1-wmr-10.1177_0734242X211057012 – Supplemental material for Assessment of in situ properties of municipal solid waste with a large-diameter borehole method

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    Supplemental material, sj-docx-1-wmr-10.1177_0734242X211057012 for Assessment of in situ properties of municipal solid waste with a large-diameter borehole method by John Hartwell, M Sina Mousavi, Jongwan Eun and Shannon Bartelt-Hunt in Waste Management & Research</p

    In-use activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks

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    <div><p>The objectives of this study were to quantify real-world activity, fuel use, and emissions for heavy duty diesel roll-off refuse trucks; evaluate the contribution of duty cycles and emissions controls to variability in cycle average fuel use and emission rates; quantify the effect of vehicle weight on fuel use and emission rates; and compare empirical cycle average emission rates with the U.S. Environmental Protection Agency’s MOVES emission factor model predictions. Measurements were made at 1 Hz on six trucks of model years 2005 to 2012, using onboard systems. The trucks traveled 870 miles, had an average speed of 16 mph, and collected 165 tons of trash. The average fuel economy was 4.4 mpg, which is approximately twice previously reported values for residential trash collection trucks. On average, 50% of time is spent idling and about 58% of emissions occur in urban areas. Newer trucks with selective catalytic reduction and diesel particulate filter had NO<sub>x</sub> and PM cycle average emission rates that were 80% lower and 95% lower, respectively, compared to older trucks without. On average, the combined can and trash weight was about 55% of chassis weight. The marginal effect of vehicle weight on fuel use and emissions is highest at low loads and decreases as load increases. Among 36 cycle average rates (6 trucks × 6 cycles), MOVES-predicted values and estimates based on real-world data have similar relative trends. MOVES-predicted CO<sub>2</sub> emissions are similar to those of the real world, while NO<sub>x</sub> and PM emissions are, on average, 43% lower and 300% higher, respectively. The real-world data presented here can be used to estimate benefits of replacing old trucks with new trucks. Further, the data can be used to improve emission inventories and model predictions.</p><p>Implications: <i>In-use measurements of the real-world activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks can be used to improve the accuracy of predictive models, such as MOVES, and emissions inventories. Further, the activity data from this study can be used to generate more representative duty cycles for more accurate chassis dynamometer testing. Comparisons of old and new model year diesel trucks are useful in analyzing the effect of fleet turnover. The analysis of effect of haul weight on fuel use can be used by fleet managers to optimize operations to reduce fuel cost.</i></p></div

    Incubation periods of hamsters intracerebrally inoculated with unbound and soil-bound PrP<sup>Sc</sup>.

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    <p>Incubation periods of hamsters intracerebrally inoculated with unbound and soil-bound PrP<sup>Sc</sup>.</p

    Repeated cycles of drying and wetting alter the resistance of HY PrP<sup>Sc</sup> to digestion with proteinase K.

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    <p>Western blot (A) and quantification (B) of PK digested HY PrP<sup>Sc</sup> alone or adsorbed to soil before (Dry 0) and after 1 (Dry 1) and 10 (Dry 10) serial rounds of drying and wetting. Migration of 29 and 21 kDa molecular weight marker is indicated on the right of the Western blot. Star indicates significant difference (p<0.05; n = 3) between treated and untreated sample.</p

    Repeated cycles of drying and wetting reduced the PMCA conversion efficiency of soil bound HY TME.

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    <p>Western blot (A) and quantification (B) of PMCA amplification (1 round) of HY PrP<sup>Sc</sup> alone or adsorbed to soil before (Dry 0) and after 1 (Dry 1) and 10 (Dry 10) serial rounds of drying and wetting. Migration of 29 and 21 kDa molecular weight marker is indicated on the right of the Western blot. Star indicates significant difference (p<0.05; n = 3) between treated and untreated sample.</p

    Reduced PMCA conversion coefficient of SCL-HY after repeated cycles of drying and wetting.

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    <p>Western blot of PMCA amplification of 10-fold serial dilutions of standardized SCL-HY PrP<sup>Sc</sup> before (Dry 0) or after 10 (Dry 10) rounds of drying and wetting. Samples in replicates (n = 3) were tested. Migration of 29 and 21 kDa molecular weight marker is indicated on the right of the Western blot.</p

    Influence of repeated cycles of drying and wetting on proteinase K resistance and amplification efficiency of DY TME.

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    <p>Western blot (A and B) and quantification (C and D) of PK digested and PMCA amplification (3 rounds) of DY PrP<sup>Sc</sup> alone or adsorbed to SCL before (Dry 0) and after 1 (Dry 1) and 10 (Dry 10) serial rounds of drying and wetting. Negative PMCA samples were diluted from corresponding PMCA seeding with a dilution factor of 80. Migration of 29 and 19 kDa molecular weight marker is indicated on the right of the Western blot. Star indicates significant difference (p<0.05; n = 3) between treated and untreated sample.</p

    Preparation of soil bound HY TME, DY TME<sup>a</sup>, and elk CWD<sup>a</sup> PrP<sup>Sc</sup>.

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    <p><sup>a</sup> SCL bound DY TME and elk CWD PrP<sup>Sc</sup> were prepared with the same soil to brain ratio and in the same condition as SCL bound HY TME. HY TME was also used for animal bioassay</p><p><sup>b</sup> BH, 10% brain homogenate.</p><p><sup>c</sup> SiO<sub>2-</sub>HA, SiO<sub>2-</sub>humic acid.</p><p><sup>d</sup> The amount of samples used for PMCA was expressed as weight of soil—equivalent volume of soil solution.</p><p><sup>e</sup> Due to the performance challenge, PMCA substrate was added to the soil pellets of weight as indicated in the table.</p><p>Preparation of soil bound HY TME, DY TME<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004638#t001fn001" target="_blank"><sup>a</sup></a>, and elk CWD<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004638#t001fn001" target="_blank"><sup>a</sup></a> PrP<sup>Sc</sup>.</p
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