Pressurized liquid extraction of six tetracyclines from agricultural soils

Veterinary antibiotics used in agriculture can be introduced into the environment through land application of animal manure, accumulating in soils and groundwaters and posing a significant risk to human health and animal well-being. As the analysis of tetracyclines in soil is challenging due to their strong interaction with soil minerals and organic carbon, the objective of this study was to develop a reliable and reproducible method for quantitative analysis of chlortetracycline and oxytetracycline, and their respective metabolites in soils. A method based on pressurized liquid extraction (PLE) with in-cell clean-up was developed for the extraction of chlortetracycline and oxytetracycline and four likely metabolites from a set of four soils. Optimized conditions included a cell size of 22?mL, soil loading of 5?g, pH of 8.0, methanol:water ratio of 3:1, 50?°C, and two cycles. Soil extracts were analysed by high-performance liquid chromatography (HPLC) coupled with ion trap mass spectrometry (MS). Recoveries of seven tetracyclines from soil ranged from 41% to 110%. The limits of detection for tetracyclines were 0.08–0.3 µg g^?1 soil, and intra- and inter-day variation ranged from 0.12–0.34%. The proposed PLE method is suitable for quantification of tetracyclines in agricultural soils at typical concentrations expected in contaminated environments.     

Dry and heat stress affects H2S production of Salmonella on selective plating media

The pH of Salmonella pre-enrichment media can become acidic (pH 4.0–5.0) when feeds/ingredients are incubated for 24?h. Salmonella in feed that have been stressed by heat and desiccation exhibit different pH tolerances than non-stressed cultures. Acidic conditions can result in cell injury/death and affect biochemical pathways. In this study, eight serotypes of Salmonella were grown in sterile meat and bone meal that was subjected to desiccation and heat stress. Cultures of non-stressed and stressed isolates were subsequently exposed to acidic pH from 4.0 to 7.0 in 0.5?pH increments (3 replicates/pH increment) in citrate buffer. At 6 and 24?h, serial dilutions were plated in duplicate on XLT-4 (xylose lysine tergitol-4) agar. Four serotypes showed an impaired ability to decarboxylate lysine on XLT-4. This inability to decarboxylate lysine was dependent on isolate, stress status, and incubation time. When the isolates’ ability to decarboxylate lysine was examined using biochemical tests, cultures were found to be able to decarboxylate lysine with the exception of S. Infantis. This suggests that XLT-4 contains a biochemical stressor(s) which affects the rate of decarboxylation by these Salmonella. These results suggest that acidic conditions may influence the detection and confirmation of Salmonella in feed.     

Trace elements and microbiological parameters in farmed Nile tilapia with emphasis on muscle,water, sediment and feed

Fish may bioaccumulate contaminants from the aquatic environment and extend them to the food chain provoking risks to human health. This study evaluated the microbiological parameters of the pond´s water and trace elements concentrations in samples of water, sediment, feed and muscle of farmed Nile tilapia used for human consumption in southern Brazil. A total of 240 fish were collected from 12 tilapia farms. Sediment, tank water and dry ration used in the animals' diet were collected for analysis. Analysis were performed by Energy Dispersion X-ray Fluorescence (EDXRF), Inductively Coupled Plasma Mass Spectrometer (ICP-MS), Induced Coupled Plasma Optical Emission Spectrometer (ICP-OES), and Atomic Absorption Spectrometer (AAS-VGA). In addition, the microbiological analysis of the water was carried out. The concentrations of Se, I, Fe, Cu and Zn in fish muscle were higher than the recommended by the Brazilian legislation, considering the advised daily intake for adults. The arsenic element had concentrations above the limit stipulated by the present Brazilian legislation, observed in all samples of muscle, sediment and tank water highlighting a possible environmental and fish contamination by the toxic element. Moreover, the arsenic concentration in the water presented a positive correlation (ρ?=?0.33) with arsenic in the muscle, suggesting that tilapia is a good environmental bioindicator, once they properly reflect the levels of arsenic in the water. It is suggested to perform an arsenic speciation for quantification of the inorganic form and accurate assessment of the degree of toxicity in the muscle samples and risks it can bring to human health. Regarding the other potentially toxic elements (Hg, Pb and Cd), and microbiological analysis of water it was verified that the consumption of the fish in question does not raise risks, since the values are within a quality benchmark established by law. The concentration of total and fecal coliforms in pond´s water in the facilities was in agreement with the microbiological indexes required by the legislation of CONAMA class II. Western region presented the lowest concentrations of fecal coliforms when compared to the other regions. There was no significant difference in the microbiological counts of total heterotrophic bacteria, Vibrio spp. and Pseudomonas spp. among the regions.     

Assessing interactions,predicting function,and increasing degradation potential of a PAH-degrading bacterial consortium by effect of an inoculant strain

Environmental Science and Pollution Research - A natural phenanthrene-degrading consortium CON was inoculated with an exogenous strain Sphingobium sp. (ex Sp. paucimobilis) 20006FA yielding the...     

Towards an assessment of the influence of climate on wet acidic deposition in Europe

The EMEP precipitation composition network is used to examine relationships between non-marine SO4(2-), NO3-, NH4+, H+ concentrations and precipitation amount and a local zonal pressure index (an index of the atmospheric circulation). The pattern of the relationships changes across Europe with the zonal pressure gradient explaining more of the variance in ion concentrations in the west, and precipitation amount explaining relatively more of the variance in the east. There is some predictive capability for precipitation composition in the zonal pressure gradient for restricted regions in Europe; R2 values are up to 40% on a daily basis but in some seasons/months attain >60%. The zonal pressure gradient is an index which appears to include pertinent information on transport and wet removal. Preliminary analysis indicates that this approach can be useful in assessing the contributions of changing atmospheric circulation to time-trends of wet acidic deposition in an area stretching from the UK over the North Sea to Denmark. The zonal pressure gradient is known to have varied on time-scales of decades, and the simple index may be one appropriate approach to assessing future deposition patterns from future climate projections.     

Altered feeding preference of beech weevil Rhynchaenus fagi L. for beech foliage under ambient air pollution

The effect of ambient air pollution with increased ozone concentrations on the feeding behaviour of the beech weevil Rhynchaenus fagi L. was studied. In a dual choice feeding test the beech weevil preferred leaf disks from beech saplings exposed to ambient air against those from filtered air in 65.5% of all cases.     

Effects of atmospheric ammonia and ammonium sulphate on Douglas fir (Pseudotsuga menziesii)

Three-year-old Douglas firs (Pseudotsuga menziesii) were fumigated with 180 microg m(-3) NH3 or clean (charcoal-filtered) air. During these fumigations the plants received 15 mm artificial rain weekly, supplemented with 20, 500 or 2500 micromol litre(-1) (NH4)2SO4. Exposure to NH3 and NH4+ for 14 weeks resulted in a change of the nutrient status of the needles. The most remarkable effect was the increase in the N/K ratio, due to both uptake of N and leaching of K. The action of NH3 was stronger than that of NH4+. Both NH3 and (NH4)2SO4 affected the epicuticular wax layer and decreased mycorhiza frequency. Following fumigation and artificial rain treatments, needles were incubated for 8 h in a medium containing 0, 50, 250, 500 and 2500 micromol litre(-1) (NH4)2SO4. Almost no exchange of Ca, Mg and K for NH4+ was found. Therefore this ion exchange probably explains only a minor part of the changes in nutrient status of the whole trees.     

Constraining SWAT Calibration with Remotely Sensed Evapotranspiration Data

Historically, many watershed studies have been based on using the streamflow flux, typically from a single gauge at the basin's outlet, to support calibration. In this setting, there is great potential for equifinality of parameters during the optimization process, especially for parameters that are not directly related to streamflow. Therefore, some of the optimal parameter values achieved during the autocalibration process may be physically unrealistic. In recent decades a vast array of data from land surface models and remote sensing platforms can help to constrain hydrologic fluxes such as evapotranspiration (ET). While the spatial resolution of these ancillary datasets varies, the continuous spatial coverage of these gridded datasets provides flux measurements across the entire basin, in stark contrast to point‐based streamflow data. This study uses Global Land Evaporation: the Amsterdam Model data to constrain Soil and Water Assessment Tool parameter values associated with ET to a more physically realistic range. The study area is the Little Washita River Experimental Watershed, in southern Oklahoma. Traditional objective metrics such as the Nash‐Sutcliffe coefficients record no performance improvement after application of this method. However, there is a dramatic increase in the number of days with receding flow where simulations match observed streamflow.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.