Browsing by Author "Whelan, M. J."
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Item Open Access Continuous-flow laboratory simulation of stream water quality changes downstream of an untreated wastewater discharge.(Elsevier Science B.V., Amsterdam., 2009-04-01T00:00:00Z) Finnegan, Chris J.; van Egmond, R. A.; Price, O. R.; Whelan, M. J.In regions of the world with poor provision of wastewater treatment, raw sewage is often discharged directly into surface waters. This paper describes an experimental evaluation of the fate of two organic chemicals under these conditions using an artificial channel cascade fed with a mix of settled sewage and river water at its upstream end and operated under continuous steady-state conditions. The experiments underpin an environmental risk assessment methodology based on the idea of an “impact zone” (IZ) – the zone downstream of wastewater emission in which water quality is severely impaired by high concentrations of unionised ammonia, nitrite and biochemical oxygen demand (BOD). Radiolabelled dodecane-6-benzene sulphonate (DOBS) and aniline hydrochloride were used as the model chemical and reference compound respectively. Rapid changes in 14C counts were observed with flow-time for both these materials. These changes were most likely to be due to complete mineralisation. A dissipation half-life of approximately 7.1 h was observed for the 14C label with DOBS. The end of the IZ was defined as the point at which the concentration of both unionised ammonia and nitrite fell below their respective predicted no-effect concentrations for salmonids. At these points in the cascade, approximately 83 and 90% of the initial concentration of 14C had been removed from the water column, respectively. A simple model of mineral nitrogen transformations based on Michaelis–Menten kinetics was fitted to observed concentrations of NH4, NO2 and NO3. The cascade is intended to provide a confirmatory methodology for assessing the ecological risks of chemicals under direct discharge conItem Open Access Development and application of a catchment scale pesticide fate and transport model for use in drinking water risk assessment(Elsevier, 2016-05-03) Pullan, S. P.; Whelan, M. J.; Rettino, J.; Filby, S.; Eyre, I. P.; Holman, Ian P.This paper describes the development and application of IMPT (Integrated Model for Pesticide Transport), a parameter-efficient tool for predicting diffuse-source pesticide concentrations in surface waters used for drinking water supply. The model was applied to a small UK headwater catchment with high frequency (8 h) pesticide monitoring data and to five larger catchments (479–1653 km2) with sampling approximately every 14 days. Model performance was good for predictions of both flow (Nash Sutcliffe Efficiency generally > 0.59 and PBIAS < 10%) and pesticide concentrations, although low sampling frequency in the larger catchments is likely to mask the true episodic nature of exposure. The computational efficiency of the model, along with the fact that most of its parameters can be derived from existing national soil property data mean that it can be used to rapidly predict pesticide exposure in multiple surface water resources to support operational and strategic risk assessments.Item Open Access Dynamic multi-phase partitioning of decamethylcyclopentasiloxane (D5) in river water(Elsevier Science B.V., Amsterdam., 2010-12-31T00:00:00Z) Whelan, M. J.; van Egmond, R. A.; Gore, D.; Sanders, D.The behaviour of decamethylcyclopentasiloxane (D5) in river water was evaluated by measuring concentration changes in open beakers. Effective values for the partition coefficient between organic carbon and water (K) were derived by least-squares optimisation of a dynamic model which accounted for partitioning between the sorbed and dissolved phases of D5, and for losses via volatilisation and hydrolysis. Partial mass transfer coefficients for volatilisation were derived from model fits to controls containing deionised water. Effective values of log (K) were between 5.8 and 6.33 (mean 6.16). These figures are higher than some other experimentally-derived values but much lower than those estimated from the octanol: water partition coefficient using single-parameter linear free energy relationships (LFERs). A poly-parameter LFER gave a predicted log (K) of 5.5. Differences in partitioning are believed to be due to the nature of the organic matter present. The new value for effective K was employed in a simple model of D5 behaviour in rivers to ascertain the extent to which a higher affinity for organic carbon would depress volatility. The results suggest that despite the revised K value, volatilisation of D5 remains a significant removal mechanism in surface waters. © 2010 Elsevier LtdItem Open Access A multi‐component method to determine pesticides in surface water by liquid‐chromatography tandem quadrupole mass spectrometry(Wiley, 2017-06-15) Ramos, Andre; Cosgrove, Stephanie; Villa, Raffaella; Jefferson, Bruce; Campo Moreno, Pablo; Jarvis, Peter; Whelan, M. J.; Guymer, I.Pesticide pollution of surface water is a major concern in many agricultural catchments The development of rapid and accurate methods for determining pesticide concentrations in water samples is, therefore, important. Here we describe a method for the simultaneous analysis of six pesticides (metaldehyde, quinmerac, carbetamide, metazachlor, propyzamide and pendimethalin) in natural waters by direct aqueous injection with liquid chromatography-tandem mass spectrometry. The method validation showed good linearity from 0.2 to 50.0 µg/L with correlation coefficients between 0.995 and 0.999. Method accuracy ranged from 84 to 100% and precision Relative standard deviation (RSD) from 4 to 15%. The limits of detection for the targeted pesticides ranged from 0.03 to 0.36 µg/L. No significant matrix effects on quantification were observed (t-test). The method was tested on water samples from a small arable catchment in eastern England. Peak concentrations for the determinands ranged from 1 to 10 µg/L.Item Open Access Predicting Aspergillus fumigatus exposure from composting facilities using a dispersion model: a conditional calibration and validation(Elsevier, 2017-01) Douglas, Philippa; Tyrrel, Sean F.; Kinnersley, Robert P.; Whelan, M. J.; Longhurst, Philip J.; Hansell, Anna L.; Walsh, K.; Pollard, Simon J. T.; Drew, Gillian H.Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are unclear. Exposure levels are difficult to quantify as established sampling methods are costly, time-consuming and current data provide limited temporal and spatial information. Confidence in dispersion model outputs in this context would be advantageous to provide a more detailed exposure assessment. We present the calibration and validation of a recognised atmospheric dispersion model (ADMS) for bioaerosol exposure assessments. The model was calibrated by a trial and error optimisation of observed Aspergillus fumigatus concentrations at different locations around a composting site. Validation was performed using a second dataset of measured concentrations for a different site. The best fit between modelled and measured data was achieved when emissions were represented as a single area source, with a temperature of 29 °C. Predicted bioaerosol concentrations were within an order of magnitude of measured values (1000–10,000 CFU/m3) at the validation site, once minor adjustments were made to reflect local differences between the sites (r2 > 0.7 at 150, 300, 500 and 600 m downwind of source). Results suggest that calibrated dispersion modelling can be applied to make reasonable predictions of bioaerosol exposures at multiple sites and may be used to inform site regulation and operational management.Item Open Access Sensitivity of predicted bioaerosol exposure from open windrow composting facilities to ADMS dispersion model parameters(Elsevier, 2016-10-13) Douglas, Philippa; Tyrrel, Sean; Kinnersley, Robert P.; Whelan, M. J.; Longhurst, Philip J.; Walsh, K.; Pollard, Simon J. T.; Drew, Gillian H.Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are not well understood, and require improved exposure classification. Dispersion modelling has great potential to improve exposure classification, but has not yet been extensively used or validated in this context. We present a sensitivity analysis of the ADMS dispersion model specific to input parameter ranges relevant to bioaerosol emissions from open windrow composting. This analysis provides an aid for model calibration by prioritising parameter adjustment and targeting independent parameter estimation. Results showed that predicted exposure was most sensitive to the wet and dry deposition modules and the majority of parameters relating to emission source characteristics, including pollutant emission velocity, source geometry and source height. This research improves understanding of the accuracy of model input data required to provide more reliable exposure predictions.