Browsing by Author "Whelan, Michael"
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Item Open Access The fate and effects of triclosan in soils amended with biosolids(Cranfield University, 2012-09) Butler, Emma; Whelan, Michael; Sakrabani, RubenMany hydrophobic pollutants can be emitted to agricultural soils if sewage sludge is used as a fertiliser. The fate and effects of pollutants in such receiving environments are relatively poorly understood compared with our knowledge of chemical behaviour and impact in surface waters. One chemical of particular concern is triclosan because it has antimicrobial properties which could affect important soil functions. Triclosan is hydrophobic, which means it will sorb appreciably to organic solids and is not readily biodegradable. It is also used extensively in personal care products. These factors have prompted considerable attention in the literature with respect to its environmental profile. In recent years, this attention has shifted away from the water environment to terrestrial systems. This thesis bridges some of the knowledge gaps considering the fate (specifically mineralisation, primary degradation and the formation of bound residues) and the effects (to the soil function and phenotype) of triclosan in soils amended with biosolids. Cont/d.Item Open Access Modelling of pesticide exposure in ground and surface waters used for public water supply(Cranfield University, 2014-01) Pullan, Stephanie; Holman, Ian P.; Whelan, MichaelDiffuse transfers of pesticides from agricultural land to ground and surface waters can lead to significant drinking water quality issues. This thesis describes the development and application of a parameter-efficient, numerical model to predict pesticide concentrations in raw water sources within an integrated hydrological framework. As such, it fills an unoccupied niche that exists in pesticide fate modelling for a computationally undemanding model that contains enough process complexity to be applicable in a wide range of catchments and hydrogeological settings in the UK and beyond. The model represents the key processes involved in pesticide fate (linear sorption and first-order degradation) and transport (surface runoff, lateral throughflow, drain flow, percolation to the unsaturated zone, calculated using a soil water balance) in the soil at a daily time step. Soil properties are derived from the national soil database for England and Wales and are used to define the boundary conditions at the interface between the subsoil and the unsaturated zone. This is the basis of the integrated hydrological framework which enables the application of the model to both surface water catchments and groundwater resources. The unsaturated zone model accounts for solute transport through two flow domains (accounting for fracture flow and intergranular matrix flow) in three hydrogeological settings (considering the presence and permeability of superficial deposits). The model was first applied to a small headwater sub-catchment in the upper Cherwell. Performance was good for drainflow predictions (Nash Sutcliffe Efficiency > 0.61) and performed better than the MACRO model and as well as the modified MACRO model. Surface water model performance was evaluated for eight pesticides in five different catchments. Performance was generally good for flow prediction (Nash Sutcliffe Efficiency > 0.59 and percentage bias below 10 %, in the validation period for all but two catchments). The 90th percentile measured concentration was captured by the model in 62 % of catchment-pesticide combinations. In theremaining cases predictions were within, at most, a factor of four of measured 90th percentile concentrations. The rank order of the frequency of pesticides detected over 0.1 μg L-1 was also predicted reasonably well (Spearman’s rank coefficient > 0.75; p < 0.05 in three catchments). Pesticide transport in the unsaturated zone model was explored at the point scale in three aquifers (chalk, limestone and sandstone). The results demonstrate that representing the unsaturated zone processes can have a major effect on the timing and magnitude of pesticide transfers to the water table. In comparison with the other catchment scale pesticide fate models that predict pesticide exposure at a daily time-step, the model developed stands out requiring only a small number of parameters for calibration and quick simulation times. The benefit of this is that the model can be used to predict pesticide exposure in multiple surface and groundwater resources relatively quickly which makes it a useful tool for water company risk assessment. The broad-scale approach to pesticide fate and transport modelling presented here can help to identify and prioritise pesticide monitoring strategies, to compare catchments in order to target catchment management and to highlight potential problems that could arise under different future scenarios.Item Open Access Modelling Soil Bulk Density using Data-Mining and Expert Knowledge(Cranfield University, 2013-04) Taalab, Khaled Paul; Corstanje, Ronald; Whelan, Michael; Creamer, Rachel E.Data about the spatial variation of soil attributes is required to address a great number of environmental issues, such as improving water quality, flood mitigation, and determining the effects of the terrestrial carbon cycle. The need for a continuum of soils data is problematic, as it is only possible to observe soil attributes at a limited number of locations, beyond which, prediction is required. There is, however, disparity between the way in which much of the existing information about soil is recorded and the format in which the data is required. There are two primary methods of representing the variation in soil properties, as a set of distinct classes or as a continuum. The former is how the variation in soils has been recorded historically by the soil survey, whereas the latter is how soils data is typically required. One solution to this issue is to use a soil-landscape modelling approach which relates the soil to the wider landscape (including topography, land-use, geology and climatic conditions) using a statistical model. In this study, the soil-landscape modelling approach has been applied to the prediction of soil bulk density (Db). The original contribution to knowledge of the study is demonstrating that producing a continuous surface of Db using a soil-landscape modelling approach is that a viable alternative to the ‘classification’ approach which is most frequently used. The benefit of this method is shown in relation to the prediction of soil carbon stocks, which can be predicted more accurately and with less uncertainty. The second part of this study concerns the inclusion of expert knowledge within the soil-landscape modelling approach. The statistical modelling approaches used to predict Db are data driven, hence it is difficult to interpret the processes which the model represents. In this study, expert knowledge is used to predict Db within a Bayesian network modelling framework, which structures knowledge in terms of probability.This approach creates models which can be more easily interpreted and consequently facilitate knowledge discovery, it also provides a method for expert knowledge to be used as a proxy for empirical data. The contribution to knowledge of this section of the study is twofold, firstly, that Bayesian networks can be used as tools for data-mining to predict a continuous soil attribute such as Db and that in lieu of data, expert knowledge can be used to accurately predict landscape-scale trends in the variation of Db using a Bayesian modelling approach.Item Open Access Towards a conceptual model of the impact zone ecology in rivers(Cranfield University, 2014-11) Roche, Nicola; Gill, A. B.; Whelan, MichaelIn many regions of the world, untreated wastewater is discharged directly into rivers containing sanitary determinands including ammonia, nitrite and organic matter which places a demand on dissolved oxygen in the water. The wastewater may also contain chemical ingredients of home and personal care products. When sewage treatment is lacking, often in developing regions, these sanitary determinands and down-the-drain chemicals may be present at high concentrations in surface waters which may adversely impact the ecological communities present downstream of the effluent outfall. Some studies have studied these ecological effects by sampling the taxa present at regular intervals downstream of an wastewater outfall, from which a common pattern in terms of macroinvertebrate species richness, dominance and diversity throughout the impact zone is evident. The aim of the project was to develop a conceptual model in order to predict the ecological composition downstream of an effluent outfall, as a result of multiple stressors’ concentration gradients. The model combines water quality data and toxicity data of the stressors on aquatic organisms, in the form of species sensitivity distributions (SSDs) to predict this impact. The model was based on selected stressors: ammonia, nitrite and dissolved oxygen which are present, in particular, in untreated wastewater; and two chemical ingredients used in home and personal care products which are washed down-the-drain. The model was applied to data from a field study on the South Elkhorn Creek in Kentucky, USA. Predicted effects on taxonomic composition were in line with field observations, although further enhancements to the model could incorporate more environmental realism. This was a useful step in the direction to creating a conceptual model of the impact zone ecology in rivers.Item Open Access Water Framework Directive Article 7, The Drinking Water Directive and European Pesticide Regulation: impacts on diffuse pesticide pollution, potable water decision making and catchment management strategy(Cranfield University, 2013-10) Dolan, Tom; Parsons, David; Howsam, Peter; Whelan, Michael; Varga, LizThe European Water Framework Directive (WFD) promotes increased awareness of catchment processes and challenges the established dependence on a ‘treatment-led approach’ for the supply of European Drinking Water Directive (DWD) compliant potable water. In particular, WFD Article 7 promotes a ‘prevention-led approach’ to DWD compliance, based on pollution prevention at source to reduce investment in new treatment. In this context the challenge of preventing diffuse pesticide pollution from agricultural sources is significant because metaldehyde (a molluscide) and to a lesser extent the herbicide clopyralid are, despite current treatment, causing DWD non compliance for drinking water in a number of English catchments. Analysis presented here identifies that a successful transition from a ‘treatment-led’ to a ‘prevention-led’ approach will require collective action from, and shared mutual understanding between, a number of stakeholder groups. However, each of these groups has a unique perspective on WFD Article 7 and other elements of the currently uncoordinated legal and voluntary framework for diffuse pesticide pollution prevention. A toolbox of intervention options and a set of criteria to evaluate current catchment management actions are proposed to help the WFD competent authority facilitate WFD Article 7 compliance.Water suppliers need to improve their understanding of the reasons for pesticide use. Through consultation with pesticide agronomists, important drivers of pesticide use, a hierarchy of adaptation options available if a particular pesticide is restricted and key messages for catchment managers and regulators were identified. Based on this foundation a classification system to inform and prioritise water sector decision making for investment in catchment management was developed.Additionally, analysis presented here demonstrates that the DWD standard for pesticides, which determines the level of catchment management required for WFD Article 7 compliance, is not itself consistent with European environmental policy principles, particularly the precautionary principle, and needs to be reviewed.