The contribution of cattle urine and dung to nitrous oxide emissions: Quantification of country specific emission factors and implications for national inventories.

Urine patches and dung pats from grazing livestock create hotspots for production and emission of the greenhouse gas, nitrous oxide (N2O), and represent a large proportion of total N2O emissions in many national agricultural greenhouse gas inventories. As such, there is much interest in developing country specific N2O emission factors (EFs) for excretal nitrogen (EF3, pasture, range and paddock) deposited during gazing. The aims of this study were to generate separate N2O emissions data for cattle derived urine and dung, to provide an evidence base for the generation of a country specific EF for the UK from this nitrogen source. The experiments were also designed to determine the effects of site and timing of application on emissions, and the efficacy of the nitrification inhibitor, dicyandiamide (DCD) on N2O losses. This co-ordinated set of 15 plot-scale, year-long field experiments using static chambers was conducted at five grassland sites, typical of the soil and climatic zones of grazed grassland in the UK. We show that the average urine and dung N2O EFs were 0.69% and 0.19%, respectively, resulting in a combined excretal N2O EF (EF3), of 0.49%, which is <25% of the IPCC default EF3 for excretal returns from grazing cattle. Regression analysis suggests that urine N2O EFs were controlled more by composition than was the case for dung, whilst dung N2O EFs were more related to soil and environmental factors. The urine N2O EF was significantly greater from the site in SW England, and significantly greater from the early grazing season urine application than later applications. Dycandiamide reduced the N2O EF from urine patches by an average of 46%. The significantly lower excretal EF3 than the IPCC default has implications for the UK's national inventory and for subsequent carbon footprinting of UK ruminant livestock products.

Modelling the cost-effectiveness of mitigation methods for multiple pollutants at farm scale.

Reductions in agricultural pollution are essential for meeting nationally and internationally agreed policy targets for losses to both air and water. Numerous studies quantify the impact of relevant mitigation methods by field experimentation or computer modelling. The majority of these studies have addressed individual methods and frequently also individual pollutants. This paper presents a conceptual model for the synthesis of the evidence base to calculate the impact of multiple methods addressing multiple pollutants in order to identify least cost solutions for multiple policy objectives. The model is implemented as a farm scale decision support tool that quantifies baseline pollutant losses for identifiable sources, areas and pathways and incorporates a genetic algorithm based multi-objective procedure for determining optimal suites of mitigation methods. The tool is generic as baseline losses can be replaced with measured data and the default library of mitigation methods can be edited and expanded. The tool is demonstrated through application to two contrasting farm systems, using survey data on agricultural practices typical of England and Wales. These examples show how the tool could be used to help target the adoption of mitigation options for the control of diffuse pollution from agriculture. The feedback from workshops where Farmscoper was demonstrated is included to highlight the potential role of Farmscoper as part of the farm advisory process.

Description of nine nutrient loss models: capabilities and suitability based on their characteristics.

In EUROHARP, an EC Framework V project, which started in 2002 with 21 partners in 17 countries across Europe, a detailed intercomparison of contemporary catchment-scale modelling approaches was undertaken to characterise the relative importance of point and diffuse pollution of nutrients in surface freshwater systems. The study focused on the scientific evaluation of different modelling approaches, which were validated on three core catchments (the Ouse, UK; the Vansjo-Hobøl, Norway; and the Enza, Italy), and the application of each tool to three additional, randomly chosen catchments across Europe. The tools involved differ profoundly in their complexity, level of process representation and data requirements. The tools include simple loading models, statistical, conceptual and empirical model approaches, and physics-based (mechanistic) models. The results of a scientific intercomparison of the characteristics of these different model approaches are described. This includes an analysis of potential strengths and weaknesses of the nutrient models.

Subannual models for catchment management: evaluating model performance on three European catchments.

Models' abilities to predict nutrient losses at subannual timesteps is highly significant for evaluating policy measures, as it enables trends and the frequency of exceedance of water quality thresholds to be predicted. Subannual predictions also permit assessments of seasonality in nutrient concentrations, which are necessary to determine susceptibility to eutrophic conditions and the impact of management practices on water quality. Predictions of subannual concentrations are pertinent to EC Directives, whereas load estimates are relevant to the 50% target reduction in nutrient loading to the maritime area under OSPAR. This article considers the ability of four models (ranging from conceptual to fully mechanistic), to predict river flows, concentrations and loads of nitrogen and phosphorus on a subannual basis in catchments in Norway, England, and Italy. Results demonstrate that model performance deemed satisfactory on an annual basis may conceal considerable divergence in performance when scrutinised on a weekly or monthly basis. In most cases the four models performed satisfactorily, and mismatches between measurements and model predictions were primarily ascribed to the limitations in input data (soils in the Norwegian catchment; weather in the Italian catchment). However, results identified limitations in model conceptualisation associated with the damping and lagging effect of a large lake leading to contrasts in model performance upstream and downstream of this feature in the Norwegian catchment. For SWAT applied to the Norwegian catchment, although flow predictions were reasonable, the large number of parameters requiring identification, and the lack of familiarity with this environment, led to poor predictions of river nutrient concentrations.

Evaluation of diffuse pollution model applications in EUROHARP catchments with limited data.

The application of diffuse pollution models included in EUROHARP encompassed varying levels of parameterisation and approaches to the preparation of input data depending on the model and modelling team involved. Modellers consistently faced important decisions in relation to data interpretation, especially in those catchments with unfamiliar physical or climatic characteristics, where catchment conditions were beyond the range for which a particular model was originally developed, or where only limited input data were available. In addition to a broad discussion of data issues, this paper compares the performance of the four sub-annual output models tested in EUROHARP (EveNFlow, NL-CAT, SWAT and TRK) in three test catchments without the modelling teams having sight of measured flow and nitrate concentration data. Model performance in this "blind test" indicate that the range of predictions generated by any individual models pre and post calibration exceed the differences between the estimates yielded by all four models. Comparison of Analysis of Variance (ANOVA) statistics for simulated and observed flow, concentration and loads underscores the benefits of calibration for these intermediate and complex model formulations. Interpretation of input data (e.g. rainfall interpolation method and pedotransfer functions selected) appeared equally (or more) important than process representation. In the absence of calibration data, modeller unfamiliarity with a particular catchment and its environmental processes sometimes resulted in questionable assumptions and input errors which highlight the problems facing modellers charged with implementing policies under the Water Framework Directive (2000/60/EC) in poorly monitored catchments. Catchment data owners and modellers must therefore work more closely given that the output from diffuse pollution models is clearly modeller-limited as well as model-limited.

Recurrent intravascular papillary endothelial hyperplasia of the right middle finger treated with radiation therapy.

We describe a case of recurrent intravascular papillary endothelial hyperplasia involving the middle finger which was successfully-treated with photon and proton radiotherapy following two previous surgical excisions.

The relationship between potentially erosive storm energy and daily rainfall quantity in England and Wales.

Erosive storm energy is the primary driver of soil detachment, and hence a major determinant of transfer of sediment and particulate phosphorus (P) to surface waters. Modelling of sediment and P loss at catchment scale, for example for the development of catchment and national mitigation policies, requires a spatially interpolated estimate of variation in erosion risk. To this end we present a method of estimating total rainfall erosivity, as kinetic energy (KE), for any location in England and Wales, from daily rainfall data or monthly climate data. Analysis of detailed, high-resolution records from eleven contrasting sites showed strong predictive correlations between daily rainfall quantity and associated daily total kinetic energy estimated from hourly rainfall intensities. The coefficients showed systematic seasonal variation, with greatest KE per unit of rainfall in late summer and autumn months. In contrast, no systematic spatial variation was found as a function of location or continentality index. The relationships were integrated with probability distributions of rainfall quantity per rain day derived from spatial climate data (monthly rainfall totals and numbers of rain days). The resulting map captures and quantifies the effects of rainfall quantity and intensity patterns on risk of sediment detachment, and as such provides a critical input layer to catchment-scale models of sediment and P transfer.