962 resultados para Royal Institution of Great Britain.
Resumo:
Total phosphorus (TP) and soluble reactive phosphorus (SRP) loads to watercourses of the River Basin Districts (RBDs) of Great Britain (GB) were estimated using inventories of industrial P loads and estimates of P loads from sewage treatment works and diffuse P loads calculated using region-specific export coefficients for particular land cover classes combined with census data for agricultural stocking densities and human populations. The TP load to GB waters was estimated to be 60 kt yr(-1), of which households contributed 73, agriculture contributed 20, industry contributed 3, and 4 came from background sources. The SRP load to GB waters was estimated to be 47 kt yr(-1), of which households contributed 78, agriculture contributed 13, industry contributed 4, and 6 came from background Sources. The 'average' area-normalized TP and SRP loads to GB waters approximated 2.4 kg ha(-1) yr(-1) and 1.8 kg ha(-1) yr(-1), respectively. A consideration of uncertainties in the data contributing to these estimates suggested that the TP load to GB waters might lie between 33 and 68 kt yr(-1), with agriculture contributing between 10 and 28 of the TP load. These estimates are consistent with recent appraisals of annual TP and SRP loads to GB coastal waters and area-normalized TP loads from their catchments. Estimates of the contributions of RBDs to these P loads were consistent with the geographical distribution of P concentrations in GB rivers and recent assessments of surface waters at risk from P Pollution.
Resumo:
The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/
Resumo:
The Met Office 1km radar-derived precipitation-rate composite over 8 years (2006–2013) is examined to evaluate whether it provides an accurate representation of annual-average precipitation over Great Britain and Ireland over long periods of time. The annual-average precipitation from the radar composite is comparable with gauge measurements, with an average error of +23mmyr−1 over Great Britain and Ireland, +29mmyr−1 (3%) over the United Kingdom and –781mmyr−1 (46%) over the Republic of Ireland. The radar-derived precipitation composite is useful over the United Kingdom including Northern Ireland, but not accurate over the Republic of Ireland, particularly in the south.
Resumo:
Includes bibliography
Resumo:
Includes bibliography
Resumo:
Spanish version available
Resumo:
by Edmund D. Morel