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Hydrogen sulphide dispersion and modelling for Nesjavellir power station using Gaussian and numerical models

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Titill: Hydrogen sulphide dispersion and modelling for Nesjavellir power station using Gaussian and numerical modelsHydrogen sulphide dispersion and modelling for Nesjavellir power station using Gaussian and numerical models
Höfundur: Nyagah, E. Munene ; Jarðhitaskóli Háskóla Sameinuðu þjóðanna
URI: http://hdl.handle.net/10802/23511
Útgefandi: United Nations University; Orkustofnun
Útgáfa: 2006
Ritröð: United Nations University., UNU Geothermal Training Programme, Iceland. Report ; 2006-15
Efnisorð: Jarðhiti; Jarðhitarannsóknir; Jarðefnafræði; Líkön; Jarðfræði; Virkjanir; Orkuver; Jarðhitaverkfræði; Nesjavellir
ISSN: 1670-7427
Tungumál: Enska
Tengd vefsíðuslóð: http://www.os.is/gogn/unu-gtp-report/UNU-GTP-2006-15.pdf
Tegund: Bók
Gegnir ID: 001516620
Athugasemdir: Í : Geothermal training in Iceland 2006, bls. 291-314.Myndefni: kort, línurit, töflur.
Útdráttur: The spatial variation of hydrogen sulphide fallout around Nesjavellir geothermal power station has been determined using Gaussian (AERMOD) and numerical models. The models quantitatively simulated atmospheric interactions and related the emission of hydrogen sulphide to air quality. The simulations, based on data from June to August 2006, were aimed at quantifying the distribution of hydrogen sulphide within the vicinity of the power station as well as validating the numerical model. The predicted concentrations were lower than the field measurements collected within the modelling area. The near-ground predictions from the two models demonstrate that hydrogen sulphide emitted from the power station undergoes significant dilution as it is dispersed by wind, resulting in low concentrations in the neighbourhood of the power station, albeit with localised high concentrations to the immediate east of the power station. The study indicates that the models can capture the real-time features governing the dispersal of hydrogen sulphide. Despite some inaccuracies, the numerical model predictions represent well the actual dispersion and with some modifications they can be adopted for use in quantifying the dispersion of gaseous emissions elsewhere.


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