Performance of the AERMOD modelling of hydrogen sulfide (H2S) concentration from geothermal power plants in Ulubelu, Indonesia and Hellisheidi-Nesjavellir, Iceland

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Titill: Performance of the AERMOD modelling of hydrogen sulfide (H2S) concentration from geothermal power plants in Ulubelu, Indonesia and Hellisheidi-Nesjavellir, IcelandPerformance of the AERMOD modelling of hydrogen sulfide (H2S) concentration from geothermal power plants in Ulubelu, Indonesia and Hellisheidi-Nesjavellir, Iceland
Höfundur: Jarðhitaskóli Háskóla Sameinuðu þjóðanna ; United Nations University ; United Nations University, Geothermal Training Programme ; Khoirunissa, Irma
URI: http://hdl.handle.net/10802/15487
Útgefandi: United Nations University
Útgáfa: 2018
Efnisorð: Jarðhiti; Jarðhitanýting; Mengun; Umhverfisáhrif; Reiknilíkön; Indónesía; Hellisheiði; Nesjavellir
Tungumál: Enska
Tengd vefsíðuslóð: https://orkustofnun.is/gogn/unu-gtp-40-ann/UNU-GTP-40-B-4-Irma-Khoirunissa.pdf
Tegund: Bók
Gegnir ID: 001494310
Athugasemdir: Presented at United Nations University, Geothermal Training Programme 40th Anniversary Workshop, Reykjavík, April 26, 2018
Útdráttur: The performance of the AERMOD model was evaluated in five cases to improve the global H2S air quality policy. The study cases simulated geothermal emission from Ulubelu power plants in Indonesia, and Hellisheidi and Nesjavellir power plants in Iceland and made comparison with observed H2S data. AERMOD assessed the maximum concentrations of 1-hour (odour standard), 8-hour (occupational health standard), 24-hour and annual time averages (public health standard). Overall, AERMOD performed better for a long-term period than a short-term period and where the observation data sample points were up to 3 km from the sources. When evaluating the level of H2S concentration based on season, it is expected to be higher during winter and autumn than other seasons for Hellisheidi and Nesjavellir. In contrast, for the Ulubelu case, the predicted H2S concentration during the dry season was forecasted higher than during the wet season. Weather conditions and weather station distance to the sources affect the results of model simulations.


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