Vinsamlegast notið þetta auðkenni þegar þið vitnið til verksins eða tengið í það: http://hdl.handle.net/1946/31882
The AERMOD model was evaluated with the aim to assess the applicability of the software to give reasonable results, in estimating H2S concentration from two geothermal fields affected by different weather conditions. The study cases were geothermal emissions from the Ulubelu power plants in Indonesia, and the emissions from the Hellisheidi and Nesjavellir power plants in Iceland. The modeled H2S distribution was also compared to observation H2S values with periods of up to one-year data. AERMOD was used to calculate the maximum concentration of 1-hour (odor standard), 8-hour (occupational health standard), 24-hour and annual time averages (public health standard). The test cases included different model setup of elevated and flat terrain options, as well as various meteorological data (e.g. onsite and offsite). Overall, the model performed better for a long-term period (annual) than a short-term period (1-hour and 24-hour), except for the Ulubelu case, where the model at 24-hour period agreed well with the measurement data sample points taken from up to 3 km from the source. In contrast, for the Hellisheidi and Nesjavellir case, the models had difficulty in predicting the concentration at receptors within 25 km from the sources. When evaluating the level of H2S concentration based on seasons, the results of the model showed higher concentrations during the winter season than summer season for the Hellisheidi and Nesjavellir case. For the Ulubelu case, the predicted H2S concentration during the dry season was estimated to be higher than during the wet season. The study highlighted the influence of weather conditions (i.e., wind stability in a tropical climate compared to cold weather) on the dispersion of geothermal emissions, as well as the effect distance of meteorological stations, receptor´s and source’s location, and terrain height have on the results of model simulations. The study shows that the model simulation does not work well when the source is far away, the weather changes rapidly and the terrain is complex. However, for stable weather conditions, it provides valuable information and can assist in mitigations measures decisions, for instance, to define H2S monitoring station points at receptors which indicates high concentration of H2S.