GIS aided prediction of CO2 emission dispersion from geothermal electricity production |
| |
| Authors: | Amin Yousefi-Sahzabi Kyuro Sasaki Hossein Yousefi Saied Pirasteh Yuichi Sugai |
| |
| Institution: | 1. Research School of Population Health, The Australian National University, Canberra, Australian Capital Territory 0200, Australia;2. Ningxia Medical University, 692 Shengli St, Xingqing, Yinchuan, Ningxia Hui Autonomous Region, PR China;3. Molecular Parasitology Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia;4. Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, 7514 AE Enschede, Netherlands;5. School of Veterinary Science, The University of Queensland, Main Dr & Outer Ring Road, Gatton, Queensland 4343, Australia;6. Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Gatton, Queensland 4343, Australia;7. School of Public Health, The University of Queensland, Brisbane, Queensland 4006, Australia;8. Children''s Health and Environment Program, Queensland Children''s Medical Research Institute, The University of Queensland, Brisbane, Queensland 4101, Australia;9. Computer Network Information Center, Chinese Academy of Sciences, Haidian District, Beijing 100190, PR China |
| |
| Abstract: | CO2 is the dominant constituent of non-condensable gases in the steam phase of most geothermal fluids. This paper attempts to present the results of a study conducted to develop prediction modeling of CO2 dispersion in the surrounding atmosphere from a planned 50 MWe geothermal power plant prior to its production. Dispersion models are widely used for predicting future concentrations of environmental emissions on a range of geographic scales. The dispersion type for gases and their average removal rate depends on the meteorological conditions such as wind direction, wind speed, precipitation, atmospheric stability, and surface roughness and topography. Geographic Information System (GIS) capabilities were used for quality visualization of the model outputs and presenting an accurate numerical copy of the study area. The results by the prediction model show that the natural transfer of CO2 will be from the power plant toward east and northeast and CO2 concentration trends after the power plant utilization will be similar to the background conditions with minor changes. This dispersion test was carried out to validate and field test the GIS aided dispersion modeling approach described in the paper and the procedure may be applicable for other studies assessing the emission dispersion of pollutants from a point source. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
