From 1 - 10 / 30
  • Geological storage of CO2 is a leading strategy for large-scale greenhouse gas emission mitigation. Monitoring and verification is important for assuring that CO2 storage poses minimal risk to people's health and the environment, and that it is effective at reducing anthropogenic CO2 emissions. Eddy Covariance (EC) has been proposed as a long-term monitoring solution for geological storage projects and is considered suitable for monitoring areas 1000 - 100,000 m2 in size. Eddy Covariance is a key micrometeorological technique which has traditionally been used for assessing ecosystem exchange of CO2 in a variety of natural and agricultural settings. It measures the vertical transfer of scalar variables such as CO2 via eddies from upwind of the instrumentation, and correlates the measured CO2 flux to the upwind source area based on several key assumptions. These assumptions include that the upwind source area is homogeneous, flat and uniform, which in turn requires that horizontal gradients in CO2 concentration are zero and that horizontal and vertical gradients in the covariance of CO2 concentration and orthogonal wind directions are zero. Work undertaken at the GA-CO2CRC Gininnderra controlled release facility, where CO2 is released from the shallow subsurface (at 2 m depth), suggests that CO2 leakage in the near subsurface will follow paths of least resistance up to the surface. Similar observations have been observed at the ZERT facility in Montana and CO2 Field Lab in Norway. This leads to CO2 leaks having localised, patchy surface expression, rather than a diffuse wide-scale leak which one typically expects (Lewicki et al. 2010). The implication of this is that the source area for a leak is highly inhomogeneous, meaning the magnitudes of CO2 flux values measured using EC are grossly unreliable. These limitations were discussed in Leuning et al.'s (2008) review on CCS atmospheric monitoring technologies yet are not addressed in much of the recent EC leak quantification literature. This presentation will present findings from the first subsurface release at the CO2CRC facility in Canberra (March - May 2012), where EC data was analysed for application in leak detection and quantification. The CO2 release rate was 144 kg/d. Eddy Covariance was successfully used to detect the leak by comparing CO2 fluxes in the direction of the leak to baseline wind sectors. Median CO2 fluxes in the leak direction were 9.1 µmol/m2/s, while the median background flux was 1.0 µmol/m2/s. Separate measurements taken using a soil flux meter found that the daytime background soil flux had a median flux of 1.8 µmol/m2/s but the peak soil flux over a leak was 1100 µmol/m2/s. Quantification and spatially locating the leak were attempted, but due to the problem of source area inhomogeneity, no substantive progress could be made. How an inhomogeneous source area contributes to 'lost' CO2 from the system, through advection and diffusion, will be discussed, coupled with suggestions for how these parameters can be evaluated in future experimental design. Leuning R., Etheridge D., Luhar A., and Dunse B., 2008. Atmospheric monitoring and verification technologies for CO2 sequestration. International Journal of Greenhouse Gas Control, 2(3), 401-414. Lewicki J. L., Hilley G. E., Dobeck L., and Spangler L., 2010. Dynamics of CO2 fluxes and concentrations during a shallow subsurface CO2 release. Environmental Earth Sciences, 60(2), 285-297.

  • To provide the solar power industry with a data resource to allow them to assess the economic potential of a site for a solar power plant. Specifically under the Solar Flagship program.

  • Following the drilling of a shallow CO2 reservoir at the Qinghai research site, west of Haidong, China, it was discovered that CO2 was continuously leaking from the wellbore due to well-failure. The site has become a useful facility in China for studying CO2 leakage and monitoring technologies for application to geological storage sites of CO2. During an eight day period in 2014, soil gas and soil flux surveys were conducted to characterise the distribution, magnitude and likely source of the leaking CO2. Two different sampling patterns were utilised during soil flux surveys. A regular sampling grid was used to spatially map out the two high flux zones which were located 20-50 m away from the wellhead. An irregular sampling grid with higher sampling density in the high flux zones, allowed for more accurate mapping of the leak distribution and estimation of total field emission rate using cubic interpolation. The total CO2 emission rate for the site was estimated at 649-1015 kgCO2/d and there appeared to be some degree of spatial correlation between observed CO2 fluxes and elevated surface H2O fluxes. Sixteen soil gas wells were installed across the field to test the real-time application of Romanak et al.'s (2012) process-based approach for soil gas measurements (using ratios of major soil gas components to identify the CO2 source) using a portable multi-gas analyser. Results clearly identified CO2 as being derived from one exogenous source, and are consistent with gas samples collected for laboratory analysis. Carbon-13 isotopes in the centre of each leak zone (-0.21 and -0.22 ) indicate the underlying CO2 is likely sourced from the thermal decomposition of marine carbonates. Surface soil mineralisation (predominantly calcite) is used to infer prior distribution of the CO2 hotspots and as a consequence highlighted plume migration of 20 m in 11 years. Detachment of the plume from the wellbore at the Qinghai research site markedly increases the area that needs surveying at sufficient density to detect a leak. This challenges the role of soil flux and soil gas in a CCS monitoring and verification program for leak detection, whereas these techniques may best be applied for characterising source and emission rate of a CO2 leak.

  • The Australian Solar Energy Information System V2.0 has been developed as a collaborative project between Geoscience Australia and the Bureau of Meteorology. The product provides pre-competitive spatial information for investigations into suitable locations for solar energy infrastructure. The outcome of this project will be the production of new and improved solar resource data, to be used by solar researchers and the Australian solar power industry. it is aimed to facilitate broad analysis of both physical and socio-economic data parameters which will assist the solar industry to identify regions best suited for development of solar energy generation. It also has increased the quality and availability of national coverage solar exposure data, through the improved calibration and validation of satellite based solar exposure gridded data. The project is funded by the Australian Renewable Energy Agency. The ASEIS V2.0 has a solar database of resource mapping data which records and/or map the following Solar Exposure over a large temporal range, energy networks, infrastructure, water sources and other relevant data. ASEIS V2.0 has additional solar exposure data provided by the Bureau of Meteorology. - Australian Daily Gridded Solar Exposure Data now ranges from 1990 to 2012 - Australian Monthly Solar Exposure Gridded Data now ranges from 1990 to 2011 ASEIS V2.0 also has a new electricity transmission reference dataset which allows for information to be assessed on any chosen region the distance and bearing angle to the closest transmission powerline.

  • Data provided by AIR Worldwide to Geoscience Australia as part of the review of the PCRAFI Phase II project, which examined hazard and risk from TCs and earthquakes in the Pacific. The review was conducted in 2010. This data should be considered in-confidence and is not for distribution or external use.

  • Global solar exposure is the total amount of solar energy falling on a horizontal surface. The hourly global solar exposure is the total solar energy for one hour. Typical values for hourly global exposure range up to 4 MJ/m2 (megajoules per square metre). The values are usually highest in the middle of the day and around summer, with localised variations caused mainly by variations in atmospheric conditions, primarily cloudiness. See metadata statement for more information.

  • Fugitive methane emissions, in particular relating to coal seam gas (CSG),has become an emerging issue in Australia over the last few years. There has been significant controversy in US regarding the magnitude of fugitive emissions during production from unconventional gas wells, with large differences in emissions reported between studies using different measurement approaches. . Preliminary research into a small number of Australia's unconventional fields suggest the average fugitive emissions per well are lower than that found in the US. The primary challenge is that the techniques for quantifying methane leakages are still at an early stage of development. Current methods for the small to medium scale use chamber based approaches or vehicles installed with fixed sampling lines and high precisions gas analysers. These technologies are promising, but generally have not been ground truthed in field conditions against known emission rates to estimate effectiveness. They also have limited application in environments where vehicle access is not possible. The Ginniderra facility is being upgraded to support a methane controlled release experiment in 2015. This will enable testing of and verifying methods and technologies for measuring and quantifying methane emissions. To address the absence of suitable techniques for emmission measurement at medium scales, several BOREAL lasers will be deployed which work at scales of 20-1000 m. It is also envisaged airborne techniques utilising laser and hyperspectral will be deployed, along with tomography work utilising multiple concurrent concentration measurements.

  • Included fields: Bureau of Meteorology Station Number. Year month day in YYYY,MM,DD format. Present weather at (00, 03, 06, 09, 12, 15, 18, 21) hours Local Time, as international code. Quality of present weather at (00, 03, 06, 09, 12, 15, 18, 21) hours Local Time. Past weather at (00, 03, 06, 09, 12, 15, 18, 21) hours Local Time, as international code. Quality of past weather at (00, 03, 06, 09, 12, 15, 18, 21) hours Local Time.

  • As part of the 2018 Tropical Cyclone Hazard Assessment (TCHA), we compiled the geospatial raster dataset that can be accessible to internal and external users via ArcGIS online and can be integrated for building additional geoprocessing applications. This web service gives more stable and easy access to data and interactive maps. With having separate geospatial layers for each recurrence interval- i.e. 5 through 10000 years, users can toggle between the layers and evaluate the changes in wind speed (km/hr) and potential areas at risk on the fly.