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  • <p>Geoscience Australia in collaboration with the CO2CRC hosted three controlled subsurface release experiments of CO2 during 2012 to 2013 at an agricultural research station managed by CSIRO Plant Industry Canberra. The facility was designed to simulate surface emissions of CO2 and other greenhouse gases from the soil into the atmosphere, and has deployed a range of near-surface monitoring techniques in the pursuit of improving detection and quantification methods and technologies. This product, which encompasses 4 geodatabases, a metadata report and a data dictionary, presents all the data collected during the experiments from over 10 research organisations, and is made to use with GIS software. The intention of this data release is make the data available for comparison with measurements taken at other controlled release experiments, CO2 storage projects and natural analogues. This will hopefully facilitate the further development of greenhouse gas monitoring technologies, methods and monitoring strategies and increase our understanding of the migration behaviour and impact of near surface CO2 leakage. <p>The contents of each geodatabase/experiment is summarised below: <p>Release 1 (Feb-May 2012): <p>- Soil microbial data <p>- Soil chemistry <p>- Free air CO2 concentration <p>- Eddy covariance <p>- Groundwater chemistry <p>- Soil gas <p>- Krypton tracers <p>- EM31 <p>- Soil flux <p>Release 2 (Oct-Dec 2012): <p>- Groundwater chemistry <p>- EM31 <p>- EM38 <p>- Soil gas <p>- Soil flux <p>- Airborne hyperspectral <p>- Ground hyperspectral <p>Release 3 (Oct-Dec 2013): <p>- Mobile CO2 surveys <p>- Groundwater depth <p>- Eddy covariance <p>- Plant physiology and chemistry <p>- EM31 <p>- EM38 <p>- Soil gas <p>- Soil flux <p>- Airborne hyperspectral <p>All Releases: <p>- Aerial images <p>- Groundwater depths <p>- Meteorological data <p>Bibliographic reference: <p>Feitz, A.J., Schroder, I.F., Jenkins, C.J., Schacht, U., Zegelin, S., Berko, H., McGrath, A., Noble, R., Palu, T.J., George, S., Heath, C., Zhang, H., Sirault, X. and Jimenez-Berni, J. 2016. Ginninderra Controlled CO2 Release Facility Dataset 2012-2013. eCat 90078, Geoscience Australia and CO2CRC, Canberra. http://pid.geoscience.gov.au/dataset/ga/90078. <p>Digital Object Identifier: http://dx.doi.org/10.4225/25/5823c37333f9d

  • There is increasing recognition that minimising methane emissions from the oil and gas sector is a key step in reducing global greenhouse gas emissions in the near term. Atmospheric monitoring techniques are likely to play an important future role in measuring the extent of existing emissions and verifying emission reductions. They can be very suitable for monitoring gas fields as they are continuous and integrate emissions from a number of potential point and diffuse sources that may vary in time. Geoscience Australia and CSIRO Marine & Atmospheric Research have collected three years of continuous methane and carbon dioxide measurements at their atmospheric composition monitoring station ('Arcturus') in the Bowen Basin, Australia. Methane signals in the Bowen Basin are likely to be influenced by cattle production, landfill, coal production, and conventional and coal seam gas (CSG) production. Australian CSG is typically 'dry' and is characterised by a mixed thermogenic-biogenic methane source with an absence of C3-C6+ alkanes. The range of '13C isotopic signatures of the CSG is similar to methane from landfill gas and cattle emissions. The absence of standard in-situ tracers for CSG fugitive emissions suggests that having a comprehensive baseline will be critical for successful measurement of fugitive emissions using atmospheric techniques. In this paper we report on the sensitivity of atmospheric techniques for the detection of fugitive emissions from a simulated new CSG field against a three year baseline signal. Simulation of emissions was performed for a 1-year period using the coupled prognostic meteorological and air pollution model TAPM at different fugitive emission rates (i.e. estimates of <1% to up to 10% of production lost) and distances (i.e. 10 - 50 km) from the station. Emissions from the simulated CSG field are based on well density, production volumes, and field size typical of CSG fields in Australia. The distributions of the perturbed and baseline signals were evaluated and statistically compared to test for the presence of fugitive methane emissions. In addition, a time series model of the methane baseline was developed in order to generate alternative realizations of the baseline signal. These were used to provide measures of both the likelihood of detecting fugitive emissions at various emission levels and of the false alarm rate. Results of the statistical analysis and an indicative minimum fugitive methane emission rate that can be detected using a single monitoring station are presented. Poster presented at the American Geophysical Union meeting, December 2013, San Francisco

  • Here we demonstrate a workflow for the development of a local, corrected wind field for severe Tropical Cyclone (TC) Debbie. We combine modelling with corrections based on observations, and local wind effects including topography, land cover, shielding and direction to provide the best estimate of actual wind speeds. This is important, as wind speed observations are sparse, and do not necessarily provide even coverage of the TC landfall region. The final corrected wind field records the maximum 0.2 second wind gust, at 10 metres above ground, throughout the lifetime of TC Debbie, and provides a best estimate of maximum wind gust speeds associated with TC Debbie. Through the development of this workflow we will demonstrate the importance of observational data for validating wind field modelling outputs, and highlight the usefulness of James Cook University’s mobile anemometers for collecting wind speed data where gaps exist in the Bureau of Meteorology’s automatic weather station network. We identify the limitations in the availability of national land cover datasets at high resolution, and demonstrate the development of a fit-for-purpose land cover dataset using GA’s Digital Earth Australia Landsat archives (Lewis et al. 2017). This report and the accompanying datasets have been released with the aim of showcasing a method, which can be refined by others to develop a standard methodology for the production of local TC wind fields. This workflow can be applied in the same way following future TC events to support the post-disaster field surveys that are routinely carried out by a range of parties following a severe TC making landfall. The local wind fields, combined with the damage surveys ultimately help to refine our vulnerability models of housing stock in Australia.