We have developed an autonomous CO2 monitoring station, based around the Vaisala GMP343 sensor. The station is powered by a solar panel and incorporates a data logger and a directional antenna for line-of-sight wireless communication with a base station. The base station communicates via the Telstra mobile phone data network. The concept of atmospheric tomography was tested at the Ginninderra site and proved very successful as a method of locating and quantifying a spatially small release of CO2. In this case the sensors were separated from the source by 40 m. The opportunity to test the method over a larger distance arose during the controlled release of Buttress gas during the stage 2B experiment at the Otway site. Gas was released at 8 tpd during daylight hours, and an approximate ring of 8 monitoring stations was deployed around the release point; the ring was about 800 m in diameter. Gas was released on 12 occasions, chosen to match wind directions that would carry the plume in the direction of one of the sensors. The dataset was too limited to carry out the full-scale Bayesian inversion that was demonstrated in the Ginninderra test (which lasted two months) but a simple inversion was possible. This located the source of the release correctly to within 20 m. The test demonstrated that inexpensive sensors could achieve enough stability and sensitivity to work (in this particular application) at the few ppm level. Moreover quite simple dispersion models could be used to predict plume geometry up to 500 m from the release. Overall the experiment indicates the basis of an inexpensive method for remotely monitoring areas of around a km2 for spatially small leakages.

In July 2010, Geoscience Australia and CSIRO Marine & Atmospheric Research jointly commissioned a new atmospheric composition monitoring station, named Arcturus, in sub-tropical Queensland, Australia. The facility is designed as a proto-type remotely operated `baseline monitoring station' that could be deployed in areas that are likely targets for commercial scale geological storage of carbon dioxide. A key question, given the ecosystem and anthropogenic sources of CO2 in the region, and the absence of a 'clean-wind' sector baseline, is how large would a CO2 leak have to be from a geological storage site before it can be detected above the background CO2 signal? To address this, CO2 leak simulation modelling was performed for 1-year period using the coupled prognostic meteorological and air pollution model TAPM at various locations, emission rates and distances (1-10 km) from the station.

The CO2CRC has been leading the international development and application of atmospheric techniques for CO2 leak detection and quantification for CCS. CSIRO's atmospheric monitoring program at the CO2CRC Otway Project demonstrated world's leading practice for atmospheric monitoring at geological storage sites. The GA-CO2CRC Ginninderra controlled release facility has enabled development and testing of a new atmospheric tomography approach for accurately quantifying CO2 emissions using atmospheric techniques. A scaled-up version of the technique using an array of more cost effective (but less accurate) sensors was applied at a larger scale at the Otway Stage 2B controlled release. Additional techniques have been developed including data filtering to optimize the detection of emitted gases against the ecosystem background and Bayesian inverse modeling to locate and quantify a source. GA and CSIRO operate a joint baseline atmospheric station in the Bowen Basin and have been independently investigating the sensitivity of CO2 leak detection through coupling of measurements taken in a sub-tropical environment with simulated leakage events. An outcome from this body of work is the importance of good quality, calibrated measurements, a long baseline record and the development and application of techniques using atmospheric models for quantifying gaseous emissions from the ground to the atmosphere. These same measurement requirements and quantification techniques have direct application to fugitive methane emissions from open cut coal mines, coal seam gas, tight gas, and conventional gas emissions. Application is easier for methane: the background signal is lower, sensors are available at affordable cost, and the emissions are measureable now. The Bowen Basin site, for example, is detecting fugitive methane emitted from open cut coal mining activities tens of kilometres away. An example of the sensitivity of atmospheric techniques for the detection of fugitive emissions from a simulated methane source will be presented.

The ultimate purpose of carbon capture and storage is to keep CO2 out of the atmosphere. However there are some scenarios in which leakage to atmosphere may occur. Because of the large and variable level of naturallyoccurring CO2 , and rapid dispersion in the atmosphere, leakage to atmosphere can be difficult to detect from concentration measurements. By using prior information from risk assessments about plausible location of leaks, it is possible to design simple yet effective systems for identifying the location of a leak within a pre-defined area of surveillance. We have designed an inexpensive system of autonomous sensors that can locate leaks of CO2 , and have tested it during a controlled release at the CO2CRC Otway site. The system proved effective and it, and its associated workflow, could be adapted and implemented in a variety of storage settings.

Weather radar data provided by the Bureau of Meteorology for initial investigation into thunderstorm tracking and analysis applications

<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. https://pid.geoscience.gov.au/dataset/ga/90078. <p>Digital Object Identifier: http://dx.doi.org/10.4225/25/5823c37333f9d

The Atmospheric Tomography software is a command line tool written in python to estimate the emission rate of a point source from concentration data. It implements an extension of the Bayesian inversion method. Bhatia, S., Feitz, A. and Francis, A. (2017) Atmospheric Tomography, GitHub repository, https://github.com/GeoscienceAustralia/atmospheric_tomography_laser

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. 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 for 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. 0.1 - 10 %) 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 statistical analysis and an indicative minimum fugitive methane emission rate that can be detected using a single monitoring station are presented. Submitted to AGU 2013, San Francisco

Tropical cyclone scenario prepared for Tonga National Emergency Management Office (NEMO) as part of the PacSAFE Project (2016-2018)

Wind speed Coefficients: 1) Fixed 2) Linear 3) Capped