Lagrangian stochastic (LS) forward modelling of CO2 plumes from above-surface release experiments conducted at the GA-CO2CRC Ginninderra GHG controlled release facility demonstrated that small surface leaks are likely to disperse rapidly and unlikely to be detected at heights greater 4 m; this was verified using a rotorcraft to map out the plume. The CO2 sensing rotorcraft unmanned aerial vehicle (RUAV) developed at the Australian National University, Canberra, is equipped with a CO2 sensor (3 ppm accuracy and 2 s response time), a GPS, lidar and a communication module. It was developed to detect, locate and quantify CO2 gas leaks. The choice of a rotorcraft UAV allows slower flight speeds compared to speeds of a fixed-wing UAV; and the electric powered motor enables flight times of 12 min. During the experiments, gaseous CO2 (100 kg per day) was released from a small diffuse source located in the middle of the paddock of the controlled release facility, and the RUAV, flying repeatedly over the CO2 source at a few metres height, recorded CO2 concentrations up to 85 ppm above background. Meteorological parameters measured continuously at the site were input in the LS model. Mapped out horizontal and vertical CO2 concentrations established the need to be close to the ground in order to detect CO2 leakage using aerial techniques. Using the rotorcraft as a mobile sensor could be an expedient mechanism to detect plumes over large areas, and would be important for early detection of CO2 leaks arising from CO2 geological storage activities.

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.

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

Source The data was sourced from CSIRO (Victoria) in 2012 by Bob Cechet. It is not known specifically which division of CSIRO, although it is likely to have been the Marine and Atmospheric Research Division (Aspendale), nor the contact details of the person who provided the data to Bob. The data was originally produced by CSIRO for their input into the South-East Queensland Climate Adaptation Research Initiative (SEQCARI). Reference, from an email of 16 March 2012 sent from Bob Cechet to Chris Thomas (Appendix 1 of the README doc stored at the parent folder level with the data), is made to 'download NCEP AVN/GFS files' or to source them from the CSIRO archive. Content The data is compressed into 'tar' files. The name content is separated by a dot where the first section is the climatic variable as outlined in the table format below: Name Translation rain 24 hr accumulated precipitation rh1_3PM Relative humidity at 3pm local time tmax Maximum temperature tmin Minimum temperature tscr_3PM Screen temperature (2 m above ground) at 3pm local time u10_3PM 10-metre above ground eastward wind speed at 3pm local time v10_3PM 10-metre above ground northward wind speed at 3pm local time The second part of the name is the General Circulation Model (GCM) applied: Name Translation gfdlcm21 GFDL CM2.1 miroc3_2_medres MIROC 3.2 (medres) mpi_echam5 MPI ECHAM5 ncep NCEP The third, and final, part of the tarball name is the year range that the results relate to: 1961-2000, 1971-2000, 2001-2040 and 2041-2099 Data format and extent Inside each of the tarball files is a collection of NetCDF files covering each simulation that constitutes the year range (12 simulations for each year). A similar naming protocol is used for the NetCDF files with a two digit extension added to the year for each of the simulations for that year (e.g 01-12). The spatial coverage of the NetCDF files is shown in the bounding box extents as shown below. Max X: -9.92459297180176 Min X: -50.0749073028564 Max Y: 155.149784088135 Min Y: 134.924812316895 The cell size is 0.15 degrees by 0.15 degrees (approximately 17 km square at the equator) The data is stored relative to the WGS 1984 Geographic Coordinate System. The GCMs were forced with the Intergovernmental Panel on Climate Change (IPCC) A2 emission scenario as described in the IPCC Special Report on Emissions Scenarios (SRES) inputs for the future climate. The GCM results were then downscaled from a 2 degree cell resolution by CSIRO using their Cubic Conformal Atmospheric Model (CCAM) to the 0.15 degree cell resolution. Use This data was used within the Rockhampton Project to identify the future climate changes based on the IPCC A2 SRES emissions scenario. The relative difference of the current climate GCM results to the future climate results was applied to the results of higher resolution current climate natural hazard modelling. Refer to GeoCat # 75085 for the details relating to the report and the 59 attached ANZLIC metadata entries for data outputs.

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.

Abstract for a Poster for the CO2CRC Symposium 2013: Atmospheric tomography is a CO2 quantification and localisation technique that uses an array of sampling points and a Bayesian inversion method to solve for the location and magnitude of a CO2 leak. Knowledge of a normalized three-dimensional dispersion plume is required in order to accurately model a leak using many meteorological parameters. A previous small scale (~20 m) study using a high precision Fourier Transform Infrared found that the emission rate was determined to within 3% of the actual release rate and the localisation within 1 m of the correct position. The technique was applied during the CO2CRC Otway Stage 2B residual saturation and dissolution test in August-October 2011. A network of eight independent CO2 sensors (Vaisala GMP343 CO2 probes) were positioned at distances ranging from 154 to 473 m from the well. A 3D sonic anemometer within the measurement area collected wind turbulence data. The results of the study indicate that, through careful data processing, measurements from the reasonably inexpensive (but lower accuracy and lower precision) CO2 sensor array can provide useful data for the application of atmospheric tomography. Results have found that the low precision of the sensors over time becomes a problem due to sensor drift. A reference measurement of CO2 helps to resolve this problem and improves the perturbation signal during data processing. Preliminary inversion modeling results will be shown to show the best estimation of locating a CO2 leakage source for the Otway Stage 2B residual saturation and dissolution test. CO2CRC Symposium 2013, Hobart

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.

Results from the first pass application of the tomography technique using low accuracy sensors is presented and limitations of the sensors and technique discussed. BUll. Seismol. Soc. AM.

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.

Deployment of Unmanned Aerial Vehicle during surface CO2 release experiments at the Ginninderra greenhouse gas controlled release facility H. Berko (CO2CRC, Geoscience Australia), F. Poppa (The Australian National University), U. Zimmer (The Australian National University) and A. Feitz (CO2CRC, Geoscience Australia) Lagrangian stochastic (LS) forward modelling of CO2 plumes from above-surface release experiments conducted at the GA-CO2CRC Ginninderra controlled release facility demonstrated that small surface leaks are likely to disperse rapidly and unlikely to be detected at heights greater 4 m; this was verified using a rotorcraft to map out the plume. The CO2 sensing rotorcraft unmanned aerial vehicle (RUAV) developed at the Australian National University, Canberra, is equipped with a CO2 sensor, a GPS, lidar and a communication module. It was developed to detect and locate CO2 gas leaks; and estimate CO2 concentration at the emission source. The choice of a rotor-craft UAV allows slower flight speeds compared to speeds of a fixed-wing UAV; and the electric powered motor enables flight times of 12 min. In experiments conducted at the Ginninderra controlled release facility, gaseous CO2 (100 kg per day) was released from a small diffuse source located in the middle of the paddock, and the RUAV was flown repeatedly over the CO2 source at a few meters height. Meteorological parameters measured continuously at the site at the time of the flight were input in the LS model. Mapped out horizontal and vertical CO2 concentrations established the need to be close to the ground in order to detect CO2 leakage using aerial techniques. Using the rotorcraft as a mobile sensor could be an expedient mechanism to detect plumes over large areas, and would be important for early detection of CO2 leaks arising from CCS activities.