Using the wind multiplier code (https://pid.geoscience.gov.au/dataset/ga/82481) and an appropriate source of classified terrain data, wind multipliers for all of Queensland at (approximately) 25 metre resolution were created. The wind multipliers have been used to guide impact assessments as part of the Severe Wind Hazard Assessment for Queensland.

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.

Geoscience Australia and the CO2CRC operate a controlled release facility in Canberra, Australia, designed for simulating subsurface emissions of CO2 by injecting gas into a horizontal well. Three controlled release experiments were conducted at this site during 2012-2013, over 7-9 week periods, to assess and develop near-surface monitoring technologies for application to carbon dioxide geological storage sites (Feitz et al., 2014). A key well-established technique for characterizing surface CO2 emission sources from controlled release sites or natural CO2 seeps is soil flux surveys. The technique is often considered as the benchmark technique for characterizing a site's emissions or as a baseline for comparing other measurement techniques, but has received less attention with regards to its absolute performance. The extensive soil gas surveys undertaken during Release 1 (Feb-May 2012) and Release 3 (Oct-Dec 2013) are the subject of this paper. Several studies have highlighted factors which can have an effect on soil flux measurements, including meteorological influences such as air pressure and wind speed, which can increase or suppress soil fluxes (Rinaldi et al. 2012). Work at the Canberra controlled release site has highlighted the influence groundwater has on the spatial distribution of fluxes.). In addition, there are several different methods available for inverting soil flux measurements to obtain the emission rate of a surveyed area. These range in complexity from planar averaging to geostatistical methods such as sequential Gaussian simulation (Lewicki et al. 2005). Each inversion technique relies on its own subset of assumptions or limitations, which can also impact the end emissions estimate. Thus deriving a realistic estimate of the total emission rate will depend on both environmental forcing as well as the applied inversion method. An in-house method for soil flux interpolation has been developed and is presented. A cubic interpolated surface is generated from all the measurement points (Figure 1), from which a background linear interpolated surface is subtracted off, leaving the net leakage flux. The background surface is prepared by identifying all background points matching a certain criteria (for this release experiment distance from release well was used) and interpolating only over those points. In these experiments, soil flux surveys were collected on a predefined grid, using an irregular sampling pattern with higher density of samples nearer to the leak hotspots to provide higher spatial resolution in the regions where flux changes most rapidly (Figure 2). The same release rate of 144 kgCO2/day was used for both experiments. It was observed that the surface flux distribution shifts markedly between experiments, most likely a function of seasonal differences (2012 was wet; 2013 was dry) and resulting differences in groundwater depth, soil saturation and the extent of the vadose zone.. The depth to the groundwater measured at monitoring wells in proximity to the release well was 0.85-1.2 m during the 2012 (wet) release whereas it ranged from 1.9-2.3 m during the 2013 (dry) release experiment. The horizontal well is located 2.0 m below the ground surface. This paper explores the performance of soil flux surveys for providing an accurate estimate of the release rate, using a series of soil flux surveys collected across both release experiments. Emission estimates are generated by applying several common inversion methods, which are then compared to the known release rate of CO2. An evaluation as to the relative suitability of different inversion methods will be provided based on their performance. Deviations from the measured release rate are also explored with respect to survey design, meteorological and groundwater factors, which can lead and inform the future deployment of soil flux surveys in a monitoring and verification program.

A metadata report for the atmospheric monitoring station installed in Arcturus, south of Emerald in central Queensland. The station was installed for baseline atmospheric monitoring to contribute to emission modelling spanning 2010-2014. The station included compositional gas analysers, supporting meteorological sensors and an eddy covariance flux tower. The metadata covered in the report include: the major variables measured by each instrument, the data duration and frequency, data accuracy, calibration and corrections, the location the data is stored, and the primary contact for the data.

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.

As part of the controlled release experiments at the Ginninderra test site, an eddy covariance (EC) flux tower was installed. The aim was to determine whether EC was an effective technique for detecting, locating and quantifying CO2 emissions from a leak. The results of this study suggest that EC can be used for leak detection, but application of the technique for quantification exposes problems in the underlying assumptions when dealing with heterogeneous localised leakage systems. The EC tower identified elevated CO2 fluxes from the direction of the leak during the release experiment. The median background CO2 flux from the field was 0.63 ?mol/m2/s, while median leakage CO2 fluxes ranged from 4.57 - 9.11 ?mol/m2/s based on proximity of wind directions to the leak. Once the controlled release stopped, CO2 fluxes from the leak direction quickly returned to background levels.

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.

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<div>An automatic algorithm for classifying wind gust events has been developed at Geoscience Australia, utilizing 1-minute weather observations from Automatic Weather Stations (AWS). This algorithm employs a comprehensive dataset of wind, temperature, dew point, and pressure measurements within a two-hour timeframe centred on the peak wind gust.&nbsp;&nbsp;</div><div> The classification methodology effectively segregates wind gust events into convective and non-convective categories. Initial development entails a subset of stations, employing visual classification verified by contemporaneous observer reports and weather radar data, to create a robust training dataset. The algorithm, based on the analysis of almost 1000 visually-classified events, demonstrates the capability to classify over 150,000 events in a matter of minutes.&nbsp;</div><div> Utilizing wind gust events from past 20 years via our algorithm, the spatial distribution, diurnal cycle and seasonal variation are investigated across Australia. Moreover, a comparative analysis of spatial and temporal disparities, along with radar characteristics, has been conducted for convective and non-convective gust events. Finally, the extreme values of wind gust events, including the 1% annual exceedance probability wind speed (using the Generalized Pareto Distribution) across Australia is shown in this presentation. &nbsp;</div> Presented at the 30th Conference of the Australian Meteorological and Oceanographic Society (AMOS) 2024

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