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Onshore and offshore site investigations along the dryland tide-dominated De Grey River delta (northwestern Australia) led to the unexpected discovery of the largest yet-known marine ooid shoals in the Indo-Pacific region. Ooids exhibit up to 60 tangential aragonitic laminae that were formed around fluvial sediment grains during the late Holocene. Covering an area >1250 km2, their spatial extent rivals in size individual ooid shoals from the Bahamas. Shoals appear to be spatially linked with the De Grey River, suggesting that fluvial outputs, combined with a macrotidal range, facilitated the precipitation of the ooids. Following their formation, ooids were reworked through tidal and wave processes along the delta. As a result, the delta sedimentary features, including beach ridges, mouth bars, and distributary channels, are composed of ooids.This discovery broadens the range of depositional and climatic environments in which ooids can form and demonstrates that fluvial runoff may not inhibit aragonite precipitation. Such a configuration also provides a unique analogue for ancient ooids found in association with siliciclastic grains and further indicates that the interpretation of typical siliciclastic geomorphologies from geophysical data does not preclude the presence of carbonate grains.

Continental as well as maritime ultrafine particles as cloud condensation nuclei (CCN) are likely initially produced by gas to particle conversion starting with nucleation mode aerosol and slowly (within several hours) growing into CCN sizes. Although these birth and growing processes were well investigated since about 50 years, the source locations, where the anthropogenic fraction of these particles are preferably formed still remain uncertain as well as the strength of individual natural or anthropogenic sources. We present an analysis based on two decades of airborne studies of number and size distribution measurements across Europe, Australia, Mexico and China on nucleation and Aitken mode particles serving as CCN or their precursors. Selected flight patterns allow source apportionment for typical major sources and even a quantitative estimate of their emission rates. Contrary to current global climate model RCP assumptions with decreasing aerosol from 2005 towards the end of the century trends of ultrafine particles and CCN are no longer correlated to sulphur emissions within the last two decades. Nowadays nitrogen and ammonia chemistry is becoming increasingly important for global anthropogenic nanoparticle particle formation and number concentrations. Due to their impact on the hydrological cycle, changes like a slowdown of raindrop production, an increased latent heat flux into the lower free troposphere, an invigoration of torrential rains and a larger water vapour column density might be the consequences. Such recently observed weather patterns are well in agreement with current observations of regional UFP/CCN concentrations and their timely evolution.

Ultrafine particles (UFP) acting as cloud condensation nuclei (CCN) are the driving force behind changing rainfall patterns. Recently observed weather extremes like floods and drought might be due to changing anthropogenic UFP emissions. However, the sources and budgets of anthropogenic primary and secondary particles are not well known. Based on airborne measurements we identified as a major contribution modern fossil fuel flue gas cleaning techniques to cause a doubling of global primary UFP number emissions. The subsequent enhancement of CCN numbers has several side effects. It's changing the size of the cloud droplets and delays raindrop formation, suppressing certain types of rainfall and increasing the residence time of water vapour in the atmosphere. This additional latent energy reservoir is directly available for invigoration of rainfall extremes. Additionally it's a further contribution to the column density of water vapour as a greenhouse gas and important for the infrared radiation budget. The localized but ubiquitous fossil fuel related UFP emissions and their role in the hydrological cycle, may thus contribute to regional or continental climate trends, such as increasing drought and flooding, observed within recent decades.

Classification of outdoor point clouds is an intensely studied topic, particularly with respect to the separation of vegetation from the terrain and manmade structures. In the presence of many overhanging and vertical structures, the (relative) height is no longer a reliable criterion for such a separation. An alternative would be to apply supervised classification; however, thousands of examples are typically required for appropriate training. In this paper, an unsupervised and rotation-invariant method is presented and evaluated for three datasets with very different characteristics. The method allows us to detect planar patches by filtering and clustering so-called superpoints, whereby the well-known but suitably modified random sampling and consensus (RANSAC) approach plays a key role for plane estimation in outlier-rich data. The performance of our method is compared to that produced by supervised classifiers common for remote sensing settings: random forest as learner and feature sets for point cloud processing, like covariance-based features or point descriptors. It is shown that for point clouds resulting from airborne laser scans, the detection accuracy of the proposed method is over 96% and, as such, higher than that of standard supervised classification approaches. Because of artifacts caused by interpolation during 3D stereo matching, the overall accuracy was lower for photogrammetric point clouds (74–77%). However, using additional salient features, such as the normalized green–red difference index, the results became more accurate and less dependent on the data source.

One of the case study sites for the Climate and Clean Air Coalition (CCAC) Methane Science Studies is the coal seam gas (CSG) field in the Surat Basin, Queensland, Australia, where there are over 6000 CSG wells and associated gas and water processing infrastructure. Previous bottom-up estimates suggest that the major source of methane in the region is cattle, not CSG (Katestone, 2018, Luhar et al. 2018).In September 2018, an airborne measurement campaign was undertaken to provide a top-down estimate of regional methane emissions. Modelling of the airborne methane mole fraction data has produced a defensible total methane emissions estimate. However, there are challenges with proportioning the top-down estimates provided by the airborne data, because of adjacent sources with similar d13C-CH4 isotopic chemistry, rapid mixing of adjacent sources and substantial dilution of the plumes at the airborne measurement sampling height. We present how we will overcome these challenges.At each gas production well, tens of thousands of litres of water are produced daily in association with the methane extracted from the coal measures. This water is stored in ponds and is also used as a water supply for cattle feedlots, which are located throughout and adjacent to the CSG wells and processing facilities. Power stations are also located within the CSG field. This arrangement makes it challenging to obtain clean top-down estimates of the emissions from CSG production. Quantifying methane emissions associated with CSG production is further complicated by numerous other sources of methane in the region immediately adjacent to the CSG field. These sources include grazing cattle, abattoirs, more power production facilities, coal mines, wetlands, natural gas seeps, and small urban centres with associated sewage treatment plants and landfills. Grab bag air samples were collected at each of these sources and analysed for d13C-CH4, d13C-CO2 and dD-CH4.The airborne measurement campaign was undertaken under warm daytime spring conditions. This caused rapid uplift and mixing of the methane plumes. The maximum difference between the lowest and highest methane mole fraction from 90 airborne collected grab bag air samples was only 0.03 ppm. Even at this low mole fraction, by implementing quality management protocols we were able to extract trends in the isotope data sets. This presentation will outline the quality management procedures and how the measurements of d13C-CH4, d13C-CO2 and dD-CH4 will be used to assist with methane source attribution.ReferenceKatestone Environmental Pty Ltd (2018) Surat Basin Methane Inventory 2015 - Summary Report. Prepared for CSIRO March 2017 (D15193-11).Luhar, A., Etheridge, D., Loh, Z., Noonan, N., Spencer, D., Day, S. (2018). Characterisation of Regional Fluxes of Methane in the Surat Basin, Queensland. Final report on Task 3: Broad scale application of methane detection, and Task 4: Methane emissions enhanced modelling. Report to the Gas Industry Social and Environmental Research Alliance (GISERA). Report No. EP185211, October 2018. CSIRO Australia.

EMC parameters of complex ICs are unknown. Therefore the simulation of the emission of electronic devices is challenging. The article introduces a method to describe ICs by an equivalent current. It is explained how this current can be determined metrological and used for a calculation of the far field. Any IC can be characterized by an equivalent current. Hence, the equivalent current can be used as a global IC EMC parameter.