An unprecedented arctic ozone depletion event during spring 2020 and its impacts across Europe

The response of the ozone column across Europe to the extreme 2020 Arctic ozone depletion was examined by analyzing ground-based observations at 38 European stations. The ozone decrease at the northernmost site, Ny-Ålesund (79°N) was about 43% with respect to a climatology of more than 30 years. The magnitude of the decrease declined by about 0.7% deg−1 moving south to reach nearly 15% at 40°N. In addition, it was found that the variations of the ozone column at each of the selected stations in March-May were similar to those observed at Ny-Ålesund but with a delay increasing to about 20 days at mid-latitudes with a gradient of approximately 0.5 days deg−1. The distributions of reconstructed ozone column anomalies over a sector covering a large European area show decreasing ozone that started from the north at the beginning of April 2020 and spread south. Such behavior was shown to be similar to that observed after the Arctic ozone depletion in 2011. Stratospheric dynamical patterns in March–May 2011 and during 2020 suggested that the migration of ozone-poor air masses from polar areas to the south after the vortex breakup caused the observed ozone responses. A brief survey of the ozone mass mixing ratios at three stratospheric levels showed the exceptional strength of the 2020 episode. Despite the stronger and longer-lasting Arctic ozone loss in 2020, the analysis in this work indicates a similar ozone response at latitudes below 50°N to both 2011 and 2020 phenomena

Carbon Nanomaterials in Electrochemical Detection

High surface-to-volume ratio, high conductivity and electrocatalytic properties are some of the most interesting characteristics of carbon nanomaterials. Such exceptional properties have found a strong application in the field of electrochemical sensing. In this chapter we present the great relevance of the introduction of carbon nanomaterials, such as carbon nanotubes and graphene, for the development of new electrochemical sensors and biosensors. The possibility to exploit carbon nanomaterials for direct electrochemical sensing is illustrated. Furthermore, the easy modification of carbon materials with biomolecules enables the development of sophisticated and ultra-sensitive electrochemical sensors and biosensors for a plethora of important analytes and biomolecules, from DNA to cancer biomarkers. The possibility of coupling nanocarbon-based electrochemical sensors as detectors in separation techniques is briefly introduced. The most typical applications are described

Tectonics, mineralisation and regolith evolution of the West African Craton

Studies of mafic dyke swarms may simultaneously provide information on the mechanical, geochemical, geochronological and magnetic environments at the time of their formation. The mafic intrusive history of different cratons can also be potentially used to unravel their assembly into their current configuration. The identification and classification of dykes is a first step to all these studies. Fortunately, even in regions with poor outcrop, we can use the strong magnetic response of mafic dykes to identify and map their extent. In West Africa the first maps of mafic dyke distribution were made over 40 years ago, but there are still large areas where there are almost no published data. In this paper we present a significantly updated map of mafic dykes for the West Africa Craton based in large part on new interpretations of the regional airborne magnetic database. This map includes the locations of over three thousand dykes across the craton, which locally shows several orientation clusters that provide a minimum estimate for the total number of dyke swarms in this region. Whilst we will have to wait until systematic dating of the different swarms is completed, we can demonstrate that there is a long and complex history of mafic magmatism across the craton, with up to 26 distinct dyke swarms mapped based according to their orientation. The mapping and dating of these swarms will provide key constraints on the assembly of the fragments that make up the modern continents

A Spatial Data-Driven Approach for Mineral Prospectivity Mapping

Mineral prospectivity mapping is a crucial technique for discovering new economic mineral deposits. However, detailed knowledge-based geological exploration and interpretations generally involve significant costs, time, and human resources. In this study, an ensemble machine learning approach was tested using geoscience datasets to map Cu-Au and Pb-Zn mineral prospectivity in the Cobar Basin, NSW, Australia. The input datasets (magnetic, gravity, faults, electromagnetic, and magnetotelluric data layers) were chosen by considering their association with Cu-Au and Pb-Zn mineralization patterns. Three machine learning algorithms, namely random forest (RF), support vector machine (SVM), and maximum-likelihood (MaxL) classification, were applied to the input data. The results of the three algorithms were ensembled to produce Cu-Au and Pb-Zn prospectivity maps over the Cobar Basin with improved classification accuracy. The findings demonstrate good agreement with known mineral occurrence points and existing mineral prospectivity maps developed using the weights-of-evidence (WofE) method. The ability to capture training points accurately and the simplicity of the proposed approach make it advantageous over complex mineral prospectivity mapping methods, to serve as a preliminary evaluation technique. The methodology can be modified with different datasets and algorithms, facilitating the investigations of mineral prospectivity in other regions and providing guidance for more detailed, high-resolution geological investigations

The (U-Th)/He Chronology and Geochemistry of Ferruginous Nodules and Pisoliths Formed in the Paleochannel Environments at the Garden Well Gold Deposit, Yilgarn Craton of Western Australia: Implications for Landscape Evolution and Geochemical Exploration

Ferruginous nodules and pisoliths that cap deeply weathered profiles and transported cover are characteristic of the Yilgarn Craton, Western Australia. Here we show how ferruginous nodules and pisoliths formed in the paleochannel sediments during Miocene can be used to locate buried Au mineralization. Three types of ferruginous nodules and pisoliths were identified in paleochannel sediments and saprolite, representing different parent materials and environments covering the Garden Well Au deposit: (i) ferruginous nodules formed in saprolite on the flanks of the paleochannel (NSP), (ii) ferruginous pisoliths formed in the Perkolilli Shale in the middle of the paleochannel (PPS) and (iii) ferruginous nodules formed in the Wollubar Sandstone at the bottom of the paleochannel (NWS). The appearance, mineralogy and geochemistry of ferruginous nodules and pisoliths vary according to their origin. The PPS and NWS are goethite-rich whereas NSP is a mixture of goethite and hematite which make them all suitable for (U–Th)/He dating. The average age of goethite in the NSP is 14.8 Ma, in the NWS is 11.2 Ma and in the PPS is 18.6 and 14 Ma. The goethite ages in ferruginous nodules and pisoliths are thought to be younger than the underlying saprolite (Paleocene-Eocene) and were formed in different environmental conditions than the underlying saprolite. Anomalous concentrations of Au, As, Cu, Sb, In, Se, Bi, and S in the cores and cortices of the NWS and the PPS reflect the underlying Au mineralization, and thus these nodules and pisoliths are useful sample media for geochemical exploration in this area. These elements originating in mineralized saprolite have migrated both upwards and laterally into the NWS and the PPS, to form spatially large targets for mineral exploration