Sodic amphiboles and pyroxenes from fenites in East Africa

During alkali metasomatism of the country-rock associated with ijolite-carbonatite complexes the development of sodic amphibole and/or pyroxene is characteristic. In this paper, some new chemical analyses of these minerals, together with published analyses from fenites of Kenya, Uganda and Tanzania, include those of co-existing pairs of amphibole and pyroxene. The common amphiboles of the fenites are magnesioarfvedsonites with 100 Mg: Mg+Fe+Mn ranging from 67 to 36. They co-exist with aegirines having 0.75 to 0.89 ions Fe⁺³. Most of these minerals are poor in Ca; co-existing pairs tend to show corresponding increases in Ca and in Fe⁺². In the syenitic fenites of Tororo and Budeda, considered to have formed at higher temperatures, the stable mineral is aegirine-augite. New analyses of richterite, magnesioarfvedsonite and aegirine from carbonate-rich rocks are also presented, and the relation between fenites and carbonatites is discussed.     

Particulate matter geochemistry of a highly industrialized region in the Caribbean:Basis for future toxicological studies

Air pollution has become an important issue,especially in Caribbean urban areas,and,particulate matter(PM)emitted by different natural and anthropogenic sources causes environmental and health issues.In this work,we studied the concentrations of PM₁₀ and PM_2.5 sources in an industrial and port urban area in the Caribbean region of Colombia.PM samples were collected within 48-h periods between April and October 2018 by using a Partisol 2000 i-D sampler.Elemental geochemical characterization was performed by X-ray fluorescence(XRF)analysis.Further,ionic species and black carbon(BC)were quantified by ion chromatography and reflectance spectroscopy,respectively.Using the Positive Matrix Factorization(PMF)receptor model,the contributions of PM sources were quantified.The average concentration of PM₁₀ was 46.6±16.2μg/m³,with high concentrations of Cl and Ca.For PM_2.5,the average concentration was 12.0±3.2μg/m³,and the most abundant components were BC,S,and Cl.The receptor model identified five sources for PM₁₀ and PM_2.5.For both fractions,the contributions of marine sea spray,re-suspended soil,and vehicular traffic were observed.In addition,PM_2.5 included two mixed sources were found to be fuel oil combustion with fertilizer industry emissions,and secondary aerosol sources with building construction emissions.Further,PM₁₀ was found to also include building construction emissions with re-suspended soil,and metallurgical industry emissions.These obtained geochemical atmospheric results are important for the implementation of strategies for the continuous improvement of the air quality of the Caribbean region.     

Accuracy of a pre-trained sentiment analysis (SA) classification model on tweets related to emergency response and early recovery assessment: the case of 2019 Albanian earthquake

Traditionally, earthquake impact assessments have been made via fieldwork by non-governmental organisations (NGO's) sponsored data collection; however, this approach is time-consuming, expensive and often limited. Recently, social media (SM) has become a valuable tool for quickly collecting large amounts of first-hand data after a disaster and shows great potential for decision-making. Nevertheless, extracting meaningful information from SM is an ongoing area of research. This paper tests the accuracy of the pre-trained sentiment analysis (SA) model developed by the no-code machine learning platform MonkeyLearn using the text data related to the emergency response and early recovery phase of the three major earthquakes that struck Albania on the 26th November 2019. These events caused 51 deaths, 3000 injuries and extensive damage. We obtained 695 tweets with the hashtags: #Albania #AlbanianEarthquake, and #albanianearthquake from the 26th November 2019 to the 3rd February 2020. We used these data to test the accuracy of the pre-trained SA classification model developed by MonkeyLearn to identify polarity in text data. This test explores the feasibility to automate the classification process to extract meaningful information from text data from SM in real-time in the future. We tested the no-code machine learning platform's performance using a confusion matrix. We obtained an overall accuracy (ACC) of 63% and a misclassification rate of 37%. We conclude that the ACC of the unsupervised classification is sufficient for a preliminary assessment, but further research is needed to determine if the accuracy is improved by customising the training model of the machine learning platform.

     

Late Pleistocene–Holocene environmental and climatic history of a freshwater paramo ecosystem in the northern Andes

This study presents the first multi-proxy palaeoenvironmental and palaeoclimatic history for northern South America based on the palaeolimnological reconstruction of a pond located in a dry paramo at 3570 masl. During the Last Glacial Maximum (LGM), the study area was under glacial conditions, then during global events Heinrich Stadial 1 (HS1), Bølling–Allerød (BA), and the Younger Dryas (YD), the pond expanded, accumulation rates and proxies for erosion reached the highest values, indicative of humid conditions, with maxima in humidity during the BA and YD. Dry conditions and pond desiccation occurred in the Greenlandian–Northgrippian and by 6010 cal a bp the area was transformed into the mire of today. Comparisons with records from other sites in South America indicate that changes in humidity are most likely controlled by the Intertropical Convergence Zone, mainly during the glacial and postglacial, and by changes in the Pacific Ocean, more pronounced after the YD.     

Spatially distributed rainfall thresholds for the initiation of shallow landslides

The evaluation of the combined influence of rainfall patterns (in terms of mean intensity and duration) and the geomorphological and mechanical characteristics of hillslopes on their stability conditions is a major goal in the assessment of the shallow landslide triggering processes. Geographic Information Systems (GIS) represent an important tool to develop models that combine hydrological and geomechanical analyses for the evaluation of slope stability, as they allow to combine information concerning rainfall characteristics with topographic and mechanical properties of the slopes over wide areas. In this paper, a GIS-based code is developed to determine physically based intensity/duration rainfall thresholds at the local scale. Given the rainfall duration and the local geometric, hydrological and mechanical characteristics of the slopes, the code evaluates the spatial distribution of the minimum rainfall intensity that triggers shallow landslides and debris flows over a given area. The key feature of the code is the capability of evaluating the time t _p required to reach the peak pore pressure head on the failure surface and computing the corresponding critical intensity/duration thresholds based on post-event peak pore pressures. The reliability of the model is tested using a set of one-dimensional analyses, comparing the physically based thresholds obtained for three different slopes with some empirical rainfall thresholds. In a log–log scale, the thresholds provided by the model decrease linearly with increased rainfall duration and they are bracketed by the empirical thresholds considered. Finally, an example of application to a study area of the Umbria region in central Italy is presented, describing the capability of the model of providing site-specific thresholds for different rainfall scenarios.     

A luminescence‐based chronology for the Harletz loess sequence,Bulgaria

The Harletz loess‐palaeosol sequence is located in northwestern Bulgaria and represents an important link between well‐studied loess sequences in eastern Romania and further sites to the west of the Carpathians (e.g. Serbia and Hungary). The aim of this study was to establish a chronostratigraphy of the deposits, using various methods of luminescence dating, together with basic stratigraphical field observations as well as magnetic properties. Luminescence dating was carried out using the quartz fine grain fraction and a SAR protocol, and the feldspar coarse grain fraction, applying the MET‐pIRIR protocol. Due to underestimation of the quartz fine grain fraction in the lower parts of the sequence, the resulting chronology is mainly based on the feldspar ages, which are derived from the stimulation temperature at 150 °C. A comparison with nearby sequences from Serbia, Hungary and Romania, and interpretations obtained through the stratigraphical and sedimentological signature of the sequence, supports the established chronology. Our data suggest that the prominent palaeosol (soil complex) in the upper quarter of the sequence was formed during MIS 5. It would follow that large parts of the Last Glacial loess overlying this palaeosol were probably eroded, and that the thick loess accumulation underlying this soil complex can be allocated to the penultimate glacial (MIS 6). A prominent MIS 6 tephra, which has been reported from other sequences in the area, is also present at Harletz.