Search Results (24)

The contagious COVID-19 disease not only brought about a global health crisis but also a disruption in the global economy. The uncertainty levels regarding the impact of the disease increased volatility. This study analyses stock market volatility and Economic Policy Uncertainty (EPU) of South Africa (SA) with that of the United States of America (USA) and Brazil, Russia, India, and China (BRIC) during the COVID-19 pandemic. The study aims to analyse volatility spillovers from a developed market (USA) to emerging markets (BRIC countries) and also to examine the causality between EPU and stock returns during the COVID-19 pandemic. By employing the GARCH-in-Mean model from a sample of daily returns of national equity market indices from 1 January 2020 to 31 March 2022, SA and China are shown to be the most volatile during the pandemic. By using the diagonal Baba, Engle, Kraft, and Kroner (BEKK) model to analyse spillover effects, evidence of spillover effects from the US to the emerging countries is small but statistically significant, with SA showing the strongest impact from US market shocks. From the Granger causality test, Brazil’s and India’s equity markets are shown to be highly sensitive to changes in EPU relative to the other countries. Full article

This study presents a global aerosol climatology derived from six years (October 2018–October 2024) of the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observations, using a U-Net Convolutional Neural Network (CNN) machine learning algorithm for Cloud–Aerosol Discrimination (CAD). Despite ICESat-2’s design primarily as an altimetry mission with a single-wavelength, low-power, high-repetition-rate laser, ICESat-2 effectively captures global aerosol distribution patterns and can provide valuable insights to bridge the observational gap between the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) missions to support future spaceborne lidar mission design. The machine learning approach outperforms traditional thresholding methods, particularly in complex conditions of cloud embedded in aerosol, owing to a finer spatiotemporal resolution. Our results show that annually, between 60°S and 60°N, 78.4%, 17.0%, and 4.5% of aerosols are located within the 0–2 km, 2–4 km, and 4–6 km altitude ranges, respectively. Regional analyses cover the Arabian Sea (ARS), Arabian Peninsula (ARP), South Asia (SAS), East Asia (EAS), Southeast Asia (SEA), the Americas, and tropical oceans. Vertical aerosol structures reveal strong trans-Atlantic dust transport from the Sahara in summer and biomass burning smoke transport from the Savanna during dry seasons. Marine aerosol belts are most prominent in the tropics, contrasting with earlier reports of the Southern Ocean maxima. This work highlights the importance of vertical aerosol distributions needed for more accurate quantification of the aerosol–cloud interaction influence on radiative forcing for improving global climate models. Full article

A seasonal climatology of the diurnal cycle of precipitation (DCP) and the assessment of its observed trend since the beginning of the 21st century using the IMERG product are performed for South America (SA). Its high spatial–temporal resolution ($\mathsf{\Delta }x=0.1^{\circ }$, $\mathsf{\Delta }t=0.5$ h) enables the examination of the fine-scale features of the DCP associated with the complex physical characteristics of SA. Using 20 years of precipitation rate data, diurnal and semi-diurnal scale processes are analyzed through harmonic analysis. Diurnal metrics—including the hourly mean precipitation rate, normalized amplitude, and phase—are employed to quantify the DCP. The results indicate that large-scale mechanisms, such as the South American Monsoon System (SAMS), seasonally modulate the DCP. These mechanisms in combination with local factors (e.g., land use, topography, and water bodies) influence the timing of peak and intensity of precipitation rates. Cluster analysis identifies regions with homogeneous DCP; however, some distant regions are classified as homogeneous, suggesting that local-scale physical processes triggering precipitation onset operate similarly across these regions (e.g., thermally induced local circulations). The trend analysis of the DCP reveals that, over the past 20 years, the tropical region of SA has undergone changes in the intensity and hourly distribution of this fine-scale climate variability mode. This trend is heterogeneous in space and time and is possibly associated with land-use changes. Full article

South America (SA) features diverse land cover types and varied climate conditions, both of which significantly influence the variability of soil moisture (SMO). Obtaining ground-truth measurements for SMO is often costly and labor-intensive, and the limited number of ground SMO stations in SA further complicates the evaluation of satellite-derived SMO products. In this work, we proposed an approach that integrates some statistical methods to assess the reliability of Soil Moisture Active Passive (SMAP), the H113 dataset from the Advanced Scatterometer (ASCAT), and Soil Moisture and Ocean Salinity (SMOS) satellite-derived SMO products in SA from 14 May 2015 to 31 December 2016. The integrated methods are error metrics (correlation (R), bias, and ubiased root mean square error (ubRMSE)), Triple Collocation Method (TCM), and Hovmöller diagrams. ERA5 and GLDAS-Noah SM products were used as references for validation. The quality of SMO products was assessed by considering environmental variables, including land cover, vegetation density, and precipitation, within the different climate zones of SA. The results presented that SMAP overall outperforms SMOS and ASCAT, with the highest average correlation (0.55 with GLDAS and 0.61 with ERA5), slight average bias (−0.058 with GLDAS and −0.014 with ERA5), and lowest average ubRMSE (0.045 with GLDAS and 0.041 with ERA5). In arid, semi-arid, and moderate vegetation regions, the SMAP satellite outperforms SMOS and ASCAT, achieving better statistics values with GLDAS and ERA5 datasets, and achieving low error variance and high S/N in the TCM analysis. While the ASCAT H113 product showed good performance, which makes it a good alternative to SMAP, it still has limitations in more dense vegetation regions. SMOS showed the lowest performance across SA, especially in the Amazon basin. The Amazon basin emerges as a critical region where all SMO products displayed a significant SMO variability; however, SMAP showed slightly better results than ASCAT and SMOS. In the absence of ground truths, the proposed approach provides a better evaluation of satellite SMO products. Meanwhile, it provides new spatiotemporal statistical insights into satellite SMO retrieval performance evaluation within diverse climate zones of SA. This research provides valuable guidance for improving SMO monitoring and agricultural management in tropical and semi-arid ecosystems. Full article

The energy transition requires significant amounts of critical raw materials, with demand projected to continue increasing. Analyses indicate that the supply of these materials will fall short of the requirements for the energy transition plans based on renewable energy sources. To address this challenge, it is essential to examine the global value chains of critical raw materials and their intermediates, identifying the risks linked to concentrating downstream processes in countries that may not operate under market-oriented principles. Such countries could become “price makers” on international markets, influencing costs and availability. This article focuses on copper, a key raw material for the energy transition, and explores its global value chains in detail. It highlights the risks associated with copper extraction in regions with the largest identified deposits, such as South America and Africa, as well as challenges related to smelting and refining, which are predominantly carried out in China. Additionally, the article presents an analysis of the operations of KGHM Polska Miedź S.A., one of Europe’s largest copper producers, headquartered in Poland but also active in North and South America. Full article

Stroke is the second leading cause of death and disability in Latin America; however, few epidemiological studies have been conducted in South America. An observational study was conducted to analyze trends in stroke mortality in South American (SA) countries. Age-standardized mortality rates and proportional mortality due to stroke in the populations of SA countries between 1990 and 2019 were assessed by extracting data from the Global Burden of Disease 2019 study. Joinpoint regression models were employed to identify trends in the annual percentage change in mortality rates for each segment. Considering the data collected over the 30 years that were studied, the age-standardized stroke mortality trend decreased in Argentina (−1.6%), Uruguay (−0.6%), Brazil (−0.5%), Guyana (−0.5%), and Bolivia (−0.4%), while Venezuela (+1.6%) and Suriname (+1.0%) showed an increasing trend. The proportional stroke mortality trend decreased in Argentina (−1.7%), Paraguay (−0.9%), Uruguay (−0.7%), Guyana (−0.7%), Brazil (−0.5%), and Chile (−0.5%), whereas Bolivia (+1.0%), Suriname (+0.6%), and Peru (+0.4%) exhibited an increasing trend. The trends in stroke mortality between 1990 and 2019 demonstrated considerable variability. While most SA countries experienced significant decreases in stroke mortality trends, Venezuela and Suriname showed increases in age-standardized mortality rates, and Bolivia, Suriname, and Peru exhibited increases in proportional mortality rates. No decreasing stroke mortality trend was observed in the segment after the last joinpoint, highlighting the need for improvement in prevention and treatment. Full article

This pioneering study evaluates the digital divide and advances in virtual education (VE) and e-learning research in the Global South Countries (GSCs). Using metadata from bibliographic and World Bank data on research and development (R&D), we conduct quantitative bibliometric performance analyses and evaluate the connection between R&D expenditures on VE/e-learning research advances in GSCs. The results show that ‘East Asia and the Pacific’ (EAP) spent significantly more on (R&D) and achieved the highest scientific literature publication (SLP), with significant impacts. Other GSCs’ R&D expenditure was flat until 2020 (during COVID-19), when R&D funding increased, achieving a corresponding 42% rise in SLPs. About 67% of ‘Arab States’ (AS) SLPs and 60% of citation impact came from SLPs produced from global north and other GSCs regions, indicating high dependence. Also, 51% of high-impact SLPs were ‘Multiple Country Publications’, mainly from non-GSC institutions, indicating high collaboration impact. The EAP, AS, and ‘South Asia’ (SA) regions experienced lower disparity. In contrast, the less developed countries (LDCs), including ‘Sub-Sahara Africa’, ‘Latin America and the Caribbean’, and ‘Europe (Eastern) and Central Asia’, showed few dominant countries with high SLPs and higher digital divides. We advocate for increased educational research funding to enhance innovative R&D in GSCs, especially in LDCs. Full article

The unique P-band synthetic aperture radar (SAR) instrument, BIOMASS, is scheduled for launch in 2024. This satellite will enhance the estimation of subcanopy topography, owing to its strong penetration and fully polarimetric observation capability. In order to conduct global-scale mapping of the subcanopy topography, it is crucial to calibrate systematic errors of different strips through interferometric SAR (InSAR) DEM (digital elevation model) block adjustment. Furthermore, the BIOMASS mission will operate in repeat-pass interferometric mode, facing the atmospheric delay errors introduced by changes in atmospheric conditions. However, the existing block adjustment methods aim to calibrate systematic errors in bistatic mode, which can avoid possible errors from atmospheric effects through interferometry. Therefore, there is still a lack of systematic error calibration methods under the interference of atmospheric effects. To address this issue, we propose a block adjustment model considering atmospheric effects. Our model begins by employing the sub-aperture decomposition technique to form forward-looking and backward-looking interferograms, then multi-resolution weighted correlation analysis based on sub-aperture interferograms (SA-MRWCA) is utilized to detect atmospheric delay errors. Subsequently, the block adjustment model considering atmospheric effects can be established based on the SA-MRWCA. Finally, we use robust Helmert variance component estimation (RHVCE) to build the posterior stochastic model to improve parameter estimation accuracy. Due to the lack of spaceborne P-band data, this paper utilized L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR data, which is also long-wavelength, to emulate systematic error calibration of the BIOMASS mission. We chose climatically diverse inland regions of Asia and the coastal regions of South America to assess the model’s effectiveness. The results show that the proposed block adjustment model considering atmospheric effects improved accuracy by 72.2% in the inland test site, with root mean square error (RMSE) decreasing from 10.85 m to 3.02 m. Moreover, the accuracy in the coastal test site improved by 80.2%, with RMSE decreasing from 16.19 m to 3.22 m. Full article

Gridded precipitation (PRP) data have been largely used in diagnostic studies on the climate variability in several time scales, as well as to validate model results. The three most used gauge-based PRP datasets are from the Global Precipitation Climatology Centre (GPCC), University of Delaware (UDEL), and Climate Research Unit (CRU). This paper evaluates the performance of these datasets in reproducing spatiotemporal PRP climatological features over the entire South America (SA) for the 1901–2015 period, aiming to identify the differences and similarities among the datasets as well as time intervals and areas with potential uncertainties involved with these datasets. Comparisons of the PRP annual means and variances between the 1901–2015 period and the non-overlapping 30-year subperiods of 1901–1930, 1931–1960, 1961–1990, and the 25-year subperiod of 1991–2015 for each dataset show varying means of the annual PRP over SA depending on the subperiod and dataset. Consistent patterns among datasets are found in most of southeastern SA and southeastern Brazil, where they evolved gradually from less to more rainy conditions from 1901–1930 to the 1991–2015 subperiod. All three datasets present limitations and uncertainties in regions with poor coverage of gauge stations, where the differences among datasets are more pronounced. In particular, the GPCC presents reduced PRP variability in an extensive area west of 50° W and north of 20° S during the 1901–1930 subperiod. In monthly time scale, PRP time series in two areas show differences among the datasets for periods before 1941, which are likely due to spurious or missing data: central Bolivia (CBO), and central Brazil (CBR). The GPCC has less monthly variability before 1940 than the other two datasets in these two areas, and UDEL presents reduced monthly variability before 1940 and spurious monthly values from May to September of the years from 1929 to 1941 in CBO. Thus, studies with these three datasets might lead to different results depending on the study domain and period of analysis, in particular for those including years before 1941. The results here might be relevant for future diagnostic and modelling studies on climate variability from interannual to multidecadal time scales. Full article

Very little is known on high mountain tropical lakes of South America. Thus, the main motivation of this research was obtaining base bathymetric data of 119 tropical lakes of the Cajas National Park (CNP), Ecuador, that could be used in future geomorphological studies. Eleven interpolation methods were applied with the intention of selecting the best one for processing the scattered observations that were collected with a low-cost fishing echo-sounder. A split-sample (SS) test was used and repeated several times considering different proportions of available observations, selected randomly, for training of the interpolation methods and accuracy evaluation of the respective products. This accuracy was assessed through the use of empirical exceedance probability distributions of the mean absolute error (MAE). A single best interpolation method could not be identified. Instead, the study suggested six better-performing methods, including the complex methods Kriging (ordinary), minimum curvature (spline), multiquadric, and TIN with linear interpolation but also the much simpler methods natural neighbour and nearest neighbour. A sensitivity analysis (SA), considering several data error magnitudes, confirmed this. This advocated that sophisticated interpolation methods do not always produce the best products as geomorphological characteristics of the study site(s) together with observation data characteristics are likely to play important roles in their performance. As such, this type of assessment should be carried out in any terrestrial mapping of bathymetry that is based on the interpolation of scattered observations. Upon the analysis of the relative hypsometric curves of the 119 study lakes, they were classified into three average form categories: convex, concave, and mixed. The separated accuracy analysis of these three groups of lakes did not help in identifying a single best method. Finally, the interpolated bathymetries of 114 of the study lakes were incorporated into the best DEM of the study site by equalising their elevation reference systems. It is believed that the resulting enhanced DEM could be a very useful tool for a more appropriate management of these very beautiful but fragile high mountain tropical lakes. Full article

Globally, greater than 30% of waste is disposed of in some form of landfill, and it is estimated that annual waste-related emissions will increase by up to 76% by 2050. Emissions arising from fossil fuel-derived products and waste disposal in landfills have prompted the development of alternative technologies that utilize renewable resources. Biomass feedstock is being investigated globally to produce renewable fuels and chemicals. Globally, crop-based biomass and waste biomass are the major feedstocks for chemical production, and the market value of crop-based biomass is expected to increase at the fastest rate. South America, Europe, and North America are currently the global leaders in renewable or bio-based chemical production. In South Africa (SA), the country is still heavily reliant on landfilling as a waste solution. Wastes from agricultural production processes in SA are considered promising feedstocks for beneficiation opportunities to produce bio-based chemicals. The second-generation (2G) agricultural feedstocks that can be used in SA include fruit waste; sugarcane by-products and waste; forestry, timber, pulp, and paper waste; and invasive alien plants. Fermentation, or “green chemistry” technologies, can be used to convert various feedstocks into bio-based chemicals. Bio-based chemicals may be used as drop-in substitutes for existing petrochemical products, for use in end-user industries such as automotive and transportation, textiles, pharmaceuticals, consumer and home appliances, healthcare, and food and beverages. Bioethanol, specifically, can be used in transport fuel, as feedstock for power generation, as an energy source for fuel cells along with hydrogen, and as feedstock in the chemicals industry. Bio-butanol, an olefin derivative, can be used as a drop-in replacement for petroleum-based butanol in all its applications. Different monomers of bio-based chemicals can be used to produce biopolymers, polyhydroxyalkanoates (PHAs), and polylactic acid (PLA), which are subsequently used to produce bioplastics. A total of 25 bio-based chemicals and the technology used to produce them are summarized in this paper. Overall, bioethanol remains the dominant sugar platform product globally. Drawing on global trends, the potential options for the South African market include bioethanol, n-butanol, acetic acid, and lactic acid. It is estimated that the conversion of 70% of the lignocellulosic biomass available in SA would meet 24% of the country’s liquid fuel requirement as a bioethanol equivalent. The most feasible sources of lignocellulosic biomass or waste for beneficiation in SA are generated by the agricultural sector, including sugarcane by-products and waste. Taking into consideration the abundance of lignocellulosic biomass, adequate market segment sizes, and socio-economic factors, it is apparent that there are potential opportunities to investigate the co-production of bioethanol with lactic acid or other bio-based chemicals on an industrial scale. Full article

Drought events are critical environmental threats that yield several socioeconomic impacts. Such effects are even more relevant for South America (SA) since different activities essential for the continent, such as agriculture and energy generation, depend highly on water resources. Thus, this study aimed to evaluate future changes in precipitation and hydrological drought occurrence in SA through climate projections from eight global climate models (GCMs) of CMIP6. To this end, statistical downscaling was applied to the projections obtained using the quantile delta mapping technique, and the method proved to be efficient in reducing systematic biases and preserving GCMs’ trends. For the following decades, the results show considerable and statistically significant reductions in precipitation over most of SA, especially during the austral spring, with the most intense signal under the SSP5-8.5 forcing scenario. Furthermore, GCMs showed mixed signals about projections of the frequency and intensity of drought events. Still, they indicated agreement regarding the increased duration and severity of events over the continent and a substantial proportion of moderate and severe events over most of Brazil during the 21st century. These results can be helpful for better management of water resources by decision-makers and energy planners. Full article

A severe foot-and-mouth disease (FMD) epidemic struck several Egyptian provinces recently, causing significant losses among animals even in vaccinated farms. This study indicated the existence of the newly emerging foot-and-mouth disease virus (FMDV) and first investigated its effect on the Egyptian water buffalo (Bubalus bubalis) and cattle calves in the Beheira province, north Egypt. Twenty tongue epithelial samples from diseased calves in five infected farms were randomly collected, prepared, and propagated using baby hamster kidney-21 (BHK-21) cells. Whole genomic RNA was extracted from the cells of the third passage. A FMDV genome was detected and serotyped using one-step reverse transcription polymerase chain reactions (RT-PCRs). Nucleotide sequencing of the purified serotype-specific PCR bands was performed, and a maximum likelihood phylogenetic tree based on 600 base pairs of VP1 was constructed. The results identified FMDV, serotype A in all infected samples, whereas the serotypes O and SAT2 were negative. The obtained 20 sequences were identical to each other and similar to the newly reported strain in Egypt that belongs to the Europe–South America (Euro–SA) topotype. The epidemiological and clinical parameters associated with such a strain were fully recorded by veterinarians and analyzed in a single infected farm including 70 cattle and buffalo calves. It caused higher peracute mortalities in buffalo (25.7%; 95% CI: 13–43) than in cattle (8.6%; 95% CI: 2–24) calves. Severe clinical signs such as dullness, hypothermia, bradycardia, and cardiac arrhythmia were common to both except in fatal cases, whereas hyperthermia and respiratory signs were prevalent in cattle calves. In conclusion, we first characterized the newly emerging FMDV in the calves of Beheira as more fatal and severe in buffalo than in cattle calves. Full article

This paper addresses the current status and future research and development perspectives associated with technologies to harness offshore renewable energy, including offshore wind, waves, tides, ocean currents, and thermal and salinity gradient, in South America (SA). It focuses on five countries: Argentina, Brazil, Chile, Colombia and Uruguay. At first, a comprehensive survey presents the number of scientific papers classified based on the resource to show the tendency and importance of such subjects in the academic community. Each country’s electricity matrix and grid connection are shown to understand the region’s renewable source participation situation. The potential of offshore renewable resources is addressed by considering the published technical papers in scientific journals. The main conflicts and synergies associated with ocean space utilization are presented by considering the exclusive economic zone of each country. The status of the regulatory frameworks to promote and development of offshore renewable energies is presented. Two sections are dedicated to presenting the active, decommissioned and planned projects, research groups and laboratory infrastructures to develop the technologies. The last section discusses the future perspectives on the development of this sector in SA. It is observed that SA, with more than 25,000 km of coastline, has a great potential for offshore renewable energy; however, so far, these resources have not been explored commercially. Larger investment in the sector, establishing an adequate legal framework and deploying full-scale demonstration projects at sea are necessary for the commercialization of such technologies in SA. Full article

Resilience describes the ability of someone to adapt to adverse life experiences by adjusting to demands with behavioral flexibility. When encountering crisis situations, resilient people typically spring back emotionally with increased strength and internal composure. Measuring resilience is important for assessing the ability of adolescents to respond to adverse situations. The objective of this study was to evaluate the psychometric performance of the Spanish version of the Connor-Davidson Resilience Scale (CD-RISC) © for South America (CD-RISC-25^SA) in a population of vulnerable Peruvian adolescents. This study used a cross-sectional design to measure sociodemographic variables and resilience. Participants were 451 adolescents living in a shelter in Lima, Perú. Face and content validity were established by expert panel, construct validity was evaluated with exploratory and confirmatory factor analysis, and internal consistency was assessed with Cronbach’s alpha. The analysis resulted in a four-dimensional model with 22 items explaining almost 27% of the variance with a Cronbach’s alpha of 0.90. The dimensions included self-confidence and self-trust from previous experiences, internal resources to cope with difficult situations, personal competence and tenacity, and self-regulation with external resources. Two of the 3 items eliminated from the instrument were related to the original dimension “spirituality influences” which may have been incorrectly translated and adapted without equivalence of meaning for cross-cultural research. The CD-RISC-25^SA is not a stable multidimensional instrument for measuring resilience across the cultures and contexts of countries. However, the instrument appears to be stable for measuring resilience as a single dimension. For measuring resilience in the context of Peru, a four-dimensional model with 22 items was validated. Variations in the psychometric properties of translated instruments may result from not establishing the equivalence of meaning for each item before performing cross-cultural research. Researchers need to search for a more precise understanding of resilience as a universal concept transferable across borders and through translations. Full article