This study examines the climatic water availability, defined as precipitation minus potential evapotranspiration (PET), in continental South America during historical (1960–2014) and future (2015–2100) periods. Observed (CRU TS, ERA5) and modeled (CMIP6) data were used, with future projections under the SSP2-4.5 and SSP5-8.5 scenarios derived from an ensemble of five models best representing the continent. To improve the drought analysis, the SNIPE (Standardized Nonparametric Indices of Precipitation and Evaporation) methodology was applied. This method aggregates the data over multiple time scales (1, 3, 6, and 12 months) and uses nonparametric rescaling to produce standardized indices (zero mean, unit variance). Unlike the SPI and SPEI indices, which rely on parametric assumptions that may bias the results if the data deviate from the assumed distributions, SNIPE uses a distribution-free approach, making it a robust tool for drought assessment. Historical data from both the observed and modeled sources show similar water availability patterns: drought in Patagonia, the Atacama, the Central Andes, and the Brazilian northeast and high availability in the Amazon and southeast Brazil. Future projections indicate an expansion and intensification of drought, mainly affecting transition zones such as the Brazilian Cerrado, the edges of the Amazon, the Chaco, and the semiarid areas of the Brazilian northeast, with more pronounced changes under SSP5-8.5. Correlation analyses between SNIPE and various climate indices (AMO, ONI, PDO, SAM, TNA, TSA, and TPI-IPO) reveal that indices such as TPI-IPO, ONI, and TSA play key roles in the water regime dynamics in southeastern South America (including the areas of southern/southeastern Brazil, Paraguay, Uruguay, and northeastern Argentina), a region frequently impacted by floods. These findings underscore SNIPE’s potential to enhance forecasting systems and water resource management strategies.

Sale, situated along the Atlantic Ocean, ranks as the third-largest city in Morocco, characterized by its high demographic density and significant air pollution challenges. The Bouregreg River delineates Sale from Rabat, the capital of Morocco. Key sources of air pollution in Sale include traffic emissions, maritime activities, potteries, fishing, domestic heating, and artisanal operations. From July 2018 to July 2019, we conducted a comprehensive study on ambient PM2.5 concentrations in an urban area of Sale. Using a Dichotomous sampler, we collected PM2.5 samples and employed Total X-Ray Fluorescence to analyze the elemental composition of the collected filters. The results indicated that PM2.5 mass concentrations fluctuated between 3.08 μg/m³ and 49.48 μg/m³, with an average of 17.30 μg/m³. Notably, peak concentrations occurred during winter months, contrasting with lower levels observed in summer. To investigate the influence of atmospheric transport on PM2.5 levels, we applied the HYSPLIT™ model for air mass back-trajectories analysis, identifying four primary transport clusters arriving at the monitoring site in Sale: Iberian Coast (24%), Near Atlantic Ocean (33%), local sources (28%), and Oceanic influences (15%). Seasonal analysis revealed variations in metal concentrations. Elements such as K, Ca, V, Mn, Fe, Ni, Cu, Zn, As, Sr, Ba, and Pb showed elevated levels during winter, while Ti and Cr peaked in autumn. Enrichment Factor (EF) assessments indicated that Ti, Sr, Mn, K, Ca, and Ba predominantly originated from airborne dust (EF < 10). Meanwhile, V, Cu, and Cr exhibited both natural and anthropogenic contributions (10 < EF < 100), while Ni, Zn, and Pb were largely anthropogenic (EF > 100). According to the Morocco National Ambient Air Quality Standard, the annual mean limit for PM2.5 is set at 35 µg/m³, indicating that the average PM2.5 concentration of 17.30 µg/m³ observed in Sale is below this limit, suggesting that while air quality is better than the standard, seasonal spikes could still pose health risks.

Introduction

The United Nations Globally Harmonized System (GHS) of classification and labelling provides specifications for the classification, management, and communication of hazards, crucial for protecting workers and consumers. However, issues and challenges exist in its application, particularly concerning respiratory sensitizers, many of which can become airborne pollutants in occupational settings and in broader environments, where they may engulf entire regions.

Methods

This is a narrative review that assesses relevant GHS documents and internationally accepted methods for determining respiratory sensitizers.

Results

Chemical sensitization is complex and depends on factors like allergen nature, dose, and exposure route, including inhalation. Sensitization initially involves the induction of specialized immunological memory in an individual by exposure to an allergen, followed by elicitation, which is the production of an allergic response following exposure of a sensitized individual to an allergen. Consequently, predictive tests also involve both induction and elicitation, followed by classification as Category 1, 1A or 1B, depending on the evidence. Unfortunately, GHS classification relies heavily on epidemiological data captured retrospectively with diagnostic testing rather than on prospective (predictive) data. Moreover, there are issues regarding the potency of chemicals and absence or presence of no-adverse-effect levels (NOAELs). Accurately assessing airborne exposure to sensitizers can be challenging, especially in complex environments, making it difficult to establish clear dose–response relationships. Lastly, the potential for certain respiratory sensitizers to become airborne and persist in the atmosphere increases the risk of prolonged inhalation exposure, underscoring the necessity for accurate GHS classification.

Conclusion

Challenges exist in interpreting results and accurately classifying sensitizers, potentially underestimating risks associated with airborne exposure. Users of GHS SDSs and labels must be aware of these limitations, particularly concerning inhalation exposure and potential airborne pathways. Further research is needed to improve GHS classification and understanding of the atmospheric behavior of sensitizers.

This study investigates the occurrence of tropical cyclones in the North Indian Ocean region, examining the influence of solar activity on the Quasi-Biennial Oscillation (QBO) and El Niño-Southern Oscillation (ENSO). The primary objective is to assess the impact of QBO and ENSO on tropical cyclone formation. The equatorial QBO anomaly is analyzed across pressure levels ranging from 10 hPa to 70 hPa, with a particular focus on 30 hPa, using data from the Freie Universität Berlin. To establish a correlation, a normalized occurrence rate of tropical cyclones was derived following the methodologies of Sonnemann and Grygalashvyly (2007) and Ekaterina Vorobeva (2019).

Between 1979 and 2017, a total of 389 tropical cyclones formed in the North Indian Ocean, specifically in the Bay of Bengal and the Arabian Sea. This study primarily examines cyclonic activity during the pre-monsoon (May–August) and post-monsoon (October–December) seasons, utilizing data from the India Meteorological Department (IMD). The results indicate that tropical cyclones predominantly occur during the easterly QBO phase, with 24 out of 39 years exhibiting easterly winds and 15 years experiencing westerly winds.

Statistical analyses, including regression analysis, correlation coefficients, and tests of statistical significance, reveal a strong positive correlation between QBO and tropical cyclone activity. Specifically, a correlation coefficient of 0.7 suggests a significant association between QBO variations and cyclone occurrence in this region.

Introduction

Human hair is an excellent biological indicator for assessing human health conditions. It can provide an indication of mineral levels and accumulation of toxic metals resulting from long-term or acute exposure. This study investigates the relationship between the concentration of toxic elements in hair and Body Mass Index (BMI) in adolescents with no environmental or occupational exposure. The latter physiological factor influences the metabolism of both essential and toxic elements in the human body, providing a valuable diagnostic framework for various diseases.

Methodology

Instrumental Neutron Activation Analysis (INAA) was used for a highly sensitive and accurate element determination. The collected samples were pre-treated with acetone and drying before the analysis.

Results

The results obtained suggested the abundance of zinc (Zn) (100 µg g^-1), followed by iron (Fe), and copper (Cu), all with concentrations above 1µg g^-1. A weak positive correlation was found between Zn and K, while magnesium (Mg) levels proportionally increased with BMI (173±129 µg g^-1; 24.0 <BMI < 25.4). Further statistical analyses, including cluster analysis and principal component analysis, suggested low similarity between sulphur (S) and chlorine (Cl), which were indirectly associated with BMI. The data obtained have been studied and discussed with data from an inorganic fraction of particulate matter, PM₁₀ and PM_2.5, registering very low levels of the elements investigated (As = 1.06 ng m^-3, Cr = 3.3 ng m^-3, and Ni = 3.5 ng m^-3 in fine granulometric fractions).

Conclusion

The results provide an important basis for assessing the effects of anthropogenic phenomena, such as atmospheric emissions, in urban areas. Although no significant correlations with BMI were found for any of the elements studied, the findings represent a baseline for further and more comprehensive understanding of the mechanisms of the accumulation or release of toxic elements in the bodies of individuals exposed in relation to BMI.