Weather Episodes Research Articles

Dual stress, equivalent harm? hypothesizing on the type of interactions between waterlogging and high temperature

Episodes of extreme weather, such as high temperatures and heavy rains causing waterlogging, have been becoming more frequent due to climate change, posing risks to crops and reducing growth and yield. While the impact of these stresses has been individually studied, there is a significant gap in understanding their combined effects within the same growing season. There were only 15 studies in the rigorous literature addressing the combined impact of high temperatures and waterlogging. None explicitly examined whether these combined effects were additive (penalties close to the sum of the individual penalties), synergistic (more severe penalties), or antagonistic (less severe penalties). We aimed to propose a sound hypothesis on the most likely type of interaction between these two stressors. Reviewing the scarce literature we found, against expectations, that antagonistic interactions were most common, followed by cases of additive effects, with synergistic interactions being rare. Notably, while the primary concern of virtually all studies was the impact on crop yield, most of them focused exclusively on leaf-level traits, whose responses did not correlate well with yield responses. This preliminary analysis provides solid roots for hypothesizing that waterlogging and high temperatures interact antagonistically; i.e., that plants might develop some resilience when exposed to one stress, potentially reducing the impact of the other. Should this hypothesis be accepted, considering not only physiological traits but also, and mainly, yield in major crops, there would be a less pessimistic view on the expected outcome of the increased frequency of crops being exposed to combined high temperature and waterlogging.

Evaluating Ionospheric Total Electron Content (TEC) Variations as Precursors to Seismic Activity: Insights from the 2024 Noto Peninsula and Nichinan Earthquakes of Japan

This study provides a comprehensive investigation into ionospheric perturbations associated with the Mw 7.5 earthquake on the Noto Peninsula in January 2024, utilizing data from the International GNSS Service (IGS) network. Focusing on Total Electron Content (TEC), the analysis incorporates spatial mapping and temporal pattern assessments over a 30-day period before the earthquake. The time series for TEC at the closest station to the epicenter, USUD, reveals a localized decline, with a significant negative anomaly exceeding 5 TECU observed 22 and 23 days before the earthquake, highlighting the potential of TEC variations as seismic precursors. Similar patterns were observed at a nearby station, MIZU, strengthening the case for a seismogenic origin. Positive anomalies were linked to intense space weather episodes, while the most notable negative anomalies occurred under geomagnetically calm conditions, further supporting their seismic association. Using Kriging interpolation, the anomaly zone was shown to closely align with the earthquake’s epicenter. To assess the consistency of TEC anomalies in different seismic events, the study also examines the Mw 7.1 Nichinan earthquake in August 2024. The results reveal a prominent negative anomaly, reinforcing the reliability of TEC depletions in seismic precursor detection. Additionally, spatial correlation analysis of Pearson correlation across both events demonstrates that TEC coherence diminishes with increasing distance, with pronounced correlation decay beyond 1000–1600 km. This spatial decay, consistent with Dobrovolsky’s earthquake preparation area, strengthens the association between TEC anomalies and seismic activity. This research highlights the complex relationship between ionospheric anomalies and seismic events, underscoring the value of TEC analysis as tool for earthquake precursor detection. The findings significantly enhance our understanding of ionospheric dynamics related to seismic events, advocating for a comprehensive, multi-station approach in future earthquake prediction efforts.

Environmental displacement and political instability: Evidence from Africa

Does environmental displacement provoke political instability? Though migration has long been considered an intermediary in the causal path between environmental change and political upheaval, the relationship remains theoretically underdeveloped and evidence has been limited. This article examines the impact of displacement caused by sudden-onset natural hazards on disruptive antigovernment events including armed conflict, protests and violent riots. It leverages the new Environmental Displacement Dataset (EnDis), an original dataset that identifies quantities of human movement in response to six types of sudden-onset natural hazards in Africa from 1990 to 2017, including floods, storms, wildfires, landslides, earthquakes and volcanic activity. The results of the analyses show that while environmental displacement is not associated with civil war onset or protests, it does increase the incidence of attacks by armed non-state actors and violent riots. Importantly, these destabilizing effects occurr primarily (1) in the context of displacement driven by floods and storms, and (2) when levels of displacement are well above average. Collectively, these findings portend deepening security crises and violent political upheaval as climate change drives more frequent episodes of extreme weather and excessive environmental displacement.

Diel metatranscriptomes capture cyanobacteria-dominated Lake Erie community response to episodic events.

Here, we report on the raw and coassembled metatranscriptomes of 39 Lake Erie surface (1.0 m) water samples collected over a 2-day diel period encompassing episodic weather and bloom events. Preliminary taxonomic annotations and read mappings revealed that Microcystis spp. accounted for up to ~47% of the transcriptionally active community.

Impact of INSAT‐3D land surface temperature assimilation via simplified extended Kalman filter‐based land data assimilation system on forecasting of surface fields over India

AbstractThe land surface temperature (LT) is a crucial variable that governs the energy and radiation budget of the earth's atmosphere and influences land‐atmosphere interactions. The LT plays a crucial role mainly in the short‐range forecast of a numerical weather prediction (NWP) model. The primary research goal in this research work undertaken is to assess the impact of assimilation of LT data from the Indian satellite (INSAT‐3D) into the NCMRWF global NWP model (NCUM) through a simplified Extended Kalman Filter (sEKF) land data assimilation system (LDAS), particularly important as there are few screen‐level observations over the region. A dedicated stand‐alone pre‐processing system has been designed to prepare LT observations in a compatible format for the land surface assimilation system. The approach for LT data assimilation from the INSAT‐3D satellite reduces the uncertainty associated with the initial state of LT analysis while simultaneously improving the accuracy of forecasts of near surface atmospheric variables. An observing system experiment (OSE) was carried out during both the summer (May) and winter (February) months by assimilating the INSAT‐3D LT data in a coupled land‐atmosphere analysis‐forecast system. The results obtained from the OSE demonstrate that the use of INSAT‐3D LT data improves the forecast skill of both maximum and minimum temperature over India, particularly in areas characterized by higher LT variability. The improvement is pronounced in forecasts of maximum (minimum) temperature during “Boreal” summer (“Boreal” winter) season. The verification scores also indicate that the incorporation of INSAT LT data substantially improves the NCUM model's forecast performance. By assimilating LT, the mean error of maximum and minimum temperature forecasts in India was decreased, accompanied by enhanced forecast accuracy within a time frame of approximately 24 h. The scores for the verification measures, specifically the Probability of Detection (POD), demonstrate a ~15% improvement in both the forecasts for maximum and minimum temperatures. This improves the temperature prediction as well as the ability to forecast intense weather episodes like cold spells and heat waves.

Survival of Calliphora vicina (Diptera: Calliphoridae) embryos under cold temperature conditions: forensic implications.

Most blow flies (Diptera: Calliphoridae) species are sarcosaprophagous during the larval stage, primarily feeding on the soft tissues of carcasses during the early stages of decomposition, making them valuable forensic indicators for minimum post-mortem interval (minPMI) estimations. Like other insects, their developmental rates are strongly influenced by the environmental temperature. Although several studies have examined the influence of temperature on the development of different blow fly species, the impact of cold temperatures remains largely unstudied, despite its potential forensic implications. The present study investigates the effect of three cold temperatures (0, -2.5 and -5°C) on the survival of Calliphora vicina embryos of five different ages (0%, 20%, 40%, 60% and 80% of the total embryonic development) and two exposure times (6 and 24 h). Our results revealed significant differences in egg survival at the earliest embryonic stages (0% and 20% of the total embryonic development), resulting in high mortality rates. While at 20% of the total embryonic development high mortality was only observed under -5°C, at 0% of the total embryonic development high mortality rates were observed at all the temperatures tested. Although C. vicina embryos demonstrate tolerance to cold temperatures once they have completed the first 20% of the total embryonic development, potentially mitigating the impact of cold weather events, the possibility of minPMI underestimations due to the death of the first egg batches should not be disregarded. Additionally, considering that the embryonic development stages may last for several days under low temperatures, caution should be taken in the analysis of entomological evidence if a cadaver is discovered following cold weather episodes.

Relevant landscape components in a large urban green space in Oporto (Portugal)

Landscape components are essential in the design and fruition of any urban green space (UGS). This is particularly relevant considering the growth rate of the urban population worldwide, the increase in the number and intensity of severe weather episodes due to climate change, and the relevance of UGSs for global human well-being, as highlighted by the United Nations in their Sustainable Development Goals. This study examines users’ perceptions of UGSs regarding the importance of landscape components, which can influence users’ preferences for UGS use. The research was conducted in a major urban park subdivided into 10 landscape units in Oporto, Portugal. The paper uses information gathered through face-to-face surveys from stationary park users (n = 500) engaged in diverse activities, through which 13 landscape elements were assessed for their relevance in determining choice of location. The results show significant differences between the assessed landscape units at the user level for all socio-demographic variables, with the exception of the gender variable. Significant differences between landscape units were also identified in terms of the relevance attributed to the different landscape components. Exploratory factor analysis identified five main factors influencing user preferences: comfort and security (including vegetation density, tranquillity of space, availability of shade, good maintenance, and forest coverage), landscape diversity (diversity of open spaces, diversity of flora and fauna, and presence of shrubs), water presence, recreational facilities, and open spaces for activities. The results also highlight an issue related to distributional justice regarding the assessed study area. Our results have relevant implications for the design and management of UGSs. We propose diverse actions, addressing issues related to the balance between open spaces and rich greenery, multifunctional design, shade coverage, maintenance, forest coverage, vegetation diversity, the incorporation of water features, and the provision of recreational facilities.

Plant nutrient stoichiometry appears out of sync from soil: Increasing influences of changing climate on the grassland in inner Mongolia, China

Extremes in weather episodes seem to be the new normal. We need to better understand how changing climatic conditions alter plant growth in grasslands, especially macro nutrient uptake and stoichiometry. However, few studies have examined how warmer/colder or wetter/drier climates influence the nutrient coupling between plants and soils at the ecosystem level. Here, we investigated the changes in carbon (C), nitrogen (N), and phosphorus (P) concentrations and their stoichiometric ratios in plants and soils from 65 grassland sites along a geographic gradient in northern China. Results showed that soil C, N and P were negatively correlated with temperature and aridity. Plant N was positively correlated with temperature and aridity, but plant P was negatively correlated with temperature and aridity. Plant C had no significant relationship with either aridity or temperature. Both temperature and aridity were positively correlated with C:N, but negatively correlated with C:P and N:P in soils. The ratio of plant C:N was negatively correlated with aridity, while plant C:P was positively correlated with temperature. Plant N:P was positively correlated with temperature and aridity. Our findings imply that the often-found positive relationships between plant and soil nutrients at one site might not apply to a broad geographic scale with varying climatic conditions, likely because of the “dilution effect” and disparate plant nutrient utilization strategies. It is conceivable that rapid climate shifts and the resulting changes in element availability, turnover rates, absorption, and use efficiency might cause desynchrony of C, N, and P cycles between plants and soils.

Прогноз сильной жары в Красноярске с использованием региональной модели WRF-ARW

The reasons for the occurrence of a severe heatwave in Krasnoyarsk have been studied, and the accuracy of the forecasts of the WRF-ARW regional model has been assessed. Four episodes of hot weather in 2020, 2021, and 2023 have been analyzed. The heatwave in June 2023 was especially intense and met the criteria for a severe weather event. All examined cases were associated with the intense advection of warm tropical air in the leading edge of the upper-air trough. The formation of the urban heat island has been investigated, and its intensity in the nighttime was found to be 6.5°C. During daytime hours, the heat island was weaker than at nighttime. It has been determined that on the second day of forecasting, the WRF-ARW model accurately reproduces the urban heat island and the impact of the Yenisei River, although it underestimates the predicted amplitude of daily temperature variations. The absolute error in air temperature predictions for the time moments close to the time of daily maximum temperatures was 2.6°C (33 hours of model time).

Optimizing thermal insulation in building facades: An examination of human-environment dynamics in Nanjing city, Eastern Asia

The external building walls are significant in mitigating adverse weather conditions. Current research on the thermal insulation of exterior walls often overlooks crucial factors such as human comfort, seasonal changes and environmental dynamics. This study introduced a performance evaluation approach for external walls that considered the human thermal zone, annual air temperature and solar radiation. Taking Nanjing City as a case study, the thermal insulation performance of five distinct types of building exterior walls was investigated. The findings highlight the impact of various insulated wall systems on thermal insulation. While different insulated walls exhibited significant variations in effectiveness during extreme weather episodes, these variations were minor over the course of the year. Analysis revealed a spectrum of performance for insulated exterior walls, ranging from excellent to poor: Outer Insulated Wall > Inside Insulated Wall = Sandwich Insulated Wall = Self-Insulated Wall > Mortar-Insulated Wall. The disparity in thermal insulation performance amongst four wall types was minimal, with the mortar-insulated wall demonstrating the lowest performance. The highest temperature recorded for the mortar-insulated wall surpassed 32.2°C over 68 days. This research contributes insights into the nuanced performance of various insulated walls, paving the way for decision-making in climate resilience strategies.

Long-term (bio)deterioration of Fe-containing and Fe-depleted sandstones: An experimental insight into biotic and abiotic interactions

Long-term experimental (bio)weathering revealed that Fe-rich sandstone was more susceptible to biodeterioration as compared to Fe-depleted sandstone. Leaching data combined with surface observations indicated higher susceptibility of goethite (FeOOH) than hematite (Fe2O3) to dissolution. Organic-rich weathering conditions were found to have a larger impact on sandstones as compared to inorganic weathering. Element release from the mineral lattice can be largely enhanced by organic conditions affecting dissolution of hematite cement and changing stoichiometric proportions of elements initially bound in matrix and cement minerals. This study highlights that long-term episodes of biotic and abiotic weathering constitute key factors affecting susceptibility of sandstones to degradation processes.

Influence of rapid vertical mixing on bacterial community assembly in stratified water columns

Water column mixing homogenizes thermal and chemical gradients which are known to define distribution of microbial communities and influence the prevailing biogeochemical processes. Little is however known about the effects of rapid water column mixing on the vertical distribution of microbial communities in stratified reservoirs. To address this knowledge gap, physicochemical properties and microbial community composition from 16 S rRNA amplicon sequencing were analyzed before and after mixing of vertically stratified water-column bioreactors. Our results showed that α-diversity of bacterial communities decreased from bottom to surface during periods of thermal stratification. After an experimental mixing event, bacterial community diversity experienced a significant decrease throughout the water column and network connectivity was disrupted, followed by slow recovery. Significant differences in composition were seen for both total (DNA) and active (RNA) bacterial communities when comparing surface and bottom layer during periods of stratification, and when comparing samples collected before mixing and after re-stratification. The dominant predicted community assembly processes for stratified conditions were deterministic while such processes were less important during recovery from episodic mixing. Water quality characteristics of stratified water were significantly correlated with bacterial community diversity and structure. Furthermore, structural equation modeling analyses showed that changes in sulfur may have the greatest direct effect on bacterial community composition. Our results imply that rapid vertical mixing caused by episodic weather extremes and hydrological operations may have a long-term effect on microbial communities and biogeochemical processes.

Role of Weather Parameters on Quality Seed Production

Weather and climate are important factors deciding the growth of any crop. Meteorologists and seed technologist view the weather as a dominant element influencing yield and acreage behaviour of crops. The meteorological inputs, unlike other inputs such as land, labour, high-yielding variety (HYV) seeds, fertilizers, pesticides, etc. is a direct input in seed production. The functional relationship between weather and yield is as much complicated as the term ‘weather’ itself. Occurrence of abnormal weather episodes during the growing season or during critical development stages may hamper growth processes resulting in yield reduction. Optimum temperature is the balanced heat requirement for the crop since lower or higher temperature results in abnormal effect of the crop growth. When the temperature goes below the minimum or the base level it is said that the physiology will be reduced or even nil. Similarly, when the temperature goes above the maximum the metabolic activity is enormous leading to the scorching or burning effect. The range of wavelength is a part of electromagnetic spectrum of the radiant energy which includes short wave, x-rays and g rays, long radio waves. The electromagnetic spectrum comprises of U-V, visible, IR wavelength which together transmits 90% of energy. Precipitation in any forms say rainfall, snow, fog, mist, dew, etc is important for the crop growth in relation to the seed production. Because the requirement of water for a plant growth is fulfilled naturally by precipitation. However, the effect is more contemplated in tropical countries like India. Amount of water vapour present in the atmosphere at a given time to the same atmosphere under saturation is termed as relative humidity. The VPD namely Vapour Pressure Deficit which is the difference between the pressure exerted by an atmosphere at a given condition to the same at atmosphere at hundred per cent saturation. That means the VPD is the prime cause for the transpiration of the crop plants. Seed production in efficient manner is a challenge in today’s context in correlation to weather parameters. The sowing window is to be adjusted accordingly so that all the growth phases coincides with favourable weather conditions and the crop is having an opportunity to produce quality seeds. The farm shall have wind breaks and shelter belts to enable suitable microclimate for crop production. Weather cannot be changed but managed by knowing before its occurrence termed as weather forecasting.

Discriminant Analysis for Severe Storm Environments in South-Central Brazil

Abstract Severe storms produce hazardous weather phenomena, such as large hail, damaging winds, and tornadoes. However, relationships between convective parameters and confirmed severe weather occurrences are poorly quantified in south-central Brazil. This study explores severe weather reports and measurements from newly available datasets. Hail, damaging wind, and tornado reports are sourced from the PREVOTS project from June 2018 to December 2021, while measurements of convectively induced wind gusts from 1996 to 2019 are obtained from METAR reports and from Brazil’s operational network of automated weather stations. Proximal convective parameters were computed from ERA5 reanalysis for these reports and used to perform a discriminant analysis using mixed-layer CAPE and deep-layer shear (DLS). Compared to other regions, thermodynamic parameters associated with severe weather episodes exhibit lower magnitudes in south-central Brazil. DLS displays better performance in distinguishing different types of hazardous weather, but does not discriminate well between distinct severity levels. To address the sensitivity of the discriminant analysis to distinct environmental regimes and hazard types, five different discriminants are assessed. These include discriminants for any severe storm, severe hail only, severe wind gust only, and all environments but broken into “high” and “low” CAPE regimes. The best performance of the discriminant analysis is found for the “high” CAPE regime, followed by the severe wind regime. All discriminants demonstrate that DLS plays a more important role in conditioning Brazilian severe storm environments than other regions, confirming the need to ensure that parameters and discriminants are tuned to local severe weather conditions.

How Blackouts during Heat Waves Amplify Mortality and Morbidity Risk.

The recent concurrence of electrical grid failure events in time with extreme temperatures is compounding the population health risks of extreme weather episodes. Here, we combine simulated heat exposure data during historical heat wave events in three large U.S. cities to assess the degree to which heat-related mortality and morbidity change in response to a concurrent electrical grid failure event. We develop a novel approach to estimating individually experienced temperature to approximate how personal-level heat exposure changes on an hourly basis, accounting for both outdoor and building-interior exposures. We find the concurrence of a multiday blackout event with heat wave conditions to more than double the estimated rate of heat-related mortality across all three cities, and to require medical attention for between 3% (Atlanta) and more than 50% (Phoenix) of the total urban population in present and future time periods. Our results highlight the need for enhanced electrical grid resilience and support a more spatially expansive use of tree canopy and high albedo roofing materials to lessen heat exposures during compound climate and infrastructure failure events.

Impacts of Extreme Space Weather Events on September 6th, 2017 on Ionosphere and Primary Cosmic Rays

The strongest X-class solar flare (SF) event in 24th solar cycle, X9.3, occurred on 6 September 2017, accompanied by earthward-directed coronal mass ejections (CMEs). Such space weather episodes are known to cause various threats to human activities ranging from radio communication and navigation disturbances including wave blackout to producing geomagnetic storms of different intensities. In this study, SFs’ ionospheric impacts and effects of accompanied heliospheric disturbances on primary cosmic rays (CR) are investigated. This work offers the first detailed investigation of characteristics of these extreme events since they were inspected both from the perspective of their electromagnetic nature, through very low frequency (VLF) radio waves, and their corpuscular nature of CR by multi-instrumental approach. Aside data recorded by Belgrade VLF and CR stations, data from GOES and SOHO space probes were used for modeling and analysis. Conducted numerical simulations revealed a significant change of ionospheric parameters (sharpness and effective reflection height) and few orders of magnitude increase of electron density. We compared our findings with those existing in the literature regarding the ionospheric response and corresponding parameters. In addition, Forbush decrease (FD) magnitude, corrected for magnetospheric effect, derived from measurements, and one predicted from power exponents used to parametrize the shape of energetic proton fluence spectra at L1 were compared and found to be in good agreement. Presented findings could be useful for investigation of atmospheric plasma properties, particles’ modeling, and prediction of extreme weather impacts on human activities.

El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach

AbstractWe examine the predictive value of El Niño and La Niña weather episodes for the subsequent realized variance of 16 agricultural commodity prices. To this end, we use high‐frequency data covering the period from 2009 to 2020 to estimate the realized variance along realized skewness, realized kurtosis, realized jumps, and realized upside and downside tail risks as control variables. Accounting for the impact of the control variables as well as spillover effects from the realized variances of the other agricultural commodities in our sample, we estimate an extended heterogeneous autoregressive (HAR) model by means of random forests to capture in a purely data‐driven way potentially nonlinear links between El Niño and La Niña and the subsequent realized variance. We document such nonlinear links, and that El Niño and La Niña increase forecast accuracy, especially at longer forecast horizons, for several of the agricultural commodities that we study in this research.

Monitoring of high temperature weather episodes with satellite data

INSAT-3D/3R Geosatellites are in orbit at 74 and 82 °E positins oerating in staggring mode of 15 minute temporal frequency providing contineous coverage in high spatial domain throgh 6 channel Imager. Satellite derived geophysical parameters like Outgoing Long wave Radiation (OLR), Land Surface Temperature (LST) and Upper Trpospheric Humidity etc are found to very useful in monitoring the high temperature weather episodes affecting almost entie country like Punjab, Hariyam Rajastham Uttar Pradesh (UP), Bihar, Madhra Pradesh (MP)P, , Maharastra, Andhra Paradesh (AP) , Telengana, Tamilnadu Orissa etc starting from mid of March-2022. The actual temperatures in the above said areas pesrsisting above normal ( ~ 4 to 7 C) from Mid March to Mid April-2022 and caued heat wave conditiions in most of the places of the country. The persisteny of the prevaling heat wave conditions is not only related to surface features but also upper air anticyclonic circulations and sinking of dry air over the affected areas. The entire feedback cycle from lower to middle ttroposphere operating with dry air mass (Northerly) almost entire Northwest , Central and parts of South (Maharastra, AP and Telengana) and keep the areas warm and above normal temperature range. The eastward moving systems also not reaching to lower northern latutudes and moving away and keeping away misture laden winds.
 This paper brought out the role of INSAT-3D/3R satellite derived products in monitoring such high temperature episodes. Such type of weather events blended with the support of climatologial features of prevailing weather systems of the season can be utilized in forecasting and its persistence over the area. It is seen from the study that, the OLR vales threshold ranges from 330 -380 watt /m2 in pockets of warmer temperatures or suffering from heat wave conditions. Similarly, the Land surface temperature and UTH values 306 -325 °K & 05-25 % respectively. The IPWV values in mm are also varies from 2-12 mm during mid-March to mid-April-2022.
 
 The satellite and climatological information can be clubbed together up to village level to help the society and disaster management authorities at state /district level in advance of such high impact weather events. This study is done with limited data sets and in future, it will be carrid out for larger doimain and a suitable the long period avarage (LPA) of past INSAT data (daily, monthly, seasonal), so that areawise thresholds can be generated from almost for entire Indian domain.

Characterization and genesis of supergene karstic vanadium ores in the Djebba Pb–Zn district (Triassic Diapirs zone, North Eastern Tunisia)

The Djebba district hosts hypogene Pb–Zn sulfides and two successive stages of supergene Pb–Zn–Fe–V mineralization. This study mainly focuses on the supergene karstic vanadium mineralization of Jebel Goraa deposit. The hypogene Pb–Zn mineralization is considered to have been formed during Late Miocene (Alpine Orogeny) by Mississippi-Valley-Type (MVT) brines, similar to that proposed for many other Pb–Zn ore deposits of the Diapirs zone in Northern Africa. During the Late Neogene-Pleistocene, several episodes of uplift and erosion enabled the exhumation and karstification of the Early Eocene host rocks, and spatially related hypogene Pb–Zn-(Fe) sulfides, their subsequent weathering, and the formation of supergene ores. Vanadium mineralization is developed in karst cavities filled with oxidized ores (goethite, smithsonite and hemimorphite) and argillaceous materials (smectite). The paragenesis of supergene ores reveals two successive stages of deposition: 1) early supergene weathering with formation of Fe-bearing carbonates in turn oxidized to goethite, smithsonite, hemimorphite, and cerussite; 2) late supergene weathering with deposition of Pb–Zn vanadate minerals (vanadinite, descloizite, and vanadinite-pyromorphite intermediate compositions), minor mimetite and late calcite.Vanadium, phosphorous and probably chlorine of the vanadate ores are inferred to have originated from the immature organic matter of Early Eocene country rocks (Tmax <435 °C and TOC average 3.4 wt%) by descending low-temperature aqueous solutions. Pb, Zn and minor As were derived from primary Pb–Zn sulfides undergoing oxidation. Genesis of supergene vanadium ores is genetically related to post-Miocene uplifting-related weathering episodes, controlled by tectono-morphological and climatic evolution following the Alpine orogeny. The formation of the vanadium mineralization spans through the Late Miocene to Holocene. However, with paleoclimatic considerations it could be generally confined to the Middle Pliocene. Genetically, the supergene vanadium ores of Djebba Pb–Zn district belong to the vanadate ores type, which have been reported in other areas of southern and northern Africa (e.g., Namibia and Morocco). The association of vanadium, particularly in highly fractured and faulted zones with high levels of immature organic matter and spatially close to surface or near-surface MVT Pb–Zn ore deposits, can be used as an exploration tool for new vanadium-bearing deposits.

Survey of per- and polyfluoroalkyl substances (PFAS) in surface water collected in Pensacola, FL

As the persistence of per- and polyfluoroalkyl substances (PFAS) become a global concern, information about the occurrence and characteristics of PFAS in estuarine and marine ecosystems is poorly represented. In this study, the presence of 51 PFAS were monitored in the Pensacola Bay System (PBS), Florida, USA. Due to the presence of many potential PFAS sources in close proximity to the PBS (e.g., military bases, industries, airports and several firefighting stations), the distribution and concentration of PFAS in this estuarine environment provides insights into the fate of these complex compounds as well as the possible impacts on coastal systems. Surface water was collected and analyzed from 45 different sites via Strata-X-AW cartridge extractions and ultra-high pressure liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analysis. Recoveries for many PFAS (13/51) were >60% (mean 77 %), with relative standard deviations below 20%, except for N-methylperfluoro-1-octanesulfonamidoacetic acid (N-MeFOSAA) (22%). Of the perfluoroalkyl carboxylic acids (PFCAs), which comprised the majority of PFAS detected: perfluorooctanoic acid (PFOA) and perfluorohexanoic acid (PFHxA) were present in all samples; however, perfluoropentanoic acid (PFPeA) was the individual PFAS with the highest concentration of this group (51.9 ng.L−1, at site 81). The PFAS detected at the highest concentrations were perfluoroalkyl sulfonic acids (PFSA), with perfluorooctane sulfonic acid (PFOS) having the highest detected concentration (269 ng.L−1, at site 81). At all sites, at least eight or more PFAS were quantified. Past and current use of PFAS-containing materials and their fate in areas surrounding military bases, airports, and industries, require more in-depth monitoring efforts to better determine the need for regulation, management, and/or remediation. Here, sites located close to areas suspected of PFAS use had elevated concentrations. For example, one coastal location near an airfield had a ΣPFAS of 677 ng.L−1. Expansion from these ongoing efforts will focus on assessment of PFAS-related effects in local wildlife and evaluating the distribution of PFAS at these “hotspot” sites during large episodic weather events, a critically understudied phenomenon regarding PFAS and vulnerable coastal environments.