Spatiotemporal assessment of pathogenic Leptospira in subtropical coastal watersheds.

The World Health Organization classifies leptospirosis as a significant public health concern, predominantly affecting impoverished and unsanitary regions. By using the Pensacola Bay System as a case study, this study examines the underappreciated susceptibility of developed subtropical coastal ecosystems such as the Pensacola Bay System to neglected zoonotic pathogens such as Leptospira. We analyzed 132 water samples collected over 12 months from 44 distinct locations with high levels of Escherichia coli (>410 most probable number/100 mL). Fecal indicator bacteria (FIB) concentrations were assessed using IDEXX Colilert-18 and Enterolert-18, and an analysis of water physiochemical characteristics and rainfall intensity was conducted. The LipL32 gene was used as a quantitative polymerase chain reaction (qPCR) indicator to identify the distribution of Leptospira interrogans. The results revealed 12 instances of the presence of L. interrogans at sites with high FIB over various land cover and aquatic ecosystem types. Independent of specific rainfall events, a seasonal relationship between precipitation and elevated rates of fecal bacteria and leptospirosis was found. These findings highlight qPCR's utility in identifying pathogens in aquatic environments and the widespread conditions where it can be found in natural and developed areas.

Interplay of natural and anthropogenic inputs on the groundwater contamination of Beenaganj-Chachura block.

The present research work investigates the impact of natural and anthropogenic inputs on the chemistry and quality of the groundwater in the Beenaganj-Chachura block of Madhya Pradesh, India. A total of 50 groundwater samples were examined for nitrates, fluoride, chlorides, total dissolved solids, calcium, magnesium, pH, total hardness, and conductivity, and their impact on entropy-weighted water quality index and pollution index of groundwater (PIG) was investigated via the response surface methodology (RSM) using the central composite design. According to analytical findings, Ca, Mg, Cl-, SO42-, and NO3- exceed the desired limit and permitted limit set by the Bureau of Indian Standards (BIS) and the World Health Organization (WHO). According to PIG findings, 76, 16, and 8% of groundwater samples, respectively, fell into the insignificant, low, and moderate pollution categories. The regression coefficients of the quadratic RSM models for the experimental data provided excellent results. Thus, RSM provides an excellent means to obtain the optimized values of input parameters to minimize the PIG values.

Mini-Open Dumps in the Paraná River Floodplain: Local Problems with Global Effects.

The growing production of urban solid waste is a structural problem faced by most cities around the world. The proliferation of mini-open dumps (MOD; small spontaneous open-air waste dumps formed in urban and peri-urban areas) on the banks of the Paraná River is particularly evident. During the historical drought (June-December 2021), we carried out sampling campaigns identifying MODs of the Santa Fe River, a secondary channel of the Paraná River. MOD were geolocated, measured, described and classified by origin. The distance to the river and other sensitive places was considered (houses-schools-health facilities). Our results suggested a serious environmental issue associated with poor waste management. MOD were extremely abundant in the study area, being mostly composed of domestic litter. Plastics clearly dominated the MOD composition. Burning was frequently observed as a method to reduce the volume of MOD. We concluded that the proliferation of MOD is a multi-causal problem associated with a failure of public policies and a lack of environmental education.

Can a naturally depauperate Ephemeroptera, Plectoptera and Trichoptera (EPT) fauna track river degradation in south-western Australia?

Freshwater aquatic ecosystems are threatened globally. Biological monitoring is required to deliver rapid and replicable assessment of changes in habitat quality. The Ephemeroptera, Plectoptera, Trichoptera (EPT) index is a globally recognised rapid bioassessment that measures taxa richness of three insect orders whose larvae are considered sensitive to freshwater habitat degradation. South-western Australia contains threatened freshwater ecosystems but has depauperate EPT fauna and high endemism, potentially reducing the capacity of the EPT index to track degradation. This study investigated if EPT species richness, composition or individual species tracked physical or chemical river degradation in three catchments in south-western Australia. We sampled EPT fauna and measured water chemistry, erosion, sedimentation, riparian vegetation cover and instream habitat at 98 sites in the winters of 2007 and 2023. We found 35 EPT taxa across the study area with a median number of species per site of two. EPT species richness had weak positive associations with a composite water quality index and dissolved oxygen and weak negative associations with electrical conductivity and total nitrogen. No association was found between physical and fringing zone degradation measures and EPT species richness. EPT community structure generally did not distinguish between sites with high or low degradation levels. The presence of the mayfly Nyungara bunni tracked salinity, dissolved oxygen and nitrogen levels, but its usefulness as a bioindicator could be limited by its restricted range. This study suggests that the EPT index would need modification or combination with other indices to be a useful rapid bioassessment in south-western Australia.

Creation of an international laboratory network towards global microplastics monitoring harmonisation.

Infrastructure is often a limiting factor in microplastics research impacting the production of scientific outputs and monitoring data. International projects are therefore required to promote collaboration and development of national and regional scientific hubs. The Commonwealth Litter Programme and the Ocean Country Partnership Programme were developed to support Global South countries to take actions on plastics entering the oceans. An international laboratory network was developed to provide the infrastructure and in country capacity to conduct the collection and processing of microplastics in environmental samples. The laboratory network was also extended to include a network developed by the University of East Anglia, UK. All the laboratories were provided with similar equipment for the collection, processing and analysis of microplastics in environmental samples. Harmonised protocols and training were also provided in country during laboratory setup to ensure comparability of quality-controlled outputs between laboratories. Such large networks are needed to produce comparable baseline and monitoring assessments.

Characteristics and risk assessment of potentially toxic elements pollution in river water and sediment in typical gold mining areas of Northwest China.

To assess the concentration characteristics and ecological risks of potential toxic elements (PTEs) in water and sediment, 17 water samples and 17 sediment samples were collected in the Xiyu River to analyze the content of Cr, Ni, As, Cu, Zn, Pb, Cd and Hg, and the environmental risks of PTEs was evaluated by single-factor pollution index, Nemerow comprehensive pollution index, potential ecological risk, and human health risk assessment. The results indicated that Hg in water and Pb, Cu, Cd in sediments exceeded the corresponding environmental quality standards. In the gold mining factories distribution river section (X8-X10), there was a significant increase in PTEs in water and sediments, indicating that the arbitrary discharge of tailings during gold mining flotation is the main cause of PTEs pollution. The increase in PTEs concentration at the end of the Xiyu River may be related to the increased sedimentation rate, caused by the slowing of the riverbed, and the active chemical reactions at the estuary. The single-factor pollution index and Nemerow pollution index indicated that the river water was severely polluted by Hg. Potential ecological risk index indicated that the risk of Hg in sediments was extremely high, the risk of Cd was high, and the risk of Pb and Cu was moderate. The human health risk assessment indicated that As in water at point X10 and Hg in water at point X9 may pose non-carcinogenic risk to children through ingestion, and As at X8-X10 and Cd at X14 may pose carcinogenic risk to adults through ingestion. The average HQingestion value of Pb in sediments was 1.96, indicating that the ingestion of the sediments may poses a non-carcinogenic risk to children, As in the sediments at X8-X10 and X15-X17 may pose non-carcinogenic risk to children through ingestion.

Exploring spatiotemporal distribution characteristics of air quality and driving factors: empirical evidence of 288 cities in China.

Excellent air quality is important for China to achieve high quality economic development. The paper analyses the spatial and temporal distribution characteristics of the air quality index (AQI) in 288 Chinese cities, and further investigates the driving factors affecting air quality using the spatial Durbin model (SDM) based on the panel data of 288 Chinese cities from 2014 to 2021. The results of the study show that: (1) China's air quality level has improved in general, but there are large differences in air quality between regions; (2) China's AQI has significant spatial positive autocorrelation, and the Moran's scatter plot shows a high-high and low-low agglomeration; (3) The driving factors of air quality have different effects, and regional heterogeneity is obvious. Some developed regions in China have already crossed the inflexion point of the environmental Kuznets curve (EKC); promoting industrial upgrading and reducing pollutant emissions can significantly improve urban PM2.5 concentrations; and the "Three-Year Strategy for Conquering the Blue Sky War" policy has lowered the AQI in North China and improved PM2.5 concentrations nationwide. Based on the above findings, the paper puts forward corresponding policy recommendations.

The consistent fuzzy suitability assessment of forest land resources with multi-source heterogeneous data.

In view of the suitability assessment of forest land resources, a consistent fuzzy assessment method with heterogeneous information is proposed. Firstly, some formulas for transforming large-scale real data and interval data into fuzzy numbers are provided. To derive the unified representation of multi-granularity linguistic assessment information, a fuzzy quantitative transformation for multi-granularity uncertain linguistic information is proposed. The proofs of the desirable properties and some normalized formulas for the trapezoidal fuzzy numbers are presented simultaneously. Next, the objective weight of each assessment indicator is further determined by calculating the Jaccard-Cosine similarity between the trapezoidal fuzzy numbers. Moreover, the trapezoidal fuzzy numbers corresponding to the comprehensive assessment values of each alternative are obtained. The alternatives are effectively ranked according to the distance from the centroid of the trapezoidal fuzzy number to the origin. Finally, based on the proposed consistent fuzzy assessment method, the suitability assessment of forest land resources is achieved under a multi-source heterogeneous data setting.

Seasonal studies of aquatic humic substances from Amazon rivers: characterization and interaction with Cu (II), Fe (II), and Al (III) using EEM-PARAFAC and 2D FTIR correlation analyses.

Aquatic humic substances (AHS) are defined as an important components of organic matter, being composed as small molecules in a supramolecular structure and can interact with metallic ions, thereby altering the bioavailability of these species. To better understand this behavior, AHS were extracted and characterized from Negro River, located near Manaus city and Carú River, that is situated in Itacoatiara city, an area experiencing increasing anthropogenic actions; both were characterized as blackwater rivers. The AHS were characterized by 13C nuclear magnetic ressonance and thermochemolysis GC-MS to obtain structural characteristics. Interaction studies with Cu (II), Al (III), and Fe (III) were investigated using fluorescence spectroscopy applied to parallel factor analysis (PARAFAC) and two-dimensional correlation spectroscopy with Fourier transform infrared spectroscopy (2D-COS FTIR). The AHS from dry season had more aromatic fractions not derived from lignin and had higher content of alkyls moities from microbial sources and vegetal tissues of autochthonous origin, while AHS isolated in the rainy season showed more metals in its molecular architecture, lignin units, and polysacharide structures. The study showed that AHS composition from rainy season were able to interact with Al (III), Fe (III), and Cu (II). Two fluorescent components were identified as responsible for interaction: C1 (blue-shifted) and C2 (red-shifted). C1 showed higher complexation capacities but with lower complexation stability constants (KML ranged from 0.3 to 7.9 × 105) than C2 (KML ranged from 3.1 to 10.0 × 105). 2D-COS FTIR showed that the COO- and C-O in phenolic were the most important functional groups for interaction with studied metallic ions.

Monitoring of toxic cyanobacterial blooms in Lalla Takerkoust reservoir by satellite imagery and microcystin transfer to surrounding farms.

Cyanobacterial harmful algal blooms (CyanoHABs) threaten public health and freshwater ecosystems worldwide. In this study, our main goal was to explore the dynamics of cyanobacterial blooms and how microcystins (MCs) move from the Lalla Takerkoust reservoir to the nearby farms. We used Landsat imagery, molecular analysis, collecting and analyzing physicochemical data, and assessing toxins using HPLC. Our investigation identified two cyanobacterial species responsible for the blooms: Microcystis sp. and Synechococcus sp. Our Microcystis strain produced three MC variants (MC-RR, MC-YR, and MC-LR), with MC-RR exhibiting the highest concentrations in dissolved and intracellular toxins. In contrast, our Synechococcus strain did not produce any detectable toxins. To validate our Normalized Difference Vegetation Index (NDVI) results, we utilized limnological data, including algal cell counts, and quantified MCs in freeze-dried Microcystis bloom samples collected from the reservoir. Our study revealed patterns and trends in cyanobacterial proliferation in the reservoir over 30 years and presented a historical map of the area of cyanobacterial infestation using the NDVI method. The study found that MC-LR accumulates near the water surface due to the buoyancy of Microcystis. The maximum concentration of MC-LR in the reservoir water was 160 µg L-1. In contrast, 4 km downstream of the reservoir, the concentration decreased by a factor of 5.39 to 29.63 µgL-1, indicating a decrease in MC-LR concentration with increasing distance from the bloom source. Similarly, the MC-YR concentration decreased by a factor of 2.98 for the same distance. Interestingly, the MC distribution varied with depth, with MC-LR dominating at the water surface and MC-YR at the reservoir outlet at a water depth of 10 m. Our findings highlight the impact of nutrient concentrations, environmental factors, and transfer processes on bloom dynamics and MC distribution. We emphasize the need for effective management strategies to minimize toxin transfer and ensure public health and safety.

Fresh records on Ichthyofaunal diversity of River Panjkora Dir, Khyber Pakhtunkhwa, Pakistan.

This study was designed to assess the ichthyofaunal diversity of River Panjkora, Khyber Pakhtunkhwa, Pakistan. For this purpose, a total of 1189 fish from six different sites were collected along the river and identified using standard keys. The fish collected and identified were representing 38 species, belonging to 7 families. The investigation spanned a year, from July 2021 to May 2022. The most dominant family was Cyprinidae 76% (n=906/1189), followed by Nemacheilidae 5.8% (n=69/1189), Channidae 5.2% (n=62/1189), Sisoridae 5.1% (n=61/1189), Mastacembelidae 4.9% (n=58/1189), Salmonidae 2.6% (n=31/1189) and least was Bagridae 0.17 (n=2/1189). The most abundant speices was Schizothorax plagiostomus with relative density of 16.8. Family Cyprinidae was represented by 21 species, Sisoridae by 7 species, Nemacheilidae by 5 species, Channidae by 2 species, while Bagridae, Salmonidae and Mastacembelidae, were each represented by a single species. PAST 3, XLSTAT and EXCEL 2019 were used for principal component analysis to study correlation of fish diversity and richness. Eigenvalue obtained from Kumrat to Busaq were 3.32, 1.01, 0.80, 0.44, 0.31 and 0.10 respectively. The higher value at Kumrat shows higher diversity. The water quality assessment showed average value of water temperature 10.4 ͦC, pH 7.0, electrical conductivity 184 mg/L, dissolved oxygen 7.9 mg/L, turbidity 43.73 mg/L, total dissolved solids 101 mg/L, total suspended solids 34.72 mg/L, total solids 135.53 mg/L, total alkalinity 75.77 mg/L, total hardness 58.37 mg/L, ammonia 0.46 mg/L, sulphate 26.03 mg/L, chloride 14.67 mg/L, calcium 69.11 mg/L, chromium 0.18 mg/L, copper 0.03, cobalt mg/L 0.04, nickel 0.039 mg/L, lead 0.02 mg/L and Zinc 0.35 mg/L. The findings of this study indicated that most of the physicochemical parameters remained within the acceptable limits throughout the study period. Analysis of fish gut contents included; nymphs, insect larvae, the presence of algae, protozoans and macroinvertebrates in the river ecosystem.

Clustering evaluation of water quality for various classes of in-flow rivers in connected brackish lakes.

Brackish waters and estuaries at the lower reaches of rivers accumulate organic matter and nutrients from various sources in the watershed. Sufficient light and shallow water depth stimulate phytoplankton growth, resulting in a more diversified ecosystem with higher trophic levels. For effective watershed management, it is crucial to characterize the water quality of all rivers, including small and medium-sized ones. Our field survey assessed water quality parameters in 26 inflow rivers surrounding Lakes Shinji and Nakaumi, two consolidated brackish lakes in Japan. The parameters included water temperature, salinity, chlorophyll-a, and nutrients. The study used hierarchical clustering. The Silhouette Index was used to assess clustering outcomes and identify any difficulties in dispersion across clusters. The 26 rivers surrounding Lakes Shinji and Nakaumi were classified into six groups based on their water quality characteristics. This classification distinguishes itself from earlier subjective methods that relied on geographical factors. The new approach identifies a need for improved management of river water quality. The results of the cluster analysis provide valuable insights for future management initiatives. It is important to consider these findings alongside established watershed criteria.

Probabilistic classification of the severity classes of unhealthy air pollution events.

Air pollution events can be categorized as extreme or non-extreme on the basis of their magnitude of severity. High-risk extreme air pollution events will exert a disastrous effect on the environment. Therefore, public health and policy-making authorities must be able to determine the characteristics of these events. This study proposes a probabilistic machine learning technique for predicting the classification of extreme and non-extreme events on the basis of data features to address the above issue. The use of the naïve Bayes model in the prediction of air pollution classes is proposed to leverage its simplicity as well as high accuracy and efficiency. A case study was conducted on the air pollution index data of Klang, Malaysia, for the period of January 01, 1997, to August 31, 2020. The trained naïve Bayes model achieves high accuracy, sensitivity, and specificity on the training and test datasets. Therefore, the naïve Bayes model can be easily applied in air pollution analysis while providing a promising solution for the accurate and efficient prediction of extreme or non-extreme air pollution events. The findings of this study provide reliable information to public authorities for monitoring and managing sustainable air quality over time.

Innovative methods for microplastic characterization and detection: Deep learning supported by photoacoustic imaging and automated pre-processing data.

Plastic products' widespread applications and their non-biodegradable nature have resulted in the continuous accumulation of microplastic waste, emerging as a significant component of ecological environmental issues. In the field of microplastic detection, the intricate morphology poses challenges in achieving rapid visual characterization of microplastics. In this study, photoacoustic imaging technology is initially employed to capture high-resolution images of diverse microplastic samples. To address the limited dataset issue, an automated data processing pipeline is designed to obtain sample masks while effectively expanding the dataset size. Additionally, we propose Vqdp2, a generative deep learning model with multiple proxy tasks, for predicting six forms of microplastics data. By simultaneously constraining model parameters through two training modes, outstanding morphological category representations are achieved. The results demonstrate Vqdp2's excellent performance in classification accuracy and feature extraction by leveraging the advantages of multi-task training. This research is expected to be attractive for the detection classification and visual characterization of microplastics.

New records on toxic cyanobacteria from Brazil: Exploring their occurrence and geography.

Cyanobacterial Harmful Algal Blooms (CyanoHABs) pose a significant threat to communities globally, impacting ecosystems and public health. This study provides an in-depth review of the current state of cyanotoxins and the distribution of CyanoHABs species in Brazil, while also detailing the methods used for their detection. Four hundred and twenty-one incidents were analyzed from 1993 to 2021, compiling cyanotoxin records and toxic CyanoHABs occurrences. The investigation begins with the first detection of microcystins in 1994 and highlights pivotal moments, like the 1996 "Caruaru Syndrome" outbreak. This event encouraged research and updated cyanotoxin-monitoring guidelines. The Brazilian drought period of 2015-2016 exacerbated cyanobacterial growth and saxitoxin levels, coinciding with Zika-related microcephaly. This study delves into methods used for cyanotoxin analysis, including ELISA, bioassays, HPLC, and LC-MS. Additionally, we investigated the toxicity of 37 cyanobacterial strains isolated from various Brazilian environments. Extracts were tested against Artemia salina and analyzed by LC-MS. Results revealed toxicity in extracts from 49 % of cyanobacterial strains. LC-MS results were analyzed using GNPS MS/MS molecular networking for comparing experimental spectra with those of cyanotoxin standards against in-house databases and the existing literature. Our research underscores the variability in cyanotoxin production among species and over time, extending beyond microcystins. LC-MS results, interpreted through the GNPS platform, revealed six cyanotoxin groups in Brazilian strains. Yet, compounds present in 75 % of the toxic extracts remained unidentified. Further research is crucial for fully comprehending the impact of potentially harmful organisms on water quality and public health management strategies. The study highlights the urgent need for continuously monitoring cyanobacteria and the cyanotoxin inclusion of management in public health policies.

Influence of meteorological variables and air pollutants on measurements from automatic pollen sampling devices.

This study examines the influence of meteorological factors and air pollutants on the performance of automatic pollen monitoring devices, as part of the EUMETNET Autopollen COST ADOPT-intercomparison campaign held in Munich, Germany, during the 2021 pollen season. The campaign offered a unique opportunity to compare all automatic monitors available at the time, a Plair Rapid-E, a Hund-Wetzlar BAA500, an OPC Alphasense, a KH-3000 Yamatronics, three Swisens Polenos, a PollenSense APS, a FLIR IBAC2, a DMT WIBS-5, an Aerotape Sextant, to the average of four manual Hirst traps, under the same environmental conditions. The investigation aimed to elucidate how meteorological factors and air pollution impact particle capture and identification efficiency. The analysis showed coherent results for most devices regarding the correlation between environmental conditions and pollen concentrations. This reflects on one hand, a significant correlation between weather and airborne pollen concentration, and on the other hand the capability of devices to provide meaningful data under the conditions under which measurements were taken. However, correlation strength varied among devices, reflecting differences in design, algorithms, or sensors used. Additionally, it was observed that different algorithms applied to the same dataset resulted in different concentration outputs, highlighting the role of algorithm design in these systems (monitor + algorithm). Notably, no significant influence from air pollutants on the pollen concentrations was observed, suggesting that any potential difference in effect on the systems might require higher air pollution concentrations or more complex interactions. However, results from some monitors were affected to a minor degree by specific weather variables. Our findings suggest that the application of real-time devices in urban environments should focus on the associated algorithm that classifies pollen taxa. The impact of air pollution, although not to be excluded, is of secondary concern as long as the pollution levels are similar to a large European city like Munich.

Ecotoxicity assessment of additives in commercial biodegradable plastic products: Implications for sustainability and environmental risk.

Biodegradable plastics have gained popularity as environmentally friendly alternatives to conventional petroleum-based plastics, which face recycling and degradation challenges. Although the biodegradability of these plastics has been established, research on their ecotoxicity remains limited. Biodegradable plastics may still contain conventional additives, including toxic and non-degradable substances, to maintain their functionality during production and processing. Despite degrading the polymer matrix, these additives can persist in the environment and potentially harm ecosystems and humans. Therefore, this study aimed to assess the potential ecotoxicity of biodegradable plastics by analyzing the phthalate esters (PAEs) leaching out from biodegradable plastics through soil leachate. Sixteen commercial biodegradable plastic products were qualitatively and quantitatively analyzed using gas chromatography-mass spectrometry to determine the types and amounts of PAE used in the products and evaluate their ecotoxicity. Among the various PAEs analyzed, non-regulated dioctyl isophthalate (DOIP) was the most frequently detected (ranging from 40 to 212 µg g-1). Although the DOIP is considered one of PAE alternatives, the detected amount of it revealed evident ecotoxicity, especially in the aquatic environment. Other additives, including antioxidants, lubricants, surfactants, slip agents, and adhesives, were also qualitatively detected in commercial products. This is the first study to quantify the amounts of PAEs leached from biodegradable plastics through water mimicking PAE leaching out from biodegradable plastics to soil leachate when landfilled and evaluate their potential ecotoxicity. Despite their potential toxicity, commercial biodegradable plastics are currently marketed and promoted as environmentally friendly materials, which could lead to indiscriminate public consumption. Therefore, in addition to improving biodegradable plastics, developing eco-friendly additives is significant. Future studies should investigate the leaching kinetics in soil leachate over time and toxicity of biodegradable plastics after landfill disposal.

Species-specific eDNA assay development for enhanced box jellyfish risk management in coastal environments.

Human interaction with marine creatures holds both positive and negative dimensions. Coastal communities benefit from marine environments, relying on them for sustenance and livelihoods. Fishing activities support economies, and marine biodiversity contributes to overall ecosystem health. However, challenges like overfishing, habitat destruction, and pollution pose threats to both marine life and human communities. Recently, there has been widespread concern regarding the potential increase in jellyfish populations across global marine ecosystems, attributed mainly to environmental factors such as climate drivers and anthropogenic forces, or their complex interactions. Encounters with hazardous marine species, such as box jellyfish, exemplify the dangers associated with coastal activities. Unintended interactions may lead to stings, injuries, and even fatalities, necessitating proactive measures and advanced technologies. This study addresses the inadequacies of existing measures in preventing box jellyfish incidents by introducing environmental DNA (eDNA) assays for detecting the deadly Chiropsoides buitendijki and focuses on developing qPCR and dPCR-based eDNA assays. Emphasising prevention over treatment, the study establishes a proactive system to assess C. buitendijki distribution across 63 tourist beaches in the Gulf of Thailand. Comparative analysis highlights the superior performance of dPCR over qPCR and traditional surveys. The dPCR experiment yielded positive results for all eDNA samples collected at sites where C. buitendijki had previously been identified. Remarkably, the eDNA testing also detected positive results in 16 additional sample locations where no physical specimens were collected, despite reported jellyfish stings at some of these sites. These findings underscore the precision and efficacy of the proposed eDNA detection technology in the early detection and assessment of box jellyfish distribution. This advancement therefore not only aids ecological research but also serves as a valuable tool for safeguarding public health, providing an early warning system for potential jellyfish encounters. Balancing positive human-marine interactions with effective risk mitigation strategies is crucial for sustainable coexistence, the preservation of marine ecosystems, and human well-being.

Quantum-level investigation of air decomposed pollutants gas sensor (Pd-modified g-C3N4) influenced by micro-water content.

In the electrical industry, there are many hazardous gases that pollute the environment and even jeopardize human health, so timely detection and effective control of these hazardous gases is of great significance. In this work, the gas-sensitive properties of Pd-modified g-C3N4 interface for each hazardous gas molecule were investigated from a microscopic viewpoint, taking the hazardous gases (CO, NOx) that may be generated in the power industry as the detection target. Then, the performance of Pd-modifiedg-C3N4 was evaluated for practical applications as a gas sensor material. Novelly, an unconventional means was designed to briefly predict the effect of humidity on the adsorption properties of this sensor material. The final results found that Pd-modified g-C3N4 is most suitable as a potential gas-sensitizing material for NO2 gas sensors, followed by CO. Interestingly, Pd-modified g-C3N4 is less suitable as a potential gas-sensitizing material for NO gas sensors, but has the potential to be used as a NO cleaner (adsorbent). Unconventional simulation explorations of humidity effects show that in practical applications Pd-modified g-C3N4 remains a promising material for gas sensing in specific humidity environments. This work reveals the origin of the excellent properties of Pd-modified g-C3N4 as a gas sensor material and provides new ideas for the detection and treatment of these three hazardous gases.

Physico-chemical characterisation of irrigation basin waters and inventory study of their algal communities.

To cope with the water shortage in Sous Massa region of Morocco, agricultural producers in the region have resorted to different types of water supply basins, known as "irrigation basins" but the phenomenon of eutrophication has hindered the continuity of agricultural productivity by altering the quality of the water used for irrigation on the one hand, and causing economic damage to agricultural producers due to the clogging of the water pumping network on the other. We began by characterising the physico-chemical quality of the water to determine the causes of its high nutrient content, then we determined the taxonomy of the algal species in the irrigation basins to which we had access. A qualitative study of the water in the irrigation basins in order to better explain the inventory obtained from the taxonomic identification of the algal biomass collected, which proved the existence of new species, not previously identified, characterising the freshwaters of the Moroccan region, is under the scope of this work. The species studied belong mainly to the following groups: green algae (11 genera of Chlorophyta and 7 genera of Charophyta), blue algae (7 genera of Cyanobacteria), brown algae (7 genera of Diatoms), and one genus of Euglenophyta.