Anomalies in radon activity have been discovered and debated by several organizations worldwide during radon monitoring. Based on the theory of neutrino oscillations and the latest results of the study of neutrino oscillation-induced radioactive decay, the material effects of high-energy atmospheric neutrinos oscillating in the atmosphere and their impact on the decay rate of radon have been analyzed. The results show that there is a possibility of Mikheyev-Smirnov-Wolfenstein (MSW) resonance with atmospheric materials when high-energy atmospheric neutrinos propagate oscillations in the atmosphere. This resonance has an excitation effect on radioactive radon and can increase the decay probability of radon. Simultaneously, we demonstrate that the amplitude of radon radioactivity fluctuations is positively correlated with the atmospheric neutrino flux and the intensity (or amplitude) of the MSW resonance. The atmospheric neutrino flux participating in MSW resonance and its oscillation intensity (or amplitude) are primarily influenced by two factors: (1) Air density. When air density increases due to factors like humidity rise or temperature decrease, the atmospheric neutrino flux participating in MSW resonance and the oscillation amplitude both increase (strengthening the signal). (2) Variations in cosmic ray intensity, solar activity, and atmospheric thickness fluctuations can alter the atmospheric neutrino flux, causing the MSW resonance to exhibit oscillation periods similar to those of cosmic ray intensity, solar activity, and lunar tides. Consequently, fluctuations in radon radioactivity correlate with atmospheric temperature, humidity, and solar activity.
Problem addressed: Bangladesh's shipbreaking and recycling industry (SBRI), particularly in Sitakunda, has led to significant environmental degradation due to releasing hazardous heavy metals into soil and seawater. Pollutants such as Arsenic (As), Lead (Pb), Cadmium (Cd), Cobalt (Co), Chromium (Cr), Copper (Cu), Nickel (Ni), and Mercury (Hg) have detrimental effects on marine ecosystems and public health. Bioremediation has recently evolved as a cost-effective and eco-friendly approach for heavy metal removal. This work models the efficiency of bioremediation-based formulas for heavy metal reduction. Experimental approach: Seawater samples were collected from the Sitakundu, Chittagong, shipbreaking yard to assess heavy metal contamination concentration using ICP-MS. Eight toxic heavy metals were identified, and four plant-derived formulations were developed to remove heavy metals. The effectiveness of these formulations in reducing heavy metal concentrations was evaluated through statistical analysis. ANOVA and TUKEY Test, performed in GraphPad Prism v10, confirmed a significant reduction (P < 0.0001). Main results and findings: Formula 4 demonstrated the highest removal efficiency, reducing heavy metals in seawater by 85–93%. While Formulas 1-3 also displayed significant adsorption capabilities, their efficiency was comparatively lower. Mercury (Hg) and Cobalt (Co) exhibited the most pronounced reduction. Across all tested heavy metals, the highest removal occurred within 36 hours. Conclusion: False daisy (Eclipta alba), Aloe vera (Aloe barbadensis), and water hyacinth (Eichhornia crassipes) were identified as the most effective plant species for bioremediation. The developed formulas demonstrate high efficiency, ease of application, and environmental safety, making them viable for large-scale implementation.
Plastics pose serious threats to aquatic environments because of their persistence and non-biodegradability. Microplastics, defined as microscopic, manufactured particles (primary sources) or fragments derived from larger plastic debris (secondary sources), can persist in waterbodies for prolonged periods. Extensive research has been conducted to assess microplastic contamination in marine systems; however, freshwater ecosystems remain underexplored, particularly in Bangladesh. To address this gap, the present study identified, quantified, and characterized microplastics across key waterbodies in and around Dhaka City—Dhanmondi Lake, Ramna Lake, Hatirjheel, Buriganga River, and Turag River—during the winter (dry) and summer (wet) seasons. Collected samples were processed through sieving, wet peroxide oxidation (H₂O₂), and density separation (NaCl solution) to isolate, quantify, and characterize microplastics according to their size, shape, color, and texture. Results revealed significant seasonal and spatial variations. Microplastic content ranged from 0.44% (Dhanmondi Lake) to 9.34% (Turag River) in winter, increasing to 1.08% (Hatirjheel)–22.6% (Turag River) in summer. Peripheral rivers (Buriganga and Turag) consistently showed higher concentrations than inland lakes. By weight, larger particles (1.18–4.75 mm) dominated, while smaller particles prevailed by count. Most microplastics were irregular with rough surfaces, indicating prolonged exposure; however, sharp-edged larger particles in Dhanmondi Lake and Buriganga River suggested recent inputs. This study provides the first comprehensive assessment of microplastic pollution in Dhaka's freshwater systems, highlighting the seasonal dynamics and spatial variability of contamination. Advanced techniques such as Raman and Fourier Transform Infrared Spectroscopy can improve microplastic identification and quantification. Developing more sensitive detection methods, coupled with public awareness of their environmental and health impacts, is essential for effective management. Moreover, enforcing stricter regulations on single-use plastics is critical to mitigate microplastic pollution.
Strains of the genus Streptomyces and the species Bacillus subtilis can produce secondary metabolites such as antimicrobials and phytohormones like auxins. Therefore, different Streptomyces spp. and B. subtilis strains were evaluated for their antimicrobial activity against phytopathogenic microorganisms. The highest inhibitions against Clavibacter michiganensis by each genus was 100 % comparable to various antibiotics, while inhibition against Fusarium oxysporum was 39 and 20 % for Streptomyces and B. subtilis respectively. One of the strains from each genus with the best results was subsequently selected to evaluate their phytohormone production in submerged culture. The selected Streptomyces strain showed a maximum accumulation of 2.2 mg/L in Gause medium on day 12, and B. subtilis produced 1.6 mg/L at hour 72 in LB medium. These results suggest that the selected strains can be used as biocontrol agents due to their antimicrobial activity and their capacity to produce phytohormones that promote growth and crop protection.
A contaminated surface patch has diffused in time within an aqueous volume when it is discovered. Emergency workers, with limited access and time, collect surface samples and those at one other nearby elevation. Only sparse space-time data is available and clever detective work is needed. Where, when and how did the pollution originate? What was its size and shape? Can this information be extrapolated, knowing only the diffusion coefficient, from this sparse set of data? An intuitively motivated inverse procedure, assisted by an accurate Alternating Direction Implicit solver operable in reverse time, shows that this is possible, and detailed three-dimensional diffusion equation validations are provided. This capability is useful to remedial correction, policy development, liability assignment and other issues pertinent governance, as well as to other related technical applications.
Face masks used during the COVID-19 pandemic are composed of polymers which when broken down release microplastics to the environment. As part of the most extensive monitoring program of COVID face mask littering ever undertaken for a coastal community, 50 parking lots in the town of Truro, Nova Scotia were surveyed for half a year (November 2021-April 2022). A total of 3,036 discarded or lost face masks were retrieved, with abandonment being consistent through time but for the notable exception of a period of rapid melting that released masks which had been damaged by snow removal maintenance. Qualitative observations and mark-and-recapture experiments indicated parking lots to be sources of litter dispersed to the wider environment. Interpolating these data on loss rates suggests that each of the 25,583 residents of Truro are estimated to have abandoned five face masks in parking lots during the 20 months of the peak pandemic. Expanding these results to the population of a quarter of a million people living around the Bay of Fundy, and using the known material composition of face masks, produces an estimate of 2,822 kg of pandemic plastic waste being generated with the potential to decompose and release microplastics over subsequent years into the Bay of Fundy, a designated World Heritage Site.
A large part of bio-aerosols is composed of biological particles such as bacteria, fungi, viruses, pollens, and their by-products such as endotoxins, metabolites, toxins, and other microbial fragments. These micro-organisms may affect human health with a wide range of adverse health effects including respiratory infections, allergies or toxic response in some individuals, especially susceptible ones. A cross-sectional study was conducted among purposely selected mining pits of Buhemba gold mine in Mara, Tanzania. To determine the microbial count, an agar strip loaded RCS® Microbial Air Sampler was used. Samples were collected at different microenvironments of the mining pit at a flow rate of 100 L min–1 for 5 minutes to yield a sample volume of 500 liters. Morphological characterization of both bacterial and fungal colonies was carried out followed by microscopic examination of fungal and gram-stained bacterial colonies. Regression analysis between mean bacterial and fungal spore counts with environmental factors like temperature and relative humidity was performed. The total aerobic bacteria concentration varied significantly (p value<0.05) between sampled pits (n=15), with the highest and lowest values of 3859 CFU/m3 and 1309 CFU/m3, respectively. However, there was no significant difference in total anaerobic bacteria concentration between sampled pits. The highest and lowest values of anaerobic bacteria were respectively 4284 CFU/m3 and 1190 CFU/m3. The highest and lowest values of total fungi concentration were 3314 CFU/m3 and 646 CFU/m3, respectively. High bacteria load that exceeds 1000 CFU/m3 as recommended by WHO was found in Buhemba gold mine.
This study was carried out in the city of Lomé in Togo. The study looked at the contribution of illegal waste landfills to climate change. The focus was on the quantities of methane released by uncontrolled landfills. In order to achieve the objectives, set by this study, the quantity of methane was recorded at twenty (20) landfills in thirteen (13) localities using microsensors over a period of thirty-two (32) days. The measurements were taken at the landfills with the measuring device stationed in the middle of the landfill at a height of 25 cm above the waste. The data collected was processed and a probability diagram was drawn up, making it possible to assess whether or not a set of data follows a given distribution such as the normal or Weibull distribution. Similarly, the contribution of each of the landfills to climate change was determined. During the measurement period, it was found that the TOGBLEKOPE 2 (6.338 g/m3 ± 4.881) with a contribution of 133.09; AMOUTIEVE (5.565 g/m3 ± 2.889) with a contribution of 116.86; ADETIKOPE GUERINKA (5.56 g/m3 ± 2.123) with a contribution of 116.76; GBOSSIME (5.323 g/m3 ± 4.442) with a contribution of 111.78; HOUNBI (4.702 g/m3 ± 3.59) with a contribution of 98.742; ADETIKOPE KPETAVE (4.363 g/m3 ± 2.841) with a contribution of 91.62 and NYEKONAKPOE 2 (4.017 g/m3 ± 3.067) with a contribution of 84.357; release more methane into the atmosphere. This shows the contribution of landfill sites in the fight against climate change.
Researchers in the marine ecosystem have documented the significant impacts that anthropogenic ocean acidification has on marine organisms. These include olfactory abilities in fish, impaired behavioral as well as physiological changes, including anti-predatory response leading to consequences in population dynamics and community structure. In this research, we endeavored to investigate and compare the growth rate of the gold mollies (Poecialia sphenops) larvae under a low pH of 5 water temperature of 28 O C, and a pH of 6.9 at a water temperature of 26 O conditions. The mollies larvae were weighed for four months (August, September, October, and November) and the data collected was analyzed using the Statistical Package for Social Sciences (IBM SPSS). The analysis was a multivariate test for a more complete examination of data by looking at independent variables and their relationship to one another. There was no statistically significant difference in the growth rate in August (p-value 0.969) and September (p-value 0.286) between the larvae in aquarium A (experimental) and those in aquarium D (control) at the beginning of the experiment. But there was a statistically significant difference in the third (3) month (October) P-value = 0.007 and in the fourth month (4) (November) P-value = 0.004. The low pH of 5 impacted the growth rate of the Poecilia sphenops larvae while those in the control aquarium pH of 6.9 seemed to have not been affected and grew well.
Land-use change disrupts several soil physico-chemical parameters. This study aimed to analyze the influence of agricultural activities, topography, and localities on soil texture, pH, and organic matter in the Dimonika Biosphere Reserve. To achieve this, 90 soil samples were collected using an auger based on land use types, topography, and localities. Analyses of soil texture, pH, total organic carbon (TOC), and total nitrogen (TN) were conducted at the IRSEN laboratory in Pointe-Noire. The results showed that clay texture predominates in the studied area, which is related to the nature of the soils. The Kruskal-Wallis ANOVA test highlighted a significant effect of agricultural activities on soil acidity, with an acidic pH ranging from 4.2 to 5 in cultivated areas, compared to a very acidic pH (3.5 to 4.2) in mature forests. However, neither topography nor localities affected pH. Total organic carbon significantly decreased in old plantations (1.3±0.3%) and fallows (1.5±0.5%) compared to mature forests (1.9±0.5%) and savannahs (2.3±0.6%), while total nitrogen showed no notable variations. Topography also had no influence on organic status (TOC, TN). However, at the local level, the Makaba area stood out with significantly higher TOC (2±0.5%) and TN (0.2±0.03%) compared to Les Saras (0.14±0.03%) and Kayes (0.16±0.2%). The C/N ratio, influenced only by agricultural activities, was below 15, indicating rapid organic matter mineralization and a low TOC content. Several potential solutions were proposed for sustainable soil management.
The study area is located in Arlit region, which is a semi-arid zone and where groundwater is the main source of water resources. In this area, the host formations of uranium mineralization are also aquifers. Thus, the waters of these aquifers naturally contain significant amounts of uranium. The consumption of water from these wells can constitute a proven health risk for population. It is therefore urgent to analyses the groundwater from these aquifers in order to determine the uranium content of these waters. The objective of this study is to determine the uranium content in these aquifers. A methodological approach based on hydrochemical analysis methods has shown that the groundwater sampled contains very high levels of uranium ranging from 0.26 mg/L to 0.0024 mg/L, which is unsuitable for any human activity, outside the processing of uranium ores. In addition, these waters naturally contain uranium related to the geological context of this area. However, other external sources such as mining activities bring uranium through water seepage or accidents. Note that these waters are not used by population because they are located in the mining area. The water from these wells is used in the processing of uranium ore for the purpose of extracting uranium contained therein. This study made it possible to identify the uranium content of groundwater in mineralized formations of study area.
Ocean acidification represents a threat to marine species worldwide, and forecasting the ecological impacts of acidification is a high priority for science, management, and policy. As research on the topic expands at an exponential rate, a comprehensive understanding of the variability in organisms' responses and corresponding levels of certainty is necessary to forecast the ecological effects. More specifically, what stands to be understood from this review is an understanding of the effects of ocean acidification and whether marine organisms have sufficient physiological plasticity to adapt to the changes in their environment as pCO2 concentration continues to rise. An experiment assessing the impact of ocean acidification on a given species, community, or ecosystem should include realistic changes for all environmental drivers (CO2, temperature, salinity, food concentrations, light availability), and be long-term (i.e., several years) to allow for natural variability and multiple generations of each species under consideration. Single experimental approaches on single organisms often do not capture the true level of complexity of in situ marine environments, and multi-disciplinary approaches involving technological advancements and development are critically needed before a correct determination is made on the mortality of marine organisms.
There is an increasing urgency to address how the light pollution risk level can be accurately and comprehensively measured and evaluated. Based on current research and data, this paper proposes a model concerning light pollution risk levels applicable to various regions. Optimized intervention strategies are then provided to reduce the effect of light pollution. For one thing, this paper establishes an Illumination-Environment-Society Evaluation (IES) model to evaluate a region’s light pollution risk level. Primary indicators of the model involve three dimensions, each quantified by 2 to 5 secondary indicators, with sufficient data analysis conducted, including data rasterization of satellite remote sensing images, K-means clustering analysis, Principal Component Analysis (PCA), Entropy Weight Method (EWM), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Analytic Hierarchy Process (AHP), and other assistant algorithms. In this regard, the present study obtains and grades some regions’ light pollution risk levels. For another, this paper determines three possible intervention strategies for light pollution based on the IES model after interpreting the results. Non-linear programming methods are also employed to optimize these three strategies. The present study aims to exploit a new avenue for relevant environmental research, providing references for light pollution measurement and intervention.
This study investigated the impact of high-density septic systems (aka Onsite Sewerage and Disposal Systems, OSTDS) along the canals located in the communities of the lower Taylor Creek area on water quality at the northern periphery of Lake Okeechobee. Using sucralose as an anthropogenic tracer, we investigated the septic derived non-point sourcing of nutrients which feed harmful algal (cyanobacterial) blooms (HABs) in Lake Okeechobee and adjacent waters. The subdivisions investigated were Treasure Island (TI) and Taylor Creek Isles (TCI) located to the east and west of Taylor Creek. TI homes are all on septic tanks whereas TCI is serviced by a municipal vacuum sewerage system. TI canals had 5.3 times the mean concentration of sucralose relative to TCI canals. On a yearly basis, the Treasure Island sites away from Taylor Creek had 2.25 times the total phosphorus and 1.20 times the total nitrogen compared to the Taylor Creek isles sites. An extensive literature review of non-point pollution is included.
The different controls of water hyacinth, an invasive species of tropical and subtropical environ-ments, have demonstrated some limitations requiring additional monitoring tasks to maintain the ecological balance. Therefore, quantifying and valuing this aquatic biomass becomes a sustainable management alternative. However, the water hyacinth estimation remains a challenging task in developing countries with regard to the used methods: empirical relationships between yield and production indices calculated experimentally, structural parameters measured or calculated through specific experiments (not dynamic), etc. These methods lose precision depending on the type of plant, cultural methods and practices and the seasons. Then, it becomes urgent to develop a dynamic estimation method with a proven track record of reliability despite the inconsistency of the factors mentioned above. This article contributes to the improvement of aquatic biomass estimation by proposing a Computer Vision based solution for estimating fresh mass of water hyacinth. To achieve this goal, the morphology of the species is assessed and an XML classifier is developed. This model is then implemented in a mobile app facilitating its end use. The proposed algorithm demonstrated a mean average precision of 96.89%. Considering the recorded level of accurateness, the developed method can be used to estimate different types of biomass.
The air, water, and lands of the Arabian Gulf countries are exposed to contamination involving organic and inorganic components resulting from industrial energy sector activities. In Qatar, marine life and air are the primary elements of the ecosystem that pollution has negatively affected since the discovery and exportation of oil and gas. For example, the mean concentration of PM2.5 reached 105 µg/m3 in 2016. This poor air quality has been attributed to several factors: dust storms, vehicle emissions, and industrial emissions. Marine life around the peninsula of Qatar has been threatened by many factors, including discharge of desalinated seawater, oil and gas activities, and the impact of climate change. Studies conducted after multiple major events showed that levels of various types of pollutants were at acceptable levels. Some areas in the Arabian Gulf, such as the coasts of Saudi Arabia and Bahrain, are still considered chronically polluted and need continual monitoring in the long term. This review discusses the pollution status on the Qatari coastlines and the reasons behind the persistence of current levels of pollution in Arabian Gulf water. The role of microorganisms (bacteria, algae, and fungi) in a biological approach for environmental manipulation of pollution problems is discussed. The agricultural lands in Qatar are possible sites of pollution due to the potential expansion of the energy, industry, and construction sectors in the future. Currently, industrial wastewater is pumped deep into the ground, and seawater is intruding into the main-land, which is causing significant contamination of soils used for the cultivation of various crops. Possible measures are reported, and practical solutions to future pollution risks are discussed.
