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.
