The study was conducted to evaluate the physicochemical parameters of water and assess the public perception of the water quality status in the Tasik Chini watershed based on a community survey. The water sample was analyzed based on standard methods and categorized according to WQI (Water Quality Index). Multivariate statistical analysis was adopted to find spatial variations in water quality, determining the pollution level and sources of contamination. The study results were compared with NWQS (National Water Quality Standard for Malaysia). The results showed that the value of dissolved oxygen (DO) was low (4.68 mg.L-1), while the level of biological oxygen demand (BOD), chemical oxygen demand (COD), and total dissolved solids (TDS) was found to be high, 2.92 mg.L-1, 26.10 mg.L-1 and 22.93 mg.L-1 respectively. High turbidity was recorded in a mining area in the rainy season (35.76 NTU). The DOE-WQI value categorized the lake under class II and class III. The Principal Component Analysis (PCA) revealed that the major sources of contamination were due to anthropogenic activities, especially settlement, mining, agriculture, and illegal activities. Overall, Tasik Chini’s water quality status was classified as slightly polluted to highly polluted based on hierarchical cluster analysis (CA) results. The survey showed that 55% of the local community reported that the water quality was poor. The knowledge and attitude level of the local people was medium category, while community practice was low. The Pearson correlation coefficient test showed a strong significant relationship at 0.01 level between knowledge and attitude and knowledge and practices. The scientific findings with public perceptions might be useful for policymakers and the general public to improve the management system for a desirable future.

The research was carried out to determine the potential effect of microbiota, organic carbon, percentage of moisture content, and microbial biomass concentration as an evaluator of variation in basal soil respiration rate. Relative distribution and composition of the microbial population were estimated from six different chronosequence manganese mine spoil (MBO0, MBO2, MBO4, MBO6, MBO8, MBO10) and forest soil (FS). The variation was seen in moisture content (6.494±0.210-11.535±0.072)%, organic carbon (0.126±0.001- 3.469± 0.099)%, MB-C (5.519±1.371- 646.969± 11.428) μg.g-1 of soil. A positive correlation was shown between OC with MB-C (r = 0.938; p< 0.01) and moisture content (MC) (r = 0.962; p< 0.01). Variation in the basal soil respiration (BSR) and microbial metabolic quotients (MMQ) was shown to range between 0.352 ± 0.007- 0.958 ±0.014μg CO2-C.g-1 and 6.5× 10-3 - 1.481×10-3 μg CO2-C.g-1 microbial-C.h-1 with BSR: OC from (2.793-0.276)% respectively. This result shows that there is a gradual increase in OC, MC, MB-C, and BSR across seven different sites due to progressive enhancement in soil fertility that leads to the initialization of succession. Stepwise multiple regression analysis further confirms the degree of variability added by microbial biomass C, moisture content, organic carbon, and microbial population on basal soil respiration in microbes. Principal component analysis enables the differentiation of seven different soil profiles into independent clusters based on cumulative variance given by physico-chemical and microbial attributes that indicate the level of degradation of land and act as an index to restore soil fertility.

This work explores the detailed study of Bangladeshi precipitation patterns, with a particular emphasis on modeling annual rainfall changes in six coastal cities using Markov chains. To create a robust Markov chain model with four distinct precipitation states and provide insight into the transition probabilities between these states, the study integrates historical rainfall data spanning nearly three decades (1994–2023). The stationary test statistic (χ²) was computed for a selected number of coastal stations, and transition probabilities between distinct rainfall states were predicted using this historical data. The findings reveal that the observed values of the test statistic, χ², are significant for all coastal stations, indicating a reliable model fit. These results underscore the importance of understanding the temporal evolution of precipitation patterns, which is crucial for effective water resource management, agricultural planning, and disaster preparedness in the region. The study highlights the dynamic nature of rainfall patterns and the necessity for adaptive strategies to mitigate the impacts of climate variability. Furthermore, this research emphasizes the interconnectedness of climate studies and the critical need for enhanced data-gathering methods and international collaboration to bridge knowledge gaps regarding climate variability. By referencing a comprehensive range of scholarly works on climate change, extreme rainfall events, and variability in precipitation patterns, the study provides a thorough overview of the current research landscape in this field. In conclusion, this study not only contributes to the understanding of precipitation dynamics in Bangladeshi coastal cities but also offers valuable insights for policymakers and stakeholders involved in climate adaptation and resilience planning. The integration of Markov chain models with extensive historical data sets serves as a powerful tool for predicting future rainfall trends and developing informed strategies to address the challenges posed by changing precipitation patterns.

The Indonesian government continues to accelerate the resolution of all problems related to the planning, infrastructure development, and arrangement of tourist visits, including the arrangement of parking spaces and commercial areas in the Borobudur temple area. The purpose of this study is to develop a waste management system in the parking and commercial areas of Kujon as an alternative to structuring the Borobudur temple area. The research method is a descriptive-qualitative observational approach. Surface water and groundwater examinations are carried out in laboratories and compared with quality criteria determined by the Indonesian government. Toxic and hazardous waste is stored in temporary facilities until it is collected by a company licensed by the Indonesian environmental ministry. The Shannon-Wiener Plankton and Benthos Diversity Index measures the diversity of organisms in a community. The study’s findings highlight the need to establish a waste processing facility based on the reduction, reuse, and recycling principles. Waste will be collected at a certain site and stored temporarily in line with the technical instructions for the Minister of Environment and Forestry’s Regulation. The findings of surface water and groundwater studies demonstrate that all measured parameters continue to meet the Indonesian government’s quality thresholds. Plankton Bioindicator Measurements: Plankton diversity index values range from 1.040 to 1.943, indicating moderate pollution, while benthos values range from 0.811 to 0.918, indicating weakly to moderately contaminated conditions. Sustainable environmental management is critical and should serve as a baseline for environmental quality in the activity area.

The majority of flood assessment and warning systems primarily focus on the occurrence of floods caused by river overflow, taking into account factors such as intense precipitation. Improving flood resilience, on the other hand, requires a deeper understanding of how these factors affect each other and how specific local conditions can have an impact. This study offers impartial tools for estimating the severity of the effects brought on by heavy rainfall to facilitate the prompt communication of effective measures, such as the evacuation of livestock and human settlements and the provision of medical assistance. These tools take into account the cascading effects of various causative factors contributing to heavy rainfall. This article aims to assess the various factors that contribute to the impacts of heavy rainfall, including the timestamp (indicating soil saturation and moisture levels), river gauges (determining water congestion in canal systems), average aerial precipitation (indicating runoff), and the rainfall itself, taking into account both in situ and ex-situ impacts. Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbour (KNN), and Naive Bayes are some of the machine learning methods used in the study to find out how dynamically vulnerable affected districts are to flooding in different compound scenarios. This analysis is conducted by leveraging historical observed datasets. The results demonstrate the feasibility of mitigating the issue of excessive and insufficient flood warnings resulting from the cumulative effects of intense precipitation. By implementing a categorization system that divides the affected areas into various portions, or districts, according to the main factors contributing to flooding, namely rainfall, river discharge, and runoff, The suggested model presents novel insights into the sequential consequences of intense precipitation in the regularly inundated regions of North Bihar, India. Innovative tools can serve as valuable resources for flood forecasters and catastrophe managers to comprehend the extent of flooding and the consequential effects of intense precipitation.

This paper examines electronic waste and cycling in Lebanon. It describes the current situation regarding e-waste among government agencies and non-governmental organizations. It addresses two research questions: The first one asks if the Lebanese society and government are aware of the dangers posed by electronic waste and whether any action has been taken to prevent an environmental catastrophe. The second question asks about Lebanese attitudes toward e-waste and whether they are willing to fight against it. Interviews provided the first question’s responses. The authors have visited Organization A and NGO B. The first is worried about gathering waste in more prominent Beirut, while the second targets spreading attention to e-waste’s risks on legislative and social levels the same. Question two was discussed through surveys filled out by arbitrary people from Lebanese society. The answers to both research questions came in a manner that demonstrates the two hypotheses expected toward the start of the study, specifically that e-waste represents an incredible danger to the Lebanese climate. Hypothesis two, if climate neighborliness and proclivity to right e-garbage removal rely upon the instructive level of some random resident, has been confirmed while analyzing the answers in the survey.

The present study aims to characterize the water and sediment quality of the Colorado and Alajua rivers within Ecuador’s Ambato River watershed, with a specific focus on the presence of heavy metals. Measurements were conducted at five sampling points along the upper and lower zones of each river, where both physicochemical and microbiological parameters, as well as concentrations of heavy metals in water and sediments, were analyzed. Most parameters exhibited statistically significant differences, as determined by the analysis of variance (ANOVA), between the values observed in the upper and lower zones of the micro-watersheds. Water quality in the mentioned rivers was assessed using specific water quality indices, WQI, namely the NSF-WQI and Dinius WQI. Additionally, the impact of heavy metal presence in the water and sediments was evaluated using the Heavy Metal Evaluation Index (HEI). While most parameters met the Ecuadorian quality standards for water sources intended for human consumption, concerns emerged regarding elevated levels of total and fecal coliforms along both rivers, which could limit the suitability of these rivers as a water source for human use and consumption. At various sampling points, water quality criteria for the preservation of aquatic life were not met for several heavy metals. For example, the Colorado River exhibited elevated levels of zinc (59-76 μg.L-1), copper (12-47 μg.L-1), lead (1.2-3.9 μg.L-1 ), iron (0.33-0.37 mg.L-1 ), and manganese (0.37-0.47 mg.L-1), while the Alajua River showed excess copper (11 μg.L-1), iron (0.61-0.72 mg.L-1), and manganese (0.62-0.98 mg.L-1). Geological factors likely contribute to the concentration of heavy metals in the upper segments of the rivers, while agricultural runoff may contribute to concentrations in the lower segments. Sediments exhibited higher average values of the Heavy Metal Evaluation Index (HEI) (20.6-26.7) compared to water samples (13.9-15.4), indicating a potential accumulation of heavy metals in the river sediments. Overall, both rivers exhibited contamination levels ranging from regular to moderate, as indicated by the calculated average Water Quality Indices (WQI), with certain areas showing slight contamination or meeting acceptable standards. These results highlight the influence of anthropogenic activities on water quality, emphasizing the necessity of continuous monitoring to assess and control their impact.

Cloud seeding involves boosting precipitation by releasing substances into the air that act as cloud condensation or ice nuclei. These substances encourage the development of clouds and precipitation. It’s like giving Mother Nature a gentle push to assist with rainfall in specific areas. The current work aimed to suggest Al2O3 as an alternate compound in cloud seeding rather than silver iodide. In this research, a unique approach is used to identify condensation nuclei, which play a crucial role in cloud formation and droplet growth. Various samples and four sources were included in the current study; refrigerated helfa powder, Himalayan salt, generator powder, and pollen, were analyzed using different physicochemical instruments. The proportions of chemical compounds in the samples show that there is 1.392% of Al2O3 in Refrigerated helfa which is the highest than in the other 3 sources, while the proportions of elements in the samples indicate that refrigerated helfa contains the lowest toxic compound, and although Al2O3 is insoluble in water, it is hygroscopic and can absorb 6.4% of humidity within 24 hours. As for the surface tension, refrigerated helfa shows lower density and surface tension than the other three sources with values of 0.9480 and 47.89 respectively. Al2O3 shows high humid absorptivity and refrigerated helfa can be used as a main source for Al2O3 which has a low effect on biota and is recommended for use in cloud seeding. However further work is recommended to be carried out in using Al2O3 as an alternative compound to silver iodide in cloud seeding.

Fly ash is generally obtained as a by-product from the combustion of coal and other waste materials. It is used for making bricks, but it has few limitations. The fly ash consists of Silica, Alumina, and other metal oxide components in minor quantities. Fly ash particles are observed in the range of nanometers to micrometers and can act as a catalyst in various reactions. The use of low-cost catalysts in the pyrolysis of thermoplastic waste would achieve a high percentage of low molecular weight fractions in liquid form which increases its applicability in commercial sectors. Hence, there is a need to enhance these fractions to achieve a sustainable approach in the catalytic pyrolysis process. fly ash, being a side product, is very cheap, so its effect on the plastic waste pyrolysis process has been studied. In the present research paper, Physical & chemical characterization of fly ash has been carried out. As fly ash consists of different metal oxides in proportion, its applicability in the process of pyrolysis of HDPE, LDPE, and PP waste has been studied. The different weight percent of fly ash (i.e., 5, 10, 15, 20) have been tried in all pyrolysis experiments. It has been observed that 5 wt % fly ash is effective for enhancing the yield of liquid fuel as compared to that without a catalyst. Liquid fuel obtained from catalytic pyrolysis of HDPE, LDPE, and PP waste with Fly ash consists of a high percent of low molecular weight fractions as compared to that of liquid fuel without catalyst, which has been concluded by calorific values & GC-MS result.

Bengawan Solo River water is a source of drinking water and raw materials for the government of Surakarta city, but the water has been mixed with domestic, industrial, and agricultural wastes. The waste contains estradiol-17 derived from urine and feces, both from livestock and humans as well as industries around the sub-watershed Bengawan Solo River. The content of estradiol-17 in the Bengawan Solo sub-watershed is quite high. This study is the first conducted in Bengawan Solo River to look at natural estrogens that are very rarely studied in the environment, which are likely could cause several health effects in humans and wildlife due to their relatively strong estrogenic potential and high levels in wastewater and river water. Therefore, research on the elimination of these compounds using effective, energy-efficient, and low-maintenance technologies for water treatment such as phytoremediation is highly expected. The purposes of this study were to identify estradiol, to measure the estradiol levels through HPLC tests as well as to test the effectiveness of phytoremediation with Portulaca plant as biological agents. The results show that the water of Bengawan Solo River contained estradiol substances ranging from 3.88 ppm to 5.76 ppm. The Portulaca plant species was effective at eliminating estrogenic waste up to 99.89%.