Mangrove ecosystems play an important role in mitigating heavy metal pollution in coastal environments; however, direct assessment of their phytoremediation potential commonly relies on intensive field sampling and laboratory analyses. This study develops a machine learning-based prediction model to classify heavy metal contamination levels in mangrove sediments as a supporting tool for phytoremediation planning. A publicly available sediment dataset obtained from Kaggle, consisting of 300 samples with concentrations of Pb, Zn, Cr, Cu, and Ni, was used as a methodological testbed. Data preprocessing included feature normalization, label encoding, and class balancing using the Synthetic Minority Over-sampling Technique (SMOTE), followed by an 80:20 train-test split. Four classification algorithms Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and XGBoost, were evaluated using accuracy, precision, recall, and F1-score metrics. Random Forest and SVM achieved the highest classification performance (92.5% accuracy), while KNN showed the lowest accuracy (81.5%). Feature importance analysis identified Cr, Pb, and Zn as the most influential variables in contamination level classification. Although the dataset is not site-specific and lacks ecological metadata, the results demonstrate the technical feasibility of machine learning models for sediment contamination classification. This study is positioned as a methodological proof-of-concept and highlights the need for future research integrating field-validated sediment data, mangrove species information, and biological uptake indicators to support robust phytoremediation assessments.

This study incorporated provincial input-output tables into the environmental assessment process for Phuket - an island with an economy based largely on tourism. The life cycle assessment approach was employed considering five impact categories including climate change, fossil scarcity, water, eutrophication and land use for green gross provincial product (GGPP) calculation. Degradation cost and depletion cost originating from global warming and fossil resource scarcity were the main contributors. The results indicated that for a tourism-based economy such as Phuket, industries associated with tourism, such as accommodation and food service activities, wholesale and retail trade and repair of motor vehicles, as well as transportation and storage are highly profitable, but also impose heavier environmental burdens compared to other sectors. The sectoral GGPP of electricity, gas, steam, and air conditioning supply, as well as water supply, sewerage, waste management and remediation activities, involved more in local residents’ living, accounted for 25% and 50% of the sectoral gross provincial product (GPP), respectively. In 2015, Phuket GGPP was 160 billion THB, corresponding to 96% of the Phuket GPP. As Phuket relies heavily on its beautiful environment to bring economic value, it is imperative to protect it against environmental damages especially irrecoverable ones.

Plastic pollution remains a critical environmental issue due to the persistence of petroleum-based plastics in natural ecosystems. This study evaluates Sargassum seaweed, an abundant coastal biomass in Malaysia, as a renewable feedstock for biodegradable bioplastic production. To overcome the inherent limitations of alginate-based bioplastics, glycerol 12.6% (w/w, relative to polymer mass) has been incorporated as a plasticizer, with calcium chloride (2% w/v) as a cross-linking agent. Bioplastic films were produced via alginate extraction, film casting, and drying, and characterized through tensile testing, differential scanning calorimetry (DSC), water absorption, grease absorption, and biodegradability analyses. The modified Sargassum-based bioplastics exhibited enhanced tensile strength (maximum force up to 6.67 N), improved elongation at break (up to 31.33%), and increased thermal stability, with a melting temperature of 160°C and degradation onset at 190°C. Swelling, biodegradation, and oil uptake behaviors were governed by the interplay between hydrophilic diffusion and calcium-mediated cross-link stabilization. Complete biodegradation was observed within 30 days in soil. These findings demonstrate that formulation optimization allows Sargassum-derived bioplastics to achieve balanced mechanical performance, barrier properties, and environmental degradability. This will enhance their potential for sustainable single-use packaging applications.

In 2025, Binh Thuan Province was merged into Lam Dong Province as part of a broader restructuring initiative by the Vietnamese government. In the former Binh Thuan Province, Vietnam, increasing pollution pressure in river basins (where wastewater is received) requires identifying and applying wastewater treatment technologies suitable to the actual situation of the wastewater sources. This study conducted a multi-criteria analysis (MCA) combined with the weighted sum method and visualized through radar charts to assess the suitability of treatment technologies, identify operational incidents, evaluate impact levels and prioritize rehabilitation of wastewater treatment systems (WWTSs) currently applied to five typical wastewater types: domestic, industrial, seafood processing, livestock and hospital wastewater. A set of criteria comprising 22 sub-criteria in four groups (technical, environmental, economic, social) is applied and the criteria are quantified based on field surveys and expert consultations. Results showed that domestic WWTS achieved the highest score (75/100) reflecting stable performance and a high level of suitability, while seafood processing WWTS scored lowest (50.625/100) due to high costs and unstable efficiency. Industrial WWTS (68.125/100), livestock WWTS (64.375/100) and hospital WWTS (68.75/100) systems performed moderately, with good technical outcomes but constraints in cost, energy use and emissions. Recurrent incidents such as aeration failures, sludge flotation and odor generation were common, though generally remediable. Seafood processing and industrial WWTS were prioritized for urgent rehabilitation. This study provides essential data and a practical MCA-based decision-support framework to improve existing WWTSs under local environmental and operational conditions, thereby supporting water resource protection in Vietnam’s river basins.

The Rungan Watershed is facing an alarming rate of environmental degradation yet continuing to support the livelihoods of local communities. Therefore, this study is essential for addressing these issues and formulating adaptive management model. This research aims to assess environmental conditions and social economic aspects to formulate management model that is expected to serve as a framework for sustainable development in Palangka Raya City. By applying both qualitative and quantitative approaches, the study collects ecological, economic, and socio-cultural data to inform the development of management strategies. Land cover, land use, and vegetation density are assessed using remote sensing imagery and land cover maps. The analysis of forest vegetation density classes is conducted through the Normalized Difference Vegetation Index (NDVI), utilizing data from Landsat imagery. Socio-cultural information is gathered through interviews and observations. The study identifies various land cover condition, information on social economic condition that serve as a basis for developing a zoning based management model that categorizes the Rungan Watershed into conservation, buffer, and general utilization zones. This model accommodates the diverse interests of multiple stakeholders within a sustainable development framework. The study concludes that the zonation management of the sub-basin must align with the biophysical ecological conditions of the area, address existing challenges, and promote community welfare.

Allium cepa L., commonly known as onion, is one of the most widely cultivated vegetables worldwide, valued for its characteristic flavor, aroma, and pungency. It is extremely concerning that around one million tonne of onion waste is produced throughout distribution, processing, and consumption. Characterization of onion waste is essential for its valorization. The study’s goal was to identify the nutritional and nonstructural carbohydrate content, antioxidant, antimicrobial activity and phytochemical elements present in the waste. The onion waste was cleaned and dried at 60°C in an air-circulating tray dryer, and ground into a fine powder. It was found to contain moisture (3.67%), protein (8.56%), carbohydrate (70.47%), fat (0.64%), crude fibre (4.49%), dietary fibre (69.06%), and insoluble dietary fibre (63.64%) and provides 321.88 kcal of energy per 100 g. The non-structural carbohydrates in the onion waste were glucose (4.40%), fructose (1.75%) and sucrose (1.10%). The ethanolic onion waste extract was found to contain phytochemicals anthraquinones, anthocyanins, phenols, flavonoids, glycosides, terpenoids, flavonoids, and tannins. Using DPPH and hydroxyl radical scavenging activity, the antioxidant activity of ethanolic onion waste extract was revealed to be strong at various concentrations. These values ranged from 42.34% to 70.50%, 65.8 to 60.5%, respectively. The ethanol extract of onion waste was found to have the strongest anti-microbial effects on Escherichia coli and Staphylococcus aureus. Onion waste characterization provides valuable insights into its potential as a source of bioactive compounds facilitating its utilization in nutraceuticals and functional foods. This approach promotes sustainable waste management and resource utilization while unlocking the hidden potential of onion waste.

Increasing biodiesel production generates excess glycerol, which has a declining economic value. Converting glycerol into triacetin, a value-added fuel additive, offers a promising solution. However, the reversible nature of the esterification reaction and the formation of water reduce selectivity. Therefore, this study was conducted to evaluate the effect of in situ water removal on reaction performance in terms of acetic acid conversion and the resulting triacetin product. Experiments were conducted in a batch reactor through three clearly defined stages. In Stage 1, the optimal glycerol-acetic acid molar ratio (1:3-1:5) was determined at 100°C and 700 rpm, using a 5% natural zeolite catalyst (based on acetic acid mass), and a reaction time of 4 h with in situ water removal. In Stage 2, residual water was removed by fractional distillation at 105°C until bubbling ceased. Stage 3 comprised the main reaction, where the distillate containing monoacetin, diacetin, triacetin, and glycerol was reacted with fresh acetic acid at the optimal ratio, while in situ water removal continued to enhance triacetin formation. Acetic acid conversion was analyzed by acid-base titration using 0.5 N NaOH, and triacetin was identified by GC-MS. This innovation showed excellent results, achieving 94.00% conversion of acetic acid with 85.58% selectivity for triacetin at 110°C and a 1:5 glycerol-to-acetic acid molar ratio. These results showed that in situ water removal intensified esterification by shifting the equilibrium, enhancing triacetin conversion and selectivity. This strategy advances glycerol valorization and supports the production of sustainable fuel additives within integrated biorefinery systems.

Coastal lowlands are highly vulnerable to seasonal changes and rainfall variability, which affect the risk of floods and droughts. Therefore, this study aimed to analyze decadal changes in the monthly rainfall distribution along the northern coast of Central Java (Pantura), using data from 51 stations of the Meteorology, Climatology, and Geophysics Agency (BMKG) and the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) v2.0. A smoothed histogram was used to calculate the probability density of rainfall for each decade. Subsequently, the distribution between decades was compared using 6 metrics to assess distribution displacement, divergence, overlap, and shift in peak, centroid, and width. The level of uncertainty was measured using the bootstrap method at confidence levels of 5%, 10%, and 25%. The six metrics were normalized and combined into a single composite index called the Total Normalized Index (TNI). K-means clustering was then applied to map changes according to the same rainfall patterns. Analysis of both sources showed a gradient pattern from west to east. Rainfall was concentrated in the west, with moderate changes in structure in the central area, and a more dispersed rainfall pattern with high variability in the east, particularly from 2011 to 2020. CHIRPS data recorded the regional trends but tended to cloud out local fluctuations. This study contributed to new investigations since the implementation of histogram-based rainfall distribution analysis into a composite index. The application of this method as part of a spatial clustering model was proposed to map alterations in rainfall distribution each decade. The method also helped in evaluating coastal climate risk and adaptation planning.

Duckweed (Lemna minor L.) is an efficient aquatic plant that accumulates heavy metals. This study aimed to investigate the ability of duckweed. To accumulate selected heavy metals (Ni, Cu, Zn, Fe, Ba, Mn, and Co) at 5 mg/L concentrations of each metal, and to study the effects of metals on plant growth and biochemical changes in the plant. This study was conducted for 14 days to control the environmental conditions. The accumulation of metal inside the plant tissue, bioconcentration factor (BCF), and relative growth rate (RGR) were measured at the end of the experiments, while plant fresh and dry weight, total chlorophyll, and protein and proline contents were measured at the beginning and end of the experiments. The results showed that the highest metal accumulation in plant tissue and BCF were 4.112 and 0.822, respectively, in the iron treatment, while the lowest values were 2.334 and 0.466, respectively, in the Ba treatment. The highest reduction in fresh weight and growth percentage was in the Ba treatment, the highest reduction in chlorophyll content was in the Ba treatment, and the lowest protein content was in the Cu treatment. Therefore, the results indicate that Duckweed can tolerate selected heavy metals and can be used in phytoremediation technology.

This study develops an integrated framework for monitoring eutrophication in Xuan Khanh Reservoir (XKR), Hanoi, Vietnam, by combining in-situ observations with Landsat 8 (L8) reflectance data. A total of 66 field measurements collected during four surveys (October 2024-July 2025) were used to calibrate an empirical model for estimating the Trophic State Index (TSI) from L8-derived reflectance. The near-infrared to red ratio (B5/B4) achieved the best performance (R²=0.81; RMSE=2.4). Nineteen cloud-free L8 images acquired between July 2021 and July 2025 were then applied to map spatiotemporal TSI variations. Results show that XKR consistently remained in a highly eutrophic to hypereutrophic state, with TSI values ranging from 64 to 82. Spatial patterns revealed persistent hotspots in shallow northern zones and inlet-connected areas, driven by external nutrient inputs and surrounding land-use pressures. These findings demonstrate the value of L8 as a cost-effective monitoring tool for small, polluted reservoirs, offering evidence to guide nutrient reduction, wastewater management, and land-use regulation. The proposed approach provides transferable insights for long-term trophic state assessment and can support policy decisions aimed at safeguarding freshwater resources in data-limited regions.