In recent decades, the decrease in rice cultivation areas in Vietnam, particularly in the Mekong River Delta, caused by climate change and soil salinization, has posed serious challenges for sustainable development. In addition to irrigation and agronomic practices, fertilizers that sustain rice growth under saline conditions play a crucial role in improving crop productivity. Amorphous silica has been reported to increase plant tolerance to drought, salinity, and heavy metal stress. In this study, nanosilica-coated urea (UCS) fertilizers were synthesized by coating urea granules with 1–5 wt% amorphous silica. The products were characterized by SEM, XRD, FTIR, TG‒DSC, and EDX to confirm their structural and chemical features. Laboratory-scale experiments on saline soils revealed that UCS reduced total dissolved salt (TDS) content by up to 40% after 30 days, increased soil organic nitrogen and silicon contents by more than 15%, and promoted stable rice growth. After 30 days, the height of the rice treated with UCS1 reached 42–44 cm, which was 124% greater on average than that with conventional urea (18–30 cm), and higher survival rates were maintained (up to 90% vs. 40%). The growth stages of rice under mild to moderate salinity conditions were evaluated throughout a 120-day cultivation period. These results highlight the strong potential of urea‒silica fertilizers for sustainable rice cultivation in saline soils (0.5%–1% NaCl).
Diatoms are widely recognized as sensitive bioindicators for reconstructing past water quality and ecological changes in aquatic ecosystems. In this study, multiple diatom-based indices were applied to sediment cores collected from three downstream stations of the Tuntang River, Central Java, to infer long-term environmental change in a tropical river system. A total of 38 sediment subsamples were analyzed, with dominant taxa including Fragilaria crotonensis (2.4–18.6%), Nitzschia palea (3.1–22.4%), and Aulacoseira granulata (2.0–15.8%), indicating sustained nutrient enrichment. Diatom indices consistently classified conditions as mesotrophic to eutrophic throughout the sediment profiles. The occurrence of the marine diatom Cylindrotheca closterium (up to 6.3%) at downstream stations suggests episodic seawater intrusion associated with hydrological alterations. Although the indices were originally developed for temperate regions, the pollution sensitivity index (IPS) and generic diatom index (IDG) performed robustly, with >70% species representation across all depths. These results demonstrate that sedimentary diatom indices provide a reliable proxy for reconstructing long-term ecological change and eutrophication trends in tropical river systems where historical water quality data are limited.
This study aims to address the key gaps in understanding the factors influencing the intention–behavior relationship of consumers in the context of the circular economy (CE). Grounded in the theory of planned behavior (TPB), this research extends the framework by integrating social pressure, attitudes toward green consumption, and the availability of CE products as crucial components that shape intention and behavior. Data were collected from 603 Vietnamese consumers and analyzed using partial least squares structural equation modeling (PLS-SEM). The results confirm the core TPB constructs, with perceived behavioral control emerging as the most influential factor. Notably, attitude toward green consumption has a greater effect on intention than does attitude toward the CE does, whereas social pressure has a stronger direct effect on behavior than subjective norms do. This research establishes the validity of an extended TPB framework within the CE context of a developing economy, providing new evidence on the psychological and sociocultural factors that shape circular consumption behavior. Finally, this study offers insights for policy makers and businesses to develop strategies for promoting CE not only for Vietnam but also for other developing countries.
In this study, the concentrations of heavy metals (As, Cd, Cr and Pb) in water, sediment, and hybrid catfish (Clarias gariepinus x C. macrocephalus) as well as chromosomal abnormalities (CAs) from a reservoir affected by leachate from a municipal landfill were compared to those in an unaffected reservoir. Heavy metal concentrations were analyzed using inductively coupled plasma‒optical emission spectrometry (ICP‒OES). Chromosomes were prepared from kidney cells by direct methods. The As, Cd and Pb concentrations in the water and sediment from both reservoirs were within the Thailand water and soil standards. The concentrations of As and Cd in the water and the concentrations of As, Cd, Cr and Pb in the sediment and hybrid catfish significantly differed between the affected and unaffected reservoirs (p<0.05). The Pb concentration in hybrid catfish from the affected reservoir exceeded Thailand's food standard. Eight types of chromosomal abnormalities were detected in the hybrid catfish from the affected reservoir (centric fragmentation, centric gap, deletion, fragmentation, iso-chromatid break, iso-chromatid gap, single chromatid break, and single chromatid gap). The most common CA was deletion in the hybrid catfish from both reservoirs. The percentages of cells with CAs in hybrid catfish from the affected (22.00%) and unaffected reservoirs (8.60%) were significantly different (p< 0.05). These findings indicated that leachate from the municipal landfill has caused heavy metal contamination in the reservoir, leading to bioaccumulation and cytogenetic damage in hybrid catfish.
This study presents a comprehensive multihazard risk assessment for Mueang Tak District, Thailand, that integrates hazard, vulnerability, and exposure (H-V-E) dimensions. By utilizing geographic information systems (GIS) and remote sensing, the analytic hierarchy process (AHP) was employed to prioritize critical risk factors. GIS analysis integrated multisource spatial data, including Landsat 9 and Sentinel-2 imagery, CHIRPS precipitation, and SRTM-derived topography, while AHP weights were established on the basis of expert judgment and socioeconomic indices such as the relative wealth index (RWI) and population statistics. The results delineate distinct spatial risk clusters: high landslide potential is concentrated in the steep terrain of Mae Tho subdistrict, critical flood exposure affects the urbanized lowlands of Tak Municipality, and severe drought vulnerability characterizes the rain-fed agricultural belts of Pa Mamuang and Wang Prachop. These spatially explicit findings demonstrate the robustness of the integrated geospatial model, providing essential data to guide local policy-makers in establishing “Disaster Risk Reduction Sandbox” areas and enhancing community resilience against compounding natural hazards.
Soil erosion remains a critical environmental challenge in the tropical highland watersheds of Southeast Asia, where steep terrain, intense monsoonal rainfall, and intensive land use interact to accelerate sediment generation and downstream degradation. This study aims to quantify spatial patterns of sediment yield and to systematically evaluate the effectiveness of individual and combined best management practices (BMPs) at both the watershed and subwatershed (SWW) scales using the Soil and Water Assessment Tool (SWAT) in a tropical highland watershed in northern Thailand. Baseline simulations reveal pronounced spatial heterogeneity in erosion severity, with substantial portions of the watershed exhibiting moderate to extreme sediment yield levels. Scenario-based simulations indicate sediment reduction efficiencies ranging from 42% to 85% across watershed and SW scales, demonstrating clear performance differences among BMP categories. Structural BMPs, particularly stone/soil bunds (SSB) and terracing (TRC), achieve the greatest immediate sediment reduction by shortening the effective slope length and disrupting runoff–sediment connectivity in erosion-prone areas. Vegetative and management-based BMPs, including reforestation (RFT), filter strips (FTS), and contour farming (CTF), produce more gradual yet persistent sediment reductions, thereby enhancing long-term hydrological regulation and watershed resilience. Integrated BMP implementation further improves sediment control by coupling rapid structural interception with sustained vegetative and management effects. Spatial prioritization at the SW scale demonstrates that compared with uniform implementation, targeted BMP deployment substantially enhances sediment reduction efficiency. Overall, the integration of SWAT-based modeling, multiscale evaluation, and spatial prioritization offers a transferable and decision-relevant framework for assessing BMP effectiveness and supporting climate-resilient erosion management in tropical highland watersheds.
Crude oil negatively affects soil physicochemical properties and microbial activity, thereby hindering plant growth and posing notable environmental and agricultural issues. The combined effects of cow dung, indole-3-acetic acid (IAA), and simulated microgravity on the recovery of soil degraded by crude oil were explored using Zea mays as the test plant. Soil was contaminated with crude oil at different concentrations (0%, 1%, 3%, and 5% v/w), with each concentration comprising eight treatments: cow dung, Zea mays seeds exposed to microgravity, and IAA alone or in combination. Changes in plant height, soil pH, soil moisture content, and soil microbial diversity were assessed. Crude oil contamination decreased plant height and soil moisture, reduced pH, and suppressed microbial diversity. However, the various treatments significantly enhanced the soil parameters both individually and in combination. Notably, T7 (cow dung + IAA + simulated microgravity) had a plant height of 60.14±9.8 cm at 12 weeks, and the soil pH and moisture content at the 5% concentration during the 3rd month were 6.45±0.02 and 25.25±2.35%, respectively. Microbial analysis revealed the presence of the hydrocarbon-associated taxa Fusarium oxysporum, Pseudomonas aeruginosa, and Bacillus cereus and the nutrient cycling taxa Alcaligenes faecalis and Bacillus cereus. Microbial diversity was highest in T7 (3.18) and lowest in T2 (maize alone) and T5 (maize+IAA), both of which had a diversity index of 2.94. Their occurrence suggests a potential contribution to soil recovery, although their functional roles were not directly assessed in this study. This research demonstrated the synergistic potential of integrating bioremediation strategies to mitigate the negative effects of crude oil contamination and to restore the ability of soil to support plant growth. The results offer a framework for developing sustainable and effective restoration practices, with implications for enhancing soil health and agricultural productivity in crude oil-polluted areas.
The growing demand for renewable energy and sustainable waste management highlights the need for efficient biomass-to-energy technologies. This study investigated the production of solid biofuel from urban tree waste (UTW) in Hanoi, Vietnam, using hydrothermal carbonization (HTC) coupled with process water (PW) recirculation. HTC was optimized at 240 °C for 3 h, yielding hydrochar with a higher heating value (HHV) of 22.95 MJ kg-1 and an energy yield of ~90%. The PW was recirculated for up to ten cycles at a fixed PW-to-freshwater ratio of 1:1. The fifth recirculation cycle resulted in the highest hydrochar quality (HHV: 22.18 MJ kg-1; energy yield: 77.15%), after which further recirculation resulted in a decrease in the HHV. PW analysis revealed that total organic carbon (TOC) and organic acids (acetic and formic acids) significantly influenced hydrochar yield and energy densification through secondary carbon deposition. A predictive model for HHV based on fixed carbon content was developed and validated with independent datasets. The produced hydrochar met or exceeded Vietnamese solid fuel standards regarding HHV, ash, and sulfur content. Overall, HTC combined with PW recirculation is an effective and sustainable approach for valorizing UTW as a high-quality solid biofuel, reducing freshwater consumption, and minimizing wastewater discharge in the environment.
In this study, the accumulation of heavy metals (Cd, Cr, Cu, Fe, and Pb) in water, suspended sediments, sediments, and seagrass in Kalase Bay, Trang Province, Thailand, during the 2024 dry season was investigated. These findings indicate that the enrichment factor (EF) for all the metals was less than 1, suggesting that anthropogenic contamination is not a significant concern in the area. The translocation factor (TF) values were less than 1 for all the metals except Cu, whose TF was greater than 1; however, these values were not statistically significant, indicating limited phytoextraction capacity. The bioconcentration factor (BCF) values for Cu and Pb in seagrass were also less than 1, indicating no substantial accumulation of these metals in seagrass tissues. Additionally, the Cd and Cr concentrations were below the detection limits, further indicating their negligible presence. This study revealed a strong correlation between the concentrations of heavy metals and fine sediment fractions, with suspended sediments playing a critical role in the transport and distribution of these metals. The presence of sand bars and seagrass beds in the region likely influences sediment dynamics, contributing to the retention and bioavailability of metals. The sediment carbon-to-nitrogen (C/N) ratio ranged between 10 and 20, indicating that mixed organic matter sources are commonly associated with coastal sediments. This suggests that sediment organic matter originates from multiple inputs rather than from a single dominant source. These results underscore the importance of implementing a comprehensive monitoring program, including suspended sediment analysis, to track heavy metal accumulation and sediment changes, which is crucial for informed conservation and management of the unique ecosystem of Kalase Bay and its carbon storage potential.
Forest fires represent one of the most critical environmental challenges in Thailand, with impacts varying depending on forest type, fuel characteristics, terrain conditions, fire intensity, and the frequency of fire occurrence on the same landscape. While forest fires can contribute to ecosystem degradation, biodiversity loss, and the depletion of natural resources, such effects are not uniformly severe across all forest ecosystems. Understanding the human-induced factors contributing to forest fire occurrence is crucial for developing effective prevention strategies and promoting sustainable forest management. This study aimed to identify the anthropogenic factors influencing forest fire areas in Thailand via multiple linear regression (MLR) analysis. Eight independent variables related to human activities, including agricultural burning, forest product gathering, hunting, livestock raising, tourism, local conflicts, illegal logging, and accidents or negligence, were analyzed via annual data from 1998--2024 obtained from governmental and environmental agencies. The analysis revealed that forest product gathering, livestock raising, tourism, local conflicts, and negligence were significantly and positively correlated with burned areas. Although agricultural burning, hunting, and illegal logging were not statistically significant in the final regression model, these activities have been reported to contribute to extensive burned areas in Thailand. The lack of statistical significance in this study may reflect limitations related to data aggregation, temporal resolution, or indirect pathways through which these activities influence fire occurrence. The final regression model demonstrated high predictive accuracy, explaining approximately 97.83% of the interannual variation in Thailand’s burned area. The findings indicate that human-related activities play a significant role in forest fire occurrence within the scope of the anthropogenic factors analyzed in this study, and the developed statistical model provides an effective tool for predicting fire-prone areas and supporting policy development for sustainable forest management and environmental protection.
Heavy metal pollution, particularly chromium (Cr) from electroplating industrial waste, has severely threatened environmental quality and human health. This study aims to develop a composite adsorbent material based on bentonite and god crown biomass capable of removing chromium ions from liquid waste through a combination of reduction and adsorption mechanisms. The god crown/bentonite (GC/Bt) composite was synthesized at a mass ratio of 2:1 and calcined at 900°C. FTIR characterization revealed active functional groups (–OH, C=O, Si–O, and Al–O–Si), whereas BET analysis revealed a mesoporous structure (surface area 31.12 m2 g-1, pore diameter 4.37 nm) suitable for ion diffusion. The reduction of Cr(VI) to Cr(III) was facilitated by infrared (IR) irradiation, with 950 nm identified as the optimum wavelength compared with 730 nm. This conversion was confirmed by the significant increase in removal efficiency, as Cr(III) is more readily adsorbed by the composite than Cr(VI). The integrated system achieved a maximum removal efficiency (%R) of 86% and an adsorption capacity (qe) of 703.19 mg g-1 under optimal continuous column conditions (bed height of 30 cm and flow rate of 4 L min-1). The isotherm study showed the best fit with the Freundlich model, indicating a heterogeneous adsorbent surface, whereas the adsorption kinetics followed the pseudo-second-order model (R2>0.97), indicating the dominance of the chemisorption mechanism. These results confirm that combining infrared reduction and chemical adsorption by GC/Bt composites is a practical approach for industrial chromium waste treatment.
This research utilizes activated carbon derived from residual Eucalyptus wood (EW) for the removal of methyl orange (MO). The residual Eucalyptus wood-based activated carbon (EWAC) was produced through carbonization at 400 °C (EWC) followed by activation with a mass ratio of H3PO4 to EWC of 1:3, which was conducted at 800 °C for 1 h. The characterization of the EWAC involved various analytical techniques, including FTIR, XRD, BET, and CHN analysis. The adsorption parameters, such as pH (range: 3–8), adsorbent dose (range: 0.01–0.5 g per 50 mL of MO solution), contact time (range: 5–720 min), initial MO concentration (range: 5–600 mg L-1), and temperature (range: 20–40 °C), were investigated. The kinetic study suggested that the adsorption behavior correlated well with the pseudo-second-order model, indicating a suitable fit for the experimental data. The intraparticle diffusion analysis suggested that the external film diffusion of dye molecules controls the overall adsorption rate. Moreover, the adsorption model provided good fit with the Langmuir isotherm model, confirming monolayer adsorption with an adsorption capacity (qmax) of 29.11 mg g-1 at 303.15 K. Thermodynamic studies also confirmed that endothermic and chemisorption processes are favored for the adsorption process even at high temperatures. Furthermore, the EWAC demonstrated potential for regeneration and reuse over four operational cycles, highlighting its cost-effectiveness and eco-friendly nature for removing MO from synthetic dyes in wastewater.
Antibiotic pollution is of great interest owing to growing concerns about antibiotic resistance worldwide. This study aims to fabricate acid-modified biochar (CBM-A) from corn plant byproducts (CRs) for sulfamethoxazole (SMX) adsorption in aqueous solutions. CBM-A was synthesized via pyrolysis at 700 °C and modified with 14% H3PO4. Kinetics, isotherms, and thermodynamics were investigated in combination with material characterization to elucidate the adsorption behaviors and mechanisms. The results showed that pyrolysis and acid modification effectively enhanced SMX adsorption by CR because of the increased number of binding groups, specific surface area, and porosity. SMX adsorption on CBM-A was optimized at a natural pH of 6.3, initial SMX concentration of 30 mg L-1, CBM-A dose of 1.5 g L-1, contact time of 2 h, and temperature of 298 K. Under the optimal conditions and initial SMX concen-tration range of 10–200 mg L-1, the maximum SMX adsorption capacity (qmax) of CBM-A was 63.29 mg g-1. The Langmuir isotherm (R2 = 0.9945) and Pseudo-second-order kinetic (R2 = 0.9928) models were appropriate for describing SMX adsorption on CBM-A. The adsorption process was favorable and endothermic. Owing to its facile preparation, high qmax value, and short equilibrium time, CBM-A is considered a promising biosorbent for eliminating SMX from aqueous solutions.
Wastewater treatment plants (WWTPs) are considered an entrance pathways for microplastic (MP) pollution in aquatic environments. This study reveals the removal and characteristics of MPs in wastewater from two municipal WWTPs in Indonesia. The influent contained 17.1 ± 5.65 particles L-1 (WWTP A) and 15.45 ± 4.31 particles L-1 (WWTP B), whereas the effluent contained 1.41 ± 0.01 and 1.5 ± 0.16 particles L-1. The removal efficiency was 91.75% for WWTP A and 90.32% for WWTP B, with no statistically significant difference (p > 0.05). WWTP A employed advanced treatment units, whereas WWTP B used a conventional pond-based system. MPs were characterized via light microscopy, with most particles ranging from 100–300 μm and 1000–5,000 μm. Fibers and fragments were the dominant shapes, with transparent and black being the most common colors. ATR-FTIR analysis identified polymers such as polypropylene (PP), polyethylene (PE), polyethylene terephthalate (PET), polyester, and polystyrene (PS). These findings emphasize the important role of WWTPs in reducing MP pollution and highlight the need to improve treatment technologies to better protect aquatic ecosystems.
The increasing severity of global warming, primarily driven by greenhouse gas emissions, underscores the urgent need for CO2 reduction and utilization strategies. Converting CO2 into methanol presents a promising approach, as methanol serves both as a fuel and a feedstock in various industries. This study evaluates the life cycle environmental impacts of three methanol production routes: (1) direct CO2 hydrogenation, (2) ethanol-assisted CO2 hydrogenation, and (3) propanol-assisted CO2 hydrogenation. Two energy scenarios are considered: conventional energy and wind power. Process simulations were performed using Aspen Plus V.14, and inventories were analyzed through Life Cycle Assessment (LCA) using the ReCiPe 2016 (H) method under a cradle-to-gate approach for 1,000 kg of methanol. The alcohol-assisted processes operated at a lower reaction temperature (150 °C) and consumed less CO2, H2, and compression energy than the conventional process (250 °C), thereby reducing environmental impacts. However, methanol purification remained energy-intensive. Under conventional energy, the propanol-assisted process exhibited the highest global warming potential (GWP), followed by the ethanol-assisted process, while the conventional route showed the lowest. The elevated impact of the propanol route was primarily attributed to higher alcohol feedstock and energy consumption. The use of wind power significantly reduced GWP in the separation stage of alcohol-assisted routes, resulting in the lowest GWP for the ethanol-assisted process.
Land utilization is an important indicator of socioeconomic and environmental changes caused by both natural and man-made factors. Land use and land cover (LULC) simulation is a critical tool for monitoring and predicting LULC and is essential for sustainable development, land resource management and planning. The cellular automata (CA) Markov model is the basis for the current study’s prediction of LULC changes in the Northeast Khong Sub Watershed (NKSW). Landsat data from 2013 to 2023 were used to investigate LULC classification and determine the spatiotemporal distributions of LULC. In addition, LULC data from 2013 and 2023 were used to generate simulations via the CA Markov model spanning eight decades (2033 to 2103) to determine how the LULC perspective has changed in the NKSW, which has undergone significant development over the years, including increases in population, settlements, the agriculture sector, and economic and social development. A population increase, according to the model, will cause rapid urbanization, rural expansion and a reduction in forest areas. In 2103, urban and built-up land is expected to account for 5.17% of the total land area, up from 4.12% in 2023. According to the CA Markov model results, the land use and settlement patterns changed significantly in the NKSW. This study urges environmentalists, planners, decision-makers, and those interested in studying LULC change to emphasize sustainable practices and make well-informed decisions for regional well-being. It is an essential tool for directing future planning efforts. Therefore, developing a future master plan for the watershed of Thailand, Lao People's Democratic Republic, and the world should be given top priority.
The increasing deployment of crystalline silicon (c-Si) photovoltaic (PV) panels has raised concerns about their waste management. This study evaluated management strategies for discarded c-Si PV panels in Thailand, integrating environmental and economic analyses. Life cycle assessment (LCA) and cost-effectiveness analysis (CEA) were applied. The LCA can be divided into 2 parts: (1) secured landfill vs decentralized recycling by existing facilities vs centralized full recovery and (2) reusing PV panels in agricultural applications. The results revealed that secured landfills were the most environmentally burdensome (34.43 Pt), whereas centralized recycling achieved net benefits (-211.93 Pt) through emission reductions and recovery of silver, copper, and silicon. The CEA confirmed the viability of the integrated reuse-recycling systems. The integration of reusing PV panels in agriculture with recycling systems by CEA was viable.
Climate change necessitates innovative strategies, with carbon markets emerging as a key tool for mitigation. This study assesses the readiness and willingness of stakeholders in Anambra State to engage in a subnational carbon market. Using a structured questionnaire distributed across government, industry, and academia, the data were analyzed through descriptive statistics, Pearson correlation, and multiple regression analysis. The findings indicate a moderate level of readiness (M = 3.47) and willingness (M = 3.48) among stakeholders. Correlation analysis revealed a significant alignment between composite willingness indicators and direct willingness to participate (r = 0.406, p = 0.004) but a weak and nonsignificant relationship between composite readiness indicators and direct readiness (r = 0.164, p = 0.261). This finding shows that willingness is partly aligned, but stakeholders doubt actual readiness. Regression analysis revealed that technological capability (B = 0.554, p = 0.002) and monitoring, reporting, and verification (MRV) capacity (B = 0.381, p = 0.006) are the strongest predictors of willingness. In contrast, financial constraints (B = 0.201, p = 0.197), institutional frameworks (B = -0.035, p = 0.858), and coordination between the government and private sectors (B = 0.137, p = 0.554) did not significantly influence willingness. These results indicate that stakeholders prioritize operational and technical readiness over financial and institutional factors, emphasizing the need for robust MRV systems and transparent technological infrastructure to foster confidence in the carbon market. The study recommends targeted investments in MRV infrastructure, governance reforms to address stakeholder skepticism, and enhanced stakeholder education on carbon market mechanisms.
Sodium gluconate (SG), a functional organic salt derived from gluconic acid, is widely utilized in various industrial sectors because of its excellent chelating ability, low toxicity, and biodegradability. SGs can be produced sustainably through the neutralization of gluconic acid, which is obtained from the microbial fermen-tation of lignocellulosic biomass such as oil palm fronds (OPFs) and empty fruit bunches (OPEFBs). To meet commercial demands, SGs must be recovered in concentrated form, and nanofiltration (NF) offers a promising membrane-based approach for this purpose. This study aimed to optimize the SG concentration from the fermentation broths of oil palm residue hydrolysates via a dead-end NF system, with feed pH as a key parameter. The NF270 membrane demonstrated optimal performance when synthetic fermentation broth was used at pH 8.0 and 9 bar, yielding 5.55±0.16 g L-1 SG, a flux of 74.47±0.39 L m⁻² h⁻¹, 28.04±2.13% rejection, and 25.21±1.12% recovery. An increased SG concentration was also achieved in real biomass-derived broths; at pH 8.0, the OPF hydrolysate pro-duced 1.56±0.02 g L-1 SG with 35.72 ± 1.36 L m⁻² h⁻¹ flux, whereas the OPEFB hydrolysate yielded 1.52 ± 0.15 g L-1 SG with 41.29 ± 1.26 L m⁻² h⁻¹ flux. The results demonstrate that feed pH significantly influences nanofiltration performance, particularly in terms of improving the SG concentration and membrane efficiency across different biomass sources. This study provides the first systematic evaluation of SG recovery from oil palm solid residues via nanofiltration, highlighting its potential as a sustainable and efficient alternative to conventional purification methods.
Landslides are natural disasters that are active if there is an interaction of environmental factors that are considered to control them, especially in mountainous areas. This study developed a landslide susceptibility map in Pidie Regency via the Dempster-Shafer (DS), statistical index (SI), and certainty factor (CF) models. A total of 957 landslide events were mapped, 70% of which were used for modeling, whereas the remaining events were used to validate the model output. Fourteen layers of conditioning factors were used: elevation, slope, aspect, curvature, TWI, SPI, STI, NDVI, rainfall, distance from river, distance from road, distance from fault, LULC, and lithology. To assess model performance, the model output was then compared with validation landslide data that had been separated from previous training data. Therefore, the receiver operating charac-teristic (ROC) curve was used, and the area under the curve (AUC) was calculated via the success rate and prediction rate curves. The results show that the CF model has the best performance, with success rates and prediction rates of 81.02% and 80.55%, respectively, followed by DS (80.25% and 78.70%) and SI (76.58% and 75.93%). Therefore, the CF model is more accurate than the DS and SI models. The resulting landslide susceptibility map can be used for early land use planning and hazard mitigation purposes.
