Journal of Environmental Science and Engineering Technology

Implementation of Marine Environmental Impact Assessment Mechanism for Marine Spatial Planning in Taiwan

2026-01-10T20:33:01+00:00

To undertake a detailed and comprehensive research on the marine environmental impact assessment mechanism of marine spatial planning in Taiwan with a specific focus on the environmental impact assessment (EIA) technique. The present research adopts methodological model based on the principles of environmental impact assessment (EIA) for analysis of the Taiwan marine ecosystem. The cumulative environmental impact of human activities within the area of scope of the study is computed as the sum of the impacts of identified human activities on selected components of the ecosystem. The collection of data related to the human activities and ecosystem components variables was limited to the last five years, between 2018 and 2023, and the pre-existing data that were openly available were sourced from different sources including the Taiwan marine spatial planning (MSP) related governmental agencies, consultancies and academic research. The impactful human activities on the Taiwan marine environment include ocean bottom trawls, oil spill shipping and sand loss extraction activities as well as turbidity ocean bottom trawl, boating effects, mining activities and marine infrastructural projects and the most affected ecosystem components include the artificial and natural coastal reefs, the shoreline shallows, the deep ocean spaces and the biological components which include the plants and the animals. The most impactful human activity on the Taiwan marine environment is attributed to dumping activities within the coast zone areas which has had the most significant impact on the coastal zone ecosystem.

Spectral Shifts and Dissociation Dynamics of Acetone in the Presence of an External Electric Field

2026-01-10T20:43:11+00:00

Acetone, a typical volatile organic compound (VOC), poses significant environmental and health risks due to its high reactivity and contribution to the photochemical smog formation. The effects of an external electric field (EEF) ranging from 0 to 30.854 V·nm^-1 on the physical and chemical properties of acetone were investigated by density functional theory (DFT) using the B3LYP/6-311+g(2d,2p) basis set. The results demonstrate that the C=O bond in acetone elongates and the total moment increases as the EEF increases, enhancing molecular polarization. Although the total energy of acetone decreases with increasing EEF, the change is primarily due to the dipole-field interaction, and does not necessarily indicate improved thermodynamic stability. The infrared (IR), Raman, and UV-Vis spectra exhibit redshifts, indicating a reduction in excitation energy. Single-point energy scans confirm that the C=O bond weakens, with dissociation predicted at 52.785 V·nm^-1.

Modeling Soil Futures: Integrating Classic and Emerging Approaches to Water Erosion

2026-01-11T21:12:13+00:00

Soil erosion by water remains one of the most pressing forms of land degradation, undermining agricultural productivity, ecosystem services, and global food security. Over the past decades, diverse modeling approaches have been developed to quantify and predict soil erosion, ranging from classical empirical models to advanced machine learning and hybrid frameworks. This review synthesizes the evolution of erosion modeling, highlighting both the historical foundations and emerging directions. Empirical models such as USLE and RUSLE provided the first standardized and widely adopted methods, while process-based models like WEPP and EUROSEM advanced mechanistic understanding but faced limitations due to extensive data demands. The integration of Geographic Information Systems (GIS) and Remote Sensing (RS) transformed erosion modeling by enabling spatially explicit risk assessments at watershed and regional scales. More recently, machine learning algorithms—including Random Forests, Support Vector Machines, and deep learning architectures—have demonstrated superior predictive power, although challenges of interpretability, transferability, and data dependency remain unresolved. Hybrid and integrated models now represent the state-of-the-art frontier, combining empirical transparency, process-based rigor, and AI-driven adaptability. Future-oriented perspectives, including GeoAI, digital twins, cloud-based platforms, and participatory modeling approaches, offer transformative potential. These innovations are particularly critical under non-stationary conditions driven by climate change and land-use transformations, which demand dynamic, probabilistic, and stakeholder-inclusive frameworks. The review concludes that no single paradigm is sufficient to capture the complexity of water erosion. The way forward lies in integrated, multi-scale, and uncertainty-aware modeling systems that bridge scientific precision with policy relevance, supporting sustainable land management and climate adaptation in the coming decades.

Early Seedling Vigor and Morphology of Five Malaysian Indica Rice Cultivars under Water

2026-01-11T21:19:04+00:00

This study evaluated the early seedling vigor and growth morphology of five Malaysian indica rice cultivars (MR263, MR219, MR220CL2, MR269, MR284) under simulated water deficit using polyethylene glycol (PEG 6000) treatments. Seeds were germinated on Petri dishes with four PEG solutions (0, –0.3, –0.9, –1.5 MPa) at 25°C. After 14 days, germination percentage, seedling vigor index, root length, and shoot (seedling) length were measured. Increasing osmotic stress significantly reduced germination speed and seedling growth for all cultivars, with the most severe stress (–1.50 MPa) causing drastic declines. Seedling vigor index decreased sharply as water potential decreased. Among cultivars, MR263 and MR219 maintained significantly higher vigor and longer roots/shoots under stress than the others. At –1.50 MPa, MR263 exhibited the highest vigor index (~3.6), root length (~5.8 cm) and shoot length (~3.8 cm), whereas MR284 had the lowest (~0.5, ~2.7 cm, ~0.3 cm, respectively). These results indicate genetic variation in drought tolerance at early stages. Our findings suggest MR263 and MR219 may be better suited for environments prone to water deficit, and highlight the importance of seed vigor and root development as selection criteria for drought resilience.

Spatial Modeling of Flood-Prone Areas Through Multi-Criteria Analysis Applied to a Brazilian Municipality

2026-01-11T21:25:38+00:00

This study applied a spatial multi-criteria analysis (MCA) integrated with Geographic Information Systems (GIS) to identify flood risk areas in Sorocaba, Brazil. The variables—slope, elevation, flow accumulation, soil susceptibility, and land use and land cover (LULC)—were standardized, reclassified into vulnerability levels, and integrated using the categories very low, low, moderate, and high, resulting in a flood risk map. Additionally, a spatial overlap analysis between LULC classes was performed to identify occupation patterns in risk areas. The areas classified as high and moderate risk are concentrated in low-altitude regions, characterized by high environmental susceptibility and intense anthropogenic occupation, especially along the Sorocaba River and its tributaries. In contrast, very low-risk zones are located in forested or silvicultural areas, associated with higher altitudes and greater infiltration capacity. The spatial overlap between risk and land use revealed that non-vegetated surfaces (38.0%) and pasture/agriculture areas (58.6%) predominate in the highest-risk zones, indicating low infiltration and increased surface runoff. These results demonstrate that flood vulnerability arises from the interaction between geomorphological and anthropogenic factors, reinforcing that land cover changes and environmental degradation intensify hydrological events. The proposed model proved efficient, transparent, and replicable, providing technical support for territorial planning, disaster risk management, and the formulation of preventive public policies.

Mineralogy, Trace Elements, and Rare Earth Element Composition of Sediments in an Amazonian Whitewater River: The Acre River

2026-01-11T21:32:36+00:00

This study characterizes the mineralogical and geochemical composition of suspended (SS) and riverbed sediments (BS) from the Acre River, a whitewater tributary in Southwestern Amazonia. Four SS and four BS samples collected during the dry season were homogenized into composite samples and analyzed by different analytical techniques (ICP-MS, ICP OES, XRD, and FTIR). The results showed that quartz (up to 75 %) and kaolinite (up to 38 %) were the dominant minerals, together with feldspars and TiO₂. Rare earth elements (REEs) were present at low to moderate concentrations (0.11-52 µg g^-1), with Ce and La being the most abundant. Trace elements such as V, Ni, Ga, Rb, and Cs showed enrichment relative to upper continental crust. Although the single-season sampling limits temporal interpretation, comparison with published datasets from the Purus and Solimões basins suggests that both natural weathering and local land-use pressures influence sediment composition. These results provide new geochemical data for a poorly studied Amazonian tributary and contribute to the broader understanding of sediment provenance and hydrogeochemical processes in whitewater rivers.

Decoding Rainfall Diversity: A Long-Term GIS Assessment of the Chikkamagaluru Region

2026-01-11T21:40:39+00:00

This study analyses long-term rainfall variability across Chikkamagaluru, Mudigere and Belur taluks using a 47-year continuous dataset (1977–2024). Spatial interpolation (Ordinary Kriging, 1 km × 1 km resolution) and temporal trend diagnostics (Mann–Kendall, Sen’s slope) were used to quantify seasonal patterns and windward–leeward gradients. Mean annual rainfall across the region is 1769 mm, with monsoon rainfall contributing 80–86% of yearly totals. Windward stations such as Kottigehara and Hosakere receive 3–4 times more rainfall (up to 4170 mm) than leeward stations such as Kalasapura (~680 mm). Trend analysis indicates weak but notable seasonal trends: monsoon rainfall shows non-significant decreasing tendencies at most leeward stations, while pre-monsoon rainfall shows slight increasing trends (Sen’s slope +1.8 to +3.2 mm/year). Spatial rainfall maps and trends align strongly with Western Ghats orography and established monsoon climatology. These findings enhance hydro-climatic understanding and provide actionable insights for watershed planning, agriculture, and hazard mitigation.

Assessing the Environmental Impacts of Urban Mixed Land-Use on Residential Livability: A Case Study of Hyderabad

2026-01-11T21:50:05+00:00

Background; Livability is increasingly recognised as a central component of sustainable urban development, and in rapidly commercialising cities, mixed-use corridors play a critical role in shaping daily experiences.

Objective; The current research examined environmental quality conditions along four mixed-use commercial corridors to determine how spatial variations in key urban environmental stressors including noise exposure, sanitation, greenery availability and environmental infrastructure reflect the effectiveness of urban environmental management practices in dense mixed-use settings.

Methods; The current study adopted a quantitative, cross-sectional survey design. Data were collected using a structured questionnaire administered to residents and routine users located along each commercial corridor. A purposive sampling method was employed to select 96 participants who had resided in the area for at least one year. The sample was proportionally distributed across the four study corridors. Seven livability indicators were assessed, including public health, environmental quality, mobility, public space, social equity, economic opportunities, and basic utilities. Furthermore, descriptive statistics and comparative analyses were conducted to examine differences across the four locations.

Results; The findings indicate that livability varies considerably across the commercial corridors. Most indicators received the highest scores on Dr. Salahuddin Road (overall mean = 3.28), suggesting more favourable perceptions of cleanliness, utility provision, clinical accessibility, mobility, and economic potential. In contrast, Wadhu Wah Road demonstrated the lowest overall livability (overall mean = 2.80), which was associated with limited greenery, inadequate pedestrian infrastructure, elevated noise levels, and suboptimal waste management. Moreover, the rating of public utilities and social interaction remained relatively positive across all areas (mean ≥ 3.05), whereas walkability (mean range: 2.70–2.95) and the availability of public spaces (mean range: 3.09–3.28) consistently emerged as weaknesses.

Conclusion; The current study reveals that a well-planned pattern of commercial development can substantially improve living conditions and reduce congestion, environmental discomfort, and risks associated with pedestrian movement.

Quantitative Assessment of Urban Sprawl Dynamics During the COVID-19 Pandemic Using AI-Supported Satellite Data

2026-01-11T22:05:05+00:00

This study aims to quantitatively assess the effects of socioeconomic changes experienced during the COVID-19 pandemic on urban sprawl dynamics. The research was conducted in the Döşemealtı District of Antalya Province, located in the Mediterranean Region of Türkiye, which stands out with its semi-rural urban characteristics and is part of one of the country’s most important tourism destinations. Settlement dynamics, expansion patterns of built-up areas, and their spatiotemporal changes in the study area were analyzed for the pre- and post-pandemic periods using artificial intelligence–supported land use/land cover (LULC) data. In this context, the Built-up class filtered from the ArcGIS Living Atlas LULC dataset was compared between 2017 (pre-pandemic) and 2023 (post-pandemic), and thematic maps of built-up surfaces were produced for each reference year. These maps were analyzed using geographic information system (GIS) technologies to evaluate the magnitude, spatial direction, and temporal trends of changes in impervious surfaces.The findings indicate that the spatial restructuring tendencies triggered by the pandemic reached a remarkable scale in the Döşemealtı District, with an increase in construction clusters within rural belts and a rapid conversion of vacant lands into built-up areas. Impervious surfaces, which covered 4146,94 km² in 2017, increased to 4412,74 km² in 2020, reached 5426,62 km² in 2023. Accordingly, a short-term increase of 30,9% in impervious surfaces was observed, largely attributable to the pandemic period. By providing a rapid, low-cost, and objective analytical framework, this study demonstrates strong potential for application in remote sensing–based urban planning and spatial change monitoring during crisis periods. The results are expected to serve as an important data source for regional and local authorities in defining urban growth strategies, supporting sustainable planning decisions, and evaluating spatial transformations in future disaster or crisis scenarios.

A Study of Agricultural Buffers and Rural-Urban Fringes: A Case Study of Deh 202 Taluka, Jhuddo District, Mirpurkhas

2026-01-11T22:16:57+00:00

The semi-arid areas like Mirpurkhas experience growing environmental pressure because of the loss of vegetation, heat stress, and the growing settlement patterns in rural-urban fringe areas. Agricultural buffers like tree belts, grass waterways, and wetland strips are globally known to enhance microclimates, lower soil erosion, and improve landscape quality. The study explores the perception of six forms of agricultural buffers and three levels of buffer intensity by the stakeholders in the rural-urban fringe of Deh 202, Taluka Jhuddo, District Mirpurkhas. Farmers, residents, and academics were surveyed using a photo-questionnaire survey. A 5-point Likert scale was used to assess six types of buffers and three conditions of the buffers (no buffer, basic buffer, and extensive buffer). The findings showed that there were no statistically significant differences in the stakeholder groups in any type of buffer or condition (all p > .05). Descriptive trends indicated a strong preference hierarchy, with the Riparian tree buffers receiving the strongest approval across stakeholder groups. And then the grass waterways, riparian grass strips, wetland buffers, odor buffers, and windbreaks. Although the differences between the groups were not significant, the stakeholders showed a strong inclination towards dense tree-based buffers, which is both a global trend and a response to local climatic requirements. The planned strategies can focus on tree-dominant buffer designs, which are subject to uniform patterns of stakeholder preferences as observed in this study.