Environmental Science Research Articles

Unveiling the impact of self-assembly on ultrafiltration: Insights from salvianolic acid B

This study explored the influence of self-assembly on the ultrafiltration (UF) rejection of salvianolic acid B (SaB), a model polyphenolic compound. Employing a combined approach of experimental analysis and molecular dynamics simulations (MDS), we demonstrated pH-dependent self-assembly of SaB at both macroscopic and microscopic levels. At lower pH, larger self-assemblies formed, exhibiting enhanced adsorption onto the membrane surface due to electrostatic attraction. This pH-dependent behavior significantly impacted rejection rates through size exclusion and adsorption mechanisms, leading to a decrease in SaB rejection from 100% to 31% as the solution pH increased from 2.4 to 5.6. These findings transcend the specific case of SaB, offering valuable insights into the broader role of self-assembly in UF processes. This knowledge holds potential applications in optimizing separation processes across diverse fields such as food, pharmaceuticals, and environmental science.

A Multidimensional Exploration of the Interplay between Human Health and Environmental Factors

This research article explores the relationship between human health and the environment, emphasizing the dire need for a holistic view to understand and addressing health challenges. Drawing upon interdisciplinary perspectives from environmental science, public health, epidemiology, and social sciences, the study investigates different environmental factors for example air and water quality, biodiversity loss, environment change, and pollution, and their impact on human health outcomes. Moreover, the paper discusses the relevance of ecosystem services in supporting human health and well-being and examines the potential of nature-based solutions for mitigating health risks associated with environmental degradation. human activities and health-related behaviors exert substantial pressure on the environment. Industrialization, urbanization, and unsustainable resource consumption degrade ecosystems, compromise biodiversity, and exacerbate climate change, thereby threatening environmental health. Deforestation, for instance, not only diminishes biodiversity but also amplifies the risk of zoonotic diseases transmission, as human encroachment brings humans closer to wildlife habitats. Promoting sustainable practices, such as renewable energy adoption and waste reduction, can mitigate environmental degradation while fostering public health. Additionally, enhancing access to healthcare services, particularly in underserved areas, and implementing policies to regulate pollution and safeguard natural resources are paramount. By elucidating the interconnectedness between health and the environment, this research contributes to a deeper understanding of the challenges facing global health and provides insights for developing effective policies and interventions to promote sustainable development and improve population health outcomes.

Development of a monthly PM2.5 forecast model for Seoul, Korea, based on the dynamic climate forecast and a convolutional neural network algorithm

A convolutional neural network (CNN) model has been developed to predict monthly concentrations of particulate matter with a diameter ≤ 2.5 μm (PM2.5) in Seoul, Republic of Korea, during winter months (November through February). Seven meteorological variables influencing PM2.5 concentrations were selected as predictors: geopotential heights at 1000 and 500 hPa, zonal and meridional winds, relative humidity and temperature at 850 hPa, and boundary layer height. These predictors were obtained from the fifth generation of the European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) for model construction and from the Korea Polar Prediction System (KPOPS) dynamic forecasts for operational predictions. From the 11-year ERA5 dataset for 2008–2020, one year was allocated for testing, while the remaining 10 years were randomly assigned for either training (80%) or validation (20%). This process was repeated until all 11 years were allocated for testing, resulting in 11 CNN models. The benchmark which used the ERA5 dataset as the predictors yielded a mean bias error (MBE) of 0.05 μg m−3, root mean square error (RMSE) of 2.41 μg m−3, Pearson correlation coefficient (R) of 0.85, and 71% hit rate in predicting the months of high PM2.5 concentrations (≥ 30 μg m−3) for the testing periods. The 11-CNN-model ensemble predictions using the KPOPS forecasts resulted in an MBE of 0.1 μg m−3, RMSE of 3.19 μg m−3, R of 0.74, and hit rate of 62.5% for the period 2008–2020. Considering that the average temporal correlation coefficients between the ERA5 and the KPOPS forecasts for the seven predictors ranged from 0.20 to 0.66, the CNN-based PM2.5 prediction model has demonstrated good performance in overcoming the adverse effects of the KPOPS forecast errors on predicting PM2.5 concentrations. The CNN model showed limitations for unusual period such as the COVID-19 period, November 2020 through February 2022, when the emissions in East Asia were substantially below their climatological normal levels. In conclusion, the CNN model developed in this study showed potential applicability to operational monthly PM2.5 concentration predictions for the years of normal emissions using solely meteorological data. This can provide professionals in various fields, such as health care and environmental science, with valuable insights for long-term planning.

Interpretable data-driven prediction methods for atmospheric chloride deposition rate

Precise estimation of atmospheric chloride deposition is crucial in environmental science, providing valuable insights into atmospheric pollution, metal corrosion, and the hydrologic cycle. The distribution of atmospheric chloride deposition involves multiple processes of production, transportation, and deposition, making it a problem with well-defined physical mechanisms. Although numerous parametric models have been proposed for atmospheric chloride distribution prediction, they present challenges in terms of generalizability and prediction accuracy due to simplifications of the holistic process. In contrast, non-parametric machine learning algorithms can analyze complex issues and have good prediction performance, but they are used less often in atmospheric chloride deposition modeling. Therefore, we develop a genetic algorithm optimized quantile regression forest (GA-QRF) model, incorporating environmental variables associated with the holistic deposition process to predict the distribution of atmospheric chloride deposition. QRF is an ensemble learning method known for delivering precise and interpretable predictions, coupled with effective uncertainty estimation. The proposed model results achieved an R2 value of 0.935 for median prediction and 98.2% coverage of the intervals for uncertainty quantification on a dataset collected from six countries. In addition, in order to verify the consistency of the black-box machine learning model with the domain knowledge, several interpretation methods are used to deconstruct the proposed model. Considering the spatial variability of atmospheric chloride deposition, the proposed model was further used to create deposition distribution maps.

Position-specific carbon stable isotope analysis of glyphosate: isotope fingerprinting of molecules within a mixture.

Glyphosate [N-(phosphonomethyl) glycine] is a widely used herbicide and a molecule of interest in the environmental sciences, due to its global use in agriculture and its potential impact on ecosystems. This study presents the first position-specific carbon isotope (13C/12C) analyses of glyphosates from multiple sources. In contrast to traditional isotope ratio mass spectrometry (IRMS), position-specific analysis provides 13C/12C ratios at individual carbon atom positions within a molecule, rather than an average carbon isotope ratio across a mixture or a specific compound. In this work, glyphosate in commercial herbicides was analyzed with only minimal purification, using a nuclear magnetic resonance (NMR) spectroscopy method that detects 1H nuclei with bonds to either 13C or 12C, and isolates the signals of interest from other signals in the mixture. Results demonstrate that glyphosate from different sources can have significantly different intramolecular 13C/12C distributions, which were found to be spread over a wide range, with δ13C Vienna Peedee Belemnite (VPDB) values of -28.7 to -57.9‰. In each glyphosate, the carbon with a bond to the phosphorus atom was found to be depleted in 13C compared to the carbon at the C2 position, by 4 to 10‰. Aminomethylphosphonic acid (AMPA) was analyzed for method validation; AMPA contains only a single carbon position, so the 13C/12C results provided by the NMR method could be directly compared with traditional isotope ratio mass spectrometry. The glyphosate mixtures were also analyzed by IRMS to obtain their average 13C/12C ratios, for comparison with our position-specific results. This comparison revealed that the IRMS results significantly disguise the intramolecular isotope distribution. Finally, we introduce a 31P NMR method that can provide a position-specific 13C/12C ratio for carbon positions with a C-P chemical bond, and the results obtained by 1H and 31P for C3 carbon agree with one another within their analytical uncertainty. These analytical tools for position-specific carbon isotope analysis permit the isotopic fingerprinting of target molecules within a mixture, with potential applications in a range of fields, including the environmental sciences and chemical forensics.

Coordination structures and stabilities of Am(III) adsorption complexes at kaolinite(0 0 1)-water interface

Understanding the structures and stabilities of actinide species is crucial for comprehending the sorption mechanisms at mineral–water interfaces. However, the relevant molecular-level fundamental aspects of actinide coordination chemistry at the mineral–water interface remain unclear. We herein conduct a systematic theoretical study of coordination structures and adsorption energies of Am3+ and Am(OH)2+ sorption complexes at the kaolinite(001)-water interface by integrating static density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations. Computational results show that stable outer- and inner-sphere adsorption complexes are respectively formed through hydrogen bonding and coordinate bonding with surface aluminol groups. The most stable inner-sphere species are predicted to be tridentate surface complexes with an eight-folded coordination structure in the first coordination sphere of Am(III). This work deepens the understanding of Am(III) adsorption and complexation behaviors at the mineral–water interface, providing essential insights for actinide migration in natural environments and nuclear waste disposal. The synergy between static DFT calculations for initial screening and AIMD simulations for comprehensive dynamic analysis in this work enhances the efficiency and accuracy of theoretical predictions for actinide environmental chemistry and can be helpful for the broader research fields of geochemistry and environmental science.

A water quality prediction approach for the Downstream and Delta of Dongjiang River Basin under the joint effects of water intakes, pollution sources, and climate change

Water quality prediction is an important means for scientific water environment management and early warning measures. However, its reliability is often restricted by the uncertainties of parameters and pollution sources. Previous methods for resolving these uncertainties still have shortcomings due to low computational efficiency and incomplete coverage of mechanisms. With insufficient data, they also overlooked revealing the comprehensive impact of water intakes, pollution sources, and climate change on water quality in river networks. Insight understanding migration law and the main driving mechanisms under these factors is crucial for water resources and sustainable socioeconomic development. Here, we developed an efficient multi-scenario ensemble water quality prediction (MEWQP) approach to address the deficiency. The Downstream and Delta of Dongjiang River Basin was the demonstrative case. Firstly, we developed multiple parameters and pollution sources inverse estimation method by incorporating the Water Quality Analysis Simulation Program (WASP), general likelihood uncertainty estimation, and inverse methods to improve accuracy. Secondly, the Markov-Chain was used to predict flows affected by climate change. Thirdly, 60 scenarios were analyzed to quantify the impacts of multiple factors on water quality including 5-day biochemical oxygen demand (BOD5), ammonia nitrogen (NH3-N), and dissolved oxygen (DO), and identify an optimized scheme of water intakes. Results show that: (1) WASP has good performance for BOD5, NH3-N, and DO with Mean Absolute Relative Error of 5.87%, 9.19%, and 15.25%, respectively; (2) pollution sources have the greatest impact, followed by extreme climate and intakes. Their combined impacts are greater than individuals; (3) under non-water intakes DO can be improved by 31%, also offset the impact of climate change by 16%; (4) the optimized scheme of intakes could improve DO by 6%. Therefore, decision-makers should simultaneously adjust water intake and reduce pollution sources to obtain high-quality water resources.

Berkeley‐RWAWC: A New CYGNSS‐Based Watermask Unveils Unique Observations of Seasonal Dynamics in the Tropics

AbstractThe UC Berkeley Random Walk Algorithm WaterMask from CYGNSS (Berkeley‐RWAWC) is a new data product designed to address the challenges of monitoring inundation in regions hindered by dense vegetation and cloud cover as is the case in most of the Tropics. The Cyclone Global Navigation Satellite System (CYGNSS) constellation provides data with a higher temporal repeat frequency compared to single‐satellite systems, offering the potential for generating moderate spatial resolution inundation maps with improved temporal resolution while having the capability to penetrate clouds and vegetation. This paper details the development of a computer vision algorithm for inundation mapping over the entire CYGNSS domain (37.4°N–37.4°S). The sole reliance on CYGNSS data sets our method apart in the field, highlighting CYGNSS's indication of water existence. Berkeley‐RWAWC provides monthly, low‐latency inundation maps starting in August 2018 and across the CYGNSS latitude range, with a spatial resolution of 0.01° × 0.01°. Here we present our workflow and parameterization strategy, alongside a comparative analysis with established surface water data sets (SWAMPS, WAD2M) in four regions: the Amazon Basin, the Pantanal, the Sudd, and the Indo‐Gangetic Plain. The comparisons reveal Berkeley‐RWAWC's enhanced capability to detect seasonal variations, demonstrating its usefulness in studying tropical wetland hydrology. We also discuss potential sources of uncertainty and reasons for variations in inundation retrievals. Berkeley‐RWAWC represents a valuable addition to environmental science, offering new insights into tropical wetland dynamics.

Hybrid CFD/techno-economic assessments of carbon capturing combustion system integrated with PEM electrolyzer for efficient hydrogen production

The issue of global warming is a significant challenge in the field of environmental science, resulting primarily from the burning of fossil fuels and the subsequent increase in greenhouse gas (GHG) emissions, thus emphasizing the importance of utilizing renewable energy vectors, carbon capture technology, oxy-fuel combustion, and carbon-free fuels like hydrogen to mitigate these negative effects. In this study, the possibility of utilizing low-calorific value biogas in a gas turbine (GT) combustor under various combustion conditions is numerically simulated, and techno-economic analysis of energy systems coupled with the GT combustor is conducted. Herein, two distinct energy systems utilizing different combustion modes for H2 production via PEM electrolyzer have been designed and examined. This investigation focuses on the impact of various influencing factors in oxy-fuel combustion mode, such as the equivalence ratio and the O2 content in the two types of oxidizers, on the rate of hydrogen production, power generation, energy/exergy efficiencies, and the economic index of the proposed energy system. Additionally, a suitable system for large-scale operation is identified among the presented systems. The findings of the study demonstrate that the energy system based on the O2/CO2 combustion mode exhibits a higher rate of hydrogen production compared to the O2/H2O combustion mode and particularly, within the equivalence ratio range of 0.55≤ϕ≤0.85, the hydrogen production rate in the O2/CO2 combustion mode decreases from 5.16 kg/h to 3.72 kg/h.

Analyzing bacterial detection and transport using redox impact electrochemistry

Understanding bacterial transport dynamics, particularly at the single-particle level, is crucial across diverse fields from environmental science to biomedical research. In recent times, the emerging impact electrochemistry method offers a transformative approach for detection of bacteria at the single-particle level. The method employs the principle of single-entity electrochemistry to scrutinize electrochemical processes during interaction with the working electrode. In this study, we utilized redox impact electrochemistry to detect bacteria and analyze their transport processes towards the working electrode. Stochastic detection using redox reactions at the ultramicroelectrode enabled the detection of individual bacteria, with collision resulting in a current spike signal due to charge transfer. Notably, the detection of bacteria was demonstrated at an exceptionally low concentration (100 CFU/mL), with recorded current spikes reaching approximately 8.1 nA. Analysis of integrated areas under these spikes unveiled a diverse distribution of charge transfer at the ultramicroelectrode during redox reactions, implying variations in bacterial sizes, collision positions on the electrode surface, and redox activity among bacteria. Remarkably, the average charge transfer per bacterium between E. coli and the electrode was found to be (244 ± 24) pC, underscoring the intrinsic redox activity of the bacteria, equivalent to (2.52 ± 0.25) × 10−15 mol. Additionally, our investigation explored the effects of cell transport mechanisms, including diffusion, migration, convection, and settlement on stochastic interactions of the bacteria at the ultramicroelectrode. Through the collision frequency calculations, we found that migration is the primary factor shaping bacterial transport, with gravitational cell settlement also exerting a significant influence.

How does participating scientific research projects affect postgraduates’ academic aspiration and interest? Grounding theory research based on six universities in H province

Participation in scientific research projects is the main way of postgraduate training, and academic aspiration and interest is an important variable affecting the quality of postgraduate training. So, how does participating in scientific research projects affect the academic aspiration and interest of master students? By interviewing 28 master students from 6 universities in H Province and using the grounded theory research method, a path model of the impact of participating in scientific research projects on the academic aspiration and interest of master students is formed: taking personal characteristics as the initial condition, important others such as tutors and research group examples and scientific research environment as the support category, and the change of graduate students' psychological state as the intermediary, Graduate students will take active or passive action strategies in scientific research activities, which will enhance or reduce their academic aspiration and interest. The change of academic aspiration and interest will react on their psychological state, forming a virtuous circle or bad circle. The model has important enlightening significance for graduate education and management.

Fauna and Flora of Gunung Datuk Recreational Forest, Negeri Sembilan, Malaysia: A Brief Documentation

The biodiversity of forests in Negeri Sembilan, such as the Gunung Datuk Recreational Forest, is remarkably diverse and supports a wide array of fauna and flora species. These species play crucial roles in nutrient cycling, pollination, medicinal and providing habitats for other species. The study documented nine (9) plant species of the Kingdom Plantae and family Ebenacae, Dioscoreaceae, Dipterocarpaceae, Arecaceae, Rubiaceae, Polypodiaceae, Piperaceae and Poaceae, four (4) fungal species of the kingdom Fungi and family Physalacriaceae, Podoscyphaceae, Omphalotaceae and Amanitaceae and five (5) animal species from the kingdom Animalia and family Trigoniulidae, Zephroniidae, Scincidae, Arebidae and Formicidae. The species abundance in the forest emphasizes the interconnectedness of biodiversity and its role in maintaining the ecological balance. This study integrates ecology, environmental science, and cultural values, providing a holistic framework for managing biodiversity. Preserving the forest biodiversity of Gunung Datuk is crucial for ecological stewardship, safeguarding cultural heritage, and ensuring sustainable development for future generations. This fosters a harmonious coexistence where biodiversity and human needs are harmonized.

Science Education in Indonesia: A Bibliometrics Study in Terms of Science Teachers’ and Students’ Perspectives

In recent years, Science Education (SE) in Indonesia has grown into a dedicated focus for all stakeholders in scientific education. All players in the field of education unanimously agree to enhance the prominence of SE among all stakeholders, particularly teachers and learners. The research analyzed the students' attitudes regarding Science Education and the impact of Science Education by SE teachers in higher educational institutions. Science Education outcomes are analyzed using a survey and descriptive evaluation. To gather details, a survey includes closed-ended and open-ended questions developed and controlled on SE teachers’ and students’ viewpoints and knowledge. This research assessed Indonesian Science Education teachers’ perspectives and experiences with Science Education teaching focused on Socio-Scientific Issues (SSI). The students were asked how they integrated relevant SSI methods into their Science Education and their difficulties. Teachers were asked what subjects they learned would be best for SSI-based learning, and most students replied that subjects like technology or environmental sciences would be good for the learning. Despite many hurdles, most Science Education teachers continued to be interested in using SSIs in their classrooms.

About holding the III International Internet conference «Current issues of Formal and Non-Formal Education in Environmental Monitoring and Conservation»

On April 26, 2024, the the Karazin Institute of Environmental Sciences hosted the III International Internet Conference "Current issues of Formal and Non-Formal Education in Environmental Monitoring and Conservation", organized by the Department of Environmental Monitoring and Conservation. The conference featured presentations on the following topics: The impact of military operations on the environment and ways of post-war revitalization of natural complexes; Problems and prospects of reserve management in Ukraine and the world; Environmental monitoring: science, education, practice; Formal and non-formal education in reserve management; The Chornobyl disaster: consequences of the tragedy and warnings for the future. Three reports-presentations of the certificate educational programs of the Institute of Ecology of Karazin University (speakers O. Gololobova, A. Kleshch and S. Burchenko) deserve special attention.

Addressing ecoparalysis: a community-engaged unit enhances undergraduate student environmental value and problem-solving self-efficacy

Undergraduates often express that they feel powerless to help solve important challenges such as climate change and environmental degradation, consistent with the broader phenomena of ecoparalysis. Viewed through value-expectancy frameworks for motivation, value for an outcome and self-efficacy to achieve it lead to goals, which motivate engagement. This study evaluates the impact of a community-engaged course unit, versus a unit without a community-engaged component, in a general-education university environmental science course in the United States on student expressions of environmental value, self-efficacy, and goals. Qualitative analysis of written reflections reveals enhancements in students’ pro-environmental values, environmental problem-solving self-efficacy, and environmentally-related goals. Paired quantitative analysis comparing code frequencies in reflections (n = 37) show statistically significant enhancements in environmental value (p = .00013, Cohen’s d = 0.930) and self-efficacy (p = .00082, d = 0.807). These outcomes suggest community-engaged coursework can help reduce students’ ecoparalysis and motivate them to engage in pro-environmental action beyond the bounds of the course.

UNTRM On the Global Scene: A Bibliometric Analysis of Its Scientific Production Indexed in Scopus

The purpose of this study is to conduct a comprehensive bibliometric analysis of the publications of authors affiliated with the Universidad Nacional Toribio Rodríguez de Mendoza (UNTRM) indexed in Scopus, in order to understand the scientific approach and research trends of this Amazonian institution. The methodology employed follows a qualitative, descriptive, non-experimental and longitudinal bibliometric approach, using the Scopus database for its broad academic coverage. A total of 455 documents related to the UNTRM were analyzed, including articles, contributions to conferences, reviews and other publications, without temporal restrictions. Data were downloaded in CSV format and processed using spreadsheets, open source software such as VOSviewer and bibliometrix R with Biblioshiny. The results reveal a significant growth in the number of UNTRM publications, with presence in high impact international journals and regional specialized sources. Prolific authors, prominent areas of knowledge such as Agricultural, Biological, Social, Environmental and Medical Sciences were identified, as well as a strong network of inter-institutional collaborations. The trend analysis showed a thematic diversity aligned with the institutional mission, encompassing biodiversity, environmental management, medicine, genetics and education, among others. In conclusion, this bibliometric study reveals a promising outlook for research at UNTRM, with remarkable growth, international presence, strong collaborations and thematic diversity relevant to the Amazon region.

The Role of Hydrogen Bonding in the Raman Spectral Signals of Caffeine in Aqueous Solution.

The identification and quantification of caffeine is a common need in the food and pharmaceutical industries and lately also in the field of environmental science. For that purpose, Raman spectroscopy has been used as an analytical technique, but the interpretation of the spectra requires reliable and accurate computational protocols, especially as regards the Resonance Raman (RR) variant. Herein, caffeine solutions are sampled using Molecular Dynamics simulations. Upon quantification of the strength of the non-covalent intermolecular interactions such as hydrogen bonding between caffeine and water, UV-Vis, Raman, and RR spectra are computed. The results provide general insights into the hydrogen bonding role in mediating the Raman spectral signals of caffeine in aqueous solution. Also, by analyzing the dependence of RR enhancement on the absorption spectrum of caffeine, it is proposed that the sensitivity of the RR technique could be exploited at excitation wavelengths moderately far from 266 nm, yet achieving very low detection limits in the quantification caffeine content.

Teaching Environmental Science to Children with Autism Spectrum Disorder: Including Environmentally Autistic Early Childhood Education

Apresentaremos os resultados de uma pesquisa que buscou a (i) compreensão das dificuldades que crianças com Transtorno do Espectro Autista (TEA) possuem acerca do Ensino das Ciências Ambientais e, junto disso, (ii) almejou evidenciar possibilidades para promover a inclusão ambiental em meio a processos de ensino e de aprendizagem vinculados à Educação Infantil destes educandos. O TEA se caracteriza por distúrbios neurológicos em que o sujeito resguarda dificuldades de comunicação, interação social e alterações sensoriais. A metodologia adotada – atividades acadêmicas antecedentes à confecção de nosso produto educacional – ligaram-se a (i) pesquisas bibliográficas e a (ii) entrevistas semiestruturadas com as quais levantamos informações junto aos professores que trabalham com crianças autistas. Este trabalho se justifica pelo auxílio a educadores interessados em incluir ambientalmente alunos autistas; sendo assim, o público atendido por ele foi composto de: (a) professores de crianças com TEA e (b) crianças autistas ensinadas por eles. Verificamos que os docentes detêm algumas imprecisões acerca do que é o TEA e das implicações dela no processo de ensino e de aprendizagem de crianças autistas, especialmente no que tange as Ciências Ambientais. Por conta disso, desenvolvemos um “folder” instrucional capaz de auxiliá-los nesse processo.

Mapping Environmental Quality Indices of Dhaka City by Using Geospatial Techniques

Dhaka, the city of over 10 million people is one of the most polluted cities due to rapid urbanization, commercial development and population pressure. The present study assessed an overall environmental quality of Dhaka South City Corporation (DSCC) and Dhaka North City Corporation (DNCC) using an Environmental Quality Index (EQI) based on five indices: Air Quality Index (AQI), Water Quality Index (WQI), Soil Quality Index (SQI), Noise Quality Index (NQI), and Vegetation Index (VI). The final EQI was determined through selecting components from background literature and an overlay analysis using predefined weights for each distinct indices. The study reveals that the west and west-central part of DSCC have experienced the most severe environmental degradation, affecting noise levels, vegetation cover, air, soil, and water quality. However, the air is less polluted especially in the peripheral zones of the city corporations. Overall, the study indicates that the environmental quality of DNCC is comparatively better than DSCC. The results of the study provides an insight on environmental quality of the city for legislators, urban planners, environmentalists, and researchers to monitor and preserve environmental quality in making the city livable, healthy and sustainable. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 12(2), 2023, P 41-53

Estimation of Consolidation and Settlement Characteristics of Madhupur Clay Formation from Dhaka City and Adjacent Area (Savar), Bangladesh

Pleistocene Madhupur Clay covers mostly the investigated region including Dhaka and the surrounding area (Savar). Without knowing the consolidation characteristics and settlement of this Clay, it is difficult for any construction sites to build infrastructure. In Bangladesh, the research on this parameter is limited hence for better understanding the consolidation and settlement behavior of Madhupur Clay samples in this area, a detail investigation is carried out by conducting one dimensional consolidation test. The undisturbed samples, Pleistocene Madhupur Clay and the fill materials which are also partly composed of the Madhupur Clay, are collected from 2.4 m to 4.11 m depths of many distinct points. The compression index Cc and coefficient of compressibility, av of the samples are range from 0.073 to 0.23 and from 0.059 to 0.14m2/mn respectively. The values recommend that both types of specimens are medium plastic clay. The Madhupur Clay are stiff consolidated clay and slightly compressible in nature whereas the Madhupur Clay fill samples are less stiff over consolidated and moderately compressible in nature. Fill samples are settled more with time and are not suitable for Shallow foundation of light or heavy infrastructure. However, the Madhupur Clay samples are only appropriate for light infrastructure foundation. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 12(2), 2023, P 27-39