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Energy Transition for Sustainability: Addressing Pollution and Climate Adaptation in Developing Countries
Abderraouf Ahmed Mtiraoui,
Leila Chemli,
Abdelmonem Snoussi
This study explores the impact of the energy transition on sustainable development in developing countries, focusing on pollution reduction, climate adaptation, and resilience. From 2000 to 2022, international funding, incentive policies, and capacity-building initiatives enabled the deployment of solar panels and small wind turbines, fostering job creation, reducing emissions, and improving energy access. A simultaneous equations model is used to examine the interactions between economic, institutional, social, and environmental factors. The research highlights the role of renewable energy, innovative policies, and localized initiatives in driving sustainable progress. Findings demonstrate how clean energy reduces greenhouse gases, strengthens institutional frameworks, and improves living conditions for vulnerable groups. Special attention is given to rural and isolated areas, where renewable energy fosters socio-economic and environmental benefits.
This study explores the impact of the energy transition on sustainable development in developing countries, focusing on pollution reduction, climate adaptation, and resilience. From 2000 to 2022, international funding, incentive policies, and capacity-building initiatives enabled the deployment of solar panels and small wind turbines, fostering job creation, reducing emissions, and improving energy access. A simultaneous equations model is used to examine the interactions between economic, institutional, social, and environmental factors. The research highlights the role of renewable energy, innovative policies, and localized initiatives in driving sustainable progress. Findings demonstrate how clean energy reduces greenhouse gases, strengthens institutional frameworks, and improves living conditions for vulnerable groups. Special attention is given to rural and isolated areas, where renewable energy fosters socio-economic and environmental benefits.
Posted: 17 February 2025
Smart, Sustainable Living: The Importance of Environmental Intelligence
Robin Precey
Posted: 17 February 2025
Social Acceptability of Waste-to-Energy: Research Hotspots, Technologies, and Factors
Casper Boongaling Agaton,
Marween Joshua A. Santos
Posted: 17 February 2025
Farmers’ Perception of the Efficacy of Current Climate risk Adaptation and Mitigation Strategies on Agriculture in The Gambia
Sheriff Ceesay,
Fatima Lambarraa-Lehnhardt,
Mohamed Ben Omar Ndiaye,
Diatou Thiaw,
Mamma Sawaneh,
Johannes Schuler
Agricultural systems face increasing challenges due to climate change, necessitating effective adaptation and mitigation strategies. This study investigates smallholder farmers' perceptions of the efficacy of these strategies in The Gambia, employing a mixed-method approach that includes a Perception Index (PI), Effectiveness Score (ES), Importance-Performance Analysis (IPA) and statistical analysis. A structured survey was conducted among 420 smallholder farmers across three agricultural regions. Farmers rated adaptation and mitigation strategies using a Likert scale, and a PI was developed to quantify their responses. The index was 0.66, indicating a moderate level of perceived effectiveness. Additionally, ES was calculated to assess the performance of various strategies, while IPA categorized strategies based on their adoption and perceived impact. Chi-square tests and factor analysis were applied to explore differences in perceptions. Findings reveal that strategies such as crop diversification, pesticide application, irrigation, and use of inorganic fertilizers are widely adopted and perceived as effective. The IPA matrix identified key strategies needing improvement, particularly those with high importance but low performance. Barriers to adoption include limited financial resources (77%), lack of government support (64%), and insufficient knowledge (52%), with no significant gender-based differences in perceptions. The study underscores the need for policy interventions that integrate farmers' perceptions to enhance climate resilience. Targeted investments in adaptive technologies, financial support, and knowledge-sharing platforms can improve adoption and effectiveness. This research provides valuable insights into the interplay between farmer perceptions, adaptation strategies, and agricultural sustainability in The Gambia.
Agricultural systems face increasing challenges due to climate change, necessitating effective adaptation and mitigation strategies. This study investigates smallholder farmers' perceptions of the efficacy of these strategies in The Gambia, employing a mixed-method approach that includes a Perception Index (PI), Effectiveness Score (ES), Importance-Performance Analysis (IPA) and statistical analysis. A structured survey was conducted among 420 smallholder farmers across three agricultural regions. Farmers rated adaptation and mitigation strategies using a Likert scale, and a PI was developed to quantify their responses. The index was 0.66, indicating a moderate level of perceived effectiveness. Additionally, ES was calculated to assess the performance of various strategies, while IPA categorized strategies based on their adoption and perceived impact. Chi-square tests and factor analysis were applied to explore differences in perceptions. Findings reveal that strategies such as crop diversification, pesticide application, irrigation, and use of inorganic fertilizers are widely adopted and perceived as effective. The IPA matrix identified key strategies needing improvement, particularly those with high importance but low performance. Barriers to adoption include limited financial resources (77%), lack of government support (64%), and insufficient knowledge (52%), with no significant gender-based differences in perceptions. The study underscores the need for policy interventions that integrate farmers' perceptions to enhance climate resilience. Targeted investments in adaptive technologies, financial support, and knowledge-sharing platforms can improve adoption and effectiveness. This research provides valuable insights into the interplay between farmer perceptions, adaptation strategies, and agricultural sustainability in The Gambia.
Posted: 17 February 2025
Visualising and Valuing Urban Agriculture for Land Use Planning: A Critical GIS Analysis of Sydney and Neighbouring Regions
Joshua Zeunert,
Scott Hawken,
Josh Gowers
Posted: 17 February 2025
Comparing Effects of the Proximity to Tree Trunks on Soil Nutrients and Fluorescence Spectral Characteristics of Dissolved Organic Carbon: A Case-Study of the Daqinggou National Nature Reserve in Southeastern Inner Mongolia
Zhiping Fan,
Litao Lin,
Xuekai Sun,
Guiyan Ai,
Guiyan Ai,
Jie Bai,
Jiawen Shi,
Wendi Shi
Vegetation restorations are crucial strategies for combating land degradation, yet their mechanisms on improving soil quality, especially from perspective of soil fertility, remain far from clear. Sparse trees in semi-arid savanna grasslands (i.e., climate communities) offer a provoking reference for vegetation restoration. Here, taking advantage of Ulmus macrocarpa Hance fertile islands of the savanna ecosystem in the Daqinggou National Nature Reserve, this study aimed to investigate the vertical and horizontal distribution patterns of soil physicochemical properties and DOC fluorescence spectral characteristics. Results showed that soil organic carbon (SOC) and DOC were significantly decreased with both the increasing distance from tree and increasing soil depth. Horizontal and vertical treatments significantly enhanced fluorescence intensities of DOC. Additionally, the soil under canopy exhibited slightly richer concentrations of NH4+–N, NO3––N, TN, and TP at topsoil compared with deep soils. The SOC, TN, TP, NH4+–N, and NO3––N showed significantly positive relationships with the DOC. The study provides evidence that trees can form fertile island effects and enhance soil nutrients and DOC. These results are vital for guiding vegetation restoration degraded ecosystem in semi-arid area.
Vegetation restorations are crucial strategies for combating land degradation, yet their mechanisms on improving soil quality, especially from perspective of soil fertility, remain far from clear. Sparse trees in semi-arid savanna grasslands (i.e., climate communities) offer a provoking reference for vegetation restoration. Here, taking advantage of Ulmus macrocarpa Hance fertile islands of the savanna ecosystem in the Daqinggou National Nature Reserve, this study aimed to investigate the vertical and horizontal distribution patterns of soil physicochemical properties and DOC fluorescence spectral characteristics. Results showed that soil organic carbon (SOC) and DOC were significantly decreased with both the increasing distance from tree and increasing soil depth. Horizontal and vertical treatments significantly enhanced fluorescence intensities of DOC. Additionally, the soil under canopy exhibited slightly richer concentrations of NH4+–N, NO3––N, TN, and TP at topsoil compared with deep soils. The SOC, TN, TP, NH4+–N, and NO3––N showed significantly positive relationships with the DOC. The study provides evidence that trees can form fertile island effects and enhance soil nutrients and DOC. These results are vital for guiding vegetation restoration degraded ecosystem in semi-arid area.
Posted: 17 February 2025
The Impact of PFAS on the Public Health and Safety of Future Food Supply in Europe: Challenges and AI Technologies Solutions of Environmental Sustainability
Ioannis Adamopoulos,
Antonios Valamontes,
John Karantonis,
Niki Syrou,
Ioanna Damikouka,
George Dounias
Posted: 17 February 2025
An Approach for Detecting Mangrove Areas and Mapping Species Using Multispectral Drone Imagery and Deep Learning
Xingyu Chen,
Xiuyu Zhang,
Changwei Zhuang,
Xuejiao Dai,
Lingling Kong,
Zixia Xie,
Xibang Hu
Posted: 17 February 2025
Co-variations of Geophysical Agents and Physicochemical Proper-ties of the Skin in Examinees in High Latitudes: Prospects for the Using of Gas-Discharge Visualization Method
Natalia Konstantinovna Belisheva,
Natalia Leonidovna Solovyevskaya,
Tatiana Andreevna Yusubova,
Ramiz Ragimogly Ysubov
The purpose of the study was to estimate the capabilities of the Gas Dis-charge Visualization (GDV) method for detection of effects of geophysical agents (GA) on the human body and to compare it's advantage with Galvanic Skin Response (GSR), usually applied for detection stress. The studies were conducted in 2017 and 2018 years on the Spitsbergen archipelago, and in 2023-2024 - in Apatity, Murmansk region, where daily the GDV and GSR indices were detected along of recruited participants of the study. For the first time, the daily covariations of GA and the GDV indices, mani-festing the physicochemical properties of the skin, were revealed in these studies. It was found, that correlations and their signs between the GA and GDV indices were determined by the intensity of the neutron flux at the Earth's surface, and the variabil-ity of the Solar Wind (SW). The correlations between the GDV and GA indices were reproduced in different years, in the case of comparability of the neutron level at the Earth's surface in the study period. The advantage of the GDV method, in comparing with the GSR was shown. The finding evident that GDV indices are indicators of ef-fects of GA on the human body.
The purpose of the study was to estimate the capabilities of the Gas Dis-charge Visualization (GDV) method for detection of effects of geophysical agents (GA) on the human body and to compare it's advantage with Galvanic Skin Response (GSR), usually applied for detection stress. The studies were conducted in 2017 and 2018 years on the Spitsbergen archipelago, and in 2023-2024 - in Apatity, Murmansk region, where daily the GDV and GSR indices were detected along of recruited participants of the study. For the first time, the daily covariations of GA and the GDV indices, mani-festing the physicochemical properties of the skin, were revealed in these studies. It was found, that correlations and their signs between the GA and GDV indices were determined by the intensity of the neutron flux at the Earth's surface, and the variabil-ity of the Solar Wind (SW). The correlations between the GDV and GA indices were reproduced in different years, in the case of comparability of the neutron level at the Earth's surface in the study period. The advantage of the GDV method, in comparing with the GSR was shown. The finding evident that GDV indices are indicators of ef-fects of GA on the human body.
Posted: 14 February 2025
Reconstruction of Effective Cross-Sections from DEMs and Water Surface Elevation for Hydraulic Modelling
Isadora Rezende,
Christophe Fatras,
Hind Oubanas,
Igor Gejadze,
P.-O. Malaterre,
Santiago Peña-Luque,
Alessio Domeneghetti
Posted: 14 February 2025
Environmental Study of Solid Waste Dumpsite in Rumueme, Portharcourt, South-South Nigeria
Victor N Nwugha,
Kenneth O Amanze,
Pamela Ify Okeke,
Glory J Okore,
Chinedum M Nwokoma,
Felix I Chinyem
Posted: 13 February 2025
The 2023 Major Baltic Inflow Event Observed by SWOT Altimetry
Saskia Esselborn,
Tilo Schöne,
Henryk Dobslaw,
Roman Sulzbach
Posted: 13 February 2025
Cd, Pb vs. Zn, Fe Accumulations in Button Mushrooms Fruit (Agaricus bisporus) Grown on Two Substrates
Brigita Popović,
Zdenko Lončarić,
Nada Parađiković,
Mihaela Blažinkov,
Nataša Romanjek Fajdetić
Posted: 13 February 2025
A Machine Learning-Driven Geophysical–Geotechnical Approach for Improved Engineering Site Assessment
Mbuotidem Dick,
Andy Bery,
Adedibu Akingboye,
Mfoniso Aka,
Joseph Gnapragasan,
Gabriel Bala,
Erukaa Moses,
Nsidibe Okonna
Subsurface geological formations are vital for validating deep engineering design assumptions, particularly in weathered terrains where unstable ground conditions pose risks. Geophysical investigations often face challenges due to inverse problem uncertainties and inadequate subsurface data. While resistivity and seismic P-wave velocity (Vp) imaging offer valuable insights, subsurface complexity necessitates integrated approaches for reliable characterization. This study introduces a machine learning-assisted geophysical–geotechnical framework combining electrical resistivity tomography, seismic refraction tomography, and borehole-based standard penetration tests (SPT-N). ML optimization metrics, including k-means clustering, PCA, Silhouette, elbow, and supervised linear regression, enhance analytical precision. A field survey over an 800 m segment in Kabota-Tawau, Sabah, Malaysia, utilized 490 collocated resistivity–Vp datasets to optimize cluster identification and interpretation accuracy. The analysis delineated four lithological units based on resistivity and Vp variations correlating with surface-subsurface properties. Clustering demonstrated strong performance, with an R² value approaching 1, a Silhouette score of 0.78, and an 88% reduction in the sum of square errors. Vulnerable zones, including weathered layers, fractures, and faults, were identified as critical for geotechnical consideration. In contrast, relatively weathered bedrock with hard-to-very-hard properties was deemed optimal for deep structural foundations requiring minimal reinforcement. This non-invasive approach enhances subsurface characterization, offering a reliable framework for construction site suitability and groundwater resource identification. It provides significant value for sedimentary regions with similar geological settings, advancing geotechnical and environmental planning.
Subsurface geological formations are vital for validating deep engineering design assumptions, particularly in weathered terrains where unstable ground conditions pose risks. Geophysical investigations often face challenges due to inverse problem uncertainties and inadequate subsurface data. While resistivity and seismic P-wave velocity (Vp) imaging offer valuable insights, subsurface complexity necessitates integrated approaches for reliable characterization. This study introduces a machine learning-assisted geophysical–geotechnical framework combining electrical resistivity tomography, seismic refraction tomography, and borehole-based standard penetration tests (SPT-N). ML optimization metrics, including k-means clustering, PCA, Silhouette, elbow, and supervised linear regression, enhance analytical precision. A field survey over an 800 m segment in Kabota-Tawau, Sabah, Malaysia, utilized 490 collocated resistivity–Vp datasets to optimize cluster identification and interpretation accuracy. The analysis delineated four lithological units based on resistivity and Vp variations correlating with surface-subsurface properties. Clustering demonstrated strong performance, with an R² value approaching 1, a Silhouette score of 0.78, and an 88% reduction in the sum of square errors. Vulnerable zones, including weathered layers, fractures, and faults, were identified as critical for geotechnical consideration. In contrast, relatively weathered bedrock with hard-to-very-hard properties was deemed optimal for deep structural foundations requiring minimal reinforcement. This non-invasive approach enhances subsurface characterization, offering a reliable framework for construction site suitability and groundwater resource identification. It provides significant value for sedimentary regions with similar geological settings, advancing geotechnical and environmental planning.
Posted: 13 February 2025
The Spatial Distribution and Driving Mechanism of Soil Organic Matter in Hilly Basin Areas Based on Genetic Algorithm Variable Combination Optimization and SHAP Interpretation
He Huang,
Yaolin Liu,
Yanfang Liu,
Zhaomin Tong,
Zhouqiao Ren,
Yifan Xie
Posted: 13 February 2025
Environmental Practice from Slovenia for Habitat Protection of Proteus anguinus
Aleksandar Šobot,
Diana Bilić-Šobot
Posted: 13 February 2025
Pyrolysis Kinetics of Herbaceous Biomass Feedstocks Using Isoconversion Methods
Oluwatosin Oginni
Pyrolysis is a major thermochemical conversion technology utilized in converting biomass to liquid fuel and bioproducts. A major process in this technology is the thermal decomposition of biomass which determines the pyrolysis products distribution. In order to optimize the distribution of these pyrolysis products, it is imperative to understand the thermal decomposition behaviors of the biomass feedstocks. The objective of this study was to investigate the thermal decomposition behaviors of Public Miscanthus and Kanlow Switchgrass using isoconversional methods. Thermogravimetric analysis was carried out by heating the biomass samples from room temperature to 700 ⁰C in an inert condition at heating rates of 5, 15, and 25 ºC/min. Three isoconversional methods (Friedman, Ozawa-Flynn-Wall, and Kissinger-Akhira-Sunrose) were used in estimating the kinetic parameters. The thermal decomposition process for the biomass samples was divided into three broad stages based on the temperature range, namely, moisture & light volatile release (< 200 ℃), devolatilization & biochar formation (200 – 400 ℃), and poly-condensation & biochar aromatization (> 400 ℃). The estimated activation energy values were influenced by the fractional conversion. There was a variation in the activation energy values estimated by the isoconversional methods, which is due to the difference in their estimation approach.
Pyrolysis is a major thermochemical conversion technology utilized in converting biomass to liquid fuel and bioproducts. A major process in this technology is the thermal decomposition of biomass which determines the pyrolysis products distribution. In order to optimize the distribution of these pyrolysis products, it is imperative to understand the thermal decomposition behaviors of the biomass feedstocks. The objective of this study was to investigate the thermal decomposition behaviors of Public Miscanthus and Kanlow Switchgrass using isoconversional methods. Thermogravimetric analysis was carried out by heating the biomass samples from room temperature to 700 ⁰C in an inert condition at heating rates of 5, 15, and 25 ºC/min. Three isoconversional methods (Friedman, Ozawa-Flynn-Wall, and Kissinger-Akhira-Sunrose) were used in estimating the kinetic parameters. The thermal decomposition process for the biomass samples was divided into three broad stages based on the temperature range, namely, moisture & light volatile release (< 200 ℃), devolatilization & biochar formation (200 – 400 ℃), and poly-condensation & biochar aromatization (> 400 ℃). The estimated activation energy values were influenced by the fractional conversion. There was a variation in the activation energy values estimated by the isoconversional methods, which is due to the difference in their estimation approach.
Posted: 13 February 2025
Retrospective Assessment of Bycatch Catch Rates in the Namibian Hake Directed Bottom Trawl Fishery: A Baseline for Long-Term Monitoring (1997–2014)
Samuel Kakambi Mafwila,
Evans Simasiku,
Johannes Angala Iitembu,
Greg Mbaimbai,
Anna-Marie Nambonga,
Kudakwashe Hove
Bottom trawling is not selective fishing method, resulting in the capture of many bycatch species. This study aimed to examine the distribution of bycatch species in the hake-directed bottom fishery and to determine their potential for bycatch management and mitigation. Observer data from a hake-directed bottom trawl fishery in Namibia from 1997 to 2014 was analysed. About 23 bycatch species, weighing 9,031,480 tonnes, were recorded. Trachurus capensis, Trachipterus trachypterus, Helicolenus dactylopterus, Lophius vomerinus, and Genypterus capensis were the dominant species, comprising 63.09% of the total catch by weight. Analysis of Similarities (ANOSIM) (R = 0.88, P< 0.05) revealed significant differences in catch composition based on sampling site. The Similarity Percentage (SIMPER) showed that three bycatch species contributed the most to the dissimilarity in groups for spatial distribution. Widespread distribution of bycatch species, with high densities in the central and southern regions, suggests that hake-directed bottom trawling could have negative effects on these species. Species with a higher proportion of their population removed as bycatch, are considered the most vulnerable and may be nearly exterminated. To avoid the risk of species extinction, the fishery must be managed through spatial exclusion and fishing seasons.
Bottom trawling is not selective fishing method, resulting in the capture of many bycatch species. This study aimed to examine the distribution of bycatch species in the hake-directed bottom fishery and to determine their potential for bycatch management and mitigation. Observer data from a hake-directed bottom trawl fishery in Namibia from 1997 to 2014 was analysed. About 23 bycatch species, weighing 9,031,480 tonnes, were recorded. Trachurus capensis, Trachipterus trachypterus, Helicolenus dactylopterus, Lophius vomerinus, and Genypterus capensis were the dominant species, comprising 63.09% of the total catch by weight. Analysis of Similarities (ANOSIM) (R = 0.88, P< 0.05) revealed significant differences in catch composition based on sampling site. The Similarity Percentage (SIMPER) showed that three bycatch species contributed the most to the dissimilarity in groups for spatial distribution. Widespread distribution of bycatch species, with high densities in the central and southern regions, suggests that hake-directed bottom trawling could have negative effects on these species. Species with a higher proportion of their population removed as bycatch, are considered the most vulnerable and may be nearly exterminated. To avoid the risk of species extinction, the fishery must be managed through spatial exclusion and fishing seasons.
Posted: 13 February 2025
Exploring High PT Experimental Charges Through the Lens of Phase Maps
Balz Samuel Kamber,
Marco Andres Acevedo Zamora,
Rodrigo Freitas Rodrigues,
Ming Li,
Gregory Yaxley,
Matthew Ng
Posted: 12 February 2025
Prediction of Oil Films on the Ocean: An Analysis of the Impact of Meteoceanographic Variables and Total Oil and Grease During Primary Petroleum Processing
Simone C Streitenberger,
Estevão L Romão,
Fabricio A Almeida,
Antonio Carlos Zambroni de Souza,
Aloisio E Orlando Jr.,
Pedro Paulo Balestrassi
Posted: 12 February 2025
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