Environmental and Earth Sciences Proceedings

9 pages, 236 KB

Open AccessProceeding Paper

The Urban Light Plan: Toward Sustainable and Resilient Cities

by Celestina Fazia, Giulia Fernanda Grazia Catania and Federica Sortino

Environ. Earth Sci. Proc. 2025, 36(1), 11; https://doi.org/10.3390/eesp2025036011 - 26 Dec 2025

Urban lighting is evolving from a basic technical infrastructure to a strategic tool for sustainable regeneration, energy efficiency, and public space reactivation. This paper explores the potential of smart and adaptive lighting systems as enablers of 24 h services, equitable access, and environmental [...] Read more.

Urban lighting is evolving from a basic technical infrastructure to a strategic tool for sustainable regeneration, energy efficiency, and public space reactivation. This paper explores the potential of smart and adaptive lighting systems as enablers of 24 h services, equitable access, and environmental resilience. By integrating lighting strategies with urban planning instruments (PRIC, PEC, PMU), cities can reduce energy consumption, limit light pollution, and foster new urban centralities. The study outlines regulatory gaps, technical solutions, and cultural shifts needed to transform lighting into a key asset for livable, inclusive, and digitally enabled urban futures. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

7 pages, 850 KB

Open AccessProceeding Paper

Urban 3D Multiple Deep Base Change Detection by Very High-Resolution Satellite Images and Digital Surface Model

by Alireza Ebrahimi and Mahdi Hasanlou

Environ. Earth Sci. Proc. 2025, 36(1), 13; https://doi.org/10.3390/eesp2025036013 - 22 Dec 2025

Abstract

Timely and accurate urban change detection is vital for sustainable urban development, infrastructure management, and disaster response. Traditional two-dimensional approaches often overlook vertical and structural variations in dense urban areas. This study proposes a three-dimensional (3D) change detection framework that integrates high-resolution optical [...] Read more.

Timely and accurate urban change detection is vital for sustainable urban development, infrastructure management, and disaster response. Traditional two-dimensional approaches often overlook vertical and structural variations in dense urban areas. This study proposes a three-dimensional (3D) change detection framework that integrates high-resolution optical imagery and Digital Surface Models (DSMs) from two time points to capture both horizontal and vertical transformations. The method is based on a deep learning architecture combining a ResNet34 encoder with a UNet++ decoder, enabling the joint learning of spectral and elevation features. The research was carried out in two stages. First, a binary classification model was trained to detect areas of change and no-change, allowing direct comparison with conventional methods such as Principal Component Analysis (PCA), Change Vector Analysis (CVA) with thresholding, K-Means clustering, and Random Forest classification. In the second stage, a multi-class model was developed to categorize the types of structural changes, including new building construction, complete destruction, building height increase, and height decrease. Experiments conducted on a high-resolution urban dataset demonstrated that the proposed CNN-based framework significantly outperformed traditional methods, achieving an overall accuracy of 96.58%, an F1-score of 96.58%, and a recall of 96.7%. Incorporating DSM data notably improved sensitivity to elevation-related changes. Overall, the ResNet34–UNet++ architecture offers a robust and accurate solution for 3D urban change detection, supporting more effective urban monitoring and planning. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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10 pages, 10963 KB

Open AccessProceeding Paper

The Strait Bridge as an Opportunity for Careful Strategic Architectural and Urban Regeneration

by Clara Stella Vicari Aversa and Celestina Fazia

Environ. Earth Sci. Proc. 2025, 36(1), 12; https://doi.org/10.3390/eesp2025036012 - 22 Dec 2025

Abstract

The Strait of Messina occupies a strategic position in the Mediterranean, representing an environmental and territorial peculiarity. The Strait area today is at the center of the political debate for the stable crossing project, a strategic infrastructure work for Italy and Europe. With [...] Read more.

The Strait of Messina occupies a strategic position in the Mediterranean, representing an environmental and territorial peculiarity. The Strait area today is at the center of the political debate for the stable crossing project, a strategic infrastructure work for Italy and Europe. With the Strait Bridge, territorial arrangements, sea fronts, infrastructure systems, and urban and architectural dimensions will change. It appears necessary to prepare the territories and take advantage of all the opportunities related to future scenarios. The Strait area is not only marked by the crossing, but the whole territorial and urban system—the coastal strip and inland areas—becomes an active part of the processes of territorial regeneration and development. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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8 pages, 3130 KB

Open AccessProceeding Paper

Propagation of Climate Model Variability to Coastal Groundwater Simulations Under Climate Change

by Aikaterini Lyra, Athanasios Loukas, Pantelis Sidiropoulos and Nikitas Mylopoulos

Environ. Earth Sci. Proc. 2024, 31(1), 24; https://doi.org/10.3390/eesp2025032024 - 19 Dec 2025

Abstract

This study investigates the propagation of climate model variability to coastal groundwater systems under the high-emission RCP8.5 scenario, focusing on the Almyros Basin in Greece. Using Med-CORDEX bias-corrected climate projections, an Integrated Modelling System (IMS) combines UTHBAL (surface hydrology) and MODFLOW (groundwater hydrology) [...] Read more.

This study investigates the propagation of climate model variability to coastal groundwater systems under the high-emission RCP8.5 scenario, focusing on the Almyros Basin in Greece. Using Med-CORDEX bias-corrected climate projections, an Integrated Modelling System (IMS) combines UTHBAL (surface hydrology) and MODFLOW (groundwater hydrology) to simulate future conditions, including precipitation, temperature, evapotranspiration, groundwater recharge, water balance, and seawater intrusion (as a quantity). The analysis quantifies both central tendencies and inter-model spread, revealing substantial declines in groundwater recharge and intensified seawater intrusion, while highlighting the uncertainty introduced by climate model projections. These findings provide critical insights for adaptive water resource management and planning in Mediterranean coastal aquifers under climate change. Full article

(This article belongs to the Proceedings of The 4th International Electronic Conference on Forests)

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1 pages, 146 KB

Open AccessEditorial

Statement of Peer Review

by Anthony R. Lupo

Environ. Earth Sci. Proc. 2025, 34(1), 19; https://doi.org/10.3390/eesp2025034019 - 9 Dec 2025

Abstract

In submitting conference proceedings to Environmental and Earth Sciences Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...] Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

5 pages, 484 KB

Open AccessProceeding Paper

Immediate and Residual Effects of Cattle Corralling and Mineral Fertilizer in Maize Cropping Systems in the Sub-Humid Zone of Northern Benin: Yields, Resource-Use Efficiency, Economic Profitability, and Post-Harvest Soil Fertility

by Pierre G. Tovihoudji, Sourogou Anasse Gounou, Mouiz W. I. A. Yessoufou, Sissou Zakari, André Adjogboto and P. B. Irénikatché Akponikpè

Environ. Earth Sci. Proc. 2025, 36(1), 10; https://doi.org/10.3390/eesp2025036010 - 9 Dec 2025

Abstract

Effective management of organic and inorganic fertilizers is vital for sustaining productivity in intensive cropping systems. This four-year study (2012–2015) assessed the immediate and residual effects of cattle corralling combined with mineral fertilizer on maize in northern Benin using a strip-plot design with [...] Read more.

Effective management of organic and inorganic fertilizers is vital for sustaining productivity in intensive cropping systems. This four-year study (2012–2015) assessed the immediate and residual effects of cattle corralling combined with mineral fertilizer on maize in northern Benin using a strip-plot design with five corralling levels No corralling(NM), immediate application (C0) and residual effects one (C1), two (C2), and three (C3) years after the initial corralling and three fertilizer rates F0 (no fertilizer), F1 (50% of the recommended rate) and F2 (the recommended rate). Cattle corralling doubled maize yield from 2.0 to 4.0 t ha⁻¹ and increased net profitability from 384 to 1000 USD ha⁻¹ compared to non-manured plots. Water-use efficiency increased from 3.4 to 6.8 kg ha⁻¹ mm⁻¹, and soil organic carbon increased nearly fourfold (3.0 to 11.2 g kg⁻¹). Residual effects declined over time without mineral inputs (C0 > C1 > C2 > C3 > NM); however, these benefits were sustained or enhanced when combined with fertilizer (C3 > C2 > C1 > C0 > NM). Fertilizer responses were minor in C0 and C1 but significant in C2 and C3, demonstrating a strong organic–inorganic synergy. Nutrient recovery efficiency was initially lower in recently corralled plots but surpassed non-manured levels after two years. These results confirm that integrating livestock corralling with optimized fertilizer use strengthens soil fertility, resource efficiency, and profitability, providing a sustainable intensification pathway for maize systems in sub-humid, low-fertility regions. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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13 pages, 721 KB

Open AccessConference Report

Chanjman Atmosfè a—Creating a Change in the Atmosphere to Broaden Climate Conversations with a Focus on Haiti

by Camellia Moses Okpodu, Bridger Huhn, Samelia Okpodu-Pyuzza and Calherbe Monel

Environ. Earth Sci. Proc. 2025, 38(1), 1; https://doi.org/10.3390/eesp2025038001 - 9 Dec 2025

Abstract

Our annual environmental conference has been a pivotal platform for addressing the unique environmental challenges faced by underrepresented communities since 2006. Adapting to the global pandemic in 2021, we seamlessly transitioned to a virtual environment, enabling us to concentrate our efforts on the [...] Read more.

Our annual environmental conference has been a pivotal platform for addressing the unique environmental challenges faced by underrepresented communities since 2006. Adapting to the global pandemic in 2021, we seamlessly transitioned to a virtual environment, enabling us to concentrate our efforts on the critical role of the diaspora in leveraging scientific knowledge. In 2023, we focused on Haiti, a nation currently facing significant political turmoil. Our one-day virtual event featured three expert panels that delved into multifaceted strategies encompassing agriculture, healthcare, political advocacy, social dynamics, and entrepreneurship. These discussions aimed to equip Haiti to navigate the impacts of climate change effectively. In partnership with the Haiti Development Initiative (HDI), we engaged in a dynamic brainstorming session to generate innovative approaches for cultivating a resilient and sustainable economy. Our guiding mantra, the Haitian Creole phrase “Chanjman atmosfè a,” reflects our commitment to transforming the environmental landscape—shifting the atmosphere. A highlight of the event was the presentation by Computational Biology students from the University of Wyoming. Their project, titled “Using R Software to Compare Climate Data,” showcased an innovative pedagogical approach to analyzing climate data using statistical software. Their presentation demonstrated the practical application of computational tools in understanding and addressing climate change, providing valuable insights and methodologies that can be applied to environmental research in Haiti and beyond. Full article

(This article belongs to the Proceedings of The Climate Conversation 2023—A Focus on Haiti)

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70 pages, 570 KB

Open AccessConference Report

Remarks and Abstracts of the 1st International Symposium on Energy and Meteorology (SIEME)

by Maria Cristina Lemos Da Silva, Helber Barros Gomes, Fernando Ramos Martins, Samira de Azevedo Santos Emiliavaca, Amanda Santana Peiter, Dirceu Luis Herdies, Heliofábio Barros Gomes, Glauber Lopes Mariano and Marisol Osman

Environ. Earth Sci. Proc. 2025, 39(1), 1; https://doi.org/10.3390/eesp2025039001 - 4 Dec 2025

Abstract

The First International Symposium on Energy and Climate (SIEME 2025) has been held in Maceió, Brazil, from 20 to 22 August 2025. Organized by the Federal University of Alagoas (UFAL) and partner institutions, the event focuses on innovations and strategies in renewable energy, [...] Read more.

The First International Symposium on Energy and Climate (SIEME 2025) has been held in Maceió, Brazil, from 20 to 22 August 2025. Organized by the Federal University of Alagoas (UFAL) and partner institutions, the event focuses on innovations and strategies in renewable energy, climate resilience, and green hydrogen within the global energy transition context. The symposium will feature keynote lectures, thematic sessions, round tables, and short courses addressing topics such as energy efficiency, extreme weather impacts, and sustainable technologies. Researchers, policymakers, and industry professionals from the Americas, among other countries, collaborated to advance sustainable energy solutions and climate adaptation strategies. Full article

(This article belongs to the Proceedings of The International Symposium on Energy and Meteorology (SIEME) 2025)

8 pages, 1233 KB

Open AccessProceeding Paper

Advancing Nanotoxicology: High-Throughput Screening for Assessing the Toxicity of Nanoparticle Mixtures

by Newton Neogi, Kristi Priya Choudhury, Sabbir Hossain, Md. Golam Sazid and Ibrahim Hossain

Environ. Earth Sci. Proc. 2025, 37(1), 2; https://doi.org/10.3390/eesp2025037002 - 3 Dec 2025

Abstract

The widespread application of nanoparticles (NPs) in fields ranging from consumer products to industrial processes has led to increased concerns about their potential toxic effects on human health and the environment. While traditional toxicological studies often evaluate the effects of individual NPs, real-world [...] Read more.

The widespread application of nanoparticles (NPs) in fields ranging from consumer products to industrial processes has led to increased concerns about their potential toxic effects on human health and the environment. While traditional toxicological studies often evaluate the effects of individual NPs, real-world exposure scenarios typically involve mixtures of NPs, where interactions between particles can significantly alter their toxicological profiles. This study provides an overview of overcoming this gap by possible utilization of high-throughput screening (HTS) for evaluation of the combined effects of NP mixtures under various exposure conditions. This review discusses HTS of metal oxide NPs, which have cytotoxic, genotoxic, and oxidative stress-inducing effects. Using HTS, this review describes multiple studies with multiple mixture ratios and exposure durations using human lung epithelial cells and zebrafish embryo systems. The review also describes a range of interactions, from synergistic effects, where the combined toxicity might be the sum of individual toxicities. Oxidative stress and metal ion release were key drivers of toxicity, particularly in metal oxide-dominant NP mixtures. This theoretical study highlights the importance of integrating HTS into nanotoxicology research to provide a more comprehensive understanding of the toxic behavior of NPs. Full article

(This article belongs to the Proceedings of The 2nd International Online Conference on Toxics)

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13 pages, 4244 KB

Open AccessProceeding Paper

Soil Moisture Mapping Using Sentinel-1 SAR Data and Cloud-Based Regression Modeling on Google Earth Engine

by Tarun Teja Kondraju, Selvaprakash Ramalingam, Rajan G. Rejith, Amrita Bhandari, Rabi N. Sahoo and Rajeev Ranjan

Environ. Earth Sci. Proc. 2025, 36(1), 9; https://doi.org/10.3390/eesp2025036009 - 27 Nov 2025

Abstract

Soil moisture is an essential environmental parameter affecting hydrological cycles, agricultural productivity, and climate systems. Conventional in situ measurements are precise but do not provide the spatiotemporal coverage for large applications. This research provides an extensive framework for estimating and mapping surface soil [...] Read more.

Soil moisture is an essential environmental parameter affecting hydrological cycles, agricultural productivity, and climate systems. Conventional in situ measurements are precise but do not provide the spatiotemporal coverage for large applications. This research provides an extensive framework for estimating and mapping surface soil moisture by integrating Sentinel-1 Synthetic Aperture Radar (SAR) data with machine learning in the Google Earth Engine (GEE) cloud platform. The study area is the agricultural region of Perambalur district in Tamil Nadu State, India. The research took place between September 2018 and January 2019. The dual-polarized (VV and VH) Sentinel-1 C-band images were collected in tandem with ground truth soil moisture data collected through the gravimetric method. A set of SAR indices and engineered features were extracted from the backscattering coefficients (σ°). A random forest (RF) machine learning model was used in this study to estimate soil moisture. The RF model incorporating the complete set of engineered features showed a coefficient of determination (R²) of 0.694 and a root mean square error (RMSE) of 1.823 (Soil moisture %). The complete processing and modeling workflow was encapsulated in the GEE-based software tool (version 1) providing an accessible, user-friendly platform for generating near-real-time maps of soil moisture. This research proves that the combination of Sentinel-1 data with clever machine-learning algorithms in the GEE cloud platform provides a scalable, efficient, and potent tool for operational soil moisture mapping serving applications in precision agriculture and in the management of the water resource. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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16 pages, 25819 KB

Open AccessProceeding Paper

Conservancies: A Demonstrable Local-Level Action for the Sustainable Development Goals in an African Indigenous Frontier

by Alexander Omondi Imbo, Uta Wehn and Kenneth Irvine

Environ. Earth Sci. Proc. 2025, 36(1), 8; https://doi.org/10.3390/eesp2025036008 - 25 Nov 2025

Abstract

This paper examines an approach to local-level community action for the global Sustainable Development Goals (SDGs), amid the growing importance of context-specific implementations to accelerate progress. Land-use governance is critical for contributions to the SDGs, as it shapes a wide range of environmental, [...] Read more.

This paper examines an approach to local-level community action for the global Sustainable Development Goals (SDGs), amid the growing importance of context-specific implementations to accelerate progress. Land-use governance is critical for contributions to the SDGs, as it shapes a wide range of environmental, social, and economic outcomes. Wildlife conservancies provide an innovative community-driven land-stewardship model that has proliferated across rangelands in various African countries as a sustainable development strategy. This study explores the potential contribution and capacity of conservancies, as a form of land-use governance, in advancing the SDGs at local levels. Using case studies from Kenya’s Maasai Mara, the research draws on qualitative primary data collected through in-depth interviews, a focus group discussion, observation, and document review, supplemented by secondary data obtained from a literature review. The data was analyzed thematically. The results show that conservancies address key socio-ecological challenges corresponding with multiple SDGs, particularly those related to poverty reduction, food security, climate action, and life on land. However, significant segments of local communities remain marginalized in decision making and benefit sharing, a situation rooted in pre-existing social hierarchies and weak governance institutions, raising concerns about social justice. Other major limitations are related to the conservancies’ over-reliance on tourism, and local people’s high dependence on natural resources. To resolve these limitations, the study recommends improving local governance via institutional strengthening, capacity building, gender empowerment, and stakeholder partnerships; diversifying income sources to reduce financial vulnerability; and adopting strategies to alleviate high dependence on natural resources in the long term. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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51 pages, 451 KB

Open AccessConference Report

Abstracts of the 7th International Electronic Conference on Atmospheric Sciences (ECAS-7)

by Anthony R. Lupo

Environ. Earth Sci. Proc. 2025, 34(1), 18; https://doi.org/10.3390/eesp2025034018 - 24 Nov 2025

Abstract

The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7) was held online from 4 to 6 June 2025 [...] Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

9 pages, 4799 KB

Open AccessProceeding Paper

Rainfall Runoff Simulation for Climate-Resilient Watershed Management: A Case Study of the Mangla Watershed, Pakistan

by Saffi Ur Rehman, Tingting Chang, Muhammad Zaman and Abdullah Bin Jaweed

Environ. Earth Sci. Proc. 2025, 36(1), 7; https://doi.org/10.3390/eesp2025036007 - 24 Nov 2025

Abstract

Due to climate change, runoff simulations and understanding the relationship between rainfall and runoff are crucial for watershed management. This study combined a Geographic Information System (GIS) and the Hydrologic Engineering Centre-Hydrologic Modeling System (HEC-HMS) to simulate rainfall-based runoff for the Mangla Watershed. [...] Read more.

Due to climate change, runoff simulations and understanding the relationship between rainfall and runoff are crucial for watershed management. This study combined a Geographic Information System (GIS) and the Hydrologic Engineering Centre-Hydrologic Modeling System (HEC-HMS) to simulate rainfall-based runoff for the Mangla Watershed. We used freely available satellite-based topography, soil and land use and land cover data, along with daily rainfall and discharge data for the hydrological modeling. For model generation, key parameters include the Curve Number method, the Unit Hydrograph method, the recession baseflow method, and the Muskingum routing method. The model was manually calibrated from 1991 to 2000 and validated from 2001 to 2010 and a sensitivity analysis was performed to check the model behavior and hydrological response of the watershed upon changing model parameters. The model’s efficiency was tested based on its statistical parameters, like the root mean square error (RMSE), standard deviation, Percent Bias, and Nash–Sutcliffe Efficiency. The Nash–Sutcliffe Efficiency for calibration and validation was 0.919 and 0.945, respectively. The findings demonstrate that HEC-HMS is an effective tool for rainfall-based runoff modeling in the Mangla Watershed and providing valuable insights for flood risk management and climate-resilient planning by using hydrological modeling to predict runoff dynamics, optimize reservoir operations, and inform adaptive strategies for managing water resources under changing climate conditions. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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8 pages, 1367 KB

Open AccessProceeding Paper

Wildfire Damage Assessment over Eaton Canyon, California, Using Radar and Multispectral Datasets from Sentinel Satellites and Machine Learning Methods

by Jacques Bernice Ngoua Ndong Avele and Viktor Sergeevich Goryainov

Environ. Earth Sci. Proc. 2025, 36(1), 6; https://doi.org/10.3390/eesp2025036006 - 20 Nov 2025

Abstract

Eaton Canyon in California serves as the focal point for a comprehensive post-wildfire ecological impact assessment. This study employs an approach integrating satellite imagery from the European Space Agency’s Sentinel constellation to study an area of 271.49 km². The data encompasses [...] Read more.

Eaton Canyon in California serves as the focal point for a comprehensive post-wildfire ecological impact assessment. This study employs an approach integrating satellite imagery from the European Space Agency’s Sentinel constellation to study an area of 271.49 km². The data encompasses both radar and multispectral data, offering a multi-dimensional view of the affected landscape. The analysis leverages the power of the random forest algorithm. Firstly, three widely used indices—the difference normalized burn ratio (dNBR), relative burn ratio (RBR), and relative difference normalized burn ratio (RdNBR)—were calculated and compared based on their accuracy and Kappa index. Secondly, we developed a fusion approach by using all the fire indices to obtain a precise severity map by classifying the affected area into distinct severity classes. Thirdly, a separate fusion approach was developed utilizing the normalized difference vegetation index (NDVI), radar vegetation index (RVI), and modified normalized difference vegetation index (MNDVI) to analyze the distribution of vegetation before and after the wildfire. The merger proposals were developed using a combination of index values to obtain better information on the fire severity map and post-fire vegetation distribution. The results indicated an accuracy of 78% when employing the dNBR index. A higher accuracy of 81% was observed with the RBR index, while the RdNBR demonstrated an accuracy of 95%. Our approach, which combines all fire indicators, offers optimal accuracy of 99%. A percentage of 56.76% did not burn due to the topography of the canyon creating natural firebreaks. Areas classified as low severity (7.83%) showed minimal damage with minimal tree mortality. Moderate- to low-severity areas (5.83%) represented regions with partial crown burns and some tree mortality. Moderate- to high-severity areas (7.22%) showed significant tree mortality. Finally, high-severity areas (22.36%), characterized by complete tree mortality and significant loss of vegetation cover, were largely concentrated in specific sections of the canyon, likely influenced by factors such as slope and fuel type. These findings provide valuable information for post-fire ecological recovery efforts and future land management strategies in Eaton Canyon and similar fire-prone landscapes. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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12 pages, 1770 KB

Open AccessProceeding Paper

Assessing Industrial Land Suitability for Sustainable Urban Planning in Dhaka Region Using Geospatial Techniques

by Sk. Tanjim Jaman Supto, Dewan Reza Hamid Karzai and Ettahad Islam Adib

Environ. Earth Sci. Proc. 2025, 36(1), 5; https://doi.org/10.3390/eesp2025036005 - 19 Nov 2025

Abstract

The Dhaka District is experiencing rapid industrial growth alongside uncontrolled urban expansion, leading to significant land-use conflicts and environmental pressures. This study investigates how to identify the optimal sites for industrial development that support sustainable urban growth by leveraging Geographic Information Systems (GISs), [...] Read more.

The Dhaka District is experiencing rapid industrial growth alongside uncontrolled urban expansion, leading to significant land-use conflicts and environmental pressures. This study investigates how to identify the optimal sites for industrial development that support sustainable urban growth by leveraging Geographic Information Systems (GISs), combined with a structured decision-making approach. The analysis incorporates key environmental and infrastructural factors to guide responsible planning aligned with global sustainability objectives. This study integrates spatial variables such as transport accessibility, land use, environmental sensitivity, and infrastructure presence. Up-to-date satellite imagery and land-use information from recent years ensure relevant and precise analysis. The findings indicate that roughly 10–15% of Dhaka District is suitable for industrial activities, predominantly the western and northwestern edges of the district. However, a considerable portion of existing industries are situated outside the officially designated zones, with nearly 9% infringing on protected environments, pointing to gaps in land management policies. Additionally, industrial expansion resulted in the conversion of over thousands of hectares of natural land, underscoring urgent ecological concerns. Scenario modeling further demonstrates how strategic land allocation can balance industrial growth with environmental conservation. This research highlights the value of integrating a GIS with multi-criteria evaluation using Analytical Hierarchy Process (AHP) to provide a flexible, data-driven framework for sustainable industrial land-use planning. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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7 pages, 861 KB

Open AccessProceeding Paper

Nanoparticle-Induced Oxidative Stress: Mechanisms and Implications for Human Health and Environmental Safety

by Newton Neogi, Kristi Priya Choudhury, Ibrahim Hossain, Sabbir Hossain and Md. Golam Sazid

Environ. Earth Sci. Proc. 2025, 37(1), 1; https://doi.org/10.3390/eesp2025037001 - 19 Nov 2025

Abstract

Nanoparticles (NPs), which possess unique physicochemical qualities such as large surface area and reactivity, have brought about a revolution in a variety of sectors, including medicine and electronics. The growing ubiquity of these substances, on the other hand, has given rise to worries [...] Read more.

Nanoparticles (NPs), which possess unique physicochemical qualities such as large surface area and reactivity, have brought about a revolution in a variety of sectors, including medicine and electronics. The growing ubiquity of these substances, on the other hand, has given rise to worries over the toxicological effects they have on human health and ecosystems. The condition known as oxidative stress, which is caused by an imbalance between the formation of reactive oxygen species (ROS) and antioxidant defenses, is one of the key processes that contribute to the toxicity of NPs. An excessive amount of ROS may cause damage to cellular components such as lipids, proteins, and DNA, which can result in detrimental consequences such as inflammation, apoptosis, and the development of cancer. NP-induced oxidative stress is investigated in this work, which focuses on the molecular mechanisms that are responsible for it. These processes include mitochondrial dysfunction, catalytic redox cycling, and the release of metal ions from particle disintegration. On top of that, we investigate how the features of NPs, such as their size, shape, surface charge, and composition, affect their capacity to produce ROS. Additionally, the consequences of oxidative stress for both acute and chronic health effects are examined, in addition to the function that it plays in the toxicity of the environment. The use of antioxidants and alterations to the surface of NPs are two examples of mitigation measures that are discussed in this article. The findings of this study highlight the significance of gaining knowledge of the processes behind oxidative stress to ensure the safe design and deployment of NPs. Full article

(This article belongs to the Proceedings of The 2nd International Online Conference on Toxics)

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7 pages, 2224 KB

Open AccessProceeding Paper

Temporal Analysis of Groundwater Quality in the Harran Plain: Linking Land Use Change to Water Contamination (2005–2025)

by Benan Yazici Karabulut and Abdullah İzzeddin Karabulut

Environ. Earth Sci. Proc. 2025, 36(1), 4; https://doi.org/10.3390/eesp2025036004 - 18 Nov 2025

Abstract

This study evaluates groundwater quality dynamics in the Harran Plain (∼1500 km²), a key agricultural zone within Türkiye’s Southeastern Anatolia Project (GAP). Satellite images from Landsat 5 TM and Landsat 8 OLI/TIRS were used to assess land-use changes over the years [...] Read more.

This study evaluates groundwater quality dynamics in the Harran Plain (∼1500 km²), a key agricultural zone within Türkiye’s Southeastern Anatolia Project (GAP). Satellite images from Landsat 5 TM and Landsat 8 OLI/TIRS were used to assess land-use changes over the years 1990, 2000, 2010, and 2020, with the GIS employed for classification and analysis. In this study, groundwater samples collected from twenty different locations in 2005, 2015 and 2025 were analyzed. For each sample, pH, EC, and various ion concentrations (Na, K, Cl, SO₄, NO₃, Ca, Mg, HCO₃) were measured. All analyses were performed using standard hydrogeochemical methods. Data from 20 wells (2005–2015) revealed significant reductions in EC (8235 to 2510 µS/cm) and NO₃⁻ (720 to 327 mg/L), due to drainage systems, improved irrigation, and fertilizer management. Nonetheless, localized pollution persisted. Land-use shifts toward high-value crops improved water efficiency, while urban and industrial expansion introduced new pressures. Results emphasize integrated water–land policies for sustainable groundwater management in arid agroecosystems. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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9 pages, 2358 KB

Open AccessProceeding Paper

Generation of Synthetic Hyperspectral Image Cube for Mapping Soil Organic Carbon Using Proximal Remote Sensing

by Rajan G. Rejith, Rabi N. Sahoo, Tarun Kondraju, Amrita Bhandari, Rajeev Ranjan and Ali Moursy

Environ. Earth Sci. Proc. 2025, 36(1), 3; https://doi.org/10.3390/eesp2025036003 - 18 Nov 2025

Abstract

The advent of hyperspectral remote sensing represented a breakthrough in the accurate, fast, and non-invasive estimation of important soil fertility parameters. The present study utilizes non-imaging hyperspectral data in the spectral range of 350–2500 nm for estimating soil organic carbon (SOC) content. When [...] Read more.

The advent of hyperspectral remote sensing represented a breakthrough in the accurate, fast, and non-invasive estimation of important soil fertility parameters. The present study utilizes non-imaging hyperspectral data in the spectral range of 350–2500 nm for estimating soil organic carbon (SOC) content. When partial least squares (PLS) scores were taken as independent variables, support vector machine (SVM) outperformed artificial neural network (ANN) and partial least squares regression (PLSR), achieving an R² value of 0.83. After pre-processing, the proximal spectral values were spatially interpolated to construct a synthetic hyperspectral image of the experimental fields. By applying the regression model to this synthetic hyperspectral imagery, a high-resolution SOC map showing the variability of organic carbon content in the soil was generated. Full article

(This article belongs to the Proceedings of The 2nd International Electronic Conference on Land)

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4 pages, 200 KB

Open AccessProceeding Paper

Efficient Nitrous Oxide Capture from Dam Lake Treatment by Malt Dust-Derived Biochar

by Pelin Soyertaş Yapıcıoğlu and Mehmet İrfan Yeşilnacar

Environ. Earth Sci. Proc. 2025, 34(1), 17; https://doi.org/10.3390/eesp2025034017 - 17 Nov 2025

Abstract

Owing to the natural texture of dam lakes, they emit nitrous oxide (N₂O) emissions. The main aim of this study was to reduce N₂O emissions resulting from dam lake treatment using malt dust-derived biochar. On average, a 21.1% reduction [...] Read more.

Owing to the natural texture of dam lakes, they emit nitrous oxide (N₂O) emissions. The main aim of this study was to reduce N₂O emissions resulting from dam lake treatment using malt dust-derived biochar. On average, a 21.1% reduction in N₂O emissions from dam lake treatment was reported using malt dust-derived biochar. The maximum nitrous oxide capture capacity corresponded to the malt dust-derived biochar fabricated at the minimum pyrolysis temperature (MD1). The statistical analysis results revealed that the optimum parameters were 4 mg/L of dissolved oxygen (DO) and 11 mg/L of nitrate (NO₃⁻) for the minimum N₂O emission. The highest correlation was calculated between N₂O emission and NO₃⁻ with the value of 97.99%. This study evidenced that agro-industrial biochar can adsorb N₂O from dam lakes. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

Journal Description

Environmental and Earth Sciences Proceedings

Vol. 39

SIEME 2025

Vol. 38

Climate Conversations 2023

Vol. 37

IOCTO 2025

Vol. 36

IECL 2025

Vol. 34

ECAS-7

Vol. 33

IConGEET 2024

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