From the evening of 1st May 2023 to 3rd May 2023, severe hydro-meteorological events occurred in the Italian Emilia-Romagna region, particularly in the provinces of Forlì-Cesena, Ravenna, Bologna, Modena, and Reggio Emilia. Additionally, on 16th-17th May, another intense meteorological event occurred, impacting the Romagna provinces. Such events caused extensive flooding, landslides, isolation of many areas, evacuation of numerous families, and significant damages to infrastructure, agriculture, buildings, and essential services. Many hilly municipalities were cut off, and thousands of civilians had to be evacuated, losses of life occurred. The consequences beyond the recorded immediate impacts on infrastructure and life were impressive, and extended to the regional economy, specifically in the Fruit Valley, where, in addition to immediate yield losses, long-term damage to orchard production is expected due to persistent flooding. The civil and cultural building heritage has also been heavily affected, both in the countryside and in inhabited centers. Some of the damage, direct and indirect, caused by flooding on buildings will also see an evolution in the medium to long term that will have to be addressed. This paper analyzes the reasons that led to the atmospheric phenomenon to understand the increasing potential occurrence of similar events from the perspective of climate change. This paper document analyzes the causes and effects of these events, additionally considering the future impacts of similar hazards potentially occurring in the context of climate change. It is crucial indeed to remark how such events, when occurring in high density agricultural areas, have the potential to threat the entire regional production system for extended periods. For example, the alteration of direct physiological processes due to root drowning may compromise production of entire productive agricultural extensions and many years will be required to their replacement.

Urbanization degrades natural habitats and creates new urban ecosystems, like domestic gardens. The plant composition of these gardens varies with socio-economic factors and urban planning levels. However, the diversity and impact of introduced species are often poorly assessed, causing potential ecological imbalances, particularly in Lubumbashi (DR Congo). The objective was to analyze the spatial structure, plant diversity, propagation strategies, and ecological functions of domestic gardens. Three distinct neighborhoods were selected: planned, unplanned and residential neighborhood. 20 avenues (with 5 plots per avenue) were chosen to represent the diversity within each neighborhood, and stratified random sampling of plots was conducted to analyze gardening practices. Gardens were classified into types, and their vegetation was evaluated based on species origin and ecological impact. The analysis of domestic gardens in Lubumbashi reveals significant variations across different neighborhood types. Residential neighborhoods exhibit larger average garden sizes (315.1 m²), higher species richness (22 species), and larger plot sizes (1032 m²) compared to unplanned and planned neighborhoods, where garden areas and species richness are notably lower. Rectangular gardens dominate in unplanned areas, while planned neighborhoods feature more intentional landscaping elements, such as flowerbeds and hedges. The use of gardens for food production is prominent in planned areas (40.7%), whereas residential neighborhoods prioritize ornamentation (51.4%). The study identifies 232 species across 68 families, with a predominance of exotic species (80%) in all neighborhoods, particularly in unplanned areas (82.25%). The data reveals that Mangifera indica and Persea americana are abundant in all neighborhoods, illustrating their adaptability to different urban contexts. Herbaceous species are most common, followed by woody plants, with vines being sparse. Species dispersal is primarily driven by human activities (anthropochory), accounting for over 85% in all neighborhoods. These findings highlight the strong human influence on the composition and structure of domestic gardens in Lubumbashi, emphasizing the dominance of exotic species and the importance of anthropogenic factors in shaping urban green spaces. Urban policies should incorporate strategies to minimize the negative impacts of exotic species on native flora.

Laboratories generate various forms of wastes which contribute to a complex network of profound and multifaceted environmental challenges and associated public health issues if not properly managed.Traditional laboratory practices particularly in developing countries, often lead to excessive waste generation, chemical contamination and resource depletion, coupled with inefficient waste management which poses risks to both ecosystem and public health. As the environmental impact of laboratory waste escalates, the need for effective waste management becomes increasingly important and urgent for safeguarding environmental health. This review examines the impact of laboratory waste management practices on environmental health and explores sustainable laboratory medicine as a mitigating response. Sustainable laboratory medicine adopts practices such as green laboratory principles involving waste minimization, resource conservation, the use of eco-friendly materials as well as energy-efficient protocols and innovative waste segregation and treatment technologies. This approach complies with regulatory standards as well as emphasizes proactive orientation towards environmental stewardship, operational efficiency and innovation while maintaining scientific integrity. Sustainable laboratory medicine appears to be a crucial framework that mitigates the environmental health impacts associated with laboratory-derived waste. This review advocates for a paradigm shift towards sustainable laboratory operations and emphasizes the need for comprehensive training, institutional commitment, and regulatory support.

This study assesses the alignment of Singaporean companies’ sustainability reporting with the newly introduced International Financial Reporting Standard S1, a global framework for sustainability-related financial disclosures. Given Singapore’s role as a major financial hub, understanding the extent to which local companies comply with this standard is critical to promoting transparency and accountability in sustainability practices. The study was conducted in two phases: the first phase was to summarize the timing of different countries’ preparations for the implementation of the IFRS S1 standard, as well as their attitudes. The second phase was a content analysis of the sustainability reports of 70 listed companies. The findings show that while companies are generally proactive in reporting governance, strategy, and metrics, they fall short in risk management disclosure, which is an important requirement of IFRS S1. This gap highlights the challenges companies face in incorporating comprehensive risk management practices into sustainability reporting. This study provides a reference for improving future sustainability reporting and encourages companies to align more closely with IFRS S1 to meet investors’ growing demand for transparent and standardized sustainability disclosures.

This study examines the combined influence of both meteorological and non-climatic factors on rice production in Bangladesh between 1990 and 2020, using the Autoregressive Distributed Lag (ARDL) model. The key variables consist of temperature, precipitation, urbanisation, fertiliser management (specifically potassium levels), and the area of permanent crops. The findings highlight the substantial detrimental impact of temperature on rice output over a prolonged period, whereas precipitation and urbanisation have a favourable affect on rice productivity. However, the utilisation of potassium fertiliser has a detrimental effect on crop productivity. Furthermore, it has been demonstrated that the development of permanent crop fields has a beneficial effect on rice output. These findings provide important information for policymakers and agricultural stakeholders, highlighting the need for adaptive strategies to improve the ability of rice production to withstand the impacts of climate change and urbanisation. The significance of these discoveries applies to rice-producing regions worldwide, offering a strategic blueprint for sustainable cultivation of rice and ensuring food security.

(1) Food banks have played an important role in reducing food losses and waste and improving the food insecurity situation of vulnerable people. This study aims to conduct a systematic review of food bank evaluation studies and bring new perspectives for future research and decision-making. (2) 58 articles were selected and analyzed from a survey on the Web of Science and Science Direct Platforms. Bibliometric analyses and analyses of the evaluation methodologies used were presented. (3) The bibliometric results indicate an internationalization of the studies since 2013, with a focus on developed countries, and a direct relationship between the location of the research institutes and the location of the organizations studied. Analysis of evaluation methodologies showed that the main aspects evaluated are related to long-term impact, short-term impact and results, indicating less interest in the internal processes and activities of organizations. This result raises important questions for researchers and decision-makers: to what extent evaluation studies reflect the reality and context of a given country or region and to what extent evaluation studies reflect the management processes of food banks.

The role of trees in watershed hydrology is governed by many environmental factors along with their inherent characteristics and not surprisingly has generated into diverse debates in the literature. Herein, this state-of-the-art review provides an opportunity to propose a conceptual model for understanding the role of trees in watershed hydrology and examine the conditions under which they can be an element that increases or decreases water supply in a watershed hydrology. To achieve this goal, this review addressed the interaction of forest cover with climatic conditions, soil types, infiltration, siltation and erosion, water availability, and the diversity of their ecological features. The novelty of the proposed conceptual model highlights that tree species and densities, climate, precipitation, type of aquifer, and topography are important factors affecting the relationships between trees and water availability. This suggests that forests can be used as a nature-based solution for conserving and managing natural resources, including water, soil and air. To sum up, forests can reduce people’s imprint, thanks to their role in improving water and air quality, conserving soil, and other ecosystem services. The outcomes of this study should be valuable for decision-makers when investing in reforestation in a watershed hydrology.

A one-dimensional numerical overland flow model based on the cascade plane theory was de-veloped to estimate rainfall-induced runoff and soil erosion on converging and diverging plane surfaces. The model includes three components: (i) soil infiltration using Horton’s infiltration equation, (ii) overland flow using the kinematic wave approximation of the one-dimensional Saint-Venant shallow water equations for a cascade of planes, and (iii) soil erosion based on the sediment transport continuity equation. The model’s performance was evaluated by comparing numerical results with laboratory data from experiments using a rainfall simulator and a soil flume. Four independent experiments were conducted on converging and diverging surfaces under var-ying slope and rainfall conditions. Overall, the numerically simulated hydrographs and sediment graphs closely matched the laboratory results, showing the efficiency of the model for the tested controlled laboratory conditions. The model was then used to numerically explore the impact of different plane soil surface geometries on runoff and soil loss. Seven geometries were studied: one rectangular, three diverging, and three converging. Constant soil surface area, rainfall intensity, and slope gradient were maintained in all simulations. Results showed that increasing convergence angles led to higher peak and total soil loss, while decreasing divergence angles reduced them.

This study examines the impact of natural resource exploitation, renewable energy consumption, economic growth, biocapacity, and information and communication technologies (ICT) on the ecological footprint of BRICS+ nations using panel data from 1991 to 2019. Advanced econometric techniques, including FMOLS, DOLS, CCR, and GMM, reveal significant findings relevant to sustainability-focused policymakers. The results show that natural resource exploitation significantly contributes to environmental degradation, while renewable energy consumption mitigates these effects to varying degrees across the studied countries. Although economic growth is crucial, it worsens ecological footprints unless accompanied by sustainable practices. ICT and biocapacity emerge as key factors in promoting environmental sustainability, with ICT enhancing innovation and efficiency to reduce ecological impacts. The study emphasizes the need for tailored policy frameworks that align economic growth with environmental sustainability, advocating for the adoption of renewable energy, eco-innovations, and green finance initiatives suited to the unique conditions of BRICS+ nations. The findings aim to guide policymakers in advancing sustainable development and mitigating the adverse environmental impacts of rapid industrialization and urbanization, while contributing to the global discourse on achieving a balance between economic growth and ecological well-being in developing countries.

Herbicides are widely used in agriculture to control weeds and enhance crop productivity. However, their application can have significant impacts on soil health and nutrient dynamics. This paper reviews the effects of herbicides on soil properties, microbial communities, and nutrient availability, with a particular focus on calcium deficiency. The review synthesizes findings from peer-reviewed journals and reports, including research conducted in Australia. The correlation between herbicide application and calcium deficiency is explored, highlighting both positive and negative impacts. The paper concludes with recommendations for sustainable herbicide use and alternative weed management strategies.

Sentinel-3 synergy (SYN) VEGETATION (VGT) products were designed to provide continuity to SPOT/VEGETATION (SPOT VGT). In past years, important changes have been implemented in the SYN VGT processing baseline. Since the PROBA-V mission acted as a gap filler between SPOT VGT and Sentinel-3, and in principle a continuous series of data products from the combined data archives of SPOT VGT (1998 – 2014), PROBA-V (2013-2020) and Sentinel-3 SYN VGT (from 2018 onwards) is available to users, consistency of Sentinel-3 SYN VGT with both the latest SPOT VGT (VGT-C3) and PROBA-V (PV-C2) archives is highly relevant. Spatio-temporal intercomparison of the combined time series of VGT-C3, PV-C2 and Sentinel-3 SYN VGT 10-day NDVI composite products with an external reference from LSA-SAF, and the intercomparison of Sentinel-3 SYN V10 products with a climatology of VGT-C3 resp. PV-C2 for 3 distinct periods with different levels of product quality have shown that the subsequent processing baseline updates have resulted in better quality products. It is therefore essential to reprocess the entire Sentinel-3 SYN VGT archive: a uniform data record of standard SPOT VGT, PROBA-V and Sentinel-3 SYN VGT products, spanning over 25 years, would provide valuable input for a wide range of applications.

A theoretical framework for agricultural landscape pattern transitions in rural areas is proposed to fill the gap of current research with an empirical study in the Alabata farm settlement in Ogun State, Southwest Nigeria. Adopting the use of ArcGIS 10.8 and Surfer 27.3 to calculate the surface area and volume of the ground surface degraded and exposed to harsh weather conditions due to both natural and man-made anthropogenic activities causing runoffs and continuous soil erosion, which has affected agricultural production and sent some of the farmers packing and abandoning their farmlands. The farm settlement within the total sampled frame area of 1.50 km² covers a total distance of 5.11 km. The sample frame was divided into 36 frames with similar ecological terrain and soil types, which fell into either identified soil types 1 and 2. The study completed a questionnaire onsite using three major criteria. Only 23 farmers responded positively to the few questions with farmers either living on the farm or working as hired laborers on-site at the visit. The transition characteristics of agricultural landscape patterns as represented in abandoned land, and orchards are analyzed from a local perspective.

(1) Background: The increasing demand for sustainable practices in the textile industry has led to the exploration of natural dyes and eco-friendly dyeing processes. This study focuses on the potential of used coffee grounds (UCG) as an eco-friendly natural dye for Nylon 6.6 woven fabrics. (2) Methods: Five dyeing processes were evaluated, varying in the use of mordants and acids, to assess their impact on color saturation, colorfastness to laundering, and crocking resistance of Nylon 6.6. fabric. The processes included a control with no mordant or acid and others that incorporated tannic acid, acetic acid, and ferrous sulfate heptahydrate. (3) Results: The results demonstrated that Process 4, which combined tannic acid pre-mordanting with acetic acid in the dye bath, provided the best balance between color saturation and colorfastness. Process 2, utilizing only tannic acid, offered some durability in laundering and crocking tests. Process 5, being the least eco-friendly process demonstrated high color saturation, but it performed poorly in colorfastness to crocking, which means that it releases the UCG-based dye after rubbing of the dyed Nylon 6.6. fabric. (4) Conclusions: The findings confirm that UCG can be an effective and sustainable natural dye for Nylon 6.6, with pre-mordanting and acid treatment significantly enhancing dye uptake and retention. However, further research is needed to optimize color intensity and expand the application of UCG in textile dyeing.

Climate change poses a significant threat to European security, implicitly to Romania’s naval forces in the Black Sea. Rising sea levels, extreme weather events, and ocean acidification impact maritime operations, infrastructure, and personnel, with potential ramifications for regional stability. This paper explores the implications of climate change for the Romanian Navy and proposes "Green Defence" strategies to enhance resilience and sustainability. These strategies encompass energy efficiency, renewable energy integration, sustainable procurement, and the application of advanced functional materials in naval operations and infrastructure. By adopting a proactive and multifaceted approach, the Romanian Navy can adapt to the changing climate, ensuring operational effectiveness while minimizing environmental impact. This approach aligns with broader European security concerns and contributes to a more sustainable and resilient defence posture in the face of climate-related challenges.

This study investigates the evolution of the vegetation and beach dune system at Enebrales Beach in Huelva, Spain, from 2003 to 2022. Utilizing orthophotographs and advanced GIS techniques, we analyzed changes in natural surface areas, vegetation cover, and dune stability. The results demonstrate significant ecological improvements: a recovery of 25,300 m² in dunes and 7,400 m² in beach areas, and a total vegetation cover increase of nearly 10,000 m². Interventions, including reforestation with native species and the stabilization of dune ridges, have been effective in enhancing the coastal ecosystem's resilience. Additionally, the beach's carrying capacity increased, allowing for approximately 2,000 more users without compromising ecological integrity. These findings underscore the importance of continued conservation efforts and adaptive management to maintain and further improve the ecological health and sustainability of Enebrales Beach Dune.

Bilberry (Vaccinium myrtillus) encroachment in subalpine and alpine ecosystems is increasing due to climate change and reduced land management. This review examines bilberry traits, environmental responses, and ecosystem impacts. As a stress-tolerant chamaephyte, bilberry thrives in acidic, nutrient-poor soils across various habitats. It propagates effectively through rhizomes and demonstrates a phalanx growth form. Bilberry's growth and distribution are influenced by elevation, soil structure, pH, water availability, and nitrogen content. Mycorrhizal associations play a crucial role in nutrient uptake. The species modifies microclimate, facilitates litter accumulation, and influences soil microbial communities, affecting nutrient turnover and biodiversity. Bilberry shows moderate tolerance to herbivory and frost, with the ability to recover through rapid emergence of new ramets. However, severe or repeated disturbances can significantly impact its abundance and reproductive success. Climate warming and atmospheric nitrogen deposition have accelerated bilberry growth in treeline ecotones. Management of bilberry encroachment requires a nuanced approach, considering its resilience, historical land-use changes, and environmental factors. The goal should be to limit, not eliminate, bilberry as it's a natural part of subalpine communities. Long-term comparative monitoring and experimental manipulation are necessary for effective management strategies.

Lualaba Province, located in the southeastern Democratic Republic of the Congo, consists of five territories with varied dominant land uses: agriculture (Dilolo, Kapanga, and Musumba in the west) and mining (Mutshatsha and Lubudi in the east). The province also includes protected areas with significant governance challenges. The unique miombo woodlands of Lualaba are threatened by deforestation, posing risks to biodiversity and local livelihoods that depend on these woodlands for agriculture and forestry. To quantify the spatio-temporal dynamics of Lualaba's landscape, we utilized Landsat images from 1990 to 2024, supported by a Random Forest Classifier. Landscape metrics were calculated at multiple hierarchical levels: province, territory, and protected areas. Our provincial-level analysis revealed a pronounced deforestation trend, with miombo woodland cover declining from 62,90 % to less than 25 % over the 34-year period. This trend was characterized by the fragmentation and dissection of woodland patches and a decline in remaining woodland fragments, due to their ongoing replacement by savannas, agriculture, and urbanization. The average distance between miombo woodland patches increased significantly, indicating heightened fragmentation and spatial isolation. Agricultural areas such as Sandoa and Kapanga were particularly vulnerable to deforestation. On the other hand, the miombo forest cover in the mining areas is still representative, with over 30% of the landscape covered. Notably, the reduction in woodland cover within protected areas was substantial, with significant losses observed across both agricultural and mining territories. The loss of miombo woodland cover in Lualaba and its territories was accompanied by an increase in landscape patch diversity, as indicated by the Shannon diversity index, suggesting a shift to more heterogeneous landscapes. These findings underscore a complex deforestation pattern, highlighting the intense local impact on miombo woodland cover loss. Urgent action is needed to implement land conservation policies, promote sustainable agricultural practices, strengthen miombo woodland regulation enforcement, and actively support protected areas. Involvement from both local and international stakeholders is imperative to preserve the ecological richness and functionality of Lualaba Province's miombo woodland ecosystems.

We describe a forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The system was developed for Pacific Gas and Electric Corporation (PG&E) to operationally forecast conditions in Northern and Central California. It was established in 2014 and has been periodically improved. In the current configuration, WRF forecasts are routinely performed multiple times each day on a 2-km grid, and the results are used as input to wildfire fuel moisture, fire probability, and wildfire spread models. Components of the system include a stochastically perturbed ensemble; an annually updated reanalysis covering more than 30 years; and validation against PG&E’s extensive mesonet and other observing networks. We describe the development and validation of the next operational edition. Configurations tested include irrigation triggered by crop growing season and an ensemble-based approach with intelligently sub-selected Global Ensemble Forecast System (GEFS) members. The latter approach allows for enhanced uncertainty sampling in WRF forecasts and can greatly improve WRF forecasts when calibrated by observations.

The resilience of towns and cities refers to their ability to adapt and recover when confronted with pressures or challenges. This study employs ten variables as indicators to assess the resilience of urban areas by analyzing official data and constructing a multilevel mixed-effects structural equation model. The empirical findings demonstrate that enhancing resilience significantly influ-ences urban service functions, such as strengthening healthcare systems, stabilizing the real estate market, and addressing socio-economic challenges. Specifically, factors such as healthcare re-sources, housing demand, population structure, and social security exhibit varying levels of resil-ience, which profoundly impact the spatial distribution of these factors and socio-economic de-velopment. Disparities in healthcare resource allocation, demographic aging trends, and shifts in the housing market closely correlate with resilience levels in different regions. Additionally, the study emphasizes that improving resilience not only boosts the reliability and security of urban services but also ensures that communities receive necessary support and protection during times of adversity. Consequently, policymakers should recognize the pivotal role of urban resilience in resource allocation and social equity, devising corresponding strategies to enhance the resilience of these areas.

Pressmud, a by-product of sugarcane processing, is typically disposed of through incineration or landfilling, though it has considerable potential in organic agriculture. This study explored the com-posting of pressmud through bioaugmentation using specific bacterial strains. Two experimental setups were created: E2 with a cellulolytic and phosphorus-solubilizing strain, Bacillus amyloliquefa-ciens-ASK11, and E3 with a nitrogen-fixing strain, Bacillus megaterium-ASNF3. A control setup (E5) was also maintained without bacterial augmentation. Nitrogen (N) and phosphorus (P) contents were measured using the Kjeldahl and Olsen methods, respectively, while Fourier-Transform Infra-red (FTIR) spectroscopy confirmed compost maturity. Results indicated that the Bacillus-enhanced composts in E2 and E3 significantly increased the nitrogen(49.27% and 91.23%) and phosphorus contents(129% and 83.85%), respectively, compared to the control with only 13.62% N and 65% P contents after 60 days of the pressmud compost maturity.. Additionally, organic matter decomposi-tion improved by 49-50% in the bioaugmented setups after 60 days. FTIR analysis revealed organic phosphate peaks and P-O-C stretching bands at 1025 cm-1 in the E2 compost, while a nitrogen vi-bration band at 3849 cm-1 in E3 indicated significantly higher nitrogen content compared to the control. The Bacillus-enriched pressmud compost not only accelerated the composting process but also enhanced nutrient levels, positioning it as a promising biofertilizer for rehabilitating barren lands.

The samples from lunar farside have great significance for the study of the Moon, and even the solar system. Chang’e-6 landed successfully on the southern mare of the Apollo basin and returned ~2 kg samples from lunar farside. To provide a better understanding for the background of the returned samples, we conducted detailed crater size-frequency distribution (CSFD) measurements in the Chang’e-6 landing region, the southern mare of the Apollo basin. The southern mare is divided into western mare (W region) and eastern mare (E region), and then subdivided into five sub-units (W1, W2, W3, W4, W5) and three units (E1, E2, E3), respectively, according to the elevation, Ti and Fe abundances. Within the W2 and W5 region, more detailed sub-units were divided. The results show that the southern mare generally have two epochs, one of the Imbrian period and the other of the Eratothenian period. The basalt eruption lasted for ~1.7 Ga, from 3.28 Ga of the eastern mare to 1.54 Ga of the western mare. W region is younger than E region, while the three units of E region has an age of ~3.2 Ga. The ages of the western mare basalts range from 2.98 Ga to 1.54 Ga, lasting for 1.4 Ga. It’s worth noting that the age of the basalt at the Chang’e-6 sampling site is ~1.68 Ga, indicating the samples returned may include components with this very young age.

The wastewater problem is becoming an increasingly significant environmental issue affecting various aspects of human activities. The generation of reactive oxygen species (ROS) in water through certain physicochemical processes, which can oxidize or degrade various organic and chemical compounds, offers an effective purification method. The main advantage of these methods is the elimination of chemical reagents. Aim of this work is to investigate the possibility of regulating the ROS content in water by altering the characteristics of the plasma discharge that occurs under hydrodynamic cavitation in the water flow. ROS concentration was determined using the permanganate oxidation titration technique. It was found that the content of various reactive oxygen species in water after treatment can be controlled by varying the power of the electrical pulses applied. Additionally, the study obtained the dependence of ROS concentration in treated water samples on storage time, indicating a prolonged effect of sonoplasma treatment on the antibacterial properties of water. Analysis of water samples using a biological test culture of Salmonella typhimurium revealed bacteriostatic properties of the water for at least 48 hours after sonoplasma discharge treatment.

Traditional seismic wave-based tunnel advanced geological forecasting techniques are primarily designed for drill and blast method construction tunnels. However, given the fast excavation speed and limited prediction space in Tunnel Boring Machine (TBM) construction tunnels, traditional methods have significant technical limitations. This paper analyzes the characteristics of different types of TBM construction tunnels and, considering the practical construction conditions, identifies an effective observation system and data acquisition method. Utilizing numerical simulation, a model for advanced detection of typical unfavorable geological formations is established by obtaining the wave field response characteristics of seismic waves in three-dimensional space. The seismic wave reflection method can effectively receive information from unfavorable geological formations in front of the tunnel face. To address the challenges in advanced forecasting for TBM construction tunnels, a method of ellipsoid positioning velocity analysis, which takes into account the constraints of three-component data directions, is proposed. Based on the characteristics of the advanced forecasting observation system, the method compares the maximum values on the spatial isochronous ellipsoidal surface to determine the average velocity of the geological layer rays, thereby enabling accurate inversion of the spatial distribution ahead. Field verification of advanced geological forecasting based on ellipsoid positioning velocity analysis for TBM tunnels is conducted. The results indicate that this method can be used to obtain the three-dimensional velocity of the predicted unfavorable geological formations in front of the tunnel and is effective for the application of geological forecasting in TBM construction tunnels, thus providing crucial references and assurances for construction.

The finite volume method (FVM) is a kind of numerical analysis method that can take into account topography and apply local subdivision cells as the finite element method (FEM). The adjoint state method (ASM) can easily calculate the gradient vector of the objective function for the inversion. The author developed a program that applied these methods to 3-D Magnetotelluric (MT) inversion and verified it using test models. As a result, it was confirmed that the program can perform analysis properly and efficiently considering topography and subsurface resistivity heterogeneity.

This review investigates the pivotal challenge of recycling material waste in the context of Additive Manufacturing with an emphasis on decentralized 3D printing, shedding light on its environmental and economic implications. With additive manufacturing experiencing exponential growth, the environmental impacts of waste generation during 3D printing processes have become increasingly significant. The paper explores various recycled materials commonly used in 3D printing, including polymers like polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), and polyethylene terephthalate glycol (PETG), evaluating their characteristics and usability. General recycling methodologies, encompassing mechanical and chemical processes, are examined with attention to challenges such as polymer sorting, additives, coatings, contamination, and thermoset reprocessing. The economic and societal impact of integrating recycled materials into 3D printing and the environmental impacts are examined. By identifying research gaps and proposing future trends, this review contributes to a deeper understanding of how recycling can play a pivotal role in achieving environmental sustainability and economic viability within the decentralized 3D printing landscape.

Diversification of cropping sequences has a positive impact on soil organic carbon, while improving nutrient cycling and crop yields. The objective of this research was to assess amylase and cellulase activity, C and N dynamics, and maize yield on a low fertility Oxisol in the Brazilian Cerrado. The experiment was conducted under field conditions during three maize crop succession cycles. Treatments consisted of cultivating maize during the summer, after sorghum and lablab cropped as green manure and fallow during the winter. Higher maize yields were achieved by sorghum-maize succession compared to monocropping, due to higher N fertilizer and biomass in-puts to topsoil. Sorghum-maize succession also provided a higher proportion of stable C and N compared to other successions. Maize yields declined as tropical soil fertility intrinsically de-creased along three crops succession cycles. Cellulase activity decreased over time, whereas amylase activity increased as the plant residues were already in advanced stages of decomposition. The sorghum-maize crop succession stood out compared to lablab and fallow as it provided the high-est maize yields, while, maintaining higher C and N levels, and amylase activity. This better performance was likely due to larger amounts of incorporated biomass and better mineral N fertilizer management.

A 7.4 m long sediment core has been retrieved from the central part of Lake Vrana on the Island of Cres to reconstruct the paleoenvironmental conditions. Lake Vrana is the deepest freshwater lake in Croatia, located in the karst region of the eastern Adriatic coast. A dated sediment sequence in Lake Vrana of 4.4 m spans the past 16.4 kyr, and features a dynamic sediment deposition until the beginning of the Holocene, including strong sediment input and supply to the lake by runoff sediments of dolomitic origin from the catchment in the period 16.4-14.4 cal kyr BP. High organic carbon content, which originates from mixed terrestrial and aquatic origins in the periods 14.4-13.3 cal kyr BP and 12.7-11.7 cal kyr BP, indicates fluctuating lake levels in shallow water environments during the late glacial to Holocene transition. The Holocene sequence indicates the development of more stable conditions and continuous sediment deposition, characterized by increasing trend of siliciclastic sediments delivered into the lake during the early Holocene (11.7-10 cal kyr BP), and dominantly from 8 to 4.4 cal kyr BP, indicating enhanced input and erosion, which coincides with humid and pluvial period, recorded in the central Mediterranean region. It is followed by sediments with high organic carbon content between 4.4 to 1.6 cal kyr BP, which points to higher lake productivity. Calcite sedimentation prevail between 1.6 to 0.4 cal kyr BP, indicating stable deeper-lake conditions, while dominantly siliciclastic sediments in the period 0.4-0.1 cal kyr BP indicate erosion during Little Ice Age (LIA), with enhanced precipitation and sediment discharge from the catchment. The re-establishment of calcite sedimentation has been observed over the last 100 years.

Quantifying methane emissions is essential for meeting near-term climate goals and typically done using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas productions sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm with maximum values of 105.9 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios show overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher price trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deploying, and allow for timely and accurate tracking of methane emissions.

Fungi play important roles in the process of material cycling and energy transfers in aquatic ecosystems. Yet little is known about the fungal community in lake sediment. In this study, sediment samples from five habitat types in Baiyangdian Lake (BYD Lake) were collected across three seasons. High-throughput sequencing techniques were used to determine the compositions of fungal communities. Fungi are highly diverse in the sediment of BYD Lake, although some important fungi have not been accurately identified. The fungal diversity was highest in winter and lowest in summer, while the variations of species richness among sampling sites were not significant. The compositions of fungal community differed among seasons and habitats. Physicochemical properties of sediments were measured and the influence of the environmental factors on fungal communities were analyzed. Temperature, P, N, and heavy metals explained 48.98% of the variations of fungal communities across three seasons. Human activities have affected the species and biomass of fungi to some extent. Temperature is the most influential factor and is negative to fungal diversity. Nutrient element in different forms have different effects on shaping the fungal community. The effect of heavy metals is not clear.

This study explores the implementation of the ANSI/373: Sustainable Production of Natural Dimension Stone standard within the North American dimension stone industry to identify driving forces behind the initiative and consider potential outcomes as it advances. The method involves a thorough review of ANSI/373, comparing it with voluntary sustainability initiatives (VSIs) in the forest industry to assess its effectiveness and challenges, and semi-structured interviews with contacts in the dimension stone field. Key drivers such as corporate social responsibility and market pressures influence the adoption of sustainability standards. The results highlight the embedded environmental considerations within the emerging dimension stone standards and their implications for sustainable practices in the industry. While the ANSI/373 standard promotes sustainable awareness and practices, it faces challenges in certification credibility and industry acceptance, particularly due to inconsistency among firms in their response, rigorous certification demands, and skepticism about certification credibility. The research advocates for enhanced collaborative frameworks to increase the standard’s adoption and impact, suggesting that industry stakeholders prioritize showcasing dimension stone as a practical, environmentally considerate material.

We introduce and analyze conceptual approximations of the Boussinesq equation for horizontal unconfined aquifers during the pure drainage phase, without any reharge and zero-inflow conditions. We employ a variety of methods, which include wave solution, variable separation and series expansion to constract a new model and explore its behavior and performance against the Boussinesq equation and its exact (non-closed form) solution, at early and later times. The modeled non-linear forms are finally linearized concluding with explicit analytical expressions that incorporate most of the basic characteristics regarding the evolution of the water table and the outflow from the exact Boussinesq equation under different initial conditions. The endeavors of this work might be useful for theoretical and modeling purposes related to this problem.

As urban areas expand and populations grow, environmental challenges such as the urban heat island effect, air pollution, and light pollution intensify. The urban heat island effect exacerbates extreme heat conditions, leading to prolonged periods of unhealthy and hazardous environments for both humans and other species. This study investigates the thermal environment associated with the urban heat island effect, focusing on the role of trees in mitigating this issue. Using ENVI-met simulations, the study examines various factors influencing tree cooling effectiveness, including seasonal variations, building shading, transpiration rates, tree placement, and spacing. A new tree-planting strategy is developed based on these findings, aiming to enhance thermal comfort. The study compares the thermal environment of sidewalks under the new tree-planting scheme with the existing arrangement across different months. Results indicate that the new scheme reduces UTCI temperatures by 2.2°C on the hottest day, 0.97°C on the coldest day, and 1.52°C annually in the study area of Los Angeles, demonstrating that the cooling benefits of trees in hot weather outweigh the potential drawbacks in cold weather, highlighting its potential to mitigate the urban heat island effect.

The artificial solar saltwork fields of Hon Khoi are important industrial and biodiversity resources in southern Vietnam. Most hypersaline environments in this area are characterized by saturated salinity, nearly neutral pH, intense ultraviolet radiation, elevated temperatures and fast desiccation processes. However, the extreme halophilic prokaryotic communities associated with these stressful environments remain uninvestigated. To fill this gap, a metabarcoding approach was conducted to characterize these communities by comparing them with solar salterns in northern Vietnam as well as with Italian salterns. Sequencing analyses revealed that the multiple reuses of crystallization ponds apparently create significant perturbations and structural instability in prokaryotic consortia. However, some interesting features were noticed when we examined the diversity of ultra-small prokaryotes belonging to Patescibacteria and DPANN Archaea. Surprisingly, we found at least five deeply branched clades, two from Patescibacteria and three from DPANN Archaea, which seem to be quite specific to Hon Khoi saltwork fields ecosystem and can be considered as a part of biogeographical connotation. Further studies are needed to characterize these uncultivated taxa, to isolate and cultivate them, which will allow us to elucidate their ecological role in these hypersaline habitats and to explore their biotechnological and biomedical potential.

Air pollution has become one of the biggest problems throughout the world. Smog has a severe effect on the pulmonary and circulatory systems, which causes a significant number of deaths globally. Therefore, the remediation of air pollutants to maintain ecosystem processes and functions and to improve human health is a crucial problem confronting mankind today. This review aims to discuss the health effects of smog on humans. This review will also focus on the bioremediation of air pollution (smog) using bacteria, fungi, phytoremediation, nanotechnology, and phylloremediation (using plants and microbes). Phyllo-remediation is the most effective technology for removing air pollution naturally. The future perspective presents a great need to produce an ecosystem where microbes, plants, and nanoparticles synergistically control smog. In addition, further advancements would be needed to modify the genetic makeup of microbes and plants. Biotechnological approaches like CRISPR-Cas9 can be applied to the editing and cutting specific genes responsible for the bioremediation of VOCs, NOx, SOx, and harmful hydrocarbons. The extracted genes can then be expressed in biologically modified microorganisms and plants for enhanced bioremediation of smog.

The study on the sustainable utilization capacity of water resources is of great significance for the realization of sustainable water resources management and development in the water-scarce regions of Northwest China. It provides insights into the potential for sustainable utilization of these resources. To evaluate the sustainable utilization capacity of the Huangshui Basin, a comprehensive evaluation index system was constructed based on three aspects: climate factors, water resources systems, and socio-economic factors. The evaluation was conducted using two methods: the fuzzy comprehensive evaluation model and the ELECTRE III evaluation method. The results indicate that the Huangshui Basin's water resources, as a whole, exhibit a medium sustainable utilization capacity. Climatic factors and socio-economic characteristics are the main factors affecting the sustainable utilization of water resources in the Huangshui Basin. Based on the results, measures such as strengthening the introduction of external water resources, enhancing water resources management, and implementing comprehensive remediation efforts in the basin can improve the level of sustainable use of water resources. The research results can provide a reference for decision-making regarding the evaluation of sustainable utilization capacity of water resources in water-scarce areas and the optimization of water resources management in the Huangshui Basin.

White oak mortality is a significant concern in forest ecosystems due to its impact on biodiversity and ecosystem functions. Understanding the factors influencing white oak mortality is crucial for effective forest management and conservation efforts. In this study, we aimed to investigate the spatial pattern of white oak mortality rates at different locations of the eastern US and explore the underlying processes involved with the spatial distribution patterns. Multicycle Forest Inventory and Analysis data were compiled to capture white oak plots across the eastern US. White oak mortality data were collected across plot systems that utilized Diameter at Breast Height between two periods. Ripley’s K function was used to study the spatial pattern of white oak mortality rate. Results found clustered patterns at both local and broad scales and random patterns at broad scales only across the southern and northern regions. However, the central region indicated both clustered and random patterns at local scale only. We found uniform patterns at a broad scale across all regions. Our findings demonstrated the importance of the spatial pattern of the white oak mortality rate and the underlying factors associated with it. This research can inform forest management practices for the conservation of white oak populations at varying scales. Future research is needed for a comprehensive assessment of biotic and abiotic factors for forest management strategies at various spatial scales aimed at mitigating white oak mortality.

The Keeling Curve shows that in addition to the progressive increase in the amount of CO₂ in the atmosphere, the rate of increase in the rate of uptake of CO₂ into the atmosphere, both in ppm and gigatons C/year, has been progressively increasing from 1960 to the present, despite some leveling off of man-made emissions. There is a similar processive increase in the earth’s heat imbalance. I propose that this is due to the additive effect of multiple partially activated tipping points putting the earth into a positive feedback mode such that these increases in rate will continue even after net zero emissions from fossil fuels is attained. As a result, controlling global warming will require a marked acceleration of Carbon Dioxide Removal using multiple Negative Emission Technologies.

The Kraaipan and Amalia greenstone belts in South Africa occurs in the western part of the Kaapvaal Craton. The two belts stretch discontinuously in an approximately north-south orientation over a distance of about 250 km from southern Botswana in the north to the Vaal River near Christiana in the south and are separated by a distance of about 90 km. Gold mineralization is hosted in banded iron-formation at both the Kalahari Goldridge deposit (Kalgold) in the Kraaipan greenstone belt in the north, and the Amalia deposit in the Amalia greenstone belt in the south, with the mineralization associated with quartz-carbonate veins. The footwall of these deposits is generally composed of mafic volcanic schist and hanging wall consisting of graywackes, schist and shale units. The Kalgold and Amalia gold deposits show some variation in the redox condition of the mineralizing system, mineralization temperatures and fluid chemistry. The ore mineral assemblage is characterized by magnetite-pyrrhotite-pyrite at Kalgold, which is indicative of reducing conditions, and magnetite-hematite-pyrite assemblage at Amalia that suggest a relatively oxidizing environment. Average mineralizing temperatures determined from chlorite geothermometry were relatively higher at the Kalahari Goldridge deposit ranging from 350 to 400oC compared to 335 to 370oC (mean, 352± 18, n = 113) at Amalia. The composition of the fluids derived from fluid inclusions are indicative of low salinity H2O-CH4-CO2-rich fluids at Kalgold against relatively H2O-CO2-rich fluids at Amalia. Evidence from strontium-carbon-oxygen isotopic ratios from carbonates suggests differences in redox conditions in the deposits could be attributed to different flow pathways by the evolving fluid from a common source (with minimum 87Sr/86Sr=0.70354) to the sites of gold deposition; with significant ore fluid interaction with thick sequence of carbonaceous meta-pelitic rock units at the Kalahari Goldridge deposit, that is absent in the Amalia deposit.

Costa Rica, widely acknowledged for its environmental leadership, is now facing a significant challenge in managing waste, a situation that could potentially compromise both its environmental and public health achievements. This analysis delves into the waste management issues in Costa Rica, particularly in urban areas such as San José, responsible for nearly half of the country's waste. The study identifies several pressing concerns, including the heavy burden on landfill capacities, a recycling rate of just 9.6%, and substantial regional differences in waste management practices.To address these challenges, the research employs a combined methodology, utilizing Linear Regression (LR) and AutoRegressive Integrated Moving Average (ARIMA) models to project future trends in CO2e emissions and waste minimization from 2024 to 2050. This method underscores the vital need for public involvement and the introduction of innovative strategies in waste management. The research also introduces a Waste Management Innovation Index to compare Costa Rica’s practices with those of leading nations like Germany and South Korea, identifying key areas for improvement.Furthermore, the study incorporates insights from stakeholders, revealing the intricate balance of cultural, economic, and regulatory factors that shape waste management policies. Despite efforts by the government, such as the Environmental Health Route and the National Circular Economy Strategy, results show limited progress, particularly in rural regions. The study highlights the urgent need for better infrastructure, targeted public awareness campaigns, and the use of advanced technologies like Artificial Intelligence (AI) and blockchain to enhance sustainable waste management practices. The research provides strategic recommendations to help Costa Rica improve its waste management systems in line with international standards, ensuring long-term environmental sustainability and protection of public health.

The electronics industry is a significant contributor to environmental challenges, generating approximately 50 million tons of electronic waste annually and high levels of carbon dioxide emissions throughout the production and disposal of devices. This paper investigates the interplay between reliability and sustainability by analyzing how degraded components affect the environmental footprint of electronic products. Using a board with 215 components as a baseline, we calculate the mean time between failures (MTBF) and compare it to scenarios involving degraded components. Our findings demonstrate that degraded components can reduce MTBF by up to 50%, resulting in higher failure rates, increased electronic waste, and up to 30% more CO2 emissions due to shortened product lifespans. This study underscores the crucial importance of component quality control in the production process to improve both reliability and sustainability. Additionally, the broader economic and environmental impacts of using unchecked components are highlighted, showing their contribution to elevated failure rates, shortened product lifespans, and an estimated 20% increase in e-waste. By adopting a 100% inspection protocol, leveraging advanced technologies, and enforcing stringent material quality controls, manufacturers can significantly enhance the reliability of electronic products while reducing their environmental impact, thus fostering a more sustainable electronics industry.

The discharge of industrial effluents containing toxic heavy metals in water sources has serious consequences for human health and the environment, and biosorption appears to be an environmental-friendly and cost-effective alternative that can be used for wastewater treatment. The use of different types of agricultural waste as biosorbents for the removal of toxic heavy metals, although an alternative, is quite difficult to apply in practice because these wastes have many other uses. Based on these considerations, in this study, soybean biomass (SB), soybean waste biomass obtained from oil extraction (SBW) and biochar obtained from soybean waste pyrolysis (BC-SBW) were testes as biosorbents form the removal of Pb(II) and Cd(II) ions, in batch systems. Under optimal conditions (pH = 5.4, 4.0 g biosorbent/L, room temperature (25 ± 1 C), contact time = 180 min), the biosorption capacity increase in the order: SB < SBW < BC-SBW for both metal ions, indicating that BC-SBW has the highest efficiency in removing toxic heavy metals. In addition, experiments on wastewater samples have shown that, in addition to significant reducing the content of heavy metals, BC-SBW also significant improved other quality indicators (such as: pH, TSM, CCO-Cr, CBO5), compared to the other biosorbents (SB and SBW). Quantitative evaluation of the biosorptive performance of each biosorbent (SB, SBW and BC-SBW) shows that BC-SBW has a real chance of being used on an industrial scale for wastewater treatment. All these aspects allowed the development of a circular approach for the use of soybean biomass in the removal processes of toxic heavy metals. This approach minimizes the shortcomings of using biomass as a biosorbent and increase the chance of using these materials in industrial practice.

The Greater Amanzule Peatland (GAP) in Ghana represents an important ecosystem facing dynamic land cover changes as a result of both natural and anthropogenic factors. This study integrates multispectral and radar remote sensing data from Landsat-7 and -8, L-band SAR, and SRTM to conduct a machine learning-based analysis of these changes from 2010 to 2020 and to predict future scenarios up to 2040. Findings reveal a 12% expansion in peatland cover, equivalent to approximately 6,570 ± 308.59 hectares, despite declines in specific peatland types. Concurrently, anthropogenic land uses have increased, evidenced by an 85% rise in rubber plantations (from 30,530 ± 110.96 hectares to 56,617 ± 220.90 hectares) and a 6% reduction in natural forest cover (5,965 ± 353.72 hectares). Sparse vegetation, including smallholder farms, decreased by 35% from 45,064 ± 163.79 hectares to 29,424 ± 114.81 hectares. Projections for 2030 and 2040 indicate minimal changes based on current trends; however, these do not consider potential impacts from climate change, large-scale development projects, and demographic shifts, necessitating cautious interpretation. The results highlight areas of stability and vulnerability within the GAP and offer critical insights for the development of targeted conservation strategies. Additionally, the methodological framework presented provides a robust approach for accurate and detailed landscape-scale monitoring of tropical peatlands, applicable to other regions facing similar environmental challenges.

Soil potentially toxic elements (PTEs) pollution in black soil is of significant concern in China. However, research is scarce regarding the current status, ecological risk, and human health risk of PTEs in the black soil area of northeast China. In our study, 304 soil samples (0-20 cm) were collected in Gonghe Town, Hailun City. The pollution degree and spatial distribution patterns of soil PTEs were analyzed by using the single-factor pollution index (PI) and the Nemerow pollution index (NPI). The source apportionment of PTEs was carried out by combining correlation analysis, principal component analysis (PCA), and positive matrix factorization (PMF) methods. Meanwhile, the potential ecological risk (RI) and the human health risk (HI) associated with soil contamination from various sources were evaluated through the RI and the HI. The results demonstrated that the average content (mean ± standard deviation) of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were 11.16 ± 1.32 mg/kg, 0.11 ± 0.04 mg/kg, 65.29 ± 3.46 mg/kg, 22.56 ± 1.32 mg/kg, 0.03 ± 0.01 mg/kg, 27.07 ± 1.46 mg/kg, 26.09 ± 2.84 mg/kg, and 66.01 ± 4.52 mg/kg, respectively. The overall PTEs in the study area exhibited slight pollution levels. The PCA and PMF model source apportionment was validated against each other to yield four sources, which were natural source (33.2%), irrigation source (29.5%), traffic source (23.4%), and fertilizer source (13.2%). The overall RI in the study area was determined to be at the level of slight ecological risk. The non-carcinogenic risk of PTEs to children and adults was ignored, and the carcinogenic risk was at an acceptable level. The comprehensive analysis of PTEs, pollutant sources, RI, and HI concluded that the fertilizer source should be the primary control source, with Cd identified as the first control PTE. The irrigation source and the traffic source were identified as the secondary control sources, with As, Pb, and Hg identified as the secondary control PTEs. This study revealed the status, risks, and sources of PTEs in black soils and provided a scientific basis of PTEs control for policymakers.

The new digital infrastructure has become an important basis for the green development of agriculture. This paper selects provincial sample data from 2006 to 2022, constructs an indicator system to measure new digital infrastructure and agricultural green total factor productivity, and explores how new digital infrastructure can promote agricultural green development. The results show that: (1) the new digital infrastructure has a significant role in promoting the green development of agriculture, and this conclusion is still valid after processing endogeneity and heteroscedasticity; (2) Technology and land factors play an intermediary role in the promotion of green agricultural development by the new digital infrastructure, that is, the new digital infrastructure helps to improve the quality and technical level of cultivated land and thus promote green agricultural development; (3) Labor force factors optimize the mediating role of technology factors, that is, the higher the quality of labor force, the stronger the role of the new digital infrastructure in promoting the green development of agriculture through the technological path; (4) The effect of new digital infrastructure on the green development of agriculture is obviously heterogeneous, and the effect is more obvious in northwest China and the regions with lower marketization level, higher environmental regulation level. This study is helpful to clarify the relationship between new digital infrastructure and agricultural green development in China, and provide corresponding policy suggestions for promoting regional agricultural green development.

Soil salinization is an essential risk factor for agricultural development as well as for food security, and how to obtain regional soil salinity information more reliably remains a priority problem to be solved. To improve the accuracy of the inversions for soil salinity, a new inversion model for soil salinity based on stacking integrated algorithm for learning was submitted for this work which took the prediction results of several basic models as new features and then trained a secondary model to fuse the prediction results of basic models. We compared and analyzed it against four machine learning regression models, namely, random forest (RF), back propagation neural network, support vector regression, and convolutional neural network. Findings indicated the stacking integrated learning regression model fitted better and had good stability, on the test set, the stacking integrated learning regression model showed a relative increase of 8.16% in R2, a relative decrease of 13.95% in RMSE, and a relative increase of 6.47% in RPD when compared to the RF model, which was the single most effective machine learning regression model, and the stacking model was able to achieve soil salinity inversion more accurately. The soil salinity in the oasis areas of the Manas River Basin tended to decrease from north to south in 2016 to 2020 from a spatial point of view, and it was reduced in April from a temporal point of view. The percentage of pixels with a high soil salinity content of 2.75–2.8 g/kg in the study area had decreased by 19.64% in April 2020 compared to April 2016. The innovatively constructed stacking integrated learning regression model improved the accuracy of soil salinity estimation on the basis of the superior results obtained in the training of the single optimal machine learning regression model. As a consequence, this model can provide technological backup for a fast monitoring and inversion of soil salinity as well as prevention and containment of salinization.

Diagenetic spheroids are rounded mineralised structures in sedimentary rocks that span several orders of size dimensions. These objects include rosettes spanning tens of micrometres, millimetre-sized granules, and centimetre- to metre-scale botryoids, nodules and concretions. Connections between diagenetic spheroids and chemically oscillating reactions (COR) have been established based on chemical and pattern similarities. Nevertheless, it is unknown if there are variations in their occurrences throughout geological time, especially during periods of global environmental change. This is because COR are pattern-forming reactions where carboxylic acids are decarboxylated by strong oxidants like sulphuric acid, bromate, or iodate. The hypothesis is that there should be a greater number of diagenetic spheroids at periods of increased atmospheric-oceanic oxygenation levels. Hence, this work presents the first compilation of occurrences of diagenetic spheroids between 0.541 to 1.8 billion years ago (Ga). The compiled patterned objects are those with concentric laminations and radially aligned crystals, which are patterns akin to equidistant circularly concentric waves that radially propagate in COR. Another characteristic of diagenetic spheroids, such as in botryoidal minerals, is the destructive interfere that forms circular twins; this is identical to the COR pattern formed when circular waves meet. The timeline of Proterozoic diagenetic spheroids produced in this work reveals a significant increase of occurrences across the Ediacaran, which is attributed to increased environmental oxidation state. During this interval, seawater is known to have become richer in sulphate and iodate, which create ideal conditions for the abiotic and diagenetic oxidation of biomass. Therefore, increased occurrences of diagenetic spheroids in the Neoproterozoic possibly represents sedimentological evidence for abiotic decarboxylation reactions and widespread COR in productive environments. The distribution of diagenetic spheroids observed during the Proterozoic may also be more broadly applicable to other epochs of Earth history.

The energy transition towards Net Zero Emission by 2060 hinges on the renewable energy power plants in Indonesia. Good practices in several countries suggest a peer-to-peer (P2P) energy trading system using blockchain technology, supported by renewable energy (solar panels), an innovation to provide equal access to sustainable electricity while reducing the impact of climate change. The P2P energy trading concept has a higher social potential than the conventional electricity buying and selling approach, such as that of PLN (the grid management concept), but does not have a sharing element. This model implements a solar-powered mini-grid system and produces a Smart Contract that facilitates electricity network users to buy, sell, and trade electricity in rural areas via smartphones. This study aims to analyze the stakeholders' perceptions of the peer-to-peer (P2P) energy trading model using blockchain technology in Gumelar District, Banyumas Regency, Central Java Province, Indonesia. The stakeholders include households, the Ministry of Energy and Mineral Resources (ESDM), the State Electricity Company (PLN), the Institute for Essential Services Reform (IESR), Awina Company, and IPB University. The strength factors of this model are the freedom to generate and sell electricity (0.1) and transparency in electricity usage and sales by disclosing the amount, duration, and price of electricity (0.1). Regarding weakness factors, this model is primarily suitable for the lower middle class residing in rural or remote areas (0.02). Additionally, the intermittent electricity production to meet the substantial demand is a weakness (0.03). The opportunity factor for the model is the increase in public awareness and cooperation in using environmentally friendly, pollution-free electricity (0.12). Furthermore, there is an opportunity for additional income (0.12) and new business investment (0.12). Regarding threat factors, the model faces significant threats from the implementation aspect involving multiple parties (0.04). There is a potential threat in the form of losses for state utilities such as PLN or individuals who have already established electricity infrastructure if this program is implemented on a large scale (0.04). This model is located at the coordinate point (-0.40; 0.31), placing it in quadrant II. This indicates that the model should apply the Stability Strategy and focus on the Selective Maintenance Strategy for improvement. The stability strategy goal is to maintain the current situation by leveraging opportunities and addressing weaknesses. For effectiveness and efficiency, the strategy emphasizes fostering collaboration with PLN, which holds the legal authority as the sole utility company in Indonesia with an extensive electricity network, as well as advocating for regulations that support the independent purchase and sale of solar-powered electricity, particularly in areas without PLN network coverage.

The Normalized Differential Spectral Attenuation (NDSA) technique was proposed years ago as an active method for measuring Integrated Water Vapor (IWV) along a Ku/K-band radio link immersed (totally or partially) in the troposphere. The approach is of the active kind, as it relies on the transmission of a couple of sinusoidal signals, whose power is measured at the receiver, thus providing the differential attenuation measurements from which IWV estimates can be in turn derived. In 2018, a prototype instrument providing such differential attenuation measurements was completed and set up for a first measurement campaign aimed at demonstrating the NDSA method. By the end of June 2022, the instrument was profoundly modified and upgraded so that a second measurement campaign could be carried out from August 1 to November 30, 2022. The transmitter was placed on the top of Monte Gomito (44.1277°lat, 10.6434°lon, 1892 m a.s.l.) and the receiver on the roof of the Department of Information Engineering of the University of Florence (43.7985°lat, 11.2528°lon, 50 m a.s.l.). The resulting radio link length was 61.15 km. Four ground weather stations of the regional weather service were selected among those available. In this paper, we describe the upgraded instrument and present the outcomes of the new measurement campaign, whose purpose was mainly to compare the IWV estimates provided by the instrument with the ground sensors measurements of air temperature, air humidity, barometric pressure, and rainfall.

Groundwater flow and transport models are essential tools for assessing and quantifying the mi-gration of organic contaminants at polluted sites. Uncertainties in the hydrodynamic and transport parameters of the aquifer have a significant effect on model predictions. Uncertainties can be quantified with advanced sensitivity methods such as Sobol’s High Dimensional Model Reduction (HDMR) and Variogram Analysis of Response Surfaces (VARS). Here we present the application of VARS and HDMR to assess the global sensitivities of the outputs of a transient groundwater flow model of the Gállego alluvial aquifer which is located downstream the Sardas landfill in Huesca (Spain). The aquifer is subject to the tidal effects caused by the daily oscillations of the water level in the Sabiñánigo reservoir. Global sensitivities are analysed for hydraulic heads, aquifer/reservoir fluxes, groundwater Darcy velocity and hydraulic head calibration metrics. Input parameters in-clude aquifer hydraulic conductivities and specific storage, aquitard vertical hydraulic conductiv-ities, and boundary inflows and conductances. VARS, HDMR and graphical methods agree to identify the most influential parameters which for most of the outputs are the hydraulic conduc-tivities of the zones closest to the landfill, the vertical hydraulic conductivity of the most permeable zones of the aquitard, and the boundary inflow coming from the landfill. The sensitivity of heads and aquifer/reservoir fluxes with respect to specific storage change with time. The aquifer/reservoir flux when the reservoir level is high shows interactions between specific storage and aquitard conductivity. VARS and HDMR parameter rankings are similar for the most influential parameters. However, there are discrepancies for the less relevant parameters. The efficiency of VARS was demonstrated by achieving stable results with a relatively small number of simulations.

The Ulytau region located at the heart of Kazakhstan is one of the promising territories for setting up geopark. Here, in the centre of Kazakhstan is a geographical and economic region which consists of desert-steppe landscapes with small, steep low-mountain massifs. This is one of the largest regions of Kazakhstan in terms of industrial potential, wealth of minerals and raw materials, natural and cultural heritage. The world's largest copper-bearing province is located here. The geological history of this area tells of no less than 500 million years of planetary development. Despite the lengthy time that geology and the active use of resources were in focus, geoheritage objects were previously lacking attention and any characterization. In the Ulytau region, many preserved archaeological and ethnographic sites indicate that the Saryarka steppes were included in the trade and cultural sphere of the Great Silk Road. Geological, historical and sacred objects make this territory an extremely interesting object for the development of geotourism and the creation of geoparks as the basis for the sustainable development of the region.

Climate variability influences plant growth. With the variation in atmospheric CO2 concentration leading to global warming, it is urgent to monitor the performance of plant ecosystems for optimal carbon sequestration. Net primary productivity (NPP) is the perfect measurement tool as it measures the net carbon flux between the atmosphere and green plants and the factors that affect it. This study applied remote sensing techniques, specifically one of the radiation use efficiency models; the CASA model (Carnegie-Ames-Stanford approach) to assess the spatio-temporal dy-namics of NPP in Togo from 1987 to 2022 and the climatic parameters that influence it. The annual average NPP over the 36 years of the study is 4565.31 Kg C ha⁻¹. Variability is observed over the years with extremes in 2017 (6312.26 Kg C ha⁻¹) and 1996 (3394.29 Kg C ha⁻¹). Natural formations identified as high-production areas saw their productivity increase between 2000 and 2022. The interaction between climate change and land use changes negatively influences the variation of Total Production (PT) between 2000 and 2022, while individually, these parameters positively influence the variation of NPP (58.28% and 188.63%). The correlation result is positive and higher between NPP and light use efficiency (LUE) (r² = 0.75). Actual evapotranspiration also shows a positive correlation with NPP (r² = 0.43). A positive but weak correlation is observed between NPP and precipitation, potential evapotranspiration (r² = 0.20; 0.10 respectively). Temperatures have almost no correlation with NPP (r² = 0.5). Climatic parameters as a whole under the LUE banner influence NPP more. This study helps understand ecosystem performance in the context of To-go's commitments to reduce greenhouse gas emissions and combat climate change.

The production of a ton of steel in an integrated steel plant generates of approximately 1 ton of ferrous slag. A great part of ferrous slags is recycled in civil and road construction etc., but a huge amount is still dumped. Recycling ferrous slag as cement precursor was considered the upcycling route. Regulation (EU) 2024/1252 requires the Member States to provide information, until November 2026, on the critical raw materials (CRM) amount in their secondary resources and on quantification methods used for. This study addresses two synergic objectives: ensuring the reliability of XRFS results and screening for CRM in ferrous slags based on XRFS outcomes. The main novelty of the paper is the way of ensuring the reliability of the XRFS results based on weighted arithmetic mean and on the maximum likelihood approach. Secondly, the XRFS measurements carried on ferrous slags demonstrate that they contain significant amounts of CRM like Ba, Sr, Y, etc. XRFS cannot detect light CRM. Our preliminary LIBS measurements on ferrous slags disclosed the presence of Li and Be. The drawbacks of the XRFS technique impose further research to develop an integrated XRFS, LIBS and XRD procedure for comprehensive and trustworthy CRM screening in extractive waste piles.

The ever-increasing industrialization of certain areas of the planet combined with the simultaneous degradation of the natural environment are alarming phenomena, especially in the field of human health. The concentration of Particulate Matter with an aerodynamic diameter of 2.5μm (PM2.5) and 10μm (PM10), nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3) needs constant monitoring, as they consist the main cause for many diseases. Based on the existence of statutory limits, by the World Health Organization (WHO), for the concentration of each of the aforementioned air pollutants, it is considered necessary to develop forecasting systems that will have the ability to correlate the current meteorological data with the concentrations of the above pollutants. In this work, the attempt to predict the air pollutants concentrations in the wider area of Beijing, China, is successfully carried out using artificial neural networks (ANNs) models. In the frame of the specific work, a significant number of ANNs was developed. For this purpose, an open-access meteorological and air pollution database was used. Finally, a statistical evaluation of the developed prognostic models was carried out. Results showed that ANNs present a re-markable prognostic ability in order to forecast the air pollution levels in an urban environment.

The sustainability concept has acquired a variety of meanings according to different currents of thought and the context in which it is used. The aim of this research was to characterize the perception of producers, extension agents and officials regarding sustainable cattle ranching (SCR) in an area where tropical cattle ranching is practiced. A survey was applied to producers chosen through stratified random sampling, and to extension agents and officials selected using the snowball technique. The perception of SCR was determined under two contexts: 1) the idea or interpretation of the individual and 2) the assessment (positive or negative) of this type of cattle ranching (net perception index, NPI). The extension agents oriented their perception of SCR mainly in economic (52.2%) and environmental (47.8%) aspects, similar to the producers (48.4% and 21.3% respectively), while the officials related it more to an environmental dimension (71.4%). It is concluded that the perception of SCR in general is positive, but its conceptualization is differentiated, according to the role the individuals play in the activity, their academic training and their expectations.

Particulate Organic Carbon (POC) plays a crucial role in the marine carbon cycle, influencing carbon flux and many important ocean biogeochemical processes in the Bay of Bengal. The purpose of this study was to examine the seasonal and annual variability of POC in the Bay of Bengal (BoB) region and its correlation with Sea Surface Temperature (SST) and Chlorophyll-a (Chlor_a). This study uses level-3 POC, Chlor_a, and SST data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua satellite. The surface POC concentration in the Bay of Bengal declined at a rate of -1.30 mgm^-3y^-1 over a ten-year period (2003-12) and ranged from 86.48 mgm^-3 to 110.93 mgm^-3 with an average of (93.74±7.50 mgm^-3). Seasonally, the mean POC was highest (97.40 mgm^-3) during the post-monsoon (October-November) and lowest (79.36 mgm^-3) in the pre-monsoon (March-May). Seasons were observed to have statistically significant differences in POC concentration in the study area (F_(3,2155) = 6.298; p <0.05). A strong positive correlation between POC and Chlorophyll was observed whereas a week positive correlation between POC and SST was observed. POC was observed to be very prominent in post-monsoon (97.40 mgm^-3) and in northeast-monsoon (97.14 mgm^-3) and moderate to low in southwest (81.12 mgm^-3) and pre-monsoon (79.36 mgm^-3). The Bay of Bengal’s annual mean POC:Chlor_a ratio ranged from 97.56 mgm^-3 to 332.89 mgm^-3, indicating a significant impact of biological processes on POC composition. To see how POC fluctuation affects biogeochemical processes in the Bay of Bengal, deeper investigation is required.

The ecosystem plays a crucial role in mitigating climate change and protecting the environment. This study employs GIS technology to conduct an in-depth analysis of the current status of Queensland's ecosystem and develops a Climate Change Vulnerability Index (CCVI) model based on six sub-factors. These sub-factors include the Exposure Index (Mean surface temperature and precipitation), the Sensitivity Index (Population density, Building density, and Proximity to forests and nature reserves), and the Adaptive Capacity Index (Nighttime light radiation). The findings indicate that the CCVI value is lowest in the southeastern coastal region of Queensland, suggesting that this area is less vulnerable to climate change. However, other coastal areas and the far western inland regions exhibit higher CCVI values, indicating greater climate vulnerability. These areas require attention and the implementation of appropriate measures. By deepening our understanding of exposure, sensitivity, and adaptive capacity, we can formulate effective policies and measures to promote sustainable development and mitigate the negative impacts of climate change on the region. This study holds significant practical implications for guiding ecological planning and management decisions in the area.

As an International Union for Conservation of Nature (IUCN) voluntary reviewer of the natural World Heritage sites nominations focusing on criteria (vii) superlative natural phenomena and (viii) geological history I had the opportunity of evaluating 13 nominations from 12 countries from 2009 - 2022 from the Central Highlands of Sri Lanka to the Vatnajokull National Park Iceland. An early appreciation of the natural history and landscapes were developed as a geologist studying, working and visiting various areas in the USA and Canada. Further experience, as an academic in Sri Lanka and Australia, where I also had the opportunity of various assignments and meetings that afforded field trips and study tours to many World Heritage sites in Asia, Africa, South America and Europe. In this paper, I highlight the following sites that were subject to IUCN World Heritage evaluations and their potential for geo-education: Central Highlands Sri Lanka, China Danxia, Ningaloo Australia, Trang An Vietnam, Lut Desert Iran, Barberton South Africa, Trondek Klondike Canada, Vatnajokull Iceland, Classic Karst Slovenia, Sof Omar Ethiopia, Ha Long Bay – Cat Ba Archipelago, Vietnam and Evaporitic Karst Caves of Northern Apennines, Italy. From these experiences it is apparent that this relevant topic, the conservation of nature, should be an important part of the geoscience’s study curriculum along with other social and environmental subjects.

In recent decades, both in Italy and internationally, the phenomenon of abandoned industrial buildings has grown considerably, causing inevitable social, urban and economic impacts. At the same time, the cultural debate has increased awareness of the problem and the strategic role that abandoned industrial sites can play in responding to new needs. This contribution analyzes the dismantling process of the Akragas Montedison factory in Porto Empedocle, Sicily, examining the evolution of disused industrial areas from the 20th century to the present day and the possibilities of reconversion for appropriate reuse.

This study highlights the importance of quantifying groundwater resources for the Monahans and Kermit dune fields in the northern Chihuahua Desert, West Texas USA as potential contributors to the regional Pecos Valley Aquifer (PVA). Sedimentary architecture models of these dune fields show perched aquifers with water tables 1-10m below the surface and southwestward groundwater flow sub-parallel to a Pleistocene/Pliocene aquitard. Sinkhole-like features into the top of the aquitard are infilled with the thickest occurrences of aeolian sand. Groundwater recharge occurs from the enhanced capture of precipitation on mostly bare active dunes where infiltration rates >250mm/hr. The deuterium and oxygen isotopic ratios for groundwater from the Kermit and Monahans dune fields show pronounced evaporative isotopic depletion and less isotopic variability than corresponding rainfall, particularly for deuterium values. Groundwater from a shallow central well in the Kermit dune field yielded contemporary 14C activity (Fm =1.02), indicating contributions from recent precipitation. In contrast, more evolved 14C values at the western margin (FM=0.84) and at 30m below the surface (FM=0.76), similar to proximal Fm values from the PVA (0.89-0.82), may indicate dissolution of older (&gt; 100 ka) DIC from buried playa-lake sediments and carbonate-soils with groundwater flux to the southwest, and less direct atmospheric influence. The perched aquifers of the Monahans and Kermit dune fields contain water volumes > 0.1 km3 and may contribute up to 9% of the total annual recharge to the PVA.

Is it possible that educating women could be the key to reducing birth rates and protecting the environment? Women's education in 3rd countries is far more than just access to basic education. It is a pathway to economic growth, social stability and self-awareness. This essay reflects on the ethical challenges and benefits of educating women in areas such as interpersonal relationships, changing the traditional role of women and sustainability. In exploring this key issue, it is possible to discover that education can transform society and bring about real change, provided humanity accepts its responsibility for the state and sustainability of a quality environment for future generations.

Geochemical mapping of river sands in the Manufahi area of Timor-Leste revealed potential areas for future mineral exploration. River sand samples from the study area were collected and geochemically analyzed to identify anomalous concentration distributions of several valuable elements and locate potential target areas and geological formations that may host mineral deposits. The 26 major and minor elements were identified using wavelength-dispersive X-ray fluorescence. The river sands exhibited varying elemental concentrations, with Cr, Cu, Zn, and Ba showing deviations from the normal distribution patterns. Identification of geochemical anomalies is an important task in mineral exploration geochemistry. The mean + 2 standard deviations (mean+2STD), median + 2 median absolute deviations (median+2MAD), and Tukeyâs inner fence (TIF) methods were used to determine the geochemical thresholds. This study shows that TIF and principal component analysis (PCA) methods are highly effective in calculating appropriate threshold values and identifying relevant elemental associations. These approaches have proven useful for delineating target areas for mineral deposits, resulting in reliable outcomes. Four predicted target areas with high potential for deposits and mineralization anomalies of Cr, Cu, Ni, and Ba were delineated in the study area.

While the beneficial effects of using magnetic and electromagnetic treatment (ET) of brackish and saline waters on soil salinity reduction in the root zone were widely reported more studies are needed to answer questions about the soil salt leaching efficiency and the effect of the duration of the exposure to ET. For this aim, pot experiments were conducted using an Aqua-4DR physical water treatment device. The first experiment included two trials. The first considered 5 concentrations: C0:1.0; C1:4.5; C2:9; C3:13.5; and C4:18 dSm-1. The results revealed that the volume and the salt concentrations of the drained waters were significantly higher under irrigation with ET saline waters than those provided by untreated waters. The drained fraction of water varied from 20 to 26% under irrigation with untreated water and increased from 33 to 56% under irrigation with electromagnetized water indicating an improvement of salt leaching. The second trial was carried out with different irrigation doses. The result showed that the higher the dose, the more obvious and significant ET effect. The different treatment durations of water exposure revealed that the volume and salinity of drained water significantly increase as the ET duration increases. An increase in ET duration induces also an increase in soil water content of around 2.5%. Based on the experimental findings, we may conclude that the ET of saline water can reduce the adverse effect of salinity on the top soil, but these leached salts are carried away in depth and there is no concentration limit of water to the effect of the ET.

Human-elephant conflict has become a conservation challenge in Asia and Africa resulting in considerable human fatalities annually. We deployed an AI-embedded camera-alert system in a conflict hotspot in West Bengal, India to determine if AI algorithms could accurately detect elephants and if real-time alerts that triggered a rapid response could prevent serious incidents. The system successfully detected elephants near villages (266 events) and transmitted real-time alerts (x̄ = 42 seconds) permitting quick response by field personnel to prevent conflict (x̄ = 18.2, SD = 12.4 min to arrival). Matriarch herds of elephants were detected mostly at night when human traffic was minimal; lone adult bulls, the class most prone to conflict, were detected day and night. Frequent detections of humans (33,217 events) on routes used by elephants highlighted the value of real-time monitoring especially during daytime. Twelve human fatalities and eighteen serious injuries occurred in the study area between 2019-2023 but none during deployment of the AI system, supporting the hypothesis that alerts integrated with rapid response can reduce conflict. Loss of lives and livelihoods underscore the urgency of applying this approach to other elephant ranges and adapting AI models to conflict-prone species to provide early warning and promote coexistence.

Maritime surveillance technology faces challenges of astronomical size in this vast ocean world—challenges vital to global security and environmental protection alike. Such as these may be reversible or not. Remotely sensed monitoring also uses photos taken from satellites, synthetic aperture radar (SAR) equipment, and unmanned aerial vehicles (UAVs) to fully monitor maritime activities but also ferret out suspicious behaviour like piracy, bootleg shipments, and illegal fishing. This mixed-method approach--quantitatively and qualitatively——measures the efficiency of difficulties associated with, and legal implications behind aerospace-monitored maritime surveillance. The results show that remote sensing provides a great deal of sea-level situational awareness; however, there are also many complex technical, operational, and legal issues, including information overcrowding, complications in integration, privacy issues, as well as the need for worldwide legal harmonisation. It ends with recommendations on ways to ultimately increase capacity, how to write standard procedures for secondary development and proposals for revising laws to absorb these new technologies. Its goal, therefore, is to benefit the global anti-maritime crime effort. Ultimately, though, it dreams that we might construct an entirely marine environment where all marine activities are conducted both safely and freely, without fear.

The development of solar energy on a regional scale necessitates a thorough understanding of available resources. Cuba, facing prolonged economic, environmental, and energy crises, urgently needs to enhance its sustainability through solar energy. While solar resource mapping is widespread, Cuba lacks extensive field measurements, often relying on models that may not be ideally suited for large regions like Matanzas province. Spanning over 12,000 km² with nearly 150 km between its northern and southern extremes, Matanzas presents challenges for high-resolution solar mapping. This study introduces a methodology that integrates various methods and databases to achieve maximum resolution in the resulting solar map. The approach is designed for large areas where conventional high-resolution models fall short. By optimizing calculation times and parameterizing the entire surface latitudinally, a high-resolution solar resource map for Matanzas has been developed. This map significantly enhances the understanding of solar resources in Cuba and proposes new methodologies for analyzing solar potential in similarly large regions.

Manure-compost-soil is the main pathway for the use of agricultural livestock waste. Biochar, regarded as the conditioner, was beneficial to nitrogen fixation during aerobic composting, and was to the enhancement of soil organic matter (OM) and nitrogen content, when applied with compost to the soil. But, the manure-compost-soil process was also related to microbial succession, whether biochar could affect this succession was not studied. In this paper, we investigated the influence of biochar on the manure-compost-soil process and its microbial community succession. Compared with the control group, biochar increased the OM and total nitrogen content of the compost. Biochar, compost and biochar-based compost improved the total carbon (TC) and OM of the soil. The genera of the initial composting sample were Saccharomonospora, Atopostipes and Lactobacillus, and were eliminated after high-temperature fermentation. Lysobacter, Glutamicibacter and Streptomyces were the dominant genera in the soil samples, promoting plant growth. Nocardiopsis, Saccharomonospora, Bacillus and Oceanobacillus dominated the genera in the whole manure-compost-soil process. Thus, aerobic composting could eliminate the toxic or negative bacteria that were directly input into the soil by manure. Those genera from compost or biochar-based compost flux into the soil could make an important contribution to OM’s cycle.

Real-Time Kinematic (RTK) is currently the most widely used method for positioning using Global Navigation Satellite Systems (GNSS) due to its accuracy, efficiency and ease of use. In forestry, position is a critical factor for numerous applications, with GNSS nowadays the preferred solution for obtaining such data. However, the decreased performance of GNSS observations in challenging environments, such as under the forest canopy, must be considered. This paper analyzes the performance of a survey-grade GNSS receiver under coniferous/deciduous tree cover, with short observation times of 30 seconds and corrections received in the field from a Continuously Operating Reference Station (CORS) of the national RTK network in Romania. 84 test points were determined, randomly distributed under the canopy, with reference data collected by topographical surveys using total station equipment. Relatively good accuracies were obtained, especially for horizontal position (RMSEs of 1.47 – 2.07 meters). The variation of GNSS performance under the different forest compositions was found to be statistically significant, while GNSS-specific factors such as DOP values only influenced the precision and not the accuracy of observations. We established that this methodology offers sufficient accuracy, application-dependent, even if the majority of GNSS solutions were code-based, rather than carrier phase-based, due to strong interference from the vegetation.

Tropical regions face unique challenges in building sustainability due to high temperatures, humidity, and heavy rainfall. While building energy regulations are essential for promoting energy efficiency, their effectiveness in addressing tropical climate conditions needs to be studied more. This research aims to systematically investigate tropical building sustainability issues and evaluate the impacts of building energy regulations on these challenges. The study will identify gaps in current regulations by analyzing existing research and recommend strategies for developing more comprehensive frameworks that promote sustainable building practices in tropical regions. This research contributes to developing effective policies and strategies for achieving sustainable and energy-efficient built environments in tropical climates.

The industry currently generates numerous substances, such as food additives, whose environmental impacts, particularly in marine environments, remain inadequately assessed. This study employs Aurelia aurita for the first time as a model organism to evaluate the toxicity of such compounds. For this, the main goal is to evaluate the toxicity of two food additives, 2-Methyl-1Phenylpropan-2-ol (S1) and 1-Phenylethan-1-ol (S2), on A. aurita ephyrae, comparing the results with other organisms representing different trophic levels, specifically the alga Phaeodactylum tricornutum and the crustacean Artemia salina. Acute toxicity tests were conducted on each organism. Mortality rates were measured for Artemia, growth inhibition for the algae, and mortality and pulsation frequency for ephyrae. LC50 values were determined using probit regression analysis with R software. Tests for algae and Artemia followed ISO guideline and international standardized protocols. For A. aurita, a modified protocol by Mercado et al. (2023) was used. The tested additives showed a toxicity around 600 mg/L for A. salina. For the algae, S1 was significantly more toxic (LC50 ≈ 100 mg/L) compared to S2 (LC50 ≈ 450 mg/L). Similarly, in A. aurita, S1 exhibited high toxicity (LC50 ≈ 10 mg/L) while S2 had a lower toxicity (LC50 ≈ 80 mg/L). Pulsation frequency data for A. aurita revealed that S1 initially increased pulsation rates at lower concentrations (maximum at 10 mg/L), followed by a significant decrease at higher concentrations. Conversely, S2 showed a steady decrease in pulsation rates up to 10 mg/L, with a slight increase at concentrations of 15, 20, and 25 mg/L. The results demonstrate varying sensitivity to the toxic effects of the two compounds across different trophic levels, with A. aurita ephyrae being the most sensitive. This suggests the potential efficacy of jellyfish as novel ecotoxicological models due to their heightened sensitivity, enabling detection of lower contaminant concentrations in test samples. Further research is required to enhance the efficiency of ecotoxicological assays using these models.

The social, environmental and scientific significance of the urban climate has shaped a research stream at Universitat Jaume I’s Climate Lab. Previous research has found higher temperature trends at urban observatories. This study examines in depth the features of the urban environment and the thermal behaviour of land use and land cover and the changes which have taken place. The CORINE Land Cover database was used to delimit the primary Land Use Land Cover (LULC) and its changes between 1990 and 2018. Once this had been established, land surface temperatures (LSTs) between 1985 and 2023 were retrieved from the Landsat database available on the Climate Engine website. Analysis of the primary land cover showed the greatest thermal increase in artificial surfaces, especially in industrial, commercial and transport units which are common on their outskirts. These areas also have the highest temperatures on a monthly basis with the biggest differences occurring in the summer. The results are less clear for urban fabrics and agricultural areas due to their diversity and complexity. The study concludes that urban growth and its commercial and industrial environment has an undeniable effect on the temperatures recorded by urban observatories and enables better decision-making when setting up weather stations for a more detailed time study of the urban heat island (UHI).

Bioremediation of crude oil-contaminated soil in Kuwait was evaluated using the biowashing pilot reactor system, whose components included 3 biowashing reactors; an oil separator, a hydrocyclone, and a dissolved air flotation. The biowashing pilot reactor system was fed with hemoglobin, a cheap and rich nutrient source containing carbon and nitrogen for bacterial growth. The initial total petroleum hydrocarbons (TPH) concentration was about 84,000 mg/kg soil. The initial TPH concentration decreased to 38,000 mg/kg soil on day 1. The degradation extents of TPH were 55%, 91%, and 96% on days 1, 3, and 5. The first-order rate constant for TPH degradation rate was 0.6820.0004/day. The initial unresolved complex mixture (UCM) concentration was 78,000 mg/kg soil. The degradation extents of UCM were 53%, 91%, and 98% on days 1, 3, and 5. Then, the degradation extents of individual components of total polycyclic aromatic hydrocarbons (PAH), alkylated PAH, and n-alkanes were measured for 5 days. 16S rRNA gene copy number was measured during 5 days for bacterial population estimation. Although there was a day delay in the accretion of the number of copies, the number increased from day 2 to day 5. The present study suggests that the biowashing pilot reactor system with a capacity of 200 L is efficient for TPH degradation.

Based on the land use data of Qingmei Harbor Mangrove Nature Reserve in Sanya, China, in 2009, 2015 and 2022, this paper utilizes the PLUS model to predict the land use changes in the region in 2035 under three development scenarios, namely natural development, urban construction and ecological protection. The results of the study show that the area of building land in this region increased rapidly from 2009-2015, and the corresponding cropland, parkland and arbor forest land as a whole showed a different degree of decline, while the expansion of the area of manmade land, such as building land, basically came to a standstill after 2015. However, the mangrove area in this region has maintained a stable growth trend from 2009-2022. The results of multi-scenario modeling of land in this region showed that the area of building land, unutilized land, and artificial land such as parkland and grassland increased the most under the urban development scenario. In the ecological protection scenario, the area of ecological land, such as arbor forest land and river and lagoon, increases significantly. However, there is no significant increase in the area of mangrove forests under any of the three development scenarios. At present, the task of “returning ponds to wetlands” has been basically completed in this area, and the space for large-scale expansion of mangrove forests in Qingmei Harbor is limited in the future, and the focus of subsequent work should be shifted to the enhancement of the quality and function of mangrove ecosystems.

Climate change presents an urgent global challenge, manifesting in rising temperatures and extreme weather events with severe societal impacts. The Eastern Mediterranean, warming faster than the global average, faces immediate repercussions. Climate literacy emerges as pivotal, empowering individuals to comprehend climate science and act accordingly. This study delves into climate literacy, attitudes, and 'greening' behaviours in the Eastern Mediterranean hotspot of Greece, based on a survey of 1,962 citizens. Findings indicate high climate literacy but lower adoption of 'greening' behaviours, especially those involving financial costs. Regression analyses highlight the significant role of climate literacy, concerns about personal impacts, coping appraisal and trust in institutions in promoting 'greening' behaviours. The study underscores the need for multifaceted strategies emphasizing financial motivation, trust-building, and societal norm shifts. Socio-demographic disparities, including gender and occupation, highlight areas for targeted interventions. The emphasis on the mental health impacts of climate-related events underscores the need for holistic disaster management. Policy implications are discussed, highlighting the potential of expanded climate literacy to catalyze collective action toward sustainability.

Molecular scattering (Rayleigh scattering) has been extensively utilized from the ground with lidars and from space to observe the limb, thereby deriving vertical temperature profiles between 30 and 80 km. In this study, we explore how temperature can be measured using the new Ozone Mapping and Profiler Suite (OMPS) sensor, aboard the Suomi NPP and NOAA-21 satellites. OMPS comprises three instruments primarily tasked with studying the composition of the stratosphere. Among them, the Limb Profiler (LP) measures the radiance of the middle atmosphere's limb (stratosphere and mesosphere, 12 to 90 km altitude) across wavelengths from 290 to 1020 nm. This new dataset has been leveraged to derive temperature profiles with a vertical resolution of 1 km. To validate the method, the OMPS-derived temperature profiles were compared with data from four ground-based lidars, the ERA5 and MSIS models, and MLS at the lidar locations. The results indicate that OMPS and the lidars agree within a margin of approximately 5 K from 30 to 80 km. Comparisons with the models also show similar results, except for ERA5 beyond 50 km. Comparisons with MLS exhibit slightly higher deviations than those with the lidars. We investigated various bias sources, such as different attenuation sources that can generate errors up to 120 K in the UV range, while instrumental errors are around 0.8 K, and noise issues can cause errors up to 150 K in the visible range for OMPS. This study also highlighted the interest in developing a new miniaturized instrument that could meet real-time observation of atmospheric vertical temperature profiles using a constellation of CubeSats.

One of the main challenges associated with spatial entities affected by potentially irreversible adverse development processes (depopulation and related changes in the population structure, economic difficulties, declining accessibility and quality of services, etc.) is coping with their consequences – taking a planned approach (as opposed to passive observation of spontaneous developments) towards mitigating adverse effects on the quality of life of the local population. Public services (healthcare, education, culture, etc.), as a fundamental human need in modern society, but also a warranty of a certain level of living quality, are particularly important in such areas. Apparently, it is necessary to accept the closing of a number of facilities as a reality, and to take a planned approach seeking to mitigate the negative effects on the life of the local population. This is a context of our research, where these services are taken as a universal human right and striving for their equitable availability as a goal of national spatial development policies. The starting point in our analysis of this issue observed through the lens of the Serbian national legal and planning framework is the spatial plan of a local self-government unit as the basic platform for defining and operationalising spatial development policies at the local level. It has been examined whether it would be possible to use the mathematical modelling of optimal spatial solutions as support in making decisions that would minimise the negative effects of the closure of a number of public service facilities. The results for the selected research area and the network of primary healthcare facilities show that it is possible to stabilise the accessibility of these facilities by modelling the spatial organisation of primary healthcare despite the expected closure of as much as one-third of the facilities, while any other solution would give more or less unfavourable results.

This study introduces an advanced method for climate downscaling using a Super-Resolution Generative Adversarial Network (SRGAN), referred to as Elevation-integrated TEmperature and Precipitation SRGAN downscaling (E-TEPS), to enhance the spatial resolution of climate data, specifically 2m-temperature above the surface and total precipitation, from the high-resolution Euro-Mediterranean Center on Climate Change (CMCC) dataset over Italy. Traditional Numerical weather prediction (NWP) as well as global climate models (GCMs) generally lack the resolution required for local applications, and this research addresses that gap by refining GCM outputs to provide detailed local climate insights. E-TEPS incorporates elevation maps as auxiliary inputs, significantly improving the accuracy of downscaled temperature and precipitation data. Utilizing Google Cloud's computational resources, the model processes large climate datasets and runs complex training operations efficiently. The system is exceptionally fast, delivering all results in under 10 seconds. The model demonstrates superior performance over two interpolation methods (bicubic and linear), used as traditional downscaling methods, achieving lower Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), higher Pearson Correlation for temperature, and higher agreement values for the precipitation. Visual comparisons confirm that E-TEPS generated high-resolution outputs exhibit fewer artifacts and better detail preservation, particularly in regions with complex terrain and variable climatic conditions. These findings underscore the potential of our model in delivering precise, high-resolution climate predictions, thereby enhancing the performance of early-warning systems and supporting more effective climate-related decision-making. This paper is the first part of a two-part series; the second part will demonstrate the integration of this downscaling method with the FourCastNet global forecasting model to enhance climate predictions at a regional level, particularly focusing on high-resolution forecasts for Italy.

Utilizing groundwater offers a promising solution to alleviate water stress in Ethiopia, providing a dependable and sustainable water source, particularly in regions with limited or unreliable surface water availability. However, effective decision-making regarding well drilling and placement is essential to maximize groundwater resource potential, enhancing agricultural productivity, reducing hunger, and bolstering food security in Ethiopia. This study concentrates on the development of two-stage stochastic mixed integer programming (SMIP) models to optimize well placement for sustainable agricultural irrigation, considering uncertain demand scenarios. Additionally, a deterministic mixed integer programming model is formulated for comparison with the two-stage SMIP. Experiments are conducted to explore various demand scenario distributions, revealing that the optimized total cost for the two-stage SMIP generally exceeds that of a deterministic setting, aligning with the two-stage SMIP's focus on long-term benefits. Moreover, slight differences are observed in well layouts under different assumption scenarios. The study also examines the impact of selected parameters, such as fixed construction costs, per-meter drilling costs, and demand scenarios. The out-of-sample performance shows that the stochastic model is more flexible and resilient, with 11% and 4% lower costs than deterministic cases 1 and 3, respectively. This flexibility provides a more robust long-term strategy for well placement and resource allocation in groundwater management.

When earthquake damage occurs, it is extremely important to quickly identify the presence or absence of such damage. In this study, we developed and evaluated a new remote sensing index to automatically determine "damage" by image analysis when damage greater than partial destruction of a house by an earthquake or tsunami occurs. The accuracy of the houses estimated as "damaged" was high and sufficient for the initial assessment of damage. The results of this research are expected to be utilized for more rapid damage assessment after a disaster.

Forest fires can occur suddenly and have significant environmental, economic, and social consequences. Timely and accurate evaluation and prediction of their progression, particularly the spread speed in difficult-to-access areas, are essential for emergency management departments to proactively implement prevention strategies and scientifically extinguish fires. This paper provides a comprehensive analysis of advanced technologies for predicting forest fire spread in China and globally. Incorporating remote sensing (RS) technology and forest fire science as the theoretical foundation, and utilizing the Wang Zhengfei forest fire spread model as the technical framework, this study constructs a forest fire spread model based on remote sensing interpretation. The model optimizes the method for acquiring parameters and enhances algorithm accuracy. By considering regional landforms (ridge lines, valley lines, slopes) and vegetation coverage, this paper establishes visual interpretation markers for identifying hotspots within the spread model. Utilizing statistical data from pixels within the fire line zone transforms the methodology for predicting forest fire spread speed, resulting in greater accuracy compared to conventional fixed-point predictions. Finally, the model was applied to the case of a forest fire in Mianning County, Sichuan Province, China and verified using high-time resolution mid-infrared image data and previous research findings. The results demonstrate that the predicted fire spread area from this RS-enabled model is consistent with both high-time resolution geostationary satellite data and previous research outcomes, indicating high reliability. This model can provide crucial fire spread information to relevant emergency departments, enabling effective preemptive measures and scientific firefighting strategies.

Microplastics, plastic fragments smaller than 5 mm present in the environment due to the decomposition of larger plastics, can cause damage to various ecosystems and species of pollinating insects such as Apis mellifera bees. These bees play a crucial role in the ecology and production of honey and pollen, also serving as bioindicators of environmental quality as they are sensitive to contaminants such as microplastics. In this study, the presence of microplastics in these insects and their bee products, pollen, and honey, collected in August 2021 and August 2023 in rural areas (Tabio and Guasca) of Cundinamarca, Colombia, and urban areas (Universidad Nacional de Colombia) was evaluated. and Pontificia Universidad Javeriana) of Bogotá, Colombia. In each year, 24 bees, 10 grams of honey and 10 grams of pollen were collected per sampling point. Microplastics in bees and their products were identified and quantified by stereomicroscopy, with or without hydrogen peroxide digestion pretreatment. Microplastics were found in bees, pollen, and honey in both periods, with an increase in their quantity observed over time due to increasing environmental pollution. Blue fibers were the most common microplastics, with a greater amount recorded in 2023 compared to 2021.

Since the Industrial Revolution, nearly 700 GtC of carbon have been emitted into the atmosphere as CO2 derived from human activities, of which 292 GtC remain uncontrolled. Furthermore, the emission rate is increasing yearly, with the latest value (2022) of 11 GtC. By the end of this century, the atmospheric CO2 concentration is predicted to surpass 700 ppm. The effects of this sudden carbon release on the worldwide biogeochemical cycles and balances are not yet fully understood, but it is undeniable that global warming and climate change are already a fact, with this gas playing a starring role. Governmental policies and international agreements on emission reduction need to produce results quickly enough, and the deadline to act is running out. Besides the agreements to reduce emissions, alternative strategies to reverse this trend must be sufficiently promoted. Biological CO2 capture is a speedy flow of the carbon cycle capable of capturing over 115 GtC annually through photosynthesis. An increase of 6.5% in this capture and the subsequent stabilization of produced biomass could counteract the current CO2 emission rate. In this overview, the artificial culture of phytoplankton is considered a potential alternative to conducting this large-scale capture. A production system model is suggested and the main technological and political challenges for using large areas as partially-natural photobioreactors are discussed. The global implementation of these large CO2 sinks and the associated infrastructure would stabilize the carbon cycle while it is developed as a new source of richness.

The study investigates the economic feasibility and farmer acceptance of utilizing treated wastewater (TWW) for agricultural irrigation, particularly in the Northern Jordan Valley. Despite its potential to mitigate water scarcity, concerns persist regarding its impact on soil health, crop yield, and land utilization, hindering widespread adoption. The research aims to measure farm profitability and farmers' willingness to embrace TWW through various blending scenarios with traditional surface water sources. The yield response function to salinity was incorporated into profit function to simulate crop profitability and water values. Results indicate that the introduction of TWW negatively affects salt-sensitive crops like citrus but positively impacts others such as date palm, olives, tomatoes, and peppers due to increased fertilizer content in irrigation water. Economic performance indicators reveal a gradual decrease in water net productivity for citrus with increasing blending ratios of TWW, with the water value decreasing accordingly. Higher percentages of treated water do not consistently lead to increased productivity, profitability, or net value added, emphasizing the need for careful consideration and understanding of economic risks associated with specific crops and water quality. To mitigate the impact of water salinity on citrus production, growers are advised to improve soil quality, periodically flush the soil with low-salinity water, and use salt-tolerant rootstocks. Regular monitoring of soil and water salinity levels is crucial for informed decision-making. While using TWW, water may offer cost savings.

Land subsidence is an environmental hazard occurring gradually over time, potentially posing significant threats to the structural stability of civilian buildings and essential infrastructures. This study presented a workflow using the SBAS-PSInSAR approach to analyze surface deformation in the Choushui River fluvial plain (CRFP) based on Sentinel-1 SAR images and validated against precise leveling. Integrating InSAR results with hydrogeological data, such as groundwater levels, multilayer compactions, and borehole loggings, a straightforward model was proposed to estimate appropriate groundwater level drops to minimize further subsidence. The results showed a huge subsidence bowl centered in Yunlin, with maximal sinking at an average 60 mm/year rate. High-resolution subsidence maps enable the quantitative analyses of the safety issues for Taiwan High Speed Rail (THSR) across the considerable subsidence areas. In addition, the analysis of hydrogeological data revealed that half of the major compaction in the study area occurred at shallow depths. Based on a maximal subsidence control rate of 40 mm/year specified in the CRFP, the model results indicated that the groundwater level drops from wet to dry seasons needed to be maintained from 3-5 m for the shallowest aquifer and 4 – 6 m for aquifers 3 and 4. The workflow demonstrated the compatibility of InSAR with traditional geodetic methods and the effectiveness of integrating multiple data sources to assess the complex nature of land subsidence in the CRFP.

Global warming and climate change have been the major concern for multiple disciplines. Population growth, urbanization, and industrialization are major contributing factors to such a problem by escalating the use of fossil fuels to meet their energy demands. The building sector has the largest share in using the total globally produced energy and emitting tons of greenhouse gas emissions. Emerging eco-friendly technologies such as solar and wind energy harvesting are being extensively explored but still, they are insufficient. Nature-inspired technologies can be the solution to our problem. For instance, algae are microorganisms that use water, light, and CO2 to produce energy and sustain life. Exploiting such characteristics in the built environment is termed algae building technology, a very efficient and green application for a sustainable future. Algae-integrated façades show great versatility through biomass and energy production, wastewater treatment, shading, and thermal and acoustic insulation. In this paper, algae will be introduced as a robust tool toward a greener and more sustainable future, The algae-building technology and its implementation will be demonstrated. Steps for applying this sustainable approach in Egypt will be discussed.

In developing nations, such as Ekiti State, Nigeria, the use of remote sensing data, especially satellite and UAV imagery, remains significantly underutilized in land administration. This limits the potential of multi-resolution imagery in land governance and socio-economic development. This study examines factors influencing UAV adoption for land administration in Nigeria, mapping six distinct rural, peri-urban, and urban sites, and creating orthomosaics with resolutions ranging from 2.2cm to 3.39cm. Boundaries were manually delineated from multi-resolution orthomosaics to acquire coordinates, and parcel areas were calculated. Using 0.05m UAV imagery as the reference, the Root Mean Square Error (RMSE) was computed to evaluate 0.1, 0.5, and 1m orthomosaics' accuracy for boundary delineation across the six geographical contexts. The Normalized Parcel Area Error (NPAE) was also calculated to determine how the multi-resolution imageries affected the property areas. Results showed a consistent increase in error with increasing resolution (0.1m to 1m) in formal areas (Igedora, Maryland, Okebola) with physical demarcations, from 0.117m to 1.747m RMSE. In contrast, informal settlements exhibited inconsistent error values, indicating a differing impact of resolution on error between formal and informal areas. The research demonstrates the role of physical demarcations in facilitating cadastral mapping, with formal settlements demonstrating the highest suitability. This study recommends the use of imagery resolution specific to each context, offering guidance for improved land governance. Implications and recommendations include promoting awareness of settlement typologies in aerial imagery use for cadastral mapping, leveraging UAVs for high-resolution aerial imagery, and addressing regulatory challenges to promote UAV adoption. Finally, the RMSE and NPAE values can serve as metrics for assessing different resolution images’ fitness for cadastral mapping.

The increasing frequency of urban flooding, driven by global climate change, poses significant threats to the safety and resilience of urban rail transit systems. This study systematically examines the cascading failure processes and resilience of these networks under flood conditions, with a specific focus on the Shanghai Metro. A comprehensive resilience evaluation model was developed by integrating geographic information, static network characteristics, and dynamic passenger flow indicators. This study employs an improved Coupled Map Lattice (CML) model to simulate cascading failures, considering the coupling effects of station centrality, geographic elevation, and passenger flow dynamics. Results indicate that stations with higher degree centrality are more likely to trigger rapid cascading failures across the network. However, incorporating dynamic passenger flow and geographic elevation data helps mitigate these effects, emphasizing the need for multi-dimensional resilience strategies. The findings provide valuable insights for urban transit management, offering a scientific foundation for developing targeted disaster response strategies to enhance network resilience against floods. This study advances the understanding of the vulnerability of urban rail transit systems and offers practical guidance for improving disaster preparedness in urban transportation infrastructure.

Salt marshes in the southern North Sea are part of the UNESCO World Heritage Site Wadden Sea, the largest unbroken system of intertidal sand and mud flats in the world. They provide a very high nature value while significantly contributing to coastal flood and erosion risk management as a nature-based element of flood and erosion risk management systems for the densely populated coastal area. Climate change-induced sea-level rise is a significant concern: An integrated approach to salt marsh management adapted to the effects of climate change necessitates a understanding of the impact of different management strategies. This review commences with a description of the biogeomorphological conditions and processes in salt marshes for a better understanding of the natural dynamics and how they are influenced by management and climate change. In a second step, the impact of salt marshes on hydrodynamic processes and their role as nature-based element of flood and erosion risk management is presented. Management options and implementation methods are discussed and analysed concerning coastal flood management and nature conservation requirements. In conclusion, a targeted salt marsh management needs to consider the initial conditions and the development aims of the specific site integrated in a conceptual framework. Salt marshes have the potential to adapt to sea-level rise, thereby contributing to the long-term protection of coastal areas.

Phytoplankton under the ice of seasonally ice-covered lakes is a key indicator species for maintaining the health of lake ecosystems. However, there is a lack of a unified definition of cold lakes internationally. In addition, there are few studies on the distribution, driving mechanism and simulation prediction of phytoplankton under the ice, which have limited the development of winter limnology and the prevention and control of spring algal blooms. The average temperature of the coldest month, the duration of the ice period and the average annual water temperature were the main indicators for defining cold lakes based on the literatures review. The cross-action of subglacial hydrodynamics and biogeochemistry during the ice period and freeze-thaw period is the key to promoting the phytoplankton growth. The migration and transformation of nutrients and the formation of hypoxic zones of subglacial were driven by physical factors such as available light and water temperature. Cyanobacteria got advantages in the ice period and above the water column through their own gas vesicles and strong adaptation to low temperature and low oxygen. Diatoms are able to multiply rapidly with the increasing of available light and the water temperature in spring. However, the migration and transformation of nutrients induced by physical factors during the freezing-freezing-thawing process, the role of microorganisms in biogeochemical reactions, and the extent and direction of the combined effects of multiple environmental factors on phytoplankton functional groups are still unclear. At present, lake algal blooms have gradually expanded to higher latitudes under the climate change. How to accurately predict the development and response mechanism of algal blooms in cold lakes under the climate change has become a key direction in the development of winter limnology. This review explains the unique physical and chemical processes of phytoplankton growth competition in cold lakes from the perspectives of bibliometrics, mechanism analysis, method construction and future prospects. These findings would provide new insights into the field of winter limnology and provide theoretical support for the future management of spring algal blooms in cold lakes.

This review stresses the need for geoscience and mining engineering students to be educated during their undergraduate studies in social and sustainability issues so they would have the skills and knowledge in their work after graduation, as professionals, to engage Indigenous People for mutual benefit. Large - scale mining development often takes place on Indigenous land and these educated mining professionals in their contact with these vulnerable communities must act in a responsible way. This includes the important mining policy issues and standards of corporate social responsibility (CSR), social license to operate and free, prior and informed consent from the Indigenous People before mining. For example, these policy standards issues would have been important to consider in Indonesia where the Indigenous Muluy Dayak community in East Kalimantan tried to resist large-scale mining operations by depicting their small-scale mining as part of their Indigenous customs and identity and in Australia where there was the recent destruction of an Aboriginal sacred site during large scale mining operations.

Interpore hydrates are the main occurrence forms of marine gas hydrates. Pore characteristics are a vital factor affecting the thermodynamic properties of hydrates and their distribution in sediments. Currently, the characterization of the pore system for hydrate-bearing reservoirs are little reported. Therefore this paper focus on the Krishna-Godavari Basin, via varies methods to characterize the hydrate-bearing sediments in the region. The results showed that X-ray Diffraction(XRD) combined with Scanning Electron Microscope (SEM)and Cast Thin Section (CTS) can better characterize the mineral composition in the reservoir, High Pressure Mercury Injection (HPMI) focused on the contribution of pore size to permeability, Constant Rate Mercury Injection(CRMI) had the advantage of distinguishing between pore space and pore throat, and Nuclear Magnetic Resonance Cryoporometry (NMRC) technique can not only obtain the pore size distribution of nanopores with a characterization range greater than Nitrogen Gas Adsorption (N2GA), but also quantitatively describe the trend of fluids in the pore system with temperature. As for pore system, Samples 58 and 68 all developed nanopores, the mineral distribution was relatively scattered, and they were rich in paleontological shells such as foraminifera, among which Sample 68 had more pyrite content, and abundant pyrite framboid was observed, which made the intergranular pore develop and provide more nanopores. Sample 58 has a high concentration of pore and throat, high pore connectivity, low pore curvature, and pores with a diameter of 10μm contributing to the main permeability, with an average pore radius of 2.495μm, whereas Sample 68 has poor pore connectivity, high curvature, and pores with a diameter of 1μm contributing to the main permeability, with an average pore diameter of 60 nm, which explains the obvious difference in permeability between the two samples.

Background- Fertilizers are essential to enhancing food security by enhancing crop growth. The selection of chemical fertilizers over organic fertilizers brings environmental consequences. The government is trying to achieve food security and promote organic fertilizers over chemical fertilizers by implementing various programs. Aim- The study is carried out to understand the effect of government policies on farmers' chemical fertilizer consumption patterns. Design- The data of fifteen years of chemical fertilizer consumption was divided into three sub-groups. Statistical analysis was done to understand the trend of chemical fertilizer consumption of the farmers. Results- The analysis of data clearly shows the steadily increasing pattern of chemical fertilizer consumption. Conclusions- The study clearly shows there is no effect of sustainable agriculture policies framed by the government on the consumption of chemical fertilizers by farmers. Across the study period, farmers were inclined to use chemical fertilizers, related to a lack of awareness of the principles of appropriate fertilizer management that can limit environmental damage.

The isotopic and nuclear techniques discussed, namely: Fallout Radionuclide, Fingerprint, and Isotope Hydrology, are linked to the evaluation of soil and water degradation processes. A traditional literature review was conducted to gain the most comprehensive understanding of both the current state of the art and the subject matter, with the aim of proposing a hypothesis that integrates the synergistic convergence of these techniques in order to offer results that are more reliable. A case study is presented as a synthesis of the preceding discussion.

The rapid urbanization process in recent decades has altered the carbon cycle and exacerbated the impact of climate change, prompting many cities to develop tree planting and green area preservation as mitigation and adaptation measures. While numerous studies have estimated the carbon stocks of urban trees in temperate and subtropical cities, data from tropical regions, including tropical botanic gardens, are scarce. This study aimed to quantify the aboveground biomass and carbon (AGB and AGC, respectively) stocks in trees at the Rio de Janeiro Botanical Garden arboretum, Rio de Janeiro, Brazil. Our survey included 6793 stems with a diameter at breast height (DBH) ≥ 10 cm. The total AGB was 8,047.24 Mg, representing 4,023.62 Mg of AGC. The AGB density was 207.4 Mg.ha-1 (AGC = 103.7 Mg.ha-1), which is slightly lower than the density stored in Brazil's main forest complexes: the Atlantic and Amazon forests, but much higher than in many cities worldwide. Our results suggest that, in addition to their global importance for plant conservation, tropical botanic gardens could function as significant carbon sinks within the urban matrix.

Facing global warming consequences is a major issue of present times. For what concerns climate, projections say that heavy rainfalls are going to increase with high probability together with temperature rise, thus also the hazard related to rainfall induced shallow landslides will likely increase in density over susceptible territories. Different modeling approaches exist and any of them is forced to make simplifications in order to reproduce landslide occurrences over space and time. Process based models can help in quantifying the consequences of heavy rainfall on the different involved processes. In this paper, a narrative review about physically-based deterministic distributed models (PBDDMs) is presented. Models were selected based on: the adoption of the infinite slope scheme (ISS), the use of a deterministic approach (i.e., input and output are treated as absolute values), the inclusion of new approaches in modeling slope stability through the ISS. Models are presented in chronological order with the aim of drawing a timeline of the evolution of PBDDMs and to give researchers and practitioners a basic knowledge on how much has been already done. Results indicate that including vegetation effects on slope stability has raised in importance over time but that there is still the need of finding an efficient way to include them, and that in the last years the literature production seems to be more focused on probabilistic approaches.

Cadmium (Cd) contaminated soil is a serious environmental problem due to its effect on crop production, soil microbial community, and risk to human health. The commercial amendments are widely used in the immobilization of heavy metal-contaminated soil because of their cost-effectiveness, eco-friendliness, and community acceptance. This study is conducted to assess the effect of sole commercial amendments including bentonite (B), talc (T), activated carbon (AC), cornstarch (CS), and their combination on exchangeable Cd content in soil, Cd uptake by the plant, and soil microbial community. The results indicated that CS and its composites (T+CS and B+CS) showed the highest effect on reducing Cd mobility in soil (up to 10% in CS), decreasing the Cd uptake by lettuce (up to 78% in T+CS), and increasing the microbial community in soil compared to the control. Furthermore, results from Biolog Ecoplate and realtime-Polymerase chain reaction indicated that the mixture amendments (B+CS and T+CS) showed the highest effect on the microbial community by increasing soil microbial population maximum of 3.81-fold difference (in B+CS) compared to the control. The results indicated that applying composite amendments provided an efficient option for immobilizing Cd in soil, reducing the Cd uptake by plants, and increasing microbial community.

Extreme weather events, such as heat waves and heavy precipitation, are becoming increasingly frequent due to climate change, necessitating the development of effective early warning systems (EWS) to mitigate their impacts. This study introduces an advanced EWS designed specifically for Italy, which integrates the FourCastNet global forecasting model with Elevation-integrated TEmperature and Precipitation SRGAN downscaling (E-TEPS) to enhance the spatial resolution and accuracy of climate predictions. Building on previous work that demonstrated E-TEPS's effectiveness in downscaling temperature and total precipitation variables, this research applies the integrated system to two severe weather events in Central Italy: the Emilia-Romagna floods of 2023 and the Marche floods of 2022. The system's performance was evaluated using key metrics, including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Pearson Correlation, by comparing downscaled outputs from FourCastNet and ERA5 datasets against high-resolution ground truth data from the Euro-Mediterranean Center on Climate Change (CMCC) dataset. The results indicate that the integrated system offers improved predictive accuracy, particularly in capturing critical climate variables, with the entire EWS delivering high-resolution forecasts and final outputs in under one minute. Although potential limitations were identified due to biases in the underlying datasets, which could affect forecast reliability in regions with complex topography or extreme weather conditions, this research highlights the potential of combining machine learning models with downscaling techniques to enhance EWS precision, providing valuable insights for future climate forecasting and disaster preparedness strategies.

This ambitious research project seeks to revolutionize sustainable glucose production by harnessing solar energy for the conversion of atmospheric gases. The process involves water collection, electrolysis for hydrogen and oxygen production, PDMS membrane-based CO2 collection, CO2 splitting, formaldehyde generation, and the synthesis of glucose/sucrose. Key innovations include the strategic application of PDMS membranes with varying pore sizes and non-reactive chemical layers to facilitate selective permeability for specific gases. Our goal is to create a cost-effective, eco-friendly glucose production method, paving the way for renewable and sustainable energy solutions.

New data obtained from core samples of two boreholes in Alba Guyot in the Magellan Seamount Trail (MST), Western Pacific, including 40Ar/39Ar age of basanite, mineralogy of basanite, tuff, tuffite, mantle-derived inclusions in basanite and tuff (lherzolite xenolith and Ol, Cpx, Opx xenocrysts), and calcareous nannofossils biostratigraphy, have implications for the guyot history. Volcanics in the upper part of the Alba Guyot main edifice and its Oma Vlinder satellite, at sea depths between 3600 and 2200 m, were deposited during the Cretaceous 112 to 86 Ma interval. In the following ~60 myr, the Alba Guyot became partly submerged, and denuded with the formation of a flat summit platform while the respective fragment of the Pacific Plate was moving to the Northern Hemisphere. Volcanic activity in the northeastern part of the guyot summit platform rejuvenated in the Miocene (24–15 Ma) and produced onshore basanitic volcanoes and layers of tuff in subaerial and tuffite in shallow-water near-shore conditions. In Middle-Late Miocene (10–6 Мa), after the guyot had submerged, carbonates containing calcareous nannofossils were deposited on the porous surfaces of tuff and tuffite. Precipitation of the Fe-Mn crust (Unit III) recommenced during the Pliocene-Pleistocene (< 1.8 Mа) when the guyot summit reached favorable sea depths. The location of the MST guyots in the northwestern segment of the Pacific Plate near the Mariana Trench, along with the Miocene age and alkali-basaltic signatures of basanite, provide evidence for petit-spot volcanism on the Alba Guyot. This inference agrees with the geochemistry of Cenozoic petit-spot basaltic rocks from the Pacific and Miocene basanite on the Alba Guyot. The numerous volcanic cones reaching up to 750 m high and 5.1 km in base diameter, which were discovered on the Alba summit platform, provide the first evidence of voluminous Miocene petit-spot basanitic volcanism upon the Cretaceous guyots and seamounts of the Pacific.

Sustainable water resource management in Bangladesh's Gumti River Basin faces challenges from climate change, urbanization, and population growth. This study aimed to calibrate and validate the HEC-HMS model for the Gumti River to enhance flood prediction and water resource planning. The model was set up using precipitation, temperature, and discharge data from 2019-2021, with SRTM elevation data for catchment delineation. Manual calibration was performed for 2019-2020, followed by validation for 2021, using parameters such as Muskingum routing and SCS Curve Number. Model performance was evaluated using R², Nash-Sutcliffe efficiency (NSE), RSR, and PBIAS metrics. Results showed satisfactory to good performance, with R² values of 0.64 and 0.68 for calibration and validation, respectively. NSE values were within the satisfactory range, while PBIAS indicated very good performance with slight underestimation. The study concludes that the calibrated HEC-HMS model provides a reliable tool for simulating the Gumti River's hydrology, though there's room for improvement. Integration with flood frequency analysis, water quality monitoring, and climate change projections is recommended for comprehensive water resource management, alongside the implementation of Sustainable Water Resource Management principles and community engagement strategies.

To explore the coupling mechanism between urban-rural transformation (URT) and the ecological environment in counties forms the basis for achieving high-quality and sustainable county development. Despite the richness of research on the relationship between urban and rural development and the ecological environment, the county level remains the basic unit of rural revitalization in China, and further research on the coupling mechanism between URT and the ecological environment at this level is needed. Therefore, the study developed an evaluation system for URT, incorporated NDVI data indicators, and employed the coupling coordination degree (CCD) model along with GIS tools to investigate the spatio-temporal pattern of URT and NDVI evolution, and the CCD in each administrative village within Lingbao City. Additionally, a geoDetector model was employed to analyze the influencing factors affecting the CCD of URT and NDVI. Finally, the study explores the coupling mechanism and optimization path. The result shows that: (1) During the study period, the URT level in administrative villages within the study area markedly improved, while NDVI exhibited an increasing-then-decreasing trend; (2) The CCD between URT and NDVI in the northern and central regions of the study area is higher than that in the southern region, with an overall low level; (3) The spatial heterogeneity of CCD is significant, largely influenced by socio-economy, natural environment, policy funds, and geographical location, where the elements comprising CCD mutually influence each other; (4) Drawing upon the coupling and coordination dynamics between URT and the ecological environment within Lingbao City, this research categorizes it into seven types with distinct optimization paths. This study provides a valuable reference for guiding the high-quality and sustainable development strategies for mountainous and hilly counties within the Yellow River basin.