A significant number and range of challenges besetting sustainability can be traced to the actions and interactions of multiple autonomous agents (people mostly) and the entities they create (e.g., institutions, policies, social network) in the corresponding social-environmental systems (SES). To address these challenges, we need to understand decisions made and actions taken by agents, the outcomes of their actions, including the feedbacks on the corresponding agents and environment. The science of Agent-based Complex Systems—ACS science—has a significant potential to handle such challenges. The advantages of ACS science for sustainability are addressed by way of identifying the key elements and challenges in sustainability science, the generic features of ACS, and the key advances and challenges in modeling ACS. Artificial intelligence and data science promise to improve understanding of agents’ behaviors, detect SES structures, and formulate SES mechanisms.

Mining activities often generate important amounts of extractive waste, and as a consequence, environmental impacts that affects all factors to a greater or lesser extent. Depending on a variety of variables, the impact can be permanent or temporary, reversible or irreversible, negative or positive. This study conducted research on the status of closure and remediation processes of mining areas in Romania, specifically in the counties of Maramureș, Suceava, Harghita, Alba, Hunedoara, and Caraș-Severin. Furthermore, based on the type and level of pollution, the degree of application of remediation techniques for water and soil pollution in the investigated mining areas was studied. From the analysed information, it is evident that although the closure and remediation process started in Romania over 20 years ago, unfortunately, to this day, the technical projects, technical assistance, and execution of closure and remediation works have not yet completely solved the complex environmental issues in the mining sector. Most of the tailing ponds and waste piles of former mines continue to pose permanent specific risk to the environment and the population. This study concludes that the mining sector in Romania, although it has the necessary techniques and technologies for the ecological rehabilitation of degraded lands related to the Extractive Waste Facilities and the elimination of negative impacts on the environment and public health, has not yet been able to fully concretize its remediation efforts.

Hundreds of thousands of kilometers of communication and power (umbilical) cables and flowlines lie undersea worldwide. Most of these offshore cables and flowlines have reached or will soon be nearing the end of their service life, necessitating the need for a viable recycling approach to recover some valuable material, e.g., copper. However, separation into constituent materials has proven very challenging due to the highly robust design of the composite cables (and flowlines) to withstand service conditions and the tough external plastic sheaths that protect against seawater corrosion. Here, we summarize the findings of the cryogenic comminution of subsea cables and flowlines for an effective separation and recovery of component materials. Heat transfer analyses of complex multilayer flowlines and umbilicals were conducted to evaluate the time required for these structures to reach their respective critical brittle-transition temperatures. Subsequently, the time was used as a guide to crush the flowline and umbilical cables under cryogenic conditions. The results show that the flowlines and umbilical cables will reach the brittle-transition temperature after approximately 1000s (i.e., 17 min) of submergence in liquid nitrogen (LN). Comminution of the materials at temperatures near the brittle-transition temperature was proven relatively efficient compared to room-temperature processing. The present evaluation of heat transfer and lab-scale crushing will afford accurate process modelling and design of a pilot cryogenic comminution of decommissioned flowlines in an LN-doped atmosphere.

In a 1.5°C warmer world, the Northeastern (NE) South America’s ecosystems will experience more severe droughts, associated with decreasing rainfall. The severity of flash drought events based on vegetation and surface soil moisture has not been identified over the Caatinga ecosys-tem. This study aimed to characterize the impact of flash drought events on vegetation response via soil moisture over NE South America during the first two decades of the 2000s. Three drought indices were used to characterize flash droughts: the Standardized Difference Vegetation Index (SDVI) derived from Meteosat Second Generation (MSG), the Standardized Precipitation Index (SPI) from ground-data, and the Surface Soil Moisture (SSM) product-based Soil Moisture and Ocean Salinity (SMOS). Results revealed dramatic impacts of flash drought events on vegetation dynamics that caused abrupt changes in the regional vegetation phenology. The regional patterns of flash drought events in 2012 over NE South America were identified and had a severe impact on its Caatinga-like vegetation-dependent moisture response. In 2012, anomalously long dry spells with negative rainfall anomalies in the non-rainy season and persistent on vege-tation greenness and rapidly decreased soil moisture were prominent, thus identifying NE South America to the impacts of flash drought events. Additionally, the results from the trends analysis of radiance fluxes estimated from the MSG satellites over 18 years revealed that an overall drying trend in the NE South America semiarid ecosystem during the last two decades. Here, flash drought events were identified as the conse-quent rainfall deficiency at SPI-3< −1 for a period of five consecutive weeks or more, which the soil moisture content dropping from the 40th percentile to below the 20th percentile, with the NDVI lower than 0.30 unit. These results could be useful to guide flash-droughts early warning systems in NE South America.

Biomass storage is an essential requirement in the supply chain of bio-refineries and power plants. This research aims to evaluate the influence of long-term outdoor storage (1 year) of baled rockrose (Cistus laurifolius L.) shrub biomass on biofuel´s quality, pre-treatment processes and on combustion emissions in an industrial boiler. The raw material was obtained from different rockrose shrublands in North-center Spain. 233 tWM (tones of wet matter) of biomass were used to produce biofuels (30 mm milled biomass and Ø 8 mm pellets) in the pre-treatment pilot plants at CEDER-CIEMAT. The combustion tests were conducted in an industrial moving grate boiler with a thermal power of 50 MWth, in a 17 MWe power plant. Outdoor storage improved some quality biofuels parameters, mainly the reduction in ash content, what allowed to classify 30 mm milled material as class I1 (ISO 17225-9:2022) and pellets as class I3 (ISO 17225-2-2021). No significant differences were observed in the total specific mass flow and energy consumptions in the pre-treatment processes. The combustion tests had similar results, being the emissions below the limits established in the Directive (EU) 2015/2193. The results obtained indicated that 1-year outdoor store of rockrose-baled biomass under Mediterranean conditions was feasible for its subsequent use as biofuel.

The development of mineral resources in China has gradually entered the stage of deep mining. Rock burst, collapse and other ground pressure disasters caused by deep high stress have become major hidden dangers restricting mine safety production. Microseismic monitoring technology is an important means of ground pressure risk prediction. In this paper, the wavelet coefficient threshold denoising method in time-frequency domain, STA/LTA method, AIC method, Skew and Kurtosis method are studied, and the automatic P-phase onset time picking model based on noise reduction and multiple detection indexes is established. Through the effect analysis of microseismic signals collected by microseismic monitoring system of coral Tungsten Mine in Guangxi, automatic P-phase onset time picking is realized. the reliability of the P-phase onset time picking method proposed in this paper based on noise reduction and multiple detection indexes is verified. The picking accuracy can still be guaranteed under the severe signal interference of background noise, power frequency interference and manual activity underground mine, Which is of great significance to the data processing and analysis of microseismic monitoring.

Cobalt (Co) is a transition metal and is classified as a beneficial metal for plants, but its benefits for plants remain obscure. Cobalt has been reported to negatively affect plant physiochemical processes both at higher (toxic) and lower (deficient) applied levels. High concentrations of cobalt in plant organs cause irreversible changes to the plant cells, mainly via enhanced production of reactive radicals. Moreover, Co and its compound play an essential role in humans as they are the central atoms of cobalamin, a co-enzyme precursor whose absence causes anemia. Hence, the optimum Co supply to plants is critical for customary plant metabolic workings. Henceforth, monitoring Co behavior in the soil-plant-human system is highly imperative. This review highlighted the latest literature on (i) Co in soil and plants; (ii) its mobility and phyto-availability in soil; (iii) phytouptake and translocation towards shoot tissues; (iv) toxic and deficient effects of Co on plants; (v) plant detoxification mechanisms under increased Co levels inside plants; and (v) its role in the human body. For this purpose, 1026 plant observations from literature data were analyzed related to Co biogeochemical behavior in the soil-plant system. The data analysis revealed an overall increase in 567 observations and a decrease in 381 observations. However, these general trends in plant responses vary significantly for different types of plant species and physiological attributes. Overall, the current review delineates an updated and critical representation of the biogeochemical behavior of Co in the soil-plant-human system, supported by up-to-date 9 main tables, 14 supporting tables, and 3 figures. The authors believe that the literature presented here can be of great interest to scientists, researchers, policymakers, and graduate-level students.

Solar geoengineering (SG) solutions have many advantages compared to the difficulty of carbon removal (CR): SG produces fast results, is shown here to have much higher efficiency than CR, is not related to fossil fuel legislation, and is something we all can participate in brightening the Earth with cool roofs, and roads. SG requirements detailed previously to mitigate global warming (GW) have been concerning primarily because of overwhelming goals and climate circulation issues. In this paper, the advantages of annual solar geoengineering (ASG) to mitigate yearly global warming increases are explored and detailed as it provides higher feasibility in geoengineering applications. ASG area modification requirements found here are generally 50 to possibly higher than 150 times less compared to the challenge of full SG GW mitigation reducing circulation concerns. Results indicate that there are mixed technologies that can help meet annual mitigation Earth brightening goals. As well, results show much higher feasibility for L1 space shading compared to prior literature estimates for full GW mitigation. However, stratosphere injections appear challenging in the annual approach. Because ASG earth brightening area requirements are much smaller than those required for full mitigation, we have concerns that worldwide negative SG would interfere with making positive advances for several reasons. Negative SG currently dominates yearly practices with the application of dark asphalt roads and roofs. This issue is discussed.

Abstract: Like other plants, every PV power plant will one day reach the end of its service life. Calculations show that 20,400 tons of PV waste will be generated worldwide by 2030 and 60.2 million tons by 2050, not including the mass of the support structure. Such large amounts of waste pose a potential threat to the environment and people if not properly managed. The paper analysed the options for dealing with PV waste, namely reuse, recycling and landfilling. For recycling as the best option in terms of environmental protection and circular economy, an overview of recycling technologies and the percentage of achievable recycling for the materials contained in each PV system component is given. In addition, the current situation of legislation and recycling of PV modules in Europe was examined with special reference to the Balkan countries. There are a small number of factories for recycling PV modules in Europe, but none in the Balkan countries. The main reason for this is the small amount of PV waste in these countries and consequently the economic unprofitability. For this reason, PV modules (after dismantling the aluminum frame and cables) are mostly disposed of as non-hazardous waste in landfills in these countries. Finally, the main barriers to faster implementation of PV module reuse and recycling are listed, along with guidelines for their removal. The cost of recycling Si modules is about ten times higher than the cost of disposal. To change this ratio in favor of recycling, cheaper recycling methods need to be developed and taxes on landfill disposal need to be increased.

Temporal downscaling of gridded geophysical data is essential for improving climate models, weather forecasting, and environmental assessments. However, existing methods often could not accurately capture multi-scale temporal features, affecting their accuracy and reliability. To address this issue, we introduce an Enhanced Residual U-Net architecture for temporal downscaling. The architecture, which incorporates residual blocks, allows for deeper network structures without the risk of overfitting or vanishing gradients, thus capturing more complex temporal dependencies. The U-Net design inherently could capture multi-scale features, making it ideal for simulating various temporal dynamics. Moreover, we implement a flow regularization technique with advection loss to ensure that the model adheres to physical laws governing geophysical fields. Our experimental results across various variables within the ERA5 dataset demonstrate an improvement in downscaling accuracy, outperforming other methods.

Influenced by geological, climatic, and natural weathering factors, the Great Wall heritage is sus-ceptible to deformations, posing significant challenges to the comprehensive preservation of the Great Wall sites. To investigate techniques for monitoring deformations in extensive linear cultural heritage sites, such as the Great Wall, this study utilizes the SBAS-InSAR technique for deformation monitoring and analysis. A dataset comprising 161 Sentinel-1A images spanning from March 2017 to January 2022 was chosen for SBAS-InSAR processing, yielding a deformation velocity field. To verify result credibility, a typical mountainous segment spanning approximately 896.53 km within the Great Wall landscape corridor underwent analysis. The findings suggest that around 75.8% of the landscape corridor along the Shanxi section of the Ming Great Wall maintain relative stability, displaying deformation rates varying from -10 to 10 mm/year. The remaining 24.2% of the land-scape corridor experiences notable deformations, including a maximum subsidence rate of 33.1 mm/year and a maximum subsidence of 148.6 mm. This study illustrates the potential utility of the SBAS-InSAR technique for monitoring and evaluating surface deformations in extensive linear cultural heritage sites.

Using a wide range of organic substrates in the methane fermentation process enables efficient biogas production. Nonetheless, in many cases, the efficiency of electricity generation in biogas plant cogeneration systems is much lower than expected, close to the calorific value of the applied feedstock. This paper analyses energy conversion efficiency in a 1 MWel agricultural biogas plant fed with corn silage or vegetable waste and pig slurry as a feedstock dilution agent, depending on the season and availability. Biomass conversion studies were carried out for 12 months, during which substrate samples were taken once a month. The total primary energy in substrates was estimated in laboratory conditions by measuring the heat of combustion in a ballistic bomb calorimeter (17,760 MWh·year-1), and in the case of pig slurry, biochemical methane potential (BMP, (201.88±3.21 m3·Mg VS-1). Further, the substrates were analysed in terms of their chemical composition — from protein, sugar and fat content to mineral matter determination, among other things. The results obtained during the study were averaged. Based on such things as the amount of biogas produced at the plant, the amount of chemical (secondary) energy contained in methane as a product of biomass conversion (10,633 MWh·year-1) was calculated. Considering the results obtained from the analyses, as well as the calculated values of the relevant parameters, biomass conversion efficiency was determined as a ratio of chemical energy in methane to (primary) energy in substrates, which was 59.87%, as well as electricity production efficiency, as a ratio of electricity produced (4,913 MWh·year-1) to primary energy, with a 35% cogeneration system efficiency. Full energy conversion efficiency, related to electricity production, reached a low value of 27.66%. This article provides an insightful, unique analysis of energy conversion in an active biogas plant as an open thermodynamic system.

Unmanned aerial vehicles (UAV) have emerged as a solution to day to day survey tasks, allowing users to visualize phenomena in real-time. This paper explores the capabilities of UAV or drones in the collection of accurate, geo-tagged data quickly, including photogrammetry software processes to deliver standardized data output. In order to explore the capabilities of UAV, Gatu Township in Centenary, Muzabani District of Zimbabwe was chosen from the national mapping topographic series. This study demonstrates the efficiency of data collection using drones, generate 2D orthomosaics in real time, so that analysts can easily visualize land cover and identify any changes, map and model large areas to produce data for 2D and 3D models. The recent development of innovative optical image processing has further lowered the costs high resolution topographic surveys.

During routine bridge maintenance, edge detection allows the partial condition of the bridge to be viewed. However, many edge detection methods often have unsatisfactory performances when dealing with images with complex backgrounds. Moreover, the processing often involves the manual selection of thresholds, which can result in repeated testing and comparisons. To address these problems in this paper, the wavelet transform modulus maxima method is used to detect the target image, and then the threshold value of the image can be determined automatically according to the OTSU method to remove the pseudo-edges. Thus, the real image edges can be detected. The results show that the information entropy and SSIM of the detection results are the highest when compared with the commonly used Canny and Laplace algorithms, which means that the detection quality is optimal. To more fully illustrate the advantages of the algorithms, images with more complex backgrounds were detected and the processing results of the algorithms in this paper are still optimal. In addition, the automatic selection of thresholds saves the operator’s effort and improves the detection efficiency. Thanks to the combined use of the above two methods, detection quality and efficiency are significantly improved, which has a good application in engineering practice.

As the largest accretionary orogen in the world, the Central Asian Orogenic Belt (CAOB) has continuous juvenile crustal growth in the Phanerozoic. The northern margin of the North China Craton(NCC) and its adjacent area is the eastern segment of the CAOB, and is a key area to study the geological evolution of Paleo-Asian Ocean (PAO). In the Permian, the west of the northern margin of NCC belongs to a post-collision extensional environment, and the east belongs to a subduction stage. But, As a connecting area, the Permian evolution of PAO in the middle of northern margin of NCC has not been systematically studied. In order to fill the blank and understand the temporal and spatial continuous evolution process of PAO, this paper focused on the Permian granitic rocks in the Chifeng area, zircon U-Pb dating and the geochemical analysis of the whole rock main and trace elements were conducted in order to build a granite chronological framework, discuss the genesis and tectonic background of the granite rocks as well as the magma-tectonic evolution history in the Chifeng area. Zircon U-Pb dating results of 8 samples are 269±1 Ma, 268±3 Ma, 260±4 Ma, 260±1 Ma, 260±1 Ma, 255±2 Ma, 254±2 Ma, 256±1Ma, which showed that the Permian granitic rocks had undergone three stages of emplacement: (1) The monzogranite and syenite (294-284 Ma); (2) The monzogranite (269-260Ma) and (3) The monzogranite and syenite (256-254Ma). The Middle Permian magmatism (269-260Ma) was represented by the monzogranite assemblages with different grain sizes. The geochemical characteristics showed that they were high-potassium calc-alkaline-potassium dossonite series of granites formed in compressional environment, indicating there was a collision between the Xing’an-Mongolian Orogenic Belt (XMOB) and the North China Craton (NCC). During the Late Permian-Early Triassic (256-248Ma), the granites in the Chifeng area are dominated by the A-type and I-type granites of high-potassium calc-alkaline series formed under an extensional environments, which constituted typical "bimodal" rock assemblage combined with the coeval basic rocks, suggesting the study area was in an extensional environment where the subducting slab is fragmented during the collision between the XMOB and the NCC. According to emplacement time and occurrence location, the plutons are interpreted to have been generated by the subduction-collision of the Paleo-Asian oceanic crust beneath the NCC. This study provides strong evidence for Permian tectonic evolution and the characterization of the eventual closure of the Paleo-Asian Ocean in the Chifeng City at the northern margin of the NCC.

Due to the expansion of applications of rare earth elements (REE) in various technological pro-cesses, increasing amounts of these metals pollute the environment, including the marine one. Very little is known about the bioaccumulation and toxicity of REE in marine organisms. In the present work, we assessed the contents of these metals, including yttrium and scandium, in rhizomes and leaves of the widespread seagrass Zostera noltei and in the nearby sediments from the Black Sea coast. The total REE content in the sediments was found to be much higher than in Z. noltei. The order of decrease in the major REE contents in the sediments and the seagrass rhizomes was identical, except for La and Y: La was the most abundant in the sediments and Y in the rhizomes. The contents of all REE in rhizomes of Z. noltei were 1.5–10 times higher than in leaves. The greatest difference in the REE contents was found for the minor heavy elements (Sm–Lu). Translocation coefficients for Sc and the minor elements (excluding Tb) from sediments to rhizomes and from rhizomes to leaves turned out to be pairwise equal, which indicate the similarity of the REE translocation mechanisms. Comparing our results with the literature data, it is possible to conclude that the seagrass Z. noltei does not have an advantage in the REE accu-mulation over marine macroalgae. However, large coastal deposits of this seagrass after storms allow it to consider as a possible resource of REE.

Information on how bacteria in plants and soil, along with extracellular enzymes, affect nutrient cycling in Encephalartos villosus growing in nutrient-poor and acidic scarp forests is lacking. Bacteria in coralloid roots, rhizosphere, and non-rhizosphere soils were isolated to determine the potential role of soil bacterial communities and their associated enzyme activities in nutrient contributions in rhizosphere and non-rhizosphere soils. The role of soil characteristics and associated bacteria on E. villosus nutrition and nitrogen source reliance was investigated. Encephalartos villosus leaves, coralloid roots, rhizosphere, and non-rhizosphere soils were collected at two scarp forests. Leaf nutrition, nitrogen source reliance, soil nutrition and extracellular enzyme activities were assayed. A phylogenetic approach was used to determine the evolutionary relationship between identified bacterial nucleotide sequences. Twenty, twelve and seven different bacterial genera were isolated from rhizosphere, non-rhizosphere, and coralloid roots, respectively. Phosphorus and nitrogen cycling enzyme activities in E. villosus rhizosphere and non-rhizosphere soils were insignificant. More than 70% of the leaf nitrogen was derived from the atmosphere. This study revealed that plant-associated bacteria with plant growth-promoting functions, soil bacteria, and associated extracellular enzymes play a role in E. villosus nutrition and nitrogen source reliance and contribute to E. villosus rhizosphere and non-rhizosphere soil nutrition.

A global existential and interlocking environmental, climate and cooperation/equity polycrisis is being faced, which increasingly impacts and is impacted by water and land systems. As a result, transformations in response are gaining increasing traction. Advances in approaches to visualising and communicating how innovations and changes in landscape features enable shifts, transformations and transitions are more crucial than ever before. Visions help focus actions, collaboration and alignment of multiple actors in working towards a common purpose, whilst also entering people’s consciousness at the deep level of values, transforming beliefs and consequently, thinking and action. They give direction on effort and pull on transformational innovation. The evidence-based ‘Water Visions Visualisation Platform’ presents an innovative and accessible way to illustrate, communicate and support future water visioning and strategizing at the landscape scale based on composite paradigms, scenarios, horizons and concepts. Plausible visions of the future are envisioned, illustrated, narratively described and qualitatively assessed, as well as connected with real-world examples and resources through the interactive Platform. This paper outlines the co-creation methodology, the architecture and the co-development of the Platform, as well as a preliminary evaluation through literature-based criteria and the sharing of the Platform with a number of audiences.

This work presents a new discussion about the vibrational properties of the carbonate ion displayed in several different environments, not only the microparameters introduced by cation substitution and different crystal lattices but also the crystal aggregation, showing how their active Raman modes are affected by these changes by using data obtained with four different laser excitation sources. New Raman spectra excited at 1064 nm are reported for calcite, aragonite, and dolomite groups, also including magnesite, witherite, rhodochrosite, siderite, malachite and azurite. These new data contribute to the discussion and understanding of these materials and their spectra, bringing new observations based on the Raman modes, focusing on the internal symmetrical and asymmetrical stretching and bending modes of the carbonate ion, highlighting the differences observed in the relative intensity and width of the bands. The results indicate some evidence of the influence of the crystal habit and/or the growth of the mineral itself in the Raman spectrum. In addition, the data show the influence of the cation substitution upon the Raman band width and that small cations contribute to less rigid crystalline structures and, consequently, larger Raman bandwidths.

The optical complexity of coastal waters is mostly caused by the water discharged from land carrying optical components (such as dissolved and particulate matter) into coastal bays and estuaries, and increasing the attenuation of light. This paper aims to investigate the links between in-water optical properties in four Swedish bays (from the northern Baltic proper up to the Bothnian bay) and the land use and land cover (LULC) and the hydrology in the respective catchment of each bay. The optical properties were measured in situ over the last two decades by various research and monitoring groups while the LULC in each bay was classified using the Copernicus Land Monitoring Service based on Landsat 8 and Sentinel-3 data. The absorption coefficient of coloured dissolve organic matter at 440 nm, aCDOM (440), and its spectral slope factor, SCDOM, were mostly correlated to natural land cover classes (Wetland, Meadow) acting as sources of CDOM, while Agricultural and Urban classes seem to act as sinks. The Agricultural class was also found to be a sink for suspended particulate organic matter (SPOM) whilst Coniferous and Mixed Forests as well as Meadows acted as a sources. SPOM seems to mostly originate from Natural classes, possibly due to the release of pollen and other organic matter. Overall, the methods applied here allow for a better understanding of effects of land used and land cover on the bio-optical properties, and thus coastal water quality, on a macroscopic scale.

Evidence shows how food system activities from production to consumption underpin food security. However, studies exploring climate impacts on food security in northern Ghana have overly focused on production systems, neglecting post-production activities that loom large in food security. This paper addresses the research need to comprehensively analyze how climate change affects post-production activities and exacerbates food insecurity risks in northern Ghana. The study collects and analyzes data on climate hazards, impacts, and food system vulnerabilities using questionnaires and participatory engagement with farming households in northern Ghana. Results show that climate-induced food insecurity risks in northern Ghana are not just products of persistent climate impacts on food production in the region. Instead, risks are inextricably connected to the vulnerability contexts within which food is harvested, processed, stored, and marketed. Specifically, the results reveal that climate hazard events such as floods, extreme temperatures, and droughts damage stored grain, disrupt food supply to the market, and cause seasonal volatilities in food prices. However, these impacts are not solely externally generated circumstances. The food system is highly vulnerable; most households lack access to threshing and grinding machines, warehouse storage, post-harvest management information, and transportation services. These underlying characteristics of the post-food-production system of northern Ghana, which is ultimately quite remote from climate change, exacerbate household-level food insecurity risks.

Poly-DADMAC (PD) is a commonly used organic polymer in water treatment, known for its effectiveness as a coagulant. However, its presence as a residue in water raises concerns related to membrane fouling and the potential formation of carcinogenic compounds. Therefore, fast and simple quantification is necessary to efficiently control and monitor the optimal dose of poly-DADMAC with minimal negative effects. This study introduces a new colorimetric quantification method for poly-DADMAC, based on complexation with a cationic dye (fast green- FG). The method was examined through varying conditions which included different analytical and commercial poly-DADMAC formulations and concentrations. The experiments confirm its effectiveness in quantifying poly-DADMAC with a detection limit of 3.22 µg L^-1 (0.02 µM based on monomers' molecular weight), which is one order of magnitude lower than regulatory requirements (50 µg L^-1). To validate the method, the effect of pH was examined, and implementation demonstrations were conducted on cyanobacteria and cowshed polluted water samples. This research introduces a fast, cost-effective innovative method to accurately quantify poly-DADMAC, enhancing water treatment strategies for high-quality purification and water reuse

This paper presents an operational approach for detecting floods and establishing flood extent using Sentinel-1 radar imagery with Google Earth Engine. Flooded areas are identified using a change-detection method based on the normalized difference. The HAND algorithm is used to delineate zones for processing. The approach was tested and calibrated at small scale to identify optimal parameters for flood detection. It was then applied to the whole of the island of Madagascar after the cyclone Batsirai in 2022. The proposed method is enabled by the computing power and data availability of Google Earth Engine and Google Colab. The results show satisfactory accuracy in delineating flooded areas. The advantages of this approach are its rapidity, online availability and ability to detect floods over a wide area. The approach relying on Google tools thus offers an effective solution for generating a large-scale synoptic picture to inform hazard management decision-making. However, one of the method’s drawbacks is that it depends to a large extent on frequent radar imagery being available at the time of flood events and on free access to the platform. These drawbacks will need to be taken into account in an operational scenario.

The aim of this paper is to compare the taxonomic composition and species diversity of the macrozoobenthos in Maritsa River (Bulgaria) and Han River (South Korea). Samples were collected at 15 selected sites in each river, including some of their main tributaries in 2020 and 2021. The number of the taxa recorded in Maritsa River was more than twice as great as in Han River: 192 taxa belonging to 19 systematic groups compared to 88 taxa belonging to 18 groups respectively. The order Ephemeroptera had the highest species richness: 31 taxa in the Bulgarian rivers and 26 taxa in the South Korean ones. The macrozoobenthic communities responded and adapted to the various conditions and impacts in the water environment with changes in the species composition and structure. The analysis of the similarity in the taxonomic composition showed low resemblance between all study sites but displayed distinct separations between the rivers and the two years. In general, the species structure of the macrozoobenthic communities in Maritsa River and its studied tributaries was better than in Han River. In both years, high species diversity was recorded at the reference sites in the rivers, characterized by conditions closely resembling natural environments. The species richness and the evenness of macrozoobenthos were very low at sites downstream subjected to considerable anthropogenic pressure. Some of the communities in Han River were almost destroyed completely.

Agriculture uses plastic products for containers, packaging, tunnels, drip irrigation tubing, mulches. Large amounts of plastics are used as mulches on the soil surface for vegetable production (tomato, cucumber, watermelon, strawberry, vine) to reduce the weed competition, increase water and fertilizer use efficiency and enhance crop yield. Portugal uses around 4,500 t/year of plastic to cover approximately 23,000 ha of agricultural land and only a scarce amount is recovered for recycling or secondary uses because of contamination with soil, vegetation, pesticide and fertilizers. Most plastic mulch is composed of polyethylene that degrades slowly and produces a large quantity of residues in soil with negative impact in the environment. In the present study, the effects of long-term cultivation of blueberry with green plastic mulch, at south Portugal, were evaluated for soil chemical and biological changes. High density green plastic mulch did not contaminate the topsoil with di(2-Ethylhexyl) phtalate and heavy metals. In the planting row with mulch a reduction of total nitrogen and organic carbon concentration, cation exchange capacity and microbial activity in topsoil compared with bare soil. Apparently, the presence of film did not affect negatively the presence of nematodes but the Rhabditida (bacterial feeders) increased in the planting row.

Several chemistry-climate models (CCM) underestimate the total column ozone (TCO) over the polar region in the Southern Hemisphere during wintertime. To evaluate potential causes of the problem, we exploit CCM SOCOLv3 to study the TCO over Antarctica sensitivity to the: (1) photo-dissociation rates of ozone for large solar zenith angles; (2) rates of the stratospheric heterogeneous reactions, and (3) intensity of the meridional flux into the polar regions due to sub-grid scale mixing processes in the model. Comparisons of the model results with the satellite-based IASI (Infrared Atmospheric Sounder Interferometer) sensor measurements showed that the most important processes for the improvement of the polar ozone simulation results are photolysis and horizontal mixing. The reasonable tuning of these factors has allowed us to improve the model representation of the ozone annual cycle over the southern polar region. The proposed increase of the horizontal mixing can be recommended for the CCMs with relatively low horizontal resolution.

Modern technologies can satisfy human needs only with the use of large quantities of fertilizers and pesticides that are harmful to the environment. For this reason, it is possible to develop new technologies for sustainable agriculture. The process could be made by using endophytic microorganisms with a (possible) positive effect on plant vitality. Bacterial endophytes have been reported as plant growth promoters in several kinds of plants under normal and stress conditions. In this study, isolates of bacterial endophytes from the roots and leaves of Miscanthus giganteus plants were tested for the presence of plant growth-promoting properties and their ability to inhibit pathogens of fungal origin. Pantoea ananatis and Pseudomonas libanensis were the predominant bacteria in leaves whereas other pseudomonads prevailed in roots. Selected bacterial isolates were able to solubilize inorganic phosphorus, to fix nitrogen, and to produce IAA, ACC deaminase and siderophore. Leaf bacterial isolate Pantoea ananatis 50 OL 2 had high production of siderophores and weak capabilities for phytohormone production. The root bacterial isolate of Pseudomonas libanensis 5 OK 7A showed the best results of phytohormone production. Four fungal cultures - Fusarium sporotrichioides DBM 3229, Sclerotinia sclerotiorum SS-01, Botrytis cinerea and Sphaerodes fimicola were used to test the antifungal activity and these cultures were selected for their representatives of known pathogenic fungi families, especially for crops. All selected roots endophyte isolates significantly inhibited the pathogenic growth of Fusarium sporotrichoides with a mean inhibition diamater (zone ≥ 5 mm). These results demonstrated that the root endophytic Pseudomonas sp. could be used as biofertilizer for crops.

Abstract: In recent years, the concentration of fine particulate matter (PM2.5) in China has decreased significantly, whereas the concentration of surface ozone (O3) has increased. The formation regime of ozone is closely related to the ratio of volatile organic compounds (VOCs) to nitrogen oxides (NOx). To reveal the reasons for this increase in ozone, we determined the sensitivity of ozone generation by determining the regional threshold of the ratio of formaldehyde to nitrogen dioxide (HCHO/NO2) in the satellite troposphere. The different FNR(HCHO/NO2) ratio ranges indicate three formation regimes: VOC-limited, transitional, and NOx-limited. The range of the transitional regime plays a crucial role in identifying the regime of ozone formation. Currently, the key threshold for ozone generation in China remains unclear. Polynomial fitting models were used to determine the threshold range for the transitional regime in the BTH region [2.0,3.1]. The ozone formation regime in the BTH region mainly exhibited a transitional and NOx-limited regime, and the overall concentration changes of the HCHO and NO2 columns in the BTH region showed a fluctuating trend from 2019 to 2022. However, compared to 2019, the ozone precursors and FNR showed varying degrees of decline in 2022. The concentration changes of NO2 were high in winter and low in summer, whereas the trend of HCHO and FNR changes was the opposite to that of NO2, being high in summer and low in winter. The concentrations of HCHO and NO2 in the BTH region showed a trend of urban agglomeration areas>urban expansion areas>non-urban areas in different land types from 2019 to 2022, whereas the FNR showed an opposite trend in urban agglomeration areas<urban expansion areas<non-urban areas.

The escalation of climate change and the increasing frequency of extreme weather events have amplified the importance of precise and timely lightning prediction. This predictive capability is pivotal for the preservation of life, protection of property, and maintenance of crucial infrastructure safety. Recently, the rapid advancement and successful application of data-driven deep learning across diverse sectors, particularly in computer vision and spatio-temporal data analysis, have opened up innovative avenues for enhancing both the accuracy and efficiency of lightning prediction. This article presents a comprehensive review of the broad spectrum of existing lightning prediction methodologies. Starting from traditional numerical forecasting techniques, we traverse the path to the most recent breakthroughs in deep learning research. We encapsulate these diverse methods, shedding light on their progression and summarizing their capabilities, while also predicting their future development trajectories. This exploration is designed to enhance our understanding of these methodologies, allowing us to better utilize their strengths, navigate their limitations, and potentially integrate these techniques to create novel and powerful lightning prediction tools. Through such endeavors, our aim is to bolster our preparedness against the growing unpredictability of our climate and ensure a proactive stance towards lightning prediction.

The aim of this study is to reduce the indicators of the amount of oxidizable pollutants present in polluted water, using magnetite Fe3O4 nanoparticles (MNPs) as adsorbents in combination with a high intensity magnet. The MNPs used as adsorbents were synthesised by co-precipitation method and analyzed by Transmission-Electron-Microscopy (TEM), scanning electron microscopy (SEM), X-ray Diffraction Analysis (XRD), Fourier transform infrared spectroscopy (FTIR), surface area analysis (BET) and Thermo-Gravimetric-Analysis (TGA). The performance on the reduction efficiency of the contaminated water was investigated under different conditions: pH (4-9), adsorbent masses (0.5 g/L - 1.5 g/L), contact times (15-90min), and stirring rates (50-300 rpm). The nanoparticles produced by co-precipitation showed a smaller size than the other techniques (10 nm). The optimum results of the treatment with Magnetite indicate the reduction conditions: contact time of 50 minutes, pH of 8, mass of magnetite of 1 g/l and stirring speed of 200 rpm. A use with a coupling of nanoparticles and an intense magnetic field (1T) generates better treatments up to 85% COD and 86% BOD5.

Deforestation brings vast and detrimental impact on the environment, economy, and social aspects of community. Thus, it is important to assess and analyze deforestation to inform the decision maker that oversees issued policy and development strategies. The present study aims to characterize deforestation in Central Kalimantan between 2006 - 2020. Utilized land cover map issued by Indonesian Ministry of Environment and Forestry, we analyzed the change in natural forest cover using Remote Sensing and Geographical Information System (GIS) to find the rate the trend, location, and land cover replacement of deforestation in Central Kalimantan Province, Indonesia. The research found that during the period Central Kalimantan lost 1.5 million ha of natural forest with the rate of deforestation 117,000 ha/year. In general, the deforestation shown decrease trend and fluctuated during the period. Deforestation majority takes place at secondary swamp and dry forest that are located at south part of the island. Most of deforestation resulted shrubs, plantations, and agriculture land. The finding of this research could be used as a base to determine the target location for rehabilitation strategy and approach to prevent further deforestation.

Using straightforward and cost-effective methods, persimmon leaves were converted into a high-quality powder. This powder was applied as an adsorbent for the removal of Cu(II) and Cd(II) from aqueous solutions. Scanning electron microscopy (SEM) indicated the presence of particles with non-homogeneous sizes and rough texture. Elemental analysis and the EDX technique confirmed the presence of elements such as sulfur, phosphorus, nitrogen, and oxygen. The results of ¹³C nuclear magnetic resonance (¹³C-NMR), obtained through the cross-polarization technique, suggest the presence of groups containing sulfur and oxygen. Infrared spectroscopy (FTIR) indicated the existence of amine and hydroxyl groups. The material was used in solid-phase extraction of Cu(II) and Cd(II) in batch experiments, and its adsorption capacity was evaluated as a function of time, pH, and analyte concentration. Kinetic equilibrium was reached within 5 minutes, and the experimental data were fitted to the pseudo-second-order kinetic model. The optimum pH for adsorption of both metal species was observed to be around 5.0. The adsorption isotherms were adjusted using the modified Langmuir equation, and the maximum amount of metal species extracted from the solution was determined to be 0.213 mmol g^-1 for Cu(II) and 0.215 mmol g^-1 for Cd(II), with high linear correlation coefficients for both metals. The persimmon leaves are typically abundant during the growing season, and since they are seasonal, the Diospyros kaki L.f. tree undergoes the natural process of leaf abscission, ensuring the availability of leaves for application.

The body of knowledge on ocean acidification gives a better understanding of biological sensitivity to low pH. Key parameters such as life-history strategies or local adaptation were identified as keys to predict species sensitivity and resolve previously some of the unexplained species- and population-specific differences. Encapsulation has been suggested as one of these keys as it exposed the embryo to low pH conditions, or ontogenetic hypercapnia, leading to physiological adaptation. We tested this hypothesis on the nudibranch Aeolidiella glauca by exposing their egg-strings containing large number of eggs to two different pH (8.1 and 7.3). The fertilized eggs developed 1 egg-cell, over early cleavage up to morula, blastula, gastrula, rhomboid-shaped rotating gastrula, early rotating veliger larvae with developed shell, to free-swimming well developed veliger larvae. Despite a corrosive environment, the exposure to low pH had no significant effect on the developmental rate. The only significant effects were a slightly smaller and narrower shell in larvae raised at low pH as compared to the high pH. Our results showed a remarkable resilient to low pH in a calcifying mollusc and support the idea that ontogenic hypercapnia is leading to low sensitivity to ocean acidification.

The Savu Sea holds significant importance as a conservation area in Indonesia, providing sustenance and livelihoods for local communities. It is situated within the Coral Triangle, a critical hotspot for marine biodiversity worldwide. However, the Savu Sea is currently facing various threats, including overfishing, pollution, and the impacts of climate change. Effective management of this conservation area relies heavily on the active participation of local communities. Therefore, this study aims to address this issue by analyzing how factors within these communities, such as the socio-economic condition of coastal households, environmental awareness, the existence of community-based conservation areas, attitudes towards activities within the conservation area, and participation in multistakeholder institutions, contribute to a positive perception of the benefits provided by the Savu conservation area. To determine the complex causal conditions that influence the outcome of perception, the study employs the Qualitative Comparative Analysis (QCA) method, specifically using crisp set QCA (csQCA). A survey was conducted among 22 coastal villages surrounding the Savu Sea, resulting in the identification of 14 different combinations of pathways that contribute to varying levels of perception regarding conservation. Valuable lessons can be drawn from this study to enhance the design of policies aimed at effectively managing the Savu conservation area.

Estuaries are excellent environments of identifying pollution episodes that have affected river basins, as their sediments are the final destination of some of the pollutants. This paper studies the geochemical evolution of five elements (As, Co, Cu, Pb, Zn) in a core extracted from the middle estuary of the Tinto River (SW Spain). Results are based on facies interpretation, ICP Atomic Emission Spectrometry analysis, the application of a regional background to obtain the geoaccumulation index and dating. Four pollution episodes have been detected at ~5.8 cal. kyr BP (acid mine drainage?), 4.7-4.5 kyr BP (first mining activities), the 1850-1960 interval (intensive mining) and the second half of the 20th century (intensive mining and industrial inputs). All episodes show an increase in one or more of these elements, as well as changes in their geochemical classes deduced from the geoaccumulation index.

In water scarcity regions, using data-driven approaches to predict groundwater level is challenging due to limited data availability. However, these regions have substantial water needs and require cost-effective groundwater utilization strategies. In this study, we use artificial intelligence to predict groundwater levels to provide guidance for drilling shallow boreholes for subsistence irrigation. The Bilate watershed, which is located in southern Ethiopia, was selected as the study area. This is typical of areas in Africa with high demand for water and limited availability of well data. Using a non-time-series database of 75 boreholes, machine learning models including multiple linear regression, multivariate adaptive regression spline, artificial neural networks, random forest regression, and gradient boosting regression (GBR) were constructed to predict the depth to the water table. 20 independent variables were considered in the models. GBR performed the best of the approaches with an average 0.77 R-squared value on testing data. Finally, a map of predicted water levels in the Bilate watershed was created based on the best model with water levels ranging from 1.6 to 245.9 meters. With the limited set of borehole data, the results show a clear signal that can provide guidance for borehole drilling decisions for sustainable irrigation with additional implications for drinking water.

New detailed geological/structural mapping as well as field-based structural analysis were carried out to investigate the deformation pattern of well-preserved high-pressure rocks of the Blueschist Unit exposed on SE Syros (Cyclades, Greece). Our new geological mapping revealed the occurrence of a metasedimentary sequence underlain by a meta-igneous sequence. The contact between these two sequences displays typically interfingering patterns in map-scale due to folding. The earlier ductile deformation phase recognized in the mapped area, is associated with the development of a penetrative foliation, which was formed under eclogite/blueschist facies conditions at peak conditions. The subsequent main deformation phase occurred at blueschist facies conditions synchronous with the early stages of exhumation of the high-pressure rocks. This phase is mainly associated with the formation of map-scale WNW-trending folds and a pervasive axial planar foliation linked with ESE-directed shearing. The main deformation ceased within blueschist facies conditions and exhumation of the rocks to greenschist facies conditions took place under very weak deformation. Greenschist retrogression observed in the southwestern part of the mapped area seems to be controlled by fluids rather than by intense deformation. Our results indicate that the high-pressure rocks of the Blueschist Unit exposed on Syros Island represent a large-scale pod of low deformation under blueschist to greenschist facies conditions, likely occupying the core of an extrusion wedge.

Considering that traditional energy sources such as fossil fuel are about to deplete during the following decades, governments try to turn to renewable energy. It is commonly known that Greece has a natural advantage of abundant solar energy and wind power due to its geographical location and characteristics.The main focus of this study is to examine how wind energy potential across the Aegean Sea and continental Greece can provide a promising field for investments in Greece, considering the economic crisis, current trends and future perspectives.We firstly focus on current legislation framework considering that laws associated with such types of investment in Greece are very complex and rapidly changing. Furthermore, a case study for a hypothetical investment plan concerning a wind park located in an Aegean island will be presented. RetScreen which is a software made by the Canadian government, will be used as a decision support tool for analyzing the potential investment scenario and a financial report will follow with estimation of the overall cost, depreciation, upcoming benefits, and payback period of the investment.Data analysis concludes that wind parks still prove to be an economically viable investment, although incentives considering the guaranteed price per kwh and faster investment times must be provided by the government.

The overexploitation of forest resources in the charcoal production basin of the city of Lubum-bashi (DR Congo) is reducing the resilience of miombo woodlands and threatening the survival of the riparian as well as urban human populations that depend on it. We assessed the socio-economic value and availability of plant-based non-timber forest products NTFPs in the rural area of Lubumbashi through ethnobotanical (100 respondents) and socio-economic (90 respondents) interviews, supplemented with floristic inventories, in two village areas selected on the basis of the level of forest degradation. The results show that 60 woody species, including 46 in the degraded forest (Maksem) and 53 in the intact forest (Mwawa), belonging to 22 families are used as sources of NTFPs in both villages. Among these species, 25 are considered priority species. NTFPs are collected for various purposes, including handcrafting, hut building, and traditional medicine. Moreover, the ethnobotanical lists reveal a similarity of almost 75%, indicating that both local communities surveyed use the same species for collecting plant-based NTFPs, despite differences in the level of degradation of the miombo woodlands in the two corresponding study areas. However, the plant-based NTFPs that are collected from miombo woodlands and traded in the urban markets have significant economic value, which ranges from 0.5 to 14.58 USD per kg depending on the species and uses. NTFPs used for handicraft purposes have a higher economic value than those used for other purposes. However, the sustainability of this activity is threatened due to unsustainable harvesting practices that include stem slashing, root digging, and bark peeling of woody species. Consequently, there is a low availability of plant-based NTFPs, particularly in the village area where forest degradation is more advanced. It is imperative that policies for monitoring and regulation of harvesting, and promoting sustainable management of communities’ plant-based NTFPs priority, be undertaken to maintain their resilience.

Taiwan is highly susceptible to global warming, experiencing a 1.4°C increase in air temperatures from 1911-2005, which is twice the average for the Northern Hemisphere. This has led to higher rates of respiratory and cardiovascular mortality. Accurately predicting maximum temperatures during the summer season is crucial, but numerical weather models become less accurate and more uncertain beyond five days. To improve forecast reliability, statistical post-processing is needed to address systematic errors. In September 2020, NOAA NCEP implemented the Global Ensemble Forecast System version 12 (GEFSv12) to help manage climate risks. This study developed a Hybrid statistical post-processing method that combines Artificial Neural Networks (ANN) and Quantile mapping (QQ) approaches to predict daily maximum temperatures and extremes in Taiwan during the summer season. The Hybrid technique, utilizing deep learning techniques, was applied to the GEFSv12 reforecast data and evaluated against ERA5 reanalysis. The Hybrid technique was the most effective among the three techniques tested. It had the lowest bias, RMSE, and highest correlation coefficient. It successfully reduced the warm bias and overestimation of Tmax extreme days. This led to improved prediction skills for all forecast lead times. Compared to ANN and QQ, the Hybrid method was more effective in predicting summer daily Tmax and its extremes on an extended-range time scale deterministic and ensemble probabilistic forecasts over Taiwan.

Brassicaceae are well known as non-arbuscular mycorrhizal (AM) host plants. This study was aimed to examine effects of two Brassica; cabbage (Brassica oleracea L. cv. cabitata) and mustard (B. juncea Coss.) on three AM species (Acaulospora, Entrophospora and Glomus) and to examine effect of root incorporation into soil on root AM infectivity in maize growing in iron toxicity soil. Experiment 1, cabbage and mustard crop reduced spore density of Acaulospora, but there was no effect on spore density of Entrophospora. While, mustard crop had more effect on Glomus spore density than cabbage crop. Experiment 2, AM spore from two conditions; without and with 6 weeks of root residues (cabbage, mustard and maize) incorporation was examined for its infectivity in maize roots. At D21, without root incorporated, the infectivity of Acaulospora, Entrophospora and Glomus were not different. By contrast, cabbage and mustard root incorporation depressed infec-tivity of Acaulospora but, there was no effect on Entrophospora. Whereas, cabbage root incorporation only depressed infectivity of Glomus. However, AM infectivity was recovered at D42. These results suggested that Brassica root incorporated into soil was the actual effect on the viability of AM spore resulting in reduction of AM infectivity at the early stage.

Anthropogenic disturbances interacting with natural disturbances, ecological and socio-economic factors can provoke forest degradation and modulate ecosystem resilience. In Haiti, protected areas recently created to reduce forest loss, require studies about forest dynamics and land use to assure the development of sustainable management policies. We combine field interview with Landsat satellite images of the Macaya National Park collected between 1985 and 2021 to investigate: 1) how much of the original forest area has been converted into agricultural or logged area since 1985; and 2) how do elevation and slope influence the expansion of human-induced land-use changes. Our results indicate an increase of 11.36% in forest cover and a reduction of 75.34% in agriculture class cover, despite the passage of seven hurricanes in the region. Forest recovery was apparently unrelated to elevation and slope, and likely reflected the implementation of new environmental laws and policies with the creation of the Macaya National Park in 1983. Restoration and protection programs contributed to ensure access to financial resources, technical assistance and new technology, thus promoting a shift into a more resilient forest system. This study brings hope for forest conservation in Haiti by showing that positive results can be achieved through inclusive collaboration.

The investigation of the spatiotemporal propagation characteristics of the "meteorological-agricultural-hydrological" drought system, under diverse climatic conditions, is crucial for the development of a robust drought warning system and the effective implementation of proactive drought prevention and resilience strategies. To achieve this, the current study utilizes the Soil and Water Assessment Tool (SWAT) model to simulate key components of the watershed water cycle, such as evaporation, surface water, soil water, and groundwater. Specifically, the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Soil Moisture Index (SSMI), and the Nonlinear Joint Hydrological Drought Index (NJHDI) are employed to characterize meteorological drought, agricultural drought, and hydrological drought, respectively. By analyzing the correlation between these types of drought, the propagation characteristics of the "meteorological-agricultural-hydrological" drought system are elucidated using the rigorous strongest correlation coefficient method. The Yellow River Basin (YRB) is chosen as the case study for this research. Results showed that (1) The propagation time from meteorological to agricultural drought exhibited distinct seasonal characteristics, with durations of 5-6 months in spring, 2-3 months in summer, 3-5 months in autumn, and 6-8 months in winter. Compared to 1961-1990, the propagation time increased in spring and summer but decreased in autumn and winter during 1991-2010 for most YRB regions. (2) The agricultural to hydrological drought propagation showed no clear seasonal differences but increased over time. Specifically, zone C (arid/semi-arid with moderate temperatures) had shorter propagation time of 1-5 months, while zones B (transitional plateau to mid-latitude) and E (semi-arid/semi-humid temperate continental climate) experienced longer propagation time of 7-12 months. (3) Despite the extended timescales, agricultural-hydrological drought correlation was weaker than meteorological-agricultural linkage. This is because meteorological deficits directly reduce soil moisture, rapidly inducing agricultural drought. However, groundwater sustaining baseflow during agricultural drought delays streamflow deficits, prolonging the agricultural-hydrological propagation time.

Abstract: A fertilisation experiment with aim to determine the effect of different potassium fertiliser rates and their interaction with nitrogen and phosphorus on field rotation productivity, potassium balance, fertiliser utilization and changes in content of potassium in soil was carried out in Lithuania between 1971 and 2020. The multi-factorial scheme with 45-treatment plots, where seven (including zero) rates of nitrogen, phosphorus and potassium fertilisers were studied. The experimental treatments during the study period included winter wheat, spring wheat, spring barley, sugar beet, spring rapeseed, annual and perennial grasses. It was found that potassium fertilisers was the most effective on agricultural crops when used in combination with other major plant nutrients – nitrogen and phosphorus. The balance of potassium (K2O) in soil, when nitrogen and phosphorus fertilisers were applied together, to compensate for potassium removal, when applying low nitrogen (N) 72 kg ha-1 and phosphorus (P2O5) 64 kg ha-1 fertiliser rates, 128 kg ha-1 of potassium fertilisers is required. When using high nitrogen 180 kg ha-1 and phosphorus 160 kg ha-1 fertiliser rates, 160 kg ha-1 of potassium is needed. The highest potassium uptake, reaching 51.6%, was achieved when plants had been fertilised with nitrogen 108 kg ha-1, phosphorus 96 kg ha-1, and potassium 96 kg ha-1. When fertilising with potassium fertilisers alone, the content of plant available K2O content in the soil increased, while fertilisation with nitrogen and phosphorus combined it’s decreased, except in the plots where the plants had been fertilised with potassium fertiliser at rates of 128 kg ha-1 and higher. Due to the influence of fertilizers, the amount of non-exchangeable potassium in the soil also increased, but relatively less compared to the amount of available potassium content.

Spectral calibration consists of the calibration of wavelengths and the measurement of the instrument's spectral response function (SRF). Unlike conventional slits, the absorbed aerosol sensors (AAS) are used as a slit homogenizer, in which the spectral response function (SRF) is not a conventional Gaussian curve. To be more precise, the SRF is the convolution of the slit function of the spectrometer, the line spread function of the optical system, and the detector response function. The SRF of the slit homogenizer is a flat-topped multi-Gaussian function. Considering the convenience of fitting, a super-Gaussian function, which looks like a similar distribution to the flat-topped multi-Gaussian function, is used to fit the measured data in a spectral calibration. According to the results, the SRF’s shapes, due to the Earth port, resemble a Gaussian curve with a flatted top could be concluded, which contains an FWHM of 1.78–1.82 nm for the AAS. The results show that the correlation coefficients are about 0.99, which proves that the fitting function could better characterize the SRF of the instrument.

The extent of single and multi-cropping systems in any region, and potential changes to it, have consequences on food and resource use raising important policy questions. However, addressing these questions is limited by a lack of reliable data on multi-cropping practices at a high spatial resolution, especially in areas with high crop diversity. In this paper, we describe a relatively low-cost and scalable method to identify double cropping at the field-scale using satellite (Landsat) imagery. The process combines machine learning methods with expert labeling. We demonstrate the process by measuring double cropping extent in a portion of Washington State in the Pacific Northwest United States--- a region with significant production of more than 60 distinct types of crops including hay, fruits, vegetables, and grains in irrigated settings. Our results indicate that the current state-of-the-art methods for identifying cropping intensity---that apply rule-based thresholds on vegetation indices---do not work well in regions with high-crop-diversity. Our deep learning model was able to capture the diverse nuances and achieve a high accuracy (99\% overall accuracy and 0.92 Kappa coefficient). Our expert labeling process worked well and has potential as a relatively low-cost, scalable approach for remote sensing applications. The product developed here is valuable to inform several policy questions related to food production and resource use.

Fire is a common natural disturbance in forest ecosystems and plays an important role in subsequent vegetation patterns. Based on the spatial sequence method instead of the time successional sequence method, this study selected burned areas in different locations in the Anning River Basin, which contains typical dry valleys. Quadrat surveys and quantitative classification were used to identify the vegetation classification, distribution pattern, and environmental interpretation during the natural restoration process after forest fire. The results showed that: (1) the vegetation community in the early stage of natural recovery after forest fire disturbance could be divided into seven community types, and Quercus guyavaefolia H. Leveille (Qg) was the dominant species in the community; (2) vegetation samples could be divided into five ecological types, and the classification and distribution pattern of community types in this region changed most obviously with altitude; and (3) detrended correspondence analysis could clearly classify vegetation community types, and detrended canonical correspondence analysis could well reveal the relationships between species and environmental factors. This study provides a scientific basis guiding the restoration of ecosystem structural stability and biodiversity in burned areas.

In recent years, the Chinese government pays more and more attention to agricultural development and ecological protection. While improving the cultivated land green use efficiency(CLGUE) is the key to promote the sustainable development of agriculture. This study aims to study the current situation and influencing factors of agricultural production from the perspective of green utilization efficiency of cultivated land. It takes 39 cities in the upper, middle and lower reaches of the Yangtze River basin in China as an example. The CLGUE values in those 39 cities from 2011 to 2020 were specifically measured, using the Super-SBM model, kernel density estimation and geographic detector method. Their temporal and spatial heterogeneity was described, and the influencing factors were detected at both single and interactive levels. The results showed that: （1）From 2011 to 2020, the green utilization efficiency value of cultivated land in the Yangtze River Basin showed an upward trend on the whole; （2）There is a clear spatial heterogeneity the CLGUE values in the Yangtze River Basin cities, as shown by: downstream region > midstream region > upstream region; (3) Cultivated land resource endowment, socioeconomic development, and agricultural production technology are important factors affecting the variability of CLGUE values. However, there are some differences in the degree and direction of influence of different influencing factors on different sample subgroups.

The powdered sorbents were applied in a batch system under "static" conditions and showed a much higher adsorption capacity than the granular one. These type of sorbents are more suitable for small quantities of water with a high concentration of arsenic. The possibilities of using all the tested methods for arsenic removal have been evaluated, and a scheme of the technological process has been proposed.

The eco-efficiency of cultivated land use (ECLU) is an important indicator for the construction of ecological civilization in China. Exploring the spatiotemporal dynamic evolution of the ECLU is helpful for sustainable use of arable land, ensuring food security and ecological security. However, previous studies have mostly focused on the use of a slacks-based measure (SBM) model for ECLU measurement, ignoring the more accurate epsilon-based measure (EBM) model. Therefore, in this study, firstly, we explored the conceptual framework of ECLU, and then, based on the panel data of the counties in the region around Beijing and Tianjin from 2005 to 2020, we investigated the spatial and temporal evolution of ECLU by using the Super-EBM model, kernel density estimation method, and spatial Markov chain model. Results displayed: (1) From 2005 to 2020, the ECLU in the region around Beijing and Tianjin displayed an increasing state, but the average value was only 0.55. (2) The time evolution of the ECLU has gradually polarized, the internal gap has widened, but it tends to stabilize. (3) The ECLU in the region around Beijing-Tianjin was more inclined to keep it the same and there was a "club convergence" phenomenon, which was meaningfully affected by the background of neighboring areas. In the light of local conditions, the government should reasonably formulate the path to optimize the ECLU, strengthen the linkage with the surrounding cities, and bring into play the positive spillover effect.

In the context of freshwater ecosystems, turbidity and suspended solids play crucial roles, with their levels significantly influenced by anthropogenic activities. This study focuses on assessing and monitoring these parameters in Albufera de Valencia using Sentinel-2 imagery. The primary aim is to establish reliable estimation algorithms that can contribute to effective ecosystem management. The study calibrated and validated algorithms for estimating turbidity and suspended solids. The R783×R705/R490 model proved to have the best performance for estimating turbidity and total solids in the Albufera. However, R783/R490 obtained a higher coefficient of de-termination for the organic part, while the R705 band was selected for the inorganic part. However, to achieve better estimates of turbidity and inorganic matter, more research is needed in the future. The implications of excessive suspended solids are underscored, including the depletion of dissolved oxygen, and reduced primary productivity due to limited light penetration and habitat availability. Collaboration between disciplines such as limnology, optics and water chemistry are crucial to advance water quality estimation models in lakes and lagoons such as Albufera. By integrating expertise and approaches from these diverse fields, new knowledge can be gained and the basis for more effective management and conservation strategies can be laid.

This investigation delves into the profound interplay between the e-commerce environment and the agricultural system, while scrutinizing the intricate human-land coupling dynamics engen-dered by transformations within the agricultural domain. Focusing on the expansion of orchards in Pinghe County, a pivotal epicenter for Chinese sweet pomelo production, this study eluci-dates the reverberations of Rural E-commerce Environment Development on Orchard Expansion through the lens of Tele-coupling. In doing so, it unveils the nuanced tapestry of the human-land coupling associations latent within the evolutionary trajectory of the agricultural system amidst the blossoming information society. The findings underscore a symbiotic relationship between the augmentation of orchard acreage and the burgeoning rural e-commerce landscape, effec-tively propelling the economic prosperity of the agricultural system. Moreover, a tele-coupling phenomenon has emerged, underscoring the intricate web of interconnections binding the mat-uration of the rural e-commerce ecosystem with the proliferation of orchards. The research illu-minates that the transformation of land utilization, imbricated within the agricultural system, manifests as a distinctive form of tele-coupling intricately woven into the fabric of urbanization and information technology advancements. Consequently, adopting a comprehensive theoreti-cal perspective, amalgamating disparate domains across distinct geographic realms, becomes imperative for discerning the intricate nuances of the human-land coupling nexus within these multifaceted, open systems.

The Yellow River Basin (YRB) is a crucial ecological zone and an environmentally vulnerable re-gion in China. Understanding the temporal and spatial trends of terraced-field areas (TRAs) and the factors underlying them in the YRB is essential for improving land use, conserving water re-sources, promoting biodiversity, and preserving cultural heritage. In this study, we employed ma-chine learning on the Google Earth Engine (GEE) platform to obtain spatial distribution images of TRAs from 1990 to 2020 using Landsat 5 (1990－2010) and Landsat 8 (2015－2020) remote sens-ing data. The GeoDa software platform was used for spatial autocorrelation analysis, revealing distinct spatial clustering patterns. Mixed linear and random forest models were constructed to identify the driving force factors behind TRA changes. The research findings reveal that TRAs were primarily concentrated in the upper and middle reaches of the YRB, encompassing provinc-es such as Shaanxi, Shanxi, Qinghai, and Gansu, with areas exceeding 40,000 km2, whereas other provinces had TRAs of less than 30,000 km2 in total. The TRAs exhibited a relatively stable trend, with provinces such as Gansu, Qinghai, and Shaanxi showing an overall upward trajectory. Conversely, Shanxi and Inner Mongolia demonstrated an overall declining trend. When com-pared with other provinces, the variations in TRAs in Ningxia, Shandong, Sichuan, and Henan appeared to be more stable. The linear mixed model (LMM) revealed that farmland, shrubs, and grassland had significant positive effects on the TRA, explaining 41.6% of the variance. The ran-dom forest model also indicated positive effects for these factors, with high R² values of 0.983 and 0.86 for the training and testing sets, respectively, thus outperforming the LMM. The findings of this study can contribute to the restoration of the YRB's ecosystem and support sustainable devel-opment. The insights gained will be valuable for policymaking and decision support in soil and water conservation, agricultural planning, and environmental protection in the region.

The water quality index (WQI) and irrigational index for groundwater were studied in the northeastern section of the Manipur Valley in northeast India. Water samples were collected in 2022 during the pre-monsoon season. To compute the water quality index for drinking water, the basic chemical parameters of total hardness, pH, electrical conductivity, total dissolved solids, Ca2+, Na+, Fe, Mg2+, Mn, Cl-, and HCO3, were used. The assessment of bacteriological quality is also done, which is crucial for overall water quality evaluation, alongside physical and chemical analyze. For determining irrigation suitability, irrigational indices such as sodium absorption ratio, sodium percentage, and magnesium hazard were calculated. WQI, %Na+, SAR, magnesium hazard, permeability Index and total hardness indicate that most water samples are harmless for irrigation and drinking purpose. They have affirmative relationships indicating that these characteristics are interdependent. Approximately 25% of the Piedmont zone groundwater is found to be unfit for agricultural and drinking usage. The encrustation of gypsum, halite, and evaporation into the Disang shares accelerate the dissolution of ions in Piedmont water, resulting in quality degradation. According to Gibbs plots, Durov Scatter Plot, and Hill Piper Trilinear Diagram of water dominated the rock-weathering process, while hydro chemical facies progressed from the beginning to the intermediate stage of Chadha's graphical representation illustrates the progression of hydro chemical processes in surface water. Therefore, proper integrated water resource management and development are required for effective water resource utilization, particularly around the Piedmont zone. To prevent a water crisis, groundwater resources must be managed sustainably. The current study also concentrated on a bibliometric examination of groundwater management and access to gauge the state of the field.

The perception of the impacts of climate risks on health systems in the Grand Lomé region of Togo is diverse. This study was carried out based on information collected in the field. The investigation was based on a questionnaire, individual interviews and field observations. Data collection was carried out in a purposive manner in twenty-four (24) health facilities with a total of 112 health service people and 13 resource people affected. This article presents the results on the perception of the impacts of climate change on health personnel, the environment and buildings. The results show that 92.31% of respondents attest that climate change has impacts on health personnel; 84.62% on the environment and 84.62% on buildings and other health infrastructure. This study shows that climate change has real consequences on human health. It is therefore urgent that those responsible for health systems in the Grand Lomé region, which is home to the capital of Togo, can focus on finding adaptation measures in relation to each health structure and according to its intervention platform.

Buildings can play an important role in reducing GHG emissions through increased energy efficiency. The European Commission issued a proposal in 2021 suggesting that all new buildings should be “zero-emission Buildings” (ZEB), aiming at a zero GHG emission building stock by 2050.The extent to which ZEB can contribute to reduced GHG emissions, however, varies between countries, due to different energy systems. It is also important to consider other environmental effects to avoid that climate benefits come with unintended consequences.Here, we explore the life-cycle environmental performance for a ZEB in a case where electricity and heating is largely fossil-free. The assessment concentrates on i) environmental impact of the use stage in relation to the product stage, ii) the interrelation between different energy sources, with attention on household electricity, and iii) the performance for more impact categories than primary energy use and climate change. While our results generally support the use of ZEBs from an environmental perspective, they also show that the climate benefit in this setting is marginal. However, given that energy systems are connected and energy savings in one place can reduce the demand for fossil energy elsewhere, the climate benefit of ZEBs is likely underestimated. Besides methdological implications for future studies, this indicates that current EU policy is promising, as incentives for implementation of ZEBs is unaffected by domestic effects.

The vibration response of soil is a key property in the field of agricultural soil tillage. Vibration components of tillage machinery are generally used to reduce tillage resistance and improve work efficiency, the pressure variation under low-frequency vibration will affect the fragmentation and dispersion of farmland soil. However, the gradient of pressure variation, frequency domain response, and effective transmission range are unclear. A new method based on DEM (Discrete Element Method) is presented to study the vibration response and pressure transmission under low-frequency vibration. Bench test results showed that peak pressure positively correlates with the vibration frequency and attenuates rapidly at the vibration distance of 100 to 250 mm. The results data were also selected to determine the simulation model parameters. Amplitude, vibration frequency, and soil depth were used as test factors in single-factor simulation tests, and their effects on the peak pressure, frequency domain response, and effective transmission distance were analyzed. The results showed a positive relationship between the peak pressure and the test factors. The peak pressure increases with a maximum gradient of 19.02 kPa/mm at a vibration distance of 50 mm. The amplitude, vibration frequency, and soil depth positively correlate with the dominant frequency amplitude. The main frequency is independent of amplitude and soil depth. At the vibration distance of 250 mm, the dominant frequency is approximately twice the vibration frequency at 7–11 Hz and approximately equal to the vibration frequency at 13–15 Hz. Multiple exponential functions were used to fit the peak pressure attenuation function, obtaining an effective transmission distance range of 347.15 to 550.37 mm for the 5kPa cut-off pressure. For a soil depth of 300 mm, the vertical shear wave diffusion angle is greater than the horizontal shear wave diffusion angle. The study clarifies the vibration response of soil under low-frequency vibration, which helps to design vibration type soil-engaging components of tillage machinery and match vibration parameters for energy saving and resistance reduction in soil tillage.

This research analyses extreme precipitation events in the Huaihe River Basin in China, a densely populated region with a history of human settlements and agricultural activities. This study aims to explore the impact of extreme precipitation index changes and provide decision-making suggestions for flood early warning and agricultural development in the Huaihe River Basin. The study utilises the NEX-GDDP-CMIP6 climate models dataset and the daily value dataset (V3.0) from China's national surface weather stations to investigate temporal and spatial changes in extreme precipitation indices from 1960 to 2014 and future projections. At the same time, this study adopted the RclimDex model, Taylor diagram and Sen+Mann-Kendall trend analysis research methods to analyse the data. The results reveal a slight increase in extreme precipitation indices from northwest to southeast within the basin, except for CDD, which shows a decreasing trend. Regarding spatial, the future increase of extreme precipitation in the Huaihe River Basin will show a spatial variation characteristic that decreases from northwest to southeast. These findings suggest that extreme precipitation events are intensifying in the region. Understanding these trends and their implications is vital for adaptation strategy planning and mitigating the risks associated with extreme precipitation events in the Huaihe River Basin.

In the last years, various changes and enhancements have been made to the technical structure of the substituted boreholes in comparison to the old boreholes. Increasing production capabilities from an individual borehole and/or a borehole field has engineering significant and economic value. Unfortunately, we are unable to change the composition of the aquifer lithology and its hydraulic properties and therefore, increasing the extraction capabilities from an individual borehole is possible by using technical improvements in drilling methods, in borehole design and in its final structure. This is illustrated through examples from two different aquifer basins, where substituted boreholes were drilled adjusted to the old borehole and in the same yard. The substituted boreholes were drilled to similar depth and to the same lithology as those in the old boreholes. That is, any discrepancies in hydraulic parameters attributable to changes and improvements in the borehole design and structure.

Abstract. The paper presents primary material on determining the presence of micro- and macroplastics in Markakol Lake, one of the high-mountainous and unique water bodies of Kazakhstan, conditionally undisturbed, but vulnerable to anthropogenic pollution. In the course of work, micro- and macroplastics were detected in all selected samples in the water area of the lake and its main tributaries, the Urunkhaika, Topolevka, Tikhushka, Matabai, Elovka rivers. When determining micro- and macroplastics, we were guided by the method of analysis in aquatic environment, NOAA research program, developed by American scientists Masura J. et al, which is used in many countries. Concentrations and sizes of MP found in the water of the main tributaries of the rivers Urunhaika in concentrations up to 211.4 µg/m3, Tikhushka – 97.9 µg/m3, Zhirelka – 67.8 µg/m3, Topolevka – 157.2 µg/m3, Matabai – 78.3 µg/m3. Concentrations of MP in the surface water layer of the lake detected during 15 minute trawling at distances from 438 m to 841 m occur in sieve mesh sizes of 1.0 mm – 316.7 µg/m3 and 0.315 mm – 520.8 µg/m3. The total concentration of detected micro- and macroplastics coming with tributaries was – 150 µg/m3, in the lake water area – 837.4 µg/m3. The sizes of plastic debris found both in river waters and along the lake water area ranged from mesoplastic debris (fishing line net fragments, foam balls, plastic bags, plastic bottles, wrappers, food labels and packaging, etc.) to microplastic particles detected using a microscope with 40X magnification in size ranges of 25 mm, 1.0 mm and 0.315 mm. Sources of MP depend on local human activities (fishing, transportation, waste disposal etc.).

The watershed hydrologic conditions in the Madre de Dios (MDD) basin in the Peruvian Amazon have been irreversibly impacted by deforestation and changes in land use cover. These changes have also had detrimental effects on the geomorphology, water quality, and aquatic habitat within the basin. However, there is a scarcity of hydrological modeling studies in this area primarily due to the limited availability of hydrometeorological data. The primary objective of this study was to examine how deforestation impacts the hydrological conditions in the MDD basin. By implementing the Soil and Water Assessment Tool (SWAT) model, this study determined that replacing 12% of the evergreen broadleaf forest area with bare land resulted in an significant increase in surface runoff by 38% monthly, a reduction of evapotranspiration by 1% annually, and an average monthly streamflow increase of 12%. Changes in spatial patterns reveal that the primary impacted watershed is the Inambari River subbasin, a significant tributary of the Madre de Dios River. This area experiences an annual average surge of 187% in surface runoff generation while witnessing an annual average reduction of 8% in evapotranspiration.These findings have important implications, as they can contribute to instances of flooding and extreme inundation events, which have already occurred in the MDD region.

Contamination by microplastics (MP) in aquatic ecosystems is largely due to the release of millions of these particles from treated effluents from Wastewater Treatment Plants (WWTP). Due to the lack of policies and regulations that establish criteria for the control and elimination of MP from WWTP effluents, this research evaluated the presence of MP for particle sizes of 38 and 150 µm in influents and effluents from three WWTP in the port of Acapulco, Mexico. Using optical microscopy and Fourier transform infrared spectroscopy (FTIR) techniques, the MP detected were polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET) and polyvinyl chloride (PVC). MP removal efficiencies of 82.5 to 98.7% (38 µm) and 86.8 to 97.5% (150µm) were obtained; the MP average daily emissions to the receiving bodies of these three WWTPs were in the ranges of 9.5 x 106 - 4.70 x 108 particles and the annual emissions in the range of 3.05 x 109 - 1.72 x 1011 particles. This work reveals the urgency of implementing regulatory policies to avoid the continuous emission of MP to aquatic ecosystems from WWTPs in Acapulco, Mexico.

Geoethics is a field of knowledge currently in full development. Researchers in geoethics are pri-marily concerned with the anthropogenic interaction with the Earth system. Due to its nature, ge-oethics holds particular importance in sustainable development due to its nature as it aims to promote ethical human behaviour that does not negatively impact the Earth system. In the present research, we implemented an intervention program addressing various issues related to the sus-tainability of the Earth system, such as the exploitation of geological resources, the management of geological risks, and the conservation and promotion of geopatrimony. The intervention program was applied to higher education students in the geosciences field. A sample of 90 students from various geosciences courses completed an initial questionnaire, revealing limited knowledge about geoethics. This study resorted to mixed-method research involving interviews with some students who volunteered (n=52). The results showed that after applying the intervention programme most students had developed a deeper understanding of the topics addressed and recognised the con-tributions this scientific area can make to sustainable development. Additional research in geoethics education is essential to foster the integration of geoethics into the curricula of higher education institutions.

The growing population with changing consumption patterns in developing countries is causing significant challenges with regards to solid waste management. Plastic wastes are particularly problematic, with single-use plastics leaking into the environment, including the marine environment, at an unprecedented rate. Approximately 80 percent of ocean plastics come from land-based sources or about 8 million tons are dumped into the ocean every year. Thailand was identified as one of the top 10 countries ranked by mass of mismanaged plastic wastes, with more than 60,000 tons per year entering the ocean through multiple outlets, including rivers. In the environment, plastic wastes can be degraded into small sizes (less than 5 mm), called microplastics (MPs), which could contaminate the ecosystems and the food chain, including foodstuffs and water supply. Tap water samples collected from a water supply treatment plant and Academic Institutions 1 and 2 in central Thailand were found to contain MPs about 304 ±90, 270 ±109 and 386 ±102 particles/L, respectively. In addition, MPs concentrations of 211 ±70 and 122 ±60 particles/L were also found in drinking water samples collected from commercial bottled water and membrane filtration water, respectively. The MPs sizes of 0-50 µm were most abundant in both the tap and drinking water samples whose shapes were mainly fragments and fiber. These data indicated potential health risks to the people who consume these water sources, and recommendations for health impacts minimization were proposed.

The assessment and prediction of drought risk under future climate change and land use land cover (LULC) scenarios is critically important for drought prevention and mitigation, as it enables a clearer understanding of potential shifts in drought patterns. The primary aim of this study is to evaluate sub-seasonal and seasonal meteorological and hydrological drought hazards across the Yellow River Basin (YRB) under projected future climate conditions and LULC patterns. The BCC-CSM1-1 climate model projections from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset are utilized to represent future climate for 2025-2060 under RCP 4.5 and 8.5 scenarios. The CA-Markov model is employed to predict future LULC distributions. Meteorological and hydrological drought risks across different YRB zones are evaluated through a copula-based risk assessment approach, based on the joint probability distribution of drought duration and severity. The results indicate that sub-seasonal meteorological and hydrological droughts will likely be the primary concern moving forward. Specifically, the upper YRB (zones A, B, C) exhibits greater vulnerability to sub-seasonal meteorological drought, while the Loess Plateau (zones C, E) shows higher susceptibility to sub-seasonal hydrological drought. Moreover, zone F in the downstream region may experience increased seasonal hydrological drought risk due to projected urban expansion in the middle and lower portions of the YRB.

Effective solid waste management is crucial for protecting public health and the environment. Global concentration on finding sustainable methods of handling waste continue to top the list of most governmental-related project checklists. This paper provides a case study on the management of municipal solid waste in the cities of Karlsruhe, Germany and Navrongo, Ghana as developed and developing countries respectively. This study aimed at comparing and drawing lessons from how these two different cities manage their solid waste. The waste management system in Karlsruhe prioritizes waste separation, recycling, and a pay-as-you-throw system has led to an efficient and sustainable waste management system that minimizes waste and protects the environment. Karlshrue's adoption of a continual developmental plan structure focused on integrated WM concepts is credited with safeguarding the long-term viability of waste management in the city. In contrast, Navrongo's waste management system faces several challenges, including inadequate resources and infrastructure, traditional waste disposal practices, and the lack of well-planned waste management strategies. To improve effective solid waste management systems in Ghana, a collaborative approach involving the government, local organizations, and the community is necessary. This can include investing in infrastructure, implementing waste separation and recycling programs, and educating the public on the benefits of sustainable waste management practices. Learning from successful models like Karlsruhe can help accelerate the development of sustainable waste management practices in Ghana, and ultimately protect public health and the environment.

The probability distribution of the interevent time between two successive earthquakes has been subject of numerous studies due to its key role in seismic hazard assessment. In recent decades, many distributions have been considered and there has been a long debate about the possible universality of the shape of this distribution when the interevent times are suitably rescaled. In this work we aim to find out if there is a link between the different phases of a seismic cycle and the variations in the distribution that best fits the interevent times. To do this, we consider the seismic activity related to the Mw 6.1 L’Aquila earthquake that occurred on April 6, 2009 in central Italy by analyzing the sequence of events recorded from April 2005 to July 2009, and then the seismic activity linked to the sequence of the Amatrice-Norcia earthquakes of Mw 6 and 6.5 respectively and recorded in the period from January 2009 to June 2018. We take into account some of the most studied distributions in the literature: q-exponential, q-generalized gamma, gamma and exponential distributions and, according to the Bayesian paradigm, we compare the value of their posterior marginal likelihood in shifting time windows with a fixed number of data. The results suggest that the distribution providing the best performance changes over time and its variations may be associated with different phases of the seismic crisis.

In Saudi Arabia’s mountainous regions, debris flow is a natural hazard that poses a threat to infrastructure and human lives. To assess the potential zones of debris flow in the Al-Hada Road area, a study was conducted using Geographic Information System (GIS) analysis and remote sensing (RS) data. The study took into account various factors that could affect debris flow, such as drainage density, elevation, slope, precipitation, land use, geology, soil, and aspect. The study also included a field trip to identify 11 previous debris flow events that were influenced by high-density drainage and slope. The study utilized weighted overlay analysis in a GIS environment to create a map indicating the potential debris flow zones in the area. According to the analysis, low-risk areas cover 35,354,062.5 square meters, medium-risk areas cover 60,646,250 square meters, and high-risk zones cover an area of 8,633,281 square meters. This result was verified using the locations of previous debris flow events. The study’s findings can help planners and decision-makers identify and prioritize areas for mitigation and prevention measures. Additionally, the study contributes to understanding debris flow hazards in arid and semi-arid regions.

Agricultural activities profoundly affect groundwater levels in Saudi Arabia. The Al Kharj and Wadi Sahba areas, central Saudi Arabia, produce groundwater mainly from the Jurassic Arab/Jubaila aquifer and the overlying Cretaceous Biyadh aquifer. A geographic information system analysis and linear regression analyses show that from 1978 to 2016, significant agricultural overexploitation of the area’s fossil groundwater was associated with groundwater level drops of ~104 m in Al Kharj and ~48 m in Wadi Sahba. The estimated total volume of groundwater withdrawal across both aquifers during this period of wheat and alfalfa irrigation was ~27 billion m3. Landsat image analysis shows that agricultural land use decreased by ~66% over the same period due to overexploitation. The 2016 phase-out of alfalfa farming was associated with increases in groundwater levels: ~26 m in the Arab/Jubaila aquifer and ~3 m in the Biyadh aquifer. This recovery was likely due to lateral flow from surrounding fossil water within the aquifer given the absence of significant surface recharge. Model-based evaluation of surface recharge of the aquifer reveals very low potential for surface infiltration, with almost no recharge into the deep aquifer. Assuming that recovery continues at the present rate, the average groundwater level for the Arab/Jubaila aquifer is expected to reach 98 m below ground level in 2025 and 74 m below ground level in 2030.

Chlorophyll-a (Chla) is a crucial pigment in phytoplankton, playing a vital role in determining phytoplankton biomass and water nutrient status. However, in optically complex water bodies, Chla concentration is no longer the primary factor influencing remote sensing spectral reflectance signals, leading to significant errors in traditional Chla concentration estimation methods. With advancements in in-situ measurements, synchronized satellite data, and computer technology, machine learning algorithms have become popular in Chla concentration retrieval. Nevertheless, when using machine learning methods to estimate Chla concentration, abrupt changes in Chla values can disrupt the spatiotemporal smoothness of the retrieval results. Therefore, this study proposes a two-stage approach to enhance the accuracy of Chla concentration estimation in optically complex water bodies. In the first stage, a one-dimensional convolutional neural network (1DCNN) is employed for precise Chla retrieval, and in the second stage, the regression layer of the 1DCNN is replaced with Support Vector Regression (SVR). The research findings are as follows: (1) In the first stage, the performance metrics (R², RMSE, RMLSE, Bias, MAE) of the 1DCNN outperform state-of-the-art algorithms (OCI, SVR, RFR) on the test dataset. (2) After the second stage, the performance further improves, with the metrics achieving values of 0.892, 11.243, 0.052, 1.056, and 1.444, respectively. (3) In mid-to-high latitude regions, the inversion performance of 1DCNN\SVR is superior to other algorithms, exhibiting richer details and higher noise tolerance in nearshore areas. (4) 1DCNN\SVR demonstrates high inversion capabilities in water bodies with medium to high nutrient levels.

Cattle slurry is an important nitrogen source for maize on dairy farms. Slurry injection is an effective measure to reduce ammonia emissions after field application, but with higher risk of nitrous oxide emission than surface application. This study compared soil mineral nitrogen dynamics and nitrous oxide emissions with two ways of application. First, traditional injection at 25 cm spacing between rows followed by ploughing (called “non-placed slurry”), and second, injection using a new so-called goosefoot slurry injector that placed the slurry in ploughed soil as a c. 30 cm broad band at 10 cm depth below maize crop rows with 75 cm spacing (named “placed slurry”). Furthermore, the effect of treating slurry with the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) in Vizura® was tested with both application methods. The field experiment was conducted on a sandy loam soil in a temperate climate. Both nitrous oxide emissions, and the dynamics of soil mineral nitrogen, were monitored for eight weeks after slurry application and seeding of maize using static chambers. The level of nitrous oxide emissions was higher with non-placed compared to placed slurry, mainly due to higher emissions during the first four weeks. That might be due to higher rates of nitrification rate and in turn stimulation of denitrification process. In both placed and non-placed slurry treatments, Vizura® caused higher soil ammonium concentrations and lower nitrate concentrations, particularly from 3 to 8 weeks after slurry application. The final level of soil nitrate was similar with and without the nitrification inhibitor, but higher with placed compared to non-placed slurry. Adding Vizura® to non-placed slurry reduced nitrous oxide emissions by 70 % when compared to placed slurry. Surprisingly, there was a non-significant trend towards higher cumulative emissions from placed slurry with the nitrification inhibitor compared to untreated slurry, which were due to higher emissions in the last part of the monitoring period (5-7 weeks after slurry application). Possibly degradation of the nitrification inhibitor, and nitrification activity inside the slurry band as the soil dried, promoted nitrous oxide emissions by this time. In summary, placement of untreated slurry in a broad band under maize seeds reduced nitrous oxide emissions compared to non-placed slurry with more soil contact. A comparable reduction was achieved by adding a nitrification inhibitor to non-placed slurry. The pattern of nitrous oxide emissions from placed slurry treated with the inhibitor was complex and requires more investigation.

The public administrations (PAs) that have joined the Covenant of Mayors must now complete their adaptation plans with the climate chapter (SECAP). At the same time, the previous Plan for sustainable energy (SEAP) was mainly dedicated to mitigation actions (sustainable energy). It was often managed directly by municipalities' in-house energy companies or agencies. The WMO1234 Recommendation (Guidance on Integrated Urban Hydrometeorological, Climate and Environmental Services) is a fundamental Guidance to allow PAs to make policies and decisions regarding city regeneration and population health prevention. The purpose of this manuscript is to describe a process undertaken in the Emilia-Romagna region to build a coherent frame from the individuation of local environmental vulnerabilities and adopt specific policies. This frame was created by the contribution of various Institutions, including the Regional Authority, which furnished the main directives and tools for the mitigation and adaptation, the Municipality of Bologna, which prepared the first Adaptation Plan following the SECAP guidance, the Emilia-Romagna branch of Italian Association of Municipalities (ANCI), which took in charge the approach to harmonize different urban contexts and to communicate with stakeholders and population, and Research Institutes and Scientific Associations to explore, with specific studies and modeling application, the outcomes produced by a joint support to the new urban directives, such as the General Urban Planning Plan (PUG). To achieve this result, the WMO Guidance 1234 has been assumed as a reference methodology to ensure the best utilization of available data and widespread a common science-based methodological approach to other municipalities.

Wastewater treatment from oils and oil products, organic mixtures are a very relevant topic that can be successfully used to solve problems of serious environmental pollution, such as oil spills, industrial oily wastewater discharges and water treatment in the water treatment process. In this work, we have developed new superhydrophobic magnetic polyurethane (PU) sponges functionalized with reduced graphene oxide (RGO), MgFe2O4 nanoparticles, and silicone oil (SO) as a selective and reusable sorbent for purification and separation of wastewater from oils and organic solvents. The surface morphology and wettability of the sponge surface were characterized by scanning electron microscopy (SEM) and a contact angle analysis system, respectively. The results showed that the obtained PU sponge PU/RGO/MgFe2O4/SO had excellent mechanical and water-repellent properties, reusable properties (more than 20 cycles), as well as fast (immersion time 20 sec) and excellent adsorption capacity (16.61- 44.86 g / g), and good magnetic properties made it easy to separate the sponge from the water with a magnet. And the presence of RGO in the composition of the nanomaterial improves the separating and cleaning properties of materials, and also leads to an increase in the absorption capacity of oil and various organic solvents. The synthesized PU sponge has great potential for practical applications due to its facile fabrication and excellent oil-water separation property.

Spatiotemporal climate variability is a leading environmental constraint to the rain-fed agricultural productivity and food security of communities in the Abbay basin and elsewhere in Ethiopia. The previous one-size-fits-all approach to soil and water management technology targeting did not effectively address climate-induced risks to rain-fed agriculture. This study, therefore, delineates homogenous climatic regions and identifies climate-induced risks to rain-fed agriculture that are important to guide decisions and selection of site-specific technologies for green water management in the Abbay basin. The k-means spatial clustering method was employed to identify homogenous climatic regions in the study area, while the Elbow method was used to determine an optimum number of the climate clusters. The k-mean clustering used the Enhancing National Climate Services (ENACTS) daily rainfall, minimum and maximum temperatures, and other derived climate variables that include daily rainfall amount, length of growing period (LGP), rainfall onset and cessation dates, and rainfall intensity, temperature, potential evapotranspiration (PET), soil moisture and AsterDEM to define climate regions. Accordingly, 12 climate clusters or regions were identified and mapped for the basin. Clustering a given geographic region into homogenous climate classes is useful to accurately identify and target locally relevant green water management technologies to effectively address local-scale climate-induced risks. The study has also provides a methodological framework that can be used in the other river basins of Ethiopia and indeed elsewhere.

The decline of fossil fuels, the increase of greenhouse gases and the global demand for energy are driving the search for alternative energy sources. Anaerobic digestion is a promising technology because it can convert organic biomass into biogas. As the climate warms, there is an increase in biomass of plant origin in water bodies, and ecosystems are unable to clean themselves. This work aims to show that macroalgae and aquatic plants can be an excellent raw material for biogas production. By mixing them with co-substrates such as cattle manure, higher biogas and methane yields can be obtained. When Cladophora glomerata and Zostera marina macroalgae are mixed with cattle manure, the biogas yield is up to 458.8 mL/gVS and 397.9 mL/gVS, respectively. Methane concentration remained high and reached 62.4%–64.1%. The obtained research results show the high energy value of biogas and the energy potential of biomass. Macroalgae increased the energy potential of biogas to 22.9 MJ/m3, and the energy potential of biomass reached 2.40 MJ/Kg. Due to its high energy value, biogas produced from the considered substrates can be an excellent alter-native to fossil fuels. Integrating aquatic macroalgae into anaerobic digestion is a promising approach for a waste-free marine and freshwater system.

Macrolide antibiotics, effective antimicrobial agents, are intensively used in human and veterinary medicine as well as in agriculture and therefore are found all over the world as environmental pollutants, harming sensitive eco-community organisms and provoking the selection of resistant forms. A novel azithromycin derivative was synthesized and as a rationally designed hapten conjugate ensured group immunorecognition of 6 major macrolide representatives (105-41%), erythromycin, erythromycin ethylsuccinate, clarithromycin, roxithromycin, azithromycin and dirithromycin in competitive immunoassay based on anti-clarithromycin antibodies. The heterologous hapten-based ELISA format simultaneously contributed to a 5-fold increase in sensitivity (ERY IC50 = 0.04 ng/mL). However, for the detection of trace macrolides in environmental samples, an underexploited in immunoassay field strategy was proposed in the present study to significantly improve the detectability of analytes. Unlike most approaches, it does not require special enhancers/amplifiers or additional concentration/extraction procedures, but only involves a larger volume of test samples. Gradual volume increase of samples (from 0.025 to 10 mL) analyzed in direct competitive ELISA, immunobeads, and immunofiltration assay formats based on the same reagents resulted in a significant improvement (more than 50-fold) in assay sensitivity and detection limit up to 5 and 1 pg/mL, respectively. The suitability of the test for detecting macrolide contamination of natural water was confirmed by recovery of macrolides from spiked blank samples (71.7-141.3%). A series of natural water samples from Lake Onega and its influents near Petrozavodsk were analyzed during a 2022-2023 using both the developed immunoassay and HPLC-MS/MS and revealed no macrolide antibiotic contamination.

In many Indian regions increased wastewater is both a threat and an opportunity. Efficient wastewater treatment and reuse schemes are needed in India to face impending water and fertiliser shortages. This study explores the application potential of wastewater fertigated Short Rotation Coppice systems (wfSRC) as a cost-efficient and promising solution for treating and reusing wastewater in a specific region (400 km2, 184 settlements) of Aligarh (UP), India. Based on real data from a local wfSRC pilot site using bamboo, willow, and poplar, we analysed the system’s treatment performance, nutrient recovery, carbon sequestration potential, land requirements, biomass production potential, and cost-benefit, under various scenarios. The results show that the pilot wfSRC system is efficiently treating 250 m3/day of domestic wastewater on 6,864 m2 of land, and serving 2,500 people. The land requirements for wfSRC systems vary depending on local conditions and user requirements, ranging from 2.75 – 25.7 m2/PE which equates to a required land area in the whole study region of between 108 and 1006 ha in 2036. This would produce up to 100 DM t/ha/yr of valuable biomass. Early local stakeholder involvement and monitoring of pollutants are recommended as priorities during the planning process for large-scale implementation of wfSRC systems in India.

We investigate if anyone is being left behind in accessing safely managed drinking water (SM) in achieving the 2030 agenda. We use 23 countries grouped globally as critically insecure water (CIWC). The results indicate none of the CIWC had over 50% of the population accessing SM, N. America and Europe had highest percentages while Sub Saharan Africa had the least. People left behind are found in rural areas, in countries vulnerable to climate change because of poor governance, low-income, and women’s low education. Institutional quality, equity and equality should be improved in using resources critical to leaving no one behind.

Air pollution includes particle-bound Polycyclic Aromatic hydrocarbons (PAHs) which eventually reach the placenta triggering adverse perinatal outcomes by long-term exposure. Late-ly, air pollution has increased over the Metropolitan Area of Medellin-Colombia (MAMC) but its effects on pregnancy are still unknown. In this research, we made a real-time analysis of airborne total PAHs using a photoelectric sensor for residential places influenced by industrial and traffic sources contrasting southern and northern MAMC during the second peak of the bimodal ten-dency for PM2.5 emissions in this region. Additionally, we analyzed individual PAHs by GC/MS coupled to pressurized hot water extraction methodology. Data was applied in an Inhalation In-take Model to assess pregnancy exposure. The average concentration of PAHs over southern MAMC was three times higher than over northern MAMC where the abortion rate has been 1.4 times higher presented in database. Previous research found that PAHs act as an Endo-crine-Disrupting Chemical (EDC) during pregnancy and even heavy congeners could reside in umbilical cord blood. Finally, the annual series of abortion rates in the MAMC showed a signifi-cant correlation with the annual average levels of PM2.5 which are associate to PAHs. Although this significant correlation does not imply causality, our results suggest an important connection between both variables. This latter finding opens a gap in deeply understanding how regions with high PAHs-convergence influences abortion rates in MAMC.

Cemeteries can be compared to landfills since their leachate, also known as necroleachate, can be transported and pollute groundwater, surface waters, and soils. In Brazil, the cemeteries management is the responsibility of states and municipalities, to ensure that they do not generate negative environmental impacts and risks to public health. This article aims to discuss Brazilian sanitary-environmental legislation relating to cemetery waste management. Among the Brazilian states, half have sanitary-environmental legislation for cemeteries, and between the municipalities, only 19 have specific legislation. The legislation is broad and has many gaps, leading to environmental vulnerability and risk of contamination for the people who live in the surrounding area.

Ammonia is an atmospheric pollutant, predominantly emitted from agriculture, leading acidification and eutrophication of soil and water and contributing to secondary PM2.5. The implementation of accurate emission inventories with high spatial and time resolution plays a fundamental role in the development of air modelling simulation and in the impact assessment of actions for air quality improvement. The development and release of new algorithms and the increase of data availability are supporting the implementation of machine learning approaches in environmental and air quality data analysis. In this paper we present a methodology developed by the application of the Random Forest algorithm to bottom-up local emission inventories of ammonia to validate annual time series of ammonia emissions and calculate high resolution temporal profiles. The model has been trained and tested by the hourly measurements of ammonia concentrations and atmospheric turbulence parameters starting from a constant emission scenario. The initial values of emissions are calculated based on a bottom-up emission inventory detailed at the municipal basis and considering a circular area of about 4 km radius centered on measurement sites. By comparing predicted and measured concentrations, the emissions are modified, the model's training and testing are repeated, and the model converges to a very high performance in predicting ammonia concentrations and establishing an hourly time changing emission profile. The site-specific emissions profiles, estimated by the proposed methodology, clearly show a nonlinear relation with measured concentrations and allow to identify the effect of atmospheric turbulence on pollutant accumulation. The estimated time series well confirm the available data of the emission inventories and the monthly emission profiles have been compared with estimated data from satellite.

This paper reports aligned activities to promote energy and resource-efficient construction practice in Vietnam. First, the governance framework is introduced, including government decrees and technical standards. Then, a laboratory with building physics measurement technology is designed and partly set up at the local partner Vietnam Institute for Building Materials (VIBM), which can be used to determine the essential characteristic values required for the implementation of energy standards. The basis for the prioritization of the characteristic values are the requirements of the National technical regulation on energy efficient buildings of Vietnam – QCVN09:2017/BXD. Furthermore, basic characteristic values from international standards are described, which can also be used for calculations to optimize the energy consumption of buildings. In order to be able to carry out transient hygrothermal computer simulations, special characteristic values were also included. These are particularly useful for the research and development of new building materials and the evaluation of entire buildings in terms of thermal and moisture protection In order to communicate the material properties to the market and enable informed decision making by the stakeholders, a labeling system has been developed. Thereby, the practical means for implementing governance instruments are provided, and the related technical applications are supported.

Lignocellulosic biomass is a powerful approach for the production of sustainable biofuels and the further achievement of the goal of biomass conversion into a second-generation clean energy that can cope with the depletion of fossil reserves and rising energy requirements. In the conversion process, a pretreatment is essential to overcome the recalcitrance of the lignocellulosic biomass, accelerate its disintegration into cellulose, hemicellulose, and lignin and, in turn, get an optimal yield of fermentable sugars in the enzymatic hydrolysis. In addition to this, it should be industrially scalable and capable of enhancing fuel properties and feedstock processability. Here, steam explosion technology has stood out due to its results and advantages such as wide applicability, high efficiency in the short term, or lack of contamination in spite of its conventionality. This gentle and fast pretreatment incorporates high temperature autohydrolysis and structural alteration by explosive decompression. Steam explosion method has been one of the most effective especially for the hydrolysis of cellulose from agricultural wastes due to the lower quantity of acetyl groups in the composition of hemicellulose. In this aspect, sugarcane bagasse is a promising feedstock for bioethanol production due to its high cellulosic content and elevated availability. The objective of this review has been to compile the latest information on steam explosion pretreatment, stages, equipment, variables involved, by-products generated, as well as the advantages and disadvantages of the technique. At the same time, its feasibility and viability using sugarcane bagasse as feedstock has been discussed. Finally, the effectiveness of the technique with different feedstocks has been evaluated.

We analysed changes in magnitude and timing of the largest annual observed daily flow (Amax), in each water year, for 596 stations in high-value water resources catchments and flood risk locations across Australia. These stations are either included in the Bureau of Meteorology's Hydrologic Reference Stations, or used in its operational flood forecasting services. Monotonic trend (which are either consistently increasing or decreasing) analyses of the magnitude and timing of flood peaks (estimated using Amax) were performed using Theil-Sen and Mann-Kendell approach and circular statistics to identify strength of seasonality and timing. Regional significance at the drainage division scale was analysed using the Walker test. Monotonic decreasing trends in Amax flood magnitude were detected in the Murray-Darling River basin and in other drainage divisions in Victoria, south-west and mid-west of Western Australia and South Australia. No significant obvious pattern in Amax magnitude was detected in northern Queensland, coastal NSW, central Australia and Tasmania. Only the Tanami-Timor Sea Coast drainage division in northern Australia showed monotonic increasing trends. Monotonic trends in Amax magnitude were regionally significant at the drainage division scale. We found two distinct patterns in flood seasonality and timing. In the northern and southern parts of Australia, flood peaks generally occur during February to March and August to October, respectively. The strength of this seasonality varies across the country. Weaker seasonality was detected for locations in the Murray-Daring River basin, and stronger seasonality was evident in northern Australia, south-west of Western Australia, South Australia, Victoria and Tasmania. The trends of seasonality and timing reveal that in general, flood peaks are occurring later in the water year in recent years. In northern Australia, flood peaks are generally occurring earlier – at a rate of 12 days/decade. In Victoria, New South Wales and Tasmania, trends in timing are generally mixed. However, in the south-west of Western Australia, the largest change in timing was evident – with Amax peaks commencing later at a rate of 15 days/decade. Decadal variability in flood timing was found at the drainage division scale as well. Most stations show a decreasing trend in Amax magnitude, but how that trend is associated with the change in timing is not clear.

A recent research has identified an inverse amplitude link between obliquity damping and short eccentricity amplification during Mid-Late Pleistocene based on LR04 δ18O and equatorial Pacific Site 846 sea surface temperature records, which is associated with the Earth's long-term cooling. In the present study, new evidence of this anticorrelation is presented from Antarctic D-CO2-CH4 records, global benthic-planktic δ18O, and regional (Atlantic, Pacific, Mediterranean, and Indian) climate-related proxies. Based on a critical review of theoretical constrains (Earth's oblateness changes and ice-volume phase lag in the obliquity band <5.0 kyr), this widespread and symmetric (bipolar) obliquity response damping has been interpreted as an effect of the obliquity-oblateness feedback, which could be the latent physical mechanism at the origin of the Mid-Pleistocene Transition (MPT). Indeed, results and considerations of the present work suggest that fast and positive/negative net variation of the Earth's oblateness in the obliquity band was controlled by dominant glacio-eustatic water mass component and, assuming a rapid response of the ice-volume to surface temperature changes, the mean obliquity lag response is estimated to be <5.0 kyr over the past 800 kyr. These elements may explain the interglacial/glacial damping observed in the obliquity response. The consolidation of the Earth's long-term icy-state in the subtrend IV, culminated with the post-MPT obliquity damping, might have contributed to the strengthening of the short eccentricity response by mitigating the obliquity ‘ice-killing’ during obliquity maxima (interglacials), favouring the obliquity-cycle skipping and a feedback amplified ice-growth in the short eccentricity band (obliquity damping hypothesis). This could suggest a different impact of the climate friction than what is generally believed, which is presumably the latent physical mechanism that triggers transient ‘competitive’ interaction between obliquity and short eccentricity started early during the Piacenzian.

Participatory landscape conservation is an innovative approach that weaves theory and practice to bridge the gap between theoretical models and practical applications. Intertropical regions as the case of Mexico face challenges to conciliate regional governability, social justice, and nature conservation. The State of Michoacan is one of these regions where the challenges exacerbate since nature conservation is last due to its ongoing territorial disputes. We implemented the participatory landscape conservation approach by creating a complementary form of protected areas with ongoing conflicts, drought conditions, and extreme poverty. We conducted participatory mapping and land cover/use analyses as main methodological tools to reach consensus among stakeholders. We integrated, macro, micro and social scales to provide sound arguments to integrate local, scholar and policy makers perceptions. The outcomes of the participatory mapping analyses were assessed. The present papers provide evidence of the positive outcome of using a Participatory Landscape Conservation to establish a Biosphere Reserve, safeguarding one of the most biologically diverse and delicate ecosystems consisting of seasonally dry tropical forests within a rather disputed region. We discussed the relevance of our findings and compared them to ongoing regional and global trends in the light of other forms of establishing protected areas.

The research employs both literature and experimental data to develop reasonable strategies for melon fly control. The objects of research were sierozem soils of the Zhanakorgan region (Kyzylorda region), bentonite clays of the Sauran region (Turkestan region), vermicompost obtained at the production site of the Research Institute "Ecology" at the International Kazakh-Turkish University named after Khoja Ahmed Yasawi. The competitive agent 'Vermiserbent' was developed by combining sulphur-perlite-containing waste (SPCW), vermicompost (VC), and natural bentonite clay. When incorporated into the soil, it serves as both an insecticide and a fertiliser recovery agent. Disinfection and enrichment of barren Sierozem soils in southern Kazakhstan could provide an eco-friendly approach to protect cucurbits (melon, watermelon, and pumpkin) against the melon fly. The average yield of watermelon treated with vermiserbent increased by 2.3 t/ha compared to the control, melon by 4.6 t/ha, pumpkin by 5.6 t/ha. The marketability of gourds as watermelons and melon after treatment with fertilizer increased by 1.2 times, and pumpkin by 1.1 times. The findings of studies conducted in agricultural fields in the Turkestan and Kyzylorda regions have shown that it is possible to produce environmentally sound gourds using a mixture of vermicompost, bentonite, and SPCW.

In order to better realize rural revitalization, this paper analyzes the spatial and temporal char-acteristics and influencing factors of agricultural surface source pollution in the Yangtze River Economic Belt from the three perspectives of government, enterprise and agriculture by using the spatial Durbin model and the dynamic GMM method in the period of 2006-2021, and further re-searches the threshold characteristics of the distortion of the factor market on the agricultural surface source pollution under the different strengths of environmental regulation. The results show that there is a positive spatial correlation between agricultural surface pollution in the Yangtze River Economic Belt, and government environmental regulation, input factor market distortion and labor force transfer all have a significant impact on agricultural surface pollution. Among them, factor market distortion has a significant spatial spillover effect on agricultural surface pollution in the Yangtze River Economic Zone, and has a significant single-threshold ef-fect on environmental regulation. Accordingly, the government should strengthen environmental regulation, continuously improve the agricultural factor market mechanism, and pay attention to the construction of talents to provide support for rural revitalization.

"Finding fresh water in the ocean of data." is a challenge that all deep learning domains struggle with, especially in the area of hyperspectral image analysis. As hyperspectral remote sensing technology advances by leaps and bounds, there are increasing amounts of hyperspectral images(HSIs) can be available. Whereas in fact, these unlabeled HSIs are powerless to be used as material to driven a supervised learning task due to the extremely expensive labeling costs and some unknown regions. Although learning-based methods have achieved remarkable performance due to their superior ability to represent features, at the cost, these methods are complex, inflexible and tough to carry out transfer learning. In this paper, we propose the "Instructional Mask AutoEncoder"(IMAE), which is a simple and powerful self-supervised learner for HSI classification that uses a transformer-based mask autoencoder to extract the general features of HSIs through a self-reconstructing agent task. Moreover, we utilize the metric learning to perform an instructor which can direct the model focus on the human interested region of the input so that we can alleviate the defects of transformer-based model such as local attention distraction, lack of inductive bias and tremendous training data requirement. In downstream forward propagation, instead of global average pooling, we employ a learnable aggregation to put the tokens into fullplay. The obtained results illustrate that our method effectively accelerates the convergence rate and promotes the performance in downstream task.

The composition and pattern of ecosystems are important factors determining the overall status and spatial differences of ecosystem service functions. However, under the background of differential land policies and ecological protection policies, research on the trend of ecological system pattern changes in the Fenhe River Basin is insufficient. Taking the upper and middle reaches of the Fenhe River Basin as the study area, based on long-term NDVI index and multi-period LUCC remote sensing images, this study used spatial statistics and time trend analysis methods to analyze the spatio-temporal dynamic changes of vegetation, land use, landscape pattern, and explored the impact of major driving factors on ecosystem changes. The results show that: (1) From 2010 to 2020, the vegetation cover in the upper and middle reaches of the Fenhe River Basin increased, with an annual NDVI increment of 0.003 (P<0.001). NDVI showed an increasing trend spatially, with significant statistics (P<0.001) and significant changes (P<0.05) in vegetation in high-altitude mountain areas, and the vegetation cover was mostly forests or grasslands. There was no significant change in vegetation cover in the low-lying urban agglomeration area. (2) From 2010 to 2020, the area of water bodies or wetlands in the study area significantly decreased, with 51.3% converted to arable land and 33.9% transferred to construction land, while only 2.2% remained as water bodies or wetlands. From 2015 to 2020, the trend of water body changes slowed down, with the proportions of conversion to arable land and construction land being 44.0% and 18.4% respectively, while the area of wetlands or water bodies remained at 16.3%. During the period of 2015-2020, the area of water bodies or wetlands converted to other land types increased by more than 14% compared to 2010-2015. This proportion reached more than 30% compared to the 13th Five-year Plan Period. (3) From 2010 to 2020, the spatial changes of landscape diversity (SHDI) and evenness (SHEI) of LUCC showed heterogeneous characteristics. In the high-altitude areas near the river basin boundary, the values of SHDI and SHEI were below 1.0. While in the low-altitude plain areas and urban areas with relatively frequent human activities, the values of SHDI and SHEI were above 1.0, and the values in urban areas could reach above 1.5. The evolution of ecosystem patterns in the upper and middle reaches of the Fenhe River Basin in the past decade has been clarified, providing a scientific basis for the construction and management of ecological environment governance and restoration projects in the Fenhe River Basin, and providing practical references for ecological protection and high-quality development practice in the Yellow River Basin.

In order to alleviate the conflict between populations and land-resource, Tianjin has adopted multi-phase reclamation projects to formed large-scale artificial reclamation land. However, the reclamation areas are susceptible to subsidence, which demonstrate a serious threat to infrastructure and people’s lives and property. The SBAS-InSAR was used to acquired surface deformation of Tianjin Binhai New Area from January 2017 year to December 2022 year, analyzed in depth the response relationship between land subsidence and reclamation projects time as well as the land use type. The results show that the Lingang Industrial Zone was the earliest to be reclaimed, with extensive reclamation completed by 2016 year, while Nangang Industrial Zone and Hangu Port started reclamation projects in 2009 year, some areas are still currently under construction. There is a strong correlation between surface deformation and reclamation time, the severe land subsidence occurred over newly reclaimed areas. Surface deformation gradually intensifies from west to east, the maximum surface settlement in Nangang Industrial Zone, Lingang Industrial Zone from the west to the east has changed from -50 mm to -890 mm,45 mm to -580 mm, respectively, reclamation area of Hangu Port with maximum surface deformation is -250 mm. Significant differences deformation among different land use types, which reclamation projects completed in the same time. Subsidence is positively correlated with surface load, in areas with higher surface loads, the surface settlement is also severer,the average surface settlement for the heavy shipyard, 67 grain storage tanks, 27 grain storage tanks, road, and bare land are -201 mm, -166 mm, -107 mm, -64 mm, and -43 mm, respectively. This study reveals significant differences of surface deformation in the reclamation completed at different times and the load is the main driving factor of settlement difference in the reclamation land completed at the same time. Which has important guiding significance for preventing and controlling geological disasters in the reclamation area and later development planning.

Sri Lanka is a top producer of premium quality concentrated latex (CL), which becomes a base material for dipped rubber products such as gloves and condoms. The processing of CL is resource-intensive, requiring significant amounts of energy, fuel, water, and chemicals. This process leads to various environmental issues such as wastewater pollution, malodor, and greenhouse gas emissions. Several environmental life cycle assessments (ELCA) have been conducted at international and local levels to address the aforesaid issues. However, ELCAs encapsulating different environmental impact areas on CL processing in Sri Lanka are absent. The study revealed that electricity usage was the main hotspot of the environmental burden, significantly impacting Abiotic depletion (fossil fuels), Global warming potential, Ozone layer depletion, Photochemical oxidation, and Acidification. Heavy reliance on coal in the Sri Lankan power grid was identified as the root of this trend. The study suggested two viable options to mitigate the environmental impact: installing inverters to centrifuge separators and solar systems in the factories. The second option was deemed more effective, reducing Acidification, Photochemical oxidation, and Global Warming Potential by approximately 37%, 36%, and 28%, respectively. Relevant officials may immediately consider these improvement options and collaborate to pave the way to a sustainable natural rubber industry.

Remote sensing methods have the potential to improve lake water quality monitoring and deci-sion-making in water management. This reviews introduces novel findings in the field of opti-cally active water quality parameters using remote sensing. It summarizes existing retrieval methods (analytical, semi-analytical, empirical, semi-empirical, and artificial intelli-gence/machine learning (AI/ML)), examines measurement methods used to determine concen-tration of specific water quality parameters, summarizes satellite systems that enable temporal data for understanding the state of the lake with focus on water quality parameters, and pro-poses enhancements for future research of lake water quality using remote sensing. As part of this review, eight optically active biological and physical water quality parameters were ana-lyzed, including chlorophyll-α (chl-α), transparency (Secchi disk depth (SDD)), colored dis-solved organic matters (CDOM), turbidity (TUR), electrical conductivity (EC), surface salinity (SS), total suspended matter (TSM), and water temperature (WT). The research proposes a shift from point-based data representation to a more reliable raster representation and encourages optimizing grid selection for in situ measurements by combining hydrodynamic model with re-mote sensing methods. This review presents a comprehensive summary of the bands, band combinations, and band equations per sensor for eight optically active water quality parameters as listed in Tables A1-A8. The review’s findings indicate that use of remotely sensed data is an effective method for estimating water quality parameters in lakes, with a significant increase in global utilization. The review highlights potential solutions and limitations to the challenges of remote sensing water quality determination in lakes.

Emerging pollutants pose significant threats to Uganda's ecosystems and public health amidst rapid urbanization, industrial growth, and intensified agriculture. This systematic review comprehensively assessed these pollutants by analyzing existing Ugandan literature and research studies, revealing various types in different environmental compartments. These pollutants, including pharmaceuticals, personal care products, pesticides, industrial chemicals, heavy metals, radionuclides, biotoxins, disinfection byproducts, hydrocarbons, and microplastics, originate from urban, industrial, and agricultural regions. Wastewater and improper waste disposal are major contributors. From an initial search of 794 articles across multiple databases such as PubMed, African Journal Online (AJOL), Web of Science, Science Direct, and Google Scholar, 138 were found relevant. The review underscores potential ecological and health impacts, including antibiotic resistance, endocrine disruption, and carcinogenicity. Existing monitoring and regulation efforts are discussed, alongside the need for specific regulations, improved data collection, and public awareness campaigns. Recommendations include advanced wastewater treatment, sustainable agriculture, and source control measures. Emphasis is placed on further research to address knowledge gaps and develop effective policies and interventions. Uganda can mitigate these risks by implementing comprehensive monitoring, robust regulations, and sustainable practices, safeguarding the environment and public health.

This study aims to explore the differences between loess and landslide deposits, focusing on as-pects such as particle distribution, consolidation characteristics, and dynamic shear modulus. Through a series of experiments, the research reveals the similarities and differences between these two entities, yielding several key findings. Firstly, the process of landsliding disrupts the original structure of the loess, resulting in a reduction in porosity and a densification of the soil. This alteration in structural properties leads to significant disparities in physical attributes be-tween landslide deposits and undisturbed loess. Additionally, the movement and sorting of par-ticles during landslides cause variations in particle size distribution across different sections of the landslide deposits. Secondly, the landslide process not only alters the soil's structure but also changes the particle sizes within the loess. Particle wear and sieving result in the transformation of larger particles into smaller ones, leading to a more uniform particle size distribution. This shift in structure and particle size directly impacts the consolidation characteristics of landslide deposits, resulting in a substantial reduction in compression coefficient. Despite undergoing consolidation for decades, the middle and lower sections of landslide deposits still exhibit un-der-consolidation. Although the differences in the maximum dynamic shear modulus between loess and landslide deposits at varying depths are relatively minor, differences in porosity and consolidation characteristics lead to faster decay rates of the dynamic shear modulus for the lat-ter. The study also highlights a reduction in the water sensitivity of the maximum dynamic shear modulus within landslide deposits. Based on experimental results, a predictive model is pro-posed, utilizing A and m values to estimate the maximum dynamic shear modulus of both loess and landslide deposits. In conclusion, this research uncovers the impact of landslide processes on the structure and properties of loess, providing insightful understanding into the disparities between these two entities.

The feasibility of using zeolites, synthesized from components found in municipal solid waste fly ash (MSW-FA), as sorbents for the recovery of nutrients (nitrate and phosphate) and heavy metals is critically assessed in this review. The inherent drawbacks of utilising a highly contaminated, variable, and relatively Al- and Si-dilute source such as MSW-FA to synthesize zeolites are discussed, and different methods to extract and decontaminate zeolite precursor materials from MSW-FA are considered. Ways to synthesize tailored zeolites and how their properties as well as the operational conditions impact the adsorption of cations such as ammonium and heavy metals are summarized. The use of surface-modified zeolites to adsorb nitrate and phosphate is also reviewed. And subsequently, approaches to utilise directly or recover for reuse the adsorbed compounds are considered, discussing potential challenges and mitigating measures related to leaching of unwanted compounds from the zeolites. Moreover, the possibility to regenerate the adsorption capacity of the zeolites for multiple adsorption cycles is considered. In the final chapter of the review a more general discussion of the main challenges and existing research gaps is provided, giving directions for recommended studies.

Revealing the multidimensional value of cultivated land resources, improving calculation methods, and exploring their spatial distribution characteristics and influencing factors are crucial for the enhancement of natural resource accounting system and the protection of cultivated land resources. This study take Guangxi, China as an example and construct a comprehensive multidimensional value evaluation system for cultivated land resources at the county scale. The income capitalization method, substitution market method, and value equivalent correction method were applied to calculate the economic, social, and ecological values of cultivated land resources in 111 counties. Furthermore, spatial autocorrelation analysis was employed to study their distribution characteristics and influencing factors. The results show that: (1) The total value of cultivated land resources in Guangxi reach 19,729.2 billion yuan, and the average cultivated land value is 5.3511 million yuan/hm2, of which the ratio of economic, social and ecological values is about 6:1:2; (2) The value of cultivated land has a certain distribution pattern in the global space, and the average economic and social value show the spatial distribution patterns of "low in the west and high in the east" and "low in the northwest and high in the southeast" respectively."(3) There is a significant spatial clustering effect of all values of cultivated land resources in local space, with "high-high" and "low-low" clustering. (4) Economic development level is significantly negatively correlated with the ecological value of cultivated land, while has a significant positive correlation with social value; (5) Natural conditions, economic development and agricultural development approaches are the key factors affecting the value of cultivated land resources.

The rapid growth of urban areas is a major challenge facing cities around the world. This growth can have a significant impact on the local climate, leading to higher temperatures and other changes. In desert climates, the effects of urban expansion can be particularly pronounced. This study investigated the impact of urban expansion on land surface temperature (LST) in Baghdad, Iraq. Notably, this study employs a sophisticated artificial intelligence method known as Random Forest for Land Use Land Cover (LULC) classification, utilizing three Landsat images spanning the temporal spectrum from 1985 to 2021 to meticulously monitor land use transformations and associated LST variations. The results showed that vegetated areas declined by 46.8% during the study period, while built-up areas increased by 124.7%. This decline in vegetation was accompanied by an increase in LST, with bare soil recording the highest temperatures. The study also found that LST has a strong inverse relationship with vegetation and moisture. This means that areas with more vegetation and moisture tend to have lower LSTs. These findings suggest that urban expansion can lead to higher LSTs in desert climates, which can have implications for the health and wellbeing of residents. The study has important implications for urban planners and policymakers in Baghdad and other cities in desert climates. By identifying the main factors that control LST, the study provides insights into strategies for mitigating the effects of urban expansion on temperature.

Landslide is one of the most common geological disasters in China, which is characterized by suddenness and uncertainty, and it is difficult to realize accurate identification, early warning and forecasting of landslide disaster by conventional means. With the development of high-resolution remote sensing satellites and InSAR surface deformation monitoring technology, the traditional means of landslide monitoring data sources are limited, and there is a lack of effective methods to excavate the characteristics of the spatial distribution of landslide hazards and their triggering factors and other issues. In this paper, the area extending 10 km outside the VII isobar of the Gengma earthquake is taken as the study area, and 13 evaluation factors are screened out by integrating the factors of InSAR surface deformation, topography and geological environment, and the Bayesian Optimized Convolutional Neural Network (BO-CNN) is used for the evaluation of landslide susceptibility, and the BO-RF and PSO-SVM models are selected for the comparative analysis. The model accuracy evaluation was carried out by three indexes: ROC curve, AUC value and FR value, in which the ROC curves of PSO-SVM, BO-RF and BO-CNN were all close to the upper-left corner of the corner, and the AUC values were 0.9388, 0.9529, and 0.9535, respectively, and the FR value of landslide in the high susceptibility area of BO-CNN was as high as 14.9, and was higher than that of PSO-SVM and BO-RF, respectively. SVM and BO-RF model is 4.55 and 3.69 higher, the experimental results show that the BO-CNN model used in this paper has a better effect in landslide susceptibility evaluation, and the research results of the local government's disaster prevention and mitigation measures are of great significance.

Solid waste has become a tenacious issue worldwide. It has been increasing exponentially due to urbanization and the increase in the population. Since the twentieth-century technological revolution, there have been significant changes in the composition of solid waste. It poses significant challenges for waste management systems worldwide. Waste management is the process of handling waste right from its creation to its final disposal, including transport, collection, treatment, and monitoring. The present solid waste management (SWM) system is affected by unfavorable institutional, economic, technical, legislative, and operational constraints. Poor waste management is affecting ecosystems and human health, damaging our finite natural resources, impeding human economic progress, and harming people's quality of life. Now, researchers are concerned about the environment's degradation, a decline in quality of life, and risks related to waste management grow as the volume of solid waste. So, they are focusing on sustainable waste management practices which will be crucial for creating a cleaner and healthier environment for future generations. This chapter focuses on the concept of solid waste, its types, management, and its effect on the health of humans and the environment.