Homogenization of climatic time series aims to remove non-climatic biases which come from the technical changes of climate observations. The method comparison tests of the Spanish MULTITEST project (2015-2017) showed that ACMANT was likely the most accurate homogenization method available at that time, in spite of the tested ACMANTv4 version gave suboptimal results when the test data included synchronous breaks for several time series. The technique of combined time series comparison has been introduced to ACMANTv5 in order to treat better this specific problem. Tests confirm that ACMANTv5 treats adequately synchronous inhomogeneities, but the accuracy has slightly worsened in some other cases. Results for a known daily temperature test dataset for 4 U.S. regions show that the residual errors after homogenization may be larger with ACMANTv5 than with ACMANTv4. Further tests have been performed to learn more about the efficiencies of ACMANTv4 and ACMANTv5, and to find solutions for the appearing problems with the new version. Planned changes in ACMANTv5 are presented in the paper along with connecting test results. The overall results indicate that the combined time series comparison can be kept in ACMANT, but smaller networks should be generated by the automatic networking process of the method. For the further improvements of homogenization methods and for obtaining more reliable and more solid knowledge about their accuracies, more synthetic test datasets mimicking fairly the true spatio-temporal structures of real climatic data would be in need.

The Pearl River Delta (PRD) has undergone complex geological development within a multi-island faulted basin, shaped by the interplay of regional tectonic movements, Quaternary sea-level fluctuations, and fluvial-marine interactions. Despite a great number of studies on the Holocene sedimentary sequences and spatial difference of lithofacies and environments, scant attention has been paid to the overarching human influence on deltaic evolution and coastline modifications since the Neolithic epoch. To further elucidate the spatial variation in Holocene sedimentation and its underlying basement topography shaped during the Last Glacial Maximum (LGM), we compiled a comprehensive dataset incorporating borehole data from over 2,800 cores within the PRD. Subsequently, high-resolution isobath maps of Quaternary deltaic deposits were generated, offering unprecedented insights into sediment distribution. This dataset facilitated a nuanced reconstruction of pre-Holocene topography, revealing a zone characterized by elongated, deep-incised valleys governed by NW-SE fault orientations. Further, we delineated coastline shifts since the period of maximum marine transgression (~7000 years BP), contributing to an enhanced understanding of the formation and evolutionary patterns of the delta and the river network oscillations. Our findings illuminate increasing anthropogenic impact on the rate of fluvial sedimentation and land growth, particularly accentuated over the last two millennia, favoring deltaic accretion. The current study has considerable implications for understanding the dynamic interplay between land-sea interactions and anthropogenic activities in shaping the delta, and stands to significantly inform land and resource management strategies, as well as future urban planning within the delta's bay areas.

A Gem-quality rubies and sapphires are often commercially heat treated at about 800°C or higher temperatures to enhance their colour and clarity, and hence quality. For this study, selected corundum samples containing diaspore- and goethite inclusions were heated step-by-step to a maximum of 1000 °C with the aim to monitor the dehydration and phase transformation of these oxyhydroxides to corundum and hematite during heating. Based on our experiments and in agreement with literature, the dehydration of diaspore in corundum occurs between 525 to 550 °C, whereas goethite transforms to hematite already between 300 and 325 °C. As both, diaspore and goethite are common inclusions in rubies, sapphires, and other corundum varieties, these dehydration reactions and phase transformations can be considered important criteria to separate unheated stones from heated ones, specifically in cases in which other methods (e.g. microscopy, FTIR) are unsuccessful.

White oak mortality is a significant concern in forest ecosystems due to its impact on biodiversity and ecosystem functions. Understanding the factors influencing white oak mortality, particularly the soil properties, is crucial for effective forest management and conservation efforts. In this study, we aimed to investigate the spatial pattern of white oak mortality and examine the influence of soil properties on mortality rates. Multicycle Forest Inventory and Analysis data were compiled to capture white oak plots across the eastern US. White oak mortality data were collected across plot systems that utilized Diameter at Breast Height between two periods. Soil variables were analyzed to assess soil properties. Spatial analysis techniques, including geostatistics and regression modeling, were used to analyze the relationship between white oak mortality and soil characteristics. Results found clustered spatial patterns of white oak mortality across a broad scale depicting the significant effects of coarser soil textures, nutrient-deficient sites, and extreme soil moisture levels. Our findings demonstrated the importance of soil properties in shaping the spatial pattern of the white oak mortality rate. This idea can inform forest management practices for the conservation of white oak populations. Future research is needed for comprehensive soil assessment including biotic and abiotic factors for forest management strategies at a broader scale aimed at mitigating white oak mortality.

Rice cultivation serves as a significant anthropogenic source of methane (CH4), a primary greenhouse gas, and nitrous oxide (N2O), a secondary greenhouse gas. Although N2O emissions remain relatively small compared to CH4 emissions, they are remarkably affected by nitrogen-fertilized soil conditions during rice cultivation. To date, investigations are very limited concerning N2O emissions from rice cultivation in relation to environmental factors such as temperature, rainfall, and soil properties. In this case study, we investigated the characteristics of N2O emissions in the central region of South Korea, where a single rice cropping cycle occurs annually over a span of three years, from May 2020 to May 2023. We investigated the impact of variations in temperature and soil moisture on N2O emissions during rice cultivation. In this context, we attempted to discover the complex dynamics of N2O emissions by comparing longer fallow periods with the rice cultivation periods and extended non-dry periods with irrigated periods. We observed that extremely high N₂O flux events encountered during the fallow period appeared to have a substantial impact on the yearly cumulative N₂O emissions, surpassing the impact of cumulative N₂O emissions during the rice cultivation period. We found that high N₂O flux events arose not only from artificial nitrogen inputs but also due to temperature and soil moisture variations influenced by weather conditions. We concluded that assessing N₂O emissions solely based on the rice cultivation period would underestimate annual emissions. To prevent underestimation of N₂O emissions, continual gas collection throughout a year covering both rice cultivation and fallow phases is required in align with monitoring of varying temperature and soil moisture conditions. Based on our findings, we recommend that at least a three whole year evaluation period is needed to ensure estimation accuracy of N₂O emissions under varying nitrogen fertilization rates. Also, the findings from this study would help prepare a further revision or refinement of N2O emission factor from rice cultivation in the national greenhouse gas inventories defined by the inter-governmental panel on climate change (IPCC).

Techniques and tools meant to aid fire management activities in the Cerrado, such as accurately determining fuel load and composition spatially and temporally, are pretty scarce. The need to have fuel information for more efficient management in a considerably heterogeneous, biodiverse, and fire-dependent environment makes a constant search for the improvement of the use of remote sensing techniques in determining fuel characteristics. This study presents the following objectives: (1) to assess the use of data from Landsat 8 OLI images to estimate the fine surface fuel load of the Cerrado during the dry season by adjusting multiple linear regression equations; (2) to estimate fuel load through Random Forest and k-Nearest Neighbor (k-NN) algorithms in comparison with re-gression analyses; and (3) to evaluate the importance of predictor variables from satellite images. Therefore, 64 sampling units were collected, and the pixel values associated with the field plots were extracted in a 3 x 3 pixel window surrounding the reference pixel. For the multiple linear regression analyses, the R² values ranged from 0.63 to 0.78, and the models fitted by the Random Forest al-gorithm ranged from 0.52 to 0.83, while those fitted by k-NN ranged from 0.30 to 0.68. Adopting the Random Forest algorithm resulted in improvements in the statistical metrics of evaluation of the fuel load estimates for Cerrado grassland relative to the multiple linear regression analyses.

Veterinary antibiotics (VAs) have been indiscriminately used in animal feed for the past five decades to increase and ensure profits with negligible environmental considerations. The VAs amoxicillin (AMX), chlortetracycline (CTC), and oxytetracycline (OTC), which can be unintentionally introduced by irrigation water during rice cultivation, were evaluated for their phytotoxic effects, absorption-translocation into plants, and soil residues using a randomized complete block design. It was found that exposure to VAs can severely affect the photosynthetic pathway of rice plants. The uptake and translocation of VAs by rice plants varied significantly. CTC and OTC translocated more easily than AMX, a member of the β-lactam class, which accumulated at the lowest concentration compared to CTC and OTC across all treatments. Rice yield was about 4.3 - 5.7% lower in the experimental plots that received fifty-fold the background levels of VAs compared to the control. The findings indicate that these widely used veterinary antibiotics can hamper crop production, leave residues in the soil, and constitute a risk to human health if introduced into the agro-ecosystem unintentionally.

Unmanned aerial vehicle (UAV) systems are widely used in many forest-related fields owing to their cost-intensive and precise surveying technology. This study classified erosion susceptibility (ES) in a timber harvesting area using machine learning (ML) and statistical approaches. In dataset generation for the training and testing process, the digital surface model (DSM) of difference (DoD) for July–June was utilized as a dependent variable, and six terrain maps of the DSM for June were used as independent variables. The ES threshold was set at 5 cm for the binary classification of ES pixels while processing using ML (e.g., random forest and extra gradient boost [XGB]) and statistical (e.g., logistic regression) algorithms for model development. The overall accuracy (OA), receiver operating characteristics, and area under the curve (AUC) were calculated for model accuracy and validation. Although the AUC of all models did not appear acceptable (AUC > 0.7), the XGB model showed the best performance regarding time duration, OA, and AUC by 2 h, 64%, and 0.63, respectively. Despite the low AUC and accuracy of the XGB model, the wheel tracks and edges of the operation road were determined to be susceptible areas in the ES map of the XGB.

Micro-nanoparticles' characteristics in geothermal fluids can be applied to detect of deep hidden geothermal resources. Observations using a nanoparticle tracking analyzer (NTA) indicated that the karst geothermal water collected in the central area of Shandong Province (Jinan and Zibo) contains many natural micro-nanoparticles with sizes primarily ranging between 100 nm and 5 μm. The micro-nanoparticles’ type, shape, crystal form, and chemical composition in the samples were analyzed using transmission electron microscopy (TEM). TEM images and energy dispersive spectroscopy showed that the micro-nanoparticles in geothermal water samples were mostly amorphous, irregular, or nearly spherical, with rough edges. The micro-nanoparticles were mainly carbonates, sulfates, and chlorine-containing Fe, Ca, Na, and Mg. The characteristics of the particles can reveal the properties of the deep, hot reservoirs and aquifers from where they originate. Therefore, we believe that natural micro-nanoparticles can be essential to detecting and studying deep, hidden geothermal resources, which is a novel approach to exploring deep, hidden geothermal resources.

The effects of wastewater step-feeding on the performance of Horizontal Subsurface Flow Constructed Wetlands (HSF CWs) are numerically investigated. The purpose is to check if this alternative feeding technique increases the ability of HSF CWs to remove pollutants. Two methodologies are used: Initially, the Tanks-In-series (TIS) methodology, based on Finite Volume Method (FVM), is analyzed by using the volumetric degradation coefficient λ. In this case the operation of CW is similar with a series of Continuous Stirred-Tank Reactors (CSTR), under steady conditions. Then, the Step-Feeding (SF) procedure is presented, when the CW is operated like a Plug Flow Reactor (PFR). The results show that the SF procedure does not improve the performance of HSF CWs on removing Biochemical Oxygen Demand (BOD), operating under Mediterranean conditions.

Water resource pollution, particularly in river channels, presents a grave environmental challenge that necessitates a comprehensive and systematic approach encompassing assessment, forecasting, and effective management. This article provides a comprehensive exploration of the methodology and modeling tools employed to scrutinize the process of river channel pollution due to silting, rooted in the fundamental principles of hydrodynamics and pollutant transport dynamics. The study's methodology seamlessly integrates numerical simulations with state-of-the-art neural network techniques, with a specific focus on the Physics-informed neural networks (PINN) method. This innovative approach represents a groundbreaking fusion of artificial neural networks (ANN) and physical equations, offering a more efficient and precise means of modeling a wide array of complex processes and phenomena. The proposed mathematical model, grounded in the Euler equation, has been meticulously implemented using the Ansys Fluent software package, ensuring accuracy and reliability in the computations. In a pivotal phase of the research, a thorough comparative analysis was conducted between the results derived from the PINN method and those obtained through conventional numerical approaches using the Ansys Fluent software package. The outcomes of this analysis revealed the superior performance of the PINN method, characterized by the generation of smoother pressure fluctuation profiles and significantly reduced computation time, underscoring its potential as a transformative modeling tool. The calculated data originating from this study assumes paramount significance in the ongoing battle against river sedimentation. Beyond this immediate application, these findings also serve as a valuable resource for creating predictive materials pertaining to river channel silting, thereby empowering decision-makers and environmental stakeholders with essential information. The utilization of modeling techniques to address pollution concerns in river channels holds the potential to revolutionize risk management and safeguard the integrity of our vital water resources. However, it is imperative to underscore that the effectiveness of such models hinges on ongoing monitoring and frequent data updates, ensuring that they remain aligned with real-world conditions. This research not only contributes to the enhanced understanding and proactive management of river channel pollution due to silting but also underscores the pivotal role of advanced modeling methodologies in the preservation of our invaluable water resources for present and future generations.

The Dst index is the geomagnetic storm index used to measure the energy level of geomagnetic storms, and the prediction of this index is of great significance for the geomagnetic storm study and the solar activity. In contrast to traditional numerical modelling techniques, machine learning, which has emerged in decades ago based on rapidly developing computer hardware and software and artificial intelligence methods, has been unprecedentedly developed in geophysics, especially solar-terrestrial space physics. This study chooses two machine learning models, the LSTM (Long-Short Time Memory, LSTM) and EMD-LSTM model (Empirical Mode Decomposition, EMD), to model and predict the Dst index. By building the Dst index data series from 2018-2023, two models were built to fit and predict the data. Firstly, we evaluated the influences of the learning rate and the amount of training data on the prediction accuracy of the LSTM model, and finally, 10-3 was thought as the optimal learning rate; secondly, the two models were used to predict the Dst index in the solar active and quiet periods, respectively, and the RMSE (Root Mean Square Error) of the LSTM model in the active period is 7.34 nT, the CC (correlation coefficient) is 0.96, those of the quiet period are 2.64nT and 0.97; the RMSE and r of EMD-LSTM model are 8.87nT and 0.93 in active time and 3.29nT and 0.95 in the quiet time. Finally, the prediction accuracy of the LSTM model in short time period is slightly better than the EMD-LSTM model. However, there will be a problem of prediction lag, which the EMD-LSTM model can then solve, and can better predict the geomagnetic storm.

The global construction sector contributes a significant share of total greenhouse gas (GHG) emissions. In Australia, infrastructure activity alone generates 18% of the GHG emissions budget. The use of low-embodied carbon building materials is crucial to achieving sustainability in the construction sector and to fulfill national and international climate goals. Industrial hemp (Cannabis sativa L.) is considered a promising feedstock for sustainable construction materials because of its biogenic carbon content, fast-growing cycles with low agricultural input requirements, and technical functionality which is comparable to traditional materials. This study has applied the life cycle assessment (LCA) guideline of ISO 14040:2006 to estimate the carbon footprint (CF) expressed in carbon dioxide equivalent (CO2eq) emissions of hemp-based building materials in Western Australia. The functional unit is 1 m2 of hemp-based board, and the system boundary includes cradle-to-gate stages, i.e., pre-farm, on-farm, and post-farm activities. The production of 1 m2 of hemp-based board is estimated to be - 2.302 kgCO2eq. Electricity from the public grid for lignin extraction during the post-farm stage is the main contributor to total CO2eq emissions (26%), followed by urea production (14%) during the pre-farm stage. Overall, the use of electricity from the SWIS during the post-farm stage accounts for 45% of total emissions. Sensitivity analysis shows that the CF of hemp-based boards is highly sensitive to the source of energy, i.e., total replacement of the SWIS by solar power decreases the CF from - 2.30 to -6.07 kgCO2eq (164%). The results suggest that hemp-based boards exhibit lower embodied GHG emissions compared to traditional materials, such as gypsum plasterboards.

This research explored the influence of spatiotemporal variations in phreatic levels and salinity on the patterns and interactions of soil mesofauna communities in a tropical urban coastal wetland. It delineated significant variations in phreatic levels and salinity, with distinct regimes characterizing different habitats and hydroperiods. A total of 120 mesofauna morphotypes across 42 taxa were identified, revealing habitat differences and similarities, and the ecosystem biodiversity. Moderate correlations were established between phreatic levels, salinity, and mesofauna richness and abundance, with habitat type and phreatic level emerging as significant predictors in the regression model. Our findings indicate that shallow phreatic levels in conjunction with oligohaline salinity conditions foster a more favorable abiotic environment, thereby promoting increased biodiversity. The study underscores the dynamic and adaptive nature of mesofauna communities in response to changing environmental conditions, offering valuable insights for effective costal urban wetland management, particularly in the context of multiple stressors such as global and regional climate change, sea level rise, and human activities. The bio-sensor capacity of soil mesofauna emerges as a vital tool for monitoring and facilitating adaptive ecosystem management, thereby ensuring their long-term health and sustainability.

In recent years, a large-scale afforestation campaign has taken place in Inner Mongolia, China, to control desertification and soil erosion. However, the water consumption associated with large-scale afforestation significantly impacts the water resources in Inner Mongolia, resulting in a substantial ecological risk. This study aimed to evaluate the ecological risk of water resources caused by afforestation in the region. In this study, based on land cover data, Normalized Difference Vegetation Index (NDVI) data, and meteorological data, used trend analysis, water balance equation, and Water resources Security Index (WSI) index to analyze the ecological risks of water resources caused by afforestation in Inner Mongolia from 2000 to 2020. The results show that:(1) The afforestation area in Inner Mongolia was 5.37×104 km2 in 2000-2020; (2) Afforestation in arid and semi-arid areas leads to the reduction of water resources. (3) Afforestation reduces water resources in the study area by 0.76×108m3/year; (4) ~76% of afforestation regions face ecological risks of water resources.

The production of high-quality wines is one of the primary goals of modern oenology. In this regard, it is known that the potential quality of a wine begins to be determined in the vineyard, where the quality of the grape, initially, and later that of the wine, will be influenced by the soil properties. Given the spatial variability of the fundamental soil properties related to the potential grape production, such as texture, soil organic matter content, or cation exchange capacity, it seems that a uniform management of a vineyard is not the most optimal way to achieve higher grape quality. In this sense, the delineation of zones with similar soil characteristics to implement site-specific management is essential, reinforcing the interest to incorporate technologies and methods to determine these homogeneous zones. A case study was conducted in a 3.3 ha vineyard located near Évora, South of Portugal. A non-contact sensor (DUALEM 1S) was used to measure soil apparent electrical conductivity (ECa) in the vineyard, and later, a kriged ECa map was generated. ECa and elevation maps were utilised to delineate homogeneous zones (management zones, MZs) in the field through a clustering process. MZs were validated using some soil properties (texture, pH, organic matter -OM, phosphorous -P2O5, potassium -K2O, sum of the exchange bases -SEB; and cation exchange capacity -CEC) which were determined from 20 soil samples taken in the different MZs. Additionally, validation was also performed using Rasch measures, which were defined based on the formula-tion of the objective and probabilistic Rasch model, integrating the information from the afore-mentioned soil properties at each sampling location. The comparison of the MZs was more evident with the use of the Rasch model, as only one value was to be employed in each MZ. The use of ECa constitutes an efficient technological tool for implementing site-specific man-agement in viticulture, which allows for the improvement of decision-making processes by con-sidering the inherent spatial variability of the soil.

Towards better understanding of factors controlling carbon (C) exchange between inland waters and atmosphere, we addressed inorganic carbon cycle in semi-arid lakes of Central Eurasia, subjected to strong impact of on-going climate change. For this, we assessed the hydrochemical vari-ability and quantified its control on formation of authigenic carbonate minerals, occurring within the upper layer of sediments in 43 semiarid lakes located in the southwest of Western Siberia (Central Eurasia). Based on measurements of pH, total dissolved solids (TDS), cationic and anionic composition, dissolved organic and inorganic C, as well as textural and mineralogical characterization of bottom sediments using X-ray diffraction and scanning electron microscopy, we demonstrate that lake water pH and TDS are primarily controlled by both lithological and climatic context of the lake watershed. We have not revealed any direct relationships between lake morphology and water chemistry. The most common authigenic carbonates scavenging atmospheric CO2 in the form of insoluble minerals in lake sediments were calcite, aragonite, Mg-calcite, dolomite and hydro-magnesite. The calcite was the most common component, aragonite mainly appears in lakes with sediments enriched in gastropod shells or artemia cysts, while hydromagnesite was most common in lakes with high Mg/Ca molar ratios, as well at high DIC concentrations. The relationships between mineral formation and water chemistry established in this study can be generalized to a wide suite of arid and semi-arid lakes in order to characterize current status of inorganic C cycle and predict its possible modification under on-going climate warming such as water temperature rise and change of hydrological connectivity, primary productivity and nutrient regime.

Abstract: This study observes the characteristics and influencing factors of carbon fluxes of the Momoge salt marsh ecosystem over four years, which behaves as a CO2 sink. The daily, seasonal, and interannual variations of CO2 fluxes in the Momoge salt marshes were observed using the eddy covariance method and compared with various environmental factors. An overall daily “U” shaped distribution was observed, with uptake during the day (negative values) and release at night (positive values). Annually, the carbon fluxes in the study area roughly exhibit a “V” shape. Carbon fluxes during the non-growing season predominantly showed positive values, indicating the release of CO2 into the atmosphere. Photosynthetically active radiation was the primary influencing factor affecting hourly and daytime variations in net ecosystem exchange (NEE) during the growing season, while temperature was the main factor influencing nighttime NEE dynamics. Air temperature, soil temperature, photosynthetically active radiation, precipitation, and water level all had significant impacts on daily net CO2 exchange. At the monthly scale, larger values of soil temperature, air temperature, photosynthetically active radiation, and aboveground biomass correspond to a stronger carbon absorption capacity of the ecosystem. Overall, temperature remains the primary factor for carbon fluxes in the Momoge wetlands.

Accurate forecast of tail water level (TWL) is of great importance for the safe and economic operation and management of hydropower stations. The predictive performance is significantly influenced by the backwater effect of downstream hydropower stations and tributaries, but the explicit quantification method of the backwater effect is lacked. In this study, a deep learning model based forecasting framework for TWL predictions is established and applied to forecast TWL of Xiangjiaba (XJB) hydropower stations, which is influenced by the backwater effect of downstream tributaries including Hengjiang River (HJR) and Minjiang River (MJR). Firstly, the lag time of the backwater effect of HJR and MJR is analyzed based on the permutation importance. The results demonstrate that the lag time of backwater effect on the TWL of XJB is 5-7 hours for the HJR and 1-2 hours for the MJR. Then, the runoff thresholds of the HJR and MJR for impacting the TWL of the XJB station are obtained by scenario comparison, and the results show that the thresholds of HJR and MJR are 700 m3/s and 7000 m3/s respectively. Finally, the deep learning methods based TWL forecasting model is established based on the lag time and threshold analysis. The model is used to forecast the TWL in future 48 hours. The results show that the forecasting model has a good predictive performance with 98.22% of absolute errors less than 20 cm. The mean absolute error over the validation dataset is 5.27 cm and the maximum absolute error is 63.35 cm.

Super Typhoon Saola came very close to Hong Kong on 1 and 2 September 2023, necessitating the issuance of No. 10 hurricane signal, the highest tropical cyclone warning signal, in Hong Kong. While there were widespread damages in Hong Kong, no people were killed in the event with effective early warning. It is rare that a super typhoon came very close to Hong Kong and this paper is the first part in the series of the documentation of Saola to summarize the interesting observations of Saola near Hong Kong for future reference by weather forecasters, including sur-face observations, upper air observations, microburst alert from weather radars, and turbulence intensity based on spectral width measurement of radars.

Soil washing is a rapid and efficient method for heavy metals removal. In this study, in order to prove the feasibility of leaching remediation technology for remediation of lead-contaminated soil around a smelter, intermittent oscillating washing tests and extensive continuous tests were conducted to remediate Pb contaminated soils. Plant growth tests with wheat (Bainong Aikang 58) were also conducted to investigate the effects of leaching on plant growth and the Pb content of stems and leaves. The results revealed that in soils, Pb mainly exists in the forms of PbCO3, Pb5(PO4)3Cl2, PbSO4, and in small amounts of PbS. The intermittent oscillating washing tests showed that a lower liquidsolid(L/S) ratio and a higher leaching temperature and time were related to increased Pb removal efficiency. The Pb removal efficiency rates in the oscillating washing tests and the extensive continuous tests were 72.50% and 69.94%, respectively. In addition, the chemical and physical characteristics of the soil were basically unchanged after the leaching regimes. The results of the plant growth tests showed that the leaching regimes did not have a negative effect on the survival rate and growth of the wheat, and the heavy metal contents of the stem and leaf were effectively reduced. This study provides a reference for the large-scale remediation of contaminated soils.

The aim of this study is to examine an efficient and environmental friendly process for hydrolyzing starch, an industrial-derived by-product of the potato processing industry, and to use the produced hydrolysates as substrates for methane production. A full factorial experiment was designed and the optimal concentrations of FeSO4·7H2O, H2O2 and temperature were determined obtaining a yield of 99.5%, with a total carbohydrates content equal to 28.65 g, when the input parameters were at their high level: FeSO4·7H2O 1.00g/L, H2O2 0.51 g/L and temperature 70.0oC. The hydrolysis kinetics were also examined revealing that temperature was the most important factor among the three optimization parameters. Furthermore, biodegradability tests were carried out to measure the methane production potential from the produced hydrolysates. The specific methanogenic activity was reached 0.669 g CODCH4/gVSS-day proving the effectiveness of the hydrolysis process and highlighting the potential of this food manufacturing by-product for bioenergy production. A preliminary cost analysis showed that a small investment for utilizing the starch in an existing wastewater treatment facility of a potato processing industry becomes profitable before the end of the 3rd year obtaining a NPV 37.5% higher than the NPV of the current utilization scenario.

The current deformation and stable state of slopes with historical shatter signs is a concern for engineering construction. Suspected landslide scarps were discovered at the rear edge of the slope of the Genie in the Sichuan-Tibet transportation corridor during a field investigation. In order to qualitatively determine the current status of the surface deformation of this slope, this paper uses high-resolution optical remote sensing, airborne LiDAR and InSAR technologies for comprehensive analysis. The interpretation of high-resolution optical and airborne LiDAR data revealed that the rear edge of the slope exhibits three levels of scarps. However, no deformation was detected with the D-InSAR analysis of ALOS-1 radar images from 2007 to 2008 or with the Stacking-InSAR and SBAS-InSAR processing of Sentinel-1A radar images from 2017 to 2020. A geological model of the slope was established in combination with field investigation stipulating that the slope is composed of steep anti-dip layered dolomite limestone and that the scarps at the rear edge of the slope were caused by historical shallow toppling. Further research is recommended to determine the extent of toppling deformation and evaluate the slope stability under the disturbance of tunnel excavation.

The main aim of this work is to compare and characterize the state of decay developed in a set of 14 monuments, including churches and Pazos (Galician traditional house) of the architectural heritage of the Barbanza Peninsula (Galicia), considering its relationship with the influence of the environmental factor. A macroscopic inspection was carried out to determine the deterioration patterns. The most reported pathology across the peninsula, due to the moisture regime, was the formation of dark areas (generally as biofilms) and the lichen growth (biological colonization). Depending on the proximity to the coast, the study area was divided into two zones. Zone 1, closer to the sea (<1 km) with an important influence of sea salts and wind and zone 2, further from the sea with higher altitudes (center of the peninsula) and important rainfall, humidity and therefore, fauna growth. Crusts (to a lesser degree, because it is a mainly rural area) are more frequent in zone 1, but the state of conservation of stone is better than in zone 2 due to the concentration of urban centers that require aesthetics and constant maintenance. In zone 2, however, abandonment is greater and biological colonization (mainly by lichens and plants) is more developed along with deterioration patterns due to biological damage. The synergy of several factors such as salt, climatic conditions and spatial characteristics of the architectural heritage studied define the degree of deterioration of each heritage objective. The research has a potential contribution to the conservation measures to be undertaken.

In situ aircraft observations in typhoons have been scarce. This paper documents and analyses the aircraft and dropsonde data collected in Super Typhoon Saola (2023) over the northern part of the South China Sea. The wind and turbulence structures of the typhoon are investigated. The turbulence intensities are quantified in terms of turbulent kinetic energy (TKE) and eddy dissipate rate (EDR), and these data are compared with other available estimates of turbulence intensities, such as those based on weather radars, meteorological satellites, and numerical weather predic-tion (NWP) models. It is found that the TKE and EDR are closely correlated, and they are con-sistent with the weather radar/satellite observations as well as NWP-based outputs. Furthermore, the boundary layer inflow, vertical wind profiles, and atmospheric stability are analysed based on the dropsonde observations. The analysed results would advance the understanding of typhoon structures and offer references for the validation of remote sensing observations and NWP models.

The process of rainfall interception by tree organs is crucial in mitigating the impact of intense rainfall on urban drainage systems, particularly in the context of climate change. this study selected ten commonly found tree species in Shanghai. Main parts of trees, including leaves, branches, and bark, were collected to analyze their ability to intercept rainwater. The optimized Artificial Rainfall Simulation System (ARSS) was applied to simulate the rainfall. The time-changing process of rainwater interception in three organs was measured during a 180-minute rainfall event which under four different rainfall intensities (4, 8, 12, and 16 mm/h, respectively). Process models of rainwater interception in different organs were fitted with adsorption kinetic equations. The rainwater interception process of tree organs complied with the quasi 2nd-order adsorption kinetic equation. The rainwater interception capacity of leaves, branches, and bark of ten urban tree species ranged from 0.05 to 0.34 mm, 0.13 to 0.24 mm, and 0.29 to 1.22 mm, respectively. The rainwater interception capacity of three organs significantly differs (p<0.05). It reveals that bark exhibits the highest rainwater interception ability. Coniferous tree species have a greater ability to intercept rainwater than broad-leaved tree species. There are also differences in the rainwater interception ability of trees in urban and natural areas.

The phosphogypsum (PG) pile of solid waste is of immense proportions and poses a grave threat to the ecological environment, with its reserves steadily increasing year after year. The urgent need for large-scale consumption and high-quality utilization of PG in industrial production has become apparent. The present study provides a comprehensive analysis of the correlation be-tween the macroscopic mechanical properties and microstructure of PG, elucidating the crystal morphology characteristics in different phases and outlining the crystallization preparation pro-cess. By integrating the physical and chemical properties of diverse PG phases with the intricacies associated with its preparation process, it is imperative to explore avenues for its high-value utili-zation, investigate possibilities for industrial-scale production, and analyze and predict the appli-cation trends and developmental directions in comprehensive PG utilization. These endeavors hold immense significance in guiding the realization of resource utilization potential inherent in PG.

The Silk Road pattern (SRP) and Circumglobal teleconnection pattern (CGT) are two well-known teleconnection patterns along the Eurasian westerly jet during boreal summer, which are often regarded as one teleconnection pattern. In view of the distinct features of the SRP/CGT on the interannual (IA) and interdecadal (ID) timescales, the present study investigates the linkages and differences between the SRP and CGT on the two timescales. On the IA timescale, the SRP and CGT feature a similar circumglobal wave train structure with strong and significant centers over Eurasia, but show clear independences. Specifically, the SRP and CGT illustrates largely the mid-/high-latitude-related and tropics-related parts of the Northern Hemisphere upper-tropospheric circulation variations, respectively. Also, the CGT shows a stronger connection to the Indian summer monsoon (ISM) heating and El Niño–Southern Oscillation than the SRP, which makes the CGT more like a tropical-forcing-driven atmospheric mode but the SRP more like an internal atmospheric mode. The linkages and differences between them are associated with their asymmetry relationship during their positive and negative phases, which are attributed mainly to the asymmetry impact of the ISM heating/cooling on the Eurasian circulations. On the ID timescale, the SRP and CGT are characterized by a coherent two-wave train structure over Eurasia, and feature more like the same teleconnection pattern, which are associated with the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation. The present findings on the linkages and differences between the SRP and CGT are helpful to understand the variability and prediction of the SRP and CGT.

: Sulfate presence is of great importance for anaerobic digestion as its addition can control the anaerobic microbial community. In this study, the effect of sulfuric acid addition on the perfor-mance of an UASB reactor fed with hydrolyzed starch was investigated. TOC, Fe and SO4-2 re-moval as well as the methane production were monitored under various COD/ SO4-2 ratios, HRTs and OLRs. When HRT was 16 hours and OLR equal to 2 g COD/LUASB-d the methane production was 0.24 L CH4/LUASB-day. After the sulfuric acid addition, TOC removal reached 95%. At HRT, OLR, and COD/ SO4-2 ratio equal to 16 hours, 2 g COD/ LUASB-d and 3.72 respectively, the methane production was 0.267 L CH4/LUASB-d. When the OLR was increased to 5.94 g COD/LUASB-d and COD/SO4-2 ratio was equal to 12.5, the methane production was 3 times higher (0.84 L CH4/LUASB-d) with a methane content in the produced biogas greater than 70%. 16s rRNA gene analysis demonstrated that after the sulfate addition, SRB were enriched and methane was mainly produced by Methanosaeta sp. This study indicates that appropriate sulfate concentrations in the feed in combination with the presence of iron in the UASB reactor lead to enhanced me-thane yields.

Land surface temperature (LST) is a crucial parameter in climate and ecology, exerting significant influence on meteorological conditions, ecosystems, and human life. LST data sources are diverse, with remote sensing being the prevailing means of acquisition. FY-4A/AGRI offers high-quality LST products for East Asia. In this study, we evaluated the performance of the product in Hunan Province and conducted refined analysis of surface heat resources based on the 4km/1h resolution product over a two-year period. The results demonstrate that the FY-4A LST product effectively captures surface temperature (R=0.893), albeit with a relatively high error level (Bias=-6.295℃; RMSE=8.58℃), particularly in capturing high LST values. The performance of this product is superior in the eastern flat terrain area of Hunan Province compared to its performance in the western mountainous region due to environmental conditions causing systematic errors that contribute to instability in detection deviation for this product. Surface heat resources are more abundant in eastern Hunan Province than in mountainous areas located west and southwardly, and the detailed distribution of them at finer scales is mainly influenced by the terrain and climate conditions. There is no obvious seasonal difference in the distribution of heat resources except in winter, and rapid urbanization within Chang-Zhu-Tan urban agglomeration during two years has significantly altered the spatial distribution pattern of surface heat resources across Hunan Province. These findings provide a quantitative baseline for assessing FY-4A satellite's detection capability while serving as a reference for further application of its LST products and establishing foundations for divisional classification and utilization strategies pertaining to surface heat resources within Hunan Province.

In several Indonesian tropical cities, such as Makassar City, frequent flooding during the peak rainy season poses a significant challenge. This study seeks to address this issue by devising effective policies to reduce flood exposure. The main obstacle lies in accurately determining the flood inundation area. To overcome this, the study utilizes multiple satellite data sources on a cloud platform, integrating them with land use data, and DEM data, aligning these with the local government's urban land use plan and existing drainage networks. The research aims to quantify the affected area, identify the predominant inundated land cover, and assess the efficiency of Makassar's drainage system and urban land use plan. The study reveals that an uncoordinated drainage system in the Tamalanrea, Biringkanaya, and Mangala sub-districts results in severe flooding, encompassing a total area of 35.28 km². The most affected land use type is cultivation, constituting approximately 43.5% of the flooded area. Furthermore, 82.26% of the urban land use plan, covering 29.02 km², is submerged. It is imperative for the local government and stakeholders to prioritize the enhancement of drainage systems and urban land use plans, particularly in low-lying and densely populated regions

Hong Kong was under strike from Super Typhoon Saola (2309), necessitating the issuance of the highest tropical cyclone warning signal. Saola skirted past the south-southwest of Hong Kong, bringing hurricane force winds and significant storm surge. Saola had its closest approach to Hong Kong on 1 September 2023, posing a unique challenge in forecasting and early warning for the commencement date of the new school term, where higher impact to traffic and public safety was anticipated. This paper covers the challenges on the forecasting aspect of the super typhoon. The predicted tropical cyclone track, intensity and wind structure are reviewed. Experience in this case showed that while there was not a perfect numerical weather prediction model in terms of the forecast track, intensity and wind structure of Saola, multi-model approach provided very use-ful and crucial information for operational weather warning services.

Morphological study of lakes defines the sensitivity of their watershed. Moreover, it plays important role in safeguarding the lake’s ecosystem services through proper planning and utilization of the lakes’ resources. In the last few decades, the morphology of lakes in Ethiopian and Kenyan Rift (EKR) valley are experiencing contradicting morphological changes. Being in the same system, some are shrinking and others are expanding beyond their natural boundaries. The objective of this review is to shed light on the trends in spatio-temporal water level fluctuation and their contributing factors for lakes to the academia and decision makers. Peer reviewed article journals, conference proceedings, thesis, and book chapters collected from online sources and supplied by authors on request formed a database of 346 documents where 226 are critically assessed. The review indicated that lakes in Ethiopian rift are shrinking and expanding, while Kenyan lakes are expanding. The en-dorheic lakes suffered the most fluctuations due to anthropogenic factors at the expense of loss of forest and woodlands in their watershed. While the lakes’ water quality related to the morphological changes are given less attention, the predicted 12 m drop of Lake Turkana due to projects in the Omo catchment did not materialize.

Flood modeling and forecasting are key to managing and preparing for extreme flood events. Hydrological flood forecasting aims to predict the system response to different input changes with minimum uncertainties. In that sense, streamflow Data Assimilation (DA) seeks to combine errors between hydrological model and water discharge observations through the update of model states. This paper aims to assess a sub-daily flood forecast system in a basin of the Peruvian Tropical Andes using two sequential data assimilation algorithms called the Ensemble Kalman Filter (EnKF) and the Particle Filter (PF). The study was conducted in the Vilcanota River basin during the rainiest months in 2022 to assess recent potential river floods. This basin is in the southern Peruvian Andes and was selected because it is continually affected by river floods such as occurred in 2010. For this purpose, the lumped GR4H rainfall-runoff model was run forward with 100 ensemble members using two different Satellite Precipitation sources (IMERG-E' and GSMaP-NRT'). Also, four DA experiments (IMERG-E'+EnKF, IMERG-E'+PF, GSMaP-NRT'+EnKF, and GSMaP-NRT'+PF) were conducted by assimilating real-time hourly discharges at the Pisac stream gauge station to examine the improvement of forecast accuracy for lead times of 1—24 hours. Results display good forecast performances during the first 10 hours, especially for the GSMaP'+EnKF scheme. Finally, this work benchmarks the application of streamflow DA in and Andean basin of Peru with sparse data availability and will support the development of more accurate climate services in Peru through hydrologic ensemble predictions.

In the land use planning framework in the neighbourhood of industrial facilities, the current approach to predicting the consequences of massive toxic gas releases is generally based on Gaussian or integral models. For many years, CFD models have been more and more used in this context, in accordance with the development of High-Performance Computing (HPC). The present paper focuses on harmonizing input data for Atmospheric Transport and Dispersion (AT&D) modelling between the widely used approaches. First, a synthesis of the practice’s harmonization for atmospheric dispersion modelling within the framework of risk assessment is presented. Then, these practices are applied to a large-scale INERIS ammonia experimental release. For illustration purposes, the impact of the proposed harmonization will be evaluated using different approaches: the SLAB model, the FDS model and the Code_Saturne model. The two main focuses of this paper are the adaptation of the source term dealing with a massive release and the wind flow modelling performance using an experimental signal for CFD models inflow. Finally, comparisons between the modelling and experimental results enable checking the consistency of these approaches and reinforce the importance of the input data harmonization for each AT&D modelling approach.

Calabar is a city where 65 per cent of people are living in poverty in informal settlements with low and decreasing access to improved water. In the low-income informal areas of the city, residents are being made responsible for securing their own water supply through several coping strategies. This paper explores the decreasing access to water and coping strategies to shortage in Calabar, Nigeria. It analyses two complementary pieces of data: (i) the households’ coping strategies and (ii) satisfaction with improved water services. A mixed method was introduced and data was collected via fieldwork at three settlements in Calabar. A household survey of 360 respondents, 27 in-depth interviews and 2 focus groups were conducted. Findings show that households engaged in different coping strategies to access water, including conservation (changing routine/reusing), purchasing (spent a significant proportion of their income on buying water) and pumping as a coping strategy. The household's tenure, socioeconomic status and water accessibility determines their decision to move if services are not provided. A crucial differentiation exists between a larger population being granted less access to water versus certain individuals receiving access to a greater quantity of water.

The interactions of metal ions with fulvic acids resulted in changes in the particle size and charge. Particle size distribution was trimodal for fulvic acids, bimodal for fulvic complexes with calcium and magnesium, and copper-fulvic complexes had only one size fraction. The compensation of negative charge of carboxylic and phenolic functional groups by positive charged metal ions resulted in the increase in zeta potential which was getting closer to zero in the case of copper-fulvic complexes. However, all metal humic complexes behaved as colloidally unstable which resulted in visually observable sedimentation. Calorimetric measurements provided positive values of changes in enthalpy which indicated endothermic processes. In contrast quantum chemical calculations as well as experiments with model compounds provided negative values indicated exothermic processes. Changes in Gibbs energy were determined as negative and changes in entropy as positive which meant spontaneous processes.

Freshwater lakes represent a potential source of methane (CH4) to the atmosphere. However, the CH4 emission contribution to the total emission in the littoral zones of lakes, especially emergent macrophytes (e.g., lotus), are poorly known. Lotus, has been cultivated in almost all provinces in China, is not only an aquatic plant but also a kind of vegetables. Two sampling zones (lotus plant and open water) were established in the lake of the middle reaches of Yangtze River. The CH4 emission was measured using a floating opaque chamber and gas chromatography between April to December of the years 2021 and 2022. The results indicated that the flux of CH4 emissions ranged from 0.10 to 59.75 mg m-2 h-1, with an average value of 5.61 mg m-2 h-1 in the open water, while ranged from 0.19 to 57.32 mg m-2 h-1, with an average value of 17.14 mg m-2 h-1 in the lotus plant zone. The maximal CH4 emissions occurred in July and August for the open water, which was highly related to the air and water temperature; whereas it happened in September for the lotus plant zone, due to the fresh organic matter inputting to sediments, CH4 transportation by lotus plant, high soil organic carbon content, and the lower dissolved oxygen concentration. Considering the carbon emissions (both CH4 and CO2) and plant productivity, although the greater CH4 emission occurring in lotus plant zone, it could still represent a potential carbon sink (213 g m-2 yr-1), compared to the open water.

This study assesses coastal flooding extension mapping based on two innovative approaches. The first is based on the coupling of two robust numerical models (SWASH and LISFLOOD), in this case, discharges were extracted from the wave overtopping results from SWASH 1D and set as boundary conditions for LISFLOOD on the crest of an existing seawall where overtopping typically occurs. The second, hereby called the ‘Tilted Bathtub Approach’ (TBTA), is based on wave run-up levels and buffering the affected area of a prior flooding event, adjusting it for expected sea-states according to different return periods. The proposed approaches are applied to a case study on the Northern Portuguese coast, at Furadouro beach, in the municipality of Ovar, which has been facing multiple flooding episodes throughout recent years, including a dramatic storm in February 2014. This event was used as validation for the proposed methods. A 30 years long hourly local wave climate time series was used both to perform an extreme value analysis in order to obtain expected sea-states according to different return periods, and also for performing a sensitivity test for established empirical formulas to estimate wave run-up at this particular case. Results indicate both approaches are valuable: they yield coherent flood extension predictions that align well with the real inundated area from the 2014 storm. The convergence of these findings underscores the potential for these methods in future coastal flood risk assessment and planning.

Monitoring snowmelt dynamics in mountains is crucial to understand water releases downstream. Sentinel-1 (S-1) synthetic aperture radar (SAR) has become one of the most widely used techniques to achieve this aim due to its high frequency of acquisitions and all-weather capability. This work aims to understand the possibilities of S-1 SAR imagery to capture snowmelt dynamics and related changes in streamflow response in semiarid mountains. The results proved that S-1 SAR imagery was able not only to capture the final spring melting but also all melting cycles that commonly appear throughout the year in these types of environments. The general change detection approach to identify wet snow was adapted for these regions using as reference the average S-1 SAR image from the previous summer, and a threshold of -3.00 dB. In addition, four different type of melting runoff onsets depending on physical snow condition were identified. When translating that at the catchment scale, distributed melting runoff onset maps were defined to better understand the spatiotemporal evolution of melting dynamics. Finally, a linear connection between melting dynamics and streamflow was found for long-lasting melting cycles, with a determination coefficient (R2) ranging from 0.62 to 0.83 and an average delay between the melting onset and streamflow peak of about 21 days.

The study investigates the impact of globalization, renewable energy consumption and economic growth on CO2 emissions in 26 European Union (EU) countries for the period 1990-2020. The second-generation panel unit root tests are applied, the Westerlund cointegration test is used, and panel Fully Modified Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) techniques are employed to estimate the long-term relationship between variables. The causality relationship among variables under investigation is identified by the heterogeneous Dumitrescu-Hurlin causality test. It is found that globalization and renewable energy consumption contributed to the carbon emissions mitigation, while economic growth induced their increase. The results are robust when control variables (i.e., financial development, foreign direct investment and urbanization) are added in the model. Foreign direct investment and urbanization are contributors to carbon emissions increase whereas financial development induce their decrease. The effect of variables under consideration on carbon emissions is differentiated by the economic development and institutional quality level. Unidirectional causalities relationships were identified from globalization to carbon emissions and from carbon emissions to foreign direct investment and bidirectional relationships between economic growth, renewable energy consumption, financial development and carbon emissions. Policy implications of the findings are also discussed.

The macro-litter (plastic) sea bottom pollution of 14 city harbors and marinas in North Africa and in the western Baltic Sea was investigated using a new simple mobile underwater camera system. The study was complemented by a harbor manager survey and 3D-hydrodynamic transport simulations. The average pollution in German marinas was 0.1 particles/m² sea floor (0.04–1.75). The pollution in North African marinas on average was 7 times higher (0.7 particles/m²) and exceeded 3 particles/m² in city center harbors. The resulting >100,000 litter particles per harbor indicate the existence of a problem. With 73%-74%, plastic particles are dominating. Existing legal and management frameworks explain the lack of plastic bottles and bags on sea floors in Germany and are one reason for the lower pollution levels. Items that indicate the role of untreated sewage water were not found. Harbor festivals seem not to be quantitatively relevant for open sea bottom pollution. Our method tends to underestimate the pollution level. Model simulations indicate that storms can cause litter reallocations and sediment cleanings. However, marina sea floor monitoring is recommendable, because it addresses pollution hot-spots, is cost-effective and takes place close to emission sources. Further, the effectiveness of land-based pollution reduction measures can easily be assessed.

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.

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.

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.).