Abstract: In acidic tea soil, boron (B) adsorption and desorption processes are dominated by the complex relationship between soil acidity, mineralogy, and organic matter. This study investigated B adsorption–desorption behavior in five acidic tea soils (pH 3.8–5.6) col-lected from the Eastern Black Sea region of Türkiye and evaluated the potential of machine learning (ML) algorithms to predict B desorption. Laboratory batch experi-ments were conducted using five initial B concentrations, and adsorption data were interpreted using the Langmuir isotherm model. Adsorption experiments indicated that B interacted with Fe/Al-oxide-containing clay minerals, which had low but fa-vorable binding affinity, as indicated by Langmuir maximum adsorption capacities (Qmax) ranging from 46.5 to 181.8 mg kg⁻¹. Desorption experiments revealed a high degree of reversibility, particularly in soils with lower adsorption capacities, ensuring potential B leaching. To capture the non-linear relationships governing B desorption, six ML algorithms were trained on 75 data points. Among the tested models, Extreme Gradient Boosting (XGBoost) showed the highest predictive accuracy (R² = 0.963), fol-lowed by Gaussian Process Regression and Random Forest. Variable importance anal-yses consistently highlighted soil pH, organic matter content, and clay fraction as the dominant factors. The results demonstrate that integrating laboratory experiments with machine learning provides an effective framework for predicting B mobility in acidic tea soils, offering a practical tool for improving boron management strategies.

Abstract: Biodiversity in Ethiopia is under mounting pressure from deforestation, agricultural expansion, climate change, and other anthropogenic pressures, yet conventional conservation approaches often fail to protect species and ecosystems effectively. Dominated by Western scientific paradigms, these approaches treat the ecosystems as isolated from human activity, relying on centralized management, protected areas, and technical interventions. In human-dominated landscapes, such models frequently overlook the adaptive capacities embedded within Indigenous Knowledge (IK) systems. Developed through generations of observation, experimentation, and social regulation, IK encodes a detailed understanding of species behavior, landscape dynamics, and sustainable resource use, functioning as a dynamic ecological system. This essay argues that integrating Indigenous knowledge into biodiversity conservation is an Ecological imperative rather than a moral preference. Evidence from Ethiopian church forests, pastoralist rangelands, and Konso terraces shows that IK sustains biodiversity, ecosystem resilience, and livelihoods. While highly effective, IK is not uniform or universally sufficient; demographic change, market pressures, and internal social inequalities can constrain its impact. Recognizing both the strengths and limits of IK, and embedding it within multi-level governance systems is essential for designing resilient, socially legitimate conservation strategies. Thoughtful integration transforms Indigenous stewardship from a cultural practice into a strategic tool for sustaining ecosystems in climatically variable, human-occupied landscapes.

Abstract: This paper applies Variety Dynamics (VD) framework to analyse persistent failures in spatial data infrastructure (SDI) governance and standardisation. Variety Dynamics provides value-neutral analytical tools for examining hyper-complex systems such as SDI governance and standardisation where conventional mental models fail beyond the two-feedback-loop cognitive boundary. VD provides a new methodological contribution to geographic information science that reveals otherwise hidden structural factors and effects operating beyond mental capacity. The Variety Dynamics analysis reveals most SDI initiatives constitute activity within unchanged variety distributions. Standards are published, coordinating bodies established, technical platforms deployed—yet situations remain problematic because no actual variety redistribution occurs. This is similar to 2007 Variety Dynamics analysis that correctly forecast Microsoft XML dominance over technically superior RDF. Almost identical dynamics now appear in geospatial markets, where hidden factors maintain concentration despite open-source technical alternatives achieving feature parity. Variety Dynamics analysis reveals data sovereignty regulations (2024-2028) offer potential for change in the power locus of SDI by forcing infrastructure migration, inverting transaction cost structures. After 2028, variety distributions will lock in for subsequent decade through path dependencies and accumulated switching costs.

Abstract: Water quality is traditionally assessed using epidemiological, organoleptic, sanitary-toxicological, and radiation criteria. However, recently, increasing evidence points to the need to consider the structure of aqueous solutions, especially when used for therapeutic purposes. In this study, electrophysical methods were used to study aqueous solutions of sodium chloride of varying concentrations, drinking water, mineral water, and seawater. Patterns in the frequency and amplitude changes of a sinusoidal oscillator compared to distilled water were identified. Based on experimental data, the Ks coefficient is proposed for assessing the structure of drinking and mineral waters. It is defined as the ratio of the oscillation amplitude of the generator at its minimum frequency to the oscillation amplitude at its maximum frequency. A theoretical justification for the formation of the structural organisation of aqueous solutions depending on the concentration of dissolved salts is presented, taking into account the presence of associated and "free" water dipoles, as well as the formation of hydrate formations in a liquid medium. The need to account for intermolecular interaction forces involving water dipoles is emphasised.

Abstract: Highly effectively and economical method to immobilize cadmium from alkaline agriculture soil is urgently needed. Through kinetic and isotherm experiments of passivators adsorption, soil passivation experiment, and cadmium leaching, this study was to explore the applicability of hydroxylapatite-organic fertilizer compound repair agents (HO), individual hydroxylapatite (HA), individual organic fertilizer (OF), sepiolite (SP) and diatomite (DE) to passivate soil cadmium and its passivating effect. In the aqueous phase, HO successfully adsorbed Cd2+ on the surface and has superior potential Cd2+ adsorption capacity than OF, DE, and SP, with its adsorption capacity closely approach to that of HA, enabling its use as a passivator in real Cd-contaminated environments. In Cd-contaminated soil, HO effectively lower the pH from 9.22 to 8.59 at the addition of 5% and change the aggregate distribution. The increase in the amount of passivator also significantly increased soil aggregate size. Moreover, the addition of HO significantly improved the extractable contents of Cd in the soil. With the addition of 5% HO, the Cd extracted by TCLP decreased by 30.95%, 42.86%, 59.52% and 69.05%, respectively. Therefore, our findings demonstrated that HO is a highly efficient and low-cost organic-inorganic composite passivator for cadmium contaminated soils..

Abstract: Air pollution is one of the leading environmental risk factors affecting human health worldwide. Fine particulate matter (PM2.5) is considered particularly harmful due to its ability to penetrate deep into the lungs and enter the bloodstream, increasing the risk of respiratory diseases. This study aims to analyze the relationship between PM2.5 concentration and respiratory disease incidence in Kyrgyzstan using data visualization techniques. The dataset was obtained from two main sources: annual PM2.5 concentration data were collected from the World Health Organization (WHO), while respiratory disease statistics were acquired from the National Statistical Committee of the Kyrgyz Republic. The data cover the period from 1990 to 2024. After preprocessing and merging the datasets, various visualization and statistical techniques were applied using Python libraries, including Pandas, Matplotlib, and Seaborn. Trend analysis revealed a significant increase in PM2.5 levels after 2010, which coincided with a rise in respiratory disease cases. Correlation analysis showed a moderate positive relationship between PM2.5 concentration and respiratory disease incidence (r = 0.56). Regression analysis further confirmed that higher pollution levels are associated with increased numbers of respiratory disease cases. Although the correlation is not strong, the results indicate that air pollution is an important contributing factor to respiratory health outcomes. The moderate strength of the relationship may be explained by delayed health effects and the influence of additional factors such as lifestyle, seasonal infections, and healthcare access.

Abstract: Polymer-based insulation materials are widely used to enhance the energy efficiency of buildings; however, their growing application raises concerns related to resource use and end-of-life management. Rigid polyurethane (PUR) foams are key core materials in structural insulated panels due to their favorable thermal and mechanical performance, yet their life cycle environmental im-pacts—particularly at end-of-life—remain insufficiently quantified. In this study, a cradle-to-grave life cycle assessment (LCA) of PUR-based insulation used in structural insulated panel systems is conducted in accordance with ISO 14040/44 and EN 15804 standards. The assessment is performed using Sphera LCA software and the CML 2016 impact assessment method. Formulation-level variations of rigid PUR foams, including changes in methylene diphenyl diisocyanate content and pentane blowing agent ratio, are explicitly incorporated to evaluate their influence on key environmental impact categories. The results indicate that increasing pentane content leads to higher global warming potential, while this effect may be mitigated or intensified by concurrent changes in diisocyanate content and foam density in fully formulated systems. Three end-of-life scenari-os—landfilling, incineration with energy recovery, and mechanical recycling—are analyzed. The findings provide material-level, decision-relevant insights that support environmentally informed formulation strategies and contribute to the development of more circular polymer-based insulation solutions for the built environment.

Abstract: Greenhouse gas (GHG) emissions from sanitary waste (SW) are not usually quantified in institutional inventories, which limits the ability to assess its management and associated carbon footprint. This study establishes emission factors (EF) for SW generated in a higher education institution (HEI), focusing on toilet paper. In 2022, 19 sanitary waste sources were monitored, obtaining a per capita generation of 3.02 g person⁻¹ day⁻¹ and an annual total of 356.87 kg of SW. Samples were characterized through proximate and elemental analyses, applying stoichiometric calculations for two disposal-site degradation pathways: Aerobic: 310 kg CO₂e t⁻¹, Anaerobic: 5,990 kg CO₂e t⁻¹. The weighted emission for the SW mixture was 1,124 kg CO₂e t⁻¹. Based on an estimated annual mass of 1.12 t yr⁻¹, emissions ranged from 0.35 to 6.71 t CO₂e yr⁻¹ depending on the scenario, here emissions could be reduced by over 90% when aerobic degradation or controlled methane capture predominates. The results suggest that separating SW at its point of generation and ensuring that it undergoes aerobic or energy-recovery treatment processes can limit its contribution to institutional GHG inventories. Having material-specific EF enables quantitative comparison among management strategies and guides continuous-improvement decisions.

Abstract: Large-scale mapping of forest canopy height (FCH) is crucial for accurately understanding ecosystem succession and forest carbon sinks. Recently, three high-resolution FCH products have been released, including global forest canopy height (GFCH), NNGI_FCH_China (NNGI_FCH), and ETH_GlobalCanopyHeight (ETH_GCH). This study provides a detailed assessment of these FCH products across China from forest area, spatial consistency, and overall accuracy using forest inventory, CLCD and field measurement data. The results showed that NNGI_FCH had the smallest relative error of 13.9% and achieved better estimates of forest area in all regions but the north and northeast regions. GFCH had the highest spatial consistency of 71.2% nationwide, followed by NNGI_FCH (69.7%), which performed slightly better than GFCH in the east and northwest regions. ETH_GCH exhibited the lowest spatial consistency of 35.6% and remained below 50% across all regions except the northeast and south regions. ETH_GCH demonstrated the highest overall accuracy across the country, with R2 and RMSE of 0.56 and 4.40 m, followed by NNGI_FCH (R2=0.48, RMSE=4.14 m) and GFCH (R2=0.48, RMSE=4.15 m). Validation results of ETH_GCH were relatively stable in different regions of China, while those of NNGI_FCH varied more but still outperformed GFCH. This study offers valuable insights by evaluating large-scale FCH products, which will be a key basis for in-depth studies on the utilization and improvement of future FCH mapping.

Abstract: Cities play a central role in shaping societal responses to the climate crisis, concen-trating both climate risks and institutional capacity to address them. While climate impacts are widely distributed, they are experienced unevenly, with marginalized populations facing disproportionate exposure to economic disruption and environ-mental stress, particularly in urban environments. This review article examines how cities can enhance climate resilience while supporting a just transition to a post-carbon economy. It addresses three interrelated questions: how vulnerable urban populations can be better prepared for green employment; how transformations in work and commuting can promote compact, mixed-use, and transit-friendly urban districts; and how such districts can be designed to protect residents from urban heat and improve walkability through shade and nature-based solutions. The analysis synthesizes find-ings from recent empirical studies and applied policy initiatives, including a municipal green-employment pilot in Tel Aviv-Yafo, the “Reinventing Paris” office-to-housing program, and urban heat and pedestrian-behavior research. Together, these cases il-lustrate how physical adaptation strategies interact with labour-market dynamics and social policy. The review concludes that effective urban climate resilience requires in-tegrating infrastructural and spatial interventions with labour-market transformation, social protection, and inclusive governance, positioning cities as key operational units for advancing equitable climate action.

Abstract: Human-elephant conflict (HEC) has become a major conservation and socio-economic challenge across Asia, particularly in elephant range countries, due to rising human encroachment and habitat loss. In India, HEC escalation is linked to habitat degradation, agricultural expansion, and linear infrastructure development. In the West Singhbhum district of Jharkhand state, changes in LULC from deforestation, mining, and agricultural encroachment have severely altered elephant habitats. The loss of migratory routes has forced elephants to remain in disturbed areas, intensifying conflict. A three-year field study (2018–2020) across Porahat, Chaibasa, Kolhan, and Saranda Forest Divisions, combined with two decades (2000–2020) of LULC analysis, recorded 157 human deaths, 2837.90 acres of crop damage, 1925 house destructions, 3146 quintals of grain loss, and 35 elephant deaths, including nine poaching cases. Dense vegetation declined from 49.14% (2000) to 28.68% (2020), while sparse vegetation and agricultural land increased by 15.35% and 3.68%, respectively. Water bodies decreased by 0.33%, and barren land increased by 3.70%. Core forests (>500 acres) reduced by 16.86%, with forest perforation increasing by 15.69%. Only 6.7% of the district remains suitable for elephants, mostly in Saranda (44.2%), while NDVI shows 83.54% non-favourable change. Ensuring coexistence demands improved landscape connectivity and targeted conservation strategies, while exclusion zones need site-specific mitigation measures.

Abstract: Grassland state assessment is essential given their vital role in food security, carbon sequestration and other ecosystem services. Harvested aboveground biomass (HAB), aboveground net primary production (ANPP) and net primary production (NPP) are among the most important grassland state indicators. However, spatially explicit production estimates are largely lacking, and grassland area estimations also remain uncertain. This study addresses these gaps for drought-prone Central European grasslands over 2017-2024. We synthesized grassland extent data, collected extensive field measurements, and used remote sensing-based biophysical proxies to build an ensemble of eight linear models for spatial extrapolation at 10 m resolution. The proxies explained 11-41% of observed biomass (BM) variability. The ensemble mean ANPP was 325.7±56.6 gBM m2 year1 (median: 316 gBM m2 year1), with modest overall interannual variability. Upscaled country-wide ANPP averaged 35.1±9.2 Mt BM year-1 annually (range: 31.9-38.3; median: 35.9 Mt BM year-1). Uncertainty from grassland area estimation was roughly twice that from model choice. Using literature and local data, NPP was estimated at 421±110 gC m2 year-1 (median value), showing low interannual variability. Results highlight grassland area uncertainty as the dominant source of error in biomass estimation, rather than the remote sensing models themselves.

Abstract: The article examines the behavior of seismic noise fields over the Japanese islands recorded by the F-net seismic network for 1997-2025. The paper uses nonlinear noise statistics: the entropy of the wavelet coefficient distribution, the Donoho-Johnston (DJ) wavelet index, and the multifractal singularity spectrum support width. These parameters were chosen because their changes reflect the complication or simplification of the noise structure. Changes in the structure of seismic noise properties are analyzed in comparison with a sequence of strong earthquakes. Using a model of the intensity of interacting point processes, the effect of the leading of local noise property extrema relative to the seismic event times is estimated. Using the Hilbert-Huang decomposition, the synchronization of the amplitudes of the envelopes of noise property time series for different IMF levels is estimated. A sequence of weighted probability density maps of extreme values of noise properties is analyzed in comparison with the mega-earthquake of March 11, 2011 and the preparation of a possible next strong seismic event.

Abstract: Air quality makes a huge difference in human health, ecological environment, economic 2 development, and global climate governance. This study introduced Time-Weighted 3 Ensemble model into the air quality prediction model and achieved good results. The 4 prediction results were consistent with reality, and the R-square of prediction is 0.54, pro- 5 viding a new reference for people to avoid air pollution. And because of the the original Air 6 Quality Index (AQI) has limited using scope and results are inaccurate, this thesis establish 7 a brandnew evaluation system, called Adaptive Air Quality Index (AAQI), which takes 8 concentration, correlation, time, and cooperation into consideration. It is more comprehen- 9 sive and advanced than the existing system. Data on six pollutants were collected from 10 six cities, namely Brasilia, Cairo, Dubai, London, New York, and Sydney, and then prepro- 11 cessed the above data using KNN interpolation, Unit transformation and normalization, 12 and calculated the correlations among them by using Mutual Information, Spearman’s 13 Rank Correlation and Kendall’s Tau Correlation. Afterwards, we incorporated it into the 14 AAQI and obtained their air quality. Among them, Sydney had the best air quality, while 15 Dubai and Cairo had relatively poor air quality. This research should be promoted and 16 applied in air quality monitoring in real life.

Abstract: The advance and delay of the rainy season is among the most frequently cited effects of climate change by Ecuadorian farmers. However, its assessment is not feasible using the conventional indicators recommended by the standardized indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). This study aims to analyze such advances and delays through harmonic analysis in Tungurahua, a predominantly agricultural province in the Tropical Central Andes, where in-situ data are scarce. Daily in-situ data from five meteorological stations were used, including precipitation, maximum, and minimum temperature records spanning 39 to 68 years. The study involved an analysis of the region’s climatology, climate change indices, and harmonic analysis using Cross Wavelet Transform (XWT) and Wavelet Coherence Transform (WCT) to identify seasonal patterns and their variability (advance or delay) by comparing historical and recent time series, and Kriggin for regionalization. The year 2000 was used as a breakpoint for comparing past and present trends. Results show a generalized increase in both minimum and maximum temperatures. In the case of extreme rainfall events, no significant changes were detected. Harmonic analysis was found to be sensitive to missing data. Furthermore, the observed advances and delays in seasonality were not statistically significant and appeared to be more closely related to the geographic location of the stations than to temporal shifts.