Members of the common lichen photobiont genus Trebouxia occur from the arctic to tropical terrestrial habitats however, the mechanisms of environmental stress tolerance in Trebouxia are little understood. Here we studied six species, which belong to the S-clade and A-clade, and were isolated from the lichen-forming fungi Umbilicaria pustulata and U. phaea. These species have demonstrated extensive genomic divergence, particularly in genome regions associated with photosynthesis. Therefore, we hypothesized that they will exhibit differential performance under varying light conditions. We assessed their physiological and transcriptomic responses to short and prolonged exposure to high light (HL). Average levels of Fv/Fm and NPQ showed significant reduction following HL exposure, but this varied among species. Further, only a few differentially expressed genes (DEGs) were found for specific species following exposure to 1 h of HL. On the other hand, there are more DEGs found for those exposed to prolonged HL, particularly photoprotection-associated genes related to NPQ, photosystem II repair, oxygen evolving assembly and biosynthesis of photoprotective pigments. Overall, our findings show that in Trebouxia, the capacity to withstand high light conditions is highly species-specific, and not driven by phylogenetic relatedness or climatic niche preference.

Greenhouse gas emissions and footprint analysis of multi-purpose dam reservoirs in temperate climates: Case study from South Korea

Benchmarking framework for decomposition models in solar irradiance estimation within a temperate climate

Influence of controlled cooling on wheat grain preservation and flour technological properties in temperate and subtropical climates

Ecological determinants and indicator-based analysis of Aedes albopictus expansion in a Central European metropolis: implications for urban sustainability.

Small-scale spatial heterogeneity of soil chemical and microbiological properties triggered by biocrusts and grasses in sand dunes of temperate climate

Meta-analysis: Efficiency of using remote sensing to monitor algal and cyanobacterial blooms in continental aquatic environments.

Introduction <i>Dirofilaria repens</i> is a parasite of dogs and other carnivorous mammals, transmitted primarily by mosquitoes. Humans are only rarely identified as accidental hosts of this nematode; however, in recent years an increasing number of human dirofilariasis cases has been documented. We present a case of human <i>D. repens</i> infection in Poland, a parasite traditionally endemic to warm climatic zones. Aim This case report presents a human <i>D. repens</i> infection in Poland diagnosed primarily on the basis of ocular symptoms, emphasizing the atypical geographic setting and the need to consider parasitic infections in the differential diagnosis of ocular lesions in temperate climates. Case study The 49-year-old woman developed an ophthalmological infection that manifested as a subconjunctival, light motile mass. The intact worm was surgically extracted under local anesthesia and subsequently identified as <i>D. repens</i> at the Parasitology Laboratory of the National Institute of Public Health in Warsaw. Results and discussion The report reviews the typical geographic distribution of <i>D. repens</i> and its increasing occurrence in atypical regions, including Poland. Factors contributing to this spread, such as climate change and the migration of carnivores or insects are discussed. Increased human mobility and globalization may also represent important contributing factors. Common clinical manifestations, particularly ocular involvement, and current treatment approaches are summarized. Conclusions Human dirofilariasis caused by D. repens is among fastest-spreading zoonosis in Europe. Given its emergence in cooler climates, it should be included in the differential diagnosis of atypical ophthalmological lesions.

This study compares and evaluates the performance of a statistical model, Multiple Linear Regression (MLR), and a deep learning model, Long Short-Term Memory (LSTM), for predicting monthly mean temperature in the Han River Basin, South Korea. Predictor variables were dynamically selected based on lagged correlation analysis between climate indices and temperature over the past 40 years, identifying the top ten variables with the highest correlations for lag times ranging from 1 to 18 months. The MLR model was developed through stepwise regression with cross-validation, while the LSTM model was constructed using an 18-month input sequence to capture temporal dependencies in the data. Model performance was evaluated using percent bias (PBIAS), Nash–Sutcliffe efficiency (NSE), Pearson’s correlation coefficient (r), and tercile-based probability metrics. Both models reproduced the seasonal variability of monthly temperature with high accuracy (NSE > 0.97, r > 0.98). The LSTM model showed slightly higher predictive skill in several periods but also exhibited larger prediction variance, reflecting the sensitivity of nonlinear architectures to variations in predictor–response relationships. In contrast, the MLR model demonstrated more stable predictive behavior with narrower uncertainty bounds, particularly under low signal-to-noise conditions, owing to its structural simplicity. These findings indicate that the two approaches are complementary; the LSTM model better captures nonlinear temporal dynamics, while the MLR model provides interpretability and robustness. Future work will explore advanced hybrid architectures such as CNN–LSTM and Transformer-based models, as well as multi-model ensemble methods, to further enhance the accuracy and reliability of medium-range temperature prediction.

This study is a representation of the physical and chemical properties of the soils in the Bashiqa district, northeast of Nineveh Governorate. Geographically, the study area is located between latitudes (36°20'47-35°36'54) north and longitudes (43°10'55-43°32'42) east, with an estimated area of about 511.40 km2. (23) samples distributed throughout the study area are collected to conduct field and laboratory tests, including the physical and chemical properties of the soil (color, texture, moisture, density, porosity, pH reaction degree, and salinity EC). The results of the laboratory work have been analyzed, and maps of the variables in the studied sites have been drawn, relying on the obtained data required for map representation. It is found that the soils vary in terms of color, which represents the color changes of the minerals present in the region. It is also shown that the worthiest soil texture in the region is mixed one, and that the quantity and quality of moisture, porosity, and density differ from one region to another according to several variables such as climate (rain, temperature, and wind), the compositional characteristics of each region, and soil formation factors. These variables also affect the degree of interaction between pH and salinity EC.

Long-term changes in weather conditions on Earth have a significant impact on the world around us. These include not only increasingly extreme weather events such as droughts and heatwaves. These effects can be felt throughout the natural environment, influencing the spread of parasites and the diseases they transmit. Climate change can alter the range and life cycles of parasites, and accelerate and lengthen the activity period of vectors. Four species are described in this manuscript: Balamuthia mandrillaris, Naegleria fowleri, Trypanosoma cruzi and Strongyloides stercoralis. Balamuthia mandrillaris is a species of an opportunistic cyst-forming free-living amoeba. The main habitat is moist soil and freshwater reservoirs. It could be pathogenic to humans. The amoeba consumes cutaneous tissue and excretes enzymes leading to an immune response of the host. Naegleria fowleri is a free-living amoeba that might cause primary amoebic meningoencephalitis (PAM) whose mortality rate reaches as much as 98%. Trophozoites enter the body through the nasal cavity while underwater. Most often cases of PAM include immunocompetent children and young adults. Trypanosoma cruzi is a flagellate protozoan with life cycle between hematophagous insects of the Triatominae subfamily and various mammal species including human. Trypanosoma cruzi causes the Chagas disease (American trypanosomiasis). Strongyloidiasis, caused by the parasite Strongyloides stercoralis, is a neglected tropical disease (NTD). Infection starts when the host walks barefoot on soil contaminated with filariform larvae that penetrate the skin. Immunosuppression in infected patients can lead to hiperinfection and death.

The three key design criteria for nearly zero-energy buildings (nZEBs) and climate-neutral buildings are minimizing energy use, ensuring high occupant comfort, and reducing environmental impact. Thermal comfort is one of the main components of indoor environmental quality (IEQ), strongly affecting occupants’ health, well-being, and productivity. As energy-efficiency requirements become more demanding, the appropriate selection of heating systems, their automated control, and the management of solar heat gains are becoming increasingly important. This study investigates the influence of two low-temperature radiant heating systems—underfloor and wall-mounted—and the use of Venetian blinds on perceived thermal comfort in a highly glazed public nZEB building located in a densely built urban area within a temperate climate zone. The assessment was based on the PMV (Predicted Mean Vote) index, commonly used in IEQ research. The results show that both heating systems maintained indoor conditions corresponding to comfort or slight thermal stress under steady state operation. However, during periods of strong solar exposure in the room without blinds, PMV values exceeded 2.0, indicating substantial heat stress. In contrast, external Venetian blinds significantly stabilized the indoor microclimate—reducing PMV peaks by an average of 50.2% and lowering the number of discomfort hours by 94.9%—demonstrating the crucial role of solar protection in highly glazed spaces. No significant whole-body PMV differences were found between underfloor and wall heating. Overall, the findings provide practical insights into the control of thermal conditions in radiant-heated spaces and highlight the importance of solar shading in mitigating heat stress. These results may support the optimization of HVAC design, control, and operation in both residential and non-residential nZEB buildings, contributing to improved occupant comfort and enhanced energy efficiency.

Environmentally friendly sucrose-based poly(ester-urethane)s were synthesized and characterized, and their stability and degradation behavior were assessed under three different aging conditions: thermal, ultraviolet (UV), and hydrolytic treatment. The specimens underwent thermal treatment in both hot and cold climates to simulate a temperate continental climate. The samples were thoroughly characterized to assess chemical and structural changes (FT-IR, TGA, and DSC) and surface modifications (contact angle measurements and AFM and SEM analyses), providing insights into surface morphology and wettability alterations. Mechanical testing was also performed to evaluate the retention rate of the strength and the elongation after the aging process. The results showed that the introduction of sucrose into the main chain of the polyurethanes protected the ester and urethane groups from environmental degradation. The best stability in all three degradation environments was achieved by PCL-poly(ester urethane) due to its higher degree of crystallinity. PCL-based polyurethane exhibited a fracture strength retention rate exceeding 85% under all aging conditions, while the weight ratio remained practically unchanged after hydrolytic degradation. Thus, the obtained polyurethanes may support the advancement of sustainable, eco-friendly materials for future industrial applications.

Green facades, commonly referred to as vertical plant systems, offer sustainable solutions. They improve the energy efficiency of buildings, reduce energy consumption, and positively impact the microclimate both at the microscale and at the urban level. Their ability to regulate temperature and improve thermal comfort, including mitigating the heat island effect, makes them a valuable element of sustainable architectural design. They also contribute to reduced energy consumption, reduced noise, mitigation of air pollution, and aesthetic and wind protection. The main goal of the study was to analyse the cooling effectiveness of green walls in a transitional temperate climate zone. The study was conducted on two experimental models located on the campus of the Wrocław University of Environmental and Life Sciences and at the Research and Educational Station in a suburban area. Both locations had different characteristics: the former contained urban development, while the latter contained open and sparsely developed areas. On warm and sunny days, the cooling effects of the systems were observed independently for both locations and their exposures. For data acquisition at a distance of 5 cm from the plants, a higher data concentration and a lower variability in the mean temperature drop were observed. In the same group, on sunny days, the cooling effect averaged 4–7 °C and depended on the location. On cloudy days, the mean maximum cooling in this group did not exceed 4 °C.

Nepal’s National Highway (NH) network is vital to meet the country's transportation demands and socio-economic development. However, a big fraction of NH network faces rapid deterioration due to increasing traffic, harsh climatic conditions and inefficient maintenance planning. This study presents a data driven framework for road management planning, utilizing the Markov hazard model for pavement deterioration for two major pavement types – Surface Dressing (SD) and Asphalt Concrete (AC) across two major climatic conditions - Tropical Savannah (Aw) and Temperate Climate with Dry winter (Cw). The framework incorporates Surface Distress Index (SDI), traffic volumes, and life cycle cost analysis (LCCA) to evaluate the long-term effectiveness of various maintenance and upgrading strategies using the Markov model. The result shows that Combined Maintenance (CM) which involves integration of routine and recurrent maintenance activities significantly delay pavement deterioration process, reducing periodic maintenance costs and improving road network performance. Upgrading SD pavement with higher deterioration rates to AC proves highly effective for high traffic roads, improving durability and overall network condition. The study evaluates several maintenance and upgrading strategies, highlighting the balance between LCC and the good to fair road percentage, enabling road agencies to set performance targets within budget constraints. The findings provide valuable information for policymakers and road agencies, emphasizing the importance of proactive, data-driven decision-making in road maintenance planning. Future research could explore indirect benefits, such as vehicle operating cost savings and reduced travel times, to further enhance the decision-making framework.

The pollution of urban soils in tropical megacities with legacy radionuclides poses a significant environmental challenge, yet risk assessment is often hampered by a reliance on models from temperate climates. This study addresses this gap by presenting the first longitudinal (2022-2024) investigation into the dynamics of soil-to-plant transfer for both natural radionuclides (2³8U, 2³2Th, 40K), which define the geological baseline, and the primary anthropogenic contaminant, 1³7Cs in Ho Chi Minh City, Vietnam. Analysis of four ecologically significant plant species indicates that radionuclide bioavailability is not static. Instead, it exhibits significant fluctuations correlated with seasonal climatic shifts, a dynamic that challenges equilibrium-based assumptions and underscores the need for process-based risk assessment models. The results inform a "right plant, right place" management strategy for urban soil pollution. Araucaria columnaris was identified as an effective phytoextractor for 1³7Cs (TF up to 0.697), while Pinus kesiya was confirmed as a low-uptake species suitable for safe urban greening. Furthermore, risk assessment of the edible Moringa oleifera confirmed a negligible public health risk from its consumption (<3% of the public dose limit) and established its potential as a valuable sentinel species for long-term environmental monitoring. This research provides a foundational dataset on soil pollution in Southeast Asia and a transferable methodology for mitigating radiological risks in urban ecosystems.

The paper considers the site of the Far Eastern Carbon Landfill (FECL), located on the shore of the Bukh River. Ajax is located in the Sea of Japan in the temperate monsoon climate zone. The main feature of the FECL is its seaside location, which allows for a comprehensive study of coastal and marine ecosystems. The site consists of 20 ha of marine water area and 4 ha of land area on the campus of the Far Eastern Federal University (FEFU) in Vladivostok and is part of a larger landfill in Primorsky Krai with an area of 304.23 ha. The paper presents the results of a study of the coastal zone of the Far Eastern Federal University (FEFU) Vladivostok campus. The possibilities of using remote sensing of the earth (remote sensing) in the framework of work to assess the sequestration potential of coastal marine ecosystems—their ability to absorb and retain carbon. The experience of combining ground-based laser scanning and aerial photography with a multispectral camera is presented, which significantly expands the possibilities of assessing ground objects. Based on the results of the survey from an unmanned aerial vehicle (UAV) and the addition of ground-based laser scanning data, the site’s territory is classified by type of land use and types of facilities. Digital models of terrain and relief, orthophotoplans, including the NDVI (Normalized Difference Vegetation Index) vegetation index, have been obtained. A quantitative assessment of trees, shrubs, grass, and buildings was performed based on a combined point cloud and raster files. Tree heights relative to open databases have been clarified. Preliminary calculations of the content of aboveground biomass and carbon reserves have been performed. A detailed cartographic framework has been created, which will be used for further work with the spatial data of the carbon polygon.

Electric Vehicle (EV) battery degradation in tropical environments remains poorly understood, with traditional linear models like OLS facing significant challenges such as multicollinearity, leading to unreliable insights into influential factors. This study aims to experimentally characterize lithium-ion battery degradation and comprehensively evaluate the influence of local climatic (temperature, humidity, dust) and driving conditions (road quality, mileage) in a Cameroonian tropical context, addressing the limitations of conventional statistical approaches. Our unique contribution involves providing empirical real-world data from a subSaharan environment and applying a novel hybrid CVAE-GRU methodology to capture complex non-linear and temporal dependencies. An embedded system continuously collected battery parameters (SoH, internal resistance) alongside environmental and driving data. The CVAE learns robust latent representations from these correlated inputs, while the GRU models their temporal dynamics for degradation prediction. Results confirm progressive SoH degradation, significantly accelerated by high temperatures, humidity, dust, and poor road quality. The CVAE-GRU approach effectively mitigates multicollinearity, offering superior accuracy and deeper insights into these influences. This work highlights the critical impact of tropical conditions on EV battery aging, providing crucial findings for developing adapted Battery Management Systems and fostering sustainable mobility in similar regions.

Herein, we present a systematic investigation of plant fossils from the Yingzuilazi Formation in Baishan City, Jilin Province, China. The Baishan flora comprises 27 genera and 46 species. They are predominantly autochthonous or parautochthonous, based on their floral composition and taphonomic attributes. An analysis of paleoecological characteristics of the fossil plant assemblages, combined with the habitat preferences of analogous modern communities, allowed us to reconstruct the Early Cretaceous plant communities in the Baishan Basin: a riparian-wetland community, lowland community, montane slope community, and montane highland community. The floral composition, a statistical analysis of foliar physiognomy, and the palynofloral characteristics indicated a warm and humid temperate climate during the deposition of the Yingzuilazi Formation. A genus-level comparison with the Yixian Formation flora of western Liaoning revealed high compositional similarity, which confirms the Baishan flora as the easternmost distribution of the Jehol Biota in China. This study provides new fossil evidence for understanding Early Cretaceous floristic provincialism and paleoenvironmental reconstruction in East Asia. It offers geological references that can predict vegetation responses to a greenhouse climate. Additionally, Sphenopsida and Filicopsida may serve as potential indicators that may identify favorable terrestrial shale oil and gas reservoirs from the Early Cretaceous.

Seasonal influenza is a recurring public-health burden that peaks in winter and tests outpatient and hospital capacity. Accurately predicting its seasonality and near-term activity is crucial to preventing avoidable hospitalisations and activating and timing season-appropriate preparedness actions. This article distils salient evidence on environmental drivers and data streams for multi-faceted surveillance and operational prediction, as well as modelling families that complement the latter. It overviews laboratory and epidemiologic evidence that absolute humidity modulates viral survival and transmissibility, thus partly explaining influenza’s robust winter seasonality in temperate climates. It then discusses surveillance systems ranging from the global WHO FluNet/GISRS to national dashboards such as CDC FluView and ECDC ERVISS that provide timely, standardised indicators and prediction targets. It subsequently reviews main method families (statistical time-series, mechanistic compartmental models, machine learning) and highlights that multimodel ensembles often outperform single approaches at predicting onset, peak week, and intensity. It also presents case studies from Europe, the U.S. and China that illustrate prediction skill, the importance of climate-aware forcing, and of practical factors such as reporting lags. Generally, robust and interpretable forecasts require well-aligned targets, hybrid/ensemble frameworks, adaptive weighting and drift monitoring, and hold promise to support earlier warnings, intervention scenario analysis, and efficient resource planning.