Variable Climatic Conditions Research Articles

Predicting Rainfall-Induced Landslides in Muriwai, Auckland: A Comprehensive Multi-Model Approach for Enhanced Risk Management

Landslide studies hold significant importance in understanding and mitigating the risks associated with these geohazards. Particularly in regions like New Zealand, where diverse topography and climatic conditions contribute to frequent landslide occurrences, such studies are crucial. This research focuses on Muriwai, Auckland, a region that has experienced substantial landslide activity triggered by rainfall. The study adopts a multi-model approach, integrating both empirical and process-based models to predict rainfall-induced landslides. This approach leverages the strengths of individual models, including logistic regression, random forest, support vector machines, artificial neural networks, and decision trees, thereby enhancing the robustness and accuracy of predictions. A comprehensive dataset, comprising historical landslide records, climatic data, and terrain and geological data, is used to train and validate these models. The data is spatially aligned within a unified Geographic Information System (GIS) database, ensuring consistency and accuracy in the analysis. The multi-model ensemble provides a probabilistic prediction of landslide occurrence, which is visualized as a landslide susceptibility map. This map serves as a valuable tool for understanding the spatial distribution of landslide risks in Muriwai. The performance of each model and the ensemble is evaluated using several metrics, ensuring the reliability of the predictions. The results are interpreted to understand the influence of different factors, particularly climatic parameters, on landslide occurrences. This study's findings contribute to effective landslide risk management and mitigation strategies in Muriwai, Auckland, and provide valuable insights for similar studies in other regions.

Comprehensive assessment of invalid and indeterminate results in Truenat MTB-RIF testing across sites under the national TB elimination program of India.

Truenat MTB-RIF assay (Truenat), a nucleic acid amplification test (NAAT), is a real-time polymerase chain reaction (RT-PCR) chip-based assay that can detect Mycobacterium tuberculosis (Mtb) and rifampicin (RIF) drug resistance using portable, battery-operated devices. The National TB Elimination Program (NTEP) in India introduced this novel tool at the district and subdistrict level in 2020. This study aimed to assess the level and causes of inconclusive results (invalid results, errors, and indeterminate results) in MTB and RIF testing at NTEP sites and the root causes of these in the programmatic setting. Truenat testing data from 1,690 functional Truenat sites under the NTEP from April to June 2021 were analyzed to assess the rates of errors, invalid MTB results, and indeterminate RIF results. Following this analysis, 12 Truenat sites were selected based on site performance in Truenat testing, diversity of climatic conditions, and geographical terrain. These sites were visited to assess the root causes of their high and low rates of inconclusive results using a structured checklist. A total of 327,649 Truenat tests performed for MTB and RIF testing were analyzed. The rate of invalid MTB results was 5.2% [95% confidence interval (CI): 5.11-5.26; n = 16,998] and the rate of errors was 2.5% (95% CI: 2.46-2.57; n = 8,240) in Truenat MTB chip testing. For Mtb-positive samples tested using the Truenat RIF chip for detection of RIF resistance (n = 40,926), the rate of indeterminate results was 15.3% (95% CI: 14.97-15.67; n = 6,267) and the rate of errors was 1.6% (95% CI: 1.53-1.78; n = 675). There was a 40.1% retesting gap for Mtb testing and a 78.2% gap for inconclusive RR results. Among the inconclusive results retested, 27.9% (95% CI: 27.23-28.66; n = 4,222) were Mtb-positive, and 9.2% (95% CI: 7.84-10.76; n = 139) were detected as RR. The main causes affecting Truenat testing performance include suboptimal adherence to standard operating procedures (SOPs), inadequate training, improper storage of testing kits, inadequate sputum quality, lack of quality control, and delays in the rectification of machine issues. Root cause analysis identified that strengthening of training, external quality control, and supervision could improve the rate of inconclusive results. Ensuring hands-on training of technicians for Truenat testing and retesting of samples with inconclusive results are major recommendations while planning for Truenat scale-up. The recommendations from the study were consolidated into technical guidance documents and videos and disseminated to laboratory staff working at the tiered network of TB laboratories under the NTEP in order to improve Truenat MTB-RIF testing performance.

Biogenic acid resistance of calcium sulfoaluminate cement: Revelations from a field study

Biogenic acid attack of concrete is prevalent in sewers, posing a serious durability concern and financial burden. There are very limited number of field studies on durability of concrete under biogenic acid attack. Field study poses challenges with respect to the variation in climatic conditions and limited accessibility in sewers. Such a biogenic acid attack study in Indian conditions has not been performed. In this study, the biogenic acid resistance of Portland cement (PC) and calcium sulfoaluminate (CSA) cement-based binders under an in-situ sewer exposure is reported. The results show that the CSA-based binder used in this study outperformed PC in the biogenic acid resistance. The superior performance of CSA-based binder could be attributed to its acid neutralisation capacity offered by the aluminum hydroxide phase and bactericidal properties. For the first time, the bacteriostatic effect of CSA cement was demonstrated by analyzing the field exposed specimens.

Identification of promising and stable genotypes of wheat (Triticum aestivum L.) for grain yield under varied climatic conditions of north-western Himalayas using joint regression analysis

Identification of promising and stable genotypes of wheat (Triticum aestivum L.) for grain yield under varied climatic conditions of north-western Himalayas using joint regression analysis

Stochastic modelling and forecasting of relative humidity and wind speed for different zones of Kerala

The variations in climatic conditions depend on seasonal changes throughout the year. Modelling and prediction of climatic conditions can help to determine the impacts of seasonal changes in climate over a specific period of time. Climate change can directly and indirectly affect agricultural, industrial, geographical and technological sectors in our society. Agriculture and the allied sector are seriously affected by changes in climate since it leads to complete destruction of cultivated crops. In this study, in order to model and forecast relative humidity and wind speed for northern, central and southern zones of Kerala, stochastic approach using SARIMA (Seasonal Autoregressive Integrated Moving Average) model was employed. The monthly weather data for the northern zone and the central zone of Kerala was taken from the location of RARS Pilicode and RARS Pattambi for a period of 39 years (1982-2020) whereas for southern zone, data was collected from the location of RARS, Vellayani for a period of 36 years (1985-2020) with the help of data access viewer. The model validation was done using MSE (mean square error), RMSE (root mean square error), MAE (mean absolute error) and RMAPE (relative mean absolute percentage error). The RMAPE values of relative humidity and wind speed in different zones of Kerala was less than 10 per cent which indicated that fitted model is showing accurate performance. The best selected SARIMA model is used in attaining anticipated values of relative humidity and wind speed for the next 5 years.

A cost-effective and optimized maximum powerpoint tracking system for the photovoltaic model

<span lang="EN-US">Solar energy is naturally available from sun, and it can be extracted by using a photovoltaic (PV) cell. However, solar energy extraction entirely depends on the climatic conditions and angle of rays falling on PV cells. Hence, maximum powerpoint tracking (MPPT) is considered in most areas under variable climatic conditions, which acts as a controller unit for PV cells. MPPT can enhance the efficiency of PV cells. However, designing an MPPT model is challenging as different uncertainties in the climatic condition may lead to more fluctuations in voltage and current in PV cells. Under the shaded condition, the PV cell may have other MPPT points that lead to the PV cell’s low efficiency in analyzing maximum power. Hence, this paper introduces a cost-effective and optimized system for the PV model that can find optimal power and improve PV cells’ efficiency. The proposed system achieves better computational performance with ~35% and ~42% than existing MPPT techniques. The improved particle swarm optimization (PSO) is smoother due to the enhanced form of MPP tracking. Hence, improved PSO takes 0.038 sec while the existing PSO technique takes 0.045 sec to obtain the MPP tracking.</span>

The Effects of Neem Tree (Azadirachta indica A. Juss) Invasion on the Growth of Indigenous Flora in Katsina State, Northwest Nigeria

Invasive or alien species are increasing in number, extent, and influence worldwide. They are both passengers and drivers of change, and they interact synergistically with many other facets of global change. The Neem trees have been grown successfully in all parts of Nigeria. Neem has become an invasive and naturalized species in various parts of Nigeria in quite diverse ecological and climatic conditions. The tree is adaptable to a wide range of climatic and topographic conditions. The objective of the study is to determine the effect of neem invasion on the growth of indigenous flora in Katsina state. The information on farmers' perception about Neem tree was obtained using semi semi-structured questionnaire. About 200 informants were interviewed. Direct counting of trees was conducted to determine the effect of Neem invasion on the indigenous flora. A total of 58 species of trees belonging to 47 genera within 15 families, of which family Fabaceae has the highest number of tree species, 44 affected by neem invasion in the study area. The result showed the effects of having neem in the farms. Some of the respondents believed that Neem spread easily and nothing grew near it. Others believed that it's difficult to kill and grow back easily. The result indicated a number of tree species found in farms compared to the number of farmers needed for that tree. A lot of farmers preferred indigenous trees then Neem in their farms. In conclusion, in Katsina and from casual observations in the study areas, we have found that Neem is spreading in a way characteristic of an invasive species. They are spread by birds and other animals, becoming numerous under native trees. The trees themselves may become 'weeds. Since farmers in Katsina do not like Neem in their fields, it can be considered a weed, and because it can reproduce in large quantities at a considerable distance from the parent plant, it is, by definition, an invasive plant.

Effect of Cutting Dates on Forage Yield of Three Vicia Varieties (Vicia Spp.) in Sulaimani Governorate.

During the winter season of 2021-2022, a field experiment was conducted at Qlyasan locations in Sulaimani governorate. The aim of this research was to examine the consequence of cutting dates on the yield of forage and seeds, as well as on the components of various Vicia varieties. The experiment was designed as a factorial design and conducted using a randomized complete block design. The least significant difference (L.S.D.) test with a significance level of 5% was used for the statistical analysis. The three Vicia varieties tested were common vetch (Vicia sativa), narbon vetch (Vicia narbonensis), and bitter vetch (Vicia ervilia). Two cutting dates were used, namely, control (Co, no cut), cut 1 (80 days after sowing), and cut 2 (20 days after the first cut). The findings of this research demonstrated that the interaction between common vetch and cutting at 80 days after sowing produced the highest values of the dry matter percentage trait. Meanwhile, the interaction between narbon vetch and cutting 20 days following the initial cut produced the maximum fresh yield (ton/ha) and stem dry weight (g) values. The highest recorded values for the characteristics "pod count per plant" and "seed yield (kg/ha)" were obtained through the interaction between the control treatment and narbon vetch. However, the interaction between cutting at 80 days after sowing and narbon vetch produced the highest values of the 100-seed weight trait (gm). The variation in climatic conditions between seasons may explain these results.

Nutrient availability and stoichiometry mediate microbial effects on soil carbon sequestration in tropical forests

The persistence of soil organic carbon (SOC) is primarily driven by microbial metabolic activities; however, how microbial effects on SOC sequestration are affected by soil nutrient status remains unclear. Here, we conducted a one-year-long in situ soil incubation experiment using mesh bags (with a mesh size of 38 μm, allowing bacterial colonization and fungal hyphal penetration while preventing root penetration). This experiment involved incubating fertile sugarcane soil and infertile sand across an elevational gradient, characterized by diverse climatic and biotic conditions within a tropical forest. Biomarkers, such as phospholipid fatty acids, carbon-, nitrogen-, and phosphorus-acquiring hydrolases, glomalin-related proteins, and amino sugars, were measured to characterize the production and accumulation of microbial biomass, exo-enzymes, extracellular glycoproteins, and microbial necromass. These measurements aimed to elucidate their respective contribution to the sequestration of SOC. We found that Gram-negative bacteria dominated the microbial community composition in fertile soil, and the higher nutrient availability was related to the production and accumulation of microbial necromass via promoting microbial biomass turnover, thus enhancing the accumulation of SOC in fertile soil. This process was negatively associated with phosphorus availability and carbon- and phosphorus-acquiring enzyme activities in fertile soil. In contrast, the SOC accumulation was positively correlated with nitrogen availability and stoichiometry (including C:N and C:P), as well as moisture content in infertile sand. However, more resources were preferentially allocated to stress-tolerant fungi and Gram-positive bacteria under nutrient deficiency in infertile sand used for microbial biomass maintenance, nutrient acquisition, and environmental adaption which further aggravated the consumption of SOC, resulting in SOC loss after one year of field incubation. Our results suggest that microbial effects on SOC persistence are highly context-dependent and nutrient availability-induced changes in microbial communities and microbial resource-allocation strategies are key processes for understanding and predicting the fate of carbon in tropical forest soils.

Earthworm populations and diversity under annual and perennial wheat in a North to South gradient in Western Europe

The challenge to sustain food security while halting the loss of biodiversity and soil quality might be achieved by a transformation in agriculture from high-input management of annual crops to a more nature-based solution introducing perennial cropping systems. This study analysed earthworm communities (numbers, biomass, ecological categories) and diversity over two years, from annual wheat and perennial intermediate wheatgrass (IWG, Thinopyrum intermedium, Kernza®) within the EU-Biodiversa project NAPERDIV from Southern to Northern Europe. Study sites in France, Belgium and Sweden represented diverse soil, climatic and plant growth conditions. In total, 16 species were identified with IWG in France having the highest (13) and annual wheat in Belgium and Sweden the lowest (7) species numbers. Improved biodiversity under perennial wheat was indicated by alpha-diversity indices (Simpson index, Shannon-Weaver index, Evenness). Earthworm abundance and biomass were generally significantly higher in IWG across the three sites (GLMM model). The overall mean earthworm number under IWG was 424.7 No. m−2 compared to 164.7 No. m−2 for annual wheat. Mean earthworm biomass under IWG was 83.7 g m−2 relative to 45.9 g m−2 under annual wheat, respectively. Remarkably, mean number of juvenile earthworms was several times higher on IWG sites relative to the annual comparatives. Moreover, endogeic and epigeic earthworms were supported on the IWG plots. Beta diversity (Sorensen coefficient) emphasised highest similarity between Belgium and Sweden and lowest between France and Sweden, indicating a possible South to North distribution within Western Europe. The Canonical Correspondence Analysis showed discrete clusters for study sites and species distribution (including the subtypes of Allolobophora chlorotica) in relation to soil parameters (pH, soil texture, TOC, TN, WHC, C–N ratio). The CCA additionally discriminated between annual and perennial plots in France. In summary, earthworm communities were more diverse under IWG and seemed to follow a South to North gradient.

Performances Analysis of Three Grid-Tied Large-Scale Solar PV Plants in Varied Climatic Conditions: A Case Study in Algeria

Currently, for the determination of the suitable and optimal PV power plant according to the climate conditions of the concerned region, researchers focus on the estimation of certain performance factors, which are reported to be the key parameters for the analysis of the performances of grid-connected photovoltaic (PV) power systems. In this context, this paper focuses on on-site real-time analysis of the performance of three solar photovoltaic plants: Sidi-bel-Abbés (12 MWp), Laghouat (60 MWp), and Ghardaïa (1.1 MWp). These plants are located in different regions experiencing diverse climatic conditions in Algeria. The analysis was carried out by the standardized norms of IEC 61724, using monitoring data collected over one year. The photovoltaic power plants were evaluated in terms of performance factors, such as the reference yield (Yr), final yield (Yf), performance ratio (PR), and capacity factor (CF). On the other side, based on real data collected at the concerned sites, two linear functions depending on solar irradiance and the PV module temperature for each site are proposed for the evaluation of the generated alternative power output (PAC) for the three PV plants. The obtained results based on the study presented in this paper can help designers of PV power plants of different technologies and different climate conditions to precisely decide the convenient technology that allows the best production of the electrical energy for grid-tied PV systems. Furthermore, this study can contribute in giving a clear vision of the implementation of upcoming large-scale solar PV power plants in Algeria within the studied area and other areas.

Genotype × environment × agronomic management interaction to enhance wheat yield in the Mediterranean rainfed environments of Morocco: II. Process based modeling

Durum wheat (Triticum turgidum subsp. durum) is the oldest and most cultivated cereal crop in Middle East and North Africa (MENA) region and under Mediterranean climatic conditions. Morocco is one of the largest producer of durum wheat in MENA region, cultivated in more than 1 million ha area produced 2.5 million tons in 2020, which accounts for 17% of the total production in the region. In the region, rainfed production system is predominant, and with declining rainfall amounts with high variability, increasing water scarcity, and suboptimal input application, its productivity growth is low and needs to be increased to fulfill the growing demand. Developing context-specific management advisory is needed to improve productivity and resilience under such variable rainfed production environments. Agricultural Production Systems sIMulator (APSIM) model was calibrated and evaluated using four years (2015–2019) of on-station experimental data from genotype × seeding time × water management experiment conducted at International Center for Agricultural Research in the Dry Areas (ICARDA) research station, Morocco. Long-term (1984–2021) simulation was carried out to determine the contribution of Genotype × Environment × Management components for sustainably improving crop productivity. The results showed rainfall or supplementary irrigation (23–36%) followed by N fertilizer (28–38%), cultivar (9–14%), and seeding date (7–14%) have the largest contribution to the yield variance of durum wheat in Merchouch, Meknes, and Sidi El Aidi regions of Morocco. Under rainfed conditions, wheat yield was highest in Merchouch (4.5 t ha−1) and lowest (1.8 t ha−1) in Sidi El Aidi. Due to significant rainfall variability, the seeding date varies across year and location; however, generally, it is between 2nd week of November to 1st week of December. Under rainfed conditions, seeding after 1st week of December caused the average yield reduction of 120, 81, and 31 kg ha−1 d−1 in Merchouch, Meknes, and Sidi El Aidi, respectively. In all locations, short-duration varieties provided higher averaged yields with better resilience than medium and long-duration varieties. Decomposing yield variance caused by Genotype × Environment × Management provides the opportunity for risk reduction, improvement of wheat yield and resilience, and designing climate-smart adaptation strategies in rainfed Mediterranean conditions. Our findings highlight one-size-fits-all approach is inadequate and context-specific tailored agronomic practices and suitable genotypes is crucial for achieving sustainability and resilience of wheat production in variable climatic condition in Morocco and similar production environment.

Assessing the future groundwater vulnerability of an urban region under variable climatic and land use conditions

Climate change and urbanization threaten groundwater resources due to over-abstraction and contamination. Groundwater vulnerability assessment aids in protecting groundwater resources; DRASTIC is the widely used groundwater vulnerability model (GVM) to assess vulnerability. This study uses an optimized DRASTIC framework to assess the impact of climate and land use change on the future groundwater vulnerability of Chennai Metropolitan Area (CMA). The frequency ratio (FR) and metaheuristic (MH) algorithms are coupled to optimize the rates and weights of GVM to reduce subjectivity. The climatic variables and land use projected for the future period 2030 and 2050 under RCP4.5 and RCP8.5 scenarios. The projected net recharge for the study region varies from 349.95 mm/yr to 458.95 mm/yr, and depth to groundwater level ranges between 4.92 and 6.42 mbgl for scenarios 1 to 4. The RCP4.5 scenario for the far future period (scenario-2) shows an increase in the vulnerability class by 41.64%, and RCP8.5 scenario for the far future period (scenario-4) exhibits a decrease in the vulnerability class by 20.67% of the total area. The integrated groundwater vulnerability analysis found that the CMA groundwater system is in critical condition of high vulnerability for near and far future periods.

An Interpretable High-Accuracy Method for Rice Disease Detection Based on Multisource Data and Transfer Learning.

With the evolution of modern agriculture and precision farming, the efficient and accurate detection of crop diseases has emerged as a pivotal research focus. In this study, an interpretative high-precision rice disease detection method, integrating multisource data and transfer learning, is introduced. This approach harnesses diverse data types, including imagery, climatic conditions, and soil attributes, facilitating enriched information extraction and enhanced detection accuracy. The incorporation of transfer learning bestows the model with robust generalization capabilities, enabling rapid adaptation to varying agricultural environments. Moreover, the interpretability of the model ensures transparency in its decision-making processes, garnering trust for real-world applications. Experimental outcomes demonstrate superior performance of the proposed method on multiple datasets when juxtaposed against advanced deep learning models and traditional machine learning techniques. Collectively, this research offers a novel perspective and toolkit for agricultural disease detection, laying a solid foundation for the future advancement of agriculture.

Techno-economic analysis on prospects and implementation of employing radiative cooling technology across broader atmospheric conditions

Achieving a transition to maximize the utilization of radiative cooling as a passive cooling strategy is challenging for several regions worldwide, mainly due to unawareness, lack of government support, and extreme seasonal climatic variations. Being characterized by a variety of atmospheric conditions from tropical coastline to arid regions along with humid highland areas to regions with continental atmospheric conditions, Pakistan faces significant seasonal and daily variations in atmospheric parameters, such as solar irradiance, temperature, precipitation patterns, humidity, etc., making it a steppe country with diverse atmospheric conditions and an energy-intensive economy dominated by fossil fuels. Therefore, following United Nation's Sustainable Development Goals, here we investigate the radiative cooling potential resource map across Pakistan, providing it as a sustainable alternative to lower the cooling demand by maximizing the emitted thermal radiation to the deep space and minimizing solar irradiance absorption by utilizing the materials' inherent properties of being highly reflective within solar spectrum range and extremely emissive within the atmospheric window. A comprehensive comparison between annual, seasonal, diurnal, and nocturnal radiative cooling capability is conducted and analyzed across all provinces of Pakistan based on the variation in regional climatic conditions. The yearly average radiative cooling capacity varies from 69.39 to 96.41 W/m2 due to swift variation from humid continental to arid climatic regions, with a 24.27 % discrepancy in daytime and nighttime radiative cooling potentials owing to the significant influence of solar irradiance. An office building model incorporating radiative cooling coating at the rooftop is further implemented to illustrate the real-case scenarios of using radiative cooling coatings as a cool roof. Compared to traditional roofs, applying radiative cooling coatings on the rooftop of a single-storey office building can reduce the annual cooling load by 76.01 to 112.77 kWh/(m2.year) for various cities under diverse climatic conditions. The annual electricity savings in several cities are estimated to be 30.40 to 45.11 kWh/(m2.year) based on the refrigerator COP of 2.5. The application of radiative cooling coatings on rooftops induces the incremental cost of 24 $/m2, with a simple payback period of 5.32 to 7.89 years in response to annual electricity savings across varying meteorological conditions. Besides, the maximum carbon emissions reduction is estimated to be up to 27.77 kg/(m2.year) based on a carbon emission factor of 0.606 kgCO2/kWh. In the end, valuable insights are discussed based on policy recommendations and limitations for developing strategies to adapt the radiative cooling technology on a broader scale based on innovative solutions, spreading public awareness, and offering financial incentives.

S13-2 VARCITIES puts the citizens and the 'human community' in the eye of the future cities’ vision

Abstract In an increasingly urbanized world, local governments and international institutions strive to increase the productivity and efficiency of cities, recognized as economic growth hubs, as well as ensure a better quality of life and better living conditions for citizens. To meet these challenges, VARCITIES puts the citizen and the “human community” in the eye of the future cities’ vision. The aim of the VARCITIES project is to translate visionary ideas into real solutions by reshaping shared public spaces and making cities livable and welcoming. Seven municipalities that are exposed to diverse climatic conditions and challenges around Europe have been identified as case studies. Each pilot city has recognized a large-scale site for co-designing and implementing local actions and has adopted an innovative cross-sectoral approach by combining urban digital transformation with nature-based actions. This innovative solution's implementation is consistent with the increase in citizens' awareness, respect for public spaces, and the integration of green spaces into everyday life. Developing a healthy green mindset for citizens and improving economic opportunities through green-digital strategies, drives the implementation of additional actions towards becoming a more sustainable and equitable city. The development process of these visionary ideas into feasible actions is approached by following a bottom-up planning and co-design participatory process involving local stakeholders, assuming a “multiple benefits” perspective, and also addressing social issues and cultural diversion.

S13-1 VARCITIES puts the citizens and the 'human community' in the eye of the future cities’ vision

Abstract In an increasingly urbanized world, local governments and international institutions strive to increase the productivity and efficiency of cities, recognized as economic growth hubs, as well as ensure a better quality of life and better living conditions for citizens. To meet these challenges, VARCITIES puts the citizen and the “human community” in the eye of the future cities’ vision. The aim of the VARCITIES project is to translate visionary ideas into real solutions by reshaping shared public spaces and making cities livable and welcoming. Seven municipalities that are exposed to diverse climatic conditions and challenges around Europe have been identified as case studies. Each pilot city has recognized a large-scale site for co-designing and implementing local actions and has adopted an innovative cross-sectoral approach by combining urban digital transformation with nature-based actions. This innovative solution's implementation is consistent with the increase in citizens' awareness, respect for public spaces, and the integration of green spaces into everyday life. Developing a healthy green mindset for citizens and improving economic opportunities through green-digital strategies, drives the implementation of additional actions towards becoming a more sustainable and equitable city. The development process of these visionary ideas into feasible actions is approached by following a bottom-up planning and co-design participatory process involving local stakeholders, assuming a “multiple benefits” perspective, and also addressing social issues and cultural diversion.

Exploring the Potential of Phase Change Material for Thermal Energy Storage in Building Envelopes

Buildings, with their significant energy consumption, pose a pressing concern for the future. Inadequate heating, ventilation, and air-conditioning (HVAC) systems further exacerbate thermal management difficulties and energy requirements. To address these challenges, Phase Change Materials (PCMs) offer valuable potential for sustainable energy reduction within the building sector, leveraging passive cooling and heating techniques. Numerical study has been conducted to explore the impact of embedding PCM within the building envelope on energy efficiency and thermal performance. The results reveal that PCM integration significantly reduces temperatures across all sections compared to scenarios without PCM. By passively absorbing and storing heat energy during phase change, PCM mitigates heat transfer through convection and conduction, leading to improved energy efficiency and reduced power consumption for cooling and heating purposes. Within the first 2 hours, the PCM achieves 50% of its average melting process, followed by a gradual decrease in the melting rate. It takes approximately 6 hours for the PCM to completely melt. As the PCM undergoes the melting process, the system's entropy values increase, reflecting an increase in disorder. At the tip of the building, the entropy value reaches 130 K/kg·K, which is more than three times the initial value. The integration of PCM in building envelopes shows promising potential for enhancing energy efficiency, thermal comfort, and durability. Future research should focus on optimizing PCM placement and configuration to maximize its benefits in diverse building designs and climatic conditions.

Interannual variability of carbon dioxide (CO2) and methane (CH4) fluxes in a rewetted temperate bog

Peatland rewetting, a management effort to restore water levels in previously drained peatlands, is important for re-establishing the role of these peatlands as carbon (C) sinks. Since rewetted peatlands have a highly variable response to interannual variations in climatic conditions and functional changes, long term studies of C fluxes in these ecosystems are needed. Here, we evaluated the impact of climate variability and functional change on the interannual variability of CO2 and CH4 fluxes at Burns Bog, a rewetted temperate bog on the Pacific Coast in Canada, based on five years of eddy covariance measurements. We found that the site alternated between being an annual-scale net CO2 sink or source, ranging from -32.6 ± 21.5 (±95% CI) to 11.9 ± 15.1 g CO2C m-2 yr-1, respectively, while consistently being a CH4 source, ranging from 11.6 ± 0.7 to 18.0 ± 1.6 g CH4C m-2 yr-1. Over the five-year period, mean annual CH4 emissions (13.7 ± 2.5 g CH4C m-2 yr-1; ±SD across years) entirely offset the CO2 sink (-12.3 ± 20.4 g CO2C m-2 yr-1), resulting in the site being near-carbon neutral over this period (1.3 ± 23.9 g C m-2 yr-1). This finding indicates that excluding CH4 fluxes from the net C balance results in an overestimation of the net C uptake at this site. Annual CO2 emissions from the bog were greatest in the year with a dry and warm summer, emphasizing the importance of temperature and water table depth at the bog. Regardless of the greenhouse gas (GHG) metrics (i.e., global warming potential or sustained global warming potential) used in calculating the annual CO2-eq balance, the site consistently had a positive GHG balance across the study period. Despite mainly acting as a GHG source, the rewetted site will likely have a cooling effect on the climate system over long timescales compared to drained bogs that are large CO2 sources.

GENOTYPIC VARIABILITY OF ACER NEGUNDO L. ALONG THE TRANS-SIBERIAN RAILWAY

The study of intraspecific variability of alien plants is crucial for revealing the patterns of their microevolution in the secondary distribution range and predicting the possibility of further dispersal and the ability to invade natural plant communities. It is still unclear how a genetically impoverished initial invasive population forms a taxon with a range exceeding the natural range of the species and, therefore, adapted to more diverse ecological and climatic conditions. Boxelder, Acer negundo L., is a remarkable object of study in this respect. The secondary distribution range of this North American species covers all regions of our plane excluding Antarctica. In Russia it spread from Kaliningrad to Vladivostok, formed invasive populations in all eight Federal Districts and was included in the TOP 100 of the most aggressive invasive species of the country. The intraspecific variability of its biomorphological characters was studied by us earlier, and the results of the study of genotypic variability are presented in this article. Invasive populations of A. negundo located along the Trans-Siberian Railway from Moscow to Vladivostok (9288 km) were examined. We isolated DNA from 38 specimens collected along the Trans-Siberian railway in Vladimir and Kostroma Regions, Republic of Tatarstan, Perm Region, Novosibirsk Region, Krasnoyarsk Territory, Amur Region, and Primorskii Territory. By the ITS 1-2 nuclear DNA site, specimens of Acer negundo from the Russian part of the secondary distribution range showed very high similarity with each other, but with 100% bootstrap support separated from specimens from the natural distribution range. According to the chloroplast high-variable trnL-trnF site, the specimens were divided into two clades that weakly correlated with the geographical origin of the specimen. Separate subclades with high bootstrap support are formed by the plants: 1) from Tatarstan (Kazan and Nizhnekamsk), 2) from Perm and Novosibirsk, and 3) samples from Krasnoyarsk. The haplotype network constructed at the trnL-trnF site also demonstrated the genetic specificity of the samples from Tatarstan. We hypothesized that only a few genotypes of A. negundo with a high degree of invasive activity were dispersed along the Trans-Siberian Railway (and possibly throughout all Russia). Other genotypes, including those that entered the territory of the former Russian Empire earlier, have not shown the ability to invade natural plant communities and occur rather rarely.