Future Conditions Research Articles

Financial intermediation and informational efficiency: Predicting business cycles

Theory posits that financial intermediation (FI) spurs economic growth and supports financial system stability by reducing informational asymmetries and agency problems. Most of this literature focuses on bank lending and has limited success in capturing changes in macroeconomic aggregates. We consider a large set of different financial intermediaries to show that aggregate FI assets contain leading information about real GDP, investment, consumption, industrial production, and unemployment. Bank and shadow bank assets alone contain only limited information about future states of the economy. Overall, FI improves informational efficiency of the markets by providing transparent leading signals of the future economic conditions.

Predictive Modelling of Sea Debris around Maltese Coastal Waters

The accumulation of sea-surface debris around the coastal waters of Malta poses significant ecological and environmental challenges, negatively affecting marine ecosystems and human activities. This issue is exacerbated due to the lack of an effective system tailored to predict surface-debris movement specifically for the Islands of Malta. To address this gap, a pipeline that combines a machine learning-based prediction system with a physics-based model is proposed. This pipeline uses data on historical sea-surface current velocities to forecast future conditions and visualise debris movement. Central to this system are two machine learning models trained to predict surface velocities for the next 24 h for a specific area. These predictions are then utilised in a Lagrangian model to simulate and visualise the debris movement, providing insights into future dispersion patterns. A comparative evaluation of both models using real-world data is made to determine which one performs best in this application. This method offers a tailored approach to addressing sea-surface debris around Malta by accurately predicting sea-surface current velocities and visualising debris movement, improving cleanup operations and marine conservation strategies.

Current and Future Distribution of the Cataglyphis nodus (Brullé, 1833) in the Middle East and North Africa

Climate change is a major threat to the Middle East and North Africa (MENA) region, which can cause significant harm to its plant and animal species. We predicted the habitat distribution of Cataglyphis nodus (Brullé, 1833) in MENA using MaxEnt models under current and future climate conditions. Our analysis indicates that the cooler regions of the MENA are projected to experience temperature increases of 1–2 °C by 2040 and 2–4 °C by the 2070s. Similarly, the warmer regions may anticipate rises of 0.5–2 °C by 2040 and 2–4 °C by the 2070s. MaxEnt model results for the current climate show good agreement with observations (mean area under the curve value of 0.975 and mean true statistical skill value of 0.8), indicating good potential habitat suitability for C. nodus. Significant factors affecting habitat suitability are elevation, mean monthly precipitation of the coldest quarter, temperature seasonality, and precipitation amount of the driest month. The research predicts that under Shared Socioeconomic Pathway (SSP) 1.2.6, the habitat suitability area may increase by 6% in 2040, while SSP 3.7.0 (0.3%) and SSP 5.8.5 (2.6%) predict a decrease. For 2070, SSP 5.8.5 predicts a 2.2% reduction in habitat suitability, while SSP 1.2.6 (0.4%) and SSP 3.7.0 (1.3%) predict slight increases. The results provide insight into the potential impacts of climate change on the species and regional biodiversity changes associated with the projected species distribution.

Modeling freezing and BioGeoChemical processes in Antarctic sea ice

AbstractThe Antarctic sea ice, which undergoes annual freezing and melting, plays a significant role in the global climate cycle. Since satellite observations in the Antarctic region began, 2023 saw a historically unprecedented decrease in the extent of sea ice. Further ocean warming and future environmental conditions in the Southern Ocean will influence the extent and amount of ice in the Marginal Ice Zones (MIZ), the BioGeoChemical (BGC) cycles, and their interconnected relationships. The so‐called pancake floes are a composition of a porous sea ice matrix with interstitial brine, nutrients, and biological communities inside the pores. The ice formation and salinity are both dependent on the ambient temperature. To realistically model these multiphasic and multicomponent coupled processes, the extended Theory of Porous Media (eTPM) is used to develop Partial Differential Equations (PDEs) based high‐fidelity models capable of simulating the different seasonal variations in the region. All critical variables like salinity, ice volume fraction, and temperature, among others, are considered and have their equations of state. The phase transition phenomenon is approached through a micro‐macro linking scheme. In this paper, a phase‐field solidification model [4] coupled with salinity is used to model the microscale freezing processes and up‐scaled to the macroscale eTPM model. The evolution equations for the phase field model are derived following Landau‐Ginzburg order parameter gradient dynamics and mass conservation of salt allowing to model the salt trapped inside the pores. A BGC flux model for sea ice is set up to simulate the algal species present in the sea ice matrix. Ordinary differential equations (ODE) are employed to represent the diverse environmental factors involved in the growth and loss of distinct BGC components. Processes like photosynthesis are dependent on temperature and salinity, which are derived through an ODE‐PDE coupling with the eTPM model. Academic simulations and results are presented as validation for the mathematical model. These high‐fidelity models eventually lead to their incorporation into large‐scale global climate models.

Spatial and Temporal Changes in Habitat Quality and Driving Forces in Typical Loess Hill and Gully Areas：A Case Study of the Zuli River Basin

Loess hills and gully areas are one of the important ecological barriers in China, and the study of the spatial and temporal changes of its habitat quality and its driving force is of great significance to guaranteeing the ecological security of China and safeguarding the national ecological rights and interests. Taking the Zuli River Basin as an example, the spatiotemporal distribution of the remote-sensing ecological index （RSEI） from 2000 to 2020 was systematically investigated using the Google Earth Engine platform and Landsat remote-sensing data. Combined with the coefficient of variation CV, the Theil-Sen Median slope estimation, the Mann-Kendall test of significance, and the Hurst index, the spatial and temporal changes of habitat quality in the study area were analyzed over a period of 20 years, and the effects of six major driving factors on the spatial distribution of RSEI were investigated using the geodetector method. The results of the study showed that： ① From 2000 to 2020, the value of the RSEI showed a downward and then upward trend, with an average annual increase of 0.084 5·（10 a）-1. ② During the 20-year period, the habitat quality improvement area accounted for 92.06%, of which the significant improvement area accounted for 28.49%, and the improvement area was mainly in Huining County, whereas the habitat degradation area only accounted for 7.82%. The trend of future ecological conditions showed that 74.98% of the areas would show a trend of continuous improvement or future improvement, but there would still be a potential risk of ecological degradation in 23.48% of the areas in the future. ③ Climate factors such as precipitation were the key factors affecting the habitat quality in the Zu Li River Basin； the interaction between factors had a higher explanatory power than that of any single factor on the habitat quality, among which the interaction between the precipitation factor and the elevation factor had the strongest explanatory power. The interaction between the terracing factor and the environmental factor significantly increased the explanatory power of the spatial variance, which indicated that terracing played an important role in improving habitat quality. The results of this study can provide a scientific basis for the management and sustainable development of the ecological environment in the loess hills and gullies.

Exploring the Opportunities and Gaps in the Transformation of Modern Rural Housing in Southern China to Net Zero Energy Buildings

This study explores modern residential buildings in rural areas of Wuhan and Guangzhou to assess the feasibility of achieving net zero energy buildings (NZEBs) through the transformation of existing buildings in southern China’s hot-summer–cold-winter and hot-summer–warm-winter regions. Energy simulations under various climatic scenarios identify effective energy-saving measures, such as the use of photovoltaic power generation. The results highlight substantial renovation potential, with energy reductions of approximately 85 kWh/m² (RCP2.6), 90 kWh/m² (RCP4.5), and 115 kWh/m² (RCP8.5). Living patterns significantly influence energy use, especially in buildings with more rooms, where the gaps in the energy demand with net zero standards can reach 560.56 kWh. At the monthly scale, different climate scenarios impact the feasibility of achieving NZEBs, particularly under RCP8.5, where eight rural housing types fail to meet the requirements, with six exceeding 200 kWh energy deficits and the largest energy deficit occurs in June 2090 in Guangzhou, reaching 592.53 kWh, while under RCP2.6, only two buildings with more rooms fail to meet NZE. In summary, in the hot-summer cold-winter region, the energy demand is higher but so is the solar yield. Therefore, under the most adverse RCP8.5 scenario, NZEBs are achievable for 9 months of the year, which is 2 months more compared to Guangzhou under similar conditions. Even after net zero transformation, new rural housing will face greater energy-saving challenges in future climatic conditions, especially under higher concentration pathways.

Effective factors on the development of bodybuilding and fitness clubs in Mashhad, Iran

The aim of this study was to investigate the effective factors in the development of bodybuilding and fitness clubs in Mashhad, Iran. This study was practical in terms of its goals, with an exploratory and analytical implementation method, classifying it as qualitative research. A total of 27 individuals were targeted and selected as samples until theoretical saturation was reached, including athletes, coaches, managers of fitness and bodybuilding clubs, members of the academic faculty of sports sciences at universities, experts from sports departments, and seniors in the field of bodybuilding in Mashhad. For data analysis, the data coding method was employed within a grounded theory framework. Based on the results, the factors affecting the development of bodybuilding and fitness clubs in Mashhad were identified in four main categories, ten sub-categories, and seventy-two components, according to expert opinions and a literature review in this field. These factors included: 1) Facility and infrastructure factors, 2) Financial and economic factors, 3) Professionalism factors, 4) Human resource factors, 5) Event factors, 6) Scientific and educational factors, 7) Organizational and managerial factors, 8) Motivational factors, 9) Media factors, and 10) Cultural-social factors. By creating and facilitating this model, the development steps for Mashhad's fitness clubs will be implemented to better align with future implementation conditions.

Future Shorelines: A Living Shoreline Site Selection and Design Decision Support Tool that Incorporates Future Conditions Induced by Sea Level Rise

Most living shoreline site selection and design decision support tools are based upon existing environmental conditions. We developed a web-based, geospatial tool called Future Shorelines that integrates high-resolution landscape elevation data and a matrix of locally derived NOAA Interagency Sea Level Rise Scenarios to characterize future conditions of submergence and shoreline translation induced by sea level rise. Once the practitioner selects a location of interest, sea level rise scenario (e.g., high), and target year (e.g., 2050), the tool will generate plan view and cross-sectional informational graphics specific to their choices. This information can then be paired with other menu options, like parcel ownership, to facilitate the planning and construction of nature-based shoreline stabilization solutions that (1) are located where opportunities for horizontal migration are optimized, (2) remain accessible for monitoring and maintenance, and (3) perform as intended over the design life of the installation. The tool’s menu options and the user interface were informed by project partner input solicited during numerous workshops convened over the duration of the 2-year project. This coproduction created a product that was familiar to the end user and therefore increased the likelihood that it would be utilized by them during the planning and design of living shoreline projects. Although developed for use in the Indian River Lagoon, located along the east-central Florida coast, it can be seamlessly replicated for application in other coastal regions of the USA where the requisite data are available.

Impact of climatic factors on water quality parameters in tilapia broodfish ponds and predictive modeling of pond water temperature with ARIMAX

Climate change represents a considerable threat to aquatic ecosystems, potentially affecting various water quality parameters.The study aims to assess the impacts climatic factors on the water quality parameters in tilapia broodfish pond and forecasting of water temperature in a tilapia broodfish pond using the ARIMAX model. Daily longitudinal time series data on water quality parameters were collected from the pond, while monthly climatic data were obtained from the Bangladesh Meteorological Department. Water temperature exhibited seasonal variation, peaking at 31.23 °C in October and dropping to 20.8 °C in December. pH levels ranged from 7.36 to 10.32, with the lowest recorded in December and the highest in August. Dissolved oxygen levels varied from 7.09 mg/L to 10.65 mg/L, with the lowest in September and the highest in January. Ammonia levels were highest in February at 0.33 mg/L. Water transparency ranged from 15.37 to 28 inches, with the highest in January and the lowest in June. Climatic factors significantly influenced these variations, as specified by Canonical correlation analysis (CCA). The best-fitting model, ARIMAX (1, 0, 1), indicated a fluctuating trend influenced by important exogenous factors like air temperature and solar intensity. By the end January 2025, the water temperature is expected to rise to 27.93 °C. This is a noticeable increase started from November to January. These higher temperatures may improve tilapia broodfish growth and development earlier. But the temperatures are predicted to drop started from February to March, which could negatively affect tilapia growth and development. A clear seasonal fluctuating pattern is exhibited in the future. These findings provide important insights for researchers, policymakers, academics, and those involved in tilapia farming. By considering air temperature and solar intensity in planning, stakeholders can better anticipate future pond conditions. Developing adaptive management strategies to reduce negative impacts and make the most of favorable conditions will be essential for sustainable tilapia production in the context of climate change.

Season-dependent climate sensitivity of the surface runoff of major rivers in Changbai Mountain

Due to the sensitivity of runoff to changes in seasonal snowpack, the changes in surface runoff within high-latitude and high-elevation areas are more complex than in other areas. However, this sensitivity is often overlooked when correlating changes in runoff with meteorological variables. Here, we analyze changes in surface runoff during snowmelt and snowless periods and their sensitivity to climate change from 1960 to 2019 in the upstream watersheds of the Songhua, Yalu, and Tumen Rivers in Changbai Mountain. Most runoff indices, except for low flow in the Yalu River, exhibited decreasing trends during snowmelt and snowless periods. Precipitation was the primary variable responsible for surface runoff during snowless and snowmelt periods. Notably, rainfall replenished all runoff indices during snowless periods, particularly under high flow conditions. The average and high flows were also primarily supplemented by rainfall during snowmelt periods. However, low flow was positively correlated with snowmelt in the Songhua and Tumen Rivers and with temperature in the Songhua, Yalu and Tumen Rivers during snowmelt periods. Additionally, extreme runoff events were closely associated with extreme precipitation. These findings demonstrate the seasonal and index-dependent climate sensitivity of surface runoff within Changbai Mountain, offering insights into the surface runoff response mechanism to climate change in high-altitude mountainous areas. Under future climate change conditions, frequent and intense extreme precipitation events may increase the risk of flooding, owing to the high sensitivity of high flows to precipitation, posing a serious threat to regional ecological security.

Development of Pavement Deterioration Models Using Markov Chain Process

A common phenomenon in developing countries is that the function of the pavement in the road network will experience structural damage before the completion of life is reached, and the uncertainty of pavement damage is difficult to predict. Planning for maintenance treatment depends on the accuracy of predicting future pavement performance and observing current conditions. This study aims to apply the Markovian probability operational research process to develop a decision support system predicting future pavement conditions. Furthermore, it determines policies and effectiveness in managing and maintaining roads. A standard approach that can be used by observing the history of pavement damage from year to year is to estimate the transition probability as a Markovian-based performance prediction model. The results show that the application of the model is quite optimal, changes in pavement conditions after repair can be easily compared with an increase in good condition, reaching 92.8%. Routinely and consistently handling road deterioration will give favorable results regarding pavement condition value. This will ease in the management of the road network and the accomplishment of the optimal maintenance and repair policies. Doi: 10.28991/CEJ-2024-010-09-012 Full Text: PDF

Climate change and extremes in the Mediterranean island of Cyprus: from historical trends to future projections

Cyprus is a European island state in the eastern Mediterranean climate change hotspot. Despite being a relatively small island, it has diverse climatic zones, ranging from semi-arid to subhumid in the mountains and humid on Mount Olympos. Given the accelerated rate of environmental change in the region, the present study aims to identify, and update observed trends of critical climate parameters, highlighting vulnerable climatic areas within the island. Moreover, since nationwide multi-model assessments of future climate conditions are limited or outdated, we aim to investigate the range of future climate projections using a 21-member EURO-CORDEX ensemble under pathways RCP2.6 and RCP8.5. Besides mean conditions, we analyze various extreme climate indicators relevant to socio-economic activities such as agriculture, biodiversity, tourism, energy and water resources. Our historical analysis revealed a statistically significant increasing temperature trend (0.4 °C–0.6 °C per decade), which is more pronounced during the summer and spring. Concerning precipitation, the observed trends are not as robust, nevertheless, the southeastern coast and the central regions near the capital city of Nicosia are substantially drier and more prone to further changes in precipitation regimes. The projections for the end of the 21st century, according to the high radiative forcing scenario (RCP8.5), indicate that Cyprus is likely to experience an annual temperature increase of over 4 °C and an approximate 20%–30% reduction in annual rainfall, relative to 1981–2000. These projections highlight an alarming trend that requires urgent attention and proactive measures to mitigate the potential impacts of climate change on the island.

Differential effects of increasing temperature on the germination of five wild species with varying range sizes in a Carrara marble quarry

Assessing the performance of spontaneous plants in abandoned quarries under future environmental scenarios is important for successful restoration practises. Air warming is one of the most relevant ongoing climatic changes in the Mediterranean. We tested the effects of increasing temperature on the germination of five species spontaneously colonising the abandoned sectors of a Carrara marble quarry (Tuscany, central Italy). We selected five plant species with different widths of their distribution range, from local endemic to invasive alien: Santolina pinnata, Globularia incanescens, Hypericum coris, Helichrysum italicum, and Buddleja davidii. Seeds were collected in situ and their germination was tested in laboratory conditions at 10, 15, 20, 25, and 30 °C. The effects of temperature and species on germination percentage (GP) and mean germination time (MGT) were tested through two-way ANOVA. Increasing temperatures negatively affected the GP of S. pinnata and H. coris. G. incanescens performed better at intermediate temperatures, whilst H. italicum benefited from increasing temperatures. B. davidii showed a similar high GP under all the treatments. MGT decreased with increasing temperature for all the species, except for S. pinnata, which showed an increase of MGT with increasing temperature. We highlighted that, under future warmer climatic conditions, the two endemic species will be disadvantaged with respect to the species with a wider distribution range and the non-native species in the studied quarry. This evidence is relevant for restoration planning since seeding the two endemic species could be unsuccessful under future environmental scenarios, when H. italicum and B. davidii will be more competitive in the colonisation of the quarry.

The ant and the grasshopper: Contrasting responses and behaviors to water stress of riparian trees along a hydroclimatic gradient

Riparian trees are particularly vulnerable to drought because they are highly dependent on water availability for their survival. However, the response of riparian tree species to water stress varies depending on regional hydroclimatic conditions, making them unevenly vulnerable to changing drought patterns. Understanding this spatial variability in stress responses requires a comprehensive assessment of water stress across broader spatial and temporal scales. Yet, the precise ecophysiological mechanisms underlying these responses remain poorly linked to remotely sensed indices. To address this gap, the implementation of remote sensing methods coupled with in situ validation is essential to obtain consistent results across diverse spatial and temporal contexts. We conducted a multi-tool analysis combining multispectral and thermal remote sensing indices with in situ ecophysiological measurements at different temporal scales to analyze the responses of white poplar (Populus alba) to seasonal changes in drought along a hydroclimatic gradient.Using this approach, we demonstrate that white poplars along the Rhône River (France) exhibit contrasting responses and behaviors during drought depending on the latitudinal context. White poplars in a Mediterranean climate show rapid stomatal closure to reduce water loss and maintain high minimum water potential levels, although this results in a decrease in remotely sensed greenness. Conversely, white poplars located upstream in a temperate climate show high transpiration and stable greenness but lower minimum water potential and water content. A site in the middle of the gradient has intermediate responses. These results demonstrate that white poplars along a climate gradient can have a range of responses to drought along the iso/anisohydricity continuum.These results are important for future climatic conditions because they show that the same species can have different mechanisms of drought resilience, even in the same river valley. This raises questions regarding how these riparian tree populations will respond to future climatic and hydrological conditions.

Transcriptome analysis and characteristics of drought resistance related genes in four varieties of foxtail millet [Setaria italica]

Foxtail millet [Setaria italica] plays a crucial role as a multigrain crop in agricultural production. However, due to future extreme weather conditions, drought remains the main abiotic stress that limits foxtail millet yield, it is highly significant to screen for drought-tolerant varieties throughout the entire growth period and identify the regulatory genes associated with drought resistance in foxtail millet breeding. We identified 217 foxtail millet seed resources for drought resistance during the maturity stage in the field, and subsequently categorized them into different levels of drought resistance. Two cultivars with extremely strong drought resistance during the maturity stage in the field, JKH4 (Chi 5422) and JKH6 (Chigu 26), as well as two cultivars with extremely weak drought resistance during the maturity stage in the field, JRK3 (17M1309) and JRK6 (Canggu 9), were selected for physiological comparison and transcriptome sequencing before and after drought treatment. Transcriptome analysis at the seedling stage revealed that JRK3 and JRK6 cultivar primarily regulated phenylpropanoid biosynthesis, MAPK signaling pathogen-plant, and plant hormone signal transduction pathway in response to drought stress. On the other hand, the fatty acid elongation pathway of JKH4 and JKH6 variety was found to be more significant. Furthermore, 22 drought resistance related genes were screened through transcriptome analysis of four foxtail millet varieties. These findings could offer valuable theoretical guidance for breeding foxtail millet with enhanced drought resistance and potentially facilitate the development of genetically engineered drought-resistant foxtail millet varieties.

Ventenata dubia projected to expand in the western United States despite future novel conditions

<i>Ventenata dubia</i> projected to expand in the western United States despite future novel conditions

Habitat shifts of the vulnerable crinoid Leptometra phalangium under climate change scenarios

Crinoid beds of Leptometra phalangium (Müller, 1841) have been identified as sensitive habitats by the General Fisheries Commission for the Mediterranean (GFCM) due to their high vulnerability to bottom trawl fisheries. Poorly resilient to physical damage, L. phalangium has been listed as a potential indicator of Vulnerable Marine Ecosystems (VMEs) in the Mediterranean Sea. If fishing activities represent the main cause of habitat destruction for this species, the ongoing changes in climate conditions may rapidly exacerbate the process. In this study, we developed an ensemble Species Distribution Modeling framework to predict the potential habitat of L. phalangium for present-days in the Mediterranean Sea, and used the model to infer potential changes in its spatial distribution by 2050 under two different climate scenarios (IPCC Representative Concentration Pathways RCP2.6 and RCP8.5). True presence-absence records were used and correlated to a parsimonious set of environmental predictors considered as important drivers of benthic species distribution. In present conditions, L. phalangium seems to be widely distributed along the continental slopes of the western and central Mediterranean. This crinoid is often described as confined to the continental shelf-break (100–200 m), but our results show that it can be found over a wider depth range, between 100 and 500 m. Our predictions obtained for the mid-21st century indicate an important habitat loss for L. phalangium under future climate conditions, mainly in the central and southern basins. Declines of 50 to 70 % in its suitable habitat were predicted under RCP2.6 and RCP8.5 compared to present-day predictions. Climate refugia (i.e., areas where environmental conditions remain suitable for the species in the future) were restricted to the northwestern basin (e.g., Gulf of Lion, the Catalan Sea, the Balearic Sea, Ligurian Sea) and in the southern Adriatic Sea. Provided by a robust statistical framework, climate refugia predictions, along with uncertainty assessments, must support the identification of priority areas for the conservation of VME indicator species by governmental bodies and regional management organizations.

Ecological niche modeling to identify cultivation areas for pineapple in the Republic of Benin

Pineapple is one of the most important tropical fruit species, widely cultivated and economically important in Benin. This study aimed to identify potentially favorable areas for the cultivation of pineapple under current and future environmental conditions in Benin. The two cultivars of pineapple grown in Benin were separately considered: Sugarloaf and Smooth Cayenne. Five (05) modeling algorithms such as Maxent, Random Forest (RF), Support-Vector Machines (SVM), Boosted Regression Trees (BRT) and Generalized Linear Model (GLM) were compared using the criteria: area under the curve (AUC), sensitivity, specificity, Cohen’s Kappa, deviance and True Skill Statistic (TSS). The future climate models available for Africa at horizon 2055 were used under the “Representative Concentration Pathways” scenario 4.5 and 8.5. Results suggested that pineapple suitable areas were governed by a combination of effects of climate (temperature and precipitation) and soils characteristics. Indeed, soil pH, temperature seasonality and precipitation of driest quarter were the main variables driving pineapple production in Benin. Results also indicated that RF was the most suitable technique to model the distribution of pineapples regardless of the variety. The current potential range of favorable areas for the two varieties was mainly found in the central and southern parts of the country. In the future, following the RCP4.5 scenario, there will be an increase in the area favorable for the cultivation of Smooth Cayenne variety by 5.28% compared to the current situation whereas, the area favorable for the cultivation of the Sugarloaf variety will be increased by 7.7%. However, suitable areas for cultivation of Smooth Cayenne and Sugarloaf following the RCP8.5 scenario will be increased, respectively by 21.82% and 31.64%. The low and medium suitability areas for the cultivation of smooth cayenne will decrease by 15.57% and 2.93%, respectively at the horizon 2055 with future conditions under RCP4.5, and 15.48% and 4.97%, respectively at the horizon 2055 with future conditions under RCP8.5. For sugarloaf, the low and medium suitable cultivation areas will decrease by 1.59% and 14.24, respectively at the horizon 2055 with future conditions under RCP4.5. According to RCP8.5, the low suitable areas will decrease by 5.08%. This study constitutes an initial step towards a sustainable scheme for planning exploration of the possibility of extending pineapple cultivation in Benin. Key words: Climate change, modeling, algorithms, pineapple, potential area distribution

Designing A Visible Light Driven TiO2-Based Photocatalyst by Doping and Co-Doping with Niobium (Nb) and Boron (B)

Water pollution has emerged as a significant worldwide issue, with organic pollutants being a key contributor. Titanium dioxide (TiO2) has demonstrated promising photocatalytic performance in removing organic pollutants under ultraviolet (UV) irradiation. However, the wide band gap (3.2 eV) of TiO2 results in low absorption capacity of visible light, hindering its overall efficiency in degrading organic pollutants. To address the limitation, this research aimed to synthesize visible light-driven TiO2 photocatalyst with different polymorphs (anatase and rutile) and investigate the effect of various doping combination (Nb, B and Nb,B) and concentrations (0.25, 0.50, 0.75 and 1.00 mol%) on the photodegradation efficiency towards methylene blue (MB) dye solution. Anatase phase was obtained when TiO2-based nanopowders were calcined at 400 °C, while the rutile phase was formed at 900 °C based on XRD analyses. Additionally, the morphology analyses revealed that the particle size of anatase is much smaller than that of rutile. The presence of dopants further reduced the particle size of both anatase and rutile phases. Based on UV-Vis absorbance spectra analyses, the anatase Nb,B-TiO2 with 0.50 mol% of dopant concentration exhibited the best photocatalytic performance towards MB. Moreover, the anatse phase of 0.50 mol% Nb,B-TiO2 showed the narrowest band gap of 2.74 eV compared to the TiO2 (3.4 eV), representing a reduction of 19.41 %, according to UV-Vis analyses. These outcomes suggest the potential application of anatase phase of 0.50 mol% Nb,B-TiO2 in treating organic pollutants in wastewater under visible light conditions in future. Copyright © 2024 by Authors, Published by BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Decoding the Yield Curve: Understanding its Significance in Economic Forecasting

Throughout history, the Romanian yield curve has assumed various shapes that correspond to differing economic conditions, representing market sentiment and anticipation of future economic activity and interest rates. In times of economic stability and growth, the yield curve has generally exhibited an upward slope, signifying investor trust in continued economic expansion and expectations of future interest rate hikes. In contrast, during periods of economic uncertainty or downturns, the yield curve has often flattened or turned negative. A flattening curve suggests uncertainty about future economic conditions, while an inverted curve, where short-term yields surpass long-term yields, indicates significant economic stress and has traditionally been an accurate predictor of forthcoming recessions. These fluctuations offer essential insights for policymakers and investors, helping in the understanding and anticipation of economic trends and in the effective management of financial risks.