Temperature Ta Research Articles

A Machine earning Algorithm to Convert Geostationary Satellite ST to Air Temperature Using In Situ Measurements: A Case Study in Rome and High-Resolution Spatio-Temporal UHI Analysis

Air temperature (Ta) measurements are crucial for characterizing phenomena ike the urban heat island (UHI), which can create critical conditions in cities during summer. This study aims to develop a machine earning-based model, namely gradient boosting, to estimate Ta from geostationary satellite ST data and to apply these estimates to investigate UHI dynamics. Using Rome, Italy, as a case study, the model was trained with Ta data from 15 weather stations, taking multi-temporal ST values (instantaneous and agged up to 4 h) and additional predictors. The model achieved an overall RMSE of 0.9 ∘C. The resulting Ta fields, with a 3 km spatial and hourly temporal resolution, enabled a detailed analysis of UHI intensity and dynamics during the summers of 2019–2020, significantly enhancing the spatial and temporal detail compared to previous studies based solely on in situ data. The results also revealed a slightly higher nocturnal UHI intensity than previously reported, attributed to the inclusion of rural areas with near-zero imperviousness, thanks to the complete mapping of Ta across the domain now accessible.

Investigation on Thermal Environment of Urban Slow Lane Based on Mobile Measurement Method—A Case Study of Swan Lake Area in Hefei, China

Abstract: Numerous issues with the urban thermal environment have been brought on by the rapid development of urbanization. The thermal climate of the slow lane, a major urban activity area, is directly tied to the well-being and comfort of city dwellers. The Swan Lake area in Hefei was chosen as the research site for this paper. The mobile measurement method was used to determine the heat island intensity distribution of the slow lane in each season of the year. The effects of building density, the percentage of permeable underlying surface, and shading on the slow lane’s thermal environment were then thoroughly examined. According to the study, the distribution of heat island intensities along the mobile measurement route varies significantly depending on season, as well as time of year. Summer and winter have the most notable variations in the distribution of heat island intensities along the mobile measurement route; the summer values range from 0.1 to 4, while the winter values range from −0.3 to 3. The results showed a maximum difference of 30.2 °C in surface temperature (Ts) readings and 11.9 °C in air temperature (Ta) readings between the identical sites with and without shading, according to tests conducted at four typical mobile measurement locations along the mobile measuring route. The shading factor has a greater effect on the slow lane’s thermal environment than permeable underlying surface and building density, as seen by the standardized coefficient of shading being significantly higher than both of these factors. With a standardized coefficient of shading of −0.493 in the winter and a standardized coefficient of shading of −0.517 in the summer, the effect of the shading factor on the thermal environment is more noticeable in the summer.

Spatio-temporal Variations of Heat Extremes across the Yangtze River Delta during 2001-2023 Based on Remotely Sensed Seamless Air Temperature.

Heat extremes become increasingly frequent and severe, posing adverse risks to public health and environment. Previous research on extreme heat mostly used meteorological observations or reanalysis data, which cannot well capture detailed spatial patterns. This study developed a seamless air temperature (Ta) dataset from remote sensing data to characterize the spatio-temporal variations of heat extremes in the Yangtze River Delta (YRD) from 2001 to 2023. First, the daily maximum Ta of cloud-free pixels was estimated through machine learning algorithms from MODIS land surface temperature (LST) and other remote sensing data. Then, gaps in the estimated Ta caused by cloud cover were filled using the Temporal Fourier Analysis (TFA) method, generating a seamless daily maximum Ta dataset. The remotely sensed Ta achieved an overall MAE of 1.11°C. Based on the remotely sensed Ta, six heat indices were calculated to characterize heat extremes, including heat days (HTD), effective accumulated high temperature (EAHT), heatwave frequency (HWF), cumulative heatwave days (HWD), maximum heatwave duration (HWMD) and average heatwave duration (HWAD). Heat extremes occurred frequently in the YRD, with obvious spatial variability. Southern basins experienced intense heat with high frequency and duration, while southern mountains and northern areas experienced weaker heat extremes. Urban areas have substantially more intense heat events than suburbs, attributed to urban heat island effect. 2022 recorded the most severe heat, with notable events also in 2013 and 2003. This study provides valuable insights into heat events in the YRD and serves as a reference for remote sensing research on heat events.

Mobile Observation Field Experiment of Atmospheric Vertical Structure and Its Application in Precipitation Forecasts Over the Tibetan Plateau

AbstractWe carried out the first Mobile Field Observation Campaign of Atmospheric Profiles (MFOCAP) in the southeast Tibet and the Three‐River Source Region (TRSR) of the Tibetan Plateau (TP) by adopting two vehicle‐mounted integrated mobile observations (MO) system from July 18 to 30, 2021. Reliable MO data sets of air temperature (Ta), water vapor density (WVD) and relative humidity (RH) with high spatio‐temporal resolution over the TP were obtained and assimilated to improve precipitation forecast using the four‐dimensional variational (4DVAR) data assimilation (DA) method. The results show that Ta, WVD and RH profile data retrieved with the mobile microwave radiometer (MR) are credible over the TP. The atmospheric vertical structure measured by the mobile MR can reproduce the spatio‐temporal evolution characteristics of water vapor transport, temperature stratification and cloud structure. The distribution pattern of 24‐hr accumulated rainfall prediction with Ta profile DA was closer to measurements, and 6–12 hr forecasts for low to moderate rainfall in the central and western regions of Qinghai province were improved significantly. Data assimilation with air temperature retrievals from mobile MR observations were found beneficial for accurate simulation of water vapor transport, convergence and divergence of wind field, and upward motion associated with precipitation events. The finding of this study highlights the value of MR remote sensing observations in improving the rainfall monitoring and forecasts over the TP and downstream regions.

Physical Aging of Poly(methyl methacrylate) Brushes and Spin-Coated Films.

While there is significant attention aimed at understanding how one-dimensional confinement and chain confirmations can impact the glass transition temperature (Tg) of polymer films, there remains a limited focus on similar effects on sub-Tg processes, notably, structural relaxation. Using spectroscopic ellipsometry, we investigated the combined influence of confinement and molecular packing on Tg and physical aging, i.e., the property changes that accompany structural relaxation, at select film thicknesses and aging temperatures (Ta). We used poly(methyl methacrylate) (PMMA) films in the brush and spin-coated morphologies as model systems. We found that whether a PMMA film exhibited a decrease or increase in physical aging rate with confinement was dependent on the morphology. Notably, PMMA brushes exhibited higher physical aging rates compared to similarly thick spin-coated films at all values of Ta. These intriguing findings reveal the strong effects of confinement and molecular packing on the structural relaxation of polymer films. Results from this study have the potential to aid in the design of thin-film materials with controllable long-term glassy-state properties.

Probing Into the Annealing Effects on Microstructure and Mechanical Properties of Impact Polypropylene Copolymer With Nodular Crystalline Morphology

ABSTRACTThe performance of polypropylene materials in high‐temperature environments is closely linked to changes in their microstructure and properties. For impact polypropylene copolymer (IPC), the evolution of structure induced by annealing remains elusive due to the complex molecular chain structure and phase morphology. Herein, we investigate the effects of the initial crystalline morphology on the microstructure and mechanical properties of IPC after annealing. Results show that melt‐quenched IPC (IPC‐m) exhibits a nodular crystalline morphology. As the annealing temperature (Ta) increases, the mesomorphic phase in IPC‐m progressively transforms into monoclinic α crystals. Simultaneously, both the size of nodular particles and their internal crystalline regions gradually increase, while the initial nodular morphology remains unchanged. Furthermore, the nodular morphology restricts the lateral growth of crystals in IPC‐m, thereby inhibiting the cavitation during stretching and resulting in higher yield strength for annealed IPC‐m. This research sheds light on the microstructure evolution mechanisms and structure–property relationships of IPC and will provide theoretical guidance for the evaluation of service life and performance optimization of polyolefins in harsh environments.

Estimating actual crop evapotranspiration by using satellite images coupled with hybrid deep learning-based models in potato fields

Estimating actual crop evapotranspiration (ETc act) is a fundamental requirement for effective crop water management, aiming to achieve precision irrigation amidst changing environmental conditions. Despite the introduction of various methods for estimating ETc act values, these methods are still associated with several challenges and limitations. Motivated by the robustness of deep learning models, this study employed two hybrid models that integrate Convolution Neural Network with either Random Forests (CNN-RF) or Support Vector Machine (CNN-SVR) to estimate potato ETc act using a limited set of input features. Three models were configured and compared for each CNN-RF (CNN-RF1, CNNRF2, CNNRF3) and CNN-SVM (CNN-SVM1, CNN-SVM2, CNN-SVM3), by using different combinations of variable input features derived from meteorological data (air temperature (Ta), vapour pressure deficit (VPD), net radiation (Rn)) and MODIS satellite data (land surface temperature (LST), fraction of photosynthetically active radiation (Fpar), leaf area index (LAI)). The results demonstrated the outstanding performance of the CNN-RF models, showcasing their superiority over the CNN-SVM models. Notably CNN-RF1 model yielded the best results, achieving a normalized root mean squared error (nRMSE) of 11.7 and 31.5 %; Nash–Sutcliffe Efficiency (NSE) of 0.97 and 0.80; Correlation coefficient (CC) of 0.99 and 0.91 at training and testing phases respectively. While, both models exhibited lower performance when using remote sensing satellite-based inputs, CNN-RF2, managed to produce satisfactory estimates of nRMSE = 16.7, 40.9 %; NSE = 0.95, 0.66; CC = 0.98, 0.813; Bias = −0.41, −4.377 W/m2 during training and testing respectively. The ETc act of potato showed to have high correlation with LST (0.74–0.84) and using LST as proxy for Ta, resulted in improved model estimates compared to using satellite data exclusively. These findings suggest that, in situations where climatic data is limited, remote sensing can serve as a viable alternative for modelling potato ETc act when coupled with CNN-RF, and further improvement can be achieved by incorporating meteorological data fusion.

Dust Content Modulation and Spring Heat Waves in Senegal (2003–2022)

The population of Senegal faces health challenges related to desert dust and heat waves (HWs). This study aims to (a) update the documentation of HWs in Senegal, expanding on the work of Sambou et al. (2019); (b) investigate the modulation of dust indicators during HWs; and (c) assess the distinct impacts of dust content on night-time and daytime HWs. We use [i] the daily maximum air temperature (Tx), minimum air temperature (Tn), and apparent temperature (Ta) from 12 stations in the Global Surface Summary of the Day (GSOD) database and [ii] the Dust Aerosol Optical Depth (Dust AOD), particulate matter (PM) concentrations, 925 hPa wind, and Mean Sea Level Pressure (MSLP) from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. HWs are defined for each station in spring as periods when Tx, Tn, or Ta exceeds the 95th percentile for at least three consecutive days. Three homogeneous zones from the Atlantic coast to inland Senegal are identified using hierarchical cluster analysis: Zone 1 (Saint-Louis, Dakar-Yoff, Ziguinchor, and Cap Skirring), Zone 2 (Podor, Linguère, Diourbel, and Kaolack), and Zone 3 (Matam, Tambacounda, Kédougou, and Kolda). Our results show that Zone 1 records the highest number of HWs for Tx, Tn, and Ta, while Zone 3 experiences more HWs in terms of Tn and Ta than Zone 2. The influence of dust is notably stronger for HWs linked to Tn and Ta than for those related to Tx. Analysis of the mechanisms shows that the presence of dust in Senegal and its surrounding regions is detected up to four days before the onset of HWs. These findings suggest that dust conditions associated with spring HWs in Senegal may be better distinguished and predicted.

Assessment of multi-factor influences on elderly usage patterns and heat-stress exposure in neighbourhood public outdoor spaces

Given the hotter weather in summer, quantifying the impacts of thermal and non-thermal factors on the usage of public outdoor spaces (POS) and exposure to heat stress among older people are essential to evaluate heat-related risks in POS and guide POS designs to guarantee the safety of outdoor activities. In this study, field tests were conducted from June to August in four POS of two public housing estates in Hong Kong, to investigate the elderly's POS usage and thermal response in relation to microclimate parameters, POS exercise function, and companionship. A method for evaluating the intensity of health-warning-heat-stress exposure in POS is proposed, aiming to guide risk reducing measures in POS. The results indicate that, at air temperatures (Ta) within the 29.0°C and 35.0°C range, one-degree increase in mean radiant temperature is associated with around 0.05 decrease in POS effective usage rate (effUR). The effUR is found less sensitive to wind conditions, while 67% of the interviewees prefer stronger wind speed. An average thermal sensation vote of 1 (slightly warm) and a fairly high effUR are found under a wide mPET range spanning from 30.0°C to 39.0°C, while moderate-to-strong heat stress may occur when mPET exceeds 35.0°C. Elderly users’ thermal sensitivities reduce in POS providing exercise functions, and when in the company of and chatting with others. The intensity of health-warning-heat-stress exposure varies over time and differs across POS, which will be exacerbated due to global warming unless climate-adapted cooling strategies are implemented.

Machine learning prediction of steel–concrete composite beam temperatures during hot asphalt paving

In the bridge construction process, the temperature distribution within the steel–concrete composite beam (SCCB) under hot asphalt paving is not negligible in its impact on the structural performance. However, traditional static analysis methods for bridge temperature fields, such as temperature measurements and numerical simulations, are plagued by high workload and costly equipment requirements. Therefore, in this study, we explore a machine learning (ML) approach based on field measurements to predict the temperature field of SCCB during hot asphalt paving. The result showed that of the various ML algorithms tested, the K-Nearest Neighbors (KNN) algorithm provided the highest predictive accuracy for the temperature field of SCCB. Through feature selection and experimental analysis, we identify beam temperature (Tbt), hot asphalt temperature (Ts), ambient temperature (Ta), and box interior temperature (Tbox) as key features for predicting the temperature of SCCB during hot asphalt paving. This study demonstrates that ML is an powerful tool for predicting the thermal behavior of bridge structures, with potential widespread application in identifying temperature evolution in bridge structures.

Incorporating environmental stress improves estimation of photosynthesis from NIRvP in US Great Plains pasturelands and Midwest croplands

Near-infrared reflectance of vegetation multiplied by incoming sunlight (NIRvP) is important for gross primary production (GPP) estimation. While NIRvP is a useful indicator of canopy structure and solar radiation, its association with heat or moisture stress is not fully understood. Thus, this research aimed to explore the impact of air temperature (Ta) and vapor pressure deficit (VPD) on the NIRvP-GPP relationship. Using Moderate Resolution Imaging Spectroradiometer (MODIS) observations, eddy-covariance measurements, and the Parameter–Elevation Regressions on Independent Slopes Model (PRISM) data, we found that NIRvP cannot fully explain the response of plant photosynthesis to Ta and VPD at both seasonal and daily scales. Therefore, we incorporated a polynomial function of Ta and an exponential function of VPD to correct its seasonal response to stress and calibrated the GPP residual via a linear function of Ta and VPD time-varying derivatives to account for its daily response to stress. Leave-one-site-out cross-validation suggested that the improvements relative to its original version were especially noteworthy under stress conditions while less significant when there was no water or heat stress across grasslands and croplands. When compared to six other GPP models, the enhanced NIRvP model consistently outperformed them or performed comparably with the best model in terms of bias, RSME, and coefficient of determinant against measurements in grasslands and croplands. Moreover, we found that parameterizing the fraction of photosynthetically active radiation term using NIRv notably improved the performance of the classic MOD17 and vegetation photosynthesis model, with an average RMSE reduction of 13 % across grasslands and croplands. Overall, this study highlights the need to consider environmental stressors for improved NIRvP-based GPP and shed light on future improvements of LUE models.

Analysis of Key Factors Affecting Case-to-Ambient Thermal Resistance in Thermal Modeling of Power Devices

In the application of power converters, the ambient temperature (Ta) experiences significant fluctuations. For the case-to-ambient resistance (Rca), apart from the influence of the material’s inherent properties, factors such as heat dissipation structure, working environment, and operational state can all have an impact on the Rca. Notably, while there are a limited number of models that consider environmental changes, existing models for calculating the Rca predominantly overlook the influence of varying working conditions or boundary conditions on the self-thermal resistance. Based on simulation and experimental analyses, the methods to calculate the Rca are outlined, and the key factors, inclusive of the coupling effects that influence the Rca in the thermal modeling of power devices, are thoroughly discussed.

Thermoregulation and survival during sepsis: insights from the cecal ligation and puncture experimental model

BackgroundSepsis remains a major global health concern due to its high prevalence and mortality. Changes in body temperature (Tb), such as hypothermia or fever, are diagnostic indicators and play a crucial role in the pathophysiology of sepsis. This study aims to characterize the thermoregulatory mechanisms during sepsis using the cecal ligation and puncture (CLP) model and explore how sepsis severity and ambient temperature (Ta) influence Tb regulation and mortality. Rats were subjected to mild or severe sepsis by CLP while housed at thermoneutral (28 °C) or subthermoneutral (22 °C) Ta, and their Tb was monitored for 12 h. Blood and hypothalamus were collected for cytokines and prostaglandin E2 (PGE2) analysis.ResultsAt 28 °C, febrile response magnitude correlated with sepsis severity and inflammatory response, with tail vasoconstriction as the primary heat retention mechanism. At 22 °C, Tb was maintained during mild sepsis but dropped during severe sepsis, linked to reduced UCP1 expression in brown adipose tissue and less effective vasoconstriction. Despite differences in thermoregulatory responses, both Ta conditions induced a persistent inflammatory response and increased hypothalamic PGE2 production. Notably, mortality in severe sepsis was significantly higher at 28 °C (80%) compared to 22 °C (0%).ConclusionsOur findings reveal that ambient temperature and the inflammatory burden critically influence thermoregulation and survival during early sepsis. These results emphasize the importance of considering environmental factors in preclinical sepsis studies. Although rodents in experimental settings are often adapted to cold environments, these conditions may not fully translate to human sepsis, where cold adaptation is rare. Thus, researchers should carefully consider these variables when designing experiments and interpreting translational implications.Graphical Graphical representation of the thermoregulatory and inflammatory responses to mild and severe sepsis in rats housed at thermoneutral (28 °C) and subthermoneutral (22 °C) ambient temperatures (Ta). The model highlights distinct body temperature outcomes: fever and hypothermia. At thermoneutral Ta, severe sepsis induces a high fever, associated with increased hypothalamic PGE2, cytokine levels, and mortality, while mild sepsis leads to a moderate fever. In contrast, at subthermoneutral Ta, severe sepsis results in hypothermia with decreased UCP1 expression and lower mortality, whereas mild sepsis maintains normal body temperature. The impact of Ta on sepsis severity, thermoregulatory mechanisms, and survival is emphasized.

Characteristics of Carbon Fluxes and Their Environmental Control in Chenhu Wetland, China

Carbon dioxide (CO2) flux measurements were conducted throughout the year 2022 utilizing the eddy covariance technique in this study to investigate the characteristics of carbon fluxes and their influencing factors in the Chenhu wetland, a representative subtropical lake-marsh wetland located in the middle reaches of the Yangtze River in China. The results revealed that the mean daily variation of CO2 flux during the growing season exhibited a U-shaped pattern, with measurements ranging from −12.42 to 4.28 μmolCO2·m−2·s−1. The Chenhu wetland ecosystem functions as a carbon sink throughout the growing season, subsequently transitioning to a carbon source during the non-growing season, as evidenced by observations made in 2022. The annual CO2 absorption was quantified at 21.20 molCO2·m−2, a figure that is lower than those documented for specific subtropical lake wetlands, such as Dongting Lake and Poyang Lake. However, this measurement aligns closely with the average net ecosystem exchange (NEE) reported for wetlands across Asia. The correlation between daytime CO2 flux and photosynthetically active radiation (PAR) can be accurately represented through rectangular hyperbola equations throughout the growing season. Vapor pressure deficit (VPD) acts as a constraining factor for daytime NEE, with an optimal range established between 0.5 and 1.5 kPa. Furthermore, air temperature (Ta), relative humidity (RH), and vapor pressure difference (VPD) are recognized as the principal determinants affecting NEE during the nocturnal period. The association between Ta and NEE during the non-growing season conforms to the van’t Hoff model, suggesting that NEE increases in response to elevated Ta during this timeframe.

Ecosystem water limitation shifts driven by soil moisture in the Loess Plateau, China

In the context of climate change, the functionality of ecosystems is primarily influenced by the availability of water and energy supply. However, there is limited research that comprehensively uses energy indicators to explore how climate change affects the water and energy limiting states of ecosystems. Here we evaluated the historical and future water and energy limitations using the Ecosystem Limitation Index (ELI) derived from evapotranspiration (ET), soil moisture (SM), net radiation (Rn), and air temperature (Ta), and conducted an in-depth analysis of the dominant factors. The results indicate that: (1) The degree of water limitation deepened initially and then weakened. Over 68 % of the region became drier initially, while over 83 % became wetter later. (2) In terms of area, soil moisture emerged as a critical factor influencing the variations in water and energy constraints within the Loess Plateau. Further research revealed the range of critical soil moisture (CSM) for the transition of water-energy limitation state is 0.286 mm3mm−3, and it varies with changes in temperature, soil texture, vegetation cover, and season. (3) Future projections suggest a transition towards heightened water limitations across the Loess Plateau. These findings underscore the efficacy of ELI in assessing and predicting dynamic ecosystem changes, offering valuable insights into the impacts of climate change on water and energy cycles within semi-arid ecosystems.

Sensitivity of gross primary production and evapotranspiration to heat and drought stress in a young temperate plantation in northern China

Assessing the sensitivities of ecosystem functions to climatic factors is essential to understanding the response of ecosystems to environmental change. Temperate plantation forests contribute to global greening and climate change mitigation, yet little is known as to the sensitivity of gross primary production (GPP) and evapotranspiration (ET) of these forests to heat and drought stress. Based on near-continuous, eddy-covariance and hydrometeorological data from a young temperate plantation forest in Beijing, China (2012–2019), we used a sliding-window-fitting technique to assess the seasonal and interannual variation in ecosystem sensitivity (i.e., calculated slopes, SGPP-Ta, SET-Ta, SGPP-EF, and SET-EF) in GPP and ET to anomalies in air temperature (Ta) and evaporative fraction (EF). The EF was used here as an indicator of drought. Seasonally, daily SGPP-Ta, SET-Ta, and SGPP-EF were greatest in summer, reaching maxima of 1.12 ​± ​0.56 ​g ​C·m−2·d−1⋅°C−1, 1.36 ​± ​0.56 ​g H2O·m−2·d−1⋅°C−1, and 0.37 ​± ​0.35 ​g ​C·m−2·d−1, respectively. Evapotranspiration was constrained by drought, especially during the spring-to-summer period, SET-EF reaching −0.51 ​± ​0.34 ​g H2O·m−2·d−1. Variables EF, Ta, soil water content (SWC), vapor pressure deficit (VPD), and precipitation (PPT) were the main controls of sensitivity, with SGPP-Ta and SET-Ta increasing with Ta, VPD, and PPT (<50 ​mm·d−1) during both spring and autumn. Increased drought stress during summer caused the positive response in GPP and ET to decrease with atmospheric warming. Variable SET-EF intensified (i.e., became more negative) with decreasing EF and increasing Ta. Interannually, annual SGPP-Ta and SET-Ta were positive, SGPP-EF near-neutral, and SET-EF negative. Interannual variability in SGPP-Ta, SET-Ta, SET-EF, and SGPP-EF was largely due to variations in bulk surface conductance. Our study suggests that the dynamics associated with the sensitivity of ecosystems to changes in climatic factors need to be considered in the management of plantation forests under future global climate change.

Effect of Thermal Processing on the Structural and Magnetic Properties of Epitaxial Co2FeGe Films.

The structure and magnetic properties of epitaxial Heusler alloy films (Co2FeGe) deposited on MgO (100) substrates were investigated. Films of 60 nm thickness were prepared by magnetron co-sputtering at different substrate temperatures (TS), and those deposited at room temperature were later annealed at various temperatures (Ta). X-ray diffraction confirmed (001) [110] Co2FeGe || (001) [100] MgO epitaxial growth. A slight tetragonal distortion of the film cubic structure was found in all samples due to the tensile stress induced by the mismatch of the lattice parameters between Co2FeGe and the substrate. Improved quality of epitaxy and the formation of an atomically ordered L21 structure were observed for films processed at elevated temperatures. The values of magnetization increased with increasing TS and Ta. Ferromagnetic resonance (FMR) studies revealed 45° in-plane rotation of the easy anisotropy axis direction depending on the degree of the tetragonal distortion. The film annealed at Ta = 573 K possesses the minimal FMR linewidth and magnetic damping, while both these parameters increase for another TS and Ta. Overall, this study underscores the crucial role of thermal treatment in optimizing the magnetic properties of Co2FeGe films for potential spintronic and magnonic applications.

Potential of Rice Husk Brackets as A New Alternative Sea Water Distillation into Clean Water

The need for clean water for people in Indonesia is increasing, especially in coastal areas, while the availability of clean water is very limited. One of the efforts made to anticipate is by utilizing sea water with a solar distillation system. In this study, the absorber used was rice husk briquettes. Various distillation technologies have been developed, but distillation technology with solar energy sources is still experiencing various obstacles so further technology and research are needed. To develop this technology, research was conducted with the aim of (1) producing a design of the thickness and density of rice husk briquettes in a seawater distillation system. (2) to produce clean water for each pair of thickness and density of rice husk briquettes through a seawater distillation system. (3) Knowing how much heat absorption efficiency is by using a rice husk briquette absorber. The research method used is a comparative method, which is a comparative study, where in this study the thickness and density of rice husk briquettes are compared. The data analysis method used the descriptive method. The parameters to be analyzed are plate temperature (Tp), glass temperature (Tg), water temperature (tw), basin room temperature (Tsv), ambient temperature (Ta) and distilled water (AT), area of absorbent plate (Ac), Collector and distillation efficiency. This research resulted in a design for the distillation of seawater into clean water using an absorber plate (absorber) of rice husk briquettes which can increase the production of clean water.

I-V Characteristics of Polycrystalline CAZTSe Heterojunction Solar Cells at Different Ag Content and Annealing Temperatures

Since the polycrystalline (Cu1-xAgx)2ZnSnSe4 (CAZTSe) demonstrated good optical absorption performance in the visible region, the focus of the present study is to grow the polycrystalline (Cu1-xAgx)2ZnSnSe4 thin films deposited by thermal evaporation method on silicon substrates with 800 nm thickness and 0.53 nm/sec deposition rate as a function of Ag content (0.0,0.1,0.2) and annealing temperature at 373 K, 473 K. From I-V measurements of Al/n-CdS/p-CAZTSe/n-Si(111)/Al heterojunction solar cells under dark and illumination conditions, we observed that the forward bias current changes roughly exponentially with bias voltage and the ideality factor and saturation current dependence on both x content and different temperatures (Ta).

Evaluating the cooling performance of vegetation combined with a fountain in horizontal and vertical urban environments

Urban greenery and fountains effectively mitigate the urban heat island (UHI) effect. While many studies have assessed individual vegetation configurations (grass, shrub, and tree) and fountains at pedestrian heights, few have explored their combined effects horizontally and vertically. This study uses the ENVI-met model to evaluate the cooling effects of three vegetation configurations and their combinations with fountains in a typical historical and cultural neighborhood. The “grass, shrub, tree and fountain” scenario achieved the most substantial cooling, reducing air temperature (Ta) by 5.61 °C and mean radiant temperature (Tmrt) by 17.39 °C. Adding shrubs to the existing trees had minimal impact on Ta and Tmrt. Incorporating fountains into various vegetation configurations scenarios further lowered Ta by 3.58°C-3.66 °C and Tmrt by 2.97°C-3.27 °C. Trees primarily improved Tmrt through shading, while fountains were more effective at reduce Ta. This study offers theoretical and scientific guidance for optimizing urban street microclimate design from horizontal and vertical perspectives.