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Simple Summary: The heat-loving paper wasp Polistes dominula builds small nests in sheltered places in quite differing habitats, providing a favorable microclimate for brood development. Their careful choice of the nesting site enables them to keep the nest and brood temperature above the ambient air temperature. In temperate Austrian (Central European) climates, the cooling efforts of the adult wasps keep the mean comb temperature from exceeding approximately 39 °C, which seems to be a threshold for optimal development. Measurement of the nest and the body temperature of the wasps at typical nesting sites revealed a close relationship with the air temperature at the nests but a suboptimal correlation with climate data from a local standard weather station or model-generated macroclimate data. The comparison emphasizes the importance of microclimate measurements if it is to judge the vulnerability of insects to climate change. The paper wasp Polistes dominula is a thermophilic species originating from the Mediterranean climate, but is now widely spread in Europe. They live in quite differing habitats; and as synanthropic species, they have been established in human settlement areas. They build a single small comb at protected places with a favorable microclimate. We measured the temperature of the wasps, the nests and their environment at typical nesting sides in Austria (Europe) in the temperate climate, in order to reveal relationships between nest and body temperature and the habitats' microclimate. The temperatures of the comb and of the wasps' body were in a wide range (~20–37 °C) above the ambient air temperature at the nest. This is an advantage as higher temperatures accelerate the development speed of the brood. However, the mean comb temperature did not exceed approximately 38.6 °C. This was managed by cooling efforts of the adult wasps. The ambient air temperature near the nest (~1–2 cm) was always clearly elevated above the ambient air temperature at a local standard weather station in the habitat. A comparison with climate-model-generated macroclimate data revealed the necessity of measuring microclimate data for a reliable description of the insects' thermal environment. [ABSTRACT FROM AUTHOR]

This research investigated a non-thermal, dielectric-barrier discharge (DBD) plasma-based approach to prepare poly(acrylic acid) (PAA) from acrylic acid in its liquid state at atmospheric temperature and pressure. Neither additives nor solvents were needed, and the polymerization was accomplished both as a film and inside a sheet of mesoporous paper. All prepared samples were characterized and the DBD plasma-initiated kinetics were analyzed for the polymerization of acrylic acid. Using FTIR semi-quantitative analysis, the degree of polymerization was monitored, and the reaction followed an overall second-order kinetic model with respect to the DBD-initiated polymerization. Additionally, the application of a PAA-modified paper as a water retention cloth or 'wet wipe' was investigated. The results showed that the PAA-modified paper substrates using DBD plasma increased water retention as a function of plasma treatment time. [ABSTRACT FROM AUTHOR]

A hybrid montmorillonite (Mt)-rich/chitosan composite (MCC) with high adsorption performance was synthesized for the decolorization of water used in the joss paper process. The performance was reported in terms of the dye removal. The composite expressed higher performance than chitosan or Mt-rich clay, respectively. The optimum condition for complete dye removal was achieved when using at least 0.6 g of the composite over a wide pH range (3–10) and initial dye concentration (10–100 mg L−1). The composite showed good reusability without the requirement of regeneration, adsorbing the dye completely for up to eight successive cycles of adsorption (>1.33 gdye gMCC−1). Thermodynamic analyses revealed the degree of spontaneity and the endothermic adsorption process. From the isotherm studies, the Koble–Corrigan isotherm model fitted very well to the experimental data, revealing that the composite had a heterogeneous surface with various active sites to adsorb the dye molecules. This also evidenced the synergistic electrostatic attraction and hydrophobic interaction between the dye and the composite. The pseudo-second-order model best explained the kinetic rate of adsorption. From evaluation of the adsorption process using the Webber and Morris equation and Boyd model, the rate-limiting step consisted of film diffusion and intra-particle diffusion. [ABSTRACT FROM AUTHOR]

Different amounts of a stable aqueous TiO2 hydrosol were used to fabricate paper sheets having photocatalytic activity. The TiO2 hydrosol was prepared in aqueous medium using titanium butoxide as precursor and acetic acid as catalyst for the hydrolysis of titanium butoxide. An aging process at room temperature and atmospheric pressure was finally applied to obtain crystalline anatase TiO2 hydrosol. The effects of different TiO2 hydrosol loadings on the mechanical strength and barrier properties of modified paper sheets were investigated in detail. The photocatalytic behavior of TiO2-modified paper sheets was investigated as well using methylene blue (MB) as target pollutant. [ABSTRACT FROM AUTHOR]

Highlights: The paper concerns the possibility of using an innovative railway rail structure in a contactless track: The correct operation of CWR track, due to the occurrence of additional thermal stresses with a value dependent on changes in rail temperature, requires a systematic diagnosis of its condition; The paper presents the research of longitudinal force load tests for a classic rail and for two cases of an innovative railway rail solution. The research presented in the paper shows that: The proposed proprietary design of the rail used for the railroad track can enable the reduction in the longitudinal force occurring as a result of high ambient temperatures; The use of an innovative rail conception will allow for less steel consumption, which means less emissions into the atmosphere during its production (lower carbon footprint). This paper presents the concept of a modified 60E1 rail dedicated to continuous welded rail (CWR) track. The presented solution is the subject of a patent application by the authors of the publication. The paper describes problems associated with the operation of CWR track and the phenomena of so-called "rail stressing", i.e., stresses created in the rail due to thermal shrinkage that, in extreme cases, can lead to the buckling of the rail track. Simulation calculations of longitudinal track loads to represent the occurrence of thermal force as a result of the occurrence of high air temperatures were carried out for the constructed conventional model of the railroad track as well as the track with the proposed solutions. A discussion of the simulation results is presented, indicating the possibility for the wider application of both varieties of modified rail. [ABSTRACT FROM AUTHOR]

There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants' thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants' comfort. [ABSTRACT FROM AUTHOR]

This paper describes the metrological procedure carried out for the evaluation of the building influence on air temperature measurements. This evaluation aims to produce reliable conclusions, information, and data to contribute to the WMO siting classification schemes for air temperature measurements. For this purpose, a field experiment was designed, deployed, and carried out. As a result, one-year-lasting air temperature measurements were collected and analyzed. In this field experiment, a 200 m wide building is the unique artificial heat source and the unique object projecting shades over a flat surface (no discernible slope) in an open space bigger than 40,000 m2, covered with short grass. Eight calibrated thermometers, equipped with the same model of artificially ventilated radiation shields, were set up at a height of 1.5 m from the ground and at different distances from a 200 m wide building. This configuration provides the observation of the horizontal air temperature radially distributed from the building and, as a conclusion, it enables the quantification of the building influences on air temperature measurements at different distances from the building. This document describes the field experiment, the analysis procedure, the evolution of the building influence on air temperature measurements along the day, and the impact of other meteorological parameters on this building effect. Two different building effects are observed: the positive building effect, where the air temperature decreases with the distance to the building, and the negative building effect, where the air temperature increases with the distance to the building. It is also noticed that the building influence is higher on clear days and the daily maximum building influence values are directly linked with the corresponding maximum solar irradiance. The influence of wind on the building effect is also analyzed, reaching the conclusion that due to characteristic of local winds, in terms of low speed and direction, the wind impact could be considered as negligible. The maximum values of building influence on air temperature measurements, the associated uncertainty analysis, and the conclusions are presented in this paper. All these points have been addressed using metrological principles with the purpose of giving consistency and robustness to the evidence presented here. [ABSTRACT FROM AUTHOR]

The Normalized Differential Spectral Attenuation (NDSA) technique was proposed years ago as an active method for measuring integrated water vapor (IWV) along a Ku/K-band radio link immersed (totally or partially) in the troposphere. The approach is of the active kind, as it relies on the transmission of a couple of sinusoidal signals, whose power is measured at the receiver, thus providing the differential attenuation measurements from which IWV estimates can be in turn derived. In 2018, a prototype instrument providing such differential attenuation measurements was completed and set up for a first measurement campaign aimed at demonstrating the NDSA method. By the end of June 2022, the instrument was profoundly modified and upgraded so that a second measurement campaign could be carried out from 1 August to 30 November 2022. The transmitter was placed on the top of Monte Gomito (44.1277°lat, 10.6434°lon, 1892 m a.s.l.) and the receiver on the roof of the Department of Information Engineering of the University of Florence (43.7985°lat, 11.2528°lon, 50 m a.s.l.). The resulting radio link length was 61.15 km. Four ground weather stations of the regional weather service were selected among those available. In this paper, we describe the upgraded instrument and present the outcomes of the new measurement campaign, whose purpose was mainly to compare the IWV estimates provided by the instrument with the ground sensor measurements of air temperature, air humidity, barometric pressure, and rainfall. In particular, we show that the temporal trends of the two IWV estimates are qualitatively consistent, and that the instrument is able to provide IWV estimates also in the presence of fog and rainfall. Conversely, a quantitative evaluation through comparison with IWV data from point weather station measurements appears challenging due to the significant spatial variability in temperature and relative humidity, even between couples of stations that are quite close to each other. [ABSTRACT FROM AUTHOR]

This paper investigates the application of Schlieren flow visualization for detecting leaks in pipelines carrying high-temperature fluids. Two experimental setups were constructed: one with a 25 mm PTFE tube featuring a 2 mm diameter perforation, and another with a 100 mm diameter pipe insulated with an aluminum jacket and featuring a 12 mm leak gap. A single-mirror-off-axis Schlieren system, employing a 150 mm diameter parabolic mirror, was used to visualize the leaks. The temperature of the leaking air varied between 20 and 100 °C, while the ambient temperature was maintained at 14 °C. To quantify the leaks, the coefficient of variation for pixel intensity within the leak region was calculated. Results showed that for the PTFE tube, leaks became detectable when the temperature difference exceeded 34 °C, with the coefficient of variation surpassing 0.1. However, in the insulated pipe, detecting clear leak patterns was challenging. This research demonstrates the potential of Schlieren visualization as a valuable tool in enhancing pipeline leak detection. [ABSTRACT FROM AUTHOR]

Given that two-phase closed thermosiphons (TPCT) are a prevalent and efficacious means of heat transfer. However, non-condensable gas (NCG) may potentially impact the heat transfer performance of the aforementioned devices. Nevertheless, the theoretical analysis of heat transfer in TPCT containing NCG is not fully comprehensive and therefore requires further supplementation by means of relevant experiments. This paper presents the development and experimental investigation of a theoretical heat transfer model for a TPCT containing NCG. The research encompasses the optimal fluid-filling ratio of R22 and R410a working fluid and the impact of NCG on heat transfer in the condenser section of TPCT. Experimental findings indicate that TPCT with R22 and R410a working fluids at a fluid-filling ratio of 60% and 50%, respectively, demonstrate excellent isotherm and heat transfer efficiency. The presence of NCG affects the condenser section heat transfer process of the vapor, leading to a 2 °C decrease in the average temperature of the condenser section of the TPCT (Tca). In comparison with the TPCT without NCG, it was observed that an increase in the mass of NCG from 0.0097 to 0.0197 mol resulted in a reduction in the effective length of the condenser section (La) and effective heat transfer rate (κ) of R22 TPCT. The decrease in La was 75.1 mm, while the decrease in κ was 15.02%. Furthermore, at the same NCG mass, the effective heat transfer rate of R410a TPCT is evidently superior to that of R22 TPCT. The NCG in the TPCT can be removed by using a check valve. Nevertheless, this will result in a reduction in the fluid-filling ratio of the TPCT. The temperature of the R410a TPCT containing 0.0197 mol NCG with a fluid-filling ratio of 50% is comparable to that observed in fluid-filling ratio of 40% after the NCG is exhausted. [ABSTRACT FROM AUTHOR]

Europe and the Mediterranean are considered climate change hot spots. This is the reason why this paper focuses on the analysis of the trends of essential climate variables in a Mediterranean country, Greece. The analyzed period is 1991–2020, and the dataset used is ERA5-Land (produced by the European Center for Medium-Range Weather Forecasts), which has global coverage and an improved resolution of ~9 × 9 km compared to other datasets. Significant climatic changes across Greece have been put in evidence during the analyzed period. More specifically, the country averaged a 30-year trend of temperature of +1.5 °C, locally exceeding +2 °C, and this increasing trend is positively correlated with the distance of the areas from the coasts. Accordingly, the number of frost days has decreased throughout the country. In terms of rainfall, a major part of Greece has experienced increasing annual rainfall amounts, while 86% of the Greek area has experienced a positive trend of days with heavy rainfall (>20 mm). Finally, a multiple signal of the trend of consecutive dry days was found (statistically non-significant in the major part of Greece). [ABSTRACT FROM AUTHOR]

The environmental temperature and humidity are crucial factors for the normal growth and development of arbor tree cuttings by altering their hormone levels and influencing their physiological activities. Developing a temperature and humidity environmental model for arbor tree cuttings serves as a key technique to improve the adjustment performance of environmental parameters in facility agriculture systems and enhance the rooting rate of cuttings. This paper provides a comprehensive summary of current research on the inherent characteristics of cuttings and the factors influencing environmental temperature and humidity. It explores the mechanisms of interaction between the inherent characteristics of cuttings and the factors influencing environmental temperature and humidity. This paper investigates the interactive relationships among the factors affecting environmental temperature and humidity. It analyzes methods to improve the efficiency of constructing temperature and humidity environmental models for arbor tree cuttings. To enhance the transferability of the environmental model, the necessary physiological activities under the influence of plant hormones are generalized as common physiological traits in the growth and development of cuttings. In addition, this paper explores the factors influencing the air and substrate temperature and the humidity in facility agriculture systems as well as two types of facilities for controlling environmental temperature and humidity. Furthermore, it reviews the research progress in environmental models from both mechanistic and data-driven perspectives. This paper provides a comparative analysis of the characteristics associated with these two model categories. Building upon this, the paper summarizes and discusses methods employed in constructing temperature and humidity environmental models for arbor tree cuttings. In addition, it also anticipates the application of deep learning techniques in the construction of temperature and humidity environmental models for arbor cuttings, including utilizing machine vision technology to monitor their growth status. Finally, it proposes suggestions for building physiological models of fruit tree-like arbor cuttings at different growth stages. To enhance the transferability of environmental models, the integration of physiological models of cuttings, environmental models, and control system performance are suggested to create an environmental identification model. This paper aims to achieve control of the common physiological activities of cuttings. [ABSTRACT FROM AUTHOR]

In this paper, we present experimental findings related to the measurement of air temperature within an enclosure. We utilized both a conventional temperature sensor and a UOTS (ultra-sensitive oscillating temperature sensor) for this purpose. The UOTS's output frequency was measured using a microcontroller's timer and direct memory access. In one experiment, we subjected the air inside the enclosure to rapid heating to evaluate the responsiveness of both sensors. In another experiment, the air temperature was indirectly increased through the laboratory's heating system. The initial experiment reaffirmed the superior responsiveness of the UOTS, as observed in previous tests. The second experiment, conducted over a duration of more than 20 h, allowed us to establish a frequency-temperature curve for the UOTS. It also enabled us to determine that the UOTS exhibits sensitivity at approximately 45 Hz per degree Celsius. This assessment provided valuable insights into temperature underestimation by the conventional temperature sensor, revealing a discrepancy of 9 °C during the rapid heating experiment. This quantified the significant advantage offered by the UOTS in terms of accuracy and responsiveness. [ABSTRACT FROM AUTHOR]

Avoiding heat stress in cows is an important condition for animal productivity and the maintaining of animal health. For this, it is necessary to provide an optimal microclimate in cowsheds using systems of air cooling. The paper analyzes one of these systems—an air humidification–cooling system. The research was carried out in a semi-insulated box-type cowshed containing 244 places. The changes in temperature, relative humidity, and temperature humidity index (THI) were studied for the air coming from outside and for the air inside the cowshed. Considering the fact that the cows were in the cowshed most of the time (51.5%) under heat stress, the use of a cooling system is appropriate. It was established that a cooling system is capable of compensating for heat released by animals. It was determined that with an increase in air temperature the relative efficiency of a cooling system increases. An intensive constant air exchange provided using fan operation avoids an excessive growth of relative humidity in a cowshed. To reduce the consumption of electricity and water, the paper suggests regulation of both the power of the fans of the system and the water supply to the nozzles not using temperature but using THI. Theoretically, when THI is used to regulate the operation of the cooling system, the consumption of electrical energy is reduced by 17.8%, and the consumption of water is reduced by 43.2% when compared to the option when the temperature is used to regulate the operation of a cooling system. [ABSTRACT FROM AUTHOR]

Agricultural sustainability is dependent on the ability to predict crop yield, which is vital for farmers, consumers, and researchers. Most of the works used the amount of rainfall, average monthly temperature, relative humidity, etc. as inputs. In this paper, an attempt was made to predict the yield of the citrus crop (Washington Navel orange, Valencia orange, Murcott mandarin, Fremont mandarin, and Bearss Seedless lime) using weather factors and the accumulated heat units. These variables were used as input parameters in an artificial neural network (ANN) model. The necessary information was gathered during the growing seasons between 2010/2011 and 2021/2022 under Egyptian conditions. Weather factors were daily precipitation, yearly average air temperature, and yearly average of air relative humidity. A base air temperature of 13.0 °C was used to determine the accumulated heat units. The heat use efficiency (HUE) for cultivars was determined. The Bearss Seedless lime had the lowest HUE of 9.5 kg/ha °C day, while the Washington Navel orange had the highest HUE of 20.2 kg/ha °C day. The predictive performance of the ANN model with a structure of 9-20-1 with the backpropagation was evaluated using standard statistical measures. The actual and estimated yields from the ANN model were compared using a testing dataset, resulting in a value of RMSE, MAE, and MAPE of 2.80 t/ha, 2.58 t/ha, and 5.41%, respectively. The performance of the ANN model in the training phase was compared to multiple linear regression (MLR) models using values of R2; for MLR models for all cultivars, R2 ranged between 0.151 and 0.844, while the R2 value for the ANN was 0.87. Moreover, the ANN model gave the best performance criteria for evaluation of citrus yield prediction with a high R2, low root mean squared error, and low mean absolute error compared to the performance criteria of data mining algorithms such as K-nearest neighbor (KNN), KStar, and support vector regression. These encouraging outcomes show how the current ANN model can be used to estimate fruit yields, including citrus fruits and other types of fruit. The novelty of the proposed ANN model lies in the combination of weather parameters and accumulated heat units for accurate citrus yield prediction, specifically tailored for Egyptian regional citrus crops. Furthermore, especially in low- to middle-income countries such as Egypt, the findings of this study can greatly enhance the reliance on statistics when making decisions regarding agriculture and climate change. The citrus industry can benefit greatly from these discoveries, which can help with optimization, harvest planning, and postharvest logistics. We recommended furthering proving the robustness and generalization ability of the results in this study by adding more data points. [ABSTRACT FROM AUTHOR]

The commonly used reference atmospheric profiles for the validation of retrieved atmospheric profiles for microwave sounders have bias compared with real atmospheric profile values, which is detrimental to the validation of the retrieval. Microwave sounder observations are the direct measurements of microwave radiation in atmospheric conditions and are a true representation of the status of the atmosphere. This paper proposed a validation method for the retrieved atmospheric temperature and atmospheric humidity profiles of the satellite-based microwave sounder using its own in-orbit observations. The validation experiments are performed both for the retrievals of the microwave temperature sounder-II (Xi'an Branch, China Academy of Space Technology, Xi'an, China. MWTS-II) and the microwave humidity and temperature sounder (National Space Science Center, Chinese Academy of Sciences, Beijing, China. MWHTS). The validation results show that the retrieved temperature profiles of MWTS-II have higher accuracy compared to the temperature profiles of ERA5 in the atmospheric pressure range of 3–30 hPa, and the accuracy of the rest of the pressure range is comparable between the profiles of ERA5 and the retrieved profiles. And the retrieved temperature profiles of MWHTS have higher accuracy compared to the temperature profiles of ERA5 in the atmospheric pressure level around 50 hPa and lower accuracy in the rest of the pressure levels. In addition, the retrieved humidity profiles of MWHTS have higher accuracy compared to the humidity profiles of ERA5 in the atmospheric pressure range of 350–925 hPa. The proposed validation method for the retrieved atmospheric temperature and atmospheric humidity profiles of MWHTS using its own observations is promising for improving the feasibility and reliability of the validation, and can be a good reference for the application of the satellite in-orbit observations and the optimization of the microwave sounders. [ABSTRACT FROM AUTHOR]

Steel structures with light weight, high rigidity, and easy assembly have become the first choice for large-span complex building materials. At the same time, transparent materials are widely used for the sake of practicality and aesthetics. However, steel structures will be deformed due to changes in temperature, which will affect the accuracy of closure. The components are restricted from free deformation as a result of multiple statically indeterminate structures. A safety hazard will occur if the residual temperature stress is not released. At present, the strain law of open-air steel structures caused by temperature change is still unclear, and the corresponding temperature–strain model has not been established. This paper is based on the third-phase reconstruction and expansion project of Taiyuan Wusu Airport in Xiaodian District, Taiyuan City, Shanxi Province (37°45′ N, 112°38′ E, average altitude of 774 m), winter long time series temperature measured data, deduced daily temperature change laws, and the established relationship model between air temperature and steel surface temperature. Based on the measured data of long-term stress and strain in winter, the strain law of open-air steel columns under temperature change is discussed. According to the results, the air temperature can be utilized to determine the strain of the open-air steel column during winter. The determination coefficient of the temperature–stress model can reach 0.868, and the radial bending stress caused by the change in daily temperature cannot be ignored, accounting for 15.7% of the radial stress at the same time, which can provide a reference for stress calculations of similar structures. [ABSTRACT FROM AUTHOR]

Aiming at the problems of large error and redundancy in the multi-node data acquisition of multi-greenhouse photo growth environmental information, a three-level fusion algorithm based on adaptive weighting, an LMBP network, and an improved D-S theory is proposed. The box-and-line graph method recognizes the original data and then replaces it based on the mean value method; the air temperature, humidity, and light intensity measurements are unbiased estimations of the true value to be estimated, so the first level of fusion chooses the adaptive weighted average algorithm to find the optimal weights of each sensor under the condition of minimizing the total mean-square error and obtains the optimal estimation of the weights of the homogeneous sensors of a greenhouse. The Levenberg–Marquardt algorithm was chosen for the second level of fusion to optimize the weight modification of the BP neural network, i.e., the LMBP network, and the three environmental factors corresponding to "suitable", "uncertain" and "unsuitable" potato growth environments were trained for the three environmental factors in the reproductive periods. The output of the hidden layer was converted into probability by the Softmax function. The third level is based on the global fusion of evidence theory (also known as D-S theory), and the network output is used as evidence to obtain a consistent description of the multi-greenhouse potato cultivation environment and the overall scheduling of farming activities, which better solves the problem of the difficulty in obtaining basic probability assignments in the evidence theory; in the case of a conflict between the evidence, the BPA of the conflicting evidence is reallocated, i.e., the D-S theory is improved. Example validation shows that the total mean square error of the adaptive weighted fusion value is smaller than the variance of each sensor estimation, and sensors with lower variance are assigned lower weights, which makes the fusion result not have a large deviation due to the failure of individual sensors; when the fusion result of a greenhouse feature level is "unsuitable", the fusion result of each data level is considered comprehensively, and the remote control agency makes a decision, which makes full use of the complementary nature of multi-sensor information resources and solves the problem of fusion of multi-source environmental information and the problem of combining conflicting environmental evaluation factors. Compared with the traditional D-S theory, the improved D-S theory reduces the probability of the "uncertainty" index in the fusion result again. The three-level fusion algorithm in this paper does not sacrifice data accuracy and greatly reduces the noise and redundancy of the original data, laying a foundation for big data analysis. [ABSTRACT FROM AUTHOR]

In this paper, the temperature dependence of single event upset (SEU) cross-section in 28 nm embedded Static Random Access Memory (SRAM) of System in Package (SiP) was investigated. An atmospheric neutron beam with an energy range of MeV~GeV was utilized. The SEU cross-section increased by 39.8% when the temperature increased from 296 K to 382 K. Further Technology Computer Aided Design (TCAD) simulation results show that the temperature has a weak impact on the peak pulse current, which is mainly caused by the change of bipolar amplification effect with temperature. As the temperature increases, the critical charge of the device decreases by about 4.8%. The impact of temperature on the SEU cross-section is determined competitively by the peak pulse current and the critical charge. The impact of temperature on critical charge is expected to become more severe as the feature size is further advanced. [ABSTRACT FROM AUTHOR]

This paper focuses on clarifying the heat transfer coefficient necessary for determining the indoor temperature distribution during night ventilation using floor-level windows. Measurements were used to identify the factors that influence the vertical temperature distribution within a room wherein phase-change materials (PCMs) were installed at the floor level. The investigation revealed a temperature differential ranging from 1 °C to a maximum of 3 °C between the floor and the center of the room, attributable to external climatic conditions (outdoor temperature and wind speed). This variation was found to depend on the degree of mixing of indoor air currents. This deviation was critical because it significantly affected the phase-change temperature of PCMs, thereby impacting their thermal storage capabilities. Consequently, this study aimed to refine the predictive accuracy of indoor temperature distributions by proposing a modified vertical temperature distribution model that incorporated these findings. The results of this study are expected to provide better design strategies for building constructions that incorporate PCMs, and to optimize their functionality in passive cooling systems. [ABSTRACT FROM AUTHOR]

In the early stages of building design, decisions are made about the building's form and envelope, but designers rarely base their decisions on sophisticated energy simulations, even though these features are critical to a building's energy performance. This paper employs three methods—empirical, parametric, and uncertainty—to assess the interconnectedness of building form, envelope, orientation, and occupancy regarding thermal comfort and energy consumption for heating and cooling a residential building across three regions: Gdyel (mediterranean climate), Oum El Bouaghi, and Constantine (semi-arid climate). The study variables include indoor air temperature, relative humidity, and energy consumption. The initial findings stem from an experiment conducted in an apartment on the top floor of a building in Gdyel, which allowed us to record the evolution of the variables mentioned throughout the year and validate the parametric results of the multi-zone model created in TRNSYS16 software. This study showed that for the considered climates, a compact form is more suitable; it was found that the top floor with SF = 0.57 needs about 30% to 54% more energy than the inter-floor with SF = 0.21. In addition, the heating and cooling methods and habits adopted by Algerian households are responsible for 18% to 35% on the top floor and the inter-floor, respectively. [ABSTRACT FROM AUTHOR]

According to piloti design, the outdoor thermal environment can be improved in cities with hot summer conditions. Taking Chinese cities with a hot summer and cold winter as the research object, this paper discusses the improvement of the outdoor thermal environment of residential districts in summer by considering piloti design factors. In this article, according to our investigation of piloti design in Wuhan, a basic model of the overhead layer in the Wuhan residential area is presented, along with the effects of different piloti ratios (0–80%), piloti heights (2–6 m), and greening rates (30–35%) on the outdoor thermal environment of buildings. The average air temperature and average wind speed at the pedestrian level are used as outdoor thermal environment indicators, the average PET is used as the outdoor thermal comfort indicator, and the comfort wind ratio is used as the outdoor wind comfort indicator. The results show that increasing the ratio of corridor columns has the greatest thermal comfort enhancement effect in the corridor area, and when the piloti ratio increases from 20% to 80%, the PET in piloti areas reduces by 2.926 °C. Improving the greening rate has the greatest thermal comfort enhancement effect in the passageway area, and when the greening rate increases from 20% to 80%, the PET in piloti areas reduces by 0.9 °C. Furthermore, the increases in both the piloti ratio and piloti height have an enhancement effect on the outdoor wind environment and wind comfort, with thresholds of a piloti ratio over 60% and a piloti height over 5 m. In contrast, the increase in the greening rate will deteriorate the outdoor wind environment and wind comfort. The conclusions of this study are of great significance for the planning and design of overhead layers in residential areas in hot and humid areas in summer. [ABSTRACT FROM AUTHOR]

This study addresses a crucial gap in understanding the impact of urban morphologies on the canopy urban heat islands (CUHI) effect. The selection of reference stations lacks a unified standard, and their surface air temperature (SAT) sequences are also inevitably influenced by urbanization. However, synchronous observational data from relocated meteorological stations could provide high-quality sample data for studying CUHI. Utilizing remote sensing techniques, the findings of this paper revealed that the observation environment of stations after relocation exhibited remarkable representativeness, with their observation sequences accurately reflecting the local climatic background. The differences in synchronized observation sequences could characterize the CUHI intensity (CUHII). Among the various factors, land use parameters and landscape parameters played particularly significant roles. Furthermore, the fitting performance of the random forest (RF) model for both training and testing data was significantly superior to that of the linear model and support vector regression (SVR) model. Additionally, the influence of local circulation on CUHI could not be overlooked. The mechanisms by which urban morphologies affect CUHII under different circulation backgrounds deserve further investigation. [ABSTRACT FROM AUTHOR]

As of 2020, it has been 50 years since the publication of Fanger's predictive model of thermal comfort that was designed for indoor environments and attention worldwide is directed at the COVID-19 pandemic and discussions around recommendations for these indoor environments. In this context, many environments and their occupants will suffer consequences related to thermal comfort due to the necessary indoor air changes. In bus cabins, the impact might be even greater, seeing that they are responsible for the mass transportation of people. Thus, this paper intends to review the studies on thermal comfort that analyzed bus cabin environments. It adapts the PRISMA methodology and, as a result, it includes 22 research papers published in journals. Among those, 73% focused on approaching the occupants' thermal sensation, followed by fuel/energy economy (18%), and driver productivity (9%). The current state-of-the-art indicates that air temperature and air velocity were the parameters most employed by the included studies, but eight papers analyzed all six parameters of the standard models of thermal comfort. The most employed model of thermal comfort was Fanger's, but there has not been an investigation that assesses its consistency in predicting the occupants' thermal sensation in the explored environment. Nevertheless, the analyzed studies recommended constant air change inside closed buses or keeping them open to minimize adverse effects on the occupants' health, especially due to airborne diseases and CO2 concentration possibly being a suitable indicator to identify the need for air change. [ABSTRACT FROM AUTHOR]

Molecular sieve oxygen-production technology, as a kind of air separation–oxygen production, is receiving more and more attention from every oxygen industry. The two-bed molecular sieve oxygen-production system studied in this paper can generally produce enriched gas with an oxygen concentration of more than 90%, which has the characteristics of strong applicability, high reliability, low cost and high efficiency. However, the gas oxygen concentration of a production system is greatly affected by internal and external factors such as the molecular sieve materials, atmospheric pressure and temperature environment. Through the continuous research of the molecular sieve oxygen-production system, it has been found that the oxygen cycle of the molecular sieve bed and the diameter of the washing and sizing hole also have an effect on the gas oxygen concentration of the production system. Therefore, in this paper, the two-bed molecular sieve oxygen-production device is the research object, with different oxygen-production cycles (including pressure time) and different washing and sizing hole diameter simulation experiments used to explore the molecular sieve oxygen-production system's optimal oxygen-production cycle (including pressure time) and the rinsing sizing hole's optimal aperture, to find the structure of the oxygen-production system and the control parameters for the oxygen-production efficiency of the law. The results show that the optimal oxygen-production cycle of the molecular sieve system is 8.0 s (pressure equalization time is 1.3 s), and the optimal diameter of the washing and sizing hole is 0.8 mm. [ABSTRACT FROM AUTHOR]

The paper took Guang'an City in Sichuan Province of China as a research region, and it built an evaluation index system based on 14 evaluation indices according to four criteria, namely, ecological background, ecological structure, ecological benefits, and ecological stress. The Delphi algorithm and entropy weight (a combination of subjective and objective methods) were used to calculate the weight value of each evaluation index, and an ideal point model was used to calculate the ideal point value. The ideal point ecological grade was classified, and the principal component analysis method was used to obtain the main control factors of each year, which revealed the relationship between the ecological distribution of ideal points and the environmental impact factor, with the changing characteristics of the ecology in the research region according to the hotspot model of the spatial differentiation of land ecological quality as the main control factor. Lastly, the paper also analyzed the land ecological quality of Guangan City in 2000, 2005, 2010, and 2015. The study results show that the overall land ecological quality in Guang'an City generally increased from 2005 to 2015. The proportion of forest land area and the temperature were the most important main control factors. The air temperature and the land ecological quality were positively correlated. [ABSTRACT FROM AUTHOR]

Accurate prediction of air temperature is of great significance to outdoor activities and daily life. However, it is important and more challenging to predict air temperature in complex terrain areas because of prevailing mountain and valley winds and variable wind directions. The main innovation of this paper is to propose a regional temperature prediction method based on deep spatiotemporal networks, designing a spatiotemporal information processing module to align temperature data with regional grid points and further transforming temperature time series data into image sequences. Long Short-Term Memory network is constructed on the images to extract the depth features of the data to train the model. The experiments demonstrate that the deep learning prediction model containing the spatiotemporal information processing module and the deep learning prediction module is fully feasible in short-term regional temperature prediction. The comparison experiments show that the model proposed in this paper has better prediction results for classical models, such as convolutional neural networks and LSTM networks. The experimental conclusion shows that the method proposed in this paper can predict the distribution and change trend of temperature in the next 3 h and the next 6 h on a regional scale. The experimental result RMSE reached 0.63, showing high stability and accuracy. The model provides a new method for local regional temperature prediction, which can support the planning of production and life in advance and tend to save energy and reduce consumption. [ABSTRACT FROM AUTHOR]

In the recent past, Andhra Pradesh (AP) has experienced increasing trends in surface air mean temperature (SAT at a height of 2 m) because of climate change. In this paper, we attempt to estimate the SAT using the GFDL-ESM2G (Geophysical Fluid Dynamics Laboratory Earth System Model version 2G), available from the Coupled Model Intercomparison Project Phase-5 (CMIP5). This model has a mismatch with the India Meteorological Department (IMD)'s observations during April and May, which are the most heat-prone months in the state. Hence, in addition to the SAT from the model, the present paper considers other parameters, such as mean sea level pressure, surface winds, surface relative humidity, and surface solar radiation downwards, that have influenced the SAT. Since all five meteorological parameters from the GFDL-ESM2G model influence the IMD's SAT, an artificial neural network (ANN) technique has been used to predict the SAT using the above five meteorological parameters as predictors (input) and the IMD's SAT as the predictand (output). The model was developed using 1981–2020 data with different time lags, and results were tested for 2021 and 2022 in addition to the random testing conducted for 1981–2020. The statistical parameters between the IMD observations and the ANN estimations using GFDL-ESM2G predictions as input confirm that the SAT can be estimated accurately as described in the analysis section. The analysis conducted for different regions of AP reveals that the diurnal variations of SAT in the IMD observations and the ANN predictions over three regions (North, Central, and South AP) and overall AP compare well, with root mean square error varying between 0.97 °C and 1.33 °C. Thus, the SAT predictions provided in the GFDL-ESM2G model simulations could be improved statistically by using the ANN technique over the AP region. [ABSTRACT FROM AUTHOR]

The air temperature changes in the Palu MW7.5 earthquake in Indonesia on 28 September 2018 were analyzed, based on the additive tectonic stress caused by celestial tidal-generating forces (ATSCTF) and air temperature data from the National Center for Environmental Prediction (NCEP). This paper explored the variation characteristics of three-dimensional stratified of air temperature caused by seismic activity and the coupling relationship between air temperature changes and the tidal force. The background information for air temperature calculation was obtained from the tidal force changes, and the air temperature increment method was used to study the temperature evolution process of different periods in the study area. The results found that the tidal force acting on the critical state earthquake faults may be an important external factor inducing earthquakes, and there was indeed a significant air temperature increase anomaly during the Palu MW7.5 earthquake. The paper also summarized the abnormal characteristics of air temperature caused by seismic activity: the air temperature closer to the land's surface has greater anomaly amplitude and a wider anomaly area than that of the upper air. [ABSTRACT FROM AUTHOR]

Yao and Guan [[26]] derive atmospheric temperature and humidity profiles under all sky conditions from GIIRS-observed brightness temperatures using three deep machine learning algorithms. This Topic covers a wide range of topics, including atmospheric dynamics and physics, synoptic weather, climate variability, climate change, and remote sensing observations for weather and climate studies. Due to noise interference, TB observations reflecting rain, clouds, tropical cyclone warm core, temperature and water vapor distributions are not readily distinguishable, especial in channels above the middle troposphere (channels 4-7 and 24), whose dynamic ranges of TB are smaller than low tropospheric channels 1-3. [[9]] is an observational study that quantifies the change in amplitude of synoptic-scale surface temperature variability across the U.S., finding a surge in the surface temperature variability in the Rockies and surrounding regions but a reduction over low land regions. [Extracted from the article]

This paper compares the ideas contained in the main papers published on climate change since World War II to arrive at a suggested consensus of our present knowledge regarding climatic changes and their causes. Atmospheric carbon dioxide is only suggested as a cause in one theory, which, despite its wide acceptance by Politicians, the media, and the Public, ignores the findings in other studies, including the ideas found in the Milankovitch Cycles. It also does not explain the well-known NASA map of the changes between the global 1951–1978 and the 2010–2019 mean annual temperatures. The other theories by Oceanographers, Earth scientists, and Geographers fit together to indicate that the variations in climate are the result of differential solar heating of the Earth, resulting in a series of processes redistributing the heat to produce a more uniform range of climates around the surface of the Earth. Key factors are the shape of the Earth and the Milankovitch Cycles, the distribution of land and water bodies, the differences between heating land and water, ocean currents and gateways, air masses, and hurricanes. Low atmospheric carbon dioxide levels during cold events could result in too little of this gas to support photosynthesis in plants, resulting in the extermination of most life on Earth as we know it. The 23 ka Milankovitch cycle has begun to reduce the winter insolation received at the surface of the atmosphere in the mid-latitudes of the Northern Hemisphere starting in 2020. This results in extreme weather as the winter insolation reaching the surface of the atmosphere in the higher latitudes of the Northern Hemisphere decreases while the summer air temperatures increase. It heralds the start of the next glaciation. A brief outline is given of some of the climatic changes and consequences that may be expected in western Canada during the next 11.5 ka. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) vegetation plays an important role in the local ecosystem, which responds significantly to climate change and can affect local and large-scale weather and climate anomalies. However, little attention has been paid to its year-to-year variation. In this paper, using two NDVI datasets (GIMMS and MODIS) originated from satellite remote sensing, the variability characteristics of NDVI over the TP on the interannual time scale and associated local climatic factors were investigated. The results show that two primary patterns of NDVI governed TP during the main growing season (June–September, JJAS) for the period 1982–2020. The first one is a uniform pattern, with a consistent spatial variation over the entire TP, and the second is a dipole pattern, with an out-of-phase spatial variation of NDVI between the northern and southern TP. Interannual variations of the different climatic factors regulate the NDVI variability over the different regions of the TP. The interannual variability of the uniform NDVI pattern is mainly affected by the two local climatic factors, the preceding May–August precipitation and simultaneous JJAS sunshine duration. Specifically, NDVIs over the southern and eastern TP have a more significant response to the preceding precipitation and simultaneous sunshine duration, respectively. The variability of the dipole NDVI pattern is primarily modulated by the preceding May–August precipitation and simultaneous surface air temperature, ground surface temperature, and sunshine duration. However, NDVIs over the northern and southern TP have different degrees of response to the four climatic factors, with the most significant response being to preceding precipitation. The combined effect of these factors contributes to the formation of the interannual variability in the uniform and dipole patterns. This paper may shed light on deeply understanding the reasons for the inconsistency in variations of vegetation over the different regions of the TP under climate change. In addition to the effect of local climatic factors that this study focuses on, the influence of external climatic factors on the variability of the TP NDVI deserves further research in the future. [ABSTRACT FROM AUTHOR]

This paper illustrates an experimental activity for the closed-loop position control of an actuator made using shape memory alloy (SMA) wire. A solution with the self-sensing effect was implemented to miniaturize the systems, i.e., without external sensors. A proportional control algorithm was initially used, demonstrating the idea's feasibility; the wire can behave simultaneously as an actuator and sensor. An experimental investigation was subsequently conducted for the optimization of the developed actuator. As for the material, a Flexinol wire, Ni-Ti alloy, with a diameter of 0.150 mm and a length of 200 mm, was used. Preliminarily, characterization of the SMA wire at constant and variable loads was carried out; the characteristics detected were elongation vs. electric current and elongation vs. electrical resistance. The control system is PC based with a data acquisition card (DAQ). A drive board was designed and built to read the wire's electrical resistance and power it by pulse width modulation (PWM). A notable result is that the actuator works with good precision and in dynamic conditions, even when it is called to support a load up to 65% different from that for which the electrical resistance–length correlation has previously been experimentally obtained, on which the control is based. This opens up the possibility of using the actuator in a counteracting configuration with a spring, which makes hardware implementation and control management simple. [ABSTRACT FROM AUTHOR]

Negative air ions (NAIs) are crucial for assessing the impact of forests on wellbeing and enhancing the physical and mental health of individuals. They serve as pivotal indicators for assessing air quality. Comprehensive research into the distribution patterns of NAI concentrations, especially the correlation between NAI concentrations and meteorological elements in tourist environments, necessitates the accumulation of additional long-term monitoring data. In this paper, long-term on-site monitoring of NAI concentrations, air temperature, relative humidity, and other factors was conducted in real time over 24 h, from April 2020 to May 2022, to explore the temporal dynamic patterns of NAIs and their influencing factors. The results showed that (1) the daily dynamics of NAI concentrations followed a U-shaped curve. The peak concentrations usually occurred in the early morning (4:30–8:00) and evening (19:10–22:00), and the lowest concentrations usually occurred at noon (12:50–14:45). (2) At the monthly scale, NAI concentrations were relatively high in February, August, and September and low in January, June, and December. At the seasonal scale, NAI concentrations were significantly higher in winter than in other seasons, with higher concentrations occurring in the summer and autumn. (3) Relative humidity, air temperature, and air quality index (AQI) were the primary factors that influenced NAI concentrations. Relative humidity showed a significant positive correlation with NAI concentrations, while air temperature and AQI both exhibited a significant negative correlation with NAI concentrations. Higher air quality corresponds to higher NAI concentrations. Our research provides new insights into NAI temporal dynamics patterns and their driving factors, and it will aid in scheduling outdoor recreation and forest health activities. [ABSTRACT FROM AUTHOR]

Physical and climatic variables such as Tree Canopy coverage, Normalized Difference Vegetation Index (NDVI), Distance to Roads, Distance to the Coast, Impervious Surface, and Precipitation can affect land surface temperature (LST). This paper examines the relationships using linear regression models and explores LST trends in the Miami Statistical Area (MSA) between 2002 and 2021. This study evaluates the effect of dry and wet seasons as well as day and night data on LST. A multiscale investigation is used to examine LST trends at the MSA scale, the individual county level, and at the pixel level to provide a detailed local perspective. The multiscale results are needed to understand spatiotemporal LST distributions to plan mitigation measures such as planting trees or greenery to regulate temperature and reduce the impacts of surface urban heat islands. The results indicate that LST values are rising in the MSA with a positive trend throughout the 20-year study period. The rate of change (RoC) for the wet season is smaller than for the dry season. The pixel-level analysis suggests that the RoC is primarily in rural areas and less apparent in urban areas. New development in rural areas may trigger increased RoC. This RoC relates to LST in the MSA and is different from global or regional RoC using air temperature. Results also suggest that climatic explanatory variables have different impacts during the night than they do in the daytime. For instance, the Tree Canopy variable has a positive coefficient, while during the day, the Tree Canopy variable has a negative relationship with LST. The Distance to the Coast variable changes from day to night as well. The increased granularity achieved with the multiscale analysis provides critical information needed to improve the effectiveness of potential mitigation efforts. [ABSTRACT FROM AUTHOR]

Three-dimensional hydrodynamic modeling for small, stratified tropical lakes in the Philippines and in Southeast Asia in general is not deeply explored. This study pioneers investigating the hydrodynamics of a small crater lake in the Philippines with a focus on temperature simulation using a Fantom Refined 3D model that has been tested mostly for temperate and sub-tropical lakes. The lake's monthly temperature during the dry season served as a reference for the model's initial condition and validation. For the simulation to proceed, input data such as weather, inflow, and bathymetry were prepared. In the absence of hourly meteorological data from local weather stations, this paper adopted the satellite weather data from Solcast. Simple correlation analysis of daily weather data between local stations and Solcast showed valid and acceptable results. Inflow values were estimated using the rational method while the stream temperature was estimated from a regression equation using air temperatures as input. The validated satellite-derived data and runoff model can therefore be employed for 3D modeling. The simulations resulted in extremely higher temperatures compared with those observed when using previous default model settings. Direct modifications were then applied to weather parameters, compromising their integrity but resulting in reasonable profiles. By adding scaling factors to heat flux equations and multiplying their components by 0.75 (shortwave), 1.35 (longwave), 0.935 (air temperature), and 0.80 (wind), better results were achieved. This study identifies several challenges in performing 3D hydrodynamic modeling, such as paucity in input hydro-meteorologic and limnologic data and the need for heat flux model improvement. Overall, this study was successful in employing 3D hydrodynamic modeling in a tropical lake, which can pave directions and serve as an excellent reference for future modeling in the same region. [ABSTRACT FROM AUTHOR]

The paper evaluates the usability of remote satellite-based and proximal ground-based agrometeorological data sources for precision agriculture and crop production in Croatia. The compared agrometeorological datasets stem from the open-access data sources Copernicus CDS and the Agri4Cast portal, and commercial in situ agrometeorological stations (PinovaMeteo) which monitor environmental parameters relevant to the physiological state of crops. The study compares relevant parameters for 10 different locations in Croatia for three consecutive years (2019, 2020, and 2021) to investigate whether model-based data from ERA5-Land and Agri4Cast are well-correlated with ground measurements from independent in situ stations (PinovaMeteo) for specific agrometeorological parameters (air and soil temperature, and precipitation). Our results indicate the following: both the ERA5-Land and Agri4Cast datasets show mostly strong positive correlations with ground observations for air temperature, modest correlations for soil temperature, but modest or even low correlations for precipitation. Analysis of the residuals indicates higher overall residual values, especially in areas with complex topography and near large bodies of water or the sea, and deviations of residuals that may limit the usability of satellite- and model-based data for decision-making in agriculture. [ABSTRACT FROM AUTHOR]

Global climate change has affected vegetation cover in alpine areas. In this paper, we analyzed the correlation between Leaf Area Index (LAI) and climate factors of the Yarlung Tsangpo River basin, and identified their contributions using the quantitative analysis method. The results show that the vegetation cover in the study area generally exhibited an increasing trend. Grassland in the middle- and high-altitude areas was the main contributing area. Temperature is the dominant climatic factor affecting the change, the effect of which increases with the rise in elevation. The influences of precipitation and radiation had obvious seasonality and regionality. The vegetation illustrated a lag response to climate drivers. With the change in the elevation band, the response time to precipitation was significantly less than that to air temperature in the low-elevation area, while the opposite trend was observed in the high-elevation area. In the future, the LAI of the watershed will show different characteristics at different time points, with the increases in the LAI in autumn and winter becoming the main factors for the future increase in the LAI. This provides a crucial basis upon which to explore hydrological and ecological processes as important components of the Third Pole region. [ABSTRACT FROM AUTHOR]

Research on spatio-temporal geostatistical modeling remains a critical challenge in numerous scientific and engineering disciplines. This paper introduces a novel extension of dual kriging, called spatio-temporal dual kriging (ST-DK), in which drift functions with fixed and adaptive coefficients are established. The approach appears to be effective in modeling complex spatio-temporal dynamics, particularly when relevant auxiliary variables exert substantial influence on the target variable. To illustrate its performance, we compare the ST-DK model with the classical spatio-temporal regression kriging (ST-RK) and geographically and temporally weighted regression (GTWR) models for estimating temperature and air pressure data from Thailand in 2018. Our findings demonstrate that both the ST-DK and ST-RK models when utilizing adaptive coefficients outperform their fixed coefficient counterparts. Furthermore, the ST-DK method consistently exhibits superior performance compared to the ST-RK and GTWR methods. [ABSTRACT FROM AUTHOR]

This paper experimentally analyses an indoor environment assessment of a large group of respondents regarding their subjective perception of overall comfort, indoor air quality and humidity. The questionnaire survey was applied as a testing method together with measurements of the physical parameters conducted with a microclimate meter. Two types of environment were analysed: educational rooms and the climate chamber. The comparative analysis of the sensations experienced within them indicates that they generate quite similar responses; however, some discrepancies have been identified. The overall comfort of the climate chamber was typically assessed as being higher than that of the educational rooms at the same air temperature. The most favourable air temperature in the climate chamber was ca. 20.7 °C, while in the educational rooms it was ca. 22.3 °C. The most preferable conditions in the climate chamber occurred at a thermal sensation vote of −0.4 ("pleasantly slightly cool"), while in the educational rooms it occurred at +0.2 ("neutral/pleasantly slightly warm"). Quite strong correlations between overall comfort and indoor air quality as well as between humidity assessment and humidity preference votes were observed, which did not seem to depend on the type of environment. These findings are important because results from the simulated conditions are often used in the analyses of actual living/working environments. [ABSTRACT FROM AUTHOR]

For a long time, wind speed profile measurement has been the primary task of weather forecasting. Therefore, the detection of atmospheric wind speed is extremely important for studying the changes in atmospheric motion. In order to solve the problems of insufficient data collection, low resolution, and low accuracy in atmospheric wind field detection, this paper introduces the relevant theories of wind speed detection, completes the optical design of the system according to the research objectives, and determines the selection of optical devices. At the same time, a Doppler wind lidar system based on a quadrichannel Mach–Zehnder interferometer is designed and built to carry out ground-based observation experiments, collect echo signal data, and inverse the atmospheric radial wind speed. Furthermore, the wind measurement error is analyzed. Firstly, the paper introduces the basic principle of the wind measurement system, i.e., using the Doppler effect of light, and then analyzes the frequency discrimination device of the system in detail, and obtains the theoretical calculation method of atmospheric wind speed inversion. At the same time, the relevant datasets of wind measurement system are analyzed, including backscattering ratio, aerosol, and molecular extinction coefficient, and the emission mechanism of the large pulse laser is also studied in detail, which provides a theoretical basis for the model construction of Doppler lidar and the research on the enhancement of pulsed laser emission energy. Secondly, according to the research index of wind measurement, a Doppler wind measurement lidar system based on a quadrichannel Mach–Zehnder interferometer is designed, including the design of ab external light path transceiver system, internal light path interferometer, software and hardware, and algorithm. The calibration of the quadrichannel Mach–Zehnder interferometer is completed, with its maximum interference contrast reaching 0.869. Through the self-developed optical transceiver system and data acquisition system, the echo signal of lidar is received and detected. Lastly, the data of echo signals collected by the interferometer are analyzed, the radial atmospheric wind speed profile is inversed, and the signal-to-noise ratio and wind speed measurement error of the system are evaluated. The experimental results show that the maximum signal-to-noise ratio (SNR) of the system can reach 1433 when the emission pulse energy of the large pulse laser is adjusted to 255 mJ, and the farthest wind speed detection distance is about 8 km. The high-precision wind speed detection range can reach 2 km, the actual wind measurement errors in this range are all within 1.593 m/s, and the minimum error is only 0.418 m/s. In addition, the backscattering coefficient and extinction coefficient of atmospheric molecules and aerosols in the range of 8 km and the atmospheric temperature in the range of 10 km are also measured. The measurement accuracy of the aerosol extinction coefficient is ±0.001 m−1, and the measurement error of atmospheric temperature within 10 km is within 2 K, achieving the expected goals. [ABSTRACT FROM AUTHOR]

The paper deals with long-term means of 557.7 nm atomic oxygen airglow intensity (OI) and air temperature within the mesopause over the southern regions of East Siberia. Data on temperature and emission parameters were obtained with a SABER radiometer, KEO Scientific "Arinae" Fabry–Pérot interferometer, SATI spectrometer and NRLMSIS model over the Tory Geophysical Observatory (52° N, 103° E). Annual variations of 557.7 nm emission intensity and temperature obtained in observations differ from model approximations. Potential reasons for the discrepancies revealed are discussed. [ABSTRACT FROM AUTHOR]

In the process of preparing asphalt-based spherical activated carbon, the molten asphalt must be formed into qualified spherical particles through the granulation process. Taking the process of molten asphalt granulation as the research direction, this paper carries out an asphalt rotational viscosity experiment and a thermogravimetric differential thermal experiment (TG–DSC), and obtains the optimal temperature and viscosity values for the asphalt granulation process. The fluent module in ANSYS software is used to input the known asphalt and prilling tower parameters. Based on the asphalt prilling principle, the thermal environment in the prilling tower during on-site melting and asphalt prilling is simulated. The results show that No. 70 matrix asphalt has good fluidity at 135 °C, and that, subsequently, the viscosity of the asphalt is stable and the fluidity of asphalt remains good with the increase in temperature; they also showed that the air velocity is fastest in the central area of the prilling tower, the air temperature is the highest at the top of the tower, and the air temperature in the central area is the lowest at the same height. Finally, a new approach to the granulation process of pitch-based spherical activated carbon is developed, which provides a reference for the basic experimental data and numerical simulation direction for the use of granulation towers to complete the granulation of molten asphalt in industry in the future. [ABSTRACT FROM AUTHOR]

Outgoing longwave radiation (OLR) data are one of the key factors in studying the radiation balance of the earth–atmosphere system in East Asia. It is of great significance to explore the influence factors on OLR. This paper processes the data of nearly 19 years, from September 2002 to February 2022, and conducts in-depth research using the exponential smoothing method, empirical orthogonal decomposition (EOF), correlation analysis, and other methods. We found that the spatial distribution of OLR is zonal symmetry and gradually decreases with the increase of latitude. Using EOF analysis, it is found that the total variance contribution of the first four decomposed spatial features exceeds 70%, and the overall change trend of the four-time coefficients in the past 19 years all show a downward trend. OLR is positively correlated with total column water vapor (TCWV), air temperature (AT), and cloud top temperature (CTT), but negatively correlated with cloud top pressure (CTP). OLR has a similar spatial correlation distribution with TCWV and AT, while the spatial correlation between OLR and CTP is opposite to the first two parameters. In most parts of East Asia, the spatial correlation with CTT exceeds 0.8. The change in OLR value is affected by various meteorological parameters. In East Asia, the positive correlation between 30° N and 60° N is significantly affected by TCWV, AT, and CTT; and the negative correlation is more significantly affected by CTP. At 0–25° N, the positive correlation is significantly affected by CTP and CTT, while the negative correlation is significantly affected by TCWV and AT. [ABSTRACT FROM AUTHOR]

In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies. [ABSTRACT FROM AUTHOR]

This article addresses the simulation of urban air temperatures with a focus on evaluating the Urban Weather Generator (UWG) model over Toulouse, France. As urban temperatures, influenced by factors like urbanization, anthropogenic heat release, and complex urban geometry, exhibit an urban heat island (UHI) effect, understanding and mitigating UHI become crucial. With increasing global warming and urban populations, aiding urban planners necessitates accurate simulations requiring data at the canyon level. The paper evaluates UWG's performance in simulating air temperatures under realistic conditions, emphasizing an operational context and a non-specialist user's perspective. The evaluation includes selecting the most suitable meteorological station, assessing the impact of the rural station choice, and conducting a sensitivity analysis of input parameters. The validation demonstrates good agreement, with a mean bias error (MBE) of 0.02 °C and a root mean square error (RMSE) of 1.73 °C. However, we highlight the fact that UWG performs better in a densely urbanized area, and exhibits limitations in sensitivity to urban surface parameter variations, particularly in less urbanized areas. [ABSTRACT FROM AUTHOR]

This paper is devoted to the analysis of air temperature and humidity changes during the two solar eclipses of 26 December 2019 and 21 June 2020 in Saudi Arabia based on data we collected from two different sites. We highlight the complexity of humidity's response to a solar eclipse, which is quite different from temperature's response. During the December event, the Sun rose already partially eclipsed, while for the June eclipse, it was only partial at Riyadh. This difference apparently affected the observed response on the recorded variables: temperature, relative humidity (RH), and vapor pressure (VP) in the two events. Changes in these variables went unnoticed for the first eclipse since they were within the natural variability of the day; yet for the other, they showed evident alterations in the slopes of the major parameters, which we analyze and discuss. A decrease in temperature of 3.2 °C was detected in Riyadh. However, RH and VP showed an oscillation that we explain taking into account a similar effect reported in other eclipses. We measured a time lag of about 15 min from the eclipse central phase in the city. Related fluctuations and dynamics from the computed rates of the temporal variation of temperature and RH are scrutinized. Furthermore, an overdue significant review of terrestrial atmospheric parameters is also offered in the context of the eclipse meteorology, particularly related to desert atmospheres. We also try to identify the influence of solar eclipses in similar environments doing a broad inter-comparison with other observations of these variables in the Near East, northern Africa, and in the United States. These inter-comparisons reveal how complex and dissimilar the response of the lower atmosphere to a solar eclipse can be within a desert environment and other similar environments. [ABSTRACT FROM AUTHOR]

The climate change–built environment nexus is complex and intertwined. Recognizing the rising air temperatures and solar radiations owing to climate-induced global warming, it is critical to manage the increased building energy and cooling loads in the Middle East Gulf states' hot desert climates (Bwh). One of the top climate priorities is to promote climate resilience by reducing risks and enhancing adaptation options. This study aims to systematically review the existing literature to document building energy performances in and the associated adaptation measures of the Middle East Gulf states, regarding the implications of climate change. It is accomplished by answering the following questions: 'How well do we understand the effects of climate change on building energy use in hot urban deserts?' and 'What are the most appropriate adaptation strategies to reduce energy use in hot urban deserts?'. Using the Preferred Reporting Items for Systematic review and Meta-Analysis protocols (PRISMA), 17 studies on the influence of present and future weather scenarios on building performance are examined, considering variations in typology, methods, and input variables. Finally, the paper identifies the preferred methods and input variables for modelling building energy performance under predicted climatic changes. Passive design considerations are considered highly effective in mitigating and adapting to climate change implications. Thermal insulation and efficient window glazing are identified as the best-performing strategies, while the use of solar Photovoltaic (PV) is considered efficient in meeting the primary energy demands. The study's findings can assist planners and designers in projecting future climatic influences on the energy usage of existing buildings. [ABSTRACT FROM AUTHOR]

This paper presents an application of the Simulink stvmgain S-function for the thermal modelling of a building zone based on the resistance–capacitance scheme of EN ISO 13790. That model in the form of the state-space matrix with time-varying elements was used in simulations of a building with hourly and, suggested in that standard, daily averaged ventilation airflow in five European cities. The following two ventilation schedules were used: occupancy-based; and wind-dependent. Comparative simulations were conducted in EnergyPlus. In general, the results obtained for the annual heating and cooling demand were better for hourly than daily averaged ventilation with an error below 10%. However, in several cases of cooling, the error was above 30%. When considering hourly indoor air temperatures, the proposed method provided very good results with MAE of up to 0.52 °C and 0.46 °C, RMSE < 0.69 °C and 0.62 °C, and CV(RMSE) < 3.09% and 2.75% for the daily averaged and hourly ventilation flow, respectively. For wind-driven ventilation, the temperatures were as follows: MAE < 0.49 °C and 0.48 °C; RMSE < 0.69 °C and 0.68 °C; and CV(RMSE) < 3.01% and 2.97%. [ABSTRACT FROM AUTHOR]

Using unmanned aerial vehicles (UAVs) for bridge inspection is becoming increasingly popular due to its ability to improve efficiency and ensure the safety of monitoring personnel. Compared to traditional manual monitoring methods, UAV inspections are a safer and more efficient alternative. This paper examines the impact of meteorological conditions on UAV-based bridge monitoring during specific tasks, with the aim of enhancing the safety of the UAV's costly components. The wake vortex behind a bridge structure can vary over time due to airflow, which can have a direct impact on the safety of UAV flights. To assess this impact, numerical analysis is conducted based on monitoring requirements specific to different tasks, taking into account wind speed, wind direction, and air temperature. In order to optimize UAV trajectory, it is important to consider the wake vortex intensity and its associated influence region, which can pose a potential danger to UAV flight. Additionally, the analysis should take into account the aerodynamic effects of different types of bridge columns on the wake vortex. An optimization algorithm was utilized to optimize the trajectory of a UAV during bridge inspections within the safe region affected by wind fields. This resulted in the determination of an effective and safe flight path. The study reveals that varying wind speeds have an impact on the safe flight zone of UAVs, even if they are below the operational requirements. Therefore, when monitoring bridges using UAVs, it is important to take into account the influence of meteorological conditions. Furthermore, it was observed that the flight path of UAVs during square cylinder column monitoring is longer and more time-consuming than round cylinder column monitoring. Determining an effective UAV inspection path is crucial for completing bridge monitoring tasks in windy conditions, establishing bridge inspection standards, and developing the Intelligent Bridge Inspection System (IBIS). [ABSTRACT FROM AUTHOR]