Function Of Air Temperature Research Articles

Physiological responses, ethology, and ingestive behavior of Anglo-Nubiana goats submitted to different air temperatures

The objective of this study was to evaluate the physiological parameters and ingestive behavior of Anglo-Nubian goats as a function of air temperature, as well as the correlation of these variables. Six male goats were distributed in a completely randomized design in a climate chamber. The treatments consisted of four different controlled AT (20, 24, 28 and 32 °C). The physiological responses: heart rate (HR), respiratory rate (RR) and rectal temperature (RT) were collected at three different times of the day (8 am, 12 pm and 4 pm). The behavioral responses evaluated were: lying inactive, standing inactive, feeding, standing ruminating and lying ruminating. The feed intake decreased linearly in the hours of 4–7 AM, according to the increase in AT. The time spent in the lying ruminating activity decreased linearly (P<0.05) with the increase in AT. The intake and the rate of dry matter intake decreased linearly (P<0.05) with the increase in AT and the water intake increased linearly (P<0.05). The overall results provide information that can be used in heat tolerance studies, helping livestock farmers around the world to plan and make decisions. In addition to contributing to the development of strategies, national and international guidelines for mitigation and accurate assessment of thermal stress.

Estimating the sensitivity of the Priestley–Taylor coefficient to air temperature and humidity

Abstract. The Priestley–Taylor (PT) coefficient (α) is generally set as a constant value or is fitted as an empirical function of environmental variables, and it can bias the evaporation estimation or hydrological projections under global warming. By using an atmospheric boundary layer model, this study derives a theoretical and parameter-free equation for estimating α as a function of air temperature (T) and specific humidity (Q). With observations from several waterbodies and non-water-limited land sites, we demonstrate that, in addition to estimating the value of α well, the derived expressions can also capture the sensitivity of α to T and Q, that is, dα/dT and dα/dQ. α is generally negatively associated with T and Q, in which regard T plays a more fundamental role in controlling α behaviors. Based on climate model data, we further show that this negative relationship between α and T is of great importance for long-term hydrological predictions. We also provide a lookup graph for practical and broad uses to directly find the values of dα/dT and dα/dQ under specific conditions. Overall, the derived expression gives a physically clear and straightforward approach to quantify changes in α, which is essential for PT-based hydrological simulation and projections.

Effects of slow temperature acclimation of photosynthesis on gross primary production estimation

The slow temperature acclimation of photosynthesis has been confirmed through early field experiments and studies. However, this effect is difficult to characterize and quantify with some simple and easily accessible indicators. As a result, the impact of slow temperature acclimation of photosynthesis on gross primary production (GPP) estimation has often been overlooked or not integrated into most GPP models. In this study, we used a theorical variable-state of acclimation (S), to characterize the slow temperature acclimation. This variable represents the temperature to which the photosynthetic machinery adapts and is defined as a function of air temperature (Ta) and time constant (τ) required for vegetation to respond to temperature, to discuss its impact on GPP simulation. We used FLUXNET2015 dataset to calculate S and established a GPP model using S and shortwave radiation (SW) based on random forest algorithm (S model). As a comparison, we directly used Ta and SW to build the other GPP model (Ta model). Moreover, the divergent temperature acclimation capacities of plants are crucial to predict and make preparations for likely temperature stress in the future. Therefore, the spatial distribution of τ values was also mapped using satellite sun induced chlorophyll fluorescence (SIF) and Ta datasets. The results indicated that: (1) taking into account the slow temperature acclimation of photosynthesis led to a more precise estimation of GPP which mainly reflected in reduction of excessive fluctuations in GPP predictions; (2) considering the slow temperature acclimation of photosynthesis can reduce the sensitivity of vegetation to temperature; (3) the improvement of S model in GPP estimations was different in different vegetation growth stages which was more significant in the springtime recovery stage; (4) τ values had significant spatial distribution which was strongly affected by the determinants of vegetation growth and seasonal variations in temperature.

Permafrost Formation in a Meandering River Floodplain

AbstractPermafrost influences 25% of land in the Northern Hemisphere, where it stabilizes the ground beneath communities and infrastructure and sequesters carbon. However, the coevolution of permafrost, river dynamics, and vegetation in Arctic environments remains poorly understood. As rivers meander, they erode the floodplain at cutbanks and build new land through bar deposition, creating sequences of landforms with distinct formation ages. Here we mapped these sequences along the Koyukuk River floodplain, Alaska, analyzing permafrost occurrence, and landform and vegetation types. We used radiocarbon and optically stimulated luminescence (OSL) dating to develop a floodplain age map. Deposit ages ranged from modern to 10 ka, with more younger deposits near the modern channel. Permafrost rapidly reached 50% areal extent in all deposits older than 200 years then gradually increased up to ∼85% extent for deposits greater than 4 Kyr old. Permafrost extent correlated with increases in black spruce and wetland abundance, as well as increases in permafrost extent within wetland, and shrub and scrub vegetation classes. We developed an inverse model to constrain permafrost formation rate as a function of air temperature. Permafrost extent initially increased by ∼25% per century, in pace with vegetation succession, before decelerating to &lt;10% per millennia as insulating overbank mud and moss slowly accumulated. Modern permafrost extent on the Koyukuk floodplain therefore reflects a dynamic balance between widespread, time‐varying permafrost formation and rapid, localized degradation due to cutbank erosion that might trigger a rapid loss of permafrost with climatic warming.

Effects of Atom Search-Optimized Thornthwaite Potential Evapotranspiration on Root and Shoot Systems in Controlled Carica papaya Cultivation

Potential evapotranspiration (PET) indicates if a cultivation area is suitable for planting. Currently, site-specific PET models that are based on large geographic regions are vulnerable to inaccurate predictions as a result of climate change and sudden changes in the environmental abiotic stressors that affect plant growth. For the aim of promoting the papaya Sinta F1 cultivar, the study optimized the standard Thornthwaite PET model by integrating three advanced physics-based metaheuristics and evolutionary computing, namely atom search (ASO), differential evolution (DE), and multiverse (MVO) optimizers. The PET value was optimized through minimization as a function of air temperature, light intensity, heat index, and extended heat index. As the PET value approaches 0, it indicates that there is more soil-water content that can be absorbed by plants. Based on the four cultivation treatments (uncontrolled, ASO, DE, and MVO) exposed in three replicates within 90 days, the ASO-optimized Thornthwaite PET-treated (ASOTh) papaya plants resulted in the highest chlorophyll a and b concentrations, densest stomatal density, concentrated root and stem xylem and phloem vessels, considerable root and stem length, most formed leaf count, and strongest action potentials coming from stem membrane for both light and dark periods. This proves the applicability of the intelligent process in modifying the Thornthwaite model for plant growth promotion. Also, through the developed ASOTh, the stem length and thickness ratio was improved for mechanical stability to facilitate more branching leaves and potential fruits during the fruiting stage, and the chlorophyll a and b ratio was enhanced, which naturally extended the light energy band for photosynthesis. Overall, the newly developed ASOTh model may be used to grow papaya seedlings year-round anywhere on Earth if there is a control system to regulate the environmental setting inside the growth chamber.

Variation of Mean Radiant Temperature in Rooms for Summer and Winter Conditions

The standard for ergonomics of the thermal environment provides information on the calculation of optimal thermal comfort. Operative temperature (OT) is one of the essential elements of thermal comfort and is a function of air temperature, mean radiant temperature (MRT), and air velocity. This paper investigates the impact of diverse influences on MRT in an office room based on occupant position and posture (seated and standing). A comparative simulation study of the varied thermal transmittance (U-value) of the only external wall with a window in an office room depending on the wide-ranging outdoor temperature is conducted in the MATLAB tool Simulink. The air temperature and air velocity are assumed according to the standards, and the MRT is simulated. The angle factors, U-value of walls/windows, occupant position, occupant posture, and outdoor temperature are the critical parameters that affect MRT. The results show varied responses from MRT for each of the five outdoor temperature scenarios simulated for three types of exterior walls. Seated occupants have equal MRT, whereas standing occupants have minor discrepancies when exposed to a window at the same distance in all outdoor scenarios. When the placement of occupants is not equally exposed to the window, the seated occupants have a higher MRT difference than the standing occupants.

Growth Rates of Vibrio parahaemolyticus Sequence Type 36 Strains in Live Oysters and in Culture Medium.

The pathogenic marine bacterium Vibrio parahaemolyticus can cause seafood-related gastroenteritis via the consumption of raw or undercooked seafood. Infections originating from relatively cool waters in the northeast United States are typically rare, but recently, this region has shown an increase in infections attributed to the ecological introduction of pathogenic sequence type 36 (ST36) strains, which are endemic to the cool waters of the Pacific Northwest. A 2005 risk assessment performed by the Food and Drug Administration (FDA) modeled the postharvest growth of V. parahaemolyticus in oysters as a function of air temperature and the length of time the oysters remained unrefrigerated. This model, while useful, has raised questions about strain growth differences in oyster tissue and whether invasive pathogenic strains exhibit different growth rates than nonclinical strains, particularly at lower temperatures. To investigate this question, live eastern oysters were injected with ST36 clinical strains and non-ST36 nonclinical strains, and growth rates were measured using the most probable number (MPN) enumeration. The presence of V. parahaemolyticus was confirmed using PCR by targeting the thermolabile hemolysin gene (tlh), thermostable direct hemolysin (tdh), tdh-related hemolysin (trh), and a pathogenesis-related protein (prp). The growth rates of the ST36 strains were compared to the FDA model and several other data sets of V. parahaemolyticus growth in naturally inoculated oysters harvested from the Chesapeake Bay. Our data indicate that the growth rates from most studies fall within the mean of the FDA model, but with slightly higher growth at lower temperatures for ST36 strains injected into live oysters. These data suggest that further investigations of ST36 growth capability in oysters at temperatures previously thought unsuitably low for Vibrio growth are warranted. IMPORTANCE Vibrio parahaemolyticus is the leading cause of seafood-related gastroenteritis in the United States, with an estimated 45,000 cases per year. Most individuals who suffer from vibriosis consume raw or undercooked seafood, including oysters. While gastroenteritis vibriosis is usually self-limiting and treatable, V. parahaemolyticus infections are a stressor on the growing aquaculture industry. Much effort has been placed on modeling the growth of Vibrio cells in oysters in order to aid oyster growers in designing harvesting best practices and ultimately, to protect the consumer. However, ecological invasions of nonnative bacterial strains make modeling their growth complicated, as these strains are not accounted for in current models. The National Shellfish Sanitation Program (NSSP) considers 10°C (50°F) a temperature too low to enable Vibrio growth, where 15°C is considered a cutoff temperature for optimal Vibrio growth, with temperatures approaching 20°C supporting higher growth rates. However, invasive strains may be native to cooler waters. This research aimed to understand strain growth in live oysters by measuring growth rates when oysters containing ST36 strains, which may be endemic to the U.S. Pacific Northwest, were exposed to multiple temperatures postharvest. Our results will be used to aid future model development and harvesting best practices for the aquaculture industry.

Thermal requirements and agrometeorological modeling of cotton growth under soil fertility levels

The objective was to quantify the thermal requirements and model the growth of cotton as a function of air temperature and degree-days, under levels of soil saturation and potassium fertilization, grown in a protected environment, in Bom Jesus, Piauí. The experimental design used was a completely randomized design (DIC) with a 3 X 3 + Witness factorial scheme, consisting of three levels of base saturation (V%) (50%, 60% and 70%) and three concentrations of potassium fertilization doses (50% below recommended; recommended, according to soil analysis; 50% above recommended) and Control, without K application, with four replications. Plant height, stem diameter, number of nodes, midrib length and leaf area were evaluated. The meteorological data were obtained in a portable meteorological station, installed inside the protected environment. Among the stages, the First Boll-Harvestpresented the highest thermal demand, with an average of 551.7 °gd and 34 days of duration, followed by the Emergence-First Floral Bud (435.6 °gd), First Floral Bud- First Flower (362.5 °gd) and First Flower-First Boll (300.3 °gd), the Sowing-Emergence phase obtained 51.4 °gd. Air temperature is the meteorological element with the greatest impact on cotton development.

From speed of sound to vapour pressure: an undergraduate school experiment as an example of systematic error research

This article presents an undergraduate project for measuring the speed of sound in the air as a function of air temperature. The measurement is implemented in two versions. The simplicity of the basic experiment in dry air is used for a detailed analysis of systematic errors: the measured values are corrected with an additive constant and optimized to match the expected parabolic dependence of the speed of sound on temperature. Such a time correction is correlated with the physical content, that is, by changing the phase of oscillation of the pressure difference at the reflection of the sound at the open end of the tube. The second part of the experiment involves measuring the speed of sound in saturated humid air as a function of air temperature and allows for a substantive connection of two areas of physics (waves and thermodynamics). The measured water vapour pressure, within the range of statistical errors, follows the theoretical course up to the upper limit of the measured temperature range (60 °C) surprisingly well.

Determining the Dependence of the Speed of Sound in Air on Air Temperature Based on Properties of Standing Waves

Standing waves are a naturally arising phenomenon in many situations where sound waves propagate in an enclosed medium. Inspired by problem 17 from the International Young Naturalists Tournament (2021), this investigation aims to establish a relationship between the speed of sound in air as a function of air temperature at constant pressure and humidity. This goal is achieved by exploiting certain properties of standing sound waves in a tube, sealed off at one end. By varying the length of the tube and the temperature of the air inside, properties of the air, such as its molar mass, can also be determined.

Kinetics of low‐temperature catalytic combustion of ethylene at wet conditions for postharvest storage applications

AbstractThe study addresses the reduction of ethylene levels in postharvest storage applications using a selected Pd‐Zn‐Sn/TiO2 catalyst (US Patent 11065579) capable of reacting trace concentrations of ethylene at temperatures as low as 278 K and relative humidity as high as 90%. The rate law is derived from data collected using a constant volume batch reactor, and a model for a storage room with an associated isothermal packed bed reactor is developed. The amount of catalyst required to maintain an ethylene concentration of 0.1 ppmv in a room containing 20 tons of fruit having an ethylene metabolism of 0.1 μl/kg h was calculated as a function of air temperature and water content. While the catalyst can continuously remove ethylene from saturated, refrigerated air, the amount of catalyst required can be reduced significantly by incorporating conventional air conditioning solutions upstream of the catalyst bed. Such combined systems and their functions are discussed.

Ambient air pollution and cardiovascular disease rate an ANN modeling: Yazd-Central of Iran

This study was aimed to investigate the air pollutants impact on heart patient's hospital admission rates in Yazd for the first time. Modeling was done by time series, multivariate linear regression, and artificial neural network (ANN). During 5 years, the mean concentrations of PM10, SO2, O3, NO2, and CO were 98.48 μg m−3, 8.57 ppm, 19.66 ppm, 18.14 ppm, and 4.07 ppm, respectively. The total number of cardiovascular disease (CD) patients was 12,491, of which 57% and 43% were related to men and women, respectively. The maximum correlation of air pollutants was observed between CO and PM10 (R = 0.62). The presence of SO2 and NO2 can be dependent on meteorological parameters (R = 0.48). Despite there was a positive correlation between age and CD (p = 0.001), the highest correlation was detected between SO2 and CD (R = 0.4). The annual variation trend of SO2, NO2, and CO concentrations was more similar to the variations trend in meteorological parameters. Moreover, the temperature had also been an effective factor in the O3 variation rate at lag = 0. On the other hand, SO2 has been the most effective contaminant in CD patient admissions in hospitals (R = 0.45). In the monthly database classification, SO2 and NO2 were the most prominent factors in the CD (R = 0.5). The multivariate linear regression model also showed that CO and SO2 were significant contaminants in the number of hospital admissions (R = 0.46, p = 0.001) that both pollutants were a function of air temperature (p = 0.002). In the ANN nonlinear model, the 14, 12, 10, and 13 neurons in the hidden layer were formed the best structure for PM, NO2, O3, and SO2, respectively. Thus, the Rall rate for these structures was 0.78–0.83. In these structures, according to the autocorrelation of error in lag = 0, the series are stationary, which makes it possible to predict using this model. According to the results, the artificial neural network had a good ability to predict the relationship between the effect of air pollutants on the CD in a 5 years' time series.

Novel and Simple Formulae to Calculate Air Molecular-Transport Properties of Momentum and Heat Transfer.(Dept.P)

In this paper three novel and simple formulae are deduced to calculate the dynamic Viscosity, the kinematic viscosity and thermal conductivity of air on knowing air temperature and pressure. These formulae can be ap p lied under a wide range of working conditions. They can be used at any temperature (up to 2500 oK) and at p ressures below 10 Atmospheres. Formula (3) gives the dynamic viscosity of air while formula (6) gives its thermal conductivity on knowing air temperature. Formula (5) gives the kinematic viscosity of air as a function of air temperature and pressure. Each formula gives the required property in one step calculation with an excellent accuracy as only ± 3% maximum deviation from the available data in the literature is noted over that wide range of working conditions. From these formulae momentum and heat-transfer calculations which need the knowldge of viscosity and thermal conductivity of air can now be done on knowing air temperature and p ressure without referring to the literature to get these p hysical properties. In this way a great simplicity and availability in air calculations is realized.

Can building orientation perturb micro-climatic conditions inside classrooms located in hot-humid climatic condition?

Thermal comfort inside classrooms located in an institutional building is examined as a function of air temperature, relative humidity and wind velocity. The effect of east-west orientation on the thermal comfort inside the classrooms located in different floor levels is understood based on field experiments and validated using computational fluid dynamics simulations. The air temperature inside the classrooms shows an increasing trend with the floor level. Air temperature and relative humidity inside the classrooms reveal an inverse relationship as a function of east-west orientation with different floor level. As time progresses, the air temperature inside classrooms located on the eastern side of the building is apparently higher than rooms situated on the western side of the building, both field experiments and simulation acknowledge the same. Appropriate reasons have been proposed behind the discussed phenomenon using computational fluid dynamics simulation.

Thermally Driven Interfacial Degradation between Li7La3Zr2O12 Electrolyte and LiNi0.6Mn0.2Co0.2O2 Cathode

Solid-state batteries offer higher energy density and enhanced safety compared to the present lithium-ion batteries using liquid electrolytes. A challenge to implement them is the high resistances, especially at the solid electrolyte interface with the cathode. Sintering at elevated temperature is needed in order to get good contact between the ceramic solid electrolyte and oxide cathodes and thus to reduce contact resistances. Many solid electrolyte and cathode materials react to form secondary phases. It is necessary to find out which phases arise as a result of interface sintering and evaluate their effect on electrochemical properties. In this work, we assessed the interfacial reactions between LiNi0.6Mn0.2Co0.2O2 (NMC622) and Li7La3Zr2O12 (LLZO) as a function of temperature in air. We prepared model systems by depositing thin-film NMC622 cathode layers on LLZO pellets. The thin-film cathode approach enabled us to use interface-sensitive techniques such as X-ray absorption spectroscopy in the near-edge as well as the extended regimes and identify the onset of detrimental reactions. We found that the Ni and Co chemical environments change already at moderate temperatures, on-setting from 500 °C and becoming especially prominent at 700 °C. By analyzing spectroscopy results along with X-ray diffraction, we identified Li2CO3, La2Zr2O7, and La(Ni,Co)O3 as the secondary phases that formed at 700 °C. The interfacial resistance for Li transfer, measured by electrochemical impedance spectroscopy, increases significantly upon the onset and evolution of the detected interface chemistry. Our findings suggest that limiting the bonding temperature and avoiding CO2 in the sintering environment can help to remedy the interfacial degradation.

Fenologia e qualidade de frutos de acessos de Physalis spp.

Objetivou-se com este trabalho avaliar a fenologia em função da temperatura do ar e a qualidade de frutos de acessos de Physalis spp. visando sua potencial utilização em programas de melhoramento genético. O experimento foi conduzido na Universidade Federal da Fronteira Sul - campus Chapecó, SC. O delineamento experimental foi inteiramente casualizado, com 67 acessos de Physalis spp. Foram avaliados componenetes fenológicos em três períodos diferentes, observando o (1) número de dias decorridos desde a emissão do botão floral à antese, (2) dias decorridos da antese à fixação de frutos e (3) número de dias para a emissão de nós. Com os dados de temperatura do ar, foi calculada a soma térmica (GD) necessária para alcançar o início de cada evento fenológico. No que tange às variáveis produtivas, foram analisadas a massa de fruto com cálice (g), massa de fruto sem cálice (g), sólidos solúveis (°Brix) e o volume médio de fruto (cm3). Os dados fenológicos foram submetidos a análises descritivas enquanto que os dados produtivos, à Análise de Componentes Principais (PCA – Principal Components Analysis). O primeiro período de observação (06 a 30 de janeiro) resultou em menor número de dias necessários para o aparecimento de nós e para atingir a frutificação à partir da floração. A presença do cálice nos frutos aumentou sensivelmente a massa média do fruto em aproximadamente 0,45 g. A temperatura influencia o ciclo fenológico dos 67 acessos de Physalis os quais, por sua vez, se diferenciam no que diz respeito à qualidade de frutos.

Historical changes in the stomatal limitation of photosynthesis: empirical support for an optimality principle.

The ratio of leaf internal (ci ) to ambient (ca ) partial pressure of CO2 , defined here as χ, is an index of adjustments in both leaf stomatal conductance and photosynthetic rate to environmental conditions. Measurements and proxies of this ratio can be used to constrain vegetation model uncertainties for predicting terrestrial carbon uptake and water use. We test a theory based on the least-cost optimality hypothesis for modelling historical changes in χ over the 1951-2014 period, across different tree species and environmental conditions, as reconstructed from stable carbon isotopic measurements across a global network of 103 absolutely dated tree-ring chronologies. The theory predicts optimal χ as a function of air temperature, vapour pressure deficit, ca and atmospheric pressure. The theoretical model predicts 39% of the variance in χ values across sites and years, but underestimates the intersite variability in the reconstructed χ trends, resulting in only 8% of the variance in χ trends across years explained by the model. Overall, our results support theoretical predictions that variations in χ are tightly regulated by the four environmental drivers. They also suggest that explicitly accounting for the effects of plant-available soil water and other site-specific characteristics might improve the predictions.

Secretory structures and chemical composition of the essential oil from leaves of Myrsine leuconeura Mart. (Primulaceae)

Myrsine leuconeura Mart. is used by ethnic groups in Brazil to treat infections of the urinary tract, but the chemical profile and morphological characteristics of this medicinal plant have not yet been reported. We have identified the secretory structures of the leaves of this species and determined the influence of geographic site and season of harvesting on the accumulation and chemical composition of the essential oil. A histochemical study was performed using optical and scanning electron microscopy, while essential oils were obtained by hydrodistillation of dried leaves and analyzed by gas chromatography/mass spectrometry. The leaf oils were composed mainly of sesquiterpenes (93.9–96.6%), bicyclogermacrene (12.2–14.7%), (E)-caryophyllene (10.6–14.4%), α-guaiene(7.7–10.1%), spathulenol (6.9–9.6%) and δ-cadinene (6.7–7.2%) being the major constituents. Although site and season of collection did not influence the qualitative composition of the leaf oil, the accumulation of (E)-caryophyllene varied as a function of air temperature and rainfall. The secretory structures in M. leuconeura leaves were identified as peltate-type glandular trichomes, secretory canals, oil cells and mucilage cells. Essential oils were stored in solitary cells and secretory canals, most especially in the latter, but not in the glandular trichomes. This is the first report on the accumulation of essential oils in leaf epidermal cells in the genus Myrsine.

Empirical prediction of snow and land-fast sea ice temperature from surface meteorology on Pistolet Bay, Northern Newfoundland

Abstract The temperature of sea ice and snow cover on the ice surface is a critical component of thermodynamic models of sea ice. Ice temperature is also an important factor in the sea ice strength and therefore in the potential loads the ice can exert on ships, ports, bridges, and offshore structures. The snow layer, while remaining distinct from the sea ice in its physical properties, can become compacted on the ice and contribute to the effective ice thickness and strength. The temperature of sea ice is governed by the atmospheric energy flux balance at the snow surface and the ocean energy flux at the ice base. In addition, snow cover acts as an insulator to sea ice, buffering it against temperature changes due to changes in surface meteorological conditions. The average internal ice temperature and total thickness (through its impact on ice salinity and brine volume) significantly affect ice strength parameters used in the calculation of loads on engineered structures. In February 2017–2019, three field campaigns were carried out on the land-fast ice on Pistolet Bay, north of St. Anthony, Newfoundland in Atlantic Canada. For approximately five days in 2017 and about four days in 2018–2019, surface air temperatures, wind speeds, and snow and ice temperature profiles were continuously measured. Dew point temperatures were obtained from the North American Regional Reanalysis (NARR) dataset. The datasets from the three field campaigns were used to develop empirical linear regression models of snow and ice surface and depth-mean temperatures as a function of the air temperature alone, and of the air and dew point temperatures and wind speed. In this paper, the meteorological data from the three field campaigns are presented, along with the snow and ice thickness and temperature data. The linear models of snow and ice temperature are presented, tested using the observed field data from the Pistolet Bay campaigns, and compared with results obtained from previously published models of snow and sea ice temperature. The results show that the models of snow and ice temperature as a function of the three meteorological variables are modestly more robust than the models as a function of air temperature alone, with R2 values of up to 0.90. The models presented in this paper have potential usefulness in improved prediction of site-specific snow/ice temperatures and associated temperature-dependent ice properties, such as strength at sites where gridded weather data or in-situ meteorological measurements are available, but in-situ snow/ice temperature measurements are nonexistent.

A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings

Building air-conditioning and mechanical ventilation (ACMV) systems are responsible for significant energy consumption and yet, dissatisfaction with the thermal environment is prevalent among the occupants, revealing a widespread disparity between energy-efficiency and indoor thermal-comfort in buildings. This paper presents an indoor-climate control framework that bridges this gap between energy and comfort. The framework comprises two main components: a thermal-comfort prediction model, and an optimization algorithm termed as the optimal air temperature (OAT) algorithm; they collectively act as an intelligent mediator between the occupant and the ACMV system. Firstly, the ACMV energy consumption is modelled as a function of air temperature, and three operating frequencies of cooling components using a feedforward neural network. Secondly, the thermal-comfort prediction model predicts the thermal state index (TSI: Cool-Discomfort/Comfort/Warm-Discomfort). Thirdly, depending on the predicted TSI, the OAT algorithm locates the optimal operating state such that Comfort state is achieved using the minimum ACMV energy consumption. Proposed framework exhibits an energy saving potential of 36.5%. It is found that 25 °C is the ideal air temperature for desired comfort with minimum energy expense in the tropical buildings. Additionally, six different TSI predictive models including two general and four personal comfort models are implemented to validate the framework. The study is substantiated with extensive real human experiments in controlled thermal environment. The proposed method is scalable for its applicability with any comfort-prediction model, and adaptive for its data-driven architecture. It exhibits the potential to achieve both occupant-comfort and energy-saving through integration with the Internet-of-Things for realizing comfort-energy balanced buildings.