Air Temperature Measurements Research Articles

Analysis of Sumatran Earthquake Coulomb Stress Changes in Geothermal Potential in Rianite, Samosir Regency

Increasing energy demand and high world oil prices are making countries turn to geothermal energy use. Indonesia is a country that has geothermal energy due to Indonesia's geographical location and geological conditions, which is located between three active earth plates so that Indonesia has 240 volcanoes and often experiences earthquakes. The 2003-2013 earthquake data obtained are coordinates, magnitude, depth, focal mechanism and all these data are analyzed in the coulomb stress method. Rianiate geothermal measurement data in March 2013 included geothermal location, hotspring and air temperature, pH, and geochemical measurements. The analysis results showed that the highest coulomb stress value was at a depth of 90 km of 0.56 bar while the shear and normal values were 0.452 bar and 0.251 bar. The result of the spread of coulomb stress is to the northeast, east and southeast. Then the results of the analysis of the direction of distribution of coulomb stress are compared to the location of the hotspring based on a decrease in temperature, the change in the potential of hotspring 1 leads to hotspring 2, 3, and 4 in the opposite direction, namely northwest or leads to the largest source of colulomb stress, so that Coulomb Stress Changes affect indirectly changes in the geothermal potential of Rianiate

Automatic correction of barometric altimeters using additional air temperature and humidity measurements

A GPS module is often combined with an atmospheric pressure sensor in onboard navigation systems. Thanks to this, using appropriate algorithms comparing the results obtained from GPS and from the barometric altimeter, it is possible to obtain much more accurate indications of the height above sea level. The authors analyzed the problem of correcting barometric altimeter errors caused by non-standard pressure and temperature conditions at sea level and the presence of water vapor in the air. The authors proposed methods of correcting the altimeter error using additional temperature and air humidity measurements. They also proposed a simple method for calibrating the altimeter prior to the mission to estimate the difference in pressure above the standard value. The paper discusses the influence of water vapor on the accuracy of the altimeter indications and the conditions for the applicability of the error correction method. The authors initially considered the possibility of using the method based on the concept of virtual temperature. However, this method was rejected because simulation studies showed that it did not give satisfactory results. Simulation tests were carried out in the MATLAB environment to assess the effectiveness of the proposed methods. The test results turned out to be satisfactory. They can be useful when designing low-cost navigation systems using simple sensors made in MEMS technology. The main envisaged application is in autonomous drone navigation systems.

The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset

Abstract. The Greenland Climate Network (GC-Net) consists of 31 automatic weather stations (AWSs) at 30 sites across the Greenland Ice Sheet. The first site was initiated in 1990, and the project has operated almost continuously since 1995 under the leadership of the late Konrad Steffen. The GC-Net AWS measured air temperature, relative humidity, wind speed, atmospheric pressure, downward and reflected shortwave irradiance, net radiation, and ice and firn temperatures. The majority of the GC-Net sites were located in the ice sheet accumulation area (17 AWSs), while 11 AWSs were located in the ablation area, and two sites (three AWSs) were located close to the equilibrium line altitude. Additionally, three AWSs of similar design to the GC-Net AWS were installed by Konrad Steffen's team on the Larsen C ice shelf, Antarctica. After more than 3 decades of operation, the GC-Net AWSs are being decommissioned and replaced by new AWSs operated by the Geological Survey of Denmark and Greenland (GEUS). Therefore, making a reassessment of the historical GC-Net AWS data is necessary. We present a full reprocessing of the historical GC-Net AWS dataset with increased attention to the filtering of erroneous measurements, data correction and derivation of additional variables: continuous surface height, instrument heights, surface albedo, turbulent heat fluxes, and 10 m ice and firn temperatures. This new augmented GC-Net level-1 (L1) AWS dataset is now available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2023) and will continue to be refined. The processing scripts, latest data and a data user forum are available at https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing (last access: 30 November 2023). In addition to the AWS data, a comprehensive compilation of valuable metadata is provided: maintenance reports, yearly pictures of the stations and the station positions through time. This unique dataset provides more than 320 station years of high-quality atmospheric data and is available following FAIR (findable, accessible, interoperable, reusable) data and code practices.

Forecasting individual exercise sweat losses from forecast air temperature and energy expenditure.

Recent success in predicting individual sweat losses from air temperature and energy expenditure measurements suggests a potential for forecasting individual sweat losses for future combinations of environment and exercise. The purpose of this study is to determine the plausibility of accurately forecasting exercise sweat losses from meteorological air temperature forecasts and individual running energy expenditure forecasts. The potential impact on plasma sodium is also estimated when setting drinking rates equal to forecast sweat losses. Individual exercise sweat losses (equated to water needs) and energy expended while running were measured in 33 participants along with air temperature and compared with forecasts of the same. Forecast inputs were used in a web app to forecast exercise sweat losses for comparison with observed values. The bias between forecast and observed exercise sweat losses was used to calculate the potential drinking impact on plasma sodium. The concordance correlation coefficient between forecast and observed values was 0.95, 0.96, and 0.91 for air temperature, energy expenditure, and exercise sweat losses, respectively, indicating excellent agreement and no significant differences observed via t-test. Perfect matching of water intake to sweat losses would lower plasma sodium concentrations from 140 to 138 mmol/L; calculations using the 95% limits of agreement for bias showed that drinking according to forecast exercise sweat losses would alter plasma sodium concentrations from 140 to between 136 and 141 mmol/L. The outcomes support the strong potential for accurately forecasting exercise sweat losses from commonly available meteorological air temperature forecasts and energy expenditure from forecast running distance.

Study of the Heavy Metals Concentration Level in the Water and Sediment and some Tissues of the Grass Carp Ctenopharyngodon idella V. Cultured in Cages in the Euphrates River

The current study was conducted in Thi Qar Governorate, Nasiriyah city on one of the private farms, grass carp were cultured, to determine the effect of some heavy elements (cadmium, copper and zinc) in the water and sediments of the Euphrates River, measuring the concentration of elements in some parts (gills, muscles and viscera) of grass carp fish. Water, sediment and fish samples were collected monthly from 11/8/2022 to 4/8/2023. The study also included field tests such as air and water temperature measurements, the air temperature ranged between 11-29 C, and the water temperature ranged between 9-25 C. Heavy metals were measured in water, sediment and fish tissues by flame atomic absorption spectrometer. The results showed the highest total concentration of cadmium in the water during April and copper in February and April, as for zinc, it recorded the highest concentration during April. The highest concentration of cadmium was recorded in the gills and muscles during April. The highest concentration of cadmium in the guts was recorded in the winter. Copper had the highest concentration in the gills and muscles during April. Zinc recorded high concentrations in the viscera, muscles and gills. As for the sediments, the values of cadmium ranged from 0.104-0.223 μg/L. Copper recorded values ranging between 5.07-13.2 μg/L. Zinc values ranged between 29.87-59.2 μg/L. The results showed that the accumulation of heavy elements was as follows: Concentrations in the water of zinc>cadmium>copper. Concentrations in the sediments of zinc> copper>cadmium. In tissues: Cadmium viscera>gills>muscle. gillscopper>viscera>muscles. Viscera>gills>muscles.

Assessing Statistical Indices for Calibrating Building Performance Simulation Models via Continuous Time Series

In engineering planning practice, building simulation is becoming increasingly crucial for evaluating buildings’ energetic and thermal behaviour. The appropriate application in the form of models that represent reality precisely, therefore, faces the challenge of realistic parameter specification for uncertain BES model properties. Many of them can only be restricted to a probable range of values. Additional knowledge can be obtained for the case of available measurement data via inverse modelling. This approach minimises cost function values representing discrepancies between associated time series (measured and simulated data sets). Much research has been published in this field for energy consumption characteristics. These approaches differ in several aspects from measured continuous physical state quantities. This article applies general cost indices to air temperature measurement series. For isolated effects such as time delay and amplitude attenuation, the impact on the characteristic values is examined, and their response is evaluated. This survey leads to the conclusion that there is no single parameter suitable for identifying all effects, and a combination is recommended. A new proposal is made for such a combined statistical index, and exemplary applied for measured temperature curves from a castle near Potsdam.

Realizing the load shifting potential of residential space heating - A field study on the control input for thermostatic control of indoor air temperature

Economic model predictive control (MPC) of residential space heating utilizes indoor air temperature fluctuations and thermal mass for load shifting of space heating consumption and it can be used for various demand response purposes in district heating systems. A field experiment imitating the behaviour of an MPC has previously been carried out in three residential buildings in Aalborg, Denmark. Here, digital radiator thermostats were used, and it was found that the load shifting period was cut short when using the temperature measurement embedded in the thermostat as control input for the MPC. Therefore, the field study reported in this paper investigated whether using indoor air temperature sensors as control input for the thermostat improved the realisation of the load shifting. The field study took place in a single-family house in Aarhus, Denmark, and tested the load shifting potential when controlling with either the temperature sensor embedded in the thermostat or an offset between the radiator thermostat setpoint and an indoor air temperature sensor measurement. The study indicates that the use of indoor air temperature measurements as thermostat control input will provide longer periods of loading and unloading the building, thereby increasing the total load shifting potential of the heating consumption.

Antarctic daily mesoscale air temperature dataset derived from MODIS land and ice surface temperature

Knowledge about local air temperature variations and extremes in Antarctica is of large interest to many polar disciplines such as climatology, glaciology, hydrology, and ecology and it is a key variable to understand climate change. Due to the remote and harsh conditions of Antarctica’s environment, the distribution of air temperature observations from Automatic Weather Stations is notably sparse across the region. Previous studies have shown that satellite-derived land and ice surface temperatures can be used as a suitable proxy for air temperature. Here, we developed a daily near-surface air temperature dataset, AntAir ICE for terrestrial Antarctica and the surrounding ice shelves by modelling air temperature from MODIS skin temperature for the period 2003 to 2021 using a linear model. AntAir ICE has a daily temporal resolution and a gridded spatial resolution of 1 km2. AntAir ICE has a higher accuracy in reproducing in-situ measured air temperature when compared with the well-established climate re-analysis model ERA5 and a higher spatial resolution which highlights its potential for monitoring temperature patterns in Antarctica.

Validation and traceability of miniaturized multi-parameter cluster radiosondes used for atmospheric observations

In this work we designed and developed a cluster of light expendable radiosondes that can float passively inside warm clouds to study their micro-physical processes. This involves the tracking of both saturated and unsaturated turbulent air parcels. The aim of this new kind of observation system is to obtain Lagrangian statistics of the intense turbulence inside warm clouds and of the lower intensity turbulence that is typical of the air surrounding such clouds. Each radiosonde in a cluster includes an electronic board, which is mounted onto a small, biodegradable balloon filled with a mixture of helium and air. The cluster is able to float inside clouds for a few hours and to measure air temperature, pressure, humidity and the associated position, velocity, acceleration and magnetic field readings of each radiosonde along their trajectory.

Greater local cooling effects of trees across globally distributed urban green spaces

Urban green spaces (UGS) are an effective mitigation strategy for urban heat islands (UHIs) through their evapotranspiration and shading effects. Yet, the extent to which local UGS cooling effects vary across different background climates, plant characteristics and urban settings across global cities is not well understood. This study analysed 265 local air temperature (TA) measurements from 58 published studies across globally distributed sites to infer the potential influence of background climate, plant and urban variables among different UGS types (trees, grass, green roofs and walls). We show that trees were more effective at reducing local TA, with reductions 2–3 times greater than grass and green roofs and walls. We use a hierarchical linear mixed effects model to reveal that background climate (mean annual temperature) and plant characteristics (specific leaf area vegetation index) had the greatest influence on cooling effects across UGS types, while urban characteristics did not significantly influence the cooling effects of UGS. Notably, trees dominated the overall local cooling effects across global cities, indicating that greater tree growth in mild climates with lower mean annual temperatures has the greatest mitigation potential against UHIs. Our findings provide insights for urban heat mitigation using UGS interventions, particularly trees across cities worldwide with diverse climatic and environmental conditions and highlight the essential role of trees in creating healthy urban living environments for citizens under extreme weather conditions.

Cold Climate Challenges: Analysis of Heat Recovery Efficiency in Ventilation Systems

As building energy consumption gains ever-increasing attention worldwide, the focus on addressing it through the examination and optimization of efficient heat recovery solutions continues to intensify. With well-insulated and airtight buildings, the proportion of heating needs attributed to ventilation is growing, leading to the widespread integration and optimization of heat recovery solutions in mechanical ventilation systems. Heat recovery in ventilation is a highly efficient strategy for reducing heat losses and conserving energy. This study involves the investigation of a ventilation unit installed in an apartment situated in Riga, Latvia, as a practical examination of heat recovery system efficiency within the Latvian climate conditions, representing a cold climate region. The objective of this study was to examine the heat recovery efficiency of the ventilation system in the Latvian climate with variable outdoor and exhaust air parameters, given that the dry heat recovery efficiency is different from the actual heat recovery efficiency. The ventilation unit was equipped with a plate heat exchanger at an airflow rate of 105 m3/h. To evaluate heat recovery efficiency, extensive measurements of air temperature and relative humidity were conducted. The collected data was analyzed, employing statistical regression analysis to ensure measurement reliability and assess correlations. The findings indicated a strong correlation between variables such as heat content, moisture content, and sensible air parameters. It was observed that the actual heat recovery efficiency was 6% higher than the calculated dry efficiency, emphasizing the importance of considering real-world conditions in heat recovery assessments. Additionally, regression analysis demonstrated a positive linear correlation with a coefficient of 0.77, highlighting the dependency between actual measurements and the theoretical model. These quantitative outcomes provide essential insights for optimizing heat recovery systems and enhancing energy-efficient ventilation practices, especially in cold climate environments. Moreover, this study highlights the strong correlation between variables such as heat content, moisture content, and sensible air parameters. Findings offer essential insights for optimizing heat recovery systems and enhancing energy-efficient ventilation practices, especially in cold climate environments.

Outdoor micro-climate: Air temperature measurements around an office building in Denmark during summer

The outdoor micro-climate caused by the presence of buildings can significantly differ from that around weather stations located outside of urban areas. However, the latter is often used to design buildings and size building systems. This could lead to significant mistakes and performance gaps. To date, there is a certain lack of experimental studies assessing the micro-climate around buildings, especially in Scandinavian countries. The current paper presents the preliminary results and analysis of a measurement campaign of the temperature gradient in the two-meter air layer around the envelope of a multi-storey office building in Denmark in the summertime. Depending on the orientation of the external building surface (South/North façade or rooftop), the distance from the latter and the weather conditions, the temperature in this two-meter air layer can vary significantly and differ from the air temperature measured at nearby open fields or recorded by the reference weather station. During sunny days, a temperature gradient of up to 3.4 °C and 13.6 °C was measured in the air layer around the South façade and the rooftop, respectively. These results could help to validate urban climate models and bridge the gap between building design and real-condition performance. The curated dataset of this measurement campaign is available in open access.

Investigation of personal air pollution exposures and occupants’ fresh air demands in two office buildings in Switzerland

This study assessed personal exposures to indoor air pollutants in office environments with dynamic occupancy profiles. A two-week field campaign was conducted in two Swiss office buildings, examining three target areas in each building. We measured air temperature (T), relative humidity (RH), CO2, PM2.5, and PM10 levels at three stationary locations of each target area. Four office workers carried a customized vest to monitor personal CO2 and PM levels near their breathing zone. Using smartwatches, the workers completed hourly surveys about their activity profiles and preferences for outdoor air. We found that CO2 and PM10 concentrations were 1.2–1.3x and 1.8–2.5x higher, respectively, in the personal monitor compared to stationary sensors. Occupants had higher personal CO2 levels during sitting activity and higher personal PM levels during standing activity. Lunch/coffee/call activities were associated with discernible peaks of personal exposure to CO2, PM2.5, and PM10. The higher T coupled with lower RH measured at the personal level was associated with higher occupant demands for outdoor air.

Making an air-source heat pump smart-grid ready

In this paper we discuss the differences between the industrial and academic definition of smart-grid readiness of heat pumps and investigate possibilities to bridge this gap such that existing heat pumps, to a higher degree, can participate in a smart-grid or flexibility setting. A weather compensated heat pump has been equipped to enable heating reference tracking by overriding the outdoor air temperature measurement. The reference tracking has been performed using a model predictive controller and a PI-controller. The results show that it is possible to track a heating reference but also that operating the heat pump according to smart-grid objectives has consequences, such as reduced COP and increased defrosting rate. The model predictive and PI-controller showed little difference in performance, meaning that even simple rule-based controllers can be used for tracking. Lastly, the paper provides suggestions for signals that should be available if heat pumps in the future should operate closer to the researchers’ expectations of smart-grid readiness.

Smart Garden System Based on Internet of Things using NodeMCU ESP8266

Gardening is an agricultural sector that requires control and monitoring of work. However, the management and monitoring are still done manually. Therefore, we developed an internet of the things-based smart garden to monitor and control plants. This study aims to determine the design and performance of the system. This research is a type of engineering research. The measurement technique is to measure directly by comparing air humidity, air temperature, soil moisture, and soil temperature with the standard tool. The indirect measurement is by analyzing the value of accuracy and precision of the instrument. The system uses a DHT11 sensor measuring air temperature and humidity, a soil moisture sensor, and a DS18B20 sensor to measure soil temperature. The device has nearly 100% accuracy in all parameters, especially in the range of 93.53% to 98.61%. Precision for all parameters of the selected devices is also close to 100% in the range of 98.6% to 99.8%. Based on these results, the design of the smart garden tool can work well

Indoor air temperature and relative humidity measurements in Finnish schools and day-care centres

Indoor air temperature and relative humidity measurements of schools and day-care centres in two research projects on indoor air conditions in municipal buildings with mechanical ventilation in Finland were combined for a large sample of occupied spaces with typical conditions experienced by users of the buildings. In addition to user experience, the occupied spaces represented the spaces with determining air humidity load when assessing moisture performance of envelope structures. Indoor air temperature was stable excluding extreme external conditions that caused crossings of limit values. Permanence within limit values of the Finnish Classification of Indoor Environment was inadequate leaving all buildings in the lowest classification level S3. Mechanical ventilation in municipal buildings is designed to keep pollutants at moderate level during high occupancy which results in non-existent indoor air moisture excess, which during winter leads to low indoor air relative humidity. Although dry indoor air provides safety of envelope structures, the drawback is poor performance with regards to the recommended range. Dry indoor air has negative effects on the indoor air quality experienced by the users, causing skin and eye irritation.

Modified shape coefficient of building with Thermal considerations: concept, experiment and Application in solar-enriched areas

ABSTRACT The shape coefficient of building (SCB) characterizes the correlation between building shape and building energy consumption. Strictly restricting the SCB was harmful to reducing energy consumption, neglecting the potential benefits of solar radiation. A novel concept and determining method of modified shape coefficient of building (MSCB) were proposed based on the energy dissipating and solar heat gain. Field measurements of the indoor air temperature of model buildings for solar radiation, building orientations, and U-values under natural and heating conditions were conducted in western Sichuan. Results demonstrated that with identical SCB, the indoor thermal environment was substantially affected by the above parameters, proving the one-sidedness of SCB simultaneously. A simulation method verified via the experiments was employed to forecast the dynamic heating load of a real building. The influence of building orientations on the MSCB under actual climatic conditions from different time scales was discussed. Results illustrated that the SCB could be reduced by 34.6% in the present case. The monthly correction factor trend and the heat consumption were consistent. The restriction on SCB could be liberalized moderately even if the heating demand was tremendous. This research could provide a reference for the energy-saving design of passive buildings.

Spatial development indicators as a tool to determine thermal conditions in an urban environment

In the face of climate change and the growing frequency of thermally burdensome conditions, urban morphology and city planning are becoming increasingly important to human health. Architects and policymakers use various tools, including spatial development indicators describing the characteristics of built-up areas, to mitigate urban climate. This study purposed to (1) indicate which widely used spatial development indicators most adequately explained the thermal conditions of the environment, and (2) investigate how large an area most accurately represents the thermal features recorded at a given air temperature measurement site. Selected indexes were used to characterize each of the 21 measuring sites located in Warsaw. First, five spatial development indicators were calculated for three distances from each site. Then, based on data from the air temperature monitoring network, 17 selected thermal characteristics were calculated. The results of the analyses indicated that the Ratio of Biologically Vital Area has the highest impact on the thermal regime with particularly strong influence on the lowest daily temperature values. The paper proves that the thermal conditions of a given location in the diverse space of a city are more precisely represented by a large area than by its nearest surroundings.

Estimasi Sensor Temperatur Udara Automatic Weather Station Menggunakan Algoritma Hybrid Arima-MLP

Abstract
 Air temperature sensor is installed in an enclosure with a relative humidity sensor at a height of 1.25 meters from the ground. This sensor is routinely calibrated every year through a field comparison mechanism using standard portable. However, air temperature sensor has potential to experience troubles due to technical or non-technical factors. Estimation of temperature data can overcome loss data. This study aims to design an estimation model for air temperature sensor data using the ARIMA-MLP hybrid algorithm. Estimated air temperature sensor is focused on AWS Cisurupan in Garut Regency, West Java on 2019. The estimated data has an interval of 10 minutes. Outlier detection uses range check and step check methods. Missing data imputation method utilizes multiple linear regression-based interpolation. ARIMA-MLP hybrid algorithm is able to detect elements of linearity and nonlinearity of air temperature measurements. This algorithm meets WMO requirements regarding air temperature measurements, if training data is used with a minimum percentage of 85% of the entire modeling dataset. The resulting RMSE value is less than 0.20C.
 Keywords: air temperature, Automatic Weather Station, hybrid ARIMA-MLP

Experimental Investigation of Solar Air Heater with Energy Storage Unit

The present study investigates a single-pass solar air collector (SAC) linked to a thermal energy storage unit. This system is designed to store energy by using a cement mortar molds storage bed during daylight hours and subsequently reutilize it at night. A solar collector was used in this research, which was consecutively connected to the cement mortar molds bed. High-density cement mortar molds (570 kg) were used as a storage medium. The experiments were conducted on clear days for two random days at a constant airflow rate (0.0217 kg/s) for the climate of Mosul City, Iraq. The study assessed the parameters influencing the thermal performance of the SAC integrated with the cement mortar molds storage bed. Measurements of solar radiation intensity and air temperatures at various locations were recorded. The data indicated that the cement mortar molds storage bed achieved a temperature difference of approximately 10? post-sunset, with this difference sustained for 4-5 hours. The cement mortar molds bed demonstrated the capability to retain heat for an extended post-sunset, releasing it during nighttime.