Relative Humidity Measurements Research Articles

Evaluating the effects of different tree species on enhancing outdoor thermal comfort in a post-industrial landscape

A frequently emphasized strategy to reduce the burden of heat in cities across the world is the implementation of street trees. Here, we examine the effects of deciduous and coniferous tree deployment on meteorological variables and pedestrian thermal comfort through analysis of the new dynamic thermal comfort (dPET) index, using the latest version of the computational fluid dynamics model ENVI-met. We performed on site observational measurements of air temperature (Ta), relative humidity (Rh), wind speed (Ws), and mean radiant temperature (MRT) at five different locations on the hottest day of summer 2023, in a post-industrial urban landscape located in Tehran, Iran. Observations were used to evaluate ENVI-met simulation performance and served as a baseline against which sensitivity experiments—based on a minimum (35%) and maximum (75%) intervention scenario for deciduous and coniferous trees—were compared against. Our analysis indicates that 35% and 75% deployment reduced Ta by 1.2 °C and 4.2 °C, respectively, for deciduous tree species, compared to a 0.9 °C and 3.1 °C reduction for coniferous species, during the hottest day of summer 2023. The maximum deployment scenario decreased MRT by approximately 60 °C and 43 °C for deciduous and coniferous tree deployment, respectively. The maximum tree deployment scenario decreased dPET by nearly 16 °C and 14 °C for deciduous and coniferous trees, respectively, during the time of day that diurnal heating is maximized. Our findings highlight micrometeorological and personalized thermal comfort effects associated with variable tree species type and extent through examination of a pedestrian’s ambulatory experience across diverse urban microclimates in a region of the world that is particularly understudied.

Humidity Sensing Using a Multimode Fiber Ring Laser with Thermal Compensation

We propose a multimode fiber laser sensor utilizing PI-SMF (polyimide-coated single mode fiber) for low-error relative humidity (RH) measurement, which is temperature compensated based on FBG. The PI-SMF in the laser cavity is used as a sensing element, and its length varies with humidity and temperature by volume-variation induced strain, which leads to frequency shift of the longitudinal mode beat frequency signal (BFS). When the 2000 MHz BFS is selected as the sensing signal, a RH sensitivity of −2.68 kHz/%RH and a temperature sensitivity of −14.05 kHz/°C are achieved. The peak shift of the FBG-based laser emission spectrum is only sensitive to temperature rather than RH with a temperature sensitivity of 9.95 pm/°C, which is used as the temperature compensation for RH measurements. By monitoring the response of the BFS and the laser wavelength, the cross-sensitivity effect of RH and temperature is overcome, and low-error RH measurement in the temperature range of 20 to 65 °C is realized with errors within ±0.67 %RH (25 to 85 %RH). The scheme does not require the design and production of complex structures and hygroscopic material coating processes, owning the advantages of simple structure, easy operation and high accuracy, and is expected to be practically applied in food safety and environmental monitoring.

High sensitivity humidity sensor based on the U-shaped tapered no-core fiber coated with MXene

Ti3C2Tx MXene is an emerging two-dimensional material that has good potential in relative humidity (RH) measurement because of its unique layer structure, strong hydrophilic nature, and large specific surface area. Here, a high-performance RH sensor integrating Ti3C2TX MXene nanosheets and U-shaped tapered no-core fiber (UTNCF) is proposed. The sensing principle is based on mode interference. The change of ambient RH leads to the change of the refractive index (RI) of Ti3C2Tx MXene, which eventually leads to the shift of the transmission spectrum of the sensing probe. The average sensitivity is 1.11 nm/%RH in the RH range of 45% to 80%, and the response time is 25 ms. The proposed micro-nano fiber RH sensor has the advantages of high sensitivity, fast response, good repeatability, and stability. In addition, the proposed sensor has a broad application prospect in human respiratory monitoring, industrial and agricultural production, and environmental monitoring.

The Cloud Indicator: A novel algorithm for automatic detection and classification of clouds using airborne in situ observations

Airborne in situ observations of aerosols and clouds provide relevant data sets crucial to improving the understanding of cloud microphysical processes and reducing uncertainties connected to future climate predictions. However, the selection and classification of cloud sequences in such data sets can be very time-consuming if done manually, and criteria used by the community are numerous and prone to misclassification, especially when coarse aerosol particles (> 1 μm diameter) are present.In this study, we present the Cloud Indicator, a novel algorithm that automatically detects and classifies measurement periods inside clouds. The Cloud Indicator was developed using data from three international airborne field campaigns, including ATom (Atmospheric Tomography; 2016–2018), A-LIFE (Absorbing aerosol layers in a changing climate: aging, lifetime and dynamics; 2017), and FIREX-AQ (Fire Influence on Regional to Global Environments Experiment and Air Quality; 2019). The algorithm utilizes size distribution measurements, combined with measurements of relative humidity and temperature, to automatically detect flight sequences in clouds and classify the cloud type. As an additional criterion for the Cloud Indicator, we established the cloud-aerosol volume factor fCA to ensure a precise and robust distinction between clouds and aerosol layers such as mineral dust or biomass burning thereby reducing misclassifications. The Cloud Indicator algorithm was developed with data from a second-generation Cloud, Aerosol, and Precipitation Spectrometer (CAPS) which was calibrated with a novel calibration procedure – introduced in this study - that results in a refractive index independent calibration and works also in the field. However, the Cloud Indicator algorithm is not restricted specifically to the CAPS and thus allows its application to a variety of in situ instruments that measure coarse aerosol and cloud particle size.Case studies from ATom and A-LIFE demonstrate the ability of the Cloud Indicator to precisely screen (airborne) in situ data sets for clouds. The algorithm separates the data set into cloud-free periods, Aerosol-Cloud Transition Regime (ACTR), liquid clouds, clouds in the Mixed-Phase Temperature Regime (MPTR), and cirrus clouds. The unique ability of the Cloud Indicator to successfully differentiate between layers of enhanced coarse-mode aerosol concentrations and clouds is demonstrated by measurements in a complex mixture of clouds embedded into a mineral dust layer during the A-LIFE. The empirically derived parameter thresholds of the Cloud Indicator are in good agreement with values in the literature.

Relative humidity measurements of a thin-film humidity sensor in condensing conditions in the temperature range from −40 °C to 5 °C

In condensing conditions, metastable states such as supersaturation of water vapour and supercooling of liquid water are commonly observed in the free atmosphere. This study investigates the response of a polymeric thin-film humidity sensor under condensing conditions at various temperatures (−40 °C, −20 °C, −5 °C, and 5 °C) and different relative humidity (RH) levels. To ensure precise control of RH, a saturator-based humidity generator operating in a two-temperature mode is utilized. The condensing conditions are achieved in two ways: by increasing water vapour pressure (WVP) at a fixed temperature and by decreasing the temperature while maintaining a constant WVP. In general, when measuring RH under condensing conditions, the sensor indicates a temporary supersaturation state with an RH peak exceeding 100% before the onset of condensation. Subsequently, the RH value exhibits a delayed decrease when exposed to a non-condensing RH level. The experiments with a constant WVP demonstrate a lower likelihood of ice condensation compared to those with a constant temperature. This study demonstrates the measurement capability and behaviour of thin-film humidity sensors above 100% RH in the supersaturation states that are commonly observed in the free atmosphere at meteorologically-relevant temperatures.

Unlocking Weather Observations at Puerto Madryn-Patagonia, Argentina, 1902–1915

The recovery of early records of maximum, minimum, and mean temperatures; pressure; and relative humidity measurements in Puerto Madryn for the period 1902–1915 is presented. A careful evaluation of the quality of the data was performed using internal coherence, tolerance, and temporal consistency tests. The monthly mean series of all the variables, constructed from daily raw data, were subject to several homogeneity tests, and only discontinuities in pressure and relative humidity were found. The homogenized monthly mean series were compared with the Twentieth Century Reanalysis series in annual and seasonal time steps. In addition, the trends of each variable were assessed using the Mann–Kendall procedure, and correlations between relative humidity and the other variables were examined. The results show a remarkably good agreement between the temperature measurements and reanalysis values with a Spearman correlation coefficient of 0.94. The raw data for minimum and maximum temperatures represent a very good upper and lower bound for the mean temperature values of both observational and reanalysis data. Agreement was found to be lower for relative humidity and pressure with the correlation coefficients being close to 0.6 in both cases. No trends were found for the variables. The correlation analysis of the humidity measurements with the other variables shows an inverse dependence of the temperatures and no relatedness with the pressure values.

Spatial mapping of indoor air quality in a light metro system using the geographic information system method

Abstract It is known that one of the greatest problems of developed countries in the twenty-first century is traffic. For this reason, engineers have searched for alternative solutions to the problem of traffic. One such solution is the construction and utilization of rail systems instead of main roads. From an engineering perspective, rail systems can be divided into three groups: metro, light metro, and tram systems. Light metro systems, which are a form of public transportation, are not directly inside the traffic. Their most important advantages include the fact that they do not release combustion products such as CO, and metro and light metro systems may be considered environmentally friendly based solely on their electricity consumption. In this study, measurements of parameters affecting indoor air quality were made inside light metro cars and in and around light metro stations belonging to the light metro system of the Metropolitan Municipality of Antalya, known as the tourism capital of Turkey. In February and March 2021, when the COVID-19 pandemic was first registered in Turkey, particulate matter (PM), temperature, and relative humidity measurements were made for testing indoor and outside air quality. Moreover, as outside air parameters, outside temperature, outside relative humidity, CO, normalized difference vegetation index, and ultraviolet aerosol index data were obtained from the General Directorate of Meteorology of Turkey. The measurement results were analyzed using the inverse distance weighting method in the geographic information system. Based on the results of the analyses, spatial maps were created for indoor and outside air quality parameters in the light metro system. Using these maps, the effects of passenger density and environmental factors both inside the metro cars and at the metro stations on indoor air quality were identified. In addition, the spread of the SARS-CoV-2 virus in the COVID-19 period was analyzed using spatial maps of the PM0.3 and PM0.5 parameters. It is believed that the results of this study will set an example for further indoor air quality studies worldwide, and this study is unique in that it employed a method that is used particularly in survey and geomatics engineering for analyzing indoor air quality in light metro systems.

Accuracy assessment of ground-based microwave radiometer in the Mount Qomolangma region

Mount Qomolangma, known as the “Roof of the World,” holds significant importance in exploring the vertical characteristics of the atmosphere, providing insights into high-altitude atmospheric features, and improving numerical models for forecasting downstream regions. Ground-based microwave radiometers (GWR) enable continuous profiling of atmospheric conditions in the troposphere, complementing radiosonde and satellite observations. This study explores the performance of the MWP967KV GWR installed at Qomolangma Base Camp by comparison with concurrent radiosonde measurements. The assessment covers GWR's atmospheric radiative brightness temperatures (Tb) detection capability, accuracy of atmospheric parameter retrievals, and uncertainties in atmospheric parameters under different weather conditions. Using MonoRTM to calculate simulated Tb from radiosonde, the results indicate a high precision of GWR's Tb observations, showing a strong correlation (R ≈ 0.99) and a deviation of merely 2.4 K compared to simulated Tb. Moreover, GWR exhibits high reliability in temperature (R ≈ 0.98) and water vapor density (ρv) (R ≈ 0.91) observations, while the accuracy of relative humidity (RH) measurements requires improvement (R ≈ 0.55). The GWR observations are affected by clouds, precipitation, and surrounding Qomolangma mountain ridges, leading to significant uncertainties in atmospheric parameter retrievals between 2000 m to 6000 m above ground level. Additionally, GWR's sensitivity to temperature variations is limited, resulting in missed detections of temperature inversion. Despite these limitations, this study offers crucial insights into meteorological observations at high altitudes using GWR. These findings hold substantial implications for meteorological research and mountaineering activities in high-altitude regions.

Prediction of Air Pollution with Machine Learning Algorithms

Air pollution has become an important problem due to its threats. Air pollutants are in complex interaction with atmosphere and environment. For this reason, it is important to study air pollution issues. In recent years, studies on prediction of air pollutants with machine learning methods have gained momentum. In this study, some air pollutants are predicted with various machine learning algorithms considering meteorological factors. In machine learning phase, a separate study is conducted with various machine learning algorithms (multilayer perceptron neural network, stochastic gradient descent, ridge regression, cross decomposition) considering temperature, relative humidity, wind, pressure and air pollutant measurements of previous hour. Consistencies of these algorithms in estimating pollutant concentrations are compared. Various statistical metrics are used to analyze the consistencies. As a result, the coefficient of determination of all algorithms are found above 0.67, considering the test section. It is found that the coefficient of determination of the multilayer perceptron neural network algorithm provides better results than other algorithms.

An Analysis of Energy Consumption In The Goverment Buildings’ In Indonesian Border

In this research, energy consumption analysis was conducted at the Main building regent’s office of nunukan. The analysis was conducted on the main variables of energy efficiency, namely: measurement of temperature and relative humidity, calculation of Overall Thermal Transfer Value (OTTV) and Roof Thermal Transfer Value (RTTV), calculation of Energy Consumption Intensity (IKE) in air-conditioned and non-air-conditioned rooms as well as an analysis of opportunities to increase the efficiency of energy consumption in the buildings.. Based on the calculation and result of IKE in both buildings, they are still considered in the category of EFFICIENT. However, based on the measurement of temperature and relative humidity, it shows that in both buildings air conditioning is still necessary to achieve the level of thermal comfort, therefore an increase of efficiency in the load is needed to avoid wastage.

Evaluation and Correction of PurpleAir Temperature and Relative Humidity Measurements

The PurpleAir PA-II sensor provides low-cost in situ measurements of meteorological variables including temperature and relative humidity (RH), as well as fine particulate matter (PM2.5) in real time. The sensors have been used in several studies investigating intracity differences in temperature and PM2.5. While the adoption and use of low-cost sensors has many benefits, care must be taken to ensure proper calibration and testing. This is true not only for PM2.5 measurements but also for temperature and RH given the synergistic health impacts from extreme heat and air pollution exposure. Here, we compare continuous temperature and RH measurements from a PA-II sensor to measurements from a Campbell Scientific 107 temperature probe and Vaisala HMP45C RH probe. All three instruments were co-located from December 2021 to June 2023 in Asheville, North Carolina. We found that the PA-II has an overall high temperature bias of 2.6 °C and root mean square error (RMSE) of 2.8 °C. Applying a linear regression correction reduces RMSE to 1.0 °C, while applying the constant 4.4 °C correction suggested by PurpleAir reduces RMSE to only 2.2 °C. Our PA-II RH measurements have a low bias of −17.4% and uncorrected RMSE of 18.5%. A linear regression correction improves the RH RMSE to 4.5%. Applying the constant 4% RH correction suggested by PurpleAir reduces RMSE to only 14.8%. We present new correction factors that differ from those suggested by PurpleAir, which overcorrect the high temperature bias and undercorrect the low RH bias. We also show that our correction factors improve estimates of dewpoint temperature (RMSE of 0.6 °C and 0.9 °C) compared to the corrections suggested by PurpleAir.

Experimental investigation of time-dependent electrical load effects through multipoints in-situ measurement of temperature and relative humidity of PEMFC bipolar plate under transient operation

In this study, multiple micro-relative humidity and temperature (RH/T) sensors were installed in the anode and cathode channels of a proton exchange membrane fuel cell (PEMFC) bipolar plate to simultaneously observe and analyze the variation in RH/T behaviors during transient operation. In order to simulate the acceleration and deceleration process, the electrical load was ramped from 10 to 40 A and then back to 10 A, with time intervals of 0, 2, and 5 s. The data corresponding to different acceleration/deceleration time intervals were compared and analyzed to assess the time-dependent effects of load changes. The analyzed data provide visual information, including the transient voltage response, transient behavior of temperature and water distribution, and evolution of RH/T within PEMFC. The results indicate that the acceleration and deceleration interval times significantly influence the temperature and water distribution within PEMFC during transient operation. Shorter acceleration times lead to more rapid changes in temperature and humidity within the PEMFC active area, resulting in higher transient temperature and water concentration. This finding explains why the output voltage decreases more when the load changes with a short time interval. This research enhances our understanding of transient temperature and water behavior, providing a foundation for further research and development of effective operational strategies and vehicle PEMFC designs.

Development and Testing of a Rocket-Based Sensor for Atmospheric Sensing Using an Unmanned Aerial System.

Measurements of the vertical structure of the lower atmosphere are important to the understanding of air quality. Unmanned Aerial Systems (UASs, drones) can provide low cost, repeatable measurements of the temperature, pressure, and relative humidity. A set of inexpensive sensors controlled with an Arduino microprocessor board were tested on a UAS against a meteorology grade sensor. Two modes of operation for sampling were tested: a forward moving sampler and a vertical ascent sampler. A small particle sensor (Sensiron SPS30) was integrated and was capable of retrieving vertical aerosol distributions during an inversion event. The thermocouple-based temperature probe and the relative humidity measurement on the Bosch BME280 sensor correlated well with the meteorological sensor. The temperature and relative humidity sensors were then deployed on a rocket sounding platform. The rocket sounding system performed well up to a height of 400 m. The inexpensive sensors were found to perform adequately for low-cost development and uses in education and research.

Embedded Wireless Sensor for In Situ Concrete Internal Relative Humidity Monitoring.

The moisture content within the concrete pore network significantly influences the mechanical, thermal, and durability characteristics of concrete structures. This paper introduces a novel fully embedded wireless temperature and relative humidity sensor connected to an automatic acquisition system designed for continuous concrete monitoring. Relative humidity measurements from this new sensor are compared with those obtained by a commercial system based on the borehole method at different depths (2.5 and 4.0 cm) and exposure conditions (oven drying and humid chamber). The results allow for proving that both systems provide consistent internal relative humidity measurements aligned with the exposure conditions and highlight the capability of fully embedded wireless sensors as a practical and reliable alternative to the conventional borehole method. Additionally, the continuous monitoring of the wireless cast-in sensor exhibits reliability during unintended temperature fluctuations, emphasizing the effectiveness of permanently installed sensors in promptly detecting unintended curing variations in real time. The continuous real-time information provided combined with the practicality of these sensors might assist construction managers to improve the quality control of the concrete curing process and shrinkage behavior, and ensure the integrity of concrete surface finishing.

3D hierarchical microcubic morphological composite and its application for Bi-functional Humidity/Pressure sensing in TENG architecture

Harnessing the power of contact electrification, triboelectric nanogenerators (TENGs) are a cutting-edge energy technology, where output performance is greatly influenced by the micro/nano scale architectures of triboelectric layers. We present a study on the development of TENG by introducing an advanced 3D hierarchical microcubic morphological structure prepared by simple solution casting method, employing a renewable material, lignin, in combination with eco-friendly polyvinyl alcohol (PVA) matrix. The strategic incorporation of epichlorohydrin (EPCH) as a crosslinker enhances thermal stability, and crosslinking within the lignin/PVA composite (LPC) film. A remarkable outcome of this integration is the emergence of a 3D hierarchical microcubic structure within the LPC film. This structure, with its intricate 3D arrangement, emerges as the cornerstone that underpins the development of LPC-TENGs devices distinguished by their simple fabrication process, elevated output performance, and multifaceted applications. The LPC-TENG, adorned with its unique 3D hierarchical microcubic architecture, establishes new standards in energy harvesting and sensing capabilities with a maximum output power density of 135.4 mWm−2, a short-circuit current of 6.44 μA, and a maximum output voltage of 65 V (5 times higher than PVA-based TENGs). Additionally, the LPC-TENG showed exceptional performance as a self-powered bifunctional sensing system, providing a steady output voltage range of 0–10 V across various humidity levels (20–90 % RH) and a wide usable pressure range (0–162 kPa) with a low detection limit of 1 kPa. We demonstrated the application of the LPC-TENG in energy harvesting from human walking, enabling simultaneous measurements of environmental relative humidity, pressure, and illumination of 27 commercial LEDs. The unique 3D hierarchical microcubic architecture offers an unparalleled foundation for accommodating overall performance and diverse sensing functionalities.

Indoor Environmental Quality In Preschool Buildings In an Andean City In Ecuador

ABSTRACT Indoor environmental quality has been associated with the health and wellbeing of building occupants; nevertheless, there is limited evidence in this regard for Latin American schools. This research aimed to characterize indoor environmental quality in public and private preschools in an Andean city in Ecuador. Data collection comprised onsite monitoring for the thermal-humidity microclimate of 90 classrooms in 30 preschools in Cuenca-Ecuador (March-August 2018). Infrared thermography and direct observation were applied to determine dampness. Classrooms seemed to be inadequate thermal-humidity microclimates; only a few maintained a comfortable temperature (6%) and relative humidity (11%) throughout the shift. When comparing public and private schools, in private schools, temperatures below the comfort range (61.3% in private schools vs 31.4% in public schools, p<0.001) and relative humidity measures above the comfort range were more frequent (74.3% in private schools vs. 58.6% in public schools, p<0.001). Hollow blocks were the primary construction material in private and public schools. Sixty-four per cent of private schools operated in adaptive, reused buildings, vs 19% in public schools (p<0.05). Infrared thermography confirmed dampness in 26% (n=23) of the classrooms in the covering structures indoors (15% in public vs 33% in private schools, p<0.05). This research reveals the urgent need to develop specific regulations and control mechanisms for building sustainable and healthy environments for preschools in Ecuador.

Fully Distributed Multi-Channel Fiber-Optic Sensor for Simultaneous Relative Humidity and Temperature Measurement with Finer Gauge Length based on Spatial-domain Time-delayed Multiplexing

Fully Distributed Multi-Channel Fiber-Optic Sensor for Simultaneous Relative Humidity and Temperature Measurement with Finer Gauge Length based on Spatial-domain Time-delayed Multiplexing

Determining precipitable water vapour from upper‐air temperature, pressure and geopotential height

AbstractRadiosonde measurements of relative humidity (RH) are the main source of uncertainty in precipitable water vapour (PWV) calculation from pressure, temperature, and RH/dewpoint (PTU) data. This paper presents a formula expressing PWV in terms of pressure and temperature as functions of geopotential height (GPH), thereby allowing the PWV to be determined: (1) without any moisture‐related calculations other than those involved in measuring GPH (in radiosondes with a pressor sensor) or pressure (otherwise); (2) without relying on humidity measurements by using Global Positioning System (GPS)‐based GPH according to the gravity field, provided that pressure is directly measured. The numerical instability associated with random data errors or deviations from hydrostatic equilibrium makes the second approach unfeasible on short time scales, revealing discrepancies between the PTU‐ and GPS‐based GPHs; however, the estimation of long‐term average PWV above a location is not hindered. The estimation of PWV without humidity data was tested using high‐resolution data from 62 upper‐air stations operated by the NOAA National Weather Service. The seasonal mean {DJF, MAM, JJA, SON} PWV from the surface to 300 hPa calculated from PT and GPS data over the period 2016–2018, after rejecting individual estimates inconsistent with the 0%–100% RH range, showed a mean bias error of {−0.1, +0.1, −1.4, −0.9} kg·m−2 relative to the PTU‐based values across the stations, and a RMSE ranging from 2.4 (DJF) to 3.2 (JJA) kg·m−2. By restricting the analysis to observations with above‐average matching between the PTU‐ and GPS‐based GPH, the bias magnitude and RMSE reduced respectively to less than 0.5 and 1 kg·m−2 in all seasons. The results indicate that evaluating the long‐term agreement between the two PWV calculation methods at different sites could be useful in detecting systematic observation errors in GPS radiosonde systems using a pressure sensor.

Electronic Measurement System for IoT Sensors Studying

The paper substantiates the choice of methodology and develops an electronic measuring system that provides opportunities to study the sensors of Internet of Things systems. Based on the analysis of existing methods of building similar systems, we chose an approach and offered a method of ensuring the given level of temperature and humidity in the climate chamber. In particular, the determination of the level of relative humidity for its further regulation is carried out using a reference sensor of relative humidity and temperature. The parameters of the sensor studied by the students are determined based on the measurement of the frequency of the generator built using the NE555 chip. The necessary humidity level in the climatic chamber is maintained by mixing wet and dry air, which flows are regulated by valves of different diameters. The developed electronic measuring system was manufactured, and its experimental testing was carried out. The experimental results of the dependence of the humidity in the climate chamber, measured using the reference sensor DHT22, on the ratio of the areas of the holes in the valves indicate its nonlinearity. At the same time, the dependence of the frequency of generated oscillations and the capacity of the analog capacitive humidity sensor on the relative humidity in the climate chamber is practically linear. According to the results of the experiments we obtained an empirical formula, taken into account when programming the device and intended for further measurements of relative humidity. The main characteristics of the developed electronic measuring system are the relative humidity adjustment range (40–80 %), the temperature change range (20–80 °C), and the time to set the specified humidity level after replacing the valves (6–7 minutes). The electronic measuring system can be used for educational purposes, as well as for solving practical tasks related to the control and regulation of temperature and relative humidity of air in a closed space.

High Energy Physics Applications on Fiber Optic Sensors in Relative Humidity

Our multidisciplinary research group has been conducting studies in recent years on the use of fiber grating-based sensors for relative humidity measurement in the Compact Muon Solenoid (CMS) instrument at CERN in Geneva. In order to monitor low relative humidity (RH) values even in cold temperatures, our multidisciplinary research group has been working to develop near-field fibre optic sensors based on tin dioxide particle layers, in light of the extensive research conducted in the past few years to evaluate the radiation hardness capability of fibre optic technology in high-energy physics settings. Compared to other sensor types, optical fiber sensors provide several advantages. These benefits mostly stem from the characteristics of optical fibers, which include their tiny size, inexpensive, electromagnetic passivity, resistance to high pressure, and resistance to high temperatures. Sensing is the process of measuring variables like temperatures, stress, or angular velocity by examining the characteristics of light. To evaluate the sensors' performance under the circumstances needed for CERN experiments, untried tests in the [0-65] %RH range at various temperatures were conducted. There were other campaigns of progressive irradiation using γ-ionizing radiations. The results obtained show that the suggested technologies have great potential for usage in High Energy Physics (HEP) activities as a reliable and acceptable replacement for commercial hygrometers in the future.