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Journal articles on the topic 'Humidity'

To see the other types of publications on this topic, follow the link: Humidity.

Author: Grafiati

Published: 4 June 2021

Last updated: 31 July 2024

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1

Purnama, Prasanti Mia, Nadia Fadila, Najmi Fajrin Baharsyah, Ulya Farahnas, and Mauilal Hasanah. "Prediksi Parameter Kelembapan Udara Berdasarkan Data Penyinaran Matahari Menggunakan Metode Aproksimasi Kuadrat Terkecil." Zeta - Math Journal 8, no. 2 (July 25, 2023): 60–65. http://dx.doi.org/10.31102/zeta.2023.8.2.60-65.

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Humidity is the measure, generally expressed as a percentage, of water vapor that presents in the air. Each place has different percentage of humidity. It happens since humidity is affected by solar radiation intensity. In this study, the percentage of relative humidity is being predicted by applying least square method and Gauss elimination. The data used in this research is the data of relative humiditity and solar radiation intensity during 2018 until 2022 which have been collected by Trunojoyo Stationary of Meteorology. The result shows that the approximation function generated by linear square method is powerful enough in order to predict the relative humidty, based on the relatively small error accumulated.

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2

Jain, Rajeev Kumar, Archa Sharma, Jaya Lalwani, Deepti Chaurasia, and Nagaraj Perumal. "Impact of relative humidity on SARS-CoV-2 RNA extraction using Nextractor automated extraction system." Journal of Biological Methods 11, no. 2 (July 4, 2024): e99010012. http://dx.doi.org/10.14440/jbm.2024.0001.

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This study investigated the influence of relative humidity (RH) on the efficiency of SARS-CoV-2 RNA extraction using the Nextractor automated system. Experiments employing clinical samples demonstrated satisfactory sensitivity and reproducibility for RNA extraction at low humidity (below 50% RH). Conversely, extractions at high humidity (above 70% RH) resulted in complete failure of reverse transcription-polymerase chain reaction assays, with neither SARS-CoV-2 RNA nor the human RNase P gene (internal control) detected. Analysis suggested that residual ethanol, incompletely evaporating due to high humidity, acted as a potent polymerase chain reaction inhibitor in these samples. These findings highlighted the importance of maintaining optimal laboratory humidity (<50% RH) for reliable SARS-CoV-2 RNA extraction using the Nextractor system. Furthermore, laboratories should implement strategies such as regular humidity monitoring, staff training on humidity’s impact, and system validation under specific humidity conditions to ensure accurate molecular diagnostic workflows for COVID-19 testing.

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3

Hendarti, R., J. Linggarjati, JC Kurnia, and R. Arkan Hanan H. "Influence of humidity on the performance of floating photovoltaic systems over ponds in a tropical urban environment." IOP Conference Series: Earth and Environmental Science 1375, no. 1 (July 1, 2024): 012015. http://dx.doi.org/10.1088/1755-1315/1375/1/012015.

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Abstract Floating solar photovoltaics (FPV) are increasingly favored for solar energy harnessing, necessitating a thorough grasp of performance-influencing factors, notably weather conditions. This study delves into the statistical scrutiny of humidity’s impact on FPV performance within tropical settings, focusing on Jakarta’s urban context. While humidity’s effect on solar cell performance, particularly voltage output, is acknowledged, its influence in urban pond settings remains underexplored. Thus, an experiment was conducted, placing a floating PV system over a 24 m2 pond to directly assess humidity’s impact. Additionally, ambient temperature and irradiance levels were analyzed to comprehensively understand their interconnected effects on system efficiency. Moreover, the study investigated airflow’s role in humidity variation and overall environmental dynamics. The experimental setup comprised two strategically positioned solar panels over a 1.5-meter-deep pond. Regression and analysis of variance (ANOVA) techniques were employed to scrutinize humidity’s impact on the FPV system. Results revealed an inverse relationship between humidity and voltage, with humidity also contributing to ambient temperature reduction, thereby enhancing the microclimate. These findings underscore the intricate interplay of factors, where humidity, driven by evaporation, negatively influences irradiance levels while indirectly benefiting PV cell temperature by lowering ambient temperature. This research provides crucial insights for optimizing FPV performance in tropical urban settings, emphasizing the importance of nuanced approaches that account for humidity’s impact on floating photovoltaic systems.

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4

Raven, Ann. "High Humidity." Harrington Lesbian Fiction Quarterly 1, no. 2 (August 16, 2000): 143–44. http://dx.doi.org/10.1300/j161v01n02_14.

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5

Regtien, Paul P. L. "Humidity sensors." Measurement Science and Technology 23, no. 1 (December 5, 2011): 010103. http://dx.doi.org/10.1088/0957-0233/23/1/010103.

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6

Martin, R. Bruce. "Relative Humidity." Journal of Chemical Education 76, no. 8 (August 1999): 1081. http://dx.doi.org/10.1021/ed076p1081.

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7

Fidler, Heidi L. "Incubator Humidity." Advances in Neonatal Care 11, no. 3 (June 2011): 197–99. http://dx.doi.org/10.1097/anc.0b013e31821d0074.

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8

Kulwicki, Bernard M. "Humidity Sensors." Journal of the American Ceramic Society 74, no. 4 (April 1991): 697–708. http://dx.doi.org/10.1111/j.1151-2916.1991.tb06911.x.

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9

Gierens, K., and K. Eleftheratos. "Upper-tropospheric humidity changes under constant relative humidity." Atmospheric Chemistry and Physics Discussions 15, no. 20 (October 29, 2015): 29497–521. http://dx.doi.org/10.5194/acpd-15-29497-2015.

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Abstract. Theoretical derivations are given on the change of upper-tropospheric humidity (UTH) in a warming climate. Considered view is that the atmosphere, getting moister with increasing temperatures, will retain a constant relative humidity. In the present study we show that the upper-tropospheric humidity, a weighted mean over a relative humidity profile, will change in spite of constant relative humidity. The simple reason for this is that the weighting function, that defines UTH, changes in a moister atmosphere. Through analytical calculations using observations and through radiative transfer calculations we demonstrate that two quantities that define the weighting function of UTH can change: the water vapour scale height and the peak emission altitude. Applying these changes to real profiles of relative humidity shows that absolute UTH changes typically do not exceed 1 %. If larger changes would be observed they would be an indication of climatological changes of relative humidity. As such, an increase in UTH between 1980 and 2009 in the northern midlatitudes as shown by earlier studies using HIRS data, may be an indication of an increase in relative humidity as well.

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10

Gierens, Klaus, and Kostas Eleftheratos. "Upper tropospheric humidity changes under constant relative humidity." Atmospheric Chemistry and Physics 16, no. 6 (March 30, 2016): 4159–69. http://dx.doi.org/10.5194/acp-16-4159-2016.

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Abstract. Theoretical derivations are given on the change of upper tropospheric humidity (UTH) in a warming climate. The considered view is that the atmosphere, which is getting moister with increasing temperatures, will retain a constant relative humidity. In the present study, we show that the upper tropospheric humidity, a weighted mean over a relative humidity profile, will change in spite of constant relative humidity. The simple reason for this is that the weighting function that defines UTH changes in a moister atmosphere. Through analytical calculations using observations and through radiative transfer calculations, we demonstrate that two quantities that define the weighting function of UTH can change: the water vapour scale height and the peak emission altitude. Applying these changes to real profiles of relative humidity shows that absolute UTH changes typically do not exceed 1 %. If larger changes would be observed they would be an indication of climatological changes of relative humidity. As such, an increase in UTH between 1980 and 2009 in the northern midlatitudes, as shown by earlier studies using the High-resolution Infrared Radiation Sounder (HIRS) data, may be an indication of an increase in relative humidity as well.

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11

Liedberg, H. G., M. R. Mnguni, and D. Jonker. "A Simple Humidity Generator for Relative Humidity Calibrations." International Journal of Thermophysics 29, no. 5 (May 21, 2008): 1660–67. http://dx.doi.org/10.1007/s10765-008-0423-z.

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12

Rouadi, Philip, Fuad M. Baroody, David Abbott, Edward Naureckas, Julian Solway, and Robert M. Naclerio. "A technique to measure the ability of the human nose to warm and humidify air." Journal of Applied Physiology 87, no. 1 (July 1, 1999): 400–406. http://dx.doi.org/10.1152/jappl.1999.87.1.400.

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To assess the ability of the nose to warm and humidify inhaled air, we developed a nasopharyngeal probe and measured the temperature and humidity of air exiting the nasal cavity. We delivered cold, dry air (19–1°C, <10% relative humidity) or hot, humid air (37°C, >90% relative humidity) to the nose via a nasal mask at flow rates of 5, 10, and 20 l/min. We used a water gradient across the nose (water content in nasopharynx minus water content of delivered air) to assess nasal function. We studied the characteristics of nasal air conditioning in 22 asymptomatic, seasonally allergic subjects (out of their allergy season) and 11 nonallergic normal subjects. Inhalation of hot, humid air at increasingly higher flow rates had little effect on both the relative humidity and the temperature of air in the nasopharynx. In both groups, increasing the flow of cold, dry air lowered both the temperature and the water content of the inspired air measured in the nasopharynx, although the relative humidity remained at 100%. Water gradient values obtained during cold dry air challenges on separate days showed reproducibility in both allergic and nonallergic subjects. After exposure to cold, dry air, the water gradient was significantly lower in allergic than in nonallergic subjects (1,430 ± 45 vs. 1,718 ± 141 mg; P = 0.02), suggesting an impairment in their ability to warm and humidify inhaled air.

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13

Heneman, P. "Change in humidity of solid biofuels." Research in Agricultural Engineering 50, No. 2 (February 8, 2012): 61–65. http://dx.doi.org/10.17221/4928-rae.

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Humidity, as one of the most important physical properties of pressed solid biofuels, affects thel calorific value of the biofuel and its consistency. Biofuel humidity depends on the initial humidity of raw material, which varies and depends on many factors. Method of manufacture and place and duration of storage have a considerable effect on solid biofuel humidity as well. Humidity of pressed solid biofuels changes not only during the pressing itself, when temperature increases by compression and a part of contained moisture evaporates, but also in the course of handling and storage under unstable environment conditions with high relative air humidity, when, on the contrary, their humidity gradually increases due to their hygroscopicity. Properties of solid biofuels change with their increasing humidity – their calorific value and consistency decreasing and the share of crumbles increasing.

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14

Chowdhury, Mashfiqul Huq, Somaresh Mondal, and Jobaidul Islam. "MODELING AND FORECASTING HUMIDITY IN BANGLADESH: BOX-JENKINS APPROACH." International Journal of Research -GRANTHAALAYAH 6, no. 4 (April 30, 2018): 50–60. http://dx.doi.org/10.29121/granthaalayah.v6.i4.2018.1475.

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Humidity (atmospheric moisture) is an important atmospheric component and has significant influence on plant growth and development. The rate of growth and the form that a plant attains is controlled by humidity. The present study is an attempt to analyze the seasonal humidity’s of Bangladesh by employing appropriate statistical techniques. The main objective of this study is to examine humidity over time in Bangladesh and find a suitable model for forecasting. This study utilizes humidity data from Bangladesh Meteorological Department (BMD), recorded at 6 divisional meteorological stations for the period of 1976 to 2015. This study found that annual average humidity of Bangladesh is 78.88%. Initially data set is checked for whether it is stationary or not through Augmented Dickey Fuller test. Data was found non-stationary but it was transformed to stationary after taking first difference. Then seasonal ARIMA model was built using Box and Jenkins approach. After examining of all diagnostic procedures, ARIMA (2,0,1)(2,1,1)12 model has been identified as an appropriate model for forecasting 60 months (2016-2020) seasonal humidity.

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15

Majewski, Jacek. "Low Humidity Characteristics of Polymer-Based Capacitive Humidity Sensors." Metrology and Measurement Systems 24, no. 4 (December 20, 2017): 607–16. http://dx.doi.org/10.1515/mms-2017-0048.

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AbstractPolymer-based capacitive humidity sensors emerged around 40 years ago; nevertheless, they currently constitute large part of sensors’ market within a range of medium (climatic and industrial) humidity 20−80%RH due to their linearity, stability and cost-effectiveness. However, for low humidity values (0−20%RH) that type of sensor exhibits increasingly nonlinear characteristics with decreasing of humidity values. This paper presents the results of some experimental trials of CMOS polymer-based capacitive humidity sensors, as well as of modelling the behaviour of that type of sensor. A logarithmic functional relationship between the relative humidity and the change of sensor output value at low humidity is suggested.

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16

Gabor, Richard. "High Humidity, Low Humidity, and Mist Therapy for Croup." JAMA 296, no. 4 (July 26, 2006): 393. http://dx.doi.org/10.1001/jama.296.4.393-b.

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17

Rubin, Yoav, Dorita Rostkier-Edelstein, Christian Chwala, and Pinhas Alpert. "Challenges in Diurnal Humidity Analysis from Cellular Microwave Links (CML) over Germany." Remote Sensing 14, no. 10 (May 12, 2022): 2353. http://dx.doi.org/10.3390/rs14102353.

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Near-surface humidity is a crucial variable in many atmospheric processes, mostly related to the development of clouds and rain. The humidity at the height of a few tens of meters above ground level is highly influenced by surface characteristics. Measuring the near-surface humidity at high resolution, where most of the humidity’s sinks and sources are found, is a challenging task using classical tools. A novel approach for measuring the humidity is based on commercial microwave links (CML), which provide a large part of the cellular networks backhaul. This study focuses on employing humidity measurements with high spatio–temporal resolution in Germany. One major goal is to assess the errors and the environmental influence by comparing the CML-derived humidity to in-situ humidity measurements at weather stations and reanalysis (COSMO-Rea6) products. The method of retrieving humidity from the CML has been improved as compared to previous studies due to the use of new data at high temporal resolution. The results show a similar correlation on average and generally good agreement between both the CML retrievals and the reanalysis, and 32 weather stations near Siegen, West Germany (CML—0.84, Rea6—0.85). Higher correlations are observed for CML-derived humidity during the daytime (0.85), especially between 9–17 LT (0.87) and a maximum at 12 LT (0.90). During the night, the correlations are lower on average (0.81), with a minimum at 3 LT (0.74). These results are discussed with attention to the diurnal boundary layer (BL) height variation which has a strong effect on the BL humidity temporal profile. Further metrics including root mean square errors, mean values and standard deviations, were also calculated.

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18

Huang, Zhi Huang, Jun Lin, and Dan Lv. "High-Precision Monitoring and Controlling System of Temperature and Humidity Based on CAN Bus." Applied Mechanics and Materials 148-149 (December 2011): 1280–84. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.1280.

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The design principles and implementation of a high-precision temperature and humidity’s monitoring and controlling system is introduced in this paper. The data acquisition and transmission of temperature and humidity node in distributed network is realized by the effective use of high-precision temperature and humidity sensor and CAN-bus. Then the principle experiments are carried out, which indicates that the system overcomes the shortcomings of the traditional temperature and humidity monitoring system, such like low transmission rate and poor real-time service, improve the accuracy of the system acquisition and meets increasingly stringent project monitoring and control applications.

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19

Skupin, A., A. Ansmann, R. Engelmann, P. Seifert, and T. Müller. "Four-year long-path monitoring of ambient aerosol extinction at a central European urban site: dependence on relative humidity." Atmospheric Chemistry and Physics Discussions 15, no. 8 (April 29, 2015): 12583–616. http://dx.doi.org/10.5194/acpd-15-12583-2015.

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Abstract. The ambient aerosol particle extinction coefficient is measured with the Spectral Aerosol Extinction Monitoring System (SÆMS) along a 2.84 km horizontal path at 30–50 m height above ground in the urban environment of Leipzig (51.3° N, 12.4° E), Germany, since 2009. The dependence of the particle extinction coefficient (wavelength range from 300–1000 nm) on relative humidity up to almost 100% was investigated. The main results are presented. For the wavelength of 550 nm, the mean extinction enhancement factor was found to be 1.75 ± 0.4 for an increase of relative humidity from 40 to 80%. The respective four-year mean extinction enhancement factor is 2.8 ± 0.6 for a relative-humidty increase from 40 to 95%. A parameterization of the dependency of the urban particle extinction coefficient on relative humidity is presented. A mean hygroscopic exponent of 0.463 for the 2009–2012 period was determined. Based on a backward trajectory cluster analysis, the dependence of several aerosol optical properties for eight air flow regimes was investigated. Large differences were not found indicating that local pollution sources widely control the aerosol conditions over the urban site. The comparison of the SÆMS extinction coefficient statistics with respective statistics from ambient AERONET sun photometer observations yield good agreement. Also, time series of the particle extinction coefficient computed from in-situ-measured dry particle size distributions and humidity-corrected SÆMS extinction values (for 40% relative humidity) were found in good overall consistency, which corroborates the applicability of the developed humidity parameterization scheme. The analysis of the spectral dependence of particle extinction (Ångström exponent) revealed an increase of the 390–881 nm Ångström exponent from, on average, 0.3 (at 30% relative humidity) to 1.3 (at 95% relative humidity) for the four-year period.

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20

Hübert, Thomas. "Humidity-Sensing Materials." MRS Bulletin 24, no. 6 (June 1999): 49–54. http://dx.doi.org/10.1557/s0883769400052519.

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21

Moss, Gerald I., and R. Dalgleish. "HIGH HUMIDITY PROPAGATION." Acta Horticulturae, no. 166 (January 1985): 67–74. http://dx.doi.org/10.17660/actahortic.1985.166.9.

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22

Shakkottai, Parthasarathy, Eug Y. Kwack, and Shakkottai P. Venkate‐Shan. "Acoustic humidity sensor." Journal of the Acoustical Society of America 92, no. 6 (December 1992): 3461. http://dx.doi.org/10.1121/1.405283.

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23

Asakura, H., H. Yamamura, and K. Uchino. "Humidity sensitive actuator." Ferroelectrics 93, no. 1 (May 1989): 205–10. http://dx.doi.org/10.1080/00150198908017347.

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24

Berlicki, T. M., E. Murawski, M. Muszyński, S. J. Osadnik, and E. L. Prociów. "Thermoelement humidity sensor." Sensors and Actuators A: Physical 64, no. 3 (January 1998): 213–17. http://dx.doi.org/10.1016/s0924-4247(97)01626-9.

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25

Green, Joel, and Ian Dyer. "Measurement of humidity." Anaesthesia & Intensive Care Medicine 10, no. 1 (January 2009): 45–47. http://dx.doi.org/10.1016/j.mpaic.2008.11.016.

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26

Dyer, Ian. "Measurement of humidity." Anaesthesia & Intensive Care Medicine 13, no. 3 (March 2012): 121–23. http://dx.doi.org/10.1016/j.mpaic.2011.12.011.

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27

Wilkes, Antony, and David Williams. "Measurement of humidity." Anaesthesia & Intensive Care Medicine 16, no. 3 (March 2015): 128–31. http://dx.doi.org/10.1016/j.mpaic.2014.12.008.

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28

Wilkes, Antony, and David Williams. "Measurement of humidity." Anaesthesia & Intensive Care Medicine 19, no. 4 (April 2018): 198–201. http://dx.doi.org/10.1016/j.mpaic.2018.01.009.

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29

Fehervari, Zoltan. "Humidity and immunity." Nature Immunology 20, no. 7 (June 18, 2019): 776. http://dx.doi.org/10.1038/s41590-019-0434-x.

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30

Agarwal, Manju, and Richard Griffiths. "Measurement of humidity." Anaesthesia & Intensive Care Medicine 7, no. 3 (March 2006): 95–96. http://dx.doi.org/10.1383/anes.2006.7.3.95.

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31

Mukode, S., and H. Futata. "Semiconductive humidity sensor." Sensors and Actuators 16, no. 1-2 (January 1989): 1–11. http://dx.doi.org/10.1016/0250-6874(89)80001-0.

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32

Wong, James. "Feeling the humidity." New Scientist 260, no. 3463 (November 2023): 44. http://dx.doi.org/10.1016/s0262-4079(23)02060-2.

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33

Yang, Yuchuan, Xiuxiu Liang, Ting Hong, and Xin Li. "A humidity compensation method for a temperature and humidity sensor." Journal of Physics: Conference Series 2221, no. 1 (May 1, 2022): 012005. http://dx.doi.org/10.1088/1742-6596/2221/1/012005.

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Abstract This paper introduces the method of humidity compensation in the temperature and humidity sensor to improve the measurement accuracy of humidity. The nonlinearity of humidity and humidity affected by temperature are compensated in circuit and data processing respectively. On the circuit, the sampling principle and the structure of the operational amplifier in the design are introduced. The data processing is mainly polynomial fitting of the chip test data by MATLAB software, so as to improve the humidity measurement accuracy. After the final fitting, the humidity error can reach ±1.5RH in the range of 10 °C to 50 °C.

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34

Yamauchi, Yachiyo, Harumi Morooka, and Hideo Morooka. "Effect of Stimulation Strength of Clothing Humidity on Humidity Sensitivity." FIBER 58, no. 2 (2002): 61–67. http://dx.doi.org/10.2115/fiber.58.61.

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35

SHIMIZU, Yasuhiro, Haruki ICHINOSE, Hiromichi ARAI, and Tetsuro SEIYAMA. "Ceramic humidity sensors. Microstructure and simulation of humidity sensitive characteristics." NIPPON KAGAKU KAISHI, no. 6 (1985): 1270–77. http://dx.doi.org/10.1246/nikkashi.1985.1270.

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36

Li, Bangjun, Lingji Hua, Yaodong Tu, and Ruzhu Wang. "A Full-Solid-State Humidity Pump for Localized Humidity Control." Joule 3, no. 6 (June 2019): 1427–36. http://dx.doi.org/10.1016/j.joule.2019.03.018.

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37

Jeong, Wooseong, Jinkyu Song, Jihoon Bae, Koteeswara Reddy Nandanapalli, and Sungwon Lee. "Breathable Nanomesh Humidity Sensor for Real-Time Skin Humidity Monitoring." ACS Applied Materials & Interfaces 11, no. 47 (November 6, 2019): 44758–63. http://dx.doi.org/10.1021/acsami.9b17584.

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38

Rübner, Katrin, D. Balköse, and E. Robens. "Methods of humidity determination Part II: Determination of material humidity." Journal of Thermal Analysis and Calorimetry 94, no. 3 (December 2008): 675–82. http://dx.doi.org/10.1007/s10973-008-9370-y.

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39

Scolnik, Dennis, Allan L. Coates, Derek Stephens, Zelia Da Silva, Elana Lavine, and Suzanne Schuh. "High Humidity, Low Humidity, and Mist Therapy for Croup—Reply." JAMA 296, no. 4 (July 26, 2006): 393. http://dx.doi.org/10.1001/jama.296.4.394-a.

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40

Lee, Sang-Wook, Young-Suk Lee, and Byung-Il Choi. "Relative Humidity Transducer Proficiency Test for KOLAS Humidity Calibration Laboratories." JOURNAL OF SENSOR SCIENCE AND TECHNOLOGY 32, no. 6 (November 30, 2023): 447–54. http://dx.doi.org/10.46670/jsst.2023.32.6.447.

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41

Abe, Hisashi, and Hiroshi Kitano. "Development of humidity standard in trace-moisture region: Characteristics of humidity generation of diffusion tube humidity generator." Sensors and Actuators A: Physical 128, no. 1 (March 2006): 202–8. http://dx.doi.org/10.1016/j.sna.2005.12.049.

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42

Kim, E. Jin, Ho Kim, and Youn-Hee Lim. "Model selection(absolute humidity and relative humidity) and Akaike's information criterion(AIC): Association between humidity and asthma admission." ISEE Conference Abstracts 2013, no. 1 (September 19, 2013): 4986. http://dx.doi.org/10.1289/isee.2013.p-2-20-16.

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43

Krivosheev, Vladimir Vasilievich, Artem Igorevich Stolyarov, and Aleksandr Aleksandrovich Semenov. "Absolute humidity of atmospheric air and COVID-19." Sanitarnyj vrač (Sanitary Doctor), no. 10 (August 7, 2021): 8–24. http://dx.doi.org/10.33920/med-08-2110-01.

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Today COVID-19 is number one global point of focus. Therefore, study of the effects of environmental conditions, in which exist pandemic subjects — people and viruses, on pandemic dynamics and results is extremely important. The authors made a correlation analysis of dependence between incidence/mortality of population and absolute and relative humidity in 73 countries and regions on different continents of the Earth. The methodology developed defines how and in what periods of time the environmental factors effect on human incidence and mortality, how strongly particular atmospheric parameter affects the process of infection and disease flow. The undertaken calculations allowed to prove that the absolute humidity is one of the dominant natural factor which influences on pandemic COVID-19 and other infectious diseases dynamics. The growth of absolute air humidity can have both positive and negative effect on incidence and mortality of population while the effect’s character depends on absolute humidity’s own level and other atmospheric parameters. Correlation of absolute and relative humidity with incidence/mortality at the same time can be different in value or sign. Existing regulations at the federal level in Russian Federation are established without taking into account the minimum allowable and physiologically optimal value of absolute humidity, and need corrections. The question of the impact of absolute humidity is of great importance for northern territories, where most of the year the value of absolute humidity is less than the minimum allowed. The achieved results show high degree of the impact of absolute humidity on incidence and mortality of population due to COVID-19 and contribute to better understanding of pandemic peaks cyclicality and conscious forecasting of start of periods of the most dangerous epidemiological reality.

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44

Musa, M. Z., M. H. Mamat, N. Vasimalai, I. B. Shameem Banu, N. Parimon, H. Hassan, M. F. Malek, and M. Rusop. "Humidity Sensing Performance of V: TiO2 3D Nanostructure-based Humidity Sensor." IOP Conference Series: Earth and Environmental Science 682, no. 1 (February 1, 2021): 012073. http://dx.doi.org/10.1088/1755-1315/682/1/012073.

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45

Duan, Zaihua, Yadong Jiang, and Huiling Tai. "Recent advances in humidity sensors for human body related humidity detection." Journal of Materials Chemistry C 9, no. 42 (2021): 14963–80. http://dx.doi.org/10.1039/d1tc04180k.

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In this review, we summarized the recent progress in a humidity sensor for human body related humidity detections (including respiratory behavior, speech recognition, skin moisture, non-contact switch, and diaper monitoring).

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46

Yao, Qing Qing, Ning Yu, Peng Fei Xu, Yang Zhou, Feng Zhao, Zhi Wen Hu, and Zhi Qin Peng. "Preparation for Humidity Control Composite Paperboard and their Humidity Control Properties." Applied Mechanics and Materials 310 (February 2013): 71–75. http://dx.doi.org/10.4028/www.scientific.net/amm.310.71.

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The humidity control composite paperboard with excellent humidity control performance was prepared, comprising sodium chloride, anhydrous potassium carbonate, diatomite, pyrrolidone carboxylic acid-Na, carboxymethyl cellulose and self-made humidity control material. The moisture absorption and desorption rate of the sample are about 0.6231 (g/7h•g-1) and 0.5852 (g/7h•g-1), respectively. The equilibrium humidity fluctuates from 52% to 56% and moisture capacity is 31 %. Moreover, it can reach to the equilibrium levels within 60 minutes. Above all, it shows outstanding humidity control properties, meeting the requirement of micro-environment particularly for something sensitive to humidity such as cultural relic.

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47

Fleming, Rex J. "A Note on Temperature and Relative Humidity Corrections for Humidity Sensors." Journal of Atmospheric and Oceanic Technology 15, no. 6 (December 1998): 1511–15. http://dx.doi.org/10.1175/1520-0426(1998)015<1511:anotar>2.0.co;2.

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Li, Yang, Kaicheng Fan, Huitao Ban, and Mujie Yang. "Detection of very low humidity using polyelectrolyte/graphene bilayer humidity sensors." Sensors and Actuators B: Chemical 222 (January 2016): 151–58. http://dx.doi.org/10.1016/j.snb.2015.08.052.

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49

Zhan, Xiancheng, Yingli Wang, Lan Cao, Linli Li, and Chengrong Li. "Determining critical relative humidity by measuring air humidity in equilibrium directly." European Journal of Pharmaceutical Sciences 41, no. 2 (October 2010): 383–87. http://dx.doi.org/10.1016/j.ejps.2010.07.002.

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50

Shimizu, Y., H. Arai, and T. Seiyama. "Theoretical studies on the impedance-humidity characteristics of ceramic humidity sensors." Sensors and Actuators 7, no. 1 (March 1985): 11–22. http://dx.doi.org/10.1016/0250-6874(85)87002-5.

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