scholarly journals Damp housing and childhood asthma; respiratory effects of indoor air temperature and relative humidity.

1989 ◽  
Vol 43 (1) ◽  
pp. 7-14 ◽  
Author(s):  
D P Strachan ◽  
C H Sanders
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Indoor Air ◽  
Childhood Asthma ◽  
Respiratory Effects

scholarly journals Microbiome in an Office Building Using a Cooling Trench as an Outdoor Air Duct

2019 ◽  
Vol 111 ◽  
pp. 06045
Author(s):  
Mizuki Niimura ◽  
U Yanagi
Keyword(s):  
Relative Humidity ◽  
Energy Saving ◽  
Air Temperature ◽  
Indoor Air ◽  
Principal Coordinate Analysis ◽  
Office Building ◽  
Metagenomic Analysis ◽  
Outdoor Air ◽  
Energy Saving Technique ◽  
Building Cooling

Subterranean temperature at a depth of 10 m is almost equal to the average outdoor air temperature of the same area. Therefore, if a building cooling trench is used as an outdoor air duct, outdoor air can be cooled in summer and warmed in winter. This energy-saving technique is often used in Japan. However, since the relative humidity in a cooling trench is high, microbe numbers tend to increase in summer. The present study sought to characterize the microbiome status in the cooling trench of such an office building in Japan. Specifically, we performed a metagenomic analysis in which we analyzed DNA directly upon collection from the environment, without intervening cultivation. The results showed the presence of bacteria of the genera Pseudomonas, Lactobacillus, Nesterenkonia, Staphylococcus, Deinococcus, Acinetobacter, Enhydorobacter, and Corynebacterium. Bacteria of the genera Nesterenkonia, Deinococcus, Enhydorobacter, and Corynebacterium predominated on the surface of the trench. Notably, bacteria of the genus Nesterenkonia constituted >50% of the organisms on the surface of the downstream end of the cooling trench. Principal coordinate analysis was used to compare bacterial inhabitants of outdoor air, indoor air from 2nd- and 3rdfloor offices, and the region downstream of the cooling trench. The results suggested that the microbiome of air in this cooling trench influenced indoor air within the building.

scholarly journals Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus

2017 ◽  
Vol 41 (3) ◽  
pp. 225-246 ◽  
Author(s):  
Elizabeth Buechler ◽  
Simon Pallin ◽  
Philip Boudreaux ◽  
Michaela Stockdale
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Indoor Air ◽  
Air Conditioning ◽  
Residential Buildings ◽  
The United States ◽  
Climate Data ◽  
Indoor Climate ◽  
Oak Ridge ◽  
Simulation Engine

The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, heating, ventilation, and air-conditioning system performance, and occupant comfort. Therefore, indoor climate data are generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies are influenced by weather, occupant behavior, and internal loads and are generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The purpose of this study was to probabilistically model homes with the simulation engine EnergyPlus to generate indoor climate data that are widely applicable to residential buildings. Monte Carlo methods were used to perform 840,000 simulations on the Oak Ridge National Laboratory supercomputer (Titan) that accounted for stochastic variation in internal loads, air tightness, home size, and thermostat set points. The Effective Moisture Penetration Depth model was used to consider the effects of moisture buffering. The effects of location and building type on indoor climate were analyzed by evaluating six building types and 14 locations across the United States. The average monthly net indoor moisture supply values were calculated for each climate zone, and the distributions of indoor air temperature and relative humidity conditions were compared with ASHRAE 160 and EN 15026 design conditions. The indoor climate data will be incorporated into an online database tool to aid the building community in designing effective heating, ventilation, and air-conditioning systems and moisture durable building envelopes.

scholarly journals Indoor air quality of newly built low-energy preschools – Are chemical emissions reduced in houses with eco-labelled building materials?

2018 ◽  
Vol 28 (4) ◽  
pp. 506-519 ◽  
Author(s):  
Josefin Persson ◽  
Thanh Wang ◽  
Jessika Hagberg
Keyword(s):  
Air Quality ◽  
Relative Humidity ◽  
Indoor Air Quality ◽  
Air Temperature ◽  
Indoor Air ◽  
Building Materials ◽  
Ventilation System ◽  
Sampling Period ◽  
Low Energy ◽  
Low Energy Buildings

The use of an airtight frame in low-energy buildings could increase the risk of health-related problems, such as allergies and sick building syndromes (SBS), associated with chemical emissions from building materials, especially if the ventilation system is not functioning properly. In this study, the indoor air quality (IAQ) was investigated in newly built low-energy and conventional preschools by monitoring the indoor air temperature, relative humidity, particle-size distribution and levels of carbon dioxide (CO2), nitrogen dioxide (NO2), formaldehyde and total volatile organic compounds (TVOC). The thermal comfort was satisfactory in all preschools, with average indoor air temperature and a relative humidity at 21.4°C and 36%, respectively. The highest levels of TVOC (range: 130–1650 µg/m3 toluene equivalents) and formaldehyde (range: 1.9–28.8 µg/m3) occurred during the first sampling period associated with strong emissions from building materials. However, those preschools constructed with environmental friendly building materials (such as Swan Eco-label) had lower initial TVOC levels compared to those preschools constructed with conventional building materials. The IAQ and indoor chemical emissions were also strongly dependent on the functioning of the ventilation system. Preliminary risk assessment indicated that exposure to acrolein and crotonaldehyde might lead to respiratory-tract irritation among occupants.

scholarly journals Characteristics of SARS-CoV-2 aerosol dispersion in indoor air: scoping review

2021 ◽  
Vol 10 (4) ◽  
pp. e44310414300
Author(s):  
Anyele Albuquerque Lima ◽  
Izabelly Carollynny Maciel Nunes ◽  
José Leandro da Silva Duarte ◽  
Lucas Meili ◽  
Patricia de Carvalho Nagliate ◽  
...  
Keyword(s):  
Viral Load ◽  
Relative Humidity ◽  
Air Temperature ◽  
Indoor Air ◽  
Scoping Review ◽  
Grey Literature ◽  
Flow Diagram ◽  
Minimum Size ◽  
Management Tool ◽  
Cochrane Library

Background: SARS-CoV-2 is the infectious agent responsible for COVID-19, its transmission occurs through the release of respiratory droplets and aerosols. Aim: Identify the main characteristics of SARS-CoV-2 aerosols dispersion in indoor air. Methods: Scoping Review was conducted using the databases: National Library of Medicines – MEDLINE/Pubmed, Scopus, Web of Science, Virtual Health Library (VHL) and Cochrane Library, the search in gray literature was performed on Google Scholar, OpenGrey and Grey Literature Report, from March to September 2020. The descriptors used were "coronavirus" and "aerosol". Data were selected and screened following the protocol established by the The Joanna Briggs Institute, PRISMA flow diagram and EndNote reference management tool. Findings: Ten papers were selected, which presented characteristics that could influence the SARS-CoV-2 aerosols dispersion, with highlight to: aerosol origin; viral load identified in the air (2.86 copies/liter of air); aerosol particle size with viral load (0.25 μm); dispersion (10.00 m); air stay time (3 h); influence of air temperature and relative humidity. Conclusion: Aerosol particles containing SARS-CoV-2 may have infectious viral charge, presenting a minimum size up to 0.25 μm, being able to reach up to 10 m of distance and survive in the air for a few hours. The variables air temperature and relative humidity did not present consistent evidence to influence the dispersion of SARS-CoV-2 aerosols.

scholarly journals Influence of indoor air temperature and relative humidity on learning performance of undergraduates

2021 ◽  
pp. 101458
Author(s):  
Chao Liu ◽  
Yalin Zhang ◽  
Limei Sun ◽  
Weijun Gao ◽  
Xiaotong Jing ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Indoor Air ◽  
Learning Performance

Thermal comfort analysis of radiant cooling panels with dedicated fresh-air system

2020 ◽  
pp. 1420326X2096114
Author(s):  
S. Y. Qin ◽  
X. Cui ◽  
C. Yang ◽  
L. W. Jin
Keyword(s):  
Relative Humidity ◽  
Surface Temperature ◽  
Thermal Comfort ◽  
Air Temperature ◽  
Indoor Air ◽  
Area Ratio ◽  
Human Thermal Comfort ◽  
Air Supply ◽  
Radiant Cooling ◽  
Air System

Radiant system has been increasingly applied in buildings due to its good thermal comfort and energy-saving potential. In this research, a simplified predicted mean vote (PMV) model and sensible cooling load equation were proposed based on human thermal comfort. Simulations were carried out using Airpak to explore relationships among thermal comfort characteristics, design and operation parameters. Results show that radiant surface temperature, fresh-air supply temperature and the area ratio are correlated approximately linearly with the indoor air temperature, while the relative humidity has little effect on the indoor air temperature. The indoor air velocity in the simulated environment was no more than 0.15 m/s, satisfying the requirements of limit values in the occupied zone. The results indicate that the optimum radiant surface temperature ( tc) is 19°C to 23°C when fresh-air supply temperature ( ts) is 26°C. The relative humidity ( φ) should be maintained at 50% to 70%, and the area ratio of radiant panels to total surfaces ( k1) should be kept within 0.15 to 0.38 when the radiant surface temperature is 20°C and the fresh-air supply temperature is 26°C. The simplified PMV model and the sensible load equation can provide reference for panel design based on characteristics of radiant cooling panels with a dedicated fresh-air system.

scholarly journals Indoor Daylighting and Thermal Response of a Passive Solar Building to Selective Components of Solar Radiation

Buildings ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 34
Author(s):  
Ochuko Kelvin Overen ◽  
Edson Leroy Meyer ◽  
Golden Makaka
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Air Temperature ◽  
Indoor Air ◽  
Temperature Response ◽  
Longwave Radiation ◽  
Thermal Conditions ◽  
Visible Radiation ◽  
Downward Longwave Radiation ◽  
Passive Solar

Solar radiation provides the most significant natural energy in buildings for space heating and daylighting. Due to atmospheric interference, solar radiation received at the Earth’s surface consists of direct beam and diffuse radiation, where diffuse can be further broken down into longwave and visible radiation. Although each of these components co-occurs, their influence on the indoor visual and thermal conditions of a building differ. This study aims to analyze the influence of the various components of solar radiation on the indoor thermal and daylighting of a passive solar building. Thus, a pyrheliometer, pyranometer, shaded-pyranometer, and pyrgeometer mounted on a SOLYS 2 (Kipp & Zonen, Delft, Netherlands) dual Axis sun tracker, were used to monitor direct, global horizontal, diffuse and downward longwave radiation, respectively. The seasonal indoor air temperature and relative humidity were measured using an HMP 60 temperature relative humidity probe. A Li-210R photometric sensor was used to monitor the indoor illuminance. The summer and winter indoor air temperature, as well as relative humidity, were found to be influenced by diffuse horizontal and global horizontal irradiance, respectively. In summer, the indoor air temperature response to diffuse horizontal irradiance was 0.7 °C/ħW/m2 and 1.1 °C/ħW/m2 to global horizontal irradiance in winter, where ħ is 99.9 W/m2. The indoor daylighting which was found to be above the minimum office visual task recommendation in most countries, but within the useful daylight illuminance range was dominated by direct normal irradiance. A response of 260 lux/ħW/m2 was observed. The findings of the study support the strategic locating of the windows in passive solar design. However, the results show that north-facing clerestory windows without shading device could lead to visual discomfort.

scholarly journals Machine Learning-Based Microclimate Model for Indoor Air Temperature and Relative Humidity Prediction in a Swine Building

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 222
Author(s):  
Elanchezhian Arulmozhi ◽  
Jayanta Kumar Basak ◽  
Thavisack Sihalath ◽  
Jaesung Park ◽  
Hyeon Tae Kim ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Indoor Air ◽  
Primary Objective ◽  
Environmental Data ◽  
Support Vector ◽  
Random Forest Regression ◽  
Multilayered Perceptron ◽  
The Right ◽  
The Given

Indoor air temperature (IAT) and indoor relative humidity (IRH) are the prominent microclimatic variables; still, potential contributors that influence the homeostasis of livestock animals reared in closed barns. Further, predicting IAT and IRH encourages farmers to think ahead actively and to prepare the optimum solutions. Therefore, the primary objective of the current literature is to build and investigate extensive performance analysis between popular ML models in practice used for IAT and IRH predictions. Meanwhile, multiple linear regression (MLR), multilayered perceptron (MLP), random forest regression (RFR), decision tree regression (DTR), and support vector regression (SVR) models were utilized for the prediction. This study used accessible factors such as external environmental data to simulate the models. In addition, three different input datasets named S1, S2, and S3 were used to assess the models. From the results, RFR models performed better results in both IAT (R2 = 0.9913; RMSE = 0.476; MAE = 0.3535) and IRH (R2 = 0.9594; RMSE = 2.429; MAE = 1.47) prediction among other models particularly with S3 input datasets. In addition, it has been proven that selecting the right features from the given input data builds supportive conditions under which the expected results are available. Overall, the current study demonstrates a better model among other models to predict IAT and IRH of a naturally ventilated swine building containing animals with fewer input attributes.

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