Coexposure to indoor pollutants in French schools and associations with building characteristics

2021 ◽  
pp. 111424
Author(s):  
Sutharsini Sivanantham ◽  
Claire Dassonville ◽  
Anthony Grégoire ◽  
Laeticia Malingre ◽  
Olivier Ramalho ◽  
...  
Keyword(s):  
Indoor Pollutants ◽  
Building Characteristics

scholarly journals Assessing the Energy Resilience of Office Buildings: Development and Testing of a Simplified Metric for Real Estate Stakeholders

Buildings ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 96
Author(s):  
Paul Mathew ◽  
Lino Sanchez ◽  
Sang Hoon Lee ◽  
Travis Walter
Keyword(s):  
Regression Models ◽  
Health And Safety ◽  
Office Buildings ◽  
Extreme Weather Events ◽  
Economic Losses ◽  
Power Outage ◽  
Continuity Of Operations ◽  
Quasi Monte Carlo ◽  
Building Characteristics ◽  
The Impact

Increasing concern over higher frequency extreme weather events is driving a push towards a more resilient built environment. In recent years there has been growing interest in understanding how to evaluate, measure, and improve building energy resilience, i.e., the ability of a building to provide energy-related services in the event of a local or regional power outage. In addition to human health and safety, many stakeholders are keenly interested in the ability of a building to allow continuity of operations and minimize business disruption. Office buildings are subject to significant economic losses when building operations are disrupted due to a power outage. We propose “occupant hours lost” (OHL) as a means to measure the business productivity lost as the result of a power outage in office buildings. OHL is determined based on indoor conditions in each space for each hour during a power outage, and then aggregated spatially and temporally to determine the whole building OHL. We used quasi-Monte Carlo parametric energy simulations to demonstrate how the OHL metric varies due to different building characteristics across different climate zones and seasons. The simulation dataset was then used to develop simple regression models for assessing the impact of ten key building characteristics on OHL. The most impactful were window-to-wall ratio and window characteristics. The regression models show promise as a simple means to assess and screen for resilience using basic building characteristics, especially for non-critical facilities where it may not be viable to conduct detailed engineering analysis.

Green Building, Green Behavior? An Analysis of Building Characteristics that Support Environmentally Responsible Behaviors

2020 ◽  
pp. 001391652094260
Author(s):  
Erin M. Hamilton
Keyword(s):  
Online Survey ◽  
Green Building ◽  
Built Environments ◽  
Sustainable Buildings ◽  
Natural Materials ◽  
Environmentally Responsible ◽  
Building Characteristics ◽  
Green Behavior ◽  
Environmentally Responsible Behaviors ◽  
Responsible Behaviors

This study examines the environmentally responsible behaviors (ERBs) of undergraduates ( n = 575). ERBs were measured in an online survey and the influence of situational context on behavior was explored at two scales: 1) green versus non-green building and 2) building characteristics. The Positive Sustainable Built Environments model was used to analyze three building characteristics: Prime, Permit, and Invite. Prime refers to characteristics that prepare occupants to adopt ERBs via communicating a sustainable ethos or restoring attentional capacity (e.g., use of natural materials and views to nature). Permit refers to features that allow occupants to conserve resources (e.g., operable light switches). Invite pertains to features that explicitly encourage ERBs (e.g., signage prompting occupants to turn off lights). Regression results demonstrated that living in a green building had no significant impact on ERBs. However, the Prime and Invite building characteristics significantly predicted improved Energy, Water, and Materials conservation. Results yield implications for designers seeking to create sustainable buildings that promote ERBs.

Dehumidification of Moist Air with Simultaneous Removal of Selected Indoor Pollutants by Triethylene Glycol Solutions in a Packed-Bed Absorber

1995 ◽  
Vol 30 (7-9) ◽  
pp. 1807-1832 ◽  
Author(s):  
Tsair-Wang Chung ◽  
Tushar K. Ghosh ◽  
Anthony L. Hines ◽  
Davor Novosel
Keyword(s):  
Triethylene Glycol ◽  
Packed Bed ◽  
Simultaneous Removal ◽  
Moist Air ◽  
Indoor Pollutants

scholarly journals Estimation of Outdoor PM2.5 Infiltration into Multifamily Homes Depending on Building Characteristics Using Regression Models

2021 ◽  
Vol 13 (10) ◽  
pp. 5708
Author(s):  
Bo-Ram Park ◽  
Ye-Seul Eom ◽  
Dong-Hee Choi ◽  
Dong-Hwa Kang
Keyword(s):  
Regression Analysis ◽  
Correlation Analysis ◽  
Field Test ◽  
Outer Surface ◽  
Regression Models ◽  
Field Tests ◽  
Test Results ◽  
Correlation And Regression Analysis ◽  
Building Characteristics ◽  
Pm2.5 Concentration

The purpose of this study was to evaluate outdoor PM2.5 infiltration into multifamily homes according to the building characteristics using regression models. Field test results from 23 multifamily homes were analyzed to investigate the infiltration factor and building characteristics including floor area, volume, outer surface area, building age, and airtightness. Correlation and regression analysis were then conducted to identify the building factor that is most strongly associated with the infiltration of outdoor PM2.5. The field tests revealed that the average PM2.5 infiltration factor was 0.71 (±0.19). The correlation analysis of the building characteristics and PM2.5 infiltration factor revealed that building airtightness metrics (ACH50, ELA/FA, and NL) had a statistically significant (p < 0.05) positive correlation (r = 0.70, 0.69, and 0.68, respectively) with the infiltration factor. Following the correlation analysis, a regression model for predicting PM2.5 infiltration based on the ACH50 airtightness index was proposed. The study confirmed that the outdoor-origin PM2.5 concentration in highly leaky units could be up to 1.59 times higher than that in airtight units.

Influence of building characteristics and renovation techniques on the energy-saving performances of EU smart city projects

2021 ◽  
Vol 252 ◽  
pp. 111477
Author(s):  
Kyuman Cho ◽  
Junho Yang ◽  
Taehoon Kim ◽  
Woosik Jang
Keyword(s):  
Energy Saving ◽  
Smart City ◽  
Building Characteristics

The temporal variation of indoor pollutants in photocopying shop

2015 ◽  
Vol 30 (4) ◽  
pp. 1289-1300 ◽  
Author(s):  
Jelena S. Kiurski ◽  
Ivana B. Oros ◽  
Vesna S. Kecic ◽  
Ilija M. Kovacevic ◽  
Snezana M. Aksentijevic
Keyword(s):  
Temporal Variation ◽  
Indoor Pollutants

scholarly journals ZnO Nanostructures to Detect Low Concentrations of Indoor Pollutants

2015 ◽  
Vol 120 ◽  
pp. 711-716 ◽  
Author(s):  
J. Gonzalez-Chavarri ◽  
I. Castro-Hurtado ◽  
E. Castaño ◽  
G.G. Mandayo
Keyword(s):  
Zno Nanostructures ◽  
Indoor Pollutants ◽  
Low Concentrations

scholarly journals Patterns of bird-window collisions inform mitigation on a university campus

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1652 ◽  
Author(s):  
Natalia Ocampo-Peñuela ◽  
R. Scott Winton ◽  
Charlene J. Wu ◽  
Erika Zambello ◽  
Thomas W. Wittig ◽  
...  
Keyword(s):  
Ad Hoc ◽  
The United States ◽  
University Campus ◽  
Student Government ◽  
News Stories ◽  
Local Media ◽  
Building Characteristics ◽  
Mitigation Action ◽  
Window Area ◽  
Architectural Characteristics

Bird-window collisions cause an estimated one billion bird deaths annually in the United States. Building characteristics and surrounding habitat affect collision frequency. Given the importance of collisions as an anthropogenic threat to birds, mitigation is essential. Patterned glass and UV-reflective films have been proven to prevent collisions. At Duke University’s West campus in Durham, North Carolina, we set out to identify the buildings and building characteristics associated with the highest frequencies of collisions in order to propose a mitigation strategy. We surveyed six buildings, stratified by size, and measured architectural characteristics and surrounding area variables. During 21 consecutive days in spring and fall 2014, and spring 2015, we conducted carcass surveys to document collisions. In addition, we also collected ad hoc collision data year-round and recorded the data using the app iNaturalist. Consistent with previous studies, we found a positive relationship between glass area and collisions. Fitzpatrick, the building with the most window area, caused the most collisions. Schwartz and the Perk, the two small buildings with small window areas, had the lowest collision frequencies. Penn, the only building with bird deterrent pattern, caused just two collisions, despite being almost completely made out of glass. Unlike many research projects, our data collection led to mitigation action. A resolution supported by the student government, including news stories in the local media, resulted in the application of a bird deterrent film to the building with the most collisions: Fitzpatrick. We present our collision data and mitigation result to inspire other researchers and organizations to prevent bird-window collisions.

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