A source depletion model for vapor intrusion involving the influence of building characteristics

2019 ◽  
Vol 246 ◽  
pp. 864-872 ◽  
Author(s):  
Ruihuan Zhang ◽  
Lin Jiang ◽  
Maosheng Zhong ◽  
George DeVaull ◽  
Matthew A. Lahvis ◽  
...  
Keyword(s):  
Vapor Intrusion ◽  
Building Characteristics ◽  
Source Depletion

scholarly journals Comparison of modeled and measured indoor air trichloroethene (TCE) concentrations at a vapor intrusion site: influence of wind, temperature, and building characteristics

2020 ◽  
Vol 22 (3) ◽  
pp. 802-811 ◽  
Author(s):  
Elham Shirazi ◽  
Gregory S. Hawk ◽  
Chase W. Holton ◽  
Arnold J. Stromberg ◽  
Kelly G. Pennell
Keyword(s):  
Indoor Air ◽  
Weather Conditions ◽  
Vapor Intrusion ◽  
Alternative Pathways ◽  
Building Characteristics ◽  
Preferential Pathways

There is a lack of vapor intrusion (VI) models that reliably account for weather conditions and building characteristics, especially at sites where active alternative pathways, such as sewer connections and other preferential pathways, are present.

Vapor Intrusion: Environmental and IAQ Challenge, Part II

The Synergist ◽  
2007 ◽  
Vol 18 (4) ◽  
pp. 36
Author(s):  
Enrique Medina
Keyword(s):  
Vapor Intrusion

An Analytical Model of Vapor Intrusion with Fluctuated Water Table

2021 ◽  
pp. 126085
Author(s):  
Xinyue Liu ◽  
Enze Ma ◽  
You-Kuan Zhang ◽  
Xiuyu Liang
Keyword(s):  
Analytical Model ◽  
Water Table ◽  
Vapor Intrusion

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.

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.

Vapor Intrusion—Forensic Approaches and Recent Developments

2004 ◽  
Vol 16 (3-4) ◽  
pp. 237-248 ◽  
Author(s):  
Sunny Healey ◽  
Ioana G. Petrisor ◽  
Robert Morrison
Keyword(s):  
Vapor Intrusion ◽  
Recent Developments
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