Assessing physical conditions of indoor space enclosing elements in schools in relation to their indoor environmental quality
Introduction
Most indoor environmental quality (IEQ) studies include field observations during which researchers record additional IEQ related information not captured by field measurements and occupants’ satisfaction survey [e.g. [1], [2]]. These relevant information includes building characteristics (i.e. floor finish type, ceiling type, and window type) and occupants’ adaptations (i.e. window opened or closed and use of portable fan) [1], [3] that are employed to explain observed trends in field measurements and causes of occupants’ discomfort. For example, Fan et al. [2] found carbon dioxide concentrations above recommended limits in houses because doors and windows were mostly closed in winter. Additionally, De Giuli et al. [4] found closed operable windows as the main cause of students’ dissatisfaction with classrooms’ indoor air quality. Building indoor spaces are enclosed by elements including walls, floors, ceilings, and windows, hence, their physical conditions are likely to influence IEQ [5], [6]. However, physical conditions of building elements are generally not assessed during IEQ field measurements and observations [7], [8], [9]. Eweda et al. [10] defined building condition assessment (BCA) as “a process of systematically evaluating an organization's capital assets in order to project repair, renewal, or replacement needs …”. Several studies have investigated building repairs and renewals implemented to improve IEQ and reported positive impact on building occupants [11], [12], [13]. However, these studies did not account for the impact of defects on IEQ prior to the repairs and renewals. Exploring the link between defects of building elements and indoor environmental conditions would likely contribute to assessing the effectiveness of IEQ-related renovations and aid strategic building maintenance decision making.
Most of the existing BCA instruments including public housing assessment system (PHAS) [14] and BUILDER™ [15] were conceptualized with physical safety and cost as their primary objectives. For example, a blocked fire escape is considered to be more important than cracked window glazing in the PHAS [14]. Therefore, their defect severities and criticalities would not logically be most suitable for IEQ-related BCA. Considering the potential health benefits of IEQ enhancements [16] to occupants of existing buildings, the importance of IEQ-related BCA cannot be over emphasized. The goal of this research was to assess the usefulness of IEQ-related BCA for determining the likely impact of key building elements’ physical conditions on IEQ performance. This research therefore proposes a new BCA instrument, space level condition assessment (SLCA), developed based on existing BCA's but with IEQ enhancement as primary objective. The SLCA conceptualized based on classroom environments in schools, was deployed in 10 schools consisting of new, renovated, and non-renovated school. IEQ field measurements were also conducted in the 10 schools. Assessing the usefulness of the SLCA involved analyzing the differences in SLCA scores and IEQ field measurements between new, renovated, and non-renovated schools. The proposed BCA instrument is intended to provide a quick and cost-effective means of conducting IEQ-related BCA for multiple school buildings. Findings of this research should be of interest to school divisions and managers looking to renovate existing schools or develop a maintenance plan focused on IEQ enhancement. Additionally, findings of this study would interest designers and engineers working on remodeling existing schools or planning new school projects. Finally, this research will be of interest to researchers investigating IEQ in schools or other building types.
Section snippets
Background
There is growing interest in the IEQ literature about the impact of renovations on buildings’ IEQ performance; however, most of these studies focused on homes and offices [17]. For homes, Wells et al. [18] conducted a post-renovation study of homes following deep energy retrofitting and energy star retrofitting and found that relative humidity, air temperature, and carbon dioxide (CO2) concentrations were within recommended ranges or below the minimum threshold. In another post-renovation study
Methods
This research is part of a two-staged study conducted in collaboration with the Government of Manitoba Public School Finance Board and two school divisions in Manitoba, Canada. The first stage involved developing IEQ satisfaction and well-being surveys for teachers in schools, and IEQ-related BCA instrument for schools [24]. The second stage involved deploying, refining, and validating these surveys [25] along with field measurements of IEQ parameters and IEQ-related BCA. This paper focused on
Results
This subsection presents the results of the SLCA and IEQ field measurements for the four main factors of IEQ: thermal comfort, IAQ, acoustics, and lighting.
Discussions
The analysis identified several statistically significant differences in SLCA scores across the three strata of schools. Firstly, four statistically significant differences were found between new and renovated schools for level 4 SLCA components related to IAQ, acoustics, and lighting. Secondly, seven statistically significant differences were found between new and non-renovated schools for level 4 SLCA components related to thermal comfort, IAQ, acoustics, and lighting. Lastly, one
Conclusions
This research investigated the usefulness of IEQ-related BCA using the newly developed SLCA in new, renovated and non-renovated schools, attesting to its merits for IEQ-related BCA. The SLCA was developed using a predefined list of defects to minimize ambiguity when interpreting findings and would thus be a useful guide to school divisions when planning and prioritizing IEQ-related maintenance for their schools. Additionally, the SLCA provides building condition information hitherto not
Acknowledgements
The authors are grateful to the Government of Manitoba Public School Finance Board, the two school divisions, and the 32 schools for agreeing to participate in this research and facilitating access to the schools and the data collection. The authors are also grateful to Md Anamul Hasan, Joshua Boateng Akom, and Katia Cavalcanti Parpinelli for their assistance with data collection. This research was funded by a Discovery Grant (RGPIN 418532-2012) from the Natural Sciences and Engineering
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