| Author: | Tsang, Tsz Wun |
| Title: | Development of novel assessment approaches and models to evaluate indoor environmental quality (IEQ) |
| Advisors: | Mui, Kwok-wai (BEEE) Wong, Ling-tim (BEEE) |
| Degree: | Ph.D. |
| Year: | 2021 |
| Subject: | Indoor air pollution Housing and health Environmental quality Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Building Services Engineering |
| Pages: | xx, 242 pages : color illustrations |
| Language: | English |
| Abstract: | Indoor environmental quality (IEQ) has become one of the main concerns in built environment due to its effects on productivity, health and well-being. Poor IEQ can lead to discomfort and sickness, and businesses may need to suffer tremendous cost associated with the negative influences induced by substandard IEQ. Therefore, IEQ shall not be overlooked in building development and facility management practice. IEQ can be categorized into a number of aspects, most popular ones include thermal comfort and indoor air quality (IAQ). Overall IEQ itself is also another perspective to evaluate building performance. The intra-relationship between factors of a particular aspect and the inter-relationship between aspects on overall IEQ have been found to be exceedingly complex, and these associations are usually task- and occupant-specific, which may change over time with lived experience by developing adaption and tolerance. To tackle the intrinsic property of IEQ of being both subjectively and objectively influenced, this study proposes three assessment approaches to evaluate overall IEQ, thermal comfort and IAQ based on their respective natures. The inadequacy of current assessment methods and models is first identified. Literature search of thermal comfort field data and field study on sleeping thermal comfort are conducted to evaluate the performance of exiting thermal comfort models. Effects and implications of using inaccurate prediction models are also discussed. Field surveys on physical environmental conditions and subjective IEQ responses are conducted in extreme living environments to determine the relationship between environmental quantities and occupant's acceptance, and to compare the new observations with established beliefs by acceptance prediction models. Discrepancies are found between predictions and actual data, suggesting the influence of contextual factors and adaptation on subjective responses to perceived environment. In order to acknowledge and reflect the influence of occupant's response in prediction model, and allow flexibility of model parameters, an open probabilistic acceptance model using frequency distribution function is developed to handle diverse range of descriptive IEQ parameters. It makes model updating easier and is more robust in reflecting occupant's environmental perception compared to existing logistic regression model. It is recognized that the characteristics of data used for model development strongly affect the accuracy, therefore the relationship expressed by prediction model shall be updated with newly observed field data. Subsequently, Bayesian updating protocol for thermal comfort and overall IEQ model is developed to propose a framework for updating the above-mentioned relationship. It is demonstrated with practical examples of existing thermal comfort model and IEQ regression model. Bayesian approach allows systematic updates of current beliefs (i.e. acceptance prediction models) with openly available field data and new observations. With the selection of target sample size and acceptable error based on managerial decision, this approach incorporates field settings into any existing model by considering the statistical significance of field data, even with a small sample size. It shall provide an achievable solution to the present challenges in establishing a reliable environmental acceptance prediction model. Additionally, being the one with severe health consequences, IAQ assessment can be conducted objectively based on health standard, rather than solely relying on subjective sense. To minimize the demand for conducting full IAQ assessment which is resource intensive, this study proposes a step-wise IAQ screening protocol with various combinations of surrogate IAQ parameters. It successfully screens out premises with high risk of problematic IAQ and those with low probability. Further to this, a large-scale IoT-based IAQ screening using low-cost sensors grid is conducted to demonstrate the identification of environmental attributes that contributed to poor IAQ and to evaluate the performance of IAQ index. The proposed novel assessment methods evaluate and predict IEQ from different perspectives – subjective-objective approach and objective-criteria approach, which shall facilitate indoor environmental management by providing an inclusive way to assess building performance. |
| Rights: | All rights reserved |
| Access: | open access |
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