Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102877
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dc.contributorDepartment of Building Environment and Energy Engineeringen_US
dc.creatorLee, KYen_US
dc.creatorMak, CMen_US
dc.date.accessioned2023-11-17T02:58:22Z-
dc.date.available2023-11-17T02:58:22Z-
dc.identifier.issn2210-6707en_US
dc.identifier.urihttp://hdl.handle.net/10397/102877-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2019 Published by Elsevier Ltd.en_US
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Lee, K. Y., & Mak, C. M. (2019). A comprehensive approach to study stack emissions from a research building in a small urban setting. Sustainable Cities and Society, 51, 101710 is available at https://doi.org/10.1016/j.scs.2019.101710.en_US
dc.subjectAir quality monitoringen_US
dc.subjectPollutant dispersion modellingen_US
dc.subjectStack emissionen_US
dc.subjectTracer gas studyen_US
dc.titleA comprehensive approach to study stack emissions from a research building in a small urban settingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume51en_US
dc.identifier.doi10.1016/j.scs.2019.101710en_US
dcterms.abstractGaseous emissions from research facilities within an urban environment have not been fully studied. The present study investigates the impacts of stack emissions from a research building in Hong Kong on nearby urban areas. Fifteen chemicals emitted from the laboratories of the building were selected for a year-long air monitoring. Among the 15 chemicals, the levels of NO2, acetonitrile, and total volatile organic compounds (TVOC) exceeded the predetermined exposure levels. A tracer gas study was performed to identify the dilution factor of the environment and to validate two turbulence models, namely, Renormalized Group (RNG) and Realizable (RLZ) k-ε models. Statistical tests, including geometric mean bias (MG) and factor of two (FAC2), demonstrated that the RNG (MG: 0.88–1.5; FAC2: 0.67–1.14) was better than the RLZ k-ε model (MG: 0.26-0.68; FAC2: 1.47–3.80) for the prediction of pollutant dispersion and concentration distribution but still could not achieve statically sound results. Despite the RNG k-ε model is a popular and economical choice in numerical simulations, careful interpretation of data would be required, and it should also be used and read in conjunction with air monitoring and tracer gas assessment data as a comprehensive approach when assessing the impact of stack emissions in an urban setting.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSustainable cities and society, Nov. 2019, v. 51, 101710en_US
dcterms.isPartOfSustainable cities and societyen_US
dcterms.issued2019-11-
dc.identifier.scopus2-s2.0-85069730617-
dc.identifier.eissn2210-6715en_US
dc.identifier.artn101710en_US
dc.description.validate202311 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberBEEE-0323-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS28676581-
dc.description.oaCategoryGreen (AAM)en_US
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