Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Land Surveying and Geo-Informatics | en_US |
| dc.contributor.advisor | Wong, Man Sing (LSGI) | en_US |
| dc.creator | Meng, Yuan | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/12448 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Assessing the impact of air pollution and human activities associated with urban morphological features on COVID-19 mortality | en_US |
| dcterms.abstract | Urban morphological features play an important role in assessing air pollution and human activities. With the rapid spread of novel coronavirus disease 2019 (COVID-19), the lock-down and social restriction exhibit significant challenges on physical and socioeconomic environment assessment, providing unprecedented opportunities to estimate the air pollution and human activity variation and their potential impact on the reported COVID-19 death cases from a new perspective. While previous studies have investigated the changing responses of air pollution and human activities, that is the spatio-temporal nonstationarity, under such social restriction, how these nonstationarities are influenced by urban morphologies and to what extent are they linked to the COVID-19 mortality remains largely unknown. To fill this gap, this dissertation presented a framework to evaluate the impact of urban morphology on air pollution and human activity variation under lockdown and social restrictions, and further to assess COVID-19 mortality influenced by the spatio-temporal nonstationarity of air pollution and human activities. | en_US |
| dcterms.abstract | First, this study proposed a new idea to explore the effects of urban functional fragmentation on nitrogen dioxide (NO2) variation with anthropogenic-emission restriction in China. NO2 data were collected from the China National Environmental Monitoring Center (CNEMC), and the temporal NO2 variations were quantified by proposing an Autoregressive Integrated Moving Average with external variables-Dynamic Time Warping (SARIMAX-DTW)-based model. Moreover, the indicators for depicting urban functional fragmentation were developed. The mediated impacts of anthropogenic-emission restriction were assessed by evaluating the fragmentation-NO2 variation association before and during the lockdown during COVID-19. The findings reveal that the mediated impact of anthropogenic-emission restriction partially increases the effect of industrial Edge Density (ED), industrial Landscape Shape Index (LSI), public LSI, urban functional Aggregation Index (AI) and Number of Patches (NP) and decreases the effect of public ED on NO2 variation. | en_US |
| dcterms.abstract | Second, a framework of assessing the multi-spatial scale association between urban morphologies and human activities with the mediated effect of social restriction across 459 U.S. cities was proposed. Human activity data were collected from SafeGraph Patterns dataset and were aggregated into census-block-group level, city level and country level. Activity-driven built environment features including transportation, greenery and land uses depicted by data from United States Census Bureau and OpenStreetMap (OSM) were evaluated with the association of human activities using a geographically weighted regression (GWR) model. Results exhibit varied decreases of human activities, from 0.25% to 76.35%, among cities during COVID-19 social restriction. Moreover, multi-spatial scale analysis demonstrated the temporal non-stationary impacts of transportation and greenery features and consistent declining impacts of land use features during social restriction. | en_US |
| dcterms.abstract | Third, a Bayesian space-time hierarchical model (BSTHM) was proposed to investigate the multi-scale spatial effect of the global air pollution, including NO2 and fine particulate matter less than 2.5 µg in diameter (PM2.5), and human activities, including driving and walking activities, on the COVID-19 mortality based on 46 cities from 6 countries. NO2 and PM2.5 were collected from Air Quality Open Data Platform and human activities were adopted from Apple Mobility. Results show positive relative risks of NO2, PM2.5 and walking activities, and negative relative risk of driving activities on COVID-19 mortality based on the global scale. Moreover, discrepancies in assessing air pollution and human activities were revealed based on individual cities. | en_US |
| dcterms.abstract | This dissertation provides scientific findings for redesigning the urban environment in related to the urban land use configuration for mitigating the air pollution and estimating dynamic activities, ultimately developing sustainable cities. Meanwhile, findings exhibit the necessity to investigate the potential impact of multi-scale spatial effect of the air pollution and activity patterns on the COVID-19 mortality. | en_US |
| dcterms.extent | xxviii, 160 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2023 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.LCSH | Air -- Pollution | en_US |
| dcterms.LCSH | Urban ecology (Sociology) | en_US |
| dcterms.LCSH | COVID-19 Pandemic, 2020- | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | open access | en_US |
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