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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

邮发代号 80-973

2018 Impact Factor: 3.883

Frontiers of Environmental Science & Engineering  2024, Vol. 18 Issue (1): 11   https://doi.org/10.1007/s11783-024-1771-z
  本期目录
Effects of the urban landscape on heatwave-mortality associations in Hong Kong: comparison of different heatwave definitions
Jinglu Song1(), Yi Lu2, Thomas Fischer3,4, Kejia Hu5
1. Department of Urban Planning and Design, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
2. Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong 999077, China
3. Environmental Assessment and Management Research Centre, School of Environmental Sciences, University of Liverpool, Liverpool L3 5TR, UK
4. Research Unit for Environmental Sciences and Management, Faculty of Natural and Agricultural Sciences, North West University, Potchefstroom 31750, South Africa
5. Institute of Big Data in Health Science, School of Public Health, Zhejiang University, Zijingang Campus, Hangzhou 310058, China
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Abstract

● The effect modifications of urban landscape were explored at the intra-urban level.

● Higher levels of green spaces could alleviate adverse health impacts of heatwaves.

● Higher building density and nighttime land surface temperatures aggravate impacts.

● Effects of urban landscape were more significant in older adults and males.

● Pronounced effect modifications were observed under hotter and longer heatwaves.

Despite increased attention given to potential modifiers of temperature-mortality associations, evidence for variations between different urban landscape characteristics remains limited. It is in this context that in this paper effect modifications of multiple urban landscape characteristics are explored under different heatwave definitions for different age groups and gender in Hong Kong, China. Daily meteorological data and heatwave-related mortality counts from 2008 to 2017 were collected from the Hong Kong Census and Statistics Department, China. A case-only design was adopted, combined with logistic regression models to examine the modification effects of five urban landscape characteristics under six heatwave definitions. Stratified analyses were conducted to investigate age- and gender-specific effect modifications. It is found that individuals living in greener areas experienced lower levels of mortality during or immediately after heatwaves. In contrast, a higher building density and nighttime land surface temperature (LST) were associated with a higher heatwave-related mortality risk. Pronounced effect modifications of these urban landscape characteristics were observed under hotter and longer heatwaves, and in older adults (age ≥ 65 years) and males. The findings provide a scientific basis for policymakers and practitioners when considering measures for coping with hotter, longer, and more frequent heatwaves in the context of global climate change.

Key wordsUrban landscape    Heatwave    Mortality    Effect modification    Intra-urban differences    Health risk reduction
收稿日期: 2023-02-16      出版日期: 2023-09-06
Corresponding Author(s): Jinglu Song   
 引用本文:   
. [J]. Frontiers of Environmental Science & Engineering, 2024, 18(1): 11.
Jinglu Song, Yi Lu, Thomas Fischer, Kejia Hu. Effects of the urban landscape on heatwave-mortality associations in Hong Kong: comparison of different heatwave definitions. Front. Environ. Sci. Eng., 2024, 18(1): 11.
 链接本文:  
https://academic.hep.com.cn/fese/CN/10.1007/s11783-024-1771-z
https://academic.hep.com.cn/fese/CN/Y2024/V18/I1/11
Urban landscape Characteristics Mean ± SD 25% Median 75%
NDVI 0.48 ± 0.18 0.34 0.52 0.64
Proximity to water (km) 1.59 ± 1.84 0.35 0.88 1.90
Building density 81.04 ± 61.98 21.88 66.01 134.00
Daytime LST (°C) 29.45 ± 1.82 27.88 29.10 30.78
Nighttime LST (°C) 24.00 ± 0.90 23.33 24.01 24.67
Tab.1  
Fig.1  
Urban landscape characteristics Heatwave definitions 2 day 4 day p-valuea)
NDVI 90P 0.96 (0.90, 1.03) 0.92 (0.85, 0.99) 0.355
92.5P 0.94 (0.88, 1.01) 0.88 (0.81, 0.96) 0.213
95P 0.92 (0.85, 1.00) 0.78 (0.68, 0.88) 0.026
p-valueb) 0.382 0.04 0.0043c)
Proximity to water 90P 1.02 (0.96, 1.07) 1.02 (0.96, 1.09) 0.868
92.5P 1.04 (0.98, 1.09) 1.03 (0.97, 1.10) 0.926
95P 1.02 (0.96, 1.08) 1.03 (0.94, 1.14) 0.811
p-valueb) 0.873 0.815 0.737c)
Building density 90P 1.00 (0.93, 1.07) 1.04 (0.96, 1.13) 0.380
92.5P 1.01 (0.94, 1.08) 1.09 (1.00, 1.19) 0.151
95P 1.04 (0.96, 1.12) 1.16 (1.02, 1.32) 0.133
p-valueb) 0.469 0.154 0.038c)
Daytime LST 90P 0.98 (0.93, 1.03) 1.00 (0.94, 1.06) 0.667
92.5P 0.98 (0.93, 1.04) 1.01 (0.95, 1.08) 0.489
95P 0.98 (0.92, 1.04) 1.00 (0.91, 1.10) 0.681
p-valueb) 0.991 0.872 0.679c)
Nighttime LST 90P 1.04 (0.98, 1.10) 1.08 (1.01, 1.16) 0.425
92.5P 1.08 (1.01, 1.15) 1.10 (1.02, 1.19) 0.645
95P 1.10 (1.03, 1.18) 1.27 (1.13, 1.42) 0.041
p-valueb) 0.221 0.039 0.003c)
Tab.2  
Fig.2  
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