Assessing Urban Risk to Extreme Heat in China
Many cities are experiencing persistent risk in China due to frequent extreme weather events. Some extreme weather events, such as extreme heat hazard, have seriously threatened human health and socio-economic development in cities. There is an urgent need to measure the degree of extreme heat risk...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | Sustainability |
Subjects: | |
Online Access: | https://www.mdpi.com/2071-1050/12/7/2750 |
id |
doaj-89d0cc057f634ea18447a5db23aad1bf |
---|---|
record_format |
Article |
spelling |
doaj-89d0cc057f634ea18447a5db23aad1bf2020-11-25T02:28:44ZengMDPI AGSustainability2071-10502020-04-01122750275010.3390/su12072750Assessing Urban Risk to Extreme Heat in ChinaXiaojun Huang0Yanyu Li1Yuhui Guo2Dianyuan Zheng3Mingyue Qi4College of Urban and Environmental Science, Northwest University, Xi’an 710127, ChinaCollege of Urban and Environmental Science, Northwest University, Xi’an 710127, ChinaCollege of Urban and Environmental Science, Northwest University, Xi’an 710127, ChinaCollege of Urban and Environmental Science, Northwest University, Xi’an 710127, ChinaCollege of Urban and Environmental Science, Northwest University, Xi’an 710127, ChinaMany cities are experiencing persistent risk in China due to frequent extreme weather events. Some extreme weather events, such as extreme heat hazard, have seriously threatened human health and socio-economic development in cities. There is an urgent need to measure the degree of extreme heat risk and identify cites with the highest levels of extreme heat risk. In this study, we presented a risk assessment framework of extreme heat and considered risk as a combination of hazard, exposure, and vulnerability. Based on these three dimensions, we selected relevant variables from historical meteorological data (1960–2016) and socioeconomic statistics in 2016, establishing an indicator system of extreme heat risk evaluation. Finally, we developed an extreme heat risk index to quantify the levels of extreme heat risk of 296 prefecture-level cities in China and revealed the spatial pattern of extreme heat risk in China in 2016 and their dominant factors. The results show that (1) cities with high levels of extreme heat hazard are mainly located in the south of China, especially in the southeast of China; (2) the spatial distribution of the extreme heat risk index shows obvious agglomeration characteristics; (3) the spatial distribution of the extreme heat risk is still mostly controlled by natural geographical conditions such as climate and topography; (4) among the four types of hazard-dominated, exposure-dominated, vulnerability-dominated, and low risk cities, the number of vulnerability-dominated cities is the largest. The results of this study can provide support for the risk management of extreme heat disasters and the formation of targeted countermeasures in China.https://www.mdpi.com/2071-1050/12/7/2750extreme heatrisk assessmenthazardexposurevulnerabilityChina |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaojun Huang Yanyu Li Yuhui Guo Dianyuan Zheng Mingyue Qi |
spellingShingle |
Xiaojun Huang Yanyu Li Yuhui Guo Dianyuan Zheng Mingyue Qi Assessing Urban Risk to Extreme Heat in China Sustainability extreme heat risk assessment hazard exposure vulnerability China |
author_facet |
Xiaojun Huang Yanyu Li Yuhui Guo Dianyuan Zheng Mingyue Qi |
author_sort |
Xiaojun Huang |
title |
Assessing Urban Risk to Extreme Heat in China |
title_short |
Assessing Urban Risk to Extreme Heat in China |
title_full |
Assessing Urban Risk to Extreme Heat in China |
title_fullStr |
Assessing Urban Risk to Extreme Heat in China |
title_full_unstemmed |
Assessing Urban Risk to Extreme Heat in China |
title_sort |
assessing urban risk to extreme heat in china |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2020-04-01 |
description |
Many cities are experiencing persistent risk in China due to frequent extreme weather events. Some extreme weather events, such as extreme heat hazard, have seriously threatened human health and socio-economic development in cities. There is an urgent need to measure the degree of extreme heat risk and identify cites with the highest levels of extreme heat risk. In this study, we presented a risk assessment framework of extreme heat and considered risk as a combination of hazard, exposure, and vulnerability. Based on these three dimensions, we selected relevant variables from historical meteorological data (1960–2016) and socioeconomic statistics in 2016, establishing an indicator system of extreme heat risk evaluation. Finally, we developed an extreme heat risk index to quantify the levels of extreme heat risk of 296 prefecture-level cities in China and revealed the spatial pattern of extreme heat risk in China in 2016 and their dominant factors. The results show that (1) cities with high levels of extreme heat hazard are mainly located in the south of China, especially in the southeast of China; (2) the spatial distribution of the extreme heat risk index shows obvious agglomeration characteristics; (3) the spatial distribution of the extreme heat risk is still mostly controlled by natural geographical conditions such as climate and topography; (4) among the four types of hazard-dominated, exposure-dominated, vulnerability-dominated, and low risk cities, the number of vulnerability-dominated cities is the largest. The results of this study can provide support for the risk management of extreme heat disasters and the formation of targeted countermeasures in China. |
topic |
extreme heat risk assessment hazard exposure vulnerability China |
url |
https://www.mdpi.com/2071-1050/12/7/2750 |
work_keys_str_mv |
AT xiaojunhuang assessingurbanrisktoextremeheatinchina AT yanyuli assessingurbanrisktoextremeheatinchina AT yuhuiguo assessingurbanrisktoextremeheatinchina AT dianyuanzheng assessingurbanrisktoextremeheatinchina AT mingyueqi assessingurbanrisktoextremeheatinchina |
_version_ |
1724836812239667200 |