Climatic, population, and spatial co-location contributions to nighttime and compound heatwave exposure in Southeast Asia

Datos Bibliográficos

ID24147802
AutoresPuyang Liu, Xian‐Xiang Li (0000-0002-8688-6206), Rui Xin (0000-0002-8452-3233), Jianjun Yu (0000-0002-2536-4332), Sandeep Sahany (0000-0002-7958-9182), Chen Chen (0000-0002-9786-8003), Aurel Florian Moise, Lup Wai Chew (0000-0003-2225-1057)
Año2026
Páginas107926
Fecha de publicación2026-09-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSustainable Cities and Society (JOURNAL)
Identificadores de la revistaISSN: 2210-6707 • E-ISSN: 2210-6715
EditorialElsevier BV (PUBLISHER)
DOI10.1016/j.scs.2026.107926
OpenAlexW7213668221
IdiomaEN
Referencias citadas62

Population exposure to daytime, nighttime, and compound heatwaves can follow distinct trajectories, yet their historical evolution and spatial overlap with population growth remain incompletely characterized across tropical Southeast Asia. ERA5-Land daily maximum and minimum temperatures for 1960–2022 were bias-corrected against SA-OBS using Quantile Delta Mapping (QDM) and used to identify mutually exclusive heatwave types. We combined cumulative heatwave exceedance with GHS-POP data for 1975–2020 to quantify burden-weighted population exposure in person· C·day across Southeast Asia, five subregions, and 12 cities. Exposure change between 1975–1984 and 2011–2020 was partitioned into climate, population, and spatial co-location contributions; the spatial co-location term is an algebraic cross-product without implying mechanistic causality. Nighttime and compound heatwave burdens increased more coherently than daytime burden. Relative to 1975–1984, nighttime and compound exposure in 2011–2020 reached 16.5 and 7.86 times their baseline levels, compared with 1.89 times for daytime exposure. Climate and spatial co-location accounted for 53.1% and 42.6% of the nighttime increase and 51.0% and 40.2% of the compound increase, while population change accounted for 90.5% of the daytime increase. At the city scale, nighttime and compound exposure showed the same pattern: seven cities were co-location-leading, two were climate-leading, and three showed no statistically clear ordering between the two contributions. City classifications were largely stable across urban boundary definitions and QDM calibration periods. These findings reveal distinct exposure structures across heatwave types and cities and support differentiated adaptation combining protection of established high-exposure populations with heat risk screening in growing metropolitan areas.

Climate change · Common spatial pattern · Daytime · Megacity · Metropolitan area · Population · Southeast asia · Spatial ecology · Climate Change and Health Impacts · Urban Green Space and Health · Urban Heat Island Mitigation