Heat health risk assessment in Philippine cities using remotely sensed data and social-ecological indicators

More than half of the world’s population currently live in urban areas and are particularly at risk from the combined effects of the urban heat island phenomenon and heat increases due to climate change. Here, by using remotely sensed surface temperature data and social-ecological indicators, focusing on the hot dry season, and applying the risk framework of the Intergovernmental Panel on Climate Change, we assessed the current heat health risk in 139 Philippine cities, which account for about 40% of the country’s total population. The cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high. The most vulnerable cities are, however, found mainly outside the national capital region, where sensitivity is higher and capacity to cope and adapt is lower. Cities with high levels of heat vulnerability and exposure must be prioritized for adaptation. Our results will contribute to risk profiling in the Philippines and to the understanding of city-level heat health risks in developing regions of the Asia-Pacific. Evaluating the heat risk among city dwellers is important. Here, the authors assessed the heat risk in Philippine cities using remote sensing data and social-ecological indicators and found that the cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high.

[1]  L. Chapman,et al.  Including the urban heat island in spatial heat health risk assessment strategies: a case study for Birmingham, UK , 2011, International journal of health geographics.

[2]  Adrian E. Raftery,et al.  Less Than 2 °C Warming by 2100 Unlikely , 2017, Nature climate change.

[3]  L. Alexander,et al.  Increasing frequency, intensity and duration of observed global heatwaves and warm spells , 2012 .

[4]  Brian M. Tomaszewski,et al.  Climate vulnerability mapping: A systematic review and future prospects , 2019, WIREs Climate Change.

[5]  Piero Toscano,et al.  Urban-Hazard Risk Analysis: Mapping of Heat-Related Risks in the Elderly in Major Italian Cities , 2015, PloS one.

[6]  J. Schwartz,et al.  Mortality risk attributable to high and low ambient temperature: a multicountry observational study , 2015, The Lancet.

[7]  Christoph Aubrecht,et al.  Identification of heat risk patterns in the U.S. National Capital Region by integrating heat stress and related vulnerability. , 2013, Environment international.

[8]  Charles C. Branas,et al.  Urban Green Space and Its Impact on Human Health , 2018, International journal of environmental research and public health.

[9]  E. Kalnay,et al.  Impact of urbanization and land-use change on climate , 2003, Nature.

[10]  N. H. Ravindranath,et al.  Applying IPCC 2014 framework for hazard-specific vulnerability assessment under climate change , 2019, Environmental Research Communications.

[11]  J. Qi,et al.  Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China , 2018, International Journal of Health Geographics.

[12]  Wenjun Ma,et al.  The spatial distribution of health vulnerability to heat waves in Guangdong Province, China , 2014, Global health action.

[13]  David C. Hoaglin,et al.  Some Implementations of the Boxplot , 1989 .

[14]  P. Ciais,et al.  Response to Comment on ``Surface Urban Heat Island Across 419 Global Big Cities'' , 2012 .

[15]  Yuji Murayama,et al.  Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987–2015) , 2017 .

[16]  Joern Birkmann,et al.  Measuring Vulnerability to Natural Hazards: towards disaster resilient societies , 2007 .

[17]  L. Feyen,et al.  Escalating impacts of climate extremes on critical infrastructures in Europe , 2016, Global environmental change : human and policy dimensions.

[18]  V. Masson,et al.  Adapting cities to climate change: A systemic modelling approach , 2014 .

[19]  F. Johnston,et al.  Heatwave and health impact research: A global review , 2018, Health & place.

[20]  J. Patz,et al.  Impact of regional climate change on human health , 2005, Nature.

[21]  Hua Qin,et al.  Urban vulnerability to temperature-related hazards: A meta-analysis and meta-knowledge approach , 2012 .

[22]  H. Wehrden,et al.  Cascades of green: A review of ecosystem-based adaptation in urban areas , 2016 .

[23]  Antonio Gasparrini,et al.  Modeling exposure–lag–response associations with distributed lag non-linear models , 2013, Statistics in medicine.

[24]  S. Perkins‐Kirkpatrick,et al.  Biological responses to the press and pulse of climate trends and extreme events , 2018, Nature Climate Change.

[25]  T. Stocker,et al.  Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of IPCC Intergovernmental Panel on Climate Change , 2012 .

[26]  H. Akbari,et al.  Urban heat island mitigation strategies: a state-of-the-art review on Kuala Lumpur, Singapore and Hong Kong , 2017 .

[27]  Hubert Wiggering,et al.  Indicating ecosystem integrity — theoretical concepts and environmental requirements , 2000 .

[28]  P. Bolund,et al.  Ecosystem services in urban areas , 1999 .

[29]  Yuji Murayama,et al.  Social–ecological status index: A preliminary study of its structural composition and application , 2014 .

[30]  K. Oleson,et al.  Strong contributions of local background climate to urban heat islands , 2014, Nature.

[31]  Thomas L. Saaty,et al.  DECISION MAKING WITH THE ANALYTIC HIERARCHY PROCESS , 2008 .

[32]  J. Sachs,et al.  Sustainable Development Report 2020 , 2021 .

[33]  Mohammad Reza Monazzam,et al.  Weighting Criteria and Prioritizing of Heat stress indices in surface mining using a Delphi Technique and Fuzzy AHP-TOPSIS Method , 2017, Journal of Environmental Health Science and Engineering.

[34]  C. Tucker,et al.  Evidence for a significant urbanization effect on climate in China. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[35]  H. Kan,et al.  Exploring the mechanisms of heat wave vulnerability at the urban scale based on the application of big data and artificial societies. , 2019, Environment international.

[36]  K. Zander,et al.  Perceived heat stress increases with population density in urban Philippines , 2018, Environmental Research Letters.

[37]  Ophelie Drouault Adapt Now: A Global Call for Leadership on Climate Resilience , 2019 .

[38]  Maosheng Zhao,et al.  A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests , 2011 .

[39]  Stef van Buuren,et al.  MICE: Multivariate Imputation by Chained Equations in R , 2011 .

[40]  Takuya Togawa,et al.  A review of quality of life (QOL) assessments and indicators: Towards a “QOL-Climate” assessment framework , 2018, Ambio.

[41]  C. Heaviside,et al.  Potential benefits of cool roofs in reducing heat-related mortality during heatwaves in a European city. , 2019, Environment international.

[42]  Rachel Warren,et al.  Global crop yield response to extreme heat stress under multiple climate change futures , 2014 .

[43]  Andrew J. Tatem,et al.  WorldPop, open data for spatial demography , 2017, Scientific Data.

[44]  Y. Yasuoka,et al.  Assessment with satellite data of the urban heat island effects in Asian mega cities , 2006 .

[45]  Naomi S. Altman,et al.  Points of Significance: Visualizing samples with box plots , 2014, Nature Methods.

[46]  Y. Honda,et al.  Evaluating the Effects of Temperature on Mortality in Manila City (Philippines) from 2006–2010 Using a Distributed Lag Nonlinear Model , 2015, International journal of environmental research and public health.

[47]  Maria Kolokotroni,et al.  Increased Temperature and Intensification of the Urban Heat Island: Implications for Human Comfort and Urban Design , 2007 .

[48]  S. Myint,et al.  Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. , 2017, The Science of the total environment.

[49]  Luis Inostroza,et al.  A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile , 2016, PloS one.

[50]  J. Remedios,et al.  A spatiotemporal analysis of the relationship between near‐surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series , 2017 .

[51]  Naomi S. Altman,et al.  Visualizing samples with box plots. , 2014, Nature methods.

[52]  G. McGregor,et al.  The development of a heat wave vulnerability index for London, United Kingdom , 2013 .

[53]  Lukas H. Meyer,et al.  Summary for Policymakers , 2022, The Ocean and Cryosphere in a Changing Climate.

[54]  Jiaguo Qi,et al.  Spatially Explicit Mapping of Heat Health Risk Utilizing Environmental and Socioeconomic Data. , 2017, Environmental science & technology.

[55]  Y. Murayama,et al.  Urban Development in Asia and Africa: Geospatial Analysis of Metropolises , 2017 .

[56]  Joel Schwartz,et al.  Mapping Community Determinants of Heat Vulnerability , 2008, Environmental health perspectives.

[57]  J. Golden,et al.  Reducing Urban Heat Islands: Compendium of Strategies - Cool Pavements , 2008 .

[58]  E. Gómez‐Baggethun,et al.  Classifying and valuing ecosystem services for urban planning , 2013 .

[59]  S. Juhola,et al.  A systematic review of dynamics in climate risk and vulnerability assessments , 2017 .

[60]  K. Zander,et al.  Human mobility intentions in response to heat in urban South East Asia , 2019, Global Environmental Change.

[61]  M. Maslin,et al.  Adaptation responses to climate change differ between global megacities , 2016 .

[62]  Y. Honda,et al.  Effect modification in the temperature extremes by mortality subgroups among the tropical cities of the Philippines , 2016, Global health action.

[63]  Z. Wan Collection-5 MODIS Land Surface Temperature Products Users' Guide , 2006 .

[64]  Philippines. Statistical Coordination Office Second National Convention on Statistics : Philippine International Convention Center, Metro-Manila, Philippines, December 2-3, 1980 , 1983 .

[65]  E. Hawkins,et al.  Global risk of deadly heat , 2017 .

[66]  Y. Murayama,et al.  A worldwide country-based assessment of social-ecological status (c. 2010) using the social-ecological status index , 2017 .

[67]  Fahim N. Tonmoy,et al.  Assessment of vulnerability to climate change using indicators: a meta‐analysis of the literature , 2014 .

[68]  Erika Upegui,et al.  Mapping heatwave health risk at the community level for public health action , 2012, International Journal of Health Geographics.

[69]  Wei Zhang,et al.  Mapping heat-related health risks of elderly citizens in mountainous area: A case study of Chongqing, China. , 2019, The Science of the total environment.

[70]  T. Oke,et al.  Thermal remote sensing of urban climates , 2003 .

[71]  Steven März,et al.  Assessing the fuel poverty vulnerability of urban neighbourhoods using a spatial multi-criteria decision analysis for the German city of Oberhausen , 2018 .

[72]  Y. Honda,et al.  Effect modification in the temperature extremes by mortality subgroups among the tropical cities of the Philippines. , 2016, Global health action.

[73]  Jean-Luc Salagnac,et al.  Adapting cities to climate Change : a systemic modelling approach , 2015 .

[74]  Antonio Gasparrini,et al.  Distributed Lag Linear and Non-Linear Models in R: The Package dlnm. , 2011, Journal of statistical software.