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      A Spatial Framework to Map Heat Health Risks at Multiple Scales

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          Abstract

          In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G i index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G i index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.

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          Most cited references56

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          The Analysis of Spatial Association by Use of Distance Statistics

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            Heat Waves in the United States: Mortality Risk during Heat Waves and Effect Modification by Heat Wave Characteristics in 43 U.S. Communities

            Background Devastating health effects from recent heat waves, and projected increases in frequency, duration, and severity of heat waves from climate change, highlight the importance of understanding health consequences of heat waves. Objectives We analyzed mortality risk for heat waves in 43 U.S. cities (1987–2005) and investigated how effects relate to heat waves’ intensity, duration, or timing in season. Methods Heat waves were defined as ≥ 2 days with temperature ≥ 95th percentile for the community for 1 May through 30 September. Heat waves were characterized by their intensity, duration, and timing in season. Within each community, we estimated mortality risk during each heat wave compared with non-heat wave days, controlling for potential confounders. We combined individual heat wave effect estimates using Bayesian hierarchical modeling to generate overall effects at the community, regional, and national levels. We estimated how heat wave mortality effects were modified by heat wave characteristics (intensity, duration, timing in season). Results Nationally, mortality increased 3.74% [95% posterior interval (PI), 2.29–5.22%] during heat waves compared with non-heat wave days. Heat wave mortality risk increased 2.49% for every 1°F increase in heat wave intensity and 0.38% for every 1-day increase in heat wave duration. Mortality increased 5.04% (95% PI, 3.06–7.06%) during the first heat wave of the summer versus 2.65% (95% PI, 1.14–4.18%) during later heat waves, compared with non-heat wave days. Heat wave mortality impacts and effect modification by heat wave characteristics were more pronounced in the Northeast and Midwest compared with the South. Conclusions We found higher mortality risk from heat waves that were more intense or longer, or those occurring earlier in summer. These findings have implications for decision makers and researchers estimating health effects from climate change.
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              The physiological equivalent temperature - a universal index for the biometeorological assessment of the thermal environment.

              P Hoppe (1999)
              With considerably increased coverage of weather information in the news media in recent years in many countries, there is also more demand for data that are applicable and useful for everyday life. Both the perception of the thermal component of weather as well as the appropriate clothing for thermal comfort result from the integral effects of all meteorological parameters relevant for heat exchange between the body and its environment. Regulatory physiological processes can affect the relative importance of meteorological parameters, e.g. wind velocity becomes more important when the body is sweating. In order to take into account all these factors, it is necessary to use a heat-balance model of the human body. The physiological equivalent temperature (PET) is based on the Munich Energy-balance Model for Individuals (MEMI), which models the thermal conditions of the human body in a physiologically relevant way. PET is defined as the air temperature at which, in a typical indoor setting (without wind and solar radiation), the heat budget of the human body is balanced with the same core and skin temperature as under the complex outdoor conditions to be assessed. This way PET enables a layperson to compare the integral effects of complex thermal conditions outside with his or her own experience indoors. On hot summer days, for example, with direct solar irradiation the PET value may be more than 20 K higher than the air temperature, on a windy day in winter up to 15 K lower.
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                18 December 2015
                December 2015
                : 12
                : 12
                : 16110-16123
                Affiliations
                [1 ]Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
                [2 ]Department of Geography, Earth and Environmental Sciences, Okanagan College, Kelowna, BC V1Y 4X8, Canada
                [3 ]Department of Geography, University of Ottawa, ON, K1N 6N5, Canada; aknudby@ 123456uottawa.ca
                [4 ]Department of Geography, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA; weihuang@ 123456uwm.edu
                Author notes
                [* ]Correspondence: hohungh@ 123456sfu.ca ; Tel. +1-778-782-4556; Fax: +1-778-782-5841
                Article
                ijerph-12-15046
                10.3390/ijerph121215046
                4690982
                26694445
                9216fe2e-9ecb-47ef-b9fc-0d2c165a6118
                © 2015 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 27 October 2015
                : 15 December 2015
                Categories
                Article

                Public health
                heat risk,modifiable areal unit problem,heat vulnerability,extremely hot weather event

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