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Journal Article

Citation

Christenson E, Elliott M, Banerjee O, Hamrick L, Bartram J. Int. J. Environ. Res. Public Health 2014; 11(2): 2169-2192.

Affiliation

The Water Institute, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27516, USA. jbartram@unc.edu.

Copyright

(Copyright © 2014, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph110202169

PMID

24566046

PMCID

PMC3945591

Abstract

Global climate change (GCC) has led to increased focus on the occurrence of, and preparation for, climate-related extremes and hazards. Population exposure, the relative likelihood that a person in a given location was exposed to a given hazard event(s) in a given period of time, was the outcome for this analysis. Our objectives were to develop a method for estimating the population exposure at the country level to the climate-related hazards cyclone, drought, and flood; develop a method that readily allows the addition of better datasets to an automated model; differentiate population exposure of urban and rural populations; and calculate and present the results of exposure scores and ranking of countries based on the country-wide, urban, and rural population exposures to cyclone, drought, and flood. Gridded global datasets on cyclone, drought and flood occurrence as well as population density were combined and analysis was carried out using ArcGIS.

RESULTS presented include global maps of ranked country-level population exposure to cyclone, drought, flood and multiple hazards. Analyses by geography and human development index (HDI) are also included. The results and analyses of this exposure assessment have implications for country-level adaptation. It can also be used to help prioritize aid decisions and allocation of adaptation resources between countries and within a country. This model is designed to allow flexibility in applying cyclone, drought and flood exposure to a range of outcomes and adaptation measures.


Language: en

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