Mapping alternatives for public policy decision making related to human exposures from air pollution sources in the Federal District, Brazil

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• 作者：Weeberb J. Requia^a ; ^{weeberb@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Henrique Llacer Roig^b ; ^{roig@unb.br" class="auth_mail" title="E-mail the corresponding author} ; Petros Koutrakis^c ; ^{petros@hsph.harvard.edu" class="auth_mail" title="E-mail the corresponding author} ; Maria Silvia Rossi^d ; ^{mariasilvia.semadf@gmail.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Mapping ; Human exposures ; Air pollution sources ; Public policy ; Decision-making
• 刊名：Land Use Policy
• 出版年：2016
• 出版时间：31 December 2016
• 年：2016
• 卷：59
• 期：Complete
• 页码：375-385
• 全文大小：3034 K

文摘

Several studies have assessed air pollution risks to guide environmental and public health policies. However, most studies have proposed risk management actions that address a specific situation. To our knowledge, no studies have investigated the spatial distribution of risks to evaluate alternatives for environmental public policies. Therefore, this study had two specific aims. The first was to map human exposures to emissions from air pollution sources in the Federal District, Brazil. The second was to create and map the alternatives for public policies related to human exposures. For this study, we used the following approaches: techniques in Geographic Information System (GIS); multicriteria model – Analytic Hierarchy Process (AHP); and, Fuzzy logic. Our findings suggest that vehicle traffic control and public transportation development are the most effective alternatives with weights equal to 0.318 and 0.332, respectively. The estimated weights for land use management and new green areas are equal to 0.179 and 0.171, respectively. Vehicle traffic, population density, illegal urban settlements, economic activities and daily flux of people (origin and destination) were the main factors determining the spatial distribution of each alternative. This proposed analytical framework may be of interest to policy makers seeking to minimize costs for designing and evaluating effective public policies.