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      Using self-organizing maps to develop ambient air quality classifications: a time series example


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          Development of exposure metrics that capture features of the multipollutant environment are needed to investigate health effects of pollutant mixtures. This is a complex problem that requires development of new methodologies.


          Present a self-organizing map (SOM) framework for creating ambient air quality classifications that group days with similar multipollutant profiles.


          Eight years of day-level data from Atlanta, GA, for ten ambient air pollutants collected at a central monitor location were classified using SOM into a set of day types based on their day-level multipollutant profiles. We present strategies for using SOM to develop a multipollutant metric of air quality and compare results with more traditional techniques.


          Our analysis found that 16 types of days reasonably describe the day-level multipollutant combinations that appear most frequently in our data. Multipollutant day types ranged from conditions when all pollutants measured low to days exhibiting relatively high concentrations for either primary or secondary pollutants or both. The temporal nature of class assignments indicated substantial heterogeneity in day type frequency distributions (~1%-14%), relatively short-term durations (<2 day persistence), and long-term and seasonal trends. Meteorological summaries revealed strong day type weather dependencies and pollutant concentration summaries provided interesting scenarios for further investigation. Comparison with traditional methods found SOM produced similar classifications with added insight regarding between-class relationships.


          We find SOM to be an attractive framework for developing ambient air quality classification because the approach eases interpretation of results by allowing users to visualize classifications on an organized map. The presented approach provides an appealing tool for developing multipollutant metrics of air quality that can be used to support multipollutant health studies.

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          Most cited references12

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          Protecting human health from air pollution: shifting from a single-pollutant to a multipollutant approach.

          To date, the assessment of public health consequences of air pollution has largely focused on a single-pollutant approach aimed at estimating the increased risk of adverse health outcomes associated with the exposure to a single air pollutant, adjusted for the exposure to other air pollutants. However, air masses always contain many pollutants in differing amounts, depending on the types of emission sources and atmospheric conditions. Because humans are simultaneously exposed to a complex mixture of air pollutants, many organizations have encouraged moving towards "a multipollutant approach to air quality." Although there is general agreement that multipollutant approaches are desirable, the challenges of implementing them are vast.
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            Cardiovascular effects associated with air pollution: potential mechanisms and methods of testing.

            A recent series of epidemiologic reports have shown associations between fine particulate matter (PM) levels and increased cardiovascular morbidity and mortality. Elevated PM levels have been linked with cardiac events, including serious ventricular arrhythmias and myocardial infarction. A workshop brought together epidemiologists, cardiologists, and toxicologists from academia, government, and industry to examine plausible mechanisms that could be responsible for such effects, and to consider the armamentarium of noninvasive tests available to examine these relationships. Possible mechanisms considered by the participants include: (a) effects on the autonomic nervous system; (b) alterations on ion channel function in myocardial cells; (c) ischemic responses in the myocardium; and (d) inflammatory responses triggering endothelial dysfunction, atherosclerosis, and thrombosis. A large number of tests were identified to assess specific mechanistic pathways underlying the cardiovascular effects of air pollution and include: (a) autonomic control of the cardiovascular system assessed primarily by heart-rate variability; (b) myocardial substrate and vulnerability assessed by the electrocardiogram and estimations of ejection fraction and wall motion abnormalities in imaging studies; and (c) endothelial function, atherosclerosis, and thrombosis assessed by clotting parameters, cytokines, lipid profiles, and forearm blood flow. A variety of approaches ranging from molecular and genetic investigations to human clinical studies were recommended to further investigate the important epidemiologic associations.
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              Is the air pollution health research community prepared to support a multipollutant air quality management framework?

              Ambient air pollution is always encountered as a complex mixture, but past regulatory and research strategies largely focused on single pollutants, pollutant classes, and sources one-at-a-time. There is a trend toward managing air quality in a progressively "multipollutant" manner, with the idealized goal of controlling as many air contaminants as possible in an integrated manner to achieve the greatest total reduction of adverse health and environmental impacts. This commentary considers the current ability of the environmental air pollution exposure and health research communities to provide evidence to inform the development of multipollutant air quality management strategies and assess their effectiveness. The commentary is not a literature review, but a summary of key issues and information gaps, strategies for filling the gaps, and realistic expectations for progress that could be made during the next decade. The greatest need is for researchers and sponsors to address air quality health impacts from a truly multipollutant perspective, and the most limiting current information gap is knowledge of personal exposures of different subpopulations, considering activities and microenvironments. Emphasis is needed on clarifying the roles of a broader range of pollutants and their combinations in a more forward-looking manner; that is not driven by current regulatory structures. Although advances in research tools and outcome data will enhance progress, the greater need is to direct existing capabilities toward strategies aimed at placing into proper context the contributions of multiple pollutants and their combinations to the health burdens, and the relative contributions of pollutants and other factors influencing the same outcomes. The authors conclude that the research community has very limited ability to advise multipollutant air quality management and assess its effectiveness at this time, but that considerable progress can be made in a decade, even at current funding levels, if resources and incentives are shifted appropriately.

                Author and article information

                Environ Health
                Environ Health
                Environmental Health
                BioMed Central
                3 July 2014
                : 13
                : 56
                [1 ]Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
                [2 ]Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
                [3 ]School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
                Copyright © 2014 Pearce et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                : 15 January 2014
                : 23 June 2014

                Public health
                air pollution,classification,cluster analysis,kohonen map
                Public health
                air pollution, classification, cluster analysis, kohonen map


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