Residential Traffic and Children’s Respiratory Health
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BackgroundLiving near traffic has been associated with asthma and other respiratory symptoms. Most studies, however, have been conducted in areas with high background levels of ambient air pollution, making it challenging to isolate an independent effect of traffic. Additionally, most investigations have used surrogates of exposure, and few have measured traffic pollutants directly as part of the study.ObjectiveWe conducted a cross-sectional study of current asthma and other respiratory symptoms in children (n = 1,080) living at varying distances from high-traffic roads in the San Francisco Bay Area, California, a highly urbanized region characterized by good regional air quality due to coastal breezes.MethodsWe obtained health information and home environmental factors by parental questionnaire. We assessed exposure with several measures of residential proximity to traffic calculated using geographic information systems, including traffic within a given radius and distance to major roads. We also measured traffic-related pollutants (nitrogen oxides and nitrogen dioxide) for a subset of households to determine how well traffic metrics correlated with measured traffic pollutants.ResultsUsing multivariate logistic regression analyses, we found associations between current asthma and residential proximity to traffic. For several traffic metrics, children whose residences were in the highest quintile of exposure had approximately twice the adjusted odds of current asthma (i.e., asthma episode in the preceeding 12 months) compared with children whose residences were within the lowest quintile. The highest risks were among those living within 75 m of a freeway/highway. Most traffic metrics correlated moderately well with actual pollutant measurements.ConclusionOur findings provide evidence that even in an area with good regional air quality, proximity to traffic is associated with adverse respiratory health effects in children.Keywords:
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In the existing environmental air quality evaluation index system, the AQI depends on the concentration of the dominant pollutant in the six types of air pollutants. However, the interaction among different pollutants and the effect of the combination of pollutants on AQI is rarely studied. In this paper, concentrations of six types of air pollutants and corresponding AQI of Tianjin in 2018 were taken as samples, and trained by Choquet integral. The Shapley interaction index of six types of pollutants are obtained by nonadditive measure. Based on the Shapley interaction index, the weights of six air pollutants on AQI and the interaction among different pollutants were analyzed. The results show that the main air pollutants in Tianjin in 2018 are PM2.5 and O 3 , and there is a negative interaction between them. Finally, the trained model is used to recalculate AQI of Tianjin in the first three months of 2019, providing a reference for air quality evaluation.
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