title: Ozone trends and their relationship to characteristic weather patterns.
abstract: Local trends in ozone concentration may differ by meteorological conditions. Furthermore, the trends occurring at the extremes of the Ozone distribution are often not reported even though these may be very different than the trend observed at the mean or median and they may be more relevant to health outcomes. Classify days of observation over a 16-year period into broad categories that capture salient daily local weather characteristics. Determine the rate of change in mean and median O3 concentrations within these different categories to assess how concentration trends are impacted by daily weather. Further examine if trends vary for observations in the extremes of the O3 distribution. We used k-means clustering to categorize days of observation based on the maximum daily temperature, standard deviation of daily temperature, mean daily ground level wind speed, mean daily water vapor pressure and mean daily sea-level barometric pressure. The five cluster solution was determined to be the appropriate one based on cluster diagnostics and cluster interpretability. Trends in cluster frequency and pollution trends within clusters were modeled using Poisson regression with penalized splines as well as quantile regression. There were five characteristic groupings identified. The frequency of days with large standard deviations in hourly temperature decreased over the observation period, whereas the frequency of warmer days with smaller deviations in temperature increased. O3 trends were significantly different within the different weather groupings. Furthermore, the rate of O3 change for the 95th percentile and 5th percentile was significantly different than the rate of change of the median for several of the weather categories.We found that O3 trends vary between different characteristic local weather patterns. O3 trends were significantly different between the different weather groupings suggesting an important interaction between changes in prevailing weather conditions and O3 concentration.
authors.affiliation: 1] Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA [2] Department of Environmental and Occupational Health, University of Washington School of Public Health, Seattle, Washington, USA.
authors.forename: Elena
authors.initials: E
authors.lastname: Austin
authors.affiliation: Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA.
authors.forename: Antonella
authors.initials: A
authors.lastname: Zanobetti
authors.affiliation: Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA.
authors.forename: Brent
authors.initials: B
authors.lastname: Coull
authors.affiliation: 1] Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA [2] Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
authors.forename: Joel
authors.initials: J
authors.lastname: Schwartz
authors.affiliation: 1] Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA [2] Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
authors.forename: Diane R
authors.initials: DR
authors.lastname: Gold
authors.affiliation: Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA.
authors.forename: Petros
authors.initials: P
authors.lastname: Koutrakis
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis*; D001900:Boston; D016208:Databases, Factual; D004784:Environmental Monitoring; D006801:Humans; D009589:Nitrogen Oxides / Q000032:analysis; D010126:Ozone / Q000032:analysis*; D016012:Poisson Distribution; D012044:Regression Analysis; D012621:Seasons; D013458:Sulfur Dioxide; D014887:Weather
chemical_list: D000393:Air Pollutants; D009589:Nitrogen Oxides; D013458:Sulfur Dioxide; D010126:Ozone