Ozone trends and their relationship to characteristic weather patterns.
Ozone trends and their relationship to characteristic weather patterns.
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DOI：
10.1038/jes.2014.45
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发表时间：
2015-09
影响因子：
4.5
通讯作者：
Koutrakis P
中科院分区：
文献类型：
--
作者：
Austin E;Zanobetti A;Coull B;Schwartz J;Gold DR;Koutrakis P
臭氧浓度的局部趋势可能因气象条件而异。此外，臭氧分布极端情况下出现的趋势往往没有报告，即使这些趋势可能与平均值或中位数时观察到的趋势有很大不同，而且它们可能与健康结果更相关。将16年期间的观测日分为几大类，以捕捉当地每日显著的天气特征。确定这些不同类别中平均和中值O3浓度的变化率，以评估浓度趋势如何受到日常天气的影响。进一步检查O3分布极值中的观察结果是否存在趋势变化。我们使用k-means聚类的基础上，最高日温度，日温度的标准差，平均日地面风速，平均日水汽压和平均日海平面气压的观测日进行分类。基于聚类诊断和聚类可解释性，五聚类解决方案被确定为合适的解决方案。集群频率和集群内的污染趋势的趋势进行了建模，使用泊松回归与惩罚样条以及分位数回归。确定了五个特征分组。在观测期间，每小时温度标准差较大的天数频率下降，而温度偏差较小的温暖天数频率增加。O3的趋势显着不同的天气分组内。此外，第95百分位数和第5百分位数的O3变化率与几种天气类别的中位数变化率有显著差异。我们发现，O3的趋势在不同的当地天气模式之间存在差异。O3的趋势显着不同的天气组之间的主要天气条件和O3浓度的变化之间的相互作用表明一个重要的。
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.