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Cluster analysis of variations in the diurnal pattern of grass pollen concentrations in Northern Europe (Copenhagen) and Southern Europe (Cordoba)

机译:北欧(哥本哈根)和南欧(科尔多瓦)草花粉浓度日变化规律的聚类分析

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From an allergological point of view, Poaceae pollen is one of the most important types of pollen that the population is exposed to in the ambient environment. There are several studies on intra-diurnal patterns in grass pollen concentrations and agreement on the high variability. However, the method for analysing the different patterns is not yet well established. The aim of the present study is therefore to examine the method of pattern analysis by statistical clustering, and to relate the proposed patterns to time of season and meteorological variables at two highly different biogeographical locations: Cordoba, Spain, and Copenhagen, Denmark. Airborne pollen is collected by Hirst-type volumetric spore traps and counted using an optical microscope at both sites. The counts were converted to 2-h concentrations, and a new method based on cluster analysis was applied with the aim of determining the most frequent diurnal patterns in pollen concentrations and their dependencies on site, season and meteorological variables. Three different well-defined diurnal patterns were identified at both locations. The most frequent pattern in Copenhagen was associated with days having peak pollen concentrations in the evening (maximum between 18 and 20h), whereas the most frequent pattern at Cordoba was associated with days having peak pollen concentrations in the afternoon (maximum between 14 and 16h). These three patterns account for 70% of days with no rain and pollen concentrations above 20grainsm(-3). The most frequent pattern accounts for 40% and 57% of the days in Cordoba and Copenhagen, respectively. The analysis clearly shows the great variation in pollen concentration pattern, albeit a dominating pattern can be found. It was not possible to explain all the differences in the patterns by the meteorological variables when examined individually. Clustering method is estimated to be an appropriate methodology for studying aerobiological phenomena with high variability.
机译:从变应学的角度来看,禾本科花粉是人群在周围环境中所接触的最重要的花粉类型之一。关于草粉花粉浓度的日内模式以及高变异性的协议已有几项研究。但是,尚未很好地建立用于分析不同模式的方法。因此,本研究的目的是通过统计聚类来检验模式分析的方法,并将拟议的模式与两个高度不同的生物地理位置(西班牙的科尔多瓦和丹麦的哥本哈根)的季节时间和气象变量联系起来。空气中的花粉通过Hirst型体积孢子阱收集,并在两个位置使用光学显微镜进行计数。将计数转换为2 h浓度,并应用基于聚类分析的新方法,旨在确定花粉浓度中最​​常见的昼夜模式及其对站点,季节和气象变量的依赖性。在两个位置都确定了三种不同的明确的昼夜模式。哥本哈根最频繁的模式与傍晚花粉浓度最高的日子有关(最大为18至20h),而科尔多瓦的最频繁的模式与下午花粉浓度最高的日子有关(最大为14至16h) 。这三种模式占70%的日子,没有降雨,花粉浓度高于20grainsm(-3)。在科尔多瓦和哥本哈根,最频繁的旅行分别占40%和57%。分析清楚地表明花粉浓度模式有很大的变化,尽管可以找到主要模式。当单独检查时,不可能通过气象变量解释模式的所有差异。估计聚类方法是研究高变异性航空生物学现象的合适方法。

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