Multivariate analysis of respiratory problems and their connection with meteorological parameters and the main biological and chemical air pollutants
Multivariate analysis of respiratory problems and their connection with meteorological parameters and the main biological and chemical air pollutants
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DOI：
10.1016/j.atmosenv.2011.05.024
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发表时间：
2011-08-01
影响因子：
5
通讯作者：
Suemeghy, Zoltan
中科院分区：
文献类型：
--
作者：
Matyasovszky, Istvan;Makra, Laszlo;Suemeghy, Zoltan
这项研究的目的是分析生物(花粉)和化学空气污染物以及气象变量对匈牙利南部Szeged地区呼吸问题住院人数的联合影响。使用的数据集涵盖九年(1999-2007年)，其独特之处在于，它不仅包括CO、PM10、NO、NO2、O-3和SO2的每小时平均浓度和气象变量(温度、全球太阳通量、相对湿度、气压和风速)，而且还包括两个花粉变量(仙人掌和不包括仙人掌的总花粉)。对豚草的花粉季节和无花粉季节的三个年龄段进行了分析。气象要素和空气污染物被聚集在一起，以确定高患者数量的最佳环境条件。然后使用方差分析来确定与集群相关的平均患者数量是否存在显着差异。此外，还应用了两种新的方法：包括特殊变换的因子分析和时变多元线性回归，它使得确定影响呼吸系统住院的影响变量的重要性以及计算影响呼吸系统疾病的参数的相对重要性成为可能。这两种技术都表明，仙人掌花粉是影响入院人数的一个重要变量(每增加10个花粉粒m(-3)就意味着患者数量增加约24%)。化学和气象参数的作用也很大，但它们的权重因季节和方法而异。对豚草的传粉季节进行了较为清晰的研究。在这里，O-3增加10微克m(-3)意味着患者数量反应从-17%增加到+11%。风速是一个令人惊讶的重要变量，S(-1)每上升1米，住院人数可能会减少42-45%。(C)2011爱思唯尔有限公司。保留所有权利。
The aim of the study is to analyse the joint effect of biological (pollen) and chemical air pollutants, as well as meteorological variables, on the hospital admissions of respiratory problems for the Szeged region in Southern Hungary. The data set used covers a nine-year period (1999-2007) and is unique in the sense that it includes-besides the daily number of respiratory hospital admissions-not just the hourly mean concentrations of CO, PM10, NO, NO2, O-3 and SO2 with meteorological variables (temperature, global solar flux, relative humidity, air pressure and wind speed), but two pollen variables (Ambrosia and total pollen excluding Ambrosia) as well. The analysis was performed using three age categories for the pollen season of Ambrosia and the pollen-free season. Meteorological elements and air pollutants are clustered in order to define optimum environmental conditions of high patient numbers. ANOVA was then used to determine whether cluster-related mean patient numbers differ significantly. Furthermore, two novel procedures are applied here: factor analysis including a special transformation and a time-varying multivariate linear regression that makes it possible to determine the rank of importance of the influencing variables in respiratory hospital admissions, and also compute the relative importance of the parameters affecting respiratory disorders. Both techniques revealed that Ambrosia pollen is an important variable that influences hospital admissions (an increase of 10 pollen grains m(-3) can imply an increase of around 24% in patient numbers). The role of chemical and meteorological parameters is also significant, but their weights vary according to the seasons and the methods. Clearer results are obtained for the pollination season of Ambrosia. Here, a 10 mu g m(-3) increase in O-3 implies a patient number response from -17% to +11%. Wind speed is a surprisingly important variable, where a 1 m s(-1) rise may result in a hospital admission reduction of up to 42-45%. (C) 2011 Elsevier Ltd. All rights reserved.