文章基本信息

标题：EXPLORING AIR QUALITY DATA FROM AN AUTOMATED MONITORING SYSTEM IN AN URBAN-INDUSTRIAL AREA
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作者：Stefania Iordache ; Daniel Dunea
期刊名称：Annals : Food Science and Technology
电子版ISSN：2065-2828
出版年度：2011
卷号：12
期号：1
出版社：Valahia University Press
摘要：The objective of this work was to perform a detailed analysis estimating central tendency, dispersion and distribution patterns for long time series of air pollutants monitored by an automated monitoring station. Descriptive statistics and factor analysis were applied to analyze the relationship between air pollutants measured in Targovi.te urban area between February 2010 and May 2011. Central tendency described the location of the distribution including the mean, median, mode, and sum of all the values. Dispersion measured the amount of variation in the data including the standard deviation, variance, range, minimum and maximum. Distribution was estimated using skewness and kurtosis describing the distribution’s shape and symmetry. The most dispersed variable was the nitrogen oxides time series based on dispersion indicators. The first principal component showed the major influence of industrial emissions that are contributing to the formation of ground level ozone. The second principal component showed the contrast effect between NOx, and PM10, and O3, CO, and SO2. The main variability in the original data (24.90%) was accounted in Factor 1. The second latent factor (Factor 2) explained 20.56% of the data set variability. Ozone had the lowest factor loading in component 1 but after rotation showed a significant increment.gi
关键词：air pollution monitoring; statistical distribution; factor analysisn