Constructing representative air quality indicators with measures of uncertainty
作者： Duncan Lee , Claire Ferguson , E. Marian Scott
DOI: 10.1111/J.1467-985X.2010.00658.X
关键词: Pollutant 、 Air quality index 、 Spatial aggregation 、 Preferential sampling 、 Pollution 、 Stage (hydrology) 、 Econometrics 、 Sample mean and sample covariance 、 Environmental science 、 Urban area 、 Statistics
摘要: Summary. Air quality indicators summarize overall concentrations of pollution for an urban area and are calculated from routine monitoring data comprising numerous pollutants measured at many locations. The indicator is constructed by aggregating these over space pollutants, typically using the sample mean, median or maximum. We propose alternative approach based on geostatistical modelling, which allows intervals uncertainty to be spatial aggregation stage, hence final indicator. then extend our model allowing fact that locations chosen monitors may depend hypothesized locations, a phenomenon known as preferential sampling. assess effectiveness methods simulation use them construct air Greater London, England, month August 2006.
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