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132 timeVariationAuthor(s)David CarslawSee AlsopolarPlot, linearRelationExamples# basic usetimeVariation(mydata, pollutant = "nox")# for a subset of conditionstimeVariation(subset(mydata, ws > 3 & wd > 100 & wd < 270),pollutant = "pm10", ylab = "pm10 (ug/m3)")# multiple pollutants with concentrations normalised## Not run: timeVariation(mydata, pollutant = c("nox", "co"), normalise = TRUE)# show BST/GMT variation (see ?cutData for more details)# the NOx plot shows the profiles are very similar when expressed in# local time, showing that the profile is dominated by a local source# that varies by local time and not by GMT i.e. road vehicle emissions## Not run: timeVariation(mydata, pollutant = "nox", type = "gmtbst")## In this case it is better to group the results for clarity:## Not run: timeVariation(mydata, pollutant = "nox", group = "gmtbst")# By contrast, a variable such as wind speed shows a clear shift when# expressed in local time. These two plots can help show whether the# variation is dominated by man-made influences or natural processes## Not run: timeVariation(mydata, pollutant = "ws", group = "gmtbst")## It is also possible to plot several variables and set type. For## example, consider the NOx and NO2 split by levels of O3:## Not run: timeVariation(mydata, pollutant = c("nox", "no2"), type = "o3", normalise = TRUE)## difference in concentrationstimeVariation(mydata, poll= c("pm25", "pm10"), difference = TRUE)# It is also useful to consider how concentrations vary by# considering two different periods e.g. in intervention# analysis. In the following plot NO2 has clearly increased but much# less so at weekends - perhaps suggesting vehicles other than cars# are important because flows of cars are approximately invariant by# day of the week## Not run:mydata
trajCluster 133timeVariation(mydata, pollutant = "no2", group = "split.by", difference = TRUE)## End(Not run)## sub plots can be extracted from the openair object## Not run:myplot
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Package ‘openair’September 19,
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4 aqStatsused. All functions check
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6 calcFno2Examples## Statistics for
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8 calcPercentilecalcPercentileCalcu
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10 calendarPlotannotatestatisticcol
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14 conditionalEvalon to cutData to
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16 conditionalQuantileArgumentsmyda
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18 corPlot## make some dummy predic
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20 cutDataSee Alsotaylor.diagram fr
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22 drawOpenKeyof this option is to
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24 drawOpenKeyvpView port to be use
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26 GoogleMapsPlotcex.range = c(2, 1
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28 GoogleMapsPlotDetailsValueNoteke
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30 importtimetime.formattz.intz.out
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32 importADMSdrop.input.datesOption
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34 importAURNimportAURNAURN data im
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36 importAURN• BIR2 Birmingham Ea
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38 importAURN• ISL London Islingt
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40 importAURNValue• WBRO Sandwell
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42 importAURNCsvis.siteHeader name
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44 importKCL## diurnal.error(so2.15
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46 importKCLAll PM10 statistics on
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48 importKCL• BY1 | Bromley - Ren
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50 importKCL• GL1 | Glasgow Centr
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52 importKCL• LB4 | Lambeth - Bri
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54 importKCL• RG4 | Reigate and B
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56 importKCL• TE0 | Tendring St O
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58 importKCLValue• ZT4 | Tunbridg
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60 importSAQNExamples## import AQ d
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62 importSAQN• | ABD8 | Aberdeen
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64 importSAQN• | PAI3 | Paisley G
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66 importTrajlocalfor example.Used
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68 kernelExceedpollutant Mandatory.
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70 linearRelationlinearRelationLine
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72 modStatsSee AlsocalcFno2Examples
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74 mydataReferencesWillmott, C.J.,
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76 openair.class## S3 method for cl
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78 openColoursnNote that because of
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80 percentileRoseintervals User-sup
Page 82 and 83: 82 polarAnnulusnormalise = FALSE, k
Page 84 and 85: 84 polarAnnuluskey.footerkey.positi
Page 86 and 87: 86 polarClustercolsDetailsangle.sca
Page 88 and 89: 88 polarFreq## how many points are
Page 90 and 91: 90 polarFreqborder.colThe colour of
Page 92 and 93: 92 polarPlotDescriptionFunction for
Page 94 and 95: 94 polarPlotupperangle.scaleunitsso
Page 96 and 97: 96 polarPlotValueAs well as generat
Page 98 and 99: 98 rollingMeanExamples#example 1##s
Page 100 and 101: 100 scatterPlotavg.timedata.threshs
Page 102 and 103: 102 scatterPlot... Other graphical
Page 104 and 105: 104 selectByDate## multiple types a
Page 106 and 107: 106 selectRunningselectRunningFunct
Page 108 and 109: 108 smoothTrendavg.timepercentileda
Page 110 and 111: 110 splitByDate# several pollutants
Page 112 and 113: 112 summaryPlotpollutantperiodbreak
Page 114 and 115: 114 TaylorDiagramUsageTaylorDiagram
Page 116 and 117: 116 TaylorDiagramdaylight/nighttime
Page 118 and 119: 118 TheilSen## Not run:## all model
Page 120 and 121: 120 TheilSenDetailsdate.breaks- 1)
Page 122 and 123: 122 timeAverageTheilSen(mydata, pol
Page 124 and 125: 124 timePlotAuthor(s)David CarslawS
Page 126 and 127: 126 timePlottypecolsplot.typekeylog
Page 128 and 129: 128 timePlotAuthor(s)David CarslawS
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Page 134 and 135: 134 trajClustertypecolssplit.aftert
Page 136 and 137: 136 trajLevelsmoothstatisticpercent
Page 138 and 139: 138 trendLevelkc1 -20 & lon 40 & l
Page 140 and 141: 140 trendLeveldrop.unused.typesHide
Page 142 and 143: 142 windRosews.intThe Wind speed in
Page 144 and 145: 144 windRoseValueNoteset of wind sp
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