README.md
In JustinLingard/rlaqn: Data retrieval from the London Air API
rlaqn: Data retrieval from the London Air API
Justin Lingard : prejjnl@gmail.com
Overview
rlaqn allows retrieval of data from the London Air API, the data feed of the London Air Quality Network, operated by the Environemntal Research Group (ERG) at King's College London (KCL). The API provides a structured and convenient way to interact with the data from the LAQN. Data is supplied in JSON format.
Similar packages
openair which provides open-source tools for the analysis of air pollution dataropenaq which provides UK-AIR latest measured levels (see https://uk-air.defra.gov.uk/latest/currentlevels) as well as data from other countriesrdefra which allows retrieval of air pollution data from the Defra's UK Air Information Resource (UK-AIR).
Dependencies
The rlaqn package depends some additional CRAN packages. Check for missing dependencies and install them using the commands below:
> packs <- c('dplyr', 'ggplot2', 'jsonlite', 'leaflet', 'pander')
> new.packages <- packs[!(packs %in% installed.packages()[, 'Package'])]
> if(length(new.packages)) install.packages(new.packages)
Installation
Install the development version from github using devtools:
> devtools::install_github('JustinLingard/rlaqn')
Load the rlaqn package:
> library('rlaqn')
Functions
get_laqn_aq_objectives
get_laqn_aq_objectives imports pre-calculated air quality objectives (statistics) for air pollutants for which national air quality objectives exist, for each station in the LAQN, from the London Air API:
- carbon monoxide, CO
- nitrogen dioxide, NO2
- ozone, O3
- sulphur dioxide, SO2, and
- particulate matter, PM10.
Statistics are calculated for each air quality monitoring station in the LAQN on a year-by-year basis. Statistics are available from the inception of the network in 1993, when it was composed of a few stations, to the much larger, current day network. The use of pre-calculated statistics removes the need to caluclate these metrics from raw, hourly data, and ensures good consistency with published data.
NOx (nitrogen oxides) and PM2.5 statistics are not currently available, but if generated in future, should be picked-up by the function.
Note: Ratification of the underlying air quality monitoring data, from which the statistics are calculated, is undertaken three to six months in arrears. Subsequently, statistics for the current year can vary over time and should be viewed as provisional statistics (awaiting final ratification).
Pre-calculated air quality statistics from the London Air API are comparable to those shown under the air quality objective values and capture rates on the Annual Air Quality Report for each air quality monitoring station in the LAQN, c.f., Annual Air Quality Report for Westminster - Marylebone Road (01/01/2015 to 01/01/2016).
Site meta data for past and current air quality monitoring station in the LAQN can be obtained using the get_laqn_sites function, as decsribed below.
> get_laqn_aq_objectives <- function (theGroup = "London", metric = "Annual",
data_type = "MonitoringObjective",
dates = 1980, datee = as.numeric(format(Sys.Date(), "%Y")),
api_type = "Json")
Running:
> aq_objectives <- get_laqn_aq_objectives()
returns all the air quality objectives since the inception of the network, even when the start year (dates) is set to 1980 (before the network came into existence). No data is retured for years where there is no data available and the function will just return an error message before moving onto the next year.
> head(aq_objectives)
SiteCode SiteName SiteType Latitude Longitude LatitudeWGS84
1 BG1 Barking and Dagenham - Rush Green Suburban 51.563752 0.177891 6721627.34498
2 BG1 Barking and Dagenham - Rush Green Suburban 51.563752 0.177891 6721627.34498
3 BL0 Camden - Bloomsbury Urban Background 51.522287 -0.125848 6714205.47041
4 BL0 Camden - Bloomsbury Urban Background 51.522287 -0.125848 6714205.47041
5 BL0 Camden - Bloomsbury Urban Background 51.522287 -0.125848 6714205.47041
6 BL0 Camden - Bloomsbury Urban Background 51.522287 -0.125848 6714205.47041
LongitudeWGS84 SiteLink
1 19802.7355367 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BG1
2 19802.7355367 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BG1
3 -14009.3352774 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BL0
4 -14009.3352774 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BL0
5 -14009.3352774 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BL0
6 -14009.3352774 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BL0
DataOwner DataManager SpeciesCode SpeciesDescription
1 Barking and Dagenham King's College London NO2 Nitrogen Dioxide
2 Barking and Dagenham King's College London SO2 Sulphur Dioxide
3 Department for Environment Food and Rural Affairs King's College London CO Carbon Monoxide
4 Department for Environment Food and Rural Affairs King's College London NO2 Nitrogen Dioxide
5 Department for Environment Food and Rural Affairs King's College London NO2 Nitrogen Dioxide
6 Department for Environment Food and Rural Affairs King's College London NO2 Nitrogen Dioxide
Year ObjectiveName Value Achieved
1 1993 Capture Rate (%) 31 YES
2 1993 Capture Rate (%) 30 YES
3 1993 Capture Rate (%) 82 YES
4 1993 200 ug/m3 as a 1 hour mean, not to be exceeded more than 18 times a year 5 YES
5 1993 40 ug/m3 as an annual mean 65 NO
6 1993 Capture Rate (%) 93 YES
get_laqn_sites
Site meta data, for each past and current air quality monitoring station in the LAQN, can be obtained using the get_laqn_sites function, e.g.,
> laqn_sites <- get_laqn_sites()
> head(laqn_sites)
LocalAuthorityCode LocalAuthorityName SiteCode SiteName
1 1 Barking and Dagenham BG3 Barking and Dagenham - North Street
2 1 Barking and Dagenham BG1 Barking and Dagenham - Rush Green
3 1 Barking and Dagenham BG2 Barking and Dagenham - Scrattons Farm
4 2 Barnet BN2 Barnet - Finchley
5 2 Barnet BN3 Barnet - Strawberry Vale
6 2 Barnet BN1 Barnet - Tally Ho Corner
SiteType DateClosed DateOpened Latitude Longitude
1 Kerbside 2011-05-25 00:00:00 2007-03-16 00:00:00 51.540444 0.074418
2 Suburban 1999-11-02 00:00:00 51.563752 0.177891
3 Suburban 1999-10-17 00:00:00 51.529389 0.132857
4 Urban Background 2012-04-20 00:00:00 2000-08-09 13:00:00 51.591901 -0.205992
5 Urban Background 2002-05-15 00:00:00 2000-08-14 14:00:00 51.6008848453589 -0.172297542087178
6 Kerbside 2012-04-20 00:00:00 1998-12-20 12:00:00 51.614675 -0.176607
LatitudeWGS84 LongitudeWGS84 DataOwner DataManager
1 6717454.5833 8284.17386585 Barking and Dagenham King's College London
2 6721627.34498 19802.7355367 Barking and Dagenham King's College London
3 6715476.18683 14789.5735883 Barking and Dagenham King's College London
4 6726669.62886 -22930.9245475 Barnet King's College London
5 6728279.54795 -19180.0746501 Barnet King's College London
6 6730751.38494 -19659.8013105 Barnet King's College London
SiteLink
1 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG3
2 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG1
3 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG2
4 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BN2
5 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BN3
6 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BN1
Comparison of the output from get_laqn_sites with importMeta(source = "kcl", all = TRUE) from the openair package reveals some differences. importMeta returns the meta data for all air quality monitoring sites operated by KCL, including those outside London, e.g., those in the UK Black Carbon network, and other local authority networks.
> kcl_sites <- openair::importMeta(source = "kcl", all = TRUE)
> head(kcl_sites)
code site Address la_id
1 ST1 Sutton - Robin Hood School Robin Hood Junior School, Thorncroft Road, Sutton 29
2 RY1 Rother - Rye Harbour Rye Harbour 211
3 SB1 South Beds - Dunstable Dunstable, South Beds 150
4 EL1 Elmbridge - Bell Farm Hersham Bell Farm, Hersham 44
5 EL2 Elmbridge - Esher High Street Esher High Street 44
6 CT6 City of London - Walbrook Wharf Upper Thames Street / Walbrook Wharf 7
Authority site.type os_grid_x os_grid_y latitude longitude OpeningDate
1 Sutton Roadside 525680 164420 51.36574 -0.1955630 1995-04-26 08:00:00
2 Rother Rural 594283 119082 50.93845 0.7639150 2002-01-11 13:30:00
3 Herts & Beds Urban Background 501906 221822 51.88567 -0.5207337 2000-10-02 07:00:00
4 Elmbridge Urban Background 511403 164915 51.37235 -0.4009194 2001-01-01 00:00:00
5 Elmbridge Roadside 514024 164792 51.37072 -0.3633206 2005-09-20 01:00:00
6 City of London Roadside 532527 180789 51.51050 -0.0916340 2007-04-01 01:00:00
ClosingDate
1 2002-04-26 01:00:00
2 <NA>
3 2010-04-28 01:00:00
4 2009-04-06 01:00:00
5 2008-07-18 09:30:00
6 <NA>
get_site_aq_objectives
get_site_aq_objectives imports pre-calculated air quality objectives (statistics) for each air quality monitoring station for which KCL are site operators, this includes the LAQN as well as a number of smaller local authority newtorks (the precise networks are detailed below under get_all_Groups).
> kcl_sites <- openair::importMeta(source = "kcl", all = TRUE)
> kcl_sites_aq_objectives <- get_site_aq_objectives(theSite = kcl_sites$code)
If all years, sites and air quality objectives are chosen, this will take some time to run, depending on your computer specification and return a large data frame with over 20,000 rows.
> dim(kcl_sites_aq_objectives)
[1] 26503 16
The structure of the data frame will be similar to that of laqn_sites_aq_objectives.
get_all_Groups
get_all_Groups returns the Groups and the respective GroupName for all the air quality monitoring networks within the London Air API.
> theGroups <- get_all_Groups()
> head(theGroups)
GroupName Description WebsiteURL
1 All All current network LAs http://www.erg.kcl.ac.uk/
2 AroundLondon Selection of boroughs around London http://www.londonair.org.uk/
3 CambridgeCity Demo group for tender
4 Cambridgeshire Demo group for tender
5 Essex All 14 councils in Essex http://www.essexair.org.uk/
6 Hampshire Various local authorities in Hampshire http://www.hantsair.org.uk/
The GroupName can be passed to get_laqn_sites to generate the site meta data for the sites in the groups identified by GroupName.
> kcl_sites <- get_laqn_sites(theGroup = theData$GroupName)
> head(kcl_sites)
LocalAuthorityCode LocalAuthorityName SiteCode SiteName
1 179 Southampton SH0 A33 Redbridge Road, Southampton
2 201 Adur AD1 Adur - Shoreham-by-Sea
3 1 Barking and Dagenham BG3 Barking and Dagenham - North Street
4 1 Barking and Dagenham BG1 Barking and Dagenham - Rush Green
5 1 Barking and Dagenham BG2 Barking and Dagenham - Scrattons Farm
6 2 Barnet BN2 Barnet - Finchley
SiteType DateClosed DateOpened Latitude Longitude
1 Roadside 2015-12-04 00:00:00 50.9205490280862 -1.46363686588104
2 Kerbside 2009-01-01 00:00:00 50.8321487360948 -0.27749852601479
3 Kerbside 2011-05-25 00:00:00 2007-03-16 00:00:00 51.540444 0.074418
4 Suburban 1999-11-02 00:00:00 51.563752 0.177891
5 Suburban 1999-10-17 00:00:00 51.529389 0.132857
6 Urban Background 2012-04-20 00:00:00 2000-08-09 13:00:00 51.591901 -0.205992
LatitudeWGS84 LongitudeWGS84 DataOwner DataManager
1 Southampton King's College London
2 6591656.3126 -30890.9946119 Adur King's College London
3 6717454.5833 8284.17386585 Barking and Dagenham King's College London
4 6721627.34498 19802.7355367 Barking and Dagenham King's College London
5 6715476.18683 14789.5735883 Barking and Dagenham King's College London
6 6726669.62886 -22930.9245475 Barnet King's College London
SiteLink
1 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=SH0
2 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=AD1
3 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG3
4 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG1
5 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG2
6 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BN2
This provides a similar output to openair::importMeta(source = "kcl", all = TRUE). Grouping and summarising the the data using dplyr reveals that there are only 354 unique SiteCodes as some sites appear several times.
> library(dplyr)
> kcl_sites %>%
group_by(SiteCode) %>%
summarise(no_rows = length(SiteCode))
# A tibble: 354 × 2
SiteCode no_rows
<chr> <int>
1 A30 4
2 AD1 4
3 AR1 4
4 AR2 4
5 BA1 2
6 BG1 4
7 BG2 4
8 BG3 4
9 BH0 4
10 BH1 4
# ... with 344 more rows
Whereas
> kcl_sites <- openair::importMeta(source = "kcl", all = TRUE)
> names(kcl_sites)
[1] "code" "site" "Address" "la_id" "Authority" "site.type" "os_grid_x"
[8] "os_grid_y" "latitude" "longitude" "OpeningDate" "ClosingDate"
> kcl_sites %>%
group_by(code) %>%
summarise(no_rows = length(code))
# A tibble: 896 × 2
code no_rows
<fctr> <int>
1 A30 1
2 AB0 1
3 AD1 1
4 AG0 1
5 AH0 1
6 AM0 1
7 AM1 1
8 AN0 1
9 AR1 1
10 AR2 1
# ... with 886 more rows
Reveals 896 unique values. Therefore openair::importMeta(source = "kcl", all = TRUE) provides a more detailed summary of KCL site meta data.
Applications
get_laqn_aq_objectives
The national air quality objective for hourly NO2 permits 18 exceedances per year (also termed the 99.8th
percentile). Defra's Local Air Quality Management Technical Guidance (TG16) document defines the locations at which hourly air quality objectives apply as "... outdoor locations (as defined in Box 1.1 on p.1-8) where they might might reasonably expected to spend one hour or longer." For "Kerbside sites" this includes pavements of busy shopping streets.
Due to high vehicle numbers and congestion on London's roads, road transport NOx emissions are high, especially in the vicinity of heavily trafficked roads, leading to elevated roadside NO2 concentrations. Consequently, this objective is exceeded at a number of roadside throughout the UK and in London. Some examples are given below.
The air quality monitoring station at Marylebone Road (Westminster - Marylebone Road Kerbside, MY1) is located next to the six lane A501. Frequent elevated hourly NO2 concentrations occur due to the high vehicle flows along the road which is an important thoroughfare in central London, running east-west from the Euston Road at Regent's Park, to the A40 Westway at Paddington.
Oxford Street forms part of the A40 and runs east-west, connecting traffic from the direction of Marble Arch, in the west, with Tottenham Court Road and Charing Cross Road, to the east. It is Europe's busiest shopping street, with around half a million daily visitors, and many retailers have flagship stores situated along the street. Traffic along the street is predominantly composed of buses and taxis, though cars have some restricted access via road intersections running perpendicular to Oxford Street. The air quality monitoring station in Oxford Street (Westminster - Oxford Street Kerbside, WM6) is located around 400, Oxford Street, opposite the entrance to the Selfridges department store seen here in Google streetview. As Google streetview shows the monitoring enclosure is situated between two sets of lights: A pedestrian crossing and the traffic light controlled junction of North Audley Street, Orchard Street and Oxford Street. Traffic can be seen queuing at the lights.
> # Load the plyr package
> library(dplyr)
> westminster_sites <- aq_objectives %>% filter(SiteCode == "MY1" | SiteCode == "WM6") %>% filter(ObjectiveName == "200 ug/m3 as a 1 hour mean, not to be exceeded more than 18 times a year")
Frequent elevated hourly NO2 concentrations also occur on Putney High Street, the A209. Two air quality monitroing stations are located here: The first is Wandsworth - Putney High Street (WA7), the second Wandsworth - Putney High Street Facade (WA8). Putney High Street links traffic passing over Putney Bridge, from the direction of central London, to the South Circular Road (A205) and Upper Richmond Road, two major arterial roads in south London. Putney High Street has been described as the most polluted street in south London.
> putney_sites <- aq_objectives %>% filter(SiteCode == "WA7" | SiteCode == "WA8") %>% filter( ObjectiveName == "200 ug/m3 as a 1 hour mean, not to be exceeded more than 18 times a year")
Combining the two sets of data provides an intercomparison of the number of exceedances of the hourly NO2 national air quality objective at the four air quality monitoring stations by year over the past twenty years. Data for 2016 and 2017 has been removed as it is provisional and subject to further change, at the current time.
> theData <- plyr::rbind.fill(westminster_sites, putney_sites)
> theData <- theData %>% filter(Year < as.integer(format(Sys.Date(), "%Y"))-1)
> library(ggplot2)
> ggplot(theData, aes(Year, Value, fill = SiteCode)) + geom_bar(stat = "identity", position = "dodge") + scale_y_continuous(name = "Exceedances per year") + theme(legend.position = "none") + facet_grid(~SiteCode) + coord_flip()
# Table 1
> theData <- arrange(select(theData, SiteCode, SiteName, Year, SpeciesCode, Value, Achieved), SiteCode, Year)
> theData$SpeciesCode <- gsub(pattern = "NO2", replacement = "NO<sub>2</sub>", theData$SpeciesCode)
> ggplot(theData, aes(Year, Value, fill = SiteCode)) + geom_bar(stat = "identity", position = "dodge") + scale_y_continuous(name = bquote('Exceedances of hourly' ~NO[2]~ 'air quality objective per year')) + theme(legend.position = "none") + facet_grid(~SiteCode) + coord_flip()
Note: There is no data for Putney High Street prior to 2009 whilst measurements at Putney High Street Facade commenced the following year. NO2 statistics for Oxford Street Kerbside are not available until 2013.
The barplot shows that hourly NO2 concentrations at all sites routinely exceed the national air quality objective of 18 exceedances per year. Whilst the number have fallen at all sites in recent years, it still remains high. The number of exceedances were especially high at Putney High Street and Putney High Street Facade where 1443 and 336 exceedances, respectively, were recorded in 2015. The number at Marylebone Road and Oxford Street Kerbside were 56 and 1391, respectively, for the same year.
get_laqn_sites
The location of the LAQN air quality monitoring stations at Marylebone Road, Oxford Street and Putney High Street can be viewed by using the ouput from get_laqn_sites.
Note: The two sites in Putney appear coincident when plotted at zoom = 12 , as given in the code below.
> # Select theSites
> theSites <- laqn_sites %>% filter(SiteCode == "MY1" | SiteCode == "WM6" | SiteCode == "WA7" | SiteCode == "WA8")
> # Load the leaflet package
> library(leaflet)
> m <- leaflet() %>%
> setView(lng = -0.17, lat = 51.5, zoom = 12) %>%
addTiles() %>%
addMarkers(lng = theSites$Longitude,
lat = theSites$Latitude,
popup = paste(theSites$SiteName, theSites$SiteLink, sep = ", "))
> m # Print the map
JustinLingard/rlaqn documentation built on May 7, 2019, 12:05 p.m.
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rlaqn: Data retrieval from the London Air API
Justin Lingard : prejjnl@gmail.com
Overview
rlaqn allows retrieval of data from the London Air API, the data feed of the London Air Quality Network, operated by the Environemntal Research Group (ERG) at King's College London (KCL). The API provides a structured and convenient way to interact with the data from the LAQN. Data is supplied in JSON format.
Similar packages
openairwhich provides open-source tools for the analysis of air pollution dataropenaqwhich provides UK-AIR latest measured levels (see https://uk-air.defra.gov.uk/latest/currentlevels) as well as data from other countriesrdefrawhich allows retrieval of air pollution data from the Defra's UK Air Information Resource (UK-AIR).
Dependencies
The rlaqn package depends some additional CRAN packages. Check for missing dependencies and install them using the commands below:
> packs <- c('dplyr', 'ggplot2', 'jsonlite', 'leaflet', 'pander')
> new.packages <- packs[!(packs %in% installed.packages()[, 'Package'])]
> if(length(new.packages)) install.packages(new.packages)
Installation
Install the development version from github using devtools:
> devtools::install_github('JustinLingard/rlaqn')
Load the rlaqn package:
> library('rlaqn')
Functions
get_laqn_aq_objectives
get_laqn_aq_objectives imports pre-calculated air quality objectives (statistics) for air pollutants for which national air quality objectives exist, for each station in the LAQN, from the London Air API:
- carbon monoxide, CO
- nitrogen dioxide, NO2
- ozone, O3
- sulphur dioxide, SO2, and
- particulate matter, PM10.
Statistics are calculated for each air quality monitoring station in the LAQN on a year-by-year basis. Statistics are available from the inception of the network in 1993, when it was composed of a few stations, to the much larger, current day network. The use of pre-calculated statistics removes the need to caluclate these metrics from raw, hourly data, and ensures good consistency with published data.
NOx (nitrogen oxides) and PM2.5 statistics are not currently available, but if generated in future, should be picked-up by the function.
Note: Ratification of the underlying air quality monitoring data, from which the statistics are calculated, is undertaken three to six months in arrears. Subsequently, statistics for the current year can vary over time and should be viewed as provisional statistics (awaiting final ratification).
Pre-calculated air quality statistics from the London Air API are comparable to those shown under the air quality objective values and capture rates on the Annual Air Quality Report for each air quality monitoring station in the LAQN, c.f., Annual Air Quality Report for Westminster - Marylebone Road (01/01/2015 to 01/01/2016).
Site meta data for past and current air quality monitoring station in the LAQN can be obtained using the get_laqn_sites function, as decsribed below.
> get_laqn_aq_objectives <- function (theGroup = "London", metric = "Annual",
data_type = "MonitoringObjective",
dates = 1980, datee = as.numeric(format(Sys.Date(), "%Y")),
api_type = "Json")
Running:
> aq_objectives <- get_laqn_aq_objectives()
returns all the air quality objectives since the inception of the network, even when the start year (dates) is set to 1980 (before the network came into existence). No data is retured for years where there is no data available and the function will just return an error message before moving onto the next year.
> head(aq_objectives)
SiteCode SiteName SiteType Latitude Longitude LatitudeWGS84
1 BG1 Barking and Dagenham - Rush Green Suburban 51.563752 0.177891 6721627.34498
2 BG1 Barking and Dagenham - Rush Green Suburban 51.563752 0.177891 6721627.34498
3 BL0 Camden - Bloomsbury Urban Background 51.522287 -0.125848 6714205.47041
4 BL0 Camden - Bloomsbury Urban Background 51.522287 -0.125848 6714205.47041
5 BL0 Camden - Bloomsbury Urban Background 51.522287 -0.125848 6714205.47041
6 BL0 Camden - Bloomsbury Urban Background 51.522287 -0.125848 6714205.47041
LongitudeWGS84 SiteLink
1 19802.7355367 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BG1
2 19802.7355367 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BG1
3 -14009.3352774 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BL0
4 -14009.3352774 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BL0
5 -14009.3352774 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BL0
6 -14009.3352774 http://www.londonair.org.uk/london/asp/publicstats.asp?site=BL0
DataOwner DataManager SpeciesCode SpeciesDescription
1 Barking and Dagenham King's College London NO2 Nitrogen Dioxide
2 Barking and Dagenham King's College London SO2 Sulphur Dioxide
3 Department for Environment Food and Rural Affairs King's College London CO Carbon Monoxide
4 Department for Environment Food and Rural Affairs King's College London NO2 Nitrogen Dioxide
5 Department for Environment Food and Rural Affairs King's College London NO2 Nitrogen Dioxide
6 Department for Environment Food and Rural Affairs King's College London NO2 Nitrogen Dioxide
Year ObjectiveName Value Achieved
1 1993 Capture Rate (%) 31 YES
2 1993 Capture Rate (%) 30 YES
3 1993 Capture Rate (%) 82 YES
4 1993 200 ug/m3 as a 1 hour mean, not to be exceeded more than 18 times a year 5 YES
5 1993 40 ug/m3 as an annual mean 65 NO
6 1993 Capture Rate (%) 93 YES
get_laqn_sites
Site meta data, for each past and current air quality monitoring station in the LAQN, can be obtained using the get_laqn_sites function, e.g.,
> laqn_sites <- get_laqn_sites()
> head(laqn_sites)
LocalAuthorityCode LocalAuthorityName SiteCode SiteName
1 1 Barking and Dagenham BG3 Barking and Dagenham - North Street
2 1 Barking and Dagenham BG1 Barking and Dagenham - Rush Green
3 1 Barking and Dagenham BG2 Barking and Dagenham - Scrattons Farm
4 2 Barnet BN2 Barnet - Finchley
5 2 Barnet BN3 Barnet - Strawberry Vale
6 2 Barnet BN1 Barnet - Tally Ho Corner
SiteType DateClosed DateOpened Latitude Longitude
1 Kerbside 2011-05-25 00:00:00 2007-03-16 00:00:00 51.540444 0.074418
2 Suburban 1999-11-02 00:00:00 51.563752 0.177891
3 Suburban 1999-10-17 00:00:00 51.529389 0.132857
4 Urban Background 2012-04-20 00:00:00 2000-08-09 13:00:00 51.591901 -0.205992
5 Urban Background 2002-05-15 00:00:00 2000-08-14 14:00:00 51.6008848453589 -0.172297542087178
6 Kerbside 2012-04-20 00:00:00 1998-12-20 12:00:00 51.614675 -0.176607
LatitudeWGS84 LongitudeWGS84 DataOwner DataManager
1 6717454.5833 8284.17386585 Barking and Dagenham King's College London
2 6721627.34498 19802.7355367 Barking and Dagenham King's College London
3 6715476.18683 14789.5735883 Barking and Dagenham King's College London
4 6726669.62886 -22930.9245475 Barnet King's College London
5 6728279.54795 -19180.0746501 Barnet King's College London
6 6730751.38494 -19659.8013105 Barnet King's College London
SiteLink
1 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG3
2 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG1
3 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG2
4 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BN2
5 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BN3
6 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BN1
Comparison of the output from get_laqn_sites with importMeta(source = "kcl", all = TRUE) from the openair package reveals some differences. importMeta returns the meta data for all air quality monitoring sites operated by KCL, including those outside London, e.g., those in the UK Black Carbon network, and other local authority networks.
> kcl_sites <- openair::importMeta(source = "kcl", all = TRUE)
> head(kcl_sites)
code site Address la_id
1 ST1 Sutton - Robin Hood School Robin Hood Junior School, Thorncroft Road, Sutton 29
2 RY1 Rother - Rye Harbour Rye Harbour 211
3 SB1 South Beds - Dunstable Dunstable, South Beds 150
4 EL1 Elmbridge - Bell Farm Hersham Bell Farm, Hersham 44
5 EL2 Elmbridge - Esher High Street Esher High Street 44
6 CT6 City of London - Walbrook Wharf Upper Thames Street / Walbrook Wharf 7
Authority site.type os_grid_x os_grid_y latitude longitude OpeningDate
1 Sutton Roadside 525680 164420 51.36574 -0.1955630 1995-04-26 08:00:00
2 Rother Rural 594283 119082 50.93845 0.7639150 2002-01-11 13:30:00
3 Herts & Beds Urban Background 501906 221822 51.88567 -0.5207337 2000-10-02 07:00:00
4 Elmbridge Urban Background 511403 164915 51.37235 -0.4009194 2001-01-01 00:00:00
5 Elmbridge Roadside 514024 164792 51.37072 -0.3633206 2005-09-20 01:00:00
6 City of London Roadside 532527 180789 51.51050 -0.0916340 2007-04-01 01:00:00
ClosingDate
1 2002-04-26 01:00:00
2 <NA>
3 2010-04-28 01:00:00
4 2009-04-06 01:00:00
5 2008-07-18 09:30:00
6 <NA>
get_site_aq_objectives
get_site_aq_objectives imports pre-calculated air quality objectives (statistics) for each air quality monitoring station for which KCL are site operators, this includes the LAQN as well as a number of smaller local authority newtorks (the precise networks are detailed below under get_all_Groups).
> kcl_sites <- openair::importMeta(source = "kcl", all = TRUE)
> kcl_sites_aq_objectives <- get_site_aq_objectives(theSite = kcl_sites$code)
If all years, sites and air quality objectives are chosen, this will take some time to run, depending on your computer specification and return a large data frame with over 20,000 rows.
> dim(kcl_sites_aq_objectives)
[1] 26503 16
The structure of the data frame will be similar to that of laqn_sites_aq_objectives.
get_all_Groups
get_all_Groups returns the Groups and the respective GroupName for all the air quality monitoring networks within the London Air API.
> theGroups <- get_all_Groups()
> head(theGroups)
GroupName Description WebsiteURL
1 All All current network LAs http://www.erg.kcl.ac.uk/
2 AroundLondon Selection of boroughs around London http://www.londonair.org.uk/
3 CambridgeCity Demo group for tender
4 Cambridgeshire Demo group for tender
5 Essex All 14 councils in Essex http://www.essexair.org.uk/
6 Hampshire Various local authorities in Hampshire http://www.hantsair.org.uk/
The GroupName can be passed to get_laqn_sites to generate the site meta data for the sites in the groups identified by GroupName.
> kcl_sites <- get_laqn_sites(theGroup = theData$GroupName)
> head(kcl_sites)
LocalAuthorityCode LocalAuthorityName SiteCode SiteName
1 179 Southampton SH0 A33 Redbridge Road, Southampton
2 201 Adur AD1 Adur - Shoreham-by-Sea
3 1 Barking and Dagenham BG3 Barking and Dagenham - North Street
4 1 Barking and Dagenham BG1 Barking and Dagenham - Rush Green
5 1 Barking and Dagenham BG2 Barking and Dagenham - Scrattons Farm
6 2 Barnet BN2 Barnet - Finchley
SiteType DateClosed DateOpened Latitude Longitude
1 Roadside 2015-12-04 00:00:00 50.9205490280862 -1.46363686588104
2 Kerbside 2009-01-01 00:00:00 50.8321487360948 -0.27749852601479
3 Kerbside 2011-05-25 00:00:00 2007-03-16 00:00:00 51.540444 0.074418
4 Suburban 1999-11-02 00:00:00 51.563752 0.177891
5 Suburban 1999-10-17 00:00:00 51.529389 0.132857
6 Urban Background 2012-04-20 00:00:00 2000-08-09 13:00:00 51.591901 -0.205992
LatitudeWGS84 LongitudeWGS84 DataOwner DataManager
1 Southampton King's College London
2 6591656.3126 -30890.9946119 Adur King's College London
3 6717454.5833 8284.17386585 Barking and Dagenham King's College London
4 6721627.34498 19802.7355367 Barking and Dagenham King's College London
5 6715476.18683 14789.5735883 Barking and Dagenham King's College London
6 6726669.62886 -22930.9245475 Barnet King's College London
SiteLink
1 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=SH0
2 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=AD1
3 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG3
4 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG1
5 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BG2
6 http://www.londonair.org.uk/london/asp/publicdetails.asp?site=BN2
This provides a similar output to openair::importMeta(source = "kcl", all = TRUE). Grouping and summarising the the data using dplyr reveals that there are only 354 unique SiteCodes as some sites appear several times.
> library(dplyr)
> kcl_sites %>%
group_by(SiteCode) %>%
summarise(no_rows = length(SiteCode))
# A tibble: 354 × 2
SiteCode no_rows
<chr> <int>
1 A30 4
2 AD1 4
3 AR1 4
4 AR2 4
5 BA1 2
6 BG1 4
7 BG2 4
8 BG3 4
9 BH0 4
10 BH1 4
# ... with 344 more rows
Whereas
> kcl_sites <- openair::importMeta(source = "kcl", all = TRUE)
> names(kcl_sites)
[1] "code" "site" "Address" "la_id" "Authority" "site.type" "os_grid_x"
[8] "os_grid_y" "latitude" "longitude" "OpeningDate" "ClosingDate"
> kcl_sites %>%
group_by(code) %>%
summarise(no_rows = length(code))
# A tibble: 896 × 2
code no_rows
<fctr> <int>
1 A30 1
2 AB0 1
3 AD1 1
4 AG0 1
5 AH0 1
6 AM0 1
7 AM1 1
8 AN0 1
9 AR1 1
10 AR2 1
# ... with 886 more rows
Reveals 896 unique values. Therefore openair::importMeta(source = "kcl", all = TRUE) provides a more detailed summary of KCL site meta data.
Applications
get_laqn_aq_objectives
The national air quality objective for hourly NO2 permits 18 exceedances per year (also termed the 99.8th percentile). Defra's Local Air Quality Management Technical Guidance (TG16) document defines the locations at which hourly air quality objectives apply as "... outdoor locations (as defined in Box 1.1 on p.1-8) where they might might reasonably expected to spend one hour or longer." For "Kerbside sites" this includes pavements of busy shopping streets.
Due to high vehicle numbers and congestion on London's roads, road transport NOx emissions are high, especially in the vicinity of heavily trafficked roads, leading to elevated roadside NO2 concentrations. Consequently, this objective is exceeded at a number of roadside throughout the UK and in London. Some examples are given below.
The air quality monitoring station at Marylebone Road (Westminster - Marylebone Road Kerbside, MY1) is located next to the six lane A501. Frequent elevated hourly NO2 concentrations occur due to the high vehicle flows along the road which is an important thoroughfare in central London, running east-west from the Euston Road at Regent's Park, to the A40 Westway at Paddington.
Oxford Street forms part of the A40 and runs east-west, connecting traffic from the direction of Marble Arch, in the west, with Tottenham Court Road and Charing Cross Road, to the east. It is Europe's busiest shopping street, with around half a million daily visitors, and many retailers have flagship stores situated along the street. Traffic along the street is predominantly composed of buses and taxis, though cars have some restricted access via road intersections running perpendicular to Oxford Street. The air quality monitoring station in Oxford Street (Westminster - Oxford Street Kerbside, WM6) is located around 400, Oxford Street, opposite the entrance to the Selfridges department store seen here in Google streetview. As Google streetview shows the monitoring enclosure is situated between two sets of lights: A pedestrian crossing and the traffic light controlled junction of North Audley Street, Orchard Street and Oxford Street. Traffic can be seen queuing at the lights.
> # Load the plyr package
> library(dplyr)
> westminster_sites <- aq_objectives %>% filter(SiteCode == "MY1" | SiteCode == "WM6") %>% filter(ObjectiveName == "200 ug/m3 as a 1 hour mean, not to be exceeded more than 18 times a year")
Frequent elevated hourly NO2 concentrations also occur on Putney High Street, the A209. Two air quality monitroing stations are located here: The first is Wandsworth - Putney High Street (WA7), the second Wandsworth - Putney High Street Facade (WA8). Putney High Street links traffic passing over Putney Bridge, from the direction of central London, to the South Circular Road (A205) and Upper Richmond Road, two major arterial roads in south London. Putney High Street has been described as the most polluted street in south London.
> putney_sites <- aq_objectives %>% filter(SiteCode == "WA7" | SiteCode == "WA8") %>% filter( ObjectiveName == "200 ug/m3 as a 1 hour mean, not to be exceeded more than 18 times a year")
Combining the two sets of data provides an intercomparison of the number of exceedances of the hourly NO2 national air quality objective at the four air quality monitoring stations by year over the past twenty years. Data for 2016 and 2017 has been removed as it is provisional and subject to further change, at the current time.
> theData <- plyr::rbind.fill(westminster_sites, putney_sites)
> theData <- theData %>% filter(Year < as.integer(format(Sys.Date(), "%Y"))-1)
> library(ggplot2)
> ggplot(theData, aes(Year, Value, fill = SiteCode)) + geom_bar(stat = "identity", position = "dodge") + scale_y_continuous(name = "Exceedances per year") + theme(legend.position = "none") + facet_grid(~SiteCode) + coord_flip()
# Table 1
> theData <- arrange(select(theData, SiteCode, SiteName, Year, SpeciesCode, Value, Achieved), SiteCode, Year)
> theData$SpeciesCode <- gsub(pattern = "NO2", replacement = "NO<sub>2</sub>", theData$SpeciesCode)
> ggplot(theData, aes(Year, Value, fill = SiteCode)) + geom_bar(stat = "identity", position = "dodge") + scale_y_continuous(name = bquote('Exceedances of hourly' ~NO[2]~ 'air quality objective per year')) + theme(legend.position = "none") + facet_grid(~SiteCode) + coord_flip()
Note: There is no data for Putney High Street prior to 2009 whilst measurements at Putney High Street Facade commenced the following year. NO2 statistics for Oxford Street Kerbside are not available until 2013.
The barplot shows that hourly NO2 concentrations at all sites routinely exceed the national air quality objective of 18 exceedances per year. Whilst the number have fallen at all sites in recent years, it still remains high. The number of exceedances were especially high at Putney High Street and Putney High Street Facade where 1443 and 336 exceedances, respectively, were recorded in 2015. The number at Marylebone Road and Oxford Street Kerbside were 56 and 1391, respectively, for the same year.
get_laqn_sites
The location of the LAQN air quality monitoring stations at Marylebone Road, Oxford Street and Putney High Street can be viewed by using the ouput from get_laqn_sites.
Note: The two sites in Putney appear coincident when plotted at zoom = 12 , as given in the code below.
> # Select theSites
> theSites <- laqn_sites %>% filter(SiteCode == "MY1" | SiteCode == "WM6" | SiteCode == "WA7" | SiteCode == "WA8")
> # Load the leaflet package
> library(leaflet)
> m <- leaflet() %>%
> setView(lng = -0.17, lat = 51.5, zoom = 12) %>%
addTiles() %>%
addMarkers(lng = theSites$Longitude,
lat = theSites$Latitude,
popup = paste(theSites$SiteName, theSites$SiteLink, sep = ", "))
> m # Print the map
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