Functions for importing air pollution data from a range of UK networks
including the Automatic Urban and Rural Network (AURN), the individual
England (AQE), Scotland (SAQN), Wales (WAQN) and Northern Ireland (NI)
Networks, and many "locally managed" monitoring networks across England.
Files are imported from a remote server operated by Ricardo that provides air
quality data files as R data objects. For an up to date list of available
sites that can be imported, see importMeta().
importUKAQ(
site = "my1",
year = 2022,
source = "aurn",
data_type = "hourly",
pollutant = "all",
hc = FALSE,
meta = FALSE,
meteo = TRUE,
ratified = FALSE,
to_narrow = FALSE,
verbose = FALSE,
progress = TRUE
)a tibble
Site code of the site to import, e.g., "my1" is Marylebone
Road. Site codes can be discovered through the use of importMeta().
Several sites can be imported at once. For example, site = c("my1", "nott") imports both Marylebone Road and Nottingham. Sites from different
networks can be imported through also providing multiple sources. Site
codes can be upper or lower case.
Year(s) to import. To import a series of years use, e.g.,
2000:2020. To import several specific years use year = c(2000, 2010, 2020).
The network to which the site(s) belong, defaulting to
"aurn". Providing a single network will attempt to import all of the
given sites from the provided network. Alternatively, a vector of sources
can be provided of the same length as site to indicate which network each
site individually belongs. Available networks include:
"aurn", The UK Automatic Urban and Rural Network.
"aqe", The Air Quality England Network.
"saqn", The Scottish Air Quality Network.
"waqn", The Welsh Air Quality Network.
"ni", The Northern Ireland Air Quality Network.
"local", Locally managed air quality networks in England.
The type of data to be returned, defaulting to "hourly"
data. Alternative data types include:
"daily": Daily average data.
"monthly": Monthly average data with data capture information for the whole network.
"annual": Annual average data with data capture information for the whole network.
"15_min": 15-minute average SO2 concentrations.
"8_hour": 8-hour rolling mean concentrations for O3 and CO.
"24_hour": 24-hour rolling mean concentrations for particulates.
"daily_max_8": Maximum daily rolling 8-hour maximum for O3 and CO.
"daqi": Daily Air Quality Index (DAQI). See
here for
more details of how the index is defined. Note that this data_type is not
available for locally managed monitoring networks.
Pollutants to import. If omitted will import all pollutants
from a site. To import only NOx and NO2 for example use pollutant =
c("nox", "no2"). Pollutant names can be upper or lower case.
Include hydrocarbon measurements in the imported data? Defaults to
FALSE as most users will not be interested in using hydrocarbon data.
Append the site type, latitude and longitude of each selected
site? Defaults to FALSE.
Append modelled meteorological data, if available? Defaults to
TRUE, which will return wind speed (ws), wind direction (wd) and
ambient temperature (air_temp). The variables are calculated from using
the WRF model run by Ricardo Energy & Environment and are available for
most but not all networks. Setting meteo = FALSE is useful if you have
other meteorological data to use in preference, for example from
the worldmet package.
Append qc column(s) to hourly data indicating whether each
species was ratified (i.e., quality-checked)? Defaults to FALSE.
Return the data in a "narrow"/"long"/"tidy" format? By
default the returned data is "wide" and has a column for each
pollutant/variable. When to_narrow = TRUE the data are returned with a
column identifying the pollutant name and a column containing the
corresponding concentration/statistic. Defaults to FALSE.
Print messages to the console if hourly data cannot be
imported? Default is FALSE. TRUE is useful for debugging as the
specific year(s), site(s) and source(s) which cannot be imported will
be returned.
Show a progress bar when many sites/years are being imported?
Defaults to TRUE.
This family of functions has been written to make it easy to import data from across several UK air quality networks. Ricardo have provided .RData files (R workspaces) of all individual sites and years, as well as up to date meta data. These files are updated on a daily basis. This approach requires a link to the Internet to work.
There are several advantages over the web portal approach where .csv files are downloaded.
First, it is quick to select a range of sites, pollutants and periods (see examples below).
Second, storing the data as .RData objects is very efficient as they are about four times smaller than .csv files --- which means the data downloads quickly and saves bandwidth.
Third, the function completely avoids any need for data manipulation or setting time formats, time zones etc. The function also has the advantage that the proper site name is imported and used in openair functions.
Users should take care if using data from both openair and web portals (for example, UK AIR). One key difference is that the data provided by openair is date beginning, whereas the web portal provides date ending. Hourly concentrations may therefore appear offset by an hour, for example.
The data are imported by stacking sites on top of one another and will have
field names site, code (the site code) and pollutant.
By default, the function returns hourly average data. However, annual,
monthly, daily and 15 minute data (for SO2) can be returned using the
option data_type. Annual and monthly data provide whole network
information including data capture statistics.
All units are expressed in mass terms for gaseous species (ug/m3 for NO, NO2, NOx (as NO2), SO2 and hydrocarbons; and mg/m3 for CO). PM10 concentrations are provided in gravimetric units of ug/m3 or scaled to be comparable with these units. Over the years a variety of instruments have been used to measure particulate matter and the technical issues of measuring PM10 are complex. In recent years the measurements rely on FDMS (Filter Dynamics Measurement System), which is able to measure the volatile component of PM. In cases where the FDMS system is in use there will be a separate volatile component recorded as 'v10' and non-volatile component 'nv10', which is already included in the absolute PM10 measurement. Prior to the use of FDMS the measurements used TEOM (Tapered Element Oscillating. Microbalance) and these concentrations have been multiplied by 1.3 to provide an estimate of the total mass including the volatile fraction.
Some sites report hourly and daily PM10 and / or PM2.5. When data_type = "daily" and there are both hourly and 'proper' daily measurements
available, these will be returned as e.g. "pm2.5" and "gr_pm2.5"; the
former corresponding to data based on original hourly measurements and the
latter corresponding to daily gravimetric measurements.
The function returns modelled hourly values of wind speed (ws), wind
direction (wd) and ambient temperature (air_temp) if available
(generally from around 2010). These values are modelled using the WRF model
operated by Ricardo.
The BAM (Beta-Attenuation Monitor) instruments that have been incorporated into the network throughout its history have been scaled by 1.3 if they have a heated inlet (to account for loss of volatile particles) and 0.83 if they do not have a heated inlet. The few TEOM instruments in the network after 2008 have been scaled using VCM (Volatile Correction Model) values to account for the loss of volatile particles. The object of all these scaling processes is to provide a reasonable degree of comparison between data sets and with the reference method and to produce a consistent data record over the operational period of the network, however there may be some discontinuity in the time series associated with instrument changes.
No corrections have been made to the PM2.5 data. The volatile component of FDMS PM2.5 (where available) is shown in the 'v2.5' column.
David Carslaw, Trevor Davies, and Jack Davison
Other import functions:
importADMS(),
importAURN(),
importEurope(),
importKCL(),
importMeta(),
importTraj()
if (FALSE) {
# import a single site from the AURN
importUKAQ("my1", year = 2022)
# import sites from another network
importUKAQ(c("bn1", "bn2"), year = 2022, source = "aqe")
# import sites across multiple networks
importUKAQ(c("my1", "bn1", "bn2"),
year = 2022,
source = c("aurn", "aqe", "aqe")
)
# get "long" format hourly data with a ratification flag
importUKAQ(
"card",
source = "waqn",
year = 2022,
to_narrow = TRUE,
ratified = TRUE
)
# import other data types, filtering by pollutant
importUKAQ(
data_type = "annual",
pollutant = c("no2", "pm2.5", "pm10"),
source = c("aurn", "aqe")
)
}
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