1.1 Air quality monitoring in Gibraltar

The Gibraltar Air Quality Data Digest provides an annual summary of the air pollutant measurements from the Gibraltar Air Quality Monitoring Network for 2019.

The Gibraltar Air Quality Monitoring Network is operated on behalf of the Government of Gibraltar by the Environmental Agency, with assistance from Ricardo Energy & Environment. The principal objective of the Gibraltar Air Quality Monitoring Network is for compliance reporting against the European Air Quality Directive (AQD) on ambient air quality and cleaner air for Europe (2008/50/EC) and the Fourth Daughter Directive (DD4) (2004/107/EC).

The Gibraltar Air Quality Monitoring Network includes a mixture of automatic pollutant monitoring stations and non-automatic air pollutant monitoring sites. The automatic air quality monitoring stations measure:

• Oxides of nitrogen (NO_X) and nitrogen dioxide (NO₂)

• Sulphur dioxide (SO₂)

• Ozone (O₃)

• Carbon monoxide (CO)

• Particulates (PM₁₀, PM_2.5)

• Heavy metals: Arsenic (As), Cadmium (Cd), Nickel (Ni), Lead (Pb)

• Benzene (Bz) and

• Polycyclic aromatic hydrocarbons (PAH), including Benzo[a]Pyrene (B[a]P).

Non-automatic sites measure monthly average concentrations of NO₂ and benzene using a passive diffusion tube based method. Diffusion tube measurements have a much higher uncertainty than automatic measurements and are purely indicative of air pollutant concentrations. As such they cannot be compared against the specific legislative values specified in the European Air Quality Directive. Further information on the air pollutants measured in Gibraltar can be found on the Air Quality in Gibraltar website.

The sites within the Gibraltar automatic air quality monitoring network provide a combination of high resolution hourly measurements and daily average air pollutant concentrations. High resolution information is communicated rapidly to the public. The main platform for information dissemination of air quality measurement in Gibraltar is the Air Quality in Gibraltar website. Non-automatic measurement sites provide an indicative measure of roadside and background air pollutant concentrations at thirty-two sites throughout Gibraltar.

The major objectives of the Gibraltar Air Quality Monitoring Network are:

• Checking if statutory air quality standards and targets are met (e.g., EC Directives)

• Informing the public about air quality

• Identifying long-term trends in air pollution concentrations

• Assessing the effectiveness of policies to control pollution in Gibraltar, as laid out in the Gibraltar Air Quality Action Plan.

The air pollutant measurements from Gibraltar Air Quality Monitoring Network are used for:

• Reporting to the European Commission as required by the Air Quality Directives

• Comparison with air quality objectives prescribed by the Air Quality Directives

• Providing the public with information through air quality bulletins

• Forecasting future air quality levels

• Policy development for human health protection.

This document provides graphical analysis and explanatory summaries of the air pollutant measurements made in Gibraltar. Compliance plots (as discussed in Section 2.2) are used to present concentrations for 2019 in the context of historical data, highlighting whether the Limit Values (LVs) or Target Values (TVs) given in the European Air Quality Directives were achieved. The other plots presented here provide useful information from which the source of air pollutants can be inferred.

1.2 Limit Values and Target Values

A summary of the relevant legislative thresholds prescribed in the Air Quality Directive and Fourth Daughter Directive are presented in Table 1. This shows each pollutant and the relevant metric and threshold applicable. Also shown is the type of threshold: Limit Value (LV), Target Value (TV), Long Term Objective (ozone only) and the year in which each LV or TV has to be achieved. These are represented in the ‘compliance plots’ as red dashed lines and the corresponding metrics are also presented in the summary data tables in this document. The air pollutants covered under the two Directives are:

• Air Quality Directive (AQD)

  • NO_X and NO₂

  • PM₁₀

  • PM_2.5

  • CO

  • SO₂

  • Ozone

  • Benzene

  • Lead

• Fourth Daughter Directive (DD4)

  • Benzo[a]Pyrene (B[a]P)

  • Arsenic

  • Cadmium

  • Nickel

Table 1: Summary of current Limit Values and Target Values (the number of permissible exceedances per year are given in brackets next to the Value)

Pollutant	Type	Year in force	Metric	Value
NO2	LV	2010	Annual mean	40 μg m-3
NO2	LV	2010	1-hr mean	200 μg m-3 (18 allowed)
PM10	LV	2005	Annual mean	40 μg m-3
PM10	LV	2005	24-hr mean	50 μg m-3 (35 allowed)
PM2.5	TV/LV (Stage 1)	2010/2014	Annual mean	25 μg m-3
PM2.5	LV (Stage 2)	2020	Annual mean	20 μg m-3
CO	LV	2005	Maximum daily running 8-hr mean	10 mg m-3
SO2	LV	2005	1-hr mean	350 μg m-3 (24 allowed)
SO2	LV	2005	24-hr mean	125 μg m-3 (3 allowed)
O3	LTO	Not defined	Maximum daily running 8-hr mean	120 μg m-3
Benzene	LV	2010	Annual mean	5 μg m-3
Lead	LV	2005	Annual mean	0.5 μg m-3
B[a]P	TV	2013	Annual mean	1 ng m-3
Arsenic	TV	2013	Annual mean	6 ng m-3
Cadmium	TV	2013	Annual mean	5 ng m-3
Nickel	TV	2013	Annual mean	20 ng m-3

1.3 Air quality monitoring locations

Information on the air pollutant monitoring methods and the composition of the Gibraltar Air Quality Monitoring Network can be found on the Gibraltar Air Quality Monitoring Network website. Table 2 provides a summary of the air pollutant monitoring stations and air pollutants measured at the automatic monitoring stations and non-automatic monitoring sites in Gibraltar in 2019. Figures 1 and 2 show the locations of the automatic monitoring stations and the non-automatic sampling points in Gibraltar in 2019, respectively. Mobile monitoring has been added into the network since 2018 and these sites and concentrations have been presented in Section 3.8.

Table 2: Summary of automatic monitoring stations and non-automatic monitoring sites in Gibraltar in 2019.

Network	Station name	Pollutants measured
Automatic monitoring sites	Bleak House	NOX, NO2, PM10 and ozone
	Rosia Road	NOX, NO2, PM10, PM2.5, CO, SO2, benzene, PAH and metals
	Withams Road	NOX and NO2
Non-automatic monitoring sites	Multiple sites	NO2 and/or benzene

Figure 1: Location of automatic air quality monitoring stations in Gibraltar, 2019 (see interactive map in subsection 2.1)

Figure 2: Location of non-automatic air quality monitoring sites in Gibraltar, 2019 (see interactive map in subsection 2.1)

Table 3: Co-ordinates of non-automatic air quality monitoring sites in Gibraltar, 2019, as shown in Figure 2.

1.4 Data processing

The data summaries and plots presented this document were generated using openair, an open-source air quality analysis toolset written in the R statistical programming language.

1.5 Meteorological observations

A summary of 2019 meteorological observations are presented to provide a context for the air pollutant concentrations measured in Gibraltar. The influence of the Rock on the flow of the wind field is evident: wind speed and direction measurements vary markedly when correponding measurements are compared to one another. Wind speeds measured using the Gibraltar Airport meteorological mast (reference height, z = 10 m), tend to be higher than those measured at the three automatic air quality monitoring stations, where wind speeds are measured at a height of 6-8 m, and are therefore correspondingly lower. Meteorological data from Gibraltar Airport has been included for comparison with the local meteorological data from the AQ monitoring stations and is considered to be more representative of the regional meteorological conditions. Plots that use meteorological data have been generated using the local meteorological data where it is available (e.g. fixed automatic stations), which are associated with the corresponding concentrations resulting from the local dispersion conditions. However, it is important to be mindful that the regional meteorological conditions can be quite different. Where meteorological data is not available to associate directly with concentrations, the regional meteorological data from the airport has been used instead (e.g. AQMesh pods).

2.1 Interactive map

Interactive maps use markers to show points of interest, for example measurement sites. The user can zoom in and out to see more or less detail. The user can also turn satellite layers on and off by selecting a different base map, using the top right button.

2.2 Compliance plot

The compliance plots show the mean concentrations, expressed as annual mean or an appropriate equivalent percentile for the year. This allows comparison of the mean value with a legislative threshold, e.g., an air quality Directive Limit Value (LV) or Target Value (TV) which is represented by the dashed red line. In instances where the European air quality Directives specify a permissible number of occasions above a threshold, the plotted data are presented as the percentile equivalent to that metric. For example, 99.8^th percentile of hourly mean NO₂ concentrations is equivalent to 18 permissible exceedances of the hourly NO₂ LV (200 μg m^-3). Compliance is indicated by values below 200 μg m^-3. Likewise for PM₁₀, the 90^th percentile of daily mean PM₁₀ is equivalent to 35 permissible exceedances of the daily PM₁₀ LV (50 μg m^-3). The plots are scaled to best represent the concentrations so where the red dashed line does not appear on the plot, this means that the measured concentrations are sufficiently below the threshold that it does not appear on the plot. PM_2.5 has two thresholds specified by the Directive: A Stage 1 LV and TV at 25 μg m^-3 and a Stage 2 LV at 20 μg m^-3.

2.3 Wind rose

The wind rose plot shows the variation in wind speed and direction at a site. The classified colour scale represents different wind speeds (in m s^-1). The magnitude of the wind speed is shown by the colours indicated in the colour bar. The orientation of the wind sectors around the plot origin represents the wind direction binned in 30° sectors. The distance outwards from the plot origin represents percentage of time the wind speed originated from a particular direction. Therefore by adding each percentage together should sum to 100.

2.4 Trend plot

The trend plot shows monthly mean air pollutant concentrations (indicated by a thin line joining closed circles) and the non-linear trend fitted to the data (bold line). The shaded grey bands represent the 95% confidence interval of the data. These plots demonstrate temporal trends over months and/or years and can be used to determine long-term trends. In some plots this data has been split according to wind direction sectors by using associated meteorological data at the site for which the trends are being plotted – in this way trends associated with air from different directions (and associated sources) can be shown. When splitting data according to wind direction (and applying a data capture threshold to the aggregated statistic to ensure it is representative for the period it is covering) there is a reduction in data volume to plot by wind sector. For this reason some of the plot panes are omitted where the data volume is too low to plot. In Gibraltar this can result from the topographical effects on the local meteorology (from the air quality monitoring station) at the point of measurement (e.g. fewer meteorological measurements of a particular wind direction as a result of the Rock acting as a barrier).

2.5 Contribution plot

Contribution plots show the influence of the wind direction on mean air pollutant concentrations. As with the wind rose, the orientation of the wind sectors around the plot origin represents the wind direction binned in 30° sectors. The radial scale indicates the percentage of time the wind from a particular wind sector contributed to the overall mean concentration. The plots show the contribution of each wind sector to the overall mean air pollutant concentration; this is particularly useful for showing the influence of wind direction on high air pollutant concentrations.

2.6 Calendar plot

Calendar plots are laid out in a similar style to a wall calendar and show the daily mean air pollutant concentrations disaggregated by day-of-week and month-of-year. The colour of each box corresponds to the daily mean pollutant concentration indicated by the colour bar. The prevailing daily wind speed is indicated by the length of arrow in each box, and the wind direction, by the arrow orientation. This allows the daily mean air pollutant concentrations to be seen relative to one another. It also allows seasonal patterns in air pollutant concentrations, trends, and the variation of the local wind field, as well as the influence of meteorology on air pollutant concentrations to be seen.

2.7 Polar plot

Polar plots show the relationship between air pollutant concentrations and wind speed and wind direction. The wind speed is represented by the distance from the plot origin and the wind direction is the orientation about the origin (as in other plots described above). The continuous colour scale represents the air pollutant concentration. The plot provides a continuous surface by smoothing between observed data points. Where meteorological data are not available at point of measurement (e.g. AQMesh pods), data from the airport meteorological station have been used.

2.8 Time variation plot

The time variation plot shows changing concentrations over several different time scales:

• Hour of the day and day of the week (upper pane)

• Hour of the day (diurnal variation, in the lower left pane)

• Month (seasonal variation, in the lower central pane)

• Day of week (in the lower right pane).

The time variation plot is useful for representing changes due to different source activities. For example, fugitive dust emissions from building work, which may cause an increase in the PM₁₀ mass concentration, might occur at specific hours of the day or days of the week; likewise NO_X and NO₂ associated with road traffic exhausts are typically higher during week days than weekend and at morning and evening rush hours.

This plot requires high-resolution (hourly) measurements of air pollutant concentrations in order to produce the temporal plot shown across the top panel and on the bottom right hand-side of the plot. PM₁₀ in Gibraltar is measured using two techniques: The FDMS, which provides hourly mean PM₁₀ mass concentrations, and by the Partisol, which provides daily mean PM₁₀ mass concentrations. PM_2.5 is only measured using the Partisol method. Therefore it is not possible to produce a time variation plot for PM_2.5 mass concentrations in Gibraltar.

2.9 Spot concentration plot

The spot concentration plot shows the measured air pollutant concentration for a range of locations. This plot is ideal for summarising the results from the NO₂ and benzene diffusion tube measurements from the Gibraltar non-automatic monitoring network. Air pollutant concentrations from the non-automatic monitoring network are measured at multiple sites

Two plots are presented for both pollutants. The first showing the annual mean air pollutant concentration at each site. The second shows the difference in the annual mean for the current year versus the long-term average, for each site, to show the long trends in air pollutant concentrations. This can be used to indicate whether air quality is improving or declining at these locations.

It should be noted that diffusion tube measurements are purely indicative of air pollutant concentrations. As such they cannot be compared against the specific legislative values specified in the European Air Quality Directive.

2.10 Interactive time series plot

Interactive time series plots show the measured air pollutant concentrations at an individual site or multiple sites. The user can zoom in and out to different time periods to see more or less detail by using the mouse to click and drag on the time series or by using the range slider bar at the bottom of the plot. The user can mouse over a pollutant trace to get more information on a specific data point. Pollutant traces can be turned on and off by clicking on the pollutant name in the legend. To see an individual pollutant channel at optimum scale, double click on the pollutant name to isolate one channel.

3.1 Wind speed and direction

Figure 3: Frequency plot of wind speed and direction at the airport and Gibraltar automatic air quality monitoring sites, 2019 (see wind rose plot in subsection 2.3)

3.2 NO_X and NO₂

Figure 4: Annual mean NO₂ measured at Gibraltar automatic air quality monitoring sites, 2005-2019 (see compliance plot in subsection 2.2)

Figure 5: 99.8th percentile 1-hr NO₂ measured at Gibraltar automatic air quality monitoring sites, 2005-2019 (see compliance plot in subsection 2.2)

Figure 6: The year-on-year NO_X concentration trend at automatic air quality monitoring sites, 2005-2019 (see trend plot in subsection 2.4)

Figure 7: The year-on-year NO₂ concentration trend at automatic air quality monitoring sites, 2005-2019 (see trend plot in subsection 2.4)

Figure 8: The percentage contribution of wind direction to annual mean NO_X concentration measured at automatic air quality monitoring sites, 2019 (see contribution plot in subsection 2.5)

Figure 9: Daily mean NO₂ concentrations at Rosia Road automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

Figure 10: Daily mean NO₂ concentrations at Withams Road automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

Figure 11: Variation in NO_X and NO₂ concentrations measured at Rosia Road automatic monitoring site for different time periods, 2019 (see time variation plot in subsection 2.8)

Figure 12: Variation in NO_X and NO₂ concentrations measured at Withams Road automatic monitoring site for different time periods, 2019 (see time variation plot in subsection 2.8)

Figure 13: Polar plots of NO_X concentrations for Gibraltar automatic air quality monitoring site, 2019 (see polar plot in subsection 2.7)

Figure 14: Annual mean NO₂ diffusion tube concentrations, 2019 (see spot concentration plot in subsection 2.9)

Figure 15: Difference in annual mean NO₂ diffusion tube concentrations 2019 minus the mean of 2005-2018 concentrations (see spot concentration plot in subsection 2.9)

3.3 Particulate matter

Figure 16: Annual mean gravimetric PM₁₀ measured at Gibraltar automatic air quality monitoring sites, 2005-2019 (see compliance plot in subsection 2.2)

Figure 17: 90th percentile gravimetric PM₁₀ concentrations measured at Gibraltar automatic air quality monitoring sites, 2005-2019 (see compliance plot in subsection 2.2)

Figure 18: Annual mean gravimetric PM_2.5 measured at Rosia Road automatic monitoring site, 2005-2019 (see compliance plot in subsection 2.2)

Figure 19: The year-on-year gravimetric PM₁₀ and PM_2.5 concentration trend at Rosia Road automatic monitoring site, 2005-2019 (see trend plot in subsection 2.4)

Figure 20: The year-on-year gravimetric PM₁₀ concentration trend at Rosia Road automatic monitoring site, 2005-2019, split by wind direction sector (see trend plot in subsection 2.4)

Figure 21: The year-on-year gravimetric PM_coarse concentration trend at Rosia Road automatic monitoring site, 2005-2019, split by wind direction sector (see trend plot in subsection 2.4)

Figure 22: The percentage contribution of wind direction to daily mean gravimetric PM₁₀, PM_2.5 and coarse PM concentrations measured at Rosia Road automatic monitoring site, 2019 (see contribution plot in subsection 2.5)

Figure 23: Daily mean gravimetric PM₁₀ concentrations at Rosia Road automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

Figure 24: Daily mean gravimetric PM₁₀ concentrations at Bleak House automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

Figure 25: Daily mean gravimetric PM_2.5 concentrations at Rosia Road automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

Figure 26: Daily mean gravimetric coarse PM concentrations at Rosia Road automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

Figure 27: Variation in PM₁₀ concentrations (TEOM-FDMS data) measured at Rosia Road automatic monitoring site for different time periods, 2019 (see time variation plot in subsection 2.8)

Figure 28: Polar plots of daily mean gravimetric PM₁₀, PM_2.5 and coarse PM concentrations measured at Rosia Road automatic monitoring site, 2019 (see polar plot in subsection 2.7)

3.4 SO₂

Figure 29: p99.18 of 24-hr mean SO₂ concentrations measured at Rosia Road automatic monitoring site, 2005-2019 (see compliance plot in subsection 2.2)

Figure 30: p99.73 of 1-hr mean SO₂ concentrations measured at Rosia Road automatic monitoring site, 2005-2019 (see compliance plot in subsection 2.2)

Figure 31: The year-on-year SO₂ concentration trend at Rosia Road automatic monitoring site, 2005-2019 (see trend plot in subsection 2.4)

Figure 32: Daily mean SO₂ concentrations at Rosia Road automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

3.5 CO

Figure 33: Maximum daily 8-hr CO concentrations measured at Rosia Road automatic monitoring site, 2005-2019 (see compliance plot in subsection 2.2)

Figure 34: The year-on-year CO concentration trend at Rosia Road automatic monitoring site, 2005-2019 (see trend plot in subsection 2.4)

Figure 35: Daily mean CO concentrations at Rosia Road automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

3.6 Ozone

Figure 36: Maximum daily 8-hr ozone concentrations measured at Bleak House automatic monitoring site, 2005-2019 (see compliance plot in subsection 2.2)

Figure 37: The year-on-year ozone concentration trend at Bleak House automatic monitoring site, 2005-2019 (see trend plot in subsection 2.4)

Figure 38: Daily mean ozone concentrations at Bleak House automatic monitoring site over the year, 2019 (see calendar plot in subsection 2.6)

3.7 Benzene

Figure 39: Annual mean benzene concentrations measured at Rosia Road automatic monitoring site, 2005-2019 (see compliance plot in subsection 2.2)

Figure 40: Annual mean benzene diffusion tube concentrations, 2019 (see spot concentration plot in subsection 2.9)

Figure 41: Difference in annual mean benzene diffusion tube concentrations 2019 minus the mean of 2005-2018 concentrations (see spot concentration plot in subsection 2.9)

3.8 Mobile monitoring (AQMesh)

In 2018 three AQMesh pods were added to the Gibraltar automatic monitoring network. The AQMesh uses electrochemical sensors to measure gaseous pollutants and a light scattering methodology to measure particulate matter. The measurements are described as indicative because direct calibration with reference materials is not possible for the detection techniques used. The pods have periodically been co-located with the reference instruments at Rosia Road in order to characterise the outputs and provide the best estimate of reported concentrations. These new monitoring technologies have been used to investigate potential pollution issues and in doing so have added to the overall understanding of air quality in Gibraltar.

Table 4 provides a summary of the AQMesh pods and figure 42 shows the locations of the AQMesh pods in Gibraltar in 2019.

Table 4: Summary of mobile monitoring (AQMesh) sites in Gibraltar in 2019.

Site name	Measurement period	Polluants measured
Catalan Bay	29/04/2019 - 06/08/2019	NO, NO2, NOX, PM10, PM2.5 and CO
Devil’s Tower Road	15/11/2019 - 13/12/2019	NO, NO2, NOX, PM10, PM2.5 and CO
Europort Road	01/01/2019 - 08/07/2019, 26/07/2019 - 31/12/2019	NO, NO2, NOX, PM10, PM2.5 and CO
Rosia Road Clocktower	05/02/2019 - 30/08/2019, 18/09/2019 - 31/12/2019	NO, NO2, NOX, PM10, PM2.5 and CO

Figure 42: Location of AQMesh pods in Gibraltar, 2019 (see interactive map in subsection 2.1)

Figure 43: Interactive plot showing concentrations of NO, NO₂, NO_X, PM₁₀ and PM_2.5 measured at Catalan Bay AQMesh site, 2019 (see interactive time series plot in subsection 2.10)

Figure 44: Interactive plot showing concentrations of NO, NO₂, NO_X, PM₁₀ and PM_2.5 measured at Devil’s Tower Road AQMesh site, 2019 (see interactive time series plot in subsection 2.10)

Figure 45: Interactive plot showing concentrations of NO, NO₂, NO_X, PM₁₀ and PM_2.5 measured at Europort Road AQMesh site, 2019 (see interactive time series plot in subsection 2.10)

Figure 46: Interactive plot showing concentrations of NO, NO₂, NO_X, PM₁₀ and PM_2.5 measured at Rosia Road Clocktower AQMesh site, 2019 (see interactive time series plot in subsection 2.10)

CO is measured in mg m^–3 and as such is plotted separately to the other pollutants. CO concentrations measured at each AQMesh site are shown on the same plot.

Figure 47: Interactive plot showing concentrations of CO measured at Catalan Bay, Devil’s Tower Road, Europort Road and Rosia Road Clocktower AQMesh sites, 2019 (see interactive time series plot in subsection 2.10)

Figure 48: Polar plot of mean NO_X concentrations measured at Catalan Bay AQMesh site, 2019 (see polar plot in subsection 2.7)

Figure 49: Polar plot of mean NO_X concentrations measured at Devil’s Tower Road AQMesh site, 2019 (see polar plot in subsection 2.7)

Figure 50: Polar plot of mean NO_X concentrations measured at Europort Road AQMesh site, 2019 (see polar plot in subsection 2.7)

Figure 51: Polar plot of mean NO_X concentrations measured at Rosia Road Clocktower AQMesh site, 2019 (see polar plot in subsection 2.7)

Figure 52: Polar plots of mean PM₁₀, PM_2.5, and coarse PM concentrations measured at Catalan Bay AQMesh site, 2019 (see polar plot in subsection 2.7)

Figure 53: Polar plots of mean PM₁₀, PM_2.5, and coarse PM concentrations measured at Devil’s Tower Road AQMesh site, 2019 (see polar plot in subsection 2.7)

Figure 54: Polar plots of mean PM₁₀, PM_2.5, and coarse PM concentrations measured at Europort Road AQMesh site, 2019 (see polar plot in subsection 2.7)

Figure 55: Polar plots of mean PM₁₀, PM_2.5, and coarse PM concentrations measured at Rosia Road Clocktower AQMesh site, 2019 (see polar plot in subsection 2.7)

4.1 Compliance reporting sites

Table 5: Summary NO₂ statistics (automatic data), 2005-2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. annual mean concentrations).

Table 6: Summary PM₁₀ statistics (gravimetric data), 2005-2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. annual mean concentrations).

Table 7: Summary PM_2.5 statistics (gravimetric data), 2005-2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. annual mean concentrations).

Table 8: Summary SO₂ statistics, 2005-2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. annual mean concentrations).

Table 9: Summary CO statistics, 2005-2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. annual mean concentrations).

Table 10: Summary O₃ statistics, 2005-2019.

*AOT 40 is the sum of the differences between hourly concentrations greater than 80 μg m^-3, i.e. 40 ppb, and 80 μg m^-3, over a given period (the months of May-July) using only the 1-hr averages measured between 08:00 and 20:00 hrs.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. annual mean concentrations).

Table 11: Summary Benzene statistics (automatic), 2005-2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. annual mean concentrations).

Table 12: Summary Metals (arsenic, cadmium, nickel, lead) statistics, 2008-2019.

Table 13: Summary PAH (BaP) statistics, 2008-2019.

4.2 AQMesh indicative sites

Table 14: Summary NO₂ statistics (AQMesh data), 2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. mean concentrations).

Table 15: Summary PM₁₀ statistics (AQMesh data), 2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. mean concentrations).

Table 16: Summary PM_2.5 statistics (AQMesh data), 2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. mean concentrations).

Table 17: Summary CO statistics, (AQMesh data) 2019.

Caution is recommended when considering records with low data capture as these may not be representative of the full averaging period represented by the metric (e.g. mean concentrations).