The Highways Agency roadside air pollution monitoring network report

Transcription

1 Transport Research Laboratory The Highways Agency roadside air pollution monitoring network report - 27 by Savage A M, McCrae I S, Price J S, Anderson E (TRL) and Carslaw D (ITS University of Leeds) CPR192 Task Reference 396 (387) PUBLISHED PROJECT REPORT

2 Transport Research Laboratory CLIENT PROJECT REPORT CPR192 The Highways Agency roadside air pollution monitoring network report: 27 by Savage A M, McCrae I S, Price J S, Anderson E (TRL) and Carslaw D (ITS University of Leeds) Prepared for: Project Record: HA Framework Task Ref: 396 (387) Client: Impact of reduced emissions on air quality - 27 Highways Agency, Michele Hackman Copyright Transport Research Laboratory November 29 The views expressed are those of the authors and not necessarily those of the Highways Agency Name Date Approved Project Manager Anna Savage 27/1/29 Technica l Referee Ian McCrae 27/1/29

3 If this report has been received in hard copy from TRL, then in support of the company s environmental goals, it will have been printed on recycled paper, comprising 1% post-consumer waste, manufactured using a TCF (totally chlorine free) process. Contents Amendment Record This report has been issued and amended as follows Versio n Date Description Editor Technical Referee 1 9/1/8 First draft A Savage I McCrae 2 3/6/9 Second draft A Savage I McCrae 3 27/1/9 Final A Savage I McCrae TRL CPR192

4 Contents Executive summary i 1 Introduction 1 2 Data presentation: continuous measurements Annual summary M25 site M4 site M6 site Bell Common site Comparison with the UK Air Quality Strategy Objectives 11 3 Detailed analysis Long term trends Accounting for meteorology Trends in emissions Relationships between pollutants Emission sources Pollution episodes Particulate analysis 33 4 Non-continuous measurements Introduction: non-continuous measurements Aldehydes Hydrocarbons Polycyclic aromatic hydrocarbons Ammonia Heavy metals Results and discussion: non-continuous measurements Aldehydes Hydrocarbons Polycyclic aromatic hydrocarbons Ammonia Metals 47 5 Summary 5 6 Acknowledgements 52 References 53 Annex A1: Hourly data summary statistics: 1992 to Annex A2: Air Quality standards 7 Annex A3: Compliance with air quality standards, limits and objectives 74 TRL PPR447

5 Annex A4: Traffic flow data summary 77 Annex A5: Exhaust emissions estimates 79 Glossary of terms and abbreviations 82 TRL PPR447

6 List of Figures Figure 2.1: Hourly time series plots for the M25 site Figure 2.2: Hourly time series plots for the M4 site Figure 2.3: Hourly time series plots for the M6 site Figure 2.4: Hourly time series plots for the Bell Common site Figure 2.5: Time series of annual mean pollutant concentrations at the four monitoring sites...13 Figure 3.1: GAM smoothed trend of pollutant concentrations at the M Figure 3.2: GAM smoothed trend of pollutant concentrations at the M Figure 3.3: GAM smoothed trend of pollutant concentrations at the M Figure 3.4: Meteorologically adjusted NO X concentrations at the M Figure 3.5: Analysed trends of NO X concentrations plotted by wind direction at the M Figure 3.6: Meteorology adjusted diurnal NO X concentrations...19 Figure 3.7: Meteorology adjusted CO concentrations (by year and time of day)...19 Figure 3.8: Meteorology adjusted trends in NO 2 concentrations...2 Figure 3.9: Meteorology adjusted diurnal NO X concentrations...2 Figure 3.1: Typical diurnal profile (weekday and weekend flow), LDV and HDV, M25, Figure 3.11: Annual average daily traffic flow at M4, M25 and M Figure 3.12: Daily emissions of CO, M Figure 3.13: Daily emissions of NO x, M Figure 3.14: Daily emissions of PM, M Figure 3.15: Daily emissions of Hydrocarbons, M Figure 3.16: Daily emissions of CO 2, M Figure 3.17: Pairs plots for 27 pollutant concentrations...26 Figure 3.18: Calculated trends in primary NO 2 (f-no 2) at the M Figure 3.19: Bivariate polar plots for the M Figure 3.2: Wind rose diagram showing wind direction (from the Heathrow Airport meteorological site)...29 Figure 3.21: Bivariate polar plot for CO concentrations (by wind speed and direction) Figure 3.22: Bivariate polar plot for NO X concentrations (by wind speed and direction)....3 Figure 3.23: Bivariate polar plot for SO 2 concentrations (by wind speed and direction)....3 Figure 3.24: Bivariate plots for pollutants at the M4, Figure 3.25: Bivariate plots of pollutants at the M6, Figure 3.26: NO 2 pollution episode, 1-14 November TRL PPR447

7 Figure 3.27: Comparison of 24 hour mean concentrations using the Partisol and TEOM analysers...33 Figure 4.1: Estimated emissions of ammonia by UNECE source: (thousand tonnes)...36 Figure 4.2: Annual average concentrations of selected aldehydes at the M25 site Figure 4.3: Annual average hydrocarbon concentrations recorded at the M25 site Figure 4.4: Annual average benzene concentrations recorded at the M25 and M6 sites and three UK automatic hydrocarbon network sites Figure 4.5: Two-weekly average concentrations of benzo[a]pyrene at the M25 and M6 sites Figure 4.6: A comparison of the quarterly average concentration of benzo[a]pyrene measured across the Defra network and the HA M25 and HA M6 sites Figure 4.7: Comparison of the annual average B[a]P and B[a]A concentrations measured across the Defra network and HA M25 and M6 sites 23 to Figure 4.8: Average NH 3 concentrations Figure 4.9: Annual average metals concentrations at the M25 site 25 to 27 (to enable display iron data has been divided by 1 and platinum data has been multiplied by 1)...48 Figure 4.1: Annual average concentrations of legislated metals at four roadside sites and the M25 site TRL PPR447

8 List of Tables Table 1-1: List of parameters measured at each monitoring site...2 Table 2-1: Summary statistics of hourly averages for the M25 site Table 2-2: Summary statistics of hourly averages for the M4 site Table 2-3: Summary statistics of hourly averages for the M6 site Table 2-4: Summary statistics of hourly averages for the Bell Common site Table 2-5: Comparison with UK objectives and EU air quality limit values Table 3-1: Percentage change in daily emissions...24 Table 3-2: Percentage change in annual mean concentrations...25 Table 3-3: Yearly percentage change in daily emissions and annual mean concentrations, M Table 4-1: Annual average concentrations of selected aldehydes 27 (µg/m 3 )...37 Table 4-2: Summary statistics of daily hydrocarbon measurements at the M25 and M6 sites - 27 ( g/m 3 )...39 Table 4-3: Percentage change in annual average hydrocarbon concentrations at the M25 site...4 Table 4-4: Annual summary statistics of PAH compounds at the M25 site 27 (ng/m 3 )...41 Table 4-5: Annual summary statistics of PAH compounds at the M6 site 27 (ng/m 3 )...42 Table 4-6: Average ammonia concentrations at the M25, M4 and M6 sites 27 (µg/m 3 )...46 Table 4-7: Summary statistics for metals at the M25 site 27 (ng/m 3 )...47 Table 4-8: Annual average concentrations of heavy metals (ng/m 3 ) at four roadside sites and the M25 site TRL PPR447

9 TRL PPR447

10 Executive summary This report is the seventh of a series summarising air pollution monitoring activities associated with the Highways Agency (HA) long term roadside monitoring network. TRL has operated this network on behalf of the HA since the early 199s. Therefore some of these sites have now been in operation for more than 15 years, and thus represent a relatively unique series of data. In addition to these pollutant measurements, these sites also record traffic and local meteorological characteristics. There are currently four monitoring sites in operation, one on the M4 motorway, one on the M6 and two on the M25. The Cheltenham site on the A4 was decommissioned in October 26 as the road was no longer under control of the HA. To replace this, TRL set up an additional site within the Bell Common Tunnel on the M25 at the start of 27. A full description of the monitoring network is available in earlier reports (e.g. McCrae and Green, 24). This report provides an analysis of the data measured during the calendar year 27, and compares the data with UK Air Quality Strategy (AQS) objectives, although they do not strictly apply to these monitoring locations. These data are further combined with the historic data recorded at each of the sites to determine the trends in individual pollutant concentrations. This report has investigated a wider range of data mining tools than previous years to identify any statistically significant trends and key source contributions, using the M25 as a case study. For example, the report shows that after adjusting for meteorology, oxides of nitrogen (NO X) concentrations at the M25 have declined by 13%, at an average rate of 16 µg/m 3 per year over the entire monitoring time period although concentrations increased slightly from 25 to 27. The analysis further suggests that the main sources of NO X are emissions from heavy duty vehicles (HDVs). In contrast, nitrogen dioxide (NO 2) concentrations have shown an overall increase, particularly in later years. It was also evident that there has been a shift in the diurnal profile of NO 2 concentrations, suggesting that the main sources of NO 2 in 27 are diesel car emissions, compared to predominantly HDVs in concentrations of the Air Quality Strategy (AQS) pollutants were similar to levels recorded in 26 with annual average NO 2 concentrations exceeding the objective at all sites. NO 2 concentrations decreased slightly from 26 to 27 except at the M6 where levels increased from 45 µg/m 3 to 52 µg/m 3. This was probably driven by increases in the number of short-term hourly peaks. The hourly NO 2 objective was exceeded at the M25, M6 and Bell Common tunnel. Concentrations of PM 1 decreased at all sites and were within the objective at all sites except the Bell Common tunnel. There were no exceedances of the 8 hour mean ozone objective at any of the sites in 27. From the non-continuous pollutant monitoring, concentrations of the polycyclic aromatic hydrocarbon (PAH), benzo[a]pyrene, did not exceed the annual mean AQS objective guideline of.25 ng/m 3 at either the M25 or M6 and concentrations were slightly lower than those recorded in 26. Concentrations of ammonia were below the critical annual mean level of 8 g/m 3 at the M25 but were exceeded at the roadside M6 site. Concentrations of heavy metals at the M25 were significantly lower than those recorded during 26, well within specified targets or limit values. TRL i PPR447

11 1 Introduction The Highways Agency (HA) set up a network of roadside air pollution monitoring stations in the early 199s to improve their understanding of the relationship between emissions and roadside pollutant concentrations, and to provide a mechanism for the derivation of trends in both emissions and air quality. TRL operates this network on behalf of the HA and provides continuous measurements of a range of vehicle-related air pollutants as well as measurements of local traffic and meteorological conditions. The first monitoring station was installed on the M4 in 1992, and was shortly followed by monitoring stations on the M25, the A4 (Cheltenham) and M6. The M25 site was relocated in 24 due to road widening on the network and the Cheltenham site was decommissioned in 26 as the road was no longer under control of the HA. A new site within the Bell Common Tunnel on the M25 was set up at the start of 27. A considerable and relatively unique database of roadside measurements has now been derived which has allowed the data to be examined in detail to identify the impacts on roadside air quality of the changing vehicle fleet (e.g. traffic flows, fleet composition and fleet turnover), and to analyse impacts of a change in background air pollution contributions and meteorological effects. A summary of the pollutants monitored at each site and brief description of the methodology are provided in Table 11. TRL has previously published six annual reports that have described the monitoring sites and concentrations of data collected in detail, dealing with each pollutant at each site in turn. This year s report provides a summary of the concentrations recorded in 27 in comparison to previous years to provide an ongoing trend. A full statistical summary of the data measured at each site is provided in the appendices. This report has a slightly different structure to previous years as it focuses on specific areas of interest, using the M25 site as a case study. To achieve this, TRL has further developed the use of data mining and statistical tools that were introduced in the 26 report (Green et al, 28) to try and better understand some of the relationships and key sources at this site. In this report, data is now provided in terms of mass units, to be consistent with the latest Air Quality Strategy (AQS) (Defra, 27a). This report contains a summary of the key statistics from the continuous measurements in Chapter 2. Chapter 3 presents the findings of the more detailed data analysis and an overview of the non-continuous measurements is given in Chapter 4. Similarly to previous years, a summary and brief recommendations for future work are provided in Chapter 5. TRL 1 CPR192

12 Table 1-1: List of parameters measured at each monitoring site. Pollutant species measured and sampling method M4 Theale M25 Staines M6 Manchester Bell Common Carbon monoxide (CO) (infra-red absorption) Oxides of nitrogen (NO X), nitric oxide (NO) and nitrogen dioxide (NO 2) (chemiluminescence) Particulate matter (PM 1 and PM 2.5) (TEOM) (Partisol) (Osiris) Ozone (O 3) (UV absorption) Total hydrocarbons (HC) and methane (CH 4) (Flame ionisation detector) Sulphur dioxide (SO 2) (UV absorption) Hydrogen sulphide (H 2S) (UV absorption) Ammonia (NH 3) (passive diffusion tubes) Aromatic hydrocarbons (BTEX pumped samples - GC) Polycyclic aromatic hydrocarbons (PAH) (particle phase by Partisol - GC) Aldehydes (pumped samples - HPLC) Metals (particle phase by Partisol - ICP) Wind speed, wind direction, temperature, relative humidity Solar radiation Traffic flow (ATCs) To maintain the long term comparisons of PM 1 data, TEOM data has been corrected with a 1.3 factor in this report. However the TEOM analyser does not pass the PM 1 equivalence test when compared to the gravimetric EU reference sampler (Harrison, 26). Therefore, the volatile correction model (VCM) developed by the Environmental Research Group (ERG) at Kings College was used to provide a comparison with the TEOM results (for 27 only) in the summary tables. This system is based on the purge measurements from the FDMS (Filter Dynamic Measurement System) analysers (ERG, 29). A more detailed comparison of this correction method will be provided in subsequent monitoring reports. TRL 2 CPR192

13 2 Data presentation: continuous measurements 2.1 Annual summary The sections below present an overview of the key statistics for 27 for each monitoring site. The historical summary statistics and long term trends are presented in Annex A M25 site Table 21 presents the 27 summary statistics for the M25 site whilst Figure 2.1 presents the hourly time series data. A high data capture was achieved at the M25 site for the key pollutants covered by the UK Air Quality Strategy (AQS). However, due to continued problems with the hydrocarbon flame ionisation detector (FID), the data capture rates for hydrocarbons were lower, at approximately 53%. Table 2-1: Summary statistics of hourly averages for the M25 site 27. Pollutant Min Median Average Max Standard deviation Data capture (% of calendar year) CO (mg/m 3 ) NO (µg/m 3 ) NO 2 (µg/m 3 ) NO X (µg/m 3 ) O 3 (µg/m 3 ) PM 1 (µg/m 3 ) PM 1 (µg/m 3 ) (TEOM, data x 1.3) PM1 ( g/m 3 ) (VCM adjusted) PM 2.5 (µg/m 3 ) CH 4 (µg/m 3 ) NMHC (µg/m 3 ) H 2S (µg/m 3 ) SO 2 (µg/m 3 ) CW Vehicles/hr ACW Vehicles/hr CW AADT (veh/day) ACW AADT (veh/day) *CW clockwise direction, ACW anticlockwise direction TRL 3 CPR192

14 NO 2 ( g/m3) PM1( g/m 3 ) PM2.5( g/m 3 ) H2S ( g/m3) CH 4 ( g/m3) Jan Fe b Mar Apr May Jun Jul Aug Sept Oct Nov Dec Figure 2.1: Hourly time series plots for the M25 site 27. TRL 4 CPR192

15 2.1.2 M4 site Table 22 presents the 27 summary statistics for the M4 site and Figure 2.2 presents the hourly time series data. The key pollutants all have a data capture rate of approximately 9%, although similarly to the M25, problems with the FID resulted in a low data capture for the hydrocarbons, which results in these data being relatively unreliable. Table 2-2: Summary statistics of hourly averages for the M4 site 27. Pollutant Min Median Average Max Standard deviation Data capture (% of calendar year) CO (mg/m 3 ) NO (µg/m 3 ) NO 2 (µg/m 3 ) NO X (µg/m 3 ) O 3 (µg/m 3 ) PM 1 (µg/m 3 ) (TEOM, unadjusted) PM 1 (µg/m 3 ) (TEOM, data x 1.3) PM 1 ( g/m 3 ) (VCM adjusted) PM 2.5 (µg/m 3 ) (TEOM, unadjusted) CH 4 (µg/m 3 ) NMHC (µg/m 3 ) EB Vehicles/hr WB Vehicles/hr EB AADT (veh/day) WB AADT (veh/day) *EB- Eastbound direction, WB- Westbound direction TRL 5 CPR192

16 15 NOx ( g/m 3 ) NO 2( g/m 3 ) CO ( g/m 3 ) PM1( g/m 3 ) PM2.5( g/m 3 ) O 3( g/m 3 ) CH 4( g/m 3 ) NMHC ( g/m 3 ) Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Figure 2.2: Hourly time series plots for the M4 site 27. TRL 6 CPR192

17 2.1.3 M6 site Table 23 presents the 27 summary statistics for the M6 site and Figure 2.3 presents the hourly time series data. Due to some technical problems with the NO X analyser at the start of the year, the overall annual data capture was slightly lower than anticipated. These problems have since been resolved. Data capture rates for CO and particulate matter were higher. Table 2-3: Summary statistics of hourly averages for the M6 site 27. Pollutant Min Median Average Max Standard deviation Data capture (% of calendar year) CO (mg/m 3 ) NO (µg/m 3 ) NO 2 (µg/m 3 ) NO X (µg/m 3 ) O 3 (µg/m 3 ) CH 4 (µg/m 3 ) NMHC (µg/m 3 ) SO 2 (µg/m 3 ) H 2S (µg/m 3 ) PM 1 (µg/m 3 ) PM 1 (µg/m 3 ) (TEOM, data x 1.3) PM 1 ( g/m 3 ) (VCM adjusted) PM 2.5 (µg/m 3 ) PM 1 (µg/m 3 ) (Partisol) * PM 2.5 (µg/m 3 ) (Partisol) * CW Vehicles/hr ACW Vehicles/hr CW AADT (veh/day) ACW AADT (veh/day) *Statistics based upon 24-hr average concentrations TRL 7 CPR192

18 8 NO ( g/m 3 ) NOx ( g/m 3 ) NO 2( g/m 3 ) CO ( g/m 3 ) PM1( g/m 3 ) PM2.5 ( g/m 3 ) O 3( g/m 3 ) SO 2 ( g/m 3 ) H2S ( g/m 3 ) CH 4( g/m 3 ) NMHC ( g/m 3 ) Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Figure 2.3: Hourly time series plots for the M6 site 27. TRL 8 CPR192

19 2.1.4 Bell Common site Bell Common is a new monitoring site that was established on the network at the start of 27. The site is located within the Bell Common tunnel on the M25 in Hertfordshire. As this site is located within a tunnel, it is intended that these data will allow a better understanding of the long term trend in emissions as the pollutant concentrations will be less affected by meteorological changes. Table 24 presents the 27 summary statistics and Figure 2.4 presents the hourly time series data. The data capture rate was over 92%, except for particulate matter, which had a low capture rate of 32%. At this site, particulates are measured with a light scattering Osiris monitor, which was not installed until July 27. Table 2-4: Summary statistics of hourly averages for the Bell Common site 27. Pollutant Min Median Average Max Standard deviation Data capture (% of calendar year) CO (mg/m 3 ) NO (µg/m 3 ) NO 2 (µg/m 3 ) NO X (µg/m 3 ) O 3 (µg/m 3 ) PM 1 (µg/m 3 ) (OSIRIS) PM 2.5 (µg/m 3 ) (OSIRIS) PM 1 (µg/m 3 ) (OSIRIS) TSP (µg/m 3 ) (OSIRIS) Total traffic (veh/hr)* Annual average daily traffic (veh/day) *Traffic available in one direction only TRL 9 CPR192

20 NOx ( g/m3) NO 2( g/m3) CO ( g/m3) O 3( g/m3) PM1( g/m 3 ) PM2.5( g/m 3 ) 1 5 PM1 ( g/m 3 ) TSP ( g/m 3 ) Figure 2.4: Hourly time series plots for the Bell Common site 27. TRL 1 CPR192

21 2.2 Comparison with the UK Air Quality Strategy Objectives A summary of UK AQS objectives and EU limit values is given in Annex A2 and A3. With respect to the objectives, compliance is required by a specified date, ranging from 23 to 21. Similarly, compliance with EU limits is required by 25 and 21, dependent on the specific pollutant. In 27, an annual mean target for PM 2.5 was added to the UK AQS objectives with an urban background exposure target of 15% reduction by (Defra, 27a). It is important to note that these objectives do not apply at the HA roadside sites, as they are classified as areas not accessible to the public which means there is no relevant exposure. However, for information, it is still considered to be useful to compare the data with these criteria. Table 25 compares the data from all four sites against the UK AQS objectives and EU limit values. During 27 the annual mean NO 2 objective was exceeded at all four sites and the hourly objective was exceeded at all sites except the M4. The only site to exceed the two PM 1 objectives was the Bell Common tunnel, although this had a data capture rate of only 32%. Table 2-5: Comparison with UK objectives and EU air quality limit values 27. Pollutant Averaging period Concentration M25 M4 M6 Bell Common CO Max. daily running 8-hr mean NO 2 Max. of 18 exceedances of 1- hr mean 1 mg/m µg/m Annual mean 4 µg/m O 3 Max. of 1 exceedances of max daily running 8-hr mean TEOM adjusted PM 1 Max. of 35 exceedances of 24- hr mean 1 µg/m 3 5 µg/m Annual mean 4 µg/m Max. of 35 Partisol exceedances of 24- PM 1 hr mean 5 µg/m Annual mean 4 µg/m Max. of 35 Osiris exceedances of 24- PM 1 hr mean 5 µg/m Annual mean 4 µg/m TRL 11 CPR192

22 Pollutant Averaging period Concentration M25 M4 M6 Bell Common TEOM PM 2.5 Annual mean 25 µg/m Partisol PM 2.5 Annual mean 25 µg/m Osiris PM 2.5 Annual mean 25 µg/m Max. 3 exceedances of 24- hr mean SO 2 Max. 24 exceedances of 1- hr mean Max. 35 exceedances of 15- min mean 125 µg/m µg/m µg/m Figure 2.5 presents a summary of the trends in measured concentrations since monitoring commenced against these air quality criteria. A full data set is provided in Annex A4. TRL 12 CPR192

23 Objective - 35 M25 M4 M Objective - 4 M25 M4 M6 Bell Ye ar Ye ar Objective - 4 M25 M4 M6 Bell Objective - 18 M25 M4 M6 Ye ar Ye ar 12 1 M25 M4 M6 Bell M25 M4 M6 Bell Objective - 1 exceedences Year Ye ar Figure 2.5: Time series of annual mean pollutant concentrations at the four monitoring sites. TRL 13 CPR192

24 3 Detailed analysis This section investigates the continuously measured data in more detail focusing on analysing specific issues, such as investigating reasons for unusual trends, assessing the relationships between pollutants and better correlating trends in emissions with measured concentrations. New analytical techniques have been applied to the data to try to answer these questions and as such this section has a different structure to previous reports. The section considers data collected over the full time period up to Long term trends Previous annual reports have typically used rolling averages to present trends to assess long-term trends. This method has the advantage of smoothing the data to ignore short-term fluctuations. However, for this report, some alternative analytical tools are used to investigate these long-term trends in more detail to better explain some of the reasons for the changes observed over time. For example, these tools can remove the influence of meteorology on concentrations to make it easier to examine the direct relationship between roadside emissions and concentrations. The tools may also be used to identify important sources and determine how these have changed over time. The first approach that has been employed is to fit a smooth line across the time period to demonstrate the shape of the overall trend in concentrations. The analysis is conducted using a generalized additive model (GAM), which relates the concentration to time. Essentially, the GAM approach determines the optimum level of smoothing i.e. a curve that is neither too noisy nor too smooth (perhaps missing real features). Figure 3.1 shows the changes in concentrations using this method at the M25. Figure 3.1 clearly shows that concentrations of NO 2 have increased in recent years. Given that NO X concentrations have decreased, this trend is striking. For concentrations of PM 1, there was a decrease early on in the time series (from ), but over the past 1 years, concentrations have effectively remained constant. The time series for PM 2.5 is not as long as for the other pollutants, but there has been a tendency towards a slight increase in concentrations over the period. For CO, there has been a clear decrease in concentrations since monitoring began in Finally the trends for SO 2 and H 2S concentrations appear quite complex, with concentrations increasing during 25 then decreasing sharply at the end of that year. It seems likely that there is a common cause, although the reason for elevated concentrations of both pollutants is unclear. One possibility is due to work associated with the carriageway due to construction vehicles using different fuel qualities to road vehicles. Ozone concentrations have been relatively steady over the full time series, and have slightly decreasd. They show a good relationship with NO X as when concentrations of NO X decreased, ozone increased and vice versa. TRL 14 CPR192

25 5 8 NOX( µg m 3 ) NO 2( µg m 3 ) year year 6 2 PM1( µg m 3 ) PM 2.5 ( µg m 3 ) year year SO 2( µg m 3 ) 2 15 H 2S (µg m 3 ) year year CO(mg m 3 ) 1..5 O 3 ( µg m 3 ) year year Figure 3.1: GAM smoothed trend of pollutant concentrations at the M25. This GAM technique has also been applied to concentrations at the M4 (see Figure 3.2) and M6 (see Figure 3.3). Figure 3.2 shows that at the M4, concentrations of CO were relatively stable from , but then underwent an abrupt and large decrease in concentrations. This abrupt change appears to be greater than that seen at the other HA sites and other UK monitoring sites. Concentrations of NO X have decreased in a way similar to the M25 whereas concentrations of NO 2 are more complex, both increasing and decreasing during the time period. The trend in concentrations of PM 1 shows some TRL 15 CPR192

26 similarities with the M25 site: a decrease in concentration initially followed by a long period of stabilisation CO( mg m 3 ) NO X ( µg m 3 ) NO 2 ( µg m 3 ) year year year 5 4 PM 1 ( µg m 3 ) O 3 ( µg m 3 ) year year Figure 3.2: GAM smoothed trend of pollutant concentrations at the M CO( mg m 3 ).6.4 NO X ( µg m 3 ) 15 NO 2 ( µg m 3 ) year year year PM1( µg m 3 ) O 3 ( µg m 3 ) 1 5 O 3 ( µg m 3 ) year year year Figure 3.3: GAM smoothed trend of pollutant concentrations at the M6. Figure 3.3 shows that concentrations of CO at the M6 have decreased since 1999, although have levelled off since 22. Concentrations of NO X have remained relatively TRL 16 CPR192

27 stable since 1999, with a decrease in 26 followed by an increase in 27. A Mann- Kendall analysis showed that there was only relatively weak evidence of a downward trend in NO X since The trend in NO 2 concentration is highly complex as concentrations increased from 22-24, decreased from and then increased in 27. Concentrations of PM 1 have remained relatively stable over the period. 3.2 Accounting for meteorology Meteorology has an important effect on the dispersion of pollutants, which makes it difficult to interpret trends in pollutants because they can be hidden or conversely, emphasised by meteorological factors. A meteorological normalisation approach has been used to predict trends in concentrations to better reveal the trend in vehicle emissions, rather than changes due to meteorology. The approach used here uses regression trees (Veneables and Ripley, 22) and builds on earlier work by Carslaw and Taylor (28). These methods have advantages in that they can take account of sudden changes in the data, such as a site re-location. This approach was applied to the M25 site to investigate trends in NO X, NO 2 and CO in more detail. The M25 site was chosen as it has a high source strength, there is additional meteorological data available from Heathrow airport and it has a long time series. The M25 site also has a complex history as the site was moved in 24 due to the motorway widening scheme and there have been ongoing road works which have influenced measured concentrations. The key finding for NO X was that concentrations decreased with increasing wind speed and increasing temperatures. Figure 3.4 shows the results of applying this approach to monthly average NO X concentrations. This Figure shows a different trend to that in Figure 3.1, with a slight increase from 25. Over the entire time period, concentrations of NO X have decreased at a rate of 16 µg/m 3 per year (with a confidence of to µg/m 3 ). This reduction is statistically significant at the % confidence interval. 4 NO X ( µg m 3 ) year Figure 3.4: Meteorologically adjusted NO X concentrations at the M25. The analysis also shows that the highest concentrations are seen for winds with an easterly component and that there is a shift of about 1 degrees in wind direction at the beginning of 24, which might be associated with a site move or change in the road layout. Figure 3.5 shows concentrations according to the wind direction over the time period, where it can be seen that the largest decrease in concentration occurred TRL 17 CPR192

28 during winds from the east and south-east (i.e. the road itself). When the wind is blowing from the west, the monitoring site will not be receiving pollution from the motorway, so the concentrations are low NW -2.6 [-5.87,.87] units/year N 3.59 [-3.12, 6.92] units/year NE [-23.62, ] units/year *** 1 5 W [-5.1, -2.79] units /year *** E [-35.14, ] units/year *** NOX( µg m 3 ) 1 5 SW [-7.34,.6] units/year * S [-29.73, ] units/year *** SE [-37.21, -27.3] units/year *** year Figure 3.5: Analysed trends of NO X concentrations plotted by wind direction at the M25. The approach can also be applied to analyse concentrations by hour of day, to demonstrate a relationship that relates more to emissions than meteorology, as shown in Figure 3.6 below. The variation shown in this graph could usefully be compared with that calculated for emissions which would help show which vehicle classes dominate the concentrations at this site. This Figure suggests that the dominant source of NO x was heavy duty vehicles, as there were no clear increases in concentrations during peak hours. TRL 18 CPR192

29 3 NO X ( µg m 3 ) hour of day Figure 3.6: Meteorology adjusted diurnal NO X concentrations. Figure 3.7 shows that CO concentrations have had a surprisingly different trend to NO X, as levels showed a sharp decrease in 24, which has been sustained into 27. The diurnal pattern is also different, as it shows two distinct peaks during rush hours. This could suggest two different dominant sources: CO dominated by petrol-powered passenger cars, compared to NO X dominated by heavy vehicles CO( mg m 3 ) 1. CO( mg m 3 ) year hour Figure 3.7: Meteorology adjusted CO concentrations (by year and time of day). This technique was also applied to NO 2 concentrations. Figure 3.8 shows a large decrease in concentrations seen at the beginning of 24 into 25, then a large increase in NO 2 concentrations in 26 which was sustained into 27. Indeed, concentrations of NO 2 are now higher than those in 1996, despite large reductions in total NO X. TRL 19 CPR192

30 8 NO 2 ( µg m 3 ) year Figure 3.8: Meteorology adjusted trends in NO 2 concentrations. To look in detail at the changes in NO 2 trends, models were developed for the first full year of data (1997) and last full year of data (27) to compare the diurnal variation. An additional explanatory variable was included, based on measurements of background O 3 at the London Teddington site. Figure 3.9 shows that the diurnal profile for 1997 had a peak in the middle of the day, characteristic of HGV emissions (similarly to NO X). In contrast, the diurnal variation in 27 is quite different, showing an increase in NO 2 during the morning peak hours. One explanation for these changes is that in more recent years, the direct (primary) emissions of NO 2 have increased from diesel cars, which tend to have their peak flows during the am/pm peak NO 2 ( µg m 3 ) NO 2 ( µg m 3 ) hour hour a) 1997 b) 27 Figure 3.9: Meteorology adjusted diurnal NO X concentrations. Traffic data has been analysed to determine if there are any differences between diurnal traffic flows of light duty vehicles (LDVs) and heavy duty vehicles (HDVs) at the M25. This data has been obtained from the Highways Agency Traffic Information Database (TRADS) (HA, 24). Daily classified flows were obtained for the week beginning Monday 19 th February 27 for clockwise and anti-clockwise directions of travel which was found to be a typical 7 day period in 27. TRADS provides daily classified vehicle flows as the total volume split by vehicle length (cm). The vehicle TRL 2 CPR192

31 lengths were assumed to correspond to vehicle types as follows: category -52 cm represents all LDVs and the sum of categories cm, cm and 115+ cm represents total HDVs. Figure 3.1 illustrates an example of the diurnal profile for each day of the week for LDVs and HDVs. The graphs show that the typical peak for LDVs on weekdays occurs between 7: and 9: and between 16: and 18: which is expected due to this category being dominant by private cars exhibiting typical rush hour traffic peaks. The HDV profile is much flatter and the typical weekday peak occurs later in the day with the highest numbers observed at around 11: to 13:. A secondary early morning weekday peak in HDVs can also be observed at around 6: to 7:. Weekend peak LDV flow typically occurs at around 11: to 13:, with a secondary peak at around 18: on a typical Sunday. The weekend HDV flows are much lower than weekday and there is a peak at around 7: to 8: on a typical Saturday, with no noticeable peak in HDV flow on a typical Sunday. Figure 3.1: Typical diurnal profile (weekday and weekend flow), LDV and HDV, M25, 27. TRL 21 CPR192

32 3.3 Trends in emissions This section examines the changes in traffic flow over time at the M25, M6 and M4 and the impact this (coupled with the tighter vehicle legislation) has had on emissions. The rate of change in vehicle emissions is then compared with changes in concentrations of pollutants measured at each site. Figure 3.11 shows the change in annual average daily traffic (AADT) flows at the three sites from the early 199s to 27. The Figure clearly shows that traffic flows have steadily increased at all sites. AADT flows at the M25 are the highest of the three, at almost 2, in both directions in 27 (a 1% increase compared to a flow of around 18, in 1995). The traffic flow at the M4 has increased by 2% to over 115, vehicles a day in 27 from More detailed yearly traffic flows are provided for each site in Annex A ) y a14 /d h e12 (v T1 D A Date M4 M25 M6 Linear (M4) Linear (M25) Linear (M6) Figure 3.11: Annual average daily traffic flow at M4, M25 and M6. The hourly traffic data were used to derive an estimate of emissions associated with the traffic on the motorway adjacent to the monitoring site. This method is described elsewhere (McCrae and Green, 24), but uses an adapted version of the calculation method contained within the DMRB (Highways Agency et al, 27). The DMRB method incorporates average speed-related emission functions for cars, light goods vehicles, heavy goods vehicles and buses. In the absence of local and continuous speed or compositional data, estimates were derived from national statistics (DfT, 27). For all periods where valid traffic data were available, hourly, daily total and 28-day running mean emission estimates of CO, HC, NO X, PM and CO 2 were calculated. These are shown in Figure 3.12 to Figure 3.16 for the M25. These figures also show the annual average daily emissions, and provide a regression line, showing the trends in these emissions. The long term trend for the M25 and other sites is for a reduction in emissions of local air quality pollutants. In contrast, emissions of carbon dioxide have increased slightly TRL 22 CPR192

33 over time, in line with the increasing traffic flow and fuel consumption (as indicated in Figure 3.16 for the M25). Figure 3.12: Daily emissions of CO, M25. Figure 3.13: Daily emissions of NO x, M25. Figure 3.14: Daily emissions of PM, M25. TRL 23 CPR192

34 Figure 3.15: Daily emissions of Hydrocarbons, M25. Figure 3.16: Daily emissions of CO 2, M25. Table 31 provides a summary of the percentage change in daily emissions at each site from when monitoring began. A more detailed description of emissions is given in Annex A5 which shows the daily emissions split between light duty vehicles (LDVs) and heavy duty vehicles (HDVs) for each year at each site. Table 3-1: Percentage change in daily emissions. Site M25 (95-7) M4 (93-7) M6 (99-7) CO NO x PM HC CO 2 LDV HDV Total LDV HDV Total LDV HDV Total LDV HDV Total LDV HDV Total -83% -43% -81% -75% -37% -59% -41% -62% -53% -85% -52% -78% 1% 13% 5% -83% -5% -81% -77% -44% -62% -47% -69% -6% -85% -65% -8% 14% 5% 11% -7% -18% -67% -61% -15% -37% -35% -38% -37% -73% -24% -61% -1% 36% 12% TRL 24 CPR192

35 Despite the fact that traffic flows have increased at each site, this table shows that vehicle emissions of regulated pollutants have substantially declined over time, particularly in the case of LDV emissions. The continued improvements in fuel quality and reduction in emissions of new cars achieved through progressively tighter European emission standards counter-acts this increase in traffic. A similar table giving percentage change in concentrations over time is given in Table 32. This table shows a varied picture in terms of changes in concentrations over a long time period, although typically concentrations have declined as emissions have declined. For example, CO concentrations at the M25 and M4 have substantially declined, by more than 25%, whereas CO concentrations at the M6 have remained stable. 27 concentrations of CO at all three sites were similar to each other. The decrease in NO x emissions has led to a reduction in measured NO x concentrations, but concentrations of NO 2 have consistently increased at all sites, with a 55% increase at the M4. There may be many reasons for this, including a rise in the fraction of primary (direct) NO 2 emitted from vehicle exhaust. This is examined in more detail in the next section. In the last few years, there has also been major development close to the site at Green Park which may have resulted in additional local sources as well as long periods of slow moving traffic through the road works on the M4. Table 3-2: Percentage change in annual mean concentrations. Site CO NO 2 NO X PM CH 4 NMHC M25 (95-7) -267% 12% -129% -56% 7% -86% M4 (93-7) -3% 55% -64% -26% -36% -65% M6 (99-7) % 19% -2% 16% 3% -67% This relationship between changes in emissions and concentrations can be examined in more detail between years. Table 33 shows an example of this relationship for three pollutants at the M25 site. The data show that concentrations do not always decline each year in line with emissions. For example, CO emissions declined from and 26-27, but concentrations remained stable. Obviously there are other influences that affect measured concentrations, such as meteorology, which can change from year to year. Table 3-3: Yearly percentage change in daily emissions and annual mean concentrations, M25. Year CO emissions CO NO x emissions NO x NO 2 PM emissions PM 1 conc. conc. conc. conc. HDV LDV Total HDV LDV Total HDV LDV Total Relationships between pollutants One of the benefits of measuring a wide range of pollutant species at each monitoring site is that relations between pollutants or combination of variables can be explored. TRL 25 CPR192

36 Figure 3.17 compares the relationship of several pollutants measured at the M25, by day of the week. Figure 3.17: Pairs plots for 27 pollutant concentrations. The Figures show that the relationships between the pollutant pairs do not vary greatly by day of the week. The relationship between NO X and NO 2 is quite spread out and is non-linear, which is to be expected from the trends shown earlier in this report. In contrast, the relationship between PM 1 and PM 2.5 is more linear providing evidence of the same source. NO 2 is shown to decrease as O 3 levels increase, which is also to be expected due to the photochemical reactions between the two pollutants. Following on from the analysis in Section 3.2, detailed calculations have also been made of the trends between NO x and NO 2 by estimating the primary NO 2 fraction (f- NO 2) using the method of Carslaw and Beevers (25) as previously described in Green et al (28). It should be stressed that there is uncertainty in these results due to site re-locations and road works in Figure 3.18 shows that f-no 2 was very low prior to 22 and from the beginning of 23 onwards there was a marked increase. By 27, f-no 2 is estimated to be around % by volume. The trend does seem to reflect that of the meteorologically normalised trend in NO 2 concentration, which is to be expected. This provides further evidence that the increase in NO 2 concentration at the M25 site in recent years has been driven by changes in f-no 2. TRL 26 CPR192

37 15 f-no 2 (%) date Figure 3.18: Calculated trends in primary NO 2 (f-no 2) at the M Emission sources There are numerous ways in which emission sources can be identified and characterised. One useful exploratory technique is to use bivariate polar plots (Carslaw et al, 26). These plots show how concentrations vary depending on both wind speed and wind direction. Because wind speed can affect sources in different ways, it can be a useful technique to identify different source influences. For example, concentrations from a ground-level source such as vehicle emissions can vary with wind speed in a different manner compared with a high level source such as a chimney stack. At the M25, the source of the majority of the pollutants is the road, as demonstrated for CO, NO x and NO 2 in Figure 3.19 in 27. Some caution is however needed for several pollutants such as PM 1 and PM 2.5 where long-range transport of secondary particulate matter cannot be ruled out. In contrast, ozone concentrations show the opposite behaviour to NO X and the methane plot is more typical of that expected at a background site for ground level sources e.g. natural gas leakage. To interpret this Figure, the centre of the plot is zero wind speed and speed increases with distance from the centre. The colour scale on the right shows the concentration of each pollutant. TRL 27 CPR192

38 NO X in 27 at the M25 (µg m 3 ) CO in 27 at the M25 (mg m 3 ) N 35 N W E W E S -5 S. NO 2 in 27 at the M25 (µg m 3 ) PM 1 in 27 at the M25 (µg m 3 ) N 12 N W E 6 W E S 2 S 1 CH 4 in 27 at the M25 (µg m 3 ) NMHC in 27 at the M25 (µg m 3 ) N 1.65 N.12 W E W E S S.4.2. Figure 3.19: Bivariate polar plots for the M To conduct more in-depth analysis of the long-term trends at the M25, meteorological data was taken from the site at Heathrow airport, as it was decided it would be more reliable than the data collected at the monitoring site as it data complies with Met. Office guidelines. Figure 3.2 shows the wind direction for each year from , where typically the prevailing wind direction is from the south west. TRL 28 CPR192

39 to to to 2.25 > 2.25 to to to 2.25 > 2.25 to to to 2.25 > to to to 2.25 > (ms 1 ) (m s 1 ) (m s 1 ) (m s 1 ) to to to 2.25 > 2.25 to to to 2.25 > 2.25 to to to 2.25 > to to to 2.25 > (ms 1 ) (m s 1 ) (m s 1 ) (m s 1 ) to to to 2.25 > 2.25 to to to 2.25 > 2.25 to to to 2.25 > to to to 2.25 > (ms 1 ) (m s 1 ) (m s 1 ) (m s 1 ) Figure 3.2: Wind rose diagram showing wind direction (from the Heathrow Airport meteorological site). Firstly, CO was considered because this pollutant provides a good tracer for road traffic emissions, as demonstrated in Figure For CO, the highest concentrations are for low wind speeds as shown by the proximity of the high concentrations to the centre of the plot and for easterly winds i.e. from the direction of the M25 (and London). This concentration pattern is typical of a road in an open area. There are no other obvious sources of CO which is as expected. Figure 3.21: Bivariate polar plot for CO concentrations (by wind speed and direction). TRL 29 CPR192

40 The bivariate polar plot for NO X shows a similar pattern to CO with the main source being from the motorway itself (Figure 3.22). There is some limited evidence of a source to the north, although it should be noted that Figure 3.2 shows that there are very few conditions when the wind is from the north. Figure 3.22: Bivariate polar plot for NO X concentrations (by wind speed and direction). The pattern is more complex for concentrations of SO 2 as seen in Figure 3.23, where although there is still evidence of a strong road source, there is also evidence of sources to the east that are important at higher wind speeds. The most likely explanation is due to stack emissions in the east Thames corridor. There is also some evidence of a source to the west that is important at high wind speeds. Again, this is most likely due to an industrial stack. Figure 3.23: Bivariate polar plot for SO 2 concentrations (by wind speed and direction). As previously noted, concentrations of SO 2 and H 2S were much higher during 25. An investigation into these concentrations indicates that there were sources to the south for higher wind speed ranges and to the north-east. It is unknown what these sources could be, but they could be due to emissions from vehicles or plants associated with the road widening scheme. This technique was also applied to the 27 data at the M4 and M6 (Figure 3.24 and Figure 3.25). Using CO as a marker for local traffic activity, it was found that concentrations at the M4 are dominated by low wind speeds from the south-west and north-east. For NO X there is some evidence of an additional source to the north, which TRL 3 CPR192

41 is also seen for NO 2. For NO X, CO, NO 2 and PM 1 there is evidence of a source for high wind speed conditions from the south-west. For PM 2.5 a source to the north-east of the site is prominent, which is not the case for most of the other pollutants. O 3 in 27 at the M4 (µg m 3 ) NMHC in 27 at the M4 (µg m 3 ) NO X in 27 at the M4 (µg m 3 ) CO in 27 at the M4 (mg m 3 ) W N E W N E W N E W N E S 2 S.1 S 5 S.5 CH 4 in 27 at the M4 (µg m 3 ) PM 2.5 in 27 at the M4 (µg m 3 ) NO 2 in 27 at the M4 (µg m 3 ) PM 1 in 27 a t the M4 ( µg m 3 ) W N S E W N S E W N S E W N S E Figure 3.24: Bivariate plots for pollutants at the M4, 27. At the M6, sources were also complicated, for example, NO x and NO 2 concentrations were dominated by the sources from the south-east, whereas CO had two sources, from the south-east and north-west. PM 1 also had a source at high wind speeds from the south-west. It is likely that there is greater source complexity at these two sites compared with the M25. It is recommended that a detailed consideration of the local environment be carried out to help identify the most important source categories. TRL 31 CPR192

42 NO X in 27 at the M6 (µg m 3 ) 16 N CO in 27 at the M6 (mg m 3 ) N.35.3 O 3 in 2 7 at the M6 (µg m 3 ) N 6 H 2 S in 27 at the M6 (µg m 3 ) N 9 8 W E W E.25.2 W E 5 4 W E S 2 S.1 S 2 S 3 2 NO 2 in27 at the M6 (µg m 3 ) PM 1 in27 at the M6 (µg m 3 ) SO 2 in 27 at the M6 (µg m 3 ) PM 2.5 in 27 at the M6 (µg m 3 ) W N E W N E W N E W N E S S 1 S 4 S 5 CH 4 in 27 at the M6 (µg m 3 ) N NMHC in 27 at the M6 (µg m 3 ).7 N.6.5 W E 1.35 W E S 1.25 S.2 Figure 3.25: Bivariate plots of pollutants at the M6, Pollution episodes In contrast to 26 when there were no exceedances of the NO 2 hourly mean AQS objective of 2 µg/m 3, both the M25 and M6 exceeded the objective in 27, with exceedances on approximately 3 occasions. The Bell Common tunnel also exceeded the objective, but this was to be expected due to the high pollutant concentrations measured within the tunnel. The majority of the NO 2 hourly exceedances occurred in winter months, during February 27 at the M25 and in November-December 27. This was probably due to cold and calm weather conditions and this was seen at other sites in the UK. Figure 3.26 shows the widespread NO 2 exceedances in early November at both sites, compared to other UK roadside monitoring sites. It was reported that on Tuesday 11 th November, the weather conditions resulted in a widespread primary pollution NO 2 episode which was thought to be the most significant NO 2 incident for 1 years (ERG, 28). 27 saw little in the way of PM 1 episodes, except during bonfire night in November and there was a moderate episode in London and the south-east between 25 th -28 th March. This was likely to be due to an influx of pollution from the continent, combined with local emissions and poor dispersal (ERG, 28). TRL 32 CPR192

43 45 4 Bury Roadside Camden Kerbside Manchester Piccadilly g / m µ 25 n tio tra n ce 2 n o C London Marylebone Road M25 M : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : Date and time 1th Nov 11th Nov 12th Nov 13th Nov 14th Nov Figure 3.26: NO 2 pollution episode, 1-14 November Particulate analysis Comparisons between particulate concentrations measured by the Partisol and the TEOM analyser at the M6 continued during 27, as a poor correlation was found between the two methods in 26. Figure 3.27 shows the 24 hour mean concentrations of PM 1 and PM 2.5 using both methods Concentration µg/m Partisol PM1 TEOM PM1 TEOM PM1*1.3 Concentration µg/m Partisol PM2.5 Figure 3.27: Comparison of 24 hour mean concentrations using the Partisol and TEOM analysers. Generally, the PM 1 TEOM data shows a good relationship with the Partisol data, except during October and November, when the Partisol had higher readings. These higher readings were also seen for the PM 2.5 data, although the annual mean readings were comparable (13.5 µg/m 3 from the TEOM and 13.6 µg/m 3 from the Partisol). Similarly to 26, the Partisol compared better to the raw TEOM data. For example, the PM 1 annual mean recorded by the Partisol was 22.6 µg/m 3, compared to 2.7 µg/m 3 recorded by the TEOM (28.3 µg/m 3 when the TEOM measurement was adjusted by a factor of 1.3). The number of exceedances of the 24 hourly objective was recorded as 13 from the TRL 33 CPR192

44 TEOM (adjusted) and 7 from the Partisol. Note that the Partisol only had a data capture rate of 65% for the year. This comparison will continue to be explored in future reports at the M6 as well as the M25 as TRL has recorded the particulate mass from the Partisol at this site since January 28. In addition, due to the fact that the TEOM does not meet the UK equivalence tests, TRL is looking to install a TEOM-FDMS instrument for comparison at one of the HA sites during 29. In the 28 report, the TEOM data will also be corrected using the Volatile Correction Method (ERG, 29) to compare against the 1.3 factor. One of the recommendations in the 26 report was to explore the relationships between PM 2.5 and PM 1, for example to identify the contribution of the secondary particulate component. This is an area of work that TRL aims to develop in the future, by comparing concentrations with a suitable background site and undertaking analysis of PM composition from the filters collected by the Partisols at the M6 and M25 sites. TRL 34 CPR192

45 4 Non-continuous measurements 4.1 Introduction: non-continuous measurements Aldehydes Formaldehyde and acetaldehyde are the most abundant of the carbonyl compounds (commonly known as aldehydes). Formaldehyde has the most implications for human health, including eye, skin and respiratory irritation and neurophysical and behavioural effects (at particularly high levels) (Green et al, 28) and is therefore the most widely studied aldehyde species. Formaldehyde is released in the exhaust gases of vehicles not equipped with catalytic converters. In the indoor environment, products containing formaldehyde (resins, glues, insulating materials, chipboard, plywood and fabrics) remain in common use. Other sources include cigarette smoke, heating and cooking. Aldehydes are not covered by the EU Air Quality Daughter Directive (EU, 28) and are subsequently not included in the UK Air Quality Regulations. Health based guidelines, however, have been produced for ambient concentrations of formaldehyde by the World Health Organisation (WHO) and recommended limits for both formaldehyde and acetaldehyde have been produced by the Committee on the Medical Effects of Air Pollutants (COMEAP) on behalf of the UK Department of Health. COMEAP recommends concentrations less than.1-.2 mg/m 3 for formaldehyde and less than 9 mg/m 3 for acetaldehyde to prevent sensory irritation, and the WHO recommends an air quality guideline value of.1 mg/m 3 as a 3-minute average for formaldehyde to prevent significant sensory irritation in the general population (WHO, 2) Hydrocarbons The UK automatic hydrocarbon monitoring network measures 25 hydrocarbon species, selected for their photochemical oxidant formation potential and possible health impacts. Within the HA network, a smaller number of hydrocarbons are separately monitored by a non-continuous method which allows for the measurement of a range of aromatic hydrocarbons including benzene, toluene, ethylbenzene, meta-, para- and ortho-xylene (collectively known as BTEX). No ambient limits or objectives apply to toluene, ethylbenzene, or the xylenes and adverse health effects caused by these hydrocarbons are unlikely to arise at normal ambient concentrations. Several hydrocarbons are classified as carcinogens and two of these are included within the AQS Regulations which sets objectives for 21 for running annual means of g/m 3 for benzene and 2.25 g/m 3 for 1,3-butadiene. The largest outdoor source of benzene is exhaust from petrol engined vehicles, combined with petrol refining and distribution (Defra, 27b) Polycyclic aromatic hydrocarbons Polycyclic aromatic hydrocarbons (PAHs) are a large group of chemical compounds with a similar structure comprising two or more aromatic rings. PAHs are formed in all processes which involve incomplete combustion of carbon-based fuels. In the UK, the main sources of PAHs are domestic coal and wood burning, fires, road transport, anode baking, and coke and aluminium production (Defra, 27b). A number of individual PAHs have been classified as likely carcinogens by the International Agency for Research on Cancer (IARC) (IARC, 26). While it is accepted that the risk of cancer is associated with the whole PAH mixture, the Expert Panel on Air Quality Standards (EPAQS) (1999) concluded that available evidence supported the use of a single PAH compound (benzo[a]pyrene: B[a]P) as a representative marker. An TRL 35 CPR192

46 average annual concentration for B[a]P of.25 ng/m 3 was adopted by Defra as a UK AQS objective for PAHs (Defra 27a) Ammonia Ammonia emissions contribute to eutrophication and acidification of soils and water, causing damage to sensitive plant communities and aquatic ecosystems (Defra, 22). The main source of ammonia in the UK is from agricultural practices (see Figure 4.1) with around 91% of total emissions arising from that source. The next largest sources, both contributing 3% of total emissions, are road transport and waste treatment and disposal. Figure 4.1 also shows that total emissions from road transport have decreased over the period 21 to 26. To date, little action has been taken to control ammonia emissions. This is perhaps due to the fact that, unlike other pollutants where application of a single technology can produce large cuts in emissions, ammonia is emitted from several sources over large areas so several methods are needed for successful control (Defra, 22). Emission reduction targets for 21 have been outlined in the Protocol to Abate Acidification, Eutrophication and Ground-level Ozone (UNECE, 1999) and the National Emission Ceilings Directive (EC, 21). Ammonia is also a precursor to secondary particulate matter. It was anticipated that an ammonia objective may be included in the updated UK Air Quality Strategy (Defra, 27a); however, this was not considered appropriate at the time. Figure 4.1: Estimated emissions of ammonia by UNECE source: (thousand tonnes) Heavy metals Heavy metals are stable chemical elements that cannot be degraded or destroyed and therefore tend to accumulate in soils and sediments. Human activities have altered the biochemical and geochemical cycles and balance of some metals. The principal manmade sources of heavy metals include industrial point sources (mines, foundries and smelters) and diffuse sources (including combustion by-products from road transport). Relatively volatile heavy metals and those that become attached to airborne particles can become widely dispersed over large areas. Emissions of heavy metals are addressed by the 1998 Protocol to the 1979 Convention on Long-Range Transboundary Air Pollution (CLRTAP), which targets cadmium, lead and TRL 36 CPR192