Ambient air SO2 patterns in 6 European cities

Accepted Manuscript AKnowledger SO2 patterns in 6 European Cities Susann Henschel, Xavier Querol, Richard Atkinson, Marco Pandolfi, Ariana Zeka, Alain Le Tertre, Antonis Analitis, Klea Katsouyanni, Olivier Chanel, Mathilde Pascal, Catherine Bouland, Daniela Haluza, Sylvia Medina, Patrick G. Goodman PII:

S1352-2310(13)00462-7

DOI:

10.1016/j.atmosenv.2013.06.008

Reference:

AEA 12241

To appear in:

Atmospheric Environment

Received Date: 13 November 2012 Revised Date:

17 May 2013

Accepted Date: 5 June 2013

Please cite this article as: Henschel, S., Querol, X., Atkinson, R., Pandolfi, M., Zeka, A., Le Tertre, A., Analitis, A., Katsouyanni, K., Chanel, O., Pascal, M., Bouland, C., Haluza, D., Medina, S., Goodman, P.G., AKnowledger SO2 patterns in 6 European Cities, Atmospheric Environment (2013), doi: 10.1016/ j.atmosenv.2013.06.008. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Manuscript changes accepted Click here to download Manuscript: Manuscript file REVISION_changes_accepted.docxClick here to view linked References

ACCEPTED MANUSCRIPT Ambient air SO2 patterns in 6 European Cities

Susann Henschela ● Xavier Querolb ● Richard Atkinsonc ● Marco Pandolfib ● Ariana Zekad ● Alain Le Tertree ● Antonis Analitisf ● Klea Katsouyannif ● Olivier Chanelg ● Mathilde Pascale ● Catherine Boulandh ● Daniela Haluzai ● Sylvia Medinae, * ● Patrick G. Goodmana

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*on behalf of the Aphekom collaborative network

Affiliations: a

Dublin Institute of Technology, Focas Institute, Camden Row, Dublin 8, Ireland, Dublin Institute of Technology, School of Physics, Kevin Street, Dublin 8, Ireland, e-mail: [email protected], [email protected]; b

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Institute of Environmental Assessment and Water Research, Spanish Research Council (IDÆA-CSIC), c/Jordi Girona 18-26, 08034 Barcelona, Spain, e-mail: [email protected], [email protected]; c

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St. George‟s, University of London, Cranmer Terrace, London SW17 0RE, United Kingdom, e-mail: [email protected]; d

Brunel University, Halsbury Building, Room 149, Kingston Lane, Uxbridge, Middlesex, UB8 3PH, United Kingdom, e-mail: [email protected]; e

Department of Environmental Health, French Institute for Public Health Surveillance (InVS), 12 rue du Val d'Osne, 94415 Saint Maurice, CEDEX France, e-mail: [email protected], [email protected], [email protected]; f

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Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, 75 Mikras Asias Street, Goudi, Athens, Greece GR-11527, e-mail: [email protected], [email protected]; g

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Aix-Marseille University (Aix-Marseille School of Economics), CNRS & EHESS, GREQAM and IDEP, 2 rue de la Charité, 13002, Marseilles, France, e-mail: [email protected]; Ecole de santé publique, Campus Erasme, Université libre de Bruxelles, ULB CP593, route de Lennik 808, 1070 Bruxelles, e-mail: [email protected]; i

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Institute of Environmental Health, Centre for Public Health, Medical University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria, e-mail: [email protected]

Corresponding author: S. Henschel () Dublin Institute of Technology, Focas Institute, Camden Row, Dublin 8, Ireland; Phone: +353(0)1-402-7978 Fax: +353 (0)1-402-7904 e-mail: [email protected]

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ACCEPTED MANUSCRIPT Abstract

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Introduction: An analysis of the hourly SO2 pollution patterns with time can be a useful tool for policy makers and stakeholders in developing more effective local policies in relation to air quality as it facilitates a deeper understanding of concentrations and potential source apportionment. A detailed analysis of hourly inter-annual, seasonal and weekday-specific SO2 concentration patterns using data obtained from 6 cities involved in the Aphekom project was conducted. This type of analysis has been done for other pollutants but less so for SO2, and not in a systematic fashion for a number of European cities. Methods: Individual diurnal SO2 profiles and working weekday versus weekend specific 24-hr plots were generated using hourly SO2 measurements from a roadside and an urban background monitoring sites for 1993, 2001 and 2009 for each of the 6 European cities (Athens, Barcelona, Brussels, London, Paris, and Vienna). This facilitated the assessment of city specific patterns and comparison of changes with time. Results: SO2 concentrations varied throughout the day and tended to be lower on the weekends. A general decreasing trend for SO2 levels with time was observable at all stations. Discussion & Conclusion: This study provides a useful European perspective on patterns of exposure. For the 6 EU cities examined, road traffic, heating, and shipping in port cities appeared to be important sources of SO2 emissions, and hence the driving components widely reflected in the diurnal profiles with lower level on the weekend likely due to lower traffic volume and industry related emissions. Although ambient SO 2 concentrations have fallen over the assessed study period at all measurement sites, the daily patterns remained relatively unchanged.

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Keywords: air pollution; hourly SO2; diurnal variation; diurnal profile; weekday vs. weekend

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ACCEPTED MANUSCRIPT 1. Introduction

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Events such as the London smogs (Godlee, 1991; Bell and Davis, 2001; Nemery et al., 2001) raised awareness of the public and policy makers to the potential for sulphur dioxide 1 (SO2) to cause adverse health effects on humans. In the 1990s, epidemiological studies suggested adverse health effects even from historically low levels of air pollution (Sunyer et al., 2003; Pope and Dockery, 2006). This evidence led to the development and implementation of numerous legislations regulating different aspects of air pollution, such as air quality limit values and guide values for SO2. In particular, the EU Council Directive for SO2 (89/427/EEC) implemented in 1993 specified that the annual average value should not exceed 80μgm-3 (median of daily mean values) with an associated value for suspended particulates of 150 μgm-3 and that the daily average value of 250 μgm-3 for SO2 must not be exceeded for more than three consecutive days (EU, 1989). Further more stringent directives, 1999/30/EC and 2008/50/EC (EU, 2008), amended Directive 89/427/EEC (EU, 1999).

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Despite current low levels of SO2, evidence for adverse health effects persist (Aphekom Summary Report, 2011) although their causality has been questioned (COMEAP, 2009). However, intervention studies have demonstrated health benefits from reducing SO2 levels (Hedley et al., 2002; Henschel et al., 2012). Evidence for a safe threshold level of ambient daily SO 2 mean concentrations below which no effect on human health is observed remains inconclusive (WHO, 2006; U.S._EPA, 2008). In addition, SO2 is involved in the formation of ammonium sulphate, a component of secondary fine particles, also linked to adverse health effects (NARSTO, 2004). Gaps remain in our understanding of the health effects from both short- and long-term exposure to SO2.

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Knowledge of diurnal, weekday and seasonal pollution patterns can assist in understanding of city specific exposure patterns. This kind of analysis can be useful to policy makers and stakeholders to develop, and set, more effective local policies for emission abatement and pollution control. The approach has been widely used in past studies to characterise pollutant dynamics and variations in single and multiple locations within one country (Flemming et al., 2005; Jo and Park, 2005; Lonati et al., 2006; Dodson et al., 2009; Zhao et al., 2009; Kalabokas et al., 2010; Bigi et al., 2012). These studies mainly focused on the analysis of pollutants, such as particulate matter, PM10 2 and PM2.53, ozone 4 (O3) and nitric oxide 5 (NOx) comparing diurnal variations of these pollutants with time. Additionally hourly pollutant profiles have been used in a number of studies in the assessment of a specific event and its effect on air quality (Ebelt et al., 2001; Lee et al., 2005; Xie et al., 2005; Cai and Xie, 2011; Whitlow et al., 2011). To our knowledge fewer studies have used this approach in the study of SO 2 (Ebelt et al., 2001; Xie et al., 2005; Moreno et al., 2009); these focused on a single or multiple locations within one country.

2. Methods

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We studied SO2 concentration patterns in 6 cities from 6 different EU countries with different air pollution sources, climatic and geographic conditions. To facilitate presentation of the data we focus on three years 1993, 2001 and 2009 to compare hourly profiles, when pollution sources and regulations were different to provide a better understanding of the local patterns, potential sources of SO2 and changes with time.

Hourly mean SO2 concentrations were obtained from six cities within the Aphekom project: Athens, Barcelona, Brussels, London, Paris, and Vienna. Data was compiled for one roadside and one urban background 6 (UB) stationary monitoring station with measurements available from 1993 to 2009 (17 years).The assumption was made that the monitoring sites were representative of the city-specific patterns and trends in SO2 concentrations for that city. Although not designed to characterize city-wide air quality patterns and trends, this study focuses on providing a representative view of SO2 concentrations and trends at a typical UB and roadside location per city - henceforth referred to as “roadside SO2 and UB SO2 concentrations”. Where more than one monitoring station(s) were available for each city, the stations with the most complete data for the study period were selected. No transformation was used for missing data; a priori, a maximum of 25% of missing data per year was set as an exclusion criterion for the years selected for presentation. The “Online Appendix, OA” Table OA-

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SO2 = sulphur dioxide PM10 = particulate matter with a median diameter of less than 10 microns 3 PM2.5 = particulate matter with a median diameter of less than 2.5 microns 4 O3 = ozone 5 NOx = nitric oxide 6 UB = urban background 2

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City-specific diurnal plots by year, season and weekday using local times were generated. Additionally, hourly SO2 averages for weekdays (Monday to Friday) and the weekend (Saturday to Sunday) were plotted for each city to compare variations. Differences in weekend vs. weekday SO2 concentrations were assessed applying the Kruskal-Wallis test. For the purpose of brevity we only illustrate graphs of diurnal, roadside and UB SO2 profiles and weekend vs. weekday plots for selected stations for the specific years 1993, 2001 and 2009. (Additional plots are available in the OA).

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Analysis of temporal trends at each site were conducted using the Theil-Sen method (Theil, 1950; Sen, 1968), in R (R Development Core Team, 2011; Carslaw and Ropkins, 2012; Carslaw, 2013). This was applied to the monthly SO2 averages to calculate the regression parameters of the trends with time and stratified by season, including slope, uncertainty in the slope and the p-value. This method yields accurate confidence intervals even with non-normal data and it is less sensitive to outliers and missing values (Hollander and Wolfe, 1999). Data were deseasonalized by using the STL (seasonal trend decomposition using loess) and all the regression parameters were estimated through bootstrap re-sampling. The slopes indicate how concentrations have changed through time and are expressed in units (μgm-3) per year. The p-values show whether the calculated trends are statistically different from zero. A statistically significant trend was assumed at the 95th percentile significance level (p<0.05). 3. Results 3.1 General features

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Summary population data, annual mean concentration of SO2 for 1993 and 2009, and mean temperature [°C] and humidity for each city are presented in Table 1. All cities apart from Athens had comparable levels of roadside SO2, temperature and humidity, additionally roadside SO2 levels in Athens were higher than other cities by a factor of 2 to 3 fold; we do not believe that this can solely be explained by the higher temperatures and lower humidity. UB levels were broadly similar between all cities. The correlations between the roadside and UB station for each city are presented in Table 2. In most cities the correlations were comparable apart from Barcelona with a low correlation of 0.3. Figure 1 shows the annual mean roadside SO2 concentrations in the 6 cities from 1993-2009; the corresponding UB concentrations are provided in Figure OA-1. Additional plots showing daily, weekday-specific and monthly SO2 concentrations are provided in the OA: Figure OA-2, 3, 6 to 8. Overall a decreasing trend with time in SO2 is observed at all stations. However, the decrease with time did not occur in a smooth consistent or linear fashion, but showed inter-annual variability , some of which might be explained by meteorological conditions (Figure 1 and Figure OA-1). Initially high roadside SO2 levels of comparable magnitude were observed in both Athens and Paris; levels in all cities dropped to roughly similar levels to each other by 2004, apart from Athens where the decline was not as dramatic. Overall the lowest concentrations were observed for Vienna and Barcelona. Initially annual average SO2 concentrations at the roadside sites were higher than the UB levels in all cities up to the year 2005. In more recent years UB and roadside concentrations approximated and this pattern inverted with mean annual UB levels being (marginally) higher than roadside levels in all cities - except Athens - due to the marked, continuous decrease in roadside SO2 levels with time (Table 1; Figure 1 & OA-1).

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An analysis of the trends using the Theil-Sen method is presented in Table 3 (and in Figure OA-4&5). Decreasing concentrations with time were observed at roadside and UB sites in all cities. The rates (percentage decrease) of the total decline in annual average SO2 levels varied between the cities with the largest decreases in Paris and London and the smallest in Athens for roadside, and the largest in London and smallest in Barcelona for UB sites. When season was considered, a larger decrease [μgm-3/year] was observed for winter months (Dec.-Feb.) and least during summer (Jun.-Aug.). The observed difference between the decrease in winter vs. summer was partly due to the fact that the highest SO2 concentrations were observed during the winter months. This is affirmed when looking at the average percentage change per year which is found to be higher during summer for the majority of cities. 3.2 Hourly SO2 patterns in the 6 EU cities

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ACCEPTED MANUSCRIPT Figure 2 to Figure 4 show diurnal roadside and UB SO2 profiles (24-hr plots) for the 6 cities for the selected years, 1993, 2001 and 2009, respectively, summarised in Table 4. Please note that in order to highlight differences in diurnal variations in SO2 between the 6 different cities the scale of the y-axis differs between the above mentioned Figures. 3.3 Diurnal variation in SO2 concentrations

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Comparing across cities, the SO2 levels across the 24-hr day, were markedly higher in Athens throughout the entire study period and in Paris up to 2001 for roadside sites. If the data are normalised to annual 24-hr averages, then similar patterns are observed in all cities, suggesting Athens in terms of diurnal variation is no different to the other cities (Figure OA-9 and OA-11). The majority of the cities experienced a significant decrease in hourly SO2 level with time, with roadside SO2 levels below 10µgm-3 by the mid-2000s and below 6µgm-3 by 2008/9 in all cities except Athens. It has to be noted that the lower detection limit of the measurement equipment poses a clear limitation to interpret these very low hourly levels in some of the cities (Table OA- 1) (Umweltbundesamt, 2012). The occurrence of the morning SO2 peak was a common feature to all cities at both UB and roadside sites. In addition, when comparing the different cities, SO2 peak concentrations were found to occur at different local times possibly reflecting the slight differences in the start and the end of a working day (Table OA- 3) and differences in life style between the different EU countries. There is some inter-annual variation in peak times for individual cities as illustrated for the 3 years presented in Figure 2 to 4, and Table 4. For Athens an extended morning peak into late afternoon and an evening peak approximately 9μgm-3 lower compared to the morning one was observed in 1993 (Figure 2). The evening peak in 2001 (Figure 3) appears to be slightly higher than the morning peak illustrating the observed inter-annual variation. Quite different patterns are observed in Athens between the UB and roadside site with respect to peak times and magnitude, with the morning SO2 peak being consistently higher than the evening peak for the UB site. In a number of cities no distinct evening SO2 peak was observed, rather a continuous decline following a midday plateau phase, e.g. in London both at the UB and roadside sites . Another important example is the diurnal pattern in Barcelona in the more recent years characterised by a midday relative maximum, coinciding with the maximum of the sea breeze intensity facilitating the transport of SO2 originating from shipping emissions in the harbour. Thus, in 2009 the peaks of SO2 from traffic rush hours are not apparent, but only the midday relative maximum.

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In general the observed diurnal patterns were quite consistent over time apart from the decreasing SO 2 levels. We observed a change in peak shape and intensity/magnitude with time in some of the cities. 3.4 Seasonal variation in SO2 concentrations

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As expected, higher levels were observed in winter than in summer in all cities throughout the study period (Figure OA- 6-8; Fig. OA-15-17). This is most likely due to increased fuel use for space heating in winter, together with meteorological conditions playing a major role, such as periods of temperature inversion in the cold season trapping pollutants in the atmospheric boundary layer and hence leading to high pollutant concentrations. 3.5 Weekend vs. weekday variation in SO2 concentrations

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A comparison of weekend hourly averages (Saturday and Sunday) vs. weekday (Monday to Friday) for each city illustrated for the years 1993, 2001 and 2009, (Figure 5 to 7, and Figure OA- 22 to 24). Lower SO2 levels were observed at the weekends compared to the weekdays for all cities. An interesting observation was that Athens had slightly higher SO2 levels during night-time and/or early morning hours at weekend compared to weekdays. A Kruskal-Wallis test was conducted (Table 5) to determine the significance of the difference in levels on weekends compared to weekdays, this was statistically significant for roadside and UB stations in each city. 4. Discussion The use of hourly pollution profiles is well established; Ebelt et al. (2001) studied SO2 and NO profiles following the German reunification, while Lee et al. (2005) and Cai and Xie (2011) assessed the effect of traffic restrictions on air quality, also comparing weekend vs. weekday variations during the 24 th Asian Games in Busan, Korea, and the 2008 Beijing Olympics, China, respectively. Hourly profiles of pollutants have been used in a variety of studies quantifying emission sources and differences in spatial and temporal composition of urban 5

ACCEPTED MANUSCRIPT air pollution (Moussiopoulos et al., 1997; Viana et al., 2005; Querol et al., 2007; Polymeneas and Pilinis, 2008; Pey et al., 2010). In this study we observed a general decreasing trend in hourly SO2 levels with time at both roadside and UB monitoring sites in all of the 6 EU cities. These trends are consistent with other published trends in SO2 levels (Hecq et al., 1997; WHO, 2006; Anttila and Tuovinen, 2010; EEA, 2010; Aphekom Summary Report, 2011; U.S._EPA, 2012) and with Antilla and Tuovinen (2010) who reported a convergence of roadside and UB levels.

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Some of the observed differences between the cities may be due to the various EU legislations being implemented on different dates in the respective cities, such as the EU Integrated Pollution Prevention and Control Directive (EU, 1996), the Gothenburg „multi-pollutant‟ protocol in 1999 to the LRTAP Convention (UNECE, 1999), the EU National Emission Ceiling Directive (EU, 2001b) and the EU Council Directive 2001/80/EC on the limitation of emissions from large combustion plants (EU, 2001a), may also have contributed to the differences between the cities. Figures 2 to 4 show that the pollution loads within any individual city are not uniform throughout the day; however with only two stations per city being presented, it is not possible to undertake an analysis of the within city distribution.

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In all cities we observed a morning SO2 peak; we believe this reflects traffic related pollution due to the commuting “rush hour”; and an evening peak which reflects possibly a combination of traffic and domestic space heating. This common observation in all the cities, suggests that traffic- and heating-related combustion sources are driving the diurnal patterns. These bi-modal patterns, most pronouncedly seen in Athens, with a distinct morning and evening peak, are similar to those reported by Zhao et al. (2009) for PM2.5 in Beijing, and for NOx by Makra et al. (2010) in Szeged, Hungary, and Freiburg, Germany. Jo and Park (2005) reported that peak SO2 levels, in Daegu, South Korea coincided with the morning and evening rush hours.

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The lower afternoon SO2 levels observed within this study may be partly explained by the dilution of ambient SO2 concentrations due to the midday growth of the mixing layer in conjunction with a decreased traffic density compared to rush hour times, and/or the cleansing effect of the sea breeze in coastal cities (Reche et al., 2011). We believe that differences in dynamics of the urban atmospheric boundary/mixing layers in the 6 different cities due to different climatic and geographical conditions, e.g. basin between mountains vs. flat terrain, coastal vs. continental, northern vs. southern Europe, contribute to some of the differences in diurnal and seasonal variations in SO2 concentrations between the cities (Baklanov et al., 2006). Additionally, seasonal differences in mixing layer heights (Baklanov et al., 2006; Pérez et al., 2008), and periods of temperature inversion can all affect local SO2 concentrations. Clearly there are likely to be other combustion sources apart from traffic contributing to the observed SO2 levels such as industries or port activity, e.g. shipping emissions in coastal cities such Barcelona. A limitation of this study is that we were not able to get a detailed inventory of the different emission sources of SO 2 in each city and thus could not quantify the influence of each source type on the observed diurnal variations. When we consider the high roadside SO2 concentrations observed in both Paris and Athens in the initial years, we believe these maybe due to the monitoring site characteristic in Paris as it was located at an urban motorway rather than at a main street as in the other cities. In Athens, where levels still remained higher than the other cities in the more recent years (Figure 3 - 4), some of this can be explained by the different mix of emission sources, with industry, energy, central heating and shipping contribute about 80% of the annual SO2 emissions in Athens (Kanakidou et al., 2011). Vehicle statistics for Athens (ANFAC-Report, 2010) indicate that Greece had the lowest number of passenger cars/1000 inhabitants and the lowest percentage of diesel vehicles compared to the other countries. A particular feature of Athens is that private diesel cars were banned from the city (Vouitsis et al., 2007) during the study period, thus the only diesel vehicles are taxis, busses and trucks. Despite the relatively low and almost constant percentage of diesel cars in Athens, the pronounced morning peak at the roadside and UB site being stretched out into late afternoon throughout the study period might be due to a well known problem in Athens - the fuel adulteration of diesel fuels for cars and to a lesser extent of heating fuels by shipping fuel (iefimerida, 2012; e-Nautilia.gr, 2013), which has high sulphur content, hence the higher levels in Athens with one of the main drivers being the taxi fleet continuously circulating during the study period. Additionally those peaks most likely reflect to a great extent heavy goods vehicles and buses, which in turn may reflect local business hours as many businesses and banks close at 2/2.30pm on working weekdays or have a midday break until late afternoon. An increase in the number of vehicles with time in all countries has been reported, with the percentage share of diesel vehicles approximately doubling in Belgium and France from 1993 to 2009, with an even larger increase in the UK and Austria (ANFAC-Report, 2010).

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The findings of this study show the biggest decline/percentage change in diurnal SO 2 levels occurs in the morning peak suggesting that particularly traffic related SO 2 emissions decreased. While a number of cities showed marked decreases in night-time/early morning hour SO2 levels that might be partially attributable to decrease in space heating related emissions. Changes to the main sources of space heating occurring at different time points within the different cities might contribute to the observed inter-city variability and as well interannual variability within a given city with time, e.g. a shift towards natural gas, which generates “almost no” SO2 emissions compared to e.g. coal combustion (Jaramillo et al., 2007). The total gross inland consumption of natural gas within the EU-27 countries increased consistently since the mid-1990‟s until 2005, after which a slight decrease has been observed (EUROSTAT, 2012). However, natural gas consumption varies markedly between the individual EU countries with Greece being the lowest of the 6 EU countries followed by Austria and with the UK and France having the highest consumption from 2008-2012 (EUROSTAT, 2012). In the UK the use of natural gas accounted for 45% of the gross electricity generation and 86% of the heat generation in 2009 respectively (European Commission, 2011b). In contrast to that, in Greece natural gas accounted for only 18% of the gross electricity generation, whereby heat generation was solely based on the use of solid fuels (99%) and petroleum products (1%) (European Commission, 2011a); with respect to domestic space heating in Athens oil is the main fuel used (Papathanasopoulou, 2010). This shift in fuel usage to natural gas for (i) 96% of the domestic heating systems since the early 1990‟s and (ii) for power generation to comply with regional air quality plans requesting the exclusive use of natural gas in power plants surrounding the city, besides the changes in vehicle fuels, is for example reflected by the changes in the diurnal SO2 pattern with time in Barcelona showing much reduced general SO2 concentrations and peak values in 2001 (Figure 3). In addition, recent findings by Schembari et al. (2012) examining the influence of shipping emissions on SO2 levels in Mediterranean harbours including Barcelona showed the impact of the implementation of the 2005 amendment of Directive 1999/32/EC limiting sulphur content in fuels for ships at berth or at anchor in ports. They reported an average decrease in daily mean SO2 concentrations by 66% in EU harbours post-implementation in January 2010 compared to the pre-legislative period. In London on the other hand, elevated SO2 levels at the roadside and UB station during midday following a morning peak observed throughout the majority of years assessed might reflect the metropolitan life-style of the city involving constant traffic use. This constant traffic might have been picked up by both of the very central measurement stations.

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Interestingly the so called weekend effect of lower pollutant levels during daytime in all years when the weekend (Saturday and/or Sunday) is compared to the other weekdays may reflect changes in activity, such as the missing traffic volume due to commuters driving to and from work during the week and lower industrial emissions. This observation has been corroborated by various studies worldwide assessing weekday specific diurnal variation of pollutants including SO2, PM, CO and NOx suggesting a significant effect of traffic on pollutant concentrations, whereby an inverse relationship was found for Ozone (Morawska et al., 2002; Jo and Park, 2005; Lee et al., 2005; Riga-Karandinos and Saitanis, 2005; Lonati et al., 2006; Gupta et al., 2008; Cai and Xie, 2011; Bigi et al., 2012). A study by Funk et al. (2001) assessing day-of-week patterns in total traffic volumes showed that compared to weekdays total daily travel activity on weekend days decreased by 13-20% with differences in travel activity patterns dependent on the vehicles type in California‟s South Coast Air Basin, U.S.. The observed slightly higher SO2 levels during night-time and/or early morning hours during the weekend compared to working weekdays most pronounced in Athens may reflect weekend night life activities and be related to higher traffic emissions due to a higher usage of transport during those hours.

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5. Conclusion

This study has shown that an analysis of hourly pollution patterns can be useful in understanding city-specific activity patterns, such as rush hour traffic, and evening space heating. The study has shown that the SO2 concentrations at the selected location within one individual city are not uniform throughout the day; additionally we observed differences between roadside and UB monitoring sites in a given city. Overall the patterns in concentrations in the assessed cities are consistent with that expected from traffic and heating sources, hence road traffic and heating, and currently shipping, appeared to be important sources of SO2 emissions. The patterns observed are informative and suggest that research to investigate reasons for peaks and differences between hours and between cities may contribute to the correct abatement strategies. This study has also confirmed the dramatic decrease in SO2 levels across all of the cities, and clearly suggests that the reduction in the sulphur content in fuels, as part of EU legislation, coupled with the shift towards the use of cleaner fuels and the improvement of the efficiency of engines, has been a significant contributor to these 7

ACCEPTED MANUSCRIPT reduced SO2 levels. This study could aid understanding of possible emission sources and may be of use to planners for a given city.

Figure 2: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 1993 Figure 3: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 2001 Figure 4: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 2009

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Figure 1: Annual mean roadside SO2 concentrations at the 6 individual stations in each city assessed from 1993 to 2009

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Figure 5: 24-hr plot of hourly SO2 for working weekdays and the weekend for a roadside station in Athens, Greece, in 1993, 2001 and 2009 Figure 6: 24-hr plot of hourly SO2 for working weekdays and the weekend for a roadside station in Barcelona, Spain, in 1993, 2001 and 2009

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Figure 7: 24-hr plot of hourly SO2 for working weekdays and the weekend for a UB station in London, UK, 1993, 2001 and 2009

Table 1: Summary of population size and mean daily temperature, relative humidity and SO 2 concentration for the 6 cities Table 2: Correlation coefficients for roadside and UB stations in each city

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Table 3: Summary of the time trend analysis using the Theil-Sen method

Table 4: Summary of the key observations for each individual city‟s diurnal SO 2 profile of 6 EU cities for 1993, 2001 and 2009

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Table 5: Kruskal-Wallis test results for difference between weekdays (MON-FRI) vs. weekend (SAT&SUN) SO2 levels

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Anttila, P., Tuovinen, J.-P., 2010. Trends of primary and secondary pollutant concentrations in Finland in 1994“2007. Atmospheric Environment 44, 30-41.

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Aphekom Summary Report, 2011. Aphekom - Summary report of the Aphekom project 2008-2011.

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Baklanov, A., Joffre, S., Piringer, M., Deserti, M., Middleton, D., Tombrou, M., Karppinen, A., Emeis, S., Prior, V., Rotach, M., Bonafè, G., Baumann-Stanzer, K., Kuchin, A., 2006. Scientific Report 06-06: Towards estimating the mixing height in urban Areas. Recent experimental and modelling results from the COST-715 Action and FUMAPEX project. . Danish Meteorological Institute, Copenhagen, Denmark.

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Bell, M.L., Davis, D.L., 2001. Reassessment of the lethal London fog of 1952: novel indicators of acute and chronic consequences of acute exposure to air pollution. Environ Health Perspect 109 Suppl 3, 389-394.

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Bigi, A., Ghermandi, G., Harrison, R.M., 2012. Analysis of the air pollution climate at a background site in the Po valley. J Environ Monit 14, 552-563.

31 32

Cai, H., Xie, S., 2011. Traffic-related air pollution modeling during the 2008 Beijing Olympic Games: The effects of an odd-even day traffic restriction scheme. Science of The Total Environment 409, 1935-1948.

33 34

Carslaw, D.C., 2013. The openair manual - open-source tools for analysing air pollution data. Manual for version 0.8-0. King‟s College London, U.K.

35 36

Carslaw, D.C., Ropkins, K., 2012. openair - ” An R package for air quality data analysis". Environmental Modelling & Software 27-28, 52-61.

37 38

COMEAP, 2009. Long-Term Exposure to Air Pollution: Effect on Mortality. Committee on the Medical Effects of Air Pollutants, Chilton, Didcot, Oxfordshire, U.K.

39 40

Dodson, R.E., Andres Houseman, E., Morin, B., Levy, J.I., 2009. An analysis of continuous black carbon concentrations in proximity to an airport and major roadways. Atmospheric Environment 43, 3764-3773.

41 42

e-Nautilia.gr, 2013. Σύσκεψη για την πάταξη τος λαθπεμποπίος ναςτιλιακών καςσίμων (Author's translation: Meeting to fight contraband of marine fuel oil). e-Nautilia.gr, Greece.

Funding: The Aphekom project was funded jointly by the European Commission‟s Programme on Community Action in the Field of Public Health (2003-2008) under Grant Agreement No. 2007105 (54.39 %), and by the many institutions that have dedicated resources to the fulfilment of this city-based project (45.61 %). Conflict of Interest The authors declare that they have no conflict of interest.

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Acknowledgements

The huge amount of work behind the Aphekom project is the fruit of the generous and constructive input from all the members of the Aphekom network and their partner organisations that provided data.

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ANFAC-Report, 2010. European Motor Vehicle Parc 2008.

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Table 1 track_changes Click here to download Table: Table 1_REVISION_track_changes.docx

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Table 1: Summary of population size and mean daily temperature, relative humidity and SO 2 concentration for the 6 assessed cities.

Mean annual SO2 (±SD)b [µg/m3]

3,400,0004,088,447

Barcelona

4,900,0005,345,603

Brussels

1,048,4913,479,951

London

7,000,0008,173,900

Paris

2,257,98111,728,240

Vienna

1,677,4682,305,023

1993 23.4 (± 30.4) n.a. 11.3 (± 8.6) 31.2 (± 35.4) 18.6 (± 16.5) 16.8 (± 22.0)

18.5

62. 8

15.0

68.7

11.7

75.2

11.3

75.7

12.4

73.6

11.2

70.7

Mean daily level (Source: Adapted from Aphekom Final Report, 2011, material not published); b mean trafficroadside/city centre SO2 from 1990-2009 dependent on data availabilityin 1993 and 2009; c population numbers for metropolitan areasregion in 2009, Sources: Eurostat, European Comission (Last update 08.05.2013). http://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do; UK Office for National Statistics, Table P04 2011 Census:

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http://www.ons.gov.uk/ons/search/index.html?newquery=Table+P04

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a

UB site 2009 n.a. [2008: 8.3 (± 2.7)] 3.1 (± 5.8) 4.9 (± 3.5) 2.8 (± 4.2) 3.4 (± 5.9) 3.1 (± 3.2)

Humiditya [%]

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Athens

Roadside Ssite 1993 2009 14.4 32.261.5 (± 32.958.8) (± 9.7) 3 9.824.6 (± 16.418.9) (± 3.2) 4.3 12.126.7 (± 12.820.5) (± 3.3) 2.7 12.437.3 (± 19.731.9) (± 2.4) 1.9 11.8n.a. (± 13.6) (± 3.7) 2.9 7.616.2 (± 10.920.8) (± 3.0)

Temperaturea [°C]

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Populationc

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City

Table 1 changes_accepted ACCEPTED MANUSCRIPT Click here to download Table: Table 1_REVISION_changes_accepted.docx

Table 1: Summary of population size and mean daily temperature, relative humidity and SO 2 concentration for the 6 assessed cities.

4,088,447

Barcelona

5,345,603

Brussels

3,479,951

London

8,173,900

Paris

11,728,240

Vienna

2,305,023

18.5

62. 8

15.0

68.7

11.7

75.2

11.3

75.7

12.4

73.6

11.2

70.7

Mean daily level (Source: Adapted from Aphekom Final Report, 2011, material not published); b mean roadside/city centre SO2 in 1993 and 2009; c population numbers for metropolitan region in 2009, Sources: Eurostat, European Comission (Last update 08.05.2013). http://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do; UK Office for National Statistics, Table P04 2011 Census: http://www.ons.gov.uk/ons/search/index.html?newquery=Table+P04

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a

Humiditya [%]

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Athens

Temperaturea [°C]

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Populationc

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City

Mean annual SO2 (±SD)b [µg/m3] Roadside site UB site 1993 2009 1993 2009 14.4 23.4 n.a. 61.5(±58.8) (± 9.7) (± 30.4) [2008: 8.3 (± 2.7)] 3 3.1 n.a. 24.6(±18.9) (± 3.2) (± 5.8) 4.3 11.3 4.9 26.7(±20.5) (± 3.3) (± 8.6) (± 3.5) 2.7 31.2 2.8 37.3(±31.9) (± 2.4) (± 35.4) (± 4.2) 1.9 18.6 3.4 n.a. (± 3.7) (± 16.5) (± 5.9) 2.9 16.8 3.1 16.2(±20.8) (± 3.0) (± 22.0) (± 3.2)

Table 2 (new) Click here to download Table: Table 2_REVISION_new.docx

ACCEPTED MANUSCRIPT Table 2: Correlation coefficients for the roadside and UB station in each individual city

Correlation coefficient for traffic and UB stations in each city City

traffic

0.6

Barcelona

traffic

0.3

Brussels

traffic

0.75

London

traffic

0.67

Paris

traffic

0.55

Vienna

traffic

SC

Athens

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UB

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0.82

Table 3 track_changes Click here to download Table: Table 3_REVISION_track_changes.docx

ACCEPTED MANUSCRIPT

Table 23: Summary of the time trend analysis using the Theil-Sen method (dependent on data availability)

/year]

Total absolute drop in annual mean SO2 levels btw 19932009 [μgm-3]; Total percentage drop [%]

-2.11

-0.94

-1.1612

(-2.38, -

(-1.08, -

(-1.3735, -

1.8485)

0.80)

0.9392)

4747

15

77%

64%

Brussels Roadside UB site site

-0.96

-0.53

-0.61

(-1.1552, -

(-2.55, -

(-1.1413,

(-0.62, -

(-0.7, -

1.26)

2.1)

-0.8192)

0.46)

0.53)

35

2726

57

1514

13

1414

57%

93%

91%

97%

81%

82%

81%

-1.4

−0.5

−1.08

-1.73

−2.39

-1.37

−1.05

-1.08

(−0.55, 0.36)

(-1.84, -1.11)

(−0.88, -0.27)

(−1.74, −0.77)

(-2.11, -1.47)

(−3.33,

(-1.76, -

(−1.51,

(-1.74, -

−1.89)

1.02)

−0.68)

0.77)

-7.12%

-5.45%

-3.33%

-6.64%

-6.20%

-7.30%

-4.87%

-5.43%

-6.04%

-0.37

-1.14

−2.25

-0.71

−0.34

-0.37

(-0.51, -0.23)

(-1.35, -0.92)

(−2.67,

(-0.84, -

(−0.4,

(-0.51, -

−2.02)

0.6)

−0.26)

0.23)

-6.80%

-6.67%

-8.16%

-5.77%

-4.96%

-6.44%

-0.45

(-0.51, -0.18)

(-1.27, -1.05)

(-0.51, -0.38)

2222

1.5

2222

6

88%

33%

84%

-1.61

−0.31

Average percentage change/year [%]

-1.78 (-2.23, -1.18)

-5.12%

−0.57)

(-2.36, -0.95)

-2.74%

-7.94%

−0.96

-0.78

(−1.19,

(-1.15, -0.31)

−0.72)

-4.78%

-7.78% a

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-4.12%

(−1.48,

EP

Average annual decline change in SO2 (95% CI) in summer over with time† [μgm-3/year]

(-3.65, -1.98)

−0.97

Vienna Roadsi UB de site site

-2.27

-1.15

−0.57

-0.88

(−1.37, 0.28)

(-1.16, -0.72)

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[μgm-3/year] Average percentage change/year [%]

-2.81

Paris Roadsid UB e site site

-1.3938

-0.34

Seasonal trends Average annual decline change in SO2 (95% CI) in winter over with time†

London Roadside UB site site

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3

Barcelona Roadside UB site site

-10.68%

-1.54

-6.66%

(-1.84, -1.3)

SC

Average annual decline change in SO2 over with time (95% CI)a [μgm-

Athens Roadside UB site site

M AN U

Trend in SO2 level

−0.36 (−0.44, −0.26)

-4.45%

over the entire study period 1993-2009, dependent on data availability (Figure OA- 12 & 3)

Table 3 changes_accepted ACCEPTED MANUSCRIPT Click here to download Table: Table 3_REVISION_changes_accepted.docx

Table 3: Summary of the time trend analysis using the Theil-Sen method (dependent on data availability)

(-2.38, -1.85)

[μgm-3/year]

Total absolute drop in annual mean SO2 levels btw 19932009 [μgm-3]; Total percentage drop [%]

-0.94 (-1.08, 0.80)

Brussels Roadside UB site site

-1.12

-0.34

-1.15

-0.45

(-1.35, -0.92)

(-0.51, -0.18)

(-1.27, -1.05)

(-0.51, -0.38)

22

6

47

15

22

77%

64%

88%

1.5 33%

Seasonal trends

[μgm-3/year] Average percentage change/year [%]

-4.12%

Average annual change in SO2 (95% CI) in summer with time†

-1.78

[μgm-3/year] Average percentage change/year [%]

(-2.23, -1.18)

-5.12%

(−1.48, −0.57)

-2.74% −0.96 (−1.19,

-4.78%

(-1.84, -1.3)

(-1.52, -1.26)

(-0.62, -

(-0.7, -

0.92)

0.46)

0.53)

82%

81%

−2.39

-1.37

−1.05

-1.08

(−3.33,

(-1.76, -

(−1.51,

(-1.74, -

−1.89)

1.02)

−0.68)

0.77)

-7.30%

-4.87%

-5.43%

-6.04%

(-2.36, -0.95)

(−0.55, 0.36)

(-1.84, -1.11)

(−0.88, -0.27)

(−1.74, −0.77)

(-2.11, -1.47)

-7.94%

-7.12%

-5.45%

-3.33%

-6.64%

-6.20%

-0.78

−0.57

-0.88

-0.37

-1.14

-4.45%

(-1.13, -

2.1)

81%

-1.73

-6.66%

(-2.55, -

97%

−1.08

-10.68%

-0.61

14

−0.5

−0.26)

-0.53

13

-1.4

(-1.16, -0.72)

-0.96

15

91%

(−1.37, 0.28)

-2.27

57

93%

−0.36

Vienna Roadsi UB de site site

27

57%

(−0.44,

Paris Roadsid UB e site site

35

−0.31

-7.78% a

-1.38

-1.61

(-1.15, -0.31)

−0.72)

-1.54

84%

TE D

(-3.65, -1.98)

−0.97

EP

-2.81

AC C

Average annual change in SO2 (95% CI) in winter with time†

London Roadside UB site site

RI PT

-2.1

Barcelona Roadside UB site site

SC

Average annual change in SO2 with time (95% CI)a

Athens Roadside UB site site

M AN U

Trend in SO2 level

(-0.51, -0.23)

(-1.35, -0.92)

-6.80%

-6.67%

over the entire study period 1993-2009, dependent on data availability (Figure OA- 2 & 3)

−2.25

-0.71

−0.34

-0.37

(−2.67,

(-0.84, -

(−0.4,

(-0.51, -

−2.02)

0.6)

−0.26)

0.23)

-8.16%

-5.77%

-4.96%

-6.44%

Table 4 track_changes Click here to download Table: Table 4_REVISION_track_changes.docx

ACCEPTED MANUSCRIPT

Roadside

n.a.

46 (10am)

31 (9am)

n.a.

17

13

n.a.

24

2

2

35 (8am)

5 (1011am)

4 (noon)

20

3

4

n.a.

n.a.

1.7

n.a.

n.a.

n.a.

n.a.

3.8

2324

9

4

37 (7am)

13 (8am)

5.2 (noon) 6 (9am)

24

8

10.5

7.2

4.5

13 (7-8am)

10.4 (7am)

5.9 (7-8am)

10.5

6.8

21

3.3

1.2

50 (9am)

9.5 (9am)

4.3 (8am)

39

8.3

22

8

2

12

0.9

13 (9am) 22 (8-9am)

4 (8am) 2.9 (11am)

31

n.a.

38 (89am) n.a.

14

9

3

30 (7-8am)

16 (8am)

11

5

2.3

24 (1112am)

14

5

3

21.5 (10am)

21 (8-9pm)

n.a.

24 (11pm)

3 (6pm)

4 (6pm)

n.a.

n.a.

4

25 (6pm)

10 (811pm)

3.3 (6pm) 4 (9pm)

4.2

11.4 (9pm)

9 (8-9pm)

3

41 (6-7pm)

8.5 (6pm)

11

3

n.a.

20

2.1

32 (6pm) n.a.

11 (6pm) 22 (7pm)

3 (7pm) 1.8 (68pm)

5 (8-9am)

16

11

3

17 (6-7pm)

12 (8pm)

8 (10am)

4 (10am)

16

6.6

2.8

15 (5-8pm)

6.4 (7-8pm)

3 (89pm) 2.7 (79pm)

7 (10am)

4 (noon)

15

5

3

16 (811pm)

6 (10pm)

M AN U

TE D

EP

Morning = 12pm1am-12noon; Afternoon = 1pm-5pm; Evening = 6pm-12pm

AC C

UB

Roadside

UB

Roadside UB Roadside

UB

Roadside UB Roadside

Barcelona Brussels London Paris Vienna

30 (8-9pm)

RI PT

10

SC

12 UB

Athens

Table 34: Summary of the key observations for each individual city’s diurnal SO2 profile of 5 6 EU cities for 1993, 2001 and 2009 City & Morning SO2 maximum SO2 Afternoon Evening SO2 maximum SO2 Morning minimum Monito value [µgm-3] and time of minimum SO2 value [µgm-3] and time of SO2 levels [µgm-3] -3 ring occurrence levels [µgm ] occurrence 2001 2009 1993 2001 2009 1993 2001 2009 station 1993 2001 2009 1993 37 16.5 12 89 31 17 48 17 13 80 34 17 (8am) (9am) (8am) (8-9pm) (9pm) (8pm)

5 (89pm) 3.1 (6pm)

3 (6pm)

Table 4 changes_accepted Click here to download Table: Table 4_REVISION_changes_accpeted.docx

ACCEPTED MANUSCRIPT

n.a.

46 (10am)

31 (9am)

n.a.

17

13

n.a.

24

2

2

35 (8am)

5 (1011am)

4 (noon)

20

3

4

n.a.

n.a.

1.7

n.a.

n.a.

5.2 (noon)

n.a.

n.a.

3.8

2324

9

4

37 (7am)

13 (8am)

6 (9am)

24

8

4

10.5

7.2

4.5

13 (7-8am)

10.4 (7am)

21

3.3

1.2

50 (9am)

9.5 (9am)

22

8

2

n.a.

12

0.9

38 (89am) n.a.

13 (9am) 22 (8-9am)

14

9

3

30 (7-8am)

11

5

2.3

14

5

3

21 (8-9pm)

n.a.

24 (11pm)

3 (6pm)

4 (6pm)

n.a.

n.a.

3.3 (6pm)

25 (6pm)

10 (811pm)

4 (9pm) 5 (89pm) 3.1 (6pm)

M AN U 10.5

6.8

4.2

11.4 (9pm)

9 (8-9pm)

4.3 (8am)

39

8.3

3

41 (6-7pm)

8.5 (6pm)

4 (8am) 2.9 (11am)

31

11

3

n.a.

20

2.1

32 (6pm) n.a.

11 (6pm) 22 (7pm)

3 (7pm) 1.8 (68pm)

16 (8am)

5 (8-9am)

16

11

3

17 (6-7pm)

12 (8pm)

24 (1112am)

8 (10am)

4 (10am)

16

6.6

2.8

15 (5-8pm)

6.4 (7-8pm)

3 (89pm) 2.7 (79pm)

21.5 (10am)

7 (10am)

4 (noon)

15

5

3

16 (811pm)

6 (10pm)

TE D

5.9 (7-8am)

EP

AC C

Roadside UB UB

Roadside

UB

Roadside UB Roadside

UB

Roadside

Barcelona Brussels London Paris Vienna

30 (8-9pm)

SC

10

RI PT

Roadside

12 UB

Athens

Table 4: Summary of the key observations for each individual city’s diurnal SO2 profile of 6 EU cities for 1993, 2001 and 2009 City Morning maximum SO2 value Afternoon Evening maximum SO2 Morning minimum & [µgm-3] and time of minimum SO2 value [µgm-3] and time of SO2 levels [µgm-3] -3 Monito occurrence levels [µgm ] occurrence ring 1993 2001 2009 1993 2001 2009 1993 2001 2009 1993 2001 2009 station 37 16.5 12 89 31 17 48 17 13 80 34 17 (8am) (9am) (8am) (8-9pm) (9pm) (8pm)

Morning = 1am-12noon; Afternoon = 1pm-5pm; Evening = 6pm-12pm

3 (6pm)

Table 5 (new) Click here to download Table: Table 5_REVISION_new.docx

ACCEPTED MANUSCRIPT ‡

Table 5: Kruskal-Wallis test results for difference between weekdays (MON-FRI) vs. weekend (SAT & SUN) SO2 levels

Barcelona Brussels London Paris Vienna

p-value

Roadside

19.62

9.43E-06

UB

15.37

8.84E-05

Roadside

25.52

4.38E-07

UB

8.17

4.27E-03

Roadside

25.04

5.60E-07

UB

17.78

2.48E-05

Roadside

21.80

3.03E-06

UB

26.83

2.22E-07

Roadside

32.77

1.04E-08

UB

45.73

1.36E-11

Roadside

21.34

3.84E-06

UB

22.46

2.14E-06

‡

M AN U

Athens

adjusted H-Value

SC

Monitoring Station

City

RI PT

Kruskal-Wallis test results for difference between weekdays vs. weekend SO2 levels

AC C

EP

TE D

Results of the Kruskal-Wallis test are equivalent to a Mann-Whitney U-test if you have just two groups to compare, like in this case (weekend vs. weekday SO2 levels).

Figure 1 track_changes

AC C

EP

TE D

M AN U

SC

RI PT

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M AN U

SC

RI PT

Figure 1: Annual mean SO2 concentrations at the 6 individual stations in each city assessed from 1993 to 2009

AC C

EP

TE D

Figure 1: Annual mean roadside SO2 concentrations at the 6 individual traffic stations in each city assessed from 1993 to 2009

Figure 1 changes_accepted

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

Figure 1: Annual mean roadside SO2 concentrations at the 6 individual traffic stations in each city assessed from 1993 to 2009

Figure 2 track_changes

M AN U

SC

RI PT

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AC C

EP

TE D

Figure 2: Diurnal city centre/traffic SO2 profiles for 6 EU cities (Athens; Barcelona; Brussels; London; Paris; Vienna) for 1993

AC C

EP

TE D

a) Hourly roadside SO2 profile, 1993

M AN U

SC

RI PT

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b) Hourly UB SO2 profile, 1993

Figure 2: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 1993

Figure 2 changes_accepted

AC C

EP

TE D

a) Hourly roadside SO2 profile, 1993

M AN U

SC

RI PT

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b) Hourly UB SO2 profile, 1993

Figure 2: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 1993

Figure 3 track_changes

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

Figure 3: Diurnal city centre/traffic SO2 profiles for 6 EU cities for 2001

AC C

EP

TE D

a) Hourly roadside SO2 profile, 2001

M AN U

SC

RI PT

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b) Hourly UB SO2 profile, 2001 Figure 3: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 2001

Figure 3 changes_accepted

AC C

EP

TE D

a) Hourly roadside SO2 profile, 2001

M AN U

SC

RI PT

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b) Hourly UB SO2 profile, 2001 Figure 3: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 2001

Figure 4 track_changes

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

Figure 4: Diurnal city centre/traffic SO2 profiles for 6 EU cities for 2009

Formatted: Normal, None

AC C

EP

TE D

a) Hourly roadside SO2 profile, 2009

M AN U

SC

RI PT

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b) Hourly UB SO2 profile, 2009 [*note: Athens UB data excluded due to data availability]

Figure 4: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 2009

Figure 4 changes_accepted

AC C

EP

TE D

a) Hourly roadside SO2 profile, 2009

M AN U

SC

RI PT

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b) Hourly UB SO2 profile, 2009 [*note: Athens UB data excluded due to data availability]

Figure 4: Diurnal roadside (a) and UB (b) SO2 profiles for 6 EU cities for 2009

Figure 5 track_changes

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

Figure 5: 24-hr plot of hourly SO2 for working weekdays and the weekend for a traffic roadside station in Athens, Greece, in 1993, 2001 and 2009

Figure 5 changes_accepted

M AN U

SC

RI PT

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AC C

EP

TE D

Figure 5: 24-hr plot of hourly SO2 for weekdays and the weekend for a roadside station in Athens, Greece, in 1993, 2001 and 2009

Figure 6 track_changes

M AN U

SC

RI PT

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AC C

EP

TE D

Figure 6: 24-hr plot of hourly SO2 for working weekdays and the weekend for a traffic roadside station in Barcelona, Spain, in 1993, 2001 and 2009

Figure 6 changes_accepted

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

Figure 6: 24-hr plot of hourly SO2 for weekdays and the weekend for a roadside station in Barcelona, Spain, in 1993, 2001 and 2009

Figure 7 track_changes

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

Figure 7: 24-hr plot of hourly SO2 for working weekdays and the weekend for a central-urbanUB station in London, UK, 1993, 2001 and 2009

Figure 7 changes_accepted

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

TE D

Figure 7: 24-hr plot of hourly SO2 for weekdays and the weekend for a UB station in London, UK, 1993, 2001 and 2009

*Highlights (for review)

ACCEPTED MANUSCRIPT Highlights:

Knowledge of hourly pollution patterns useful in understanding city-specific emission issues



In 6 EU cities: Pollution loads not uniform throughout day

AC C

EP

TE D

M AN U

SC

RI PT

