Interim Annual Assessment Report for 2015

Home , 2016 in Europe

European air quality in 2015

Issued by: INERIS Date: 28/07/2016 REF.: CAMS71_2016SC1_D71.1.1.2_201609

Copernicus Atmosphere Monitoring Service

This document has been produced in the context of the Copernicus Atmosphere Monitoring Service (CAMS). The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of CAMS on behalf of the European Union (Delegation Agreement signed on 11/11/2014). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. For the avoidance of all doubts, the European Commission and the European Centre for Medium-Range Weather Forecasts has no liability in respect of this document, which is merely representing the authors view.

CAMS D71.1.1. | Interim Annual Assessment Report for 2015

Copernicus Atmosphere Monitoring Service

Interim Annual Assessment Report for 2015

European air quality in 2015

NILU (L. Tarrasón, P.Hamer, C. Guerreiro) INERIS (F. Meleux, L. Rouïl)

Date: 29/09/2016

REF.: CAMS71_2016SC1_D71.1.1.2_201609

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Contents: Contents ...... 1 Contents: ...... 3 Executive Summary ...... 2 1. Introduction ...... 4 1.1 Timeliness ...... 4 1.2 Origin of episode events ...... 5 1.3 Extended use of CAMS data and information ...... 5 2. Pollution episodes in 2015 ...... 7 2.1 Rationale for episode identification ...... 7 2.2 Identified pollution events in 2015 ...... 7 2.3 Origin of pollution episodes ...... 10 2.3.1 1st – 5th July Ozone Episode ...... 12 th th 2.3.2 12 - 20 February PM10 Episode ...... 14 th th 2.3.3 17 - 20 March PM10 Episode ...... 17 th th 2.3.4 29 October to 7 November PM10 Episode ...... 20 3 Air Quality Indicators in 2015 ...... 25 3.1 Ozone in 2015 ...... 25 3.1.1 Meteorological characterisation ...... 25 3.1.2 Ozone Health Indicators...... 28 3.1.3 Ozone Ecosystem Indicator ...... 30 3.2 Nitrogen Dioxide in 2015 ...... 31 3.2.1 Seasonal variations ...... 31 3.2.2 Nitrogen Dioxide Health Indicators ...... 32

3.3 PM10 in 2015 ...... 33 3.3.1 Meteorological characterisation ...... 33 3.3.2 PM10 Health Indicators ...... 34

3.4 PM2.5 in 2015 ...... 35 3.4.1 Meteorological characterisation and health indicators ...... 35 4 Conclusions ...... 37 5 References ...... 39

CAMS D71.1.1. | Interim Annual Assessment Report for 2015

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Executive Summary (WMO) as a historically warm record year globally. In Europe as a whole, 2015 was the second warmest in the last five This is the Copernicus Atmosphere years. There were floods caused by Monitoring Service (CAMS) Interim heavy rain in February in parts of Annual Assessment report (IAAR) for Albania, the former Yugoslav Republic of 2015. It provides timely reference Macedonia, Greece and Bulgaria and information for environmental record high monthly precipitation records authorities to support them when for different months over Northern reporting and assessing air quality in Europe and Scandinavia. Still, some their countries under European areas remained particularly dry, which legislation. gave rise to a series of forest fires that had consequences for recorded air The report is elaborated on the basis of quality values. non-validated up-to-date observations gathered by the European Environment In terms of air quality, 2015 experienced Agency (EEA) and selected modelled the highest maximum daily 8-hour mean data from the CAMS services. Therefore, ozone values over Central Europe over its timeliness is considerably advanced the last five years and elevated annual with respect to other existing European- levels of PM10 over the last years. A wide air quality assessments. Since the series of large scale pollution events CAMS Interim Annual Assessment is affected European air quality over the based on non-validated data, the report different seasons in 2015. There were does not aim at presenting a ozone episode events during the summer fullyquantitative estimate of the and significant PM10 pollution events in background European air quality winter, spring and autumn. situation in 2015 regarding regulatory objectives, but rather a characterization In 2015, a significant PM10 pollution of that year’s air quality status with event took place from 12th to 20th respect to previous years and an analysis February, affecting most areas in Europe. of the origin of identified episodes. The origin of this winter pollution episode varies from country to country but it is a The IAAR report is based on a number of complex combination of different products and data developed within the anthropogenic and natural sources. CAMS services: the interim CAMS re- Emissions from residential heating, analyses of the regional model ensemble, including wood and coal combustion, information from the CAMS regional dominate the PM10 pollution levels of the green-scenario calculations, as well as winter episode, especially in Southern the global aerosol production of dust and Eastern Europe, followed closely by concentrations. It provides information the contribution of ammonia emissions on the origin of single episodes by from agriculture. In Central Europe, identifying areas where the episodes are however, agriculture emissions dominate susceptible to have a significant natural as origin of this PM10 episode over other dust contribution as well as an indication anthropogenic sources. In the winter of what can be the main anthropogenic episode from 12th to 20th February, a emission sectors responsible of specific Saharan dust intrusion affected also PM10 episodes. pollution levels over Southern and Western Europe. The results from the The year 2015 has been characterised by CAMS post-processed PM20 data can be the World Meteorological Organisation used as indicator of the importance of the

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contribution of Saharan dust in PM10. th th The winter PM10 episode involved also The PM10 episode of 29 October to 7 contributions from forest fires. Although November was the largest autumn these contributions have not yet been episode and it was actually divided in two quantified, ongoing work will provide different episodes. The first one, from such quantification in future analysis. 29th October to 31st October occurred over Central and Northern Europe. The rd th There was another important PM10 second one, from 3 November to 7 episode in March 2015. It took place from November affected mostly Eastern and 17th to 20th March and recorded the Southern Europe. The first part of the highest PM10 daily levels in 2015 over autumn episode was dominated by areas in The Netherlands, Belgium, agriculture emissions in Northern and Luxembourg, France, Germany, and Central Europe and, to a lesser degree, Southern United Kingdom. In these by residential emissions. The influence of areas, the episode included an important Saharan dust intrusions on this part of contribution from a Saharan dust the episode were very limited. The intrusion. It is interesting to note that second part of the episode, in the while the winter PM10 episode was beginning of November 2015, was primarily driven by a combination of centred over Germany, Poland and most residential heating emission and of Eastern Europe. It was dominated by emissions from agriculture, the March agriculture emissions, with significant episode is clearly dominated by contributions from residential and agriculture emissions in the areas of industrial emissions. In this second part, highest PM10 levels. In Eastern Europe, the presence of a Saharan dust intrusion however, the main anthropogenic was identified reaching as far north as contribution is from residential sources, Germany. not agriculture. The natural contribution from Saharan dust plays also a Understanding the main emission significant role in the elevated pollution sources behind identified episodes is a levels in Eastern Europe on 18th-20th requirement in the reporting obligations March. The Saharan dust intrusion of the Members States under the Air showed very high PM20 levels over Quality Directive (EU, 2008). The Southern and Central Europe. Although episode evaluation in this report can be PM20 is only valid as an indicator to the extended to other type of situations and actual Saharan dust contribution to PM10, can be used as an example of how CAMS it is clear that in some areas over Italy, products can support reporting the cause Spain and France, the Saharan dust of specific pollution levels in different contribution was much higher in this countries. episode than in any of the other identified episodes in 2015.

There were no marked summer episodes of PM10 in 2015. Instead, the series of heatwaves affecting Europe in 2015 resulted in different ozone episodes. The largest ozone episode occurred between 1st and 5th July 2015. Traffic and industrial emissions are the main emission sectors contributing to this ozone episode event.

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1. Introduction experts who are in charge of air quality reporting.

The Copernicus Atmosphere Monitoring This Interim Annual Assessment Service (CAMS Report (IAAR) documents the status http://atmosphere.copernicus.eu/) of air quality in Europe for the year delivers global and regional atmospheric 2015. It provides timely reference composition information. As part of the information for policy makers about the CAMS services, some products are climatological characterization of 2015 specifically designed to support policy and explains how this affects background users especially in the area of air quality. air quality and the occurrence of large- The CAMS policy products aim at scale episodes. describing air quality in Europe and its evolution over the years, identifying air The first part of the report provides a pollution episodes that impact on health review of the main episodes that and the environment, as well as the main occurred over the past year (2015), drivers responsible for such pollution when monitoring stations registered events. These drivers may differ exceedance of the limit or target values significantly from region to region and over large European regions, and an depend on the period. Good analysis of the reasons and main drivers understanding of the origin of air behind these episode events. The second pollution is essential for policy users to part of the report describes the define the most appropriate and efficient background situation for the main control strategies, both in the long-term regulatory pollutants (ozone, NO2, PM10 and in the short-term. and PM2.5) in terms of concentrations and main environmental indicators as The information, data and assessments compared to previous years. from the CAMS policy product services aim to support European environmental The main differences of this IAAR with authorities in reporting and assessing air respect to previous Assessment Reports quality under European legislation. from the pre-operational MACC project are: This report is the first CAMS Interim Annual Assessment Report. The CAMS - The timeliness of the report; Interim Annual Assessment Reports - The focus on characterising the (IAAR) are elaborated on the basis of so origin of identified episodes; called “interim re-analyses” of air quality - The extended use of data and that are provided by other CAMS regional information from CAMS. services. Interim re-analyses of air quality are issued from model runs corrected by up-to-date observation data 1.1 Timeliness using state-of-the-art data assimilation techniques. They provide best estimated The timeliness of Interim Annual maps of air pollution patterns. Each Assessment (IAAR) reports has been Member State of the European Union and established to respond to the demands associated countries has specific from policy users. Earlier feedback from obligations in terms of compliance and these users indicated the need to have reporting air quality every year. The the reports produced shortly after the objective of the CAMS IAAR reports is to considered year. Consequently, the provide concrete inputs to the national interim annual assessments reports use

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up-to-date non-validated observational Episode events are identified in this data and the elements highlighted in the report in terms of up-to-date IAAR are to be revised and confirmed in observations from the European the Annual Assessment Reports (AAR). Environment Agency (EEA). Their origin, The AARs are released one year later and however, is established based on: a) are based on validated observation data. modelling results from the CAMS interim re-analyses of the regional model Up-to-date (UTD) data are reported by ensemble, b) results from the CAMS the Member States to the European regional green-scenario calculations, and Environment Agency (EEA) as soon as c) results from the global aerosol possible after their production, according production of dust concentrations. In this to the AQ e-reporting process. These way, the report provides information on data may be verified and validated some areas where episodes are susceptible to time after they are reported first and the have a significant natural dust UTD data are updated in the EEA contribution as well as an indication of database. Interim air quality re-analyses what can be the main anthropogenic for a given day are produced within a emission sectors responsible for specific twenty days’ delay. Therefore, the data episodes. Such information is subject to is not formally validated (in the fewer uncertainties, as it relies on regulatory perspective) but should be documented modelling approaches. reliable enough for assimilation in the CAMS models and interim re-analyses 1.3 Extended use of CAMS production. Such a process should allow data and information the production of the IAAR for the previous year by early June each year1. . The IAAR focusses on the characterization of the origin of 1.2 Origin of episode European-wide pollution episodes. In events this report, the contribution of Saharan dust intrusions to European-wide air Since the CAMS Interim Annual pollution episodes is presented, as well Assessment is based on non-validated as an identification of the relative data, the report does not aim to present importance of agricultural sources versus a fully quantitative estimate of industrial, traffic, and residential sources background European air quality in such events. However, the situation regarding regulatory contribution of forest fires to pollution objectives, but rather a characterization events is only superficially addressed. of the year’s status with respect to For the next editions, it is envisaged to previous years and an analysis of the add to the analysis of the contribution origin of identified episodes. Such from forest fires and sea salt. In this way, information is often more reliable as it is a plausible characterization of natural primarily associated to the comparison of versus anthropogenic contributions to modelling products with acknowledged different pollution events will be given systematic deviation that can be going forward. accounted for. For future editions, it is also envisaged to relate to the new source-receptor

1 Except this year for the 2015 IAAR because the service started only in April.

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calculations under the operational CAMS policy product service development. CAMS will initiate the production of daily forecasts of air quality for the main capitals in Europe showing the influence of local versus transboundary air pollution. It is also planned for a series of on-demand country-to-country source– receptor allocation runs to determine which countries are mainly responsible for specific episode events. Such data will be incorporated in future IAAR analysis as it becomes available.

With this content, we believe that the report will prove useful to policy users in supporting the process of reporting the cause of exceedances in their countries and in the elaboration of their plans and programs related to air quality.

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2. Pollution episodes in industrial sites nor episodes of NO2, 2015 related mostly to traffic sites, are included in the CAMS episode event 2.1 Rationale for episode analysis. identification The CAMS episodes are identified for An air pollution episode is a combination PM10 and ozone on the basis of short- 2 of emissions and meteorology that gives term indicators elevated above the EU rise to elevated levels of air pollution limit or target values, as they are over a large area, lasting for a period of representative of the short-term nature a few days up to 2-3 weeks. of air pollution episodes.

In the context of CAMS, air pollution 2.2 Identified pollution episodes are defined as situations with events in 2015 pollution levels over EU short-term standards affecting a large number of Up-to-date observations from the stations reporting under EIONET, the EEA/EIONET were analysed to identify European Environment Information and pollution episode events in 2015. For Observation Network. The identification ozone, this involved data from 99 rural, of elevated pollution levels draws on 102 suburban, and 144 urban observations and not model results to background stations; while, for PM , it avoid systematic errors, while the origin 10 involved data from 53 rural, 61 of the episodes is analysed in terms of suburban, and 142 urban background modelling to help in their interpretation. stations. The number of stations

considered here are largely the same as The observations used are up-to-date in previous Annual Assessments reports. data compiled under EIONET by the

European Environment Agency (EEA). Ozone episodes occur under special The CAMS policy products are relevant meteorological situations characterised for assessing rural and urban by stagnant high-pressure areas. Since background concentrations and, the formation of ozone requires sunlight, consequently, the episode events ozone episodes tend to occur mainly considered here correspond to elevated during summer. PM episodes are pollution levels in background rural and 10 usually related to stable dry conditions urban areas. Only rural, suburban and and, due to the seasonal variations of urban background station data are their main emissions, PM episodes tend considered for episode identification. The 10 to occur in winter, spring and autumn. products from CAMS are not intended for mapping or interpreting local episodes Figure 1 shows the basis for episode and exceedances at hotspots, i.e. at characterisation in 2015. The upper street level or near industrial sites. The panels show the number of elevated model resolution is too coarse to ozone incidences above the information reproduce correctly such situations and threshold; while the lower panels show appropriate local models should be used the number of incidences of PM values for such analysis. This implies that 10 above the EU legislation daily threshold. neither episodes of SO , related to 2

2 I.e. Daily means for PM10 and maximum daily 8-hour mean for ozone. There is no daily limit value for PM2.5

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Figure 1: Episode identification in 2015. Upper left panel shows the number of incidences of ozone observed values above the information threshold of 180 µg/m3 for hourly means in different European regions. Upper right panel shows the ability of the CAMS regional models and their ensemble to reproduce the observed number of incidences of ozone values above the information 3 threshold. Lower left panel shows the number of incidences of PM10 values above the threshold daily mean value of 50µg/m in different European areas. Lower right panel shows the ability of the CAMS regional models and their ensemble to reproduce the observed number of incidences of PM10 values above the daily threshold.

For ozone, the European Union's Air For PM10, the episode identification is Quality Directive (2008/50/EC) sets four done with respect to the number of standards to reduce ozone (O3) air incidences exceeding the daily average pollution and its impacts on health. Of concentration threshold of 50μg/m3; as these, daily values are regulated by a established in the Air Quality Directive. long-term objective on the maximum daily 8-hour mean concentration of The left panels in Figure 1 show the ozone that should not exceed 120μg/m3. number of incidences with observations Still, in this report, and in order to keep above threshold values in five different consistency with previous assessment areas. These areas correspond to the reports under MACC-III (Rouïl et al., country selection in Figure 2 and include 2015) the ozone episodes have been Western Europe (EUW), Central Europe identified by the number of incidences (EUC), Southern Europe (EUS), Northern exceeding the regulatory information Europe (EUN) and Eastern Europe (EUE). threshold of 1-hour average ozone concentration above 180μg/m3. In future IAARs, the long-term objective value will be used instead.

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incidences were considered for further analysis.

There is a notable bias towards identifying episodes that take place in Central and Western Europe. This is because the spatial coverage of the EIONET stations is higher in these regions. Scarce number of stations in Eastern and Southern Europe imply the possibility that a number of episodes would remain unregistered in these areas. Figure 2: European countries included in the classification of European regions used throughout this report. Region Ozone PM10 Western June 5th–6th, January 1st–9th, st th nd The right panels in Figure 1 are included Europe July 1 –5 , January 22 – July 10th–17st 23rd; to qualify the results of episode February 10th – characterisation when using the data 16th; from CAMS modelling results in order to March 12th–21st; provide information about the origin of April 8th-10th, rd th the episodes. The figures provide the April 23 -24 ; October 4th-14th; number of incidences as registered in November 1th- observations versus the number of 7nd; incidences modelled by the regional December, 18th– th CAMS models and their ensemble. As it 19 Central June 5th–6th; January 1st–9th; is indicated in these panels, the largest Europe July 1st–5th February 10th- ozone episodes are generally well August 7th-9th, 20th; reproduced by the models in the CAMS August 11th- March 15th-25th, regional re-analysis production, but with 16th April 22nd-23rd; th th a marked bias to underestimate the August30 to October 28 - September 3nd. 31st; incidence of the episodes. Still the November 1st-9th, episodes are mostly well reproduced by November 26th- the models in 2015 probably because 29th; th these took place in Central and Western December 18 - 20th Europe, where the models usually Southern No significant No significant perform better. The capabilities of the Europe episodes in episodes in data models to reproduce the episodes of PM10 data are more limited, as they missed the Northern No significant July 13th-15th, th th January, and October episodes. Still, for Europe episodes in July 24 -26 data the three largest PM10 episodes, although Eastern No significant February 2nd -3; underestimating, the models managed to Europe episodes in reproduced the episode incidences. data Table 1. Episodes identified by region according to the The above episode identification is EEA/EIONET observation database. summarised in Table 1 that shows how the identified episodes occur mainly in Western and Central Europe. Of these, the ones with the largest number of

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For ozone, the largest episode occurred (http://atmosphere.copernicus.e between: u/services/air-quality- atmospheric-composition).  1st to 7th July when exceedances of These data have been used to the hourly information threshold were visualise the extent of the registered in Central and Western episode event. Europe. 2. The dust aerosol forecast data For PM10, the three largest episodes products from the global CAMS took place from: production chain (Morcrette et al., 2008) were post-processed th th  12 to 20 February with daily to calculate PM20 mass concentrations over threshold in concentrations, to allow Central and Western Europe comparison with the regional interim re-analysis PM10  17th to 20th March when concentration levels. The concentrations over daily threshold resulting PM20 concentration were registered in Central and provides a valuable upper Western Europe estimate to the relative contribution of natural dust when th th  29 October to 7 November when present in a PM10 pollution concentrations over daily threshold episode. In the global CAMS were registered in Central and system, observations of Aerosol Western Europe. Optical Depth from the US instrument MODIS have been 2.3 Origin of pollution assimilated.

episodes 3. The green scenario forecast data from the CAMS policy products The origin and evolution of a pollution (http://atmosphere.copernicus.e episode is intrinsically determined by a u/services/air-quality- combination of meteorological conditions atmospheric-composition) and the contribution from different provides information on the emission sources. A first evaluation of contribution of emissions from the main emissions contribution to four main sectors to the concentration levels during the identified forecasted concentration levels. pollution events is presented below. These data have been post- processed to provide valuable The evaluation of the main emission estimates of the contribution sources contributing to the episode from agriculture, industry, traffic events is based on three different CAMS and residential sources to the products. These are: concentration levels for each day of the episode. 1. The interim regional re-analyses products, carried out on the basis The CAMS modelled results are of up-to-date in-situ surface data appropriate for the identification of reported to EIONET/EEA in sources and their relative contributions combination with the CAMS to pollution levels, because the relative operational regional air quality results are not affected by the systematic modelling system at errors (biases, underestimations) that

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limit the applicability of concentration results to define exceedance areas.

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2.3.1 1st – 5th July Ozone Episode representative of the maximum values during the day. The summer of 2015 was characterised by a series of heatwaves affecting Europe Traffic and industrial emissions are the from May throughout September (WMO main contributors to this ozone episode statement, 2016), with monthly average as shown in Figure 4. The figure presents records for July both in Austria and the contribution of the main four Spain. As a result, elevated ozone levels emission sectors (agriculture, industry, were observed during the summer of traffic and residential combustion) to the 2015. The largest episode occurred ozone levels in the first three days of the between 1st and 5th July, stopped on the episode. 6th and continued some places until the 7th July. The values in Figure 4 are provided as concentration in µg/m3, but represent Figure 3 presents the modelled ozone differences (and not absolute averaged fields as provided by the CAMS concentration like in Figure 3) between a interim re-analysis data for the first five reference run with current emission days of the episode. It provides an levels and CAMS green scenarios illustration of the evolution of the episode characterized by sectoral emission ad the areas affected by it. The ozone averages are 8-hourly mean values from 11:00 to 19:00 GMT, considered

Figure 3: Panel of CAMS regional ensemble modelled results for maximum daily 8-hour mean (11:00 to 19:00) for the 1st to 5thJuly summer episode. Each plot represents a different day: (a) July 1st, (b) July 2nd, (c) July 3rd, (d) July 4th, and (e) July 5th.Units: [µg/m3]

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Figure 4: Panel of daily mean differences in ozone between each CAMS green scenario simulation and the reference run from 3rd July to 5th July. Each row is a different green scenario; from top to bottom: agricultural, industrial, traffic, and residential. Each column is a different day from the three-day simulations: first column for 3rd July, second column for the 4th July and third column for the 5th July. reduction by 30%. Still, the green green scenarios post-processed as daily scenario results are directly comparable averages, are useful to rank the influence to each other, so that the different of the different emission source contributions can be ranged in order of contributions to the given episode in importance. In this way, results from the different areas across Europe.

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th th 2.3.2 12 - 20 February PM10 includes PM10 and additional coarse Episode particles with diameters larger than 10µm. th th The PM10 episode of 12 to 20 February was the largest winter episode extending Figure 6 shows that there was an over different European areas in 2015. intrusion of Saharan dust over Europe at the beginning of the winter PM10 episode th th Figure 5 shows that this winter episode with significant effects from 13 to 15 extended over most of Europe, also February. The figure is very valuable to Southern and Eastern Europe, reaching show the temporal and spatial extent of parts of Northern Europe, although it was the Saharan dust intrusion, in originally identified here on the basis of conjunction with the PM10 evolution. The elevated measured values in Central and actual PM20 values are also valuable in Western Europe. The modelled PM10 daily comparison with the PM10 calculations, as averages from the CAMS ensemble they represent an upper limit of the interim re-analysis in Figure 5 can be contribution of Saharan dust to PM10 used as an indication of the most concentrations. probable temporal and spatial evolution th of the episode. When drawing For instance, over Southern UK, on 15 conclusions from Figure 5, it is important February, CAMS modelled PM10 levels are 3 to remember that the modelled PM10 calculated to about 30µg/m , while the concentrations are generally dust PM20 contribution is identified to be 3 representative of background about 5µg/m . This means that the concentrations, and we can therefore actual contribution of Saharan dust to expect daily averages above the EU the PM10 levels over the UK is likely to be threshold of 50 µg/m3 in locally in some well below 16% this day. European regions that are not represented in Figure 5. PM10 originates from a complex mix of emission sources and it is often difficult The CAMS modelled results are to assign episodes to a single source. It appropriate for the identification of is possible, however, to compare the sources and their relative contributions emission sector contributions against to PM10 levels, because the relative each other and rank their relative results are not affected by the systematic importance during the episode. As in the errors (biases, underestimations) that case of the summer ozone episode, we limit the applicability of concentration have compiled information from the results to define exceedance areas. CAMS green scenario calculations to facilitate such evaluation. To support source allocation, data from the CAMS global aerosol dust forecast has been post-processed to be comparable to PM10 air concentrations. The dust products consist of three different size bins with diameters of 0.03 - 0.55µm, 0.55 - 0.9µm, and 0.9 - 20µm and are given in units of kgdust/kgair. The mass from all three bins has been added and converted to µg/m3. By doing so, the dust aerosol data provides information about PM20 mass concentrations. PM20

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st th Figure 5: Panel of daily CAMS PM10 average ensemble model concentrations for the 12 to 20 February winter episode. Each plot represents a different day. Units: [µg/m3]

st th Figure 6: Panel of daily averaged CAMS modelled dust concentrations as PM20 for the 12 to 20 February winter episode. Each plot represents a different day. Units: [µg/m3]

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Figure 7 shows the available data from dominate the PM10 pollution levels, the CAMS green scenarios, for the last 3 especially in Southern and Eastern days of the episodes. Data for the Europe, followed closely by the residential sector contribution on 18th contribution of ammonia emissions from February was also unavailable. agriculture. The influence of agriculture emissions in the PM10 levels of the winter Emissions from residential heating, episode is larger over Central Europe, including wood and coal combustion where it even dominates as origin over

Figure 7: Panel of daily mean differences in PM10 between each CAMS green scenario simulation and the reference run from 18th to 20nd February. Each row is a different green scenario; from top to bottom: agricultural, industrial, traffic, and residential. Each column is a different day from the three-day simulations. Note that green scenario data are missing for residential heating emissions on 18thFebruary.

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the residential emission sector. The this case, some of the data was missing. contribution from traffic and industrial Data was not available for the 18th emissions is smaller European-wide. March, and for the 17th March some data for the industrial and residential sector In addition to anthropogenic sources and contribution was not available either. Saharan dust intrusions, the winter PM10 episode also involved contributions from It is interesting to note that, while the forest fires, especially those in winter PM10 episode was primarily driven Kaliningrad. Unfortunately, such by a combination of residential heating information is not easy to process nor emissions and emissions from visualise, yet. agriculture, the March episode is clearly dominated by agriculture emissions in th th the areas of higher PM10 levels. These 2.3.3 17 - 20 March PM10 Episode areas are The Netherlands, Belgium,

th th Luxembourg, France, Germany and The PM10 episode of 17 to 20 March Southern United Kingdom. In these was the largest early spring episode and areas, the Saharan dust intrusion has with the highest recorded PM10 values in also a significant contribution to the many places in 2015. pollution event. In Eastern Europe, however, the main anthropogenic Figure 8 shows modelled PM10 daily contribution is from residential sources, averages from the CAMS ensemble not agriculture. The natural contribution interim re-analyses. Very high PM10 from Saharan dust plays also a relevant values (above 70µg/m3) were modelled role in the elevated pollution levels in over Central and Western Europe. A Eastern Europe on 18th-20th March. Saharan dust intrusion is also clearly depicted in the temporal and spatial However, the main emission sector evolution of this March episode. contributions to the episode event vary from place to place and needs to be Figure 9 shows the evolution of the considered by specific analysis of the Saharan dust intrusion as PM20 (from the area in question. CAMS aerosol products) during this early spring episode of 17th to 20th March. The intrusion shows very high PM20 levels over Southern and Central Europe. Although PM20 is only valid as an upper limit of the actual Saharan dust contribution to PM10, it is clear that in some areas over Italy, Spain and France, the Saharan dust contribution was much higher in this episode than in any of the other identified episodes in 2015.

As for the other episodes, we have compiled information from the CAMS green scenario calculations to evaluate the influence of anthropogenic emissions and rank their contribution to the pollution episode. Figure 10 shows the available data from the CAMS green scenarios for the March episode. Also in

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th th Figure 8: Panel of daily CAMS PM10 average ensemble model concentrations for the 17 to 20 March early spring episode. Each plot represents a different day. Units: [µg/m3]

st th Figure 9: Panel of daily averaged CAMS modelled dust concentrations as PM20 for the 17 to 20 March early spring episode. Each plot represents a different day. Units: [µg/m3]

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th Figure 10: Panel of daily mean differences in PM10 between each CAMS green scenario simulation and the reference run for17 , 19th and 20th March. Each row is a different green scenario; from top to bottom: agricultural, industrial, traffic, and residential. Each column is a different day from the three-day simulations. Note that green scenario data are missing for the industrial and residential heating emissions on 17thMarch

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2.3.4 29th October to 7th November industrial emissions. This is depicted in PM10 Episode Figure 16 that compiles information from the CAMS green scenario calculations, th th The PM10 episode of 29 October to 7 which evaluate the influence of November was the largest autumn anthropogenic emissions and rank their episode in 2015 and it was actually contribution to the pollution episode. divided in two different episodes. The first one, from 29th October to 31st October occurred over Central and Northern Europe. The second one, from 3rd November to 7th November affected mostly Eastern and Southern Europe.

Figure 11 shows modelled PM10 daily averages from the CAMS ensemble interim re-analysis for the first part of the episode. The influence of Saharan dust intrusions on the first part of the episode is very limited as indicated in Figure 12 that shows the evolution of the Saharan dust intrusion as PM20 from the CAMS aerosol products during this autumn episode of 29th to 31st October.

The first part of the autumn episode was dominated by agriculture emissions in Northern and Central Europe and, to a lesser degree on residential emissions, as depicted in Figure 13 that shows the available data from the CAMS green scenarios for the October episode.

The second part of the episode, in the beginning of November 2015, was centred over Germany, Poland and most of Eastern Europe. Figure 14 shows the temporal and spatial evolution of the second part of the episode and Figure 15 shows the presence of a Saharan dust intrusion associated to the November episode reaching as far north as Germany. The PM20 levels in Figure 14 are to be considered as an upper limit to the actual Saharan dust contribution to PM10 in November 2015.

The second part of the autumn episode in November 2015, was dominated by agriculture emissions, with significant contributions from residential and

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th st Figure 11: Panel of daily CAMS PM10 average ensemble model concentrations for the 29 to 31 October autumn episode over Germany and Northern Europe. Each plot represents a different day. Units: [µg/m3]

th st Figure 12: Panel of daily averaged CAMS modelled dust concentrations as PM20 for the 29 to 31 October autumn episode over Germany and Northern Europe. Each plot represents a different day. Units: [µg/m3]

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th Figure 13: Panel of daily mean differences in PM10 between each CAMS green scenario simulation and the reference run for29 , 30th and 31st October. Each row is a different green scenario; from top to bottom: agricultural, industrial, traffic, and residential. Each column is a different day from the three-day simulations.

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rd tht Figure 14: Panel of daily CAMS PM10 average ensemble model concentrations for the 3 to 7 November autumn episode. Each plot represents a different day. Units: [µg/m3]

rd th Figure 15: Panel of daily averaged CAMS modelled dust concentrations as PM20 for the 3 to 7 November autumn episode. Each plot represents a different day. Units: [µg/m3]

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Figure 16: Panel of daily mean differences in PM10 between each CAMS green scenario simulation and the reference run for the 3rd to the 6th November. Each row is a different green scenario; from top to bottom: agricultural, industrial, traffic, and residential. Each column is a different day from the four-day simulations. Note that green scenario data are missing for all emission sectors for 7th November.

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3 Air Quality Indicators in 3.1 Ozone in 2015 2015 3.1.1 Meteorological characterisation

The World Meteorological Organisation Statement on the Status of the Global Background ozone concentrations are Climate in 2015 (WMO, 2016) has strongly linked to temperature through characterised 2015 as a record warm key photochemical reactions responsible year globally. In Europe as a whole 2015 for the formation of ozone; higher was the second warmest in the last five temperatures typically lead to higher years. Heatwaves affected Europe from ozone levels. Here we compare ozone May throughout September, with average concentrations in winter, spring, monthly average records for July, both in summer, and autumn 2015 and relate it Austria and Spain, affecting ozone levels to the analysis of differences between in the areas. There were floods caused by seasonal average temperatures in 2015 heavy rain in February in parts of and the corresponding average over a

Albania, the former Yugoslav Republic of decade (2000-2010). Macedonia, Greece and Bulgaria and record high monthly precipitation records The seasonal temperature anomalies for different months over Northern relative to the 2000-2010 meteorology Europe and Scandinavia. Still, some are estimated by the Copernicus Climate areas remained particularly dry. Like in Change Service (C3S). The temperature April, in Austria, which gave rise to a anomalies presented in Figure 17 are series of forest fires that had calculated for Europe on the basis of the consequences for recorded air quality C3S/ECMWF ERA interim reanalysis (Dee levels. et al., 2011).

The meteorological conditions of 2015 The ERA-Interim daily reanalysis is affect air quality levels in conjunction available freely (for member states) from with emission data as reflected in the air http://apps.ecmwf.int/datasets/data/int quality status presented here for ozone, erim-full-daily/levtype=sfc/. nitrogen dioxide and particulate matter, both as PM10 and PM2.5. The air quality As indicated in Figure 17, the 2015 winter indicators in this chapter are derived for was warmer than the average winter 2015 meteorological conditions but are temperature in the period 2000-2010 based on non-validated air quality over most of Europe by 0.2-4.0C. The observations. Therefore, the indicators warm anomaly was strongest in the here do not aim at presenting a Eastern and Northern parts of Europe as quantification of the background shown in Figure 17. There were only few European air quality situation in 2015 exceptions to the prevailing warm regarding regulatory objectives, but conditions mostly only over the Iberian rather a characterization of that year’s Peninsula. The effects of these air quality status with respect to previous temperature conditions are visible upon years. the winter ozone mean reanalysis in Figure 18. Mean ozone concentrations were higher, in general, over Eastern and Northern Europe compared to previous years, but were slightly lower over Southern France and the Iberian

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Peninsula in comparison with other Italy, Southern France, Eastern Europe, years. and Scandinavia. The spring ozone average is shown in Figure 19.

Figure 19. Ozone spring average concentrations for 2015. 3 Figure 17. 2015 winter mean temperature anomalies relative Units: [µg/m ] to a 2000-2010 baseline (source: C3S/ECMWF ERA-Interim). Figure 17 showed that the 2015 summer was warmer over Southern and Central Europe as well as France, Southern UK, the Benelux, and the Southern part of Eastern Europe by 0.5-2.0C. In general, it was cooler over Northern UK, Scandinavia, and Russia by up to -2.0C. The hot conditions over Southern, Central and Eastern Europe led to high ozone levels over most of Europe, including even those regions that experienced cooler than average temperatures. It is likely that the cooler than average regions were affected by Figure 18. Ozone winter average concentrations for 2015. long-range transport of ozone. Only Units: [µg/m3] Northern Russia and Scandinavia experienced more typical and lower Figure 17 also showed that levels of ozone. Figure 20 shows the spring 2015 was warmer over Southern summer ozone average in 2015. France, the Western Mediterranean, and the Iberian Peninsula by 0.2-1.0C, and warmer over Northern Eastern Europe by 0.2-4.0C. In other regions, the temperature was consistent with the 10- year average temperature. The influence of the spring temperature anomalies is reflected on the mean 2015 spring ozone concentration, leading to elevated levels of ozone over the Iberian Peninsula,

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Overall, 2015 was a hotter than average year over most of Europe compared to the 2000-2010. This led to higher mean annual ozone concentrations throughout Europe compared to previous years, and these elevated ozone levels were particularly pronounced during spring and summer.

Figure 20. Ozone summer average concentrations for 2015 Units: [µg/m3]

The temperature anomalies in Figure 17 also showed that it was warmer during autumn 2015 over all of Europe by up to 2.0C except over UK and parts of western Europe. These generally warmer autumn conditions led to higher than normal ozone concentrations over most of Europe, compared to previous years. Only the UK had lower ozone concentrations than in the reanalyses of previous years, which may be explained by the cooler temperature in autumn 2015, compared to the average 2000- 2010 autumn temperature. The autumn ozone average for 2015 is shown in Figure 21.

Figure 21. Ozone autumn average concentrations for 2015. Units: [µg/m3]

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3.1.2 Ozone Health Indicators In addition, the World Health Organisation (WHO) has defined the sum The European Union's Air Quality of maximum 8-hour ozone levels over Directive (EU, 2008) sets four standards 35ppb (70μg/m3) or SOMO35 as a to reduce air pollution by ozone and its measure for the quantification of health impacts on health: hazards from ozone. This indicator is  an information threshold: 1-hour used as a health impact constraint in average ozone concentration of impact assessment modelling (WHO, 180μg/m3, 2008).  an alert threshold: 1-hour average ozone concentration of 240μg/m3, Below follows a comparison of the ozone  a long-term objective: the information threshold indicator, the alert maximum daily 8-hour mean threshold and SOMO35 for 2015 with the concentration of ozone should not same indicators calculated for earlier exceed 120μg/m3, years 3 (2007 to 2013). Note that the  and a target value: long-term information for 2015 is based on the objective should not be exceeded CAMS interim re-analysis, while the on more than 25 days per year, information from previous years is based averaged over 3 years. on validated data. Still, the figures below provide a good characterisation of the ozone values in 2015 and their

Figure 22: Number of days when the 8-hour daily average of ozone exceeds the information threshold of 180μg/m3. The different figures in the panel show results for different meteorological years (from left to right: 2015, 2013, 2012, 2011, 2010, 2009, 2008 and 2007). Unit: [Number]

3 For the comparison of ozone interim op.meteo.fr/index.php?category=eva_acces concentrations in 2015 with previous years, s) Validated values for 2014 are still not we used the CAMS re-analyses of ozone available. from 2007 to 2013 (http://macc-raq-

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associated health impacts with respect to the ozone information threshold of previous years. 180μg/m3 from 2007 to 2013 and for 2015. It shows that the generally Figure 22 shows the number of days elevated values of ozone in 2015 with when the 8-hour daily average exceeded respect to previous year’s results also in

Figure 23: Number of days when the maximum 8-hour daily mean of ozone exceeds the long-term objective value of 120μg/m3. The different figures in the panel show results for different meteorological years (from left to right: 2015, 2013, 2012, 2011, 2010, 2009, 2008 and 2007). Unit: [Number]

Figure 24: WHOs health indicator SOMO35. This is the sum of maximum daily 8-hour running mean of ozone above 35ppb (70μg/m3). The different figures in the panel show results for different meteorological years (from left to right: 2015, 2013, 2012, 2011, 2010, 2009, 2008 and 2007). Unit: [μg/m3.day]

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a higher number of days with 3.1.3 Ozone Ecosystem Indicator exceedances of the information threshold, especially in Central and The indicator generally used in Western Europe. In Central and Western regulatory reporting to assess ozone Europe, the situation in 2015 for this impact on vegetation according to the Air indicator is similar to the levels of the Quality Directive (EU, 2008) is the extreme year 2010. Also for the long- accumulated dose over a threshold of 40 term objective indicator, the number of ppb (AOT40). AOT40 is the sum of the days when the maximum 8-hour daily differences between the hourly ozone 3 mean of ozone exceeds 120μg/m is concentration (in ppb) and 40ppb, generally higher in 2015 than in the calculated for each hour when the previous 3-4 years, as shown in Figure concentration exceeds 40 ppb, 23. What seemed to be a general accumulated during daylight hours decreasing trend for high ozone peak (8:00-20:00 UTC). In the Air Quality values as reported by EEA (EEA, 2014) Directive (EU, 2008), the target value of was interrupted in 2015. By contrast, the AOT40 calculated from May to July is results shown in Figure 24, on the 18.000 (μg/m3·hours), with a long term evolution of the SOMO35 indicator, objective of 6.000 (μg/m3·hours). As shows less differences between 2015 and indicated in Figure 25, 2015 was the previous years. This is consistent characterized by elevated AOT40 levels, with the reported trends of an even especially in Southern and Central increase in background ozone levels Europe, in some places even exceeding (EEA, 2014) of which SOMO35 is also a the levels of the extreme year 2010. good indicator.

Figure 25: AOT40 indicator for protection of crops and vegetation. The different figures in the panel show results for different meteorological years (from left to right: 2015, 2013, 2012, 2011, 2010, 2009, 2008 and 2007). Unit: [μg/m3.hour]

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3.2 Nitrogen Dioxide in 2015 their emission sources. The footprint of main European city areas and maritime 3.2.1 Seasonal variations traffic emissions are the most significant features of the spatial distribution of High nitrogen dioxide concentrations are background NO2 for all seasons. generally measured in traffic or industrial stations. Nitrogen dioxide is generally Winter and autumn are the seasons with associated with hotspots situations that the highest average values. This is develop near busy roads or at industrial related to the higher frequency of stable sites. The products from CAMS are not meteorological conditions in winter and intended for reproducing the air quality autumn, with meteorological inversions situation at hotspots because the model that trap the NO2 to the ground and allow resolution is too coarse and appropriate the build-up of the pollutant near its local models should be used instead. sources. It is also in winter and autumn However, the CAMS products can provide when the photochemical processes that information on background nitrogen reduce NO2 levels are less active, thus dioxide concentrations. contributing to further accumulation of

NO2 levels. Figure 26 show the seasonal variation of background nitrogen dioxide (NO2) in 2015. The concentrations of nitrogen dioxide in background air clearly relate to

Figure 26: Seasonal averages of background nitrogen dioxide in 2015. Upper left pane is winter; lower left panel is spring; upper right panel is summer and lower right panel is autumn. Unit: [μg/m3]

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3.2.2 Nitrogen Dioxide Health also shows a comparison of the annual Indicators mean of NO2 calculated for earlier 4 There are two health indicators for years (2009 to 2013). The cities nitrogen dioxide in the Air Quality footprint is clearly marked with annual Directive (EU, 2008). The first one background concentrations ranging from 3 imposes a limit value of 200 µg/m3 to the 20 to 30µg/m in most of the places, and 3 hourly concentration of NO2 not to be reaching 40µg/m or being close to the exceeded more than 18 times per year. limit value in few ones, especially in the This is an episode-related indicator that Pô Valley, Paris area and in Russia. There applies at hotspots and is not properly is little difference between 2015 and addressed without local scale modelling. previous years with respect to the annual The second indicator refers to annual mean concentrations of nitrogen dioxide, mean nitrogen dioxide concentrations indicating the larger influence of that should not exceed the limit value of emission sources in the spatial 3 distribution of this pollutant. 40 µg/m to be in compliance with the 2008 AQ Directive. This annual mean indicator mapped throughout Europe is shown in Figure 27 for 2015. The figure

Figure 27: Annual mean value of nitrogen dioxide. The different figures in the panel show results for different meteorological years (from left to right: 2015, 2013, 2012, 2011, 2010, 2009). Unit [µg/m3]

4 For the comparison of NO2 interim op.meteo.fr/index.php?category=eva_acces concentrations in 2015 with previous years, s) Validated values for 2014 are still not we used the CAMS re-analyses of NO2 from available. 2009 to 2013 (http://macc-raq-

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3.3 PM10 in 2015 with higher PM10 levels, while PM10 concentrations decrease with The Air Quality Directive (EU, 2008) sets precipitation. This association between two standards to reduce air pollution by precipitation and PM10 is stronger at lower temperatures, when evaporative PM10 and its impacts on health: PM10 mass loss plays less of a role in PM10 removal. Furthermore, low temperature  an annual PM10 concentration limit value of 40μg/m3, is a major driver of emissions from household combustion, in autumn,  a daily PM10 concentration limit value of 50μg/m3, not to be spring, and especially in winter. exceeded more than 35 times per year Figure 28 shows PM10 average concentrations in winter, spring, 3.3.1 Meteorological summer, and autumn 2015. As characterisation emissions are larger for PM10 in winter Background PM10 concentrations are and autumn, the average concentrations linked to precipitation, temperature and in air are also larger in these seasons. stability conditions as these Spring, summer and autumn in 2015 was meteorological parameters play generally drier than in previous years, as important roles in PM10 formation and illustrated by the precipitation anomalies losses mechanisms. Precipitation is a presented in Figure 29. The analysis of very important removal mechanism for differences between seasonal average PM10 in the atmosphere. Drier conditions precipitation in 2015 and the are therefore more frequently associated corresponding averages over a decade

Figure 28: Seasonal averages of background PM10 in 2015. Upper left pane is winter; lower left panel is spring; upper right panel is summer and lower right panel is autumn. Unit: [μg/m3]

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Figure 30. Number of days with PM10 above 50µg/m3 for 2015. Unit [Number]

Figure 29. Seasonal precipitation rate anomalies for 2015 derived from C3S/ECMWF ERA interim re-analysis.

(2000-2010) is been calculated from the ERA interim on-line data for 2015 (Dee et al., 2011).

3.3.2 PM10 Health Indicators

Figure 30 shows the number days with exceedance of the daily limit value of 50µg/m3. The indicator is quite similar in 2015 and previous years. Also for the annual PM10 indicator, the background concentrations in 2015 are very similar to the results from previous years. This is illustrated in Figure 31 where the annual PM10 concentrations in 2015 are compared with annual averages from earlier years5 (2007 to 2013).

5 Using MACC/CAMS PM10 reanalysis op.meteo.fr/index.php?category=eva_acces (http://macc-raq- s)

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Figure 31: Annual mean value of PM10. The different figures in the panel show results for different meteorological years (from left to right: 2015, 2013, 2012, 2011, 2010, 2009, 2008 and 2007). Unit [µg/m3]

of PM2.5 average seasonal 3.4 PM in 2015 concentrations, compared with earlier 2.5 years6. The generally drier conditions in

2015 resulted in elevated levels of PM2.5 The Air Quality Directive (EU, 2008) sets concentrations, with concentrations a standard to reduce air pollution by above the limit value in particular over PM2.5 and its impacts on health: an the PO valley. annual PM2.5 concentration limit value of 3 25μg/m . Figure 32 shows the 2015 average

seasonal PM2.5 concentrations over 3.4.1 Meteorological Europe. Again, as emissions are larger characterisation and health for PM2.5 in winter and autumn, the indicators average concentrations in air are also larger in these seasons.

Background PM2.5 concentrations are also linked to precipitation and temperature, Compared to previous years, PM2.5 in much the same way as explained in levels were relatively high over the Iberian Peninsula, the Po Valley, and section 3.3.1 for PM10. PM2.5 is more strongly affected by wet removal than most of Central and Eastern Europe. This may be explained by the drier conditions PM10, and therefore precipitation is a prevailing in 2015 and consequent stronger predictor of PM2.5. reduced PM2.5 wet removal. The In this analysis, we have used the 2015 differences with previous are well seasonal precipitation anomalies shown illustrated in Figure 33. in Figure 29 to support the interpretation

6 Using MACC/CAMS PM2.5 re-analyses op.meteo.fr/index.php?category=eva_acces (http://macc-raq- s)

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Figure 32: Seasonal averages of background PM2.5 in 2015. Upper left pane is winter; lower left panel is spring; upper right panel is summer and lower right panel is autumn. Unit: [μg/m3]

Figure 33: Annual mean value of PM2.5 The different figures in the panel show results for different meteorological years (from left to right: 2015, 2013, 2012, 2011, 2010, 2009 and 2008). Unit [µg/m3]

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The four most significant air pollution 4 Conclusions episodes, affecting an extended European area, for each of the four

seasons were identified. Their origin has The year 2015 has been characterised by been evaluated with the help of currently WMO as a record warm year globally available CAMS products: a) the CAMS (WMO, 2016). In Europe as a whole 2015 regional ensemble interim re-analysis for was the second warmest in the last five 2015, b) the CAMS global aerosol dust years as indicated by results from the products and c) the CAMS green scenario ERA interim reanalysis (Dee et al. 20111) calculations for anthropogenic emissions. from the Copernicus Climate Change

Service (C3S). Heatwaves affected In 2015, a significant PM pollution Europe from May throughout September, 10 event took place from 12th to 20th with monthly average records for July February, affecting most areas in Europe. both in Austria and Spain. There were The origin of this winter episode varies floods caused by heavy rain in February from country to country and is a complex in parts of Albania, the former Yugoslav combination of different anthropogenic Republic of Macedonia, Greece and and natural sources. Emissions from Bulgaria and record high monthly residential heating dominate the PM precipitation records for different months 10 pollution levels of the winter episode, over Northern Europe and Scandinavia. especially in Southern and Eastern Still, some areas remained particularly Europe, followed closely by the dry, which gave rise to a series of forest contribution of ammonia emissions from fires that had consequences for recorded agriculture. In Central Europe, however, air quality levels. agriculture emissions dominate as origin

of this PM episode over other The effect of the meteorological 10 anthropogenic sources. Furthermore, a conditions of 2015 on air pollution has Saharan dust intrusion affected also PM been studied here in conjunction with 10 pollution levels over Southern and emission data. The generally warm Western Europe. In addition, the winter conditions in 2015 result in elevated PM episode involved also contributions ozone peak levels with respect to 10 from forest fires in a few locations. previous years. In Central and Western

Europe, the situation in 2015 for ozone Another important PM episode occurred over information threshold indicator is 10 in March 2015. It took place from 17th to similar to the levels of the extreme year 20th March and it is a typical early spring 2010. The generally drier conditions in episode. While the winter PM episode 2015 resulted also in elevated PM2.5 10 was primarily driven by a combination of annual levels, and the calculations show residential, heating emissions and the highest annual PM values over the 2.5 emissions from agriculture, the March past few years in the Po Valley, the episode is clearly dominated by Iberian Peninsula and most of central agriculture emissions in the areas of and Eastern Europe. higher PM levels. These areas are in 10 Central and Western Europe, where also A series of large-scale pollution events Saharan dust intrusions has a significant affected European air quality over the contribution to the pollution event. In different seasons in 2015. There were Eastern Europe, however, the main ozone episode events during the summer anthropogenic contribution is from and significant PM pollution events in 10 residential sources, not agriculture. The winter, spring and autumn. natural contribution from Saharan dust

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plays also a relevant role in the elevated pollution levels in Eastern Europe on 18th-20th March. The Saharan dust intrusion lead to very high PM20 levels over Southern and Central Europe. Although PM20 is only valid as an upper limit to the actual Saharan dust contribution to PM10, it is clear that in some areas over Italy, Spain and France, the Saharan dust contribution was much higher in this episode than in any of the other identified episodes in 2015.

There were no summer episodes of PM10 in 2015. Instead, the series of heatwaves affecting Europe in 2015 resulted in different ozone episodes. The largest ozone episode occurred between 1st and 5th July 2015. Traffic and industrial emissions are the main contributors to this ozone episode event.

th th The PM10 episode of 29 October to 7 November was the largest autumn episode and it was divided in two different episodes. The first one, from 29th October to 31st October, occurred over Central and Northern Europe. The second one, from 3rd November to 7th November affected mostly Eastern and Southern Europe. The first part of the autumn episode was dominated by agriculture emissions in Northern and Central Europe and, to a lesser degree, on residential emissions. The influence of Saharan dust intrusions on this part of the episode were very limited. The second part of the episode, in the beginning of November 2015, was centred over Germany, Poland and most of Eastern Europe. It was dominated by agriculture emissions, with significant contributions from residential and industrial emissions. In this second part, the presence of a Saharan dust intrusion was identified reaching as far north as Germany. However, the main emission contributions to the episode event vary from place to place.

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5 References

Berrisford, P., et al. "The ERA-Interim archive Version 2.0, ERA Report Series 1, ECMWF, Shinfield Park." Reading, UK 13177 (2011).

Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.- K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553–597. doi:10.1002/qj.828

EU (2008) Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe (OJ L 152, 11.6.2008, p. 1–44).

EEA (2014) Air pollution by ozone across Europe during summer 2013 – Overview of exceedances of EC ozone threshold values: April-September 2013. EEA Technical Report No. 3/2014. ISBN 978-92-9213-422-8

Morcrette, J.-J., A. Beljaars, A. Benedetti, L. Jones, and O. Boucher (2008), Sea-salt and dust aerosols in the ECMWF IFS model, Geophys. Res. Lett., 35, L24813, doi:10.1029/2008GL036041

Rouïl, L. et al. (2015) European Air Quality assessment report for 2013 - MACC-III report 54.7

Schulz, M. A. Valdebenito, M. Gauss, A. Mortier, H. Fagerli, A. Nyiri, P. Wind (2016) Methodology and system setup for the production of regional and city source receptor calculations, CAMS-D71.3.1

Schaap,M., R. Kranenburg, S. Jonkers, A. Segers, M. Schulz, S. Valiyaveetil, A. Valdebenito (2016) Methodology and system setup for the production of country source receptor calculations CAMS-D71.3.2

WHO (2008) Health risks of ozone from long-range transboundary air pollution-ISBN 978 92 890 42895

WMO (2016) WMO Statement of the Status of Global Climate in 2015, WMO No. 1167 ISBN 978-92-63-11167-8

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ECMWF Shinfield Park Reading RG2 9AX UK

Contact: [email protected]

atmosphere.copernicus.eu copernicus.eu ecmwf.int