# Atmospheric aerosol variability above the Paris Area during the 2015 heat wave - Comparison with the 2003 and 2006 heat waves

Patrick Chazette, Julien Totems, Xiaoxia Shang

► To cite this version:

Patrick Chazette, Julien Totems, Xiaoxia Shang. Atmospheric aerosol variability above the Paris Area during the 2015 heat wave - Comparison with the 2003 and 2006 heat waves. Atmospheric Environment, 2017, 170, pp.216-233. 10.1016/j.atmosenv.2017.09.055. hal-02902908

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# Atmospheric aerosol variability above the Paris Area during the 2015 heat wave - comparison with the 2003 and 2006 heat waves

Patrick Chazette, Julien Totems and Xiaoxia Shang

LSCE (IPSL), CEA-CNRS-UVSQ, UMR 8212, Gif-sur-Yvette, France

## Abstract.

The aerosol layers during the heat wave of July 2015 over Paris Area have been studied using a N₂-Raman lidar with co- and cross-polarized channels. The lidar observations are examined to allow the identification of main aerosol types and their origins, in synergy with measurements of the AERONET sunphotometer network and back trajectory studies from the HYSPLIT model. The results are compatible with spaceborne observations of MODIS and CALIOP. As for previous heat waves of August 2003 and July 2006 occurring in France, the aerosol optical thickness is very large, up to 0.8 at the lidar wavelength of 355 nm (between 0.5 and 0.7 at 550 nm). However, air mass trajectories highlight that the observed aerosol layers may have multiple and diverse origins during the 2015 heat wave (North America, Northwest Africa, Southern and Northern Europe). Biomass burning, pollution and desert dust aerosols have been identified, using linear particle depolarisation ratio, lidar ratio and analysis of back trajectories initiated at the altitudes and arrival times of the plumes. These layers are elevated and are shown to have little impact on surface aerosol concentrations (PM₁₀ < 40 µg m⁻³ or PM₂.₅ < 25 µg m⁻³) and therefore no influence on the local air quality during the 2015 heat wave, unlike in 2003 and 2006. However, they significantly modify the radiative budget by trapping part of the solar ingoing/outgoing fluxes, which leads to a mean aerosol radiative forcing close to +50±17 Wm⁻² per aerosol optical thickness unit at 550 nm (AOT₅₅₀) for solar zenith angles between 55 and 75°, which are available from sunphotometer measurements. This value is smaller than those of the 2003 and 2006 heat waves, which are assessed to be +95±13 and +70±18 Wm⁻²/AOT₅₅₀, respectively. The differences between the heat wave of 2015 and the others are mainly due to both the nature and the diversity of aerosols, as indicated by the dispersion of the
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single scattering albedo distributions at 550 nm: 0.90±0.03, 0.95±0.02 and 0.93±0.04 for 2003, 2006 and 2015, respectively.

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Keywords: heat wave, aerosol origins, N₂-Raman lidar, air quality, radiative forcing

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# 1 Introduction

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Significant heat waves happen about once in every 10 years in France, and climate change is believed to contribute to an increase of this frequency (IPCC, 2014). Three heat waves occurred in France since the beginning of the 21st century. France and most of Western Europe experienced a strong heat wave in August 2003 with severe societal impact (Poumadère et al., 2005). Approximately 15000 deaths were recorded during that period in France, and 35000 in Europe, with about one third related to both ozone and aerosol pollutions. The meteorological event was well forecasted, but not its societal consequences. Three years later, in July 2006, another heat wave occurred with a lesser human impact. The mean ground-level daily temperature was ~25°C during that heat wave, ~3°C less than that of August 2003 (temperature measurements by Météo-France).

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As in August 2003 and July 2006, the heat wave of July 2015 is associated with a weather blocking system located above Western Europe for ~5 days. Such a high-pressure system favours the transport of warm air masses from southern regions. Aerosols may be trapped within these air masses as demonstrated by Hodzic et al. (2007) for the heat wave of August 2003, when biomass burning particles originating from forest fires in Portugal covered a large part of France, including the Paris Area. Associated with low wind speeds, the aerosol layers may help increase the stability of the lower troposphere by absorbing solar radiation, delaying or preventing the development of the planetary boundary layer (PBL). This, in turn, helps maintain high temperatures during night time (Péré et al., 2011) and may increase the concentration of pollutants close to the surface.

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Ground-based lidar observations are commonly used to study atmospheric aerosols (e.g. Müller et al., 2005; Ansmann et al., 1992) and operational lidar networks are expanding (e.g. Papayannis et al., 2008; Sicard et al., 2011; Pappalardo et al., 2013; Balis et al., 2016; Baars et al., 2016). Nevertheless, heat waves are poorly documented using lidar intense observation campaigns, mainly
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because it is difficult to predict heat wave occurrence in advance and raise funds from governmental agencies. Therefore, they are mainly studied using modeling (e.g. Ordóñez et al., 2010) and spaceborne observations (e.g. Hodzic et al., 2006).

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In this paper, we take advantage of continuous measurements by a N₂-Raman lidar in the Paris Area during the heat wave of 2015, which as far as we know represents the first continuous atmospheric column dataset during a heat wave in Western Europe. The same type of instrument was used during the European program MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation, Royer et al., 2011) in July 2009. It allowed the validation of mesoscale chemical transport models used for air quality forecasting (Wang et al., 2013). During the Chemistry-Aerosol Mediterranean Experiment (ChArMEx, http://charmex.lsce.ipsl.fr) and Hydrological cycle in the Mediterranean eXperiment (HyMeX, http://www.hymex.org/) of the multidisciplinary programme Mediterranean Integrated Studies at the Regional and Local Scales (MISTRALS; http://www.mistrals-home.org), a similar lidar system proved to be a powerful instrument for aerosol identification (Chazette et al., 2014; Chazette et al., 2016).

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Following weather forecasts which predicted a heat wave several days before it started on 1st July 2015, the lidar system LAASURS (Automatic Lidar for Atmospheric Surveys using Raman Scattering) was put into operation in Palaiseau (48.7°N 2.22°E), south of Paris. Its observations cover the heat wave period between 1st and 5th July, and the post heat wave period on 6th-10th July. Simultaneously, a co-located meteorological station performed measurements of thermodynamic temperature, pressure and relative humidity. Hereafter we describe the observational datasets and analysis methods (section 2), followed by the weather conditions (section 3). Our observations of the tropospheric aerosol content seen above Palaiseau during the 2015 heat wave are presented in section 4. In the same section, the Moderate Resolution Imaging Spectroradiometers (MODIS) is used to compare the main fields of the regional aerosol optical thickness for the heat waves of 2003, 2006 and 2015. In section 5, using ensemble back-trajectories, we discuss the link between the long-range

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transport of aerosols commonly observed in such events and the local air quality. The aerosol typing derived from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) in the pollution plumes is also used. The impacts on the local pollution (section 6) and the radiative forcing (section 7), highlighting differences between the heat waves of 2015 and those of 2003 and 2006, are finally presented.

## 2 Datasets and methods

### 2.1 AERONET data

The aerosol optical thickness (AOT), the visible Ångström exponent and the single scattering albedo (SSA) are derived from the AEROSOL RObotic NETwork (AERONET) sunphotometer stations (http://aeronet.gsfc.nasa.gov/). We use the level 2 (version 2) cloud-screened data (Dubovik and King, 2000). The AOT is retrieved with a maximal absolute uncertainty of 0.02, independent of the aerosol load, at 7 wavelengths of the solar spectrum between 340 and 1020 nm.

The aerosol radiative forcing parameters are also extracted from the AERONET database. The operational inversion of sunphotometer data uses a complete radiative transfer model (García et al., 2008). The broadband fluxes between 0.2 and 4 µm are computed thanks to the discrete ordinate (DISORT, Nakajima and Tanaka, 1988; Stamnes et al., 1988) for the aerosol contribution and the global atmospheric (GAME, Dubuisson et al., 1996; Roger et al., 2006) models.

For the surface level instantaneous radiative forcing of atmospheric aerosols (BOARF), García et al. (2008) performed a significant study based on a comprehensive sampling of atmospheric aerosol load (~4000 measurements), which happen to include both the range of AOT and the diversity of aerosol type observed during the 2015 heat wave above France. They found on the BOARF, for mixed aerosol types, a bias of 9 Wm⁻² (when comparing to direct irradiance measurements as shown by García et al. (2008)) and a standard deviation of 12 Wm⁻². The uncertainty on the top of atmosphere instantaneous radiative forcing of atmospheric aerosols (TOARF) is difficult to assess directly, but its impact on the radiative budget will be taken into account in section 7.
In the following we will consider the available data, of the French AERONET station (Avignon, Carpentras, Dunkerque, Fontainebleau, Le Fauga, Lille, Palaiseau, La Crau, OHP observatoire, Paris, Toulon, Villefranche, Arcachon, Aubière, Bure, Clermont Ferrant, and Frioul; see http://aeronet.gsfc.nasa.gov/), acquired during the three considered heat waves. The data of the Palaiseau station will be used as a constraint for the inversion of lidar profiles during daytime.

## 2.2 N₂-Raman lidar

LAASURS is similar to the Water vapour and Aerosol Lidar (WALI), which was operational during HyMeX (http://www.hymex.org/, Chazette et al., 2014) and ChArMEx (http://www.mistrals-home.org, Chazette et al., 2016), but with a lower emitted energy (16 mJ per pulse instead of 60 mJ at 355 nm) and without a water vapour Raman channel. The LAASURS system itself is well described and validated in Royer et al. (2011) and Chazette et al. (2012). The wide field-of-view (FOV) ~2.3 mrad allows a full overlap of the transmission and reception paths beyond ~150-250 m. Three different channels record the total, the cross-polarized (with respect to the laser emission) elastic backscatter signal of the atmosphere (elastic channels), and the inelastic nitrogen vibrational Raman backscattered signal (N₂-Raman channel). The LAASURS instrument can be used in urban/peri-urban areas because its low emitted energy density fulfills eye-safety requirements.

The use of the N₂-Raman channel during night time allows retrieving the total AOT but also the cumulative AOT profile, which when combined with the elastic channel yields the aerosol extinction/backscatter coefficient (AEC/ABC) and the lidar ratio (LR). The method is well described in Chazette et al. (2016) and the main uncertainties sources are discussed in Royer et al. (2011). The relative uncertainty on the lidar-derived total AOT retrieved from the N₂-Raman channel is less than 2%, when considering a temporal resolution of 30 minutes. On the other hand, the LR profile is typically constrained using the cumulative AOT profile between 0.3 and 3 km, which requires a signal-to-noise ratio (SNR) greater than 10 up to the maximum altitude of this analysis. At higher altitudes, the SNR is not sufficient to perform the inversion. With a mini-lidar like LAASURS, and in the atmospheric conditions encountered during the heat wave of 2015 (AOT > 0.4 at 355 nm and
significant aerosol content up to 6 km, see below), a long temporal integration over ~4 hours with a
vertical resolution ~30 m is necessary for a lidar profile inversion to reach more than 6 km altitude.
Given the remaining noise and errors on the spectral dependency of the aerosol optical properties
(Ångström coefficient), the uncertainty on the determination of the LR is in the range of 10-15 sr
(following error calculations in Royer et al. (2011)). This still made it possible to verify that the LR
did not vary much between the aerosol layers and therefore an equivalent, altitude-independent value
has been used to invert the lidar profiles with a temporal resolution of the order of 10 minutes. During
daytime, the SNR of the N₂-Raman channel is insufficient and the inversion is instead constrained by
the sunphotometer-derived AOT. We do not give a detailed presentation of the inversion method here,
as it is now fairly standard and is well explained in previous publications on lidar instrumentation
that we have developed (e.g. Royer et al., 2011; Chazette et al., 2016).

The linear particle depolarization ratio (PDR) is retrieved after calibration of the lidar using the
method presented in Chazette et al. (2012). The PDR is calculated only for AEC greater than
0.04 km⁻¹, as it is undefined and noisy for a lesser aerosol content. The relative uncertainties on the
PDR are close to 10% for the encountered AOTs at 355 nm (> 0.2).

## 2.3 Meteorological probe

A Vaisala PTU-300 probe is set-up next to the lidar at ~2 m height above ground level (agl). It
measures the atmospheric pressure within an uncertainty of 0.6 hPa, the thermodynamic temperature
within an uncertainty of 0.15 K and the relative humidity within a relative uncertainty of 5%, for each
lidar profile (1 minute sampling time).

## 2.4 AIRPARIF stations

During the heat wave and post heat wave periods, we use hourly-mean PM₂.₅ and PM₁₀
measurements from the in-situ station network of the Paris air quality agency AIRPARIF
(http://www.airparif.asso.fr/). Only the urban, peri-urban and rural stations are considered, excluding
traffic sites. After calibration, the uncertainty on PM₁₀ concentrations measured within the
158 AIRPARIF network is assessed to be between 14.8 and 20.9% (personal communication from
159 AIRPARIF).

160 **2.5 Spaceborne measurements**

161 **SEVIRI.** The Spinning Enhanced Visible and Infra Red Imager (SEVIRI), onboard Meteosat
162 Second Generation (MSG) (https://wdc.dlr.de/sensors/seviri/), allows the retrieval of the AOT
163 (SEV_AER-OC-L2 product over the ocean) with spatial and temporal resolutions of 10×10 km² and
164 15 minutes, respectively. The uncertainty on the SEVIRI-derived AOT is very dependent on the
165 aerosol type (Bennouna et al., 2009). Compared to AERONET products from coastal stations,
166 Thieuleux et al. (2005) do not highlight any significant bias on the AOT at 550 nm derived from
167 SEVIRI for values between ~0.07 and 1. However, Chazette et al. (2016) show that a bias exists when
168 using the operational version 1.03 of the AOT product at 550 nm and a correction was made following
169 the same authors. We use SEVERI-derived AOT above ocean when the MODIS product is not
170 available, due to occasional sun glint.

171 **MODIS.** The Moderate Resolution Imaging Spectroradiometers (MODIS, Salmonson et al.,
172 1989; King et al., 1992) are aboard the Aqua and Terra platforms (http://modis-atmos.gsfc.nasa.gov).
173 The polar orbit of Terra (http://terra.nasa.gov) passes over the equator from north to south in the
174 morning, whereas Aqua (http://aqua.nasa.gov) has its ascending node over the equator during the
175 afternoon. They provide a complete coverage of the Earth surface in one to two days with a resolution
176 between 250 and 1000 m at ground level depending on the spectral band. We use the Terra and Aqua
177 AOT at 550 nm from the MODIS aerosol product level-2 data. Both products are given with a spatial
178 resolution of 10×10 km² at nadir. The standard deviation on the AOT retrieval (Remer et al., 2005)
179 over land (ocean) is 0.15±0.05*AOT* (0.05±0.03*AOT*).

180 **CALIOP.** The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) flies onboard the
181 Cloud-Aerosol Lidar Pathfinder Satellite Observation (CALIPSO). Details on the CALIOP
182 instrument, data acquisition, and science products are given by Winker et al. (2007). In this work, we
183 use CALIOP level-2 data, version 4.10, which was corrected for aerosol typing as noted in Burton et
al. (2015). The lidar profiles are considered below 8 km above the mean sea level (amsl) at the wavelength of 532 nm (https://www-calipso.larc.nasa.gov/products/).

## 2.6 Dynamic modelling

The dynamical analyses performed for this study are based on the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model (Draxler and Rolph, 2015; Stein et al., 2015). The wind fields used as the input of the HYSPLIT model are from GDAS (Global Data Assimilation System, http://www.ncep.noaa.gov/) at 0.5° horizontal resolution. The isentropic ensemble mode with 24 individual back trajectories is considered hereafter. It allows to take into account the transport trajectory spread associated with the wind field. To help the understanding of spatial observations, the reanalyzed wind fields of the European Centre for Medium-range Weather Forecasts/integrated forecast system (ECMWF/IFS, http://www.ecmwf.int) are also used with 0.75° horizontal resolution, as in Kim et al. (2004).

## 3 Meteorological conditions during the heat wave of 2015

The temporal evolution of ground-based temperature and relative humidity measurements at 2 m agl at Palaiseau for the entire measurement period, i.e. from 30th June to 10th July, is shown in Figure 1a. The temperature in the shade is maximal on 1st July and reaches ~38 °C. It remains high until 5th July with nightly values above 20°C, fulfilling the defining characteristics of a heat wave (e.g. Miralles et al., 2014). Similarly, high temperatures were reported all across Western Europe, as far as Poland, where the mean temperature in the shade reached 36°C for the same time period. At 0900 UTC on 1st July, the temperature was already 32.5 °C at Heathrow, resulting in the highest maximum night time temperature between 2100 and 0900 UTC on record for the United Kingdom. Such a hot spell over Western Europe is in fact associated with an area of high-pressure aloft, nosing north-eastward from the Iberian Peninsula into parts of Northern Europe. Such an anomaly corresponds to a positive phase of the North Atlantic Oscillation index (NAO), as previously reported for similar events (Hurrell et al., 2004). Climate change projections predict a significant increase in
209 the frequency of such extreme events, in the wake of the one that occurred in 2003 in Europe
210 (Beniston, 2004; Stott et al., 2004; IPCC, 2014). Recent publication by Bador et al. (2016) shows that
211 summer record-breaking temperatures in Western Europe are already more frequent than what would
212 be expected in a stationary climate since the late 1980s.

213 Figure 2 shows, on 1st July 2015, the geopotential altitude for 2 pressure levels: 975 hPa (Figure
214 2a) and 800 hPa (Figure 2b). A high is located in altitude (~800 hPa) south of the Western
215 Mediterranean Basin. A deep low is located over Iceland. Such a pattern allows air mass
216 transportation from south-southwest towards Western Europe, as shown by the presence of a cold
217 front mainly spread along latitude over the Atlantic Ocean off Spanish and French coasts. High
218 pressure in the free troposphere also induces lower wind speeds, between 1 and 2 m s⁻¹, in the low
219 troposphere (Figure 2). Dry, sinking air and light winds allow stifling heat to build up and persist over
220 time. This is associated with dry soil and an evapotranspiration deficit leading to reduced latent heat
221 flux. Indeed, both lower atmospheric circulation and land-atmosphere interaction seem to be
222 important criteria for a persistent heat wave (Miralles et al., 2014). Due to the specific atmospheric
223 circulation in the free troposphere during the heat wave, France may be subject to aerosol plumes
224 from remote sources. During the considered time span, eastward long range transport occurs ~5-7 km
225 amsl over the Atlantic along a planetary wave (also called an atmospheric Rossby wave, a giant
226 meander in high-altitude winds induced by the latitudinal gradient of Coriolis inertia) located between
227 40 and 55° N (not shown).

<figure><img src="image_2.png" /></figure>
<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /><figcaption>Figure 1: Temporal evolutions, from 30th June to 10th July 2015, of a) thermodynamic temperature and relative humidity at 2 m agl; b) lidar and sunphotometer-derived aerosol optical thickness (AOT) at 355 nm, Ångström exponent over the visible domain (440 nm–670 nm) retrieved by sunphotometer and column-equivalent lidar ratio (LR); c) Mean ground level aerosol particle matter with aerodynamic diameter less than 2.5 (PM<sub>2.5</sub>) and 10 µm (PM<sub>10</sub>) for the urban, peri-urban and rural station of the AIRPARIF air quality network. The standard deviations on PM<sub>10</sub> and PM<sub>2.5</sub> are represented by the vertical lines.</figcaption></figure>
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<figure><img src="image_5.png" /></figure>
b)

<figure><img src="image_6.png" /><figcaption>Figure 2: Geopotential altitude given for the pressure levels of a) 975 and b) 800 hPa at 1200 UTC on 1st July 2015, from reanalyses of numerical weather prediction model ECMWF/IFS. The wind field is also shown on each figure. The cold front is given in white for the pressure level of 975 hPa.</figcaption></figure>

# 4 Description of remote sensing aerosol measurements

## 4.1 Local observations

### 4.1.1 Integrated optical properties

The sunphotometer-derived AOT and Ångström exponent are shown in Figure 1b for both the heat wave and post heat wave periods. Around Paris, the AOT at the wavelength of 355 nm rapidly increases during 1st July, from average (0.15) to outstanding values of around 0.5. They remain high until 5th July at noon with a maximum mean daily value of ~0.8 on 2nd July. The Ångström exponent also changes during this period with values close to 1.5 up until 2nd July and lower than 1.4 for the rest of the period, reaching 1.1. This could show a shift of origin for the air masses passing over the Paris Area during the heat wave. Particles of larger size would have been added to urban aerosols,
which have an Ångström exponent somewhat larger than 1.5 in the Paris Area (e.g. Royer et al., 2011).

In comparison, the highest daily mean AOTs at the same wavelength during the heat wave of 2003 (from 5th to 14th August) is calculated to be ~1.0 and 0.9 on 8th and 14th August, respectively. The corresponding visible Ångström exponent is between 1 and 1.4, which could indicate a mixing of dust-like and pollution/biomass burning aerosols. The AOT stays higher than 0.5 during all the heat wave. For the heat wave of July 2006 (from 19th to 26th July), the aerosols exhibited an Ångström exponent ~1.6±0.25 and a maximal mean daily AOT of ~0.8 on 26th July.

### 4.1.2 Vertical structure profiling

The high temporal variability of the aerosol content in the lower and middle troposphere, observed on sunphotometer measurements, is also seen on lidar vertical profiles derived from the LAASURS instrument (Figure 3). For the entire period, the inversion of the lidar vertical profiles during night time shows that the LR vertical dependence in the observed aerosol layers is small compared to the uncertainty of 10-15 sr. Conversely, as shown in Figure 1b and on the histogram given in Figure 4a, LR evolves significantly with time. It is much higher (50 to 80 sr) at the beginning of the heat wave and almost constant with a value close to 40 sr from 4th July. Hence, there is a strong standard deviation of 21.9 sr of the LR (larger than the uncertainty of ~10-15 sr) around its mean value of 44.2 sr, confirming a high variability of the aerosol type in the lower and middle troposphere all along the measurement period, ranging from the onset of the heat wave to its disappearance.

An example of the cumulative AOT profile is given in the inset of Figure 4a for the night on 2nd-3rd July where different aerosol layers are present in the troposphere. The comparison between the vertical profiles of cumulative AOT deduced directly from the N₂-Raman measurement and the classic inversion scheme proposed by Klett (1985) (see Royer et al., 2011) clearly emphasises that a altitude-independent LR is a good compromise (Figure 4a). For this example, the column-equivalent LR is determined to be equal to 57 sr. The cumulative AOT computed using LR of 47 and 67 sr are also given, showing only a small difference of AOT (<5%) than the noise-induced error. Moreover,
Figure 4b gives the vertical profiles of ABC derived from the N₂-Raman and the elastic channels, matching within 2% even in the main two aerosol layers close to 1.5 and 3.5 km amsl. It is worth noting that the lidar-derived LR for the lower and upper aerosols layers are assessed to be 57.5 and 61 sr; such a difference is not considered significant compared to the estimated uncertainty (10-15 sr).

The temporal evolution of vertical profiles of both the AEC and the PDR are shown in Figure 3. The high temporal variability of the integrated optical parameters is closely related to the complex vertical structure of the aerosols signature in the low and middle troposphere, with many well-differentiated layers. Some of them have significantly different values of PDR (between 7 and 15%) than the ones of urban aerosols (PDR < 2%, Dieudonné et al. (2015)). Using the same previous example, Figure 4b gives the vertical profiles of the PDR (in blue), which is very variable due to the change of the aerosol properties within the troposphere, but also to the lower SNR in the upper part of the profile. The peak close to 5 km amsl has to be considered with caution (AEC < 0.01 km⁻¹), and the increase above 6 km amsl is likely due to a smaller aerosol backscattering.

In Section 5, we will investigate the origin of air masses responsible for the main observed vertical structures.

a)

<figure><img src="image_7.png" /></figure>
b)

<figure><img src="image_8.png" /><figcaption>Figure 3: Temporal evolutions of the vertical profiles of a) the aerosol extinction coefficient (AEC) and b) the linear particle depolarization ratio (PDR). The PDR is only considered for AEC > 0.04 km⁻¹. Time gaps are due to cloudy profiles that were not inverted. The main air mass origins are also given in (a), they are determined using HYSPLIT backtrajectories initiated at the time and location of the aerosol layers identified by the lidar.</figcaption></figure>

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<figure><img src="image_9.png" /></figure>
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<figure><img src="image_10.png" /></figure>

Figure 4: a) Occurrence of the LR for the heat wave and post heat wave periods. In the inset, the mean vertical profiles over 4 hours of the cumulative aerosol optical thickness (AOT) are given for the night on 2^nd^-3^rd^ July. They are derived from the Raman inversion using N₂-Raman channel and the classic Klett inversion scheme (Klett, 1985). The gap between the two previous approaches is given by the grey area. b) mean verticals profiles, for the same night (averaged over 4 hours), of the N₂-Raman- and Klett-derived aerosol backscatter coefficients (ABC), the Klett-derived aerosol extinction coefficient (AEC) and linear particle depolarization ratio (PDR).

## 4.2 Regional observations

MODIS measurements provide the AOT over Western Europe and are a good reference to compare the aerosol load during the 3 heat waves. Figure 5 shows the AOTs on 5^th^ August 2003 (a) and 25^th^ July 2006 (b), representative days of the 2003 and 2006 heat waves. As pointed out by Hodzic et al. (2006) (see Fig. 7b of this reference) for the 2003 heat wave, the Portuguese forest fires could be responsible for the aerosol plume spreading between Spain and northern England (mushroom shaped with AOT> 0.5 at 550 nm; Figure 5a). This plume is dispersed East and South the following days and goes on to cover a large part of France. Along with more local emissions, it is one of the strongest contributor to the AOT during the 2003 heat wave. It is worth noting that very low wind speeds (<4 ms⁻¹) are observed at 700 hPa in the biomass burning aerosol plume center, and the same at ground-level (not shown), favoring the accumulation of pollution.

On 25^th^ July 2006 (Figure 5b), the AOT close to Paris is as high as in 2003 (Figure 5a). For the heat wave of July 2006, the information is sparse about the aerosol plume origins. Nevertheless, literature reports the advection of hot and dry air from North Africa which may be linked with Saharan
dust transport above the PBL (Struzewska and Kaminski, 2008). Back trajectory studies performed by Terrenoire and Fèvre-Nollet (2008) also show a north-easterly flow arriving over the North of France associated with likely polluted air masses maintained by equally low wind speeds (<2 ms⁻¹). This is confirmed when surveying CALIOP orbits during the period of the 2006 heat wave, we find polluted continental/polluted dust, and sometimes elevated smoke, on all 10 observations from the 19th to 27th of July. An example of the CALIOP-derived aerosol typing is given in Figure 6 on the 25th of July 2006, corresponding to the CALIOP ground track given in Figure 5b.

During the 2015 heat wave, as shown in Figure 5c on 3rd July, high AOTs (> 0.4 at 550 nm) cover the entire metropolitan France. This confirms the similar importance of the three heat waves in terms of aerosol load in the low troposphere, although we will see in Section 5 that the 2015 heat wave is associated with a larger diversity of aerosol types.

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<figure><img src="image_11.png" /></figure>

b)

<figure><img src="image_12.png" /></figure>
<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

Figure 5: Aerosol optical thickness (AOT) at 550 nm on a) 5th August 2003 with the wind field at 700 hPa, b) 25th July 2006 (1200 – 1400 UTC) with the wind field at 850 hPa, c) 3rd July 2015 (1200 – 1400 UTC) with the wind field at 950 hPa (easterly dominant in the Paris Area), and d) 9th July 2015 (1200 – 1400 UTC) with the wind field at 500 hPa (northwesterly dominant in the Paris Area). (a), (b) and (d) are derived from MODIS over land and sea; (c) is derived from a combination between MODIS over land and SEVIRI over sea. The night time (~0200 UTC) ground tracks of CALIOP are given in black continuous lines for 25th July 2006 (b) and 9th July 2015 (d). The daytime (~1200 UTC) ground tracks of CALIOP is given in black continuous lines on 3rd July 2015. Wind fields from ECMWF/IFS reanalyses.

<figure><img src="image_15.png" /></figure>

Figure 6: CALIOP-derived aerosol typing for the night time (~0300 UTC) orbit of 25th July 2006. The latitudinal location of the ground-based lidar is indicated by the vertical black line.

5 Air mass origins: back trajectory analysis for the heat wave of 2015
Throughout the heat wave of 2015 in France, the transport of aerosol layers in the lower and middle troposphere was mainly from the south. This situation may favour Saharan dust contributions to the aerosol load. However, the moderate PDR values, mostly lower than 10%, as reported on Figure 3b, associated with Ångström coefficients which predominantly remain larger than 1 on Figure 1b, indicate a mixture in which dust may not be predominant. Note that, during spring, dust aerosol transports are often observed above Western Europe, and may even occur in the higher troposphere (e.g. Müller et al., 2005). Such a situation is less common in summer and the aerosol loads are mainly associated with both local emission and resuspension by dynamic process above dry soils, as droughts increase erodibility (Hodzic et al., 2006).

The main aerosol layers observed during the heat wave of July 2015 have been identified by coupling lidar measurements with back trajectory studies. The lidar-derived vertical structure of the atmosphere (see Figure 3) is used to define the back trajectory endpoints before running the HYSPLIT model in ensemble mode as described in section 2. The altitude range of the considered aerosol layers is reported in Table 1.

Following the computed back trajectories, the probable origins of the main plumes are given in Figure 3a and Table 1. They are very diverse, with air masses transporting aerosols from various sources. Indeed, a contribution of Saharan sources is highlighted, but so are the local pollution and more distant aerosol emitters. We note that, as it is often the case and has been observed in previous measurement campaigns (e.g. Chazette et al., 2001), the transportation of aerosols from distant sources is laminar, at well localized altitudes, therefore mixing rarely occurs between neighbouring layers. These aerosol layers persist for several days in the free troposphere, trapped in air masses which keep the thermodynamic signature of their origins. Table 1 also summarizes various properties of the aerosol layers identified as in Figure 3a. Overall, we notice a high aerosol load above the planetary boundary layer for most of the duration of the heat wave.

We will not go into the details of identification for each aerosol layer, but will focus on a few representative situations of the wide variety of particles present in the lower and middle troposphere
during both the heat wave and the post heat wave of 2015. In the lower layers, the air mass origins are quite conventional: from Southern to North-western France. Wind sectors are particularly variable during the period but with relatively low wind speeds, remaining mostly under 6 m s⁻¹. This is not the case at higher altitude with south-southwest wind sectors where there are more remote origins.

**1st July afternoon.** As given from MODIS observations (not shown), the AOTs throughout France, as in the Paris Area, are generally high, between 0.4 and 0.7 at the wavelength of 550 nm, matching the sunphotometer measurements for the same wavelength. At the beginning of the heat wave on 1st July, the aerosol plume, between 2 and 6 km amsl, seems to originate from Spain and Saharan according to 2-days back trajectories (not shown). The probable Spanish contribution may be from the Ebro Valley where MODIS-derived AOT is 0.4, which may be mixed with air masses of Saharan origin during the night of 1st-2nd July. Depolarizing particles (PDR ~ 10%) are observed during the day in the previous plume. They descend to lower altitude during the night of 1st-2nd July (Figure 3b), and reach the top of the nocturnal inversion layer located at ~0.7 km amsl. These Saharan air masses will affect the very low troposphere in the morning of 2nd July. In the lower troposphere, under 2.5 km amsl, back trajectories and lidar measurements indicate likely polluted aerosol from South France.

**2nd-3rd July.** As suggested by back trajectories, aerosol plumes at high altitudes may originate alternatively from remote sources within the North American continent and Southern Europe (Spain, Southern France), including the Sahara. During the night 2nd-3rd July, an aerosol plume from North America is located between 3 and 4.5 km amsl. It is not significantly depolarizing (PDR < 2.5%, Figure 3b) and it may have originated from strong forest fires occurring in Canada. Note that 10-days back trajectories are needed to reach the fire area highlighted from the MODIS operational product (not shown). The lower layer, located under ~3 km amsl on 2nd July is probably originating from the south of France. The wind veers on 3rd July and the aerosol contribution in the lower atmosphere (< ~1 km amsl) seems to originate from the industrial sites of Benelux and Germany. The MODIS-derived AOT on 3rd July is given in Figure 5c with the wind field at 950 hPa. The wind blows from
Eastern Europe with wind speed smaller than 2 ms⁻¹. CALIOP observation on 2nd July (night overpass) are difficult to interpret due to cloud cover over France, whereas the night time (~0300 UTC) and daytime (~1200 UTC) orbits on 3rd July are rich in information. A smoke plume is identified at ~4 km amsl from the night time orbit (not shown), which seems to confirm the North America biomass burning aerosol also sampled by our ground-based lidar. At latitudes larger than 48°, the aerosols from Germany are well identified in the lower troposphere from the daytime orbit presented in Figure 8. They show AECs higher than 0.13 km⁻¹ at 532 nm with PDRs larger than 20% (not shown). The CALIOP-derived aerosol classification is mainly dust, polluted dust and polluted continental or smoke (Table 1). Dust is also observed at ~4 km amsl, which may correspond to the Saharan air mass identified on 3rd July on Figure 3.

**4th July.** From the MODIS measurements, the larger AOT is encountered on Eastern France with values larger than 0.6 at 550 nm (not shown). The wind is from southwest at 650 hPa, transporting aerosol plumes from Spain, as confirmed by 2-days back trajectories. The lower aerosol layer is mainly originated from South France, and likely local. Pollution and dust aerosol layers are identified at ~4 km amsl from the night time CALIOP orbit (~0200 UTC) on 4th July for latitude higher than 52°, when passing over Benelux.

**5th-6th July.** It is the transition period between the heat wave and the post heat wave. The MODIS-derived AOT remains large on 5th July with values close to 0.5 all over France. The northwest part of France is cloudy. Like the sunphotometer-derived AOTs, the MODIS-derived AOT significantly decreases on 6th July to reach ~0.2 with a maximum around the Paris Area (~0.3). The aerosol plumes in the middle and lower troposphere are from South France.

**7th July at noon.** The plume observed between 2.1 and 4.7 km amsl on 7th July is identified as coming from North America after travelling over 8 days. It is most likely due to major forest fires that spread in Canada in the Northwest Territories, between the Great Bear Lake and Great Slave Lake. These fires developed between 28th and 30th June. The 10-days back trajectories plotted in Figure 7 illustrate the track of the aerosol plume observed over Paris on 7th July. In addition, the figure
shows two important observations by MODIS on 29th June that confirm the previous interpretation: dense forest fires (locations represented by red dots), and high AOTs (shown in colour). Strong AOTs, generally greater than 2 at 550 nm wavelength, allow a precise tracking of the biomass burning aerosol plume from its origin through its transport over the first 24 hours. Above the Paris Area, the maximum contribution of biomass burning plumes to the AOT at the lidar wavelength of 355 nm appears to be of the order of 0.1, i.e. ~20% of the total AOT. The transport of biomass burning plumes from North America was noted by various authors such as Formenti et al. (2002) and more recently by Ancellet et al. (2016). Note that the cloud cover prevents the use of CALIOP products directly above France on this date.

**9th July.** This is the last day of the post heat wave period. In the lower troposphere, the wind veers to the northeast carrying pollution aerosols from the northwest of France and United Kingdom (UK). As shown in Figure 5d, the MODIS-derived AOT significantly increases in northern France, reaching 0.7. The 10-days back trajectories identified a North America origin for the aerosol layer located between 4 and 7 km amsl. To increase the confidence in this inferred North-American transport, Figure 9 shows measurements during the night time orbit (~0200 UTC) of CALIOP, in which a smoke plume is identified between 5 and 7 km at latitudes close to 50° (Figure 9). The CALIOP-derived PDR is lower than 4% at 532 nm for AEC close to 0.13 km⁻¹ in the plume. The PDR of the same aerosol layer can reach 10% from our ground-based lidar during night time; whereas it is very patchy during daytime, likely due to an insufficient SNR in the upper aerosol layers. A Saharan dust contribution can be suspected because biomass burning aerosols cross the tropical Atlantic, but this is not clearly established. The aerosol type retrieved from CALIOP for the lower aerosol layer is polluted continental, in agreement with what was inferred from back trajectories.

Table 1: Characteristics of the aerosol plumes detected over Paris Area during the heat wave of July 2015. For each aerosol layer, the table gives the observation period, origin inferred from back trajectories (see text), altitude range, aerosol optical thickness (AOT), value of the linear particle depolarization ratio (PDR) and the aerosol classification from CALIOP.

<table><tr><td>Back trajectory</td><td>N<sub>2</sub>-Raman lidar</td><td>CALIOP</td></tr></table>
<table><thead><tr><th>Period (UTC)<br>(dd/mm hhmm)</th><th>Aerosol origin</th><th>Layer<br>altitude<br>amsl<br>(km)</th><th>AOT<br>at<br>355 nm</th><th>PDR<br>(%)</th><th>Aerosol<br>classification</th></tr></thead><tbody><tr><td>01/07 0330<br>to 02/07 1430</td><td>Spain<br>&amp; Sahara</td><td>~2.5 - 5.5</td><td>~0.25</td><td>~3.5 - 15</td><td>Polluted continental<br>or smoke</td></tr><tr><td>01/07 1000<br>to 02/07 0000</td><td>South France</td><td>~0.1 - 2.6</td><td>~0.25</td><td>~2</td><td>Polluted dust</td></tr><tr><td>02/07 1820<br>to 03/07 0345</td><td>North America</td><td>~3.0 - 4.5</td><td>~0.1</td><td>~2.5</td><td>Polluted continental<br>or smoke<br>Elevated smoke</td></tr><tr><td>02/07 1230<br>to 03/07 1330</td><td>Benelux/Germany</td><td>~0.1 - 3.0</td><td>~0.35</td><td>~1.5</td><td>Dust<br>Polluted dust<br>Polluted continental<br>or smoke</td></tr><tr><td>03/07 1800<br>to 04/07 0130</td><td>Sahara</td><td>~2.5 - 6.0</td><td>~0.15</td><td>~20</td><td>Dust<br>Polluted dust</td></tr><tr><td>04/07 0200<br>to 05/07 0400</td><td>Spain</td><td>~1.0 - 5.0</td><td>~0.2</td><td>~4-8</td><td>Polluted dust<br>Dust</td></tr><tr><td>04/07 0630<br>to 05/07 0100</td><td>Southwest France</td><td>~0.1 - 2.4</td><td>~0.25</td><td>~1.5</td><td>Out of the aerosol<br>plume or too cloudy</td></tr><tr><td>05/07 0730<br>to 06/07 0000</td><td>South France</td><td>~1 - 4.5</td><td>~0.23</td><td>~1.5</td><td>Out of the aerosol<br>plume or too cloudy</td></tr><tr><td>05/07 0730<br>to 09/07 0100</td><td>Local</td><td>~0.1 - 2.5</td><td>~0.22</td><td>~2.5</td><td>Out of the aerosol<br>plume or too cloudy</td></tr><tr><td>07/07 0800<br>to 07/07 1400</td><td>North America</td><td>~2.1 - 4.7</td><td>~0.07</td><td>~0.5</td><td>Out of the aerosol<br>plume or too cloudy</td></tr><tr><td>09/07 0430<br>to 09/07 2330</td><td>North America<br>&amp; Sahara</td><td>~4 - 6.5</td><td>~0.07</td><td>~6</td><td>Elevated smoke</td></tr><tr><td>09/07 0445<br>to 10/07 0000</td><td>UK<br>&amp; Northwest<br>France</td><td>~0.1 - 2</td><td>~0.1</td><td>~3.5</td><td>Polluted continental<br>or smoke</td></tr></tbody></table>
<figure><img src="image_16.png" /><figcaption>Figure 7: MODIS-derived fire locations (red dots) and aerosol optical thickness (AOT) at 550 nm (color scale of the lower left corner). The back trajectories over 10 days, calculated using HYSPLIT model in ensemble mode (24 back trajectories) are superimposed with the temporal color scale in the lower right corner. The back trajectories endpoint is at 3.5 km amsl following the lidar-derived vertical structure at 1200 UTC on 7th July 2015.</figcaption></figure>

<figure><img src="image_17.png" /></figure>
b)

<figure><img src="image_18.png" /><figcaption>Figure 8: CALIOP-derived a) aerosol extinction coefficient (AEC) at 532 nm and b) aerosol typing for the daytime (~1200 UTC) orbit on 3rd July 2015. The latitudinal location closest to the ground-based lidar is indicated by the vertical black line.</figcaption></figure>

a)

<figure><img src="image_19.png" /></figure>
b)

<figure><img src="image_20.png" /><figcaption>Figure 9: CALIOP-derived a) aerosol extinction coefficient (AEC) at 532 nm and b) aerosol typing for the night time (~0200 UTC) orbit on 9th July 2015. The latitudinal location closest to the ground-based lidar is indicated by the vertical black line.</figcaption></figure>

## 6 Impact on ground level air quality

Figures 1 b) and c) give a first insight on interactions between aerosol optical properties retrieved from ground-based sunphotometer and lidar, and surface concentrations of PM₁₀ and PM₂.₅ (http://www.airparif.asso.fr/, cf. section 2). We note that PM₁₀ and PM₂.₅ show similar temporal evolutions with a somewhat constant ratio PM₂.₅/ PM₁₀ close to 60% before 5th July. There is no marked correlation between air column aerosol content as represented by AOT, and mass concentrations at ground level. Also, factoring in lidar measurements of Figure 3, it seems very unlikely that surface concentrations are affected by upper aerosol layers. In Figure 10 we plot the correlation coefficient between the 300 m altitude layer and the rest of the atmospheric column sampled by the lidar. This calculation is performed on vertical profiles of aerosol extinction over the period of interest. We note a very fast decrease of correlation as a function of altitude. It falls below 0.5 at 1 km amsl and remains around 0.4 in advected aerosol layers between 2 and 5 km amsl. Figure 10 also shows the correlation distance for different altitude levels. That distance seldom exceeds 1 km. It is a little larger in advected aerosol layers as a function of their vertical spread.

From this, we can infer that during the heat wave of July 2015 there has not been systematic influence of long range aerosol transports on surface air quality, in contrast with the episode described
476 by Hodzic et al. (2007) during the 2003 heat wave. Ground-level pollution is not a good indicator of
477 the full aerosol load in the atmospheric column, better documented by the lidar and sunphotometer
478 which can constrain calculations of the radiative balance. Our results are in the line of the findings of
479 Toth et al. (2014), who have shown the inconsistencies between surface PM<sub>2.5</sub> and satellite-derived
480 AOT.

<figure><img src="image_21.png" /><figcaption>Figure 10: Vertical profile of the correlation coefficient $C_{1j}$ calculated from the reference altitude of 0.3 km amsl. Ground level is at ~0.1 km amsl. The vertical bars are the distance of correlation ($\Delta z_c$) for each altitude $z_k$ such as $C_{kj} > 0.5$, where j is the subscript for altitude $z_j \neq z_k$.</figcaption></figure>

481

482

483

484

485

# 7 Aerosol direct radiative forcing during heat waves

486 The high amount of aerosol advected over the Paris Area during the heat waves also induces
487 strong variations of the solar broadband fluxes. Sunphotometer measurements offer an interesting
488 opportunity to determine both the top and bottom instantaneous radiative forcing of atmospheric
489 aerosols (TOARF and BOARF, respectively). Hence, the heat waves can also be compared in terms
490 of the radiative forcing efficiency.

487

488

489

490
## 7.1 Aerosol radiative forcing for the heat wave of July 2015

Considering the values given for all the AERONET stations where data is available during the heat wave of July 2015, the TOARF is mostly between ~-5 and -30 Wm⁻² and the BOARF between ~-10 and -50 Wm⁻² (Figure 11a), for solar zenith angles between 55 and 75°. Indeed, only the solar aureole/sky radiances give access to a sufficient range of scattering angles to perform this calculation. There was no significant variability in the measurement against the solar zenith angle. Note that these ranges of aerosol radiative forcing do not take into account any measurements with AOT₃₅₅ (AOT₅₅₀) larger than 0.6 (0.45), which did occur, but in between sunphotometer samplings or during cirrus contamination (see Figure 1b).

Figure 11b shows the flux trapped in the aerosol layer against the AOT at 550 nm (difference between the TOARF and the BOARF). A linear relationship with a correlation coefficient of 0.7 is found, also highlighting a bias of 5 Wm⁻² which is likely to include the bias on both TOARF and BOARF. Hence, the mean radiative forcing by unit of AOT at 550 nm of aerosol (i.e. mean radiative forcing efficiency) above France during the 2015 heat wave is estimated to be close to +50±17 Wm⁻²/AOT₅₅₀ after removing the bias. Note that the flux trapped in the aerosol layers leads to a heating rate close to 1-2 K per day in the aerosol layers, favouring the stabilization of the lower troposphere and a reduction of the PBL height (e.g. Péré et al., 2011).

## 7.2 Aerosol radiative forcing for the heat waves of August 2003 and July 2006

The same type of calculation can be carried out for the heat waves of 2003 and 2006 with the available AERONET measurements. They are also shown in Figure 11b. Linear relationships are found with correlation coefficients of 0.7 and 0.8, respectively. The radiative forcing, ~+95±13 Wm⁻²/AOT₅₅₀ in August 2003 and ~+70±18 Wm⁻²/AOT₅₅₀ in July 2006, is higher than the one of the heat wave of July 2015. The standard deviations have been assessed using a Monte Carlo approach taking into account the uncertainties given by García et al. (2008) and an absolute error of 0.2 on the AOT (Dubovik and King, 2000). The differences are mainly due to the nature of aerosols implicated during the heat waves, whereas the AOTs are similar.
In 2003, the forest fires in Portugal injected large amounts of highly absorbent particles in the atmosphere above Western Europe (e.g. Lyamani et al., 2006), explaining the stronger radiative impact highlighted from sunphotometer-derived solar broadband fluxes. The difference on the mean radiative forcing efficiency between 2006 and 2015 is within the error bars and less relevant for discussion. It should be noted that these assessments are based on data acquired over the entire duration of the heat waves and the aerosol origins may change, as is particularly the case in 2015. The enhancement of air pollution at ground level during a heat wave may be a function of the radiative forcing amplitude (absorption of solar radiation by the aerosol plumes, via the heating rates) as well as of the vertical distribution of aerosols.

## 7.3 Complementary highlight from the SSA distribution

The previous conclusion can also be illustrated by the statistical distribution of the SSA over periods of heat waves. This parameter is not independent of the mean radiative forcing efficiency, which uses the measured SSA in its computation and is proportional to (1-SSA) at the first order. Nevertheless, histograms of SSA during the heat wave periods shown in Figure 12 clearly highlight the differences between the three heat waves. As expected, the mean SSA of 2003 (~0.9±0.03) is significantly lower than the ones of other heat waves: ~0.95±0.02 and ~0.93±0.04 for 2006 and 2015 heat waves, respectively. Nevertheless, the distribution is much more dispersed during the heat wave of 2015, which confirms the wide variety of aerosols advected over France during this period. The heat waves of 2006 and 2015 have similar mean SSA values, which does not make it possible to conclude with certainty on the relative importance of aerosol radiative forcing. The difference could lie in the temporal evolution of the aerosol contents and types within the atmospheric column.
a)

<figure><img src="image_22.png" /></figure>

b)

<figure><img src="image_23.png" /><figcaption>Figure 11: a) Temporal evolution of the sunphotometer-derived top of atmosphere and bottom of atmosphere radiative forcing ($\Phi_{TOA}$ and $\Phi_{BOA}$, respectively), direct radiative forcing of aerosols ($\Delta\Phi = \Phi_{TOA} - \Phi_{BOA}$) and aerosol optical thickness at 550 nm ($AOT_{550}$), during the heat wave and post heat wave of July 2015 (30th June – 10th July). b) $\Delta\Phi$ against $AOT_{550}$ approximated by a linear law with a correlation coefficient $r$ of 0.7, 0.8 and 0.7 for the heat waves of 2003, 2006 and 2015, respectively.
The equations are given in the figure. The data is obtained from the AERONET web site for all the available French stations.</figcaption></figure>
a)

<figure><img src="image_24.png" /></figure>

b)

<figure><img src="image_25.png" /></figure>

c)

<figure><img src="image_26.png" /></figure>
Figure 12: Statistical distribution of the single scattering albedo (SSA) over periods of heat waves: a) August 2003, b) July 2006, and c) July 2015. The probability density functions (PDFs) are also given.

## 8 Conclusive discussion

Comprehensive datasets from MODIS, CALIOP, AERONET, ECMWF reanalyses, and HYSPLIT backtrajectories have been used in conjunction with our own observations, to compare the heatwaves of 2003, 2006 and 2015 over Paris. Continuous ground-based lidar observations were processed to allow the identification of aerosol types over Paris in July 2015, together with HYSPLIT back trajectories to assess possible air mass origins. This represents the first such published lidar dataset during a heat wave in Western Europe. Even if the meteorological situations seem analogous between the first three heat waves experienced in France in the 21st century, there is evidence that the air masses advected over France, directly causing the phenomenon, carry different types of aerosols. The heat wave of July 2015 appears to be different in that aspect from the two previous ones in 2003 and 2006. Thermodynamic temperatures are similar on a more or less long duration, but the origins of aerosols are very different and highly variable along time. For the heat wave of July 2015, using the coupling between multiple back trajectories, MODIS and CALIOP operational products, AERONET sunphotometer, and ground based N₂-Raman lidar, aerosol plumes have been mainly shown here to originate from: i) Spain, North America, and Saharan (North Africa) for the upper level aerosol layers, and ii) South France, Germany, Benelux and United Kingdom for the lower level aerosol layers. In 2003 and 2006, the air mass histories have been established only using mesoscale transport models as in Hodzic et al. (2007) and Struzewska and Kaminski (2008), respectively. The aerosol load in August 2003 was mainly due to exceptional forest fires in Portugal and surface-level emissions (Hodzic et al., 2006; Lyamani et al., 2006). For the heat wave of July 2006, literature (Struzewska and Kaminski, 2008; Terrenoire and Fèvre-Nollet, 2008), confirmed by CALIOP-derived aerosol typing, reports the advection of hot and dry air from North Africa and north-easterly flow arriving over the North of France associated with likely polluted air masses.
The impact on local air quality also is different. In 2015, no significant mixing between the aerosol plumes due to long-range transport and the surface level pollution plumes from the UK and Germany/Bernelux are observed, and the PM₁₀ and PM₂.₅ in the Paris Area do not exceed the sanitary alert threshold. During the heat waves of 2003 and 2006, the particle pollution increased to overpass the threshold of 50 and 25 µg m⁻³ on non-traffic stations for PM₁₀ and PM₂.₅, respectively (see http://www.airparif.asso.fr). Incidentally, this conclusion raises the question of the representativeness of ground-level measurements to identify the cause of high AOT events when elevated aerosols are present.

Taking into account the aerosol load present during the heat wave of 2015, the direct aerosol radiative forcing has been assessed using the available measurements performed by the French stations of the AERONET network. The mean aerosol radiative forcing is assessed to be close to 50±17 Wm⁻²/AOT₅₀ for solar zenith angles between 55 and 75°. With such radiative flux trapped in aerosol layers, it may significantly increase temperature in the PBL (heating rate larger than 2 K per day), especially inside cities, aggravating the consequences of the heat wave on health and social conditions. When comparing with the two previous heat waves (95±13 and 70±18 Wm⁻²/AOT₅₀ for 2003 and 2006, respectively), the aerosol radiative forcing is lower in 2015, highlighting less absorbent particles. The August 2003 heat wave may have been worsened by the highly absorbent carbonaceous particle advected from Portugal forest fires throughout its duration.

## Acknowledgments

This work was supported by the Commissariat à l'Energie Atomique et aux énergies alternatives (CEA). The Centre National d'Etude Spatial (CNES) helped to maintain the Raman-lidar instrument. The authors would like to thank the AIRPARIF network for providing ground-level aerosol data (available at http://www.airparif.asso.fr/en/telechargement/telechargement-station), the AERONET network for sunphotometer products (at https://aeronet.gsfc.nasa.gov/). The authors acknowledge the MODIS Science, Processing and Data Support Teams for producing and providing MODIS data (at https://modis.gsfc.nasa.gov/data/dataprod/), and the NASA Langley Research Center Atmospheric Sciences Data Center for the data processing and distribution of CALIPSO products (level 4.10, at https://eosweb.larc.nasa.gov/HORDERBIN/HTML_Start.cgi). The NOAA Air Resources Laboratory (ARL) is acknowledged for the provision of the HYSPLIT transport and dispersion model and READY website (http://www ready.noaa.gov) used in this publication. ECMWF data used in this
602 study have been obtained from the ESPRI/IPSL data server. The authors also strongly acknowledge
603 Franco Marenco for its thoughtful and constructive comments on our manuscript.

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