ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus GmbHGöttingen, Germany10.5194/acp-15-2985-2015Two years of near real-time chemical composition of submicron aerosols
in the region of Paris using an Aerosol Chemical Speciation Monitor (ACSM)
and a multi-wavelength AethalometerPetitJ.-E.je.petit@air-lorraine.orghttps://orcid.org/0000-0003-1516-5927FavezO.SciareJ.CrennV.Sarda-EstèveR.BonnaireN.MočnikG.https://orcid.org/0000-0001-6379-2381DupontJ.-C.HaeffelinM.Leoz-GarziandiaE.Institut National de l'Environnement Industriel et des Risques,
Verneuil-en-Halatte, FranceLaboratoire des Sciences du Climat et de l'Environnement
(CNRS-CEA-UVSQ), CEA Orme des Merisiers, Gif-sur-Yvette, FranceAerosol d.o.o., Ljubljana, SloveniaLaboratoire de Météorologie Dynamique, Institut Pierre Simon
Laplace, Ecole Polytechnique, Palaiseau, Francenow at: Air Lorraine, 20 rue Pierre Simon Laplace 57000 Metz, FranceJ.-E. Petit (je.petit@air-lorraine.org)17March20151562985300522July201418September201419February201525February2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://www.atmos-chem-phys.net/15/2985/2015/acp-15-2985-2015.htmlThe full text article is available as a PDF file from https://www.atmos-chem-phys.net/15/2985/2015/acp-15-2985-2015.pdf
Aerosol mass spectrometer (AMS) measurements have been successfully used towards a better
understanding of non-refractory submicron (PM1) aerosol chemical
properties based on short-term campaigns. The recently developed Aerosol
Chemical Speciation Monitor (ACSM) has been designed to deliver quite similar
artifact-free chemical information but for low cost, and to perform robust
monitoring over long-term periods. When deployed in parallel with real-time
black carbon (BC) measurements, the combined data set allows for a
quasi-comprehensive description of the whole PM1 fraction in near real
time. Here we present 2-year long ACSM and BC data sets, between mid-2011 and
mid-2013, obtained at the French atmospheric SIRTA supersite that is
representative of background PM levels of the region of Paris. This large
data set shows intense and time-limited (a few hours) pollution events
observed during wintertime in the region of Paris, pointing to local
carbonaceous emissions (mainly combustion sources). A non-parametric wind
regression analysis was performed on this 2-year data set for the major
PM1 constituents (organic matter, nitrate, sulfate and source apportioned BC) and ammonia in order to better
refine their geographical origins and assess local/regional/advected
contributions whose information is mandatory for efficient mitigation strategies. While ammonium
sulfate typically shows a clear advected pattern, ammonium nitrate partially
displays a similar feature, but, less expectedly, it also exhibits a
significant contribution of regional and local emissions. The contribution of
regional background organic aerosols (OA) is
significant in spring and summer, while a more pronounced local origin is
evidenced during wintertime, whose pattern is also observed for BC
originating from domestic wood burning. Using time-resolved ACSM and BC
information, seasonally differentiated weekly diurnal profiles of these
constituents were investigated and helped to identify the main parameters
controlling their temporal variations (sources, meteorological parameters).
Finally, a careful investigation of all the major pollution episodes observed
over the region of Paris between 2011 and 2013 was performed and classified
in terms of chemical composition and the BC-to-sulfate ratio used here as a
proxy of the local/regional/advected contribution of PM. In conclusion, these
first 2-year quality-controlled measurements of ACSM clearly demonstrate
their great potential to monitor on a long-term basis aerosol sources and
their geographical origin and provide strategic information in near real time
during pollution episodes. They also support the capacity of the ACSM to be
proposed as a robust and credible alternative to filter-based sampling
techniques for long-term monitoring strategies.
Introduction
The understanding of the formation and fate of atmospheric
particulate pollution in urban areas represents sanitary, scientific,
economic, societal and political challenges, greatly amplified by increasing
media coverage of pollution episodes all around the world. Growing evidence
of adverse health effects of atmospheric pollutants (Chow et al., 2006; Pope
and Dockery, 2006; Ramgolam et al., 2009) is illustrated by the fact that ambient air pollution
has been characterized as carcinogenic since December 2013 by the
International Agency for Research on Cancer (IARC, 2013). However, the
“aerosol cocktail effect”, directly linked to the complexity of the
chemical composition and sources of the particulate phase, remains poorly
understood.
In an effort to fill these lacks of knowledge, worldwide coordinated
networking activities (such as Global Atmosphere Watch, European Monitoring
and Evaluation Programme, and AErosol RObotic NETwork) have been documenting,
for decades, the chemical, physical and optical properties of aerosol
pollution in various environments. At a European level, this effort is also
supported by the Aerosols, Clouds and Traces gases Research InfraStructure
network (ACTRIS) program that aims at pooling high-quality data from
state-of-the-art instrumentation such as the Aerosol Chemical Speciation
Monitor (ACSM, Aerodyne Research Inc., Billerica, MA, USA).
The ACSM has recently been developed with the aim of robust and easy-to-use
near real-time and artifact-free measurements of the major chemical
composition of non-refractory submicron aerosol (organic matter (OM),
NO3-, SO42-, NH4+ and Cl-) on a long-term basis
(Ng et al., 2011). In parallel, a growing interest is also dedicated
worldwide to the monitoring of black carbon (BC), considered as an adequate
indicator of potential anthropogenic emissions having sanitary impacts
(Janssen et al., 2011). In particular, the use of a seven-wavelength
Aethalometer (Magee Scientific, USA) allows furthermore for BC source
apportionment (Sandradewi et al., 2008), proven as robust over long-term
periods (Herich et al., 2011). The combination of measurements from both
instruments may thus constitute an efficient and relatively low-cost tool for
the monitoring of submicron aerosol chemistry and a better knowledge of their
phenomenology. Such a strategy may be particularly useful for documenting
aerosol sources and their geographical origin large urban areas that are characterized by a complex mixture of
gaseous and particulate pollutions. Paris (France) is one of the largest
European megacities and is rather isolated from other major urban
environments. With ∼ 11 million inhabitants, the Paris region accounts
for 20 % of the total French population distributed over only 2 % of
its territory, leading to enhanced exposure to various types of pollution.
Moreover, the flat orography of the Paris region favors pollution transport,
making it representative of northwestern European aerosol pollution.
Airparif, the regional air quality monitoring network, recently estimated
that, since 2007, about 2 million people per year have been exposed to poor
air quality (referring to the daily PM10 concentration for European
limit values; AIRPARIF, 2014) in this region. Over the past 7 years, annual
PM2.5 concentrations in Paris have remained quite stable, although no
continuous monitoring of the chemical composition of the particulate phase is
available to investigate any trends in the major sources of fine aerosols.
A recent research program, based on a 1-year (2009–2010) daily filter
sampling carried out at five various sites (traffic, urban, suburban and
regional backgrounds; Ghersi et al., 2010), was a unique opportunity to give
insight into the seasonal variations, sources and geographical origins of
aerosol pollution in the region of Paris (Bressi et al., 2013, 2014; Petetin et al., 2014). However,
long-term monitoring strategies based on the chemical analysis of aerosols
sampled on filters are subject to various sampling and analytical artifacts
(Appel et al., 1984; Turpin et al., 1994; Pathak et al., 2004; Cheng et al.,
2009) and assumptions (an OC-to-OM ratio, for instance): they involve laborious laboratory
analyses, they cannot capture processes governing diurnal variations of
atmospheric pollutants, and fail to provide rapid diagnostics during
pollution events.
In this context, Aerosol Mass Spectrometer (AMS) techniques have provided
extremely valuable information on the artifact-free real-time chemical
composition of submicron aerosols in urban areas over the past 10 years
(Zhang et al., 2004, 2007; Jimenez et al., 2009). In Europe, OM and ammonium
nitrate are generally the two main constituents of PM1 (Zhang et al.,
2007), showing, however, significant discrepancies during pollution episodes
in terms of chemical composition. Real-time AMS data have improved the
understanding of the physical and chemical (trans)formation pathways of both
fractions, through the characterization of pollution dynamics and source
apportionment analyses. Intensive field campaigns involving AMS measurements
were performed during the 2009 summer and 2010 winter seasons in the
framework of the European MEGAPOLI (Megacities: Emissions, urban, regional
and Global Atmospheric POLlution and climate effects, and Integrated tools
for assessment and mitigation) research program. They greatly improved the
understanding of the sources and transformation processes of Paris aerosols,
and especially their submicron organic fraction (Crippa et al.,
2013a, b and c; Freutel et al., 2013; Healy et al., 2012, 2013; Laborde et
al., 2013; Zhang et al., 2013). However, AMS techniques' cost, size and
intensive control requirements make them impractical for unattended
monitoring. Nevertheless, they may still represent the best strategy for
investigating specific trends in aerosol sources, especially in the context
of elevated and stable PM concentrations as observed over the region of Paris
during the past few years. From that perspective, the recently commercialized
ACSM may represent an interesting alternative and may ultimately represent
the best strategy to deploy for long-term monitoring of submicron aerosol
sources and geographical origins.
As part of the ACTRIS project, a new in situ atmospheric station was
implemented in 2011 at a background site of the region of Paris, allowing the
chemical, physical and optical characterization of submicron aerosol
pollution on a regional scale. The key aim of the present paper is to
describe and discuss one of the first long-term data sets obtained with the
ACSM, offering opportunities for the evaluation of the scientific relevance
of a new experimental strategy for long-term monitoring of near real-time
chemical composition of PM1. Seasonal trends, wind sector analysis,
diurnal variations and pollution episodes retrieved from 2-year real-time
measurement ACSM and BC data sets are presented and interpreted in order to
refine the origins and parameters controlling the (trans)formation of
particulate pollution over the region of Paris.
Material and methodsSampling site and instrumentation
Long-term in situ observations of the chemical, optical and physical
properties of atmospheric aerosols have been initiated at SIRTA (Site
Instrumental de Recherche par Télédétection Atmosphérique,
http://sirta.ipsl.fr) since June 2011 within the EU-FP7 ACTRIS
(Aerosols, Clouds, and Traces gases Research InfraStructure Network,
http://www.actris.net) program. Located 20 km southwest of Paris
(2.15∘ E, 48.71∘ N, 150 m above sea level) in a semi-rural
area, this atmospheric supersite is representative of the regional background
pollution over the region of Paris (Haeffelin et al., 2005; Crippa et al.,
2013a).
The chemical composition of non-refractory submicron aerosol has been
continuously monitored using a Quadripole Aerosol Chemical Speciation Monitor
(Aerodyne Research Inc.), which has been described in detail by Ng et
al. (2011). Briefly, PM2.5 aerosols are sampled at 3 L min-1
(from a PM2.5 cyclone inlet) and then sub-sampled at 85 mL min-1
(volumetric flow) through an aerodynamic lens, focusing submicron particles
(40–1000 nm aerodynamic diameter, A.D.) onto a 600 ∘C-heated
conical tungsten vaporizer where non-refractory material is flash-vaporized
and quasi-instantaneously ionized by electron impact at 70 eV. Fragments are
detected following their mass-to-charge ratio by a quadrupole mass
spectrometer. Briefly, the instrument calibration has been performed
following the recommendation of Jayne et al. (2000) and Ng et al. (2011),
where generated mono-disperse 300 nm A.D. ammonium nitrate particles are
injected into both ACSM and a condensation particle counter (CPC) at
different concentrations. Throughout the measuring period, three response
factor (RF) calibrations and one (NH4)2SO4 calibration were
performed, summarized in Table 1. The low drift of the obtained slopes
allowed the use of an average response factor of 2.72 × 10-11
(with a standard deviation of ±13 %), and relative ion
efficiencies (RIE) of 5.9, 1.2 and 1.4 for ammonium, sulfate and organic
matter, respectively, were used for the whole data set. Collection
efficiencies were corrected using algorithms proposed by Middlebrook et
al. (2012), and data were finally cross-validated using collocated PM1
as well as PM2.5 urban background measurements, retrieved from the
regional association of air quality monitoring (AIRPARIF,
http://www.airparif.asso.fr). The PM1 and PM2.5 data sets
were obtained using tapered element oscillating microbalances (TEOM) equipped
filter dynamic measurement systems (FDMS) as described by Grover (2005). A
comprehensive determination of the overall uncertainty (as well as PM1
components) associated with ACSM-derived measurements was carried out in
November 2013 through an inter-comparison exercise (Crenn et al., submitted;
Fröhlich et al., 2015). Here, the consistency of ACSM measurements has
been assessed from the comparison with co-located measurements, as described
in Sect. 3.
A total number of ∼ 26 000 ACSM data points (with a temporal
resolution of 30 min) were collected from June 2011 to June 2013 covering on
average 92 ± 9 % of each month over this 2-year period (it is to be
noted that September–October 2012 and February–March 2013 were not taken
into account within the latter calculation because the instrument was used
for short-term intensive campaigns at other locations).
Response factors obtained through IE calibrations from June 2011 to
May 2013.
Aerosol light absorption coefficients babs were retrieved every
5 min from a seven-wavelength (370, 470, 520, 590, 660, 880 and 950 nm)
AE31 Aethalometer from June 2011 to February 2013, and from a
seven-wavelength (370, 470, 520, 590, 660, 880 and 950 nm) AE33 Aethalometer
from February 2013 to May 2013. In both cases, instruments sampled aerosols
with a PM2.5 cut-off inlet, operating at 5 L min-1. Filter-based
absorption measurements need to be compensated for by multiple scattering in
the filter matrix and for loading effects, using mathematical algorithms
(Collaud Coen et al., 2010). While AE31 data were compensated for using the
corrections of Weingartner et al. (2003) as described in Sciare et
al. (2011), the use of the Dual-Spot
Technology® in the AE33 avoids the need for
manual post-processing to compensate the data (Drinovec et al., 2014). Both
instruments performed absorption measurements simultaneously during 7 days in
February 2013 (Fig. S1a in the Supplement). Absorption coefficients at
880 nm showed a slope of 0.93 and a very satisfactory r2 (0.96,
n= 3023 of 5 min data points). Black carbon concentrations for the whole
(2-year) data set were then calculated from the absorption coefficient at
880 nm, with a mass absorption cross section (MAC) of
8.8 m2 g-1 (Fig. S1b), determined from the comparison with
collocated filter measurements of elemental carbon (EUSAAR2 thermo-optical
protocol, Cavalli et al., 2010). This value is close to the default input
value implemented in the AE33 at 880 nm (7.77 m2 g-1). Although
still under discussion (Bond and Bergstrom, 2006; Cappa et al., 2012), such
relatively high MAC values might be related to a possible encapsulation of
soot particles by organic/inorganic compounds at our regional background
site, and to the presence of BC from wood-burning emissions during
wintertime, both leading to an increase in BC mass absorption efficiency
(Liousse et al., 1993; Bond and Bergstrom, 2006; Lack et al., 2008). A total
number of ∼ 280 000 BC data points (∼ 133 000 5 min points
from AE31 and ∼ 147 000 1 min points from AE33) were collected from
June 2011 to June 2013.
Ammonia measurements during selected periods (mainly during the spring,
winter and summer seasons) were carried out using an AiRRmonia (Mechatronics
Instruments BV, the Netherlands). Based on the conductimetric detection of
ammonium, gaseous ammonia is sampled at 1 L min-1 through a sampling
block equipped with an ammonia-permeable membrane; a water counter-flow
allows ammonia to solubilize in ammonium. A second purification step is
applied by adding 0.5 mM sodium hydroxide, leading to the detection of
ammonium in the detector block. The instrument has been calibrated regularly
using solutions of 0 and 500 ppb of ammonium. Two sets of sampling syringes
ensure a constant flow throughout the instrument, but also create a temporal
shift, estimated at 20 to 40 min by different studies (Cowen et al., 2004;
Zechmeister-Boltenstern, 2010). In our case, this shift was set at 30 min.
Pre-fired 47 mm diameter quartz filters were sampled in PM2.5 at the
same location using a low-volume (1 m3 h-1) sampler (Partisol
Plus, Thermo Environment) equipped with a volatile organic compound active
charcoal denuder. Four-hour filters and 24 h filters were discontinuously
sampled, respectively, from 10 February to 2 March 2012 and during the period
from August 2012 to April 2013. These filters were analyzed for their
water-soluble inorganic (anions and cations) and elemental/organic carbon
contents using, respectively, an ion chromatography and Sunset OC / EC
analyzer (EUSAAR2 thermal protocol), according to Sciare et al. (2008) and
Cavalli et al. (2010).
Finally, standard meteorological parameters (temperature, relative humidity,
wind speed and direction) were obtained from continuous measurements at Ecole
Polytechnique, located 4 km east of our station, with an A100R Campbell
Scientific cup anemometer for wind speed and a W200P weather vane for wind
direction, at 10 m above ground level (m a.g.l.). Additionally, the
boundary layer height (BLH) was derived from Pal et al. (2013) methodology.
The attribution of the BLH was processed in combining a diagnostic of the
surface stability from high-frequency sonic anemometer measurements and LIght
Detection and Ranging (LIDAR) attenuated backscatter gradients from aerosols
and clouds.
All measurements presented here are expressed in Coordinated Universal
Time (UTC). Seasons are differentiated upon seasonal equinoxes.
Urban background PM2.5 measurements
Within the framework of mandatory air quality monitoring, urban background
measurements are continuously being carried out in the region of Paris.
Hourly PM2.5 data from TEOM-FDMS measurements were retrieved from the
three stations representative of the Paris urban background (namely, Bobigny,
Gennevilliers and Vitry-sur-Seine). Data sets are available online upon
request at http://www.airparif.asso.fr.
Backtrajectories and non-parametric wind regression
To illustrate air mass origin during specific pollution episodes, 72 h
backtrajectories were calculated every 3 h from the PC-based version of
Hysplit (Draxler, 1999) with GDAS meteorological field data. Backtrajectories
were set to end at SIRTA coordinates (48.71∘ N, 2.21∘ E) at
100 m a.g.l.
Time series of the major 30 min non-refractory (top, concentrations
are aggregated) and 5 min refractory (bottom, concentrations are
dissociated) PM1 chemical constituents, and 5 min ammonia at SIRTA from
June 2011 to May 2013. The two large data gaps in October 2012 and March 2013
correspond to two field intensive campaigns during which the ACSM was
deployed elsewhere.
Non-parametric wind regression (NWR) is a smoothing algorithm (Henry et al.,
2009) to alternatively display pollution roses, and has already been
successfully applied to various atmospheric pollutants and pollution sources
(Yu et al., 2004; Pancras et al., 2011; Olson et al., 2012). The objective is
to estimate the concentration of a pollutant given any (θ, υ) couple (wind direction and speed, respectively), from measured wind speed
and direction, and concentration.
Eθ|ϑ=∑i=1NK1θ-Wiσ⋅K2ϑ-Yih⋅Ci∑i=1NK1θ-Wiσ⋅K2ϑ-Yih,
where E is the concentration estimate at a wind direction θ and
speed υ; Wi, Υi and Ci the wind direction,
speed and atmospheric concentrations, respectively, measured at ti;
σ and h the smoothing factors; and K1 and K2 two kernel
smoothing functions defined as
K1x=12π⋅e-0.5⋅x2,-∞<x<∞.K2x=0.75⋅1-x2,-1<x<1=0.
The choice of the two smoothing factors σ and h can be carried out
using statistical calculations, although its empirical determination stays
feasible, as the final interpretation should not be changed. Here, σ
and h were set to 7 and 1.5, similarly to Petit et al. (2014). Finally, the
equivalent of the wind rose is calculated from the probability density
fθ,ϑ=1Nσh⋅∑i=1NK1θ-WiσK2ϑ-Yih,
where N the is the total number of points.
Due to higher measurement uncertainties in wind direction at low speeds, data
associated with wind speeds lower than 1 m s-1 were discarded,
potentially inducing an underestimation of very local pollution events.
Source apportionment of carbonaceous aerosols
The measurement of aerosol absorption at multiple wavelengths is allowing for
BC source apportionment. Organic molecules, especially polycyclic aromatic
hydrocarbons and humic-like substances, strongly absorb in the UV and blue
parts of the light spectrum. Based on the fact that these compounds are
primarily related to biomass combustion, the deconvolution of BC into two
contributions, fuel fossil and wood burning (BCff and
BCwb, respectively), can be carried out (Sandradewi et al.,
2008). Such source apportionment has already been successfully performed
during intensive field campaigns as well as for long-term monitoring periods,
frequently enlightening the significant contribution of wood burning to
ambient BC concentrations during wintertime (Favez et al., 2009, 2010; Sciare
et al., 2011, Herich et al., 2011; Crippa et al. 2013a). Here, the 470 and
880 nm channels were used, with an absorption Ångström exponent of
2.1 and 1.0 for pure wood burning and traffic, respectively, similarly to
previous work focusing on the February–March 2012 period of the same data
set (Petit et al., 2014).
Scatterplot of chemically speciated ACSM measurements versus filter
analyses for nitrate, organic matter (compared to OC filter-based
measurements) and sulfate.
Mass closure exercise between daily averaged reconstructed PM1
(ACSM + BC) and measured PM1 by TEOM-FDMS.
The source apportionment of our organic aerosol data is not presented here,
although positive matrix factorization applied to the AMS or ACSM database is
an efficient tool for the identification of organic aerosol primary sources
and secondary formation processes (see, for instance, Lanz et al., 2007;
Jimenez et al., 2009; El Haddad et al., 2013; Carbone et al., 2013;
Bougiatioti et al., 2014; Petit et al. 2014). Such a work will be reported
elsewhere (Crenn et al., submitted), as important issues related to the
seasonal variation of specific organic aerosol factor profiles have to be
addressed in many details, with a lot of sensitivity tests that are beyond
the objectives of the present study.
Cross-validation of particulate chemical species concentrations
Figure 1 illustrates the temporal variations of chemical species
concentrations used for the present study from June 2011 to May 2013. This
extended duration highlights the robustness of used instruments, and in
particular the ACSM, which did not undergo any major failures over this
2-year period. The consistency of the concentrations of each chemical
constituent retrieved from the ACSM has been checked via comparisons with
filter measurements (Fig. 2) as well as a chemical mass closure of PM1
(Fig. 3).
ACSM nitrate is very consistent with filter measurements, the slope of the
linear regression being close to 1 (r2= 0.85, N= 147). No
overestimation of ACSM nitrate is observed at high concentrations, which
suggests the ability of the Middlebrook algorithm to properly correct our
ACSM collection efficiencies. Higher discrepancies are observed for sulfate.
This feature has already been mentioned in previous studies for ACSM (Ng et
al., 2011; Budisulistiorini et al., 2014) and AMS instruments (Takegawa et
al., 2005). This could be partly related to the size distribution of sulfate,
as fine (PM2.5) sulfate can partially be associated with submicron sea
salt and/or dust particles. Fine ammonium sulfate aerosols originating from
secondary processes and long-range transport (Sciare et al., 2010; Freutel et
al., 2013) may also present a larger size mode extending above 1 µm
and partially not sampled by the ACSM. A sulfate ion efficiency calibration
was also performed in May 2013 to investigate possible changes in RIE, but no
significant discrepancy from the default value of 1.2 was found.
The OM-to-OC ratio obtained from the comparison between ACSM and filter-based
measurements exhibits a mean value of approximately 1.5, which is lower than
the value recommended for urban areas (1.6 ± 0.2, Turpin and Lim, 2001)
and 33 % lower than and/or equal to values used in the Paris metropolitan
area in previous studies (∼ 2 in Bressi et al., 2013; 1.6 in Sciare et
al., 2010). Although this ratio is subject to caution, by virtue of potential
geographical and temporal discrepancies, the relatively low value observed
here might be explained by the presence of organic material between 1 and
2.5 µm as well as filter sampling artifacts.
A chemical mass closure exercise, where the combination of validated ACSM and
Aethalometer data is compared to co-located PM1 TEOM-FDMS measurements,
was used to assess the capacity of the two former instruments to correctly
describe the PM1 fraction over long-term periods. For this purpose, the
reconstructed PM1 (PMchem) introduced here corresponds to
the sum of all non-refractory species measured by the ACSM (OM, NO3-,
SO42-, NH4+ and Cl-) and black carbon measured by
Aethalometer, and is assumed to quasi-exhaustively account for submicron
aerosols (Putaud et al., 2004). PMchem daily averages were
compared to the TEOM-FDMS data set, since the latter instrument is considered
to be equivalent to the gravimetric reference method on this temporal scale.
From June 2011 to May 2013, the 341-point (this number being due to the
combined availability of ACSM, BC and PM data) scatterplot shows a very
satisfactory correlation coefficient (r2= 0.85) with a slope of 1.06.
Comparison between observed and average PM2.5, temperature,
hours of sunshine and accumulated rainfall in the region of Paris.
Average wind rose during June 2011 and June 2013; the radial axis
represents the wind occurrence (in %).
Representativeness of our 2-year observation period
Monthly mean atmospheric conditions were compared to standard meteorological
parameters in order to investigate any anomalies over the 2011–2013 period
(Fig. 4). Temperature, rainfall and sun exposure representative of the region
of Paris were retrieved from monthly weather reports available at
https://donneespubliques.meteofrance.fr, and are calculated from a
30-year period (1981–2010) (Arguez and Vose, 2011). A similar study was also
performed for particulate matter concentrations, with representative
PM2.5 defined as the average PM2.5 concentrations calculated from
2007 to 2014 at the three historical Airparif urban background stations.
Briefly, autumn 2011 was relatively mild, PM2.5 levels being close to
representative concentrations for the period. The end of winter 2011–2012
and early spring 2012 were particularly dry and sunny, enabling enhanced
photochemical transformation, and exhibited unusually high PM2.5
concentrations in February and March 2012. The summer of 2012 was chilly and
rainy, especially in June 2012, leading to lower PM2.5 levels (Yiou and
Cattiaux, 2013). Finally, the first two months of 2013 were unusually cold,
whereas March 2013 was remarkably representative of wintertime conditions.
The highest observed discrepancies occur with the highest measured mass,
which may highlight an intensification of pollution episodes. From a broader
perspective, this feature is also observed through inter-annual variability
of urban background PM2.5 concentrations (Fig. S2). This underlines the
need for continuous monitoring over several year periods. Interestingly, no
direct link can be drawn between meteorological anomalies and unusually high
PM2.5 concentrations. Indeed, while the high PM2.5 levels observed
in February and March 2012 may be linked to unusually low temperatures,
exceptionally high temperatures can also be associated with high PM2.5
concentrations. This has to be related to the seasonal variability of
sources, origins and (trans)formation pathways, and is investigated within
the following sections, taking advantage of long-term trend analysis, wind
regression, diurnal variations, and the analysis of pollution episodes.
Finally, it should be underlined that the Paris region is mostly influenced
by winds coming from the southwestern (Fig. 5) sector. This sector is
characterized by clean air masses from the Atlantic Ocean with high wind
speeds, and is usually associated with low PM concentrations. The
northeastern wind sector exhibits a smaller occurrence than previously
observed between September 2009 and September 2010 (Supplementary information
of Bressi et al., 2013).
(a) PM1 chemical composition for different mass
classes (top), with the seasonal occurrence frequency and number of points in
each bin (bottom) and (b) seasonal PM1 chemical composition.
Long-term trend and general features
Two-year temporal variations of the chemical composition of submicron
aerosols (OM, NO3-, SO42-, NH4+, Cl-,
BCff and BCwb) and ammonia (NH3) are presented
in Fig. 1. Similarly to Bressi et al. (2013), a clear seasonal pattern is
observed here, with the highest concentrations observed during winter and
early spring, while summer periods exhibit the lowest pollution levels
(Fig. 6a), which is also consistent with general patterns observed in
northern Europe (Barmpadimos et al., 2012; Waked et al., 2014). Regardless of
the season, OM dominates the PM1 chemical composition, followed by
ammonium nitrate, whose contribution is highest during spring, a feature that
is generally observed for European urban areas (Zhang et al., 2007; Putaud et
al., 2010). Figure 6b presents the binned major chemical composition and the
frequency per season of data points as a function of PM1 concentration
levels. The contribution of secondary inorganic aerosols (SIA, mostly
NO3-, SO42- and NH4+) increases with the increases in
PM1 mass until 50 µg m-3, highlighting the role of
inorganic secondary pollution during spring months (Fig. 6b). This
well-documented pattern that has already been reported for the region of
Paris in several studies (see, for instance, Sciare et al., 2010 and Bressi
et al., 2013). Very interestingly, above 50 µg m-3, organic
contribution, as well as wintertime frequency, increases to dominate the
chemical composition of the highest measured PM1 concentrations with an
associated increase in BC, a feature that has not been seen during the
Airparif–Particules projects, essentially due to highly time resolved
measurements, nor investigated during the MEGAPOLI project. There are
well-defined occurrences of high concentrations (∼ 150 data points of
30 min), suggesting sharp pollution events with a limited temporal duration,
contrary to the 20–50 µg m-3 mass class presenting many more
data points that highlight either a higher frequency of sharp events and/or
pollution episodes with a longer temporal duration.
Source contribution to BC, absorption Ångström exponent,
BC / SO4 ratio (ACSM sulfate), and contribution of BC to PM1,
depending on PM1 mass.
We have used here the BC / SO4 ratio to assess potential transport
of pollution. Sulfate mainly forms through heterogeneous processes with a
slow kinetic rate and spreads over large scales (Putaud et al., 2004). For
that reason, it can be considered as a good indicator of long-range transport
assuming minor local SO2 sources (background annual SO2
concentrations of about 2 µg m-3 in the region of Paris;
AIRPARIF, 2014). On the contrary, black carbon in the region of Paris shows
an important gradient from the city center to the regional background (Bressi
et al., 2013) and can be used to better infer local (Paris city) influence at
our background station. Although in situ sulfate formation may occur (for
instance, during fog episodes; Healy et al., 2012) and long-range transport
of BC may be observed over the region of Paris (Healy et al., 2012 and 2013),
as a whole, the use of the BC / SO4 ratio may support our study on
local/regional/advected pollution. As shown in Fig. 7, the BC / SO4
ratio decreases along with the increase in PM1 (and thus secondary ion
mass fraction), suggesting potential regional and/or trans-boundary
transport, and large-scale pollution episodes, as previously reported by
several studies in northern France (Bessagnet et al., 2005; Sciare et al.,
2010; Bressi et al., 2013; Waked et al., 2014; Freutel et al., 2013). Very
interestingly, this BC / SO4 ratio dramatically increases for the
highest concentrations, where the concomitant increases in the
Ångström exponent, of the contribution of BCwb relative
to BC, along with the increase in OM and wintertime frequency (Fig. 7),
suggest intense local and/or regional wood-burning pollution episodes during
winter. Moreover, except for the single wood-burning episode observed on 5
February 2012 (described in Petit et al., 2014), all these intense PM
pollution peaks (PM1 > 60 µg m-3) also
occurred at most of the rural/suburban/urban Airparif monitoring stations.
This pattern underlines homogeneous meteorological conditions over the region
of Paris, with “local” emissions being measured on a regional scale (within
a distance of at least 50 km from the city center).
Seasonality and insights into geographical origins
Figure 8 displays the wind regression analysis plots for
species of interest, namely, OM, NO3-, SO42-, NH3,
BCff and BCwb.
Overall, OM concentrations do not exhibit a particular dependence on wind
direction, the regional background always staying at a significant
contribution throughout seasons (∼ 3–6 µg m-3).
However, higher OM concentrations occurred in autumn and winter and are
associated with very low wind speeds, suggesting higher local influence
together with higher local wood-burning emissions (as previously suggested
from Figs. 6b and 7). During summer, OM concentrations are lower (by a factor
of ∼ 2.2) and show a more homogeneous distribution (e.g., with lower
local influences).
As expected, semi-volatile nitrate concentrations are higher during the
coldest months (in spring and winter). They are associated with relatively
high wind speeds (∼ 20 km h-1) coming from the northerly and
northeasterly directions, suggesting significant medium- to long-range
transport of ammonium nitrate during these seasons, which is consistent with
similar observations reported for the region of Paris (Bressi et al., 2013;
Freutel et al., 2013; Petetin et al., 2014). However, the significant nitrate
concentrations observed for all the range of wind speeds from the N–NE
direction suggest, at least for the lowest wind speed, a significant
contribution of the region of Paris. Possible impacts of industrial
activities in the Seine estuary (i.e., Rouen, Le Havre), especially during
spring, may also be responsible for the noticeable nitrate hotspot observed
in the northwestern sector. In autumn, nitrate concentrations are higher at
low wind speeds, in agreement with the fact that traffic emissions are
slightly higher in September and October than the rest of the year in Paris
(V-Trafic report, 2014), and that BCff concentrations are also
highest during these months. This is also consistent with a relatively fast
nitrate formation mechanism from local NOx emissions as reported
by Petetin et al. (2014).
Sulfate features different behavior than nitrate, where the non-local origin
is much more pronounced. High concentrations are associated with high wind
speeds originating from the NNE, leading to the same conclusions as those
reported in the literature on the major role of the long-range transport of
this compound (Pay et al., 2012; Bressi et al., 2014; Petetin et al., 2014;
Waked et al., 2014). Petrochemical and shipping activities may explain the
observed hotspot in the marine northwestern sector, especially noticeable in
spring, which may be linked to meteorological conditions enhancing ammonium
sulfate formation and transport.
The region of Brittany, located less than 300 km west of the region of
Paris, is the principal emitter of ammonia in France through intense
agricultural activities
(http://prtr.ec.europa.eu/DiffuseSourcesAir.aspx). However, no clear
contribution from this region is observed from our wind regression analysis.
This may be partly related to very few occurrences of air masses passing over
Brittany and reaching the region of Paris. Despite hotspots from the
northeast/east in spring, or from the north/northeast in winter, no clear
wind sector is directly responsible for high NH3 concentrations at our
station, suggesting a diffuse regional source for this compound.
In Europe, BCff is assumed to be an excellent tracer of traffic
emissions in urban areas (Herich et al., 2011, for instance). Although
long-range transported BCff may not be excluded, as shown by
Healy et al. (2012, 2013), here, wind regression analyses show that high
BCff concentrations occurred at low wind speeds, highlighting the
importance of local/regional traffic emissions in the Paris region,
especially during the autumn and winter seasons. In spring, a clear
distribution over a large range of wind speeds is noticeable in the NNE wind
sector. This is consistent with the fact that Paris is located NNE of our
station (e.g., a higher contribution of the Paris city plume to measured
BCff concentrations at SIRTA). This is also related to a higher
occurrence of this wind sector during spring.
Black carbon from biomass burning combustion (BCwb) presents a
clear seasonal trend similar to OM, with the highest concentrations during
cold seasons at low wind speeds, suggesting increasing local influence in
wood-burning emissions. The lowest boundary layer heights (BLHs) observed
during wintertime favoring the accumulation of pollutants at ground level
together with the large contribution of individual (domestic) wood-burning
sources homogeneously spread over the region of Paris may explain the
significant contribution of regional emissions observed during winter.
Finally, it should be noted that the geographical origin of each investigated
chemical constituent remains globally unchanged throughout the year, with a
well-defined sectorized location. While SIA and BCff fractions
are mainly associated with the NNE sector (coming from Paris and/or farther
away), the highest OM and BCwb concentrations exhibit strong
local NW and SE sector origins. Various sources of organic matter also
contribute to a significant contribution of the (unsectorized) regional
background.
Seasonal NWR plots for the major components of PM1 and gaseous
ammonia. Radial and tangential axes represent the wind direction and speed
(km h-1), respectively.
Average diurnal variations by seasons of temperature (a)
and BLH (b).
Weekly diurnal profiles and insight into sources and processes
Near real-time observations over long-term periods offer a unique opportunity
to provide robust diurnal profiles for each season. First, Fig. 9 shows the
average diurnal profiles of ambient temperatures (Fig. 9a) and BLH (Fig. 9b)
across seasons. Weekly diurnal profiles for OM, NO3-, NH4+,
NH3, BCff and BCwb are presented for different
seasons from hourly averages (Fig. 10). Sulfate variations are not presented
and discussed here because they lead to poor daily variations (average of
0.75 µg m-3± 2 %), which are consistent with its
mid- to long-range transport origin.
Seasonal weekly diurnal variations of OM (green), NO3-
(blue), NH4+ (dark yellow), NH3 (purple), BCff
(black) and BCwb (brown).
Clear weekly and diurnal patterns can be observed for carbonaceous aerosols.
Independently of the investigated season, BCff presents a
well-marked bimodal diurnal profile, with maxima in the morning (starting at
06:00 UTC) and the evening (starting at 17:00). This reflects the proximity
of the traffic source (with daily commuting) and dilution in the boundary
layer during daytime (Fig. 9b). With an average of
0.61 µg m-3, weekdays exhibit slightly higher concentrations
than weekends (0.51 µg m-3 on average). By comparison, the
diurnal variability of BCwb is revealed only in autumn and
winter, with the combination of enhanced wood-burning emissions, low
temperatures and BLH (Fig. 9), leading to a unimodal pattern with increasing
concentrations after 18:00 UTC. Although individual wood-burning stoves only
represent around 5 % of the means of heating in the region of Paris, they
contribute almost 90 % of PM10 residential emissions in the region
of Paris (Airparif emission inventory for the year 2010; Airparif, 2013) and
are likely to represent the major contributor to BCwb.
For OM, the highest variations (in terms of concentration amplitude) are
observed during autumn and winter, with a growing influence of wood-burning
heating, as OM concentrations nicely follow BCwb ones. Levels of
both compounds during the evening are approximately 20 % higher during
weekends than during weekdays. More specifically, low BLHs in winter (Fig.
9b) increase measured concentrations, leading, for example, to morning OM
peaks that should be linked to traffic emissions. By contrast, the diurnal
profile is rather flat, with poor temporal variations in summer, and is in
accordance with the homogeneous geographical distribution from the NWR
calculation for this season. The lack of a decrease in the afternoon during
weekdays suggests rapid formation of secondary organic aerosols (SOA) from
diverse anthropogenic (traffic for instance, as underlined by Platt et al.,
2013 and Nordin et al., 2013) and biogenic sources (Carlton et al., 2009).
During spring, OM globally follows the variations of nitrate, highlighting
fast displacements of gas-particle equilibriums of semi-volatile material due
to meteorological conditions. Some peaks are observed some days during the
night, which could underline the residual contribution of wood-burning
emissions in March and April.
Correlation between ammonia and temperature in spring (circles),
summer (squares) and winter (triangles) colored as a function of the hour of
the day.
For SIA, nitrate and ammonium display very similar diurnal and weekly
profiles, illustrating the importance of ammonium nitrate by comparison with
ammonium sulfate. Both compounds display well-marked diurnal profiles with
maxima at night (especially in autumn and winter) and/or early morning
(especially in spring and summer), which has to be related to the enhancement
of ammonium nitrate formation at low temperatures and/or high relative
humidity. The temporal variations of the two compounds can also be linked to
the one of ammonia. For instance, during summertime, ammonia presents
unimodal diurnal profiles, with the highest values around noon, and nicely
follows temperature (Fig. 9a), in good agreement with previous studies (Bari
et al., 2003; Lin et al., 2006). This phenomenon is exactly opposite to the
variations of ammonium and nitrate exhibiting unimodal patterns with the
highest concentrations during the night. Meteorological conditions can then
fully explain the formation/partitioning of SIA as well as ammonia
concentrations during summer.
Interestingly however, ammonia shows different profiles as a function of the
season. In particular, during springtime, this compound displays a clear
bimodal profile, with a morning and an evening peak, concomitant with traffic
emissions and that come over elevated regional background levels due to the
use of nitrogen-containing fertilizers in this period of the year. However,
this bimodal pattern is not observed during the summer and winter seasons,
where traffic also occurs. Although traffic-related ammonia has already been
reported in urban environments (Edgerton et al., 2007; Pandolfi et al., 2012;
Saylor et al., 2010) and several studies raise concerns about uncontrolled
ammonia emissions from De–NOx systems (Baum et al., 2001; Heeb
et al., 2006 and 2012, for instance), this spring bimodal profile may also be
related to parameters other than traffic emissions. Indeed, as already
described by Bussink et al. (1996), emission of ammonia can occur during the
evaporation of the morning dew, especially when soils are loaded with
fertilizers. The morning decrease observed for ammonia in spring can then be
associated with the growing of the mixing depth layer (Fig. 9b) while, in the
afternoon, ammonia increases may be partly explained by temperature-driven
gas-phase partitioning changes in ammonium nitrate.
PM1 pollution episodes over the region of Paris
An in-depth characterization of each pollution episode over the region of
Paris is particularly important in the context of mitigation policies, which
are usually taken on a local scale during these episodes. Such an
investigation should provide useful information regarding PM (trans)formation
processes and help to identify parameters influencing the temporality of
their chemical composition.
Statistical representativeness of pollution episodes (duration and intensity)
may be addressed using our long-term data sets. Based on our 2-year data set,
the highest 1 % of observed PM1 concentrations (q99∼ 49 µg m-3, representing around 200 data points of
30 min, i.e., approximately 100 h) mostly occur during February, April and
November, while persistent pollution episodes
(PM1 > 20 µg m-3 during at least 3
consecutive days) mostly occur in early spring. More interestingly, the
majority of the highest PM1 concentrations fall within these persistent
pollution episodes. As previously suggested from higher BC / SO4
ratios (Sect. 5 and Fig. 7), the highest PM1 concentration peaks are
associated with rather local emissions. This result clearly points to the
contribution of local/regional emissions during persistent pollution
episodes. A more detailed analysis (episode-by-episode) is performed in the
following to better characterize the local/regional versus advected PM
pollution during persistent pollution episodes.
Essential parameters describing the eight pollution episodes, such
as the start and end dates, average temperature and relative humidity,
fraction dominating the chemical composition (SIA stands for secondary
inorganic aerosols), BC-to-SO4 ratio and main geographical
contribution.
Episode no.Start–end dateTemp. (∘C)RH (%)Chemical compositionBC / SO4Geographical contribution119–24/11/20118.593OM3.56Regional205–13/02/2012-4.771OM then SIA0.91Strong local, then regional and advected329/02–03/03/20128.295SIA1.12Strong regional, low advected412–17/03/201210.778SIA0.95Advected and regional523–26/03/20121548SIA2.37Strong advected, low regional628–31/03/201212.362SIA1.42Strong advected and regional716–21/01/2012-393OM and SIA0.72Strong regional and advected801–08/04/20134.264SIA0.12Advected
PM1 chemical composition of the eight pollution episodes.
Eight persistent pollution episodes
(PM1 > 20 µg m-3 during at least 3
consecutive days) were detected between mid-2011 and mid-2013, and are
displayed in Table 2 and Figs. 12 and 13. Figure 12 shows the averaged
PM1 chemical composition (in µg m-3) for each episode,
chronologically numbered, from 1 to 8. Table 2 summarizes key information for
each episode. Figure 13 shows air mass origins, a wind rose and temporal
variations of the chemical composition of each episode. As a general pattern
for each episode, the chemical composition of PM1 is dominated by OM
and/or ammonium nitrate. Sulfate presents the highest variability
(concentration standard deviation of 53 % over all episodes) compared to
OM and nitrate (∼ 30 %), possibly suggesting various contributions
of advected pollution.
The following provides a thorough description of each episode.
Episode 1 (19–24 November 2011): while winds come from the NW and E sectors,
72 h backtrajectories originate from SSE and exhibit a recirculation over a
part of northern France. Moreover, along with the BC / SO4 ratio
(3.56; i.e., the highest of all episodes) and a low BLH with no significant
variations, the chemical composition is largely dominated by OM (60.8 %
of PM1), suggesting significant local influence. The contribution of
BCwb remains insignificant compared to BCff, which
could underline the accumulation in the atmosphere of fossil-fuelled
combustion sources (notably illustrated by the very low altitude of the air
masses ending on the 21 and 23 November).
Episode 2 (5–13 February 2012): this episode presents two distinct phases.
At the beginning, air masses come from the southeast, but originate from the
east at low altitudes, along with very low temperatures (below 0 ∘C
all day), high OM and BC concentrations and BC / SO4 ratios (average
of 22.6 and 0.6 µg m-3, and 2.7, respectively, from 5 to 8
February). This is related to an intense local wood-burning episode already
thoroughly described in Petit et al. (2014). Then, from 8 February, winds and
air masses originate from NNE, and secondary inorganic ions, especially
ammonium nitrate, dominate the chemical composition. The associated wind
speed may underline mid- to long-range transport, although the impact of the
Paris plume cannot be excluded here.
Episode 3 (29 February–3 March 2012): along with this pollution episode,
trajectories have rapidly changed in origin but have remained low in
altitude. The RH remained very high, reaching 100 % most of the time.
Very interestingly, concentrations dropped on 1 and 3 March during the
beginning of the day, coinciding with two stratus lowering fog events. These
two fog events occurred during the second half of the night, and evaporated
as the sun rose. The influence of fogs regarding the chemical transformation
of PM1 is notably highlighted by higher sulfate concentrations just
after the evaporation of the first fog (and also when trajectories flew over
the English Channel and Belgium), which could suggest transported SO2
and oxidation over the region of Paris enhanced by fast fog processing (Kai
et al., 2007; Rengarajan et al., 2011).
Episode 4 (12–17 March 2012): winds have originated from all directions (but
mostly from NNE), suggesting anticyclonic conditions. The first half of the
period exhibits a rather stable chemical composition (dominated by ammonium
nitrate) and clear diurnal variations of RH, T and BHL. Then, after 15
March, daily amplitudes of the following three meteorological parameters
increased: T reached 20 ∘C, RH 30 % and BHL 1000 m, compared
to the first half, where they reached 15 ∘C, 50 % and 600 m,
respectively. This caused rapid decreases in concentrations, due to higher
temperature amplitudes, enhancing the gas partitioning of semi-volatile
material, and an increase in BLH, allowing the dilution of atmospheric
pollutants.
Episode 5 (23 March 2012–26 March 2013): air masses originated from the
northeast to the east, and winds from the north to the northeast. This
episode is characterized by the strong diurnal variation of OM and ammonium
nitrate, due the high amplitude of the BLH and temperatures going above
15 ∘C, similarly to the previous episode. The high average
BC / SO4 ratio (2.37) is not representative of its temporality; the
highest values are observed for lowest PM concentrations (26 March,
afternoon). With this exception, low BC / SO4 values (< 1)
and the chemical composition dominated by ammonium nitrate suggest mid-
and/or long-range transport.
Episode 6 (28–31 March 2012): it exhibits the same behavior as episode 5,
with a clear medium- to long-range origin pattern (wind speed
∼ 10 km h-1, chemical composition dominated by ammonium
nitrate), but with backtrajectories coming from the northwest/northeast. Low
altitudes of backtrajectories illustrate the accumulation of pollutants along
the trajectory of the air masses. However, the BC peak on the morning of 30
March (the high BCff fraction suggests traffic emissions) could
underline an influence of the Paris plume.
Episode 7 (16–21 January 2013): air masses display a coiling pattern around
northern France. The BC / SO4 ratio, remaining lower than 1,
suggests advected pollution. However, the strong variability of
BCwb illustrates a significant influence of wood-burning
emissions. No BHL data are available during this episode, but the altitude of
backtrajectories may underline a more important dilution of the pollution.
Episode 8 (1–8 April 2013): this episode actually started on 22 March, but
no ACSM data were available at that time; however, meteorological conditions
from 22 March to 1 April were very similar, notably in terms of wind speeds
and direction. It is characterized by air masses originating from the
northeast and a very low BC / SO4 ratio, illustrating a typical case
of advected secondary pollution clearly dominated by ammonium nitrate and
sulfate.
Overall, the observed variability, in terms of meteorological conditions, air
mass origins, and chemical composition illustrates the variety of persistent
pollution episodes, in terms of PM sources and different geographical
origins. The BC / SO4 ratio has been shown to represent a useful
tool for assessing the local/regional/advected dimension of a specific
pollution episode. Indeed, high ratios (≥ 2) are usually associated
with accumulation of local and/or regional emissions, while very low ratios
(≤ 0.5) are more representative of secondary advected pollutants.
Ratios within this range should then be associated with a combined influence
of regional and advected pollution. Finally, artifact-free ACSM data have
been shown to be adequate for documenting semi-volatile aerosols (ammonium
nitrate and a fraction of OM), which strongly contribute to PM1 during
persistent pollution episodes, and real-time measurements allow one to
illustrate the close interactions between the chemical composition and
meteorological parameters influencing its temporality.
Conclusions
The chemical composition of submicron (PM1) aerosols was continuously
monitored in near real time at a regional background site of the region of
Paris between June 2011 and May 2013 using a combination of an ACSM and an
Aethalometer. The obtained 2-year data set allows an appraisal of the
robustness of ACSM measurements over several month periods, as well as
Aethalometer measurements and BC source apportionment.
Illustration of meteorological conditions and chemical composition
during the eight pollution episodes. Left graphs represent 72 h
backtrajectories ending at SIRTA at 100 m a.g.l. every 3 h and their
altitude; middle graphs illustrate the wind rose (radial axis in
km h-1); right graphs represent the chemical composition, in
µg m-3 of submicron particles (organic, nitrate, sulfate,
ammonium, chloride and black carbon in green, blue, red, orange, pink and
dark grey, respectively), the contribution of traffic and wood burning to BC,
the BC / SO42- ratio, and temperature, RH and BLH.
Non-parametric wind regression calculations have been performed for each
season and provided useful information regarding the geographical origin of
PM1 chemical constituents. SIA, in particular ammonium sulfate, show a
clear advected pattern, leading to a uniform signal over large scales.
Ammonium nitrate also exhibits a significant contribution of regional and
local emissions. The highest concentrations of OM were identified as having a
major local origin, while regional background OM concentrations remain
significant, especially in spring and summer. The region of Brittany (western
France), the major hotspot of ammonia in France, seems to have little
influence on the concentrations of this species at our station in the region
of Paris; overall regional background concentrations of ammonia dominate,
especially in spring. Similarly to OM, wintertime BCwb
concentrations are mainly from local emissions from domestic heating,
although a noticeable regional background is still observed for this tracer
of wood burning. As expected, BCff shows a clear local (nearby)
origin, as well as a contribution from the Paris city plume, and remains
fairly constant throughout seasons, due to its regional traffic origin.
Such near real-time observations over long-term periods offer a unique
opportunity to provide robust diurnal profiles for each season. For instance,
diurnal profiles of semi-volatile nitrate aerosols were observed in different
seasons with temperatures favoring its partitioning into the particulate
phase in the morning and in the gas phase in the afternoon. No clear
contribution of traffic could be proven regarding ammonia variability, and
the regional background seems to prevail.
All the persistent pollution episodes
(PM1 > 20 µg m-3 during at least 3
consecutive days) that occurred between 2011 and 2013 were carefully examined
showing different meteorological conditions, sources and geographical
origins, making it difficult to draw general rules for these episodes. The
BC / SO4 ratio was used here to better separate local, regional (BC
dominated) and advected (SO4 dominated) contributions, and showed that,
with very few exceptions, most of these persistent episodes were dominated by
medium- to long-range transported pollution. However, it is interesting to
note that the majority of the highest (time-limited) PM1 concentrations
(30 min ACSM data points with
PM1 > 50 µg m-3) fell within these
persistent pollution episodes and were characterized by a significant
local/regional contribution (high BC / SO4 ratios). This result,
obtained with real-time measurements, may offer new perspectives in the
definition and the evaluation of the effectiveness of local mitigation
policies such as emergency measures (traffic or wood-burning restrictions,
for instance) taken to improve air quality during pollution events. In
parallel, the long-term characterization of the organic fraction would surely
lead to a better assessment of aerosol sources and some (trans)formation
processes of secondary pollution in the Ile-de-France area.
In conclusion, these first 2-year quality-controlled measurements of ACSM
clearly demonstrate their great potential to monitor on a long-term basis
aerosol sources and their geographical origin, and provide strategic
information in near real time during pollution episodes. They also support
the capacity of the ACSM to be proposed as a robust and credible alternative
to filter-based sampling techniques for long-term monitoring strategies. The
networking of such instrumentation (ACSM and BC) throughout Europe – as is
currently being built up within the European ACTRIS program – will certainly
offer tremendous opportunities for modeling studies in order to improve
prevision models, as well as large-scale spatially and temporally resolved
source apportionment studies of organic aerosols using the high potential of
ACSM organic fragments.
The Supplement related to this article is available online at doi:10.5194/acp-15-2985-2015-supplement.
Acknowledgements
The research leading to these results has received funding from INERIS, CNRS,
CEA, the French SOERE-ORAURE network, the European Union Seventh Framework
Program (FP7/2007–2013) project ACTRIS under grant agreement no. 262254, the
DIM-R2DS program for the funding of the ACSM equipment, and the
PRIMEQUAL-PREQUALIF and ADEME-REBECCA programs for the long-term observations
of black carbon at SIRTA. Edited by: J. Allan
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