Ari Setyan
email: ari.setyan@gmail.com

Pascal Flament
email: pascal.flament@univ-littoral.fr

Nadine Locoge

Karine Deboudt

Véronique Riffault

Laurent Y Alleman

Coralie Schoemaecker

Jovanna Arndt

Patrick Augustin

Robert M Healy

John C Wenger

Fabrice Cazier

Hervé Delbarre

Dorothée Dewaele

Pascale Dewalle

Marc Fourmentin

Paul Genevray

Cyril Gengembre

Thierry Leonardis

Hélène Marris

Saliou Mbengue

Prof Pascal Flament

Investigation on the near-field evolution of industrial plumes from metalworking activities

Keywords:

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Epidemiological studies have demonstrated that exposure to atmospheric pollution has adverse effects on human health, such as cardiovascular [START_REF] Brook | Air pollution and cardiovascular disease -A statement for healthcare professionals from the expert panel on population and prevention science of the American Heart Association[END_REF] and pulmonary [START_REF] Oberdörster | Pulmonary effects of inhaled ultrafine particles[END_REF] diseases and cancer [START_REF] Pope | Lung Cancer and Cardiovascular Disease Mortality Associated with Ambient Air Pollution and Cigarette Smoke: Shape of the Exposure-Response Relationships[END_REF]. In particular, particles smaller than 2.5 µm (PM 2.5 ) are more dangerous than coarse ones (PM 2.5-10 ), because the former can penetrate deeper into the lungs, reach the alveoli and enter the cardiovascular system [START_REF] Kelly | Air pollution and airway disease[END_REF]. According to the Clean Air for Europe (CAFE, see Table S1 in the supplementary material for acronyms) program, the average decrease of life expectancy in Europe due to exposure to PM 2.5 is nine months, but increases to 12-36 months in Benelux and in the north-east area of France (2005). However, many uncertainties still remain on the identity of chemicals in the particle phase, their mixing state (which may lead to synergy in terms of toxicity) and source inventories for fine particles bearing toxic chemicals.

Previous studies have shown that industrial activities release large quantities of both gaseous and particulate matter into the atmosphere. The physico-chemical nature of particles emitted by industry has already been reviewed [START_REF] Riffault | Fine and ultrafine particles in the vicinity of industrial activities: A review[END_REF][START_REF] Sanderson | A review of chemical and physical characterisation of atmospheric metallic nanoparticles[END_REF][START_REF] Taiwo | A review of receptor modelling of industrially emitted particulate matter[END_REF]. A high variability of chemical composition and size distribution can be observed depending on the type of industrial processes involved. Nevertheless, tracers of specific industrial activities, such as heavy metals [START_REF] Dall'osto | A Study of the Size Distributions and the Chemical Characterization of Airborne Particles in the Vicinity of a Large Integrated Steelworks[END_REF][START_REF] Wong | In-stack and in-plume characterization of particulate metals emitted from a copper smelter[END_REF][START_REF] Yang | Characterization of PM10 surrounding a cement plant with integrated facilities for co-processing of hazardous wastes[END_REF], the organic-to-elemental carbon ratio (OC/EC) [START_REF] Chow | PM2.5 source profiles for black and organic carbon emission inventories[END_REF], diagnostic ratios or concentrations of some specific polycyclic aromatic hydrocarbons (PAHs) [START_REF] Katsoyiannis | PAH Molecular Diagnostic Ratios Applied to Atmospheric Sources: A Critical Evaluation Using Two Decades of Source Inventory and Air Concentration Data from the UK[END_REF][START_REF] Leoni | Source Impact Determination using Airborne and Ground Measurements of Industrial Plumes[END_REF], secondary inorganic species such as ammonium sulfate, nitrate, and chloride [START_REF] Setyan | Very low emissions of airborne particulate pollutants measured from two municipal solid waste incineration plants in Switzerland[END_REF][START_REF] Wu | Responses of secondary aerosols to relative humidity and photochemical activities in an industrialized environment during late winter[END_REF], and the carbon preference index (CPI, defined as the ratio of the sum of odd carbon number of n-alkanes to the sum of even carbon number of n-alkanes) [START_REF] Fraser | Molecular composition of organic fine particulate matter in Houston, TX[END_REF][START_REF] Li | Distributions and sources of n-alkanes in PM2.5 at urban, industrial and coastal sites in Tianjin, China[END_REF] have been identified as a means by which to provide estimates of the relative contribution of pollutant sources from heavily industrialized regions. Many industrial activities emit a range of PAHs, volatile organic compounds (VOCs) and inorganic gases including NO x and SO 2 . For instance, selected industrial processes in steelworks, such as coke production, iron ore sintering [START_REF] Ciaparra | Characterisation of volatile organic compounds and polycyclic aromatic hydrocarbons in the ambient air of steelworks[END_REF], and electric arc furnaces [START_REF] Baraniecka | Emission of polycyclic aromatic hydrocarbons from selected processes in steelworks[END_REF], release large amounts of PAHs. Coke ovens, commonly used in steelworks, also emit significant concentrations of VOCs [START_REF] Lin | Fugitive Coke Oven Gas Emission Profile by Continuous Line Averaged Open-Path Fourier Transform Infrared Monitoring[END_REF].

In this context, our NANO-INDUS project had two main objectives: 1) to produce new data on PM 2.5 , carbonaceous particles, heavy-metal concentrations and trace gases released by metalworking activities; and 2) to provide new information on the chemical composition, mixing state and source identification of industrial atmospheric particulate matter.

In terms of atmospheric processes, NANO-INDUS was motivated by three inter-related questions:

1) How much do the physico-chemical characteristics of atmospheric fine particles at the boundary of a metalworking industrial complex differ from those directly emitted from the stacks?

2) Is there a link between the presence of fine particles at the boundary of this site and gases directly emitted from the stacks?

3) Do fine particles within a metalworking plume have a homogeneous chemical composition as essentially primary particles, or are they produced or evolving by condensation and/or agglomeration, leading to secondary particles with heterogeneous compositions?

To help address these questions, a field campaign was conducted at an industrial site close to the Dunkirk metropolitan area (Grande-Synthe). This region is highly industrialized and the particle concentrations regularly exceed the World Health Organization annual mean guideline value of 10 µg m -3 for PM 2.5 (World Health Organization, 2006). Of particular interest is the industrial area of Grande-Synthe, which is comprised of various industries (steel industry, metallurgy, smelting works, chemical industry, refineries, food-processing industry, power production, cement works) (DREAL, 2011) located 7 km from downtown Dunkirk.

Following the diversity of industrial activities at this location, Grande-Synthe is very similar to many other industrial areas throughout the world, where industrial emissions had also been studied in previous publications, e.g. at Port Talbot (United Kingdom) [START_REF] Dall'osto | A Study of the Size Distributions and the Chemical Characterization of Airborne Particles in the Vicinity of a Large Integrated Steelworks[END_REF], Taranto (Italy) [START_REF] Amodio | Monitoring of the Deposition of PAHs and Metals Produced by a Steel Plant in Taranto (Italy)[END_REF], and Hangzhou in the Yangtze River Delta (China) [START_REF] Dai | Characterization and Source Identification of Heavy Metals in Ambient PM10 and PM2.5 in an Integrated Iron and Steel Industry Zone Compared with a Background Site[END_REF]. Previous studies have also been performed within the industrial park of Grande-Synthe [START_REF] Cazier | Characterisation and seasonal variations of particles in the atmosphere of rural, urban and industrial areas: Organic compounds[END_REF][START_REF] Crenn | Fine particles sampled at an urban background site and an industrialized coastal site in Northern France -Part 1: Seasonal variations and chemical characterization[END_REF][START_REF] Mbengue | Bioaccessibility of trace elements in fine and ultrafine atmospheric particles in an industrial environment[END_REF]. Particulate metal content has been extensively studied, due to the importance of steelworks and metallurgy at Grande-Synthe [START_REF] Alleman | PM10 metal concentrations and source identification using positive matrix factorization and wind sectoring in a French industrial zone[END_REF][START_REF] Arndt | Scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX) and aerosol time-of-flight mass spectrometry (ATOFMS) single particle analysis of metallurgy plant emissions[END_REF][START_REF] Flament | Iron isotopic fractionation in industrial emissions and urban aerosols[END_REF][START_REF] Hleis | Chemical profile identification of fugitive and confined particle emissions from an integrated iron and steelmaking plant[END_REF][START_REF] Kfoury | PM2.5 source apportionment in a French urban coastal site under steelworks emission influences using constrained non-negative matrix factorization receptor model[END_REF][START_REF] Landkocz | Fine and ultrafine atmospheric particulate matter at a multi-influenced urban site: Physicochemical characterization, mutagenicity and cytotoxicity[END_REF][START_REF] Marris | Fast changes in chemical composition and size distribution of fine particles during the near-field transport of industrial plumes[END_REF][START_REF] Marris | Fe and Mn Oxidation States by TEM-EELS in Fine-Particle Emissions from a Fe-Mn Alloy Making Plant[END_REF][START_REF] Mbengue | Size-distributed metallic elements in submicronic and ultrafine atmospheric particles from urban and industrial areas in northern France[END_REF][START_REF] Mbengue | Metal-bearing fine particle sources in a coastal industrialized environment[END_REF][START_REF] Santos | Estimating airborne heavy metal concentrations in Dunkerque (northern France)[END_REF]. A number of elements or elemental ratios have been used as tracers for specific sources within the industrial area, e.g. Mn or Mn/Fe ratio for emissions from the ferromanganese alloy factory [START_REF] Marris | Fast changes in chemical composition and size distribution of fine particles during the near-field transport of industrial plumes[END_REF], Pb and Fe isotopes for steelworks emissions [START_REF] Flament | Iron isotopic fractionation in industrial emissions and urban aerosols[END_REF], V and Ni for petrochemistry [START_REF] Alleman | PM10 metal concentrations and source identification using positive matrix factorization and wind sectoring in a French industrial zone[END_REF], Fe, Ca, Al and Mn for selected iron and steel processes such as sintering, blast furnace, steelmaking and desulfurization slag processing [START_REF] Hleis | Chemical profile identification of fugitive and confined particle emissions from an integrated iron and steelmaking plant[END_REF]. A few studies have also focused on the measurement of VOCs in this area. For instance, Badol et al (Badol et al., 2008a;Badol et al., 2008b) identified specific industrial activities as important sources of benzene (metallurgical, steel industries), octane (lubricant storage), pentane (hydrocarbon storage), and propene (hydrocarbon cracking). Roukos et al. (2009) measured BTEX (benzene, toluene, ethylbenzene, xylene) during two contrasting seasons. In winter, BTEX concentrations were mainly due to local pollution, while in summer, they decreased because of photochemical activity and the influence of continental aged air masses, highlighting the fact that even in anthropogenically-influenced areas, longrange transport can have a significant contribution to the observed concentrations. Finally, [START_REF] Xiang | Development of a methodology examining the behaviours of VOCs source apportionment with micro-meteorology analysis in an urban and industrial area[END_REF] emphasized the influence of vertical turbulence on the dispersion of VOCs at the local scale.

The aim of the present paper is to give an overview of the measurements performed during the NANO-INDUS project, and to present the main findings of this study. First, we will present results obtained during the intensive field campaign performed at the near-field sampling site, and those obtained during the samplings at the stacks. Then, physico-chemical characteristics of particles measured when the near-field sampling site was impacted by plumes from the Fe-Mn plant will be compared to particles measured during periods from other influences (petrochemistry, urban emissions).

Experimental

Sampling site

All sampling and measurements took place next to the site of a ferromanganese alloy manufacturing facility (Fe-Mn plant), located in the industrial area of Grande-Synthe, ~2 km west of the Dunkirk metropolitan area and ~7 km from the city center (51° 01' 44" north, 2° 16' 10" east, 10 m above sea level). Figure 1a shows a map of the area with the sampling site located centrally within the industrial zone of Grande-Synthe and ~800 m southwest of the emission chimneys in the Fe-Mn plant.

Atmospheric composition at the sampling site can be influenced by a variety of different emission sources, depending on the wind direction. Pollutant sources to the east of the sampling site are mainly industrial in origin due to the presence of a large steelworks (< 1 km), but also urban-influenced due to Fort-Mardyck (3'600 inhabitants, ~2 km from the sampling site) and Dunkirk (93'000 inhabitants, ~7 km from the site). The North Sea is only 1 km to the north and northwest, bringing marine and ship emissions to the site. Approximately 200 m to the north of the site is an outdoor storage area for manganese ores which is a potential source of dust during windy periods. Finally, pollutant sources to the west (petrochemistry, glass production) and southwest (refineries) of the site also mainly originate from industrial activities.

The Fe-Mn plant receives iron-enriched manganese ores by boat, and transforms these ores into a ferromanganese alloy, which is used in steelworks to improve the mechanical properties of steel. Figure 2 shows a schematic drawing of the production process. In the first step, manganese ores are sintered with anthracite and calcite (CaCO 3 ) in an oven. This step involves heating of the sinter, followed by cooling. In the second step, the manganese ore included in the sinter is reduced into metallic Mn in an electric arc furnace, which provides the necessary energy for the redox reaction. The third and last step consists of crushing the alloy to obtain the final product. Particles and gases emitted during these steps are collected in three different chimneys, in which they are treated by filters before their release into the atmosphere. Two of these chimneys are located in the sintering unit, above the firing and the cooling areas, respectively, while the third chimney is in the smelting unit. The sintering unit works 24 hours a day with particles and gases continuously emitted from its two chimneys.

Emissions from the smelting unit, where electrochemical reduction of the manganese ore and casting of the final product takes place, occur about once every six hours.

Instrumentation

The field campaign took place between May 15 and June 12, 2012. The complete list of instruments deployed during this field campaign is given in Table S2. Local meteorological parameters were measured using a weather station (Davis Instruments, Hayward, CA; model Vantage Pro 2) and a sonic anemometer (METEK GmbH, Elmshorn, Germany; model USA-1). A Doppler sonic detection and ranging (SODAR; Remtech, Vélizy, France; model PA2) instrument was used to determine turbulence and vertical profiles of the wind components. An aerosol light detection and ranging (LIDAR; Raymetrics S.A., Paiania, Greece) instrument was installed near the sampling site (Figure 1b). Every 15 minutes, the LIDAR scanned in four different directions, and the backscattered light was used to determine the particle abundance as a function of the altitude and the distance from the instrument.

A large suite of instruments was set up to characterize the concentration, chemical composition and size distribution of particles with a high time resolution (~5 minutes). These instruments were connected to a common isokinetic particle sampler (Alfaro et al., 2003) operated at 52 m 3 hr -1 , 7 m above ground level. The Particle Loss Calculator (von der Weiden et al., 2009) was used to calculate particle loss across the sampler (Figure S1 in the supplementary material). The cut-off size of the sampling line was 2.5 µm (PM 2.5 ), assuming an average particle density of 2.5 g cm -3 based on the measured chemical composition. This high particle density is due to the fact that the sampling site was impacted by a high fraction of sea salts, metal oxide particles (Fe, Mn, Al), and CaCO 3 (see Section 4.1). A highresolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS; Aerodyne Research Inc., Billerica, MA) [START_REF] Canagaratna | Chemical and microphysical characterization of ambient aerosols with the Aerodyne aerosol mass spectrometer[END_REF][START_REF] Decarlo | Fielddeployable, high-resolution, time-of-flight aerosol mass spectrometer[END_REF] measured the chemical composition and size distribution of non-refractory submicron particles (NR-PM 1 ) in the range 50-1000 nm (in vacuum aerodynamic diameter, D va ). Since this instrument uses a thermal method to vaporize aerosol species, refractory materials, such as black carbon, sea salt and most metallic species, cannot be detected with this technique. An aerosol time-offlight mass spectrometer (ATOFMS; TSI Instruments Ltd., High Wycombe, U.K.; model 3800-100) [START_REF] Arndt | Scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX) and aerosol time-of-flight mass spectrometry (ATOFMS) single particle analysis of metallurgy plant emissions[END_REF][START_REF] Gard | Real-Time Analysis of Individual Atmospheric Aerosol Particles: Design and Performance of a Portable ATOFMS[END_REF] simultaneously measured single particle composition and mixing state in the size range 100-3000 nm (in D va ). The ATOFMS vaporizes aerosol species by laser ablation, enabling the measurement of refractory species, which are expected to play a significant role in the particle chemistry at this industrial site.

Over 700'000 single particle mass spectra were collected during the campaign and clustered using the K-means algorithm (K=90), as described in detail elsewhere [START_REF] Gross | Environmental chemistry through intelligent atmospheric data analysis[END_REF][START_REF] Healy | Source apportionment of PM2.5 in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements[END_REF][START_REF] Healy | Characterisation of single particles from in-port ship emissions[END_REF]. A 2-wavelength Aethalometer (Magee Scientific, Berkeley, CA; model AE42) was deployed to measure organic-like (OC) and black carbon (BC) concentrations via the measurement of absorption coefficients at 370 and 880 nm, respectively. The algorithm presented by [START_REF] Weingartner | Absorption of light by soot particles: determination of the absorption coefficient by means of aethalometers[END_REF] was used to reduce measurement artifacts due to filter loading and the scattering of the light beam in the filter matrix. Two scanning mobility particle sizers (SMPS) and an optical particle counter (OPC) were used to measure the particle size distribution. The first SMPS system (Grimm Aerosol Technik, Ainring, Germany) was comprised of a differential mobility analyzer (DMA; model 55-900) and a condensation particle counter (CPC; model 5.403), enabling particle counting in the size range 10-1000 nm (in mobility diameter, D m ), while the second SMPS (TSI Inc., Shoreview, MN) was constituted of a CPC model 3010, an electrostatic classifier model 3080, and a DMA model 3081, enabling particle counting in the size range 10-480 nm (in D m ). The OPC (Grimm Aerosol Technik; model 1.108) measured particles in the size range 300 nm -20 µm (in optical diameter).

In addition to the above-mentioned instruments for online particle measurements, several cascade impactors (Dekati Ltd., Tampere, Finland; 13-stage low pressure impactor, and 3stage PM 10 impactors) and a speciation sampler (Thermo Fisher Scientific, Waltham, MA; model Partisol 2300) were also deployed to sample particles on filters for subsequent off-line analyses. These results, some of which have already been published [START_REF] Mbengue | Size-distributed metallic elements in submicronic and ultrafine atmospheric particles from urban and industrial areas in northern France[END_REF], included the measurement of metals by inductively-coupled plasma mass spectrometry (ICP/MS) (Varian Inc., Santa Clara, CA; model 820-MS; or Perkin Elmer, Waltham, MA; model DRC Elan 6100) and by inductively-coupled plasma atomic emission spectroscopy (ICP/AES) (IRIS Intrepid, Thermo-Scientific), and organic carbon (OC) and elemental carbon (EC) by a thermal-optical method (Sunset Laboratory, Tigard, OR; Lab OC-EC aerosol analyzer).

A proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) (Kore Technology Ltd, Ely, Cambridgeshire, U.K.; model Series I) (de [START_REF] De Gouw | Measurements of volatile organic compounds in the earths atmosphere using proton-transfer-reaction mass spectrometry[END_REF][START_REF] Lindinger | On-line monitoring of volatile organic compounds at pptv levels by means of proton-transfer-reaction mass spectrometry (PTR-MS) -Medical applications, food control and environmental research[END_REF] allowed for measurement of VOCs with a proton affinity higher than that of water. Long-chain alkanes and aldehydes (>C 8 ) were sampled on adsorbing cartridges with an automatic sampler, and analyzed after thermal desorption by gas chromatography coupled to a mass spectrometer (GC/MS) (Agilent Technologies Inc., Santa Clara, CA; GC: model 6890N; MS: model 5975) following a procedure previously developed and validated [START_REF] Detournay | Development of a sampling method for the simultaneous monitoring of straight-chain alkanes, straightchain saturated carbonyl compounds and monoterpenes in remote areas[END_REF]. Finally, automatic analyzers were used to monitor CO 2 (Horiba Ltd, Kyoto, Japan; model VA-3000) as well as CO (model CO 12M), NO x (model AC 31M), O 3 (model O 3 41M), and SO 2 (model AF 22M), all from Environnement S.A., Poissy, France.

Sampling at the stacks of the ferromanganese alloy production facility was performed using automatic analyzers for gases (SO 2 , CO, NO x ), cascade impactors and adsorbing cartridges for collection of particles and VOCs/PAHs for subsequent off-line analysis (Table S3). PM was collected in the flues of each stack (downstream of the industrial filters) by installing a 3stage cascade impactor (Dekati Ltd) into the center of the chimney flue. The impactor was equipped with a vertical PM 10 sampling head and the sampling rate was adapted to the stack flue in order to obtain an isokinetic sample. This sampling meets European standards for stack dust sampling for emission controls. More details can be found elsewhere [START_REF] Arndt | Scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX) and aerosol time-of-flight mass spectrometry (ATOFMS) single particle analysis of metallurgy plant emissions[END_REF][START_REF] Mbengue | Size-distributed metallic elements in submicronic and ultrafine atmospheric particles from urban and industrial areas in northern France[END_REF].

Date and time are reported in Coordinated Universal Time (UTC). The local time during this study was Central European Summer Time (CEST), which corresponds to UTC+2:00.

Meteorology

Meteorological conditions and atmospheric dynamics

Figure 3 shows the time series of standard meteorological parameters (temperature, relative humidity, solar radiation, rainfall, wind direction and speed) observed during the measurement period, along with atmospheric stability, while back trajectory analysis is presented and discussed in the supplementary material (Figures S2-S4). The temperature varied between 6 and 24°C, but for most of the field campaign, was in the range 10-15°C. The maximum solar radiations were in the range 750-850 W m -2 . Several occasional rainy periods occurred during the field campaign, especially after June 2. The relative humidity was rather high (mean ± 1 σ: 78.9 ± 14.3%) due to the coastal location of the receptor site.

The wind direction was an important parameter to identify periods during which the site was under the influence of metalworking emissions, and in particular when NE winds could transport plumes from the emission stacks of the Fe-Mn plant to the sampling site. The wind direction was variable during the field campaign, as shown by the wind rose plot (Figure 1c).

Three dominant wind directions each with an occurrence rate of 15-20% were observed, corresponding to winds blowing from the southwest, northwest, and north. The wind was northeasterly for about 5% of the field campaign, and we identified two periods during which the plume could be transported to the site from this direction: May 25-27, and June 2. The period between May 25 and 27 was the longest period with a NE wind, corresponding to the hottest days of the campaign and elevated solar irradiation (~800 W m -2 ), which could increase photo-oxidation and promote relatively faster chemical transformations of particles and precursor gases between the emission stacks and the sampling site. Moreover, a high temperature gradient also promotes sea breezes, and thus a vertical mixing of the plumes (see below).

During these NE wind periods, it is important to assess the stability of the atmosphere, which describes the mixing of emissions over a large area and explain the vertical and horizontal dispersion of the plume. In the current study, the Monin-Obukhov length scale (deduced from the sonic anemometer), which depends mainly on heat and momentum fluxes, friction velocity and temperature, has been used to estimate the atmospheric stability classes [START_REF] Stull | An Introduction to Boundary Layer Meteorology[END_REF]. Figure 3d shows the time series of the atmospheric stability during the whole campaign. High occurrences of unstable periods were observed and represent ~47% and 17% of unstable and very unstable atmospheric conditions, respectively, thus favoring plume dispersion. Moreover, LIDAR measurements can confirm this dispersion effect, and that plumes effectively reach the sampling site during NE wind periods (see below).

Winds were blowing from NW to NE on 18 days during the campaign, while 11 sea breeze events were also observed. Sea breezes have been frequently observed at Dunkirk during previous studies [START_REF] Boyouk | Impact of sea breeze on vertical structure of aerosol optical properties in Dunkerque, France[END_REF][START_REF] Roukos | Radial diffusive samplers for determination of 8-h concentration of BTEX, acetone, ethanol and ozone in ambient air during a sea breeze event[END_REF][START_REF] Talbot | Impact of a sea breeze on the boundary-layer dynamics and the atmospheric stratification in a coastal area of the North Sea[END_REF]. Sea breeze coming from the sea toward the land may modify the lower troposphere stratification by the formation of a thermal internal boundary layer (TIBL) [START_REF] Augustin | Investigation of local meteorological events and their relationship with ozone and aerosols during an ESCOMPTE photochemical episode[END_REF]. The TIBL is a thin unstable layer where pollutants can be trapped and mixed. Furthermore, since the SODAR echo depends on fluctuation of temperature due to the signature of the boundary layer top, the TIBL top, characterized by high echo values, can be detected [START_REF] Beyrich | Mixing height estimation from sodar data -A critical discussion[END_REF].

During the present campaign, the NE wind period between May 25 and May 27 is of particular interest, because according to the wind direction and wind speed time-height sections from the SODAR (Figure 4a), these three days are characterized by long sea breeze events (e.g. on May 25 from 10:00 am to 8:00 pm, on May 26 from 9:00 am to 8:00 pm, and on May 27 from 11:00 am to 8:00 pm), with winds at ground level coming mainly from the NE and likely transporting plumes from the Fe-Mn plant to the sampling site. According to Figure 4e, these sea breeze events are also characterized by an increase in the concentration of particulate phase organics and ammonium nitrate, and a decrease in the concentration of sulfate. These results suggest that organics and ammonium nitrate could possibly be emitted by metalworking activities.

Detection and monitoring of metalworking plumes

Ground-based remote sensing instruments (SODAR and LIDAR) were used to monitor the propagation of metalworking plumes in the vicinity of the sampling site. Figure 4 includes the SODAR, LIDAR, AMS, Aethalometer, and SMPS data during the period 25-27 May when the winds were from the NE and sea breezes were observed, while Figure S5 shows a few examples of LIDAR vertical scans for four relevant directions. The LIDAR data shown in Figures 4b and S5 correspond to the depolarization ratio at 355 nm, i.e. the ratio between the measured perpendicular and parallel backscattered LIDAR signals. This parameter provides information in order to distinguish spherical (e.g. haze) from non-spherical particles (e.g. dust and smoke) in the atmosphere. For example, non-spherical particles as industrial dust (e.g. fly ash from metalworking or steelworks) can depolarize LIDAR signals, resulting in high depolarization ratio values. The higher 355 nm-depolarization ratios were observed during 25-27 May sea breeze events (Figure 4b), clearly indicating that during these precise time slots our sampling site was influenced by metalworking plumes.

To confirm the identification of periods during which the sampling site was specifically impacted by these plumes, a two-steps analysis of SODAR and LIDAR data was performed.

First, the SODAR data (Figure 4a) was used to determine periods during which the wind at ground level was coming from the NE. Then, the LIDAR data for these periods (Figures 4b andS5) was used to determine whether the sampling site was under the influence of the plumes, as well as to confirm the origin of these plumes. For instance, Figure S5d shows a LIDAR vertical scan measured toward an azimuth angle of 228°, corresponding to the direction of the sampling site (Figure S5e). This scan shows that a plume was located very close to the sampling site. LIDAR scans measured less than an hour earlier toward the stacks (azimuth angle 13°, Figure S5a) and the azimuth angles 308° (Figure S5b) and 238° (Figure S5c) helped us to determine that the plume was mainly coming from the stacks of the Fe-Mn plant, possibly mixed with emissions from the nearby steelworks.

Results and discussion

Particle chemical composition

Figure 5b shows the time series of the five NR-PM 1 species measured by the HR-ToF-AMS, along with BC measurements from the Aethalometer. The average NR-PM 1 concentration during the study was 10.7 µg m -3 . This mean value, taking only NR-PM 1 into account, slightly exceeds the WHO recommendations (10 µg m -3 ). Concentrations were very high between May 24 and May 27 (in the range 20-75 µg m -3 ), but decreased significantly after June 5 (below 5 µg m -3 ). According to meteorological conditions and atmospheric dynamics during these periods (Section 3), high mass loadings were concurrent with low wind speed coming from the northeast and east (metalworking activities sector), while the decrease in particle mass loading during the last week occurred when the wind speed increased significantly and wind direction shifted to the south, bringing a few rain episodes. NR-PM 1 was dominated by inorganic species, which accounted for ~2/3 of the total mass, while organics accounted for ~1/3 (Figure 5, upper pie chart). However, the chemical composition varied significantly throughout the study, and several pollution events dominated by ammonium nitrate, ammonium sulfate or organics were observed, especially downwind of metalworking emissions. Despite the fact that very few studies emphasized the contribution of nonrefractory submicron aerosols (NR-PM 1 ) to metalworking (steel industry, metallurgy, smelting works) emissions [START_REF] Almeida | Chemical characterization of atmospheric particles and source apportionment in the vicinity of a steelmaking industry[END_REF][START_REF] Crenn | Fine particles sampled at an urban background site and an industrialized coastal site in Northern France -Part 1: Seasonal variations and chemical characterization[END_REF], this confirms the importance of secondary aerosols in these emissions. We also observed several periods with an increase in the non-refractory chloride concentration up to ~5 µg m -3 . This chloride does not correspond to sea salt, given that the AMS, operated in standard conditions (with the vaporizer set at 600°C), cannot evaporate and measure NaCl. Examination of the dependence of chloride mass concentrations upon wind direction indicates that this species was observed only during NE wind periods, i.e. when the sampling site was under the direct influence of the Fe-Mn plant and the adjacent steelworks. Moreover, chloride was found to be very well correlated with the K + fragment of the AMS (r 2 =0.67), suggesting that chloride was mainly present in the form of KCl. This might be due to the high formation of KCl during the sintering process in steelworks [START_REF] Hleis | Chemical profile identification of fugitive and confined particle emissions from an integrated iron and steelmaking plant[END_REF][START_REF] Ji | Characteristics of PM2.5 from iron ore sintering process: Influences of raw materials and controlling methods[END_REF][START_REF] Peng | Separation and Recovery of Potassium Chloride from Sintering Dust of Ironmaking Works[END_REF] and is consistent with previous observations using the same instrument at a nearby location [START_REF] Crenn | Fine particles sampled at an urban background site and an industrialized coastal site in Northern France -Part 1: Seasonal variations and chemical characterization[END_REF]. Thus, the non-refractory chloride signal may be a useful proxy to determine periods during which a receptor site is under the influence of emissions from steelworks. This is confirmed by complementary data obtained using the ATOFMS (Figure 5c), which identified 34 distinct particle classes that were subsequently grouped into 10 general categories for clarity. Sea salt particles dominated the dataset by number (24.4% of total spectra), followed by K-containing particles (23.2%) and EC (23.1%). The remaining particle classes correspond to Fe-containing (5.0%), Ca-containing (1.7%), OC and PAH-containing (1.7%), V-containing (1.4%), Mn-containing (1.2%), Pb-containing (1.1%), and other metals (17.1%, including Zn and, in addition, S-and amine-containing particles). Most particle classes are associated with industrial sources [START_REF] Arndt | Scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX) and aerosol time-of-flight mass spectrometry (ATOFMS) single particle analysis of metallurgy plant emissions[END_REF], based on their composition and wind dependence. K-containing particles are usually associated with biomass burning sources, especially in winter in this region, however domestic wood burning is expected to be negligible at this time of year (May/June). The significant abundance of K-containing particles is consistent with the high signal for non-refractory chloride observed by the AMS and confirms the importance of steelworks sintering emissions containing KCl. EC particle numbers increased towards the end of the sampling period, while OC and PAH-containing particles were detected in their largest numbers on June 2. EC-containing particles were more plentiful during E-NE wind periods (Figure 5a-c), i.e. when the sampling site was more specifically under the influence of the nearby coke production facility of the integrated steelmaking plant. [START_REF] Weitkamp | Fine particle emission profile for a large coke production facility based on highly time-resolved fence line measurements[END_REF] showed that elemental carbon contributes up to 30 wt.% to coke production emissions. Ca-containing, Fe-containing and Mn-containing particles clearly increase on May 25, 26 and 27 (downwind of the metalworking emissions), while the latter two categories (Fe-and Mn-containing particles) also increased sharply on May 17, under the influence of urban emissions. Given their composition and size, particles in these categories are almost certainly emitted by either the ferromanganese alloy production plant or the neighboring steelworks. This is supported by the fact that these particles are detected in higher numbers during periods when meteorological conditions were most favorable for plumes to be transported from these two plants, as monitored by LIDAR sensing (see Section 3.2). Further discussion and interpretation of the ATOFMS data, including the other metals category, will be the subject of future publications.

Figure 6 represents the time series of size-resolved elemental composition, determined by ICP/MS and ICP/AES analysis of filters collected using a 13-stage impactor with a time resolution of 24 or 48 hours, while Figure 7a shows the time series of the mass concentration.

The concentration of the following elements increased significantly during the periods May 25-27 and June 1-3, when the wind was predominantly coming from the metallurgical complex (NE winds): Fe, Mn, Ca, K, Zn, Pb, plus a few minor elements (Cu, Ti, Ba, Rb, Sr).

The size distribution indicates that some elements are enriched in the submicron fractions, (K, Zn, Pb, V, Ni, Cr, Rb, Mo, As, Cd, Sb), while others are more abundant in the coarse fraction (Fe, Ca, Mn, Ti, Ba, Sr), depending on the wind direction. The fact that both Mn and Fe, abundant downwind of ferromanganese-and steelworks-emissions, were more concentrated in the coarse fraction may be due to a combination of (i) the resuspension of dust from the iron-enriched manganese ores stored outdoors (Figure 1b), (ii) industrial mechanical processes (excavating, crushing or ore pile processing), in addition to stationary emissions (sintering, etc.), and (iii) road dust resuspension in the harbor area. The comparison between elemental ratios at the emission stacks of the Fe-Mn alloy plant and at the sampling site has been used to confirm periods during which the sampling site was under the influence of emissions from this plant (Table 1). Among the three plant stacks, the one located above the cooling area of the sintering unit (stack B, Figure 2) was by far the most important emitter of fine particles [START_REF] Arndt | Scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX) and aerosol time-of-flight mass spectrometry (ATOFMS) single particle analysis of metallurgy plant emissions[END_REF], ~4 times more than stack A (firing area) and ~50 times more than stack C (smelting unit) (Figure 7b). Given that the plant was manufacturing ferromanganese alloy, the most suitable proxy for our analysis is the Mn/Fe ratio [START_REF] Marris | Fast changes in chemical composition and size distribution of fine particles during the near-field transport of industrial plumes[END_REF]. Emissions from the stacks of the plant show an enrichment of Mn compared to Fe, with a Mn/Fe ratio around 3 (Table 1). At the near-field site, the Mn/Fe ratio remained below 1, except for two periods (May 19-21 and May 31-June 1) when both metal concentrations were very low. In addition, the Mn/Fe ratio during the two periods under the influence of NE winds (May 25-27 and June 1-3) was in the range 0.3-0.4. This result, coupled with the increase of potassium from KCl (steelworks sintering emissions proxy) observed by the HR-ToF-AMS during the same periods, suggests that the plumes emitted by the Fe-Mn plant were mixed, before reaching the sampling site, with emissions from the adjacent steelworks, for which the Mn/Fe ratio is very low (<0.01) [START_REF] Alleman | PM10 metal concentrations and source identification using positive matrix factorization and wind sectoring in a French industrial zone[END_REF]. Other elemental ratios reported in Table 1 show that values calculated for the near-field site are very different from those determined at the stacks, suggesting that the plumes were quickly (within a few minutes) mixed with pollutants emitted by other sources (e.g. steelworks, truck traffic in the industrial zone) [START_REF] Mbengue | Metal-bearing fine particle sources in a coastal industrialized environment[END_REF] before reaching the sampling site. This is certainly due to the unstable atmospheric conditions prevailed most of the time during the sampling campaign (Figure 3d), favoring plumes dispersion. This is especially true during sea breeze events, with the formation of an unstable TIBL, as those unambiguously identified during the May 25-27 period, the longer sea breeze episode of the field campaign.

Particle size distributions

Figure 8 shows the time series of the particle number size distribution between 10 and 500 nm, along with the average size distribution for the entire study. The average size distribution has a single mode at 40 nm (in D m ). However, the particle number concentrations and size distributions varied dynamically during the study. Several periods displayed an increase in the particle number concentration. During most of these periods, size distributions were unimodal with a mode centered at 40-60 nm (e.g. May 19, 28, 29, 30, June 1). However, size distributions observed during NE wind periods (May 25-27, June 2) were very different, and showed a mode at much smaller sizes, below 20 nm. This observation was also quite obvious during sea breeze events on May 25-27 (Figure 4d), systematically associated with an increase in particles of small sizes centered at around 20 nm. The presence of this nucleation mode when the sampling site was under the direct influence of metalworking emissions suggests the occurrence of new particle formation events. New particle formation is a phenomenon which has been extensively observed at various urban, remote, and coastal locations [START_REF] Curtius | Nucleation of atmospheric aerosol particles[END_REF][START_REF] Holmes | A review of particle formation events and growth in the atmosphere in the various environments and discussion of mechanistic implications[END_REF][START_REF] Kulmala | Formation and growth rates of ultrafine atmospheric particles: a review of observations[END_REF][START_REF] Zhang | Nucleation and Growth of Nanoparticles in the Atmosphere[END_REF]. Thus, these events may occur in polluted as well as in very clean environments. Usually, when new particle formation and growth events occur at a regional scale, the SMPS data trend line shows a "banana shape". Indeed, an increase of the concentration of very small particles (<15 nm) is first observed when these new particles are formed. Then, an increase of the mode is observed during the following hours, when gaseous compounds with low volatility condense onto the surface of these new particles, or when these particles agglomerate to form bigger ones [START_REF] Setyan | Chemistry of new particle growth in mixed urban and biogenic emissions -insights from CARES[END_REF][START_REF] Setyan | Characterization of submicron particles influenced by mixed biogenic and anthropogenic emissions using highresolution aerosol mass spectrometry: results from CARES[END_REF]. The absence of "banana shapes" and the presence of a constant nucleation mode during several hours in the present SMPS dataset (Figure 4d) suggest that new particle formation was due to continuous emissions from a single point source, located at a constant distance from the near-field sampling site. This may be due to major emissions of these new particles or gaseous precursors from the Fe-Mn plant stacks (or adjacent steelworks emissions), which undergo rapid cooling in the ambient air, thus promoting fast condensation of the gaseous emissions and transformation of stack pipe generated particles, before reaching the sampling site.

Another evidence for new particles formation and growth is emphasized by mass size distribution measurements. Figure 7a shows the mass size distributions determined at the sampling site with the 13-stage impactor. PM 2.5 concentrations varied in the range of 11-44 µg m -3 during this study. The highest concentrations observed during the whole field campaign were reached when the wind was coming from the NE direction at relatively low speed, which counteracted dilution of the plumes. The total mass was dominated by submicron particles (from 0.1 to 1 µm), which accounted for 63.1% of the mass, while particles larger than 1 µm accounted for 33.5%. Particles in the ultrafine size range (<0.1 µm) had a negligible contribution to the mass (3.4%), even if their number was much higher than particles of larger sizes. The mass size distributions did not fluctuate drastically during the study, except for two periods. Between May 15-17, the mass was dominated by coarse particles (65% of the total, with probably a high contribution of sea salts, considering the wind direction and results from ATOFMS and ICP/MS -Figures 5c and6), while from May 29-31, the contribution of submicron particles was higher (77% of the total mass). These size distributions observed at the near-field site were very different to those observed at the stacks of the Fe-Mn plant (Figure 7b). Emissions from the plant were totally dominated by particles in the ultrafine range (60.1% of particles <0.1 µm), while these particles accounted for only 3.4% at the near-field site. These observations provide further evidence to support the fast evolution of the plumes and also indicate that emissions from the stacks are likely very quickly diluted in an air mass containing larger particles before reaching the sampling site. In the presence of those larger particles, ultrafine particles freshly emitted at the stacks may quickly agglomerate to form larger particles before reaching the sampling site. In summary, ultrafine particles (D m ~20 nm) seem to be continuously generated by Fe-Mn plant and steelworks emissions, but within the plumes fast agglomeration processes could result, in a few minutes, in the formation of larger particles in the accumulation mode (0.1-1.0 µm).

Trace gases

Figure 5f-h shows the time series of several VOC families (aromatics, alkanes, alkenes, oxygenated VOCs, biogenic VOCs). Most of them exhibited high concentrations during the first five days of the campaign (May 15-19), then decreased significantly until the end of the study. However, some short events are also apparent, especially during the NE wind periods, i.e. under the influence of metalworking activities. Benzene was the only VOC to increase significantly when the sampling site was under the influence of emissions from the Fe-Mn plant and steelworks. Toluene also increased during these periods, but to a lesser extent.

Toluene and benzene were by far the most concentrated VOCs released from the stacks of the Fe-Mn factory, especially from the stack above the firing area, with a toluene/benzene ratio in the range 2-3. However, during NE wind periods, the toluene/benzene ratio was always ~0.5 at the sampling site, similar to the ratio previously measured in the same area [START_REF] Roukos | VOC in an urban and industrial harbor on the French North Sea coast during two contrasted meteorological situations[END_REF]. This result implies either that emissions from the stacks were already highly processed when the plumes reached the sampling site (as evidenced previously for particles), or that there was another important source of benzene near the Fe-Mn plant (e.g. the steelworks, [START_REF] Ciaparra | Characterisation of volatile organic compounds and polycyclic aromatic hydrocarbons in the ambient air of steelworks[END_REF]. Several additional events were identified, such as during the nights of May 22-23, May 23-24, and May 31-June 1, with an increase of short-chain alkanes (Figure 5g). These events took place during NW and W wind periods, suggesting that short-chain alkane emissions could possibly be related to petrochemical industrial activities in the area (Figure 1a).

On the bottom right of Figure 5, two pie charts show the average VOC composition during NE wind periods (downwind metalworking sources) and measured at the stacks. VOCs emitted at the stacks are totally dominated by aromatic compounds (mainly toluene and benzene), which account for 60% of the total measured VOCs, while this class of compounds accounts for only 31% at the sampling site during NE wind periods. These pie charts also show that oxygenated compounds emitted at the stacks represent 7% of the total VOCs, while at the sampling site, they account for 27% of the total VOCs. Moreover, none of the oxygenated compounds identified at the sampling site come from aromatic precursors. These results suggest that emissions from the stacks are, during NE wind periods, quickly diluted in an aged air mass before reaching the sampling site. This also confirms previous observations within the same industrial complex [START_REF] Roukos | VOC in an urban and industrial harbor on the French North Sea coast during two contrasted meteorological situations[END_REF] that highlighted the fact that even in anthropogenically-influenced areas, long-range transport can have a significant contribution to the observed concentrations of gaseous pollutants.

Figure 5d-e shows the time series of the main trace gases (CO, CO 2 , NO x , O 3 , SO 2 ). Among them, CO 2 and O 3 were the only gases to show significant diurnal trends. O 3 varied between 20 ppb (nighttime) and 40 ppb (daytime) on average. The average CO 2 concentration was 460 ppm during the night and 430 ppm during the day. Its diurnal pattern was mainly driven by boundary layer dynamics. Vegetation and variation in the surface temperature of the sea could also influence the diurnal pattern of CO 2 . The concentration of the other gases varied dynamically throughout the study. CO and SO 2 increased significantly during NE wind periods, when the sampling site was under the direct influence of metallurgical emissions.

The CO concentration during these periods was in the range 3-10 ppm, ~10 times higher than during other periods. The SO 2 concentration also increased 10-fold during NE wind periods.

Measurements performed at the stacks of the Fe-Mn factory confirmed that the firing area of the sintering unit of the plant emitted very large amounts of these two gases (Table 2). Sulfuric acid is one species commonly involved in particle nucleation, along with water [START_REF] Holmes | A review of particle formation events and growth in the atmosphere in the various environments and discussion of mechanistic implications[END_REF][START_REF] Zhang | Nucleation and Growth of Nanoparticles in the Atmosphere[END_REF]. Therefore, the very high amounts of SO 2 emitted by this factory, followed by its rapid oxidation to sulfuric acid, could play a major role in the new particle formation events observed at the sampling site downwind of metalworking emissions (Section 4.2). However, for the period of sea breezes during which the sampling site was unambiguously influenced by metalworking plumes (Figure 4b and4d), organics in NR-PM 1 are clearly more abundant than sulfates (Figure 4e). Thus, after the formation of new particles, which have a diameter of a few nm, the growth of these particles up to larger sizes could be more driven by organics than by sulfate formation, or results from fast agglomeration processes with preexisting particles.

Physico-chemical characteristics of plumes influenced by different pollutant sources

Considering the atmospheric dynamic from LIDAR and SODAR data (section 3), three short time (30 minutes) but highly specific events were identified, influenced by steelworks and Fe-Mn plant activities (from NE-E wind direction), by petrochemical activity (from NW wind direction) and by urban activities (from SE wind direction), respectively. The corresponding gas and particle parameters are listed in Table 2, while Figure 9 shows the average particle number size distributions during these three thirty-minute periods. The particle (PM 2.5 , sum NR-PM 1 and particles number concentrations) and gas (CO, SO 2 ) concentrations were very high in the metalworking emissions. Indeed, the total NR-PM 1 concentration in this plume was 37.7 µg m -3 , much higher than in the plume from the refinery in the NW (16.2 µg m -3 ) and from the urban traffic in the S (2.9 µg m -3 ), while the particle number concentration was around 20-30 times higher. In terms of chemical composition, the contributions of nitrate (22.3%, vs. 12.3% for petrochemistry and 13.8% for urban emissions) and non-sea salt chloride (6.9%, vs. 1.2% and 3.4%) were significantly higher, and that of sulfate lower (12.7%, vs. 50.0% and 24.1%) in the plume from the metallurgy plant and steelworks, compared to the two other plumes. Results obtained with the ATOFMS (Table 2) showed that most metal-containing particles were also mainly coming from the metallurgical area, such as Fe-and K-rich particles. In addition to these, Ca, Pb, and other metals-rich particles were also present in much higher concentrations when the near-field site was under the influence of metallurgical emissions. Among the trace gases, CO and SO 2 were significantly higher during the NE-E wind period, compared to other periods, and thus their presence was highly influenced by these industrial activities. The presence of high mixing ratios of SO 2 (47.8 ppb), and low contributions of sulfate during the NE-E wind period suggest that chemical processing was not fast enough to totally oxidize SO 2 to sulfate over a distance of <1 km, even if new particle formation events were observed at the sampling site during this NE-E wind period (see Section 4.3). However, considering metal-bearing particles as a proxy for refractory compounds, the latter contribution to particles smaller than 100 nm is relatively low during NE wind periods (Figure 6,. This size fraction is then probably dominated by the non-refractory fraction, and notably by organic compounds which account for 45 % or NR-PM 1 concentration during the plume from the NE-E (Table 2). This result strongly suggests that after the formation of new particles in the plume from the metallurgical area, their growth to larger sizes was largely driven by the condensation of organics.

Conclusion

The aim of the NANO-INDUS project was to study the evolution of physico-chemical characteristics of fine particles emitted by industrial activities over a short distance, before they reach surrounding populated areas. This was performed in two steps. First, particles emitted by a ferromanganese alloy plant, located in a multi-influenced industrial area, were directly sampled and analyzed. Secondly, a field campaign was undertaken in the near-field of the plant chimneys, in order to determine the concentration, chemical composition, and size distribution of the fine particles emitted in this multifaceted atmospheric environment.

Results obtained during the field campaign showed that unstable atmospheric conditions inside the thermal internal boundary layer (TIBL), due to the occurrence of sea breezes, promote entrapment and mix of pollutants (here Fe-Mn plant emissions, mixed with emissions from an adjacent steelworks). These TIBL unstable periods were characterized by a very high mass concentration of fine particles (38 µg m -3 NR-PM 1 ), compared to other periods dominated by urban or marine influences. These results highlight the huge influence of metalworking emissions on ambient air quality and raise questions about occupational exposure of workers. The chemical composition of particles during these sea breeze periods was also characteristic, as the contribution of metal-rich particles, organics, and nitrates increased significantly, while that of sulfate decreased, compared to other periods. In addition to new particle formation at the stacks of the Fe-Mn plant, particle growth was also observed in the plume from the metallurgical area. In parallel to possible fast agglomeration processes with preexisting particles, the latter phenomenon was mainly driven by the condensation of organics.

This work has important implications in terms of air quality monitoring strategies. First, people working in an industrial area may be continuously exposed to fine particle concentrations going well beyond recommendations from Public Health Authorities (e.g. the WHO annual mean guideline value of 10 µg m -3 for PM 2.5 ). Second, our results show that, even over short distances, the chemical composition and size of these fine particles may evolve rapidly, and that their characteristics at the boundary of an industrial complex may differ from those directly emitted at the stacks, the only position monitored by manufacturers to comply with regulation and develop emission control strategies. Generally speaking, it is therefore suggested, for towns increasingly influenced by such activities, that air quality management plans address these observations, for example by means of special monitoring in neighboring urban zones, dedicated to the apportionment of processed metalworking emissions.

Author contribution

PF, NL, KD, VR, LYA, CS, and JCW designed the study. AS, PF, NL, KD, VR, LYA, and CS organized the field campaign at the Fe-Mn plant. AS, PF, NL, KD, VR, LYA, CS, JA, PA, RMH, FC, DD, PD, MF, PG, TL, HM, and SM participated in the data acquisition during the field campaign and worked on the data treatment. All the co-authors participated in the interpretation of the results. AS wrote the manuscript, with contributions from PA and MF for the sections on atmospheric dynamics and metalworking plume detection. All the co-authors gave their feedback on the different versions of the manuscript, and approved the final version. 2) (data from the SMPS).

Figure 1 .

 1 Figure 1. (a) Map of the industrial area near Grande-Synthe, with the locations of the sampling site, the emission chimneys of the ferromanganese alloy manufacturing plant, and other industries. (b) Enlarged map showing the location of the LIDAR, with the four directions scanned by the instrument every 15 minutes. (c) Wind rose plot for the entire campaign. Key: C chemical plant; G glass manufacturing factory; M metallurgy; P plastic manufacturing plant; PC petrochemistry; PP power plant; S steelworks.

Figure 2 .Figure 3 :Figure 4 .

 234 Figure2. Schematic drawing of the ferromanganese alloy manufacturing process and the filtration system used for each stack.Mn-enriched ores

Figure 5 .

 5 Figure 5. Time series of (a) the daily average wind direction (with length of arrows 889 proportional to the wind speed), (b) chemical species measured by the AMS, the 890 Aethalometer, and (c) the ATOFMS, (d) CO, CO 2 , and NO x , (e) O 3 and SO 2 , (f) benzene and 891toluene, (g) alkanes and alkenes, (h) biogenic and oxygenated VOCs. Shaded regions 892 correspond to NE wind periods (from stacks). The pie charts show the average contribution of 893 the species to the total PM 1 mass and VOCs. 894

Figure 6 .

 6 Figure 6. Time series of the size-resolved elemental composition (data from ICP/MS and ICP/AES analyses of Teflon filters), along with the average wind direction (length of arrows are proportional to wind speed).

Figure 7 .Figure 8 .

 78 Figure 7. (a) Time series of mass size distributions at the near-field sampling site and average wind directions, and (b) average mass size distributions at the stacks of the ferromanganese alloy manufacturing plant (gravimetrically determined from 13-stage impactor filters). Sizes of arrows are proportional to the wind speed.

Table 1 .

 1 List of selected elemental ratios for the stacks and the sampling site (data from ICP/MS and ICP/AES analyses).Mn/Fe Mn/Al Fe/Ca Na/Mg V/Ni Zn/Pb Cu/Sb Pb/Cd

	Stacks	Firing area (A) Cooling area (B) Smelting unit (C)	2.62 3.34 0.46	2.99 3.59 1.25	0.91 4.19 2.86	<DL <DL 2.47	0.34 0.53 0.00	0.07 0.51 11.9	12.2 70.0 <DL	15.0 21.3 46.3
		15-17/5	0.67	0.86	0.70	2.23	0.62	1.03	10.2	36.6
		17-19/5	0.26	0.34	1.07	0.43	0.19	5.56	10.4	31.3
		19-21/5	1.90	1.29	1.43	1.09	0.88	2.32	15.8	13.5
		21-23/5	0.59	0.24	0.61	1.92	1.01	2.00	3.15	35.7
		23-25/5	0.58	0.75	0.92	5.18	1.17	2.31	8.77	29.8
		25-27/5	0.30	1.51	1.86	2.17	1.08	3.19	11.1	19.5
	Sampling site	27-29/5 29-31/5 31/5-1/6 1-3/6 3-5/6	0.28 0.73 1.19 0.39 0.45	0.66 0.43 0.55 1.29 0.30	1.61 0.43 0.46 1.48 1.00	6.27 0.35 0.81 3.43 0.85	1.20 1.12 0.72 0.79 0.45	2.83 1.52 3.61 3.48 2.11	7.21 3.55 3.19 13.2 7.62	26.3 37.7 31.6 42.2 56.4
		5-6/6	0.96	0.07	0.34	0.00	0.05	4.74	2.61	15.7
		Average	0.69	0.69	0.99	2.06	0.77	2.89	8.06	31.4
		Std dev	0.47	0.46	0.51	1.98	0.38	1.31	4.31	11.9
		Median	0.59	0.61	0.96	1.51	0.84	2.58	8.20	31.5
		Min	0.26	0.07	0.34	0.00	0.05	1.03	2.61	13.5
		Max	1.90	1.51	1.86	6.27	1.20	5.56	15.8	56.4
	DL: Detection Limit

Table 2 .

 2 Summary of meteorological conditions and concentrations of particle-and gas-phase data during specific plumes reaching the sampling site and identified with the LIDAR and SODAR.

		Wind direction	NE-E	NW	SE
		Plumes	Steelworks Fe-Mn plant	Petrochemistry Urban
		Date	26/05/2012	03/06/2012	07/06/2012
		Start time (UTC)	10:15 am	11:30 am	5:30 am
		End time (UTC)	10:45 am	12:00 pm	6:00 am
		Temperature [°C]	21.3	11.8	15.6
	Weather station	Relative humidity [%]	55	94	87
		Solar radiation [W m -2 ]	801	51	90
	Sonic anemometer	Wind speed [m s -1 ] Atmosphere	4.4 unstable	2.8 very unstable	3.4 unstable
	Beta Gauge	PM 2.5 [µg m -3 ]	65.7	N/A	4.5
	SMPS	Particle number [#/cm 3 ]	154'847	5'809	7'446
		Org [µg m -3 ]	16.8	2.4	1.3
	HR-ToF-AMS	2-[µg m -3 ] -[µg m -3 ] NO 3 SO 4 + [µg m -3 ] NH 4 Cl -[µg m -3 ]	4.8 8.4 5.1 2.6	8.1 2.0 3.5 0.2	0.7 0.4 0.4 0.1
		Sum NR-PM 1 [µg m -3 ]	37.7	16.2	2.9
	Aethalometer	BC [µg m -3 ]	1.3	0.4	1.0
		Na-rich [count hr -1 ]	27	44	224
		K-rich [count hr -1 ]	275	89	31
		EC [count hr -1 ]	75	274	35
		OC & PAH [count hr -1 ]	6	8	8
	ATOFMS	Fe-rich [count hr -1 ] Ca-rich [count hr -1 ]	67 25	58 13	8 10
		Mn-rich [count hr -1 ]	10	11	5
		Pb-rich [count hr -1 ]	23	14	0
		V-rich [count hr -1 ]	2	3	0
		Others [count hr -1 ]	220	6	12
		Biogenic VOCs [µg m -3 ]	1.8	0.8	0.6
	VOCs cartridges, TD-GC/MS	Aromatics [µg m -3 ] Alkanes [µg m -3 ] Alkenes [µg m -3 ]	9.1 7.7 8.7	5.7 17.7 3.2	1.5 2.0 2.5
		Oxygenated VOCs [µg m -3 ] 11.5	6.2	3.9
		CO [ppb]	4666	363	692
	Gas analyzers	NO x [ppb] O 3 [ppb]	N/A 17.6	15.7 16.7	12.8 7.2
		SO 2 [ppb]	47.8	N/A	6.6

  species measured by the AMS, the 890 Aethalometer, and (c) the ATOFMS, (d) CO, CO 2 , and NO x , (e) O 3 and SO 2 , (f) benzene and 891 toluene, (g) alkanes and alkenes, (h) biogenic and oxygenated VOCs. Shaded regions 892 correspond to NE wind periods (from stacks). The pie charts show the average contribution of 893 the species to the total PM 1 mass and VOCs.

	894
									Org
			AMS conc.	[µg/m 3 ]	25 20 15 10 5	SO 4 2-	31.4% 21.5% 15.8% 24.3% 3.1% 4.0%	Cl BC -
	CO [ppm]	16 12 8 4	ATOFMS conc.	[count/hr]	0 1500 1000 500 0		NO 3	-	NH 4 +
		0
								Sampling site
									NE wind
							Alkenes	Oxygenated
								20.1%	26.7%
							17.4%	4.8%	Biogenics
							Alkanes	31.0%
									Aromatics
									Stacks
								Alkanes	Alkenes
								15.4%	15.0%
									Oxygenated
									7.0%
									2.2%	Biogenics
								60.4%
							Aromatics
	895
	896

Acknowledgements

The NANO-INDUS project was funded by the French Environment and Energy Management Agency (ADEME), grant N° 11-81-C0089. IMT Lille Douai, LPCA and PC2A participate in the CaPPA (funded by the ANR through the PIA) and CLIMIBIO projects, both also funded by the "Hauts-de-France" Regional Council and the European Regional Development Fund.

HM and JA acknowledge support from the ADEME and the Irish Research Council, respectively. The authors would also like to thank Emmanuel Fiani (ADEME) for fruitful discussions, François Blond (Glencore Manganèse France) for logistic assistance during the field campaign, and Philippe Le Louer (LECES) for the samplings at the chimneys.

Declarations of interest