Daouda Dawaï
email: daoudadawai@gmail.com

Mélina Macouin
email: melina.macouin@get.omp.eu

Sonia Rousse
email: sonia.rousse@get.omp.eu

Jean-François Léon
email: jean-francois.leon@aero.obs-mip.fr

Merlin Gountié Dedzo

Loïc Drigo
email: loic.drigo@get.omp.eu

Tracking Airborne Pollution with Environmental Magnetism in A Medium-Sized African City

Keywords: magnetic susceptibility, biomagnetism, neem trees, Central Africa, deposited atmospheric dust, urban pollution, air quality

As in other parts of the world, air pollution over West and Central Africa has major health and meteorological impacts. Air quality assessment and its possible sanitary impact have become essential even in medium-sized towns, therefore amplifying the need for easy-to-implement monitoring methods with low environmental impact. We present here the potential of magnetic methods to monitor air quality at street level in the medium-sized city of Maroua (northern Cameroon) affected by dust-laden desert winds. More than five hundred (544) samples of bark and leaves taken from Neem trees in Maroua were analyzed. Magnetic susceptibility, saturation remanence, and S-ratio were found to determine the concentration and nature of magnetic particles. They are dominated by magnetite-like particle signals as a part of particulate emissions due to urban activities, including both traffic, composed of a substantial proportion of motorcycles, and wood burning for food preparation. We show that both bark and leaves from Neem trees are adequate passive bio-recorders. The use of both enables different times and heights to be sampled, allowing for the high-resolution monitoring, in terms of spatialization, of various urban environments. Particle emissions require assessment and screening that could be carried out rapidly and efficiently by magnetic methods on bio-recorders, even in cities impacted by dust-laden wind.

Introduction

Atmospheric pollution resulting from urban traffic is now fully recognized as a major health issue in cities of any size (e.g., [START_REF] Marié | Vehicle-derived emissions and pollution on the road autovia 2 investigated by rock-magnetic parameters: A case study from Argentina[END_REF]). In recent decades, pollution by airborne particulate matter (PM) has been acknowledged as responsible for a growing range of health hazards leading to premature deaths [START_REF] Dockery | Acute Respiratory Effects of Particulate Air Pollution[END_REF][START_REF] Englert | Fine particles and human health-A review of epidemiological studies[END_REF][START_REF] Kelly | Air pollution and public health: Emerging hazards and improved understanding of risk[END_REF][START_REF] Burnett | Global estimates of mortality associated with longterm exposure to outdoor fine particulate matter[END_REF]. Most of the health burden is likely related to chronic exposure to PM2.5 (i.e., airborne particles with aerodynamic dimensions less than 2.5 µm) (e.g., [START_REF] Pascal | Assessing the public health impacts of urban air pollution in 25 European cities: Results of the Aphekom project[END_REF]). According to the WHO [START_REF]Ambient Air Pollution: A Global Assessment of Exposure and Burden of Disease[END_REF], 4.2 million deaths every year are attributed to exposure to ambient (outdoor) air pollution.

The rapid urbanization and population growth in African cities have resulted in a significant increase in the emission of pollutants in urban centers. Owili et al. [START_REF] Owili | The associations between types of ambient PM2.5 and under-five and maternal mortality in Africa[END_REF] demonstrated that ambient PM2.5 is associated with under-five and maternal mortality in Africa. It is expected that anthropogenic emissions will triple (including traffic, biomass burning, and oil and mining industries) between 2000 and 2030 [START_REF] Liousse | Explosive growth in African combustion emissions from 2005 to 2030[END_REF]. Recent observations in western African cities [START_REF] Djossou | Mass concentration, optical depth and carbon composition of particulate matter in the major southern West African cities of Cotonou (Benin) and Abidjan (Côte d'Ivoire)[END_REF] indicate that the PM2.5 concentrations exceed the WHO recommendations by a factor of 3. Western African cities have specific fine particle sources that are either natural or anthropogenic. The fleet of light and heavy-duty vehicles is old and includes a large number of motorcycles. Motorcycles, specifically 2-stroke engines using a mix of oil and gasoline, emit more PM than cars [START_REF] Ntziachristos | Particle Emissions Characteristics of Different On-Road Vehicles[END_REF]. It results in large emission factors of combustion aerosols [START_REF] Keita | Particle and VOC emission factor measurements for anthropogenic sources in West Africa[END_REF]. Other specific sources, such as charcoal production, biomass burning, open stove and barbecue cooking, and waste burning, have a significant impact on air quality and health [START_REF] Xu | Personal exposure to PM2.5 emitted from typical anthropogenic sources in southern West Africa: Chemical characteristics and associated health risks[END_REF] in western African cities. On the other hand, aeolian mineral dust is also a large contributor to PM in the cities located downwind arid areas of the Sahel and the Sahara, such as the city of Maroua in northern Cameroon. In southern West Africa, the contribution of dust follows a seasonal cycle driven by monsoon and Harmattan flow alternations [START_REF] Knippertz | The possible role of local air pollution in climate change in West Africa[END_REF][START_REF] Léon | PM2.5surface concentrations in southern West African urban areas based on sun photometer and satellite observations[END_REF].

Over the last decade, environmental magnetism has proven its cost-effectiveness for the monitoring of atmospheric pollution [START_REF] Hofman | Biomagnetic Monitoring of Atmospheric Pollution: A Review of Magnetic Signatures from Biological Sensors[END_REF]. Magnetic properties of pumped-air filters are related to the atmospheric PM2.5 [START_REF] Leite | PM2.5 Magnetic Properties in Relation to Urban Combustion Sources in Southern West Africa[END_REF] or the nitrogen oxides (NOX) concentrations [START_REF] Saragnese | Nanometric-sized atmospheric particulate studied by magnetic analyses[END_REF]. Biocollectors-based environmental magnetism is a rapid and non-destructive way to monitor emitted particle dispersion in various environments ( [START_REF] Hofman | Biomagnetic Monitoring of Atmospheric Pollution: A Review of Magnetic Signatures from Biological Sensors[END_REF] and reference therein). Tree leaves or lichens and, to a lesser extent, tree bark, have been extensively used in recent years [START_REF] Marié | Vehicle-derived emissions and pollution on the road autovia 2 investigated by rock-magnetic parameters: A case study from Argentina[END_REF][START_REF] Sagnotti | Compositional, morphological, and hysteresis characterization of magnetic airborne particulate matter in Rome, Italy[END_REF][START_REF] Vezzola | Investigating distribution patterns of airborne magnetic grains trapped in tree barks in Milan, Italy: Insights for pollution mitigation strategies[END_REF][START_REF] Winkler | Combined magnetic, chemical and morphoscopic analyses on lichens from a complex anthropic context in Rome, Italy[END_REF][START_REF] Dunlop | Rock Magnetism: Fundamentals and Frontiers[END_REF][START_REF] Chaparro | Fine air pollution particles trapped by street tree barks: In situ magnetic biomonitoring[END_REF] as bio-monitors. Plant leaves, particularly tree leaves, can trap airborne particles, making them good passive monitors of ambient airborne pollution [START_REF] Maher | Rain and dust: Magnetic records of climate and pollution[END_REF]. Tree leaves have been used as a bio-monitor for air pollution in many cities worldwide as well as in heavily polluted areas (see [START_REF] Jordanova | Magnetic Signature of Different Vegetation Species in Polluted Environment[END_REF] for example) and with various plant species [START_REF] Rai | Monitoring of spatial variations of particulate matter (PM) pollution through bio-magnetic aspects of roadside plant leaves in an Indo-Burma hot spot region[END_REF][START_REF] Reyes | Reconnaissance environmental magnetic study of urban soils, dust and leaves from Bogotá, Colombia[END_REF][START_REF] Szönyi | A refined biomonitoring study of airborne particulate matter pollution in Rome, with magnetic measurements on Quercus Ilex tree leaves[END_REF].

The rapid development of urban areas in West Africa raises a challenge in the deployment of air quality monitoring networks. Most of the largest conurbations, and moreover, medium-sized cities, are still not equipped with standard air quality monitoring devices. Biomagnetism is a promising tool to monitor particulate pollution spatial distribution in cities with scarce observations as it is based on easy-to-implement recorders with minimal costs [START_REF] Castañeda-Miranda | Magnetic evaluation of TSP-filters for air quality monitoring[END_REF]. Moreover, to date, environmental magnetism has not been tested to assess pollution in West and Central African cities, but it has the potential to facilitate simple and inexpensive monitoring. A particularity of the western African urban environments is that they are strongly affected by dust-laden winds, which dramatically impairs air quality. Besides sophisticated chemical speciation of PM, the use of magnetic methods on passive biocollectors could be implemented to reveal the impact of transported dust on local air quality.

To answer this question, we measured magnetic susceptibility and we used magnetic parameters to infer the mineralogy in order to monitor air pollution in Maroua, a mediumsized city of northern Cameroon. We used both leaves and bark from Neem trees that are naturally present in the city to track the dispersion of airborne particles related to anthropogenic activities. In addition, the results from isothermal remanent magnetizations (IRMs) and S-ratio measurements helped to distinguish between iron oxides blown by the wind and those derived for traffic, as well as to assess the resuspension processes.

Materials and Methods

Study Area

The city of Maroua (10 • 35 N, 14 • 18 E) is located in the extreme northern area of Cameroon (Figure 1). This part of Cameroon has a Sudano-Sahelian climate characterized by an average temperature of 33 • C and an annual thermal amplitude of approximately 21 • C. The annual precipitation is approximately 800 mm. There are two contrasting climatic seasons: a short rainy season and a long dry season. The short rainy season starts in June and ends in October with a precipitation peak in August. The dry season, almost without any precipitation, extends from October to May. Between November and March, a frequent and intense wind, called Harmattan coming mostly from the North or Northeast, sweeps the region. Harmattan is a dry wind and often laden with dust particles coming from northern desertic regions.

Maroua is built in the Diamare plain bordered on the West by the Mandara Mountains. Dominant soils in the region are vertisols and ferruginous soils derived from quaternary sediments. A few fersiallitic soils of low thickness are also present, mostly derived from Neoproterozoic metagabbros and metavolcanic and metasedimentary rocks surrounding the city (i.e., metavolcanic rocks, [START_REF] Tsozué | Genesis and classification of soils developed on gabbro in the high reliefs of Maroua region, North Cameroon 2017[END_REF]). Maroua is built in the Diamare plain bordered on the West by the Mandara Mountains. Dominant soils in the region are vertisols and ferruginous soils derived from quaternary sediments. A few fersiallitic soils of low thickness are also present, mostly derived from Neoproterozoic metagabbros and metavolcanic and metasedimentary rocks surrounding the city (i.e., metavolcanic rocks, [START_REF] Tsozué | Genesis and classification of soils developed on gabbro in the high reliefs of Maroua region, North Cameroon 2017[END_REF]).

With a population of approximately 400,000, Maroua is the fifth-most populated city in Cameroon. The main economic activities are services, trade, agriculture, and craft production. Industrial activity is virtually nonexistent. Cars and motorcycles, regularly used by the population for their daily journeys, are the major sources of anthropogenic airborne With a population of approximately 400,000, Maroua is the fifth-most populated city in Cameroon. The main economic activities are services, trade, agriculture, and craft production. Industrial activity is virtually nonexistent. Cars and motorcycles, regularly used by the population for their daily journeys, are the major sources of anthropogenic airborne particle pollution in the city. In addition, wood burning and charcoal making, as in many other places in West Africa [START_REF] Keita | Particle and VOC emission factor measurements for anthropogenic sources in West Africa[END_REF] can represent a source of particulate matter [START_REF] Djossou | Mass concentration, optical depth and carbon composition of particulate matter in the major southern West African cities of Cotonou (Benin) and Abidjan (Côte d'Ivoire)[END_REF].

The sampling on the Neem trees was focused along the two main roads of Maroua, namely, "Boulevard du Renouveau" (D) (best known by the name of "Deux voies Domayo") and "Avenue Kakataré" (or "Avenue du Marché") (K). Several economic activities are concentrated on these two main roads, such as bars, restaurants, shops, joinery and street trading, thus draining important daily traffic. Boulevard du Renouveau and Avenue Kakataré are 2.60 km and 1.38 km long, respectively, and roughly east-west oriented. Located in the heart of Maroua, these two roads are separated by a distance of 0.6 to 0.9 km. Like most of the roads in Maroua, these roads are paved but locally degraded.

They are planted with rows of Neem trees on their edges (Figure 1). Additional sampling was also realized in some adjacent streets (see Figure 1). Control sites correspond to three sites located in the peripheral districts of Maroua, namely, Doualaré (site 1), Palar (site 2) and Ouro-Tchédé (site 3). The control site of Doualaré is located north of the study area, ~1.5 km from Avenue Kataré and ~2. The Neem (Azadirachta indica, A. Juss), a member of the Meliaceae family, is a tropical evergreen tree that originates from the Indian subcontinent. It is now valued worldwide as an important source of phytochemicals for use in human health and pest control. It is a hardy fast-growing small-to-medium-sized tree (7 to 15 m for mature specimens), with a straight trunk, wide and spreading branches and moderately thick, rough longitudinally fissured barks. It can tolerate high temperatures, as well as poor or degraded soil. It requires little water (450 to 1500 mm) and plenty of sunlight. The young leaves are reddish to purple, while the mature leaves are bright green, consisting of petiole, lamina, and the base that attaches the leaf to the stem and may bear two small lateral leaf-like structures known as stipules [START_REF] Ogbuewu | The growing importance of neem (Azadirachta indica A. Juss) in agriculture, industry, medicine and environment: A review[END_REF][START_REF] Forim | Processo de Obtenção de Nanopartículas Biopoliméricas Contendo Óleo e Extratos de Azadirachta Indica a. Juss (neem)[END_REF].

Sampling

A total of 435 leaf samples and 109 bark samples of Neem trees were collected from Boulevard du Renouveau, Avenue Kakataré, and adjacent streets (Figures 1 and2). Leaf and bark samples were also collected in the control sites far from the urban center, where traffic concentration is low (Figure 1). Site 1 is located in an almost uninhabited sector, and sites 2 and 3 are located in a semi-rural area.

Magnetic Measurements and Microscopic Observations.

Magnetic measurements were carried out in the Geosciences Environnement Toulouse (GET) laboratory in France.

Bulk mass magnetic susceptibilities were measured for all samples using a KLY-3S Samples were collected on trees on both sides of the roads at ~100 m spacing for leaves and 200 m spacing for bark. Four sampling campaigns were conducted on the same trees from August to December 2014 to monitor potential seasonal variability. The first (A) and second (B) sampling campaigns were carried out in mid-August and at the end of September, respectively, i.e., during the rainy season, while the last two (C and D) were completed during the dry season, in mid-November and at the end of December, respectively. The collection of bark was only performed during the first (A) (August) and third (C) (November) campaigns. Samples were collected using nonmagnetic packaging (paper or plastic). They were taken at different heights, between 1 and 1.5 meters from the ground for the bark and 1.5 and 2.5 meters for the leaves. These heights were chosen to represent the mean breathing exposure for pedestrians. Leaves were taken at the lowest possible level. During the rainy season, samplings were performed one or two days after the last precipitation.

The samples, unwashed, were dried for 3 to 4 days at constant temperature of 45 • C in a drying oven at the University of Maroua (Cameroon). The dried leaves and bark were subsequently crushed by hand.

Magnetic Measurements and Microscopic Observations

Magnetic measurements were carried out in the Geosciences Environnement Toulouse (GET) laboratory in France.

Bulk mass magnetic susceptibilities were measured for all samples using a KLY-3S Kappabridge (AGICO, Brno).

Isothermal remanent magnetizations (IRMs) were acquired for a total of 43 leaf and bark samples. IRMs were induced using a Pulse Magnetizer (Magnetic Measurements) and measured using a JR5 magnetometer (AGICO, Brno). The JR5 spinner magnetometer has a sensibility of 2.4 × 10 -6 A/m (AGICO manual specification). Its use may prevent an accurate determination of the magnetization for very weak samples.

Reverse IRMs at 300 mT (IRM-300 mT) were acquired to calculate the S ratio, which is given by IRM-300 mT/SIRM [START_REF] King | Sedimentary Magnetism, Environmental Magnetism, and Magnetostratigraphy[END_REF].

IRM acquisition curves were obtained on 7 leaf and 7 bark samples. IRM acquisitions were analyzed using the curve-fitting program MAX UnMix [START_REF] Maxbauer | UnMix: A web application for unmixing magnetic coercivity distributions[END_REF] (available online at http: //www.irm.umn.edu/maxunmix, accessed on 7 July 2021), based on analyses developed by [START_REF] Kruiver | Quantification of magnetic coercivity components by the analysis of acquisition curves of isothermal remanent magnetisation[END_REF][START_REF] Heslop | Analysis of isothermal remanent magnetization acquisition curves using the expectation-maximization algorithm[END_REF][START_REF] Egli | Characterization of individual rock magnetic components by analysis of remanence curves. 2. Fundamental properties of coercivity distributions[END_REF]. This software uses skew-normal distributions that can be described with a mean coercivity (Bh), a dispersion parameter (DP, equivalent to one standard deviation in log-space), and a skewness factor (S). The magnetic mineralogy is interpreted from the range of coercivities derived from the IRM parameters.

Magnetic particles were investigated in situ by electron microscopy and imaged using a JEOL (JSM-6300 scanning electron microscope (SEM) housed at the GET laboratory (Toulouse, France) operating at 20 keV with an electron dispersive system (EDS) that allows for a rapid qualitative characterization of the chemical composition.

Results

Magnetic Content

Mass susceptibility (χ) is commonly used as a proxy for the concentration of magnetic minerals and mainly magnetite [START_REF] Dunlop | Rock Magnetism: Fundamentals and Frontiers[END_REF]. The three control area sites present "near-zero" susceptibility values between -5 and 5.3 × 10 -9 m 3 kg -1 (Figure 3), reflecting the dominance of the diamagnetism of the leaves and bark themselves as organic compounds.

For downtown Maroua, considering all campaigns together, mass susceptibilities (χ) range between 42.5 × 10 -9 m 3 kg -1 and 577.4 × 10 -9 m 3 kg -1 for leaves and between 2.0 × 10 -9 m 3 kg -1 and 64.0 × 10 -9 m 3 kg -1 for bark samples (Figure 3). For both bark and leaves, magnetic susceptibility values are higher in the main streets than in their adjacent secondary streets.

the diamagnetism of the leaves and bark themselves as organic compounds.

For downtown Maroua, considering all campaigns together, mass susceptib range between 42.5 × 10 -9 m 3 kg -1 and 577.4 × 10 -9 m 3 kg -1 for leaves and between 2.0 × 10 and 64.0 × 10 -9 m 3 kg -1 for bark samples (Figure 3). For both bark and leaves, m susceptibility values are higher in the main streets than in their adjacent secondar Leaf χ values display high variability (Figure 2) depending on the street ty main or secondary roads) and the season (dry versus rainy). Overall, the χ value nificantly higher than those recorded in the control areas (Figure 3). Additionally the high intrinsic variability observed (Figures 2 and3 Leaf χ values display high variability (Figure 2) depending on the street types (i.e., main or secondary roads) and the season (dry versus rainy). Overall, the χ values are significantly higher than those recorded in the control areas (Figure 3). Additionally, despite the high intrinsic variability observed (Figures 2 and3), leaf samples taken during the dry season give significantly higher χ values than those taken during the rainy season for a given road. Leaves taken during the dry season on the main streets show the highest recorded χ values up to 221 × 10 -9 m 3 kg -1 (discarding an extreme value of 577 × 10 -9 m 3 kg -1 , probably reflecting uncontrolled contamination). Comparing main and secondary streets, for Kakataré Avenue, for example, a mean χ value of 58.5 ± 36.5 × 10 -9 m 3 kg -1 is recorded during campaign C (dry season) versus a mean value of 28.8 ± 19.7 × 10 -9 m 3 kg -1 for its secondary streets. During the wet season, leaves from Kakataré Avenue and its secondary streets display mean χ values of 11.00 ± 5.8 × 10 -9 m 3 kg -1 and 2.6 ± 11.2 × 10 -9 m 3 kg -1 , respectively. Domayo Avenue displays a higher and more complex variability in magnetic susceptibility. Nevertheless, as for the Kataré Avenue, higher χ values are found during the dry season than during the rainy season. Magnetic susceptibilities are similarly greater on the main road than in the secondary street network independently of the season. It may be noted that leaves from the streets cutting Kakataré Avenue display greater χ values than those near Domayo Avenue. The χ values from the secondary streets intersecting Domayo Avenue present close-to-zero values in the same range as the control sites.

In contrast, bark χ values display similar values between the dry and wet seasons (Figure 3). For instance, the average values for Avenue K vary from 33.0 ± 14.0 × 10 -9 m 3 kg -1 for the wet season to 34.3 ± 17.8 × 10 -9 m 3 kg -1 for the dry season. Magnetic susceptibility values for bark are less influenced by climatic conditions. The mean χ values in the urban area are significantly higher than those in the control area (down to -0.3 ± 1.6 × 10 -9 m 3 kg -1 ) for both the main and secondary streets (Figures 2 and3). Bark χ is greater for main avenues than secondary intersecting streets.

Isothermal remanent magnetization (IRM) is another parameter that can reflect the concentration of magnetic particles. Here, IRM@2T comprised between 3.52 × 10 -5 and 1.13 × 10 -3 Am 2 kg -1 and between 4.26 × 10 -5 and 3.18 × 10 -4 Am 2 kg -1 for the leaves and bark, respectively. IRM@2T and χ display linear correlations (Figure 4), indicating that IRM roughly reflects mainly the low to moderate coercivity magnetite-like content, at least for χ less than 120 × 10 -9 m 3 kg -1 . However, IRM can also be influenced by the magnetic composition and grain size, as we will discuss in the next section. Due to the increase in the intensity of the measurable signal linked to the IRM@2T procedure, this parameter allows qualifying the number of magnetic minerals when χ is close to the limit of detection as in the control areas.

bility values for bark are less influenced by climatic conditions. The mean χ va urban area are significantly higher than those in the control area (down to -0.3 m 3 kg -1 ) for both the main and secondary streets (Figures 2 and3). Bark X is main avenues than secondary intersecting streets.

Isothermal remanent magnetization (IRM) is another parameter that can concentration of magnetic particles. Here, IRM@2T comprised between 3.52 1.13 × 10 -3 Am 2 kg -1 and between 4.26 × 10 -5 and 3.18 × 10 -4 Am 2 kg -1 for the bark, respectively. IRM@2T and χ display linear correlations (Figure 4), indi IRM roughly reflects mainly the low to moderate coercivity magnetite-like cont for χ less than 120 × 10 -9 m 3 kg -1 . However, IRM can also be influenced by th composition and grain size, as we will discuss in the next section. Due to the the intensity of the measurable signal linked to the IRM@2T procedure, this allows qualifying the number of magnetic minerals when χ is close to the limit o as in the control areas. In the two control sites measured, sites 2 and 3, IRMs@2T obtained on bark samples (2 samples) did not present any significant differences between the dry and wet seasons (Figure 5). In contrast, leaves show a relatively significant increase in magnetic content during the dry season (Figure 5). It can also be noted that the values of IRM@2T from control areas are two orders of magnitude lower than those from the urban area.

(Figure 5). In contrast, leaves show a relatively significant increase in magnetic conten during the dry season (Figure 5). It can also be noted that the values of IRM@2T from control areas are two orders of magnitude lower than those from the urban area.

Magnetic Characterization

The shape of the IRM acquisition curves reflects the magnetic mineralogy. The com parison of sites from the Avenue Kakatare/Domayo (12 samples) and one control site (sit 3, 2 samples) indicates the presence of both moderate coercivity magnetic minerals (mag netite-type, including maghemite and Ti-magnetite) and high coercivity magnetic mine als (hematite/goethite) (Figure 6). We perform an analysis of the IRM acquisition curves [START_REF] Maxbauer | UnMix: A web application for unmixing magnetic coercivity distributions[END_REF] t better estimate the different components. The moderate coercivity component is charac terized by a mean coercivity (Bh) between 44 and 80 mT, with the dispersion paramete (DP) decreasing from 0.49 to 0.39 while Bh increases. High DP (>0.45) could indicate th presence of a low and a moderate coercivity component. Accurate determination of low coercivity components is hampered by the fact that the acquisitions were performed wit only 20 acquisition steps with the objective of identifying the presence of high coercivit minerals. The high coercivity component is difficult to extract because its Bh is sometime greater than the maximum field applied (2 T). When reasonably identifiable, the high co ercivity component displays Bh values superior to 2000 mT (see Figure 6), which probabl corresponds to goethite [START_REF] Rochette | Field and temperature behavior of remanence in synthetic goethite: Paleomagnetic implications[END_REF][START_REF] Abrajevitch | Variations in relative abundances of goethite and hematite in Bengal Fan sediments: Climatic vs. diagenetic signals[END_REF][START_REF] Itambi | Magnetic mineral inventory of equatorial Atlantic Ocean marine sediments off Senegal-glacial and interglacial contrast[END_REF] or fine-grained hematite [START_REF] Rochette | Non-saturation of the defect moment of goethite and fine-grained hematite up to 57 Teslas[END_REF].

Magnetic Characterization

The shape of the IRM acquisition curves reflects the magnetic mineralogy. The comparison of sites from the Avenue Kakatare/Domayo (12 samples) and one control site (site 3, 2 samples) indicates the presence of both moderate coercivity magnetic minerals (magnetite-type, including maghemite and Ti-magnetite) and high coercivity magnetic minerals (hematite/goethite) (Figure 6). We perform an analysis of the IRM acquisition curves [START_REF] Maxbauer | UnMix: A web application for unmixing magnetic coercivity distributions[END_REF] to better estimate the different components. The moderate coercivity component is characterized by a mean coercivity (Bh) between 44 and 80 mT, with the dispersion parameter (DP) decreasing from 0.49 to 0.39 while Bh increases. High DP (>0.45) could indicate the presence of a low and a moderate coercivity component. Accurate determination of low coercivity components is hampered by the fact that the acquisitions were performed with only 20 acquisition steps with the objective of identifying the presence of high coercivity minerals. The high coercivity component is difficult to extract because its Bh is sometimes greater than the maximum field applied (2 T). When reasonably identifiable, the high coercivity component displays Bh values superior to 2000 mT (see Figure 6), which probably corresponds to goethite [START_REF] Rochette | Field and temperature behavior of remanence in synthetic goethite: Paleomagnetic implications[END_REF][START_REF] Abrajevitch | Variations in relative abundances of goethite and hematite in Bengal Fan sediments: Climatic vs. diagenetic signals[END_REF][START_REF] Itambi | Magnetic mineral inventory of equatorial Atlantic Ocean marine sediments off Senegal-glacial and interglacial contrast[END_REF] or fine-grained hematite [START_REF] Rochette | Non-saturation of the defect moment of goethite and fine-grained hematite up to 57 Teslas[END_REF].

The relative proportion of high coercivity versus moderate coercivity magnetic minerals varies as a function of sites and differs between leaves and bark. High coercivity minerals are slightly more represented in bark samples and in control areas. To further investigate this trend, we use the S-ratio, which is a sensitive parameter for estimation of the relative proportion of hematite and goethite versus magnetite in terms of magnetic remanence (see, for example, [START_REF] Frank | Mineral magnetic properties of artificial samples systematically mixed from haematite and magnetite[END_REF]). Values approaching 1 indicate the dominance of magnetite on the magnetic signal. In Maroua, this ratio varies from 0.79 to 0.98 for both leaves and bark. While this ratio indicates that the magnetite-like signal is preponderant, this ratio also evidenced the important abundance of hematite [START_REF] Frank | Mineral magnetic properties of artificial samples systematically mixed from haematite and magnetite[END_REF]. There is no identifiable difference between the dry and wet seasons. Figure 7 presents the mean S-ratio by sector and all campaigns combined. It shows that the high coercivity component increases toward zones with lower traffic, with the lowest values of S-ratio found in control areas sites (Figure 7). Bark samples present lower S-ratios than leaf samples at all sites. This indicates that their IRMs are influenced by both a moderate (magnetite-like) component and a high coercivity (hematite/goethite) component. Conversely, the hematite/goethite component is only detectable for leaves in the control areas. In the Maroua streets (main and secondary), the magnetite-like signature is dominant.

SEM Observation

We analyzed eight samples under the SEM comprising six leaves and two bark samples (Figures 8 and9). The observation of the PM content shows that large detrital particles (> to 10 microns) dominate (Figures 8a,b). They can form clusters on some leaves (Figure 8a). EDS spectra (Figures 8e,f and9b,d,f) reveal mainly Mg, Al, Ti, Si and Fe in these particles. Fe-rich particles are not very common and relatively small (<10 microns).

An apparently spherical magnetite (Figure 8c,d) that could be a typical spherule derived from combustion processes [START_REF] Spiteri | Magnetic screening of a pollution hotspot in the Lausitz area, Eastern Germany: Correlation analysis between magnetic proxies and heavy metal contamination in soils[END_REF][START_REF] Lu | Magnetic properties as indicators of heavy metals pollution in urban topsoils: A case study from the city of Luoyang, China[END_REF][START_REF] Gautam | Environmental magnetic approach towards the quantification of pollution in Kathmandu urban area, Nepal[END_REF] is observed in sample DD48 from Domayo Avenue. This sample, taken during the dry season, displays a high magnetic susceptibility of 143 x10 -9 m 3 kg -1 . Apart from this occurrence, in all observed samples, Fe-oxides and nonspherical iron-rich particles are dominant, and magnetic spherules are almost absent. This indicates that non-exhaust emissions related to brakes and tyres prevail [START_REF] Winkler | Magnetic emissions from brake wear are the major source of airborne particulate matter bioaccumulated by lichens exposed in Milan (Italy)[END_REF]. Figures 9e,g present irregular and platy Fe-rich particles. In some cases, Fe-rich particles are associated with Pb (Figure 9c,d). Although aeolian dust may occasionally contain Pb [START_REF] Grousset | Tracing dust sources and transport patterns using Sr, Nd and Pb isotopes[END_REF], this association clearly indicates an anthropogenic origin (see, e.g., [START_REF] Hassan | Chemical characteristics of atmospheric PM2.5 loads during air pollution episodes in Giza, Egypt[END_REF][START_REF] Tang | Characteristics of major elements and heavy metals in atmospheric dust in Beijing, China[END_REF]).

SEM Observation

We analyzed eight samples under the SEM comprising six leaves and two bark samples (Figures 8 and9). The observation of the PM content shows that large detrital particles (> to 10 microns) dominate (Figure 8a,b). They can form clusters on some leaves (Figure 8a). EDS spectra (Figures 8e,f and9b,d,f) reveal mainly Mg, Al, Ti, Si and Fe in these particles. Fe-rich particles are not very common and relatively small (<10 microns).

An apparently spherical magnetite (Figure 8c,d) that could be a typical spherule derived from combustion processes [START_REF] Spiteri | Magnetic screening of a pollution hotspot in the Lausitz area, Eastern Germany: Correlation analysis between magnetic proxies and heavy metal contamination in soils[END_REF][START_REF] Lu | Magnetic properties as indicators of heavy metals pollution in urban topsoils: A case study from the city of Luoyang, China[END_REF][START_REF] Gautam | Environmental magnetic approach towards the quantification of pollution in Kathmandu urban area, Nepal[END_REF] is observed in sample DD48 from Domayo Avenue. This sample, taken during the dry season, displays a high magnetic susceptibility of 143 × 10 -9 m 3 kg -1 . Apart from this occurrence, in all observed samples, Fe-oxides and non-spherical iron-rich particles are dominant, and magnetic spherules are almost absent. This indicates that non-exhaust emissions related to brakes and tyres prevail [START_REF] Winkler | Magnetic emissions from brake wear are the major source of airborne particulate matter bioaccumulated by lichens exposed in Milan (Italy)[END_REF]. Figure 9e,g present irregular and platy Fe-rich particles. In some cases, Fe-rich particles are associated with Pb (Figure 9c,d). Although aeolian dust may occasionally contain Pb [START_REF] Grousset | Tracing dust sources and transport patterns using Sr, Nd and Pb isotopes[END_REF], this association clearly indicates an anthropogenic origin (see, e.g., [START_REF] Hassan | Chemical characteristics of atmospheric PM2.5 loads during air pollution episodes in Giza, Egypt[END_REF][START_REF] Tang | Characteristics of major elements and heavy metals in atmospheric dust in Beijing, China[END_REF]).

Discussion

Anthropogenic Pollution and Traffic-Related Particles

The aim of the approach presented here is to develop a method applicable to endemic tree species with an easy sampling of many biocollectors that can be applied in mediumsized cities where monitoring stations are sparse or nonexistent. We tested it for the city of Maroua, where different concentrations and types of magnetic airborne particles are found in the considered urban microenvironments (main, secondary roads and control areas) that can be tracked in the magnetic signal.

Control sites display mostly near-zero or negative χ values. Such values are attributed to the dominance of the diamagnetism of the leaves and bark themselves as organic compounds. They were chosen, far from anthropogenic sources (Figure 1), as witnesses of the lithic input. This lithic input exhibits a weak ferrimagnetic signal. Magnetic susceptibilities and hence magnetic particle contents increase toward zones with more human activities and traffic. This strongly suggests that most ferrimagnetic particles detected by magnetic susceptibility measurements originate from anthropic activities and not from wind-borne mineral dust.

Mineral dust transported over western Africa is known to be rich in iron oxides, mainly hematite and goethite [START_REF] Formenti | Dominance of goethite over hematite in iron oxides of mineral dust from Western Africa: Quantitative partitioning by X-ray absorption spectroscopy[END_REF][START_REF] Lyons | Mineral magnetic properties of surface soils and sands across four North African transects and links to climatic gradients[END_REF][START_REF] Larrasoaña | Environmental magnetic fingerprinting of anthropogenic and natural atmospheric deposition over southwestern Europe[END_REF]. Goethite seems to dominate in all regions [START_REF] Formenti | Dominance of goethite over hematite in iron oxides of mineral dust from Western Africa: Quantitative partitioning by X-ray absorption spectroscopy[END_REF][START_REF] Ohta | Chemical compositions and XANES speciations of Fe, Mn and Zn from aerosols collected in China and Japan during dust events[END_REF][START_REF] Prietzel | Iron speciation in soils and soil aggregates by synchrotron-based X-ray microspectroscopy (XANES, µ-XANES)[END_REF], although magnetic methods may be more sensitive to hematite content [START_REF] Larrasoaña | Source-to-sink magnetic properties of NE saharan dust in Eastern Mediterranean marine sediments: Review and paleoenvironmental implications[END_REF]. In Maroua, the S-ratio results (see Figure 7) show increasing hematite/goethite proportion toward areas with less traffic, strongly suggesting that these minerals are part of the natural regional lithic dust component that can be wind-blown. The presence of iron-rich oxides incorporating Ti (Figure 9a,b) also indicates a lithic origin of some of the iron-rich particles, in accordance with the regional geology. However, their occurrence is very scarce in both bark and leaf samples (Figure 3), inducing only weak magnetic susceptibility. Therefore, observed variations in magnetic susceptibility are interpreted as reflecting mostly the anthropogenic contribution of the urban magnetic dust that masks the magnetic lithic fraction. This demonstrates that magnetic methods are a useful tool to monitor urban particulate pollution even in environments affected by Saharan dust and not only in megacities. Traffic is the main source of magnetic particles in downtown Maroua, since neither industrial plants nor mining sites are present. Motorcycles represent an important part of circulating vehicles, as in other African cities. Particulate emissions from these vehicles are different from those of diesel engines, mainly due to the lubricating oil permanently added in two-stroke engines [START_REF] Rijkeboer | Particulate matter regulation for two-stroke two wheelers: Necessity or haphazard legislation?[END_REF]. Two-stroke engines release a large amount of both particles and gases [START_REF] Etissa | Investigation of particles emitted from modern 2-stroke scooters[END_REF]. For instance, two-stroke motorcycles have been shown to emit more ultrafine particles (see a review in [START_REF] Zuurbier | The contribution of moped emissions to ultrafine and fine particle concentrations on bike lanes[END_REF][START_REF] Leong | Influence of benzene emission from motorcycle on Bangkok air quality[END_REF]). This could explain the large magnetic susceptibility values obtained in Maroua. Comparing the magnetic susceptibility data obtained on deciduous and evergreen leaves in some other cities, the values obtained in Maroua fall within the range of high traffic zones of diverse cities (see Table 1). However, variations occurring in the two main streets, especially very high magnetic susceptibility values near the eastern part of Domayo Avenue, require additional sources other than traffic to explain them. These values are found close to restaurants and shops with no evident traffic density variations compared to the rest of the avenue. This artisanal activity involves open stoves (sometimes giant) or other types of wood/coal burning (Figure 1) [START_REF] Djossou | Mass concentration, optical depth and carbon composition of particulate matter in the major southern West African cities of Cotonou (Benin) and Abidjan (Côte d'Ivoire)[END_REF]. The burning of wood and coal in connection with cooking on an open stove next to the street (and trees) could represent an additional provider of magnetite particles, thus explaining the higher values. Indeed, coal generally contains a high Fe content [START_REF] Kabir | Trace metal contents in barbeque (BBQ) charcoal products[END_REF], which results in a high iron oxide content in the fly ashes from coal combustion [START_REF] Leite | PM2.5 Magnetic Properties in Relation to Urban Combustion Sources in Southern West Africa[END_REF][START_REF] Smeda | Application of sequential extraction and the ICP-AES method for study of the partitioning of metals in fly ashes[END_REF]. As the building material of the stove contains iron itself, it may also contribute to the magnetic particle load. Urban wood burning can release a substantial quantity of PM2.5 particles [START_REF] Xu | Personal exposure to PM2.5 emitted from typical anthropogenic sources in southern West Africa: Chemical characteristics and associated health risks[END_REF][START_REF] Ries | Intake fraction of urban wood smoke[END_REF] containing magnetite [START_REF] Leite | PM2.5 Magnetic Properties in Relation to Urban Combustion Sources in Southern West Africa[END_REF][START_REF] Mcclean | Contributions of wood ash magnetism to archaeomagnetic properties of fire pits and hearths[END_REF]. For example, it has been shown that winter wood burning for indoor heating represents an important part of the total suspended particles in some North American cities [START_REF] Ries | Intake fraction of urban wood smoke[END_REF].

SEM observations reveal that large amounts of detrital particles are trapped in both bark and leaves in all places from the control area to the busiest streets of Maroua. The occurrence of magnetic spherules, typical of traffic-related emissions, is very low compared to data on lichens and bark obtained from other cities [START_REF] Chaparro | Biomonitors of urban air pollution: Magnetic studies and SEM observations of corticolous foliose and microfoliose lichens and their suitability for magnetic monitoring[END_REF][START_REF] Suzuki | Characterisation of airborne particulates and associated trace metals deposited on tree bark by ICP-OES, ICP-MS, SEM-EDX and laser ablation ICP-MS[END_REF]. However, if microscopic observations and detections of anthropogenic iron oxides are difficult due to the amount of mineral dust, magnetic measurements allow a clear determination of their relative amount.

Neem Bark and Leaves as Complementary Biocollectors

Climate and leaf types are known to affect the magnetic record on trees [START_REF] Sagnotti | Compositional, morphological, and hysteresis characterization of magnetic airborne particulate matter in Rome, Italy[END_REF][START_REF] Szönyi | A refined biomonitoring study of airborne particulate matter pollution in Rome, with magnetic measurements on Quercus Ilex tree leaves[END_REF][START_REF] Kardel | Leaf saturation isothermal remanent magnetization (SIRM) as a proxy for particulate matter monitoring: Inter-species differences and in-season variation[END_REF][START_REF] Mitchell | Rates of particulate pollution deposition onto leaf surfaces: Temporal and inter-species magnetic analyses[END_REF][START_REF] Rodríguez-Germade | The influence of weather and climate on the reliability of magnetic properties of tree leaves as proxies for air pollution monitoring[END_REF]. Neems are evergreen trees; thus, both bark and leaves can be considered permanent or at least with a lifespan greater than one year for the leaves. In Maroua, leaves and bark dissimilarly record both the ambient airborne particle content and the seasonality effect. The bark displays similar magnetic susceptibility values throughout the year, while for leaf records, low values are observed during the wet season and higher values are observed during the dry season. This observation is valid in all zones, from the busiest streets to the control areas. Thus, bark and leaves must be considered two different types of biocollectors: season-dependent for the leaves and season-independent for the bark.

As magnetic parameters reflect the concentration of magnetic particles, i.e., χ and IRM, data obtained from bark and leaves, cannot be directly compared. First, the time during which particles are collated on both biocollectors is probably different. Second, mass normalization does not compensate in the same way for each collector. The surface area per surface unit (or per mass unit), where magnetic particles can be trapped, is different for bark and leaves. Bark has surface rugosity and porosity, preventing important rain washing. This probably allows particles to be efficiently trapped. Particles trapped on the bark appear to have reached a stable balance over time between trapping and release, as evidenced by their relative stability throughout the year.

On leaves, the sequestration of particulate matter and, more specifically, of magnetic particulate matter, depends on their surface morphology [START_REF] Muhammad | Atmospheric net particle accumulation on 96 plant species with contrasting morphological and anatomical leaf characteristics in a common garden experiment[END_REF]. For example, Kardel et al. [START_REF] Kardel | Leaf saturation isothermal remanent magnetization (SIRM) as a proxy for particulate matter monitoring: Inter-species differences and in-season variation[END_REF] and Mitchell et al. [START_REF] Mitchell | Rates of particulate pollution deposition onto leaf surfaces: Temporal and inter-species magnetic analyses[END_REF] showed that hairy leaves trapped more magnetic particles than smoother leaves did. It has also been proposed that leaf structure or their waxy protec-tive layer could incorporate part of the magnetic particulate matter [START_REF] Sagnotti | Compositional, morphological, and hysteresis characterization of magnetic airborne particulate matter in Rome, Italy[END_REF][START_REF] Urbat | Biomonitoring of air quality in the Cologne conurbation using pine needles as a passive sampler-Part I: Magnetic properties[END_REF], potentially accounting for up to half of the magnetic susceptibility signal [START_REF] Szönyi | A refined biomonitoring study of airborne particulate matter pollution in Rome, with magnetic measurements on Quercus Ilex tree leaves[END_REF].

In terms of temporal dynamics, Rodríguez-Germade et al. [START_REF] Rodríguez-Germade | The influence of weather and climate on the reliability of magnetic properties of tree leaves as proxies for air pollution monitoring[END_REF] described a constant gradual increase in PM concentrations on Platanus Hispanica tree leaves using magnetic parameters. Conversely, for Mitchell et al. [START_REF] Mitchell | Rates of particulate pollution deposition onto leaf surfaces: Temporal and inter-species magnetic analyses[END_REF], particles gradually accumulate on the surfaces of deciduous tree leaves until a dynamic equilibrium between particle deposition and particle loss is reached. This equilibrium is reached rapidly, on the order of 6 days, for birch and lime trees [START_REF] Mitchell | Rates of particulate pollution deposition onto leaf surfaces: Temporal and inter-species magnetic analyses[END_REF], whereas it is reached after 26 months for pine needles [START_REF] Lehndorff | Accumulation histories of magnetic particles on pine needles as function of air quality[END_REF]. Neem leaves, being smooth and oily, probably combine particle entrapment in their foliar structure and dynamic equilibrium on the outer leaf surface.

Climatic variations are the most obvious candidate to explain differences in the leaf records between dry and wet seasons. During the rainy season, both the atmosphere and ground are washed by precipitation, meaning that the air contains fewer particles from the vehicles themselves and the resuspension phenomena [START_REF] De La Paz | Implementation of road dust resuspension in air quality simulations of particulate matter in Madrid (Spain)[END_REF]. The leaching of leaves during the wet season can also be invoked. Indeed, Rodríguez-Germade et al. [START_REF] Rodríguez-Germade | The influence of weather and climate on the reliability of magnetic properties of tree leaves as proxies for air pollution monitoring[END_REF] showed that meteorological conditions, particularly air humidity, control the relative influence of pollutants, lithic dust and biological effects on the magnetic record of tree leaves. The rain leaching of particles deposited on leaves has been described in various cities [START_REF] Szönyi | A refined biomonitoring study of airborne particulate matter pollution in Rome, with magnetic measurements on Quercus Ilex tree leaves[END_REF][START_REF] Rodríguez-Germade | The influence of weather and climate on the reliability of magnetic properties of tree leaves as proxies for air pollution monitoring[END_REF][START_REF] Matzka | Magnetic biomonitoring of roadside tree leaves: Identification of spatial and temporal variations in vehicle-derived particulates[END_REF][START_REF] Mcintosh | The magnetic properties of particles deposited on Platanus x hispanica leaves in Madrid, Spain, and their temporal and spatial variations[END_REF][START_REF] Mitchell | Evaluation and application of biomagnetic monitoring of traffic-derived particulate pollution[END_REF][START_REF] Prajapati | Monitoring of vehicles derived particulates using magnetic properties of leaves[END_REF]. However, for evergreen trees, some authors argue that rainfall has little influence [START_REF] Szönyi | A refined biomonitoring study of airborne particulate matter pollution in Rome, with magnetic measurements on Quercus Ilex tree leaves[END_REF][START_REF] Moreno | Biomonitoring of traffic air pollution in Rome using magnetic properties of tree leaves[END_REF], such as pine needles [START_REF] Urbat | Biomonitoring of air quality in the Cologne conurbation using pine needles as a passive sampler-Part I: Magnetic properties[END_REF][START_REF] Lehndorff | Accumulation histories of magnetic particles on pine needles as function of air quality[END_REF], because magnetic particles are trapped in the wax layer that covers the leaf or are adsorbed by the leaf via the stomatal cavities [START_REF] Urbat | Biomonitoring of air quality in the Cologne conurbation using pine needles as a passive sampler-Part I: Magnetic properties[END_REF]. In the case of the Neem leaves sampled in Maroua, the significant differences in magnetic grain content between the dry and wet seasons imply an observable washing effect of the heavy rains that spread throughout the region between July and September.

Using the IRM data, S-ratio and SEM observations, the ratio between the mineral dust component and the anthropogenic component can be compared between bark and leaves. Leaves appear to be dominated by traffic-related particles when taken near main and connected streets. They do not display a clear hematite/goethite component. Instead, they show magnetite-like particle dominance on the magnetic signal (as evidenced by the S-ratio). Conversely, bark always presents a small hematite/goethite component even in the busiest part.

The presence of this natural lithic dust fraction in the magnetic signal on the bark and not on the leaves can be due to the difference in the mean sampling height of each collector. Bark was sampled between 1 and 1.5 m away, while the height of leaf sampling was between 1.5 and 2.5 m. Bark can, therefore, be more impacted by a resuspension component. Maroua sidewalks and secondary roads are not always paved, and a substantial amount of lithic dust covers all surfaces (including main roads). Especially during the dry season, dust brought by both the wind and the traffic is deposited on the ground. Then, dust is resuspended by the wind itself and by the passing vehicles. The resuspension of dust in urban environments can significantly increase exposure to traffic-related particles [START_REF] Abu-Allaban | Tailpipe, resuspended road dust, and brake-wear emission factors from on-road vehicles[END_REF]. For example, Meza-Figueroa et al. [START_REF] Meza-Figueroa | Traffic signatures in suspended dust at pedestrian levels in semiarid zones: Implications for human exposure[END_REF] have shown that in a medium-sized city of a Mexican state with a semi-arid climate, humidity is the controlling factor for the concentration of suspended particles, with the highest values occurring during the dry season. They emphasize the fact that the effect is maximum at the pedestrian level and that suspended particulate matter filter data must take that into account for the assessment of human exposure to traffic-related particles in a semi-arid climate. In our study, heights sampled by bark and leaves allow this exposure to be taken into account qualitatively, with the bark representing the pedestrian level.

Another explanation could be a difference in PM accumulation capacity of leaves and bark. Indeed, Xu et al. [START_REF] Xu | Atmospheric particulate matter accumulation on trees: A comparison of boles, branches and leaves[END_REF] showed that stem bark tends to accumulate a greater proportion of large particles compared to leaves. This could also explain the difference in the relationship between magnetic susceptibility and IRM@2T (Figure 2).

It is worth noting that both types of biocollectors, bark and leaves, indicate the same variations in magnetic particle concentrations related to anthropogenic activities across the city. This makes them both reliable for environmental studies. However, it should be kept in mind that collector types may induce a difference in recording due to the biocollectors specific trapping capacities (see [START_REF] Chaparro | Fine air pollution particles trapped by street tree barks: In situ magnetic biomonitoring[END_REF][START_REF] Paoli | Magnetic properties and element concentrations in lichens exposed to airborne pollutants released during cement production[END_REF]).

To compare the values obtained here with other cities and various leaf types, we compile data of magnetic susceptibility values obtained on leaves from different cities (Table 1, [START_REF] Reyes | Reconnaissance environmental magnetic study of urban soils, dust and leaves from Bogotá, Colombia[END_REF][START_REF] Szönyi | A refined biomonitoring study of airborne particulate matter pollution in Rome, with magnetic measurements on Quercus Ilex tree leaves[END_REF][START_REF] Rodríguez-Germade | The influence of weather and climate on the reliability of magnetic properties of tree leaves as proxies for air pollution monitoring[END_REF][START_REF] Urbat | Biomonitoring of air quality in the Cologne conurbation using pine needles as a passive sampler-Part I: Magnetic properties[END_REF][START_REF] Lehndorff | Accumulation histories of magnetic particles on pine needles as function of air quality[END_REF][START_REF] Moreno | Biomonitoring of traffic air pollution in Rome using magnetic properties of tree leaves[END_REF][START_REF] Gautam | Magnetic susceptibility of dust-loaded leaves as a proxy of traffic-related heavy metal pollution in Kathmandu city, Nepal[END_REF][START_REF] Norouzi | Biomagnetic monitoring of heavy metals contamination in deposited atmospheric dust, a case study from Isfahan, Iran[END_REF][START_REF] Sant'ovaia | Particle pollution-An environmental magnetism study using biocollectors located in northern Portugal[END_REF]. We report, when available, the lowest-highest individual value and mean values. Individual values and means are not directly comparable since they depend on the sampling strategy (trees from various distances of the road, areas of the city and exposure times). We choose to take the highest average provided by the authors. Sometimes this represents only a specific road section or only one of the sampling campaigns carried out. It appears that the data obtained on persistent leaves are generally higher than those on deciduous leaves (Table 1). For example, in Rome, Moreno et al. [START_REF] Moreno | Biomonitoring of traffic air pollution in Rome using magnetic properties of tree leaves[END_REF] specifically compared the leaves of deciduous plane trees with those of Q. ilex, an evergreen oak species. They found that magnetic susceptibility values obtained on Q. ilex leaves were consistently higher on low/moderate and high traffic roads. Sant'Ovaia [START_REF] Sant'ovaia | Particle pollution-An environmental magnetism study using biocollectors located in northern Portugal[END_REF] made a similar comparison in Porto by sampling evergreen leaves of Nerium and deciduous leaves of Quercus spp. and Platanus spp. (plane tree). Oaks showed higher values than plane trees and Nerium did. The authors attributed these differences to the presence of trichomes. However, it can be noted that if the oaks and the plane trees are located in the central reservation of a busy road, the Nerium is located a few meters away at the edge of the same road, which hinders a direct comparison.

If we compare only data from deciduous leaves, magnetic susceptibility values obtained on Maroua's leaves are in the same range as data obtained in Portugal (Porto, Braga and Valongo, [START_REF] Sant'ovaia | Particle pollution-An environmental magnetism study using biocollectors located in northern Portugal[END_REF]) and Nanjing (<8 M inhabitants, China, [START_REF] Leng | Leaf magnetic properties as a method for predicting heavy metal concentrations in PM2.5 using support vector machine: A case study in Nanjing, China[END_REF]) or Kathmandu [START_REF] Gautam | Magnetic susceptibility of dust-loaded leaves as a proxy of traffic-related heavy metal pollution in Kathmandu city, Nepal[END_REF] but lower than those measured in Rome [START_REF] Szönyi | A refined biomonitoring study of airborne particulate matter pollution in Rome, with magnetic measurements on Quercus Ilex tree leaves[END_REF][START_REF] Moreno | Biomonitoring of traffic air pollution in Rome using magnetic properties of tree leaves[END_REF]. While relatively isolated medium-sized African cities such as Maroua are not emission "hot spots", such as large cities in West Africa and sub-Saharan Africa [START_REF] Doumbia | Flaring emissions in Africa: Distribution, evolution and comparison with current inventories[END_REF], our data imply that these cities display locally values comparable to the particulate emissions of some Asian or European cities. Monitoring air pollution is therefore also crucial, and more easy-to-implement methods, including biomonitoring with low environmental impact, as proposed here, must be developed and implemented.

Conclusions

This study illustrates that in a medium-sized African city such as Maroua, with a population of 400,000, anthropogenic activities can induce an important release of particles in the urban air, efficiently tracked by magnetic methods. We showed that magnetite-like particles can be used as a proxy for particulate emissions due to urban activities, including traffic and local handicrafts. While relatively isolated medium-sized African cities such as Maroua are not emission "hot spots", such as large cities in West Africa and sub-Saharan Africa [START_REF] Doumbia | Flaring emissions in Africa: Distribution, evolution and comparison with current inventories[END_REF], our data imply that in these cities, local emissions from traffic and biomass combustion dominate over desert dust. The latter mainly consists of goethite, hematite and magnetite-like minerals present in the soil environment and carried by the wind.

We show that both bark and leaves from Neem trees are adequate passive biorecorders. The use of both enables different times and heights to be sampled. Neem trees are therefore good candidates for the low environmental impact monitoring of airborne particulate pollution because of their widespread occurrence in sub-arid to sub-humid regions. This study highlights that, in medium-sized cities in West and Central Africa, the health impact of particulate matter emissions, particularly related to wood burning and a large motorcycle fleet [START_REF] Owili | The associations between types of ambient PM2.5 and under-five and maternal mortality in Africa[END_REF] remains to be assessed. Such emissions are contributing to the increased aerosol loads over West Africa known to have the potential to change the local climate [START_REF] Knippertz | The possible role of local air pollution in climate change in West Africa[END_REF]. Therefore, anthropogenic air emissions of medium-sized cities, including resuspension phenomena, require evaluation and screening that could be rapidly, efficiently and cost-effectively realized with environmental magnetic methods.

Atmosphere 2021 ,

 2021 12, x FOR PEER REVIEW 3 of 22 a frequent and intense wind, called Harmattan coming mostly from the North or Northeast, sweeps the region. Harmattan is a dry wind and often laden with dust particles coming from northern desertic regions.

Figure 1 .

 1 Figure 1. Localization of sampling sites modified from @Google Earth (a,c,f) and photographs (@Daouda Dawai) illustrating anthropogenic activities in the streets of Maroua, Cameroon (b,d,e).

Figure 1 .

 1 Figure 1. Localization of sampling sites modified from @Google Earth (a,c,f) and photographs (@Daouda Dawai) illustrating anthropogenic activities in the streets of Maroua, Cameroon (b,d,e).

  3 km from Boulevard du Renouveau. The control sites of Palar and Ouro-Tchédé neighborhoods, ~1.7 km apart from each other, are located west of the study areas. The control site of Palar is located ~3 km from Avenue Kakataré and ~2.7 km from Boulevard du Renouveau, whereas the control site of Ouro-Tchédé is located approximately ~4.1 km from Avenue Kakataré and ~3.6 from Boulevard du Renouveau.

Atmosphere 2021 ,

 2021 12, x FOR PEER REVIEW 5 of 22

Figure 2 .

 2 Figure 2. Mass magnetic susceptibility obtained on leaves during campaigns A (mid-August) and D (end-December).

Figure 2 .

 2 Figure 2. Mass magnetic susceptibility obtained on leaves during campaigns A (mid-August) and D (end-December).

Figure 3 .

 3 Figure 3. Mean leaf and bark mass magnetic susceptibility values by sector and sampling campaign, showing the v tions of magnetic susceptibility on leaves as a function of the season and the stability of the bark's values. K is Ave Kakataré and D, Boulevard du Renouveau. Ksec and Dsec refer to secondary streets crossing perpendicularly K an respectively (see Figures 1 and 2 for localization). Error bars represent the standard deviation, N the number of data.

Figure 3 .

 3 Figure 3. Mean leaf and bark mass magnetic susceptibility values by sector and sampling campaign, showing the variations of magnetic susceptibility on leaves as a function of the season and the stability of the bark's values. K is Avenue Kakataré and D, Boulevard du Renouveau. Ksec and Dsec refer to secondary streets crossing perpendicularly K and D, respectively (see Figures 1 and 2 for localization). Error bars represent the standard deviation, N the number of data.

Figure 4 .

 4 Figure 4. Saturation isothermal remanent magnetization (SIRM) as a function of mass magnetic susceptibility depicting correlations for both leaves (green dots) and bark (blue squares).

Figure 5 .

 5 Figure 5. Individual isothermal remanent magnetizations (IRMs) obtained at 2 T for control area site and by campaign. Bark does not present any significant difference between the dry and wet seasons, while leaves display an enhanced magnetic concentration during the dry season compared to the wet season.

Figure 5 .

 5 Figure 5. Individual isothermal remanent magnetizations (IRMs) obtained at 2 T for control area site and by campaign. Bark does not present any significant difference between the dry and wet seasons, while leaves display an enhanced magnetic concentration during the dry season compared to the wet season.

Figure 6 .

 6 Figure 6. Isothermal Remanent Magnetization. (a) IRM acquisition curves for samples from site K19 and the control site 3 taken during campaign C (mid-November). Curves do not saturate for fields up to 2T, indicating the presence of high coercivity minerals (goethite and/or hematite). At site K19, bark displays a higher contribution to the IRM of high coercivity minerals. (b) IRMs showing a high coercivity component in the side streets highlighted by the analysis of IRM components using the MaxUnmix program[START_REF] Maxbauer | UnMix: A web application for unmixing magnetic coercivity distributions[END_REF]. Shown in gray are the data, black is the spline, yellow is the fitting model, and pink and purple are components 1 and 2, respectively. Shaded areas of each color represent error envelopes of 95% confidence intervals.

Figure 7 .

 7 Figure 7. Mean S-ratio (all campaigns together) for each site type. Error bars represent the standard deviation.

Figure 7 .

 7 Figure 7. Mean S-ratio (all campaigns together) for each site type. Error bars represent the standard deviation.

Figure 8 .

 8 Figure 8. SEM observations (a-d) and EDS spectra (e,f) acquired on the location marked by the cross on c and d, respectively. (a) Leaf from site D13 taken during campaign D. All others: leaf from site D48 taken during campaign D.

Figure 9 .

 9 Figure 9. SEM observations on a leaf from site D48 taken during campaign D (a,c,d) and respective EDS spectra (b,d,f) acquired on the location marked by the cross.

Table 1 .

 1 Magnetic susceptibility values (in m 3 kg -1 ) obtained on leaves in different cities. Env. is environment, Sus_min is the minimum magnetic susceptibility values, Sus_max is the minimum magnetic susceptibility values, Sus_mean is the mean magnetic susceptibility and Ref. is the reference.

	Country	City	City Pop-ulation	Env.	Species	Species Common Name	Type of leaf	Sus_Min	Sus_Max	Sus_Mean	Comments	Ref.
	Nepal	Kathmandu	1,000,000	urban	Cupressus corneyana	Cypress	evergreen	1.00 × 10 -10	5.40 × 10 -7	-	-	Gautam et al., 2005 [45]
	Nepal	Kathmandu	1,000,000	urban	Grevillea robusta	Silky Oak	evergreen	2.75 × 10 -8	4.03 × 10 -7	-	-	Gautam et al., 2005 [45]
	Nepal	Kathmandu	1,000,000	urban	Callistemon lanceolatus	Bottlebrush	-	1.12 × 10 -8	2.35 × 10 -7	-	-	Gautam et al., 2005 [45]
	Germany	Cologne	1,080,000	urban	Pine needle	Pine	evergreen	-5.0 × 10 -9	8.00 × 10 -8	-	-	Lehndorff et al., 2006 [71]
	China	Nanjing	8,200,000	urban	Cedar deodara G. Don	Cedar	evergreen	7.31 × 10 -9	7.95 × 10 -8	4.67 × 10 -8 ± 1.60 × 10 -8	Winter values	Leng et al., 2018 [85]
	China	Nanjing	8,200,000	urban	Ligustrum lucidum Ait	Privet	evergreen	4.69 × 10 -9	4.31 × 10 -8	3.08 × 10 -8 ± 7.95 × 10 -9	Winter values	Leng et al., 2018 [85]
	China	Nanjing	8,200,000	urban	Osmanthus fragrans Lour	Sweet os-manthus	evergreen	2.61 × 10 -9	4.84 × 10 -8	3.27 × 10 -8 ± 8.23 × 10 -9	Winter values	Leng et al., 2018 [85]
	Italy	Rome	2,500,000	urban	Quercus ilex	Oak	evergreen	-	-	3.34 × 10 -7 ± 1.95 × 10 -8	High traffic means	Moreno et al., 2003 [77]
	Italy	Rome	2,500,000	urban	Platanus sp.	Plane	deciduous	1.00 × 10 -9	1.04 × 10 -7	-	-	Moreno et al., 2003 [77]
	Iran	Isfahan	1,796,967	urban	Platanus orientalis L.	Plane	deciduous	1.43 × 10 -8	1.24 × 10 -7	-	From the unwashed leaves	Norouzi et al., 2016 [83]
	Colombia	Bogota	6,778,691	urban	Sambucus nigra	Elder	deciduous	-	1.0 × 10 -7	-	Values from Fig. 4	Reyes et al., 2013 [27]
	Spain	Madrid	5,000,000	urban	Platanus hispanica	Plane	deciduous	-9.0 × 10 -9	3.22 × 10 -7	6.59 × 10 -7 ± 6.42 × 10 -7	-	Rodríguez-Germade et al., 2014 [68]
	Portugal	Porto	260,000	urban	Platanus spp.	Plane	deciduous	2.54 × 10 -8	4.17 × 10 -8	3.11 × 10 -8 ± 6.40 × 10 -9	Hopital	Sant'Ovaia et al., 2012 [84]

Table 1 .

 1 Cont.

	Country	City	City Pop-ulation	Env.	Species	Species Common Name	Type of leaf	Sus_Min	Sus_Max	Sus_Mean	Comments	Ref.
	Portugal	Porto	260,000	urban	Quercus spp.	Oak	deciduous	3.00 × 10 -10	2.96 × 10 -7	9.04 × 10 -8 ± 9.46 × 10 -8	Hopital	Sant'Ovaia et al., 2012 [84]
	Portugal	Porto	260,000	urban	Nerium oleander	Oleander	evergreen	2.49 × 10 -8	6.17 × 10 -8	3.94 × 10 -8 ± 1.13 × 10 -8	Hopital	Sant'Ovaia et al., 2012 [84]
	Portugal	Porto	260,000	urban	Tilia spp.	Lime tree	deciduous	3.10 × 10 -9	8.06 × 10 -8	3.96 × 10 -8 ± 2.80 × 10 -8	Heavy traffic	Sant'Ovaia et al., 2012 [84]
	Portugal	Valongo	170,000	urban	Nerium oleander	Oleander	evergreen	2.85 × 10 -8	1.09 × 10 -7	7.39 × 10 -8 ± 2.38 × 10 -8	Suburban traffic, heavy	Sant'Ovaia et al., 2012 [84]
	Portugal	Braga	20,000	urban	Nerium oleander	Oleander	evergreen	3.78 × 10 -8	9.41 × 10 -8	6.39 × 10 -8 ± 1.94 × 10 -8	Suburban traffic, heavy	Sant'Ovaia et al., 2012 [84]
	Portugal	Trancoso-Reboleiro	300	rural	Tilia spp.	Lime tree	deciduous	-8.90 × 10 -9	-2.1 × 10 -9	-6.10 × 10 -9 ± 2.10 × 10 -9	-	Sant'Ovaia et al., 2012 [84]
	Italy	Rome	2500,000	urban	Q. Ilex	Oak	evergreen	1.00 × 10 -8	7.00 × 10 -7	3.20 × 10 -7 ± 1.78 × 10 -7	-	Szönyi et al., 2008 [28]
	Germany	Cologne	1,080,000	urban	Pine needle	Pine	evergreen	-6.0 × 10 -10	1.60 × 10 -7	-	-	Urbat et al., 2004 [70]
											Highest
	Cameroon	Maroua	400,000	urban	Azadirachta indica	Neem	evergreen	-5.0 × 10 -9	2.21 × 10 -7	5.85 × 10 -8 ± 3.65 × 10 -8	values in Kakataré highest street and	This study
											campaign

Acknowledgments:

The authors would like to thank Thierry Aigouy from the Géosciences Environnement Toulouse (GET) laboratory for his help with SEM observations.

Conflicts of Interest:

The authors declare no conflict of interest.


Cecile Courreges

Delphine Flahaut

Mélanie Bonnecaze

Sophie Nolivos

Regis Grimaud

Joachim Allouche

Cécile Courrèges

Régis Grimaud

AES and ToF-SIMS combination for single cell chemical imaging of gold nanoparticle-labeled Escherichia coli

In order to fully apprehend complex biological processes occurring at a multicellular level as well as at the ecosystems level, investigating molecular mechanisms occurring in a single cell is essential. 1 This is crucial for answering to a wide range of biological issues related to fundamental biology as well as pathological processes. 2 Single cell imaging provides morphological, chemical and physical characterizations at a length scale from microns to nanometers. 3 Particularly, single cell chemical imaging is still challenging as it presents a dual constraint consisting in (i) an elemental, isotopical or molecular detection with (ii) a chemical localization at a nanometer scaled lateral resolution. This is especially the case for bacteria due to their smaller sizes (≈ 1 µm) compared to eukaryotic cells. Only a few techniques capable of meeting those requirements are currently available. For instance, super-resolved optical techniques have benefited in the past recent years from technical advances allowing to reach nanoscaled resolution. 4,5 Different approaches based on fluorescent tags, 4,6 pump-probe process 7 or coherent scattering 8 have been developed using optical algorithms or mathematical signal treatment 3 to extend the boundaries of the optical microscopy Abbe's diffraction resolution limit. 9 However, few of them allowed chemical, elemental or molecular multi-detection excepting for instance plasmonic based optical spectroscopy like Surface Enhanced Raman Spectroscopy (SERS). 10 This technique has recently given chemical spatial resolution near those of scanning electron microscopy (SEM) by exploiting the plasmon resonance of metallic nanostructures. 3,11 Concerning non optical imaging techniques, transmission electron microscopy (TEM) combined to energy dispersive spectroscopy (EDS) or electron loss energy spectroscopy (EELS) 12,13 still provide high resolved chemical images (< 10 nm) but require time consuming and complex sample preparation based on resin inclusions and ultramicrotome cutting. Another example is X-ray fluorescence (XRF) nanotomography that has been performed recently using hard X-ray with a sub-15 nm nanoprobe beamline to image the elemental distribution in E. coli at nanoscale. 14 Secondary ion mass spectrometry (SIMS) have also been performed successfully to image single cells. 15,16 Nano-SIMS is for instance one of the best resolved techniques to image elemental and isotopic distributions at the single cell level with lateral resolution close to 50 nm. 17 ToF-SIMS has yet been performed in combination to other techniques to image materials 18 as well as single cells including bacteria with submicron lateral resolution. [19][20][21][22] However, unambiguous peak assignment of the fragments coming from high molecular weight cell surface species is still challenging on bacteria. AES is a surface sensitive technique based on the detection of the short escape depth Auger electrons (in the 0.3 to 5 nm range). 23,[START_REF] Unger | Characterization of Nanoparticles[END_REF] This technique, widely used to perform chemical imaging at a high lateral resolution (up to 10 nm) of materials, [START_REF] Ledeuil | [END_REF]26 has never been used previously to characterize the surface of bacteria at a single cell level. In this paper, we propose a novel approach (scheme 1) based on the ex situ combination of AES and ToF-SIMS equipped with a Tandem MS analyzer 27,28 to image the surface of bacteria at a single cell Please do not adjust margins Please do not adjust margins level. To our knowledge, this is the first use of AES for elemental mapping of bacteria at a single cell level. In contrary to other techniques, our method provides a unique chemical fingerprint of cell surface through the complementary of molecular and elemental detections at nanoscale. Gelatin coated gold nanoparticles have been used to tag cells and enhance the chemical signals detection.

In a first step, ToF-SIMS mass spectra (figure 1) were acquired, using the same analysis conditions in negative polarity, for E. coli cells (top line), E. coli cells incubated with gelatin-coated gold nanoparticles (middle line) and gelatincoated gold nanoparticles (bottom line). m/z ranges specific of CN -(m/z 26.00), PO2 -(m/z 62.97), Au - (m/z 196.96), CN-Au2 -(m/z 419.94) and Au3 -(m/z 590.89) molecular fragments, are presented for each system. CN - fragment is most likely to come from bacteria outer membrane molecules (like phospholipids and lipopolysaccharides) and gelatin coated on gold nanoparticles. For cells with gold nanoparticles, the two signals are overlaid which is consistent with a higher intensity signal. Phosphate groups (PO2 -) originate from bacteria outer membrane phospholipids and are only observed for cells alone and cells with gold nanoparticles. Tandem MS was used to confirm the assignment of m/z 419.94 and m/z 590.89 peaks to CNAu2 -and Au3 -respectively (figure S3 ESI ‡), which are molecular fragments specific of gold nanoparticles alone or in interaction with cells. More interestingly, Au -signal (m/z 196.96) is only detected for gold nanoparticles without bacteria; indeed, the signal observed at m/z 196.91 for cells alone and in interaction with nanoparticles is attributed to C7H4NO4P -molecular fragment, which is characteristic of cells outer membrane phospholipids. The same observation was done in positive polarity (figure S4 ESI ‡), where specific peaks of the phosphatidylcholine head group of bacteria membrane phospholipids are detected for E. coli cells interacted with gold nanoparticles, but no peaks characteristics of gold. Such result can be explained either by a change of the gold fragmentation pattern when nanoparticles interact with cells or by a higher ionization yield of organic species that hide elemental gold signal. 29 In a second step, 2D spatial distributions of CN -, PO2 -CNAu2 -and Au3 -molecular fragments were obtained by ToF-SIMS chemical imaging (figure 2) for cells interacting with nanoparticles (top line) and cells alone (bottom line) over 25µmx25µm field of view. The co-localization of all signals for bacteria with gold nanoparticles, proves the interactions between these two species; indeed the signal of phosphate groups characteristics of bacteria outer membrane phospholipids is detected at the same area as CNAu2 -and Au3 -signals, specific of gelatin coatedgold nanoparticles. Due to opposite global charges (negative for bacteria and positive for nanoparticles), it is more than likely that these entities are attracted by each other through electrostatic forces. For cells alone, only CN -and PO2 -signals are observed with a much lower intensity compared to the one of cells with nanoparticles; in the last case, the signal enhancement, especially noticeable for CN-, may be attributed to the presence of gold metal, which improves the ionization yield of species nearby. 30,31 Please do not adjust margins

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To go further on the bacteria characterization at nanoscale, AES was performed. Firstly, E. coli without gold nanoparticles used as control sample were deposited on silica wafers and characterized by AES. Figure 3a For comparison, the dot 4 spectrum corresponding to the substratum analysis exhibits an intense Si peak but no nitrogen and phosphorus signals coming from BSE contribution. This is due to the density of SiO2 that lower the excitation volume in comparison to dots 1 to 3. 23,[START_REF] Unger | Characterization of Nanoparticles[END_REF] On the other hand, elemental Scanning Auger Maps (SAM) of phosphorus, carbon, nitrogen and oxygen are displayed on Figure 3d, e, f and g. Figure 3c and Figure 3h correspond to the SEM image and to the P+C+O signals overlay respectively. It is worth noting that the SAM pictures match the SEM image shown on Figure 3c perfectly, indicating the good lateral resolution of AES for the elemental imaging of single cells. 30 ± 10 nm gelatin coated gold nanoparticles (see ESI ‡ for XPS characterization and figure S1 for TEM pictures) were bound on the bacteria surface due to electrostatic interactions between positive and negative charge of gold nanoparticles and E. coli membrane surface respectively. On Figure 4a, one dividing E. coli cell has been decorated by gold nanoparticles and two analysis target dots have been selected. The corresponding AES spectra of these target dots displayed on Figure 4b show C, O, and N transitions as for control samples and Si KLL (1450 eV-1630 eV) transition corresponding to the BSE contribution substrate signal as mentioned above. Au MNN (1625 eV-2125 eV) transition was also detected for dot 1 which match the gold nanoparticles bound on cells. The spectrum of dot 2 focusing bacteria membrane (without gold nanoparticles) does not exhibit detectable Au transition attesting of the good surface sensitivity and high lateral selectivity by the AES probe. High resolution SAM elemental mapping has been performed on one other dividing cell (SEM on Figure 5a). The mapping has been carried out by focusing the scanning analysis area within the red dotted line square using high magnification operating conditions. SEM image is depicted on Figure 5b Please do not adjust margins Please do not adjust margins spatial chemical resolution is in the range of the best resolved chemical characterization techniques. Such results confirm the power of the ToF-SIMS Tandem MS technique to image E. coli with unambiguous molecular identification of species coming specifically from nanoparticles and bacteria in interaction. ToF-SIMS provides molecular information whereas AES, used for the first time on bacteria, gives elemental distribution data at nanoscale, supporting the good complementarity of the two techniques. This approach highlights the possible identification of a unique and enhanced chemical fingerprint of bacteria surface opening the way to new strategies for the study of pathogen outer membrane or characterization of biomarkers on cells surface. We would like to thanks Arkema for TEM analyses of gold nanoparticles and CNRS, UPPA-E2S and Aquitaine region for their financial support.

Figure 1 .

 1 Figure 1. Negative ToF-SIMS mass spectra over CN -(m/z 26.00), PO2 -(m/z 62.97), Au -(m/z 196.96), CN-Au2 -(m/z 419.94) and Au3 -(m/z 590.89) m/z ranges of E. coli cells (top line), E. coli cells incubated with gelatin-coated gold nanoparticles (middle line) and gelatin-coated gold nanoparticles (bottom line); Intensity scale expenders are indicated when necessary.

Figure 2 .

 2 Figure 2. ToF-SIMS 2D chemical mappings of i) CN -(m/z 26.00), PO2 -(m/z 62.97), CNAu2 -(m/z 419.94) and Au3 -(m/z 590.89) molecular fragments of E. coli cells incubated with gelatin-coated gold nanoparticles and ii) CN -(m/z 26.00), PO2 -(m/z 62.97) of single E.coli cells, over 25µmx25µm field of view (the color scale is indicated on the side: red represents the highest intensity and purple the lowest one).

  displays a SEM image of a single cell with 4 target analyses dots corresponding to the Auger spectra obtained on Figure 3b. For dot 1, 2 and 3, the P LVV (100 eV-125 eV), C KLL (220 eV-280 eV), N KLL (349 eV-395 eV) and O KLL (465 eV-520 eV) Auger transitions attest of a good detection of the cell outer membrane molecules: proteins, lipopolysaccharides (LPS) and phospholipids (PL). Due to the well-known contribution of the backscattered electron (BSE) diffusion to the Auger signal, a Si LVV transition (40 eV-95 eV) corresponding to the adhesion substratum was also observed.

  whereas the Figures 5c to 5g display the elemental maps of carbon, gold, nitrogen, oxygen and carbon + gold overlay respectively. The latter exhibits a very good correspondence of the Au (gold nanoparticles) and C (cell membrane) Auger signals with the SEM image (figure S6 ESI ‡ for lower magnification maps). The chemical lateral resolution has been estimated successfully to 30 nm using an AES line profile image (scanning mode, figure S5 ESI ‡) performed on C and Au signals detected along a line on the cell surface. To our knowledge, these results has never been obtained elsewhere previously on bacteria using AES. This

Figure 4 .

 4 Figure 4. AES spectra analyses of E. coli cells decorated by gelatin coated gold nanoparticles. (a) SEM image of cells with the target dots and (b) the corresponding AES dot 1 and dot 2 spectra focusing gold nanoparticles on cell membrane and gold-free cell membrane respectively.

Figure 5 .

 5 Figure 5. High resolution SAM elemental maps of gold nanoparticles coated E. coli. (a) SEM images of cells showing the analyzed area (red square) used for the elemental maps. (b) SEM image and related SAM elemental maps of (c) Carbon, (d) Gold, (e) Nitrogen, (f) Oxygen and (g) Carbon + Gold overlay signals.

Figure 3 .

 3 Figure 3. AES characterization of a single E. coli. (a) SEM image with target dots and (b) the corresponding AES spectra, (c) SEM image and the corresponding SAM elemental maps of (d) Phosphorus, (e) Carbon, (f) Nitrogen, (g) Oxygen and (h) P+C+O overlay signals (scale bar = 400 nm).

Conflicts of interest

There are no conflicts to declare.

Notes and references