# Metrological Characterization of an Aerosol Exposure Chamber to Explore the Inhalation Effects of the Combination of Paraquat and TiO2 Nano-objects

Quentin Hamdaoui, A. Bencsik, Frederic Flamant, Simon Delcour, Tatiana Macé, Sophie Vaslin-Reimann, François Gaie-Levrel

► To cite this version:

Quentin Hamdaoui, A. Bencsik, Frederic Flamant, Simon Delcour, Tatiana Macé, et al.. Metrological Characterization of an Aerosol Exposure Chamber to Explore the Inhalation Effects of the Combination of Paraquat and TiO2 Nano-objects. Aerosol and Air Quality Research, 2021, 21 (8), pp.200626. 10.4209/aaqr.200626. hal-03416520

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Aerosol and Air Quality
Research

# Metrological Characterization of an Aerosol Exposure Chamber to Explore the Inhalation Effects of the Combination of Paraquat and TiO₂ Nano-objects

Quentin Hamdaoui<fnref n="1" />,<fnref n="3" />, Anna Bencsik<fnref n="2" />, Frédéric Flamant<fnref n="3" />, Simon Delcour<fnref n="1" />, Tatiana Macé<fnref n="1" />, Sophie Vaslin-Reimann<fnref n="1" />, François Gaie-Levrel<fnref n="1" />*

## ABSTRACT

Agriculture emits a significant quantity of airborne contaminants, and the prospective environmental release of nanopesticides, a new type of agrochemical that employs engineered nanomaterials (ENMs) as either active substances or additives in a pesticide formulation, raises concerns about the risks of inhalation which are still unknown. Although the adverse effects of pesticides have been studied extensively, the potential synergistic toxicity between these substances and ENMs has rarely been investigated. To this end, toxicological models are essential to estimating the health consequences of such aerosols. Thus, to assess the respiratory hazards of titanium dioxide nano-objects (specifically, AEROXIDE® TiO₂ P25 nanopowder [nTiO₂]) in combination with paraquat (PQ), we developed a dynamic whole-body exposure chamber for rodents in compliance with guidelines for inhalation toxicity testing (Organization for Economic Cooperation and Development (OECD)) and animal welfare. First, we metrologically characterized the generated test aerosols by determining their mass and number concentrations, size distributions and atmospheric homogeneity at the laboratory. Then, we evaluated the reproducibility and proper functioning of the chamber during a preliminary field campaign, which validated the consistency of the aerosols' mass and number concentrations between the laboratory characterization and the rodent exposure sessions. Finally, we examined the inhalation effects on the rodents.

**Keywords:** Aerosol, Inhalation paraquat, TiO₂ nano-objects

## 1 INTRODUCTION

Epidemiological studies highlight converging evidence suggesting a link between the professional and residential exposures to specific pesticides and chronic illnesses such as neurodegenerative diseases and cancers (INSERM, 2013; Kim et al., 2017). Pesticides represent an occupational risk for farmers, pesticides applicators and manufacturers, but also for the general population who may be indirectly exposed to pesticides during their application or because of their persistence in the air (Lu et al., 2000; Coscollà et al., 2013; Brouwer et al., 2017; Mattei et al., 2019). Engineered nanomaterials (ENMs) are generally defined as novel materials designed at the nanoscale, with external or internal structures under the size of 100 nm (e.g., ISO/TR 18401:2017). ENMs could be used either as active ingredients or co-formulants, to provide nanopesticides (NPEs) proposing a reformulation of conventional pesticides. They are expected to enhance the efficiency of agrochemicals and to mitigate the environmental footprint of modern agriculture. Despite the lack of data on their current use, the number of granted patents associated with ENMs in agriculture grew significantly starting in the 1990s to reach 1,254 patents in 2016 (Kah et al., 2019).

**OPEN ACCESS**

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

**Received:** November 12, 2020

**Revised:** March 11, 2021

**Accepted:** April 4, 2021

* Corresponding Author:
francois.gaie-levrel@lne.fr

**Publisher:**
Taiwan Association for Aerosol Research
**ISSN:** 1680-8584 print
**ISSN:** 2071-1409 online

CC Copyright: The Author(s).
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

<footnote n="1">¹ Laboratoire national de métrologie et d'essais (LNE), Paris, France</footnote>

<footnote n="2">² Université Claude Bernard Lyon 1, ANSES, Laboratoire de Lyon, France</footnote>

<footnote n="3">³ IGFL, Functional genomics of thyroid hormone signaling group, Lyon, France</footnote>
<figure><img src="image_2.png" /></figure>

Aerosol and Air Quality
Research

# Metrological Characterization of an Aerosol Exposure Chamber to Explore the Inhalation Effects of the Combination of Paraquat and TiO₂ Nano-objects

Quentin Hamdaoui<fnref n="1" />,<fnref n="3" />, Anna Bencsik<fnref n="2" />, Frédéric Flamant<fnref n="3" />, Simon Delcour<fnref n="1" />, Tatiana Macé<fnref n="1" />, Sophie Vaslin-Reimann<fnref n="1" />, François Gaie-Levrel<fnref n="1" />*

## ABSTRACT

Agriculture emits a significant quantity of airborne contaminants, and the prospective environmental release of nanopesticides, a new type of agrochemical that employs engineered nanomaterials (ENMs) as either active substances or additives in a pesticide formulation, raises concerns about the risks of inhalation which are still unknown. Although the adverse effects of pesticides have been studied extensively, the potential synergistic toxicity between these substances and ENMs has rarely been investigated. To this end, toxicological models are essential to estimating the health consequences of such aerosols. Thus, to assess the respiratory hazards of titanium dioxide nano-objects (specifically, AEROXIDE® TiO₂ P25 nanopowder [nTiO₂]) in combination with paraquat (PQ), we developed a dynamic whole-body exposure chamber for rodents in compliance with guidelines for inhalation toxicity testing (Organization for Economic Cooperation and Development (OECD)) and animal welfare. First, we metrologically characterized the generated test aerosols by determining their mass and number concentrations, size distributions and atmospheric homogeneity at the laboratory. Then, we evaluated the reproducibility and proper functioning of the chamber during a preliminary field campaign, which validated the consistency of the aerosols' mass and number concentrations between the laboratory characterization and the rodent exposure sessions. Finally, we examined the inhalation effects on the rodents.

**Keywords:** Aerosol, Inhalation paraquat, TiO₂ nano-objects

## 1 INTRODUCTION

Epidemiological studies highlight converging evidence suggesting a link between the professional and residential exposures to specific pesticides and chronic illnesses such as neurodegenerative diseases and cancers (INSERM, 2013; Kim et al., 2017). Pesticides represent an occupational risk for farmers, pesticides applicators and manufacturers, but also for the general population who may be indirectly exposed to pesticides during their application or because of their persistence in the air (Lu et al., 2000; Coscollà et al., 2013; Brouwer et al., 2017; Mattei et al., 2019). Engineered nanomaterials (ENMs) are generally defined as novel materials designed at the nanoscale, with external or internal structures under the size of 100 nm (e.g., ISO/TR 18401:2017). ENMs could be used either as active ingredients or co-formulants, to provide nanopesticides (NPEs) proposing a reformulation of conventional pesticides. They are expected to enhance the efficiency of agrochemicals and to mitigate the environmental footprint of modern agriculture. Despite the lack of data on their current use, the number of granted patents associated with ENMs in agriculture grew significantly starting in the 1990s to reach 1,254 patents in 2016 (Kah et al., 2019).

**OPEN ACCESS**

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

**Received:** November 12, 2020

**Revised:** March 11, 2021

**Accepted:** April 4, 2021

* Corresponding Author:
francois.gaie-levrel@lne.fr

**Publisher:**
Taiwan Association for Aerosol Research
**ISSN:** 1680-8584 print
**ISSN:** 2071-1409 online

CC Copyright: The Author(s).
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

<footnote n="1">¹ Laboratoire national de métrologie et d'essais (LNE), Paris, France</footnote>

<footnote n="2">² Université Claude Bernard Lyon 1, ANSES, Laboratoire de Lyon, France</footnote>

<footnote n="3">³ IGFL, Functional genomics of thyroid hormone signaling group, Lyon, France</footnote>
<figure><img src="image_3.png" /></figure>

Moreover, some NPEs have already been identified on the market (Kumar *et al.*, 2019), showing that those products are likely to emerge in a near future. As the fate of NPEs is still not understood, some authors have already emphasized the knowledge gap surrounding the environmental impact of these emerging products (Kah *et al.*, 2018) and some research agencies have integrated these new compounds as a healthcare priority (USDA, 2015).

Several studies analyzed the presence of pesticides in the atmosphere (Coscollà *et al.*, 2010; Estellano *et al.*, 2015; López *et al.*, 2017; Désert *et al.*, 2018). Their air concentrations ranged from few picograms to hundreds of nanograms per cubic meter. Nevertheless, the air concentration of pesticides can be locally much higher in treated parcels during the seasonal spreading. For instance, a study with paraquat (PQ) sprayers showed that the PQ mass concentration can reach 125 µg m⁻³ in the breathing zone during work (Morshed *et al.*, 2010). Another study assessed the size distribution of the pesticide residues in a French rural area (Coscollà *et al.*, 2013). Most pesticides were accumulated in the particulate phase, especially in the fine size range (0.1–1 µm), which represent an inhalable fraction, whose size distribution enables particles to be deposited in the respiratory tract. Accordingly, inhalation toxicology studies appear necessary to assess the risk associated with NPE exposure. However, to our knowledge no toxicological data are available on NPE inhalation effects, involving both nano-objects and their aggregates and agglomerates (NOAAs), and pesticides.

A validation of the inhalation facility with characterized aerosol parameters is needed to conduct animal inhalation studies that will provide toxicity data for the risk assessment of nanopesticides. Among the variety of inhalation devices used for animal experimentation, there are two main exposure modalities, namely nose-only and whole-body devices (OECD TG 403; Yeh *et al.*, 1990). The nose-only strategy facilitates the control of the exposure dose for each animal. Animals are not able to move during the aerosol exposure, as they are restrained in a tube to be exposed individually by limiting other routes of exposure, such as the dermal and oral routes (Dorato and Wolff, 1991). However, the stress induced by restraint during gestation could be problematic, notably in case of repeated exposures. By contrast, in whole-body devices, subjects are immersed within the chamber atmosphere, which reflects environmental or occupational exposure scenarios, which are less restraining for animals since they are able to behave naturally. Whole-body exposure chambers encompass various types of chambers, using single-animal holders or large-sized compartments for long-term studies using numerous subjects (Wong, 2007). They are particularly suitable for chronic studies or exposure during the gestation to minimize the stress induced by treatments. It must be noted that animals may be exposed by skin, as they collect particles on their fur during the whole-body exposures (Griffis *et al.*, 1979), which can lead to the particle ingestion during grooming. Nevertheless, as inhalation and dermal routes are considered as the main occupational exposure pathways to pesticides (Damalas and Eleftherohorinos, 2011), this additional source of exposure could be relevant to consider.

To comply with the Organization for Economic Cooperation and Development (OECD) test guidelines 413 on subchronic inhalation toxicity (OECD TG 413), the physicochemical characterization of ENMs is necessary prior to the aerosol exposures. Currently, AEROXIDE® TiO₂ P25 nanopowder (nTiO₂) is one of the most studied ENMs in toxicology and it has already been characterized in a previous study in terms of crystalline structure, size of primary particles, specific surface area and chemical composition (Motzkus *et al.*, 2014). Additionally, nTiO₂ appears as a good candidate to be integrated as a nano-additive in NPEs for its valuable properties in agriculture (Wang *et al.*, 2016), such as its photocatalytic activity, which can be used to degrade PQ (Florêncio *et al.*, 2004). PQ is one of the most worldwide used herbicide, despite the fact it is suspected to be associated with the occurrence of the Parkinson disease among farmers (Kamel *et al.*, 2007; Costello *et al.*, 2009; Tanner *et al.*, 2011). PQ and nTiO₂ under the form of a colloidal suspension may constitute a model of NPE with interesting features based on the technological inputs brought by nTiO₂ in agriculture and its ability to decrease the environmental PQ half-life in soils which could reach several years (Sartori and Vidrio, 2018).

Given the fact that the nanopesticide inhalation effects are still not addressed in the literature, the present study is the first necessary step to establish a proof of concept of a transdisciplinary methodology combining aerosol metrology and toxicology to address properly this question. The present paper is dedicated to the metrological characterization of an aerosol exposure chamber to explore the inhalation effects of the herbicide PQ combined with nTiO₂ used as reference
<figure><img src="image_4.png" /></figure>

Moreover, some NPEs have already been identified on the market (Kumar *et al.*, 2019), showing that those products are likely to emerge in a near future. As the fate of NPEs is still not understood, some authors have already emphasized the knowledge gap surrounding the environmental impact of these emerging products (Kah *et al.*, 2018) and some research agencies have integrated these new compounds as a healthcare priority (USDA, 2015).

Several studies analyzed the presence of pesticides in the atmosphere (Coscollà *et al.*, 2010; Estellano *et al.*, 2015; López *et al.*, 2017; Désert *et al.*, 2018). Their air concentrations ranged from few picograms to hundreds of nanograms per cubic meter. Nevertheless, the air concentration of pesticides can be locally much higher in treated parcels during the seasonal spreading. For instance, a study with paraquat (PQ) sprayers showed that the PQ mass concentration can reach 125 µg m⁻³ in the breathing zone during work (Morshed *et al.*, 2010). Another study assessed the size distribution of the pesticide residues in a French rural area (Coscollà *et al.*, 2013). Most pesticides were accumulated in the particulate phase, especially in the fine size range (0.1–1 µm), which represent an inhalable fraction, whose size distribution enables particles to be deposited in the respiratory tract. Accordingly, inhalation toxicology studies appear necessary to assess the risk associated with NPE exposure. However, to our knowledge no toxicological data are available on NPE inhalation effects, involving both nano-objects and their aggregates and agglomerates (NOAAs), and pesticides.

A validation of the inhalation facility with characterized aerosol parameters is needed to conduct animal inhalation studies that will provide toxicity data for the risk assessment of nanopesticides. Among the variety of inhalation devices used for animal experimentation, there are two main exposure modalities, namely nose-only and whole-body devices (OECD TG 403; Yeh *et al.*, 1990). The nose-only strategy facilitates the control of the exposure dose for each animal. Animals are not able to move during the aerosol exposure, as they are restrained in a tube to be exposed individually by limiting other routes of exposure, such as the dermal and oral routes (Dorato and Wolff, 1991). However, the stress induced by restraint during gestation could be problematic, notably in case of repeated exposures. By contrast, in whole-body devices, subjects are immersed within the chamber atmosphere, which reflects environmental or occupational exposure scenarios, which are less restraining for animals since they are able to behave naturally. Whole-body exposure chambers encompass various types of chambers, using single-animal holders or large-sized compartments for long-term studies using numerous subjects (Wong, 2007). They are particularly suitable for chronic studies or exposure during the gestation to minimize the stress induced by treatments. It must be noted that animals may be exposed by skin, as they collect particles on their fur during the whole-body exposures (Griffis *et al.*, 1979), which can lead to the particle ingestion during grooming. Nevertheless, as inhalation and dermal routes are considered as the main occupational exposure pathways to pesticides (Damalas and Eleftherohorinos, 2011), this additional source of exposure could be relevant to consider.

To comply with the Organization for Economic Cooperation and Development (OECD) test guidelines 413 on subchronic inhalation toxicity (OECD TG 413), the physicochemical characterization of ENMs is necessary prior to the aerosol exposures. Currently, AEROXIDE® TiO₂ P25 nanopowder (nTiO₂) is one of the most studied ENMs in toxicology and it has already been characterized in a previous study in terms of crystalline structure, size of primary particles, specific surface area and chemical composition (Motzkus *et al.*, 2014). Additionally, nTiO₂ appears as a good candidate to be integrated as a nano-additive in NPEs for its valuable properties in agriculture (Wang *et al.*, 2016), such as its photocatalytic activity, which can be used to degrade PQ (Florêncio *et al.*, 2004). PQ is one of the most worldwide used herbicide, despite the fact it is suspected to be associated with the occurrence of the Parkinson disease among farmers (Kamel *et al.*, 2007; Costello *et al.*, 2009; Tanner *et al.*, 2011). PQ and nTiO₂ under the form of a colloidal suspension may constitute a model of NPE with interesting features based on the technological inputs brought by nTiO₂ in agriculture and its ability to decrease the environmental PQ half-life in soils which could reach several years (Sartori and Vidrio, 2018).

Given the fact that the nanopesticide inhalation effects are still not addressed in the literature, the present study is the first necessary step to establish a proof of concept of a transdisciplinary methodology combining aerosol metrology and toxicology to address properly this question. The present paper is dedicated to the metrological characterization of an aerosol exposure chamber to explore the inhalation effects of the herbicide PQ combined with nTiO₂ used as reference
<figure><img src="image_4.png" /></figure>

materials. The second step consisting in the neurotoxicological assessment of these aerosols, will be addressed separately in upcoming dedicated articles. Thus, a new whole-body exposure chamber was developed to explore the inhalation effects of aerosols. It is a simple device which can fit easily in any animal facility to be operated safely by conforming with animal welfare. As a complete metrological set-up cannot be implemented permanently in an animal facility for long-term studies, the characterization had to be made prior to the animal exposure. The characterization was made in the LNE (Laboratoire National de métrologie et d'Essais) laboratory, in terms of size distribution (Scanning Mobility Particle Sizer [SMPS] + Aerodynamic Particle Sizer [APS]), mass concentration (Tapered Element Oscillating Microbalance [TEOM] + indirect measurements of the sampled mass on 47-mm filters), number concentration (Condensation Particle Counter [CPC]), temperature, pressure and relative humidity. In addition, based on the particle size distribution, the chamber geometry and the airflows, computational fluid dynamics (CFD) modeling was used to investigate the homogeneity of the particle concentration within the cage. The main goal for the CFD simulation was to investigate the fill-up process of the chamber, the possibility of error induced by the relative positions of the injection tube and the measurement sampling tube. These parameters were assessed in accordance with the standard method on the reproducibility measurement (ISO 5725-2:2020).

Because it is essential to validate the functioning of the characterized aerosol exposure chamber on the field, here we also report the comparison of the measurements made in the LNE metrological lab (without animal) in regard to the first preliminary data obtained in the animal facility (with animals) for each of the three aerosols. During the animal exposure, a reduced monitoring of the aerosol was used to check the proper aerosol generation, to enable a precise metrological follow-up of the exposures. The mass concentration and the particle number concentration were therefore used to validate animal exposure sessions in accordance with the metrological characterization phase.

# 2 MATERIALS AND METHODS

## 2.1 Inhalation Exposure Chamber

The exposure chamber is composed of a rodent cage used as a whole-body exposure system (Fig. 1). The chamber was sealed and customized with antistatic silicon pipes to be integrated within the generation device. This cage, initially dedicated to rodents hosting (rats, mice, hamsters or others) in animal facilities, is made out of polysulfone (internal volume of 19.8 L, overall dimensions of 395 × 346 × 213 mm [W × D × H]; GR900; Tecniplast). It was selected for the chemical resistance and the transparency of this material (Tuttle et al., 2010), which allowed a visual follow-up of animals during the exposure sessions. Coupled with this chamber, an aerosol nebulizer (Model 3076; TSI Inc.) was operated to generate three aerosols of interest, i.e., nTiO₂, PQ and nTiO₂ with PQ produced from daily prepared colloidal suspensions and solutions with bulk powders of nTiO₂ (75% anatase, 25% rutile; AEROXIDE P25; Evonik [Reference 718467 Sigma-Aldrich]) and PQ dichloride hydrate (Reference 856177; Sigma-Aldrich, France). All colloidal suspensions and solutions were prepared using ultrapure water (18.2 MΩ cm resistivity; Milli-Q; Millipore) with nTiO₂ and PQ concentrations of 3 g L⁻¹ and 28 mg L⁻¹ respectively and were kept under constant stirring during the nebulization process using a magnetic stirrer. These concentrations were used in order to produce aerosols achieving the target concentrations. Concerning the nTiO₂ use in nanopesticides, it is not possible to know the precise mass concentration to which people could be exposed in link with professional or residential exposures. Nevertheless, some authors investigated the mass concentrations of nTiO₂ in Korean production sites, thanks to personal sampling and real-time monitoring using SMPS (Lee et al., 2011). As a result, they highlighted that TiO₂ mass concentrations can reach 4.99 mg m⁻³, involving a particle size range of 15–710.5 nm. In addition, to be comparable with other studies dealing with nTiO₂ inhalation that showed relevant toxicological endpoints using rodents (Bermudez et al., 2004; Disdier et al., 2017; Chézeau et al., 2019), a target concentration of 10 mg m⁻³ was chosen.

Concerning PQ, the minimum lethal mass concentration in rats from a single 4-h inhalation exposure was reported to be 0.6–1.4 mg m⁻³ (McLean et al., 1985). Moreover, a 3-week inhalation study in rats reported the lowest observed adverse effect level (LOAEL) of 100 µg m⁻³, based on
<figure><img src="image_5.png" /></figure>

materials. The second step consisting in the neurotoxicological assessment of these aerosols, will be addressed separately in upcoming dedicated articles. Thus, a new whole-body exposure chamber was developed to explore the inhalation effects of aerosols. It is a simple device which can fit easily in any animal facility to be operated safely by conforming with animal welfare. As a complete metrological set-up cannot be implemented permanently in an animal facility for long-term studies, the characterization had to be made prior to the animal exposure. The characterization was made in the LNE (Laboratoire National de métrologie et d'Essais) laboratory, in terms of size distribution (Scanning Mobility Particle Sizer [SMPS] + Aerodynamic Particle Sizer [APS]), mass concentration (Tapered Element Oscillating Microbalance [TEOM] + indirect measurements of the sampled mass on 47-mm filters), number concentration (Condensation Particle Counter [CPC]), temperature, pressure and relative humidity. In addition, based on the particle size distribution, the chamber geometry and the airflows, computational fluid dynamics (CFD) modeling was used to investigate the homogeneity of the particle concentration within the cage. The main goal for the CFD simulation was to investigate the fill-up process of the chamber, the possibility of error induced by the relative positions of the injection tube and the measurement sampling tube. These parameters were assessed in accordance with the standard method on the reproducibility measurement (ISO 5725-2:2020).

Because it is essential to validate the functioning of the characterized aerosol exposure
chamber on the field, here we also report the comparison of the measurements made in the LNE
metrological lab (without animal) in regard to the first preliminary data obtained in the animal
facility (with animals) for each of the three aerosols. During the animal exposure, a reduced
monitoring of the aerosol was used to check the proper aerosol generation, to enable a precise
metrological follow-up of the exposures. The mass concentration and the particle number
concentration were therefore used to validate animal exposure sessions in accordance with the
metrological characterization phase.

2 MATERIALS AND METHODS

## 2.1 Inhalation Exposure Chamber

The exposure chamber is composed of a rodent cage used as a whole-body exposure system (Fig. 1). The chamber was sealed and customized with antistatic silicon pipes to be integrated within the generation device. This cage, initially dedicated to rodents hosting (rats, mice, hamsters or others) in animal facilities, is made out of polysulfone (internal volume of 19.8 L, overall dimensions of 395 × 346 × 213 mm [W × D × H]; GR900; Tecniplast). It was selected for the chemical resistance and the transparency of this material (Tuttle *et al.*, 2010), which allowed a visual follow-up of animals during the exposure sessions. Coupled with this chamber, an aerosol nebulizer (Model 3076; TSI Inc.) was operated to generate three aerosols of interest, i.e., nTiO₂, PQ and nTiO₂ with PQ produced from daily prepared colloidal suspensions and solutions with bulk powders of nTiO₂ (75% anatase, 25% rutile; AEROXIDE P25; Evonik [Reference 718467 Sigma-Aldrich]) and PQ dichloride hydrate (Reference 856177; Sigma-Aldrich, France). All colloidal suspensions and solutions were prepared using ultrapure water (18.2 MΩ cm resistivity; Milli-Q; Millipore) with nTiO₂ and PQ concentrations of 3 g L⁻¹ and 28 mg L⁻¹ respectively and were kept under constant stirring during the nebulization process using a magnetic stirrer. These concentrations were used in order to produce aerosols achieving the target concentrations. Concerning the nTiO₂ use in nanopesticides, it is not possible to know the precise mass concentration to which people could be exposed in link with professional or residential exposures. Nevertheless, some authors investigated the mass concentrations of nTiO₂ in Korean production sites, thanks to personal sampling and real-time monitoring using SMPS (Lee *et al.*, 2011). As a result, they highlighted that TiO₂ mass concentrations can reach 4.99 mg m⁻³, involving a particle size range of 15–710.5 nm. In addition, to be comparable with other studies dealing with nTiO₂ inhalation that showed relevant toxicological endpoints using rodents (Bermudez *et al.*, 2004; Disdier *et al.*, 2017; Chézeau *et al.*, 2019), a target concentration of 10 mg m⁻³ was chosen.

Concerning PQ, the minimum lethal mass concentration in rats from a single 4-h inhalation exposure was reported to be 0.6–1.4 mg m⁻³ (McLean *et al.*, 1985). Moreover, a 3-week inhalation study in rats reported the lowest observed adverse effect level (LOAEL) of 100 µg m⁻³, based on
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 1.** Experimental set-up of the inhalation exposure chamber. The part surrounded by a red dotted line corresponds to the instruments used only for the metrological characterization phase; the different flowrates are presented in red. MFC: mass flow controller.</figcaption></figure>

the histopathological changes in the upper respiratory tract (Grimshav *et al.*, 1979). Thus, the target concentration of 100 µg m⁻³ corresponding to the National Institute for Occupational Safety and Health (NIOSH) occupational limit was chosen to avoid pain and distress. This concentration is also in line with the 125 µg m⁻³ occupational exposure reported by Morshed *et al.* (2010). The mixture being composed of both nTiO₂ and PQ aerosols, its target concentration was assumed to be 10.1 mg m⁻³. The doses were chosen to be both relevant doses and realistic to cause slight adverse effects in the lungs due to inflammation and oxidative stress, in order to investigate any potential synergy effects due to the mixture. Briefly, these concentrations can be extrapolated to human beings based on the aerosol characterization using the Multiple-Path Particle Dosimetry Model (MPPD), and they are comparable with the NIOSH recommendations for nTiO₂ and PQ. The target concentration choice was made to highlight any possible cocktail effects between nTiO₂ and PQ within a toxicology protocol involving chronic exposures.

The nebulizer (Model 3076; TSI Inc.) produced stable particle concentrations using compressed air (Pujalté *et al.*, 2017b). It was operated at 2.4 bar which supplied a constant flowrate of 3.2 L min⁻¹. The compressed air was supplied by a silent air compressor coupled with a filtration and drying device (Model 3074B; TSI Inc.). The produced airflow enabled a controlled dilution of the generated aerosols entering the exposure chamber. It was also dedicated to the dilution of a CPC to prevent the instrument upper range (10⁵ particles cm⁻³) to be exceeded. The instrument airflow was checked for each aerosol generation to adjust concentrations with the proper dilution factor. Two downstream diffusion dryers were used to obtain aerosols with a steady relative humidity
<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 1.** Experimental set-up of the inhalation exposure chamber. The part surrounded by a red dotted line corresponds to the instruments used only for the metrological characterization phase; the different flowrates are presented in red. MFC: mass flow controller.</figcaption></figure>

the histopathological changes in the upper respiratory tract (Grimshav *et al.*, 1979). Thus, the target concentration of 100 µg m⁻³ corresponding to the National Institute for Occupational Safety and Health (NIOSH) occupational limit was chosen to avoid pain and distress. This concentration is also in line with the 125 µg m⁻³ occupational exposure reported by Morshed *et al.* (2010). The mixture being composed of both nTiO₂ and PQ aerosols, its target concentration was assumed to be 10.1 mg m⁻³. The doses were chosen to be both relevant doses and realistic to cause slight adverse effects in the lungs due to inflammation and oxidative stress, in order to investigate any potential synergy effects due to the mixture. Briefly, these concentrations can be extrapolated to human beings based on the aerosol characterization using the Multiple-Path Particle Dosimetry Model (MPPD), and they are comparable with the NIOSH recommendations for nTiO₂ and PQ. The target concentration choice was made to highlight any possible cocktail effects between nTiO₂ and PQ within a toxicology protocol involving chronic exposures.

The nebulizer (Model 3076; TSI Inc.) produced stable particle concentrations using compressed air (Pujalté *et al.*, 2017b). It was operated at 2.4 bar which supplied a constant flowrate of 3.2 L min⁻¹. The compressed air was supplied by a silent air compressor coupled with a filtration and drying device (Model 3074B; TSI Inc.). The produced airflow enabled a controlled dilution of the generated aerosols entering the exposure chamber. It was also dedicated to the dilution of a CPC to prevent the instrument upper range (10⁵ particles cm⁻³) to be exceeded. The instrument airflow was checked for each aerosol generation to adjust concentrations with the proper dilution factor. Two downstream diffusion dryers were used to obtain aerosols with a steady relative humidity
<figure><img src="image_7.png" /></figure>

during the assays. The aerosols were injected horizontally thanks to a four-branched input in the top of the chamber in order to optimize the dispersion of particles. APS, SMPS and TEOM, which were present only during the characterization phase, needed a total flowrate of 5.8 L min⁻¹. SMPS and TEOM airflows were not diluted while a dilution of the APS flowrate was set at 2.5 L min⁻¹. The sample outlet flowrate of the exposure chamber was therefore set at 7.8 L min⁻¹ thanks to the global instrumental flowrate (5.8 L min⁻¹), the filter holder sampling (1.7 L min⁻¹) and the CPC (0.3 L min⁻¹). In absence of the instruments used for the metrological characterization phase, a 7.5 L min⁻¹ flowrate was set for the filter-holder sampling line. To comply with OECD TG 413 guidelines, temperature, pressure, relative humidity and airflows were monitored in the chamber as environmental parameters during the characterization.

## 2.2 Aerosol Characterization and Monitoring

To characterize particle number size distributions (PNSDs), mass and number concentration, a multi-instrumental set-up composed of a real-time monitoring and off-line aerosol samplings was used (Fig. 1, part surrounded by a red dotted line). PNSDs of submicronic aerosols were measured thanks to an SMPS (TSI Inc.) composed of a differential mobility analyzer (DMA; Model 3081; TSI Inc.) and a CPC (Model 3775; TSI Inc.). An APS (Model 3321; TSI Inc.) monitored the 0.6–20 µm particle size range. At the top of the exposure chamber, a CPC (Model 3007; TSI Inc.) was set up to measure the total particle number concentrations in real time during the metrological characterization and during the exposure sessions. Total mass concentrations were measured in real time using a TEOM (Model 1400; Thermo Fisher Scientific Inc.) set at 50°C during the characterization, and a 47-mm filter holder allowed a gravimetric monitoring of aerosols during the exposure phase. This latter gravimetric measurement was performed to assess the mass concentrations, by using the mass difference between pre- and post-sampling filters, to be compared with the real-time aerosol mass concentrations assessed with TEOM. The aerosol filtration was made by a filter holder with 47-mm filters (Pallflex® Emfab TX40HI20WW; Pall Corp.) made out of borosilicate glass microfibers reinforced with woven glass cloth and bonded with PTFE. The filter holder was used to enable a complementary indirect gravimetric measurement during the characterization phase as well as the exposure phase. Gaie-Levrel et al. (2018) reported the use of these filters, which filtration efficiency was measured to characterize the most penetrating particle size (MPPS). For the size range of 100 nm particles, the filtration efficiency was 99.97%. Consequently, the sample's fraction of particles on 47-mm filters is representative of the total mass concentration. This filter holder was also coupled with a downstream high-efficiency particulate air (HEPA) filter to prevent any potential particle release during the experiment. Filters may adsorb water, which would alter the quality of particle mass concentration assessment. Nevertheless, our experimental procedure was compared with the reference values of mass concentrations measured with TEOM during the metrological characterization phase to check the consistency between both measurement techniques. A maximum deviation of 3% was obtained by comparing TEOM results with gravimetric analysis on filters.

The TEOM mass concentration measurements were not possible to achieve on a daily basis during the exposures of animal. Therefore, thanks to the 47-mm filter holder, the mass concentration was measured for each experiment, based on the mass difference between pre- and post-sampling filters. These concentrations were used to check the steady functioning of aerosol generation during animal exposure, using as a reference the TEOM characterization data made in real time during the characterization.

For the metrological characterization, 10 experiments of 2 h were performed on five days without animals, in order to characterize each generated aerosol, i.e., PQ, nTiO₂ and PQ + nTiO₂. To assess the reproducibility of the generation method, the relative reproducibility standard deviation (SR) according to the ISO 5725-2 standard (ISO 5725-2:2020) was reported. Due to the containment requirements of the animal facility (biosafety levels 1, 2 and 3), all objects entering the building must be sterilized and only workers accredited in animal experimentation can use the facility. As a consequence, it was technically impossible to use all the metrology instruments in situ within the animal facility. Therefore, the characterization phase was performed prior to animal experimentation without animal, to use the average number and mass concentrations as tracking parameters to validate the proper aerosol generation during the animal exposure. The exposure campaign, in presence of mice, consisted in 11 exposure sessions of 1.5 h for each aerosol,
<figure><img src="image_8.png" /></figure>

during the assays. The aerosols were injected horizontally thanks to a four-branched input in the top of the chamber in order to optimize the dispersion of particles. APS, SMPS and TEOM, which were present only during the characterization phase, needed a total flowrate of 5.8 L min⁻¹. SMPS and TEOM airflows were not diluted while a dilution of the APS flowrate was set at 2.5 L min⁻¹. The sample outlet flowrate of the exposure chamber was therefore set at 7.8 L min⁻¹ thanks to the global instrumental flowrate (5.8 L min⁻¹), the filter holder sampling (1.7 L min⁻¹) and the CPC (0.3 L min⁻¹). In absence of the instruments used for the metrological characterization phase, a 7.5 L min⁻¹ flowrate was set for the filter-holder sampling line. To comply with OECD TG 413 guidelines, temperature, pressure, relative humidity and airflows were monitored in the chamber as environmental parameters during the characterization.

## 2.2 Aerosol Characterization and Monitoring

To characterize particle number size distributions (PNSDs), mass and number concentration, a multi-instrumental set-up composed of a real-time monitoring and off-line aerosol samplings was used (Fig. 1, part surrounded by a red dotted line). PNSDs of submicronic aerosols were measured thanks to an SMPS (TSI Inc.) composed of a differential mobility analyzer (DMA; Model 3081; TSI Inc.) and a CPC (Model 3775; TSI Inc.). An APS (Model 3321; TSI Inc.) monitored the 0.6–20 µm particle size range. At the top of the exposure chamber, a CPC (Model 3007; TSI Inc.) was set up to measure the total particle number concentrations in real time during the metrological characterization and during the exposure sessions. Total mass concentrations were measured in real time using a TEOM (Model 1400; Thermo Fisher Scientific Inc.) set at 50°C during the characterization, and a 47-mm filter holder allowed a gravimetric monitoring of aerosols during the exposure phase. This latter gravimetric measurement was performed to assess the mass concentrations, by using the mass difference between pre- and post-sampling filters, to be compared with the real-time aerosol mass concentrations assessed with TEOM. The aerosol filtration was made by a filter holder with 47-mm filters (Pallflex® Emfab TX40HI20WW; Pall Corp.) made out of borosilicate glass microfibers reinforced with woven glass cloth and bonded with PTFE. The filter holder was used to enable a complementary indirect gravimetric measurement during the characterization phase as well as the exposure phase. Gaie-Levrel et al. (2018) reported the use of these filters, which filtration efficiency was measured to characterize the most penetrating particle size (MPPS). For the size range of 100 nm particles, the filtration efficiency was 99.97%. Consequently, the sample's fraction of particles on 47-mm filters is representative of the total mass concentration. This filter holder was also coupled with a downstream high-efficiency particulate air (HEPA) filter to prevent any potential particle release during the experiment. Filters may adsorb water, which would alter the quality of particle mass concentration assessment. Nevertheless, our experimental procedure was compared with the reference values of mass concentrations measured with TEOM during the metrological characterization phase to check the consistency between both measurement techniques. A maximum deviation of 3% was obtained by comparing TEOM results with gravimetric analysis on filters.

The TEOM mass concentration measurements were not possible to achieve on a daily basis during the exposures of animal. Therefore, thanks to the 47-mm filter holder, the mass concentration was measured for each experiment, based on the mass difference between pre- and post-sampling filters. These concentrations were used to check the steady functioning of aerosol generation during animal exposure, using as a reference the TEOM characterization data made in real time during the characterization.

For the metrological characterization, 10 experiments of 2 h were performed on five days without animals, in order to characterize each generated aerosol, i.e., PQ, nTiO₂ and PQ + nTiO₂. To assess the reproducibility of the generation method, the relative reproducibility standard deviation (SR) according to the ISO 5725-2 standard (ISO 5725-2:2020) was reported. Due to the containment requirements of the animal facility (biosafety levels 1, 2 and 3), all objects entering the building must be sterilized and only workers accredited in animal experimentation can use the facility. As a consequence, it was technically impossible to use all the metrology instruments in situ within the animal facility. Therefore, the characterization phase was performed prior to animal experimentation without animal, to use the average number and mass concentrations as tracking parameters to validate the proper aerosol generation during the animal exposure. The exposure campaign, in presence of mice, consisted in 11 exposure sessions of 1.5 h for each aerosol,
<figure><img src="image_8.png" /></figure>

during which the mass and number concentrations were measured to assess the reproducibility of
the aerosol generation procedure, in order to validate the operating device on the field.

## 2.3 Aerosol Dispersion Modeling

To study the atmosphere homogeneity in the exposure chamber, simulations of the aerosol dispersion were performed for PQ and nTiO₂ aerosols using COMSOL Multiphysics software (version 5.4). A computer-aided design (CAD) model of the test chamber was built and imported in COMSOL. Using the symmetry of the device, half of the chamber was modeled in order to reduce computational time. A preliminary simulation was run to characterize the flow behavior inside the exposure chamber without particles. Reynolds number in the injection tube is evaluated around 1000; hence, a laminar flow formulation of Navier-Stokes equations was used. As the exposure chamber is small, and the ambient temperature is maintained for the duration of the test, it can be assumed that Brownian diffusion will not play an important part in the dispersion of the particles inside the chamber. An order of magnitude computation using the AeroCalc spreadsheet based on Willeke and Baron (2001) shows that diffusion losses are expected to reach a maximum of 2%, given chamber dimensions, flow rate and ambient parameters. It must be noted that such a computation gives a general order of magnitude of the diffusion contribution, which can still be significant at small spatial scale and yield local non-uniformities. Similarly, the small size of the particles leads to negligible inertial effects. Hence, the dispersion analysis was conducted using a passive scalar method. Navier-Stokes equations are resolved on a tetrahedral unstructured mesh with dedicated boundary layers meshing. The mesh includes around 568 k elements, with an average element quality (skewness) of 0.67. Initial conditions are set with no velocity and no particles inside the chamber. At time point T = 0, the fluid flow is ramped up on 3 s, with a target velocity of 0.64 m s⁻¹ at both inlets using the experimental flow rate and an input concentration of 1000 particles m⁻³. The outlet was set at a constant pressure difference of -60 Pa. The simulation was run for 900 s (15 CPUs, 32 GB RAM) of simulated time with a total computation time around 80 min.

## 2.4 Paraquat Stability

Thanks to a UV-visible spectrophotometer (LAMBDA 25; PerkinElmer), suspensions of PQ with nTiO₂ were analyzed at different times, i.e., T = 0, 1, 2 and 24 h, to assess the possible photocatalytic degradations of PQ due to nTiO₂. For PQ, the absorbance peak was selected at 257 nm and by-products of degradations can be potentially observed in the 200–230 nm range (Cantavenera et al., 2007). For instrumental calibration, aqueous solutions of PQ with concentrations ranging from 6.25 to 40 mg L⁻¹ were used. As nTiO₂ absorbs in the UV-visible wavelength, suspensions were filtered (pore diameter of 0.22 µm; Millex-GS Syringe Filter Unit; Millipore) prior to analysis in order to prevent nTiO₂ aggregates to interfere with measurements.

# 3 RESULTS

## 3.1 Environmental Parameters

Temperature (T, °C) and relative humidity (RH) were monitored for 2-h sessions within the exposure chamber during the characterization phase (Fig. S1 in the supplementary data). Average T°C and RH were characterized to be 24.5 ± 0.4°C and 20.1 ± 0.7% respectively with external laboratory conditions of 22.5 ± 1.2°C and 42.5 ± 7.8%. The difference in temperature was induced by the compressor operating temperature, which was comprised between 50–70°C, explaining the slight increase of temperature along the duration of nebulization, and the temperature difference with the lab conditions. At the outlet, a vacuum pump enabled a slight depression in the chamber (–60 ± 4 Pa) preventing the aerosol leakage in the laboratory. Based on the outlet airflow and the chamber volume, the air renewal was 23 volumes h⁻¹.

## 3.2 Particle Number Size Distribution

Figs. 2(A) and 2(B) present the average PNSD measured in the exposure chamber during the characterization phase using SMPS and APS. They were unimodal and broadly ranged from 10 to
<figure><img src="image_9.png" /></figure>

during which the mass and number concentrations were measured to assess the reproducibility of
the aerosol generation procedure, in order to validate the operating device on the field.

## 2.3 Aerosol Dispersion Modeling

To study the atmosphere homogeneity in the exposure chamber, simulations of the aerosol dispersion were performed for PQ and nTiO₂ aerosols using COMSOL Multiphysics software (version 5.4). A computer-aided design (CAD) model of the test chamber was built and imported in COMSOL. Using the symmetry of the device, half of the chamber was modeled in order to reduce computational time. A preliminary simulation was run to characterize the flow behavior inside the exposure chamber without particles. Reynolds number in the injection tube is evaluated around 1000; hence, a laminar flow formulation of Navier-Stokes equations was used. As the exposure chamber is small, and the ambient temperature is maintained for the duration of the test, it can be assumed that Brownian diffusion will not play an important part in the dispersion of the particles inside the chamber. An order of magnitude computation using the AeroCalc spreadsheet based on Willeke and Baron (2001) shows that diffusion losses are expected to reach a maximum of 2%, given chamber dimensions, flow rate and ambient parameters. It must be noted that such a computation gives a general order of magnitude of the diffusion contribution, which can still be significant at small spatial scale and yield local non-uniformities. Similarly, the small size of the particles leads to negligible inertial effects. Hence, the dispersion analysis was conducted using a passive scalar method. Navier-Stokes equations are resolved on a tetrahedral unstructured mesh with dedicated boundary layers meshing. The mesh includes around 568 k elements, with an average element quality (skewness) of 0.67. Initial conditions are set with no velocity and no particles inside the chamber. At time point T = 0, the fluid flow is ramped up on 3 s, with a target velocity of 0.64 m s⁻¹ at both inlets using the experimental flow rate and an input concentration of 1000 particles m⁻³. The outlet was set at a constant pressure difference of -60 Pa. The simulation was run for 900 s (15 CPUs, 32 GB RAM) of simulated time with a total computation time around 80 min.

## 2.4 Paraquat Stability

Thanks to a UV-visible spectrophotometer (LAMBDA 25; PerkinElmer), suspensions of PQ with nTiO₂ were analyzed at different times, i.e., T = 0, 1, 2 and 24 h, to assess the possible photocatalytic degradations of PQ due to nTiO₂. For PQ, the absorbance peak was selected at 257 nm and by-products of degradations can be potentially observed in the 200–230 nm range (Cantavenera et al., 2007). For instrumental calibration, aqueous solutions of PQ with concentrations ranging from 6.25 to 40 mg L⁻¹ were used. As nTiO₂ absorbs in the UV-visible wavelength, suspensions were filtered (pore diameter of 0.22 µm; Millex-GS Syringe Filter Unit; Millipore) prior to analysis in order to prevent nTiO₂ aggregates to interfere with measurements.

# 3 RESULTS

## 3.1 Environmental Parameters

Temperature (T, °C) and relative humidity (RH) were monitored for 2-h sessions within the exposure chamber during the characterization phase (Fig. S1 in the supplementary data). Average T°C and RH were characterized to be 24.5 ± 0.4°C and 20.1 ± 0.7% respectively with external laboratory conditions of 22.5 ± 1.2°C and 42.5 ± 7.8%. The difference in temperature was induced by the compressor operating temperature, which was comprised between 50–70°C, explaining the slight increase of temperature along the duration of nebulization, and the temperature difference with the lab conditions. At the outlet, a vacuum pump enabled a slight depression in the chamber (–60 ± 4 Pa) preventing the aerosol leakage in the laboratory. Based on the outlet airflow and the chamber volume, the air renewal was 23 volumes h⁻¹.

## 3.2 Particle Number Size Distribution

Figs. 2(A) and 2(B) present the average PNSD measured in the exposure chamber during the characterization phase using SMPS and APS. They were unimodal and broadly ranged from 10 to
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /><figcaption>**Fig. 2.** Average PNSD measured in the exposure chamber during the metrological characterization phase using (A) SMPS and (B) APS without animals, for each generated aerosol, i.e., PQ, nTiO₂ and PQ + nTiO₂. (C) PNSD temporal stability based on SMPS measurements for the PQ + nTiO₂ aerosol.</figcaption></figure>

200 nm for PQ and from 15 to 2000 nm for nTiO₂ and PQ with nTiO₂. The count median mobility diameters (CMMDs) were respectively 50 ± 1 nm, 220 ± 7 nm and 173 ± 2 nm for PQ, nTiO₂ and PQ with nTiO₂ aerosols respectively, with uncertainties corresponding to reproducibility standard deviation (SR) in agreement with ISO 5725-2 standard. Modal diameters for each aerosol were respectively 56 ± 1 nm, 264 ± 15 nm and 191 ± 5 nm; mean diameters were respectively 56 ± 1 nm, 264 ± 6 nm and 214 ± 2 nm. PNSDs were stable for 2 h of aerosol generation, as shown in Fig. 2(C), which presents the average PNSD evolution over time for the PQ with nTiO₂ aerosol. PNSDs reached an equilibrium state around 20 min (T₂₀) after the aerosol generation beginning and dropped at 120 min (T₁₂₀), which corresponds to the end of aerosol generation. In the 0.8–20 µm particle size range monitored using APS (Fig. 2(B)), no particles were detected for the aerosol of PQ.

## 3.3 Particle Number Concentration Monitoring

The temporal evolution of the average particle number concentrations during both phases is presented in Fig. 3. The real-time monitoring is shown in Figs. 3(A) and 3(B), while the evolution of the average concentrations for each aerosol generation is presented in Figs. 3(C) and 3(D). The real-time measurements during the metrological characterization (Fig. 3(A)) showed that average concentrations were 258 × 10³ particles cm³ ± 11%, 205 × 10³ particles cm³ ± 10% and
<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /><figcaption>**Fig. 2.** Average PNSD measured in the exposure chamber during the metrological characterization phase using (A) SMPS and (B) APS without animals, for each generated aerosol, i.e., PQ, nTiO₂ and PQ + nTiO₂. (C) PNSD temporal stability based on SMPS measurements for the PQ + nTiO₂ aerosol.</figcaption></figure>

200 nm for PQ and from 15 to 2000 nm for nTiO₂ and PQ with nTiO₂. The count median mobility diameters (CMMDs) were respectively 50 ± 1 nm, 220 ± 7 nm and 173 ± 2 nm for PQ, nTiO₂ and PQ with nTiO₂ aerosols respectively, with uncertainties corresponding to reproducibility standard deviation (SR) in agreement with ISO 5725-2 standard. Modal diameters for each aerosol were respectively 56 ± 1 nm, 264 ± 15 nm and 191 ± 5 nm; mean diameters were respectively 56 ± 1 nm, 264 ± 6 nm and 214 ± 2 nm. PNSDs were stable for 2 h of aerosol generation, as shown in Fig. 2(C), which presents the average PNSD evolution over time for the PQ with nTiO₂ aerosol. PNSDs reached an equilibrium state around 20 min (T₂₀) after the aerosol generation beginning and dropped at 120 min (T₁₂₀), which corresponds to the end of aerosol generation. In the 0.8–20 µm particle size range monitored using APS (Fig. 2(B)), no particles were detected for the aerosol of PQ.

## 3.3 Particle Number Concentration Monitoring

The temporal evolution of the average particle number concentrations during both phases is presented in Fig. 3. The real-time monitoring is shown in Figs. 3(A) and 3(B), while the evolution of the average concentrations for each aerosol generation is presented in Figs. 3(C) and 3(D). The real-time measurements during the metrological characterization (Fig. 3(A)) showed that average concentrations were 258 × 10³ particles cm³ ± 11%, 205 × 10³ particles cm³ ± 10% and
<figure><img src="image_11.png" /></figure>

Metrological characterization

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

Animal exposure

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

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

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

**Fig. 3.** Particle number concentrations measured with CPC during (A, C) the metrological characterization phase and (B, D) the animal exposure sessions. Mean results presented (A, B) in function of time or (C, D) as individual aerosol generations ± standard deviation, the dotted line corresponding to the mean value for each aerosol.

292 × 10³ particles cm³ ± 8% for PQ, nTiO₂ and PQ with nTiO₂ respectively. Comparatively, these concentrations were respectively 249 × 10³ particles cm³ ± 7%, 202 × 10³ particles cm³ ± 8% and 308 × 10³ particles cm³ ± 9% during the animal exposure phase (Fig. 3(B)). The fact that particle number concentration in the mixture do not correspond to the sum of PQ and nTiO₂ number concentrations could be explained by an internal mixing between both components during the aerosol nebulization process. Number concentrations in both conditions reached a steady state between 5 and 10 min; they remained stable over time until the end of the aerosol generation. By taking the metrological characterization phase as reference, the real-time measurements during the first step of the animal exposure phase allowed the validation of the aerosol generation for each inhalation exposure. The results and their S<sub>R</sub> are summarized in Table 1.

**3.4 Total Mass Concentration**

Fig. 4 presents the average mass concentrations measured by TEOM in the exposure chamber during the metrological characterization phase with their corresponding S<sub>R</sub>. The total mass concentrations reached a steady state 10 min after the generation beginning for 2 h of aerosol generation. For PQ, nTiO₂ and PQ with nTiO₂ they were respectively 98.7 ± 3.2 µg m⁻³, 10.2 ± 0.9 mg m⁻³ and 10.2 ± 0.4 mg m⁻³. These values comply with the target concentrations of 100 µg m⁻³ and 10 mg m⁻³ for PQ, nTiO₂ and PQ with nTiO₂. Comparatively, during the exposure sessions, the average mass concentrations were 10.1 ± 0.4 mg m⁻³ for nTiO₂ and 9.9 ± 0.8 mg m⁻³ for PQ with nTiO₂.
<figure><img src="image_12.png" /></figure>

Metrological characterization

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

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

Animal exposure

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

<figure><img src="image_16.png" /></figure>

**Fig. 3.** Particle number concentrations measured with CPC during (A, C) the metrological characterization phase and (B, D) the animal exposure sessions. Mean results presented (A, B) in function of time or (C, D) as individual aerosol generations ± standard deviation, the dotted line corresponding to the mean value for each aerosol.

292 × 10³ particles cm³ ± 8% for PQ, nTiO₂ and PQ with nTiO₂ respectively. Comparatively, these concentrations were respectively 249 × 10³ particles cm³ ± 7%, 202 × 10³ particles cm³ ± 8% and 308 × 10³ particles cm³ ± 9% during the animal exposure phase (Fig. 3(B)). The fact that particle number concentration in the mixture do not correspond to the sum of PQ and nTiO₂ number concentrations could be explained by an internal mixing between both components during the aerosol nebulization process. Number concentrations in both conditions reached a steady state between 5 and 10 min; they remained stable over time until the end of the aerosol generation. By taking the metrological characterization phase as reference, the real-time measurements during the first step of the animal exposure phase allowed the validation of the aerosol generation for each inhalation exposure. The results and their S<sub>R</sub> are summarized in Table 1.

**3.4 Total Mass Concentration**

Fig. 4 presents the average mass concentrations measured by TEOM in the exposure chamber during the metrological characterization phase with their corresponding S<sub>R</sub>. The total mass concentrations reached a steady state 10 min after the generation beginning for 2 h of aerosol generation. For PQ, nTiO₂ and PQ with nTiO₂ they were respectively 98.7 ± 3.2 µg m⁻³, 10.2 ± 0.9 mg m⁻³ and 10.2 ± 0.4 mg m⁻³. These values comply with the target concentrations of 100 µg m⁻³ and 10 mg m⁻³ for PQ, nTiO₂ and PQ with nTiO₂. Comparatively, during the exposure sessions, the average mass concentrations were 10.1 ± 0.4 mg m⁻³ for nTiO₂ and 9.9 ± 0.8 mg m⁻³ for PQ with nTiO₂.
<figure><img src="image_16.png" /><figcaption>**Table 1.** Mass and number concentrations measured during the metrological characterization phase and the animal exposure sessions. Results are presented as averages ± S<sub>R</sub> with their corresponding relative S<sub>R</sub> in brackets.</figcaption></figure>

<table><thead><tr><th rowspan="2">Aerosol</th><th colspan="2">Average mass concentration [mg m<sup>-3</sup>]</th><th colspan="2">Average number concentration [× 10<sup>3</sup> particles cm<sup>-3</sup>]</th></tr><tr><th>Metrological characterization</th><th>Animal exposure*</th><th>Metrological characterization</th><th>Animal exposure</th></tr></thead><tbody><tr><td>PQ</td><td>98.7 [10<sup>-3</sup>] ± 3.2 (3%)</td><td>–</td><td>258 ± 29 (11%)</td><td>249 ± 17 (7%)</td></tr><tr><td>nTiO<sub>2</sub></td><td>10.2 ± 0.9 (9%)</td><td>10.1 ± 0.4 (4%)</td><td>205 ± 21 (10%)</td><td>202 ± 17 (8%)</td></tr><tr><td>PQ + nTiO<sub>2</sub></td><td>10.2 ± 0.4 (4%)</td><td>9.9 ± 0.8 (8%)</td><td>292 ± 22 (8%)</td><td>308 ± 27 (9%)</td></tr></tbody></table>

-: Data not available. * Off-line gravimetric measurements.

<figure><img src="image_17.png" /><figcaption>**Fig. 4.** Average total mass concentration in the exposure chamber using TEOM for 2 h of aerosol generation without animals. Results are presented as averages ± standard deviation (dotted lines) in function of time.</figcaption></figure>

## 3.5 Aerosol Dispersion Modeling

According to the PNSD values assessed during the prior characterization, no difference was observed by simulation in the particle dispersion between PQ and nTiO₂ (data not shown). Consequently, nTiO₂ aerosol was selected according to their characterized mean diameter (264 nm). Fig. 5(A) presents the chamber and its associated CAD model used for the simulation. Fig. 5(B) shows the particle number concentration simulation at T = 10 min and T = 15 min. At T = 10 min, the atmosphere was still heterogeneous, since the top area of the exposure chamber presented a slightly higher particle concentration, whereas a lower concentration was observable in the middle zone and at the bottom corner below the injection site. This atmosphere heterogeneity decreased over time and the atmosphere became mostly homogeneous at T = 15 min. Such a result is expected as the simulation was made using a passive scalar method (no diffusion, no inertia). As the characterization was made using aerosol sampling from the top of the chamber, the atmosphere homogeneity was assessed to check if the aerosol characterization reflected what animals were really breathing during exposures. To this end, the simulated number concentrations were specifically obtained in the transverse plane the chamber floor (at a height of 1 cm) corresponding to the breathing area of mice. In addition, particle size distributions were compared using SMPS in both top and floor areas and no difference in the particle size distribution were visible between sampling points (data not shown) highlighting the aerosol spatial homogeneity of particles. Fig. 5(C) compared the simulated and the experimental average number concentrations
<figure><img src="image_17.png" /><figcaption>**Table 1.** Mass and number concentrations measured during the metrological characterization phase and the animal exposure sessions. Results are presented as averages ± S<sub>R</sub> with their corresponding relative S<sub>R</sub> in brackets.</figcaption></figure>

<table><thead><tr><th rowspan="2">Aerosol</th><th colspan="2">Average mass concentration [mg m<sup>-3</sup>]</th><th colspan="2">Average number concentration [× 10<sup>3</sup> particles cm<sup>-3</sup>]</th></tr><tr><th>Metrological characterization</th><th>Animal exposure*</th><th>Metrological characterization</th><th>Animal exposure</th></tr></thead><tbody><tr><td>PQ</td><td>98.7 [10<sup>-3</sup>] ± 3.2 (3%)</td><td>—</td><td>258 ± 29 (11%)</td><td>249 ± 17 (7%)</td></tr><tr><td>nTiO<sub>2</sub></td><td>10.2 ± 0.9 (9%)</td><td>10.1 ± 0.4 (4%)</td><td>205 ± 21 (10%)</td><td>202 ± 17 (8%)</td></tr><tr><td>PQ + nTiO<sub>2</sub></td><td>10.2 ± 0.4 (4%)</td><td>9.9 ± 0.8 (8%)</td><td>292 ± 22 (8%)</td><td>308 ± 27 (9%)</td></tr></tbody></table>

<figure><img src="image_18.png" /><figcaption>**Fig. 4.** Average total mass concentration in the exposure chamber using TEOM for 2 h of aerosol generation without animals. Results are presented as averages ± standard deviation (dotted lines) in function of time.</figcaption></figure>

## 3.5 Aerosol Dispersion Modeling

According to the PNSD values assessed during the prior characterization, no difference was observed by simulation in the particle dispersion between PQ and nTiO₂ (data not shown). Consequently, nTiO₂ aerosol was selected according to their characterized mean diameter (264 nm). Fig. 5(A) presents the chamber and its associated CAD model used for the simulation. Fig. 5(B) shows the particle number concentration simulation at T = 10 min and T = 15 min. At T = 10 min, the atmosphere was still heterogeneous, since the top area of the exposure chamber presented a slightly higher particle concentration, whereas a lower concentration was observable in the middle zone and at the bottom corner below the injection site. This atmosphere heterogeneity decreased over time and the atmosphere became mostly homogeneous at T = 15 min. Such a result is expected as the simulation was made using a passive scalar method (no diffusion, no inertia). As the characterization was made using aerosol sampling from the top of the chamber, the atmosphere homogeneity was assessed to check if the aerosol characterization reflected what animals were really breathing during exposures. To this end, the simulated number concentrations were specifically obtained in the transverse plane the chamber floor (at a height of 1 cm) corresponding to the breathing area of mice. In addition, particle size distributions were compared using SMPS in both top and floor areas and no difference in the particle size distribution were visible between sampling points (data not shown) highlighting the aerosol spatial homogeneity of particles. Fig. 5(C) compared the simulated and the experimental average number concentrations

<footnote>-: Data not available. * Off-line gravimetric measurements.</footnote>
<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /><figcaption>**Fig. 5.** (A) Chamber pictures and their associated CAD model used for simulation; 1: aerosol sampling point used for CPC measurements; 2: inlet; 3: outlet. (B) Results of the particle number concentration simulation at 10 min and 15 min within the sagittal plane (at the top) and a transverse plane (at the bottom) that represents the chamber floor (+1 cm) corresponding to the breathing area of mice. (C) Comparison of the experimental and simulated normalized particle number concentrations within the exposure chamber. (D) Normalized particle number concentrations assessed by simulation in planes located at different heights: 20 cm (top), 10 cm (middle) and 1 cm (bottom). T95: needed time to reach 95% of the atmosphere equilibration in the chamber.</figcaption></figure>

in the chamber over time. According to the guidelines for subchronic inhalation toxicology studies (OECD TG 413), T95 can be defined as the time required to reach 95% of the atmosphere steadiness in the exposure chamber. It was reached at T = 377 s by simulation and T = 428 s
<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

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

<figure><img src="image_23.png" /></figure>

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

**Fig. 5.** (A) Chamber pictures and their associated CAD model used for simulation; 1: aerosol sampling point used for CPC measurements; 2: inlet; 3: outlet. (B) Results of the particle number concentration simulation at 10 min and 15 min within the sagittal plane (at the top) and a transverse plane (at the bottom) that represents the chamber floor (+1 cm) corresponding to the breathing area of mice. (C) Comparison of the experimental and simulated normalized particle number concentrations within the exposure chamber. (D) Normalized particle number concentrations assessed by simulation in planes located at different heights: 20 cm (top), 10 cm (middle) and 1 cm (bottom). T95: needed time to reach 95% of the atmosphere equilibration in the chamber.

in the chamber over time. According to the guidelines for subchronic inhalation toxicology studies (OECD TG 413), T95 can be defined as the time required to reach 95% of the atmosphere steadiness in the exposure chamber. It was reached at T = 377 s by simulation and T = 428 s
<figure><img src="image_20.png" /></figure>

according to the experimental data, which highlighted the consistency between both datasets. In the exposure chamber, the breathing area of mice was in the range of 1–10 cm height, while the CPC measurement spot was located at the top of the chamber (20 cm height). To check if the sampling location could affect the particle concentrations, three transverse planes were defined inside the chamber at different heights (1 cm, 10 cm and 20 cm). Based on the simulated data, average number concentrations were calculated for each plane and T<sub>95</sub> were respectively 382 s, 475 s, and 446 s (Fig. 5(D)). At 8 min, a plateau corresponding to the atmosphere steady state was reached, showing the representativity of the aerosol sampling location at the top of the chamber compared to the mice breathing area at the bottom.

## 3.6 Paraquat Stability

Regarding the stability of PQ + nTiO<sub>2</sub> suspension, no significant decrease of PQ concentration was detectable up to 24 h after the solution preparation (Fig. S2). The concentration at T<sub>0</sub>, T<sub>120</sub> and T<sub>24</sub> hours were respectively 24.0 mg L<sup>-1</sup>, 23.6 mg L<sup>-1</sup> and 23.1 mg L<sup>-1</sup>. This slight decrease correlated with an increase in the 200–230 nm range corresponding to by-product formation (Cantavenera *et al.*, 2007). PQ concentration was expected to decrease, by the nTiO<sub>2</sub> filtration process if adsorbed, which was not the case.

# 4 DISCUSSION

In this article, an experimental set-up complying with OECD TG 413 guidelines, dedicated to inhalation toxicology studies with rodents is presented. The nanopesticide inhalation effects are still not addressed in the literature. Besides the novelty of this field of research, the insights of the article rely mainly in the fact that no whole-body chamber has already been used and characterized in this context. The cocktail effects associating nanomaterials and toxic substances have already been reported in numerous ecotoxicological studies, for instance as reviewed by Naasz *et al.* (2018), but not in toxicological studies. Thus, it seems essential to extend this novel topic of research to human health, by beginning to investigate the underlying mechanisms of toxicity, namely on the nervous system which is known to be a specific target of some nanosized toxics (Bencsik *et al.*, 2018). Consequently, the protocol was established by generating inhalable particles whose size is characterized, in order to model the deposit fraction in the airways in upcoming article involving this device, to provide health data related to characterized exposure concentrations and conditions, for regulatory and toxicology purposes. In addition, nanopesticides represent a variety of different products, requiring a case-by-case toxic assessment depending on the conditions of use. The facility could be used to investigate other kind of nanosized substances, on the condition that a minimal characterization of aerosol is reported (size distribution, mass and number concentrations).

Stringent requirements are needed for chronic studies, like stated in the OECD TG 413 guidelines, as this facility is meant to be able to perform subchronic inhalation study lasting more than 30 days. The choice of a nebulizer reflects agricultural use of pesticides, which are typically sprayed using hydraulic nozzles (Hilz and Vermeer, 2013). The humidity control is essential to avoid the generation of too-large aggregates and agglomerates, and to avoid the proliferation of microorganisms within the cage. In comparison to dry powder generation process, wet aerosol generation is more similar to sprayings. Two diffusion dryers were required to obtain a steady humidity for generations of 2 h, by making a fast evaporation of the droplets before entering the exposure chamber. Nevertheless, this is indeed a model of generation and not an exact representation of the droplet size distribution generated with a hydraulic nozzle. In addition, some authors suggested that this type of nebulizer could represent a most versatile choice, suitable for inhalation toxicology studies (Schmoll *et al.*, 2009; Pujalté *et al.*, 2017b). The stability of the exposure conditions and the test atmosphere were characterized in order to comply with the OECD requirements for the testing of chemicals by inhalation. Environmental parameters (exposure chamber airflows, temperature and relative humidity) and test atmosphere were characterized in terms of number size distribution, number and mass concentrations and spatio-temporal aerosol stability. To be consistent between both phases of this study, the animal exposure session includes a real-time concentration monitoring and a gravimetric sampling that are used in a complementary manner, in order to confirm the generation stability of aerosols. As a result, no significant difference was found between both
<figure><img src="image_25.png" /></figure>

according to the experimental data, which highlighted the consistency between both datasets. In the exposure chamber, the breathing area of mice was in the range of 1–10 cm height, while the CPC measurement spot was located at the top of the chamber (20 cm height). To check if the sampling location could affect the particle concentrations, three transverse planes were defined inside the chamber at different heights (1 cm, 10 cm and 20 cm). Based on the simulated data, average number concentrations were calculated for each plane and T<sub>95</sub> were respectively 382 s, 475 s, and 446 s (Fig. 5(D)). At 8 min, a plateau corresponding to the atmosphere steady state was reached, showing the representativity of the aerosol sampling location at the top of the chamber compared to the mice breathing area at the bottom.

## 3.6 Paraquat Stability

Regarding the stability of PQ + nTiO<sub>2</sub> suspension, no significant decrease of PQ concentration was detectable up to 24 h after the solution preparation (Fig. S2). The concentration at T<sub>0</sub>, T<sub>120</sub> and T<sub>24</sub> hours were respectively 24.0 mg L<sup>-1</sup>, 23.6 mg L<sup>-1</sup> and 23.1 mg L<sup>-1</sup>. This slight decrease correlated with an increase in the 200–230 nm range corresponding to by-product formation (Cantavenera *et al.*, 2007). PQ concentration was expected to decrease, by the nTiO<sub>2</sub> filtration process if adsorbed, which was not the case.

# 4 DISCUSSION

In this article, an experimental set-up complying with OECD TG 413 guidelines, dedicated to inhalation toxicology studies with rodents is presented. The nanopesticide inhalation effects are still not addressed in the literature. Besides the novelty of this field of research, the insights of the article rely mainly in the fact that no whole-body chamber has already been used and characterized in this context. The cocktail effects associating nanomaterials and toxic substances have already been reported in numerous ecotoxicological studies, for instance as reviewed by Naasz *et al.* (2018), but not in toxicological studies. Thus, it seems essential to extend this novel topic of research to human health, by beginning to investigate the underlying mechanisms of toxicity, namely on the nervous system which is known to be a specific target of some nanosized toxics (Bencsik *et al.*, 2018). Consequently, the protocol was established by generating inhalable particles whose size is characterized, in order to model the deposit fraction in the airways in upcoming article involving this device, to provide health data related to characterized exposure concentrations and conditions, for regulatory and toxicology purposes. In addition, nanopesticides represent a variety of different products, requiring a case-by-case toxic assessment depending on the conditions of use. The facility could be used to investigate other kind of nanosized substances, on the condition that a minimal characterization of aerosol is reported (size distribution, mass and number concentrations).

Stringent requirements are needed for chronic studies, like stated in the OECD TG 413 guidelines, as this facility is meant to be able to perform subchronic inhalation study lasting more than 30 days. The choice of a nebulizer reflects agricultural use of pesticides, which are typically sprayed using hydraulic nozzles (Hilz and Vermeer, 2013). The humidity control is essential to avoid the generation of too-large aggregates and agglomerates, and to avoid the proliferation of microorganisms within the cage. In comparison to dry powder generation process, wet aerosol generation is more similar to sprayings. Two diffusion dryers were required to obtain a steady humidity for generations of 2 h, by making a fast evaporation of the droplets before entering the exposure chamber. Nevertheless, this is indeed a model of generation and not an exact representation of the droplet size distribution generated with a hydraulic nozzle. In addition, some authors suggested that this type of nebulizer could represent a most versatile choice, suitable for inhalation toxicology studies (Schmoll *et al.*, 2009; Pujalté *et al.*, 2017b). The stability of the exposure conditions and the test atmosphere were characterized in order to comply with the OECD requirements for the testing of chemicals by inhalation. Environmental parameters (exposure chamber airflows, temperature and relative humidity) and test atmosphere were characterized in terms of number size distribution, number and mass concentrations and spatio-temporal aerosol stability. To be consistent between both phases of this study, the animal exposure session includes a real-time concentration monitoring and a gravimetric sampling that are used in a complementary manner, in order to confirm the generation stability of aerosols. As a result, no significant difference was found between both
<figure><img src="image_21.png" /></figure>

phases. Between all aerosol generations, the chamber average concentrations did not deviate from the mean by more than ± 20%. Moreover, the time to reach the chamber equilibration (T95) was around 7 min, which is short in comparison with the total duration of exposures. Three different aerosols were generated with a homogeneous and unimodal number size distribution, characterized by a CMMD of 50 nm for PQ, 173 nm for nTiO2 and 220 nm for PQ with nTiO2, with respective geometric standard deviations (GSDs) of 1.7, 2.1 and 2.2. The CMMD differences between the mixture and the compounds alone could be explained by the internal mixing between PQ and nTiO2 during the aerosol nebulization process. This can be clearly observed on the corresponding size distribution which is a convolution of PQ and nTiO2 size distributions. The reproducibility standard deviation was comprised between 3–9% for mass concentrations and 7–11% for particle number concentrations. The size of primary nTiO2 particles used in the study is 22 nm as previously described (Motzkus et al., 2014). However, the generation in the aerosol phase of individual primary particles is impossible due to high Van der Waals forces which do not allow dissociation of aggregates. Thus, the nebulization process enables a deagglomeration but not a disaggregation, explaining the mean size of 264 nm, as it was already previously discussed (Gaie-Levrel et al., 2020).

The characteristics comparison of existing exposure chambers may be inappropriate, because each system has its own requirements, depending on the protocol to achieve. The device presented in this article is in accordance with our expectations and the system was validated for our experimental conditions. It has general advantages; it is easy to transport, economical, compact, and thus adaptable to the constraints of animal facilities. It is also simple to operate and easily put in place, and it offers versatility to work with various rodent species (mice, rats, hamster or others). Moreover, the atmosphere homogeneity was assessed temporally and spatially, and both experimental and simulated data were consistent during the characterization and the exposures. These important features (mass concentration and size distribution) enabled a precise assessment of the exposure dose of animals, which is an essential requirement in chronic inhalation toxicology studies. Regarding the accuracy of data, our device compares advantageously to others. Cosnier et al. (2017) reported the generation of P25 nTiO₂ aerosols using a rotation brush generator coupled with a nose-only device. Based on the target mass concentration of 10 mg m⁻³, the calculated CMMD was 347 nm with a GSD of 2.29. The mean intra-experiment precision was comprised between 14% and 22% over six inhalation campaigns. Focusing on studies involving nTiO₂ nebulizers, Pujalté et al. (2017a) generated aerosols at a mass concentration of 15.57 mg m⁻³ (min–max of 9–21 mg m⁻³) using a six-jet collision nebulizer with PNSD characterized by a GSD of 1.87 and a geometric mean diameter of 76.91 nm. Using also a six-jet collision nebulizer, Grassian et al. (2007) generated aerosols of nTiO₂ using a whole-body device for different exposure scenarios, which involved a subacute exposure (10 days, 4 h per day) at a mass concentration of 8.88 ± 1.98 mg m⁻³ with PNSD characterized by a geometrical mean diameter of 128 nm (GSD of 1.7). Yi et al. (2013) used an innovative nebulizer to produce aerosol of nTiO₂ with PNSD characterized by a CMMD of 145 nm and a GSD of 2.3 in a 500 L whole-body inhalation exposure chamber. In their article, the atmosphere spatial homogeneity was assessed, by measuring the concentrations at different spots within the chamber, thereby showing a spatial maximum relative deviation from the mean concentration < 6%.

In this study, specific care was taken concerning animal welfare to reduce stress. This is a matter of prime importance, because a stress undergone during gestation is critical for the fetal development, and then prenatal stress can have long-term consequences for the offspring (Weinstock, 2005). Consequently, the maternal stress in rodents, possibly due to restraint of poor exposure chamber design, may exacerbate negative developmental effects (Rasco and Hood, 1995). In this regard, we selected a whole-body inhalation device to expose animals, as this cage allowed daily exposures with a direct visual follow-up without constraint. It also enables animals to move freely, which simulates a physical activity enhancing the pulmonary ventilation of mice to reflect more accurately occupational exposures. Glass and stainless steel are the classical material used in whole-body devices, because of their ability to age slowly compared to plastics (Dorato and Wolff, 1991). Some authors used stainless steel exposure chamber with a vertical injection flow (Kimmel et al., 1997) or a combination of vertical and horizontal flows input/output to reach a uniform aerosol concentration (Oldham et al., 2004). In our study, we chose a polysulfone cage dedicated to rodent hosting, because it is an inexpensive alternative, which is easy to accommodate in a rodent facility. It can be used to expose mice or other species continuously in
<figure><img src="image_26.png" /></figure>

phases. Between all aerosol generations, the chamber average concentrations did not deviate from the mean by more than ± 20%. Moreover, the time to reach the chamber equilibration (T95) was around 7 min, which is short in comparison with the total duration of exposures. Three different aerosols were generated with a homogeneous and unimodal number size distribution, characterized by a CMMD of 50 nm for PQ, 173 nm for nTiO₂ and 220 nm for PQ with nTiO₂, with respective geometric standard deviations (GSDs) of 1.7, 2.1 and 2.2. The CMMD differences between the mixture and the compounds alone could be explained by the internal mixing between PQ and nTiO₂ during the aerosol nebulization process. This can be clearly observed on the corresponding size distribution which is a convolution of PQ and nTiO₂ size distributions. The reproducibility standard deviation was comprised between 3–9% for mass concentrations and 7–11% for particle number concentrations. The size of primary nTiO₂ particles used in the study is 22 nm as previously described (Motzkus et al., 2014). However, the generation in the aerosol phase of individual primary particles is impossible due to high Van der Waals forces which do not allow dissociation of aggregates. Thus, the nebulization process enables a deagglomeration but not a disaggregation, explaining the mean size of 264 nm, as it was already previously discussed (Gaie-Levrel et al., 2020).

The characteristics comparison of existing exposure chambers may be inappropriate, because each system has its own requirements, depending on the protocol to achieve. The device presented in this article is in accordance with our expectations and the system was validated for our experimental conditions. It has general advantages; it is easy to transport, economical, compact, and thus adaptable to the constraints of animal facilities. It is also simple to operate and easily put in place, and it offers versatility to work with various rodent species (mice, rats, hamster or others). Moreover, the atmosphere homogeneity was assessed temporally and spatially, and both experimental and simulated data were consistent during the characterization and the exposures. These important features (mass concentration and size distribution) enabled a precise assessment of the exposure dose of animals, which is an essential requirement in chronic inhalation toxicology studies. Regarding the accuracy of data, our device compares advantageously to others. Cosnier et al. (2017) reported the generation of P25 nTiO₂ aerosols using a rotation brush generator coupled with a nose-only device. Based on the target mass concentration of 10 mg m⁻³, the calculated CMMD was 347 nm with a GSD of 2.29. The mean intra-experiment precision was comprised between 14% and 22% over six inhalation campaigns. Focusing on studies involving nTiO₂ nebulizers, Pujalté et al. (2017a) generated aerosols at a mass concentration of 15.57 mg m⁻³ (min–max of 9–21 mg m⁻³) using a six-jet collision nebulizer with PNSD characterized by a GSD of 1.87 and a geometric mean diameter of 76.91 nm. Using also a six-jet collision nebulizer, Grassian et al. (2007) generated aerosols of nTiO₂ using a whole-body device for different exposure scenarios, which involved a subacute exposure (10 days, 4 h per day) at a mass concentration of 8.88 ± 1.98 mg m⁻³ with PNSD characterized by a geometrical mean diameter of 128 nm (GSD of 1.7). Yi et al. (2013) used an innovative nebulizer to produce aerosol of nTiO₂ with PNSD characterized by a CMMD of 145 nm and a GSD of 2.3 in a 500 L whole-body inhalation exposure chamber. In their article, the atmosphere spatial homogeneity was assessed, by measuring the concentrations at different spots within the chamber, thereby showing a spatial maximum relative deviation from the mean concentration < 6%.

In this study, specific care was taken concerning animal welfare to reduce stress. This is a matter of prime importance, because a stress undergone during gestation is critical for the fetal development, and then prenatal stress can have long-term consequences for the offspring (Weinstock, 2005). Consequently, the maternal stress in rodents, possibly due to restraint of poor exposure chamber design, may exacerbate negative developmental effects (Rasco and Hood, 1995). In this regard, we selected a whole-body inhalation device to expose animals, as this cage allowed daily exposures with a direct visual follow-up without constraint. It also enables animals to move freely, which simulates a physical activity enhancing the pulmonary ventilation of mice to reflect more accurately occupational exposures. Glass and stainless steel are the classical material used in whole-body devices, because of their ability to age slowly compared to plastics (Dorato and Wolff, 1991). Some authors used stainless steel exposure chamber with a vertical injection flow (Kimmel et al., 1997) or a combination of vertical and horizontal flows input/output to reach a uniform aerosol concentration (Oldham et al., 2004). In our study, we chose a polysulfone cage dedicated to rodent hosting, because it is an inexpensive alternative, which is easy to accommodate in a rodent facility. It can be used to expose mice or other species continuously in
<figure><img src="image_22.png" /></figure>

chronic toxicity studies because this product is standard-equipped to provide water and food. Moreover, it is easily washed and it can be used under a hood if necessary. A large number of animals can be exposed at the same time in a convenient way, which can significantly save time. Complications could arise from an important animal loading in the cage, which can increase the temperature, the relative humidity and the amount of air pollutants inside the chamber. Indeed, the ammonia coming from animal feces may be an issue since ammonia could affect animals and may also react with the test aerosols (Barrow and Steinhagen, 1982). According to Silver *et al.* (1946), the overall animal volume should not exceed 5% of the chamber volume to prevent this phenomenon (OECD TG 403). Therefore, we chose an important air renewal (23 volumes h⁻¹) and a low animal loading (< 1% of chamber volume) to prevent particles and metabolites to be accumulated in our device. However, while air renewal within the cage is a key factor in the aerosol dispersion and homogenization, it must be limited to avoid a cold stress.

Some studies also took into consideration the environmental conditions associated with their exposure chambers (Kimmel and Kirk, 1997; Jeon *et al.*, 2002; Oldham *et al.*, 2004; Lucci *et al.*, 2019), while other studies did not (Barrow and Steinhagen, 1982; Cheng *et al.*, 1989; Phillpotts *et al.*, 1997; Bhaskar and Upadhyay, 2003; O'Shaughnessy *et al.*, 2003). It is indeed necessary to perform a deeper aerosol characterization, before following limited metrological endpoints during animal exposures. This characterization is necessary to enable an accurate assessment of the exposure concentration delivered to each animal. This assessment is based on the simulated deposited dose of particles in the lungs, which is a function of the aerosol mass concentration and size distribution. In addition, a homogeneous atmosphere is required, in order to minimize the variability of deposited dose between animals. For all these reasons, the minimum requirements are the mass and number concentrations, the size distribution, and also the environmental parameters assessments (temperature, air renewal, humidity and pressure), which are mandatory to get the experimentation authorization from the ethics committee. Moreover, it is important to note that only few studies validated their exposure chamber thanks to aerosol dispersion modeling (Kimmel *et al.*, 1997; Oldham *et al.*, 2004). The homogenization process results mainly from an adequate air renewal within the chamber, with proper inlet flows and chamber geometry (Kimmel *et al.*, 1997). The analysis of the chamber structure and mass transfer forces such as diffusion is crucial to understand the test material distribution. Rajabi-Vardanjani *et al.* (2019) suggested that numerical simulation techniques should be used to predict flow velocity and aerosol dispersion in function of the chamber geometry in order to optimize an exposure chamber and the associated aerosol generation. Kimmel *et al.* (1997) found a clear agreement between assessment of chamber performance by CFD modeling and the analysis of performances by more conventional methods, which is in accordance with the results of this study. Nevertheless, their apparatus was much larger than in this work (700 L versus 19.8 L), which consequently required a more complete CFD modeling to be conducted. Cheng *et al.* (1989) and O'Shaughnessy *et al.* (2003) assumed that spatial and temporal uniformity were independent from each other in their whole-body exposure chambers. Oldham *et al.* (2004) did not make this assumption, taking in consideration the size of their chamber (20 L), which is relatively small in comparison with others, but similar to this work. The results we reported tended to conform with their statement. Uniformity assessment seemed not as good for whole-body chamber compared to those reported in nose-only exposure systems (Yeh *et al.*, 1990; Cheng and Moss, 1995). However, it is consistent with the characterization reported for other large stationary whole-body exposure chambers (Schreck *et al.*, 1981; MacFarland, 1983; Yeh *et al.*, 1986; Cheng and Moss, 1995; O'Shaughnessy *et al.*, 2003). The aerosol uniformity in several transverse planes (± 5%) was judged acceptable, and since exposures occur with animal moving freely in the totality of the exposure chamber, the stability requirements are less stringent compared to nose-only devices. Nonetheless, variations may be caused by changes in small inward air leaks, mice movements and induced thermal convection, or other any unknown factors.

## 5 CONCLUSIONS

To expose rodents to submicrometer-sized airborne particles, we developed a simple and versatile whole-body inhalation chamber that can be used with various exposure testing protocols
<figure><img src="image_27.png" /></figure>

chronic toxicity studies because this product is standard-equipped to provide water and food. Moreover, it is easily washed and it can be used under a hood if necessary. A large number of animals can be exposed at the same time in a convenient way, which can significantly save time. Complications could arise from an important animal loading in the cage, which can increase the temperature, the relative humidity and the amount of air pollutants inside the chamber. Indeed, the ammonia coming from animal feces may be an issue since ammonia could affect animals and may also react with the test aerosols (Barrow and Steinhagen, 1982). According to Silver et al. (1946), the overall animal volume should not exceed 5% of the chamber volume to prevent this phenomenon (OECD TG 403). Therefore, we chose an important air renewal (23 volumes h⁻¹) and a low animal loading (< 1% of chamber volume) to prevent particles and metabolites to be accumulated in our device. However, while air renewal within the cage is a key factor in the aerosol dispersion and homogenization, it must be limited to avoid a cold stress.

Some studies also took into consideration the environmental conditions associated with their exposure chambers (Kimmel and Kirk, 1997; Jeon et al., 2002; Oldham et al., 2004; Lucci et al., 2019), while other studies did not (Barrow and Steinhagen, 1982; Cheng et al., 1989; Phillpotts et al., 1997; Bhaskar and Upadhyay, 2003; O'Shaughnessy et al., 2003). It is indeed necessary to perform a deeper aerosol characterization, before following limited metrological endpoints during animal exposures. This characterization is necessary to enable an accurate assessment of the exposure concentration delivered to each animal. This assessment is based on the simulated deposited dose of particles in the lungs, which is a function of the aerosol mass concentration and size distribution. In addition, a homogeneous atmosphere is required, in order to minimize the variability of deposited dose between animals. For all these reasons, the minimum requirements are the mass and number concentrations, the size distribution, and also the environmental parameters assessments (temperature, air renewal, humidity and pressure), which are mandatory to get the experimentation authorization from the ethics committee. Moreover, it is important to note that only few studies validated their exposure chamber thanks to aerosol dispersion modeling (Kimmel et al., 1997; Oldham et al., 2004). The homogenization process results mainly from an adequate air renewal within the chamber, with proper inlet flows and chamber geometry (Kimmel et al., 1997). The analysis of the chamber structure and mass transfer forces such as diffusion is crucial to understand the test material distribution. Rajabi-Vardanjani et al. (2019) suggested that numerical simulation techniques should be used to predict flow velocity and aerosol dispersion in function of the chamber geometry in order to optimize an exposure chamber and the associated aerosol generation. Kimmel et al. (1997) found a clear agreement between assessment of chamber performance by CFD modeling and the analysis of performances by more conventional methods, which is in accordance with the results of this study. Nevertheless, their apparatus was much larger than in this work (700 L versus 19.8 L), which consequently required a more complete CFD modeling to be conducted. Cheng et al. (1989) and O'Shaughnessy et al. (2003) assumed that spatial and temporal uniformity were independent from each other in their whole-body exposure chambers. Oldham et al. (2004) did not make this assumption, taking in consideration the size of their chamber (20 L), which is relatively small in comparison with others, but similar to this work. The results we reported tended to conform with their statement. Uniformity assessment seemed not as good for whole-body chamber compared to those reported in nose-only exposure systems (Yeh et al., 1990; Cheng and Moss, 1995). However, it is consistent with the characterization reported for other large stationary whole-body exposure chambers (Schreck et al., 1981; MacFarland, 1983; Yeh et al., 1986; Cheng and Moss, 1995; O'Shaughnessy et al., 2003). The aerosol uniformity in several transverse planes (± 5%) was judged acceptable, and since exposures occur with animal moving freely in the totality of the exposure chamber, the stability requirements are less stringent compared to nose-only devices. Nonetheless, variations may be caused by changes in small inward air leaks, mice movements and induced thermal convection, or other any unknown factors.

## 5 CONCLUSIONS

To expose rodents to submicrometer-sized airborne particles, we developed a simple and versatile whole-body inhalation chamber that can be used with various exposure testing protocols
<figure><img src="image_23.png" /></figure>

and animal species. In this chamber, stable and reproducible generations of PQ, nTiO₂ or PQ-nTiO₂ aerosols were characterized in terms of particle number size distributions, mass and number concentrations with reproducibility standard deviations comprised between 1–11% for up to 2 h in the laboratory. We then validated the reliability of these measurements by conducting inhalation exposure sessions in the field, which exhibited a reproducibility standard deviation of 4–9%. These results confirmed the homogeneity of the chamber's atmosphere and hence the accuracy of the exposure assessment. Our project facilitates the collection of toxicological data, which are essential to evaluating the health risks of emerging substances, such as NPEs.

## ACKNOWLEDGMENTS

This paper was carried out as part of a thesis supported by a CIFRE fellowship involving the collaboration of LNE and the École Normale Supérieure de Lyon (ENS de Lyon). We acknowledge the contribution of the SFR Biosciences animal facility (UMS3444/CNRS, US8/Inserm, ENS de Lyon, UCBL), especially the staff of the PBES for its precious help.

## DISCLAIMER

The authors declare no conflicts of interest.

## REFERENCES

Barrow, C.S., Steinhagen, W.H. (1982). Design, construction and operation of a simple inhalation exposure system. Fundam. Appl. Toxicol. 2, 33–37. https://doi.org/10.1016/S0272-0590(82)80061-4

Bencsik, A., Lestaevel, P., Guseva Canu, I. (2018). Nano- and neurotoxicology: An emerging discipline. Prog. Neurobiol. 160, 45–63. https://doi.org/10.1016/j.pneurobio.2017.10.003

Bermudez, E., Mangum, J.B., Wong, B.A., Asgharian, B., Hext, P.M., Warheit, D.B., Everitt, J.I. (2004). Pulmonary responses of mice, rats, and hamsters to subchronic inhalation of ultrafine titanium dioxide particles. Toxicol. Sci. 77, 347–357. https://doi.org/10.1093/toxsci/kfh019

Bhaskar, S., Upadhyay, P. (2003). Design and evaluation of an aerosol infection chamber for small animals. Int. J. Pharm. 255, 43–48. https://doi.org/10.1016/s0378-5173(03)00023-1

Brouwer, M., Huss, A., van der Mark, M., Nijssen, P.C.G., Mulleners, W.M., Sas, A.M.G., van Laar, T., de Snoo, G.R., Kromhout, H., Vermeulen, R.C.H. (2017). Environmental exposure to pesticides and the risk of Parkinson's disease in the Netherlands. Environ. Int. 107, 100–110. https://doi.org/10.1016/j.envint.2017.07.001

Cantavenera, M.J., Catanzaro, I., Loddo, V., Palmisano, L., Sciandrello, G. (2007). Photocatalytic degradation of paraquat and genotoxicity of its intermediate products. J. Photochem. Photobiol., A 185, 277–282. https://doi.org/10.1016/j.jphotochem.2006.06.021

Cheng, Y.S., Barr, E.B., Carpenter, R.L., Benson, J.M., Hobbs, C.H. (1989). Improvement of Aerosol Distribution in Whole-Body Inhalation Exposure Chambers. Inhalation Toxicol. 1, 153–166. https://doi.org/10.3109/08958378909145663

Cheng, Y.S., Moss, O.R. (1995). Inhalation exposure systems. Toxicol. Methods 5, 161–197. https://doi.org/10.3109/15376519509049118

Chézeau, L., Kohlstaedt, L.A., Faou, A.L., Cosnier, F., Rihn, B., Gaté, L. (2019). Proteomic analysis of bronchoalveolar lavage fluid in rat exposed to TiO₂ nanostructured aerosol by inhalation. J. Proteomics. 207, 103451. https://doi.org/10.1016/j.jprot.2019.103451

Coscollà, C., Colin, P., Yahyaoui, A., Petrique, O., Yusà, V., Mellouki, A., Pastor, A. (2010). Occurrence of currently used pesticides in ambient air of Centre Region (France). Atmos. Environ. 44, 3915–3925. https://doi.org/10.1016/j.atmosenv.2010.07.014

Coscollà, C., Yahyaoui, A., Colin, P., Robin, C., Martinon, L., Val, S., Baeza-Squiban, A., Mellouki, A., Yusà, V. (2013). Particle size distributions of currently used pesticides in a rural atmosphere of France. Atmos. Environ. 81, 32–38. https://doi.org/10.1016/j.atmosenv.2013.08.057

Cosnier, F., Bau, S., Grossmann, S., Nunge, H., Brochard, C., Viton, S., Payet, R., Witschger, O.,
<figure><img src="image_28.png" /></figure>

and animal species. In this chamber, stable and reproducible generations of PQ, nTiO₂ or PQ-nTiO₂ aerosols were characterized in terms of particle number size distributions, mass and number concentrations with reproducibility standard deviations comprised between 1–11% for up to 2 h in the laboratory. We then validated the reliability of these measurements by conducting inhalation exposure sessions in the field, which exhibited a reproducibility standard deviation of 4–9%. These results confirmed the homogeneity of the chamber's atmosphere and hence the accuracy of the exposure assessment. Our project facilitates the collection of toxicological data, which are essential to evaluating the health risks of emerging substances, such as NPEs.

## ACKNOWLEDGMENTS

This paper was carried out as part of a thesis supported by a CIFRE fellowship involving the collaboration of LNE and the École Normale Supérieure de Lyon (ENS de Lyon). We acknowledge the contribution of the SFR Biosciences animal facility (UMS3444/CNRS, US8/Inserm, ENS de Lyon, UCBL), especially the staff of the PBES for its precious help.

## DISCLAIMER

The authors declare no conflicts of interest.

## REFERENCES

Barrow, C.S., Steinhagen, W.H. (1982). Design, construction and operation of a simple inhalation exposure system. Fundam. Appl. Toxicol. 2, 33–37. https://doi.org/10.1016/S0272-0590(82)80061-4

Bencsik, A., Lestaevel, P., Guseva Canu, I. (2018). Nano- and neurotoxicology: An emerging discipline. Prog. Neurobiol. 160, 45–63. https://doi.org/10.1016/j.pneurobio.2017.10.003

Bermudez, E., Mangum, J.B., Wong, B.A., Asgharian, B., Hext, P.M., Warheit, D.B., Everitt, J.I. (2004). Pulmonary responses of mice, rats, and hamsters to subchronic inhalation of ultrafine titanium dioxide particles. Toxicol. Sci. 77, 347–357. https://doi.org/10.1093/toxsci/kfh019

Bhaskar, S., Upadhyay, P. (2003). Design and evaluation of an aerosol infection chamber for small animals. Int. J. Pharm. 255, 43–48. https://doi.org/10.1016/s0378-5173(03)00023-1

Brouwer, M., Huss, A., van der Mark, M., Nijssen, P.C.G., Mulleners, W.M., Sas, A.M.G., van Laar, T., de Snoo, G.R., Kromhout, H., Vermeulen, R.C.H. (2017). Environmental exposure to pesticides and the risk of Parkinson's disease in the Netherlands. Environ. Int. 107, 100–110. https://doi.org/10.1016/j.envint.2017.07.001

Cantavenera, M.J., Catanzaro, I., Loddo, V., Palmisano, L., Sciandrello, G. (2007). Photocatalytic degradation of paraquat and genotoxicity of its intermediate products. J. Photochem. Photobiol., A 185, 277–282. https://doi.org/10.1016/j.jphotochem.2006.06.021

Cheng, Y.S., Barr, E.B., Carpenter, R.L., Benson, J.M., Hobbs, C.H. (1989). Improvement of Aerosol Distribution in Whole-Body Inhalation Exposure Chambers. Inhalation Toxicol. 1, 153–166. https://doi.org/10.3109/08958378909145663

Cheng, Y.S., Moss, O.R. (1995). Inhalation exposure systems. Toxicol. Methods 5, 161–197. https://doi.org/10.3109/15376519509049118

Chézeau, L., Kohlstaedt, L.A., Faou, A.L., Cosnier, F., Rihn, B., Gaté, L. (2019). Proteomic analysis of bronchoalveolar lavage fluid in rat exposed to TiO₂ nanostructured aerosol by inhalation. J. Proteomics. 207, 103451. https://doi.org/10.1016/j.jprot.2019.103451

Coscollà, C., Colin, P., Yahyaoui, A., Petrique, O., Yusà, V., Mellouki, A., Pastor, A. (2010). Occurrence of currently used pesticides in ambient air of Centre Region (France). Atmos. Environ. 44, 3915–3925. https://doi.org/10.1016/j.atmosenv.2010.07.014

Coscollà, C., Yahyaoui, A., Colin, P., Robin, C., Martinon, L., Val, S., Baeza-Squiban, A., Mellouki, A., Yusà, V. (2013). Particle size distributions of currently used pesticides in a rural atmosphere of France. Atmos. Environ. 81, 32–38. https://doi.org/10.1016/j.atmosenv.2013.08.057

Cosnier, F., Bau, S., Grossmann, S., Nunge, H., Brochard, C., Viton, S., Payet, R., Witschger, O.,
<figure><img src="image_24.png" /></figure>

Gaté, L. (2017). Design and characterization of an inhalation system to expose rodents to nanoaerosols. Aerosol Air Qual. Res. 16, 2989-3000. https://doi.org/10.4209/aaqr.2016.01.0034

Costello, S., Cockburn, M., Bronstein, J., Zhang, X., Ritz, B. (2009). Parkinson's disease and residential exposure to maneb and paraquat from agricultural applications in the central valley of California. Am. J. Epidemiol. 169, 919-926. https://doi.org/10.1093/aje/kwp006

Damalas, C.A., Eleftherohorinos, I.G. (2011). Pesticide exposure, safety issues, and risk assessment indicators. Int. J. Environ. Res. Public. Health 8, 1402-1419. https://doi.org/10.3390/ijerph8051402

Désert, M., Ravier, S., Gille, G., Quinapallo, A., Armengaud, A., Pochet, G., Savelli, J.L., Wortham, H., Quivet, E. (2018). Spatial and temporal distribution of current-use pesticides in ambient air of Provence-Alpes-Côte-d'Azur Region and Corsica, France. Atmos. Environ. 192, 241-256. https://doi.org/10.1016/j.atmosenv.2018.08.054

Disdier, C., Chalansonnet, M., Gagnaire, F., Gaté, L., Cosnier, F., Devoy, J., Saba, W., Lund, A.K., Brun, E., Mabondzo, A. (2017). Brain inflammation, blood brain barrier dysfunction and neuronal synaptophysin decrease after inhalation exposure to titanium dioxide nano-aerosol in aging rats. Sci. Rep. 7, 12196. https://doi.org/10.1038/s41598-017-12404-5

Dorato, M.A., Wolff, R.K. (1991). Inhalation exposure technology, dosimetry, and regulatory issues. Toxicol. Pathol. 19, 373-383. https://doi.org/10.1177/0192623391019004-106

Estellano, V.H., Pozo, Karla, Efstathiou, C., Pozo, Katerine, Corsolini, S., Focardi, S. (2015). Assessing levels and seasonal variations of current-use pesticides (CUPs) in the Tuscan atmosphere, Italy, using polyurethane foam disks (PUF) passive air samplers. Environ. Pollut. 205, 52-59. https://doi.org/10.1016/j.envpol.2015.05.002

Florêncio, M., Pires, E., Castro, A., Nunes, M., Borges, C., Costa, F. (2004). Photodegradation of Diquat and Paraquat in aqueous solutions by titanium dioxide: Evolution of degradation reactions and characterisation of intermediates. Chemosphere 55, 345-55. https://doi.org/10.1016/j.chemosphere.2003.11.013

Gaie-Levrel, F., Bourrous, S., Macé, T. (2018). Development of a portable reference aerosol generator (PRAG) for calibration of particle mass concentration measurements. Particuology 37, 134-142. https://doi.org/10.1016/j.partic.2017.06.005

Gaie-Levrel, F., Bau, S., Bregonzio-Rozier, L., Payet, R., Artous, S., Jacquinot, S., Guiot, A., Ouf, F.X., Bourrous, S., Marpillat, A., Foulquier, C., Smith, G., Crenn, V., Feltin, N. (2020). An intercomparison exercise of good laboratory practices for nano-aerosol size measurements by mobility spectrometers. J. Nanoparticle Res. 22, 103. https://doi.org/10.1007/s11051-020-04820-y

Grassian, V.H., O'Shaughnessy, P.T., Adamcakova-Dodd, A., Pettibone, J.M., Thorne, P.S. (2007). Inhalation exposure study of titanium dioxide nanoparticles with a primary particle size of 2 to 5 nm. Environ. Health Perspect. 115, 397-402. https://doi.org/10.1289/ehp.9469

Griffis, L.C., Wolff, R.K., Beethe, R.L., Hobbs, C.H., McClellan, R.O. (1979). Pulmonary deposition of a 99m Tc labeled aerosol in a whole-body exposure. Inhalation Toxicology Research Institute Annual Report. Lovelace Biomedical Environmental Research Institute, Albuquerque, NM, pp. 259-266.

Grimshaw, P., Hardy, C.J., Cobb, L.M., Lewis, D.J., Prentice, D.E. (1979). Three-week inhalation study in rats exposed to an aerosol of paraquat (repeat study). Unpublished report, number CTL/C/810 from Huntingdon Research Centre, Alconbury Weston, England. Submitted to WHO by Syngenta.

Hilz, E., Vermeer, A.W.P. (2013). Spray drift review: The extent to which a formulation can contribute to spray drift reduction. Crop Prot. 44, 75-83. https://doi.org/10.1016/j.cropro.2012.10.020

INSERM (2013). Expertise collective: Pesticides Effets sur la santé. La science pour la santé. https://www.inserm.fr/information-en-sante/expertises-collectives/pesticides-effets-sur-sante (accessed 20 September 2020).

ISO 5725-2:2020. Accuracy (trueness and precision) of measurement methods and results. https://standards.iteh.ai/catalog/standards/sist/362ad6b6-2faf-42b5-8f67-9b200bf2977f/sist-iso-5725-2-2020 (accessed 5 June 2019).

ISO/TR 18401:2017. Nanotechnologies - Plain language explanation of selected terms from the ISO/IEC 80004 series. https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/st andard/06/23/62384.html (accessed 31 May 2020).
<figure><img src="image_29.png" /></figure>

Gaté, L. (2017). Design and characterization of an inhalation system to expose rodents to nanoaerosols. Aerosol Air Qual. Res. 16, 2989-3000. https://doi.org/10.4209/aaqr.2016.01.0034

Costello, S., Cockburn, M., Bronstein, J., Zhang, X., Ritz, B. (2009). Parkinson's disease and residential exposure to maneb and paraquat from agricultural applications in the central valley of California. Am. J. Epidemiol. 169, 919-926. https://doi.org/10.1093/aje/kwp006

Damalas, C.A., Eleftherohorinos, I.G. (2011). Pesticide exposure, safety issues, and risk assessment indicators. Int. J. Environ. Res. Public. Health 8, 1402-1419. https://doi.org/10.3390/ijerph8051402

Désert, M., Ravier, S., Gille, G., Quinapallo, A., Armengaud, A., Pochet, G., Savelli, J.L., Wortham, H., Quivet, E. (2018). Spatial and temporal distribution of current-use pesticides in ambient air of Provence-Alpes-Côte-d'Azur Region and Corsica, France. Atmos. Environ. 192, 241-256. https://doi.org/10.1016/j.atmosenv.2018.08.054

Disdier, C., Chalansonnet, M., Gagnaire, F., Gaté, L., Cosnier, F., Devoy, J., Saba, W., Lund, A.K., Brun, E., Mabondzo, A. (2017). Brain inflammation, blood brain barrier dysfunction and neuronal synaptophysin decrease after inhalation exposure to titanium dioxide nano-aerosol in aging rats. Sci. Rep. 7, 12196. https://doi.org/10.1038/s41598-017-12404-5

Dorato, M.A., Wolff, R.K. (1991). Inhalation exposure technology, dosimetry, and regulatory issues. Toxicol. Pathol. 19, 373-383. https://doi.org/10.1177/0192623391019004-106

Estellano, V.H., Pozo, Karla, Efstathiou, C., Pozo, Katerine, Corsolini, S., Focardi, S. (2015). Assessing levels and seasonal variations of current-use pesticides (CUPs) in the Tuscan atmosphere, Italy, using polyurethane foam disks (PUF) passive air samplers. Environ. Pollut. 205, 52-59. https://doi.org/10.1016/j.envpol.2015.05.002

Florêncio, M., Pires, E., Castro, A., Nunes, M., Borges, C., Costa, F. (2004). Photodegradation of Diquat and Paraquat in aqueous solutions by titanium dioxide: Evolution of degradation reactions and characterisation of intermediates. Chemosphere 55, 345-55. https://doi.org/10.1016/j.chemosphere.2003.11.013

Gaie-Levrel, F., Bourrous, S., Macé, T. (2018). Development of a portable reference aerosol generator (PRAG) for calibration of particle mass concentration measurements. Particuology 37, 134-142. https://doi.org/10.1016/j.partic.2017.06.005

Gaie-Levrel, F., Bau, S., Bregonzio-Rozier, L., Payet, R., Artous, S., Jacquinot, S., Guiot, A., Ouf, F.X., Bourrous, S., Marpillat, A., Foulquier, C., Smith, G., Crenn, V., Feltin, N. (2020). An intercomparison exercise of good laboratory practices for nano-aerosol size measurements by mobility spectrometers. J. Nanoparticle Res. 22, 103. https://doi.org/10.1007/s11051-020-04820-y

Grassian, V.H., O'Shaughnessy, P.T., Adamcakova-Dodd, A., Pettibone, J.M., Thorne, P.S. (2007). Inhalation exposure study of titanium dioxide nanoparticles with a primary particle size of 2 to 5 nm. Environ. Health Perspect. 115, 397-402. https://doi.org/10.1289/ehp.9469

Griffis, L.C., Wolff, R.K., Beethe, R.L., Hobbs, C.H., McClellan, R.O. (1979). Pulmonary deposition of a 99m Tc labeled aerosol in a whole-body exposure. Inhalation Toxicology Research Institute Annual Report. Lovelace Biomedical Environmental Research Institute, Albuquerque, NM, pp. 259-266.

Grimshaw, P., Hardy, C.J., Cobb, L.M., Lewis, D.J., Prentice, D.E. (1979). Three-week inhalation study in rats exposed to an aerosol of paraquat (repeat study). Unpublished report, number CTL/C/810 from Huntingdon Research Centre, Alconbury Weston, England. Submitted to WHO by Syngenta.

Hilz, E., Vermeer, A.W.P. (2013). Spray drift review: The extent to which a formulation can contribute to spray drift reduction. Crop Prot. 44, 75-83. https://doi.org/10.1016/j.cropro.2012.10.020

INSERM (2013). Expertise collective: Pesticides Effets sur la santé. La science pour la santé. https://www.inserm.fr/information-en-sante/expertises-collectives/pesticides-effets-sur-sante (accessed 20 September 2020).

ISO 5725-2:2020. Accuracy (trueness and precision) of measurement methods and results. https://standards.iteh.ai/catalog/standards/sist/362ad6b6-2faf-42b5-8f67-9b200bf2977f/sist-iso-5725-2-2020 (accessed 5 June 2019).

ISO/TR 18401:2017. Nanotechnologies - Plain language explanation of selected terms from the ISO/IEC 80004 series. https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/st andard/06/23/62384.html (accessed 31 May 2020).
<figure><img src="image_25.png" /></figure>

Jeon, K., Yu, I.J., Ahn, K.H. (2012). Evaluation of newly developed nose-only inhalation exposure chamber for nanoparticles. Inhalation Toxicol. 24, 550–556. https://doi.org/10.3109/0895837.8.2012.696742

Kah, M., Kookana, R.S., Gogos, A., Bucheli, T.D. (2018). A critical evaluation of nanopesticides and nanofertilizers against their conventional analogues. Nat. Nanotechnol. 13, 677–684. https://doi.org/10.1038/s41565-018-0131-1

Kah, M., Navarro, D., Kookana, R.S., Kirby, J.K., Santra, S., Ozcan, A., Kabiri, S. (2019). Impact of (nano)formulations on the distribution and wash-off of copper pesticides and fertilisers applied on citrus leaves. Environ. Chem. 16, 401–410. https://doi.org/10.1071/EN18279

Kamel, F., Tanner, C., Umbach, D., Hoppin, J., Alavanja, M., Blair, A., Comyns, K., Goldman, S., Korell, M., Langston, J., Ross, G., Sandler, D. (2007). Pesticide exposure and self-reported Parkinson's disease in the agricultural health study. Am. J. Epidemiol. 165, 364–374. https://doi.org/10.1093/aje/kwk024

Kim, K.H., Kabir, E., Jahan, S.A. (2017). Exposure to pesticides and the associated human health effects. Sci. Total Environ. 575, 525–535. https://doi.org/10.1016/j.scitotenv.2016.09.009

Kimmel, E.C., Yerkes, K.L., Carpenter, R.L. (1997). Performance, fluid mechanics, and design of a small-animal, whole-body inhalation exposure chamber. Inhalation Toxicol. 9, 287–316. https://doi.org/10.1080/089583797198268

Kumar, S., Nehra, M., Dilbaghi, N., Marrazza, G., Hassan, A.A., Kim, K.H. (2019). Nano-based smart pesticide formulations: Emerging opportunities for agriculture. J. Controlled Release 294, 131–153. https://doi.org/10.1016/j.jconrel.2018.12.012

Lee, J.H., Kwon, M., Ji, J.H., Kang, C.S., Ahn, K.H., Han, J.H., Yu, I.J. (2011). Exposure assessment of workplaces manufacturing nanosized TiO₂ and silver. Inhalation Toxicol. 23, 226–236. https://doi.org/10.3109/08958378.2011.562567

López, A., Yusà, V., Muñoz, A., Vera, T., Borràs, E., Ródenas, M., Coscollà, C. (2017). Risk assessment of airborne pesticides in a Mediterranean region of Spain. Sci. Total Environ. 574, 724–734. https://doi.org/10.1016/j.scitotenv.2016.08.149

Lu, C., Fenske, R.A., Simcox, N.J., Kalman, D. (2000). Pesticide exposure of children in an agricultural community: Evidence of household proximity to farmland and take home exposure pathways. Environ. Res. 84, 290–302. https://doi.org/10.1006/enrs.2000.4076

Lucci, F., Tan, W.T., Krishnan, S., Hoeng, J., Vanscheeuwijck, P., Jaeger, R., Kuczaj, A. (2020). Experimental and computational investigation of a nose-only exposure chamber. Aerosol Sci. Technol. 54, 277–290. https://doi.org/10.1080/02786826.2019.1687843

MacFarland, H.N. (1983). Designs and operational characteristics of inhalation exposure equipment — A review. Fundam. Appl. Toxicol. 3, 603–613. https://doi.org/10.1016/S0272-0590(83)80110-9

Mattei, C., Dupont, J., Wortham, H., Quivet, E. (2019). Influence of pesticide concentration on their heterogeneous atmospheric degradation by ozone. Chemosphere 228, 75–82. https://doi.org/10.1016/j.chemosphere.2019.04.082

McLean, L., Marsh, J.R., Millward, S.W. (1985). Paraquat: 4-hour acute inhalation toxicity study in the rat. Unpublished study, number CTL/P/1325 from ICI Central Toxicology Laboratory. Submitted to WHO by Syngenta.

Morshed, M.M., Omar, D., Mohamad, R., Wahed, S., Rahman, M.A. (2010). Airborne paraquat measurement and its exposure to spray operators in treated field environment. Int. J. Agric. Biol. 12, 679–684.

Motzkus, C., Gaie-Levrel, F., Ausset, P., Maillé, M., Baccile, N., Vaslin-Reimann, S., Idrac, J., Oster, D., Fischer, N., Macé, T. (2014). Impact of batch variability on physicochemical properties of manufactured TiO₂ and SiO₂ nanopowders. Powder Technol. 267, 39–53. https://doi.org/10.1016/j.powtec.2014.06.055

Naasz, S., Altenburger, R., Kühnel, D. (2018). Environmental mixtures of nanomaterials and chemicals: The Trojan-horse phenomenon and its relevance for ecotoxicity. Sci. Total Environ. 635, 1170–1181. https://doi.org/10.1016/j.scitotenv.2018.04.180

O'Shaughnessy, P.T., Achutan, C., O'Neill, M.E., Thorne, P.S. (2003). A small whole-body exposure chamber for laboratory use. Inhalation Toxicol. 15, 251–263. https://doi.org/10.1080/0895837.0304504

OECD TG 413 (2018). Test Guidelines N°413: Subchronic Inhalation Toxicity: 90-day Study, OECD
<figure><img src="image_30.png" /></figure>

Jeon, K., Yu, I.J., Ahn, K.H. (2012). Evaluation of newly developed nose-only inhalation exposure chamber for nanoparticles. Inhalation Toxicol. 24, 550–556. https://doi.org/10.3109/0895837.8.2012.696742

Kah, M., Kookana, R.S., Gogos, A., Bucheli, T.D. (2018). A critical evaluation of nanopesticides and nanofertilizers against their conventional analogues. Nat. Nanotechnol. 13, 677–684. https://doi.org/10.1038/s41565-018-0131-1

Kah, M., Navarro, D., Kookana, R.S., Kirby, J.K., Santra, S., Ozcan, A., Kabiri, S. (2019). Impact of (nano)formulations on the distribution and wash-off of copper pesticides and fertilisers applied on citrus leaves. Environ. Chem. 16, 401–410. https://doi.org/10.1071/EN18279

Kamel, F., Tanner, C., Umbach, D., Hoppin, J., Alavanja, M., Blair, A., Comyns, K., Goldman, S., Korell, M., Langston, J., Ross, G., Sandler, D. (2007). Pesticide exposure and self-reported Parkinson's disease in the agricultural health study. Am. J. Epidemiol. 165, 364–374. https://doi.org/10.1093/aje/kwk024

Kim, K.H., Kabir, E., Jahan, S.A. (2017). Exposure to pesticides and the associated human health effects. Sci. Total Environ. 575, 525–535. https://doi.org/10.1016/j.scitotenv.2016.09.009

Kimmel, E.C., Yerkes, K.L., Carpenter, R.L. (1997). Performance, fluid mechanics, and design of a small-animal, whole-body inhalation exposure chamber. Inhalation Toxicol. 9, 287–316. https://doi.org/10.1080/089583797198268

Kumar, S., Nehra, M., Dilbaghi, N., Marrazza, G., Hassan, A.A., Kim, K.H. (2019). Nano-based smart pesticide formulations: Emerging opportunities for agriculture. J. Controlled Release 294, 131–153. https://doi.org/10.1016/j.jconrel.2018.12.012

Lee, J.H., Kwon, M., Ji, J.H., Kang, C.S., Ahn, K.H., Han, J.H., Yu, I.J. (2011). Exposure assessment of workplaces manufacturing nanosized TiO₂ and silver. Inhalation Toxicol. 23, 226–236. https://doi.org/10.3109/08958378.2011.562567

López, A., Yusà, V., Muñoz, A., Vera, T., Borràs, E., Ródenas, M., Coscollà, C. (2017). Risk assessment of airborne pesticides in a Mediterranean region of Spain. Sci. Total Environ. 574, 724–734. https://doi.org/10.1016/j.scitotenv.2016.08.149

Lu, C., Fenske, R.A., Simcox, N.J., Kalman, D. (2000). Pesticide exposure of children in an agricultural community: Evidence of household proximity to farmland and take home exposure pathways. Environ. Res. 84, 290–302. https://doi.org/10.1006/enrs.2000.4076

Lucci, F., Tan, W.T., Krishnan, S., Hoeng, J., Vanscheeuwijck, P., Jaeger, R., Kuczaj, A. (2020). Experimental and computational investigation of a nose-only exposure chamber. Aerosol Sci. Technol. 54, 277–290. https://doi.org/10.1080/02786826.2019.1687843

MacFarland, H.N. (1983). Designs and operational characteristics of inhalation exposure equipment — A review. Fundam. Appl. Toxicol. 3, 603–613. https://doi.org/10.1016/S0272-0590(83)80110-9

Mattei, C., Dupont, J., Wortham, H., Quivet, E. (2019). Influence of pesticide concentration on their heterogeneous atmospheric degradation by ozone. Chemosphere 228, 75–82. https://doi.org/10.1016/j.chemosphere.2019.04.082

McLean, L., Marsh, J.R., Millward, S.W. (1985). Paraquat: 4-hour acute inhalation toxicity study in the rat. Unpublished study, number CTL/P/1325 from ICI Central Toxicology Laboratory. Submitted to WHO by Syngenta.

Morshed, M.M., Omar, D., Mohamad, R., Wahed, S., Rahman, M.A. (2010). Airborne paraquat measurement and its exposure to spray operators in treated field environment. Int. J. Agric. Biol. 12, 679–684.

Motzkus, C., Gaie-Levrel, F., Ausset, P., Maillé, M., Baccile, N., Vaslin-Reimann, S., Idrac, J., Oster, D., Fischer, N., Macé, T. (2014). Impact of batch variability on physicochemical properties of manufactured TiO₂ and SiO₂ nanopowders. Powder Technol. 267, 39–53. https://doi.org/10.1016/j.powtec.2014.06.055

Naasz, S., Altenburger, R., Kühnel, D. (2018). Environmental mixtures of nanomaterials and chemicals: The Trojan-horse phenomenon and its relevance for ecotoxicity. Sci. Total Environ. 635, 1170–1181. https://doi.org/10.1016/j.scitotenv.2018.04.180

O'Shaughnessy, P.T., Achutan, C., O'Neill, M.E., Thorne, P.S. (2003). A small whole-body exposure chamber for laboratory use. Inhalation Toxicol. 15, 251–263. https://doi.org/10.1080/0895837.0304504

OECD TG 413 (2018). Test Guidelines N°413: Subchronic Inhalation Toxicity: 90-day Study, OECD
<figure><img src="image_26.png" /></figure>

Guidelines for the Testing of Chemicals, Section 4. https://www.oecd-ilibrary.org/environmen
t/test-no-413-subchronic-inhalation-toxicity-90-day-study_9789264070806-en (accessed 5 June
2019).

Oldham, M.J., Phalen, R.F., Robinson, R.J., Kleinman, M.T. (2004). Performance of a portable whole-body mouse exposure system. Inhalation Toxicol. 16, 657–662. https://doi.org/10.1080/08958370490464670

Phillpotts, R.J., Brooks, T.J., Cox, C.S. (1997). A simple device for the exposure of animals to infectious microorganisms by the airborne route. Epidemiol Infect. 118, 71–75.

Pujalté, I., Dieme, D., Haddad, S., Serventi, A.M., Bouchard, M. (2017a). Toxicokinetics of titanium dioxide (TiO₂) nanoparticles after inhalation in rats. Toxicol. Lett. 265, 77–85. https://doi.org/10.1016/j.toxlet.2016.11.014

Pujalté, I., Serventi, A., Noël, A., Dieme, D., Haddad, S., Bouchard, M. (2017b). Characterization of aerosols of titanium dioxide nanoparticles following three generation methods using an optimized aerosolization system designed for experimental inhalation studies. Toxics 5, 14. https://doi.org/10.3390/toxics5030014

Rajabi-Vardanjani, H., Asilian-Mahabadi, H., Sedehi, M. (2019). Particulate matter inhalation exposure chambers and parameters affecting their performance: A systematic review Study. Health Scope. 8, e80163. https://doi.org/10.5812/jhealthscope.80163

Rasco, J.F., Hood, R.D. (1995). Maternal restraint stress-enhanced teratogenicity of all-trans-retinoic acid in CD-1 mice. Teratology 51, 57–62. https://doi.org/10.1002/tera.1420510203

Sartori, F., Vidrio, E. (2018). Environmental fate and ecotoxicology of paraquat: A California perspective. Toxicol. Environ. Chem. 100, 479–517. https://doi.org/10.1080/02772248.2018.1460369

Schmoll, L., Elzey, S., Grassian, V., O'Shaughnessy, P. (2009). Nanoparticle aerosol generation methods from bulk powders for inhalation exposure studies. Nanotoxicology 3, 265–275. https://doi.org/10.3109/17435390903121931

Schreck, R.M., Soderholm, S.C., Chan, T.L., Smiler, K.L., D'arcy, J.B. (1981). Experimental conditions in GMR chronic inhalation studies of diesel exhaust. J. Appl. Toxicol. 1, 67–76. https://doi.org/10.1002/jat.2550010205

Silver, S.D. (1946). Constant flow gassing chambers: Principles influencing design and operation. J. Lab. Clin. Med. 31, 1153–1161. https://doi.org/10.5555/uri:pii:0022214346901576

Tanner, C.M., Kamel, F., Ross, G.W., Hoppin, J.A., Goldman, S.M., Korell, M., Marras, C., Bhudhikanok, G.S., Kasten, M., Chade, A.R., Comyns, K., Richards, M.B., Meng, C., Priestley, B., Fernandez, H.H., Cambi, F., Umbach, D.M., Blair, A., Sandler, D.P., Langston, J.W. (2011). Rotenone, paraquat, and Parkinson's disease. Environ. Health Perspect. 119, 866–872. https://doi.org/10.1289/ehp.1002839

Tuttle, R.S., Sosna, W.A., Daniels, D.E., Hamilton, S.B., Lednicky, J.A. (2010). Design, assembly, and validation of a nose-only inhalation exposure system for studies of aerosolized viable influenza H5N1 virus in ferrets. Virol. J. 7, 135. https://doi.org/10.1186/1743-422X-7-135

United States Department of Agriculture (USDA) (2015). USDA announces $4.6 Million for Nanotechnology Research. https://nifa.usda.gov/announcement/usda-announces-46-million nanotechnology-research (accessed 4 June 2019).

Wang, Y., Sun, C., Zhao, X., Cui, B., Zeng, Z., Wang, A., Liu, G., Cui, H. (2016). The application of Nano-TiO₂ photo semiconductors in agriculture. Nanoscale Res. Lett. 11, 529. https://doi.org/10.1186/s11671-016-1721-1

Weinstock, M. (2005). The potential influence of maternal stress hormones on development and mental health of the offspring. Brain. Behav. Immun. 19, 296–308. https://doi.org/10.1016/j.bi.2004.09.006

Willeke, K., Baron, P. (2001). Aerosol measurement: Principles, techniques, and applications. Van Nostrand Reinhold. https://doi.org/10.1002/9781118001684

Wong, B.A. (2007). Inhalation exposure systems: Design, methods and operation. Toxicol. Pathol. 35, 3–14. https://doi.org/10.1080/01926230601060017

Yeh, H.C., Newton, G.J., Barr, E.B., Carpenter, R.L., Hobbs, C.H. (1986). Studies of the temporal and spatial distribution of aerosols in multi-tiered inhalation exposure chambers. Am. Ind. Hyg. Assoc. J. 47, 540–545. https://doi.org/10.1080/15298668691390197

Yeh, H.C., Snipes, M.B., Eidson, A.F., Hobbs, C.H., Henry, M.C. (1990). Comparative evaluation of
<figure><img src="image_31.png" /></figure>

Guidelines for the Testing of Chemicals, Section 4. https://www.oecd-ilibrary.org/environmen
t/test-no-413-subchronic-inhalation-toxicity-90-day-study_9789264070806-en (accessed 5 June
2019).

Oldham, M.J., Phalen, R.F., Robinson, R.J., Kleinman, M.T. (2004). Performance of a portable whole-body mouse exposure system. Inhalation Toxicol. 16, 657–662. https://doi.org/10.1080/08958370490464670

Phillpotts, R.J., Brooks, T.J., Cox, C.S. (1997). A simple device for the exposure of animals to infectious microorganisms by the airborne route. Epidemiol Infect. 118, 71–75.

Pujalté, I., Dieme, D., Haddad, S., Serventi, A.M., Bouchard, M. (2017a). Toxicokinetics of titanium dioxide (TiO₂) nanoparticles after inhalation in rats. Toxicol. Lett. 265, 77–85. https://doi.org/10.1016/j.toxlet.2016.11.014

Pujalté, I., Serventi, A., Noël, A., Dieme, D., Haddad, S., Bouchard, M. (2017b). Characterization of aerosols of titanium dioxide nanoparticles following three generation methods using an optimized aerosolization system designed for experimental inhalation studies. Toxics 5, 14. https://doi.org/10.3390/toxics5030014

Rajabi-Vardanjani, H., Asilian-Mahabadi, H., Sedehi, M. (2019). Particulate matter inhalation exposure chambers and parameters affecting their performance: A systematic review Study. Health Scope. 8, e80163. https://doi.org/10.5812/jhealthscope.80163

Rasco, J.F., Hood, R.D. (1995). Maternal restraint stress-enhanced teratogenicity of all-trans-retinoic acid in CD-1 mice. Teratology 51, 57–62. https://doi.org/10.1002/tera.1420510203

Sartori, F., Vidrio, E. (2018). Environmental fate and ecotoxicology of paraquat: A California perspective. Toxicol. Environ. Chem. 100, 479–517. https://doi.org/10.1080/02772248.2018.1460369

Schmoll, L., Elzey, S., Grassian, V., O'Shaughnessy, P. (2009). Nanoparticle aerosol generation methods from bulk powders for inhalation exposure studies. Nanotoxicology 3, 265–275. https://doi.org/10.3109/17435390903121931

Schreck, R.M., Soderholm, S.C., Chan, T.L., Smiler, K.L., D'arcy, J.B. (1981). Experimental conditions in GMR chronic inhalation studies of diesel exhaust. J. Appl. Toxicol. 1, 67–76. https://doi.org/10.1002/jat.2550010205

Silver, S.D. (1946). Constant flow gassing chambers: Principles influencing design and operation. J. Lab. Clin. Med. 31, 1153–1161. https://doi.org/10.5555/uri:pii:0022214346901576

Tanner, C.M., Kamel, F., Ross, G.W., Hoppin, J.A., Goldman, S.M., Korell, M., Marras, C., Bhudhikanok, G.S., Kasten, M., Chade, A.R., Comyns, K., Richards, M.B., Meng, C., Priestley, B., Fernandez, H.H., Cambi, F., Umbach, D.M., Blair, A., Sandler, D.P., Langston, J.W. (2011). Rotenone, paraquat, and Parkinson's disease. Environ. Health Perspect. 119, 866–872. https://doi.org/10.1289/ehp.1002839

Tuttle, R.S., Sosna, W.A., Daniels, D.E., Hamilton, S.B., Lednicky, J.A. (2010). Design, assembly, and validation of a nose-only inhalation exposure system for studies of aerosolized viable influenza H5N1 virus in ferrets. Virol. J. 7, 135. https://doi.org/10.1186/1743-422X-7-135

United States Department of Agriculture (USDA) (2015). USDA announces $4.6 Million for Nanotechnology Research. https://nifa.usda.gov/announcement/usda-announces-46-million nanotechnology-research (accessed 4 June 2019).

Wang, Y., Sun, C., Zhao, X., Cui, B., Zeng, Z., Wang, A., Liu, G., Cui, H. (2016). The application of Nano-TiO₂ photo semiconductors in agriculture. Nanoscale Res. Lett. 11, 529. https://doi.org/10.1186/s11671-016-1721-1

Weinstock, M. (2005). The potential influence of maternal stress hormones on development and mental health of the offspring. Brain. Behav. Immun. 19, 296–308. https://doi.org/10.1016/j.bi.2004.09.006

Willeke, K., Baron, P. (2001). Aerosol measurement: Principles, techniques, and applications. Van Nostrand Reinhold. https://doi.org/10.1002/9781118001684

Wong, B.A. (2007). Inhalation exposure systems: Design, methods and operation. Toxicol. Pathol. 35, 3–14. https://doi.org/10.1080/01926230601060017

Yeh, H.C., Newton, G.J., Barr, E.B., Carpenter, R.L., Hobbs, C.H. (1986). Studies of the temporal and spatial distribution of aerosols in multi-tiered inhalation exposure chambers. Am. Ind. Hyg. Assoc. J. 47, 540–545. https://doi.org/10.1080/15298668691390197

Yeh, H.C., Snipes, M.B., Eidson, A.F., Hobbs, C.H., Henry, M.C. (1990). Comparative evaluation of
<figure><img src="image_27.png" /></figure>

nose-only versus whole-body inhalation exposures for rats—Aerosol characteristics and lung deposition. *Inhalation Toxicol.* 2, 205–221. https://doi.org/10.3109/08958379009145255

Yi, J., Chen, B.T., Schwegler-Berry, D., Frazer, D., Castranova, V., McBride, C., Knuckles, T.L., Stapleton, P.A., Minarchick, V.C., Nurkiewicz, T.R. (2013). Whole-body nanoparticle aerosol inhalation exposures. *J. Vis. Exp. JoVE.* 75, e50263. https://doi.org/10.3791/50263
<figure><img src="image_32.png" /></figure>

nose-only versus whole-body inhalation exposures for rats—Aerosol characteristics and lung deposition. *Inhalation Toxicol.* 2, 205–221. https://doi.org/10.3109/08958379009145255

Yi, J., Chen, B.T., Schwegler-Berry, D., Frazer, D., Castranova, V., McBride, C., Knuckles, T.L., Stapleton, P.A., Minarchick, V.C., Nurkiewicz, T.R. (2013). Whole-body nanoparticle aerosol inhalation exposures. *J. Vis. Exp. JoVE.* 75, e50263. https://doi.org/10.3791/50263