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# Human health impacts and indoor chemical reactions of VOCs from cleaning products and occupants

Rachna Bhoonah, Maxence Mendez, Alice Maury-Micolier

► To cite this version:

Rachna Bhoonah, Maxence Mendez, Alice Maury-Micolier. Human health impacts and indoor chemical reactions of VOCs from cleaning products and occupants. Atmospheric Environment, 2024, 338, pp.120846. 10.1016/j.atmosenv.2024.120846. hal-04801752

HAL Id: hal-04801752

https://hal.inrae.fr/hal-04801752v1

Submitted on 25 Nov 2024

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# Human health impacts and indoor chemical reactions of VOCs from cleaning products and occupants

Rachna Bhoonah<sup>a,b,*</sup>, Maxence Mendez<sup>c</sup>, Alice Maury-Micolier<sup>c</sup>

## HIGHLIGHTS

* Health impacts of cleaning products and occupants were up to 13 s/day, of which 12 % are linked to occupants.

* Indoor air chemistry increased impacts by up to 28% for the case studied.

* Particulate matter concentrations increased by a factor 1.2 (mass) and 25000 (number).

## ABSTRACT

Occupants and indoor activities are sources of volatile organic compounds (VOCs). We propose a framework to simulate the pollutant pathway using the INCA-Indoor© model and VOC emission rates to derive dynamic concentrations, and the USEtox model to evaluate health impacts in DALYs (Disability-Adjusted Life Years). The applicability of the framework is tested on a case study, and the effect of indoor chemical reactions on health impacts is assessed. In this case study, health impacts were of 0.3 µDALY/day without and 0.4 µDALY/day (13 s/day) with indoor air chemistry (+28 %) out of which 12 % were linked to occupant breath and skin emissions. Cleaning activities led to the highest impacts without chemical reactions (terpinolene, responsible for 0.14 µDALY/day), but indoor air chemistry led to high impacts linked to formaldehyde formation (0.18 µDALY/day). These reactions led to the formation of more formaldehyde, hence leading to 20% more impacts, in summer than in winter. Occupants' contribution to CO₂ concentrations exceeded recommended limits under the given occupancy and ventilation scenario. Secondary organic aerosol (SOA) formation affected indoor particulate matter mass concentrations by up to a factor 1.2 and their number concentrations by up to a factor 25,000 in the presence of VOC emissions. Results of this study indicate that chemical reactions and SOA formation are important factors to consider in indoor air quality impact assessment. A larger number of activities and scenarios can be tested to improve the robustness of the conclusions, since, under different scenarios (for e.g. activities with lower emission rates) and with more complete toxicity data, these conclusions are likely to change.

## 1. Introduction

Indoor air quality (IAQ) is of particular concern to health since humans spend about 85% of their time in indoor environments, hence being exposed to potentially harmful substances (ANSES, 2013). Indoor pollutant sources include materials, indoor activities and occupants (from skin, breath and clothes). Construction and furniture materials can emit volatile organic compounds (VOCs) continuously, irrespective of occupancy, while VOC emissions from occupants are continuous and linked to occupancy. As for indoor activities, they emit VOCs or fine particulate matter (PM₂.₅) punctually and are related to occupancy. VOCs commonly present indoors such as formaldehyde or d-limonene can be highly toxic, and even carcinogenic. Their effects were reported in epidemiological studies and are quantified in the USEtox database

(Fantke et al., 2017).

Indoor pollutant emissions occur in relatively small volumes with low air renewal rates and high surface-to-volume ratios. Thus, resulting VOC concentrations can be higher than acute toxicological value thresholds, especially for cleaning (Karr et al., 2021). VOCs are added in cleaning products and air fresheners to prevent bacteria formation and mask or enhance odours (Weschler and Carslaw, 2018). Occupants are also direct sources of pollutants such as VOCs and carbon dioxide (CO₂) from their skin (Mochalski et al., 2014) and breath (Kruza and Carslaw, 2019; Sun et al., 2017). These emissions depend on diet, metabolism, smoking habits, use of perfumes and cosmetics, and cutaneous reactions.

Another important factor influencing indoor air quality is indoor air chemistry. The indoor environment is particularly favourable to chemical reactions between substances in air, due to direct sunlight, low

<footnote><sup>a</sup> Mines Paris PSL, Centre Efficacité Energétique des Systèmes, 5 Rue Leon Blum, 91120, Palaiseau, France</footnote>

<footnote><sup>b</sup> UMR ECOSYS, INRAE, AgroParisTech, Université Paris-Saclay, Palaiseau, France</footnote>

<footnote><sup>c</sup> Octopus Lab, 270 Avenue de La République, 59110, La Madeleine, France</footnote>

<footnote>* Corresponding author. Mines Paris PSL, Centre Efficacité Energétique des Systèmes, 5 Rue Leon Blum, 91120, Palaiseau, France.
E-mail address: rachna.bhoonah@agroparistech.fr (R. Bhoonah).</footnote>
temperature fluctuations, the absence of rain, high surface-to-volume ratios and high concentrations of organic compounds (Weschler and Carslaw, 2018). Reactive substances include ozone and VOCs (in particular terpenoids), and reaction products include secondary VOCs or organic aerosols (SOA). For instance, five of the VOCs emitted by an air freshener were degraded and caused the formation of SOA in the presence of O3 (Liu et al., 2004). Studies suggest that the health effects of secondary substances could be non-negligible, but they are complex due to the large variety of substances present in air and high number of possible reactions (Nazaroff and Goldstein, 2015; Nazaroff and Weschler, 2004; Weschler, 2011; Weschler and Carslaw, 2018). Secondary pollutants are directly linked to some symptoms (Carslaw and Wolkoff, 2006; Nazaroff and Weschler, 2004; Weschler, 2004) and produce dangerous substances such as formaldehyde and acetaldehyde (Liu et al., 2004; Mendez et al., 2015). Models have been developed to simulate these reactions (Carslaw, 2007; Carter, 2010; Mendez et al., 2015; Sørensen and Weschler, 2002). For instance, the INCA Indoor model (Mendez et al., 2015) which is based on the SAPRC-07 model (Carter, 2010) takes into account the different physical and chemical reactions, including photolysis, coagulation, condensation and nucleation processes.

The evacuation of pollutants leads to a decrease in their intake as well as a decrease in formation of secondary substances. The main mode of evacuation is ventilation: ventilating after an activity can help reduce concentrations by a factor of 10–1000 (Karr et al., 2021). However, high ventilation rates could lead to higher energy consumption by ventilation fans or for heating in winter and thus increase environmental impacts. The integration of IAQ to the life cycle assessment (LCA) of buildings would not only allow to consider impacts of all stages of the building’s life cycle, but also allow to avoid impacts, namely of IAQ, right at the design phase. Ideal ventilation strategies could thus be elaborated by including occupant and activity related impacts in life cycle assessment (LCA) to avoid the transfer of impacts. A framework was developed by Maury-Micolier et al. (2023a) and Bhoonah et al. (2023a) for calculating health impacts from construction materials in the endpoint unit used in LCA, the disability-adjusted life years (DALYs), recommended by the World Health Organisation (Murray and Acharya, 1997).

In the case of activities, some studies have aimed at evaluating their health risks, but using indicators incompatible with LCA. They are often based on monitoring, which is a curative measure and not preventive since impacts have potentially already occurred (Dimitroulopoulou et al., 2015; Huang et al., 2011a; Karr et al., 2021; Lee et al., 2006; Slezakova et al., 2018; Zhu et al., 2001). Such studies provide emission rates and indoor air concentrations of released VOCs by different indoor activities (Huang et al., 2011b; Nazaroff and Weschler, 2004; Singer et al., 2006) and by occupant breath and skin (Fenske and Paulson, 1999; Kruza and Carslaw, 2019; Sun et al., 2017; Zou et al., 2020). Environmental impacts of different cleaning products have been calculated using LCA throughout their lifespan, but only water consumption and no exposure to released VOCs were considered in the use stage (Van Lieshout et al., 2015). This is why this paper proposes a framework accounting for occupant and activity VOC emissions in building LCA. The entire pollutant pathway linking emission rates to exposure concentrations and health damage is studied, with a unit common to the LCA end-point health damage indicator: the DALY. Another innovation of this study is an explorative research on the effects of indoor air chemistry and the assessment of its importance on occupant health. The framework is applied on a case study with the following steps:

1. Collect breath, skin, clothes and activity VOC emission rates for a given activity scenario.

2. Calculate indoor VOC concentrations for given activity scenarios, emission rates and building parameters using INCA-Indoor®

3. Calculate indoor VOC concentrations for the same scenarios, considering indoor chemical reactions

4. Evaluate health damages by coupling concentrations to occupant exposure via different intake pathways and effect factors.

## 2. Materials and methods

### 2.1. General framework

The proposed framework for the calculation of health damages resulting from exposure to indoor VOCs from occupants and indoor activities is presented in Fig. 1.

Activities with available VOC emission rates (µg/h) are identified in literature. The VOCs’ indoor air concentrations are calculated by INCA-Indoor®, coupled with CONTAM for the airflow modelling, based on 1) building characteristics modelled on Pleiades (ÉNERGIES, 2001) (air flow rates and room volume, as described in the case study description), 2) meteorological conditions (wind speed, temperature), 3) outdoor pollution levels and 4) an activity scenario. Dynamic concentrations are coupled with exposure factors (which depend on occupancy scenario) to calculate the intake $M_{in.path}$ (µgintake) for four different pathways: inhalation, ingestion, direct dermal contact and gaseous dermal uptake (Huang et al., 2017; Maury-Micolier et al., 2023b; Rosenbaum et al., 2007). Health impacts are evaluated using $M_{in.path}$ and the effect factor $EF$ (µDALY/µgintake) for each substance and for all paths. The total intake $M_{in.path}$ of a substance is calculated by equation (3) below for a given intake pathway:

$$M_{in.path} = V_{room} \int_{t=0}^{T} XF_{path} \times C_{in}dt \quad (1)$$

Where $V_{room}$ (m³) is the room volume, $C_{in}$ (µg/m³) is the indoor air concentration of the substance, $T$ (h) is the duration of exposure and $XF_{path}$ (h⁻¹) is the exposure factor of all occupants for a given pathway, described in Supporting Information section S.1. Health impacts are calculated using the USEtox model (Fantke et al., 2017). The total health impacts $HI$ (µDALY) is given by the product of the effect factor $EF$ (µDALY/µgintake) and the total mass intake $M_{in}$ (µgintake) of the substance for each pathway.

$$HI = \sum_{path} M_{in.path} \times EF_{path} \quad (2)$$

The effect factor of a substance can be obtained from its $ED_{10}$ or $ED_{50}$ (the lifetime doses per person that cause a disease probability of 10% and 50% after intake), as described in Supporting Information section S.2.

### 2.2. Case study description

An office of Octopus Lab (developer of INCA-Indoor®), having a 42-m³ volume and occupied by 3 persons during working days from 8:30–12:30 and 13:30–18:00 is used as case study. Common activities, identified as important contributors to indoor VOCs, are considered: cleaning and using air fresheners (Nazaroff and Weschler, 2004; Singer et al., 2006). The room is cleaned in the morning and occupants use air fresheners at 14:00. A fixed air renewal rate of 1 h⁻¹ is considered, with a standard infiltration rate of 1.7 m³/m²·h under 4 Pa, corresponding to the low-end of average tertiary buildings (e.g. offices, schools, supermarkets or hospitals) (Carrié and Fournier). The floor plan of the office (Office – 1) is given in Fig. 2.

### 2.3. Emission data

Data obtained from various measurement campaigns of VOC emissions from occupants and activities and the durations are summarised in Table 1. The list of emitted substances and their emission rates are presented in SI Table S1 – S6.
<figure><img src="image_4.png" /><figcaption>Fig. 1. Framework for evaluating health damage from occupants and activities: linking emission rates to exposure and health damage.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Fig. 2. Floor plan of the office (Office - 1).</figcaption></figure>

The contribution of occupants to indoor CO₂ emission is also studied. The emission rate Vco₂ (L/s) can be determined by the following relationship established by Persily and de Jonge (2017) as a function of basal metabolic rate BMR (MJ/day) and metabolic rate M (met), the ratio of the working metabolic rate to the resting metabolic rate:

$$V_{co_2} = 1.79 \times 10^{-4} \times BMR \times M \times (T/P) \quad (3)$$

where T (K) is the air temperature and P (kPa) the pressure. The mass of CO₂ generated can be calculated from its density of 1.84 g/L. The BMR according to age and sex can be obtained from the same study and M
<caption>**Table 1**</caption>

Activities and direct occupant emissions considered in the office and their durations.

<table><thead><tr><th>Emission Source</th><th>Reference</th><th>Duration (min)</th></tr></thead><tbody><tr><td>Skin</td><td>Mochalski et al., 2014</td><td>During occupant presence</td></tr><tr><td>Exhaled air</td><td>Riess et al., 2010; Persily and de Jonge 2017</td><td>During occupant presence</td></tr><tr><td>Shoes</td><td>Kurosawa et al., 2008</td><td>During occupant presence</td></tr><tr><td>Air freshener</td><td>Singer et al., 2006</td><td>1<sup>a</sup></td></tr><tr><td>Counter cleaner</td><td>Singer et al., 2006</td><td>10</td></tr><tr><td>Floor cleaner</td><td>Singer et al., 2006</td><td>15</td></tr></tbody></table>

<sup>a</sup> Though 1-min of deodorant use seems to be unrealistic, INCA-Indoor® does not allow to simulate few seconds of an activity.

(met) can be determined according to the activity intensity (Harvard School of Public Health. and Staying Active, 2012). Since office activities are generally of low intensity, no significant variation in the amount of CO₂ released per person was considered. The average of female and male CO₂ emissions for the 21–30 age group are calculated for M = 1.2 met activity intensity, corresponding to office work. This results in 28 g/h per person.

## 2.4. Simulation using INCA-Indoor®

The INCA-Indoor® multizone model uses building parameters (e.g. room volume, materials), occupancy scenarios, activity emission rates, air renewal rates and indoor gas phase chemistry to calculate indoor concentrations of gases and particulate matter. Each room is considered as one zone with well-mixed air. Thus, the air concentration is uniform in all points of the room. The building location has to be indicated, so that it is linked to outdoor ozone, nitrogen oxides, and particulate matter (PM) concentrations obtained from monitoring stations. These substances are carried indoors by the air exchanges between indoors and outdoors. Air flows are simulated using CONTAM (Dols and Polidoro, 2020) considering infiltration, exfiltration, and flows between rooms based on indoor and outdoor pressures and temperatures (Mendez et al., 2015). The entire ventilation system is defined, i.e. filters, recirculation, operating schedule. Indoor temperatures are considered to be constant and equal to 20 °C. Air is treated as an ideal gas, obeying the ideal gas law. The SAPRC-07 detailed chemical mechanism is used in INCA-Indoor® to simulate the concentrations of about 800 VOCs and their reactivity with the main oxidants (OH•, O₃, NO₃•, etc), as described in Mendez et al. (2015).

Ozone deposition on surfaces is accounted for using a deposition velocity of 0.35 cm/s. As a consequence, less ozone remains in the gaseous phase to interact with VOCs. Its deposition on the skin is not considered in this study, as these surfaces are small compared to the walls, ceiling and floor. They are equal to 150 m², participating in heterogeneous reactions with ozone. In contrast, 0.33 m² of skin surface is available per occupant for ozone uptake ((Mosteller, 1987)), representing only 1% of the total room surfaces available for such reactions. Consequently, reactivity on the occupant is disregarded, but heterogeneous reactivity is still partially considered.

It is important to note that not all substances emitted by the activities considered are treated by INCA-Indoor®: out of the 79 different substances emitted by occupants and activities altogether, 51 of them, treated by the SAPRC-07 model, are included in INCA-Indoor® and in the results. In particular, there are 45 out of 65 substances treated for skin emissions, 12 out of 15 for breath, 3 out of 9 for air freshener and 6 out of 16 for the counter and floor cleaners. It is thus expected that exposure will be underestimated. Outdoor VOC concentrations are considered as negligible (Heeley-Hill A et al., 2021; Jia et al., 1987; Xu et al., 2016).

### 2.4.1. Scenarios

INCA-Indoor® can simulate concentrations by accounting for emissions from activities or from occupants, or in the absence of emissions. Simulations can include precursors to indoor chemical reactions: ozone (O₃) or nitrogen oxides (NO and NO₂). They react with VOCs (Mendez et al., 2015), and their concentrations can also be set to zero throughout the simulation in order to evaluate their influence on chemical reactions. INCA-Indoor® includes secondary organic aerosol (SOA) formation through condensation and nucleation (Berger et al., 2023), based on the hydrophilic/hydrophobic organic (H₂O) model by Couvidat et al. (2012) to calculate the equilibrium between the gas phase and the aerosols of several species or groups of species. Other physical processes linked to particulate matter such as coagulation and deposition have also been validated by Berger et al. (Xu et al., 2016). Results are presented for different combinations, summarised in Table 2:

Seasonal variations alter outdoor environmental conditions, including temperature and wind, which subsequently affect the infiltration rate of outdoor air. However, due to the presence of an air handling unit (AHU) in the building, infiltration contributes only minimally to the air exchange rate in rooms equipped with supply and/or control vents. Additionally, seasonal changes impact radiation levels, influencing photochemical processes. Finally, outdoor concentrations of ozone and NOx also vary with the season. Therefore, the baseline scenario is equal for summer and winter since chemical reactions are not taken into account.

## 3. Results

### 3.1. Primary VOC concentration curves

INCA-Indoor® can evaluate concentrations for a desired period, and a duration of one day is selected since 24 h are sufficient to evacuate all emitted/produced pollutants in the context of this study. Results are thus representative of one summer working day. Due to the large number of substances (64) and for ease of comprehension, only those with the highest concentrations and/or leading to significant impacts are presented. Indoor activities (cleaning and the use of air freshener) contribute to the increase of mainly two substances: terpinolene and d-limonene, presented in Fig. 3(a) and (b). Thus, the different scenarios presented in Fig. 3 consider these activities:

<caption>**Table 2**</caption>

Simulated scenarios according to season, emission sources and secondary substance formation where *wint* corresponds to winter, *sum* corresponds to summer, *chem* corresponds to chemical reactions, and *occ* and *act* indicate the presence of occupant and activity emissions respectively.

<table><thead><tr><th>Scenario name</th><th>Season</th><th>Chemical reactions</th><th>Occupants</th><th>Activities</th><th>SOA</th></tr></thead><tbody><tr><td>wint/sum</td><td>Winter/</td><td>x</td><td>x</td><td>x</td><td>x</td></tr><tr><td>baseline</td><td>Summer</td><td></td><td></td><td></td><td></td></tr><tr><td>wint/chem.</td><td>Winter</td><td>✓</td><td>x</td><td>x</td><td>x</td></tr><tr><td>wint/chem. + occ.</td><td>Winter</td><td>✓</td><td>✓</td><td>x</td><td>x</td></tr><tr><td>wint + occ. + act.</td><td>Winter</td><td>x</td><td>✓</td><td>✓</td><td>x</td></tr><tr><td>wint/chem. + occ. + act.</td><td>Winter</td><td>✓</td><td>✓</td><td>✓</td><td>x</td></tr><tr><td>sum/chem.</td><td>Summer</td><td>✓</td><td>x</td><td>x</td><td>x</td></tr><tr><td>sum/chem. + occ.</td><td>Summer</td><td>✓</td><td>✓</td><td>x</td><td>x</td></tr><tr><td>sum + occ. + act.</td><td>Summer</td><td>x</td><td>✓</td><td>✓</td><td>x</td></tr><tr><td>sum/chem. + occ. + act.</td><td>Summer</td><td>✓</td><td>✓</td><td>✓</td><td>x</td></tr><tr><td>sum/chem. + occ. + act. + SOA</td><td>Summer</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>sum/chem. + SOA</td><td>Summer</td><td>✓</td><td>x</td><td>x</td><td>✓</td></tr></tbody></table>
<figure><img src="image_6.png" /><figcaption>Fig. 3. Air concentrations of two main VOCs (a) terpinolene and (b) d-limonene in summer for scenarios including activity emissions (act), with and without chemical reactions (chem).</figcaption></figure>

1) concentrations related to indoor activities, without chemical reactions (sum + act, solid pink line)

2) concentrations related to indoor activities, with chemical reactions (sum/chem + act, dotted red line)

3) concentrations related to indoor activities and occupant contribution, with chemical reactions (sum/chem + act + occ, solid yellow line)

During the activity (cleaning), there is an increase by about 560 and 570 µg/m³ for d-limonene and terpinolene respectively, followed by an exponential decay due to evacuation by air renewal. Chemical reactions lead to a decrease in concentrations of both substances which are consumed: by up to 90 µg/m³ for terpinolene (16 % of the peak concentration) and 44 µg/m³ for d-limonene (8 % of the peak concentration). There is no difference between the scenarios sum/chem + act and sum/chem + act + occ, indicating that VOCs emitted by occupants do not interfere with reactions between terpinolene, d-limonene and precursors.

Though occupants do not contribute to terpinolene and d-limonene emissions, they contribute to the presence of 56 VOCs through their skin and breath (see SI Tables S1 and S2). Fig. 4 illustrates the concentrations of the 10 VOCs emitted by occupant breath and skin leading to the highest health impact.

<figure><img src="image_7.png" /><figcaption>Fig. 4. Concentration of the 10 VOCs emitted by occupant breath and skin with the highest health impacts, in the presence of indoor air chemistry. The substances are listed by order of their health impact: formaldehyde having the highest and acetone the smallest.</figcaption></figure>

VOC concentrations increase with the presence of occupants and decrease during their absence at midday. The peak concentration of acetone is of about a tenth of the concentration of terpinolene emitted by cleaning (55 v/s 570 µg/m³). The VOCs are listed by order of impacts in the legend of Fig. 4. Thus, VOCs with the highest concentrations do not necessarily lead to the highest impacts. For instance, formaldehyde leads to the highest impacts of 0.003 µDALY/day and a peak concentration of 0.2 µg/m³, while acetone has the highest peak concentration of all VOCs (54 µg/m³), but its impacts are 65 times lower than formaldehyde.

Formaldehyde, isoprene, acetaldehyde, acetonitrile, phenol and acetone are mainly emitted by breath, and the others are emitted by skin. Recent studies have shown that skin emissions are affected by ozone: in the presence of this precursor, skin oils oxidise, hence increasing VOC emission rates by up to 5% (Qu et al., 2023). However, there is data on only a limited number of VOCs. The increase in concentrations, and consequently on health the impacts, are of up to 5 % (see SI Figure S1). In this case study, the occupancy rate is of 0.2 occ/m² (3 occupants for a 15 m² office). A scenario with double occupancy has also been tested (see SI section S.7.), corresponding to a likely occupancy rate for a classroom. Concentrations increase considerably, and health impacts per occupant increase by 11 % for the sum/chem + occ + act scenario (occupants and activity emissions in summer, with chemical reactions).

Occupants also breathe out CO₂, whose air concentrations are illustrated in Fig. 5. The concentration is presented in ppm (parts per million,

<figure><img src="image_8.png" /><figcaption>Fig. 5. CO₂ concentration in air (green curve) and the recommended limit (red line and shaded area).</figcaption></figure>
where 1 ppm CO₂ = 1800 µg/m³) since it corresponds to the unit generally used for CO₂ and can hence be compared to recommendations.

The CO₂ concentration increases while the occupants are present and decreases during their absence. It can also be noted that, for a large part of the day and during almost the whole occupancy period of the office, CO₂ concentrations are above the recommended limit of 1000 ppm set by different national guidelines (ANSES, 2013; Canada Health, 2021). The concentrations remain within an acceptable range where occupants could experience increased drowsiness and lack of concentration, as compared to stronger symptoms such as increased heart rates, headaches or even suffocation occurring at much higher concentrations of over 40,000 ppm according to the USDA FSIS Safety (Food Safety and Inspection Service).

## 3.2. Secondary species concentration curves

The importance of indoor air chemistry on calculated concentrations of VOCs and particulate matter is explored. VOCs are precursors to many indoor chemical reactions: they react with O₃ and other oxidants. Reactions are hence dependent on the presence of these inorganic species. In summer, high temperatures and greater solar radiation accentuate the production of ozone outdoors. Therefore, we test for seasonal variations (summer/winter), with or without chemical reactions, with or without secondary organic aerosol (SOA) formation and with or without indoor VOC emissions (emi/no emi).

Fig. 6 shows the difference in concentrations with and without considering chemical reactions for seven VOCs emitted by both cleaning and occupants (terpinolene, d-limonene, alpha-pinene, beta-pinene, formaldehyde, acetaldehyde and methanol) in (a) winter and (b) summer. Negative values indicate that the substance is being consumed by chemical reactions.

Substances are mostly consumed by the chemical reactions. There is up to 90 µg/m³ decrease in terpinolene concentration due to chemical reactions and 3.3 µg/m³ increase for formaldehyde in summer. The effects are lower in winter, where the decrease is only up to 17 µg/m³ and the increase of up to 0.6 µg/m³ for the same substances. Higher effects of indoor air chemistry in summer can be explained by higher outdoor (and thus indoor as well) ozone concentrations in summer as compared to winter (see Fig. 6 (c)), with an average of 16 µg/m³ in summer and 2 µg/m³ in winter due to higher outdoor temperatures and lower wind speeds favouring its formation in the atmosphere, and higher photolysis rates. From Fig. 6 (c), we also note a sudden drop in indoor O₃ concentrations after 8 a.m. for scenarios considering indoor air chemistry, corresponding to the beginning of activities and VOC emissions. It illustrates that O₃ is consumed in these chemical reactions.

Formaldehyde is produced by reactions between organic compounds (e.g. isoprene, monoterpenes and oxygenated compounds) and hydroxyl radicals, nitrate radicals or ozone (Salthammer et al., 2010). In particular, d-limonene, beta-pinene and terpinolene, emitted by the activities considered in this study, were found to react with ozone to produce formaldehyde (Atkinson and Carter, 1984; Grosjean et al., 1993). Despite a relatively lower effect of chemical reactions on formaldehyde concentrations as compared to d-limonene and terpinolene (Fig. 6 (a*)) and (b*)), its health impact is higher (see SI Figure S3).

Formation of secondary organic aerosols (SOA) by nucleation, coagulation or condensation processes can affect the concentration of particulate matter. In Fig. 6, the effect of these reactions on air concentrations of PM₂.₅ with and without indoor VOC emissions are shown (a) by mass and (b), (c) and (d) by number. In INCA-Indoor®, particles are separated into 32 categories according to their diameter, ranging from 0.005 µm to 50 µm. The particle number shown are from the following categories: (b) 0.005–0.007 µm, (c) 0.07–0.09 µm and (d) 0.7–0.9 µm. We note that the scales are different in each plot: the particle number concentration goes up to over 10⁶ #/cm³ for the smallest particles in category (b), 750 #/cm³ for category (c) and less than 2 #/cm³ for category (d).

<figure><img src="image_9.png" /><figcaption>Fig. 6. Difference in concentrations with and without chemical reactions in (a) winter and (b) summer for seven VOCs, and (c) indoor O₃ concentrations in winter and summer for a typical day during the presence of occupants and cleaning activities in an office.</figcaption></figure>

It can be noted that PM₂.₅ concentrations increase by up to 2.8 µg/m³ due to SOA formation in the presence of VOC emissions, but there is no formation in the absence of these emissions. The increases are of 2.9 µg/m³ and 2.7 µg/m³ for PM₁ and PM₁₀ (see SI Figure S2). This change in mass is almost entirely due to the smallest particles of diameter under 7 nm (Fig. 7 (b)). These small, and consequently light, particles are formed by nucleation. Their formation leads to a significant increase in particle number (by a factor 25,000) but a lesser increase in mass (by up to a factor 1.2) because of their small diameter. These formations coincide with the release of VOCs from activities at 9 a.m.

The main organic species responsible for SOA formation (as modelled in INCA-Indoor®) include d-limonene, α-pinene, β-pinene, camphene, γ-terpinene and terpinolene, emitted by the cleaning detergent and air freshener (Weschler and Shields, 1999). Those SOA precursors are mainly oxidised by OH radicals and O₃. Their oxidation products, having low vapor pressure, tend to condense on existing particles or can even nucleate to form new particles. Other emitted
<figure><img src="image_10.png" /><figcaption>**Fig. 7.** Particle (a) mass and number concentrations with occupant and activity emissions in summer without SOA (chem), with SOA (soa), and without indoor emissions but with SOA (soa/no emi) for: (b) 0.005–0.007 µm, (c) 0.07–0.09 µm and (d) 0.7–0.9 µm.</figcaption></figure>

substances, namely monoterpenes that are found in essential oils and used to enhance odours, are not treated by INCA-Indoor© but could influence SOA formation. The scenarios are presented only for summer, since ozone levels are higher, leading to more reactions with terpenes for SOA formation.

### 3.3. Intake quantities and health damages

Intake quantities $M_{in.path}$ (µgintake/day) for VOCs are calculated and coupled with available effect factors (µDALY/µgintake) for each exposure pathway and each substance to obtain the total health impact per day (µDALY/day) across all substances. Total health impacts are the sum of impacts of substances for which toxicity data are available: 39 out of 67 VOCs studied (see SI S.6.). Fig. 8 shows the health impacts of VOCs for seven scenarios.

Health impacts linked to both cleaning activities and occupant emissions are of up to 0.43 µDALY/day (14 s lost per day). Occupants' contribution to health impacts from skin and breathing emissions

represent about 12 % of all impacts. The relative contribution of occupant emissions to the total health impact increases with occupancy density: for a classroom-type occupancy density, the health impact attributable to occupant emissions accounts for one-fifth of the total impact (see SI section S.7.). Thus, occupant emissions must not be neglected in air quality assessments.

It can also be noted that chemical reactions can increase health impacts by up to 28 % in summer and 7 % in winter (lower $O_3$ concentrations in winter, thus lower reactivity to produce toxic substances such as formaldehyde). Furthermore, impacts of occupant emissions could increase by 5 % if ozone reactivity with skin oils are considered, representing an increase of 2 % overall (see SI section S.4.).

These results are non-negligible when compared to impacts linked to VOCs emitted by materials, which represented $6.2 \times 10^{-3}$ µDALY/day to 2.4 µDALY/day for gypsum walls in an office of the same surface area for long (10,000 days) and short (10 days) exposure durations respectively (Bhoonah et al., 2023a). The difference is that, for materials, emissions decrease exponentially with time: aged materials tend to contain and emit less VOCs.

Even in the absence of indoor emissions from activities or occupants, some VOCs can be formed by chemical reactions. It is, for example, the case for formaldehyde in this case study, which is responsible for $1.4 \times 10^{-3}$ µDALY/day in summer, without any emission source (sum/chem scenario). As a comparison, for a room of the same surface area (15 m²), formaldehyde-related impacts were of about $1.0 \times 10^{-3}$ µDALY/day (long-term) to 1.03 µDALY/day (short-term) for gypsum board (Kruza and Carslaw, 2019) and $4.2 \times 10^{-2}$ µDALY/day for insulation materials (Maury-Micolier et al., 2023a). Since impacts due to secondary VOC formation are about an order of magnitude lower than those reported for VOCs emitted by materials, they should not be neglected in an effort to reduce human impacts of IAQ. Furthermore, concentrations of secondary formaldehyde reach up to 3.5 µg/m³ in summer (see Fig. 5), which is comparable to values measured for most cleaning products in literature, which range from 4 µg/m³ to 10 µg/m³ (Solal et al., 2008).

The increment in PM concentration due to SOA formation leads to an increment in inhalation of 9 µgPM2.5 (5%). Resulting increase in health impacts are expected to be of the same order, but are outside of the scope of this paper which focuses on VOC impacts of indoor activities.

### 4. Conclusions and perspectives

In this paper, a framework linking VOC emission data to health impacts was presented. Applied to a case study, the health damage due to VOCs emitted by occupants (skin, breath and shoes) and office activities (floor and counter cleaning, use of air freshener) were calculated. Damages are of up to 0.4 µDALY/day, leading to 18 µDALY/year for all occupants (9.5 minuteslost/year). Occupants contribute to about 12 % of all impacts. Health damages are most certainly underestimated due to lack of toxicity data, but also because INCA-Indoor© does not treat all substances: 39 out of 105 species (37%) were not considered. Results show that indoor chemistry is important to consider as once considered, it can affect the health of occupants by up to 30 % for an indoor mean $O_3$ concentration of 16 µg/m³. The formation of secondary organic aerosols affects PM concentrations in this case study by up to 2.9 µg/m³ (up to 21%) due to coagulation and nucleation. Seasonal variations were found to affect indoor VOC concentrations through chemical reactivity. For instance, terpinolene concentrations decreased by 90 µg/m³ in summer and 18 µg/m³ in winter due to chemical reactions. Furthermore, skin oil emissions are also dependent on ozone concentrations, often higher in summer.

A perspective of this study is to include missing toxicity data for VOCs, $NO_x$, $O_3$ and $CO_2$ when they become available. Though it is difficult to assess impacts of all known toxic substances since they rely on laboratory and epidemiology studies, machine learning models are being developed and their results can contribute to the robustness of this study (Hou et al., 2020). It was seen, in the case study, that $CO_2$
<figure><img src="image_11.png" /><figcaption>**Fig. 8.** Impacts (µDALY/day) in winter (orange) or summer (blue), with/without chemical reactions (patterns), considering occupant emissions (occ) and activity emissions (act).</figcaption></figure>

concentrations were higher than recommended values throughout the day. Besides climatic effects, CO₂ has up to now been mainly linked to short-term effects such as drowsiness or headaches, but recent studies indicate that it could have long-term health effects such as bone demineralisation, kidney calcification or induced high-level cognitive disabilities (Jacobson et al., 2019). Efforts should be made to further characterise its toxicity and derive effect factors for LCA.

Another important aspect of occupant emission is the reactivity of skin emissions to ozone. In the given case study and for an average ozone concentration of 16 µg/m³, emission rates increase by 1–5 % for the species considered. The ozone-dependency of these emission suggests that they should be considered, especially for settings with high ozone concentrations. Furthermore, under high occupancy rates, the concentrations of occupant-related VOCs can increase: in our case study, at twice the occupancy (corresponding to a classroom), the health impact per occupant increases by 11 %. Special attention should be paid to low-ventilated rooms which can favour the production of toxic substances such as formaldehyde (Salthammer, 2015), and SOA formation. The health effects of SOA should also be considered, as they form as a result of cleaning activities (especially for small particles of diameter <1 µm which penetrate more easily into the respiratory tract). This could be done by following the framework proposed by Bhoonah et al. (2023b). A study on secondary substances formation as a function of ventilation rates could help quantify the effect of ventilation rates on secondary species formation. Furthermore, in this study, only VOCs emitted by specific activities were considered. By including background VOC sources (e.g. materials and other activities), indoor chemical reactions could be affected, hence also affecting pollutant concentrations and resulting health impacts.

This framework can be applied to different activities with known emission rates to characterise their effects on health and integrate them into LCA. Another perspective would be to include emission models of VOCs from activities based on existing studies, summarised by Wei et al. for example (Wei et al., 2022). For instance, once a surface has been cleaned, the emission rate decreases with time due to evaporation. For air freshener emissions, the model proposed by Liu et al. (2004) could also be used. In addition, the exact location of the activity (and, subsequently, emissions), user and occupants could provide more precise exposure factors and exposure concentrations. This can be addressed by the use of computational fluid dynamics (CFD) modelling and agent-based modelling to define occupant behaviour. However, these are time-consuming while the method proposed in this paper allows drawing insights (high throughput screening) to then focus on design parameters that allow to reduce overall impacts. This framework can

help devise intelligent ventilation systems in order to avoid the introduction of precursors such as O₃ and NOₓ when buildings are not occupied, and ventilate for a given period before occupants enter the building to evacuate pollutants emitted by (and accumulated due to) other sources such as materials.

### CRediT authorship contribution statement

**Rachna Bhoonah:** Writing – review & editing, Writing – original draft, Visualization, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Maxence Mendez:** Writing – review & editing, Software. **Alice Maury-Micolier:** Writing – review & editing, Supervision, Methodology, Conceptualization.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Data availability

Data is given in the supplemental file

### Acknowledgements

The authors would like to thank the financial support by the Chair ParisTech VINCI Eco-design of buildings and infrastructure.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.atmosenv.2024.120846.

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