Transient Multimedia Model for Investigating the Influence of Indoor Human Activities on Exposure to SVOCs

Modeling clothing as a secondary source of exposure to SVOCs across indoor microenvironments

BACKGROUND

Evidence suggests that clothing can influence human exposure to semi-volatile organic compounds (SVOCs) through transdermal uptake and inhalation.

OBJECTIVES

The objectives of this study were [1] to investigate the potential for clothing to function as a transport vector and secondary source of gas-phase SVOCs across indoor microenvironments, [2] to elucidate how clothing storage, wear, and laundering can influence the dynamics of transdermal uptake, and [3] to assess the potential for multiple human occupants to influence the multimedia dynamics of SVOCs indoors.

METHODS

A computational modeling framework (ABICAM) was expanded, applied, and evaluated by simulating and augmenting two "real-world" chamber experiments. A primary strength of this framework was its representation of occupants and their clothing as unique entities with the potential for location changes.

RESULTS

Estimates of transdermal uptake of diethyl phthalate (DEP) and di(n-butyl) phthalate (DnBP) were generally consistent with those extrapolated from measured concentrations of urinary metabolites, and those predicted by two other mechanistic models. ABICAM predicted that clean clothing (long sleeves, long pants, and socks, 100% cotton, 1 mm thick) readily accumulated DEP (6900-9700 μg) and DnBP (4500-4800 μg) from the surrounding chamber air over 6 h of exposure to average concentrations of 233 (DEP) and 114 (DnBP) μg·m-3. Because of their high capacity, clean clothing also effectively minimized transdermal uptake. In addition, ABICAM predicted that contaminated clothing functioned as a vector for transporting DEP and DnBP across indoor microenvironments and reemitted 13-80% (DEP) and 3-27% (DnBP) of the accumulated masses over 48 h.

SIGNIFICANCE

Though the estimated secondary inhalation exposures from contaminated clothing were low compared to the corresponding primary exposures, these secondary exposures could be accentuated in other contexts, for example, involving longer timeframes of clothing storage, multiple occupants wearing contaminated clothing, and/or repeated instances of clothing-mediated transport of contaminants (e.g., from an occupational setting).

IMPACT

This modeling study reaffirms the effectiveness of clean clothing in reducing transdermal uptake of airborne SVOCs and conversely, that contaminated clothing could be a source of SVOC exposure via transdermal uptake and by acting as a vector for transporting those contaminants to other locations.

Simulating patterns of life: More representative time-activity patterns that account for context

BACKGROUND

Complex contributions of environment to health are intimately connected to human behavior. Modeling of human behaviors and their influences helps inform important policy decisions related to critical environmental and public health challenges. A typical approach to human behavior modeling involves generating daily schedules based on time-activity patterns of individual humans, simulating 'agents' with these schedules, and interpreting patterns of life that emerge from the simulation to inform a research question. Current behavior modeling, however, rarely incorporates the context that surrounds individuals' truly broad scope of activities and influences on those activities.

OBJECTIVES

We describe in detail a range of elements involved in generating time-activity patterns and connect work in the social science field of behavior modeling with applications in exposure science and environmental health. We propose a framework for behavior modeling that takes a systems approach and considers the broad scope of activities and influences required to simulate more representative patterns of life and thus improve modeling that underlies understanding of environmental contributions to health and associated decisions to promote and protect public health.

METHODS

We describe an agent-based modeling approach reliant on generating a population's schedules, filtering the schedules, simulating behavior using the schedules, analyzing the emergent patterns, and interrogating results that leverages general empirical information in a systems context to inform fit-for-purpose action.

DISCUSSION

We propose a centralized and standardized program to codify behavior information and generate population schedules that researchers can select from to simulate human behavior and holistically characterize human-environment interactions for a variety of public health applications.

Modeling Clothing as a Vector for Transporting Airborne Particles and Pathogens across Indoor Microenvironments

Evidence suggests that human exposure to airborne particles and associated contaminants, including respiratory pathogens, can persist beyond a single microenvironment. By accumulating such contaminants from air, clothing may function as a transport vector and source of "secondary exposure". To investigate this function, a novel microenvironmental exposure modeling framework (ABICAM) was developed. This framework was applied to a para-occupational exposure scenario involving the deposition of viable SARS-CoV-2 in respiratory particles (0.5-20 μm) from a primary source onto clothing in a nonhealthcare setting and subsequent resuspension and secondary exposure in a car and home. Variability was assessed through Monte Carlo simulations. The total volume of infectious particles on the occupant's clothing immediately after work was 4800 μm3 (5th-95th percentiles: 870-32 000 μm3). This value was 61% (5-95%: 17-300%) of the occupant's primary inhalation exposure in the workplace while unmasked. By arrival at the occupant's home after a car commute, relatively rapid viral inactivation on cotton clothing had reduced the infectious volume on clothing by 80% (5-95%: 26-99%). Secondary inhalation exposure (after work) was low in the absence of close proximity and physical contact with contaminated clothing. In comparison, the average primary inhalation exposure in the workplace was higher by about 2-3 orders of magnitude. It remains theoretically possible that resuspension and physical contact with contaminated clothing can occasionally transmit SARS-CoV-2 between humans.

Textile Washing Conveys SVOCs from Indoors to Outdoors: Application and Evaluation of a Residential Multimedia Model

Indoor environments have elevated concentrations of numerous semivolatile organic compounds (SVOCs). Textiles provide a large surface area for accumulating SVOCs, which can be transported to outdoors through washing. A multimedia model was developed to estimate advective transport rates (fluxes) of 14 SVOCs from indoors to outdoors by textile washing, ventilation, and dust removal/disposal. Most predicted concentrations were within 1 order of magnitude of measurements from a study of 26 Canadian homes. Median fluxes to outdoors [μg·(year·home)^-1] spanned approximately 4 orders of magnitude across compounds, according to the variability in estimated aggregate emissions to indoor air. These fluxes ranged from 2 (2,4,4'-tribromodiphenyl ether, BDE-28) to 30 200 (diethyl phthalate, DEP) for textile washing, 12 (BDE-28) to 123 200 (DEP) for ventilation, and 0.1 (BDE-28) to 4200 (bis(2-ethylhexyl) phthalate, DEHP) for dust removal. Relative contributions of these pathways to the total flux to outdoors strongly depended on physical-chemical properties. Textile washing contributed 20% tris-(2-chloroisopropyl)phosphate (TCPP) to 62% tris(2-butoxyethyl)phosphate (TBOEP) on average. These results suggest that residential textile washing can be an important transport pathway to outdoors for SVOCs emitted to indoor air, with implications for human and ecological exposure. Interventions should try to balance the complex tradeoff of textile washing by minimizing exposures for both human occupants and aquatic ecosystems.

Assessing Human Exposure to SVOCs in Materials, Products, and Articles: A Modular Mechanistic Framework

A critical review of the current state of knowledge of chemical emissions from indoor sources, partitioning among indoor compartments, and the ensuing indoor exposure leads to a proposal for a modular mechanistic framework for predicting human exposure to semivolatile organic compounds (SVOCs). Mechanistically consistent source emission categories include solid, soft, frequent contact, applied, sprayed, and high temperature sources. Environmental compartments are the gas phase, airborne particles, settled dust, indoor surfaces, and clothing. Identified research needs are the development of dynamic emission models for several of the source emission categories and of estimation strategies for critical model parameters. The modular structure of the framework facilitates subsequent inclusion of new knowledge, other chemical classes of indoor pollutants, and additional mechanistic processes relevant to human exposure indoors. The framework may serve as the foundation for developing an open-source community model to better support collaborative research and improve access for application by stakeholders. Combining exposure estimates derived using this framework with toxicity data for different end points and toxicokinetic mechanisms will accelerate chemical risk prioritization, advance effective chemical management decisions, and protect public health.

Addressing uncertainty in mouthing-mediated ingestion of chemicals on indoor surfaces, objects, and dust

In indoor environments, humans ingest chemicals present as surface residues and bound to settled particles (dust), through mouthing hands (hand-to-mouth transfer) and objects (object-to-mouth transfer). Here, we introduce a novel modeling approach in support of systematic investigation into the mouthing-mediated ingestion of chemicals present in indoor environments. This model explicitly considers the indoor dynamics of dust and chemicals, building on mechanistic links with physicochemical properties of chemicals, features of the indoor environment, and human activity patterns. The evaluation of this model demonstrates that it satisfactorily reproduces chemical hand loadings and exposure data reported in the literature. We then use the evaluated model to investigate the response of mouthing-mediated ingestion to chemical partitioning between the gas phase and solid phases, expressed as the octanol-air partition coefficient (K_OA). Assuming a unit emission rate to the indoor environment, we find that low-volatility chemicals (with a K_OA greater than 10⁹) are more efficiently enriched in hand skin, resulting in higher mouthing-mediated ingestion than other compounds. For individuals living in a room with a typical level of dustiness, more than half of the chemical mass found in their hands comes from dust transfer, whereas more than half of the chemical mass ingested is the fraction present as residues on hands. We also use the new model to explore how the mouthing-mediated ingestion of chemicals is dependent on factors describing the indoor environment and human behavior. The model predicts that less frequent cleaning leads to higher accumulation of dust on indoor surfaces, thereby transferring more chemicals to hands and mouth in each contact. Introducing more dust into the room, but maintaining the same cleanup frequency, increases the dustiness of indoor surfaces, which promotes the transfer of relatively volatile chemicals (with a K_OA lower than 10⁹) to hands and mouth but decreases the transfer of chemicals with low volatility. More frequent hand contact with indoor surfaces increases both the hand loading and mouthing-mediated ingestion of chemicals, but the increases are more remarkable for adults than children because the higher surface contact frequency of children "saturates" hand loadings. An increase in handwashing frequency lowers the hand loading and mouthing-mediated ingestion of chemicals and this mitigating process is more prominent for relatively volatile chemicals. The new evaluated modeling approach can facilitate the prediction of mouthing-mediated ingestion for various age groups and the model predictions can be used to aid future fate and (bio)monitoring studies focusing on indoor contamination.