Novel Bayesian Method to Derive Final Adjusted Values of Physicochemical Properties: Application to 74 Compounds

Temperature dependence of the rain-gas and snow-gas partition coefficients for nearly a thousand chemicals

Compared to the particle-gas partition coefficients (KPG), the rain-gas (KRG) and snow-gas (KSG) partition coefficients are also essential in studying the environmental behavior and fate of chemicals in the atmosphere. While the temperature dependence for the KPG have been extensively studied, the study for KRG and KSG are still lacking. Adsorption coefficients between water surface-air (KIA) and snow surface-air (KJA), as well as partition coefficients between water-air (KWA) and octanol-air (KOA) are vital in calculating KRG and KSG. These four basic adsorption and partition coefficients are also temperature-dependent, given by the well-known two-parameters Antoine equation logKXY = AXY + BXY/T, where KXY is the adsorption or partition coefficients, AXY and BXY are Antoine parameters (XY stand for IA, JA, WA, and OA), and T is the temperature in Kelvin. In this study, the parameters AXY and BXY are calculated for 943 chemicals, and logKXY can be estimated at any ambient temperature for these chemicals using these Antoine parameters. The results are evaluated by comparing these data with published experimental and modeled data, and the results show reasonable accuracy. Based on these coefficients, temperature-dependence of logKRG and logKSG is studied. It is found that both logKRG and logKSG are linearly related to 1/T, and Antoine parameters for logKRG and logKSG are also estimated. Distributions of the 943 chemicals in the atmospheric phases (gas, particle, and rain/snow), are illustrated in a Chemical Space Map. The findings reveal that, at environmental temperatures and precipitation days, the dominant state for the majority of chemicals is the gaseous phase. All the AXY and BXY values for logKSG, logKRG, and basic adsorption and partition coefficients, both modeled by this study and collected from published work, are systematically organized into an accessible dataset for public utilization.

Widespread occurrence of pesticides in low-income housing

BACKGROUND

Low socioeconomic status (SES) residents living in social housing, which is subsidized by government or government-funded agencies, may have higher exposures to pesticides used in indoor residences since pesticides are applied due to structural deficiencies, poor maintenance, etc. OBJECTIVE: To estimate exposure of residents in low-SES social housing built in the 1970s to legacy and current-use pesticides and to investigate factors related to exposures.

METHODS

Twenty-eight particle-phase pesticides were measured in the indoor air of 46 units in seven low-income social housing, multi-unit residential buildings (MURBs) in Toronto, Canada using portable air cleaners deployed for 1 week in 2017. Pesticides analyzed were legacy and current use in the classes: organochlorines, organophosphates, pyrethroids, and strobilurins.

RESULTS

At least one pesticide was detected in 89% of the units with detection frequencies (DF) for individual pesticides of up to 50%, including legacy organochlorines and current-use pesticides. Current-use pyrethroids had the highest DF and concentrations, with the highest particle-phase concentration for pyrethrin I at 32,000 pg/m3. Heptachlor, restricted for use in Canada in 1985, had the highest estimated maximum total air (particle plus gas phase) concentration of 443,000 pg/m3. Heptachlor, lindane, endosulfan I, chlorothalonil, allethrin, and permethrin (except in one study) had higher concentrations than those measured in low-income residences reported elsewhere. In addition to the intentional use of pesticides to control pests and their use in building materials and paints, tobacco smoking was significantly correlated with the concentrations of five pesticides used on tobacco crops. The distribution of pesticides with high DF in individual buildings suggested that pest eradication programs by the building management and/or pesticide use by residents were the major sources of measured pesticides.

IMPACT

Low-income social housing fills a much-needed demand, but the residences are prone to pest infestation and hence pesticide use. We found exposure to at least 1 of 28 particle-phase pesticides in 89% of all 46 units tested, with the highest DF and concentrations for current-use pyrethroids and long-banned organochlorines (e.g., DDT, heptachlor) due to very high persistence indoors. Also measured were several pesticides not registered for use indoors, e.g., strobilurins used to treat building materials and pesticides used on tobacco crops. These results, which are the first Canadian data for most pesticides indoors, show widespread exposure to numerous pesticides.

Bioretention Design Modifications Increase the Simulated Capture of Hydrophobic and Hydrophilic Trace Organic Compounds

Stormwater rapidly moves trace organic contaminants (TrOCs) from the built environment to the aquatic environment. Bioretention cells reduce loadings of some TrOCs, but they struggle with hydrophilic compounds. Herein, we assessed the potential to enhance TrOC removal via changes in bioretention system design by simulating the fate of seven high-priority stormwater TrOCs (e.g., PFOA, 6PPD-quinone, PAHs) with log KOC values between -1.5 and 6.74 in a bioretention cell. We evaluated eight design and management interventions for three illustrative use cases representing a highway, a residential area, and an airport. We suggest two metrics of performance: mass advected to the sewer network, which poses an acute risk to aquatic ecosystems, and total mass advected from the system, which poses a longer-term risk for persistent compounds. The optimized designs for each use case reduced effluent loadings of all but the most polar compound (PFOA) to <5% of influent mass. Our results suggest that having the largest possible system area allowed bioretention systems to provide benefits during larger events, which improved performance for all compounds. To improve performance for the most hydrophilic TrOCs, an amendment like biochar was necessary; field-scale research is needed to confirm this result. Our results showed that changing the design of bioretention systems can allow them to effectively capture TrOCs with a wide range of physicochemical properties, protecting human health and aquatic species from chemical impacts.

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.

Applicability Domains Based on Molecular Graph Contrastive Learning Enable Graph Attention Network Models to Accurately Predict 15 Environmental End Points

In silico models for predicting physicochemical properties and environmental fate parameters are necessary for the sound management of chemicals. This study employed graph attention network (GAT) algorithms to construct such models on 15 end points. The results showed that the GAT models outperformed the previous state-of-the-art models, and their performance was not influenced by the presence or absence of compounds with certain structures. Molecular similarity density (ρs) was found to be a key metrics characterizing data set modelability, in addition to the proportion of compounds at activity cliffs. By introducing molecular graph (MG) contrastive learning, MG-based ρs and molecular inconsistency in activities (IA) were calculated and employed for characterizing the structure-activity landscape (SAL)-based applicability domain ADSAL{ρs, IA}. The GAT models coupled with ADSAL{ρs, IA} significantly improved the prediction coefficient of determination (R2) on all the end points by an average of 14.4% and enabled all the end points to have R2 > 0.9, which could hardly be achieved previously. The models were employed to screen persistent, mobile, and/or bioaccumulative chemicals from inventories consisting of about 106 chemicals. Given the current state-of-the-art model performance and coverage of the various environmental end points, the constructed models with ADSAL{ρs, IA} may serve as benchmarks for future efforts to improve modeling efficacy.

Molecular Dynamics Simulation Prediction of the Partitioning Constants (KH, Kiw, Kia) of 82 Legacy and Emerging Organic Contaminants at the Water-Air Interface

The tendency of organic contaminants (OCs) to partition between different phases is a key set of properties that underlie their human and ecological health impacts and the success of remediation efforts. A significant challenge associated with these efforts is the need for accurate partitioning data for an ever-expanding list of OCs and breakdown products. All-atom molecular dynamics (MD) simulations have the potential to help generate these data, but existing studies have applied these techniques only to a limited variety of OCs. Here, we use established MD simulation approaches to examine the partitioning of 82 OCs, including many compounds of critical concern, at the water-air interface. Our predictions of the Henry's law constant (K_H) and interfacial adsorption coefficients (K_iw, K_ia) correlate strongly with experimental results, indicating that MD simulations can be used to predict K_H, K_iw, and K_ia values with mean absolute deviations of 1.1, 0.3, and 0.3 logarithmic units after correcting for systematic bias, respectively. A library of MD simulation input files for the examined OCs is provided to facilitate future investigations of the partitioning of these compounds in the presence of other phases.

Emissions and fate of organophosphate esters in outdoor urban environments

Cities are drivers of the global economy, containing products and industries that emit many chemicals. Here, we use the Multimedia Urban Model (MUM) to estimate atmospheric emissions and fate of organophosphate esters (OPEs) from 19 global mega or major cities, finding that they collectively emitted ~81,000 kg yr^-1 of ∑₁₀OPEs in 2018. Typically, polar "mobile" compounds tend to partition to and be advected by water, while non-polar "bioaccumulative" chemicals do not. Depending on the built environment and climate of the city considered, the same compound behaves like either a mobile or a bioaccumulative chemical. Cities with large impervious surface areas, such as Kolkata, mobilize even bioaccumulative contaminants to aquatic ecosystems. By contrast, cities with large areas of vegetation fix and transform contaminants, reducing loadings to aquatic ecosystems. Our results therefore suggest that urban design choices could support policies aimed at reducing chemical releases to the broader environment without increasing exposure for urban residents.

Retrieval, Selection, and Evaluation of Chemical Property Data for Assessments of Chemical Emissions, Fate, Hazard, Exposure, and Risks

Reliable chemical property data are the key to defensible and unbiased assessments of chemical emissions, fate, hazard, exposure, and risks. However, the retrieval, evaluation, and use of reliable chemical property data can often be a formidable challenge for chemical assessors and model users. This comprehensive review provides practical guidance for use of chemical property data in chemical assessments. We assemble available sources for obtaining experimentally derived and in silico predicted property data; we also elaborate strategies for evaluating and curating the obtained property data. We demonstrate that both experimentally derived and in silico predicted property data can be subject to considerable uncertainty and variability. Chemical assessors are encouraged to use property data derived through the harmonization of multiple carefully selected experimental data if a sufficient number of reliable laboratory measurements is available or through the consensus consolidation of predictions from multiple in silico tools if the data pool from laboratory measurements is not adequate.

A holistic modeling framework for estimating the influence of climate change on indoor air quality

The IPCC 2021 report predicts rising global temperatures and more frequent extreme weather events in the future, which will have different effects on the regional climate and concentrations of ambient air pollutants. Consequently, changes in heat and mass transfer between the inside and outside of buildings will also have an increasing impact on indoor air quality. It is therefore surprising that indoor spaces and occupant well-being still play a subordinate role in the studies of climate change. To increase awareness for this topic, the Indoor Air Quality Climate Change (IAQCC) model system was developed, which allows short and long-term predictions of the indoor climate with respect to outdoor conditions. The IAQCC is a holistic model that combines different scenarios in the form of submodels: building physics, indoor emissions, chemical-physical reaction and transformation, mold growth, and indoor exposure. IAQCC allows simulation of indoor gas and particle concentrations with outdoor influences, indoor materials and activity emissions, particle deposition and coagulation, gas reactions, and SVOC partitioning. These key processes are fundamentally linked to temperature and relative humidity. With the aid of the building physics model, the indoor temperature and humidity, and pollutant transport in building zones can be simulated. The exposure model refers to the calculated concentrations and provides evaluations of indoor thermal comfort and exposure to gaseous, particulate, and microbial pollutants.

Stormwater Bioretention Cells Are Not an Effective Treatment for Persistent and Mobile Organic Compounds (PMOCs)

Bioretention cells are a stormwater management technology intended to reduce the quantity of water entering receiving bodies. They are also used to reduce contaminant releases, but their performance is unclear for hydrophilic persistent and mobile organic compounds (PMOCs). We developed a novel eight-compartment one-dimensional (1D) multimedia model of a bioretention cell ("Bioretention Blues") and applied it to a spike and recovery experiment conducted on a system near Toronto, Canada, involving PMOC benzotriazole and four organophosphate esters (OPEs). Compounds with (log D_OC) (organic carbon-water distribution coefficients) < ∼2.7 advected through the system, resulting in infiltration or underdrain flow. Compounds with log D_OC > 3.8 were mostly sorbed to the soil, where subsequent fate depended on transformation. For compounds with 2.7 ≤ log D_OC ≤ 3.8, sorption was sensitive to event size and compound-specific diffusion parameters, with more sorption expected for smaller rain events and for compounds with larger diffusion coefficients. Volatilization losses were minimal for all compounds tested. Direct uptake by vegetation also played a negligible role regardless of the compounds' physicochemical properties. Nonetheless, model simulations showed that vegetation could play a role by increasing transpiration, thereby increasing sorption to the bioretention soil and reducing PMOC release. Model results suggest design modifications to bioretention cells.

Temperature and indoor environments

From the thermodynamic perspective, the term temperature is clearly defined for ideal physical systems: A unique temperature can be assigned to each black body via its radiation spectrum, and the temperature of an ideal gas is given by the velocity distribution of the molecules. While the indoor environment is not an ideal system, fundamental physical and chemical processes, such as diffusion, partitioning equilibria, and chemical reactions, are predictably temperature-dependent. For example, the logarithm of reaction rate and equilibria constants are proportional to the reciprocal of the absolute temperature. It is therefore possible to have non-linear, very steep changes in chemical phenomena over a relatively small temperature range. On the contrary, transport processes are more influenced by spatial temperature, momentum, and pressure gradients as well as by the density, porosity, and composition of indoor materials. Consequently, emergent phenomena, such as emission rates or dynamic air concentrations, can be the result of complex temperature-dependent relationships that require a more empirical approach. Indoor environmental conditions are further influenced by the thermal comfort needs of occupants. Not only do occupants have to create thermal conditions that serve to maintain their core body temperature, which is usually accomplished by wearing appropriate clothing, but also the surroundings must be adapted so that they feel comfortable. This includes the interaction of the living space with the ambient environment, which can vary greatly by region and season. Design of houses, apartments, commercial buildings, and schools is generally utility and comfort driven, requiring an appropriate energy balance, sometimes considering ventilation but rarely including the impact of temperature on indoor contaminant levels. In our article, we start with a review of fundamental thermodynamic variables and discuss their influence on typical indoor processes. Then, we describe the heat balance of people in their thermal environment. An extensive literature study is devoted to the thermal conditions in buildings, the temperature-dependent release of indoor pollutants from materials and their distribution in the various interior compartments as well as aspects of indoor chemistry. Finally, we assess the need to consider temperature holistically with regard to the changes to be expected as a result of global emergencies such as climate change.

Quantum Chemical Calculation and Evaluation of Partition Coefficients for Classical and Emerging Environmentally Relevant Organic Compounds

Octanol/water (K_OW), octanol/air (K_OA), and hexadecane/air (K_HdA) partition coefficients are calculated for 67 organic compounds of environmental concern using computational chemistry. The extended CRENSO workflow applied here includes the calculation of extensive conformer ensembles with semiempirical methods and refinement through density functional theory, taking into account solvation models, especially COSMO-RS, and thermostatistical contributions. This approach is particularly advantageous for describing large and nonrigid molecules. With regard to K_OW and K_HdA, one can refer to many experimental data from direct and indirect measurement methods, and very good matches with results from our quantum chemical workflow are evident. In the case of the K_OA values, however, good matches are only obtained for the experimentally determined values. Larger systematic deviations between data computed here and available, nonexperimental quantitative structure-activity relationship literature data occur in particular for phthalic acid esters and organophosphate esters. From a critical analysis of the coefficients calculated in this work and comparison with available literature data, we conclude that the presented quantum chemical composite approach is the most powerful so far for calculating reliable partition coefficients because all physical contributions to the conformational free energy are considered and the structure ensembles for the two phases are generated independently and consistently.

Emerging investigator series: the role of chemical properties in human exposure to environmental chemicals

One of the ultimate goals of environmental exposure science is to mechanistically understand how chemical properties and human behavior interactively determine human exposure to the wide spectrum of chemicals present in the environment. This comprehensive review assembles state-of-the-art knowledge of the role of partitioning, dissociation, mass transfer, and reactive properties in human contact with and absorption of organic chemicals via oral, dermal, and respiratory routes. Existing studies have revealed that chemicals with different properties vary greatly in mass distribution and occurrence among multiple exposure media, resulting in distinct patterns of human intake from the environment. On the other hand, these chemicals encounter different levels of resistance in the passage of intestinal, dermal, and pulmonary absorption barriers and demonstrate different levels of bioavailability, due to the selectivity of biochemical, anatomical and physiological structures of these absorption barriers. Moving forward, the research community needs to gain more in-depth mechanistic insights into the complex processes in human exposure, advance the technique to better characterize and predict chemical properties, generate and leverage experimental data for a more diverse range of chemicals, and describe better the interactions between chemical properties and human behavior.