Earth Systems to Anthropocene Systems: An Evolutionary, System-of-Systems, Convergence Paradigm for Interdependent Societal Challenges.

Humans have made profound changes to the Earth. The resulting societal challenges of the Anthropocene (e.g., climate change and impacts, renewable energy, adaptive infrastructure, disasters, pandemics, food insecurity, and biodiversity loss) are complex and systemic, with causes, interactions, and consequences that cascade across a globally connected system of systems. In this Critical Review, we turn to our "origin story" for insight, briefly tracing the formation of the Universe and the Earth, the emergence of life, the evolution of multicellular organisms, mammals, primates, and humans, as well as the more recent societal transitions involving agriculture, urbanization, industrialization, and computerization. Focusing on the evolution of the Earth, genetic evolution, the evolution of the brain, and cultural evolution, which includes technological evolution, we identify a nested evolutionary sequence of geophysical, biophysical, sociocultural, and sociotechnical systems, emphasizing the causal mechanisms that first formed, and then transformed, Earth systems into Anthropocene systems. Describing how the Anthropocene systems coevolved, and briefly illustrating how the ensuing societal challenges became tightly integrated across multiple spatial, temporal, and organizational scales, we conclude by proposing an evolutionary, system-of-systems, convergence paradigm for the entire family of interdependent societal challenges of the Anthropocene.

A rapid micro chamber method to measure SVOC emission and transport model parameters.

Assessing exposure to semivolatile organic compounds (SVOCs) that are emitted from consumer products and building materials in indoor environments is critical for reducing the associated health risks. Many modeling approaches have been developed for SVOC exposure assessment indoors, including the DustEx webtool. However, the applicability of these tools depends on the availability of model parameters such as the gas-phase concentration at equilibrium with the source material surface, y0, and the surface-air partition coefficient, Ks, both of which are typically determined in chamber experiments. In this study, we compared two types of chamber design, a macro chamber, which downscaled the dimensions of a room to a smaller size with roughly the same surface-to-volume ratio, and a micro chamber, which minimized the sink-to-source surface area ratio to shorten the time required to reach steady state. The results show that the two chambers with different sink-to-source surface area ratios yield comparable steady-state gas- and surface-phase concentrations for a range of plasticizers, while the micro chamber required significantly shorter times to reach steady state. Using y0 and Ks measured with the micro chamber, we conducted indoor exposure assessments for di-n-butyl phthalate (DnBP), di(2-ethylhexyl) phthalate (DEHP) and di(2-ethylhexyl) terephthalate (DEHT) with the updated DustEx webtool. The predicted concentration profiles correspond well with existing measurements and demonstrate the direct applicability of chamber data in exposure assessments.

Biosynthesis of 2-methylisoborneol is regulated by chromatic acclimation of Pseudanabaena.

Cyanobacteria can sense different light color by adjusting the components of photosynthetic pigments including chlorophyll a (Chl a), phycoerythrin (PE), and phycocyanin (PC), etc. Filamentous cyanobacteria are the main producer of 2-methylisoborneol (MIB) and many can increase their PE levels so that they are more competitive in subsurface layer where green light is more abundant, and have caused extensive odor problems in drinking water reservoirs. Here, we identified the potential correlation between MIB biosynthesis and ambient light color induced chromatic acclimation (CA) of a MIB-producing Pseudanabaena strain. The results suggest Pseudanabaena regulates the pigment proportion through Type III CA (CA3), by increasing PE abundance and decreasing PC in green light. The biosynthesis of MIB and Chl a share the common precursor, and are positively correlated with statistical significance regardless of light color (R2=0.68; p<0.001). Besides, the PE abundance is also positively correlated with Chl a in green light (R2=0.57; p=0.019) since PE is the antenna that can only transfer the energy to PC and Chl a. In addition, significantly higher MIB production was observed in green light since more Chl a was synthesized.

Modeling Primary Emissions of Chemicals from Liquid Products Applied on Indoor Surfaces.

Liquid products applied on material surfaces and human skin, including many household cleaning products and personal care products, can lead to intermittent emissions of chemicals and peak concentrations in indoor air. The existing case-based models do not allow inter-comparison of different use scenarios and emission mechanisms. In this context, the present work developed a mechanistic model based on mass transfer theories, which allowed emissions into the air from the liquid product to be characterized. It also allowed for diffusion into the applied surface during product use and re-emission from the applied surface after the depletion of the liquid product. The model was validated using literature data on chemical emissions following floor cleaning and personal care product use. A sensitivity analysis of the model was then conducted. The percentage of the chemical mass emitted from the liquid to the air varied from 45% (applied on porous material) to 99% (applied on human skin), and the rest was absorbed into the applied material/skin. The peak gas-phase concentration, the time to reach the peak concentration, and the percentage of the liquid-to-air emission depended significantly on the chemical's octanol/gas and material/gas partition coefficients and the diffusion coefficient of the chemical in the applied material/skin.

A modular mechanistic framework for estimating exposure to SVOCs: Next steps for modeling emission and partitioning of plasticizers and PFAS.

Estimates of human exposure to semi-volatile organic compounds (SVOCs) such as phthalates, phthalate alternatives, and some per- and polyfluoroalkyl substances (PFAS) are required for the risk-based evaluation of chemicals. Recently, a modular mechanistic modeling framework to rapidly predict SVOC emission and partitioning in indoor environments has been presented, in which several mechanistically consistent source emission categories (SECs) were identified. However, not all SECs have well-developed emission models. In addition, data on model parameters are missing even for frequently studied SVOCs. These knowledge gaps impede the comprehensive prediction of the fate of SVOCs indoors. In this paper, sets of high-priority phthalates, phthalate alternatives, and PFAS were identified based on chemical occurrence indoors and additional selection criteria. These high-priority chemicals served as the basis for exploring model parameter availability for existing indoor SVOC emission and partitioning models. The results reveal that additional experimental and modeling work is needed to fully understand the behavior of SVOCs indoors and to predict exposures with greater confidence and lower uncertainty. Modeling approaches to fill some of the identified gaps are proposed. The prioritized sets of chemicals and proposed new modeling approaches will help guide future research. The inclusion of polar phases in the framework will further expand its applicability and scope. IMPACT STATEMENT: This paper compiles data on high-priority chemicals commonly found indoors and information on the availability of applicable models and model parameters to predict emission, partitioning, and subsequent exposure to these chemicals. Modeling approaches for a selection of the missing SECs (source emission categories) are proposed, to illustrate the path forward. The comprehensive data set helps inform researchers, exposure assessors, and policy makers to better understand the state of the science regarding modeling of indoor exposure to semi-volatile organic compounds (SVOCs) and per- and polyfluoroalkyl substances (PFAS).

Demonstrating a systems approach for integrating disparate data streams to inform decisions on children's environmental health.

BACKGROUND: The use of systems science methodologies to understand complex environmental and human health relationships is increasing. Requirements for advanced datasets, models, and expertise limit current application of these approaches by many environmental and public health practitioners. METHODS: A conceptual system-of-systems model was applied for children in North Carolina counties that includes example indicators of children's physical environment (home age, Brownfield sites, Superfund sites), social environment (caregiver's income, education, insurance), and health (low birthweight, asthma, blood lead levels). The web-based Toxicological Prioritization Index (ToxPi) tool was used to normalize the data, rank the resulting vulnerability index, and visualize impacts from each indicator in a county. Hierarchical clustering was used to sort the 100 North Carolina counties into groups based on similar ToxPi model results. The ToxPi charts for each county were also superimposed over a map of percentage county population under age 5 to visualize spatial distribution of vulnerability clusters across the state. RESULTS: Data driven clustering for this systems model suggests 5 groups of counties. One group includes 6 counties with the highest vulnerability scores showing strong influences from all three categories of indicators (social environment, physical environment, and health). A second group contains 15 counties with high vulnerability scores driven by strong influences from home age in the physical environment and poverty in the social environment. A third group is driven by data on Superfund sites in the physical environment. CONCLUSIONS: This analysis demonstrated how systems science principles can be used to synthesize holistic insights for decision making using publicly available data and computational tools, focusing on a children's environmental health example. Where more traditional reductionist approaches can elucidate individual relationships between environmental variables and health, the study of collective, system-wide interactions can enable insights into the factors that contribute to regional vulnerabilities and interventions that better address complex real-world conditions.

Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool.

STOFFENMANAGER® and the Advanced REACH Tool (ART) are recommended tools by the European Chemical Agency for regulatory chemical safety assessment. The models are widely used and accepted within the scientific community. STOFFENMANAGER® alone has more than 37 000 users globally and more than 310 000 risk assessment have been carried out by 2020. Regardless of their widespread use, this is the first study evaluating the theoretical backgrounds of each model. STOFFENMANAGER® and ART are based on a modified multiplicative model where an exposure base level (mg m-3) is replaced with a dimensionless intrinsic emission score and the exposure modifying factors are replaced with multipliers that are mainly based on subjective categories that are selected by using exposure taxonomy. The intrinsic emission is a unit of concentration to the substance emission potential that represents the concentration generated in a standardized task without local ventilation. Further information or scientific justification for this selection is not provided. The multipliers have mainly discrete values given in natural logarithm steps (…, 0.3, 1, 3, …) that are allocated by expert judgements. The multipliers scientific reasoning or link to physical quantities is not reported. The models calculate a subjective exposure score, which is then translated to an exposure level (mg m-3) by using a calibration factor. The calibration factor is assigned by comparing the measured personal exposure levels with the exposure score that is calculated for the respective exposure scenarios. A mixed effect regression model was used to calculate correlation factors for four exposure group [e.g. dusts, vapors, mists (low-volatiles), and solid object/abrasion] by using ~1000 measurements for STOFFENMANAGER® and 3000 measurements for ART. The measurement data for calibration are collected from different exposure groups. For example, for dusts the calibration data were pooled from exposure measurements sampled from pharmacies, bakeries, construction industry, and so on, which violates the empirical model basic principles. The calibration databases are not publicly available and thus their quality or subjective selections cannot be evaluated. STOFFENMANAGER® and ART can be classified as subjective categorization tools providing qualitative values as their outputs. By definition, STOFFENMANAGER® and ART cannot be classified as mechanistic models or empirical models. This modeling algorithm does not reflect the physical concept originally presented for the STOFFENMANAGER® and ART. A literature review showed that the models have been validated only at the 'operational analysis' level that describes the model usability. This review revealed that the accuracy of STOFFENMANAGER® is in the range of 100 000 and for ART 100. Calibration and validation studies have shown that typical log-transformed predicted exposure concentration and measured exposure levels often exhibit weak Pearson's correlations (r is <0.6) for both STOFFENMANAGER® and ART. Based on these limitations and performance departure from regulatory criteria for risk assessment models, it is recommended that STOFFENMANAGER® and ART regulatory acceptance for chemical safety decision making should be explicitly qualified as to their current deficiencies.

An integrated exposure and pharmacokinetic modeling framework for assessing population-scale risks of phthalates and their substitutes.

To effectively incorporate in vitro-in silico-based methods into the regulation of consumer product safety, a quantitative connection between product phthalate concentrations and in vitro bioactivity data must be established for the general population. We developed, evaluated, and demonstrated a modeling framework that integrates exposure and pharmacokinetic models to convert product phthalate concentrations into population-scale risks for phthalates and their substitutes. A probabilistic exposure model was developed to generate the distribution of multi-route exposures based on product phthalate concentrations, chemical properties, and human activities. Pharmacokinetic models were developed to simulate population toxicokinetics using Bayesian analysis via the Markov chain Monte Carlo method. Both exposure and pharmacokinetic models demonstrated good predictive capability when compared with worldwide studies. The distributions of exposures and pharmacokinetics were integrated to predict the population distributions of internal dosimetry. The predicted distributions showed reasonable agreement with the U.S. biomonitoring surveys of urinary metabolites. The "source-to-outcome" local sensitivity analysis revealed that food contact materials had the greatest impact on body burden for di(2-ethylhexyl) adipate (DEHA), di-2-ethylhexyl phthalate (DEHP), di(isononyl) cyclohexane-1,2-dicarboxylate (DINCH), and di(2-propylheptyl) phthalate (DPHP), whereas the body burden of diethyl phthalate (DEP) was most sensitive to the concentration in personal care products. The upper bounds of predicted plasma concentrations showed no overlap with ToxCast in vitro bioactivity values. Compared with the in vitro-to-in vivo extrapolation (IVIVE) approach, the integrated modeling framework has significant advantages in mapping product phthalate concentrations to multi-route risks, and thus is of great significance for regulatory use with a relatively low input requirement. Further integration with new approach methodologies will facilitate these in vitro-in silico-based risk assessments for a broad range of products containing an equally broad range of chemicals.

Kinetic multi-layer model of film formation, growth, and chemistry (KM-FILM): Boundary layer processes, multi-layer adsorption, bulk diffusion, and heterogeneous reactions.

Large surface area-to-volume ratios indoors cause heterogeneous interactions to be especially important. Semi-volatile organic compounds can deposit on impermeable indoor surfaces forming thin organic films. We developed a new model to simulate the initial film formation by treating gas-phase diffusion and turbulence through a surface boundary layer and multi-layer reversible adsorption on rough surfaces, as well as subsequent film growth by resolving bulk diffusion and chemical reactions in a film. The model was applied with consistent parameters to reproduce twenty-one sets of film formation measurements due to multi-layer adsorption of multiple phthalates onto different indoor-relevant surfaces, showing that the films should initially be patchy with the formation of pyramid-like structures on the surface. Sensitivity tests showed that highly turbulent conditions can lead to the film growing by more than a factor of two compared to low turbulence conditions. If surface films adopt an ultra-viscous state with bulk diffusion coefficients of less than 10-18  cm2 s-1 , a significant decrease in film growth is expected. The presence of chemical reactions in the film has the potential to increase the rate of film growth by nearly a factor of two.

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.

Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach.

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socio-environmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socio-environmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems.

Children's Environmental Health: A Systems Approach for Anticipating Impacts from Chemicals.

Increasing numbers of chemicals are on the market and present in consumer products. Emerging evidence on the relationship between environmental contributions and prevalent diseases suggests associations between early-life exposure to manufactured chemicals and a wide range of children's health outcomes. Using current assessment methodologies, public health and chemical management decisionmakers face challenges in evaluating and anticipating the potential impacts of exposure to chemicals on children's health in the broader context of their physical (built and natural) and social environments. Here, we consider a systems approach to address the complexity of children's environmental health and the role of exposure to chemicals during early life, in the context of nonchemical stressors, on health outcomes. By advancing the tools for integrating this more complex information, the scope of considerations that support chemical management decisions can be extended to include holistic impacts on children's health.

A framework to model exposure to per- and polyfluoroalkyl substances in indoor environments.

Per- and polyfluoroalkyl substances (PFAS) include a wide range of halogenated chemicals, which have been used as water- and stain-resistant coatings for consumer products and industrial purposes. PFAS are persistent in the environment and several are bioaccumulative, and thus relevant for human and environmental health. Given their pervasiveness, we need to understand how we are exposed to PFAS, especially in indoor environments where many people spend most of their time. Research on indoor exposure to semivolatile organic compounds (SVOCs) has progressed rapidly in recent years. Because many PFAS can be considered SVOCs, much of what has been learned about SVOCs may be used to guide research on PFAS exposure in indoor environments. Here, we briefly review what has been done to assess indoor exposure to PFAS. Then, we propose a systematic indoor exposure framework for PFAS based on methods to estimate exposure to SVOCs. We illustrate how critical parameters such as partition coefficients for different media (particles, dust, surfaces, and clothing) for different types of PFAS could be measured, how these measurements can be used in exposure models for PFAS, and how fundamental, predictive relationships might be used to estimate necessary parameters for emerging compounds.

Improved Modeling of Sediment Oxygen Kinetics and Fluxes in Lakes and Reservoirs.

To understand water quality degradation during hypoxia, we need to understand sediment oxygen fluxes, the main oxygen sink in shallow hypolimnia. Kinetic models, which integrate diffusion and consumption of dissolved oxygen (DO) in sediments, usually assume a downward flux of DO from the sediment-water interface (SWI) with a zero-flux condition at the lower boundary of the oxic sediment layer. In this paper, we separately account for the oxidation of an upward flux of reduced compounds by introducing a negative flux of DO as a lower boundary condition. Using in situ measurements in two lakes, kinetic models were fit to DO microprofiles using zero-order and first-order kinetics with both zero and non-zero lower boundary conditions. Based on visual inspection and goodness-of-fit criteria, the negative-flux lower boundary condition, -0.25 g O2 m-2 d-1, was found to more accurately describe DO consumption kinetics. Fitted zero-order rate constants ranged from 50 to 510 mg L-1 d-1, and first-order rate constants ranged from 60 to 400 d-1, which agree well with prior laboratory studies. DO fluxes at the SWI calculated from the simulated profiles with the negative-flux lower boundary condition also showed better agreement with the observed DO fluxes than the simulated profiles with the zero-flux lower boundary condition.

Assessing Human Exposure to Chemicals in Materials, Products and Articles: The International Risk Management Landscape for Phthalates.

Risk-based chemical safety assessments are increasingly being conducted to support chemical management decisions and informed substitution to protect public health. Rapid evaluation and prioritization of large numbers of chemicals used in materials, products, and other indoor articles has become a major focus of chemical risk management strategies. Internationally, although a shared understanding of the value of rapid risk-based evaluations appears to be emerging, implementation strategies and associated management decisions vary from one agency and jurisdiction to another. This paper highlights the international chemical risk management landscape focusing on phthalates as an example, and reviews how phthalate exposure assessments have been performed, resulting at times in different decisions based on the application of scientific information within different policy contexts. In general, the need for efficient and effective risk-based assessment approaches is driving increased needs for high-quality exposure data and validated, mechanistic exposure models. Further development of mechanistic models and related parameters will reduce uncertainties in exposure estimates and support scientific risk-based evaluations of chemical/product combinations for a variety of decisions.

Machine learning and statistical models for predicting indoor air quality.

Indoor air quality (IAQ), as determined by the concentrations of indoor air pollutants, can be predicted using either physically based mechanistic models or statistical models that are driven by measured data. In comparison with mechanistic models mostly used in unoccupied or scenario-based environments, statistical models have great potential to explore IAQ captured in large measurement campaigns or in real occupied environments. The present study carried out the first literature review of the use of statistical models to predict IAQ. The most commonly used statistical modeling methods were reviewed and their strengths and weaknesses discussed. Thirty-seven publications, in which statistical models were applied to predict IAQ, were identified. These studies were all published in the past decade, indicating the emergence of the awareness and application of machine learning and statistical modeling in the field of IAQ. The concentrations of indoor particulate matter (PM2.5 and PM10 ) were the most frequently studied parameters, followed by carbon dioxide and radon. The most popular statistical models applied to IAQ were artificial neural networks, multiple linear regression, partial least squares, and decision trees.

Total surface area in indoor environments.

Certain processes in indoor air, such as deposition, partitioning, and heterogeneous reactions, involve interactions with surfaces. We have characterized the surface area, volume, shape, and material of objects in 10 bedrooms, nine kitchens, and three offices. The resolution of the measurements was ∼1 cm. The ratio of surface area with contents to that without contents did not vary by type of room and averaged 1.5 ± 0.3 (mean ± standard deviation) across all rooms. The ratio of the volume minus contents to nominal volume averaged 0.9 ± 0.1 and was lower for kitchens compared to bedrooms and offices. Ignoring contents, the surface-area-to-volume ratio was 1.8 ± 0.3 m-1; accounting for contents, the ratio was 3.2 ± 1.2 m-1, or 78% higher. These two ratios did not vary by type of room and were similar to those measured for 33 rooms in another study. Due to substantial differences in the design and contents of kitchens, their ratios had the highest variability among the three room types. The most common shape of surfaces was flat rectangular, while each room also had many irregularly-shaped objects. Paint-covered surfaces and stained wood were the two most common materials in each room, accounting for an average of 42% and 22% of total surface area, respectively, although the distribution of materials varied by room type. These findings have important implications for understanding the chemistry of indoor environments, as the available surface area for deposition, partitioning, and reactions is higher and more complex than assumed in simple models.

Modeling the formation and growth of organic films on indoor surfaces.

Emission, transport, and fate of semi-volatile organic compounds (SVOCs), which include plasticizers, flame retardants, pesticides, biocides, and oxidation products of volatile organic compounds, are influenced in part by their tendency to sorb to indoor surfaces. A thin organic film enhances this effect, because it acts as both an SVOC sink and a source, thus potentially prolonging human exposure. Unfortunately, our ability to describe the initial formation and subsequent growth of organic films on indoor surfaces is limited. To overcome this gap, we propose a mass transfer model accounting for adsorption, condensation, and absorption of multiple gas-phase SVOCs on impervious, vertical indoor surfaces. Further model development and experimental research are needed including more realistic scenarios accounting for surface heterogeneity, non-ideal organic mixtures, and particle deposition.

Particle/Gas Partitioning of Phthalates to Organic and Inorganic Airborne Particles in the Indoor Environment.

The particle/gas partition coefficient Kp is an important parameter affecting the fate and transport of indoor semivolatile organic compounds (SVOCs) and resulting human exposure. Unfortunately, experimental measurements of Kp exist almost exclusively for atmospheric polycyclic aromatic hydrocarbons, with very few studies focusing on SVOCs that occur in indoor environments. A specially designed tube chamber operating in the laminar flow regime was developed to measure Kp of the plasticizer di-2-ethylhexyl phthalate (DEHP) for one inorganic (ammonium sulfate) and two organic (oleic acid and squalane) particles. The values of Kp for the organic particles (0.23 ± 0.13 m3/µg for oleic acid and 0.11 ± 0.10 m3/µg for squalane) are an order of magnitude higher than those for the inorganic particles (0.011 ± 0.004 m3/µg), suggesting that the process by which the particles accumulate SVOCs is different. A mechanistic model based on the experimental design reveals that the presence of the particles increases the gas-phase concentration gradient in the boundary layer, resulting in enhanced mass transfer from the emission source into the air. This novel approach provides new insight into experimental designs for rapid Kp measurement and a sound basis for investigating particle-mediated mass transfer of SVOCs.

Equilibrium Relationship between SVOCs in PVC Products and the Air in Contact with the Product.

Phthalates and phthalate alternatives are semivolatile organic compounds (SVOCs) present in many PVC products as plasticizers to enhance product performance. Knowledge of the mass-transfer parameters, including the equilibrium concentration in the air in contact with the product surface ( y0), will greatly improve the ability to estimate the emission rate of SVOCs from these products and to assess human exposure. The objective of this study was to measure y0 for different PVC products and to evaluate its relationship with the material-phase concentrations ( C0). Also, C0 and y0 data from other sources were included, resulting in a substantially larger data set ( Ntotal = 34, T = 25 °C) than found in previous studies. The results show that the material/gas equilibrium relationship does not follow Raoult's law and that therefore the assumption of an ideal solution is invalid. Instead, Henry's law applies, and the Henry's law constant for all target SVOCs consists of the respective pure liquid vapor pressure and an activity coefficient γ, which accounts for the nonideal nature of the solution. For individual SVOCs, a simple partitioning relationship exists, but Henry's law is more generally applicable and will be of greater value in rapid exposure assessment procedures.