Occurrence of Single- and Double-Peaked Emission Profiles of Synthetic Chemicals

This work aims to elucidate the circumstances that can lead to two peaks in the temporal emission profile of synthetic chemicals. Using a simplified substance flow model, we explore how emission factors, product lifespan, and degradation half-life in waste stock influence the (i) relative importance of emissions from three lifecycle stages (industrial processes, use phase, and waste disposal), and (ii) the resulting composite emission profile. A double-peaked emission profile occurs if the lifespan of products containing the chemical is longer than its production history, and the gross emission factor from waste disposal exceeds that from the use phase. Since most chemicals fail to meet these two conditions, it is reasonable to use single-peaked emission profile as the default in environmental studies. On the basis of their emission profiles and contributions from individual lifecycle stages, we can categorize chemicals into “simple single-peakers”, “composite single-peakers”, and “double-peakers”. Our simplified model derived emission profiles for five real chemicals that agree well with earlier, more sophisticated calculations, indicating the model’s ability to capture the essential features of actual emissions. It is hoped that the model and conclusions in this work will benefit both environmental modelers and decision makers

Model for Screening-Level Assessment of Near-Field Human Exposure to Neutral Organic Chemicals Released Indoors

Screening organic chemicals for hazard and risk to human health requires near-field human exposure models that can be readily parametrized with available data. The integration of a model of human exposure, uptake, and bioaccumulation into an indoor mass balance model provides a quantitative framework linking emissions in indoor environments with human intake rates (<i>iR</i>s), intake fractions (<i>iF</i>s) and steady-state concentrations in humans (<i>C</i>) through consideration of dermal permeation, inhalation, and nondietary ingestion exposure pathways. Parameterized based on representative indoor and adult human characteristics, the model is applied here to 40 chemicals of relevance in the context of human exposure assessment. Intake fractions and human concentrations (<i>C</i>_U) calculated with the model based on a unit emission rate to air for these 40 chemicals span 2 and 5 orders of magnitude, respectively. Differences in priority ranking based on either <i>iF</i> or <i>C</i>_U can be attributed to the absorption, biotransformation and elimination processes within the human body. The model is further applied to a large data set of hypothetical chemicals representative of many in-use chemicals to show how the dominant exposure pathways, <i>iF</i> and <i>C</i>_U change as a function of chemical properties and to illustrate the capacity of the model for high-throughput screening. These simulations provide hypotheses for the combination of chemical properties that may result in high exposure and internal dose. The model is further exploited to highlight the role human contaminant uptake plays in the overall fate of certain chemicals indoors and consequently human exposure

Effect of Sodium Sulfate, Ammonium Chloride, Ammonium Nitrate, and Salt Mixtures on Aqueous Phase Partitioning of Organic Compounds

Dissolved inorganic salts influence the partitioning of organic compounds into the aqueous phase. This influence is especially significant in atmospheric aerosol, which usually contains large amounts of ions, including sodium, ammonium, chloride, sulfate, and nitrate. However, empirical data on this salt effect are very sparse. Here, the partitioning of numerous organic compounds into solutions of Na₂SO₄, NH₄Cl, and NH₄NO₃ was measured and compared with existing data for NaCl and (NH₄)₂SO₄. Salt mixtures were also tested to establish whether the salt effect is additive. In general, the salt effect showed a decreasing trend of Na₂SO₄ > (NH)₂SO₄ > NaCl > NH₄Cl > NH₄NO₃ for the studied organic compounds, implying the following relative strength of the salt effect of individual anions: SO₄^2– > Cl^– > NO₃^– and of cations: Na⁺ > NH₄⁺. The salt effect of different salts is moderately correlated. Predictive models for the salt effect were developed based on the experimental data. The experimental data indicate that the salt effect of mixtures may not be entirely additive. However, the deviation from additivity, if it exists, is small. Data of very high quality are required to establish whether the effect of constituent ions or salts is additive or not

Estimating Screening-Level Organic Chemical Half-Lives in Humans

Relatively few measured data are available for the thousands of chemicals requiring hazard and risk assessment. The whole body, total elimination half-life (<i>HL</i>_T) and the whole body, primary biotransformation half-life (<i>HL</i>_B) are key parameters determining the extent of bioaccumulation, biological concentration, and risk from chemical exposure. A one-compartment pharmacokinetic (1-CoPK) mass balance model was developed to estimate organic chemical <i>HL</i>_B from measured <i>HL</i>_T data in mammals. Approximately 1900 <i>HL</i>s for human adults were collected and reviewed and the 1-CoPK model was parametrized for an adult human to calculate <i>HL</i>_B from <i>HL</i>_T. Measured renal clearance and whole body total clearance data for 306 chemicals were used to calculate empirical <i>HL</i>_B,emp. The <i>HL</i>_B,emp values and other measured data were used to corroborate the 1-CoPK <i>HL</i>_B model calculations. <i>HL</i>s span approximately 7.5 orders of magnitude from 0.05 h for nitroglycerin to 2 × 10⁶ h for 2,3,4,5,2′,3′,5′,6′-octachlorobiphenyl with a median of 7.6 h. The automated Iterative Fragment Selection (IFS) method was applied to develop and evaluate various quantitative structure–activity relationships (QSARs) to predict <i>HL</i>_T and <i>HL</i>_B from chemical structure and two novel QSARs are detailed. The <i>HL</i>_T and <i>HL</i>_B QSARs show similar statistical performance; that is, <i>r</i>² = 0.89, <i>r</i>^2‑ext = 0.72 and 0.73 for training and external validation sets, respectively, and root-mean-square errors for the validation data sets are 0.70 and 0.75, respectively

Application of Mass Balance Models and the Chemical Activity Concept To Facilitate the Use of in Vitro Toxicity Data for Risk Assessment

Practical, financial, and ethical considerations related to conducting extensive animal testing have resulted in various initiatives to promote and expand the use of in vitro testing data for chemical evaluations. Nominal concentrations in the aqueous phase corresponding to an effect (or biological activity) are commonly reported and used to characterize toxicity (or biological response). However, the true concentration in the aqueous phase can be substantially different from the nominal. To support in vitro test design and aid the interpretation of in vitro toxicity data, we developed a mass balance model that can be parametrized and applied to represent typical in vitro test systems. The model calculates the mass distribution, freely dissolved concentrations, and cell/tissue concentrations corresponding to the initial nominal concentration and experimental conditions specified by the user. Chemical activity, a metric which can be used to assess the potential for baseline toxicity to occur, is also calculated. The model is first applied to a set of hypothetical chemicals to illustrate the degree to which test conditions (e.g., presence or absence of serum) influence the distribution of the chemical in the test system. The model is then applied to set of 1194 real substances (predominantly from the ToxCast chemical database) to calculate the potential range of concentrations and chemical activities under assumed test conditions. The model demonstrates how both concentrations and chemical activities can vary by orders of magnitude for the same nominal concentration

Revisiting the Contributions of Far- and Near-Field Routes to Aggregate Human Exposure to Polychlorinated Biphenyls (PCBs)

The general population is exposed to polychlorinated biphenyls (PCBs) by consuming food from far-field contaminated agricultural and aquatic environments, and inhalation and nondietary ingestion in near-field indoor or residential environments. Here, we seek to evaluate the relative importance of far- and near-field routes by simulating the time-variant aggregate exposure of Swedish females to PCB congeners from 1930 to 2030. We rely on a mechanistic model, which integrates a food-chain bioaccumulation module and a human toxicokinetic module with dynamic substance flow analysis and nested indoor-urban-rural environmental fate modeling. Confidence in the model is established by successfully reproducing the observed PCB concentrations in Swedish human milk between 1972 and 2016. In general, far-field routes contribute most to total PCB uptake. However, near-field exposure is notable for (i) children and teenagers, who have frequent hand-to-mouth contact, (ii) cohorts born in earlier years, e.g., in 1956, when indoor environments were severely contaminated, and (iii) lighter chlorinated congeners. The relative importance of far- and near-field exposure in a cross-section of individuals of different age sampled at the same time is shown to depend on the time of sampling. The transition from the dominance of near- to far-field exposure that has happened for PCBs may also occur for other chemicals used indoors

Modeling the Uptake of Neutral Organic Chemicals on XAD Passive Air Samplers under Variable Temperatures, External Wind Speeds and Ambient Air Concentrations (PAS-SIM)

The main objective of this study was to evaluate the performance and demonstrate the utility of a fugacity-based model of XAD passive air samplers (XAD-PAS) designed to simulate the uptake of neutral organic chemicals under variable temperatures, external wind speeds and ambient air concentrations. The model (PAS-SIM) simulates the transport of the chemical across the air-side boundary layer and within the sampler medium, which is segmented into a user-defined number of thin layers. Model performance was evaluated using data for polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) from a field calibration study (i.e., active and XAD-PAS data) conducted in Egbert, Ontario, Canada. With some exceptions, modeled PAS uptake curves are in good agreement with the empirical PAS data. The results are highly encouraging, given the uncertainty in the active air sampler data used as input and other uncertainties related to model parametrization (e.g., sampler–air partition coefficients, the influence of wind speed on sampling rates). The study supports the further development and evaluation of the PAS-SIM model as a diagnostic (e.g., to aid interpretation of calibration studies and monitoring data) and prognostic (e.g., to inform design of future passive air sampling campaigns) tool

Field Calibration of XAD-Based Passive Air Sampler on the Tibetan Plateau: Wind Influence and Configuration Improvement

The passive air sampler based on XAD-2 resin (XAD-PAS) has proven useful for collecting atmospheric persistent organic pollutants (POPs) in remote regions. Whereas laboratory studies have shown that, due to the open bottom of its housing, the passive sampling rate (PSR) of the XAD-PAS is susceptible to wind and other processes causing air turbulence, the sampler has not been calibrated in the field at sites experiencing high winds. In this study, the PSRs of the XAD-PAS were calibrated at three sites on the Tibetan Plateau, covering a wide range in temperature (<i>T</i>), pressure (<i>P</i>) and wind speed (<i>v</i>). At sites with low wind speeds (i.e., in a forest and an urban site), the PSRs are proportional to the ratio <i>T</i>^1.75/ <i>P</i>; at windy sites with an average wind speed above 3 m/s, the influence of <i>v</i> on PSRs cannot be ignored. Moreover, the open bottom of the XAD-PAS housing causes the PSRs to be influenced by wind angle and air turbulence caused by sloped terrain. Field calibration, wind speed measurements, and computational fluid dynamics (CFD) simulations indicate that a modified design incorporating an air spoiler consisting of 4 metal sheets dampens the turbulence caused by wind angle and sloped terrain and caps the PSR at ∼5 m³/day, irrespective of ambient wind. Therefore, the original XAD-PAS with an open bottom is suitable for deployment in urban areas and other less windy places, the modified design is preferable in mountain regions and other places where air circulation is complicated and strong

Measuring and Modeling the Salting-out Effect in Ammonium Sulfate Solutions

The presence of inorganic salts significantly influences the partitioning behavior of organic compounds between environmentally relevant aqueous phases, such as seawater or aqueous aerosol, and other, nonaqueous phases (gas phase, organic phase, etc.). In this study, salting-out coefficients (or Setschenow constants) (<i>K</i>_<i>S</i> [M^–1]) for 38 diverse neutral compounds in ammonium sulfate ((NH₄)₂SO₄) solutions were measured using a shared headspace passive dosing method and a negligible depletion solid phase microextraction technique. The measured <i>K</i>_<i>S</i> were all positive, varied from 0.216 to 0.729, and had standard errors in the range of 0.006–0.060. Compared to <i>K</i>_<i>S</i> for sodium chloride (NaCl) in the literature, <i>K</i>_<i>S</i> values for (NH₄)₂SO₄ are always higher for the same compound, suggesting a higher salting-out effect of (NH₄)₂SO₄. A polyparameter linear free energy relationship (pp-LFER) for predicting <i>K</i>_<i>S</i> in (NH₄)₂SO₄ solutions was generated using the experimental data for calibration. pp-LFER predicted <i>K</i>_<i>S</i> agreed well with measured <i>K</i>_<i>S</i> reported in the literature. <i>K</i>_<i>S</i> for (NH₄)₂SO₄ was also predicted using the quantum-chemical COSMO<i>therm</i> software and the thermodynamic model AIOMFAC. While COSMO<i>therm</i> generally overpredicted the experimental <i>K</i>_<i>S</i>, predicted and experimental values were correlated. Therefore, a fitting factor needs to be applied when using the current version of COSMO<i>therm</i> to predict <i>K</i>_<i>S</i>. AIOMFAC tends to underpredict the measured <i>K</i>_S((NH₄)₂SO₄) but always overpredicts <i>K</i>_S(NaCl). The prediction error is generally larger for <i>K</i>_S(NaCl) than for <i>K</i>_S((NH₄)₂SO₄). AIOMFAC also predicted a dependence of <i>K</i>_<i>S</i> on the salt concentrations, which is not observed in the experimental data. In order to demonstrate that the models developed and calibrated in this study can be applied to estimate Setschenow coefficients for atmospherically relevant compounds involved in secondary organic aerosol formation based on chemical structure alone, we predicted and compared <i>K</i>_S for selected α-pinene oxidation products

Large Bubbles Reduce the Surface Sorption Artifact of the Inert Gas Stripping Method

Accurate Henry’s law constants between air and water (<i>H</i>) are crucial for understanding a chemical’s environmental behavior. During inert gas stripping (IGS) <i>H</i> is derived from the rate of a chemical’s disappearance from aqueous solution as a result of air bubbling through a water-filled column. While <i>H</i> of many semivolatile organic compounds has been measured by IGS, inconsistent results between different studies have been attributed to chemical adsorption to the bubble surface. This surface adsorption artifact is expected to increase with a chemical’s interface–air partition coefficient (<i>K</i>_IA) and decreasing bubble size. Previous work with normal alkanols of variable chain length identified a <i>K</i>_IA threshold of approximately 0.001 m, above which IGS is compromised by the surface sorption artifact. In this study, we repeated IGS measurements of <i>H</i> of normal alkanols at different temperatures of 298.15 K, 305.65 K, 323.15 K, and 343.15 K using a modified gas inlet mechanisms that results in the formation of large bubbles (diameter approximately 5.5 mm). The new <i>H</i> values agreed very well with those measured with a head space technique that is much less susceptible to surface adsorption. The method is judged suitable for measuring <i>H</i> of surface active chemicals with <i>K</i>_IA values below 0.02 <i>m</i>