Systematic Investigation of the Sorption Properties of Tenax TA, Chromosorb 106, Porapak N, and Carbopak F

Assessing Aquatic Baseline Toxicity of Plastic-Associated Chemicals: Development and Validation of the Target Plastic Model

We developed a Target Plastic Model (TPM) to estimate the critical plastic burden of organic toxicants in five types of plastics, namely, polydimethylsiloxane (PDMS), polyoxymethylene (POM), polyacrylate (PA), low-density polyethylene (LDPE), and polyurethane ester (PU), following the Target Lipid Model (TLM) framework. By substituting the lipid-water partition coefficient in the TLM with plastic-water partition coefficients to create TPM, we demonstrated that the biomimetic nature of these plastic phases allows for the calculation of critical plastic burdens of toxicants, similar to the notion of critical lipid burdens in TLM. Following this approach, the critical plastic burdens of baseline (n = 115), less-inert (n = 73), and reactive (n = 75) toxicants ranged from 0.17 to 51.33, 0.04 to 26.62, and 1.00 × 10-6 to 6.78 × 10-4 mmol/kg of plastic, respectively. Our study showed that PDMS, PA, POM, PE, and PU are similar to biomembranes in mimicking the passive exchange of chemicals with the water phase. Using the TPM, median lethal concentration (LC50) values for fish exposed to baseline toxicants were predicted, and the results agreed with experimental values, with RMSE ranging from 0.311 to 0.538 log unit. Similarly, for the same data set of baseline toxicants, other widely used models, including the TLM (RMSE: 0.32-0.34), ECOSAR (RMSE: 0.35), and the Abraham Solvation Model (ASM; RMSE: 0.31), demonstrated comparable agreement between experimental and predicted values. For less inert chemicals, predictions were within a factor of 5 of experimental values. Comparatively, ASM and ECOSAR showed predictions within a factor of 2 and 3, respectively. The TLM based on phospholipid had predictions within a factor of 3 and octanol within a factor of 4, indicating that the TPM's performance for less inert chemicals is comparable to these established models. Unlike these methods, the TPM requires only the knowledge of plastic bound concentration for a given plastic phase to calculate baseline toxic units, bypassing the need for extensive LC50 and plastic-water partition coefficient data, which are often limited for emerging chemicals. Taken together, the TPM can provide valuable insights into the toxicities of chemicals associated with environmental plastic phases, assisting in selecting the best polymeric phase for passive sampling and designing better passive dosing techniques for toxicity experiments.

Dynamic Breath Limonene Sensing at High Selectivity

Liver diseases (e.g., cirrhosis, cancer) cause more than two million deaths per year worldwide. This is partly attributed to late diagnosis and insufficient screening techniques. A promising biomarker for noninvasive and inexpensive liver disease screening is breath limonene that can indicate a deficiency of the cytochrome P450 liver enzymes. Here, we introduce a compact and low-cost detector for dynamic and selective breath limonene sensing. It comprises a chemoresistive sensor based on Si/WO₃ nanoparticles pre-screened by a packed bed Tenax separation column at room temperature. We demonstrate selective limonene detection down to 20 parts per billion over up to three orders of magnitude higher concentrated acetone, ethanol, hydrogen, methanol, and 2-propanol in gas mixtures, as well as robustness to 10-90% relative humidity. Most importantly, this detector recognizes the individual breath limonene dynamics of four healthy volunteers following the ingestion (swallowing or chewing) of a limonene capsule. Limonene release and subsequent metabolization are monitored from breath measurements in real time and in excellent agreement (R² = 0.98) with high-resolution proton transfer reaction mass spectrometry. This study demonstrates the potential of the detector as a simple-to-use and noninvasive device for the routine monitoring of limonene levels in exhaled breath to facilitate early diagnosis of liver dysfunction.

Selectivity evaluation of extraction systems

Extraction is the most common sample preparation technique prior to chromatographic analysis for samples which are too complex, too dilute, or contain matrix components incompatible with the further use of the separation system or interfere in the detection step. The most important extraction techniques are biphasic systems involving the transfer of target compounds from the sample to a different phase ideally accompanied by no more than a tolerable burden of co-extracted matrix compounds. The solvation parameter model affords a general framework to characterize biphasic extraction systems in terms of their relative capability for solute-phase intermolecular interactions (dispersion, dipole-type, hydrogen bonding) and within phase solvent-solvent interactions for cavity formation (cohesion). The approach is general and allows the comparison of liquid and solid extraction phases using the same terms and is used to explain the features important for the selective enrichment of target compounds by a specific extraction phase using solvent extraction, liquid-liquid extraction, and solid-phase extraction for samples in a gas, liquid, or solid phase. Hierarchical cluster analysis with the system constants of the solvation parameter model as variables facilitates the selection of solvents for extraction, the identification of liquid-liquid distribution systems with non-redundant selectivity, and evaluation of different approaches using liquids and solids for the isolation of target compounds from different matrices.

Selective formaldehyde detection at ppb in indoor air with a portable sensor

Formaldehyde is a carcinogenic indoor air pollutant emitted from wood-based furniture, building materials, paints and textiles. Yet, no low-cost sensor exists for on-site monitoring to fulfill stringent current and upcoming (e.g., 8 parts-per-billion by volume, ppb, in France by 2023) exposure guidelines. Here, we present an inexpensive and handheld formaldehyde detector with proven performance in real indoor air. Selectivity is achieved by a compact packed bed column of nanoporous polymer sorbent that separates formaldehyde from interferants present in ambient air. Downstream, a highly sensitive nanoparticle-based chemoresistive Pd-doped SnO₂ sensor detects formaldehyde in the relevant concentration range down to 5 ppb within 2 min. As a proof-of-concept, we measured formaldehyde in indoor air and from different wood product emissions, in excellent agreement (R² > 0.98) with high-resolution proton-transfer-reaction time-of-flight mass spectrometry. This detector is simple-in-use and readily applicable for on-site formaldehyde exposure monitoring at home or work. It is promising for internet-of-things (IOT) sensing networks or even wearables for personal exposure assessment.

Passive air sampling for semi-volatile organic chemicals

During passive air sampling, the amount of a chemical taken up in a sorbent from the air without the help of a pump is quantified and converted into an air concentration. In an equilibrium sampler, this conversion requires a thermodynamic parameter, the equilibrium sorption coefficient between gas-phase and sorbent. In a kinetic sampler, a time-averaged air concentration is obtained using a sampling rate, which is a kinetic parameter. Design requirements for kinetic and equilibrium sampling conflict with each other. The volatility of semi-volatile organic compounds (SVOCs) varies over five orders of magnitude, which implies that passive air samplers are inevitably kinetic samplers for less volatile SVOCs and equilibrium samplers for more volatile SVOCs. Therefore, most currently used passive sampler designs for SVOCs are a compromise that requires the consideration of both a thermodynamic and a kinetic parameter. Their quantitative interpretation depends on assumptions that are rarely fulfilled, and on input parameters, that are often only known with high uncertainty. Kinetic passive air sampling for SVOCs is also challenging because their typically very low atmospheric concentrations necessitate relatively high sampling rates that can only be achieved without the use of diffusive barriers. This in turn renders sampling rates dependent on wind conditions and therefore highly variable. Despite the overall high uncertainty arising from these challenges, passive air samplers for SVOCs have valuable roles to play in recording (i) spatial concentration variability at scales ranging from a few centimeters to tens of thousands of kilometers, (ii) long-term trends, (iii) air contamination in remote and inaccessible locations and (iv) indoor inhalation exposure. Going forward, thermal desorption of sorbents may lower the detection limits for some SVOCs to an extent that the use of diffusive barriers in the kinetic sampling of SVOCs becomes feasible, which is a prerequisite to decreasing the uncertainty of sampling rates. If the thermally stable sorbent additionally has a high sorptive capacity, it may be possible to design true kinetic samplers for most SVOCs. In the meantime, the passive air sampling community would benefit from being more transparent by rigorously quantifying and explicitly reporting uncertainty.

Room-temperature-ionic-liquid coated graphitized carbons for selective preconcentration of polar vapors

Most adsorbent materials used for preconcentrating and thermally desorbing volatile and semi-volatile organic compounds (S/VOCs) in portable or "micro" gas chromatographic (GC/µGC) instruments preferentially capture non-polar or moderately polar compounds relative to more polar compounds. Here, we explore the use of a known trigonal-tripyramidal room-temperature ionic liquid (RTIL) as a surface modifier for the graphitized carbons, Carbopack B (C-B) and Carbopack X (C-X), with the goal of enhancing their capacity and selectivity for polar S/VOCs. Breakthrough tests were performed by challenging tubes packed with ∼2.5 mg of C-B or RTIL-coated C-B (RTIL/C-B) with 13 individual S/VOCs, including several organophosphorus compounds and reference alkyl and aromatic hydrocarbons of comparable vapor pressures, at concentrations ranging from 14 to 130 mg/m³. The 10% breakthrough volume, V_b10, was used as the measure of capacity. For the RTIL/C-B, the V_b10 values of the five organophosphorus vapors tested were consistently ∼2.5 times larger than those for the untreated C-B, and V_b10 values of the four non-polar reference vapors were 11-26 times smaller for the RTIL/C-B than for the untreated C-B. For compounds of similar vapor pressure the capacity ratios for polar vs. non-polar compounds with the RTIL/C-B ranged from 1.8 to 34. Similar results were obtained with C-X and RTIL/C-X on a smaller set of compounds. Tests at 70% relative humidity or with a binary mixture of a polar and non-polar compound had no effect on the capacity of the RTIL/C-B, and there were no changes in V_b10 values after several months of testing that included cycling from 25 to 250 °C. Capacity was strongly correlated with vapor pressure. Attempts to reconcile the selectivity using models based on linear-solvation-energy relationships were only partially successful. Nonetheless, these results indicate that RTIL coating of carbon adsorbents affords a simple, reliable means of rendering them selective for polar S/VOCs.

Influence of Adsorbent Nature on the Dynamic Headspace Study of Insect Semiochemicals

In chemical ecology studies (insect–insect, insect–plant relationships), it is important to choose the appropriate sampling methods and the correct optimization of sampling by using dynamic systems. In the present work, different adsorbents were evaluated in a dynamic system that presents a stream of purified air flowing through an aeration chamber containing a mixture of volatile organic compounds, mainly insect semiochemicals such as α-pinene, sulcatone, β-linalool, menthone, isomenthone, methyl salicylate, grandlure I, grandlure II, grandlure III, grandlure IV, eugenol, and α-ionone. Traditional adsorbents such as Tenax TA, Porapak Q, Hayesep Q, and activated charcoal were evaluated; further, alternatives such as Porapak Rxn RP, HLB, SCX, and silica gel, among others were proposed owing to their lower cost. The results demonstrated that Porapak Q and Porapak Rxn RP, despite their different chemical composition, were able to produce similar ratios of compounds to that of the reference solution and, moreover, with the highest recovery yields. However, it is important to emphasize the adsorption selectivity provided by SCX for eugenol and α-ionone. When Porapak Rxn RP was used in the analysis of Eucalyptus globulus volatiles, excellent results were obtained, and these agree with reported data from a hydrodistillation method.

Screening-level models to estimate partition ratios of organic chemicals between polymeric materials, air and water

Polymeric materials flowing through the technosphere are repositories of organic chemicals throughout their life cycle. Equilibrium partition ratios of organic chemicals between these materials and air (KMA) or water (KMW) are required for models of fate and transport, high-throughput exposure assessment and passive sampling. KMA and KMW have been measured for a growing number of chemical/material combinations, but significant data gaps still exist. We assembled a database of 363 KMA and 910 KMW measurements for 446 individual compounds and nearly 40 individual polymers and biopolymers, collected from 29 studies. We used the EPI Suite and ABSOLV software packages to estimate physicochemical properties of the compounds and we employed an empirical correlation based on Trouton's rule to adjust the measured KMA and KMW values to a standard reference temperature of 298 K. Then, we used a thermodynamic triangle with Henry's law constant to calculate a complete set of 1273 KMA and KMW values. Using simple linear regression, we developed a suite of single parameter linear free energy relationship (spLFER) models to estimate KMA from the EPI Suite-estimated octanol-air partition ratio (KOA) and KMW from the EPI Suite-estimated octanol-water (KOW) partition ratio. Similarly, using multiple linear regression, we developed a set of polyparameter linear free energy relationship (ppLFER) models to estimate KMA and KMW from ABSOLV-estimated Abraham solvation parameters. We explored the two LFER approaches to investigate (1) their performance in estimating partition ratios, and (2) uncertainties associated with treating all different polymers as a single "bulk" polymeric material compartment. The models we have developed are suitable for screening assessments of the tendency for organic chemicals to be emitted from materials, and for use in multimedia models of the fate of organic chemicals in the indoor environment. In screening applications we recommend that KMA and KMW be modeled as 0.06 ×KOA and 0.06 ×KOW respectively, with an uncertainty range of a factor of 15.

Applications of polyparameter linear free energy relationships in environmental chemistry

Partitioning behavior of organic chemicals has tremendous influences on their environmental distribution, reaction rates, bioaccumulation, and toxic effects. Polyparameter linear free energy relationships (PP-LFERs) have been proven to be useful to characterize the equilibrium partitioning of organic chemicals in various environmental and technical partitioning systems and predict the respective partition coefficients. Over the past decade, PP-LFER solute descriptors for numerous environmentally relevant organic chemicals and system parameters for environmentally important partitioning systems have been determined, extending substantially the applicability of the PP-LFER approaches. However, the information needed for the use of PP-LFERs including descriptors and parameters is scattered over a large number of publications. In this work, we review the state of the art of the PP-LFER approaches in environmental chemical applications. The solute descriptors and system parameters reported in the literature and the availability of their database are summarized, and their calibration and prediction methods are overviewed. We also describe tips and pitfalls associated with the use of the PP-LFER approaches and identify research needs to improve further the usefulness of PP-LFERs for environmental chemistry.

Improved performance of micro-fabricated preconcentrators using silica nanoparticles as a surface template

A new approach of enhancing the adsorption capability of the widely used polymer adsorbent Tenax TA poly(2,6-diphenylene oxide) through its deposition on a nano-structured template is reported. The modified Tenax TA-coated silica nanoparticles (SNP) are incorporated as an adsorbent bed in silicon based micro-thermal preconcentrator (μTPC) chips with an array of square microposts embedded inside the cavity and sealed with a Pyrex cover. The interior surface of the chip is first modified by depositing SNP using a layer-by-layer self-assembly technique followed by coating with Tenax TA. The adsorption capacity of the SNP-Tenax TA μTPC is enhanced by as much as a factor of three compared to the one coated solely with thin film Tenax TA for the compounds tested. The increased adsorption ability of the Tenax TA is attributed to the higher surface area provided by the underlying porous SNP coating and the pores between SNPs affecting the morphology of deposited Tenax TA film by bringing nano-scale features into the polymer. In addition, the adsorption ability of the SNP coating as a pseudo-selective inorganic adsorption bed for polar compounds was also observed. The modified Tenax TA-coated SNP μTPC is a promising development toward integrated micro-gas chromatography systems.

Predicting sorption of pesticides and other multifunctional organic chemicals to soil organic carbon

Chemicals of current environmental concern are often multifunctional and more polar and more complex than classical pollutants such as polychlorinated biphenyls (PCB) or polycyclic aromatic hydrocarbons (PAH). Traditional models for predicting the partitioning in the environment such as group contribution methods or correlations with octanol-water partitioning cannot be expected to work well for such complex chemicals. In contrast, poly parameter Linear Free Energy Relationships (pp-LFERs) have been proven to describe partitioning of polar and nonpolar chemicals in all kinds of sorbing systems. Here, a pp-LFER model for soil-water partitioning was calibrated with data for 79 polar and nonpolar compounds that cover a very wide range of the relevant intermolecular interactions. The data set used for the model calibration in this work is more diverse and covers a wider range of the chemical space than other pp-LFERs published so far. Subsequently, the experimental data for about 50 pesticides and pharmaceuticals -not involved in the model calibration- were used as independent validation of this new calibrated model. The model performs well with a standard error of 0.25 log units for fitting the calibration data and with a root-mean-square error of 0.4 log units for the pesticides and pharmaceuticals. The validation with the independent data set for pesticides and pharmaceuticals also shows that the pp-LFER model reported here performs better compared to earlier published pp-LFER models and to the traditional log Kow correlation.