Physicochemical and biochemical properties for the dialkyl phthalates

The effect of the assigned descriptors for phthalate esters on the characterization of their separation properties using the solvation parameter model

Revised descriptors are determined for fifteen phthalate esters for use in the solvation parameter model and form part of the Wayne State University (WSU) compound descriptor database. For thirteen phthalate esters a comparison is made with the same compounds in the Abraham descriptor database. Gas chromatographic retention factors on poly(methyloctylsiloxane), SPB-Octyl, and poly(cyanopropylphenyldimethylsiloxane), DB-225, stationary phases are used to facilitate an assessment of the contribution of cavity formation and dispersion interactions, L descriptor, and dipole-type interactions, S descriptor, to the experimental retention factors (log k) for the phthalate esters with minimum interference from competing intermolecular interactions. The results indicate a systematic overprediction of the cavity and dispersion interaction term and underprediction of dipole-type interactions for the Abraham descriptors compared with the WSU descriptors for the phthalate esters. The average absolute deviation (AAD) for 13 phthalate esters on SPB-Octyl is 0.039 (WSU descriptors) compared with 0.252 (Abraham descriptors) and for 9 phthalate esters on DB-225 0.030 (WSU descriptors) compared with 0.167 (Abraham descriptors). The results for dipole-type interactions are confirmed and extended to include the hydrogen-bond basicity of the phthalate esters, B descriptor, by evaluation of partition constants in aqueous biphasic systems and the n-heptane-2,2,2-trifluoroethanol biphasic system. Differences in the contribution of the hydrogen-bond basicity of the phthalate esters to the experimental partition constants are largely random with respect to database selection but important for the accurate prediction of the partition constants. The AAD for the partition constant for 15 phthalate esters is 0.063 (WSU descriptors) compared with 0.320 (Abraham descriptors) for the heptane-2,2,2-trifluoroethanol biphasic system and 0.13 (WSU descriptors) compared with 0.25 (Abraham descriptors) for 9 phthalate esters in the octanol-water biphasic system. The WSU descriptors for the phthalate esters exhibit a better fit with the experimental data for separation systems and are free of the extreme values predicted for the Abraham descriptors for several phthalate esters.

The influence of descriptor database selection on the solvation parameter model for separation processes

The distribution of neutral compounds in biphasic separation systems can be described by the solvation parameter model using six solute properties, or descriptors. These descriptors characterize the size (McGowan's characteristic volume), V, excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity and basicity, A and B, and the gas-liquid partition constant on n-hexadecane at 298.15 K, L. McGowan's characteristic volume and the excess molar refraction for liquids are available by calculation (E requires and experimental refractive index). The other descriptors and excess molar refraction for solids are experimental quantities and subject to greater variation or are estimated using computational or empirical models. Solute descriptors for several thousand compounds are available in the Abraham descriptor database and for several hundred compounds in the WSU descriptor database. These publicly accessible databases were developed independently using different approaches and for many compounds provide different descriptor values. In this report we evaluate the effect of mixing descriptors from the two databases on modeling chromatographic retention factors and liquid-liquid partition constants. It is shown that the two descriptor databases are not interchangeable. The WSU descriptor database consistently demonstrates improved model quality as determined by statistical parameters. Model system constants exhibit a general dependence on database selection with an approximately linear trend as a function of the fraction of compounds assigned descriptors from either database. There is no general model performance advantage to using mixed descriptor datasets and no real cause for concern for relatively large datasets containing < 15 % of compounds with descriptors assigned from the other database. For small datasets, descriptor quality is an important variable for adequate model performance.

Recent advances for estimating environmental properties for small molecules from chromatographic measurements and the solvation parameter model

The transfer of neutral compounds between immiscible phases in chromatographic or environmental systems can be described by six solute properties (solute descriptors) using the solvation parameter model. The solute descriptors are size (McGowan's characteristic volume), V, excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity and basicity, A and B, and the gas-liquid partition constant on n-hexadecane at 298.15 K, L. V and E for liquids are accessible by calculation but the other descriptors and E for solids are determined experimentally by chromatographic, liquid-liquid partition, and solubility measurements. These solute descriptors are available for several thousand compounds in the Abraham solute descriptor databases and for several hundred compounds in the WSU experimental solute descriptor database. In the first part of this review, we highlight features important in defining each descriptor, their experimental determination, compare descriptor quality for the two organized descriptor databases, and methods for estimating Abraham solute descriptors. In the second part we focus on recent applications of the solvation parameter model to characterize environmental systems and its use for the identification of surrogate chromatographic models for estimating environmental properties.

Phthalate metabolites in paired human serum and whole blood

Presence of phthalate metabolites (PMs) in human serum has been well documented. However, the distribution pattern of PMs in different human blood matrixes remains not well known. To investigate this, paired serum and whole blood samples were collected from 145 adults (76 males and 69 females) in Quzhou, China, and analyzed for nine PMs in this study. All PMs had high detection frequencies (> 70%) in human serum and whole blood, except mono benzyl phthalate. Total concentrations of detected PMs in serum and whole blood were 0.70-61 ng/mL (mean 12 ng/mL) and 1.6-33 ng/mL (7.5 ng/mL), respectively. Mono methyl phthalate (MMP), mono (2-ethylhexyl) phthalate, and mono butyl phthalate were consistently the predominant PMs in human serum and whole blood, with the mean concentrations of 3.4 and 2.0 ng/mL, 3.3 and 2.1 ng/mL, and 2.8 and 1.8 ng/mL, respectively. Females had higher mean serum concentrations of PMs, except MBP, than males. Youngest age group (20-30 years) consistently had the lowest mean whole blood levels of all PMs. For the first time, the distribution pattern of PMs in human blood was evaluated based on the calculated partitioning coefficient (K_p) between serum and whole blood. MMP had the highest mean K_p value (1.6; 10th-90th percentile: 1.0-2.2), while mono (2-ethyl-5-oxohexyl) phthalate had the lowest mean K_p value (0.63; 10th-90th percentile: 0.25-1.3). These results help better understand the occurrence of PMs in human blood.

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.

Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy

We present a group contribution method (SoluteGC) and a machine learning model (SoluteML) to predict the Abraham solute parameters, as well as a machine learning model (DirectML) to predict solvation free energy and enthalpy at 298 K. The proposed group contribution method uses atom-centered functional groups with corrections for ring and polycyclic strain while the machine learning models adopt a directed message passing neural network. The solute parameters predicted from SoluteGC and SoluteML are used to calculate solvation energy and enthalpy via linear free energy relationships. Extensive data sets containing 8366 solute parameters, 20,253 solvation free energies, and 6322 solvation enthalpies are compiled in this work to train the models. The three models are each evaluated on the same test sets using both random and substructure-based solute splits for solvation energy and enthalpy predictions. The results show that the DirectML model is superior to the SoluteML and SoluteGC models for both predictions and can provide accuracy comparable to that of advanced quantum chemistry methods. Yet, even though the DirectML model performs better in general, all three models are useful for various purposes. Uncertain predicted values can be identified by comparing the three models, and when the 3 models are combined together, they can provide even more accurate predictions than any one of them individually. Finally, we present our compiled solute parameter, solvation energy, and solvation enthalpy databases (SoluteDB, dGsolvDBx, dHsolvDB) and provide public access to our final prediction models through a simple web-based tool, software packages, and source code.

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.

Predicting the Gas/Particle Distribution of SVOCs in the Indoor Environment Using Poly Parameter Linear Free Energy Relationships

Understanding the partitioning of semi volatile organic compounds (SVOCs) between gas phase and particle phase is essential for exposure analysis and risk assessment in the indoor environment. Numerous attempts have been made to calculate gas/particle partitioning coefficients K_ip. Single-parameter adsorption and absorption models, which relate K_ip to the vapor pressure P_s or the octanol/air distribution coefficient K_OA are usually applied. In this work we use poly parameter Linear Free Energy Relationships (pp-LFER) to describe the partitioning behavior of 14 SVOCs with high relevance for the indoor environment. The pp-LFER concept is based on Abraham descriptors and considers interactions between molecule and particle by separate parameters. van der Waals interactions can be approximated by the logarithm of the hexadecane/air partitioning coefficient (log K_HdA = L), which is a key parameter for the 14 polar but nonionizable organic esters being studied here. For many of the examined compounds experimentally determined L-values were not available and had to be measured using gas chromatography. It is shown that the pp-LFER method is a strong alternative to single-parameter approaches and gives reliable coefficients for gas/particle distribution in the indoor environment.

Passive sampling for spatial and temporal monitoring of organic pollutants in surface water of a rural-urban river in Kenya

Passive sampling is an emerging monitoring strategy for surface waters and can be applied in a range of environments including remote locations. Silicone rubber (SR) as a robust single-phase passive sampler was applied to characterize the spatial and temporal variability of organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), polyaromatic hydrocarbons (PAHs) and three phthalates, namely, dibutyl phthalate (DBP), benzyl butyl phthalate (BBP) and bis(2-ethylhexyl)phthalate (DEHP) in a tropical river traversing rural and urban catchments. OCPs and PCBs were not detected. Up to 31.8ng/L of freely dissolved concentrations of PAHs were quantified and were dominated by the lower molecular weight members. Mean concentrations of DBP, BBP and DEHP were 72.6ng/L, 3.9ng/L and 7.1ng/L respectively. However, in sampling for phthalates using SR, quality control and assurance remains the key challenge and must always be ensured. Spatial variability in concentrations was evident and could be related to land use. Temporal variability was not significant.

Determination of free and total phthalates in commercial whole milk products in different packaging materials by gas chromatography-mass spectrometry

We developed a method for extraction and determination of free and total phthalate esters in commercial whole milk products. The free phthalates in milk samples were extracted with ethyl acetate after general pretreatment procedures including protein precipitation, centrifugation, and filtration. The bound phthalates in samples were first desorbed with the aid of ultrasound irradiation before extraction of total phthalates. The separation and determination of phthalates in extracts was performed by gas chromatography coupled with mass spectrometric detection. The detection limits were in the range of 0.09 to 0.36ng/g and the average recovery between 79.1 and 110.3%. The developed methods were applied to extract and determine phthalates in commercial whole milk products with different packaging materials, including plastic, glass, and metal. All samples contained several phthalates, including diethyl, diisobutyl, and bis(2-ethylhexyl) phthalates at concentrations between 2.60 and 156.4ng/g. The identified phthalates occurred in both free and bound forms. The amounts of phthalates in milk samples packaged in glass and metal containers were much lower than those in plastic containers. Plastic packaging materials are a possible source of phthalate contamination in commercial whole milk products, and a considerable portion of bleached phthalates from packaging can be adsorbed on proteins and other solid components of milk.

Is there an intramolecular hydrogen bond in 2-halophenols? A theoretical and spectroscopic investigation

H-bonding is the most important interaction in life. We present a theoretical and spectroscopic investigation of intramolecular H-bonding in 2-halophenols.