Fate Model Research Articles

A machine learning based approach for estimating site-specific partition coefficient Kd of organic compounds: Application to nonionic pesticides

The partitioning coefficient Kd for a specific compound and location is not only a key input parameter of fate and transport models, but also critical in estimating the safety environmental concentration threshold. In order to reduce the uncertainty caused by non-linear interactions among environmental factors, machine learning based models for predicting Kd were developed in this work based on literature datasets of nonionic pesticides including molecular descriptors, soil properties, and experimental settings. The equilibrium concentration (Ce) values were specifically included for the reason that a varied range of Kd corresponding to a given Ce occurred in a real environment. By transforming 466 isotherms reported in the literature, 2618 paired equilibrium concentrations of liquid-solid (Ce-Qe) data points were obtained. Results of SHapley Additive exPlanations revealed that soil organic carbon, Ce, and cavity formation were the most important. The distance-based applicability domain analysis was conducted for the 27 most frequently used pesticides with 15952 pieces of soil information from the HWSD-China dataset by setting three Ce scenarios (i.e., 10, 100, and 1000 μg L−1). It was revealed the groups of compounds showing log Kd < 0.06 and log Kd > 1.19 were composed mostly of those with log Kow of −0.800 and 5.50, respectively. When log Kd varied between 0.100 and 1.00, it was impacted by interactions among soil types, molecular descriptors, and Ce comprehensively, which accounted for 55% of the total 2618 calculations. It could be concluded that site-specific models developed in this work are necessary and practicable for the environmental risk assessment and management of nonionic organic compounds.

A method for simulating spatial fates of chemicals in flowing lake systems: Application to phthalates in a lake

In order to describe spatio-temporal distribution of chemicals in flowing lake systems, a dynamic multimedia fate model of chemicals with spatial differentiation was constructed by coupling the level IV fugacity model with lake hydrodynamics. It was successfully applied to four phthalates (PAEs) in a lake recharged by reclaimed water and its accuracy was verified. Results show that under the long-term influence of flow field, the distributions of PAEs in both lake water and sediment have significant spatial heterogeneity of 2∼5 orders of magnitude, but present different distribution rules, which was explained by analysis of PAE transfer fluxes. The spatial distribution of PAEs in the water column depends on hydrodynamic conditions and whether the primary source is reclaimed water or atmospheric input. Slow water exchange and flow speed promote the migration of PAEs from water to sediment, causing them to always accumulate in sediments far away from the recharging inlet. Uncertainty and sensitivity analysis show that the PAE concentrations in water phase are mainly affected by emission and physicochemical parameters, while those in sediment phase are also sensitive to environmental parameters. The model can provide important information and accurate data support for the scientific management of chemicals in flowing lake systems.

Targeting chromatin mediated cellular plasticity in vivo.

Advances in cancer treatment, including precision oncology, are significantly hindered by cancer cell plasticity. The ability to adapt to various external stressors is due to two attributes of highly plastic cells: transcriptional malleability, which is the ability of a cell to quickly upregulate survival pathways, and transcriptional heterogeneity, or the variance in the pathways utilized by cells to evade cell death. Both aspects of phenotypic plasticity have been directly linked to a measure of statistical chromatin organization, the chromatin packing scaling D, which facilitates changes in gene expression. To study the role of chromatin in plasticity-mediated survival, we performed time-course imaging of chemotherapy-treated cancer cells using label-free Partial Wave Spectroscopic (PWS) microscopy. The population distribution of D shifted over the course of treatment such that all surviving cells exhibited high D values. Accordingly, cell cluster tracking demonstrated a negative correlation between the initial D and the increase in D induced by treatment. We developed a computational model of cell fate based on changes in transcription due to D, which could recapitulate experimental results. We predicted that pharmacologically lowering D would reduce plasticity and improve chemotherapeutic efficacy. Specifically, we screened compounds that would lower D by facilitating chromatin-nucleoplasm interactions through either histone tail modifications or changes in the nuclear ionic environment. Adding a D-lowering agent to chemotherapy treatment increased the probability of cell death compared to chemotherapy alone, which matched model predictions. We next tested these treatments in vivo in a PDX model where our model predicted that although tumors would still be able to adapt to chemotherapy treatment, the combination treatment would exhibit a higher cell growth inhibition rate and stunt tumor adaptation. Significantly, our results demonstrated that lowering D improves treatment outcomes even in a conservative treatment with low-dose chemotherapy.

Understanding impacts of organic contaminants from aquaculture on the marine environment using a chemical fate model.

As demand for sustainable marine aquaculture (mariculture) and marine food supply surges worldwide, there is a growing need for new tools to assess mariculture impacts on local ecosystems, including the cycling of toxic organic contaminants. With this in mind, we developed the Contaminant Fate in Aquaculture-Modified Ecosystems (CFAME) model. The current model was designed to explore the fate of mariculture-derived organic contaminants in the Marlborough Sounds, New Zealand, known for its Chinook salmon farming industry. Model evaluation indicated robust model design, with 80% of modeled concentrations falling within a factor of ten of measured ones for native biota. Model results showed that mariculture was a source of organic contaminants in the sediment even at the Marlborough Sounds regional level and in wild marine fishes with high trophic levels near the farm area. Future research attention should be directed toward measuring chemicals with low log KAW (<0) and high log KOW values (e.g., >3) in sediment, and chemicals with log KOW values of 3-9 in wild fish.

Understanding Dyad, Person, and Contextual Effects in Dyadic Analysis

Several interesting variations on the Common Fate Model (CFM) for dyadic analysis have emerged over the past decade. For instance, the multilevel-CFM is characterized by directional paths between Person level observed X and Y variables in addition to the Dyad level direct path between the corresponding latent variables. Although this model appears to provide a decomposition of the Y on X regression into Dyad and Person level components, close examination reveals that this specification yields a Dyad level coefficient that captures the contextual effect, or the discrepancy in the between- and within-cluster coefficients. The present work elucidates key features of the multilevel-CFM that produce the contextual effect parametrization, and introduces an alternative specification, the between-within-CFM that yields a decomposition of the Y on X regression consistent with the general multilevel SEM literature. These variations on the CFM are illustrated using empirical examples, supported by syntax for commonly used SEM software.

Bridging the lab to field divide: Advancing oil spill biological effects models requires revisiting aquatic toxicity testing

Oil fate and exposure modeling addresses the complexities of oil composition, weathering, partitioning in the environment, and the distributions and behaviors of aquatic biota to estimate exposure histories, i.e., oil component concentrations and environmental conditions experienced over time. Several approaches with increasing levels of complexity (i.e., aquatic toxicity model tiers, corresponding to varying purposes and applications) have been and continue to be developed to predict adverse effects resulting from these exposures. At Tiers 1 and 2, toxicity-based screening thresholds for assumed representative oil component compositions are used to inform spill response and risk evaluations, requiring limited toxicity data, analytical oil characterizations, and computer resources. Concentration-response relationships are employed in Tier 3 to quantify effects of assumed oil component mixture compositions. Oil spill modeling capabilities presently allow predictions of spatial and temporal compositional changes during exposure, which support mixture-based modeling frameworks. Such approaches rely on summed effects of components using toxic units to enable more realistic analyses (Tier 4). This review provides guidance for toxicological studies to inform the development of, provide input to, and validate Tier 4 aquatic toxicity models for assessing oil spill effects on aquatic biota.Evaluation of organisms’ exposure histories using a toxic unit model reflects the current state-of the-science and provides an improved approach for quantifying effects of oil constituents on aquatic organisms. Since the mixture compositions in toxicity tests are not representative of field exposures, modelers rely on studies using single compounds to build toxicity models accounting for the additive effects of dynamic mixture exposures that occur after spills. Single compound toxicity data are needed to quantify the influence of exposure duration and modifying environmental factors (e.g., temperature, light) on observed effects for advancing use of this framework. Well-characterized whole oil bioassay data should be used to validate and refine these models.

Herbicide Fate and Transport in the Great Barrier Reef: A Review of Critical Parameters

Herbicides used for weed management on agricultural land in Australia’s Great Barrier Reef catchments are a key concern for its ecosystem, including the lagoon’s marine plants and corals, whose productivity has been found to decline. The most reliable way to assess herbicide risk is by monitoring a site regularly, but this is costly and time-consuming, so numerical simulations and computer models are an alternative method. Despite the availability of low-cost and less labor-intensive modelling methods, they have been limited in their effectiveness due to a lack of specific herbicide usage data and an inadequate understanding of the breakdown and transport processes of herbicides after application. This paper reviews current findings regarding herbicide risk in all Great Barrier Reef catchments according to their agricultural land use, and the most recent Reef Water Quality Protection Plan recommendations. The various pathways for fate and transport of the herbicides were also examined, and a list of critical parameters was developed to help with computer simulations. The accuracy and reliability of modelling can be improved by including aerial drifts, interceptions by crop residues, mechanisms within the root zone, and subsurface and groundwater contributions to the herbicide load in the GBR lagoon. Moreover, the findings will provide new directions for management practices adoption data with the fate and transport model from paddock to reef and improve the reliability of model results.

Seeing beyond the smoke: Selecting waterpipe wastewater chemicals for risk assessments

BackgroundIncreasing use prevalence of waterpipe tobacco products raises concerns about environmental impacts from waterpipe waste disposal. The U.S. Food and Drug Administration (FDA) is required to assess the environmental impact of its tobacco regulatory actions per the National Environmental Policy Act. This study builds on FDA’s efforts characterizing the aquatic toxicity of waterpipe wastewater chemicals. MethodsWe compiled a comprehensive list of waterpipe wastewater chemical concentrations from literature. We then selected chemicals for risk assessment by estimating persistence, bioaccumulation, and aquatic toxicity (PBT) characteristics (U.S. Environmental Protection Agency), and hazardous concentration values (concentration affecting specific proportion of species). ResultsOf 38 chemicals in waterpipe wastewater with concentration data, 20 are listed as harmful or potentially harmful constituents (HPHCs) in tobacco smoke and tobacco products by FDA, and 15 are hazardous waste per U. S. Environmental Protection Agency. Among metals, six (cadmium, chromium, lead, mercury, nickel and selenium) are included in both HPHC and hazardous waste lists and were selected for future risk assessments. Among non-metals, nicotine, and 4-methylnitrosamino-1-(3-pyridyl)− 1-butanone (NNK) were shortlisted, as they are classified as persistent and toxic. Further, N-nitrosonornicotine (NNN), with a low hazardous concentration value (HC50; concentration affecting 50 % of aquatic species) for chronic aquatic toxicity, had high aquatic toxicity concern and is selected. ConclusionsThe presence of multiple hazardous compounds in waterpipe wastewater highlights the importance of awareness on the proper disposal of waterpipe wastewater in residential and retail settings. Future studies can build on the hazard characterization provided in this study through fate and transport modeling, exposure characterization and risk assessments of waterpipe wastewater chemicals.

Homologue-based Estimations of Short-Chain Chlorinated Paraffin Emissions and Concentrations in Japan

Short-chain chlorinated paraffins (SCCPs) are persistent organic pollutants. In Japan, SCCPs are widely detected in the environment although the production and use of SCCPs have been banned. It is essential to estimate the amount and sources of SCCPs to implement countermeasures for SCCP emission. In this study, we estimated the emission and environmental concentrations of SCCP homologues in Japan from 1950 to 2050. Initially, the material flow of total SCCPs was estimated considering the material recycling process. The emission from each process during the entire life cycle of products containing SCCPs was estimated for each homologue. Volatilization factors of long-term-use products were specifically estimated from release factors and surface area, weight, and SCCP concentration of products containing SCCPs. The environmental concentrations were then estimated using the environmental fate model. In the material flow and emission estimation, parameter uncertainties, such as emission factors and SCCP application distribution, were considered, assuming each parameter follows a uniform distribution. The results of emission estimation suggested a decreasing trend of SCCP emission in recent years and continuation of this trend in the future. However, some emissions from long-term-use products may persist. In the future, products that have a long lifetime with closed-loop recycling, such as polyvinyl chloride wire-coating materials, are expected to significantly contribute to atmospheric emission. Moreover, recycled products may contain SCCPs. Based on the estimated concentration, the estimated water and sediment concentrations were within the range of the observed concentrations. Conversely, we could reduce the gap between the estimated and observed atmospheric SCCP concentrations compared with those in previous studies that did not consider the volatilization factor for each SCCP-containing product and material recycling process. However, a difference between the estimated and observed concentrations suggests that some unconsidered emission sources may exist that emit SCCPs into the atmosphere, such as SCCPs as impurities in medium-chain chlorinated paraffins, imported products containing SCCPs, and atmospheric advection from other countries. Hence, it is essential to calculate emissions from sources other than products that intentionally contain SCCPs produced in the past.

Exploring controls on perfluorocarboxylic acid (PFCA) gas-particle partitioning using a model with observational constraints.

The atmospheric fate of perfluorocarboxylic acids (PFCAs) has attracted much attention in recent decades due to the role of the atmosphere in global transport of these persistent chemicals. There is a gap in our understanding of gas-particle partitioning, limited by availability of reliable atmospheric measurements, partitioning properties, and models of gas-particle interactions. The gas-particle equilibrium phase partitioning of C2-C16 PFCAs in the atmosphere were modeled here by taking account of both deprotonation and phase partitioning equilibria among air, aerosol liquid water, and particulate water-insoluble organic matter using a range of available PFCA partitioning properties. We systematically varied water and organic matter content to simulate the full range of atmospheric conditions. Except in severe organic matter pollution episodes, shorter-chain PFCAs are predicted to mainly partition between air and aqueous phase, while for PFCAs with carbon chains longer than 12, organic matter is more likely to be the dominant particle phase reservoir. The model framework underestimated the particle fraction of C2-C8 PFCAs compared with several ambient observations, with larger discrepancies observed for longer-chain PFCAs. The discrepancy could result from externally mixed dust components, non-ideality of aerosol liquid water, surfactant descriptions at phase boundaries, and missed interactions between organic matter and charged PFCA molecules. Reliable measurements of ambient PFCAs with high time resolution and the measurement of uptake parameters by particle-relevant components will be beneficial to more reliable environmental fate modeling of ambient PFCAs.

Risk Assessment of Combined Exposures to Paddy Pesticides with an Environmental Fate Model

Risk Assessment of Combined Exposures to Paddy Pesticides with an Environmental Fate Model

GIS Atmospheric Chemical Fate Model Simulation of Iron Released from High Intensity Bombing in Northwestern Laos

The atmospheric dispersal of iron fragments ejected from detonated ordnance released within the Nam Souy sub-basin during the secret bombing campaign of Laos from 1965 ~ 1973 was simulated through python integration with ArcGIS. The data for the study was obtained from the US National Archives and shows that of a total of 7,667,619 weapons delivered in Laos (4.5 million tons), 19,005 (5,900 tons) were dropped within the study site. The simulation adapted Gaussian isotropic puff modeling for the dust/grain-sized fragments and explosive force radial release modeling for the larger fragments into python script to produce temporal raster output images of the dispersal patterns of the analyte. The use of code language libraries ArcPy, NumPy, and numba and the logic for their application is discussed and reported along with the script developed. The simulation produced 9 m2 resolution raster images displaying iron material loading at ground level. Loading density is reported at a range between 0 ~ 7.5 g/m2 washable iron load, 0 ~ 0.65 kg/m2 of suspended iron load, and 0 ~ 3.5 kg/m2 of bedded load. The results are intended for use in subsequent studies of surface removal over time with a potential application in exposure risk analysis and for the assessment of impact on natural environments.

Octanol/Air Partition Coefficient─A General-Purpose Fragment Model to Predict Log Koa from Molecular Structure.

The octanol/air partition coefficient Koa is important for assessing the bioconcentration of airborne xenobiotics in foliage and in air-breathing organisms. Moreover, Koa informs about compound partitioning to aerosols and indoor dust, and complements the octanol/water partition coefficient Kow and the air/water partition coefficient Kaw for multimedia fate modeling. Experimental log Koa at 25 °C has been collected from literature for 2161 compounds with molecular weights from 16 to 959 Da. The curated data set covers 18.2 log units (from -1.0 to 17.2). A newly developed fragment model for predicting log Koa from molecular structure outperforms COSMOtherm, EPI-Suite KOAWIN, OPERA, and linear solvation energy relationships (LSERs) regarding the root-mean-squared error (rms) and the maximum negative and positive errors (mne and mpe) (rms: 0.57 vs 0.86 vs 1.09 vs 1.19 vs 1.05-1.53, mne: -2.55 vs -3.95 vs -7.51 vs -7.54 vs (-5.63) - (-7.34), mpe: 2.91 vs 5.97 vs 7.54 vs 4.24 vs 6.89-10.2 log units). The prediction capability, statistical robustness, and sound mechanistic basis are demonstrated through initial separation into a training and prediction set (80:20%), mutual leave-50%-out validation, and target value scrambling in terms of temporarily wrong compound-Koa allocations. The new general-purpose model is implemented in a fully automatized form in the ChemProp software available to the public. Regarding Koa indirectly determined through Kow and Kaw, a new approach is developed to convert from wet to dry octanol, enabling higher consistency in experimental (and thus also predicted) Koa.

Adolescent problematic gaming and its association with maternal behaviors: A dyadic study focusing on the relational-emotional correlates

IntroductionAssociations between Problematic Gaming (PG) and the relational-emotional correlates of parenting have been reported in the literature. Previous research mostly collected information from adolescents, however, and suggested that little is known about the perceptions of parents and whether these are shared among parent-adolescent dyads. Therefore, this study aimed to (a) examine multiple informants’ reports of adolescent PG and maternal behaviors (i.e., warmth and indifference) and (b) disentangle the associations between the behaviors shared by mothers and adolescents from those unique to each member. MethodData were collected by using self-administered online questionnaires from 137 Italian mother-adolescent dyads in Italy. The mean age of adolescents (n = 92 males, n = 42 females, n = 3 nonbinary) was 14.68 (±1.25) years and that of mothers 47.48 (±4.69) years. Descriptive statistics and common fate model (CFM) analyses were conducted. ResultsMothers reported higher scores of their offspring’s PG. Within-reporter interclass correlations revealed positive associations between maternal indifference and adolescent PG for both informants. CFM indicated that correlations between maternal behaviors and adolescent PG based on shared perceptions did not reach statistical significance, whereas correlations based on unique mothers’ perceptions were statistically significant for all the observed relationships. ConclusionsIn the context of adolescent PG, mothers may have a heightened motivation to perceive their parenting as crucial. The multi-informant approach allows a more accurate examination of the associations between adolescent PG and maternal behaviors and underscores the need to consider discordant assessment of the same phenomenon between mothers and adolescents.

A dyadic analysis of parent and child pain catastrophizing and health-related quality of life in pediatric sickle cell disease.

The purpose of this study was to examine the dyadic and individual level effects of parent and child pain catastrophizing on child health-related quality of life (HRQOL) in pediatric sickle cell disease. Questionnaires assessing child pain frequency, child and parent pain catastrophizing, and child HRQOL were completed by youth and their primary caregiver. A Common Fate Model was estimated to test the dyadic level relationship between parent and child pain catastrophizing and child HRQOL. An Actor-Partner-Common Fate Model hybrid was estimated to test the relationship between child HRQOL and individual-level child pain catastrophizing and parent pain catastrophizing, respectively. In each model, child HRQOL was modelled as a dyadic variable by factoring parent and child ratings. Patients (N = 100, M age = 13.5 years, 61% female) and their caregivers (M age = 41.8 years, 86% mothers) participated. Dyad-level pain catastrophizing was negatively associated with child HRQOL, demonstrating a large effect (β = -0.809). Individual-level parent and child pain catastrophizing were each uniquely negatively associated with child HRQOL, demonstrating small to medium effects (β = -0.309, β = -0.270). Individual level effects were net of same-rater bias, which was significant for both parents and children. Both the unique and the overlapping aspects of parent and child pain catastrophizing are significant contributors to associations with child HRQOL, such that higher levels of pain catastrophizing are associated with worse child HRQOL. Findings suggest the need for multipronged intervention targeting factors common to parent-child dyads and factors unique to parents and children, respectively.

Development of a Harmonized Protocol for Measurement of Foliar Wash-off Parameters: First Results.

The foliar wash-off coefficient is a parameter used by environmental fate models to estimate the amount of chemical removed from leaf surfaces by rainfall. In the European Union it is used by FOCUS surface water models to estimate soil loadings following rainfall after leaf surfaces have been treated with plant protection products. Currently, a default value of 0.5/cm is assumed for this parameter, although there is provision to provide experimental data to replace this default. The European Food Safety Authority proposed to increase the default parameter value to 1.0/cm. This increases the need for experimental refinement studies. However, no guidance for a harmonized protocol exists to estimate this parameter. We describe the results of a ring-test conducted to start a process of developing a harmonized experimental protocol to measure the foliar wash-off parameters, conducted by several laboratories across Europe. The proposed design uses whole plants (rather than individual leaves) to retain as much realism as possible. The extent of wash-off is then determined by comparison of compound residues in two sets of plants (with and without a defined rainfall event) measured using a fully validated crop residue method. This initial ring test used tebuconazole (Folicur EW 250) sprayed at 100 g ai/ha onto tomato plants at BBCH25. Each laboratory measured the residues before and after a rainfall event of 20 mm/h for 1 h and calculated the percentage of wash-off from these data. There was good agreement across the eight participating laboratories with a mean percentage of wash-off of 66.8% and a 95% confidence interval of ±11.8%. Determination of robust wash-off parameters was therefore considered feasible using the proposed test design. Environ Toxicol Chem 2023;42:535-541. © 2022 SETAC.

Environmental fate and metabolism of the systemic triazolinthione fungicide prothioconazole in different aerobic soils

As a best-selling triazolinthione fungicide, prothioconazole (PTZ) has been widely used worldwide and has aroused concern about its environmental effect. This study used phenyl-UL-14C-labeled PTZ and an improved fate model to investigate the fate and metabolism of this fungicide in aerobic soil. During 120 d of incubation, PTZ rapidly transformed into metabolites and bound residues, with a half-life (DT50) of less than 1 d. After 120 d, approximately 45–55% of PTZ formed bound residues, and the extractable metabolite residues were gradually degraded over time. Approximately 19%, 44% and 27% of phenyl-UL-14C-PTZ was mineralized in red soil, fluvo-aquic soil and cinnamon soil, respectively, but only approximately 3% was mineralized in black soil. Five metabolites were identified and confirmed, and a possible metabolic pathway for phenyl-UL-14C-PTZ in soil was proposed. Based on the correlation analysis between soil properties and model rate constants, soil properties exerted important effects on PTZ transformation. These results will provide basic data for environmental risk assessments and removal of the PTZ pollutant and suggest that the soil type should be considered in the selection and application of pesticides.

A mechanism-based fate model of pesticide solutions on the plant surface under aerial application

ABSTRACT Pesticide residues on plant surfaces are a primary source of pesticide bioaccumulation in crops. In this context, we propose a mechanism-based model for understanding the pesticide fate on the plant surface following aerial application, taking into account fate modelling of the pesticide spray solution on the plant surface. Using chlorothalonil as an example, the simulation results revealed that the spray solution dissipated rapidly after aerial application, resulting in the formation of a saturated pesticide solution, which facilitated the diffusion process of the pesticide residue from the plant surface into the peel tissue. The proposed model generated higher simulated residue concentrations in the peel or pulp than the current model, owing to the proposed model’s assumption of rapid dissipation of the spray solution. This indicated that the proposed model specified the influence of the spray solution on the plant’s exposure to residues via the surface deposition pathway, whereas the current modelling approach presented a generic estimate of the residue dissipation on the plant surface that linked to the residue’s fate in the soil.

To put asunder: Are there perils of partialing in actor-partner interdependence models?

In research on couples, statistical adjustment (i.e., partialing) for correlations between partners' parallel scores is common and useful, as in the actor-partner interdependence model. Original and partialed scores are typically interpreted as assessing the same construct, but this may not be a valid assumption. Other approaches to nonindependence-such as common fate modeling-may better represent some couple constructs. This study of 300 couples utilized participants' interpersonal circumplex ratings of partners' typical behavior during marital interactions to evaluate the interpersonal meaning of unadjusted and partialed forms of the Marital Adjustment Test (MAT), a measure of overall relationship quality, and the Quality of Relationships Inventory-Support (QRI-S) and Conflict (QRI-C) scales, which measured perceived support from and conflict with the partner. After partialing partners' scores, MAT and QRI-S scores were substantially less closely associated with ratings of partners' warmth, their primary expected interpersonal correlates. Partner-partialed QRI-C scores were substantially less closely correlated with ratings of partners' hostility and were associated with a somewhat more controlling form of hostility. In contrast, partialing partners' trait optimism scores resulted in minimal changes in interpersonal correlates of this personality characteristic. Couple-level MAT, QRI-S, and QRI-C variables representing overlapping variance across partners while partialing unshared variance in spouses' scores (i.e., common fate scores) had highly similar interpersonal correlates when compared to unadjusted versions. Potential alterations in construct validity resulting from partialing partners' scores warrant interpretive caution, and alternative analytic frameworks (e.g., the common fate model) may better maintain the construct validity of some dyadic measures. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Generation of reproducible model freshwater particulate matter analogues to study the interaction with particulate contaminants

Aquatic fate models and risk assessment require experimental information on the potential of contaminants to interact with riverine suspended particulate matter (SPM). While for dissolved contaminants partition or sorption coefficients are used, the underlying assumption of chemical equilibrium is invalid for particulate contaminants, such as engineered nanomaterials, incidental nanoparticles, micro- or nanoplastics. Their interactions with SPM are governed by physicochemical forces between contaminant-particle and SPM surfaces. The availability of a standard SPM material is thus highly relevant for the development of reproducible test systems to evaluate the fate of particulate contaminants in aquatic systems. Finding suitable SPM analogues, however, is challenging considering the complex composition of natural SPM, which features floc-like structures comprising minerals and organic components from the molecular to the microorganism level. Complex composition comes with a heterogeneity in physicochemical surface properties, that cannot be neglected. We developed a procedure to generate SPM analogue flocs from components selected to represent the most abundant and crucial constituents of natural riverine SPM, and the process-relevant SPM surface characteristics regarding interactions with particulate contaminants. Four components, i.e., illite, hematite, quartz and tryptophan, combined at environmentally realistic mass-ratios, were associated to complex flocs. Flocculation was reproducible regarding floc size and fractal dimension, and multiple tests on floc resilience towards physical impacts (agitation, sedimentation-storage-resuspension, dilution) and hydrochemical changes (pH, electrolytes, dissolved organic matter concentration) confirmed their robustness. These reproducible, ready-to-use SPM analogue flocs will strongly support future research on emerging particulate contaminants.