Emissions of pharmaceuticals and plant protection products to the lagoon of Venice: development of a new emission inventory

Estimating the emissions of chemical pollutants to water is a fundamental step for the development and application of effective and sustainable management strategies of water resources, but methods applied so far to build chemicals inventories at the European or national scale show several limitations when applied at the local scale. The issue is particularly relevant when considering contaminants of emerging concern (CECs), whose environmental releases and occurrence are still poorly studied and understood. In this work, an approach to estimate water emissions of nine active pharmaceutical ingredients (APIs) and ten most applied plant protection products (PPPs) is presented, considering proxy indicators (e.g., sales data and census information). The application area is the lagoon of Venice (Italy), a complex transitional environment highly influenced by anthropic pressures (e.g., agricultural and industrial activities, animal breeding, and wastewater discharge). The presented approach can be tailored to the information available for any local scale case study. Data on annual regional sales of PPPs and APIs were integrated with georeferenced demographic and economic statistics (such as census and land-use information) to estimate chemicals emissions to surface water and groundwater. A sensitivity and uncertainty analysis identified the main factors affecting emissions estimates, and those contributing more significantly to results uncertainty. Results showed the highest estimated emissions of APIs for antibiotics (i.e., amoxicillin, clarithromycin, azithromycin, and ciprofloxacin) used for humans and animals, while most of hormones' emission (i.e., 17- α-ethinylestradiol and 17-β-estradiol) derived from animal breeding. Regarding PPPs, glyphosate and imidacloprid emissions were one to two orders of magnitude higher compared to the other chemicals. Uncertainty and sensitivity analysis showed that the variability of each parameter used to estimate emissions depends greatly both on the target chemical and the specific emission source considered. Excretion rates and removal during wastewater treatment were major key parameters for all the target pharmaceutical compounds, while for PPPs the key parameter was their loss into the natural waters after application.

Role of Physiologically Based Kinetic modelling in addressing environmental chemical mixtures - A review

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The availability and applicability of Physiologically Based Kinetic (PBK) models for mixtures is reviewed.

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PBK models can support risk assessment of mixtures by incorporating the toxicokinetic processes.

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Quantitative structure-activity relationship (QSAR) models can be used to fill data gaps in PBK modelling.

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PBK models for mixtures can be improved by including various types of interactions.

The role of Physiologically Based Kinetic (PBK) modelling in assessing mixture toxicology has been growing for the last three decades. It has been widely used to investigate and address interactions in mixtures. This review describes the current state-of-the-art of PBK models for chemical mixtures and to evaluate the applications of PBK modelling for mixtures with emphasis on their role in chemical risk assessment. A total of 35 mixture PBK models were included after searching web resources (Scopus, PubMed, Web of Science, and Google Scholar), screening for duplicates, and excluding articles based on eligibility criteria. Binary mixtures and volatile organic compounds accounted for two-thirds of the chemical mixtures identified. The most common exposure route and modelled system were found to be inhalation and rats respectively. Twenty two (22) models were for binary mixtures, 5 for ternary mixtures, 3 for quaternary mixtures, and 5 for complex mixtures. Both bottom-up and top-down PBK modelling approaches are described. Whereas bottom-up approaches are based on a series of binary interactions, top-down approaches are based on the lumping of mixture components. Competitive inhibition is the most common type of interaction among the various types of mixtures, and usually becomes a concern at concentrations higher than environmental exposure levels. It leads to reduced biotransformation that either means a decrease in the amount of toxic metabolite formation or an increase in toxic parent chemical accumulation. The consequence is either lower or higher toxicity compared to that estimated for the mixture based on the additivity principle. Therefore, PBK modelling can play a central role in predicting interactions in chemical mixture risk assessment.

Computational models for the assessment of manufactured nanomaterials: Development of model reporting standards and mapping of the model landscape

Different types of computational models have been developed for predicting the biokinetics, environmental fate, exposure levels and toxicological effects of chemicals and manufactured nanomaterials (MNs). However, these models are not described in a consistent manner in the scientific literature, which is one of the barriers to their broader use and acceptance, especially for regulatory purposes. Quantitative structure-activity relationships (QSARs) are in silico models based on the assumption that the activity of a substance is related to its chemical structure. These models can be used to provide information on (eco)toxicological effects in hazard assessment. In an environmental risk assessment, environmental exposure models can be used to estimate the predicted environmental concentration (PEC). In addition, physiologically based kinetic (PBK) models can be used in various ways to support a human health risk assessment. In this paper, we first propose model reporting templates for systematically and transparently describing models that could potentially be used to support regulatory risk assessments of MNs, for example under the REACH regulation. The model reporting templates include (a) the adaptation of the QSAR Model Reporting Format (QMRF) to report models for MNs, and (b) the development of a model reporting template for PBK and environmental exposure models applicable to MNs. Second, we show the usefulness of these templates to report different models, resulting in an overview of the landscape of available computational models for MNs.

Physiologically based mathematical models of nanomaterials for regulatory toxicology: A review

The development of physiologically based (PB) models to support safety assessments in the field of nanotechnology has grown steadily during the last decade. This review reports on the availability of PB models for toxicokinetic (TK) and toxicodynamic (TD) processes, including in vitro and in vivo dosimetry models applied to manufactured nanomaterials (MNs). In addition to reporting on the state-of-the-art in the scientific literature concerning the availability of physiologically based kinetic (PBK) models, we evaluate their relevance for regulatory applications, mainly considering the EU REACH regulation. First, we performed a literature search to identify all available PBK models. Then, we systematically reported the content of the identified papers in a tailored template to build a consistent inventory, thereby supporting model comparison. We also described model availability for physiologically based dynamic (PBD) and in vitro and in vivo dosimetry models according to the same template. For completeness, a number of classical toxicokinetic (CTK) models were also included in the inventory. The review describes the PBK model landscape applied to MNs on the basis of the type of MNs covered by the models, their stated applicability domain, the type of (nano-specific) inputs required, and the type of outputs generated. We identify the main assumptions made during model development that may influence the uncertainty in the final assessment, and we assess the REACH relevance of the available models within each model category. Finally, we compare the state of PB model acceptance for chemicals and for MNs. In general, PB model acceptance is limited by the absence of standardised reporting formats, psychological factors such as the complexity of the models, and technical considerations such as lack of blood:tissue partitioning data for model calibration/validation.

Grouping of nanomaterials to read-across hazard endpoints: from data collection to assessment of the grouping hypothesis by application of chemoinformatic techniques

BACKGROUND

An increasing number of manufactured nanomaterials (NMs) are being used in industrial products and need to be registered under the REACH legislation. The hazard characterisation of all these forms is not only technically challenging but resource and time demanding. The use of non-testing strategies like read-across is deemed essential to assure the assessment of all NMs in due time and at lower cost. The fact that read-across is based on the structural similarity of substances represents an additional difficulty for NMs as in general their structure is not unequivocally defined. In such a scenario, the identification of physicochemical properties affecting the hazard potential of NMs is crucial to define a grouping hypothesis and predict the toxicological hazards of similar NMs. In order to promote the read-across of NMs, ECHA has recently published "Recommendations for nanomaterials applicable to the guidance on QSARs and Grouping", but no practical examples were provided in the document. Due to the lack of publicly available data and the inherent difficulties of reading-across NMs, only a few examples of read-across of NMs can be found in the literature. This manuscript presents the first case study of the practical process of grouping and read-across of NMs following the workflow proposed by ECHA.

METHODS

The workflow proposed by ECHA was used and slightly modified to present the read-across case study. The Read-Across Assessment Framework (RAAF) was used to evaluate the uncertainties of a read-across within NMs. Chemoinformatic techniques were used to support the grouping hypothesis and identify key physicochemical properties.

RESULTS

A dataset of 6 nanoforms of TiO₂ with more than 100 physicochemical properties each was collected. In vitro comet assay result was selected as the endpoint to read-across due to data availability. A correlation between the presence of coating or large amounts of impurities and negative comet assay results was observed.

CONCLUSION

The workflow proposed by ECHA to read-across NMs was applied successfully. Chemoinformatic techniques were shown to provide key evidence for the assessment of the grouping hypothesis and the definition of similar NMs. The RAAF was found to be applicable to NMs.

Investigating cell type specific mechanisms contributing to acute oral toxicity

The replacement of animals in acute systemic toxicity testing remains a considerable challenge. Only animal data are currently accepted by regulators, including data generated by reduction and refinement methods. The development of Integrated Approaches to Testing and Assessment (IATA) is hampered by an insufficient understanding of the numerous toxicity pathways that lead to acute systemic toxicity. Therefore, central to our work has been the collection and evaluation of the mechanistic information on eight organs identified as relevant for acute systemic toxicity (nervous system, cardiovascular system, liver, kidney, lung, blood, gastrointestinal system and immune system). While the nervous and cardiovascular systems are the most frequent targets, no clear relationship emerged between specific mechanisms of target organ toxicity and the level (category) of toxicity. From a list of 114 chemicals with acute oral in vivo and in vitro data, 98 were identified with target organ specific effects, of which 93% were predicted as acutely toxic by the 3T3 neutral red uptake cytotoxicity assay and 6% as non-toxic. This analysis will help to prioritise the development of adverse outcome pathways for acute oral toxicity, which will support the assessment of chemicals using mechanistically informed IATA.

Improving the prediction of environmental fate of engineered nanomaterials by fractal modelling

A critical analysis of the available engineered nanomaterials (ENMs) environmental fate modelling approaches indicates that existing tools do not satisfactorily account for the complexities of nanoscale phenomena. Fractal modelling (FM) can complement existing kinetic fate models by including more accurate interpretations of shape and structure, density and collision efficiency parameters to better describe homo- and heteroaggregation. Pathways to including hierarchical symmetry concepts and a route to establishing a structural classification of nanomaterials based on FM are proposed.

The virtual cell based assay: Current status and future perspectives

In order to replace the use of animals in toxicity testing, there is a need to predict in vivo toxic doses from concentrations that cause toxicological effects in relevant in vitro systems. The Virtual Cell Based Assay (VCBA) estimates time-dependent concentration of a test chemical in the cell and cell culture for a given in vitro system. The concentrations in the different compartments of the cell and test system are derived from ordinary differential equations, physicochemical parameters of the test chemical and properties of the cell line. The VCBA has been developed for a range of cell lines including BALB/c 3T3 cells, HepG2, HepaRG, lung A459 cells, and cardiomyocytes. The model can be used to design and refine in vitro experiments and extrapolate in vitro effective concentrations to in vivo doses that can be applied in risk assessment. In this paper, we first discuss potential applications of the VCBA: i) design of in vitro High Throughput Screening (HTS) experiments; ii) hazard identification (based on acute systemic toxicity); and iii) risk assessment. Further extension of the VCBA is discussed in the second part, exploring potential application to i) manufactured nanomaterials, ii) additional cell lines and endpoints, and considering iii) other opportunities.

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VCBA as an alternative approach can be applied in the domain of nanotoxicology.

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VCBA can support better testing strategies in acute toxicity.

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Refinement of the VCBA taking into account biological oscillators could improve toxicity prediction.

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Extensions of the VCBA can capture effects related to additional subcellular compartments.

Modeling the influence of climate change on the mass balance of polychlorinated biphenyls in the Adriatic Sea

Climate forcing is forecasted to influence the Adriatic Sea region in a variety of ways, including increasing temperature, and affecting wind speeds, marine currents, precipitation and water salinity. The Adriatic Sea is intensively developed with agriculture, industry, and port activities that introduce pollutants to the environment. Here, we developed and applied a Level III fugacity model for the Adriatic Sea to estimate the current mass balance of polychlorinated biphenyls in the Sea, and to examine the effects of a climate change scenario on the distribution of these pollutants. The model's performance was evaluated for three PCB congeners against measured concentrations in the region using environmental parameters estimated from the 20th century climate scenario described in the Special Report on Emission Scenarios (SRES) by the IPCC, and using Monte Carlo uncertainty analysis. We find that modeled fugacities of PCBs in air, water and sediment of the Adriatic are in good agreement with observations. The model indicates that PCBs in the Adriatic Sea are closely coupled with the atmosphere, which acts as a net source to the water column. We used model experiments to assess the influence of changes in temperature, wind speed, precipitation, marine currents, particulate organic carbon and air inflow concentrations forecast in the IPCC A1B climate change scenario on the mass balance of PCBs in the Sea. Assuming an identical PCBs' emission profile (e.g. use pattern, treatment/disposal of stockpiles, mode of entry), modeled fugacities of PCBs in the Adriatic Sea under the A1B climate scenario are higher because higher temperatures reduce the fugacity capacity of air, water and sediments, and because diffusive sources to the air are stronger.

Modeling the global levels and distribution of polychlorinated biphenyls in air under a climate change scenario

We used the multimedia chemical fate model BETR Global to evaluate changes in the global distribution of two polychlorinated biphenyls, PCB 28 and PCB 153, under the influence of climate change. This was achieved by defining two climate scenarios based on results from a general circulation model, one scenario representing the last twenty years of the 20th century (20CE scenario) and another representing the global climate under the assumption of strong future greenhouse gas emissions (A2 scenario). The two climate scenarios are defined by four groups of environmental parameters: (1) temperature in the planetary boundary layer and the free atmosphere, (2) wind speeds and directions in the atmosphere, (3) current velocities and directions in the surface mixed layer of the oceans, and (4) rate and geographical pattern of precipitation. As a fifth parameter in our scenarios, we considerthe effect of temperature on primary volatilization emissions of PCBs. Comparison of dynamic model results using environmental parameters from the 20CE scenario against historical long-term monitoring data of concentrations of PCB 28 and PCB 153 in air from 16 different sites shows satisfactory agreement between modeled and measured PCBs concentrations. The 20CE scenario and A2 scenario were compared using steady-state calculations and assuming the same source characteristics of PCBs. Temperature differences between the two scenarios is the dominant factor that determines the difference in PCB concentrations in air. The higher temperatures in the A2 scenario drive increased primary and secondary volatilization emissions of PCBs, and enhance transport from temperate regions to the Arctic. The largest relative increase in concentrations of both PCB congeners in air under the A2 scenario occurs in the high Arctic and the remote Pacific Ocean. Generally, higher wind speeds under the A2 scenario result in more efficient intercontinental transport of PCB 28 and PCB 153 compared to the 20CE scenario. Our modeling indicates that in a future impacted by climate change, we can expectincreased volatilization emissions and increased mobility of persistent organic pollutants with properties similar to those of PCBs.

Introducing an integrated climate change perspective in POPs modelling, monitoring and regulation

This paper presents a review on the implications of climate change on the monitoring, modelling and regulation of persistent organic pollutants (POPs). Current research gaps are also identified and discussed. Long-term data sets are essential to identify relationships between climate fluctuations and changes in chemical species distribution. Reconstructing the influence of climatic changes on POPs environmental behaviour is very challenging in some local studies, and some insights can be obtained by the few available dated sediment cores or by studying POPs response to inter-annual climate fluctuations. Knowledge gaps and future projections can be studied by developing and applying various modelling tools, identifying compounds susceptibility to climate change, local and global effects, orienting international policies. Long-term monitoring strategies and modelling exercises taking into account climate change should be considered when devising new regulatory plans in chemicals management.