A new twist on an old regression: transfer of chemicals to beef and milk in human and ecological risk assessment

Transfer of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) from oral exposure into cow's milk - part II: toxicokinetic predictive models for risk assessment

Understanding the transfer of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) as well as polychlorinated biphenyls (PCBs) from oral exposure into cow's milk is not purely an experimental endeavour, as it has produced a large corpus of theoretical work. This work consists of a variety of predictive toxicokinetic models in the realms of health and environmental risk assessment and risk management. Their purpose is to provide mathematical predictive tools to organise and integrate knowledge on the absorption, distribution, metabolism and excretion processes. Toxicokinetic models are based on more than 50 years of transfer studies summarised in part I of this review series. Here in part II, several of these models are described and systematically classified with a focus on their applicability to risk analysis as well as their limitations. This part of the review highlights the opportunities and challenges along the way towards accurate, congener-specific predictive models applicable to changing animal breeds and husbandry conditions.

Transfer of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) from oral exposure into cow's milk - Part I: state of knowledge and uncertainties

Polychlorinated dibenzo-para-dioxins (PCDDs) and dibenzofurans (PCDFs) (collectively and colloquially referred to as 'dioxins') as well as polychlorinated biphenyls (PCBs) are persistent and ubiquitous environmental contaminants that may unintentionally enter and accumulate along the food chain. Owing to their chronic toxic effects in humans and bioaccumulative properties, their presence in feed and food requires particular attention. One important exposure pathway for consumers is consumption of milk and dairy products. Their transfer from feed to milk has been studied for the past 50 years to quantify the uptake and elimination kinetics. We extracted transfer parameters (transfer rate, transfer factor, biotransfer factor and elimination half-lives) in a machine-readable format from seventy-six primary and twenty-nine secondary literature items. Kinetic data for some toxicologically relevant dioxin congeners and the elimination half-lives of dioxin-like PCBs are still not available. A well-defined selection of transfer parameters from literature was statistically analysed and shown to display high variability. To understand this variability, we discuss the data with an emphasis on influencing factors, such as experimental conditions, cow performance parameters and metabolic state. While no universal interpretation could be derived, a tendency for increased transfer into milk is apparently connected to an increase in milk yield and milk fat yield as well as during times of body fat mobilisation, for example during the negative energy balance after calving. Over the past decades, milk yield has increased to over 40 kg/d during high lactation, so more research is needed on how this impacts feed to food transfer for PCDD/Fs and PCBs.

Explore the Dosimetric Relationship between the Intake of Chemical Contaminants and Their Occurrence in Blood and Urine

The dosimetric relationship between the human intake dose of a chemical contaminant (an "external dose") and its concentrations in bodily fluids such as blood and urine (related to an "internal dose"), often characterized by a dose-to-concentration ratio, has critical applications in exposure science, toxicology, and risk assessment, especially in the "new approach methods" era. However, there is a lack of a mechanistic, systematic understanding of how such a dosimetric relationship depends on fundamental chemical properties, such as partition coefficients and biotransformation half-lives. Here, we investigate this issue using a well-evaluated toxicokinetic model, which links external and internal doses by quantifying the absorption and elimination of chemicals. Results are visualized in a series of chemical partitioning space plots, whereby a chemical's dose-to-concentration ratio can be approximately predicted based on its partitioning between air, water, and octanol phases. Our results indicate that when taken in equal doses, chemicals with low volatility and moderate to high hydrophobicity exhibit the highest concentrations in the blood, and chemicals undergoing significant biotransformation tend to exhibit lower concentrations in comparison to their counterparts undergoing negligible biotransformation but possessing similar partitioning properties. Chemicals with high hydrophilicity have the highest concentrations in urine. Such revealed property dependence is similar for both adults and children and for individuals with normal body weights and with obesity. Overall, insights gained from this study are important in predicting blood and urinary concentrations from exposure information and in determining the exposure rate that produces the blood or urinary concentrations observed in biomonitoring studies.

Current knowledge on urease and nitrification inhibitors technology and their safety

OBJECTIVE

Urea is one of the most widely used commercial fertilisers worldwide due to its high N density and cost effectiveness. However, it can be lost in the form of gaseous ammonia and other greenhouse gas (GHG) emissions which can potentially lead to environmental pollution. Farmers are compelled to apply more urea to account for those losses, thereby increasing their expenditure on fertilization. The objective of this paper is to present a literature review on current knowledge regarding inhibitor technologies such as urease inhibitor; n-(N-butyl) thiophosphoric triamide (NBPT), and nitrification inhibitor; dicyandiamide (DCD).

METHODS

A thorough review of all the scientific literature was carried out and a proposed risk assessment framework developed.

RESULTS

The study showed that the urease inhibitor NBPT significantly reduced NH3 loss from urea. However, concerns about NBPT safety to human health had been raised when the nitrification inhibitor DCD appeared as a residue in milk. This article presents a risk assessment framework for evaluating human exposure to chemicals like NBPT or DCD, following the consumption of foods of animal origin (e.g. milk) from cows grazing on inhibitor-treated pasture.

CONCLUSION

The EU's target of a 40% reduction of greenhouse gas emissions by 2030 can be aided by using NBPT as part of an overall suite of solutions. A comprehensive risk assessment is advised for effective evaluation of potential risks from exposure to these inhibitors.

Average transfer factors are not enough: The influence of growing cattle physiology on the transfer rate of polychlorinated biphenyls from feed to adipose

Food of animal origin accounts for >90% of the overall human exposure to polychlorinated biphenyls (PCBs). Food regulatory maximum levels help to control this exposure, but bovine meat has been found to be prone to exceed those occasionally. In order to ensure the chemical safety of bovine meat, the aim was to explore the dependency of the bioconcentration (BCF) and biotransfer (BTF) factor, and assimilation efficiency (AE) of PCBs on carcass lipid proportion and growth rate of beef cattle. Eleven bulls were fattened for 293 days with three different diets (7.0, 7.4, 7.5 MJ net energy for growth kg^-1 dry matter) at PCB background levels, until slaughter at 530 or 600 kg body weight. Feed and perirenal adipose tissue were sampled for PCB analyses via GC/HRMS and carcass lipid proportion was estimated by the 11^th rib dissection technique. For all tested PCBs, BCF (ranging from 0.7 to 18.4) and BTF (ranging from 0.1 to 2.7) decreased at least 1.5 up to 10.6-fold when the carcass lipid proportion increased by 4%, resulting from a typical dilution process. For a faster growth rate of 0.18 kg d^-1 however, only a non-significant increasing trend in transfer factors (1.1 to 2.1-fold) was seen. Besides, the transfer factors increased with PCB chlorination degree, non-ortho substitution and lipophilicity. These results underpin the complex interaction between animal physiology and PCB physicochemical properties, making it challenging to interpret average transfer factors to support chemical risk assessment and management.

Risk assessment of contaminants of emerging concern in the context of wastewater reuse for irrigation: An integrated modelling approach

Direct reuse of reclaimed wastewater (RWW) in agriculture has recently received increasing attention as a possible solution to water scarcity. The presence of contaminants of emerging concern (CECs) in RWW can be critical, as these chemicals can be uptaken in irrigated crops and eventually ingested during food consumption. In the present study, an integrated model was developed to predict the fate of CECs in water reuse systems where RWW is used for edible crops irrigation. The model was applied to a case study where RWW (originating from a municipal wastewater treatment plant) is discharged into a water channel, with subsequent irrigation of silage maize, rice, wheat and ryegrass. Environmental and human health risks were assessed for 13 CECs, selected based on their chemical and hazard characteristics. Predicted CEC concentrations in the channel showed good agreement with available measurements, indicating potential ecotoxicity of some CECs (estrogens and biocides) due to their limited attenuation. Plant uptake predictions were in good agreement with existing literature data, indicating higher uptake in leaves and roots than fruits. Notably, high uncertainties were shown for weakly acidic CECs, possibly due to degradation in soil and pH variations inside plants. The human health risk due to the ingestion of wheat and rice was assessed using the threshold of toxicological concern and the hazard quotient. Both approaches predicted negligible risk for most CECs, while sulfamethoxazole and 17α-ethinylestradiol exhibited the highest risk for consumers. Alternative scenarios were evaluated to identify possible risk minimization strategies (e.g., adoption of a more efficient irrigation system).

Quantitative risk assessment of antimicrobials in biosolids applied on agricultural land and potential translocation into food

The use of biosolids as a fertiliser may be an indirect route for contaminants into the food chain. One of the main concerns regarding the spreading of biosolids on agricultural land is the potential uptake of contaminants into plants which may bio-transfer into grazing animals that supply the food chain directly (e.g. meat and milk) and hence are subsequently consumed. The aim of this project was to create a quantitative risk assessment model to estimate the fate and translocation of triclosan (TCS) and triclocarban (TCC) into the feed (grass) and food chain with subsequent human exposure. The model's results indicate that TCS and TCC have low potential to transfer into milk and beef following the ingestion of contaminated grass by dairy cows. Mean estimated TCS and TCC residues in milk and beef show that TCC had the greatest concentration (mean values of 7.77×10^-6mgkg^-1 in milk and 1.36×10^-4mgkg^-1 in beef). Human exposure results show that TCC was greater for milk consumption in infants (1-4years) (mean value 1.14×10^-7mgkg^-1bwd^-1) and for beef consumption by teens (12-17years) (mean value 6.87×10^-8mgkg^-1bwd^-1). Concentrations of TCS and TCC were well below the estimated acceptable daily intake (ADI). Human health risk was estimated by evaluation of the hazard quotient (HQ), which used the NOAEL as a toxicity endpoint, combined with milk and beef human exposure estimates. HQ results show that all values were <0.01 (no existing risk). A sensitivity analysis revealed that the K_ow and initial concentration in biosolids as the parameters of greatest importance (correlation coefficients 0.91 and 0.19, respectively). This highlights the importance of physio-chemical properties of the compounds and their detection in biosolids post wastewater treatment along with their persistence in soil following application. This model is a valuable tool in which to ascertain the potential transfer of contaminants in the environment into animal forage with knock on consequences for exposure through the human food chain.

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K _OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K _OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

Risk assessment of persistent pharmaceuticals in biosolids: Dealing with uncertainty

A screening-level risk assessment of biosolids-borne PPCPs in agricultural scenarios was developed in this work. While several of these compounds are efficiently removed in sewage treatment plants (STPs), others are recalcitrant to degradation and can be found in sludge at significant levels. As the rate of biosolids reuse for fertilising and/or amendment purposes is increasing, it is necessary to evaluate the fate in soil and possible biotransfer of this type of pollutants in the long-term. The study includes six compounds that were selected considering data availability, presence in sludge and persistence. Due to the scarce data still present in literature, a probabilistic assessment to address uncertainty was developed. A 95th percentile of the hazard index (HI) exceeding 1 was obtained, with main contributions of triclosan and carbamazepine. Although these estimates were obtained under a worst-case approach, and that they can vary depending on scenario characteristics, they change the least-concern classification associated to the presence of PPCPs in biosolids. A sensitivity analysis indicates the high influence of application rate and sludge concentration level on the results. Thus, the importance of developing new strategies of removal in advanced STPs and the establishment of a specific biosolids reuse regulation including this type of compounds acquires an added significance.

Assessment and improvement of biotransfer models to cow's milk and beef used in exposure assessment tools for organic pollutants

The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow's milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.

Performance of the CalTOX fate and exposure model in a case study for a dioxin-contaminated site

Soil with high levels of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) is found at contaminated sites all over the world. Transfer of PCDD/Fs from contaminated soil to the food chain could lead to elevated human exposure. As a complement to available monitoring data, multimedia fate and exposure modeling can be applied to support risk assessment of sites with PCDD/F contaminated soil. In this study, we evaluated the performance of the CalTOX fate and exposure model for 2,3,7,8-substituted PCDD/Fs against measured concentrations in air, soil, grass, carrots, potatoes, milk, meat, and eggs from a contaminated site in northern Sweden. The calculated total toxic equivalent (TEQ) concentrations agree with measurements within a factor of 10 for all exposure media but one. Results for individual congeners demonstrated that the model did not always perform well at describing key processes that mobilize PCDD/Fs out of soils, such as transfer into root crops and ingestion of soil by chickens. Uncertainty in only a small subset of input parameters affects the model output. Improved information and models describing transfer of soil particles onto leafy vegetation by rain splash and biotransfer factors for PCDD/Fs to milk, meat, and eggs are particular research needs to reduce uncertainties in model-based assessments.

Assessment of plant uptake models used in exposure assessment tools for soils contaminated with organic pollutants

The aim of this study was to evaluate and improve the accuracy of plant uptake models for neutral hydrophobic organic pollutants (1 < logK(OW) < 9, -8 < logK(AW) < 0) used in regulatory exposure assessment tools, using uncertainty and sensitivity analyses. The models considered were RAIDAR, EUSES, CSOIL, CLEA, and CalTOX. In this research, CSOIL demonstrated the best performance of all five exposure assessment tools for root uptake from polluted soil in comparison with observed data, but no model predicted shoot uptake well. Recalibration of the transpiration and volatilisation parameters improved the performance of CSOIL and CLEA. The dominant pathway for shoot uptake simulated differed according to the properties of the chemical under consideration; those with a higher air-water partition coefficient were transported into shoots via the soil-air-plant pathway, while chemicals with a lower octanol-water partition coefficient and air-water partition coefficient were transported via the root. The soil organic carbon content was a particularly sensitive parameter in each model and using a site specific value improved model performance.

Quantitative modelling to estimate the transfer of pharmaceuticals through the food production system

Use of pharmaceuticals in animal production may cause an indirect route of contamination of food products of animal origin. This study aimed to assess, through mathematical modelling, the transfer of pharmaceuticals from contaminated soil, through plant uptake, into the dairy food production chain. The scenarios, model parameters, and values refer to contaminants in emission slurry production, storage time, immission into soil, plant uptake, bioaccumulation in the animal's body, and transfer to meat and milk. Modelling results confirm the possibility of contamination of dairy cow's meat and milk due the ingestion of contaminated feed by the cattle. The estimated concentration of pharmaceutical residues obtained for meat ranged from 0 to 6 ng kg(-1) for oxytetracycline, from 0.011 to 0.181 μg kg(-1) for sulfamethoxazole, and from 4.70 to 11.86 μg kg(-1) for ketoconazole. The estimated concentrations for milk were: zero for oxytetracycline, lower than 40 ng L(-1) for sulfamethoxazole, and from 0.98 to 2.48 μg L(-1) for ketoconazole. Results obtained for the three selected pharmaceuticals indicate a minor risk for human health. This study showed that supply chain modelling could be an effective tool in assessing the indirect contamination of feedstuff and animal products by residues of pharmaceuticals. The model can easily be adjusted to other contaminants and supply chain and, in this way, present a valuable tool to underpin decision making.

Spatially explicit prioritization of human antibiotics and antineoplastics in Europe

This paper presents a screening tool for the location-specific prioritization of human pharmaceutical emissions in Europe, based on risk quotients for the aquatic environment and human health. The tool provides direction towards either monitoring activities or additional research. Its application is illustrated for a set of 11 human antibiotics and 7 antineoplastics. Risk quotients for the aquatic environment were highest for levofloxacin, doxycycline and ciprofloxacin, located in Northern Italy (Milan region; particularly levofloxacin) and other densely populated areas in Europe (e.g. London, Krakow and the Ruhr area). Risk quotients for human health not only depend on pharmaceutical and location, but also on behavioral characteristics, such as consumption patterns. Infants in eastern Spain that consume locally produced food and conventionally treated drinking water were predicted to run the highest risks. A limited comparison with measured concentrations in surface water showed that predicted and measured concentrations are approximately within one order of magnitude.

Assessing model uncertainty of bioaccumulation models by combining chemical space visualization with a process-based diagnostic approach

As models describing human exposure to organic chemicals gain wider use in chemical risk assessment and management, it becomes important to understand their uncertainty. Although evaluation of parameter sensitivity/uncertainty is increasingly common, model uncertainty is rarely assessed. When it is, the assessment is generally limited to a handful of chemicals. In this study, a strategy for more comprehensive model uncertainty assessment was developed. A regulatory model (EUSES) was compared with a research model based on more recent science. Predicted human intake was used as the model end point. Chemical space visualization techniques showed that the extent of disagreement between the models varied strongly with chemical partitioning properties. For each region of disagreement, the primary human exposure vector was determined. The differences between the models' process algorithms describing these exposure vectors were identified and evaluated. The equilibrium assumption for root crops in EUSES caused overestimations in daily intake of superhydrophobic chemicals (log K(OW) > 11, log K(OA) > 10), whereas EUSES's approach to calculating bioaccumulation in fish prey resulted in underestimations for hydrophobic compounds (log K(OW) ∼ 6-8). Uptake of hydrophilic chemicals from soil and bioaccumulation of superhydrophobic chemicals in zooplankton were identified as important research areas to enable further reduction of model uncertainty in bioaccumulation models.

CKow: a dynamic model for chemical transfer to meat and milk

The objective of this study is to increase the understanding and transparency of chemical biotransfer modeling into meat and milk and explicitly confront the uncertainties in exposure assessments of chemicals that require such estimates. In cumulative exposure assessments that include food pathways, much of the overall uncertainty is attributable to the estimation of transfer into biota and through food webs. Currently, the most commonly used meat and milk-biotransfer models date back two decades and, in spite of their widespread use in multimedia exposure models, few attempts have been made to advance or improve the outdated and highly uncertain K(ow) regressions used in these models. Furthermore, in the range of K(ow) where meat and milk become the dominant human exposure pathways, these models often provide unrealistic rates and do not properly reflect the transfer dynamics. To address these issues, we developed a dynamic three-compartment cow model (called CKow), distinguishing lactating and nonlactating cows. For chemicals without available overall removal rates in the cow, a correlation is derived from measured values reported in the literature to predict this parameter from K(ow). Results on carry over rates (COR) and biotransfer factors (BTF) demonstrate that a steady-state ratio between animal intake and meat concentrations is almost never reached. For meat, empirical data collected on short-term experiments need to be adjusted to provide estimates of average longer term behaviors. The performance of the new model in matching measurements is improved relative to existing models-thus reducing uncertainty. The CKow model is straightforward to apply at steady state for milk and dynamically for realistic exposure durations for meat COR.