Challenges and opportunities when moving food production and consumption toward sustainable diets in the Nordics: a scoping review for Nordic Nutrition Recommendations 2023.

The terms 'Nordic countries' or 'The Nordics' include the five countries Denmark, Finland, Island, Norway, and Sweden. This review includes evaluation of the Nordic countries against Food and Agricultural Organisation (FAO)/World Health Organizations' (WHO) guiding principles for healthy, sustainable diets with respect to environmental impact (principles #9 - #13) and sociocultural aspects (principles #14 - #16). A food systems perspective is taken to summarize and discuss the most important challenges and opportunities for achieving sustainable diets. Food system, food security, self-sufficiency, and resilience perspectives are applied. The information can underpin decisions when developing and implementing Food Based Dietary Guidelines (FBDG) in the Nordics. None of the Nordic countries are on track to reach the 2030 UN climate and biodiversity goals. We describe how food production, processing, and consumption contribute to these and other environmental challenges, and what kinds of dietary changes/transitions consistent with these goals are required. A major challenge is the high production and consumption of meat and too low consumption of fish, vegetables, and fruits. Meat production is a major source of emissions and, together with farmed fish, heavily dependent on imported feed ingredients, leaving a large land-use and water footprint in exporting countries while domestic land resources are not used optimally. Dietary patterns have changed drastically over the past 50 years, and in large parts of the population, meat consumption has doubled since the 1970s, rendering historic food culture less useful as a basis for present-day recommendations. The Nordics have Europe's lowest use of antibiotics in animal and fish production and have made some progress in reducing food waste along the food chain. A major opportunity is better alignment of food production and consumption based on local or regional production potentials, in conjunction with better and more constructive integration with the global food system while integrating novel technologies to reduce emissions and resource use.

Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive Effects.

Chemical points of departure (PODs) for critical health effects are crucial for evaluating and managing human health risks and impacts from exposure. However, PODs are unavailable for most chemicals in commerce due to a lack of in vivo toxicity data. We therefore developed a two-stage machine learning (ML) framework to predict human-equivalent PODs for oral exposure to organic chemicals based on chemical structure. Utilizing ML-based predictions for structural/physical/chemical/toxicological properties from OPERA 2.9 as features (Stage 1), ML models using random forest regression were trained with human-equivalent PODs derived from in vivo data sets for general noncancer effects (n = 1,791) and reproductive/developmental effects (n = 2,228), with robust cross-validation for feature selection and estimating generalization errors (Stage 2). These two-stage models accurately predicted PODs for both effect categories with cross-validation-based root-mean-squared errors less than an order of magnitude. We then applied one or both models to 34,046 chemicals expected to be in the environment, revealing several thousand chemicals of moderate concern and several hundred chemicals of high concern for health effects at estimated median population exposure levels. Further application can expand by orders of magnitude the coverage of organic chemicals that can be evaluated for their human health risks and impacts.

Probabilistic Reference and 10% Effect Concentrations for Characterizing Inhalation Non-cancer and Developmental/Reproductive Effects for 2,160 Substances.

Chemicals assessment and management frameworks rely on regulatory toxicity values, which are based on points of departure (POD) identified following rigorous dose-response assessments. Yet, regulatory PODs and toxicity values for inhalation exposure (i.e., reference concentrations [RfCs]) are available for only ∼200 chemicals. To address this gap, we applied a workflow to determine surrogate inhalation route PODs and corresponding toxicity values, where regulatory assessments are lacking. We curated and selected inhalation in vivo data from the U.S. EPA's ToxValDB and adjusted reported effect values to chronic human equivalent benchmark concentrations (BMCh) following the WHO/IPCS framework. Using ToxValDB chemicals with existing PODs associated with regulatory toxicity values, we found that the 25th %-ile of a chemical's BMCh distribution (PODp25BMCh) could serve as a suitable surrogate for regulatory PODs (Q2 ≥ 0.76, RSE ≤ 0.82 log10 units). We applied this approach to derive PODp25BMCh for 2,095 substances with general non-cancer toxicity effects and 638 substances with reproductive/developmental toxicity effects, yielding a total coverage of 2,160 substances. From these PODp25BMCh, we derived probabilistic RfCs and human population effect concentrations. With this work, we have expanded the number of chemicals with toxicity values available, thereby enabling a much broader coverage for inhalation risk and impact assessment.

Quantifying pesticide emissions for drift deposition in comparative risk and impact assessment.

Estimating emissions of chemical pesticides used in agriculture is an essential component in evaluating the potential toxicity-related impacts on humans and ecosystems in various comparative risk and impact assessment frameworks, such as life cycle assessment, environmental footprinting, absolute environmental sustainability assessment, chemical substitution, and risk prioritization. Emissions related to drift deposition-usually derived from drift experiments-can reach non-target areas, and vary as a function of crop characteristics and application technique. We derive cumulative drift deposition fractions for a wide range of experimental drift functions for use in comparative and mass-balanced approaches. We clarify that cumulative drift deposition fractions require to integrate the underlying drift functions over the relevant deposition area and to correct for the ratio of deposition area to treated field area to arrive at overall mass deposited per unit mass of applied pesticide. Our results show that for most crops, drift deposition fractions from pesticide application are below 0.03 (i.e. 3% of applied mass), except for grapes and fruit trees, where drift fractions can reach 5% when using canon or air blast sprayers. Notably, aerial applications on soybeans can result in significantly higher drift deposition fractions, ranging from 20% to 60%. Additionally, varying the nozzle position can lead to a factor of five differences in pesticide deposition, and establishing buffer zones can effectively reduce drift deposition. To address remaining limitations in deriving cumulative drift deposition fractions, we discuss possible alternative modelling approaches. Our proposed approach can be implemented in different quantitative and comparative assessment frameworks that require emission estimates of agricultural pesticides, in support of reducing chemical pollution and related impacts on human health and the environment.

Near-field exposures and human health impacts for organic chemicals in interior paints: A high-throughput screening.

Interior paints contain organic chemicals that might be harmful to painters and building residents. This study aims to develop a high-throughput approach to screen near-field human exposures and health impacts related to organic chemicals in interior paints. We developed mass balance models for both water- and solvent-based paints, predicting emissions during wet and dry phases. We then screened exposures and risks, focusing on Sri Lanka where residential houses are frequently repainted. These models accurately predict paint drying time and indoor air concentrations of organic chemicals. Exposures of both painter and household resident were estimated for 65 organic chemicals in water-based and 26 in solvent-based paints, considering 12 solvents. Chemicals of concerns (CoCs) were identified, and maximum acceptable chemical contents (MACs) were calculated. Water-based paints generally pose lower health risks than solvent-based paints but might contain biocides of high concern. The total human health impact of one painting event on all household adults ranges from 1.5 × 10-3 to 2.1 × 10-2 DALYs for solvent-based paints, and from 4.1 × 10-4 to 9.5 × 10-3 DALYs for water-based paints. The present approach is a promising way to support the formulation of safer paint, and is integrated in the USEtox scientific consensus model for use in life cycle assessment, chemical substitution and risk screening.

Potential for Machine Learning to Address Data Gaps in Human Toxicity and Ecotoxicity Characterization.

Machine Learning (ML) is increasingly applied to fill data gaps in assessments to quantify impacts associated with chemical emissions and chemicals in products. However, the systematic application of ML-based approaches to fill chemical data gaps is still limited, and their potential for addressing a wide range of chemicals is unknown. We prioritized chemical-related parameters for chemical toxicity characterization to inform ML model development based on two criteria: (1) each parameter's relevance to robustly characterize chemical toxicity described by the uncertainty in characterization results attributable to each parameter and (2) the potential for ML-based approaches to predict parameter values for a wide range of chemicals described by the availability of chemicals with measured parameter data. We prioritized 13 out of 38 parameters for developing ML-based approaches, while flagging another nine with critical data gaps. For all prioritized parameters, we performed a chemical space analysis to assess further the potential for ML-based approaches to predict data for diverse chemicals considering the structural diversity of available measured data, showing that ML-based approaches can potentially predict 8-46% of marketed chemicals based on 1-10% with available measured data. Our results can systematically inform future ML model development efforts to address data gaps in chemical toxicity characterization.

Including the bioconcentration of pesticide metabolites in plant uptake modeling.

Although several models of pesticide uptake into plants are available, there are few modeling studies on the bioconcentration of metabolites in plants. Ignoring metabolites in plant uptake models can result in an underestimation of the parent compound's overall impacts on human health associated with pesticide residues in harvested food crops. To address this limitation, we offer a metabolite-based plant uptake model to predict the bioconcentration of the parent compound and its metabolites in plants. We used the uptake of glyphosate and its major metabolite (aminomethylphosphonic acid, AMPA) into potato as an example. The analysis of variability revealed that soil properties (affecting the soil sorption coefficient), dissipation half-life in soil, and metabolic half-life in the potato had a significant impact on the simulated AMPA concentration in the potato, indicating that regional variability could be generated in the plant bioconcentration process of metabolites. The proposed model was further compared using the non-metabolite model. The findings of the comparison suggested that the non-metabolite model, which is integrated with the AMPA bioconcentration process, can predict the AMPA concentration in the potato similarly to the proposed model. In conclusion, we provide insight into the bioconcentration process of metabolites in tuber plants from a modeling viewpoint, with some crucial model inputs, such as biotransformation and metabolic rate constants, requiring confirmation in future studies. The modeling demonstration emphasizes that it is relevant to consider bioaccumulation of metabolites, which can propagate further into increased overall residues of harmful compounds, especially in cases where metabolites have higher toxicity effect potency than their respective parent compounds.

To Split or Not to Split: Characterizing Chemical Pollution Impacts in Aquatic Ecosystems with Species Sensitivity Distributions for Specific Taxonomic Groups.

Bridging applied ecology and ecotoxicology is key to protect ecosystems. These disciplines show a mismatch, especially when evaluating pressures. Contrasting to applied ecology, ecotoxicological impacts are often characterized for whole species assemblages based on Species Sensitivity Distributions (SSDs). SSDs are statistical models describing per chemical across-species sensitivity variation based on laboratory toxicity tests. To assist in the aligning of the disciplines and improve decision-support uses of SSDs, we investigate taxonomic-group-specific SSDs for algae/cyanobacteria/aquatic plants, invertebrates, and vertebrates for 180 chemicals with sufficient test data. We show that splitting improves pollution impact assessments for chemicals with a specific mode of action and, surprisingly, for narcotic chemicals. We provide a framework for splitting SSDs that can be applied to serve in environmental protection, life cycle assessment, and management of freshwater ecosystems. We illustrate that using split SSDs has potentially large implications for the decision-support of SSD-based outputs around the globe.

Micro- and nanoplastics in soil: Linking sources to damage on soil ecosystem services in life cycle assessment.

Soil ecosystems are crucial for providing vital ecosystem services (ES), and are increasingly pressured by the intensification and expansion of human activities, leading to potentially harmful consequences for their related ES provision. Micro- and nanoplastics (MNPs), associated with releases from various human activities, have become prevalent in various soil ecosystems and pose a global threat. Life Cycle Assessment (LCA), a tool for evaluating environmental performance of product and technology life cycles, has yet to adequately include MNPs-related damage to soil ES, owing to factors like uncertainties in MNPs environmental fate and ecotoxicological effects, and characterizing related damage on soil species loss, functional diversity, and ES. This study aims to address this gap by providing as a first step an overview of the current understanding of MNPs in soil ecosystems and proposing a conceptual approach to link MNPs impacts to soil ES damage. We find that MNPs pervade soil ecosystems worldwide, introduced through various pathways, including wastewater discharge, urban runoff, atmospheric deposition, and degradation of larger plastic debris. MNPs can inflict a range of ecotoxicity effects on soil species, including physical harm, chemical toxicity, and pollutants bioaccumulation. Methods to translate these impacts into damage on ES are under development and typically focus on discrete, yet not fully integrated aspects along the impact-to-damage pathway. We propose a conceptual framework for linking different MNPs effects on soil organisms to damage on soil species loss, functional diversity loss and loss of ES, and elaborate on each link. Proposed underlying approaches include the Threshold Indicator Taxa Analysis (TITAN) for translating ecotoxicological effects associated with MNPs into quantitative measures of soil species diversity damage; trait-based approaches for linking soil species loss to functional diversity loss; and ecological networks and Bayesian Belief Networks for linking functional diversity loss to soil ES damage. With the proposed conceptual framework, our study constitutes a starting point for including the characterization of MNPs-related damage on soil ES in LCA.

System Approach for Characterizing and Evaluating Factors for Occupational Health Impacts Due to Nonfatal Injuries and Illnesses for the Use in Life Cycle Assessment.

Occupational injuries and illnesses are major risk factors for human health impacts worldwide, but they have not been consistently nor comprehensively considered in life cycle impact assessment (LCIA) methods. In this study, we quantified occupational health impacts as disability-adjusted life years (DALYs) for nonfatal injuries and illnesses in all US industries. We further applied an economic input-output model of the US economy to develop a new data set of characterization factors (CFs) that links direct and indirect occupational health impacts to product life cycle final demand. We found that the CF data set varies significantly by industry, ranging from 6.1 to 298 DALYs per billion dollars. About 20% of final demand in the US economic system contributes nearly 50% of the total impacts of occupational health, suggesting occupational health impacts are concentrated in a small portion of industries. To verify the feasibility of the CFs and demonstrate their importance, we included a case of an office chair. The occupational health impacts caused by nonfatal injuries and illnesses during the production of an office chair are of the same order of magnitude as those caused by chemical emissions across the chair's life cycle, with 1.1 × 10-5 and 1.4 × 10-5 DALYs per chair, respectively. Results and data sets derived from this study support the integration of occupational health impacts with LCIA methods.

FAIR environmental and health registry (FAIREHR)- supporting the science to policy interface and life science research, development and innovation.

The environmental impact on health is an inevitable by-product of human activity. Environmental health sciences is a multidisciplinary field addressing complex issues on how people are exposed to hazardous chemicals that can potentially affect adversely the health of present and future generations. Exposure sciences and environmental epidemiology are becoming increasingly data-driven and their efficiency and effectiveness can significantly improve by implementing the FAIR (findable, accessible, interoperable, reusable) principles for scientific data management and stewardship. This will enable data integration, interoperability and (re)use while also facilitating the use of new and powerful analytical tools such as artificial intelligence and machine learning in the benefit of public health policy, and research, development and innovation (RDI). Early research planning is critical to ensuring data is FAIR at the outset. This entails a well-informed and planned strategy concerning the identification of appropriate data and metadata to be gathered, along with established procedures for their collection, documentation, and management. Furthermore, suitable approaches must be implemented to evaluate and ensure the quality of the data. Therefore, the 'Europe Regional Chapter of the International Society of Exposure Science' (ISES Europe) human biomonitoring working group (ISES Europe HBM WG) proposes the development of a FAIR Environment and health registry (FAIREHR) (hereafter FAIREHR). FAIR Environment and health registry offers preregistration of studies on exposure sciences and environmental epidemiology using HBM (as a starting point) across all areas of environmental and occupational health globally. The registry is proposed to receive a dedicated web-based interface, to be electronically searchable and to be available to all relevant data providers, users and stakeholders. Planned Human biomonitoring studies would ideally be registered before formal recruitment of study participants. The resulting FAIREHR would contain public records of metadata such as study design, data management, an audit trail of major changes to planned methods, details of when the study will be completed, and links to resulting publications and data repositories when provided by the authors. The FAIREHR would function as an integrated platform designed to cater to the needs of scientists, companies, publishers, and policymakers by providing user-friendly features. The implementation of FAIREHR is expected to yield significant benefits in terms of enabling more effective utilization of human biomonitoring (HBM) data.

Probabilistic Points of Departure and Reference Doses for Characterizing Human Noncancer and Developmental/Reproductive Effects for 10,145 Chemicals.

BACKGROUND: Regulatory toxicity values used to assess and manage chemical risks rely on the determination of the point of departure (POD) for a critical effect, which results from a comprehensive and systematic assessment of available toxicity studies. However, regulatory assessments are only available for a small fraction of chemicals. OBJECTIVES: Using in vivo experimental animal data from the U.S. Environmental Protection Agency's Toxicity Value Database, we developed a semiautomated approach to determine surrogate oral route PODs, and corresponding toxicity values where regulatory assessments are unavailable. METHODS: We developed a curated data set restricted to effect levels, exposure routes, study designs, and species relevant for deriving toxicity values. Effect levels were adjusted to chronic human equivalent benchmark doses (BMDh). We hypothesized that a quantile of the BMDh distribution could serve as a surrogate POD and determined the appropriate quantile by calibration to regulatory PODs. Finally, we characterized uncertainties around the surrogate PODs from intra- and interstudy variability and derived probabilistic toxicity values using a standardized workflow. RESULTS: The BMDh distribution for each chemical was adequately fit by a lognormal distribution, and the 25th percentile best predicted the available regulatory PODs [R2≥0.78, residual standard error (RSE)≤0.53 log10 units]. We derived surrogate PODs for 10,145 chemicals from the curated data set, differentiating between general noncancer and reproductive/developmental effects, with typical uncertainties (at 95% confidence) of a factor of 10 and 12, respectively. From these PODs, probabilistic reference doses (1% incidence at 95% confidence), as well as human population effect doses (10% incidence), were derived. DISCUSSION: In providing surrogate PODs calibrated to regulatory values and deriving corresponding toxicity values, we have substantially expanded the coverage of chemicals from 744 to 8,023 for general noncancer effects, and from 41 to 6,697 for reproductive/developmental effects. These results can be used across various risk assessment and risk management contexts, from hazardous site and life cycle impact assessments to chemical prioritization and substitution. https://doi.org/10.1289/EHP11524.

Modernizing persistence-bioaccumulation-toxicity (PBT) assessment with high throughput animal-free methods.

The assessment of persistence (P), bioaccumulation (B), and toxicity (T) of a chemical is a crucial first step at ensuring chemical safety and is a cornerstone of the European Union's chemicals regulation REACH (Registration, Evaluation, Authorization, and Restriction of Chemicals). Existing methods for PBT assessment are overly complex and cumbersome, have produced incorrect conclusions, and rely heavily on animal-intensive testing. We explore how new-approach methodologies (NAMs) can overcome the limitations of current PBT assessment. We propose two innovative hazard indicators, termed cumulative toxicity equivalents (CTE) and persistent toxicity equivalents (PTE). Together they are intended to replace existing PBT indicators and can also accommodate the emerging concept of PMT (where M stands for mobility). The proposed "toxicity equivalents" can be measured with high throughput in vitro bioassays. CTE refers to the toxic effects measured directly in any given sample, including single chemicals, substitution products, or mixtures. PTE is the equivalent measure of cumulative toxicity equivalents measured after simulated environmental degradation of the sample. With an appropriate panel of animal-free or alternative in vitro bioassays, CTE and PTE comprise key environmental and human health hazard indicators. CTE and PTE do not require analytical identification of transformation products and mixture components but instead prompt two key questions: is the chemical or mixture toxic, and is this toxicity persistent or can it be attenuated by environmental degradation? Taken together, the proposed hazard indicators CTE and PTE have the potential to integrate P, B/M and T assessment into one high-throughput experimental workflow that sidesteps the need for analytical measurements and will support the Chemicals Strategy for Sustainability of the European Union.

Burden of infectious disease studies in Europe and the United Kingdom: a review of methodological design choices.

This systematic literature review aimed to provide an overview of the characteristics and methods used in studies applying the disability-adjusted life years (DALY) concept for infectious diseases within European Union (EU)/European Economic Area (EEA)/European Free Trade Association (EFTA) countries and the United Kingdom. Electronic databases and grey literature were searched for articles reporting the assessment of DALY and its components. We considered studies in which researchers performed DALY calculations using primary epidemiological data input sources. We screened 3053 studies of which 2948 were excluded and 105 studies met our inclusion criteria. Of these studies, 22 were multi-country and 83 were single-country studies, of which 46 were from the Netherlands. Food- and water-borne diseases were the most frequently studied infectious diseases. Between 2015 and 2022, the number of burden of infectious disease studies was 1.6 times higher compared to that published between 2000 and 2014. Almost all studies (97%) estimated DALYs based on the incidence- and pathogen-based approach and without social weighting functions; however, there was less methodological consensus with regards to the disability weights and life tables that were applied. The number of burden of infectious disease studies undertaken across Europe has increased over time. Development and use of guidelines will promote performing burden of infectious disease studies and facilitate comparability of the results.

Comparative selective pressure potential of antibiotics in the environment.

To guide both environmental and public health policy, it is important to assess the degree of antibiotic resistance selection pressure under measured environmental concentrations (MECs), and to compare the efficacy of different mitigation strategies to minimize the spread of resistance. To this end, the resistance selection and enrichment potential due to antibiotic emissions into the environment must be analysed from a life cycle perspective, for a wide range of antibiotics, and considering variations in the underlying fitness costs between different resistance mutations and genes. The aim of this study is to consistently derive fitness cost-dependent minimum selective concentrations (MSCs) from readily available bacterial inhibition data and to build MSC-based species sensitivity distributions (SSDs). These are then used to determine antibiotic-specific resistance selection concentrations predicted to promote resistance in 5% of exposed bacterial species (RSC5). Using a previously developed competition model, we provide estimated MSC10 endpoints for 2,984 antibiotic and bacterial species combinations; the largest set of modelled MSCs available to date. Based on constructed SSDs, we derive RSC5 for 128 antibiotics with four orders of magnitude difference in their 'selective pressure potential' in the environment. By comparing our RSC5 to MECs, we highlight specific environmental compartments (e.g. hospital and wastewater effluents, lakes and rivers), as well as several antibiotics (e.g. ciprofloxacin, norfloxacin, enrofloxacin, and tetracycline), to be scrutinized for their potential role in resistance selection and dissemination. In addition to enabling comparative risk screening of the selective pressure potential of multiple antibiotics, our SSD-derived RSC5 provide the point of departure for calculating new life cycle-based characterization factors for antibiotics to compare mitigation strategies, thereby contributing towards a 'One-Health' approach to tackling the global antibiotic resistance crisis.

Linking freshwater ecotoxicity to damage on ecosystem services in life cycle assessment.

Freshwater ecosystems provide major benefits to human wellbeing-so-called ecosystem services (ES)-but are currently threatened among others by ecotoxicological pressure from chemicals reaching the environment. There is an increased motivation to incorporate ES in quantification tools that support decision-making, such as life cycle assessment (LCA). However, mechanistic models and frameworks that can systematically translate ecotoxicity effect data from chemical tests into eventual damage on species diversity, functional diversity, and ES in the field are still missing. While current approaches focus on translating predicted ecotoxicity impacts to damage in terms of species loss, no approaches are available in LCA and other comparative assessment frameworks for linking ecotoxicity to damage on ecosystem functioning or ES. To overcome this challenge, we propose a way forward based on evaluating available approaches to characterize damage of chemical pollution on freshwater ES. We first outline an overall framework for linking freshwater ecotoxicity effects to damage on related ES in compliance with the boundary conditions of quantitative, comparative assessments. Second, within the proposed framework, we present possible approaches for stepwise linking ecotoxicity effects to species loss, functional diversity loss, and damage on ES. Finally, we discuss strengths, limitations, and data availability of possible approaches for each step. Although most approaches for directly deriving damage on ES from either species loss or damage to functional diversity have not been operationalized, there are some promising ways forward. The Threshold Indicator Taxa ANalysis (TITAN) seems suitable to translate predicted ecotoxicity effects to a metric of quantitative damage on species diversity. A Trait Probability Density Framework (TPD) approach that incorporates various functional diversity components and functional groups could be adapted to link species loss to functional diversity loss. An Ecological Production Function (EPF) approach seems most promising for further linking functional diversity loss to damage on ES flows for human wellbeing. However, in order to integrate the entire pathway from predicted freshwater ecotoxicity to damage on ES into LCA and other comparative frameworks, the approaches adopted for each step need to be harmonized in terms of assumptions, boundary conditions and consistent interfaces with each other.

Considering degradation kinetics of pesticides in plant uptake models: proof of concept for potato.

BACKGROUND: Degradation kinetics of pesticides in plants are crucial for modeling mechanism-based pesticide residual concentrations. However, due to complex open-field conditions that involve multiple pesticide plant uptake and elimination processes, it is difficult to directly measure degradation kinetics of pesticides in plants. To address this limitation, we proposed a modeling approach for estimating degradation rate constants of pesticides in plants, using potato as a model crop. An operational tool was developed to backward-estimate degradation rate constants, and three pesticides were selected to perform example simulations. RESULTS: The simulation results of thiamethoxam indicated that the growth dynamics of the potato had a significant impact on the degradation kinetic estimates when the pesticide was applied during the early growth stage, as the size of the potato determined the uptake and elimination kinetics via diffusion. Using mepiquat, we demonstrated that geographical variations in weather conditions and soil properties led to significant differences in the dissipation kinetics in both potato plants and soil, which propagated the variability of the degradation rate constant. Simulation results of chlorpyrifos differed between two reported field studies, which is due to the effect of the vertical distribution of the residue concentration in the soil, which is not considered in the majority of recent studies. CONCLUSIONS: Our proposed approach is adaptable to plant growth dynamics, preharvest intervals, and multiple pesticide application events. In future research, it is expected that the proposed method will enable region-specific inputs to improve the estimation of the degradation kinetics of pesticides in plants. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Framework for defining pesticide maximum residue levels in feed: applications to cattle and sheep.

BACKGROUND: Pesticide residues in animal feed can endanger animal health and compromise the safety of livestock products for human consumption. Even though policymakers such as the European Union and the World Health Organization have established maximum residue levels (MRLs) for pesticides in both human food and animal feed, there is no systematic management of pesticides in animal feed that considers the entire supply chain. In response, we propose a framework for defining consistent MRLs for pesticides in animal feed that assesses the impact of defined MRLs on upstream (e.g., MRLs in feed crops) and downstream (e.g., MRLs in livestock products) sectors of the livestock-product supply chain. RESULTS: The MRLs determined for the selected pesticides in the feed of cattle and sheep as case study animals indicate that lipophilic pesticides tend to have lower MRLs than hydrophilic pesticides, primarily due to the relatively high toxicity and biotransfer factors of lipophilic pesticides. In addition, we observe that, primarily for lipophilic pesticides, upstream and downstream regulations are not aligned in terms of defining MRLs in feed using current MRLs in crops with relevance to feed and foods of animal origin. CONCLUSION: Some of the current pesticide regulations in the livestock-product supply chain need to be re-evaluated to ensure that MRLs in the upstream sector (i.e., crops) do not result in unacceptable residues in the downstream sector (i.e., MRLs in livestock products affecting animal and human health). Finally, we provide recommendations for optimizing the derivation of MRLs in feed, including the evaluation of residue fate during feed and food manufacturing processes. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Generating environmental sampling and testing data for micro- and nanoplastics for use in life cycle impact assessment.

Ongoing efforts focus on quantifying plastic pollution and describing and estimating the related magnitude of exposure and impacts on human and environmental health. Data gathered during such work usually follows a receptor perspective. However, Life Cycle Assessment (LCA) represents an emitter perspective. This study examines existing data gathering and reporting approaches for field and laboratory studies on micro- and nanoplastics (MNPs) exposure and effects relevant to LCA data inputs. The outcomes indicate that receptor perspective approaches do not typically provide suitable or sufficiently harmonised data. Improved design is needed in the sampling, testing and recording of results using harmonised, validated and comparable methods, with more comprehensive reporting of relevant data. We propose a three-level set of requirements for data recording and reporting to increase the potential for LCA studies and models to utilise data gathered in receptor-oriented studies. We show for which purpose such data can be used as inputs to LCA, particularly in life cycle impact assessment (LCIA) methods. Implementing these requirements will facilitate proper integration of the potential environmental impacts of plastic losses from human activity (e.g. litter) into LCA. Then, the impacts of plastic emissions can eventually be connected and compared with other environmental issues related to anthropogenic activities.