Plant uptake of pesticides and human health: dynamic modeling of residues in wheat and ingestion intake

Exploring the dynamic behaviors of five pesticides in lettuce: Implications for consumer health through field and modeling experiments

Lettuce, a globally consumed nutritious vegetable, is often linked to concerns regarding pesticide residues. To address this issue, we conducted field trials and utilized dynamiCROP modeling to examine the uptake, distribution, translocation, and dissipation of five pesticides (λ-cyhalothrin, difenoconazole, acetamiprid, dimethomorph, and β-cypermethrin) commonly detected in lettuce. At harvest, pesticides residues were below the maximum residue limits (MRLs) at 0.05, 0.39, 0.047, 0.72, and 0.072 mg kg-1, respectively. Simulation results elucidated distinct behaviors of the pesticides following application to lettuce foliage across various compartments. However, all pesticides exhibited a common dissipation trend, initially stabilizing or increasing before gradually declining. For all five pesticides, the largest contribution of residues on lettuce leaves came from the leaf surface during the early period after application, and from the soil in the long term. Health risk assessments indicated negligible risks associated with consuming lettuce containing these pesticides, both in the short and long term.

Dissipation kinetics and risk assessment of residues of combination product of two fungicides, fluxapyroxad, and pyraclostrobin in cumin

Supervised field trial studies were conducted to understand dissipation kinetics and harvest time residues of a combination product of fluxapyroxad and pyraclostrobin in cumin plant/leaves and seeds at different locations in India. The results showed initial accumulation of fluxapyroxad at the levels of 15.4 and 20.2 mg kg-1 and pyraclostrobin at the level of 21.2 and 33.4 mg kg-1 in cumin leaves/plant in Anand, Gujarat. Fluxapyroxad and pyraclostrobin followed zero-order and first-order dissipation kinetics in cumin plant/leaves samples respectively. The residues translocated to cumin seeds. As the hazard quotient (HQ) was <1 in all cases consumer health risk may be negligible.

Analysis of nationwide soil pesticide pollution: Insights from China

China is a typical agricultural country that heavily relies on pesticides. Some pesticides can remain in the soil after application and thus pose a significant threat to human health. In order to characterize the status and hazards of nationwide soil contamination, this study extracted concentration data from published literature and analyzed them by a scoring approach, standard comparison and health risk assessment. For the soil pollution score, northern regions got the highest values, such as Henan (0.63), Liaoning (0.55), Heilongjiang (0.54) and Jilin (0.53), which implies high soil pesticide residues in these provinces. In contrast, Qinghai (-0.77), Guizhou (-0.64) and Tibet (-0.63) had lower scores. China's soil pesticide standards cover only 16 pesticides, and these pesticide concentrations were all below the corresponding standards. Direct exposure to soil pesticides in this study generally posed a negligible risk to children. Furthermore, pesticide dissipation and usage intensity in each province were analyzed as they were possible influences on pollution. The result showed that soil in the northern regions could accumulate more pesticides than those in the southern regions, and this geographic pattern was basically consistent with the distribution of soil pollution. However, the relationship between agricultural activities and soil pollution was less well characterized. It is recommended to establish a long-term monitoring database for pesticides and include more pesticides in regulatory frameworks. Additionally, efforts to accelerate pesticide degradation and shift the planting structure to reduce pesticide usage can help alleviate the pressure on soil from pesticides. This study can serve as a critical reference for policymakers and stakeholders in the field of agriculture.

Harmonizing pesticides environmental quality standards: A fate-pathway perspective

Regulatory agencies worldwide set pesticide environmental quality standards, which are proposed independently in each dependent environmental media rather than across the complete fate route. Thus, lacking the fate-pathway perspective in defining pesticide environmental quality standards might cause undesirable pesticide residue from the upper compartment (e.g., soil) to the lower compartment (e.g., water). This study aimed to harmonize the self-consistency of pesticide environmental quality standards across environmental media via the fate-pathway analysis. The introduced qualitative and quantitative rules defined environmental quality standards of pesticides in six major environmental scenarios in the soil and water system based on related regulatory objectives. Fate factors simulated via USEtox were used to create a preliminary quantitative link between theoretical maximum legal masses of pesticides across environmental compartments. Using chlorpyrifos and 2,4-D as examples, their standard values were comparatively assessed in selected environmental media in China and the United States. According to the investigative findings, missing the respective environmental quality standards of pesticides in the agricultural soil could significantly influence the implementation of those in freshwater. Taking a fate-pathway perspective, the self-consistency test highlighted that defining pesticide environmental quality standards for freshwater was the most challenging task, as the freshwater compartment typically comprises multiple lower environmental compartments with diverse regulatory objectives. Overall, this theoretical study has the potential to illuminate the harmonization of pesticide environmental quality standards throughout the entire environmental fate pathway, ultimately leading to improved regulatory efficiency and communication. Future research should focus on risk-based model implementation, regulatory response evaluation, and legal limit interpretation to better integrate environmental pesticide management under a variety of regulatory goals.

Assessing potential soil pollution from plant waste disposal: A modeling analysis of pesticide contamination

Pesticide residues can be taken up by plants after pesticide application, potentially resulting in soil pollution following the disposal of plant wastes at harvest. Currently, there is a lack of simple and efficient methods that can conduct high-throughput simulations to explore this problem across various chemicals and plant species. We present a modeling approach to simulating pesticide residue concentrations in soil as a result of plant waste disposal to assess the impact of plant wastes on agricultural soil pollution with respect to pesticide residues. This modeling approach employs well-established plant uptake models, providing versatility in evaluating different chemicals and plant species. The simulation process was tabulated in the spreadsheet interface, providing users with the flexibility to adjust input values for specific chemicals, plant species, and regions. The simulation results revealed that pesticides with relatively low lipophilicity (i.e., log KOW < 2) had low simulated residue concentrations in the soil as a result of plant waste disposal at harvest, whereas soil concentrations for lipophilic pesticides dramatically rose. This indicated that disposal of plant waste in agricultural soils will not pose significant ecological concerns to pesticides with low lipophilicity. The variability analysis showed that for certain pesticides, environmental factors (such as temperature and humidity) had a significant impact on the simulated residue concentrations in the soil as a result of plant waste disposal, which aided in the assessment of regional ecological risk as well as plant disposal management. Although some modeling aspects such as plant decomposition process, advanced plant uptake models, heterological distribution of residue concentrations in the soil, and plant waste stacking patterns require further research, the proposed approach can be used to assist in managing soil pesticides from plant waste disposal in preliminary stages.

Streamlining Pesticide Regulation Across International River Basins for Effective Transboundary Environmental Management

Pesticide standard values (PSVs) are critical for environmental management, environmental quality control, and remediation. Some countries or regions share river basins; however, their pesticide regulations are inconsistent, which could create a barrier to transboundary environmental management. To address this issue, we propose PSV scores for neighboring countries in order to promote pesticide regulatory harmonization within international river basins. Representative pesticides were selected to define PSV scores, including chemicals that are currently and historically widely used. Countries or regions from five international river basins were chosen for analysis: the Amazon, Mekong-Lancang, Rhine-Meuse, Danube, and Great Lakes. PSV scores were calculated for each of four environmental compartments: soil, surface freshwater, groundwater, and drinking water. The results revealed that current regulatory agencies lack PSVs of current used pesticides for surface freshwater. With the exception of the member states of the European Union and the Great Lakes states of the United States, the majority of basin countries or regions lack uniform pesticide regulations in environmental compartments to facilitate transboundary environmental management. In addition, PSVs have not been established for a large number of pesticides currently used in agriculture, which could lead to water contamination by pesticides used in upstream environmental compartments (e.g., croplands). Also, current PSVs do not align across environmental compartments, which could cause inter-environmental contamination by pesticides used in upstream compartments. In light of the fact that current river basins lack uniform pesticide regulations, the following recommendations are provided to promote transboundary environmental management: (1) river basin regions should collaborate on pesticide regulation establishment, (2) pesticide regulations should be aligned across environmental compartments, (3) current-use pesticides should receive more attention, and (4) quantitative approaches should be proposed for linking PSVs across environmental compartments. This study provides a regulatory tool to identify possible gaps in transboundary environmental management and improve the pesticide regulatory policies. It is expected to establish cooperation organizations to enhance regulatory communications and collaborations for transboundary environmental pesticide management.

Assessing human internal exposure to chemicals at different physical activity levels: A physiologically based kinetic (PBK) model incorporating metabolic equivalent of task (MET)

Physical activity levels have the potential to impact human internal exposure to environmental chemicals. However, the current lack of simple modeling approaches hinders the high-throughput screening of chemical exposure at different physical activity levels. To address this gap, this study proposes a straightforward model for assessing human internal exposure to chemicals. Our approach is based on the physiologically based kinetic (PBK) model and utilizes the metabolic equivalent of task (MET) to characterize internal exposure to chemicals at varying activity levels. To facilitate the application of this model, we have developed an Excel-based operation tool, allowing users to easily modify the MET value and generate simulation results for different physical activity levels. The simulation results demonstrate that as physical activity levels increase, the biotransfer factors (BTFs) of chemicals decrease, suggesting that higher physical activity levels reduce the bioaccumulation potential of chemicals. The intensified physical activity enhances the overall elimination kinetics of chemicals from the human body. However, the simulated concentrations of chemicals in the human body increase with higher physical activity levels, due to the significantly increased external exposure to chemicals, such as through inhalation. Our proposed modeling approach, along with the operational tool, enables high-throughput simulation of human chronic internal exposure to chemicals at different physical activity levels, where the findings can assist in screening chemicals for further health risk assessment. To accomplish this, the model incorporates certain assumptions and utilizes generic model input values. However, due to the intricate nature of the interaction between external and internal exposures at different physical activity levels, validating the simulation through experimental studies becomes challenging and is not performed in this study. For future studies, we recommend incorporating more MET-related physiological input variables, improving energy balance estimates, comprehending external exposure estimates, and conducting cohort studies to enhance and validate the proposed modeling approach.

Global assessment of honeybee exposure to pesticides through guttation consumption: An indicator approach

Guttation consumption is a potential pathway of pesticide residue exposure in honeybees. However, modeling tools for assessing honeybee exposure to pesticide residues in guttation drops are lacking. In this study, we propose an indicator-based approach for qualitatively or quantitatively analyzing the guttation-based exposure pathway, allowing us to conduct region-specific pesticide residue exposure assessments for honeybees. Exposure scores (the product of guttation production and residue level scores) were established to compare or rank honeybee exposure to pesticide residues via guttation intake across locations using three specified indicators (i.e., air temperature, relative humidity, and precipitation intensity). Warm, dry regions had high residue level scores (indicating high residue levels in guttation), whereas cold, wet regions had high guttation production scores (indicating high possibilities of guttation formation on leaf surfaces); their exposure scores were a combination of these two values. We evaluated and ranked honeybee exposure to imidacloprid residue across regions in Brazil, China, the United States, and selected European Union member states, revealing that pesticide application in many Brazilian federative units may raise honeybee risks due to high exposure scores. We also compared the guttation pathway to other common exposure pathways (nectar and pollen), suggesting that for some moderately lipophilic compounds, the guttation exposure pathway may not be ignored and should be further evaluated.

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.

Dynamic modeling of pesticide residue in proso millet under multiple application situations

Proso millet (Panicum miliaceum L.) is a cereal crop with potential resistance to drought and heat stress, making it a promising alternative crop for regions with hot and dry climates. Because of its importance, it is crucial to investigate pesticide residues in proso millet and assess their potential risks to the environment and human health to protect it from insects or pathogens. This study aimed to develop a model for predicting pesticide residues in proso millet using dynamiCROP. The field trials consisted of four plots, with each plot containing three replicates of 10 m2. The applications of pesticides were conducted two or three times for each pesticide. The residual concentrations of the pesticides in the millet grains were quantitatively analyzed using gas and liquid chromatography-tandem mass spectrometry. The dynamiCROP simulation model, which calculates the residual kinetics of pesticides in plant-environment systems, was employed for predicting pesticide residues in proso millet. Crop-specific, environment-specific, and pesticide-specific parameters were utilized to optimize the model. Half-lives of pesticides in grain of proso millet, which were needed to input for dynamiCROP, were estimated using a modified first-order equation. Proso millet-specific parameters were obtained from previous studies. The accuracy of the dynamiCROP model was assessed using statistical criteria, including the coefficient of correlation (R), coefficient of determination (R2), mean absolute error (MAE), relative root mean square error (RRMSE), and root mean square logarithmic error (RMSLE). The model was then validated using additional field trial data, which showed that it could accurately predict pesticide residues in proso millet grain under different environmental conditions. The results demonstrated the accuracy of the model in predicting pesticide residues in proso millet after multiple applications.

Predicting pesticide residues in pod fruits with a modified peel-like uptake model: A green pea demonstration

Peas are among the most popular leguminous plants, consumed by both humans and animals in large quantities. Pesticides are widely used globally to increase pea yield, and as a result, pesticide residues can be taken up by pea plants and bioaccumulate in their fruits, including peas and pods. However, there is a lack of modeling approaches available to predict residue concentrations in peas. To address this issue, a pod fruit model (specifically designed for neutral organic compounds) was proposed to simulate the bioaccumulation process of pesticide residues in pea plants, which was developed by modifying a peel-like uptake model. The simulation results, based on green pea as the modeling demonstration, reveal that moderately-lipophilic pesticides (i.e., log KOW around 3) have higher simulated concentrations in peas at harvest compared to hydrophilic (i.e., log KOW less than 0) or highly-lipophilic (i.e., log KOW over 5) pesticides, which is due to the enhanced uptake process of moderately-lipophilic compounds in the pod-pea system, such as their ability to penetrate the pod cuticle and be transported via phloem sap. The sensitivity test and variability analysis conducted in this study revealed that the degradation kinetics, including metabolism, hydrolysis, and photolysis, had a significant impact on moderately-lipophilic pesticides due to their high simulated concentrations in the pea plant. This can result in substantial loss of residue mass via degradation. The validation of the model demonstrated that the simulation results, specifically residue concentrations in the fruit, were consistent with the harvested data. However, some inconsistency was observed immediately after pesticide application, which could be attributed to plant growth dynamics and initial surface mass distributions. The proposed pod fruit model provides new insights into the bioaccumulation process of pesticide residues in pea plants and enables high-throughput simulations of residue concentrations at harvest. To enhance the performance of the pod fruit model, future research should consider plant growth dynamics, plant uptake of ionizable compounds, and initial mass distribution functions.

A dynamic inventory database for assessing age-, gender-, and route-specific chronic internal exposure to chemicals in support of human exposome research

In this study, we proposed a dynamic inventory database to evaluate chronic internal exposure to chemicals at a population level, which enables users to perform modeling exercises specific to a particular chemical, route of exposure, age group, and gender. The database was built based on the steady-state solution of physiologically based kinetic (PBK) models. The biotransfer factors [BTF, the steady-state ratio between the chemical concentration in human tissues and the average daily dose (ADD) of the chemical] of 931 organic chemicals in major organs and tissues were simulated for a total of 14 population age groups for males and females. The results indicated that infants and children had the highest simulated BTFs of chemicals, and middle-aged adults had the lowest simulated BTFs. The route-specific analysis of the simulated BTFs indicated that the biotransformation half-life and octanol-water partition coefficient of chemicals had a profound impact on the BTFs. Organ- and chemical-specific results indicated that the biotransfer potential of chemicals in human bodies was primarily determined by bio-thermodynamic variables (e.g., lipid contents). In conclusion, the proposed inventory database can be conveniently used to access chronic internal exposure doses of chemicals by multiplying the route-specific ADD values for different population groups. In future studies, we recommend incorporating human biotransformation data, partition coefficients of ionizable chemicals, age-specific vulnerable indicators (e.g., the degree of maturation of immune systems), physiological variations within the same age group (e.g., intensity of daily physical activities), growth rates (i.e., the dilution effect on chemical biotransfer), and all possible target organs of carcinogenicity (e.g., bladder) into the proposed dynamic inventory database to help promote human exposome research.

Generalizing routes of plant exposure to pesticides by plant uptake models to assess pesticide application efficiency

Pesticide application techniques are critical not only for integrated pest management (IPM) but also for food and environmental safety. Assessing pesticide application efficiency on plants can help optimize IPM and reduce pesticide environmental impacts. With hundreds of pesticides registered for use in agriculture, this study proposed a modeling approach based on plant uptake models for generalizing routes of plant chemical exposures that can correspond to different types of pesticide application methods and evaluating their respective efficiency on plants. Three representative pesticide application methods (i.e., drip irrigation, foliar spray, and broadcast application) were selected for modeling simulations. The simulation results for three representative pesticides (i.e., halofenozide, pymetrozine, and paraquat) revealed that the soil-based transpiration exposure route facilitated the bioaccumulation of moderately lipophilic compounds in leaves and fruits. While the plant surface-based exposure route (i.e., leaf cuticle penetration) made it easier for highly lipophilic compounds to enter plants, moderately lipophilic pesticides (i.e., log K_OW ∼ 2) were more soluble in phloem sap, which enhanced their subsequent transport within plant tissues. In general, moderately lipophilic pesticides had the highest simulated residue concentrations in plant tissues for the three specific application methods, indicating they had the highest application efficiency due to their enhanced uptake routes (via transpiration and surface penetration) and increased solubility in xylem and phloem saps. Compared to foliar spray and broadcast application, drip irrigation produced higher residue concentrations for a wide variety of pesticides, exhibiting the highest application efficiency for many pesticides, especially for moderately lipophilic compounds. Future research should incorporate plant growth stages, crop safety, pesticide formulations, and multiple application events into the modeling approach for understanding pesticide application efficiency evaluation.

A Modeling Approach for Assessing Ecological Risks of Neonicotinoid Insecticides from Emission to Nontarget Organisms: A Case Study of Cotton Plant

The use of neonicotinoid insecticides in agriculture has posed threats to ecological systems, and there is a need to assess the ecological risks of neonicotinoids from emission to nontarget organisms. We introduced a modeling approach to assess the ecological risks of neonicotinoids using honeybee and earthworm as model organisms, and the simulation was flexible under different environmental conditions. Using the cotton plant as an example, the simulation results demonstrated that under current recommended application rates, the use of common neonicotinoid insecticides posed no threat to earthworms, with the simulated risk quotients (RQs) much lower than 1. However, the simulation for some neonicotinoid insecticides (e.g., acetamiprid) indicated that using these insecticides on cotton plants could threaten honeybees, with simulated RQs higher than 1. The variability analysis showed that in high-latitude regions, the unacceptable risk to honeybees posed by insecticide application can be further elevated due to cold, wet weather that results in relatively high insecticide levels in pollen and nectar. The model evaluation showed large overlaps of simulated risk intervals between the proposed and existing (BeeREX) models. Because the proposed and existing models have different simulation mechanisms, we recommend that these two models be used together to complement each other in future studies. Environ Toxicol Chem 2023;42:928-938. © 2023 SETAC.

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.

Modeling banana uptake of pesticides by incorporating a peel-pulp interaction system into a multicompartment fruit tree model

According to field research, banana peels have a significant impact on the uptake of pesticide residues by banana pulps. To predict pesticide residue concentrations in harvested bananas, however, current modeling approaches did not take into consideration the banana peel as a single simulating compartment. To address the problem, we incorporated a peel-pulp interaction system into a modified multicompartment fruit tree model in order to simulate pesticide residue concentrations in banana plants. The simulation results revealed that lipophilicity played a crucial role in regulating pesticide bioaccumulation in banana plants, showing that moderately- or highly-lipophilic compounds had a high potential for bioaccumulation in banana pulps and peels. Some model inputs, such as peel thickness, degradation rates in plant tissues, and dissipation rates in the soil, had a substantial impact on the bioaccumulation of pesticides in banana pulps and peels. Even if more aspects (such as dynamically morphological properties of banana plants and ionizable chemical compounds) must be considered for in future research, the proposed modeling approach can aid in the comprehension of the pesticide bioaccumulation mechanism in banana plants.

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.

Modeling pesticide residue uptake by leguminous plants: a geocarpic fruit model for peanuts

BACKGROUND

Pesticide residues are frequently found in leguminous plants; however, no modeling approaches predict residue concentrations in edible legume seeds. In this study, a geocarpic fruit model, simplified for neutral organic compounds, was proposed for high-throughput simulations (over 700 pesticides) of the residue uptake by peanut plants, which characterized three scenarios, namely (i) pesticide foliar application during the pre-seed development stage, (ii) foliar application during the seed development stage, and (iii) soil contamination before plant germination.

RESULTS

In the foliar application scenario, in general, lipophilic pesticides have high simulated residue unit doses (RUDs, residue concentrations in plants per 1.0 kg ha^-1 of pesticide application) in peanut leaves owing to intensified uptake via surface deposition, whereas hydrophilic pesticides have high simulated RUDs in peanuts because the uptake of residues via diffusion is enhanced. For the soil-contamination scenario, organic compounds with moderate lipophilicity have a high bioconcentration potential (i.e. the soil-plant system) in leaves and peanuts, due to large transpiration stream concentration factors (TSCFs) that boost the uptake via transpiration.

CONCLUSIONS

The simulation results have some degrees of agreement with field measurements, indicating that the proposed model can be used as a screening tool for dietary risk assessment of pesticides in peanuts. In future research, pH-dependent physicochemical properties (e.g. soil-water partition coefficient and TSCF) and degradation rate constants of chemicals need to be refined to improve the simulation analysis. © 2022 Society of Chemical Industry.

Screening safe pesticide application rates in crop fields for protecting consumer health: A backward model for interim recommended rates

To reduce human health risks and comply with regulatory standards, it is necessary to provide safe application rates of pesticides in crop fields. In this study, a screening-level model is proposed to improve the regulation of pesticide application rates based on the dynamiCrop platform, which can serve as a complementary approach to field trials for regulatory agencies. The screening-level model can conveniently simulate safe application rates of pesticides based on consumer health risks and maximum residue levels (MRLs). Using 2,4-D as an example, the simulation results agreed with the data of field trials under Good Agricultural Practices and demonstrated that current manufacturers' recommended application rates can effectively comply with MRLs and protect human health. In addition, we simulated the default safe application rates of 449 pesticides in five common crops using the default values of the acceptable daily intake (ADI; 0.01 mg kg^-1  day^-1 ) and MRL (0.01 mg kg^-1 ). The results demonstrated that aerial-fruit crops (e.g., tomatoes and apples) had much lower default safe application rates of pesticides than tuber crops due to the different pesticide uptake mechanisms of plants. In addition, the MRL-based default safe application rates were significantly lower than the ADI-based default rates, indicating that the default MRL of 0.01 mg kg^-1 adopted by current regulatory agencies is very conservative regarding population health risks. Although other factors, such as the variability of residue levels in crops, occupational exposure (farmers and operators), and multiple pesticide application patterns, need to be considered in future studies, our screening-level model could be used as a complementary tool in field trials to assist regulatory agencies in regulating pesticide application rates in crop fields. Integr Environ Assess Manag 2023;19:126-138. © 2022 SETAC.

Mapping Plant Bioaccumulation Potentials of Pesticides from Soil Using Satellite-Based Canopy Transpiration Rates

The transpiration rate is an important factor that determines the bioaccumulation potential of pesticides from soil and can present a spatiotemporal pattern. In the present study, we proposed a satellite-based approach to map the bioaccumulation potential of pesticides from soil using the Global Land Evaporation Amsterdam Model (GLEAM). In the proposed model, the spatiotemporal variable (i.e., plant transpiration rate) was separately analyzed from the plant- and chemical-specific variables. The simulated bioaccumulation factors (BAFs; steady-state concentration ratios between plants and soil) of atrazine and lindane for the United States indicated that the proposed model can better predict the spatiotemporal pattern of bioaccumulation potentials of pesticides from soil than a previous weather-based model. The proposed approach using GLEAM's satellite data avoids the overestimation of plant transpiration rate in regions with a dry and warm climate. The comparison of BAFs between the proposed and weather-based models indicated that the satellite-based simulation was consistent with the weather-based simulation for most states and was more effective for the southwest region. Furthermore, plant- and chemical-specific variables were simulated for over 700 pesticides, which could be multiplied by satellite-based canopy transpiration rates to map the bioaccumulation potentials of chemicals from soil. Further evaluation of plant-specific variables, partitioning behaviors of ionizable compounds, and multiple uptake routes (e.g., airborne residue deposition) will aid in the evaluation of the spatiotemporal patterns of pesticide BAFs in plants in future research. Environ Toxicol Chem 2023;42:117-129. © 2022 SETAC.

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

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.

Modeling pesticide residues in tobacco leaves for improving life cycle inventory analysis of pesticides in the cigarette industry

To promote pesticide management in tobacco products, we conducted a life cycle inventory (LCI) analysis by simulating pesticide residues in tobacco leaves during tobacco farming, manufacturing, and product use stages in the cigarette industry. For the tobacco farming stage, the bioaccumulation-potential analysis of pesticide residues in fresh tobacco leaves indicated that lipophilicity and degradation half-life in soil were two significant factors determining residue mass in leaves. For the manufacturing stage, the persistence analysis of pesticide residues in processed tobacco leaves revealed that pesticides with high volatility or high degradability in plant tissues had small processing factors. For the product use stage, exposure and toxicity assessment of pesticide residues were conducted for tobacco consumed via smoking, which generated characterization factors linking pesticides to impacting human health. According to the LCI analysis, we quantitatively showed that pesticides with low lipophilicity, high degradability, and high volatility limited consumers' exposure to residues via smoking.

Uptake of endosulfan isomers from soils by leafy vegetable lettuce: A comparative study between model-predicted and field-experimented results

The organochlorine insecticide endosulfan has been classified as a persistent organic pollutant due to its long persistence and high toxicity, and banned in most countries. However, endosulfan residues are still detected in various environmental sites (even in non-agricultural areas) and have a likelihood to return to agricultural soils through various routes. In this study, time-dependent uptake of α- and β-isomers of endosulfan by lettuce from soils was estimated using theoretical models which include parameters describing sorption/dissipation in soil and plants, plant transpiration, root-soil transfer, and plant growth. A chemical-specific residue (CSR) model developed in a previous study was used as a sub-model to estimate the portion of endosulfan residues in soils ready to be absorbed by lettuce, and the accuracy of the CSR model was verified by properly estimating concentrations of endosulfan isomers in soils with different organic matters; a low mean deviation (18.8 %) was observed between the modeled and measured values. Modeled results of β-endosulfan using a soil-lettuce uptake model satisfactorily matched the experimentally measured results, with a moderate correlation (R2 > 0.79) and a low residual error (0.42) against a mean factor of -1.04. However, the uptake model showed the low potential to predict the soil-lettuce uptake of α-endosulfan (176.3 % mean deviation), probably due to not considering an intrinsic trait of β-isomer converting to α-isomer. Although the improvement with more sophisticated parameters is needed, the plant uptake model developed in this study could be utilized to predict soil-lettuce uptake of at least β-endosulfan and as a model template that may apply for other types of plants and contaminants.

Fluroxypyr-1-methylheptyl ester induced ROS production and mitochondrial apoptosis through the MAPK signaling cascade in porcine trophectoderm and uterine luminal epithelial cells

FPMH (Fluroxypyr-1-methylheptyl ester) is a synthetic auxin herbicide used in agriculture. The mechanism by which FPMH induces adverse effects in porcine trophectoderm (pTr) and porcine uterine luminal epithelial (pLE) cells, which are involved in porcine implantation, have not been studied yet. Therefore, the present study investigates the toxicological effects of FPMH on pTr and pLE cells. We confirmed that FPMH induced cytotoxic effects on the cells, including apoptosis induction, mitochondrial membrane potential (MMP) depolarization, and ROS production. The phosphorylation of the MAPK pathway (ERK1/2, JNK, and p38) was dysregulated by FPMH administration. In addition, FPMH could suppress cell-cell adhesion and migration abilities of pTr and pLE, which are crucial for implantation. Therefore, exposure to FPMH induced adverse effects in pTr and pLE cells and could result in implantation failure.

Regulation of Paraquat for wheat crop contamination

Paraquat is a highly toxic and persistent pesticide in soil but is still used for wheat crops in many countries. Paraquat can pose potential health hazards if it is translocated from soil into wheat grains, but no study is available for its possible translocation causing wheat grain contamination. The present study aimed at finding out Paraquat residue in wheat grains under field conditions for two crop seasons to explore the sustainability of this pesticide. The experiments were conducted scientifically under field conditions at agricultural fields Pusa, Delhi, India. The soil texture was classified as sandy loam. Paraquat dichloride 24% SL (herbicide) was applied on five fields except for control field. Paraquat in wheat grains was analyzed using HPLC equipped with a photodiode array (PDA) detector. The method of analysis was validated for the pesticide residue recovery. The results showed that there was an alarming concentration of Paraquat in wheat grains ranging between 21.6 and 49.02 mg kg^-1 against maximum residue level of 0.1 mg kg^-1. Paraquat was also found in control crop (3.1 mg kg^-1) due to background residue in soil even when no Paraquat was applied. Furthermore, wheat flour samples from market also gave alarming Paraquat residue (20.39, 25.88, and 27.68 mg kg^-1). Paraquat residue was primarily dependent on % clay in field soils. More the % clay lesser was Paraquat residue in wheat grain. Thus, Paraquat was translocated from soil into wheat grains and resulted in worrying concentration of Paraquat residue in wheat grains. Consequently, use of Paraquat for wheat crops needs to be regulated as it contaminated the soil and resulted in the wheat grain contamination posing severe health hazards for humans.

Halloysite Nanotube-Based Pesticide Formulations with Enhanced Rain Erosion Resistance, Foliar Adhesion, and Insecticidal Effect

The incorporation of green and sustainable nanomaterials in pesticide formation is an effective method to lower the use of conventional pesticides without adverse effects on productivity. Here pesticide Pickering emulsions stabilized by halloysite nanotubes (HNTs) were developed for low cost, less environmental pollution, low toxic effects, and better emulsion stability. HNTs were added to chlorantraniliprole (CAP) emulsions, and good stability was exhibited due to the adsorption and aggregation of HNTs at the interface of CAP oil droplets, forming a three-dimensional network structure that prevented the emulsion from aggregation. In addition, Spodoptera frugiperda was used as a pest model and corn was used as a plant model to explore the washout resistance, insecticidal effect, and biological safety of HNTs-CAP emulsion. After spraying emulsion on corn leaves and washing for 10 min, the HNTs-CAP emulsion (5 wt % HNTs) pesticide residue rate was 2.7 times that of pristine CAP emulsion. When the HNT dispersion concentration was 2 wt %, the larva mortality was 83%, which was 1.5 times that of the CAP emulsion group. These results demonstrated that HNTs-CAP emulsion showed good foliar adhesion, rainfall resistance, and insecticidal effect. The tubular clay-based nanopesticide formulations show potential applications in the control of crop pests with modern agriculture technology.

Prioritizing agricultural pesticides to protect human health: A multi-level strategy combining life cycle impact and risk assessments

In this study, a multi-level strategy to prioritize pesticides for use in agriculture is proposed in support of protecting human health. The strategy includes four levels (production, application, distribution, and bioaccumulation) of screening approaches, for which the life cycle impact assessment (LCIA) and human health risk assessment (HHRA) models were applied to generate priority lists at each level. The LCIA model was used at the production level (i.e., chemical design; before pesticides being registered and entering the market), providing the inventory management based on environmental persistence and toxicity potential of pesticides, whereas the HHRA models were used at the other three levels, assessing human health risks based on pesticide emission to cropland. Priority scores (PS) of 319 pesticides were simulated with high scores indicating high priority for use in agriculture (relatively high human safety). The simulated results via the LCIA at the production level had strong positive correlations with those via the HHRA at the other three levels, indicating that the LCIA tool was capable of an initial screening of pesticides for use in agriculture. The simulated PS values of 319 pesticides indicated that some pesticides (e.g., chlorpyrifos and fipronil) with low PS values (e.g., < 8) that are currently used in some countries should be further evaluated. For other pesticides with high simulated PS values (e.g., > 15) for use in agriculture, their ecotoxicity impacts and ecological risks should be considered in protecting human health.

Dissipation kinetics, residue modeling and human intake of endosulfan applied to okra (Abelmoschus esculentus)

The non-judicious application of the harmful pesticide endosulfan on okra, one of India's most consumed vegetable crops, has resulted in the frequent detection of residues in food samples. This can lead to resistance and the resurgence of various pests and diseases. In this context, combined dissipation and residue dynamics of different endosulfan components or mixtures (isomers and metabolites) in crop compartments are not yet well understood. To address this research gap, the present study evaluates the dissipation and persistence behavior of different endosulfan isomers (alpha-, beta-isomers) and major metabolite (endosulfan sulfate) on okra during 2017 and 2018. The half-life of endosulfan on okra leaves was found to be between 1.79 and 3.47 days. Half of the endosulfan deposits on okra fruits at the recommended doses were dissipated after 2.39 days compared to 1.99 days at double recommended doses (mean of 2017 and 2018 residue data). Measured endosulfan residues were evaluated against the dynamic plant uptake model dynamiCROP. The better fits were observed between modeled and measured residues for fruits (R² from 0.84 to 0.96 and residual standard error (ER) between 0.6 and 1.47) as compared to leaves (R² from 0.57 to 0.88). We also report fractions of endosulfan components ingested by humans after crop harvest. Intake fractions range from 0.0001-7.2 g_intake/kg of applied pesticide. Our results can evaluate pesticide residues in different crops grown for human consumption, including their isomers and metabolites. They can be combined with dose-response information to evaluate human exposure and/or health risk assessment.

Modeling plant uptake of organic contaminants by root vegetables: The role of diffusion, xylem, and phloem uptake routes

The uptake of organic contaminants by root vegetables involves diffusion, transport by xylem and phloem saps, degradation, and volatilization. To understand the role of uptake and elimination routes in the bioconcentration modeling of organic contaminants, a two-compartment uptake model (root and leaf compartments) was proposed. The results showed that for the root compartment, logarithm values of bioconcentration factors (log BCF, the concentration ratio between plant tissues and soil) of chemicals fell within a narrow range when the logarithm of octanol-water partition coefficient (log K_OW) was less than 3.0, whereas log BCF values decreased rapidly with increasing log K_OW values when log K_OW was greater than 3.0. This is because the diffusion route had a significant impact on the root uptake of chemicals, wherein the first-order rate constant dropped rapidly for high-lipophilicity chemicals, resulting in very low log BCF values. For the leaf compartment, chemicals with moderate lipophilicity (log K_OW of 3.0-4.0) had the highest simulated log BCF values. This is because moderate log K_OW values generated the highest transpiration stream concentration factors (TSCFs, the concentration ratio between xylem or phloem saps and water), resulting in high uptake efficiency of chemicals by leaves. Furthermore, we improved the uptake model by considering the surface-deposition route for pesticides (foliar spray), and the simulation results indicated that this uptake route cannot be neglected for lipophilic compounds. Although the simulations agreed with an experimental study and some reported data, future studies should focus on factors, such as plant physiology (plant varieties, periderm effects and compositions of xylem and phloem saps) and environmental conditions (soil properties and weather conditions), to improve the plant uptake model.

Development and application of a numerical dynamic model for pesticide residues in apple orchards

BACKGROUND

Limited understanding of the fate of pesticides in apple orchards may lead to recurring pests or pose risks to food safety. In this study, through a field experiment conducted in an apple orchard, a dynamic plant uptake model, coupled with a soil water model, was developed to simulate measured pesticide concentrations in soil and different plant compartments.

RESULTS

Results showed that the overall model could adequately describe the data set of four pesticides in the apple orchard. An estimated 15%-24.7% of applied pesticides were deposited on leaves and 0.37%-0.58% on fruits. Decreasing pesticide concentrations in fruits were observed after pesticide application, with 9.6%-64.8% of this decrease explained by biodegradation, 29.8%-75.8% by fruit growth dilution and 11.3%-47.6% by wash-off. Furthermore, a first estimation of dietary risks indicated that ingestion of the apples may not represent an acute or chronic risk to human health.

CONCLUSION

The dynamic plant uptake model, coupled with the tipping buckets soil water model, could successfully be fitted to describe to the data set for the fate of four pesticides applied in an apple orchard. The contribution of different pathways to pesticide concentration was highly influenced by precipitation, fruit growth dilution and the characteristics of different pesticides. This model can improve our understanding of pesticide fate in apple orchards and has great potential for supporting food safety assessment and decision-making to minimize impacts arising from pesticide applications. © 2022 Society of Chemical Industry.

Cellular Process of Polystyrene Nanoparticles Entry into Wheat Roots

Nanoscale plastic particles are widely found in the terrestrial environment and being increasingly studied in recent years. However, the knowledge of their translocation and accumulation mechanism controlled by nanoplastic characterizations in plant tissues is limited, especially in plant cells. Here, 20 mg L^-1 polystyrene nanoparticles (PS NPs) with different sizes and amino/carboxy groups were employed to investigate the internalization process in wheat roots and cells. From the results, we found that the uptake of small-size PS NPs in the root tissues was increased compared to that of large-size ones, but no PS NPs were observed in the vascular cylinder. Similar results were observed in their cellular uptake process. Besides, the cell wall could block the entry of large-size PS NPs while the cell membrane could not. The -NH₂ group on the PS NPs surface could benefit their tissular/cellular translocation compared to the -COOH group. The internalization of PS NPs was controlled by both particle size and surface functional group, and the size should be the primary factor. Our findings offer important information for understanding the PS NPs behaviors in plant tissues, especially at the cellular level, and assessing their potential risk to food safety, quality, and agricultural sustainability.

Modeling pesticide residues in nectar and pollen in support of pesticide exposure assessment for honeybees: A generic modeling approach

Pesticide residues in nectar and pollen of plants can damage honeybees; however, few modeling approaches have simulated residue levels in nectar and pollen in support of exposure assessment for honeybees. This study introduced a generic modeling approach based on plant uptake models and simple partitioning rules that specifies soil incorporation and foliar spray application scenarios of pesticides and is flexible for conducting variability analysis for various environmental conditions, pesticide application patterns, chemical individuals, and plant varieties. The results indicated that, in general, systemic or moderate lipophilicity (log K_OW of ~2.5) pesticides have relatively high simulated residue levels in nectar and pollen because of the enhanced residue uptake process from soil. For non-systemic or highly lipophilic pesticides, the residue uptake via leaf surface deposition pathway can be enhanced, and more residues will be bioaccumulated in pollen than nectar due to a relatively high lipid content of pollen (as compared to nectar), but the overall residue levels in nectar and pollen are lower than systemic or moderately lipophilic pesticides. The variability analysis showed that environmental conditions, pesticide application patterns, chemical properties, and plant varieties cause considerable variations in simulated residue levels in nectar and pollen, indicating that spatiotemporal, chemical, and plant-related factors must be considered in pesticide exposure assessment for honeybees. Moreover, the comparison between the simulated and measured data showed a high degree of consistency, indicating that the proposed model could be used to conduct a screening-level pesticide exposure assessment for honeybees.

Quantifying exposure source allocation factors of pesticides in support of regulatory human health risk assessment

One of the challenges while assessing the aggregate exposure risk of pesticides is quantifying exposure doses from various exposure pathways. To address this issue, a regulatory screening approach is proposed for evaluating pesticide allocation factors (AFs) for major exposure pathways for rural and urban residents. This was achieved by integrating dynamiCrop and other screening models to estimate the potential human intake of residues from major crops at harvest, livestock products, and main environmental media (air, water, and soil). The AFs were calculated from the average daily dose factors (ADDFs) of pesticides via major exposure pathways, where a large AF of an exposure pathway indicates that a greater margin of exposure should be given to that exposure pathway. The simulated results for many current-use pesticides showed that the ingestion of crops had pesticide AFs close to 1.0, which indicated that the crop exposure pathway contributed to a significant portion of the total exposure to pesticides. In contrast, for legacy pesticides with high lipophilicity and low degradability in the environment, the simulated AFs for major environmental compartments (air, freshwater, and soil) accounted for relatively large exposures. As legacy pesticides have been banned globally, exposure pathways via the food web and environmental media cannot be neglected because of their high lipophilicity and environmental persistence. Although other factors such as geographical conditions and living habits should be considered to improve the spatial resolution of the model, the method proposed in this study can serve as a preliminary tool to conduct screening-level risk assessments for populations by considering the allocated exposure to pesticides via major exposure pathways.

New implication of pesticide regulatory management in soils: Average vs ceiling legal limits

To help regulatory agencies better interpret pesticide soil standards (PSSs) and promote pesticide soil regulations, this study revealed new PSS implications by introducing the average (i.e., PSS_AC) and ceiling (i.e., PSS_CC) legal limits of pesticides. The PSS_AC indicates the average legal limit of a pesticide in the soil over a duration (e.g., annual or monthly average), ensuring that no adverse human health effects can occur. The PSS_CC indicates the ceiling legal limit that cannot be exceeded by pesticide concentrations in the soil, which was introduced to comply with pesticide application in real-world scenarios. We introduced the regulatory ceiling factor (RCF) to screen whether a pesticide in the surface soil could be regulated using the PSS_AC and PSS_CC values. The results indicated that except for some pesticides with high lipophilicity and low degradability (e.g., legacy pesticides), many pesticides were eligible to be regulated by both average and ceiling legal limits. In addition, we conducted a case study to evaluate chlorpyrifos soil standards via a four-step regulatory procedure; the results indicated that our new interpretation using the simulated PSS_AC and PSS_CC values of chlorpyrifos demonstrated that most current chlorpyrifos soil standards can protect population health, which is in contrast to the findings of current regulatory studies. Furthermore, based on the new implication of PSSs interpreted in this study, we recommend that regulatory agencies clarify PSSs to avoid confusion and promote cost-efficient remediations, and recommend improving the regulatory communication between environmental agencies and pesticide manufacturers to define a comprehensive policy integrating PSSs and application patterns.

Simulation modeling the effects of peels on pesticide removal from potatoes during household food processing

The impact of crop peels on reducing pesticide residue levels in crops during household food processing was evaluated in this study. We proposed a series of pesticide fate models to simulate the removal efficiency of residues in crop peels and medullas (i.e., pulps) via soaking and washing. The simulated results indicated that the variation in the peel thickness had a significant impact on residue removal from the peel compartment. However, the peel compartment had a low impact on the removal efficiency of pesticide residues from the medulla compartment, as demonstrated by the simulated results from the non-peel model (i.e., already peeled crops). In addition, we observed that even though systemic pesticides have a higher potential to penetrate from the peel into the medulla, the increasing residue level caused by the mass transfer from the peel into the medulla is too low to cause human health damage, because the absolute mass of residues in the peel is considerably small. Based on the simulation results, we concluded that washing or soaking crops with or without peels using water is not effective in reducing residue levels in crop medullas. Modifying crops into slices, instead of directly washing or soaking crops, could significantly improve the removal efficiency of pesticide residues inside the medulla. The models proposed in this study can improve our understanding on the fate of pesticides in crops during household food processing.

Improving pesticide fate models for a simple household food processing: considering multiple crop units

To understand the fate of pesticides in crops during household cooking processes and human health risks associated with the ingestion of pesticide-contaminated crops, we propose unit-variability-enhanced models, which are capable of evaluating the removal efficiency of pesticides in multiple crop units by soaking in water. The approach integrates the lognormal production model to reveal the modeling mechanics of internal contamination among two crop units in one soaking bowl. The simulated results for 197 pesticides indicate that pesticides with larger unit-to-unit variability factors (VF) at the residue levels and diffusivity rates in water (D_W) are more likely to cause internal contamination. Although internal contamination of pesticide residues between two crop units may occur, we find that the overall removal factor ([Formula: see text]) for two crop units is independent of the ratio of initial residue levels between the two crop units. Based on this discovery, we propose the unit-variability-based (UVB) rule to generalize the [Formula: see text] for an n-crop-unit system, where n crop units soak simultaneously in one container. In addition, we demonstrate that under the same consumable and recycling resources, the soaking of two crop units together in one container can yield a maximum mass removal of pesticides if the two units are randomly sampled. Although other factors, such as temperature and the nature of solutions in the cooking process, should be considered in future studies, our models suggest that this soaking method can be conveniently realized in households to reduce negative health effects.

Predicting crop root concentration factors of organic contaminants with machine learning models

Accurate prediction of uptake and accumulation of organic contaminants by crops from soils is essential to assessing human exposure via the food chain. However, traditional empirical or mechanistic models frequently show variable performance due to complex interactions among contaminants, soils, and plants. Thus, in this study different machine learning algorithms were compared and applied to predict root concentration factors (RCFs) based on a dataset comprising 57 chemicals and 11 crops, followed by comparison with a traditional linear regression model as the benchmark. The RCF patterns and predictions were investigated by unsupervised t-distributed stochastic neighbor embedding and four supervised machine learning models including Random Forest, Gradient Boosting Regression Tree, Fully Connected Neural Network, and Supporting Vector Regression based on 15 property descriptors. The Fully Connected Neural Network demonstrated superior prediction performance for RCFs (R² =0.79, mean absolute error [MAE] = 0.22) over other machine learning models (R² =0.68-0.76, MAE = 0.23-0.26). All four machine learning models performed better than the traditional linear regression model (R² =0.62, MAE = 0.29). Four key property descriptors were identified in predicting RCFs. Specifically, increasing root lipid content and decreasing soil organic matter content increased RCFs, while increasing excess molar refractivity and molecular volume of contaminants decreased RCFs. These results show that machine learning models can improve prediction accuracy by learning nonlinear relationships between RCFs and properties of contaminants, soils, and plants.

Spatio-temporal assessment of pregnant women exposure to chlorpyrifos at a regional scale

BACKGROUND

The aim of this study was to use an integrated exposure assessment approach, combining spatiotemporal modeling of environmental exposure and fate of the chemical to assess the exposure of vulnerable populations. In this study, chlorpyrifos exposure of pregnant women in Picardy was evaluated at a regional scale during 1 year. This approach provided a mapping of exposure indicators of pregnant women to chlorpyrifos over fine spatial and temporal resolutions using a GIS environment.

METHODS

Fate and transport models (emission, atmospheric dispersion, multimedia exposure, PBPK) were combined with environmental databases in a GIS environment. Quantities spread over agricultural fields were simulated and integrated into a modeling chain coupling models. The fate and transport of chlorpyrifos was characterized by an atmospheric dispersion statistical metamodel and the dynamiCROP model. Then, the multimedia model Modul'ERS was used to predict chlorpyrifos daily exposure doses which were integrated in a PBPK model to compute biomarker of exposure (TCPy urinary concentrations). For the concentration predictions, two scenarios (lower bound and upper bound) were built.

RESULTS

At fine spatio-temporal resolutions, the cartography of biomarkers in the lower bound scenario clearly highlights agricultural areas. In these maps, some specific areas and hotspots appear as potentially more exposed specifically during application period. Overall, predictions were close to biomonitoring data and ingestion route was the main contributor to chlorpyrifos exposure.

CONCLUSIONS

This study demonstrated the feasibility of an integrated approach for the evaluation of chlorpyrifos exposure which allows the comparison between modeled predictions and biomonitoring data.

A disease-specific screening-level modeling approach for assessing the cancer risks of pesticide mixtures

As humans are always exposed to multiple pesticides, it is necessary to conduct risk assessments for pesticide mixtures. Due to data limitations, in this study, we introduced a disease-specific screening-level modeling framework to simulate the cumulative cancer risk (CR) of carcinogenic pesticides, which was developed based on the lognormal dose-response (LDR) curve of chemicals with disease-specific modes of action (MOAs). The simulated results of a case study indicate that the cumulative CR can be at least two orders of magnitude higher than the simulated CRs of individual pesticides. The comparison between the LDR model and the linear extrapolation (or cancer slope factor, CSF) model indicates that the CSF model can greatly overestimate population cancer risks. In addition, we applied our model to evaluate current regulatory standards of carcinogenic pesticide mixtures, and the results indicate that current standards for the selected jurisdictions can control the cumulative cancer risks within the acceptable level. However, the CSF model suggests that all selected jurisdictions cannot protect population health against the carcinogenic pesticide mixture, which is due to the nature of the low-dose linear extrapolation that triggers an initial slope when the effect dose is close to zero. Thus, we concluded that although the MOAs of pesticides in human bodies must be evaluated in future studies, our disease-specific model can be a useful and practical tool for cancer risk assessment and regulatory management of pesticide mixtures.

Improving screening model of pesticide risk assessment in surface soils: Addressing regional specific human exposure risks and regulatory management

In this study, a simple screening approach was proposed to evaluate region-specific population health risks of soil pesticides, which was achieved by introducing region-specific factors of pesticides, including fate factors (FFs), environmental distribution factors (DFs), and intake factors (IFs). These region-specific factors were characterized using simple weather variables and calculated the characterization factors (CFs) to link pesticide emissions to population exposure risks. The CF at the reference state indicates the potential of a pesticide entering the human body. Simulations for over 700 pesticides showed that pesticides that are thermodynamically stable in soil organics have large CFs. In addition, we conducted a case study on the region-specific risk assessment of malathion in the United States. The results indicated that colder regions have larger CFs of malathion than those of the warmer regions due to the large FF values for the same emission rates. However, from a regulatory perspective, colder regions should have less strict malathion soil standards than those of warmer regions as children in colder regions spend limited time outdoors. Although other region-specific factors such as soil type and population density need to be considered to improve the model, the approach proposed in this study can be used as a simple screening tool to evaluate region-specific population health risks and manage soil residues for different regions.

Modeling pesticides in global surface soils: Exploring relationships between continuous and discrete emission patterns

Continuous pesticide emission at constant rate does not occur in reality, but can be a useful and simple concept in modeling studies. To explore the relationship between continuous and discrete emission patterns, we introduced a simple equivalent approach based on a comparison of simulated surface soil pesticide concentrations. The simulated results indicate that, at high soil pesticide dissipation rates and low emission frequencies, the average concentrations under the continuous and discrete emission scenarios were very similar. We demonstrated that the continuous emission model that used the simple average method to calculate the emission rate always overestimated the simulated pesticide concentrations in the surface soil compared to the discrete emission model when using a one-year period based on agricultural practices. In addition, we incorporated the equivalent approach into the USEtox model (a screening-level tool), which can approximate the average pesticide concentrations in surface soil using the time-integrated fate factors at different emission frequencies. The results indicate that the continuous-emission simulations agree with the discrete emission for at least 90% of the selected pesticides based on annual or semi-annual emission patterns. Further studies into other topics, such as random emission patterns and simulation periods, are required to improve the model. Nevertheless, the equivalent approach presented in this study can aid in transforming discrete emission patterns into continuous-emission-based models and improve surface soil pesticide management.

The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk

Exposure to chemicals is influenced by associations between the individual's location and activities as well as demographic and physiological characteristics. Currently, many exposure models simulate individuals by drawing distributions from population-level data or use exposure factors for single individuals. The Residential Population Generator (RPGen) binds US surveys of individuals and households and combines the population with physiological characteristics to create a synthetic population. In general, the model must be supported by internal consistency; i.e., values that could have come from a single individual. In addition, intraindividual variation must be representative of the variation present in the modeled population. This is performed by linking individuals and similar households across income, location, family type, and house type. Physiological data are generated by linking census data to National Health and Nutrition Examination Survey data with a model of interindividual variation of parameters used in toxicokinetic modeling. The final modeled population data parameters include characteristics of the individual's community (region, state, urban or rural), residence (size of property, size of home, number of rooms), demographics (age, ethnicity, income, gender), and physiology (body weight, skin surface area, breathing rate, cardiac output, blood volume, and volumes for body compartments and organs). RPGen output is used to support user-developed chemical exposure models that estimate intraindividual exposure in a desired population. By creating profiles and characteristics that determine exposure, synthetic populations produced by RPGen increases the ability of modelers to identify subgroups potentially vulnerable to chemical exposures. To demonstrate application, RPGen is used to estimate exposure to Toluene in an exposure modeling case example.

Improved plant bioconcentration modeling of pesticides: The role of periderm dynamics

BACKGROUND

There is a continuous need to advance pesticide plant uptake models in support of improving pest control and reducing human exposure to pesticide residues. The periderm of harvested root and tuber crops may affect pesticide uptake, but is usually not considered in plant uptake models. To quantify the influence of the periderm on pesticide uptake from soil into potatoes, we propose a model that includes an explicit periderm compartment in the soil-plant mass balance for pesticides.

RESULTS

Our model shows that the potato periderm acts as an active barrier to the uptake of lipophilic pesticides with high K_OW , while it lets more lipophobic pesticides accumulate in the medulla (pulp). We estimated bioconcentration factors (BCFs) for over 700 pesticides and proposed parameterizations for including the effects of the periderm into a full plant uptake modeling framework. A sensitivity analysis shows that both the degradation half-life inside the tuber and the lipophilicity drive the contributions of other aspects to the variability of BCFs, while highlighting distinct dynamics in the periderm and medulla compartments. Finally, we compare model estimates with measured data, showing that predictions agree with field observations for current-use pesticides and some legacy pesticides frequently found in potatoes.

CONCLUSION

Considering the periderm improves the accuracy of quantifying pesticide uptake and bioconcentration in potatoes as input for optimizing pest control and minimizing human exposure to pesticide residues in edible crops.

Regulation of pesticide soil standards for protecting human health based on multiple uses of residential soil

To help environmental agencies manage pesticides in residential soil and reduce the associated risks to human health, we developed a screening-level framework that derives pesticide soil standards (PSSs) while considering the multiple uses of residential soil. Our screening models simulated the risk from exposure to soil pesticides via direct and three major indirect (i.e., tuber crops, animal-sourced food, and groundwater) exposure pathways. Based on these models, we derived PSSs for five types of residential soil. Our results showed that, in general, indirect pathways contributed more than the direct pathway to the overall exposure to soil pesticides. Consequently, in rural environments, where residential soil is also subjected to activities such as agriculture, animal grazing, and groundwater consumption, the derived PSSs were low. In addition, we compared the derived PSSs to the current worldwide standards for 13 commonly used pesticides. We found that the current global PSSs were appropriate only for urban residential soil. In many rural environments where the boundaries between different soil uses may be indistinct, the current PSSs are insufficient to protect humans from exposure to soil pesticides. Based on this analysis and the proposed PSSs, we provide regulatory recommendations for the management of pesticides in various types of residential soils.

Improving pesticide uptake modeling and management in potatoes: A simple and approximate phloem-adjusted model

To evaluate the impact of the phloem flux on the pesticide uptake process in potatoes, this study developed a phloem-adjusted model based on the classic model that focuses mainly on the diffusion process. To achieve high-throughput simulations, we introduced an approximate method to convert the phloem flux transport process into a simple specific uptake rate of pesticides. In comparison to the classic model (non-phloem model), the phloem-adjusted model generated higher pesticide concentrations and bioconcentration factors (BCFs) in potatoes, owing to the additional pesticide uptake route introduced to the adjusted model. However, the simulation, which was conducted for 740 pesticides, indicated that for most pesticides, the phloem flux route did not contribute a significant portion of the pesticide uptake to potato tubers compared with the soil diffusion route. This was further characterized, using the differential factor (DF), to evaluate the difference in the simulated results between the proposed model and classic models. The largest DF (~0.11) was obtained for pesticides with moderate lipophilicity (i.e., log K_OW of 3.0), indicating that only a difference of 10% was generated between the two models. The 10% increase in pesticide concentration (or BCFs) in potatoes, simulated by the phloem-adjusted model, was within the acceptable uncertainty interval of the classic model, thus confirming the validity of using the classic model to predict the pesticide uptake process in potato tubers. However, we found that the negligibility of the phloem flux route was not merely due to hydrophobicity (i.e., hypothesis of the classic model), but was related to the i) plant physiology of potatoes, ii) lipophilicity of a pesticide, and iii) the diffusivity of a pesticide in water. Although future studies on pesticide concentrations in phloem sap and the dynamic growth of potatoes need to be undertaken, the model developed in this study reveals a more comprehensive pesticide uptake process in potatoes, which can promote the understanding of the pesticide uptake mechanism in potatoes.

Modeling pesticides in global surface soils: Evaluating spatiotemporal patterns for USEtox-based steady-state concentrations

To better manage pesticide pollution in surface soils, we introduced a first-order-kinetics-based screening model to evaluate the steady-state concentrations of pesticides in surface soils while considering degradation, volatilization, plant uptake, and precipitation processes. For each process, we developed a spatiotemporal-pattern-based model using spatiotemporal variables, including air temperature (T_A), relative humidity (RH_A), and rainfall intensity (I_R^A), to characterize the overall dissipation rates (k_T) of pesticides in the soil. These dissipation rates were converted to fate factors (FFs), which are commonly used in life cycle analyses. The results indicate that, in general, the k_T values increase with increasing T_A and I_R^A and decrease with increasing RH_A. This is because increased T_A boosts the degradation, volatilization, and plant uptake processes, whereas increased RH_A lowers the plant transpiration rate. Also, the simulation for over 700 pesticides indicated that the degradation process dominates the overall dissipation of most pesticides in the soil, and the volatilization process contributes the least. In addition, we simulated chlorpyrifos FFs for Brazil, China, the US, and the European Union (EU) using the annual average T_A, RH_A, and I_R^A values. The results indicate that, in general, Brazilian federal units have the smallest FFs and the narrowest simulated FF range because of their humid tropical climates. Meanwhile, the EU member states have the largest FFs and the widest FF range because of their range in locations. In addition, our simulated results show that the surface soils in the high-latitude regions could accumulate more chlorpyrifos than those in low-latitude regions because of the larger simulated FFs. Furthermore, we parameterized our model using 737 pesticides with the USEtox, thereby providing an alternative approach to simulate the steady-state concentration of pesticides in surface soils from the USEtox available data. The model developed herein is a useful screening tool for predicting pesticide concentrations in surface soil worldwide to improve soil and ecological health risk management.

Mechanistic modeling of pesticide uptake with a 3D plant architecture model

Meaningful assessment of pesticide fate in soils and plants is based on fate models that represent all relevant processes. With mechanistic models, these processes can be simulated based on soil, substance, and plant properties. We present a mechanistic model that simulates pesticide uptake from soil and investigate how it is influenced, depending on the governing uptake process, by root and substance properties and by distributions of the substance and water in the soil profile. A new root solute uptake model based on a lumped version of the Trapp model (Trapp, 2000) was implemented in a coupled version of R-SWMS-ParTrace models for 3-D water flow and solute transport in soil and root systems. Solute uptake was modeled as two individual processes: advection with the transpiration stream and diffusion through the root membrane. We set up the model for a FOCUS scenario used in the European Union (EU) for pesticide registration. Considering a single vertical root and advective uptake only, the root hydraulic properties could be defined so that water and substance uptake and substance fate in soil showed a good agreement with the results of the 1D PEARL model, one of the reference models used in the EU for pesticide registration. Simulations with a complex root system and using root hydraulic parameters reported in the literature predicted larger water uptake from the upper root zone, leading to larger pesticide uptake when pesticides are concentrated in the upper root zone. Dilution of root water concentrations at the top root zone with water with low pesticide concentration taken up from the bottom of the root zone leads to larger uptake of solute when uptake was simulated as a diffusive process. This illustrates the importance of modeling uptake mechanistically and considering root and solute physical and chemical properties, especially when root-zone pesticide concentrations are non-uniform.

Improving screening model of pesticide risk assessment in surface soils: Considering degradation metabolites

As pesticides can be degraded to toxic metabolites in the soil, metabolite toxicity should be considered in human health risk assessments. In this study, a screening-level modeling framework was developed to manage pesticides in surface soil, which was discussed under discrete and continuous emission scenarios. In addition, we selected glyphosate and its major metabolite (aminomethylphosphonic acid or AMPA) as examples to conduct screening-level risk management at regional, national, and global scales. The results indicated that if soil AMPA were not considered, human health risks could be significantly underestimated because of the large half-life of AMPA in the soil. For example, the added concentration factors of AMPA were simulated as 0.19 and 6.72 considering all major elimination pathways and considering the degradation pathway alone, respectively, indicating that AMPA formation could lead to severe extra health burdens. Furthermore, the evaluation of current glyphosate soil standards suggested that toxic metabolites should be considered in the regulatory process; otherwise, many standards could theoretically trigger high levels of soil AMPA, which could result in serious human health damage. Our proposed screening-level model can help to improve risk assessment and regulatory management of pesticides in surface soils.