Model Assessment Research Articles

Integrated Modeling Approach to Assess Freshwater Inflow Impact on Coastal Water Quality

The quality of freshwater input from tributaries of the Western Mississippi Sound (WMSS) impacts the quality of coastal water. Hydrological and hydrodynamic models can be coupled to assess the impact of freshwater inflow from coastal watersheds. This study aims to compare the performance of a hydrodynamic model and a hydrological–hydrodynamic coupled model in detecting the effect of freshwater inflow from the coastal watersheds of the state of Mississippi into the WMSS. A hydrological model, the Soil and Water Assessment Tool (SWAT), and a hydrodynamic model, the visual Environmental Fluid Dynamics Code (vEFDC), were coupled to evaluate the difference between the hydrodynamical modelling approach, which employs an area-weighted approach to define flow and nutrient concentrations, and the more recent coupling model approach, which uses a hydrological model to determine the flow and nutrient load of the model. Furthermore, a nutrient load sensitivity analysis of the effect of freshwater inflow on water quality in the WMSS was conducted in addition to assessing the repercussions of tropical depressions. Hydrological assessments of the major tributaries watersheds of Saint Louis Bay (SLB) at the WMSS were performed using the SWAT model. After calibration/validation of the SWAT model, the streamflow output from the SWAT was incorporated into the vEFDC model. Finally, hydrodynamic simulation of the SWAT-vEFDC model was conducted, and water quality output was compared at different SLB locations. The salinity, dissolved oxygen, total nitrogen (TN), and total phosphorus (TP) were assessed by comparing the vEFDC and SWAT-vEFDC outputs. The results indicated that hydrological input from the SWAT alters the flow and nutrient concentration results as compared to an area-weighted approach. In addition, a major impact on the concentration of TN and TP occurred at the location where the freshwater flows into SLB. This impact diminishes further away from the point of freshwater inflow. Moreover, a 25% nutrient load variation did not demonstrate a difference in water quality at the WMSS besides TN and TP in a post-tropical depression scenario. Therefore, the SWAT-vEFDC coupled approach provided insights into evaluation of the area-weighted method, and of hydrological model output to the hydrodynamical model, the effect of freshwater inflow into coastal waters, and nutrient sensitivity analysis, which are important for integrated coastal ecosystems management.

Non-Conventional Data for Farming-Related Air Pollution: Contributions to Modelling and Risk Assessment in the Lombardy Region, Italy

Air pollution is one of the most critical global health concerns today. While emissions from industrial activities and combustion processes are the primary threats to air quality, intensive farming activities also contribute significantly, especially through ammonia emissions that promote the formation of secondary pollutants, such as particulate matter. Advancements in air quality research have been achieved by enhancements in emissions characterisation, modelling techniques, and sensor technology, expanding the availability of air pollution data beyond traditional ground sensor observations, which are often lacking in rural agricultural areas. Accordingly, this paper demonstrates the advantages of integrating traditional and non-conventional data to investigate farming-related air pollution through a case study in the Lombardy Region, Northern Italy. The study incorporates an array of data sources, including ground sensors and atmospheric composition model estimates. The concurrent utilisation of these diverse datasets is explored through machine learning modelling, focusing on assessing the influence of agricultural activities on particulate matter distribution patterns. Finally, the reliability of non-conventional air pollution data for health risk assessment applications is also investigated. The paper critically discusses the main findings based on empirical results, highlighting the significance of integrating multiple data sources to complement traditional air quality monitoring while outlining the main limitations in terms of the accuracy and usability of such non-conventional data.

Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost

With the rapid development of electric vehicles, the infrastructure for charging stations is also expanding quickly, and the failure rate of charging piles is increasing. To address the effective operation and maintenance of charging stations, a method based on the XGBoost algorithm for electric vehicle DC charging stations is proposed. An operation and maintenance system is constructed based on state analysis, considering the operational status of the charging stations and users’ charging habits. Factors such as driving and charging habits, road traffic, and charging station equipment are taken into account. The training sample data are established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. Risk tracking of the charging stations is conducted using the energy not charged (ENC), evaluating the risk level of each station and determining the operation and maintenance order. The optimal operation and maintenance model for DC charging stations, aimed at achieving both economic and reliability goals, is constructed to determine the operation and maintenance schedule for each station. The results of the case study demonstrate that the state evaluation and operation and maintenance strategy can significantly improve the reliability of the system and the overall benefits of operation and maintenance while meeting the required standards.

An integrated policy approach for sustainable decarbonization pathways of energy system in a city under climate change scenarios

An integrated assessment model has been developed to estimate useful energy demand, followed by an optimization model for planning the energy supply. Four scenarios have been developed. The findings of this study highlight the impact of behavioral, climate change, and socio-economic factors on energy demand and supply. Specifically, these factors can lead to significant variations in demand, such as a more than 3.48-fold difference in cooling demand or a 1.75-fold difference in the transportation demand by cars across various scenarios.The use of a dual-fuel car and electric motorcycle is suggested in all scenarios. Waste processing has been done with a landfill in all scenarios except in the final years of the net-zero emission target scenario, where an incinerator is proposed. The supply model for electricity generation in the early years suggests the combined cycle power plant followed by solar energy at the end. However, in the low-cost electricity scenario, it is always suggested to import electricity. The sensitivity analysis showed that the emission penalty and electricity price are the most important parameters. The results of this study will help policymakers and decision-makers in energy system planning and provide researchers with appropriate information, tools, and methods for future research.

Effects of insulin resistance and β-cell function on diabetic complications in Korean diabetic patients.

Diabetes mellitus is characterized by insulin resistance (IR) and dysfunctional insulin secretion from pancreatic β-cells. However, little research has been conducted on the relationship between IR and β-cell function in relation to diabetic complications among Korean diabetic patients. This study aimed to examine the differential associations between IR and β-cell function and various diabetic complications among Korean diabetic patients. The analysis employed a common data model (CDM). IR and β-cell function were quantified using the homeostasis model assessment for insulin resistance (HOMA-IR) and β-cell function (HOMA-β), respectively. Hazard ratios for diabetic nephropathy, diabetic retinopathy, and cardiovascular disease (CVD) events were calculated. The study cohort consisted of 2,034 diabetic patients aged over 20 years who visited EUMC between January 2001 and December 2019. Among diabetic patients in the highest quartile of HOMA-IR, the adjusted hazard ratio for total CVD events was 1.76 (95% confidence interval [CI], 1.20-2.57) compared with those in the lowest quartile of HOMA-IR (P = 0.004). In contrast, diabetic patients in the lowest quartile of HOMA-β exhibited an adjusted hazard ratio of 3.91 (95% CI, 1.80-8.49) for diabetic retinopathy compared to those in the highest quartile of HOMA-β (P = 0.001). Insulin resistance and β-cell function exhibited different associations with diabetic complications among Korean diabetic patients. Specifically, lower β-cell function was associated with an increased risk of diabetic retinopathy, whereas higher IR was associated with an increased risk of CVD events. Individuals with pronounced IR should prioritize CVD prevention measures, and those with significant β-cell dysfunction may benefit from early, intensive surveillance for diabetic retinopathy.

Emodin derivatives as novel potent DPP-4 inhibitors: Design, synthesis, and in vitro evaluation

Dipeptidyl peptidase-4 (DPP-4) inhibitors have gained recognition as effective agents for lowering blood sugar levels, significantly improving glycemic control for individuals with type 2 diabetes mellitus (T2DM). Emodin, an anthraquinone derived from the traditional herbs rhubarb (Rheum officinale) and Polygonum cuspidatum, has been identified as an important component in the development of new treatments for diabetes. In the present work, we explored the DPP-4 inhibitory activity of emodin derivatives. This study focused on the design, synthesis, and evaluation of emodin derivatives for their in vitro DPP-4 inhibitory activity. Molecular docking studies indicated that 3-o-toluoyl emodin (OTEM) had the lowest docking score (−134.073) against the DPP-4 protein among the tested compounds. OTEM also achieved the highest drug-likeness score of 0.56 and demonstrated DPP-4 inhibitory activity, with an IC50 value of 0.77 μM. Furthermore, structure-activity relationship (SAR) analysis suggested that the addition of an ortho-toluoyl group at the C-3 position could enhance DPP-4 inhibition. Additionally, quantitative structure-activity relationship (QSAR) model assessments revealed that log P was the only descriptor significantly influencing DPP-4 inhibitory activity. Therefore, the current study indicates that OTEM could serve as a promising lead compound to address the demand for antidiabetic agents.

Evaluation of retinal nerve fiber layer and choroidal structure in obese children and adolescents

Aim: Obesity-related vascular damage and endothelial dysfunction have deleterious effects on the ocular vasculature. It was aimed to examine optical coherence tomography (OCT) parameters in obese and overweight children and to define their relationship with metabolic markers in this study. Methods: The patient group consisted of 26 obese, 24 overweight patients aged between 8 and 18 years. The control group consisted of 25 healthy children with normal body mass index (BMI). This was a cross-sectional observational study. Serum glucose, lipid parameters, and homeostasis model assessment of insulin resistance (HOMA-IR) were investigated. Measurement of choroidal thickness was performed with Cirrus HD-OCT (Carl Zeiss Meditec Inc., Dublin, CA, USA). Retinal nerve fiber layer (RNFL) thickness was determined by an automatic computer algorithm without the need for user measurement. Results: There were no differences in subfoveal, nasal, temporal choroidal thickness, and RNFL between obese, overweight, and control groups (p>0.05). A positive (linear) moderate relationship was found between RNFL and the HOMA-IR of 26 patients in the obese group (r=0.389) (p=0.049). A positively weak correlation was found between height and RNFL in obese patient group (r=0.264, p=0.028). Conclusion: In the study, RNFL thickness increased as HOMA-IR level increased in obese children and adolescents. RNFL decreased as the height increased in obese children and adolescents. We believe that more comprehensive data about the effect of obesity on RNFL and choroidal thickness will be obtained with prospective studies in which the obese patient group with insulin resistance is taken separately and disease durations are defined, and long-term patient follow-up is performed.

Three-dimensional intelligent monitoring and early warning technology for tailings ponds based on spatiotemporal fusion of multisource big data.

To solve the difficult problems of tailings dam instability and environmental pollution, multisource information perception, prediction and early warning technology for tailings dams are investigated. Taking a tailings pond in China as an example, a three-dimensional visualization intelligent management platform based on the spatiotemporal fusion of multisource big data is established to realize intelligent real-time monitoring, prediction and early warning of tailings dams. A monitoring system for air-space-ground integration was developed via high-resolution optical image recording, unmanned aerial vehicles (UAVs), radar, video surveillance and displacement sensors. This approach can realize pollution monitoring and efficient identification of high-risk areas. In addition, a machine learning algorithm is used to mine spatiotemporal data in detail. The Alibaba cloud platform was adopted to develop a data integration framework. Multisensor spatiotemporal data from tailings dams and multisource monitoring data from the environment were integrated. The integrated management of tailings dam environmental monitoring, pollution and stability assessment is realized. A stability prediction model for tailings dams based on multisource data is proposed. The temporal and spatial information of various forms of data is analysed from multiple levels and perspectives. Rapid prediction of the disaster situation and stability of tailings ponds is realized. Moreover, a tailings pollution assessment model based on a neural network is integrated with multisource information to establish a multifactor environmental pollution neural network assessment model and a multilevel warning platform. This work can provide technical support for intelligent monitoring and early warning systems for tailings ponds.

Application of time series and multivariate statistical models for water quality assessment and pollution source apportionment in an Urban River, New Jersey, USA.

Water quality monitoring reveals changing trends in the environmental condition of aquatic systems, elucidates the prevailing factors impacting a water body, and facilitates science-backed policymaking. A 2020 hiatus in water quality data tracking in the Lower Passaic River (LPR), New Jersey, has created a 5-year information gap. To gain insight into the LPR water quality status during this lag period and ahead, water quality indices computed with 16-year historical data available for 12 physical, chemical, nutrient, and microbiological parameters were used to predict water quality between 2020 and 2025 using seasonal autoregressive moving average (ARIMA) models. Average water quality ranged from good to very poor (34 ≤ µWQI ≤ 95), with noticeable spatial and seasonal variations detected in the historical and predicted data. Pollution source tracking with the positive matrix factorization (PMF) model yielded significant R2 values (0.9 < R2 ≤ 1) for the input parameters and revealed four major LPR pollution factors, i.e., combined sewer systems, surface runoff, tide-influenced sediment resuspension, and industrial wastewater with pollution contribution rates of 23-30.2% in the upstream and downstream study areas. Significant correlation of toxic metals, nutrients, and sewage indicators suggest similarities in their sources.

A Comprehensive Review on the Screening Models for the Pharmacological Assessment of Antipsychotic Drugs

Background: Psychosis is a debilitating mental disorder characterized by a profound disconnection from reality, manifesting in symptoms such as hallucinations, delusions, and disorganized thinking. The pathophysiology of psychosis is multifaceted, involving an interplay of neurobiological, genetic, and environmental factors. Neurobiologically, dysregulation of neurotransmitter systems particularly dopaminergic, serotonergic, and glutamatergic pathways-plays a central role, with excessive dopaminergic activity linked to positive symptoms and glutamatergic dysfunction implicated in cognitive impairments. Genetic predisposition, evidenced by significant heritability and associations with specific genetic variants, intersects with environmental factors such as stress, trauma, and substance use to influence the onset and progression of psychosis. Cognitive disruptions, including deficits in attention, memory, and executive function, exacerbate the disorder’s impact. This phenomenon has led to short-term as well as long-term psychosocial and mental health implications for all. Objective: To determine the antipsychotic activity of pharmaceuticals, numerous antipsychotic screening models are available. Determining the optimal animal model for measuring antipsychotic activity is the primary goal of this study. Methods: A search for literature was carried out using several keywords, including "Antipsychotic," "In-vivo models," "In-vitro models," and "Behavior models," on the databases Science Direct and PubMed. For the purpose of obtaining the most appropriate articles to fulfil the goal of this review article, the search was customized by using the necessary filters. Results: Research and review articles based on neuroleptic screening models are available to determine the antipsychotic activity of novel pharmacological compounds. Conclusion: Following our research, we identified several helpful models for evaluating the antipsychotic activity of pharmaceuticals and proposed that combining invitro and in-vivo techniques with behavioral methodologies might yield the most appropriate results for our field of study.

Reducing uncertainties of climate projections on solar energy resources in Brazil.

The share of solar power in Brazil's electrical grid has rapidly increased, relieving GHG emissions and diversifying energy sources for greater energy security. Besides that, solar resource is susceptible to climate change, adding uncertainty to electrical grid resilience. This study uses satellite and reanalysis data to evaluate the performance of CMIP6 models in replicating and predicting surface solar irradiance (SSR) in Brazil. The results from the most reliable models indicate an increase in SSR by 2% to 8% in most regions, with a decrease of around 3% in the South. These findings highlight the potential for increased photovoltaic (PV) yield if backed by supportive public policies while underlining the importance of uncertainty assessment of climate models.

Decision-analytics-based PET plastic recycling selection - a hesitant fuzzy comprehensive ratio assessment model

Decision-analytics-based PET plastic recycling selection - a hesitant fuzzy comprehensive ratio assessment model

Reflective portfolios: a learning and self-assessment tool

Recent studies have emphasized the growing relevance of portfolios in higher education, particularly as a tool that fosters reflective and formative assessment practices. This article presents a qualitative study conducted with a group of Education students, exploring the portfolio as the primary assessment method. The research investigates the conditions under which portfolios can serve as effective tools for both self and peer assessment, using reflective cognition (metacognition) to enhance learning. Classroom observations were combined with open-ended questionnaires, and data analysis was conducted using webQDA software to ensure rigor and objectivity in interpreting the findings. The study reveals that the use of portfolios not only fostered student agency and autonomy but also strengthened self-responsibility and promoted deeper engagement with the learning process. Furthermore, portfolios facilitated a more dynamic, transparent, and collaborative relationship between students and instructors, offering a structured yet flexible approach to assessment. By aligning with competency-based curricula, the portfolio enables a more personalized and meaningful evaluation of students' development, shifting away from traditional, static assessment models. This study contributes to the advancement of assessment practices in higher education, advocating for portfolios as a critical tool in promoting cognitive development, reflexive thinking, and an integrated approach to learning and assessment.

Research on doctor-patient communication teaching for oncology residents: a new teaching model.

At present, there is no specific teaching method for doctor-patient communication for oncology residents. This study combined BOPPPS (bridge-in, learning objective, pretest, participatory learning, posttest, and summary) teaching model and SBAR (situation-background-assessment-recommendation) communication model to try a new teaching and assessment model of doctor-patient communication, aiming to explore and improve the teaching method of doctor-patient communication for oncology residents. Ninety residents were randomly divided into two groups: the experimental group (n = 45) was trained with the BOPPPS teaching model combined with the SBAR communication model, the routine teaching method was adopted in the control group (n = 45). Indicators of assessment included doctor-patient communication skills, satisfaction with teaching, and patient satisfaction. The scores for doctor-patient communication ability were significantly better in experimental group than control group (p < 0.05). The degree of satisfaction degree (very satisfied + satisfied) of the experimental group were higher than control group (p < 0.05). The overall teaching satisfaction of the experimental group was 100.00%, the control group was 77.78%, p < 0.001. Patients' satisfaction with the residents in the experimental group (93.3%) was significantly higher than control group (80.0%), p = 0.043. The application of the BOPPPS combined with the SBAR can effectively enhance residents' doctor-patient communication ability and improve teaching satisfaction and patient satisfaction. This new model can effectively improve resident physician‒patient communication ability, which is worth actively promoting in clinical teaching work.

The Environmental Stake of Bitcoin Mining: Present and Future Challenges

The environmental impact of Bitcoin mining has raised severe concerns considering the expected growth of 30% by 2030. This study aimed to develop a Life Cycle Assessment model to determine the carbon dioxide equivalent emissions associated with Bitcoin mining, considering material requirements and energy demand. By applying the impact assessment method IPCC 2021 GWP (100 years), the GHG emissions associated with electricity consumption were estimated at 51.7 Mt CO2 eq/year in 2022 and calculated by modelling real national mixes referring to the geographical area where mining takes place, allowing for the determination of the environmental impacts in a site-specific way. The estimated impacts were then adjusted to future energy projections (2030 and 2050), by modelling electricity mixes coherently with the spatial distribution of mining activities, the related national targeted goals, the increasing demand for electricity for hashrate and the capability of the systems to recover the heat generated in the mining phase. Further projections for 2030, based on two extrapolated energy consumption models, were also determined. The outcomes reveal that, in relation to the considered scenarios and their associated assumptions, breakeven points where the increase in energy consumption associated with mining nullifies the increase in the renewable energy share within the energy mix exist. The amount of amine-based sorbents hypothetically needed to capture the total CO2 equivalent emitted directly and indirectly for Bitcoin mining reaches up to almost 12 Bt. Further developments of the present work would rely on more reliable data related to future energy projections and the geographical distribution of miners, as well as an extension of the environmental categories analyzed. The Life Cycle Assessment methodology represents a valid tool to support policies and decision makers.

Effect of exercise alone and in combination with time-restricted eating on cardiometabolic health in menopausal women

There is a need to investigate the effect of lifestyle modifications on cardiometabolic health-related issues that occur during menopause. The aim of this study was to compare the effect of resistance and endurance circuit training program alone (exercise group, n = 34) with the effect of time-restricted eating (16:8) combined with a training program (combination group, n = 28) on cardiometabolic health in 62 menopausal women (aged 51.3 ± 4.69 years). Testing was conducted before and after a 12-week period and included an assessment of body composition, glycemic control, lipid panel, blood pressure, and anthropometric measurements. Decreases in body mass index and systolic blood pressure were significantly greater in the combination group than in the exercise group (F(1,60) = 4.482, p = 0.038, η2 = 0.07; F(1,57) = 5.215, p = 0.026, η2 = 0.08, respectively, indicating moderate effects). There were significant decreases in fat mass (p = 0.001, r = 0.654), glucose level (p = 0.017, r = 0.459), insulin level (p = 0.013, r = 0.467), homeostatic model assessment for insulin resistance (p = 0.009, r = 0.499), waist circumference (p = 0.002, r = 0.596), and waist-to-height ratio (p = 0.003, r = 0.588) (indicating moderate effect) in the combination group, while there were no significant changes in the exercise group. There were no changes in lipid panel indicators in either group. This is the first study to investigate the effect of time-restricted eating combined with exercise in menopausal women. The results of the study provide evidence that the combination of time-restricted eating and exercise leads to a greater body mass index reduction than exercise alone in menopausal women.Trial registration: ClinicalTrials.gov, NCT06138015 registered 18 November 2023—Retrospectively registered, https://clinicaltrials.gov/study/NCT06138015.

Determination of the Modal Parameters of the Historical Elevated Water Tank Using Experimental and Numerical Methods

Determining the modal parameters of historical buildings is crucial for understanding their dynamic behavior, which is essential for their preservation and safety for future generations. Experimental and numerical studies are commonly used to characterize modal properties such as natural frequencies and mode shapes. Experimental studies typically employ the operational modal analysis method, while numerical studies employ the finite element method. Vibration measurements of the structure under various environmental conditions, including wind and traffic, were used to determine the modal parameters. However, discrepancies often arise between modal parameters obtained from experimental research and those assessed by finite element models, primarily due to unknown factors like boundary conditions and material properties. The purpose of this study was to measure the vibrations of a historic elevated water tank a 150-year history under ambient conditions to determine its modal characteristics. Comparing the modal parameters obtained from numerical and experimental investigations revealed that the water tank's finite element model requires updating to align with the findings of the experimental modal study. Using the updated finite element model in future evaluations or assessments of the structure can lead to a better understanding of the behavior of the structure.

Relationship Between Iron Deficiency Anemia and Stunting in Pediatric Populations in Developing Countries: A Systematic Review and Meta-Analysis.

Iron deficiency anemia (IDA) and stunting are prevalent global health issues, particularly in developing countries, where previous studies have suggested a potential relationship between them. This systematic review aims to analyze the relationship between iron deficiency anemia and stunting in pediatric populations in developing countries. Literature searches were conducted on PubMed, EMBASE, Cochrane Library, and EBSCO Host. The primary outcome was the association between IDA and stunting. Risk of bias was assessed using the Newcastle-Ottawa Scale (NOS) for cohort studies and the Effective Public Health Practice Project (EPHPP) for other observational studies. Meta-analysis was performed with a random-effects model and heterogeneity assessment. A Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) assessment was performed to determine the certainty and importance of the study. Out of 19,095 articles, 15 studies were included in the systematic review, and 4 studies were included in the meta-analysis, encompassing 21,936 subjects aged 0 to 12 years. IDA prevalence ranged from 3.6 to 58.8%, while stunting prevalence varied from 6.6 to 44.5%. Nine articles supported a significant relationship between IDA and stunting, revealing that stunted children had a 1.31-6.785 times higher risk of developing IDA. The odds ratio of children with IDA to be stunted was 2.27 (95% CI = 1.30-3.95). All studies exhibited a moderate risk of bias. GRADE assessment suggested that the evidence's certainty is low but important. The high IDA prevalence in developing countries, including Indonesia, is associated with stunting in children, suggesting a synergistic relationship.

Liquid solvent direct air capture’s cost and carbon dioxide removal vary with ambient environmental conditions

Emission trajectories produced by integrated assessment models increasingly suggest that gigatonnes of carbon removal will be required to stabilize atmospheric greenhouse gas concentrations at safe levels. This can be accomplished using the direct air capture of carbon dioxide, among other technologies. Process models of these systems assume that they would operate at standard ambient temperature and pressure, when capture rates vary with ambient conditions, including temperature, relative humidity, and other factors. Here, we build an open-source model of a liquid solvent direct air capture technology and analyze its capture performance as a function of hourly varying ambient environmental conditions across Canada. We find that, in the cool climate considered, capture performance is degraded due to both varying environmental conditions and the intermittent operation that could result. Our findings can be used to calibrate policy and investment decisions, and to support engineers in making operational design choices.

Subjectivity of visual assessments in FOCUS kinetics and acceptability of first-order fits for regulatory modelling

The degradation half-life (DegT50) of a substance in soil plays an important role in the approval process of a plant protection product and is a sensitive input parameter for regulatory models. It is usually derived through least squares optimizations of mathematical models to measured degradation data according to EU FOCUS degradation kinetics guidance. A strong consensus on degradation parameters provides a solid foundation for parts of the environmental risk assessment. The DegT50 of a substance for regulatory modeling is preferably derived from a single first-order (SFO) model as this is currently the only kinetic model implemented in EU regulatory models of the environmental fate of pesticides. However, kinetic optimisation tools do not always provide a regulatory acceptable SFO fit even though a visual inspection of the data suggests it may be possible. It was therefore hypothesized that more acceptable SFO fits might be achieved by adapting the objective function that is minimized during the optimization.Eight objective functions with varying weightings were tested on 29 laboratory soil degradation datasets. A web-based app was developed to allow experts in environmental safety of plant protection products to visually assess the goodness of fits resulting from different objective functions. The visual assessments and a quantitative metric, newly introduced in the proposed update of the FOCUS guidance, show that the acceptability of SFO fits can be increased, but no single objective function exclusively improves all fits. The assessment reveals that expert judgment is very subjective. Participants tended to change their mind when judging the acceptance of a fit, assumingly caused by a learning curve or a period of calibration.It is concluded that different objective functions could be considered in the kinetic assessment as it can improve the acceptability of SFO fits and hence endpoints for regulatory modeling. This study reveals that various qualitative factors influence the visual judgment of experts when performing a kinetic modeling assessment. The proposed quantitative metric seems to be in alignment with the visual assessment of fits to derive modeling endpoints and a promising step toward less subjective kinetic modeling assessments.