Influence of monitoring data selection for optimization of a steady state multimedia model on the magnitude and nature of the model prediction bias

Pharmaceuticals and personal care product modelling: Unleashing artificial intelligence and machine learning capabilities and impact on one health and sustainable development goals

The presence of pharmaceutical and personal care products (PPCPs) in the environment poses a significant threat to environmental resources, given their potential risks to ecosystems and human health, even in trace amounts. While mathematical modelling offers a comprehensive approach to understanding the fate and transport of PPCPs in the environment, such studies have garnered less attention compared to field and laboratory investigations. This review examines the current state of modelling PPCPs, focusing on their sources, fate and transport mechanisms, and interactions within the whole ecosystem. Emphasis is placed on critically evaluating and discussing the underlying principles, ongoing advancements, and applications of diverse multimedia models across geographically distinct regions. Furthermore, the review underscores the imperative of ensuring data quality, strategically planning monitoring initiatives, and leveraging cutting-edge modelling techniques in the quest for a more holistic understanding of PPCP dynamics. It also ventures into prospective developments, particularly the integration of Artificial Intelligence (AI) and Machine Learning (ML) methodologies, to enhance the precision and predictive capabilities of PPCP models. In addition, the broader implications of PPCP modelling on sustainability development goals (SDG) and the One Health approach are also discussed. GIS-based modelling offers a cost-effective approach for incorporating time-variable parameters, enabling a spatially explicit analysis of contaminant fate. Swin-Transformer model enhanced with Normalization Attention Modules demonstrated strong groundwater level estimation with an R2 of 82 %. Meanwhile, integrating Interferometric Synthetic Aperture Radar (InSAR) time-series with gravity recovery and climate experiment (GRACE) data has been pivotal for assessing water-mass changes in the Indo-Gangetic basin, enhancing PPCP fate and transport modelling accuracy, though ongoing refinement is necessary for a comprehensive understanding of PPCP dynamics. The review aims to establish a framework for the future development of a comprehensive PPCP modelling approach, aiding researchers and policymakers in effectively managing water resources impacted by increasing PPCP levels.

Presence of polycyclic aromatic hydrocarbons among multi-media in a typical constructed wetland located in the coastal industrial zone, Tianjin, China: Occurrence characteristics, source apportionment and model simulation

In-depth understanding and accurately predicting the occurrence and fate of polycyclic aromatic hydrocarbons (PAHs) in constructed wetlands (CWs) is extremely crucial for optimizing the CWs construction and strengthening the risk control. However, few studies have focused on the PAHs among sediment-water-plant and model simulation in CWs. In this study, sediment, surface water and reed samples were gathered and analyzed from a typical CW. The concentrations of 16 PAHs (Σ₁₆PAHs) in sediments, surface water and reeds ranged from 620 to 4277 μg/kg, 114 to 443 ng/L and 74.5 to 362 μg/kg, respectively. The coefficients of variation (CV) were calculated as 0.796, 0.431 and 0.473 for the above three media respectively, indicating that the spatial distribution variation was medium intensity. The fugacity fraction (ff) suggested that sediments might act as the secondary release source of most PAHs. According to the diagnostic ratios and principal component analysis-multiple linear regression (PCA-MLR), PAHs in this CW mainly come from fossil fuels combustion and petroleum leakage. PAHs in sediments showed high ecological risk at water inlet and moderate risk at the other functional zones, while low risks for surface water at all functional zones. Although the human health risk assessment indicated relatively low cancer risk, the health risk still cannot be ignored with the continuous input and accumulation of exogenous PAHs. A mathematical model covering the hydraulics parameters and composition characteristics of the wetland was established, and its reliability was verified. The simulated results obtained by the established model were basically consistent with the measured values. In addition, the total remove efficiency of PAHs in surface water was 40.2%, which calculated by the simulated model. This work provides helpful insight into the comprehension of occurrence and fate of PAHs among multi-media in CWs.

Exploring the Environmental Exposure to Methoxychlor, α-HCH and Endosulfan-sulfate Residues in Lake Naivasha (Kenya) Using a Multimedia Fate Modeling Approach

Distribution of pesticide residues in the environment and their transport to surface water bodies is one of the most important environmental challenges. Fate of pesticides in the complex environments, especially in aquatic phases such as lakes and rivers, is governed by the main properties of the contaminants and the environmental properties. In this study, a multimedia mass modeling approach using the Quantitative Water Air Sediment Interaction (QWASI) model was applied to explore the fate of organochlorine pesticide residues of methoxychlor, α-HCH and endosulfan-sulfate in the lake Naivasha (Kenya). The required physicochemical data of the pesticides such as molar mass, vapor pressure, air-water partitioning coefficient (K_AW), solubility, and the Henry's law constant were provided as the inputs of the model. The environment data also were collected using field measurements and taken from the literature. The sensitivity analysis of the model was applied using One At a Time (OAT) approach and calibrated using measured pesticide residues by passive sampling method. Finally, the calibrated model was used to estimate the fate and distribution of the pesticide residues in different media of the lake. The result of sensitivity analysis showed that the five most sensitive parameters were K_OC, logKow, half-life of the pollutants in water, half-life of the pollutants in sediment, and K_AW. The variations of outputs for the three studied pesticide residues against inputs were noticeably different. For example, the range of changes in the concentration of α-HCH residue was between 96% to 102%, while for methoxychlor and endosulfan-sulfate it was between 65% to 125%. The results of calibration demonstrated that the model was calibrated reasonably with the R² of 0.65 and RMSE of 16.4. It was found that methoxychlor had a mass fraction of almost 70% in water column and almost 30% of mass fraction in the sediment. In contrast, endosulfan-sulfate had highest most fraction in the water column (>99%) and just a negligible percentage in the sediment compartment. α-HCH also had the same situation like endosulfan-sulfate (e.g., 99% and 1% in water and sediment, respectively). Finally, it was concluded that the application of QWASI in combination with passive sampling technique allowed an insight to the fate process of the studied OCPs and helped actual concentration predictions. Therefore, the results of this study can also be used to perform risk assessment and investigate the environmental exposure of pesticide residues.

A multimedia fugacity model to estimate the fate and transport of polycyclic aromatic hydrocarbons (PAHs) in a largely urbanized area, Shanghai, China

Increasing PAHs pollution is creating more complex urban pollution system. However, the availability of sufficient monitoring activities for PAHs in multicompartment and corresponding multi-interface migration processes is still not well understood. In this study, a Level III steady state fugacity model was validated to evaluate the detailed local variations, and mass fluxes of PAHs in various environmental compartments (i.e., air, soil, sediment, water, vegetation and organic film). This model was applied to a region of Shanghai in 2012 based on a large number of measured data and brings model predictions in 2020. The model results indicate that most of the simulated concentrations agreed with the observed values within one order of magnitude with a tendency of underestimation for vegetation. Direct emission is the main input pathway of PAHs entering the atmosphere, whereas advection is the main outward flow from Shanghai. Organic film was achieved the highest concentration of PAHs compared to other compartments up to 58.17 g/m³. The soil and sediment served as the greatest sinks of PAHs and have the longest retention time (2421.95-78642.09 h). Importantly, a decreasing trend of PAHs was observed in multimedia from 2012 to 2020 and the transfer flux from the air to vegetation to soil was the dominant pathways of BaP intermedia circulation processes. A sensitivity analysis showed that temperature was the most influential parameter, especially for Phe. A Monte Carlo simulation emphasized heavier PAHs were overpredicted in film and sediment, but lighter PAHs in air and water were generally underestimated.