A risk ranking of pesticides in Irish drinking water considering chronic health effects

Exploring the Use of a Lipopeptide in Dipalmitoylphosphatidylcholine Monolayers for Enhanced Detection of Glyphosate in Aqueous Environments

The growing reliance on pesticides for pest management in agriculture highlights the need for new analytical methods to detect these substances in food and water. Our research introduces a SPRWG-(C18H37) lipopeptide (LP) as a functional analog of acetylcholinesterase (AChE) for glyphosate detection in environmental samples using phosphatidylcholine (PC) monolayers. This LP, containing hydrophilic amino acids linked to an 18-carbon aliphatic chain, alters lipid assembly properties, leading to a more flexible system. Changes included reduced molecular area and peak pressure in Langmuir adsorption isotherms. Small angle X-ray scattering (SAXS) and atomic force microscopy (AFM) analyses provided insights into the LP's structural organization within the membrane and its interaction with glyphosate (PNG). Structural and geometric parameters, as derived from in silico molecular dynamics simulations (MD), substantiated the impact of LP on the monolayer structure and the interaction with PNG. Notably, the presence of the LP and glyphosate increased charge transfer resistance, indicating strong adherence of the monolayer to the indium tin oxide (ITO) surface and effective pesticide interaction. A calibration curve for glyphosate concentration adjustment revealed a detection limit (LOD) of 24 nmol L-1, showcasing the high sensitivity of this electrochemical biosensor. This LOD is significantly lower than that of a similar colorimetric biosensor in aqueous media with a detection limit of approximately 0.3 μmol L-1. Such an improvement in sensitivity likely stems from adding a polar residue to the amino acid chain of the LP.

Assessing pesticide residues occurrence and risks in water systems: A Pan-European and Argentina perspective

Freshwater ecosystems face a particularly high risk of biodiversity loss compared to marine and terrestrial systems. The use of pesticides in agricultural fields is recognized as a relevant stressor for freshwater environments, exerting a negative impact worldwide on the overall status and health of the freshwater communities. In the present work, part of the Horizon 2020 funded SPRINT project, the occurrence of 193 pesticide residues was investigated in 64 small water bodies of distinct typology (creeks, streams, channels, ditches, rivers, lakes, ponds and reservoirs), located in regions with high agricultural activity in 10 European countries and in Argentina. Mixtures of pesticide residues were detected in all water bodies (20, median; 8-40 min-max). Total pesticide levels found ranged between 6.89 and 5860 ng/L, highlighting herbicides as the dominant type of pesticides. Glyphosate was the compound with the highest median concentration followed by 2,4-D and MCPA, and in a lower degree by dimethomorph, fluopicolide, prothioconazole and metolachlor(-S). Argentina was the site with the highest total pesticide concentration in water bodies followed by The Netherlands, Portugal and France. One or more pesticides exceeded the threshold values established in the European Water Framework Directive for surface water in 9 out of 11 case study sites (CSS), and the total pesticide concentration surpassed the reference value of 500 ng/L in 8 CSS. Although only 5 % (bifenthrin, dieldrin, fipronil sulfone, permethrin, and terbutryn) of the individual pesticides denoted high risk (RQ > 1), the ratios estimated for pesticide mixtures suggested potential environmental risk in the aquatic compartment studied.

Stochastic modelling of pesticide transport to drinking water sources via runoff and resulting human health risk assessment

A modelling framework was developed to facilitate a probabilistic assessment of health risks posed by pesticide exposure via drinking water due to runoff, with the inclusion of influential site conditions and in-stream processes. A Monte-Carlo based approach was utilised to account for the inherent variability in pesticide and population properties, as well as site and climatic conditions. The framework presented in this study was developed with an ability to integrate different data sources and adapt the model for various scenarios and locations to meet the users' needs. The results from this model can be used by farm advisors and catchment managers to identify lower risk pesticides for use for given soil and site conditions and implement risk mitigation measures to protect water resources. Pesticide concentrations in surface water, and their risk of regulatory threshold exceedances, were simulated for fifteen pesticides in an Irish case study. The predicted concentrations in surface water were then used to quantify the level of health risk posed to Irish adults and children. The analysis indicated that herbicides triclopyr and MCPA occur in the greatest concentrations in surface water, while mecoprop was associated with the highest potential for health risks. The study found that the modelled pesticides posed little risk to human health under current application patterns and climatic conditions in Ireland using international acceptable intake values. A sensitivity study conducted examined the impact seasonal conditions, timing of application, and instream processes, have on the transport of pesticides to drinking water.

Chlormequat chloride induced activation of calmodulin mediated PI3K/AKT signaling pathway led to impaired sperm quality in pubertal mice

Chlormequat chloride (CCC), as a widely used plant growth regulator, can cause impaired sperm quality and decreased testosterone synthesis in pubertal rats, but the underlying mechanism remains unclear. The purpose of this study was to elucidate the toxicokinetics and tissue distribution of CCC, as well as the possible mechanism of CCC-induced impairment in sperm quality. The concentration of CCC reached its peak 1 h after a single dose (200 mg/kg·bw) administration in mice plasma, and a bimodal phenomenon appeared in the testes, liver, and epididymis. In vivo, 200 mg/kg CCC caused testicular damage and impaired sperm quality in pubertal mice, and the expression of p-tyrosine and GSK3α decreased in cauda epididymidis, sperm and testes. CCC also caused the down-regulation of AKAP4 and the up-regulation of calmodulin (CaM), and activated the PI3K/AKT signaling pathway in the testes. In vitro, CCC reduced the levels of p-tyrosine, AKAP4 and GSK3α, increased the level of CaM and activated the PI3K/AKT signaling pathway in GC-1 cells. CaM antagonist (W-7 hydrochloride) and PI3K inhibitor (LY294002) can effectively improve the expression of GSK3α and AKAP4 by suppressing the PI3K/AKT signaling pathway in GC-1 cells treated with CCC. It was indicated that CCC induced impairment in sperm quality might be partially related to the activation of PI3K/AKT signaling pathway mediated by CaM.

Human health risk assessment based on direct and indirect exposure to endocrine disrupting herbicides in drinking, ground, and surface water in Croatia

The recognition of certain herbicides as endocrine disrupting compounds has raised concerns due to their ability to interfere with the normal functioning of the endocrine system, which regulates various physiological processes in organisms. The objective of this study was to assess the possible human health risks associated with terbuthylazine and endocrine-disrupting herbicides atrazine, acetochlor, and metolachlor in the drinking, surface, and groundwater of the Zagreb city region, Croatia. We relied on advanced statistical methods and principal component analysis (PCA), which revealed higher levels of atrazine and acetochlor in drinking and groundwater samples and higher presence of metolachlor and terbuthylazine in surface waters. To evaluate the danger to human health, various exposure scenarios have been assessed. The risk of direct human exposure to analyzed herbicides through drinking or bathing with drinking (tap) or groundwater, as well as from recreational activities like swimming in rivers, streams, and lakes, has been quantified. In addition to these direct exposure scenarios, indirect ones based on consumer goods, fruits, and vegetables, treated with surface and groundwater for irrigation, were assessed to investigate the danger to human health. Judging by the reported herbicide levels there was no significant risk of carcinogenic (CR ≤ 1 × 10-6) or non-carcinogenic (HI < 1) diseases, not even when we assessed the so-called "cocktail effect" of combined the herbicide exposure in different waters.

Impact of historical legacy pesticides on achieving legislative goals in Europe

Pesticides are widely used in agriculture to optimise food production. However, the movement of pesticides into water bodies negatively impacts aquatic environments. The European Union (EU) aims to make food systems fair, healthy and environmentally friendly through its current Farm to Fork strategy. As part of this strategy, the EU plans to reduce the overall use and risk of chemical pesticides by 50 % by 2030. The attainment of this target may be compromised by the prevalence of legacy pesticides arising from historical applications to land, which can persist in the environment for several decades. The current EU Farm to Fork policy overlooks the potential challenges of legacy pesticides and requirements for their remediation. In this review, the current knowledge regarding pesticide use in Europe, as well as pathways of pesticide movement to waterways, are investigated. The issues of legacy pesticides, including exceedances, are examined, and existing and emerging methods of pesticide remediation, particularly of legacy pesticides, are discussed. The fact that some legacy pesticides can be detected in water samples, more than twenty-five years after they were prohibited, highlights the need for improved EU strategies and policies aimed at targeting legacy pesticides in order to meet future targets.

Membrane-based water and wastewater treatment technologies: Issues, current trends, challenges, and role in achieving sustainable development goals, and circular economy

Membrane-based technologies are recently being considered as effective methods for conventional water and wastewater remediation processes to achieve the increasing demands for clean water and minimize the negative environmental effects. Although there are numerous merits of such technologies, some major challenges like high capital and operating costs . This study first focuses on reporting the current membrane-based technologies, i.e., nanofiltration, ultrafiltration, microfiltration, and forward- and reverse-osmosis membranes. The second part of this study deeply discusses the contributions of membrane-based technologies in achieving the sustainable development goals (SDGs) stated by the United Nations (UNs) in 2015 followed by their role in the circular economy. In brief, the membrane based processes directly impact 15 out of 17 SDGs which are SDG1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16 and 17. However, the merits, challenges, efficiencies, operating conditions, and applications are considered as the basis for evaluating such technologies in sustainable development, circular economy, and future development.

Screening priority pesticides for drinking water quality regulation and monitoring by machine learning: Analysis of factors affecting detectability

Proper selection of new contaminants to be regulated or monitored prior to implementation is an important issue for regulators and water supply utilities. Herein, we constructed and evaluated machine learning models for predicting the detectability (detection/non-detection) of pesticides in surface water as drinking water sources. Classification and regression models were constructed for Random Forest, XGBoost, and LightGBM, respectively; of these, the LightGBM classification model had the highest prediction accuracy. Furthermore, its prediction performance was superior in all aspects of Recall, Precision, and F-measure compared to the detectability index method, which is based on runoff models from previous studies. Regardless of the type of machine learning model, the number of annual measurements, sales quantity of pesticide for rice-paddy field, and water quality guideline values were the most important model features (explanatory variables). Analysis of the impact of the features suggested the presence of a threshold (or range), above which the detectability increased. In addition, if a feature (e.g., quantity of pesticide sales) acted to increase the likelihood of detection beyond a threshold value, other features also synergistically affected detectability. Proportion of false positives and negatives varied depending on the features used. The superiority of the machine learning models is their ability to represent nonlinear and complex relationships between features and pesticide detectability that cannot be represented by existing risk scoring methods.

Membrane technology for pesticide removal from aquatic environment: Status quo and way forward

The noxious side effects of pesticides on human health and environment have prompted the search of effective and reliable treatment techniques for pesticide removal. The removal of pesticides can be accomplished through physical, chemical and biologicals. Physical approaches such as filtration and adsorption are prevailing pesticide removal strategies on account of their effectiveness and ease of operation. Membrane-based filtration technology has been recognized as a promising water and wastewater treatment approach that can be used for a wide range of organic micropollutants including pesticides. Nanofiltration (NF), reverse osmosis (RO) and forward osmosis (FO) have been increasingly explored for pesticide removal from aquatic environment owing to their versatility and high treatment efficiencies. This review looks into the remedial strategies of pesticides from aqueous environment using membrane-based processes. The potentials and applications of three prevailing membrane processes, namely NF, RO and FO for the treatment of pesticide-containing wastewater are discussed in terms of the development of advanced membranes, separation mechanisms and system design. The challenges in regards to the practical implementation of membrane-based processes for pesticide remediation are identified. The corresponding research directions and way forward are highlighted. An in depth understanding of the pesticide nature, water chemistry and the pesticide-membrane interactions is the key to achieving high pesticide removal efficiency. The integration of membrane technology and conventional removal technologies represents a new dimension and the future direction for the treatment of wastewater containing recalcitrant pesticides.