Prioritization of substances for national ambient monitoring of sediment in Switzerland

What Approaches Should be Used to Prioritize Pharmaceuticals and Personal Care Products for Research on Environmental and Human Health Exposure and Effects?

Pharmaceuticals and personal care products (PPCPs) are released from multiple anthropogenic sources and thus have a ubiquitous presence in the environment. The environmental exposure and potential effects of PPCPs on biota and humans has aroused concern within the scientific community and the public. Risk assessments are commonly conducted to evaluate the likelihood of chemicals including PPCPs that pose health threats to organisms inhabiting various environmental compartments and humans. Because thousands of PPCPs are currently used, it is impractical to assess the environmental risk of all of them due to data limitations; in addition, new PPCPs are continually being produced. Prioritization approaches, based either on exposure, hazard, or risk, provide a possible means by which those PPCPs that are likely to pose the greatest risk to the environment are identified, thereby enabling more effective allocation of resources in environmental monitoring programs in specific geographical locations and ecotoxicological investigations. In the present review, the importance and current knowledge concerning PPCP occurrence and risk are discussed and priorities for future research are proposed, in terms of PPCP exposure (e.g., optimization of exposure modeling in freshwater ecosystems and more monitoring of PPCPs in the marine environment) or hazard (e.g., differential risk of PPCPs to lower vs. higher trophic level species and risks to human health). Recommended research questions for the next 10 years are also provided, which can be answered by future studies on prioritization of PPCPs. Environ Toxicol Chem 2024;43:488-501. © 2022 SETAC.

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.

Selection of priority pesticides in Japanese drinking water quality regulation: Validity, limitations, and evolution of a risk prediction method

Several risk scoring and ranking methods have been applied for the prioritization of micropollutants, including pesticides, and in the selection of pesticides to be regulated regionally and nationally. However, the effectiveness of these methods has not been evaluated in Japan. We developed a risk prediction method to select pesticides that have a high probability of being detected in drinking water sources where no monitoring data is available. The risk prediction method was used to select new pesticides for the 2013 Primary List in the Japanese Drinking Water Quality Guidelines. Here, we examined the effectiveness of the method on the basis of the results of water quality examinations conducted by water supply authorities across Japan, and studied ways to improve the risk prediction method. Of the 120 pesticides in the 2013 Primary List, 80 were detected in drinking water sources (raw water entering water treatment plants). The rates of detection of the newly selected pesticides and previously listed pesticides were not significantly different: 64% and 68%, respectively. When the risk predictor was revised to incorporate degradability of dry-field pesticides and current pesticide sales data, the rate of detection of pesticides selected as having a high risk of detection improved from 72% to 88%. We prepared regional versions of the Primary List using the revised risk predictors and verified their utility. The number of listed pesticides varied greatly by region, ranging from 32 to 73; all regional lists were much shorter than the national Primary List. In addition, 55% to 100% of the pesticides detected in each region were included in a Regional Primary List. This work verifies the ability of the risk prediction method to screen pesticides and select those with a high risk of detection.

Pesticide prioritization approaches and limitations in environmental monitoring studies: From Europe to Latin America and the Caribbean

Assessment and management of issues related to pesticide residues, such as environmental fate, monitoring and toxicity, are complex and, in many cases, require costly studies. The early establishment of a priority list of pesticides that should be monitored and assigned to a restricted-use policy is an important issue of post-registration Risk Assessment (RA). Various pesticide registration approaches have been adopted by different countries with those from Europe and the USA being the most popular, constituting the major prototypes for registration approaches in other countries. Adoption of pesticide registration and monitoring systems developed in Europe or USA by Latin American and Caribbean countries may underestimate factors affecting the environmental fate and toxicity of pesticides in their own countries. Incentive for this short review was the activities undertaken during the three KNOWPEC workshops held in Costa Rica, Argentina and Bolivia where European pesticide experts met Latin American experience in the form of Costa Rica's exceptional environmental conditions and ecology, Argentina's and Uruguay's soyisation and Bolivia's contrasting climate and agricultural zones. During the parallel activities of the workshop - including scientific presentations, field trips, interviews and meetings among European partners and pesticide stakeholders in Latin America, - the whole pesticide chain (import-export, trade, application, plant protection-efficacy, residues, monitoring, remediation and risk) was studied and clarified. Recently-published chemical prioritization studies were reviewed to consider their use as a tool to support risk assessments. Differences in regional practices are highlighted as regards to the establishment of RA or prioritization strategy in European and Latin American regimes. General guidance of establishing a cost-effective pesticide monitoring scheme in water bodies of Latin America and the Caribbean (LAC) is also proposed. Moreover, we summarize the most important factors that should be taken into consideration for prioritization approaches and categorization used in pesticide environmental monitoring studies. Consideration of current RA approaches and limitations, and pesticide prioritization exercises highlighted in this Commentary could assist in the management of pesticides in Latin America and Caribbean.

The Swiss Ecotox Centre: bridging the gap between research and application

The Swiss Centre for Applied Ecotoxicology (Ecotox Centre) was created in recognition of the urgent societal need to provide expertise, education and tools for assessing the risks and effects of anthropogenic chemicals in the environment. Founded in 2008, the Ecotox Centre conducts applied, practice-oriented research in the areas of aquatic (water and sediment) and terrestrial (with focus on soil) ecotoxicology, and provides further education and consulting services to its stakeholders. To date, its most important activities focus on (1) the validation and standardization of bioassays for use in monitoring of water, sediment or soil quality and (2) the development of tools for retrospective risk assessment, including approaches to assess mixture risk.

Application of prioritization approaches to optimize environmental monitoring and testing of pharmaceuticals

Pharmaceuticals are ubiquitous in the natural environment with concentrations expected to rise as human population increases. Environmental risk assessments are available for a small portion of pharmaceuticals in use, raising concerns over the potential risks posed by other drugs that have little or no data. With >1900 active pharmaceutical ingredients in use, it would be a major task to test all of the compounds with little or no data. Desk-based prioritization studies provide a potential solution by identifying those substances that are likely to pose the greatest risk to the environment and which, therefore, need to be considered a priority for further study. The aim of this review was to (1) provide an overview of different prioritization exercises performed for pharmaceuticals in the environment and the results obtained; and (2) propose a new holistic risk-based prioritization framework for drugs in the environment. The suggested models to underpin this framework are discussed in terms of validity and applicability. The availability of data required to run the models was assessed and data gaps identified. The implementation of this framework may harmonize pharmaceutical prioritization efforts and ensure that, in the future, experimental resources are focused on molecules, endpoints, and environmental compartments that are biologically relevant.