Using Geospatial Data and Random Forest To Predict PFAS Contamination in Fish Tissue in the Columbia River Basin, United States

Statistical Mapping of PFOA and PFOS in Groundwater throughout the Contiguous United States

Per-and polyfluoroalkyl substances (PFAS) are synthetic chemicals that are increasingly being detected in groundwater. The negative health consequences associated with human exposure to PFAS make it essential to quantify the distribution of PFAS in groundwater systems. Mapping PFAS distributions is particularly challenging because a national patchwork of testing and reporting requirements has resulted in sparse and spatially biased data. In this analysis, an inhomogeneous Poisson process (IPP) modeling approach is adopted from ecological statistics to continuously map PFAS distributions in groundwater across the contiguous United States. The model is trained on a unique data set of 8910 PFAS groundwater measurements, using combined concentrations of two PFAS analytes. The IPP model predictions are compared with results from random forest models to highlight the robustness of this statistical modeling approach on sparse data sets. This analysis provides a new approach to not only map PFAS contamination in groundwater but also prioritize future sampling efforts.

Using machine learning to reveal drivers of soil microplastics and assess their stock: A national-scale study

The issue of microplastic (MP) contamination in soil is a significant concern. However, due to limited large-scale studies and stock assessments, our understanding of the drivers of their distribution and fate remains incomplete. To address this, we conducted a comprehensive study in China, collected MP data from 621 sites, and utilized machine learning techniques for analysis. Our findings revealed 9 key factors influencing the distribution of soil MPs, highlighting their nonlinear influence processes. Among these factors, atmospheric deposition emerged as the most dominant driver, while wind and precipitation could lead to the transformation of soil from a sink to a source of MPs. MP concentrations in Chinese soils vary from 1.4 to 4333.1 particles/kg, with human activities significantly affecting their distribution, resulting in higher concentrations in the east and lower concentrations in the west. The estimated MP stock in Chinese soils is 1.92 × 1018 particles, equivalent to a mass of 2.11-8.64 million tonnes. This stock alone surpasses that found in global oceans, making global soil the largest reservoir of MPs. Overall, this study enhances our understanding of the environmental behavior of MPs and provides valuable data and theoretical support for the prevention, control, and management of this contamination.

PFAS in Nigeria: Identifying data gaps that hinder assessments of ecotoxicological and human health impacts

This review examines the extensive use and environmental consequences of Per- and Polyfluoroalkyl Substances (PFAS) on a global scale, specifically emphasizing their potential impact in Nigeria. Recognized for their resistance to water and oil, PFAS are under increased scrutiny for their persistent nature and possible ecotoxicological risks. Here, we consolidate existing knowledge on the ecological and human health effects of PFAS in Nigeria, focusing on their neurological effects and the risks they pose to immune system health. We seek to balance the advantages of PFAS with their potential ecological and health hazards, thereby enhancing understanding of PFAS management in Nigeria and advocating for more effective policy interventions and the creation of safer alternatives. The review concludes with several recommendations: strengthening regulatory frameworks, intensifying research into the ecological and health impacts of PFAS, developing new methodologies and longitudinal studies, fostering collaborative efforts for PFAS management, and promoting public awareness and education to support sustainable environmental practices and healthier communities in Nigeria.

Optimizing the development of contaminated land in China: Exploring machine-learning to identify risk markers

Often available for use, previously developed land, which includes residential and commercial/industrial areas, presents a significant challenge due to the risk to human health. China's 2018 release of health risk assessment standards for land reuse aimed to bridge this gap in soil quality standards. Despite this, the absence of representative indicators strains risk managers economically and operationally. We improved China's land redevelopment approach by leveraging a dataset of 297,275 soil samples from 352 contaminated sites, employing machine learning. Our method incorporating soil quality standards from seven countries to discern patterns for establishing a cost-effective evaluative framework. Our research findings demonstrated that detection costs could be curtailed by 60% while maintaining consistency with international soil standards (prediction accuracy = 90-98%). Our findings deepen insights into soil pollution, proposing a more efficient risk assessment system for land redevelopment, addressing the current dearth of expertise in evaluating land development in China.

Target and suspect per- and polyfluoroalkyl substances in fish from an AFFF-impacted waterway

A major source of toxic per- and polyfluoroalkyl substances (PFAS) is aqueous film-forming foams (AFFF) used in firefighting and training at airports and military installations, however, PFAS have many additional sources in consumer products and industrial processes. A field study was conducted on fish tissues from three reaches of the Columbia Slough, located near Portland International Airport, OR, that are affected by AFFF and other PFAS sources. Fishes including largescale sucker (Catostomus macrocheilus), goldfish (Carassius auratus), and largemouth bass (Micropterus salmoides) were collected in 2019 and 2020. Fish blood, liver, and fillet (muscle) were analyzed for target and suspect PFAS by liquid chromatography high resolution mass spectrometry (LC-HRMS). Data were analyzed for patterns by fish species, tissue type, and river reach. Thirty-three out of 50 target PFAS and additional suspect compounds were detected at least once during the study, at concentrations up to 856 ng/g. Seven carboxylic acids (PFOA, PFNA, PFDA, PFUdA, PFDoA, PFTrDA, PFTeDA), three sulfonates (PFHxS, PFOS, PFDS), three electrofluorination-based compounds (FBSA, FHxSA, FOSA), and two fluorotelomer-based compounds (8:2 FTS, 10:2 FTS) were the most frequently detected compounds in all tissue types. The C6 (PFHxS) to C10 (PFDS) homologs were detected with PFOS and FHxSA at concentrations 1-3 orders of magnitude greater than the other PFAS detected. This is the first report of Cl-PFOS, FPeSA, and FHpSA detected in fish tissue. In all fish samples, fillet concentrations of PFAS were the lowest, followed by liver, and blood concentrations of PFAS were the highest. Differences in PFAS concentrations were driven primarily by tissue types and to a lesser extent fish species, but weakly by river reach. The Oregon Health Authority modified an existing fish consumption advisory on the Columbia Slough to recommend no whole-body consumption of most fish to avoid elevated levels of PFOS in fish liver. Measured PFAS concentrations in fish tissues indicate the potential for adverse ecological effects.