GSI Environmental (United States)

This study presents a systematic quality assurance/quality control (QA/QC) framework for new technology adopters to validate environmental monitoring instruments when consistent, standardized validation and calibration procedures do not readily exist. This QA/QC framework is especially relevant for newly developed environmental monitoring instruments prior to deployment in field settings as part of environmental site investigations. Key QA/QC parameters used in the framework include repeatability, intermediate precision, reproducibility, linearity, limits of detection (LOD), limit of quantification (LOQ), trueness, and recovery. The QA/QC framework is demonstrated on the autonomous rugged optical multigas analyzer for VOCs (AROMA-VOC), a technology that employs cavity ring-down spectroscopy (CRDS) with preconcentration and chromatographic separation prior to CRDS detection. QA/QC protocols for nine VOCs, and results for AROMA-VOC were compared with laboratory-based gas chromatography/mass spectrometer (GC-MS). Results demonstrated high linearity (R 2 > 0.95) and low LOQ values (0.0004 ± 0.0002-0.0455 ± 0.0192 μg/L). The instrument also exhibited ranges of LOD at least an order of magnitude lower than that of the referenced GC-MS. AROMA-VOC demonstrated acceptable precision [repeatability, intraday relative standard deviation (RSD %): 1.72-12.1%; intermediate, interday RSD %: 2.01-10.93%] and substantial recovery (104.8% to 212.4%). Interlaboratory testing also concluded that AROMA-VOC can produce consistent detections (R 2 > 0.90). The z-score findings suggested that the performance of the instrument was satisfactory, with the exceptions of xylenes and 1,3-butadiene. Overall, using the systematic QA/QC framework presented in this study, AROMA-VOC is shown to be a robust method for volatile organic compound analysis.

This review explores the role of Artificial Intelligence (AI) in critical mineral exploration, examining key challenges and opportunities. Global decarbonisation efforts are driving a significant increase in the demand for critical minerals, intensifying the need to find new deposits, improve operational efficiencies and diversify global mineral supply capabilities. Challenges encountered in critical mineral exploration, such as increasingly complex geological settings in new exploration, declining ore grades and the need for sustainable practices, are calling for a more comprehensive analysis of a diverse set of aspects, including large geoscientific and economic datasets, as well as Environmental, Social and Governance (ESG) considerations. Traditional methods of analysing such extensive information are time-intensive, expensive and often result in lower predictability. This, combined with the growing need for faster and more accurate decision-making, has driven the adoption of innovative approaches such as AI-based techniques that bring vast amounts of multifaceted information into the analysis. Integrating AI applications in the exploration of critical minerals is bringing rapid transformation to the sector, driving new trends in the market dynamics. AI methodologies, Machine Learning (ML) and AI-enabled data analytics are improving the predictive modelling and automation of exploration studies and allowing enhanced decision-making capabilities. The shift towards data-driven strategies allows the use of both new and previously underutilised datasets owned by the companies, leading to better assessments of the project viability, more effective and rapid evaluation of a wide range of datasets for exploration potential and identification of opportunities for cost reduction. These advancements influence risk identification and management, bring strategic shifts in the critical minerals market and global supply chains and offer valuable insights to stakeholders shaping investment patterns. Challenges in the application of AI in critical mineral exploration include data requirements, technical complexity and ethical and regulatory concerns. Recognising AI’s vast potential, extensive research and development efforts are underway, focussing on refining AI algorithms, developing novel approaches to integrate with geoscientific data, promoting collaboration between geoscientists and AI experts and addressing the ethical, regulatory and ESG considerations.

About 3 billion new tires are produced each year and about 800 million tires become waste annually. Global dependence upon tires produced from natural rubber and petroleum-based compounds represents a persistent and complex environmental problem with only partial and often-times, ineffective solutions. Tire emissions may be in the form of whole tires, tire particles, and chemical compounds, each of which is transported through various atmospheric, terrestrial, and aquatic routes in the natural and built environments. Production and use of tires generates multiple heavy metals, plastics, PAH's, and other compounds that can be toxic alone or as chemical cocktails. Used tires require storage space, are energy intensive to recycle, and generally have few post-wear uses that are not also potential sources of pollutants (e.g., crumb rubber, pavements, burning). Tire particles emitted during use are a major component of microplastics in urban runoff and a source of unique and highly potent toxic substances. Thus, tires represent a ubiquitous and complex pollutant that requires a comprehensive examination to develop effective management and remediation. We approach the issue of tire pollution holistically by examining the life cycle of tires across production, emissions, recycling, and disposal. In this paper, we synthesize recent research and data about the environmental and human health risks associated with the production, use, and disposal of tires and discuss gaps in our knowledge about fate and transport, as well as the toxicology of tire particles and chemical leachates. We examine potential management and remediation approaches for addressing exposure risks across the life cycle of tires. We consider tires as pollutants across three levels: tires in their whole state, as particulates, and as a mixture of chemical cocktails. Finally, we discuss information gaps in our understanding of tires as a pollutant and outline key questions to improve our knowledge and ability to manage and remediate tire pollution.

Nontuberculous mycobacteria (NTM) are environmentally acquired opportunistic pathogens that can cause chronic lung disease. Within the U.S., Hawai'i shows the highest prevalence rates of NTM lung infections. Here, we investigated a potential role for active volcanism at the Kīlauea Volcano located on Hawai'i Island in promoting NTM growth and diversity. We recovered NTM that are known to cause lung disease from plumbing biofilms and soils collected from the Kīlauea environment. We also discovered viable Mycobacterium avium, Mycobacterium abscessus, and Mycobacterium intracellulare subsp. chimaera on volcanic ash collected during the 2018 Kīlauea eruption. Analysis of soil samples showed that NTM prevalence is positively associated with bulk content of phosphorus, sulfur, and total organic carbon. In growth assays, we showed that phosphorus utilization is essential for proliferation of Kīlauea‐derived NTM, and demonstrate that NTM cultured with volcanic ash adhere to ash surfaces and remain viable. Ambient dust collected on O'ahu concurrent with the 2018 eruption contained abundant fresh volcanic glass, suggestive of inter‐island ash transport. Phylogenomic analyses using whole genome sequencing revealed that Kīlauea‐derived NTM are genetically similar to respiratory isolates identified on other Hawaiian Islands. Consequently, we posit that volcanic eruptions could redistribute environmental microorganisms over large scales. While additional studies are needed to confirm a direct role of ash in NTM dispersal, our results suggest that volcanic particulates harbor and can redistribute NTM and should therefore be studied as a fomite for these burgeoning, environmentally acquired respiratory infections.

Abstract Remediation of per‐ and polyfluoroalkyl substances (PFAS) in groundwater is particularly challenging because of their unique chemical and fate and transport properties. Many conventional in‐situ remediation technologies, commonly applied to address other groundwater contaminants, have proven ineffective for treatment of PFAS. Given their stability, destruction of PFAS in‐situ has remained elusive as an in‐situ treatment option. Consequently, new approaches to manage PFAS groundwater plumes are of great interest to environmental practitioners. We propose that enhancing PFAS retention can play an important role in reducing PFAS mass flux and providing long‐term protection of downgradient groundwater receptors. Enhanced retention of PFAS fits directly into the enhanced attenuation (EA) framework, an established groundwater remediation strategy that was developed in the first decade of the 2000s for other groundwater contaminants. In this paper, we propose eight EA approaches for PFAS in groundwater, including technologies that are currently being implemented at PFAS sites (e.g., injection of particulate carbon amendments), applications of conventional remediation technologies to PFAS sites (e.g., capping to retain PFAS in the vadose zone), and novel, innovative approaches (e.g., intentional food grade LNAPL emplacement to retain PFAS) for enhanced PFAS retention. These EA approaches leverage the properties of PFAS to (i) facilitate sorption to conventional and novel sorbents, (ii) concentrate PFAS at air/water interface via gas sparging, and/or (iii) encourage retention via tidal pumping and PFAS salting out processes. For each of the proposed EA approaches, we describe the methodology or concept and discuss the key processes, potential applications, anticipated increases in PFAS retention compared to natural systems, potential challenges, alternate designs, and current likelihood of large‐scale adoption.

Soil and groundwater from an aqueous film-forming foam (AFFF)-impacted site were sampled at high resolution (n = 105 for soil, n = 58 for groundwater) and analyzed for an extensive list of anionic, zwitterionic, and cationic poly- and perfluoroalkyl substances (PFASs). Spatial trends for perfluoroalkyl acids and many precursors enabled a better understanding of PFAS composition, transport, and transformation. All PFASs without analytical standards were semi-quantified. Summed PFAS and individual PFAS concentrations were often higher at depth than near the surface in soil and groundwater. Zwitterionic and cationic compounds composed a majority of the total PFAS mass (up to 97%) in firefighter training area (FTA) soil. Composition of PFAS class, chain length, and structural isomers changed with depth and distance from the FTA, suggesting in situ transformation and differential transport. The percentage of branched perfluorooctane sulfonate increased with depth, consistent with differential isomeric transport. However, linear perfluorooctanoic acid (PFOA) was enriched, suggesting fluorotelomer precursor transformation to linear PFOA. Perfluorohexane sulfonamide, a potential transformation product of sulfonamide-based PFASs, was present at high concentrations (maximum 448 ng/g in soil, 3.4 mg/L in groundwater). Precursor compounds may create long-term sources of perfluoroalkyl acids, although many pathways remain unknown; precursor analysis is critical for PFAS fate and transport understanding.

Abstract Over the past 10 years, there has been an increased recognition that matrix diffusion processes are a significant factor controlling the success of groundwater remediation. New field techniques and modeling tools have, consequently, been developed to understand how contaminants diffuse into and then out of low‐permeability (“low‐k”) zones and assess the resulting impact on groundwater quality. Matrix diffusion, in turn, is driven by one key factor: geologic heterogeneity. The importance of heterogeneity is being emphasized in the groundwater field by general rules of thumb such as “90% of the mass flux occurs in 10%‐20% of the cross‐sectional area” and conceptual models that show most of the groundwater flow occurs through the aquifer's “mobile porosity” which just a small fraction of commonly used effective porosity values (between 0.02 and 0.10 for mobile porosity vs. 0.25 for effective porosity). For this study, 141 boring logs from 43 groundwater remediation sites were evaluated to develop an empirically based estimate of the groundwater flow versus aquifer cross‐sectional area to confirm or reject the general flow versus area rules of thumb. This study indicated that at these 43 sites, an average of 30% of the cross‐sectional area carried 90% of the groundwater flow. Our flow‐only analysis does provide moderate (but not confirmatory) support for the “mobile porosity” concept with an estimated representative mobile porosity value of about 0.11 at the 43 sites.

Density-dependent flow and transport solutions for coastal saltwater intrusion investigations, analyses of fluid injection into deep brines, and studies of convective fingering and instabilities of denser fluids moving through less dense fluids typically formulate the groundwater flow equation in terms of pressure or equivalent freshwater head. A formulation of the flow equation in terms of hydraulic head is presented here as an alternative. The hydraulic-head formulation can facilitate adaptation of existing constant-density groundwater flow codes to include density-driven flow by avoiding the need to convert between freshwater head and hydraulic head within the code and by incorporating density-dependent terms as a compartmentalized "correction" to constant-density calculations already performed by the code. The hydraulic-head formulation also accommodates complexities such as unconfined groundwater flow and Newton-Raphson solution schemes more readily than the freshwater-head formulation. Simulation results are presented for four example problems solved using an implementation of the hydraulic-head formulation in MODFLOW.