Ohio Environmental Protection Agency

Wastewater treatment plants (WWTPs) house diverse populations of microbial communities that are dynamic across treatment stages. Although viruses, especially non-pathogenic ones are relatively less studied compared to their bacterial counterparts, they are equally important players in WWTP microbiomes. In this study, we sampled influent, activated sludge, and effluent stages of a WWTP in southwest Ohio to sequence their viral population using multiple displacement amplification (MDA) and metagenomic approaches. We recovered 1003 viral genomes, the majority of which were ssDNA (single-stranded DNA) viruses that formed distinct clusters representing novel species and phylogenetic groups not closely related to known human gut or terrestrial viruses. Additionally, tracking viruses across treatment stages showed several persisted across multiple treatment stages. These results suggest that further studies are needed to understand the persistence of viral populations, particularly non-pathogenic ones, across different stages of WWTPs.

Excess riverine nitrate causes downstream eutrophication, notably in the Gulf of Mexico where hypoxia is linked to nutrient-rich discharge from the Mississippi River Basin (MRB). We developed a long short-term memory (LSTM) model using high-frequency sensor data from across the conterminous US to predict daily nitrate concentrations, achieving strong temporal validation performance (median KGE = 0.60). Spatial validation-or prediction in unmonitored basins-yielded lower performance for nitrate concentration (median KGE = 0.18). Nonetheless, spatial validation was crucial in quantifying the impact of current data gaps and guiding the model's targeted application to the MRB where spatial validation performance was stronger (median KGE = 0.34). Modeling results for the MRB from 1980 to 2022 showed relatively low riverine nitrate export (19 ± 4% of surplus), indicating large-scale retention of surplus nitrate within the MRB. Interannual nitrate yields varied significantly, especially in Midwestern states like Iowa, where wet-year export fractions (42 ± 24%) far exceeded dry year export (6 ± 6%), suggesting increased hydrologic connectivity and remobilization of legacy nitrogen. Further evidence of legacy nitrate remobilization was noted in a subset of Midwestern basins where, on occasion, annual surplus export fractions exceeded 100%. Interpretable Shapley values identified key spatial drivers influencing mean nitrate concentrations-tile drainage, roadway density, wetland cover-and quantitative, non-linear thresholds in their influence, offering management targets. This study leverages machine learning and aquatic sensing to provide improved spatiotemporal predictions and insights into nitrate drivers, thresholds, and legacy impacts, offering valuable information for targeted nutrient management strategies in the MRB.

Water characteristic impacts on granular activated carbon (Filtrasorb 400) adsorption of nine per- and polyfluoroalkyl substances (PFAS) were studied. Multispecies competitive isotherms had lower effective solid phase capacities (q e ) than single species isotherms. pH 9 q e s were somewhat reduced (max 19%) compared to pH 7.7-8.1. Decreasing ionic strength (10 to 2 mM) substantially (79%-146%) increased PFAS q e s. Divalent ion (calcium and sulfate) presence without changing ionic strength increased q e s (43%-140%). Natural organic matter (NOM) presence reduced PFAS q e s with the reduction somewhat offset by calcium and sulfate presence. This reduced capacity suggested both direct competition with NOM and pore-blockage hindered PFAS adsorption. Ideal adsorbed solution theory poorly predicted the competition, likely due to nonideal behaviors of adsorbed species and GAC surface heterogeneity. Findings provide insights into the complex interactions between different water constituents and the adsorptive surface to help optimize PFAS treatment efficacy and minimize operational costs.

The Newcomb-Benford number law has found applications in the natural and social sciences for decades, with limited ecological attention. The aim of this communication is to highlight a statistical correspondence between the first significant digit frequencies of the Benford probability distribution and ecological systems in a balanced state of dynamic equilibrium. Analytical methods, including multidimensional Euclidean distance, Cohen-W effect size, Kossovsky sum of squared deviations (SSD), and Pearson residuals are presented to facilitate the identification of this canonical representation across multiple levels of ecological organization and scale. Case studies reveal novel applications of the Benford distribution for detecting impending state transitions in marginally stable systems, as well as temporal and spatial divergence of ecological information through the measurement of Kullback-Leibler relative entropy. Widespread documentation of the leading digit phenomenon is expected as ecologists revisit empirical datasets and formalize sampling protocols for its detection. The conversion of randomly collected sets of arithmetic data into logarithmic probabilities of first significant digits presents unique opportunities to advance our understanding of ecological processes related with stability, complexity, and maturity.

The International Commission on Radiological Protection (ICRP) Task Group 120 (TG120) is developing ICRP recommendations for radiological protection for a wide range of radiation accidents and malicious events, complementing those given in ICRP Publication 146 (2020) for large nuclear accidents. The scope includes accidents involving criticalities, operating faults, and fires and explosions in nuclear facilities, inadvertent damage to sealed radiation sources, as well as malicious events, such as sabotage of nuclear facilities or materials, use of radiological dispersal devices, the contamination of food and drinking water supplies, and the deployment of nuclear weapons. A template has been designed to collate relevant information on a wide range of case studies and hypothetical malicious scenarios to ensure that the recommendations developed are broadly applicable and comprehensive. For all scenarios, a graded approach to protection is being taken, accepting that specific guidance may be required for some distinctive aspects, for example, protection during times of armed conflict. This paper provides an overview of the scenarios and scope of the work of TG120, including some of the radiological and non-radiological impacts of radiation emergencies, along the response and recovery timeline.

Abstract Reducing greenhouse gas (GHG) emissions will be accompanied by air quality improvements. The potential for these ‘co-benefits’ has been demonstrated globally and in the United States, but the impact on disparities in air pollution exposure is not well understood. Here we couple a state-level energy system model with air quality modeling to project fine-scale pollution impacts of the transition to a net zero economy. We find that achieving net zero in the United States leads to substantial reductions in PM2.5 and ozone overall, but not everywhere, and that its influence on exposure disparities is complex. The two pollutants sometimes move in opposite directions, as do the effects on future disparities across socioeconomic groups. Future meteorology plays an underappreciated role; more warming can flip a reduction in an exposure disparity to an increase in some areas, even when holding emissions constant, suggesting that the level of climate action by other nations will impact air pollution exposure inequities within the United States.

When cyanobacterial phytoplankton form harmful cyanobacterial blooms (HCBs), the toxins they produce threaten freshwater ecosystems. Hydrogen peroxide is often used to control HCBs, but it is broadly toxic and dangerous to handle. Previously, we demonstrated that glucose addition to lake water could suppress the abundance of cyanobacteria. In this study, glucose was compared to hydrogen peroxide for the treatment of cyanobacterial phytoplankton communities. The six-week study was conducted in the large mesocosms facility at Grand Valley State University's Annis Water Resources Institute in Michigan. To 1000 L of Muskegon Lake water, glucose was added at either 150 mg or 30 mg glucose/L. Hydrogen peroxide was added at 3 mg/L to two 1000 L mesocosms. And two mesocosms were left untreated as controls. Triplicate 100 mL samples were collected weekly from each mesocosm, which were then filtered and frozen at -80 °C for 16S rRNA amplicon sequencing. The 16S rRNA amplicon sequencing results revealed that hydrogen peroxide treatment quickly reduced the relative abundance of the cyanobacteria compared to the control mesocosms, but the cyanobacteria population returned over the course of the 6-week study. On the other hand, both glucose concentrations caused a rapid proliferation of multiple low abundance proteobacterial and bacteroidotal taxa resulting in notable increases in taxonomic richness over the duration of the study and reducing the relative abundance of cyanobacteria. Although hydrogen peroxide quickly suppressed the cyanobacteria, the population later returned to near starting levels. The glucose suppressed the cyanobacterial phytoplankton apparently by promoting competitive heterotrophic bacteria.