Science of The Total Environment

The aquatic toxicity of tire wear particles (TWPs) depends on the leaching of various components. The leaching process is time-dependent and influenced by various environmental factors, leading to fluctuation in leachate toxicity. In this study, we quantified the temporal dynamics of leachate toxicity using the dose-response model. Meanwhile, to simulate weathering conditions, TWPs were exposed to ultraviolet (UV) irradiation and elevated temperature. The results indicated that the leachate toxicity over time fitted a biphasic pattern, with an initial increase followed by a decrease, peaking at the 11th day. The toxicity fluctuation cannot be characterized by any single component, but rather leachate should be considered as an integral whole aligning with a typical hormesis dose-response curve. High temperature of road surface increased leachate toxicity by 66%, due to elevated concentrations of 67 identified organic compounds. UV irradiation, however, mitigated this effect, acting as antagonism. These findings underline the seasonal and spatial heterogeneity in leachate toxicity. Additionally, high temperature induced the volatilization of organic compounds within TWPs, highlighting an independent exposure pathway. The methodology developed in this study will provide foundation and standard for future research on the aquatic ecotoxicity of TWPs. Environmental ImplicationThe toxicity of leachate from ubiquitous tire wear particles (TWPs) to aquatic organisms has been confirmed in field and experimental studies. However, existing researches indirectly used TWPs quantity as sole proxy for leachate toxicity, neglecting its fluctuations over leaching duration and in situ environmental factors, potentially confounding toxic effects. Herein, this study quantifies these dynamics of leachate toxicity based on measurable biological response, aiming to establish a standard scale for further quantitative assessment of TWPs ecological risk.

Greenhouse gas (GHG) emissions from reservoirs are quantitatively relevant for atmospheric climatic forcing. These emissions have large temporal variability, with daily changes accounting for a substantial part of this variability. However, most estimations for GHG fluxes are based on the upscaling of discrete measurements performed during the daytime and, in general, they do not account for nighttime emissions. Here, we explored the daily patterns of CO2, N2O, and diffusive and ebullitive CH4 fluxes in two eutrophic reservoirs with contrasted morphometries in two different years. We found a daily pattern for CO2, N2O, and diffusive CH4 fluxes with consistent higher emissions during the daytime than during the nighttime, irrespectively of reservoir morphometry. These three diffusive fluxes showed evident daily synchrony suggesting a common driver. The emissions were coupled with the daily solar cycle, wind speed, and water temperature. The daily emissions of the CO2, N2O, and CH4 were also positive and significantly related to oxygen saturation. In contrast, we did not find a consistent daily pattern for the ebullitive CH4 fluxes, although they represented a significant fraction of the total CH4 emitted in these reservoirs. Our study suggests that the daily variability in GHG emissions may be as relevant as the variability at spatial scale or inter-system variability. Therefore, daily ranges should be considered in future GHG budgets to refine temporal trends of GHG emissions from reservoirs.

Bioassays are powerful tools to comprehensively understand the effects of complex environmental mixtures on humans and other animal species. In particular, the fish embryo test (FET) with zebrafish (Danio rerio) is one of the most used bioanalytical tools to test in vivo the effect of environmental extract. However, it is well known that the preparation technique of complex environmental samples for bioanalytical testing could have huge impact on the composition of exposure solutions and hence the corresponding toxicity Considering this, it is important to develop reliable environmental sample preparation procedures to obtain accurate and reproducible results in the zebrafish embryo toxicity studies. In the present study, we aimed to investigate how different experimental set-ups using a Solid Phase Extraction (SPE) extract of a complex water sample might influence the toxicity assessment using embryos of Danio rerio. Firstly, we assess the influence of two typical carrier solvents (methanol and dimethyl sulfoxide) for dosing environmental extracts. We further investigated the effect of increasing exposure media pH. Finally, we studied the effect of the SPE blank on lethal and sublethal effects in embryos of Danio rerio. Although no significant differences were observed for different solvents, we observed an adverse effect on hatching rate when testing the blank. This indicates the potential impact of background contamination in experimental setups, highlighting the need for appropriate blank correction methods. Furthermore, the differential effects observed with different pH correction methods highlight the importance of carefully selecting the appropriate pH adjustment strategy to accurately assess toxicity levels. Overall, our study enhances the knowledge base and methodology for accurate and comprehensive ecotoxicological assessments in aquatic ecosystems, aiding in the protection and conservation of these fragile environments.

The effects of urban trees on public health should change over decades due to shifts in tree composition and abundance, environmental conditions, human demography, and disease incidence. However, there are few case studies documenting changes in the health-related ecosystem services and disservices provided by trees over time. Here we use seven tree censuses to quantify changes in the effects of city-owned trees on air pollution, allergenic pollen, hydrology, and heat due to shifts in tree abundance and environmental conditions in Ithaca, New York, a small city in the Northeastern United States. We also review how shifts in disease incidence have affected these trees health consequences. From 2005 to 2021, trees removed 20% more ozone and 268% more PM2.5; they also removed substantially more runoff and had higher cooling capacity. In contrast, the amount of certain air pollutants removed by trees dropped from 2005 to 2021 for sulfur dioxide (361 kg/yr to 8 kg/yr), carbon monoxide (65 kg/yr to 32 kg/yr), and nitrogen dioxide (380 kg/yr to 298 kg/yr) as their ambient concentrations dropped. Pollen production by street trees from 1947 to 2021 initially dropped due to Dutch elm disease but has quadrupled since the 1980s due to increases in several high-pollen producing genera. Overall, this study illustrates how the public health effects of trees vary over decades due to changes in tree composition and abundance, environmental conditions, and changes in disease incidence and human demography, emphasizing the importance of incorporating long-term perspectives into contemporary tree management decisions. Highlights[bullet] Urban trees health-related ecosystem services changed over decades in a case study [bullet]The removal of SO2, NO2, and CO by urban trees is diminishing due to cleaner air [bullet]Shifts in tree composition have had large effects on allergenic pollen production [bullet]Changes in human disease incidence over decades mediate trees health effects

This study firstly investigated the tissue-specific responses and interactive characteristics of the crop-microbe system to co-pollution with ofloxacin (OFL) and chromium (Cr) in soil. The results emphasized the hormesis effect induced by low-dose OFL (1 mg L-1) on ginger plants subjected to soil Cr stress. However, high-dose OFL (100 mg L-1) and Cr co-stressed plants exhibited reduced growth, root activity, antioxidant enzyme activities and photosynthesis-fluorescence performances, while the reactive oxygen species (ROS) reflected by O2{middle dot}- and H2O2 significantly increased up to 43.34% and 78.63%, respectively, compared to other treatments. In addition, high-throughput sequencing indicated that OFL influenced rhizosphere microbial diversity, composition, and evolution, favoring Proteobacteria proliferation under co-pollution. Meanwhile, root exudate patterns shifted, with humic-like exudates, potentially interacting with pollutants and microbes. Notably, enrichments of antibiotic resistance gene (qnrS) in edible rhizome and potential pathogenic bacteria in ginger rhizosphere were observed under OFL and Cr co-pollution, raising environmental and food chain concerns. Through structural equation modeling, we quantitatively established correlations within soil-crop-microbe factors, emphasizing their interconnected nature. Overall, this study sheds light on the complex responses of the crop-microbe system to OFL and Cr co-pollution, highlighting the importance of understanding pollutant interactions for enhancing plant resilience and mitigating environmental risks. HighlightsO_LIRevealed a hormesis from low-dose OFL on Cr-polluted ginger, enhancing resilience. C_LIO_LIRhizosphere microbial composition shift under co-pollution, favoring Proteobacteria. C_LIO_LIqnrS and potential pathogens increased under co-pollution, posing food chain risks. C_LIO_LIStructural equation modeling quantified correlations in soil- crop-microbe factors. C_LIO_LIClarified crop-microbe "One Health" interactions role under Cr & OFL co-pollution. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/561380v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@bd3d20org.highwire.dtl.DTLVardef@1f8024eorg.highwire.dtl.DTLVardef@15f6154org.highwire.dtl.DTLVardef@ef0aeb_HPS_FORMAT_FIGEXP M_FIG C_FIG

Groundwater ecosystems fulfil functions that humankind relies upon, e.g. for sustainable drinking water production. Quantification of these services is lacking so far. Thus, it is not possible to predict scenarios (e.g. future climates). Based on data from a comprehensive groundwater ecosystem study comprising four zones of varying land use and groundwater / surface water exchange, we parameterized a quantitative dynamic food web model (recharged organic carbon, microorganisms using the biodegradable fraction of this carbon, and fauna grazing on the microorganisms). With the model satisfactorily reflecting the field data, we calculated five further scenarios, three of which without fauna (mortality e.g. due to contamination, sudden peaks of temperature etc.). Two of the "fauna" and two of the "no fauna" scenarios were run with temperature elevated by 1.5{degrees}C and 3{degrees}C, respectively. The ecosystem service of carbon degradation was expressed as the difference in carbon concentration between the beginning of the simulation and the end of the simulation. In most scenarios, remaining carbon increased over time. The remaining carbon in some scenarios was up to 6.6 times as high in the "no fauna" scenarios compared to the reference case. Fauna was thus shown to fulfil a service by promoting microbial carbon degradation that may be substantial. Sustainable drinking water production is more reliable and less costly, the more active the groundwater fauna in the production area is. This model set up can serve to test other cases of varying physical and chemical variations and disturbances.

Arsenic (As) contamination of groundwater in parts of South and Southeast Asia is a public health disaster. Millions of people living in these regions could be chronically exposed to drinking water with As concentrations above the World Health Organizations provisional guideline of 10 {micro}g/L. Recent field investigations have shown that the distribution of groundwater As in many shallow aquifers in India and Bangladesh is evolving rapidly due to massive irrigation pumping. This study compares a decade-old dataset of As concentration measurements in groundwater with a dataset of recent measurements using geospatial machine learning techniques. We observed that the probability of As concentrations >10 {micro}g/L was much greater in the regions between two major rivers than in the regions close to the Ganges River on the eastern border of the study area, where As concentrations >10 {micro}g/L had been measured prior to 2005. The greater likelihood that As is present away from the river channel and is found instead in the interfluvial regions could be attributed to the transport and flushing of aquifer As due to intense groundwater pumping for agriculture. We estimated that about 2.8 million people could be chronically exposed to As concentrations >10 g/L. This high population-level exposure to elevated As concentrations could be reduced through targeted well-testing campaigns, promoting well-switching, provisions for safe water access, and developing plans for raising public awareness. Policymakers could use the ternary hazard map to target high-risk localities for priority house connections of piped water supply schemes to help reduce human suffering. Key pointsO_LIA high-resolution predictive analysis was conducted using geospatial machine learning techniques to identify human suffering. C_LIO_LIA comparison of decadal arsenic measurements and a machine learning prediction suggests a shift in hotspot location. C_LIO_LIGroundwater in a region between two major rivers was found to be unsafe for agricultural and drinking purposes. C_LI Plain language summaryWe conducted a high-resolution predictive analysis using geospatial machine learning algorithms to identify the extent and hotspot location of arsenic (As) contamination in the Murshidabad district of West Bengal, India. The predictive analysis identified an area between two adjacent major rivers in which the probability of As concentrations >10 g/L in groundwater is significantly greater than in other areas. There is a shift in As hotspot location from the regions near the river toward the regions between the two adjacent rivers, possibly due to intense groundwater pumping for agriculture. We estimated that about 1.6 million people could be at high-risk from drinking water contaminated by As concentrations >10 g/L. Policymakers could use the hazard map and the analysis of treated piped drinking water networks to provide access to targeted safe water wells for affected households.

The characterization of risk due to recreational exposure to water needs to assess the concentration of pathogens in the water and the degree of contact with those pathogens. In this study we assessed the risk associated to E. coli and cyanobacteria in a large South American Reservoir heavily used for recreation, by i) gathering field environmental data from two water agencies (six sites, summers 2011-2015), ii) generating satellite data at landscape scale (750 km2, summers 2011-2017) and running a health survey related to water exposure (summer 2017). Field data showed that cyanobacteria abundances recurrently surpassed the moderate and high-risk categories across sites and year analyzed, and a significant positive link between cyanobacteria abundance and microcystin concentration. Nevertheless, microcystin concentrations were in 90% of cases mostly within the low to moderate risk categories. Mean E. coli concentrations during 2011-2015 were within the high-risk category in 30% of the sites, but in 2017, sites identified as low risk had high-risk. The latter underscores the high risk posed by E. coli in the reservoir. Cyanobacteria (cell abundance and microcystin) and coliform bacteria abundances were unrelated, suggesting different responses to environmental or anthropogenic triggers. Satellite data evidenced that the highest risk related to cyanobacteria abundance occurred in the dendritic areas of the Argentinean side of the reservoir, areas which currently remain unmonitored by water agencies. Satellite monitoring bridged the limited spatial and temporal coverage of field samplings for cyanobacteria abundance (yet not for toxicity nor E. coli abundances) and rendered a risk map at landscape scale, which can be used by water agencies to effectively monitor and manage cyanobacteria blooms, and to-coupled with exposure variables-assess health risks related to cyanobacteria. The health survey identified few numbers of suspected patients with symptoms and who bathed in the Salto Grande reservoir. At the time of exposure, sites in the environment evidenced high bacteria concentration (mostly E. coli and to a lesser extent cyanobacteria) denoting situations where aspects of the biophysical environment affect human health. More studies and integration among environmental and health disciplines are needed to assess the impacts of these water born bacteria in human health. Finally, we further assessed how well cyanobacteria quantitative proxies monitored in the field explained the outcome of a qualitative risk communication system-the cyano-traffic-light-which is ongoing since 2011. We obtained a significant predictive model only for cyanobacteria abundance, yet with low predictive value. This probably occurred because the variables used to build each cyano-traffic-light category (cyanobacteria abundance, toxicity and chlorophyll-a, scums) were monitored with different frequencies, and because at least two of these variables needed to surpass the threshold of each category to be allocated into a risk category. Based upon our results we propose several modifications to the current cyano-traffic-light, that believe would better reflect what happens in the field and protect human health: i) include E. coli concentration and satellite estimated cyanobacteria abundance (mostly in areas not covered by field monitoring), ii) relax the thresholds for cyanobacteria abundance and toxicity, and iv) base each risk category upon the surpassing of one of either E. coli, cyanobacteria abundance, microcystin.

Microplastics (MPs) are pervasive pollutants that may threaten aquatic organisms, especially during early life stages. This study investigated effects of MPs on the hatching rate of Japanese flounder eggs. Fertilized eggs were exposed to polystyrene (PS) microbeads (primary microplastics) (3 and 10 {micro}m, at 20 and 200 particles/ml), and secondary MPs derived from coastal debris (rope, plastic bottles, fish net, string, and rubber pads) collected in Nagasaki, Japan. Hatching rates of flounder eggs were unaffected by either primary or secondary microplastics, suggesting limited impact of microplastics on this brief developmental stage.

The contamination of non-target organisms and ecosystems by pesticides can adversely affect biodiversity and key ecosystem services such as pollination or natural pest control. In this study, we used honey bee colonies as sentinels of environmental contamination in four distinct habitats--urban, suburban, forest, and vineyard--and collected bees every three weeks from May to November. Pesticide residues were extracted using an adapted QuEChERS method and analyzed by LC-MS/MS, while inorganic elements were measured by ICP-MS and ICP-AES. Our results show that land-use and seasonal changes shape contaminant patterns in bees. Vineyards left the strongest chemical footprint on bees, as indicated by the wide diversity of contaminants detected in this environment. This reflects multiple exposure to both current and historical pesticide inputs--such as copper--which can accumulate over time to potentially harmful levels. Pollinators like honey bees provide effective indicators of environmental risk, as their health and contaminant loads can reveal broader ecological impacts. Overall, environmental exposure and local contaminant inputs determine the pollutant burdens in pollinators, which may affect honey bee health and the ecosystem services they provide.

The Rio Doce estuary was critically impacted in 2015 by the worlds largest mining tailing spill, with still unclear long-term effects. Here we present a long-term (2015 to 2020) assessment of estuarine benthic assemblages, where Annelida and Mollusca were dominant (52.6% and 26.3%, respectively). Our results demonstrated that the density and richness of benthic taxa decreased in response to an increase in potentially toxic elements concentrations, suggesting a chronic pollution effect that lasted for at least 4.2 years in the estuary. Our data demonstrated that despite the decline in sediment potentially toxic elements concentration over time, there was a continued low habitat quality for the benthic fauna characterized by a reduction of 96% on macroinvertebrate density and 48% on species richness. The long-term impacts on benthic macrofauna highlight that water quality levels can misguide impact assessment programs, and reveal that mine tailings impacts persist for many years in estuarine ecosystems.

1A series of mass mortalities (wash-ups) of marine life were documented along Englands north east coastline with peaks in September and October 2021, coincident with a programme of intensified maintenance dredging of the River Tees. Decapod crustaceans were the worst affected fauna, with brown crab (Cancer pagurus), European lobster (Homarus gammarus, L.), green shore crab (Carcinus maenas, L.) and velvet swimming crab (Necora puber, L.) populations severely affected. Moribund animals presented with twitching behaviours and paralysis. A potential release of the industrial pollutant pyridine was forwarded as one explanation; however, toxicology data for pyridine in decapods is lacking. In this study, we address this knowledge gap by executing a programme of immersion exposure experiments (pyridine at 2 - 100 mg L-1) using C. pagurus, measuring toxicity effects at the individual (survival) and cellular levels (cellular, mitochondrial, and lipid peroxidation reactive oxygen species (ROS) formation in the gills, hepatopancreas and claw muscle). Highest mortality rates were seen after 72 hours of exposure, returning an LC50 value of 2.75 mg L-1. Exposed crabs presented with patterns of convulsions, limb twitching, paralysis, and death. Crabs exposed to the lowest pyridine dose (2 mg L-1) were noticeably more docile than controls. Concentration was a significant factor influencing mitochondrial ROS formation at low concentrations, with tissue type, time, and their interaction all significant at 100 mg L-1. Computer simulations were used to model the transport of any pyridine released from the dredging work, demonstrating the potential for a pyridine plume to extend from Seaham to the north of the Tees to Whitby and Robin Hoods Bay to the south. This range corresponds well with the reported wash-ups and subsequent declines in catch rates.

The detection of diverse pathogens and chemical compounds in community wastewater facilitates the monitoring of public health trends of emerging diseases and health conditions. During the COVID-19 pandemic, detection of viral RNA in wastewater assisted in monitoring the infection rates in different geographies and this drew attention to the method of wastewater-based epidemiology (WBE). In contrast to individual clinical testing, WBE offers an affordable, population-wide overview of the infection status of a community including asymptomatic carriers and those without access to healthcare facilities. To understand the community status of the infections caused by respiratory syncytial virus, SARS-CoV-2 and influenza virus subtypes in the monsoon season in Vijayawada city in the state of Andhra Pradesh in India, we longitudinally analyzed wastewater samples once a week between July-August 2024 from 7 sewage treatment plants in the city. The data obtained from the multiplexed RT-qPCR was used to calculate the viral loads in the wastewater samples at the city level and the proportion of population shedding the virus was estimated. All three viruses RSV A+B, SARS-CoV-2 and Influenza A+B were detected in the wastewater during our sampling period. Amongst the three viruses, the city had the largest load of SARS-CoV-2 RNA in the wastewater followed by RSV A+B and Influenza A+B. The study demonstrates the potential of utilizing wastewater surveillance system coupled to multiplexed RT-PCR to understand the population level dynamics of co-existence of multiple pathogens during the monsoon season in the urban settings.

The escalating global demand for food has intensified agricultural practices, leading to substantial changes in land use. This transformation poses a threat to farmland biodiversity, compounded by the presence of pollutants from anthropogenic activities. While the impact of specific pollutants is known in controlled environments, their compounded effects under field conditions remain largely unexplored. We investigated correlations between farmland bird distribution, landscape features, land use patterns, and anthropogenic pressures, including nutrient pollution, acidifying compounds, and synthetic chemicals. Using distribution maps of the Netherlands at a 1x1 km{superscript 2} grid cell, we analyzed the association of farmland bird species richness and abundance with landscape characteristics and varying levels of exposures to unintended pollutants. We also compared species richness distribution patterns between 1998 and 2018. We found a strong negative relationship between farmland bird species richness and abundance with atmospheric deposition of inorganic nitrogen (NHx, NOy). Furthermore, mixed associations were observed between farmland birds and local toxic pressure variation in surface waters, with consistent relationships to industrial chemicals (negative) and products of combustion (positive). Lastly, change in species richness from 1998 and 2018, showed that many of the relationships observed now were already evident two decades ago, with recent declines in species richness concentrated in landscapes hosting a considerable number of species, and low nitrogen deposition grid cells. We conclude that although it is likely that there is some direct negative effects of pollutants on farmland birds, it is reasonable to also assume that the identified relationships are proxies for the overarching intensity of farming, human disturbance, and broader landscape changes. Our study highlights a) a possible role of synthetic pollutants and acidifying eutrophicating substances in farmland bird decline b) the need for well-designed field studies to complement correlative evidence from big data approaches such as ours to enhance our understanding and c) the broader implications for sustainable land management, emphasizing the importance of a holistic approach in addressing the intricate relationships between pollutants and landscape changes.

Wastewater surveillance to monitor the incidence of infections faces challenges, in terms of discrepancies with sentinel-confirmed cases. We examined whether testing rates could explain the discrepancy between SARS-CoV-2 RNA found in a City of Sapporo wastewater treatment plant and the number of infections recorded at Hokkaido University Hospital over a period of approximately four years. Then, we analyzed the association between wastewater RNA concentrations with incidences of new cases among hospital-acquired infections. Linear regression analyses were performed using wastewater RNA concentrations as the independent variable and infected cases with and without correction for the testing rate as the dependent variable. In addition, modified Poisson regression analyses were performed, with the incidence of new cases among hospital-acquired infections as the dependent variable. After the legal reclassification of COVID-19 in Japan was changed to the same category as seasonal influenza, the rate of hospital testing declined significantly, though wastewater RNA concentrations remained high. Compared to non-correction for testing rates, corrected community-acquired infection cases showed a stronger association with wastewater RNA concentrations (R2 = 0.54 and 0.75, respectively). The incidence of hospital-acquired infections was positively associated with wastewater RNA concentrations (incidence risk rate: 2.24 [95% confidence interval: 1.36-3.71]), and a log10 wastewater RNA concentration [copies/L] of 4.57 (4.10-5.03) was suggested as a 25% probability of new incidence. This study emphasized that SARS-CoV-2 wastewater surveillance is an objective and useful indicator reflecting infection incidence independent of testing rates.

Wastewater surveillance represents an alternative approach for the diagnosis and early detection of infectious agents of public health importance. This study aimed to evaluate SARS-CoV-2 and other quality markers in oxidation lagoons, estuarine areas and seawater at Guayas and Santa Elena in Ecuador. Sample collections were conducted twice at 42 coastal sites and 2 oxidation lagoons during dry and rainy seasons (2020-2021). Physico-chemical and microbiological parameters were evaluated to determine organic pollution. Quantitative reverse transcription PCR was conducted to detect SARS-CoV-2. Results showed high levels of Escherichia coli and low dissolved oxygen concentrations. SARS-CoV-2 was detected in sea-waters and estuaries with salinity levels between 34.2-36.4 PSU and 28.8 {degrees}C-31.3 {degrees}C. High amounts of fecal coliforms were detected and correlated with the SARS-CoV-2 shedding. We recommend to decentralized autonomous governments in developing countries such as Ecuador to implement corrective actions and establish medium-term mechanisms to minimize a potential contamination route. HIGHLIGHTSO_LISARS-CoV-2 RNA was detected in estuaries, bays and the wastewater treatment systems in Playas and Santa Elena. C_LIO_LIHigh levels of fecal coliforms were detected along shorelines. C_LIO_LIWater quality parameters revealed a negative impact on the beaches studied associated with human activities. C_LI

The hydrothermal compounds massively released into the sea by the geothermal power plant of Bouillante (Guadeloupe, Lesser Antilles) support the growth of sulphur-oxidising bacteria like around black smokers. Opportunistic animals of the bay were previously shown to actively seek and consume the bacterial biofilm. To investigate the role of these bacterial mats in enhancing the transfer of Hg, a highly toxic heavy metal, its concentrations were assessed in sediments, bacteria, and 6 low trophic levels animals from the Bouillante Bay and a Control Site nearby containing only natural sources of Hg. Concentrations of Hg in all samples from Bouillante were greater than those from the Control Site (2 to 627 times higher). A comparison with the Hg concentrations reported in the literature for similar samples types reveals that they are abnormally high in most Bouillante samples. Although bacterial biofilm contained high levels of Hg, the link between bacteria contribution to diet and Hg concentration was more complex than expected, which might be due to interspecific differences in Hg uptake and elimination rates. Species not consuming bacteria (i.e. filter feeders) still presented higher levels of Hg, suggesting that significant amounts of Hg are released along with discharge waters from the Bouillante geothermal plant, and are integrated through diffusion. Differences in Hg concentrations between tissues do not indicate that Hg contained in samples from animals was under the form of MeHg, lowering the biomagnification potential of Hg in the Bouillante Bay trophic food web. Overall, the Bouillante case study emphasises for the first time an important role played by sulphur bacteria mats as a vector of hydrothermal inorganic Hg, and potentially other trace metals emitted in vents area, through dietary pathways.

Antimicrobial resistance (AMR) is an ever-increasing threat to population health. Industrial, environmental and societal factors are increasingly recognized as important contributors to AMR within communities. Here, we investigated the spatial distribution of AMR genes (ARGs) across Alberta, Canada and their association with socio-economic, immigration-related, and agro-industrial characteristics using municipal wastewater-based surveillance. We analyzed monthly wastewater metagenomes collected between March 2022 and March 2023 across eleven municipalities, representing 39% of Alberta's population. Integration with census data enabled multivariate analysis, revealing that municipal resistome profiles were strongly structured along income and immigration-related population gradients. ARGs spanning 14 resistance classes exhibited distinct distributional patterns across income and immigration gradients, including contrasting associations among beta-lactam, aminoglycoside, and macrolide-lincosamide-streptogramin ARGs, consistent with heterogeneous selection pressures across sub-populations. These findings demonstrate the capacity of longitudinal wastewater surveillance to identify persistent population-level resistome patterns and highlight the importance of incorporating sociodemographic context into AMR surveillance and mitigation strategies.

In the ongoing SARS-CoV-2 pandemic, there is a need for new strategies for surveillance and identification of arising infection waves. Reported cases of new infections based on individual testing are soon deemed inaccurate due to ever changing regulations and limited testing capacity. Wastewater based epidemiology is one promising solution that can be broadly applied with low efforts in comparison to current large-scale testing of individuals. Here, we are combining local wastewater data from the city of Dresden (Germany) along with reported cases and vaccination data from a central database (Robert-Koch-Institute) with virus variant information to investigate the correlation of virus concentrations in the wastewater and reported SARS-CoV-2 cases. In particular, we compared Linear Regression and Machine Learning (ML) models, which are both revealing an existing correlation of virus particles in wastewater and reported cases. Our findings demonstrate that the different virus variants of concern (Alpha, Delta, BA.1, and BA.2) contribute differently over time and parameters vary between variants, as well. By comparing the Linear Regression and ML-based models, we observed that ML can achieve a good fit for training data, but Linear Regression is a more robust tool, especially for new virus variants. We hereby conclude that deriving the rate of new infections from local wastewater by applying Linear Regression may be a robust approximation of tracing the state of the pandemic for practitioners and policy makers alike.

This paper aims to determine whether population normalisation significantly alters the SARS-CoV-2 trends revealed by wastewater-based epidemiology, and whether it is beneficial and/or necessary to provide an understanding of prevalence from wastewater SARS-CoV-2 concentrations. It uses wastewater SARS-CoV-2 data collected from 394 sampling sites, and implements normalisation based on concentrations of a) ammoniacal nitrogen, and b) orthophosphate. Wastewater SARS-CoV-2 metrics are evaluated at a site and aggregated level against three indicators prevalence, based on positivity rates from the Office for National Statistics Coronavirus Infection Survey and test results reported by NHS Test and Trace. Normalisation is shown to have little impact on the overall trends in the wastewater SARS-CoV-2 data on average. However, significant variability between the impact of population normalisation at different sites, which is not evident from previous WBE studies focussed on a single site, is also revealed. Critically, it is demonstrated that while the impact of normalisation on SARS-CoV-2 trends is small on average, it is not reasonable to conclude that it is always insignificant. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and indicators of prevalence; however, confidence in the improvement is low. Lastly, it is noted that most data were collected during periods of national lockdown and/or local restrictions, and thus the impacts and benefits of population normalisation are expected to be higher when normal travel habits resume.