Linking fecal bacteria in rivers to landscape, geochemical, and hydrologic factors and sources at the basin scale

A multi-tiered approach to assess fecal pollution in an urban watershed: Bacterial and viral indicators and sediment microbial communities

Development of effective pollution mitigation strategies require an understanding of the pollution sources and factors influencing fecal pollution loading. Fecal contamination of Turkey Creek in Gulfport, Mississippi, one of the nation's most endangered creeks, was studied through a multi-tiered approach. Over a period of approximately two years, four stations across the watershed were analyzed for nutrients, enumeration of E. coli, male-specific coliphages and bioinformatic analysis of sediment microbial communities. The results demonstrated that two stations, one adjacent to a lift station and one just upstream from the wastewater-treatment plant, were the most impacted. The station adjacent to land containing a few livestock was the least impaired. While genotyping of male-specific coliphage viruses generally revealed a mixed viral signature (human and other animals), fecal contamination at the station near the wastewater treatment plant exhibited predominant impact by municipal sewage. Fecal indicator loadings were positively associated with antecedent rainfall for three of four stations. No associations were noted between fecal indicator loadings and any of the nutrients. Taxonomic signatures of creek sediment were unique to each sample station, but the sediment microbial community did overlap somewhat following major rain events. No presence of Escherichia coli (E. coli) or enterococci were found in the sediment. At some of the stations it was evident that rainfall was not always the primary driver of fecal transport. Repeated monitoring and analysis of a variety of parameters presented in this study determined that point and non-point sources of fecal pollution varied spatially in association with treated and/or untreated sewage.

Quantitative fecal source characterization of urban municipal storm sewer system outfall 'wet' and 'dry' weather discharges

Urban areas are built environments containing substantial amounts of impervious surfaces (e.g., streets, sidewalks, roof tops). These areas often include elaborately engineered drainage networks designed to collect, transport, and discharge untreated stormwater into local surface waters. When left uncontrolled, these discharges may contain unsafe levels of fecal waste from sources such as sanitary sewage and wildlife even under dry weather conditions. This study evaluates paired measurements of host-associated genetic markers (log10 copies per reaction) indicative of human (HF183/BacR287 and HumM2), ruminant (Rum2Bac), canine (DG3), and avian (GFD) fecal sources, 12-hour cumulative precipitation (mm), four catchment land use metrics determined by global information system (GIS) mapping, and Escherichia coli (MPN/100 ml) from seven municipal separate storm sewer system outfall locations situated at the southern portion of the Anacostia River Watershed (District of Columbia, U.S.A.). A total of 231 discharge samples were collected twice per month (n = 24 sampling days) and after rain events (n = 9) over a 13-month period. Approximately 50 % of samples (n = 116) were impaired, exceeding the local E. coli single sample maximum of 2.613 log10 MPN/100 ml. Genetic quality controls indicated the absence of amplification inhibition in 97.8 % of samples, however 14.7 % (n = 34) samples showed bias in DNA recovery. Of eligible samples, quantifiable levels were observed for avian (84.1 %), human (57.4 % for HF183/BacR287 and 40 % for HumM2), canine (46.7 %), and ruminant (15.9 %) host-associated genetic markers. Potential links between paired measurements are explored with a recently developed Bayesian qPCR censored data analysis approach. Findings indicate that human, pet, and urban wildlife all contribute to storm outfall discharge water quality in the District of Columbia, but pollutant source contributions vary based on 'wet' and 'dry' conditions and catchment land use, demonstrating that genetic-based fecal source identification methods combined with GIS land use mapping can complement routine E. coli monitoring to improve stormwater management in urban areas.

Integrating quantitative microbiological risk assessment and disability-adjusted life years to evaluate the effects of urbanization on health risks for river recreationists

Urban rivers provide an excellent opportunity for water recreation. This study probabilistically assessed health risks associated with water recreation in urban rivers in the Bitan Scenic Area, Taiwan, by employing quantitative microbial risk assessment and disability-adjusted life years (DALYs). Moreover, the effects of urbanization on the health risks of river recreation induced by waterborne pathogenic Escherichia coli (E. coli) were investigated. First, data on river E. coli levels were collected in both the Bitan Scenic Area and the upstream river section, and model parameters were obtained through a questionnaire administered to river recreationists. Monte Carlo simulation was then employed to address parameter uncertainty. Finally, DALYs were calculated to quantify the cumulative effects in terms of potential life lost and years lived with disability. The results indicated that the 90 % confidence intervals for the disease burden (DB) were 0.2-74.1 × 10-6, 0.01-94.0 × 10-6, and 0.3-128.9 × 10-6 DALY per person per year (pppy) for canoeing, swimming, and fishing, respectively, in the Bitan Scenic Area. Furthermore, urbanization near the Bitan Scenic Area approximately doubled the DB risks to river recreationists in upstream rural areas. At the 95th percentile, the DB risks exceeded the tolerances recommended by the World Health Organization (1 × 10-6) or U.S. Environmental Protection Agency (1 × 10-4). The findings suggest that the simultaneous implementation of effluent sewer systems and best management practices can reduce health risks to river recreationists by at least half, reducing the DALY levels below 1 × 10-4 or even 1 × 10-5 pppy.

Seasonal assessment of risks to canoeists' health in a Taiwanese recreational river

Canoeing is the most favorite recreational activity in several Taiwanese rivers. However, river water frequently contains elevated levels of pathogenic Escherichia coli, which has adverse effects on human health. This study adopted a quantitative microbial risk assessment to analyze seasonal risks to canoeists' health in the Dongshan River, Taiwan. First, river E. coli concentrations were statistically analyzed to determine the seasonal distributions. The exposure duration (ED) was determined by field observations. To propagate the parametric uncertainty, Monte Carlo simulation was employed to model the probability distributions of seasonal pathogenic E. coli levels, ingestion rates, and ED for athletes. Finally, the beta-Poisson dose-response model was implemented to determine seasonal health risks for canoeists. The study results indicated that the health risks in infection probability ranged from 0.5 × 10-3 to 8.8 × 10-3 illnesses/person/day for tourists and 1.2 × 10-3 to 7.7 × 10-3 illnesses/person/day for athletes. The health risks in the Lizejian Bridge area for tourists exceeded an acceptable level suggested by the U.S. Environmental Protection Agency, 8 × 10-3 illnesses/person/day, in spring for an ED of 2 h/day, and the health risks for tourists and athletes approached this level in spring and winter for an ED exceeding or equaling 1.5 h/day. According to sensitivity analysis, the geometric standard deviation of river E. coli levels was the most sensitive parameter affecting seasonal risks to canoeists' health. To protect canoeists' health, effluent sewer systems, best management practices, and total maximum daily loads should be promptly implemented in this watershed.

The use of sterol profiles, supported with other faecal source tracking methods, to apportion septic tanks contamination in rural catchments

Identifying the origin of faecal pollution in water is needed for effective water management decisions to protect both human health and aquatic ecosystems. Traditionally used indicators of faecal contamination, such as E. coli, only indicate pollution from warm-blooded animals and not the specific source of contamination; hence, more source specific tracers are required. The study has focussed on separating the two main sources of contaminants within rural catchments in Ireland, agriculture and on-site wastewater treatment systems (predominantly septic tanks). While human-specific effluent tracers may assist in identifying potential pathways from individual septic tanks to surface waters, it is difficult to quantify the cumulative impact of such systems at a catchment scale. This study has investigated faecal sterols as a method to quantify such an impact on four small catchments in areas of low subsoil permeability with high densities of septic tanks. The results demonstrate the usefulness of faecal sterols which provide a quantitative evaluation of the respective impact between agricultural pasture inputs and on-site effluent showing differences between the four catchments. The study also highlights the need to derive more specific local reference sterol profile databases for specific countries or regions, using local source material of animal faeces and effluent. Two intensive sampling campaigns on the four catchments then used faecal sterols in parallel to fluorescent whitening compounds (FWCs), caffeine, artificial sweeteners and selected pharmaceuticals to gain further insights and confirmation about contamination hotspots as well as providing comparison between the different parameters. The combination of sterols, FWCs, caffeine, acesulfame and cyclamate has proven suitable to provide an estimate of the extent of human contamination in these rural catchments and has yielded additional information about potential pollution pathways and proximity of contamination. Overall, this methodology can help to facilitate a targeted and effective water management in such catchments.

Investigating the Relationship between Surface Water Pollution and Onsite Wastewater Treatment Systems

Onsite wastewater treatment systems (OWTSs) are important nonpoint sources (NPSs) of pollution to consider in watershed management. However, limited OWTS data availability makes it challenging to account for them as an NPS of water pollution. In this study, we succeeded in obtaining OWTS permits and integrated them with environmental data to model the pollution potential from OWTSs at the watershed scale using GIS-based multicriteria decision analysis. Then, in situ water quality parameters─Escherichia coli (E. coli), total nitrogen, total phosphorus, temperature, and pH─were measured along the main tributary at base-flow conditions. Three general linear models were developed to relate E. coli to water quality parameters and OWTS pollution indicators. It was found that the model with the OWTS pollution potential had the lowest corrected Akaike information criterion (AICc) value (35.01) compared to the models that included classified OWTS pollution potential input criteria (AICc = 36.76) and land cover (AICc = 36.74). These results demonstrate that OWTSs are a significant contributor to surface water pollution, and future efforts should be made to improve access to OWTS data (i.e., location and age) to account for these systems as an NPS of water pollution.

Using watershed characteristics to enhance fecal source identification

Fecal pollution is one of the most prevalent forms of pollution affecting waterbodies worldwide, threatening public health and negatively impacting aquatic environments. Microbial source tracking (MST) applies polymerase chain reaction (PCR) technology to help identify the source of fecal pollution. In this study, we combine spatial data for two watersheds with general and host-associated MST markers to target human (HF183/BacR287), bovine (CowM2), and general ruminant (Rum2Bac) sources. Concentrations of MST markers in samples were determined with droplet digital PCR (ddPCR). The three MST markers were detected at all sites (n = 25), but bovine and general ruminant markers were significantly associated with watershed characteristics. MST results, combined with watershed characteristics, suggest that streams draining areas with low-infiltration soil groups and high agricultural land use are at an increased risk for fecal contamination. Microbial source tracking has been applied in numerous studies to aid in identifying the sources of fecal contamination, but these studies usually lack information on the involvement of watershed characteristics. Our study combined watershed characteristics with MST results to provide more comprehensive insight into the factors that influence fecal contamination in order to implement the most effective best management practices.

Land use as a critical determinant of faecal and antimicrobial resistance gene pollution in riverine systems

The WHO recognises antimicrobial resistance (AMR) as a global health threat. The environment can act as a reservoir, facilitating the exchange and the physical movement of resistance. Aquatic environments are at particular risk of pollution, with large rivers subject to pollution from nearby human, industrial or agricultural activities. The land uses associated with these activities can influence the type of pollution. One type of pollution and a likely contributor to AMR pollution that lowers water quality is faecal pollution. Both pose an acute health risk and could have implications for resistance circulating in communities. The effects of land use are typically studied using physiochemical parameters or in isolation of one another. However, this study aimed to investigate the impact of different land uses on riverine systems. We explored whether differences in sources of faecal contamination are reflected in AMR gene concentrations across agricultural and urban areas. Water quality from three rivers impacted by different land uses was assessed over one year by quantifying faecal indicator bacteria (FIB), microbial source tracking markers (MST) and AMR genes. In addition, a multiparametric analysis of AMR gene pollution was carried out to understand whether agricultural and urban areas are similarly impacted. Faecal indicators varied greatly, with the highest levels of FIB and the human MST marker observed in urban regions. In addition, these faecal markers correlated with AMR genes. Similarly, significant correlations between the ruminant MST marker and AMR gene levels in agriculture areas were observed. Overall, applying multiparametric analyses to include AMR gene levels, separation and clustering of sites were seen based on land use characterisation. This study suggests that differences in prescription of antimicrobials used in animal and human healthcare may influence environmental resistomes across agricultural and urban areas. In addition, public health risks due to exposure to faecal contamination and AMR genes are highlighted.

Chemical and biological tracers to identify source and transport pathways of septic system contamination to streams in areas with low permeability soils

Septic systems are widely used in rural areas that lack centralized sewage treatment systems. Incomplete removal of domestic wastewater contaminants in septic systems can lead to leaching of nutrients (P and N), bacteria/viruses, and trace contaminants to surrounding groundwater and surface water. This study focuses on delineating the fate of wastewater contaminants in localities where septic systems are installed in moderate to fine-grained overburden materials to assess potential impacts on groundwater and surface water quality in these settings. Nutrients and a suite of anthropogenic tracers, including host-specific fecal indicator bacteria (bovine- and human-specific Bacteroides), pharmaceutical compounds (caffeine, carbamazepine, gemfibrozil, ibuprofen, naproxen, and sulfamethoxazole), and an artificial sweetener (acesulfame-K), were selected to evaluate differences in transport properties. Surface water samples (n = 103) were collected from streams upstream (US) and downstream (DS) of three rural hamlets up to two times monthly over one year. Results indicate the presence of wastewater indicators in the streams, with DS locations showing significantly elevated concentrations of both chemical and biological anthropogenic tracers. Human-specific Bacteroides, caffeine, and acesulfame-K were consistently observed at elevated concentrations at all DS sites. Nutrients exhibited varied concentrations between US and DS locations at three study sites. The occurrence of human-specific Bacteroides in the surface water samples suggests the presence of preferential flow pathways within the silt/clay overburden. These results demonstrate the advantages of using a combined tracer approach, involving a conservative tracer such as acesulfame-K coupled with the human-specific biological indicator Bacteroides (BacHum), to understand not only impacting sources but also potential transport pathways of septic system contamination to nearby streams. Septic systems may be an underappreciated contaminant source in rural hamlets located in fine-grained overburden materials; although, a distinction of specific nutrient sources (septic systems vs. agriculture) remains challenging.

Linking downstream river water quality to urbanization signatures in subtropical climate

Urbanization has several hydro-ecological effects on receiving waters. Hence, understanding how urbanization influences river water quality is essential for proper river management. However, an inappropriate approach that correlates urbanization signatures with water quality may result in spurious correlations. This study aimed to investigate the relationship of urbanization signatures with two key pollutants of stream flows: nutrients and pathogens. In contrast to the commonly used approaches that are based on economic or demographic metrics, our approach represents urbanization signatures using related anthropogenic activities and evaluates the effect of such activities on water quality parameters. The approach was also applied to evaluate the impacts of urbanization on nutrient and pathogen trends in the river waters of Hong Kong. The data were collected for the period of 1986-2020 from the Environmental Protection Department and monthly measurements were performed. Total nitrogen (TN), total phosphorus (TP), Escherichia. coli (E. coli), and fecal coliforms (FC) showed consistently decreasing trends. However, the long-term seasonality of nutrients differed from that of pathogens. TP and TN exhibited homogenous seasonality with an approximately sinusoidal relationship from January to December, whereas the seasonality of pathogens was more complex and not dependent on river flow dilution effects. Additionally, urbanization impacts on station nutrients and pathogen characteristics were found to be unevenly distributed; under high water temperatures, nutrient concentrations were found to be decreased because of the rainfall dilution effect on river flows. Both urban point and diffuse sources of pollution significantly contributed to nutrient pollution in rivers. Furthermore, the concentrations of FC were not highly influenced by suspended solids, and dissolved oxygen was negatively correlated with all pathogens. Furthermore, the river flow rate was found to improve the water quality in terms of both nutrients and pathogens; urban point source pollution and river temperature alteration were shown to mainly contribute to seasonal variations in both nutrients and pathogens.

Antimicrobial Resistance Linked to Septic System Contamination in the Indiana Lake Michigan Watershed

Extended-spectrum β-lactamases confer resistance to a variety of β-lactam antimicrobials, and the genes for these enzymes are often found on plasmids that include additional antimicrobial resistance genes (ARG). We surveyed aquatic environments in the Indiana Lake Michigan watershed in proximity to areas with high densities of residential septic systems to determine if human fecal contamination from septic effluent correlated with the presence of antimicrobial resistance genes and phenotypically resistant bacteria. Of the 269 E. coli isolated from environmental samples and one septic source, 97 isolates were resistant to cefotaxime, a third-generation cephalosporin. A subset of those isolates showed phenotypic resistance to other β-lactams, fluoroquinolones, sulfonamides, and tetracyclines. Quantitative PCR was used to quantify human-associated Bacteroides dorei gene copies (Human Bacteroides) from water samples and to identify the presence of ARG harbored on plasmids from E. coli isolates or in environmental DNA. We found a strong correlation between the presence of ARG and human fecal concentrations, which supports our hypothesis that septic effluent is a source of ARG and resistant organisms. The observed plasmid-based resistance adds an additional level of risk, as human-associated bacteria from septic systems may expand the environmental resistome by acting as a reservoir of transmissible resistance genes.

Application of magnetic carbon nanocomposite from agro-waste for the removal of pollutants from water and wastewater

Water pollution has significant impact on water usage, and various contaminants, such as organic and inorganic compounds, heavy metals, dyes, pharmaceuticals compounds, pathogens and radioactive compounds, are implicated. The quest for globalisation, structural developments and other related anthropogenic activities promote the release of contaminants that induce water pollution. Hence, treatment and remediation options that can remove pollutants from watercourses and wastewater have been developed. Applied nanotechnology using carbon nanocomposites has recently drawn attention because it has the advantages of low preparation cost, high surface area, pore volume and environmental stability. Magnetic carbon nanocomposites usually exhibit excellent performance in adsorbing contaminants from aqueous solutions, and thus expanding the use of nanotechnology in water treatment is of great importance. Therefore, this review explores the geographical outlook of water pollution, sources of water pollution and types of contaminants found in water and discusses the use of carbon nanocomposites as an emerging sustainable technology for water pollutant removal. The various properties of carbon-based composites influence the extent of pollutant adsorption during water treatment processes. Most carbon-based nanocomposites are generated from biomass produced by agro-waste materials. Magnetic activated carbon nanocomposites produced from walnut shells and rice husk waste can remove 78% of Cd(II) from contaminated aqueous systems. Magnetic nanocomposites from peanut shell, tea waste, curcumin nanoparticles, sunflower head waste, rice husk, hydrophyte biomass, palm waste and sugarcane bagasse facilitate hydrothermal carbonisation, chemical precipitation, co-precipitation, chemical activation, calcination and fast pyrolysis. These nanocomposites have benefitted wastewater treatment by increasing efficiency in removing pharmaceutical, dye and organic contaminants, such as promazine, ciprofloxacin, amoxicillin, rhodamine 6G, methyl blue, phenol and phenanthrene. Hence, this review discusses the relatively low costs, good biocompatibility, large surface-to-volume ratio, magnetic separation capability and reusability carbon materials and highlights the advantages of using magnetic carbon nanocomposites in the removal of contaminants from water or wastewater through adsorption mechanisms.

Stream bacterial diversity peaks at intermediate freshwater salinity and varies by salt type

Anthropogenic freshwater salinization is an emerging and widespread water quality stressor that increases salt concentrations of freshwater, where specific upland land-uses produce distinct ionic profiles. In-situ studies find salinization in disturbed landscapes is correlated with declines in stream bacterial diversity, but cannot isolate the effects of salinization from multiple co-occurring stressors. By manipulating salt concentration and type in controlled microcosm studies, we identified direct and complex effects of freshwater salinization on bacterial diversity in the absence of other stressors common in field studies using chloride salts. Changes in both salt concentration and cation produced distinct bacterial communities. Bacterial richness, or the total number of amplicon sequence variants (ASVs) detected, increased at conductivities as low as 350 μS cm^-1, which is opposite the observations from field studies. Richness remained elevated at conductivities as high as 1500 μS cm^-1 in communities exposed to a mixture of Ca, Mg, and K chloride salts, but decreased in communities exposed to NaCl, revealing a classic subsidy-stress response. Exposure to different chloride salts at the same conductivity resulted in distinct bacterial community structure, further supporting that salt type modulates responses of bacterial communities to freshwater salinization. Community variability peaked at 125-350 μS cm^-1 and was more similar at lower and upper conductivities suggesting possible shifts in deterministic vs. stochastic assembly mechanisms across freshwater salinity gradients. Based on these results, we hypothesize that modest freshwater salinization (125-350 μS cm^-1) lessens hypo-osmotic stress, reducing the importance of salinity as an environmental filter at intermediate freshwater ranges but effects of higher salinities at the upper freshwater range differ based on salt type. Our results also support previous findings that ~300 μS cm^-1 is a biological effect concentration and effective salt management strategies may need to consider variable effects of different salt types associated with land-use.

Aquifer vulnerability assessment for fecal coliform bacteria using multi-threshold logistic regression

Assessing aquifer vulnerability is crucial for preventing groundwater pollution. In this study, aquifer vulnerability to fecal coliform (FC) pollution was assessed using auxiliary environmental data in the Pingtung Plain, Taiwan. Moreover, key environmental factors inducing different fecal pollution levels were determined. First, 23 explanatory variables on land uses, population density, livestock and poultry densities, sanitary condition, antecedent precipitation, groundwater quality, aquifer characteristics, and subsurface hydrology were obtained using geographic information systems in 2014. As dependent variables, groundwater FCs were also simultaneously obtained. Then, multi-threshold logistic regression (LR) was adopted to model aquifer vulnerability assessment after cross validation. The thresholds of aquifer vulnerability causing risks of incidental ingestion were analyzed by risk assessment. Risks to human health were acceptable for a low-level threshold and exceeded the acceptable level for medium- and high-level thresholds when residents incidentally ingested FC-polluted groundwater. Finally, key environmental factors inducing low, medium, and high levels of groundwater FC pollution were characterized. The key environmental factors for the LR with low- and medium-level thresholds were sand and gravel soil textures of unsaturated aquifers and antecedent 3-day cumulative precipitation, and those for the LR with high-level thresholds were chicken farming, urban land use, and ratio of tap water use. Thus, the multi-threshold LR indicated that environmental factors must be ranked for assessing aquifer vulnerability.

Septic system-groundwater-surface water couplings in waterfront communities contribute to harmful algal blooms in Southwest Florida

As human population growth has expanded in Southwest Florida, water quality has become degraded with an increased occurrence of harmful algal blooms (HABs). Red tide (Karenia brevis) originating offshore, intensifies in nearshore waters along Florida's Gulf Coast, and blue-green algae (Microcystis spp.) originating in Lake Okeechobee is discharged into the Caloosahatchee River. These HABs could be enhanced by anthropogenic nitrogen (N) and phosphorus (P) from adjacent watersheds. North Fort Myers is a heavily developed, low-lying city on the Caloosahatchee River Estuary serviced by septic systems with documented nutrient and bacterial pollution. To identify sources of pollution within North Fort Myers and determine connections with downstream HABs, this multiyear (2017-2020) study examined septic system- groundwater- surface water couplings through the analysis of water table depth, nutrients (N, P), fecal indicator bacteria (FIB), molecular markers (HF183, GFD, Gull2), chemical tracers (sucralose, pharmaceuticals, herbicides, pesticides), stable isotopes of groundwater (δ¹⁵N-NH₄, δ¹⁵N-NO₃) and particulate organic matter (POM; δ¹⁵N, δ¹³C), and POM elemental composition (C:N:P). POM samples were also collected during K. brevis and Microcystis spp. HAB events. Most (>80%) water table depth measurements were too shallow to support septic system functioning (<1.07 m). High concentrations of NH₄⁺ and NO_x, up to 1094 μM and 482 μM respectively, were found in groundwater and surface water. δ¹⁵N values of groundwater (+4.7‰) were similar to septic effluent (+4.9‰), POM (+4.7‰), and downstream HABs (+4.8 to 6.9‰), indicating a human waste N source. In surface water, FIB were elevated and HF183 was detected, while in groundwater and surface water sucralose, carbamazepine, primidone, and acetaminophen were detected. These data suggest that groundwater and surface water in North Fort Myers are coupled and contaminated by septic system effluent, which is negatively affecting water quality and contributing to the maintenance and intensification of downstream HABs.

Antifouling Property of Cu2O-Free Self-Polishing Antifouling Coatings Based on Amide Derivatives Inspired by Capsaicin

The evidence from many studies shows that antifoulants (Cu₂O) and organic antifouling agents with broad-spectrum characteristics in antifouling coatings cause varying degrees of damage to the environment. Therefore, this study prepared Cu₂O-free self-polishing antifouling coatings based on amide derivatives inspired by capsaicin (ADIC-CSAC) with green and environmentally friendly characteristics. First, the structure of ADIC and the composition of ADIC-CSAC were characterized by IR, ¹H NMR, ¹³C NMR, HRMS, and EDX. Moreover, antibacterial, anti-algal, static raft tests and changes in the mass loss, roughness, contact angle, and surface energy were used to evaluate the antifouling and self-polishing properties of ADIC-CSAC. The test results showed that ADIC and ADIC-CSAC were successfully prepared and ADIC-CSAC possessed good antifouling and self-polishing properties. ADIC-CSAC exhibited antibacterial and anti-algal rates of over 88 and 72%, respectively, and was found to have satisfactory antifouling properties over 9 months in a real marine field. Overall, the prepared ADIC-CSAC possesses good and green antifouling and self-polishing properties, which lays a foundation for research on green antifouling coatings used for environmental protection.

Environmental and anthropogenic factors associated with the likelihood of detecting Salmonella in agricultural watersheds

Surface water is one of the primary sources of irrigation water for produce production; therefore, its contamination by foodborne pathogens, such as Salmonella, may substantially impact public health. In this study, we determined the presence of Salmonella in surface water and characterized the relationship between Salmonella detection and environmental and anthropogenic factors. From April 2019 to February 2020, 120 samples from 30 sites were collected monthly in four watersheds located in two different central Chile agricultural regions (N = 1080). Water samples from rivers, canals, streams, and ponds linked to each watershed were obtained. Surface water (10 L) was filtrated in situ, and samples were analyzed for the presence of Salmonella. Salmonella was detected every month in all watersheds, with a mean detection percentage of 28% (0%-90%) across sampling sites, regardless of the season. Overall, similar detection percentages were observed for both regions: 29.1% for Metropolitan and 27.0% for Maule. Salmonella was most often detected in summer (39.8% of all summer samples tested positive) and least often in winter (14.4% of winter samples). Random forest analysis showed that season, water source, and month, followed by latitude and river, were the most influential factors associated with Salmonella detection. The influences of water pH and temperature (categorized as environmental factors) and factors associated with human activity (categorized as anthropogenic factors) registered at the sampling site were weakly or not associated with Salmonella detection. In conclusion, Salmonella was detected in surface water potentially used for irrigation, and its presence was linked to season and water source factors. Interventions are necessary to prevent contamination of produce, such as water treatment before irrigation.

Connecting microbial, nutrient, physiochemical, and land use variables for the evaluation of water quality within mixed use watersheds

As non-point sources of pollution begin to overtake point sources in watersheds, source identification and complicating variables such as rainfall are growing in importance. Microbial source tracking (MST) allows for identification of fecal contamination sources in watersheds; when combined with data on land use and co-occuring variables (e.g., nutrients, sediment runoff) MST can provide a basis for understanding how to effectively remediate water quality. To determine spatial and temporal trends in microbial contamination and correlations between MST and nutrients, water samples (n = 136) were collected between April 2017 and May of 2018 during eight sampling events from 17 sites in 5 mixed-use watersheds. These samples were analyzed for three MST markers (human - B. theta; bovine - CowM2; porcine - Pig2Bac) along with E. coli, nutrients (nitrogen and phosphorus species), and physiochemical paramaters. These water quality variables were then paired with data on land use, streamflow, precipitation and management practices (e.g., tile drainage, septic tank density, tillage practices) to determine if any significant relationships existed between the observed microbial contamination and these variables. The porcine marker was the only marker that was highly correlated (p value <0.05) with nitrogen and phosphorus species in multiple clustering schemes. Significant relationships were also identified between MST markers and variables that demonstrated temporal trends driven by precipitation and spatial trends driven by septic tanks and management practices (tillage and drainage) when spatial clustering was employed.

Humans and Hoofed Livestock Are the Main Sources of Fecal Contamination of Rivers Used for Crop Irrigation: A Microbial Source Tracking Approach

Freshwater bodies receive waste, feces, and fecal microorganisms from agricultural, urban, and natural activities. In this study, the probable sources of fecal contamination were determined. Also, antibiotic resistant bacteria (ARB) were detected in the two main rivers of central Chile. Surface water samples were collected from 12 sampling sites in the Maipo (n = 8) and Maule Rivers (n = 4) every 3 months, from August 2017 until April 2019. To determine the fecal contamination level, fecal coliforms were quantified using the most probable number (MPN) method and the source of fecal contamination was determined by Microbial Source Tracking (MST) using the Cryptosporidium and Giardia genotyping method. Separately, to determine if antimicrobial resistance bacteria (AMB) were present in the rivers, Escherichia coli and environmental bacteria were isolated, and the antibiotic susceptibility profile was determined. Fecal coliform levels in the Maule and Maipo Rivers ranged between 1 and 130 MPN/100-ml, and 2 and 30,000 MPN/100-ml, respectively. Based on the MST results using Cryptosporidium and Giardia host-specific species, human, cattle, birds, and/or dogs hosts were the probable sources of fecal contamination in both rivers, with human and cattle host-specific species being more frequently detected. Conditional tree analysis indicated that coliform levels were significantly associated with the river system (Maipo versus Maule), land use, and season. Fecal coliform levels were significantly (p < 0.006) higher at urban and agricultural sites than at sites immediately downstream of treatment centers, livestock areas, or natural areas. Three out of eight (37.5%) E. coli isolates presented a multidrug-resistance (MDR) phenotype. Similarly, 6.6% (117/1768) and 5.1% (44/863) of environmental isolates, in Maipo and Maule River showed and MDR phenotype. Efforts to reduce fecal discharge into these rivers should thus focus on agriculture and urban land uses as these areas were contributing the most and more frequently to fecal contamination into the rivers, while human and cattle fecal discharges were identified as the most likely source of this fecal contamination by the MST approach. This information can be used to design better mitigation strategies, thereby reducing the burden of waterborne diseases and AMR in Central Chile.

Review of Antimicrobial Resistance in Wastewater in Japan: Current Challenges and Future Perspectives

Antimicrobial resistance (AMR) circulates through humans, animals, and the environments, requiring a One Health approach. Recently, urban sewage has increasingly been suggested as a hotspot for AMR even in high-income countries (HICs), where the water sanitation and hygiene infrastructure are well-developed. To understand the current status of AMR in wastewater in a HIC, we reviewed the epidemiological studies on AMR in the sewage environment in Japan from the published literature. Our review showed that a wide variety of clinically important antibiotic-resistant bacteria (ARB), antibiotic resistance genes (ARGs), and antimicrobial residues are present in human wastewater in Japan. Their concentrations are lower than in low- and middle-income countries (LMICs) and are further reduced by sewage treatment plants (STPs) before discharge. Nevertheless, the remaining ARB and ARGs could be an important source of AMR contamination in river water. Furthermore, hospital effluence may be an important reservoir of clinically important ARB. The high concentration of antimicrobial agents commonly prescribed in Japan may contribute to the selection and dissemination of AMR within wastewater. Our review shows the importance of both monitoring for AMR and antimicrobials in human wastewater and efforts to reduce their contamination load in wastewater.

Detangling Seasonal Relationships of Fecal Contamination Sources and Correlates with Indicators in Michigan Watersheds

Despite the widely acknowledged public health impacts of surface water fecal contamination, there is limited understanding of seasonal effects on (i) fate and transport processes and (ii) the mechanisms by which they contribute to water quality impairment. Quantifying relationships between land use, chemical parameters, and fecal bacterial concentrations in watersheds can help guide the monitoring and control of microbial water quality and explain seasonal differences. The goals of this study were to (i) identify seasonal differences in Escherichia coli and Bacteroides thetaiotaomicron concentrations, (ii) evaluate environmental drivers influencing microbial contamination during baseflow, snowmelt, and summer rain seasons, and (iii) relate seasonal changes in B. thetaiotaomicron to anticipated gastrointestinal infection risks. Water chemistry data collected during three hydroclimatic seasons from 64 Michigan watersheds were analyzed using seasonal linear regression models with candidate variables including crop and land use proportions, prior precipitation, chemical parameters, and variables related to both wastewater treatment and septic usage. Adaptive least absolute shrinkage and selection operator (LASSO) linear regression with bootstrapping was used to select explanatory variables and estimate coefficients. Regardless of season, wastewater treatment plant and septic system usage were consistently selected in all primary models for B. thetaiotaomicron and E. coli. Chemistry and precipitation-related variable selection depended upon season and organism. These results suggest a link between human pollution (e.g., septic systems) and microbial water quality that is dependent on flow regime.

IMPORTANCE In this study, a data set of 64 Michigan watersheds was utilized to gain insights into fecal contamination sources, drivers, and chemical correlates across seasons for general E. coli and human-specific fecal indicators. Results reaffirmed a link between human-specific sources (e.g., septic systems) and microbial water quality. While the importance of human sources of fecal contamination and fate and transport variables (e.g., precipitation) remain important across seasons, this study provides evidence that fate and transport mechanisms vary with seasonal hydrologic condition and microorganism source. This study contributes to a body of research that informs prioritization of fecal contamination source control and surveillance strategy development to reduce the public health burden of surface water fecal contamination.

Characterizing Differences in Sources of and Contributions to Fecal Contamination of Sediment and Surface Water with the Microbial FIT Framework

Surface water monitoring and microbial source tracking (MST) are used to identify host sources of fecal pollution and protect public health. However, knowledge of the locations of spatial sources and their relative impacts on the environment is needed to effectively mitigate health risks. Additionally, sediment samples may offer time-integrated information compared to transient surface water. Thus, we implemented the newly developed microbial find, inform, and test framework to identify spatial sources and their impacts on human (HuBac) and bovine (BoBac) MST markers, quantified from both riverbed sediment and surface water in a bovine-dense region. Dairy feeding operations and low-intensity developed land-cover were associated with 99% (p-value < 0.05) and 108% (p-value < 0.05) increases, respectively, in the relative abundance of BoBac in sediment, and with 79% (p-value < 0.05) and 39% increases in surface water. Septic systems were associated with a 48% increase in the relative abundance of HuBac in sediment and a 56% increase in surface water. Stronger source signals were observed for sediment responses compared to water. By defining source locations, predicting river impacts, and estimating source influence ranges in a Great Lakes region, this work informs pollution mitigation strategies of local and global significance.

Septic systems drive nutrient enrichment of groundwaters and eutrophication in the urbanized Indian River Lagoon, Florida

Effluent from septic systems can pollute groundwater and surface waters in coastal watersheds. These effects are unknown for the highly urbanized central Indian River Lagoon (CIRL), Florida, where septic systems represent > 50% of wastewater disposal. To better understand these impacts, water quality was assessed along both canals and a tributary that drain into the CIRL. Dissolved nutrient concentrations were higher near septic systems than in natural areas. δ¹⁵N values of groundwater (+7.2‰), surface water (+5.5‰), and macrophytes (+9.7‰) were within the range for wastewater (>+3‰), as were surface water concentrations of the artificial sweetener sucralose (100 to 1700 ng/L) and fecal indicator bacteria density. These results indicate that septic systems are promoting eutrophication in the CIRL by contributing nutrient pollution to surface water via groundwater. This study demonstrates the need to reduce reliance on septic systems in urbanized coastal communities to improve water quality and subsequently mitigate harmful algal blooms.

Integrative Survey of 68 Non-overlapping Upstate New York Watersheds Reveals Stream Features Associated With Aquatic Fecal Contamination

Aquatic fecal contamination poses human health risks by introducing pathogens in water that may be used for recreation, consumption, or agriculture. Identifying fecal contaminant sources, as well as the factors that affect their transport, storage, and decay, is essential for protecting human health. However, identifying these factors is often difficult when using fecal indicator bacteria (FIB) because FIB levels in surface water are often the product of multiple contaminant sources. In contrast, microbial source-tracking (MST) techniques allow not only the identification of predominant contaminant sources but also the quantification of factors affecting the transport, storage, and decay of fecal contaminants from specific hosts. We visited 68 streams in the Finger Lakes region of Upstate New York, United States, between April and October 2018 and collected water quality data (i.e., Escherichia coli, MST markers, and physical–chemical parameters) and weather and land-use data, as well as data on other stream features (e.g., stream bed composition), to identify factors that were associated with fecal contamination at a regional scale. We then applied both generalized linear mixed models and conditional inference trees to identify factors and combinations of factors that were significantly associated with human and ruminant fecal contamination. We found that human contaminants were more likely to be identified when the developed area within the 60 m stream buffer exceeded 3.4%, the total developed area in the watershed exceeded 41%, or if stormwater outfalls were present immediately upstream of the sampling site. When these features were not present, human MST markers were more likely to be found when rainfall during the preceding day exceeded 1.5 cm. The presence of upstream campgrounds was also significantly associated with human MST marker detection. In addition to rainfall and water quality parameters associated with rainfall (e.g., turbidity), the minimum distance to upstream cattle operations, the proportion of the 60 m buffer used for cropland, and the presence of submerged aquatic vegetation at the sampling site were all associated based on univariable regression with elevated levels of ruminant markers. The identification of specific features associated with host-specific fecal contaminants may support the development of broader recommendations or policies aimed at reducing levels of aquatic fecal contamination.

A Combined Digital PCR and Next Generation DNA-Sequencing Based Approach for Tracking Nearshore Pollutant Dynamics Along the Southwest United States/Mexico Border

Ocean currents, multiple fecal bacteria input sources, and jurisdictional boundaries can complicate pollution source tracking and associated mitigation and management efforts within the nearshore coastal environment. In this study, multiple microbial source tracking tools were employed to characterize the impact and reach of an ocean wastewater treatment facility discharge in Mexico northward along the coast and across the Southwest United States- Mexico Border. Water samples were evaluated for fecal indicator bacteria (FIB), Enterococcus by culture-based methods, and human-associated genetic marker (HF183) and Enterococcus by droplet digital polymerase chain reaction (ddPCR). In addition, 16S rRNA gene sequence analysis was performed and the SourceTracker algorithm was used to characterize the bacterial community of the wastewater treatment plume and its contribution to beach waters. Sampling dates were chosen based on ocean conditions associated with northern currents. Evidence of a gradient in human fecal pollution that extended north from the wastewater discharge across the United States/Mexico border from the point source was observed using human-associated genetic markers and microbial community analysis. The spatial extent of fecal contamination observed was largely dependent on swell and ocean conditions. These findings demonstrate the utility of a combination of molecular tools for understanding and tracking specific pollutant sources in dynamic coastal water environments.

Microbial faecal pollution of river water in a watershed of tropical Ethiopian highlands is driven by diffuse pollution sources

Tropical communities in the developing world depend heavily on riverine systems for their socioeconomic development. However, these resources are poorly protected from diffuse pollution, and there is a lack of quantitative information regarding the microbial pollution characteristics of riverine water, despite frequently reported gastrointestinal diseases. The aim of our study was to apply faecal taxation (i.e., faecal pellet counting in representative test areas to estimate the potential availability of diffuse pollution sources) in combination with a detailed microbiological faecal pollution analysis in a riverine environment to elucidate the importance of diffuse pollution. To realize this approach, ambient faecal pellets, a multiparametric data set for standard faecal indicator bacteria (SFIB), including Escherichia coli, Clostridium perfringens spores and enterococci from catchment soil and river water, and a number of riverine water physicochemical variables were analysed during a one-year cycle. We demonstrated that the abundance of ambient faecal pellets, which were consistently counted at reference sites in the catchment, was associated with faecal pollution in the river water. Water SFIB, dissolved oxygen, nutrients, conductivity and total suspended solids were strongly linked with the abundance of ambient faecal pellets in the river catchment, as demonstrated by principal component analysis (PCA). Elevated concentrations of SFIB in the riverine water in the absence of rainfall also suggested the direct input of faecal bacteria into the riverine water by livestock (e.g., during watering) and humans (e.g., during bathing). Statistical analyses further revealed that the microbiological water quality of the investigated riverine water was not influenced by SFIB potentially occurring in the soil. This study demonstrates the importance of diffuse faecal pollution sources as major drivers of the microbiological quality of riverine water in the Ethiopian highlands. In addition, the new successfully applied integrated approach could be very useful for developing predictive models, which would aid in forecasting riverine microbiological quality in tropical developing countries.

Evaluating the impact of hydrometeorological conditions on E. coli concentration in farmed mussels and clams: experience in Central Italy

Highly populated coastal environments receive large quantities of treated and untreated wastewater from human and industrial sources. Bivalve molluscs accumulate and retain contaminants, and their analysis provides evidence of past contamination. Rivers and precipitation are major routes of bacteriological pollution from surface or sub-surface runoff flowing into coastal areas. However, relationships between runoff, precipitation, and bacterial contamination are site-specific and dependent on the physiographical characteristics of each catchment. In this work, we evaluated the influence of precipitation and river discharge on molluscs' Escherichia coli concentrations at three sites in Central Italy, aiming at quantifying how hydrometeorological conditions affect bacteriological contamination of selected bivalve production areas. Rank-order correlation analysis indicated a stronger association between E. coli concentrations and the modelled Pescara River discharge maxima (r = 0.69) than between E. coli concentration and rainfall maxima (r = 0.35). Discharge peaks from the Pescara River caused an increase in E. coli concentration in bivalves in 87% of cases, provided that the runoff peak occurred 1-6 days prior to the sampling date. Precipitation in coastal area was linked to almost 60% of cases of E. coli high concentrations and may enhance bacterial transportation offshore, when associated with a larger-scale weather system, which causes overflow occurrence.

Impact of wastewater infrastructure improvements on beach water fecal indicator bacteria levels in Monroe County, Florida

The effects of wastewater infrastructure construction on regional and local environments is unknown. This project evaluated the effects of such projects in Monroe County, Florida, an area that had undergone regional wastewater infrastructure improvements. We used fecal indicator bacteria (FIB) (fecal coliform and enterococci), as a proxy indicator of beach water quality for an 18-year period of record. At the highest level of aggregation, FIBs for all 17 beaches within the county were combined to evaluate trends on a yearly basis. At the lower level, yearly FIB trends were evaluated for each beach separately. FIB data on infrastructure project period (categorical variables: before, during, and after construction), and the influences of environmental conditions (quantitative variables of rainfall and temperature) were also evaluated. In the multiple regression models, enterococci and fecal coliform were significantly associated with rainfall (24 h, p < 0.0001) and water temperature (p < 0.0001) when only the quantitative variables were considered. When both categorical and quantitative variables were considered, project period was significant for enterococci (p < 0.0001) and fecal coliform (p < 0.0001), as was 24 h lagged rainfall. Overall, the most significant factors for both fecal coliform and enterococci were rainfall and project period. Considering all beaches, infrastructure projects seem to have the collective desired effects in the years following construction, as there were decreased FIBs measured at beach sites. Only through the aggregation of all projects and measurements at all beach sites could the decreases in FIB levels be observed. Local analysis is needed to explain anomalies from these general trends for specific beaches. This understanding of FIBs, their responses to environmental and project factors, and the need for aggregated and local site analysis can provide guidance to managers at other locations with similar issues of failing wastewater infrastructure and frequent FIB exceedances.

Freshwater salinization increases survival of Escherichia coli and risk of bacterial impairment

Elevated levels of Escherichia coli (E. coli) are responsible for more designated freshwater stream impairments than any other contaminant in the United States. E. coli are intentionally used as a sentinel of fecal contamination for freshwaters because previous research indicates that salt concentrations in brackish or marine waters reduce E. coli survival, rendering it a less effective indicator of public health risks. Given increasing evidence of freshwater salinization associated with upland anthropogenic land-use, understanding the effects on fecal indicators is critical; however, changes in E. coli survival along the freshwater salinity range (≤ 1500 µS cm^-1) have not been previously examined. Through a series of controlled mesocosm experiments, we provide direct evidence that salinization causes E. coli survival rates in freshwater to increase at conductivities as low as 350 µS cm^-1 and peak at 1500 µS cm^-1, revealing a subsidy-stress response across the freshwater-marine continuum. Furthermore, specific base cations affect E. coli survival differently, with Mg²⁺ increasing E. coli survival rates relative to other chloride salts. Further investigation of the mechanisms by which freshwater salinization increases susceptibility to or exacerbates bacterial water quality impairments is recommended. Addressing salinization with nuanced approaches that consider salt sources and chemistry could assist in prioritizing and addressing bacterial water quality management.

Using multi-threshold regression techniques to assess river fecal pollution in the highly urbanized Tamsui River watershed

Rivers are an important urban water resource. This study adopted multivariate linear regression (MLR) and logistic regression (LR) with multiple thresholds to assess river fecal pollution in the Tamsui River watershed using auxiliary environmental data. First, environmental data between 2015 and 2017 on land use, antecedent precipitation, population density, sewerage infrastructure, and river water quality were obtained using geographic information systems and served as explanatory variables. River fecal coliforms (FC), the dependent variable, were also collected for the same period. Then, MLR was used to establish an overall prediction model after validation, and to determine significant factors influencing the level of river fecal pollution. Finally, after stratifying the fecal pollution as low, medium, and high levels, LR with multiple thresholds was employed to explore key factors affecting different FC pollution levels. The study results revealed that land use type and river water quality (other than FC) strongly affected river FC pollution. The discharge of household sewage and wastewater from urban areas was a major source of river FC pollution, particularly for low and medium pollution levels, while farmland land use was negatively correlated with the medium and high levels of river FC pollution in the highly urbanized watershed. Biochemical oxygen demand and suspended solids were highly correlated with medium and high pollution levels in river water.

Tracking Major Sources of Water Contamination Using Machine Learning

Current microbial source tracking techniques that rely on grab samples analyzed by individual endpoint assays are inadequate to explain microbial sources across space and time. Modeling and predicting host sources of microbial contamination could add a useful tool for watershed management. In this study, we tested and evaluated machine learning models to predict the major sources of microbial contamination in a watershed. We examined the relationship between microbial sources, land cover, weather, and hydrologic variables in a watershed in Northern California, United States. Six models, including K-nearest neighbors (KNN), Naïve Bayes, Support vector machine (SVM), simple neural network (NN), Random Forest, and XGBoost, were built to predict major microbial sources using land cover, weather and hydrologic variables. The results showed that these models successfully predicted microbial sources classified into two categories (human and non-human), with the average accuracy ranging from 69% (Naïve Bayes) to 88% (XGBoost). The area under curve (AUC) of the receiver operating characteristic (ROC) illustrated XGBoost had the best performance (average AUC = 0.88), followed by Random Forest (average AUC = 0.84), and KNN (average AUC = 0.74). The importance index obtained from Random Forest indicated that precipitation and temperature were the two most important factors to predict the dominant microbial source. These results suggest that machine learning models, particularly XGBoost, can predict the dominant sources of microbial contamination based on the relationship of microbial contaminants with daily weather and land cover, providing a powerful tool to understand microbial sources in water.

Assessing the Socio-Environmental Risk of Onsite Wastewater Treatment Systems to Inform Management Decisions

Quantifying the risk that failing onsite waste treatment systems (OWTS), such as septic systems, present to human health and the environment is a key component in natural resource management. We integrated environmental and socio-demographic data to assess the potential environmental risk and environmental justice concerns related to septic infrastructure. We used this process to develop a framework that can be applied in other jurisdictions. We found only 8% of the registered OWTS presented potential environmental risk due to the topographic, hydrologic, or edaphic characteristics of their placement. In contrast, almost 70% of the OWTS presented potential environmental risk due to their age (25 years or older). Approximately 60% of the OWTS we estimated to be at risk from age or placement were found in census blocks with more than 30% of the population living below the poverty line, had a population that was more than 50% nonwhite, or was predominantly nonwhite and impoverished. Our work suggests that jurisdictions with limited information about septic infrastructure may be able to use geospatial data that they do have to predict the parcel-level locations of OWTS. These locations can then be used to inform environmental monitoring to proactively address environmental justice concerns.

Achieving Sustainable Development Goal for Clean Water in India: Influence of Natural and Anthropogenic Factors on Groundwater Microbial Pollution

Worldwide, >2 billion people (~1/3 world population), mostly living in economically stressed areas of Africa and South Asia, still do not have access to basic sanitation, and ~1 billion still practice open defecation. Water pollution due to open defecation may primarily be linked to economy, and other factors such as social and hygiene practices, land use and hydrogeological parameters could also have sufficient influence. The present study describes the effect of human development index (HDI, 2001-2015) and economic development (NL, 1992-2013) on groundwater microbial pollution (FC, 2002-2017) across India. Economic development pattern suggested discernable inverse relationship with FC in most areas, although areas with inferior water quality, improper human practices were found to outweigh economic development. Vulnerability modelling, using these data, along with measured FC in groundwater-sourced drinking water locations (n = 235) demonstrated the heterogeneity of FC distribution potential in areas of homogenous economy, social practices, and land use. High-resolution numerical modelling of the advective transport of the hypothetical FC particles in the aquifers, suggest up to ~24 times faster movement of pollutants under irrigation-induced pumping regimes. Hence, the results of our study highlight and quantify the potential pitfalls that are possible hindrance for achieving the United Nations sustainable development goal, despite social and economic development, across the spatial scales.

The challenges of microbial source tracking at urban beaches for Quantitative Microbial Risk Assessment (QMRA)

Urban beaches are frequently impacted from multiple sources of fecal contamination. This along with high beach usage underscores the importance of appropriate management that protects swimmer health. The USEPA has enabled the use of QMRA as a tool for quantifying swimmer health risk and setting site-specific water quality objectives. This study illustrates the challenges associated with human and non-human source identification and how these challenges influence the decision of whether QMRA at typical urban beaches for water quality management is appropriate. In this study, a similar and correlated spatial relationship with elevated Enterococcus and avian-specific markers was observed, suggesting shorebirds as a primary source of FIB. However, human-associated markers were also detected frequently but at low concentrations. Ultimately, a QMRA was not conducted because pathogen loading from potential human sources could not be confidently quantified, having consequences for health risk in receiving waters where recreational contact occurs.

Identifying septic pollution exposure routes during a waterborne norovirus outbreak - A new application for human-associated microbial source tracking qPCR

In June 2017, the Pennsylvania Department of Health (PADOH) was notified of multiple norovirus outbreaks associated with 179 ill individuals who attended separate events held at an outdoor venue and campground over a month period. Epidemiologic investigations were unable to identify a single exposure route and therefore unable to determine whether there was a persistent contamination source to target for exposure mitigation. Norovirus was detected in a fresh recreational water designated swimming area and a drinking water well. A hydrogeological site evaluation suggested a nearby septic leach field as a potential contamination source via ground water infiltration. Geological characterization revealed a steep dip of the bedrock beneath the septic leach field toward the well, providing a viral transport pathway in a geologic medium not previously documented as high risk for viral ground water contamination. The human-associated microbial source tracking (MST) genetic marker, HF183, was used as a microbial tracer to demonstrate the hydrogeological connection between the malfunctioning septic system, drinking water well, and recreational water area. Based on environmental investigation findings, venue management and local public health officials implemented a series of outbreak prevention strategies including discontinuing the use of the contaminated well, issuing a permit for a new drinking water well, increasing portable toilet and handwashing station availability, and promoting proper hand hygiene. Despite the outbreaks at the venue and evidence of ground water contamination impacting nearby recreational water and the drinking water well, no new norovirus cases were reported during a large event one week after implementing prevention practices. This investigation highlights a new application for human-associated MST methods to trace hydrological connections between multiple fecal pollutant exposure routes in an outbreak scenario. In turn, pollutant source information can be used to develop effective intervention practices to mitigate exposure and prevent future outbreaks associated with human fecal contaminated waters.

Untreated sewage contamination of beach sand from a leaking underground sewage system

Thirty people (mostly children) experienced an episode of skin rash days after a sand sifting beach operation at Porto Pim Beach in Faial, Azores during June 2019. An environmental and epidemiologic investigation was conducted to identify the cause of the outbreak of skin rash. The epidemiologic investigation found that some of the patients experiencing symptoms had never entered the beach water. During the pollution period and throughout the epidemiologic investigation, faecal indicator bacteria levels (94 CFU/100 ml for intestinal enterococci and 61 CFU/100 ml for Escherichia coli) in water remained under the limits used for the ninety-five percentile calculation of an Excellent coastal and transitional bathing water defined in the Portuguese Legislation (100 CFU/100 ml for intestinal enterococci and 250 CFU/100 ml for Escherichia coli). Thus sand contact was considered as a likely primary exposure route. Sand microbiological analysis for faecal indicator organisms and electron microscopy strongly suggested faecal contamination. Chemical analysis of the sand also revealed a concomitant substance compatible with sodium-hypochlorite as analysed using gas chromatography and subsequently confirmed by free chlorine analysis. Inspection of the toilet facilities and sewage disposal system revealed a leaking sewage distribution box. Collectively, results suggest that the cause of the outbreak was the leaking underground sewage distribution box that serviced the beach toilet facilities (40 m from beach), where sodium-hypochlorite was used for cleaning and disinfection. This sewage then contaminated the surficial sands to which beach goers were exposed. Chlorine being an irritant substance, was believed to have been the cause of the symptoms given the sudden presentation and dissipation of skin rashes. No gastro-intestinal illness was reported during this episode and during the following 30 days. Like water, beach sand should also be monitored for safety, especially for areas serviced by aged infrastructure.

Implementation and integration of microbial source tracking in a river watershed monitoring plan

Fecal pollution of water bodies poses a serious threat for public health and ecosystems. Microbial source tracking (MST) is used to track the source of this pollution facilitating better management of pollution at the source. In this study we tested 12 MST markers to track human, ruminant, sheep, horse, pig and gull pollution to assess their usefulness as an effective management tool of water quality. First, the potential of the selected markers to track the source was evaluated using fresh fecal samples. Subsequently, we evaluated their performance in a catchment with different impacts, considering land use and environmental conditions. All MST markers showed high sensitivity and specificity, although none achieved 100% for both. Although some of the MST markers were detected in hosts other than the intended ones, their abundance in the target group was always several orders of magnitude higher than in the non-target hosts, demonstrating their suitability to distinguish between sources of pollution. The MST analysis matched the land use in the watershed allowing an accurate assessment of the main sources of pollution, in this case mainly human and ruminant pollution. Correlating environmental parameters including temperature and rainfall with MST markers provided insight into the dynamics of the pollution in the catchment. The levels of the human marker showed a significant negative correlation with rainfall in human polluted areas suggesting a dilution of the pollution, whereas at agricultural areas the ruminant marker increased with rainfall. There were no seasonal differences in the levels of human marker, indicating human pollution as a constant pressure throughout the year, whereas the levels of the ruminant marker was influenced by the seasons, being more abundant in summer and autumn. MST analysis integrated with land use and environmental data can improve the management of fecal polluted areas and set up best practice.

Microbial Water Quality Conditions Associated with Livestock Grazing, Recreation, and Rural Residences in Mixed-Use Landscapes

Contamination of surface waters with microbial pollutants from fecal sources is a significant human health issue. Identification of relative fecal inputs from the mosaic of potential sources common in rural watersheds is essential to effectively develop and deploy mitigation strategies. We conducted a cross-sectional longitudinal survey of fecal indicator bacteria (FIB) concentrations associated with extensive livestock grazing, recreation, and rural residences in three rural, mountainous watersheds in California, USA during critical summer flow conditions. Overall, we found that 86% to 87% of 77 stream sample sites across the study area were below contemporary Escherichia coli-based microbial water quality standards. FIB concentrations were lowest at recreation sites, followed closely by extensive livestock grazing sites. Elevated concentrations and exceedance of water quality standards were highest at sites associated with rural residences, and at intermittently flowing stream sites. Compared to national and state recommended E. coli-based water quality standards, antiquated rural regional policies based on fecal coliform concentrations overestimated potential fecal contamination by as much as four orders of magnitude in this landscape, hindering the identification of the most likely fecal sources and thus the efficient targeting of mitigation practices to address them.

Occurrence, distribution, and source track of antibiotics and antibiotic resistance genes in the main rivers of Chongqing city, Southwest China

In this study, the occurrence of 14 antibiotics, four corresponding antibiotic resistance genes (ARGs) and two microbial source tracker (MST) indicators were analyzed in two rivers of Chongqing city, southwest China. The results showed that 13 antibiotics were detected in all 12 sites and their detection frequencies were much higher in September, but concentrations were lower than that in March. Of them, erythromycin (ETM) and ofloxacin (OFL) were the predominant antibiotics in both seasons. The remarkably higher concentration of antibiotics in sediments of these rivers than those in other rivers were found. Environmental risk assessment found that four antibiotics posed high risk toward some sensitive algae. For ARGs, their relative abundances were higher in waters than those in sediments, higher in March than in September. Correlation analysis showed that antibiotics were not the exclusive selective pressure of ARGs; many environmental factors like dry matter contents on a mass basis, organic matter, total organic carbon, dissolved organic carbon, temperature, oxidation reduction potential and nitrite could affect the occurrence of ARGs. MST indicators analysis demonstrated that this river basin was largely polluted by human and pig feces, and human feces might be one main source of the four ARGs and five antibiotics.

Spatial and Temporal Characterization of Escherichia coli, Suspended Particulate Matter and Land Use Practice Relationships in a Mixed-Land Use Contemporary Watershed

Understanding land use practice induced increases in Escherichia (E.) coli and suspended particulate matter (SPM) concentrations is necessary to improve water quality. Weekly stream water samples were collected from 22 stream gauging sites with varying land use practices in a representative contemporary mixed-land use watershed of the eastern USA. Over the period of one annual year, Escherichia (E.) coli colony forming units (CFU per 100 mL) were compared to suspended particulate matter (SPM) concentrations (mg/L) and land use practices. Agricultural land use sub-catchments comprised elevated E. coli concentrations (avg. 560 CFU per 100 mL) compared to proximate mixed development (avg. 330 CFU per 100 mL) and forested (avg. 206 CFU per 100 mL) sub-catchments. Additionally, agricultural land use showed statistically significant relationships (p < 0.01) between annual E. coli and SPM concentration data. Quarterly PCA biplots displayed temporal variability in land use impacts on E. coli and SPM concentrations, with agricultural land use being closely correlated with both pollutants during Quarters 2 and 3 but not Quarters 1 and 4. The data collected during this investigation advance the understanding of land use impacts on fecal contamination in receiving waters, thereby informing land use managers on the best management practices to reduce exposure risks.

Anthropogenic pollution of aquatic ecosystems: Emerging problems with global implications

Aquatic ecosystems cover over two thirds of our planet and play a pivotal role in stabilizing the global climate as well as providing a large array of services for a fast-growing human population. However, anthropogenic activities increasingly provoke deleterious impacts in aquatic ecosystems. In this paper we discuss five sources of anthropogenic pollution that affect marine and freshwater ecosystems: sewage, nutrients and terrigenous materials, crude oil, heavy metals and plastics. Using specific locations as examples, we show that land-based anthropogenic activities have repercussions in freshwater and marine environments, and we detail the direct and indirect effects that these pollutants have on a range of aquatic organisms, even when the pollutant source is distant from the sink. While the issues covered here do focus on specific locations, they exemplify emerging problems that are increasingly common around the world. All these issues are in dire need of stricter environmental policies and legislations particularly for pollution at industrial levels, as well as solutions to mitigate the effects of anthropogenic pollutants and restore the important services provided by aquatic ecosystems for future generations.

Advancing Understanding of Land Use and Physicochemical Impacts on Fecal Contamination in Mixed-Land-Use Watersheds

Understanding mixed-land-use practices and physicochemical influences on Escherichia (E.) coli concentrations is necessary to improve water quality management and human health. Weekly stream water samples and physicochemical data were collected from 22 stream gauging sites representing varying land use practices in a contemporary Appalachian watershed of the eastern USA. Over the period of one annual year, Escherichia (E.) coli colony forming units (CFU) per 100 mL were compared to physicochemical parameters and land use practices. Annual average E. coli concentration increased by approximately 112% from acid mine drainage (AMD) impacted headwaters to the lower reaches of the watershed (approximate averages of 177 CFU per 100 mL vs. 376 CFU per 100 mL, respectively). Significant Spearman’s correlations (p < 0.05) were identified from analyses of pH and E. coli concentration data representing 77% of sample sites; thus highlighting legacy effects of historic mining (AMD) on microbial water quality. A tipping point of 25–30% mixed development was identified as leading to significant (p < 0.05) negative correlations between chloride and E. coli concentrations. Study results advance understanding of land use and physicochemical impacts on fecal contamination in mixed-land-use watersheds, aiding in the implementation of effective water quality management practices and policies.

Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural Water

Agricultural water is an important source of foodborne pathogens on produce farms. Managing water-associated risks does not lend itself to one-size-fits-all approaches due to the heterogeneous nature of freshwater environments. To improve our ability to develop location-specific risk management practices, a study was conducted in two produce-growing regions to (i) characterize the relationship between Escherichia coli levels and pathogen presence in agricultural water, and (ii) identify environmental factors associated with pathogen detection. Three AZ and six NY waterways were sampled longitudinally using 10-L grab samples (GS) and 24-h Moore swabs (MS). Regression showed that the likelihood of Salmonella detection (Odds Ratio [OR] = 2.18), and eaeA-stx codetection (OR = 6.49) was significantly greater for MS compared to GS, while the likelihood of detecting L. monocytogenes was not. Regression also showed that eaeA-stx codetection in AZ (OR = 50.2) and NY (OR = 18.4), and Salmonella detection in AZ (OR = 4.4) were significantly associated with E. coli levels, while Salmonella detection in NY was not. Random forest analysis indicated that interactions between environmental factors (e.g., rainfall, temperature, turbidity) (i) were associated with likelihood of pathogen detection and (ii) mediated the relationship between E. coli levels and likelihood of pathogen detection. Our findings suggest that (i) environmental heterogeneity, including interactions between factors, affects microbial water quality, and (ii) E. coli levels alone may not be a suitable indicator of food safety risks. Instead, targeted methods that utilize environmental and microbial data (e.g., models that use turbidity and E. coli levels to predict when there is a high or low risk of surface water being contaminated by pathogens) are needed to assess and mitigate the food safety risks associated with preharvest water use. By identifying environmental factors associated with an increased likelihood of detecting pathogens in agricultural water, this study provides information that (i) can be used to assess when pathogen contamination of agricultural water is likely to occur, and (ii) facilitate development of targeted interventions for individual water sources, providing an alternative to existing one-size-fits-all approaches.

Fecal indicator dynamics at the watershed scale: Variable relationships with land use, season, and water chemistry

Tracking fecal contamination in surface waters is critical to remediating water quality; however, general and source-specific fecal indicators often provide conflicting results. To understand the spatial and temporal dynamics of multiple fecal indicators and the sources they represent, we measured weekly concentrations of two general fecal indicator bacteria (FIB), a genetic indicator of human-associated Bacteroides (HF183), and surface water chemistry in nine mixed land-use watersheds in southwest Virginia, USA. At the watershed scale, general and source-specific indicators were decoupled, with distinct spatial, temporal, and chemical patterns. Random Forest analysis of individual sample variability identified temperature, watershed, nutrients, and cations as top predictors of indicator concentrations. However, these patterns - and the specific nutrients and cations identified - varied by indicator type. Among watersheds, FIB increased with developed land cover and during the summer months, while HF183 increased during the winter and only in urban watersheds. Nutrients generally related poorly to FIB and HF183, except E. coli, which correlated with total nitrogen. In contrast, all fecal indicators showed strong correlations with cations. FIB were more strongly related to calcium, magnesium, and potassium concentrations, while HF183 was related to sodium. These results suggest that, even at the watershed scale, 1) HF183 detects mainly human fecal contamination, while FIB detect broader ecosystem fecal inputs, and 2) poor correlation between specific and generalist fecal indicators is caused by unique spatial, temporal, and transport dynamics of different fecal sources in watersheds.

Impact of sanitation and socio-economy on groundwater fecal pollution and human health towards achieving sustainable development goals across India from ground-observations and satellite-derived nightlight

Globally, ~1 billion people, mostly residing in Africa and South Asia (e.g. India), still lack access to clean drinking water and sanitation. Resulting, unsafe disposal of fecal waste from open-defecation to nearby drinking water sources severely endanger public health. Until recently, India had a huge open-defecating population, leading declining public health from water-borne diseases like diarrhoea by ingesting polluted water, mostly sourced to groundwater. However, in recent past, sanitation development to achieve Sustainable Development Goals (SDGs) has been encouraged throughout India, but their effect to groundwater quality and human health conditions are yet-unquantified. Here, for the first time, using long term, high-spatial resolution measurements (>1.7 million) across India and analyses, we quantified that over the years, groundwater fecal coliform concentration (2002-2017, -2.56 ± 0.06%/year) and acute diarrheal cases (1990-2016, -3.05 ± 0.01%/year) have significantly reduced, potentially influenced by sanitation development (1990-2017, 2.63 ± 0.01%/year). Enhanced alleviation of groundwater quality and human health have been observed since 2014, with initiation of acceletated constructions of sanitation infrastructures through Clean India (Swachh Bharat) Mission. However, the goal of completely faecal-pollution free, clean drinking water is yet to be achieved. We also evaluated the suitability of using satellite-derived night-time light (NL_an, 1992-2013, 4.26 ± 0.05%/year) as potential predictor for such economic development. We observed that in more than 80% of the study region, night-time light demonstrated to be a strong predictor for observed changes in groundwater quality, sanitation development and water-borne disease cases. While sanitation and economic development can improve public health, poor education level and improper human practices can strongly influence on water-borne diseases loads and thus health in parts of India.

Impacts of a changing earth on microbial dynamics and human health risks in the continuum between beach water and sand

Although infectious disease risk from recreational exposure to waterborne pathogens has been an active area of research for decades, beach sand is a relatively unexplored habitat for the persistence of pathogens and fecal indicator bacteria (FIB). Beach sand, biofilms, and water all present unique advantages and challenges to pathogen introduction, growth, and persistence. These dynamics are further complicated by continuous exchange between sand and water habitats. Models of FIB and pathogen fate and transport at beaches can help predict the risk of infectious disease from beach use, but knowledge gaps with respect to decay and growth rates of pathogens in beach habitats impede robust modeling. Climatic variability adds further complexity to predictive modeling because extreme weather events, warming water, and sea level change may increase human exposure to waterborne pathogens and alter relationships between FIB and pathogens. In addition, population growth and urbanization will exacerbate contamination events and increase the potential for human exposure. The cumulative effects of anthropogenic changes will alter microbial population dynamics in beach habitats and the assumptions and relationships used in quantitative microbial risk assessment (QMRA) and process-based models. Here, we review our current understanding of microbial populations and transport dynamics across the sand-water continuum at beaches, how these dynamics can be modeled, and how global change factors (e.g., climate and land use) should be integrated into more accurate beachscape-based models.

Linking landscape patterns to sources of water contamination: Implications for tracking fecal contaminants with geospatial and Bayesian approaches

Microbial source tracking (MST) techniques have been designed to identify the host source of fecal contamination in water. However, current MST techniques cannot provide geographic origins of particular sources because they do not provide any spatial information beyond the points of observation. In this study, the associations between landscape patterns and the major sources of microbial contamination were examined and the application of geospatial techniques (e.g., remote sensing and geographic information systems) and Bayesian modeling was explored to track microbial sources over the landscape. The land cover information of three watersheds (the lower Dungeness Watershed, the Middle Rio Grande Watershed, and the Arroyo Burro Watershed) in the United States was obtained either by classifying high resolution satellite images or directly using land cover datasets (e.g., National Land Cover Dataset, 2006 and 2011). Then, the relationship between land use/land cover (LULC) and microbial sources from these three geographically disparate watersheds were analyzed using Bayesian hierarchical models. The results showed the predictive positive associations between human sources of fecal contamination and developed area, between dog sources and grassland, and between bird sources and water, but negative associations between human sources and forest and water areas. Furthermore, the diversity of microbial sources had positive associations with landscape fragmentation and diversity indices. This study demonstrates associations between landscape patterns and major microbial sources and offers new insight in tracking the dominant sources of fecal contamination in water using geospatial and Bayesian techniques.

Fecal indicator bacteria levels at beaches in the Florida Keys after Hurricane Irma

Hurricanes cause infrastructure failures which can lead to contamination of impacted areas. The objective of the current study was to evaluate whether Hurricane Irma contributed towards sewage contamination of coastal beaches. Through this study we evaluated indicators of fecal pollution (fecal indicator bacteria [FIB], enterococci and fecal coliform) and physico-chemical parameters (salinity, pH, turbidity, and temperature) in coastal waters of the Florida Keys shortly after the hurricane. To augment available county sampling data, two sets of sampling efforts were conducted; one focused on collecting samples spatially throughout the Keys to assess whether areas closer to hurricane landfall were more highly impacted. The second was to collect temporally intensive samples at one location during falling tide to evaluate the hypothesis of groundwater contamination. Samples were analyzed for FIB using a new method called timed appearance of culture signal (TACS), which was subsequently calibrated using traditional membrane filter and chromogenic substrate methods. Results showed that coastal beach waters were characterized by elevated but sporadic levels of fecal indicator bacteria up to two months after the hurricane. Spikes were not correlated with physico-chemical characteristics of the water. Our temporally intensive sampling effort did not support the hypothesis that groundwater was a source of elevated FIB. Competing factors could have played a role in the sporadic nature of the FIB levels after the hurricane. We suggest that beach erosion may have flushed out sediments at beaches closer to the hurricane landfall location thereby improving water quality during dry conditions. We also suggest that during wet conditions a source of FIB could include runoff from debris staging areas. Preemptive beach closures immediately after the hurricane were justified due to the sporadic nature of FIB contamination.

Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds

Fecal contamination from sewage and agricultural runoff is a pervasive problem in Great Lakes watersheds. Most work examining fecal pollution loads relies on discrete samples of fecal indicators and modeling land use. In this study, we made empirical measurements of human and ruminant-associated fecal indicator bacteria and combined these with hydrological measurements in eight watersheds ranging from predominantly forested to highly urbanized. Flow composited river samples were collected over low-flow ( n = 89) and rainfall or snowmelt runoff events ( n = 130). Approximately 90% of samples had evidence of human fecal pollution, with highest loads from urban watersheds. Ruminant indicators were found in ∼60-100% of runoff-event samples in agricultural watersheds, with concentrations and loads related to cattle density. Rain depth, season, agricultural tile drainage, and human or cattle density explained variability in daily flux of human or ruminant indicators. Mapping host-associated indicator loads to watershed discharge points sheds light on the type, level, and possible health risk from fecal pollution entering the Great Lakes and can inform total maximum daily load implementation and other management practices to target specific fecal pollution sources.