Considering Water Quality of Urban Rivers from the Perspectives of Unpleasant Odor

Metagenomic profiling of antibiotic resistance genes and their associations with the bacterial community along the Kanda River, an urban river in Japan

Antibiotic resistance genes (ARGs) present in urban rivers have the potential to disseminate antibiotic-resistant bacteria into other environments, posing significant threats to both ecological and public health. Although metagenomic analyses have been widely employed to detect ARGs in rivers, our understanding of their dynamics across different seasons in diverse watersheds remains limited. In this study, we performed a comprehensive genomic analysis of the Kanda River in Japan at 11 sites from upstream to estuary throughout the year to assess the spread of ARGs and their associations with bacterial communities. Analysis of 110 water samples using the 16S rRNA gene revealed variations in bacterial composition corresponding to seasonal changes in environmental parameters along the river. Shotgun metagenomics-based profiling of ARGs in 44 water samples indicated higher ARG abundance downstream, particularly during the summer. Weighted gene co-expression network analysis (WGCNA) linking bacterial lineages and ARGs revealed that 12 ARG subtypes co-occurred with 128 amplicon sequence variants (ASVs). WGCNA suggested potential hosts for ErmB, ErmF, ErmG, tetQ, tet (W/N/W), aadA2, and adeF, including gut-associated bacteria (e.g., Prevotella, Bacteroides, Arcobacter) and indigenous aquatic microbes (e.g., Limnohabitans and C39). In addition, Pseudarcobacter (a later synonym of Arcobater) was identified as a host for adeF, which was also confirmed by single cell genomics. This study shows that ARG distribution in urban rivers is affected by seasonal and geographical factors and demonstrates the importance of monitoring rivers using multiple types of genome sequencing, including 16S rRNA gene sequencing, metagenomics, and single cell genomics.

Spatial distribution of cable bacteria in nationwide organic-matter-polluted urban rivers in China

An overload of labile organic matter triggers the water blackening and odorization in urban rivers, leading to a unique microbiome driving biogeochemical cycles in these anoxic habitats. Among the key players in these environments, cable bacteria interfere directly with C/N/S/O cycling, and are closely associated with phylogenetically diverse microorganisms in anoxic sediment as an electron conduit to mediate long-distance electron transport from deep-anoxic-layer sulfide to oxic-layer oxygen. Despite their hypothesized importance in black-odorous urban rivers, the spatial distribution patterns and roles of cable bacteria in large-scale polluted urban rivers remain inadequately understood. This study examined the diversity and spatial distribution pattern of cable bacteria in sediment samples from 186 black-odorous urban rivers across China. Results revealed the co-existence of two well-characterized cable bacteria (i.e., Candidatus Electrothrix and Candidatus Electronema), with Candidatus Electrothrix exhibiting a comparatively wider distribution in the polluted urban rivers. Concentrations of DOC, SS, sulfate, nitrate, and heavy metals (e.g., Ni and Cr) were correlated with the cable bacteria diversity, indicating their essential role in biogeochemical cycles. The activation energy of cable bacteria was 0.624 eV, close to the canonical 0.65 eV. Furthermore, cable bacteria were identified as key connectors and module hubs, closely associated with denitrifiers, sulfate-reducing bacteria, methanogens and alkane degraders, highlighting their role as keystone functional lineages in the contaminated urban rivers. Our study provided the first large-scale and comprehensive insight into the cable bacteria diversity, spatial distribution, and their essential function as keystone species in organic-matter-polluted urban rivers.

The impact of combined sewer outflows on urban water quality: Spatio-temporal patterns of fecal coliform in indianapolis

Many urban waterways with older stormwater drainage systems receive a significant amount of untreated or poorly treated waste from Combined Sewer Outflow (CSO) systems during precipitation events. The input of effluent waste from CSO to urban water streams during storm events often leads to elevated fecal coliform, specifically Escherichia Coli (E. Coli) in these waterways. The aim of the study is to examine fecal coliform concentration, water chemistry, and water quality parameters to better understand spatio-temporal patterns of fecal coliform associated with CSO events in three waterways from Indianapolis, Indiana (USA). The waterways are Pleasant Run Creek (PRW), Fall Creek (FC) and White River (WR). The sampling occurred biweekly over one year for PRW, nine months for FC, and an intense (∼every three days) sub-analysis of the presumed peak period of fecal coliform growth (July) for WR. All PRW and FC sampling sites significantly exceeded the EPA contact standard limit of 200 CFU/100 mL for fecal coliform concentrations during the sampling period. We found no relationship between fecal coliform levels and the number or density of CSO outfalls above a given site. The most significant predictors of increased fecal coliform concentrations were precipitation on the sampling day and cumulative degree days. The most significant predictors of decreased fecal coliform were maximum precipitation during the ten-day window prior to sampling and median discharge during a three-day window prior to sampling. These findings suggest a push-pull balance within the system where CSO activation and seasonal gradients replenish and promote fecal coliform growth. At the same time, large hydrologic events act to flush and dilute fecal coliform concentrations. The results from this study help us to better understand how different drivers influence fecal coliform growth and how this information can be potentially used to predict and remediate the conditions of urban water streams.

Microbial sulfur metabolism and environmental implications

Sulfur as a macroelement plays an important role in biochemistry in both natural environments and engineering biosystems, which can be further linked to other important element cycles, e.g. carbon, nitrogen and iron. Consequently, the sulfur cycling primarily mediated by sulfur compounds oxidizing microorganisms and sulfur compounds reducing microorganisms has enormous environmental implications, particularly in wastewater treatment and pollution bioremediation. In this review, to connect the knowledge in microbial sulfur metabolism to environmental applications, we first comprehensively review recent advances in understanding microbial sulfur metabolisms at molecular-, cellular- and ecosystem-levels, together with their energetics. We then discuss the environmental implications to fight against soil and water pollution, with four foci: (1) acid mine drainage, (2) water blackening and odorization in urban rivers, (3) SANI® and DS-EBPR processes for sewage treatment, and (4) bioremediation of persistent organic pollutants. In addition, major challenges and further developments toward elucidation of microbial sulfur metabolisms and their environmental applications are identified and discussed.

Monitoring urban black-odorous water by using hyperspectral data and machine learning

Economic development, population growth, industrialization, and urbanization dramatically increase urban water quality deterioration, and thereby endanger human life and health. However, there are not many efficient methods and techniques to monitor urban black and odorous water (BOW) pollution. Our research aims at identifying primary indicators of urban BOW through their spectral characteristics and differentiation. This research combined ground in-situ water quality data with ground hyperspectral data collected from main urban BOWs in Guangzhou, China, and integrated factorial data mining and machine learning techniques to investigate how to monitor urban BOW. Eight key water quality parameters at 52 sample sites were used to retrieve three latent dimensions of urban BOW quality by factorial data mining. The synchronically measured hyperspectral bands along with the band combinations were examined by the machine learning technique, Lasso regression, to identify the most correlated bands and band combinations, over which three multiple regression models were fitted against three latent water quality indicators to determine which spectral bands were highly sensitive to three dimensions of urban BOW pollution. The findings revealed that the many sensitive bands were concentrated in higher hyperspectral band ranges, which supported the unique contribution of hyperspectral data for monitoring water quality. In addition, this integrated data mining and machine learning approach overcame the limitations of conventional band selection, which focus on a limited number of band ratios, band differences, and reflectance bands in the lower range of infrared region. The outcome also indicated that the integration of dimensionality reduction with feature selection shows good potential for monitoring urban BOW. This new analysis framework can be used in urban BOW monitoring and provides scientific data for policymakers to monitor it.

Identifying the location of odour nuisance emitters using spatial GIS analyses

The primary objective of the article was to establish the location of odour emitters with the use of spatial GIS analyses. The odour emitter location analysis based on measurements was carried out using QGIS software tools. The algorithm of the procedure was developed by analysing vector elements, including simulated odour streaks (in the form of wedge buffer surfaces) and a regular grid of points needed to determine the presence of a given buffer in a given location. Statistical analysis was performed in ArcGIS software. The detailed aim of the conducted study was to analyse the nuisance of odours from the measurement data on the basis of IDW interpolation and the arrangement of buildings. An innovative element of the developed analysis is the application of the inversed method of fragrance streak propagation. Identifying a streak from the measuring point towards the blowing wind is very likely to determine the approximate location of the odour emitter measured. The described method should provide better results at the location of emitters than the above mentioned methods using interpolation, because of taking into account wind direction and speed. In addition, it is a method that can be applied over a large open area where methods based on simulation and particle propagation would not be efficient or highly impossible to apply due to extensive and complex analysis. It was necessary to conduct field studies in order to meet the main goal, which resulted in sensory evaluation of the intensity of odour nuisance in an urbanised area. Odour concentration tests using field olfactometry with NasalRanger olfactometer were taken.

Linking microbial community and biological functions to redox potential during black-odor river sediment remediation

The black-odor phenomenon in polluted urban rivers is a serious environmental problem that has received increasing attention in the recent years. The low redox potential (less than - 100 mV) in the sediment is considered to be the key factor causing the occurrence of black-odor phenomenon. Here, we studied the structure and function of the microbial community during the remediation of urban rivers. Results showed a clear improvement in water quality after undergoing river remediation processes. The on-site treatments showed a succession in the microbial composition and their predicted functions. The primary iron- and sulfur-reducing bacteria (Thiobacillus, Sulfuricurvum, and Sulfursoma) and the related reactions rapidly decreased after the dredging treatment but reappeared after a year. The structure and abundance of nitrogen and methane participants were also affected by river remediation process. These results indicated that although the water quality temporarily improved shortly after a dredging process, a recurrence of the black-odor phenomenon may occur as a result of the rebound in the microbial communities.

Characteristics and Influencing Factors of Spatial Differentiation of Urban Black and Odorous Waters in China

The pollution problem caused by urban black and odorous waters has received much attention from the Chinese government. Our research aims at systematically identifying the characteristics and the influential factors of spatial differentiation of urban black and odorous waters across China. The research, based on the data of black and odorous waters from 2100 Chinese cities, was conducted with the spatial analysis tool of ArcGIS. We found that the amount of Chinese urban black and odorous waters varied in spatial distribution, which was an agglomerated type with significant agglomeration. The kernel density was characterized by independent single kernel centers with ribbon-like and sporadic distributions of subcenters. The cold and hot spots showed a gradient distribution pattern of cold in the southwest and hot in the central east. These spatial distribution characteristics could be attributed to the following core factors, total wastewater discharge, length of urban drainage pipelines, municipal solid waste collection, daily urban sewage treatment capacity, and investment in urban pollution treatment of wastewater. The findings reveal the current geospatial distribution of black and odorous waters pollution and provide reference for the Chinese government to treat the pollution from several key points. Lastly, it is suggested that the Chinese government should establish joint control, joint prevention, and joint treatment mechanisms in the black and odorous waters areas and improve the safety standards of the whole water environment, so as to promote the treatment and elimination of urban black and odorous waters.