Bacterial Indicators Are Ubiquitous Members of Pelagic Microbiome in Anthropogenically Impacted Coastal Ecosystem

Coastal zones are exposed to various anthropogenic impacts, such as different types of wastewater pollution, e.g., treated wastewater discharges, leakage from sewage systems, and agricultural and urban runoff. These various inputs can introduce allochthonous organic matter and microbes, including pathogens, into the coastal marine environment. The presence of fecal bacterial indicators in the coastal environment is usually monitored using traditional culture-based methods that, however, fail to detect their uncultured representatives. We have conducted a year-around in situ survey of the pelagic microbiome of the dynamic coastal ecosystem, subjected to different anthropogenic pressures to depict the seasonal and spatial dynamics of traditional and alternative fecal bacterial indicators. To provide an insight into the environmental conditions under which bacterial indicators thrive, a suite of environmental factors and bacterial community dynamics were analyzed concurrently. Analyses of 16S rRNA amplicon sequences revealed that the coastal microbiome was primarily structured by seasonal changes regardless of the distance from the wastewater pollution sources. On the other hand, fecal bacterial indicators were not affected by seasons and accounted for up to 34% of the sequence proportion for a given sample. Even more so, traditional fecal indicator bacteria (Enterobacteriaceae) and alternative wastewater-associated bacteria (Lachnospiraceae, Ruminococcaceae, Arcobacteraceae, Pseudomonadaceae and Vibrionaceae) were part of the core coastal microbiome, i.e., present at all sampling stations. Microbial source tracking and Lagrangian particle tracking, which we employed to assess the potential pollution source, revealed the importance of riverine water as a vector for transmission of allochthonous microbes into the marine system. Further phylogenetic analysis showed that the Arcobacteraceae in our data set was affiliated with the pathogenic Arcobacter cryaerophilus, suggesting that a potential exposure risk for bacterial pathogens in anthropogenically impacted coastal zones remains. We emphasize that molecular analyses combined with statistical and oceanographic models may provide new insights for environmental health assessment and reveal the potential source and presence of microbial indicators, which are otherwise overlooked by a cultivation approach.

Irrigation quality and management determine salinization in Israeli olive orchards

Olive (Olea europaea L.) orchard brackish water irrigation with incorrect irrigation management reduces soil fertility and degrades soil health through soil salinization. This study was conducted in the Beit She'an Valley, one of the main agricultural regions in Israel, in an olive orchard in which a combination of soil salinization and poor drainage conditions impedes plant development and causes severe economic damage. By combining various research methods, including soil salinity monitoring, field experiments, remote sensing (frequency domain electromagnetic – FDEM), and unsaturated soil profile saline water movement modeling, the salinization processes were quantified. Irrigation water conductance of 3.13 dS m−1 points to salinization within the tree upper root zone, whereas the modeling results suggest that salinization danger is greater with brackish treated wastewater rather than with lower-salinity brackish irrigation groundwater and that irrigation with potable water can help reduce salt accumulation and recover damaged plots.

A review of the function of using carbon nanomaterials in membrane filtration for contaminant removal from wastewater

Water is a necessity for all living and non-living organisms on this planet. It is understood that clean water sources are decreasing by the day, and the rapid rise of Industries and technology has led to an increase in the release of toxic effluents that are discharged into the environment. Wastewater released from Industries, agricultural waste, and municipalities must be treated before releasing into the environment as they contain harmful pollutants such as organic dyes, pharmaceuticals wastes, inorganic materials, and heavy metal ions. If not controlled, they can cause serious risks to human beings' health and contaminate our environment. Membrane filtration is a proven method for the filtration of various harmful chemicals and microbes from water. Carbon nanomaterials are applied in wastewater treatment due to their high surface area, making them efficient adsorbents. Carbon nanomaterials are being developed and utilized in membrane filtration for the treated wastewater before getting discharged with the rise of nanotechnology. This review studies carbon nanomaterials like fullerenes, graphenes, and CNTs incorporated in the membrane filtration to treat wastewater contaminants. We focus on these CNM based membranes and membrane technology, their properties and applications, and how they can enhance the commonly used membrane filtration performance by considering adsorption rate, selectivity, permeability, antimicrobial disinfectant properties, and compatibility with the environment.

Machine Learning Approach to Predict Quality Parameters for Bacterial Consortium-Treated Hospital Wastewater and Phytotoxicity Assessment on Radish, Cauliflower, Hot Pepper, Rice and Wheat Crops

Raw hospital wastewater is a source of excessive heavy metals and pharmaceutical pollutants. In water-stressed countries such as Pakistan, the practice of unsafe reuse by local farmers for crop irrigation is of major concern. In our previous work, we developed a low-cost bacterial consortium wastewater treatment method. Here, in a two-part study, we first aimed to find what physico-chemical parameters were the most important for differentiating consortium-treated and untreated wastewater for its safe reuse. This was achieved using a Kruskal–Wallis test on a suite of physico-chemical measurements to find those parameters which were differentially abundant between consortium-treated and untreated wastewater. The differentially abundant parameters were then input to a Random Forest classifier. The classifier showed that ‘turbidity’ was the most influential parameter for predicting biotreatment. In the second part of our study, we wanted to know if the consortium-treated wastewater was safe for crop irrigation. We therefore carried out a plant growth experiment using a range of popular crop plants in Pakistan (Radish, Cauliflower, Hot pepper, Rice and Wheat), which were grown using irrigation from consortium-treated and untreated hospital wastewater at a range of dilutions (turbidity levels) and performed a phytotoxicity assessment. Our results showed an increasing trend in germination indices and a decreasing one in phytotoxicity indices in plants after irrigation with consortium-treated hospital wastewater (at each dilution/turbidity measure). The comparative study of growth between plants showed the following trend: Cauliflower > Radish > Wheat > Rice > Hot pepper. Cauliflower was the most adaptive plant (PI: −0.28, −0.13, −0.16, −0.06) for the treated hospital wastewater, while hot pepper was susceptible for reuse; hence, we conclude that bacterial consortium-treated hospital wastewater is safe for reuse for the irrigation of cauliflower, radish, wheat and rice. We further conclude that turbidity is the most influential parameter for predicting bio-treatment efficiency prior to water reuse. This method, therefore, could represent a low-cost, low-tech and safe means for farmers to grow crops in water stressed areas.