Journal of Environmental Engineering

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

In recent times methanotrophs have gained immense interest due to their ability to sequester and utilize methane, which is an inexpensive carbon source as well as a very potent greenhouse gas. Despite their vast potential for both industrial and environmental applications, only a few methanotrophs have been well studied to date. A novel and an efficient obligate methanotroph was isolated from a methanotrophic consortium originated from a municipal solid waste leachate. The isolate belonged to the genus Methylosarcina as confirmed by 16S ribosomal ribonucleic acid (rRNA) phylogenetic analysis and was further characterized by scanning electron microscopy, chemotaxonomic, and carbon, hydrogen, nitrogen, and sulphur (CHNS) elemental analysis. Methane oxidation by the isolate was studied in detail, including kinetics, specific oxygen requirement, and carbon capture efficiency. Further, the fate of oxidized methane was determined, unraveling its potential in the bioremediation of methane.

A numerical framework was developed to study oil-particle aggregate (OPA) formation by incorporating NEMO3D code and the A-DROP model into an open-source platform, OpenFOAM. The developed framework was then used to study oil transport and OPA formation in a two-dimensional (2D) hypothetical river at a depth of $3.0\mathrm{m}$. The river’s hydrodynamic profile was used in conjunction with the A-DROP model to simulate OPA formation, whereas the NEMO3D model was used to track the movement of the oil droplets and OPAs. Results suggest that an increase in buoyancy results in a decrease in the streamwise variance and spreading coefficient. The small (i.e., $50\mathrm{\mu m}$) droplets became entrained in the deep water column at high-energy dissipation rates, which enhanced OPA formation. The large (i.e., $200\mathrm{\mu m}$) droplets aggregated much more rapidly than the small ones in the same turbulence environment owing to differential sedimentation. In general, OPA formation in the upper rivers was dominated by collisions caused by differential sedimentation, while in the deep water column, collision caused by turbulence shear plays a more critical role. The aggregation rates of the formed OPAs were less than 60% within a short period ($20\min$) in a river with relatively mild turbulence ($\epsilon {<5\times 10}^{-4}\mathrm{W}/\mathrm{kg}$).

The development of pathogenic bacteria encompassing antibiotics-resistant genes (ARGs) is a severe environmental concern related to human health. Among all antibiotics administered to humans, the β-lactam group’s antibiotics account for two-thirds of the total weight due to its clinical effectiveness and low toxicity. This study investigated the abundance of gene NDM-1 (New Delhi metallo-β-lactamase-1) as an emerging contaminant in Hyderabad, India’s water bodies using a quantitative polymerase chain reaction (qPCR). The quantitative microbial risk assessment (QMRA) method was applied to forecast the human health risk linked to ingestion/subjection of surface water with bacteria containing the NDM-1 gene. The gene copy number of the NDM-1 in the exposure route was taken into consideration for the determination of risk in best- and worst-case scenarios. The lowest and highest gene copy numbers were selected as the best-case scenario and the worst-case scenario, respectively. The outlet of Amberpet sewage treatment plant (STP) exhibited the lowest risk, $2\times {10}^{-2}$, i.e., 2 of 100 people are exposed to infection. In contrast, Mir Alam tank lake exhibited the highest risk, $77\times {10}^{-2}$, i.e., 77 of 100 people are exposed to infection. Risk assessment categorized the sampling locations into low, medium, and high risk of infection. Sampling areas with a low risk of infection included Amberpet STP outlet ($2\times {10}^{-2}$), Ameenpur lake ($24\times {10}^{-3}$), Manjeera water treatment plant (WTP) outlet ($26\times {10}^{-3}$), and Osman Sagar lake ($24\times {10}^{-3}$). Sampling locations with a medium risk of infection included Alwal lake ($23\times {10}^{-2}$), Durgamcheru lake ($47\times {10}^{-2}$), Hussain Sagar lake ($21\times {10}^{-2}$), Mominpet lake ($27\times {10}^{-2}$), and Saroor Sagar lake ($43\times {10}^{-2}$). Sampling zones including Fox Sagar lake ($53\times {10}^{-2}$), Himayat Sagar lake ($70\times {10}^{-2}$), Kandi lake ($56\times {10}^{-2}$), Manjeera dam ($66\times {10}^{-2}$), Mir Alam tank lake ($77\times {10}^{-2}$), Nagole lake ($54\times {10}^{-2}$), Safilguda lake ($55\times {10}^{-2}$), and Singur dam ($57\times {10}^{-2}$) were categorized as zones with a high risk of infection. The findings of the occurrence of the NDM-1 gene containing bacteria in water bodies surrounding Hyderabad and its related risk will be valuable for developing strategies to safeguard the public from the threat of clinical risks correlated with the dissemination of NDM-1.