Degradation of multiple PAHs and co-contaminants by microbial consortia and their toxicity assessment.

The anthropogenic activities toward meeting the energy requirements have resulted in an alarming rise in environmental pollution levels. Among pollutants, polycyclic aromatic hydrocarbons (PAHs) are the most predominant due to their persistent and toxic nature. Amidst the several pollutants depuration methods, bioremediation utilizing biodegradation is the most viable alternative. This study investigated the biodegradation efficacy using developed microbial consortium PBR-21 for 2-4 ringed PAHs named naphthalene (NAP), anthracene (ANT), fluorene (FLU), and pyrene (PYR). The removal efficiency was observed up to 100 ± 0.0%, 70.26 ± 4.2%, 64.23 ± 2.3%, and 61.50 ± 2.6%, respectively, for initial concentrations of 400 mg L-1 for NAP, ANT, FLU, and PYR respectively. Degradation followed first-order kinetics with rate constants of 0.39 d-1, 0.10 d-1, 0.08 d-1, and 0.07 d-1 and half-life t 1 / 2  of 1.8 h, 7.2 h, 8.5 h, and 10 h, respectively. The microbial consortia were found to be efficient towards the co-contaminants with 1 mM concentration. Toxicity examination indicated that microbial-treated PAHs resulted in lesser toxicity in aquatic crustaceans (Artemia salina) than untreated PAHs. Also, the study suggests that indigenous microbial consortia PBR-21 has the potential to be used in the bioremediation of PAH-contaminated environment.

Interaction of physico-chemical parameters with Shannon-Weaver Diversity Index based on phytoplankton diversity in coastal water of Diu, India.

Phytoplankton acts as carbon sinks due to photosynthetic efficacy and their diversity is expressed by SWDI (Shannon-Weaver Diversity Index), which depends on water quality parameters. The coastal water of Diu was studied for three seasons, and the relationship between different parameters and SWDI was established. Subsequently, an attempt was made to build up a prediction model of SWDI based on multilayer perceptron Artificial neural network (ANN) using the R programme. Analysis shows interrelationship between the water quality parameters and phytoplankton diversity is same in linear principal component analysis (PCA) and neural network model. Variations of different parameters depend on seasonal changes. The ANN model shows that ammonia and phosphate are key parameters that influence the SWDI of phytoplankton. Seasonal variation in SWDI is related to variation in water quality parameters, as explained by both ANN and PCA. Hence, the ANN model can be an important tool for coastal environmental interaction study.

Pre-to-post COVID-19 lockdown and their environmental impacts on Ghoghla beach and Somnath beach, India.

Environmental impact of COVID-19 imposed lockdown (2020) and the new normal condition (2021) on two different beaches of India (Ghoghla beach, Diu and Somnath beach, Veraval) were compared with the pre-lockdown era, 2013. The lockdown phase favored the natural restoration of the beaches and showed infinitesimal values of the parameters tested when compared with the pre-lockdown regime. However, the new normal situation in 2021 opened up the accessibility of these beaches to the tourists and pilgrims resulting in significant changes of water quality. The release of diluted sewage mixed with freshwater from the Somnath town to the sea has led to the drastic change in beach water quality. The mean cadmium concentration increased drastically in beach waters (Ghoghla: 1.35, 0.28 and 7.09 µg/L; Somnath: 0.45, 0.28 and 0.58 µg/L) during pre-to-post lockdown, respectively. However, post-lockdown resulted in the rise of toxic heavy metals in the sediments of Somnath beach but Ghoghla beach remained to be pristine which may be due to the Blue Flagship status. The total number of marine bacteria was higher during 2013 and 2021 when compared during lockdown describing greater human interventions. For instance, Vibrio spp. count in Ghoghla beach water during pre-lockdown phase was 7733 CFU/mL and this value reduced to 70 and 5 CFU/mL in the lockdown and post-lockdown phases. Interestingly, the diversity of planktonic and benthic components showed a different trend from pre-to-post lockdown due to significant change in the inorganic nutrients and metal bioaccumulation. To our knowledge, this will be the first comprehensive assessment to report the environmental and ecological health of Ghoghla beach and Somnath beach during the pre-to-post lockdown.

Impact of 2nd wave of COVID-19-related lockdown on coastal water quality at Diu, western coast of India and role of total alkalinity on bacterial loads.

A detailed coastal water monitoring near Diu coast, western part of India was performed from October, 2020 to May, 2021 covering the 2nd lockdown time. Average monthly fluctuation from 7 different sampling stations of total 9 physico-chemical parameters such as pH, salinity, turbidity, nitrite (NO2), nitrate (NO3), ammonia (NH3), phosphate (PO4), total alkalinity and silicate were recorded. Initially, Mann-Kendall trend test for all the 9 parameters showed non-zero trend, which may be either linear or non-linear. During 2nd lockdown period, there was a fluctuation of value for parameters like pH, salinity, nitrate, nitrite and phosphate. Average total bacterial count and differential bacterial count also gradually decreased from March, 2021 sampling. Principal component analysis (PCA) plot covering all the physico-chemical parameters as well as the differential bacterial count showed a distinct cluster of all bacterial count with total alkalinity value. Subsequently, mathematical equation was formulated between total alkalinity value and all differential bacterial count. Upto our knowledge, this is the first report where mathematical equation was formulated to obtain value of different bacterial load based on the derived total alkalinity value of the coastal water samples near Diu, India.