A review of the prospects, efficacy and sustainability of nanotechnology-based approaches for oil spill remediation.

Numerous marine oil spill incidents and their environmental catastrophe have raised the concern of the research community and environmental agencies on the topic of the offshore crude oil spill. The oil transport through oil tankers and pipelines has further aggravated the risk of the oil spill. This has led to the necessity to develop an effective, environment-friendly, versatile oil spill clean-up strategy. The current review article analyses various nanotechnology-based methods for marine oil spill clean-up, focusing on their recovery rate, reusability and cost. The authors weighed the three primary factors recovery, reusability and cost distinctively for the analysis based on their significance in various contexts. The findings and analysis suggest that magnetic nanomaterials and nano-sorbent have been the most effective nanotechnology-based marine oil spill remediation techniques, with the magnetic paper based on ultralong hydroxyapatite nanowires standing out with a recovery rate of over 99%. The chitosan-silica hybrid nano-sorbent and multi-wall carbon nanotubes are also promising options with high recovery rates of up to 95-98% and the ability to be reused multiple times. Although the photocatalytic biodegradation approach and the nano-dispersion method do not offer benefits for recovery or reusability, they can nevertheless help lessen the negative ecological effects of marine oil spills. Therefore, careful evaluation and selection of the most appropriate method for each marine oil spill situation is crucial. The current review article provides valuable insights into the current state of nanotechnology-based marine oil spill clean-up methods and their potential applications.

Resource recovery from soiled sanitary napkin waste-a state-of-the-art review.

With ever-improving social and medical awareness about menstrual hygiene in India, the demand for sanitary napkins has increased significantly. The utilization of high-quality and environment-friendly raw materials to produce these pads is further supporting the growth of the market. However, with improving demand and usage, the need for proper disposal techniques becomes more relevant, since all of these pads get contaminated with human blood which makes them a biohazard and can cause significant damage to human health and the environment. One sanitary pad takes around 800 years to degrade naturally and the plastic and super absorbent polymers (SAPs) in sanitary pads are non-biodegradable and can take multiple decades to degrade. Waste management technologies such as pyrolysis, gasification, and resource recovery can be adopted to manage tons of sanitary waste. Currently, sanitary waste treatment mainly focuses on landfilling, incineration, and composting, where biohazard wastes are mixed with tons of solid waste. Disposable sanitary pads have a high carbon footprint of about 5.3 kg CO2 equivalent every year. Innovative solutions for sanitary pad disposal are discussed in the manuscript which includes repurposing of derived waste cellulose and plastic fraction into value-added products. Future aspects of disinfection strategies and value addition to waste cellulose recovered from napkins were systematically discussed to promote a circular economy.

Comparative risk assessment studies estimating the hazard posed by long-term consumption of PPCPs in river water.

This study assesses the risk due to Emerging Contaminants (ECs), present in Indian rivers - Ganga (650 million inhabitants), Yamuna (57 million inhabitants), and Musi (7,500,000 inhabitants), 13 ECs in total, have been used for risk assessment studies. Their concentrations (e.g., Fluconazole: 236950 µg/l, Ciprofloxacin: 31000 µg/l, Caffeine: 21.57 µg/l, etc.) were higher than the threshold concentrations for safe consumption (e.g. Fluconazole allowable level is 3.8 µg/l, and Ciprofloxacin allowable level is 0.51 µg/l). Three different pathways of emerging contaminants (ECs) transfer (oral water ingestion, oral fish ingestion, and dermal water contact) have been considered and the study is carried out in 2 ways: (i) deterministic and (ii) probabilistic approaches (using Monte Carlo iterative methods with 10000 simulations) with the aid of a software - Risk (version 7.5). The risk value, quantified by Hazard Quotient (HQ) is higher than the allowable limit of 1 for several compounds in the three rivers like Fluconazole (HQ = 18276.713), Ciprofloxacin (HQ = 278.675), Voriconazole (HQ = 14.578), Cetirizine (HQ = 1006.917), Moxifloxacin (HQ = 8.076), Caffeine (HQ = 55.150), and Ibuprofen (HQ = 9.503). Results show that Fluconazole and Caffeine pose the maximum risk in the rivers via the "oral pathway" that allows maximum transfer of the ECs present in the river (93% and 82% contribution to total risk). The risk values vary from nearly 25 times to 19000 times the United States Environmental Protection Agency (USEPA) threshold limit of 1 (e.g., Caffeine Infant Risk = 25.990 and Fluconazole Adult Risk = 18276.713). The most susceptible age group, from this study, is "Adults" (19-70 years old), who stand the chance of experiencing the adverse health hazards associated with prolonged over-exposure to the ECs present in the river waters. Musi has the maximum concentration of pollutants and requires immediate remediation measures. Further, both methods indicate that nearly 60-70% of the population in all the three study areas are at risk of developing health hazards associated with over-exposure to ECs regularly, making the areas inhabitable.

Long-term impacts of climate change on coastal and transitional eco-systems in India: an overview of its current status, future projections, solutions, and policies.

Urbanization and industrial development are increasing rapidly. These are accompanied by problems of population explosion, encroachment of agricultural, and construction lands, increased waste generation, effluent release, and escalated concentrations of several greenhouse gases (GHGs) and pollutants in the atmosphere. This has led to wide-scale adverse impacts. Visible effects are fluctuations in temperatures and precipitation, rising sea levels, unpredictable floods, storms and cyclones, and disruption to coastal and transitional ecosystems. In a country like India with a massive population of nearly 1.4 billion and around 420 million people dwelling on or near the coasts, this effect is pre-dominant. India has extensive coastlines on both sides that are subject to greater contact and high impact from the water bodies. The factors impacting climate change, its consequences, and future predictions must be analyzed immediately for implementing precautionary measures to ameliorate the detrimental effects. Several endemic species have been endangered as these changes have resulted in the loss of habitat and interfered with the food webs. Climatic impacts on transitional ecosystems also need to be considered to preserve the diversity of each. The cooperation of governmental, independent organizations and policymakers throughout the world is essential to control and mediate the impacts on health, agriculture, and other related sectors, the details of which have been elaborated in this review. The review analyses the trends in climatic variation with time and discusses a few extremities which have left permanent effects on the population primarily concerning the coastal - Indian scenario and its eco-systems.

Thermal degradation model of used surgical masks based on machine learning methodology.

Background: The COVID-19 pandemic has leveraged facial masks to be one of the most effective measures to prevent the spread of the virus, which thereby has exponentially increased the usage of facial masks that lead to medical waste mismanagements which pose a serious threat to life. Thermal degradation or pyrolysis is an effective treatment method for the used facial mask wastes and this study aims to investigate the thermal degradation of the same. Methods: Predicted the TGA experimental curves of the mask components using a Machine Learning model known as Artificial Neural Network (ANN). Significant findings: Three different parts of the mask namely- ribbon, body, and corner were separated and used for the analysis. The thermal degradation behavior is studied using Thermogravimetric Analysis (TGA) and this is crucial for determining the reactivity of the individual mask components as they are subjected to a range of temperatures. Using the curves obtained from TGA, kinetic parameters such as Activation energy (E) and Pre-exponential factor (A) were estimated using the Coats-Redfern model-fitting method. Using the determined kinetic parameters, thermodynamic quantities such as a change in Enthalpy (ΔH), Entropy (ΔS), and Gibbs-Free energy (ΔG) were also calculated. Since TGA is a costly and time-consuming process, this study attempted to predict the TGA experimental curves of the mask components using a Machine Learning model known as Artificial Neural Network (ANN). The dataset obtained at a heating rate of 10°C/min was used to train the 3 different neural networks corresponding to the mask components and it showed an excellent agreement with experimental data (R2 > 0.99). Through this study, a complex chemical process such as thermal degradation was modelled using Machine Learning based on available experimental parameters without delving into the intricacies and complexities of the process.