Human exposure to uranium through drinking water and its detrimental impact on the human body organs.

Human exposure to high concentrations of uranium is a major concern due to the risk of developing numerous internal organ malignancies over time. In addition to the numerous attributes of uranium in the nuclear power industry, the radiological characteristics and chemical toxicity of uranium present a substantial risk to human health. This study aims to evaluate potential negative health impacts associated with the ingestion of uranium through drinking water in the Noida and Greater Noida region within the Gautam Buddha districts of Uttar Pradesh (India), due to extreme industrial revolution in this geological location. The mean concentration of uranium in drinking water of the examined area was estimated to range from 0.23 to 78.21 µg l-1. The hair compartment biokinetic model is used to estimate the retention and radiological doses of uranium in distinct organs and tissues. Studies on time-dependent factors revealed variations in uranium retention, with lower levels observed in the Gastrointestinal Tract (GIT) region and higher levels on cortical bone surfaces causes the skeletal deformities. The kidney, liver, and other soft tissues (OST) exhibited a non-saturation pattern in the retention of uranium via exposure of drinking water. The age-wise non-carcinogenic and carcinogenic doses were estimated for the health hazards studies. The outcome of this study will be useful for water resource management authorities to supply safe potable water to the local residents.

Sustainable approaches towards green synthesis of TiO2 nanomaterials and their applications in photocatalysis-mediated sensing to monitor environmental pollution.

Nanomaterials are gaining enormous interests due to their novel applications that have been explored nearly in every field of our contemporary society. In this scenario, preparations of nanomaterials following green routes have attracted widespread attention in terms of sustainable, reliable, and environmentally friendly practices to produce diverse nanostructures. In this review, we summarize the fundamental processes and mechanisms of green synthesis approaches of TiO2 nanoparticles (NPs). We explore the role of plants and microbes as natural bioresources to prepare TiO2 NPs. Particularly, focus has been made to explore the potential of TiO2 -based nanomaterials to design a variety of sensing platforms by exploiting the photocatalysis efficiency under the influence of a light source. These types of sensing are of massive importance for monitoring environmental pollution and therefore for inventing advanced strategies to remediate hazardous pollutants and offer a clean environment.

Assessment of ground and surface water quality along the river Varuna, Varanasi, India.

Multivariate statistical techniques were employed for monitoring of ground-surface water interactions in rivers. The river Varuna is situated in the Indo-Gangetic plain and is a small tributary of river Ganga. The study area was monitored at seven sampling sites for 3 years (2010-12), and eight physio-chemical parameters were taken into account for this study. The data obtained were analysed by multivariate statistical techniques so as to reveal the underlying implicit information regarding proposed interactions for the relevant area. The principal component analysis (PCA) and cluster analysis (CA), and the results of correlations were also studied for all parameters monitored at every site. Methods used in this study are essentially multivariate statistical in nature and facilitate the interpretation of data so as to extract meaningful information from the datasets. The PCA technique was able to compress the data from eight to three parameters and captured about 78.5% of the total variance by performing varimax rotation over the principal components. The varifactors, as yielded from PCA, were treated by CA which grouped them convincingly into three groups having similar characteristics and source of contamination. Moreover, the loading of variables on significant PCs showed correlations between various ground water and surface water (GW-SW) parameters. The correlation coefficients calculated for various physiochemical parameters for ground and surface water established the correlations between them. Thus, this study presents the utility of multivariate statistical techniques for evaluation of the proposed interactions and effective future monitoring of potential sites.