scholarly journals MAGNITUDE OF INORGANIC ARSENIC CONTAMINATION INGROUNDWATERS OF MIDDLE GANGETIC BASIN OF UTTAR PRADESH AND BIHAR, INDIA

2016 ◽  
Author(s):  
Manoj Kumar ◽  
◽  
A.L. Ramanathan
2020 ◽  
Vol 32 (3) ◽  
pp. 550-554 ◽  
Author(s):  
Suresh Kumar Patel ◽  
Dhananjay Singh ◽  
Rahul Dev

Arsenic is a ubiquitous and short-term poisoning element, which affects living things. In this study, the removal of arsenic from Gomti river water, Lucknow, Uttar Pradesh integrated modified double slope solar still with activated adsorption bed has been applied. Arsenic contamination in Gomti river at five places were found in the river water in the range of 55.70 ppb to 681.60 ppb, which exceed the maximum permissible limit of 10 ppb as recommended by WHO. Maximum concentration of arsenic in water was found in Mohan Maekins (681.60 ppb). However, mean arsenic concentration in water followed the order: Gaughat (115.37 ppb) < Hanuman setu (297.80 ppb) < Barrage (302.62 ppb) <Kukrail (336.27 ppb) < Mohan Maekins (481.89 ppb). The amount of adsorbed arsenic was increased with increasing initial concentration of arsenic. The aim of this study is to develop a low-cost process for the removal of arsenic effectively including the production of potable water. After results, data were analyzed with ICP-MS method and also verified with Langmuir and Freundlich adsorption isotherm models.


2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Surjeet Singh ◽  
Pinki Sharma ◽  
Raju Mudhulkar ◽  
Biswajit Chakravorty ◽  
Ankit Singh ◽  
...  

2014 ◽  
Vol 7 (1) ◽  
pp. 101-112
Author(s):  
Amit Mehrotra ◽  
A. Mishra ◽  
R. M. Tripathi ◽  
Naveen Shukla

2015 ◽  
Vol 58 (12) ◽  
pp. 1898-1905 ◽  
Author(s):  
Xiaowei Li ◽  
Ke Xie ◽  
Bing Yue ◽  
Yunyun Gong ◽  
Yi Shao ◽  
...  

Author(s):  
Soumika Roy ◽  
Soma Samaddar

Looking at the global scenario, it has been found that a huge perccntage of population around the globe consider groundwater as their main source for drinking. But unfortunately, this main source is being heavily exposed to various heavy metals like mercury, cadmium, arsenic making it unfit for consumption, ultimately posing threat to human health out there. Although groundwater is considered as safe, but high concentrations of heavy metals like arsenic (As) (above the permissible limit) in ground water can pose risk to human health. Toxicity level of inorganic arsenic is more than the organic one. Arsenic contamination is having a worldwide effect. Arsenic is found to be carcinogcnic in nature, genotoxic as well as cytotoxic. Prolonged exposure to arsenic causes various health hazards like arsenicosis, skin cancer, pigmentation, neurobehavioral effects, impaired intellect and various other chronic illness. Creating awareness and providing proper medical care still remains a big challenge. The biomarkers of arsenic exposure include nails, hair, urine and blood sample. This paper provides an overall overview of ground water arsenic contamination, its health hazards, its toxicity and metabolism in human body. The paper also reviews various analytical techniques that are being used to detect arsenic, the collective steps required to eradicate this global problem and provide high quality safe drinking water for the future generations to come.


Planta Medica ◽  
2012 ◽  
Vol 78 (11) ◽  
Author(s):  
C Ubonnuch ◽  
S Ruangwises ◽  
N Ruangwises ◽  
W Gritsanapan
Keyword(s):  

2018 ◽  
Vol 15 (3) ◽  
pp. 389-398
Author(s):  
Ruchi Singh

Rural economies in developing countries are often characterized by credit constraints. Although few attempts have been made to understand the trends and patterns of male out-migration from Uttar Pradesh (UP), there is dearth of literature on the linkage between credit accessibility and male migration in rural Uttar Pradesh. The present study tries to fill this gap. The objective of this study is to assess the role of credit accessibility in determining rural male migration. A primary survey of 370 households was conducted in six villages of Jaunpur district in Uttar Pradesh. Simple statistical tools and a binary logistic regression model were used for analyzing the data. The result of the empirical analysis shows that various sources of credit and accessibility to them play a very important role in male migration in rural Uttar Pradesh. The study also found that the relationship between credit constraints and migration varies across various social groups in UP.


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