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Dataset on assessment of River Yamuna, Delhi, India using indexing approach.

ABSTRACT: The objective of the present study is to investigate the status of pollution load in River Yamuna, Delhi. The 13 sites for sampling, spread through the Delhi stretch of Yamuna, starting from the Wazirabad barrage till the Okhla barrage has been selected. Physicochemical parameters such as pH, temperature, DO (Dissolved oxygen), TDS (Total dissolved solids), salinity and conductivity were determined. The concentration of heavy metals (Cd, Ni, Zn, Fe, Cu, Pb, and Cr,) were assessed and found to be (0.03, 0.025, 1.365, 6.175, 0.08, 0.02, and 0.03) respectively. Varying concentration of heavy metals was found due to the widespread discharge of industrial effluents into the river. The overall mean concentration of heavy metals was observed in the following order Fe > Zn > Cu > Ni > Cr > Pb > Cd. It can be concluded that our study area as a whole is critically polluted in terms of mean Fe concentration (6.175?mg/L) due to pollutant load from various anthropogenic activities and need treatment before further use. This dataset is beneficial for policymakers, and researchers in the field of River Yamuna water quality management.

SUBMITTER: Yadav A

PROVIDER: S-EPMC6293046 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Dataset on assessment of River Yamuna, Delhi, India using indexing approach.

Yadav Anshu A Khandegar Vinita V

Data in brief 20181129

The objective of the present study is to investigate the status of pollution load in River Yamuna, Delhi. The 13 sites for sampling, spread through the Delhi stretch of Yamuna, starting from the Wazirabad barrage till the Okhla barrage has been selected. Physicochemical parameters such as pH, temperature, DO (Dissolved oxygen), TDS (Total dissolved solids), salinity and conductivity were determined. The concentration of heavy metals (Cd, Ni, Zn, Fe, Cu, Pb, and Cr,) were assessed and found to be ...[more]

PMID: 30581899

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Project description:BackgroundIn India and global mental health, a key component of the care gap for people with mental health problems is poor system engagement with the contexts and priorities of community members. This study aimed to explore the nature of community mental health systems by conducting a participatory community assessment of the assets and needs for mental health in Uttarkashi, a remote district in North India.MethodsThe data collection and analysis process were emergent, iterative, dialogic and participatory. Transcripts of 28 in-depth interviews (IDIs) with key informants such as traditional healers, people with lived experience and doctors at the government health centres (CHCs), as well as 10 participatory rural appraisal (PRA) meetings with 120 people in community and public health systems, were thematically analysed. The 753 codes were grouped into 93 categories and ultimately nine themes and three meta-themes (place, people, practices), paying attention to equity.ResultsYamuna valley was described as both 'blessed' and limited by geography, with bountiful natural resources enhancing mental health, yet remoteness limiting access to care. The people described strong norms of social support, yet hierarchical with entrenched exclusions related to caste and gender, and social conformity that limited social accountability of services. Care practices were porous, pluralist and fragmented, with operational primary care services that acknowledged traditional care providers, and trusted resources for mental health such as traditional healers (malis) and government health workers (accredited social health activists. ASHAs). Yet care was often absent or limited by being experienced as disrespectful or of low quality.ConclusionFindings support the value of participatory methods, and policy actions that address power relations as well as social determinants within community and public health systems. To improve mental health in this remote setting and other South Asian rural locations, community and public health systems must dialogue with the local context, assets and priorities and be socially accountable.

Project description:Globally, urban water bodies have emerged as an environmental reservoir of antimicrobial resistance (AMR) genes because resistant bacteria residing here might easily disseminate these traits to other waterborne pathogens. In the present study, we have investigated the AMR phenotypes, prevalent plasmid-mediated AMR genes, and integrons in commensal strains of Escherichia coli, the predominant fecal indicator bacteria isolated from a major urban river of northern India Yamuna. The genetic environment of bla CTX-M-15 was also investigated. Our results indicated that 57.5% of the E. coli strains were resistant to at least two antibiotic classes and 20% strains were multidrug resistant, i.e., resistant to three or more antibiotic classes. The multiple antibiotic resistance index of about one-third of the E. coli strains was quite high (>0.2), reflecting high contamination of river Yamuna with antibiotics. With regard to plasmid-mediated AMR genes, bla TEM-1 was present in 95% of the strains, followed by qnrS1 and armA (17% each), bla CTX-M-15 (15%), strA-strB (12%), and tetA (7%). Contrary to the earlier reports where bla CTX-M-15 was mostly associated with pathogenic phylogroup B2, our study revealed that the CTX-M-15 type extended-spectrum ?-lactamases (ESBLs) were present in the commensal phylogroups A and B1, also. The genetic organization of bla CTX-M-15 was similar to that reported for E. coli, isolated from other parts of the world; and ISEcp1 was present upstream of bla CTX-M-15. The integrons of classes 2 and 3 were absent, but class 1 integron gene intI1 was present in 75% of the isolates, denoting its high prevalence in E. coli of river Yamuna. These evidences indicate that due to high prevalence of plasmid-mediated AMR genes and intI1, commensal E. coli can become vehicles for widespread dissemination of AMR in the environment. Thus, regular surveillance and management of urban rivers is necessary to curtail the spread of AMR and associated health risks.

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Dataset on assessment of River Yamuna, Delhi, India using indexing approach.

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Dataset on assessment of River Yamuna, Delhi, India using indexing approach.

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