Dataset Information

Data on physicochemical quality of drinking water in the rural area in Divandarreh county, Kurdistan, Iran.

ABSTRACT: Good quality of drinking water is very important in the maintenance of human health. The gathered data from the present work was used to evaluate the quality of drinking water resources in the rural villages of Divandarreh, Iran. Physicochemical quality of water was determined by a collection of 35 random samples during dry and rainy seasons in 2015. The APHA approach was used to determine the physicochemical parameters of the samples. The results showed that the average concentration of Ca, Mg, Na, K, Cl, SO4, TDS and TH during dry season was 85.64?mg/l, 13.41?mg/l, 34.11?mg/l, 2.8?mg/l, 9.9?mg/l, 45.7?mg/l, 326.06?mg/l and 269.61?mg/l, respectively. Also, the average concentration of the parameters during rainy season was 77.3?mg/l, 18.27?mg/l, 30.3?mg/l, 1.9?mg/l, 12.54?mg/l, 39?mg/l, 269.1?mg/l and 316.17?mg/l, respectively.

SUBMITTER: Maleki A

PROVIDER: S-EPMC6141269 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Data on physicochemical quality of drinking water in the rural area in Divandarreh county, Kurdistan, Iran.

Maleki Afshin A Kamarehie Bahram B Rezaee Reza R Jafari Ali A Zandsalami Yahya Y Bahmani Pegah P Ghahramani Esmail E Karami Mohammad Amin MA

Data in brief 20180622

Good quality of drinking water is very important in the maintenance of human health. The gathered data from the present work was used to evaluate the quality of drinking water resources in the rural villages of Divandarreh, Iran. Physicochemical quality of water was determined by a collection of 35 random samples during dry and rainy seasons in 2015. The APHA approach was used to determine the physicochemical parameters of the samples. The results showed that the average concentration of Ca, Mg, ...[more]

PMID: 30229041

Similar Datasets

Project description:Anthropogenic activities in catchments used for drinking water production largely contaminates source waters, and this may impact the quality of the final drinking water product. These contaminants may also affect taxonomic and functional profiles of the bacterial communities in the drinking water. Here, we report an integrated insight into the microbiome and water quality of four water treatment plants (NWC, NWE, WCA and NWG) that supply portable water to communities in South Africa. A new scoring system based on combined significant changes of physicochemical parameters and microbial abundance from raw to treated water was used to evaluate the effectiveness of the treatment plants at water purification. Physicochemical parameters which include total soluble solids, turbidity, pH, nitrites and phosphorus among others, were measured in source, treated, and distributed water. There were general statistically significant (P ≤ 0.05) differences between raw and treated water, demonstrating the effectiveness of the purification process. Illumina sequencing of the 16S rRNA gene was used for taxonomic profiling of the microbial communities and this data was used to infer functional attributes of the communities. Structure and composition of the bacterial communities differed significantly (P < 0.05) among the treatment plants, only NWE and NWG showed no significant differences (P > 0.05), this correlated with the predicted functional profile of the microbial communities obtained from Phylogenetic Investigation of Communities by Reconstruction of Observed States (PICRUSt), as well as the likely pollutants of source water. Bacteroidetes, Chlorobi and Fibrobacteres significantly differed (P < 0.05) between raw and distributed water. PICRUSt inferred a number of pathways involved in the degradation of xenobiotics such as Dichlorodiphenyltrichloroethane, atrazine and polycyclic aromatic hydrocarbons. More worryingly, was the presence of pathways involved in beta-lactam resistance, potential pathogenic Escherichia coli infection, Vibrio cholerae infection, and Shigellosis. Also present in drinking and treated water were OTUs associated with a number of opportunistic pathogens.

Project description:BackgroundTrihalomethanes (THMs) are the most dominant fraction of all the byproducts formed during chlorination of water. Disinfection by product (DBP) formation in water is a function of numerous factors, including pH, temperature, residual chlorine, source water characteristics, and organic matter. No study has determined the THM level in the drinking water supply of Addis Ababa, Ethiopia.MethodsA cross-sectional design was conducted to collect water samples in the water supply distribution networks of Addis Ababa, Ethiopia. Twenty-one (21) sampling stations yielded a total of one hundred twenty (120) samples of drinking water. The sample handling and collection procedures were carried out in accordance with USEPA guidelines. A DB-5 capillary column was used to separate the THMs, which were detected using GC-ECD (gas chromatography-electron capture detector). Spectrophotometric and in situ methods were used for physicochemical parameters. Redundancy analysis (RDA) was used for data analysis of trihalomethanes and environmental variables using CANOCO 4.5.ResultsThe mean concentration of total trihalomethanes in drinking water in Addis Ababa was 76.3 μg/L. The concentration of chloroform in the drinking water supply in Addis Ababa, Ethiopia, ranged between 4.03 and 79.4 μg/L. The mean total THMs in the Legedadi and Gefersa water supply systems were 77.4 μg/L and 69.66 μg/L, respectively. The residual chlorine, phosphates, UV absorbance at 254 nm, and combined chlorine had positive correlations with THM formation. However, electron conductivity had a negative correlation with THM formation.ConclusionsChloroform contributed the most to TTHMs in nearly all samples. The residual chlorine, UV absorbance, phosphate and hardness as calcium, and electron conductivity were found to be the main predictors determining the abundance and distribution of trihalomethanes. The monitoring and regulation of the THMs is required on a regular basis to analyse trends and guide the water treatment and distribution system.

Dataset Information

Data on physicochemical quality of drinking water in the rural area in Divandarreh county, Kurdistan, Iran.

Publications

Data on physicochemical quality of drinking water in the rural area in Divandarreh county, Kurdistan, Iran.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets