Impacts of a flash flood on drinking water quality: case study of areas most affected by the 2012 Beijing flood

Sun, Rubao; An, Daizhi; Lü, Wei; Shi, Yun; Wang, Lili; Zhang, Can; Zhang, Ping; Qi, Hongjuan; Wang, Qiang

doi:10.1016/j.heliyon.2016.e00071

Cited by 22 publications

(14 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The factor score of each VF multiplied by its variance contribution rate extracts a common factor, which can then be weighted to obtain composite scores for each sampling site. For any sampling site, the larger the factor score, the more serious the pollution at that point [31]. It is seen from the scores that the pollution levels at the sampling points varied (Table S1).…”

Section: Resultsmentioning

confidence: 99%

Investigation and Source Apportionment of Air Pollutants in a Large Oceangoing Ship during Voyage

Wang

Sun

et al. 2019

IJERPH

Self Cite

View full text Add to dashboard Cite

The aims of this study were to determine compartmental air pollution during navigation of a large oceangoing ship and to identify preliminarily the major pollution sources. During the voyage of a bulk carrier ship, air samples were collected at 18 selected sites using a stratified sampling method. The concentrations of 15 pollutants were determined using gas chromatography. Results showed the concentrations of these pollutants varied significantly among the sampling sites, indicating major pollution sources at or nearby those locations. Five common factors extracted using factor analysis explained 89.092% of the total variance. Multivariate linear regression analysis showed the contributions to air pollution of these five common factors, i.e., the volatilization of ship paint, volatilization of ship-based oil, cooking activities, high-temperature release of rubber components on the ship and daily use of chemical products, and the application of deodorant and insecticide, were 41.07%, 25.14%, 14.37%, 11.78%, and 7.63%, respectively. Three significant groups were determined using cluster analysis based on their similarity, i.e., high, medium, and low pollution of sampling sites. This study established that the air of the bulk carrier ship was heavily polluted, and that effective identification of pollution sources could provide a scientific basis for its control.

show abstract

Section: Resultsmentioning

confidence: 99%

Investigation and Source Apportionment of Air Pollutants in a Large Oceangoing Ship during Voyage

Wang

Sun

et al. 2019

IJERPH

Self Cite

View full text Add to dashboard Cite

show abstract

“…During the 2012 Beijing flooding, Sun et al [34] found the impact of flash flooding in drinking water quality. Nine water samples were collected and analyzed for eight parameters, namely turbidity, total hardness, total dissolved solids, sulfates, chlorides, nitrates, total bacterial count, and total coliform groups.…”

Section: Discussionmentioning

confidence: 99%

Microbiological Assessment of Tap Water Following the 2016 Louisiana Flooding

Phan

Sherchan

2020

IJERPH

View full text Add to dashboard Cite

Floods are a prominent risk factor in the world of public health, as there is a risk of dispersal of harmful biological and chemical contaminants in floodwater. As climate change increases, the occurrence of natural disasters and risk of adverse health outcomes due to flash flooding also increases. Fecal indicator bacteria, such as Escherichia coli and Enterococci, are often encountered in contaminated floodwater and can cause gastrointestinal illnesses as well as a variety of infections. In August 2016, East Baton Rouge and surrounding parishes in Louisiana suffered heavy floods due to intense rainfall. No study of water quality during flooding has been conducted previously in Baton Rouge, Louisiana. Twenty-three pre-flush and post-flush water samples were collected immediately from accessible homes that had been affected by the floods in order to quantify concentrations of fecal indicator bacteria. These samples were analyzed for the presence of E. coli and Enterococci through both quantitative polymerase chain reaction (qPCR) and the IDEXX enzyme substrate method. The qPCR results indicated that 30% of the samples contained Enterococci and 61% of the samples contained E. coli, with the highest concentrations found in the pre-flush outdoor hose and the pre-flush kitchen tap. The IDEXX method yielded total coliforms in 65% of the samples, E. coli in 4%, and Enterococci in 35%, with the highest concentrations in the pre-flush outdoor faucet and the pre-flush post-filtration kitchen tap. Physical parameters including temperature, barometer pressure, dissolved oxygen, oxidation reduction potential, pH, conductivity, and salinity of these samples were also recorded. Of these parameters, conductivity and salinity were significant, suggesting they may positively influence E. coli and Enterococci growth.

show abstract

“…Due to human influence, the expert opinion method can be subjective and uncertain. In an attempt to reduce the subjectivity in parameter selection, statistical tools have been developed and widely adopted as common practice [15,20,[34][35][36]. Hypothetically, this might be the most objective method, but still, the human influence is evident on the choice of data that is statistically analyzed, hence compromising the accuracy of the procedure [5].…”

Section: Selection Of Water Quality Parametersmentioning

confidence: 99%

“…Hypothetically, this might be the most objective method, but still, the human influence is evident on the choice of data that is statistically analyzed, hence compromising the accuracy of the procedure [5]. Nevertheless, through the use of pattern recognition; statistical methods remain the most powerful technique for interpreting the variance between a large number of variables and convert them into smaller groups of independent variables [34,36].…”

Section: Selection Of Water Quality Parametersmentioning

confidence: 99%

Development of Water Quality Indices (WQIs): A Review

Banda¹,

Kumarasamy²

2020

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

Water quality indices (WQIs) are necessary for simplifying the reporting of complex and technical water quality information. They are scientifically based communication models that are capable of converting multi-variable water quality data to produce a single unit less digit score that describes overall water quality. This in turn is important for providing a structured platform to evaluate and compare water quality of various water resources [1, 2]. Water quality indices are not aimed at replacing detailed water quality analysis, rather they are tools aimed at providing a quick guide to assist water quality experts, policymakers and the public by communicating water quality data in a more consistent and ongoing manner [2, 3]. Following the studies by Poonam, et al. [2], Lumb et al. [4], Sutadian et al. [5], and Paun et al. [6], it has been noted that most WQIs are designed for a particular region and are source-specific, thus creating a gap and ample scope to develop a universally acceptable WQI. However, it is extremely difficult to develop a water quality model that is globally acceptable, hence

show abstract

Impacts of a flash flood on drinking water quality: case study of areas most affected by the 2012 Beijing flood

Cited by 22 publications

References 22 publications

Investigation and Source Apportionment of Air Pollutants in a Large Oceangoing Ship during Voyage

Investigation and Source Apportionment of Air Pollutants in a Large Oceangoing Ship during Voyage

Microbiological Assessment of Tap Water Following the 2016 Louisiana Flooding

Development of Water Quality Indices (WQIs): A Review

Contact Info

Product

Resources

About