Examination of discrete and counfounding effects of water quality parameters during the inactivation of MS2 phages andBacillus subtilispores with free chlorine

2004 ◽  
Vol 3 (4) ◽  
pp. 255-268 ◽  
Author(s):  
Benoit Barbeau ◽  
Debra Huffman ◽  
Chandra Mysore ◽  
Raymond Desjardins ◽  
Michele Prévost
Keyword(s):  
Water Quality ◽  
Quality Parameters ◽  
Free Chlorine ◽  
Water Quality Parameters

scholarly journals Water Quality as a Predictor of Legionella Positivity of Building Water Systems

Pathogens ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 295 ◽  
Author(s):  
David Pierre ◽  
Julianne L. Baron ◽  
Xiao Ma ◽  
Frank P. Sidari ◽  
Marilyn M. Wagener ◽  
...  
Keyword(s):  
Water Quality ◽  
Cold Water ◽  
Water Systems ◽  
Quality Parameters ◽  
Free Chlorine ◽  
Hot Water ◽  
Water Quality Parameters ◽  
Plate Count ◽  
Poor Correlation ◽  
Distal Site

Testing drinking water systems for the presence of Legionella colonization is a proactive approach to assess and reduce the risk of Legionnaires’ disease. Previous studies suggest that there may be a link between Legionella positivity in the hot water return line or certain water quality parameters (temperature, free chlorine residual, etc.) with distal site Legionella positivity. It has been suggested that these measurements could be used as a surrogate for testing for Legionella in building water systems. We evaluated the relationship between hot water return line Legionella positivity and other water quality parameters and Legionella colonization in premise plumbing systems by testing 269 samples from domestic cold and hot water samples in 28 buildings. The hot water return line Legionella positivity and distal site positivity only demonstrated a 77.8% concordance rate. Hot water return line Legionella positivity compared to distal site positivity had a sensitivity of 55% and a specificity of 96%. There was poor correlation and a low positive predictive value between the hot water return line and distal outlet positivity. There was no correlation between Legionella distal site positivity and total bacteria (heterotrophic plate count), pH, free chlorine, calcium, magnesium, zinc, manganese, copper, temperature, total organic carbon, or incoming cold-water chlorine concentration. These findings suggest that hot water return line Legionella positivity and other water quality parameters are not predictive of distal site positivity and should not be used alone to determine the building’s Legionella colonization rate and effectiveness of water management programs.

Framework for cost-effective prediction of unregulated disinfection by-products in drinking water distribution using differential free chlorine

2018 ◽  
Vol 4 (10) ◽  
pp. 1564-1576 ◽  
Author(s):  
Gyan Chhipi-Shrestha ◽  
Manuel Rodriguez ◽  
Rehan Sadiq
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Water Distribution ◽  
Cost Effective ◽  
Quality Parameters ◽  
Free Chlorine ◽  
Water Quality Parameters ◽  
Drinking Water Distribution ◽  
By Products

A framework for estimating the concentration of unregulated disinfection by-products in water distribution using ΔCl2 and other basic water quality parameters.

Investigation of Some Water Quality Parameters of Pond Water under Mymensingh Municipality

2015 ◽  
Vol 8 (1) ◽  
pp. 85-89
Author(s):  
F Zannat ◽  
MA Ali ◽  
MA Sattar
Keyword(s):  
Water Quality ◽  
Water Samples ◽  
Chemical Properties ◽  
Pond Water ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Urban Region ◽  
Mn Toxicity ◽  
Ph Values ◽  
Drinking Water Standard

A study was conducted to evaluate the water quality parameters of pond water at Mymensingh Urban region. The water samples were collected from 30 ponds located at Mymensingh Urban Region during August to October 2010. The chemical analyses of water samples included pH, EC, Na, K, Ca, S, Mn and As were done by standard methods. The chemical properties in pond water were found pH 6.68 to 7.14, EC 227 to 700 ?Scm-1, Na 15.57 to 36.00 ppm, K 3.83 to 16.16 ppm, Ca 2.01 to 7.29 ppm, S 1.61 to 4.67 ppm, Mn 0.33 to 0.684 ppm and As 0.0011 to 0.0059 ppm. The pH values of water samples revealed that water samples were acidic to slightly alkaline in nature. The EC value revealed that water samples were medium salinity except one sample and also good for irrigation. According to drinking water standard Mn toxicity was detected in pond water. Considering Na, Ca and S ions pond water was safe for irrigation and aquaculture. In case of K ion, all the samples were suitable for irrigation but unsuitable for aquaculture.J. Environ. Sci. & Natural Resources, 8(1): 85-89 2015

Assessement of Water Quality Parameters in Some Potential Pollutant Areas from Romania

2018 ◽  
Vol 69 (8) ◽  
pp. 2045-2049
Author(s):  
Catalina Gabriela Gheorghe ◽  
Andreea Bondarev ◽  
Ion Onutu
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Chemical Parameters ◽  
Water Quality Data ◽  
Pollutant Sources ◽  
Water Quality Forecasting

Monitoring of environmental factors allows the achievement of some important objectives regarding water quality, forecasting, warning and intervention. The aim of this paper is to investigate water quality parameters in some potential pollutant sources from northern, southern and east-southern areas of Romania. Surface water quality data for some selected chemical parameters were collected and analyzed at different points from March to May 2017.

Influence of Discharges from Storage Reservoirs on the Tastes and Odours Appearing in the Seine and Marne Rivers

1982 ◽  
Vol 14 (4-5) ◽  
pp. 43-58 ◽  
Author(s):  
M Rizet ◽  
J Mouchet
Keyword(s):  
Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Severe Drought ◽  
Storage Reservoirs ◽  
Metabolite Concentrations

This study was conducted in order to understand the taste and odour problems that occurred in the Seine and the Marne rivers during the severe drought of 1976. Samples were taken every 15 days from several locations in the rivers themselves and from storage reservoirs upstream from Paris. Algae and actinomycetes were identified and counted. Metabolite concentrations were measured. These data were correlated with threshold odor numbers and bacteriological water quality parameters.

scholarly journals Spatio-Temporal Analysis of Water Quality Parameters in Machángara River with Nonuniform Interpolation Methods

Water ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 507 ◽  
Author(s):  
Iván Vizcaíno ◽  
Enrique Carrera ◽  
Margarita Sanromán-Junquera ◽  
Sergio Muñoz-Romero ◽  
José Luis Rojo-Álvarez ◽  
...  
Keyword(s):  
Water Quality ◽  
Temporal Analysis ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Interpolation Methods ◽  
Spatio Temporal

scholarly journals Effect of Maritime Traffic on Water Quality Parameters in Santa Marta, Colombia

2021 ◽  
Vol 9 (5) ◽  
pp. 474
Author(s):  
René Rodríguez-Grimón ◽  
Nestor Hernando Campos ◽  
Ítalo Braga Castro
Keyword(s):  
Water Quality ◽  
Petroleum Hydrocarbons ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Maritime Traffic ◽  
Natural Park ◽  
High Concentrations ◽  
The Impact ◽  
The Relationship ◽  
Multiple Chemical

Since 2013, there has been an increase (>23%) in naval traffic using maritime routes and ports on the coastal fringe of Santa Marta, Colombia. Of major concern, and described by several studies, is the relationship between maritime traffic and coastal contamination. This study proposed a maritime traffic indicator considering the simultaneous effects of several relevant measurements of water quality parameters to estimate the impact of naval activity. The approach involved developing a model including the number of vessels, hull length, and permanence time in berths. In addition, water quality variables, considering climatic seasons, were used to verify association with maritime traffic and touristic activities. The high concentrations of total coliforms (TC) and dissolved/dispersed petroleum hydrocarbons in chrysene equivalents (DDPH) reported by the International Marina of Santa Marta (SM) were affected by the local anthropic activities, including tourism, naval traffic, and urban wastewater discharges. Moreover, our results suggest the occurrence of multiple chemical impacts within Tayrona National Natural Park (PNNT) affecting conservation goals. The estimation of the maritime traffic indicator proposed in this study may be an easy and more complete tool for future studies evaluating the impact of naval activities on environmental quality.

scholarly journals Comparison of Forecasting Models for Real-Time Monitoring of Water Quality Parameters Based on Hybrid Deep Learning Neural Networks

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1547
Author(s):  
Jian Sha ◽  
Xue Li ◽  
Man Zhang ◽  
Zhong-Liang Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Deep Learning ◽  
Real Time ◽  
Best Management Practices ◽  
Input Data ◽  
Management Practices ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Real Time Monitoring

Accurate real-time water quality prediction is of great significance for local environmental managers to deal with upcoming events and emergencies to develop best management practices. In this study, the performances in real-time water quality forecasting based on different deep learning (DL) models with different input data pre-processing methods were compared. There were three popular DL models concerned, including the convolutional neural network (CNN), long short-term memory neural network (LSTM), and hybrid CNN–LSTM. Two types of input data were applied, including the original one-dimensional time series and the two-dimensional grey image based on the complete ensemble empirical mode decomposition algorithm with adaptive noise (CEEMDAN) decomposition. Each type of input data was used in each DL model to forecast the real-time monitoring water quality parameters of dissolved oxygen (DO) and total nitrogen (TN). The results showed that (1) the performances of CNN–LSTM were superior to the standalone model CNN and LSTM; (2) the models used CEEMDAN-based input data performed much better than the models used the original input data, while the improvements for non-periodic parameter TN were much greater than that for periodic parameter DO; and (3) the model accuracies gradually decreased with the increase of prediction steps, while the original input data decayed faster than the CEEMDAN-based input data and the non-periodic parameter TN decayed faster than the periodic parameter DO. Overall, the input data preprocessed by the CEEMDAN method could effectively improve the forecasting performances of deep learning models, and this improvement was especially significant for non-periodic parameters of TN.

Sign in / Sign up

Export Citation Format

Share Document