scholarly journals Development of an Environmental Decision Support System for Enhanced Coagulation in Drinking Water Production

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2115 ◽  
Author(s):  
Jordi Suquet ◽  
Lluís Godo-Pla ◽  
Meritxell Valentí ◽  
Marta Verdaguer ◽  
Maria J. Martin ◽  
...  
Keyword(s):  
Drinking Water ◽  
Decision Support ◽  
Water Treatment ◽  
Decision Support System ◽  
Support System ◽  
Control Level ◽  
Drinking Water Treatment ◽  
Water Production ◽  
Drinking Water Production ◽  
Environmental Decision

Drinking water production is subject to multiple water quality requirements such as minimizing disinfection byproducts (DBPs) formation, which are highly related to natural organic matter (NOM) content. For water treatment, coagulation is a key process for removing water pollutants and, as such, is widely implemented in drinking water treatment plants (DWTPs) facilities worldwide. In this context, artificial intelligence (AI) tools can be used to aid decision making. This study presents an environmental decision support system (EDSS) for coagulation in a Mediterranean DWTP. The EDSS is structured hierarchically into the following three levels: data acquisition, control, and supervision. The EDSS relies on influent water characterization, suggesting an optimal pH and coagulant dose. The model designed for the control level is based on response surface methodology (RSM), targeted to optimize removal for the response variables (turbidity, total organic carbon (TOC), and UV254). Results from the RSM model provided removal percentages for turbidity (64.6%), TOC (21.9%), and UV254 (30%), which represented an increase of 4%, 33%, and 28% as compared with the DWTP water sample. Regarding the entire EDSS, 62%, 21%, and 25% of turbidity, TOC, and UV254 removal were fixed as the optimization criteria. Supervision rules (SRs) were included at the top of the architecture to intensify process performance under specific circumstances.

scholarly journals Implementation of an environmental decision support system for controlling the pre-oxidation step at a full-scale drinking water treatment plant

2020 ◽  
Vol 81 (8) ◽  
pp. 1778-1785 ◽  
Author(s):  
Lluís Godo-Pla ◽  
Pere Emiliano ◽  
Santiago González ◽  
Manel Poch ◽  
Fernando Valero ◽  
...  
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Decision Support ◽  
Water Treatment ◽  
Decision Support System ◽  
Predictive Model ◽  
Support System ◽  
Drinking Water Treatment ◽  
Oxidation Step ◽  
Environmental Decision

Abstract Drinking water treatment plants (DWTPs) face changes in raw water quality, and treatment needs to be adjusted to produce the best water quality at the minimum environmental cost. An environmental decision support system (EDSS) was developed for aiding DWTP operators in choosing the adequate permanganate dosing rate in the pre-oxidation step. To this end, multiple linear regression (MLR) and multi-layer perceptron (MLP) models are compared for choosing the best predictive model. Besides, a case-based reasoning (CBR) model was approached to provide the user with a distribution of solutions given similar operating conditions in the past. The predictive model consisted of an MLP and has been validated against historical data with sufficient good accuracy for the utility needs (R2 = 0.76 and RSE = 0.13 mg·L−1). The integration of the predictive and the CBR models in an EDSS gives the user an augmented decision-making capacity of the process and has great potential for both assisting experienced users and for training new personnel in deciding the operational set-point of the process.

Enhanced particle removal in drinking water treatment plants – case studies

2000 ◽  
Vol 41 (7) ◽  
pp. 135-142
Author(s):  
P. Lipp ◽  
G. Baldauf
Keyword(s):  
Drinking Water ◽  
Water Treatment ◽  
Case Studies ◽  
Surface Waters ◽  
Drinking Water Treatment ◽  
Particle Removal ◽  
Water Production ◽  
Water Treatment Plants ◽  
Drinking Water Production

Measurements of parasites in surface waters in Germany showed that their presence is widely spread. Concentrations may reach values up to a maximum of 50 cysts per 100 l. Normally raw waters used for drinking water production show much lower values. In order to ensure sufficient parasite removal in drinking water treatment plants an enhancement of particle removal is required. For filtration processes parameters influencing particle removal are filter media, filtration velocity, flocculant dosage, preozonationand filter back wash. Moderate filtration conditions show best results. Three case studies show that preozonation, optimized energy input and use of flocculants improve particle removal. One case study shows results of the first ultrafiltration plant in Germany treating reservoir and spring water for drinking water production.

scholarly journals Metagenomic profiling of ammonia- and methane-oxidizing microorganisms in a Dutch drinking water treatment plant

2020 ◽  
Author(s):  
Lianna Poghosyan ◽  
Hanna Koch ◽  
Jeroen Frank ◽  
Maartje A.H.J. van Kessel ◽  
Geert Cremers ◽  
...  
Keyword(s):  
Drinking Water ◽  
Water Treatment ◽  
Microbial Communities ◽  
Treatment Plant ◽  
Drinking Water Treatment ◽  
Water Treatment Plant ◽  
Water Production ◽  
Sand Filter ◽  
Clade B ◽  
Drinking Water Production

AbstractElevated concentrations of ammonium and methane in groundwater can cause severe problems during drinking water production. To avoid their accumulation, raw water in the Netherlands, and many other countries, is purified by sand filtration. These drinking water filtration systems select for microbial communities that mediate the biodegradation of organic and inorganic compounds. In this study, the active layers and wall biofilm of a Dutch drinking water treatment plant (DWTP) were sampled at different locations along the filtration units of the plant over three years. We used high-throughput sequencing in combination with differential coverage and sequence composition-based binning to recover 56 near-complete metagenome-assembled genomes (MAGs) with an estimated completion of ≥70% and with ≤10% redundancy. These MAGs were used to characterize the microbial communities involved in the conversion of ammonia and methane. The methanotrophic microbial communities colonizing the wall biofilm (WB) and the granular material of the primary rapid sand filter (P-RSF) were dominated by members of the Methylococcaceae and Methylophilaceae. The abundance of these bacteria drastically decreased in the secondary rapid sand filter (S-RSF) samples. In all samples, complete ammonia-oxidizing (comammox) Nitrospira were the most abundant nitrifying guild. Clade A comammox Nitrospira dominated the P-RSF, while clade B was most abundant in WB and S-RSF, where ammonium concentrations were much lower. In conclusion, the knowledge obtained in this study contributes to understanding the role of microorganisms in the removal of carbon and nitrogen compounds during drinking water production. We furthermore found that drinking water treatment plants represent valuable model systems to study microbial community function and interaction.HighlightsMicrobial distribution was mainly influenced by sampling location within the DWTPClade A comammox Nitrospira were the dominant nitrifiers in the primary sand filterClade B was most abundant in samples from wall biofilm and the secondary filterA novel Methylophilaceae-affiliated methanotroph dominated the primary sand filter

Dissolved air flotation in drinking water production

2001 ◽  
Vol 43 (8) ◽  
pp. 9-18 ◽  
Author(s):  
T. Schofield
Keyword(s):  
Drinking Water ◽  
Water Treatment ◽  
Potable Water ◽  
Water Production ◽  
Process Technology ◽  
Dissolved Air Flotation ◽  
Drinking Water Production ◽  
Air Flotation ◽  
Potable Water Treatment ◽  
Dissolved Air

Dissolved Air Flotation (DAF) has become increasingly important in the field of potable water treatment, as a preferred option for treating upland and stored lowland waters. This paper outlines the development of dissolved air flotation (DAF) in potable water treatment, the benefits and disadvantages and the recent advances that has taken the process technology from an art to a science.

Performance management of small water treatment plant operations: a decision support system

2017 ◽  
Vol 31 (3) ◽  
pp. 330-344 ◽  
Author(s):  
Dan Stein ◽  
Gopal Achari ◽  
Cooper H. Langford ◽  
Mohammed H. I. Dore ◽  
Husnain Haider ◽  
...  
Keyword(s):  
Decision Support ◽  
Water Treatment ◽  
Decision Support System ◽  
Performance Management ◽  
Support System ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Small Water ◽  
Plant Operations

scholarly journals C-Language Programming for Development of Conventional Water Treatment Plants Decision Support System

2014 ◽  
Vol 03 (04) ◽  
pp. 129-139
Author(s):  
Thogare N. Shridhara ◽  
Samson O. Ojoawo ◽  
Pilli V. Mahaganesha ◽  
Mallaura R. Thippeswary ◽  
Rahul Anand ◽  
...  
Keyword(s):  
Decision Support ◽  
Water Treatment ◽  
Decision Support System ◽  
Support System ◽  
C Language ◽  
Water Treatment Plants
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