scholarly journals Sewage treatment efficiencies estimation for urban areas located in the River Pardo’s watershed by associating nonlinear programming and water quality modeling

2020 ◽  
Vol 56 (1) ◽  
pp. 65-75
Author(s):  
Lucas Gonçalves Rocha ◽  
Karinnie Nascimento de Almeida ◽  
José Antonio Tosta dos Reis ◽  
Antonio Sergio Ferreira Mendonça ◽  
Fernando das Graças Braga da Silva
Keyword(s):  
Water Quality ◽  
Organic Matter ◽  
Nonlinear Programming ◽  
Urban Areas ◽  
Sewage Treatment ◽  
Water Quality Modeling ◽  
Optimization Models ◽  
Organic Matter Removal ◽  
Quality Modeling ◽  
Removal Efficiencies

Estimating efficiencies required for sewage treatment plants within a river watershed, where there are usually multiple sewage discharges and water withdrawals points in watercourses, presenting different quality conditions and sewage assimilation capacities, is a complex task. In this context, combined optimization techniques and water quality modeling can be important tools to support sewage treatment efficiencies appropriation processes. In the present paper, QUAL-UFMG water quality model and Nonlinear Programming (NLP) are jointly applied to sewage treatment levels selection for the river Pardo’s (watercourse located in Espírito Santo State, Southern region, Brazil) watershed different urban areas. Four different optimization models were tested for estimating the minimum organic matter removal efficiencies. The results indicate strong dependence between the estimated minimum organic matter removal efficiencies within the watershed and equity measures incorporated in the optimization models.

scholarly journals Analysis of Research Trends Based on Text Mining in the Journal of Korean Society of Environmental Engineering

2021 ◽  
Vol 43 (2) ◽  
pp. 101-109
Author(s):  
Donghyeon Lee ◽  
Sojeong Lee ◽  
Dokyeong Lim ◽  
Jongkwan Park
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Text Mining ◽  
Sewage Treatment ◽  
Water Quality Modeling ◽  
Research Trends ◽  
Environmental Engineering ◽  
Korean Society ◽  
Term Frequency ◽  
Quality Modeling

Objectives : The purpose of this study is to analyze research trends based on text mining technology from the published papers in the Journal of Korean Society of Environmental Engineering.Methods : From 2000 to 2019, a total of 2,743 published papers were analyzed using text mining techniques. Term frequency, TF-IDF for document classification, word association analysis were applied to find the characteristics of text data.Results and Discussion : When confirming the high appearance of the word in the published paper during 2000-2019, ‘adsorption’, ‘heavy metals’, ‘activated carbon’, ‘sediment’, ‘sewage sludge’ was found in order. It implies that large number of studies in the journal were focused on the water quality field mainly. TF-IDF analysis classified the studies into five groups; 1) drinking water treatment field, 2) water quality modeling field, 3) heavy metal adsorption field, 4) biological sewage treatment field, 5) environmental catalyst field. These results by TF-IDF show that a large proportion of studies were published in the field of water quality modeling and biological sewage treatment. When we analyzed the term frequency every five years, “adsorption” and “heavy metals” were the highly-frequency occurrence words from 2000 to 2009, but in the last 5 years, new words such as “fine dust”, “cesium”, and “ecological toxicity” were appeared. It seems that the research was reflected in the recent environmental issues.Conclusions : A lot of studies has been focused on the field of water quality but in recent years, new research topics are being studied related to atmosphere, toxicity, and radiation. Applying a more sophisticated and diverse text mining technique will be of great help to improve the environmental engineering research field.

Hydrodynamic and Water Quality Modeling of Lake Eğirdir

2014 ◽  
Vol 42 (11) ◽  
pp. 1573-1582 ◽  
Author(s):  
Meltem Kaçıkoç ◽  
Mehmet Beyhan
Keyword(s):  
Water Quality ◽  
Water Quality Modeling ◽  
Quality Modeling

Water quality modeling in the watershed-based approach for waste load allocations

1998 ◽  
Vol 38 (10) ◽  
pp. 165-172 ◽  
Author(s):  
Ruochuan Gu ◽  
Mei Dong
Keyword(s):  
Water Quality ◽  
Point Source ◽  
Water Quality Modeling ◽  
Point Sources ◽  
Low Flow ◽  
Quality Analysis ◽  
Management Approach ◽  
Water Quality Control ◽  
Quality Modeling ◽  
Waste Load

The conventional method for waste load allocations (WLA) employs spatial-differentiation, considering individual point sources, and temporal-integration, using a constant flow, typically 7Q10 low flow. This paper presents a watershed-based seasonal management approach, in which non-point source as well as point sources are incorporated, seasonal design flows are used for water quality analysis, and WLA are performend in a watershed scale. The strategy for surface water quality modeling in the watershed-based approach is described. The concept of seasonal discharge management is discussed and suggested for the watershed-based approach. A case study using the method for the Des Moines River, Iowa, USA is conducted. Modeling considerations and procedure are presented. The significance of non-point source pollutant load and its impact on water quality of the river is evaluated by analyzing field data. A water quality model is selected and validated against field measurements. The model is applied to projections of future water quality situations under different watershed management and water quality control scenarios with respect to river flow and pollutant loading rate.

Electricity generation through a photo sediment microbial fuel cell using algae at the cathode

2017 ◽  
Vol 76 (12) ◽  
pp. 3269-3277 ◽  
Author(s):  
B. Neethu ◽  
M. M. Ghangrekar
Keyword(s):  
Power Generation ◽  
Organic Matter ◽  
Microbial Fuel Cells ◽  
Carbon Capture ◽  
Algal Growth ◽  
Oxygen Demand ◽  
Sediment Organic Matter ◽  
Overlying Water ◽  
Organic Matter Removal ◽  
Removal Efficiencies

Abstract Sediment microbial fuel cells (SMFCs) are bio-electrochemical devices generating electricity from redox gradients occurring across the sediment–water interface. Sediment microbial carbon-capture cell (SMCC), a modified SMFC, uses algae grown in the overlying water of sediment and is considered as a promising system for power generation along with algal cultivation. In this study, the performance of SMCC and SMFC was evaluated in terms of power generation, dissolved oxygen variations, sediment organic matter removal and algal growth. SMCC gave a maximum power density of 22.19 mW/m2, which was 3.65 times higher than the SMFC operated under similar conditions. Sediment organic matter removal efficiencies of 77.6 ± 2.1% and 61.0 ± 1.3% were obtained in SMCC and SMFC, respectively. With presence of algae at the cathode, a maximum chemical oxygen demand and total nitrogen removal efficiencies of 63.3 ± 2.3% (8th day) and 81.6 ± 1.2% (10th day), respectively, were observed. The system appears to be favorable from a resources utilization perspective as it does not depend on external aeration or membranes and utilizes algae and organic matter present in sediment for power generation. Thus, SMCC has proven its applicability for installation in an existing oxidation pond for sediment remediation, algae growth, carbon conversion and power generation, simultaneously.

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