Use of chemical upgrading (CU) in Hungary and Slovakia

1994 ◽  
Vol 30 (5) ◽  
pp. 87-95 ◽  
Author(s):  
Susan E. Murcott ◽  
Donald R. F. Harleman
Keyword(s):  
Wastewater Treatment ◽  
Biological Treatment ◽  
Treatment Plant ◽  
Domestic Sewage ◽  
Metal Salts ◽  
Plant Performance ◽  
Eastern European ◽  
Low Doses ◽  
The Past ◽  
Treatment Technologies

In the past decade, the development of polymers and new chemical technologies has opened the way to using low doses of chemicals in wastewater treatment. “Chemical upgrading” (CU) is defined in this paper as an application of these chemical technologies to upgrade overloaded treatment systems (typically consisting of conventional primary plus biological treatment) in Central and Eastern European (CEE) countries. Although some of the chemical treatment technologies are proven ones in North America, Scandinavia, and Germany, a host of factors, for example, the variations in composition and degree of pollution, the type of technologies in use, the type and mix of industrial and domestic sewage, and the amount of surface water, had meant that the viability of using CU in CEE countries was unknown. This report describes the first jar tests of CU conducted during the summer of 1993. The experiments show CU's ability to improve wastewater treatment plant performance and to potentially assist in the significant problem of overloaded treatment plants. Increased removal of BOD, TSS, and P in the primary stage of treatment is obtained at overflow rates above 1.5 m/h, using reasonably priced, local sources of metal salts in concentrations of 25 to 50 mg/l without polymers.

Upgrading a Large Municipal Sewage Treatment Plant by a Combination of Biological and Chemical Processes

1990 ◽  
Vol 22 (7-8) ◽  
pp. 105-112 ◽  
Author(s):  
H. H. Hahn ◽  
E. Hoffmann ◽  
A. Kleinschmidt ◽  
R. Klute
Keyword(s):  
Biological Treatment ◽  
Structural Changes ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Chemical Processes ◽  
Plant Performance ◽  
Municipal Sewage ◽  
The Past

The Standards controlling sewage treatment are continuously in development. Thus, upgrading existing plants is a frequently encountered problem. In the past this meant structural changes, mostly in terms of enlargement of existing facilities or addition of new units. More recently the possibilities of improving plant performance through chemicals addition (inducing precipitation and coagulation) with or without intensified biological treatment have been explored. Chemicals addition has become necessary in many instances due to the tightening of standards for phosphorous concentrations in the plant effluent. The present discussion is based on a case study where possibilities and limits of chemical and/or biological upgrading have been investigated. The analysis showed that neither chemical stages nor secondary biological stages alone can guarantee the effluent standards formulated by the water authorities.

scholarly journals Modern technologies of wastewater treatment for low-capacity facilities

2018 ◽  
Vol 178 ◽  
pp. 09016 ◽  
Author(s):  
Elena Gogina ◽  
Olga Ruzhitskaya ◽  
Varvara Shmalko
Keyword(s):  
Wastewater Treatment ◽  
Biological Treatment ◽  
Treatment Plant ◽  
Tertiary Treatment ◽  
Plant Operation ◽  
Current State ◽  
Treatment Stage ◽  
Treatment Technologies ◽  
Small Capacity ◽  
Modern Technologies

The article touches upon the issues of wastewater treatment on the facilities of small capacity. The brief analysis of the current state is given. The paper reveals main problems to be solved that consider small treatment plant operation, its influence on environment and most prospective solutions. The article considers the developed wastewater treatment technologies, as well as the implementation of these technologies on the patented small plants for deep biological treatment, including with the removal of phosphates at the tertiary treatment stage.

Sludge disposal and wastewater treatment in the region of Bratislava

2013 ◽  
Vol 8 (2) ◽  
pp. 286-303
Author(s):  
J. Kriš ◽  
M. Galík ◽  
V. Kvassay ◽  
G. Ivanič
Keyword(s):  
Wastewater Treatment ◽  
Biological Treatment ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Direct Application ◽  
Forest Land ◽  
Sludge Disposal ◽  
Sludge Digestion ◽  
Treatment Technologies ◽  
Total Capacity

In the process of wastewater treatment there are generated products that wastewater treatment plant operators want to eliminate. The most important product – waste generated in mechanical-biological treatment of wastewater – is sludge. Bratislava Water Company (BVS) operates three wastewater treatment plants (WWTP) with different mechanical-biological treatment technologies in the region of the Slovak capital. The total capacity of these WWTP is 1,515,000 population equivalent (p.e.). The WWTP serve the needs of about 557,000 p.e. who produce about 140,000 m3/day of wastewater. Annual production of mechanically dewatered anaerobically stabilized sludge is about 560,000 tons. At present, the biogas obtained from sludge is used for bioenergy production. The resulting thermal energy is used for technological purposes such as heating of operating premises and sludge digestion tanks. The obtained sludge is further recovered as a component in production of industrial compost or it can also be used for direct application to agricultural or forest land (if appropriate composition).

Savings with upgraded performance through improved activated sludge denitrification in the combined activated sludge–biofilter system of the Southpest Wastewater Treatment Plant

2008 ◽  
Vol 57 (8) ◽  
pp. 1287-1293 ◽  
Author(s):  
A. Jobbágy ◽  
G. M. Tardy ◽  
Gy. Palkó ◽  
A. Benáková ◽  
O. Krhutková ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plant ◽  
Biological Treatment ◽  
Treatment Plant ◽  
Oxygen Demand ◽  
Process Efficiency ◽  
Initial Value ◽  
Initial Profile ◽  
Biological Treatment System

The purpose of the experiments was to increase the rate of activated sludge denitrification in the combined biological treatment system of the Southpest Wastewater Treatment Plant in order to gain savings in cost and energy and improve process efficiency. Initial profile measurements revealed excess denitrification capacity of the preclarified wastewater. As a consequence, flow of nitrification filter effluent recirculated to the anoxic activated sludge basins was increased from 23,000 m3 d−1 to 42,288 m3 d−1 at an average preclarified influent flow of 64,843 m3 d−1, Both simulation studies and microbiological investigations suggested that activated sludge nitrification, achieved despite the low SRT (2–3 days), was initiated by the backseeding from the nitrification filters and facilitated by the decreased oxygen demand of the influent organics used for denitrification. With the improved activated sludge denitrification, methanol demand could be decreased to about half of the initial value. With the increased efficiency of the activated sludge pre-denitrification, plant effluent COD levels decreased from 40–70 mg l−1 to < 30–45 mg l−1 due to the decreased likelihood of methanol overdosing in the denitrification filter

scholarly journals Biological Nutrient Removal Model No. 2 (BNRM2): a general model for wastewater treatment plants

2013 ◽  
Vol 67 (7) ◽  
pp. 1481-1489 ◽  
Author(s):  
R. Barat ◽  
J. Serralta ◽  
M. V. Ruano ◽  
E. Jiménez ◽  
J. Ribes ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Nitrogen Removal ◽  
Nutrient Removal ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Operating Conditions ◽  
Plant Performance ◽  
Biological Nutrient Removal ◽  
Nitrite Oxidizing Bacteria ◽  
Removal Model

This paper presents the plant-wide model Biological Nutrient Removal Model No. 2 (BNRM2). Since nitrite was not considered in the BNRM1, and this previous model also failed to accurately simulate the anaerobic digestion because precipitation processes were not considered, an extension of BNRM1 has been developed. This extension comprises all the components and processes required to simulate nitrogen removal via nitrite and the formation of the solids most likely to precipitate in anaerobic digesters. The solids considered in BNRM2 are: struvite, amorphous calcium phosphate, hidroxyapatite, newberite, vivianite, strengite, variscite, and calcium carbonate. With regard to nitrogen removal via nitrite, apart from nitrite oxidizing bacteria two groups of ammonium oxidizing organisms (AOO) have been considered since different sets of kinetic parameters have been reported for the AOO present in activated sludge systems and SHARON (Single reactor system for High activity Ammonium Removal Over Nitrite) reactors. Due to the new processes considered, BNRM2 allows an accurate prediction of wastewater treatment plant performance in wider environmental and operating conditions.

Integrated Wastewater Treatment Plant Performance Evaluation Using Artificial Neural Networks

1999 ◽  
Vol 40 (7) ◽  
pp. 55-65 ◽  
Author(s):  
Mohamed F. Hamoda ◽  
Ibrahim A. Al-Ghusain ◽  
Ahmed H. Hassan
Keyword(s):  
Neural Networks ◽  
Wastewater Treatment ◽  
Artificial Neural Networks ◽  
Wastewater Treatment Plant ◽  
Municipal Wastewater ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Plant Performance ◽  
Municipal Wastewater Treatment ◽  
Artificial Neural

Proper operation of municipal wastewater treatment plants is important in producing an effluent which meets quality requirements of regulatory agencies and in minimizing detrimental effects on the environment. This paper examined plant dynamics and modeling techniques with emphasis placed on the digital computing technology of Artificial Neural Networks (ANN). A backpropagation model was developed to model the municipal wastewater treatment plant at Ardiya, Kuwait City, Kuwait. Results obtained prove that Neural Networks present a versatile tool in modeling full-scale operational wastewater treatment plants and provide an alternative methodology for predicting the performance of treatment plants. The overall suspended solids (TSS) and organic pollutants (BOD) removal efficiencies achieved at Ardiya plant over a period of 16 months were 94.6 and 97.3 percent, respectively. Plant performance was adequately predicted using the backpropagation ANN model. The correlation coefficients between the predicted and actual effluent data using the best model was 0.72 for TSS compared to 0.74 for BOD. The best ANN structure does not necessarily mean the most number of hidden layers.

scholarly journals Wastewater Treatment Plant Performance Inside Multi-Soil-Layering System

2017 ◽  
Vol 14 (1) ◽  
pp. 53-59 ◽  
Author(s):  
Lamzouri Khaoula ◽  
Mahi Mustapha ◽  
Masunaga Tsugiyuki ◽  
Ouattar Said ◽  
Bartali El Houssine ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Plant Performance ◽  
Soil Layering

scholarly journals Short investigation on occurrence and removal of semivolatiles during wastewater treatment processes

2021 ◽  
Vol 3 (2) ◽  
pp. 130-140
Author(s):  
Maria Diana Puiu ◽  
Keyword(s):  
Wastewater Treatment ◽  
Organic Contaminants ◽  
Biological Treatment ◽  
Organic Matter Content ◽  
Treatment Plant ◽  
Oxygen Demand ◽  
Matter Content ◽  
Physical Treatment ◽  
Dissolved Air Flotation ◽  
Treatment Processes

The food industry wastewater is known to present a high organic matter content, due to specific raw materials and processing activities. Even if these compounds are not directly toxic to the environment, high concentrations in effluents could represent a source of pollution as discharges of high biological oxygen demand may impact receiving river's ecosystems. Identifying the main organic contaminants in wastewater samples represents the first step in establishing the optimum treatment method. The sample analysis for the non-target compounds through the GC-MS technique highlights, along with other analytical parameters, the efficiency of the main physical and biological treatment steps of the middle-size Wastewater Treatment Plant (WWTP). Long-chain fatty acids and their esters were the main abundant classes of non-target identified compounds. The highest intensity detection signal was reached by n-hexadecanoic acid or palmitic acid, a component of palm oil, after the physical treatment processes with dissolved air flotation, and by 1-octadecanol after biological treatment.

scholarly journals Plant-wide modelling for assessment and optimization of upgraded full-scale wastewater treatment plant performance

2018 ◽  
Vol 13 (3) ◽  
pp. 566-582 ◽  
Author(s):  
Nadja Hvala ◽  
Darko Vrečko ◽  
Cirila Bordon
Keyword(s):  
Wastewater Treatment ◽  
Simulation Model ◽  
Wastewater Treatment Plant ◽  
Performance Indicators ◽  
Treatment Plant ◽  
Full Scale ◽  
Plant Performance ◽  
Limit Values ◽  
Reject Water ◽  
Integrate State

Abstract This paper presents the design of a plant-wide CNP (carbon-nitrogen-phosphorus) simulation model of a full-scale wastewater treatment plant, which will be upgraded for tertiary treatment to achieve compliance with effluent total nitrogen (TN) and total phosphorus (TP) limit values. The plant-wide model of the existing plant was first designed and extensively validated under long-term dynamic operation. The most crucial step was a precise characterization of input wastewater that was performed by extending the plant performance indicators both to a water line and sludge line and systematically estimating identifiable wastewater characterization parameters from plant-wide performance indicators, i.e. effluent concentrations, biogas and sludge production, and sludge composition. The thus constructed simulation model with standard activated sludge model (ASM2d) and anaerobic digestion model (MantisAD) overpredicted ortho-P and ammonia-N on the sludge line, indicating a need to integrate state-of-the-art physico-chemical minerals precipitation models to simulate plant-wide interactions more precisely. The upgraded plant with multimode anaerobic/anoxic/oxic configuration shows limited denitrification potential. Therefore, additional reject water treatment was evaluated to improve effluent TN and TP performance.

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