scholarly journals The use of Holt–Winters method for forecasting the amount of sewage inflowing into the wastewater treatment plant in Nowy Sącz

2016 ◽  
Vol 27 (2) ◽  
pp. 7-12
Author(s):  
Ewa Wąsik ◽  
Krzysztof Chmielowski
Keyword(s):  
Time Series ◽  
Wastewater Treatment ◽  
Linear Regression ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Exponential Smoothing ◽  
Model Fit ◽  
Daily Amount

Abstract The aim of the study was to determine changes of daily amount of sewage inflowing into a wastewater treatment plant in Nowy Sącz in the years 2008-2014. To this end, the data in the form of time series corresponding to the investigated multi-year period were analysed. Daily volume of sewage for annual periods was forecast using a seasonal method of Holt and Winters based on the exponential smoothing algorithms. The model fit to actual daily amount of sewage for 2014 was assessed using linear regression. The results of fit for the additive Holt-Winters model confirmed the usefulness of this tool for forecasting the amount of sewage inflowing into the wastewater treatment plant.

scholarly journals Time-series genome-centric analysis unveils bacterial response to operational disturbance in activated sludge

2019 ◽  
Author(s):  
María Victoria Pérez ◽  
Leandro D. Guerrero ◽  
Esteban Orellana ◽  
Eva L. Figuerola ◽  
Leonardo Erijman
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Wastewater Treatment ◽  
Activated Sludge ◽  
Microbial Communities ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Operating Conditions ◽  
The Face

ABSTRACTUnderstanding ecosystem response to disturbances and identifying the most critical traits for the maintenance of ecosystem functioning are important goals for microbial community ecology. In this study, we used 16S rRNA amplicon sequencing and metagenomics to investigate the assembly of bacterial populations in a full-scale municipal activated sludge wastewater treatment plant over a period of three years, including a period of nine month of disturbance, characterized by short-term plant shutdowns. Following the reconstruction of 173 metagenome-assembled genomes, we assessed the functional potential, the number of rRNA gene operons and thein situgrowth rate of microorganisms present throughout the time series. Operational disturbances caused a significant decrease in bacteria with a single copy of the ribosomal RNA (rrn) operon. Despite only moderate differences in resource availability, replication rates were distributed uniformly throughout time, with no differences between disturbed and stable periods. We suggest that the length of the growth lag phase, rather than the growth rate, as the primary driver of selection under disturbed conditions. Thus, the system could maintain its function in the face of disturbance by recruiting bacteria with the capacity to rapidly resume growth under unsteady operating conditions.IMPORTANCEIn this work we investigated the response of microbial communities to disturbances in a full-scale activated sludge wastewater treatment plant over a time-scale that included periods of stability and disturbance. We performed a genome-wide analysis, which allowed us the direct estimation of specific cellular traits, including the rRNA operon copy number and the in situ growth rate of bacteria. This work builds upon recent efforts to incorporate growth efficiency for the understanding of the physiological and ecological processes shaping microbial communities in nature. We found evidence that would suggest that activated sludge could maintain its function in the face of disturbance by recruiting bacteria with the capacity to rapidly resume growth under unsteady operating conditions. This paper provides relevant insights into wastewater treatment process, and may also reveal a key role for growth traits in the adaptive response of bacteria to unsteady environmental conditions.

scholarly journals Analysis of the time series of waste water quality at the inflow of the wastewater treatment plant and transfer functions

2014 ◽  
Vol 62 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Ivan Nesmerak ◽  
Sarka D. Blazkova
Keyword(s):  
Time Series ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Transfer Functions ◽  
Treatment Plant ◽  
Total Precipitation ◽  
Periodic Components ◽  
The Relationship ◽  
Pollution Loads ◽  
Daily Total

Abstract Time series of the daily total precipitation, daily wastewater discharges and daily concentrations and pollution loads of BOD5, COD, SS, N-NH4, Ntot and Ptot were analyzed at the inflow to the wastewater treatment plant (WWTP) for a larger city in 2004-2009 (WWTP is loaded by pollution from 435,000 equivalent inhabitants). The time series of the outflow from a WWTP was also available for 2007. The time series of daily total precipitation, daily wastewater discharges, concentrations and pollution loads at the inflow and outflow from the WWTP were standardized year by year to exclude a long-term trend, and periodic components with a period of 7 days and 365 days (and potentially also 186.5 days) were excluded from the standardized series. However, these two operations eliminated only a small part of the variance; there was a substantial reduction in the variance only for ammonium nitrogen and total nitrogen at the inflow and outflow from a WWTP. The relationship between the inflow into a WWTP and the outflow from a WWTP for the concentrations and pollution loads was described by simple transfer functions (SISO models) and more complicated transfer functions (MISO models). A simple transfer function (SISO model) was employed to describe the relationship between the daily total precipitation and the wastewater discharge.

scholarly journals The importance of pollutional loads during wet weather

2019 ◽  
pp. 271-282
Author(s):  
Oddvar Georg Lindholm ◽  
Lars Aaby
Keyword(s):  
Time Series ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
The Other ◽  
Combined Sewer Overflows ◽  
Combined Sewer ◽  
Receiving Waters ◽  
Wet Weather ◽  
Annual Discharge

Wet weather discharges consist mainly of washed out surface pollution in separate sewered areas, but in combined sewered areas; resuspended pipe deposits, surface washoff and sewage, discharging via combined sewer overflows (CSOs). Of the three mentioned sources, resuspended pipe solids is dominating over the other two and may contribute as much as 50 to 90 % of the total amount of the CSO. The CSO in a normal catchment may also on an annual bases be of the same amount, or even twice as much as the effluent from the wastewater treatment plant (WWTP). If the receiving waters are vulnerable to shock loads on a daily base, it is important to be aware that the amount of CSO might, at its most adverse be up to I 00 times more than the effluent from the WWTP during a day. The annual discharge via CSOs in a catchment may easily vary with a factor of up to 8 from the driest to the wettest year, during time series of 20 to 40 years.

scholarly journals Time Series Genome-Centric Analysis Unveils Bacterial Response to Operational Disturbance in Activated Sludge

mSystems ◽  
2019 ◽  
Vol 4 (4) ◽  
Author(s):  
María Victoria Pérez ◽  
Leandro D. Guerrero ◽  
Esteban Orellana ◽  
Eva L. Figuerola ◽  
Leonardo Erijman
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Full Scale ◽  
Operating Conditions ◽  
Lag Phase

ABSTRACT Understanding ecosystem response to disturbances and identifying the most critical traits for the maintenance of ecosystem functioning are important goals for microbial community ecology. In this study, we used 16S rRNA amplicon sequencing and metagenomics to investigate the assembly of bacterial populations in a full-scale municipal activated sludge wastewater treatment plant over a period of 3 years, including a 9-month period of disturbance characterized by short-term plant shutdowns. Following the reconstruction of 173 metagenome-assembled genomes, we assessed the functional potential, the number of rRNA gene operons, and the in situ growth rate of microorganisms present throughout the time series. Operational disturbances caused a significant decrease in bacteria with a single copy of the rRNA (rrn) operon. Despite moderate differences in resource availability, replication rates were distributed uniformly throughout time, with no differences between disturbed and stable periods. We suggest that the length of the growth lag phase, rather than the growth rate, is the primary driver of selection under disturbed conditions. Thus, the system could maintain its function in the face of disturbance by recruiting bacteria with the capacity to rapidly resume growth under unsteady operating conditions. IMPORTANCE Disturbance is a key determinant of community assembly and dynamics in natural and engineered ecosystems. Microbiome response to disturbance is thought to be influenced by bacterial growth traits and life history strategies. In this time series observational study, the response to disturbance of microbial communities in a full-scale activated sludge wastewater treatment plant was assessed by computing specific cellular traits of genomes retrieved from metagenomes. It was found that the genomes observed in disturbed periods have more copies of the rRNA operon than genomes observed in stable periods, whereas the in situ mean relative growth rates of bacteria present during stable and disturbed periods were indistinguishable. From these intriguing observations, we infer that the length of the lag phase might be a growth trait that affects the microbial response to disturbance. Further exploration of this hypothesis could contribute to better understanding of the adaptive response of microbiomes to unsteady environmental conditions.

Time Series Analysis for Uncertainty Evaluation of Influent Fluctuation of a Wastewater Treatment Plant

2015 ◽  
Vol 2015 (8) ◽  
pp. 3519-3526 ◽  
Author(s):  
Jamal Alikhani ◽  
Heather A Stewart ◽  
Imre Takacs ◽  
Ahmed Al Omari ◽  
Sudhir Murthy ◽  
...  
Keyword(s):  
Time Series ◽  
Wastewater Treatment ◽  
Time Series Analysis ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Uncertainty Evaluation ◽  
Series Analysis

Forecasting Influent-Effluent Wastewater Treatment Plant Using Time Series Analysis and Artificial Neural Network Techniques

2007 ◽  
Vol 2 (3) ◽  
Author(s):  
Sameer Al-Asheh ◽  
Farouq Sabri Mjalli ◽  
Hassan E. Alfadala
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Wastewater Treatment ◽  
Time Series Analysis ◽  
Quality Indicators ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Series Analysis ◽  
Plant Data ◽  
Artificial Neural

We consider the problem of predicting the future behavior of wastewater treatment plant quality indicators by creating prediction models using historical plant data. One of the main aims of this work is to be able to predict plant operational situations in advance so that corrective actions can be taken in time. Sets of historical plant data, such as BOD, COD and TSS were collected for a local wastewater treatment plant in Doha, the capital of the State of Qatar. These variables characterize the performance of any wastewater treatment plant and can be considered as quality indicators of the plant performance. Data were collected over a period of 4 years for the influent and effluent streams of the station. The plant influent and effluent predictions were performed using different techniques. These include time-series analysis, where the ARIMA (Autoregressive Integrated Moving Average) model was implemented in this case, and two Artificial Neural Networks (ANN) algorithms, namely Adaptive Linear Neuron networks (ADALINE) and Multi-layer Feedforward (ML-FF) neural networks. The predictions from the three techniques were presented and compared. The ML-FF model predictions proved to be more reliable than that of the equivalent ARIMA predictions followed by the ADALINE predictions, particularly for the finial effluent stream variables.

scholarly journals Analysis of hydraulic load of a wastewater treatment plant in Jasło

2016 ◽  
Vol 28 (1) ◽  
pp. 61-67 ◽  
Author(s):  
Dariusz Młyński ◽  
Krzysztof Chmielowski ◽  
Anna Młyńska
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Frequency Of Occurrence ◽  
Daily Amount ◽  
Study Results ◽  
Hydraulic Load ◽  
The One ◽  
Average Daily Amount

Abstract The paper presents an analysis of hydraulic load in a wastewater treatment plant (WTP) in Jasło. The study was based on the records of daily sewage volume entering the treatment plant within a multi-year period of 2010–2014. The analysis took into account the average daily amount of incoming sewage, the maximum daily peaking factor for the incoming sewage, changes in the sewage volume depending on specific month and day of a week, and class intervals with the greatest frequency of occurrence. The analysis revealed that the average daily volume of the sewage entering the WTP in Jasło in the investigated multi-year period was 13 045 m3·d−1. The amount of incoming sewage was variable, as evidenced by the maximum peaking factors of daily sewage inflow that ranged from 1.07 to 2.78, depending on a specific month. The sewage admission was the largest in March, May and June and on Saturdays. Sewage volume interval most often occurring at the WTP in Jasło was the one between 8 000 and 10 000 m3·d−1. The study results indicated that the facility was hydraulically underloaded.

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