Catchment &amp; sewer network simulation model to benchmark control strategies within urban wastewater systems

Saagi, Ramesh; Flores-Alsina, Xavier; Fu, Guangtao; Butler, David; Gernaey, Krist V.; Jeppsson, Ulf

doi:10.1016/j.envsoft.2015.12.013

Cited by 36 publications

(34 citation statements)

References 36 publications

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“…Furthermore, many studies revealed that the daily variation of wastewaters flows and pollutants content depend on the populations activities during all day. In this sense, Gernaey et al (2011) and Saagi et al (2016) have indicated an appearance of the pollution peaks in the early morning and early evening. Overnight, concentrations of pollutants declined sharply in water due to low wastewater production and also because, pollutants subjected to low flows are deposited in the pipelines.…”

Section: Introductionmentioning

confidence: 94%

Physico-chemical characterization of domestic wastewaters in the "Vie-Nouvelle" agglomeration, Cotonou, Benin

Atinkpahoun¹,

Soclo²,

Pons³

et al. 2018

Int. J. Bio. Chem. Sci

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Wastewaters are characterized by a high variability of flow and composition according to its origin. The objectives of this study were to evaluate the daily variation of the pollutants load from domestic wastewater in "Vie-Nouvelle" agglomeration in the city of Cotonou. In practice, samples were collected over 24 hours with one sample every hour, at the entrance of wastewater treatment plant of the agglomeration. Various parameters were measured at laboratory. Determination of methods specific to each parameter was used. The results show that these wastewaters are characterized by a great pollution variability during the diurnal period of day. The pollutant load showed the following variations : pH values ranging: 7.

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Section: Introductionmentioning

confidence: 94%

Physico-chemical characterization of domestic wastewaters in the "Vie-Nouvelle" agglomeration, Cotonou, Benin

Atinkpahoun¹,

Soclo²,

Pons³

et al. 2018

Int. J. Bio. Chem. Sci

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“…A correlation with either NH 4 + or CODpart was found for the pharmaceuticals considered in this study. In order to calibrate a Markov Chain, enough data has to be available to distinguish between the different states and to calculate the transition probabilities between these states (Madsen et al 1985;Saagi et al 2016). …”

Section: Description Of Compounds With Irregular Patternmentioning

confidence: 99%

“…There are several published studies that try to describe mathematically how these compounds appear at the inlet of the WWTP as reviewed by Martin and Vanrolleghem (2014) and the more recent studies of Talebizadeh et al (2016) and Saagi et al (2016). For example, Ort et al (2005) developed a stochastic model, describing short-term variations of benzotriazole concentrations (a chemical contained in dishwasher detergents).…”

Section: Introductionmentioning

confidence: 98%

Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies

Snip

Flores-Alsina

Aymerich

et al. 2016

Science of The Total Environment

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The use of process models to simulate the fate of micropollutants in wastewater treatment plants is constantly growing. However, due to the high workload and cost of measuring campaigns, many simulation studies lack sufficiently long time series representing realistic wastewater influent dynamics. In this paper, the feasibility of the Benchmark Simulation Model No. 2 (BSM2) influent generator is tested to create realistic dynamic influent (micro)pollutant disturbance scenarios. The presented set of models is adjusted to describe the occurrence of three pharmaceutical compounds and one of each of its metabolites with samples taken every 2-4h: the anti-inflammatory drug ibuprofen (IBU), the antibiotic sulfamethoxazole (SMX) and the psychoactive carbamazepine (CMZ). Information about type of excretion and total consumption rates forms the basis for creating the data-defined profiles used to generate the dynamic time series. In addition, the traditional influent characteristics such as flow rate, ammonium, particulate chemical oxygen demand and temperature are also modelled using the same framework with high frequency data. The calibration is performed semi-automatically with two different methods depending on data availability. The 'traditional' variables are calibrated with the Bootstrap method while the pharmaceutical loads are estimated with a least squares approach. The simulation results demonstrate that the BSM2 influent generator can describe the dynamics of both traditional variables and pharmaceuticals. Lastly, the study is complemented with: 1) the generation of longer time series for IBU following the same catchment principles; 2) the study of the impact of in-sewer SMX biotransformation when estimating the average daily load; and, 3) a critical discussion of the results, and the future opportunities of the presented approach balancing model structure/calibration procedure complexity versus predictive capabilities.

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“…Absorbance (essentially surrogate measurements for TSS -Total Suspended Solids or COD -Chemical Oxygen Demand) time series can be used to estimate the dry weather contribution to total TSS and COD loads measured during storm events [14], [15]. In fact, most models of storm weather pollutant loads in combined sewer systems are based on the assumption that total storm event load is the sum of dry and wet weather contributions, with the latter including surface runoff plus possible erosion of deposits accumulated in sewers [16]- [19]. Therefore, during rain events, it is important to distinguish the fraction of flow rate corresponding to dry weather and that corresponding to wet weather.…”

Section: Introductionmentioning

confidence: 99%

Detection of Outliers and Imputing of Missing Values for Water Quality UV-VIS Absorbance Time Series

Plazas-Nossa

Angulo

Torres

2017

Ing.

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Context: The UV-Vis absorbance collection using online optical captors for water quality detection may yield outliers and/or missing values. Therefore, pre-processing to correct these anomalies is required to improve the analysis of monitoring data. The aim of this study is to propose a method to detect outliers as well as to fill-in the gaps in time series. Method: Outliers are detected using Winsorising procedure and the application of the Discrete Fourier Transform (DFT) and the Inverse of Fast Fourier Transform (IFFT) to complete the time series. Together, these tools were used to analyse a case study comprising three sites in Colombia ( (i) Bogotá D.C. Salitre-WWTP (Waste Water Treatment Plant), influent; (ii) Bogotá D.C. Gibraltar Pumping Station (GPS); and, (iii) Itagüí, San Fernando-WWTP, influent (Medellín metropolitan area) ) analysed via UV-Vis (Ultraviolet and Visible) spectra. Results: Outlier detection with the proposed method obtained promising results when window parameter values are small and self-similar, despite that the three time series exhibited different sizes and behaviours. The DFT allowed to process different length gaps having missing values. To assess the validity of the proposed method, continuous subsets (a section) of the absorbance time series without outlier or missing values were removed from the original time series obtaining an average 12 % error rate in the three testing time series. Conclusions: The application of the DFT and the IFFT using the 10 % most important harmonics of useful values, can be advantageous for its later use in different applications, specifically for time series of water quality and quantity in urban sewer systems. One potential application would be the analysis of dry weather affecting rainy seasons, a feature achieved by detecting values that correspond to unusual behaviour in a time series. Additionally, the results hint at the potential of the method in correcting other hydrologic time series.

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Catchment & sewer network simulation model to benchmark control strategies within urban wastewater systems

Cited by 36 publications

References 36 publications

Physico-chemical characterization of domestic wastewaters in the "Vie-Nouvelle" agglomeration, Cotonou, Benin

Physico-chemical characterization of domestic wastewaters in the "Vie-Nouvelle" agglomeration, Cotonou, Benin

Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies

Detection of Outliers and Imputing of Missing Values for Water Quality UV-VIS Absorbance Time Series

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