Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Data mining application in assessment of weather-based influent scenarios for a WWTP : getting the most out of plant historical data

Tools
- Tools
+ Tools

Borzooei, Sina, Teegavarapu, Ramesh, Abolfathi, Soroush, Amerlinck, Youri, Nopens, Ingmar and Zanetti, Maria Chiara (2019) Data mining application in assessment of weather-based influent scenarios for a WWTP : getting the most out of plant historical data. Water, Air, & Soil Pollution, 230 . 5. doi:10.1007/s11270-018-4053-1 ISSN 0049-6979.

[img]
Preview
PDF
WRAP-data-mining-application-assessment-weather-based-influent-scenarios-WWTP-Abolfathi-2019.pdf - Accepted Version - Requires a PDF viewer.

Download (1735Kb) | Preview
Official URL: https://doi.org/10.1007/s11270-018-4053-1

Request Changes to record.

Abstract

Since the introduction of environmental legislations and directives, the impact of combined sewer overflows (CSO) on receiving water bodies has become a priority concern in water and wastewater treatment industry. Time-consuming and expensive local sampling and monitoring campaigns are usually carried out to estimate the characteristic flow and pollutant concentrations of CSO water. This study focuses on estimating the frequency and duration of wet-weather events and their impacts on influent flow and wastewater characteristics of the largest Italian wastewater treatment plant (WWTP) located in Castiglione Torinese. Eight years (viz. 2009–2016) of historical data in addition to arithmetic mean daily precipitation rates (PI) of the plant catchment area are elaborated. Relationships between PI and volumetric influent flow rate (Qin), chemical oxygen demand (COD), ammonium (N-NH4), and total suspended solids (TSS) are investigated. A time series data mining (TSDM) method is implemented with MATLAB computing package for segmentation of time series by use of a sliding window algorithm (SWA) to partition the available records associated with wet and dry weather events. According to the TSDM results, a case-specific wet-weather definition is proposed for the Castiglione Torinese WWTP. Two significant weather-based influent scenarios are assessed by kernel density estimation. The results confirm that the method suggested within this study based on plant routinely collected data can be used for planning the emergency response and long-term preparedness for extreme climate conditions in a WWTP. Implementing the obtained results in dynamic process simulation models can improve the plant operational efficiency in managing the fluctuating loads.

Item Type: Journal Article
Subjects: T Technology > TD Environmental technology. Sanitary engineering
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH): Sewage -- Purification -- Castiglione Torinese
Journal or Publication Title: Water, Air, & Soil Pollution
Publisher: Springer
ISSN: 0049-6979
Official Date: January 2019
Dates:
DateEvent
January 2019Published
15 December 2018Available
6 December 2018Accepted
Volume: 230
Article Number: 5
DOI: 10.1007/s11270-018-4053-1
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): This is a post-peer-review, pre-copyedit version of an article published in Water, Air, & Soil Pollution. The final authenticated version is available online at: https://doi.org/10.1007/s11270-018-4053-1
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 4 May 2019
Date of first compliant Open Access: 15 December 2019
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDSocietà Metropolitana Acque TorinoUNSPECIFIED

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us