A stochastic model to predict flow, nutrient and temperature changes in a sewer under water conservation scenarios
- Submitting institution
-
The University of Bath
- Unit of assessment
- 12 - Engineering
- Output identifier
- 211980734
- Type
- D - Journal article
- DOI
-
10.3390/w12041187
- Title of journal
- Water
- Article number
- 1187
- First page
- -
- Volume
- 12
- Issue
- 4
- ISSN
- 2073-4441
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
https://www.mdpi.com/2073-4441/12/4/1187/s1
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
6
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The sewer models developed here are used to simulate SARS-CoV-2 spreading through sewer networks and have led to a £2.45m grant from the Department of Health and Social Care (grant number to be confirmed), in collaboration with Middlesex University London to investigate the role of schools in SARS-CoV-2 infections by analysing the schools’ waste water. This paper also forms the basis of a successful collaboration with KWR Water Research Institute in the Netherlands.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -