BOOK
Optimisation of Corrosion Control for Lead in Drinking Water Using Computational Modelling Techniques
Colin Hayes | T. N. Croft | Corine Houtman | Ron van der Oost | H. David Stensel | S. E. Strand | D. Wait | M. Sobsey | D. Wood | J. Funk
(2013)
Additional Information
Book Details
Abstract
In many respects, lead in drinking water has become a forgotten problem, since the mid 1980s when a range of environmental controls were implemented to reduce exposure to lead. This is largely because the sampling protocols, that underpin regulatory controls, are mostly inadequate and have tended to under-estimate the amount of lead that can be present in drinking water (IWA, 2010).
Optimisation of Corrosion Control for Lead in Drinking Water Using Computational Modelling Techniques shows how compliance modelling has been used to very good effect in the optimisation of plumbosolvency control in the United Kingdom, particularly in the optimisation of orthophosphate dosing. Over 100 water supply systems have been modelled, involving 30% of the UK’s water companies. This “proof-of-concept” project has the overall objective of demonstrating that these modelling techniques could also be applicable to the circumstances of Canada and the United States, via three case studies.
This report is the first in the Research Report Series published by the IWA Specialist Group on Metals and Related Substances in Drinking Water.
Authors: Dr. C. R. Hayes and Dr. T. N. Croft Collaborators A. Campbell, City of Ottawa Water (CA) I. P. Douglas, City of Ottawa Water (CA) P. Gadoury, Providence Water (US) M. R. Schock, US Environmental Protection Agency (US)
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Cover\r | Cover | ||
| Contents | v | ||
| Foreword | viii | ||
| Acknowledgements | ix | ||
| Disclaimers | x | ||
| Executive Summary | xi | ||
| Chapter 1: Introduction\r | 1 | ||
| 1.1 CORRECTIVE WATER TREATMENT FOR REDUCING LEAD IN DRINKING WATER | 1 | ||
| 1.2 REGULATORY BACKGROUND IN THE UNITED STATES AND THE NEED FOR FURTHER OPTIMISATION OF PLUMBOSOLVENCY CONTROL | 1 | ||
| 1.3 REGULATORY BACKGROUND IN CANADA AND THE NEED FOR FURTHER OPTIMISATION OF PLUMBOSOLVENCY CONTROL | 2 | ||
| 1.4 OPTIMISATION OF PLUMBOSOLVENCY CONTROL IN THE UNITED KINGDOM AND THE USE OF COMPUTATIONAL MODELLING TECHNIQUES | 3 | ||
| 1.5 PROJECT OUTLINE, OBJECTIVES AND BENEFITS\r | 4 | ||
| (a) Project outline | 4 | ||
| (b) Objectives | 5 | ||
| (c) Benefits | 5 | ||
| Chapter 2: Description of the computational compliance\rmodels | 6 | ||
| 2.1 INTRODUCTION | 6 | ||
| 2.2 THE SINGLE PIPE MODEL | 6 | ||
| 2.3 THE ZONAL MODELLING FRAMEWORK | 7 | ||
| 2.4 SIMULATING SAMPLING\r | 8 | ||
| (a) Introduction | 8 | ||
| (b) Random daytime (RDT) sampling | 8 | ||
| (c) 6 hours stagnation sampling | 9 | ||
| (d) 30 minutes stagnation (30MS) sampling | 9 | ||
| (e) Examples of model output | 9 | ||
| Chapter 3: Simulation of water flow in a pipe using \rcomputational fluid dynamics | 10 | ||
| 3.1 INTRODUCTION | 10 | ||
| 3.2 THE FLUID FLOW EQUATIONS AND THEIR COMPUTATIONAL SOLUTION | 10 | ||
| 3.3 COMPARISON OF PLUG AND LAMINAR FLOW ALONG A STRAIGHT PIPE | 11 | ||
| 3.4 APPLICATION OF VOLUMETRIC PROFILES | 13 | ||
| Chapter 4: Calibration and validation\r | 14 | ||
| 4.1 INTRODUCTION | 14 | ||
| 4.2 CALIBRATION | 14 | ||
| 4.3 VALIDATION | 15 | ||
| Chapter 5: Case study: City A (US)\r | 17 | ||
| 5.1 BACKGROUND | 17 | ||
| 5.2 CALIBRATION AND USE OF THE LEAD EMISSION MODEL\r | 17 | ||
| (a) Lead pipe lengths and diameters\r | 17 | ||
| (b) Non-lead pipe lengths and diameters | 17 | ||
| (c) Water consumptions and patterns of use | 18 | ||
| (d) Plumbosolvency factors | 18 | ||
| (e) Other model inputs | 18 | ||
| (f) Uncertainties | 18 | ||
| (g) Premise plumbing | 18 | ||
| 5.3 RESULTS\r | 19 | ||
| (a) Matching predicted to observed LCR survey results | 19 | ||
| (b) Orthophosphate dosing scenarios | 20 | ||
| (c) Risk assessment | 20 | ||
| 5.4 DISCUSSION | 21 | ||
| 5.5 CONCLUSIONS | 21 | ||
| Chapter 6: Case study: City B (CA)\r | 22 | ||
| 6.1 BACKGROUND | 22 | ||
| 6.2 CALIBRATION AND USE OF THE LEAD EMISSION MODEL\r | 22 | ||
| (a) Lead service pipe lengths and diameters | 22 | ||
| (b) Non-lead pipe lengths and diameters | 22 | ||
| (c) Water consumptions and patterns of use | 23 | ||
| (d) Plumbosolvency factors | 23 | ||
| (e) Other model inputs | 23 | ||
| (f) Uncertainties | 23 | ||
| (g) Premise plumbing | 23 | ||
| 6.3 RESULTS\r | 23 | ||
| (a) Predicted and observed 30MS survey results | 23 | ||
| (b) Predicted results for sequential sampling after 6 hrs stagnation | 23 | ||
| (c) Risk assessment | 25 | ||
| 6.4 DISCUSSION | 25 | ||
| 6.5 CONCLUSIONS | 26 | ||
| Chapter 7: Case study: City C (US)\r | 27 | ||
| 7.1 BACKGROUND | 27 | ||
| 7.2 ASSESSMENT OF LEAD DATA FROM SEQUENTIAL SAMPLING SURVEYS\r | 27 | ||
| (a) Results profiles\r | 27 | ||
| (b) LCR compliance | 28 | ||
| 7.3 LEAD SERVICE LINES AND PLUMBOSOLVENCY CHARACTERISATION | 29 | ||
| 7.4 MODELLING\r | 29 | ||
| (a) Zonal compliance modelling | 29 | ||
| (b) Additional modelling to investigate laminar flow effects | 30 | ||
| 7.5 DISCUSSION | 30 | ||
| 7.6 CONCLUSIONS | 31 | ||
| Chapter 8: Investigations into sequential sampling\r | 32 | ||
| 8.1 INTRODUCTION | 32 | ||
| 8.2 SEQUENTIAL SAMPLING SURVEYS IN CITIES A, B AND C\r | 32 | ||
| (a) City A–results of sequential sampling by the State Health Authority | 32 | ||
| (b) City B – results of sequential sampling by the utility\r | 33 | ||
| (c) City C – results of sequential sampling by the USEPA\r | 33 | ||
| 8.3 MODELLING ZONAL COMPLIANCE | 34 | ||
| 8.4 USING REYNOLD’S NUMBER | 34 | ||
| 8.5 MODELLING SEQUENTIAL SAMPLING AT A SINGLE HOUSE\r | 35 | ||
| (a) Introduction | 35 | ||
| (b) Validation exercise | 35 | ||
| (c) Effect of copper pipe length | 36 | ||
| (d) Effect of lead pipe length | 37 | ||
| (e) Effect of pipe diameters | 40 | ||
| (f) Conclusions from the modelling exercises | 41 | ||
| Chapter 9: Discussion\r | 42 | ||
| 9.1 THE USE OF MODELLING IN THE OPTIMISATION OF PLUMBOSOLVENCY CONTROL\r | 42 | ||
| (a) The limitations of sampling | 42 | ||
| (b) The use of computational modelling tools | 42 | ||
| (c) Supporting techniques | 43 | ||
| 9.2 REGULATORY ASPECTS\r | 43 | ||
| (a) United States | 43 | ||
| (b) Canada | 43 | ||
| 9.3 OPERATIONAL ASPECTS | 44 | ||
| 9.4 RISK ASSESSMENT | 44 | ||
| 9.5 THE WAY FORWARD | 45 | ||
| Chapter 10: Conclusions\r | 46 | ||
| Chapter 11: References\r | 47 | ||
| Appendix 1: Calibration data\r | 49 | ||
| CITY A | 49 | ||
| CITY B | 50 | ||
| Appendix 2: Examples of model output\r | 51 |