Assessing the health consequences of deficiencies in water distribution networks

Transcription

1 Assessing the health consequences of deficiencies in water distribution networks Victor Vinas

2 THE DISTRIBUTION NETWORK 07/12/2018 Introduction Distribution Network 2

3 Introduction Distribution Network Transports safe drinking water from source to the consumers and other users 07/12/2018 Introduction Distribution Network 3

4 Introduction Distribution Network 07/12/2018 Introduction Distribution Network 4

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7 Loss of pressure 07/12/2018 Introduction Distribution Network 7

8 Introduction Distribution Network Combination of hydraulic and physical breaches Pathogens in the DN Gastrointestinal Illness (GI) E. Coli (O157:H7) 07/12/2018 Introduction Distribution Network 8

9 Aging infrastructure Rehabilitation rate today not enough to counter aging Aging = More frequent incidents = More risk of contamination Need for a PROACTIVE approach to deliver SAFE drinking water under deteriorating conditions 07/12/2018 Introduction Distribution Network 9

10 Aim Lay the foundation for management framework 1) to handle microbial risks in distribution networks (DN) Distribution Network Microbial Assessment Survey/Tool & 2) using Quantitative Microbial Risk Assessment (QMRA) as the basis for the framework Risk management QMRA 07/12/2018 Introduction Aim 10

11 QMRA Bild: QMRAwiki 07/12/2018 QMRA 11

12 WHAT WE KNOW About microbial risks & QMRA 07/12/

13 Microbial risks in the DN Intrusion events (Inträgning) Cross-connections and backflows (Korskoppling och backflöde) Improper installation, rehabilitation and repair of water mains Improper management of storage facilities Biofilms 07/12/2018 Microbial Risks 13

14 QMRA performed in the DN Study Contamination event analysis Transport Historical Experimental Modelling Experimental Modelling Dose- Response Models Exposure Consumption studies Modelling Risk characterization Monte Carlo simulations McInnis et al 2004 Storey et al 2004 van Lieverloo et al 2007 X X X X X X X X X X X X X X X X X Mena et al 2008 X X X X X X Teunis et al 2010 X X X X X Yang et al 2015 X X X X X X X Blokker et al 2018 X X X X X X 07/12/2018 I. Results - QMRA 14

15 Insights QMRA models available for the network - Require high degree of technical expertise - No integrated tool available yet - Not validated against real systems 07/12/2018 I. Literature Review - Insights 15

16 Cross-connection and backflows Fault tree & risk estimation 07/12/2018 Cross-connections and backflows 16

17 CROSS-CONNECTIONS AND BACKFLOWS Non-potable element P drinking < P non-potable + absence of control 07/12/2018 Cross-connections and backflows 17

18 Fault tree analysis Top event Graphical method that allows modelling how component failures can lead to a system-wide failure AND-gate OR-gate Intermediate event 1 Basic event A Basic event B Intermediate event 2 Basic event C Basic event D 07/12/2018 Cross-connections and backflows 18

19 Risk of cross-connection and backflow RR = PP xx CC where R is annual risk of infection P is the likelihood of a cross-connection and backflow C is the consequence of the cross-connection and backflow 07/12/2018 Cross-connections and backflows - Risk 19

20 Cross-connection and backflow fault tree RR = PP xx CC 07/12/2018 Cross-connections and backflows - Fault Tree 20

21 Initial calculations National level estimates were created with historical data at two levels: Top level Average length of the distribution network = 231 km 07/12/2018 Cross-connections and backflows - Fault Tree 21

22 Cross-connection and backflow fault tree RR = PP xx CC 07/12/2018 Cross-connections and backflows - Fault Tree 22

23 Consequence = infection 3 infection scenarios taken from previous study in Swedish networks Endemic (0.005% % wastewater) Elevated (0.7% wastewater) Extreme (10% treated wastewater) RR = PP xx CC 3 different pathogens (bacteria, virus, protozoa) Dose-response modelling to calculate C was performed with existing QMRA tool for source water and treatment plant 07/12/2018 Cross-connections and backflows - Consequence 23

24 Results - Annual risk of infection Risk Case C Bacteria C Virus C Protozoa P (per km of pipe) Endemic 100% 100% 100% 1.82 x 10-5 Elevated 100% 100% 100% 4.48 x 10-6 Extreme 100% 100% 100% 8.96 x 10-7 For average Swedish network (L = 231 km) Risk Case Risk of infection (R) Bacteria Risk of infection (R) Virus Risk of infection (R) Protozoa Endemic 4.2 x x x 10-3 Elevated 1 x x x 10-3 Extreme 2.1 x x x 10-4 US health target = 10-4 /person/year 07/12/2018 Results Annual probability of infection 24

25 Results (cont.) All estimated values over the 10-4 per person per year health target Cross-connections have high infectivity, even in the least critical scenario 07/12/2018 II. Results Annual probability of infection 25

26 Limitations Is input data relevant for all systems? Probably not, national estimate =/= site-specific estimate! Is it sensible to take historical data as reference values? Maybe. New data might need to be collected systematically to ensure reliability. Technical limitations Still using different software to perform single calculations. 07/12/2018 II. Cross-connections and backflow - Limitations 26

27 Summary Plenty of available information about microbial risks that can be used as input data Initial estimations of risk indicate that cross-connections are high risk incidents at a national level - Even endemic case was higher than the threshold 07/12/

28 Future Work Distribution Network Microbial Assessment Survey/Tool Future work dealing with all parts Risk management QMRA 07/12/2018 Future Work 28

29 Future Work MSc thesis pit sampling microbial quality (Input data) Collection of local data from GR municipalities to test crossconnections and backflows method (Input data) Translating methods into integrated tool (QMRA) Addressing other risks (QMRA) Integrations of costs into analysis (Management) 07/12/2018 Future Work 29

30 Further Reading Licentiate thesis: 07/12/

31 Acknowledgements I would like to thank the 13 municipalities from the Göteborg Region Association of Local Authorities (GR) for financing this project and sharing their experience throughout the development of this work. 07/12/

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