Jayanath Ananda School of Business

1. Eco-efficiency of Urban Water and Wastewater Management: Some Preliminary Observations Jayanath Ananda School of Business

2. Outline • Background • Research objectives • Methodology • Preliminary results • Concluding remarks Page 2

3. Background • The worst recorded drought in history and dwindling water supplies • Long-term degradation of fragile river systems • Policy responses • Stringent permanent water restrictions • Long-distance pipelines • Desalinisation • (1) Water policy reforms continue • Corporatization and competition policy • Highly variable institutional and operational structures • Complex regulatory and funding arrangements Page 3

4. Background • (2) Sustainable urban water management policy goal • Pressure to enhance water supply augmentation and formulate water supply and demand strategies • Increased targets of water recycling, wastewater & grey water, stormwater management and advancements in treatment • (3) Climate change policy • Stern report (2006); Task Group Report on Emission Trading (2007); Garnaut (2008) • Australian National Emission Trading Scheme (2008) Page 4

5. Climate Change Policy • Carbon Pollution Reduction Scheme – 2010 • A Cap and Trade System • Firms with more than 25,000 tonnes of CO2/yr to be included in the scheme • Australian urban water sector vulnerable to climate change • The highest growth in emissions (47% increase) • Although the overall contribution small (6.4%) • Greenhouse Emissions Reduction Strategy for water industry Page 5

6. Water industry (Vic) electricity consumption forecast Source: WISA, 2006

7. Sources of GHG emissions for a water business (Vic) Page 7

8. Sources of GHG emissions for a water business Source: WISA, 2006

9. Exogenous drivers of emission efficiency • Institutional structure (Private, State-owned company, Statutory Authority, Local council) • Network density (length of water and sewage mains) • Compliance with environmental regulators • Public disclosure of wastewater performance • Age of capital stock (water loss as a proxy) • Size of population being served (customer base) • % water sourced from non-catchment sources • Topography of the service area • Temperature • Rainfall Page 9

10. Objective To examine GHG emission efficiency of selected urban water businesses Guide GHG emission target setting Benchmark the emission performance and to identify the ‘industry best practice’ in GHG efficiency

11. Methodology • Standard DEA measures the efficiency of homogenous set of DMUs using inputs and outputs (‘goods’) - ‘best practice frontier’ • Does not require a priori functional form or weights • Potential outlier and error term problems (Fried et al. 1993) • Input and output orientations • Modelling ecologically undesirable outputs (‘bads’) eg. waste or emissions • Many approaches: Level of analysis and the treatment of ‘bads’ Page 11

12. Extending DEA to measure EE Treatment of environmental effects: As ordinary outputs (taking reciprocals), inputs Asundesirable ‘inputs’ (Tyteca, 1997; Ball et al. 2000; Sarkis & Talluri, 2005) Asundesirable outputs (Färe et al. 1989; Ball et al. 1994; Pittman, 1983) As undesirable outputs with non-discretionary inputs (Banker & Morey, 1986) Abatement inputs vs. traditional inputs (Shadbegian & Gray, 2005) As joint production (byproducts)

13. Input-oriented DEA • Since urban water utilities’ key output (urban water supplied) is exogenous, the input-orientation was selected • Pollutants are assumed to be weakly disposable(Shephard, 1970; Färe et al. 1989) and modelled as an undesirable input. • Overall TE indicates the maximum reduction of all inputs subject to the constraints imposed by the observed outputs and the technology • Subvector inefficiency (Eg. emissions) indicates the possibility to contract emissions while holding other input and output constant (Färe et al.1994). Page 13

14. DEA Model specification • Core Variables • Good output – Total urban water supplied (ML), % sewage treated to a secondary level and % sewage treated to a tertiary level • Inputs – Capital cost ($), Operating cost ($) (discretionary) • Bad inputs – Net GHG emissions (Net tonnes CO2-equivalents Page 14

15. Data • National Performance Report 2005-06 of urban water utilities • 37 water businesses were considered for the analysis Page 15

16. Net greenhouse gas emissions (net tons CO2-equivalents) 2005-06

17. Preliminary results Page 17

18. Preliminary results 24% of water businesses are technically efficient 62% of water businesses scored >50% efficiency in GHGs The mean pure technical efficiency is 69% meaning an average water business could reduce its inputs usage by 31% and still produce the same output The mean scale efficiency is 95% meaning that the loss of productivity due to scale inefficiency is low (only 5% on average).

19. GHG emission performance (PTE) (VRS scores)

20. GHG emission performance (TE) (CRS scores)

21. Potential improvements Water utility: Bega

22. Reference comparison

23. Step-wise regression Exogenous variables tested: The length of water and wastewater mains Institutional type of the water business (private company; state-owned company; statutory authority; local council) Source of water (own; bulk exports; mixed) Compliance (dummy) Disclosure (dummy) Total customer connections (significant at 5%) Needs further exploration (eg. Composition of customer base: residential vs non-residential)

24. Concluding remarks Eco-efficiency demands a fresh look at the water and wastewater operations and policy goals Supply augmentation capacity and GHG implications in the light of ETS Repeat analysis with different model specifications and more data on explanatory variables Use of alternative techniques (eg. SFA) to increase the reliability of results Emission target setting should take into account varied non-discretionary factors

25. Thank You Example presentation title Page 25