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Eco-efficiency of Urban
Water and Wastewater
Management: Some
Preliminary Observations
Jayanath Ananda
School of Business
Outline
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Background
Research objectives
Methodology
Preliminary results
Concluding remarks
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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
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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)
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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
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Water industry (Vic) electricity
consumption forecast
Source: WISA, 2006
Sources of GHG emissions for a
water business (Vic)
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Sources of GHG emissions for a
water business
Source: WISA, 2006
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
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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
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’
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Extending DEA to measure EE
• Treatment of environmental effects:
– As ordinary outputs (taking reciprocals), inputs
– As undesirable ‘inputs’ (Tyteca, 1997; Ball et al. 2000;
Sarkis & Talluri, 2005)
– As undesirable 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)
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).
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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 CO2equivalents
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Data
• National Performance Report 2005-06 of urban
water utilities
• 37 water businesses were considered for the
analysis
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Net greenhouse gas emissions (net tons CO2equivalents) 2005-06
Preliminary results
1.0000
0.9000
0.8000
Efficiency Score
0.7000
0.6000
0.5000
0.4000
0.3000
0.2000
0.1000
0.0000
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10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37
Water Utility
TE
PTE
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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).
GHG emission performance (PTE)
(VRS scores)
GHG emission performance (TE)
(CRS scores)
Potential improvements
Water utility: Bega
Reference comparison
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)
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
Thank You
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