Benchmark Indicators for Integrated and
Sustainable Waste Management (ISWM)
Professor David C Wilson
Independent Waste & Resource
Management Consultant
Imperial College London
ISWA World Congress, Vienna, 8 October 2013
Context: Why Benchmark Indicators?
1. Availability, comparability &
reliability of SWM data is poor
2. Need a consistent means to
assess the current baseline in a
city & highlight priorities for
improvement
3. Allow consistent comparison
of performance between cities
4. Allow monitoring of progress
Photos:
Illegal dumping in Port Harcourt, Nigeria
Moshi, ‘the cleanest city in Tanzania’
Photo credits: © Kaine Chinwah; Alodia Ishengoma
‘Wasteaware’ ISWM Benchmark Indicators
1. Project started in 2009, many
people involved
2. Written paper provides
progress report to end 2012
3. Scope goes beyond ‘hard’ data
– ‘soft’ aspects often critical
4. Ambition is to apply the
indicators to any city – North
or South
Photos: Collection in Bamako, Mali and Adelaide, Australia
Photo credits: © Erica Trauba; Justin Lang, Zero Waste South Australia
Step 1: 2010 UN-Habitat Book
• Compiled by a team of 30+
professionals from North & South
• Objective 1: to provide a critical
review and guidelines on SWM in
the World’s cities
• Objective 2: address the critical
lack of solid waste & recycling
benchmarks – ISWM Indicators
set ‘Prototype A’
• Set out to collect reliable and
consistent data from 20 cities Scheinberg A, Wilson D.C. and Rodic L. (2010).
Solid Waste Management in the World’s Cities.
using that methodology
Published for UN-Habitat by Earthscan, London
Step 2: Analysis and Further Testing
• Using
‘Prototype A’
• Comparative
analysis for
the ‘20 cities’
• Additional
testing in
further cities
Rotterdam, NL
Varna, BG
San Francisco,US
Tompkins County, US
Sousse, TU
Bahrain•
Managua, NC
Bamako, ML
•Bishkek
Ghorahi, NP
Delhi, IN
Bengaluru, IN
Nairobi, KE
Kunming, CH
Dhaka, BN
Quezon City, PH
Moshi,TZ
Canete, PR
Belo Horizonte, BR
Lusaka, ZM
Curepipe, MU
Adelaide, AU
Analysis: Wilson, D.C., Rodic L., Scheinberg, A., Velis, C.A. and Alabaster, G. (2012).
Comparative analysis of solid waste management in 20 cities.
Waste Management & Research, 30, 237-254.
Bahrain: Al Sabbagh et al, 2012. Waste Management & Research, 30(8), 813-824.
Bishkek: Sim et al, 2013. Waste Management and Research, 31 (10 Supplement).
Step 3: Revise indicators
• Based on experience in use
• New version – ‘Prototype B’
• Initially tested in 5 case study cities as
part of GIZ ‘Operator Model’ project
• Focus of this presentation
Case studies (from top): Qena, Egypt; Castries, St. Lucia;
CIGRES, Rio Grande do Sul, Brazil; Maputo, Mozambique.
Also, Surat, India
GIZ report: Soos et al, 2013. Operator Models – Understanding Local Objectives:
Respecting Diversity. Eschborn: GIZ (in press).
Simplified ISWM analytical framework
1. Public health –
Collection
2. Environment
– Disposal
Physical
3. Resource value
3Rs – Reduce,
Reuse, Recycle
Concept: Scheinberg A, Wilson D.C.
and Rodic L. (2010). Solid Waste Management
in the World’s Cities. Earthscan for UN-Habitat
4. Inclusivity
Governance
6. Sound
Institutions
& Pro-active
Policies
5. Financial
Sustainability
© David Wilson, Ljiljana Rodic, Costas
Velis. See Proceedings of the Institution of
Civil Engineers, Waste and Resource
Management, 2013, 166, WR2, 52-68.
Quantitative indicators
Physical
component
Indicator
Public health
Collection
1. Collection
coverage
Environmental
protection
Treatment &
disposal
2. Controlled
disposal
Resource value
3Rs: reduce,
reuse, recycle
3. Recycling rate
Driver
(including organics
recycling)
Public health – 1. Collection coverage
World Bank website: 30-60% in low & middle income countries
100%
Wilson, D.C., Rodic L.,
Scheinberg, A., Velis, C.A.
and Alabaster, G. (2012).
Comparative analysis of
solid waste management in
20 cities.
Waste Management &
Research, 30, 237-254.
80%
70%
60%
50%
40%
GNI per capita (000' $)
50000
30000
8000
10000
6000
4000
2000
700
900
500
0%
1
Collection / sweeping coverage (%)
90%
Income level
High
Upper-middle
Lower-middle
Low
Other quantitative indicators (20 cities analysis)
1990s baseline for environmental control : open dumping
still dominant in middle and low-income countries
Income Level
High
2. Controlled 3. Recycling
Disposal
Rate
100%
54%
Upper-middle
95%
15%
Lower-middle
93%
27%
Low
53%
27%
Substantial progress has been made,
particularly in middle-income countries
Data source: Scheinberg A, Wilson D.C. and Rodic L. (2010). Solid Waste
Management in the World’s Cities. Published for UN-Habitat by Earthscan, London
Quantitative indicators only part of story
Income Level
2. Controlled
Disposal
High
100%
Upper-middle
Lower-middle
95%
93%
Low
53%
100%
80%
70%
60%
50%
40%
50000
30000
8000
10000
6000
4000
2000
700
900
500
0%
1
Collection / sweeping coverage (%)
90%
Income level
High
Upper-middle
Lower-middle
Low
GNI per capita (000' $)
So revised Prototype B: introduced complementary
qualitative indicators – 1Q, 2Q, 3Q
Each is a composite indicator,
scored against 5 or 6 criteria
Example: Criteria used to derive 1Q:
Quality of waste collection/ street cleaning
No
Criterion
Appearance of waste
1Q.1
collection points
1Q.2
Effectiveness of
street cleaning
Effectiveness of
1Q.3 collection in low
income districts
Effectiveness of
1Q.4
supervision and
management control
Health and safety of
1Q.5
collection workers
Description
Presence of accumulated waste around
collection points/containers
Presence of litter and of overflowing litter
bins in city centre, along main roads and in
popular places where people gather
Presence of accumulated waste/ illegal
dumps/ open burning in and around lower
income districts of the city
Appropriate service implementation,
management and supervision in place
Use of appropriate personal protection
equipment & supporting procedures
User manual provides guidance on
assessment against each criterion
For example:
No
Criterion
Appearance of waste
1Q.1
collection points
Description
Presence of accumulated waste around
collection points/containers
Score to be assigned
Assessment
0
Incidence is:
Very
high
5
10
15
20
High
Medium/
High
Medium
Low
Role of the ‘User’ or ‘Assessor’ is critical:
requires a level of ‘professional judgment’
Governance indicators – ‘Prototype A’
• Governance is by definition difficult to measure
• Approach taken in original UN-Habitat indicators:
Indicator
No.
4U
4P
5
6
Short name
Description of what that indicator
represents
Composite qualitative indicator:
User inclusivity
Degree of User inclusivity
Provider
Composite qualitative indicator:
inclusivity
Degree of provider inclusivity
Quantitative indicator: % of total
Financial
households both using and paying
sustainability
for collection services
Sound
Composite qualitative indicator:
institutions & assesses the policy framework and
proactive
the degree of municipal control and
policies
institutional coherence
Governance indicators – ‘Prototype B’
•
•
•
•
Extensive revisions: all composite, qualitative indicators
Revamped criteria for existing 4U and 4P
Introduced 6 criteria for revised 5F
Split No. 6 into two composite indicators
No.
Description of what indicator represents
4U
Degree of User inclusivity
4P
Degree of Provider inclusivity
5F
Financial sustainability
6N
Adequacy of national SWM framework
6L
Local institutional coherence
All indicators summarised as ‘traffic lights’
• Qualitative indicators: assessment ‘linear’ vs calculated ‘scores’
• Quantitative indicators: assessment scales different for each
‘Traffic light’ colour coding
No
Indicator
MEDIUM HIGH
LOW/
LOW
MEDIUM
MEDIUM
/ HIGH
All qualitative
0-20%
indicators
Collection
1
0-49%
Coverage
Controlled
2
0-49%
disposal
3 Recycling rate 0-9%
21-40%
41-60%
61-80%
50-69%
70-89%
90-98%
50-74%
75-84%
85-94%
10-24%
25-44%
45-64%
81100%
99100%
95100%
65%+
Supplementary information
to characterise a city’s
solid waste management performance
© David Wilson, Ljiljana Rodic, Costas Velis
Worked Example: Maputo, Mozambique
A: Supplementary information
No
Category
Indicator
Background information on the city
Results
G1
Country income
level
World Bank income category
Low
GNI per capita
$470
G2
Population of city
Total population of the city
1,131,149
G3
Waste generation
MSW generation (tonnes/year)
508,000
Key Waste-related data
449 (or
MSW per capita (kg per year)
316)
3 key fractions – as % wt. of waste generated
W1
Waste per capita
W2
Composition:
W2.1
Organic
Food and green wastes
65%
W2.2
Paper
Paper
8.5%
W2.3
Plastics
Plastics
8.0%
Worked Example: Maputo, Mozambique
B: Physical indicators
No
1
1Q
2
2Q
3
3Q
Category
Public health –
Waste collection
Environmental
control – waste
treatment and
disposal
3Rs – reduce, reuse
and recycling
Indicator
Collection coverage
Quality of waste
collection service
Controlled disposal
Environmental quality
of waste treatment and
disposal
Results
82%
M/H
0%
L/M
Recycling rate
< 5%
Quality of 3Rs
provision
L/M
Worked Example: Maputo, Mozambique
C: Governance indicators
No
Category
Indicator
4U
User inclusivity
Degree of user
inclusivity
M
4P
Provider
inclusivity
Degree of provider
inclusivity
M/H
5F
Financial
sustainability
Financial
sustainability
M/H
Sound
institutions,
proactive
policies
Adequacy of national
SWM framework
L/M
Degree of institutional
coherence
M
6N
6L
Results
Step 4: On-going work
• Further testing of ‘Prototype B’ in
12+ cities
• Extensive expert peer review
• In-depth testing within a country
(Egypt) – 19 more cities
• Preliminary updating to ‘prototype C’
and testing in Guadalajara, Mexico
• Comparative analysis for 36 cities
• Complete updating - ‘Prototype D’
• Next steps: Finalise, upload to web,
widespread roll-out
Guadalajara
Photo credits: © Recaredo Vilches
Summary – benefits of benchmarking
• Provides a rapid assessment of
the solid waste management
situation in a city
• Allows areas of comparatively
strong and poor performance to
be identified, to help prioritise
future work
• Allows consistent comparison
between cities and countries
• Allows for monitoring over time.
Progress can be recorded and
analysed
Photo credits: GIZ; Ljiljana Rodic
Qena, Egypt
Kunming,
China
‘Wasteaware’ ISWM benchmark indicators
• Many person-years of
development since 2009
• Uses integrated sustainable
waste management
framework
• Applicable both ‘South’ &
‘North’
• Cover both physical and
governance aspects
• Revised version: 3
quantitative + 8 composite
qualitative indicators
(comprising 43 criteria)
• ‘Finalised’ by end 2013
Please use
them!
Thanks to …
• UN-Habitat for their leadership
and funding of initial work and
data gathering
• GIZ who part-funded steps 3 & 4
• My many co-authors, including
Ljiljana Rodic, Mike Cowing,
Andy Whiteman, Joachim Stretz
and Anne Scheinberg
• The global community of
practice (CWG) who did the
work behind the Habitat book
• The many ‘testers’ in 36 cities
• My students at Imperial College
• and most of all to …
One size does not fit all – large
and small composting plants in
Adelaide and Canete, Peru
Photo credits: © Justin Lang, Zero Waste South Australia; Oscar Espinoza
… the millions of
professional waste
workers around
the world
Clockwise from top left: Canete, Nepal, Delhi, Sousse,
Cairo, Bengaluru, Dhaka, San Francisco, Rotterdam
Photo credits in same order: © Oscar Espinoza; Bhusan Tuladhar;
Enrico Fabian; Verele de Vreede; David C Wilson; Jeroen Ijgosse;
Waste Concern; Portia M. Sinnott; Rotterdam
Thank you for
listening!
www.davidcwilson.com
waste@davidcwilson.com
d.c.wilson@imperial.ac.uk