INDIA: Municipal Financing Requirements –

Water, Sewerage and Solid Waste

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1

INDIA: Municipal Financing Requirements –

Water, Sewerage and Solid Waste

June 2010

SOUTH ASIA URBAN & WATER UNIT

BACKGROUND STUDY FOR HIGH POWERED EXPERT COMMITTEE

2

INTRODUCTION 3

A. MUNICIPAL FINANCING NEEDS: WSS AND MSW SECTOR 5

B. URBAN WATER SUPPLY SERVICES 21

C. URBAN SEWERAGE SERVICES 40

D. MUNICIPAL SOLID WASTE 52

E. INVESTMENT NEEDS -A PART OF A COMPLEX PICTURE 65

ANNEX I: METHODOLOGICAL APPROACH 68

ANNEX II: SAMPLE DESCRIPTION 85

ANNEX III: INDIA URBAN POPULATION FORECASTS 86

ANNEX IV: MAIN RESULTS 93

ANNEX V: PROFESSIONALIZATION FOR SUSTAINABLE WSS DEVELOPMENT 99

ANNEX VI: CROSS-COUNTRY COMPARISONS 101

3

Acknowledgements

This study was conducted as part of the Non-lending Technical Assistance (NLTA) to the High

Powered Expert Committee (HPEC) on Urban Development, as an input to the HPEC

estimation of expenditure (investment and O&M) requirements for urban Water Supply and

Sanitation (WSS) and Municipal Solid Waste (MSW).

The study has been prepared by a team comprising Elisa Muzzini (TTL), Gabriela Aparicio and

Karan Rajput with contributions from Bill Kingdom, Shruti Garga, Deena Magnall, Vasudha

Sarda, Martina Tonizzo under the supervision of Junaid Ahmad. The cost models have been

developed in close collaboration with Dr. Isher Alwhawalia (HPEC Chair), Ramesh

Ramanathan and Prof. Om Mathur (HPEC members), Ranesh Nair and Shubhagato Dasgupta

(HPEC consultants), Prof. Usha Ragupathi and Chetan Vadya (National Institute of Urban

Affairs) and technical support from a panel of experts comprising Maruthi Mohan, Bill

Kingdom, Oscar Alvarado, N. V.V. Raghava, Guillermo Yepes for WSS and Sampath Kumar

and Da Zhu for MSW. A number of HPEC meetings were held to review and discuss the

results of the study.

Comments and contributions at various stages of the study have been provided by peer

reviewers Steve Karam, Christine Kessides and Paul Noumba, and Augustin Pierre Maria, Luis

Andres, Dan Biller, Sudeshna Banerjee, Songsu Choi, Fook Chuan, Celine Ferre, Matt Glasser,

Santiago Guerrero, Kristen Hommann, Dan Hoornweg, Pete Kolsky, Fernanda Nunez,

Eduardo Perez and Giovanna Prennushi.

JNNURM Project Appraisal Notes and Detailed Project Reports have been made available to

the team by HPEC for the purpose of the study. The team is grateful to Caroline van den Berg

and Sasha Danilenko for providing access to the IbNet database, and the Tamil Nadu Urban

Development Fund (TNUDF), the Karnataka Urban Water Supply and Drainage Board

(KUIDFC) and the Andhra Pradesh Municipal Development Project, Municipal Strengthening

Unit for sharing their project data with the team. The team would also like to thank Oscar

Alvarado, Shruti Garga, Raghu Kesavan and N. V.V. Raghava for coordinating the data

collection. Support to the team has been provided by Michelle Lisa Chen and Sunita Singh.

4

Introduction

1. The paper presents the main results of the cost models developed as an input the High

Powered Expert Committee (HPEC) on Urban Development in the estimation of investment

and O&M requirements for urban water and sanitation (WSS) and municipal solid waste

(MSW) for the period 2007-31. Each cost model builds on the methodological approach

developed by HPEC in consultation with sector experts. The service standards adopted for the

cost models, and the main assumptions, are the results of a number of consultations

undertaken by HPEC with support from sector experts. The cost models are designed as tools

that allow linking the various building blocks of the cost estimation to one other, and testing

the impact of the main model assumptions on the overall investment requirements. A cross-

country comparison is also conducted to benchmark the key service standards adopted in the

models against international experience.

2. The paper is organized in five main sections and six Annexes: Section A presents the

overall methodological approach adopted for the cost estimation and the consolidated results

of the three costs models; Section B, C, and D discusses the methodology and main results of

the water supply, sewerage and solid waste cost models respectively; Section E outlines the

main policy implications emerging from the cost estimation; Annex I discusses in detail each

step of the methodological approach and the main assumptions of the three cost models;

Annex II describes the sample data and the data sources; Annex III explains the methodology

for the urban population forecasts; Annex IV present in more detail the results of the cost

estimation; Annex V describes the methodology for the estimation of the costs of low

professionalization in the WSS sector; finally, Annex VI illustrates the main results of the cross-

country comparison of sector indicators.

5

A. Municipal Financing Needs: WSS and MSW Sector

A.I India Urban Population and Infrastructure Trends

3. India’s urban population is estimated to double in size from 2001 to 2031. The urban

population of India, estimated at 286 million in 2001, is expected to reach 627 million by 2031,

equivalent to 40 percent of the Indian population.1 Megacities (with population above 5

million) will also double in size over the same period, from 61 million to 133 million. Indian

cities with population between 1 and 5 million will register the highest absolute increase in

urban population, from 46 to 126 million, equivalent to an increase from 15 to 20 percent in

their share of India urban population (see Figure 1 and Figure 2). The average annual

population growth rate for urban India is expected to stabilize at 2.5 percent per annum, in line

with the population growth rate recorded over the period 1995-2000, although below the

record growth of 3-4 percent registered in the previous decades.

Figure 1: Urban Population by Class Size (million),

2001-2031

Figure 2: Urban Population by Class Size (million),

2001 and 2031

Source: Estimates based on UN World Urbanization Prospects 2007 and Census of India.

4. The challenge of a fast growing urban population is compounded by the high

backlog in urban service delivery. Infrastructure deficits in urban areas are large and

growing. Universal water access for urban population in India has yet to be realized. To date,

virtually no city in India has 24/7 piped water supply. The water supply in Indian cities is

characterized by limited hours of access per day and, in some cases, alternate day access. In

the case of sanitation, the national average for sewerage network coverage is only 33 percent

(based on 2001 census data), with some States receiving virtually no service. Although 300

urban centers have sewerage systems, most of these systems only partially cover their

1 Estimates based on UN population forecasts. The methodology for the estimation is described in

Annex III.

0

100

200

300

400

500

600

700

I.A : > 5m

I.B: 1-5m

I.C: 1m-100k

II: 50-100K

III: 20-50k

IV+: <20k

27 52356828

5499

195

46

126

61

133

0

100

200

300

400

500

600

700

2001 2031

I.A : > 5m

I.B: 1-5m

I.C: 1m-100k

II: 50-100K

III: 20-50k

IV+: <20k

6

populations. More than one third of the urban population relies on septic tanks as a form of

sanitation. Additionally, treatment facilities exist in only 70 cities and the services are

rudimentary at best. The present level of solid waste management is similarly dismal. There is

no public system of waste collection from the source in Indian cities. As a result, street

sweeping of waste has become the primary de facto method of waste collection. Furthermore,

barring a few exceptions, there are no sanitary landfills in India, posing serious public health

and environmental concerns. Uncovered solid waste is instead dumped haphazardly within or

outside cities. 2

5. A comprehensive and updated assessment of urban infrastructure investment

requirements for India is not available. There has been no systematic bottom-up assessment

of service delivery and expenditure norms for urban India since the seminal Zakaria

Committee’s Report of 1963.3 The most recent Government of India (GoI) assessment of

infrastructure investment needs for urban India, the Rakesh Mohan Committee’s Report (also

known as the 1996 Infrastructure Report) departed from the Zakaria Committee’s methodology

by taking a macro or top-down approach to the estimation of urban investment needs.4 The

rest of this section provides a short summary of the methodologies adopted by the 1963 and

1996 seminal GoI studies.

6. The Zakaria Committee’s Report (1963). The Zakaria Committee adopted a demand-

driven approach to estimate physical norms (service standards) and financial norms (per capita

investment requirements) for urban India. The standards were derived based on actual data

collected from a sample of cities on level of urban basic services, demand for services, cost for

provision, services maintenance and municipal finances. The assessment included water

supply, sewerage, storm water drainage, urban roads and footpaths.5 For example, per capita

water consumption was estimated to range between 45 and 270 liters per day depending on

city size.6 The Zakaria Committee’s financial norms adjusted for inflation are still widely

applied today as a benchmark for assessing infrastructure requirements in Indian cities.

7. The Rakesh Mohan Committee’s Report (1996). The Rakesh Mohan Committee

adopted a top down approach to the estimation of infrastructure investments for urban India

over the period 1996-2006. The exercise involved full-scale macroeconomic projections based

on assumptions about expected economic growth for the Indian economy. The underlying

2 3i Network. 2006. ‚India Infrastructure Report‛. New Delhi. 3 Committee of Ministers constituted by the Central Council of Local Self Government (1963),

‚Augmentation of Financial Resources of Urban Local Bodies‛ (also known as the Zakaria Committee’s

Report). 4 Expert Group on the Commercialization of Infrastructure Projects (1996). ‚The India Infrastructure

Report – Policy Imperatives for Growth and Welfare‛ (also known as the Rakesh Mohan Report or the

India Infrastructure Report, 1996). 5 Solid waste was not included in the cost estimation. 6 M.P. Mathur, Rajesh Chandra, Satpal Singh and Basudha Chattopadhyaya (2007). ‚Norms and

Standards of Municipal Basic Services in India‛. National Institute of Urban Affairs Working Paper 07-

01.

7

principle of the estimation is that infrastructure investments will only take place in a policy

environment that is investor friendly and transparent. The Rakesh Mohan Committee

estimated the cost of urban infrastructure at Rs 28,000 crore or USD 5.6 billion (1996 prices),

over the period 1996 -2006 across the three key services of water, sanitation and roads. Of this,

the investment share for urban water and sanitation was estimated at Rs 15,523 crore, or USD 3

billion, which is significantly below what is considered, 15 years later, as an appropriate

estimate of investment requirements in the WSS sector. With increasing volume of data made

available from the Jawaharlal Nehru National Urban Renewal Mission (JNNURM), there is

now sufficient project data available to re-visit the previous estimations of urban investment

needs.

8. JNNURM, established in 2006, is the only centrally sponsored scheme for urban

infrastructure improvement in India. The Jawaharlal Nehru National Urban Renewal Mission

(JNNURM) is a centrally sponsored scheme launched in 2006 with the objective of improving

urban infrastructure through a combination of investments and urban reforms. The duration of

the scheme is seven years (2006-2012). JNNURM comprises four separate windows of

assistance (or ‚Sub-missions‛), which share the same principles of engagement but differ in

their investment focus and target cities. There are two windows of assistance with a focus on

urban infrastructure investment: the Urban Infrastructure and Governance (UIG) scheme and

the Urban Infrastructure Development Scheme for Small and Medium Towns (UIDSSMT). The

UIG window targets 65 mission cities, selected based on their strategic importance for urban

development. The UIDSSMT window is open to all other urban centers in India, excluding the

65 UIG cities. All four windows of assistance are project-based schemes, as funds are

disbursed against sanctioned urban projects.7

9. The high level of funds committed under the JNNURM program signals a significant

un-met demand for infrastructure investment in urban areas. As of June 2009, the total

central budget allocation to the two JNNURM infrastructure windows amounts to about USD

8.6 billion which are expected to be disbursed over a period of seven years (2006-2012). In the

majority of the States, the central allocation is closed to be fully committed. When States’ and

ULBs’ contributions are included, total UIG and UIDSSMT commitments amount to about

USD 14 billion. UIG is the window of assistance with the largest central allocation (USD 6.3

billion) and commitments (USD 4.7 billion), and also the best performing window in terms of

disbursement (USD 1.7 billion). Projects sanctioned under the UIG window are sector-specific

investments; water supply and sewerage account for about 63 percent of committed funds in

the 65 mission cities, followed by urban transport projects (18 percent). The average size of a

UIG project is USD 21 million. Projects sanctioned under the UIDSSMT are small-scale

integrated urban projects, with an average project size of USD 4 million.8 The project data

approved under the JNNURM UIG window have been utilized for the cost estimation based

on information provided in the JNNURM Project Appraisal Notes.

7 Eligible cities are provided with a menu of investment options and requested to prepare City

Development Plans to prioritize investments within the eligible sectors. 8 Analysis based on MoUD data.

8

A.2 Methodology: The Building Blocks of the Models

10. This section discusses the overall methodological approach adopted for the estimation

of investment and O&M requirements for urban WSS and MSW over the period 2007-31. For

each sector, a cost model has been developed as a tool to support HPEC in the estimation. The

objectives of the cost models are the following: (i) to provide a framework for exploring the

linkages between the various building blocks of the cost estimation and the total expenditure

(investment and O&M) requirements; (ii) to compare the financial costs associated with

alternative service standards, and (iii) to facilitate the updating and refining of the estimates as

the data sample expands. The rest of the Section discusses the building blocks of the cost

models, and how they relate to one other.

Investment requirements

11. The estimation of investment requirements is based on the following four building

blocks: (a) service standards, (b) cost drivers; (c) unit/per capita costs; and (d) three investment

components (backlog or ‚unmet demand‛, demand growth and asset re-placement). The

methodological approach adopted for the investment estimation, and the relationship between

the four building blocks and the total investment needs, is summarized in Figure 3 below.

Figure 3: Cost Models – Building Blocks

Demand-side Supply -side

• City size• Population density

Cost drivers

Investment componentsUnit/Per Capita Costs

• 2006 backlog (un-met demand) • Demand growth (2007-31)• Asset re-placement

Investment requirements2007-31

• Per capita consumption - 2006 level- 2007-31 growth

• Supply option• Coverage/ Level of service• Efficiency• Economic life of assets

• Project data• Cost simulation

Service standards

Ass

um

pti

on

sEs

tim

atio

n

9

Service standards

12. The first step in the investment cost estimation is the setting of service standards or

targets, based on both demand and supply considerations. The service standards adopted for

the cost estimates have been determined by HPEC through a consultative process. A cross-

country comparison is conducted as part of the study to benchmark these service standards

vis-à-vis levels of service in comparable countries.

13. The main demand standard incorporated into the cost model is per capita consumption

(level and growth). For all services, per capita consumption is highly dependent on income

growth and pricing policies. In the absence of reliable data on the elasticity of demand vis-à-vis

price and income, a cross-country comparison is conducted to estimate the expected level of

WSS demand and solid waste generation in lower-middle income countries. While a full

Willingness-to-Pay (WTP) analysis is beyond the scope of this study, an affordability test is

carried out to estimate the share of household budgets that could be allocated toward to the

costs of service provision.

14. The supply-side standards that are incorporated into the models are the following (a)

supply option (e.g. network versus off-network water supply systems), (b) coverage rate, (c)

level of service (e.g. private water connection versus stand-posts) and (d) economic life of the

assets. Efficiency considerations are reflected in the cost estimation to the extent possible. For

example, the investment cost estimation for the water sector assumes an efficient level of water

leakage (equivalent to 20 percent of water production). In addition, the assumption related to

the economic life of the assets is based on efficiency considerations – e.g., an economic life of 30

years for water and sewerage assets implies an efficient operation and management of the WSS

systems.

15. Service standards affect the cost estimation through several channels. First, service

standards determine the sample of projects available for the cost estimation. For example, 24/7

water supply continuity is one of the main targets for the water sector. Given that very few

projects in India are designed to deliver 24/7 water supply, a cost simulation is conducted to

complement the limited sample of 24/7 pilot projects. Second, the demand standards are used

as reference to estimate the project beneficiaries (defined as the number of people that would

be served by the incremental capacity delivery by a project). For example, the per capita water

consumption standard of 135 lpcd (plus an allowance for efficient leakage) is used as the

reference to estimate the number of beneficiaries of JNNURM water production projects.9

16. The service standards also determine the size of the investment components (backlog,

demand growth and asset replacement). First, investment requirements for asset replacement

are estimated based on the economic life of the assets. Second, investment backlogs are related

to the supply standards. For example, assuming 24/7 water supply continuity as one of the

sector standards increases the backlog investment requirements, given that intermittent water

9 This is done by dividing the incremental project capacity by the demand standard.

10

supply is currently the norm for the vast majority of the India urban population. Finally,

investment requirements for demand growth depend on the level of per capita consumption

and its growth over time.

Cost drivers

17. The spatial pattern of urbanization is one of the key determinants of the unit costs of

service provision. For example, everything being equal, it is more expensive on a per capita

basis to provide piped water supply to low-density and small urban settlements than

megacities. Modeling the relationship between cost drivers and unit investment costs would

require the estimation of cost functions, which is beyond the scope of this work. An attempt

has however been made to model the impact of selected cost drivers (namely city population

and density) on investment requirements by estimating unit costs by city size class. The classes

adopted for the estimation are in line with the census classification, with two main differences.

Fist, the first census class (including cities with more than 100,000 inhabitants) is split into three

sub-categories (> 5m, 1-5m, 100k-1m). Second, the last three census categories (IV-VI) have

been aggregated into one class, which include small towns with less than 20,000 inhabitants.

18. Unfortunately, the number of project data available for small and medium towns at this

stage is limited, and not representative, given that the cities receiving JUNNURM UIG funds

are concentrated in the first Census class (> 100,000). Hence, only investment requirements for

all urban India are presented as part of the study. In spite of the limited sample size, clear

correlations between unit costs and population size and density are identified in most of the

models, and are discussed as part of the study.

19. Other important cost drivers related to city topography could not be systematically

captured in the cost models, but relevant findings are documented to the extent possible in the

study. For example, the unit costs of composting are significantly higher in coastal cities,

because weather conditions require that the compost plant be covered. The presence of

economies of scale is also tested based on project data for all sectors.

Per capita and unit costs

20. The per capita/ unit costs are estimated based on a sample of JNNURM UIG projects

complemented by a data collection in selected States where the Bank has ongoing projects

(Karnataka, Tamil Nadu and Andhra Pradesh). As a first step, JNNURM Project Appraisal

Notes have been reviewed by sector experts to build a sample of representative projects. A

combination of engineering and statistical criteria has been used to screen for outliers. As a

second step, the Notes have been analyzed to compute project costs by sub-sectors. For

example, solid waste project costs are estimated separately for collection and transportation,

processing and disposal. As a third step, unit and per capita costs have been estimated by city

size class based on the project’s design-year incremental capacity and number of beneficiaries.

21. Given the very limited number of water supply projects designed to deliver 24/7, a cost

simulation has been conducted to estimate the cost of 24/7 water supply up-gradation and 24/7

11

distribution extension. The methodological approach for the cost simulation is described in

detail in Annex I.

Investment components

22. Investment requirements are estimated for the period 2007-31. The previous GoI

Rakesh Mohan’s Committee Report estimated investment requirements up to the year 2006;

hence 2006 is chosen as the base year of the model. The following three main investment

components over the period 2007-2031 are considered for the cost estimation:

2006 backlog. The backlog is equivalent to the un-met demand for the 2006 base year.

The main data sources for the estimation of backlogs are the City Development Plans

complemented by the 2001 Population Census data.

Demand growth over the period 2007-31. Demand growth is estimated based on urban

population forecasts and per capita consumption level and growth. Industrial demand

growth in cities with more than 500,000 inhabitants is also included in the estimation of

water investment requirements. Urban population forecasts over the period 2007-2031

are based on UN estimates.

Asset re-placement. Replacement requirements are estimated based on the economic life

of the assets.

As for the unit costs, the investment components are estimated by city size class.

Total investment requirements

23. Total investment requirements are estimated by multiplying unit or per capita costs by

investment components for each sub-sector. Investment requirements are expressed as a band

rather than as a point estimate, to account for the variance in the unit/per capita cost estimates.

The band is based on a 90 percent confidence interval for the unit/per capita costs. The

mechanics of the estimation of backlog investment requirements for solid waste collection and

transportation (C&T) is presented in Figure 4 below as an example. The Figure shows the

relationship between unit costs /per capita costs and backlog (un-met demand).

12

Figure 4: Total investment Requirements (C&T Backlog)

Operation & Maintenance

24. Operations & Maintenance (O&M) costs are estimated on an annual basis over the

period 2007-2031 for the served population. Annual O&M costs are computed by multiplying

unit O&M costs by total volume, which is estimated based on the coverage rate and per capita

demand in a given year. Hence, annual O&M costs are expected to escalate as connection rates

increase from the current level to full coverage. For the purpose of the estimation, coverage

rates are simulated based on the assumption that full coverage would be achieved by 2031.

Unit O&M costs are estimated based on a sample of projects and expert advice. It has to be

noted that O&M costs depend to a significant extent on local conditions, and the variation in

O&M costs across localities couldn’t be captured as part of the cost modeling.

Strengths and limitations of the cost estimation

25. The main strengths of the methodological approach adopted for the estimation of

investment requirements are (a) the establishment of clear linkages between service standards

and per capita/unit costs; and (b) the modeling of important cost drivers related to the spatial

patterns of urbanization, namely city population and population density.

26. The main drawback of the exercise is the data limitation. Although the recent launch of

JNNURM has significantly increased the amount of project data available for WSS and solid

waste, information on small and medium towns (with population below 100,000) is still very

limited. Hence, the sample of project data that has been collected is too small to allow the

estimation of investment requirements by city size class with a reasonable level of accuracy.

13

27. Second, only information on approved JNNURM project costs is available at this stage,

given that the JNNURM program has only recently started, and the project completion rate is

still relatively low. Anecdotal information suggests that cost escalation represent a significant

share of total costs, up to 20-30 percent. As more and more JNNURM projects reach closure, it

would be important to compare approved costs with actual costs, and determine the main

drivers of cost escalation. This will allow ascertaining the extent to which cost escalation is due

to causes outside the control of implementing agencies, rather than inefficiencies in

procurement and implementation.

28. Finally, land costs are not included in the estimation of investment requirements,

although they are likely to represent a significant share of investment costs in the MSW sector.

Information on land costs is not available from JNNURM projects, given that JNNURM does

not cover the cost of land acquisition. Such costs are therefore not reported in the JNNURM

Project Appraisal Notes.

14

A.3 Municipal Investment and O&M Requirements- WSS and MSW

29. Overall investment requirements for urban WSS and MSW for the period 2007-31

range from Rs 4,637 to 6,785 Bn (2009 prices), equivalent to USD 103-151 Bn. The point

estimate for the total investment requirements is Rs 5,711 Bn, equivalent to USD 127 Bn. The

investment requirements for the residential water and sewerage sectors are comparable: the

investment requirements for the residential water sector ranges from Rs 2,035 to 3,139 Bn (USD

45-70 Bn), while the investment requirements for the sewerage sector ranges from Rs 1,913 to

2,544 Bn (USD 43-57 Bn).10 The MSW investment requirements are in the scale of Rs 368 to 607

Bn (USD 8-13 Bn). Finally, the investment requirements for the industrial water sector ranges

from Rs 321 to 496 Bn (USD 7-11 Bn). The sector with the highest cost variation relative to the

size of the sector’s investment requirements is MSW, followed by water; while sewerage has

the least cost variation. Investment requirements by sector are presented in Figure 5.

30. The confidence intervals for the total investment requirements (Rs 4,637 - 6,785 Bn)

reflect the variability in per capita investment costs (PCIC). The variation of per capita costs

observed across projects is large; thus, the actual PCIC of any particular future project may be

higher or lower than the average PCIC estimated from the sample. This PCIC variation is used

to construct a 90 percent confidence interval for the total investment requirements. Thus, 90

percent of the times, total investment requirements will be contained whithin the confidence

interval, depending on how large or how small the actual PCIC turn out to be.

31. The PCIC for the water sector is comparable to the PCIC for the sewerage sector as

the interval estimates overlap. The water PCIC ranges from Rs 3,363 to 5,188 (including both

water production and distribution). The PCIC for sewerage (network and treatment) ranges

from Rs 3,101 to 4,124. The PCIC for solid waste varies from Rs 323 to 515, including collection

& transportation, processing and disposal. The water sector has the largest per capita annual

O&M cost (Rs 501), followed by MSW (Rs 190), the sewerage sector the smallest (Rs 102). See

Figure 6.

32. Demand growth is the main driver of investment requirements. The largest

component of total investment requirements is residential demand growth, which accounts for

44 percent of the total investment requirements. Industrial demand growth accounts for an

additional 7 percent of total capital requirements. The backlog, or unmet demand, accounts for

35 percent of investment requirements, while assets replacement accounts for the remaining 14

percent. While demand growth is the main investment component for both water and

sewerage, assets replacement is the main driver of investment requirements for solid waste.

Figure 7 shows the share of the total investment requirements accounted for by each of the

three investment components.

10

See Box 2 for methodological issues that need to be taken into account when comparing water and

sewerage investment requirements.

15

33. The investment trend is estimated on a five year basis coinciding with the Planning

Commission’s five year plans. For the purpose of estimating the profile of the investments, the

assumption is made that full service coverage would be achieved by the end of the 15th Plan

(2027-32). The investment requirements are found to increase over time. The first phase of the

investment trend, coinciding with the 11th Plan of the Planning Commission, amounts to Rs 961

Bn. The last phase, coinciding with the 15th Plan, amounts to Rs 1,404 Bn. The average

investment per Plan is Rs 1,142 Bn (in 2009 prices). The investment trend is presented in Figure

8.

34. On average, for the period 2007-31, investment requirements account for about 1

percent of GDP per plan. The five year trend of investment requirements is estimated as a

share of GDP, assuming a 7 percent real GDP growth rate over 2007-31. Investment

requirements as a share of GDP decrease over time. The first investment, coinciding with the

11th Plan represents 1.6 percent of GDP. The last investment, coinciding with the 15th Plan

accounts for 0.6 percent of GDP. On an annual basis, investment requirements on average

account for 0.21 percent of GDP. The results are overall comparable with investment

requirements estimated based on alternative, but complementary top-down models (See Box

1). Results are presented in Figure 9.

35. Annual O&M costs are expected to more than double in real terms over the period

2007-31 as a result of the increase in coverage. O&M costs are calculated annually for the

period 2007-31. The data shows an increasing trend in annual O&M costs, as indicated in

Figure 10. O&M costs are expected to increase from Rs 178 Bn in 2007 to Rs 609 Bn in 2031 (in

2009 prices). The water sector accounts for the largest share of total O&M costs (70 percent of

the total)11, followed by MSW (20 percent of total). The sewerage sector accounts for the

smallest share of total O&M costs (11 percent of the total).

36. For the median urban person, annual O&M costs account for about 6.2 percent of per

capita expenditure.12 Overall, the affordability analysis suggests that there is scope for

recovering O&M costs from the connected population. The water sector accounts for the largest

budget share (3.9 percent of per capita expenditure), followed by sewerage (1.5 percent), and

solid waste (0.8 percent). Hence, user fees in line with O&M costs for the WSS sector would

represent 5.4 percent of per capita expenditure for the median urban person. The estimated

WSS expenditure budget share is broadly in line with internationally recognized affordability

norms for the WSS sector.

11 The residential water sector accounts for 55 percent of O&M costs, the industrial water sector for 15

percent. 12 The daily per capita expenditure for the median urban person is estimated at Rs 26 for the year 2004/05

based on National Sample Survey (NSS) data. The per capita expenditure is extrapolated to the year

2009 taking into account annual growth rate in per capita expenditure and inflation. The annual per

capita expenditure for the year 2009 for the median households is estimated at Rs 12,726.

16

Box 1: Investment Requirements - Benchmarking of Results

Fay and Yepes (2003) estimate infrastructure investment requirements for the period 2000-10 based on a

model that relates demand for infrastructure with economic growth. Chatterton and Puerto (2006) refine

Fay and Yepes’ estimation for the South Asia region. Results from both of these prior studies are not

directly comparable to those obtained from the cost models for various reasons. First they use a top-down

rather than a bottom-up methodology. Secondly, they are not country specific, they cover both urban and

rural areas, and they do not include rehabilitation / upgrading costs. In spite of these differences,

comparing the results of the models may provide useful insights on the order of magnitude of the

investment requirements based on alternative, but complementary methodologies.

Estimates obtained by Fay and Yepes for 2005-2010 and estimates obtained by Chatterton and Puerto for

2006-2010 are compared with estimates from the model for a comparable time-frame, such as the 11th Plan

(2007-2012).

According to the cost models, expected annual investment needs for water and sanitation (WSS) for the 11th

Plan are equivalent to 0.29 percent of GDP. Estimates from Fay and Yepes (2003) for South Asia amount to

0.4 percent of GDP for the same two sectors. Estimates from Chatteton and Puerto (2006) are equivalent to

0.49 percent of GDP for India (See Figure 11). As expected, investment estimates based on the (bottom-up)

urban cost models are lower than estimates based on the top-down models, which cover both urban and

rural areas. It is however worth noting that the difference between the two models can’t be considered a

proxy for rural investment requirements give the important methodological differences between the two

models listed above. In addition, the investment requirements for the 11th Plan period, as estimated based

on the bottom-up models, depend on the profiling of the investments. For the purpose of the estimation, it

is assumed that full coverage will be achieved by the year 2031. In addition, the bottom-up models also

estimate water production investment requirements for industrial customers, which are not included in the

top down models by Fay and Yepes (2003) and Chatterton and Puerto (2006).

Source: Fray and Yepes (2003); and Chatterton and Puerto (2006).

17

Box 2: Comparison of Water and Sewerage Investment Requirements

In general, capital expenditures for the sewerage sector are more expensive than capital expenditures for

the water sector. As a result, most countries have achieved a higher level of piped water coverage

compared to sewerage network coverage. For example, while high income countries have 96 percent piped

water coverage on average (See Table 25); they only have 70 percent sewerage network coverage (See Table

29). Thus, it may seem surprising that the models’ point estimate for water investment requirements is

higher than the point estimate for sewerage investment requirements, although the interval estimates

overlap . However, there are a number of explanations for this result.

First, water and sewerage PCICs are estimated based on slightly different methodologies. The PCIC for

sewerage is estimated from project data, for both network and treatment cost components. The PCIC for

water is estimated partially based on project data (for the water production component) and partially

based on a cost simulation (for the water distribution 24/7 component), given that very few projects in

India are designed to supply water 24/7. On average, estimates based on project data are more vulnerable

to cost escalation than estimates based on cost simulations, as the project costs data are based on cost

estimates at project design, rather than actual costs (which were not available at the time the study was

conducted). A sample of sewerage projects in Karnataka suggests that costs at contract award are 20

percent higher than costs at project design (net of inflation). As a result, the under-estimation may affect

sewerage more than water.

Second, the PCIC for water distribution (24/7 standards) include house connections and metering costs

(equivalent to Rs 2500 per household, or Rs 500 per capita) that are likely to be borne by consumers. When,

beneficiary contributions are excluded, the per capita cost for water decline by Rs 500.

Third, due to high PCIC variability, it is more appropriate to compare interval estimates, rather than point

estimates. When interval estimates are considered, there is no statistical difference between water and

sewerage investment requirements, as the two intervals overlap.

18

Figure 5: Investment Requirements 2007-31, Rs Bn (2009 prices)

Note: Confidence Intervals shown above reflect variability in per capita investment costs (PCIC).

Figure 6: PCIC (Rs/capita) and PC annual O&M, by Sector13

Figure 7: Investment Requirements 2007-31, By Component, Rs Bn (2009 prices)

13 Per Capita Investment Costs in the solid waste sector is expected to increase over time as a result of

growth in per capita waste generation. The average over 2007-31 is presented in the Figure.

2,587

2,229

487 408

2,035 1,913

368 321

3,139

2,544

607 496

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Water (Residential) Sewerage Solid Waste Water (Industrial)

Rs

Bn

(2

00

9 P

rice

s)

Backlog35%

Demand Growth (Residential)

44%

Replacement14%

Demand Growth (Industrial Water)

7%

19

Figure 8: Investment Requirements, by Five-year Plan, Rs Bn (2009 prices)

Figure 9: Investment Requirements, by Five-Year Plan, Share of GDP

Figure 10: Annual O&M Costs, Rs Bn (2009 prices)

525 520 556 676 718 599

374 397 433491 534

44662 61

104108

152

97961 9781,094

1,2761,404

1,142

0

250

500

750

1,000

1,250

1,500

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

April 2007 -March 2012

April 2012 -March 2017

April 2017 -March 2022

April 2022 -March 2027

April 2027 -March 2032

Average per plan

Solid waste Sewerage Water

0.86%0.64% 0.49% 0.42% 0.32%

0.55%

0.61%

0.49%

0.38%0.31%

0.24%

0.41%

0.10%

0.08%

0.09%0.07%

0.07%

0.08%

1.57%

1.21%

0.96%0.80%

0.62%

1.03%

0.21%

0.00%

0.50%

1.00%

1.50%

2.00%

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

April 2007 -March 2012

April 2012 -March 2017

April 2017 -March 2022

April 2022 -March 2027

April 2027 -March 2032

Average per plan

Average per year

Solid waste Sewerage Water

17

8

19

0

20

4

21

7

23

1

24

5

25

9

27

4

28

9

30

5

32

1

33

8

35

6

37

4

39

2

41

0

43

0

45

0

47

0

49

1

51

3

53

6

55

9

58

4

60

9

0

100

200

300

400

500

600

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

19

20

20

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

20

31

RS

Bn

(20

09

pri

ces)

Solid waste Sewerage Water (Residential) Water (Industrial)

20

Figure 11: WSS Annual Investment Requirements (Share of GDP): Benchmarking of Results

0.17% 0.21% 0.26% 0.18%

0.12%0.19%

0.42%

0.31%0.29%0.40%

0.68%

0.49%

0.00%

0.20%

0.40%

0.60%

0.80%

India, Urban South Asia, Urban and Rural

South Asia, Urban and Rural

India, Urban and Rural

% of GDP % of GDP % of GDP % of GDP

(2007-11) (2005-10) (2006-10) (2006-10)

Cost Models Fay and Yepes (2003) Chatterton and Puerto (2006)

Exp

ect

ed

An

nu

al In

vest

me

nt N

eed

sSewerage Water

21

B. Urban Water Supply Services

B.I Urban Water Service Standards

DEMAND SUPPLY

Per capita residential water

consumption (2007-31)

135 lpcd Supply option

(distribution)

Piped water supply

Annual growth in industrial

water demand (2007-31)14

7 % Level of service

(distribution)

24/7, private connections

Target coverage 100%

Efficient leakage 20% of water production

Assets’ economic life 30 years

37. The service standards that are incorporated into the water supply cost model are

defined along the following four dimensions: (a) supply option; (b) level of service/ continuity

of supply; (c) efficient leakage and (d) per capita consumption norm. The cost model is based

on the target of full piped water supply coverage through private connections, on a 24/7 basis.

The per capita consumption norm is assumed at 135 liters per capita per day (lpcd) as an

average for the period 2007-31, in line with MoUD benchmarking standards and with

consumption data for lower-middle income countries.15 Including an allowance for efficient

leakage (20 percent of water production), the per capita production norm is set at 168 lpcd.

The level of efficient leakage is in line with MoUD benchmarking standards, and consistent

with the leakage level in well run water utilities in developed countries.16 The same targets are

assumed across all urban India, although the model allows to differentiate standards across

city size classes, and to conduct a sensitivity analysis to estimate the impact of changing

standards on total investment requirements.

38. The service standards incorporated into the model should be in line with consumers’

expectations. A cross-country comparison is thus under-taken to benchmark India WSS

performance with respect to comparable countries. Although a full Willingness-To-Pay (WTP)

14 For cities with more than 500,000 inhabitants. 1515

See Ministry of Urban Development (2008), Handbook of Service Level Benchmarking. Delhi. See

also Figure 15 and Table 27 in Annex VI. 16 It is however worth noting that the current level of leakage in Indian water utilities is well above the

efficient level. Leakage levels are estimated at about 40 percent of water production, based on anecdotal

evidence (the true level of leakage is unknown given the widespread lack of metering). Hence, reducing

leakage levels from the current level to an efficient level would entail significant reforms in the

management and governance structure of Indian water utilities.

22

study is not carried out as part of the study, a number of tests are conducted to asses the extent

to which the model assumptions are in line with consumers demand.

Cross-country comparison

39. Private Connections. About 49 percent of urban households are estimated to have private

(within premises) access to water supply in urban India based on WHO/Unicef data collected

as part of the Millennium Development Goal’s Joint Monitoring Program (JMP). The estimate

is in line with the average access rate for urban India based on 2001 Population Census data (48

percent). Based on census data, the access rate varies from 57 percent in megacities, with

population above 5 million, to 31 percent in towns with less than 20,000 inhabitants (see Figure

12). The urban India access rate is below the average for lower-middle income countries,

estimated at 70 percent based on a sample of 43 countries (see Figure 13 ). For example, lower-

middle income countries such as like the Philippines and China perform significantly better

than India, with private connections covering 69 and 87 percent respectively of total urban

households. WHO/Unicef estimates are broadly consistent with estimates based on IbNET’s

utility data, which report access rates of the order of 70 percent for lower-middle income

countries based on data from 773 utilities, including both private and shared connections (see

Table 25 in Annex VI). 17

40. Continuity of supply. India is one of the countries with the lowest standards for water

continuity of supply, with an average of only 4 hours of water supply per day in urban areas.

The average number of hours of water supply is 16 hours in lower-middle income countries,

and 23 hours in upper-middle income countries (see Figure 14).

41. Per capita water consumption. Data on per capita water consumption in urban India are

difficult to obtain because of the widespread lack of metering and the uncertainty surrounding

the level of water losses. The per capita consumption standard set by MoUD as part of the WSS

benchmarking exercise (135 lpcd) is adopted for the model. The MoUD standard is within the

appropriate range identified by the cross-country comparison for comparable countries. Based

on utility data, per capita water consumption in urban India is estimated at 132 lpcd based on a

sample of 8 utilities18. The average includes both private and shared connections and public

taps. Efficient pricing is controlled for by excluding from the sample utilities that don’t recover

their operating costs. Based on IbNet’s utility data, the average level of per capita consumption

for lower- and upper-middle income countries is estimated at 103 and 162 lpcd respectively

based on a sample of 707 utilities. (See Figure 15). Assuming a level of efficient leakage of 20

percent, a per capita production norm of 168 lpcd is adopted for the model.

42. It is difficult to estimate how per capita consumption will evolve and respond to

income growth and efficient pricing, given that most utilities currently do not charge the full

17

See the International Benchmarking Network for Water and Sanitation Utilities (IbNET),

http://www.ib-net.org/ 18

Data for India obtained from the 2007 Benchmarking and Data Book of Water Utilities in India

23

economic cost of service provision to their customers. While income growth may increase

demand for water, the introduction of efficient pricing may deter further increases in

consumption. Based on a survey of 1,100 households conducted in Dehra Dun in the northern

Indian State of Uttar Pradesh in 1995, the price elasticity for individually connected users was

estimated at --0.31 (a 10 percent increase in the price of water would lead to a 3 percent

decrease in water consumption for households with individual connections). Household

income was found to have a larger impact on water use: water use increases 4.1 percent as

household income increases 10 percent.19 Given that the net impact of price and income effects

are expected to counterbalance each other to some degree and vary across localities, no change

is assumed in the per capita consumption norm of 135 lpcd over the period 2007-31.

Willingness-to-pay

43. Ability to pay can be considered an upper bound estimate of WTP for improved service

delivery. An affordability analysis is conducted to estimate the ability-to-pay of the median

urban person for private water connections. The results indicate that there is significant scope

for recovering O&M costs of private water connections from residential customers, although

subsidies to cover the capital expenditure of water connections would be required. Based on a

per capita consumption norm of 135 lpcd, water charges in line with O&M costs would

represent 3.9 percent of per capita expenditure for the median urban person. The budget share

is below the affordability norm, which is generally estimated at 3-5 percent of household

budgets. A recent World Bank study on the ‚Review of Effectiveness of Rural Water Supply

Schemes in India‛ finds that even among rural households there is WTP to cover the O&M

costs for private connections. Rural households’ WTP for house connections is estimated to

range from Rs 40-58 per household/month, or 1 – 2 percent of monthly household income.20

The results of the analysis suggest that the standard of house connection is broadly in line with

consumers’ demand.

44. Coping costs can be considered a lower bound estimate of WTP for continuous water

supply. The coping costs of intermittent water supply can therefore be estimated as a lower

bound for the WTP of 24/7 up-gradation. The empirical evidence suggests that the coping costs

of intermittent water supply are significant across all income groups. The main coping costs

are investment in water-related equipment for households with private connections and the

value of time spent fetching water for households that rely on public taps. See Box 3.

19 See Choe, Varley and Bijlani (1995). ‚Coping with Intermittent Water Supply: Problems and

Prospects‛. Activity Report N. 26. 20 World Bank (2008), ‚Review of Effectiveness of Rural Water Supply Schemes in India‛ Sustainable

Development Unit. South Asia Region. June.

24

Box 3: Household Coping Costs of Intermittent Water Supply

Most of the urban population in the developing world receives intermittent water service. While it is

evident that unreliable water supply worsens the quality of service provided to customers, the full extent of

the problem is not easily recognized. Indeed, all consumers incur costs to cope with intermittent water

supply.

For households with access to piped water supply, the main coping costs include investments in water-

related equipment such as water storage, and the monthly maintenance costs of operating such equipment.

The coping strategies, for households who can afford it, include increasing the households’ water holding

capacity, enhancing water pressure and purifying water via water tanks, electric pumps and water filters.

Such coping strategies require large lumpy investments. Indeed, according to a survey in Dehra Dun, the

average cost for all coping equipment is Rs 4,905 and Rs 3,688 (in 2009 prices) for individuals with private

and shared connections, respectively. Moreover, the average payment for coping mechanisms, including

capital investment and regular maintenance and operation, is as high as Rs 71 and Rs 52/household/month

(Rs 3.9 – Rs 4/m3) for private and shared connections, respectively.

For households that rely on public taps, the main coping cost is the value of the time spent queuing in

line to fetch water. Households that rely on public taps generally belong to a low-income class and cannot

afford the capital investment or access to credit to finance major equipment purchase. Their capital

equipment expenditures are limited to small containers and the like. However, the opportunity cost of the

hours spent fetching implies loss of wage income. In Dehra Dun, this cost equals Rs 7 per hour21 (in 2009

prices). Moreover, since the average household spends 3 hours per day collecting water, the lost income

potential equals almost Rs 356/household/month (approximately 10 percent of their monthly income). Thus

the total coping costs (including storage and lost time) amount to Rs 367/household/month (Rs 82/m3) for

the regular season.

Coping costs are large compared to the tariffs paid. For example, connected customers in Dehra Dun are

billed on average Rs 4/m3 (in 2009 prices); however, once the private investment in water storage is taken

into account, the actual costs are over Rs 8/m3. Similarly, although public tap users pay no cash to the water

utility, the real costs arising from the opportunity cost of the time spent queuing are over Rs 94/m3 in the

dry season. As a result, the poor pay higher real costs for water than those who are connected, due to the

limited options that the poor have in adopting alternative coping strategies. Such large coping costs (which

can be considered a lower bound estimate of WTP) suggest that even the poorest households are willing

and able to pay for improved service delivery.

Customers are willing to pay for continuous water supply. The present situation of low cost recovery is

usually attributed to high prices; however, low cost recovery can also be interpreted as an indication of

customers’ dissatisfaction with the performance of the water utility. Indeed, it has been estimated that in

Dehra Dun, households would be willing to pay an additional Rs 5/m3 for continuous supply above the Rs

4 that they are billed on average (for a total willingness to pay of Rs 9/m3).

Source: Choe, Varley and Bijlani (1995), Yepes, Ringskog and Sarkar (2001) and Zérah (2000).

21

Based on 80 percent of hourly wage rates among public-tap users

25

Figure 12: Urban Piped Water Supply Coverage in India, by City Size Class

Source: 2001 Population Census. Notes: Number of urban centers/towns in parenthesis.

Figure 13: Urban Piped Water Supply –Selected Countries (2006) – Private Connections

Source: WHO/Unicef. Notes: For income groups sample size (number of countries) in parenthesis.

Figure 14: Urban Water Continuity of Supply – Selected Countries (2004-08)

Source: IBnet. Notes: Based on a sample of utilities for each country.

57% 55%48%

41%37%

31%

48%

0%

10%

20%

30%

40%

50%

60%

70%

Class I.A Class I.B Class I.C Class II Class III Class IV+ Weighted Average

(7) (27) (360) (404) (1,164) (2,415) (4,377)

96 90 96 88 8470

8769

49 4834

7

4359

20

020406080

100

Hig

h in

com

e

Upp

er m

iddl

e in

com

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Mex

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Bra

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com

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Phi

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nes

Indi

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Pak

ista

n

Indo

nesi

a

Nig

eria

Low

inco

me

Vie

tnam

Ban

glad

esh

(43) (36) . (47) . (42) .

Upper middle income Lower middle income Low income

Co

vera

ge

as a

% o

f p

op

ula

tio

n

INDIA

0

4

8

12

16

20

24

0 5,000 10,000 15,000 20,000 25,000

hrs

/day

$ GNI per capita 2008 (PPP)

26

Figure 15: Urban Per Capita Water Consumption –

Private/Shared Connections and Public Taps

Source: IBnet; Water in Asian Cities; 2007 Benchmarking and Data Book of Water Utilities in India

Notes: Based on a sample of utilities. Number of utilities available for each income groups in parenthesis.

179 162202

171

103132 122 114

7297 97 76

197

127 11077

050

100150200250

Hig

h in

com

e

Upp

er m

iddl

e in

com

e

Sou

th A

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Low

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com

e Indi

a

Phi

lippi

nes

Indo

nesi

a

Chi

na

Low

inco

me

Vie

tnam

Ban

glad

esh

Sha

ngha

i

(C

hina

)

Kar

achi

(Pak

ista

n)

Man

ila

(P

hilip

pine

s)

Del

hi

(Ind

ia)

Jaka

rta

(Ind

ones

ia)

(142) (494) . (213) . (201) .

Upper middle inc. Lower middle income Low income City Level

Lp

cd

27

B.II Urban Water Supply Cost Model Methodology

45. Urban water investment requirements are calculated for both (A) residential customers

and (B) industrial customers. O&M costs are estimated separately on an annual basis for both

customer groups. The rest of the Section discusses the methodological approach adopted for

the cost estimation. A summary of the methodology is presented in Table 14. A detailed step-

by-step description of the approach and data sources is provided in Annex I and II.

46. Residential customers – The methodology for estimating investment requirements for

residential customers consist of the following four building blocks: (1) service standards, which

are described in detail in the previous section; (2) investment components, (3) cost drivers and

(4) Per capita investment costs (PCIC).

There are three main investment components. The first investment component

corresponds to the backlog or un-met demand, defined as the percentage of the current

population that is un-served, in relation to the service standard. The second component

corresponds to demand growth, defined as the population that will require service over

the period 2007-31. Finally, the last component corresponds to assets replacement, which

is the cost of replacing outdated assets.

Per capita investment costs (PCIC) are calculated based on project data and cost

simulations. Three separate PCIC are estimated for (a) production; (b) distribution

extension (based on 24/7 standards) and (c) 24/7 up-gradation.

The two main cost drivers associated with the spatial pattern of urbanization are city size

and population density. The correlation between cost drivers and PCIC is explored by

estimating PCICs by city size class.

47. Investment requirements are calculated as the product of each one of the investment

components times the PCIC of the corresponding sub-sector (production or distribution) or the

PCIC for 24/7 up-gradation. Overall, the methodological approach is depicted in the diagram

presented in Figure 16 below. The diagram presents a breakdown of investment requirements

based on cost component (production, distribution and 24/7 up-gradation) and investment

component (backlog, demand growth and asset re-placement). The investment requirements

include: total investment requirements for backlog [1+ 2+ 5]; total investment requirements for

demand growth [3+4]; and total investment requirements for assets replacement (water

production) [6]. Investment requirements are estimated as a band based on a 90 percent

confidence interval for PCICs.22

48. Industrial customers – Investment requirements for industrial customers are calculated at

the city-level (for cities with more than 500,000 inhabitants). First, industrial water demand is

22 There is a one-to-one relationship between PCICs and total investment requirements – i.e. a 10 percent

increase in PCICs leads to a 10% increase in total investment requirements.

28

forecasted based on the percentage of water production capacity dedicated to industrial

customers and demand growth. Second, city-level investment requirements are estimated

based on unit water production costs. Finally, total investment requirements are computed as

the product of city-level investment needs and the total numbers of cities in each city class.

49. O&M costs are calculated on an annual basis for the served residential population and

industrial customers.

Figure 16: Urban Residential Water Supply Cost Model - Methodology

29

Figure 17: Urban Water Supply Cost Model Methodology: Building Blocks

Residential Water Supply

(1) Service Standards

100% piped water supply (private connections); per capita water consumption at 135 lpcd over 2007-31.

(2) Investment Components

(2.1)

2006 Backlog (Un-met demand)

(2.2) Demand Growth

2007-31 (2.3) Assets Replacement

Production [1] Production [3] Production [6]

Definition: percent of base-year un-met residential water demand based on a per capita water production norm of 168 lpcd. Source: City Development Plans (CDPs) (Sample size 67 obs.)

Definition: Incremental water demand over the period 2007-2031. Source: Forecasted yearly by applying UN population growth rates to the 2001 Census population.

Definition: Assets are assumed to have a 30 year economic life.

24/7 Up-gradation [5]

Definition: percent of base-year urban population without access to water supply on a 24/7 basis. Source: Equivalent to the entire Indian urban population connected to piped water supply (virtually no city in India has 24/7).

Distribution Extension [2] Distribution Extension [4] There are no assets replacement costs for distribution, because replacement costs of existing assets are accounted for in 24/7 up-gradation.

Percent of the base year urban population without access to piped water supply (within premises).

Same as production (see [3])

Source: Census Data (Sample size: all UA, cities and towns).

(3) Per Capita Investment Costs (PCIC)

(3.1) Production (3.2) 24/7 Up-gradation (3.3) Distribution Extension

Definition: Costs for source augmentation, treatment, and transmission. PCIC are calculated as project costs over beneficiaries. Project beneficiaries are defined as the number of people that could be served at the level of the per capita production norm (168 lpcd) given the incremental capacity generated by project. Source: 27 JNNURM Project Appraisal Notes; data collection from Karnataka; and CDPs (Sample size 41 obs.)

Definition: Costs of rehabilitating the existing distribution network to achieve 24/7. PCIC are calculated based on a sample of pilot 24/7 project data and a cost simulation. The cost simulation assumes that 50 percent of the existing network is to be replaced, and includes the costs of connection, metering and storage. Source: JNNURM Project Appraisal Notes; data collection from Karnataka, and CDPs (Sample size 33 obs.)

Definition: Costs for distribution, storage, connection and metering. PCIC are calculated based on a cost simulation, which includes the cost of extending the network to connect additional people (50% of the per capita cost of the connected population, as some of the network is already in place), and the cost of connection, metering and storage. Source: CDPs (Sample size 31 obs.)

30

Industrial Water Supply

(1) Service Standards

Industrial production requirements are estimated to increase in line with the average annual growth rate for industry value added over the past 10 years (7 percent per annum).

(2) Investment Components (2.2) Demand Growth 2007-31

It is assumed that 20% of the city-level production capacity is dedicated to industrial customers (based on expert estimate and CDPs). Demand growth is estimated based on annual growth rate of 7 percent.

Sources: JNNURM, CDPs, UN forecasts. (3) Unit Costs (3.1) Production

Unit production costs are estimated based on JNNURM project data.

O&M (Residential and Industrial)

Annual O&M costs are calculated based on the volume of water produced for the served residential population and industrial customers.

Source: O&M unit cost estimates have been made available by sector experts based on recent project data.

31

B.III Urban Water Investment and O&M Requirements

50. Investment requirements for urban water supply range from Rs 2,356 to 3,634 Bn

(2009 prices), or USD 52-81 Bn, as shown in Figure 19. This estimate accounts for both

residential and industrial investment requirements. The point estimate is Rs 2,995 Bn, or USD

67 Bn. Industrial water needs account for 14 percent of total water investment requirements.

Cost variation is roughly the same in both sub-sectors (the coefficient of variation for

distribution is .8 compared to .7 for production). Confidence intervals reflect the variability in

per capita investment costs (PCIC) across projects. The methodology for the computation of

interval estimates for investment requirements is discussed in Annex I. Investment

requirements by sub-sector and cost component are reported in Figure 18.

51. The total PCIC for residential urban water supply (including production and

distribution) ranges from Rs 3,363 to 5,188 (2009 prices). The PCIC for distribution extension

ranges from Rs 2,164 to 3,491 (based on a 90 percent confidence interval), with a point estimate

equal to Rs 2,828. The PCIC for water production ranges from Rs 1,199 to 1,697, with a point

estimate equal to Rs 1,448. The backlog for water production is estimated to be 35 percent of

the base-year urban population; the backlog for water distribution extension is higher, at 52

percent. PCIC and backlog percentages are reported in Figure 20.

52. The PCIC for 24/7 up-gradation is estimated to range from Rs 1,873 to 3,153, with a

point estimate of Rs 2,513 per capita. The backlog for 24/7 up-gradation is estimated at 48

percent, which is equivalent to the piped water supply coverage rate for the year 2006 (See

Figure 20). The costs of 24/7 up-gradation are estimated for the current population only

(backlog), given that all future investment in the distribution network are assumed to be made

based on 24/7 standards.. Investment requirements for 24/7 up-gradation are estimated based

on a cost simulation and a sample of six pilot projects. The per capita costs for the pilot projects

are reported in Table 24 in Annex IV.

53. Demand growth is the main driver of water supply investment requirements. The

largest share of capital expenditure is associated with demand growth, which accounts for 56

percent of the total investment requirements. Demand growth from residential customers

account for 42 percent of total investment requirements, and demand growth for industrial

customers for an additional 14 percent. The second largest cost component is backlog or unmet

demand (for residential customers), which accounts for 34 percent of total requirements. More

specifically, the un-met demand for distribution extension accounts for 17 percent of total

investment requirement; the un-met demand for water production 5 percent, and the backlog

for 24/7 up-gradation 12 percent. Replacement costs account for 10 percent of the total capital

expenditure. Figure 21 shows the share of the total water investment requirements accounted

for by each of the cost components.

54. The profile of the investments is estimated based on the assumption that full

coverage would be achieved by the end of the 15th plan. Investment requirements are

estimated at five year intervals, which correspond to the Planning Commission’s five-year

32

Plans. Investment requirements are estimated to increase over time. For the first phase of the

investment trend, coinciding with the 11th plan of the Planning Commission, investment

requirements are estimated to be Rs 525 Bn (in 2009 prices). The last investment, in the amount

of Rs 718 Bn, coincides with the 15th plan. The investment trend for the water sector is

presented in Figure 22.

55. The investment requirements as a share of GDP decrease over time. The five year

trend of investment requirements for the water sector is calculated as a share of GDP, based on

the assumption that full coverage will be achieved by the end of the 15th plan. Results are

presented in Figure 23. On average, for the period 2007-31, the investment requirements

account for 0.55 percent of GDP per plan (based on a 7 percent real GDP growth rates). The

first investment, coinciding with the 11th plan represents 0.9 percent of GDP. Instead, the last

investment, coinciding with the 15th plan represents 0.32 percent of GDP.

56. Total annual O&M costs are estimated to triple over the period 2007-31 as a result of

the expected increase in coverage. O&M costs are calculated annually. The cost estimation

indicates an increasing trend in annual O&M costs, as shown in Figure 24. Annual O&M costs

for urban water supply are estimated to increase from Rs 135 Bn in 2007 to Rs 420 Bn in 2031,

or from USD 3 to 9 Bn (in 2009 prices), as a result of the expected increase in coverage. The per

capita annual O&M expenditure is estimated at 501 Rs/capita.

57. Distribution extension (based on 24/7 standards) accounts on average for 52 percent

of residential urban water supply investment requirements. Production accounts for the

second largest share (34 percent) followed by 24/7 up-gradation for the connected population

(14 percent). The relatively higher cost share associated with distribution extension is

explained by the fact that distribution costs account for about 70 percent of total capital

expenditure on a per capita basis. In addition, the backlog for distribution extension

(estimated at 52 percent) is significantly higher than the un-met demand for water production

(35 percent).

33

Figure 18: Urban Water Supply Investment Requirements

Residential Water Supply

2006 Backlog (Un-met demand)

Demand Growth

2007-31 Assets replacement

Production [1] Production [3] Production [6]

Total Production

(Residential)

Rs Bn: 160 Rs Bn: 428 Rs Bn: 288 Rs Bn: 875

$Us Million: 3,554 $Us Million: 9,511 $Us Million: 6,390 $Us Million: 19,455

24/7 Up-gradation [5]

Total 24/7 Up-gradation

(Residential)

Rs Bn: 369 Rs Bn: 369

$Us Million: 8,210 $Us Million: 8,210

Distribution

Extension [2]

Distribution Extension [4]

Total Distribution Extension (Residential)

Rs Bn: 522 Rs Bn: 819 Rs Bn: 1,342

$Us Million: 11,608 $Us Million: 18,209 $Us Million: 29,817

Total Backlog (Residential)

Total Demand Growth (Residential)

Total Assets Replacement (Residential)

TOTAL RESIDENTIAL

Rs Bn: 1,052 Rs Bn: 1,247 Rs Bn: 288 Rs Bn: 1,342

$Us Million: 23,371 $Us Million: 27,721 $Us Million: 6,390 $Us Million: 29,817

Industrial Water Supply

Demand Growth

(Production) TOTAL INDUSTRIAL

Rs Bn: 408 Rs Bn: 408

$Us Million: 9,075 $Us Million: 9,075

Total Water Supply (Industrial + Residential)

Total Backlog

(Residential + Industrial)

Total Demand Growth

(Residential + Industrial)

Total Assets Replacement

(Residential + Industrial)

TOTAL RESIDENTIAL+

INDUSTRIAL

Rs Bn: 1,052 Rs Bn: 1,656 Rs Bn: 288 Rs Bn: 2,995

$Us Million: 23,371 $Us Million: 36,796 $Us Million: 6,390 $Us Million: 66,557

34

Figure 19: Urban Water Investment Requirements, 2007-31, Rs Bn (2009 prices)

Note: Confidence Intervals shown above reflect variability in per capita investment costs (PCIC). Specifically, the

actual total investment requirement will be contained within the interval 90 percent of the times, given that actual

PCIC costs may differ from the avereage estimate from the sample of projects.

Figure 20: Per Capita Investment Costs (Rs/capita) and Backlog (%), by Sub-sector

Figure 21:Urban Water Investment Requirements, By Component (Rs Bn)

2,356

2,995

3,634

0

1,000

2,000

3,000

4,000

LOWER BOUND AVERAGE UPPER BOUND

Rs

Bn

, 200

9 p

rice

s

1,448

2,513

2,827

1,697

3,1533,491

1,199

1,8732,164

0

1,000

2,000

3,000

4,000

Production 24/7 Up-gradation

Distribution Extension

PC

IC (R

S/p

ers

on

)

Backlog (24/7 upgradation)

12%

Backlog (production)

5%

Backlog (dist extension)

17%Demand Growth

(Residential)42%

Asset Replacement10%

Demand Growth (Industrial)

14%

35

Figure 22: Urban Water Investment Requirements, by Five-Year Plan (Rs Bn)

Figure 23: Urban Water Investment Requirements, Share of GDP (2007-31)

Figure 24: Annual O&M Costs (Rs Bn) and Production Coverage Trends (%)

74 74 74 74 74

136 136 136 136 136

172 214 246 290 326110 35 39

49 5532 61 61

127127

0

100

200

300

400

500

600

700

800

900

1,000

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

April 2007- March 2012

April 2012- March 2017

April 2017- March 2022

April 2022- March 2027

April 2027- March 2032

Rs

Bil

lio

n (2

00

9 P

rice

s)Industrial - Demand growthResidential -Asset Replacement (production)Residential -Demand GrowthResidential - Backlog (production and dist extension)Residential - Backlog (24/7 Upgradation)

0.3%0.3% 0.2% 0.2%

0.3%0.3%

0.2%0.2%

0.1%

0.2%

0.2%

0.1%

0.1%

0.1%0.1%

0.1%

0.1%

0.9%

0.6%

0.5%0.42%

0.32%

0.55%

0.11%

0.0%

0.3%

0.5%

0.8%

1.0%

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

April 2007 -March 2012

April 2012 -March 2017

April 2017 -March 2022

April 2022 -March 2027

April 2027 -March 2032

Average per plan

Average per year

Industrial Asset Replacement Demand Growth Backlog

0%

20%

40%

60%

80%

100%

-

100

200

300

400

500

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

19

20

20

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

20

31

Co

verage

(%)

Rs

Bn

Annual O&M Coverage (production) %

36

B.IV Capital Works Unit Cost Analysis

Cost drivers

58. City population size and population density are both important cost drivers of urban

water supply investments. The cost model makes an attempt to capture the correlation

between cost drivers and unit costs, by estimating investment requirements by city size class.

While the data sample is not large enough to allow the estimation of investment requirements

with sufficient accuracy for each city size class, significant trends and correlation emerge from

the analysis.

59. The analysis indicates a slightly negative correlation between city population (or city

size) and the unit costs of water production for the entire data sample. The main explanatory

variable is distance to water sources, which tends to be significantly longer in megacities,

compared to other urban localities. In the data sample, the correlation is driven by two

megacities projects, which have significantly higher than average production costs. The first

project in Mumbai involves the construction of a dam to store water and transmit water by a

tunnel. The second project in Chennai involves the construction of a transmission main at a

significant distance from the city (pumping is 14.6 km and gravity main is 34.5 Km). These two

JNNURM water production projects are excluded from the sample as their unit costs are

significantly above the average, and they are not considered representative for urban India.

Although both projects are deleted from the sample due to engineering reasons, one of them

also fits the statistical definition of an outlier (its values is more than three standard deviations

away from the mean). If the two outliers are removed, no correlation is found between city

population and the unit cost of water production. The data also show limited economies of

scale in water production if these two outliers are excluded from the sample. This is in line

with conventional thinking that economies of scale in water production are generally not as

large as in water distribution. (See Figure 25 and Figure 26).

60. The prevailing water source for JNNURM projects is surface water. Only one project

(for Rajkot city) relies on groundwater as the main source of water. The prevalence of surface

water is consistent with the most recent trends in urban India, as surface water is overtaking

groundwater as the major source of water supply across urban areas, because of declining

groundwater levels.

61. Population density is the main cost driver for water distribution costs. Small cities have

lower population density and therefore higher per capita distribution costs, compared to large

cities. The per capita length of the distribution network calculated based on CDP data is

significantly higher in small and medium towns compared to large cities. As a results, per

capita investment costs increase significantly from Class I.A to Class IV+ cities, although the

magnitude of the increase cannot be estimated with sufficient accuracy given the limited

number of observations. (See Figure 27).

37

62. The main cost driver that explains variation in O&M costs is the water head, as higher

heads imply higher power charges, which are estimate to account for about 40 percent of total

O&M costs based on a sample of project data. Maintenance costs are estimated to account for

about 10 percent of total O&M costs. Also, large cities are found to have higher unit O&M costs

than the average: O&M costs are estimated to vary from 12 Rs/m3 in Class I.A to 3 Rs/m3 in

Class IV+ (see Table 4 in Annex I). The trend is mainly explained by the fact that large cities

tend to rely on more distance sources of water supply, compared to other urban localities.

Sensitivity analysis on service standards

63. A sensitivity analysis is conducted to assess the impact of changing service standards

on project costs. The main standards in the model that have a direct impact on costs are (a) the

per capita production norm and (b) the supply option (piped water supply with private

connections).

64. Per capita production norm. Assuming a lower per capita production norm for small and

medium towns is shown to have only a marginal impact on total investment costs – for

example, lowering the per capita production norm from 168 to 88 lpcd for towns with less than

50,000 inhabitants (Class III and IV+) would only marginally decrease total investment

requirements, from Rs 2,995 Bn to 2,939 Bn (see Figure 28). This is explained by the fact that a

lower per capita production standard would affect the cost for water production (which

account for about 30 percent of total investment costs), but not for water distribution. A lower

per capita consumption norm for small and medium towns wouldn’t affect the optimal

distribution system capacity for the following two reasons. First, the distribution network is

characterized by economies of scale, mainly related to the cost of excavating and re-surfacing

the roads. Given the large economies of scale, the distribution system is generally over-

designed. For example, if per capita water consumption in a small town is 70 lpcd, the optimal

design solution may be to build a distribution network for 100 lpcd to achieve economies of

scale. Second, conservative assumptions have been made to estimate the mix of pipes required

for the extension of the distribution network in small and medium towns, based on

information reported by the towns themselves as part of the data collection and expert advice.

The baseline model assumes an average mix of pipes of 250-350mm diameter, with a minimum

size of 100mm diameter. Based on a cost simulation, it is estimated that in a town of 50,000

inhabitants, a distribution network with a mix of pipes of 250-350 mm diameter would deliver

a daily per capita consumption in the range of 70-135 lpcd. Assuming a lower standard of per

capita consumption would therefore not affect the mix of pipes and the cost estimates for water

distribution.

65. Supply option. The second main standard incorporated in the model is the supply option

(piped water supply with private connections). A full sensitivity analysis has not been

conducted to estimate the impact on costs of adopting standposts as a service standard rather

than private connection in small towns (for a given level of water consumption), because of

limited data available on the cost of standposts. The savings associated with standpipes are

related to distribution costs, and more specifically to the costs of house connection and tertiary

38

distribution. Considering that small towns (with less than 50,000 inhabitants) account for only

19 percent of urban India population based on 2009 estimates, the impact of a lower

distribution standard in small towns is likely to be modest.

Figure 25: Unit Production Costs (Rs/m3) and City Size (2009 prices)

Notes: Two projects excluded from the sample for engineering reasons (project not representative) and

statistical reasons (outlier with value more than 3 standard deviations above the mean).

Figure 26: Unit Water Production Costs (Rs/m3): Economies of Scale (2009 prices)

Notes: Two projects excluded from the sample for engineering reasons (project not representative) and

statistical reasons (outlier with value more than 3 standard deviations above the mean).

0

10,000

20,000

30,000

40,000

50,000

- 2 4 6 8 10 12 14 16 18

Un

it c

ost

(R

s/m

3)

City size (m)

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

- 100 200 300 400 500 Un

it c

ost

(R

s/m

3)

Incremantal capacity (MLD)

39

Figure 27: Per Capita Distribution Costs (Rs/capita) and City Size (2009 Prices)

Figure 28: Sensitivity Analysis: Water Per capita Production Norm

0

2,000

4,000

6,000

8,000

10,000

12,000

- 2 4 6 8 10 12 14

Pe

r C

apit

a C

ost

s (

Rs/

cap

ia)

City size (m)

3,635 3,570

2,995 2,939

2,356 2,308

0

1,000

2,000

3,000

4,000

Production norm 168 lpcd (City Class III and IV+) Production norm 88 lpcd (City Class III and IV+)

Assumption 1 Assumption 2

Rs

Bn

, 20

09

Pri

ces

40

C. Urban Sewerage Services

C.I Urban Sewerage Service Standards

DEMAND SUPPLY

Per capita sewerage

generation (2007-31)

108 lpcd Supply option

(collection)

Sewerage network

Target coverage 100%

Assets’ economic life 30 years

66. Urban sewerage investment requirements are estimated based on the target of full

network and treatment coverage. Per capita sewerage generation is assumed at 108 lpcd,

which is equivalent to 80 percent of per capita water demand. The norm is considered

appropriate for middle-income countries with an average per capita water demand of 135 lpcd.

Hence, no growth is assumed in sewerage generation on a per capita basis over the period

2007-31. The economic life of the assets for both network and sewerage is assumed to be 30

years. This implicitly assumes an efficient operation and maintenance of the assets. Should the

assets not be properly maintained, the economic life of the assets would shorten significantly.

67. A cross-country comparison is conducted to cross-check the targets vis-à-vis service

levels in comparable countries. The percentage of urban India population with access to

sewerage network is 33 percent based on 2001 population census data. Access varies

significantly across city size classes, from 53 percent in the megacities to 14 percent in small

towns with less than 20,000 inhabitants (see Figure 29). On average, sewerate network

coverage for urban India (33 percent) is significantly below the average for lower-middle

income countries, estimated at 56 percent for a sample of 15 countries, based on UNSTATS

data. Sewerage treatment coverage in urban India is estimated at 28 percent, slightly below the

36 percent average for lower-middle income countries, based on a sample of 13 countries. (See

Figure 30 and Figure 31). On average, the cross-country comparison indicates that coverage

rates for urban sewerage are significantly below access rates for urban piped water supply

across all countries’ income groups. The average sewerage coverage rate for high income

countries is 77 percent for network and 70 percent for treatment based on a sample of 38 and 37

countries respectively. These results are in contrast with the almost universal coverage in

piped water supply in high income countries (see Figure 13).

68. The model assumes an increase in sewerage coverage in urban areas from 33 and 28

percent for network and treatment respectively to 100 percent over the period 2007-31. For the

41

simulation of the investment profile, the assumption is made that full coverage would be

achieved by the end of the 15th Plan.

42

Figure 29: Urban Sewerage Network Coverage in India, by City Size Class

Source: 2001 Census. Notes: Sample size (number of urban centers) in parenthesis.

Figure 30: Urban Sewerage Network Coverage - Selected Countries (2000-07)

Source: UNSTATS; 2001 Census for India. Notes: Sample size (number of countries) in parenthesis.

Figure 31: Urban Sewerage Treatment Coverage- Selected Countries (2000-07)

Source: UNSTATS; CDPs for India. Notes: Sample size (number of countries) in parenthesis.

53%46%

28%20%

15% 14%

33%

0%

20%

40%

60%

Class I.A Class I.B Class I.C Class II Class III Class IV+ Weighted Average

(7) (27) (360) (404) (1,164) (2,415) (4,377)

77

55

6860

4856

9887 83

46

33

15 19

0

20

40

60

80

100

High Income

Upper Middle Income

Mexico (2005)

South Africa (2007)

Brazil (2006)

Lower Middle Income

Jordan (2004)

Morocco (2007)

Armenia (2006)

China (2004)

India (2001)

Paraguay (2007)

Low Income

(38) (23) . (15) . (5)

Upper Middle Income Lower Middle Income .

70

43

57

3526

36

80

52

2834 33

26

5

0

20

40

60

80

100

High Income

Upper Middle Income

South Africa (2007)

Mexico (2005)

Brazil (2006)

Lower Middle Income

Morocco (2007)

Jordan (2004)

India Armenia (2006)

China (2004)

Iraq (2005)

Low Income

(37) (20) . (13) . (4)

Upper Middle Income Lower Middle Income .

43

C.II Sewerage Cost Model Methodology

69. This Section discusses the overall methodological approach for the cost estimation. A

summary of the approach is presented in Figure 33. A detailed step-by-step description of the

methodology is provided in Annex I.

70. The methodology for estimating investment requirements for urban sewerage consists

of four building blocks: (1) service standards, which have been described in detail in a previous

section; (2) investment components, (3) cost drivers (city population and density) and (4) Per

capita investment costs (PCIC). Urban sewerage investment requirements are calculated for

residential customers only.

There are three main investment components. The first investment component

corresponds to the backlog or un-met demand, defined as the percentage of the base year

population that is un-served, given the chosen service standards. The second component

corresponds to demand growth, defined as the population that will require service over

the period 2007-31. Finally, the last component corresponds to assets replacement, which

is the cost of replacing outdated assets.

Per capita investment costs (PCIC) are calculated based on project data. Two separate

PCIC are estimated for (a) network and (b) treatment.

The correlation between city size and population density and PCICs is explored by

estimating PCICs by city size class.

71. Investment requirements are calculated as the product of each one of the investment

components times the PCIC of the corresponding sub-sector (network and treatment). The

overall methodological approach is depicted in the diagram presented in Figure 32 below. The

diagram presents a breakdown of investment requirements based on sub-sector (network and

treatment) and investment component (backlog, demand growth and assets replacement). The

investment requirements include: total investment requirements to close the backlog, or un-

met demand [1+ 2]; total investment requirements for demand growth [3+4]; and assets

replacement costs [5]. Investment requirements are estimated as a band based on a 90 percent

confidence interval for PCICs.23

72. O&M costs are calculated on an annual basis for the served residential population.

23 There is a one-to-one relationship between PCICs and total investment requirements – i.e. a 10 percent

increase in PCICs leads to a 10 percent increase in total investment requirements.

44

Figure 32: Sewerage Cost Model Methodology

45

Figure 33: Sewerage Cost Model Methodology – Building Blocks

Investments

(1) Service Standards

Supply: 100% target coverage; Demand: per capita sewerage generation of 108 lpcd (80% of per capita water consumption norm)

(2) Investment Components

(2.1)

2006 Backlog (un-met demand)

(2.2) Demand Growth

2007-2031 (2.3) Assets Replacement

Network [1] Network [3] Network [5]

Definition: % of base year urban population without access to wastewater network. Source: Census Data (Sample size: all UA, cities and towns)

Definition: Demand from incremental urban population over the period 2007-2031. Source: Forecasted yearly by applying UN population growth rates to the 2001 Census population.

Definition: Assets are assumed to have a 30 year economic life prior to replacement.

Treatment [2] Treatment [4] Treatment [5]

Definition: % of base year urban population without access to wastewater treatment. Source: City Development Plans (CDPs) (Sample size 80 obs.)

Same as for Network (above).

Same as for Network (above).

(3) Per Capita Investment Costs (PCICs)

(3.1) Network (3.3) Treatment

Definition: Estimated using the formula PCIC = total sub-sector project cost / project beneficiaries. Project beneficiaries are defined as the number of people that can be served by the project given the level of the per capita norm (108 lpcd) and the incremental capacity generated by project.

Definition: Same as for network (left)

Source: 47 JNNURM Project Appraisal Notes complemented by data collection in Karnataka, Tamil Nadu, and Andhra Pradesh (Sample size 113 projects).

Source: Same as for network (left) (Sample size 79 projects).

A

O&M

1

Annual O&M costs are calculated based on wastewater generation for the served residential population. Source: O&M unit cost estimates have been made available by sector experts based on recent project data.

V

46

C.III Urban Sewerage Investment and O&M Requirements

73. Total investment requirements for urban sewerage range from Rs 1,913 to 2,544 Bn

(2009 prices), or USD 43-57 Bn. The point estimate for the investment requirements is Rs 2,229

Bn, or USD 50 Bn, as shown in Figure 35. This value accounts only for residential investment

requirements. The sub-sector with the highest cost variation is network (the coefficient of

variation is 1 compared to .7 for treatment). The confidence intervals reflect the variability in

per capita investment costs (PCIC) across projects. The methodology for the computation of

interval estimates for investment requirements is discussed in Annex I. Investment

requirements by sub-sector and cost components are reported in Figure 34.

74. Network investment accounts for 66 percent of total investment requirements. The

total PCIC for urban sewerage is estimated to range from Rs 3,101 to 4,124. The PCIC for

network accounts for 66 percent of total costs on a per capita basis, ranging from Rs 2,019 to

2,727 with a point estimate equal Rs 2,373 per capita. The PCIC for treatment ranges from Rs

1,082 to 1,398, with a point estimate equal Rs 1,240 per capita (in 2009 prices).The backlog for

network is estimated at 67 percent, the backlog for treatment is only slightly higher at 72

percent. PCIC and backlog percentages are reported in Figure 36.

75. Demand growth accounts for 47 percent of total investment requirements. Figure 37

shows the share of the total sewerage investment requirements accounted for by each of the

cost components. The largest share of the cost is associated with demand growth (47 percent of

total). The second largest cost component is the backlog or un-met demand, which accounts for

39 percent of the sewerage costs. Replacement costs account for 14 percent of the sewerage

investment costs.

76. Investment costs are estimated at five year intervals, in line with the Planning

Commission’s five-year Plans. The investment trend for the sewerage sector is presented in

Figure 38. Investment requirements are estimated to increase over time. The first phase of the

investment trend coincides with the 11th Plan of the Planning Commission, and the investment

is estimated to be in the amount of Rs 374 Bn, or USD 8 Bn. The last investment, in the amount

of Rs 534 Bn (USD 12 Bn), coincides with the 15th Plan.

77. On average, for the period 2007-31, investment requirements account for 0.4 percent

of GDP per plan (based on a 7 percent real GDP growth rate). The five year trend of

investment requirements for the sewerage sector is calculated as a share of GDP. Results are

presented in Figure 39. The investment requirements as a share of GDP decrease over time.

The first investment, coinciding with the 11th Plan represents 0.61 of GDP. The last investment,

coinciding with the 15th Plan represents 0.24 percent of GDP.

78. Annual O&M costs for the sewerage sector are estimated to increase exponentially

over the period 2007-31 as a result of increase in coverage. O&M costs are calculated annually

based on per capita sewerage generation and coverage in any given year. As shown in Figure

47

40, annual O&M costs are forecasted to increase from Rs Bn 8 (USD 0.18 Bn) in 2007 to Rs Bn 64

(USD 1.4) in 2031. Per capita annual O&M costs are estimated at Rs 102.

Figure 34: Urban Sewerage Investment Requirements

Investments (Residential)

2006 Backlog (Un-met demand)

Demand Growth

2007-31 Assets Replacement

Network [1] Network [3] Network [5] Total Network

Rs Bn: 559 Rs Bn: 700 Rs Bn: 214 Rs Bn: 1,473

$Us Million: 12,423 $Us Million: 15,549 $Us Million: 4,765 $Us Million: 32,737

Share of Total 66%

Treatment [2] Treatment [4] Treatment [5] Total Treatment

Rs Bn: 314 Rs Bn: 356 Rs Bn: 85 Rs Bn: 756

$Us Million: 6,987 $Us Million: 7,917 $Us Million: 1,895 $Us Million: 16,790

Share of Total 34%

Total Backlog

Total Demand Growth

Total Assets

Replacement TOTAL

Rs Bn: 873 Rs Bn: 1,056 Rs Bn: 300 Rs Bn: 2,229

$Us Million: 19,401 $Us Million: 23,466 $Us Million: 6,660 $Us Million: 49,527

Share of Total 39% Share of Total 47% Share of Total 13%

48

Figure 35: Urban Sewerage Investment Requirements,

2007-31 (2009 prices), (Rs Bn)

Note: Confidence Intervals shown above reflect variability in per capita investment costs (PCIC).

Figure 36: Per Capita Investment Costs (Rs/capita) and Backlog (%), by Sub-sector

Figure 37: Urban Sewerage Investment Requirements, By Investment Driver, (Rs Bn)

1,913

2,229

2,544

0

500

1,000

1,500

2,000

2,500

3,000

LOWER BOUND AVERAGE UPPER BOUND

Rs

Bn,

200

9 Pr

ices

67%72%

0%

25%

50%

75%

Network Treatment

Ba

ck

log

(%

)

Backlog39%

Demand Growth47%

Assets Replacement

14%

49

Figure 38: Urban Sewerage Investment Requirements, 5 year trends, Rs Bn (2009 Prices)

Figure 39: Urban Sewerage Investment Requirements, Share of GDP

Figure 40: Annual Urban Sewerage O&M Costs (Rs Bn) and Coverage Trends (%)

175 175 175 175 175

151 182 209 242 27249

4049

7487

0

100

200

300

400

500

600

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

April 2007- March 2012

April 2012- March 2017

April 2017- March 2022

April 2022- March 2027

April 2027- March 2032

Rs

Bn

(2

00

9 P

rice

s)Assets Replacement Demand growth Backlog

0.29%0.22%

0.15% 0.11% 0.08%0.17%

0.25%

0.22%

0.18%0.15%

0.12%

0.19%

0.08%

0.05%

0.04%

0.05%

0.61%

0.49%

0.38%0.31%

0.24%

0.41%

0.08%

0.00%

0.25%

0.50%

0.75%

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

April 2007 -March 2012

April 2012 -March 2017

April 2017 -March 2022

April 2022 -March 2027

April 2027 -March 2032

Average per plan

Average per year

Assets Replacement Demand Growth Backlog

8

12 14 16 18 20 21 23 25 27 29 32 34 36 38 40 42 45 47 49 52 54 57 59 62 64

0%

20%

40%

60%

80%

100%

-

10

20

30

40

50

60

70

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

19

20

20

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

20

31

Co

verage

A

nn

ual

O&

M (R

s B

n)

Annual O&M (Rs Bn)

Network coverage (%)

50

C.IV Capital Works Unit Cost Analysis

Cost drivers

79. The results indicate that some economies of scale are present in both network and

treatment sub-sectors. The unit costs are negatively correlated with the incremental project

capacity, with a negative correlation of 35 percent (See Figure 41). The cost model makes an

attempt to capture the correlation between unit costs and cost drivers, such as city population

size and population density, by estimating investment requirement by city size class. While

the data gathered is not large enough to estimate investment requirements with sufficient

accuracy for each city size class, significant correlation emerge from the analysis. Larger and

more densely populated cities tend to have lower costs on a per capita basis for sewerage

network than small, low-density towns. The per capita network of sewerage collection almost

doubles from Class I.A to Class IV+.

80. It is worth noting that the sewerage cost model is based on project cost estimates rather

than actual costs. This may have led to an under-estimation of the per capita costs, as cost

escalation at contract award and implementation is reported to be an an issue in the sector

(based on a sample of sewerage projects in Karnataka, costs at contract award are estimated to

be about 20 percent higher than costs at project design stage). The scope for under-estimation is

more limited in the water sector, compared to the sewerage sector –water distribution costs

which account for the bulk of water capital expenditure are estimated based on a cost

simulation, rather than on project data.

Sensitivity analysis

81. A sensitivity analysis is conducted to assess the impact of assuming different standards

on total investment requirements. As in the case of the water sector, a sensitivity analysis is

carried out to assess the impact of lowering the per capita sewerage generation norm for small

towns with less than 50,000 inhabitants. A reduction of the norm from 108 lpcd to 70 lpcd

would lead to a negligible decline in the point estimate for the overall investment requirements

from Rs 2,229 Bn to Rs 2,030 Bn (See Figure 42).

82. Sewerage network is the supply standard adopted for the cost estimation. Septic tanks

are the lower supply standard considered for the sensitivity analysis. The capital expenditure

of a septic tank is in the range of Rs 12,000 – 15,000. An additional per capita cost of Rs 1,000 is

required for the proper disposal of effluents. The overall per capita cost of septic tanks is

therefore Rs 3,400 -4,000 (based on an average household size of five). Septic tanks also require

cleaning every alternate year at a cost of about Rs 1,000, equivalent to an annual per capita

O&M cost of about Rs 500.

83. Based on the results of the cost model, septic tanks (with a per capita cost of Rs 3,400-

4,000) are an economical option only for Class II, III and IV+ cities (i.e. cities and towns with

51

population below 100,000). The cost savings are relatively limited on a per capita basis.24 In

addition Class II-III-IV+ account for only 28 percent of the urban population (as of 2009).

Assuming septic tanks as a service standard in Class II-III-IV+ cities is therefore not expected to

have a significant impact on the overall urban investment requirements for the sewerage

sector.

Figure 41: Treatment Unit Costs and Incremental Capacity (MLD)

Figure 42: Sensitivity Analysis: Changes in Sewerage Per capita Production Norm

24 The limited cost savings may be partially due to the possible under-estimation of sewerage network

costs mentioned in Para. 77

-

5,000

10,000

15,000

20,000

25,000

- 100 200 300 400 500 600 700 800

Un

it c

ost

(R

s/m

3)

Incremental capacity (MLD)

2,5442,330

2,2292,030

1,9131,730

0

1,000

2,000

3,000

Production Norm 108 lpcd (City Class III and IV+) Production Norm 70 lpcd (City Class III and IV+)

Assumption 1 Assumption 2

Rs

Bn

, 20

09

Pri

ces

52

D. Municipal Solid Waste

D.I Municipal Solid Waste Service Standards

DEMAND SUPPLY

Per capita waste

generation (2006)

02-06 Kg/cap/day Target C&T coverage 100% of solid waste

generation

Per capita annual

growth rate

1.3 percent Target compost share 65%-50% of MSW

generation

Target landfill share 30-45% of MSW

generation

Assets’ economic life 10 yrs (C&T), 5 yrs

(landfill at half of

original unit costs)

84. The cost models is built on the following demand and supply standards:

85. Per capita MSW generation is estimated to range between 0.2 to 0.6 Kg/capita/day

across Indian cities and depending on city size (See Figure 64 in Annex IV).25 On average per

capita waste generation is estimated to increase at 1.3 percent per annum on a per capita basis

over the period 2007-31. The assumption is in line with references provided in the empirical

literature.26 Coverage for collection and transportation (C&T) is estimated to increase from the

current level of 60 percent to 100 percent.

86. A cross-country comparison is conducted to benchmark waste generation patterns

across a number of comparable countries. The per capita waste generation for Indian cities that

is reference in the literature is significantly below the average for comparable countries (see

Figure 43 and Figure 62 in Annex VI ). This implies that solid waste generation is expected to

increase significantly as India’s process of economic and demographic transformation unfolds.

The benchmarking also indicates that the urban coverage rate for C&T (estimated at 60 percent

based on CDPs) is below the expected value for a sample of comparable countries (see Figure

44 and Figure 63 in Annex VI).

87. The prevailing solution for waste processing in Indian cities is composting, while

sanitary disposal is virtually non-existent, with the exception of a limited number of cities. The

international comparison suggests that the percentage of processed and landfill waste varies to

25

Estimated are based on 1995 NEERI data, as reported in 3i Network (2006), ‚India Infrastructure Report‛. 1995

data are updated to the base year of the model (2006) assuming a 1.3 percent annual growth rate in solid waste

generation. 26 See for example Shekdar, A.V., 1999. ‚Municipal solid waste management – the Indian perspective‛. Journal of

Indian Association for Environmental Management 26 (2), 100–108).

53

a significant extent across countries. The type of processing also depends on local conditions.

Incineration is for example the most widespread solution in countries such as Japan where

land is extremely scarce (See Figure 45). On average, the most widespread solution in both low

and middle income countries is sanitary disposal in landfill sites.

88. The target compost share for the purpose of the estimation is assumed to range from 65

to 50 percent of solid waste generation. The assumption is made that the sector will gradually

move from the prevailing target compost share of about 65 percent to 50 percent within a

period of 10 years. Fifty percent is assumed to be the optimal target share for composting, as it

is broadly in line with the share of compostable waste based on available empirical evidence.

The average compostable share ranges significantly across countries, from 20 to 80 percent,

based on UNSTAT data for a sample of countries (see Figure 46). In India, it is estimated that

35 to 55 of municipal waste material is organic waste, which can be converted into useful

compost.27 The current widespread Indian practice of mixed composting (i.e. the composting of

un-segregated waste) has led to a much higher target share of composting, which is estimated

at 65 percent. Mixed composting is however not considered sustainable in the long-term. The

assumption is therefore made in the model that the target compost share would decline over

time to levels that are in line with the share of compostable waste.

89. The target landfill share is assumed to range from 30 to 45 percent of total solid waste

generation. The assumption is made that the sector will move from the prevailing target

landfill share of 30 percent to 45 percent. While very few cities safely dispose of MSW, the

construction of landfill sites is in the pipeline in a number of cities. It is therefore expected that

the optimal landfill share will increase over time, in spite of the land scarcity. Alternative

target rates can be specified as model assumptions, to assess the impact of different solid waste

policy options on investment requirements. For example, the model allows testing the cost

savings associated with increase in recycling, which would reduce the target compost and

landfill share.

90. The following assumptions are embedded in the cost model with respect to the

economic life of the assets: C&T assets are expected to have an economic life of ten years,

while the replacement costs for landfill are estimated at five year intervals, in line with

information provided by JNNURM project data, which cover landfill capital expenditure for a

planning horizon of five years.28 Replacement costs for composting are not included, as they

are expected to be covered by compost sales.

27

See for example World Bank (2008). ‚Improving Municipal Solid Waste Management in India‛. Washington DC. 28 The replacement costs for landfill are estimated at 50 percent of the original unit costs, based on the assumption

that certain fixed costs (e.g. road to the landfill sites) would only be incurred once.

54

Figure 43: Municipal Waste Generation vs.

GNI per capita (1995)

Figure 44: Population Served by Waste

Collection vs. GNI per capita (2000-07)

Source: World Bank (1999). Source: UNSTATS; CDPs for India

Figure 45: Treatment and Disposal of Municipal Solid Waste (2000-07)

Source: UNSTATS.

India

0

0.2

0.4

0.6

0.8

1

1.2

0 1,000 2,000 3,000 4,000Was

te G

en

era

tio

n (

kg/c

ap/d

ay)

GNP per capita ($)

India

20

40

60

80

100

0 25,000 50,000 75,000

Po

pu

lati

on

Se

rve

d (

%)

GNI per capita ($)

0

20

40

60

80

100

Au

stra

lia (

20

03

)

Un

ited

Sta

tes

(20

05

)

Ko

rea,

Rep

. (2

00

4)

Can

ada

(20

04

)

Jap

an (

20

03

)

Alg

eria

(2

00

3)

Ch

ile (

20

06

)

Mex

ico

(2

00

6)

Lith

uan

ia (

20

07

)

Po

lan

d (

20

07

)

Co

lom

bia

(2

00

5)

Arm

enia

(2

00

7)

Mo

rocc

o (

20

00

)

Yem

en (

20

07

)

Tun

isia

(2

00

4)

Syri

an A

. Rep

. (2

00

3)

Ch

ina

(20

03

)

Uga

nd

a (2

00

6)

Mad

agas

car

(20

07

)

High income Upper middle income Lower middle income Low income

Unknown (%) Composted (%) Recycled (%) Incinerated (%) Landfilled (%)

55

Figure 46: Composition of Urban Solid Waste 1995 (Asian Countries)

Source: World Bank (1999). Notes: Classification based on 1995 GNP per capita.

0

20

40

60

80

100Si

nga

po

re

Jap

an

Ho

ng

Ko

ng

Ind

on

esia

Ph

ilip

pin

es

Thai

lan

d

Mal

aysi

a

Nep

al

Ban

glad

esh

Mya

nm

ar

Lao

PD

R

Ind

ia

Sri L

anka

Ch

ina

High Income Middle Income Low Income

Others Metal Glass Plastic Paper Compostables

56

D.II Municipal Solid Waste Methodology

91. This Section presents the overall methodological approach for the estimation of

investment and O&M requirements for MSW. A summary of the approach is presented in

Figure 48. A detailed step-by-step description of the methodology is provided in Annex I.

92. The methodology for estimating investment requirements consists of four building

blocks: (1) service standards, which have been described in detail in the previous section; (2)

investment components, (3) cost drivers (city population size and density) and (4) unit costs.

There are three main investment components. The first investment component

corresponds to the backlog or un-met demand, defined as the percentage of the base

year waste that is not collected & transported, properly processed and disposed. The

second component corresponds to demand growth, defined as the incremental volume

of waste that will need to be collected & transported, processed and disposed over the

period 2007-31. Finally, the last component corresponds to assets replacement, which is

the cost of replacing outdated assets.

Unit costs are estimated based on project data. Three separate unit costs are estimated

for (a) C&T; (b) processing (composting) and (c) disposal.

The correlation between unit costs and city population size and population density is

assessed by estimating unit costs by city size class.

93. Investment requirements are calculated as the product of each one of the investment

components times the unit costs of the corresponding sub-sector (C&T, processing and

disposal). Overall, the methodological approach is depicted in the diagram presented in Figure

47 below. The diagram presents a breakdown of investment requirements based on cost

component (C&T, processing and disposal) and investment component (backlog, demand

growth and asset re-placement). The investment requirements include: total investment

requirements for the backlog [1+ 2+ 3]; total investment requirements for demand growth

[4+5+6]; and assets replacement costs [7]. Investment requirements are estimated as a band

based on a 90 percent confidence interval for the unit costs.29

94. O&M costs are calculated on an annual basis based on the total solid waste collected,

transported and disposed.

29 There is a one-to-one relationship between unit costs and total investment requirements – i.e. a 10

percent increase in unit costs leads to a 10% increase in total investment requirements.

57

Figure 47: MSW Cost Model Methodology

58

Figure 48: MSW Cost Model Methodology – Building Blocks

Investments

(1) Service Standards

Supply: 100% target C&T, 65-50% target compost share; 30-45% target landfill share,

Demand: 0.2-0.6 Kg/capita/day solid waste generation, 1.3% annual growth rate

(2) Investment Components

(2.1)

2006 Backlog (un-met demand)

(2.2) Demand Growth

2007-2031 (2.3) Assets Replacement

Collect & Transport [1] Collect & Transport [4] Collect & Transport [7]

Definition: percent of base-year municipal waste generation that is not collected and transported. Source: City Development Plans (CDPs) (Sample size 51 obs.)

Definition: Incremental municipal waste generation to be collected and transported over the period 2007-2031. Source: Estimated based on UN population forecasts, annual per capita growth in MSW generation.

Definition: Assets are assumed to have a 10 year economic life prior to replacement.

Processing [2] Processing [5]

Definition: percent of base-year urban waste generation that is not properly treated.

Definition: Incremental municipal waste generation to be processed based on optimal compost share (2007-2031). Source: Same as C&T.

There are no assets replacement costs for processing because these costs are generally funded by compost sale revenues.

Source: City Development Plans (CDPs) (Sample size 49 obs.)

Disposal [3] Disposal [6] Disposal [7]

Definition: percent of base-year urban waste generation that is not properly disposed. Source: Equivalent to the entire Indian urban population (virtually no landfills in India).

Definition: Incremental municipal waste generation to be disposed based on optimal landfill share (2007-2031). Source: Same as C&T.

Definition: Assets are assumed to have a 5 year life prior to replacement. Assets replacement costs are estimated at 50% of original unit costs.

(3) Unit Costs

(3.1) Collect & Transport (3.2) Processing (3.3) Disposal

Definition: Estimated dividing the total project costs for C&T by the volume of waste generation in the project design year.

Definition: Estimated dividing the total project processing cost over the volume of waste processing capacity of the compost plant.

Definition: Estimated dividing the total landfill project costs over the estimated volume of waste

disposed in the project design year.

Source: 22 JNNURM Project Appraisal Notes (PANs); data collection from Karnataka; (Sample size 40 obs.)

Source: Same as for C&T (left) (Sample size 27 obs.)

Source: Same as for C&T (left) (Sample size 33 obs.)

O&M Z

Annual O&M costs are calculated based on total solid waste collected &transported and disposed (O&M costs for treatment are not included as they are generally covered by compost revenues). Source: O&M unit cost estimates have been made available by sector experts based on recent project data.

V

59

D.III Municipal Solid Waste Sector Investment and O&M Requirements

95. MSW investment requirements are in the range of Rs 368-607 Bn. The point estimate

for the MSW sector is Rs 487 Bn (in 2009 prices), or USD 11 Bn. The 90 percent confidence

interval for the investment requirements ranges from Rs 368 Bn to Rs 607 Bn (USD 8.2 to 13.5

Bn), as shown in Figure 50. The processing sub-sector has the largest cost variation, followed

by disposal; while C&T has the smallest cost variation. The methodology for the computation

of interval estimates for investment requirements is discussed in Annex I; confidence intervals

reflect the variability in per capita investment costs (PCIC) across projects. Investment

requirements by sub-sector and cost components are reported in Figure 49Figure 34.

96. For the period 2007-31, the average PCIC for MSW is estimated to range from Rs 323

to Rs 518. As shown in Figure 51, the PCIC for the solid waste sector is expected to increase

over time as a result of growth in per capita waste generation. The PCIC for C&T exhibits an

increasing trend, with values ranging from Rs 117 per capita in 2007 to Rs 159 per capita in

2031, and an average value of Rs 137 per capita. The PCIC for disposal is also increasing over

time. The average PCIC for disposal over 2007-31 is Rs 152 per capita; the value for 2007 is Rs

96 per capita, and the value for 2031 is Rs 187 per capita. The PCIC for treatment is somewhat

flatter overtime, with an average value of Rs 131 per capita. This is due to the fact that the

target share of per capita solid waste generation that is expected to be sent to compost plant is

assumed to decline over time from 65 to 50 percent.

97. Asset replacement is the main investment component. Figure 52 shows the share of

the total sewerage investment requirements accounted for by each of the cost components. The

largest share of investment requirements is associated with assets replacement, which accounts

for 42 percent of the total investment requirements. The second largest cost component is

demand growth, which accounts for 39 percent of total capital expenditure requirements.

Backlog accounts for the remaining 19 percent of MSW capital expenditure.

98. The disposal sub-sector accounts for the largest share of investment requirements.

The disposal sub-sector accounts for 42 percent of total capital expenditure, followed by C&T

(37 percent) and processing (21 percent). Disposal has the highest backlog (100 percent),

followed by processing (93 percent) and C&T (41 percent). See Figure 51.

99. The investment trend is estimated based on the assumption that full coverage would

be achieved by the end of the 15th Plan. Investment requirements are expected to increase over

time. The first phase of the investment trend coincides with the 11th Plan of the Planning

Commission, and the investment is estimated to be in the amount of Rs 62 Bn (in 2009 prices).

The last investment, in the amount of Rs 152 Bn, coincides with the 15th Plan. The investment

trend for the solid waste sector is presented in Figure 53.

100. Investment requirements as a share of GDP decrease over time. The five year trend of

investment requirements for the solid waste sector is computed as a share of GDP, based on

the assumption of 7 percent real GDP growth. On average, for the period 2007-31, the

60

investment requirements account for 0.08 percent of GDP per plan. The first investment,

coinciding with the 11th Plan represents 0.10 percent of GDP. The last investment, coinciding

with the 15th Plan represents 0.07 percent of GDP. Results are presented in Figure 54.

101. Annual O&M costs are estimated to increase over time as a result of the increase in

coverage. There is an increasing trend in annual O&M costs, as shown in Figure 55. Annual

O&M costs for the MSW sector are estimated to increase from Rs 31 Bn (USD 0.7 Bn) in 2007 to

Rs 124 Bn (USD 2.8 Bn) in 2031 (in 2009 prices). The per capita annual O&M is estimated at Rs

190.

Figure 49: MSW Investment Requirements

Investments (Residential)

2006 Backlog (Un-met demand)

Demand Growth

2007-31 Assets Replacement

Collect & Transport [1] Collect & Transport [4] Collect & Transport [7]

Total Collect & Transport

Rs Bn: 14 Rs Bn: 58 Rs Bn: 109 Rs Bn: 182

$Us Bn: 315 $Us Bn: 1,297 $Us Bn: 2,422 $Us Bn: 4,034

Share of Total 37%

Processing [2] Processing [5] Total Processing

Rs Bn: 51 Rs Bn: 54 Rs Bn: 106 $Us Bn: 1,139 $Us Bn: 1,206 $Us Bn: 2,345

Share of Total 22%

Disposal [3] Disposal [6] Disposal [7] Total Disposal

Rs Bn: 26 Rs Bn: 76 Rs Bn: 98 Rs Bn: 200

$Us Bn: 508 $Us Bn: 1,698 $Us Bn: 2,169 $Us Bn: 4,453

Share of Total 41%

Total Backlog Total Demand Growth Total Assets

Replacement TOTAL Rs Bn: 92 Rs Bn: 189 Rs Bn: 207 Rs Bn: 487 $Us Bn: 2,040 $Us Bn: 4,201 $Us Bn: 4,592 $Us Million: 10,832

Share of Total 19% Share of Total 39% Share of Total 42%

61

Figure 50: MSW Investment Requirements, 2007-31 (2009 prices), (Rs Bn)

Note: Confidence Intervals shown above reflect variability in per capita investment costs (PCIC).

Figure 51: Per Capita Investment Costs (Rs/capita) and Backlog (%), by Sub-sector

m

Figure 52: MSW Investment Requirements (2007-31), by Component, (Rs Bn)

368

487

607

0

200

400

600

800

Lower Bound Average Upper Bound

Rs

Bn

, 200

9 p

rice

s

41%

93%100%

0%

25%

50%

75%

100%

125%

C&T Processing Disposal

Ba

ck

log

(%

)

Backlog19%

Demand Growth39%

Assets Replacement

42%

62

Figure 53: MSW Investment Requirements, 5 year trends (Rs Bn)

Figure 54: MSW Investment Requirements, Share of GDP

Figure 55: Annual MSW O&M Costs (Rs Bn) and Coverage Trends (%)

18 18 18 18 18

26 30 38 44 5218 13

48 46

82

62 61

104 108

152

0

25

50

75

100

125

150

175

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

April 2007- March 2012

April 2012- March 2017

April 2017- March 2022

April 2022- March 2027

April 2027- March 2032

Rs

Bil

lio

n (2

00

9 P

rice

s)

Assets Replacement

Demand Growth

Backlog Investments

0.03% 0.02% 0.02% 0.02%

0.04%0.04%

0.03%0.03% 0.02%

0.03%

0.03%

0.02% 0.04%

0.03% 0.04%

0.03%

0.10%

0.08%0.09%

0.07% 0.07%0.08%

0.02%

0.00%

0.05%

0.10%

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

April 2007 -March 2012

April 2012 -March 2017

April 2017 -March 2022

April 2022 -March 2027

April 2027 -March 2032

Average per plan

Average per year

Backlog Demand Growth Assets Replacement

31

34

36

39

42

45

49

52

55

59

63

66

70

74

78

82

86

90

95

99

10

4

10

9

114

119

12

4

0%

20%

40%

60%

80%

100%

-

20

40

60

80

100

120

140

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

19

20

20

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

20

31

Co

verage

(%)

Rs

Bn

Annual O&M Coverage C&T Coverage Disposal

63

D.IV Capital Works Unit Cost Analysis

Cost drivers

102. The most common technology for processing solid waste in India is composting. The

results indicate that there are no significant economies of scale in processing. The main cost

driver for composting is geography. When roof cover in coastal areas is to be done costs are

significantly higher, as it is the case in Trivandrum, Chennai and Imphal. (See Figure 56). City

size and density are not shown to be significantly correlated with unit costs. This may be

related to the fact that land costs are not included in the investment cost estimation (JNNURM

does not cover the cost of land acquisition), as land costs tend to be significantly higher in large

cities compared to small and medium towns.

Sensitivity analysis

103. A sensitivity analysis is conducted to assess the impact of changing service standards

on investment requirements. Assuming a different combination of target compost and landfill

share does not have a major impact on overall project costs. For example, assuming a target

composting and landfill share equal to the transition share (65 percent for composting and 30

percent for landfill) reduces total investment costs by roughly 5 percent, from Rs 487 to Rs 469

Bn. Growth in per capita waste generation has a more significant impact on overall capital

expenditure. For example, increasing the per capita growth rate from 1.3 to 1.6 percent is

estimated to increase overall investment requirements by 13 percent, from Rs 487 to Rs 558 (see

Figure 57 and Figure 58).

64

Figure 56: Unit Processing Costs (Rs/TPD): Economies of Scale (2009 prices)

Note: One project has been excluded from the graph because its plant capacity is more than three standard

deviations away from the average.

Figure 57: Sensitivity Analysis: Changes in Share of Waste Treated and Disposed

Figure 58: Sensitivity Analysis: Changes in Growth Rate of Solid waste Generation

-

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

- 100 200 300 400 500 600

Un

it C

ost

(R

s/TP

D)

Incremental Capacity (TPD)

Non Coastal Cities

Coastal Cities

607 584

487 469

368 355

0

200

400

600

Target: Composting 50% and Landfill 45% Target: Composting 65% and Landfill 30%

Transition: Composting 65% and Landfill 30%

Transition: Composting 65% and Landfill 30%

Assumption 1 Assumption 2

Rs

Bn,

200

9 Pr

ices

607695

487

558

368422

0

100

200

300

400

500

600

700

Per Capita Solid Waste Growth Rate of 1.3%

Per Capita Solid Waste Growth Rate of 1.6%

Assumption 1 Assumption 2

Rs

Bn

, 20

09

Pri

ces

65

E. Investment Needs -A Part of a Complex Picture

104. The results of the cost estimation give an indication of the magnitude of the physical

investment requirements in the urban WSS and MSW sectors, and the growing O&M

requirements as sector coverage increases. Total investment requirements as a share of GDP

range from 1.6 to 0.6 percent over the period 2007-31, with an average of 0.9 percent. While

the shares are purely indicative, as they depend on the profile of the investments, they are

significantly above the current share of capital expenditure in municipal services, and therefore

raise important questions with respect to the sectors’ absorptive capacity. Is the current policy

framework appropriate to support the much needed scale-up of municipal investments? What sector

interventions are needed to minimize the costs and maximize the impact of physical investments? How

to ensure that these investments translate into effective and efficient service delivery?

105. Physical investments are a necessary component for the delivery of municipal services

in an efficient, effective and sustainable manner. However, investments alone are not sufficient.

These investments will not deliver their potential unless they are complemented by actions to

strengthen autonomy & accountability of service providers, enhance incentives, and improve

professionalization. The rest of this section exemplifies how incentives and

professionalization, combined with adequate investments, can work together in improving the

delivery of urban WSS services.

106. Current institutional arrangements for urban WSS service provision in India do not

reflect good international practices where well run public water companies share the

characteristics of reasonable financial and managerial autonomy, clear accountability to

stakeholders and a strong customer orientation. Moving to such an institutional framework

will take time, and States and cities need support and guidance on how to make such changes.

107. First, people respond to incentives. The current institutional arrangements in the WSS

sector provide low incentives with regards to service delivery to customers and (operational

and capital) efficiency. It is worthwhile considering the impact appropriate incentives might

have on making maximum use of investment funds. In the United Kingdom, where a high

incentive regulatory structure is in place, unit capital expenditure to deliver the required levels

of service reduced by almost 25 percent over the 10 year period from 1994-2003. The impact of

such levels of savings in India would be significant. See Box 1 for more details on the England

and Wales’s regulatory system.

108. Second, high quality technical, managerial and commercial skills are needed to make the

most of existing assets, and to ensure that new investments provide good service for their full

economic life. Inadequate skills will mean sub-optimal performance of assets, which result in

poor quality of service to customers. This in turn will make it more difficult to engage with

customers in the steps needed to turn around ailing service providers – including for example,

improving commercial operations of the providers, and reducing losses.

66

109. Inadequate skills, coupled with insufficient revenues, also mean that assets are not

properly operated and maintained leading to shortened asset lives. It has been estimated that

the economic loss associated with shortened asset lives in the urban WSS sector amounts to Rs

438 Billion (USD 10 Billion) over the next forty years (2009 prices). See Box 2 for details. While

this is a coarse assessment, it is clear that investment in human capacity can provide significant

pay back - not just in terms of deferring future capital expenditures, but also in improving

quality of service to customers. In other words the less obvious need to invest in

professionalization of the sector must be addressed alongside the more obvious need to invest

in assets.

67

Box 4: Economic Regulation in the England and Wales WSS Sector

An institutional environment that provides utilities with incentives for efficiency improvements can

gradually lead to a reduction in the unit cost of service provision, and ultimately reduce the capital

expenditure requirements for the WSS industry as a whole. The England and Wales’ WSS sector is a case in

point. Following the 1989 privatization of the WSS sector, England and Wales has created an institutional

and regulatory environment that incentivizes efficiency improvements.

In the England and Wales WSS sector, the hallmark of economic regulation is the use of price caps

combined with yardstick or comparative competition. The price caps set the maximum prices that utilities

are allowed to charge over a five year period. Water prices are set at the efficient level that allows water

companies to finance their functions, including the earning of an adequate return on investments. An

autonomous economic regulator, the Office of Water or Ofwat, was established to minimize political

interference in the price-setting process. Since the water sector was privatized, Ofwat has undertaken four

reviews of water charges – the 1994, 1998, 2004, and 2010 Periodic Reviews.

Price-cap regulation is one of high-powered incentives: companies have an incentive to reduce their costs

beyond the efficiencies expected by the regulator, as they can retain the financial benefits for distribution to

their stakeholders. The efficiency incentives generated by price cap regulation are based on a system of

yardstick competition that rewards companies that achieve efficiency gains above the industry average,

and push the industry’s revealed efficiency frontier forward. The system of yardstick competition

established by Ofwat covers both inputs - operating and capital expenditure - as well as outputs – as

measured by a series of quality of service indicators. For operating and capital expenditure, Ofwat’s

efficiency assessment is based on a combination of econometric techniques and unit costs analysis.

A comparative capital unit cost approach, known as the ‚cost base‛ was developed by Ofwat to compare

capital expenditure across the industry and identify those companies that appeared to be more efficient at

procuring capital assets than others. Companies with higher unit capital costs were considered to have

more scope for savings in their expenditure projections that companies with lower capital unit costs. The

analysis conducted by Ofwat as part of the 1998 and 2004 Periodic Review indicates that substantial

efficiency gains have been achieved by the industry as a whole since economic regulation was introduced.

Over the period 1994-98, unit capital expenditure decreased by 10 percent for water services and by 15

percent for sewerage services across the industry as a whole.30 Over the period 1998-2003, unit capital

expenditure declined by an additional 15 percent for water services and by 10 percent for sewerage services. 31 Improved procurement processes and the use of innovative techniques were reported by the companies

as the main drivers of capital expenditure reductions. 32

Improvements in efficiency are reflected in future price limits resulting in lower bills for consumers.

Reductions in capital works unit costs also create space for a larger maintenance program and other

improvements to be carried out at no extra costs for consumers.

30 Ofwat (1998), ‚Capital Works Unit Costs in the Water Industry: An Analysis of the June 1998 Water

Company Cost Base Submissions‛. 31 Ofwat (2004), ‚Capital Works Unit Costs in the Water Industry: Feedback on Our Analysis of the

March 2003 Water Company Cost Base Submissions‛. 32 It is important to note that efficiency savings explain a large part, but not the totality, of the industry

reduction. Changes in companies’ methodologies contribute in some part to the variances in the capital

unit costs.

68

Annex I: Methodological Approach

Urban Water Supply STEP-BY-STEP METHODOLOGY

Urban water investment requirements are estimated for both residential and industrial

customers for the period 2007-31. O&M requirements are computed on an annual basis over

the same period. Investment requirements are estimated separately for water production

(source augmentation and transmission) and distribution (network, storage and metering). The

methodological approach adopted for the estimation consists of the following main steps:

Step I: Define sector targets to be achieved by 2031

Defining service standards based on demand and supply considerations is the first step for

estimating investment requirements for urban water supply. The cost model is based on the

assumption of homogeneous service standards across urban India. The supply-side service

standards embedded in the cost model are the following: (a) 100 percent target piped water

supply coverage (for both water production and distribution), (b) 24/7 water supply continuity,

and (c) a 20 percent leakage. The demand-side service standards are the following: (d) a per

capita residential consumption norm of 135 lpcd, and (e) a 7 percent annual increase in

industrial water demand for cities with population above 500,000.

Step II: Classify Sample Cities based on Population

All cities for which the data is available are classified into six categories on the basis of their

population as reported in the census. The first census class, including all cities with population

above 100,000, is further divided in three sub-categories: Class I.A (megacities, > 5 million),

Class I.B (1-5 million) and Class I.C (100k-1 million). 33 The classification is based on Urban

Agglomeration (UA) population whenever applicable. The rationale for the classification of

sample cities into size classes is to capture differences in capital expenditure norms across the

spectrum of urban cities. See Table 1.

Table 1: City Size Classes

Class I.A 7 Mega-cities, > 5 million

Class I.B 1 – 5 million

Class I.C 100,000 – 1 million

Class II 50,000 – 100,000

Class III 20,000 – 50,000

Class IV+ < 20,000

33 The seven mega-cities are Delhi, Mumbai, Hyderabad, Kolkata, Chennai, Bangalore and Ahmadabad.

All megacities currently have population above 5 million. Note that Ahmadabad is classified in Class

I.A but was not yet a megacity in 2001 being its population below 5 million.

69

Step III: Estimate Urban Households Water Backlogs

The backlog percentages for water distribution are calculated based on 2001 Population Census

data. Water distribution backlogs are defined as the percentage of the current urban

population with no private water connection. It is assumed that the 2001 backlog percentages,

as estimated based on census data, apply to 2006.34 Backlog percentages for water production

are estimated based on City Development Plans (CDPs)’ data, most of which were prepared

around 2006 when the JNNURM program was launched. Water production backlogs are

computed as the difference between city-level production capacity (net of industrial water

use), as reported in the CDPs, and residential production requirements. To ensure

comparability across cities, residential production backlogs are estimated based on the per

capita production norm of 168 lpcd across all city size classes. The backlog for 24/7 up-

gradation is assumed equal to the entire urban population connected to water supply, given

that virtually no Indian city currently benefit from 24/7 water supply continuity. The backlog

percentage for each of the six classes of cities is calculated as the average backlog for all cities

in that category weighted by city population. Similarly, the backlog percentage for all urban

India is estimated as the average backlog for all city size categories weighted by the total urban

population in each category.

Step IV: Project Urban Population by City Size Class

The 2001 census population is taken as the base year population for the cost model. Population

forecasts are based on estimates provided by the United Nations Population Division of the

Department of Economic and Social Affairs (DESA) in its regular statistical publication, the

World Urbanization Prospects (2007 revision). For each city class, population is forecasted by

applying the UN population growth rates to 2001 census population figures over the period

2001-2031. There is no complete alignment between the six Census of India city classes, as

reported in this study, and the UN population classes. More specifically, the UN projection

model provides estimates for only 5 broad city classes – the lowest class including all cities

with population below 500,000. As a result, the same growth rate is applied to all Indian cities

with population below 500,000.

Step V: Calculate 2006 Backlog Population and Incremental Urban Population (2007-2031)

The 2006 population for each class of cities is multiplied by the corresponding backlog

percentage to calculate the total backlog population for production, 24/7 up-gradation and

distribution extension. The total additional population over the period 2007-2031 for each class

of cities is calculated by deducting the 2006 population from the projected population of the

year 2031.

34 Census data is used to estimate distribution backlogs instead of CDPs for the following two reasons:

first, CDPs are only available for a small sample of cities (most of which are in Class I.A-I.C), second a

few cities, including megacities, do not include slum area in the estimation of the coverage rate. In spite

of the significant difference in the coverage rate estimated based on the two data sources, using the

CDPs rather than the census figures for the backlog estimation has a negligible impact on total

investment requirements.

70

Step VI: Estimate Unit and Per Capita Investment Costs for Residential Water Production

The unit and Per Capita Investment Costs (PCICs) for production are calculated based on

JNNURM project data. The PCICs are computed by dividing total JNNURM production costs

by the target beneficiaries. Beneficiaries are computed by dividing the project design-year

incremental capacity by the 168 lpcd production norm (this methodology ensures a consistent

approach in the definition of project beneficiaries across all JNNURM projects, given that a

number of JNNURM Project Appraisal Notes do not provide information on design-year

project population). The unit costs for water production are estimated by dividing total project

cost by the project incremental capacity.

Step VII: Estimate Water Production Investment Requirements for Industrial Customers

The investment requirements to meet the production requirements of industrial customers are

estimated for all Indian cities with population above 500,000. The assumption is made that

about 20 percent of the production capacity of Indian cities is dedicated to industrial customers

(based on expert estimates and average percentages reported by CDPs). Industrial production

requirements are estimated to increase in line with the annual growth rate for industry value

added (at about 7 percent per annum). City-level production investment requirements for

industrial customers are then estimated for each city in the sample based on JNNURM average

unit production costs for city size classes. Total investment requirements are computed by

multiplying city-level investment needs by the total numbers of cities in each city class,

estimated based on UN forecasts. Investment requirements for industrial water production are

only calculated for cities with population above 500,000, because UN estimates on numbers of

cities are only available for Class I.A and Class I.B cities and a sub-set of Class I.C cities (1m -

500k).

Step VIII: Estimate PCIC for 24/7 Up-gradation

Estimating the per capita costs of upgrading the existing distribution network to achieve 24/7

water supply continuity is methodologically complex, given that virtually no Indian city has

24/7 water supply with the exception of a few pilot projects (e.g. Karnataka towns and Nagpur

in Maharashtra). It is also complex because the solution to delivering 24/7 is a mix of

rehabilitation of old assets (e.g. to fix leaks in old pipes and service connections), new assets

(e.g. improved network layout, creation of district meter areas for leakage management), and

(importantly) significantly improved distribution system management. Assumptions have

therefore been made on the type of investment required to achieve 24/7 water supply across

the various categories of cities and towns. In the absence of project data, a cost simulation

exercise has been conducted to estimate the PCIC for 24/7 up-gradation. The cost simulation

exercise has been complemented by cost data based on a small number of 24/7 up-gradation

pilot projects.

Estimating the cost of partially replacing the distribution system (cost simulation).

Many of the water distribution networks in Indian Cities are old and poorly

constructed. The share of the distribution network that needs to be replaced to achieve

71

24/7 varies from city to city. In the absence of accurate city-level information on the

conditions of the water distribution assets, the estimate is based on the assumption that

on average 50 percent of the distribution network needs to be replaced. The same

replacement share is applied to water storage and household connection/metering

costs. The replacement share is assumed to range from 40 percent for Class I.A cities to

60 percent to Class III and IV+. The variation across city size classes takes into account

the fact small cities may have to replace a higher share of the network because of the

lower maintenance standards, compared to the largest cities. For the purpose of the cost

simulation, the per capita optimal storage capacity is assumed to be equivalent to one

third of per capita water consumption. The cost of partially replacing the distribution

network is estimated on the basis of information provided by the City Development

Plans on the length of the distribution network per connected person, and the diameter

of pipes for the primary, secondary and tertiary network. Variation in the length of the

network per connected person across cities captures differences in population density

across city size classes. The cost of pipes of different diameters has been provided by

experts based on recent project data. Metering and storage costs are estimated based on

cost norms gathered through the data survey and expert estimates.

Estimating the costs of achieving 24/7 water supply (project data). Very few JNNURM

projects are designed to achieve 24/7 water supply continuity. Nevertheless, a number

of 24/7 water pilot projects have been recently carried out across a number of cities in

India. The actual and proposed costs for a small sample of 24/7 projects have been

collected and included in the model (see Table 24). All 24/7 up-gradation pilot projects

envisage a partial replacement of the distribution network. The share of the

distribution network that is replaced to deliver 24/7 varies across projects, from 90

percent in Hubli to 40 percent in Nagpur.

Step IX: Estimate PCIC for Extending the Distribution Network (based on 24/7 Standards)

Delivering 24/7 water supply to the un-connected urban population requires an expansion of

the existing distribution system (based on 24/7 standards), household connection and metering

installation and the building of an optimal level of water storage capacity. The following

methodological approach has been to calculate distribution extension PCICs for the sample

cities. First, in a given city the per capita distribution network requirements are estimated

based on the length of the distribution network for the served population (including primary,

secondary and tertiary network). It is assumed that the average per capita distribution pipes’

extension that is needed to connect the un-served population is equal to 50 percent of the per

capital length of the distribution pipe for the served population (given that part of the network

is expected to be already in place). The per capita cost of extending the distribution network is

estimated based on cost norms for a mix of water pipes. Second, the per capita cost of

household connections, metering and water storage are computed based on the methodology

described above as they are necessary conditions for the provision of 24/7 water supply.

Step X: Estimate Total Investment Needs for the Period 2007 – 31

Water investment requirements are estimated as the total of the following cost components:

72

Investments for 2006 backlog (un-met demand)

Investments for demand growth (2007-2031)

Capital re-placement costs for residential water production

Production investments for industrial customers

Investments for backlog: The backlog population for production, 24/7 up-gradation and

distribution extension are multiplied by the PCIC for the respective cost components to

estimate total backlog investments.

Investments for demand growth: To calculate the investment requirements for the additional

urban population, the PCIC for production and distribution extension (24/7 standards) are

multiplied by the incremental urban population, as any additional urban population will need

investment in both production and distribution. To simulate the profiling of the investment,

the incremental investments are computed on a five year basis.

Assets replacement costs (production): Assets replacement costs for residential water

production are estimated based on the assumptions that assets fully depreciate in 30 years. For

example, 1981 assets would reach the end of their economic life and would need to be replaced

in 2011, while in 2021 (2031), replacement will be required for the 1991 (2001) connected

population.

Production investments for industrial customers: Production investment costs for industrial

customers for cities with population above 500,000 have been estimated and included in the

total investment requirements.

To account for the fact the most JNNURM approved costs are expressed in 2006 prices, the

total investment needs are then converted in 2009 prices.

Step XI: Estimate Annual O&M Needs for the period 2007 – 31

Annual O&M requirements are estimated based on total volume of water production in each

year for residential and industrial customers. The total annual O&M requirements are

estimated to increase over time as the connection rate increases. O&M unit cost estimates have

been made available by sector experts based on recent project data. Distance to water sources is

the main factor affecting O&M unit costs – the further away are water resources, the higher the

O&M costs. Variation in unit costs across cities reflect the fact that large cities are generally

further away to water sources than small and medium towns.

Step XII: Conduct Sensitivity Analysis

Investment requirements are calculated as a band rather than a single point estimate. The band

reflects the reliability of the investment estimates, which in turn depends on the accuracy of the

PCICs, backlog percentage and population forecasts. Among these three factors, the PCIC is

the most critical variable affecting investment estimates – a 10 percent increase in PCIC leads to

an equivalent increase in investment requirements – while variation in the other two variables

73

lead to a less than proportional change in investment requirements. The standard deviation is

calculated to measure the variation of the PCICs for each of the sub-sectors.35 Based on the

standard deviation, a 10 percent confidence interval for the total PCIC is estimated. Given that

a change in the PCIC leads to a proportional change in total investment requirements, the low

and high estimate boundaries of the confidence interval for the PCICs can be converted into a

range of values for the investment requirements.

Step XIII: Simulate the profile of the investments

In order to simulate the profile of the investments, investment requirements are estimated in

line with the 5-year Planning Periods. For example, the 2006 base year corresponds to the

period April 2006-March 2007, and the first five year interval (2007-2011) correspond to the 11th

Plan (April 2007 - March 2012). For the purpose of the simulation, it is assumed that full

coverage would be achieved by the end of the 15th Plan (2027-2032).

35 The standard deviation is a good proxy of the accuracy of a variable. A low standard deviation

indicates that the data points tend to be very close to the average value of the distribution, whereas high

standard deviation indicates that the data are spread out over a large range of values. The standard

deviation also depends on the sample size: everything else being equal, the larger the sample size, the

more accurate the estimates, and the lower the standard deviation.

74

Urban Sewerage STEP-BY-STEP METHODOLOGY

Sewerage investment requirements for the urban population are estimated for the period 2007-

31. O&M requirements are computed on an annual basis over the same period. Investment

requirements are estimated separately for network and treatment. The methodological

approach adopted for the estimation consists of the following main steps:

Step I: Set Service Targets for Urban Sewerage

Defining service standards based on demand and supply considerations is the first step for

estimating investment requirements for urban sewerage. The cost model is based on the

assumption of homogeneous service standards across urban India. The standards embedded

in the cost model are (a) 100 percent target coverage rate for both sewerage collection and

treatment (supply-side) and (b) a per capita residential sewerage generation of 108 lpcd, i.e. 80

percent of per capita water consumption, over the period 2007-2031 (demand-side). The

objective of the cost model is to estimate the investment requirements to meet the specified

sector targets.

Step II: Classify Sample Cities based on Population

All cities for which the data is available are classified into six categories on the basis of their

population as reported in the census. The first census class, including all cities with population

above 100,000, is further divided in three sub-categories: Class I.A (megacities, > 5 million),

Class I.B (1-5 million) and Class I.C (100k-1 million). 36 The classification is based on Urban

Agglomeration (UA) population whenever applicable. The rationale for the classification of

sample cities into size classes is to capture differences in expenditure norms across the

spectrum of urban cities. See Table 2.

Table 2: City Size Classes

Class I.A 7 Mega-cities (> 5 million)

Class I.B 1 – 5 million

Class I.C 100,000 – 1 million

Class II 50,000 – 100,000

Class III 20,000 – 50,000

Class IV+ < 20,000

36 The seven mega-cities are Delhi, Mumbai, Hyderabad, Kolkata, Chennai, Bangalore and Ahmadabad.

All megacities currently have population above 5 million. Note that Ahmadabad is classified in Class

I.A but was not yet a megacity in 2001 being its population below 5 million.

75

Step III: Estimate Backlog Percentages for Urban Sewerage

Backlog percentages for sewerage network are estimated based on 2001 Population Census

data. It is assumed that the 2001 backlog percentage applies to the base year 2006.37 Backlog

percentages for treatment are estimates for a sample of cities based on City Development

Plans, most of which were prepared around 2006 when the JNNURM program was launched,

and information provided through data collection. The estimation of treatment backlogs is

based on a demand-driven per capita sewerage generation norm of 108 lpcd. The treatment

backlog at the city level is computed based on the difference between current treatment

capacity, as provided in the CDPs, and treatment requirements to meet the per capita norms.

The average backlog percentage for each of the six classes of cities is calculated as the average

backlog for all cities in that category weighted by city population. Similarly, the backlog

percentage for all urban India is estimated as the average backlog for all city size categories

weighted by the total urban population in each category.

Step IV: Forecast Urban Population over the Period 2001-2031

The 2001 census population is taken as the base year population for the cost model. Population

forecasts are based on estimates provided by the United Nations Population Division of the

Department of Economic and Social Affairs (DESA) in its regular statistical publication, the

World Urbanization Prospects (2007 revision). For each city class, population is forecasted by

applying the UN population growth rates to 2001 census population figures over the period

2001-2031. There is no complete alignment between the six Census of India city classes, as

reported in this study, and the UN population classes. More specifically, the UN projection

model provides estimates for only 5 broad city classes – the lowest class including all cities

with population below 500,000. As a result, the same growth rate is applied to all Indian cities

with population below 500,000.

Step V: Calculate 2006 Backlog and additional population (2007-31)

The 2006 population for each class of cities is multiplied by the corresponding backlog

percentage to calculate the total backlog population for both network and treatment for each

class of cities for the year 2006. The total additional population over the period 2007-2031 for

each class of cities is calculated by deducting the 2006 population from the projected

population of the year 2031.

Step VI: Estimate Unit and Per Capita Investment Costs (PCIC)

Unit and Per Capita Investment Costs (PCICs) are calculated separately for each of the two

sub-sectors: (a) network and (b) treatment. For each sub-sector, project costs are divided by the

beneficiary project population to calculate the PCIC. For cities with more than one project, the

city-level PCICs are estimating by averaging out the PCICs for all projects in that city. Project

37

Census data is used to estimate network backlogs instead of CDPs for the following two reasons: first,

CDPs are only available for a small sample of cities (most of which are in Class I.A-I.C), second a few

cities do not include slum area in the estimation of the coverage rate. However, using the CDPs rather

than the census figures for the backlog estimation has a negligible impact on total investment

requirements.

76

beneficiaries are calculated by dividing the project design-year incremental capacity by the per

capita sewerage generation norm (108 lpcd). This is to ensure a consistent approach in the

definition of project beneficiaries across all JNNURM projects, given that a number of

JNNURM Project Appraisal Notes do not provide information on design-year project

population. When no specific reference is made in the Project Appraisal Notes, pumping costs

when present are allocated to the treatment sub-sector.

Step VII: Calculate Total Investment Requirements for the period 2007-2031

Investment requirements include the following cost components:

Investments for 2006 backlog (un-met demand)

Investments for demand growth (2007-2031)

Assets replacement costs

Investments for backlog: The backlog populations for network and treatment are multiplied by

the PCIC for the respective cost components. The two cost components are then added to

compute the total investment costs for the backlog. The baseline scenario is based on the

assumption that full coverage is achieved by 2031.

Investments for demand growth: To calculate the financing required for providing sewerage

services to the additional urban population, the total PCIC costs for network and treatment is

multiplied by the incremental population over the period 2006-2031. The underlying

assumption is that any additional urban population will need to have access to all sewerage

services (i.e. network and treatment).

Assets replacement costs: The replacement costs for sewerage network and treatment are

estimated based on an economic life of the assets of 30 years. For example, it is assumed that

the assets replacement for the population covered in 1981 will be made in 2011, assets

replacement for the population covered in 1991 (2001) will be made in 2021 (2031).

All project costs and investment requirements are converted in 2009 prices.

Step VIII: Calculate Annual O&M Costs for the period 2007-2031

Annual O&M requirements costs are calculated based on annual sewerage generation, which is

estimated based on projected coverage rate and a per capita sewerage generation norm of 108

lpcd. The total annual O&M requirements are estimated to increase over time as the connection

rate increases. The unit O&M costs are estimated based on sector estimates and Bank’s project

data.

Step IX: Conducting Sensitivity Analysis

Investment requirements are calculated as a band rather than a single point estimate. The band

reflects the reliability of the investment estimates, which in turn depend on the accuracy of the

PCICs, backlog percentage and population forecasts. Among these three factors, the PCIC is

77

the most critical variable affecting investment estimates – a 10 percent increase in PCIC leads to

an equivalent increase in investment requirements – while variation in the other two variables

leads to a less than proportional change in investment requirements. The standard deviation is

calculated to measure the variation of the PCICs for each of the two sub-sectors.38 Based on the

standard deviation, a 10 percent confidence interval for the total PCIC is estimated. Given that

a change in the PCIC leads to a proportional change in total investment requirements, the low

and high estimate boundaries of the confidence interval for the PCICs can be converted into a

range of values for the investment requirements.

Step X: Simulate the profile of the investments

In order to simulate the profile of the investments, investment requirements are estimated in

line with the 5-year Planning Periods. For example, the 2006 base year corresponds to the

period April 2006-March 2007, and the first five year interval (2007-2011) correspond to the 11th

Plan (April 2007 - March 2012). For the purpose of the simulation, it is assumed that full

coverage would be achieved by the end of the 15th Plan (2027-2032).

38 The standard deviation is a good proxy of the accuracy of a variable. A low standard deviation

indicates that the data points tend to be very close to the average value of the distribution, whereas high

standard deviation indicates that the data are spread out over a large range of values. The standard

deviation also depends on the sample size: everything else being equal, the larger the sample size, the

more accurate the estimates, and the lower the standard deviation.

78

Municipal Solid Waste

STEP-BY-STEP METHODOLOGY

Municipal solid waste investment requirements for the urban population are estimated for the

period 2007-31. O&M requirements are computed on an annual basis over the same period.

Investment requirements are estimated separately for Collection & Transportation (C&T),

processing and disposal. The methodological approach adopted for the estimation consists of

the following main steps:

Step I: Set Service Targets for Urban Solid Waste Management

Defining the service standards based on demand and supply considerations is the first step for

estimating investment requirements for municipal solid waste. The demand-side standards

embedded in the cost model are (a) per capita waste generation ranging from 0.2 to 0.6

kg/capita/day, (b) 1.3 percent annual per capita solid waste generation.39 The supply-side

standards are the following: (c) a target collection and transportation coverage of 100 percent,

(d) a target compost share of 65-50 percent; (e) a target landfill share of 30- 45 percent. For

composting, the assumption is made the MSW sector will gradually move from the prevailing

target compost share of 65 percent to 50 percent within a period of 10 years. For landfill, it is

assumed that the sector will move from the prevailing 30 percent target to 45 percent over a

period of 10 years. From 2017 onward, the target compost and landfill share are therefore

expected to be 50 and 45 percent respectively.

Step II: Classify Sample Cities based on Population

All cities for which the data is available are classified into six categories on the basis of their

population as reported in the census. The first census class, including all cities with population

above 100,000, is further divided in three sub-categories: Class I.A (megacities40, > 5 million),

Class I.B (1-5 million) and Class I.C (100k-1 million). The classification is based on Urban

Agglomeration (UA) population whenever applicable. The rationale for the classification of

sample cities into size classes is to capture differences in expenditure norms across the

spectrum of urban cities. See Table 3.

39

See Shekdar, A.V., 1999. ‚Municipal solid waste management – the Indian perspective‛. Journal of

Indian Association for Environmental Management 26 (2), 100–108. 40 The seven mega-cities are Delhi, Mumbai, Hyderabad, Kolkata, Chennai, Bangalore and Ahmadabad.

All megacities currently have population above 5 million. Note that Ahmadabad is classified in Class

I.A but was not yet a megacity in 2001 being its population below 5 million.

79

Table 3: City Size Classes

Class I.A 7 Mega-cities, > 5 million

Class I.B 1 – 5 million

Class I.C 100,000 – 1 million

Class II 50,000 – 100,000

Class III 20,000 – 50,000

Class IV+ < 20,000

Step III: Estimate Backlogs for Urban Solid Waste

Backlog percentages for solid waste C&T, processing and disposal are estimated based on City

Development Plans. The backlog percentage for each of the six classes of cities is calculated as

the average backlog for all cities in that category weighted by city population. Similarly, the

backlog percentage for all urban India is estimated as the average backlog for all city size

categories weighted by the total urban population in each category.

Step IV: Forecast Urban Population over the period 2001-31

The 2001 census population is taken as the base year population for the cost model. Population

forecasts are based on estimates provided by the United Nations Population Division of the

Department of Economic and Social Affairs (DESA) in its regular statistical publication, the

World Urbanization Prospects (2007 revision). For each city class, population is forecasted by

applying the UN population growth rates to 2001 census population figures over the period

2001-2031. There is no complete alignment between the six Census of India city classes, as

reported in this study, and the UN population classes. More specifically, the UN projection

model provides estimates for only 5 broad city classes – the lowest class including all cities

with population below 500,000. As a result, the same growth rate is applied to all Indian cities

with population below 500,000.

Step V: Calculate 2006 Backlog (un-met demand) and demand growth over 2007-31

The 2006 waste generation estimates for each class of cities is multiplied by the target C&T,

compost and landfill shares to estimate the total amount of waste that would need to be

composted and sent to landfill sites in the base year. The waste volume for C&T, processing

and disposal is multiplied by the corresponding backlog percentages to calculate the total

backlog waste (un-met demand) for the year 2006. The additional waste generation for the

period 2007-31 is estimated based on population forecasts and a 1.3 percent annual increase in

per capita waste generation. The target C&T, processing and disposal shares are applied to

total waste generation to forecast the total volume of waste that would need to be collected &

transported, composted and sent to a landfill site in a given year.

Step VI: Estimate Unit Investment Costs

Unit Investment Costs are calculated separately for each of the three sub-sectors: (a) C&T; (b)

processing and (c) disposal. For each sub-sector, project costs are divided by the

corresponding project incremental capacity (expressed in volume of waste) to calculate unit

costs. For collection and transportation, the volume of waste is assumed to be equal to the

80

design-year solid waste generation for the project area. The assumption is in line with the

specification in the Project Appraisal Notes that the project would include the replacement of

the existing equipment, which has reached the end of its economic life. For composting, the

incremental waste volume is estimated based on the design-year size of the compost plant,

which is reported by most Project Appraisal Notes.41 For landfill, the incremental waste

volume is available for only a few projects. For the available projects, on average the landfill

share is equivalent to 32 percent of the design-year solid waste generation. The share is

applied to estimate volume of waste that is disposed for projects for which data is not

available. For cities with more than one project, the city-level unit costs are calculated by

averaging out the unit costs for all projects within that city. Per Capita Investment Costs

(PCIC) are computed based on unit costs and per capita waste generation.

Step VII: Estimate Total Investment Requirements for the period 2007-2031

Investment requirements include the following cost components:

Investments for 2006 backlog (un-met demand)

Investments for demand growth (2007-2031)

Assets replacement costs

Investments for backlog: The un-met demand for C&T, processing and disposal is multiplied

by the unit costs for the respective cost components. The three cost components are then added

to compute the total backlog investment costs.

Investments for demand growth: To calculate the investment requirements for demand growth,

the unit costs for collection and transportation, processing and disposal are multiplied by the

incremental waste volume that would need to be collected & transported, processed and

disposed over the period 2007-31. The incremental waste volume is estimated based on

population forecasts and increase in per capita waste generation.

Assets replacement costs: Assets replacement costs for collection and transportation are

estimated based on an asset life of 10 years. This implies that, for example, the stock of vehicles

purchased in 2001 would need to be replaced in 2011. Assets replacement costs for disposal

are estimated based on a five year interval at a unit cost equal to 50 percent of the initial cost.

This is consistent with the fact that landfill costs provided in the JNNURM Project Appraisal

Notes are generally for a 5 year period. However, the incremental costs of landfill are going to

be lower than the original cost (50 percent of the initial costs) because some initial investments

(e.g. roads) will not be needed in the future. Assets replacement costs for processing are not

included, as they are generally funded by compost sale revenues.

41

On average, the size of the compost plant is about 48 percent of the design-year waste generation

capacity for the project area. For the three projects that do not provide information on the size of the

compost plant, the incremental processing capacity of the project is estimated based on the 48 percent

share.

81

While land costs cannot be estimated, land requirements for landfill sites are computed for the

year 2031 based on a norm of 150 acres per 150 Tpd.

All project costs and investment requirements are converted in 2009 prices.

Step VIII: Estimate Annual O&M Costs for the period 2007-2031

Annual O&M costs for both C&T and disposal are estimated based on total waste volume.

O&M costs for processing are not considered because they are covered by compost sale

revenues. The average unit O&M cost is estimated at Rs 1,200 per ton of waste generation (Rs

1,000 per ton for C&T and Rs 200 for disposal) based on a sample of project data and expert

estimates.

Step VIII: Conducting Sensitivity Analysis

Investment requirements are calculated as a band rather than a single point estimate. The band

reflects the reliability of the investment estimates, which in turn depends on the accuracy of the

PCICs, backlog percentage and population forecasts. Among these three factors, the PCIC is

the most critical variable affecting investment estimates – a 10 percent increase in PCIC leads to

an equivalent increase in investment requirements – while variation in the other two variables

leads to a less than proportional change in investment requirements. The standard deviation is

calculated to measure the variation of the PCICs for each of the three sub-sectors.42 Based on

the standard deviation, a 10 percent confidence interval for the total PCIC is estimated. Given

that a change in the PCIC leads to a proportional change in total investment requirements, the

low and high estimate boundaries of the confidence interval for the PCICs can be converted

into a range of values for the investment requirements.

Step XIII: Simulate the profile of the investments

In order to simulate the profile of the investments, investment requirements are estimated in

line with the 5-year Planning Periods. For example, the 2006 base year corresponds to the

period April 2006-March 2007, and the first five year interval (2007-2011) correspond to the 11th

Plan (April 2007 - March 2012). For the purpose of the simulation, it is assumed that full

coverage would be achieved by the end of the 15th Plan (2027-2032).

42

The standard deviation is a good proxy of the accuracy of a variable. A low standard deviation

indicates that the data points tend to be very close to the average value of the distribution, whereas high

standard deviation indicates that the data are spread out over a large range of values. The standard

deviation also depends on the sample size: everything else being equal, the larger the sample size, the

more accurate the estimates, and the lower the standard deviation.

82

MODEL ASSUMPTIONS

General

Cities are classified into six categories on the basis of their population as per the census

data. The first Census Category (Class I), which include all cities with more than 100,000

population, is split into the following three sub-classes: Class I.A: 7 Megacities; Class I.B:

1-5 million and Class I.C: 100,000-1 million.

For the classification of cities, where applicable, the population of ‘urban agglomeration’ is

used instead of the population within the area of municipal corporation/ municipality.

This is because the City Development Plans (CDPs) have been prepared for the urban

agglomeration (and not just the area under the municipal corporation/ municipality). For

cities where the population figures for urban agglomeration are either not available or not

applicable, population figures for the municipal corporation/ municipality are used. This

is because the backlog percentages for these cities were specifically for the area under

municipality and not the urban agglomeration.

The base year for the estimation of investment needs is 2006. The model uses year 2031 as

the forecast year.

The backlog percentages that are estimated based on the City Development Plans are

generally for the year 2006. The backlog percentages that are estimated based on 2001

population census data are assumed to apply to the base year 2006 (for example, for the

estimation of the water distribution backlog, it is assumed that the share of urban

population with private water connection in 2001 is the same as the share in 2006). The

sewerage backlog data collected directly from the cities in Karnataka, Tamil Nadu and

Andhra Pradesh may not necessarily be as of 2006; when this is the case, it is assumed that

the same backlog percentage applies to the year 2006.

When the CDPs express the backlog for coverage in terms of area, it is assumed that the

population is evenly distributed within the area; hence the same percentage is used to

determine the population backlog.

Investment needs are converted in 2009 prices, given that most JNNURM approved

projects costs are in 2006 prices. The rate of inflation used for conversion of 2005-06 prices

into 2008-2009 prices is 30 percent. This is derived using the whole sale price index (non-

food items) sourced from Reserve Bank of India. For the sake of simplicity, it is assumed

that all project costs are in 2006 prices when the date of project approval is not available.

The exchange rate that is used in the model was: USD 1 = INR 45.

83

Water

The average per capita production norm is assumed to be 168 liters/per capita/day across

all city size classes. The average per capita consumption standard is 135 lpcd.

For cities with population above 500,000, industrial water production is estimated to

account for about 20 percent of total water production, based on City Development Plans

information for a sample of cities.

For cities with population above 500,000, industrial water production is estimated to

increase at 7 percent per annum, in line the average industry value added for the last ten

years.

The assumption is made that on average 50 percent of the distribution network would need

to be replaced to deliver 24/7 water supply in Indian cities. The replacement share ranges

from 40 percent for Class I.A cities to 60 percent to Class III and IV+.

. It is assumed that the average per capita distribution pipes’ extension that is needed to

connect the un-served population is equal to 50 percent of the per capital length of the

distribution pipe for the served population

Unit costs for O&M are estimated based on a number of projects provided by sector

experts. The unit costs for each city size class are reported in Table 4.

Table 4: Unit Water O&M Costs (Rs/m3)

Class Unit Cost (Rs/m3)

Class I.A 12

Class I.B 9

Class I.C 7

Class II 7

Class III 5

Class IV+ 3

Unit costs of pipes are based on project data provided by sector experts. The costs are

reported in the Table 5 below.

Table 5: Unit Cost of Pipes (Rs/m)

Diameter Cost

100 1,200

150-200 1.857

250-300 2,514

350-400 3,965

450-550 5,524

600 8,650

650 9,739

700 and above 10,827

84

Based on project data provided by sector experts, unit costs of storage are estimated at 5

Rs/l for storage capacity above 500 MLD, 8 Rs/l for storage capacity of 150-500 MLD, and 12

Rs/l for storage capacity below 150 MLD. Per capita storage requirements are estimated at

one third of per capita water consumption.

For the estimation of replacement costs, the economic life of water production assets is

assumed to be 30 years.

Sewerage

For the estimation of replacement costs, the economic life of network and treatment assets

is assumed to be 30 years.

The unit O&M costs are assumed to be equal to 1.6 Rs/m3 for treatment and 1 Rs/m3 for

network based on a sample of projects provided by sector experts.

Solid Waste

Per capita waste generation is estimated based on 1995 data as reported in the 3i Network

2006 Infrastructure Report, assuming an annual growth rate of 1.3 percent.

Table 6: Per Capita Waste Generation (2006)

Class Gr/capita/day

Class I.A 577

Class I.B 404

Class I.C 288

Class II 242

Class III 242

Class IV+ 242

Source: Estimates based on 3i Network. 2006.

‚India Infrastructure Report‛. New Delhi.

The economic life of the assets assumed for the estimation of assets replacement costs is

summarized below

Table 7: Per Capita Replacement Costs

C&T Every 10 years

Processing No re investment

Disposal Every 5 years at 50% of original unit cost

The target compost share is assumed to be gradually declining from the prevailing 65

percent to about 50 percent over a 10 year period. In parallel, the target landfill share is

expected to gradually increase from 30 to 45 percent.

85

Annex II: Sample Description

Table 8: Project Sample Size, by Sector

I.A I.B I.C II III IV+ TOTAL

Megacities 1-5m 100k-1m 50-100k 20-50k <20k

Water

Production 9 16 13 2 1 0 41

24/7 Up-gradation 6 8 8 1 10 0 33

Distribution extension 5 7 8 1 10 0 31

Sewerage

Network 11 21 33 13 30 5 113

Treatment 15 22 23 10 4 5 79

Solid Waste

C&T 3 15 15 2 5 0 40

Processing 3 15 8 0 1 0 27

Disposal 3 15 10 1 4 0 33

Table 9: Backlog Sample Size (CDP’s and Census), by Sector

I.A I.B I.C II III IV+ TOTAL

Megacities 1-5m 100k-1m 50-100k 20-50k <20k

Water

Production (CDPs) 6 23 21 2 10 5 67

Distribution extension

(Census)

7 27 360 404 1,164 2,415 4,377

Sewerage

Network (Census) 7 27 360 404 1164 2415 4,377

Treatment (CDPs) 6 18 29 11 12 4 80

Solid Waste

C&T (CDPs) 7 18 16 0 7 3 51

Processing (CDPs) 7 19 14 0 6 3 49

Disposal (CDPs) 6 23 21 2 10 5 67

86

Data Sources

Data Sources for Projects

SEWERAGE Network Treatment

JNNURM Project Appraisal Notes 41 46

Tamil Nadu Urban Development Fund (TNUDF) 24 23

Karnataka Urban Water Supply and Drainage Board 43 5

Andhra Pradesh Municipal Development Project,

Municipal Strengthening Unit 5 5

WATER Production

JNNURM Project Appraisal Notes 35

Karnataka Urban Water Supply and Drainage Board 3

Projects provided by sector expert: Ponnur, Kadiri, and

Eluru. 3

WATER Distribution

Cost Simulation (based on 22 CDPs, Karnataka Urban

Infrastructure Development and Finance Corporation

‚KUIDFC‛ data for 9 Karnataka cities, and expert advice)

31

WATER Up-gradation

Cost Simulation (based on 26 CDPs and expert advice) 26

JNNURM 24/7 water pilot projects (Detailed Project

Reports: Kolkata, Allahabad, and Nagpur) 3

Karnataka 24/7 water pilot projects: Hubli, Gulbarga,

Belgaum. 3

SOLID WASTE C&T Processing Disposal

JNNURM Project Appraisal Notes 22 22 22

Multiple Sources (including: Karnataka Urban

Development and Coastal Environmental Management

Project (KUDCEMP); Infrastructure Development

Consultancy Karnataka).

18 5 11

87

Data Sources for Backlog

Source Sector

46 CDPs for JNNURM mission cities

9 CDPs for small and medium towns in Karnataka

Sewerage Treatment; Water Production;

Solid Waste C&T, Processing and Disposal

Census data Water Distribution; and Sewerage

Network

Data sources for O&M

Source Sector

Estimates provided by sector experts based on data from

Hyderabad city and from multi village schemes

Water

15 projects in Karnataka (Vrishabhavathi; Koramangala

and Challaghatta; and Hebbal)

Sewerage

88

Annex III: India Urban Population Forecasts

110. Indian urban population is expected to double in size from 2001 to 2031. Based on

UN estimates, the population of Indian cities is expected to reach 627 million by 2031,

equivalent to 40 percent of the Indian population.43 Over the same period, the population of

Indian megacities (with population above 5 million) is estimated to double, from 61 million in

2001 to 133 million in 2031. The second largest category of Indian cities (with population

between 1 and 5 million) is expected to record the highest absolute increase in urban

population, from 46 to 126 million over the 30-year period. As a result, the share of Indian

urban population residing in cities with 1-5 million population is expected to increase from 15

to 20 percent over the period 2001-2031 (see Figure 1 and 2).44

111. The annual population growth rate for urban India is expected to stabilize at about

2.5 percent per annum over the period 2001-31. The forecasted growth rate is in line with the

population growth recorded over the period 1995-2000, although below the record growth of 3-

4 percent registered in the previous decades. Cities with population between 1 and 5 million

are expected to grow at a significant higher growth rate than the national average, of about 3.4

percent per annum. The growth rate of cities below 1 million, currently below national

average, is forecasted to steadily increase to reach 2.6 percent by 2020. Megacities are expected

to grow in line with the national average, although their growth rate will experience a decline

from the current level of 4.0 percent to 1.9 percent in 2031. Unfortunately, the UN data

available does not allow distinguishing the sources of population growth – i.e. re-classification

(i.e. cities switching to a higher size class), natural population growth and migration. See

Figure 59 and Table 10.

43

The 2001 urban population of India is estimated at 196 million, based on UN estimates. 44

Population Division of the Department of Economic and Social Affairs of the United Nations

Secretariat, World Population Prospects: The 2006 Revision and World Urbanization Prospects: The 2007

Revision, http://esa.un.org/unup.

89

Figure 59: India Urban Population Growth Rates, 2001-2031

Source: World Urbanization Prospects 2007 and Census of India.

Table 10: Average Annual Growth Estimates, 2001-2031

Class/ Year 2001-05 2005-10 2010-15 2015-20 2020-25 2025-31 2001-31

Class I.A > 5 m 4.0 3.3 1.9 2.9 1.9 1.9 2.6

Class I.B 1-5 m 4.5 3.5 3.8 2.7 3.0 3.0 3.4

Class I.C 1 m-100,000 1.4 1.7 2.3 2.4 2.8 2.7 2.3

Class II 50-100,000

1.0 1.8 2.4 2.4 2.6 2.6 2.2 Class III 20-50,000

Class IV+ < 20,000

All Classes 2.3 2.4 2.5 2.6 2.6 2.6 2.5

Source: World Urbanization Prospects 2007 and authors’ calculations.

Notes: See Table 3 for assumptions.

Methodology

112. Population forecasts are based on estimates provided by the United Nations

Population Division of the Department of Economic and Social Affairs (DESA) in its regular

2.3%2.6%

4.0%

1.9%

4.5%

3.0%

1.4%

2.7%

1.0%

2.6%

0%

1%

2%

3%

4%

5%

00-05 05-10 10-15 15-20 20-25 25-31

All classes I.A : > 5m I.B: 1-5m I.C: 1m-100k II-IV+: < 100k

90

statistical publication, the World Urbanization Prospects (2007 revision).45 The World

Urbanization Prospects is a database reporting past, current and future urban population for

each country in the world and their major agglomerations. The database is revised and

updated every two years. The latest revision was published in 2007. Being the most

comprehensive database on urbanization currently available, the UN data is largely used and

referred to for urban population trends and projections. The UN relies on data produced by

national statistical offices, and adopts national definition of urban areas. Historical urban

population trends are based on and fully consistent with Census of India statistics, and adopt

the concept of urban agglomeration. The UN urban population projections are based on the

basic assumption that urbanization slows down with growing urbanization. A projection

model is built based on the intrapolation and extrapolation of urban-rural growth differentials.

113. Population forecasts for urban India are based on 2001 population census figures and

UN growth rate estimates by city class. For each city class, population is forecasted by

applying the UN population growth rates to 2001 census population figures over the period

2001-2031. Unfortunately, there is no complete alignment between the Census of India city

classes, as reported in this study, and the UN population classes (see Table 2 below). More

specifically, the UN projection model provides estimates for only 5 broad city classes – the

lowest class including all cities with population below 500,000. The Census of India

classification, as adopted in this study, is more fine-grained, with the lowest class including all

towns with population below 20,000. As a result, the same growth rate is applied to all Indian

cities with population below 500,000 given that forecasts for individual classes are not

available.

45

World Urbanization Prospects. The 2007 Revision. United Nations Department of Economic and Social

Affairs (DESA) Population Division - Population Estimates and Projections Section.

http://esa.un.org/unup/

91

Table 11: Census of India versus UN Classes

114. The forecasts are based on the following assumptions:

2001 census population for the two largest city classes (Class I.A and Class I.B) are

taken from the World Urbanization Prospects database, given that there is a perfect

match between these two census classes and the first three UN classes.46 The population

figures reported in the UN database are sourced from the Census of India 2001. For the

other city classes that do not match the UN classes, 2001 population figures are sourced

directly from the Census of India website.47

An exponential growth rate is assumed to forecast urban population, in line with the

methodology applied by the UN.

For the period 2025-30, UN provides projections only for entire urban India, with no

breakdown by city class. Given that the urban India population growth rate for the

period 2025-30 is estimated to be the same as the growth rate for the period 2020-25,

growth rates for individual classes are also assumed to be equal to the growth rates of

the 2025-30 period.

UN estimates are only available up to the year 2030. Population figures for 2031 are

projected assuming the same annual growth applied to the period 2025-2030.

Urban population forecasts for the period 2001-2031 by city class are reported in Table

12 below.

46

http://esa.un.org/unup/ 47 http://www.censusindia.gov.in/Census_And_You/area_and_population.aspx

Census Classes UN classes

Class I.A > 5 m

Class UN.1 10 -5m

Class UN.2 > 5 m

Class I.B 1-5 m Class UN.3 1-5 m

Class I.C 1 m - 100,000 Class UN.4 1 m - 500,000

Class UN.5 < 500,000 Class II 50 - 100,000

Class III 20 - 50,000

Class IV+ < 20,000

92

Table 12: Urban Population, 2001-2031 (million)

Notes:

(1) Separate growth estimates for Class II – IV+ are not available.

(2) UN estimates are only available up to the year 2030. Population figures for 2031 are

projected assuming the same annual growth applied to the period 2025-2030.

(3) For the period 2025-30, UN provides projections only for urban India, with no breakdown

by city class. Given that the national urban population growth rate for 2025-30 is estimated

to be the same as the growth rate for 2020-25, growth rates for individual city classes for

2025-30 are also assumed to be equal to the growth rates for 2020-25.

Class 2001 2005 2006 2009 2010 2015 2020 2025 2030 2031

I.A 61 72 75 82 85 93 108 119 130 133

I.B 46 55 57 63 66 79 91 106 123 126

I.C 99 105 107 112 114 128 144 166 190 195

II 28 29 29 31 32 36 40 46 52 54

III 35 37 37 39 40 45 51 58 66 68

IV+ 27 28 28 30 30 34 39 44 50 52

TOTAL 296 326 333 358 367 416 473 538 611 627

93

Annex IV: Main Results

Investment Requirements

Table 13: Total Urban Investment Requirements, by Sector

2006-2031 (2009 prices), Rs Bn

Rs Bn WATER SEWERAGE SOLID WASTE

Residential

Backlog 1,052 873 92

Additional requirements 1,248 1,056 189

Assets replacement 288 300 207

Total residential 2,587 2,229 487

Industrial

Additional requirements 408 - -

Total industrial 408 - -

TOTAL 2,995 2,229 487

Table 14: Urban Water Investment Requirements, by Sub-sector

2006-2031 (2009 prices), Rs Bn

Rs Bn Production

24/7

Up-gradation

Distribution

extension Total

Residential

Backlog 160 369 522 1,052

Additional requirements 428 - 820 1,248

Re-placement 288 - - 288

Total residential 875 369 1,342 2,587

Industrial

Additional requirements 408 - - 408

Total industrial 408 - - 408

TOTAL 1,284 369 1,342 2,995

94

Table 15: Urban Sewerage Investment Requirements, by Component

2006-2031 (2009 prices), Rs Bn

Rs Bn Network Treatment Total

Residential

Backlog 559 314 873

Additional requirements 700 356 1,056

Re-placement 214 85 300

TOTAL 1,473 756 2,229

Table 16: Municipal Solid Waste Investment Requirements, by Component

2006-2031 (2009 prices), Rs Bn

Rs Bn

Collection &

Transportation Processing Disposal Total

Residential

Backlog 14 51 26 92

Additional requirements 58 54 76 189

Re-placement 109 - 98 207

TOTAL 182 106 200 487

95

Backlog

Table 17: Backlog Percentage, by Sector

I.A I.B I.C II III IV+ Urban

Population Megacities 1-5m 100k-1m 50-100k 20-50k <20k

Percent of total

population

Water

Production 46% 29% 18% 29% 56% 62% 35%

24/7 Up-gradation 57% 55% 48% 41% 37% 31% 48%

Dist. extension 43% 45% 52% 59% 63% 69% 52%

Percent of total

population

Sewerage

Network 54% 54% 72% 80% 85% 86% 67%

Treatment 47% 54% 77% 88% 96% 100% 72%

Percent of total waste

Solid Waste

C&T 13% 48% 41% 41% 65% 75% 41%

Processing 88% 94% 93% 93% 100% 100% 93%

Disposal 100% 100% 100% 100% 100% 100% 100%

96

Per Capita / Unit Costs

Table 18: Per Capita and Unit Costs, Water

Investment O&M

Per Capita Costs

(Rs/capita)

Unit Costs

(Rs/m3)

Per capita annaul

Costs (Rs/capita)

Production 1,448 7,558 -

24/7 Up-gradation 2,513 - -

Distribution Extension 2,828 - -

TOTAL 4,276 - 501

Table 19: Per Capita and Unit Costs, Sewerage

Investment O&M

Per Capita Costs

(Rs/capita)

Unit Costs

(Rs/m3)

Per capita annual

Costs (Rs/capita)

Network 2,373 6,526 -

Treatment 1,240 3,368 -

TOTAL 3,613 9,894 102

Table 20: Per Capita and Unit Costs, Solid Waste

Investment O&M

Per Capita Costs

(Rs/capita)

Unit Costs

(Rs/TPD)

Per capita annual

Costs (Rs/capita)

C&T 137 319,458 175

Processing 131 578,559 -

Disposal 152 835,826 15

TOTAL 421 1,733,844 190

Note: per capita costs are the average for the period 2007-2031.

97

Investment Profile

Table 21: Profile of Total Investment Requirements, by Sector

April 2007-

March 2012

April 2012-

March 2017

April 2017-

March 2022

April 2022-

March 2027

April 2027-

March 2032 TOTAL

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

Rs Bn 2007-2011 2012-2016 2017-2021 2022-2026 2027-2031 2007-2031

Water 525 520 556 676 718 2,995

Sewerage 374 397 433 491 534 2,229

Solid waste 62 61 104 108 152 487

Total 961 978 1,094 1,276 1,404 5,711

Table 22: Investment Requirements (Share of GDP), by Sector

April 2007-

March 2012

April 2012-

March 2017

April 2017-

March 2022

April 2022-

March 2027

April 2027-

March 2032 TOTAL

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

Rs Bn 2007-2011 2012-2016 2017-2021 2022-2026 2027-2031 2007-2031

Water 0.9% 0.6% 0.5% 0.4% 0.3% 2.7%

Sewerage 0.6% 0.5% 0.4% 0.3% 0.2% 2.0%

Solid waste 0.1% 0.1% 0.1% 0.1% 0.1% 0.4%

Total 1.6% 1.2% 1.0% 0.8% 0.6% 5.2%

Table 23: Profile of Household Coverage, by Sector (As of the end of the period)

April 2007-

March 2012

April 2012-

March 2017

April 2017-

March 2022

April 2022-

March 2027

April 2027-

March 2032

11th Plan 12th Plan 13th Plan 14th Plan 15th Plan

2007-2011 2012-2016 2017-2021 2022-2026 2027-2031

Water

Production 75% 84% 90% 96% 100%

Sewerage

Network 53% 69% 82% 92% 100%

Treatment 49% 66% 80% 91% 100%

Solid waste

C&T 74% 85% 92% 97% 100%

Disposal 46% 72% 85% 94% 100%

98

24/7 Pilot Projects

Table 24: 24/7 Water Pilot Projects

City Class Costs

(Rs M) Beneficiaries

PCIC

(Rs/capita) Investment Source

Kolkata I.A 252 218,000 1,157 (Partial) Distr.

replacement JNNURM

Allahabad I.B 1,623 615,360 2,638 (Partial) Distr.

Replacement JNNURM

Nagpur I.B 3,470 2,350,000 1,477 Dist replacement

(40%) JNNURM

Hubli I.C 123 65,765 1,865 Distr. Replacement

(90%) KUIDFC

Gulbarga I.C 40 17,500 2,291 (Partial) Distr.

Replacement KUIDFC

Belgaum I.C 98 41,650 2,353 (Partial) Distr.

Replacement KUIDFC

99

Annex V: Professionalization for Sustainable WSS Development

115. Inadequate human capacity to manage the urban WSS sector carries a very high

opportunity cost. Low professionalization48 in the WSS sector leads to inadequate

maintenance of the assets, which as a result fail to deliver their full economic life. Low

professionalization also translates into sub-optimal WSS system operation, with direct impact

on service to customers. The opportunity to introduce cost-recovery pricing schemes is limited

when quality of service does not meet consumers’ expectations, and willingness-to-pay is low.

This leads to a vicious circle which drastically reduces the prospects for the sustainable

development of the WSS sector: the poor financial performance of the water utilities becomes a

major constraint to sector professionalization and capacity building, which is in turn a

necessary condition for improving the financial prospects of the sector. The monetary value of

inadequate capacity is particularly high in countries with very large investment requirements,

like India, as low professionalization negatively impacts the rate of return of new investments,

by escalating asset replacement costs.

116. The economic benefits of scaling up professionalization in the urban WSS sector are

estimated at about Rs 438 billion (USD 10 billion) over the next forty years, in 2009 prices

(see Box 5).49 The estimation is based on the assumption that the low professionalization of the

WSS sector results into a 10-year reduction in the optimal economic life of the assets. This

implies that the all new assets will have a reduced economic life, unless steps are taken to

improve sector capacity. By improving the professionalization of the WSS sector, investing in

capacity building would extend the life of the assets to their full economic value and defer

assets replacement costs. A real discount rate of 5 percent is used to annualize the monetary

gains of scaling up capacity building. The economic benefits are lower, but still substantial

when a higher real discount rate is applied - the estimated benefits are about Rs 212 (USD 5

billion) based on a 10 percent discount rate. The results indicate that the economic gains of

improving WSS sector capacity are expected to be significantly above the costs, and sizeable

net economic benefits can therefore be reaped by investing in capacity building.

117. What steps are required to improve the professionalization in the WSS sector? The

promotion of continuing professional development and management training for utility staff,

the introduction of professional accreditation, the design of university and vocational course,

and the establishment of active professional associations are among the important steps that

need to be taken to enhance the professionalization of WSS utilities in India. In parallel, there is

a need to improve the capacity of political and administrative decision makers who, by their

actions, affect the ability of utility professionals to do their jobs.

48 Deemed to include all WSS professionals and owners/oversight agencies involved in the process of

delivering, or facilitating the delivery of WSS services. 49 Note the estimated benefits may slightly change as the PCIC are finalized.

100

Box 5: Methodology for estimating the economic benefits of

professionalization in the WSS sector

The economic benefits of investing in the professionalization of the WSS sector are estimated based on the

cost models for urban water and sewerage. The two scenarios of optimal and low professionalization are

compared. Under the scenario of optimal professionalization (Scenario I), the assets have a full economic

life of 30 years. Under the scenario of low professionalization (Scenario II), the life of the assets is

shortened to 20 years. Assets replacement costs are estimated under the two scenarios over the period

2006-2050 for the water sector (production and distribution) and the sewerage sector (network and

treatment). A 5 percent real discount rate is used to annualize the assets replacement costs. The difference

in the Net Present Value between the two scenarios is equivalent to the economic benefits of investing in

capacity building to reach optimal professionalization in the WSS sector. A sensitivity analysis is carried

out based on alternative discount rates.

The estimation is sensitive to the profile of the investments. The assumption is made that investments will

ramp up in the WSS sector so that full coverage is achieved by the end of the 15th Plan. The water cost

model is built under the assumption that a significant part of the existing distribution network has already

reached the end of its economic life, and need to be replaced to deliver 24/7 water supply continuity. The

assumption is made that the required replacement of the existing distribution network will be completed

by 2021. Hence, for the estimation of the economic benefits of professionalization, assets replacement costs

for water distribution are calculated starting from the year 2021. Under the scenario of low

professionalization, the newly built distribution assets would need to be replaced in 2041 (assuming a 20

year economic life of the assets). Under the scenario of optimal professionalization, the assets would need

to be replaced in 2051 (assuming a 30 year economic life of the assets).

101

Annex VI: Cross-country Comparison of Service Performance

Table 25: Urban Piped Water Coverage (2006 and 2004-08)

URBAN URBAN (SELECTED UTILITIES) [3]

Private Connections [1] Private and Shared Connections [2]

2006 2004-08 Obs.[4]

High income[5] 96 96 335

Upper middle income 90 85 1,790

Mexico 96 84 38

Brazil 88 80 603

South Africa 84 86 45

Lower middle income 70 72 773

China 87 91 167

Philippines 69 46 46

India 49 - -

Pakistan 48 - -

Indonesia 34 - -

Nigeria 7 34 3

Low income 43 54 426

Vietnam 59 60 225

Bangladesh 20 48 38

Notes:

[1] Coverage is defined as piped water coverage into dwelling, yard or plot.

[2] Coverage is defined as the share of population with private or shared connections as a percentage of total population under the responsibility of the water utility.

[3] Country level coverage rates are calculated as the average of selected utility data for the period 2004-2008. The coverage rates are for urban areas, as the utilities for which data is available are primarily urban.

[4] The number of observations is equal to the number of utilities times the number of years for which data is available.

[5] Economies are divided according to 2008 GNI per capita, calculated using the World Bank Atlas method. The groups are: low income, $975 or less; lower middle income, $976 - $3,855; upper middle income, $3,856 - $11,905; and high income, $11,906 or more.

Sources:

[1] WHO/UNICEF (http://www.childinfo.org/water_data.php)

[2] IBNET (http://www.ib-net.org/)

102

Table 26: Urban Continuity of Water Supply (2004-08)

COUNTRY LEVEL URBAN (SELECTED UTILITIES) [2]

Duration of Water Supply (Hrs/day)[1]

2004-08 Observations[3]

High income[5] 24 781

Upper middle income 23 3,380

Brazil 24 1,993

South Africa 24 45

Mexico 21 38

Lower middle income 16 834

China 24 167

Philippines 21 46

Indonesia 20 7

Pakistan 10 12

Nigeria 9 12

India 4 10

Low income 19 576

Vietnam 22 272

Bangladesh 11 38

CITY LEVEL[4] 1995-96

Shanghai (China) 24

Jakarta (Indonesia) 18

Manila (Philippines) 17

Lagos (Nigeria) 6

Delhi (India) 4

Karachi (Pakistan) 3

Notes:

[1] The duration of water supply is defined as the average hours of service per day.

[2] Country level duration of water supply is calculated as the average of utility data for the period 2004-2008. The indicator is for urban areas, as the utilities for which data is available are primarily urban.

[3] The number of observations is equal to the number of utilities times the number of years for which utility data is available.

[4] The indicator is calculated for a city's main utility in 1995-1996.

[5] Economies are divided according to 2008 GNI per capita, calculated using the World Bank Atlas method. The groups are: low income, $975 or less; lower middle income, $976 - $3,855; upper middle income, $3,856 - $11,905; and high income, $11,906 or more.

Source:

[1] IBNET (http://www.ib net.org/) [4] Second Water Utilities Data Book – Asian and Pacific Region (http://www.adb.org/Documents/Books/Second_Water_Utilities/default.asp) and Africa Infrastructure Country Diagnostic (AICD) WSS Survey (http://www.infrastructureafrica.org/)

103

Table 27: Urban Per Capita Water Consumption (2001 and 2004-06) –

Private/Shared Connections and Public Taps

COUNTRY LEVEL URBAN (SELECTED UTILITIES) [2]

Per capita Water Consumption (lpcd) [1]

2004-2006 Observations[3]

High income[5] 179 142

Upper middle income 162 494

South Africa 202 10

Mexico 171 18

Brazil - -

Lower middle income 103 213

India 132 8

Philippines 122 40

Indonesia 114 6

China 72 88

Low income 97 201

Vietnam 97 157

Bangladesh 76 17

Per capita water consumption (lpcd) [1]

CITY LEVEL [4] 2001

Shanghai (China) 251 Karachi (Pakistan) 197

Manila (Philippines) 127

Delhi (India) 110

Jakarta (Indonesia) 77

Notes: [1] Per capita water consumption is defined as the volume of total annual residential water consumption (sold through private and shared connections and public taps) as a fraction of the population served.

[2] Country level per capita water consumption is calculated as the average of utility data for 2004-2006. The per capita water consumption is for urban areas, as the utilities for which data is available are primarily urban. Controlled for water pricing by including in the sample only utilities with operating cost coverage ratio (revenues/ operating costs) > 1

[3] The number of observations is equal to the number of utilities times the number of years for which utility data is available. [4] City level per capita water consumption is the value for a city's main utility in 2001. Water pricing is not controlled for at the city level. [5] Economies are divided according to 2008 GNI per capita, calculated using the World Bank Atlas method. The groups are: low income, $975 or less; lower middle income, $976 - $3,855; upper middle income, $3,856 - $11,905; and high income, $11,906 or more.

Sources: [2] IBNET (http://www.ib-net.org/) and 2007 Benchmarking and Data Book of Water Utilities in India (http://www.adb.org/documents/reports/Benchmarking-DataBook/default.asp

[4] Water in Asian Cities - Utilities Performance and Civil Society Views (http://www.adb.org/Documents/Books/Water_for_All_Series/Water_Asian_Cities/default.asp)

104

Table 28: Urban Per Capita Water Consumption (2004-06) -

Private and Shared Connections

COUNTRY-LEVEL URBAN (SELECTED UTILITIES) [2]

Per Capita Water Consumption (lpcd) [1]

2004-2006 Observations[3]

High income[4] 181 139

Upper middle income 126 292

Colombia 105 63

Poland 102 89

Lower middle income 108 192

Philippines 122 40

China 70 88

Low income 96 150

Vietnam 97 114

Bangladesh 84 17

Notes:

[1] Per capita water consumption is defined as the volume of total annual residential water consumption (sold through private and shared connections) as a fraction of the population served. Controlled for water pricing by including in the sample only utilities with operating cost coverage ratio (revenues/operating costs) >1.

[2] Country level per capita water consumption is calculated as the average of utility data for the period 2004-2006. The per capita water consumption is for urban areas, as the utilities for which data is available are primarily urban.

[3] The number of observations is equal to the number of utilities times the number of years for which data is available.

[4] Economies are divided according to 2008 GNI per capita, calculated using the World Bank Atlas method. The groups are: low income, $975 or less; lower middle income, $976 - $3,855; upper middle income, $3,856 - $11,905; and high income, $11,906 or more.

Sources: [1] IBNET (http://www.ib-net.org/)

105

Table 29: Urban Sewerage Network Coverage – Selected Countries (2000-07)

Population connected to wastewater collecting system (%) 2000-07 Countries

High Income 77 38

Upper Middle Income 55 23

Mexico (2005) 68 South Africa (2007) 60 Brazil (2006) 48

Lower Middle Income 56 15

Jordan (2004) 98 Morocco (2007) 87 Armenia (2006) 83 China (2004) 46 Iraq (2005) 26 Paraguay (2007) 15

Low Income 19 5

Notes:

[1] Urban sewerage network coverage is defined as the percentage of the resident population connected to the wastewater collecting systems (sewerage). [2] Economies are divided according to 2008 GNI per capita, calculated using the World Bank Atlas method. The groups are: low income, $975 or less; lower middle income, $976 - $3,855; upper middle income, $3,856 - $11,905; and high income, $11,906 or more.

Source: UNSTATS (http://unstats.un.org/unsd/environment/Time%20series.htm#Waste)

Table 30: Urban Sewerage Treatment Coverage – Selected Countries (2000-07)

Population connected to urban wastewater treatment (%) [1] 2000-07 Countries

High Income 70 37

Upper Middle Income 43 20

South Africa (2007) 57 Mexico (2005) 35 Brazil (2006) 26

Lower Middle Income 36 13

Morocco (2007) 80 Jordan (2004) 52 Armenia (2006) 34 China (2004) 33 Iraq (2005) 26

Low Income 5 4

Notes:

[1] Urban sewerage treatment coverage is defined as the percentage of the resident population whose wastewater is treated at wastewater treatment plants. [2] Economies are divided according to 2008 GNI per capita, calculated using the World Bank Atlas method. The groups are: low income, $975 or less; lower middle income, $976 - $3,855; upper middle income, $3,856 - $11,905; and high income, $11,906 or more.

Source: UNSTATS (http://unstats.un.org/unsd/environment/Time%20series.htm#Waste)

106

Figure 60: Urban per Capita Water Consumption: Selected Countries (2004-06) Private and

Shared Connections

Source: IBnet. Note: Number of utilities in parenthesis.

Figure 61: Urban Water Unit Operational Costs, Selected Countries (2004-08)

Source: IBnet. Notes: 2008 Prices. Number of utilities in parenthesis.

Figure 62: Urban Solid Waste Generation Rate 1995 (Based on a sample of cities)

Source: World Bank (1999).

181

126105 102 108

122

7096 97

84

0

40

80

120

160

200

High income

Upper middle income

Colombia Poland Lower middle income

Philippines China Low income

Vietnam Bangladesh

(139) (292) (63) (89) (192) (40) (88) (150) (114) (17)

Upper middle income Lower middle income Low income

Lpcd

0.94

0.42

0.94

0.300.52

0.29 0.21 0.21 0.17 0.16 0.18 0.14 0.06

-0.100.300.701.101.50

Hig

h

in

com

e

Up

per

mid

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in

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Sou

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Low

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ia (

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Rs

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)

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Low

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me

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Ban

glad

esh

(247) (1,010) (25) (35) (712) (5) (165) (45) (2) (7) (382) (239) (38)

High Upper middle income Lower middle income Low income

US$

/m3

0

10,000

20,000

30,000

40,000

0

1

2

3

4

5

6$

GN

P p

er

Cap

ita

Kg/

cap

/day

Waste Generation Rate GNP per Capita

107

Figure 63: Municipal Waste Collected vs. GNI per capita (2000-07)

Source: UNSTATS; CDPs for India.

Figure 64: Urban Waste Generation in India 1995

Source: World Bank (1999).

India0

1

2

3

4

0 25,000 50,000 75,000

kg/c

apit

a se

rve

d/d

ay

GNI per capita ($)

0

2

4

6

8

10

12

14

0

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0.3

0.4

0.5

0.6

0.7

Nag

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108

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