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Municipal Corporation of Delhi

Feasibility Study and Master Plan for Optimal Waste Treatment and Disposal for the Entire State of Delhi based on Public Private Partnership Solutions Volume 6: Municipal Solid Waste Characterisation Report

April 2004

. in association with Kadam Environmental Consultants

Municipal Corporation of Delhi

Feasibility Study and Master Plan for Optimal Waste Treatment and Disposal for the Entire State of Delhi based on Public Private Partnership Solutions Volume 6: Municipal Solid Waste Characterisation Report

April 2004

Report no. 006

Issue no. 001

Date of issue 29-04-2004

Prepared Project Team

Checked SKA, SAK

Approved SKA

Feasibility Study and Master Plan for Optimal Waste Treatment and Disposal for the Entire State of

Delhi based on Public Private Partnership Solutions

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Table of Contents

1 Introduction 3 1.1 Project Background 3 1.2 Objectives and Output of the Study 4 1.3 Municipal Solid Waste Characterisation Report 4

2 Previous Studies on Municipal Solid Waste Generation and Composition 6

2.1 Sources of Municipal Solid Waste Generation 6 2.2 Municipal Solid Waste Received at Landfills 8 2.3 Municipal Solid Waste Composition 12

3 Waste Characterisation Survey Methodology 16 3.1 Parameters Tested and Analytical Methods Used 16 3.2 Socio-Economic Waste Survey 17 3.3 Survey of Specific Waste Streams 21 3.4 Survey of Waste Received at Landfills and Compost

Plants 23

4 Waste Sampling Results 27 4.1 Waste from Residential Areas – Higher Income

Groups 27 4.2 Waste from Residential Areas – Middle Income

Groups 28 4.3 Waste from Residential Areas – Lower Income

Groups 29 4.4 Waste from Residential Areas – JJ Clusters 30 4.5 Waste from Vegetable Markets 31 4.6 Waste from Institutional Areas 32 4.7 Waste from Streets 33 4.8 Waste from Commercial Areas 34 4.9 Waste Entering Landfills 35 4.10 Waste Entering Compost Plant 37



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4.11 Waste Rejects from Compost Plant 37 4.12 Comparison of Results of COWI-Kadam (2004),

JICA (2004) and NEERI (1996) 38 4.13 Waste Flow Diagram 40 4.14 Potential suitability of Selected Technologies for

Sampled Waste Streams 41 4.15 Analysis of Household Solid Waste Survey 42 Appendices: A: Detailed Sampling Results B: Photo Documentation



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1 Introduction United Nations Office for Project Services (UNOPS) has contracted COWI of Denmark (with Kadam Environmental Consultants, India, as local partners) for implementation of the project “Feasibility Study and Master Plan for Optimal Waste Treatment and Disposal for the Entire State of Delhi Based on Public Private Partnership Solutions”1. The project beneficiary is the Municipal Cor-poration of Delhi. The United Nations Development Programme (UNDP), New Delhi, is also co-operating with the Consultants’ Project Team in developing the required output.

1.1 Project Background The State of Delhi with a population of approximately 15 millions is one of the biggest metropolises of the World. Municipal Corporation of Delhi (MCD) is responsible for municipal solid waste management in most of the State running a comprehensive operation of street cleansing, waste transportation and waste disposal involving a large number of staff and mobile equipment and plant. New Delhi Municipal Corporation (NDMC) and the Cantonment Board are re-sponsible for municipal solid waste management in smaller central areas of the State completing the State territory.

The municipal solid waste operation under MCD is by far the biggest in the State with more than 50,000 employees. Collection and transportation is carried out by the respective bodies. The following treatment and disposal facilities are present in the state of Delhi:

• NDMC operated composting plant in Okhla;

• A composting plant in Bhalswa, operated as a joint venture between MCD and a private company;

• MCD operated composting plant in Okhla;

• MCD operated landfills at Gazipur, Okhla and Bhalswa. 1 Contract no. CPH-03-001, Project no. INT/03/R11. Activity no. 03 IND 1150. Contract-ing date 02 January 2004



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1.2 Objectives and Output of the Study The current study forms part of a series of new initiatives in municipal solid waste management. The broader objective of this work is to engage private op-erators for collection and transportation of municipal solid waste in selected zones under MCD and to implement a treatment and disposal plan for the entire State of Delhi through Public Private Partnerships. The specific objective for the present study is to converge on an optimal and economically and environ-mentally sustainable waste treatment and disposal plan for the State of Delhi.

The output of the study defined in the Terms of Reference is a Master Plan for Treatment and Disposal of Municipal Solid Waste covering the following re-ports.

• Volume 1: Inception Report

• Volume 2: Study Tour report

• Volume 3: Executive Summary

• Volume 4: Master Plan Report

• Volume 5: Current Municipal Solid Waste Facilities in Delhi

• Volume 6: Municipal Solid Waste Characterisation Report

• Volume 7: Master Plan Appendices

• Volume 8: Institutional Capacity Developments in MCD (CSE) and Private Public Partnership Framework and Road Map

• Volume 9: Technical Report (Okhla Compost Plant and C&D Waste Proc-essing Facility)

• Volume 10: Action Plan 2005 - 2009

1.3 Municipal Solid Waste Characterisation Report This report (Volume 6) of the project; covers the requirement of characterising waste in the state of Delhi as per the Terms of Reference2.

2 Terms of Reference, 03 IND 1150: Feasibility Study and Master Plan for Optimal Waste Treatment and Disposal for the Entire State of Delhi Based on Public Private Partnership Solutions. November 2003.



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The first part of this report provides information regarding the generation and composition of Municipal Solid Waste (MSW) in Delhi. This is followed by the survey methodology and summary results of the waste characterisation survey conducted by the Consultants under the Master Plan and Feasibility Study pro-ject.



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2 Previous Studies on Municipal Solid Waste Generation and Composition

2.1 Sources of Municipal Solid Waste Generation Delhi had an average family size of 5.06 persons in 1990. Assuming, a similar average household size, and a population of 150 lakhs (15 million), there would be 29,64,427 (2.96 million) households in Delhi today, these becoming the largest source of solid waste generation.

Besides the large number of the households, the following sources also gener-ate significant amounts of solid waste in the state.

Markets for Agricultural Products

As on 31st March 2001, there were nine principal markets and twelve sub-markets functioning in Delhi, under the Delhi Agricultural Marketing Board. These include: the Azadpur fruit and vegetable market (the biggest fruit and vegetable market in Asia and one of the biggest in the world), APMC Narela, APMC Najafgarh, Fish Market Gazipur, APMC Shahdara, APMC Zakhira (fodder market), Khoya / Mawa Market Bagh Diwar, and the Flower Market, at Mehrauli.

Retail and Commercial Markets

Delhi has about 16,000 organised markets; 24,600 wholesale establishments; 100 weekly markets; 6000 makeshift shopping spaces and 1, 40,000 informal retail units. All these are generating wastes, most of which arrive at the landfills after scavenging.

Hospitals and Nursing Homes

Delhi has more than 80 hospitals and 1000 nursing homes. Reportedly, provi-sions requiring independent segregation, treatment and disposal of bio-medical wastes under the Bio-Medical Waste (Management & Handling) Rules, have started being implemented. However, a study done by the Delhi College of En-gineering (DCE 2004) gives photographic evidence of bio-medical waste end-ing up at landfills being operated by the MCD, and it is possible that a small



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portion of potentially hazardous bio-medical wastes continue to be deposited at the landfills.

Industries

The Economic Census of 1998 indicates that Delhi has 1.29 lakh industrial units employing about 14.40 lakh persons. The manufacturing sector in Delhi contributes about 7-8% to the state income. Delhi does not have a single func-tioning hazardous waste facility to receive wastes from these units. Conse-quently, industrial wastes that are not stockpiled at industries are likely to end up in dhalaos or are clandestinely entering landfills.

Slaughterhouses

As per MSW Rules, 2000, “wastes from slaughter houses, meat and fish mar-kets which are biodegradable in nature, require to be managed to make use of such wastes”. However, except for a single government operated slaughter-house, a significant amount of slaughtering of animals is carried out by the in-formal sector. Consequently management of slaughterhouse wastes is a prob-lem and such wastes tend to reach landfills, specially the landfill at Gazipur.

Construction Demolition Activities

Construction and demolition activities within Delhi lead to generation of Con-struction Demolition Waste. Management of this waste falls under the purview of MCD’s Engineering Department, and this department utilises the waste in filling operations, disposing the remainder to the landfills. As per discussions with the MCD’s CSE department, currently about 1000 TPD of such waste was deposited daily at the three landfills, at Gazipur (200 TPD), Bhalswa (500 TPD) and Okhla (300 TPD).

Street Sweeping

The 49000 Safai Karamcharis or street sweepers employed by the MCD sweep the streets of Delhi and these activities result in a significant amount of waste generation, a large portion of which is inert, although the proportion of inert material varies depending on location. The street sweeping was not segregated from household wastes at most collection places, leading to an increase in inerts in the mixed wastes.

Institutional Areas

Delhi has a high proportion of institutions ranging from educational institutes to government complexes and institutes carrying out research and developmental activities in different spheres. These too, generate solid wastes in significant amounts.



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2.2 Municipal Solid Waste Received at Landfills Information available with regard to the MSW quantities across 12 months (April - March) for the financial year 2002-3 and 5 months (April – August) for the financial year 2003-4, based on weighbridge data at the landfill sites was collected from the Municipal Corporation of Delhi (MCD)3. These are pre-sented in Table 2.1 and Table 2.2. The changes (in absolute numbers and per-centages) during the April-August period for the financial years 2002-3 and 2003-4 are presented in Table 2.3.

3 Earlier data is available, but has not been used since it was not based on accurate weighbridge data.

Feasibility Study and Master Plan for Optimal Waste Treatment and Disposal for the Entire State of Delhi based on Public Private Partnership Solutions

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Table 2.1: Municipal Solid Waste Received at Landfills during 2002-2003 as per figures provided by the MCD (in tonnes unless indicated) No. Zone Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Total % of

MSW

1 Shahadra-South 14,441 14,572 14,367 17,115 15,828 19,136 18,005 16,938 15,890 15,861 15,650 15,551 1,93,354 10.8

2 Shahadra- North 11,165 11,569 13,195 14,192 12,929 14,632 13,056 13,770 12,953 13,952 13,898 12,662 1,57,973 8.8

3 Rohini 11,210 11,771 12,791 14,749 12,503 12,382 14,427 13,961 13,873 12,536 12,755 12,355 1,55,313 8.7

4 Civil Lines 10,220 11,051 11,384 12,956 13,871 12,856 13,549 14,265 14,305 13,207 13,829 14,190 1,55,683 8.7

5 Najafgarh 6,583 7,253 7,045 7,677 9,498 6,589 8,386 9,066 9,152 8,549 8,367 9,012 97,177 5.4

6 Narela 1,947 2,100 2,127 2,426 2,802 2,388 2,504 2,687 2,798 2,709 2,505 3,031 30,024 1.7

7 City 12,555 11,638 11,881 13,342 15,530 15,470 14,785 14,727 13,716 13,715 13,412 14,329 1,65,100 9.2

8 Karol Bagh 9,501 10,023 10,437 11,125 9,726 8,219 10,385 10,409 10,720 9,680 10,038 10,715 1,20,978 6.8

9 Central 10,781 11,582 12,058 11,554 10,749 11,529 12,131 12,104 12,764 11,735 11,082 11,513 1,39,582 7.8

10 South 10,652 11,005 11,749 10,759 10,235 10,957 11,753 11,604 11,795 11,600 11,238 11,212 1,34,559 7.5

11 Sadar Paharganj 8,369 7,228 7,864 8,993 8,821 9,624 9,452 8,885 8,057 7,788 8,584 8,063 1,01,728 5.7

12 West 15,025 13,857 15,638 16,049 13,038 12,876 15,485 17,207 16,373 14,864 14,809 14,818 1,80,039 10.1

13 NDMC, Can-tonment Board & Other areas

9,838 13,140 12,601 12,625 13,756 16,389 13,988 13,156 12,661 12,121 13,224 12,542 1,56,041 8.7

Total 1,32,287 1,36,789 1,43,137 1,53,562 1,49,286 1,53,047 1,57,906 1,58,779 1,55,057 1,48,317 1,49,391 1,49,993 17,87,551 100

% of total 7.4 7.7 8.0 8.6 8.4 8.6 8.8 8.9 8.7 8.3 8.4 8.4 100


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Table 2.2: Municipal Solid Waste Received at Landfills during 5 months of 2003-2004 as per figures pro-vided by the MCD (in tonnes unless indicated) No. Zone Apr May Jun Jul Aug Total % of

MSW

1 Shahadra - South 14,816 14,958 16,168 15,062 17,459 78,463 10.3

2 Shahadra - North 11,806 12,314 11,912 10,516 13,405 59,953 7.9

3 Rohini 12,076 12,467 11,961 12,349 15,967 64,820 8.5

4 Civil Lines 12,579 12,753 12,934 14,620 16,151 69,037 9.1

5 Najafgarh 8,250 7,139 7,499 9,747 11,545 44,180 5.8

6 Narela 2,686 2,292 2,369 2,805 4,027 14,179 1.9

7 City 13,744 12,302 13,129 13,741 14,018 66,934 8.8

8 Karol Bagh 10,392 10,922 11,684 11,589 14,758 59,345 7.8

9 Central 10,796 11,127 10,627 12,913 12,693 58,156 7.6

10 South 10,279 10,481 12,334 12,693 14,119 59,906 7.9

11 Sadar Paharganj 8,250 7,267 7,399 8,271 9,614 40,801 5.4

12 West 13,813 14,219 14,040 12,889 19,261 74,222 9.8

13 NDMC, Cantonment Board & Other areas

14,161 12,057 12,345 14,613 18,252 71,428 9.4

Total 1,43,648 1,40,298 1,44,401 1,51,808 1,81,269 7,61,424 100


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Table 2.3: Monthly & April-August increase or decrease (-) in MSW receipt at landfills between 2002 & 2003, (in tonnes unless indicated) No. Zone Apr May Jun Jul Aug Total %

increase / decrease

1 Shahadra - South 375 386 1,801 -2,053 1,631 2,140 2.8

2 Shahadra - North 641 745 -1,283 -3,676 476 -3,097 -4.9

3 Rohini 866 696 -830 -2,400 3,464 1,796 2.8

4 Civil Lines 2,359 1,702 1,550 1,664 2,280 9,555 16.1

5 Najafgarh 1,667 -114 454 2,070 2,047 6,124 16.1

6 Narela 739 192 242 379 1,225 2,777 24.4

7 City 1,189 664 1,248 399 -1,512 1,988 3.1

8 Karol Bagh 891 899 1,247 464 5,032 8,533 16.8

9 Central 15 -455 -1,431 1,359 1,944 1,432 2.5

10 South -373 -524 585 1,934 3,884 5,506 10.1

11 Sadar Paharganj -119 39 -465 -722 793 -474 -1.1

12 West -1,212 362 -1,598 -3,160 6,223 615 0.8

13 NDMC, Cantonment Board & Other areas

4,323 -1,083 -256 1,988 4,496 9,468 15.3

Increase / decrease 11,361 3,509 1,264 -1,754 31,983 46,363 6.5

Increase / decrease in % 8.6 2.6 0.9 -1.1 21.4 6.5



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Inferences from the above tables are:

• Total MSW received at the three landfills at Bhalswa, Okhla and Gazipur4, for the year 2002-2003 was 1,787,551 tonnes. It would mean 4,897 tonnes per day assuming the landfills are operational all 365 days a year. The waste was subject to some scavenging at the landfill and thus the total quantity of waste actually disposed of in the landfill would be slightly less than this figure;

• There was an increase of 6.5% in receipt of MSW at landfills over the April-August period between the years 2002 and 2003. This increase was not equally distributed. Certain zones (Civil Lines, Najafgarh, Narela, South Zone & NDMC/Cantonment Board/Other Areas) have experienced double-digit growth vis-à-vis other zones, that have seen slow or even negative growth. Similarly, temporally the growth has been irregular with April and August recording increases of 8.6% and 21.4% growth respec-tively, with May, June and July recording slow or negative growth. Cli-matic conditions and short term factors could also cause increase or de-crease in MSW deposition at landfills, besides demography and economics. Therefore, in the absence of reliable medium / long term historical data, not much could be concluded about the growth pattern of MSW from these short term trends, except that growth in MSW deposition at landfills was actually happening. (This also indicated the importance of collecting and collating such information regularly, especially with the availability of weighbridge data);

• MSW collected zone-wise varied from a high of 193,354 tonnes at Sha-hadra – South, (about 10.8% of the total) to a low of 30,024 tonnes at Narela (about 1.7% of the total). The West Zone was also a major source of MSW with 10.1% of the total MSW received. In order of generation, the zones that follow are: City, Shahadra – North, Others5, Civil Lines, Rohini, Central, South, Karol Bagh, Sadar Paharganj and Najafgarh;

• Monthly MSW collected across the year 2002-3 varied from a low of 132,287 tonnes (7.4% of total for the year) in April to a high of 158,779 tonnes (8.7% of total for the year) in November.

2.3 Municipal Solid Waste Composition As discussed in the previous sections, waste reaching the landfill sites com-prised of biodegradable waste, non-biodegradable waste, recyclables, silt and construction wastes, wastes from hospitals and sometimes also industrial waste. Studies carried out by MCD on the physical and chemical characteristics of the

4 MSW supplied to composting plants is registered at nearby landfills and transferred to the plants. 5 Others include the NDMC and Cantonment Board areas serviced by MCD.



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waste generated in the state of Delhi are presented in Table 2.4 and Table 2.5 respectively.

Table 2.4: Physical Composition of Municipal Solid Waste in Delhi Parameters Percentage Biodegradable 38.6 Paper 5.6 Plastic 6.0 Metal 0.2 Glass and Crockery 1.0 Non-biodegradable (leather, rubber, bones, and other synthetic mate-rial)

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Inert (stones, bricks, ashes etc.) 34.7 Source: Performance measurement of pilot cities, TERI, March 2002. Table 2.5: Chemical Composition of Mixed Municipal Solid Waste in Delhi Parameter Percentage Moisture 43.8% Organic Carbon 20.5% Nitrogen as N 0.9% Phosphorus as P2O2 0.3% Potassium as K2O 0.7% C/N ratio 24.1 Calorific value 713 kCal/kg Source: Performance measurement of pilot cities, TERI, March 2002. A recent JICA financed study (IPE 2004) conducted sample surveys in three localities in the MCD service area of Delhi. Table 2.6 shows the results of the surveys taken from the report6.

6 The data was made available through the draft report given to the consultants by MCD, (pending final verification)



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Table 2.6: Selected Results from Sampling Survey financed by JICA (IPE 2004) Location

Jahangirpuri Krishan Kunj Vasant Kunj Social characterisa-tion

Low income Middle income High income

Household income (INR)

Maximum earning less than 3,000 per month

Maximum earning between 5,000-12,000 per month

More than 2/3 earn more than 15,000 per month

Average family size 5 5 4 Average daily quan-tity of waste per fam-ily (kg)

0.729 1.423 1.238

Average daily quan-tity of biodegradable waste per family (kg)

0.448 (62%) 0.870 (61%) 0.794 (64%)

Average daily quan-tity of recyclable waste per family (kg)

0.162 (22%) 0.462 (33%) 0.342 (28%)

Average daily quan-tity of other waste per family (kg)

0.119 (16%) 0.091(6%) 0.102 (8%)

Other waste here is the sum of the two fractions “hazardous waste” and “other waste” used in the JICA financed survey.

Inferences from the above are:

• Per capita waste generation figures for high income, middle income and low income groups are 309 gm, 285 gm and 146 gm respectively.

• The contents of biodegradable waste was shown to be high (38.6%) fol-lowed by very high contents of inert waste (34.7%) mainly consisting of street sweeping and construction waste;

• Recyclables i.e. papers, plastics, metals and glass constituted around 10% of the total waste, however this depends very much on where in the waste cycle the measurements actually took place;

• The moisture content of the waste was high (43.8%) and the calorific value of the waste was very low of around 713 kCal/kg making it unsuitable for thermal treatment.

The moisture content in the MSW varied from 25% in dry season to 45% in the rainy season. The solid waste generated from different sources and collected



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from various locations may show variation in the composition. The C/N ratio varied from 20-36 and the calorific value ranges from 528-895 kCal/kg.



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3 Waste Characterisation Survey Methodology

The Terms of Reference for the project and the proposal from the Consultants both stipulated the survey to be conducted for waste collected at the waste col-lection points (Dhalaos). From the discussions with the Task Force appointed by MCD, it was understood that MCD wished the survey to cover also the waste generation, a possible advantage of which could be to assess individual waste streams for specific waste treatment technologies. COWI/Kadam ac-knowledged this point of view and prepared an alternative - and more resource demanding - approach, based on three types of surveys, keeping the require-ment of 160 samples mentioned in the TOR as a reference point:

• Socio-economic waste survey covering residential areas across different income groups – 56 samples;

• Survey of specific waste streams covering commercial areas, vegetable markets, institutional areas, and streets – 35 samples;

• Survey of waste received at landfills and compost plants – 69 samples;

Planning for the waste characterisation survey started right from the inception of the project and involved setting up of a project laboratory, sampling teams, getting permissions from relevant agencies and arrangement of logistics involv-ing sample collection, transport, analysis and logistics. These three surveys are detailed in Chapter 4.

3.1 Parameters Tested and Analytical Methods Used All samples were tested for:

• Composition of waste, as per Table 3.3,

• Moisture content,

• Ash content,



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• Bulk density,

• Calorific value, and

• Carbon/Nitrogen (C/N) ratio

A project laboratory was set up by the Consultants for testing of solid waste. For testing of carbon, dry samples were sent (as part of C/N ratio analysis) to suitably equipped laboratories equipped for analysis of the same, a protocol for which had been established. Table 3.1 states the methods employed for analysis of samples. Methods used were those prescribed by the Bureau of Indian Stan-dards for testing of solid wastes, except bulk density which was carried out us-ing the guidance given in WB 2001.

Table 3.1: Methods used for analysis of wastes Method Name Methodology Method for preparation of solid waste sample for chemical and micro-biological analysis

IS:9234, 1979, Reaffirmed 1998

Methods of analysis of solid wastes (excluding indus-trial solid wastes) including:

IS:10158, 1982, Reaffirmed 1995

Carbon (Serial Number 4) Kjeldahl (Organic) Nitrogen (Serial Number 6) Physical Analysis and Determination of Moisture in Solid Wastes, excluding Industrial Solid Wastes

IS: 9235, 1979, Reaffirmed 1997

Method of detecting Ash and Sulphated Ash IS:8769, 1978 Bulk density7 WB 2001 Calorific value IS:1350, Part IV/ Section 1, 1974,

Reaffirmed 1994

3.2 Socio-Economic Waste Survey

3.2.1 Selection of Sampling Areas Selection of the sampling area was done taking help of MCD staff and due con-sideration was given to knowing which area would be indicative with regard to socio-economic distribution of the Delhi as a whole. Selected areas included a survey of four socio-economic groups of residential areas - high income, mid-dle income, low income and jhuggi-jhopdi (slum) clusters (JJ clusters). A total of 8 surveys were planned and these covered one high income area, two middle income areas, three lower income areas and two jhuggi-jhopdi (slum) clusters. 7 Bulk Density can be determined by simply obtaining a 1m3 representative sub-sample of the waste selected for analysis and loosely filling a container of known volume and weight with the waste materials. The density is then the weight of the container and waste, minus the weight of the empty container. The results are expressed in kg/ m3. However the waste densities will tend to increase along the management chain due to settling and compaction.



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The reason for this break up was to get an indicative fraction of waste from Delhi’s socio-economic structure.

Prior to site selection, time was spent in studying neighbourhood level maps to locate various residential areas according to the above classification. Samples were collected as they are disposed daily to the neighbourhood dhalao. This also means that waste (newspapers etc) sold to iterant buyer was not part of the sample survey. For the purpose of ensuring co-operation of the households, prior to sampling resident welfare associations, community leaders, MCD offi-cials and informal waste collection contractors were approached to enlist their support in sampling of households. Finalisation of areas was done considering:

• Approach and accessibility to the area / neighbourhood,

• An estimation of sampling logistics (such as waste collection timings and sampling equipment) based on reconnaissance surveys of the areas with re-spective MCD officials,

• Availability of manual labourers or informal contractors handling wastes for assistance in source separation, and

• Willingness of such persons to co-operate, including their willingness to use personal protective equipment such as gloves and face masks,

Finally, a tentative schedule was prepared for collecting samples from individ-ual house holds. The areas selected for sampling are shown in Table 3.2.

Table 3.2: Areas selected for sampling - socio-economic survey Location Socio-economic level Samples Hauz Khas (Safdarjang Development Area) Higher Income Group 7 Vikas Puri Middle Income Group 7 Vivek Vihar, Phase II Middle Income Group 7 Kalyanpuri, Block 16 Lower Income Group 7 Sadhnagar, Palam Lower Income Group 7 Sultanpuri Block ( A,B,C) Lower Income Group 7 Ring road, opposite Nagla Machi village Jhuggi-Jhopdi (slums) cluster 7 Wazirpur Jhuggi-Jhopdi (slums) cluster 7

Total 56

3.2.2 Sample Collection, Preparation and Handling Each survey area contained approximately 50 households and each survey was run for seven days with samples being collected every day totalling approxi-mately 2,800 household samples for the entire survey. Each household was provided a plastic bag for storing their daily waste and the bag containing solid waste was collected next morning, ensuring that no waste was delivered to itin-erant waste buyers. Each sample was coded, weighed and mixed with other



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samples in a specified manner. Care was taken to prevent mixing of other mat-ter / soil with collected waste

Following activities were carried out prior to and during actual sampling:

Before sampling:

• Each household was explained why the survey was being undertaken and their co-operation was sought,

• Numbered plastic bags were distributed for depositing waste one day prior to sampling.

During sampling:

• Waste was collected from each household on a door-to-door collection ba-sis with replacement of the previous day’s bag with a fresh bag having the same number,

• All bags thus collected were taken to a suitable, level space, with a clean plastic sheet spread on the ground, preferably near a dhalao,

• The bags were then individually weighed and emptied on the plastic sheet lying on the ground,

• Bulk density of the entire collected waste was noted at the site,

• The entire waste collected was then segregated into different streams as per the segregation format mentioned in Table 3.3. Each segregated category was weighed and a percentage for each (on wet basis) was derived and noted,

• Segregated samples totalling 5.0 kg were collected and put in separate, coded plastic bags. The proportion of each constituent was relative to its composition that day,

• Plastic bags containing waste thus separated were dispatched to the labora-tory along with a data sheet that also served as a chain of custody docu-ment.

• Remaining waste was disposed in the nearest Dhalao after completion of composite sample preparation. The manual labourers or informal contrac-tors were allowed to take away any recyclables collected.

Preparation of composite sample, in laboratory:



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• A space in the laboratory was kept reserved for storage of incoming sam-ples. The segregated samples for the day were arranged in a row,

• The laboratory staff prepared a composite sample from the waste contained in the received, segregated bags on a proportionate basis using information contained in the data sheet,

• Composite samples thus prepared were analysed for different parameters.

The advantage of keeping segregated samples in the laboratory (as opposed to one composite sample) was that it allowed analysis of individual constituents of waste as well as composites. It also allowed a constant level of sample integrity in case of re-analysis. This is because grab composite samples were avoided and a constitution of samples, as observed at site, was always maintained.

Table 3.3: Constituent information collected - physical composition study Sr. No.

Composition Category Products included

Paper, news paper, wrappers 1 Paper Recyclable Cardboards, packaging papers Plastic bags, plastic bottles 2 Plastic Recyclable Plastic packaging materials, wires

3 Rubber Recyclable Rubber, Tyre Vegetable matter Food waste

4 Vegetable Biodegradable

Garden waste, Wood Biomedical, syringes Discarded medicines, bottles containing pesticides, medicines, dry cells, electronic circuits, Other hazardous material

5 Hazardous material

Other

Thermacol, foam packing materials Ferrous, cables 6 Metals Recyclable Nonferrous, foils, cables etc.

7 Glass Recyclable Glass, bottles Ceramics 8 Ceramics Inert Pottery Soil, sand, ash, dust 9 Soil Inert Construction material, stones, bricks

10 Miscellaneous Other Cloth and material not covered under previ-ous categories



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3.3 Survey of Specific Waste Streams

3.3.1 Selection of Sampling Areas

This survey included random sampling of specific waste streams that are of in-terest for planning of future waste treatment and disposal systems. The areas selected for sampling are shown in Table 3.4. Activities similar to those men-tioned in Section 3.2.2 (for residential areas) and involving study of maps, site visits, meetings with concerned persons etc. were carried out prior to site selec-tion.

Table 3.4: Areas selected for sampling - specific waste streams Location Specific Waste Stream Samples Azadpur vegetable market (APMC) Vegetable Market 5 Okhla vegetable market (APMC) Vegetable Market 5 Nehru place commercial shopping complex Commercial area 5 Chandni Chowk main market Commercial area 5 Indian Institute of Foreign Trade - Qutub Institu-tional area

Institutional area 5

Miranda House college - Delhi University Campus Institutional area 5 Patpar Ganj Road - Railway flyover to Vikas Marg Street sweeping 1 Ghonda Road - Wazirabad road to Bus depot Street sweeping 1 Dariyaganj Road – Delhi gate to Vegetable market Street sweeping 1 Najafgarh Road - Motinagar II to Raja garden Street sweeping 1 Aurobindo Marg – IOC office to IIT Flyover Street sweeping 1

Total 35

The generation and composition of non-hazardous waste from industries is characterised by huge variations from one generator to the other. It was beyond the scope and resources of the present study to sample such waste for analysis and to establish a sufficient pool of data for reliable interpretation of composi-tion. Other waste types that were not sampled for analysis of composition in-clude construction and demolition waste and slaughterhouse waste, since these are planned to be routed to purpose built treatment and disposal facilities.

3.3.2 Sample Collection, Preparation and Handling For the purpose of enlisting co-operation of the target groups prior to sampling, concerned authorities, administrative personnel and MCD officials were ap-proached to enlist their support in sampling of afore mentioned specific waste streams.

Commercial areas:

• The survey for each commercial area entailed sampling of 50 shops for one day, totalling 100 shops’ samples for the survey, since two commercial ar-



22


eas were selected. This exercise was carried out twice; i.e. two commercial areas were sampled and a total of 10 samples were sent to the laboratory.

• The activities done before, during and after sampling for commercial areas were similar to those carried out during sampling of households described in Section 3.2.2, except that mixing was carried out by collecting wastes from groups of 10 shops, thereby preparing 5 heaps, with each heap being segregated based on its composition, with representative fractions being sent to the laboratory for analysis. Thus, a total of 5 samples were prepared for analysis in the laboratory.

Institutional areas:

• It was observed that institutional areas contained separate waste streams such as administrative block, canteen, hostel mess, hostel house keeping and garden sweeping. For each institutional area, these 5 waste streams were collected in the morning and prepared into heaps on any one working day, other than Monday. Each heap was segregated based on its composi-tion and a representative sample of the heap was prepared on weight basis and checked for bulk density. Thus, a total of 5 samples from each institu-tional area were prepared and sent for laboratory analysis.

• This exercise was planned to be carried out twice; i.e. two institutional ar-eas were sampled and a total of 10 samples were sent to the laboratory. The activities done before, during and after sampling for institutional areas were similar to those carried out during sampling of households described in Sec-tion 3.2.2, with the exceptions mentioned in the above paragraph.

Vegetable markets:

• The survey for each vegetable market entailed collection of waste from four different waste streams from different sections within each market. These sections were loosely classified into fruits, seasonal vegetables, perennial vegetables and a section for common vegetables sold in large quantities such as potatoes, onions and tomatoes. Wastes from all four streams were collected in the morning, and representative samples were taken from each section after segregation on weight basis. A fifth composite sample was prepared from the other four samples on the basis of composition on weight basis. All five samples were checked for bulk density.

• Thus a total of 5 samples were collected and sent to the laboratory for analysis. The activities done before, during and after sampling for institu-tional areas are similar to those carried out during sampling of households described in Section 3.2.2., with the exceptions mentioned in the above paragraph.



23


Streets:

• It was noted that each street sweeper had a fixed stretch of street called a ‘street sweeping beat’ in which he or she had to sweep the street and collect and deposit the waste into dhalaos. Sections of streets selected for sampling in the survey varied from 0.5 to 1.0 km. It was observed that amongst the streets selected, several beats were present, the exact number depending upon the length of the stretch of street selected for sampling and each safai karamchari prepared heaps and the numbers of heaps varied depending upon location. All heaps within the stretch were collected in wheel barrows and then brought to a location, typically near a dhalao. The entire heap thus prepared was weighed, segregated on the basis of its composition and then one representative composite sample was prepared on the basis of weight and sent to the laboratory for analysis. In all 5 streets were sampled.

• The activities done before, during and after sampling for institutional areas were similar to those carried out during sampling of households described in Section 3.2.2., with the exceptions mentioned in the above paragraph.

3.4 Survey of Waste Received at Landfills and Compost Plants

This survey included random sampling of specific waste supplies to the 3 land-fills and 2 compost plants in operation during the survey period8. Table 3.5 shows the number of samples taken.

Table 3.5: Areas selected for survey of specific waste streams Waste Facility Type of facility No. of Samples Okhla Compost Plant Compost plant 4 Bhalswa Compost Plant Compost plant 5 Okhla Landfill 20 Gazipur Landfill 20 Bhalswa Landfill 20

Total 69

3.4.1 Sample Selection

Landfills:

Several hundred truck trips are made to the three landfills located at Gazipur, Bhalswa (including Bhalswa crossing) and Okhla each day. Twenty samples were sampled at each landfill as per the sampling programme. In order to have indicative sampling of the incoming waste into the landfills, it was thought nec-essary to understand the nature of wastes entering the landfills. Hence the Con-

8 The Okhla compost plant operated by the MCD was either closed during the survey period or operating in sub-optimal conditions. Hence sampling from this plant was avoided.



24


sultants collected information of incoming wastes into the three landfills from 6th February 2004 to 12th February 2004, (information at Okhla was also col-lected on 5th February 2004). The resulting information was used in selecting trucks from which waste was to be sampled.

For the observation period, it was noted that:

• The three landfills at Okhla, Bhalswa and Gazipur respectively received an average of 275, 607, and 416 truck trips daily.

• The incoming trucks were visually observed and notes were made with re-gards to their general contents in terms of the type of waste they carried.

• Information was also collected with regards to the weight of solid waste carried by each truck as it entered the landfill, and its source of generation.

On the basis of the above observations a sampling strategy was drawn for waste streams covering the three sites as follows:

• At Okhla, it was noted that overwhelming proportion of trucks carried mixed wastes from residential areas while a few trucks carried specific waste streams. Further, wastes were typically sourced from 5 zones. Hence, sampling strategy focussed on selecting trucks from residential areas, carry-ing mixed wastes and covering all the zones from where waste was re-ceived at the site.

• At Bhalswa, it was noted that the overwhelming portion of trucks carried mixed wastes from West, Civil Lines and Rohini zones. Wastes were also observed to arrive in significant numbers from Narela and SP zones. Hence, sampling strategy focussed on selecting trucks carrying mixed wastes from all five zones mentioned.

• At Gazipur, it was noted that a large proportion of trucks carried mixed wastes from Shahdra North and South zones in addition to NDMC, Can-tonment Board, City and Sadar Paharganj zones. Trucks from Shahdra North and South zones typically brought in residential wastes, while those from SP and City zones brought in slaughterhouse wastes and some resi-dential and commercial wastes as well. It was observed that NDMC trucks brought in a large proportion of garden waste.

Specific waste streams such as those from fish, poultry and egg markets, in-stitutions, agricultural markets and construction and demolition wastes were also observed to arrive at this landfill. These were not sampled as discussed earlier. Hence, sampling strategy focussed on selecting trucks from differ-ent zones carrying wastes from residential areas, mixed landuse areas, and mixed residential / garden wastes from NDMC.



25


Compost Plants:

Compost plants treat incoming wastes as well as generate waste rejects (sent to landfills for final disposal). An understanding of the composition of both these streams was considered useful for determining optimal treatment and disposal options. Sampling at compost plant therefore focussed on both these waste streams.

All waste trucks entering the compost plant at Bhalswa (run by Nature Waste Management India Limited) were first routed to the Bhalswa landfill where a representative of the compost plant was stationed. This representative knew the daily waste requirements of the compost plant and he accordingly directed spe-cific streams of wastes from the landfill weighbridge to the compost plant. Wastes selected by the representative comprised a combination of fractions that tended to have high biodegradable nature in general. Therefore wastes typically selected were those from vegetable markets, dairy industry (chiefly cow-dung) and a large proportion of mixed wastes consisting of trucks arriving from routes known to generate higher fractions of biodegradable wastes. Some slaughter-house wastes were also reportedly sourced from the Gazipur landfill to the Bhalswa compost plant.

Amongst the above streams, sampling of incoming wastes at Bhalswa Plant was done only from the mixed wastes containing high biodegradable fractions. This was so, since slaughterhouse and industrial wastes were not being sampled and wastes from vegetable markets were being sampled separately as part of the specific waste stream sampling programme.

In addition to the above, sampling of waste rejects (1 sample each) was also undertaken at the compost plant. There were four waste reject streams at the compost plant and one composite waste sample from these waste streams was prepared in proportion to the generation of waste at the plant.

3.4.2 Sample Collection, Preparation and Handling The following programme was followed at the landfills and compost plants.

Before sampling:

• Preliminary meetings and permissions from the site officials were sought. During sampling:

• Waste was collected from different trucks or waste reject streams as de-scribed in Section 3.4.1.

• Wastes were spread around on a clean and plain piece of ground such that thickness of the waste on the ground was uniform,



26


• The wastes were mixed and levelled again with a mechanical front loader,

• Wastes were then quartered and then samples totalling about 100 kg were collected from each quarter and mixed. These were then segregated as per the format shown in Table3.3.

• Segregated samples totalling 5.0 kg were collected and put in separate, coded plastic bags. The proportion of each constituent was relative to its composition,

• Plastic bags containing waste thus separated were dispatched to the labora-tory along with a data sheet that also served as a chain of custody docu-ment.

• Remaining waste was disposed back in the landfill or compost plant.

Preparation of composite sample, in laboratory:

• A space in the laboratory was kept reserved for storage of incoming sam-ples. The segregated samples for the day were arranged in a row,

• The laboratory staff prepared a composite sample from the waste contained in the received, segregated bags on a proportionate basis using information contained in the data sheet,

• Composite samples thus prepared were analysed for different parameters.



27


4 Waste Sampling Results 160 samples were collected as part of the survey, and this sample size was higher than any previous study of MSW in Delhi brought to the notice of the Consultant. However, sampling carried out was still for a tiny fraction of wastes generated in Delhi (in absolute numbers), albeit covering a fairly large cross-section of waste types during February-March 2004. The variation in wastes found in Delhi is vast and these results do not aim to provide an ‘at a glance’ description of waste composition and properties for all wastes across the State of Delhi. Further, the impacts of seasonal variation on waste quality could not be assessed. However, the purpose of this survey was to get an under-standing of the composition and properties of specific wastes types generated in Delhi, and to evaluate if any of these could be used for specific treatment facili-ties. The results for each waste type are given in subsequent paragraphs, and conclusions made with regards to the potential use of each waste stream for use in methanisation, RDF and composting9, three treatment technologies that may possibly be applicable in Delhi.

4.1 Waste from Residential Areas – Higher Income Groups

Results of waste sampling from higher income group residential areas are shown in Table 4.1

9 Based on input characteristics for different treatment options as mentioned in the CPHEEO (2000)



28


Table 4.1: Sampling of waste streams – Higher Income Group (HIG) House-holds

Parameter Average Range Remarks Composition (%):

Biodegradables 71.9 66.7-77.0

Wastes contained mainly food waste

Recyclables 23.1 19.8-26.2

The recycling fraction gets reduced as it moves from dhalao to landfills.

Inerts 0.3 0.0-0.6 - Others 4.7 2.1-7.5 -

Bulk Density (kg/m3) 267 160-631 Low bulk density due to lack of compac-tion.

Ash Content (%) 10.9 4.2-19.3 - Moisture (%) 59 51-65 - Lower Calorific Value (kCal/kg)

1623 1300-1887

-

Higher Calorific Value (kCal/kg)

4907 4503-5359

-

C/N Ratio 31 19-58 -

Utility for composting, Moisture content and C/N ratio were adequate and high organic content indi-cated possibility for composting.

Utility for use in RDF High moisture content of 59% increase cost of drying. Low inert quantities were present and this was a requirement of most consumers.

Utility for methanisation C/N ratio was adequate, high moisture and organic content indicated possibility for biomethanisation.

Conclusion To conclude, the waste is suitable for biomethanisation / composting.

4.2 Waste from Residential Areas – Middle Income Groups

Results of waste sampling from middle income group residential areas are shown in Table 4.2.



29


Table 4.2: Sampling of waste streams – Middle Income Group (MIG) House-holds

Parameter Average Range Remarks Composition (%):

Biodegradables 75.9 71.3-80.2

Wastes contained mainly food waste

Recyclables 21.1 17.0-25.8

-

Inerts 0.4 0.0-1.4 - Others 2.6 1.2-4.9 -


Ash Content (%) 7.6 4.0-12.7 Moisture (%) 64 52-75 Mainly due to organic matter Lower Calorific Value (kCal/kg)

1409 732-1960

-


4933 3415-6307

-

C/N Ratio 25 13-50 -

Utility for composting, Moisture content was adequate and the CN ratio was at the desirable level of 25-30. Further, high organic content indicated possibility for composting.

Utility for use in RDF HCV was high and LCV was moderate and this was acceptable. High moisture content of 65% could however increase cost of drying.

Utility for methanisation High moisture and organic content indicated possibility for biomethanisation. However, C/N ratio was within the desirable range.

Conclusion To conclude, the waste is more suitable for biomethanisation / composting.

4.3 Waste from Residential Areas – Lower Income Groups

Results of waste sampling from lower income group residential areas are shown in Table 4.3



30


Table 4.3: Sampling of waste streams – Lower Income Group (LIG) Households Parameter Average Range Remarks

Composition (%): Biodegradables 63.2 39.6-

87.6 Waste contained mostly food waste

Recyclables 16.6 8.5-27.1 Most of the recyclables were sold di-rectly

Inerts 17.3 0.0-43.0 It was observed that many households were using wood as a supplementary fuel which generates ash as waste.

Others 3.0 0.0-8.5 - Bulk Density (kg/m3) 226 160-327 Low bulk density due to lack of compac-

tion. Ash Content (%) 18.0 4.3-40.1 Relatively higher ash content due to us-

age of firewood in houses sampled. Moisture (%) 54 39-76 Attributed mainly to organic matter Lower Calorific Value (kCal/kg)

1406 682-2455

-


3818 2238-5456

-

C/N Ratio 42 23-134 -

Utility for composting, Moisture content was adequate and the CN ratio was higher than the desirable level of 25-30. Therefore this would require to be suitably addressed by addi-tion of other waste streams. High organic content indicated possibility for com-posting.

Utility for use in RDF HCV was high and LCV was moderate and this was acceptable. Further high moisture content of 54% increased cost of drying. Low inerts quantities were required by most consumers.

Utility for methanisation High moisture and organic content indicated possibility for biomethanisation. However, C/N ratio was slightly on the higher side and this would require to be taken care of suitably.

Conclusion The waste is more suitable for biomethanisation / composting.

4.4 Waste from Residential Areas – JJ Clusters Results of waste sampling from JJ cluster residential areas are shown in Table 4.4



31


Table 4.4: Sampling of waste streams – JJ Cluster Households Parameter Average Range Remarks

Composition (%): Biodegradables 72.2

60.9-85.6

Waste contained mostly food waste

Recyclables 16.2 8.9-24.7 Attributed to higher paper and plastic content

Inerts 9.5 5.5-27.4 From sweeping of houses. Others 2.1 0.0-8.9 -


Ash Content (%) 11.5 3.3-23.2 - Moisture (%) 60 44-71 Due to presence of biodegradables. Lower Calorific Value (kCal/kg)

1259 204-2180

Calorific Value was lowered due to higher moisture content


4022 1582-5539

Due to presence of biodegradables.

C/N Ratio 54 21-77 -

Utility for composting, Moisture content was adequate and the CN ratio was higher than the ideal level of 25-30. Therefore this would require to be suitably addressed. High organic content indicated possibility for composting.

Utility for use in RDF HCV was high and LCV was moderate and this was acceptable. Further high moisture content of 63% increased cost of drying. Low inerts quantities were acceptable to most consumers.

Utility for methanisation High moisture and organic content indicated possibility for biomethanisation. However, C/N ratio was on the higher side and this would require to be suitably taken care of.


4.5 Waste from Vegetable Markets The Vegetable Market waste sampling results are shown in Table 4.5.



32


Table 4.5: Sampling of waste streams – Vegetable Markets Parameter Average Range Remarks

Composition (%) Biodegradables 97.2 90.1-

100.0 Waste sample contained mainly fresh vegetables. Significant seasonal variation unlikely due to continuous inflow of vegetables and fruits from neighbouring states, all year.

Recyclables 2.3 0.0-9.9 It was observed that most of the recycla-bles were sold such as packing boxes, wooden boxes, paper, plastic which did not end in to dustbin/dhalao.

Inerts 0.5 0.0-4.8 Waste samples contained fresh vegeta-bles, not coming in contact with soil.

Others Nil Nil - Bulk Density (kg/m3) 202 140-269 Low bulk density due to nature of waste. Ash Content (%) 3.3 1.5-7.8 - Moisture (%) 76 62-82 - Lower Calorific Value (kCal/kg)

497 0-1309 Presence of high moisture content lead to lower LCV figures.


3827 3083- 4442

-

C/N Ratio 16 4 -38 -

Utility for composting, The moisture content was adequate; however the CN ratio was less than ideal level of 25-30, and therefore this would require to be suitably addressed.

Utility for use in RDF HCV was high and this was desirable, however, high moisture content of 76% entailed increased drying costs, which would require to be reduced, at a cost. The reduction in volume would also be high, and therefore large amounts of waste would be required.

Utility for methanisation High moisture and organic content indicated possibility for biomethanisation. However, C/N ratio was possibly on the lower side.


4.6 Waste from Institutional Areas The Institutional Area waste sampling results are shown in Table 4.6



33


Table 4.6: Sampling of waste streams – Institutional Areas Parameter Average Range Remarks

Composition (%): Biodegradables 59.7 0-100.0 Recyclables 33.8 0-100 Inerts 4.0 0-30 Others (including hazardous wastes)

2.5 0-16.2

Bulk Density (kg/m3) 253 51-690 Ash Content (%) 6.7 1.2-31.7 Moisture (%) 50 5.0-84 Lower Calorific Value (kCal/kg)

1693 129-3778


4159 2642-5459

Two samples were from administration building having mostly recyclables and some biodegradable material. Two samples were from canteen and mess respectively containing mostly food waste, some recyclables as well as lot of leaf litter. Seasonal changes are expected especially in summer glass and tin cans are ex-pected to increase, vacations in summer would result in waste quantity reduction. Low bulk density due to lack of compac-tion.

C/N Ratio 35 6-110

Utility for composting, The moisture content was adequate; however the CN ratio was higher than ideal level of 25-30, and therefore this would require to be suitably addressed. Individual streams such as garden wastes could however be suitable for composting.

Utility for use in RDF HCV was high, LCV was moderate and this was desirable, however, moderate moisture content of 50% entailed some drying, which would require to be re-duced, at a cost.

Utility for methanisation High moisture and organic content indicated possibility for biomethanisation. However, C/N ratio was on the higher side and this would require to be suitably taken care of. Some waste streams (for e.g. canteen waste) could be more suit-able for bio-methanisation.

Conclusion To conclude, the waste is more suitable for biomethanisation / composting.

4.7 Waste from Streets Results of waste sampling from streets are shown in Table 4.7



34


Table 4.7: Sampling of waste streams – Streets Parameter Average Range Remarks


57.5 Recyclables 12.0 2.3-25.7 Inerts 56.1 23.6-

81.3 Others 3.5 0-6.4

Two streets sampled had mixed wastes containing considerable organic matter, with some recyclables. Street sweeping contained considerable amount of dust.

Bulk Density (kg/m3) 326 167-591 Low due to lack of compaction. Ash Content (%) 56.7 35.3-

72.8 Expected in street sweepings.

Moisture (%) 19 5-33 Dry conditions. Lower Calorific Value (kCal/kg)

1598 1007-2041

Calorific value was relatively high due to biodegradables and recyclables.


2199 1188-3289

Wastes contained mostly recyclables and small amount of organic waste.

C/N Ratio 51 11-78 -

Utility for composting, High inerts could lead to difficulties in composting. Further, moisture content was low and the CN ratio was higher than the ideal level of 25-30.

Utility for use in RDF HCV and LCV were moderate and this was acceptable. Further low moisture content of 19% entailed minimal drying. High inerts quantities might not be acceptable to most consumers.

Utility for methanisation High inerts would lead to difficulties in biomethanation. Further, waste con-tained low moisture and organic contents, indicating difficulty in biomethanisa-tion. However, C/N ratio was also on the higher side and this would require to be suitably taken care of.

Conclusion This waste will require removal of inerts before consideration as input for any treatment option.

4.8 Waste from Commercial Areas Results of waste sampling from commercial areas are shown in Table 4.8



35


Table 4.8: Sampling of waste streams – Commercial Areas Parameter Average Range Remarks

Composition (%): Biodegradables 15.6 0.0-57.7 - Recyclables 68.0 40.4-

100 It was observed that most of the recycla-bles were sold such as packing boxes, wooden boxes, paper, plastic. These would not end in to dustbin/dhalao.

Inerts Nil Nil The shops visited did not sweep floors or the swept matter was attached to other material.

Others 16.4 0-56.6 - Bulk Density (kg/m3) 57 7-94 Light, bulky waste. Ash Content (%) 8.8 2.8-16.2 - Moisture (%) 18 2-52 - Lower Calorific Value (kCal/kg)

3532 1815-4593

LCV was high due to higher amounts of paper and plastic. Hence this calorific value was not representative of fractions entering landfills from commercial areas.


4576 3373-6185

Less difference between HCV and LCV due to low moisture levels.

C/N Ratio 158 34-345 -

Utility for composting Low moisture content, very high C/N ratio and low organic waste content indi-cated non-suitability for composting.

Utility for use in RDF HCV and LCV were high and this was acceptable. Further low moisture con-tent entailed minimal drying. It could be possible to use this waste for RDF.

Utility for methanisation Low moisture, organic content and high C/N ration rendered this waste unsuit-able for biomethanisation.

Conclusion This waste can be used for RDF. However large quantities of such wastes are not expected since scavenging of this waste is likely after it is disposed in dha-laos.

4.9 Waste Entering Landfills Results of waste sampling from landfills are shown in Table 4.9. The wastes selected were mixed wastes, with low inert content.



36


Table 4.9: Sampling of waste streams – Landfills Parameter Average Range Remarks


94.6 Recyclables 9.2 2.8-16.3 Inerts 10.8 0.0-72.2 Others 6.3 0.3-16.2

Samples were mainly taken from trucks containing mixed waste and originating from residential areas and having under-gone scavenging at generation level and dhalaos. Trucks containing construction and demolition waste were not consid-ered for sampling, resulting in lower levels of inerts than the average.



1777 191-4495

Relatively higher calorific value due to nature of samples drawn.


3927 2042-5315

Difference in HCV & LCV was lower due to reduction in moisture over time and dry conditions.

C/N Ratio 38 5-110 -

Utility for composting, Moisture content was adequate and the C/N ratio was higher than the ideal level of 25-30. Therefore this would require to be suitably addressed. High organic content indicated possibility for composting.

Utility for use in RDF HCV was high and LCV was moderate and this was acceptable. Further high moisture content of 47% increased cost of drying. Low inerts quantities were acceptable to most consumers.

Utility for methanisation High moisture and organic content indicated possibility for biomethanisation. However, C/N ratio was on the higher side and this would require to be suitably taken care of.

Conclusion The sampled waste is more suitable for biomethanisation / composting. (These results were from trucks having higher biodegradable content, since inert bear-ing trucks were not sampled, and such trucks were a fraction of all waste enter-ing the landfills).



37


4.10 Waste Entering Compost Plant Results of sampling of wastes entering the compost plant are shown in Table 4.10.

Table 4.10: Sampling of waste streams – Compost Plants Parameter Average Range Remarks


83.9 Recyclables 7.8 4.8-13.0 Inerts 9.5 5.8-15.2 Others 5.9 4.1-9.1

Trucks originating from residential areas and containing mixed waste were se-lected from localities tending to have more organic wastes. A representative of the compost plant directed those trucks to compost plant.



1767 896-2838

-


4076 3153-4582

-

C/N Ratio 39 22-61 -

Utility for composting, Moisture content was adequate and the CN ratio was higher than the ideal level of 25-30. CN ratio required to be suitably addressed (and this was done at the compost plants by addition of other waste types). High organic content con-firmed suitability for composting.

Conclusion The waste requires additional waste streams to balance CN ratio and this was being practised at the plant.

4.11 Waste Rejects from Compost Plant Results of waste rejects at the compost plant are shown in Table 4.11.There were four streams of rejects at the plant: 200mm rejects, 50mm rejects, 4mm rejects and rejects from the destoner. The four streams of rejects were gener-ated in the ratio of 0.5:0.25:0.18:0.17. The 4mm rejects and the destoner rejects were 100% inert.



38


Table 4.11: Sampling of waste streams – Waste Rejects from Compost Plants Parameter Weighted

Average Range Remarks

Composition (%): Biodegradables 23.3 0-69.9 Recyclables 11.7 0-54.5 Inerts 50.7 14.8-100 Others 14.3 0-26.6

Two waste streams constitut-ing the waste were 100% inert. 50mm rejects were having a high organic content, while the 200 mm rejects had high calo-rific value.

Ash Content (%) 58.4 23.8-84.1 High ash content due to pres-ence of inerts.

Moisture (%) 14 7-17 Low moisture content. Lower Calorific Value (kCal/kg)

2159 100-3501 200mm rejects had high lower calorific value.


2543 153-3996 Low moisture content resulted in less difference between LCV & HCV.

Utility for RDF / incineration Relatively high LCV and low moisture content indicated the possibility of us-ing the wastes for incineration or RDF. In all probability, the inert streams would require to be addressed before this could be done.

Conclusion The waste may be considered for RDF or incineration after removal of inerts.

4.12 Comparison of Results of COWI-Kadam (2004), JICA (2004) and NEERI (1996)

Waste characterisation survey was undertaken by COWI-Kadam in 2004 and the sampling results were compared with results of the JICA financed study undertaken by IPE in 2004 and NEERI study undertaken in 1996. The compari-son of results is as shown in Table 4.12.



39


Table 4.12: Comparison of Results of COWI-Kadam (2004), JICA (IPE 2004)) and NEERI (1996)

COWI-Kadam (2004)

JICA (IPE 2004)

NEERI (1996)

No of Samples 160 - 137 Remarks For household samples, COWI-Kadam undertook survey in 50

households for each income category and each survey was run for seven days with samples being collected every day totaling approximately 2,800 household samples for the entire survey.

High Income Group (HIG) Avg. Biodegradables 71.9% 64% 44.5% Avg. Recyclables 23.1% 28% 15.4% Avg. Inerts and Others 5% 8% 40.1% Per capita waste genera-tion (gms)

420 309 -

Middle Income Group (MIG) Avg. Biodegradables 75.9% 61% 39.9% Avg. Recyclables 21.1% 33% 12.6% Avg. Inerts and Others 3% 6% 47.5 Per capita waste genera-tion (gms)

240 285 -

Lower Income Group (LIG) Avg. Biodegradables 63.2.4% 62% 36.4% Avg. Recyclables 16.6% 22% 11.9% Avg. Inerts and Others 20.2% 16% 51.7% Per capita waste genera-tion (gms)

150 146 -

Remarks The recyclable component in JICA study includes the items like newspapers etc that are sold to iterant buyers while the COWI-Kadam study does not include these items in recycla-bles, resulting in lower % of recyclables. The % of biodegrad-ables and inerts / others is quite comparable for the two stud-ies. For the NEERI study, the exact sampling location (house-hold or dhalao) was not clear from the available text, possibly resulting in higher inerts and others, in case samples were col-lected at dhalaos. Hence the results of NEERI are not compa-rable with the COWI-Kadam study, and based on available information, the NEERI study could not be replicated by COWI-Kadam. Sampling of JJ clusters was not part of the JICA/NEERI studies.

Commercial Area Avg. Biodegradables 15.6% - 38.5% Avg. Recyclables 68% - 20.2% Avg. Inerts and Others 16.4% - 41.3% Remarks The COWI-Kadam study observed that most of the recyclables

in commercial area were sold as packing boxes, wooden boxes, paper, plastic etc. These would not end in to community



40


COWI-Kadam (2004)

JICA (IPE 2004)

NEERI (1996)

bin/dhalao therby accounting for high percentage of recycla-bles. Sampling of commercial areas was not part of the JICA financed study.

Landfills Avg. Biodegradables 73.7% - 30.6% Avg. Recyclables 9.2% - 9.8% Avg. Inerts and Others 17.1% - 59.6% Remarks COWI-Kadam took samples mainly from trucks containing

mixed waste and originating from residential areas and having undergone scavenging at generation level and dhalaos. Trucks containing construction and demolition waste were not consid-ered for sampling, resulting in lower levels of inerts. Details on sampling procedure of NEERI were not available. Sampling of landfills was not part of the JICA financed study.

4.13 Waste Flow Diagram A waste flow diagram is shown in Figure 4.1. This shows waste flows on the basis of available results of the JICA financed study (indicating wastes gener-ated at the household levels, in %) and from the current study (indicating wastes disposed to dhalaos / community bins, in %) It must be borne in mind that the figures in the flow diagram can not be co-related, since the studies were done independently and at different locations. However, the diagram indicates the extent of recycling being carried out at the households by citizens, and the scavenging of recyclables by rag-pickers.



41


Figure 4.1: Partial Waste Flow Diagram

4.14 Potential suitability of Selected Technologies for Sampled Waste Streams

On the basis of the results discussed in Sections 4.1 to 4.11, the suitability of different waste streams for selected technologies is presented in Table 4.13. (Wastes entering landfills and compost plants are not discussed because they are waste disposal methods themselves).

Recyclables removed during scavenging

Recyclables sold to Itenerants

Waste from other streams (mainly garden and vegetable market

waste)

Recyclables: ~ 6% Recyclables: ~ 12%

Middle Income Group Low Income Group

Recyclables: ~ 5%

Composition Biodegradables: 71.9%

Recyclables: 23.1% Inerts & Others: 5%


Recyclables: 21.1% Inerts & Others: 3%


Recyclables: 16.6% Inerts & Others: 20.2%

High Income Group

Waste Gener-ated at House-

holds (JICA fi-

nanced study)

Household Waste sent to Community

Bins/Dhalaos (COWI-Kadam

Study)

Recyclables re-moved during

scavenging

Composition Biodegradables: 74%

Recyclables: 9% Inerts & Others: 17%

Waste Received at Landfill

(Mainly from Residential

areas but also containing some

garden and vegetable mar-

ket waste)









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Table 4.13: Potential suitability of sampled waste streams for selected technolo-gies Waste Stream Potential Suitability

Higher Income Group Methanisation, composting Middle Income Group Methanisation, composting Lower Income Group Methanisation, composting JJ (Slum) Clusters Methanisation, composting Vegetable Markets Methanisation, composting Institutional Areas Methanisation, composting Streets RDF, if inerts can be reduced / removed Commercial Areas RDF, however waste quantities may be low Waste Rejects RDF or incineration, if inerts can be reduced / removed

4.15 Analysis of Household Solid Waste Survey Household survey was carried out in several residential areas which represented different socio-economic population groups (e.g. according to income levels: low, middle and high income groups). The number of households surveyed was 50 for HIG, 100 for MIG, 150 for LIG and 100 for JJ clusters.

The purpose of the household survey was to identify, methods of collection and disposal of solid waste, recycling/resource recovery practices of solid waste and to quantify figures of waste being disposed into community bins/dhalaos.

Based on the analysis of the collected information, it could be inferred that for HIG and MIG localities, the disposal mechanism is by door to door collection system. For LIG, about 69% of the households dispose solid waste at dhalao while the rest 31% rely on door to door collection system. 73% of the households in JJ clusters dispose their solid waste at open spaces, 18% dispose at dhalao and remaining 9% dispose by door to door collection system. The door step collection is operated pri-vately in all HIG and MIG localities and in 47% of the households in LIG category. The entire collection is by MCD in JJ Clusters.

The recyclables like newspapers, metals, utensils, clothes etc were disposed by households of different income streams by different mechanisms as shown in Table 4.14 below.



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Table 4.14: Disposal of Recyclables Income Category Door Step Local Recycling Mar-

ket Bulk Recycling Mar-ket

High Income Group 47% 32% 21% Middle Income Group

- 52% 48%

Lower Income Group

48% 6% 46%

JJ (Slum) Clusters 23% 46% 31%

The per capita per day waste disposal into dhalaos/community bins varies across different income streams and has a value ranging from 420 gm for HIG, 240 gm for MIG, 150 gm for LIG and 80 gm for JJ clusters.



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