WASTE MANAGEMENT: A FRAMEWORK FOR INTERVENTION
KAVERI KALA
DEPARTMENT OF MECHANICAL ENGINEERING INDIAN INSTITUTE OF TECHNOLOGY DELHI
JULY 2023
© Indian Institute of Technology Delhi (IITD), New Delhi, 2023
WASTE MANAGEMENT: A FRAMEWORK FOR INTERVENTION
by
KAVERI KALA
Department of Mechanical Engineering
Submitted
in fulfillment of the requirements of the degree of Doctor of Philosophy
to the
INDIAN INSTITUTE OF TECHNOLOGY DELHI
JULY 2023
In the loving memory of our beloved cats Motula and
Munni...
Certificate
This is to certify that the thesis entitled “Waste Management: A Framework for Intervention”, submitted by Miss Kaveri Kala to the Indian Institute of Technology Delhi, for the award of the degree ofDoctor of Philosophy, is a record of the original, bonafide research work carried out by her under my supervision and guidance. The thesis has reached the standards fulfilling the requirements of the regulations related to the award of the degree.
The results contained in this thesis have not been submitted in part or in full to any other university or institute for the award of any degree or diploma to the best of our knowledge.
Prof. Nomesh B. Bolia Department of Mechanical Engineering, Indian Institute of Technology Delhi, New Delhi - 110016, India.
Acknowledgements
Undertaking this PhD has been a life altering experience for me and it would not have been possible to do without the guidance of my supervisor, Nomesh B. Bolia. I express my deepest sense of respect and gratitude to him for his continuous support and patience during my PhD study. I feel privileged to be one of his students. I shall remain thankful to him forever for his endless support and cooperation during my research work.
I am grateful to the members of Student Review Committee (SRC) Prof. P.V.M.
Rao, Prof. Sangeeta Kohli and Prof. Sushil for their creative and valuable sugges- tions during my research work. My special thanks to my sister Shivani Kala for endless corrections and her contributions to my doctoral thesis. My deepest grati- tude is towards my mother Mrs. Anita Kala for immense support and sacrifice while taking care of me in all ways. I wish to acknowledge the support of my father Mr K.P Kala for helping me to reach here. I am also thankful to my friends Shobhit, Nachiketas, Sai Ganesh and Rishita for helping me out during my dissertation. I would also like to thank my friends Rutha, Sumegha, Prerna and Nikita who kept me sane during turbulent times. I am also thankful to my research colleagues Ab- hishek, Maansi, Soham, Deepak, Gaurav and Rajat for their friendship. I would like to thank my research seniors Lakshay and Hemant for their academic support.
I would also like to thank Mr. Rama Shankar and Mr. Prem Chand for providing logistical support. I would further like to thank all the experts and organizations for participating in our research. I am thankful to Ms. Rama Saxena who provided all the facilities in the lab whenever needed. Last but not the least, I thank all my well-wishers, friends and relatives who helped me directly or indirectly during my research work.
(Kaveri Kala)
Abstract
Municipal Solid Waste Management (MSWM) is a complex system wherein a typical waste management process, and intervention includes segregation, collection, pro- cessing, and disposal. Moreover, waste management apparatus varies from region to region; therefore, site-specific data and analysis are often required to determine appropriate and region-relevant waste management strategies. The complexities of a waste management system in India are even further complicated due to the involve- ment of various participants in the decision-making process, such as the government, local municipalities, the informal sector, institutional experts, and on occasions, the general public. Citizens are one of the primary stakeholders and play an important role in the value chain before the waste is collected. At the same time, municipalities and the informal sector are equally important stakeholders, majorly responsible for the collection and processing of the waste.
Evidently, the waste management system in India encompasses multiple socio-economic and environmental facets. In a country as diverse as India, there is a need for het- erogeneous, context-based, and evidence-driven policies that lead to efficient out- comes. It is important the policies thus designed should also focus on identifying the strengths of a country and leveraging them.
The currently practiced homogenous policy framework for waste management is indeed not working in favor of India. This can be illustrated by the World Bank data, according to which India generates the highest amount of waste worldwide, more than even China. As much as 77 percent of this waste is simply dumped in the open, with all its noxious fumes and toxins. And Delhi is one of the tops in the list of Indian cities with maximum waste generation. Therefore, Delhi has been chosen to demonstrate the need for contextual policies.
There is a clear need to limit the disturbing trend of waste generation and mitigate the consequences. This can only happen if we break the old systems of waste man- agement and build new ones through context-based policy-making, such that we: 1) capture the perception of citizens belonging to different socio-economic categories while simultaneously designing waste management policies contingent on the type of residence, 2) devise ways to make both formal and informal system of waste man- agement work in conjunction and 3) make currently existing waste collection system
more efficient. The work in the thesis caters to the three aspects (above mentioned) around which waste management policies should be designed.
Accordingly, the framework and models are developed for Delhi to yield interest- ing insights. This work suggests possible recommendations that can make waste management more efficient and thus, may enable shifting of policy framework from exclusivity to inclusivity.
Keywords: Municipal Solid Waste Management, Contextual Policy, Stakeholders in Waste Management, Data-driven Approaches, Citizen Engagement
सार
नगरपालिका ठोस कचरा प्रबंधन (एमएसडब्ल्यूएम) एक जटिि प्रणािी है जजसमें प्ररूपी कचरा प्रबंधन प्रक्रिया और हस्तक्षेप में पृथक्करण, संग्रह, प्रसंस्करण, और ननपिान शालमि है। इसके अिावा, कचरा
प्रबंधन उपकरण एक क्षेत्र से दूसरे क्षेत्र में लिन्न होता है; इसलिए, उचचत और क्षेत्र-प्रासंचगक कचरा प्रबंधन रणनीनतयों को ननधााररत करने के लिए अक्सर साइि-ववलशष्ि डेिा और ववश्िेषण की आवश्यकता होती है।
िारत में कचरा प्रबंधन प्रणािी, ननणाय िेने की प्रक्रिया में ववलिन्न प्रनतिाचगयों, जैसे सरकार, स्थानीय नगर पालिकाएं, अनौपचाररक क्षेत्र, संस्थागत ववशेषज्ञों और किी-किी आम जनता, की िागीदारी के कारण और िी जटिि हो गई हैं। नागररक प्राथलमक टहतधारकों में से एक हैं और कचरा एकत्र करने से पहिे
मू्य श्ृंखिा में महत्वपूणा िूलमका ननिाते हैं। साथ ही, नगर पालिकाएं और अनौपचाररक क्षेत्र समान रूप से महत्वपूणा टहतधारक हैं, जो कचरे के संग्रह और प्रसंस्करण के लिए प्रमुख रूप से जजम्मेदार हैं।
जाटहर है, िारत में कचरा प्रबंधन प्रणािी में कई सामाजजक-आचथाक और पयाावरणीय पहिू शालमि हैं।
िारत जैसे ववववधतापूणा देश में, ववववध, संदिा-आधाररत और साक्ष्य-संचालित नीनतयों की आवश्यकता है
जो कुशि पररणाम प्रदान करें। यह महत्वपूणा है क्रक इस प्रकार तैयार की गई नीनतयों का ध्यान इस देश की शजक्तयों की पहचान करने और उनका िाि उठाने पर िी होना चाटहए।
कचरा प्रबंधन के लिए वतामान में प्रचलित समरूप नीनत ढांचा वास्तव में िारत के पक्ष में काम नहीं कर रहा है। इसे ववश्व बैंक के आंकडों से स्पष्ि क्रकया जा सकता है, जजसके अनुसार िारत दुननया िर में सबसे
अचधक मात्रा में कचरा उत्पन्न करता है, यहां तक क्रक चीन से िी अचधक। इस कचरे का 77 प्रनतशत टहस्सा अपने सिी हाननकारक धुएं और ववषाक्त पदाथों के साथ खुिे में फेंक टदया जाता है। और टद्िी
सबसे अचधक कचरा उत्पन्न करने वािे िारतीय शहरों की सूची में शीषा पर है। इसलिए, प्रासंचगक नीनतयों
की आवश्यकता को प्रदलशात करने के लिए टद्िी को चुना गया है।
कचरा उत्पादन की चचंताजनक प्रवृवि को सीलमत करने और पररणामों को कम करने की स्पष्ि आवश्यकता
है। यह केवि तिी हो सकता है जब हम संदिा-आधाररत नीनत-ननमााण के माध्यम से कचरा प्रबंधन की
पुरानी प्रणालियों को तोडें और नई प्रणालियों का ननमााण करें, जैसे क्रक हम: 1) कचरा प्रबंधन नीनतयों को
डडजाइन करते समय ववलिन्न सामाजजक-आचथाक श्ेणणयों से संबंचधत नागररकों की धारणा को पकडें, 2) कचरा प्रबंधन की औपचाररक और अनौपचाररक दोनों प्रणालियों को एक साथ काम करने के तरीके ईजाद करें और 3) वतामान में मौजूद कचरा संग्रहण प्रणािी को और अचधक कुशि बनायें। थीलसस में काम तीन पहिुओं (ऊपर उज्िणखत) को पूरा करता है जजसके आसपास कचरा प्रबंधन नीनतयों को डडजाइन क्रकया
जाना चाटहए।
तदनुसार, टदिचस्प अंतर्दाजष्ि प्राप्त करने के लिए टद्िी के लिए रूपरेखा और मॉडि ववकलसत क्रकए गए हैं। यह काया संिाववत लसफाररशों का सुझाव देता है जो कचरा प्रबंधन को अचधक कुशि बना सकते हैं
और इस प्रकार, नीनत ढांचे को ववलशष्िता से समावेलशता की ओर स्थानांतररत करने में सक्षम बना सकते
हैं।
Contents
Certificate
Acknowledgements
Abstract
Contents List of Figures List of Tables Abbreviations Symbols
1 Introduction 1
1.1 Preamble . . . 1
1.2 Waste Management in Delhi . . . 3
1.3 Motivation. . . 4
1.4 Research Problem . . . 6
1.4.1 Research Objectives . . . 7
1.4.2 Research Stages . . . 7
1.5 Thesis Organisation . . . 9
1.6 Summary . . . 10
2 Literature Review 13 2.1 Introduction . . . 13
2.2 Interventions Needed in Waste Management . . . 14
2.2.1 Citizens . . . 15
Contents
2.2.1.1 Citizens Engagement in a centralised urban city of a
developing country . . . 17
2.2.1.2 Citizen Engagement in a Decentralized Environment 23 2.2.2 Collectors . . . 24
2.2.2.1 Informal Waste Management Sector . . . 29
2.2.2.2 Formal Waste Management Sector . . . 35
2.3 Research Gaps. . . 37
2.4 Observations from the Literature Review . . . 37
2.5 Summary . . . 40
3 Citizen Engagement in Open Residential Spaces 41 3.1 Introduction . . . 41
3.2 Materials and Methods . . . 42
3.2.1 Study Area . . . 43
3.2.2 Survey Design . . . 45
3.2.3 Descriptive Statistics . . . 47
3.2.4 Model Details . . . 52
3.3 Analysis of factors related to the quantity and composition of waste generated . . . 54
3.3.1 Model 1: Analysis of factors related to the quantity of waste generated . . . 54
3.3.2 Model 2: Analysis of factors related to the type of waste gen- erated . . . 58
3.3.3 Discussion and Policy Implications . . . 61
3.4 Analysis of Household Waste Management Practices . . . 65
3.4.1 Analysis of Segregation Model . . . 66
3.4.2 Analysis of Composting Model. . . 68
3.4.3 Analysis of Segregation Incentives Model . . . 69
3.4.4 Analysis of Composting Incentives Model . . . 73
3.4.5 Discussions and Policy Implications . . . 75
3.4.5.1 Insights . . . 75
3.4.5.2 Action Items . . . 76
3.5 Formulation of Waste Management Communication Policy . . . 79
3.5.1 Analysis based on “Econometrics”: MLR . . . 79
3.5.2 Discussion and Policy Implication . . . 82
3.5.2.1 Proposed WMCP . . . 85
3.6 Summary . . . 87
4 Citizen Engagement in a Gated Community 89 4.1 Introduction . . . 89
4.2 Background . . . 90
4.2.1 Study Area . . . 90
Contents
4.2.2 Data Collection . . . 91
4.3 Comparison of perception between colonies of SDMC and IIT-D . . . 93
4.3.1 Chi-Square Test for homogeneity . . . 94
4.3.2 Descriptive Analysis . . . 97
4.3.3 Logistic Regression . . . 100
4.3.4 Interpretation from the Analyses . . . 102
4.4 Analysis of Waste Management in IIT Delhi . . . 106
4.4.1 Univariate and Correlation Analysis . . . 107
4.4.2 Interpretations from the Analyses . . . 113
4.5 Discussions . . . 114
4.5.1 Challenges inside the campus . . . 115
4.5.2 Action Items . . . 117
4.6 Summary . . . 119
5 Importance of Informal Waste Management System 121 5.1 Introduction . . . 121
5.2 The Informal orKabaadi System in the Indian context . . . 123
5.2.1 Data Collection . . . 125
5.2.1.1 Results from the Household Survey . . . 126
5.2.1.2 Informal Waste Management Actors . . . 126
5.2.2 Challenges of Informal Sector . . . 127
5.3 Policy Framework . . . 130
5.3.1 System Optimization: Recommendations and Actionable In- sights . . . 132
5.3.2 System Change: A comprehensive policy for informal waste management system . . . 133
5.3.2.1 TOPSIS . . . 136
5.3.2.2 CIWM Policy Framework . . . 141
5.4 Model Development . . . 144
5.4.1 Model Tests and Validation . . . 146
5.4.1.1 Tests for Model Structures . . . 150
5.4.1.2 Tests for Model Behavior . . . 151
5.4.2 Results. . . 153
5.4.3 Discussions . . . 158
5.5 Summary . . . 164
6 Strategising Collection Routes for Formal Waste Management Sec- tor 165 6.1 Introduction . . . 165
6.2 Materials and Methods . . . 167
6.2.1 Research Methodology . . . 167
6.2.2 Study Area . . . 167
Contents
6.2.3 Data . . . 168
6.3 Improved Routes within a Ward using the Vehicle Routing Problem . 171 6.3.1 Revised Nearest Neighbour Algorithm . . . 173
6.3.2 A MILP Formulation of the VRP . . . 173
6.3.2.1 Sub-Tour Elimination Constraints and Exogeneous Heuristic . . . 177
6.3.2.2 Partitioning the Wards . . . 179
6.3.2.3 Results for Truck Routing . . . 180
6.4 Evaluating the Ward Structure . . . 181
6.4.1 Perturbing the distance matrix . . . 182
6.5 Summary . . . 184
7 CONCLUSION 185 7.1 Summary . . . 185
7.2 Utility of the Research Work . . . 190
7.3 Policy, Planning and Operational Implications . . . 192
7.4 Research Contribution . . . 194
7.5 Limitations of the Study . . . 196
7.6 Suggested Directions for Future Research . . . 197
7.7 Summary . . . 199
Bibliography 201
List of Publications 225
Biography of Researcher 227
List of Figures
1.1 MSW generation, land requirement, and population from 2001 to 2051 6
1.2 Flow Diagram of Research Stages . . . 8
2.1 Literature Review Classification . . . 14
3.1 Research Methodology for Chapter 3 . . . 43
3.2 Study Area . . . 46
3.3 Household Survey . . . 49
4.1 Study Area . . . 92
4.2 Number of Dustbins . . . 97
4.3 Source of Waste . . . 97
4.4 Service Satisfaction . . . 98
4.5 WM Services . . . 98
4.6 Problems in Residence . . . 98
4.7 Individual Challenge . . . 98
4.8 Segregation . . . 99
4.9 Composting . . . 99
4.10 Segregation Incentives . . . 100
4.11 Composting Incentives . . . 100
5.1 Casual Loop Diagram. . . 145
5.2 Stock and Flow Diagram . . . 146
5.3 Behaviour Reproduction Test . . . 152
5.4 Sensitivity Analysis . . . 154
5.5 Informal Recycling Coefficient . . . 158
5.6 Amount of Waste Recycled. . . 159
5.7 MCD Landfill Flow . . . 159
5.8 Illegal Flow . . . 159
5.9 Net Environmental Benefit . . . 162
5.10 Net Land Saved . . . 163
5.11 Net Money Saved . . . 163
5.12 Employability . . . 163
List of Figures
6.1 The area covered the SDMC area in New Delhi, India . . . 169 6.2 The current ward structure for the central zone of the SDMC with a
single landfill and five depots, one each for the five wards that are a partition of the collection points shown in different colors . . . 170 6.3 A pictorial view of the waste-collection process . . . 172 6.4 Revised Nearest Neighbour Algorithm. . . 174
List of Tables
1.1 Thesis outline . . . 9
2.1 Literature Review . . . 19
2.2 Literature Review for HEI . . . 25
2.3 Policy Literature Review . . . 31
2.4 Types of Waste Collection VRPs . . . 38
3.1 MSW profile of the SDMC . . . 45
3.2 Problems, citizen response, and response after rectification of the survey 50 3.3 Characteristics of a household (independent variables used in the models) . . . 55
3.4 Logistic Regression Results for Income Subcategories . . . 57
3.5 Logistic Regression Results for Income Subcategories . . . 60
3.6 Results by MLR Models (WMCP). . . 86
3.7 Policy Suggestions . . . 88
4.1 Results of Chi-Square Test of Homogeneity . . . 95
4.2 Parameter Estimates of Type of System of BLR . . . 102
4.3 Parameter Estimates of Type of system of MLR . . . 103
4.4 Cramer’s V Coefficient . . . 108
4.5 Summary Statistics for Ordinal Data: Low Segregation Efficiency . . 109
4.6 Summary Statistics for Ordinal Data: Best Mode for Communication 109 4.7 Basic Summary Statistics for Nominal Data . . . 110
5.1 Parameters for informal sector . . . 128
5.2 Recommendations to the existing or future policies with respect to informal waste sector . . . 134
5.3 Combined Decision Matrix . . . 137
5.4 Normalised Fuzzy Decision Matrix. . . 138
5.5 Priority Table . . . 140
5.6 Parameter Values for System Dynamics Model . . . 147
5.7 Pivotal Policy Parameters . . . 158
6.1 Input Parameters . . . 171
List of Tables
6.2 Variables and Parameters used in MILP Model. . . 175 6.3 Explanation for each constraint . . . 178 6.4 Results from different solution methods . . . 181 6.5 Transportation costs obtained for tours generated for the existing
ward structure and that generated with MST and K-Medoids for the 22 instances of the distance matrix, and the rank of the clustering method based on the lower transportation cost for each instance . . . 183
Abbreviations
WM Waste Management MSW Municipal Solid Waste
SDMC South Delhi Municipal Corporation
WMCP Waste Management CommunicationPolicy SDG Sustainable DevelopmentGoal
UN United Nations CE CircularEconomy
IWMS Informal Waste Management System NCT NationalCapitalTerritory
SWMR Solid WasteManagementRules WCS Waste ManagementSystem ORS Open ResidentialSpaces LR Logistic Regression
BLR Binomial LogisticRegression MLR Multinomial Logistic Regression
TOPSIS Technique for Order Performance bySimilarilty toIdeal Solution GST Goods and Services Tax
WTE WasteTo Energy
BHM Board of Hostel Management EPA Environment Protection Act BAU Business As Usual
ULB Urban Local Body
MRF Material Recovery Facility PPE PersonalProtective Equipment SC Segregation Coefficient
ERC Ease of Recycling Coefficient
Abbreviations
IRC Informal Recycling Coefficient MC MotivationCoefficient
NEP National Environment Policy NFP National Forest Policy
EPR ExtendedProducer Responsibility SBA SwachhBharatAbhiyan
NAPCC National Action Plan for Climate Change DS DentralisedSystem
HW Household Waste SES SocioEconomic Status HEI Higher Education Instutute HIG High Income Group
MIG MiddleIncome Group LIG Low Income Group
Symbols
P probability of the event H0 null Hypothesis
H1 alternate Hypothsis xi independent variables
Y the specific variable/ intervention being analyzed α significance level
p likelihood of an event under null hypothesis I set of the trucks at the garage (1,2,..., I) G set of depots (1,2,...,G)
N set of collection points (1,2,. . . ,N)
L set of landfill sites (G+N+1,. . . G+N+L) i vehicle index (i)
j, k indices of nodes (j,k∈G∪N ∪L) m index for the trip (m∈M) g index of the depots (g ∈G) l index of the landfills (l ∈L)
B total number of trucks currently being used
M maximum number of trips a truck can take (heuristics) qg quantity of waste at depots
ql quantity of waste at landfills
qk quantity of waste atkth collection point dj,k distance between jth and kth collection point tj,k travel time betweenjth and kth collection point Fi,g capacity of ith truck from gth depot
Cf fixed cost of running a truck Cv variable cost of running per km
Symbols
Ti,g maximum shift time for ith truck from gth depot
