Characterizing the Spatial and Temporal Patterns of Open Burning of

Oct 8, 2015 - ABSTRACT: Open-burning of municipal solid waste (MSW) is a major ... estimate of total MSW-burned for Delhi city ranged from 190 to 246 ...
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Characterizing the Spatial and Temporal Patterns of Open Burning of Municipal Solid Waste (MSW) in Indian Cities Ajay S Nagpure, Anu (Anuradha) Ramaswami, and Armistead G. Russell Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b03243 • Publication Date (Web): 08 Oct 2015 Downloaded from http://pubs.acs.org on October 13, 2015

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Environmental Science & Technology

Characterizing the Spatial and Temporal Patterns of Open Burning of Municipal Solid Waste (MSW) in Indian Cities Ajay Singh Nagpure1*, Anu Ramaswami1, Armistead Russell2 1

Center for Science, Technology, and Environmental Policy, Hubert H. Humphrey School of Public

Affairs, University of Minnesota, Twin Cities, MN, USA 2

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA



Corresponding author phone: +1-919-800-8194; E-mails: [email protected]; [email protected] Word count: ~5195 words (excluding references), 5 figures and 1 table

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ABSTRACT

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Open-burning of municipal solid waste (MSW) is a major source of PM emissions in developing

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world cities, but few studies have characterized this phenomenon at the city and intra-city

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(neighborhood) scale relevant to human health impacts. This paper develops a consistent field

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method for measuring the spatial frequency of the incidence of MSW-burning and presents

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results in three neighborhoods of varying socioeconomic status (SES) in Delhi, India, observed

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in winter and summer over 2 years. Daily MSW-burning incidents ranged from 24-130/km2-day

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during winter and 5-87/km2-day during summer, with the highest intensity in low SES

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neighborhoods. Distinct seasonal and diurnal patterns are observed. The daily mass of MSW-

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burned was also estimated at 90-1170 kg/km2-day and 13-1100 kg/km2-day in highest to low

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SES neighborhoods, in winter and summer, respectively. The scaled-up estimate of total MSW-

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burned for Delhi city ranged from 190-246 tons/day, about 2%-3% of total generated MSW;

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morning-burning contributed >65% of the total. MSW composition varied systematically across

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neighborhoods and season. Agra had much higher MSW-burning (39-202 incidents/km2-day;

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672-3485kg/km2-day) in the summer. The field method thus captures differences in MSW-

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burning across cities, neighborhoods, diurnally and seasonally, important for more fine grained

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air pollution modeling, and for tracking/monitoring policy effectiveness on-ground.

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Keywords:

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Emissions

Municipal solid waste burning; Urban waste management; Air pollution; PM

20 21 22 23

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INTRODUCTION

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Environmental scientists and pollution control agencies are increasingly focusing on air pollution

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by particulate matter (e.g., PM10, particles whose diameters are less than 10 µm, and PM2.5),

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because short- and long-term exposure to these pollutants is associated with a number of health

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impacts, including respiratory and cardiovascular disease, adverse birth outcomes, and cancer1-10.

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Based on these studies and evidence from occupationally exposed populations, the International

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Agency for Research on Cancer (IARC) has identified PM2.5, specifically, as a Group 1 human

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carcinogen11. Most recently, estimates from the Global Burden of Disease (GBD) study indicate

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that outdoor particulate pollution is the fifth major cause of premature death and disability-

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adjusted life years lost in India after high blood pressure, indoor air pollution, tobacco smoking

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and poor nutrition, with about 695,000 premature deaths estimated per year12. Furthermore, when

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the outdoor air pollution sources are concentrated near residential areas, the related emissions

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can infiltrate indoors, contributing to the indoor air-quality problems. In addition to these serious

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health effects, PM pollution has also been associated with aesthetic damage of culturally

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important statues and monuments in Indian cities, notably the Taj Mahal in Agra13.

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Open burning of municipal solid waste (MSW) is increasingly being recognized as a major

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source of PM10 and PM2.5 emissions in the cities of developing countries14-16, along with other

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sources, such as traffic emissions and industrial and power plant combustion operations. MSW

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refers to non-industrial and non-medical solid waste generated in municipal (urban) areas, i.e.,

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garbage generated from households and commercial establishments in cities. Open burning of

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MSW (MSW-burning) refers to MSW burned in urban neighborhoods, without the use of

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incinerators, with the resulting combustion-related pollutants released to the atmosphere at the 3 ACS Paragon Plus Environment

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surface, with relatively less buoyant plumes. MSW-burning differs from biomass burning, as the

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latter traditionally has been used in the context of burning crop residues and other biogenic

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residues (such as dung-cakes), often in agricultural settings. In contrast, MSW is not purely

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biomass, but often includes plastics, rubber and metal-containing refuse, the burning of which

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releases toxic emissions (including halogenated compounds from plastics burning). All these

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factors highlight the importance of MSW-burning to public health at the urban and intra-city

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scale.

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In emission inventories conducted for a few major Indian cities, the Central Pollution Control

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Board of India17 estimates that open MSW-burning may contribute 5% to 11% of all direct PM

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emitted from sources within a city boundary. Similar estimates are reported for Mexico City

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(3% to 30%) and Ulaanbaatar, Mongolia (4% to 7%)15,18. Thus the phenomenon of MSW-

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burning is likely to be very important to urban public health in India. A majority of Indian cities

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with populations exceeding 1 million rank among the top 100 world urban areas with worst PM10

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pollution19. A recent global study16 highlights the importance of MSW-burning, estimating that

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it could contribute approximately 8% and 22% of direct PM emissions in India and China,

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respectively. Despite the emerging recognition of the importance of this phenomenon, most city-

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scale air pollution emission inventories neglect MSW-burning because of the large uncertainty in

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the estimates of the fraction of MSW being burned and the paucity of actual field observations of

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the phenomenon at the city scale. Without any field estimation or baseline study, the

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implementation and success of any laws or policies attempting to remedy the situation are

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difficult to evaluate, as are the potential health impacts on different populations within the cities.

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At present, mass estimates of MSW-burning vary widely and are typically derived from either

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expert opinions or rule-of-thumb assumptions that estimate the burn fraction of daily MSW

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generated (Table S1). These estimates of MSW-burning vary and typically are not based on

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detailed analysis of the specific locations or the relationships to neighborhood characteristics

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within a city. Furthermore, these estimates do not account for the spatial variation in MSW-

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burning emissions and their linkage to socioeconomic status (SES) within the cities. Given that

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MSW-burning emissions have their main impact on human health at the local scale

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(neighborhood and city), developing a robust bottom-up field approach to studying MSW-

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burning within cities (at intra-urban scales) and its variation according to neighborhood SES and

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infrastructure provisions is important for assessing health and local environmental impacts.

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To date, there have not been detailed field observations exploring the spatial and temporal

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patterns of MSW-burning at the urban and intra-urban scale.

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established for characterizing MSW-burning patterns, with sensitivity to infrastructural and

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socioeconomic differences among cities and neighborhoods. Such methods are important for

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beginning to understand the linkage between neighborhood characteristics and MSW-burning

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emissions, and are essential for assessing health impacts and designing location-sensitive

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programs and policies to reduce the practice of MSW-burning. This is important because

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exposure to emissions from MSW-burning, and their related health effects, occur near-field,

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meaning that urban residents in proximity to MSW-burning are likely to be more at risk. The

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incidence of MSW-burning is likely to show sharp gradients across SES, with higher incidences

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observed in lower income areas with less infrastructure provision. Yet little is known about these

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finer scale intra-urban variations that have important implications for health and urban inequity

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in exposure to pollution.

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The objective of this paper is to develop a consistent field method for measuring the daily

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incidence (i.e., the spatial frequency) of MSW-burnings and to estimate the mass of MSW

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burned per unit area in different neighborhoods of varying socioeconomic status (SES) in Indian

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cities.

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We first present general observations about the MSW-burning in Delhi, India during early field

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work conducted in 2014. We then present a method for field measurement of the spatial

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frequency of MSW-burning incidents, MSW composition, and mass of MSW burned at the intra-

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urban scale. The method was tested in Delhi in winter and summer 2014-15 in three different

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neighborhoods of varying socioeconomic status, with and without MSW collection services. The

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method was then streamlined and deployed in Agra in summer 2015, offering an inter-city

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comparison.

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Key questions asked during the development of this method are: What is the best way to track

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and represent the daily spatial frequency of MSW-burning in a neighborhood, i.e., whether by

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the number of incidents per unit of area, or per household? Does the method capture seasonal/

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temporal patterns, and is it repeatable? Can the field method developed to record MSW-burning

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incidence also be applied to assess the composition and mass of the MSW being burned? What

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are the ways that neighborhood scale MSW-burning data can be scaled-up to the whole city to

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contribute to a city wide emission inventory?

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Developing methods for estimating the mass of MSW generated and the fraction that is burned at

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the neighborhood scale, and its relationship with various factors such as the provision of MSW

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collection services (or lack thereof), as well as the socioeconomic status of households (HHs),

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can help ground-truth the rules of thumb currently being used. This can help inform better

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policies to address the issue of MSW-burning at the city and neighborhood scale.

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METHODS

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Transect distance sampling approach

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A distance sampling approach, also called the line transect method20, was employed to estimate

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the spatial frequency, volume, and composition of MSW-burning at the neighborhood and city

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scale. The distance sampling approach draws upon a field method typically used by researchers

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for estimating the biological density and/or wildlife abundance in a specific habitat. In this

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method the observer moves along a line/road and counts the objects in a predetermined distance

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from the transect line (typically just visible range is used as the distance). Object density is then

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estimated by the total object count and surveyed area (Fig. S1). Fundamentally, it is assumed that

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all objects within the transect line of sight are detected. Employing a similar approach, a transect

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line (route) was designed for each neighborhood that covered a large proportion of each

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neighborhood (about 12-40%, See Fig. 1), and included both residential and commercial areas

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with diverse street types. Each MSW-burning incident along the transect route is recorded by the

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field researcher. The transect route, as well as the latitude and longitude waypoint of each MSW-

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burning incident were recorded by a hand-held Garmin GPS 72. Each neighborhood transect in

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Delhi was repeated three times each season, during summer and winter, in 2014 and 2015. The

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transects were covered by vehicle (two-wheeler or auto rickshaw) and by walking in some

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neighborhoods where the streets were not conducive to motorized travel. Several cross-Delhi

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transects spanning multiple neighborhoods were also conducted (Fig. S3). For an intercity

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comparison, multiple-neighborhood, cross-city transects were conducted in the nearby city of

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Agra during summer 2015.

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Delhi (28.61° N, 77.20° E, population 16.7 million) is the capital city of India and covers an

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area of 1,484 km2. Delhi is divided into 2,064 neighborhoods which are called colonies in India

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21,26

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houses the world heritage historical monument the Taj Mahal.

. The city of Agra (27°12' N 78°12' E) has an area of 141 km2 with 1.63 million people and

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Daily patterns and spatial frequency of MSW-burning

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Pre-transect observations of MSW-burning incidents were conducted in Delhi along three

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neighborhood transects, on two hour intervals throughout the day and late evening. These

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observations indicated that there were more MSW-burning incidents in the morning compared to

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the evening, typically starting around 6 am. MSW-burning was not observed in the afternoon,

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and then commenced again at dusk. Therefore the formal transect studies tracked both morning

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and evening observations each day, but not in the afternoon. Transect sampling stopped at 10 pm

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due to safety concerns for the researcher. However, any ash piles from burning past 10pm were

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noted by the researcher during the next morning’s transect and were added to the morning tally.

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Daily temperatures were also recorded on each of the transect study days. Individual transects

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were repeated over three days each in each of the three neighborhoods and in the three cross-

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Delhi transects, both in January 2014 and in May 2014 (pre-monsoon). The same transects were

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repeated in January and May 2015. Thus three different neighborhood transects and three cross-

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Delhi transects were observed over the period of 2 years. The team learned from the 2014 field

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experience, and recorded both morning and evening transects consistently every sampling day in

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2015.

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Neighborhood choice & context

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The transect studies of MSW-burning were conducted in three neighborhoods of Delhi, that

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varied significantly in socioeconomic status and levels of MSW collection service.

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Delhi’s Municipal Valuation Committee Report21 has classified the neighborhoods of Delhi

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according to different parameters such as the capital value of land, rental value, age of the

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colony, condition of the road, quality of physical and social infrastructure, and economic status.

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Neighborhoods are categorized into 8 types (A-H) with A representing the highest SES and H

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the lowest. As per the report, Brijpuri (BP) belongs to the F and G category, Jangpura Extension

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(JPE) to the B category, and Safdarjung Enclave (SJE) to the A category. The BP neighborhood

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was selected to represent a low-income slum area with poor MSW collection. The two high

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income areas, JPE and SJE, with apparently similar MSW service levels, were selected to assess

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any differences in MSW-burning patterns across more wealthy neighborhoods. The

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characteristics of the three neighborhoods, and their MSW-management infrastructures, are

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summarized below (and in Table 1 and Fig. S4).

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Brijpuri (BP) is considered a slum, with a low income level, a very high population density of

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about 87,000 people/km2, and minimal MSW collection services. Also, due to the low income of

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the residents, there were no privately employed household waste collectors. Only one

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municipality-employed street sweeper was seen by the research team; street sweepers are tasked

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with only sweeping debris from the streets. No designated waste collection centers - which are

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used for discarding MSW and serve as a collection point for truck to haul away the waste - were

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observed during the canvassing of Brijpuri in January 201422. Residents also informed the

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research team that a city-provided waste-pickup truck comes once a day, though it cannot access

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a majority of the narrow streets22.

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Safdarjung Enclave (SJE) is considered a high-income area, based on census data26 and also

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supported by visual observations of the housing types in the area. It is categorized as a type “A”

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neighborhood, reflecting the best SES in Delhi21. Households in SJE employ household waste

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collectors who collect and transport the MSW by tricycle to neighborhood waste collection

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centers. A typical waste collection center

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collection centers are noted in Supplementary Fig. S4b), and the municipality trucks haul away

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waste once or twice a day. In addition, several municipal street sweepers serve the area and were

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observed by the research team.

serves 500-600 homes (locations

of the waste

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Jangpura extension (JPE) is considered a high- to medium-income neighborhood, with a slightly

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lower neighborhood rating of “B”21 compared to SJE. SJE and JPE have lower population

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densities than BP, approximately 14,000-20,000 people/km2. JPE households also employ

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household waste collectors and have waste collection centers located in the neighborhood (1 for

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every 500 to 600 HHs) (Location of the waste collection centers are noted in Supplementary Fig.

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S4c).

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Composite MSW generation data were gathered in the three neighborhoods (Table 1). The data

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were collected by enlisting the services of the neighborhood household waste collector (except in

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BP where the researcher did the collection as no waste collector is employed by the households).

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MSW generated by 25 households was collected by the waste collector according to their normal

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routine. All MSW generated by these homes was aggregated and then segregated according to

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the type (biodegradable & recyclable) and weighed by the researcher, in a way similar to the

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method given by Ojeda et al., 200837. Dividing the composite trash weight by the number of

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homes served by the waste collector yielded the average waste generated per household. This

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process was repeated on 3 separate days.

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The average mass of the total MSW generated per person per day in BP, SJE, and JPE was 0.17

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kg, 0.39 kg, and 0.39 kg, respectively. The percentage of the MSW that was

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biodegradable/compostable for BP, SJE, and JPE was 90%, 75%, and 78%, respectively.

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In the SJE and JPE neighborhoods, at least 13% to 45% of the neighborhood area was covered

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by the road transect, as shown in Fig. 1, to ensure representative coverage. The BP transects

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were done along two routes; one accessible by two-wheeler vehicle, and another route was only

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wide enough for pedestrians (the researchers walked this transect). Each of the transects covered

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approximately 3 to 6 km, and the same transects were used for estimating seasonal variability in

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winter and in summer.

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information was recorded: the GPS location, as well as the estimated weight, composition, and

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any apparent reason of burning (e.g. if people were warming themselves it was assumed to be

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due to the need for heat).

During the sighting of each MSW-burning incident, the following

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For cross-Delhi transects, similar records of incidents of MSW-burning were recorded in

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different parts of the city, including the central core. The cross-Delhi transects covered diverse

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neighborhoods ranging from A-G, and included commercial areas and ring roads. About 40km of

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distance was covered in each cross-Delhi city transect (Fig. S3). Data have been also collected

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from Agra during summer 2015, by laying down two transects that ranged from 35 to 45 km and

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covered diverse neighborhoods of the city.

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Daily MSW-burning incidences per unit area and per unit household

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The number of MSW-burning incidents per unit of road length was converted to per unit area

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using the average line of sight distance on both sides of the road (Fig. S1), which was equivalent

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to the distance between the centerline of the transect road and its parallel road. The data were

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also converted to number of incidents per household by dividing the area by the housing density

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in each neighborhood (after subtracting for green spaces).

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Composition & coarse estimation of the mass of MSW burned

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Since it is difficult to weigh burning MSW, samples of MSW were obtained and weighed before

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and during different stages of burning, by sprinkling water on it and subsequently subtracting the

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added water weight. This coarsely estimates the mass of the burning MSW, while its

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composition was assessed by spreading out the burning MSW (after extinguishing) and recording

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its partially burned components. In this manner, an average weight and composition per burning

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incident could be estimated from the observation of each MSW-burning incident, during this first

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deployment of the field method.

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Scale-up from transect studies

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Data were scaled up to the city level for Delhi using the following different approaches:

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Approach (i). MSW-burning incidents per household scaled by neighborhood type:

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In this method we have classified all the neighborhoods of Delhi into two Groups (1) E-H:

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Lower SES, and, (2) A-D: Higher SES, according to the categories given by the valuation

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committee21. The scaling-up was done on the basis of the number of households in the different

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neighborhood types. Incidence of MSW-burning per household from BP were applied to

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estimate the MSW-burning from Group (1) neighborhoods, while the same data from SJE were

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used to calculate estimates for Group (2) neighborhoods. Our follow-up study of the social

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actors engaged in waste management (details are reported in 22), found that

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management is better in JPE than in the other two neighborhoods because of the direct

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involvement of the local residents and their neighborhood association in overseeing the daily

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waste pickup operations. Since such active management of MSW collection is uncommon, we

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considered JPE to be atypical, and therefore opted to focus on SJE and BP as representative of

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high- and low-SES areas, respectively. Our scale-up estimate using this approach is a first

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approximation of a land-use informed scale-up of the observed neighborhood MSW-burning.

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Future studies may consider traversing multiple neighborhoods of different types, for improved

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aggregation by neighborhood classification. Neighborhood routes include the main roads and

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arterials leading to them, as well as associated commercial establishments present locally with

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the households.

MSW

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Approach (ii) Cross-city transect MSW-burning incidents and mass per area: In the second

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approach, multiple neighborhoods are traversed in well-planned cross-city transects. Such

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transects should be planned carefully to cover diverse areas of the whole city. The average of

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multiple cross-city transects reported per unit area is then scaled to the total urban area23 of the

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city 920 km2 for Delhi and 185km2 in Agra.

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In general, we consider the first approach, i.e., of knowing and sampling neighborhoods of

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varying SES and scaling up by the population residing in the neighborhood types, to be a better

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approach. This first approach is expected to converge with the second approach, as long as the

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cross-city transects give a representative sample of diverse neighborhoods of the city.

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RESULTS

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MSW-burning spatial frequency: differences across neighborhoods (Intra urban)

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MSW-burning frequencies per unit area were found to be highest in the low-SES neighborhood

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(BP), and in the morning in all neighborhoods during both winter and summer (Fig. 2a). As seen

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in Fig. 2a, the spatial frequency of total daily MSW-burning incidents (morning plus evening)

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ranged from 24 incidents/km2-day to 130 incidents/km2-day during winter and 5 incidents/km2-

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day to 87 incidents/km2-day during summer, and were found to be highest in the low SES

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neighborhood (BP). Field results showed that differences in daily MSW-burning incidents per

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unit area between the neighborhoods were considerable, with JPE (24 incidents/km2-day) having

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about 87% less incidence frequency than BP (130 incidents/km2-day), based on full-day

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observation in winter (Fig. 2a). Similar patterns were observed in summer with the difference

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between JPE (5 incidents/km2-day) and BP (87 incidents/km2-day) being about 94%. Likewise,

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the estimated daily mass burned per unit of area (Fig. 2b) was also highest in BP, where

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infrastructure services are poor.

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The results from JPE and SJE (higher-SES areas) show, as expected, lower MSW-burning

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incidence (Fig. 2a) and lower mass burned per unit area (Fig. 2b) and per households (not

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shown) than BP (statistically significant at a = 0.05). It is important to note that the spatial

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frequency of MSW-burning incidences was non-zero in these high SES areas that have waste

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collection services. More surprising is that JPE had statistically lower MSW-burning incidence

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during winter compared to SJE, which has a higher SES and a higher neighborhood

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classification. Both have similar levels of MSW service provision. A follow-up survey of

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households (described in ref 22) indicated that factors such as the participation of neighborhood

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associations in monitoring waste collection service provides are important in reducing MSW-

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burning incidents22. A summary of these findings reported in Table 1 indicates, for example, that

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65% of the households surveyed in JPE were aware of the neighborhood association and its role

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in informally monitoring waste management in the neighborhoods, compared to less than 5% of

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homes in SJE. Furthermore, the neighborhood association in SJE did not take on a waste

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management role. Details of the social actor study are provided elsewhere22. These observations

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(both physical and social) indicate that the field method was able to detect these finer differences

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among neighborhoods quite consistently in different years.

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Daily and seasonal patterns

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Daily and seasonal variation in the spatial frequency of MSW-burning incidences was also

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significant. For the diurnal patterns, the MSW burning frequency observed in the evening was

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always lower than the morning in all three neighborhoods, in summer and winter (See Fig. 2).

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No MSW-burning incidents were observed in JPE and SJE during the evening transects in

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summer.

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Seasonal variations in MSW-burning were also observed with winter always higher than

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summer. SJE experiences the largest differences in daily MSW-burning rates between the winter

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(56 incidents/km2-day) and the summer (6 incidents/km2-day), while BP has the smallest

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difference between winter (130 incidents/km2-day) and summer (87 incidents/km2-day).

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In terms of the seasonal patterns in the estimate of daily MSW-burned per unit area, the low-SES

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BP neighborhood has the largest daily mass of MSW burned (1170 kg/km2-day), recorded in

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winter. This is about 14 times higher than JPE (89 kg/km2-day) full day MSW-burning in winter.

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For summer the full-day mass MSW-burning in BP is estimated at about 1100 kg/km2-day,

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followed by 18 kg/km2-day in SJE and 13 kg/km2-day in JPE (Fig. 2b). There is no statistical

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difference between the daily mass burnt per unit area observed in BP during summer (1170±108

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kg/km2-day) and winter (1100±481 kg/km2-day). This suggest that lack of collection services in

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low SES BP results in similar daily MSW mass burned per unit area, both in summer and

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winter.

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Another interesting note that we also did not observe a significant difference (a = 0.05) in total

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daily MSW-burning incidents between JPE and SJE in summer. Our field observations suggest

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that SJE showed higher night-time MSW-burning than JPE in winter, when household guards

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were often observed burning MSW to keep warm. Restrictions by residents in JPE may have

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limited this practice, resulting in winter-time differences between these two neighborhoods.

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When MSW-burning occurs to provide warmth, often firewood and other combustibles are

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added to the fire, as noted below in the composition details discussed next.

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Composition of MSW Being Burned

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Field observations indicate (Fig. 3) that the composition of the MSW being burned varies

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significantly and systematically across the three neighborhoods and across season. In winter,

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added purchased firewood is seen burning in the wealthier neighborhood to provide heat, while

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paper and plastics were found burning in lower-SES areas for the purpose of providing heat. The

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burning of plastics is particularly hazardous24 and reflects an environmental justice issue in the

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slum areas. These observations show that significant amounts of the materials like plastic and

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purchased firewood, which are not present in household waste streams, are being burned with

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MSW in winter. In summer, compostable waste (both kitchen waste and leaves/twigs) are

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dominant in waste burning in all the neighborhoods. Yard waste is burned more dominantly in

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wealthier areas, while kitchen waste is predominant in lower-SES areas. The summer inter-city

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comparison showed remarkable similarity in the waste composition between the low-SES area of

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Delhi and Agra in summer. The waste composition data suggest that much of the waste can be

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composted in summer. Neighborhood composting could be considered as an alternative to the

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present system.

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Scale-up from Transect Studies

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Applying the two approaches, we estimate the average daily spatial frequency of MSW-burning

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incidents in Delhi to be 38-40 incident/km2-day in winter and 25-31 incident/km2-day in summer

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(Fig. 4a) and the average daily mass of MSW-burned per unit area in Delhi to be 236-263

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kg/km2-day in the winter and 206-246 kg/km2-day in the summer (Fig. 4b). The Morning

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burning accounting for more than 65% in both seasons (Fig. 4). It is interesting to note that the

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averages scale up similarly in Delhi, using both approaches, which is expected when the cross-

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city transects sample a number of diverse neighborhoods. The daily total mass of MSW burned

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for the whole city is estimated to be about 190 to 246 tons/day. These preliminary calculations

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estimate that ~2-3% of MSW generated (8390 tons/day) 25 is burned in city streets in Delhi. The

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estimated percentage burned of total generated waste are within the range specified in the various

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literatures (Table S1) for Indian megacities, but it appears to be not as large as the higher

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percentages of 10% assumed by others. However, we note that burning in landfills may also

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contribute further.

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In contrast, the inter-city comparison showed Agra to be very different, with significantly higher

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MSW-burning spatial frequencies and a higher mass/area compared to Delhi (Fig. 4). For Agra

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the MSW burned was observed to be much higher in three different SES areas that were covered

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– ranging from frequencies of 39 to 202 incidents/km2-day, and 672 to 3485 kg/km2-day in

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highest- to lowest-SES neighborhoods in summer 2015 (Fig.5). This compares with