Characterizing the Spatial and Temporal Patterns of Open Burning of

Subscriber access provided by - Access paid by the | UCSB Libraries

Article

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

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 31

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

1 ACS Paragon Plus Environment


1

ABSTRACT

2

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

3

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

4

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

5

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

6

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

7

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

8

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

9

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

10

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

11

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

12

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

13

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

14

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

15

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

16

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

17

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

18

Keywords:

19

Emissions

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

20 21 22 23


Page 2 of 31

Page 3 of 31


24

INTRODUCTION

25

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

26

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

27

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

28

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

29

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

30

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

31

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

32

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

33

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

34

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

35

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

36

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

37

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

38

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

39 40

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

41

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

42

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

43

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

44

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

45

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

46

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


47

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

48

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

49

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

50

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

51

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

52

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

53

scale.

54 55

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

56

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

57

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

58

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

59

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

60

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

61

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

62

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

63

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

64

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

65

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

66

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

67

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

68

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

69


Page 4 of 31

Page 5 of 31


70

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

71

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

72

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

73

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

74

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

75

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

76

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

77

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

78

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

79

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

80 81

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

82

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

83

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

84

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

85

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

86

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

87

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

88

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

89

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

90

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

91

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


Field methods are not yet


92

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

93

in exposure to pollution.

94 95

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

96

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

97

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

98

cities.

99 100

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

101

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

102

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

103

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

104

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

105

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

106

comparison.

107 108

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

109

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

110

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

111

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

112

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

113

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

114

contribute to a city wide emission inventory?


Page 6 of 31

Page 7 of 31


115

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

116

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

117

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

118

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

119

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

120 121

METHODS

122

Transect distance sampling approach

123

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

124

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

125

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

126

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

127

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

128

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

129

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

130

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

131

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

132

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

133

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

134

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

135

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

136

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

137

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



138

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

139

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

140

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

141

Agra during summer 2015.

142 143

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

144

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

145

21,26

146

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

147 148

Daily patterns and spatial frequency of MSW-burning

149

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

150

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

151

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

152

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

153

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

154

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

155

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

156

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

157

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

158

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

159

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

160

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


Page 8 of 31

Page 9 of 31


161

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

162

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

163

2015.

164 165

Neighborhood choice & context

166

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

167

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

168 169

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

170

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

171

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

172

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

173

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

174

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

175

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

176

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

177

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

178

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

179

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

180 181

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

182

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

183

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



Page 10 of 31

184

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

185

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

186

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

187

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

188

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

189

a majority of the narrow streets22.

190 191

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

192

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

193

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

194

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

195

centers. A typical waste collection center

196

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

197

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

198

observed by the research team.

serves 500-600 homes (locations

of the waste

199 200

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

201

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

202

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

203

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

204

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

205

S4c).

206


Page 11 of 31


207

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

208

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

209

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

210

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

211

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

212

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

213

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

214

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

215

process was repeated on 3 separate days.

216 217

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

218

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

219

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

220 221

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

222

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

223

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

224

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

225

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

226

winter and in summer.

227

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

228

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

229

due to the need for heat).

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



230

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

231

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

232

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

233

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

234

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

235

covered diverse neighborhoods of the city.

Page 12 of 31

236 237

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

238

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

239

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

240

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

241

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

242

in each neighborhood (after subtracting for green spaces).

243 244

Composition & coarse estimation of the mass of MSW burned

245

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

246

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

247

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

248

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

249

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

250

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

251

deployment of the field method.

252


Page 13 of 31


253

Scale-up from transect studies

254

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

255

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

256

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

257

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

258

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

259

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

260

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

261

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

262

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

263

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

264

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

265

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

266

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

267

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

268

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

269

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

270

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

271

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

272

the households.

MSW

273 274

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

275

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



276

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

277

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

278

city 920 km2 for Delhi and 185km2 in Agra.

Page 14 of 31

279 280

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

281

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

282

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

283

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

284 285

RESULTS

286

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

287

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

288

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

289

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

290

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

291

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

292

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

293

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

294

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

295

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

296

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

297

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

298

infrastructure services are poor.


Page 15 of 31


299 300

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

301

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

302

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

303

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

304

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

305

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

306

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

307

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

308

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

309

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

310

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

311

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

312

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

313

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

314

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

315

among neighborhoods quite consistently in different years.

316 317

Daily and seasonal patterns

318

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

319

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

320

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



321

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

322

summer.

Page 16 of 31

323 324

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

325

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

326

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

327

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

328 329

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

330

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

331

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

332

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

333

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

334

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

335

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

336

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

337

winter.

338 339

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

340

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

341

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

342

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

343

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


Page 17 of 31


344

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

345

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

346 347

Composition of MSW Being Burned

348

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

349

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

350

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

351

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

352

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

353

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

354

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

355

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

356

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

357

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

358

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

359

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

360

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

361

present system.

362 363

Scale-up from Transect Studies

364

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

365

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

366

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



Page 18 of 31

367

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

368

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

369

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

370

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

371

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

372

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

373

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

374

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

375

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

376

contribute further.

377 378

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

379

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

380

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

381

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

382

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

Characterizing the Spatial and Temporal Patterns of Open Burning of

Recommend Documents