Qualitative determination of energy potential and methane generation from municipal solid waste (MSW) in Dhanbad (India)

Qualitative determination of energy potential and methane generation from municipal solid waste (MSW) in Dhanbad (India)

Accepted Manuscript Qualitative determination of energy potential and methane generation from Municipal Solid Waste (MSW) in Dhanbad (India) Drake Mb...

5MB Sizes 0 Downloads 38 Views

Accepted Manuscript Qualitative determination of energy potential and methane generation from Municipal Solid Waste (MSW) in Dhanbad (India)

Drake Mboowa, Shireen Quereshi, Chiranjit Bhattacharjee, Kukeera Tonny, Suman Dutta PII:

S0360-5442(17)30183-4

DOI:

10.1016/j.energy.2017.02.009

Reference:

EGY 10302

To appear in:

Energy

Received Date:

19 August 2016

Revised Date:

06 January 2017

Accepted Date:

02 February 2017

Please cite this article as: Drake Mboowa, Shireen Quereshi, Chiranjit Bhattacharjee, Kukeera Tonny, Suman Dutta, Qualitative determination of energy potential and methane generation from Municipal Solid Waste (MSW) in Dhanbad (India), Energy (2017), doi: 10.1016/j.energy. 2017.02.009

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Highlights  characterization of municipal solid waste (MSW) of Dhanbad city is done  methane gas generation from landfill sites at Dhanbad city is estimated  energy recovery potential from MSW is studied  ANOVA study is done for composition of municipal solid waste at Dhanbad city

ACCEPTED MANUSCRIPT

1

Qualitative determination of energy potential and methane generation from Municipal Solid

2

Waste (MSW) in Dhanbad (India)

3

Drake Mboowaa, Shireen Quereshib, Chiranjit Bhattacharjeeb, Kukeera Tonnya, Suman Duttab*

4

a Makerere

University, Department of Agricultural and Bio-Systems Engineering, P. O. Box 7062,

5 6

Kampala, Uganda. b

Department of Chemical Engineering, Indian Institute of Technology (ISM) Dhanbad, India

7 8

Abstract

9

Methane generation from waste landfills is one of the biggest contributors to global warming. The

10

purpose of this study was twofold: (i) to investigate methane concentration from Municipal Solid

11

Waste (MSW) at three landfills in Dhanbad city, India and (ii) to evaluate the amount of energy

12

that could be recovered based on the MSW characteristics if it were to be incinerated. The waste

13

samples were collected and analysed for composition, energy content, and methane concentration.

14

Results from MSW characterisation revealed that the main component of Dhanbad MSW is

15

organic waste, which made up to 75% of the waste by weight. Methane concentration and

16

moisture content from Railway station (site 1) and Memco-more (site 2 and site 3) measured as

17

140.53, 18.18 and 20.28 ppm methane/g waste and 25.49, 3.40 and 2.96% dry weight respectively.

18

The calorific value for the waste samples ranged between 10.7 to 13.0 MJ/kg. These findings

19

confirm that the methane generated at the sites can be used for energy recovery. Additionally, the

20

energy content of the MSW suggests that it is a suitable feedstock that can be utilized for electricity

21

generation through combustion.

22 23

Key words: Dhanbad city; Municipal solid waste; Waste landfills; Methane generation; Energy

24

content

25

*Corresponding author e-mail: [email protected] (Suman Dutta)

1

ACCEPTED MANUSCRIPT

26

1. Introduction

27

Global warming has been and is still a global concern whose reduction has been a subject of debate

28

for the past decades. Globally, municipal solid waste (MSW), is one of the biggest contributors to

29

global warming, with recent estimates at 16 % greenhouse gas (GHG) emissions [1]. Among other

30

ways, reduction of GHG emissions and hence global warming is through, quantification of methane

31

emission from landfills. Various studies show that methane can be used as green energy source.

32

Hydrogen is produced via steam reforming of methane (SRM) and high temperature water gas shift

33

reaction [2]. Abánades et al. [3] mentioned three state-of-the-art methane pyrolysis processes such

34

as direct thermal cracking, catalysed methane cracking, combined thermal and electrochemistry

35

methods. In this study, accurate assessment of MSW composition, estimation of methane emissions

36

by laboratory scale anaerobic digestion of organic waste as well as energy content of MSW were

37

investigated in Dhanbad city, India.

38 39

Dhanbad city, located in the eastern part of India has a population of 2.68 million people [4], and

40

this population is estimated at 3.9% growth rate per annum. Such a growth rate has resulted in an

41

increase in the amount of waste generated. Municipal solid waste (MSW) generation, collection,

42

treatment, and disposal activities pose an environmental problem to the city. Currently, 440 tons of

43

MSW are generated daily in the Municipal Corporation jurisdiction and the responsible agencies

44

collect about 165 tons [5]. This represents approximately 37% of the total waste generated. The

45

remaining uncollected waste is normally disposed of in unauthorized sites, leading to health and

46

environmental problems. This calls for city authorities to develop an integrated approach for solid

47

waste management through frequent waste collection, recycling and combustion in order to recover

48

energy from this waste. Power generation from MSW is possible using an incineration plant [6].

49

Regrettably, for such approaches to work, basic data on the characteristics of the waste produced is

50

central.

2

ACCEPTED MANUSCRIPT

51

The landfills in Dhanbad are mainly non-engineered low-lying open dumps that have neither

52

bottom liners nor leachate collection and treatment systems. Compaction and leveling of waste and

53

final covering by earth are not done, and these sites lack a landfill gas monitoring and collection

54

equipment [7,8]. Such a waste management system is a threat as it results in higher methane

55

emissions if the gas is not flared or recovered [9]. It also gives rise to serious environmental

56

degradation accruing from air pollution, surface, and underground water pollution [10].

57 58

Since methane gas liberated from landfills account for the anthropogenic sources in the world,

59

therefore, estimation of methane gas generation is vital to provide a basis for evaluation and

60

formulation of energy recovery counter measures. This way, reduction in the atmospheric

61

concentration of methane can be reduced. International procedures based on models such as First

62

order model [11], Mass balance model [12], LandGEM [13], EPER model France (ADEME) etc.

63

have already been put into place by the United Nations to ensure qualitative estimation of methane

64

emission from landfills. These models require harmonization since they provide results with huge

65

differences, hence doubting their accuracy [14]. The amount (mass) and rates of methane

66

generation depend on many factors that are difficult to quantify and these vary from site to site [9].

67

Onsite measurement tools that quantify methane gas generation are expensive and scarce in

68

developing countries. Most studies use models based on the available data and provide erroneous

69

results. Hence, the objectives of this study is to qualitatively determine the methane gas generation

70

from selected waste landfills in Dhanbad City using a gas chromatography equipped with a Flame

71

Ionization Detector (GC-FID) method and to evaluate the amount of energy that could be

72

recovered from MSW based on the local characteristics if it were to be combusted..

73 74

2. Materials and methodology

75

2.1 Study area

3

ACCEPTED MANUSCRIPT

76

Dhanbad is the largest city in Jharkhand state and covers a total area of 2041.62 km2. It is bounded

77

by latitude 86°07´ and 86°50´ E and longitude 24°37´ and 24°02´N (Fig. 1). The area experiences

78

five climate seasons namely spring, summer, monsoon, autumn, and winter season. The

79

temperatures normally range from 2°C to 40°C but can stretch to 47°C in summer and −4°C in

80

winter. The city lacks a defined landfill site and hence waste is dumped in non-engineered low-

81

lying landfills. There are no scavenger activities at these sites and they lack a leachate treatment

82

plant.

83 84

This study was conducted on three main landfill sites, with two sites located in Memco-more, a

85

suburb of Dhanbad city, and another site at Dhanbad railway station (Fig. 2). The site at the railway

86

station mainly comprised of organic waste since it was next to a very busy market, while sites in

87

Memco-more mainly comprised of inorganic materials since most of the waste disposed of at those

88

sites was mainly from residential areas.

89 90

2.2 Determining the physical composition of the waste

91

This consisted of sample collection, sorting of various materials and laboratory analysis to

92

determine MSW composition. The method of sampling was based on ASTM D5231 [15] and

93

followed a procedure as described by Abdalqader & Hamad [16].

94 95

We collected 10 waste samples from site 1 (Railway station), site 2 and site 3 (Memco-more) were

96

randomly in summer (September to October) and autumn season (November to December) when

97

the average temperature was 35-30°C. For each sample, sorting was done and waste was separated

98

into organics, hard plastics, metals, papers, soft plastics (polythene), glass, textiles & leather and

99

others. It was then weighted and the amount of different waste fractions were recorded. The

100

organic fraction was then thoroughly mixed and spread out by hand on a 5 by 2 m grid, from which

101

10 samples of 1 kg each were randomly picked per grid. These 10 samples were then thoroughly

4

ACCEPTED MANUSCRIPT

102

mixed and a final 1 kg sample was drawn and taken to the laboratory for anaerobic digestion,

103

proximate and ultimate analysis. This exercise was repeated for all the 30 randomly collected

104

samples from sites 1,2 and 3 on each sampling day and average values were taken.

105 106

For energy analysis, 500 g of unsorted MSW was collected and taken to the laboratory. This

107

procedure was done in triplicates for all the landfills that are described in this study and was

108

repeated once a week for four months. Therefore, for all the sampling day 16 samples were

109

collected for energy analysis per site.

110 111

2.3 Formation of methane in anaerobic condition

112

From each of the three landfills, 10 organic waste samples were prepared to produce gas at

113

anaerobic conditions. About 30 g of organic waste sample from each of the three sites were

114

transferred into 250 ml plastic bottles (digester), 50 ml of distilled water gently added and the

115

bottle tightly capped. The samples were left to stand at room temperature (32°C ± 3°C) and

116

analyzed after 10 days of digestion. Gas samples of 10 µl were collected from the digester using a

117

syringe and immediately injected to Gas chromatography (GC) analyser for composition analysis.

118

This experiment was done in triplicates for each sample and average values noted.

119 120

2.4 Methane estimation by Gas Chromatography (GC) method

121

The gas produced by anaerobic digestion was analyzed for methane gas using Varian CP-3800

122

Gas chromatography (GC) equipped with a Flame Ionization Detector (FID). The column was

123

WCOT fused silica (50 m x 0.25 mm ID). Coating CP-SIL 8CB (5% phenyl; 95% di-methyl

124

polysiloxane), D.F 0.12. The carrier and make up gas was high purity gas nitrogen at 1 ml/min.

125

The column oven was programmed at an initial temperature of 50°C held at 3 minutes, then

126

50°C to 200°C at a rate of 20°C/min. The oven was then held at 200°C for 3 minutes. The

5

ACCEPTED MANUSCRIPT

127

injector was set at 200°C; split ratio of 1:10. The FID detector was set at 240°C at a range of

128

10. The flow rate was set at 1 ml/min.

129 130

The GC was calibrated with the known concentration of pure methane. The methane gas peaks

131

were formed and the area under their graphs noted. A calibration curve was plotted as the

132

concentration of methane (ppm) vs. area under the curve (mV.s). The actual amounts of methane

133

gas emitted by the organic waste samples were measured using this calibration curve.

134 135

2.5 Proximate analysis and ultimate analysis of organic waste

136

Proximate analysis was done on the organic waste samples to determine the gross component of

137

moisture, volatile matter, fixed carbon, and ash content. The moisture content was determined in

138

accordance with ASTM E1756-08 standard [17]. Organic waste sample of 5 g was placed in an

139

oven at 105°C for 2 hours. The sample was then cooled in a desiccator and reweighed. The

140

difference in weight difference denoted the moisture content expressed as a percentage. The

141

volatile matter was determined following the ASTM standard E-872 [18]. The aforementioned

142

organic sample used for moisture determination was covered in a crucible and heated in a furnace

143

for 2 hours. The crucible was later taken out of the furnace and cooled in a desiccator and

144

reweighed. The weight difference was taken as volatile matter. Ash content was determined by

145

placing the remaining organic sample from volatile matter calculations in the furnace at 575°C for

146

an hour for combustion following a procedure as described by ASTM D1102, 2013 [19]. All

147

carbon was burnt, and the sample was cooled in a desiccator and then reweighed. The weight

148

difference was taken as the ash content. Fixed carbon in fuel was determined by the subtraction 100

149

from the moisture, volatile matter, and ash contents. Proximate analysis was done in triplicates and

150

the average value was taken.

151

FC= 100 - M - VM - ASH

152

Where: FC - Fixed carbon, M - Moisture, VM -Volatile matter and ASH – remaining ash

6

ACCEPTED MANUSCRIPT

153

Ultimate analysis was done on a using the CHNS analyser (type: Vario micro cube) which employs

154

classic oxidation, decomposition, and reduction technique. Organic sample of 0.5 g was dried at

155

105°C for 3 hours, cooled in the desiccators, and then grounded to powder form by using pestle and

156

mortal and later formed into pellets. The pellets were then put in the CHNS analyser to determine

157

the percentage composition of C, H, N and S. Oxygen (O) was calculated by difference from C, H,

158

N and S as described by Lee and Hauffman [20].

159 160

2.6 Calorific value determination

161

The calorific value of the MSW was determined using GallenKamp autobomb. An amount of 100 g

162

MSW was collected from each landfill site, dried and ground into small particles. 1 g of these

163

particles was weighed, sieved and compressed formed into pellets. The pellets were placed in the

164

sample pan of the bomb calorimeter one at a time and the energy content of the sample was

165

determined following the procedure by Jesup in 1960 [21]. This experiment was done in triplicates

166

for each landfill site and average values were taken.

167 168

3. Results and discussion

169

The results obtained through this study are given in Tables 1, 2, 3 and 4. The collected data was

170

analyzed using R statistical software. Two-way ANOVA and Tukey tests were used at 95%

171

confidence interval to check whether there was any statistical difference in the results obtained

172

from the three landfills.

173 174

3.1 Physical composition of waste

175

The mean percentage of waste composition (by weight) for the Dhanbad city as obtained from

176

three landfills (Table 1) revealed that the most dominant waste fraction is the organic waste

177

(75%). The other fractions weighed as, hard plastics (7.7%), metals (0.3%), papers (0.6%), soft

178

plastics (13%), glass (0.5%), textiles and leather (2.4%) and others (0.5%). These results are far

7

ACCEPTED MANUSCRIPT

179

different from those reported for other Indian cities like Kolkata [22], Varanasi city [23] and

180

Aurangabad City [24]. Therefore, studies that assume average values of waste composition for

181

Indian cities may result into erroneous results. This is because waste composition depends on a

182

wide range of factors such as food habits, cultural traditions, lifestyles, climate, and income, etc.

183

[8].

184 185

Two-way ANOVA showed a significant difference (P<0.001) in organics, hard and soft

186

plastics among the different sites whereas no significant difference (P>0.05) between sites 2 &

187

3 was showed. Tukey test revealed that organic fraction of site 1 was significantly greater

188

(P<0.001) than that of site 2 & 3, while site 2 and 3 was significantly greater (P<0.001) in hard

189

and soft plastics as compared to site1. Two-way ANOVA revealed that there was no significant

190

difference (P>0.005) in metals, others, and glass; however, a significant difference (P<0.05)

191

was showed for textiles and leather. Further analysis with the Tukey test revealed that site 2

192

had more leather and textiles followed by site 3 and lastly site 1.

193 194

Railway station, site 1 had more organics (92%) followed by Memco-more, site 3 (69%) and then

195

Memco-more, site 2 (64%). This can be attributed to the food consumption and social activity at

196

the railway station. For example, there are many restaurants where the majority of the people and

197

workers have their meals and refreshments. There is also a big market where agricultural products

198

are sold, and these contribute to the high percentage of organic waste. This is contrary to Memco-

199

more site 2 and 3 which are situated in areas which are sparsely populated and there are little

200

activities that contribute to organic waste. Metals, papers, glass, textiles & leather and others had

201

the small fractions.

202 203

Site 2 and 3 had more plastics, metal, paper, textiles & leather, and others as compared to site 1.

204

The high percentage of plastic can be explained by increasing the number of packaging factories

8

ACCEPTED MANUSCRIPT

205

in Dhanbad city and the cost of packaging with plastics being cheaper than with paper, textiles of

206

organic materials. The high percentage of recyclable materials at the landfill sites 2 and 3

207

revealed that there is a need to set up recycling facilities at these landfill sites. The recovery

208

process can be considered as one of the suitable methods to handle and reduce the high volume

209

of plastic and other recyclable materials [25]. There is not much difference between the amount

210

of paper waste in site 2 and site 3, but the percentage is higher than that of site 1. This may be

211

attributed to the increase in the number of schools, offices, and commercial areas that are

212

neighboring those sites. The large variation in the amount of textiles & leather with site 2 having

213

a higher percentage followed by site 3 and then site 1, is largely due to the growing population

214

around site 2. As the population increases, more textile & leather materials will be on demand for

215

wearing and other purposes related to human nature.

216 217

3.2 Proximate and ultimate analyses of organic waste

218

Two-way ANOVA indicated a significant difference (P<0.001) in MC, ASH, VM, and FC

219

obtained from the three landfill sites. Tukey test showed that MC from site 1 (Table 2) was

220

significantly greater (P<0.001) than that of site 2 & 3. However, there was no significant

221

difference (P>0.05) in MC, ASH, VM, and FC obtained from site 2&3.

222 223

Moisture content on a dry basis for the three landfill sites was approximately 10% dry weight. The

224

results were low as the study was carried out in summer and early autumn when the temperatures

225

(40 – 45°C) were high. This observation was similar in other studies as reported by some other

226

researchers [26-28]. Moisture content was high at Railway station, site 1 as compared to Memco-

227

more, site 2 and 3. This is attributed to the presence of a higher percentage of agricultural and food

228

waste and presence of a stream of water that passes through it at Railway station, site 1.

229

Municipal solid waste of site 2 and 3 presented high volatile solids of 54.82% dry weight, fixed

230

carbon of 11.69% dry weight and ash content of 30.31% dry weight, as compared to site 1 with

9

ACCEPTED MANUSCRIPT

231

volatile solids of 45.28% dry weight, fixed carbon of 4.53% dry weight and ash content of 24.71%

232

dry weight. This high volatile matter from the landfill sites showed that the amount of organic

233

matters was high since it ranged from 69 to 92% of the total waste from the three landfill sites. This

234

high volatile solid is an indicator that high heat energy can be produced from such waste. Site 2 and

235

3 had more fixed carbon as compared to site 1 and this implied that fuels from site 2 and 3 require

236

longer retention time in the combustion chamber for complete combustion as compared with fuel

237

from site 1 [29].

238 239

The volatile matter ranged between 56.22 and 45.28 for the three sites wt. % dry basis, while

240

Ash ranged between 24.71 to 31.69 wt. % dry basis and the fixed carbon ranged between 4.53 to

241

11.89 wt. % dry basis. Site 1 had higher moisture content because it is located next to a drainage

242

channel and one of the streams contributing to the flow of that channel passes through it, as

243

opposed to site 2 and 3 which are located on a dry free land. Usually, the low moisture content is

244

expected during summer, and it is the season in which this study was carried out.

245 246

The ash content from the three landfill sites ranged between 24-29 wt.% dry basis. In comparison

247

with the standard ash content (5-15 wt.% dry basis) as reported by US.EPA [30] recommended for

248

incineration, this was quite high. High ash content was attributed to the high amount of inert

249

materials found in the municipal solid waste sample.

250 251

The ultimate analysis results showed no significant difference (P>0.05) in the elemental

252

composition of organic waste in all landfills (Table 3). The average carbon, hydrogen, nitrogen,

253

sulphur and oxygen of the municipal solid waste constituted approximately 31.3, 3.9, 1.2, 0.2 and

254

24.3%, respectively. The hydrogen, sulphur, and nitrogen amounts were low while there was little

255

high oxygen and carbon amounts. The high carbon was attributed to a large amount of organic

256

matter in the organic waste. These results and findings are in agreement and comparison with those

10

ACCEPTED MANUSCRIPT

257

from other sources as reported by some researcher [31,32] at Phetchaburi province in Thailand and

258

Panjab (India). However, they were also quite different from those reported by Chiang Mai Green

259

Energy Co., Ltd. at Chiang Mai University in 2012 [33] (Table 3).

260 261

3.3 Calorific Value of MSW

262

Based on laboratory analysis result, the calorific value on the dry basis was found to be of highest

263

value approximately 13.0 MJ/kg at site 3 followed by site 2 (12.2 MJ/kg), and lastly, site 1 (10.7

264

MJ/kg). According to GIZ and PCD (2011) [34], solid waste with a calorific value of 11-17 MJ/kg

265

or more is highly recommended for use as refuse-derived fuel (RDF). Therefore, waste from all the

266

landfill sites qualify to be used as fuel. The calorific value was relatively high because of the

267

presence of less amount of inert materials in the municipal solid waste. Such calorific value result

268

also compares with the value of 11MJ/Kg, obtained from UK municipal solid waste [35].

269 270

3.4 Methane gas estimation

271

Methane concentration for the three landfill sites was analyzed by Gas Chromatograph in Parts

272

per million (ppm). The average methane concentration values were observed highest at site 1 as

273

140.53 ppm methane/g waste while site 2 and site 3 measured 18.18 ppm methane/g waste and

274

20.28 ppm methane/g waste respectively. These values are sufficient for utilisation in electricity

275

production through combustion processes that use the Organic Rankine Cycle or through the use of

276

a biogas generator [36]. Two-way ANOVA indicated a significant difference (P<0.001) in

277

methane concentration obtained from the three landfill sites. Further analysis of this difference

278

using the Tukey test revealed that the methane concentration from site 1 was significantly

279

greater (P<0.001) than that of site 2 & 3. However, there was no significant difference (P>0.05)

280

in the methane quantities from site 2&3 (Table 4).

281

11

ACCEPTED MANUSCRIPT

282

This was attributed to a high percentage of moisture content and organic materials observed at site

283

1 as compared to site 2 and site 3. Gurijala and Suflita [37] also reported that higher methane

284

emission was quantified at higher moisture contents in landfill areas, while Kazuyuki & Katsuyuki

285

[38] reported that organic matter application had an effect on methane emission from some

286

Japanese paddy fields, with high organic matter application producing more methane gas and vice

287

versa. However, the methane quantities concentration is also affected by ash content. Site 1 with

288

lower fractions of ash content, has the highest values of methane concentration and vice versa for

289

site 2 & 3. This observation agrees with many studies of biochar and charcoal [39,40].

290 291

4. Conclusions

292

The analysis of the physical composition of municipal solid waste generated in Dhanbad city

293

showed that on average it mostly comprises of organic waste. Based on the results, there is a

294

correlation between moisture content, composition of the organic waste and the quantity of

295

methane gas emissions. The more the moisture content and organic waste composition and less the

296

ash content, the higher the methane gas produced, hence Railway station site 1 produced more

297

methane concentration than Memco-more site 2 & 3. Since methane gas is one of the major

298

contributors to global warming, mitigation steps must be undertaken to trap it and be used a source

299

of green energy. The concentration of methane at tall the three sites suggest that the landfills can be

300

utilized for energy production; however, more research needs to be carried out concerning techno-

301

economic evaluation. The low moisture content indicated that the sampled waste was suitable for

302

combustion, other than composting and other biological waste management methods, hence

303

suitable for energy production. The average energy content in municipal solid waste from the three

304

landfills was approximately 11.97 MJ/kg. This compares to about 69.4% of energy from pure

305

biomass and about 31.3% of the energy of bituminous coal. An integrated solid waste management

306

scheme for Dhanbad city is recommended so as to harness energy from solid waste as a

307

supplementary energy to the existing national grid and natural gas industry. This can help to reduce

12

ACCEPTED MANUSCRIPT

308

the over-dependence on fossil fuel and also the production of clean energy which is healthier to the

309

environment as well as providing jobs to the local who will be engaged in collection, sorting,

310

recycling and composting of the municipal solid waste. Further studies are recommended for the

311

same study during the winter, monsoon, spring and fall seasons to come up with a general

312

conclusion on the viability of such a project. More research and data is required so as to design and

313

construct engineered landfill site for Dhanbad city as a way of managing the waste generated in the

314

city.

315 316

5. Acknowledgement

317

The authors thank Centre for Science and Technology of the Non-Aligned and Other Developing

318

Countries (NAM S&T Centre) for initiating the collaboration and sponsoring the research. They

319

also thank the Department of Chemical Engineering, India Institute of Technology (ISM) Dhanbad

320

for the provision of laboratory services.

321 322

6. References

323

[1] Edenhofer O. et al. Mitigation of Climate Change. Contribution of Working Group III to the

324

Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge

325

University Press, Cambridge, UK and New York, NY; 2014.

326

[2] LeValley TL, Richard AR, Fan M. Development of catalysts for hydrogen production through

327

the integration of steam reforming of methane and high temperature water gas shift. Energy

328

2015; 90:748-58

329 330

[3] Abánades A, Rubbia C, Salmieri D. Technological challenges for industrial development of hydrogen production based on methane cracking. Energy 2012; 46: 359-63

331

[4] Census 2011, India, http://www.censusindia.gov.in.

332

[5] City Development Plan, Dhanbad, 2007, Final report by Dhanbad Municipal Corporation.

13

ACCEPTED MANUSCRIPT

333

[6] Tsai W-T, Kuo K-C. An analysis of power generation from municipal solid waste (MSW)

334

incineration plants in Taiwan. Energy 2010; 35:4824-30

335

[7] Bhide AD, Shekdar AV. Solid waste management in Indian urban centers. International Solid

336 337 338

Waste Association Times (ISWA) 1998; 1:26–8. [8] Gupta S, Krishna M, Prasad RK, Gupta S, Kansal A. Solid waste management in India: options and opportunities, Resource, Conservation and Recycling 1998; 24:137–54.

339

[9] Nakibuuka MM, Tashobya D, Banadda N, Ayaa F, Nhapi I, Wali GU, Kimwaga R. New

340

method for qualitative determination of Methane Gas at selected sites in Kampala City,

341

Uganda. Open Environ Eng J 2012; 5:50-5.

342 343 344 345 346 347 348 349 350 351 352 353 354 355

[10] Sharholy M, Ahmed K, Mahmood G, Trivedi RC. Municipal solid waste management in Indian cities – A review. Waste Management 2008; 28: 459-67. [11] Oonk J. & Boom A. Landfill gas formation, recovery and emissions . TNO Inst. of Environmetal and Energy Technology; 1995, p. 95-203. [12] IPCC. IPCC Guidelines for National Greenhouse Gas Inventions: Reference Manual, National Physical Laboratory, New Delhi, India; 2006, p. 6-15. [13] Landfill Gas Emissions Model (LandGEM) Version 3.02 User’s Guide, EPA-600/R-05/047. http://www.epa.gov/ttn/catc/dir1/landgem-v302-guide.pdf>, USA. [14] Scharff H, Jacobs J. Applying guidance for methane emission estimation for landfills. Waste Management 2006; 26:417-29. [15] ASTM D5231-92: Standard Test Method for Determination of the Composition of Unprocessed Municipal Solid Waste, ASTM International, West Conshohocken, PA, 2016. [16] Abdalqader A, Hamad J. Municipal solid waste composition determination supporting the integrated solid waste management in Gaza strip. Int J Environ Sci Dev 2012; 3(2): 172-77.

356

[17] ASTM E1756-08: Standard Test Method for Determination of Total Solids in Biomass,

357

ASTM International, West Conshohocken, PA, 2015.

14

ACCEPTED MANUSCRIPT

358

[18] ASTM E872-82: Standard Test Method for Volatile Matter in the Analysis of Particulate

359

Wood Fuels, ASTM International, West Conshohocken, PA, 2013.

360

[19] ASTM D. 1102-84: Standard test method for ash in wood. American Society for Testing and

361

Materials, West Conshohocken. 2013.

362

[20] Lee CC, Hauffman GL. Solid Waste Calculations: Thermodynamics used in Environmental

363

Engineering. Handbook of Incineration. 2001; 2(2.47).

364

[21] Jessup, R.S.1960. Precise measurement of heat of combustion with a bomb calorimeter.

365

http://digital.library.unt.edu/ark:/67531/metadc13253/m2/1/high_res_d/NBS%20Monograph

366

%207.pdf. [accessed 04.02.2016]

367 368

[22] Das S, Bhattacharyya BK. Municipal Solid Waste Characteristics and Management in Kolkata, India. Int J Emer Tech & Adv Eng 2013; 3:147-52.

369

[23] Srivastava R, Krishna V, Sonkar I. Characterization and management of municipal solid

370

waste: a case study of Varanasi city, India. Int Journal of Cur Res & Acad Rev 2014; 2:10-6.

371

[24] Late A, Mule MB. Composition and Characterization Study of Solid Waste from Aurangabad

372 373 374

City. Universal Journal of Environmental Research and Technology 2011; 1: 55-60. [25] Kalanatarifard A, Yang, GS. Identification of the Municipal Solid Waste Characteristics and Potential of Plastic Recovery at Bakri Landfill, Muar, Malaysia. J Sus Dev 2012; 5(7): 11-7.

375

[26] Pockman WT, Small, EE. The influence of spatial patterns of soil moisture on the grass and

376

shrub responses to a summer rainstorm in a Chihuahuan Desert ecotone. Ecosystems 2010;

377

13: 511-25.

378 379 380 381

[27] West AG, Hultine KR, Burtch KG., Ehleringer JR. Seasonal variations in moisture use in a pinon-juniper woodland. Oecologia 2007; 153:787-98. [28] Dong-Wook K. Modeling air-drying of douglas-fir and hybrid poplar biomass in Oregon. PhD diss., Oregon State University, 2012.

15

ACCEPTED MANUSCRIPT

382 383 384 385

[29] Pichtel J. Waste Management Practices: Municipal, Hazardous, and Industrial. (2nd ed.). Florida: CRC Press; 2014. [30] United States Environmental Protection Agency (U.S.EPA)., 2014. Municipal Solid Waste: Ash Generated from the MSW Combustion Process.

386

http://www.epa.gov/epawaste/nonhaz/municipal/wte/basic.htm. [accessed 15.02.2016]

387

[31] Suthapanich W. “Characterization and assessment of municipal solid waste for energy

388 389 390 391 392

recovery options in Phetchaburi, Thailand.” PhD diss., Asian Institute of Technology, 2014. [32] Sethi S, Kothiyal NC, Nema AK, Kaushik MK. Characterization of Municipal Solid Waste in Jalandhar City, Panjab, India. J Hazard Toxic Radioact Waste 2009; 1:97-106. [33] Chiang Mai University. Waste Separation and Analysis. Chiang Mai Green Energy Co. Ltd; 2012.

393

[34] www.giz.de

394

[35] Nasserzadeh V, Swithenbank J, Scott D, Jones B. Design optimization of a large municipal

395 396 397 398 399 400 401

solid waste incinerator," Waste Management, vol. 11 (1991) pp. 249-61. [36] Lee TH, Huang SR, Chen CH. The experimental study on biogas power generation enhanced by using waste heat to preheat inlet gases. Renewable Energy 2013; 50:342-47. [37] Gurijala KR, Suflita JM. Environmental factors influencing methanogenesis from refuse in landfill samples, samples, Environ Sc & Tech 1993; 27: 1176–81. [38] Kazuyuki Y, Katsuyuki M. Effect of organic matter application on methane emission from some Japanese paddy fields. Soil Sc & Plant Nutr 2012; 36: 599-10.

402

[39] Spokas KA. Review of the stability of biochar in soils. Carbon Manage 2010; 1: 289–303.

403

[40] Lee JW, Kidder M, Evans BR, Paik S, Buchanan III AC, Garten CT, Brown RC.

404

Characterization of biochars produced from cornstovers for soil amendment. Environ Sci

405

Technol 2010; 44(20): 7970–74.

406 407

List of Figures:

16

ACCEPTED MANUSCRIPT

408

Fig.1: Location of Dhanbad city (Google map)

409

Fig. 2: Location of three sites and our institute (Google map)

410

Fig. 3: Calorific Value of MSW collected from three different sites

411 412

List of Tables:

413

Table 1: Composition of MSW from Dhanbad by percentage weight (Mean ± standard deviation)

414

Table 2: Results of proximate analysis of different waste samples (organic fractions) from three

415

landfill sites

416

Table 3: Results of ultimate analysis of municipal solid waste (Mean ± Standard deviation)

417

Table 4: Methane generation from solid waste collected from three different sites

17

ACCEPTED MANUSCRIPT

Table 1: Composition of MSW from Dhanbad by percentage weight (Mean ± standard deviation)

Area

Organic %

Hard Plastics %

Metals %

Papers %

Soft plastics %

Glass %

Railway station, site 1 Memcomore, site 2 Memco more, site 3 Average

92.0 0.0

±

0.9 0.3

±

0.1 0.4

±

0.3 0.8

±

5.1 0.4

±

64.0 0.0

±

10.6 ± 0.6

0.5 0.9

±

0.7 0.9

±

69.1 0.0

±

11.5 ± 0.8

0.3 0.9

±

0.7 0.9

±

7.7

0.3

75

0.6

Other %

0.4 ± 0.2

Textiles & Leather % 0.9 ± 0.1

19.1 ± 0.5

0.3 ± 0.6

4.1 0.9

±

0.6 ± 0.8

14.9 ± 0.5

0.7 ± 1.1

2.3 0.8

±

0.5 ± 0.8

13

0.5

2.4

0.3 ± 0.7

0.5

ACCEPTED MANUSCRIPT

Table 2: Results of proximate analysis of different waste samples (organic fractions) from three landfill sites

Moisture content

Ash

Volatile matter

Fixed carbon

(wt % DB)

(wt % DB)

(wt % DB)

(wt % DB)

Railway station, site 1 25.49

24.71

45.28

4.53

Memco more, site 2

3.40

31.69

53.41

11.49

Memco more, site 3

2.96

28.92

56.22

11.89

Area

DB – Dry basis.

ACCEPTED MANUSCRIPT

Table 3: Results of ultimate analysis of municipal solid waste (Mean ± Standard deviation)

Area

N (%, DB)

C (%, DB)

H (%, DB)

S (%, DB)

O (%, DB)

Railway station, site 1

1.4 ± 0.1

27.1 ± 0.4

3.4 ± 0.3

0.3 ± 0.0

17.6 ± 0.0

Memco-more, site 2

1.1 ± 0.1

32.2 ± 0.0

3.8 ± 0.8

0.1 ± 0.0

27.7 ± 0.0

Memco-more, site 3

1.2 ± 0.0

34.6 ± 1.8

4.6 ± 0.1

0.2 ± 0.0

27.5 ± 0.0

Suthapanich W., 2014 [31]

0.92

47.94

6.9

0.16

26.77

Sethi et al., 2009 [32]

1.16

28.2

3.77

0.63

18.4

Chiang Mai University, 2012

0.58

55.35

8.13

0.43

18.19

[33] DB – Dry basis.

ACCEPTED MANUSCRIPT

Table 4: Methane generation from solid waste collected from three different sites

Concetration Area

(ppm methane/g waste)

Railway station (site 1)

140.53

Memco more (site 2)

18.18

Memco more (site 3)

20.28