Heat Generation and Accumulation in Municipal Solid Waste Landfills

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Heat Generation and Accumulation in Municipal Solid Waste Landfills Zisu Hao, Mei Sun, Joel Ducoste, Craig H. Benson, Scott Luettich, Marco J. Castaldi, and Morton A Barlaz Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b01844 • Publication Date (Web): 21 Sep 2017 Downloaded from http://pubs.acs.org on September 22, 2017

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Environmental Science & Technology

1

Heat Generation and Accumulation in Municipal Solid Waste Landfills

2 3

Zisu Hao a,*, Mei Sun b, Joel J. Ducoste a, Craig H. Benson c, Scott Luettich d, Marco J. Castaldi e , Morton A. Barlaz a

4 5 6 7

a

Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Raleigh, NC 27695 b

Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, Charlotte, NC 27223

8

c

School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22904

9

d

Geosyntec Consultants, 125 Community Dr., Augusta, ME 04330

10 11 12

e

Chemical Engineering Department, The City College of New York, City University of New York, New York, NY 10031 * Corresponding author. Phone: (919) 522-5571; email: [email protected]

13 14

ABSTRACT

15

There have been reports of North American landfills that are experiencing temperatures in

16

excess of 80 − 100°C. However, the processes causing elevated temperatures are not well

17

understood. The objectives of this study were to develop a model to describe the generation,

18

consumption and release of heat from landfills, to predict landfill temperatures, and to

19

understand the relative importance of factors that contribute to heat generation and accumulation.

20

Modeled heat sources include energy from aerobic and anaerobic biodegradation, anaerobic

21

metal corrosion, ash hydration and carbonation, and acid-base neutralization. Heat removal

22

processes include landfill gas convection, infiltration, leachate collection, and evaporation. The

23

landfill was treated as a perfectly mixed batch reactor. Model predictions indicate that both

24

anaerobic metal corrosion and ash hydration/carbonation contribute to landfill temperatures

25

above those estimated from biological reactions alone. Exothermic pyrolysis of refuse, which is

26

hypothesized to be initiated due to a local accumulation of heat, was modeled empirically to

27

illustrate its potential impact on heat generation. 1 ACS Paragon Plus Environment


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Keywords: landfills; heat generation; biodegradation; metal corrosion; ash hydration and

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carbonation

30

INTRODUCTION

31

Recently, there have been several reports of municipal solid waste (MSW) landfills that have

32

been experiencing temperatures in excess of 80 − 100°C.1–3 In some cases, these elevated

33

temperatures have resulted in damage to the landfill’s gas collection system, rapid settlement

34

with subsequent implications for the integrity of the landfill cover and slope stability, elevated

35

leachate volume and strength, reduced methane content that may impact landfill gas treatment

36

and energy generation processes, odorous gases, and/or challenges with regulatory compliance.1,4

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In cases where the elevated temperature extends to the bottom of the landfill, there may also be

38

impacts on the service life of the geomembrane liner. Consequently, elevated temperature

39

landfills (ETLFs) often require increased monitoring and management. While some ETLF

40

owners have acknowledged receipt of reactive wastes that are a source of excessive heat, other

41

owners are unaware of the burial of such wastes. Moreover, there is considerable uncertainty as

42

to the mechanisms controlling heat accumulation in landfills.

43

Hanson et al.5 reported on spatial and temporal variations in temperatures at landfills in

44

Alaska, British Columbia, Michigan, and New Mexico, and reported temperature ranges of 0.9 −

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33.0, 14.4 − 49.2, 14.8 − 55.6, and 20.5 − 33.6°C, respectively.

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temperatures fluctuated seasonally near the landfill edges and surface, but had a stable core.6,7 In

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contrast to these ranges, temperatures above 100°C have been reported at some ETLFs.1–3

Within these landfills,

48

A number of heat-generating reactions occur when MSW and other non-hazardous wastes are

49

buried in landfills. Reactions include both aerobic and anaerobic biodegradation,4,8 anaerobic

50

metal corrosion,2 and acid-base neutralization.9 Some landfills accept ash from the combustion

51

of coal, MSW, or other carbonaceous materials. Fly ash typically contains oxides (e.g., CaO),

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that undergo both hydration and carbonation reactions.10,11 While not documented in landfills,

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there are reports of thermochemical (pyrolytic) reactions in biomass.12,13 Pyrolytic reactions may

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occur in landfills at elevated but undefined temperatures. While these aforementioned reactions

55

generate heat in landfills, understanding the extent to which heat accumulates is critical.

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Several studies in which aspects of heat generation in landfills have been modeled are

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summarized in Table S1 of the Supporting Information (SI). Unfortunately, published models do 2 ACS Paragon Plus Environment

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not consider abiotic reactions including metal corrosion, acid-base neutralization, ash hydration

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and carbonation, or pyrolysis. In addition, many models incorporate complex descriptions of

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biological processes.14–17 While mechanistically accurate, parameterization in a landfill context

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is difficult and adds uncertainty. A second limitation of the aforementioned models is that they

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neglect other heat flows including the evaporation of water that saturates landfill gas, and

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moisture condensation.

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The objective of this study was to develop a mathematical model to predict temperature

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impacts associated with a number of biological and chemical reactions that may occur in MSW

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landfills. Modeled heat sources include aerobic and anaerobic biological reactions, anaerobic

67

metal corrosion, acid-base reactions, and ash hydration and carbonation. The model includes

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convective heat transport and removal mechanisms, including heat that is removed due to

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leachate collection, gas extraction, and evaporation. The governing equations for each heat

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source and sink are described next, followed by selected model simulations and sensitivity

71

analyses.

72 73

MODEL DEVELOPMENT

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A model was developed to describe a single addition of MSW to a landfill, thus representing

75

a relatively simple system for quantifying heat generation (Figure 1). The single addition of

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MSW was assumed to be a non-continuous and perfectly mixed closed unit where biotic and

77

abiotic reactions occur. Therefore, the landfill unit was modeled as a batch reactor. Based on

78

the developed model, the temperature and concentrations do not vary spatially within the landfill

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unit, which was assumed to be surrounded by other waste with liquid and gas flux into and out of

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the unit volume. Water that enters with the waste as well as that from infiltration is considered.

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Since the system is closed and based on the single addition of MSW, gas and water movement

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only influence the transport of heat from the system but do not change the physical properties of

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the MSW. For this system, the outlet gas and liquid phases have the same temperature as the

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landfill unit. The model was developed to maximize flexibility with respect to user-specified

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input parameters in recognition of the site-specific nature of landfills as well as parameter

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uncertainty.

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The model employs an energy balance, where heat accumulation is equal to the net heat influx and heat generation (Eqn. 1). ,

=

. ,! ,"

+

&!' ,&

−∆ + −∆

, − − #,! $#

+ ! ,! )%! −

&!' ,& ,(

%

(1)

89 90 91 92 93 94

where and , are the weighted average density and heat capacity of the buried waste (Eqns.

S1 and S2), and A are the volume and surface area of the landfill, is the generation rate of

the indicator species, ∆ is the heat (enthalpy change) of the chemical reactions, is the

biological O2 consumption rate, ∆ is the enthalpy change due to aerobic biodegradation, ,

is the heat capacity of species i, is the ambient temperature, T is the temperature in the

95

landfill, #,! is the density of saturated water vapor (Eqn. S3)18, $# is the latent heat of water

96

evaporation (−2400 -/ ! ), ! and ,! are the density and heat capacity of water, % is the

97

-.

flow rate of gaseous component i, and %! is the infiltration rate.

98

The left side of Eqn. 1 represents heat accumulation in a landfill unit volume. The first term

99

on the right side is the heat gain from chemical and anaerobic biodegradation reactions, the

100

second term is the heat gain from aerobic biodegradation, and the third, fourth, and fifth terms

101

are heat losses by convection, evaporation, and infiltration, respectively.

102 103

Convection and infiltration

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Convection includes gas and liquid transport through the landfill. The temperature of gases

105

and liquid entering the system are user specified. Heat removal from the transport of landfill gas,

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which is comprised of CH4, CO2, and N2, represents convection due to gas transfer.

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Determination of gas flow rates is described in the section on biodegradation reactions.

108

Liquid movement is based on infiltration, assuming that water percolates vertically through

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the landfill until it is removed in the leachate collection system. The model does not allow liquid

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accumulation. Infiltration is based on an assumed rate of leachate generation [volume/(area4 ACS Paragon Plus Environment

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day)] that was adopted from industry estimates of typical leachate generation (Table 1). The

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flow of gas and liquid in the landfill leads to convective heat transfer, which is proportional to

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the temperature difference between the landfill and inlet fluid temperatures. The effect of

114

infiltration on landfill temperature can therefore be considered as the convection of water. The

115

heat capacities of the wastes, liquids, and gases are presented in Tables 1 and S3.

116 117 118

Evaporation and condensation Phase changes of water will consume or release energy.

Inlet landfill gas (LFG) was

119

assumed to be saturated with moisture at the initial gas temperature and LFG was assumed to

120

remain saturated with increasing landfill temperatures. Thus, the evaporation of water from the

121

waste to saturate LFG represents an energy sink. In contrast, if the temperature of refuse

122

surrounding the landfill unit (Figure 1) was cooler than the refuse in the unit, then as hot LFG

123

flows to the surrounding waste, energy would be released due to condensation. In the current

124

batch reactor model formulation, variations in waste temperature and condensation could not be

125

considered.

126

To assess the importance of condensation, a separate analysis was conducted. Assuming

127

saturated LFG travels from BOX1 (hot) to BOX2 (cool), the temperature of BOX2 will increase

128

from its initial temperature ( ) to the equilibrium temperature (0 ) as a result of condensation

129

with subsequent energy release. The heat release (12 ) includes the phase change of hot LFG

130

leaving BOX1 at 3 and the decrease in water temperature from 3 to 0 (Eqn. 2).

131

12 = ! /,45 − ! /,4 678 [$# + ,! 3 − 0 ]

(2)

132 133

where ! /,45 and ! /,4 represent the density of steam at 3 and 0 , and 678 is the

134

volume of LFG released from BOX1. Similarly, the heat absorbed by solid waste and water in

135

BOX2 will result in a temperature change from to 0 (1; ) and can be written as:

136

1; = , ?0 − @ + >! ,! ?0 − @]

(3)

137



138

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where < is the volume ratio of BOX1 to BOX2, and ! are the density of waste and

139

liquid water, > is the moisture content in the waste, and is the initial temperature of BOX2.

140

At steady state, the heat released from hot LFG (12 ) is equal to the heat absorbed by BOX2 (1; ),

141

and the temperature (0 ) can be calculated.

142

The heat released by condensation consists of the phase change of water at T1 and water

143

cooling from 3 to 0 . The MSW in BOX2 is heated from to 0 . Since the moisture content

144

and density of saturated LFG are functions of temperature, the heat balance equation is coupled

145

with Eqn. 3 and solved simultaneously.

146 147

Aerobic Biodegradation

148

When waste is disposed in a landfill, some air is entrained at burial.19 This air was assumed

149

to be rapidly consumed and the resulting temperature increase is considered when specifying the

150

initial waste temperature. As freshly buried waste is by definition near the landfill surface, heat

151

loss will be high and the initial O2 content was assumed to be an insignificant source of energy.

152

Of more potential significance is the impact of air intrusion that may result from excess vacuum

153

applied to the landfill’s gas collection and control system (GCCS). Ideally, GCCS operation

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would not result in air intrusion; but the presence of N2 in LFG suggests that some air intrusion

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occurs. The available O2 was estimated from the LFG production rate (described below) and the

156

user-specified N2 concentration. Consequently, the volume of O2 intrusion was estimated as

157

21/78 times the volume of N2 based on the composition of air.

158

Several potential substrates may react with O2. For simplicity, two are considered in this

159

analysis, methane and cellulose (Eqns. 4 and 5). If the bacteria that convert CH4 to CO2 in the

160

presence of O2 (methanotrophs) survive without O2, then aerobic methane oxidation (Eqn. 4) is

161

likely to dominate O2 consumption. While the long-term survival of methanotrophs has not been

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tested in landfills, they have been reported to survive for ~170 years in deep, aged lake

163

sediments.20

164

A + 2B0 → B0 + 20 B ∆ = −27822

FG FH B0

(4)

165


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166 167


In contrast, if methanotrophs do not survive, then cellulose oxidation (Eqn. 5) will likely govern. The effect of both substrates (CH4 and cellulose) is considered in the Results.

168

I 3J BK + 6MB0 → 6MB0 + 5M0 B ∆ = −17360

FG FH PQRRSRTUQ

(5)

169 170

The biological O2 consumption rate was calculated using Eqn. 6.

171

=

21 % 78 (

(6)

172 173

where is the density of O2, and %( is the flow rate of N2. Since aerobic reactions are much

174

faster than anaerobic reactions, O2 was assumed to be consumed instantaneously after entering

175

the landfill.

176

The ∆H for the biological reactions in Eqns. 4 and 5 and below does not consider that some

177

energy associated with substrate conversion is used for cell synthesis. As such, the enthalpies

178

used in the model represent an upper limit on the amount of energy released.

179 180

Anaerobic Biodegradation

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Three biodegradable components of MSW (carbohydrates, protein, lipids) were considered as

182

substrates for CH4 generation. The stoichiometry and energetics for each substrate are presented

183

in Eqns. 7 – 9, with carbohydrates (cellulose, hemicellulose, starch) represented as cellulose.

184

I 3J BK + M0 B → 3MA + 3MB0 ∆ = −1672

FG FH PQRRSRTUQ

83I 0A BK V + 660 B → 75A + 53B0 + 8VW ∆ = −1295

23I W0 B0 + 140 B → 23A + 9B0 ∆ = −1826

FG FH YZT Q[M

FG FH R[Y[U

(7) (8) (9)

185



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The rate of heat release was calculated from the rate of CH4 generation as described here. In

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practice, US EPA’s LFG emissions model (LandGEM)21 is typically used to estimate CH4

188

generation and the default value for the CH4 generation rate constant (km) in non-arid regions is

189

0.04 yr−1.22 The LandGEM modeling approach was adopted here. Using km for MSW, de la

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Cruz and Barlaz23 described a method to estimate waste component specific decay rates (kmi) for

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the major biodegradable components of MSW (food waste, grass, leaves, various types of paper).

192

The CH4 generation rate was calculated for each waste component using Eqn. 10 and previously

193

reported values for L0 and kmi for each waste component (Table S4). The CH4 generation rate

194

was then used with the stoichiometric relationships defined in Eqns. 7 – 9 to estimate the

195

substrate biodegradation rate and subsequent rate of heat release. With the exception of food

196

waste, all biodegradation was attributed to carbohydrates.

197

carbohydrate, protein and lipid fractions as described in Table S4.

Food waste was divided into

198

%

J.d

^ _- = \&!' F] $J Q `a b,c 10

(10)

J eJ.J

199 200

where % is the CH4 generation rate in year n of biodegradable component i, \&!' is defined

201

in Eqn.11, kmi is the first-order decay rate constant of biodegradable component i, L0i is the CH4

202

generation potential of biodegradable component i, Mp is the waste mass placement in year p, q

203

is an intra-annual time increment used to calculate CH4 generation, and t is time. For the model

204

described here, only one mass of MSW was disposed at one time.

205

While methanogens have been reported to survive at temperatures as high as 89°C, this is not

206

typical.24 Thermophilic methanogens in anaerobic digesters and methanogenesis from acetate

207

are reported to have an upper temperate limit of ~75°C.25–28 To account for the influence of

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temperature on CH4 generation, an inhibition function [\&!' ] was developed (Eqn. 11).

209

\&!' = 4

I f4g f4I + I f4g + g

(11)

210


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211

where is temperature and f4 is a constant (37 ºC). The inhibition function is 1 at 37 ºC and

212

diminishes as the temperature increases (Figure S1).

213 214

Ash hydration and carbonation

215

Ash disposed in landfills typically contains several oxides/hydroxides including

216

CaO/Ca(OH)2, MgO/Mg(OH)2, Na2O/NaOH, K2O/KOH, and P2O5.10,29,30. The hydration of CaO

217

is illustrated in Eqn. 12 and hydration of other oxides is given in Eqns. S4 to S7.

218

hB + 0 B → hB0 ∆ = −1164

FG FH hB

(12)

219 220

Ultimately, the generated hydroxides are converted to carbonates by reacting with CO2, as

221

described by Eqn. 13 for Ca(OH)2 and Eqns. S8 to S10 for other hydroxides.11

222

hB0 + B0 → hBW + 0 B ∆ = −1718

FG FH hB0

(13)

223 224

Both water and CO2 were assumed to be present in excess and both hydration and carbonation

225

are explored in the results.

226

The presence of oxides versus hydroxides is specific to the waste source and the manner in

227

which the ash is handled prior to disposal. As such, the user can specify the content of the ash

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and the fraction that is present as oxides and hydroxides (default values are presented in Table

229

S5). The rates of ash hydration and carbonation were assumed to follow first-order consecutive

230

reaction models (Eqns. 14 and 15).

231

"ij = Pkl j F"ij

(14)

mn = P"ijkl j Fmn

(15)

232



233

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where "ij and mn are the rates of ash hydration and carbonation, Pkl j and P"ijkl j are

234

the concentration of oxides and hydroxides in the ash, and F"ij and Fmn are the reaction rate

235

constants for hydration and carbonation, respectively.

236 237

Anaerobic metal corrosion

238

Landfills receive Al and Fe in elemental form from both MSW and special wastes that may

239

include Al processing waste and auto shredder residue.2,31 Both Al and Fe have been reported to

240

undergo corrosion reactions (Eqns. 16 and 17). 3 FG )R + 30 B → )RBW + 0 ∆ = −15922 FH )R 2 oQ + B0 + 0 B → oQBW + 0 ∆ = −1268

FG FH oQ

(16) (17)

241

The rate and extent of corrosion will be governed by the surface area of the metal as well as

242

the presence of protective coatings or oxides, and environmental conditions. To model heat

243

generation from the corrosion of Al and Fe, corrosion was assumed to occur uniformly across the

244

metal surface at a rate specified in mm⋅yr−1. To account for pitting type corrosion, which would

245

not impact the entire surface, sensitivity analyses were conducted with reduced effective surface

246

areas.

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The content of Al and Fe in MSW was coupled with metal sheet thickness and metal density

248

to estimate the total surface area available for corrosion. Three categories of Al were considered

249

(containers, foil, other) to allow for three thicknesses and three alloys, while two categories with

250

two thicknesses were considered for Fe (containers, other). The characteristics of each metal are

251

presented in Table S6 and additional information on metal corrosion is presented in the SI. The reaction rates for anaerobic metal corrosion (Al and Fe) are described by Eqns. 18 and

252 253

19: q

2 = 2 p2 ) 2

(18)

q

7 = 7 p7 ) 7

(19)


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254 255 256


where 2 and 7 are the reaction rates of metal source i (i=Al or Fe containers, Al foil, and q

q

other Al or Fe in Table S6), 2 and 7 are the density of Al and Fe, p2 and p7 are the corrosion rates of metal alloy j, and )2 and ) 7 are the surface area of metal i.

257

Hydrogen is a product of metal corrosion and can be converted to CH4 by hydrogenotrophic

258

methanogens (Eqn. 20). Since CO2 is a major constituent in LFG, the H2 generated was assumed

259

to be consumed instantaneously at the rate at which it is generated subject to the temperature

260

inhibition defined in Eqn. 11.

261

40 + B0 → A + 20 B ∆ = −20625

FG FH 0

(20)

262 263

Neutralization (Acid-base reaction)

264

Carboxylic acids are anaerobic biodegradation intermediates. When the microbial activity

265

involved in waste decomposition is balanced, carboxylic acids do not accumulate and acid-base

266

reactions are of little energetic consequence. However, there are scenarios in which carboxylic

267

acids accumulate and the landfill pH may decrease to ~5. In this scenario, acidic leachate may

268

percolate through the landfill and be neutralized by hydroxide ions generated by ash hydration

269

and metal corrosion processes and/or the buffer capacity of the refuse. Acid-base neutralization

270

was represented in the model with the simplifying assumption that all carboxylic acids are

271

present as acetic acid (Eqn. 21). Neutralization was assumed to be instantaneous and the

272

concentration of acetic acid is user-specified. W BB + B _ → W BB_ + 0 B ∆ = −57

FG rTR

(21)

273 274

MODEL PARAMETERIZATION AND INPUT ASSUMPTIONS

275

The parameters required to describe the physical characteristics of the landfill and the waste

276

are presented in Table 1. The chemical composition of the MSW was estimated from the

277

composition of each waste component (Table S7). The biodegradable components in the waste

278

include carbohydrates (25.4%), protein (4.4%) and lipids (8.3%), and the complete chemical



279

composition is given in Table S8. The values in Tables 1 and S8 represent a base case and

280

illustrative sensitivity analyses are presented with the results.

281

RESULTS AND DISCUSSION

282

Relative contributions of various processes to heat accumulation and loss were evaluated

283

through a series of systematic simulations. The base case simulation uses parameters at the

284

default values (Tables 1 and S8). The first set of simulations is based on biological reactions

285

only, after which the contributions attributable to ash hydration and carbonation, metal corrosion,

286

acid-base neutralization, and condensation are considered.

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287 288

Biodegradation

289

Simulations of heat generation due to aerobic and anaerobic biodegradation of MSW are

290

presented in Figure 2. Simulations were conducted with and without consideration of heat loss

291

processes (evaporation, convection, cooling due to infiltration). Simulations without heat loss

292

represent an upper bound as some heat loss is expected in landfills due to gas and leachate

293

removal, and evaporation. The 2% N2 cases translates to the availability of ~0.5% O2.

294

In the base case, the assumed air intrusion results in a ~1°C increase relative to the

295

temperature resulting from anaerobic decomposition only. When gas collection and leachate

296

removal are the only heat removal processes, the model predicts a slight temperature decrease

297

relative to no heat loss. Similarly, the heat loss due to evaporation is relatively low because

298

temperature inhibition of biological gas production reduces evaporative heat loss. In the absence

299

of the temperature inhibition term (Eqn. 11), evaporative heat loss dominates (data not shown).

300

When infiltration is added as a heat sink, the temperature decrease between years 12 and 20

301

reflects heat loss associated with the infiltration of cooler water and leachate removal from the

302

system. The temperature increase after year 20 is due to the assumed placement of a final cover

303

with the subsequent cessation of infiltration and leachate removal, and the dynamic equilibrium

304

between heat generation from biodegradation and heat removal processes.

305

When the infiltration rate was increased by 50% relative to the base case, there is some

306

additional cooling and the effect is most pronounced between years 10 and 20 at which time

307

infiltration is constant but heat from biodegradation is decreasing. The case of evaporation plus

308

convection is also a case of no infiltration (e.g., arid conditions) and the maximum temperature 12 ACS Paragon Plus Environment

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difference between no infiltration and infiltration at 150% of the base case infiltration rate is

310

~8°C.

311

When the CH4 generation rate constant is doubled, the predicted temperature is most

312

sensitive to the rate about 5 years after waste burial at which time methane generation is not

313

completely inhibited due to high temperature (Eqn. 10). The temperature increase due to the

314

consumption of CH4 as opposed to cellulose as the biodegradable substrate under aerobic

315

conditions was less than 0.6°C and cellulose was adopted as the substrate for aerobic

316

biodegradation.

317 318

Ash hydration

319

Figure 3 displays the predicted temperature in a landfill that contains a mixture of MSW

320

(90%) and ash (10%). The presence of ash results in additional heat accumulation due to ash

321

hydration and carbonation.

322

temperature increase in year 10 for cases with and without heat loss.

323

carbonation results in increases of ~28°C relative to the base case in year 10 for cases without

324

and with heat loss. This trend is consistent with the greater enthalpy change associated with

325

carbonation relative to hydration and the temperature trends also reflect the slower rate of

326

carbonation relative to hydration. When the ash content of the buried waste is doubled, the year

327

10 temperature increases relative to the base case are 72 and 67°C for cases without and with

328

heat loss, respectively. In simulations of carbonation with heat loss, the temperature increase

329

after year 20 is due to the continued slow release of energy from carbonation in contrast to the

330

rapid release of heat in hydration simulations.

Considering ash hydration only, the model predicts a ~12°C Inclusion of ash

331

The temperature is sensitive to the rate of ash carbonation which is uncertain but likely

332

enhanced by typical LFG CO2 concentrations of ~50% (Figure S2). While not considered in

333

these simulations, the heat generation associated with ash hydration and carbonation may also

334

accelerate other reactions for which the reaction rate is temperature dependent.

335 336

Metal corrosion

337

Simulations of the impact of Al corrosion on temperature are presented in Figure 4. For the

338

temperature profiles without heat loss, the slope decreases at years 22 and 31 are due to the 13 ACS Paragon Plus Environment


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339

consumption of Al foil and Al containers, respectively. The predicted temperatures indicate that

340

Al corrosion may significantly impact landfill temperatures. For example, the year 10 increase

341

in predicted temperature is ~20°C relative to the base case for simulations with and without heat

342

loss, and a 100% corroded surface area (i.e., uniform corrosion). At the predicted temperatures,

343

biological methane production is inhibited and the H2 produced from Al corrosion will

344

accumulate. Infiltration is again the dominant heat loss mechanism though not apparent from the

345

temperature profiles.

346

To consider the occurrence of pitting as opposed to uniform corrosion, the affected surface

347

area was reduced, which results in a decrease in heat accumulation. When heat removal

348

processes are incorporated, temperatures are still elevated relative to the MSW only case. For

349

the case of 50% corroded surface area, the temperature increases 9°C compared to the MSW

350

only case at year 10.

351

The effect of a higher corrosion rate for the first 6 months is presented in Figure S3. The

352

complete consumption of Al foil occurs 5 years earlier than the case with a constant corrosion

353

rate, and the year 10 increase in predicted temperature is slightly higher than that predicted for a

354

uniform corrosion rate, which is due to the greater heat release in the first 6 months after burial.

355

In contrast to Al corrosion, which resulted in predicted year 10 temperatures of 19°C above

356

the base case with heat loss considered, the increase associated with Fe corrosion is less than 1°C

357

at year 10 (Figures 4 and S4). These results are consistent with the enthalpy data in Eqns. 16 and

358

17. However, the temperature impact of Fe is sensitive to corrosion rate (Figure S4).

359 360

Neutralization reaction

361

To evaluate the importance of acid-base neutralization, 35 g/L of acid was assumed to be

362

neutralized. The results are presented in Figure S5 and indicate that heat generation due to

363

neutralization is not important using the base case assumptions, as the temperature increased by

364

only 0.7°C in year 30.

365 366

Condensation


Page 15 of 32


367

Condensation reactions could not be evaluated in the model. Thus, separate calculations

368

were performed as described by Eqns. 2 and 3. There are a number of variables that affect the

369

impact of condensation including the temperature of the gas moving from BOX1 (hot) to BOX2

370

(cool), the simulation time, and the relative volumes of BOX1 and BOX2. In an actual landfill,

371

the hottest gas would interact with a directly adjacent small mass of refuse, which suggests that

372

the mass in BOX1 should be larger than that in BOX2.

373

The results show that the temperature in BOX2 increases with an increase in the temperature

374

of the gas in BOX1, simulation time, and the ratio of BOX1 to BOX2 (Table 2). These results

375

suggest that condensation of LFG can result in elevated temperatures when condensation impacts

376

a relatively small volume of refuse. Condensation may occur as LFG moves laterally and

377

represents a mechanism for the spread of heat in ETLFs.

378 379

Maximum Plausible Temperature

380

The maximum (year 30) temperatures associated with biological reactions are about 65 and

381

58°C, for cases without and with heat loss, respectively. In contrast, even when heat loss is

382

considered, the presence of 1.7% Al resulted in a predicted year 10 temperature of 77°C for a

383

case with 100% corroded area available. To develop a higher but plausible temperature, a

384

simulation was conducted with 80% MSW, 20% ash, waste decay rates that are double the

385

default values, and the base case Al, Fe, and carboxylic acid contents. The predicted year 10

386

temperatures are 151 and 162°C for cases with and without heat loss, respectively (Figure S6).

387

While temperatures up to ~140°C have been reported at ETLFs,1,3 most landfills that receive the

388

types of waste considered in the model simulations do not reach temperatures of even 77°C as

389

estimated for Al corrosion, suggesting that the model is overestimating temperatures in some

390

cases.

391

There are several potential explanations for the overestimate. Metal corrosion has the largest

392

contribution to heat accumulation but the concentration and corrosion rate applied in the

393

simulations are uncertain and some corrosion may have occurred prior to burial. Second, the

394

relative concentrations of oxides vs. hydroxides are uncertain as are the rates of hydration and

395

carbonation.



Page 16 of 32

396

The described model assumes a completely mixed system although landfills are

397

heterogeneous with variable reactant concentrations and reaction rates. Localized accumulations

398

of reactive materials (e.g., Al) may occur, resulting in areas where the temperature exceeds that

399

predicted in a batch reactor.

400

waste could be even more important considering that an alkaline waste (e.g., fly ash) will

401

accelerate the rate of anaerobic Al corrosion.

402

accumulation of heat, the potential for such an accumulation to initiate self-sustaining pyrolysis

403

is explored in the following section.

The potential significance of a local accumulation of a reactive

To explore the significance of a localized

404 405

INCORPORATION OF PYROLYSIS

406

To better understand the characteristics of pyrolysis in a landfill and its potential impact on

407

temperature, the pyrolysis process was incorporated into the model. Unfortunately, pyrolysis in

408

a landfill has not been quantified and the present implementation is exploratory. Pyrolysis of

409

lignocellulosic materials has been described as a first-order reaction39 (Eqn. 22).

410

ik = Pm Fik

(22)

411 412

where ik is the rate of the pyrolytic reaction, Pm is the cellulose concentration, and Fik is

413

the reaction rate constant.

414

Mok et al.40 and Antal and Gronli41 showed that cellulose pyrolysis consists of endothermic

415

and exothermic stages. In the endothermic stage, the combination of external heat and the

416

presence of volatiles are required to raise the temperature to initiate an exothermic stage. In the

417

exothermic stage, the pyrolytic reaction itself provides sufficient heat for the reaction to be self-

418

sustaining. The products of exothermic pyrolysis include char, tar, condensable volatile species,

419

and H2, CO, CO2, and H2O.

420

Three parameters were used to represent pyrolysis empirically: (1) initiation temperature

421

( ), (2) reaction rate constant ( ik , and (3) enthalpy (∆ik ). An initiation function is

422

proposed to describe exothermic pyrolysis initiation (Eqn. 23). Exothermic pyrolysis begins and

423

a heat generation rate calculated when the system temperature (T) exceeds . 16 ACS Paragon Plus Environment

Page 17 of 32


\ = 0.2√2tQZ\ uv

− √2

w + 2.5x

(23)

424 425

To incorporate pyrolysis into the model, an additional source term was added to the right side of

426

Eqn. 1 and is shown as the last term in Eqn. 24:

427 ,

=

, ,! ,"

+

&!' ,&

−∆

, − + −∆

− #,! $#

&!' ,& ,(

(24)

% + ! ,! )%! −

+ \ ik −∆ik 428 429

A range of enthalpy changes (∆ik ) have been reported for cellulose pyrolysis (−2100 to

430

2510 kJ·kg−1).42 As ∆ik for hemicellulose, starch, protein, lipids, and lignin have not been

431

published, cellulose was used as the representative substrate.

432

To simulate the potential impact of pyrolysis, initiation temperatures ( ) of 120 and 180°C

433

were assumed along with a ∆ik of −1000 kJ/kg cellulose and a reaction rate of 1 yr−1. All

434

biological and chemical processes were simulated using the default values in Tables 1 and S8.

435

The simulations presented in Figure 5 reflect the heat released by biodegradation until the

436

temperature exceeds the maximum temperature for anaerobic biodegradation, as well as heat

437

release due to Al and Fe corrosion, ash hydration and carbonation, and acid-base neutralization.

438

When the is 120°C, the landfill temperature is predicted to exceed the pyrolysis initiation

439

temperature in years 11 and 14 for the no heat loss and heat loss cases, respectively. Once

440

pyrolysis occurs, the model predicts a sharp temperature increase. Thereafter, the temperature

441

continues to increase even when heat loss is considered.

442

evaporative heat losses are low, as only gas generation from biological reactions was considered,

443

and biological reactions are inhibited. At a of 180°C, the system does not exceed the

444

initiation temperature, even for the case without heat removal. In ongoing experimental work,

445

reactors are being operated to characterize the initiation and energetics of MSW pyrolysis.

This is because convective and



446

Page 18 of 32

IMPLICATIONS AND FUTRUE WORK

447

The results highlight the importance of heat removal on landfill temperatures, as predicted

448

temperatures are considerably higher in the absence of convection and evaporation. While

449

neither metal corrosion nor ash hydration and carbonation in MSW landfills is fully understood,

450

the results show that these reactions have the potential to significantly increase landfill

451

temperature.

452

There is uncertainty in many of the default parameter values as they were adopted from

453

literature on systems other than landfills.

In addition to parameter uncertainty, the first-order

454

representation of ash hydration and carbonation has not been demonstrated in a landfill, further

455

emphasizing the need for process-related research applicable to landfills.

456

temperatures associated with metal corrosion are not realistic as some metal is routinely disposed

457

in landfills and ETLFs are not widespread.

458

hypothesized to be important in ETLFs, the model adopted in this study must be considered

459

illustrative until a better understanding of landfill pyrolysis is developed. A model that treats the

460

landfill as series of interconnected control volumes with varying waste properties allowed in

461

each control volume is under development to incorporate the heterogeneity of a landfill in which

462

reactive wastes and air intrusion may be localized.

The predicted

Similarly, while exothermic pyrolysis is

463


Page 19 of 32


464

SUPPORTING INFORMATION

465

Summary of previously published models, additional background on metal corrosion, additional

466

modeling parameters, data on waste composition, summary of model nomenclature, illustration

467

of the biological temperature inhibition function, simulations of Al and Fe corrosion and acid-

468

base neutralization, and additional sensitivity analysis.

469

NOTES

470

The authors declare no competing financial interest.

471 472

ACKNOWLEDGEMENTS

473

This research was supported by a grant from the Environmental Research and Education

474

Foundation.

475



REFERENCES

476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520

Page 20 of 32

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Luettich, S. M.; Yafrate, N. Measuring Temperatures in an Elevated Temperature Landfill. Geo-Chicago 2016, 162–176.

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Hanson, J. L.; Yesiller, N.; Oettle, N. K. Spatial and Temporal Temperature Distributions in Municipal Solid Waste Landfills. J. Environ. Eng. 2010, 136, 804–814.

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Hanson, J. L.; Yesiller, N.; Kendall, L. A. Integrated temperature and gas analysis at a municipal solid waste landfill. In Proceedings of the 16th International Conference on Soil Mechanics and Geotechnical Engineering, 2005; pp 2265–2268.

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Grillo, R. J. Energy Recycling-Landfill Waste Heat Generation and Recovery. Current Sustainable/Renewable Energy Reports 2014, 1, 150–156.

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Rees, J. F. Optimisation of Methane Production and Refuse Decomposition in Landfills by Temperature Control. J. Chem. Technol. Biotechnol. 1980, 30, 458–465.

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Speiser, C.; Baumann, T.; Niessner, R. Morphological and Chemical Characterization of Calcium-Hydrate Phases Formed in Alteration Processes of Deposited Municipal Solid Waste Incinerator Bottom Ash. Environ. Sci. Technol. 2000, 34, 5030–5037.

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Li, X.; Bertos, M. F.; Hills, C. D.; Carey, P. J.; Simon, S. Accelerated Carbonation of Municipal Solid Waste Incineration Fly Ashes. Waste Manage. 2007, 27, 1200–1206.

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Ciuta, S.; Patuzzi, F.; Baratieri, M.; Castaldi, M. J. Biomass Energy Behavior Study during Pyrolysis Process by Intraparticle Gas Sampling. J. Anal. Appl. Pyrol. 2014, 108, 316–322.

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Kwon, E. E.; Castaldi, M. J. Urban Energy Mining from Municipal Solid Waste (MSW) via the Enhanced Thermo-Chemical Process by Carbon Dioxide (CO2) as a Reaction 20 ACS Paragon Plus Environment

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Garg, A.; Achari, G. A Comprehensive Numerical Model Simulating Gas, Heat, and Moisture Transport in Sanitary Landfills and Methane Oxidation in Final Covers. Environ. Model. Assess. 2010, 15, 397–410.

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White, J.; Robinson, J.; Ren, Q. Modelling the Biochemical Degradation of Solid Waste in Landfills. Waste Manage. 2004, 24, 227–240.

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Wagner, W.; Pruß, A. The IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use. J. Phys. Chem. Ref. Data 2002, 31, 387–535.

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Rothfuss, F.; Bender, M.; Conrad, R. Survival and Activity of Bacteria in a Deep, Aged Lake Sediment (Lake Constance). Microbial Ecol. 1997, 33, 69–77.

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Page 24 of 32

620 621

622 623 624 625

TOC art


Page 25 of 32


626 627 628 629

Figure 1. Schematic of the Landfill Batch Reactor Model. (Q is flow rate, T is temperature, and C is concentration)



630 631 632 633 634 635 636 637

Page 26 of 32

Figure 2. Heat accumulation associated with MSW biodegradation in the presence and absence of O2. Solid lines represent cases without heat removal. Dashed lines consider heat removal process (Conv = convection, Evap = evaporation, heat loss = evaporation + convection + infiltration), 2x DecayRate = decay rate (km) doubled for each biodegradable component listed in Table S4.


Page 27 of 32


638 639 640 641 642 643 644

Figure 3. Impact of ash hydration and carbonation on landfill temperature. The solid and dashed black lines represent the base cases given in Figure 2. The blue and green lines represent the presence of 10% ash (Table S5) and 90% MSW. The ashhyd line considers hydration only. The ashcrb lines consider hydration and carbonation as hydration is an essential reaction for carbonation at landfill temperatures. The plot simulates the sensitivity to 20% ash. The ash hydration and carbonation rates are 0.5 and 0.1yr−1, respectively.

645



Page 28 of 32

646 647 648 649 650

Figure 4. Impacts of Al corrosion on landfill temperature using the corrosion rates given in Table 1. The solid and dashed black lines represent the base cases given in Figure 2. The lines for 50% and 25% simulate partial corrosion across the surface area.


Page 29 of 32


651 652 653 654

Figure 5. Simulation results with pyrolysis incorporated into the batch reactor model. The solid and dashed black lines represent the base case given in Figure 2. The red and blue lines consider different initiation temperatures for pyrolysis with (dashed) and without (solid) heat loss.

655



656

Page 30 of 32

Table 1. Default model parameters used to describe landfill characteristics Parameter Unit Value Comments and citations Initial mass Mg 544 Daily waste mass for medium sized landfill (20% moisture) Depth

m

30

Assumption

Infiltration rate

m3·m−2·yr−1

0.137

Value used in industry for landfills in regions receiving ~100 cm rain·yr−1

Infiltration time

yr

20

Assumed time prior to placement of low conductivity final cover

Initial temperature

°C

40

Assumed in consideration of some selfheating associated with initial aerobic decomposition

20

Assumed environmental temperature

890

Approximate industry average

1281

Approximate industry average

1.32

Estimated as the sum of the heat capacity of individual components multiplied by their fractions.32 Default waste composition data given in Tables S4 and S7 and heat capacities given in Table S4.

Ambient temperature °C Waste density Ash density

kg·m

−3

kg·m

−3 −1

−1

Waste heat capacity

kJ·kg ·°C

Ash heat capacity

kJ·kg−1·°C−1

0.8

Liang et al.33

CH4 generation rate constant (km)

yr−1

component specific

Data for km given in Table S4.

CH4 Production potential (L0)

m3 CH4·Mg−1 component waste specific

Data for L0 given in Table S4.

N2

%

2

Used to quantify air intrusion

−1

Corrosion rate of Al (alloy 3004)

mm·yr

0.003

Eashwar et al.34

Corrosion rate of Al (alloy 1100)

mm·yr−1

2.54×10−4

Ezuber et al.35

Corrosion rate of coated Al (alloy 3004)

mm·yr−1

5.17×10−4

Shabani-Nooshabadi et al.36

Corrosion rate of steel

mm·yr−1

5×10−4

Smart et al.37

Corrosion rate of coated steel

mm·yr−1

2.54×10−4

Smith et al.38 30

ACS Paragon Plus Environment

Page 31 of 32


Rate of ash hydration

yr−1

0.5

Assumption

Rate of ash carbonation

yr−1

0.1

Assumed rate is 20% of hydration rate based on literature from other environments.30

Acetic acid concentration

g·L−1

35

Assumption

657 658



659

Table 2. Impact of gas condensation on waste temperaturea Temp of gas flowing from BOX1 T1(°C)

Simulation Time (yr)

The volume ratio of BOX1 to BOX2 (ω)

Temp of waste in Box2 after equilibration T2 (°C)a

70

0.1 0.1 1 1 0.1 0.1 1 1

1 10 1 10 1 10 1 10

41 44 44 60 41 49 49 75

85

660

Page 32 of 32

a. The initial temperature of BOX2 was assumed to be 40°C.


Heat Generation and Accumulation in Municipal Solid Waste Landfills

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