Comparison of Overall Resource Consumption of Biosolids

Page 1 of 33

Environmental Science & Technology

1

Comparison of Overall Resource Consumption of

2

Biosolids Management System Processes Using

3

Exergetic Life Cycle Assessment

4

Sevda Alanya¥, Jo Dewulf § and Metin Duran*¥

5 6 7

¥

Civil and Environmental Engineering Department, Villanova University, 19085, Villanova, PA, United States § Research Group ENVOC, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium

8 9 10

Keywords: (Exergetic) Life Cycle Assessment, resource footprint, CEENE, biosolids management

11 12 13 14 15

*

Corresponding author information: Metin Duran; E-mail: [email protected]; Tel.: (610) 519-4963; Fax: (610) 519 6754; Address: Civil and Environmental Engineering Department, 800 Lancaster Ave., Villanova, PA 19085

16

ABSTRACT

17

This study focused on the evaluation of biosolids management systems (BMS) from a natural

18

resource consumption point of view. Additionally, the environmental impact of the facilities was

19

benchmarked using Life Cycle Assessment (LCA) to provide a comprehensive assessment. This

20

is the first study to apply a Cumulative Exergy Extraction from the Natural Environment

21

(CEENE) method for an in-depth resource use assessment of BMS where two full-scale BMS

1 Environment ACS Paragon Plus


22

and seven system variations were analyzed. CEENE allows better system evaluation and

23

understanding of how much benefit is achievable from the products generated by BMS, which

24

have valorization potential. LCA results showed that environmental burden is mostly from the

25

intense electricity consumption. The CEENE analysis further revealed that the environmental

26

burden is due to the high consumption of fossil and nuclear-based natural resources. Using

27

Cumulative Degree of Perfection (CDP), higher resource-use efficiency, 53%, was observed in

28

the PTA-2 where alkaline stabilization rather than anaerobic digestion is employed. On the other

29

hand, an anaerobic digestion process is favorable over alkaline stabilization, with 35% lower

30

overall natural resource use. The most significant reduction of the resource footprint occurred

31

when the output biogas was valorized in a combined heat and power (CHP) system.

32 33

INTRODUCTION

34

Sludge is an inevitable byproduct of wastewater treatment plants (WWTPs) and the energy

35

use and fees related to sludge handling, treatment, and disposal generally constitute a

36

considerable part, 25-50%, of overall operating costs.1 This, along with the growing scarcity of

37

natural resources on a global scale, is the driving force toward sustainable biosolids management

38

systems (BMS). Sewage sludge is generated as a byproduct at WWTPs and it needs to be

39

processed before being disposed or beneficially used. The series of processes, BMSs, are used in

40

order to decrease the water content and breakdown the microorganisms to reduce the pathogen

41

levels, known as stabilization. Biosolids are generated in large quantities and it is a waste stream

42

that has significant potential for being beneficially used. It can be considered as a renewable

43

energy source due to its energy content, or as fertilizer due to its nitrogen, phosphorus, and

44

potassium content. The term ‘biosolids’ was first defined by the Water Environment Federation


Page 2 of 33

Page 3 of 33


45

(WEF) and used to denote treated sewage sludge that can be beneficially used.2 Within the

46

context of this study ‘biosolids’ refers to the treated end product of BMS, while the term ‘sludge’

47

is used to designate the solids input to and processed by BMS.

48

Decisions on end use or disposal of municipal biosolids have traditionally been based on

49

cost, environmental regulations, and public acceptance considerations. However, comprehensive

50

systems analysis is necessary for better identification and quantification of inefficiencies and

51

resource use, in order to develop process alternatives and take advantage of the valorization

52

potential of biosolids.

53

Most traditional quantitative tools used to analyze the performance of BMS are plant level

54

energy consumption/efficiency analysis and LCA. Although conventional energy analysis is

55

commonly used to identify energy utilization and enables estimation of energy use and heat

56

losses, it does not provide information on the quality of energy used and the irreversibility in a

57

system. Exergy analysis provides more relevant data than energy analysis regarding the resource

58

conservation in a system since exergy measures the true value of energy in any real system

59

where some portion of potential work is lost as a result of irreversibility.3 Additionally, the non-

60

fuel resource consumption cannot be quantified in energy analysis while exergy based analysis

61

can quantify energy and non-energy flows of a system using a common unit.

62

LCA has been widely used for the sustainability assessment of WWTP systems.4-6 Most of

63

the studies have focused on energy consumption and global warming (GW) impact categories. 7-10

64

There are also several studies focusing on the sludge treatment and end-use options.7,8,11

65

However, LCA methods mainly focus on the resulting impact rather than the resource

66

consumption and use efficiency. The impact calculation associated with the resource



67

consumption is mainly based on scarcity, depletion rate or economic value, not on the actual

68

consumption rate.

69

On the other hand, exergy-based resource use assessment accounts for all resources based on

70

their exergy content. Exergetic Life Cycle Assessment (ELCA) is the use of exergy as a metric in

71

LCA, and it quantifies the cumulative exergy use resulting from the consumption of natural

72

resources through the life cycle of a product or service. There is an emphasis on waste to

73

resource recovery and waste to energy approach where this can be properly addressed by using

74

exergetic LCA methodology for biosolids that is a waste with high energy and resource content.

75

The first use of the exergy concept at a life cycle level rather than a single process level was

76

suggested by Szargut and Morris who proposed the Cumulative Exergy Consumption (CExC)

77

approach.12 CExC is employed to quantify the total exergy of all natural resources consumed in

78

the lifetime of a product. The work by Bösch et al.13 expanded the application by integrating

79

exergy consumption into LCA as an operational LCIA method called Cumulative Exergy

80

Demand (CExD), by creating characterization factors (CF) for ecoinvent elementary flows.14

81

This methodology is further improved by Dewulf et al. by identifying and complementing the

82

shortcomings of previous approaches.15 The developed methodology is titled Cumulative Exergy

83

Extraction from the Natural Environment (CEENE). Alvarenga et al. further improved the land

84

occupation category by developing a new framework for taking both land occupation and

85

biomass content into account. 16 Taelman et al. broadened the scope of the method by developing

86

exergy based characterization factors for accounting land occupation in marine environments.17

87

Liao et al. evaluated several resource indicators and recommended CEENE as the most

88

appropriate thermodynamics-based life cycle impact assessment method for resource use

89

accounting.18 Compared to the previously developed methods, CEENE method covers a broader


Page 4 of 33

Page 5 of 33


90

range of resource flows and includes up-to-date thermodynamic data for exergetic values of

91

these resource flows. It also takes into account the land occupation as a resource category, which

92

was not considered by previous methods. CEENE offers a comprehensive view of the removal

93

of resources from nature with integrated resource categories. That allows evaluating the

94

performance at life cycle level and enables identification of key areas for resource efficiency

95

improvements. Unlike LCA, which uses weighting to achieve a single score, the use of exergy-

96

based units is unique because exergy values can be calculated for all resources with known

97

composition. As such, all of the resources were accounted for in exergy-based assessments.

98

A number of previous studies have applied ELCA for environmental assessment and

99

comparison of systems, including application to the construction sector, to evaluate resource

100

depletion19 and resource use efficiency.20 Another application is in energy production systems,

101

where it is used to quantify exergy consumption of biodiesel from used cooking oil21 and to

102

identify lifetime irreversibilities and exergy efficiency of hydrogen production process.22 One

103

recent study, Dong et al.23, investigated four commonly used sewage sludge treatment systems in

104

China, including composting, co-combustion in a power plant, thermal drying-incineration, and

105

cement manufacturing using the CExC method proposed by Szargut et al.24 The results of the

106

study showed that the resource conversion efficiency–the ratio of the exergy content of useful

107

products to the overall exergy input–is higher when thermal processes such as combustion and

108

incineration are used. The authors, however, excluded the burden resulting from the treatment of

109

the liquor generated at the thickening and dewatering processes in the study, which may have a

110

significant influence on the overall results, considering its extra burden to WWTP. In addition,

111

the CExC method is not linked to the Ecoinvent database; therefore, the data is not representative



112

when country-specific data and the technology are considered. In addition, the method is based

113

on outdated thermodynamic data and excludes land occupation as a resource category.

114

Objectives and Contribution. This study focuses on determining the optimal process train

115

alternatives for biosolids management focusing on resource consumption and resource use

116

efficiency, which would provide the greatest environmental benefit, in order to effectively

117

valorize BMS products. The goal was to perform the first application and illustration of CEENE

118

method that effectively uses exergetic LCA method for comprehensive and complete assessment

119

in the context of BMS taking into account the impact of resource input. CEENE is a unique

120

method in that it evaluates efficiencies of resource consumption while quantifying resource

121

demand. The resource footprints of two most commonly used BMS in the United States of

122

America (USA) were evaluated in this study. Compared to previous work on the evaluation of

123

BMS, our study evaluates BMS from a resource point of view and couples it with traditional

124

LCA for complete assessment while taking into account the impact of emissions, rather than

125

focusing solely on the resulting impact of these systems. This work forms a basis for future

126

studies on the integration of this exergy-based analysis tool for evaluating alternative system

127

configurations in biosolids management, and it may lead to better decision making and

128

management practices.

129 130

MATERIALS AND METHODS

131

This study evaluates two functionally compatible BMS with different process trains, by

132

making use of the LCA tool and CEENE for a comprehensive environmental assessment

133

focusing on not only the environmental impact but also on resource use. The method evaluates


Page 6 of 33

Page 7 of 33


134

the resources extracted from the ecosystem as the amount of exergy taken from the natural

135

environment. This is accomplished by setting the exergy values for each resource flow using

136

184 reference flows (as they are represented in the Ecoinvent database version 1.2). Each

137

reference flow is grouped under one of eight main resource use categories; fossil fuels, metal

138

ores, nuclear energy, land occupation, renewable energy flows (wind, hydropower, solar),

139

minerals and mineral aggregates, atmospheric resources and water resources allowing the

140

calculation of the overall exergy demand (see the Supporting Information (SI) for additional

141

information for CEENE calculations). LCA guidelines–ISO14040 and ISO1404425-26– provided

142

guidance in conducting this study and were generally followed using the SimaPro 7.3 software

143

for the analyses.

144

Scope Definition. The two facilities investigated were named Process Train Alternative

145

(PTA) 1 and 2. The scope of the life cycle level analysis includes the unit processes of the BMS

146

treating primary sludge (PS) from primary sedimentation tank and waste activated sludge (WAS)

147

from the secondary sedimentation tank of a municipal wastewater treatment plant and application

148

of biosolids to farmland. For the product systems under investigation, no consideration was

149

given to the environmental impact resulting from the construction phase and the upstream

150

infrastructure and processes (e.g. sanitary system, pumping stations, and the operation of the

151

wastewater treatment plant). In previous studies, the environmental impact resulting from

152

operation of the facility showed to be significantly higher when compared to the construction

153

phase; the construction phase had a negligible environmental burden within the life cycle of the

154

plant.8,10,27,28 Therefore, infrastructure, manufacturing and maintenance of equipment used in the

155

product system were left outside the system boundaries due to their negligible impact. The



156

functional unit (FU) in this study is defined as 1 tonne of sewage sludge to be treated in dry basis

157

(1 tonne Dry Solids or t.DS).

158

In addition to two full-scale facility comparisons, seven system configurations were analyzed

159

in order to evaluate the environmental impact of process variation. Landfill and land application

160

options for biosolids end-use and no utilization, boiler and CHP options for the use of biogas

161

produced were included as different scenarios (see Figures S1 and S2 of SI for scenario

162

flowcharts).

163

The life cycle level system boundaries for each of the two full-scale BMSs, PTA-1 and PTA-

164

2, are depicted in Figure 1a and 1b, respectively. System boundary is presented at three levels, as

165

developed by Dewulf et al.; α (process level), β (plant level) and ɣ (industrial level). The α-level

166

system boundary is at the process level including the core individual processes in a plant.29 The

167

plant level (β) is the gate-to-gate approach and covers the entire plant including all unit processes

168

and supporting processes. The system boundary at industrial level (ɣ) is the life cycle approach

169

and considers all the manufacturing processes of material and energy inputs to the system

170

studied.


Page 8 of 33

Page 9 of 33

171 172 173


Figure 1. Three levels of system boundaries of the (a) PTA-1 and (b) PTA-2. (α-system boundary: process level; β- system boundary: gate-to-gate level; γ- system boundary: cradle-tograve level.)



Page 10 of 33

174 175

Systems Investigated. Two full-scale sludge stabilization processes considered in this study

176

are anaerobic digestion (AD) and alkaline stabilization (AS), the most widely used stabilization

177

processes in the USA.30 The sub-units of the full-scale existing BMS investigated are provided in

178

detail in Figure 2. Both facilities are located in the USA and both receive WAS and PS from

179

municipal wastewater treatment plants. Both facilities produce biosolids as the only product of

180

the system that is used as fertilizer on farmland. The centrate generated at dewatering and

181

thickening processes is returned to the head of the WWTP to be treated at both facilities.

182

Anaerobic digesters (AD) at PTA-1 are operated at about 37 °C, in the mesophilic range.

183

Currently, at PTA-1 the biogas produced is burned in boilers for onsite heating and any excess

184

biogas is flared by torch. In PTA-1, energy consumption occurs in the form of electricity during

185

thickening, centrifugation, pumping, and mixing of polymer. Heat consumption occurs in sludge

186

heating during anaerobic digestion process, which is supplied by the heat generated from biogas

187

combustion. No additional fuel is required for digester heating.

188

At PTA-2 dewatered sludge is stabilized via alkaline treatment by raising the pH of the

189

system above 12 through quicklime (CaO) addition, at an average dosage of 130 kg CaO per

190

tonne of dry solids. Stabilized biosolids are loaded to trucks and transferred to farmland

191

approximately 96 km away from the treatment plant.


Page 11 of 33


192 193 194 195

Figure 2. Flowchart of Biosolids Management Systems Investigated: PTA-1 and PTA-2 (Abbreviations: PS: Primary Sludge, WAS: Waste Activated Sludge, WTP: Wastewater Treatment Plant)

196 197

Inventory Analysis. In the second phase of LCA analysis, all relevant quantitative data and

198

input-output flows associated with the unit processes included in the system boundaries of PTA-

199

1 and PTA-2 are collected. The types of flows relevant to this study include input of resources

200

from nature, products from the technosphere, and the land while the outputs include the product

201

and waste in the form of air emissions, wastewater, and soil contaminants. Material and energy

202

flows of the BMS (foreground data) are based on the design specifics and operational data for



203

core processes and the raw data on daily operation of the plants in year 2011, provided by the

204

facilities. The background data of processes, such as supply of electricity, manufacturing of the

205

chemicals, transport and disposal of centrate to WWTP, came from Ecoinvent v2.2, US-EI 2.2

206

databases, which were used as a secondary data source.14,31 US-EI 2.2 database is based on

207

Ecoinvent processes but modified to be compatible with USA circumstances. The environmental

208

burden resulting from transportation of chemicals and materials from manufacturers to treatment

209

plant and from transportation of biosolids to the farmland and landfill are also included.

210

According to the information obtained from the plant operators, 40-tonne trucks are used to

211

transport the biosolids produced from the WWTP to farmland roughly 96 km away from the

212

plant. The acrylonitrile process from the Ecoinvent database is used as the most representative

213

process for polymer production.5,32

Page 12 of 33

214

Air emissions from biogas combustion are calculated according to stoichiometric

215

considerations, mass balance, and emission factors provided in the literature.33,34 CO2 emissions

216

from combustion of biogas generated in the AD process is considered biogenic, in line with

217

Intergovernmental Panel on Climate Change (IPCC) approach. These emissions are reported in

218

analysis but do not contribute to climate change.35,36 The combustion system efficiency for

219

biogas combustion is assumed to be 99%, where one per cent of the methane (CH4) is without

220

being subject to any change, as a result of incomplete combustion.27,37 The methane released to

221

atmosphere is accounted for in the impact assessment as it contributes to climate change impact

222

category. The nitrogen-based emissions, NO2, NH3, and N2O were calculated using the emission

223

factors provided by Doka.38 About 98% of nitrogen (N) in biogas is released as N2 after

224

incineration and the total amount of N2 in the exhaust gas is equal to the N2 coming from biogas


Page 13 of 33


225

plus the air used in combustion where NO2, NH3, and N2O factors are adopted as 0.668, 0.074

226

and 0.049, respectively.38

227

Quantification of the environmental impact of heavy metals (HM) discharged to soil includes

228

high uncertainty due to the unknowns associated with the factors that affect the behavior of HM

229

in soil after land application.5,11 In addition, high uncertainties and drawbacks are present in the

230

impact assessment models, particularly in the models used to calculate the toxicity impact

231

category relevant to HM emissions.39 The recommended method, USEtox, was used in this study

232

for toxicity assessment.40,41 USEtox model has been set up to model a global default continent,

233

which increases the uncertainty when spatial differentiation is considered. Despite the

234

uncertainties in quantification, biosolids generated in both facilities is used as fertilizer and it is a

235

source of metal input to the soil. Therefore, its potential human toxicity and ecotoxicity along

236

with its environmental burden are highly relevant to this study. The toxicity impact methods

237

consider the emissions of toxic substances to air, water and soil. Terrestrial Ecotoxicity refers to

238

impacts of toxic substances on terrestrial ecosystems. In addition to ecotoxicity impact category,

239

the terrestrial ecotoxicity sub-category is especially included in order to provide more specific

240

consideration on the impact of adding heavy metal to agricultural soil through land application of

241

biosolids on terrestrial environment. Therefore, metal input to the soil and relevant toxicity

242

impact categories were considered using the best available method, USEtox. Potential impacts

243

of micropollutants that result from land application of biosolids are not included in this study due

244

to high uncertainty associated with characterization factor and limited data availability.41,42

245

At the time of the study, the end use of biosolids generated at PTA-1 and PTA-2 was land

246

application (LA) of the biosolids to farmland to be used as fertilizer. Although this is still the

247

case for PTA-2, PTA-1 has since shifted to producing pellets from biosolids for fertilizer and



Page 14 of 33

248

bio-fuel production. Nevertheless, all biosolids from both facilities were assumed to be land

249

applied. Therefore the amount and type of synthetic fertilizer that can be substituted based on

250

their nutrient content–nitrogen (N) and phosphorous (P)–were calculated and accounted for.

251

There are a variety of synthetic fertilizers available in the market, indicating the need to consider

252

local trends in terms of the specific consumption. In this case, ‘local trends’ means the USA

253

trends. The most recent USA-specific fertilizer consumption data provided by the United States

254

Department of Agriculture (USDA) in 2010 was used.42 Not all nutrients in biosolids are

255

available to plants. Therefore, the amount of plant-available nutrients in the substitution

256

calculations was adopted from relevant literature.43,44 Background data regarding the fertilizer

257

production comes from Ecoinvent database (Ecoinvent data v2.2). In addition, the amount of

258

Agricultural lime (Aglime) offset by using lime-treated biosolids at PTA-2 was therefore

259

accounted for in the analyses. Aglime is used in farming to reduce the acidity of the soil and it is

260

essential for the soil fertility.45

261

Soil amendments are considered as potential carbon sequestration method, as recommended

262

by IPCC.37,46 Since biosolids application increases soil carbon, the stable portion of organic

263

carbon–the humic matter–can be considered as carbon credit.11,47 Carbon sequestration due to the

264

land application of biosolids is accounted for and was quantified using the methodology

265

developed by Hermann et al.,47 based on calculating the respective share of carbon that

266

contributes to humus formation. Biogenic emissions resulting from biogas combustion is a part

267

of short carbon cycle. On the other hand, organic carbon sequestration has a relatively longer

268

turnover time thus resulting in retardation of emission cycle and it is valuable for decreasing the

269

concentration in the atmosphere. Alternative scenarios considered for PTA-1 and PTA-2 evaluate

270

different uses of the biogas produced; i.e., flaring, boiler for heat generation or a CHP system for


Page 15 of 33


271

heat and electricity production, and biosolids disposal/end use; i.e. land application and landfill

272

disposal. In the case of CHP, the heat produced is used for digesters, hot water, and heating the

273

buildings–a substitute for natural gas. The electricity generated is a substitute for electricity

274

coming from the grid. In addition, land application and landfill options are considered as final

275

fate of the biosolids produced. The inventory results for the PTA-1, PTA-2 and seven scenarios

276

are provided in the SI, Tables S2-S4.

277

Impact Assessment. As mentioned earlier, the impact assessment method used in this study,

278

CEENE, allows for the identification of the resource footprint of a system by evaluating the

279

necessary exergy input to the system in order to obtain the desired final product. In the case of

280

the two BMS investigated, biosolids are the final product. Resource flows into the biosolids

281

production are grouped under one of eight main resource use categories: fossil fuels, metal ores,

282

nuclear energy, land occupation, renewable energy (wind, hydropower, solar), minerals and

283

mineral aggregates, atmospheric and water resources.

284

The overall system efficiency of ELCA can be expressed by Cumulative Degree of

285

Perfection (CDP) as suggested by Szargut and Morris.12 CDP is the efficiency at life cycle level

286

and it is defined as the ratio of exergy contained in the product or service over the total amount

287

of exergy of the system inputs required to obtain the desired product. CDP is used to quantify the

288

efficiency at life cycle level (see the SI for the calculations).

289

The impact assessment is performed for both the midpoint and endpoint levels to provide a

290

comprehensive evaluation and comparison of facilities. The midpoint level impact assessment

291

methods for the relevant impact categories are selected according to the recommendations of the

292

ILCD handbook and previous LCA studies focusing on sludge treatment.5,9,11,40,48 The selected



Page 16 of 33

293

impact categories, along with the impact methods, are presented in Table 1. Among the available

294

methods for the LCIA at endpoint level, ReCiPe Endpoint hierarchical (H) method49 allowed us

295

compare PTA-1 and PTA-2 using a single unit (Ecopoints, Pt), and it was used as LCIA method

296

for the endpoint analysis.

297 298

299

Table 1. Midpoint Impact Assessment Categories and Methods Impact category

Abv.

Unit

Human Toxicity

HT

CTU*h

USEtox

Ecotoxicity

ET

CTUe

USEtox

Terrestrial Ecotoxicity

TET

kg 1,4-DB eq±

ReCiPe Midpoint

Global Warming Potential

GWP

kg CO2 eq

IPCC 2007 (100a)

Abiotic Depletion Potential

ADP

kg Sb eq

CMLϯ 2002

Cumulative Energy Demand

CED

MJ

CED

Acidification (terrestrial)

TA

kg SO2 eq

ReCiPe Midpoint

Eutrophication (freshwater)

FE

kg P eq

ReCiPe Midpoint

Eutrophication (marine)

ME

kg N eq

ReCiPe Midpoint

* comparative toxic units;

±

Midpoint Method

ϯ

1,4 dichlorobenzene; Center of Environmental Science (CML) of Leiden University

300 301

Sensitivity Analysis. A sensitivity analysis was performed to determine how sensitive the

302

results are to certain changes in parameters used; i.e. transportation distance, quicklime dosing,

303

polymer dosing and electricity consumption, as well as to validate and check the reliability of the

304

CEENE and LCA results. In addition, the sensitivity of the electricity consumption is


Page 17 of 33


305

investigated based on the different production mixes used in four countries. The details of

306

assumptions and calculations are provided in SI, Table S10-11.

307

RESULTS AND DISCUSSION

308

Total Resource Consumption. The CEENE analysis results for seven categories (with units

309

of 1 tonne of DS to be treated) at PTA-1 and PTA-2 facilities are presented in Figure 3a. The

310

total resource extracted from the natural environment for the PTA-1 operation is 1,333 MJex

311

higher than PTA-2, which is roughly equivalent of 1,236 cubic feet (35 m3) of natural gas (at 1

312

atmosphere and 15 oC) per tonne of dry solids treated.50 In terms of resource consumption, the

313

PTA-2 facility is more favorable than the PTA-1, with a 22% lower exergy input required to

314

process one tonne of DS input. In both facilities, the fossil fuel category has the largest share,

315

above 50%, followed by nuclear energy. When non-energy resources are considered, PTA-1 has

316

a higher impact in terms of land occupation and water resource categories. The resource footprint

317

in terms of mineral and mineral aggregates and metal ores resources is negligible (less than 1%)

318

compared to other categories at both facilities. The resulting data illustrating the CEENE values

319

over eight resource categories can be found in SI.



a)

Page 18 of 33

7,000

CEENE (MJex/tonne dry solids treated)

6,000 5,000 4,000 PTA-1 3,000

PTA-2

2,000 1,000 0 Total

Renewable

Fossil

Nuclear

Metal

Minerals

Water

-1,000

Land occupation

5,000

b)

3,000

Land occupation

2,000

Water

1,000

Minerals Metal

0

Nuclear

Ut i li

ti e

s Tr an sp or tat io n

Renewable LA

-2,000

AD

Fossil CD

-1,000

DA F

CEENE (MJex/tonne DS treated)

4,000

4,000

c)

CEENE (MJex/tonne DS treated)

3,000

Land occupation Water Minerals Metal Nuclear Fossil Renewable

2,000 1,000 0 -1,000

321 322 323 324 325

po rt ati on

Ut i li ti e s

LA

AS

Tr an s

320

CD

GT

-2,000

Figure 3. The resource footprint of PTA-1 and PTA-2 for 1 tonne of DS to be treated (FU): (a) Distribution of resource extracted from natural environment at PTA-1 and PTA-2 facilities (b, c) Comparison of process contribution to overall resource extraction from natural environment: CEENE and contribution of each core process and supplementary processes (utilities and transportation) to consumption of resources at PTA-1 and PTA-2 facilities (a: PTA-1; b: PTA-2).


Page 19 of 33


326 327

The contribution of core and supplementary processes to the overall exergy extracted from

328

the natural environment for both facilities is illustrated in Figure 3b and c. More information on

329

the distribution of resource consumption based on categorized inputs is presented in SI. The

330

negative values in the figure represent the environmental benefits due to fertilizer substitutions

331

and carbon sequestration. At PTA-1, DAF and CD processes are responsible for a significant

332

share in all resource categories (overall about 54% and 21% of total CEENE, respectively),

333

which is due to both electricity consumption and the large amount of centrate generated. At

334

PTA-2 the results of the analysis clearly demonstrate that CD process has the highest resource

335

footprint, with 56% of total exergy extracted from nature, followed by GT and AS processes

336

which have similar impacts, roughly 1,000 MJex. Overall, energy intensive processes such as

337

DAF and CD lead the highest resource extraction at both facilities. This originates not only from

338

the electricity consumption but also the resources used in treatment of the centrate generated in

339

these processes. When the stabilization processes are compared, AD is more favorable than AS

340

in terms of exergy extraction from nature as AS requires 53% more exergy input per FU and

341

accounts for a considerable share of the total renewable resource use (24%) and total land

342

occupied (47%) at PTA-2. Most exergy extraction related to AS originates from quicklime

343

manufacturing. The thickening process dominates mineral resource use at PTA-1 and PTA-2,

344

73% and 84%, respectively, and that is mainly due to the mineral resource consumption

345

occurring at the WWTP that treats the centrate. Land application brings significant benefits in

346

mineral resource consumption, where the savings is about 95% and 51% higher than the overall

347

mineral resource use at PTA-1 and PTA-2, respectively. There is a significant benefit from using

348

biosolids as fertilizer in the fossil fuel resource category.



Page 20 of 33

349

Among the midpoint level impact methods, two categories considered, CED and ADP, are

350

related to resources, while the rest are relevant to impact assessment due to emissions. The

351

results of the resource-related midpoint level impact methods provided similar conclusions, with

352

PTA-1 having a higher score on consumption, compared to PTA-2. When the resource categories

353

are compared, the fossil fuel category exhibits a large share at both CEENE and CED methods,

354

with a score higher than 60% at both facilities. In terms of the resource use indicators, CEENE

355

method provides comprehensive information, while CED accounts for energy resources. The

356

ADP method does not provide information on resource categories. CEENE analysis showed that,

357

even though minerals and metal consumption do not have a high contribution, water resources

358

and land occupation constitute about 15% and 12% of the overall resources consumption,

359

respectively. This consumption is not possible to be accounted for in other methods due to

360

scientific limitations (e.g. water has no calorific value).

361 362

Resource Use Efficiency. The resource use efficiency, CDP, of PTA-1 is 31%, which means

363

only 31% of the resources derived from natural environment are captured in the final product,

364

biosolids. On the other hand, it is about 53% at PTA-2. The lower CDP of PTA-1 facility relative

365

to PTA-2 facility indicates that the PTA-2 is more favorable over PTA-1 in terms of the resource

366

use efficiency. It is worth mentioning that the conversion of the organic carbon into biogas at

367

PTA-1 is a major factor for the lower CDP. Biogas is not accounted as a product, since a portion

368

of the biogas is used internally for digester heating and the rest is flared.

369

Life Cycle Impact Assessment Analysis. At midpoint level, nine impact categories were

370

investigated and the results are presented in Figure 4 (see SI for detailed data). Considering the


Page 21 of 33


371

global warming potential (GWP) impact category in terms of process contribution, the greatest

372

contributor at PTA-1 (51%) is the dissolved air flotation (DAF) process. On the other hand, at

373

PTA-2, the centrifuge dewatering (CD) process accounts for a majority of the impact, 43%.

374

PTA-2 has three main background processes that have notable contributions to GWP; centrate

375

sent to WWTP (17%), quicklime production (28%), and electricity consumption (36%). In PTA-

376

1, electricity consumption accounts for 68% of the total GWP contribution, while about 8% is

377

attributed to emission from biogas combustion. A majority of the GWP impact at both facilities

378

comes from fossil fuels, since the USA electricity is heavily based on fossil sources. The

379

beneficial effect of land application is significant in the GWP category due to the savings from

380

carbon sequestration and from the circumvention of synthetic fertilizer manufacturing. Overall,

381

when all the benefits and burdens are considered, the GWP of PTA-2 is −92 kg CO2 eq while it

382

is +166 kg CO2 eq at PTA-1 facility. The negative value is due to the savings achieved through

383

fertilizer substitutions and carbon sequestration. The eco-toxicity (ET) and terrestrial eco-toxicity

384

(TET) categories are dominated by heavy metal (HM) leaching from land application at both

385

facilities, with more than 97% contribution. PTA-1 proved to be favorable over PTA-2 in the ET

386

and TET impact categories with 7% and 45% lower impact, respectively, as the biosolids end

387

use, land application, is the main contributor to these impact categories at both facilities. On the

388

other hand, at PTA-2, other background processes have influence on the human toxicity (HT)

389

category. For example, 42% of the overall impact results from the high volume of centrate,

390

which is treated at the WWTP. A major portion of the HT comes from HM leaching at PTA-1

391

and PTA-2, 99% and 48%, respectively. It is important to note that the release of certain metals

392

have a greater influence on the resulting toxicity, which also explains the significant difference



393

between the HT potential of PTA-1 and PTA-2. As opposed to the other impact categories, the

394

benefits of fertilizer substitution in the toxicity impact category are negligible.

Page 22 of 33

395

For the eutrophication impact categories, freshwater eutrophication (FE) and marine

396

eutrophication (ME), PTA-1 proved to have better performance, as seen in Figure 4 where

397

negative values indicate environmental savings. Significant benefit is achieved by fertilizer

398

substitution via land application. Centrate generation at both facilities is the main contributor to

399

eutrophication, therefore the DAF thickening process at PTA-1 and GT at PTA-2 are the

400

dominant processes in this category. Overall, 76% of FE and 97% ME in the GT process result

401

from the centrate treatment. In the acidification category, PTA-1 has 5% lower impact compared

402

to PTA-2. At PTA-1 the impact, 69% of overall impact, is mainly from electricity consumption.

403

On the other hand, at PTA-2, the impact is from the high volume of centrate produced, 39% of

404

the total impact, and the fossil fuel dominated electricity consumption, 38%. In terms of the

405

CED, the energy used at both facilities comes mainly from the non-renewable energy sources;

406

i.e. fossil and nuclear. That is simply because of the fact that the USA electricity mix at grid is

407

based mainly on fossil fuel (coal power), followed by nuclear energy.


Page 23 of 33


300%

200%

100%

0%

-100%

-200%

-300% PTA-1

PTA-2

Climate change

408 409 410

PTA-1

PTA-2

Human Toxicity

AS

PTA-1

PTA-2

Ecotoxicity

GT

PTA-1

PTA-2

Terrestrial ecotoxicity

Transportation

PTA-1

PTA-2

PTA-1

PTA-2

Resource Depletion Cumulative Energy Demand

Utilities

LA

AD

PTA-1

PTA-2

Acidification (terrestrial)

CD

PTA-1

PTA-2

Eutrophication (freshwater)

PTA-1

PTA-2

Eutrophication (marine)

DAF

Figure 4. Results of Comparative LCA analysis at midpoint level using selected impact assessment methods

411 412

The midpoint analysis results show that it is not possible to make an overall conclusion since,

413

from an environmental burden perspective, favorable processes change according to the impact

414

category considered. Therefore, endpoint-level analysis were performed in order to make a

415

holistic comparison considering overall environmental burden resulting from the facilities. When

416

the overall impact of the two facilities is investigated, PTA-1 results in 46% higher impact

417

compared to PTA-2, due to high fossil fuel-based electricity consumption (see Figure S3). At

418

PTA-2 a considerable amount of the environmental burden (about 32% of the overall impact) is

419

from the chemical, polymer and quicklime, input. When the environmental burden specific to

420

stabilization processes is considered, the impact of AS is about 44% higher than the AD process.

421

In the AS processes, almost all impact is due to the manufacturing of quicklime consumed in this

422

process. Whereas in the AD process, impact is mainly due to electricity consumption–about

423

76% of overall impact–and the remaining impact is from biogas combustion emissions.



424

Electricity consumption of the AD process results from circulation of the sludge in the system

425

where no mechanical mixing is applied and mixing is achieved via sludge recirculation.

Page 24 of 33

426 427

Scenario Analysis. Figure 5 below presents the comparison of scenarios in terms of overall

428

resource demand in exergy units and the resulting environmental impact of each scenario for

429

treatment of one tonne of DS. The results of CEENE analysis represented by the columns are

430

normalized, for all scenarios, to the highest-value scenario showing the percentage contribution

431

(left axis) of the seven resource categories (Figure 5a). The plotted line values (right axis)

432

provide the net amount of resources extracted at each scenario from the natural environment in

433

exergy units. It should be noted that the benefit of a CHP system is significant in Scenario 3 and

434

Scenario 4. The resource footprint of an AD process with a boiler for biogas utilization (Scenario

435

2) is about 719 MJex. When a CHP system is used for biogas utilization in Scenario 3, the

436

resulting CEENE is about -9,840 MJex. Biogas utilization has a significant influence on the

437

overall system performance, where the adaptation of CHP system results in about 9 GJ/t.DS less

438

exergy consumption. Scenario 4 appears to be the most favorable system configuration, where

439

the major benefits originate from the fossil fuel savings. LCA analysis reveals that Scenario 3

440

and Scenario 4 are the most promising process configurations when the net environmental

441

impact resulting from all scenarios are considered (Figure 5b).


Page 25 of 33


CEENE (MJex/ t.DS)

Relative Contribution (%)

a)

Land occupation (and transformation) Minerals (and mineral aggregates) Nuclear energy Renewable Resources

Water Resources Metal ores Fossil fuels

Relative Contribution (%)

b)

442 443 444 445 446 447

Figure 5. Result of the comparative CEENE and LCA analyses for 1 tonne of DS to be treated (FU) for seven scenarios at endpoint level (a: relative contribution of resource categories (%); b: process contribution at endpoint level, %) (AD: Anaerobic Digester; AS: Alkaline Stabilization; CD: Centrifuge Dewatering; DAF: Dissolved Air Floatation; GT: Gravity Thickener; LA: Land Application)



Page 26 of 33

448

The two tools, CEENE and LCA, provided similar results, both indicating that overall PTA-2

449

has better performance over PTA-1. LCA results showed that the environmental burden is

450

mainly from the intense electricity consumption of DAF and CD processes.

451

analysis further revealed that it is due to the high resource consumption, dominated by fossil fuel

452

and nuclear based natural resources. CEENE analysis showed that the use of CHP system in

453

biogas utilization would lead to significant savings in overall resource consumption. In sum, the

454

results show that CEENE analysis provides the critical supplemental information to evaluate

455

BMS processes for identification and quantification of resource use and efficiency, such that

456

BMS products are most beneficially valorized.

The CEENE

457

The overall results of ReCiPe endpoint and CEENE methods have a similar outcome

458

confirming that PTA-2 is more advantageous compared to PTA-1. One crucial difference is

459

related to use of biosolids as fertilizer. Land application of biosolids accounts for a large portion

460

of the credits, about 24% at PTA-1 and 31% at PTA-2 in CEENE analysis, which has

461

significantly higher impact when ReCiPe is used (about 33% and 68%, respectively). This is

462

mainly due to the carbon sequestration and avoided fertilizer production, which is more

463

significant compared to exergetic resource consumption avoided.

464 465

Sensitivity Analysis. Sensitivity analysis (details provided in SI, Figures S3 and S4 and

466

Tables S12 and S13) shows that it is crucial to invest in accurate data acquisition, especially for

467

the parameters of electricity consumption, polymer and quicklime consumption at both facilities,

468

and additionally of transport distance at PTA-2. Electricity usage data is the key parameter.

469

Analysis using electricity mixes from various countries shows that changes in the contribution of


Page 27 of 33


470

the resources used drastically affects the overall resulting impact (at both LCA and CEENE

471

Results).

472 473



474

ASSOCIATED CONTENT

475

Supporting Information.

476

Additional information as noted on the text is available free of charge via the Internet at

477

http://pubs.acs.org.

478

AUTHOR INFORMATION

479

Corresponding Author

480

Metin Duran; E-mail: [email protected]; Tel.: (610) 519-4963; Fax: (610) 519 6754

481

Author Contributions

482

The manuscript was written through contributions of all authors. All authors have given approval

483

to the final version of the manuscript.

484

Notes

485

The authors declare no competing financial interest.

486

ACKNOWLEDGMENTS

487

The partial support for Sevda Alanya was provided by Edward A. Daylor Chair in

488

Environmental Engineering for this study. We thank Valley Forge Sewer Authority for all their

489

help and effort in providing data. In addition the authors also thank the anonymous staff of the

490

facility used in the study also for providing information and support in data collection.

491


Page 28 of 33

Page 29 of 33

492


ABBREVIATIONS AD

Anaerobic Digester

AS

Alkaline Stabilization

BMS

Biosolids Management Systems

CEENE

Cumulative Exergy Extraction from the Natural Environment

CD

Centrifuge Dewatering

CDP

Cumulative Degree of Perfection

DAF

Dissolved Air Floatation

ELCA

Exergetic Life Cycle Assessment

GT

Gravity Thickener

LA

Land Application

LCA

Life Cycle Assessment

LCIA

Life Cycle Impact Assessment

PTA

Process Train Alternative

WWTP

Wastewater Treatment Plant

493 494

REFERENCES

495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513

1.

2. 3.

4. 5.

6. 7.

Batstone, D.J.; Darvodelsky, P.; Keller, J. 2008. Trends in biosolids handling technologies: economics and environmental factors. Biosolids Specialty Conference IV, Adelaide, Australia, 11-12 June, 2008. NEBRA. Information Update: Official Usage of the Term “Biosolids”. North East Biosolids and Residuals Association (NEBRA): NH, USA, 2008. Sciubba, E.; Bastianonib, S.; Tiezzi, E. Exergy and extended exergy accounting of very large complex systems with an application to the province of Siena, Italy. Journal of Environmental Management. 2008, 86, 372–382. Foley, J.; de Haas, D.; Hartley, K.; Lan, P. Comprehensive life cycle inventories of alternative wastewater treatment systems. Water Research. 2010, 44, 1654–1666. Hospido, A.; Moreira, M.T.; Martin, M.; Rigola, M.; Feijoo, G. Environmental evaluation of different treatment processes for sludge from urban wastewater treatments: anaerobic digestion versus thermal processes. International Journal of Life Cycle Analysis. 2005, 5, 336–345. Hospido, A.; Moreira, M.T.; Feijoo, G. Comparison of Municipal Wastewater Treatment Plants for Big Centres of Population in Galicia (Spain). Int. J. LCA. 2008, 13(1), 57-64. Houillon, G.; Jollie, O. Life cycle assessment of processes for the treatment of wastewater urban sludge: energy and global warming analysis. J. Cleaner Production. 2005, 13, 287– 299.



514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558

8. 9.

10.

11. 12. 13.

14. 15.

16.

17.

18.

19.

20.

21.

22. 23.

Page 30 of 33

Peters, G.; Lundie, S. Life-Cycle Assessment of Biosolids Processing Options. Journal of Industrial Ecology. 2001, 25 (2), 103-121. Lundin, M.; Olofsson, M.; Pettersson, G.J.; Zetterlund, H. Environmental and economic assessment of sewage sludge handing options. Resources Conservation and Recycling. 2004, 41, 255–278. Murray, A.; Horvath, A.; Nelson, K.L. Hybrid Life-Cycle Environmental and Cost Inventory of Sewage Sludge Treatment and End-Use Scenarios: A Case Study from China. Environ. Sci. Technol. 2008, 42, 3163–3169. Peters, G.; Rowley, H.V. Environmental Comparison of Biosolids Management Systems Using Life Cycle Assessment. Environ. Sci. Technol. 2009, 43 (8), 2674-2679. Szargut, J.; Morris, D. R. Cumulative exergy consumption and cumulative degree of perfection of chemical processes. Int. J. En. Res. 1987, 11, 245–261. Bösch, M.E.; Hellweg, S.; Huijbregts, M.A.J.; Frischknecht, R. Applying cumulative exergy demand (CExD) indicators to the ecoinvent database. The Int. Journal of Life Cycle Assessment. 2007, 12, 181-190. Ecoinvent Center. Ecoinvent data v2.2. Swiss Centre for Life Cycle Inventories: Dubendorf, Switzerland, 2010. Dewulf, J.; Bösch, M.E.; De Meester, B.; Van der Vorst, G.; Van Langenhove, H.; Hellweg, S.; Huijbregts, M.A.J. Cumulative Exergy Extraction from the Natural Environment (CEENE): a comprehensive Life Cycle Impact Assessment method for resource accounting. Environmental Science & Technology. 2007, 41, 8477-8483. Alvarenga, R. A. F.; Dewulf, J.; Langenhove, H.; Huijbregts, M. A. J. Exergy-based accounting for land as a natural resource in life cycle assessment. Int. J. Life Cycle Assess. 2013, 18, 939–947. Taelman, S.E.; De Meester, S.; Schaubroeck, T.; Sakshaug, E.; Alvarenga, R.A.F.; Dewulf, J. Accounting for the occupation of the marine environment as a natural resource in life cycle assessment: an exergy based approach. Resources, Conservation and Recycling. 2014, 91, 1-10. Liao, W.; Heijungs R.; Huppes, G. Thermodynamic resource indicators in LCA: a case study on the titania produced in Panzhihua city, southwest China. Int. J. Life Cycle Assess. 2012, 17, 951–961. De Meester, B.; Dewulf, J.; Verbeke, S. ; Janssens, A. ; Van Langenhove, H. Exergetic lifecycle assessment (ELCA) for resource consumption evaluation in the built environment. Build. Environ. 2009, 44, 11–17. Hoque, M.R.; Durany, X.G.; Méndez, G.V.; Sala, C.S. Exergetic Life Cycle Assessment: An Improved Option to Analyze Resource Use Efficiency of the Construction Sector Smart Innovation. Systems and Technologies. 2013, 22, 313-321. Talens Peiró, L.; Lombardi, L. ; Villalba Méndez, G.; Gabarrell Durany, X. Life cycle assessment (LCA) and exergetic life cycle assessment (ELCA) of the production of biodiesel from used cooking oil (UCO). Energy. 2010, 35, 889–893. Ozbilen, A.; Dincer, I.; Rosen,M.A. Exergetic life cycle assessment of a hydrogen production process. Int. journal of hydrogen energy. 2012, 37, 5665-5675. Dong, J.; Chi, Y.; Tang, Y.; Wang, F.; Huang, Q. Combined Life Cycle Environmental and Exergetic Assessment of Four Typical Sewage Sludge Treatment Techniques in China. Energy Fuels. 2014, 28, 2114−2122.


Page 31 of 33

559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603


24.

Szargut, J.; Morris., D. R.; Steward, F. R. Exergy Analysis of Thermal, Chemical, and Metallurgical Processes. Hemisphere Publishing Corporation, Berlin, Germany, 1988. 25. ISO 14040: Environmental Management: Life Cycle Assessment– Principles and framework: Geneva, Switzerland, 2006. 26. ISO 14044: Environmental management–Life cycle assessment–Requirements and guidelines: Geneva, Switzerland, 2006. 27. Dong, B. Life-cycle Assessment of Wastewater Treatment Plants. Master’s thesis, Massachusetts Institute of Technology, Boston, MA, 2012. 28. Hong, J.; Otaki, M.; Jolliet, O. Environmental and economic life cycle assessment for sewage sludge treatment processes in Japan. Waste Management. 2009, 29, 696–703. 29. Dewulf, J.; Van der Vorst, G.; Aelterman, W.; De Witte, B.; Vanbaelen, H.; Van Langenhove, H. Integral resource management by exergy analysis for the selection of a separation process in the pharmaceutical industry. Green Chemistry. 2007, 9, 785– 791. 30. WEF; ASCE. Design of Municipal Wastewater Treatment Plants. WEF manual of practice No. 8, 5th Edition ASCE manuals and reports on engineering practice No. 76: Alexandria, VA, 2010. 31. EarthShift. 2014. US-EI SimaPro Database. http://www.earthshift.com/software/USEIdatabase (accessed January 1, 2014). 32. Gallego, A.; Hospido, A.; Moreira, M.T.; Feijoo, G. Environmental performance of wastewater treatment plants for small populations. Resources, Conservation and Recycling. 2008, 52, 931–940. 33. Pourmovahed, A.; Opperman, T.; Lernke, D. Performance and Efficiency of a Biogas CHP System Utilizing a Stirling Engine. Proceedings of the International Conference on Renewable Energies and Power Quality, Las Palmas, Spain, 13-15 April, 2011. 34. Saidur, R.; Ahamed, J.U.; Masjuki, H.H. Energy, exergy and economic analysis of industrial boilers. Energy Policy. 2010, 38, 2188–2197. 35. IPCC. IPCC Guidelines for National Greenhouse Gas Inventories: Wastewater treatment and discharge. Intergovernmental Panel on Climate Change National Greenhouse Gas Inventories Programme, 2006, Volume 5, Chapter 6. 36. USEPA. California Wastewater Climate Change Group. EPA-HQ-OAR-2010-0560; U.S. Environmental Protection Agency, 2010. 37. SYLVIS. The Biosolids Emissions Assessment Model (BEAM): A Method for Determining Greenhouse Gas Emissions from Canadian Biosolids Management Practices. SYLVIS Environmental, document #800-9: BC, Canada, 2009. 38. Doka, G. Life Cycle Inventories of Waste Treatment Services: Final report ecoinvent v2.1. Ecoinvent report No. 13. Swiss Centre for Life Cycle Inventories: Dübendorf, Switzerland, 2009. 39. Guo, M.; Murphy, R.J. LCA data quality: Sensitivity and uncertainty analysis. Science of the Total Environment. 2012, 435–436, 230–243. 40. EC-JRC. ILCD Handbook: Recommendations for Life Cycle Impact Assessment in the European context- based on existing environmental impact assessment models and factors. Publications Office of the European Union: Luxembourg, LU, 2011. 41. Corominas, L., Foley, J., Guest, J.S., Hospido, A., Larsen, H.F, Morera, S., Shaw, A. Life cycle assessment applied to wastewater treatment: State of the art. Water research. 2013, 47-15, 5480-5492.



604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632

42. 43.

44.

45.

46. 47.

48.

49.

50.

Page 32 of 33

Fertilizer Use and Price. http://www.ers.usda.gov/data-products/fertilizer-use-andprice.aspx#26720 (accessed March 25, 2013) Remy, C. Life Cycle Assessment of conventional and source-separation systems for urban wastewater management. Ph.D. Dissertation. Technical University of Berlin, Germany, 2010. Stehouwer, R. Land Application of Sewage Sludge in Pennsylvania- Use of Biosolids in Crop Production. Penn State Collage of Agricultural Sciences, PA, 1999; http://extension.psu.edu/plants/crops/esi/biosolids-use. West, T.O.; McBride, A.C. The contribution of agricultural lime to carbon dioxide emissions in the United States: dissolution, transport, and net emissions. Agriculture, Ecosystems and Environment. 2005, 108, 145–154. Favoino, E.; Hogg, D. The potential role of compost in reducing greenhouse gases. Waste Management & Research. 2008, 26, 61–69. Hermann, B.G.; Debeer, L.; De Wilde, B.; Blok, K.; Patel, M.K. To compost or not to compost: Carbon and energy footprints of biodegradable materials’ waste treatment. Polymer Degradation and Stability. 2011, 96, 1159-1171. Hospido, A.; Carballa, M.; Moreira, M.; Omil, F.; Lema, J.; Feijoo, G. Environmental assessment of anaerobically digested sludge reuse in agriculture: Potential impacts of emerging micropollutants. Water Research. 2010, 44, 3225-3233. Goedkoop, M.; Heijungs, R.; Huijbregts, M.; de Schryver, A.; Struijs, J.; van Zelm, R. ReCiPe 2008, A life cycle impact assessment method which comprises harmonized category indicators at the midpoint and the endpoint level. First edition Report I: The Hague, The Netherlands, 2009. EIA. 2014. U.S. Energy Information Administration. http://www.eia.gov/tools/faqs/faq.cfm?id=667&t=2 (accessed January 1, 2014).


Page 33 of 33


ACS Paragon Plus Environment

Comparison of Overall Resource Consumption of Biosolids

Recommend Documents