Life cycle energy assessment and economic feasibility of stormwater harvested from pervious pavements

Journal Pre-proof Life cycle energy assessment and economic feasibility of stormwater harvested from pervious pavements Igor Catão Martins Vaz, Enedir Ghisi, Liseane Padilha Thives PII:

S0043-1354(19)31096-6

DOI:

https://doi.org/10.1016/j.watres.2019.115322

Reference:

WR 115322

To appear in:

Water Research

Received Date: 4 July 2019 Revised Date:

22 October 2019

Accepted Date: 17 November 2019

Please cite this article as: Martins Vaz, Igor.Catã., Ghisi, E., Thives, L.P., Life cycle energy assessment and economic feasibility of stormwater harvested from pervious pavements, Water Research (2019), doi: https://doi.org/10.1016/j.watres.2019.115322. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Potential for potable water savings (%)

Dec

Oct

Nov

Sep

Jul

Aug

Jun

Apr

May

Mar

Jan

600 550 500 450 400 350 300 250 200 150 100 50 0 Feb

Monthly rainfall (mm) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Average monthly consumption (litres)

450000 400000 350000 300000 250000 200000 150000 100000 50000 0

55 50 45 40 35 30 25 20 15 10 5 0

Lower rainwater tank capacity for three different literature pervious pavement models (litres) Hammes

1 2

Pinto

Acioli

Water consumption data, rainfall data and potential for potable water savings by harvesting stormwater from a parking lot of a public building in Florianópolis, Brazil.

1

Life Cycle Energy Assessment and Economic

2

Feasibility of Stormwater Harvested from

3

Pervious Pavements

4

Igor Catão Martins Vaz*, Enedir Ghisi and Liseane Padilha Thives

5

Laboratory of Energy Efficiency in Buildings, Department of Civil

6 7 8 9

Engineering, Federal University of Santa Catarina, Florianópolis, SC 88040-900, Brazil, [email protected] (I.C.M.V.); [email protected] (E.G.)

10

[email protected] (L.P.T.)

11

*Correspondence: [email protected].

12

Abstract: Pervious pavements are one of the most used construction

13

techniques among the Sustainable Urban Drainage Systems (SUDS).

14

The objective of this article is to analyse the energy life cycle and the

15

life cycle cost of stormwater harvesting systems using pervious

16

pavements models in order to compare and evaluate the differences

17

and verify what influences the profitability and sustainability. The

18

method proposed started with the definition of pervious pavement

19

models based on literature review. The main characteristic of the

20

models analysed was the use of porous asphalt with different

21

underlying

22

hydrological-hydraulic design of the pavements was also assessed.

23

The potential for potable water savings due to harvesting stormwater

24

from a parking lot was estimated for a public building in

layers,

i.e.

thickness

and

material.

The

2 of 36

25

Florianópolis, southern Brazil. The models were compared to identify

26

what most influences the potable water savings, the profitability and

27

the sustainability of the systems. The maximum potable water

28

savings found were 42%. It was also observed that the overall

29

consumption of the building has been decreasing over the years, and

30

the yearly rainfall has increased, which leads to a higher potential. In

31

the current water consumption pattern, none of the systems

32

evaluated was profitable or presented sustainability, evaluated herein

33

as negative energy balance. However, it was verified that if analysed

34

comparatively with non-pervious pavement, it was profitable to use

35

stormwater harvested from the pervious pavement. Thus, it can be

36

concluded that stormwater harvesting systems in combination with

37

pervious pavements are promising, serving as SUDS and saving

38

money for users. It is also noticeable that the use of porous asphalt is

39

not recommended when aiming for systems with low embedded

40

energy.

41

Keywords: Pervious pavements; life cycle assessment; embedded

42

energy; rainwater harvesting; sustainability; potable water savings.

43 44

1. Introduction

45

To minimise problems caused by the waterproofing of urban

46

surfaces, construction techniques classified as Sustainable Urban

47

Drainage Systems (SUDS) have been increasingly proposed against

48

the usual urban drainage. The waterproofing of urban surfaces

3 of 36

49

produces discontinuities in the hydrological cycle, sometimes

50

overloading the urban drainage systems. As drainage systems

51

become inefficient to drain stormwater, floods and user discomfort

52

are generated (Tucci, 2005). SUDS then introduce a concept of

53

sustainable drainage by treating water locally, which reduces the

54

possibility of overloading stormwater distribution networks (Poleto

55

and Tassi, 2012).

56

One of the techniques contemplated in SUDS is the use of

57

pervious pavements to harvest stormwater and reduce water flow to

58

the public drainage system. The use of pervious pavements aims to

59

reduce the amount of stormwater runoff, through infiltration in the

60

pavement. Some benefits arise from the use of pervious pavements,

61

such as the filtration of heavy metals (Legret et al., 1996), oil retention

62

(Pratt et al., 1999), decrease in the amount of stormwater runoff

63

(Araújo et al., 2000; Meurer Filho, 2001), decrease in traffic noise

64

(Bernucci et al., 2008; Knabben, 2012), decrease in water spray from

65

tires and improvement in road visibility (Bernucci et al., 2008).

66

The design of pervious pavements has already been widely

67

studied, and there are numerous manuals, guidelines (DEQ-Virginia,

68

2011; NAPA, 2008; FHWA, 2015; CIRIA, 2015) and examples of

69

existing cases. In Brazil, there are some studies of pervious pavement

70

models with the definitions of the pervious layers, their thicknesses

71

and characteristics (Acioli, 2005; Pinto, 2011; Hammes et al., 2018).

72

Another benefit that can be obtained with the application of

73

pervious pavements is the harvesting of stormwater for use in

74

buildings (Hammes et al., 2018; Kandhal and Mishra, 2014;

4 of 36

75

Gomez-Ullate et al., 2010). The water collected by the pervious

76

pavements is redirected for use in non-potable purposes, such as

77

flushing toilets and cleaning outside areas, thus reducing the amount

78

of potable water that would be consumed in the building. Such use

79

aligns the concept of SUDS with the fight against global water scarcity

80

by saving potable water. Some studies on quality (Hammes et al.,

81

2018; Antunes et al., 2016; Thives et al., 2017) and quantity (Hammes

82

et al., 2018; Thives et al., 2017) indicate that stormwater infiltrated in

83

pervious pavements can be used for non-potable purposes in

84

buildings.

85

According to the United Nations Environment Program (UNEP,

86

2002), about one-third of the world's population lived in countries

87

where water availability was lower than water consumption in 2002.

88

UNEP also estimates that before 2027, two thirds of the world's

89

population will be in the same conditions of water availability. Thus,

90

the use of alternatives such as rainwater harvesting becomes

91

fundamental.

92

Currently, several countries are carrying out studies on the use

93

of rainwater as an alternative to water scarcity, including studies of

94

potable water savings potential (Ghisi et al., 2005; Liuzzo et al., 2016;

95

Hammes et al., 2018), public policies to encourage rainwater use (Lee

96

et al., 2017; Ward et al., 2012), life cycle assessment of rainwater

97

harvesting systems (Anand and Apul, 2010; Vialle et al., 2015), among

98

more specific studies.

99

Ghisi et al. (2005), for example, studied the potential for potable

100

water savings by collecting rainwater from roofs in the state of Santa

5 of 36

101

Catarina, Brazil. The water availability in the state will be less than

102

2000 m³ in the year 2100, which is considered a low availability,

103

according to UNEP (2002). Thus, they evaluated the potential for

104

potable water savings in 62 cities in Santa Catarina. The average

105

potential for potable water savings was 69%, ranging from 34% to

106

92%.

107

Studies can also be found on the sustainability of rainwater

108

harvesting systems, mainly related to embedded energy. Marinoski et

109

al. (2012), for example, carried out a study to analyse the

110

environmental feasibility of rainwater harvesting systems and

111

greywater reuse systems for non-potable uses. For the rainwater

112

harvesting system, the energy benefit was 1587.8 MJ, which

113

corresponded to 12.85% of the total embedded energy in the

114

rainwater harvesting system.

115

For the comparison of sustainability between systems, the Life

116

Cycle Assessment (LCA) can be mentioned, which is a tool capable of

117

providing

118

improvement of products and services. Through this methodology,

119

all impacts and inputs pertinent to the life cycle of innovations are

120

verified, in order to ensure that the implementation is beneficial to the

121

environment and users. Variations such as Life Cycle Energy

122

Assessment and Life Cycle Cost Assessment appear as a simplified

123

option for the methodology, in which only inputs and processes that

124

involve energy and money, respectively, are considered.

key

information

in

sustainability,

helping

the

125

According to Fay et al. (2000), the Life Cycle Energy Assessment

126

(LCEA) is a derivation of the LCA, created with the specific objective

6 of 36

127

of analysing the energy belonging to the construction, maintenance

128

and end of life of a given system. LCEA has been widely used in civil

129

construction projects to improve them energetically and make them

130

more sustainable and economical (Fay et al., 2000; Tavares, 2006). Its

131

popularity has grown strongly with the increased focus given to the

132

conservation of natural resources and concern for ecological aspects.

133

Life Cycle Cost Assessment (LCCA) is an analysis similar to LCEA,

134

but with focus on money-related activities.

135

Despite the benefits provided by the installation of pervious

136

pavements and their capacity to harvest stormwater, the application

137

of stormwater harvesting systems through pervious pavements is still

138

not widely spread in Brazil. As a result, studies that analyse the

139

sustainability and profitability of stormwater harvesting systems

140

through pervious pavements are increasingly required in order to

141

assist their improvement.

142

2. Objective

143

The objective of this work is to analyse the energy life cycle and

144

the life cycle cost of stormwater harvesting systems, in order to

145

compare and evaluate the differences and verify what influences the

146

profitability and sustainability of different types of pavement.

147

3. Methodology

148

Three different pervious pavement models were used in this

149

work. They were assessed in terms of embodied energy and economic

150

benefits. The site used for the evaluation of the system is a parking lot

7 of 36

151

of a public building of the Federal University of Santa Catarina

152

(UFSC). The different pavement models were obtained through a

153

literature review of Brazilian works in the same field of study.

154

3.1. Definition of models to be compared

155

The three models used were defined based on three Brazilian

156

studies: Acioli (2005), Pinto (2011) and Hammes et al. (2018). These

157

studies were selected because they are studies in the area of pervious

158

pavement that design pervious pavement models with porous

159

asphalt concrete. Also, they have the main parameters that this study

160

required for the simulation and subsequent LCEA and LCCA. Some

161

modifications were made to some of the characteristics in order to be

162

possible to understand how the differences between the models

163

impact on the sustainability and profitability of the systems.

164

Table 1 shows the main characteristics of the pervious pavement

165

models taken from the studies in addition to the use of each of the

166

characteristics.

167

3.2. Potential for potable water savings

168

The simulations performed to achieve the potential for potable

169

water savings were performed using the computer programme

170

Netuno 4 (Ghisi and Cordova, 2014). Simulations were performed

171

considering daily rainfall for the year 2017 and also for a long-term

172

rainfall time series. The rainfall data were provided by the Santa

173

Catarina Agricultural Research and Rural Extension Company

174

(EPAGRI-SC), including data between 01/01/2003 and 31/12/2017.

8 of 36

175

The area of pervious pavement was estimated as 1500 m², and it

176

was determined that the total area of influence, which directs water to

177

the pervious pavement, was 1700 m².

178

Water consumption in the building was obtained from the

179

Department of Architecture and Engineering Projects (DAEP, 2017) of

180

UFSC. The non-potable water demand was obtained from Botelho

181

(2008), who estimated the water end-uses in the same building that

182

we are using as a case study.

183

3.3. Sizing of aggregate reservoir course

184

The hydrological-hydraulic design of the pavement was

185

performed using two methods: the method proposed by Hammes et

186

al. (2018) and the envelope curve. The goal of performing the design

187

using both methods is to confirm the thicknesses obtained.

188

It was necessary to obtain the Intensity Duration Frequency

189

(IDF) curve and Talbot equations for Florianópolis, in order to

190

estimate the maximum average rainfall intensity. Eq. 1 shows the IDF

191

equation. For the IDF equation, the following parameters, as

192

proposed by Back (2013) for Florianópolis, were used: k = 1168.46; m =

193

0.237; d = 9.12 and n = 0.703. In both methods, the thickness was

194

assessed for return periods equal to 2, 5 and 10 years.

195

For the Talbot curve, which is similar to the IDF, no parameters

196

were found for Florianópolis. Thus, it was necessary to make a curve

197

adjustment to find which parameters, when inserted in the Talbot

198

curve, generate the smallest difference for the IDF equation. The

199

parameters differ according to the return period chosen; thus, for

9 of 36

200

each return period, a different Talbot curve was generated. Eq. 2

201

shows the equation of the Talbot curve. As an example, the following

202

parameters were obtained and used for a return period equal to 5

203

years in the Talbot curve: a = 4858; b = 0.168 and c = 18.82. =

∗ ( + )

(1)

204

where: K, m, n and d are variables according to the place of

205

research (non-dimensional); T is the return period (years); i is the

206

maximum average rainfall intensity (mm/h); t is the duration of

207

rainfall (minutes). =

∗ ( + )

(2)

208

where: a, b and c are variables according to the place of research

209

(non-dimensional); T is the return period (years); i is the maximum

210

average rainfall intensity (mm/h); t is the duration of rainfall

211

(minutes).

212 213

The method proposed by Hammes et al. (2018) is shown in Eq. 3,

214

adapted from Araújo et al. (2000). The specific output flow through

215

the drains (qs) was considered constant and can be obtained using Eq.

216

4. By dividing the input flow by the effective drainage area of the

217

pavement, an area in which there is pervious pavement, the specific

218

output flow could be obtained (Hammes et al., 2018). ℎ=

∗( ∗ −

)

(3)

10 of 36

219

where: h is the reservoir course thickness (mm); i is the

220

maximum average design rainfall intensity (mm/h); t is the design

221

rainfall duration (h); R is the ratio between the drained area (pervious

222

pavement and impermeable areas which contribute to surface runoff)

223

and the pervious pavement area (dimensionless); qs is the specific

224

output flow (mm/h);

is the reservoir course porosity (%). =

∗ ∗ 1000 ∗ ∗

(4)

225

where: qs is the specific output flow (m/h); i is the maximum

226

average design rainfall intensity (mm/h); t is the design rainfall

227

duration (h); At is the total area that directs water to the pervious

228

pavement (m²); Ap is the pervious pavement area (m²); te is the

229

depletion period (hours).

230 231

The second method tested was the envelope curve, as proposed

232

by Silveira (2003). According to Silveira (2003), the envelope curve

233

method is a classic method that uses the simplified water balance and

234

can be adapted for the pre-design of pervious pavements. The

235

method consists of deriving the difference between the input volume

236

and the output volume to find the maximization of the function. Eq. 5

237

was used to estimate the maximum thickness of the water layer found

238

in the reservoir layer. Instead of using the IDF data, the method uses

239

the Talbot curve coefficients. Eq. 6 shows how to obtain the thickness

240

of the reservoir layer from the maximum depth of water in the layer.

á

=(

60

∗ !∗

/#

−

60

∗

)#

(5)

11 of 36

ℎ =

á

(6)

241

where: Vmax is the design volume (mm); a, b and c are coefficients

242

from the Talbot curve of the site (dimensionless); T is the return

243

period of the enterprise (years); h is the necessary thickness of the

244

reservoir course (mm); qs is the specific output flow (mm/h); β is a

245

coefficient used in the calculation of the envelope curve regarding the

246

drained area and the pervious pavement area (dimensionless); is the

247

porosity of the reservoir layer (%).

248 249

The method used for calculating the specific output flow was the

250

same one as used by Hammes et al. (2018). The only difference in the

251

final value of the specific output flow was the use of a safety factor, as

252

stated by Acioli (2005) in her research, which takes into account the

253

flood risks in case of inability to store stormwater. The safety factor

254

was considered herein as 1.5, considering no significant damage by

255

an overflow in the parking lot. The final specific output flow for the

256

envelope curve method was obtained by dividing qs from Eq. 4 by the

257

safety factor.

258

It was also necessary to increase the thickness of the reservoir

259

course to give a slope to the bottom drains. The largest dimension

260

found in the direction of flow was 77 meters, between the furthest

261

edge of the parking lot and the drain outlet to the lower reservoir. The

262

inclination was taken as 0.5%, so as not to generate accentuated

263

thicknesses. The inclination thickness was obtained according to Eq.

264

7.

12 of 36

%′ =

'∗( 2

(7)

265

where: H' is the thickness to be added (mm); I is the slope of the

266

drains (m/m); L is the longest length from the drainage outlet point to

267

an edge of the pavement (mm).

268 The final thickness for the LCEA and LCCA was chosen

269 270

considering a return period equal to 5 years and rounded down.

271

3.4. Life Cycle Energy Assessment

272

The life cycle energy assessment, as well as the life cycle cost

273

assessment, took into account the phases of construction and

274

maintenance of the system. The choice to leave out the options after

275

the end of the lifespan of the system was made due to the numerous

276

construction possibilities (restoration or recycling, for example). It

277

was also considered that it would not bring a significant difference in

278

terms of energy or terms of cost in the final comparison between the

279

models. The following values were considered in the LCEA:

280 281

•

Initial embedded energy;

282

•

Initial transport energy of the materials;

283

•

Recurring embedded energy;

284

•

Operating energy due to the motor pumps;

285

•

Energy benefits of water savings.

286

3.4.1. Embedded energy

13 of 36

287

The embedded energy is the energy belonging to the materials

288

used in the initial production of the system. It was calculated as

289

shown in Eq. 8. It follows the same model as other similar studies that

290

evaluated the embedded energy of construction systems (Tavares,

291

2006; Ramesh et al., 2010; Marinoski et al., 2012; Proença and Ghisi,

292

2013; Fay et al., 2000).

**+ = , -. ∗ /.

(8)

.01

293

where: EEmat is the embedded energy of the subsystem j (MJ); n is

294

the number of materials the system has; Mi is the quantity of certain

295

material in the system (kg); mi is the embedded energy of a given

296

material in the system (MJ/kg).

297

3.4.2. Transport energy of the construction materials

298

The transport energy of the materials was obtained using Eq. 9,

299

proposed by Tavares (2006). The energy consumption due to

300

transport was taken as 1.5 MJ/t.km, based on similar studies (Tavares,

301

2006; Kalbusch and Ghisi, 2012).

302 *234

+

= , -. ∗ 5. ∗ .01

.

(9)

303

where: Etransj is the transport energy of the construction materials

304

for the subsystem j (MJ); n is the number of materials; Mi is the

305

quantity of a given material in the system (kg); li is the distance from

306

the manufacturer of a certain material to the construction site (km);

14 of 36

307

TRi is the energy consumption due to the type of transportation used

308

(MJ/kg.km).

309

3.4.3. Recurrent embedded energy

310

Recurrent embedded energy is the energy belonging to the

311

materials used in the system that need to be replaced because they

312

have a shorter lifespan than the stipulated lifespan for the system. Eq.

313

10 shows how to calculate the recurrent embedded energy; it is

314

adapted from Ramesh et al. (2010). **3 = , /. -. [7

( 8 − 1] ( .

(10)

315

where: EEr is the recurrent embedded energy (MJ); mi is the

316

amount of material in the system (Kg); Mi is the amount of embedded

317

energy per amount of material (MJ/Kg); Lb is the lifespan of the

318

system (years); Lmi is the lifespan of the material to be replaced

319

(years).

320

3.4.4. Energy for pumping water

321

The usage phase comprises all the energy required to keep the

322

system in full operation. There is the energy consumption for the

323

operation of pumps and the energy embedded in the chlorine used

324

for water treatment. Since water quality was not assessed, only the

325

energy consumption for pumping water was calculated. Eq. 11 was

326

used to calculate the monthly energy consumption for pumping

327

water, similarly to Marinoski (2010). *:;

:

= 23 ∗ 0.7355 ∗ 3.6 ∗ @A ∗ ∗ B

(11)

15 of 36

328

where: EPumps is the monthly energy consumption for pumping

329

water (MJ); Pot is the power of the pumps installed (HP); t is the time

330

of use of the pumps per day (h/day); Fc is the conversion factor from

331

secondary to primary energy (dimensionless).

332 333

The constant "23" is related to the number of days that the pump

334

is on in one month. The number 0.7355 is used to convert the energy

335

from horsepower (HP) to kilowatt (kW). The number 3.6 is used in

336

Eqs. 11 and 12 to convert from kilowatt-hour (kWh) to megajoule

337

(MJ). The conversion factor from secondary to primary energy was

338

obtained through a review of studies in the area (Cursino, 2011), and

339

was considered as 1.5.

340

3.4.5. Energy savings due to potable water savings

341

During the life cycle of the system, there will be the benefit of

342

reducing the amount of water treated by the local water utility. This

343

benefit was calculated according to Eq. 12, similar to the methodology

344

addressed by Marinoski et al. (2012). *CDEF3G = 3.6 ∗ '*HI42

3

∗ J44 ∗ (HK ∗

@ 4L. M ∗B 100

(12)

345

where: EBhydro is the energy savings due to the decrease in the

346

amount of treated water by the water utility over the entire life cycle

347

of the stormwater harvesting system (MJ); IECwater is the index of

348

energy consumption for the distribution of water treated by the local

349

water utility (kWh/m³); Daa is the average annual water demand

350

(m³/year); LCs is the life cycle of the system (years); Psavings is the

16 of 36

351

potential for potable water savings due to the installation of the

352

stormwater harvesting system (%); Fc is the conversion factor from

353

secondary to primary energy (dimensionless).

354 355

The index of energy consumption for water treatment was

356

obtained from SNIS (2017); the figure used was 0.4 kWh/m³ of treated

357

water. It corresponds to the energy necessary for all facilities which

358

directly or indirectly demand energy in order to supply potable

359

water. It includes distribution, water harvesting, administrative

360

facilities, and any additional energy need in the water utility. The

361

coefficient used is based on Florianópolis data from 2003 to 2015,

362

obtained via SNIS (2017).

363

The final energy balance can be obtained by summing all the

364

energies considered and the energy savings due to potable water

365

savings. Eq. 13 shows the energy required for the construction and

366

maintenance of the stormwater harvesting system through pervious

367

pavements. *N.

4O

= **+ + *234

+

+ **3 + *:;

:

− *CDEF3G

(13)

368

where: Efinal is the final energy balance; EEj is the embedded

369

energy of the subsystem j; Etransj is the transport energy of the

370

construction materials for the subsystem j; EEr is the recurrent

371

embedded energy (MJ); EPumps is the monthly energy consumption for

372

pumping water (MJ); EBhydro is the energy savings due to the decrease

373

in the amount of treated water by the water utility (MJ).

374

17 of 36

375

3.5. Life Cycle Cost Assessment

376

To assess the economic feasibility of the pervious pavements

377

systems, the costs due to the implementation and maintenance, and

378

the economic benefit of decreasing the potable water consumption

379

were obtained. The costs considered in LCCA were:

380

•

Initial costs (purchase of materials);

381

•

Maintenance and labour costs;

382

•

Pumps costs;

383

•

Benefit from potable water savings.

384

3.5.1. Initial costs

385

The initial costs are the sum of the labour costs and the costs of

386

all materials used. The costs were obtained through SICRO, SICRO 2

387

and SINAPI, which are government data used to assist in the

388

budgeting of public works. Costs not included in these spreadsheets

389

were obtained through research on the Internet. The objective was to

390

detail as much as possible the stormwater harvesting systems,

391

including the components of the water system and the components of

392

the pervious pavement.

393

3.5.2. Maintenance and labour costs

394

Labour costs were estimated through budget research on similar

395

projects. Some government data (SICRO and SICRO 2) of basic

396

service costs were also checked. The analysis was similar to that

397

performed by Marinoski (2010).

18 of 36

398

Maintenance costs were also estimated through government data

399

on basic service costs. For the pavement, the costs of cleaning were

400

estimated. As for the water system maintenance, labour costs due to

401

the replacement of devices with a lifespan shorter than that of the

402

system were also considered.

403

3.5.3. Cost of water pumping

404

To calculate the costs of water pumping, we obtained the fee that

405

UFSC pays for each MJ provided. Using data provided by the

406

Department of Architecture and Engineering Projects (DAEP) of

407

UFSC, it was possible to estimate an average fee paid for each kWh

408

delivered, which was then converted to each MJ delivered. The

409

monthly cost of water pumping was obtained using Eq. 14.

410 H:;

:

= *:;

:

∗BO

2

(14)

411

where: Cpumps is the monthly cost of pumping water (R$); Epumps is

412

the monthly energy consumption due to pumping water (MJ); Felet is

413

the average fee paid by UFSC (R$/MJ).

414

3.5.4. Benefit from potable water savings

415

The economic benefits due to potable water savings arise from

416

the reduction of costs in the water bill. The calculation of the monthly

417

benefit was performed by analysing the water bills before and after

418

the new system. Eq. 15 shows the calculation of the monthly benefit. *C. = H. ∗ P. − H. ∗ P.,

RG

∗ (1 −

@ RG ) 100

(15)

19 of 36

419

where: EBi is the economic benefit for month i (R$); Peco is the

420

potential for potable water savings (%); Ci is the water consumption

421

in month i (m³); fi is the water tariff without the implementation of the

422

stormwater harvesting system using pervious pavements (R$/m³);

423

fi,econ is the water tariff with the implementation of the stormwater

424

harvesting system using pervious pavements (R$/m³).

425

3.5.5. Economic feasibility

426

The methods used to evaluate the economic feasibility of the

427

system were: the Net Present Value (NPV), the Internal Rate of

428

Return

429

Attractiveness Rate of Return (MARR) was set at the basic interest

430

rate of Brazil’s economy (SELIC rate) in December 2017, at 7.4% per

431

year. The SELIC rate varied considerably in 2017, making it difficult

432

to obtain a fixed reference value.

433

(IRR)

and

the

discounted

payback.

The

Minimum

20 of 36

434

4. Results and Discussion

435

This section presents the results obtained, i.e. the potential for

436

potable water savings, thicknesses of the reservoir layer for the

437

different methods, energy life cycle assessment and life cycle cost

438

assessment.

439 440

4.1. Potential for potable water savings

441

It was necessary to obtain data on potable water consumption

442

and daily rainfall in order to simulate the potential for potable water

443

savings. The first flush was considered zero since stormwater is

444

meant to be harvested from the pavement. The catchment area,

445

pervious pavement plus the impermeable area that directs water to

446

the pavement, was considered to be 1700 m². The water end-uses

447

were considered those of Botelho (2008), who estimated the water

448

demand for non-potable uses as 69% of the total water demand.

449

Botelho (2008) studied the water end-uses in the same building

450

that we are using as a case study. The results showed that the major

451

water consumption was in toilets, corresponding to 62%. The urinals

452

corresponded to 7%, washbasins corresponded to 28% and drinking

453

fountains to 3%. By adding the percentage from urinals and toilets,

454

69% of the water demand was estimated to be non-potable.

455

4.1.1. Potable water consumption

456

Fig. 1 shows the minimum, average and maximum monthly

457

water consumption from 2011 to 2017. One can see there is a variation

21 of 36

458

of water consumption in the vacation period and the school period.

459

From the data provided by DAEP, the values necessary to simulate

460

the potable water savings were extracted. Average monthly water

461

consumption was used for the analysis over 2011‒2017. For 2017, the

462

measurements of water consumption over that year were used. Table

463

2 shows the data extracted from water bills in 2017.

464

4.1.2. Rainfall Data

465

Daily rainfall data over January 2003 to September 2012 were

466

assessed from the Information Centre for Environmental Resources

467

and Hydrometeorology of Santa Catarina (CIRAM). Rainfall data for

468

2017 was also assessed. Fig. 2 shows the monthly rainfall data from

469

January 2003 to September 2012. Fig. 3 shows the data used for the

470

year 2017. For input in Netuno 4 computer programme, rainfall was

471

taken on a daily basis.

472

4.1.3. Potable water savings considering rainfall over 2017

473

Fig. 4 shows the potential for potable water savings as a function

474

of the rainwater tank capacity for the three models considering

475

rainfall over 2017. For all three models evaluated, the ideal tank

476

capacity was 20,000 litres. The potential for potable water savings

477

found for each of the models was:

478

•

Hammes model: 42.09% savings;

479

•

Pinto model: 42.88% savings;

480

•

Acioli model: 43.57% savings.

481

22 of 36

482 483

Such a difference in the potential for potable water savings is due to the available water coefficient, which is different for each model.

484 485

4.1.4. Potable water savings considering a long-term rainfall time

486

series

487

The results obtained considering a long-term rainfall time series

488

were slightly lower than those considering rainfall over 2017. The

489

average potential for potable water savings was approximately 38%.

490

Fig. 5 shows the potential for potable water savings due to the use of

491

stormwater in the building for the three models. For all three models

492

evaluated, the ideal tank capacity was again 20,000 litres.

493

4.2.1. Reservoir course thickness

494

The thicknesses obtained using the Hammes et al. (2018) method

495

are shown in Table 3. It can be seen that the thickness of the models

496

with lower porosity is much greater than those with higher porosity.

497

This occurs because the method correlates the thickness and the

498

porosity with inverse proportion. It is also notable the variation

499

caused by the difference in the return period used. Longer return

500

periods generated more conservative thicknesses.

501

The thicknesses calculated using the envelope curve were very

502

similar to those obtained using the Hammes et al. (2018) method,

503

especially if the safety coefficient parameter that Acioli (2005)

504

indicated is not taken into account. The results obtained without the

505

use of the safety coefficient were very similar to those obtained using

23 of 36

506

the Hammes et al. (2018) method. Table 4 shows the thicknesses

507

obtained, with the safety coefficient, using the envelope curve

508

method (Silveira, 2003).

509 510

The final reservoir course thicknesses, defined for use in LCEA

511

and LCCA, with the increase of the inclination thickness, are shown

512

in Table 5. They were chosen considering the return period equal to 5

513

years and rounded down.

514 515

The values obtained using the envelope curve method (Silveira,

516

2003) were rounded down using the return period equal to 5 years.

517

This choice took into account that the thicknesses obtained using this

518

method were all higher than those obtained using the Hammes et al.

519

(2018) method because there was a safety coefficient. The literature

520

review, which indicated a return period equal to 5 years as sufficient

521

for the type of reservoir, was also taken into account. Fig. 6 shows, as

522

an example, one of the final profiles obtained, demonstrating the

523

presence of the inclination in the model.

524

4.3. Life Cycle Energy Assessment

525

To carry out the LCEA, and later the LCCA, the system was

526

divided into two subsystems: the pavement subsystem, containing all

527

pavement layers, and the hydraulic subsystem, with the necessary

528

components for pumping and using stormwater. The pavement

529

subsystem differs in the three models, as there are differences

530

between the types and thicknesses of the layers. The hydraulic

24 of 36

531

subsystem was the same for all models since the results of potential

532

for potable water savings were very similar, and there was no need

533

for different pumps, reservoirs or pipes.

534

Table 6 shows the main data used in each layer and model. Based

535

on such values, it was possible to obtain the embedded energy of the

536

pavement subsystem – called Epav. The transport energy took into

537

account two distances: 3.5 km from the nearest building material

538

store and 12 km from the nearest quarry. Transport energy of the

539

pavement subsystem was called Etranspav. Weights and quantities

540

shown in Table 6 were used.

541

For the hydraulic subsystem, the pipes and the hydraulic pump

542

were sized. The capacities of the upper and lower reservoirs were

543

taken from the results obtained from Netuno 4. The fittings and

544

components were estimated as being one-third of the weight of the

545

pipes. Table 7 shows the data used to calculate the embedded energy

546

of the hydraulic subsystem – Ehyd – and transport energy of the

547

hydraulic subsystem – Etranshyd.

548

The operational energy of the systems includes the energy used

549

to replace the materials and the energy required for the operation of

550

the water pump. It was estimated that there would be a replacement

551

of the pumps and fittings and components every ten years, i.e. half

552

the life cycle of the system. This estimate took into account the

553

lifespan of the pumps, usually ten years. The result was 930 MJ.

554

The energy required for the operation of the water pump

555

considered the power of the chosen pump, the time in a day that it

556

would be on and the number of days of service, in addition to the

25 of 36

557

factor of conversion of secondary energy to primary energy. The time

558

in which the pump is on is a function of the water consumption in the

559

building. The energy consumption for the operation of the water

560

pump over the life cycle of the system was 23.68 GJ for the 2017 data

561

and 25.49 GJ for the long-term time series data.

562

The energy benefit of water treatment was then quantified. The

563

value found for the energy benefit varied according to the model and

564

the rainfall data used. This occurs because it takes into account the

565

potential for potable water savings, which varied among the rainfall

566

data and models. Table 8 summarizes all data used for the LCEA.

567

Table 9 shows the final energy balance for each of the stages analysed.

568

The main difference between the systems was the embodied

569

energy and transport energy in the pavement subsystem. Even

570

though the energy benefit from potable water savings was variable,

571

no significant differences were found as the potential for potable

572

water savings were very similar in all subsystems. Energy for

573

pumping was also variable according to the water consumption data

574

used, i.e. 2017 versus long-term time series data (almost 2GJ

575

difference). As for the hydraulic components, all systems had the

576

same values, as no differences in components were obtained in

577

fittings, pumps, drains and tanks.

578

26 of 36

579

4.4. Life Cycle Cost Assessment

580

Table 10 shows the initial costs for the Hammes model as an

581

example. The initial costs of the Acioli and Pinto models followed the

582

same trend. It is worth mentioning that the three models evaluated in

583

this study were researched for different purposes by their authors,

584

being compared in this study only to understand what influences the

585

final costs of pervious pavements.

586

The Acioli model had an initial cost equal to R$139,271.58. The

587

main differences for the Hammes model were the additional 2 cm of

588

porous asphalt, the absence of a chocker course, using an extra layer

589

of geotextile, and the difference of the reservoir course thickness.

590

The Pinto model had an initial cost equal to R$150,812.65. The

591

main differences from the Hammes model were the use of

592

bituminous macadam in the chocker course, the use of grit as the last

593

layer and the difference of the reservoir layer thickness. Even with the

594

grit, it was decided to keep the waterproofing material in the model.

595

The labour costs for the initial installation of the hydraulic

596

subsystem were estimated through research into existing budgets for

597

similar projects. The costs were estimated at R$80.00 per day for each

598

plumber and R$50.00 per day for each assistant. The labour cost was

599

R$4,500.00. For the pavement subsystem, it was considered that the

600

initial costs included the installation.

601

The maintenance cost of the pavement subsystem was difficult to

602

obtain. Considering the land cleaning value of SICRO 2 (2016) as a

603

reference, an estimated value of R$0.25 per square meter was

604

obtained. The annual cost of cleaning the pavement was R$1,125.00.

27 of 36

605

In year 10 of the analysis, it was considered the cost of replacing

606

the components that had a life cycle shorter than the system. The costs

607

of two water pumps, one float-level and one solenoid valve were

608

considered. Labour costs were estimated as R$180.00.

609

The pumping costs were calculated by multiplying the total

610

amount of energy consumed during the life cycle of the system by the

611

average rate UFSC pays to the energy utility. The tariff used was

612

R$0.60 per kWh. For 2017 the cost was R$131.63; while for the

613

long-term time series, it was R$142.00 per year.

614

The economic benefit of the decrease in water consumption in

615

the building was then assessed. As the water supply tariffs vary

616

according to the amount of water supplied and vary during the

617

months of the year, a logarithmic regression was extrapolated to

618

make it possible to calculate the new potable water supply tariff,

619

regarding the potable water savings. Table 11 shows the benefits of

620

each model for the two rainfall data scenarios.

621

The models and scenarios were then economically analysed.

622

Table 12 shows the results obtained for NPV and IRR. The MARR

623

used was 7.4% per year.

624

Due to the high initial cost that all models presented they were

625

not economically feasible. All the analyses made in the study

626

corroborate for the conception that the pervious asphalt model is

627

promising as a stormwater harvesting system, but has high initial

628

costs, compromising the economic feasibility of the project. Such costs

629

are mainly linked to the thickness of the reservoir layer, the plastic

630

components used and the porous asphalt.

28 of 36

631

Such costs are also high in asphalt paving projects without the

632

purpose of collecting rainwater. Thus, a second analysis was carried

633

out, in which it was verified whether it is worth investing the

634

additional costs to build a pervious pavement instead of a

635

non-pervious pavement. In other words, to compare a pervious

636

model to a non-pervious model, the costs of the non-pervious model

637

can be subtracted. The analysis was carried out as if both pavements,

638

pervious and non-pervious, were analysed before the construction of

639

the parking lot, in a design approach. The non-pervious pavement

640

was designed regarding only the traffic in the parking lot, containing

641

only the pavement layers; and the pervious pavement was designed

642

regarding the hydrological-hydraulic containing the pervious

643

pavement

644

components.

layers,

geotextiles,

waterproofing

and

hydraulic

645

The thicknesses of the non-pervious pavement for a parking lot

646

have taken into account a pre-sizing according to Brazil National

647

Department of Transport Infrastructure standards (DNIT). No traffic

648

or subgrade data were obtained, so that only an estimate of the

649

thicknesses was made. Table 13 shows the thicknesses of

650

non-pervious asphalt pavement for the site and the relative cost of the

651

layers.

652

By making the comparative economic analysis, i.e. reducing the

653

initial costs of the non-pervious pavement model, the systems would

654

be economically feasible. Table 14 shows the NPV, IRR and

655

discounted payback for all models and data.

656

29 of 36

657

5. Conclusions

658

It can be concluded that the use of pervious pavements in

659

parking lots for stormwater harvesting is promising. Literature

660

review shows many benefits for users and the hydrologic cycle.

661

Pervious pavements can be able to attenuate the effects of

662

waterproofing urban surfaces. Also, stormwater can be harvested and

663

used for non-potable uses, reducing potable water costs and

664

stormwater runoff. In the current state of the urban drainage systems,

665

local SUDS can be helpful to mitigate floods.

666

Costs and energy consumption to manufacture the pavement are

667

very high right now, hindering economic benefits and making it

668

impossible to have a positive energy balance. It is recommended to

669

verify the profitability and sustainability of systems similar to those

670

studied in this research by replacing the coating with pervious

671

concrete pavers, in order to try to obtain better results.

672

It was also observed that the implementation of a stormwater

673

harvesting system would allow for potential for potable water

674

savings of at least 37.0%. This would bring a reduction in potable

675

water expenses of up to R$200,000.00 over the entire system lifespan.

676

There was also no major difference in the potable water savings using

677

higher available water coefficients. This shows that, even if the

678

pavement loses some water to evaporation or absorption from the

679

aggregates, potable water savings higher than 37.0% would be

680

achieved for available water coefficients ranging from 0.80 to 0.95. If

681

water available is closer to 80% of total rainfall, which is more

30 of 36

682

common, it can lead to results very similar to those due to higher

683

available water coefficients.

684

The systems were not economically feasible due to the high

685

initial cost of the pervious pavement, regarding the reservoir layer,

686

the plastic components used and the porous asphalt. However, by

687

analysing the implementation of the stormwater harvesting system as

688

an alternative to the non-pervious pavement, profitability was

689

obtained. Therefore, if analysed since the initial design stage,

690

choosing to construct a pervious pavement to harvest stormwater

691

instead of a usual non-pervious pavement could be economically

692

feasible.

693

It was observed that, when considering rainfall over only 2017,

694

the results were better than those for the long-term time series due to

695

the decrease in water consumption and the increase in rainfall

696

pattern. Both patterns helped the system to obtain greater potable

697

water savings potential.

698

The main conclusion is that stormwater harvesting systems

699

using pervious pavements can be profitable. For this, it is necessary to

700

be rigorous in the definition of pervious layers, preferring granular

701

layers to plastic components, to save money. Besides, it is

702

recommended a reasonable control of the compaction of the reservoir

703

layer, so that it has the porosity designed to store stormwater

704

temporarily.

705

As for sustainability, it was observed that the system saves more

706

energy than it consumes over the life cycle. However, due to the high

707

embedded energy in the system, mainly related to bituminous,

31 of 36

708

granular and plastic materials, it is impossible to ensure a negative

709

energy balance at the end of the life cycle. Further research on the

710

field, regarding other types of coating and models of layers, is

711

recommended to design more energy-friendly pervious pavements. It

712

was observed that the pavement subsystem energy and costs were

713

higher than any of the hydraulic components, which indicates that to

714

obtain profitability the pervious pavement has to be focused on cost

715

reduction and on LCEA.

716 717

Acknowledgements: The authors would like to thank CNPq, an

718

agency of the Brazilian government for technological and scientific

719

development, for the scholarship to Igor Catão Martins Vaz.

720

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ANAND, C.; APUL, D. S. Economic and environmental analysis of standard,

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Mitigadora da Impermeabilização do Solo Urbano. 2011. 256 p. Tese

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POLETO, C.; TASSI, R. Sustainable urban drainage systems. Drainage Systems. INTECH, p. 55-72, 2012.

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PRATT, C. J. Use of permeable, reservoir pavement constructions for

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stormwater treatment and storage for re-use. Water science and

832

technology, v. 39, n. 5, p. 145-151, 1999.

833

PROENÇA, L. C.; GHISI, E. Assessment of Potable Water Savings in Office

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RAMESH T.; PRAKASH, R.; SHUKLA, K.K. Life cycle energy analysis of

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838

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841

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842

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843

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844

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permeáveis e trincheiras de infiltração. Simpósio ABRH, Curitiba/PR, 10

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p., 2003.

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da

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nas/downloads.aspx#categoria_662>. Access on 25 jun. 2018.

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Serviços de Água e Esgoto - 2015. Ministério das Cidades, Brasília:

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Ministério das Cidades – SNSA, 2017.

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edificações residenciais brasileiras. Tese de Doutorado. Programa de

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857

Catarina. Florianópolis, 2006.

858 859 860 861 862 863

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869

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870

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1

Table 1. Main characteristics of the pervious pavement models used

Layer

Coating

Choker course Reservoir course Grit Geotextile

2 3 4 5 6 7 8 9 10 11 12

Acioli (2005) (Model 2) 7 cm 9.5 – 19 mm 5%

Pinto (2011) (Model 3) 5 cm 9.5 – 76 mm 4.5%

0.8

0.9491

0.881

3 cm 19 mm

-

LCCA/LCEA

Granite

-

LCCA/LCEA Sizing LCCA/LCEA LCCA/LCEA

37.5 mm 0.42 2

25.4 mm 0.36 1

5 cm Bituminous macadam 37.5 mm 0.253 5 cm 2

Usage

Thickness Aggregate size Binder % Available water coefficient Thickness Aggregate size

LCCA/LCEA LCCA/LCEA LCCA/LCEA Water savings potential LCCA/LCEA LCCA/LCEA

Materials Aggregate size Porosity Thickness Quantity

1 - The runoff coefficient was extrapolated through the results obtained by Acioli and Pinto. In their studies, they obtained the runoff coefficient by dividing the volume of water that became runoff to the total precipitated water. The available water coefficient corresponds to the amount of water that infiltrated the pavement in relation to the total volume of precipitated water, and therefore is available for use in the system; 2 - The value used in Hammes model was taken from the literature, which, according to the author, indicates values between 0.25 and 0.4; 3 - Pinto also indicates values between 0.25 and 0.4. The minimum value was chosen to obtain different results from Hammes model and understand how this impacts on the final result.

Table 2. Potable water consumption in the building over 2017

Initial date 01/01/2017 21/01/2017 21/02/2017 23/03/2017 21/04/2017 21/05/2017 21/06/2017 20/07/2017 20/08/2017 20/09/2017 19/10/2017 19/11/2017 21/12/2017

13 14

Hammes et al. (2018) (Model 1) 5 cm 4.8 – 9.5 mm 5%

Characteristic

Final date 20/01/2017 20/02/2017 22/03/2017 20/04/2017 20/05/2017 20/06/2017 19/07/2017 19/08/2017 19/09/2017 18/10/2017 18/11/2017 20/12/2017 31/12/2017

Water consumption (litres per day) 1,355 2,548 6,667 9,966 7,900 11,258 2,276 6,548 8,065 6,310 6,710 5,750 967

2 of 6

15

Table 3. Sizing the reservoir course using Hammes et al. (2018) method

Model Hammes Acioli Pinto

16 17

Reservoir course thickness (mm) Return period equal to 2 Return period equal to 5 Return period equal to 10 years years years 190.34 236.50 278.86 211.49 262.78 309.84 304.55 378.40 446.17 Table 4. Sizing the reservoir course using the envelope curve method

Model Hammes Acioli Pinto

Reservoir course thickness (mm) Return period equal to 2 Return period equal to 5 Return period equal to 10 years years years 201.49 250.31 295.31 223.88 278.12 328.12 322.39 400.49 472.50

18 19

Table 5. Final reservoir course thickness

Model Hammes Acioli Pinto

20 21

Final reservoir course thickness (mm) 440.00 470.00 590.00

3 of 6

22

Table 6. Data for LCEA of the pavement subsystem

Model

Hammes

Acioli

Pinto

Embedded Energy 2 7.0 GJ/m³

Layer

Quantity

Density

Asphaltic coating

75 m³

-

Chocker course

45 m³

2600 kg/m³ 6

1

0.15 MJ/kg

Reservoir course*

516 m³

2600 kg/m³ 6

1

0.15 MJ/kg

Geotextile Waterproofing plastic component** Asphaltic coating Chocker course

3000 m²

400 g/m²

4

95 MJ/kg

1594 m²

1000 kg/m³ 8

1

95 MJ/kg

105 m³ -

-

2

7.0 GJ/m³ -

Reservoir course*

561 m³

2600 kg/m³ 6

Geotextile Waterproofing plastic component** Asphaltic coating

1500 m²

400 g/m²

4

95 MJ/kg

1600 m²

1000 kg/m³ 8

1

95 MJ/kg

75 m³

-

5

6.5 GJ/m³

Chocker course

75 m³

2600 kg/m³ 6

1

0.15 MJ/kg

Reservoir course*

741 m³

2600 kg/m³ 6

1

0.15 MJ/kg

Geotextile Waterproofing plastic component**

3000 m²

400 g/m² 7

4

95 MJ/kg

1626 m²

1000 kg/m³ 8

1

95 MJ/kg

Grit

75 m³

1580 kg/m³ 9

1

0.15 MJ/kg

0.042 MJ/kg

3

23 24 25 26 27 28 29 30 31 32 33

Material Porous asphalt Aggregate (19.0 mm) Aggregate (37.5 mm) Geotextile High-density polyethene Porous asphalt Aggregate (37.5 mm) Geotextile High-density polyethene Porous asphalt Aggregate with bitumen dilute (0.8 l/m²) Aggregate (37.5 mm) Geotextile High-density polyethene Grit with diameter < 5 mm

* - The volume of the reservoir course was calculated as the multiplication of the base area by the average height of the pavement (average between the thickness with and without the inclination increase in height). ** - The area comprised by the waterproofing membrane is the sum of the base area (1500 m²) and the lateral areas (multiplication of the maximum floor depth height by the perimeter of 213 m). Source: 1 – Tavares (2006); 2 – Athena (2006); 3 – Falcão et al. (2013) apud Fundo Verde (2015); 4 – Lopes (2014); 5 – Based on Athena (2006); 6 - http://www.operaction.com.br/densidade-dos- materiais, access on June, 2018; 7 - http://diprotecgeo.com.br/blog/geotextil-naotecido-diferencas- entre-gramatura-e-resistencia-a-tracao/, access on July, 2018; 8 - http://www.neoplastic.com.br/documentos_ tecnicos/Manual_Geomembrana.pdf, access on July, 2018; 9 - http://www.pedreirasantocristo.com.br/produtos .html, access on June, 2018.

4 of 6

34

Table 7. Data for LCEA of the hydraulic subsystem

Model

Object Lower rainwater tank Upper rainwater tank

Hammes Acioli Pinto

35 36 37 38

Main drain Branched drains Suction pipe Pump pipe Fittings and components Water pump

Quantity 2 of 10,000 litres each 1 of 5,000 litres each 105 m 235 m 45 m 20 m 1/3 of the PVC pipes weight 2 of 1/2 HP each

Weight

Embedded Energy (MJ/kg)

Material

140 kg

24

GFRP

76 kg

24

GFRP

4.5 kg/m 1.5 kg/m 0.433 kg/m 0.3 kg/m

95 95 80 80

HDPE HDPE PVC PVC

-

80

PVC

4.02 kg/pump

31

Cast iron

Note: GFRP stands for Glass Fibre Reinforced Polymer; HDPE stands for High-Density Polyethylene; PVC stands for Polyvinyl Chloride.

Table 8. Data used for the LCEA

Data used for the LCEA

39 40

EEpav

Quantities and embedded energy of material described in Table 6.

EEhyd

Quantities and embedded energy of material described in Table 7.

Etranspav / Etranshyd

Quantities described in Tables 6 and 7. Distances of 3.5 and 12 km according to the material source. Energy consumption equal to 1.5 MJ/t.km due to the type of transportation used.

EEr

Replacement one time during the life cycle of the system. Embedded energy of pumps and fittings.

Epump

Power equal to ½ HP. Maximum pump flow equal to 2000 litres/hour. In use over 2.16 hours per workday, using 2017 data. In use over 2.33 hours per workday for the long-term time series data. 23 workdays per month, 12 months per year and 20 years in the life cycle.

EBhydro

Life cycle of 20 years. Conversion factor of 1.5. Index energy consumption of 0.4. Average annual consumption equal to 2,460 m³ for the long-term time series data, and 2,286 m³ for 2017 data. Potential for potable water savings differing according to the model and rainfall and consumption data used. Conversion factor equal to 3.6 to convert from kWh to MJ.

5 of 6

41

Table 9. Results for the LCEA

Rainfall data

2017

Long-term time series

Model

Energy values for each stage analysed (GJ) EEpav

Etranspav

EEhyd

Etranshyd

EEr

Epump

EBhydro

Efinal

Hammes

776.40

14.20

89.89

0.006

0.93

23.68

- 41.57

863.54

Acioli

891.00

15.86

89.89

0.006

0.93

23.68

- 43.03

978.34

Pinto

895.00

26.59

89.89

0.006

0.93

23.68

- 42.35

993.75

Hammes

776.40

14.20

89.89

0.006

0.93

25.49

- 39.39

867.53

Acioli

891.00

15.86

89.89

0.006

0.93

25.49

- 40.95

982.23

Pinto

895.00

26.59

89.89

0.006

0.93

25.49

- 40.29

997.62

42 43 44 45

Note: Efinal stands for final energy balance; EEmat stands for embedded energy; Etransmat stands for transport energy of the construction materials; EEr stands for recurrent embedded energy (MJ); EPumps stands for monthly energy consumption for pumping water (MJ); EBhydro stands for energy savings due to the decrease in the amount of treated water by the water utility over the entire life cycle (MJ).

46 47

Table 10. Initial costs for Hammes model

Model

Object

Quantity 2 tanks of 10,000 litres each

Unitary cost (R$)

Material

Cost (R$)

2,700.00 per tank

Glass Fiber

5,400.00

5,000 litres

1,300.00

Glass Fiber

1,300.00

105 m 235 m 45 m 20 m 1 unit 1 unit 3/4 HP

12.60 per metre 6.10 per metre 36.80 per 6 metres 10.60 per 6 metres 138.00 per unit 438.00 per unit 180.00 per unit

1,323.00 1,433.50 294.4 42.4 138 438 360

Asphalt coating

75 m³

586.85 per m³

Chocker course

75 m³

59.35 per m³

Reservoir course

516 m³

52.60 per m³

HDPE HDPE PVC PVC PVC PVC Cast iron Porous asphalt Aggregate (Size 1) Aggregate (Size 3) Geotextile

Lower rainwater tank

Hammes hydraulic subsystem

Hammes pavement subsystem

Upper rainwater tank Main drain Branched drains Suction pipe Pump pipe Solenoid valve Float-level Water pump

Geotextile 2 of 1,500 m² 3.00 per m² Waterproofing 1,594 m² 20.00 per m² plastic component Initial cost for Hammes model

48 49

HDPE

44,013.75 4,451.25 27,141.60 9,000.00 31,880.00 127,215.90

6 of 6

50

Table 11. Annual savings due to stormwater harvesting.

Rainfall data 2017

Long-term time series

Model Hammes Acioli Pinto Hammes Acioli Pinto

Potential for potable water savings (%) 42.09 43.57 42.88 37.07 38.54 37.92

Yearly benefit (R$) 9,687.73 10,016.77 9,863.49 9,251.72 9,608.16 9,457.94

51 52 53

Table 12. NPV and IRR of each model and data analysed.

Data 2017

Long-term time series

54 55 56

Model

NPV (R$)

IRR (% per year)

Hammes

-45,654.08

2.41

Acioli

-54,329.70

1.90

Pinto

-67,445.34

0.94

Hammes

-50,234.43

1.84

Acioli

-58,628.59

1.39

Pinto

-71,713.82

0.45

Table 13. Initial costs of a non-pervious pavement

Layer

Thickness

Quantity

Unitary cost (R$)

Material

Cost (R$)

Asphalt coating

5 cm

75 m³

586.85 per m³

Porous asphalt

44,013.75

Base

15 cm

225 m³

130.11 per m³

Crushed stone

29,274.75

Sub-base

15 cm

225 m³

43.37 per m³

Stabilized soil

57 58 59

Table 14. NPV, IRR and discounted payback for all models and rainfall data

Rainfall data 2017

Long-term time series

60

9,758.25 83,046.75

Initial cost of a non-pervious pavement

Model

NPV (R$)

IRR (% per year)

Discounted payback

Hammes

37,392.67

16.41

7 years and 10 months

Acioli

28,717.05

13.13

10 years and 3 months

Pinto

15,601.41

10.12

13 years and 10 months

Hammes

32,812.32

15.39

8 years and 5 months

Acioli

24,418.16

12.32

10 years and 1 month

Pinto

11,332.93

9.39

15 years and 1 month

Average monthly consumption (litres)

450000 400000 350000 300000 250000 200000 150000 100000 50000 0

1 2 3

Jan

Feb

Mar

Apr May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Figure 1. Minimum, maximum and average monthly water consumption in the building over 2011‒ 2017.

Monthly rainfall (mm)

4

5 6 7

600 550 500 450 400 350 300 250 200 150 100 50 0

179

163 121

174 120

98 52

Jan

Feb

Mar

Apr

May

Jun

74

Jul

96

Aug

121

Sep

126

Oct

Nov

141

Dec

Figure 2. Minimum, maximum and average monthly rainfall in Florianópolis between 2003 and 2012.

2 of 3

120

Rainfall (mm/day)

100 80 60 40 20 0

8 9

Figure 3. Daily rainfall in Florianópolis in 2017.

50000

47500

45000

42500

40000

37500

35000

32500

30000

27500

25000

22500

20000

17500

15000

12500

10000

7500

5000

2500

55 50 45 40 35 30 25 20 15 10 5 0 0

Potential for potable water savings (%)

10

Lower rainwater tank capacity (litres) Hammes

11 12 13

Pinto

Acioli

Figure 4. Potential for potable water savings for the three models considering rainfall over 2017.

Pinto

21

50000

47500

Acioli

Figure 5. Potential for potable water savings for the three models considering a long-term rainfall time series.

17 18

19 20

45000

42500

40000

37500

35000

32500

30000

27500

25000

22500

Lower rainwater tank capacity (litres) Hammes

14 15 16

20000

17500

15000

12500

10000

7500

5000

2500

55 50 45 40 35 30 25 20 15 10 5 0 0

Potential for potable water savings (%)

3 of 3

Figure 6. Cross section of Hammes model with reservoir course sized.

Highlights:

Stormwater was assessed to be harvested for non-potable uses in a public building. The hydrological-hydraulic design of the reservoir course was assessed. The pervious pavement system was economically feasible compared to a non-pervious one

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: