Alternative decentralized water sources – Opportunities ... · Alternative decentralized water...

Eran Friedler

Faculty of Civ. & Env. Eng.

The Grand Wat. Res. Inst.

Technion – Israel Inst. of Technol.

Alternative decentralized water sources – Opportunities and

challenges

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• Opportunities

• Risks / Real world

• System approach

• Rainwater Harvesting

• Stormwater Harvesting

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Water ReuseDecentralised vs. Centralised

Water ReuseDecentralised vs. Centralised

Urban Areas

1. Toilet flushing

2. Landscape irrigation

3. Garden farming (urban agriculture)

↸Short reuse cycle

↸

Long reuse cycle

WWTP

Arg. Irrig

Rural Areas

1. Landscape irrigation

2. Garden farming (1 - poor areas)

3. Toilet flushing

Centralised Decentralised

Laundry; Dishwashing; Car washing; Fire-fighting; Cleaning streets. . .

?

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WW / GW / BW ?

Urban water demand

Domestic consumption Other uses

Greywater Blackwater

~70 % ~30 %

LGW DGW

Bath

Shower

Washbasin

K. Sink

Dishwasher

W. Machine ?

Potential reduction

GWR (Toilet) ~ 30%

GWR (Toilet & Garden) ~ 40%

10-20% of Urban water demand

~2/3 ~1/3

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Typical installation in a multi-storey building

Taken from: Gross et al. (2015)5

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0

200

400

600

800

1000

1200

1400

1600

2012 2020 2030 2050

ממל

" ש

עירוני

MC

M

Growth rate of urban water demand in Israel

Italy ~ 0.3

1.8

6

34

0

200

400

600

800

1000

1200

1400

1600

2012 2020 2030 2050

ממל

" ש

עירוני

עירוני עם מיחזור

GWR can slow -down the growth rate of urban water demand - Opportunity

GWR can slow -down the growth rate of urban water demand - Opportunity

2050 – 30% penetration (only buildings built after 2012)

Urban Demand

Urban Demand with

GWR

140 MCM

(Averted Desalination)

140 MCM

(Averted Desalination)M

CM

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• Opportunities


• System approach



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Potential impacts of GW reuse

GW contains elevated levels of:

� COD (organic matter); MPs

� Surfactants

� Salts (Na, EC, SAR)

� Boron (in some cases)

� FC (~105 cfu/100 ml); HPC (~107 cfu/ml)� Pathogens (bacteria, viruses, protozoa ..)

� Skin and mucous tissues� Faecal� Food handling

Close proximity between the reused GW & the public

Sanitary quality of GW is very important !9

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Treatment Technologies – RequirementsTreatment Technologies – Requirements

GW is polluted - Barrier

• Sanitary quality (public health )

• Aesthetic quality (public acceptance )

• Eliminate negative Environmental effects

Requirements from treatment technologies (Solution) :

• Efficiency

• Reliability

• Safety

• Reasonable O&M (technical & economical)

Treatment

of

“Light” GW

!

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FC S. a.

P. a.HPC

0.0

0.5

1.0

1.5

2.0

2.5

0.5 3 6

Contact time (h)S

. au

reu

s (C

FU

/100

ml)

Residual chlorine 0.5 mg/l Residual chlorine 1.0 mg/l

BD BD

D

0

20

40

60

80

100

120

0.5 3 6

Contact time (h)

P. a

eru

gin

osa

(C

FU

/100

ml)


C

0

1

2

3

4

5

6

0.5 3 6

Comtact time (h)

FC

(CF

U/1

00m

l)


BD

A

0

200

400

600

800

1,000

1,200

0.5 3 6

Contact time (h)

HP

C (C

FU

/1m

l)


B

RBC effluent along the reuse system

% ZeroFRT - Flow regulation tank

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RiskIdentification

Exposureassessment

Dose-ResponseModel

RiskCharacterisation

RiskManagement

Risk Assessment – QMRA(Quantitative Microbial Risk Assessment)

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Risk IdentificationSingle family �� Multi family home

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Single family home Multi family home

Exposure Routes Various Especially viagreywater

Vector of disease Low High

“import-export” - +

Toilet Flushing

1. Splashing

2. Aerosols

3. (Cross connections)

Garden Irrigation

1. Splashing (large volumes)

2. Punctures (irrigation equipment)

3. Miss-use

4. (Cross connections)

Risk IdentificationRisk Identification

Inhalation / ingestion of small droplets

Body contact / ingestion

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Frequency(event/y)

Volume(ml/event)

Exposure scenarios

1100Accidental ingestion

37 Days(300 h/y)

1Routine ingestion from touching plants & lawns

0.1Ingestion of sprays from irrigation system

5 Days(60 h/y)

10-100 mgIngestion of soil contaminated by GW

0.36 - 10.8Eating home-grown plants that was exposed to GW

Exposure Assessment

• Literature (volumes)• Questionnaires (frequencies)16

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Dose Response Model

Probability of infection vs. Pathogen concentration

Haas’s beta-poisson dose-response

d - Pathogen dose

Pi(d) - Probability of infection

N50 - Dose at which 50% of the population is infected

α - Infectivity constant (pathogen specific)

Pi(A)(d) - Annual risk of infection

n - Number of exposure events per year.

Pi(d)=1-[1+( d/N50)(21/α-1)] –α

Pi(A)(d) =1- [1- Pi(d)] n

For Rotavirus:

α=0.253, N50=6.17

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Rotavirus - Probability of infection (Based on E. Coli conc. Found in real

systems) & 37 exposure days (questionnaires)

Risk characterisation

Average probability of infection (annual)

Daily volume exposure

E. coli

~ 105

]cfu/100ml[

E. coli

~ 102

]cfu/100ml[

0.01 ml 2.5 ·10-3 5.8·10-6

0.1 ml 2.1·10-2 5.8·10-5

1 ml 1.0·10-1 5.8·10-4

50 ml (single event) 1.1·10-1 8.0·10-4

100 ml (single event) 1.4·10-1 1.6·10-3

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skin S. aureus: Cumulative probability for 3Figure infection based on increasing exposure time and exposed body area to water containing the average concentration

found in the survey (1.2 x 103 CFU 100 mL-1)

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What happens in reality?

Are there evidencesof

“ill GW users”?20

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GW reuse for garden irrigation posed no additional health risk21

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75 p.(20 fam.)

73 p. (17 fam.)

• Opportunities


• System approach



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B1012

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1640

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1504B

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1506

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1014

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9

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23040

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2306

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270

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3040

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Subsystem_38

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Subsystem_3086

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Subsystem_308

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Subsystem_3046

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Subsystem_3042

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Subsystem_3040

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Subsystem_304

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Subsystem_270

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Subsystem_2306

In1

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Subsystem_23040

In1

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Subsystem_23

In1

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Subsystem_17

In1

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Subsystem_168

In1

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Subsystem_1640

In1

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Subsystem_1594

In1

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Subsystem_159

In1

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In1

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In1

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In1

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Subsystem_1504B

In1

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In1

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Subsystem_1014

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Subsystem_101

Rain_speci fic9'rainzero. rain'

Rain_specifi c8'rainzero.rain'

Rain_speci fic7'rainzero.rain'


Rain_specif ic5' rainzero.rain'

Rain_specif ic4'rainzero. rain'


Rain_specifi c33' rainzero.rain'

Rain_specif ic32'rainzero.rain'



Rain_specif ic3' rainzero.rain'


Rain_specifi c28'rainzero. rain'






Rain_specifi c21' rainzero.rain'






Rain_speci fic16'rainzero.rain' Rain_speci fic15

'rainzero.rain'







Rain_speci fic' rainzero.rain'

Dry_Specif ic_ru_wc_irr9






Dry_Speci fic_ru_wc_irr34





Dry_Specifi c_ru_wc_i rr3 Dry_Specif ic_ru_wc_irr29


Dry_Specifi c_ru_wc_irr26









Dry_Specif ic_ru_wc_irr18Dry_Specif ic_ru_wc_irr17

Dry_Speci fic_ru_wc_irr16Dry_Specif ic_ru_wc_irr15



Dry_Specifi c_ru_wc_irr12




Dry_Specif ic_ru_wc_irr

Dry_Specif ic_ru_wc9

Dry_Specifi c_ru_wc8

Dry_Speci fic_ru_wc7









Dry_Specifi c_ru_wc3 Dry_Specif ic_ru_wc29











Dry_Specif ic_ru_wc18Dry_Specifi c_ru_wc17

Dry_Specif ic_ru_wc16 Dry_Specifi c_ru_wc15







Dry_Specif ic_ru_wc

Dry_Specifi c_no_ru9


Dry_Specif ic_no_ru7





Dry_Speci fic_no_ru33




Dry_Specif ic_no_ru3 Dry_Speci fic_no_ru29











Dry_Specif ic_no_ru18Dry_Specifi c_no_ru17

Dry_Specifi c_no_ru16 Dry_Specif ic_no_ru15







Dry_Specifi c_no_ru

1

320

In1

In2

In4

In6

Out1

Subsystem_320

Rain_specific'rainzero.rain'

Dry_Specific_ru_wc_irr

Dry_Specific_ru_wc

Dry_Specific_no_ru

320

312

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3086

3082

304

3046

3042

3040

4

38

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27

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2306

23040

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9

1014

1506

1504B

150

168

1640

159

1594

153

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B1012

INFLOWS

1

Out1

(4+0) ha(0+0) l/s

ru_wc_irr

(4+0) ha(0+0) l/s

ru_wc

(4+0) ha(0.35139+0) l/s

no_ru

4

In6

3

In4

2

In2

1

In1

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• Opportunities


• System approach



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Study area (Haifa – Israel)

Dry period 151 d (105-220)

Rainy season

• Rainfall – 538 mm/y (292-925)

• 50 (rainy d)/y (35-69)

• Time between consecutive events

– 4.1 d (S.D. 6.2)

– Median 1 d

– 75% ≤ 5 d

• 151dry days (105-220)

Rain is highly stochastic - challenge

� � � ��

�

� � �� 27

34

Main Algorithm for Vmax calculation

Rain

Roof runoff

Mass balance

Vmax

• Daily time-steps• Random simulations• 100 y

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Model Input

• Roof type: Concrete, Steel-sheets, Tiles

• Roof size: 75, 100, 150, 200, 400 m2

• No. of residents: 4, 8, 12, 24, 48, 64

• Water demand: 68 L/(c·d) (44% of in-house demand)

WC 55 L/(c·d)

WM 13 L/(c·d)

Roof type aL/(mm ·m2)

bl/(m2·d)

R(y=0)*

mmn**

Concrete 0.78 -1.8 2.3 47Steel sheets 0.80 -0.033 0.041 45Tiles 0.91 -0.34 0.37 36

��

�� !

�� ∙ #$%& � ��29

34

Maximum storage tank volume

RUE = 100%100 stochastic simulation runs

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WSE• Increases with roof A• No sig. diff. V = 0.3-0.9 ˣ Vmax

• More peopleLower WSE

RUE• Decreases with Roof A• More sensitive to V• More people � Higher RUE

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My current research

� A multi-objective LCA-based model for sustainabilit y assessment of

urban water reuse alternatives of varying centralis ation scales

� Impacts of onsite greywater reuse on urban wastewater systems

� Personal care products (PCPs) as source for micropo llutants in

Greywater – Identification, quantification and on-si te treatment

(biological + UV-AOP)

� Urban stormwater harvesting & reuse

� Atmospheric moisture harvesting

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Website: http://www.technion.ac.il/~civil/friedler/

Email: [email protected]

Thank you for

your attention

Special thanks to my Collaborators, Students

… and Funders

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Alternative decentralized water sources – Opportunities ... · Alternative decentralized water...

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