lecture: advanced environmental assessments · industrial wastewater treatment, task 4: stefanie...

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Case Study

22.12.2016 Stefanie Hellweg 1

Lecture:

Advanced Environmental Assessments


• Deepening the knowledge achieved in the lecture by looking at the

application in a case study

• Exam preparation… case study is one example of how an exam is

structured


Learning goals

| | www.ifu.ethz.ch/ESD 22.12.2016 Stefanie Hellweg 3

Case studies

Methodological issues that will be discussed:

• Basic methodology (functional unit etc.)

• Allocation

• Impact assessment of toxic releases

• Regionalization

• Data quality, uncertainties, transparency

• Optimization


Purification of 1 m3 of wastewater with the below pollutant

concentrations; the quality of the treated water must fulfill the regulations.

Industrial Wastewater treatment, task 1:

functional unit


TOCtotal Ntotal Cutotal PO43-

1 g/L 0.1 g/L 0.02 g/L 0.001 g/L


Industrial Wastewater treatment, task 2: ISO


Slide Rolf Frischknecht, lecture on allocation


Industrial Wastewater treatment, task 2: avoided

burden allocation (system expansion)


- Wastewater system 1


Industrial Wastewater treatment, cut-off

approach


• All emissions and resource uses are allocated fully to the service

„wastewater treatment“

• Generated steam/heat and ammonia solution are free of

environmental burden (consumers of these products benefits from

this allocation)



system division



• Foreground data sources: primary data e.g. from monitoring water

emissions; wastewater treatment plant operator; accounting

department; sustainability department (e.g. energy demand); plant-

internal documentation (e.g. Wastewater treatment cards); etc.

• Background data: LCI process databases; Input/output databases;

literature; own research


inventory data





Influent pollutant amount per m3:

1 kg TOC

0.02 kg Cu

System 1:

Outflow: 1 kg TOC/m3 * 5% = 0.05 kg TOC/m3

0.02 kg Cu * 7% = 0.0014 kg Cu/m3

AETP (TOC) = 0.05 kg TOC/m3 * 10 kg 1,4 DCB-eq/kg TOC = 0.5 kg 1,4 DCB-eq

AETP (Cu) = 0.0014 kg Cu/m3 * 6.9 kg 1,4 DCB-eq/kg Cu = 0.00966 kg 1,4 DCB-eq.

System 2:

Outflow: 1 kg TOC/m3 * 10% = 0.1 kg TOC/m3

0.02 kg Cu * 13% = 0.0026 kg Cu/m3

AETP (TOC) = 0.1 kg TOC/m3 * 10 kg 1,4 DCB-eq/kg TOC = 1 kg 1,4 DCB-eq

AETP (Cu) = 0.0036 kg Cu/m3 * 6.9 kg 1,4 DCB-eq/kg Cu = 0.01794 kg 1,4 DCB-eq.


Regionalization necessary?



Uncertainties background data



If many data points available…

Statistical fitting of distribution functions

Rela

tive f

requency

2 ^

e.g. Maximum Likelyhood

estimation of parameters

For a Normal distribution:

Fitting is most desirable procedure … but often

there is not enough data available

Goodness of fit test (e.g. Kolmogorov-Smirnov or Chi-Square)


Example procedure for parameter estimation,

assuming log-normal distribution


2

2( ) 95%

g

g g

g

p X

If only typical value and a maximum and/or minimum value is known:

typical value is assumed to be the geometric mean

Maximum and minimum values are used to estimate the geometric

standard deviation:

If enough data is available:

Calculate geometric mean and standard deviation


Reliability verified data data on the basis estimations

of assumptions

Completenes representative data with large gaps

data

Temporal < 3 years < 10 years unknown, > 15 Jahre

correlation

Geographical Data from the same Data from similar Daten from unknown

correlation location location or other location

Technical Data from same company Data from similar

correlation process/material process

Data quality characterization according to Pedigree approach

Paramter estimation if only one value is available

Quelle: Weidema et al. 1996, Journal of Cleaner Production 4(3-4) Lecture slides class onuncertainty


Translation of Pedigree indicators into

parameter values of lognormal distribution

2 2 2 2

1 2 62 2 2 2

2 2 2 2 2 2 2

1 2 6

2 2 2 2 2 2 2

1 2 6

log( ) log( ) log( ) log( )( ) ( ) ( ) ... ( )

2 2 2 2

log( ) (log( )) (log( )) ... (log( ))

exp( (log( )) (log( )) ... (log( )) )

g g g g

g g g g

g g g g

Lecture slides class onuncertainty


Monte-Carlo Simulation


0.01

0.1

1

10

100

median

75th

25th

95th

5th

97.5th

2.5th

percentiles

Iterations (often several

thousands); picking one

value of each uncertain

parameter per iteration

(according to probability

distribution)

Lecture slides class onuncertainty


Optimization


Cumulative

tributary

wastewater (ww)

flows

Production facilities

Product isolation: filter presses

WW 1 WW 2 WW 3 WW 4

EL: > 90%pH: 2-5

EL: < 90%TOC: < 15 g/LpH: 2-6

EL: < 90%TOC: > 15 g/LpH: 8-9Cutotal < 9.5 g/m3

EL: < 20%pH: 8-9product-specific composition


Product isolation: filter presses and membrane filtration

Mechanical-biological wastewater

treatment (MBTP)

Cumulative

tributary

wastewater (ww)

flows

WW 1

Reverse osmosis (RO)

P: 25 bar; pH: ~ 7

Cut-off: 200 g/mol

Extraction (EX)

pH: 2-4

WW 2 WW 4

Sludge

incineration

(SI)

WW 3

EL: > 90%pH: 2-5

EL: < 20%

pH: 8-9

product-specific composition

EL: < 90%

pH: 2-6

EL: < 90%

pH: 8-9

System 1: end-of-pipe system System 2: process-integrated system


treatment (MBTP)

High-pressure wet -air

oxidation (WAOP)

T: ~280°C; P: 140 bar

TOC: 15-30 g/L; pH: 3


P: 25 bar; pH: ~ 7

cut-off: 200 g/mol

Extraction (EX)

pH: 2-4

Sludge

incineration

(SI)

RaffinateExtractConcentrate

Permeate

Raffinate

Extract

TOC: ~100 g/LConcentrate

TOC: ~100 g/L

Permeate

TOC: ~50 g/LTOC: ~15 g/L

Cumulative

tributary

wastewater (ww)

flows


Product isolation: filter presses

WW 1 WW 2 WW 3 WW 4

EL: > 90%pH: 2-5

EL: < 90%TOC: < 15 g/LpH: 2-6

EL: < 90%TOC: > 15 g/LpH: 8-9Cutotal < 9.5 g/m3

EL: < 20%pH: 8-9product-specific composition


Product isolation: filter presses and membrane filtration


treatment (MBTP)

Cumulative

tributary

wastewater (ww)

flows

WW 1


P: 25 bar; pH: ~ 7

Cut-off: 200 g/mol

Extraction (EX)

pH: 2-4

WW 2 WW 4

Sludge

incineration

(SI)

WW 3

EL: > 90%pH: 2-5

EL: < 20%

pH: 8-9

product-specific composition

EL: < 90%

pH: 2-6

EL: < 90%

pH: 8-9

System 1: end-of-pipe system System 2: process-integrated system


treatment (MBTP)

High-pressure wet -air

oxidation (WAOP)

T: ~280°C; P: 140 bar

TOC: 15-30 g/L; pH: 3


P: 25 bar; pH: ~ 7

cut-off: 200 g/mol

Extraction (EX)

pH: 2-4

Sludge

incineration

(SI)

RaffinateExtractConcentrate

Permeate

Raffinate

Extract

TOC: ~100 g/LConcentrate

TOC: ~100 g/L

Permeate

TOC: ~50 g/LTOC: ~15 g/L

At this plant:

• Approx.100 products

• with 1000 wastewater

streams (varying

composition)

• > 500,000 m3/yr


Optimization


environmental impact 1

Objective: Min Z = environmental impact 2

cost

Subject to:

• Fulfilling demand (treating all wastewaters)

• A given module network structure

• Treatment efficiency of each module

• Capacity constraints treatment modules

• Meeting pollution limits for each wastewater stream

lecture: advanced environmental assessments · industrial wastewater treatment, task 4: stefanie...

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