Institute for Water Quality, Resources and Waste Management

The Methodology of MFA -

Case Studies

Paul H. Brunner

Vienna University of Technology

Institute for Water Quality, Resources and Waste Management

http://www.iwa.tuwien.ac.at

Content

1. Motivation

2. Definitions and STAN 3. Scale

4. Applications

5. Integration of MFA in governance

Vision and Motivation

1. Sustainable development:

- long term environmental protection - „best“ resource use

- „utility and happiness forever“

2. How to measure and to achieve SD?

3. MFA as a key method in the tool box for SD 4. The two aspects: goods and substances

- goods as economic units (quantity)

- substances determining ecological and resource qualities

MFA definitions

• Goods and substances

• Processes and stocks

• Flows and fluxes

• Transfer coefficients

• System and system boundaries

Most simple case of MFA: 1-process system

A

B

C

D s + Δ ^s

systems boundary

Process

wwtp

landfill agr. soil

plant cultivation

industry private hh

fertilicer

animal feedstock

industrial products surface water

river

sewer animals

atmosphere

flow = 230 t/a export = 170 t/a

food cleaners

meat, milk, eggs

cereals

vegetables, fruits

surface water

food 10 000+68

74

>40

17 17

?

30

24 85

3

21 13

19 45

>61

100 109

? 17

38 28

78

phosphorous [t/a]

stock 10.000 + 70 t/a

10-process system „regional phosphorous flows and stocks“

Procedure to establish MFA

Problem definition

Interpretation and illustration Selection of

substances

Determination of system boundaries Selection of

processes Selection of goods

Adjustment System definition

Adjust sy ste m Determination of

mass flows

Balancing of goods

Determination of concentrations

Balancing of substances Determination of

flows and stocks

1. R e fi n e concent ra tions

2. Refine mass f lo w s 1. R e fi n e mass f lo w s 2. Redetermine goods Redefine p roblem

STAN freeware to support MFA including uncertainty

STAN:

http://www.iwa.tuwien.ac.at/iwa226_english/stan.html

composting plant.mfa

STAN allows modelling more complexe systems such as wm

Scale: from human to …

50 100

450

270

human body 1700

390

food

400

20

700

0

respiration transpiration

feces

urine

sewage

mass [kg/c.a]

phosphorus [g/c.a]

Scale: from human to household to …

50 100

450

270

human body 1700

430

total food wastes to sewering

system kitchen

food

100 40

400 20

900

390

700 0 respiration

transpiration

feces

urine

garbage sewage

to MSW treatment

to STP mass [kg/c.a]

phosphorus [g/c.a]

systems boundaries: phh/ 1year

Scale: from human to household to regional to…

wwtp

landfill agr. soil

plant cultivation

industry private hh

fertilicer

animal feedstock

industrial products surface water

river

sewer animals

atmosphere

flow = 230 t/a export = 170 t/a

food cleaners

meat, milk, eggs

cereals

vegetables, fruits

surface water

food 10 000+68

74

>40

17 17

?

30

24 85

3

21 13

19 45

>61

100 109

? 17

38 28

78

phosphorous [t/a]

stock 10.000 + 70 t/a

Scale: from human to household to regional to national to…

[kg/c.a]

5 1

4 0,6 0,4

agriculture food 0,4 processing

agricultural losses and wastes

food processing wastes

private household

sewage

and MSW

systems boundaries: region/1year

A: direct and indirect inputs of animal waste products, B: erosion and leaching

C: direct flows from private households and industry D: diffuse inputs from forestry (erosion, percolation),

Contribution of various sectors to the nu- trients in the river Danube watershed

Scale: from human to household to regional to national to watershed…

Ismail Tirgu Mures

Kosice

Novi Sad Osijek

Nis Klagenfurt

Insbruck

Gyor

Szombathely

Rijeka

Split

Constanca

Varna Craiova

Cluj-Napoca

Brasov

Ploesti Braila

Galat Iasi Tchernovte

Miskolc

Debrecen

Oradea

Arad Szeged

Pecs

Zagr eb Ljubljana

Sarajevo Bratislava Brno

Linz Regensburg

Augsburg

Munchen

Szekesfehervar Graz

Salzburg

Sofia

Bucuresti Budapest

Wien

Beograd Praha

Trnava

Nitra Trencin

Prievidza Banska Bystr ica Zilina

Mart in

Prasov

Levice PiestanyTopolcany

Povazska Bystrica Liptovsky Mikulas

Zvolen Spisska Nova Ves

Bardejov

Humenne

Michalovce

Komarno

BM3

BM9

BM1 BM4

BM8 BM25

BM5 BM2

BM38 BM16

BM35 BM36

BM37 BM22BM23

BM15 BM19

BM10

BM14

BM18

BM21 BM12

BM24 BM11BM17 BM28

BM26 BM29

BM32 BM31

BM27 BM33

BM13

BM34 BI1

BI2 BI3

BI4 BI5

BI9

BS334 BS147 BS336 BS17

BS335 BS337

BS175BS18 BS342

BS346 BS345 BS344 BS178 BS339 BS27 BS348

BS32 BS197

BS37 BS30

BS191 BS29 BS190 BS28

BS189

BS25 BS355 BS40 BS39

BS201

BS33 BS352 BS198 BS194

BS199 BS198

BS45 BS206

BS44 BS43

BS42 BS205BS206

BS51 BS360 BS358

BS53 BSBS4

BS220 BS270 BS49 BS216 BS210

BS209 BS208

BS234 BS232 BS364BS363

BS56 BS230231BS229 BS55BS228

BS361

BS182

BS347 u61 u62

u59 u48

u58 u57 u56

u55

u47 u46

u45 u71

u54 u53

u52

u44u50

u49u65

u70 u69 u66

u67

u64 BeregovoVinogradov

Vilok Khust Ir shava

Mezhgorie Svalyava

VishkovoTyachev Chop

Solotvina V.Bychkov Rakhov Dybovoe

Kolomia

Yaremcha Kosov

Snyatin

Storozhinets Mukachevo

Uzhgorod CM4

CM7

CM43 CM30 CM36CM38 CM34

CM18 CM29 CM31CM22

CM35 CM9

CM26 CM23

CM2

CM5

CM0 CM17 CM28

CM33

CM32

CM8 CM25

CM14CM11 CM23 CM46 CM21CM45 CM40 CM44CM13CM42CM27 CM39 CM6

CM41 CM19

CM15CM20

CM10

CM3 CS3545 CS3639 CS1132

CS1133 CS1134

CS1171 CS3670

CS1169 CS1135

CS1174

CS1139 CS1140 CS1195 CS1188 CS1187 CS1186

CS1194 CM1191

CS3742 CS1181

CS1179 CS1184 CS1176

Kranj Maribor

Celje Jesenice

Skofja LokaDomzale Trbovlje Velenje

Novo Mesto Ptuj Murska Sobota

S1

S2 S3 S4S5

S6 S7 S8

S9 S10

S11S12

S13

m1

m2 m3 m4

m5

m6

m7

m8

m9

m10

m11

m12

m13 m14

m15 Bziceni

Ocnita

Edinet

Geodeni

Falesti

Ungheni

Nisporeni

Carpineni

Leova

Comrat

Congaz Ciadiz-Lunga

Taraclia

Vulcanesti Cahul

BenderTiraspol Belti

Kishinev A326A323A322

A324 A321

A522 A521

A721 A723

A724 A621

A821 A923

A924 A1024

A921A922A1023 A1025

A1026 A1021

A1121

A1022 A1031 A1029 A1028 A1027 A1030 A1032A1221A1321

A1428 A1414 A1427

A1424 A1422 A1421 A1426 A1425

A1528 A1524 A1526 A1527 A1525 A1523 A1522 A1521

A422 A423

A722

A421

A1222

A/ 73100007 A/ 73200417

A/ 73200617 A/73300407

A/ 75000987 A/40502037

A/40502017 A/ 4041017

A/54110127 A/5411057

A/54110017

A/51210147 A/73390966

A/40607017

A/ 40607027 A/ 40709117

A/40709077 A/40709067 A/ 40709047

A/40709037 A/ 40709027

A/40710027 A/ 40710017

A/ 40907037 A/40814047 A/ 30900057

A/ 30900047 A/30900027 A/30900017

A/ 92001017

A/31000017A/31000027 A/ 31100047 A/31100057 A/ 31100037

A/ 31200037 A/ 10000077 A/ 10000027

A/10000107 A/10000097 A/10000087

A/ 61400147 A/61400137 A/61400127 A/ 61400117 A/ 61400107

A/ 61400087 A/61400157

A/21560297 A/ 21500087 A/ 21551267 A/ 21551257

A/21500057 A/21530157 A/ 21500047 A/ 21500027 A/ 21510107 A/71560907

BUDAPEST1

BUDAPEST2 BUDAPEST3

DEBRECEN MISKOLC

SZEGED

PECS GYOR

NYIREGYHAZA1 NYIREGYHAZA2

SZEKESFEHERVAR

KECSKEMET SZOMBATHELY

SZOLNOK TATABANYA

KAPOSVAR

BEKESCSABA VESZPREM

ZALAEGERSZEG

EGER

DUNAUJVAROS SOPRON

NAGYKANIZSA HODMEZOVASARHELY

ERD SALGOTARJAN

OZD

BAJA CEGLED

SZEKSZARD

KAZINCBARCIKA

GYONGYOS

PAPA VAC

GYULA AJKA

KISKUNFELEGYHAZA SZENTES

HAJDUBOSZORMENY MOSONMAGYAROVAR1

MOSONMAGYAROVAR2

GODOLLO JASZBERENY ESZTERGOM

KOMLO

OROSHAZA DUNAKESZI

NAGYKOROS VARPALOTA

MAKO

TATA HATVAN

TOROKSZENTMIKLOS HAJDUSZOBOSZLO

KARCAG

BEKES BUDAORS

OROSZLANY SZENTENDRE

SZIGETSZENTMIKLOS

DOMBOVAR

MOHACS KOMAROM

PAKS

MEZOTUR

CSONGRAD HAJDUNANAS

MONOR

TAPOLCA GYAL

SZARVAS MATESZALKA

BALMAZUJVAROS BALASSAGYARMAT

SATORALJAUJHELY

TISZAUJVAROS

KALOCSA VECSES

KISVARDA

MEZOKOVESD

SZAZHALOMBATTA BERETTYOUJFALU

GYOMAENDROD SARVAR

ABONY BATONYTERENYE

DUNAHARASZTI

DABAS

SAROSPATAK

BONYHAD MOR

FOT TISZAFURED

TISZAVASVARI

GOD

SAJOSZENTPETER

SARBOGARD

NYIRBATOR

PUSPOKLADANY DOROG

KISUJSZALLAS POMAZ

KORMEND

HAJDUHADHAZ

MARCALI

NAGYATAD

BARCS

GYOMRO

TOLNA NAGYKATA

CELLDOMOLK PILISVOROSVAR

KOSZEG

TISZAKECSKE BUDAKESZI

HEVES

TISZAFOLDVAR

MEZOBERENY BICSKE

SZIGETVAR PECEL

SARKAD LAJOSMIZSE KAPUVARCSORNA

ALBERTIRSA

SIKLOS PASZTO

TURKEVE SZERENCS

KUNSZENTMARTON EDELENY

UJFEHERTO

SZIGETHALOM

SZEGHALOM BUDAPEST, CANNING-BREWERY BUDAPEST,PAPER

TISZAUJVAROS, CHEMICAL KAZINCBARCIKA, CHEMICAL

DUNAUJVAROS, PAPER DUNAUJVAROS, METALLURGICAL ALMASFUZITO, CHEMICALLABATLAN, PAPER

MARCALI, LEATHER BALATONFUZFO, CHEMICAL

PET, CHEMICAL

PECS, LEATHER 01FF01

01FF02 01FF0701FF04

02FF51

02FF02

02FF32

03FF06

03FF05

03FF07

03FF01 01FF13

01FF11

01FF22 01FF12

02FF17

02FF03

06FF27

04FF11 04FF14

02FF12 01FF62

01FF40 01FF38

05FF18 06FF23

07FF01 07FF04

07FF05

08FF02

08FF04

10FF02

10FF04

10FF12

10FF14

11FF11

11FF12

07FF10

07FF11 07FF29

08FF07

09FF03 08FF15

10FF22

11FF63

11FF32 CID

CIC CIB CIE

CIA

BUDAORS, CHEMICAL

CM12 CM47

PECS, LEATHER A711A713

A712

A311 A411

A1111 A1112

A1012

A1413A1411 A1414

A1412 A1416

A1311 A1313 A1312 A913 A912 A612

A611 A911

BUDAORS, CHEMICAL

PET, CHEMICAL

BALATONFUZFO, CHEMICAL

MARCALI, LEATHER DUNAUJVAROS, PAPER CIECIB

CIA

CID CIC

BI4 BI1

BI3 BI2

BI5 BI9 TISZAUJVAROS, CHEMICAL

KAZINCBARCIKA, CHEMICAL

Phosphorus

105 kt/a

Nitrogen

825 kt/a

agriculture WWTP

others

agriculture WWTP

others

MFA for environmental protection and resources management

1st generation MFA: Environmental protection

• DDT

• CFCs

• PCBs, NP etc.

• C -> CO ₂ and CH ₄

MFA for greenhouse gas emission assessment

fossil

biogenic Energy from …. sources

CO ₂ from …. sources

fossil biogenic

Concept of Balance Method

Operating data from WTE plant

Waste input, flue gas volume, CO2, O2, steam production

Material data of waste input

Biogenic matter C, H, O, N, S, Cl Fossil matter C, H, O, N, S, Cl

Balance equations

m I

c B · m B + c F · m F

HV B · m B + HV F · m F -2.45·m W

d _O2-CO2 · m B + d _O2-CO2 · m F

m B + m F + m I + m w

= a waste

= c waste

= HV waste

= d O2-CO2,waste

= 1

O 2 C

,B · m B + O 2 C

,F · m F = O ₂ ^C _waste

m I

c B · m B + c F · m F

HV B · m B + HV F · m F -2.45·m W

d _O2-CO2 · m B + d _O2-CO2 · m F

m B + m F + m I + m w

= a waste

= c waste

= HV waste

= d O2-CO2,waste

= 1

O 2 C

,B · m B + O 2 C

,F · m F = O ₂ ^C _waste

0 200 400 600 800

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

kg  CO 2  fo ss  /  t  wa st e Re vi si o n  of  pl ant

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

01.07.07 01.08.07 01.09.07 01.10.07 R a ti o of e n e rgy f ro m b io g e n ic sou rce s [ % ] Line 1

Line 2

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

01.07.07 01.08.07 01.09.07 01.10.07 R a ti o of e n e rgy f ro m b io g e n ic sou rce s [ % ] Line 1

Line 2

Balance Equation

m _I c _B · m _B + c _F · m _F

HV _B · m _B + HV _F · m _F -2.45·m _W

d _{O 2 -CO 2} · m _B + d _{O 2 -CO 2} · m _F

m _B + m _F + m _I + m _w

= a _waste

= c _waste

= HV _waste

= d _{O 2 -CO 2 ,waste}

= 1 Mass balance

“Ash”-balance Carbon-balance Energy-balance

Difference of O ₂ -cons. +CO ₂ -prod.

Derived from operating data

O ₂ -consumption O ₂ ^C _,B · m _B + O ₂ ^C _,F · m _F

= O ₂ ^C _waste

Coefficients (given by the

chemical composition of

Results (annual values)

CO ₂ - Emissions

81,9 ± 3,9

72,7 ± 3,1

0 20.000 40.000 60.000 80.000 100.000

CO 2 -Emissions [kilo tons/year]

biogenic fossil

52.9% 47.1%

0%

10%

20%

30%

40%

50%

60%

70%

Fraction of fossil CO ₂ emissions [%]

Radiocarbon method

Balance method

MFA for environmental protection and resources management

1st generation MFA: Environmental protection:

• DDT

• CFCs

• PCBs, NP etc.

• C -> CO ₂ and CH ₄

2nd generation Resource management:

• Regional nutrient flows -> integrated P management

• Regional and global metal flows and stocks (Graedel)

-> future metal management

Copper management based on MFA

source: Graedel et al. 2002 and Rechberger

11.000 11.500 3.800

540 11.000

300.000 +7.700

580.000

-11.000 85.000

+3.100

"World 1994”

products cathodic

copper

Cu scrap III

680 Cu scrap II

waste

1.700

Waste to landfill 1.200

waste slag 150 Ore

use Waste

management 5 4

1 6

Lithosphere landfill

flows: 1.000 t/a stocks: 1.000 t 1.400 Cu scrap I

11.000 11.500

copper production

2

Copper manufacturing

3

Application of MFA for governance in waste management

Goal: improve waste management practice

step 1: professional MFA standard ÖWAV guideline (consensus) step 2: Austrian Standard ONORM S 2096 “MFA- Application in

waste management”

step 3: easy to use software STAN (freeware) for MFA in wm

step 4: mandatory MFA requirement for certified MSW companies step 5: routine waste analysis by MFA on selected MSW incinerators step 6: Link all relevant information for a new knowledge base (e.g.

for national waste management plan)

Conclusions

Objective:

- sustainable resource use

- long-term environmental protection MFA is instrumental for this objective because:

• it is a rigid, transparent, and objectiv method to model and visualize material flows including uncertainty

• It facilitates understanding and public acceptance of decisions

• It is a key decision support tool for resource management, environmental management, and waste management

• It is indispensable to establish knowledge bases for em, rm, and wm

• It needs to be standardized in order to fully exploit its potential

Thank you

Thank you