DOCUMENTATION OF LCWE DATA IN GABI 4 - GaBi Software

DOCCUMENNTATION 

OF LLCWE 

DATA IN 

GABBI 

1 

Sustainability 

is ann 

increasing gly used expression 

an nd many pr roducts are marketed as a being 

sustainaable. 

The ddefinition 

of f sustainabbility 

include es ecologic cal, econommic 

and als so social 

aspectss, 

as preseented 

in Fi igure 1. Cuurrently, 

fo or example carbon foootprints 

are 

highly 

discussed 

and therrefore 

envir ronmental aand 

also eco onomic prof files of prodducts, 

but es specially 

the soccial 

aspectss 

are often n largely nneglected. 

The challe enge for coonducting 

a social 

assessmment 

along the comple ete life cyclee 

is the nee ed of plenty y – so far nnot 

acquired d – data. 

This situuation 

is coomparable 

to t the effortts 

that had to be done at the beginning 

of Life 

Cycle 

Assessmment 

itself iin 

the 1980s s. 

Figure 

INTROODUCTION 

N 

1: Sustaiinability: 

Integration 

of ecologic, 

econo omic, soccial 

and te echnical 

dimenssion 

in a so oftware and 

database e system 

In order 

to fill thesse 

existing gaps, stattistical 

sour rces can be e employedd 

to gather socially 

relevantt 

data. Thee 

University of Stuttgarrt, 

Chair of Building Ph hysics (LBPP), 

Dept. Life 

Cycle 

Engineeering 

(GaBii) 

develope ed the methhod 

of Life Cycle Wor rking Enviroonment 

(LC CWE) to 

integratte 

social asspects 

into Life Cycle Assessme ent (LCA). In applyingg 

this method, 

high 

quality pprocess-speecific 

data concerning c social aspe ects for use in product LCA is obta ained by 

using sttatistical 

souurces. 

The following asspects 

are covered: c 

Page 1 / 15

• AAmount 

andd 

qualification 

level of wwork 

• 

The nexxt 

paragrapphs 

will doc cument the method tha at was applied 

to geneerate 

social l profiles 

for all unit 

processees 

in the Ga aBi databasse. 

2 

When thinking 

aboout 

social effects, e onee 

of the firs st questions s to considder 

is which h criteria 

should be measured 

and which w indicaators 

should 

be emp ployed to ddescribe 

the 

social 

implicattions 

of a huuman 

action n. For the mmethod 

desc cribed here, 

the objectiive 

was to integrate 

social aassessmentt 

into the already a exissting 

metho odology of Life L Cycle EEngineering 

g (LCE). 

That immposes 

somme 

restrictio ons upon tthe 

choice of indicators. 

Therefoore, 

the crit teria the 

employeed 

indicatorrs 

have to comply c with are describ bed in the fo ollowing. 

2.1 

The soccial 

goals shhould 

have an actual reelevance 

and 

a broad internationaal 

consensu us. They 

should iif 

necessaryy 

allow for the 

inclusionn 

of other societal 

or cu ultural valuees. 

2.2 

The indicators 

and their ascer rtainment shhould 

be im mpartial and revisable. 

2.3 CCompleteness 

and attributabbility 

1. AAll 

relevant goals shou uld be addreessed. 

2. TThe 

indicatoor 

should co over the resspective 

social 

goal co omprehensivvely. 

2.4 QQuantitatiiveness 

The inddicator 

shouuld 

compris se a quantittative 

meas sure in order 

to be agggregated 

over o the 

whole life 

cycle. 

2.5 

Health and safety. 

SELECCTION 

CR RITERIA FOOR 

INDICA ATORS 

Relevancee 

and Con nsensus 

Impartialitty 

3. TThe 

indicattor 

should be b clearly aand 

complet tely attributable 

to the respective product 

or proceess. 

Pertinencce 

of indica ator sum 

The summ 

of the indicator 

valu ues of all pprocesses 

of o one site, company, industrial sector s or 

country should acccurately 

des scribe the ovverall 

situat tion. 

Page 2 / 15

2.6 

2.7 CComparabbility 

of targets 

andd 

indicator rs 

1. TThe 

goals aand 

indicato ors should bbe 

compara able in an international 

context. 

2. TThe 

goals aand 

indicato ors should bbe 

compara able between 

different iindustries. 

2.8 

The goaals 

and inddicators 

sho ould have a direct rela ation to pro oducts or prrocesses 

or 

should 

facilitatee 

to be relatted 

to them. 

2.9 AAverage 

vvalidity 

The indicators 

should 

remain valid for aveerage 

mode elling, i.e. useful 

for LCCWE 

databa ases. 

2.10 SSystem 

booundaries 

s, cut-off ccriteria, 

re eference sy ystem 

They arre 

chosen iin 

accordan nce with thee 

ISO 1404 40 and 140 044 (CEN 22006), 

whereas 

the 

“environnmental 

releevance” 

is substituted s by the “social 

relevanc ce”. 

2.11 TTemporal 

stability and a time sseries 

The callculation 

of the social indicators sshould 

be repeatable r for other ye years, which h means 

that timee 

series shoow 

the actu ual changess. 

2.12 

The datta 

collectionn 

should be viable undeer 

justifiable e effort. 

3 

The nexxt 

paragrapphs 

will exp plain the LLCWE 

meth hod develop ped at Univversity 

of Stuttgart, S 

LBP-GaaBi. 

3.1 

No Overlaap 

There sshould 

be nno 

overlap between thhe 

different indicators to avoid doouble 

counting 

and 

thereforre 

overvaluaation 

of sing gle effects. 

Product/PProcess-re 

elatednesss 

Data availlability/eff 

fort 

LCWEE 

METHOD D DESCRIPPTION 

Indicatorss 

chosen for f integraation 

into LCA 

Table 1 shows thhe 

indicators 

chosen to be inte egrated into o the Life 

methodology 

basinng 

on the cr riteria descrribed 

above. 

Cycle Eng gineering 

Page 3 / 15

Table 1: 

Social Inddicators 

ch hosen 

Qualiffied 

workingg 

time 

3.2 

Heaalth 

and Safeety 

In geneeral, 

both, a bottom-up p and a topp-down 

app proach for data d acquissition 

do ex xist. The 

bottom-up 

approacch 

would be 

the separate 

acquis sition of dat ta for everyy 

unit proce ess. The 

top-dowwn 

approachh 

correspon nds to the prorating 

of aggregate a data d to single 

processe es. 

3.2.1 

Applyingg 

this approach, 

social 

indicatoors 

have to o be collec cted for eaach 

process s in the 

producttion 

chain. HHere 

the pr roblem occuurs 

that suc ch data is ra arely availaable 

at the moment, m 

becausee 

a meaningful 

use and comprrehensive 

approach a for f such inndicators 

was w non- 

existentt 

so far. The 

initiation n of a conntinuous 

as scertainment 

of this data 

would be cost 

intensivve 

and time consuming. 

Due to this, for the 

beginning g the top-down 

attemp pt is chosen 

for the LLCWE 

meth hodology 

developped 

at the UUniversity 

of o Stuttgart. . Neverthele ess, the da ata acquisitiion 

for ever ry single 

processs 

remains thhe 

middle-te erm to long-term 

goal because b of its more preecise 

result ts. 

3.2.2 

Group 

Data acquuisition 

me ethod 

Indica ator 

General Qualification n level A (GQ QL A) 

General Qualification n level B (GQ QL B) 

General Qualification n level C (GQ QL C) 

General Qualification n level D (GQ QL D) 

General Qualification n level E (GQ QL E) 

Total worki ing time 

Lethal acc cidents 

Non-lethal accidents a 

Separatee 

data acq quisition foor 

unit pro ocesses 

Prorationn 

of aggre egated datta 

to singl le process s 

Statisticcal 

data cooncerning 

social s issuees 

is available 

for most m of thee 

highly de eveloped 

countriees, 

for somee 

of them de etailed enouugh 

to use them t in the LCWE metthodology. 

To proraate 

this dataa 

down to process p leveel, 

the follow wing assum mptions are aapplied: 

Unit 

[sec c] 

[sec c] 

[sec c] 

[sec c] 

[sec c] 

[sec c] 

[case es] 

[case es] 

1. TThe 

social impacts of f a processs 

are propo ortional rela ated to the amount of f human 

llabour 

of the 

process. 

Page 4 / 15

2. TThe 

amounnt 

of human n labour of a process is i related to o the effort made to ad dd value 

bby 

processiing 

(which is 

equivalennt 

to the add ded-value itself). 

The aboove 

assumpptions 

are valid 

within tthe 

same in ndustry and in the samee 

country only. 

In contrrast 

to the ssituation 

for r environmeental 

Input-O Output table es, the amoount 

of hum man work 

is very well correlated 

with the 

econommic 

value ad dded of a process. Thhe 

precision 

of the 

results tthat 

can bee 

reached is s hence higgh 

enough to t be used as a reasonable 

starti ing point 

for modelling 

on the 

product le evel. 

Figure 2 shows thhe 

different t steps of tthe 

approac ch developed 


Stuttgart 

aiming aat 

the calcuulation 

of pro ocess speccific 

LCWE data. d 

Figure 2: Generattion 

of proc cess-specific 

social information 

n 

In the foollowing 

parragraphs, 

th he steps shoown 

in Figu ure 2 are de escribed in mmore 

detail. . 

3.3 GGeneral 

qqualificatio 

on level off 

jobs 

In the first step, single pro ofessions aare 

allocate ed to different 

qualifiication 

leve els. The 

classificcation 

is made 

accord ding to the Internation nal Standar rd Classificcation 

of Ed ducation 

(UNESCCO 

INSTITUTTE 

FOR STATISTICS 

19997). 

This cla assification was develooped 

in 199 97 by the 

UNESCCO 

in orderr 

to classify y and charaacterize 

diff ferent school 

types annd 

school systems. s 

The ISCCED 

addreesses 

the required r quualification 

of a job po osition rathher 

than the 

actual 

qualificaation 

of the employees s. It classifiees 

seven dif fferent quali ification leveels 

(Level 0 – Level 

6). In thhe 

course of the development 

oof 

this meth hod Level 0, Level 1 and Level 2 were 

combineed 

to one leevel. 

The distinctions 

mmade 

in thes se levels for 

the require red qualifica ation of a 

job are not relevant 

enough to o be kept in the classification 

for th he developeed 

method. 

Page 5 / 15

3.4 

In the seecond 

step, 

the profes ssion distribution 

per industry 

is ca alculated viaa 

a matrix based b on 

the SICC 

code (OCCCUPATIONA 

AL HEALTH AND SAFE ETY ADMINIS STRATION 1992). 

In th he table 

elementts 

of the maatrix, 

the nu umber of poositions 

of each e profession 

in every 

single industry 

is 

presentted. 

From thhis, 

the emp ployee profile 

of each industry 

can n be identifieed. 

3.5 SSeconds 

oof 

labour per VA 

The secconds 

of labour 

per va alue added are derive ed from the U.S. Economic 

Census 

(U.S. 

CENSUSS 

BUREAU 11997). 

This s statistic ggives 

inform mation abou ut the nummber 

of employees, 

averagee 

number off 

production n workers, pproduction 

workers' ho ours, cost of contract work w and 

the valuue 

added. TThe 

value ad dded given in the statis stic is calcu ulated from tthe 

income through 

the salee 

of the prooduced 

goo ods less thee 

expenditu ures for aux xiliary mateerials, 

interm mediates 

and/or resources and the expenditurees 

for sub bcontracting g. The value 

added for the 

calculattion 

of the sseconds 

of labour per VA – relation 

is theref fore correctted 

by this number. 

The woorking 

time is only qu uoted for wworkers, 

no ot for appo ointees. It iis 

assumed d in the 

methodology, 

that an appointe ee works the 

same hou urs per year r as a workeer. 

3.6 QQualificattional 

labo our profilee 

of the ind dustry 

In the next 

step, thhe 

total work king time peer 

value add ded can be broken dowwn 

with the e support 

of the taables 

and mmatrixes 

ge enerated in the steps before. b The result is a qualificatio on profile 

of each industry per 

value ad dded generrated. 

This qualification n profile shhows 

the am mount of 

workingg 

time in eacch 

of the fiv ve qualificattion 

levels to t generate one Euro vvalue 

added d. These 

values, same as thhe 

total wor rking to gennerate 

one Euro E value added, varry 

between different 

industriees. 

3.7 

For thee 

calculationn 

of non-fa atal injuriess, 

two kinds s of data are a availabble 

(UNITED STATES 

DEPARTTMENT 

OF LAABOR 

1999) : The injuriees 

listed as injury rates s, as well ass 

absolute numbers n 

of injuries 

per inddustry. 

The injury ratees 

present the numbe ers of injurries 

per pe erformed 

workingg 

time. Thesse 

rates are e corresponnding 

with the 

risk of th he employeees 

to get in njured in 

the speecific 

industrry. 

The abs solute ratess 

give the to otal number 

of injuriess 

without ta aking the 

total number 

of emmployees 

in the specificc 

industry in nto account t. In the conntext 

of the e method 

describeed 

here, thhe 

non – fa atal injuriess 

have to be b related to t the totall 

working time 

and 

respectively 

to the 

value ad dded in orrder 

to cla assify them m to the ddifferent 

pro ocesses. 

Therefoore, 

the ratee 

of non-fata al injuries iss 

used. 

3.8 

Employeee 

profile of f the indusstry 

Rate of noon-fatal 

injuries 

perr 

VA 

Rate of fatal 

injuries 

per VA 

The fataal 

injuries aare 

also collected 

and ppublished 

by b the U. S. Departmennt 

of Labor (UNITED 

STATES DEPARTMEENT 

OF LAB BOR 1999). For the fa atal injuries s only absoolute 

numb bers are 

Page 6 / 15

available. 

A statemment 

concer rning the rissk 

of fatal in njuries in the 

different industries therefore 

is not poossible. 

In orderr 

to relate thhe 

fatal injuries 

to the ttotal 

workin ng time and hence to thhe 

value added, 

the 

workingg 

time for eevery 

industry 

has to be available. 

For the reasons exxplained 

in the last 

paragraaph, 

values should no ot be drawnn 

from diff ferent sourc ces. So vaalues 

from different 

tables, generated based on th he source mmentioned 

above on non-fatal n annd 

fatal injuries, 

are 

used: TThe 

total woorking 

time for each inddustry 

is de erived from the non-fattal 

injuries rate and 

from thee 

absolute nnumber 

of non-fatal n injuries. 

3.9 SSocial 

Proofile 

of the e industryy 

The soccial 

profile ffor 

each ind dustry includdes 

the wo orking time in different qualification 

levels, 

the non-fatal 

and the 

fatal inju uries, each related to one o Euro of f value addeed 

generate ed in the 

respective 

industryy. 

3.10 

Prices forr 

GaBi-Flows 

For relaating 

the social 

data to o LCA proceess 

data, th he value added 

of eachh 

LCA proc cess has 

to be iddentified. 

Thhis 

is done by calculating 

the delta 

of prices 

between the output and the 

input floows 

of eachh 

process. Therefore, for all mate erials, intermediate 

prooducts 

or products, p 

as well as variouss 

energy fl luxes, whicch 

go in an nd out of processes, p prices hav ve to be 

determined 

and asssigned. 

Sin nce the prooduct 

prices s depend on n a dynamicc 

market, th he same 

referencce 

period ffor 

both the e prices annd 

for the identificatio on of the vvalue 

added d of the 

industriees 

should be selected d. In this ccase 

the calculation 

is 

made wiith 

annual average 

values oof 

the same 

reference e period. A foreign trade 

statistic is used to provide co onsistent 

price daata 

(U.S. CEENSUS 

BURE EAU 2002A, U.S. CENSU US BUREAU 2002B). 2 

For moost 

of the fflows, 

price es can be calculated regarding quantities and total value v of 

exported 

commodiities. 

In cas ses where tthis 

is not possible, p pr rices are esstimated 

pe er expert 

judgemeent 

using tthe 

assump ptions that tthere 

are no n negative e value adddeds 

and th hat price 

ranges can be esttimated 

on the basis oof 

the lowe er price of a preliminaary 

product and the 

higher pprice 

of a suubsequent 

product. p This 

kind of es stimation ha as an impacct 

on the res sult if 

1. tthe 

according 

flow pas sses from onne 

industry into anothe er industry aand 

2. tthe 

social pprofile 

of bot th industriess 

varies. 

3.11 VValue 

Addded 

of GaB Bi-Processses 

In orderr 

to calculatte 

the value added of a single proc cess, the to otal value off 

the incoming 

flows 

is subtrracted 

fromm 

the total value of thhe 

outgoing g flows of a process. The total value is 

calculatted 

by multiplying 

the amount of the flow wi ith its price and then bby 

summing g up the 

values oof 

all flows. 

Page 7 / 15

This steep 

requires an access s to a life cyycle 

model on a unit process levvel 

of the particular p 

productt. 

Furthermore, 

as consistent 

ass 

possible data d are necessary 

foor 

all econ nomically 

relevantt 

material and 

energy flows, f whichh 

flow in and 

out the un nit processees. 

3.12 

To geneerate 

a LCWWE 

process s data set, each individ dual proces ss must be classified to 

one of 

the variious 

industrries. 

Subse equently, thee 

social pro ofile of the industry is multiplied with the 

value addded 

of the individual process. p In doing this, the reference 

to one EEuro 

of valu ue added 

is lost aand 

the induustry 

profile is scaled on 

a unit pro ocess. 

3.13 

In the ccourse 

of the 

balance calculation, c the values of unit processes 

are e summarize ed along 

the valuue 

chain according 

to o the summmarization 

of o LCA inventory 

dataa 

and can thus be 

evaluateed 

equally. 

3.14 

Process DData 

Sets 

Evaluationn 

Processinng 

of Data(-sets) 

in the Softw ware 

In the cclassic 

LCAA 

the particu ular processses 

are sc caled accord ding to theiir 

connectio ons over 

input annd 

output floows. 

Beside es, the elemmentary 

flow ws, which exceed e the system bou undaries 

and thus 

cause an impact, are e scaled witth 

the factor 

of their or riginal proceess. 

In this way, w the 

contribuution 

of eaach 

individu ual processs 

to the fu unction of the t total sy system is weighted w 

correctlyy. 

By includding 

social data into LLCA 

datase ets, the sam me weightinng 

principle es apply, 

thus leaading 

to correct 

results that can bee 

evaluated in accordance 

to LCAA 

results. 

3.15 GGeneratioon 

of Indic cators andd 

Evaluatio on 

In classsic 

LCA methodolo ogy, the summation n is follo owed by classificatio on and 

characteerization. 

Inn 

contrast, the indicattors 

for the social aspects 

are chhosen 

the way w that 

they eaach 

build iits 

own cla ass. The sstep 

of the e classification 

as relation 

of particular p 

contribuutors 

to a ppotential 

kin nd of impacct 

therefore is superflu uous. Withinn 

each clas ss, there 

are no contributorrs 

that hav ve to be vvalued 

differently. 

Com mpared to a consider ration of 

ecologiccal 

values, a characte erization thherefore 

is not necess sary. This can be seen 

as a 

fundamental 

differrence 

between 

ecologgical 

LCA and social aspects cconsideratio 

on within 

LCA; in case of the 

ecologica al LCA the interim bala ance of mass 

and eneergy 

flows is s drown. 

These flows are then misca alculated inn 

respect to t their va arious envirronmental 

impacts. 

Howeveer, 

when eexamining 

social asppects, 

the indicators are seleccted 

so th hat they 

correspond 

directlyy 

with a soc cial aspect. The evalua ation of indic cators howeever 

can be e done in 

analogyy 

to the claassic 

LCA-m method: Eaach 

indicato or receives s its own immpact 

category 

(or 

rather for each impact ca ategory a described indicator is to be found) an nd each 

characteerization 

factor 

gets the 

value onee. 

Page 8 / 15

3.16 VValidity 

As explained 

abovve, 

a respec ctive validitty 

of a resu ult depends on the seleection 

of th he social 

indicatoors, 

on their 

ability to o be summmed 

up, on an ability to be weiighted 

that can be 

comparred 

with maaterial 

and energy e flowws 

and, of course, c on the availabbility 

of data a for the 

unit proocesses. 

AAll 

these co onditions aare 

given fo or the wor rking time values in different 


levels, 

the non-fa atal and fataal 

injuries presented 

ab bove. If there 

is a poss sibility to 

relate thhem 

to the basic value e working timme, 

also for r other socia al factors too 

be develo oped, the 

criteriass 

of summinng 

up and weighting w caan 

be accomplished. 

The T availabbility 

of data a is to be 

proved separatelyy, 

and a ge eneral validdity 

or rath her reasona ableness sshould 

be used u as 

primary selection ccriterion. 

4 

To showw 

the potenntials 

and va alidate the feasibility of o the asses ssment metthod, 

it was s applied 

in severral 

projects so far. There 

are princcipally 

two possibilities 

p to use the LCWE method: 

1. 

Use of thee 

comprehe ensive andd 

consistent 

backgrou und databaase. 

The da ata was 

ccalculated 

aas 

explained 

above. 

2. GGathering 

oof 

own, project 

and proocess 

specific 

data. The 

data can be inserted d directly 

in the LCWE 

tab, when n creating a new proce ess. 

For the example, ddata 

from the 

backgrouund 

databas se is used in n order to sshow 

the application 

of the mmethod. 

Twoo 

different kinds k of plasstic 

are com mpared. 

4.1 

Concernning 

the soccial 

implicat tions, the wwhole 

production 

phase e of the diffeerent 

alternatives 

is 

assesseed 

including 

all upstr ream valuee 

chains (p production and supplly 

of all precursor p 

substannces, 

operatting 

supplie es, auxiliary materials, energies etc.). 

In the ffollowing, 

thhe 

results for the asssessment 

of o two route es will be sshown 

exemplarily: 

Polyethylene 

fibress 

production n and the prroduction 

of f Polyethyle ene terephthhalate 

(PET T) fibres. 

4.2 

EXAMMPLE 

Descriptioon 

of the assessed a system 

Results 

Table 2 shows thee 

working time t distribbution 

into the t general 

qualificatioon 

levels ( GQL) in 

secondss, 

that is reelated 

to jobs 

with thee 

respective e qualificatio on level ass 

requireme ent. Jobs 

with a GGQL 

A do hhave 

the hig ghest qualiffication 

as prerequisite 

p e, Jobs withh 

a GQL E relate to 

work wwith 

low qualification 

requirement 

r ts. The tot tal working time, beinng 

the sum m of the 

numberrs 

listed under 

the diff ferent GQLLs, 

is the su um of all human 

labouur 

employe ed in the 

producttion 

of 1 kg plastic. 

As Table 

2 and FFigure 

3 pre esent, the plastic PET T production 

requires considerab bly more 

human labour thaan 

PE prod duction. This 

is cause ed by the more compplex 

manuf facturing 

processs 

for PET than 

for PE. 

Page 9 / 15

Table 2 

Quualification 

Level 

GQL A [s] 

GQL B [s] 

GQL C [ss] 

GQL D [ss] 

GQL E [s] 

Tottal 

working tiime 

[s] 

Lethhal 

accidents [cases] 

Non-leethal 

accidennts 

[cases] 

The graaphics 

also show that in i industriall 

process ch hains rather 

few jobs wwithout 

qua alification 

and witth 

a very high qualifi ication cann 

be found. 

Industry requires a minimum level of 


and only 

few peo ople with a very high qualification 

q n on the maanagement 

level. A 

higher sshare 

of wworkers 

with hout qualificcation 

is ra ather found in the serrvice 

sector 

(sales, 

direct seervices 

etc. ). 

250,0 

200,0 

150,0 

100,0 

50,0 

Qualified working time in [s] 2: Working 

0,0 

time and accidents a fo for the prod duction of 1 kg PE annd 

1 kg PET T 

Quualifiedd 

Workking 

Timme 

PE 

Figure 3: Qualifiedd 

working time for thhe 

production 

of 1 kg PE and PEET 

PE 

1.4 

11.0 

14.4 

15.1 

7.6 

49.5 

3,23E-07 

5,45E-10 

Figure 4 and Figurre 

5 show the 

amount of non-leth hal and letha al accidentss 

for the pro oduction 

of 1 kg PE or PET. . The numb bers are verry 

small as they are related 

to thee 

functional unit of 1 

kilogramm. 

PET 

PET 

9.9 

61.1 

72.5 

59.4 

27.2 

230.1 

11,06E-06 

11,03E-09 

GQL 

E [s] 

GQL 

D [s] 

GQL 

C [s] 

GQL 

B [s] 

GQL 

A [s] 

Page 10 / 15

Non‐lethal accidents [cases] 

Figure 4: Non-lethhal 

acciden nts caused by the pro oduction of f 1 kg PE aand 

PET 

The geeneral 

results 

are sim milar to quaalified 

work king time: There are significant tly more 

accidennts 

when producing 

a kg of PETT 

than PE. 

Again thi is is due to the more e labour 

intensivve 

and moree 

complex manufacturi 

m ng process of PET. 

Lethal accidents [cases] 

1,20E‐09 

1,00E‐09 

8,00E‐10 

6,00E‐10 

4,00E‐10 

2,00E‐10 

0,00E+00 

1,20E‐066 

1,00E‐066 

8,00E‐077 

6,00E‐077 

4,00E‐077 

2,00E‐077 

0,00E+000 

NNon‐lethhal 

accidents 

PE 

Lethal 

accideents 

PE 

PPET 

Figure 5: Lethal aaccidents 

caused c by tthe 

produc ction of 1 kg g PE and PPET 

PET 

Page 11 / 15

6 

The meethod 

develooped 

and th he respectivve 

backgrou und database 

is a firstt, 

promising attempt 

to addreess 

the social 

pillar of sustainabilit 

s ty in the sco ope of the well w establisshed 

metho od of Life 

Cycle AAssessmennt 

and Life e Cycle Enngineering. 

Social eff fects that would hav ve been 

neglecteed 

by an LLCA 

can be e included aand 

show remarkable 

results. Prooblem 

shifting 

from 

the environmental 

realm to the e social fieldd 

can be av voided. 

The exaample 

showws, 

that the results of thhe 

LCWE method m can be used simmilarly 

to the e results 

of an LLCA: 

Informmation 

is pr resented onn 

a unit pro ocess level 

and also project or process 

specific informatioon 

can be inserted. IInformation 

about soc cial issues is summa able and 

scalablee 

as the LCCA 

user is fa amiliar with from the environment 

e tal LCA. In the compre ehensive 

backgroound 

databaase, 

informa ation for alll 

unit processes 

regard ding the quaalified 

work king time 

and lethhal 

and noon-lethal 

ac ccidents is available. Additionally y, informatiion 

concern ning the 

following 

indicatorss 

can be ins serted in thee 

GaBi softw ware in the LCWE tab by the user r: 

AActual 

wommen 

employment 

CChild 

labour 

 

 

 

 

 

 

Discussioon 

and out tlook 

Holistic and forwaard-looking 

decisions must be based b on a broad baasis 

of all relevant 

information. 

The soocial 

dimens sion of humman 

actions clearly mus st be considdered. 

Discrimination 

in job ac ccess 

Forced laboour 

Hazardous child labour 

No collectivve 

bargainin ng 

No right to oorganise 

Unequal remuneration 

All inforrmation 

has to be in relation 

to working 

time in 

seconds. 

Howeveer, 

it has to be stated that due too 

the above mentioned restrictionss 

for indicators, 

not 

all relevvant 

social information can be acccounted 

for r by this me ethod, so faar. 

Additional 

social 

effects hhave 

to be considered in future deevelopment 

t of the meth hodology. 

As all LCWE 

data currently pr resent in thee 

GaBi data abase is de erived from US statistic cs, it can 

be regaarded 

valid for all coun ntries holdinng 

similar economic e and a socio-ecconomic 

co onditions 

than thee 

US. 

Using thhe 

LCWE ddata 

for decision 

makinng, 

it has to be conside ered that ass 

the data is s derived 

from staatistics, 

it dooes 

not rep present exacct 

site spec cific situations 

and shoould 

only be e used to 

comparre 

for exammple 

genera al product options. For 

the com mparison off 

social aspects 

of 

different 

suppliers, company-s specific dataa 

has to be used. 

To conclude 

with, , the social 

database can be used 

as a hotspot daatabase 

in order to 

examinee 

the main contributor rs to social profiles along 

the pro ocess chainns 

of produ ucts. For 

these mmain 

contributors, 

site specific s soccial 

data can n be gathere ed in a secoond 

step in order to 

get a more 

precisee 

picture of the t social immplications 

of a produc ct. 

Page 12 / 15

6 

LITERRATURE 

NATIONNAL 

CROSSSWALK 

SERVICCE 

CENTERR 

(1997) ) 

OCCUPPATIONAL 

HEALTHH 

ANDD 

SAFETYY 

ADMINI- 

STRATIION 

(1992) 

UNESCCO 

INSTITUUTE 

FORR 

STATISSTICS 

(1997) ) 

UNITEDD 

STATESS 

DEPARRTMENT 

LABORR 

(1999) 

OFF 

NATIONA AL CROSSWAALK 

SERVIC CE CENTER (1997): NOOICC 

Maste er Crosswallk, 

Version 4.3. National 

Crosswa alk Service Center. C 

Online: http://www.x 

h xwalkcenter.org/index. 

php. 

OCCUPA ATIONAL HEAALTH 

AND SA AFETY ADMIN NISTRATION (1992): Sta andard 

Industria al Classificaation 

(SIC) system. s United 

States Department 

of Labor; 

Occupat tional Health 

and Safet ty Administr ration. 

Online: http://www.o 

h osha.gov/pl ls/imis/sic_m manual.htmml; 

http://ww ww.census.ggov/epcd/w 

www/sic.html. 

UNESCO O INSTITUTEE 

FOR STATISTICS 

(1997 7): Internatio ional Standa ard 

Classific cation of Edducation 

ISC CED 1997. UNESCO U Innstitute 

for Statistics. S 

Online: 

http://ww ww.unesco.oorg/education/informat 

tion/nfsunessco/doc/isced_1997.httm 

; http://w www.uis.uneesco.org/ev_ 

_en.php?ID D=7433_2011&ID2=DO_ 

_TOPIC. 

UNITED STATES S DEPPARTMENT 

OF O LABOR (1999): 

US Fa Fatal and No on-Fatal 

Injuries and a illnessees. 

United States S Depa artment of LLabor 

and Bureau B of 

Labor St tatistics. 

Online: 

http://ww ww.bls.gov/iiif/oshwc/os 

sh/os/ostb06 641.pdf; htttp://www.bls 

s.gov/iif/oshhw 

c/osh/os s/ostb0642.ppdf. 

U.S. CENSUSS 

U.S. CEN NSUS BUREAAU 

(1997): 1997 1 Econo omic Censuus. 

General Summary 

BUREAAU 

(1997) Mining and a Manufaacturing, 

Ind dustry Summ mary Constr truction. U.S S. Census 

Bureau. Online: httpp://www.cen 

nsus.gov/pr rod/ec97/977m31s-gs.pdf; 

http://ww ww.census.ggov/prod/ec 

c97/97c23-is.pdf; 

http://ww ww.census.ggov/prod/ec 

c97/97n21-g gs.pdf. 

U.S. IMPORTS 


MERCHHANDISE 

U.S. IMP PORTS OF MEERCHANDISE 

E (2002A): History H DVDD-ROM. 

U.S S. Census 

Bureau. 

(2002AA) 

Online: http://www.c 

h census.gov v/foreign- 

trade/ref ference/prooducts/catalo 

og/imphisto ory.html. 

U.S. EEXPORTS 


MERCHHANDISE 

U.S. EXP PORTS OF MMERCHANDIS 

SE 2002B: History H DVD-ROM. 

U.S. 

Census 

Bureau. 

(2002BB) 

Online: http://www.c 

h census.gov v/foreign- 

trade/ref ference/prooducts/catalo 

og/exphistoory.html. Page 13 / 15

APPENNDIX 

In this chapter thee 

data sources 

are aaddressed, 

which serv ve as a bassis 

for the method 

developped 


Stuttgart. S Thhe 

particular 

statistics should s meeet 

various criteria c to 

be usedd 

in this metthod. 

These e criteria aree 

as well sp pecified in th he followingg 

paragraph hs. 

U.S. Ecconomic 

CCensus 

The “U. .S. Econommic 

Census” ” (http://wwww.census.g 

gov/) is a comprehenssive 

data co ollection, 

that givees 

a detaileed 

review of o the American 

economy. 

It is fulfilled 

by thee 

“Census Bureau”, B 

the Ameerican 

demmographic 

ag gency. Thee 

results are e gathered every five yyears, 

whereas 

the 

collecteed 

basic datta 

include to o a large exxtent 

the sta atistics of all a US comppanies. 

At th he same 

time, thhe 

data collection 

for the t agriculture 

and the e authoritie es takes plaace 

in para allel. The 

data coollection 

is based on a clear struuctured 

cla assification of the whoole 

econom my into a 

strictly hierarchicaal 

system of o industriaal 

sectors and subse ectors – the 

so calle ed North 

Americaan 

Industry Classification 

Standarrd 

(NAICS). . It is import tant that noot 

the companies 

as 

a wholee, 

but the single 

locatio on of these ccompanies 

as minimum m unit are listed. 

It allo ows both 

a betterr 

spatial ressolution 

and d a better reesolution 

ac ccording to activity, as a company y can be 

active inn 

different ssectors. 

The 

NAICS cclassifies 

1179 

various industries, 1070 of which w are 

coveredd 

in the U.S. 

Economic c Census. 

The datta 

is provideed 

for free and a is suppposed 

to ser rve several purposes. The following 

fields 

of appliccation 

exemmplify 

this: 

CCompaniess 

can comp pare their ssales 

figure es with thos se for theirr 

whole ind dustry. It 

aallows 

themm 

to calcula ate their maarket 

share in order to check theirr 

performan nce or to 

ddefine 

new targets. 

CCompaniess 

can also compare thheir 

business 

ratio wit th average numbers from f the 

U.S. Census 

as a benchmark b 

to assess s their per rformance with those e of the 

cconcurrent 

organizatio ons. 

CCompaniess 

which sell their goodss 

or service es to other companies c can find in the U.S. 

CCensus 

neew 

target industriess. 

Besides, 

producer rs learn ffrom 

the material 

cconsumptioon 

statistics more abouut 

the indust tries that co onsume theiir 

products. 

CCompaniess 

can use the data tto 

determin ne their sa ales areas, to place a target 

aadvertisemeent 

and to find f the besst 

locations for f their new w establishmments. 

 

Important kkey 

figures about a the eeconomic 

de evelopment t as monthlyy 

retail sale es or the 

ggross 

domeestic 

produc ct are baseed 

on the da ata of the U.S. U Censuss. 

Associati ions and 

tthe 

press analyze th he data to identify ec conomic circumstancees 

and to forecast 

ddevelopments. 

TThe 

legislattive 

body uses 

the datta 

for the preparation 

p and assesssment 

of ne ew laws. 

TThe 

state and local authorities a monitor the e Census data d to undderstand 

economic 

bbasics 

and to decide whether w theey 

should se ettle new businesses 

oor 

keep the e already 

eexisting 

onees. 

Page 14 / 15

CConsultantss 

and researchers 

maake 

use of the data to o analyze tthe 

change es in the 

industries’ sstructure 

or r in the spattial 

resolutio on. These data d are nott 

explicitly collected c 

ffor 

the usee 

in the me ethod. Neveertheless 

th hey work well w for the developed method 

bbecause 

of f the level of o detail andd 

their basis s on the clear 

hierarchical 

structure 

of the 

industries’ cclassificatio 

on. 

In the 22002 

U.S. EEconomic 

Census C the data for th he year 200 02 are colleected. 

In De ecember 

2002 data 

collecttion 

questio onnaires wwere 

sent to 

more than 

5 millioon 

compan nies, the 

deadlinee 

was set oon 

the 12th h of February 

2003. Du ue to adapt tion of the ddata 

entry forms to 

the individual 

industries, 

there e exist noww 

more than n 600 differ rent versionns. 

Only some 

very 

small coompanies 

ddo 

not rece eive questioonnaires. 

Fo or them the e data alreaady 

available 

at the 

federal authorities’ ’ are used. These autthorities 

pro ovide basic c data as loocation 

and d kind of 

businesss, 

sales figures, 

wage es and salarries, 

numbe er of employ yees and foorm 

of organization. 

The U.SS. 

Econommic 

Census is enshrineed 

in title 13 of the United U Stattes 

Code. The law 

commitss 

organizatiions 

to send d back the ffilled 

forms and awards 

penalties in case companies 

omit this. 

Besides, , the law sw wears the CCensus 

Bu ureau to sec crecy. No ddata 

are pu ublished, 

which disclose 

the identity or activity a of an 

individual l or a company. 

Standaard 

Industtry 

Classif fication (SSIC) 

The Staandard 

Induustry 

Classi ification (SIC)-Code 

is s a four-digit 

numerical 

code assigned 

by 

the U.SS. 

governmeent 

to the business 

esttablishment 

ts to identify y the primaary 

business s activity 

of the eestablishmeent 

(http://w www.osha.gov/pls/imis/ 

/sic_manual.html). 

Thee 

classificat tion was 

developped 

to facilitate 

the collection, 

ppresentation 

n and analy ysis of datta; 

and to promote 

uniformity 

and comparability 

in the preesentation 

of statistic cal data coollected 

by various 

agenciees 

of the federal go overnment, state age encies and d private oorganization 

ns. The 

classificcation 

coveers 

all eco onomic acttivities: 

agr riculture, fo orestry, fisshing, 

hunting 

and 

trappingg; 

mining; cconstruction 

n; manufactturing; 

trans sportation; communicaations, 

elec ctric, gas 

and sanitary 

services; 

whole esale tradee; 

retail trade; 

finance e; insurance ce and real 

estate; 

servicess; 

and publiic 

administr ration. 

The Burreau 

of Labbour 

Statistics 

is a unit of U.S. Department 

of f Labour. Thhis 

unit is in n charge 

for the ffact-finding 

for the fede eral governnment 

in the e wide field of occupattional 

econo omy and 

occupattional 

statistics. 

US Impport/Export 

History 

The data 

about “UU.S. 

Expor rts of Mercchandise” 

(U U.S. CENSU US BUREAU 2002B) an nd “U.S. 

Imports of Merchaandise” 

(U.S S. CENSUS BUREAU 20 002A) are gathered g annd 

provided d by the 

U.S. Ceensus 

Bureau. 

The export 

statistiics 

contain data about t the value and the qu uantity of 

9.000 vvarious 

goods, 

which were w exporrted 

from th he USA; the e import staatistics 

prov vide this 

information 

for 177.000 

differ rent importeed 

goods. Depending g on the uunit 

the quantity 

is 

specifieed 

in, an aveerage 

price of the goodds 

can be calculated c based b on thhese 

data. The T data 

are alsoo 

available ffor 

the past t years. For r the method d described d here, dataa 

from the re eference 

year 2002 

was useed. 

Page 15 / 15

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