Multi-criteria selection of human health scenarios due to private consumption 1. International Open Nomiracle workshop, June 2006 Marianne Thomsen Multi-criteria

Multi-criteria selection of human health scenarios due to private consumption

1. International Open Nomiracle workshop, June 2006Marianne ThomsenMulti-criteria selection of human health scenarios due to private consumption

Boundary conditions of the Risk Problem

Element Boundary

Target Human in general

Condition for exposure Private households

Substances to be considered 145 chemicals; the majority from the list of already assessed chemicals under EU*

Other stressors No


*Of the 145 substances included, 78 have already been risk assessed, 63 are on the EU priority list but have not yet

been subjected to a thorough risk assessment, 4 substances are top scores in the Danish NIR, but not included in the

four EU priority lists of substances.

The System Model for the private consumption scenario

• Problem Specification Model (PSM) • Problem Tree mapping 195 single sub-problems to be

addressed in the household risk scenario

• Scenario Composition Model (SCM)• Selection of fraction of sub-problems considered the most

important ones • biased by data availability

• Criteria Model (CM)• Approximating sub-problems by criteria

• usage and toxicity category data

• Scenario Selection Model (SSM)• Criteria data values are used as input parameters in

order to identify the most problematic substance/-s and derived from this the most serious circumstances for risk assessment


Problem Specification Model (PSM)Qualitative model


Problem Tree mapping 195 single sub-problems as part of the household risk scenario P

roduction

Hum

an Health

Exposure

Effects

Release

Industrial Processing

Consum

er products

Toxic action

Acute

Chronic

Genetic disorder

Carcinogenicity

Personal care

Painting / C

olouring

Household detergents

Pest control

Solvents

Various

Fate

External body

Body entrance

Transport

Internal body

Ventilation

Solid w

aste

wastew

ater

Truck

Ship

Train

Pipe

Intermediate

Food additives

Solid products

Propellants

Pharm

aceuticals

Fuel

Hum

an usage

Veterinary use

Agriculture

Aquaculture

On hum

ans

Not on hum

ans

Indoor

Outdoor

Indoor

Outdoor

Painting

Printers/C

opying

Colouring

Skin care

Hair care

Cleaning

Scent

’Indoor

Outdoor

Oral contact

Skin contact

Contact to food / drinking item

s

Indoor use / A

ir contacts

Outdoor use/

Air contact

Ventilation

Solid w

aste

Wastew

ater

Degradation

Transport

Soil

Freshw

ater

Marine

Air

Biota

Water colum

n

Sedim

ent

Water colum

n

Sedim

ent

Indoor

Outdoor

Terrestrial

Aquatic

Outdoor

Betw

een out- / indoor

Indoor / air

Betw

een compartm

ents

Within com

partments

Betw

een com

partments/B

iota

Within B

iota

Terrestrial

Aquatic

Terrestrial

Aquatic

Sedim

ent

Water colum

n

Plant

Anim

al

Plant

Anim

al

Soil/ B

iota

Freshw

ater /( biota

Air/ biota

Plant

animal

plant

animal

plant

animal

Degradation

Dispersion/

convection

Air

Water

Freshw

ater

Marine w

ater

´Groundw

ater

Sedim

ent

Soil

Water

Freshw

ater

Marine w

ater

Groundw

ater

Freshw

ater

Marine

sediment / w

ater

soil / water

Soil / air

Air / w

ater

air / marine w

ater

air / freshwater

sediment / freshw

ater

sediment / m

arine

air born

waterborne

inhalation

Ingestion

dermal

indoor

outdoor

vapour

particles

vapour

particles

food

drinking

vegetables

meat

open source

packing

groundwater

surface water

persistency

secretion

eye

brain

lung

viscera

nerve

skin

neurodevelopmental

Endocrine disruption

allergy

skin

respiratory

Carcinogenicity

imm

une disorder

loss of fertility

male

female

DA

MP

learning disability

Autistic disorder

Reproductive disorders

lung

breast

colorectal

leukaemia

loss of fertility

Children health disorder

Male

female

mentally

physically

Vulnerability

health status

Genetically

Physical stress status

infection

stress

age

children

old people

bacteria

vira

noise

particles

UV

rays

Scenario Composition Model


Ingestion

Human Health

Exposure Effects

Release Fate


Consumer products

Toxic action

Acute Chronic

Neuro-developmental

DisorderGenetic disorder

Carcinogenicity Personal carePainting / Colouring


Pest control Solvents Various

Body entrance

Inhalation Endocrine disruptor

Carcinogenicity

Criteria ModelOrdinal model for each sub problem


Human Health

Exposure Effects

Release Fate


Consumer products

Toxic action

Acute Chronic

Neuro-developmental

Disorder

Endocrine disruption

Genetic disorder

Carcinogenicity Personal carePainting / Colouring


Pest control Solvents Various

Body entrance

Inhalation Ingestion

Cr1 Cr2

Carcinogenicity

Cr3

Cr5 Cr6 Cr7 Cr8 Cr9 Cr10

Cr4

SPIN data DEPA QSARProduct Category Model EU Classification & Labelling

Toxicity criteria approximations: Cr1 quantified by R20,R23,R26 (harmful, toxic and very toxic by inhalation),Cr2 by R22,R25,R28 (harmful, toxic and very toxic by oral intake), Cr3 by R39, R48 (danger of very serious irreversible effects, danger of serious damage to health by prolonged exposure) and Cr4 by R45,R46 (may cause cancer, may cause heritable genetic damage)

Scenario Selection Model

Ordinal model for risk level

Multi-criteria model

by use of Partial order ranking methodologies

Highest risk scenarios due to private consumption

Set of criteriaCr1 to Cr10

Value uncertainty

Multi-attribute uncertainty



1

3

4

5

6

8

9

10

12

13

14

15

16

18

19

20 21 23

24

28

30

32

35

36

41

43

46

47

49

59

60 61

63

66 68

72

79

87 89

94

96

101

102

104

105

107 117

118

119

124

129

133

136

139

Hasse Diagram including only realised positions in the Event Space, i.e. the 145 VOC and semi-VOC substances

Cr(1, 2, 3, 4, 5, 6, 7, 8, 9,10) = [0,0,0,0,1,1,1,1,1,1] Cr(1, 2, 3, 4, 5, 6, 7, 8, 9,10) = [1,1,1,1,0,1,1,1,1,1]

Substances closest related to the top ranked substance (Id 94,

benzene) represent the set of highest concern substances

Reference substance: Id 94, benzene, Cas No.: 71-43-2 1 1 1 1 0 1 1 1 1 1

Number of common values of unity

Id Name Cas No.Cr

1Cr

2Cr

3Cr

4Cr

5Cr

6Cr

7Cr

8Cr9

Cr10

8 124 stoddard solvent** 8052-41-3 1 0 1 1 0 1 1 1 1 1

7 19 Toluene 108-88-3 1 0 1 0 0 1 1 1 1 1

7 30 2-butoxyethanol* 111-76-2 1 1 0 0 0 1 1 1 1 1

7 85 solvent naphtha** 64742-88-7 1 0 1 0 0 1 1 1 1 1

7 101 Methyloxirane 75-56-9 1 1 0 1 0 1 1 0 1 1

6 4 Ethylbenzene* 100-41-4 1 0 0 0 0 1 1 1 1 1

6 8 4,4'-methylenedianiline 101-77-9 1 1 1 1 0 1 0 0 0 1

6 20 Phenol 108-95-2 1 1 1 0 0 1 0 0 1 1

6 107 hydrogen peroxide 7722-84-1 1 1 0 0 0 0 1 1 1 1

*Substances one of the priority lists, but have not yet been risk assessed**Substances not on the EU priority list


Hasse Diagram visualising the Event Space constructed based on the Cr1 to Cr10

Grey circle represents non-realised objects, the numbered white circles the 145 VOCs and semi-VOCs

Id´s representing groups of equivalent substances: Id 1(29), Id 6 (2), Id 9 (12), Id 10 (3), Id 13 (6),Id 15 (3), Id 16 (2), Id 18 (5), Id 19 (2)Id 35 (5), Id 36 (6), Id 47 (2), Id 49 (2), Id 60 (2), Id 68 (5), Id 102 (2)


Probability distribution of ranking levels for each single substance

Case 1 Case 2 Case 3

Id 30: Cr(1, 2, 3, 4, 5, 6, 7, 8, 9,10) = (1,1,0,0,0,1,1,1,1,1)2-butoxyethanol

111-76-2

All criteria equally important Cr1-Cr4 > Cr 5-Cr10 Cr3-Cr4 > Cr1-Cr2 > Cr5-Cr19


Case 1 Case 2 Case 3

Mean Ranking Estimate for the individual substances

All criteria equally important Cr1-Cr4 > Cr 5-Cr10 Cr3-Cr4 > Cr1-Cr2 > Cr5-Cr19

Some simple observations concerning the test scenario

Acu

te in

hala

tion

(Cr1

)

Acu

te in

gestio

n (C

r2)

Ch

ron

ic (Cr3

)

Gen

eric d

isord

er (C

r4)

Perso

nal ca

re (C

r5)

Pain

t an

d co

lou

ring

(Cr6

)

Hou

se h

old

dete

rgen

t (Cr7

)

Pest co

ntro

l (Cr8

)

Solv

en

ts (Cr9

)

Vario

us (C

r10

)

43 47 18 17 6 66 39 24 20 38

•The majority of the 145 substances are ranked in the lower of the risk scenario ranking

•i.e. having criteria values of “1” on less than 50% of the ten criteria

•57 of the 145 substances have no or little relevance in relation to indoor exposure sources

•28 chemicals of the 78 risk assessed chemicals at EU level, and 30 of 63 the not yet risk assessed chemical, have no criteria values of “1” on the exposure estimator criteria, Cr5 to Cr10, for private consumption in households

Additional facts!

• The absolute top candidate, i.e. highest risk chemical, is benzene

• Except for 2-butoxyethanol and ethylbenzene, all top candidates are have positive scores on the chronic toxicity criteria

• Two top candidates, i.e. solvent naphta and stoddard solvent, are not on the EU priority lists of chemicals.

– These are examples of top scores in the Danish emission inventory with an indicated high frequency of use in private household conditions having criteria values of 1 on all exposure estimator criteria except for Cr5, personal use. Both are acute toxic by inhalation, Cr1, and show potential for chronic and irreversible health effects, Cr3.

• Two top candidates, i.e. 2-butoxyethanol and ethylbenzene, have not been subjected to RA at EU level but are on the priority lists.

– These substances show no chronic toxicity related to Cr3 and Cr4. Both substances have a high frequency of use in terms of consumer product categories.

The methodological Approach• The System Model

– increases awareness of boundary conditions of the risk problems• hypothesis driven approach• Ignorance

– increases awareness uncertainty induced by • delimitations of the problem three• approximation of sub-problems by criteria

– increases awareness data availability and aggregation level of the scenario description

• The Multi Criteria Ranking model – Input parameters / criteria values are binary

• thus only able to take one out of two possible values as “high” or “low” • which makes it possible to define an Event Space that includes all possible criteria data

values• . which makes it possible to identify substances that have the same criteria data value

combination

– the possibility of defining relative criteria importance prior to object ranking

– the ability of quantifying multi-attribute uncertainty

Thanks!

Documents

Multi-criteria selection of human health scenarios due to private consumption 1. International Open Nomiracle workshop, June 2006 Marianne Thomsen Multi-criteria