Expert Elicitation

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Expert Expert Elicitation Elicitation A Worked Example

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Expert Elicitation. A Worked Example. Avoiding Bias. Basing judgement on all knowledge and consider all available relevant evidence; Consider the widest possibilities for a range of values and not be constrained by a particular value or range; - PowerPoint PPT Presentation

Transcript of Expert Elicitation

Page 1: Expert Elicitation

Expert ElicitationExpert Elicitation

A Worked Example

Page 2: Expert Elicitation

Avoiding Bias Basing judgement on all knowledge and

consider all available relevant evidence; Consider the widest possibilities for a

range of values and not be constrained by a particular value or range;

Be prepared to contradict your own previous thinking and statements

Be realistic about your level of confidence or experience of a particular subject;

Avoid decisions that might be biased towards organisational goals.

Page 3: Expert Elicitation

Component Chosen values1) % that is solvent based ink 75%2) % solvent content of ink 60%3) % Inks use in unabated plant 10%4) % lost from abated plant 10%

EF for unabated Plant 45.0EF for abated Plant 40.5

EF for current mix kg/t inks used 85.5

Emission Parameters

a) % that is Solvent based ink

b) % Solvent content of ink

c) % inks used in unabated plant

d) % lost from abated plant

75%

60%10%

10%

a * b * (c + (1-c) * d) = 85.5

Page 4: Expert Elicitation

Probability Distribution Functions

Lognormal

Uniform

Triangular

Distribution Types:

normal

MeanMin Max

Page 5: Expert Elicitation

Sales of Solvent based Inks

a) % that is Solvent based ink

b) % Solvent content of ink

c) % inks used in unabated plant

d) % lost from abated plant

75%

60%10%

10%

Min Max UncertaintyMean

74% - 76% --

Page 6: Expert Elicitation

60% Solvent

45% Solvent 75% Solvent

Most Likely

Least Likely

80% ?40% ?Extremes

65% Solvent55% Solvent

Likely average value range

Solvent Content Assessment

55% - 65% +- 8%60%10%

10%

a) % that is Solvent based ink

b) % Solvent content of ink

c) % inks used in unabated plant

d) % lost from abated plant

75%Min Max UncertaintyMean

74% - 76% --

Page 7: Expert Elicitation

13%

Assumed 2 additional unabated plant

Assumed all 11 plant are abated

40%

Assumed all 11 plant are unabated

Of 11 unknown plant

Min MaxMost Likely

Least Likely

55% - 65% +- 8%60%

10%

10%

a) % that is Solvent based ink

b) % Solvent content of ink

c) % inks used in unabated plant

d) % lost from abated plant

75%Min Max UncertaintyMean

74% - 76% --

7%

Known level of unabatement

7% - 13% +- 30%

% of solvent Ink consumption in unabated plant

Page 8: Expert Elicitation

10% 20%

Extremes

5% 15%

Most Likely

Least Likely

Min Max UncertaintyMean

55% - 65% +- 8%60%

10%

10%

a) % that is Solvent based ink

b) % Solvent content of ink

c) % inks used in unabated plant

d) % lost from abated plant

75% 74% - 76% --

7% - 13% +- 30%

% losses due to Fugitive

5% - 15% +- 50%

Min Max

Page 9: Expert Elicitation

a) % that is Solvent based ink 75% 74% - 76% --

Min Max UncertaintyMean

55% - 65% +- 8%60%b) % Solvent content of ink

10%c) % inks used in unabated plant 7% - 13% +- 30%

10%d) % lost from abated plant 5% - 15% +- 50%

Summary

Combining UncertaintiesApproach 1 (Equation)

Approach 2 (Monte Carlo)

85.5kg/tonne ink +- 29%

Use Good Practice Guide

Page 10: Expert Elicitation

Elicitation Documentation

D o c u m e n t a t i o n E l e m e n t D o c u m e n t a t i o n E x a m p l e

R e f e r e n c e n u m b e r f o r j u d g e m e n t ; E J I P P U 2 0 0 5 - 0 0 1 - i n k s

D a t e ; 5 t h S e p t e m b e r 2 0 0 5

N a m e o f e x p e r t ( s ) i n v o l v e d D r S P e n n i n g

E x p e r t s ’ b a c k g r o u n d ( r e f e r e n c e s , r o l e s , e t c . ) ; P r i n t i n g i n k s e m i s s i o n s e x p e r t

T h e q u a n t i t y b e i n g j u d g e d ; N a t i o n a l e m i s s i o n f a c t o r f o r C O 2 f r o m P r i n t i n g i n k s

T h e l o g i c a l b a s i s f o r j u d g e m e n t , i n c l u d i n g a n y d a t a t a k e n i n t o c o n s i d e r a t i o n . T h i s s h o u l d i n c l u d e t h e r a t i o n a l e f o r t h e h i g h e n d , l o w e n d , a n d c e n t r a l t e n d e n c y o f a n y u n c e r t a i n t y d i s t r i b u t i o n ;

S e e M i n u t e s o f t h i s m e e t i n g

T h e r e s u l t : e . g . a c t i v i t y v a l u e , e m i s s i o n f a c t o r o r f o r u n c e r t a i n t y t h e p r o b a b i l i t y d i s t r i b u t i o n , o r t h e r a n g e a n d m o s t l i k e l y v a l u e a n d t h e p r o b a b i l i t y d i s t r i b u t i o n s u b s e q u e n t l y i n f e r r e d ;

I d e n t i f i c a t i o n o f a n y e x t e r n a l r e v i e w e r s ; M r I n k w e l l f r o m I n k e r s I n c . & M r s I n k s i g h t f r o m E S C A T

R e s u l t s o f a n y e x t e r n a l r e v i e w ; T B A

A p p r o v a l b y i n v e n t o r y c o m p i l e r , s p e c i f y i n g d a t e a n d p e r s o n .

T B A

C o m p o n e n t C h o s e n v a l u e s M i n M a xE x p r e s s e d

u n c e r t a i n t y1 ) % t h a t i s s o l v e n t b a s e d i n k 7 5 % 7 5 % 7 5 % + - 0 %2 ) % s o l v e n t c o n t e n t o f i n k 6 0 % 5 5 % 6 5 % + - 8 %3 ) % I n k s u s e i n u n a b a t e d p l a n t 1 0 % 7 % 1 3 % + - 3 0 %4 ) % l o s t f r o m a b a t e d p l a n t 1 0 % 5 % 1 5 % + - 5 0 %

E F f o r u n a b a t e d P l a n t 4 5 . 0 2 8 . 9 6 3 . 4E F f o r a b a t e d P l a n t 4 0 . 5 1 9 . 2 6 3 . 6

E F f o r c u r r e n t m i x k g / t i n k s u s e d 8 5 . 5 4 8 . 1 1 2 7 . 0