The emep eea emissions inventory guidebook
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The EMEP/EEA Emissions Inventory Guidebook . Dr Chris Dore Chair of the TFEIP . Contents. Accuracy In Emission Inventories Principles of Uncertainty Uncertainty Tools Conclusions Discussion Points. 1. Accuracy. Does it matter?!

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The EMEP/EEA Emissions Inventory Guidebook

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The emep eea emissions inventory guidebook

The EMEP/EEA Emissions Inventory Guidebook

Dr Chris Dore

Chair of the TFEIP


Contents

Contents

  • Accuracy In Emission Inventories

  • Principles of Uncertainty

  • Uncertainty Tools

  • Conclusions

  • Discussion Points


1 accuracy

1. Accuracy

Does it matter?!

  • Actually, it is not very important for demonstrating compliance with targets

  • But key for trying to reflect the real world.


1 accuracy1

1. Accuracy

Some starting considerations…

  • Point sources vs area sources

  • Source/fuel mix

  • Activity data – trends with time vs absolute

  • EFs – variations across time series, applicability

  • Completeness vs guidebook

  • Completeness vs real world

  • Mapping emissions

  • Projections & scenarios


1 accuracy2

1. Accuracy


2 principles of uncertainty

2. Principles of Uncertainty

  • Uncertainty analysis is generally used to represent “accuracy”

  • Point sources- combination of random independent errors

  • Area sources- one EF, prone to bias.


3 uncertainty tools 1

3. Uncertainty Tools (1)

Propagation of Errors

  • Assign uncertainty to AD and EF

    • from measurement, default ranges, expert judgement

  • “,… root the sum of the squares…”

  • Simple mathematical combination of elements to give an uncertainty for the total emission.


3 uncertainty tools 2

3. Uncertainty Tools (2)

Monte-Carlo Analysis

  • Uncertainty profiles, accounts for inter-dependencies...

  • Much better tool, but more challenging to use.


3 uncertainty tools 3

3. Uncertainty Tools (3)

Trend Uncertainties

  • Standard tool used for assessing the uncertainty in the trend included in the Guidance.


3 uncertainty tools

3. Uncertainty Tools

Strengths

  • Methodologies common with GHGs (UNFCCC)

  • Standard mathematical approaches for assessing uncertainty

  • Simple methods available.


3 uncertainty tools1

3. Uncertainty Tools

Weaknesses

  • Low uncertainty does not necessarily mean good accuracy!

    • incomplete inventory, use of inappropriate EFs etc.

  • Uncertainty ranges applied to EFs are usually no better than a guess!

    • Not usually enough data points for a statistical analysis

  • Error propagation analysis is too simple

    • Does not account for interdependencies/biases etc.

  • Modellers want uncertainty on mapped emissions.


3 uncertainty tools2

3. Uncertainty Tools

Development of New Tools

  • Moran’s co-efficient

    • A mathematical metric of spatial autocorrelation (chess board = -1, random = 0, uniform = +1).

    • Indicates adjacent grid cell dependencies

  • Uncertainty of mapped emissions


3 uncertainty tools3

3. Uncertainty Tools

Development of New Tools

  • Uncertainty of mapped emissions

  • Combination of emissions uncertainty with mapping uncertainty


3 uncertainty tools4

3. Uncertainty Tools

Learning from the Past


4 conclusions

4. Conclusions

Important Considerations

  • EF uncertainties are not robust enough

  • Error propagation analysis - too simple?

  • Uncertainty analysis does not indicate the ability to represent the real world

  • Modellers want uncertainty on mapped emissions.

  • … we need to improve what we are delivering!

  • … and in particular better explain what it represents.


5 discussion points

5. Discussion Points

Some Questions

  • Can we improve current EF uncertainties?

  • Should we all be using Monte-Carlo analysis?

  • Can we add to/adjust uncertainty results to give an indication of real-world representation?

  • Can tools be developed that better provide the information that users need?

  • What resources do we have to support this?


The emep eea emissions inventory guidebook

THANK-YOU FOR

YOUR ATTENTION


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