Department of Geographical and Earth Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
School of Biological and Environmental Sciences, University of Stirling, Stirling, FK9 4LA, UK
Summary of the CLAD-hosted Carbon Calculator Meeting
(Friday 7th May 2010)
Dr Jo Smith: School of Biological Sciences, University of Aberdeen (jo.smith@abdn.ac.uk)
Dr Dali Nayak: School of Biological Sciences, University of Aberdeen (d.nayak@abdn.ac.uk)
Dr Simon Drew: Department of Geographical & Earth Sciences, University of Glasgow.
School of Biological & Environmental
Sciences, University of Stirling. (Simon.Drew@stir.ac.uk)
Dr Ian Grieve: School of Biological & Environmental Sciences, University of Stirling.(i.c.grieve@stir.ac.uk)
Dr Susan Waldron: Department of Geographical & Earth Sciences, University of Glasgow. (Susan.Waldron@ges.gla.ac.uk)
Introduction
This document presents the proceedings of a meeting hosted at Glasgow University and organised
by the CLAD (Carbon Landscapes and Drainage) project. CLAD is a knowledge-exchange network
funded by NERC (the UK Natural Environment Research Council) with the overall aim of exchanging
knowledge among stakeholders with interests in carbon-rich landscapes. CLAD specifically aims to
enhance understanding of the effect of disturbance on carbon losses in peatlands, and improve
management practice through a program of events and other mechanisms. Its membership includes
a wide range of interest groups including renewable developers and landowners, conservation
groups, regulators, researchers and environmental consultants. The meeting provided a forum to
allow the authors of the Carbon Payback Calculator for Windfarms on Peatland (Drs. Nayak and
Smith) to present their work, with recent amendments and additions, to an audience representing
the stakeholder community drawn the CLAD membership and others. It also provided an
opportunity for this group to present questions to the authors based on their experiences of using
the calculator and also wider aspects of its use.
A video record of sections of the meeting can be found on the CLAD-TV Youtube channel
(http://www.youtube.com/user/n2242880#p/u).
This document should be cited as ‘CLAD Meeting Notes (2:2010): Summary of the CLAD-hosted
Carbon Calculator Meeting.’
Session 1 ‘The windfarm carbon payback calculator: the scientific basis for
the calculator and structural components and assumptions’. Dr Dali Nayak
(Aberdeen University)
Dali outlined the details of the Calculator and its development to date
Windfarms are more likely to be developed in rural exposed areas where peat resources are more
prevalent. The calculator was developed following worries that the carbon savings generated by
windfarms were counterbalanced by losses of carbon in peat soils during the development process.
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Annual carbon emission savings from windfarms were calculated using the calculator and compared
with total losses of carbon from different components of the development process. The
infrastructure carbon overheads were outlined with respect to turbines. Backup power generation
required to account for variability in wind energy generation was considered before accounting for
changes in the carbon dynamics of peatlands. Results of a sensitivity analysis of the equations to the
calculator input parameters indicate water table depth is a particularly important factor and is
clearly affected by the extent of drainage. Losses of carbon due to felling of forestry were considered
as were carbon savings due to habitat improvements such as peatland restoration. An example of
how to apply the calculator was given with respect to a real development in central Scotland.
Payback time was shown to be strongly positively sensitive to the extent of drainage, carbon
sequestered by forestry plantation and the area of forestry felled. Payback time showed strongest
negative responses to the capacity factor and the counterfactual emissions factor.
This was followed by an uncertainty analysis of a range of input variables to determine the effect
that such uncertainty might have on the final payback time of a development. It was found that final
restoration of the site following decommissioning had the largest effect followed by extent of
drainage. It was pointed out that, as extent of drainage has been shown to have a large impact on
payback time but has a large degree of associated uncertainty, this area is ripe for applied research
to answer some of the associated questions pertinent to windfarm developments.
Session 2 ‘The Evolution of the Carbon Calculator for Windfarms on
Peatland’. Dr Jo Smith (Aberdeen University) (This part of the day can be seen on CLAD-TV at
http://www.youtube.com/user/n2242880#p/u/0/v7vi5HvERMs)
Jo Smith of Aberdeen University described some of the recent amendments/changes to the
calculator
Guidance on the need to use the tool has been added as has best/worse case scenarios associated
with a number input variables. Protocols for measurement of different input parameters have also
been added.
Jo introduced the new guidance on the calculator. The previous approach to considering the effect
of forestry was outlined and an explanation was given regarding the new consideration of carbon
losses from felling of forestry. A more sophisticated analysis of the effect of net primary productivity
of the forestry is included. Also, losses from soil carbon due to felling are included as are emissions
from harvesting and savings, if material from short rotation forestry is used as a biofuel. Finally, the
effect of different management options for site forestry operations have been included.
Session 3 ‘Question Time’ (Questions were answered by Dr Jo Smith and Dr Dali Nayak of
Aberdeen University)
Questions in this section were submitted before the meeting and Jo and Dali have also provided
written answers which are included below. For more detailed discussions surrounding these
questions please see CLAD-TV at http://www.youtube.com/user/n2242880#p/u/12/NTqLNKEjuso.
Questions were organised into three broad areas:
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
Detail of the existing model

Windfarm impacts unconsidered

Extension of the C-calculator to different land-uses-places
i) Detail of the existing model
Submitted by Clare Wharmby (SK Enviros).
Q1. One of the key parameters for the model is the average drainage distance. The report states
that: ‘The extent of drainage around the site of construction strongly influences the total volume of
peat impacted by the construction of the wind farm. Where sufficient measurements are available to
describe the hydrological features of the wind farm area, this should be used together with a detailed
hydrological model to simulate the likely changes in peat hydrology. If insufficient measurements are
available, a worst case estimate of extent of drainage around the development features should be
used.’
Is it possible to have further guidance about what a detailed hydrological model would involve in
terms of site measurements? Many of the sites we have worked on are upland sites that are already
disturbed and drained through forestry and are not especially homogeneous in terms of ground
conditions. Discussions with hydrologists indicate that a different approach might need to be taken
for upland sites where topography is more influential in dictating drainage, in comparison with flat
raised blanket bogs where the interconnectedness of the drainage channels might be the key
feature.
A1. The topography, bedrock, soil layers, vegetation and drainage of the site would need to be fully
mapped.
Submitted by Jane MacDonald (SSE Renewables, not present)
Q2. Does the model assume that any excavated peat is lost and that the restoration "Y" button only
kicks in upon decommissioning of the wind farm after 25 yrs, or if you intend to implement
compensatory peatland restoration as part of an HMP?
A2. No, the model assumes that the area of restored borrow pits stated under “Restoration of peat
removed from borrow pits” are adequately restored from the time given under “Time required for
hydrology and habitat of borrow pit to return to its previous state on restoration (years)”. The
carbon remaining in the peat after this time is assumed to be saved from decomposition. There is no
presumption by the model that this will happen: it is up to the user to ensure that the stated
restoration is actually effective. The time to restoration allows the model to account for the
percentage of dewatering / drying out that occurs resulting in some of the C from the extracted and
restored peat from being lost. If the user considers it is unlikely the C in the peat restored in a
borrow pit will be saved from decomposition, it is their responsibility to not include this in the
restoration area. The “Y” button in the “Restoration of site after decommissioning” section only
refers to the restoration of the site that occurs after the lifetime of the wind farm.
Submitted by Katharine Blythe (RPS Group)
Q3. SEPA is currently asking for an indication of the peat which may be disturbed as a result of wind
farm construction - primarily to establish the amount of "waste" peat which will be produced from
wind farm construction, which will require consideration in the peat management plan. The use of
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the "average" depth of peat over the site is therefore not necessarily relevant to this direct
disturbance, as sites may be designed to avoid deep peat so the peat extracted may be less than the
average depth (it is acknowledged that the model also allows for average depth of hardstanding/
roads etc to be inputted separately). Is there potential to calculate the amount of peat extracted
(rather than averages) and use this as the basis for calculations of drainage etc? Or would the wider
impact of drainage over the "averaged" site be the same regardless of the exact amount of peat
removed?
A3. It would be easy to change the spreadsheet to using the volume of peat excavated, rather than
using the volume calculated from the area and the average depth. However, the volume of peat
impacted by drainage would also need to be changed to account for the depth of the features. This
is technically very easy, if users usually have this amount of information to drive the spreadsheet.
We would appreciate feedback on whether this more complex form of input would be preferred.
Submitted by Clare Wharmby (SK Enviros)
Q4. In some cases, we have used the model to predict carbon emissions from sites with different
types of infrastructure. These include: meteorology masts, settlement ponds etc. Would it be
possible to add a category for additional infrastructure, where the total volume of peat removed can
be calculated and entered?
A4. As above, yes definitely, but it would require an additional piece of work. Alternatively, if you
have these figures you can enter them as “Carbon dioxide emissions from turbine life” in the current
spreadsheet.
Submitted by Katharine Blythe (RPS)
Q5. Often the amount of information we have for a site at the ES stage when using the calculator is
pretty basic, and we don't have data on e.g. extent of drainage, carbon sequestration rate, or even
final restoration plans etc. Therefore the suggested default values do often end up being used, or
educated guesses made! Objectors do seem to be cottoning onto the use of default values,
though...Is there an indication as to the effect of any particular value on the model, and how much
this will affect the payback time (i.e. which is the most important parameter to get right?!)? Is
running the model using only the default values and site layout data (km of track, hardstanding areas
etc) effectively useless?
A5. Yes, we have done a sensitivity analysis of the different inputs to the model – now published in
Mires & Peats. In later versions, we intend to include this information in the spreadsheet. We have
also changed the input sheet so that the minimum and maximum value can be entered: this allows
you to do your own quick sensitivity analysis on the inputs. Using the “default” values is effectively
useless: these were never meant to be default values and were only included as an example run.
The following questions were submitted by Janet Moxley (SEPA) (These questions were not
considered on the day but are reproduced and answered here for completeness):
Practical aspects of site operation
Q6. The tool is very sensitive to whether restoration is undertaken. After 25 years the site is unlikely
to be fully restored and it may not be desirable to aim to do this. Site restoration appears to
influence payback time by a factor of 10. What is meant by restore and what are the assumptions
that are made?
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A6. Site restoration means that the hydrology and habitat of the degraded / drained areas of the site
are returned to the state they were in before the wind farm was constructed. The calculator makes
no judgement as to how this should be done: the science of site restoration is still developing, with
some power companies employing ecologists and hydrologists to study restoration of degraded
areas of the site, and significant work being undertaken in universities and research institutes. A
review of available research is needed to inform best practice guidelines. However, for practical
purposes, if the user states the site will be restored, the onus is on the user to ensure the hydrology
and habitat are (as far as possible) returned to the previous state: drains blocked, foundations
removed, species reintroduced.
Q7. A significant consideration is whether after construction drainage is blocked off. In the case
study overall payback changes by nearly 17 years, again the model makes a number of assumptions.
Is it possible to clarify best practice?
A7. Best practice to reduce peat decomposition would be to block drains immediately after
construction. Whether this is best practice in terms of the structural features is one further
consideration, but outside the scope of the carbon calculator. Again, a review of available research is
needed to inform best practice guidelines.
Q8. Borrow-pits can also make a large difference. What are the important parameters relating them
which need to be managed?
A8. The borrow pits should be undrained and the habitat should be restored. Detailed guidelines on
how to successfully restore borrow pits are needed. There is a large amount of research being
undertaken both by power companies and academics that could be used to inform these guidelines.
Q9. How can different peat depths for each turbine be accounted for?
A9. In the current version of the calculator this cannot be accounted for. This is technically easy to
do, if there is general agreement that this is needed.
Underlying theory
Q10. What are realistic assumptions for drainage distances in Scottish peat systems? Table 6.5.1
gives values from 50 m to 1.5 m. The sites with 50 m drainage were i) a fibric peat in Minnesota - not
sure how typical this is of Scottish peat ii) Wicken Fen in East Anglia. I'm not sure about Wicken Fen
specifically, but much of the drainage in East Anglia is mechanically pumped to lower the water table
which would increase the drainage distances. The two intermediate sites may be more like typical
Scottish peat. The other five sites which seem much more typical only drain for 1.5 - 5m. Despite the
largest literature drainage distance found anywhere being 50 m, the paragraph below table 6.5.1
discusses drainage for up to 200m. This does not seem very representative of Scottish peat systems.
A10. The drainage distance depends on topography as well as the peat characteristics. If the site
were perfectly flat, a reasonable estimate of drainage distance could be obtained from
E  11.958  log H   9.361
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where E is the extent of drainage around the site of disturbance (m), and H is the hydraulic
conductivity (mm d-1), as shown in figure 6.5.1 in the report. However, sites are usually not flat.
Therefore, we have not used this equation in the spreadsheet and recommend that you measure the
extent of drainage at each site.
Q11. The calculator assumes that if the site is drained and not restored 100% of the C in the drained
area will be lost. How valid is this given that some soil C is quite reactive and some more
recalcitrant? Is the timescale of loss important? If C is all lost, but over a much longer period than
the lifetime of the windfarm how should this be included in the calculation?
A11. The lifetime of the wind farm is not relevant here. The important fact is that a change to the
site has been made, which will result in decomposition of the soil organic matter until a new steady
state has been reached. This may be reached within the lifetime of the wind farm, or it may be
reached some time afterwards. The losses occurring as the soil moves to the new steady state are
still attributable to the actions of the wind farm developers, even if they occur after the wind farm
has been decommissioned.
In mineral soils, clay minerals help to protect the soil organic matter from decomposition, so a
steady state is reached where plant inputs balance the losses and the soil C content stops changing.
However, in peat soils, the organic matter content is extremely high, and there is very little
protection of the soil organic matter from decomposition. Therefore, in a peat soil, the new steady
state is very close to zero soil C. Some pools of soil organic matter are more recalcitrant than others,
but eventually, most of the soil C will be lost.
The recalcitrance of the soil organic matter is accounted for in the formulae used to determine the
rate of decomposition. In a soil containing more recalcitrant soil organic matter, the losses will be
slower. Therefore, if you fully restore the site on decommissioning a higher proportion of the soil C
can be saved from decomposition than in a soil containing more labile soil organic matter.
Q12. What are the modes of C loss from peat in borrow pits; CO2 emission, CH4 emission or DOC
leaching followed by conversion to CO2? There seems to be an evidence gap in this area, but mode
of loss (especially understanding whether loss is as CO2 or CH4, but also loss rate) is important to
assessing GHG emissions from the site.
A12. This depends on the hydrological state of the peat in the borrow pit. If it is flooded, a higher
proportion will be as CH4 than CO2. If there is free drainage, a higher proportion will be as DOC and
CO2.
Q13. Section 6.7.1 derives site specific equations using multiple linear regression, but it is very likely
that the relationships between e.g., peat depth, water table depth and emission or temperature and
emission are non-linear. How valid is the linear regression approach?
A13. The principle of parsimony states that you should always look for the simplest solution. The
linear regression provided a significant fit, and so this approach was initially used. However, these
equations have since been revised because they were providing inaccurate results at depth. The
equations used are now non-linear.
For acid bogs:
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RCO 2 
CCO 2  C CO 2
 ((6700  exp( 0.26  exp( 0.0515  ((W  100)  50))))  ((72.54  T )  800)
1000
RCH 4 
CCH 4C CO 2
 ((500  exp( 0.1234)  (W  100))  ((3.529  T )  36.67)
1000
For fens:
RCO 2 
CCO 2C CO 2
 ((16244  exp( 0.175  exp( 0.073  ((W  100)  50))))  (153.23  T )
1000
RCH 4 
CCH 4C CO 2
 (( 10  563.62  exp( 0.097)  (W  100))  (0.662  T )
1000
(see Nayak et al, 2009, Mires & Peats).
Submitted by Cameron McIver (Cameron Ecology)
Q14. How should piled foundation designs (where the foundation has peat underneath it) should be
treated in the calculator?
A14. There is not a lot of experimental evidence on this. However, if the design constructs the
foundations on top of a layer of peat, and the impact of the construction is to compress the peat
without drainage, we would suggest the losses will be small and can be left out of the calculations.
The compression of the peat is not likely to increase the rate of decomposition as it remains
anaerobic. The losses from plant input to the peat will remain, but these are a small component of
the total losses.
Mandy Gloyer (Scottish Power)
Q15. Can the model account for beneficial effects from re-planting (e.g. planting broadleaves) or for
different forestry treatments? For example, the CO2 effects would be different if the forestry was
mulched on site, than if it was transported from the site and burned for fuel.
A15. The new version of the spreadsheet is bringing in these specific management issues. Still work
to do on this, and it would be very useful to have input as to what practices need to be included.
ii) Windfarm impacts unconsidered
Submitted by Tom Dargie (Boreas Ecology)
Q16. Calculation of carbon savings from forestry for ground to involve tree felling for a wind farm
The current forestry component of the calculator takes no account of situations in which forestry, to
be cleared for a wind farm, is established on deep peat (>0.5 m depth). Ground preparation of peat
for forestry involves much more extensive drainage than a wind farm. Usually there is complete
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destruction of the acrotelm and thus loss of carbon capture by mire vegetation, unless the peat
retains sufficient wetness to check tree growth (this seems to be rare). Good tree growth inevitably
results in higher evapotranspiration and a very different hydrological balance, including a significant
fall in the water table. The effects of forestry on peat have been documented well at Bad a Cheo
(Flow Country). Predictions of tree growth on peat suggest that after three rotations the carbon
balance becomes negative. Is there scope for offering an option of calculating the short and longterm effects of forestry on deep peat on the carbon balance, to compare with felling and restoration
back to active blanket bog, as part of mitigation for a wind farm development?
A16. The current version of the calculator does take account of drainage of peat due to previous
forestry. This is done in a very simple way through the water table depth at the start. If the area of
and has been previously drained by installing land drains and / or through the evaporative action of
growing trees, this is reflected in the initial water table depth entered in the input data sheet. A
lower initial water table depth will mean that a smaller portion of the peat is considered to be
drained due to the wind farm – or it might even mean that the area of land is considered to be
rewetted and so restoration of carbon at the site occurs.
Submitted by Tom Dargie (Boreas Ecology)
Q17.Wind farm effects on microclimate and the water table in deep peat
The current paradigm, built into the calculator, is that wind farm impacts dry out peat via changes in
drainage, contributing to increases in CO2 emissions. Short and medium-term monitoring (5 - 10
years) of habitats around wind farm infrastructure and broader areas around a turbine array suggest
the opposite might be happening: habitats are becoming wetter, not drier. If these observations are
correct, it suggests that wind speed reduction by kinetic energy capture is sufficient to reduce
evapotranspiration from adjacent mire and areas downwind, raising the water table (or reducing the
fall, critically, in summer), increasing surface wetness. What evidence in peer-reviewed publications
would be required for the calculator to include this effect?
A17. Measurements of the rate of drying that occurs to depth, related to the drivers that control the
changes in the rate of evaporation – e.g., topography, wind speed, average air temperature.
Submitted by Clare Wharmby (SK Enviros)
Q18. The model provides for the input of the turbine lifecycle emissions but does not include the
other building components from the wind farm construction. Significant quantities of material such
as concrete and aggregate are likely to be used. The most significant element is likely to be concrete
used in foundations.
For a turbine foundation of a MM92 (80m hub height) turbine, this equates to 310m 3 of concrete
and 35 tonnes of reinforcement steel per turbine.
a) For the concrete, using the ICE value for high strength concrete of 0.209 kg CO2/kg and a
density of 1500 kg/m3 (www.simetric.co.uk/si_materials), this gives around 97 tonnes of
CO2
b) For the steel, using the ICE value for general steel (recycled content of 43%) of 1.77 kg
CO2/kg, this gives around 62 tonnes of CO2
Therefore for a single turbine foundation, the lifecycle carbon emissions could be around 160
tonnes. For a 2MW turbine, using the ‘calculate with installed capacity’, this would add over 10% to
the estimated value of 1,400 tonnes of CO2 for the turbine lifecycle emissions. The embedded
carbon in the site infrastructure is often flagged up as an issue by decision-makers and therefore
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would it be possible to amend the model to be able to include other site construction materials such
as concrete, aggregate, steel and sand etc.?
A18. The concrete used in construction should be included in the value entered under the “Carbon
dioxide emissions from turbine life”. If the correct value is entered here by the user then these
emissions have been accounted for. It has been suggested by various people that they would like the
calculator to include the assessment of emissions associated with construction. This could easily be
done, but is an additional piece of work. The advantage of keeping the construction emissions
separate is that we are not making any erroneous assumptions about the specific circumstances of
the site.
iii) Extension of the C-calculator to different land-uses-places
Submitted by Clare Wharmby (SK Enviros)
Q19. We also have a number of sites outwith Scotland, which contain peat. How applicable do the
authors consider the model to be for England, Wales and Ireland? (obviously with revised
counterfactual emission factors for the Republic of Ireland).
A19. The model was parameterised using data from a range of sites around Europe. Therefore the
results should be applicable to England, Wales and Ireland as well as Scotland.
Submitted by Katharine Blythe (RPS Group)
Q20. Does the tool still apply where the soil is not peat - just as a way of calculating carbon savings
where forest is to be felled etc? (even though it is probably over-specified for this!).
A20. The next version of the model includes a lot more detail on forestry, so could be used for
mineral soils where forestry is to be felled. The current version includes only a simple description of
forestry, but can be used to do calculations on C losses by assuming that the losses from mineral
soils, which are already drained and contain much less soil C, are negligible. Therefore, the soils
component of the losses is omitted. The spreadsheet could be adapted to do this for you.
Summary
This meeting represented a successful opportunity to allow the stakeholder community to question
the authors of the Carbon Calculator and allow the development of new ideas regarding its
development.
It became clear during the course of the meeting that there has been a significant uptake in the use
of the calculator, generally driven by regulatory comment at various stages of the development
process. It also became clear that there is interest in developing similar calculators for carbon
budgeting exercises in other carbon landscapes.
Representatives from the Scottish Government indicated that a wider ranging consultation exercise
will take place at some point in the future (probably during 2010). Interested parties should contact
the authors.
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There had been some significant misunderstanding over the use of the so-called “default values” in
the model. Jo and Dali stressed that these were not intended as default values per se, but simply
examples of values for a hypothetical case. In applying the model it is essential to use input values
which represent conditions at the site under consideration.
Much of the scientific discussion and questions had focussed on our understanding of site hydrology
(parameters such as drainage distance) and the links between hydrology and carbon losses. There
was clearly concern within both the user community and the research community over these issues,
but also an appreciation that these issues were central to both the work of CLAD and to the further
development of the Carbon Payback Calculator. Further communication between those working on
the two projects should promote exchange of knowledge with mutual benefits