The C Free Carbon Footprint Calculation Methodology

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This document is intended to give a description for both technical and non-technical readers of the nature and methodology of our carbon footprint calculations.

Throughout this document we will describe the algorithms that we use to calculate carbon footprints for clients we work with. However, many businesses have features of their practices unique to them. The algorithms used for calculation of such activity thus requires specific design for the given case and therefore cannot be elucidated here. However, these details can always be found in the report associated with any given calculation. Indeed, if you wish to understand the specifics of any particular calculation, the associated report is the best place to look. Such reports and this document should independently verify the validity, efficacy, and innovative nature of our approach. Having said this, this document will elucidate our approach to such situations and demonstrate the principles by which we conduct our calculations.

All of our calculations follow the Greenhouse Gas Protocol. This is the standard internationally renowned carbon calculations methodology. In our view, a major impediment to the uptake of carbon footprint calculations is the ease of use; without appropriate technology, calculations can take weeks of data collection and calculation. Therefore, we have built our algorithms to standardise data collection from clients making it simple for them to collect the data we need to calculate.

In addition we have built a comprehensive test suite for our calculation software, where changes to the code are validated against peer reviewed and government released carbon footprint data, and an uncertainty calculation module, implementing the pedigree matrix approach. Details can be found at the end of this document.

Key Terms

Scopes 1 & 2


Although gas consumption is often part of scope 1, many companies we work with rent their offices, making gas consumption part of scope 2. Therefore, we have grouped scope 1 and 2 to reflect this ambiguity. We then separate scopes 1 and 2 when reporting back to the company depending on the situation of that specific client.


Typically, either the body we are calculating for (client), or a close partner of theirs (e.g. landlord) has access to the kWh of gas consumed. We collect this in our activity spreadsheet for all the premises under the control of the client. In cases were gas is metered for an entire building of which the client only has partial financial control, we typically collect the area under their control and divide it by the total rented area in the building, to get an approximate factor for their usage.


We take gas emission factors from DBEIS published statistics.


We combine the annual usage of kWh (where necessary, factored by the proportion of area of the building under operational control), xfx_f, with the appropriate emissions factor, efe_f, to get the emissions due to this activity, EfE_f, as follows:

xgas[kWh]×egas[kgCO2ekWh]=Egas[kgCO2e]\begin{equation}x_{gas} [kWh] \times e_{gas} [\frac{kgCO2_e}{kWh}] = E_{gas}[kgCO2_e]\end{equation}

where xgas=xT×a1aTx_{gas} = x_{T}\times \frac{a_1}{a_T}, where xTx_T, a1a_1, and aTa_T are the total gas usage, the area of the building under operational control of the client, and the total rented area of the building respectively.

Electricity/ heating/ steam/ cooling

The first three in this list represent energy being converted elsewhere into a useful form to be consumed by the client and are therefore scope 2. Although cooling does not exactly fit this description, the methodology used to calculate is similar, and it also belongs to scope 2.

Due to the introduction onto global energy markets of specific contracts designed to incentivise green energy production (RECs), two types of electricity calculation can be applicable; location-based which assesses the grid mix for a given area, and market-based, where the specific nature of the contract the client has with their energy supplier is taken into account. For instance, many green tariffs are available in the UK that use a majority renewable energy sources to supply energy. This would result in a lower market-based emissions factor. Location-based calculations are mandatory to report, where as market-based are only reported where relevant.


As with the previous section, we collect the kWhs consumed in an activity spreadsheet. Again, this is typically known by the client but in some cases, electricity is metered for a group of companies. In such a case we adopt the same strategy.


For location-based electricity calculations we take our factors from DBEIS published statistics for UK companies. For other nations, we take the emissions factor from the relevant governmental body in that nation or, if unavailable, from UN data.

For market-based electricity calculations we inspect the terms of the contract that the client has with the energy supplier, confirming that it satisfies the GHG protocol’s Scope 2 Quality Criteria.


The calculation takes the following form:

xenergy[kWh]×eenergy[kgCO2ekWh]=Eenergy[kgCO2e]\begin{equation}x_{energy} [kWh] \times e_{energy} [\frac{kgCO2_e}{kWh}] = E_{energy}[kgCO2_e]\end{equation}


Often companies consume fuel, typically inside company owned vehicles. This is therefore scope 1.


Typically companies will have fuel data from fuel cards and therefore have a record of litres of fuel consumed. This is collected in the activity data spreadsheet. Alternatively, in some cases distance travelled is recorded, which again is collected in our activity spreadsheet. However, in some cases this data is not retained. In these cases, we automatically process the account transactions of the client, and extract all fuel purchases.


For fuel consumption or emissions-per-distance-travelled we take our emissions factor from DBEIS. If only spending is available, we take the average price of fuel over the reporting period.


According to the data available, there are two calculation methodologies that apply.

Vfuel[L]×efuel[kgCO2eL]=Efuel[kgCO2e]\begin{equation} V_{fuel}[L]\times e_{fuel}[\frac{kgCO2_e}{L}] = E_{fuel}[kgCO2_e] \end{equation}
Dtravel[km]×etravel[kgCO2ekm]=Etravel[kgCO2e]\begin{equation} D_{travel}[km]\times e_{travel}[\frac{kgCO2_e}{km}] = E_{travel}[kgCO2_e] \end{equation}

where VV and DD represent volume of fuel consumed and distance travelled respectively. If activity data is not present Vfuel=Sfuel×PfuelV_{fuel} = S_{fuel}\times \langle P_{fuel}\rangle where SfuelS_{fuel} is the total fuel spend and Pfuel\langle P_{fuel}\rangle is the average price of fuel over the accounting period.

Fugitive Emissions

Fugitive emissions occur when a greenhouse gasses leak from an asset into the atmosphere. They are Scope 1 emissions as they are directly caused by the activities of the client.


When leakage occurs, the necessary fluids need to be refilled in the asset. Therefore we allocate these emissions upon the refilling of the asset. This has the added benefit of indicating a measured amount of the leaked fluid as the client will be billed for the amount replaced.


The factors for these fluids are given in DBEIS.


We apply the following equation

ixfug,i[kg]efug,i[kgCO2ekg]=Efug[kgCO2e]\begin{equation} \sum_i x_{fug, i}[kg]* e_{fug,i}[\frac{kgCO2_e}{kg}] = E_{fug}[kgCO2_e] \end{equation}

where ii runs over the fugitive gas leaking assets, and efuge_{fug} and xfugx_{fug} are the fugitive gas emissions factor and the amount of fugitive gas leaked respectively.

Scope 3

Purchased Goods and Services

In general, scope 3 emitting activities are goods and services the client pays for. However, we endeavour, and indeed specialise, in extracting as much activity data as possible from the client in an automatic way. However, some purchased goods and services are (a) core to the business offering and, (b) have high emissions factors e.g. some raw material acquisition. In these instances, we typically ask the client to specifically extract activity data so as to get an honest and accurate impression of the client emissions.


We split purchased goods and services into Raw Materials and Purchasing. If a company has significant raw material usage we ask that they enter the weights into an activity spreadsheet. For less important spending, we automatically process through accounting data, categorising their expenses and applying the spend-based method only where activity data cannot be gleaned from the data fields present in the account.


Due to the wide variety of spending that can be done by a company, we use a huge variety of emissions factors when processing this data. However, we have two significant sources; (1) DBEIS published statistics related to spending and, (2) the Ecoinvent emissions factors database.


We have two primary methodologies for calculating purchased goods and services; the spend-based method,

xspend[£]×espend[kgCO2e£]=Espend[kgCO2e]\begin{equation} x_{spend}[£]\times e_{spend}[\frac{kgCO2_e}{£}] = E_{spend}[kgCO2_e] \end{equation}

and average data method,

xactivity[kg]×eactivity[kgCO2ekg]=Eactivity[kgCO2e]\begin{equation}x_{activity}[kg]\times e_{activity}[\frac{kgCO2_e}{kg}] = E_{activity}[kgCO2_e]\end{equation}
xactivity[unit]×eactivity[kgCO2eunit]=Eactivity[kgCO2e]\begin{equation} x_{activity}[unit]\times e_{activity}[\frac{kgCO2_e}{unit}] = E_{activity}[kgCO2_e] \end{equation}

Here, we receive data in some cases by weight (for certain raw materials) but in some cases in terms of functional units of a given product e.g. number of toilet rolls bought rather than total weight of toilet roll.

Capital Goods

This category pertains to the upstream cradle to gate emissions of capital goods acquired in the reporting period. These are assets with a long life that are required to provide a product or service.


As in the previous section, where emissions are significant and data is available we ask for activity data and use the average data method. If these conditions are not met, we use our innovative accounts processing techniques to assess the spending on different capital goods, extracting activity data where possible.


In many cases, in particular computer equipment acquisition, we apply the supplier specific methodology as many providers have conducted LCAs of their products as part of their offering. If this data is unavailable we follow the same methodology as in the previous section.


For calculation methodology, see previous section.

Fuel- and Energy-Related Activities Not Included in Scope 1 or Scope 2

Due to resistance in the electricity grid, some proportion of electrical energy is lost into the environment. This is known as Transmissions and Distribution (T&D). This decreases the efficiency of the system resulting in slightly increased emissions for electricity consumption. However, this is not a direct or indirect operationally controlled emissions and therefore cannot be grouped with scope 2 electricity consumption.

Further to these emissions, we also consider the emissions associated not with the generation of energy, but with the mining and transportation of the fuel. This is often referred to as Well to Tank emissions (WTT).


The necessary data acquisition strategy is laid out in the Scope 2 electricity section.


The relevant emissions factors for T&D and WTT are supplied by DBEIS.


The calculation methodology follows that laid out in the Scope 2 electricity section.

Upstream Transportation and Distribution

This category includes transportation of products from the companies suppliers to its own facilities where these operations are not under direct operational control of the client. This includes air, rail, road, and marine transport as well as the use of storage facilities such as warehouses not owned or operated by the client.


If upstream transportation represents a significant proportion of the client footprint, we collect specific activity data about the journeys including mode of transport, start location, and end location in an activity spreadsheet. However, if very little upstream delivery occurs and it does not represent a significant part of the client operations, we again extract the necessary information from the accounts and apply the spend-based method.


All emissions factors for these calculations are supplied by DBEIS.


In instances where activity data is collected, we automatically process this data using various APIs/ datasets to calculate the distance covered. We then apply the emissions factors according to the distance equation given in the fuel section in the following way

iDi[km]ei[kgCO2ekm]=Edistribution[kgCO2e]\begin{equation} \sum_i D_i[km] * e_i[\frac{kgCO2_e}{km}] = E_{distribution}[kgCO2_e] \end{equation}

where ii runs over the transportation journeys, DD is the distance of that journey, and ee varies with mode of transport.

Mode of transportDistance calculation source
AirCarbon Interface API
RailGoogle API
RoadGoogle API
MarineCERDI sea distance dataset

Waste Generated in Operations

Waste treatment facilities owned and operated by third parties (and thus excluding it from Scope 1) can release greenhouse gasses during both the treatment phase, and during matter deterioration. Typically it includes, landfill use and recycling but can also apply to incineration, composting and wastewater treatment.


In some cases clients work with a specific waste management company, who know precisely the waste disposed of. Otherwise, we ask clients to estimate their usage.


Factors differ based on the methodology used to dispose of the waste. Factors again are taken from DBEIS.


The calculation follows the following methodology

ixwaste,i[kg]×ewaste,i[kgCO2ekg]=Ewaste[kgCO2e]\begin{equation} \sum_i x_{waste, i}[kg]\times e_{waste, i}[\frac{kgCO2_e}{kg}] = E_{waste}[kgCO2_e]\end{equation}

where ii  runs over the different methods of waste disposal.

Business Travel

This category includes emissions from transportation undertaken in vehicles not owned or controlled by the client. This includes transportation undertaken by the client in direct service of its business initiatives (e.g. flights for staff to go to sales meetings).


We either collect activity data (including end points, number of travellers, mode of transport) through the spreadsheet or try to extract activity data using our accounts processing routines. If such information is unavailable we rely on the spend-based method.


Business Travel factors again are taken from DBEIS.


If activity data is present, in this calculation we use the following equations depending on whether it is public or private transport

iDi[km]ei[kgCO2ekm]=Etravel[kgCO2e]\begin{equation} \sum_i D_i[km] * e_i[\frac{kgCO2_e}{km}] = E_{travel}[kgCO2_e] \end{equation}
ini[passengers]Di[km]ei[kgCO2ekmpassengers]=Etravel[kgCO2e]\begin{equation} \sum_i n_i[passengers] * D_i[km] * e_i[\frac{kgCO2_e}{km*passengers}] = E_{travel}[kgCO2_e] \end{equation}

where DD is distance, nn is the number of passengers, and ii runs over the different transport methods. We calculate distances using the APIs given in the table in the upstream transportation and distribution section. Otherwise, we use the spend-based method given in Purchased Goods and Services.

Employee Commuting

Commuting includes all emissions resultant from employees travelling to and from their workplace. We also include working from home in this category (as per the GHG protocol).


As employers often don’t have data regarding their employees commuting habits, we issue a survey to all employees which procures data about their commuting habits in any given month in the reporting period. This includes the employee’s postcode, their primary office postcode, their mode of transport while commuting, and the number of times they commuted in a given month.

For working from home, we use data collected in an employee survey to ascertain the number of days spent working from home in any given month.


Commuting factors as well as working from home factors are again taken from DBEIS as well as working from home factor.

In some historical calculations, we used average increased energy consumption to measure home working emissions as specific emissions factors for this activity were not yet published.


This calculation using the google API to calculate commute distances. With those we apply the equation given in the distance methodology in the fuel section.

ji2ni,jDi,j[km]ei,j[kgCO2ekm]=Eemployee_commuting[kgCO2e]\begin{equation} \sum_j\sum_i 2*n_{i,j}*D_{i,j}[km]*e_{i,j}[\frac{kgCO2_e}{km}] = E_{employee\_commuting}[kgCO2_e] \end{equation}

where i,ji,j  run over the employees and the months of the reporting period respectively, nn is the number of days worked in the office in a given month by a given employee, DD is the distance travelled by the employee, and ee varies with respect to the mode of transport used. The factor of 2 comes from the assumption that the employees returned home with same method that they came to work.

For working from home, we use the following equation

jini,j[day]ei,j[kgCO2eday]=EWFH[kgCO2e]\begin{equation} \sum_j\sum_i n_{i,j}[day]*e_{i,j}[\frac{kgCO2_e}{day}] = E_{WFH}[kgCO2_e] \end{equation}

where i,ji,j are the same as before, but nn is the number of days working from home in a given month for a given employee.

Upstream Leased Assets

Clients that operate through leasing others inventory equipment that they is not included in scope 1 and scope 2 will include those emissions here.


To calculate the emissions form this activity we follow either asset specific, leaser specific methodology, or average data methodology. If the first, we collect the scope 1 and 2 data for the asset. If the second, we collect the scope 1 and 2 of the leaser. Typically, the third would be applied to rented building space where we would usually define the organisational boundaries such that these are included in scope 1 and 2.


The factors required vary greatly depending on the asset in question. Typically we would find the functional unit of consumption for the given asset and find an emissions factor in terms of that functional unit. These would most likely follow the same methodologies as that in scope 1 and 2 sections.


This methodology will typically follow that laid out in the scope 1 and 2 section where we would sum over the leased assets (as shown in the following equation). If this is impossible, we apply the spend-based method following the spend-based equation given in Purchased Goods and Services.

ixi[kWh]ei[kgCO2ekWh]=Eleased[kgCO2e]\begin{equation} \sum_i x_i[kWh] * e_i[\frac{kgCO2_e}{kWh}] = E_{leased}[kgCO2_e] \end{equation}

where ii runs over the leased assets.

Downstream Transportation and Distribution

Downstream Transportation pertains to the transport emissions of distribution of products and services to clients in vehicles not owned or controlled by the client. It also includes warehouse emissions.


Although our methodology can follow the upstream equivalent, in many cases clients use distribution services that track the data precisely (e.g. royal mail). In such cases, we directly process activity data from the partner.


We use the same factor sources given Upstream Transportation and Distribution.


The calculation methodology is the same as in Upstream Transportation and Distribution. Having said this there is a common complication; how to account for shared distribution services (e.g. royal mail)? In this case, we allocate by weight of package as a proportion of the vehicles average load assuming a van is used for transportation.

Processing of Sold Products

The processing of sold products pertains to emissions produced in the processing of sold products (in the reporting period) by a third party before they are sold. Although there can often be multiple downstream applications and therefore the emissions associated with this category cannot be reasonably ascertained, there are certain cases in which a product is universally sold to third party (or type of third party) which undertakes specific processing of that component. In such cases, we can calculate the emissions resultant from this as part of the downstream emissions profile.


If the client has a strong relationship with the downstream partner, we will get scope 1 and scope 2 emissions data relating to the processing of the clients sold product directly from that partner in an activity data spreadsheet. If this is unavailable, we will get the number of units sold (or a reasonable alternative unit e.g. mass).


In the first case, factors we use would be the same as those given in the scope 1 and 2 sections. In the second case, matters are not so simple. We would search manufacturing and processing emissions factors in the Ecoinvent database and, failing that, peer reviewed LCA research.


In the first case, the calculation follows those laid out in Scope 1 and 2. In the case where such data is not applicable we follow

xprocessing[unit]×eprocessing[kgCO2eunit]=Eprocessing[kgCO2e]\begin{equation} x_{processing}[unit]\times e_{processing}[\frac{kgCO2_e}{unit}] = E_{processing}[kgCO2_e] \end{equation}

where unit is the suitable unit of processing gathered from the client (e.g. number of components/ kg).

Use of Sold Products

Similarly to the previous, in some cases a clear use case for a product can be established which has some emissions.


Again, if feasible, we gather scope 1 and 2 data from the downstream partners using the product. If this is untenable, we look collect a reasonable functional unit of the product sold.


In the first case we follow the scope 1 and 2 sections. In the second, we again rely on the Ecoinvent database or peer reviewed LCA research.


The calculation methodology follows that of the previous section.

End-of-Life Treatment of Sold Products

This category includes emissions resultant from the disposal of sold products at the end of its life for all products sold in the reporting period.


We collect the total mass of products sold (including packaging) in the activity spreadsheet.


Typically we will take the waste treatment factors from DBEIS statistics.


We apply the following equation

imi[kg]eproduct_waste,i[kgCO2ekg]=Eproduct_waste[kgCO2e]\begin{equation} \sum_i m_{i}[kg]*e_{product\_waste,i}[\frac{kgCO2_e}{kg}] = E_{product\_waste}[kgCO2_e] \end{equation}

where mim_i is the mass of waste being disposed of with treatment method ii and eproduct_waste,ie_{product\_waste,i} is the relevant emissions factor for that treatment.

Downstream Leased Assets

This category includes emissions resulting from assets owned by the client and leased to other users.


We collect the total scope 1 and 2 emissions for the given leased asset.


These will mirror those given in the scope 1 and 2 sections.


This will reflect the methodology of scope 1 and 2 where we sum over the leased assets.


This section includes emissions from businesses operating under a licence to distribute and sell the clients good and services from a specific location.


Should data be available, we adopt the franchise specific method where we collect individualised scope 1 and 2 emissions data from each franchise. Otherwise, we use the average data method where we collect the number of franchises, the floor space, and information on any carbon emitting activities specific to a given franchise (e.g. company cars).


If we adopt the franchise specific method, the factors used will be those given in the Scope 1 and 2 sections. In the alternate case, we take the emissions factors for floor space and for the extra assets given (e.g. company cars)


The calculation follows the following formula

iAi[m2]efran,i[kgCO2em2]+jnjeasset,j[kgCO2easset]=Efran[kgCO2e]\begin{equation} \sum_i A_i[m^2]*e_{fran,i}[\frac{kgCO2_e}{m^2}] + \sum_j n_{j}*e_{asset,j}[\frac{kgCO2_e}{asset}] = E_{fran}[kgCO2_e] \end{equation}

where AiA_i is the area of franchise ii, and njn_j is the number of a given type of asset class.


This section is relevant to companies that invest with the intention of making profit, such as investors or financial service companies. If such a client has significant investment that produce greenhouse gasses which must be accounted for.

For the purposes of these calculations, there are four categories of investment:

  1. Equity investment
  1. Debt investment
  1. Project finance
  1. Managed investment and client services (e.g. mutual funds)


Equity investment

If scope 1 and 2 of the investee are known, we take these along with the equity owned. If this is unavailable, we use the average data approach. In this case we collect the equity share, the sector the investee operates in, and the investee’s total revenue.

Debt investment

If the use of the loan by the investee is known there are two possible approaches; project-specific and average data methods. In the first case, we take the scope 1 and 2 emissions resultant from the project invested in as well as the proportional share of the total project cost. In the alternate case, we take the clients proportional share of the project cost as well as the total project cost (if in construction phase) and project revenue (if in revenue phase).

When the use of the debt is unknown, methodology follows that of equity investment.

Project investment

Project investment follows the same calculation methodology as debt investment where the use of the debt is known.

Managed assets

Managed assets can be reported using the previous methodologies. However, asset managers are not the intended target of the GHG protocol and have specific issues that are not addressed in the supporting documents. Therefore, we would advise such a client to seek specialist advise.


To date, we have not conducted a calculation of an investment company that would require this kind of calculation. Therefore we have not collected emissions factors for this section. However, relevant emissions factors can be found in the following databases.


The calculations follow the following formulas for each section.

Equity investment

iEi[kgCO2e]si[%]=Eequity[kgCO2e]\begin{equation} \sum_i E_i[kgCO2e]*s_i[\%] = E_{equity}[kgCO2_e] \end{equation}

where EiE_i  is the emissions factor for the investee (whether calculated by their scope 1 and 2 emissions or by taking an average for a company in that sector)

Debt investment

When the use of the debt is known

iCi[£]ef,i[kgCO2e£]si[%]=Edebt[kgCO2e]\begin{equation} \sum_i C_i[£]*e_{f,i}[\frac{kgCO2_e}{£}] * s_i[\%] = E_{debt}[kgCO2_e] \end{equation}

where CiC_i  is either the project construction cost or the revenue depending on the phase of construction.

When the use of the debt is unknown we follow the methodology of equity investment.

Project investment

See debt investment where the sue of the debt is known.

Managed assets

We follow the methodology of equity investment.

Uncertainty Calculation

According to the pedigree matrix method, each parameter is assigned a geometric standard deviation (assuming log-norm distributions) with a 95% confidence interval.

σj2=e[ln(Uj)]2\begin{equation} \sigma_j^2 = e^{\sqrt{\sum [ln(U_j)]^2}} \end{equation}

where UjU_j represent different uncertainty factors.


ln(σtotal)2=Sj2(ln(σJ)2)\begin{equation} ln(\sigma_{total})^2 = \sum S_j^2(ln(\sigma_J)^2) \end{equation}

where SjS_j is the given significance of each parameter.

Test Suite

Our test suite tests our algorithms against established carbon footprint data to validate our calculations. We allow for a 2% variation for all test methodologies except those using the google api which has some natural variance associated with it and therefore we allow 5%. This is both (a) a very ambitious target and (b) trivial compared to the error resultant from data collection.