The UK is committed to net-zero carbon emissions by 2050, so in 2022 Carbon Footprinting is more important than ever. Temple is committed to removing carbon from our operations and supporting the transition to zero-carbon globally. We are signatories to the Pledge to Net Zero and have measured and reduced our carbon emissions for the past decade. This last year has been particularly interesting.
Firstly, looking back on what was a somewhat unprecedented 18+ months, the COVID-19 pandemic brought a shift in the UK’s Greenhouse Gas (GHG), measured as Carbon Dioxide equivalents (CO2e). The pandemic induced lifestyle impacts of 2020 led to a huge 13% decline in the 2019 CO2e emissions – the largest recorded drop since records began in 1990. As the latter half of 2021 saw a return to some form of normality, Temple wanted to use this 2020 drop as a focal point for any potential shortcuts we could take in reducing our own CO2e emissions.
Upon examination, it became apparent the largest contributing factor to the national 2020 decline was the mass reduction in emissions associated with the transport sector, which fell by 40% from 2019. This was a dynamic we had not fully explored when measuring our company footprint, given we had not previously included commuting, only business travel. In 2021 we added commuting to our footprint.
In 2021, Temple went through a business restructure, which resulted in over a 50% increase in employees, mostly ecologists who travel to the site for surveys, increasing our business travel significantly.
We also decided to add data storage (server) associated with CO2e to our calculations to produce a more complete footprint.
In essence, this means that 2021 has become a new baseline year for our carbon footprint. This article explores the latter commuting and data storage additions and the challenges they posed.
Calculating the CO2e emissions of our commuting patterns added a new kind of challenge. We looked at Temple employees’ individual journeys to and from the office and calculated the total CO2e emissions for each type of transportation used (train, car, underground, tram, etc.). We used a survey to gather our data and scaled it up to represent all employees company-wide to produce the best estimate figure for our commuting.
Another factor we had not previously considered was the CO2e associated with the use of servers. Data storage has become crucial in the 21st century but often being off-site (i.e. ‘the cloud’) can make it a bit abstract and overlooked, we felt the importance of including server emissions in our footprint was vital, however, this was no mean feat. Due to the nature of this sector, calculating our server usage was not that straightforward as there are many variables that come into play, such as the size of the server, its energy usage, and whether it uses renewable energy to run, leading to a lot of assumptions. Thanks to our IT provider and a little research, we know Temple uses approximately 12 cloud servers. Calculations were driven from these figures, assuming we use standard cloud servers (manufacturing of one cloud server produces 160 kgCO2e, and running the server uses 880.2 kWh/year (186.9 kgCO2e). Our provider, Azure Microsoft is committed to using 100% renewable energy by 2025 but has not published its progress to date, so we assumed a worst-case scenario that the servers currently run-on traditional energy sources.
Commuting and data storage both contribute to scope 3 (Scope 3 Emissions – unglobalcompact.org.uk), meaning they are indirect emissions that Temple is not in direct control of. To a certain extent, this means they are more complicated to calculate and require more broad assumptions.
Overall our Scope 3 emissions formed 17% (88.7tCO2e) of our total footprint. Commuting contributes 6.4% (34.3 tCO2e) and data storage to 0.8% (4.2 tCO2e).
Engagement in the staff survey was better for 2021 than 2020 (57% response rate in 2021, compared to 40% in 2020), but we still had to rely on several assumptions when scaling up our data, which for a large group of individuals can lead to misrepresentation.
The same is true for CO2e emissions from data servers, our final figure is reliant on a lot of assumptions, including the type and efficiency of the hardware we use. The calculation of energy usage is further complicated as the servers are located in data centres and shared with other users. The amount of energy a server uses also depends on how much data is stored, unfortunately, information on cloud storage emissions is not widely available posing a further problem.