Interest in Science-Based Targets (SBTs) has grown significantly following last year’s Conference of the Parties (COP21) in Paris (which led to a climate change agreement signed by 195 member states) and more recently at COP22 in Marrakech. For a general overview, take a look at Part 1 for a short introduction to Science-Based Targets.
The importance of greenhouse gas emission reductions is expected to have varying implications across different industries. For the commercial real estate sector, there are several issues to consider.
Science-Based Targets: Categorising Emissions
SBT platforms require the input of emissions data, which is then analysed to generate emission reduction targets over time. Greenhouse gas emissions are caused by multiple organisational activities. One way to describe greenhouse gas emissions is through Scopes 1, 2 and 3 according to the GHG Protocol as shown in Figure 1.
Data on emissions from sources is collected, entered into a model, and then targets for each emission scope are set based on the business’ contribution to the overall 2°C reduction plan (agreed at COP21). This relies on the ability to measure and monitor accurately the different categories of greenhouse gas emissions for an organisation’s activities (Figure 1 – GHG Protocol, 2011). The Better Buildings Partnership (2016) recently made this observation, but specifically mentioned the landlord-tenant split and allocation of emissions as the key challenges. The problem for commercial real estate firms is who is made accountable for the emissions– the landlord, the tenant or both?
[clickToTweet tweet=”The problem for #CRE firms is who is accountable for #emissions – the landlord, the tenant or both?” quote=”The problem for commercial real estate firms is who is made accountable for the emissions– the landlord, the tenant or both?”]
We have been asked by clients to explain how Science-Based Targets actually work in practice. This is a good question. At present, there are many approaches available. Examples include: the Sectoral Decarbonisation Approach (SDA); The Absolute Emissions Compression; The 3% Solution; Climate Stabilisation Intensity Targets (CSI); Corporate Finance Approach to Climate-Stabilising Targets (C-FACT); GHG Emissions per Value Added (GEVA) and Context-based Carbon Metrics (CSO). All have different approaches.
[clickToTweet tweet=”How do #sciencebasedtargets actually work in practice? This blog explores the answer…” quote=”How do Science-Based Targets actually work in practice?”]
The Sectoral Decarbonisation Approach (SDA) is currently being considered alongside other approaches within commercial real estate. It was originally developed by the Carbon Disclosure Project, World Resources Institute and WWF. Here, we focus on this approach, but in the future, we will consider other methodologies.
How does SDA work?
In short, this method splits up the carbon reduction pathway to different kinds of sectors and activities and is based on the establishment of business-level emission trajectories that support the 2°C global warming threshold, developed by the International Energy Agency, which limits the total remaining cumulative energy-related CO2 emissions between 2015 and 2100 to 1,000 GtCO2 (IEA, 2014).
The step-by-step approach for setting emissions targets
The steps below provide a summary of how SDA targets are set (this is intended to be an overview, please contact us for more information).
- Identify emissions by converting energy use into CO2e
- Categorize by Activity Type or Scope
- Produce a forecast of business-as-usual for each activity type – what will emissions look like if the business continues without intervention?
- Produce a forecast for each activity type based on the emission reduction required to align with the global 2°C carbon reduction target. This becomes your SBT
- Compare Business-as-Usual vs. Science-Based Target for the different activities
- Combine activity-level analysis to identify an overall target
- Track progress over time, engage and review
Modelling Methodologies – Some Considerations
Emissions data is not the only input that goes into the model – especially with regard to real estate. There are other things to consider:
- Scale: What do the emissions cover and what is the timescale – building level or portfolio level?
- Geography and Location: Where does it apply?
- Activities: What kinds of activities occur in the building? What activity levels are we expecting to see in the building? What are the occupancy levels like? What does the electricity-use look like?
- Trends and Changes Over Time: What are the consumption trends and how do we see this changing in the future i.e. rates of change?
- The Grid and Energy Procurement: Should carbon emissions from the grid be factored into the model? How are regional variations in the make-up of the grid and type of energy procurement taken into account in the emission scenarios?
On the whole, there is the question of what to include or exclude from the model. There is a risk of data over-refinements and normalisation, which could lead to an erroneous not-so-Science-Based result, which could be meaningless as a strategy!
Data Accuracies: Measurement and Monitoring
Target-Setting begins with data. If the data was poor at the outset, it cannot be considered to be a true reflection of what is happening in reality and as a result, any target would be inaccurate. SBTs are only scientific in their alignment to decarbonisation pathways which lead to a limit of 2°C global surface temperature increase, but it is wrong to believe that SBTs can act as the silver-bullet approach to achieve cost-savings and greenhouse gas emission reductions directly.
[clickToTweet tweet=”It is wrong to believe that #sciencebasedtargets can act as a silver-bullet approach…” quote=”It is wrong to believe that SBTs can act as the silver-bullet approach to achieve cost-savings and greenhouse gas emission reductions directly.”]
Another issue is how to set the baseline for SBTs. Of course, the scale and extent of data matters in this case, especially with the issues of measurement, monitoring and completeness of greenhouse gas emissions data at the building and portfolio level.
Setting SBTs has the potential to convey a message and a common goal; but there is a need to link to the bigger picture.
Other factors should be considered alongside SBTs for maximizing the performance of portfolios through achieving energy and cost-saving opportunities. The setting of SBTs as outlined above does not consider opportunity for improvement. SBTs should be used as the initial framework and its design should be informed by data and sustainability management strategies, as well as the climate science. Performance must also be tracked over time to assess alignment to the target.
In the future, SBTs are expected to be a popular area for development, but for now, take-up is still slow in the commercial real estate industry.
What next? It is clear that there is no one-size-fits-all approach, if you identify any issues on sustainability and data management strategies that you would like to talk to us more about, please get in touch.
— EVORA (@evoraglobal) December 9, 2016