CRREM 2.0: Industrializing Transition Risk Quantification for Real Estate

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A Brief History of CRREM

On 12 Dec 2015 at COP21, 196 countries adopted the Paris Agreement and committed to limit global warming to well below 2˚C and preferably 1.5˚C when compared to pre-industrial levels. The agreement defines a legally binding framework to tackle climate change and requires each signatory to submit Nationally Determined Contributions (NDCs) every five years, detailing, amongst other things, how they will reduce Greenhouse Gas (GHG) emissions

The EU ratified the Paris Agreement in Oct 2016 and initially committed to reducing GHG emissions by 40% by 2030 from 1990 levels, updated to 55% in Dec 2020. In May 2018, the EU adopted the Effort Sharing Decision (ESD), which set binding GHG reduction targets for 2030 for each member state, and most sectors not already covered by the EU Emission Trading System (EU-ETS).

The ESD covers the Building sector, which represents about 40% of EU energy consumption (largest energy consumer) and about 30% of GHG emissions. Moreover, 75% of EU building stock is currently not energy efficient, and only 1% gets renovated each year. The property sector is therefore highly exposed to transition risks, especially premature obsolescence and potential depreciation.
The Carbon Risk Real Estate Monitor (CRREM) is an EU-funded research consortium that aims to mitigate those risks and accelerate decarbonisation and the resilience of commercial real estate. At the current rate, the EU carbon budget, allocated to the sector until 2050 (i.e. 24 GtCO2e for a 2˚C scenario), is only expected to last until 2039, which underlines the importance of the project.

So what is CRREM exactly?

CRREM provides a methodology and excel-based tool to quantify transition risk for any stakeholder in the commercial property sector. It effectively distributes NDCs to derive property-level decarbonisation targets and pathways and estimate when buildings are likely to exceed their emission target, i.e. its stranding risk. The projected excess carbon emissions get converted into a financial cost. CRREM defines the present value of (future) excess emissions as the Value at Risk (VaR). By understanding stranding risk, investors can optimise and retrofit actions to their property portfolio.

The chart below illustrates the basic principle underpinning the stranding risk calculations.

Figure 1. Stranding Risk (modified from CRREM).

Decarbonisation pathway: This is defined by the expected target emissions over time for a given property and given global warming scenario. It is usually expressed in KgCO2e/m2/annum (carbon intensity) and results from the so-called CRREM downscaling process. Carbon targets are broken down by country and property type using inputs from the IPCC and IEA, and a systematic allocation process based on the Sectoral Decarbonisation Approach (SDA) developed by the Science Based Targets (SBT) initiative. The main property types defined by CRREM include Office, Retail (High Street / Shopping Centre), Hotels, Warehouse, Education etc.

Projected Emissions: While the decarbonisation pathway depends solely on the global warming scenario and the property location/type, projected emissions are calculated based on specific building characteristics, energy consumption/generation and projected:

  • Grid decarbonisation (reducing property emissions)
  • Climate change impact (increasing emissions), measured in terms of changes in heating and cooling demand 
  • Cost of carbon and energy

Carbon Risk and retrofitting: Properties are declared stranded when their projected carbon intensity exceeds the target. Quantifying the associated risk requires several metrics, including time to stranding, cumulative excess emissions after a stranding event (in KgCo2e), and penalties/cost of covering excess emissions. CRREM also allows investors to simulate retrofitting costs, i.e. investments meant to reduce the property carbon intensity, taking into account the “embodied carbon” (i.e. emissions from upstream and downstream building activities). 

How could CRREM be improved?

The CRREM tool has already gained some traction. Several companies and institutions use it to estimate the carbon risk of their commercial real estate portfolios. However, we believe that the current version of the tool has limitations and that deploying the CRREM methodology at an industrial scale would require improvements

  1. Data Modelling: Although the Excel tool structures data in tables, proper entities and relationships are not defined, and therefore no data integrity. Building a relational database would address this issue and provide a strong foundation for feeding calculation engines and build corporate-grade applications. The data model itself could be improved and made more generic, granular and include a time dimension so that users can track and visualise the evolution of inputs and outputs. A more flexible data model the potential to extend the CRREM methodology to other sectors.
  2. Data Inputs: The CRREM model relies on many inputs, including energy conversion factors, global warming potential of gases, the share of electricity for heating or cooling, many mapping tables, and carbon and energy prices. The data inputs used in the excel tool are static; whilst this is acceptable in some cases, it is much more problematic for highly dynamic and potentially volatile data like the price of carbon and energy. These parameters are critical for calculating the cost of excess emissions and up-to-date data is essential for realistic results. Connections to data providers like exchanges, Bloomberg, Refinitiv or others to source market prices are also potentially required. Another necessary input in the CRREM model is the estimated energy consumption. We believe IoT (sensors and meters) would be a great way to retrieve much more reliable and live information on energy consumption/generation and GHG emissions.
  3. Data Outputs: As explained earlier, one of the main outputs of the CRREM model is the Value at Risk (VaR), i.e. the discounted value of excess emissions. The terminology might mislead some. In Finance, VaR commonly refers to a statistical loss measure, while the CRREM version is deterministic. However, given that the level of several calculation parameters is highly uncertain, it would be interesting to generate a probabilistic estimate of the future excess emissions value. Creating Monte-Carlo simulations for Energy and Carbon prices would allow us to calculate “market-adjusted” Value at Risk with a given confidence level or provide the whole distribution of simulated outcomes. The model could include other variables, but estimated parameter values would need to come from reliable sources.

What’s next? Risk and Opportunities.

CRREM provides a robust framework for quantifying and managing transition risk in the real estate sector and has become an essential part of the overall climate risk assessment. While many businesses acknowledge climate risk and integrate it into their processes, we should appreciate that adapting to climate change presents opportunities. The Task Force on Climate-related Financial Disclosure (TCFD) reiterated this point and highlighted that new markets, products or services may emerge from the transition process. We can see initiatives maturing in the real estate sector. For example, the Green Finance Institute (GFI) is partnering with businesses and proposing “demonstrator projects” to facilitate the financing of energy-efficient buildings. Technologies like IoT, AI and Blockchain could also prove to be enablers in the sector, and this is an area BCI Research Divisions are exploring through their work on Blockchain Green Bonds and Loans.

The combined effects of improving climate risk management and financing solutions will hopefully be a catalyst for a faster transformation to a more sustainable economy. Time will tell. But time is short.


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