Road To Zero Carbon Feature
Road To Zero Carbon
Bridging the funding gap for social housing retrofits
The social housing sector is faced with a retrofit funding deficit of over £90bn, and so far, government grants and private sector investments are falling short. Tim Meanock of Tallarna explains how an ecosystem approach overcomes this challenge to deliver affordable warmth that pays for itself.
T
o meet the UK’s 2050 net zero targets, social housing providers must undertake the enormous task of retrofitting over four million homes. Not only does this involve building work of considerable magnitude,
it also comes with an eye-watering price tag of £104bn. Tat’s almost the equivalent of paying rent for all social and private tenants in the UK over a 15-month period. While the government has mandated such decarbonisation work, their
financial contribution amounts to less than 10% of the total cost. Te Social Housing Decarbonisation Fund (SHDF) and ECO grants combined only cover £7.8bn of the required finance. Obtaining private investment, therefore, is essential. However, this remains hard to achieve in a way that is mutually acceptable to both parties. Current financing options require security against assets (such as social homes themselves), as opposed to the cash flows generated from retrofits (savings on the bill). Tis is too risky for most landlords. And the reason for these terms? Investors’ lack of confidence in retrofit outcomes.
BRIDGING THE UNCERTAINTY GAP Bridging the private sector’s uncertainty gap requires data and proof-points. One technology that plays a vital role in this early in the project development
cycle is thermal imaging. It helps establish objective energy baselines without human bias or limitations. Infrared thermal imaging surveys provide an accurate insight into properties’
energy efficiency issues – many of which would otherwise go undiscovered. Tese include missing or inadequate insulation, draughts, porous brickwork, and waterproofing issues. Termal imaging can be combined with open data sources and statistical
analysis on archetypal building performance and enhanced by artificial intelligence (AI) to provide a clear retrofit pathway. Tis empowers social housing providers to understand which homes need to be addressed first, what measures carry the most risk, and whether a project is financially viable. Doing this early on optimises the balance between energy, carbon, and bill reductions. Accurately predicting project outcomes is a key part of the decision-making
process. Social housing providers need to know the ratio of cost-to-savings, what cash flows will look like post-retrofit, and how to structure projects across an entire portfolio. Only then will they be able to make the right choices. But providers’ decisions can only be as good as the data they rely on. And,
as investors are acutely aware, expectations are oſten different to reality. Tis is where risk quantification comes in. By using AI to understand the likelihood
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