The whole pamphlet, Remaking Home Heating in the UK, is published today on People & Nature, and can be downloaded for free here.
Anyone who has spent any time in the UK knows from experience the poor fabric efficiency of homes. I vividly recall first travelling from the UK to Germany and to Hungary in the winter of 2002, and being surprised at how insulated and well-made the windows felt, compared to the average window in the UK.
Fabric efficiency concerns the capacity of a building to keep heat in or out to maintain thermal comfort. The UK’s homes in general perform very poorly on this front. In winter, they rapidly dissipate heat like water through a sieve. Overheating when it is hot outside is also of increasing concern. (In my previous pamphlet, I outlined some of the standard ways that fabric efficiency and thermal performance can be maximised.[1])
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| Members of Living Rent, an Edinburgh collective, demanding action on mould and damp in council flats. Photo: Scottish Housing News, December 2022 |
When it is too cold or too hot inside, households need to add or remove that thermal energy to maintain thermal comfort—and this means consuming energy. With the majority of homes thermally inefficient, that means using energy in large quantities.
In the for-profit energy system of the UK, that energy is expensive at the best of times. Since many people cannot afford to keep themselves comfortable, the inevitable outcome is high rates of fuel poverty.
And when energy prices are riding high—as they continue to, even after the energy crisis of 2022-23—that makes things worse and draws more households into the energy poverty trap.
The situation is simple: poor fabric efficiency needlessly ups demand for heating in winter and cooling in summer; it increases misery, busts personal finances, and expands greenhouse gas (GHG) emissions.
In this article, I start by looking at the definitions and the extent of fuel poverty across the UK, then at the extent of health impacts from poor fabric efficiency, focusing on “excess deaths”, and the assessed economic costs of cold, damp homes.
Unfortunately, accurately gauging fabric efficiency itself in the UK’s housing stock is not easy or straightforward. According to the Low Energy Transformation Initiative (LETI), there is “no detailed single source of housing data” in the public domain for Great Britain or the UK as a whole—and no corresponding body of data that correlates the variety of homes to building structure, fabric efficiency, and energy use. The primary metric used at the moment is the “Energy Performance Certificate” (EPC), which is widely derided.
I provide an overview of the EPC system and its problems, and look at the existing data about the physical state of the UK’s homes, with a focus on England. I then outline LETI’s own recent efforts at providing a decent housing stock model for the UK mainland as a whole, with an emphasis on understanding fabric (in)efficiencies, and the scale of annual supplementary space heating energy use in homes.
Fuel poverty in the UK
I have already indicated the meagre financial assistance available in the UK for those living in fuel poverty. However, the legal definitions of fuel poverty vary across the UK.
For England, the government’s Department for Business, Energy & Industrial Strategy (BEIS) has a “Low Income Low Energy Efficiency” (LILEE) indicator. That defines fuel poverty as (a) living with a disposable income less than 60% of the national median income (£34,500 in 2023), after paying for housing and energy—so, less than £20,700 in 2023; and (b) living in a home rated D or worse according to the home’s Energy Performance Certificate (EPC).
In Scotland, Wales and Northern Ireland, the definition of fuel poverty is wider.
In Scotland fuel poverty is when (i) a household spends more than 10% of its net income after housing costs on “reasonable fuel needs”, and (ii) the household income that remains “is not enough to maintain an acceptable standard of living”. That remaining income / acceptable standard of living is defined as being at least 90% of the UK Minimum Income Standard, after care benefits and childcare costs are deducted.
For 2024, the 90% definition would include any single person left with less than £25,200 a year, or any couple with two children left with less than £62,460. Extreme fuel poverty is defined as above but with (i) defined as spending more than 20% of after-housing income on fuel.
In Wales and Northern Ireland, fuel poverty is defined simply as when a household spends more than 10% of all its income on fuel. In Wales, spending more than 20% is “severe” fuel poverty.
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| Damp and mould. Photo by David Singleton, CC BY-NC 2.0 |
The most recent LILEE data show that in England in 2023, 13% of households (3.17 million households) were classified as living in fuel poverty.[2]
In Scotland, 861,000 households lived in fuel poverty in 2023 (34% of all households), under the Scottish definition. Of those, 491,00 households (19.4%) lived in extreme fuel poverty.
In Wales, the most recent (2021) figures indicate that 14% of households (about 196,000) live in fuel poverty, with about 3% in severe fuel poverty.
In Northern Ireland, 22% of households are estimated to live in fuel poverty.
The proportion of England’s population defined as living in fuel poverty seems to have declined from about 22% in 2010.
With the boom in gas prices that followed Russia’s invasion of Ukraine in 2022, the Institute of Health Equity forecast in September 2022 that 55% of UK households would be in fuel poverty by January 2023 if additional interventions were not made. In the event, the government did intervene to freeze Ofgem’s fuel price cap.
However, energy prices still rose precipitously. In consequence, the number of fuel poor households rose, and households had to pay more in energy costs to avoid falling into fuel poverty. As you can see in Figure 1, the average scale of that extra spending (the “fuel poverty gap”, shown in orange) rose by 66% in real terms between 2020 and 2023, in line with the rise in fuel prices (in red).
Figure 1. Energy prices and the “fuel poverty gap” in England (2014-2023)[3]
Health impacts of poor fabric efficiency
The largest health impacts of poor fabric efficiency are felt during the winter months, when cold, damp homes cause widespread illness and death. Heat-related death in the UK is also an increasing problem: during a heat wave, homes that afford inadequate protection from incident sun can heat up like greenhouses.
“Excess winter deaths” are the deaths that occur in winter compared to non-winter months.[4] The number of excess winter deaths varies from year to year, based on multiple factors, but in large part due to the severity of the winter—and people’s needless exposure to the cold and the damp. Winter 2017-18 was especially bad, when there were an estimated 49,410 excess winter deaths in England and Wales according to the Office for National Statistics (ONS).
In 2022, the UK chief coroner found that Awaab Ishak, who was two years old, died in December 2020 as a direct result of prolonged exposure to black mould in the council flat where he was living. (In England, 3% of homes have problems with serious condensation/mould.)
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| Photo by Climate Justice Collective, CC BY 2.0 |
The flat where Awaab lived was owned and managed by the housing association Rochdale Boroughwide Housing, on behalf of Rochdale Borough Council in Greater Manchester. According to the trade publication Inside Housing, Awaab’s father, Faisal Abdullah, had “repeatedly raised concerns about the mould with the housing association, which failed to fix the problem”.
It was recently reported that, in 2024, English councils spent in excess of £2.1 billion on temporary accommodation. In England, 164,000 children live in temporary housing, and the dire quality of such homes contributed to the deaths of at least 74 children in the last five years, according to the Shared Health Foundation.
Additional excess deaths resulted from the Covid-19 pandemic. Moreover, since 2020 the number of year-round excess deaths has remained elevated, with the cause blamed in part on the continued effects of Covid-19, combined with an ongoing crisis of care in the NHS.
In 2022, year-round excess deaths were 44,255 (7.2%) higher than the five-year rolling average (excluding 2020), and higher than at any other period since 1950, outside of the Covid-19 pandemic. This trend persisted into the first six months of 2023. (Data are not currently available for 2022-23.)
Plainly, an excess of death, and an excess of deaths in winter, concern more than just poorly insulated homes. Counterintuitively, research by Southampton Data Observatory finds “little evidence to show a clear relationship between deprivation and winter mortality”, including for people over 85 years old. Nevertheless, excess winter deaths associated just with cold homes were already estimated to run at an average of around 10,000 per year across the UK before 2022, according to the NHS Confederation.
In summer 2022, temperatures in the UK reached 40°C for the first time since records began. In England, 2803 people aged 65 and over died as a result of the heat, the greatest number of heat-related deaths recorded for this most vulnerable of age groups since 2004, when the ONS started to track heat-related deaths in this way.[5]
Summer 2025 has brought dangerous heat waves across Europe. Moreover, global warming is forecast to heighten risks from heat-related death dramatically, worldwide. Nevertheless, worldwide—and certainly in the UK—deaths attributed to cold are far more prevalent.[6]
Peaks in heat-related deaths and winter deaths are often followed by a lull in deaths, suggesting that these periods of heat and cold “bring forward” deaths in the elderly and infirm (“short-term mortality displacement”). However, this is no mitigation: people should not be exposed to environmental conditions that push them closer to death; their homes should protect them.
These are social failures. Government and landlord negligence have allowed persistently poor thermal performance, with high fuel prices and poverty, combining to produce fuel poverty, misery, ill health, and death from the cold and damp, and from heat.
Over the medium to long term, the UK’s Met Office notes that climate change is likely to bring milder, wetter winters to the UK (with increased risk of flooding), and hotter, drier summers.
The economic cost of cold, damp homes
In money terms—hardly the most important metric, but sadly tangible—the NHS in England only reported in 2022 that it spends £1.3 billion every year on mitigating the harms caused to people’s health by buildings’ generally appalling thermal performance—“treating preventable conditions caused by cold, damp homes”.
The Building Research Establishment (BRE) estimates, however, that those costs typically comprise only about 6% of the total economic costs to society—so that the real costs total about £23 billion annually for the UK as a whole.[7]
Those are simply the economic indices of all the pain, discomfort, suffering, and grief inflicted by cold, damp homes. (I know of no similar metrics measuring the costs of heat-related death, illness, and discomfort.)
Extraordinarily, the NHS announced in 2022 that it would pilot a perverse scheme whereby 1000 vulnerable patients in the Tees Valley and in Aberdeenshire would have their winter energy bills paid for them, in a bid to reduce the costs to the NHS of treating them for illnesses made worse by the cold. Who would be paying for this? The “social impact fund” of BP. (A smaller parallel scheme would be funded by the government.)
No moneys would be directed at reducing the demand for heat by improving the fabric efficiency of homes.
Energy Performance Certificates (EPCs)
In the UK, the conventionally accepted measure of a home’s fabric efficiency is an Energy Performance Certificate (EPC) score. However, the EPC system is deeply flawed. Fundamentally, EPCs are not a fabric efficiency metric at all, providing instead a measure that is incomplete, messy and inaccurate.
The flaws are widely recognised, and the CCC has long recommended the overhaul of the EPC system. A 2020 report on EPCs from the BEIS recommended the same, and in December 2024 the government finally launched a formal consultation on the EPC regime.
EPCs are peculiar to the UK, and were introduced in 2007 by the then Labour government, to comply with the EU Directive on the energy performance of buildings.
EPC scores range 1-100 (1 is bad, 100 is excellent), and there is a corresponding rating system of letters, A-G, and colour band. “A” means good, “G” means bad. Since 2013, all new, for sale or rented homes are meant to have an EPC and a thermal performance score, provided by a certified assessor.
An EPC certificate is valid for ten years—but that limited validity period means that many homes do not have a valid EPC certificate. According to analysis by the consultancy firm Kamma Climate, 49% of UK homes do not.
Besides this issue of poor coverage for the UK’s housing stock as a whole, the problems with the EPC system were highlighted by the Climate Change Committee (CCC) in a February 2023 Annex report.[8]
The main problem as far as fabric efficiency is concerned is that the EPC is an amalgam score, encompassing the physical fabric efficiency of a home, its heating source, and other factors besides: it is not an expression of just the physical fabric efficiency of a home.
Equally serious is that the EPC is misnamed. An EPC rating is not calculated on the basis of energy performance. Instead it estimates the money cost of heating, and on that basis the cost effectiveness of running a home.[9] An EPC score of “A” actually means cheap, and “G” means expensive. Varying costs of energy and outdated baseline assumptions further blunt an EPC’s usefulness even on this score.
The EPC comprises two different ratings: an Energy Efficiency Rating (EER), and an Environmental Impact Rating (EIR).
Figure 2 Typical Energy Efficiency and Environmental Impact Rating[10]
The EER and EIR scores are generated using the so-called “Standard Assessment Procedure” (SAP), which concerns the physical characteristics of a home and its heating systems. The SAP is primarily concerned with space heating and hot water (which usually dominate residential energy use). It focuses on factors like insulation, double glazing, and sources of heat, but it also includes lighting. (The SAP does not consider appliance use).
Existing homes usually receive a simplified assessment with fewer inputs (the “reduced data” SAP, or RdSAP). However, the SAP itself is rife with problems.
Because electricity prices are disproportionately high compared to gas, homeowners are actively disincentivised from switching to heat pumps, even though heat pumps are far more energy efficient.
For similar reasons, the SAP methodology applied to current energy prices results in a better EER score for homes with a gas boiler: a perverse state of affairs, and a clear additional disincentive for homeowners to install a heat pump.
Another problem arises with the simplified 1-100 scoring system for the EPC: a home with solar panels that is a net producer of energy can theoretically score above 100.
On the other hand, the underlying fabric efficiency and building physics component of the SAP is itself inaccurate. It is not based on any measured “in use” physical properties of a home, such as the rate of heat loss, nor even on theoretical or modelled energy use in a dwelling.
The scoring system is not based on actual units of energy use or energy cost. Instead, the SAP is based on a series of “box tick” assessments and relies on clumsy simplifying assumptions to spit out a cost estimate, rendering SAP scores misleading for most homes. For instance, data on factors such as the thermal conductivity of insulation are to be gathered only when “[prior] documentary evidence is available”; otherwise a default value is assumed.
The Department for Business, Energy & Industrial Strategy (BEIS) themselves have cautioned that the SAP likely significantly under-estimates rates of heat loss from homes—by up to 45% on average, according to one study.
Around 15% of home EPC ratings are apparently wrong on their own terms, simply due to poor measurement. In short, the typical EPC gives a terrible sense of a building’s thermal performance, provides an inaccurate picture of a home’s environmental impact, and gives a poor indication of the amount of supplemental space heating that is required to live decently or in comfort in the UK when it is cold outside.
In 2020, the Passivhaus Trust published a small study on EPCs that corroborates these criticisms. It includes the graph in Figure 3. You can see that—for the sample of 410 homes in England—the actual, measured total energy use of homes per square metres per year varies enormously within each EPC band:
Figure 3. UK home energy consumption (y-axis), compared to EPC score[11]
Beyond these factors, the assessment from the CCC highlights that the EPC’s 1-100 scale is opaque; the different rating bands also vary in size.
Given the additional fact that the EPC score is not tied to a consistent underlying set of unit measurements, the scale itself is not linear. Rating comparisons offer only vague indications of the underlying physics of home energy efficiency.
Among the people whose opinions they surveyed, the BEIS found very low levels of confidence in EPCs, and in EPC assessors, and a lack of transparency in the scoring. They suggested that EPCs should be based instead on “more sophisticated building modelling that takes actual energy consumption into account (while remaining a measure of building performance and not occupant behaviour)”.
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| Cressingham Gardens, Lambeth, London. Photo: Paul Watt, CC-BY-SA 4.0 |
The CCC recommends that the existing 1-100 rating scale be replaced by a set of four metrics quantified in actual physical units, represented by a series of ratings bands similar to the present system.
The four metrics the CCC recommends are:
(1) a “headline” metric on overall “energy use intensity” (quantified in kilowatt hours per square metre per year (kWh/m2/yr));
(2) a “fabric” metric (also quantified in kWh/m2/yr), providing “a clear indication of the underlying fabric efficiency of a home (excluding the impact of heating system choice)”;[12]
(3) a “heating” metric, related to the type of heating system in a home;
(4) a “cost” metric (in pounds sterling per square metre per year (£/m2/yr)), related to all home energy use.
Over the last decade or so, it has become politically mainstream in the UK to advocate for all homes to be raised to EPC grade C. Notwithstanding the analytic imprecision of the SAP, as far as the BEIS are concerned, the EPC grade C expectation corresponds to a space heating energy use of 90 kWh/m2/year.
Existing Data on the Physical State of the UK’s Homes
As the EPC system is not fit for purpose, alternative analytical tools need to be established instead, and widely deployed, if we are to have a scientific understanding about the state of the UK’s housing stock and its underlying fabric efficiency.
One other existing way to assess the physical state of the UK’s homes is through the English Housing Survey (EHS), which measures the prevalence of damp and mould in homes, alongside EPC records.[13]
According to the EHS, as of 2023, 5% of England’s homes have problems with damp, “higher than in any of the last five years”, and 3% have problems with serious condensation/mould (up from 2% in 2019)—the cause of death of Awaab Ishak in winter 2022. Overall, owner-occupied homes have the lowest occurence of damp and mould—indicating the importance of strictly enforced guidelines in the private rental and social housing sectors.
Figure 4. Percentage of homes with damp problems (England, 1996-2023)[14]
Meanwhile, the EPC data, while blunt, inaccurate, and scattershot in building physics terms, still provide some indication of the variation and distribution of fabric efficiency standards in the UK housing stock.
The next graphs come via sampling by the EHS in 2023. The EHS data indicate a steady uplift in England’s EPC grades over the last decade—and this goes back to at least 2004.[16] About 88% of homes of all tenures in England were grade C or D on the EPC scale in 2023. Around 50% were rated grade D or below.
Figure 6. EPC rating bands for homes in England (2013-2023)[17]
Figure 7. EPC rating bands for homes in England, by tenure (2023)[18]
Figure 8 EPC rating bands for homes in England, by dwelling age (2023)[19]
Nearly two thirds (64%) of England’s homes were owner-occupied in 2023, and these had the worst EPC score of all tenure types, closely followed by privately rented accommodation (roughly half of both have an EPC rating of D or worse). The private-rented sector comprises about 19% of homes in England, but houses roughly 34% of fuel poor households.
This is socially useful information. It is just a pity the data are based on EPC grades.
Looking beyond the EPC grading system, one private source of data has measured the actual thermal performance of homes via the proxy of changing internal ambient temperatures.
The company tado°, producer of smart thermostats, several years ago circulated press releases about UK homes’ poor thermal performance, citing data collected from their devices. These give no breakdowns by housing type or tenure. They are also confined to tado°’s own userbase. But they do give overall national comparisons between a handful of European countries of unwanted heat losses and heat gains.
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| Home heat loss in winter (left), and home heat gain in summer (right). Maps from tado° (2020), tado° (2021) |
In these maps of Europe, the map on the left shows unwanted heat loss in winter, by country. Using data from the smart thermostats of 80,000 tado° customers in the winter of 2019-20, the company found that, with a temperature of 20°C inside and 0°C outside, UK customers’ homes on average lost 3°C of heat over the course of five hours (presumably after the heating had been turned off!).
That compared to an average 1°C heat loss in Germany and 1.5°C in Italy. The implication is that the insulation of customers’ homes is about three times less effective in the UK than in Germany. Heating systems in the UK, on average, will have to work harder to maintain a consistent indoor temperature.
The map on the right shows unwanted temperature gain in summer. Here the company sampled 300,000 customer thermostats in the summer of 2021, and found that, when the temperature inside was 20°C, and the temperature outside was 30°C, after three hours of sunny weather the temperature inside had on average risen a whole 4.9°C in the UK—versus 4.6°C in Sweden and 2.2°C in Italy.[21]
Here, the results appear to reflect the lack, in the UK, Ireland, and the Nordic countries sampled, of passive architectural features common to homes in southern Europe, which minimise solar gain. The heat waves of summer 2022 only further demonstrated this unfortunate fact to residents of places like the UK.
These tado° data indicate above all that UK homes are among the worst-performing in Europe in thermal terms. However, these results are also presumably subject to skews in the kinds of homes and householders likely to possess these smart thermostats. Could it be that these data over-estimate the insulating capacities of European homes?
The CCC cited the first tado° press release above—“Home temperature loss after 5 hours”—in their (March 2022) assessment of “The UK’s Heat and Buildings Strategy”. That fact alone tells us there is a poverty of suitable data out there about the fabric efficiency of the UK’s homes. The tado° data are interesting, but not self-evidently robust, and there is obvious room for bias in reporting.
LETI housing stock model
As indicated by the CCC and others, the fabric efficiency of homes should be quantified in actual physical units. You want to know about the actual physical movement of heat, and how that relates to the different components of buildings, and their overall structure.
The gold standard is empirical in-situ testing. There are some common diagnostic tools for such measurements: for instance, you can measure the air tightness of a building using a blower door, and you can detect paths of thermal leakage using infrared thermography (IRT).[22] Naturally, in-situ measurement can only be performed on existing homes.
Alongside in-situ measurement, however, decent modelling is also important. Building physics methodologies like the “Passive House Planning Package” (PHPP) are far superior in this regard than the SAP assessment on which the EPC system is based. The PHPP focuses on quantifying the passage of actual heat energy across the building envelope, and modelling likely supplemental energy use in kWh/m2/year.
“Post-occupancy surveys”, and in-situ spot testing, can then be used to refine building physics models, and update theoretical modelling about the performance of individual buildings, various building designs, materials, and combinations of materials.
All these steps can then be used in concert with one another, to construct ever more detailed assessments about the likely thermal performance of the existing UK housing stock as a whole, across its various typologies or “archetypes”. Likewise, architects and engineers can in this way get a sense of the comparative effects of different modifications, and how best to retrofit buildings to make them more energy efficient.
According to the Low Energy Transformation Initiative (LETI), the best public domain source for physical data about homes in England remains the iteration of the English Housing Survey conducted in 2011.[23]
That grouped homes according to 14,000 different archetypes, along with a record of thermal upgrades made to the building structure, such as wall or loft insulation, or double glazing. Subsequent years of EHS data are only published in summary form (and tend, as shown above, to draw on EPC data.)
The Cambridge Housing Model takes the 2011 English Housing Survey data, and couples it to the database of homes’ EPCs, to provide estimates for the scale and variety of final energy use in homes, and the corresponding CO2 emissions. However, this is all confined to England—which houses 84% of the UK’s population. The UK’s Building Research Establishment (BRE) published just a summary of housing data for the whole of the UK in 2020.
In the apparent absence of anything more physically descriptive, LETI in 2021 developed its own rough-and-ready housing stock model for the UK mainland (i.e. England, Scotland and Wales—the UK minus Northern Ireland).
LETI’s model is based on that most comprehensive recent English Housing Survey data, from 2011, which LETI have combined with summary data from the English Housing Survey and BRE.
From these, they have extrapolated a likely picture of the housing stock of the UK mainland as of 2018. They include information on things like the presence of a gas boiler. With some additional simplifying assumptions, they include information about the physical structure of buildings—like the typical wall structures found in dwellings of different ages and different styles, and the presence or absence of insulating measures.
For the sake of simplicity and manageability, the LETI model is based not on the English Housing Survey’s 14,000 housing archetypes, but on five simplified archetypes: detached house, semi-detached house, mid-terrace, bungalow, and flat.[24] LETI fed all of the sources above into a modified version of the Passive House Planning Package (PHPP) to model “bottom up” the likely fabric efficiency of the different archetypes of homes.
The model includes typical fabric efficiency values for each of the five archetypes of home, the various ages of dwellings, and the modelled insulation values for the different styles of construction, building components, and renovations that have been recorded: different kinds of walls, wall insulation, loft insulation, single- and double-glazed windows, and so on.
These factors are constrained to 1125 possible combinations of parameters. They also accounted for varying patterns of occupancy, modelling that 5% of homes are unoccupied at any one time.
The aim here was to model likely physical heating energy needs (N, here “demand”) as a proxy for fabric efficiency, and match those needs to the distribution of energy consumption based on end-use data compiled by the government. The housing stock model assumes that thermal comfort in a home requires consistent temperatures of 20°C, but acknowledges that such temperatures are very unlikely to be maintained in the majority of dwellings.[25]
(There is a note about how the terms energy need (N), energy use (U) and energy consumption (C) are being used here, in the Introduction to Remaking Home Heating in the UK.)
The bottom-up fabric performance model was tallied against top-down, real-world consumption data for gas and electricity from 2018—“to demonstrate that the model was producing accurate results”. Total heating energy consumption for the UK mainland (across all energy carriers) was modelled at 474 TWh. Real-life consumption was 484 TWh, according to government data.
Not all heating energy needs are met. There is significant under-consumption of energy for home heating, and especially space heating—and considerable thermal discomfort is endured. As such there is what we could call a “demand gap” between energy need (N) and energy use (U).
With that in mind, LETI “tapered” their modelled energy use to an assumed level of under-heating “of up to 30%” in those homes with the worst rates of heat loss. The LETI data effectively tell us how much thermal energy households “need to use” in order to maintain thermal comfort (i.e. for N=U).[26]
The result of LETI’s modelling is a rough-and-ready model of the housing stock. It is based on an approximation of real building physics, while also incorporating real-life energy consumption data. It gives us an image of the likely distribution of fabric efficiency in the UK mainland’s housing stock, and the fabric efficiency of the housing stock as a whole.
LETI’s is also a good example for how a public domain housing stock model could work, so that the data are accessible to everyone. Presumably more resources could deliver a more refined model, with a more granular approach to the housing stock—and it is to be hoped that such a model can be constructed in future.
All the additional social and empirical indices recorded by the English Housing Survey and BRE—tenure type, age of dwelling, presence of damp—could be added to LETI’s model, and used to refine it. Widespread in-situ testing could do the same.
As things stand, the information LETI have at their fingertips through the housing stock model seems to be incredibly rich—though they only share some parts of their findings in their published documents. The data they do show are typically presented in a very well-designed and accessible way.
According to LETI’s housing stock model, most homes need to use 110-160 kWh/m2/year of thermal energy for space heating to maintain thermal comfort indoors. The modelled average (mean) for the whole UK mainland housing stock is given to be about 128 kWh/m2/year (not marked on the graph above, but shown here). Again, these numbers are “energy out” of a boiler or heat pump—not the amount of energy consumed (C) for that purpose.
As I mentioned above, EPC grade C has become the mainstream target of choice among politicians in the UK—and the BEIS reckon that on average that can be considered to correspond to a space heating energy use of about 90 kWh/m2/year.
I mentioned previously the apparently strong connection between the age of homes in England and Wales, and low EPC scores. The ONS say that age “is the biggest single factor” in the energy efficiency of homes in England and Wales. However, LETI’s modelling points to other more significant factors instead: notably, form factor. For instance, the occupants of semis, mid-terraces and bungalows seem on the average to use thermal energy at a much greater rate per m2 of internal floor area.
The ONS do not mention wall type or insulation—but pre-1900 is evidently a reasonable proxy for “poorly insulated”. In any case, according to the UK’s Building Research Establishment (BRE), as of 2016, the UK had the oldest homes in the EU, on average—with 37.8% of the UK’s homes built before 1946.[27]
The average 128 kWh of thermal energy needed (or used) annually, per m2 of a home, just to stay warm, is a lot of energy. The average dwelling size in the UK is 94m2 – which suggests about 12,000 kWh on average, per year per home, of thermal energy needed for space heating.[28]
(With an average 85% boiler efficiency, that further suggests about 14,000 kWh-worth of gas consumed for space heating alone, if thermal comfort is to be maintained. Whereas, recall that according to Ofgem, the average household in the UK currently consumes 11,500 kWh of gas each year, for space heating and hot water combined.)
To put those numbers in some further context: boiling a full kettle uses approximately 0.2 kWh of heat. 128 kWh of thermal energy per m2 per year, for an average 94m2 dwelling, would correspond to about 60,000 hot kettles, or about 400,000 mugs of tea.[29] Plainly there is plenty of scope to reduce the quantity of heat energy that we need to stay warm, to thereby improve thermal comfort, and reduce the amount of gas, or electricity, that must be consumed.
That is where retrofit comes in.
🔴This is an excerpt from Remaking Home Heating in the UK, a People & Nature pamphlet by Tom Ackers, which can be downloaded for free here. In a linked article here, Tom puts the case for an integrated approach based on electrification and retrofit
🔴 Two further excerpts, on electrification and retrofit, will be published by People & Nature tomorrow
🔴 More People & Nature commentary and analysis of the decarbonisation of home heating is here.
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[1] See Decarbonising the Built Environment: a Global Overview, part 9
[2] Based on the English Housing Survey (2022) sample of 10,890 homes
[3] Source: DESNZ (2025). The fuel poverty gap is, “the reduction in fuel bill that a fuel poor household needs to not be classed as fuel poor”
[4] “The ONS [UK Office for National Statistics] standard method defines the winter period as December to March, and compares the number of deaths that occurred in this winter period with the average number of deaths occurring in the preceding August to November and the following April to July.” See here
[5] Statistical analysis aimed to exclude deaths from Covid-19
[6] Epidemiological studies suggest that, globally, 8.5% of all deaths are cold-related and about 0.9% are heat-related—a ratio of 9:1
[7] Author’s calculation for the whole of the UK in 2023 prices, based on the BRE report’s estimates for England in 2018. 84% of the UK’s population live in England, according to the Office for National Statistics. The stated figure in BRE’s report is £15.4 billion (2018 prices) of savings, if cold and dampness in homes is entirely mitigated in England. Out of that, the costs to the NHS are £1.1 billion. Overall, BRE estimates that the annual cost to society of poor housing in England is £23.1 billion (2023 prices)—across all hazard types. BRE defines “poor housing” as “a dwelling that fails to meet the statutory minimum standard of housing in England”
[8] See also this May 2024 report by the National Retrofit Hub
[9] The SAP derives a figure for “regulated” (expected) energy use
[10] Source: House Planning Help (2023)
[11] Source: Passivhaus Trust / Etude (2020)
[12] This would (as far as I can tell) correspond to my definition of space heating energy use (“U”). See the Introduction to the pamphlet Remaking Home Heating in the UK
[13] The EHS’s most recent assessment took place in 2023-24. See also here
[14] Source: EHS (2025).
[15] Source: EHS (2025). Note that “serious condensation” is synonymous with the presence of mould in a home
[16] See here. Recall that only about half of homes in the UK presently have a current EPC rating, according to Kamma Climate
[17] Source: EHS (2024)
[18] Graph by the author. Data: EHS (2024), Annex Table 2.4
[19] Graph by the author. Data: EHS (2024), Annex Table 2.4
[20] Verified for England and Wales as a whole, by a separate assessment carried out by the ONS in 2022
[21] This is presumably in the absence of additional air cooling measures—though I wonder how reliable would be the assumption that smart thermostats in warm countries are connected to individual air conditioners
[22] See Decarbonising the Built Environment: a Global Overview, part 9
[23] See LETI (2021), Climate Emergency Retrofit Guide, p.176
[24] These are roughly the same archetypes from LETI that I cited in the section on “form factor” in Part 9 of the previous series
[25] “A typical dwelling will use periodic heating (i.e. heating will be on for periods when the dwelling is occupied and off overnight) and will cool down below the target temperature outside of those periods. The worse the building fabric, the more rapidly it will cool and thus the lower the average temperature. The PHPP model was therefore modified to include the same methodology that is used in SAP. The heat loss parameter of the dwelling is calculated and then used to determine an average monthly internal temperature based on a standard heating pattern. This adjusted temperature is then used for the dwelling’s heat loss calculations.”
[26] However: government space heating energy consumption data, when combined with average energy efficiency data for the different sources of home heat, average dwelling size, and the LETI estimate for space heating energy need, per square metre, (based on “tapered” energy use, fed back into this further calculation), indicate instead that roughly one third of all space heating energy needs in the UK are not presently met. For example, 128 kWh/m2/year x 94m2 (the average dwelling size in England) x 29.5 million homes in the UK (in 2020) = 355 TWh of space heating energy need (N) annually. Whereas, for 2020: 278 TWh of energy consumed for home space heating across the UK suggests no more than about 230 TWh of useful heat energy (U) made available in homes
[27] In second place after the UK was Belgium, with 37.1% of homes built before 1946, then Denmark with 34.1%. You can see the full BRE breakdown here
[28] The 94m2 figure comes from the EHS 2018-19
[29] See “How much electricity does a kettle use? The cost of making a cup of tea”. Figure based on a typical 3kW electric kettle, which holds 1.7 litres of water, and typically takes about 230 seconds to boil. Estimate assumes that all electrical energy is transferred to the hot water, and assumes an average 250ml mug size.
