Non-Domestic National Energy Efficiency Data-Framework 2024 (England and Wales): geographical annex
Source: environment.data.gov.uk (2025-08-21)

Non-domestic National Energy Efficiency Data-Framework (ND-NEED). The National Energy Efficiency Data-Framework was set up to provide a better understanding of energy use and intensity in domestic and non-domestic buildings.

These documents provide data on non-domestic energy use.

Responsible statistician: James Hemingway
Media enquiries: xx-xxxx-xxxx
Email: xxx@xxx.xx
Statistical enquiries: xx-xxxx-xxxx
The Non-Domestic National Energy Efficiency Data-Framework
2024 (England and Wales) Geographical Annex
19 December 2024
Official Statistics
This report summarises analysis of the geographical differences in the non-domestic building
stock and non-domestic building energy consumption in England and Wales using the latest
version of the Non-Domestic National Energy Efficiency Data-Framework (ND-NEED)
published in August 2024.
The key results are:
•
Electricity and gas consumption from ND-NEED non-domestic buildings varies substantially
between regions in England and Wales.
o
Non-domestic buildings in London consumed the most electricity in 2022, three
times more than the North East which consumed the least.
o
Non-domestic buildings in the North West consumed the most gas in 2022, three
times more than the North East which consumed the least.
•
The proportion of electricity and gas consumption from ND-NEED non-domestic buildings in
a particular type of building varies between regions in England and Wales.
o
London accounts for 35% of electricity consumption from offices, while the North
East accounts for just 3%.
o
East of England accounts for 22% of gas consumption from factories, while the
North East accounts for just 3%.
•
The proportion of factories, offices, shops, or warehouses in a region is broadly similar to
the proportion of all non-domestic buildings in that region.
o
The exceptions to these are: London, which contains 14% of non-domestic buildings
in England and Wales, but 21% of offices; and the South West, which contains 11%
of non-domestic buildings but 20% of hospitality buildings.
•
There are 268,700 off-gas grid ND-NEED non-domestic buildings in England and 23,500 in
Wales, 17% of the ND-NEED non-domestic building stock.
•
Broadly, the proportions of all non-domestic buildings that are off-gas grid by building type
mirror that for all buildings, with offices accounting for the highest proportion (20%), closely
followed by factory and hospitality buildings.
•
The South West and East regions have the highest shares of non-domestic buildings laying
off the gas grid (27% and 25% respectively), with London the lowest (10%). In the South

Responsible statistician: James Hemingway
Media enquiries: xx-xxxx-xxxx
Email: xxx@xxx.xx
Statistical enquiries: xx-xxxx-xxxx
West, 42% of hospitality buildings are off the gas grid. In total, off-gas grid buildings
comprise 17% of the non-domestic building stock.
• This year, we have included new maps, showing the proportions of off-gas grid buildings
within all non-domestic buildings in England and Wales, by region and local authorities.
What you need to know about these statistics:

The statistics in ND-NEED cover all non-domestic buildings in England and Wales, under
the ND-NEED definition (see main ND-NEED 2024 report for detail).

Information on the non-domestic building stock (building number, building use, building
size, off-gas grid) reflects the position at the end of March 2024.

Information on energy consumption is presented for 2022, and comprises electricity and
gas consumed via the public distribution system (onsite generated electricity, oil, LPG
and biomass consumption are not included).

All geographic maps and associated data are split using the administrative boundaries in
England and Wales for 2024.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
3

Contents
1. Introduction _____________________________________________________________ 4
What questions can be answered by ND-NEED Geographical Annex? ________________ 5
What questions cannot be answered by ND-NEED Geographical Annex? _____________ 6
2. Changes since the ND-NEED 2023 Geographical Annex __________________________ 7
3. Results _________________________________________________________________ 8
England and Wales ND-NEED non-domestic building stock ________________________ 9
Number of non-domestic buildings by region __________________________________ 9
Number of non-domestic buildings by region and building use ____________________ 10
Number of non-domestic buildings by local authority (LA) _______________________ 13
Number of non-domestic buildings by parliamentary constituency (PC) _____________ 17
Number of non-domestic off-gas grid buildings ________________________________ 19
Floor area of non-domestic buildings by region and building use __________________ 26
England and Wales non-domestic building energy consumption ____________________ 27
Non-domestic total consumption by region (ND-NEED meter level population) _______ 29
Non-domestic total consumption by region, split by building use (ND-NEED weighted
matched sample) ______________________________________________________ 31
Non-domestic total consumption by region, 2020 to 2022 (ND-NEED meter level
population) ___________________________________________________________ 33
4. Method ________________________________________________________________ 36
Creating the ND-NEED Geographical Annex Dataset ____________________________ 36
Missing floor area data in ND-NEED Geographical Annex dataset __________________ 46
Weighting the ND-NEED matched sample consumption dataset ____________________ 48
Creating the Geographical ND-NEED meter dataset _____________________________ 51
Comparing the measures of non-domestic consumption __________________________ 53
Validating the regional breakdown of ND-NEED weighted matched sample consumption
data against ND-NEED meter level consumption data __________________________ 54
Creating Geographical ND-NEED maps _______________________________________ 55
5.Further information _______________________________________________________ 57
Accompanying tables _____________________________________________________ 57
Future updates to these statistics ____________________________________________ 58
Related statistics ________________________________________________________ 58
Revisions policy _________________________________________________________ 60
Code of Practice for Statistics compliance _____________________________________ 60
User engagement ________________________________________________________ 60
Contact ________________________________________________________________ 60

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
4

1. Introduction
The Non-Domestic National Energy Efficiency Data-Framework (ND-NEED) 2024
Geographical Annex (Geographical ND-NEED) provides additional geographical insight into
the ND-NEED 2024 publication.
It provides information and analysis into the differences in electricity and gas consumption of
non-domestic buildings within England and Wales in 2022 by region, local authority (LA) and
parliamentary constituency (PC).
Additionally, it provides information and analysis into the differences in the non-domestic
building stock – under the ND-NEED definition - within England and Wales in 2024 by region,
LA and PC. Further splits are provided for ND-NEED building uses, building sizes and for non-
domestic buildings in areas that have no buildings connected to the gas distribution network
(off-gas grid buildings). This is summarised in Table 1.
Table 1: Summary of the data presented in the Geographical ND-NEED annex

This is an annex to ND-NEED to provide information regarding geographical differences in
non-domestic building energy use and the non-domestic building stock within England and
Wales. It is intended that the data tables will be updated following the main ND-NEED
publication, the next update of which is planned for the summer of 2025.
Metric
Regional
Local Authority &
Parliamentary Constituency
Number of buildings
Building use

Larger than or smaller than or
equal to 1,000m2

Off-gas Grid – rural or urban

Building use

Off-gas Grid – rural or urban

Floor area
Aggregated building uses

Aggregated building uses
Electricity and gas
consumption
Total consumption (from meter
population)

Building use (from weighted
ND-NEED matched sample)

Total consumption (from meter
population)

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
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The ND-NEED geographical annex uses postcode information in the ND-NEED dataset and
geographical datasets from the Office for National Statistics (ONS) to split the ND-NEED data
by geography. Data from Xoserve was used to identify buildings in postcodes that have no
buildings connected to the gas distribution network (off-gas grid buildings).
The datasets used in Geographical ND-NEED are:
1. The ND-NEED 2024 dataset1 of all non-domestic buildings in England and Wales
(under the ND-NEED definition) which includes information on building postcode,
building use, building size, and building energy consumption.

2. The ONS National Statistical Postcode Lookup (NSPL)2 which relates postcodes in the
UK to ONS area codes (Region, Local Authority (LA) and Parliamentary Constituency
(PC)). This also includes information on whether a postcode is in a rural or urban area.

3. The ONS Names and Codes lookup tables3 which relates the names of geographical
areas to ONS area codes used in the NSPL.

4. The ONS Boundary shapefiles4 which contain the boundary shape of UK LAs and PCs.
This is used to produce maps of the geographical data.

5. Xoserve off-gas grid data5. This lists postcodes in Great Britain in which there are no
buildings, domestic or non-domestic, connected to the national gas grid.
The 1,755,000 non-domestic buildings in the ND-NEED dataset were matched by postcode to
the ONS NSPL, with a 99.6% match rate. This allowed the region, LA and PC codes of the
1,749,000 matched non-domestic buildings to be identified. More information about this
matching process can be found in the method section.
The ONS Names and Codes lookup tables were used to obtain the area names corresponding
to these codes and the ONS Boundary shapes files were used to obtain the shape of these
areas so geographical maps could be created.
The postcodes in the ND-NEED dataset were also matched to the Xoserve off-gas grid dataset
and a flag was created for non-domestic buildings in postcodes where no buildings, domestic
or non-domestic, are connected to the national gas grid.
What questions can be answered by ND-NEED Geographical
Annex?
• How many non-domestic buildings were there in a particular geographical area (region,
LA, PC) in England and Wales in 2024, split by building use?

• How much non-domestic building floor area was there in a particular geographical area
(region, LA, PC) in England and Wales in 2024, split by building use?

1 ND-NEED 2024
2 ONS NSPL
3 ONS LA Names and Codes and ONS PC Names and Codes
4 ONS LA Boundaries and ONS PC Boundaries
5 Xoserve data

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
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• How many non-domestic buildings were there in a particular geographical area (region,
LA, PC) in England and Wales in 2024 that were off the gas grid?

• How did the non-domestic electricity/gas consumption vary by geographical area
(region, LA, PC) of England and Wales in 2022? How has this changed over time?

• How did the non-domestic electricity/gas consumption/intensity vary by region of
England and Wales in 2022, split by building use?
What questions cannot be answered by ND-NEED
Geographical Annex?
• What are the variations in characteristics or energy consumption of the non-domestic
building stock across Scotland and Northern Ireland?

• How much of other fuels (e.g. biomass/LPG/oil) do non-domestic buildings consume in
each geographical area?

• How has the non-domestic building stock or consumption changed over time?
Currently, only the latest year is presented here, providing a snapshot. For building
stock figures, comparison may be made with the previous publication. However, two
caveats should be noted:

a. The previous snapshot was three years prior, so any growth should be
considered over that time.
b. ND-NEED building stock is produced on a Unique Property Reference
Number (UPRN) basis. Not every building is allocated a UPRN, however, the
allocation rate may improve over time, so a small percentage of any change
between the years may be due to this. As an example, in the main ND-NEED
2024, around 1% of the building stock in 2024 were buildings that existed
previously but had only been allocated UPRNs in the latest edition.6

To analyse consumption, by building use or size, over time, it is recommended that
users refer to the main ND-NEED 2024 publication, which presents a complete time-
series of this, but for England and Wales only. Alternatively, a time-series of non-
domestic meter population for electricity and gas consumption for the last three years,
by local authorities and regions, can be found in tables 4a, 4b, 11a and 11b of the
accompanying data tables in the ND-NEED Geographical Annex 2024 publication. A
longer time-series (on a slightly different basis) is available in the sub-national electricity
and gas consumption statistics; however, there is no further disaggregation by building
use or size presented in these. Table 14 in the method section presents the other key
differences between that data, and the data presented here.

• How does non-domestic building characteristics or energy use differ in each
geographical area between:
•
Rented or owner-occupied buildings?
•
Public or private buildings?

6 See the ND-NEED 2024 methodology note (page 4) for more details on this.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
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•
Buildings occupied by small, medium, or large businesses?
2. Changes since the ND-NEED 2023
Geographical Annex
The ND-NEED Geographical Annex was last published in February 2024 (consistent with ND-
NEED 2023). Since then, several changes have been made.

The key changes are listed below – the first two of these are data updates to align with the
latest ND-NEED publication, the third is a data update specific to the geographical annex
publication, the fourth is a new addition to the report, while the fifth is a new addition to the
accompanying data tables:

1. Updated building stock data. This now covers the stock as of March 2024 (March
2023 previously). This is used as the basis for creating the ND-NEED sample (where
electricity and gas consumption data are matched to the building stock), and therefore
impacts on the consumption data presented. More information on the building stock
update can be found in the ND-NEED methodology note (page 4).

2. Updated electricity and gas meter consumption data. This now covers 2022 (from 2021
previously).

3. Updated look up and boundary files. The report uses updated boundary and lookup
files from the latest NSPL (National Statistics Postcode Lookup) published in August
2024 which reflects the most recent Parliamentary Constituency (PC) breakdowns,
which now takes on the July 2024 structure. The regions affected by this change are:
a. Wales which now has 32 PCs in comparison to 40 in the 2023 Geographical
Annex.
b. North East which now has 27 PCs in comparison to 29 previously
c. North West which now has 73 PCs in comparison to 74 previously.
d. East Midlands which now has 47 in comparison to 45 previously.
e. West Midlands which now has 57 in comparison to 59 previously.
f. East of England which now has 61 in comparison to 58 previously
g. London which now has 75 in comparison to 73 previously.
h. South East now 91 compared to 86 previously.
i. South West which now has 58 in comparison to 55 previously.

Further details of these changes can be found in table 9.

4. New off-gas grid building maps. We have included new heat maps showing the
proportions of off-gas grid buildings within all non-domestic buildings in each region and
local authority.

5. Time series of energy consumption. The electricity and gas consumption from the
ND-NEED meter population by region, local authority and parliamentary constituencies
have been extended to previous years covering 2020, 2021 and 2022 data (Tables 4a,
4b, 11a and 11b of the accompanying data tables). Details of revisions to the 2021 data
previously published in Tables 4 and 11 can be found in the ND-NEED methodology
note (pages 6-8).

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
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3. Results
The following data is presented in the data tables accompanying this publication. An asterisk
(*) indicates that this data is also presented in this report for further analysis.

Table
Region
Local
Authority
Parliamentary
constituency
Table 1: the number of ND-NEED non-domestic
buildings, by building use*
X
X

Table 2: the floor area of ND-NEED non-
domestic buildings, by building use*
X
X

Table 3A: the number of ND-NEED non-domestic
off-gas grid buildings, by rural and urban
X
X

Table 3B: the number of off-gas grid ND-NEED
non-domestic buildings, by building use
X

Table 4A and 4B: the electricity and gas
consumption from ND-NEED meters*
X
X

Table 5: the ND-NEED number of non-domestic
buildings larger than 1,000m2, by building use*
X

Table 6: the ND-NEED number of non-domestic
buildings smaller than or equal to 1,000m2, by
building use*
X

Table 7A: the scaled ND-NEED non-domestic
electricity consumption, by building use*
X

Table 7B: the scaled ND-NEED non-domestic
gas consumption, by building use*
X

Table 8: the number of ND-NEED non-domestic
buildings, by building use*

X
Table 9: the floor area of ND-NEED non-
domestic buildings, by building use

X
Table 10: the number of off-gas grid ND-NEED
non-domestic buildings, by rural and urban*

X
Table 11A and 11B: the electricity and gas
consumption from ND-NEED meters

X

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
9

England and Wales ND-NEED non-domestic building stock
Under the ND-NEED definition, there were 1,755,000 non-domestic buildings in England and
Wales at the end of March 2024. Of this total, 1,749,000 were successfully matched to a
location in England and Wales, and 6,000 non-domestic buildings failed to match to a location
due to the postcode not being present in the NSPL. More information about this matching
process can be found in the Method section.
The ND-NEED definition covers all non-domestic buildings included in the Valuation
Office Agency (VOA)’s non-domestic ratings list (NDR)7, excluding premises that are not
considered to be buildings for ND-NEED purposes. These are caravan parks, advertising
premises, car parks, beach huts, quarries, and telecoms units. For more information on
non-buildings, see page 23 of ND-NEED Methodology Note 2024.

Note, in the NDR the data is at the hereditament8 (Unique Address Reference Number
(UARN)) level. In ND-NEED it is aggregated to the building (Unique Property Reference
Number (UPRN)) level.

Number of non-domestic buildings by region
The number of ND buildings can be presented for each region of England and Wales. This is
displayed as a heatmap in Figure 1. The corresponding data can be found in Table 1 in the
accompanying data tables.
Note, as it is common for most areas to have values closer to the median than the
outliers, all heat maps use a log scale to improve clarity by better highlighting differences.
Darker blues indicate a comparatively higher number of non-domestic buildings, and
lighter yellows indicate a comparatively lower number of non-domestic buildings.

From Figure 1, the South East and London are the regions with the highest number of non-
domestic buildings while the North East and Wales have the lowest number of non-domestic
buildings. This variation in non-domestic building number between regions is broadly
consistent with the variation in population. South East and London have the highest
populations, whilst the North East and Wales have the lowest populations (ONS, 2022)9. This
indicates that there is a strong correlation between the number of people that live in a
particular area and the number of non-domestic buildings it contains.

7 Non-domestic rating 2024
8 A hereditament is a rateable property for the purpose of business rates.
9 Data from ONS population estimates

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
10

Figure 1: Number of non-domestic buildings by region in England and Wales

Number of non-domestic buildings by region and building use
The number of non-domestic buildings by region can also be disaggregated by building use.
This can be seen in Table 2 for the four non-domestic building uses with the highest number of
buildings (factories; offices; shops; and warehouses). Information about the other ND-NEED
building uses (arts, community, and leisure; education; emergency services; health; hospitality;
and other) can be found in Table 1 in the accompanying data tables.
Table 2 shows that the proportion of factories, offices, shops and warehouses in a region are
all broadly in line with the proportion of all non-domestic buildings in that region. The one

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
11

notable exception is London. London has a disproportionately high number of offices (21% of
all offices in England and Wales) compared to the 14% of all non-domestic buildings that are in
London. London also has a disproportionately low number of factories and warehouses (9% of
those in England and Wales compared to 14% for all non-domestic buildings that are in
London).
Table 2: The proportion of factories, offices, shops and warehouses in England and
Wales that are in each region10
Region
Factories
Offices
Shops
Warehouses All Building
Uses
England
94%
95%
94%
94%
94%
North East
5%
4%
5%
3%
4%
North West
12%
12%
14%
13%
13%
Yorkshire and The
Humber
11%
10%
10%
11%
10%
East Midlands
10%
7%
7%
8%
8%
West Midlands
11%
9%
10%
11%
9%
East
11%
9%
9%
12%
10%
London
9%
21%
18%
9%
14%
South East
14%
15%
13%
15%
14%
South West
12%
9%
9%
12%
11%
Wales
6%
5%
6%
6%
6%
Total
100%
100%
100%
100%
100%

Number of non-domestic buildings by region, building use and building size
The number of non-domestic buildings by region and building use can also be disaggregated
further, by building size. This analysis excludes the 18% (319,000) of non-domestic buildings in
the ND-NEED Geographical Annex dataset that are missing floor area data. More information
about why these buildings are missing floor area data can be found in the Method section.
The proportion of buildings that are missing floor area information differs substantially between
building uses, from 100% missing from emergency services buildings, to only 2% missing from
factory buildings, further details on this can be seen on table 13 of the ND-NEED methodology
document. Because of this, building use splits are only presented for the four that have over
80% of floor area present (factories, offices, shops, and warehouses).

10 These four building uses are presented here as they are the four largest ND-NEED building uses by building
number and because they align with the floor area figures presented later in the report.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
12

Table 3 contains the proportion of all non-domestic buildings larger than 1,000m2 in England
and Wales in each region, split by building use11 .
In general, the proportion of factories, offices, shops, and warehouses in a region are all similar
to the proportion of all non-domestic buildings in that region. This is the same pattern as was
seen for all non-domestic buildings in Table 2.
As in Table 2, the exception to this is London. London contains 10% of large non-domestic
buildings in England and Wales, but 27% of offices larger than 1,000m2. This is more than the
21% of all offices that are located in London. This could be because companies often locate
their headquarters in London, which are likely to be larger than offices in other areas. London
also contains 3% of factories larger than 1,000m2 (compared to 10% of all large non-domestic
buildings that are in London).
Table 3: Proportion of non-domestic buildings larger than 1,000m2 in England and Wales
that are in each region, by key building uses

Region
Factories
Offices
Shops
Warehouses
All Building
uses
England
94%
96%
94%
95%
95%
North East
6%
4%
5%
4%
5%
North West
14%
13%
14%
14%
14%
Yorkshire and The
Humber
14%
8%
10%
12%
12%
East Midlands
12%
6%
8%
10%
10%
West Midlands
15%
8%
11%
12%
12%
East
10%
9%
11%
12%
11%
London
3%
27%
10%
8%
10%
South East
11%
16%
14%
14%
13%
South West
9%
7%
11%
9%
9%
Wales
6%
4%
6%
5%
5%
Total
100%
100%
100%
100%
100%

11 This threshold has been chosen as it is an important threshold for non-domestic building decarbonisation policy.
For example the performance-based policy framework.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
13

Table 4 contains the proportion of non-domestic buildings smaller than or equal to 1,000m2
that are in each region in England and Wales, split by building use.
Again, the proportions by region in each building use are generally in line with the proportion of
all non-domestic buildings smaller than or equal to 1,000m2 in the region. London is still an
exception, but this difference is less for all non-domestic buildings or non-domestic buildings
larger than 1,000m2.
Table 4: Proportion of non-domestic buildings smaller than or equal to 1,000m2 in
England and Wales that are in each region, by key building uses

Region
Factories
Offices
Shops
Warehouses
All Building
uses
England
94%
95%
94%
94%
94%
North East
5%
4%
5%
3%
4%
North West
11%
12%
14%
13%
13%
Yorkshire and The
Humber
11%
10%
10%
10%
10%
East Midlands
10%
7%
7%
8%
8%
West Midlands
11%
9%
10%
11%
10%
East
11%
10%
8%
12%
10%
London
9%
20%
18%
9%
15%
South East
14%
15%
13%
15%
14%
South West
12%
9%
9%
12%
10%
Wales
6%
5%
6%
6%
6%
Total
100%
100%
100%
100%
100%

Number of non-domestic buildings by local authority (LA)
The number of non-domestic buildings in each LA was also calculated and presented as seen
on the heatmap in Figure 2. The corresponding data can be found in Table 1 in the
accompanying data tables.
Cornwall in the South West region has the highest number of non-domestic buildings with
32,000. LAs covering major cities including Birmingham, Leeds, Bradford, Sheffield and
Manchester are all in the top 10, with 15,000 or more non-domestic buildings. Westminster in
London is fourth highest with 27,000 non-domestic buildings.
The Isles of Scilly has the lowest number of non-domestic buildings at 480. All other LAs have
more than 1,000 non-domestic buildings.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
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Figure 2: Number of non-domestic buildings by LA in England and Wales

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
15

Note, there are large variations in the population of local authorities. For example, the
Metropolitan District of Birmingham has a population of 1,160,000, whilst the Isles of
Scilly has a population of 2,300 (ONS, 2022) 12

As there is a correlation between the population of a local authority and the number of
non-domestic buildings it contains (see Figure 3), population differences should be
considered when interpreting results at the local authority level.

To help with this, the number of buildings in a local authority per 100,000 population is
also presented in the data tables (see Table 1 in the accompanying data tables).

The number of non-domestic buildings in each parliamentary constituency are also
presented in this report below. Parliamentary constituencies have broadly similar
populations, so patterns seen will not be driven by population differences.
From Figure 3 we can see that there is a correlation between the population of the local
authority and the number of non-domestic buildings it contains, which at least partly explains
the results described above. There are however three prominent outliers: Cornwall, North
Yorkshire13 and Westminster have a much higher number of non-domestic buildings than
would be expected based on their population. Cornwall has a 1.8% share of the total number
of non-domestic buildings (at 32,000), followed by North Yorkshire with 1.7% (30,000) and
Westminster with 1.5% (27,000).
Figure 3: Variation of the number of non-domestic buildings with population for LA in
England and Wales 12

12 ONS population estimates
13 North Yorkshire became a local (unitary) authority as part of the restructure in 2023 – see ND-NEED 2023
Geographical Annex (page 32)

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
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In Cornwall this could be due to the relatively high number of tourists; 17 million tourist bed
nights were spent in Cornwall per year on average between 2021 and 2023, 5% of England’s
total14. Tourists increase the demand for hospitality buildings, but will not be counted in the
population estimates, increasing the number of non-domestic buildings per 100,000 population.
The demand for hospitality buildings in Cornwall can been seen in Table 1 (in the
accompanying data tables). Cornwall has one-third of the hospitality buildings in the South-
West, and the most hospitality buildings in England and Wales with almost 13,000 buildings
(6.7% of hospitality buildings in England and Wales).
The 13,000 hospitality buildings in Cornwall represents a decrease of 7% compared to the
figure presented in the 2023 geographical annex , which may be partly due to the removal of
holiday homes following The Non-Domestic Rating (Definition of Domestic Property) (England)
Order 2022 (which means that holiday lets have to meet certain criteria to remain on the NDR
list). All regions – except for London - have seen decreases of between 1% and 7% in
hospitality buildings.
In Westminster, the high number of non-domestic buildings, compared with the population,
could be due to the disproportionately high number of office buildings in this area. Westminster
contains the largest share (4.6%) of all offices in England and Wales, but only 1.5% of all non-
domestic buildings. Many of the workers in these offices will not live in the local area but will
commute from elsewhere, and so will not be included in the population estimates. The high
number of offices in the area will also drive demand for other non-domestic buildings such as
hospitality buildings, to cater for the workforce.
Whilst the overall number of offices in England and Wales has decreased roughly in line with
the overall building stock (by around 0.5%) since the last update in the 2023 geographical
annex , there has been variation. The number of offices in the West Midlands increased by
1.6%, driven by a 9.5% (6,650 to 7,280) increase in Birmingham, while the South-East fell by
1.3% and London by 1.1%. Within London, most local authorities saw falls in the number of
offices in 2024, with Wandsworth the largest fall. In this local authority, following a slight
increase in the number of offices (2%) between 2020 and 2023, the number fell by 11%, from
1,880 to 1,670 buildings, in 2024. Slough in the South East showed a similar pattern –
following an increase of 5% across 2020 to 2023 to 910 buildings, the number of offices fell by
21% to 720 buildings this year, which could be a result of offices closure and hybrid working.
Adjusting for population, the City of London, the Isles of Scilly and Westminster have the most
non-domestic buildings of any LA (30,000, 21,000 and 13,000 non-domestic buildings per
100,000 population respectively). Bracknell Forest in the South East has the lowest rate, at
1,000 non-domestic buildings per 100,000 population. Bracknell Forest also has the fourth
lowest number of non-domestic buildings of any LA in England and Wales at 1,000. Of the 10
LAs with the lowest number of non-domestic buildings per 100,000 population, six are in the
South East and outer London areas.

14 Visit Britain Local Authority Data

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
17

Number of non-domestic buildings by parliamentary constituency (PC)
Figure 4 shows the number of non-domestic buildings in each PC. The corresponding data can
be found in Table 8 in the accompanying data tables.
PC boundaries are drawn so that they contain voting populations of broadly the same
size (House of Commons, 2023)15. Because of this, data presented at PC level will be
relatively unaffected by variations in population. To note that this year’s report takes on
the 2023 review boundaries (increasing the number of PCs by two) – further information
can be found in the Method section.

The PC of the Cities of London and Westminster has the highest number of non-domestic
buildings in England and Wales, with 28,000 non-domestic buildings or 1.5% of the non-
domestic buildings in England and Wales.
The PC of Birmingham Ladywood has the second highest number of non-domestic buildings
with 13,000 buildings at a 0.7% share, with the constituencies of Manchester Central,
Westmorland and Lonsdale, Liverpool Riverside, North Cornwall and Dwyfor Meirionnydd
joining three other London constituencies to complete the ten PCs with the most non-domestic
buildings. Seven of the top ten are within large cities, suggesting that perhaps city centres tend
to have few domestic properties and densely packed non-domestic properties.
The PCs with the lowest number of non-domestic buildings are also in urban areas but tend to
be located towards the outskirts of towns and cities, rather than in the centre. For example,
Sheffield Hallam has the fewest non-domestic buildings (1,000) while Bracknell has the second
fewest with 1,030 non-domestic buildings. This could be because suburban areas towards the
edge of large cities/towns have a higher proportion of domestic buildings and fewer non-
domestic ones.

15 House of Commons Research Briefing on PC boundaries

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
18

Figure 4: Number of non-domestic buildings by PC in England and Wales

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
19

Number of non-domestic off-gas grid buildings
Further analysis has been undertaken to identify the geographical distribution of the non-
domestic buildings in England and Wales that are off the gas grid. Full results at PC, LA and
regional level can be found in the accompanying data tables (Table 3A, Table 3B and Table
10).
Buildings in the ND-NEED Geographical Annex were identified as either ‘on-gas grid’ or ‘off-
gas grid’ using Xoserve data containing postcodes with no connections to the national gas grid
(2024). More information on the classification of off-gas grid buildings is available in the
Method section.
The ND-NEED definition of an off-gas grid non-domestic building is a non-domestic
building in a postcode where no building, domestic or non-domestic, has a connection to
the gas distribution network.

This analysis shows that 17% (292,000) of non-domestic buildings in England and Wales are
off-gas grid. The proportion of buildings that are off-gas grid varies substantially between
regions from only 10% in London to 27% in the South West (see Table 3A and Table 3B in the
accompanying data tables and Figure 5A and Figure 5B).

Data is also available for the number of domestic properties that are not connected to the gas
grid16. Whilst this is on a slightly different basis from the method used for non-domestic
buildings (see Method section), the headline results are similar, with 15% of domestic
properties in Great Britain not connected to the gas grid17.
Number of off-gas grid buildings by region
Figure 6a shows the proportion of the off-gas grid buildings within all non-domestic buildings by
region in England and Wales. The South West has the highest share of off-gas grid buildings in
the non-domestic buildings at 27%, followed by the East at 25%. London has the lowest
proportion of off-gas grid buildings in non-domestic buildings at 10%, followed by the North
West at 12% (See Table 3B of the accompanying data tables).

16 Subnational estimates of properties not connected to the gas network
17 Subnational electricity and gas consumption summary report 2022

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
20

Figure 5a: Proportion of non-domestic buildings that are off-gas grid by region in
England and Wales

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
21

Number of off-gas grid buildings by region and building use
Analysis of the number of off-gas grid buildings by building use found that offices make up the
highest proportion of all off-gas grid non-domestic buildings (20%), closely followed by
factories (18%) and hospitality (18%). The building uses with the lowest proportion of all off-
gas grid non-domestic buildings were emergency services (0.1%), health (1%) and education
(2%). These proportions broadly follow a similar pattern to the proportion of each building type
in England and Wales. The exceptions to this pattern are factories and hospitality buildings
which make up 14% and 11% of non-domestic buildings respectively yet each account for 18%
of off-gas grid buildings.
The proportion of factories, offices, shops, and warehouses in each region are also generally in
line with the proportion of all non-domestic floor area in that region. Again, London is the
exception, with a disproportionately high share of offices off the gas grid (21%), and a
disproportionately low share of factories off the gas grid (4%), compared with an 8% share of
all off-gas grid buildings.
Table 5 shows the number of off-gas grid non-domestic buildings as a proportion of all non-
domestic buildings of that building type by region18. The South West and East regions stand
out in particular with relatively higher shares of their building stock laying off the gas grid. The
South West has the highest proportion of off-gas grid buildings at 27%, particularly 42% of
hospitality buildings in the South West lay off the gas grid. This is closely followed by East
where 25% of its non-domestic buildings are off the gas grid, with around 35% of each of its
factories laying off the gas grid. Across all regions, shops have the lowest proportion of
buildings off the gas grid, ranging from 5 to 10%.
Number of off-gas grid buildings by local authority
Figure 5b shows the proportion of off-gas grid buildings within all non-domestic buildings by
local authority in England and Wales. The Isles of Scilly (in the South West) has the highest
share at 100%, followed by Torridge in the South West at 60%. Tamworth in the West
Midlands has the lowest proportion of off-gas grid buildings in non-domestic buildings at 1%,
followed by Erewash in the East Midlands at 2% (See Table 3B of the accompanying data
tables).

18 Alongside the other four building use categories that are included in previous tables, hospitality has been
included in table 5 due to its significance of off-gas grid buildings. It has the second highest number of off-gas grid
non-domestic buildings (after offices), and, besides the “other” category, the highest proportion of non-domestic
buildings laying off the gas grid.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
22

Figure 5b: Proportion of non-domestic buildings that are off-gas grid by local authority
in England and Wales

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
23

Number of off-gas grid buildings by parliamentary constituency
Analysis of the number of off-gas grid buildings by parliamentary constituency found that the
PCs with the highest proportion of off-gas grid non-domestic buildings were in the
predominantly rural Ceredigion Preseli (59%) and Waveney Valley and South (58%). The PCs
with the lowest proportion of off-gas grid non-domestic buildings were in Leicester East,
Birmingham Hodge Hill and Solihull North, and Mitcham and Morden. All these PCs have less
than 1% of non-domestic buildings off-gas grid.
Rural/Urban split
As the PC level data indicates that there is a difference between the number of off-gas grid
buildings in rural and urban area, the data can be disaggregated further, using the ONS NSPL
rural-urban classification method. This shows that 185,000 off-gas grid non-domestic buildings
are situated in rural areas (63%), and 108,000 off-gas grid non-domestic buildings are in urban
areas (37%). The number of off-gas grid non-domestic buildings in each PC that are urban or
rural respectively are presented in Figures 6a and 6b.
Note, the maps in Figure 6a and 6b are presented at the PC level, whereas the
urban/rural split is at the 2024 Census Output Areas level, which are much smaller than
PCs. This means the majority of PCs are coloured in both the urban and rural maps, as
they contain both urban and rural Output Areas.
The PCs with the highest number of urban off-gas grid non-domestic buildings are in city
centres, including the Cities of London and Westminster (7,700), Manchester Central (1,600)
and Holborn and St Pancras (1,400). The PCs with the highest total number of rural off-gas
grid non-domestic buildings are in North Cornwall (4,000), St Ives (3,400) and North Norfolk
(2,800).
The top rural PCs have a higher number of off-gas grid buildings than the top urban PCs. As
urban PCs are likely to be more densely populated, this suggests that rural PCs tend to have
larger geographical areas that are off the gas grid than urban PCs. The higher number of off-
gas grid buildings in rural areas also ties in with the fact that 63% of all off-gas grid buildings
are in rural areas.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
24

Figure 6a: Number of rural off-gas grid buildings by PC in England and Wales

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
25

Figure 6b: Number of urban off-gas grid buildings by PC in England and Wales

Note, In Figures, 6a and 6b, NA (shaded in grey) represents areas where there are no
rural or urban off-gas grid buildings, such as Dwyfor Meirionnydd in Wales in Figure 6b.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
26

Table 5: Number of off-gas grid non-domestic buildings as a proportion of all non-
domestic buildings in each region in England and Wales, by building use

Floor area of non-domestic buildings by region and building use
Analysis has also been carried out to disaggregate non-domestic building floor area in England
and Wales by region, local authority and parliamentary constituency. Analysis of the results at
the regional level can be found below. Data at the local authority level can be found in Table 2
in the accompanying data tables, and at the parliamentary constituency level in Table 9.
Note, 319,000 (18%) of the 1,755,000 non-domestic buildings in the ND-NEED
Geographical Annex dataset do not have floor area information, and so are excluded
from this analysis.

The proportion of buildings missing floor area information varies slightly between regions,
ranging from 14% in London to 26% in the South West (see Table 11 in the Method
section). This may inflate the results from regions with a higher proportion of floor area
present and deflate the results from the regions with a lower proportion of floor area
present.

Table 6 shows the proportion of floor area of non-domestic buildings in each region in England
and Wales, split by building use. As with Tables 2 and 3, data are only presented for building
uses that have floor area for more than 80% of buildings.
Region
Factories
Hospitality
Offices
Shops
Warehouses
All
Building
uses
England
21%
25%
16%
6%
22%
16%
North East
15%
31%
12%
6%
17%
14%
North West
14%
18%
14%
5%
14%
12%
Yorkshire and
The Humber
14%
21%
12%
5%
16%
13%
East Midlands
19%
19%
14%
5%
19%
15%
West Midlands
18%
23%
13%
6%
18%
14%
East
35%
33%
22%
9%
34%
25%
London
10%
6%
16%
6%
9%
10%
South East
29%
18%
19%
7%
28%
18%
South West
33%
42%
19%
10%
32%
27%
Wales
25%
43%
14%
8%
20%
21%
England &
Wales
22%
27%
16%
6%
22%
17%

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
27

Table 6: Proportion of floor area of non-domestic buildings in each region in England
and Wales, by building use

Table 6 shows that floor area has a similar pattern to building numbers (see Table 2). The
proportion of factories, offices, shops, and warehouses in each region are all generally in line
with the proportion of all non-domestic floor area in that region. Again, London is the exception,
with a disproportionately high share of office floor area (26%), and a disproportionately low
share of factory floor area (3%), compared with 10% of non-domestic building floor area in
London.
England and Wales non-domestic building energy consumption
This section of the report analyses the distribution of non-domestic building electricity and gas
consumption, in England and Wales.
Two methods are used to produce this analysis. A brief outline of these methods are
summarised in Figure 7, and the implications this has on the resulting analysis is provided
below.
Please consider this when deciding which energy consumption method is most
appropriate for your work. More information and a comparison of the methods used,
including how these methods compare to the sub-national statistics19, and their impact on
the energy consumption analysis, can be found in the Method section.

19 Subnational electricity and gas consumption summary report 2022
Region
Factories
Offices
Shops
Warehouses
All Building
uses
England
93%
96%
94%
96%
95%
North East
7%
4%
5%
4%
5%
North West
14%
12%
14%
13%
13%
Yorkshire and The
Humber
15%
8%
10%
12%
12%
East Midlands
12%
6%
8%
13%
10%
West Midlands
13%
8%
10%
13%
12%
East
10%
8%
10%
13%
11%
London
3%
26%
14%
7%
10%
South East
10%
15%
14%
13%
13%
South West
9%
8%
10%
8%
9%
Wales
7%
4%
6%
4%
5%
Total
100%
100%
100%
100%
100%

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
28

1. ND-NEED meter population total consumption
Consumption data by geographical area can be presented using the entire underlying ND-
NEED meter population. This is the meter level data of all non-domestic buildings in England
and Wales and is what the ND-NEED sample consumption data is scaled to (see the
methodology note of the main ND-NEED 2024).
The major advantage of this method is it captures all electricity and gas consumption from non-
domestic buildings. This allows meaningful comparisons of consumption between all
geographical areas.
The key disadvantages of this method are that:
1. The data cannot be split by building use or building size. This is because these meters
have not been matched to their corresponding buildings, so the characteristics of the
buildings they are in are unknown.

2. The data includes consumption from ‘non-buildings’ that are excluded under the ND-
NEED definition, for example car parks or quarries. This adds an extra 10-15% to the
weighted matched sample consumption figures also presented here.
Due to the lack of a geographical component in the weighting method, this is the best
representation of the distribution of total electricity and gas consumption across region, local
authority or parliamentary constituency.
2. ND-NEED weighted matched sample consumption
Due to the limitations of the address-matching process, just over 50% of buildings in the ND-
NEED stock were successfully allocated 2022 electricity consumption meter data. This creates
a sample of 859,000 non-domestic buildings with 2022 electricity consumption data. Out of
which, 349,000 non-domestic buildings were also matched to 2022 gas consumption data.
As the sample of matched buildings is not representative of the entire building stock, ND-
NEED weights the sample to the population level. The weights scale a building in the matched
sample based on its use and size. Full details of the weighting process can be found in the
methodology note of ND-NEED 2024.
The key advantage of this method is that the consumption data can be split by building use
since the consumption data has been linked to the corresponding ND-NEED buildings.
The key disadvantage of this method is that the number of buildings missing electricity or gas
consumption information in the matched sample differs between geographical areas. This bias
in the matching process is not fully accounted for in the weighting process. Because of this
bias, data from the ND-NEED meter population method should be used when building use or
building size splits are not needed.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
29

Figure 7: Methods for calculating consumption of non-domestic consumption from ND-
NEED data

Non-domestic total consumption by region (ND-NEED meter level population)
As outlined above, this report presents consumption from the ND-NEED meter population, split
by region. The results of this analysis at regional level are summarised in Figures 8a and 8b,
while the ND-NEED meter population consumption data, and how this has changed in the
years since 2020, at local authority and parliamentary constituency level can be found in
Tables 4A, 4B, 11A and 11B in the accompanying data tables.
*Includes meter data from ‘non-buildings’, under the ND-NEED definition

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
30

The ND-NEED meter population dataset (England and Wales) differs from the non-
domestic subnational dataset (GB) because it includes consumption from low-consuming
‘domestic-like’ non-domestic meters.

Electricity consumption
The non-domestic subnational electricity consumption data contains all electricity meters
in non-domestic profile classes (0, 3-8). ND-NEED meter population dataset contains all
these meters and any meters in domestic profile classes (1 and 2) that can be matched to
a non-domestic address.

Gas consumption
The non-domestic subnational gas consumption data contains all gas meters that
consume greater than 73.2 MWh. ND-NEED meter population dataset contains all these
meters and any meters that consume less than 73.2 MWh that can be matched to a non-
domestic address.

More information on the differences between the ND-NEED meter population dataset and
the non-domestic subnational dataset can be found in the Method section.

Figure 8a shows that meter level electricity consumption is highest in London and the South-
East (16% and 14% of the total ND-NEED electricity meter level consumption respectively),
and lowest in the North East and Wales (5% and 6% respectively). This is in line with the
number of non-domestic building in these regions, with London and the South East containing
the highest number of non-domestic buildings, and the North East and Wales containing the
lowest number of non-domestic buildings.
Within London, the Cities of London and Westminster parliamentary constituency has the
highest electricity consumption (3% of all of England and Wales), and at the local authority
level, Westminster (1.9% of England and Wales). See Tables 4a and 11a of the accompanying
data tables for more details.
Figure 8b shows that the meter level gas consumption has a slightly different regional pattern
than electricity. It is highest in the North West (16%), London (13%) and Yorkshire and the
Humber (12%). In the case of North West and Yorkshire and the Humber, this could be driven
by the high gas demands of factories in these traditionally industrial areas, as factories
consume more than twice as much gas as any other ND-NEED building use (see Table 7b in
the accompanying data tables). This interpretation is supported by the fact that the North West
is the region that contains the most factories floor area (14%), followed closely by Yorkshire
and the Humber (15%). As with meter level electricity consumption, the regions with the lowest
meter level gas consumption are in the North-East (5%) and Wales (6%).
Within the North-West, Stretford and Urmston parliamentary constituency has the highest gas
consumption (1.0% of England and Wales), and at the local authority level, Trafford (1.1% of
England and Wales). See Tables 4b and 11b of the accompanying data tables for more details.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
31

Figure 8: Meter level consumption of non-domestic buildings by region in England and
Wales, 2022

Non-domestic total consumption by region, split by building use (ND-NEED
weighted matched sample)
Non-domestic building consumption can also be estimated using the ND-NEED weighted
matched sample. This method relies upon a sample which is scaled up to represent the
population, and therefore will be less accurate than the ND-NEED meter population data.
However, this data includes building stock information, and therefore can be presented at a
building use level. An analysis of the accuracy of the weighted matched sample when
compared to the meter level data is available in the Method section.
Tables 7 and 8 show the proportion of electricity and gas consumed by region in England and
Wales based on the weighted ND-NEED matched sample. This is shown for the four ND-
NEED building uses with the largest number of buildings. These are the same building uses
that were presented for the building stock in Tables 2-6. Consumption data for other building
uses can be found in the Tables 7A and 7B of the accompanying data tables.
Figure 8a: Electricity meter consumption
Figure 8b: Gas meter consumption

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
32

Table 7 shows that 35% of electricity consumed by offices is consumed in London. Table 2
shows that 21% of offices are in London, which suggests that offices in London consume an
above average amount of electricity. On average, offices in London are larger than in other
parts of England and Wales (average office floor area in London is 305m2, compared to 234m2
in England and Wales (see accompanying data table 2). This may contribute to their high
electricity consumption.
Table 7: Proportion of electricity consumption by region in England and Wales by
building use using ND-NEED weighted matched sample data

Table 8 shows that Yorkshire and the Humber, the East and the North West are each
responsible for around one fifth of the gas consumed in factories. Table 2 shows that the North
West contains 12% of factories in England and Wales, East contains 11% and Yorkshire and
the Humber contains 11%. Table 3 shows that Yorkshire and the Humber and the North West
regions contain 15% and 14% factory floor area respectively in England and Wales. This
suggests these factories are larger than average, which may contribute to their high gas
consumption.

Region
Factories
Offices
Shops
Warehouses
All Building
uses
England
90%
95%
95%
97%
94%
North East
9%
3%
5%
3%
5%
North West
17%
8%
12%
15%
15%
Yorkshire and The
Humber
14%
8%
10%
10%
10%
East Midlands
12%
5%
8%
11%
9%
West Midlands
11%
5%
9%
12%
9%
East
9%
8%
10%
13%
10%
London
3%
35%
18%
11%
15%
South East
10%
17%
14%
14%
13%
South West
6%
6%
9%
8%
8%
Wales
10%
5%
5%
3%
6%
Total
100%
100%
100%
100%
100%

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
33

Table 8: Proportion of gas consumption by region in England and Wales by building use
using ND-NEED weighted matched sample data

Region
Factories
Offices
Shops
Warehouses
All Building
uses
England
92%
96%
95%
95%
93%
North East
3%
4%
5%
6%
5%
North West
18%
11%
13%
11%
17%
Yorkshire and The
Humber
19%
9%
10%
12%
12%
East Midlands
12%
10%
9%
13%
11%
West Midlands
7%
8%
10%
12%
8%
East
22%
12%
10%
12%
15%
London
4%
23%
17%
11%
10%
South East
4%
12%
14%
12%
9%
South West
3%
7%
8%
6%
6%
Wales
8%
4%
5%
5%
7%
Total
100%
100%
100%
100%
100%

Non-domestic total consumption by region, 2020 to 2022 (ND-NEED meter level
population)
This year, we have extended the electricity and gas consumption data to show previous years.
This section shows how meter level consumption of non-domestic buildings has changed in the
last three years, by region (see Tables 4a, 4b, 11a and 11b of the accompanying data tables
for more details).
In 2022, electricity consumption from the ND NEED meter population fell by 0.3% on 2021,
following an increase of 5% on 2020. Meanwhile, gas consumption fell by 5% in 2022
following a similar decrease of 5% in 2021. These patterns are similar to that seen in ND
NEED weighted matched electricity and gas consumption over the last three years - see tables
8a-8d of ND-NEED 2024 for further details.
Figure 9a shows how electricity consumption has changed in the last three years by region in
England and Wales. After a 6% fall in 2021, consumption in England remained broadly flat in
2022, with small increases in London and the South East offsetting reductions across all other
regions. Consumption in Wales also fell by around 3%, following a 7% fall in 2021.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
34

Figure 9a: Meter level electricity consumption of non-domestic buildings by region in
England and Wales, 2020 to 2022

Figure 9b shows how gas consumption has changed in the last three years by region in
England and Wales. With consumption in 2021 broadly unchanged from 2020, consumption in
England fell by around 4% in 2022. Whilst all regions saw a fall in gas consumption in 2022,
this was principally driven by 7% falls in each of the North West (the region with the highest
gas consumption), the North East and the South East. Consumption in Wales also fell by
around 4%, following a 3% fall in 2021.

0
5
10
15
20
25
2020
2021
2022
Electricity Consumption (TWh)
Wales
North East
North West
Yorkshire and The Humber
East Midlands
West Midlands
East
London
South East
South West

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
35

Figure 9b: Meter level gas consumption of non-domestic buildings by region in England
and Wales, 2020 to 2022

0
5
10
15
20
25
30
2020
2021
2022
Gas Consumption (TWh)
Wales
North East
North West
Yorkshire and The Humber
East Midlands
West Midlands
East
London
South East
South West

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
36

4. Method
To produce the results in the ND-NEED geographical annex two new datasets are created.
These are:
The ND-NEED Geographical Annex dataset.
The ND-NEED Geographical Annex dataset is the ND-NEED dataset used in the main report,
with geographical area information added.
The ND-NEED dataset contains all ND-NEED non-domestic buildings in England and Wales. It
is based on the non-domestic ratings data from the VOA which contain all non-domestic
hereditaments that pay business rates. This data is aggregated to the building level. Certain
building uses are excluded as they are not considered to be buildings. This creates a dataset
of 1,755,000 ND-NEED non-domestic buildings with information on their building use and
building size.
These 1.8 million non-domestic buildings are then matched to electricity and gas consumption
information held by DESNZ, using address matching. This matches around 51% of buildings to
their electricity consumption data and 20% of buildings to their gas consumption data.
Consumption from these ‘matched’ buildings is weighted to produce consumption figures for
the whole non-domestic building population.
This dataset is used to produce geographical breakdowns of non-domestic building number,
non-domestic floor area and non-domestic electricity/gas consumption (by building use only).
The ND-NEED Geographical meter dataset.
The ND-NEED Geographical meter dataset is the ND-NEED meter population dataset with
geographical area information added.
The ND-NEED meter population dataset contains all non-domestic meters and is used in the
main ND-NEED report to inform the weights used to scale up consumption of the matched
buildings in the ND-NEED dataset.
This dataset is used to produce geographical breakdowns of non-domestic electricity and gas
consumption.
Creating the ND-NEED Geographical Annex Dataset
The ND-NEED dataset contains all non-domestic buildings in England and Wales with
information about their building use and building size. The following steps were taken to
convert this to a geographical annex dataset.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
37

Adding geographical area information
The ND-NEED dataset contains postcode information for over 99.6% of the UK’s 1,755,000
non-domestic buildings. This enabled 1,749,000 buildings in the ND-NEED dataset to be
matched against the ONS NSPL (May 2024) by postcode. This is summarised in Figure 10.
During matching, 6,000 buildings failed to match because their postcodes were not in the
NSPL, leaving an ND-NEED Geographical dataset of 1,749,000 non-domestic buildings which
have associated geographical area codes (region, LA, PC). This is 99.6% of the main ND-
NEED dataset.
The region, LA and PC codes were matched against the codes in the ONS Names and Codes
lookup tables to provide names for the PC, LA and regions (last updated May 2024 for PC and
regions, and April 2024 for LA).
This year, we have changed our PC breakdowns in line with the new structure (under the 2023
boundary review). For more information, see Table 9 and House of Commons Research
Briefing on PC boundaries. This has led to an increase in the number of parliamentary
constituencies from 573 in 2023 to 575 this year.
Table 9: Change in parliamentary constituencies (PC’s) from 2023 to 2024
Region
Old (removed)
Parliamentary
Constituencies
New (added) Parliamentary
Constituencies
North East
Berwick-upon-Tweed

Blaydon

Blyth Valley
Gateshead

Jarrow

Middlesbrough

Newcastle upon Tyne Central

Newcastle upon Tyne East
North Tyneside

North West Durham
Sedgefield

Stockton South

Wansbeck

Washington and Sunderland
West
Blaydon and Consett
Blyth and Ashington
Cramlington and Killingworth
Gateshead Central and Whickham
Jarrow and Gateshead East
Middlesbrough and Thornaby East
Newcastle upon Tyne Central and
West
Newcastle upon Tyne East and
Wallsend
Newton Aycliffe and Spennymoor
North Northumberland
Stockton West
Washington and Gateshead South
North West
Blackley and Broughton
Blackpool North and
Cleveleys
Bolton South East
City of Chester
Copeland
Denton and Reddish
Eddisbury
Ellesmere Port and Neston
Garston and Halewood
Halton
Heywood and Middleton
Blackley and Middleton South

Blackpool North and Fleetwood

Bolton South and Walkden
Chester North and Neston
Chester South and Eddisbury

Ellesmere Port and Bromborough
Gorton and Denton
Heywood and Middleton North

Lancaster and Wyre
Leigh and Atherton
Liverpool Garston

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
38

Lancaster and Fleetwood
Leigh
Manchester, Gorton
Oldham West and Royton
Pendle
Penrith and The Border
Salford and Eccles
Weaver Vale
Wirral South
Workington
Worsley and Eccles South
Wyre and Preston North

Manchester Rusholme

Mid Cheshire
Oldham West, Chadderton and
Royton

Pendle and Clitheroe

Penrith and Solway
Runcorn and Helsby

Salford

Whitehaven and Workington

Widnes and Halewood

Worsley and Eccles

Yorkshire and The
Humber
Barnsley Central
Barnsley East
Batley and Spen
Brigg and Goole
Cleethorpes
Dewsbury

Don Valley
East Yorkshire
Elmet and Rothwell
Great Grimsby
Haltemprice and Howden
Hemsworth
Keighley
Kingston upon Hull North
Kingston upon Hull West and
Hessle
Leeds Central
Leeds West
Morley and Outwood
Normanton, Pontefract and
Castleford
Pudsey
Richmond (Yorks)
Selby and Ainsty
Wakefield
Wentworth and Dearne Corby
Barnsley North
Barnsley South
Bridlington and The Wolds
Brigg and Immingham
Dewsbury and Batley
Doncaster East and the Isle of
Axholme
Goole and Pocklington
Great Grimsby and Cleethorpes
Keighley and Ilkley
Kingston upon Hull North and
Cottingham
Kingston upon Hull West and
Haltemprice
Leeds Central and Headingley
Leeds South
Leeds South West and Morley
Leeds West and Pudsey
Normanton and Hemsworth
Ossett and Denby Dale
Pontefract, Castleford and
Knottingley
Rawmarsh and CSouth
Westonisbrough
Richmond and Northallerton
Selby
Spen Valley
Wakefield and Rothwell
Wetherby and Easingwold
East Midlands
Bosworth
Charnwood
Corby
Grantham and Stamford

Corby and East Northamptonshire
Grantham and Bourne
Harborough, Oadby and Wigston

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
39

Harborough
Nottingham North
Rutland and Melton
Sherwood
Wellingborough
Hinckley and Bosworth
Melton and Syston
Mid Leicestershire
Nottingham North and Kimberley
Rutland and Stamford
Sherwood Forest
Wellingborough and Rushden
West Midlands
Birmingham, Hall Green
Birmingham, Hodge Hill
Burton
Coventry North East
Dudley North
Dudley South
Halesowen and Rowley Regis
Ludlow
Meriden
Mid Worcestershire
North Warwickshire
Shrewsbury and Atcham
Solihull
South Staffordshire
Stone
Walsall North
Walsall South
Warley
West Bromwich East
West Bromwich West

Birmingham Hall Green and
Moseley
Birmingham Hodge Hill and Solihull
North
Burton and Uttoxeter
Coventry East
Droitwich and Evesham
Dudley
Halesowen
Kingswinford and South
Staffordshire
Meriden and Solihull East
North Warwickshire and Bedworth
Shrewsbury
Smethwick
Solihull West and Shirley
South Shropshire
Stone, Great Wyrley and Penkridge
Tipton and Wednesbury
Walsall and Bloxwich
West Bromwich

East of England
Broadland
Bury St Edmunds
Hitchin and Harpenden
Luton South
North East Bedfordshire
Rochford and Southend East
Saffron Walden
South East Cambridgeshire
South West Bedfordshire
Southend West
Waveney

Broadland and Fakenham
Bury St Edmunds and Stowmarket
Dunstable and Leighton Buzzard
Ely and East Cambridgeshire
Harpenden and Berkhamsted
Hitchin
Lowestoft
Luton South and South
Bedfordshire
North Bedfordshire
North West Essex
Southend East and Rochford
Southend West and Leigh
St Neots and Mid Cambridgeshire
Waveney Valley

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
40

London
Beckenham
Bethnal Green and Bow
Brent Central
Brent North
Bromley and Chislehurst
Camberwell and Peckham
Croydon Central
Croydon North
Edmonton
Eltham
Enfield, Southgate
Hammersmith
Hampstead and Kilburn
Hornsey and Wood Green
Kensington
Lewisham West and Penge
Lewisham, Deptford
Streatham
Vauxhall
West Ham
Westminster North
Beckenham and Penge
Bethnal Green and Stepney
Brent East
Brent West
Bromley and Biggin Hill
Clapham and Brixton Hill
Croydon East
Croydon West
Edmonton and Winchmore Hill
Eltham and Chislehurst
Hammersmith and Chiswick
Hampstead and Highgate
Hornsey and Friern Barnet
Kensington and Bayswater
Lewisham North
Lewisham West and East Dulwich
Peckham
Queen's Park and Maida Vale
Southgate and Wood Green
Stratford and Bow
Streatham and Croydon North
Vauxhall and Camberwell Green
West Ham and Beckton
South East
Brighton, Kemptown
Brighton, Pavilion
Buckingham
Dover
Fareham
Henley
Hove
Isle of Wight
Maidstone and The Weald
Meon Valley
Milton Keynes South
Mole Valley
North Thanet
Reading East
Reading West
South Thanet
South West Surrey
Tonbridge and Malling
Wantage
Wealden
Bicester and Woodstock

Brighton Kemptown and
Peacehaven
Brighton Pavilion

Buckingham and Bletchley
Didcot and Wantage

Dorking and Horley
Dover and Deal

Earley and Woodley
East Grinstead and Uckfield

East Thanet
Fareham and Waterlooville
Farnham and Bordon

Godalming and Ash
Hamble Valley

Henley and Thame
Herne Bay and Sandwich
Hove and Portslade
Isle of Wight East

Isle of Wight West
Maidstone and Malling

Mid Buckinghamshire

Milton Keynes Central

Reading Central

Reading West and Mid Berkshire

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
41

Sussex Weald

Tonbridge

Weald of Kent

South West
Bridgwater and West
Somerset
Bristol West
Devizes
East Devon
Kingswood
North East Somerset
North Swindon
North Wiltshire
Somerton and Frome
South Swindon
Taunton Deane
The Cotswolds
Tiverton and Honiton
Torridge and West Devon
Totnes
Wells
Bridgwater
Bristol Central
Bristol North East
East Wiltshire
Exmouth and Exeter East
Frome and East Somerset
Glastonbury and Somerton
Honiton and Sidmouth
Melksham and Devizes
North Cotswolds
North East Somerset and Hanham
South Cotswolds
South Devon
Swindon North
Swindon South
Taunton and Wellington
Tiverton and Minehead
Torridge and Tavistock
Wells and Mendip Hills
Wales
Aberavon
Aberconwy
Arfon
Blaenau Gwent
Brecon and Radnorshire
Cardiff Central
Carmarthen East and Dinefwr
Carmarthen West and South
Pembrokeshire
Ceredigion
Clwyd South
Clwyd West
Cynon Valley
Delyn
Islwyn
Merthyr Tydfil and Rhymney
Monmouth
Montgomeryshire
Neath
Newport West
Ogmore
Preseli Pembrokeshire
Rhondda
Swansea East
Vale of Clwyd

Aberafan Maesteg
Bangor Aberconwy
Blaenau Gwent and Rhymney
Brecon, Radnor and Cwm Tawe
Caerfyrddin
Cardiff East
Ceredigion Preseli
Clwyd East
Clwyd North
Merthyr Tydfil and Aberdare
Mid and South Pembrokeshire
Monmouthshire
Montgomeryshire and Glyndwr
Neath and Swansea East
Newport West and Islwyn
Rhondda and Ogmore

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
42

Figure 10: Production of the ND-NEED geographical annex dataset

ND-NEED
2024 data
From DESNZ 1,755,000
buildings
ND-NEED
Geographical
Annex data
1,749,000 buildings

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
43

Rural/urban flag
The NSPL also contains information on whether a building is in a rural or urban location. This
is used to add a flag to all non-domestic buildings in a rural rather than urban postcode,
according to the ONS definition.
Off-gas grid flag
To determine whether a building was in an area where it could not reasonably connect to the
gas National Transmission System – Great Britain’s interconnected gas supply network (‘the
gas grid’) - the Xoserve off-gas grid postcode dataset is used, as outlined below and
summarised in Figure 11.
The Xoserve dataset contains all postcodes in the Great Britain that have no connections to
the gas grid in 2024. This is then matched against the ND-NEED data by postcode. Where a
building is in a postcode identified by the Xoserve dataset to have no buildings, domestic or
non-domestic, with a connection to the gas distribution network, it is initially flagged as ‘off-gas
grid’. A total of 296,000 non-domestic buildings were flagged as off-gas grid.
The buildings flagged as off-gas grid were checked to see if they had a gas meter reading in
2022. There were 3,700 buildings marked as in a postcode with no buildings connected to the
gas grid in 2024 but had a gas meter reading in 2022. The off-gas grid flag was removed from
these buildings, leaving 292,000 off-gas grid buildings.
However, an unknown number of buildings are missing gas consumption data as described in
the ND-NEED matched sample method section. It is therefore likely that more than 2,500
buildings marked as in an off-gas grid postcode consumed gas in 2022. Assuming that the
address matching success rate for gas meters is similar to electricity data (about 51%), this
suggests that the true number of buildings marked as in on off-gas grid postcodes, but
consuming gas, to be 4,000-5,000. This would suggest that 292,000 off-gas grid buildings is a
small overestimate.
All buildings not matched to an off-gas grid postcode, with no postcode or with a gas meter
reading of greater than 0 kWh are considered to be ‘on-gas grid’. This means that buildings
that have chosen not to be connected to the gas grid are considered to be ‘on-gas grid’.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
44

Figure 11: Merging ND-NEED with Xoserve Off-Gas Grid data

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
45

Comparison with domestic off-gas grid method
The method used for estimating the number of domestic properties not connected to the gas
grid differs slightly from that used here. It deducts the number of gas meters in a region from
the number of properties. This method is less suitable for non-domestic buildings due to:
1. Deducting the number of gas meters in a region from the number of non-domestic buildings
would overestimate the number of off-gas grid buildings. This is because low consuming
non-domestic buildings are identified by address-matching; if a gas meter matches to an
ND-NEED non-domestic building address, it is considered to be non-domestic. However,
due to limitations of the address-matching algorithm, not all low consuming non-domestic
meters are detected in ND-NEED. The number of gas meters is therefore an
underestimate, causing the difference between the number of buildings and the number of
gas meters to be too large.
2. The domestic approach would also capture buildings that lay in on-grid areas but have
chosen not to connect.
Weighted Matched Sample Consumption Data
The ND-NEED Geographical Annex dataset contains 1,749,000 non-domestic buildings all of
which have geographic area information, information about building use and building size
(though 18% of buildings are missing building size information as described in the ‘missing
floor area’ section) and rural/urban and off-gas grid flags.
A sample of around 51% of the buildings in this dataset also have electricity consumption
information, and around 20% also have gas consumption information. This sample is scaled up
with weights calculated based on a building’s use and size, to remove bias in the matching
process. This weighting does not take into consideration geographical biases in the matching
process. This is described in the ‘missing consumption data’ section.
Information about the non-domestic building stock and energy use in each region, LA and PC
could then be obtained by summarising this dataset. This could optionally be split or filtered by
building use or building size.
This data was calculated based on the methods described in Table 10.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
46

Table 10: Methods for summarising non-domestic building data by geography

Variable
Method
Total Number
Count the number of rows of data.
Floor Area, Weighted
Electricity or Gas
Consumption
Sum all values of non-domestic buildings’ floor area or weighted
electricity and gas consumption data, including zero values where
the data is missing from ND-NEED.
Sample size of
variable
Count the number of non-domestic buildings in the ND-NEED
dataset with a non-zero and non-NA value for: Floor area; Electricity
and Gas Consumption.
Share of variable

Divide variable for each geography by the England and Wales total
and multiply by 100. The England and Wales total is taken as the
matched ND-NEED Geographical Annex total, ignoring buildings that
were not matched to a geography, to allow for direct comparisons
between geographies. This was done for the following variables:
Number of Buildings; Floor area; Energy, Electricity and Gas
Consumption.

Disclosure: where there are fewer than five buildings in a consumption data point, or a building
represents over 90% of the total, consumption data will be removed. Where there is only one
geographical area (for example, region) that meets this condition, to avoid disclosure by
residual, the next closest data point laying within the same upper level area (for example,
country) is also supressed.
Missing floor area data in ND-NEED Geographical Annex
dataset
In ND-NEED 2024 dataset, 319,000 (18%) of buildings do not have floor area data. This is
because:
1. This information is missing from the VOA data that ND-NEED is based on (12%).

2. The floor area information is removed from the ND-NEED dataset because the data is
believed to be unreliable - around 1% of the total ND-NEED floor area.
a. This is done for all buildings with a floor area of less than 15m2 (17%). This
removes around 1,466,000m2 of floor area.
b. This is done for buildings in subsectors not used to inform the VOA’s building
rating (9%). This removes around 4,000,000m2 of floor area. 20

20 For a full list of subsectors that have floor area removed for all ND-NEED buildings, please see Annex D in the
methodology note of ND-NEED 2024.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
47

This means that 319,000 (18%) of buildings in the ND-NEED Geographical Annex are also
missing floor area data. The remaining buildings failed to match into the Geographical Annex
due to missing or incorrect postcodes.
The exact amount of floor area missing from ND-NEED is not known and therefore cannot be
accounted for. All floor area data presented is therefore believed to be an underestimate.
Table 11 shows the proportion of non-domestic buildings that are missing floor area data in
each region, for the largest ND-NEED building uses. The ‘Totals’ column shows that there is
not a huge difference between the number of non-domestic buildings in each region that are
missing floor area data, so comparisons between regions can reasonably be made.
However, this is not the case for building uses. From Table 11, it can be seen that the
proportion of buildings missing floor area information in the ND-NEED Geographical Annex
dataset varies substantially between building uses. Floor area data has therefore only been
presented for building uses where less than 20% of buildings are missing floor area data. For
all of these building uses, the principal reason floor area data is missing is because it was
removed from buildings with a floor area of <15m2. This suggests that the absence of this floor
area data doesn’t have a large effect on the total floor area presented.
These building uses missing less than 20% of floor area data were: Factories; Offices; Shops;
and Warehouses. The following remaining building uses were combined to create an ‘All other
building uses’ category: Arts, Community and Leisure; Education; Emergency Services;
Health; Hospitality; and Other. Around 54% of buildings in the ‘All other building uses’ category
are missing floor area data.
Due to variations, floor area comparisons between building uses must be done with caution.
A full breakdown of total floor area and proportion of buildings missing floor area, by region and
building use, is available in Table 2 in the accompanying data tables.
Floor area data is also presented at the LA and PC level for the four building uses where more
than 80% of buildings have floor area present in the accompanying data tables (Table 2 and
9).

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
48

Table 11: Percentage of non-domestic buildings missing floor area data

Region
Factories
Offices Shops Warehouses
All other
building
uses
All building
uses
England
2%
14%
3%
6%
53%
18%
North East
1%
12%
2%
9%
55%
19%
North West
2%
13%
2%
5%
53%
17%
Yorkshire and
The Humber
3%
13%
3%
8%
55%
19%
East
Midlands
1%
12%
3%
4%
51%
16%
West
Midlands
2%
12%
3%
3%
49%
14%
East
1%
13%
3%
6%
53%
19%
London
9%
17%
4%
7%
35%
14%
South East
2%
14%
3%
6%
50%
17%
South West
2%
13%
3%
7%
67%
26%
Wales
1%
14%
3%
11%
62%
24%
England &
Wales
2%
14%
3%
6%
54%
18%
Weighting the ND-NEED matched sample consumption
dataset
ND-NEED matches VOA building stock data to meter level energy consumption data held by
DESNZ using an address matching algorithm. However, this matching process is only able to
match 2022 electricity consumption meter data to 859,000 buildings out of the 1,755,000
buildings in the ND-NEED dataset. Of these 859,000 buildings, 349,000 were also successfully
matched to 2022 gas consumption meter data.
This means that consumption data for 896,000 non-domestic buildings is not available. In ND-
NEED 2024, weights are used to scale up the ND-NEED sample consumption to the ND-
NEED population level.
The ND-NEED weights take into account differences in the address matching rate between
building use and building size. This is done by stratifying the building population and the
matched sample based on a building’s use and size, creating a matrix. For each cell, the
population count is divided by the matched sample count. This creates a weight for each
building.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
49

This weighting for each building is then adjusted for electricity and gas consumption. The
number of electricity or gas meters in the matched sample multiplied by their building weight is
compared with the number of meters in the ND-NEED meter level population, split by
consumption band and meter profile. The difference gives an electricity and gas weighting for
each building in the matched sample. These weights allow the matched sample to represent
the non-domestic building population in England and Wales.
However, this weighting process does not account for geography. Therefore, the ability to
compare the data between geographical areas is dependent on the proportion of buildings that
are missing consumption data being consistent between these areas.
Table 12 shows that this is broadly true for electricity consumption at the regional level with the
number of non-domestic buildings missing 2022 electricity consumption data broadly similar
(ranging from 46% to 52%) across the regions.
Note, it is assumed that all non-domestic buildings use electricity from the Great Britain
National Grid, and therefore should have electricity consumption data in ND-NEED. Any
building that does not have electricity consumption information is therefore considered to
be missing this information.
Table 12: Number of non-domestic buildings with 2022 electricity consumption data in
ND-NEED 2024

Region
Number of
buildings
Number of buildings
with electricity data
Proportion of
buildings with
electricity data
England
1,638,000
807,000
49%
North East
75,000
39,000
52%
North West
223,000
108,000
49%
Yorkshire and The
Humber
181,000
88,000
49%
East Midlands
138,000
69,000
50%
West Midlands
166,000
81,000
49%
East
175,000
86,000
49%
London
241,000
114,000
47%
South East
243,000
121,000
50%
South West
197,000
101,000
51%
Wales
110,000
50,000
46%
Total
1,749,000
857,000
49%

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
50

Table 13 shows the number of non-domestic buildings with 2022 gas meter readings in the
ND-NEED matched sample, split by region. It shows that the proportion of all non-domestic
buildings that have gas meter data is similar (18% to 22%) across the regions. This suggests
that regional comparisons are reasonable.
Note, as not all non-domestic buildings are thought to have a gas connection the proportion
of non-domestic buildings missing gas consumption information cannot be calculated. To
assess the validity of comparing gas consumption data between regions we therefore rely
on the assumption that the proportion of buildings with gas connections is similar between
regions.

Table 13: Sample size of non-domestic buildings with 2022 gas consumption data in
unscaled ND-NEED matched sample

This data is also available split by building uses in Tables 7A and 7B of the accompanying data
tables.
However, this data cannot be presented at PC and LA level. The extra granularity means that
there are large differences in the proportion of buildings missing consumption data between
geographies. As the weighting process does not take into account these differences between
geography, the weighted matched sample does not represent the population at these levels.

Region
Number of
buildings
Number of buildings
with gas data
Proportion of
buildings with gas
data
England
1,638,000
328,000
20%
North East
75,000
15,000
20%
North West
223,000
49,000
22%
Yorkshire and The
Humber
181,000
38,000
21%
East Midlands
138,000
28,000
21%
West Midlands
166,000
33,000
20%
East
175,000
31,000
18%
London
241,000
50,000
21%
South East
243,000
48,000
20%
South West
197,000
36,000
18%
Wales
110,000
20,000
18%
Total
1,749,000
348,000
20%

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
51

Creating the Geographical ND-NEED meter dataset
This method uses meter-level data from the 2,332,000 electricity and 621,000 gas meters in
non-domestic buildings in England and Wales (the ND-NEED meter population).
The electricity and gas meters are matched to the ONS NSPL (May 2024) by postcode to
obtain their associated geographical area codes (region, LA, PC). Due to missing postcodes,
12,800 electricity meters and 7,100 gas meters could not be matched. A further 40,900
electricity and 3,700 gas meters with postcodes failed to match to an active postcode in the
NSPL.
The region, LA and PC codes were then matched against the codes in the ONS Names and
Codes lookup tables to provide names for the PC, LA and regions (last updated July 2024 for
PC and regions, and April 2024 for LA). This created the Geographical ND-NEED meter
dataset which contains 2,332,000 electricity meters and 621,000 gas meters, with information
about their geographical location. This is summarised in Figure 12.
Information about the energy use in each region, LA and PC could then be obtained by
summarising this dataset.
The key advantage of this method is that all electricity and gas consumption from all non-
domestic buildings is captured. This allows meaningful comparisons of consumption between
all geographical area.
However, as the meters have not been matched to the corresponding non-domestic building
the data cannot be broken down by building use or building size or provide any information on
the distribution of the non-domestic building stock.
In keeping with the method use for the Subnational consumption data, which provides the
basis for this dataset, data for any geographical areas that contain less than five meters, or
where two meters represent over 90% of the total, will be removed. Where there is only one
geographical area (for example, parliamentary constituency) that meets this condition, to avoid
disclosure by residual, the next closest data point - laying within the same upper level area (for
example, region) - to also meeting the condition is also suppressed. The total for the upper
level area remains unchanged. In this year’s data, no areas have been suppressed.
Note, the ND-NEED meter population dataset contains all non-domestic electricity and
gas meters in England and Wales. This means it includes meters that are located in ‘non-
buildings’ such as car parks.

Consumption from these ‘non-buildings’ is excluded from the ND-NEED 2024
consumption totals. However, as the meters in the ND-NEED meter population dataset
have not been associated with their corresponding building, the meters in these ‘non-
buildings cannot be identified for removal.

The inclusion of these ‘non-buildings’ will inflate the consumption of the ND-NEED meter
population by 10-15%.

More information on non-buildings can be found on page 23 of the ND-NEED 2024
report.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
52

Figure 12: Production of the Geographical ND-NEED meter dataset

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
53

Comparing the measures of non-domestic consumption
Two methods of presenting non-domestic electricity and gas consumption have been
presented: the weighted version of the matched ND-NEED sample; and the ND-NEED
electricity and gas meter population used to create the sample. A third way is published in the
Subnational electricity and gas consumption statistics. Table 14 summarises the key
differences between these measures.
Table 14: Comparison of measures of non-domestic consumption
Comparison
ND-NEED
buildings:
weighted
matched
sample
ND-NEED meter
population
Subnational
consumption
statistics: Non-
domestic
consumers
Non-domestic coverage
All non-domestic
buildings that
pay business
rates, excluding
‘non-buildings’
All electricity meters
of profile 3+ and gas
meters with annual
consumption of >73
MWh, plus smaller
non-domestic building
consumers falling
outside these bands
All electricity meters
of profile class 3 to 8
and half-hourly
meters + and gas
meters with annual
consumption of >73
MWh
Geographical coverage
England and
Wales
England and Wales
Great Britain
England &
Wales 2022
consumption
Electricity
(GWh)
122,452
143,011
142,384
Gas (GWh)
156,064
160,853
153,631
England &
Wales 2022
meters
Electricity
n/a
2,331,729
2,239,837
Gas
n/a
620,636
224,467
Geography split
Regions
LA and PC
LA (and below)
Non-Domestic building
use split
ND-NEED
categories
No
No
Includes non-domestic
“non-buildings”?
No
Yes
Yes
Includes smaller21 non-
domestic building
consumers?
Yes
Yes
No

21 Non-domestic buildings with electricity meters in profiles 1 or 2, and/or gas meters with consumption of less
than 73.2MWh. These would be considered domestic in Subnational energy consumption data.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
54

Validating the regional breakdown of ND-NEED weighted matched sample
consumption data against ND-NEED meter level consumption data
The assumption that the ND-NEED matched sample is not regionally biased can be checked
by comparing the ND-NEED weighted matched sample against the ND-NEED meter level
population.
The ND-NEED meter level dataset includes consumption from 102,000 establishments that
ND-NEED considers not to be buildings (‘non-buildings’), and therefore are excluded from the
ND-NEED 2024 dataset. The 21 TWh electricity and 5 TWh gas consumption difference
between the meter level data and the weighted sample is therefore likely to be due to
consumption from the ‘non-buildings’.
However, assuming that the proportion of consumption from non-buildings is evenly distributed
between the regions, a direct comparison, shown in Table 15, can be made between the
proportion of consumption between the meter level data and the weighted matched sample.
Table 15: Comparison of proportion of non-domestic building consumption between
meter level data and weighted matched sample.

Region
Share of electricity
consumption (%)

Share of gas consumption
(%)

Meter
level
Weighted
Matched
Sample
Meter level
minus
sample
difference
(Percentage
Point)

Meter
level
Weighted
Matched
Sample
Meter level
minus
sample
difference
(Percentage
Point)
England
93.7%
94.0%
-0.3%

94.1%
92.6%
+1.5%
North East
4.6%
5.4%
-0.8%

5.3%
4.5%
+0.8%
North West
12.2%
15.1%
-2.9%

15.8%
17.0%
-1.2%
Yorkshire
and The
Humber
9.5%
10.5%
-1.0%

12.4%
12.2%
+0.2%
East
Midlands
8.6%
8.9%
-0.3%

9.9%

10.5%
-0.6%
West
Midlands
9.3%
9.1%
+0.2%

10.1%
7.9%
+2.2%
East
10.0%
9.5%
+0.5%

9.5%
14.5%
-5.0%
London
16.4%
14.5%
+1.9%

12.9%
10.0%
+2.9%
South East
14.5%
13.1%
+1.4%

11.1%
9.5%
+1.6%
South West
8.6%
7.8%
+0.8%

7.3%
6.4%
+0.9%
Wales
6.3%
6.0%
+0.3%

5.9%
7.4%
-1.5%

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
55

This shows that the proportion of electricity and gas consumed by non-domestic buildings in
each region is quite strongly correlated with the meter level consumption data and the
weighted matched sample data (92% correlation for electricity and 80% for gas).
For example, according to ND-NEED meter level data, electricity consumption in the North
East makes up 4.6% of the total for England and Wales and 5.4% of the total electricity
consumption in the ND-NEED matched sample, a difference of 0.8%. For both electricity and
gas consumption, there is less than 2.9 percentage points difference in the proportions
between meter level data and weighted matched sample data for most regions, with the
exception of gas in the East at 5.0 percentage points.
Consumption data using both meter level data and weighted matched sample data is available
in the accompanying tables at regional level.
The strong correlation at regional level between the meter population and the weighted
matched sample is not seen once the consumption is broken down into smaller geographical
areas. The extra granularity in the breakdown of the data makes any geographical bias in the
weighted matched sample more visible. This causes the correlation between meter level
consumption and the weighted matched sample consumption at PC level to drop to 72% for
electricity and 61% for gas. Furthermore, in 12% of PCs the weighted matched sample
consumption value is more than 50% larger or smaller than the meter level data. This data is
therefore not presented in the data tables.
Creating Geographical ND-NEED maps
The ND-NEED Geographical Annex dataset was also matched to ONS boundary shapefiles of
each PC (updated July 2024) or LA (updated May 2024) by PC code or LA code respectively.
This is summarised in Figure 13
Region boundaries were calculated by grouping PCs together by region and merging
boundaries to form regional boundaries. The regional boundaries could then be matched to the
regional ND-NEED data by region name.
Heatmaps could then be produced, by filling each PC’s, LA’s or region’s boundaries with a
colour based on the concentration of a variable in each geography. This was done using the R
Leaflet package. As it was common for most areas to have values closer to the median than to
the outliers, a base 10 log scale was used to determine the colour scales, allowing the
heatmaps to show differentiation between areas more clearly.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
56

Figure 13: Production of the Geographical ND-NEED heatmaps

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
57

5.Further information
Accompanying tables
The following tables are available on the department’s statistics webpage for ND-NEED:

At regional level:
• Table 1 shows the number of ND-NEED non-domestic buildings, by building use*.

• Table 2 shows the floor area of ND-NEED non-domestic buildings, by building use*.

• Table 3A shows the number of ND-NEED non-domestic off-gas grid buildings, by rural
and urban.

• Table 3B shows the number of off-gas grid ND-NEED non-domestic buildings, by
building use.

• Table 4A shows the electricity consumption from ND-NEED meters*.

• Table 4B shows the gas consumption from ND-NEED meters*.

• Table 5 shows the ND-NEED number of non-domestic buildings larger than 1,000m2, by
building use*.

• Table 6 shows the ND-NEED number of non-domestic buildings smaller than or equal to
1,000m2, by building use*.

• Table 7A shows the scaled ND-NEED non-domestic electricity consumption, by building
use*.

• Table 7B shows the scaled ND-NEED non-domestic gas consumption, by building use*.

At local authority level:
• Table 1 shows the number of ND-NEED non-domestic buildings, by building use*.

• Table 2 shows the floor area of ND-NEED non-domestic buildings, by building use*.

• Table 3A shows the number of ND-NEED non-domestic off-gas grid buildings, by rural
and urban.

• Table 4A shows the electricity consumption from ND-NEED meter population, over
time*

• Table 4B shows the gas consumption from ND-NEED meter population, over time*

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
58

At parliamentary constituency level:
• Table 8 shows the number of ND-NEED non-domestic buildings, by building use. *

• Table 9 shows the floor area of ND-NEED non-domestic buildings, by building use.

• Table 10 shows the number of off-gas grid ND-NEED non-domestic buildings, by rural
and urban*.

• Table 11A shows the electricity consumption from ND-NEED meter population, over
time.

• Table 11B shows the gas consumption from ND-NEED meter population, over time.

Future updates to these statistics
The next release of these statistics is intended to be following the main ND-NEED publication,
the next update of which is planned for the summer of 2025.
The following updates will also be considered for future editions:
• With regards to the ND-NEED matched sample consumption data, an improved
weighting method will be considered. This may include adapting the weighting
methodology to take into account geographical biases in the ND-NEED matched
sample. This would allow building use level consumption data to be presented at a LA
and PC level.

• Additional analysis and weighting will be considered to improve the reliability of floor
area data. This would allow floor area data to be presented for more building uses.

• The publication of geographical breakdowns of ND-NEED consumption and building
stock data for additional years, prior to those presented here, will be considered.
Related statistics
The Non-Domestic National Energy Efficiency Data-Framework 2024
Previous release of the ND-NEED statistics, August 2024.
Non-domestic National Energy Efficiency Data-Framework: energy statistics 2006-2012
Previous release of the ND-NEED statistics, March 2015.
The non-domestic National Energy Efficiency Data-Framework (ND-NEED)
Overview of the concept of ND-NEED, known issues, plans for improvement, preliminary results
and the proposed weighting methodology, May 2014.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
59

National Energy Efficiency Data-Framework (NEED)
Summary statistics of domestic energy consumption 2005-2022, June 2024.

Non-Domestic National Energy Efficiency Data-Framework 2024 Geographical Annex
60

Revisions policy
The DESNZ statistical revisions policy sets out the revisions policy for these statistics, which
has been developed in accordance with the UK Statistics Authority Code of Practice for
Statistics.
Code of Practice for Statistics compliance
These official statistics comply with the standards of trustworthiness, quality and value in the Code
of Practice for Statistics.

These data support geographical analysis of non-domestic buildings electricity and gas
consumption, as well as off-gas grid analysis. Data and processing undergo careful quality
assurance, and users are kept informed about significant changes. Details of key data
limitations can be found within the relevant coverage and data limitation sections of the method
section, as well as the main ND-NEED 2024 methodology note.

Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the
standards of trustworthiness, quality and value in the Code of Practice for Statistics that all
producers of official statistics should adhere to. You are welcome to contact us directly
(xxx@xxx.xx) with any comments about how we meet these
standards. Alternatively, you can contact OSR by emailing xxx@xxx.xx or via
the OSR website.
User engagement
Users are encouraged to provide comments and feedback on how these statistics are used
and how well they meet user needs. Comments on any issues relating to this statistical release
are welcomed and should be sent to: xxx@xxx.xx.
The DESNZ statement on statistical public engagement and data standards sets out the
department’s commitments on public engagement and data standards as outlined by the Code
of Practice for Statistics.
Contact
• Responsible statistician: James Hemingway
• Email: xxx@xxx.xx
• Media enquiries: xx-xxxx-xxxx
• Statistical enquiries: xx-xxxx-xxxx

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