Frequently Asked Questions

All three, and the tools are arranged so that each can stop at the level of detail they need. The audience we design for first is councillors and local authority officers developing decarbonisation policy, because they hold many of the levers and are rarely given evidence at neighbourhood scale. Community groups use the tools to make a local case, and researchers use the underlying data directly. Every chart carries a plain-language Overview, a Policy note on why the measure matters for decision making, and a Methods note on where the numbers come from.

The most common uses we see are targeting: identifying which neighbourhoods should be first in line for an area-based retrofit scheme, evidencing a bus service improvement plan with twenty years of frequency data, and testing whether a proposed development site is somewhere people could live without a car. The tools are evidence for those decisions, not a substitute for local knowledge or survey work. We would rather you treated a striking result as a question to investigate than as a finding to act on directly.

Yes. Please cite Morgan (2026) and link to www.carbon.place. Note that some basemaps carry third-party copyright, so check the manual before reproducing a screenshot that uses the satellite or historical basemaps. The data page sets out the licence conditions in full.

Carbon & Place is funded by UK Research and Innovation, through the Engineering and Physical Sciences Research Council and the Economic and Social Research Council, via the Energy Demand Research Centre (grant EP/Y010078/1). It forms part of the EDRC Place theme. The original Place-Based Carbon Calculator was funded through the Centre for Research into Energy Demand Solutions (grant EP/R035288/1), which closed in 2023.

Yes, though not on a fixed schedule. Each dataset is rebuilt when its source publishes an update, so the most recent year differs between charts and is stated on each one. Funding for the current phase runs to 2028. We cannot promise indefinite maintenance, which is one reason the analysis code and most of the outputs are published openly: if this project ends, the work can be continued by others.

Great Britain, and not evenly. The short version: England has everything; Wales has everything except most planning designations; Scotland has the carbon footprints, energy, transport and buildings data but not accessibility, property prices, dwelling type and age, or planning designations; and Northern Ireland is not covered at all. The table sets out where each dataset stops.

Where a dataset stops short, the chart or layer says so rather than showing a blank, and every chart's Methods tab names its source and its coverage.

Because the data is published separately there, on different terms, and in three cases we have not been able to include it.

Property prices. Sales in England and Wales come from HM Land Registry Price Paid Data, which is open. Scottish sales are published by Registers of Scotland under different licence terms, so we cannot republish them here.

Accessibility and proximity. This analysis counts how many services of each type are reachable from every neighbourhood. It is built on the Ordnance Survey Points of Interest dataset, and our licence for it does not extend to Scotland.

Dwelling type and build period. The Valuation Office Agency publishes counts of homes by built form and age for England and Wales. There is no Scottish equivalent, so those two charts are blank for a Scottish neighbourhood. Council tax band counts are available for Scotland and are shown.

Population after 2022. Scotland's census was held in 2022 rather than 2021, and National Records of Scotland has not yet published small-area estimates beyond it, so Scottish population series stop at 2022 while England and Wales run to 2024.

Everything else, including the carbon footprints themselves, energy use, EPCs, public transport and vehicles, covers Scotland in full. Scottish neighbourhoods are 2022 Data Zones rather than LSOAs, which are the equivalent unit and a similar size.

Not at present, and we would like to. Almost every dataset behind Carbon & Place is published for Great Britain only, by bodies whose remit stops at the Irish Sea: the Department for Energy Security and Net Zero publishes sub-national energy statistics for Great Britain, the Driver and Vehicle Licensing Agency's records exclude Northern Ireland, and the census, small-area geography and area classifications are run separately by the Northern Ireland Statistics and Research Agency.

Covering Northern Ireland would mean rebuilding most of the pipeline against a different set of sources rather than extending the existing one, which we have not had the funding to do. Entering a Northern Irish postcode tells you so rather than failing silently. For Northern Ireland statistics, NISRA is the place to start.

Because planning is devolved, and the designations it maps are created and published by different agencies in each country. Most layers in that tool (flood zones, green belt, conservation areas, listed buildings, national parks, nature reserves, registered parks and gardens, road and rail noise, historic landfill) come from English bodies and cover England only. Some layers do go wider: Sites of Special Scientific Interest cover Great Britain; Ramsar sites, Special Areas of Conservation and Special Protection Areas are international designations covering the UK; National Landscapes and ancient woodland cover England and Wales.

Each layer's help button states its coverage. The other four tools are not affected: they cover Great Britain except where the table above says otherwise.

From three kinds of source, and the difference between them matters when you read the results. Domestic gas and electricity are measured, from meter readings published by the Department for Energy Security and Net Zero. Car and van emissions are derived, by combining vehicle registrations with mileages from MOT odometer readings. Everything else, including flights, food, goods, and services, is modelled, by matching a synthetic population built from census data to spending records in the Living Costs and Food Survey. The measured components are the most reliable and the modelled ones the least. The manual explains each in detail, and the analysis pipeline is published in full.

It depends on the tool. Carbon footprints run from 2010. Public transport frequency in the Transport and Accessibility Explorer runs from 2004, with gaps in 2012 and 2013 where no timetable archive survives. Energy consumption in the Retrofit Explorer runs from 2010. The end year varies by dataset and is shown on each chart.

Mostly the 2021 Census for England and Wales and the 2022 Census for Scotland. All neighbourhood boundaries are the 2021 LSOAs and 2022 Data Zones, with earlier years mapped onto them. Some contextual datasets lag: the ONS area classification used for the "similar areas" comparison is still the 2011 version, which is a known weakness we intend to update.

They are different datasets built for different purposes, and they will not agree. The official statistics are territorial: they count emissions physically released within an area, including from industry and from traffic passing through. Carbon & Place is consumption-based: it counts the emissions caused by the people who live in an area, wherever in the world those emissions occurred, and excludes traffic that merely passes through. Neither is more correct; they answer different questions. Use the official statistics for territorial reporting obligations, and this tool for understanding what local residents' consumption implies.

As part of residents' consumption, rather than as emissions at the site. The emissions of a car factory are attributed to the neighbourhoods where the cars are eventually bought, not to the neighbourhood containing the factory. This means a town with heavy industry does not carry those emissions in this tool, and it also means the tool cannot answer questions about industrial decarbonisation at a site. For that, use the territorial statistics.

The scopes framework describes the emissions of organisations, so it does not map neatly onto a place-based footprint. The closest analogy is to imagine asking every resident of a neighbourhood to complete a detailed personal carbon footprint and then averaging the results: that includes what a company would call scope 1 (their gas boiler), scope 2 (their electricity), and much of scope 3 (everything they buy). It is not a substitute for an organisational inventory.

It is a real limitation, and worth stating plainly rather than defending. The categories with the best data, principally metered gas and electricity, are not the largest categories, and the largest categories rest on survey-based modelling. Three things follow. First, we present grades in wide bands rather than precise values, so that attention falls on large differences rather than on differences the data cannot support. Second, comparisons between places and trends over time are far more trustworthy than any single value for a single area in a single year. Third, each Methods tab states the specific weakness of that category, so you can judge how much weight to put on it. If you need a defensible number for one small area, the metered energy figures are the ones to use.

On residents. Flights are allocated using the synthetic population and research on how flying varies with income and demographics, so living near an airport does not raise a neighbourhood's figure. Our estimates are higher than the Department for Transport's official figures for three reasons: the DfT counts only departing flights, whereas we count flights taken by British residents in either direction; the DfT counts only commercial aviation, whereas we include private flights; and the DfT counts carbon dioxide alone, whereas we use the UK government conversion factors including their radiative forcing uplift for emissions released at altitude, which roughly doubles the figure. Note that this is still conservative: Lee et al. (2021) and a CREDS briefing put aviation's full warming effect at around three times its CO₂ alone, so a case can be made that our figures are too low rather than too high.

Commercial segmentation products such as Mosaic and Acorn cannot be included in an open-source tool under their licences. Open datasets such as the Index of Multiple Deprivation could be added, but they are already well mapped elsewhere, so we have concentrated on producing data that does not otherwise exist at this scale. You can download our data and join it to any of these yourself.

No. Carbon & Place measures emissions caused by residents and does not net off carbon stored in the land within a neighbourhood. For most urban neighbourhoods the quantities involved are small relative to the footprint, but that is not true everywhere: a rural area containing peatland or extensive woodland could store or release amounts that matter. Sequestration is also genuinely hard to estimate at this scale, and attributing land carbon to the residents of the LSOA that happens to contain it raises questions we have not resolved. Treat its absence as a gap in the tool rather than as a judgement that it does not matter.

Yes. Every neighbourhood report card compares the area with its local authority, with the national average for Great Britain, and with neighbourhoods of the same ONS area classification. The last of these is usually the most informative, because it compares like with like rather than setting a rural village against the national average. For larger areas, the Reports section provides ready-made summaries for local authorities, wards, parishes, and Westminster constituencies.

By the Office for National Statistics area classification, which groups neighbourhoods with similar social, economic, and demographic characteristics. Carbon & Place currently uses the classification derived from the 2011 Census; an updated version based on 2021 data exists and we intend to move to it.

Not at present. You can turn on the administrative boundary layers to see where your area begins and ends, and the Reports section produces a summary for a single authority. Filtering the map to one authority is a reasonable request that we have not yet implemented.

Not within the tool, but you can download the neighbourhood data and aggregate it yourself. One statistical warning: averaging the per-person values of a set of neighbourhoods is not the same as the per-person value for the combined population, because neighbourhoods differ in size. Weight by population to avoid that bias.

It helps with a particular kind of question: what about this place, rather than these people, shapes the emissions here. An area with high car use and poor bus frequency is telling you something about the transport available, not about the willpower of residents, and that is a problem local government can act on. It is less useful for questions about individual behaviour, which neighbourhood averages cannot answer and should not be used to imply.

Not directly. The tools show historical and current footprints and include a reference line derived from the Sixth Carbon Budget, but they do not project forward or account for local targets, and the reference line divides the national budget equally per person rather than reflecting what would be fair or feasible in a given place. You can download the data and build your own budget from it. Downscaled local pathways, based on the Positive Low Energy Futures scenarios, are in development through the EDRC Futures theme.

Not yet. The tools describe what has happened rather than what is planned, and they contain no local targets. Adding scenario and target-tracking features is something we would like to do and is dependent on future funding.

The code is open source under the GNU Affero General Public Licence v3, so you may build your own version provided it is also open source. You can find it on GitHub. We do not permit embedding the hosted tools in third-party sites, partly because some of the underlying data licences do not allow it, but you are welcome to download the data and build your own visualisations, citing Carbon & Place as the source.

It is a real problem with any map of areas that are equal in population but wildly unequal in size. Our partial answer is the dasymetric view, which is on by default: it colours only the built-up parts of each neighbourhood, so a large rural area no longer floods the map with a colour representing a few hundred people. A cartogram, which resizes areas by population, would address it more completely at the cost of geographical accuracy, and we have not had the resources to build one.