The average person in England and Wales used roughly *** liters of water per day as of 2024. This means that a household of four could potentially use more than *** liters of water a day. Portsmouth Water customers had the highest daily water usage in England and Wales in 2023, at *** liters per person. Metered and un-metered water usage The amount of water consumed by households can vary depending on whether the customer has a water meter installed. On average, households in England and Wales with a water meter consumed around ** liters less per person than those without a water meter. While most homes have traditional water meters, smart water meters have been rolled out since 2016. These allow customers to track water usage, save money, and allow water companies to detect leaks. What uses the most water in UK homes? The average water consumption of household appliances varies greatly, with some using significantly more than others. A full bath uses the largest amount of water by far, at approximately ** liters. This is ** liters more than the average washing machine cycle. Meanwhile, a dishwasher on an eco-setting can noticeably reduce water consumption when compared with a regular cycle.

Water usage per person in Scotland is the highest in the United Kingdom on average, at *** liters. This is noticeably more than in England, Wales, and Northern Ireland, where less than *** liters is used per person per day on average.

Household water consumption varies greatly from appliance to appliance, with baths and washing machines consuming by far the most. A full bath in the United Kingdom uses an average of ** liters of water, while showers are far less demanding. An electric shower uses just **** liters per minute, with power showers slightly less efficient at ** liters per minute.

Household water usage in the UK

The average water usage per person in England and Wales was *** liters per day in financial year 2022, with a three-year rolling average of *** liters per day. Water consumption varies depending on whether the customer has metered or un-metered water, with metered water consumption far lower than customers without a water meter.

Water bills

Combined household water and sewerage bills in England and Wales averaged 417 British pounds for the year ended March 2023. On average, customers of South West Water had the most expensive water and sewerage bills in the UK , at *** British pounds. It is forecasted that bills from this utility will decrease for the year ending March 2022.

Portsmouth Water customers consumed the most water per person per day in England and Wales in financial year 2024, at ***** liters. This was higher than their three-year rolling average of ***** liters per person per day. Nevertheless, Affinity Water is still the company with the highest three-year rolling average at *** liters per person per day.

Data History

Data Origin

Domestic consumption data is recorded using water meters. The consumption recorded is then sent back to water companies. This dataset is extracted from the water companies.

Data Triage Considerations

This section discusses the careful handling of data to maintain anonymity and addresses the challenges associated with data updates, such as identifying household changes or meter replacements.

Identification of Critical Infrastructure

This aspect is not applicable for the dataset, as the focus is on domestic water consumption and does not contain any information that reveals critical infrastructure details.

Commercial Risks and Anonymisation Individual Identification Risks

There is a potential risk of identifying individuals or households if the consumption data is updated irregularly (e.g., every 6 months) and an out-of-cycle update occurs (e.g., after 2 months), which could signal a change in occupancy or ownership. Such patterns need careful handling to avoid accidental exposure of sensitive information.

Meter and Property Association

Challenges arise in maintaining historical data integrity when meters are replaced but the property remains the same. Ensuring continuity in the data without revealing personal information is crucial.

Interpretation of Null Consumption

Instances of null consumption could be misunderstood as a lack of water use, whereas they might simply indicate missing data. Distinguishing between these scenarios is vital to prevent misleading conclusions.

Meter Re-reads

The dataset must account for instances where meters are read multiple times for accuracy.

Joint Supplies & Multiple Meters per Household

Special consideration is required for households with multiple meters as well as multiple households that share a meter as this could complicate data aggregation.

Schema Consistency with the Energy Industry

In formulating the schema for the domestic water consumption dataset, careful consideration was given to the potential risks to individual privacy. This evaluation included examining the frequency of data updates, the handling of property and meter associations, interpretations of null consumption, meter re-reads, joint suppliers, and the presence of multiple meters within a single household as described above.

After a thorough assessment of these factors and their implications for individual privacy, it was decided to align the dataset's schema with the standards established within the energy industry. This decision was influenced by the energy sector's experience and established practices in managing similar risks associated with smart meters. This ensures a high level of data integrity and privacy protection.

Schema The dataset schema is aligned with those used in the energy industry, which has encountered similar challenges with smart meters. However, it is important to note that the energy industry has a much higher density of meter distribution, especially smart meters.

Aggregation to Mitigate Risks The dataset employs an elevated level of data aggregation to minimise the risk of individual identification. This approach is crucial in maintaining the utility of the dataset while ensuring individual privacy. The aggregation level is carefully chosen to remove identifiable risks without excluding valuable data, thus balancing data utility with privacy concerns.

Data Freshness Users should be aware that this dataset reflects historical consumption patterns and does not represent real-time data. Publish Frequency Weekly.

Data Triage Review Frequency An annual review is conducted to ensure the dataset's relevance and accuracy, with adjustments made based on specific requests or evolving data trends.

Data Specifications For the domestic water consumption dataset, the data specifications are designed to ensure comprehensiveness and relevance, while maintaining clarity and focus. The specifications for this dataset include: • Each dataset encompasses recordings of domestic water consumption as measured and reported by the data publisher. It excludes commercial consumption. • Where it is necessary to estimate consumption, this is calculated based on actual meter readings. • Meters of all types (smart, dumb, AMR) are included in this dataset. • The dataset is updated and published Weekly. • Historical data may be made available to facilitate trend analysis and comparative studies, although it is not mandatory for each dataset release. • The dataset includes LSOAs with 2 or more meters. Any LSOAs with less than 2 meters have been excluded. • Consumption data is only included where we have the full consumption data for a year for a given meter.

Context Users are cautioned against using the dataset for immediate operational decisions regarding water supply management. The data should be interpreted considering potential seasonal and weather-related influences on water consumption patterns.

The geographical data provided does not pinpoint locations of water meters within an LSOA.

The dataset aims to cover a broad spectrum of households, from single-meter homes to those with multiple meters, to accurately reflect the diversity of water use within an LSOA.

Supplementary InformationBelow is a curated selection of links for additional reading, which provide a deeper understanding of this dataset.1.Ofwat guidance on water meters. https://www.ofwat.gov.uk/wp-content/uploads/2015/11/prs_lft_101117meters.pdf Data Schema DATA_SOURCE: Company that provided the data YEAR: The calendar year covered by the data LSOA_CODE: LSOA or Data Zone converted code of the meter location NUMBER_OF_METERS: Number of meters within an LSOA TOTAL_CONSUMPTION: Average consumption within the LSOA TOTAL_CONSUMPTION_UNITS: Units for average consumption

Welsh Water customers had the highest annual combined water and sewerage bill in England and Wales for the year ended March 2023, at *** British pounds. This was considerably more than the average combined household water and sewerage bill in England and Wales that year. Water utilities companies in Britain In 1989, the water sector in England and Wales became privatized, resulting in the sale of the ** regional water authorities, including Severn Trent, United Utilities, and Anglian Water. With more than ** million customers, Thames Water is the largest water and wastewater company in Great Britain. Water infrastructure in Britain Between 2015 and 2020, investment in Britain's water sector totaled ** billion British pounds. This averaged some ***** British pounds per property over the five year period. Water companies own hundreds of thousands of kilometers of water pipes that span the country. However, many pipes date back to the Victorian era and are prone to leakage. Because of this, billions of liters of water are lost every day.

Data History Data Origin Domestic consumption data is recorded using water meters. The consumption recorded is then sent back to water companies. This dataset is extracted from the water companies. Data Freshness Users should be aware that this dataset reflects historical consumption patterns and does not represent real-time data. Publish Frequency Annually Data Specifications For the domestic water consumption dataset, the data specifications are designed to ensure comprehensiveness and relevance, while maintaining clarity and focus. The specifications for this dataset include:• Each dataset encompasses recordings of domestic water consumption as measured and reported by the data publisher. It excludes commercial consumption.• Where it is necessary to estimate consumption, this is calculated based on actual meter readings.• Meters of all types (smart, dumb, AMR) are included in this dataset.• The dataset is updated and published annually.• Historical data may be made available to facilitate trend analysis and comparative studies, although it is not mandatory for each dataset release.• The dataset includes LSOAs with 2 or more meters. Any LSOAs with less than 10 meters have been excluded. Context Users are cautioned against using the dataset for immediate operational decisions regarding water supply management. The data should be interpreted considering potential seasonal and weather-related influences on water consumption patterns. The geographical data provided does not pinpoint locations of water meters within an LSOA. The dataset aims to cover a broad spectrum of households, from single-meter homes to those with multiple meters, or a single meter for multiple domestic units, to accurately reflect the diversity of water use within an LSOA. This dataset has been aggregated from actual read data and does not use estimated values to align reads to calendar years. Our approach subtracts the latest meter read from the preceding year from the latest meter read in the reported year; this is divided by the number of days between the two reads, then multiplied by the number of days in the reporting year to get the annualised consumption for each individual property. The annualised consumption is then aggregated for each LSOA and then divided by the number of properties within the LSOA to calculate the average annual consumption per household for that LSOA. Data are removed from meters considered as void for seven or more months during the year. Void properties are those within the company’s supply area, which are connected for either a water service only, a wastewater service only or both services but do not receive a charge, as there are no occupants. Supplementary Information Below is a curated selection of links for additional reading, which provide a deeper understanding of this dataset. 1. Ofwat guidance on water meters: https://www.ofwat.gov.uk/wp-content/uploads/2015/11/prs_lft_101117meters.pdf2. Wessex Water performance commitment data on void sites: https://marketplace.wessexwater.co.uk/dataset/void-sites-performance-commitment-data

Household water consumption in England and Wales is far lower for metered customers when compared to non-metered customers. In financial year 2024, metered customers in England and Wales used an average of ***** liters per person daily, compared with ****** liters per day for non-metered customers.

In financial year 2024, water consumption for metered Essex and Suffolk Water customers averaged ***** liters per day. This was the highest household water consumption throughout England and Wales for metered customers that year. Water consumption for metered customers is typically far lower when compared with non-metered customers. Households with metered water consumption in England and Wales averaged ***** liters of water per person per day in financial year 2024.

Monthly meter readings expressed as mean litres/day. These readings are of customers paying their bill by rateable value. Customers have been selected to be representative of the Yorkshire Water customer population, and are used to estimate water use by customers paying by rateable value in Yorkshire between 2010 and 2015. The data has been anonymised to remove personal data and make it Data Protection Act compliant. PLEASE NOTE Property reference - unique anonymised property identifier between 1 and 2470. These identifiers are not continuous. Postal District - the postal district where the property is. Jan/2010 - the month/year which the mean litres/day reading refers to. *This dataset has been published within the YOD thanks to the courtesy of Leeds Data Mill

The average annual combined water and sewerage bill in England and Wales was *** British pounds in financial year 2023, and is forecast to total *** British pounds for the year ended March 2024. South West Water customers pay the most for their combined water and sewerage bills.

United Kingdom UK: Water Productivity: Total: Constant 2010p USD(GDP) Gross Domestic Productper Cubic Meter of Total Freshwater Withdrawal data was reported at 313.499 USD/Cub m in 2012. This records an increase from the previous number of 296.853 USD/Cub m for 2007. United Kingdom UK: Water Productivity: Total: Constant 2010p USD(GDP) Gross Domestic Productper Cubic Meter of Total Freshwater Withdrawal data is updated yearly, averaging 139.500 USD/Cub m from Dec 1980 (Median) to 2012, with 7 observations. The data reached an all-time high of 313.499 USD/Cub m in 2012 and a record low of 91.344 USD/Cub m in 1980. United Kingdom UK: Water Productivity: Total: Constant 2010p USD(GDP) Gross Domestic Productper Cubic Meter of Total Freshwater Withdrawal data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Energy Production and Consumption. Water productivity is calculated as GDP in constant prices divided by annual total water withdrawal.; ; Food and Agriculture Organization, AQUASTAT data, and World Bank and OECD GDP estimates.; Weighted Average;

United Kingdom UK: Annual Freshwater Withdrawals: Domestic: % of Total Freshwater Withdrawal data was reported at 71.410 % in 2012. This records an increase from the previous number of 70.360 % for 2007. United Kingdom UK: Annual Freshwater Withdrawals: Domestic: % of Total Freshwater Withdrawal data is updated yearly, averaging 61.950 % from Dec 1980 (Median) to 2012, with 5 observations. The data reached an all-time high of 71.410 % in 2012 and a record low of 46.250 % in 2002. United Kingdom UK: Annual Freshwater Withdrawals: Domestic: % of Total Freshwater Withdrawal data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Energy Production and Consumption. Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Data are for the most recent year available for 1987-2002.; ; Food and Agriculture Organization, AQUASTAT data.; Weighted average;

List of the five highest and lowest ranked strata for the predicted mean daily water intake from Model 1B (I-MAIHDA analysis). Sex (p 

Overview Water companies in the UK are responsible for testing the quality of drinking water. This dataset contains the results of samples taken from the taps in domestic households to make sure they meet the standards set out by UK and European legislation. This data shows the location, date, and measured levels of determinands set out by the Drinking Water Inspectorate (DWI). Key Definitions  AggregationProcess involving summarising or grouping data to obtain a single or reduced set of information, often for analysis or reporting purposes  Anonymisation Anonymised data is a type of information sanitisation in which data anonymisation tools encrypt or remove personally identifiable information from datasets for the purpose of preserving a data subject's privacy Dataset Structured and organised collection of related elements, often stored digitally, used for analysis and interpretation in various fields.  Determinand A constituent or property of drinking water which can be determined or estimated. DWI Drinking Water Inspectorate, an organisation “providing independent reassurance that water supplies in England and Wales are safe and drinking water quality is acceptable to consumers.”  DWI Determinands Constituents or properties that are tested for when evaluating a sample for its quality as per the guidance of the DWI. For this dataset, only determinands with “point of compliance” as “customer taps” are included.   Granularity Data granularity is a measure of the level of detail in a data structure. In time-series data, for example, the granularity of measurement might be based on intervals of years, months, weeks, days, or hours ID Abbreviation for Identification that refers to any means of verifying the unique identifier assigned to each asset for the purposes of tracking, management, and maintenance.  LSOA Lower-Level Super Output Area is made up of small geographic areas used for statistical and administrative purposes by the Office for National Statistics. It is designed to have homogeneous populations in terms of population size, making them suitable for statistical analysis and reporting. Each LSOA is built from groups of contiguous Output Areas with an average of about 1,500 residents or 650 households allowing for granular data collection useful for analysis, planning and policy- making while ensuring privacy.  ONS Office for National Statistics  Open Data Triage The process carried out by a Data Custodian to determine if there is any evidence of sensitivities associated with Data Assets, their associated Metadata and Software Scripts used to process Data Assets if they are used as Open Data.  Sample A sample is a representative segment or portion of water taken from a larger whole for the purpose of analysing or testing to ensure compliance with safety and quality standards.  Schema Structure for organizing and handling data within a dataset, defining the attributes, their data types, and the relationships between different entities. It acts as a framework that ensures data integrity and consistency by specifying permissible data types and constraints for each attribute.  Units Standard measurements used to quantify and compare different physical quantities.  Water Quality The chemical, physical, biological, and radiological characteristics of water, typically in relation to its suitability for a specific purpose, such as drinking, swimming, or ecological health. It is determined by assessing a variety of parameters, including but not limited to pH, turbidity, microbial content, dissolved oxygen, presence of substances and temperature. Data History Data Origin  These samples were taken from customer taps. They were then analysed for water quality, and the results were uploaded to a database. This dataset is an extract from this database. Data Triage Considerations Granularity Is it useful to share results as averages or individual? We decided to share as individual results as the lowest level of granularity Anonymisation It is a requirement that this data cannot be used to identify a singular person or household. We discussed many options for aggregating the data to a specific geography to ensure this requirement is met. The following geographical aggregations were discussed: • Water Supply Zone (WSZ) - Limits interoperability with other datasets • Postcode – Some postcodes contain very few households and may not offer necessary anonymisation • Postal Sector – Deemed not granular enough in highly populated areas • Rounded Co-ordinates – Not a recognised standard and may cause overlapping areas • MSOA – Deemed not granular enough • LSOA – Agreed as a recognised standard appropriate for England and Wales • Data Zones – Agreed as a recognised standard appropriate for Scotland Data Triage Review Frequency  Annually unless otherwise requested Publish Frequency Annually Data Specifications • Each dataset will cover a year of samples in calendar year • This dataset will be published annually • Historical datasets will be published as far back as 2016 from the introduction of The Water Supply (Water Quality) Regulations 2016 • The determinands included in the dataset are as per the list that is required to be reported to the Drinking Water Inspectorate. • A small proportion of samples could not be allocated to an LSOA – these represented less than 0.1% of samples and were removed from the dataset in 2023. • See supplementary information for the lookup table applied to each calendar year of data. Context Many UK water companies provide a search tool on their websites where you can search for water quality in your area by postcode. The results of the search may identify the water supply zone that supplies the postcode searched. Water supply zones are not linked to LSOAs which means the results may differ to this dataset. Some sample results are influenced by internal plumbing and may not be representative of drinking water quality in the wider area. Some samples are tested on site and others are sent to scientific laboratories. Supplementary information Below is a curated selection of links for additional reading, which provide a deeper understanding of this dataset.   1. Drinking Water Inspectorate Standards and Regulations: https://www.dwi.gov.uk/drinking-water-standards-and-regulations/   2. LSOA (England and Wales) and Data Zone (Scotland): https://www.nrscotland.gov.uk/files/geography/2011-census/geography-bckground-info-comparison-of-thresholds.pdf   3. Description for LSOA boundaries by the ONS: https://www.ons.gov.uk/methodology/geography/ukgeographies/censusgeographies/census2021geographies4. Postcode to LSOA lookup tables (2022 calendar year data): https://geoportal.statistics.gov.uk/datasets/3770c5e8b0c24f1dbe6d2fc6b46a0b18/about5. Postcode to LSOA lookup tables (2023 calendar year data): https://geoportal.statistics.gov.uk/datasets/b8451168e985446eb8269328615dec62/about6. Postcode to LSOA lookup tables (2024 calendar year data): https://geoportal.statistics.gov.uk/datasets/068ee476727d47a3a7a0d976d4343c59/about7. Legislation history: https://www.dwi.gov.uk/water-companies/legislation/

Overview

Water companies in the UK are responsible for testing the quality of drinking water. This dataset contains the results of samples taken from the taps in domestic households to make sure they meet the standards set out by UK and European legislation. This data shows the location, date, and measured levels of determinands set out by the Drinking Water Inspectorate (DWI).

Key Definitions

Aggregation

Process involving summarizing or grouping data to obtain a single or reduced set of information, often for analysis or reporting purposes

Anonymisation

Anonymised data is a type of information sanitization in which data anonymisation tools encrypt or remove personally identifiable information from datasets for the purpose of preserving a data subject's privacy

Dataset

Structured and organized collection of related elements, often stored digitally, used for analysis and interpretation in various fields.

Determinand

A constituent or property of drinking water which can be determined or estimated.

DWI

Drinking Water Inspectorate, an organisation “providing independent reassurance that water supplies in England and Wales are safe and drinking water quality is acceptable to consumers.”

DWI Determinands

Constituents or properties that are tested for when evaluating a sample for its quality as per the guidance of the DWI. For this dataset, only determinands with “point of compliance” as “customer taps” are included.

Granularity

Data granularity is a measure of the level of detail in a data structure. In time-series data, for example, the granularity of measurement might be based on intervals of years, months, weeks, days, or hours

ID

Abbreviation for Identification that refers to any means of verifying the unique identifier assigned to each asset for the purposes of tracking, management, and maintenance.

LSOA

Lower-Level Super Output Area is made up of small geographic areas used for statistical and administrative purposes by the Office for National Statistics. It is designed to have homogeneous populations in terms of population size, making them suitable for statistical analysis and reporting. Each LSOA is built from groups of contiguous Output Areas with an average of about 1,500 residents or 650 households allowing for granular data collection useful for analysis, planning and policy- making while ensuring privacy.

ONS

Office for National Statistics

Open Data Triage

The process carried out by a Data Custodian to determine if there is any evidence of sensitivities associated with Data Assets, their associated Metadata and Software Scripts used to process Data Assets if they are used as Open Data. <

Sample

A sample is a representative segment or portion of water taken from a larger whole for the purpose of analysing or testing to ensure compliance with safety and quality standards.

Schema

Structure for organizing and handling data within a dataset, defining the attributes, their data types, and the relationships between different entities. It acts as a framework that ensures data integrity and consistency by specifying permissible data types and constraints for each attribute.

Units

Standard measurements used to quantify and compare different physical quantities.

Water Quality

The chemical, physical, biological, and radiological characteristics of water, typically in relation to its suitability for a specific purpose, such as drinking, swimming, or ecological health. It is determined by assessing a variety of parameters, including but not limited to pH, turbidity, microbial content, dissolved oxygen, presence of substances and temperature.

Data History

Data Origin

These samples were taken from customer taps. They were then analysed for water quality, and the results were uploaded to a database. This dataset is an extract from this database.

Data Triage Considerations

Granularity

Is it useful to share results as averages or individual?

We decided to share as individual results as the lowest level of granularity

Anonymisation

It is a requirement that this data cannot be used to identify a singular person or household. We discussed many options for aggregating the data to a specific geography to ensure this requirement is met. The following geographical aggregations were discussed:

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Water Supply Zone (WSZ) - Limits interoperability with other datasets

<!--·
Postcode – Some postcodes contain very few households and may not offer necessary anonymisation

<!--·
Postal Sector – Deemed not granular enough in highly populated areas

<!--·
Rounded Co-ordinates – Not a recognised standard and may cause overlapping areas

<!--·
MSOA – Deemed not granular enough

<!--·
LSOA – Agreed as a recognised standard appropriate for England and Wales

<!--·
Data Zones – Agreed as a recognised standard appropriate for Scotland

Data Specifications

Each dataset will cover a calendar year of samples

This dataset will be published annually

Historical datasets will be published as far back as 2016 from the introduction of of The Water Supply (Water Quality) Regulations 2016

The Determinands included in the dataset are as per the list that is required to be reported to the Drinking Water Inspectorate.

Context

Many UK water companies provide a search tool on their websites where you can search for water quality in your area by postcode. The results of the search may identify the water supply zone that supplies the postcode searched. Water supply zones are not linked to LSOAs which means the results may differ to this dataset

Some sample results are influenced by internal plumbing and may not be representative of drinking water quality in the wider area.

Some samples are tested on site and others are sent to scientific laboratories.

Data Publish Frequency

Annually

Data Triage Review Frequency

Annually unless otherwise requested

Supplementary information

Below is a curated selection of links for additional reading, which provide a deeper understanding of this dataset.

<!--1.
Drinking Water Inspectorate Standards and Regulations:

<!--2.
https://www.dwi.gov.uk/drinking-water-standards-and-regulations/

<!--3.
LSOA (England and Wales) and Data Zone (Scotland):

<!--4. https://www.nrscotland.gov.uk/files/geography/2011-census/geography-bckground-info-comparison-of-thresholds.pdf

<!--5.
Description for LSOA boundaries by the ONS: Census 2021 geographies - Office for National Statistics (ons.gov.uk)

<!--[6.
Postcode to LSOA lookup tables: Postcode to 2021 Census Output Area to Lower Layer Super Output Area to Middle Layer Super Output Area to Local Authority District (August 2023) Lookup in the UK (statistics.gov.uk)

<!--7.
Legislation history: Legislation - Drinking Water Inspectorate (dwi.gov.uk)

DescriptionAs part of our commitment to transparency and environmental responsibility, United Utilities is publishing detailed greenhouse gas (GHG) emissions data for the previous financial years from 2023. These datasets provide a comprehensive breakdown of emissions across our operations, including water and wastewater services, transport, energy use, and supply chain activities.All of our emissions are related to activities and energy consumption in the UK. We use the financial control approach, so our energy and carbon accounting is aligned with the consolidated financial statements for United Utilities Group PLC for the relevant period. Our GHG inventory, including all the underlying energy data, has undergone independent third-party verification by Achilles Group and is certified to the requirements of the Toitū Carbon Reduce programme.The data is structured according to the Greenhouse Gas Protocol and includes Scope 1 (direct emissions), Scope 2 (indirect emissions from purchased electricity), and Scope 3 (other indirect emissions such as supply chain and employee commuting). Emissions are reported in tonnes of carbon dioxide equivalent (tCO₂e), using the AR5 100-year Global Warming Potential factors for FY2025 and AR4 for earlier years.This data aligns to that published in the United Utilities Group Integrated Annual Report. Small differences are due to greater detail presented here and rounding.Data SpecificationsEmissions are calculated by estimating the individual greenhouse gases that result from all United Utilities’ activities, converted into a tonnes carbon dioxide equivalent (tCO2e).Tools and values used include:UK water industry Carbon Accounting Workbook (CAW)UK Government GHG conversion factors for company reportingGlobal warming potentials from the Intergovernmental Panel on Climate Change (IPCC)Global Comprehensive Environmental Data Archive (CEDA)Market-based figures for electricity use emission factors specific to the actual electricity purchased. Emissions from electricity for recently adopted sites were supplied on standard tariffs until they can be moved onto our corporate renewable contracts. For electricity supplied on a standard grid tariff, we use CO2e per kWh from suppliers’ public fuel mix disclosures.Location-based figures use average UK grid emissions to calculate electricity emissions.Further notes:Scope 1, scope 2 and scope 3 categories 3, 4, 5 and 6 use activity records, 2022, 2023 and 2024 UK Government GHG conversion factors for company reporting and UK water industry Carbon Accounting Workbook v17,18 and 19.From 2023/24, emission factors use IPCC AR5 global warming potentials where methane = 28, nitrous oxide = 265. Earlier years used AR4 where methane = 25, nitrous oxide = 298.Scope 3 categories 1 (excluding chemicals) and 2 use the latest Global CEDA to estimate emissions based on the amount spent by spend category. CEDA is a multi-region, environmentally extended input-output database that has global coverage and is a CDP recommended tool. Global ’22 was used for 2022/23, CEDA v6 for 2023/24 and CEDA v7 for 2024/25.Category 7 used EcoAct models to estimate emissions from employee commuting and homeworking based on company FTE figures and home, site, and hybrid working policies.

Water companies in the UK are responsible for testing the quality of drinking water. This dataset contains the results of samples taken from the taps in domestic households to make sure they meet the standards set out by UK and European legislation. This data shows the location, date, and measured levels of determinands set out by the Drinking Water Inspectorate (DWI).Key Definitions  AggregationProcess involving summarising or grouping data to obtain a single or reduced set of information, often for analysis or reporting purposes  Anonymisation Anonymised data is a type of information sanitisation in which data anonymisation tools encrypt or remove personally identifiable information from datasets for the purpose of preserving a data subject's privacy Dataset Structured and organised collection of related elements, often stored digitally, used for analysis and interpretation in various fields.  Determinand A constituent or property of drinking water which can be determined or estimated. DWI Drinking Water Inspectorate, an organisation “providing independent reassurance that water supplies in England and Wales are safe and drinking water quality is acceptable to consumers.”  DWI Determinands Constituents or properties that are tested for when evaluating a sample for its quality as per the guidance of the DWI. For this dataset, only determinands with “point of compliance” as “customer taps” are included.   Granularity Data granularity is a measure of the level of detail in a data structure. In time-series data, for example, the granularity of measurement might be based on intervals of years, months, weeks, days, or hours ID Abbreviation for Identification that refers to any means of verifying the unique identifier assigned to each asset for the purposes of tracking, management, and maintenance.  LSOA Lower-Level Super Output Area is made up of small geographic areas used for statistical and administrative purposes by the Office for National Statistics. It is designed to have homogeneous populations in terms of population size, making them suitable for statistical analysis and reporting. Each LSOA is built from groups of contiguous Output Areas with an average of about 1,500 residents or 650 households allowing for granular data collection useful for analysis, planning and policy- making while ensuring privacy.  ONS Office for National Statistics  Open Data Triage The process carried out by a Data Custodian to determine if there is any evidence of sensitivities associated with Data Assets, their associated Metadata and Software Scripts used to process Data Assets if they are used as Open Data.  Sample A sample is a representative segment or portion of water taken from a larger whole for the purpose of analysing or testing to ensure compliance with safety and quality standards.  Schema Structure for organizing and handling data within a dataset, defining the attributes, their data types, and the relationships between different entities. It acts as a framework that ensures data integrity and consistency by specifying permissible data types and constraints for each attribute.  Units Standard measurements used to quantify and compare different physical quantities.  Water Quality The chemical, physical, biological, and radiological characteristics of water, typically in relation to its suitability for a specific purpose, such as drinking, swimming, or ecological health. It is determined by assessing a variety of parameters, including but not limited to pH, turbidity, microbial content, dissolved oxygen, presence of substances and temperature. Data History Data Origin  These samples were taken from customer taps. They were then analysed for water quality, and the results were uploaded to a database. This dataset is an extract from this database. Data Triage Considerations Granularity Is it useful to share results as averages or individual? We decided to share as individual results as the lowest level of granularity Anonymisation It is a requirement that this data cannot be used to identify a singular person or household. We discussed many options for aggregating the data to a specific geography to ensure this requirement is met. The following geographical aggregations were discussed: • Water Supply Zone (WSZ) - Limits interoperability with other datasets • Postcode – Some postcodes contain very few households and may not offer necessary anonymisation • Postal Sector – Deemed not granular enough in highly populated areas • Rounded Co-ordinates – Not a recognised standard and may cause overlapping areas • MSOA – Deemed not granular enough • LSOA – Agreed as a recognised standard appropriate for England and Wales • Data Zones – Agreed as a recognised standard appropriate for Scotland Data Triage Review Frequency  Annually unless otherwise requested Publish Frequency Annually Data Specifications • Each dataset will cover a year of samples in calendar year • This dataset will be published annually • The determinands included in the dataset are as per the list that is required to be reported to the Drinking Water Inspectorate. Context Many UK water companies provide a search tool on their websites where you can search for water quality in your area by postcode. The results of the search may identify the water supply zone that supplies the postcode searched. Water supply zones are not linked to LSOAs which means the results may differ to this dataset. Some sample results are influenced by internal plumbing and may not be representative of drinking water quality in the wider area. Some samples are tested on site and others are sent to scientific laboratories. Supplementary information Below is a curated selection of links for additional reading, which provide a deeper understanding of this dataset.   1. Drinking Water Inspectorate Standards and Regulations: https://www.dwi.gov.uk/drinking-water-standards-and-regulations/   2. LSOA (England and Wales) and Data Zone (Scotland): https://www.nrscotland.gov.uk/files/geography/2011-census/geography-bckground-info-comparison-of-thresholds.pdf   3. Description for LSOA boundaries by the ONS: https://www.ons.gov.uk/methodology/geography/ukgeographies/censusgeographies/census2021geographies4. Postcode to LSOA lookup tables (2024 calendar year data): https://geoportal.statistics.gov.uk/datasets/7fc55d71a09d4dcfa1fd6473138aacc3/about

Data HistoryData OriginReservoir level data is sourced from Water Companies who may also update this information on their website and government publications such as the Water Situation Reports provided by the UK government.Data Triage ConsiderationsIdentification of Critical InfrastructureSpecial attention is given to safeguard data on essential reservoirs in line with the National Infrastructure Act, to mitigate security risks and ensure resilience of public water systems. Currently, it is agreed that only reservoirs with a location already available in the public domain are included in this dataset.Commercial Risks and AnonymisationThe risk of personal information exposure is minimal to none since the data concerns Reservoir levels, which are not linked to individuals or households.Data FreshnessIt is not currently possible to make the dataset live. Some companies have digital monitoring, and some are measuring Reservoir levels analogically. This dataset may not be used to determine Reservoir level in place of visual checks where these are advised.Data Triage Review FrequencyAnnually unless otherwise requested.Data SpecificationsData specifications define what is included and excluded in the dataset to maintain clarity and focus. For this dataset:• Each dataset covers measurements taken by the publisher.• This dataset is published periodically in line with the publisher’s capabilities.• Historical datasets may be provided for comparison but are not required.• The location data provided may be a point from anywhere within the body of water or on its boundary.Reservoirs included in the dataset must be:• Open bodies of water used to store raw/untreated water.• Filled naturally.• Measurable.• Contain water that may go on to be used for public supply.ContextThis dataset must not be used to determine the implementation of low supply or high supply measures such as hose pipe bans being put in place or removed. Please await guidance from your water supplier regarding any changes required to your usage of water.Particularly high or low Reservoir levels may be considered normal or as expected given the season or recent weather.This dataset does not remove the requirement for visual checks on Reservoir level that are in place for caving/pot holing safety.Some water companies calculate the capacity of Reservoirs differently than others. The capacity can mean the useable volume of the Reservoir or the overall volume that can be held in the Reservoir including water below the water table.Data Publish FrequencyMonthly.Supplementary informationBelow is a curated selection of links for additional reading, which provide a deeper understanding of this dataset.1.Uses of Reservoirs: https://britishdams.org/about-dams/dam-information/uses-for-reservoirs/2.Inventory of UK Reservoirs: https://catalogue.ceh.ac.uk/documents/f5a7d56c-cea0-4f00-b159-c3788a3b2b383.Reservoirs Act 1975 as applied in England: https://britishdams.org/assets/documents/Dam%20Legislation%20-%20England%20-%20October%202016.pdf4.Reservoirs Act (Northern Ireland) 2015: https://britishdams.org/assets/documents/Dam%20Legislation%20-%20Northern%20Ireland%20-%20October%202016.pdf5.Reservoirs (Scotland) Act 2011: https://britishdams.org/assets/documents/Dam%20Legislation%20-%20Scotland%20-%20October%202016.pdf6.Reservoirs Act 1975 as applied in Wales: https://britishdams.org/assets/documents/Dam%20Legislation%20-%20Wales%20-%20October%202016.pdf7.Monthly local reports on Reservoir levels: Water situation: area monthly reports for England 2024 - GOV.UK (www.gov.uk) Data Schema RESERVOIR_ID: Reservoir ID given by the water companyRESERVOIR_NAME: Name of the ReservoirDATE: Date of measured water storage levelLATITUDE: Latitude coordinates of the ReservoirLONGITUDE: Longitude coordinates of the ReservoirCAPACITY: Reservoir capacityCAPACITY_UNITS: Reservoir capacity unitsCURRENT_LEVEL: Measurement of raw water levelCURRENT_LEVEL_UNITS:Units of measured raw water levelCURRENT_PERCENTAGE: Percentage of volume storage that is filled with raw water