Britain Breathing: UK Air Quality and Meteorological Estimates by Postcode District

The Britain Breathing 2016-2019 dataset provides estimated daily mean and maximum values for air quality, meteorological, and pollen measurements across UK postcode districts. Ann Gledson from the University of Manchester created it using a 'concentric regions' method to interpolate data from the DEFRA AURN network, Met Office MIDAS archives, and EMEP model forecasts. It includes a 'rings' variable indicating the distance of sensors used for each estimate, allowing users to filter for confidence.

Use Cases

• Analyzing long-term exposure to pollutants like PM2.5 and NO2 based on postcode district.
• Validating regional air quality models using the provided EMEP model forecast data.
• Studying correlations between meteorological factors (temperature, humidity) and pollen counts.
• Assessing estimation uncertainty by filtering results using the 'rings' distance metric.

Strengths

• Covers a four-year time range from 2016 to 2019.
• Provides a confidence indicator ('rings') for each spatial estimate, detailing sensor proximity.
• Integrates multiple data sources: measured data from DEFRA AURN and Met Office, plus EMEP model forecasts.
• Associated code and source data are archived on Zenodo and GitHub, supporting reproducibility.

Limitations

• Key metadata such as row count, file size, and specific column names are not provided in the available descriptions.
• Estimates for areas with high 'rings' values are derived from distant sensors, which may reduce local accuracy.
• The 'last updated' date is unknown, making it difficult to assess the dataset's currency.

Provenance

Source

University of Manchester (Ann Gledson). Data sourced from DEFRA AURN, UK Met Office MIDAS archives via MEDMI server, and EMEP model forecasts.

Collection Method

Estimates generated using a 'concentric regions' interpolation method on source station data, with code publicly available.

Time Range

2016-2019

Geography

United Kingdom and Crown Dependencies, aggregated to postcode district level (e.g., 'AB').