User’s Guide to the AQ+ Data Navigating the air quality datascape

This guide summarises some of the data made available for the Air Quality+ project, and is primarily intended to support responses to the AQ+ challenges.  More information is available in the air quality archive, along with examples. A quickstart technical guide to the stations and monitoring emissions is available.

The core AQ+ data is the environmental monitoring data captured through sensor stations and diffusion tubes.

  • Three active stations capture data up to every 20 minutes.
  • Historical data going back to 2000 exists for 8 sensor stations

The sensor stations variously record data for the a range of emissions:

  • Nitrogen Oxide (NO2)
  • Particulate Matter (PM10)
  • Particulate Matter (PM25)
  • Atmospheric pressure
  • Sulphur dioxide (SO2)
  • Ozone (O3)
  • Carbon Monoxide (CO)

Data for these emissions is structured using the W3C’s Semantic Sensor Network ontology. The project wiki shows sample queries to interrogate and access the data, as well as to get the underlying information about where stations are located and how far back data is collected.

Around 250 community diffusion tubes capture nitrogen dioxide levels nitrogen dioxide levels across 30 areas across the city. Levels are checked monthly and reported in an aggregate annual figure. While it loses frequency and calibration is less reliable than sensor stations, data goes back to 2003 and provides both useful trend information and several data points.

Some 150 industrial processes are regulated. Data is available for the businesses in Sheffield licensed to carry out these processes. Some processes require annual testing: data is partially available for this but is a bit more clunky to interrogate.

Beyond immediate environmental monitoring data, the AQ+ project is interested in data that points to possible causes or consequences of air pollution, as well as other datasets to consider in the air quality context. These are captured to an extent within the AQ+ datascape, which includes reference to (among others):

* More related datasets covering different data and geographical ranges can be found on the Sheffield Council datastore.

Most of the data cited is geared towards Sheffield. Some comparable datasets are likely available from other locations, to allow geographical comparisons. Some translation is likely required to make it comparable (one of the reasons we aim to use standards such as the Semantic Sensor Network ontology).