Schools Weather and Air Quality (SWAQ) –Metadata – Urban Network, Sydney (NSW)

Schools Weather and Air Quality (SWAQ) is a citizen science project funded by the Department of Industry, Innovation and Science as part of its Inspiring Australia - Citizen Engagement Program. SWAQ is equipping public schools across Sydney with research-grade meteorology and air quality sensors, enabling students to collect and analyse research quality data through curriculum-aligned classroom activities.

The network includes twelve automatic weather stations and seven automatic air quality stations, stretched from -33.5995° to -34.0424° latitude and from 150.6918° to 151.2706° longitude. The average spacing is 10.2 km and the average installation height is 2.5 m above ground level. Six meteorological parameters (dry-bulb temperature, relative humidity, barometric pressure, rain, wind speed, and wind direction) and six air pollutants (SO2, NO2, CO, O3, PM2.5, and PM10) are recorded via Vaisala WXT 536 and Vaisala AQT 420 with a 20 minutes sampling frequency. 

SWAQ data provides urban canopy layer observations of the intra-urban heterogeneity and inter-parameter dependency of all major urban climate and air quality variables, valuable across diverse urban disciplines. SWAQ stations are located where there are gaps in existing government networks, and focus on Sydney’s western suburbs, where the highest urbanization rate is taking place, to better inform future urban planning. QC procedures are designed to ensure observations of extreme episodes are not excluded. Beyond research purposes, SWAQ is a citizen-centered network, conceived to promote valuable STEM (science, technology, engineering, mathematics) skills among citizens and students.

This collection includes the metadata files for all SWAQ stations, in pdf. Metadata describe the site (type, geographic coordinates, elevation, orographic setting, representativeness, local climatic zone, dominant land use, percent land cover, mean tree and building heights, proximity to water/heat and pollutants sources/sinks, estimation of Davenport Roughness, traffic density, sky view factor), and the instrumentation (variables, models, manufacturers, calibration and installation dates). Site characteristics are described at three radial scales: 20 km, 500 m, and 50 m. Graphical representations include: satellite images, street-view maps, cardinal direction photographs, panoramic photos, and close-up photos of sensors, solar panels, and connections. Optimum site allocation was determined by undertaking a multi-criteria weighted overlay analysis to ensure data representativeness and quality. All SWAQ sensors are installed:

• in homogenous urban regions, without sections of anomalous variation in the regional urban makeup and aspect-ratio, and without large, concentrated heat/pollution sources or sinks;
• in areas falling into the WMO Class 4 with no electromagnetic sources that could have distorted the transmission;
• at a constant height of  2 - 3.5 m above ground level.

The actual data is available from the Australian Terrestrial Ecosystem Research Network (TERN) data portal and is regularly updated. The data available from TERN has undergone a rigorous quality check routine before upload.

• Calibration: Sensors and gateways are calibrated and tested by Vaisalain controlled conditions 
• Quality Assurance: Annual maintenance log
• Quality control: continuity tests, fixed range tests (on both physical and instrumental limits), dynamic range and step tests (both performed on a monthly basis), internal consistency tests (on known atmospheric relations) and persistence tests. 

The files are in csv format. On the SWAQ website a non quality controlled subset is available for educational purposes only.

This project was funded by an Australian Government Department of Industry, Innovation and Science, Inspiring Australia – Science Engagement Program: Citizen Science Grants (CSG56028).

It was also part of the Centre of Excellence for Climate Extremes research project "Attribution & Risk".

More information is available in the readme file, in particular a full list of the variables and a legend for the quality flags used.