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Schools Weather and Air Quality (SWAQ) – Quality Controlled Urban Dataset – Sydney (NSW) 

Ver: 1.0
Status of Data: onGoing
Update Frequency: periodic
Security Classification: unclassified
Record Last Modified: 2025-12-02
Viewed 5261 times
Accessed 214 times
Dataset Created: 2021-05-31
Dataset Published: 2021-07-02
Data can be accessed from the following links:
HTTPPoint-of-truth metadata URLHTTP2021-04-30_Cleaned.csvHTTP2021-04-30_Raw.csvHTTPDataset_Guide__Glossary_JyvznNc.pdfHTTPSWAQ_METADATA.zipHTTPro-crate-metadata.json
How to cite this collection:
Hart, M., Maharaj, A., Di Virgilio, G. & Ulpiani, G. (2021). Schools Weather and Air Quality (SWAQ) – Quality Controlled Urban Dataset – Sydney (NSW). Version 1.0. Terrestrial Ecosystem Research Network. Dataset. https://portal.tern.org.au/metadata/f59ae00d-2017-48c1-911a-8400249f1088 
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 -34.0421° latitude and from 150.6913° to 151.2708° longitude. The average spacing is 10.2 km and the average installation height is 2.5 m above ground level. Optimum site allocation was determined by undertaking a multi-criteria weighted overlay analysis to ensure data representativeness and quality. 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. Observations and metadata are available from September 2019 for WXT536 + AQT420 stations and from October 2019 for WXT536 stations (refer to Table 1 of the Dataset Guide), thus encompassing the Black Summer bushfire and the COVID-19 lockdown period. Data routinely undergo quality control, quality assurance and publication. 
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging. Department of Industry, Innovation and Science. Inspiring Australia - Citizen Engagement Program 
Purpose
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. Beyond research purposes, SWAQ is a citizen-centered network, conceived to promote valuable STEM (science, technology, engineering, mathematics) skills among citizens and students. 
Lineage
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. Quality control includes 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. Data failing any of the above tests are flagged as described in the Supplemental Information. Two quality-controlled datasets are available: “YYYY-MM-DD_Raw.csv” where flags supplement but do not alter the original data and “YYYY-MM-DD_Cleaned.csv” that contains a ready-to-use cleaned dataset, as recommended by the SWAQ team. 
Method DocumentationData not provided.
Procedure Steps

1. 

Quality Assurance: Annual maintenance log 

2. 

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. 

Temporal Coverage
From 2019-09-01 to on going 
Spatial Resolution

Data not provided.

Vertical Extent

Between 0 and 0 Meters

Data Quality Assessment Scope
Sensors and gateways are calibrated and tested by Vaisala in controlled conditions 
Data Quality Report
Data not provided. 
Data Quality Assessment Outcome
Sensors and gateways come with independent test reports reporting the successful outcome of the calibration and testing 
ANZSRC - FOR
Atmospheric composition, chemistry and processes
Atmospheric sciences
Climate change processes
Climatology
Meteorology
Other built environment and design
Urban and regional planning
GCMD Sciences
ATMOSPHERE - AIR QUALITY
ATMOSPHERE - AIR TEMPERATURE
ATMOSPHERE - CARBON MONOXIDE
ATMOSPHERE - LOCAL WINDS
ATMOSPHERE - NITROGEN OXIDES
ATMOSPHERE - PARTICULATE MATTER
ATMOSPHERE - RAIN
ATMOSPHERE - RELATIVE HUMIDITY
ATMOSPHERE - SULFUR DIOXIDE
ATMOSPHERE - TROPOSPHERIC OZONE
HUMAN DIMENSIONS - URBAN AREAS
HUMAN DIMENSIONS - WILDFIRES
Horizontal Resolution
10 km - < 50 km or approximately .09 degree - < .5 degree
Parameters
air pressure
air temperature
mass concentration of carbon monoxide in air
mass concentration of nitrogen dioxide in air
mass concentration of ozone in air
mass concentration of sulfur dioxide in air
mass fraction of pm10 aerosol in air
mass fraction of pm2p5 aerosol in air
rainfall rate
relative humidity
wind from direction
wind speed
Temporal Resolution
1 minute - < 1 hour
Topic
climatologyMeteorologyAtmosphere
environment
User Defined
air quality
bushfire
citizen science
COVID lockdown
intra-urban heterogeneity
ourdoor air quality
pollution
urban canopy monitoring
urban climate
urban heat
urban heat island
urban pollution
Author
Hart, Melissa
Co-Author
Maharaj, Angela
Di Virgilio, Giovanni
Ulpiani, Giulia
Contact Point
Hart, Melissa
Publisher
Terrestrial Ecosystem Research Network
Air quality impacts of the 2019-2020 black summer wildfires on Australian schools
Schools Weather and Air Quality SWAQ website
DOI in Zenodo
Supplemental Information
For more information on variable names, formats, quality control and flagging systems, see "Dataset Guide & Glossary.pdf" 
Resource Specific Usage
Data not provided. 
Environment Description
Data not provided. 
Export to DCATExport to BibTeXExport to EndNote/Zotero
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Creative Commons Attribution 4.0 International Licence
https://creativecommons.org/licenses/by/4.0/
Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}. 
TERN services are provided on an "as-is" and "as available" basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure.
Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.

Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting 

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Version:6.2.22