ICOS

Atmospheric composition time series result, Schule Auzelg (3.1 m)

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2024-01-01–2024-07-31
11676/Xj2rLgqzkx9SobYi_SIIXrYd (link)

Generic gas and related tracers observational time series in ATC format

Grange, S. (2024). Atmospheric composition time series result, Schule Auzelg (3.1 m), 2024-01-01–2024-07-31, ICOS Cities, https://hdl.handle.net/11676/Xj2rLgqzkx9SobYi_SIIXrYd
BibTex
@misc{https://hdl.handle.net/11676/Xj2rLgqzkx9SobYi_SIIXrYd,
  author={Grange, Stuart},
  title={Atmospheric composition time series result, Schule Auzelg (3.1 m), 2024-01-01–2024-07-31},
  year={2024},
  keywords={WMOX2017, Zürich},
  url={https://hdl.handle.net/11676/Xj2rLgqzkx9SobYi_SIIXrYd},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/Xj2rLgqzkx9SobYi_SIIXrYd}
}
RIS
TY - DATA
T1 - Atmospheric composition time series result, Schule Auzelg (3.1 m), 2024-01-01–2024-07-31
ID - 11676/Xj2rLgqzkx9SobYi_SIIXrYd
PY - 2024
UR - https://hdl.handle.net/11676/Xj2rLgqzkx9SobYi_SIIXrYd
PB - Carbon Portal
AU - Grange, Stuart
KW - WMOX2017
KW - Zürich
ER - 
zuerich_ZAZG_2024_co2_9438.zip
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Acquisition

2024-01-01 00:30:00
2024-07-31 23:30:00
3.1

Production

2024-09-18 09:00:00
CO2 low_cost; type dl_lp8; sensor id=1157; sensingelement id=4157.0

Previewable variables

Name Value type Unit Quantity kind Preview
TIMESTAMP time instant, UTC
co2 CO2 (dry air mole fraction) µmol mol-1 portion Preview
NbPoints number of points cardinal number Preview
Flag quality flag

Statistics

0
0

Submission

2024-09-18 09:58:54
2024-09-18 09:58:54

Technical information

O, R, U
zip
5e3dab2e0ab3931f52a1b622fd22085eb61d5c24e9a65fd59bec26b3b4226cf2
Xj2rLgqzkx9SobYi/SIIXrYdXCTppl/Vm+wms7QibPI
Lat: 47.413856, Lon: 8.57215, Alt: 428.6 m
WMOX2017 Zürich dry air mole fraction low-mid-cost urban
3 pilot cities
15 countries
15 cities
30 scientific partners
13M€ funding
2021-2025
EU flag PAUL, Pilot Applications in Urban Landscapes - Towards integrated city observatories for greenhouse gases (ICOS Cities), has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 101037319.