Data

Exhaust identification data from IN2018_V01 (CAPRICORN2)

Commonwealth Scientific and Industrial Research Organisation
Humphries, Ruhi ; McRobert, Ian ; Ponsonby, Will ; Ward, Jason ; Keywood, Melita ; Loh, Zoe ; Krummel, Paul ; Harnwell, James
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/f8s8-cy20&rft.title=Exhaust identification data from IN2018_V01 (CAPRICORN2)&rft.identifier=https://doi.org/10.25919/f8s8-cy20&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=This data set contains an exhaust identification product for the voyage IN2018_V01 (CAPRICORN2). The data boolean time series represents whether atmospheric measurements are impacted by exhaust from diesel combustion or waste incineration from the RV Investigator itself.\n\nThe product utilises black carbon (BC), carbon monoxide (CO),\ncarbon dioxide (CO2) and aerosol number concentrations (CN) data \ntogether to identify exhaust via a rolling statistical filter.\n\nThis exhaust identification algorithm was calculated post-voyage using the algorithm described in Humphries et al. Identification of platform exhaust on the RV Investigator, Atmospheric Measurement Techniques, \ndoi:https://doi.org/10.5194/amt-12-3019-2019, 2019.\n\nLevel 1 data are those produced automatically from the algorithm described below.\nLevel 2 data are those refined with manual review of high time resolution data and manual exhaust filtering.\n\n\nh5 files can be accessed using the key exhaust.&rft.creator=Humphries, Ruhi &rft.creator=McRobert, Ian &rft.creator=Ponsonby, Will &rft.creator=Ward, Jason &rft.creator=Keywood, Melita &rft.creator=Loh, Zoe &rft.creator=Krummel, Paul &rft.creator=Harnwell, James &rft.date=2022&rft.edition=v2&rft.coverage=westlimit=131.9824; southlimit=-66.4585; eastlimit=150.015; northlimit=-42.897; projection=WGS84&rft_rights=Creative Commons Attribution-ShareAlike 4.0 International Licence https://creativecommons.org/licenses/by-sa/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2020.&rft_subject=exhaust&rft_subject=rv investigator&rft_subject=exhaust filter&rft_subject=aerosols&rft_subject=co2&rft_subject=co&rft_subject=black carbon&rft_subject=exhaust identification&rft_subject=Air pollution processes and air quality measurement&rft_subject=Atmospheric sciences&rft_subject=EARTH SCIENCES&rft_subject=Atmospheric aerosols&rft_subject=Atmospheric sciences not elsewhere classified&rft.type=dataset&rft.language=English Access the data

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CC-BY-SA

Creative Commons Attribution-ShareAlike 4.0 International Licence
https://creativecommons.org/licenses/by-sa/4.0/

Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO 2020.

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Brief description

This data set contains an exhaust identification product for the voyage IN2018_V01 (CAPRICORN2). The data boolean time series represents whether atmospheric measurements are impacted by exhaust from diesel combustion or waste incineration from the RV Investigator itself.

The product utilises black carbon (BC), carbon monoxide (CO),
carbon dioxide (CO2) and aerosol number concentrations (CN) data
together to identify exhaust via a rolling statistical filter.

This exhaust identification algorithm was calculated post-voyage using the algorithm described in Humphries et al. Identification of platform exhaust on the RV Investigator, Atmospheric Measurement Techniques,
doi:https://doi.org/10.5194/amt-12-3019-2019, 2019.

Level 1 data are those produced automatically from the algorithm described below.
Level 2 data are those refined with manual review of high time resolution data and manual exhaust filtering.


h5 files can be accessed using the key "exhaust".

Available: 2022-05-19

Data time period: 2018-01-10 to 2018-02-21

This dataset is part of a larger collection

Click to explore relationships graph

150.015,-42.897 150.015,-66.4585 131.9824,-66.4585 131.9824,-42.897 150.015,-42.897

140.9987,-54.67775