Articles | Volume 18, issue 9
Atmos. Chem. Phys., 18, 6543–6566, 2018
https://doi.org/10.5194/acp-18-6543-2018

Special issue: Atmospheric emissions from oil sands development and their...

Atmos. Chem. Phys., 18, 6543–6566, 2018
https://doi.org/10.5194/acp-18-6543-2018

Research article 08 May 2018

Research article | 08 May 2018

The use of hierarchical clustering for the design of optimized monitoring networks

Joana Soares et al.

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Joana Soares on behalf of the Authors (27 Mar 2018)  Author's response    Manuscript
ED: Publish as is (02 Apr 2018) by Randall Martin
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Short summary
Grouping data on the basis of (dis)similarity can be used to assess the efficacy of monitoring networks. The data are cross-compared in terms of temporal variation and magnitude of concentrations, and sites are ranked according to their level of potential redundancy. The methodology can be applied to measurement data, helping to identify sites with different measuring technologies or data flaws, and to model output, generating maps of areas of spatial representativeness of a monitoring site.
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