Articles | Volume 18, issue 9
https://doi.org/10.5194/acp-18-6543-2018
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, Paul Andrew Makar, Yayne Aklilu, and Ayodeji Akingunola

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Cited articles

Airdata warehouse: Government of Alberta, available at: http://airdata.alberta.ca/, last access: 5 May 2018. 
Akingunola, A., Makar, P. A., Zhang, J., Darlington, A., Li, S.-M., Gordon, M., Moran, M. D., and Zheng, Q.: A chemical transport model study of plume rise and particle size distribution for the Athabasca oil sands, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-155, in review, 2018. 
Alberta Environment and Parks (AEP): Development of Performance Specifications for Continuous Ambient Air Monitoring Analyzers, Government of Alberta, AEP, Alberta, Canada, 2014. 
Alberta Environment and Parks (AEP): Air Monitoring Directive Chapter 4: Monitoring Requirements and Equipment Technical Specifications, Government of Alberta, AEP, Air, No. 1–4, Alberta, Canada, 2016. 
Bari, M. A., Curran, R. T. L., and Kindzierski, W. B.: Field performance evaluation of Maxxam passive samplers for regional monitoring of ambient SO2, NO2 and O3 concentrations in Alberta, Canada, Atmos. Environ., 114, 39–47, 2015. 
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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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