Articles | Volume 10, issue 2
Geosci. Instrum. Method. Data Syst., 10, 265–285, 2021
https://doi.org/10.5194/gi-10-265-2021
Geosci. Instrum. Method. Data Syst., 10, 265–285, 2021
https://doi.org/10.5194/gi-10-265-2021

Research article 03 Nov 2021

Research article | 03 Nov 2021

Evaluation of multivariate time series clustering for imputation of air pollution data

Wedad Alahamade et al.

Data sets

Data Selector Department for Environment, Food & Rural Affairs https://uk-air.defra.gov.uk/data/data_selector_service?show=auto&submit=Reset&f_limit_was=1

Wedad-O-A/Modelled-concentrations-: Modelled_Concentration_Air_Qaulity (v3.5.2) Wedad Alahamade https://doi.org/10.5281/zenodo.5602618

Model code and software

Wedad-O-A/Modelled-concentrations-: Modelled_Concentration_Air_Qaulity (v3.5.2) Wedad Alahamade https://doi.org/10.5281/zenodo.5602618

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Short summary
The goal is to reduce the uncertainty in air quality assessment by imputing all missing pollutants in monitoring stations and identify where more measurements can be beneficial. The proposed approach is based on spatial or temporal similarity between stations. Our proposed approach enables us to impute and estimate plausible concentrations of multiple pollutants at stations across the UK, and the modelled concentrations from the selected models correlated well with the observed concentrations.