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Dataset for publication: "Using explainable machine learning to interpret the effects of policies on air pollution: COVID-19 lockdown in London"

<p>This online repository offers supplementary datasets supporting the findings in&nbsp;the research article titled &quot;Using explainable machine learning to interpret the effects of policies on air pollution: COVID-19 lockdown in London,&quot; published in Environmental Science &amp; Technology. The dataset contains air quality data from different monitoring sites in London between 2016 and 2020 and weather data for the same period. Additionally, the dataset incorporates 136 features relating to London&#39;s Middle Layer Super Output Areas (MSOAs) in the year 2019, which can be used to identify the key factors contributing to the heterogeneous changes in air quality levels at different spatial locations during the pandemic. Please refer to the metadata file for detailed data sources and&nbsp;descriptions.&nbsp;</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

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