Meteorological Normalisation Using Boosted Regression Trees to Estimate the Impact of COVID-19 Restrictions on Air Quality Levels

Sandra Ceballos-Santos, Jaime González-Pardo, David C. Carslaw, Ana Santurtún, Miguel Santibáñez and Ignacio Fernández-Olmo
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Sandra Ceballos-Santos: Department of Chemical and Biomolecular Engineering, University of Cantabria, 39005 Santander, Spain
Jaime González-Pardo: Department of Chemical and Biomolecular Engineering, University of Cantabria, 39005 Santander, Spain
David C. Carslaw: Wolfson Atmospheric Chemistry Laboratories, University of York, York YO10 5DD, UK
Ana Santurtún: Unit of Legal Medicine, Department of Physiology and Pharmacology, University of Cantabria, 39011 Santander, Spain
Miguel Santibáñez: Global Health Research Group, Department of Nursing, University of Cantabria, 39008 Santander, Spain
Ignacio Fernández-Olmo: Department of Chemical and Biomolecular Engineering, University of Cantabria, 39005 Santander, Spain

IJERPH, 2021, vol. 18, issue 24, 1-18

Abstract: The global COVID-19 pandemic that began in late December 2019 led to unprecedented lockdowns worldwide, providing a unique opportunity to investigate in detail the impacts of restricted anthropogenic emissions on air quality. A wide range of strategies and approaches exist to achieve this. In this paper, we use the “deweather” R package, based on Boosted Regression Tree (BRT) models, first to remove the influences of meteorology and emission trend patterns from NO, NO 2 , PM 10 and O 3 data series, and then to calculate the relative changes in air pollutant levels in 2020 with respect to the previous seven years (2013–2019). Data from a northern Spanish region, Cantabria, with all types of monitoring stations (traffic, urban background, industrial and rural) were used, dividing the calendar year into eight periods according to the intensity of government restrictions. The results showed mean reductions in the lockdown period above −50% for NO x , around −10% for PM 10 and below −5% for O 3 . Small differences were found between the relative changes obtained from normalised data with respect to those from observations. These results highlight the importance of developing an integrated policy to reduce anthropogenic emissions and the need to move towards sustainable mobility to ensure safer air quality levels, as pre-existing concentrations in some cases exceed the safe threshold.

Keywords: air pollution; COVID-19; lockdown; deweather; meteorological normalisation; boosted regression trees (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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