TY - JOUR
T1 - NO2 levels as a contributing factor to COVID-19 deaths
T2 - the first empirical estimate of threshold values
AU - Mele, Marco
AU - Magazzino, Cosimo
AU - Schneider, Nicolas
AU - Strezov, Vladimir
PY - 2021/3
Y1 - 2021/3
N2 - This study represents the first empirical estimation of threshold values between nitrogen dioxide (NO2) concentrations and COVID-19-related deaths in France. The concentration of NO2 linked to COVID-19-related deaths in three major French cities were determined using Artificial Neural Networks experiments and a Causal Direction from Dependency (D2C) algorithm. The aim of the study was to evaluate the potential effects of NO2 in spreading the epidemic. The underlying hypothesis is that NO2, as a precursor to secondary particulate matter formation, can foster COVID-19 and make the respiratory system more susceptible to this infection. Three different neural networks for the cities of Paris, Lyon and Marseille were built in this work, followed by the application of an innovative tool of cutting the signal from the inputs to the selected target. The results show that the threshold levels of NO2 connected to COVID-19 range between 15.8 μg/m3 for Lyon, 21.8 μg/m3 for Marseille and 22.9 μg/m3 for Paris, which were significantly lower than the average annual concentration limit of 40 μg/m³ imposed by Directive 2008/50/EC of the European Parliament.
AB - This study represents the first empirical estimation of threshold values between nitrogen dioxide (NO2) concentrations and COVID-19-related deaths in France. The concentration of NO2 linked to COVID-19-related deaths in three major French cities were determined using Artificial Neural Networks experiments and a Causal Direction from Dependency (D2C) algorithm. The aim of the study was to evaluate the potential effects of NO2 in spreading the epidemic. The underlying hypothesis is that NO2, as a precursor to secondary particulate matter formation, can foster COVID-19 and make the respiratory system more susceptible to this infection. Three different neural networks for the cities of Paris, Lyon and Marseille were built in this work, followed by the application of an innovative tool of cutting the signal from the inputs to the selected target. The results show that the threshold levels of NO2 connected to COVID-19 range between 15.8 μg/m3 for Lyon, 21.8 μg/m3 for Marseille and 22.9 μg/m3 for Paris, which were significantly lower than the average annual concentration limit of 40 μg/m³ imposed by Directive 2008/50/EC of the European Parliament.
KW - COVID-19
KW - NO₂
KW - Machine learning
KW - Artificial neural networks
UR - http://www.scopus.com/inward/record.url?scp=85099644088&partnerID=8YFLogxK
U2 - 10.1016/j.envres.2020.110663
DO - 10.1016/j.envres.2020.110663
M3 - Article
C2 - 33417906
AN - SCOPUS:85099644088
SN - 0013-9351
VL - 194
SP - 1
EP - 11
JO - Environmental Research
JF - Environmental Research
M1 - 110663
ER -