Modelling and Forecast of Air Pollution Concentrations during COVID Pandemic Emergency with ARIMA Techniques: the Case Study of Two Italian Cities

Abstract

An efficient and punctual monitoring of air pollutants is very useful to evaluate and prevent possible threats to human beings’ health. Especially in areas where such pollutants are highly concentrated, an accurate collection of data could suggest mitigation actions to be implemented. Moreover, a well-performed data collection could also permit the forecast of future scenarios, in relation to the seasonality of the phenomenon. With a particular focus on COVID pandemic period, several literature works demonstrated a decreasing of pollutant concentrations in air of urban areas, mainly for NOx, while CO and PM10, on the opposite, has been observed to remain still, mainly because of the intensive usage of heating systems by the people forced to stay home (on specific regions). With the present contribution the authors here present an application of Time Series analysis (TSA) approach to pollutants concentration data of two Italian cities during first lockdown (9 march – 18 may 2020), demonstrating the possibility to predict pollutants concentration over time.