Citation: Badyda, A.; Brzezi ´ nski, A.; Dybicz, T.; Jesionkiewicz-Niedzi´ nska, K.; Olszewski, P.; Osi´ nska, B.; Szagala, P.; Mucha, D. Impact of COVID-19 Mobility Changes on Air Quality in Warsaw. Appl. Sci. 2022, 12, 7372. https://doi.org/10.3390/app12157372 Academic Editor: Simone Morais Received: 25 April 2022 Accepted: 14 July 2022 Published: 22 July 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). applied sciences Article Impact of COVID-19 Mobility Changes on Air Quality in Warsaw Artur Badyda 1, * , Andrzej Brzezi ´ nski 2, *, Tomasz Dybicz 2 , Karolina Jesionkiewicz-Niedzi ´ nska 2 , Piotr Olszewski 2 , Beata Osi ´ nska 2 , Piotr Szagala 2 and Dominika Mucha 1 1 Faculty of Building Services Hydro- and Environmental Engineering, Warsaw University of Technology, 00-653 Warsaw, Poland;dominika.mucha@pw.edu.pl 2 Faculty of Civil Engineering, Warsaw University of Technology, 00-637 Warsaw, Poland; tomasz.dybicz@pw.edu.pl (T.D.); karolina.jesionkiewicz@pw.edu.pl (K.J.-N.); piotr.olszewski@pw.edu.pl (P.O.); beata.osinska@pw.edu.pl (B.O.); piotr.szagala@pw.edu.pl (P.S.) * Correspondence: artur.badyda@pw.edu.pl (A.B.); andrzej.brzezinski@pw.edu.pl (A.B.) Featured Application: The article describes the results of a project that concerned the creation of a method of using big data to build traffic models in special periods (e.g., during a pandemic) when obtaining data in a traditional way is difficult or not possible. Then, based on the comparison between those models and the typical state of the transport system, it is possible to perform comparative analysis and impact analyses. For example, analyses of social cost related to travel restrictions can be estimated. Abstract: During a pandemic, the mobility of people changes significantly from the normal situation (the number of trips made, the directions of travel and the modes of transport used). Changes in mobility depend on the scale of the pandemic threat and the scale of the restrictions introduced and assessing the impact of these changes is not straightforward. This raises the question of the social cost of changes in mobility and their impact on the environment, including air quality. The article shows that it is possible to determine this impact using big data from mobile operators’-SIM card movements and data from air quality monitoring stations. Data on SIM card movements allows for reconstructing the state of the transport system before and during the different phases of a pandemic. The changes in mobility of people determined in this way can be related to the results of measurements of pollutant concentrations in the air. In this way, it is possible to identify links between mobility changes and air quality. The article presents the extent (in relation to the state without the pandemic) of changes in the mobility of the population during the pandemic and the related impact on air quality using the example of Warsaw. Keywords: COVID-19 pandemic; lockdown; big data; mobility; emissions; air quality; transport 1. Introduction 1.1. Impact of Transport on Air Quality Transport can contribute to the pollution of soil, groundwater and surface water by increasing the amount of waste, such as used vehicles, tyres, oils, electrolytes, coolants and other materials used for cleaning and maintaining vehicles. It may also expose a significant part of the population to excessive noise and vibration and, above all, to loss of life and health as a result of traffic accidents [1]. However, the greatest threat to human health from motor vehicles, particularly in metropolitan settings, is air pollution [2]. Fossil fuels (petrol and diesel) burnt in internal combustion engines of road vehicles (cars, trucks, buses, taxis, etc.) cause direct emissions of pollutants such as nitrogen oxides (NOx), carbon monoxide (CO), carbon dioxide (CO 2 ), black carbon (BC), particulate matter (PM) and, to a lesser extent, non-methane volatile organic compounds (NMVOC), methane (CH 4 ), ammonia (NH 3 ) or sulphur dioxide (SO 2 ), Appl. Sci. 2022, 12, 7372. https://doi.org/10.3390/app12157372 https://www.mdpi.com/journal/applsci