## 1 Introduction  
Polluted air can contain a substantial amount of chemicals in the form of microparticles and harmful gases. Among the most common atmospheric gaseous pollutants are carbon monoxide (CO), nitrogen oxides (NO and NO\({}_{2}\)), sulfur dioxide (SO\({}_{2}\)) and ozone (O\({}_{3}\)). All of them can cause a variety of respiratory and cardiovascular health problems and are especially dangerous for at-risk populations: the young, the elderly and people with respiratory or cardiovascular problems [1]. The air pollutant concentrations can be affected by social dynamics, such as the trigger of mass protests due to economic troubles, job insecurity and rapidly growing inequality [2]. In 2019, a huge number of public protests and strikes spiked up in developing and developed countries, including Europe, Asia and the Americas [3, 4, 5, 6]. At the end of 2019, Latin America was in the center stage of demonstrations against governments in Mexico [7], Chile [8], Bolivia [9, 10], Colombia [11] and Ecuador [12]. Massive protests and riots spread from capital cities overtaking significant parts of the countries, and in a few cases even lasting well into 2020 or 2021 [13, 14]. As social dissatisfaction is growing more vocal, it encourages scientific curiosity to question the effects that protests and strikes might have on air quality. During those special events, the protesters often cause restrictions or complete seizure of public and private transportation, which might improve air quality, however, they might also cause riots, vandalisms, burning and looting [15]. Though protests have previously been investigated from the social science perspective [16; 17], the research on air pollution dynamics is still very limited. Previous research analyzing the air quality during strike events has demonstrated a variety of effects on air quality. A study in Hong Kong during large-scale street protests reported a substantial reduction in NO\({}_{2}\) in the central area [5]. An investigation in Sao Paulo during a truck drivers' strike showed a 50% reduction in CO and NO concentrations, although NO\({}_{2}\) and particulate matter (PM) indicated no changes [18]. In contrast, during public transport strikes in Italy and Spain, CO levels increased due to the greater use of private vehicles [19; 20]. Such differences in research findings suggest a need for a broader understanding of the impact of these events on air quality. In previous studies, pollution change estimates are often based on differences between central and background sites [5] or \"trend conditions\". The latter are usually calculated using a comparable period (e.g., 3 to 5 years) prior to the protest event [18] or simply comparing pollution pre-strike levels to those during the strike [21]. Depending on the nature of the pollutant, these types of analyses could be subject to biases, as meteorological conditions that influence the production and transport of certain contaminants could vary between the time periods used for comparison [22]. In the case of traffic-borne primary pollutants, however, macroscopic observations before and after events that cause a change in traffic, are useful as differences are directly related to the physical source of pollution. In the case of statistics-based models (e.g., machine learning algorithms), meteorology variables can be included in order to avoid biases and to increase confidence when calculating business-as-usual (BAU) conditions, as previously done in COVID-19 impact studies [23; 24; 25]. As the number and scale of protests spiral, especially considering the economic burden due to the global COVID-19 pandemic, it is crucial to be able to evaluate the true environmental impact of these events. Hence, the purpose of this study is to find out how local is the impact of these events on urban air quality and how long do the effects last after the protests stop? For that, a new approach is proposed to quantify the effect of such an event on urban pollution.