Gradient Boosting Machine to Assess the Public Protest Impact on Urban Air Quality

Abstract

Political and economic protests build-up due to the financial uncertainty and inequality spreading throughout the world. In 2019, Latin America took the main stage in a wave of protests. While the social side of protests is widely explored, the focus of this study is the evolution of gaseous urban air pollutants during and after one of these events. Changes in concentrations of NO2, CO, O3 and SO2 during and after the strike, were studied in Quito, Ecuador using two approaches: (i) inter-period observational analysis; and (ii) machine learning (ML) gradient boosting machine (GBM) developed business-as-usual (BAU) comparison to the observations. During the strike, both methods showed a large reduction in the concentrations of NO2 (31.5–32.36%) and CO (15.55–19.85%) and a slight reduction for O3 and SO2. The GBM approach showed an exclusive potential, especially for a lengthier period of predictions, to estimate strike impact on air quality even after the strike was over. This advocates for the use of machine learning techniques to estimate an extended effect of changes in human activities on urban gaseous pollution.

War Impact on Air Quality in Ukraine

“…However, probably due to the nature of public protests, including restrictions on circulation and simultaneously burning barricades or other objects, this type of study is more suitable for comparison to war conditions. NO 2 concentrations dropped 31.5-32.36% during the public protests in the Ecuadorian capital comparing the best to the findings of this study [13].…”

“…These increases are also more regional, due to the total column concentration data, spreading over a bigger area, unlike the localized events described with NO 2 pollution. In contrast to reported CO concentration reduction, as also shown here during the first two weeks of the war for Ukraine and Kyiv, during unusual events such as global pandemic or local political protests, O 3 concentrations tend to increase, as also shown in this work due to war activities [2,13]. An increase in CO concentrations might be an indicator of an increase of war related combustion activities (e.g., fires, explosions, etc.…”

“…Sokhi and colleagues [2] showed 25-60% reduction in SO 2 concentrations, varying across the countries, depending on the level of strictness implemented nationally to stop the spread of the virus. Meanwhile, only ~7% reduction in SO 2 levels was registered during the violent public protest in Quito, Ecuador [13].…”

“…These exceptional events, however, may create additional sources of pollution, for instance, due to an increased use of private vehicles, or burning, and vandalism in order to create physical barriers [10][11][12]. Even then, an overall reduction in urban pollution levels is reported [13].…”

Actual Evapotranspiration Estimation Using Sentinel-1 SAR and Sentinel-3 SLSTR Data Combined with a Gradient Boosting Machine Model in Busia County, Western Kenya

“…Khoi et al [84] also demonstrated its good performance in predicting the water quality index. The model has further shown an exclusive potential to predict the impact of air quality on urban areas and an impressive performance in predicting pollution caused by human activities [85].…”