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- Zalakeviciute, R., et al.
(författare)
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A Traffic-based method to predict and map urban air quality
- 2020
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Ingår i: Applied Sciences (Switzerland). - : MDPI. - 2076-3417. ; 10:6
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Tidskriftsartikel (refereegranskat)abstract
- As global urbanization, industrialization, and motorization keep worsening air quality, a continuous rise in health problems is projected. Limited spatial resolution of the information on air quality inhibits full comprehension of urban population exposure. Therefore, we propose a method to predict urban air pollution from traffic by extracting data from Web-based applications (Google Traffic). We apply a machine learning approach by training a decision tree algorithm (C4.8) to predict the concentration of PM2.5 during the morning pollution peak from: (i) an interpolation (inverse distance weighting) of the value registered at the monitoring stations, (ii) traffic flow, and (iii) traffic flow + time of the day. The results show that the prediction from traffic outperforms the one provided by the monitoring network (average of 65.5% for the former vs. 57% for the latter). Adding the time of day increases the accuracy by an average of 6.5%. Considering the good accuracy on different days, the proposed method seems to be robust enough to create general models able to predict air pollution from traffic conditions. This affordable method, although beneficial for any city, is particularly relevant for low-income countries, because it offers an economically sustainable technique to address air quality issues faced by the developing world.
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- Zalakeviciute, R., et al.
(författare)
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Chemical characterization of urban PM10 in the Tropical Andes
- 2019
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Ingår i: Atmospheric Pollution Research. - : Elsevier BV. - 1309-1042. ; 11:2, s. 343-356
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Tidskriftsartikel (refereegranskat)abstract
- Complex inhalable particles have become one of the main causes to trigger health problems worldwide. While the level of concern depends on the chemical composition of these particles, some regions are poorly studied, particularly, the Andes. In this work, the chemical characterization of atmospheric PM10 filter samples, collected between January and October of 2017, was carried out for the first time in the world's highest capital, Quito, Ecuador. This study investigates PM10 relation with meteorological variables and criteria pollutants. Average PM10 concentrations ranged from 24.9 μg m−3 to 26.2 μg m−3, with some alarming peaks during the episodes of fires and New Year's celebration. The major elements at study sites were Ca, Na, S, Mg, P, K, Fe, Si and Al, while the major water-soluble ion was SO42−. Meteorology plays an important role at this complex terrain city. Factor analysis showed natural dust and soil resuspension as the main source of particulate matter. Moreover, two less urbanized sites showed evidence of industrial activities or airport emissions, while the central city site showed a very strong signal of traffic-related pollution. These results are compared with representative cities around the world. As is the case in developing countries, low-quality diesel fuel is recognized for emitting large amounts of heavy metals, resulting in higher levels of those tracers in traffic flow areas. This work demonstrates the problems facing a midsize city, such as the lack of stricter regulations and, thus compromised air quality. This may imply serious respiratory and cardiovascular health effects.
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- Zalakeviciute, R., et al.
(författare)
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Gradient boosting machine to assess the public protest impact on urban air quality
- 2021
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 11:24
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Tidskriftsartikel (refereegranskat)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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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- Zalakeviciute, R., et al.
(författare)
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War Impact on Air Quality in Ukraine
- 2022
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 14:21
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Tidskriftsartikel (refereegranskat)abstract
- In the light of the 21st century, after two devastating world wars, humanity still has not learned to solve their conflicts through peaceful negotiations and dialogue. Armed conflicts, both international and within a single state, still cause devastation, displacement, and death all over the world. Not to mention the consequences that war has on the environment. Due to a lack of published research about war impact on modern air quality, this work studies air pollution evolution during the first months of the Russian-Ukrainian conflict. Satellite images of NO2, CO, O3, SO2, and PM2.5 over Ukrainian territory and PM2.5 land monitoring data for Kyiv were analyzed. The results showed that NO2 and PM2.5 correlated the most with war activities. CO and O3 levels increased, while SO2 concentrations reduced four-fold as war intensified. Drastic increases in pollution (especially PM2.5) from bombing and structural fires, raise additional health concerns, which might have serious implications for the exposed local and regional populations. This study is an invaluable proof of the impact any armed conflict has on air quality, the population, and environment. © 2022 by the authors.
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