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Increased ozone pollution alongside reduced nitrogen dioxide concentrations during Vienna's first COVID-19 lockdown: Significance for air quality management.

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TLDR
In this article, the authors examined the impact of Vienna's first lockdown on ground-level concentrations of nitrogen dioxide (NO2), ozone (O3) and total oxidant (Ox).
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This article is published in Environmental Pollution.The article was published on 2021-04-15 and is currently open access. It has received 30 citations till now. The article focuses on the topics: Air quality index & Air pollution.

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Impact of COVID-19 Pandemic on Air Quality: A Systematic Review

TL;DR: In this article , a systematic review aimed to identify and discuss the scientifically validated literature that evaluated the impact of the COVID-19 pandemic and associated restrictions on air quality, focusing on the 1st lockdown, comparing with the pre- and post-lockdown periods and usually in urban areas.
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Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia

TL;DR: In this article , the authors investigated changes in mass concentrations of particulate matter (PM) during the Coronavirus Disease of 2019 (COVID-19) lockdown in Croatia.
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Local Integrated Air Quality Predictions from Meteorology (2015 to 2020) with Machine and Deep Learning Assisted by Data Mining

TL;DR: In this article , a newly compiled dataset for 2015 to 2020 covering Dallas County (USA), combining six pollutants into a combined local area benchmark (CLAB), is assessed in terms of eleven meteorological variables.
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Influence of conducive weather on ozone in the presence of reduced NOx emissions: A case study in Chicago during the 2020 lockdowns

TL;DR: This paper analyzed the response of near-surface O 3 in Chicago to the COVID-19 lockdowns using observational data at the surface and from satellite, showing that even though the lockdowns caused NO x emissions to decrease by 18%, Chicago still experienced 17 high O 3 (>70 ppb) days in 2020, and the mean O 3 mixing ratio did not show a significant change in 2020 compared with 2015-2019.
Journal ArticleDOI

Changing Air Quality and the Ozone Weekend Effect during the COVID-19 Pandemic in Toronto, Ontario, Canada

William A. Gough, +1 more
- 15 Mar 2022 - 
TL;DR: In this paper , the authors compared a 10-year (2010-2019) climatology of these pollutants for two monitoring sites in Toronto, Ontario, Canada, coinciding with local lockdown measures during the first wave of the COVID-19 pandemic.
References
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Journal ArticleDOI

Random Forests

TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.

Atmospheric chemistry and physics: from air pollution to climate change.

TL;DR: In this article, the authors present a model for the chemistry of the Troposphere of the atmosphere and describe the properties of the Atmospheric Aqueous phase of single aerosol particles.
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Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015

TL;DR: In this paper, the authors explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels, and estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using nonlinear exposure-response functions spanning the global range of exposure.
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ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R

TL;DR: It is shown that ranger is the fastest and most memory efficient implementation of random forests to analyze data on the scale of a genome-wide association study.
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