ArticleAir quality, atmosphere, & health2023
Surface, satellite ozone variations in Northern South America during low anthropogenic emission conditions: a machine learning approach.
Article in Air quality, atmosphere, & health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Response of PMEnvironmental pollution (Barking, Essex : 1987) · 2023Article
- Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
2020 presented the ideal conditions for studying the air quality response to several emission reductions due to the COVID-19 lockdowns. Numerous studies found that the tropospheric ozone increased even in lockdown conditions, but its reasons are not entirely understood. This research aims to better understand the ozone variations in Northern South America. Satellite and reanalysis data were used to analyze regional ozone variations. An analysis of two of the most polluted Colombian cities was performed by quantifying the changes of ozone and its precursors and by doing a machine learning decomposition to disentangle the contributions that precursors and meteorology made to form O Supplementary Information: The online version contains supplementary material available at 10.1007/s11869-023-01303-6.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.