Estimates of UV Indices During the Periods of Reduced Ozone Content over Siberia in Winter–Spring 2016

Чубарова, Н. Э.; Timofeev, Yu. M.; Virolainen, Ya. A.; Polyakov, A. V.

doi:10.1134/s1024856019020040

Cited by 11 publications

(4 citation statements)

References 11 publications

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“…But in the metropolitan area it does not exceed the level recommended by Peruvian laws 16 , specifically in the winter season, despite the fact that the general levels are not high compared to those of spring-summer. Ozone is likely to have an impact, even at low concentrations 29 .…”

Section: Methodsmentioning

confidence: 99%

A machine learning approach to analyse ozone concentration in metropolitan area of Lima, Peru

Carbo-Bustinza

Belmonte

Jimenez

et al. 2022

Sci Rep

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The main objective of this study is to model the concentration of ozone in the winter season on air quality through machine learning algorithms, detecting its impact on population health. The study area involves four monitoring stations: Ate, San Borja, Santa Anita and Campo de Marte, all located in Metropolitan Lima during the years 2017, 2018 and 2019. Exploratory, correlational and predictive approaches are presented. The exploratory results showed that ATE is the station with the highest prevalence of ozone pollution. Likewise, in an hourly scale analysis, the pollution peaks were reported at 00:00 and 14:00. Finally, the machine learning models that showed the best predictive capacity for adjusting the ozone concentration were the linear regression and support vector machine.

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Section: Methodsmentioning

confidence: 99%

A machine learning approach to analyse ozone concentration in metropolitan area of Lima, Peru

Carbo-Bustinza

Belmonte

Jimenez

et al. 2022

Sci Rep

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show abstract

“…In recent decades, ozone anomalies in spring have also been observed in the Arctic and adjacent regions. These anomalies are less pronounced and more variable than those in the Antarctic region, but they also contribute to the increase in UV radiation at the surface [4,39] and consequently to the increase in UV index even in midlatitudes [40]. Opposite to the Antarctic, the dynamics in the stratosphere during Arctic winters are some of the major factors that influence the ozone loss in the Arctic springs [41].…”

Section: Analysis Of Ikfs-2 Toc Retrievalsmentioning

confidence: 99%

Six Years of IKFS-2 Global Ozone Total Column Measurements

et al. 2023

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Atmospheric ozone plays an important role in the biosphere’s absorbing of dangerous solar UV radiation and its contributions to the Earth’s climate. Nowadays, ozone variations are widely monitored by different local and remote sensing methods. Satellite methods can provide data on the global distribution of ozone and its anomalies. In contrast to measurement techniques based on solar radiation measurements, Fourier-transform infrared (FTIR) satellite measurements of thermal radiation provide information, regardless of solar illumination. The global distribution of total ozone columns (TOCs) measured by the IKFS-2 spectrometer aboard the “Meteor M N2” satellite for the period of 2015 to 2020 is presented. The retrieval algorithm uses the artificial neural network (ANN) based on measurements of TOCs by the Aura OMI instrument and the method of principal components for representing IKFS-2 spectral measurements. Latitudinal and seasonal dependencies on the ANN training errors are analyzed and considered as a first approximation of the TOC measurement errors. The TOCs derived by the IKFS-2 instrument are compared to independent ground-based and satellite data. The average differences between the IKFS-2 data and the independent TOC measurements are up to 2% (IKFS-2 usually slightly underestimates the other data), and the standard deviations of differences (SDDs) vary from 2 to 4%. At the same time, both the analysis of the ANN approximation errors of the OMI data and the comparison of the IKFS-2 results with independent data demonstrate an increase in discrepancies towards the poles. In the spring–winter period, SDDs reach 8% in the Southern and 6% in the Northern Hemisphere. The technique presented can be used to process the IKFS-2 spectral data, and as a result, it can provide global information on the TOCs in the period of 2015–2020, regardless of the solar illumination and the presence of clouds.

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“…In addition to atmospheric chemistry, the connection between stratospheric O 3 , UV radiation and health effects needs to be addressed in the populated urban environments of Siberia. Chubarova et al (2019b) estimated that the wintertime O 3 depletion in northern regions of Siberia is not critical, but the much larger O 3 reductions observed in the early spring can lead to dangerous levels of erythema UV radiation (see also Sect. 2.4.3, Natural hazards and UV variation).…”

Section: Northern Eurasian Ozone (O 3 )mentioning

confidence: 99%

“…Black carbon emitted by the Siberian forest fires and some other sources and its long-range transport to the Arctic are also widely discussed (Kalogridis et al, 2018;Bondur et al, 2016;Bondur and Ginzburg, 2016;Mikhailov et al, 2017;Breider et al, 2017;Shevchenko et al, 2015;Konovalov et al, 2018;Marelle et al, 2018). In addition, measurements of ozone in the troposphere and stratosphere provide insight into atmospheric chemistry in urban environments , UV radiation and human health (Chubarova et al, 2019b). Environmental health, including the impacts of air quality and UV radiation, is foreseen as a high-momentum research topic in the PEEX domain, and further research is called for in this area.…”

Section: Future Research Needs From the System Perspectivesmentioning

confidence: 99%

Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective

et al. 2022

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Abstract. The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for the rapidly changing Arctic-boreal region. Air quality in China, together with the long-range transport of atmospheric pollutants, was also indicated as one of the most crucial topics of the research agenda. These two geographical regions, the northern Eurasian Arctic-boreal region and China, especially the megacities in China, were identified as a “PEEX region”. It is also important to recognize that the PEEX geographical region is an area where science-based policy actions would have significant impacts on the global climate. This paper summarizes results obtained during the last 5 years in the northern Eurasian region, together with recent observations of the air quality in the urban environments in China, in the context of the PEEX programme. The main regions of interest are the Russian Arctic, northern Eurasian boreal forests (Siberia) and peatlands, and the megacities in China. We frame our analysis against research themes introduced in the PEEX Science Plan in 2015. We summarize recent progress towards an enhanced holistic understanding of the land–atmosphere–ocean systems feedbacks. We conclude that although the scientific knowledge in these regions has increased, the new results are in many cases insufficient, and there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures, especially the lack of coordinated, continuous and comprehensive in situ observations of the study region as well as integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, especially “the enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate climate change” and the “socio-economic development to tackle air quality issues”.

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Estimates of UV Indices During the Periods of Reduced Ozone Content over Siberia in Winter–Spring 2016

Cited by 11 publications

References 11 publications

A machine learning approach to analyse ozone concentration in metropolitan area of Lima, Peru

A machine learning approach to analyse ozone concentration in metropolitan area of Lima, Peru

Six Years of IKFS-2 Global Ozone Total Column Measurements

Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective

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