The Signature of the Coronavirus Lockdown in Air Pollution in Greece

Varotsos, C.; Christodoulakis, J.; Kouremadas, George A.; Fotaki, Eleni-Foteini

doi:10.1007/s11270-021-05055-w

Cited by 30 publications

(16 citation statements)

References 21 publications

(18 reference statements)

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“…However, on the contrary, Anand et al (2021a) did not support this idea and directly state this in their paper. In the abstract in the same paper, Zhu et al (2021) concluded: “In recent days, PM exposure could be related as a carrier for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus transmission and Coronavirus disease 2019 (COVID-19) infection.” Ho et al (2021) , citing Setti et al (2020a) : “Second, the SARS-COV-2 virus may spread through the air by attaching to PM2.5/PM10 particles as demonstrated in previous study (35), thereby spreading COVID-19 disease to other people.” Varotsos et al (2021) , citing Setti et al (2020d) : “In addition, the rapid spread of COVID-19 infection in selected areas of northern Italy is believed to be related to PM10 pollution due to airborne particles that may serve as carriers of pathogens ( Setti et al, 2020d ).” Kayalar et al (2021) , citing Setti et al (2020a) : “The only study confirming the presence of virus in atmospheric PM has reported qualitative results (negative or positive) ( Setti et al, 2020b ), . …” …”

Section: Citation Networkmentioning

confidence: 99%

“… Varotsos et al (2021) , citing Setti et al (2020d) : “In addition, the rapid spread of COVID-19 infection in selected areas of northern Italy is believed to be related to PM10 pollution due to airborne particles that may serve as carriers of pathogens ( Setti et al, 2020d ).”…”

Section: Citation Networkmentioning

confidence: 99%

“…54 were involved in spreading the misconception ( Al Huraimel et al, 2020 ; Amoatey et al, 2020 ; Arslan et al, 2020 ; Baron, 2021 ; Borak, 2020 ; Cao et al, 2021 ; Carraturo et al, 2020 ; Chen et al, 2021 ; Coccia, 2020a , b ; Comunian et al, 2020 ; Copat et al, 2020 ; Dettori et al, 2020 ; Domingo and Rovira, 2020 ; Dunker et al, 2021 ; Gaddi and Capello, 2020 ; He and Han, 2021 ; Ho et al, 2021 ; Ingram et al, 2021 ; Kayalar et al, 2021 ; Kumar et al, 2021 ; Linillos-Pradillo et al, 2021 ; Lorenzo et al, 2021 ; Maleki et al, 2021 ; Marquès et al, 2021 ; Martelletti and Martelletti, 2020 ; Mehmood et al, 2021 ; Mukherjee et al, 2021 ; Nor et al, 2021 ; Pegoraro et al, 2021 ; Poyraz et al, 2021 ; Prather et al, 2020 ; Qu et al, 2020 ; Ram et al, 2021 ; Sanità di Toppi et al, 2020 ; Shao et al, 2021 ; Sharma et al, 2020 ; Senatore et al, 2021 ; Setti et al, 2020a -f; Tang et al, 2020 ; Trancossi et al, 2021 ; Tretiakow et al, 2021 ; Tung et al, 2021 ; van der Valk and In 't Veen, 2021 ; Varotsos et al, 2021 ; Wang et al, 2020a , b ; Xu et al, 2020 ; Zhang et al, 2020a , c ; Zhu et al, 2021 ; Zoran et al, 2020 );…”

Section: Citation Networkmentioning

confidence: 99%

See 2 more Smart Citations

“SARS-CoV-2 is transmitted by particulate air pollution”: Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception

Ishmatov

2022

Environmental Research

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In epidemiology, there are still outdated myths associated with the spread of respiratory infections. Recently, we have witnessed the origination of a new misconception, to the effect that SARS-CoV-2 is transmitted in the open air by way of particulate air pollution (atmospheric particulate matter (PM)). There is no evidence to support the idea behind this misconception. Nevertheless, more and more people are involved in animated debate and the number of studies concerning atmospheric PM as a carrier of SARS-CoV-2 is growing rapidly. In this work, the origin of the misconception was investigated, and the published papers which have contributed to the spread of this myth were analyzed. The results show that the following factors lie behind the origin and spread of the misconception: a) The specific terminology is not always clearly defined or consistently used by scientists. In particular, the terms ‘particulate matter’, ‘atmospheric aerosol particles’, ‘air pollutants’, and ‘atmospheric aerosols’ need to be clarified, and besides they are often equated to ‘infectious aerosols’, ‘virus-bearing aerosols’, ‘bio-aerosols’, ‘virus-laden particles’, ‘respiratory aerosol/droplets’, and ‘droplet nuclei’. b) Authors misinterpret statistical data and information from other sources. Interpretation of the correlation between PM levels and the increasing incidence and severity of COVID-19 infection, is often changed from “PM may reflect the indirect action of certain atmospheric conditions that maintain infectious nuclei suspended for prolonged periods, parameters that also act on atmospheric pollutants” to “PM could cause an increase in infectious droplets/aerosols containing SARS-CoV-2.” This is a dramatic change to the meaning. Moreover, it is often not taken into account that PM may reflect activities in areas with high population density and this population density at the same time contributes to the spread COVID-19. c) Skewed citation practices. Many authors cite a hypothetical conclusion from an original study, then other authors cite the papers of these authors as primary sources. This practice leads to the effect that there are many witnesses to a ‘phenomenon’ that did not ever occur. Thus, the terminology used in interdisciplinary communications should be more nuanced and defined precisely. Authors should be more careful when citing unconfirmed data (and hypotheses) as well as in interpreting statistical data so as to avoid confusion and spreading false information. This is especially important now in the era of the COVID-19 pandemic.

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Section: Citation Networkmentioning

confidence: 99%

Section: Citation Networkmentioning

confidence: 99%

Section: Citation Networkmentioning

confidence: 99%

See 1 more Smart Citation

“SARS-CoV-2 is transmitted by particulate air pollution”: Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception

Ishmatov

2022

Environmental Research

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“…In recent years, many previous studies have pointed out that the intensity drastic variation and fragmentation process of the polar vortex will lead to more extreme weather events, such as cold waves and strong snowfall [5][6][7]. Strengthening of polar vortex intensity will lead to low ozone values, which may have a connection with air pollution and extreme weather events [20,21], further causing sudden changes in the global ecological environment and affecting human health. Among the studies on the effect of polar vortex intensity, Baldwin et al [22] pointed out that the breaking and weakening of the polar vortex are accompanied by the rise of stratospheric temperature and potential height, which affect the global weather change on the surface, and the weak polar vortex event also can cause temperature fluctuations in the lower troposphere and cause the Arctic Oscillation (AO) to have a continuous negative phase [12].…”

Section: Introduction 1concept and Research Backgroundmentioning

confidence: 99%

Polar Vortex Multi-Day Intensity Prediction Relying on New Deep Learning Model: A Combined Convolution Neural Network with Long Short-Term Memory Based on Gaussian Smoothing Method

Peng

Cao

Liu

et al. 2021

Entropy

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The variation of polar vortex intensity is a significant factor affecting the atmospheric conditions and weather in the Northern Hemisphere (NH) and even the world. However, previous studies on the prediction of polar vortex intensity are insufficient. This paper establishes a deep learning (DL) model for multi-day and long-time intensity prediction of the polar vortex. Focusing on the winter period with the strongest polar vortex intensity, geopotential height (GPH) data of NCEP from 1948 to 2020 at 50 hPa are used to construct the dataset of polar vortex anomaly distribution images and polar vortex intensity time series. Then, we propose a new convolution neural network with long short-term memory based on Gaussian smoothing (GSCNN-LSTM) model which can not only accurately predict the variation characteristics of polar vortex intensity from day to day, but also can produce a skillful forecast for lead times of up to 20 days. Moreover, the innovative GSCNN-LSTM model has better stability and skillful correlation prediction than the traditional and some advanced spatiotemporal sequence prediction models. The accuracy of the model suggests important implications that DL methods have good applicability in forecasting the nonlinear system and vortex spatial–temporal characteristics variation in the atmosphere.

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“…More importantly, severe air pollution episodes occurred during the COVID-19 period in Beijing, with the highest concentration of PM 2.5 reaching 206 µg m −3 . In contrast, the PM 2.5 concentrations have reduced in China and Italy, with no significant change in Greece and most cities in the USA [8][9][10]. This raises interesting questions as to why pollution is increasing in Beijing but not others, and what the major cause of this heavy air pollution in Beijing where the air pollutant emissions experienced a large reduction is.…”

Section: Introductionmentioning

confidence: 99%

The Occurrence of Heavy Air Pollution during the COVID-19 Outbreak in Beijing, China: Roles of Emission Reduction, Meteorological Conditions, and Regional Transport

Xiao

Shi²,

Cao

et al. 2021

Sustainability

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To prevent the spread of coronavirus disease (COVID-19) and mitigate the epidemic risk, strict lockdown measures were implemented in Beijing during the quarantine period, significantly reducing human activities. However, severe air pollution episodes occurred frequently in Beijing. To explore the occurrence of severe air pollution during the quarantine period, the impacts of emission reductions, meteorological conditions, and regional transport on heavy air pollution were individually evaluated using the Community Multiscale Air Quality (CMAQ) model. Observations showed that the more unfavorable meteorological conditions which occurred during the pandemic as compared to the corresponding 2019 levels, including higher temperature, relative humidity, and frequency of strong southerly winds, and lower HPBL, led to an increase in PM2.5 concentrations. The model results also showed that the meteorological conditions in February 2020 favored PM2.5 formation. The PM2.5 concentrations were mainly dominated by regional transport, which became more significant in the quarantine period than in 2019, suggesting the importance of joint control on regional sources for reducing heavy air pollution. This study highlights that, although the emissions in Beijing and surrounding regions were largely reduced during the quarantine period, severe air pollution in Beijing did not reduce due to the unfavorable meteorological conditions.

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The Signature of the Coronavirus Lockdown in Air Pollution in Greece

Cited by 30 publications

References 21 publications

“SARS-CoV-2 is transmitted by particulate air pollution”: Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception

“SARS-CoV-2 is transmitted by particulate air pollution”: Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception

Polar Vortex Multi-Day Intensity Prediction Relying on New Deep Learning Model: A Combined Convolution Neural Network with Long Short-Term Memory Based on Gaussian Smoothing Method

The Occurrence of Heavy Air Pollution during the COVID-19 Outbreak in Beijing, China: Roles of Emission Reduction, Meteorological Conditions, and Regional Transport

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