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Geoscience and health during the Covid-19 pandemic

The virus is still with us, with more potent variants. It remains the most immediate challenge for geosciences and health, including its impacts on geoscience development (data collection, training, dissemination) and the achievement of the UN Sustainable Development Goals, in particular that urban systems should increase well-being and health.

Long-term visions based on transdisciplinary scientific advances are therefore essential. As a consequence, this session, like the ITS1.1 session in 2021, calls for contributions based on data-driven and theory-based approaches to health in the context of global change. This includes :
- main lessons from lockdowns?
- how to get the best scientific results during a corona pandemic?
- how to manage field works, geophysical monitoring and planetary missions?
- qualitative improvements in epidemic modelling, with nonlinear, stochastic, and complex system science approaches;
- eventual interactions between weather and/or climate factors and epidemic/health problems
- new surveillance capabilities (including contact tracing), data access, assimilation and multidimensional analysis techniques;
- a fundamental revision of our urban systems, their greening and their need for mobility;
- a special focus on urban biodiversity, especially to better manage virus vectors;
- urban resilience must include resilience to epidemics, and therefore requires revisions of urban governance.

Co-organized by AS4/BG8/CL3.2/ESSI4/GI1/NH8, co-sponsored by AGU and AOGS
Convener: Daniel Schertzer | Co-conveners: Tommaso AlbertiECSECS, Klaudia Oleshko, Hongliang Zhang
| Thu, 26 May, 15:55–18:30 (CEST)
Room N1

Thu, 26 May, 15:10–16:40

Chairpersons: Tommaso Alberti, Daniel Schertzer, Hongliang Zhang

Introduction I

Virtual presentation
Jean-Francois Oehler et al.

COVID-19 effects on measurements of the Earth Magnetic Field in the urbanized area of Brest (Brittany, France)

Jean-François OEHLER1, Sylvain LUCAS1, Alexandre LEON1, André LUSVEN1, Gildas DELACHIENNE1

1Shom (Service Hydrographique et Océanographique de la Marine), Brest, France


Since September 2019, Shom’s Magnetic Station (SMS) has been deployed in the north neighbourhoods of the medium-sized city of Brest (Brittany, France, about 210,000 inhabitants). SMS continuously measures the intensity of the Earth Magnetic Field (EMF) with an absolute Overhauser sensor. The main goal of SMS is to derive local external variations of the EMF mainly due to solar activity. These variations consist of low and high parasitic frequencies in magnetic data and need to be corrected. Magnetic mobile stations or permanent observatories are usually installed in isolated areas, far from human activities and electromagnetic effects. It is clearly not the case for SMS, mainly for practical reasons of security, maintenance and data accessibility. However, despite its location in an urbanized area, SMS stays the far western reference station for processing marine magnetic data collected along the Atlantic and Channel coasts of France.

The corona pandemic has had unexpected consequences on the quality of measurements collected by SMS. For example, during the French first lockdown between March and May 2020, the noise level significantly decreased of about 50%. Average standard deviations computed on 1 Hz-time series over 1 min. periods fell from about 1.5 nT to 0.8 nT. This more stable behavior of SMS is clearly correlated with the drop of human activities and traffic in the city of Brest.


Keywords: Shom’s Magnetic Station (SMS), Earth Magnetic Field, COVID19.


How to cite: Oehler, J.-F., Leon, A., Lucas, S., Lusven, A., and Delachienne, G.: COVID-19 effects on measurements of the Earth Magnetic Field in the urbanized area of Brest , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3936, https://doi.org/10.5194/egusphere-egu22-3936, 2022.

Virtual presentation
Peng Wang et al.

Economic activities and the associated emissions have significantly declined during the 2019 novel coronavirus (COVID-19) pandemic, which has created a natural experiment to assess the impact of the emitted precursor control policy on ozone (O3) pollution. In this study, we utilized comprehensive satellite, ground-level observations, and source-oriented chemical transport modeling to investigate the O3 variations during the COVID-19 pandemic in China. Here, we found that the significant elevated O3 in the North China Plain (40%) and Yangtze River Delta (35%) were mainly attributed to the enhanced atmospheric oxidation capacity (AOC) in these regions, associated with the meteorology and emission reduction during lockdown. Besides, O3 formation regimes shifted from VOC-limited regimes to NOx-limited and transition regimes with the decline of NOx during lockdown. We suggest that future O3 control policies should comprehensively consider the effects of AOC on the O3 elevation and coordinated regulations of the O3 precursor emissions.

How to cite: Wang, P., Zhu, S., and Zhang, H.: Comprehensive Insights Into O3 Changes During the COVID-19 From O3 Formation Regime and Atmospheric Oxidation Capacity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4170, https://doi.org/10.5194/egusphere-egu22-4170, 2022.

On-site presentation
Will Drysdale et al.

Since 2020, countries around the world have implemented various interventions in response to a global public health crisis. The interventions included restrictions on mobility, promotion of working from home and the limiting of local and international travel. These, along with other behavioural changes from people in response to the crisis affected various sources of air pollution, not least the transport sector. Whilst the method through which these changes were implemented is not something to be repeated, understanding the effects of the changes will help direct policy for further improving air quality. 


We analysed NOx, O3 and PM2.5 data from many 100s of air quality monitoring sites in urban areas around the world, and examined 2020 in relation to the previous 5 years. The data were examined alongside mobility metrics to contextualise the magnitude of changes and were viewed through the lens of World Health Organisation guidelines as a metric to link air quality changes with human health. Interestingly, reductions in polluting activities did not lead to wholesale improvements in air quality by all metrics due to the more complex processes involved with tropospheric O3 production.


How to cite: Drysdale, W., Stapleton, C., and Lee, J.: Changes in Global Urban Air Quality due to Large Scale Disruptions of Activity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9812, https://doi.org/10.5194/egusphere-egu22-9812, 2022.

On-site presentation
Shubham Sharma et al.

The COVID-19 lockdowns worldwide provided a prospect to evaluate the impacts of restricted movements and emissions on air quality. In this study, we analyze the data obtained from the ground-based observation stations for six air pollutants (PM10, PM2.5, CO, NO2, O3 and SO2) and meteorological parameters from March 25th to May 31st in 22 cities representative of five regions of India and from March 16th to May 14th in 21 districts of Finland from 2017 to 2020. The NO2 concentrations dropped significantly during all phases apart from East India's exception during phase 1. O3 concentrations for all four phases in West India reduced significantly, with the highest during Phase 2 (~38%). The PM2.5 concentration nearly halved across India during all phases except South India, where a very marginal reduction (2%) was observed during Phase 4. SO2 (~31%) and CO (~41%) concentrations also reduced noticeably in South India and North India during all the phases. The air temperature rose by ~10% (average) during all the phases across India when compared to 2017-2019. In Finland, NO2 concentration reduced substantially in 2020. Apart from Phase 1, the concentrations of PM10 and PM2.5 reduced markedly in all the Phases across Finland. Also, O3 and SO2 concentrations stayed within the permissible limits in the study period for all four years but were highest in 2017 in Finland, while the sulfurous compounds (OSCs) levels increased during all the phases across Finland. The changes in the mobility patterns were also assessed and were observed to have reduced significantly during the lockdown. The benefits in the overall mortality due to the reduction in the concentrations of PM2.5 have also been estimated for India and Finland. Therefore, this research illustrates the effectiveness of lockdown and provides timely policy suggestions to the regulators to implement interventions to improve air quality.

How to cite: Sharma, S., Heibati, B., Suneja, J., and Kota, S. H.: The Effects of COVID-19 Lockdown on Air Quality and Health in India and Finland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9213, https://doi.org/10.5194/egusphere-egu22-9213, 2022.

Changes of air quality and its associated health and economic burden in 31 provincial capital cities in China during COVID-19 pandemic
Xinlei Ge and Dongyang Nie
Virtual presentation
Weijun Li and Liang Xu

Black carbon (BC) not only warms the atmosphere but also affects human health. The nationwide lockdown due to the COVID-19 pandemic led to a major reduction in human activity during the past thirty years. Here, the concentration of BC in the urban, urban-industry, suburb, and rural areas of a megacity Hangzhou were monitored using a multi-wavelength Aethalometer to estimate the impact of the COVID-19 lockdown on BC emissions. The citywide BC decreased by 44% from 2.30 μg/m3 to 1.29 μg/m3 following the COVID-19 lockdown period. The source apportionment based on the Aethalometer model shows that vehicle emission reduction responded to BC decline in the urban area and biomass burning in rural areas around the megacity had a regional contribution of BC. We highlight that the emission controls of vehicles in urban areas and biomass burning in rural areas should be more efficient in reducing BC in the megacity Hangzhou.

How to cite: Li, W. and Xu, L.: Responses of concentration and sources of black carbon in a megacity during the COVID-19 pandemic, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12907, https://doi.org/10.5194/egusphere-egu22-12907, 2022.

Virtual presentation
Yangzi Qiu et al.

In the last few decades, Nature-based Solutions (NBS) has become widely considered a sustainable development strategy for the development of urban environments. Assessing the performances of NBS is significant for understanding their efficiency in addressing a large range of natural and societal challenges, such as climate change, ecosystem services and human health. With the rapid onset of the COVID-19 pandemic, the inner relationship between humans and nature becomes apparent. However, the current catchment management mainly focuses on reducing hydro-meteorological and/or climatological risks and improving urban climate resilience. This single-dimensional management seems insufficient when facing epidemics, and multi-dimensional management (e.g., reduce zoonosis) is necessary. With this respect, policymakers pay more attention to NBS. Hence, it is significant to increase the connectivity of the landscape to improve the ecosystem services and reduce the health risks from COVID-19 with the help of NBS.

This study takes the Guyancourt catchment as an example. The selected catchment is located in the Southwest suburb of Paris, with a total area of around 5.2 km2. The ArcGIS software is used to assess the patterns of structural landscape connectivity, and the heterogeneous spatial distribution of current green spaces over the catchment is quantified with the help of the scale-independent indicator of fractal dimension. To quantify opportunities to increase landscape connectivity over the catchment, a least-cost path approach to map potential NBS links urban green spaces through vacant parcels, alleys, and smaller green spaces. Finally, to prioritise these potential NBS in multiscale, a new scale-independent indicator within the Universal Multifractal framework is proposed in this study.

The results indicated that NBS can effectively improve the connectivity of the landscape and has the potential to reduce the physical and mental risks caused by COVID-19. Overall, this study proposed a scale-independent approach for enhancing the multiscale connectivity of the NBS network in urban areas and providing quantitative suggestions for on-site redevelopment.

How to cite: Qiu, Y., Tchiguirinskaia, I., and Schertzer, D.: Nature-based Solutions in actions: improving landscape connectivity during the COVID-19, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5126, https://doi.org/10.5194/egusphere-egu22-5126, 2022.

Thu, 26 May, 17:00–18:30

Chairpersons: Daniel Schertzer, Tommaso Alberti, Klaudia Oleshko

On-site presentation
Michael Ghil

For many of us, the Covid-19 pandemic brought long-time scientific interest in epidemiology to the point of involvement. An important aspect of the evolution of acute respiratory epidemics is their seasonal character. Our toolkit for handling seasonal phenomena in the geosciences has increased in the last dozen years or so with the development and application of concepts and methods from the theory of nonautonomous and random dynamical systems (NDSs and RDSs). In this talk, I will briefly:

  • Introduce some elements of these two closely related theories.

  • Illustrate the two with an application to seasonal effects within a chaotic model of the El

    Niño–Southern Oscillation (ENSO).

  • Introduce to a geoscientific audience a simple epidemiological “box” model of the

    Susceptible–Exposed–Infectious–Recovered (SEIR) type.

  • Summarize NDS results for a chaotic SEIR model with seasonal effects.

  • Mention the utility of data assimilation (DA) tools in the parameter identification and

    prediction of an epidemic’s evolution


    - Chekroun, M D, Ghil M, Neelin J D (2018) Pullback attractor crisis in a delay differential ENSO model, in Nonlinear Advances in Geosciences, A. Tsonis (Ed.), Springer, pp. 1–33, doi: 10.1007/978-3-319-58895-7

    - Crisan D, Ghil, M (2022) Asymptotic behavior of the forecast–assimilation process with unstable dynamics, Chaos, in preparation

    - Faranda D, Castillo I P, Hulme O, Jezequel A, Lamb J S, Sato Y, Thompson E L (2020) Asymptotic estimates of SARS-CoV-2 infection counts and their sensitivity to stochastic perturbation<? Chaos, 30(5): 051107, doi: 10.1063/5.0009454

    - Ghil, M (2019) A century of nonlinearity in the geosciences. Earth & Space Science 6:1007–1042, doi:10.1029/2019EA000599

    - Kovács, T (2020) How can contemporary climate research help understand epidemic dynamics? Ensemble approach and snapshot attractors. J. Roy. Soc. Interface, 17(173):20200648, doi: 10.1098/rsif.2020.0648

How to cite: Ghil, M.: Time-dependent forcing in the geosciences and in epidemiology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13522, https://doi.org/10.5194/egusphere-egu22-13522, 2022.

M. Ghil's Invited Talk additional time

On-site presentation
Jean-Baptiste Renard et al.

The time evolution of the Covid-19 death cases exhibits several distinct episodes since the start of the pandemic early in 2020. We propose an analysis of several Southern Europe regions that highlights how the beginning of each episode correlates with a strong increase in the concentrations level of pollution particulate matter smaller than 2.5 µm (PM2.5). Following the original PM2.5 spike, the evolution of the Covid-19 spread depends on the (partial) lockdowns and vaccinate races, thus the highest level of confidence in correlation can only be achieved when considering the beginning of each episode. The analysis is conducted for the 2020-2022 period at different locations: the Lombardy region (Italy), where we consider the mass concentrations measurements obtained by air quality monitoring stations (µg.m-3), and the cities of Paris (France), Lisbon (Portugal) and Madrid (Spain) using in-situ measurements counting particles (cm-3) in the 0.5-2.5 µm size range obtained with hundreds of mobile aerosol counters. The particle counting methodology is more suitable to evaluate the possible correlation between PM pollution and Covid-19 spread because we can better estimate the concentration of the submicronic particles compared with a mass concentration measurement methodology which would result in skewed results due to larger particles. Very fine particles of lesser than one micron go deeper inside the body and can even cross the alveolar-capillary barrier, subsequently attacking most of the organs through the bloodstream, potentially triggering a pejorative systemic inflammatory reaction. The rapidly increasing number of deaths attributed to the covid-19 starts between 2 weeks and one month after PM events that often occur in winter, which is coherent with the virus incubation time and its lethal outcome. We suggest that the pollution by the submicronic particles alters the pulmonary alveoli status and thus significantly increase the lungs susceptibility to the virus.

How to cite: Renard, J.-B., Delaunay, G., Poincelet, E., and Surcin, J.: Possible effect of the particulate matter (PM) pollution on the Covid-19 spread in southern Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1890, https://doi.org/10.5194/egusphere-egu22-1890, 2022.

On-site presentation
Davide Faranda

In the past two years, numerous advances have been made in the ability to predict the progress of COVID19 epidemics.  Basic forecasting of the health state of a population with respect to a given disease is based on the well-known family of SIR models (Susceptible Infected Recovered). The models used in epidemiology were based on deterministic behavior, so the epidemiological picture tomorrow depends exclusively on the numbers recorded today. The forecasting shortcomings of the deterministic SEIR models previously used in epidemiology were difficult to highlight before the advent of COVID19  because epidemiology was mostly not concerned with real-time forecasting.  From the first wave of COVID19 infections, the limitations of using deterministic models were immediately evident: to use them, one should know the exact status of the population and this knowledge was limited by the ability to process swabs. Futhermore, there is an intrinsic variability of the dynamics which depends on age, sex, characteristics of the virus, variants and vaccination status. 

Our main contribution was to define a SEIR model that assumes these parameters as constants could not be used for reliable predictions of COVID19 pandemis and that more realistic forecasts can be obtained by adding fluctuations in the model. The fluctuations in the dynamics of the virus induced by these factors do not just add variaiblity around the deterministic solution of the SIR models, the also introduce another timing of the pandemics which influence the epidemic peak. With our model we have found that even with a basic reprdocution number Rt less than 1 local epidemic peaks can occur that resume over a certain period of time. 

Introducing noise and uncertainty allows  to define a range of possible scenarios, instead of making a single prediction. This is what happens when we replace the deterministic approach, with a probabilistic approach. The probabilistic models used to predict the progress of the Covid-19 epidemic are conceptually very similar to those used by climatologists, to imagine future environmental scenarios based on the actions taken in the present.  As human beings we can intervene in both systems. Based on the choices we will make and the fluctuations of the systems, we can predict different responses. In the context of the emergency that we faced, the collaboration between different scientific fields was therefore fundamental, which, by comparing themselves, were able to provide more accurate answers. Furthermore, a close collaboration has arisen between epidemiologists and climatologists. A beautiful synergy that can give a great help to society in a difficult moment.


-Faranda, Castillo, Hulme, Jezequel, Lamb, Sato & Thompson (2020). Chaos: An Interdisciplinary Journal of Nonlinear Science30(5), 051107.

-Alberti & Faranda (2020).  Communications in Nonlinear Science and Numerical Simulation90, 105372.

-Faranda & Alberti (2020). Chaos: An Interdisciplinary Journal of Nonlinear Science30(11), 111101.

-Faranda, Alberti, Arutkin, Lembo, Lucarini. (2021).  Chaos: An Interdisciplinary Journal of Nonlinear Science31(4), 041105.

-Arutkin, Faranda, Alberti, & Vallée. (2021). Chaos: An Interdisciplinary Journal of Nonlinear Science31(10), 101107.

How to cite: Faranda, D.: How concepts and ideas from Statistical and Climate physics improve epidemiological modelling of the COVID 19 pandemics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2801, https://doi.org/10.5194/egusphere-egu22-2801, 2022.

D. Faranda's Invited Talk additional time

On-site presentation
Ioulia Tchiguirinskaia and Daniel Schertzer

Defining optimal COVID-19 mitigation strategies remains at the top of public health agendas around the world. It requires a better understanding and refined modeling of the intrinsic dynamics of the epidemic. The common root of most models of epidemics is a cascade paradigm that dates to their emergence with Bernoulli and d’Alembert, which predated Richardson’s famous quatrain on the cascade of atmospheric dynamics. However, unlike other cascade processes, the characteristic times of a cascade of contacts that spread infection and the corresponding rates are believed to be independent on the cascade level. This assumption prevents having cascades of scaling contamination.

In this presentation, we theoretically argue and empirically demonstrate that the intrinsic dynamics of the COVID-19 epidemic during the phases of growth and decline, is a cascade with a rather universal scaling, the statistics of which differ significantly from those of an exponential process. This result first confirms the possibility of having a higher prevalence of intrinsic dynamics, resulting in slower but potentially longer phases of growth and decline. It also shows that a fairly simple transformation connects the two phases. It thus explains the frequent deviations of epidemic models rather aligned with exponential growth and it makes it possible to distinguish an epidemic decline from a change of scaling in the observed growth rates. The resulting variability across spatiotemporal scales is a major feature that requires alternative approaches with practical consequences for data analysis and modelling. We illustrate some of these consequences using the now famous database from the Johns Hopkins University Center for Systems Science and Engineering.

Due to the significant increase over time of available data, we are no longer limited to deterministic calculus. The non-negligible fluctuations with respect to a power-law can be easily explained within the framework of stochastic multiplicative cascades. These processes are exponentials of a stochastic generators Γ(t), whose stochastic differentiation remains quite close to the deterministic one, basically adding a supplementary term σdt to the differential of the generator. When the generator Γ(t) is Gaussian, σ is the “quadratic variation”. Extensions to Lévy stable generators, which are strongly non-Gaussian, have also been considered. To study the stochastic nature of the cascade generator, as well as how it respects the above-mentioned symmetry between the phases of growth and decline, we use the universal multifractals. They provide the appropriate framework for joint scaling analysis of vector-valued time series and for introducing location and other dependencies. This corresponds to enlarging the domain, on which the process and its generator are defined, as well as their co-domain, on which they are valued. These clarifications should make it possible to improve epidemic models and their statistical analysis.

More fundamentally, this study points out to a new class of stochastic multiplicative cascade models of epidemics in space and time, therefore not limited to compartments. By their generality, these results pave the way for a renewed approach to epidemics, and more generally growth phenomena, towards more resilient development and management of our urban systems.

How to cite: Tchiguirinskaia, I. and Schertzer, D.: Scaling Dynamics of Growth Phenomena: from Epidemics to the Resilience of Urban Systems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11475, https://doi.org/10.5194/egusphere-egu22-11475, 2022.

On-site presentation
Tommaso Alberti and Davide Faranda

COVID-19 waves, mostly due to variants, still require timely efforts from governments based on real-time forecasts of the epidemics via dynamical and statistical models. Nevertheless, less attention has been paid in investigating and characterizing the intrinsic and extrinsic spatio-temporal dynamics of the epidemic spread. The large amount of data, both in terms of data points and observables, allows us to perform a detailed characteristic of the epidemic waves and their relation with different sources as testing capabilities, vaccination policies, and restriction measures.

By taking as a case-study the epidemic evolution of COVID-19 across Italian regions we perform the Hilbert-Huang Transform (HHT) analysis to investigate its spatio-temporal dynamics. We identified a similar number of temporal components within all Italian regions that can be linked to both intrisic and extrinsic source mechanisms as the efficiency of restriction measures, testing strategies and performances, and vaccination policies. We also identified mutual scale-dependent relations within different regions, thus suggesting an additional source mechanisms related to the delayed spread of the epidemics due to travels and movements of people. Our results are also extremely helpful for providing long term extrapolation of epidemics counts by taking into account both the intrinsically and the extrinsically non-linear nature of the underlying dynamics. 

How to cite: Alberti, T. and Faranda, D.: COVID-19 waves: intrinsic and extrinsic spatio-temporal dynamics over Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12302, https://doi.org/10.5194/egusphere-egu22-12302, 2022.

On-site presentation
Tamás Kovács

Standard epidemic models based on compartmental differential equations are investigated under continuous parameter change as external forcing. We show that seasonal modulation of the contact parameter superimposed upon a monotonic decay needs a different description from that of the standard chaotic dynamics. The concept of snapshot attractors and their natural distribution has been adopted from the field of the latest climate change research. This shows the importance of the finite-time chaotic effect and ensemble interpretation while investigating the spread of a disease. By defining statistical measures over the ensemble, we can interpret the internal variability of the
epidemic as the onset of complex dynamics—even for those values of contact parameters where originally regular behaviour is expected. We argue that anomalous outbreaks of the infectious class cannot die out until transient chaos is presented in the system. Nevertheless, this fact becomes apparent by using an ensemble approach rather than a single trajectory representation. These findings are applicable generally in explicitly time-dependent epidemic systems regardless of parameter values and time scales.

How to cite: Kovács, T.: How can contemporary climate research help understand epidemic dynamics? -- Ensemble approach and snapshot attractors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13534, https://doi.org/10.5194/egusphere-egu22-13534, 2022.

T. Kovács's Invited Talk additional time

Virtual presentation
Xia Meng et al.

The Coronavirus (COVID-19) epidemic, which was first reported in December 2019 in Wuhan, China, has been becoming one of the most important public health issues worldwide. Previous studies have shown the importance of weather variables and air pollution in the transmission or prognosis of infectious diseases, including, but not limited to, influenza and severe acute respiratory syndrome (SARS). In the early stage of the COVID-19 epidemic, there was intense debate and inconsistent results on whether environmental factors were associated with the spread and prognosis of COVID-19. Therefore, our team conducted a series studies to explore the associations between atmospheric parameters (temperature, humidity, UV radiation, particulate matters and nitrogen dioxygen) and the COVID-19 (transmission ability and prognosis) at the early stage of the COVID-19 epidemic with data in early 2020 in China and worldwide. Our results showed that meteorological conditions (temperature, humidity and UV radiation) had no significant associations with cumulative incidence rate or R0 of COVID-19 based on data from 224 Chinese cities, or based on data of 202 locations of 8 countries before March 9, 2020, suggesting that the spread ability of COVID-19 among public population would not significantly change with increasing temperature or UV radiation or changes of humidity. Moreover, we found that particulate matter pollution significantly associated with case fatality rate (CFR) of COVID-19 in 49 Chinese cities based on data before April 12, 2020, indicating that air pollution might exacerbate negative prognosis of COVID-19. Our studies provided an environmental perspective for the prevention and treatment of COVID-19.

How to cite: Meng, X., Yao, Y., Wang, W., and Kan, H.: The associations between environmental factors and COVID-19: early evidence from China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5150, https://doi.org/10.5194/egusphere-egu22-5150, 2022.

Digital Habitat: Green, Healthy, Sustainable
Valerie Livina
Virtual presentation
Ghislain Motos et al.

Recurrent epidemic outbreaks such as the seasonal flu and the ongoing COVID-19 are disastrous events to our societies both in terms of fatalities, social and educational structures, and financial losses. The difficulty to control COVID-19 spread in the last two years has brought evidence that basic mechanisms of transmission for such pathogens are still poorly understood.

             Three different routes of virus transmission are known: direct contact (e.g. through handshakes) and indirect contact through fomites; ballistic droplets produced by speaking, sneezing or coughing; and airborne transmission through aerosols which can also be produced by normal breathing. The latter route, which has long been ignored, even by the World Health Organization during the COVID-19 pandemics, now appears to play the predominant role in the spread of airborne diseases (e.g. Chen et al., 2020).

             Further scientific research thus needs to be conducted to better understand the mechanistic processes that lead to inactivate airborne viruses, as well as the environmental conditions which favour these processes. In addition to modelling and epidemiological studies, chamber experiments, where viruses are exposed to various types of humidity, temperature and/or UV dose, offer to simulate everyday life conditions for virus transmission. However, the current standard instrumental solutions for virus aerosolization to the chamber and sampling from it use high fluid forces and recirculation which can cause infectivity losses (Alsved et al., 2020) and also do not compare to the relevant production of airborne aerosol in the respiratory tract.

             In this study, we utilized two of the softest aerosolization and sampling techniques: the sparging liquid aerosol generator (SLAG, CH Technologies Inc., Westwood, NJ, USA), which forms aerosol from a liquid suspension by bubble bursting, thus mimicking natural aerosol formation in wet environments (e.g. the respiratory system but also lakes, sea, toilets, etc…); and the viable virus aerosol sampler (BioSpot-VIVAS, Aerosol Devices Inc., Fort Collins, CO, USA), which grows particle via water vapour condensation to gently collect them down to a few nanometres in size. We characterized these systems with particle sizers and biological analysers using non-pathogenic viruses such as bacteriophages suspended in surrogate lung fluid and artificial saliva. We compared the size distribution of produced aerosol from these suspensions against similar distributions generated with standard nebulizers, and assess the ability of these devices to produce aerosol that much more resembles that produced in human exhaled air. We also assess the conservation of viral infectivity with the VIVAS vs. conventional biosamplers.




We acknowledge the IVEA project in the framework of SINERGIA grant (Swiss National Science Foundation)




Alsved, M., Bourouiba, L., Duchaine, C., Löndahl, J., Marr, L. C., Parker, S. T., Prussin, A. J., and Thomas, R. J. (2020): Natural sources and experimental generation of bioaerosols: Challenges and perspectives, Aerosol Science and Technology, 54, 547–571.

Chen, W., Zhang, N., Wei, J., Yen, H.-L., and Li, Y. (2020): Short-range airborne route dominates exposure of respiratory infection during close contact, Building and Environment, 176, 106859.

How to cite: Motos, G., Violaki, K., Schaub, A., David, S., Kohn, T., and Nenes, A.: Improving the conservation of virus infectivity during airborne exposure experiments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3690, https://doi.org/10.5194/egusphere-egu22-3690, 2022.

Virtual presentation
Ulrich Pöschl et al.

The public and scientific discourse on how to mitigate the COVID-19 pandemic is often focused on the impact of individual protective measures, in particular on vaccination. In view of changing virus variants and conditions, however, it seems not clear if vaccination or any other protective measure alone may suffice to contain the transmission of SARS-CoV-2. Accounting for both droplet and aerosol transmission, we investigated the effectiveness and synergies of vaccination and non-pharmaceutical interventions like masking, distancing & ventilation, testing & isolation, and contact reduction as a function of compliance in the population. For realistic conditions, we find that it would be difficult to contain highly contagious SARS-CoV-2 variants by any individual measure. Instead, we show how multiple synergetic measures have to be combined to reduce the effective reproduction number (Re) below unity for different basic reproduction numbers ranging from the SARS-CoV-2 ancestral strain up to measles-like values (R0 = 3 to 18).

Face masks are well-established and effective preventive measures against the transmission of respiratory viruses and diseases, but their effectiveness for mitigating SARS-CoV-2 transmission is still under debate. We show that variations in mask efficacy can be explained by different regimes of virus abundance (virus-limited vs. virus-rich) and are related to population-average infection probability and reproduction number. Under virus-limited conditions, both surgical and FFP2/N95 masks are effective at reducing the virus spread, and universal masking with correctly applied FFP2/N95 masks can reduce infection probabilities by factors up to 100 or more (source control and wearer protection).

Masks are particularly effective in combination with synergetic measures like ventilation and distancing, which can reduce the viral load in breathing air by factors up to 10 or more and help maintaining virus-limited conditions. Extensive experimental studies, measurement data, numerical calculations, and practical experience show that window ventilation supported by exhaust fans (i.e. mechanical extract ventilation) is a simple and highly effective measure to increase air quality in classrooms. This approach can be used against the aerosol transmission of SARS-CoV-2. Mechanical extract ventilation (MEV) is very well suited not only for combating the COVID19 pandemic but also for sustainably ventilating schools in an energy-saving, resource-efficient, and climate-friendly manner.  Distributed extract ducts or hoods can be flexibly reused, removed and stored, or combined with other devices (e.g. CO2 sensors), which is easy due to the modular approach and low-cost materials (www.ventilationmainz.de).

The scientific findings and approaches outlined above can be used to design, communicate, and implement efficient strategies for mitigating the COVID-19 pandemic.


Cheng et al., Face masks effectively limit the probability of SARS-CoV-2 transmission, Science, 372, 1439, 2021, https://doi.org/10.1126/science.abg6296 

Klimach et al., The Max Planck Institute for Chemistry mechanical extract ventilation (MPIC-MEV) system against aerosol transmission of COVID-19, Zenodo, 2021, https://doi.org/10.5281/zenodo.5802048  

Su et al., Synergetic measures to contain highly transmissible variants of SARS-CoV-2, medRxiv, 2021, https://doi.org/10.1101/2021.11.24.21266824


How to cite: Pöschl, U., Cheng, Y., Helleis, F., Klimach, T., and Su, H.: Efficiency and synergy of simple protective measures against COVID-19: Masks, ventilation and more, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1024, https://doi.org/10.5194/egusphere-egu22-1024, 2022.

U. Pöschl's Invited Talk additional time

On-site presentation
Michalis Chiotinis et al.

The COVID-19 pandemic has brought forth the question of the need for draconian interventions before concrete evidence for their need and efficacy is presented. Such interventions could be critical if necessary for avoiding threats, or a threat in themselves if harms caused by the intervention are significant.

The interdisciplinary nature of such issues as well as the unpredictability of various local responses considering their potential for global impact further complicate the question.

The study aims to review the available evidence and discuss the problem of weighting the predictability of interventions vis-à-vis their intended results against the limits of knowability regarding complex non-linear systems and thus the predictability in non-interventionist approaches.

How to cite: Chiotinis, M., Dimitriadis, P., Illiopoulou, T., Mamassis, N., and Koutsoyiannis, D.: To act or not to act. Predictability of intervention and non-intervention in health and environment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11747, https://doi.org/10.5194/egusphere-egu22-11747, 2022.

On-site presentation
Daniel Schertzer et al.

There have been a series of sessions on the generic theme of “Covid-19 and Geosciences” on the occasion of AGU, AOGS and EGU conferences, since 2020 including during the first lockdown that required a very fast adaptation to unprecedented health measures. We think it is interesting and useful to have an overview of these sessions and try to capture what could be the lessons to learn.

To our knowledge, the very first such session was the Great e-Debate “Epidemics, Urban Systems and Geosciences” (https://hmco.enpc.fr/news-and-events/great-e-debate-epidemics-urban-systems-and-geosciences-invitations-and-replays/). It was virtually organised with the help of the UNESCO UniTwin CS-DC (Complex Systems Digital Campus) thanks to its expertise in organising e-conferences long before the pandemic and the first health measures. This would not have been possible without the strong personal involvement of its chair Paul Bourgine. It was held on Monday 4th May on the occasion of the 2020 EGU conference, which became virtual under the title “EGU2020: Sharing Geoscience Online” (4-8 May 2020). The Great e-Debate did not succeed in being granted as an official session of this conference, despite the fact that the technology used (Blue Button) by the Great e-Debate was much more advanced. Nevertheless, it was clearly an extension of the EGU session ITS2.10 / NP3.3: “Urban Geoscience Complexity: Transdisciplinarity for the Urban Transition”. 

Thanks to a later venue (7-11 December 2020) and the existence of a GeoHealth section of the AGU, the organisation of several regular sessions for the 2020 Fall Meeting was easier. For EGU 2021 (19-30 April 2021), a sub-part of the  inter- transdisciplinary sessions ITS1 “Geosciences and health during the Covid pandemic”, a Union Session US “Post-Covid Geosciences” and a Townhall meeting TM10 “Covid-19 and other epidemics: engagement of the geoscience communities” were organised. A brief of the special session SS02 “Covid-19 and Geoscience” of the (virtual) 18th Annual Meeting of AOGS (1-6 August 2021) is included in the proceedings of this conference (in press). 

We will review materials generated by these sessions that rather show a shift from a focus on the broad range of scientific responses to the pandemic, to which geoscientists could contribute with their specific expertise (from data collection to theoretical modelling), to an expression of concerns about the broad impacts on the geophysical communities that appear to be increasingly long-term and constitute a major transformation of community functioning (e.g., again data collection, knowledge transfer).

How to cite: Schertzer, D., Dimri, V., and Fraedrich, K.: Geophysicists facing Covid-19 , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11584, https://doi.org/10.5194/egusphere-egu22-11584, 2022.

Session wrap-up