One of the most challenging sustainable goals of the UN 2030 Agenda and other international agreements is that urban systems have to increase well-being and health. Indeed, these networked systems already host more than half of the world's population and are going to host most of its growth, while they have been mostly designed and managed with limited visions, in particular with respect to their geophysical environment.
This goal got an unforeseen acuity with the Covid-19 pandemic, starting with the confinement strategies that radically brought into question the functioning of these systems, e.g., drastically reducing mobility and breaking its ever increasing trend. Covid-19 was not without precursor (e.g., SARS, MERS) and will not be without successors.
Long term visions based on transdisciplinary scientific advances are therefore indispensable, particularly from the geoscience community. As a consequence, this session calls for contributions from data-driven and theory-driven approaches of urban health under global change. This includes:
- qualitative improvements of epidemic modelling, as trans-disciplinary and nonlinear as possible
- possible interplays between meteorological and/or climate drivers and epidemic/health issues
- novel monitoring capabilities (including contacts tracking), data access, assimilation and multidimensional analysis techniques
- managing field works, geophysical monitoring and planetary missions
- how to have the highest science output during corona pandemic
- a fundamental revision of our urban systems, their greening as well as their mobility offer
- a particular focus on urban biodiversity, in particular to better manage virus vectors
- urban resilience must include resilience to epidemics, and therefore requires revisions of urban governance.
Related to ITS1:
- Union Session US2 "PostCovid Geosciences" Friday 23 April 15:00-17:00
- Town Hall meeting TM10 "Covid-19 and other epidemics: engagement of the geoscience communities", Wednesday 28 April 17:30-19:00
ZOOM data will be displayed in the program 15 min. prior to the meeting
please suggest on https://www.surveymonkey.com/r/5KZ3NYV
- a special issue of Nonlinear Processes in Geophysics is foreseen
- Union Session US2 "PostCovid Geosciences" Friday 23 April 15:00-17:00
- Town Hall meeting TM10 "Covid-19 and other epidemics: engagement of the geoscience communities", Wednesday 28 April 17:30-19:00
ZOOM data will be displayed in the program 15 min. prior to the meeting
please suggest on https://www.surveymonkey.com/r/5KZ3NYV
- a special issue of Nonlinear Processes in Geophysics is foreseen
vPICO presentations: Thu, 29 Apr
In this PICO, we outline methods used to inventory the spatial distribution and characteristics of COVID-19 response activities (‘interventions’) in Kibera (Nairobi, Kenya). About 1/8 of the World’s Population live in slums and informal settlements. For these people, COVID-19 has presented unique challenges for managing health and livelihoods within the constraints of high-density housing and poor-quality infrastructure. In addition, reliable spatial, demographic and health data is often limited for these areas. Between April and July 2020, using the Survey123 smartphone application, combined with social media searches and phone enumeration, we inventoried 270 individual COVID-19 interventions taking place in Kibera, an informal settlement of 2.67 km2 and an estimated 187,000 to 1 000,000 inhabitants. Results show a large variety in the type of intervention (58 unique types) and organiser (>88 individual organisers), with 39% of interventions led by small scale organisations such as local NGOs and community groups. We found an uneven spatial distribution of interventions within Kibera, with some already underserved neighbourhoods having less access to COVID-19 relief. Many interventions are clustered around the limited open spaces with good accessibility by road, highlighting the need for better coordination between organisers, and the importance of open space for resilience building. Using isochronal service area analysis, we find that 80% of structures are within a 9-minute round trip of a handwashing station. However, 64% of structures have a 24-54 minute round trip to female sanitary supplies, illustrating gender differences in the impact and recovery from COVID-19. Our data is available online in an interactive map dashboard. Our survey results illustrate that rather than being seen as vectors of disease, low income urban neighbourhoods are part of the solution for managing pandemics, and highlight the importance of infrastructure upgrading and planning to build resilience to a range of shocks and stresses.
How to cite: Taylor, F., Talib, M., Wandera, A., Mulligan, J., Bukachi, V., Drummond, J., Malamud, B., and Pelling, M.: Remote data collection methods to inventory COVID-19 interventions in low-income urban settlements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2198, https://doi.org/10.5194/egusphere-egu21-2198, 2021.
Human-natural processes that generate extreme events with large financial, social, and health consequences, are inherently non-stationary due to ever-changing anthropogenic pressures and societal exposure. The issues posed by non-stationarity are recognized and addressed in Earth system science. However, extensive epidemiological information remains fragmented and virtually unexplored from this perspective due to the lack of approaches to leverage observations of a heterogeneous past. To address this gap, we assembled a long historical record (1600-present) of infectious disease epidemics from the literature. This new record enabled the development and applications of methods to quantify the time-varying probability of occurrence of extreme epidemic events. We define the intensity of epidemic events, the number of deaths/time/global population, and find that observations from several hundred years, covering almost four orders of magnitude of epidemic intensity, follow a probability distribution with a slowly-decaying power-law tail (Generalized Pareto Distribution, asymptotic exponent = -0.705). To the contrary, the yearly number of epidemics is non-stationary, implying that conventional extreme value analyses are inappropriate. We find that the rate of occurrence of extreme epidemics varies nine-fold over centennial time scales, from about 0.4 to 3.6 epidemics/year. As a result, yearly occurrence probabilities of extreme epidemics are far from constant: The intensity computed for the most extreme event on record – the “Spanish Influenza” of 1918-1920 – has a probability of occurrence varying from 0.27 to 1.75 %/year in the time frame from 1600 to present. When optimistically assuming that 1 year is required to develop, produce, and begin distributing a vaccine/treatment for a new disease (e.g. the recent COVID-19 case), we estimate that the average recurrence time of a pandemic killing most of the global population is now less than 12,000 years.
How to cite: Marani, M., Katul, G., Pan, W., and Parolari, A.: Intensity and frequency of extreme novel epidemics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9227, https://doi.org/10.5194/egusphere-egu21-9227, 2021.
The COVID-19 pandemic has made urgent the need to improve the resilience of urban system from the effects of different hazards (natural, biological, technological and slow-onset climate change-related) through a multi hazard and multi sector approach that allows a more efficient use of resources and a holistic view of risk, including the interconnectedness across multiple hazards. According to Bangkok Principles for the implementation of the health aspects of the Sendai Framework for Disaster Risk Reduction 2015-2030, systematic integration of health aspects in Disaster Risk Reduction strategies is undelayable.
Building urban resilience means identifying vulnerabilities rapidly and adopting adequate actions to anticipate, resist and recover with the least amount of damage in front hazards impacts.
In this context, a synthetic index to measure vulnerability to COVID-19 is developed, by integrating different levels of information related to demographic characteristics, health profiles and access to resources, in order to identify any situations of fragility and predisposition to the spread of the epidemic, thus constituting a support element for the adoption of an efficient intervention strategy and for the management of any new epidemic waves. The integrated and multi-disciplinary approach that has been chosen allows, indeed, to take into account the complexity and multi-disciplinary nature of the concept of vulnerability. The following information are analysed: demographic characteristics (population density, age, residence in welfare and prisons facilities); health profiles (presence of previous chronic diseases, such as cancer, diabetes, heart disease, lung disease, and particular lifestyles, such as smoking, alcohol consumption, poor diet) and characteristics of the local health infrastructure (number of beds, ratio of population to family doctor, number of health facilities in the area). To construct the vulnerability index, a Geographical Information System is setted up, through which the data are analysed, processed through normalisation, given the different availability and heterogeneity of the information, and combined. The resulting spatial data infrastructure allows us to rapidly identify situations of adversities and possible infrastructural deficiencies.
The first prototypical result provides the implementation of an index of vulnerability to COVID19 and the related information support system, related to the metropolitan area in central Tuscany, in which there is a good availability of open data at different levels of geographical details and for which research on vulnerability to various types of risk is carried out and in progress.
How to cite: Pileggi, T., Cioli, S., and Caporali, E.: Vulnerability mapping to Covid-19 of the metropolitan area in central Tuscany , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12677, https://doi.org/10.5194/egusphere-egu21-12677, 2021.
The current Covid-19 pandemic has underlined the need to thoroughly revisit our conceptions of managing and developing urban systems and to make them resilient to epidemics. For instance, it fundamentally questions the long-held goal of continually increasing human mobility. More generally, the definition of optimal Covid-19 mitigation strategies remains worldwide on the top of public health agendas, especially in the face of a second wave. However, the relevance of resilient strategies depends heavily on our understanding and our ability to model epidemic dynamics.
Epidemic models are phenomenologically based on the paradigm of a cascade of contacts that spreads infection. However, scaling -a fundamental characteristic that easily results from cascade models,- is not taken into account by conventional epidemic models. The introduction of ad-hoc characteristic times and corresponding rates spuriously break their scale symmetry.
Here, we theoretically argue and empirically demonstrate that Covid-19 dynamics, during both growth and decline phases, is a cascade with a rather universal scale symmetry whose power-law statistics drastically differ from those of exponential processes. This implies slower but longer phases; which are furthermore linked by a fairly simple symmetry. The resulting variability across space-time 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 Johns Hopkins University Center for Systems Science and Engineering database.
The obtained results explain biases of epidemic models and help to improve them. By virtue of their generality, these results pave the way for a renewed approach to epidemics, and more generally to growth phenomena, towards more resilient development and management of our urban systems.
How to cite: Schertzer, D. and Tchiguirinskaia, I.: Covid-19: What about Resilience and Scaling Dynamics?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13488, https://doi.org/10.5194/egusphere-egu21-13488, 2021.
As we move towards the more critical age of technology and learning, understanding the underlying dynamics of events such as the unforeseen and unpredictable pandemics in the ecological system are deemed invaluable and important. In this paper, using acquired observations of daily cases of CoVid-19 in the US, UK and some parts of Asia, Recurrence Quantification Analysis (RQA) and the plots of state space were constructed. In this study, it was found that some countries have shown similar trends in RQA statistics as compared to classic chaotic attractors and functions while others have shown similar state space plots as that of the other countries. The authors believe that the data currently available worldwide does not allow reliable forecast because of the presence of untested asymptomatic cases, therefore construction of the evolution of the CoVid-19 cases signal in the absence of priori knowledge of other factors as well as analysing the RQA statistics can serve as a starting point as well as provide information for the appropriate prediction method for the prevalent CoVid-19 outbreaks.
How to cite: Necesito, I., Kim, D., Lee, J., Eom, J., Kim, D.-W., and Kim, H. S.: Understanding CoVid-19’s chaotic dynamics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14008, https://doi.org/10.5194/egusphere-egu21-14008, 2021.
COVID-19 has forced quarantine measures in several countries across the world. These measures have proven to be effective in significantly reducing the prevalence of the virus. To date, no effective treatment or vaccine is available. In the effort of preserving both public health as well as the economical and social textures, France and Italy governments have partially released lockdown measures. Here we extrapolate the long-term behavior of the epidemics in both countries using a Susceptible-Exposed-Infected-Recovered (SEIR) model where parameters are stochastically perturbed with a log-normal distribution to handle the uncertainty in the estimates of COVID-19 prevalence and to simulate the presence of super-spreaders. Our results suggest that uncertainties in both parameters and initial conditions rapidly propagate in the model and can result in different outcomes of the epidemics leading or not to a second wave of infections. Furthermore, the presence of super-spreaders adds instability to the dynamics, making the control of the epidemics more difficult. Using actual knowledge, asymptotic estimates of COVID-19 prevalence can fluctuate of order of ten millions units in both countries.
How to cite: Faranda, D. and Alberti, T.: Modelling the second wave of COVID-19 infections in France and Italy via a Stochastic SEIR model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2615, https://doi.org/10.5194/egusphere-egu21-2615, 2021.
Faced with the first Covid-19 epidemic wave in France, the hospital sector has been forced to considerably increase the number of intensive care beds. To meet this crucial need, some hospital structures have been adapted. This is the case with one of the intensive care sectors of the Burn Treatment Center (CTB) at Saint-Louis Hospital, which has intensive care rooms dedicated to treat burn patients. Beyond the provision and adaptation of these care structures to Covid patients, the hospital has currently an imperative need to progress on the understanding of the dispersion of buccopharyngeal droplets which constitute one of the risk vectors of airborne transmission and as a corollary of manual transmission.
As part of a partnership between CTB and the EDF Foundation, a CEREA research team provided the hospital with its aeraulics expertise which mainly relies on the digital modelling tool (CFD) code_saturne developed for more than 20 years by EDF-Research and Development. Numerical modelling in fluid mechanics makes it possible to accurately reproduce an architectural ensemble, to describe the air flows and what they carry, and thus to better understand where the risks of airborne contamination lie.
The objective of the study is to understand the dispersion of the buccopharyngeal droplets in the resuscitation room according to their sizes, identify the areas at risk of deposit, adapt the treatment protocols and optimise the level and the frequency of systematic bio-cleaning of surfaces exposed to deposit of oral-pharyngeal droplets. It should be noted that we are not directly dealing with the spread of the covid-19 virus but with one of the potential vehicles of oral-pharyngeal droplets.
The methodology consist of a parametric study of poly-dispersion of classes of particles. Each class correspond to a droplet diameter and contains one million of independent droplets for which a Generalized Langevin Model is solved to calculate the instantaneous fluid velocity seen from the particle, the particle velocity and its position. These particles are carried by a turbulent flow using the Reynolds Averaged Navier-Stokes approach, calculating only moments. The specific characteristics of this model allow dealing with poly-dispersed two-phase flow even for particles with very small diameters. The studied parameters are the angle of droplet ejection, the volume of humid air ejected and the time duration of this event and the air flowing activation of the room.
Expected conclusions are found: the largest particles sediment the fastest and close to the source, the finest droplets follow the streamlines to the air vents. In addition, non-intuitive areas of potential deposit are observed and a major impact of air conditioning on residence time is demonstrated.
How to cite: Ferrand, M., Guingo, M., Beauchêne, C., Mimoun, M., and Minier, J.-P.: Modelling buccopharyngeal droplet dispersion in an intensive care unit for Covid patients, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7187, https://doi.org/10.5194/egusphere-egu21-7187, 2021.
The COVID-19 pandemic has highlighted the importance of public health policies and crisis management. The spread of diseases is a complex phenomenon with many time-dependent variables, which hampers an accurate prediction of epidemic evolution. Models of epidemic spread play an important role in guiding in designing public health policies, enabling hypothetical scenarios simulation and rapid analyses of ongoing epidemics.
Over the last century disease spread models evolved from deterministic compartmental models into complex metapopulation and agent-based simulations. Today’s solutions consider many factors, not limiting to the disease itself but also simulating socio-demographic structure and population flows. In the era of globalisation, human mobility became the major factor of rapid disease spread. Although current models consider international and regional travels, used mobility models are simplistic. This limits the accuracy and spatio-temporal resolution of these simulations, providing daily cases updates aggregated to large regions.
We propose an agent-based mobility model, offering a simulation of hourly temporal resolution depicting mobility with less than a few hundreds of meters spatial precision. Agent-based models allow each simulation agent to assign different characteristics, e.g. susceptibility to infection, mobility behaviour.
We integrate our mobility model with disease spread simulation, using an agent’s interaction to detect virus transmission. In every time step of the model, the interaction between the agents, their current state and localisation of interaction are used to determine the probability of infection. Social interactions in the context of the spread of the disease are a fundamental element influencing the temporal and spatial extent of the disease. An essential aspect of our model is the integration of the simulation environment with the points-of-interests (POIs), which represent the destination of the majority of non-home-work related activities. We validate the accuracy of mobility replication and present hypothetical scenarios of disease spread in one of the large European cities, presenting capabilities of our solution.
How to cite: Knop, K., Smolak, K., Kasieczka, B., Rohm, W., Smolarczyk, T., and Zyga, M.: Mobility modelling for simulation of spatial spread of infectious diseases, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13112, https://doi.org/10.5194/egusphere-egu21-13112, 2021.
Our work is aimed at analyzing the intrinsic variability of epidemic compartmental models, including the main qualitative characteristics of the Covid-19 pandemic, such as a relatively long asymptomatic contagious incubation period and a time-limited immunity. Intrinsic variability is important in order to quantitatively distinguish it from extrinsic variation factors, such as variability of virulence, social behavior, weather and climate, or statistical interpretation of data. The influence of vaccination rates is also analyzed, in as far as different scenarios may avert or revert the existence of an asymptotic endemic equilibrium point, as well as contribute to the build-up of herd immunity.
How to cite: Carsteanu, A. A. and Langousis, A.: Epidemic compartmental models: Realizations for Covid-19 and the bearing of vaccination scenarios, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13720, https://doi.org/10.5194/egusphere-egu21-13720, 2021.
While COVID-19 is rapidly propagating around the globe, the need for providing real-time forecasts of the epidemics pushes fits of dynamical and statistical models to available data beyond their capabilities. Here we focus on statistical predictions of COVID-19 infections performed by fitting asymptotic distributions to actual data. By taking as a case-study the epidemic evolution of total COVID-19 infections in Chinese provinces and Italian regions, we find that predictions are characterized by large uncertainties at the early stages of the epidemic growth. Those uncertainties significantly reduce after the epidemics peak is reached. Differences in the uncertainty of the forecasts at a regional level can be used to highlight the delay in the spread of the virus. Our results warn that long term extrapolation of epidemics counts must be handled with extreme care as they crucially depend not only on the quality of data, but also on the stage of the epidemics, due to the intrinsically non-linear nature of the underlying dynamics. These results suggest that real-time epidemiological projections should include wide uncertainty ranges and urge for the needs of compiling high-quality datasets of infections counts, including asymptomatic patients.
Alberti T. and Faranda D. (2020) On the uncertainty of real-time predictions of epidemic growths: A COVID-19 case study for China and Italy. Commun. Nonlin. Sci. Num. Sim., 90, 105372.
How to cite: Alberti, T. and Faranda, D.: On the uncertainty of real-time predictions of epidemic growths: A COVID-19 case study for China and Italy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2742, https://doi.org/10.5194/egusphere-egu21-2742, 2021.
More than a year since its emergence, there is conflicting evidence on the potential influence of weather conditions on SARS-CoV-2 transmission dynamics. We used a two-stage ecological modelling approach to estimate weather-dependent signatures in SARS-CoV-2 transmission in the early phase of the pandemic, using a dataset of 3 million COVID-19 cases reported until 31 May 2020, spanning 409 locations in 26 countries. We calculated the effective reproduction number (Re) over a location-specific early-phase time-window of 10-20 days, for which local transmission had been established but before non-pharmaceutical interventions had become established as measured by the OxCGRT Government Response Index. We calculated mean levels of meteorological factors, including temperature and humidity observed in the same time window used to calculate Re. Using a multilevel meta-regression approach, we modelled nonlinear effects of meteorological factors, while accounting for government interventions and socio-demographic factors. A weak non-monotonic association between temperature, absolute humidity and Re was identified, with a decrease in Re of 0.087 (95% CI: 0.025; 0.148) between mean temperature of 10.2°C (maximum) and 20°C (minimum) and a decrease in Re of 0.061 (95% CI: 0.011; 0.111) between absolute humidity of 6.6 g/m3 (maximum) and 11 g/m3 (minimum). However, government interventions explained twice as much of the variation in Re compared meteorological factors. We find little evidence of meteorological conditions having influenced the early stages of local epidemics, and conclude that population behaviour and governmental intervention are more important drivers of transmission.
How to cite: Lowe, R., Armstrong, B., Abbott, S., Meakin, S., O'Reilly, K., Von Borries, R., Schneider, R., Roye, D., Hashizume, M., Pascal, M., Tobias, A., Vicedo-Cabrera, A. M., Gasparrini, A., and Sera, F. and the MCC Network & CMMID COVID-19 working group: Analysis of the potential drivers of seasonality in COVID-19 transmission dynamics in 409 locations across 26 countries , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8955, https://doi.org/10.5194/egusphere-egu21-8955, 2021.
This research is a general reflection of the possible transmission not only of COVID-19 but of any influenza disease depending on environmental parameters such as solar radiation, air humidity and air temperature (vapor pressure deficit), evoking the Penman-Monteith model regarding the evaporation of the water that constitutes the small water droplets (aerosols) that carry the virus. In this case the evapotranspiration demand of the atmosphere with which it can be deduced that the spread of the disease will be higher in those places with less evaporative demand, that is, high air humidity and / or low temperatures, and / or low radiation intensities, and vice versa. It can also be deduced that the hours of greatest potential contagion are the night hours, while those with the lowest risk are between 2:00 p.m. and 4:00 p.m. On the other hand, in those rooms with low temperatures the contagion would be more effective. So, considering that the drops produced by a sneeze, by speaking or breathing can go beyond two meters away, it is roughly explained that the use of face masks and keeping a safe minimum distance of two meters can limit transmission of viruses and / or infections. However, this practice is not entirely safe as the environment can play an important role. What is recommended to reduce the spread of these pathogens is to produce high evaporative demands: increasing solar radiation, and increasing air temperature and reducing air humidity, which is practice that can be effective in closed rooms.
How to cite: Barradas, V. L. and Ballinas, M.: A reflexion on the environmental effect on the transmission of COVID-19, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10284, https://doi.org/10.5194/egusphere-egu21-10284, 2021.
The warmest July ever in Portugal was observed during 2020, leading to the highest number of total deaths in July months (10430) since consistent records became available in 2009. This record summed up to the very high death toll throughout the year, characterized by the COVID-19 pandemic. As a combined result of these factors, cumulated deaths during 2020 are also the largest in the records available since 2009 (123753), corresponding to an excess of ~12000 deaths (~11% above the baseline). COVID-19 was responsible for the largest fraction of anomalous mortality during the spring months (62% of the excess during March-May) and from autumn onwards (85% of the excess during October-December). However, during the warmer season, the direct impact of the pandemic decreased substantially (as in the rest of Europe) and other causes were the main trigger for the observed excessive mortality (~3500 versus 553 COVID-19 deaths). Prolonged hot spells, occurring between June 21 and August 7, triggered persistent mortality anomalies in the upper tertile (>310 deaths/day) reaching its peak in mid-July (+45% deaths/day). Two other shorter hot spells occurring outside summer months (May and September) also appear to have contributed to significant mortality anomalies.
July 2020 registered an overall temperature anomaly of +2.6ºC over continental Portugal, and a cumulated anomaly of +127ºC. The lethality rate associated to these cumulated anomalies (+14 deaths per cumulated ºC) was higher than that observed in recent relevant heat-related mortality episodes, even those with higher absolute temperature anomalies, such as in 2013 and 2018. Rates comparable to those observed in 2020 in Portugal are only found far back in tragic heatwaves like those experienced in June 1981 or August 2003. In fact, the 2003 European heatwaves triggered significant changes in public health policies, in order to minimize the mortality burden associated to hot spells, which resulted in lower lethality rates, until 2020. These results are further supported by a statistical model developed to estimate expected deaths due to cold/heat (calibrated for 2009-2019: r=0.84; ME=7%), estimating an amplification of at least 50% in heat-related deaths during 2020 compared to pre-pandemic years. We argue that the significant decrease observed in emergency admissions (ER) and disruption in health-care since the start of the pandemic helps explaining this amplification factor. A ~2/3 decrease in total ERs was observed at the peak of the COVID-19 crisis, never returning to normal pre-pandemic levels. Furthermore, in average cases classified as emergent and very urgent in triage remained below 80% of previous reference levels throughout the 2020 summer, particularly the latter.
The authors would like to acknowledge the financial support FCT through project UIDB/50019/2020 – IDL.
How to cite: Sousa, P. M., Trigo, R. M., Russo, A., Geirinhas, J. L., Rodrigues, A., Silva, S., and Torres, A.: Heat-related mortality in Portugal amplified during the COVID-19 pandemic, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12733, https://doi.org/10.5194/egusphere-egu21-12733, 2021.
Lockdowns to avoid the spread of COVID-19 have created an unprecedented reduction in human emissions, however emissions estimates are typically only available after one or more years, making it hard to incorporate these reductions into emissions projections. In this talk we will outline how mobility data and power usage can nowcast country-and-sector emissions of various gases. In this way we show that the short-term impact of lockdown on emissions data is not expected to be significant for long-term temperature trends.
We will also outline how different recovery pathways can be made using basic longer-term emissions projections and how to construct detailed scenarios for non-CO2 emissions, using assumptions about the effects of lockdown on nationally determined contributions and a new software package called Silicone that can infill missing greenhouse gas emissions. Silicone allows the consistent incorporation of tradeoffs between emission species as modelled by IAMs, and as expressed in available greenhouse gas emission scenarios, to be applied to the proposed pathways. We will then show how to make these projections into the more detailed, gridded, CMIP-6 compatible emissions estimates that are required to run General Circulation Models (GCM).
How to cite: Lamboll, R., Forster, P., Jones, C., Skeie, R., Fiedler, S., Samset, B., and Rogelj, J.: Modifying emissions data and projections to incorporate the effects of lockdown in climate modelling, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-42, https://doi.org/10.5194/egusphere-egu21-42, 2020.
On 11 March 2020, the World Health Organization declared Covid19 a pandemic. Countries around the world rushed to declare various states of emergencies. Canada also implemented emergency measures to restrict the movements of people including the closure of borders, non-essential services, and schools and offices to slow the spread of Covid19. I used this opportunity to measure changes in seismic vibrations registered in Canada before, during, and after the lockdown due to the slowdown in transportation, economic, and construction activities. I analyzed continuous seismic data for 6 Canadian cities: Calgary and Edmonton (Alberta), Montreal (Quebec), Ottawa, and Toronto (Ontario), and Yellowknife (Northwest Territories). These cities represented the wide geographical spread of Canada. The source of data was seismic stations run by the Canadian National Seismograph Network (CNSN). Python and ObSpy libraries were used to convert raw data into probabilistic power spectral densities. The seismic vibrations in the PPSDs that fell between 4 Hz and 20 Hz were extracted and averaged for every two weeks period to determine the trend of seismic vibrations. The lockdown had an impact on seismic vibrations in almost all the cities I analyzed. The seismic vibrations decreased between 14% - 44% with the biggest decrease in Yellowknife in the Northwest Territories. In the 3 densely populated cities with a population of over 1 million - Toronto, Montreal, and Calgary, the vibrations dropped by over 30%.
To enable other students to undertake similar projects for their cities, I created a comprehensive online training module using Jupyter notebooks available on Github. Students can learn about seismic vibrations, how to obtain datasets, and analyze and interpret them using Python. They can share their findings with local policymakers so that they become aware of the effectiveness of the lockdown imposed and are better prepared for lockdowns in the future. When we make data and technology accessible, then lockdowns because of pandemics can be an opportunity for students to take up practical geoscience projects from home or virtual classrooms.
How to cite: Nath, A.: Using COVID19 as an Opportunity to Measure Seismic Silences and Bring Geoscience Projects to Students, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1268, https://doi.org/10.5194/egusphere-egu21-1268, 2021.
The lockdown measures taken to control and stop the spread of the novel coronavirus (COVID-19) in cities around the globe caused an unprecedented reduction of anthropic activities. The signature of this reduction, different from one place to another, has been captured by the seismic stations installed in the urban areas where lockdown restrictions have been implemented. Bucharest, the capital of Romania, was no exception from this phenomenon.
In this paper, we investigate the effect of the COVID-19 lockdown measures imposed by the Romanian authorities on the high-frequency ambient seismic noise (ASN) data recorded by the Bucharest Metropolitan Seismic Network (BMSN). BMSN consists of 26 stations of which 19 are equipped with strong motion sensors and 7 have both short-period velocity and accelerometer sensors. All the stations are continuously recording the ground motion and the data is sent in real-time to the data center of the National Institute for Earth Physics.
The reduction of ASN was first observed at stations installed in educational units (kindergartens, schools) starting with 11th of March 2020, when the Romanian government decided to close the schools in Romania. For these stations, the largest reduction of ASN, up to 82%, was noticed in the 25-40 Hz frequency band. On 16th of March the state of emergency was imposed in Romania and a few days later, on 25th of March, the stay-at-home order was issued. These new restrictions caused substantial reduction in urban traffic and people’s mobility and reflected in significant reduction of ASN at almost all the other BMSN stations, located either free-field or in buildings. For these stations, we observed a decrease of the noise levels by as much as 66% in the 15-25 Hz frequency band. We also correlated the ambient seismic noise with other types of data that might be affected by human activity, such as the mobility data from Google and Apple, and we found good correlation between ASN in different frequency bands and various mobility data categories. Finally, we showed that the noise reduction due to lockdown measures improved the signal-to-noise ratio of the stations in the Bucharest area, allowing us to record smaller earthquakes which otherwise would not have been recorded.
How to cite: Grecu, B., Tiganescu, A., Poiata, N., Borleanu, F., Dinescu, R., and Tataru, D.: The impact of the COVID-19 lockdown measures on the seismic monitoring in the Bucharest (Romania) metropolitan area, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8385, https://doi.org/10.5194/egusphere-egu21-8385, 2021.
Ecuador, with a population of approximately 17.08 million inhabitants, is one of the most COVID-19 affected countries in the world. On March 16th, 2020, a countrywide state of exception was declared by the national government, therefore applying measures to restrict mobility, suspension of working hours and closure of borders. This situation caused an increase in the massive demand for masks and gloves as the primary ways to preventing infection. These masks and gloves are single-used and discarded, causing an impact on the environment due to the time they take to decompose. In addition, syringes and other hospital may also become infectious waste.
Although hospitals may comply the regulations for the management and treatment of hazardous solid waste in Ecuador, the health emergency surprised all hospitals, clinics and health centers due to the increase in patients with coronavirus. This situation led to the establishment of new protocols for this type of waste and also for the management of corpses with COVID-19.
Health personnel are the ones that have been most affected during this time, so they have been working on the front line and have been the most exposed to contagion, increasing the use of disposable masks, gloves and gowns and contributing to the increase of waste from hospitals and health centers.
The objective of this study is to investigate and understand how the management of hospital waste has been developed in times of pandemic in the Ecuadorian Institute of Social Security (IESS) Manuel Ignacio Monteros in the city of Loja.
To carry out this study, information are taken from the records and databases generated in the IESS about the amount of hospital waste generated during the months of March to December 2020. Results are obtained making comparisons with the amount of hospital waste generated in the previous year 2019. The information was collected through surveys directed both to medical and administrative personnel who were in direct care of COVID-19 managing operations.
Results show that a considerable increase in the quantity and characteristics of hospital waste generated during the months of analysis was found. Hazardous hospital waste have been managed correctly as established by various protocols and agreements (Ministerial Agreement 0323) in full compliance with current legislation.
How to cite: Ponce Ochoa, K. E., Rodrigo-Ilarri, J., and Rodrigo-Clavero, M.-E.: Sanitary waste management under Covid-19 restrictions in Ecuador, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9346, https://doi.org/10.5194/egusphere-egu21-9346, 2021.
In 2020, the entire world population has witnessed an unprecedented virus outbreak in terms of COVID-19, which led to restrictions in human activities across the world. Strict measures in Germany started on March-21, 2020 and ended on April-30, 2020, while more relaxed measures continued until July 2020. Vehicle traffic volume and industrial activities were drastically reduced, and, as a result, pollutant emission rates were expected to be reduced. Changes in atmospheric pollutant concentrations are an indicator for changes in emission rates although they are not directly proportional as concentrations are heavily influenced by meteorological conditions and as atmospheric photochemical reactions can be non-linear. Without accounting for the influence of meteorology and atmospheric photochemical reactions, a simple comparison of the lockdown period pollutant concentration values with pre-lockdown only to estimate emissions could be misleading. To normalize the effects of meteorological conditions and atmospheric chemical transformation and reactions, we adopted a method of comparing the predicted Business As Usual (BAU) NO2 and O3 concentrations, i.e., the expected value of NO2 and O3 concentration for 2020 meteorological conditions without lockdown restrictions, with the observed NO2 and O3 concentrations. BAU NO2 and O3 concentrations corresponding to 2020 meteorological conditions were predicted based on wind speed and sunshine duration (and season of the day) using the previous year NO2 and O3 concentrations as the references. Compared to BAU levels, big metropolitan cities in Germany show a decline in observed NO2 level (-24.5 to -37.7 %) in the strict lockdown period and rebound to the BAU level at the end of July 2020. In contrast, there is a marginal change in O3 level (+9.6 to -7.4 %). We anticipate that the imbalanced changes in precursors emission (decrease in NOX and increase in volatile organic compounds (VOCs) emission) are attributed to the marginal changes in observed O3 level compared to BAU level; decreased NOX would decrease the O3 concentration due to NOX-limited conditions, and increased VOCs would increase the O3 concentration. These results imply that the balanced emission control between the VOCs and NOX are required to limit the secondary pollutant (O3) formation.
How to cite: Balamurugan, V., Bi, X., Gensheimer, J., Chen, J., Keutsch, F., Bhattacharjee, S., and Shekhar, A.: Impacts of COVID-19 lockdown restrictions on urban NO2 and O3 level in Germany with consideration of meteorological impacts and seasonal variation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12035, https://doi.org/10.5194/egusphere-egu21-12035, 2021.
Covid-19 pandemic has led to severe consequences to humanity worldwide. Yet, to our knowledge, little scientific evidence is available exploring the impact of the pandemic on criminality. Thus, it is imperative to examine their relationships spatially to obtain a better understanding of societal characteristics during the pandemic.
This study aims at demonstrating the use of geoinformation in analyzing the spatial patterns between crime properties and Covid-19 spread using as a case study New York City, USA, one of the largest metropolitan cities of the world. To address our objectives, geostatistical analysis and data visualization methods have been implemented in real-world crime data acquired from a web-GIS platform. Our analysis concerns two equal time periods before and after the lockdown implementation.
Results revealed some very interesting patterns spatially between the examined parameters and societal characteristics existing in the study region. The methodological framework presented underlined the added value of geoinformation as a robust and cost-effective approach in examining the impact of the pandemic to the society.
Keywords: Covid-19, pandemic, crime rates, geoinformation, New York
How to cite: Tselka, I., Demertzi, I. I., and Petropoulos, G. P.: Investigating the effects of COVID-19 to crime rates through a geospatial approach: the case of New York, USA, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15125, https://doi.org/10.5194/egusphere-egu21-15125, 2021.
Quantitative monitoring of CO2 sources and sinks over cities is needed to support the urban adaptation and mitigation measures, but it is a challenging task. The Paris metropolitan area is a highly built-up and densely populated region in France. The two national COVID-19 forced confinements that are 1) effective on March 17th, with a duration of 55 days until May 11th, 2) effective on October 30th, with a duration of 46 days until December 15th provide an opportunity to assess the behaviour and robustness of the dedicated atmospheric inversion system for estimating the city-scale CO2 emissions.
In this study, the atmospheric Bayesian inversion approach that couples six in-situ continuous CO2 monitoring stations with the WRF-Chem transport model at 1-km horizontal resolutions has been used to quantify the impacts of lockdown on CO2 emissions for the Paris megacity. The prior emission estimate was from the Origins inventory, a near-real-time dataset of fossil fuel CO2 emissions by sector (transportation, residential, tertiary, industry and sink) at 1km² and hourly resolution recently developed by Origins.earth. Estimates of CO2 emissions were retrieved from the inversion by assimilating CO2 concentration gradients between upwind-downwind stations using a refined configuration of the existing Parisian inversion system developed by Bréon et al. (2015) and Staufer et al. (2016). A set of experiments was performed to assess the sensitivity of the posterior CO2 estimates to the changes in different inversion setups, including the selection of observations, prior flux uncertainties and error correlations. We also analyzed the potential contribution of the expanding CO2 monitoring network, in particular the two newly built urban stations in the city center since 2014, to the inverse modeling systems.
The optimized CO2 estimates show decreases of around 42% and 25% in anthropogenic CO2 emissions during the first and second lockdowns respectively when compared with the same period in past two years. Both lockdown emission reduction estimates from the inversion are consistent with recent estimates from activity data (resp. 37% and 19%), suggesting that our near-real time monitoring system is able to detect and quantify short-term variations at the whole-city level.
How to cite: Lian, J., Lauvaux, T., Utard, H., Broquet, G., Bréon, F.-M., Ramonet, M., Laurent, O., Cucchi, K., and Ciais, P.: Assessing the effectiveness of an urban CO2 monitoring network through the COVID-19 lockdown natural experiment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16098, https://doi.org/10.5194/egusphere-egu21-16098, 2021.
The COVID-19 pandemic has changed the way we work and live, and as of January 2020, the increase in cases and the initiation of the vaccine introduces even more uncertainty into the short-term future. With an increase in domestic responsibilities for many people, there is a heighted concern about the productivity of the Earth and space science research community, and especially the impact on student, early career researchers, and women. AGU's rich data has allowed us to investigate how the pandemic has affected our constituents, and in a poster presented at AGU 2020, we showed that submissions increased in 2020 with the same proportion of women submitting in 2020 and little monthly variation. Submissions from men and women in their 20s decreased in 2020 compared to 2019, while submissions from women in their 30s and 50s and men in their 40s increased. We saw minor monthly fluctuations in submissions by the country-region of submitting author, with an increase in total and proportional submissions from China continuing from 2019. Additionally, our editors were concerned about the time the most affected scientists could devote to research and peer reviewing. This analysis seeks to update demographics of submitting authors with Q1 2021 data and introduce an analysis of the effect the pandemic had on our article peer reviewers. Preliminary analysis shows very little difference in the invite rates of women in 2020 compared to 2019 (+1%), and only a 0.4% decrease in women's accept to review rates in 2020 compared to 2019. We also only see slight monthly fluctuations in invite and review accept rates. Invitations to review by country of reviewer are proportionally similar in 2020 to those in 2019. This analysis will also investigate any changes in invited and agreed reviewer age to see how the pandemic may have influenced those likely to have research, teaching, and family commitments.
How to cite: Wooden, P. and Hanson, B.: Geoscience Authors and Reviewers during the COVID-19 Pandemic: Demographic Analysis of AGU's Authors and Peer Reviewers, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1229, https://doi.org/10.5194/egusphere-egu21-1229, 2021.
Epidemics, climate change and natural hazards are increasingly affecting humankind and are plausibly re-shaping the way in which people perceive multiple risks. Here we integrate epidemiological, policy, climate and natural hazard data with the results of two waves of nationwide surveys in Italy and Sweden. These were conducted in two different phases of the COVID-19 pandemic corresponding to low (August 2020) and high (November 2020) levels of infection rates. We investigate the interplay between negative impacts and public perceptions of multiple hazards including epidemics, floods, droughts, wildfires, earthquakes, and climate change. Similarities and differences between Italy and Sweden allow us to investigate the role of policy, media coverage, and direct experience in explaining public perceptions of multiple hazards. The way in which people think about epidemics, for example, is expected to have been substantially influenced by the COVID-19 pandemic that has severely affected both countries, but to which the Italian and Swedish authorities responded differently. Indeed, we found that epidemics are perceived as less likely and more impactful in Italy compared to Sweden. In addition, when multiple hazards are considered, people are more worried about risks related to recently occurred events. This is in line with the cognitive process known as availability heuristic: individuals assess the risk associated with a given hazard based on how easily it comes to their mind. Furthermore, for the majority of hazards, we found that in both countries women and younger people are generally more concerned. These new insights about the interplay between multiple hazards and public perceptions can inform the development of sustainable policies to reduce disaster risk while promoting public health.
How to cite: Di Baldassarre, G., Mondino, E., and Raffetti, E.: Epidemics, climate change and natural hazards: Impacts and risk perceptions under COVID-19, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2408, https://doi.org/10.5194/egusphere-egu21-2408, 2021.
The COVID-19 pandemic is a wake-up call for water security issues. It makes us acutely aware how crucial access, and ability, for adequate hand hygiene are for reducing transmission risks of communicable diseases. An estimated 40% of households globally lack access to basic handwashing facilities. A recent cross-cultural study of household water insecurity experiences (HWISE) found that nearly one in four of 6,637 randomly sampled households across 23 sites in 20 low- and middle-income countries. Similar water, sanitation and hygiene problems impact on poorer families in high-income nations too.
We explore the challenge of hand hygiene in a changing water world and reflect on the importance of making rapid progress towards “ensure availability and sustainable management of water and sanitation for all” (UN Sustainable Development Goal 6). We contest that urgent action on water security is essential to better prepare societies for the future, including global health crises. Drawing on the latest evidence, we provide recommendations on how to increase handwashing, and improve human health and wellbeing more broadly, by reducing water insecurity. Across our world, policymakers must focus on: investment in water infrastructure, water independent alternatives, and behavioural change and knowledge promotion. Moreover, we must prioritise holistic, evidence-based solutions that address 3 facets of water (in)security: availability, quality & accessibility.
How to cite: Hannah, D. M., Lynch, I., Mao, F., Miller, J. D., Young, S. L., and Krause, S.: Handwashing and water security in the context of a pandemic, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10438, https://doi.org/10.5194/egusphere-egu21-10438, 2021.
During COVID – 19 pandemic, the main strategy to prevent virus dissemination adopted worldwide was the social distancing, in different degrees (ranging from simple recommendations to the population, to complete lockdown). In this context, many studies were performed around the world to assess the impacts of such measures on the environment, specially on air quality. The reported results almost unanimously pointed to a reduction in air contaminants, mainly as a response to vehicular traffic depletion and, at some level, to reduced human and industrial activities. On March 24th, 2020, a partial lockdown was decreed in São Paulo state, Brazil, and since then it has undergone, back and forth, several stages of strictness according to contamination and hospitalization rates, being stricter whenever intensive care units (ICU) occupation increased. Our study aims to evaluate environmental aspects (air quality and meteorology) in Campinas city (São Paulo, Brazil), during the pandemic, from March 24th to December 31st, and compare it with the weeks prior to the social distancing and with the previous year. In addition to the environmental variables, the “social distancing index” (obtained by using mobile phone data to assess displacements) and medical data (hospital admissions and deaths) were employed to a preliminary analysis of the influence of environmental factors on COVID – 19 evolution in the city.
How to cite: Kabke Bainy, B. and Heuminski de Ávila, A. M.: Environmental factors during COVID – 19 pandemic in Campinas, Brazil, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13561, https://doi.org/10.5194/egusphere-egu21-13561, 2021.
The identification of the severe COVID-19 virus in December 2019 led the World Health Organization to declare a global pandemic by March 2020. Up till recently with the first available vaccines, the only prevention measures include strict social, travel, and working restrictions in a so-called lockdown period that lasted for several weeks (mid-March to the end of April 2020 for most of Europe). This abrupt change in social behavior is expected to impact local but also regional atmospheric composition, and the environmental impact is potentially of high interest to policy and decision-makers.
The Aerosol, Clouds, and Trace Gases Research Infrastructure (ACTRIS) is a pan-European research infrastructure producing high-quality data and information on short-lived atmospheric constituents and on the processes leading to the variability of these constituents in natural and controlled atmospheres. Realizing the crucial scientific value of ACTRIS observations of atmospheric composition changes across Europe, the ACTRIS community promptly actioned internal communication [AD1] thread to organize and set-up COVID-19 related activities. Such reactive internal involvement of ACTRIS partners generated timely outcomes. In fact, during the lockdown period in spring 2020, most of the ACTRIS observational and exploratory platforms were operational providing continuous access to data on air quality and atmospheric composition and, as a tailored service arrangement, to reinvent ACTRIS simulation chambers for testing mask filtering efficiencies. [AD2]
ACTRIS response to the COVID-19 pandemic showcases multiple benefits to policy- and decision-makers focused on environmental and societal impacts of COVID-19 and the closing down of several sectors of society (e.g. transport, industry, services). To boost the visibility of ACTRIS COVID-19 response at the European level, ACTRIS actively engaged and collaborated with the wider community of Research Infrastructures (ESFRI, ENVRI, and ERF-AISBL) in Europe to support joint activities for SARS-CoV-2. The Open Science Session on COVID-19 during the ACTRIS week event brought together a broad audience and key-note speaker from major European agencies and organizations (ESA, ECMWF, FMI, ICOS). The online format of the event created the opportunity to open ACTRIS science to a broader public. At the national level, atmospheric scientists were interviewed on COVID impacts raising awareness on the work undertaken in the research infrastructure to the general public.
ACTRIS aims at establishing further engagement and direct communication with decision and policy-makers and, for that, envisage the implementation of ad-hoc efforts. This presentation will showcase the various efforts and success stories to capture society as well as policy- and decision-makers.
How to cite: Saponaro, G., Dubost, A., Juurola, E., and Laj, P.: Communicating ACTRIS science in times of COVID-19, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8622, https://doi.org/10.5194/egusphere-egu21-8622, 2021.
More than one year after its first appearance, COVID-19 has spread to almost all territories around the world –including more than 93 million confirmed infections and 2 million reported deaths. The real numbers are probably substantially higher as unreported cases remain particularly high in countries with weak state welfare and institutions. To date the COVID-19 pandemic has had a strong impact on social, cultural and economic life, stretching from physical isolation to the exacerbation of global famines, and to the largest global economic recession since the Great Depression in the 1930s. It is therefore important to analyse and monitor in detail how this pandemic is being approached and managed by the different governments and in their specific environmental and socio-cultural contexts. Given the slow-onset character of climate change in developing clearly visible effects on a short term, the respective actions to tackle multiple impacts on natural and social systems lack priority and are often delayed. Nonetheless, the climate crisis is considered to be a comparatively fundamental existential threat to humanity.
Based on an extensive literature review, here we analyse the interactions between the COVID-19 pandemic and the climate crisis as compound impacts, i.e. systemic risks that have to be taken into consideration in national emergency programs and in disaster risk management. Human populations with limited resources and capacities tend to be more vulnerable to such exceptional crisis, and as such COVID-19 is exacerbating existing inequalities at national, regional and global levels. Nevertheless, the national responses to the pandemic and their accuracy are not only related to resources and capacities; there are also important political and social factors at play. For instance, the pandemic spread has triggered migration from cities to rural areas and, as a consequence, could lead to higher social-ecological pressures and accelerated land-use change dynamics including e.g. deforestation, changes in water provision and wetland loss in the rural areas. In turn, these impacts would most likely exacerbate the climate crisis. However, some of these risks can be transformed into long-term opportunities, such as a growing implementation of Nature-based Solutions in order to increase the resilience of ecosystems, virtual solutions that reduce travel and emissions (changing working conditions), renovation and diversification of the tourism sector towards more sustainability, and an increase in uptake of sustainable solutions (e.g., car-free days, improved / less energy consuming material and food supply-chains, agroecological production, etc.).
As a “stress test” this pandemic outbreak and ongoing crisis has already taught us several important lessons that should be considered for dealing with the climate crisis. These include the need and opportunity to redesign social-ecological systems as a whole, aiming for transformational change as a globally coordinated and locally implemented effort at all socio-political levels, in the framework of actions based on the principles of the 2030 Agenda for Sustainable Development and the Paris Agreement on Climate Change.
How to cite: Baiker, J. R., Castro-Izaguirre, N., Huggel, C., Allen, S., Drenkhan, F., and Muccione, V.: How the COVID-19 pandemic is teaching us to tackle the climate crisis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15801, https://doi.org/10.5194/egusphere-egu21-15801, 2021.
We are sorry, but presentations are only available for users who registered for the conference. Thank you.
We are sorry, but presentations are only available for users who registered for the conference. Thank you.