The 2020 coronavirus lockdown and seismic monitoring of anthropic activities in Northern Italy

Forecasting ocean wave-induced seismic noise

Ocean waves induce the power peak in the seismic ground motion seen everywhere in the world between 0.03 and ~ 1 Hz, defining the seismic noise baseline. The precise generation mechanisms are well understood, and the dependence of seismic noise on sea weather has been precisely quantified using long-term time series. However, this knowledge has never been exploited to forecast the seismic noise background. Here we report the prediction of the seismic noise spectrum around 1 Hz at the Low-Noise Underground Laboratory (LSBB) in Rustrel, for up to 16 days in advance, limited by the time span of sea weather forecasts. We first characterize the dependence of the seismic noise at the LSBB on the Mediterranean Sea and Atlantic Ocean weather, using buoy data for 2020-2021. We exploit significant correlation in the 0.15 Hz < f < 2.5 Hz frequency band to make predictions, converting sea weather forecasts into seismic noise forecasts. The expected seismic background noise can be used to optimize the performance and running costs of scientific and industrial activities, by scheduling them during quiet intervals or adopting adaptive data analysis techniques to identify target signals in the predicted noise.

Identifying the Fingerprint of a Volcano in the Background Seismic Noise from Machine Learning-Based Approach

This work is devoted to the analysis of the background seismic noise acquired at the volcanoes (Campi Flegrei caldera, Ischia island, and Vesuvius) belonging to the Neapolitan volcanic district (Italy), and at the Colima volcano (Mexico). Continuous seismic acquisition is a complex mixture of volcanic transients and persistent volcanic and/or hydrothermal tremor, anthropogenic/ambient noise, oceanic loading, and meteo-marine contributions. The analysis of the background noise in a stationary volcanic phase could facilitate the identification of relevant waveforms often masked by microseisms and ambient noise. To address this issue, our approach proposes a machine learning (ML) modeling to recognize the “fingerprint” of a specific volcano by analyzing the background seismic noise from the continuous seismic acquisition. Specifically, two ML models, namely multi-layer perceptrons and convolutional neural network were trained to recognize one volcano from another based on the acquisition noise. Experimental results demonstrate the effectiveness of the two models in recognizing the noisy background signal, with promising performance in terms of accuracy, precision, recall, and F1 score. These results suggest that persistent volcanic signals share the same source information, as well as transient events, revealing a common generation mechanism but in different regimes. Moreover, assessing the dynamic state of a volcano through its background noise and promptly identifying any anomalies, which may indicate a change in its dynamics, can be a practical tool for real-time monitoring.

How Effective Is a Traffic Control Policy in Blocking the Spread of COVID-19? A Case Study of Changsha, China

(1) Background: COVID-19 is still affecting people’s daily lives. In the past two years of epidemic control, a traffic control policy has been an important way to block the spread of the epidemic. (2) Objectives: To delve into the blocking effects of different traffic control policies on COVID-19 transmission. (3) Methods: Based on the classical SIR model, this paper designs and improves the coefficient of the infectious rate, and it builds a quantitative SEIR model that considers the infectivity of the exposed for traffic control policies. Taking Changsha, a typical city of epidemic prevention and control, as a study case, this paper simulates the epidemic trends under three traffic control policies adopted in Changsha: home quarantine, road traffic control, and public transport suspension. Meanwhile, to explore the time sensitivity of all traffic control policies, this paper sets four distinct scenarios where the traffic control policies were implemented at the first medical case, delayed by 3, 5, and 7 days, respectively. (4) Results: The implementation of the traffic control policies has decreased the peak value of the population of the infective in Changsha by 66.03%, and it has delayed the peak period by 58 days; with the home-quarantine policy, the road traffic control policy, and the public transport suspension policy decreasing the peak value of the population of the infective by 56.81%, 39.72%, and 45.31% and delaying the peak period by 31, 18, and 21 days, respectively; in the four scenarios where the traffic control policies had been implemented at the first medical case, delayed by 3, 5, and 7 days, respectively, the variations of both the peak value and the peak period timespan of confirmed cases under the home-quarantine policy would have been greater than under the road traffic control and the public transport suspension policies. (5) Conclusions: The implementation of traffic control policies is significantly effective in blocking the epidemic across the city of Changsha. The home-quarantine policy has the highest time sensitivity: the earlier this policy is implemented, the more significant its blocking effect on the spread of the epidemic.

Change in the Level of Microseismic Noise During the COVID-19 Pandemic in the Russian Far East

With the outbreak of the COVID-19 pandemic, many seismologists all over the world have noted a sharp (up to 30-50%) decrease in the daily background seismic noise during the period from March to May, 2020 (Lecocq et al., Science 369(6509):1338-1343, 2020). The authors studied the influence of the self-isolation regime introduced in the Russian Federation from March 30, 2020 and, as a consequence, the restriction of the work of public institutions and the mobility of the population, on the quality of seismological observations at seismic stations in large cities of the Russian Far East for the period from March 23, 2020 to April 12, 2020. The work analyses the records of seismic noise by the seismic stations of Khabarovsk and Vladivostok located in busy parts of the cities and, accordingly, strongly influenced by anthropogenic impact, as well as it analyses the records of the Yuzhno-Sakhalinsk seismic station located in the relatively «calm» part of the city. Power spectra and temporal variations of microseismic noise levels for the listed above seismic stations were constructed based on the data of broadband seismometers records in the range of 1-20 Hz. The analysis of noise level variations with the data on the population mobility was carried out on the basis of self-isolation index by Yandex, which shows the level of town activity over a selected period. The main sources of the increased microseismic noise at seismic stations were identified.

Characteristics and impact of environmental shaking in the Taipei metropolitan area

Examining continuous seismic data recorded by a dense broadband seismic network throughout Taipei shows for the first time, the nature of seismic noise in this highly populated metropolitan area. Using 140 broadband stations in a 50 km × 69 km area, three different recurring, strong noise signals characterized by dominant frequencies of 2–20 Hz, 0.25–1 Hz, and < 0.2 Hz are explored. At frequencies of 2–20 Hz, the seismic noise exhibits daily and weekly variations, and a quiescence during the Chinese New Year holidays. The largest amplitude occurred at a station located only 400 m from a traffic-roundabout, one of the busiest intersections in Taipei, suggesting a possible correlation between large amplitude and traffic flow. The median daily amplitude for the < 0.2 Hz and 0.2–1.0 Hz frequency bands is mostly synchronized with high similarity between stations, indicating that the sources are persistent oceanic or atmospheric perturbations across a large area. The daily amplitude for the > 2 Hz band, however, is low, indicating a local source that changes on shorter length scales. Human activities responsible for the 2–40 Hz energy in the city, we discovered, are able to produce amplitudes approximately 2 to 1500 times larger than natural sources. Using the building array deployed in TAIPEI 101, the tallest building in Taiwan, we found the small but repetitive ground vibration induced by traffic has considerable effect on the vibration behavior of the high-rise building. This finding urges further investigation not only on the dynamic and continuous interaction between vehicles, roads, and buildings, but also the role of soft sediment on such interaction.

COVID-19 lockdown and environmental pollution: an Indian multi-state investigation

Originating from China, COVID-19 became the first-ever coronavirus pandemic, wreaking havoc in 218 nations. The lack of a potential treatment exacerbated by the inability of the healthcare infrastructure to contain the viral trajectory led to a worldwide lockdown. The anthropogenic halt presented an unprecedented background to quantify the effect of the anthroposphere on environmental pollution. Consequently, we analyzed the variations in the air (PM₁₀, PM_2.5, NO₂, SO₂) and water pollutants (BOD, COD, DO, coliform) using real-time monitoring data in the majorly hit Indian metropolitan states during the lockdown in contrast to 2019 levels. The overall AQI (air quality index) de-escalated by -31.35%, -34.35%, -32.63%, -29.25% in Delhi, Tamil Nadu, West Bengal, and Karnataka, respectively, from the 2019 levels. The daily concentrations of NO₂, PM_2.5, and PM₁₀ plunged tremendously. The exact pre-disposing factors responsible for higher COVID-19 transmission in some geographical centers remain elusive. Investigations have corroborated putative links between air pollutants and COVID-19 mortalities. Therefore, we further mapped PM_2.5, PM₁₀, NO₂, and SO₂ to co-relate with COVID-19 infectivity and mortality across the study states. Significant (P < 0.001) positive correlation between COVID-19 transmission was established for all pollutants with maximum co-relation with AQI followed by NO₂. River Ganga water in Uttarakhand was deemed "fit for drinking" for the first time in two decades. An aggregate of -71.94, -61.32, and -77.94 decrease in BOD, COD, total coliform levels, and an 11.75 rise in the average DO levels from 2019 data. This study will better assist the future framework of health and environment restoration policies.

Temporal changes in anthropogenic seismic noise levels associated with economic and leisure activities during the COVID-19 pandemic

Seismic ambient noise with frequencies > 1 Hz includes noise related to human activities. A reduction in seismic noise during the COVID-19 pandemic has been observed worldwide, as restrictions were imposed to control outbreaks of the SARS-CoV-2 virus. In this context, we studied the effect of changes in anthropogenic activities during COVID-19 on the seismic noise levels in the Tokyo metropolitan area, Japan, considering time of day, day of the week, and seasonal changes. The results showed the largest reduction in noise levels during the first state of emergency under most conditions. After the first state of emergency was lifted, the daytime noise reverted to previous levels immediately on weekdays and gradually on Sundays. This was likely because economic activities instantly resumed, while non-essential outings on Sundays were still mostly avoided. Furthermore, the daytime noise level on Sundays was strongly reduced regardless of changes on weekdays after the second state of emergency, which restricted activities mainly at night. Sunday noise levels gradually increased from the middle of the second state of emergency, suggesting a gradual reduction in public concern about COVID-19 following a decrease in the number of infections. Our findings demonstrate that seismic noise can be used to monitor social activities.

Air Pollution Analysis during the Lockdown on the City of Milan

From February 2020, the progressive adoption of measures to contain coronavirus’s contagion has resulted in a sudden change in anthropogenic activities in Italy, especially in Lombardy. From a scientific point of view, this situation represents a unique laboratory for understanding and predicting the consequences of specific measures aimed at improving air quality. In this work, the lockdown effect on Milan’s (Italy) air quality was analyzed. The PM10 and PM2.5 values were measured by the ARPA Lombardia, and the real-time on-road (ROM) air quality monitoring network indicates the seasonality of these pollutants, which typically record the highest values in the coldest months of the year. The 10-year particulate matter concentrations analysis shows a PM10 reduction of 35% from 2010 to 2020. March 2020 data analysis shows an alternation of days with higher and lower particulate matter concentrations; values decrease in pollutants concentrations of 16%, respective to 2018. The complexity of the phenomena related to the atmospheric particulates formation, transport, and accumulation is highlighted by some circumstances, such as the Sahara dust events. The study showed that the trend of a general pollutant concentration reduction should be attributed to the decrease in emissions (specifically, from the transport sector) from the variation of meteorological and environmental conditions.

Environmental externalities of the COVID-19 lockdown: Insights for sustainability planning in the Anthropocene

The COVID-19 pandemic has abruptly halted the Anthropocene's ever-expanding reign for the time being. The resulting global human confinement, dubbed as the Anthropause, has created an unprecedented opportunity for us to evaluate the environmental consequences of large-scale changes in anthropogenic activities. Based on a methodical and in-depth review of related literature, this study critically evaluates the positive and negative externalities of COVID-19 induced lockdown on environmental components including air, water, noise, waste, forest, wildlife, and biodiversity. Among adverse impacts of the lockdown, increased amount of healthcare waste (300-400%), increased level of atmospheric ozone (30-300%), elevated levels of illicit felling in forests and wildlife poaching were prominent. Compared to the negative impacts, significant positive changes in various quality parameters related to key environmental components were evident. Positive impacts on air quality, water quality, noise level, waste generation, and wildlife were apparent in varying degrees as evaluated in this study. By presenting a critical overview of the recommendations given in the major literature in light of these documented impacts, this paper alludes to potential policy reforms as a guideline for future sustainable environmental management planning. Some of the key recommendations are e.g., enhance remote working facilities, cleaner design, use of internet of things, automation, systematic lockdown, and inclusion of hazardous waste management in disaster planning. The summarized lessons of this review, pertinent to the dynamic relationship between anthropogenic activities and environmental degradation, amply bring home the need for policy reforms and prioritization of Sustainable Development Goals in the context of the planetary boundaries to the environmental sustainability for a new post-pandemic world.

Urban seismic monitoring in Brasília, Brazil

Urban seismology has gained scientific interest with the development of seismic ambient noise monitoring techniques and also for being a useful tool to connect society with the Earth sciences. The interpretation of the sources of seismic records generated by sporting events, traffic, or huge agglomerations arouses the population’s curiosity and opens up a range of possibilities for new applications of seismology, especially in the area of urban monitoring. In this contribution, we present the analysis of seismic records from a station in the city of Brasilia during unusual episodes of silencing and noisy periods. Usually, cultural noise is observed in high-fequency bands. We showed in our analysis that cultural noise can also be observed in the low-frequency band, when high-frequency signal is attenuated. As examples of noisy periods, we have that of the Soccer World Cup in Brazil in 2014, where changes in noise are related to celebrations of goals and the party held by FIFA in the city, and the political manifestations in the period of the Impeachment trial in 2016, which reached the concentration of about 300,000 protesters. The two most characteristic periods of seismic silence have been the quarantine due to the COVID-19 pandemic in 2020, and the trucker strike that occurred across the country in 2018, both drastically reducing the movement of people in the city.

Assessing the impact of COVID-19 and safety parameters on energy project performance with an analytical hierarchy process

COVID-19 has destabilized the global economy, disrupted the lives of billions of people globally, and caused the workforce to suffer. Furthermore, the spread of this disease has caused most nations to impose strict lockdown regulations and shutdown most industries. This study aimed to highlight the key issues of energy project performance alongside construction activities that were halted during the COVID-19 outbreak to follow social distancing, lockdown, and public safety parameters. A questionnaire survey was administered to accomplish the purpose of this study. The responses of 42 energy project professionals and experts were evaluated using the analytical hierarchy process (AHP) for group decision-making. AHP shows that the biggest influences on project performance during COVID-19 pandemic were government measures and personal factors. The findings provide insight to support energy project planning and management during and after the pandemic, including prioritization of labor force health and safety.

Picking up the hydrothermal whisper at Ischia Island in the Covid-19 lockdown quiet

In this paper, we analyse the seismic noise at Ischia Island (Italy) with the objective of detecting the hydrothermal source signals taking advantage of the Covid-19 quiescence due to lockdown (strong reduction of anthropogenic noise). We compare the characteristics of the background noise in pre-, during and post-lockdown in terms of spectral content, energy release (RMS) and statistical moments. The continuous noise is decomposed into two independent signals in the 1-2 Hz and 2-4 Hz frequency bands, becoming sharpened around 1 Hz and 3 Hz respectively in lockdown. We propose a conceptual model according to which a dendritic system of fluid-permeated fractures plays as neighbour closed organ pipes, for which the fundamental mode provides the persistent whisper and the first higher mode is activated in concomitance with energy increases. By assuming reasonable values for the sound speed in low vapor-liquid mass fraction for a two-phase fluid and considering temperatures and pressures of the shallow aquifer fed by sea, meteoric and deep hydrothermal fluids, we estimate pipe lengths in the range 200-300 m. In this scheme, Ischia organ-like system can play both continuous whisper and transients, depending on the energy variations sourced by pressure fluctuations in the hydrothermal fluids.

Monitoring Sound and Its Perception during the Lockdown and De-Escalation of COVID-19 Pandemic: A Spanish Study

The lockdown measures in Spain due to the SARS-CoV-2 or COVID-19 (Coronavirus disease 2019) pandemic from 13 March to 21 June 2020 had extensive social and environmental implications. This study aims to understand how the measures of lockdown have influenced noise levels, as well as people's perception of sound quality before and after lockdown, including de-escalation. For this purpose, an online survey was carried out. Moreover, the noise linked to the Global Positioning System (GPS) position of each individual respondent was recorded aiming to correlate the noise level with the result of the survey. An average reduction of over 30 dB was observed compared with the sound pressure level before lockdown. Furthermore, it was found that the loudness parameter, together with the overall level, increased as the country started relaxing restrictions. Additionally, results showed that the perception of noise quality changed depending on the phase of de-escalation (p < 0.01), the type of property (p < 0.05), and the outside noise (p < 0.01). Moreover, noise annoyance was determined considering age (p < 0.01), gender (p < 0.05), type of property (p < 0.001), and home refurbishment (p < 0.05). It may be concluded that the most important measure to decrease noise levels is the reduction of traffic noise, through using eco-friendly public transportation or bicycles and limiting nightlife hours.

Two-step seismic noise reduction caused by COVID-19 induced reduction in social activity in metropolitan Tokyo, Japan

The COVID-19 pandemic that started at the end of 2019 forced populations around the world to reduce social and economic activities; it is believed that this can prevent the spread of the disease. In this paper, we report an analysis of the seismic noise during such an induced social activity reduction in the Tokyo metropolitan area, Japan. Using seismic data obtained from 18 stations in the Metropolitan Seismic Observation Network (MeSO-net), a two-step seismic noise reduction was observed during the timeline of COVID-19 in Tokyo. The first noise reduction occurred at the beginning of March 2020 in the frequency band of 20-40 Hz. This corresponded with the request by the Prime Minister of Japan for a nationwide shutdown of schools. Although social activity was not reduced significantly at this juncture, local reduction of seismic wave excitation in the high-frequency band, 20-40 Hz, was recorded at some MeSO-net stations located in school properties. The second reduction of seismic noise occurred at the end of March to the beginning of April 2020 in a wider frequency band including lower frequency bands of 1-20 Hz. This timing corresponds to when the Governors of the Tokyo metropolitan area requested citizens to stay home and when the state of emergency was declared for the Tokyo metropolitan area by the government, respectively. Since then, the estimated population at train stations abruptly dropped, which suggests that social activity was severely reduced. Such large-scale changes in social activity affect the seismic noise level in low-frequency bands. The seismic noise level started to increase from the middle of May correlating with increase in population at the train stations. This suggests that social activity restarted even before the state of emergency was lifted at the end of May. The two-step seismic noise reduction observed in this study has not been reported in other cities around the world. Unexpected reduction of social activity due to COVID-19 provided a rare opportunity to investigate the characteristics of seismic noise caused by human activities.

Imprints of COVID-19 Lockdown on GNSS Observations: An Initial Demonstration Using GNSS Interferometric Reflectometry

The ongoing coronavirus disease 2019 (COVID-19) pandemic has imposed tight mobility restrictions in urban areas, causing substantial reduction in roadway traffic. Many public parking lots are nearly vacant as people across the world have gone on lockdown since mid-March. This environmental change may have impacts on Global Navigation Satellite System (GNSS) sensors installed on roof of buildings. Here, we use a monitoring site in Boston to exemplify a likely sensitivity of precise GNSS sensors to their nearby dynamic environments including parked vehicles in parking lots. We show that reduced number of parked vehicles since 23 March has decreased the reflector roughness, resulting in an increase in the reflected signal power whose amplitude is quantified by GNSS interferometric reflectometry technique. The uncertainty of retrieved GNSS antenna height drops with beginning of lockdown, allowing more accurate estimate of reflector height, which could have a general implication for better understanding of the fundamental limitations of the technique.

COVID-19 lockdown and its latency in Northern Italy: seismic evidence and socio-economic interpretation

The Italian Government has decreed a series of progressive restrictions to delay the COVID-19 pandemic diffusion in Italy since March 10, 2020, including limitation in individual mobility and the closure of social, cultural, economic and industrial activities. Here we show the lockdown effect in Northern Italy, the COVID-19 most affected area, as revealed by noise variation at seismic stations. The reaction to lockdown was slow and not homogeneous with spots of negligible noise reduction, especially in the first week. A fresh interpretation of seismic noise variations in terms of socio-economic indicators sheds new light on the lockdown efficacy pointing to the causes of such delay: the noise reduction is significant where non strategic activities prevails, while it is small or negligible where dense population and strategic activities are present. These results are crucial for the a posteriori interpretation of the pandemic diffusion and the efficacy of differently targeted political actions.

City-Scale Dark Fiber DAS Measurements of Infrastructure Use During the COVID-19 Pandemic

Throughout the recent COVID-19 pandemic, real-time measurements about shifting use of roads, hospitals, grocery stores, and other public infrastructure became vital for government decision makers. Mobile phone locations are increasingly assimilated for this purpose, but an alternative, unexplored, natively anonymous, absolute method would be to use geophysical sensing to directly measure public infrastructure usage. In this paper, we demonstrate how fiber-optic distributed acoustic sensing (DAS) connected to a telecommunication cable beneath Palo Alto, CA, successfully monitored traffic over a 2-month period, including major reductions associated with COVID-19 response. Continuous DAS recordings of over 450,000 individual vehicles were analyzed using an automatic template-matching detection algorithm based on roadbed strain. In one commuter sector, we found a 50% decrease in vehicles immediately following the order, but near Stanford Hospital, the traffic persisted. The DAS measurements correlate with mobile phone locations and urban seismic noise levels, suggesting geophysics would complement future digital city sensing systems.

Global quieting of high-frequency seismic noise due to COVID-19 pandemic lockdown measures

Human activity causes vibrations that propagate into the ground as high-frequency seismic waves. Measures to mitigate the coronavirus disease 2019 (COVID-19) pandemic caused widespread changes in human activity, leading to a months-long reduction in seismic noise of up to 50%. The 2020 seismic noise quiet period is the longest and most prominent global anthropogenic seismic noise reduction on record. Although the reduction is strongest at surface seismometers in populated areas, this seismic quiescence extends for many kilometers radially and hundreds of meters in depth. This quiet period provides an opportunity to detect subtle signals from subsurface seismic sources that would have been concealed in noisier times and to benchmark sources of anthropogenic noise. A strong correlation between seismic noise and independent measurements of human mobility suggests that seismology provides an absolute, real-time estimate of human activities.