Seismic background noise observed at frequencies above 1 Hz primarily consists of cultural noise, which is generated by human activities (Stutzmann et al., 2000; McNamara and Buland, 2004; Groos and Ritter, 2009; Green et al., 2017) such as trains (Chen et al., 2004; Sheen et al., 2009; Ribes-Llario et al., 2017) , road traffic (Hao and Ang, 1998; Coward et al., 2003) and airports (Meng and Ben-Zion, 2018) . These noise sources are now known to be useful for studying the subsurface structures (Nakata et al., 2011; Riahi and Gerstoft, 2015; Quiros et al., 2016; Ajo-Franklin et al., 2019) .
The outbreak of the novel coronavirus SARS-CoV-2 disease (hereafter: COVID-19) was first reported in Wuhan, Hubei, China, in December 2019 (Andersen et al., 2020) . In early to mid-January 2020, the virus spread to other Chinese provinces, facilitated by increased travel during the Chinese Lunar New Year. With Wuhan being a major rail transport hub in China, the virus quickly spread throughout the country. On 23 January 2020, Wuhan and other cities of Hubei province imposed a lockdown in an effort to quarantine the epicenter of the COVID-19 outbreak (Lu, 2020) . All public transportation except for emergency and supply vehicles were suspended. A total of 12 other counties to prefecture-level cities in Hubei, including Enshi, the location of one of the seismic stations used in this study, were placed on travel restrictions by the end of 24 January 2020 (Table 1 ). The World Health Organization (WHO) declared the outbreak to be a Public Health Emergency of International Concern on 30 January 2020. By chance, this outbreak closely coincided with the Chinese Lunar New year of 2020, and the Chinese government utilized this coincidence to facilitate lockdown logistics, essentially extending the traditional week-long national holiday for several months. In Italy, following the rapid expansion of an outbreak of COVID-19 cases in the north of the country in late February 2020, the Italian government imposed a lockdown on many of its Northern provinces on 8 March 2020. The lockdown restricted all movement except for work, health circumstances and essential activities. On the evening of 9 March, quarantine measures were extended to the entire nation, becoming effective the next day. This quarantine included some important differences from the restrictions in China. For example, the lockdown did not apply to the public transportation system, including buses, railways, flights, and ferry services. People with self-declared travel exemptions were permitted to travel. On 11 March 2020, the WHO declared the outbreak a pandemic. This sudden declaration of a public health emergency provides an unusual dataset in which we can compare changes in seismic noise to the known timings of social orders.
In this study, we analyze continuous seismic time series from seismic stations in China and Italy (Fig. 1) . We particularly focus on understanding the characteristics of cultural noise before and after the lockdowns. We show that the lockdown of cities in China led to a ~4-12 dB reduction in cultural noise. In contrast, there was only ~1-6 dB energy decrease of cultural noise in Italy, possibly due to ongoing traffic.
We utilized data from the New China Digital Seismograph Network (NCDSN), in operation since 1992, with the network code IC. Data from IC were obtained from the Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC; www.iris.edu/dms) from 1 January 2000 to 15 April 2020. Those stations are: station IC.ENH, located in Enshi, Hubei province; station IC.MDJ, located in Mudanjiang, Heilongjiang province in the northeast region of China; station IC.BJT which is located in the northwest of Beijing, the capital of China; and station IC.QIZ which is located on Hainan island in Qiongzhou (Fig. 1a) . We also analyzed data from the Italian National We analyzed broadband high-gain vertical seismograms (BHZ) and high-sample-rate highgain broadband three-component seismograms (HHN, HHE, and HHZ), with sample rates of 20 Hz and 100 Hz, respectively. Ground acceleration records were retrieved by deconvolving the instrumental response from the original seismograms. All seismic data were divided into one-hour segments with overlapping time intervals of 50% (30 minutes).
Each one-hour segment was detrended, tapered with a Hanning window, and the power spectral densities (PSD) were calculated. We did not remove earthquake signals from the time series, because the effects of earthquakes are limited to short time intervals and predominantly contain their most characteristic signals at lower frequencies. Thus they have extremely small overall effects on the estimation of cultural noise. We show noise power levels in units of decibels (dB) with respect to 10log &' ( ) * + , -. ) . We also performed a frequency-dependent polarization analysis for the high broadband three-component seismic data to determine the source directions of the cultural noise (Samson, 1983; Park et al., 1987; Koper and Hawley, 2010) .
We use a twenty-year-long seismic record from station IC.ENH, located in Enshi, Hubei province, China, to establish important baselines and patterns in the cultural noise, illustrating the detailed ways in which this signal is related to societal behavior. The vertical PSD for this station is shown in Figure show that the noise level started to drop 5-6 days before the holiday and did not fully recover until another two weeks after (Fig. 7) . This frequency band also exhibits seasonal variations ( Fig. 5a ) which is longer strong noise signal in the summer than the winter corresponding to variation in daylight hours. We infer that 1.5-8 Hz noise is probably generated by the local factories, pedestrians (Alyamkin and Eremenko, 2011) , and lowspeed urban road traffic (Green et al., 2017) .
By contrast, the noise in the frequency band 10-20 Hz is relatively stable during the Chinese Lunar New Year. This persistence allows the noise source to be identified. Long (1971) found that moving vehicles on the freeway generate noise with peak frequency at about 10-20 Hz, and that this signal can be detected within 5-8 km. The station IC.ENH is located ~3 km from the freeway G50 to its southeast (Fig. 1a) . The G50 is a 1900 km long and east-west bound expressway connecting Shanghai, China to the east and Chongqing, China to the west. While we are not yet able to retrieve the record of daily traffic-flow volume on the G50 near city Enshi, traffic data for a segment of this freeway named as Huanghuang east of Wuhan can be accessed (http://www.hhgs.org.cn/) and we use it as the representative of the general traffic flow on this road within Hubei province. The average daily traffic-flow volume on the freeway during the 2018 Chinese Lunar New Year was only 31% less than the daily volume on the regular days (Table 2 ). This suggests that the cultural noise peak in the frequency band 10-20 Hz can be explained by the high-speed cars on the freeway. This is further supported by the back azimuths of the polarization ellipsoids in Figure 3b . The source direction of cultural noise in the 10-20 Hz frequency band is from the southeast (back azimuths are ~ 120° -150°) during the daytime, indicating the noise arrives from the direction of the freeway. The northwest noise source during the night ( Fig. 3c) is probably from the downtown area, which lies in that direction. This dataset also shows a period of freeway traffic control between 13 September 2018 and 26
October 2018, when freeway access was limited or cut off due to road repairs. Station IC.ENH exhibits clear 10-20 Hz noise energy reduction during this period (Fig. 5b ).
Our findings agree with previous analyses of frequency bands typical for road traffic (Groos and Ritter, 2009; Boese et al., 2015; Chang et al., 2016; Green et al., 2017) and consistent with a correlation between the cars' noise frequency content and their speed: the peak frequency band for the low-speed urban road traffic is 1.5-8 Hz, and for the high-speed cars traveling on the freeway it is 10-20 Hz (Long, 1971) . Overground rail transportation could generate the seismic noise above 30 Hz in the seismograms (Chen et al., 2004; Boese et al., 2015; Riahi and Gerstoft, 2015; Green et al., 2017) , and the Chinese Lunar New Year is the peak travel season for the railway stations. However, according to our observations, there is a 5 dB reduction in the frequency band 30-40 Hz during this period, suggesting that the noise generated by the rail does not dominate our seismic record, perhaps due to the high attenuation and relatively far distance (8 km).
These data also reveal the various living habits of people in different cities (Fig. 5 ). For station IC.ENH located in Enshi ( Fig. 5a and 5b) , China, as we mentioned before, we can see the lull caused by the Chinese Lunar New Year in January or February (Fig. 2) . In general, people in Enshi show most activity from 8 a.m. to 5 p.m. during the winter. In the summer, people tend to be active for longer, from 7:00 a.m. to 6:00 p.m. There is a lunchtime lull year-round at noon. However, for the frequency band 10-20 Hz generated by the traveling cars on the freeway (Fig. 5b) , the lunch-time lull is longer and continues for about two hours during the summer. This may reflect hot noon-time weather in the summer discouraging people from going outside. Interestingly, the Chinese data do not show clear weekly cycles; work and activity continue week-round. In Milan, Italy ( Fig. 5c and 5d (Fig. 8b) . Interestingly, there are four distinct sources in frequency bands 1-2 Hz, 3-8 Hz, 10-20 Hz, and 20-40 Hz for station IV.RMP which located in the ~20 km southeast of Rome (Fig. 8e) . We estimate the first peak in 1-2 Hz ( Fig. 9a) , with a ~5 dB reduction during the 2019 Christmas period, is generated by pedestrians (Alyamkin and Eremenko, 2011) , since we expect fewer pedestrians on the street during the holiday of Christmas. By comparison to the Chinese data, we believe the second peak at 3-8 Hz (Fig. 9b) is generated by the local factories and low-speed cars on the street; this band a ~3dB deduction at Christmas. Finally, the high-speed cars on the freeway and the trains are responsible for the frequency bands at 10-20 Hz and 20-40 Hz respectively, which exhibit a ~2 dB reduction during Christmas (Fig. 8f) . However, there is no obvious energy diminishing during the Christmas holiday for station IV.MONC (Fig.   8d ), in which the noise is mainly from the freeway nearby (Fig. 1b) time shift in the frequency band 10-40 Hz (Fig. 5d) at the time of clock changes is reflective of the fact that this energy is generated by public transportation, such as trains, and buses, which have a fixed schedule. We highlight how cultural noise data reflects nuances in societal behavior in order to illustrate how these data can provide a detailed proxy account of the societal COVID-19 response.
In 2020 we observe a sharp decrease in cultural noise in (Figs 4a and 4d) which coincides with the time when the city of Enshi went under lockdown due to COVID-19 (Table 1) , and the extended new year holiday. By comparison to historical data (Fig. 2) , in the 1-8 Hz band the ~12 dB decrease was equivalent to the abrupt cessation of roughly 20 years' worth of urbanization and development activity. In Figure 4a , a weak peak still appears during the lockdown time in the frequency band around 10-20 Hz. This could be caused by the official vehicles and the supply vehicles on the road (Groos and Ritter, 2009; Boese et al., 2015; Chang et al., 2016; Green et al., 2017) . The energy of this peak increases steadily as more vehicles appear on the road from approximately Julian day 70 onwards. Directional analysis of this noise reveals that it mainly comes from the southeast even at night (Fig. 4b and 4c) where the national freeway is located (Fig. 1a) . The systematic increase in traffic as the lockdown eased serves as a natural experiment that we can leverage to better understand the relationship between traffic and seismic noise. Seismic noise generated by pedestrians and local industry is usually in the frequency band 1-5 Hz (Alyamkin and Eremenko, 2011) . On the one hand, the marked decrease of seismic energy in this frequency band during the lockdown period (Fig. 4a ) reflects the many fewer pedestrians and cars on the street. On the other hand, the observation that 1-5 Hz social noise increased ~5 dB in a two week period from Julian days 71 to 85 suggests that Enshi started to gradually reopen much earlier than the official lift of the lockdown. Note that the increase in social noise at Enshi is correlated well with the traffic flow volume at the highway segment 600 km away (Fig. 4d) . It suggests that this gradual reopening is a province-wide activity.
The lockdown of Hubei province came one day before the 2020 Chinese Lunar New Year (January 25), the most important festival in the country. To quantify the energy reduction in cultural noise caused by the coronavirus alone, we compared the daily cultural noise energy variation between 2018 and 2020 using the day of Chinese Lunar New Year as the reference time in Figure 7 . It is worth noting that they show a similar pattern before the lockdown of the cities in the Hubei province. However, after the lockdown, the cultural noise energy in 2020 is much lower than in 2018. The average reduction was ~10 dB in the frequency band 1.5-8 Hz and ~12 dB in 10-20 Hz for the station IC.ENH (Fig. 7c) .
We conducted a similar analysis at several other stations located within urban centers in China ( Fig. 6 and Fig. 7) . None of these regions came under direct lockdown. We again compared the vertical component power spectral densities between the years 2018 ( Fig. 6 , left) and 2020 (Fig. 6, right) . We found that the peak frequencies of cultural noise appear to be different for different cities. This is probably due to the relative distances to the noise sources and the installation (environmental) conditions at different station sites (Trnkoczy et al., 2012) .
For station IC.MDJ, located in the northeast region of China, the cultural noise is seen in mainly two peaks, similarly to at IC.ENH. One spans the frequency band 5-10 Hz and the other the frequency band 10-30 Hz. The first peak seems to be consistent with the local road traffic, and the second peak is consistent with the noise by the nearby railway that is at a distance of about 3 km. A substantial change in noise is observed coincident with the lockdown of Hubei and Lunar New Year. The duration and magnitude of this noise change, when compared to the 2018 record, demonstrates that this change substantially exceeded the 'normal' variation due to the new year holiday, indicating that industry and civilians altered behavior in Mudanjiang in response to COVID-19 despite the lack of formal local lockdown. There was a ~3 dB reduction in the frequency band 5-10 Hz and ~4 dB in the frequency band 10-30 Hz (Fig. 7a) . The lowest noise conditions persisted for ~20 days, followed by a slow return to normal noise levels over a further ~60 day period.
Station IC.BJT, located in Beijing, shows only the lower frequency cultural noise, in this station mostly at 2-5 Hz (Figs 6c and 6d ). This may be related to site installation: this seismograph was installed in a deep tunnel, which might suppress high-frequency noise (McNamara and Buland, 2004) . This 2-5 Hz cultural noise is likely to be generated by both the road traffic and by pedestrians (Alyamkin and Eremenko, 2011; Boese et al., 2015; Green et al., 2017) . As with other stations, the COVID-19 effects produced a protracted lull in the cultural noise, with a reduction ~4 dB in 2-5 Hz (Fig. 7b) . At this station the duration of the noise reduction was longer, more than 81 days. The return to 'normal' cultural noise levels was much substantially more gradual than at other stations, with a slow increase in amplitudes from Julian day 30 and recovery to early-January noise levels Station IC.QIZ, located on Hainan island, which is famous for its tourism industry during the winter, shows a similar pattern to IC.ENH (Figs 6e and 6f) , with a dominant cultural noise peak in the range 2-20 Hz that seems to include distinct sources in bands 2-8 Hz and 8-20 Hz. This is probably because both stations are closer to the freeways (unlike station IC.MDJ) (Fig. 1a) . IC.QIZ manifests a similar noise variation to IC.MDJ, with a ~30 day lull, followed by a gradual return to 'normal' but still less than the background levels in 2018 over a further ~51 day period (Fig. 7d) . The average reduction is ~10 dB in the frequency band 2-8 Hz and ~8 dB in the frequency band 10-20 Hz. Interestingly, the higher frequency (10-20 Hz) noise at this station seems to recover faster than the lower frequency (2-8 Hz) noise. If the former reflects high-speed vehicular traffic and the latter reflects pedestrian traffic, this staggered recovery may result from civilians feeling safe travelling in their own cars earlier than they feel comfortable walking around.
Italy was put under a dramatic lockdown (Table 1) as the coronavirus continued to spread in the country. Although it was one of the toughest responses implemented outside of China, their lockdown policy was less strict than China. As a result, we might expect traffic noise not to have decreased as sharply as we found in mainland China. We find only ~1 dB of energy decrease of cultural noise in the frequency band 10-40 Hz in IV.MILN and ~5 dB of decrease in IV.MONC after Italy declared its lockdown (Fig. 8) . For station IV.RMP, the energy reduction was ~6 dB in 1-2 Hz (Fig. 9a) , indicating many fewer pedestrians on the street. There is a ~4 dB reduction in the frequency band 3-8 Hz (Fig. 9b) and ~5 dB reduction in the frequency band 10-40 Hz (Fig. 8f) , which implies the decrease in trafficvolume was less than the reduction in foot-traffic. Our observations are consistent with the local lockdown policies. The Italian authorities required that their schools, universities, theaters, cinemas, bars, and nightclubs must be closed. Religious gatherings, including funerals and weddings, and sporting events were suspended or postponed. Restaurants and bars were allowed to be open from 6 a.m. to 6 p.m., and shopping malls and markets could open on weekdays with a decreased density of patrons. Under such conditions, the cultural noise should be primarily generated by transportation systems. Lack of any decreasing seismic noise across the lockdown timing seems to corroborate the inference that the primary noise source was public transportation, which was not impacted by the lockdown (Pepe et al., 2020) . It appears that the continuous operation of the public transportation system maintained the persistently high level of cultural noise.
Despite this, a modest but significant decrease in noise level is observed at all Italian stations, from a period beginning at the official lockdown until at least Julian day 106 (time of writing). At stations with higher overall cultural noise (IV. MILN and IV.RMP), the pattern of noisy weekdays and less noisy weekends continues after the lockdown, although both shift to lower-noise than their pre-lockdown counterparts. In fact, for IV.RMP, near
Rome, the post-lockdown week days are less noisy than even the quiet pre-lockdown weekends.
For station IV.MILN, the lowest noise energy appears in the first weekend after lockdown of the country, with the lowest noise conditions persisting just for one day. We also note that even the quietest post-lockdown day is not as quiet as the 2019 Christmas day. Since
Julian day 74 we observe a slow increase in noise over a further 40 day period, perhaps indicating that civilians are increasingly willing to go outside in Milan. However, the noise levels have not yet reached pre-lockdown levels. For station IV. MONC, seismic noise reduced ~5dB following the lockdown over a period of 5 days. There is no clear trend of noise increase at this station, perhaps indicating a more strict maintenance of social distancing and stay-at-home behavior. Station IV.RMP, by contrast, recorded a nearimmediate reduction in seismic noise over the few days following the lockdown, and actually manifests a gradually decreasing trend for the entire cultural noise frequency band 1-40 Hz. The decrease is particularly evident in the 1-2 Hz and 3-8 Hz period bands associated with pedestrians and local urban traffic (Fig. 9 ). This trend may imply that people in Rome are increasingly concerned by the COVID-19 pandemic and are adjusting their behavior to be more conservative.
Seismic records provide unique signals that can elucidate human activities on a large scale.
In this paper, we examined variations in seismic noise between 1 Hz and 40 Hz, which provide proxy information on cultural behavior. In particular, we focused on the effects of governmental lockdowns and self-imposed behavioral alterations due to the outbreak of
Italy, we show that the cultural noise in the range of about 2-40 Hz was primarily generated by the local transportation and population sources and study the living habits of local people by using seismic data. The lockdown of the cities and imposition of travel restrictions led to a ~4-12 dB energy decrease in cultural noise on the background of the noise energy in mainland China. According to our observations, different Chinese cities experienced distinct periods of diminished cultural noise, related to the differing local responses to the epidemic. A marked noise change was found even in cities that did not come under government-mandated quarantine. In contrast, there was only ~1-6 dB energy decrease of cultural noise after Italy was put under a total lockdown, due to continuous public transport. Italian cities seem to be responding differently in terms of social behavior as the lockdown continues.
The data used in this study were collected from the Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC; www.iris.edu/dms) and the Italian National Institute of Geophysics and Volcanology (INGV; http://webservices.ingv.it) in Italy using ObsPy Python package (Beyreuther et al., 2010) . We used GMT (Wessel and Smith, 1991) to make many of the figures in this paper. Our data for seismic PSD, polarization results and traffic-flow volume on the freeway can be obtained from https://zenodo.org/record/3740214#.XojbDC2ZNE6. The grey line is plotted in half-hour bins and the red line is plotted in one-day average bins. 