###### Abstract  
Continuous time series data from geomagnetic observatories are increasingly contaminated by anthropogenic noise related to developing socio-economic activities. More and more sophisticated techniques of data processing are used to eliminate this noise; nonetheless, some of it cannot be removed. The main sources of noise in the Hyderabad (HYB) data are vehicular traffic, power lines and a power station, 500 m to 1 km away. During the nationwide COVID-19 pandemic lockdown from 24 March to 17 May 2020, both road and metro rail traffic came to a complete halt. The data from this time interval give us an opportunity to evaluate the effects of the absence of traffic-generated noise sources. We found noticeable differences in the noise levels present in vector and scalar variation data, due to the vehicular noise observed before and during the lockdown periods. Noise spectrum estimates quantify the reduction in the noise levels during this period. We also noticed decreased scatter in absolute values of the H (horizontal), D (declination), Z (vertical) and I (inclination) components of the geomagnetic field during lockdown. The details of increased data quality in the absence of traffic-generated noise sources are discussed.  
geomagnetic vertical component; total field component; COVID-19 lockdown; vehicular traffic; noise levels +
Footnote †: journal: Medical  
remove the noise in HYB Observatory data caused by the metro line, based on its structural stability. The algorithm works as follows: when a change in dZ between neighboring measurements (in absolute value), exceeding a given threshold, is found, three subsequent measurements are discarded. It is clear that this algorithm creates the following risks: (a) natural signals with sharp edges, for example, during magnetic disturbances, may be discarded; (b) noise may be incompletely removed if its duration is long; (c) noise can be missed if, due to a small shift, its leading edge takes two samples. However, to calculate the minute values of magnetic field variations, this may be enough [7]. Representing the natural field variations is becoming a challenging task, due to increased construction, public transportation and development activities around the magnetic observatories, which has become a source of degradation of magnetic data quality. The parameters that affect the data quality depend on the instrument characteristics, data resolution, expertise of the observer and characteristics of the geomagnetic field, defined by the specific location of a magnetic observatory. Such parameters could be natural (temperature, humidity, groundwater circulation, telluric currents, frequency of lightning, magnetic gradient, etc.) or man-made (AC and DC sources in the vicinity of the sensor, sensor alignment, time stamping, etc.). Due to the increase in urban expansion, as well as the infrastructural facilities in cities, producing good quality and highly accurate geomagnetic measurements by cleaning the artificial noise is increasingly difficult, even though the observatories were originally built in magnetically quiet locations. In this context, to maintain good data quality, it is necessary to understand and assess the factors associated with changing environmental day-to-day conditions that influence data quality, so as to improve the data acquisition and processing procedure accordingly.  
During the COVID-19 pandemic situation, the INTERMAGNET Hyderabad Observatory has committed to continue its operations in recording the Earth's magnetic field without any interruption even with very limited staff during the nationwide lockdown in India (from 24 March to 17 May 2020). An attempt is made to identify and characterize the anthropogenic noise due to metro rail services and vehicular traffic on the 1s data quality of vector and scalar magnetic measurements at HYB.