ABSTRACT
Particulate matters having diameters of 2.5 micrometers or less (PM2.5) have been linked with life threatening health issues worldwide. Data centric approach to ascertain the patterns in the propagation of PM2.5 materials in the atmosphere of a region can help policy makers take informed decisions to take proper action. In this paper, we analyze and identify seasonal, hourly, and regional patterns of PM2.5 propagation in Bangladesh from 2017 to 2020 using the Berkeley Earth dataset. We observe that the concentration of PM2.5 particles has a nationwide median value of about 50 mu gm(-3), which is unhealthy for sensitive individuals. The concentration varies seasonally and diurnally. We observe that the concentrations of PM2.5 in the air is around five times more in winter than in summer. The mean PM2.5 concentration inside Dhaka is significantly worse around 70 mu gm(-3), which is 1.25 times than the average concentration throughout Bangladesh. We also observe average concentration dropped during the covid-19 pandemic due to lockdown. Using cross correlation analysis, we observed how spikes in PM2.5 concentration levels in one zone may correspond with peaked concentrations in a different zone a few hours later, indicating that air currents may cause the particles to move in certain directions. Our exploratory analysis serves as the first cross-country data centric study of the state and propagation patterns of PM2.5 particles within Bangladesh and our findings can serve as foundation for further research on the topic.
ABSTRACT
In this study, we wanted to see how as a representative of a society newspaper portrayed COVID-19. For this purpose, this study considered two countries United Kingdom (UK) and Bangladesh (BD), and analyzed how COVID-19 as an external event was focused in the newspapers. To conduct the analysis, we handpicked a set of covid related feature terms, and using Latent Dirichlet Allocation (LDA) we verified the coherency of the chosen terms. The main finding of this study is that, initially as a new event COVID-19 found huge importance in the newspapers, but with gradual time progression, this became a new normal event and lost its initial insurgence of focus and took a stable condition. We also observed that despite being quite different demographically, geographically, economically along with being affected differently due to covid, UK and BD exhibit quite similar characteristics in portraying covid in newspapers. The decisions were arrived at by applying different types of Natural Language Processing (NLP) tools and statistical analysis. For experimentation, we collected all the published news articles from two newspapers, the Guardian and the Daily Star from January 1, 2020, to March 31, 2021. © 2021, IFIP International Federation for Information Processing.