A One Health Approach
Air Quality Index vs Covid-19 Infection Reports
Summary
The goal of our project is to compare the effects of air pollution and the infection rates of COVID-19. Due to the origins of COVID-19 being in China, as well as China’s extreme levels of air pollution, our data comparisons were focused on China. Our app allows the comparison of three different air pollutants (as well as an index of these three based on NIOSH guidelines) to the amounts of COVID-19 cases across the months of January to June of 2020 (as well as cumulative data across this time range). We believe that this app will help better visualize the relationship between air pollution and COVID-19.
How We Addressed This Challenge
With the widespread pandemic and ever-increasing concentration of hazardous air pollutants, it is important for us to analyze the effects of air quality on the spread of COVID-19. We developed a visualization map for analyzing air quality and new COVID-19 infections using NASA Earth Data and Reactjs. Our visualization map is a interactive and informative map that utilizes 3 air pollutants (CO, O3, and CH4) as well an Air Quality Index we derived ourselves. The map features hexagon plots with height weights of new cases and a color index on the air quality. Through our map, we hope to assist scientists and researchers in fighting the spread of this deadly virus.
How We Developed This Project
We were inspired by the opportunity to analyze COVID-19 and its spread. With the rising cases in many countries, we felt a special attachment to this challenge. We approached this challenge by researching possible air pollutants and its effects. This led us to find three very prevalent air pollutants from NASA Earth Data: O3 (ozone), CH4 (methane), and CO (carbon monoxide). Using python, we collected the datasets and manipulated it them to our needs. Then, we used the data to plot it on our own Reactjs app using the deck.gl module. We ended up having limitations in lack of COVID-19 data but overall we managed to accomplish what we needed.
How We Used Space Agency Data in This Project
Project Demo
Data & Resources
Beoutbreakprepared - Overview. (n.d.). Retrieved October 05, 2020, from https://github.com/beoutbreakprepared
GES DISC. (n.d.). Retrieved October 05, 2020, from https://disc.gsfc.nasa.gov/datasets/AIRS3STD_7.0/summary
GES DISC. (n.d.). Retrieved October 05, 2020, from https://disc.gsfc.nasa.gov/datasets/GLDAS_NOAH025_M_2.1/summary
MERRA-2 inst3_3d_chm_Nv: 3d,3-Hourly,Instantaneous,Model-Level,Assimilation,Carbon Monoxide and Ozone Mixing Ratio 0.625 x 0.5 degree V5.12.4 (M2I3NVCHM) at GES DISC. (n.d.).
Retrieved October 05, 2020, from https://cmr.earthdata.nasa.gov/search/concepts/C1276812901-GES_DISC.html
MYD11C1 v006. (n.d.). Retrieved October 05, 2020, from https://lpdaac.usgs.gov/products/myd11c1v006/