Reading Data Sets
Digital collection of annotated data sets.
Digital collection of annotated data sets.
Research update by the COVID-19 Data Working Group.
I'm interested in better understanding the ongoing geological processes that shape St. Louis and the Mississippi Valley region. So far, I've been looking into the history of seismicity in the region, focusing on the fascinating but little known history of the New Madrid earthquakes of 1811 and 1812 -- the most devastating earthquakes to have hit the US east of the Rockies. I've also been exploring how St. Louis and surrounding areas are dealing with the possibility of another earthquake occurring in the future. According to one article I read, one of the biggest uncertainties is what would happen to the heavily engineered Mississippi River in the case of another major tremblor. The shaking could break the levees, flooding wide areas along the river and creating cascading effects. The flow of the river might also reverse completely, as occurred during the New Madrid earthquakes.
On these possibilities and the lack of scientific consensus surrounding intraplate seismicity in this zone, see this article in The Atlantic.
On current efforts to create earthquake hazard maps in St. Louis, see this overview on the US Geological Survey site.
For a deeper dive into the history of the New Madrid earthquakes, see this book by historian of science Conevery Bolton Valencius.
According to the article, officials were trying to evacuate the areas that they predict to have the most damage, move people to higher ground, tell people to stay indoors, and close all public transportation systems.
The aim of this organization is to work as a collaborative team to address efforts in reducing greenhouse gases, adapt to changes that are already underway, and foster social inclusion and cohesion.
Air pollution causes many eye and skin irritation in addition with lung problems resulting in asthma and even cancer. These risks would affect people who live in communities that have high pollution, severely.
This is a list of analytics by the COVID-19 Data Group.