Lake Superior State University
Lake Superior State University
 
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Alum Success

“I chose LSSU expecting a very good engineering education. What I didn’t expect was faculty with real-world engineering experience and abilities, labs with real-world equipment, projects with real-world outcomes, and an entire campus staff with real interest in my success, as a student and yet today. My LSSU engineering education has created or supported every desired career opportunity. LSSU was absolutely the right place for me.”

Dan Goodrich,
Mechanical Engineering 1999,
Vehicle Test & Development,
Electronic Brake Systems Group

School of Engineering

Team KISS from EGNR101 competitionMembers of Team KISS from EGNR101 Introduction to Engineering show off their winning robot. From left to right: James Claus, ME, Holden, MA; Victor Duffrin, ME, Menominee, MI; Matt Johnston, ME, Sault Ste. Marie, ON; Steven Jacobs, EE, New Carlisle, IN; and Shervorn Mathews, GE, Bronx, NY.

Office Hours:
  • September-April: Monday-Friday, 8 am-5 pm
  • May-August: Monday-Friday, 8 am-4:30 pm
  • Summer Camps: arrival Sunday afternoons

Contact Us

Address:

School of Engineering and Technology
650 W Easterday Ave.
Sault Sainte Marie, MI 49783, U.S.A.

Phone:

+ (906) 635 2207

Fax:

+ (906) 635-6663

E-mail:

engineering@lssu.edu

 

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Questions or Comments :

A Spatial Analysis of Greenhouse Gasses and Household Income

Scott Sowers

Emissions of greenhouse gases (GHG) by industries have been increasing at an exponential rate in the past century. As these emissions increase in number of sources, as well as amount of output, the impact on the environment becomes more significant. However, the United States relies heavily on industry for creation of new products, materials, and economic factors such as employment. Industries attract employment opportunities, which in return attract living accommodations. The basis of this project was to see if there is any spatial correlation between GHG emissions and income of households (within a county) of a GHG emitter. Using Geographical Information Science (GIS), we are able to search for a correlation between lower class households and amounts of GHG emissions. After processing the data, we are able to show that there is no trend in GHG emissions and the proximity to lower class households. Towards the end of the project, we were able to see an extremely slight trend of lower amounts of GHG emissions near upper class households. The project also provides the statistics, or any autocorrelation, of the data for significance testing to determine whether or not there is a probability of the relationship. The statistics provided will be the R2 value, regression, and correlation.

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