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Welcome to SIGHPy!

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SIGHPy: Data

  • Users can calculate the impact of DCs in the vicinity over a user-specified time frame. Personal compute time can be specified to be factored into the calculation.
  • Users can choose to see the sum or the average of their carbon emissions or temperature impacts.

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SIGHPy: Data

  • These are rough calculations - we average the data value over the number of DCs within its geographic box (with the option to average using personal compute time as well). With more data, this calculation can become more refined.
  • However, we believe this is a good proxy - from this example here, it is clear that CO2 emissions in Reston, VA have steadily been increasing over the course of the pandemic.

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SIGHPy: Mapping and Visualization

  • Screenshot of map full
  • Plots?

On the home page, users can see examples of data centres that we are tracking.

By clicking on a DC, users can visualize trends in average CO2 emissions before and during the pandemic. In the future, we want to incorporate temperature data and make the plots interactive to correspond with user inputs.

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COVID-19 Comparisons

  • Using our database and visualization tools, we can compare the environmental impact of data centres before and during the pandemic
  • While an in-depth analysis of the data has not yet been completed, qualitatively it is

clear that some major DC epicentres have experienced an uptick in CO2 emissions and increase in temperature compared to the previous year. Based

on our assumptions, we can say that COVID-19 conditions have had a negative environmental impact via increased emissions from data centres.