Study of atmospheric pollution in Martorell

You can find here an original way to present real-time data created in our school.

  1. Download data from Generalitat de Catalunya (different pollutants, cities and years)
  2. Download R software for data analysis.
  3. Add your badge of finishing the R introduction online in your wordpress blog
  4. Download R Studio
  5. Download data, books, articles sent by your teacher in a zip wetransfer file before a week
  6. Install R libraries. There are thousands available on CRAN. Some of the most interesting ones for your project are:
    • openair (to analyse air pollution)
    • ggplot2 (plotting the easy way, e.g. error bars)
    • ggvis and googleVis (interactive visualization),
    • ggmap and googleVis (google maps visualization of data if you don’t like fusion tables)
    • aplpack (Chernoff faces)
    • forecast,
    • timeSeries,
    • corrplot (correlation plots)
    • lubridate (working with dates and hours),
    • Rcmdr (R Commander GUI for statistics)
    • e1071 (skewness, kurtosis, etc),
    • nortest (normality tests),
    • car (homocedascity Levene’s test),
    • reshape2 and dplyr (manipulate data sets) etc: >install.packages(c(“openair”, “ggplot2”, “forescast”,…))
  7. Convert pollution data in comma separated values file (csv format) using  first Microsoft Excel or LibreOffice Calc (Save As … csv) and the replace commas to points (decimal values) and then semicolons to commas using Sublime Text . Replace “Sense dades” values to NA values. Check the file  contents carefully with Sublime Text
  8. Introduce pollution data in R Studio (read.csv(“mydata.csv”) instruction)
  9. Analyse data with R (statistical analysis, time series forescast, interactive visualization)
  10. Present data with interactive plots and graphs.
  11. Draw conclusions from data: Is the data normally distributed? Is Martorell more polluted than the Catalan city chosen for you? Is it more polluted at night, at weekends, world car free day (22 September 2016)? What is the pollution forecast for the next days?  Are all week days equally polluted (Mon to Sun)? Are pollutants correlated?
  12. Write a scientific poster with your conclusions: introduction, materials and methods, results and discussion, conclusions and bibliography from science scholar, WHO, EU, EPA and NCBI.
  13. Discuss health effects (BreatheLife 2030 WHO)  and legal limits (WHO, EU, EPA, etc.) of air pollutants.
  14. All information must be included also in your blog.
  15. Try to convert graphs in art objects as in enviromental graphiti website.

Un bloc a XTECBlocs