Working with air quality and meteorological data Exercises (Part-2)

August 29, 2017
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Atmospheric air pollution is one of the most important environmental concerns in many countries around the world, and it is strongly affected by meteorological conditions. Accordingly, in this set of exercises we use openair package to work and analyze air quality and meteorological data. This packages provides tools to directly import data from air quality measurement network across UK, as well as tools to analyse and producing reports.

In the previous exercise set we used data from MY1 station to see how to import data and extract basic statistical information from data. In this exercise set we will use some basic and useful functions that are available in openair package to analyze and visualize MY1 data.

Answers to the exercises are available here.

For other parts of this exercise set follow the tag openair

Please load the package openair before starting the exercises.

Exercise 1
Use summaryPlot function to plot timeseries and histogram for pm10, and o3

Exercise 2
Use windRose function to plot monthly wind rose.

You can use Air Quality Data and weather patterns in combination with spatial data visualization, Learn more about spatial data in the online course
[Intermediate] Spatial Data Analysis with R, QGIS & More
. this course you will learn how to:

  • Work with Spatial data and maps
  • Learn about different tools to develop spatial data next to R
  • And much more

Exercise 3
Use pollutionRose function to plot monthly pollution roses for
a. pm10
b. pm2.5
b. nox
c. no
d. o3

Exercise 4
Use pollutionRose to plot seasonal pollution roses for
a. pm10
b. pm2.5
b. nox
c. no
d. o3

Exercise 5
Use percentileRose function to plot monthly percentile roses for
a. pm10
b. pm2.5
b. nox
c. no
d. o3

Exercise 6
Use polarCluster function to plot cluster roses plot for
a. pm10
b. pm2.5
b. nox
c. no
d. o3

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