Examining Air Quality Data in Germany

Audience

Course module will be deployed Spring ‘22 for a Foreign Study Program in Berlin.

The module will span approximately three weeks of class time. The course consists of 18-20 students who are expected to have Basic plotting knowledge (e.g. histogram/scatter plot). New plots relevant to the assignment (wind rose, pollution rose, etc.) will be explained in the assignments. R and RStudio will be used, but no past experience required. 

Other applicable courses that may benefit from this module:

The R introduction assignment can be extended to any group in which R is relevant, and Openair assignments are useful for any group interested in air quality analysis.

Project Summary

Primary Objective

The primary objective of this module is to learn and then apply air quality dispersion modeling using an R-based programming module, with the help of the package ‘openair’ and open-sourced air quality datasets of cities in Germany. 

Goals

Students will be able to:

• understand the basics of dispersion modeling

• obtain and clean data sets

• analyze those data sets

• communicate results to peers and target audience members

Content Outline

Assignment 1: R Installation and Tutorial

• Tech: downloading and installing R and RStudio, done before class

• Material: slides, full assignment doc / answer doc, answer key

• Code: R_intro.R, R_intro_dataset.csv

Assignment 2: Selecting Your Site

• Material: slides, full assignment doc, selecting your site sign-up sheet

• Code: data files for each Germany site

Assignment 3: Openair Primer

• Material: slides, full assignment doc / answer doc, answer key

• Code: openair_primer.R, openair_primer_dataset.csv

Assignment 4: Preliminary Presentation

• Material: full assignment doc, slides for all-class submission (used for presentation)

Assignment 5: More on Openair

• Material: slides, full assignment doc

• Code: more_on_openair.R

Assignment 6: Final Project

• Material: slides, full assignment doc

• “Gala” type event at end of term to showcase targeted media components

Datasets Used/Applicable

• Load data in R

  • Easy to load UK data: openair

  • Data from rest of Europe, requires cleaning (example code provided): saqgetr

• In-class example city dataset:

  • UK's Automatic Urban and Rural Network (AURN)

    • More stable; has weather (wind speed and wind direction) already included

    • site = "my1", year = 2000:2005

• Group work datasets:

  • 21 datasets corresponding to different monitoring sites across Germany

    • Berlin (5), Hannover (2), Leipzig (2), Munich (2), Hamburg (2), Cologne (2), Düsseldorf (2), and Rural Germany near Berlin (3)

    • Types: suburban, urban, traffic, industrial, rural, near airport

  • These dataset are cleaned up ahead of time and must be downloaded

    • Code for extracting air quality data, merging with weather data, and cleaning: AQMET_data_extractor_all.R (in github)

For more information email: difuse-pi-group@dartmouth.edu