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German Annual Air Emissions Visualized

The starting point of my project was a report by the German Environment Agency in 2021 on annual emissions data by sector since the 90's until 2019.

Dataset

My dataset consists of 30 tables with around 160 rows by 140 columns – really massive. 

First I started with a summary on the annual emissions by the Bundesumweltamt but realised, that I have massive gaps in the 90's. Then I found the original report, published by the European Environment Agency with a lot more data – including high resolution categorisation. Nevertheless I only included the pollutants mentioned in the summary and excluded all heavy metals. This was because I already had a design and a working visualization.

Data Processing

I cleaned the data using jupyter notebooks and prepared a lot of different tables for the final web application – for instance: summing up categories so the browser does not have to lift this load.

Design and Development

First I tried to fit my visualization project with force to the topic of the course, but failed. My data was not really suited for a network viz. 

I tried different pictorial solutions but they all lacked clarity and the possibility to really explore this dataset.

In the end I reiterated many many times between development and going back to the drawing board trying out new stuff.

Here are some failed design examples:

Screenshot 2022-04-04 at 16.39.02.pngScreenshot 2022-04-04 at 16.39.02.png
Screenshot 2022-04-04 at 16.39.15.pngScreenshot 2022-04-04 at 16.39.15.png
Screenshot 2022-04-04 at 16.39.23.pngScreenshot 2022-04-04 at 16.39.23.png
Screenshot 2022-04-04 at 16.39.37.pngScreenshot 2022-04-04 at 16.39.37.png
Screenshot 2022-04-04 at 16.39.30.pngScreenshot 2022-04-04 at 16.39.30.png
Screenshot 2022-04-04 at 16.40.07.pngScreenshot 2022-04-04 at 16.40.07.png
Screenshot 2022-04-04 at 16.40.17.pngScreenshot 2022-04-04 at 16.40.17.png
Screenshot 2022-04-04 at 16.40.24.pngScreenshot 2022-04-04 at 16.40.24.png
Screenshot 2022-04-04 at 16.40.31.pngScreenshot 2022-04-04 at 16.40.31.png
Screenshot 2022-04-04 at 16.40.45.pngScreenshot 2022-04-04 at 16.40.45.png
Screenshot 2022-04-04 at 16.40.56.pngScreenshot 2022-04-04 at 16.40.56.png
Screenshot 2022-04-04 at 16.41.13.pngScreenshot 2022-04-04 at 16.41.13.png
Screenshot 2022-04-04 at 16.41.26.pngScreenshot 2022-04-04 at 16.41.26.png
Screenshot 2022-04-04 at 16.41.41.pngScreenshot 2022-04-04 at 16.41.41.png
Screenshot 2022-04-04 at 16.42.24.pngScreenshot 2022-04-04 at 16.42.24.png
Screenshot 2022-04-04 at 16.45.13.pngScreenshot 2022-04-04 at 16.45.13.png

Result

Screenshot 2022-04-04 at 17.17.45.pngScreenshot 2022-04-04 at 17.17.45.png
Screenshot 2022-04-04 at 17.18.07.pngScreenshot 2022-04-04 at 17.18.07.png
Screenshot 2022-04-04 at 17.17.56.pngScreenshot 2022-04-04 at 17.17.56.png
Screenshot 2022-04-04 at 17.18.35.pngScreenshot 2022-04-04 at 17.18.35.png
Screenshot 2022-04-04 at 17.18.16.pngScreenshot 2022-04-04 at 17.18.16.png

In the end I am quite satisfied with the result. As I mentioned it does not really fit the course topic but for the real first steps on data viz ground I am quit pleased.

This semester ignited my interest in data visualizations and I am curios what will come in the future.

github source

demo

Ein Projekt von

Fachgruppe

Interfacedesign

Art des Projekts

Studienarbeit im Hauptstudium

Betreuung

foto: Mark-Jan Bludau

Zugehöriger Workspace

Advances in Data Visualization: Networks & Hierarchies

Entstehungszeitraum

Wintersemester 2021 / 2022

Keywords