Greenwashing in the US Metal Industry? A Novel Approach Combining SO2 Concentrations From Satellite Data, a Plant-Level Firm Database and Web Text Mining

29 Pages Posted: 8 Mar 2022

See all articles by Sebastian Schmidt

Sebastian Schmidt

Centre for Geoinformatics (Z_GIS), University of Salzburg

Jan Kinne

Centre for European Economic Research (ZEW)

Sven Lautenbach

Heidelberg University

Thomas Blaschke

Centre for Geoinformatics (Z_GIS), University of Salzburg

David Lenz

Justus-Liebig-University Giessen

Bernd Resch

University of Salzburg

Date Written: 2022

Abstract

This Discussion Paper deals with the issue of greenwashing, i.e. the false portrayal of companies as environmentally friendly. The analysis focuses on the US metal industry, which is a major emission source of sulfur dioxide (SO2), one of the most harmful air pollutants. One way to monitor the distribution of atmospheric SO2 concentrations is through satellite data from the Sentinel-5P programme, which represents a major advance due to its unprecedented spatial resolution. In this paper, Sentinel-5P remote sensing data was combined with a plant-level firm database to investigate the relationship between the US metal industry and SO2 concentrations using a spatial regression analysis. Additionally, this study considered web text data, classifying companies based on their websites in order to depict their self-portrayal on the topic of sustainability. In doing so, we investigated the topic of greenwashing, i.e. whether or not a positive self-portrayal regarding sustainability is related to lower local SO2 concentrations. Our results indicated a general, positive correlation between the number of employees in the metal industry and local SO2 concentrations. The web-based analysis showed that only 8% of companies in the metal industry could be classified as engaged in sustainability based on their websites. The regression analyses indicated that these self-reported 'sustainable' companies had a weaker effect on local SO2 concentrations compared to their 'non-sustainable' counterparts, which we interpreted as an indication of the absence of general greenwashing in the US metal industry. However, the large share of firms without a website and lack of specificity of the text classification model were limitations to our methodology.

Keywords: Sentinel-5P, air pollution, natural language processing, spatial regression

JEL Classification: Q53, Q56, R11

Suggested Citation

Schmidt, Sebastian and Kinne, Jan and Lautenbach, Sven and Blaschke, Thomas and Lenz, David and Resch, Bernd, Greenwashing in the US Metal Industry? A Novel Approach Combining SO2 Concentrations From Satellite Data, a Plant-Level Firm Database and Web Text Mining (2022). ZEW - Centre for European Economic Research Discussion Paper No. 22-006, 2022, Available at SSRN: https://ssrn.com/abstract=4049830 or http://dx.doi.org/10.2139/ssrn.4049830

Sebastian Schmidt (Contact Author)

Centre for Geoinformatics (Z_GIS), University of Salzburg ( email )

Schillerstr. 30, Building 15, 3rd Floor
Salzburg, 5020
Austria

Jan Kinne

Centre for European Economic Research (ZEW) ( email )

P.O. Box 10 34 43
L 7,1
D-68034 Mannheim, 68034
Germany

Sven Lautenbach

Heidelberg University ( email )

Grabengasse 1
Heidelberg, 69117
Germany

Thomas Blaschke

Centre for Geoinformatics (Z_GIS), University of Salzburg ( email )

Schillerstr. 30, Building 15, 3rd Floor
Salzburg, 5020
Austria

David Lenz

Justus-Liebig-University Giessen ( email )

Licher Str. 64
Giessen, 35394
Germany

HOME PAGE: http://https://www.uni-giessen.de/fbz/fb02/fb/professuren/vwl/winker/kontakt/mitarbeiter/lenz

Bernd Resch

University of Salzburg ( email )

Akademiestra├če 26
Salzburg, Salzburg 5020
Austria

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