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Greenwashing in the US metal industry? A novel approach combining SO2 concentrations from satellite data, a plant-level firm database and web text mining

Author

Listed:
  • Schmidt, Sebastian
  • Kinne, Jan
  • Lautenbach, Sven
  • Blaschke, Thomas
  • Lenz, David
  • Resch, Bernd

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.

Suggested Citation

  • Schmidt, Sebastian & Kinne, Jan & Lautenbach, Sven & Blaschke, Thomas & Lenz, David & Resch, Bernd, 2022. "Greenwashing in the US metal industry? A novel approach combining SO2 concentrations from satellite data, a plant-level firm database and web text mining," ZEW Discussion Papers 22-006, ZEW - Leibniz Centre for European Economic Research.
  • Handle: RePEc:zbw:zewdip:22006
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    References listed on IDEAS

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    1. Bongsug (Kevin) Chae & Eunhye (Olivia) Park, 2018. "Corporate Social Responsibility (CSR): A Survey of Topics and Trends Using Twitter Data and Topic Modeling," Sustainability, MDPI, vol. 10(7), pages 1-20, June.
    2. Richard Schmalensee & Robert N. Stavins, 2013. "The SO 2 Allowance Trading System: The Ironic History of a Grand Policy Experiment," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 103-122, Winter.
    3. Shuhua Ma & Zongguo Wen & Jining Chen, 2012. "Scenario Analysis of Sulfur Dioxide Emissions Reduction Potential in China's Iron and Steel Industry," Journal of Industrial Ecology, Yale University, vol. 16(4), pages 506-517, August.
    4. World Commission on Environment and Development,, 1987. "Our Common Future," OUP Catalogue, Oxford University Press, number 9780192820808.
    5. Jan Kinne & Janna Axenbeck, 2020. "Web mining for innovation ecosystem mapping: a framework and a large-scale pilot study," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2011-2041, December.
    6. repec:rre:publsh:v:37:y:2007:i:1:p:5-27 is not listed on IDEAS
    7. M Tiefelsdorf & D A Griffith & B Boots, 1999. "A Variance-Stabilizing Coding Scheme for Spatial Link Matrices," Environment and Planning A, , vol. 31(1), pages 165-180, January.
    8. Julian Schwierzy & Robert Dehghan & Sebastian Schmidt & Elisa Rodepeter & Andreas Stoemmer & Kaan Uctum & Jan Kinne & David Lenz & Hanna Hottenrott, 2022. "Technology Mapping Using WebAI: The Case of 3D Printing," Papers 2201.01125, arXiv.org.
    9. Abdullah Gök & Alec Waterworth & Philip Shapira, 2015. "Use of web mining in studying innovation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 653-671, January.
    10. Ki‐Hoon Lee, 2017. "Does Size Matter? Evaluating Corporate Environmental Disclosure in the Australian Mining and Metal Industry: A Combined Approach of Quantity and Quality Measurement," Business Strategy and the Environment, Wiley Blackwell, vol. 26(2), pages 209-223, February.
    11. Jan Kinne & David Lenz, 2021. "Predicting innovative firms using web mining and deep learning," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-18, April.
    12. Dörr, Julian Oliver & Kinne, Jan & Lenz, David & Licht, Georg & Winker, Peter, 2021. "An integrated data framework for policy guidance in times of dynamic economic shocks," ZEW Discussion Papers 21-062, ZEW - Leibniz Centre for European Economic Research.
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    More about this item

    Keywords

    Sentinel-5P; air pollution; natural language processing; spatial regression;
    All these keywords.

    JEL classification:

    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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