Assessing economic impacts of environmental research infrastructures: overview of methodological tools
<p>The data generated by environmental research infrastructures (ENV RIs) are key to analysing the quality of general living standards and the conditions of development of environmentally sensitive economic activities: monitoring the atmosphere and ocean is increasingly and critically importan...
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2020-03-01
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Series: | Geoscience Communication |
Online Access: | https://www.geosci-commun.net/3/19/2020/gc-3-19-2020.pdf |
Summary: | <p>The data generated by environmental research infrastructures (ENV RIs) are key to analysing the quality of general living standards and the
conditions of development of environmentally sensitive economic activities:
monitoring the atmosphere and ocean is increasingly and critically important
in a context marked by the risks caused by global warming.</p>
<p>Given the cost of ENV RIs, their benefits to society, in terms of economic
impacts, must be assessed and demonstrated. The primary objective of this
article is to review the main tools used to assess the economic impacts of
ENV RIs and to propose a methodological framework. The latter classifies the
impacts into three categories: (1) upstream impacts on equipment suppliers;
(2) downstream impacts on the performance and quality of observational data,
monitoring services and forecasts; and (3) feedback impacts in terms of improved
knowledge about the environment to the benefit of economic activities. In this
framework, the entire data and service supply chain is considered for the
assessment of impacts.</p>
<p>An ocean-related case study serves as a practical example: Argo, a global
in situ ocean observing system, provides an understanding of the supply chain
from upstream suppliers of ENV RIs to primary and processed ocean data
providers. It highlights the methodological issues involved in assessing the
different categories of impacts.</p>
<p>The article gives precedence to tried and tested methods. It concludes that
further work and more data are needed to improve assessment methods.</p> |
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ISSN: | 2569-7102 2569-7110 |