Valuation of Ecosystem Services for Implementing Innovative Clean Technology

Tomasz Goliński , Zenon Foltynowicz

Abstract

Sustainable development of high nature value areas promotes the use of resources and services that rely on the unique assets of a particular ecosystem without undermining its integrity. Implementing innovative technologies, especially in the field of renewable energy sources, supports this process and helps to preserve environmentally valuable areas such as semi-natural grasslands. This study employs the ecosystem services valuation method to assess the environmental impacts of implementation of innovative IFBB technology in the Notec River Valley of western Poland as a part of a proposed implementation potential analysis framework. Six different categories of ecosystem services were analysed. Results show that implementing IFBB technology has a positive impact on the local ecosystem, generates additional value for potential investors, and thus could affect the perception of a renewable energy generation technology as being viable to implement.
Author Tomasz Goliński (WT / KTiEPP)
Tomasz Goliński,,
- Department of Industrial Products and Ecology
, Zenon Foltynowicz (WT / KTiEPP)
Zenon Foltynowicz,,
- Department of Industrial Products and Ecology
Journal seriesPolish Journal of Environmental Studies, ISSN 1230-1485, (A 15 pkt)
Issue year2018
Vol27
No4
Pages1513-1521
Publication size in sheets0.5
Keywords in Englishecosystem services, renewable energy sources, innovative technology implementation, semi- natural grasslands, biomass
ASJC Classification2300 General Environmental Science; 2304 Environmental Chemistry
DOIDOI:10.15244/pjoes/77097
URL http://www.pjoes.com/Valuation-of-Ecosystem-Services-for-Implementing-Innovative-Clean-Technology,77097,0,2.html
Languageen angielski
Score (nominal)15
Score sourcejournalList
ScoreMinisterial score = 15.0, 17-04-2020, ArticleFromJournal
Publication indicators WoS Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2017 = 0.631; WoS Impact Factor: 2018 = 1.186 (2) - 2018=1.3 (5)
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