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Exposure factors for marine eutrophication impacts assessment based on a mechanistic biological model

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  • Cosme, Nuno
  • Koski, Marja
  • Hauschild, Michael Z.

Abstract

Emissions of nitrogen (N) from anthropogenic sources enrich marine waters and promote planktonic growth. This newly synthesised organic carbon is eventually exported to benthic waters where aerobic respiration by heterotrophic bacteria results in the consumption of dissolved oxygen (DO). This pathway is typical of marine eutrophication. A model is proposed to mechanistically estimate the response of coastal marine ecosystems to N inputs. It addresses the biological processes of nutrient-limited primary production (PP), metazoan consumption, and bacterial degradation, in four distinct sinking routes from primary (cell aggregates) and secondary producers (faecal pellets, carcasses, and active vertical transport). Carbon export production (PE) and ecosystems eXposure Factors (XF), which represents a nitrogen-to-oxygen ‘conversion’ potential, were estimated at a spatial resolution of 66 large marine ecosystem (LME), five climate zones, and site-generic. The XFs obtained range from 0.45 (Central Arctic Ocean) to 15.9kgO2kgN−1 (Baltic Sea). While LME resolution is recommended, aggregated PE or XF per climate zone can be adopted, but not global aggregation due to high variability. The XF is essential to estimate a marine eutrophication impacts indicator in Life Cycle Impact Assessment (LCIA) of anthropogenic-N emissions. Every relevant process was modelled and the uncertainty of the driving parameters considered low suggesting valid applicability in characterisation modelling in LCIA.

Suggested Citation

  • Cosme, Nuno & Koski, Marja & Hauschild, Michael Z., 2015. "Exposure factors for marine eutrophication impacts assessment based on a mechanistic biological model," Ecological Modelling, Elsevier, vol. 317(C), pages 50-63.
    • Handle: RePEc:eee:ecomod:v:317:y:2015:i:c:p:50-63
    DOI: 10.1016/j.ecolmodel.2015.09.005
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    References listed on IDEAS

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    1. Strandesen, M. & Birkved, M. & Holm, P.E. & Hauschild, M.Z., 2007. "Fate and distribution modelling of metals in life cycle impact assessment," Ecological Modelling, Elsevier, vol. 203(3), pages 327-338.
    2. Kevin R. Arrigo, 2005. "Marine microorganisms and global nutrient cycles," Nature, Nature, vol. 437(7057), pages 349-355, September.
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    1. Tereza Bernasová & Václav Nedbal & Mohammad Ghorbani & Jakub Brom & Elnaz Amirahmadi & Jaroslav Bernas, 2024. "Eutrophication Risk Potential Assessment between Forest and Agricultural Sub-Catchments Using LCIA Principles," Land, MDPI, vol. 13(8), pages 1-14, July.
    2. Ertürk, Ali & Sakurova, Ilona & Zilius, Mindaugas & Zemlys, Petras & Umgiesser, Georg & Kaynaroglu, Burak & Pilkaitytė, Renata & Razinkovas-Baziukas, Artūras, 2023. "Development of a pelagic biogeochemical model with enhanced computational performance by optimizing ecological complexity and spatial resolution," Ecological Modelling, Elsevier, vol. 486(C).
    3. Daniel Koch & Anton Friedl & Bettina Mihalyi, 2023. "Influence of different LCIA methods on an exemplary scenario analysis from a process development LCA case study," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6269-6293, July.
    4. Francesca Verones & Stefanie Hellweg & Assumpció Antón & Ligia B. Azevedo & Abhishek Chaudhary & Nuno Cosme & Stefano Cucurachi & Laura de Baan & Yan Dong & Peter Fantke & Laura Golsteijn & Michael Ha, 2020. "LC‐IMPACT: A regionalized life cycle damage assessment method," Journal of Industrial Ecology, Yale University, vol. 24(6), pages 1201-1219, December.

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