Accounting for the occupation of the marine environment as a natural resource in life cycle assessment: An exergy based approach

Abstract The human population is rising and the availability of terrestrial land and its resources are finite and, perhaps, not sufficient to deliver enough food, energy, materials and space. Thus, it is important to (further) explore and exploit the marine environment which covers no less than 71% of the earth's surface. The marine environment is very complex but can roughty be divided into two systems: natural (e.g. wild fishing) and human-made (e.g. artificial islands). In this study, characterization factors (CF) for natural and human-made marine systems were calculated in order to be able to assess the environmental impact of occupying marine surfaces, which was not possible so far in life cycle assessment. When accounting for natural resources while occupying one of these systems, it is important to consider the primary resources that are actually deprived from nature, which differs between the natural and human-made marine systems. In natural systems, the extracted biomass was accounted for through its exergy content, which is the maximum quantity of work that the system can execute in its environment. Reference flows for marine fish, seaweeds, crustaceans and mollusks were proposed and their correlated CF was calculated. For human-made systems, the deprived land resource is, in fact, the occupied area of the marine surface. Based on potential marine net primary production data (NPP), exergy based spatial and temporal CFs for ocean areal occupation were calculated. This approach was included in the Cumulative Exergy Extraction from the Natural Environment (CEENE) method which makes it the first life cycle impact assessment (LCIA) method capable of analyzing the environmental impact (and more specific the resource footprint) of marine areal occupation. Furthermore, the methodology was applied to two case studies: comparing resource consumption of on- and offshore oil production, and fish and soybean meal production for fish feed applications.

[1]  J. H. Shieh,et al.  Energy and exergy estimation using the group contribution model , 1983 .

[2]  J Dewulf,et al.  Cumulative exergy extraction from the natural environment (CEENE): a comprehensive life cycle impact assessment method for resource accounting. , 2007, Environmental science & technology.

[3]  S. Maritorena,et al.  Bio-optical properties of oceanic waters: A reappraisal , 2001 .

[4]  Stefanie Hellweg,et al.  Applying cumulative exergy demand (CExD) indicators to the ecoinvent database , 2006 .

[5]  Matthias Finkbeiner,et al.  Towards life cycle sustainability management , 2011 .

[6]  D. Sigman,et al.  The biological productivity of the ocean , 2012 .

[7]  Ian S. Robinson,et al.  Discovering the Ocean from Space: The Unique Applications of Satellite Oceanography , 2010 .

[8]  Toby Tyrrell,et al.  The relative influences of nitrogen and phosphorus on oceanic primary production , 1999, Nature.

[9]  Jennifer L. Molnar,et al.  Marine Ecoregions of the World: A Bioregionalization of Coastal and Shelf Areas , 2007 .

[10]  F. Malcata Microalgae and biofuels: a promising partnership? , 2011, Trends in biotechnology.

[11]  David A. Siegel,et al.  Climate-driven trends in contemporary ocean productivity , 2006, Nature.

[12]  Justin Kitzes,et al.  Current Methods for Calculating National Ecological Footprint Accounts 【特集論文 エコロジカル・フットプリント指標の現状と課題】 , 2007 .

[13]  P. Falkowski,et al.  Photosynthetic rates derived from satellite‐based chlorophyll concentration , 1997 .

[14]  M. P. M. Reddy,et al.  Descriptive Physical Oceanography , 1990 .

[15]  N. Erkan,et al.  A preliminary study of amino acid and mineral profiles of important and estimable 21 seafood species , 2011 .

[16]  M. Delucchi,et al.  Impacts of biofuels on climate change, water use, and land use , 2010, Annals of the New York Academy of Sciences.

[17]  A. C. Redfield The biological control of chemical factors in the environment. , 1960, Science progress.

[18]  Hsin-I Wu,et al.  A model comparison for daylength as a function of latitude and day of year , 1995 .

[19]  Scott C. Doney,et al.  Projected 21st century decrease in marine productivity: a multi-model analysis , 2009 .

[20]  S. S. De Vries Thermodynamic and economic principles and the assessment of bioenergy + Book of Surveys , 1999 .

[21]  Roland W. Scholz,et al.  Assessment of Land Use Impacts on the Natural Environment. Part 1: An Analytical Framework for Pure Land Occupation and Land Use Change (8 pp) , 2007 .

[22]  P. Matanjun,et al.  PROXIMATE COMPOSITIONS AND TOTAL PHENOLIC CONTENTS OF SELECTED EDIBLE SEAWEED FROM SEMPORNA, SABAH, MALAYSIA , 2012 .

[23]  Pol Coppin,et al.  Land use impact evaluation in life cycle assessment based on ecosystem thermodynamics , 2006 .

[24]  Arnaud Hélias,et al.  Review on Land Use Considerations in Life Cycle Assessment: Methodological Perspectives for Marine Ecosystems , 2011 .

[25]  D. Antoine,et al.  Oceanic primary production: 1. Adaptation of a spectral light‐photosynthesis model in view of application to satellite chlorophyll observations , 1996 .

[26]  Stefanie Hellweg,et al.  Ecological footprint accounting in the life cycle assessment of products , 2008 .

[27]  Gjalt Huppes,et al.  Thermodynamic resource indicators in LCA: a case study on the titania produced in Panzhihua city, southwest China , 2012, The International Journal of Life Cycle Assessment.

[28]  Llorenç Milà i Canals,et al.  Method for assessing impacts on life support functions (LSF) related to the use of ‘fertile land’ in Life Cycle Assessment (LCA) , 2007 .

[29]  Jan Szargut,et al.  Exergy Analysis of Thermal, Chemical, and Metallurgical Processes , 1988 .

[30]  M. Livi-bacci,et al.  A Concise History of World Population , 1994 .

[31]  H. Haberl,et al.  Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems , 2007, Proceedings of the National Academy of Sciences.

[32]  Stijn Bruers,et al.  Exergy: its potential and limitations in environmental science and technology. , 2008, Environmental science & technology.

[33]  W. Visessanguan,et al.  Comparative studies on chemical composition and thermal properties of black tiger shrimp (Penaeus monodon) and white shrimp (Penaeus vannamei) meats , 2007 .

[34]  David Pennington,et al.  Recent developments in Life Cycle Assessment. , 2009, Journal of environmental management.

[35]  A. D. Beneditto,et al.  Feeding preference of adult females of ribbonfish Trichiurus lepturus through prey proximate-composition and caloric values , 2012 .

[36]  J. Baldock,et al.  The biochemical and elemental compositions of marine plankton: A NMR perspective , 2002 .

[37]  Thomas Koellner,et al.  Assessment of land use impacts on the natural environment , 2006 .

[38]  W. Richard,et al.  TEMPERATURE AND PHYTOPLANKTON GROWTH IN THE SEA , 1972 .

[39]  Edward J. Carpenter,et al.  A kinetic approach to the effect of temperature on algal growth1 , 1974 .

[40]  Stefanie Hellweg,et al.  Solar energy demand (SED) of commodity life cycles. , 2011, Environmental science & technology.

[41]  A. Robinson,et al.  The global coastal ocean : multiscale interdisciplinary processes , 2005 .

[42]  A. Morel,et al.  Surface pigments, algal biomass profiles, and potential production of the euphotic layer: Relationships reinvestigated in view of remote‐sensing applications , 1989 .

[43]  Jo Dewulf,et al.  Exergy-based accounting for land as a natural resource in life cycle assessment , 2013, The International Journal of Life Cycle Assessment.