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Uncertainty and spatial variability in characterization factors for aquatic acidification at the global scale

  • LIFE CYCLE IMPACT ASSESSMENT (LCIA)
  • Published:
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Abstract

Purpose

Characterization factors (CFs) quantifying the potential impact of acidifying emissions on inland aquatic environments in life cycle assessment are typically available on a generic level. The lack of spatial differentiation may weaken the relevance of generic CFs since it was shown that regional impact categories such as aquatic acidification were influenced by the surroundings of the emission location. This paper presents a novel approach for the development of spatially differentiated CFs at a global scale for the aquatic acidification impact category.

Methods

CFs were defined as the change in relative decrease of lake fish species richness due to a change in acidifying chemicals emissions. The characterization model includes the modelling steps linking emission to atmospheric acid deposition (atmospheric fate factor) change, which lead to lake H+ concentration (receiving environment fate factor) change and a decrease in relative fish species richness (effect factor). We also evaluated the significance of each factor (i.e. atmospheric fate, receiving environment fate and effects) to the overall CFs spatial variability and parameter uncertainty.

Results and discussion

The highest CFs were found for emissions occurring in Canada, Scandinavia and the northern central Asia because of the extensive lake areas in these regions (lake areas being one of the parameters of the CFs; the bigger the lake areas, the higher the CFs). The CFs’ spatial variability ranged over 5, 6 and 8 orders of magnitude for NOx, SO2 and NH3 emissions, respectively. We found that the aquatic receiving environment fate factor is the dominant contributor to the overall spatial variability of the CFs, while the effect factors contributed to 98 % of the total parameter uncertainty.

Conclusions

The resulting characterization model and factors enable a consistent evaluation of spatially explicit acidifying emissions impacts at the global scale.

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References

  • Amarasinghe US, Welcomme RS (2002) An analysis of fish species richness in natural lakes. Environ Biol Fish 65:327–339

    Article  Google Scholar 

  • Araoye PA (2009) The seasonal variation of pH and dissolved oxygen (DO2) concentration in Asa lake IIorin, Nigeria. Int J Phys Sci 4(5):271–274

    CAS  Google Scholar 

  • Bey I, Jacob D, Yantosca R, Logan J, Field B, Fiore A, Li Q, Liu H, Mickley L, Schultz M (2001) Global modeling of tropospheric chemistry with assimilated meteorology: model description and evaluation. J Geophys Res 106(D19):23073–23905

    Article  CAS  Google Scholar 

  • Downing RJ, Hettelingh J-P, de Smet PAM (1993) Calculation and mapping of critical loads in Europe: status report. Bilthoven, Netherlands

    Google Scholar 

  • Driscol CT, Van Dreason R (1993) Seasonal and long-term temporal patterns in the chemistry of Adirondack lakes. Water Air Soil Pollut 67:319–344

    Article  Google Scholar 

  • Dupont J (2004) La problématique des lacs acides au Québec, Direction du suivi de l’état de l’environnement, ministère de l’Environnement, envirodoq no. ENV/2004/0151

  • Evans M, Jingqiu M (ed) (2009) Updated chemical reactions now used in GEOS-Chem v8-02-01 through GEOS-Chem v8-02-03. In Oxidants and Chemistry Working Group. http://acmg.seas.harvard.edu/geos/wiki_docs/chemistry/chemistry_updates_v5.pdf. Accessed 22 Jun 2011

  • Finnveden G, Hauschild M, Ekvall T, Guinée J, Heijungs R, Hellweg S, Koehler A, Pennington D, Suh S (2009) Recent development in life cycle assessment. J Environ Manag 91:1–21

    Article  Google Scholar 

  • Guinée JB, Gorrée M, Heijungs R, Huppes G, Kleijn R, Koning A, Oers L, Sleeswijk AW, Suh S, Udo de Haes H, Bruijn H, Duin Rv, Huijbregts M (2001) An operational guide to the ISO standards: part A, Part B, Part 2B and Part 3

  • Hauschild M, Goedkoop M, Guinee J, Heijungs R, Huijbregts M, Jolliet O, Margni M, De Schryver A (2011) Recommendations for Life Cycle Impact Assessment in the European context - based on existing environmental impact assessment models and factors (International Reference Life Cycle Data System - ILCD handbook). European Commission-Joint Reasearch Centre (ed). p 159. http://publications.jrc.ec.europa.eu/repository/handle/111111111/26229

  • Heijungs R, Guinée JB, Huppes G, Lankreijer RM, Haes HAUd, Wegener A, Sleeswijk, Ansems AMM, Eggels AMM, Duin Rv, Goede HPd (1992) Environmental life cycle assessment of products. Guidelines and backgrounds. The Netherlands: Centre of Environmental Science

  • Huijbregts M, Schöpp W, Verkuijlen E, Heijungs R, Reijnders L (2000) Spatially explicit characterization of acidifying and eutrophying air pollution in life-cycle assessment. J Ind Ecol 4(3):75–92

    Article  CAS  Google Scholar 

  • Humbert S, Margni M, Jolliet O (2004) IMPACT 2002+: User Guide Draft for Version 2.0.1-37

  • Jacob D, Liu H, Mari C, Yantosca R (2000) Harvard wet deposition scheme for GMI. Harvard University Atmospheric Chemistry Modeling Group

  • Jeffries DS, Ouimet R (2004) 2004 Canadian Acid Deposition Sci. Assessment and Summary of Key Results Service Météorologique. Canada, Downsview

    Google Scholar 

  • Kottek M, Grieser J, Beck C, Rudolf B, Rubel F (2006) World map of the Köppen-Geiger climate classification updated. Meteorol Z 15(3):259–263

    Article  Google Scholar 

  • Kourzeneva E (2009) Global dataset for the parameterization of lakes in Numerical Weather Prediction and Climate modeling. ALADIN Newsletter, No 37, July-December, 2009, F. Bouttier and C. Fischer (eds) Meteo-France, Toulouse, pp 46-53

  • Krewitt W, Trukenmüller A, Bachmann TM, Heck T (2001) Country-specific damage factors for air pollutants. Int J Life Cycle Assess 6(4):199–210

    Article  CAS  Google Scholar 

  • Kuylenstierna J, Rodhe H, Cinderby S, Hicks K (2001) Acidification in developing countries: ecosystem sensitivity and the critical load approach on a global scale. Ambio 30(1):20–28

    CAS  Google Scholar 

  • Lehner B, Döll P (2004) Development and validation of a global database of lakes, reservoirs and wetlands. J Hydrol 296(1–4):1–22

    Article  Google Scholar 

  • NOAA National Climatic Data Center (2005) State of the Climate: Global Analysis for Annual 2005. www.ncdc.noaa.gov/sotc/global/2005/13. Accessed 5 Jun 2011

  • Payet J (2006) Novel Methods for Integrated Risk Assessment of Cumulative Stressors in Europe: D.4.1.4 Report describing a method for the quantification of impacts on aquatic freshwater ecosystems resulting from different stressors (e.g., toxic substances, eutrophication, etc.).

  • Posch M (2004) Manual on methodologies and criteria for modelling and mapping critical loads & levels and air pollution effects, risks and trends Chapter 5: Mapping critical loads. UNECE convention on long-range Transboundary air pollution, UNECE

  • Potting J, Hauschild MZ (2006) Spatial differentiation in Life Cycle Impact Assessment: a decade of method development to increase the environmental realism in LCIA. Int J Life Cycle Assess 11(1):11–13

    Google Scholar 

  • Potting J, Schöpp W, Blok K, Hauschild M (1998) Site-dependent life-cycle impact assessment. J Ind Ecol 2(2):63–87

    Article  CAS  Google Scholar 

  • Rapp L, Bishop K (2003) Modeling surface water critical loads with PROFILE: possibilities and challenges. J Environ Qual 32:2290–2300

    Article  CAS  Google Scholar 

  • Roy P-O, Deschênes L, Margni M (2012a) Life cycle impact assessment of terrestrial acidification: modeling spatially explicit soil sensitivity at the global scale. Environ Sci Technol 46(15):8270–8278

    Article  CAS  Google Scholar 

  • Roy P-O, Huijbregts MAJ, Deschênes L, Margni M (2012b) Spatially-differentiated atmospheric source-receptor relationships for nitrogen oxides, sulfur oxides and ammonia emissions at the global scale for life cycle impact assessment. Atmos Environ 62:74–81

    Article  CAS  Google Scholar 

  • Seppälä J, Posch M, Johansson M, Hetteling J-P (2006) Country-dependant characterisation factors for acidification and terrestrial eutrophication based on accumulated exceedance as an impact category indicator. Int J Life Cycle Assess 11(6):403–416

    Article  Google Scholar 

  • Skjelkvale BL, Stoddard JL, Jeffries DS, Tørseth K, Høgasen T, Bowman J, Mannio J, Monteith DT, Mosello R, Rogora M, Rzychon D, Vesely J, Wieting J, Wilander A, Worsztynowicz A (2005) Regional scale evidence for improvements in surface water chemistry 1990-2001. Environ Pollut 137:165–176

    Article  CAS  Google Scholar 

  • van Zelm R, Huijbregts M, van Jaarsveld HA, Jan Reinds G, de Zwart D, Struijs J, van de Meent D (2007) Time horizon dependant characterization factors for acidification in life-cycle assessment based on forest plant species occurrence in Europe. Environ Sci Technol 41(3):922–927

    Article  Google Scholar 

  • Vörösmarty CJ, Fekete BM, Meybeck M, Lammers R (2000a) Geomorphometric attributes of the global system of rivers at 30-minute spatial resolution (STN-30). J Hydrol 237:17–39

    Article  Google Scholar 

  • Vörösmarty CJ, Fekete BM, Meybeck M, Lammers R (2000b) Global system of rivers: Its role in organizing continental land mass and defining land-to-ocean linkages. Glob Biogeochem Cycles 14:599–621

    Article  Google Scholar 

  • Wang B-J, Chen C-TA (1990) Geochemistry of the anoxic Great Ghost lake. Proc Nat Sci Counc Repub China 14(1):14–20

    Google Scholar 

  • Weidema BP, Bauer C, Hischier R, Mutel C, Nemecek T, Reinhard J, Vadenbo CO, Wernet G (2012) Overview and methodology: Data quality guideline for the ecoinvent database version 3

Download references

Acknowledgments

The CIRAIG would like to thank its industrial partners for their financial support: ArcelorMittal, Bombardier, Bell Canada, Cascades, Eco Entreprises Québec, RECYC-QUÉBEC, Groupe EDF, Gaz de France, Hydro-Québec, Johnson & Johnson, LVMH, Michelin, Mouvement des caisses Desjardins, Nestlé, Rio Tinto Alcan, RONA, SAQ, Solvay, Total, Umicore and Veolia Environment.

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Correspondence to Pierre-Olivier Roy.

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Responsible editor: Mark Huijbregts

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Roy, PO., Deschênes, L. & Margni, M. Uncertainty and spatial variability in characterization factors for aquatic acidification at the global scale. Int J Life Cycle Assess 19, 882–890 (2014). https://doi.org/10.1007/s11367-013-0683-0

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  • DOI: https://doi.org/10.1007/s11367-013-0683-0

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