Abstract
Background, aim, and scope
Traditional life cycle impact assessment methodologies have used aggregated characterization factors, neglecting spatial and temporal variations in regional impacts like photochemical oxidant formation. This increases the uncertainty of the LCA results and diminishes the ease of decision-making. This study compares four common impact assessment methods, CML2001, Eco-indicator 99, TRACI, and EDIP2003, on their underlying models, spatial and temporal resolution, and the level at which photochemical oxidant impacts are calculated. A new characterization model is proposed that incorporates spatial and temporal differentiation.
Materials and methods
A photochemical air quality modeling system (CAMx-MM5-SMOKE) is used to simulate the process of formation, transformation, transport, and removal of photochemical pollutants. Monthly characterization factors for individual US states are calculated at three levels along the cause–effect chain, namely, fate level, human and ecosystem exposure level, and human effect level.
Results and discussion
The results indicate that a spatial variability of one order of magnitude and a temporal variability of two orders of magnitude exist in both the fate level and human exposure and effect level characterization factors for NOx. The summer time characterization factors for NOx are higher than the winter time factors. However, for anthropogenic VOC, the summer time factors are lower than the winter time in almost half of the states. This is due to the higher emission rates of biogenic VOCs in the summer. The ecosystem exposure factors for NOx and VOC do not follow a regular pattern and show a spatial variation of about three orders of magnitude. They do not show strong correlation with the human exposure factors. Sensitivity analysis has shown that the effect of meteorology and emission inputs is limited to a factor of three, which is several times smaller than the variation seen in the factors.
Conclusions
Uncertainties are introduced in the characterization of photochemical precursors due to a failure to consider the spatial and temporal variations. Seasonal variations in photochemical activity influence the characterization factors more than the location of emissions. The human and ecosystem exposures occur through different mechanisms, and impacts calculated at the fate level based only on ozone concentration are not a good indicator for ecosystem impacts.
Recommendations and perspectives
Spatial and temporal differentiation account for fate and transport of the pollutant, and the exposure of and effect on the sensitive human population or ecosystem. Adequate resolution for seasonal and regional processes, like photochemical oxidant formation, is important to reduce the uncertainty in impact assessment and improve decision-making power. An emphasis on incorporating some form of spatial and temporal information within standard LCI databases and using adequately resolved characterization factors will greatly increase the fidelity of a standard LCA.
Similar content being viewed by others
References
Andersson-Sköld Y, Grennfelt P, Pliejel K (1992) Photochemical ozone creation potentials: a study of different concepts. J Air Waste Manag Assoc 42(9):1152–1158
Bare JC, Norris GA, Pennington DW, McKone T (2003) TRACI: The Tool for the Reduction and Assessment of Chemical and other environmental Impacts. J Ind Ecol 6(3):49–78
Bell MI, McDermott A, Zeger SL, Samet JM, Dominici F (2004) Ozone and short-term mortality in 95 US urban communities, 1987–2000. JAMA 292(19):2372–2378
Bellekom S, Potting J, Benders R (2006) Feasibility of applying site-dependent impact assessment of acidification in LCA. Int J LCA 11(6):417–424
Carter WPL (1998) Updated maximum incremental reactivity scale for regulatory applications. Preliminary report to California Air Resource Board. August 6. http://pah.cert.ucr.edu/∼carter/bycarter.htm, accessed 21.7.2007
Carter WPL (2007) Development of the SAPRC-07 chemical mechanism and updated ozone reactivity scales. Final report to California Air Resource Board. August 31. http://pah.cert.ucr.edu/∼carter/SAPRC/, accessed Sept. 15, 2007
Derwent RG, Jenkin ME (1991) Hydrocarbons and the long range transport of ozone and PAN across Europe. Atmos Env 25A(8):1661–1678
Derwent RG, Jenkin ME, Saunders SM (1996) Photochemical ozone creation potential for a large number of reactive hydrocarbons under European conditions. Atmos Env 30(2):181–199
Derwent RG, Jenkin ME, Saunders SM, Pilling MJ (2001) Characterization of the reactivities of volatile organic compounds using a master chemical mechanism. J Air Waste Manag Assoc 51(5):699–707
Environ International Corporation (2006) CAMx user’s guide v4.40. http://www.camx.com/publ/index.php, accessed March 4, 2007
Goedkoop M, Spriensma R (2001) The eco-indicator 99 A damage oriented method for life cycle impact assessment. PRé Consultants, Amersfoort
Guinée JB, Gorrée M, Heijungs R, Huppes G, Kleijn R, de Koning A, van Oers L, Sleeswijk AW, Suh S, Udo de Haes HA, de Bruijn H, van Duin R, Huijbregts MAJ (2002) Handbook on Life Cycle Assessment: Operational Guide to the ISO Standards. Kluwer, Dordrecht
Haushild M, Wenzel H (1998) Environmental assessment of products vol. 2—scientific background. Kluwer, Boston
Hauschild M, Potting J (2005) Spatial differentiation in life cycle impact assessment—the EDIP2003 methodology. Environmental News No. 80. Danish Environmental Protection Agency, Copenhagen, Denmark
Heyes C, Schopp W, Amann M, Unger S (1996) A reduced form model to predict long term ozone concentrations in Europe. Interim report WP-96-12/December. International Institute for Applied Systems Analysis, Laxenburg, Austria
Heyes C, Schopp W, Amann M, Bertok I, Cofala J, Gyarfas F, Klimont Z, Makowski M, Shibayev S (1997) A model for optimizing strategies for controlling ground level ozone in Europe. Interim report IR-97-002/January 1997. International Institute for Applied Systems Analysis, Laxenburg
Hofstetter P (1998) Perspectives in life cycle impact assessment: a structured approach to combine models of the technosphere, ecosphere, and valuesphere. Kluwer, Boston
Kasibhatla P, Chameides WL, Saylor RD, Olerud D (1998) Relationships between regional ozone pollution and emissions of nitrogen oxides in the eastern United States. J Geophys Res 103(D17):22663–22669
Lee SM, Fernando HJS, Clarke-Grossman S (2007) MM5-SMOKE-CMAQ as a modeling tool for the 8-h ozone regulatory enforcement: application to the state of Arizona. Environ Model Assessment 12:63–74
Norris GA (2003) Impact characterization in the Tool for the Reduction and Assessment of Chemical and other environmental Impacts. J Ind Ecol 6(3–4):79–101
Pennington DW, Potting J, Finnveden G, Lindeijer E, Jolliet O, Rydberg T, Rebitzer G (2004) Life cycle assessment part 2: current impact assessment practice. Env Int 30:721–739
Potting J, Haushild M (2005) Background for spatial differentiation in life cycle impact assessment—the EDIP2003 methodology. Environmental Project No. 996. Danish Environmental Protection Agency, Copenhagen, Denmark. http://www2.mst.dk/Udgiv/publications/2005/87-7614-581-6/html/indhold_eng.htm, accessed March 10, 2007
Potting J, Hauschild M (2006) Spatial differentiation in life cycle impact assessment. Int J LCA 11(Sp. Iss. 1):11–13
Russell AG (1997) Regional photochemical air quality modeling: model formulations, history, and state of science. Annu Rev Energy Environ 22:537–588
Shannon JD (1991) A model of regional long-term average sulfur atmospheric pollution, surface removal, and net horizontal flux. Atmos Environ 15(5):689–701
Shah VP (2008) A characterization model with spatial and temporal resolution for life cycle impact assessment of photochemical precursors in the United States. MS Thesis. University of Pittsburgh, Pittsburgh PA, USA
Simpson D (1993) Photochemical model calculations over Europe for two extended summer periods: 1985 and 1989. Model results and comparison with observations. Atmos Env 27A(6):921–943
Tonnesen G, Wang Z, Omary M, Chien CJ, Morris R, Mansell G (2005) Final report for the Western Regional Air Partnership (WRAP) Regional Modeling Center (RMC) for the project period March 1, 2004 through February 28, 2005. http://pah.cert.ucr.edu/aqm/308/reports/final, accessed Sept. 18, 2007
Udo de Haes HA, Jolliet O, Finnveden G, Goedkoop M, Hauschild M, Hertwich E, Hofstetter P, Jolliet O, Klöpffer W, Krewitt W, Lindeijer E, Muller-Wank R, Olsen I, Pennington D, Potting J, Steen B (2002) Life cycle impact assessment: striving towards best practice. SETAC, Pensacola
USEPA (2005a) Technical support document for the final Clean Air Interstate Rule—air quality modeling. http://www.epa.gov/scram001/reportsindex.htm, accessed Sept. 8, 2007
USEPA (2005b) Regulatory impact analysis for the final Clean Air Interstate Rule. EPA-452/R-05-002. http://www.epa.gov/scram001/reportsindex.htm, accessed Jan. 18, 2008
Author information
Authors and Affiliations
Corresponding author
Additional information
Responsible editors: Michael Hauschild and José Potting
Electronic supplementary material
Below is the link to the electronic supplementary material.
ESM 1
Supporting Information (PDF 148 kb)
Rights and permissions
About this article
Cite this article
Shah, V.P., Ries, R.J. A characterization model with spatial and temporal resolution for life cycle impact assessment of photochemical precursors in the United States. Int J Life Cycle Assess 14, 313–327 (2009). https://doi.org/10.1007/s11367-009-0084-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11367-009-0084-6