A characterization model with spatial and temporal resolution for life cycle impact assessment of photochemical precursors in the United States

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 NO_x. The summer time characterization factors for NO_x 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 NO_x 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. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.