Life‐Cycle Assessment and Temporal Distributions of Emissions: Developing a Fleet‐Based Analysis

Abstract

Although the product-centered focus of life-cycle assessment has been one of its strengths, this analytical perspective embeds assumptions that may conflict with the realities of environmental problems. This ar ticle demonstrates, through a series of mathematical derivations, that all the products in use, rather than a single product, frequently should be the appropriate unit of analysis. Such a "fleet-centered" approach supplies a richer perspective on the comparative emissions burdens generated by alternative products, and it eliminates certain simplifying assumptions imposed upon the analysis by a product-centered approach.A sample numerical case, examining the comparative emissions of steel-intensive and aluminum-intensive automobiles, is presented to contrast the results of the two approaches. The fleet-centered analysis shows that the "crossover time" (i.e., the time required before the fuel economy benefits of the lighter aluminum vehicle offset the energy intensity of the processes used to manufacture the aluminum in the first place) can be dramatically longer than that predicted by a product-centered life-cycle assessment.The fleet-centered perspective explicitly introduces the notion of time as a critical element of comparative lifecycle assessments and raises important questions about the role of the analyst in selecting the appropriate time horizon for analysis. Moreover, with the introduction of time as an appropriate dimension to life-cycle assessment, the influences of effects distributed over time can be more naturally and consistently treated.

The ESPA (Enhanced Structural Path Analysis) method: a solution to an implementation challenge for dynamic life cycle assessment studies

“…Using this new impact assessment method, one case study has shown that conclusions from an LCA study might significantly vary when different time horizons are considered. Other publications (Dubreuil et al 2007;Field et al 2000;Hellweg 2001;Kendall and Price 2012;Kendall 2012) have presented similar conclusions even though some authors (Schwietzke et al 2011) minimize its relevance for biofuel scenarios.…”

“…In the last 15 years, however, compelling arguments have been proposed to explain why industrial and environmental dynamics might have significant impacts on the results of some LCA studies (Field et al 2000;Finnveden et al 2009;Graedel 1998;Owens 1997;Reap et al 2008;Udo de Haes et al 2002). Indeed, not considering temporal variability is now recognized as one of the shortcomings of the LCA methodology (ISO 14 040 and 14 044).…”

“…1.2 Considering time for system modeling and life cycle inventory calculation Specific mathematical models have been provided to account for a few temporal systems variations in different DLCA studies (Bjork and Rasmuson 2002;Collinge et al 2011;Field et al 2000;Kendall et al 2009;Pehnt 2006;Stasinopoulos et al 2012;Zhai and Williams 2010). Such models usually describe how parts of systems vary over the life cycles.…”

Improvement of Certified Artisan Cheese Production through Systemic Analysis—Serra da Estrela PDO

“…Systemic maps identify variables which may not typically be identified and considered in LCA studies but may have significant influence upon environmental impacts through cause-effect chains [11]. Suggestions for optimization are traditionally made on the basis of a single unit, not taking into account, for instance, the product line [12][13][14], infrastructure systems [15], the interrelations between the products and the infrastructure system. The traditional approach may hinder the possibilities of achieving higher levels of efficiency and of reduction of negative environmental impacts [16].…”

Dynamic fleet-based life-cycle greenhouse gas assessment of the introduction of electric vehicles in the Portuguese light-duty fleet

“…In addition, they lack a future time perspective regarding advances in material processing, technology development and changes in electricity production (Nordelöf et al 2014). However, when the goal is to assess new or changing technologies, transient effects may be important and cannot be captured with such static, single-product analysis (Field et al 2000). Moreover, if the goal is to explore solutions able to reduce overall environmental impacts (e.g., to meet medium/long-term policy targets), both scale and timing of adoption may influence the results (Hillman and Sandén 2008;Stasinopoulos et al 2011).…”