Time-adjusted global warming potentials for LCA and carbon footprints

Kendall, Alissa

doi:10.1007/s11367-012-0436-5

Cited by 129 publications

(92 citation statements)

References 19 publications

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“…1a,b). Present approaches to technology evaluation use an equivalency metric to convert emissions to their CO 2 -equivalent value [1][2][3]9]. The most common metric is the global warming potential (GWP(τ )), which takes the ratio of the time-integrated radiative forcing of pulse non-CO 2 and CO 2 emissions over a fixed time horizon (τ ), typically 100 years.…”

Section: Introductionmentioning

confidence: 99%

“…These metrics are formulated to make either instantaneous [15,16] or time-integrated comparisons of gases [1,9], based on their relative contributions to radiative forcing [1,12], temperature change [15,16], or economic impacts [17,18]. Alternatively, some have argued that direct comparisons of gases are not feasible, and have called for a multi-basket emissions policy [5,6], where similar gases are grouped into baskets and trading between baskets is prohibited.…”

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confidence: 99%

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Climate impacts of energy technologies depend on emissions timing

Edwards

Trancik

2014

Nature Clim Change

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Energy technologies emit greenhouse gases with differing radiative efficiencies and atmospheric lifetimes [1][2][3]. Standard practice for evaluating technologies, which uses the global warming potential (GWP) to compare the integrated radiative forcing of emitted gases over a fixed time horizon [4], does not acknowledge the importance of a changing background climate relative to climate change mitigation targets [5,6]. Here we demonstrate that the GWP misvalues the impact of CH 4 -emitting technologies as mid-century approaches, and we propose a new class of metrics to evaluate technologies based on their time of use. The instantaneous climate impact (ICI) compares gases in an expected radiative forcing stabilization year, and the cumulative climate impact (CCI) compares their integrated radiative forcing up to a stabilization year. Using these dynamic metrics, we quantify the climate impacts of technologies and show that high-CH 4 -emitting energy sources become less advantageous over time. The impact of natural gas for transportation, with CH 4 leakage, exceeds that of gasoline within 1-2 decades for a commonly-cited 3 W/m 2 stabilization target. The impact of algae biodiesel overtakes that of corn ethanol within 2-3 decades, where algae co-products are used to produce biogas and corn co-products are used for animal feed. The proposed metrics capture the changing importance of CH 4 emissions as a climate threshold is approached, thereby addressing a major shortcoming of the GWP for technology evaluation [7,8].Comparing the climate impacts of energy technologies is challenging because they emit differing types and quantities of greenhouse gases, most notably CH 4 and CO 2 , and these gases have dissimilar properties (Fig. 1a,b). Present approaches to technology evaluation use an equivalency metric to convert emissions to their CO 2 -equivalent value [1][2][3]9]. The most common metric is the global warming potential (GWP(τ )), which takes the ratio of the time-integrated radiative forcing of pulse non-CO 2 and CO 2 emissions over a fixed time horizon (τ ), typically 100 years. The GWP(100) was initially intended as a placeholder [10], in large part because of its sensitivity to the arbitrarily selected time horizon [7] (Fig. 1c,d), but it remains the standard metric for technology evaluation.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Climate impacts of energy technologies depend on emissions timing

Edwards

Trancik

2014

Nature Clim Change

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“…As detailed in the main manuscript, the impact of GHG time-dependency was tested for the cultivation of Miscanthus (including iLUC), based on the methodology described in (86). Table S19 presents the emissions occurring over the 20y time scope of the study, for two selected processes only: cultivation of Miscanthus and iLUC.…”

Section: Gwp Time-dependencymentioning

confidence: 99%

Bioenergy Production from Perennial Energy Crops: A Consequential LCA of 12 Bioenergy Scenarios including Land Use Changes

Tonini

Hamelin

Wenzel

et al. 2012

Environ. Sci. Technol.

105

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In the endeavor of optimizing the sustainability of bioenergy production in Denmark, this consequential life cycle assessment (LCA) evaluated the environmental impacts associated with the production of heat and electricity from one hectare of Danish arable land cultivated with three perennial crops: ryegrass (Lolium perenne), willow (Salix viminalis) and Miscanthus giganteus. For each, four conversion pathways were assessed against a fossil fuel reference: I) anaerobic co-digestion with manure, II) gasification, III) combustion in small-to-medium scale biomass combined heat and power (CHP) plants and IV) co-firing in large scale coal-fired CHP plants. Soil carbon changes, direct and indirect land use changes as well as uncertainty analysis (sensitivity, MonteCarlo) were included in the LCA. Results showed that global warming was the bottleneck impact, where only two scenarios, namely willow and Miscanthus co-firing, allowed for an improvement as compared to the reference (-82 and -45 t CO 2 -eq. ha -1 , respectively). The indirect land use changes impact was quantified as 310 ±170 t CO 2 -eq. ha -1 , representing a paramount average of 41% of the induced greenhouse gas emissions. The uncertainty analysis confirmed the results robustness and highlighted the indirect land use changes uncertainty as the only uncertainty that can significantly change the outcome of the LCA results.3

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“…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.…”

Section: Introductionmentioning

confidence: 56%

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

Beloin-Saint-Pierre

Heijungs

Blanc

2014

Int J Life Cycle Assess

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Purpose By analyzing the latest developments in the dynamic life cycle assessment (DLCA) methodology, we identify an implementation challenge with the management of new temporal information to describe each system we might want to model. To address this problem, we propose a new method to differentiate elementary and process flows on a temporal level, and explain how it can generate temporally differentiated life cycle inventories (LCI), which are necessary inputs for dynamic impact assessment methods. Methods First, an analysis of recent DLCA studies is used to identify the relevant temporal characteristics for an LCI. Then, we explain the implementation challenge of handling additional temporal information to describe processes in life cycle assessment (LCA) databases. Finally, a new format of temporal description is proposed to minimize the current implementation problem for DLCA studies. Results and discussion A new format of process-relative temporal distributions is proposed to obtain a temporal differentiation of LCA database information (elementary flows and product flows). A new LCI calculation method is also proposed since the new format for temporal description is not compatible with the traditional LCI calculation method. Description of the requirements and limits for this new method, named enhanced structural path analysis (ESPA), is also presented. To conclude the description of the ESPA method, we illustrate its use in a strategically chosen scenario. The use of the proposed ESPA method for this scenario reveals the need for the LCA community to reach an agreement on common temporal differentiation strategies for future DLCA studies. Conclusions We propose the ESPA method to obtain temporally differentiated LCIs, which should then require less implementation effort for the system-modeling step (LCA database definition), even if such concepts cannot be applied to every process.

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Time-adjusted global warming potentials for LCA and carbon footprints

Cited by 129 publications

References 19 publications

Climate impacts of energy technologies depend on emissions timing

Climate impacts of energy technologies depend on emissions timing

Bioenergy Production from Perennial Energy Crops: A Consequential LCA of 12 Bioenergy Scenarios including Land Use Changes

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

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