Valuing temporary carbon storage

Levasseur, Annie; Brandão, Miguel; Lesage, Pascal; Margni, Manuele; Pleurdeau, David; Clift, Roland; Samson, Réjean

doi:10.1038/nclimate1335

Cited by 82 publications

(48 citation statements)

References 9 publications

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“…Since emissions are usually aggregated to a single point in time, the information required to consistently handle fixed and finite time horizons is missing (Levasseur et al 2011). Methods to overcome this limitation were proposed, mainly for the global warming impact category.…”

Section: Temporally Differentiated Cfsmentioning

confidence: 99%

Temporal differentiation of background systems in LCA: relevance of adding temporal information in LCI databases

Pinsonnault

Lesage

Levasseur

et al. 2014

Int J Life Cycle Assess

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Purpose Because the potential impacts of emissions and extractions can be sensitive to timing, the temporal aggregation of life cycle inventory (LCI) data has often been cited as a limitation in life cycle assessment (LCA). Until now, examples of temporal emission and extraction distributions were restricted to the foreground processes of product systems. The objective of this paper is to evaluate the relevance of considering the temporal distribution of the background system inventory. Methods The paper focuses on the global warming impact category for which so-called dynamic characterization factors (CFs) were developed and uses the ecoinvent v2.2 database as both an example database to which temporal information can be added and a source of product systems to test the relevance of adding temporal information to the background system. Temporal information was added to the elementary and intermediate exchanges of 22 % of the unit processes in the database. Using the enhanced structure path analysis (ESPA) method to generate temporally differentiated LCIs in conjunction with time-dependent global warming characterization factors, potential impacts were calculated for all 4,034 product systems in the ecoinvent database. Results and discussion Each time, the results were calculated for (1) systems in which temporal information was only added to the first two tiers, representing studies in which only the foreground system is temporally differentiated, and (2) systems in which temporal information was also added to the background system. For 8.6 % of the database product systems, adding temporal differentiation to background unit processes affected the global warming impact scores by more than 10 %. For most of the affected product systems, considering temporal information in the background unit processes decreased the global warming impact scores. The sectors that show most sensitivity to the temporal differentiation of background unit processes are associated with wood and biofuel sectors. Conclusions Even though the addition of temporal information to unit processes in LCI databases would not benefit every LCA study, the enhancement can be relevant. It allows for a more accurate global warming impact assessment, especially for LCAs in which products of biomass are present in substantial amounts. Relevance for other impact categories could be discussed in further work.

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Section: Temporally Differentiated Cfsmentioning

confidence: 99%

Temporal differentiation of background systems in LCA: relevance of adding temporal information in LCI databases

Pinsonnault

Lesage

Levasseur

et al. 2014

Int J Life Cycle Assess

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“…The longer carbon is stored relative to the period of time its impact is considered, the greater the benefits of delaying its release (Levasseur et al, 2012). Under the most common time horizon (100 yr) used for carbon reporting under the United Nations Framework Convention on Climate Change (UNFCCC), OC stored for decades or longer becomes increasingly relevant (Levasseur et al, 2012;Marland et al, 2001;Trumbore, 2000). This necessitates the robust estimation of accumulation rates and residence times of soil OC within pools that persists over these longer time frames.…”

Section: Introductionmentioning

confidence: 99%

Modeling Organic Carbon Accumulation Rates and Residence Times in Coastal Vegetated Ecosystems

et al. 2019

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Coastal vegetated "blue carbon" ecosystems can store large quantities of organic carbon (OC) within their soils; however, the importance of these sinks for climate change mitigation depends on the OC accumulation rate (CAR) and residence time. Here we evaluate how two modeling approaches, a Bayesian age-depth model alone or in combination with a two-pool OC model, aid in our understanding of the time lines of OC within seagrass soils. Fitting these models to data from Posidonia oceanica soil cores, we show that age-depth models provided reasonable CAR estimates but resulted in a 22% higher estimation of OC burial rates when ephemeral rhizosphere OC was not subtracted. This illustrates the need to standardize CAR estimation to match the research target and time frames under consideration. Using a two-pool model in tandem with an age-depth model also yielded reasonable, albeit lower, CAR estimates with lower estimate uncertainty, which increased our ability to detect among-site differences and seascape-level trends. Moreover, the two-pool model provided several other useful soil OC diagnostics, including OC inputs, decay rates, and transit times. At our sites, soil OC decayed quite slowly both within fast cycling (0.028 ± 0.014 yr −1 ) and slow cycling (0.0007 ± 0.0003 yr −1 ) soil pools, resulting in OC taking between 146 and 825 yr to transit the soil system. Further, an estimated 85% to 93% of OC inputs enter slow-cycling soil pools, with transit times ranging from 891 to 3,115 yr, substantiating the importance of P. oceanica soils as natural, long-term OC sinks.

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“…The DLCA framework proposed by Levasseur and colleagues () relies on the development of a temporally differentiated life cycle inventory (TDLCI) that can then be converted into environmental impacts using time‐dependent CFs. Applying this DLCA framework, Levasseur and colleagues (, , ) have shown that considering emissions timing can be important in specific case studies, such as when fossil fuels FFs are replaced with biofuels or when the effects of temporary carbon storage are considered. Kendall () has reached similar conclusions for a commercial building case study when they used time‐adjusted warming potentials.…”

Section: Introduction and General Goalmentioning

confidence: 99%

Implementing a Dynamic Life Cycle Assessment Methodology with a Case Study on Domestic Hot Water Production

Beloin-Saint-Pierre¹,

Levasseur²,

Margni³

et al. 2016

J of Industrial Ecology

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International audienceThis work contributes to the development of a dynamic life cycle assessment (DLCA) methodology by providing a methodological framework to link a dynamic system modeling method with a time-dependent impact assessment method. This three-step methodology starts by modeling systems where flows are described by temporal distributions. Then, a temporally differentiated life cycle inventory (TDLCI) is calculated to present the environmental exchanges through time. Finally, time-dependent characterization factors are applied to the TDLCI to evaluate climate-change impacts through time. The implementation of this new framework is illustrated by comparing systems producing domestic hot water (DHW) over an 80-year period. Electricity is used to heat water in the first system, whereas the second system uses a combination of solar energy and gas to heat an equivalent amount of DHW at the same temperature. This comparison shows that using a different temporal precision (i.e., monthly vs. annual) to describe process flows can reverse conclusions regarding which case has the best environmental performance. Results also show that considering the timing of greenhouse gas (GHG) emissions reduces the absolute values of carbon footprint in the short-term when compared with results from the static life cycle assessment. This pragmatic framework for the implementation of time in DLCA studies is proposed to help in the development of the methodology. It is not yet a fully operational scheme, and efforts are still required before DLCA can become state of practice

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Valuing temporary carbon storage

Cited by 82 publications

References 9 publications

Temporal differentiation of background systems in LCA: relevance of adding temporal information in LCI databases

Temporal differentiation of background systems in LCA: relevance of adding temporal information in LCI databases

Modeling Organic Carbon Accumulation Rates and Residence Times in Coastal Vegetated Ecosystems

Implementing a Dynamic Life Cycle Assessment Methodology with a Case Study on Domestic Hot Water Production

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