PMID- 30566497
OWN - NLM
STAT- MEDLINE
DCOM- 20190528
LR  - 20200309
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 13
IP  - 12
DP  - 2018
TI  - Does the use of pre-calculated uncertainty values change the conclusions of 
      comparative life cycle assessments? - An empirical analysis.
PG  - e0209474
LID - 10.1371/journal.pone.0209474 [doi]
LID - e0209474
AB  - In life cycle assessment (LCA), performing Monte Carlo simulation (MCS) using 
      fully dependent sampling typically involves repeated inversion of a technology 
      matrix for a sufficiently large number of times. As the dimension of technology 
      matrices for life cycle inventory (LCI) databases grows, MCS using fully 
      dependent sampling is becoming a computational challenge. In our previous work, 
      we pre-calculated the distribution functions of the entire LCI flows in the 
      ecoinvent ver. 3.1 database to help reduce the computation time of running fully 
      dependent sampling by individual LCA practitioners. However, it remains as a 
      question whether the additional errors due to the use of pre-calculated 
      uncertainty values are large enough to alter the conclusion of a comparative 
      study, and, if so, what is the odds of such cases. In this study, we empirically 
      tested the probability of altering the conclusion of a comparative LCA due to the 
      use of pre-calculated uncertainty values. We sampled 10,000 random pairs of 
      elementary flows of ecoinvent LCIs (ai and bi) and ran MCSs (1) using 
      pre-calculated uncertainty values and (2) using fully dependent sampling. We 
      analyzed the distribution of the differences between ai and bi (i.e., ai-bi) of 
      each run, and quantified the probability of reversing (e.g., ai > bi became ai < 
      bi) or moderating the conclusion (e.g., ai > bi became ai  approximately  bi). In order to 
      better replicate the situation under a comparative LCA setting, we also sampled 
      10,000 random pairs of elementary flows from the processes that produce 
      electricity, and repeated the same procedure. The results show that no LCIs 
      derived using pre-calculated uncertainty values constitute large enough 
      differences from those using fully dependent sampling to reverse the conclusion. 
      However, in 5.3% of the cases, the conclusion from one approach is moderated 
      under the other approach or vice versa. When elementary flow pairs are sampled 
      only from the electricity-producing processes, the probability of moderating the 
      conclusions increases to 10.5%, while that of reversing the conclusions remains 
      nil. As the number of unit processes in LCI databases increases, running full 
      MCSs in a PC-environment will continue to be a challenge, which may lead some LCA 
      practitioners to avoid uncertainty analysis altogether. Our results indicate that 
      pre-calculated distributions for LCIs can be used as a proxy for comparative LCA 
      studies in the absence of adequate computational resources for full MCS. 
      Depending on the goal and scope of the study, LCA practitioners should consider 
      using pre-calculated distributions if the benefits of doing so outweighs the 
      associated risks of altering the conclusion.
FAU - Qin, Yuwei
AU  - Qin Y
AD  - Bren School of Environmental Science and Management, University of California, 
      Santa Barbara, California, United States of America.
FAU - Suh, Sangwon
AU  - Suh S
AUID- ORCID: 0000-0001-8290-6276
AD  - Bren School of Environmental Science and Management, University of California, 
      Santa Barbara, California, United States of America.
LA  - eng
PT  - Journal Article
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20181219
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - Environmental Monitoring/*methods
MH  - Monte Carlo Method
MH  - *Uncertainty
PMC - PMC6300256
COIS- The authors have declared that no competing interests exist.
EDAT- 2018/12/20 06:00
MHDA- 2019/05/29 06:00
PMCR- 2018/12/19
CRDT- 2018/12/20 06:00
PHST- 2018/02/08 00:00 [received]
PHST- 2018/12/06 00:00 [accepted]
PHST- 2018/12/20 06:00 [entrez]
PHST- 2018/12/20 06:00 [pubmed]
PHST- 2019/05/29 06:00 [medline]
PHST- 2018/12/19 00:00 [pmc-release]
AID - PONE-D-18-04226 [pii]
AID - 10.1371/journal.pone.0209474 [doi]
PST - epublish
SO  - PLoS One. 2018 Dec 19;13(12):e0209474. doi: 10.1371/journal.pone.0209474. 
      eCollection 2018.