Page 288 - Biofuels for a More Sustainable Future
P. 288
Life-cycle costing: Analysis of biofuel production systems 253
Hoogmartens, R., Van Passel, S., Van Acker, K., Dubois, M., 2014. Bridging the gap
between LCA, LCC and CBA as sustainability assessment tools. Environ. Impact Assess.
Rev. 48, 27–33. https://doi.org/10.1016/j.eiar.2014.05.001.
Ilg, P., Scope, C., Muench, S., Guenther, E., 2017. Uncertainty in life cycle costing for long-
range infrastructure. Part I: leveling the playing field to address uncertainties. Int. J. Life
Cycle Assess. 22, 277–292. https://doi.org/10.1007/s11367-016-1154-1.
Kennedy, D.J., Montgomery, D.C., Quay, B.H., 1996. Data quality. Int. J. Life Cycle Assess.
1, 199–207. https://doi.org/10.1007/BF02978693.
Khang, D.S., Tan, R.R., Uy, O.M., Promentilla, M.A.B., Tuan, P.D., Abe, N., et al., 2017.
Design of experiments for global sensitivity analysis in life cycle assessment: the case of
biodiesel in Vietnam. Resour. Conserv. Recycl. 119, 12–23. https://doi.org/10.1016/j.
resconrec.2016.08.016.
Khang, D.S., Tan, R.R., Uy, O.M., Promentilla, M.A.B., Tuan, P.D., Abe, N., et al., 2018.
A design of experiments approach to the sensitivity analysis of the life cycle cost of bio-
diesel. Clean Techn. Environ. Policy 20, 573–580. https://doi.org/10.1007/s10098-
017-1384-3.
Kloepffer, W., 2008. Life cycle sustainability assessment of products (with comments by
Helias A. Udo de Haes, p. 95). Int. J. Life Cycle Assess. 13, 89–94. https://doi.org/
10.1065/lca2008.02.376.
Lloyd, S.M., Ries, R., 2008. Characterizing, propagating, and analyzing uncertainty in life-
cycle assessment: a survey of quantitative approaches. J. Ind. Ecol. 11, 161–179. https://
doi.org/10.1162/jiec.2007.1136.
Moreau, V., Weidema, B.P., 2015. The computational structure of environmental life cycle
costing. Int. J. Life Cycle Assess. 20, 1359–1363. https://doi.org/10.1007/s11367-015-
0952-1.
Myint, L.L., El-Halwagi, M.M., 2009. Process analysis and optimization of biodiesel produc-
tion from soybean oil. Clean Techn. Environ. Policy 11, 263–276. https://doi.org/
10.1007/s10098-008-0156-5.
Ong, H.C., Mahlia, T.M.I., Masjuki, H.H., Honnery, D., 2012. Life cycle cost and sensi-
tivity analysis of palm biodiesel production. Fuel 98, 131–139. https://doi.org/10.1016/
j.fuel.2012.03.031.
Peters, G.P., 2007. Efficient algorithms for life cycle assessment, input-output analysis, and
Monte-Carlo analysis. Int. J. Life Cycle Assess. 12, 373–380. https://doi.org/10.1065/
lca2006.06.254.
R€odger, J.M., Kjær, L.L., Pagoropoulos, A., 2017. Life cycle costing: an introduction. In: -
Hauschild, M., Rosenbaum, R.K., Olsen, S. (Eds.), Life Cycle Assessment: Theory and
Practice. Springer International Publishing, Cham, pp. 373–399. https://doi.org/
10.1007/978-3-319-56475-3_15.
Tan, R.R., 2008. Using fuzzy numbers to propagate uncertainty in matrix-based LCI. Int. J.
Life Cycle Assess. 13, 585–592. https://doi.org/10.1007/s11367-008-0032-x.
Tang, Z.C., Zhenzhou, L., Zhiwen, L., Ningcong, X., 2015. Uncertainty analysis and global
sensitivity analysis of techno-economic assessments for biodiesel production. Bioresour.
Technol. 175, 502–508. https://doi.org/10.1016/j.biortech.2014.10.162.
United Nations, 2015. Transforming our World: The 2030 Agenda for Sustainable
Development. United Nations Secretariat, New York.
UNEP/SETAC, 2011. Life Cycle Initiative. Towards a Life Cycle Sustainability Assessment.
Ye, K.Q., 1998. Orthogonal column Latin hypercubes and their application in
computer experiments. J. Am. Stat. Assoc. 93, 1430–1439. https://doi.org/10.1080/
01621459.1998.10473803.