Development of a Disaggregated Hybrid Model for Life Cycle Assessment and De-man
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Abstract: The de-manufacturing stage is an overlooked component of most current LCA (life cycle assessment) methodologies. Most of the current LCA techniques do not fully account for the usage of the product and end of life aspects. This paper introduces a comprehensive methodology that takes strong consideration of the inventory costs of use and end of life of the functional unit by combining manufacturing and de-manufacturing into the centerpiece of the hybrid analysis. In order to obtain this goal, a new disaggregated model was developed by enhancing current LCA hybrid methods related to life cycle inventory compilations. The new methodology is also compared to existing methodologies.
Key words: Disaggregated hybrid, hybrid life cycle analysis, life cycle analysis, LCA (life cycle assessment).
Since the number of sectors (including hypothetical sectors involved in creation of A matrix) is the same as the number of industries in B matrix, then number of columns in B matrix will match the number of columns in square A matrix. Since the part of calculations of the total environmental inventory is multiplication of B by (I – A)-1 and B~ by ?-1, then if A= |aij| is r × r matrix, then ?=|?ij| is r × r matrix as well, since the same process is considered in both cases. Then, using the same logic, B = |bij| andB~ =
| are both q × v matrices.
Sectors/processes in Bqxn = |bij| matrices are disaggregated exactly the same way as in A = |aij| matrices. The side q (pollutants/resources) does not change from the original methods, since the same pollutants and resources are considered regardless of methodology.
4.1 Tiered Disaggregated Hybrid
In the tiered hybrid, the direct manufacturing and downstream requirements (for manufacture, use and end-of-life), and some important near upstream requirements of the functional unit are examined by the PA [25, 26]. The remaining upstream (material extraction, etc.) requirements are examined by the IO analysis. Tiered hybrid also allows supplementing“missing” process data with equivalent IO data [8, 22, 25]. The tiered hybrid has the following structure shown in Eq. (20):
of the centerpiece of the method. Because de-manufacturing is included, arbitrary scaling factors are re-calculated, using techniques shown earlier in the chapter. Eq. (21) displays disaggregated tiered hybrid’s structure:
(21) where ″ refers to the disaggregated matrix that includes both manufacturing and de-manufacturing processes, and t is a 1 × n matrix, where values for the manufacturing stage are equal to one and values for the de-manufacturing stage range are scaled based on the forecasted relative environmental inventory of de-manufacturing based on the product design and expected technology change over the lifetime of the product.
In linear form, the disaggregated tiered hybrid is shown in Eq. (22).
where (n+1) and (n+2) sectors correspond to life cycle and end of life of functional unit. However, life and end-of-life sectors, if information is available, may be disaggregated further. For example, the life of the passenger vehicles may be disaggregated into such sectors as gasoline consumption, oil consumption, replacement parts manufacturing, etc.. By disaggregating sectors, it generates a new matrix A(n+p) ×(n+p), where p is a number of disaggregated sectors designed to describe life and/or end-of-life components of the functional unit as displayed in Eq. (26):
where,
subscript (r) refers to environmental cost of raw materials;
subscript (s) refers to environmental cost of transportation;
subscript (m) refers to environmental cost of manufacturing;
subscript (l) refers to environmental cost of useful life;
subscript (d) refers to environmental cost of de-manufacturing;
subscript (e) refers to environmental cost of end of life.
Coefficient t is a temporal coefficient that may be taken into consideration to account for the interventions that affect environment over the significant length of time. In cases where time is not a significant factor, or not enough data is available, t may be set to value of 1.
The environmental inventory of the end of life may be further separated into components via Eq. (30):
aij(e) = dcd + rcr + ucu + (1-d-r-u)cg (30)
where, d is the percent of the material/product that is being disposed;
cd is an environmental cost coefficient of disposal.
In the same way, “r” represents recycling, “u”represents “reuse” and “g” represents “energy recovery and any other alternative methods of completion of product’s life”.
If Eq. (24) or Eq. (25)’s format is chosen, a single entry of aij changes from original (currently used in the literature) aij (p) into aij (total), where:
aij = aij (total) = (1-l-e)aij + laij + eaij (31)
of the method. They are:
? The proposed method requires an exchange of proprietary information between the manufacturer and de-manufacturer (this may not be the case if the manufacturer is responsible for treatment of its own products at the end of their useful life);
? The data collection process on the de-manufacturing stage is difficult since the manufactured product may not have yet completed its lifecycle and, therefore, have not arrived to the de-manufacturing stage. Then, the de-manufacturing data for the similar (earlier versions) product may be used and adjusted by factor t, as described earlier. In addition, any change to the design of the product may be used to estimate changes in de-manufacturing inventory compilations. Such estimates bring in errors due to timing of de-manufacturing and changes in product design. However, for many commodity products and mature market products de-manufacturing data may be reasonably accurate. For new market products, however, such approach may introduce a large degree of error, comparable with error due to use of IO data.
Process is more time and cost consuming, compared to other hybrid methods (it may not be more time consuming than integrated hybrid, depending on application).
At the present time, no computer software is designed to account for disaggregated hybrid method analysis.
The disaggregated hybrid method, similar to other LCA methods, may be prone to errors based on inputted data. Actual impact of errors is yet to be determined, based on the practical examples. From the theoretical standpoint, the disaggregated hybrid method is more accurate than the tiered hybrid method, more accurate than the IO-based hybrid method and very different from the integrated method to judge the accuracy the integrated hybrid has only been first introduced by Suh [16] less than seven years ago, and few studies regarding errors are published.
emission in Taiwan: An input-output approach, Energy Pol. 26 (1998) 5-12.
[14] R. Heijungs, S. Suh, The Computational Structure of Life Cycle Assessment, Kluwer Academic Publishers, Dordrecht, Netherlands, 2002.
[15] T. Marheineke, R. Friedrich, W. Krewitt, Application of a Hybrid Approach to the Life Cycle Inventory Analysis of a Freight Transport Task, SAE Tech. Paper Series 982201, Atlanta, 1998.
[16] S. Suh, System boundary selection in life-cycle inventories using hybrid approaches, Env. Sci. and Tech. 38 (3) (2004) 657-664.
[17] Y. Moriguchi, Y. Kondo, H. Shimizu, Analyzing the life cycle impact of cars: The case of CO2, Ind. and Env. 16(1) (1993) 42-45.
[18] H. Hondo, K. Nishimura, Y. Uchiyama, Energy Requirements and CO2 Emissions in Production of Goods and Services: Applications of the Input-Output Table to Life Cycle Analysis, Technical report for Central Research Institute of Electric Power Industry, Tokyo, Japan, 1996.
[19] S. Suh, G. Huppes, Techniques of life cycle inventory of a product, Ph.D. Thesis, University of Leiden, Netherlands, 2002.
[20] J.B. Guinee, M. Gorree, R. Heijungs, G. Huppes, R. Kleijn, L. Wegener Sleeswick, et al., Handbook on Life Cycle Assessment: Operational Guide to the ISO Standards, Kluwer Academic Publisher, Dorchester, Netherlands, 2002.
[21] S. Suh, Functions, commodities and environmental impact in an ecological-economic model, Ecol. Econ. 48(2004) 451-467.
[22] R. Heijungs, Reformulation of matrix-based LCI: From product balance to process balance, J. of Cleaner Prod. 23(1) (2006) 47-51.
[23] R.T. Hunt, L. Boguski, K. Weitz, A. Sharma, Case studies examining LCA streamlining techniques, International Journal of life cycle assessment 3 (1)(1998) 452-461.
[24] M. Lenzen, Errors in conventional and input-output-based life-cycle inventories, J. of Ind. Ecol. 4 (4) (2000) 127-148.
[25] G. Huppes, F. Schneider, Proceedings of the European Workshop on Allcation in LCA, Feb. 24-25, 1994, Leiden.
[26] R.H. Crawford, Greenhouse gas emissions embodied in reinforced concrete and timber railway sleepers, Environ. Sci. Technol. 43 (2009) 3885-3890.