Abstract
Purpose
The environmental impact of a product may change according to who adopts it, where it is adopted, and how it is used. Market forces are an inherent part of consequential LCA and the practice of coupling economic models with life cycle inventory data has increased in popularity. Nevertheless, the actual relationship between the price of a commodity and potential changes to its life cycle inventory has rarely been discussed explicitly. The adoption price effect refers to a change in a product’s environmental impact associated with a change in price, calculated on a functional unit basis. The price of a product influences the type and quantity of incumbent product(s) it displaces. This study provides insights on when the adoption price of a product is likely to influence its life cycle inventory and also identifies conditions where adoption price is expected to have negligible effects on inventory results.
Methods
A switchgrass bioenergy case is used to demonstrate the adoption price effect on life cycle inventory results when introducing a new product (i.e., switchgrass) into a system with multiple incumbents (i.e., crops, hay, pasture). This study estimates the adoption price effect on nutrient emissions by coupling biogeochemical models with a simplified economic breakeven model that estimates potential switchgrass adoption.
Results and discussion
In this case study, high switchgrass prices correspond to nitrate emission reductions that are three times greater than low switchgrass prices (0.67 kg N reduced/Mg switchgrass vs 0.21 kg N reduced/Mg switchgrass). The large adoption price effect found within the Southeastern USA is due to the highly heterogeneous landscape in the region. There is no single dominant land use, each incumbent product has a different environmental baseline, and each is displaced at a different switchgrass price range. Meanwhile, the adoption price effect is expected to be negligible in mostly homogenous landscapes, such as the more commonly studied Corn Belt, which has a single dominant incumbent in the form of corn-soy production. In addition to the specific case study, this analysis discusses general adoption conditions likely to lead to adoption price effects when conducting consequential LCA.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Anderson-Teixeira KJ, Davis SC, Masters MD, Delucia EH (2009) Changes in soil organic carbon under biofuel crops. GCB Bioenergy 1:75–96. https://doi.org/10.1111/j.1757-1707.2008.01001.x
Barford MM and C (2013) Farm-level feasibility of bioenergy depends on variations across multiple sectors. Environ Res Lett 8:15005
Bergerson JA, Brandt A, Cresko J, Carbajales-Dale M, MacLean HL, Matthews HS, McCoy S, McManus M, Miller SA, Morrow WR, Posen ID, Seager T, Skone T, Sleep S (2019) Life cycle assessment of emerging technologies: evaluation techniques at different stages of market and technical maturity. J Ind Ecol n/a: doi 24:11–25. https://doi.org/10.1111/jiec.12954
Brandt AR, Farrell AE (2007) Scraping the bottom of the barrel: greenhouse gas emission consequences of a transition to low-quality and synthetic petroleum resources. Clim Chang 84:241–263. https://doi.org/10.1007/s10584-007-9275-y
Chamberlain JF, Miller SA (2012) Policy incentives for switchgrass production using valuation of non-market ecosystem services. Energy Policy 48:526–536. https://doi.org/10.1016/j.enpol.2012.05.057
Chamberlain JF, Miller SA (2011) Using DAYCENT to quantify on-farm GHG emissions and N dynamics of land use conversion to N-managed switchgrass in the Southern U.S. Agric Ecosyst Environ 141:332–341
Clarens AF, Resurreccion EP, White MA, Colosi LM (2010) Environmental life cycle comparison of algae to other bioenergy feedstocks. Environ Sci Technol 44:1813–1819
Dale VH, Kline KL, Wright LL, Perlack RD, Downing M, Graham RL (2011) Interactions among bioenergy feedstock choices, landscape dynamics, and land use. Ecol Appl 21:1039–1054. https://doi.org/10.1890/09-0501.1
Del Grosso SJ, Mosier AR, Parton WJ, Ojima DS (2005) DAYCENT model analysis of past and contemporary soil N2O and net greenhouse gas flux for major crops in the USA. Soil Tillage Res 83:9–24. https://doi.org/10.1016/j.still.2005.02.007
Deng L, Williams ED (2011) Functionality versus “typical product” measures of technological progress. J Ind Ecol 15:108–121
Dunn JB, Mueller S, Kwon H, Wang MQ (2013) Land-use change and greenhouse gas emissions from corn and cellulosic ethanol. Biotechnol Biofuels 6:1–13. https://doi.org/10.1186/1754-6834-6-51
Earles JM, Halog A (2011) Consequential life cycle assessment: a review. Int J Life Cycle Assess 16:445–453. https://doi.org/10.1007/s11367-011-0275-9
Egbendewe-Mondzozo A, Swinton SM, Izaurralde CR, Manowitz DH, Zhang X (2011) Biomass supply from alternative cellulosic crops and crop residues: a spatially explicit bioeconomic modeling approach. Biomass Bioenergy 35:4636–4647. https://doi.org/10.1016/J.BIOMBIOE.2011.09.010
Ekvall T (2000) A market-based approach to allocation at open-loop recycling. Resour Conserv Recycl 29:91–109. https://doi.org/10.1016/S0921-3449(99)00057-9
Fargione JE, Plevin RJ, Hill JD (2010) The ecological impact of biofuels. Annu Rev Ecol Evol Syst 41:351–377. https://doi.org/10.1146/annurev-ecolsys-102209-144720
Fazio S, Monti A (2011) Life cycle assessment of different bioenergy production systems including perennial and annual crops. Biomass and Bioenergy 35:4868–4878. https://doi.org/10.1016/j.biombioe.2011.10.014
Fisher B, Turner K, Zylstra M, Brouwer R, Groot R, Farber S, Ferraro P, Green R, Hadley D, Harlow J, Jefferiss P, Kirkby C, Morling P, Mowatt S, Naidoo R, Paavola J, Strassburg B, Yu D, Balmford A (2008) Ecosystem services and economic theory: integration for policy-relevant research. Ecol Appl 18:2050–2067. doi: https://doi.org/10.1890/07-1537.1
Font Vivanco D, Voet E (2014) The rebound effect through industrial ecology’s eyes: a review of LCA-based studies
Frijia S, Guhathakurta S, Williams E (2012) Functional unit, technological dynamics, and scaling properties for the life cycle energy of residences. Environ Sci Technol 46:1782–1788. https://doi.org/10.1021/es202202q
Gelfand I, Zenone T, Jasrotia P, Chen J, Hamilton SK, Robertson GP (2011) Carbon debt of conservation reserve program (CRP) grasslands converted to bioenergy production. PNAS 108:13864–13869
Gopalakrishnan G, Cristina Negri M, Salas W (2012) Modeling biogeochemical impacts of bioenergy buffers with perennial grasses for a row-crop field in Illinois. GCB Bioenergy 4:739–750. https://doi.org/10.1111/j.1757-1707.2011.01145.x
Hertwich EG (2008) Consumption and the rebound effect: an industrial ecology perspective. J Ind Ecol 9:85–98. https://doi.org/10.1162/1088198054084635
Jain AK, Khanna M, Erickson M, Huang H (2010) An integrated biogeochemical and economic analysis of bioenergy crops in the Midwestern United States. GCB Bioenergy 2:217–234. https://doi.org/10.1111/j.1757-1707.2010.01041.x
Jansson J (2011) Consumer eco-innovation adoption: assessing attitudinal factors and perceived product characteristics. Bus Strateg Environ 20:192–210. https://doi.org/10.1002/bse.690
Jensen K, Clark CD, Ellis P et al (2007) Farmer willingness to grow switchgrass for energy production. Biomass Bioenergy 31:773–781. https://doi.org/10.1016/j.biombioe.2007.04.002
Kainuma M, Matsuoka Y, Morita T (2000) Estimation of embodied CO2 emissions by general equilibrium model. Eur J Oper Res 122:392–404
Kätelhön A, Bardow A, Suh S (2016) Stochastic technology choice model for consequential life cycle assessment. Environ Sci Technol 50:12575–12583. https://doi.org/10.1021/acs.est.6b04270
Kätelhön A, von der Assen N, Suh S, Jung J, Bardow A (2015) Industry-cost-curve approach for modeling the environmental impact of introducing new technologies in life cycle assessment. Environ Sci Technol 49:7543–7551. https://doi.org/10.1021/es5056512
Khanna M, Crago CL (2012) Measuring indirect land use change with biofuels: implications for policy. Annu Rev Resour Econ 4:161–184. https://doi.org/10.1146/annurev-resource-110811-114523
Kim S, Dale BE (2005) Environmental aspects of ethanol derived from no-tilled corn grain: nonrenewable energy consumption and greenhouse gas emissions. Biomass Bioenergy 28:475–489
Marvuglia A, Benetto E, Rege S, Jury C (2013) Modelling approaches for consequential life-cycle assessment (C-LCA) of bioenergy: critical review and proposed framework for biogas production. Renew Sustain Energy Rev 25:768–781. https://doi.org/10.1016/j.rser.2013.04.031
Matthews JA (2009) Biofuels and indirect land use change effects: the debate continues. Biofuels Bioprod Biorefin 3:305–317
McLaughlin SB, Adams Kszos L (2005) Development of switchgrass (Panicum virgatum) as a bioenergy feedstock in the United States. Biomass and Bioenergy 28:515–535. https://doi.org/10.1016/j.biombioe.2004.05.006
Miller SA, Keoleian GA (2015) Framework for analyzing transformative technologies in life cycle assessment. Environ Sci Technol 49:3067–3075. https://doi.org/10.1021/es505217a
Moni SM, Mahmud R, High K, Carbajales-Dale M (2019) Life cycle assessment of emerging technologies: a review. J Ind Ecol 24:52–63. https://doi.org/10.1111/jiec.12965
Mooney DF, Roberts RK, English BC, Tyler DD, Larson JA (2009) Yield and breakeven price of “Alamo” switchgrass for biofuels in Tennessee. Agron J 101:1234–1242. https://doi.org/10.2134/agronj2009.0090
Olson EL (2013) Perspective: the green innovation value chain: a tool for evaluating the diffusion prospects of green products. J Prod Innov Manag 30:782–793. https://doi.org/10.1111/jpim.12022
Pehnt M (2006) Dynamic life cycle assessment (LCA) of renewable energy technologies. Renew Energy 31:55–71. https://doi.org/10.1016/j.renene.2005.03.002
Pesonen T, Fleischer G, H. E, Huppes G, Jahn C et al (2000) Framework for scenario development in LCA. Int J Life Cycle Assess 5:21–30
Qualls DJ, Jensen KL, Clark CD, English BC, Larson JA, Yen ST (2012) Analysis of factors affecting willingness to produce switchgrass in the southeastern United States. Biomass Bioenergy 39:159–167. https://doi.org/10.1016/j.biombioe.2012.01.002
Sarkar S, Miller SA (2014) Water quality impacts of converting intensively-managed agricultural lands to switchgrass. Biomass and Bioenergy 68:32–43. https://doi.org/10.1016/j.biombioe.2014.05.026
Sarkar S, Miller SA, Frederick JR (2011) Modeling nitrogen loss from switchgrass agricultural systems. Biomass Bioenergy 35:4381–4389
Sharp BE, Miller SA (2014) Estimating maximum land use change potential from a regional biofuel industry. Energy Policy 65:261–269. https://doi.org/10.1016/j.enpol.2013.10.062
Sharp BE, Miller SA (2016) Potential for integrating diffusion of innovation principles into life cycle assessment of emerging technologies. Environ Sci Technol 50:2771–2781. https://doi.org/10.1021/acs.est.5b03239
Soimakallio S, Kiviluoma J, Saikku L (2011) The complexity and challenges of determining GHG (greenhouse gas) emissions from grid electricity consumption and conservation in LCA (life cycle assessment) – a methodological review. Energy 36:6705–6713. https://doi.org/10.1016/j.energy.2011.10.028
Somerville C, Youngs H, Taylor C et al (2010) Feedstocks for lignocellulosic biofuels. Science 329(80):790 LP–790792
Thiesen J, Christensen TS, Kristensen TG, Andersen RD, Brunoe B, Gregersen TK, Thrane M, Weidema BP (2006) Rebound effects of price differences. Int J Life Cycle Assess 13:104–114. https://doi.org/10.1065/lca2006.12.297
Tilman D, Hill J, Lehman C (2006) Carbon-negative biofuels from low-input high-diversity grassland biomass. Science 314(80):1598–1600
U.S Department of Energy (2016) 2016 billion-ton report: advancing domestic resources for a thriving bioeconomy, volume 1: economic availability of Feedstocks. Oak Ridge, Tennessee
USDA (2013) National Agricultural Statistics Service quick stats 2.0 database
Venkatesh A, Jaramillo P, Griffin WM, Matthews HS (2012) Implications of changing natural gas prices in the United States electricity sector for SO2, NOx and life cycle GHG emissions. Environ res Lett 7:
Wang M, Lee H, Molburg J (2004) Allocation of energy use in petroleum refineries to petroleum products. Int J Life Cycle Assess 9:34–44. https://doi.org/10.1007/BF02978534
Weidema BP, Thrane M (2007) Comments on the development of harmonized method for sustainability assessment of technologies (SAT). In: Sustainability assessment of technologies. Brussels, Belgium, pp 1–9
Wender B, Foley R, Hottle T et al (2014) Anticipatory life-cycle assessment for responsible research and innovation. J Responsible Innov 1:200–207
Xing H, Cheng H, Zhang L (2015) Demand response based and wind farm integrated economic dispatch. CSEE J power energy Syst 1:37–41. Doi: https://doi.org/10.17775/CSEEJPES.2015.00047
Yadav V, Malanson GP, Bekele E, Lant C (2009) Modeling watershed-scale sequestration of soil organic carbon for carbon credit programs. Appl Geogr 29:488–500. doi: https://doi.org/10.1016/j.apgeog.2009.04.001
Yang Y, Bae J, Kim J, Suh S (2012) Replacing gasoline with corn ethanol results in significant environmental problem-shifting. Env Sci Technol 46:. doi: https://doi.org/10.1021/es203641p, 3671, 3678
Zamagni A, Guinée J, Heijungs R, Masoni P, Raggi A (2012) Lights and shadows in consequential LCA. Int J Life Cycle Assess 17:904–918. https://doi.org/10.1007/s11367-012-0423-x
Funding
This material is based in part upon work supported by the National Science Foundation under Grant Number CBET 1127584 and by the U.S. Environmental Protection Agency STAR Fellowship Assistance Agreement no. FP917172.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Disclaimer
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or Environmental Protection Agency.
Additional information
Responsible Editor: Andrew Henderson
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 46 kb)
Rights and permissions
About this article
Cite this article
Miller, S.A., Sharp, B.E., Chamberlain, J.F. et al. Exploring adoption price effects on life cycle inventory results. Int J Life Cycle Assess 25, 1078–1087 (2020). https://doi.org/10.1007/s11367-020-01760-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11367-020-01760-6