The International Journal of Life Cycle Assessment Impact Factor & Information

Publisher: Springer Verlag

Journal description

The International Journal of Life Cycle Assessment (Int J LCA) is the first journal devoted entirely to LCA. LCA has become a recognized instrument to assess the ecological burdens and impacts connected with products and systems, or, more generally, with human activities. The LCA-Journal - which has been expanded by a section on Life Cycle Management (LCM) - is a forum for: Scientists developing LCA and LCM; LCA and LCM practitioners; Managers concerned with environmental aspects of products; Governmental environmental agencies responsible for product quality; Scientific and industrial societies involved in LCA development; Ecological institutions and bodies.

Current impact factor: 3.99

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 3.988
2013 Impact Factor 3.089
2012 Impact Factor 2.773
2011 Impact Factor 2.362
2010 Impact Factor 3.148
2009 Impact Factor 2.636
2008 Impact Factor 1.828
2007 Impact Factor 1.607
2006 Impact Factor 1.42
2005 Impact Factor 1.483
2004 Impact Factor 1.068
2003 Impact Factor 1.035

Impact factor over time

Impact factor

Additional details

5-year impact 4.38
Cited half-life 5.80
Immediacy index 0.58
Eigenfactor 0.01
Article influence 1.12
Website International Journal of Life Cycle Assessment website
Other titles International journal of life cycle assessment (Online)
ISSN 0948-3349
OCLC 60628611
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Springer Verlag

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on pre-print servers such as
    • Author's post-print on author's personal website immediately
    • Author's post-print on any open access repository after 12 months after publication
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany link to published version (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification
    ​ green

Publications in this journal

  • The International Journal of Life Cycle Assessment 12/2015;
  • The International Journal of Life Cycle Assessment 10/2015; 20(10). DOI:10.1007/s11367-015-0941-4
  • The International Journal of Life Cycle Assessment 10/2015; 20(10). DOI:10.1007/s11367-015-0946-z
  • The International Journal of Life Cycle Assessment 10/2015; 20(10). DOI:10.1007/s11367-015-0953-0
  • The International Journal of Life Cycle Assessment 09/2015; DOI:10.1007/s11367-015-0938-z
  • The International Journal of Life Cycle Assessment 09/2015; DOI:10.1007/s11367-015-0966-8
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    ABSTRACT: Purpose Consumption of high quantities of pesticides in viticulture emphasizes the importance of including pesticide emissions and impacts hereof in viticulture LCAs. This paper addresses the lack of inventory models and characterization factors suited for the quantification of emissions and ecotoxicological impacts of pesticides applied to viticulture. The paper presents (i) a tailored version of PestLCI 2.0, (ii) corresponding characterization factors for freshwater ecotoxicity characterization and (iii) result comparison with other inventory approaches. The purpose of this paper is hence to present a viticulture customized version of PestLCI 2.0 and illustrate the application of this customized version on a viticulture case study. Methods The customization of the PestLCI 2.0 model for viticulture includes (i) addition of 29 pesticide active ingredients commonly used in vineyards, (ii) addition of 9 viticulture type specific spraying equipment and accounting the number of rows treated in one pass, and (iii) accounting for mixed canopy (vine/cover crop) pesticide interception. Applying USEtox™, the PestLCI 2.0 customization is further supported by the calculation of freshwater ecotoxicity characterization factors for active ingredients relevant for viticulture. Case studies on three different vineyard technical management routes illustrate the application of the inventory model. The inventory and freshwater ecotoxicity results are compared to two existing simplified emission modelling approaches. Results and discussion The assessment results show considerably different emission fractions, quantities emitted and freshwater ecotoxicity impacts between the different active ingredient applications. Three out of 21 active ingredients dominate the overall freshwater ecotoxicity: Aclonifen, Fluopicolide and Cymoxanil. The comparison with two simplified emission modelling approaches, considering field soil and air as part of the ecosphere, shows that PestLCI 2.0 yields considerable lower emissions and, consequently, lower freshwater ecotoxicity. The sensitivity analyses reveal the importance of soil and climate characteristics, canopies (vine and cover crop) development and sprayer type on the emission results. These parameters should therefore be obtained with site-specific data, while literature or generic data that are acceptable inputs for parameters whose uncertainties have less influence on the result. Conclusions Important specificities of viticulture have been added to the state-of-the-art inventory model PestLCI 2.0. They cover vertically trained vineyards, the most common vineyard training form; they are relevant for other perennial or bush crops provided equipment, shape of the canopy and pesticide active ingredients stay in the range of available options. A similar and compatible model is needed for inorganic pesticide active ingredients emission quantification, especially for organic viticulture impacts accounting.
    The International Journal of Life Cycle Assessment 09/2015; DOI:10.1007/s11367-015-0949-9
  • The International Journal of Life Cycle Assessment 09/2015; DOI:10.1007/s11367-015-0960-1
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    ABSTRACT: Purpose: Integrated agriculture and aquaculture (IAA), as typified by the mulberry dike-pond system (DPS) of the Pearl River delta of southern China, is often cited as an example of sustainable intensified production due to its characteristic closed loop recycling of nutrients. In this study we tackle two issues that have been hardly addressed in previous analyses of aquaculture production; greenhouse gas emissions (GHGe) from the pond and the role of labour. Methods: Previous assessments led us to revisit the sustainability of the DPS system as a model for a well-studied IAA system using a life cycle assessment (LCA) methodology. Our study quantifies on-farm CH4 and N2O emissions and indirect emissions embedded in inputs, using the global warming potential (GWP) metric. To model the indirect impact of the high labour requirements of the system, a simple methodology based on metabolizable energy requirements is proposed. Results and discussion: Our GHGe assessment suggests that using fish ponds to treat organic waste results in higher net emissions than alternative waste processing options (e.g. composting), even when the co-production of fish is accounted for. The majority of total system GWP100 (97%) can be attributed to methane from the fertilised ponds. Food required to meet labour requirements plays an important role, from 11% to 22% of total environmental impact. Conclusions: Methane from semi-intensive ponds fertilised with organic waste appears to be a significant source of GWP, calling into question the environmental sustainability of IAA systems such as the mulberry DPS. Improving sustainability in such systems will require better understanding of GHGe from waste-fed aquaculture ponds, notably with respect to on-farm N2O and CH4.
    The International Journal of Life Cycle Assessment 09/2015; 20(10). DOI:10.1007/s11367-015-0950-3
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    ABSTRACT: Purpose There is an apparent convention within both consequential and attributional life cycle assessment (LCA) to assume a 1:1 substitution ratio between functionally equivalent product systems. However, this convention may not be compatible with the purpose of consequential LCA, which is to model the actual consequences of the decision at hand. This paper explores the implications of the convention using the illustrative example of a 1 % tax on whole milk. Methods A consequential LCA which assumes a 1:1 substitution ratio between two functionally equivalent product systems is compared with the results of an analysis that estimates the actual substitution ratio based on empirical data. Cross-price elasticities of demand for possible competitor products are modelled using a linear approximated almost ideal demand system (LA-AIDS). Results and discussion The results show a 1:0.52 substitution ratio between whole and low fat milk, rather than a 1:1 substitution ratio. Depending on the consequential LCA values for whole and low fat milk, the 1:1 convention could underestimate the greenhouse gas emission reductions from the tax by over 400 %. Conclusions The results suggest that it is highly important to model actual substitution ratios between competing product systems in order to capture the consequences of the decision at hand. As a subsidiary contribution, the paper also shows the importance of modelling the displacement effects of milk fat co-products, which are generally not considered in the existing LCA literature on milk.
    The International Journal of Life Cycle Assessment 09/2015; 20(9). DOI:10.1007/s11367-015-0939-y
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    ABSTRACT: Purpose The social life cycle impact assessment (SLCIA) incorporates either a type I or type II characterization model. We improved both models by introducing explicit causality by using statistic modeling through development of (1) a quantitative approach to simultaneously identify impact pathways of type II models with multiple impact categories, targeting SLCIA method developers and (2) a new hybrid model to establish causality between inventory indicators and subcategories, targeting social life cycle assessment practitioners. Methods Causality establishments for type II impact pathways and the new hybrid model are the core requirements for this study. We used structural equation modeling (SEM) to identify the impact pathways for type II characterization models, therefore resolving the issues of unobservability and unvalidatibility in type II models. Using country-level data from the World Bank, the method was applied to an example impact pathway at macro-scale. We applied Bayesian networks in our hybrid model to address the issues of relevance and representativeness in type I models, assuming the unobservable social performances of an organization are the causes for observable inventory indicators. The method was applied to a hypothetical example for the stakeholder of the worker at company scale. Temporal precedence (i.e., lag effects) was incorporated into both models. Results and discussion The results from the confirmatory SEM supported our hypotheses that comprised the impact pathway from economic development to health outcomes, which were fully mediated by health expenditures and health access. A 1-year lag between each impact category resulted in the best model fit. Limitations on the data as well as subjective choice of indicators to represent impact categories are subject to criticism. The results from the hybrid model showed that, depending on the likelihood of the inventory indicators, the posterior probability of subcategories either deviated from their prior probability or behaved similarly. The construction of proper conditional probability tables and the choice of probability distribution for the likelihood are major challenges for the hybrid model. Conclusions This study was the first attempt in using statistic causal models to quantitatively identify unobservable impact pathways of the type II model and to develop a hybrid model for SLCIA. A SEM that incorporates temporal precedence enables identification of impact pathways with multiple unobservable impact categories. The hybrid model using Bayesian networks represents the subcategories in posterior probabilities instead of absolute scores, helping companies to better develop instructions for future management practices.
    The International Journal of Life Cycle Assessment 09/2015; 20(9). DOI:10.1007/s11367-015-0915-6
  • The International Journal of Life Cycle Assessment 08/2015; DOI:10.1007/s11367-015-0956-x
  • The International Journal of Life Cycle Assessment 08/2015; DOI:10.1007/s11367-015-0944-1
  • The International Journal of Life Cycle Assessment 08/2015; 20(10). DOI:10.1007/s11367-015-0928-1