Total lipids (TL, phospholipids (PL) and fatty acid composition of TL and PL (the latter in blood and eggs only) were estimated in Candida lipolytica cultivated on n-alkanes by industrial method ("Toprina") in 0%, 10% and 15% "Toprina" diets and in eggs, blood and faeces of laying hens fed these diets. With increasing concentrations of dietary "Toprina" 15:0 and 17:0 fatty acids increased, 17:1 and 17:2, typical of the product, appeared and increased in diets, eggs, blood and faeces. Other fatty acid values were not affected by dietary yeast. 相似文献
A review of LCA process datasets is an important element of quality assurance for databases and for other systems to provide LCA datasets. Somewhat surprisingly, a broadly accepted and applicable set of criteria for a review of LCA process datasets was lacking so far. Different LCA databases and frameworks are proposing and using different criteria for reviewing datasets. To close this gap, a set of criteria for reviewing LCA dataset has been developed within the Life Cycle Initiative.
Methods
Previous contributions to LCA dataset review have been analysed for a start, from ISO and various LCA databases. To avoid somewhat arbitrary review criteria, four basic rules are proposed which are to be fulfilled by any dataset. Further, concepts for assessing representativeness and relevance are introduced into the criteria set from established practices in statistics and materiality. To better structure the criteria and to ease their application, they are grouped into clusters. A first version of the developed review criteria was presented in two workshops with database providers and users on different levels of experience, and draft versions of the criteria were shared within the initiative. The current version of the criteria reflects feedback received from various stakeholders and has been applied and tested in a review for newly developed datasets in Brazil, Malaysia and Thailand.
Results and discussion
Overall, 14 criteria are proposed, which are organised in clusters. The clusters are goal, model, value, relevance and procedure. For several criteria, a more science-based definition and evaluation is proposed in comparison to ‘traditional’ LCA. While most of the criteria depend on the goal and scope of dataset development, a core set of criteria are seen as essential and independent from specific LCA modelling. For all the criteria, value scales are developed, typically using an ordinal scale, following the pedigree approach.
Conclusions
Review criteria for LCI datasets are now defined based on a stringent approach. They aim to be globally acceptable, considering also database interoperability and database management aspects, as well as feedback received from various stakeholders, and thus close an important gap in LCA dataset quality assurance. The criteria take many elements of already existing criteria but are the first to fully reflect the implications of the ISO data quality definition, and add new concepts for representativeness and relevance with the idea to better reflect scientific practice outside of the LCA domain. A first application in a review showed to be feasible, with a level of effort similar to applying other review criteria. Aspects not addressed yet are the review procedure and the mutual recognition of dataset reviews, and their application for a very high number of datasets.
Consequential LCA (CLCA) is becoming widely used in the scientific community as a modelling technique which describes the consequences of a decision. However, despite the increasing number of case studies published, a proper systematization of the approach has not yet been achieved. This paper investigates the methodological implications of CLCA and the extent to which the applications are in line with the theoretical dictates. Moreover, the predictive and explorative nature of CLCA is discussed, highlighting the role of scenario modelling in further structuring the methodology.
Methods
An extensive literature review was performed, involving around 60 articles published over a period of approximately 18?years, and addressing both methodological issues and applications. The information was elaborated according to two main aspects: what for (questions and modes of LCA) and what (methodological implications of CLCA), with focus on the nature of modelling and on the identification of the affected processes.
Results and discussion
The analysis points out that since the modelling principles of attributional LCA (ALCA) and CLCA are the same, what distinguishes the two modes of LCA is the choice of the processes to be included in the system (i.e. in CLCA, those that are affected by the market dynamics). However, the identification of those processes is often done inconsistently, using different arguments, which leads to different results. We suggest the use of scenario modelling as a way to support CLCA in providing a scientifically sound basis to model specific product-related futures with respect to technology development, market shift, and other variables.
Conclusions
The CLCA is a sophisticated modelling technique that provides a way to assess the environmental consequences of an action/decision by including market mechanisms into the analysis. There is still room for improvements of the method and for further research, especially in relation to the following aspects: clarifying when and which market information is important and necessary; understanding the role of scenario modelling within CLCA; and developing a procedure to support the framing of questions to better link questions to models. Moreover, we suggest that the logic of mechanisms could be the reading guide for overcoming the dispute between ALCA and CLCA. Going further, this logic could also be extended, considering CLCA as an approach??rather than as a modelling principle with defined rules??to deepen LCA, providing the conceptual basis for including more mechanisms than just the market ones. 相似文献
A paleoecological and sedimentological study was carried out on shallow-water carbonates of the Kras Plateau (SW Slovenia)
with the goal of reconstructing paleoenvironmental conditions and evolution of foraminiferal communities on the northwestern
Adriatic Carbonate Platform (AdCP) during the Late Paleocene–earliest Eocene. Three facies have been recognized and summarized
in a carbonate ramp model. Within these facies, six foraminiferal assemblages, representing different ramp sub-environments,
have been defined: during the Late Paleocene sedimentation took place in a protected innermost ramp with (1) smaller miliolids-
and (2) small benthic foraminifera-dominated assemblages thriving on partly vegetated, soft substrates. In the Uppermost Paleocene,
sedimentation primarily occurred along a mid ramp. The upper mid-ramp was sporadically influenced by storms/currents and occupied
by (3) Assilina-dominated assemblage occurring on a soft sandy substrate. The deeper mid-ramp was characterized by (4) ‘bioconstructors’-
and (5) orthophragminids-dominated assemblages, colonizing biotopes with substrates of different nature. During the earliest
Eocene, deposition occurred in an inner-ramp setting with (6) alveolinids-nummulitids assemblage thriving on muddy and sandy
substrate, partly covered or close to seagrass beds. The Late Paleocene–earliest Eocene environmental conditions, coupled
with the long-term evolution of larger benthic foraminifera (LBF), seem to have favored this low-light dependent group as
common sediment contributors. By comparing the evolution of the shallow-water biota from the Adriatic area with data from
the Pyrenees and Egypt, a general latitudinal trend can be recognized. However, on a smaller geographical scale, local conditions
are likely to have played a pivotal role in promoting the evolution of biota characterized by suites of unique features. 相似文献
The purpose of this study was to test the chain-organization environmental footprint (chain-OEF) approach by applying it to part of a pork production chain in Belgium. The approach is supposed to provide insight into the environmental impact of a specific production chain in an efficient manner by applying pragmatic data collection throughout the chain. This is achieved by allocating the environmental impact of each of the production sites to the product of interest using straightforward allocation rules.
Methods
The cradle-to-gate (up to retail) environmental impact of pork was determined by life cycle assessment (LCA), in line with the product and organisation environmental footprint guidelines (PEF and OEF; European Commission 2013b). Foreground data was gathered at a feed production site, two farmers, a slaughterhouse and a meat processing site. All foreground operations are part of the same pork production chain in Belgium. The chain was completed using background data from Ecoinvent v3.01 (Wernet et al. 2016), Agri-Footprint v1.0 (Blonk 2014), European Life Cycle Database v3.0, LCA Food Database (Nielsen et al. 2003) and OEF Sector Rules Retail (Humbert et al. 2015b). The impact was quantified using the international reference life cycle data system (ILCD) midpoint method for 14 impact categories, but focussing on climate change.
Results and discussion
The total carbon footprint of the cradle-to-gate pork production system equals 0.46 kg CO2-eq. (100 g pork)?1. This result is quite similar to that of earlier studies analysing the pork production chain: 0.58 and 0.57 kg CO2-eq. (100 g pork)?1 (Bracquené et al. 2011, Agri-Footprint 2014). Most of the carbon footprint was caused by feed production and more specifically, by the feed ingredients and their transport. Grains, soy and palm oil have the largest impact contributions. The farms are responsible for most of the remaining impact. N2O and CH4 emissions are the largest cause of greenhouse gas emissions at the farms. Also, in the other 13 considered impact categories, feed production and farming are responsible for more than half of the total impact, mostly followed by meat processing.
Conclusions
Applying the chain-OEF approach in this study has shown that a chain LCA can be performed successfully and pragmatic data collection allows obtaining LCA results relatively fast, especially for small or medium-sized enterprises (SMEs). Whereas data availability was not such an issue, the main bottlenecks identified are data management and the link of LCA to other disciplines such as engineering, policy, etc. which could increase the added value of LCA studies.
