Questions for Life Cycle Inventory (LCI)

In India, dairy sector has important impacts on the economy and ecosystem services and contributes to essential societal needs for food. Economic survey (2015–16) noted that India ranks first in milk production with an annual output of 146.3 million tonnes with a growth of 6.26% during 2014–15 accounting for 18.5% of world milk production. Whereas, FAO (2014) reported a 3.1% increase in world milk production from 765 million tonnes in the year 2013 to 789 million tonnes in the year 2014. The per capita availability of milk in India has increased from 176 g/d in the year 1990–91 to 322 g/d by 2014–15 which was more than the world average of 294 g/d during the year 2013. This represents a sustained growth in availability of milk and milk products for the growing population. As the public concern about climate change and environmental sustainability continues to grow and societal pressures on the dairy industry to reduce its environmental impact are rising, therefore, the concept of life cycle assessment (LCA) of GHG emissions for milk production helps in quantifying the environmental impact of dairy sector and furnishing a method of identifying mitigation options suited to reduce those environmental burdens. The process of LCA is generally composed of 4 components including goal and scope, life cycle inventory (LCI) analysis, life cycle impact assessment and interpretation. Creating an LCI of emissions to the environment (e.g. GHG emissions) for an animal agricultural system such as dairy sector, is challenging. The diversity of management systems across operations and segments of the dairy sector contribute to the challenges of creating LCI analyses. The purpose of this article was to assess the current LCA methodologies being used in analysis of the dairy sector and to compare the complexity and variations among LCA studies. It is also emphasised that more of such studies are required under different livestock rearing systems for different species under different agro-climatic zones of India.

Life cycle assessment of three Peruvian fishmeal plants: Toward a cleaner production

According to some recent studies, noise from road transport is estimated to cause human health effects of the same order of magnitude as the sum of all other emissions from the transport life cycle. Thus, ISO 14′040 implies that traffic noise effects should be considered in life cycle assessment (LCA) studies where transports might play an important role. So far, five methods for the inclusion of noise in LCA have been proposed. However, at present, none of them is implemented in any of the major life cycle inventory (LCI) databases and commonly used in LCA studies. The goal of the present paper is to define a requirement profile for a method to include traffic noise in LCA and to assess the compliance of the five existing methods with this profile. It concludes by identifying necessary cornerstones for a model for noise effects of generic road transports that meets all requirements. Requirements for a methodological framework for inclusion of traffic noise effects in LCA are derived from an analysis of how transports are included in 66 case studies published in International Journal of Life Cycle Assessment in 2006 and 2007, in the sustainability reports of ten Swiss companies, as well as on the basis of theoretical considerations. Then, the general compliance of the five existing methods for inclusion of noise in LCA with the postulated requirement profile is assessed. Six general requirements for a methodological framework for inclusion of traffic noise effects in LCA were identified. A method needs to be applicable for (1) both generic and specific transports, (2) different modes of transport, (3) different vehicles within one mode of transport, (4) transports in different geographic contexts, (5) different temporal contexts, and (6) last but not least, the method needs to be compatible with the ISO standards on LCA. One of the reviewed methods is not specific for transports at all and two are only applicable for specific transports. The other two allow generic and specific road transports to be assessed. The methods either deal with road traffic noise only or they compare noise from different sources, ignoring the fact that not only physical sound levels but also the source of sound determines the effect. Three methods only differentiate between vehicle classes (lorries and passenger cars) while one method differentiates between specific vehicles of the same class. Four of the methods consider the geographic context and three of them differentiate between day- and nighttime traffic. None of the existing methods for traffic noise integration in LCA complies with the proposed requirement profile. They either lack the genericness for a wide application or they lack the specificity needed for differentiations in LCA studies. There is no method available that allows for appropriate inter- or intramodal comparison of traffic noise effects. Thus, the benefit of the existing methods is limited. They can, in the better cases, only demonstrate the relative importance of road or rail traffic noise effects compared to the nonnoise-related effects of transportation. Currently, none of the major LCI databases includes traffic noise indicators. Thus, noise effects are usually not considered in LCA studies. We introduce a requirement profile for methods that allow the inclusion of noise in LCI. Due to the estimated significance of noise in transport LCA, this inclusion will change the overall results of many LCA studies. None of the existing methods fully complies with the requirement profile. Two of the methods can be modified and extended for inclusion in generic LCI databases. A third model allows for intermodal comparison. From an LCA perspective, all methods include weaknesses and need to be amended in order to make them widely usable. In part 2 of this paper, an in-depth analysis of the promising methods is provided, improvement potential is evaluated, and a new context-sensitive framework for the consistent LCI modeling of noise emissions from road transportation is presented. Appropriate methods for modeling rail and air traffic noise will have to be developed in the future in order to arrive at a methodological framework fully compliant with the requirement profile. Furthermore, future research is needed to identify appropriate methods for impact assessment.

Life Cycle Assessment (LCA) has been introduced to Thai industries in 1997 as one of the ISO 14000 series. The concept of LCA is being gradually accepted. However, there are few formal LCA studies in Thailand so far due to a limited number of LCA experts and a lack of sufficient databases relevant to domestic conditions. The LCA activities in Thailand can be divided into 3 areas, which are (1) Workshops and seminars (2) Use of LCA studies in Ecolabelling and (3) Life Cycle Inventory (LCI) and LCA studies. The first LCI study was to develop LCI data for Thailand Electricity Grid Mixes. There are a few LCA thesis studies in some universities, but these studies used databases from commercial software programs. The study and use of LCA may increase in the future only if domestic background database will be provided by research institutes and the government, and if industry understands LCA methodology through periodical workshops and seminars. INTRODUCTION Life Cycle Assessment has been introduced to Thai industries in 1997 as one of the ISO 14000 series. The concept of LCA is being gradually accepted. However, there are few formal LCA studies in Thailand so far due to a limited number of LCA experts and a lack of sufficient databases relevant to domestic conditions. ACTIVITIES The LCA activities in Thailand can be divided into 3 areas including (1) Workshops and seminars (2) Use of LCA studies in Ecolabelling and (3) Life Cycle Inventory (LCI) and LCA studies. 1. Workshop and Seminar To introduce the LCA concept to Thai Industries, the Thailand Environment Institute (TEI), in cooperation with many organizations, organized LCA seminars/workshops in Thailand annually between 1997-2002. All seminars successfully gained attention from Thai industry and educational institutes. The Thailand LCA Forum (http://doi.eng.cmu.ac.th/Thailca) has been launched by TEI in January of 2002. 2. Use of LCA studies in Ecolabelling The Green Label project was initiated in October 1993 by the Thailand Business Council for Sustainable Development (TBCSD) in association with the Ministry of Industry. This project is supported by the Secretariat, which is formed by a partnership between the Thai Industrial Standards Institute (TISI) and TEI. The objectives of the project are to establish the product criteria and award certification to specific products that are shown to have less impact on the environment, when compared with other products serving the same function (not including foods, drinks, and pharmaceuticals). The project came about from the idea that the green label can stimulate market choice thus encouraging producers to improve the environmental quality of their products and services in response to consumer demand. Award of the Thai Green label is based on the product criteria developed by a technical subcommittee. The subcommittee consists of representatives from the scientific, business and environmental groups and others if appropriate and available. A new subcommittee is established for each selected product category. At present, there are 29 product categories that are eligible for the Thai Green Label, and up to the end of November 2001, 227 individual products have received the Green Label award. Being aware of the high cost involved and time consumed in developing product criteria through format LCA, the Thai Green Label scheme has decided that a full quantitative LCA is not applicable for setting criteria for all products, especially in developing countries. The development of award criteria for the scheme has followed different methodologies. It will take into account not only significant environmental impact during the life cycle of the products (Life Cycle Consideration: LCC), but also capability to meet proposed criteria with reasonable process modification and/or improvement. The availability of testing institutes and the ability to perform tests are considered carefully, while setting the criteria. Results from existing LCA studies have been used as a scientific tool in the Thai Green Label Scheme for the development of environmental criteria for a few product categories. 3. Life Cycle Inventory (LCI) and LCA Studies

This chapter introduces the life cycle inventory (LCI) analysis – the topic of this volume. A brief history of the concept is provided, including its procedure according to different standards and guidance books. The LCI analysis phase of the life cycle assessment (LCA) framework has remained relatively constant over the years in terms of role and procedural steps. Currently, the LCI analysis is situated in between the goal and scope definition phase and the life cycle impact assessment phase in the LCA framework, although it is interconnected also with the interpretation phase. Central concepts in LCI analysis are defined, including product system, process, flow, functional unit, and system boundary. Four important steps of LCI analysis are outlined: constructing a flow chart, gathering data, conducting calculations, as well as interpreting results and drawing conclusions. The focus is on the process LCA approach, which is the most common in LCA practice. Environmentally-extended input-output analysis is also described briefly. Finally, an overview of the other chapters of this volume and their relevance to the topic of LCI analysis is provided.

The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One example of the latter approach was published in Science by Farrell and colleagues (2006) clarifying the net energy and greenhouse gas (GHG) emissions of ethanol, in which adjustments included the addition of coproduct credit, the addition and subtraction of processes within the system boundary, and a reconciliation of differences in the definition of net energy metrics. Such adjustments therefore provide an even playing field on which all studies can be considered and at the same time specify the conditions of the playing field itself. Understanding the conditions under which a meta-analysis was conducted is important for proper interpretation of both the magnitude and variability in results. This special supplemental issue of the Journal of Industrial Ecology includes 12 high-quality metaanalyses and critical reviews of LCAs that advance understanding of the life cycle environmental impacts of different technologies, processes, products, and materials. Also published are three contributions on methodology and related discussions of the role of meta-analysis in LCA. The goal of this special supplemental issue is to contribute to the state of the science in LCA beyond the core practice of producing independent studies on specific products or technologies by highlighting the ability of meta-analysis of LCAs to advance understanding in areas of extensive existing literature. The inspiration for the issue came from a series of meta-analyses of life cycle GHG emissions from electricity generation technologies based on research from the LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a laboratory of the U.S. Department of Energy, which also provided financial support for this special supplemental issue. (See the editorial from this special supplemental issue [Lifset 2012], which introduces this supplemental issue and discusses the origins, funding, peer review, and other aspects.) The first article on reporting considerations for meta-analyses/critical reviews for LCA is from Heath and Mann (2012), who describe the methods used and experience gained in NREL's LCA Harmonization Project, which produced six of the studies in this special supplemental issue. Their harmonization approach adapts key features of systematic review to identify and screen published LCAs followed by a meta-analytical procedure to adjust published estimates to ones based on a consistent set of methods and assumptions to allow interstudy comparisons and conclusions to be made. In a second study on methods, Zumsteg and colleagues (2012) propose a checklist for a standardized technique to assist in conducting and reporting systematic reviews of LCAs, including meta-analysis, that is based on a framework used in evidence-based medicine. Widespread use of such a checklist would facilitate planning successful reviews, improve the ability to identify systematic reviews in literature searches, ease the ability to update content in future reviews, and allow more transparency of methods to ease peer review and more appropriately generalize findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired by a meta-analysis, for categorizing main methodological topics, reconciling diverging methodological developments, and identifying future research directions in LCA. Their procedure involves the carrying out of a literature review on articles selected according to predefined criteria.« less

Life Cycle Assessment (LCA) has been applied in the Malaysian oil palm industry since 2010. It is important to ensure that this main industry is ready to meet the demands and expectations of European market on the environmental performance of the oil palm industry. In addition, oil palm biomass, especially oil palm trunk (OPT) are abundantly available after replanting every year. In order to maximize the usage of OPT as a green product, it can be converted to palm lumber as a value-added product. Palm lumber act as a basis product from OPT before it is converted to panel product such as plywood, sandwich board and so on. However, the LCA study on palm lumber production is still scarce in Malaysia. Hence, this paper aims to perform and collect the inventory data for palm lumber production, which is known as Life Cycle Inventory (LCI). A gate-to-gate system boundary and the functional unit of 1 m3 of palm lumber produced have been used in this study. This inventory data was collected from three batches of the production cycle. The inputs are mainly the raw materials which are the OPT and the energy from diesel and electricity from the grid. Generally, each consumption of input such as energy and fossil fuel were different at each stage of palm lumber production. Kiln-drying represents a prominent stage in terms of energy consumption, which electrical use in the dryer represents 94% of total electrical grid consumption as compared to another stage of palm lumber production. By adding the inventory information especially in the downstream sector of biomass industry, hopefully it can improve the sustainability of oil palm industry in Malaysia.Life Cycle Assessment (LCA) has been applied in the Malaysian oil palm industry since 2010. It is important to ensure that this main industry is ready to meet the demands and expectations of European market on the environmental performance of the oil palm industry. In addition, oil palm biomass, especially oil palm trunk (OPT) are abundantly available after replanting every year. In order to maximize the usage of OPT as a green product, it can be converted to palm lumber as a value-added product. Palm lumber act as a basis product from OPT before it is converted to panel product such as plywood, sandwich board and so on. However, the LCA study on palm lumber production is still scarce in Malaysia. Hence, this paper aims to perform and collect the inventory data for palm lumber production, which is known as Life Cycle Inventory (LCI). A gate-to-gate system boundary and the functional unit of 1 m3 of palm lumber produced have been used in this study. This inventory data was collected from three batches of t...

Background, aim, and scopeAn inclusion of traffic noise effects could change considerably the overall results of many life cycle assessment (LCA) studies. However, at present, noise effects are usually not considered in LCA studies, mainly because the existing methods for their inclusion do not fulfill the requirement profile. Two methods proposed so far seem suitable for inclusion in generic life cycle inventory (LCI) databases, and a third allows for inter-modal comparison. The aim of this investigation is an in-depth analysis of the existing methods and the proposition of a framework for modeling road transport noise emissions in LCI in accordance to the requirement profile postulated in part 1.Materials and methodsThis paper analyzes three methods for inclusion of traffic noise in LCA (Danish LCA guide method, Swiss EPA method, and Swiss FEDRO method) in detail. The additional basis for the analysis are the Swiss road traffic emission model “SonRoad,” traffic volume measurements at 444 sites in the Swiss road network, vehicle-type-specific noise measurements in free floating traffic situations in Germany, and noise emission measurements from different tires.ResultsThe Danish LCA guide method includes a major flaw that cannot be corrected within the methodological concept. It applies a dose-response function valid for average noise levels of a traffic situation to maximum noise levels of single vehicles. The Swiss FEDRO method is based on an inappropriate assumption since it bases distinctions of specific vehicles on data that do not allow for such a distinction. Noise emissions cannot be distinguished by the make and type of a vehicle since other factors, especially the tires, are dominant for noise emissions. Several problems are also identified in the Swiss EPA method, but they are not of a fundamental nature. Thus, we are able to base a new framework for vehicle and context-sensitive inclusion of road traffic noise emissions in LCI on the Swiss EPA method. We show how specific vehicle classes can be distinguished, how the influence of different tires can be dealt with, and what temporal and spatial aspects of traffic need to be distinguished.DiscussionWhile the Danish LCA guide method and the Swiss FEDRO method are not suitable for our purpose, the Swiss EPA method can be used as a basis to better meet the requirement profile identified in Part 1 of this paper. The proposed method for consistent, context-sensitive modeling of noise emissions from road transports in LCI meets all the requirements except that it is restricted to road transport.ConclusionsWe show limitations of the existing methods and approaches for improving them. Our proposed model allows for a more specific consideration of the various vehicles and contexts in terms of space and time and thus in terms of speed and traffic volume. This can be used on one hand for a consistent, context sensitive assessment of different vehicles in different traffic situations. On the other hand, it also allows for an inclusion of noise in LCA of transports on which only very little is known. This new LCI model meets five of the six requirements postulated in Part 1.Recommendations and perspectivesIn a next step, additional noise emissions due to additional traffic needs to be calculated based on the proposed framework and national or regional traffic models. Furthermore, the consideration of noise from different traffic modes should be addressed. The approach presented needs to be extended in order to make it also applicable for rail and air traffic noise, and the methods need to be implemented in LCI databases to make them easily available to practitioners. Furthermore, suitable impact assessment methods need to be identified or developed. They could base on the proposals made in the Swiss EPA and in the Swiss FEDRO methods.

Digitalising food manufacturing

Life cycle inventory (LCI) regionalization (i.e., the determination of input and output flows from production processes at a subcountry scale) is a priority in life cycle assessment (LCA) studies, particularly in the agri-food sector. Many regionalized LCAs fail to ensure that microlevel inventories are consistent with country-level aggregated data-or "scale consistent." They also fail to construct LCIs using international reference guidelines and trustworthy standardized data sources. This failure generates inaccuracies and biases in inventories and can compromise comparability among international LCA studies. Our study introduces scale consistency as a principle for regionalized agri-food LCIs. We present a generic procedure that defines how scale-dependent LCI flows should be regionalized, depending on data availability. We then present a list of inventory flows that require regionalization and their suggested calculation procedures (methods and models) from 2 methodological guides developed by projects Agribalyse and World Food LCA Database. As proof of concept, we apply the procedure to Portugal and assess whether the methods and models proposed for each type of inventory flow in both guides can potentially be applied consistently with the data available. For 17 inventory flows, we apply calculated scale-consistent inventory flows for Portuguese agriculture, covering 260 products that can be used in future LCA studies. Comparing results with international databases, we show that this procedure can improve country-level estimates significantly. Our study is the first step in introducing scale consistency as a guiding principle for regionalized LCIs for agri-food LCA studies. Integr Environ Assess Manag 2017;13:939-951. © 2017 SETAC.

Addressing the social life cycle inventory analysis data gap: Insights from a case study of cobalt mining in the Democratic Republic of the Congo

LCA studies require a high volume of data and their quality has a direct influence on the quality of the Life Cycle Inventory (LCI) and Life Cycle Assessment (LCA) study overall. The use of LCA databases enables users to (i) reduce time, efforts, and resources for data collection and (ii) reflect supply chains they have no direct control over. On the other side, it creates the need to align own modeling of the foreground LCA study with the modeling in the database. In recent years, countries worldwide have been more and more motivated in supporting LCA studies by providing national databases that reflect their economy, energy mix, and disposal technologies. This article aims to give insights on the main needs, requirements, and challenges for the creation of an LCA database, with a special focus on national, reference databases. First, the article defines the main characteristics of LCA datasets and discusses data collection approaches. Secondly, LCA databases are defined, and the creation of LCA databases from developed datasets is addressed, including the case of national LCA databases. Finally, the existence of tools that could ease the LCA dataset and database creation process is investigated, namely the LCA Collaboration Server and the LCA Data-Machine. It is important that countries willing to create a national database are supported, for example with capacity-building workshops, by actors with a long tradition in the field, which is of mutual benefit: Countries with a long tradition in LCA will benefit from interactions with newcomers, for instance by discussing together unsolved methodological and interoperability issues; newcomers do not need to start from scratch but can benefit from gained experiences. Creating databases that provide specific data for various parts of the world supports LCA methodology and application in general, and it is not the least a chance for local LCA communities to bring in innovation into LCA, and benefit from existing experiences at the same time.

Like any other manufactured chemical compounds, explosives are produced using chemical reactants and other utilities (steam, heat, compressed air, feed water and electricity) and generate a set of environmental impacts (waste water, solid and water residue and waste heat, for example). On top of that, one can count the intrinsic hazard characteristic of explosives and the possibility of accidents involving these compounds. Within this framework, explosives present themselves as chemical compounds suitable for both LCI (Life Cycle Inventory) and LCA (Life Cycle Assessment). This LCI study takes into account all the raw materials, utilities and wastes taking place during the production process. In this particular article, lead azide has its processed mapped and inventoried under the scope of ISO 14040. ISO 14040:2006 describes the principles and framework for life cycle assessment (LCA), including: definition of the goal and scope of the LCA, the life cycle inventory (LCI) analysis phase, the life cycle impact assessment (LCIA) phase,the life cycle interpretation phase, reporting and critical review of the LCA, limitations of the LCA, the relationship between the LCA phases and conditions for use of value choices and optional elements. The Lead azide was chosen due its singular explosive characteristics (very sensitive, which makes lead azide the explosive of choice as a primer in several applications. The results and conclusions of this study are drawn from the review of the process, its analysis, as well as from the application of life cycle inventory methods upon the manufactory of lead azide, a highly sensitive primer explosive, providing solid ground for the further studies, such as a full LCA assessment. Furthermore, for explosives, most LCA research works aims towards disposal, not addressing manufacturing, which is the main strength of this work.

Feeding a growing, increasingly affluent population while limiting environmental pressures of food production is a central challenge for society. Understanding the location and magnitude of food production is key to addressing this challenge because pressures vary substantially across food production types. Applying data and models from life cycle assessment with the methodologies for mapping cumulative environmental impacts of human activities (hereafter cumulative impact mapping) provides a powerful approach to spatially map the cumulative environmental pressure of food production in a way that is consistent and comprehensive across food types. However, these methodologies have yet to be combined. By synthesizing life cycle assessment and cumulative impact mapping methodologies, we provide guidance for comprehensively and cumulatively mapping the environmental pressures (e.g., greenhouse gas emissions, spatial occupancy, and freshwater use) associated with food production systems. This spatial approach enables quantification of current and potential future environmental pressures, which is needed for decision makers to create more sustainable food policies and practices.

The Life Cycle Assessment (LCA) is an impact research methodology that focuses on the life cycle of a product (by extension, services), and is standardized by the ISO 14000 Series. This methodology has been applied in so many areas related to sustainable development, in order to evaluate the environmental, economic and social aspects of the processes of production and distribution of products and service goods. Despite this wide range of applications, the technique still presents weaknesses, especially in the question of the evaluation and expression of the uncertainties present in the various phases of the studies and inherent to the stochastic or subjective variations of the data sources and the generation of models, sometimes reducing the consistency and accuracy of the proposed results. In the present study, we will evaluate a methodology to deal with the best expression of such uncertainties in LCA studies, focusing on the Life Cycle Inventory (LCI) phase. The hypothesis explored is that the application of the Monte Carlo Simulation and Fuzzy Set Theory to the estimation and analysis of stochastic uncertainties in LCA allows a better expression of the level of uncertainty in terms of the Guide to Expression of Uncertainty in Measurements [11], in situations where the original life cycle inventory does not specify the initial uncertainties. The iron ore transport was selected as a process unit by means of an off-road- truck (OHT) with a load capacity of 220 tons and a power of 1700 kW, acting on the route between the mine and the primary crushing of a mining company, in the city of Congonhas (MG). Monte Carlo simulations and Fuzzy Set Theory applications were performed using spreadsheets (MS Excel). The LCA study was conducted in OpenLCA 1.6 (open source) software from data inventories of ELCD database 3.2, also freely accessible. The results obtained were statistically compared using Hypothesis Test and Variance Analysis to identify the effect of the techniques on the results of the Life Cycle Impact Assessment (LCIA) and a Sensitivity Analysis was performed to test the effect of the treatment and function of the distribution of probabilities in the expression of the parameters associated with the items of the original life cycle inventory. Research indicates that inventories with treated data may have their uncertainty expressed to a lesser degree than that expressed in the original inventory, with no change in the final values of the Life Cycle Impact Assessment (LCIA). The treatment of life cycle inventory data through Monte Carlo Simulation and Fuzzy Set Theory resulted in the possibility of expressing the LCI results with a degree of uncertainty lower than that used to express the uncertainty under the standards. Data treatment through Monte Carlo simulation with normal probability distribution showed the lowest values of uncertainty expression with significant difference in relation to the original inventory, at a significance level of 1%.