Managing LCI Data Gathering

<div class="htmlview paragraph">As a means of effectively incorporating the concept of “life cycle” for reducing the environmental impact of the automobile, we carried out a life cycle inventory study on a part-by-part basis.</div> <div class="htmlview paragraph">The targets of our study are the fuel tanks that are made of different materials and manufacturing processes. One is made of steel, and the other is made of plastic, both perform identical functions. Our evaluation study encompasses the period from the manufacturing of the main materials until the disposal of the tanks.</div> <div class="htmlview paragraph">The evaluation items consist of the amount of energy consumed and the emissions (of CO<sub>2</sub>, NOx, SOx, and PM) that are released into the atmosphere. The results show that the plastic tank poses a greater burden in terms of the amount of energy consumed and the CO<sub>2</sub> and NOx emitted. This study confirmed that the areas to be improved in the life cycle of the tank, which could not be adequately assessed through the life cycle inventory analysis of the entire automobile, can be effectively extracted through the life cycle assessment of the tank itself.</div> <div class="htmlview paragraph">Lastly, we considered the issues that we should address in order to render the life cycle assessment (LCA) into practical application.</div>

<div class="htmlview paragraph">Studies have been made of the standardization of implementation procedures of the life cycle assessment (LCA), standardized as ISO14040 series, under the joint collaboration of industries, government agencies and universities.</div> <div class="htmlview paragraph">A life cycle inventory (LCI) of motorcycles, cases of research of whose LCA are scarce, has been attempted by taking infrastructures of Japan into consideration.</div> <div class="htmlview paragraph">Energy saving property “as mobility of motorcycles” was verified by building up a practical macro LCI method covering the stages of the life cycle of motorcycles.</div> <div class="htmlview paragraph">Furthermore, in the development of aluminum die-cast frames for scooters, micro LCI was performed for manufacturing stages to quantify the environmental advantage of fully utilizing recycled materials and clarify problematical points in the design of new materials. This proved that LCA method is effective for the selection of optimum materials and optimum manufacturing plans.</div>

Excerpts reprinted with permission from Parvatker, A. G.; Eckelman, M. J. Comparative Evaluation of Chemical Life Cycle Inventory Generation Methods and Implications for Life Cycle Assessment Results. ACS Sustain. Chem. Eng. 2019, 7 (1). Copyright 2019 American Chemical Society. Excerpts reprinted with permission from Parvatker, A. G.; Tunceroglu, H.; Sherman, J. D.; Coish, P.; Anastas, P.; Zimmerman, J. B.; Eckelman, M. J. Cradle-to-Gate Greenhouse Gas Emissions for Twenty Anesthetic Active Pharmaceutical Ingredients Based on Process Scale-Up and Process Design Calculations. ACS Sustain. Chem. Eng. 2019, 7 (7), 6580-6591. Copyright 2019 American Chemical Society. Excerpts reprinted with permission from Parvatker, A. G.; Eckelman, M. J. Simulation-Based Estimates of Life Cycle Inventory Gate-to-Gate Process Energy Use for 151 Organic Chemical Syntheses. ACS Sustain. Chem. Eng. 2020, 8 (23), 8519-8536. Copyright 2019 American Chemical Society. Synthetic chemicals are ubiquitous and are an integral part of almost every value chain in the industrialized world. Hence, comprehensive assessment of health and environmental impacts over the chemicals life cycle is critical in the pursuit of sustainable development, using quantitative modeling tools such as life-cycle assessment (LCA). However, lack of primary production data, and time- or resource-intensive design calculations often forces LCA practitioners to rely on simplistic methods for estimating chemical process data. Use of such "shortcut" methods for calculating chemical life cycle inventory (LCI) data introduces uncertainties and inaccuracies in environmental sustainability analysis. Research in this doctoral dissertation focuses on developing and implementing novel methods to reduce the time and resources required in chemical LCI data generation. An analysis of eight alternative methods to account for missing chemical LCI data was conducted to identify their strengths and drawbacks. Out of the four methods with whichfull LCIs can be generated, the advanced process-based methods give the most accurate life cycle GHG emission results compared to plant data for the case studies of styrene and its downstream product, acrylonitrile-butadiene-styrene (ABS). Stoichiometric calculations, which are the most commonly used approach, underestimate the actual global warming results by 35-50%.1 Among the 18 impact categories of the ReCiPe LCIA method, results for the estimated LCI data were within 10% of the actual plant results for only 4-5 categories. These techniques were then used in conjunction with a novel process scale-up and design method to estimate LCIs and cradle-to-gate greenhouse gas emissions for twenty common active pharmaceutical ingredients (API) used as injectable anesthetics and 130 intermediate pharma compounds. The cradle-to-gate GHG emissions of the 20 anesthetic drugs range from 11 kg CO2 eq. for succinylcholine to 3,000 kg CO2 eq. for dexmedetomidine. The LCI methods and data generated in this work greatly expand the available environmental data on APIs and can serve as a guide for LCA practitioners in future analysis of other pharmaceutical drugs. Process energy is a key input in a chemical LCI and has significant impact on LCA results. A streamlined process simulation-based methodology was developed to estimate energy consumption in chemical manufacturing. The methodology is applied to 151 different chemical processes using Aspen Plus to estimate their gate-to-gate process energy use, representing the largest such simulation-based LCI data set to date.3 The results from process simulations were then used to develop predictive models for heating and cooling requirements in chemical production. The multiple linear regression (MLR) and artificial neural network (ANN) models with R2 of 0.63 to 0.73 with measured error of less than 50% are robust alternatives for rapid estimations and screening analysis compared to the current methods used in LCI databases. The series of methods presented in this work can be used with varying availability of chemical synthesis data for life cycle inventory modeling. This research not only introduces and demonstrates novel methods for chemical LCI data estimation but also adds a significant number of new LCI data sets to the literature.--Author's abstract

Life cycle inventory (LCI) data gathering is one of the most time-consuming and data-intensive tasks in life cycle assessment (LCA) studies. Until now, it has mainly been described at a theoretical level and is associated with non-specific guidelines in LCA reference documents, thus leaving LCA practitioners with limited guidance prone to inefficient, not transparent, and sometimes inconsistent steps taken in the LCI phase. To tackle this problem, a stepwise data collection guidance is developed based on a critical review of existing guidelines and LCA case studies published in peer-reviewed scientific journals. The guidance encompasses three steps: (i) planning of data collection, including the outlining of LCI blocks, which represent unit processes in an aggregation level that is technology-wise appropriate; (ii) data gathering using the LCI blocks; and (iii) LCI blocks finalization. A customizable, generic LCI template for data collection is provided to facilitate the conduct of steps (i)-(iii). A real-life data collection case of lithium-ion batteries manufacturing is used to demonstrate the guidance's applicability. LCI block datasets were produced using the customized LCI template and the proposed guidance. Cooperation with the case data provider thus enabled to fill the data collection template, which was then reviewed iteratively. Although this case evidences the guidance's operability and its benefits in facilitating and strengthening LCA practice, several constraints undermining reproducibility and transparency could be identified, in particular issues related to data confidentiality. Despite these limitations, which require further efforts from practitioners and more transparency from stakeholders involved in the commission of LCA studies, the authors call for applying the proposed stepwise guidance to enhance future LCA practice.

<div class="htmlview paragraph">In this paper we present a hybrid approach to Life Cycle Assessment (LCA) using the case study of an electronically controlled unit injector (EUI), which is a time-controlled fuel injection system. Using the hybrid approach, we are able to quantify environmental information on upstream production processes preceding manufacture at Bosch without the need to gather all supplier data empirically. Life Cycle Inventory (LCI) data based on “conventional” process models are combined with LCI data from economic input-output relations between different industry sectors and associated pollution discharges and nonrenewable resource consumption. The economic input-output-based LCA (EIO-LCA) allows us to quantify indirect environmental impacts of production processes generally neglected in conventional LCA models. As EIO-LCA quantifies environmental impacts on a rather aggregate level, additional process models for LCA are used to account for specific characteristics of the processes investigated. The hybrid approach significantly reduces the effort required for data gathering and analysis and allows for a more comprehensive assessment of the environmental burdens associated with a product or process. To validate our approach, we contrast the results of the hybrid LCA to the results obtained from a conventional process LCA.</div>

Advances in Life Cycle Assessment (LCA) toward greater automation and methodological integration have intensified challenges in standardizing heterogeneous raw Life Cycle Inventory (LCI) data, which rarely aligns with LCI database nomenclature. Rule-based mapping approaches struggle with linguistic variations, typographical errors, unit inconsistencies, and location granularity mismatches. Furthermore, they fail to adapt automatically when data or terminology change. FAULDIER (Framework for lArge langUage modeL assisteD lIfe cyclE inventoRy) is proposed as a framework to bridge heterogeneities between raw LCI data and LCI database requirements. It aims to automate data transformation by resolving naming inconsistencies, classifying flow types, and harmonizing locations and units. By using LLMs, FAULDIER supports handling multilingual inputs, correcting typographical errors, resolving location granularity mismatches, and choosing proxies for missing processes. In a test scenario using the open LCI database FORWAST and a use case characterized by non-standardized multilingual entries, unit inconsistencies, and typographical errors, FAULDIER achieved approximately 57% process and elementary flow mapping accuracy (single-expert validated), with unit conversion error rates below 1%. Current limitations include LCI database constraints, LLM token limitations, performance variability of open-weight LLMs, mapping ability, and reproducibility across runs. Within these limitations, FAULDIER indicates the feasibility of LLM-assisted LCI construction for LCA modeling, particularly for non-standardized raw LCI data. Future work could focus on developing confidence metrics for mapped LCI data, optimizing LLM query efficiency, and expanding testing across additional LCI databases, use cases, and LLMs.

<div class="htmlview paragraph">In a project carried out for a major French company in the energy sector, we used the data from the Life Cycle Inventory (LCI) of an industrial transformation process and experimented with three external cost evaluation methods. This paper is a presentation of the results obtained. The first part outlines the three external cost evaluation methods and presents the way we used them. The second part presents the results obtained. The third part discusses the relevance of external costs in a corporate decision making context.</div>

Solar PV is a crucial technology for the transition to more sustainable economies. Multiple Life Cycle Assessments (LCA) have been made to assess PV environmental impacts. The core of these studies lies on the Life Cycle Inventories (LCI) used for the manufacturing of PV system components. This work identifies several research gaps in the existing LCI: 1) the LCI needed to be systematically updated to take account of technological developments, 2) the facilities and services supporting the main production processes were not covered in detail, and 3) the LCI aggregated at the factory level doesn’t allow the study of energy, material and resource flows. This dissertation presents a process-based bottom-up modelling approach to integrate LCI and circularity strategies for the polysilicon to PV module value chain. Circular production LCI for p- type Cz silicon wafers, Passivated Emitter and Rear Contact (PERC) solar cells and glassbacksheet PV modules with an aluminium frame are integrated and disclosed. The methodology includes a first step of data collection and validation for the reference products and production processes. In a second step, the required process and facilities equipment is determined and dimensioned. The third step is to dimension the civil, structural, and architectural infrastructure for a polysilicon to PV module industrial site with a production capacity of 5 GWp/a. With both the operational and the infrastructure requirements, integral reference products LCI are created. Finally, a number of circularity strategies are proposed and evaluated through comparative LCA and their Total Cost of Ownership., these analyses and results are published in three peer-reviewed publications that integrate this cumulative dissertation. A first publication examines material and solid waste flows and proposes the circular strategies Revalorized Waste (RW) and Vertical Integration (VI). With the RW and VI strategies, it is possible to avoid and revalorize 87% of the solid waste produced in a 5 GWp/a Poly-Si to PV module industrial site, this represents a circular flow of raw materials of 18,756 metric tons per year. In a second publication, the water, chemical, wet exhaust and wastewater flows of a PERC solar cell factory are scrutinized and the circular strategies Low Contaminated wastewater Reclaim (LCR) and Minimal Liquid Discharge (MLD) are envisioned. With the MLD strategy 79% of the water consumption and 84% of the wastewater indirect discharge of a PERC cell factory can be saved. In regions with limited water availability, the LCR and MLD strategies, as well as the reduction or elimination of silane consumption, can become enablers for new investments in PV manufacturing and reduce operational risks of existing production sites. Finally, a third publication calculates the environmental impact of the procurement and construction of the industrial site and proposes the use of a sustainable structural Timber Building System (Timber BS). A key outcome is the creation of updated and state-of-the-art LCI datasets for PV factories. Their adoption into the Ecoinvent database is recommended to replace outdated II datasets from the early 2000s. The LCI update resulted in factory environmental impact reductions ranging from 11.7% to 94.3% for 14 of the 15 environmental impact categories assessed. The updated factory environmental impacts contribute between 0.16% and 4.42% of the total PV module environmental impact for all impact categories assessed. These results show that most of the environmental impacts are due to the operation of the industrial site rather than from its procurement and construction. A sensitivity analysis shows that the most effective measure to reduce environmental impacts of all categories and the cost is to increase the PV module efficiency. A 10% efficiency increase translates into 9.1% reductions on all environmental impacts and Total cost of ownership. A 10% reduction in metallization paste consumption reduces the Resource use, mineral and metals impact by 6.6%. Silane consumption savings of 10% in the cell factory allow a reduction of Water use of 5.7%. Technical parameters with a significant environmental impact, so-called environmental hotspot parameters, and a strong cost driver, such as higher cell efficiency and thinner wafer pitch, are being continuously improved by the PV industry. However, to promote improvements in environmental hotspot parameters with a strong environmental driver and a weak cost driver, such as silane and water consumption and wastewater discharge reduction, environmental policy instruments may be required.

PurposeThe European Commission’s Integrated Product Policy Communication, 2003, defined Life Cycle Assessment (LCA) as the ‘best framework for assessing the potential environmental impacts of products’. Since then, the use of LCA and life cycle approaches has been developing in a wide range of European policies, and its use has also significantly grown in business. Increasing the availability of quality-assured Life Cycle Inventory (LCI) data is the current challenge to ensure the development of LCA in various areas.MethodsOne solution to increase availability is to use LCI data from multiple database sources but under the condition that such LCI data are fully interoperable.Results and discussionThis paper presents original solutions and recent achievements towards increased availability, quality and interoperability of life cycle inventory data, developed through European Commission-led activities and based on wide stakeholder consultation and international dialogue. An overview of related activities, such as the International Reference Life Cycle Data System (ILCD), the European Reference Life Cycle Database (ELCD) and the ILCD Entry-Level quality requirements are presented. The focus is then on the Life Cycle Data Network (LCDN).ConclusionsA non-centralised data network of LCI datasets complying with minimum quality requirements that was politically launched in February 2014, already includes several database nodes from different worldwide sources and has the potential to contribute to the needs of the international community.

<div class="section abstract"> <div class="htmlview paragraph">This document provides preliminary<sup><span class="xref">1</span></sup> safety-relevant guidance for in-vehicle fallback test driver training and for on-road testing of vehicles being operated by prototype conditional, high, and full (Levels 3 to 5) ADS, as defined by SAE J3016. It does not include guidance for evaluating the performance of post-production ADS-equipped vehicles. Moreover, this guidance only addresses testing of ADS-operated vehicles as overseen by in-vehicle fallback test drivers (IFTD).</div> <div class="htmlview paragraph">These guidelines do not address:</div> <ul class="list disc"> <li class="list-item"> <div class="htmlview paragraph">Remote driving, including remote fallback test driving of prototype ADS-operated test vehicles in driverless operation. (Note: The term “remote fallback test driver” is included as a defined term herein and is intended to be addressed in a future iteration of this document. However, at this time, too little is published or known about this type of testing to provide even preliminary guidance.)</div></li> <li class="list-item"> <div class="htmlview paragraph">Testing of driver support features (i.e., Levels 1 and 2), which rely on a human driver to perform part of the dynamic driving task (DDT) and to supervise the driving automation feature’s performance in real time. (Refer to SAE J3016.)</div></li> <li class="list-item"> <div class="htmlview paragraph">Closed-course testing.</div></li> <li class="list-item"> <div class="htmlview paragraph">Simulation testing (except for training purposes).</div></li> <li class="list-item"> <div class="htmlview paragraph">Component-level testing.</div></li></ul> <div class="htmlview paragraph">These guidelines also do not address prototype vehicle and IFTD performance data collection and retention. The collection of data invokes various legal and risk management considerations that users of this document should nevertheless bear in mind, such as:</div> <ul class="list disc"> <li class="list-item"> <div class="htmlview paragraph">Maintaining auditable procedures and documentation.</div></li> <li class="list-item"> <div class="htmlview paragraph">Adhering to applicable privacy laws and principles.</div></li> <li class="list-item"> <div class="htmlview paragraph">Ensuring adequate data collection and recording integrity to support post-crash forensic analysis.</div></li></ul></div>

<div class="htmlview paragraph">Life cycle assessments (LCA) require extensive quantities of data on processes as well as on material and energy flows. Therefore, simplifying methods that reduce the effort in modeling the product system do have the most potential to make reliable LCAs of complex products like automobiles more efficient. Methodological approaches allowing the LCA practitioner to conduct the scope definition and life cycle inventory (LCI) with minimal effort through “smart” software based support are introduced. The suggested methodology has been validated with a case study on material options for a front subframe system of a Ford passenger car.</div>

In this chapter, a wide range of Life Cycle Assessment (LCA) methods, new initiative for reducing emissions and improving resource efficiency, and Product Environmental Footprint are examined, in order to introduce the research tendency in this filed and clarify the differences among these Life Cycle Impact Assessment (LCIA) methods. The LCIA methods are broadly categorized as resource based and emission based. Life Cycle Inventory (LCI) database are also investigated, and the features of the generic LCI database are presented. The data formats of the ecoinvent database are deeply examined, with the aim of clarifying the attributes, types of each data components to help users to understand the role of inventory database in the practices.

Life cycle inventory for currently produced pine roundwood

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.

Decision tree-based approach to extrapolate life cycle inventory data of manufacturing processes