ABSTRACT. In a globalized world it is becoming more difficult to find out where products and all their components come from and under which conditions they are produced. More and more customers care about all of the impacts the products and goods they purchase leave behind over their whole live cycle. Hence, the demand for more transparency along supply chains in order to have a choice between more or less sustainable products is growing. However, while Environmental Life Cycle Assessments (E-LCA) are comparatively easy to carry out, the social impacts of products along their life cycles are hard to uncover. A database which contains transparent and comprehensive information about the social impacts of products does not yet exist. If nothing else, because social data is often of qualitative nature and, therefore, difficult to access, organize and evaluate.

The increasing necessity of Social Life Cycle Assessment (S-LCA), however, requires solutions and methods for the most urgent questions: What topics, indicators and type of data are appropriate and necessary for S-LCA? And how can such data be made tangible, measurable and practicable?

Bearing these problems in mind, GreenDelta is developing a database – PSILCA – that aims to be a comprehensive and up-to-date foundation for S-LCA containing global data for every industry sector. In order to make S-LCAs of different products comparable, a rather broad set of quantitative and qualitative social indicators will be covered by the database using the subcategories proposed in the UNEP/SETAC guidance book as a starting point. The assessment of indicators is transparently based on performance reference points that can be adapted to individual requirements, by the user. External input about the further development of PSILCA is provided by an expert and user group.

The completely new database shows how social data can be organized, assessed and finally used for social LCA or Life Cycle Sustainability Assessment. Another field of application is to investigate social impacts independently, in order to detect potential social risks in product life cycles. Furthermore, positive social impacts hidden in product supply chains can also be revealed by applying PSILCA.

In the presentation the methodology, composition and intended usage of the database will be outlined, based on a case study for guitars. Possible improvements and forms of use will be discussed, such as, for example, the combination of the PSILCA approach of S-LCA with E-LCA.

ABSTRACT. After decades of global, corporate, local, and personal sustainability-driven efforts, human society still remains on an unsustainable trajectory [1]. Critical to these sustainability efforts in recent decades, Life Cycle Assessment (LCA) has been an important framework and tool for identifying environmental benefits and tradeoffs of products and technologies. In some cases, LCA has been blamed when progress has not been made despite its adoption. However, it is clear that LCA is not a “magic bullet” of sustainability, but instead a tool to help guide solutions to sustainability challenges.

The Dow Chemical Company is a global organization committed to solving sustainability challenges. In 2015, The Dow Chemical Company announced its third decade of corporate sustainability goals. In its 2005 Environmental, Health & Safety Goals, the company focused on its footprint, setting culture-changing goals to improve safety performance and operational efficiency. In its 2015 Sustainability Goals, Dow expanded beyond footprint to focus on its “handprint” – the positive life cycle impact of its products – and dedicated significant LCA resources to measuring, improving, and communicating the life cycle impact of its products using. In its 2025 Sustainability Goals [2], Dow has moved beyond footprint and handprint to stress the importance of a “blueprint” – the combination of technology, public policy, and behavior change that will lead human society to sustainability.

This talk will demonstrate the importance of LCA and life-cycle thinking in defining a blueprint and achieving the transition to a sustainable society. We will provide examples where LCA is critical to defining solutions at the intersection of technology, public policy, and behavior change. By applying LCA to a blueprint, we can help human society to move from an unsustainable trajectory to one that allows billions of people to live well within the limits of the planet.

References

1. Global Environment Outlook 5, UNEP (2012), http://www.unep.org/geo/pdfs/geo5/GEO5_report_full_en.pdf, accessed 28 April, 2015. 2. Dow Launches 2025 Sustainability Goals to Help Redefine the Role of Business in Society, http://www.dow.com/news/press-releases/dow%20launches%202025%20sustainability%20goals%20to%20help%20redefine%20the%20role%20of%20business%20in%20society, accessed 15 April, 2015.

ABSTRACT. The number of studies applying multi-criteria decision analysis to energy choices within the framework of life cycle sustainability assessment is increasing [1–3]. However, earlier studies are not explicit about how preferences are constructed by acquiring sustainability information and by applying decision support methods. Therefore, we conducted an experimental study to prove the hypothesis that acquisition of sustainability information and use of decision support methods consistently construct participants’ preferences.

We focused on electricity generation technologies using renewable energies. The energy sources include solar power, wind power, small-scale hydroelectric power, geothermal power, wood biomass, and biogas. The sustainability information was prepared using a renewable energy-focused input-output model of Japan and contains life-cycle GHG emissions, electricity generation cost, and employment generated by the technologies. Each criterion corresponds to the environmental, economic, and social aspect of sustainability.

We measured rank-ordered preferences at the following four steps in experimental workshops conducted for 18 municipal officials, who were not familiar with sustainability assessment and decision analysis: (1) provision of the energy source names; (2) provision of the sustainability information; (3) provision of additional explanation about public value; and (4) provision of knowledge and techniques about multi-attribute value functions [4], wherein single-attribute value functions are supposed to be linear. In the steps 1–3, the preferences were measured through sorting cards with each energy source name or cards with sustainability information for each technology. In the step 4, we used the weighting procedure with appropriate range sensitivity of attribute weights [5]. The degree of changes in preferences was measured using Spearman's rank correlation coefficient. The consistency of preferences among participants was measured by the maximum eigenvalue for the coefficient matrix.

The results are summarized as follows: (1) The individual preferences evolved drastically in response to the sustainability information and the decision support method. (2) The preferences among participants became more consistent by acquiring the sustainability information and the decision support method. These results indicate that the systematic development of sustainability criteria is essential for a more deliberate human behavior and that information provision coupled with decision support technologies is effective for collective decision making.

Citations:

[1] Bessette, D.L., Arvai, J., Campbell-Arvai, V., 2014. Decision support framework for developing regional energy strategies. Environmental Science and Technology, 48, 1401–8. [2] Maxim, A, 2014. Sustainability assessment of electricity generation technologies using weighted multi-criteria decision analysis. Energy Policy, 65, 284–297. [3] Santoyo-Castelazo, E., Azapagic, A., 2014. Sustainability assessment of energy systems: Integrating environmental, economic and social aspects. Journal of Cleaner Production, 80, 119–138. [4] Goodwin P., Wright, G., 2014. Decision Analysis for Management Judgment, 5th Edition, Wiley. [5] Keeney R.L., 2002. Common mistakes in making value trade-offs. Operations Research, 50, 935–945.

ABSTRACT. In recent years, smartphone app use has risen dramatically and with it have emerged a number of educational apps that use LCA to communicate the environmental and social impacts of purchasing certain food products. For example, in the Netherlands, the app “Questionmark” has a database of nearly 30,000 food products and measures public health, environment, human rights, and animal welfare impacts. While these apps are innovative ways to educate consumers about how their food choices affect the world, are they enough of a trigger to induce behavioral change over the short or long-term? Additionally, are the apps able to apply pressure on the food industry to change or improve their operations toward ecological or social betterment? Through an online investigation and interviews of smartphone app developers, this paper reviews a number of food-related LCA smartphone apps used in Europe and North America and evaluates their capacities, functionality, and interface/design. We also analyze the apps’ overall significance in terms of consumer use and educational benefit, as well as their ability and potential to induce change on the side of industry. Finally, we speculate on a design for the “ideal food LCA smartphone app” geared for use in Asian countries.

ABSTRACT. There is a growing consensus among scientists that the primary cause of climate change is anthropogenic greenhouse gas (GHG) emissions. Given the strengthening science behind the human influence on climate change, it will be necessary for the global community to use low-carbon technologies in both the energy and industrial sectors. As a result of the recent focus on GHG emissions, the U.S. Environmental Protection Agency (EPA) and state agencies are implementing policies and programs to quantify and regulate GHG emissions from key emitting sources in the United States. These policies and programs have generated a need for a reliable source of information regarding GHG mitigation options for both industry and regulators. In response to this need, EPA developed a comprehensive GHG mitigation options database (GMOD) that was compiled based on information from industry, government research agencies, and academia. The database is a repository of data on available GHG technologies in various stages of development for several high-emitting industry sectors. It is designed to address multi-sector GHG emissions from stationary sources and help the user determine the most attractive options from performance and cost perspectives. It can be used for analyses of various GHG control technology options and their implications on sector-specific output, economics, and environmental parameters. The current version of the GMOD contains three sectors including Power, Cement and Pulp & Paper. A refinery sector is under development and is scheduled to be available in GMOD database in 2017.

ABSTRACT. Currently, to access LCA data associated with literature, practitioners must search for supporting information with journal publishers or contact the corresponding author directly. Even worse, data may become inaccessible when the original researchers retire, or the hard drive holding the data becomes damaged. The National Agricultural Library (NAL) is expanding its contribution to the LCA community with library and metadata curation services to assist in the discovery, re-use, archiving, and preservation of LCA research data and resources. The tools employed in library services contribute to a convergence of LCA data representation through controlled vocabulary and structured data models. Here we present the LCA Commons collection at the NAL’s Ag Data Commons, and the National Agricultural Library Thesaurus (NALT), a structured agricultural thesaurus recently expanded with sustainability and LCA terminology.

The Ag Data Commons is a web catalogue and repository of research data and resources from a wide range of fields related to agriculture, allowing visitors to easily find and access information using controlled keywords and search terms. Similar to the general purpose Dryad Data Repository (datadryad.org), Ag Data Commons also connects research data to the associated publications, provides descriptive metadata and data dictionaries, and facilitates tracking of re-use by assigning unique DOIs to the datasets themselves (as opposed to the research publication associated with the data). Through these services the LCA Commons collection at the Ag Data Commons will add value to the already valuable data source underpinning an LCA.

Controlled keywords and search terms are critical for effective access to archived resources. Since 2002, the National Agricultural Library has maintained and developed a rich, expertly-constructed thesaurus, NALT, which it uses to index its collection. NALT is being expanded with LCA terminology to provide preferred terms and often-used synonyms, as well as the vertical relationships between general and specific concepts. This functionality aids data discovery and interoperability by providing a consistent concept model translating between nomenclatures, documentation styles, and file formats. The NALT is a tool that can be used to implement a controlled vocabulary for LCA, to lay the foundation for semantic modeling, data management and data discovery applications.

ABSTRACT. As the benefits of using Life Cycle Assessment (LCA) becomes more apparent to global decision makers, countries are seeking to capitalize on these benefits by supporting the creation of national life cycle inventory (LCI) databases or networks. Such systems would allow users to integrate data from more than one LCI source, a major driving force behind the Global Network for LCA Databases to enable interoperability and data exchange on an international level (Joint Research Centere: European Platform on Life Cycle Assessment, 2014). Data quality is a major issue to be resolved when combining data from various sources. This study addresses the use of data quality indicators, focusing on differences in indicator systems and reproducibility of data quality indicators (DQIs). In order to show global trends in implementing data quality systems, we perform a methodological review of data quality standards and systems used in existing databases. Two major types of systems emerged from this study; the criteria-based system and the more widely used matrix-based systems. Using a sample process data set, we then compare the reproducibility of data quality indicators for the criteria-based and matrix-based data quality systems across seven data quality indicators. These indicator categories are: reliability, completeness, temporal, geographic, technological, uncertainty, and precision. We find current quality practices can be highly subjective for applications and reporting, which produce variability in data quality ratings. This lack of consistency and reproducibility in data quality ratings undermine the purpose and effectiveness of a data quality system. Evaluation of a sample data set using all systems confirms the findings of our review and shows no discernable pattern of reproducibility. No indicator reached a 100% agreement using either DQI system. 32% of indicators achieved a >80% agreement using the criteria-based system, while only 14% of indicators using the matrix-based system achieved this same level of agreement. This study shows the need for more structured methodologies in the field of LCA data quality to ensure reproducibility while maintaining the desired practitioner autonomy.

References Joint Research Centere: European Platform on Life Cycle Assessment. (2014). EPLCA. Retrieved from Life Cycle Data Network: http://eplca.jrc.ec.europa.eu/?page_id=134

ABSTRACT. Life cycle assessment (LCA) results often crucially depend on the life cycle inventories (LCI) of electricity generation and supply drawn from background databases. Therefore, their up-to-dateness and representativeness are essential factors [1, 2]. We provide an overview of the new LCI data for the electricity sector (power generation and power supply, i.e. electricity markets) implemented in ecoinvent v3.2 [3]. New LCI data are based on latest statistics and recently published literature. Inventory data for power generation technologies representative for single countries or smaller regions were harmonized throughout the database concerning parent-child relationship, use of parameters, variables and mathematical relations, water balance as well as technology levels. Global averages were coherently calculated. Six additional countries were included, allowing for complete coverage of the EU-28 member states. Additionally, China was split into 31 provinces on the generation technology level and into two electricity markets according to the two main grid operators in China. Unit processes for electricity production in 107 geographic regions covering 56 countries are now available in ecoinvent v3.2, representing 89% of global generation in 2012. LCI data for several new electricity (and heat) generation technologies were introduced: hard coal, lignite and oil plants with combined heat and power generation and solar thermal power plants. Region-specific power plant efficiencies as well as operational emissions were updated and latest annual yields for photovoltaics and wind turbines implemented. Additional updates include deep geothermal power, CO2 and CH4 emission factors from hydro reservoirs due to decomposition of biomass, geography-specific electricity losses in the power grid and technology-specific market shares. The updates and extensions of LCI data for the electricity sector in ecoinvent v3.2 once more stress the importance of high spatial resolution of these data due to substantial geography-specific variations. The observed changes in the LCI data compared to ecoinvent v3.0 [4, 5] highlight the importance of regular updates of the electricity sector. With the new electricity markets representative for year 2012, ecoinvent v3.2 provides the most up-to-date, complete and representative LCI data for electricity generation and power supply to users of generic background LCI data.

[1] Masanet, E. et al. (2013) Life-Cycle Assessment of Electric Power Systems. Annual Review of Environment and Resources 38:107-136. doi:10.1146/annurev-environ-010710-100408. [2] Turconi, R., Boldrin, A., Astrup, T. (2013) Life cycle assessment (LCA) of electricity generation technologies: Overview, comparability and limitations. Renewable and Sustainable Energy Reviews 28:555-565. doi: http://dx.doi.org/10.1016/j.rser.2013.08.013. [3] The ecoinvent LCA database, v3.2 (2015) The ecoinvent center. www.ecoinvent.org. [4] Treyer, K., Bauer, C. (2013) Life cycle inventories of electricity generation and power supply in version 3 of the ecoinvent database – part I: electricity generation. Int J Life Cycle Assess:1-19, doi:10.1007/s11367-013-0665-2. [5] Treyer, K., Bauer, C. (2014) Life cycle inventories of electricity generation and power supply in version 3 of the ecoinvent database – part II: electricity markets. Int J Life Cycle Assess:1-14. doi:10.1007/s11367-013-0694-x.

ABSTRACT. The objective of this study is to investigate the method to consider a scale effect in LCA through the case studies of future technologies. The environmental impacts of laboratory scale future technology using small scale processes are much larger than those of conventional technology using the large scale mass production processes because an efficiency of small scale process is generally lower than that of large scale process. Therefore, the extension of LCA to consider a scale effect is necessary to compare the environmental impacts of laboratory scale technology to those of commercial scale conventional technologies. In this study, we propose a method to consider a scale effect in LCA. The following two cradle-to-gate LCA case studies are conducted to demonstrate our method; carbon nanotube super growth method [1] and oxidation process using hydrogen peroxide [2]. The CO2 impacts of the two technologies are estimated at the following three different scales; laboratory scale, pilot plant scale, and commercial scale. The inventory data of laboratory scale is obtained from the researchers. That of pilot plant is estimated from the patent data [3] and report [4]. That of commercial scale is estimated from the inventory of pilot plant using scaling factor [5]. The scaling factor is calculated using the machinery specification data on the website [6]. In this study, we consider the scale effect of energy consumption. CO2 impacts are estimated using the IDEA database [7]. The CO2 impacts to produce 1kg carbon nanotube using super growth method become 1/3 when the scale changes from laboratory to commercial. The CO2 impacts to oxide 1kg alpha-pinene using hydrogen peroxide become 1/700 when the scale changes from laboratory to commercial. The results imply that the scale effect is critical to compare the environmental impacts of laboratory scale future technology to those of the commercial scale conventional technology. Considering the scale effect, it becomes possible to estimate the potential of future technology in LCA framework.

[1] K. Hata, D. N. Futaba, K. Mizuno, T. Namai, M. Yumura, S. Iijima, Science, 2004, pp. 1362-1364. [2] Y. Kon, K. Sato, AIST TODAY, 2012, pp. 12. [3] Japan patent JP 4581146 [4] NEDO, Development of Fundamental Technologies for Green and Sustainable Chemical Processes/Development of Innovative Chemical Process-Product with Less Waste Emission Fundamental Technology/Development of Innovative Oxidation Process (FY2009-FY2011), Final Report Summary. [5] G. F. Nemet, Energy Policy, 34 (2006), pp. 3218-3232. [6] Alibaba, http://www.alibaba.com/ [7] K. Tahara et al, Proc. 9th Meeting of the Institute of Life Cycle Assessment, Japan, 2013, pp. 174-175.

ABSTRACT. The development of advanced manufacturing technologies is essential in enhancing U.S. competitiveness as well as reducing industrial life-cycle energy consumption over next decades [1][2][3]. Such development is majorly driven by investment from governmental authorities and industries; therefore understanding the potential environmental and economic implications of the advanced manufacturing technologies is useful in better related decision-makings.

In this study, a life cycle modeling framework is developed to assess the net impact of emerging manufacturing technologies. Aspects that matter to current manufacturing industry are evaluated, including life cycle energy consumption, GHG emissions, costs, revenue, and manufacturing leading time. A multi-scale approach is explored by comparing results at process, facility and industry level as well as different spatial and temporal scales. Integrated Life cycle assessment (LCA) with techno-economic analysis is used to quantify the net changes of manufacturing systems and corresponding national impacts. Model results provide stakeholders at different levels with a good understanding of potential energy savings, GHG emission reductions, and economic benefits through adopting advanced manufacturing technologies, as well as identifying technology development opportunities that maximize these benefits.

For model application, additive manufacturing technologies are applied to different industries and compared with conventional manufacturing processes. In the case study of U.S. passenger aircraft industry, the results show a cumulative fleet-wide life-cycle primary energy savings of 1.2-2.8 billion GJ and 92-215 million metric tons of GHG emissions by 2050. In the case study of tooling, the model displayed that potentially 36% of the primary energy, 51% CO2-e emissions, 54% lead-time and 34% life cycle cost could be saved, and identified that improving machine throughput as well as reducing raw material (metal powder) cost could speed up achieving these benefits.

The modeling framework is a useful tool for decision makers in technology investment. The multi-scale approach and integrated analysis provides necessary detailed insights at different levels for stakeholders with distinguished preferences, such as researchers, managers, and policy makers. These outcomes are helpful to improve U.S. manufacturing in reducing energy and resource consumptions through emerging manufacturing technologies.

[1] Council on Competitiveness, Make, An American Manufacturing Movement, 2011 [2] National Science and Technology Council, A National Strategic Plan for Advanced Manufacturing, 2012 [3] President’s Council of Advisors on Science and Technology, Report to the President on Ensuring Leadership in Advanced Manufacturing, 2011

ABSTRACT. The GE Ecoassessment Center of Excellence has been applying LCA to explore the environmental impacts, benefits, and trade-offs of additively manufactured aircraft engine parts compared to traditional machined or cast parts. This presentation will explore a case study focused primarily on GE Aviation’s additively manufacturing fuel nozzle for the CFM LEAP engine. The fuel nozzle is traditionally manufactured by forging and machining in which the desired part shape is achieved via removal of material from a solid metal ingot and then multiple parts are joined together. Additive manufacturing involves building the desired part shape by adding material layer by later, in this case by direct laser melting to fuse metal powders. The additive manufacturing approach offers the potential for novel part geometries that result in reduced life cycle environmental impact due to enhanced performance (e.g., reduced fuel consumption over the life of the engine due to lower weight) and net lower raw material consumption.

GE has been piloting the US Department of Defense draft Sustainability Assessment methodology, which incorporates streamlined life cycle assessment/life cycle costing (SLCA/LCC) into the acquisitions process. The LCA portion of the assessment is a hybrid approach involving environmental input-output data for the upstream (supply chain) impacts and activity-based scoring factors for the downstream (operation, sustainment, end of life) impacts.

Since the use of additive manufacturing at a commercial scale represents a significant change affecting manufacturing techniques, materials choices and supply chain, GE Aviation is also interested in understanding supply chain and manufacturing impacts in greater detail using traditional process LCA. We have therefore been performing process LCA in parallel with the US DoD SLCA/LCC method.

This presentation will provide an overview of the SLCA/LCC and process-LCA approaches used, and discuss how the insights gained can be leveraged for both supplier (GE Aviation) and customer (US DoD).

ABSTRACT. The rapid growth of information and communication technology (ICT) has the potential to transform the industrial sector through Smart Manufacturing, where networked sensors, controls, and platforms are applied for the optimization of manufacturing processes. The use of ICT to create real-time data collection, diagnostics, analytics, and optimization can enable dynamic performance management, improved process accuracy, and energy and cost savings. We show how the adoption of Smart Manufacturing technology in the industrial sector will create new demands and opportunities for Life-Cycle Assessment. First, we discuss how the development of Smart Manufacturing technologies, and the application of these technologies in the industrial sector, will have large impacts when applying LCA to manufacturing equipment, manufactured products, and product supply chains. Along with changes within specific industrial sectors, our framework expands the scope of industrial LCA to include ICT infrastructure, from on-site IT equipment to data centers and house processing, storage, and network equipment. Second, we highlight the need for new LCA models for use in optimization at the factory and supply chain level. Lastly, the deployment of Smart Manufacturing systems will generate scores of data on energy usage, equipment utilization and maintenance, and material consumption and waste that can create opportunities to conduct new LCA with exceptional accuracy. We outline a national strategy to collect and apply this data, propose possible public and private sector roles and activities, and discuss the key barriers to implementation.

ABSTRACT. Hydraulic fracturing of oil reservoirs has resulted in a profound change in US oil futures: a 40-year decline in oil US production has been almost entirely reversed in the space of 7 years. However, the environmental impacts of hydraulic fracturing, including greenhouse gas (GHG) emissions are still uncertain.

We apply an open-source engineering-based LCA model called the Oil Production Greenhouse Gas Emissions Estimator to examine well-level emissions intensity of over 7,000 oil wells in the Bakken formation of North Dakota and 8,000 wells in the Eagle Ford formation of Texas. In order to do this, we leverage a new open-source tool called GHGfrack, which computes the greenhouse gas emissions associated with drilling and fracturing wells.

Results suggest that emissions from the Bakken formation are highly bi-modal. Wells which do not flare have upstream emissions that are 25-50% those of a “typical” oil reservoir (3.3 gCO2/MJ production weighted mean, 5%-95% range of 1.2 to 4.9 gCO2/MJ). Wells that do flare have emissions intensity similar to oil sands projects or high-flaring regions like Nigeria (12.9 gCO2/MJ, 5%-95% range of 3.1 to 32.5 gCO2/MJ). Wells in the Eagle Ford formation exhibit results more similar to non-flaring Bakken wells, although the large volume of co-produced natural gas liquids results in complications due to co-production analysis choices. Another key uncertainty is the treatment of flowback fluids during well completion.

These results highlight the importance of understanding and regulating air emissions from hydraulic fracturing operations. The difference between flaring and non-flaring wells in the Bakken formation is about 10 gCO2/MJ. This reduction is of the same magnitude as the targets set in a variety of regulations in the US (e.g., California Low Carbon Fuel Standard) and EU (e.g., Fuel Quality Directive). This implies that significant strides in fuel GHG intensity could be made by tighter controls on flaring rates.

ABSTRACT. Through a Critical Literature Review of 40 Life Cycle Analyses (LCA) that evaluate the environmental implications of liquefaction of natural gas (LNG) and their applicability to LNG production in British Columbia (intended system analysis), a systematic methodology was designed to determine the need and scope for a new LCA. A summary of the literature was performed focused on capturing the details of the LNG supply chain. The summary was built using a matrix format that includes 11 key aspects on critical review of LCA as per ISO 14044 Environmental Management – LCA – Requirements and guidelines. Finally, the literature was evaluated based on the appropriateness of the information to be used to achieve the intended goal. Statistics regarding the focus and the geographical representation of each analysis were developed. For example, it was demonstrated that the analyses of environmental impacts of the supply chain of LNG derived from Australian operations (33%) dominate existing LCA documentation. However, from the total upstream LNG LCAs, few of them (3 out of 12) represent a complete and/or consistent LNG supply chain. Also, the matrix designed was used to illustrate for each study the level of rigor used in the 11 criteria and its applicability to the intended goal. The methodology allowed to demonstrate the limited degree of overlap in scope, goals, methodology, resource base, and production methods between available LCA and what would be required to assess British Columbia’s situation that means existing LCA are only useful when a rough first overview of the system impacts is needed. However, such analyses would not provide meaningful insights into the contributions of specific elements in a British Columbian system which would include raw gas composition, natural gas recovery and production technology, liquefaction plant efficiency, electricity sources, and regulatory framework on venting and flaring emissions management, natural gas and natural gas liquids final market. The systematic framework developed can be used by policy makers or researchers to inform about the acceptability of applying existing LCA to a specific intended goal and to make the decision of whether or not and how to allocate resources to a new LCA.

ABSTRACT. According to the EIA, U.S. coal consumption in 2013 was approximately 15% lower than 2003 (EIA, 2014). As a result, coal producers have taken advantage of the growth in foreign coal demand via export markets. Over the same period, exports of steam coal from the U.S. increased by a factor of 2.5 (EIA, 2014). Historically, the majority of U.S. steam coal exports were shipped to Europe and the rest of North America. Since 2009, steam coal exports to the Asian markets have increased by an order of magnitude. The International Energy Agency (IEA) forecasts that steam coal trade will grow 3.2 percent annually through 2019, from 787 to 950 million tonnes (IEA, 2014). Chinese imports peak in 2017 at approximately 200 million tonnes. Demand in Europe will drop of slightly over the forecast period, while Japan and Korea show modest increases of 0.7 percent and 2.4 percent per year. The current capacity of U.S. export terminals is approximately 150 million tonnes per year. Two new facilities (Millenium Bulk Terminal and Gateway Pacific Terminal), which are currently under review in Washington state, could add an additional 90 million tonnes of export capacity (REF 2). These facilities would make it more economical to export low sulfur sub-bituminous coal from the Powder River Basin (PRB) from the Pacific Coast to Asian markets. The goal of this effort is to compare the life cycle GHG emissions of exporting PRB coal to destinations in Asia with regional alternatives. IEA forecasts that Indonesia will remain the largest coal exporter in the world with a 40 percent market share in 2019, while Australia will continue to be the second largest exporter (IEA, 2014). Exports from the PRB will be compared to exports from those countries. The scope of this LCA is a cradle-to-grave comparison of 1 MWh of electricity generated at an advanced power plant (ultra-supercritical pulverized coal) in Asia (Japan, Korea, and Taiwan). The Wyoming Infrastructure Authority has connected NETL with industry partners to obtain operating data for U.S. and international activities.

ABSTRACT. The U.S. crude consumption mix has changed dramatically since the National Energy Technology Laboratory (NETL) first performed a comprehensive LCA of petroleum derived fuels (NETL, 2008). According to the Energy Information Administration’s Annual Energy Outlook, domestic production will account for nearly 60% of U.S. crude consumption by 2015 (EIA, 2015). In 2005, the reference year for the NETL Petroleum Baseline, domestic production accounted for only 34% of U.S. consumption. Almost half of the domestic production in 2015 is predicted to be from tight oil, predominantly shale oil, which can be recovered economically because of technological advances in directional drilling and hydraulic fracturing. Thus, the U.S. reliance on overseas crude imports is projected to drop substantially. There are obvious energy security implications of these shifts, but what remains unclear is how these changes will impact the life cycle footprint of conventional fuels produced domestically. This study examines the life cycle GHG footprint of diesel, gasoline, and jet fuel projected to 2040. Changes to the domestic crude slate not only affect the emissions associated with crude extraction, but also the processing intensity in U.S. refineries based on changes to the quality of the crude. The results of this analysis encompass a cradle-to-grave inventory of GHG emissions by utilizing open-source models (Oil Production Greenhouse gas Emissions Estimator (OPGEE) and Petroleum Refinery Life Cycle Inventory Model (PRELIM)) paired with Monte Carlo simulation to account for changes to crude extraction, transport and refining as well as forecast uncertainty from the EIA Annual Energy Outlook (El-Houjeiri et al, 2013; Abella & Bergerson, 2012). The results of this analysis encompass a cradle-to-grave inventory of GHG emissions by utilizing updated models to account for changes to crude extraction, transport and refining. Section 526 of the Energy Independence and Security Act (EISA) of 2007 notes that life cycle GHG emissions from alternative fuels contracted by a federal agency, other than for research and testing, must be less than or equal to life cycle emissions from conventional fuels (USC, 2007). There are potential policy implications resulting from this study since the NETL Petroleum Baseline serves as the reference for the conventional fuels included in EISA Section 526.

ABSTRACT. This study was carried out with the LCA of greenhouse grown tomatoes in Thailand. The functional unit of this study was 1 kg of tomato and the system boundary was cradle to gate of greenhouse tomato fruits (seedling process to packaging process), which includes seedling, growing, harvesting and packaging process.

The third order of LCA was applied in this study by using SimaPro 7.1 software program. The Eco-Indicator 99 H/H was selected as method for evaluating environmental impacts of greenhouse grown tomatoes. LCIA based on the characterization and single score elements. The selected impact categories of Eco-Indicator 99 method are carcinogens, respiratory organic and inorganics, climate change, radiation, ozone layer, acidification and ecotoxicity, land use, mineral, fossil fuels.

Limitations of this study are transportation processes of products to the market and food storage of tomato products, neither of which were included in this study. Moreover, no waste scenario analysis of product system was studied.

ABSTRACT. Steam curing can enhance the early strength of concrete, but may cause a certain loss of long-term strength; fly ash can increase the strength of concrete with age. Therefore, in this paper, the effect of steam curing on compressive of fly ash concrete was investigated by experiments, and then the environmental impact of fly ash concrete was calculated by life cycle assessment. The results showed that high volume fly ash concrete had better adaptability to steaming curing; environmental impacts tended to decrease with the increase in the addition of fly ash, whether under normal curing regime or under steaming curing regime; the difference of each environmental impact per strength between the two curing regimes became smaller with the increase in the addition of fly ash.

ABSTRACT. Installing carbon capture lines in power plants, which provides zero and even negative net emissions, is considered to be a vital part of GHG emission mitigation strategy. However, retrofitting coal- fired power plants in this way will significantly decrease power output and increase material cost.

Exergy, a thermal metric that denotes the potential to drive changes, is a good measurement to quantify the life cycle change incurred by installing amine absorption equipment. This study builds two power plant models based on NETL baseline case 9 and case 10, with an emphasis on material cost. Major equipment of the amine absorption line, such as absorbers, strippers, blowers, compressors, pumps, heat exchangers, pipeline, etc. are modeled in detail. A life cycle exergy calculation method based on the Ecoinvent database is subsequently used to calculate the life cycle exergy from these two power plant models.

It is discovered that lifetime exergy efficiency will decrease significantly from 26.52% to 19.04% between the two cases. Most of the exergy change is due to the increased coal consumption, while the installment of carbon capture equipment only account for 0.015% of the exergy input change.

From a life cycle point of view, the amine absorption equipment itself, while large in size, is not very demanding in exergy input. The decreased electricity output, which mainly goes to fuel the additional reboiler heat duty, should require more attention.

ABSTRACT. Although the importance of uncertainty analysis in Life Cycle Assessment studies is well-known, a methodological procedure to identify, integrate and quantify the error propagation throughout the analysis is still lacking. This study presents an uncertainty classification methodology, along with an integrated, quantitative analysis as a best practice example for uncertainty quantification.

Three case studies have been chosen to apply the uncertainty methodology; the first being a simple product system-an electric kettle, the second a more complex product system-an apartment complex, and lastly, a complex fluctuating market- the production of electricity in Ireland. These three LCA case studies require various amounts of data, making uncertainty quantification more complex. Comparisons of the application of the uncertainty analysis methodology to each case study are made.

ABSTRACT. BACKGROUND: Ethanol production via biochemical conversion of cellulosic forest residuals requires critical conversion steps; including biomass collection and pre-processing, pretreatment, enzyme production, enzymatic hydrolysis, and fermentation. Mild Bisulfite (MBS) pretreatment (a variant of SPORL pulping) is an emerging option for the breakdown and subsequent processing of biomass towards fermentable sugars. An environment assessment of the entire process (biomass-to-ethanol) using this technique is critical to discern its future sustainability in the ever-changing biofuels landscape. CONCLUSIONS: The results reveal that global warming and eutrophication were greatly impacted by enzyme production and the preparation/transport of biomass within the MBS process towards cellulosic sugar. This work, which singly highlights the impacts of ethanol production from cellulosic materials, will be critical in informing the growing biofuels literature.

ABSTRACT. The brewing industry has experienced a renaissance in recent decades, with the number of micro- and craft- brewers increasing rapidly. Campaigns and initiatives, for example, the UK based CAMRA (Campaign for Real Ale) ‘LocAle’ scheme (highlighting local and ‘green’ produce), have helped drive the increasing demand. Whilst exact definitions for “micro-” or “craft-“ breweries vary, typically they are small scale independently owned breweries using traditional brewing methods. Typically they adopt a different approach to marketing and distribution in order to compete in an extremely competitive market, with an emphasis on flavour, quality, and individuality. Despite the relative simplicity - inputs of malt, hops, water, yeast and energy - of the craft beer manufacturing process opportunities exist for brewers to enhance sustainability – environmentally, socially and economically. To realise these opportunities breweries must first examine the supply-chain, manufacturing, and distribution processes to establish points of impact, compare alternative possibilities. This poster will present the results of an applied research project investigating the environmental sustainability of the micro-brewing industry in the UK. The geographic and economic extent of the micro-brewing industry in the UK is first explored. Subsequently LCA results from case-study micro-breweries are used to compare the full range and temporal/spatial extent of environmental impacts resulting from the micro-brewing process.

ABSTRACT. Agricultural production is not very well investigated in Iran environmentally and LCA has attracted very little attention. The aim of this study was introducing LCA and its application as well as assessment of sugar beet life cycle in different cropping systems in Iran. For this purpose the cradle to gate LCI was developed from 93 sugar beet farms grouped into mechanized, semi-mechanized and traditional cropping systems in the east of Iran. Field operations and agricultural machinery data were obtained from Ecoinvent [1] and adjusted to Iran condition before use. Modeling of mixed electricity production was carried out using Simapro 7.3.0. [2]. Different techniques were used to calculate field emissions [3]. Heavy metal emissions to water and soil were assessed by a simple annual input output balance by SALCA-heavy metal [4]. Phosphorous based emissions due to the application of fertilizers were calculated according to Prasuhn [5]. The dynamics of available nitrogen in the soil were modelled using SUNDIAL [6] and nitrous oxide emissions were estimated using an adapted IPCC method (4). Nitrogen oxides emissions and release of carbon dioxide after urea application were estimated from the emissions of N2O according to Nemecek and Kagi [7]. EPD, V 1.03 system of SEMC [8] used for LCIA. The results showed 489 kg CO2-equivalent, 83 mg CFC-11 -equivalent, 0.33 kg C2H4-equivalent, 2.2 kg SO2-equivalent, 0.64 kg PO43--equivalent, 7987 MJ-equivalent in global warming, ozone layer depletion, photochemical oxidation, acidification, eutrophication, non-renewable energy demand impacts categories per metric ton of sugar beets respectively. environmental impacts of all mechanized sugar beet farms in all impact categories was lower than the total average of different systems while these impacts was larger than average in 57 and 33 percent of traditional and semi-mechanized farms respectively. Contribution analysis showed that irrigation, direct emissions from field and production of chemical fertilizers had the highest contribution on environmental impacts of sugar beet farms and should be reviewed to improve environmental performance of sugar beet production in Iran. Results indicated that environmental impacts for one ton sugar beet production in Iran were between 2 and 40 times more than the Swiss condition. Use of LCA is hindered by the lack of LCI data on agricultural inputs in countries such as Iran. This study is an attempt to develop a comprehensive life cycle inventory and show its use on LCA of sugar beet production in Iran. These results also show the possibility of reducing environmental impacts to enhance both environmental and economical sustainability in Iranian sugar beet production system.

Reference:

1. Ecoinvent Centre, 2010. Ecoinvent data v1.3, Final reports ecoinvent 2006 No. 1–15, Swiss Centre for Life Cycle Inventories, Dübendorf, 2006, CD-ROM. 2. PRé Consultants, 2011. SimaPro Database Manual-Methods library. Available online at http://www.pre.nl. 3. Bazrgar, A. B., Soltani, A., Koocheki, A., Zeinali, E., and Ghaemi,A., 2011. Environmental emissions profile of different sugar beet cropping systems in East of Iran, African Journal of Agricultural Research Vol. 6(29), pp. 6246-6255 4. Nemecek, T., Erzinger, S., 2005. Modeling Representative life cycle inventories for Swiss arable crops. Int. J. LCA 10(1) 1-9 5. Prasuhan, V., 2006. Erfassung der PO4-Austrage fur die Okobilanzierung SALCA Phosphor. Agroscope Rekenholz Tanikon ART, 20p. Online at http://www.art.admin.ch/themen/00617/00744/index.html?lang=en. 6. Smith, J.U., Bradbury, N.J., Addiscott, T.M,. 1996. SUNDIAL: a PC-based system for simulating nitrogen dynamics in arable land. Agron. J. 88, 38–43. 7. Nemecek, T., Kagi, T., 2007. Life Cycle Inventories of Swiss and European Agricultural Production Systems. Final report ecoinvent V2.0 NO. 15a. Agroscope Reckenholz- Taenikon Research Station ART, Swiss Centre for Life Cycle Inventories, Zurich and Dubendorf, CH. 8. Swedish Environmental Management Council (SEMC), 2008. Introduction, intended uses and key programme elements for Environmental Product Declarations, EPD, available in: www.environdec.com.

ABSTRACT. Life Cycle Assessment (LCA) can provide critical insights during the design of a chemical to minimize its life cycle impacts. However, developing a life cycle inventory (LCI) of a chemical is time-consuming, while over 15,000 new chemicals are newly registered every day. Therefore, a method that enables a rapid analysis of life cycle environmental implications of a chemical at an early stage of its development when data is limited is needed. To bridge the data gap, we present here our work of estimating chemical’s life cycle inventory using machine learning techniques to based on its chemical structure.

The possibility of a using statistical model as an alternative approach to developing a complete LCI has been proved by some studies1. Here we extend the literature in two ways: (1) expanding the number of predictable flows in LCI and improved its accuracy using Artificial Neural Networks (ANNs); (2) targeting direct inputs rather than LCI or LCIA to minimize regional biases. ANNs is a nonlinearity regression model which has been applied in many areas. In this study, the model will be trained using existing chemical LCI data in the Ecoinvent database and corresponding chemical descriptors will be generated. First, we examine the feasibility of ANN in predicting elementary flows in chemical manufacturing using larger training datasets. Elementary flows in the training set may contain regional biases, distorting the input and output relationships inherent to the chemical structure. Therefore, second, we conduct a contribution analysis to identify significant intermediate flows in chemical manufacturing, and apply ANNs to predict the volume of such flows.

The results show strong correlations between chemical structures and LCI and/or LCIA results. For example, the model that predicts Cumulative Energy Demand (CED) has Median Relative Error (MRE) of about 30% on the test data set. More than 80% of the models have a MRE lower than 80%. However, to avoid the regional bias in predicting elementary flows, significant products (direct inputs to make a chemical) have been identified and a predictive model will be applied on those products at the next step. Uncertainty will also be incorporated into the model.

Using these techniques, LCIs and LCIAs of chemicals can be predicted using only the information on chemical structures, in the absence of any better quality data at hand. The techniques will be incorporated into the Chemical Life Cycle Collaborate (CLiCC) tool, which will be an online, open-access platform for rapid LCA of chemicals.

1. Wernet, Gregor, et al. "Bridging data gaps in environmental assessments: Modeling impacts of fine and basic chemical production." Green Chemistry11.11 (2009): 1826-1831.

ABSTRACT. LCA research and use in industry are growing[1]; however, a prevalent shortcoming of LCA is the practicability to inform decision makers in policy, industry and at the consumer level[2].

The objective of the Chemical Life Cycle Collaborative (CLiCC) is to use predictive tools to provide a full LCA when large data gaps are prohibitive to understanding the impact of a chemical. The CLiCC tool will be an open-access, rapid-response method for generating LCA results for chemicals. To improve the practicability, CLiCC is engaging potential users through an iterative communication process, and the tool will be pilot tested with CLiCC’s industry and regulatory collaborators.

The first step in improving the usability of the CLiCC tool was to identify the stakeholders. These include ten industry partners from upstream and downstream companies in various sectors, as well as US EPA and California DTSC[3]. A project launch workshop and interviews helped establish a list of the tool’s potential applications, each with a profile characterizing the user. This information is guiding development of CLiCC’s individual modules (inventory estimation, release, fate & transport) as well as the overall tool architecture. Quarterly updates and additional interviews have identified other areas for development, including stochastic representation of uncertainty and provision of supporting data sources for individual tool outputs. Early-stage pilot tests of individual modules are identifying methods to improve usability that otherwise may not have been discovered until the tool’s development was complete.

As LCA becomes a more mainstream decision-making tool, it is critical to develop methods to improve usability. The approach adopted by CLiCC reduces the distance between LCA developers and decision-makers. Presented here are current findings from CLiCC’s stakeholder engagement process and an outline of how this knowledge transfer guides the continual development of the CLiCC tool to improve its practicability.

Masanet, E.; Chang, Y. Who Cares About Life Cycle Assessment? Journal of Industrial Ecology 2014, V18, 787–791.

Zamagni, A.; Masoni, P.; Buttol, P.; Raggi, A.; Buonamici, R. Finding Life Cycle Assessment Research Direction with the Aid of Meta-Analysis. Journal of Industrial Ecology 2012, V16, S39-S52.

Department of Toxic Substance Control (DTSC)

ABSTRACT. Adequate quantitative uncertainty analysis in LCA is still an unresolved issue. However, the latest version of the Ecoinvent database v3.1 does not include quantitative uncertainty values at the LCI level due to the high computational power required.

We use Monte Carlo simulation (MCS) to quantify stochastic uncertainty of unit process data. While MCS does not need a complex mathematical framework, attributing uncertainty ranges to unit process data from the Ecoinvent v3.1 requires intensive computation and large memory space. This work solves the challenge of using MCS for LCI uncertainty propagation involving large-scale unit process data and intensive computational requirements. Our study shows that parallel programming with large memory can reduce the computation time by a factor of 1000.

After a sufficiently high number of simulations is completed, the output of the uncertainty analysis of LCI data is stored in the similar format as Ecoinvent v2 with stochastic values that describe the probability distribution generated by the MCS.

This development of an LCI database with quantitative uncertainty information can support LCA users to generate further uncertainty analysis on LCA and aid in making informed sustainable decisions.

ABSTRACT. This paper explores the possibility of Life Cycle Assessment (LCA) application as a tool supporting Strategic Environmental Assessment (SEA). Different scenarios of electricity generation structure according to Polish Energy Policy by 2030 were assessed and quantified (comparing the current energy generation structure with various approaches to diversification of the electricity generation structure such as increase use of renewable energy sources, introduction of nuclear energy). The environmental performance of these scenarios was compared using LCA, which takes into account direct and indirect environmental impact, i.e. from minerals extraction to waste management. Using a life cycle perspectives is important when comparing different energy generation structures, particularly in the case of Poland where the current structure of energy generation is based mainly on hard coal and brown coal (approx. 90%). To compare the total cradle-to-gate environmental impact the functional unit was defined as 1TJ of electricity generated, based on release of final energy from a power plant. The Impact2002+ v2.05 method was chosen, as it proposes a feasible implementation of a combined midpoint/damage category method, for example including both global warming (midpoint) and climate change (damage). The inventory data were collected from Polish statistics and the Ecoinvent database (v.2.2) The LCA results show that the highest environmental impact of electricity generation in Poland is related mainly with emission to the air reflected in global warming and respiratory inorganic impact categories. The significant decrease in global warming (more than 20% lower in comparison to reference scenario 2006) could be achieved in 2020 when coal will be replaced by renewable (19,3% in total structure) and nuclear energy (6,7%). Diversification in energy production can result in fulfilling the Polish obligation connected with the CQ2eq reduction per the Kyoto protocol. By introducing LCA it was proved that overall environmental impact of energy sector will be also reduced. It was found that LCA methodology can support the assessment of different scenarios presented in planning documents by determining ecological effects based on quantified impact.

ABSTRACT. Being a party to the Kyoto Protocol, Turkey is keen to reduce the GHG and other emissions. It is, therefore, important that Turkey identifies possible future electricity options, if climate change and other environmental impacts are to be curbed. This work focuses on electricity and considers 15 scenarios up to 2050 in Turkey including business as usual (BAU) and different carbon reduction targets scenarios to estimate the related life cycle environmental impacts. All life cycle stages are considered, including extraction, processing and transport of fuels and raw materials, plant construction, operation and decommissioning. 14 technologies are considered including fossil-fuel technologies with and without CCS, nuclear and a range of renewable options. For most technologies, future technological improvements have been taken into account, based on projections by various sources. The findings indicate that continuing with BAU would increase up to three times the current annual life cycle GHG emissions. Switching from the current mix to renewables (with a contribution up to 79%) and nuclear (up to 30%) would lead to a reduction of seven impacts such as acidification and eutrophication compared to the current situation. This is despite the fact that the electricity demand is assumed to increase four-fold, from the current 211 TWh to 852 TWh in 2050. The results indicate that per kWh of electricity generated, the electricity mixes assumed in all the scenarios are environmentally more sustainable than at present, including BAU; this is due to technology learning curves. The only exception to this is depletion of elements which increases up to four times on today’s value because of the need to build new plants. However, due to a large increase in demand over the years, the total impacts increase up to 70 times. Therefore, technological improvements on their own are not sufficient and must be coupled with reducing the demand for a more sustainable future electricity system in Turkey. This the first attempt at assessing the life cycle environmental impacts of future scenarios for Turkey aiming to inform on the impacts and the hotspots to help improve the environmental performance of the electricity sector in the future.

ABSTRACT. Life cycle assessment (LCA) is being used by policymakers to inform decision-making about the effects of greenhouse gas (GHG) emissions regulations, particularly regulations applied to transportation fuels. LCA can be a useful tool for comparing the environmental impacts of different products or processes. However, there is no mechanism within traditional LCA for capturing the indirect, market-mediated effects resulting from a policy change, a major criticism of the use of LCA as a policy tool. Computable general equilibrium (CGE) models have been used by economists to predict how different sectors in an economy will react when a policy is implemented. While several LCA examples exist that have utilized both CGE and LCA models to explore these indirect effects, a broader understanding of the role of these modeling approaches for GHG emissions policy analysis is lacking.

We compare LCA and CGE modeling approaches and their potential use by policymakers, paying particular attention to how they have been utilized and are expected to be applied in assessments of GHG emissions regulations. We present a case study of the oil sands, using an existing LCA model and an existing CGE model that have been developed to assess different carbon policy options and the impacts on different oil sands stakeholders. The oil sands provide a unique case in which to examine these model approaches outside of the typical U.S. or European bioenergy examples where these models have been most widely applied. This is the first application that employs CGE and LCA to a Canadian energy issue. The results from the oil sands case study are used to demonstrate how each of the approaches can be applied outside of the US and EU bioenergy discussion, and the types of insights that can be obtained from each of the modeling approaches. A discussion of the appropriate development and application of these tools follows that can provide policymakers with more information to better inform policy decisions.

ABSTRACT. Policy makers across the world are implementing increasingly stringent regulations in an attempt to curb the GHG emissions released by automobiles into our environment. Current legislation focuses almost exclusively on ‘tailpipe’ or use-phase emissions. There is a clear need for policy makers to account for emissions from other phases, because:

• Present regulations aren’t achieving the intended net GHG reductions • There is the very real possibility of unintended consequences, including higher overall emissions, problem-shifting, etc.

As part of our ongoing, long term commitment to Life Cycle Assessment, worldautosteel has partnered with the Technical University of Berlin to study modalities for including life cycle thinking in policy, particularly automotive emissions regulations.

The research study (2013-2015) includes the identification and prioritization of policy options, the description of its technical requirements and characteristics and the development of implementation scenarios. As an example CO2 legislation in the automotive industry is chosen, but the principal approach can be transferred to other environmental regulations and sectors as well.

In the 1st phase of the study promising policy options were identified without having indicated a clear analytical, scientific overall preference for one single option. We learned that technical implementation strongly depends on the implementation level and that solutions for most technical requirements are already available, but that a consensus on their proper setting is missing. In the 2nd phase the research process was continued including a broader stakeholder dialogue in Europe, the US, Japan and China. Now, in the 3rd phase, the feedback obtained is used for refining the policy options and specifying implementation scenarios for integrating LCA in policy.

ABSTRACT. The Sustainable Apparel Coalition (SAC) has conducted screening LCAs on the production of three classes of non-leather shoes: Sport, Leisure/Fashion, and Work/Waterproof. The identified environmental hotspots of these shoes will be used to inform European legislation around calculation of Product Environmental Footprints (PEFs) for shoes. The European Commission is crafting legislation [1] requiring LCA-based reporting for products across many sectors via the PEF program [2] and PEF guide [3]. Calculating these PEFs may become mandatory for doing business in Europe, so each affected industry is identifying hotspots within their product’s life cycle and creating PEF Category Rules (PEFCRs) to provide specific guidance for calculating and reporting a products’ life cycle environmental impacts, similar to a PCR being used for the creation of EPDs. This screening study identifies the most relevant life cycle stages, processes, impact categories, and data quality needs to derive the definition of benchmarks for comparison and any other major requirement to be part of the final PEFCR. The functional unit evaluated was one pair of non-leather shoes used for one year. Three shoe classes were sampled from eight brands, representing 14 specific shoes. Environmental hotspots were identified in life cycle phases raw material acquisition and manufacturing (separated between Tiers 1, 2, and 3). The impacts associated with raw material acquisition are affected by a combination of the shoe’s overall weight and its specific Bill of Materials (BOM), with the presence of leather as a key factor. Energy use is the main driver of impact in manufacturing, with location of manufacture also acting as a key factor. The contributions from transport, retail, use, and disposal are small, though the impacts of transportation are relevant for a few impact categories. This presentation will give an overview of the ongoing PEF process, describe hotspots in the life cycle of non-leather shoes, and explain how the results are being used in the creation of a PEFCR and benchmark classes. The PEF program drives requirements around legislation in Europe and affects the production of shoes world-wide, so understanding the life cycle impacts of shoes is of highest importance before standards for reporting and communication are finalized. [1]: 2013/179/EU: Commission Recommendation of 9 April 2013 on the use of common methods to measure and communicate the life cycle environmental performance of products and organisations [2]: Official Journal of the European Union; volume 56; PEF-OEF Methods; May 2013 [3]: PEF Guide 4.0; Guidance for the implementation of the EU PEF during the EF pilot phase - Version 4.0

ABSTRACT. The European Commission started a pilot to create a “Single Market for Green Products”, that aims at facilitating better information on the environmental performance of products and organisations. Currently, 27 pilots made of companies, industrial and stakeholder organisations in the EU are drafting respectively 25 Product Environmental Footprint Category Rules (PEFCR) and 2 Organisation Environmental Footprint Sector Rules (OEFSR). One of the pilot is drafting the OEFSR for the retail sector and is composed by six retailers: Carrefour SA, Colruyt Group, Oxylane Group (Decathlon), Picard, Kering, and Office Depot; three public agencies: Environment Agency Austria (EAA), French Environment and Energy Management Agency (ADEME) and Italian National agency for New Technologies, Energy and Sustainable Economic Development (ENEA); one non-governmental organization: Global 2000; one association PERIFEM; and one LCA consultant: Quantis. As of April 2015 an assessment of the impacts of an average retailer has been performed using the 15 impact categories required. A first OEFSR has been drafted and submitted for public consultation. The results of the assessment, the draft and its main methodological points (e.g., for direct, as well as upstream and downstream indirect contributions), as well as the benefits of this OEFSR for companies will be presented highlighting latest developments and feedback. These points also include the issue pertaining to consistency with the product approach for a sector as interdisciplinary as the retail sector. As an example of results, an average general retailer supplying products for 3’000’000 people can have a carbon footprint in the order of magnitude of 10’000’000 t CO2-eq per year, most of it being associated with the life cycle of its products sold. Interaction between OEFSRs and PEFCRs such as cross cutting issues and consistency will also be addressed. As an example of methodological agreement that has been reached among sectors is how allocation among meat, milk, pet food and leather should be performed among cattle co-products. Such type of agreement is key for a sector like the retail to be able to consistently perform its Environmental Footprint. One of the significant differences with traditional corporate footprint is that assessment and reporting for OEF goes beyond the traditional carbon footprint and includes impact categories such as water footprint, pressure on resources as well as impact on human health through environmental pollution. Pressure on biodiversity or deforestation throughout the supply chain is also included.

ABSTRACT. We analysed the environmental performance of passenger and freight air transport from 1990 to 2050 for five different plane size categories.

We developed a parameterised model of an airplane, including thrust requirements, passenger and freight capacity, operating empty mass, and flight stages including idling, ground maneuvering, landing, take-off and cruising. Aircraft material composition, fuel consumption and operating emissions are modeled based on the year of aircraft manufacture. Values from 1990 to 2015 are based on historical data from the European commercial aircraft fleet, while projections are used until 2050. We used our model to construct life cycle inventories for airplane travel with flight length, freight and seat load factor, landing and take-off cycle characteristics, aircraft lifetime, and year of aircraft manufacture as variable parameters. We assessed the comparative importance of each LCI input parameter with simplified sensitivity analysis.

Preliminary results indicate that airplane fuel consumption and exhaust emissions are strongly dependent on the year of aircraft manufacture; this parameter has rarely been included in LCA calculations. We also demonstrate the importance of user assumptions such as seat and freight capacity load factors. The separation of flight stages will allow the future addition of regionalised and altitude dependent impact methods for operation pollutant emissions.

Our model allows for more realistic and less uncertain inclusion of the per-passenger or -ton kilometer impacts of air transport. Parameterisation of important input variables will allow LCI database users to more accurately reflect their specific input conditions and help further the understanding of the environmental impacts of air travel. Finally, fleet analysis over time shows that the environmental impacts of aircraft travel are diminishing as aircraft technology develops, and gives an indication of what the impacts of future aircraft travel may look like.

This work was supported by the SCCER Mobility project (www.sccer-mobility.ch).

ABSTRACT. The Chemical Abstract Service (CAS) registry contains more than 96 million unique organic and inorganic chemical substances. New chemical are added to the registry at the rate of 15,000 per day.

LCA needs to respond to such rapid pace of new chemical discoveries, since the results of LCA studies are increasingly required by regulatory bodies. The California's Safer Consumer Product regulation, the EU REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) directive, and other chemical substance control regulations in part also require the information on life-cycle impacts of chemicals. Under the multi-disciplinary project Chemical Life-Cycle Collaborative (CLiCC; clicc.ucsb.edu), we created a partnership between industry, academia, and government to develop an open-access tool to rapidly evaluate life-cycle environmental impacts of chemicals.

The CLiCC tool allows assessing chemicals at an early stage of their development also when only limited information is available. The CLiCC tool uses techniques such as chemical process design simulation based on Feinberg's theorem, predictive toxicology models, multi-media fate-and-transport models, and use and end-of-life phase simulators to rapidly construct LCI data and characterization models of a chemical with uncertainty estimations. The analysis can be subsequently refined as additional data becomes available.A modular structure is employed, allowing the user to run single or more complex assessments according to their specific needs. The tool also makes use of cutting-edge information technologies such as semantic network and Resource Description Framework (RDF) techniques. These novel techniques allow an efficient storage of the resulting LCI and LCIA outputs to the database library allowing the open-access LCA database to organically grow.

Through the assessment of some preliminary results, we will discuss the relevance of the project to the research field of LCA, but also to the broader stakeholders’ base, which is contributing to its development. The CLiCC tool, in fact, allows chemical industries, consumer product manufacturers, researchers, and regulators to develop and access information on chemical life-cycle impacts and facilitate science and data-driven alternative assessment.

ABSTRACT. In LCA, practitioners commonly rely on large LCI databases to model background data in their studies. Such databases are complex systems, so a proven and reliable database can be a significant time-saver. However, the practitioner is still required to understand the background data and their influences on the study results. With the transition to version 3, the ecoinvent database, a large background LCI database, has changed both methodological approaches and carried out a significant data update at the same time. This parallel development can leave practitioners uncertain why results changed in datasets compared to previous versions. An analysis was carried out to assess the major causes of results changes. The presentation highlights the relevant changes in version 3 and explains their impacts on LCIA results throughout the database. Some, such as the global modeling of supply chains, have a significant effect on results, with supply chains now reflecting the impacts of global industrial distribution better, leading to a noticeable increase in impacts in parts of the database. System model changes, e.g. to a consequential model, can have drastic effects but are not mandatory, and beneficial for practitioners working with a consequential goal and scope. Data updates have significant effects on the results of studies, and are often the major source of differences, together with the globalized supply chains. Other changes, e.g. the introduction of consumption mixes (market datasets) have little to no effect on the overall results. As the database under analysis is one of the most commonly used databases, the findings will be of relevance to many LCA practitioners planning to or already working with the ecoinvent database in their daily work.

ABSTRACT. Although there is a wide variety of software available for preparation of LCA studies and computation of results, the community lacks a straightforward way to publish results that facilitates open-ended evaluation and interpretation. The traditional publication format for an LCA is a static technical report describing the model from a single point of view and (by necessity) containing a limited scope of analysis. If another researcher wishes to make use of the results to compare them against another study, or investigate the model’s sensitivity to input parameters, that researcher must hope that the required information is contained in the published report, or else painstakingly reconstruct the model.

Following a recent experience conducting a high-profile LCA study for a state agency, we were motivated to develop a mechanism that would permit the study audience to conduct independent scenario and sensitivity analysis of the results directly, without an interpretive step to reproduce the model. To do this we designed a web service that implements the core inventory and impact assessment computations, enabling data users to submit queries regarding the model structure and receive results in a machine-readable format for automated processing and integration. The tool supports parametric scenario development, sensitivity analysis, and contribution analysis at different hierarchical levels within the product system model. Data sets designated as private are withheld from direct scrutiny, but their contributions to category scores are still included.

The web service approach provides a provenance framework for LCA results, permitting users to trace results back to source data and perform independent validation and verification without the involvement of the study author. The product system model is also described precisely, filling a gap in existing LCA data serialization formats. Using the tool, study authors can present their models and results transparently while protecting confidential data. By providing a structured, interactive format for publishing and data sharing, the tool can foster the use of LCA for applications involving high levels of scrutiny and public review, such as public policy development.

ABSTRACT. Resource efficiency analysis of production processes is an important basis for the reduction of climate impacts and costs in the chemical industry. A large number of modeling and analysis techniques exist to guide the reduction of resource consumption and the assessment of related ecological and economic impacts.

The consortium project InReff (‘Integrated Resource Efficiency for Reducing Climate Impacts in the Chemical Industry’, founded by the German Federal Ministry of Education and Research, BMBF) strives to combine modeling and analysis techniques from different fields for a holistic view upon resource efficiency analyses. This includes material flow networks [1], life cycle analysis [2], flow sheet simulation [3], heat integration [4], material flow cost accounting [5], and mathematical optimization [6]. The approach is guided by a developed methodology and supported by an IT-based modeling platform [7]. Project partners from the chemical industry successfully applied parts of the framework on practical case studies; see e.g. [8, 9, and 10].

This paper’s focus is on the combination of heat integration analysis and material flow networks. Techniques for heat integration analysis, such as Pinch [4] or specialized optimization algorithms [e.g. 11], allow the identification of theoretical potentials and utilization of technical aspects (i.e. heat exchanger networks) to productively re-use heat surplus in production processes in order to reduce resource consumption and climate impacts.

Material flow networks are an appropriate tool for process modeling in a more descriptive form than typical heat stream tables. Furthermore, they enable ecological and economic impact assessment of alternative scenarios identified in heat integration analyses; taking into account the whole production process or product life cycle.

For an iterative, model-based improvement of resource efficiency, a seamless integration of the involved software tools is an important precondition. This contribution will present a conceptual and technical interface as well as specific modeling aids to couple material flow networks [12] with different exemplary tools for heat integration analysis [13, 14]. The applicability of the integrated analysis will be shown on the example of a demonstrative case study from the chemical industry.

Literature

[1] Möller A., Page B., Rolf A., Wohlgemuth V. (2001): Foundations and Applications of Computer Based Material Flow Networks for Environmental Management. In: Rautenstrauch, C., Patig, S., editors. Environmental Information Systems in Industry and Public Services. London: Idea Group, pp. 379–396.

[2] Baumann H., Tillman A.M. (2004): The Hitch Hiker’s Guide to LCA: An Orientation in Life Cycle Assessment Methodology and Application, Studentlitteratur AB, Lund (Sweden).

[3] Seider W.D., Seader J.D., Lewin D.R., Widagdo S.: Product and Process Design Principles: Synthesis, Analysis and Design. 3rd edition, John Wiley & Sons Inc., Hoboken, 2008.

[4] Kemp I.C. (2011): Pinch Analysis and Process Integration: A User Guide on Process Integration for the Efficient Use of Energy. Butterworth-Heinemann.

[5] Tachikawa H. (2014): Manual on Material Flow Cost Accounting ISO 14051. ISBN 978-92-833-2450-8, Asian Productivity Organization, Tokyo (Japan).

[6] Nickel S., Stein O., Waldmann K.-H. (2014): Operations Research. 2nd edition, Springer / Gabler, Berlin / Heidelberg, ISBN 978-3-642-54367-8.

[7] Viere, T. et al. (2014): Integrated Resource Efficiency Analysis for Reducing Climate Impacts in the Chemical Industry. In: Journal of Business Chemistry, June 2014. http://www.businesschemistry. org/article/?article=192, last visit 2015-4-30.

[8] Denz N., Ausberg L., Bruns M., Viere T. (2014): Supporting resource efficiency in chemical industries - IT-based integration of flow sheet simulation and material flow analysis. Proceedings of the 21st CIRP Conference on Life Cycle Engineer-ing, Trondheim (Norway), June.

[9] Zschieschang E., Lambrecht H., Denz N., Viere T. (2014): Resource efficiency-oriented optimization of material flow networks in chemical process engineering, in: Proceedings of the 21st CIRP Conference on Life Cycle Engineering, Trond-heim (Norway), June.

[11] Brandt C., Fieg G., Luo X., Liu X. (2011): Improving genetic algorithms for the synthesis of heat exchanger networks. World Congress on Engineering and Technology (CET), Shanghai.

[12] http://www.umberto.de/en, last visit 2015-4-30.

[13] http://pinch-analyse.ch/index.php/en, last visit 2015-4-30.

[14] http://www.xrg-simulation.de/en/products/xrg-applications/synthex, last visit 2015-4-30.

ABSTRACT. Every consumer product has the potential to expose humans to chemical ingredients during use, via multiple exposure pathways. However, many product oriented exposure assessment accounts mostly for indirect environmental exposure and not direct exposure of consumer to product during use. We therefore aim to a) Identify the most efficient interface between LCI and LCIA for the use and disposal stage of consumer products, b) determine the chemical concentration in product as an LCI input, c) define and calculate the Product Intake Fraction (PiF), a metric that accounts for near field exposure in LCA:, d) demonstrate the framework and models through examples from various consumer products. We propose to first determine the mass of chemical in product per functional unit (FU) as inventory flow and point of departure to then calculate intake and impact. This inventory flow is the amount of product used per FU multiplied by the chemical content in product. This content is either based on measured data, derived from household product databases, or determined based on chemical -product specific function and frame formulations. Intakes are then determined using the product intake fractions - the fraction of the chemical in product that is taken in via each exposure pathway, considering the specific point of entry (cosmetics, chemical in article, indoor air, etc.). We propose a new near & far field multi-media matrix of transfer fractions, with one column and row for each point of entry, for each environmental compartment and for each exposure pathway. The multiple transfer and product intake fraction (e.g from chemical in article to inhalation of indoor air) is obtained by inverting the transfer fraction matrix, yielding the infinite multi-media transfer fractions. Product intake fraction range from 10e-7 for an SVOC in a thick flooring, to 5e-3 for an indoor air emission up to 96% for a leave-on cosmetic ingredient.

ABSTRACT. It has been estimated that there are thousands of chemicals used in personal care products (PCPs) and human exposure to these chemicals can be dominated by the use stage. Within chemically mediated human health (HH) life cycle impact assessment (LCIA), focus has historically been on far-field environmentally mediated exposures with less focus on exposure occurring in the near-field (e.g. in the indoor environment) during the product use stage. We used the concept of the product intake fraction (PiF) [1] to estimate near- and far-field exposure factors associated with chemicals in PCPs. We combine these with effect factors available in USEtox [2] to calculate characterization factors (CFs) for a subset of PCP chemicals and compare them to CFs associated with far-field emissions.

The PiF can be used to quantify the amount of chemical taken in per mass of chemical used in a PCP and can be combined with product composition to estimate chemical intake due to product use. The use-stage PiF for PCPs was estimated using mass balance modeling with physicochemical properties and product usage characteristics (e.g., leave-on or wash-off) as data inputs for dermal aqueous uptake, gaseous dermal exposure, and inhalation. Disposal stage PiFs were estimated by combining the fraction of chemical washed down the drain after product use and USEtox calculated far-field intake fractions. Additionally, to understand which physicochemical properties drive use-stage exposure, we calculated PiFs for a range of properties.

Varying physicochemical properties indicates the PiF is dominated by dermal aqueous uptake when a chemical has a relatively large Kow (octanol-air partition coefficient) combined with a relatively small Kaw (air-water partition coefficient). Furthermore, use-stage PiFs were 4-100% and 0.001-100% for leave-on and wash-off products, respectively, indicating a variability of about five orders of magnitude across PCP chemicals. Disposal-stage PiFs were 0-0.3% and in general were several orders of magnitude smaller than use-stage PiFs, however, some chemicals had comparable use- and disposal- stage PiFs. CFs for PCP use thus may have substantially different ranking compared to CFs for far-field releases and may dominate overall impact scores.

1. Jolliet et al., 2015, Environmental Science & Technology, Submitted. 2. http://www.usetox.org/

ABSTRACT. MAMTech (Macro-level Technology Assessment Model) is a modeling framework integrating chemical process design and modeling, life cycle assessment and techno-economic analysis for assessing the net energy and emissions implications of technology changes in the U.S. chemical production from a life cycle perspective. This assessment is critical because it can provide policy makers with good references on future investment and technology promotion, provide manufacturers and researchers with better understanding on technology potentials, possible bottlenecks and directions for future improvements. However, the assessment of new technology is challenging for lack of process data, general evaluation approach across different products and robust methodology over the temporal scale[1]. MAMTech is designed to overcome these barriers.

In this work, MAMTech is used to evaluate the macro-level life cycle energy and GHG emissions of several emerging technologies for ethylene production; in order to (1) demonstrate the function of MAMTech; (2) provide prospective insights on the energy and emissions reduction potentials of different technologies for ethylene production in future decades. Ethylene is chosen because it is one of the largest energy consumer and GHG emissions resources in chemical industry. According to IEA’s analysis, ethylene accounts 13% of global energy consumption and 15% of GHG emissions[2, 3].

Based on the preliminary results, 100-150 million GJ/year of energy consumption can be saved in the U.S. ethylene production life cycle under a high feedstock supply scenario through a new catalysis-based technology for steam cracker. This reduction of energy consumption mitigates 7-18 million ton of CO2-e/year. The ranges given here are based on results of Monto Carlo simulation considering uncertainties and system variances. Regarding the emerging technology that is not for improving current process but an alternative production pathway, MAMTech is able to overcome the knowledge barriers and provide a credible assessment by integrated modules of life cycle assessment and chemical process design. The results of different technologies are later compared together at different scenarios.

The results can shed the light on technology opportunities with the largest reduction potentials of energy and GHG emissions at a foreseeable time frame. The modeling framework itself is an effective tool assisting policy making, environmental and energy analysis, and R&D.

References [1] EIA. (01/02). The National Energy Modeling System: An Overview Available: http://www.eia.gov/oiaf/aeo/overview/ [2] Y. Yao, D. Graziano, M. Riddle, J. Cresko, and E. Masanet, "Greener pathways for energy-intensive commodity chemicals: opportunities and challenges," Current Opinion in Chemical Engineering, vol. 6, pp. 90-98, 11// 2014. [3] IEA, ICCA, and DECHEMA, "Technology Roadmap, Energy and GHG Reductions in the Chemical Industry via Catalytic Process," IEA, ICCA, DECHEMA, France2013.

ABSTRACT. Coatings provide both protection and aesthetic appeal. Just a thin layer of paint can extend the useful life of everyday objects and thus avoid the environmental burden that would come with an early replacement. Consequently, the sustainability of coatings should be assessed over the entire product life cycle in order to adequately capture the impact of coatings performance in a given application.

Coatings are formulated products, i.e. they are made from a blend of ingredients such as resins, pigments, filler, and additives. Choosing the right ingredients is essential to achieving the desired product specifications in commonly used performance metrics such as opacity, hiding power, washability, scrub resistance etc. With their embedded environmental footprint, ingredients also influence the environmental impact profile of coatings. Life Cycle Assessment (LCA) forms a solid basis for holistic formulation choices, where ingredients are not judged in isolation, but in consideration of their impact on the performance throughout the life cycle of the ultimate article [1].

In this work, a novel formulation tool will be demonstrated that integrates LCA with a predictive model of coatings performance for flat and low sheen interior wall paints. The LCA approach mimics the definitions and assumptions of the CEPE Eco footprint tool [2], which is widely used in the coatings industry. In accordance with the emerging guidelines for the product environmental footprinting of paint, the functional unit for fair comparisons addresses the key aspects of how much surface is coated by a certain quality of paint for how long. Paint properties are estimated with a mixture design model that is calibrated with comprehensive laboratory test data.

This integrated formulation tool drastically reduces the experimental effort to develop new paints. It effectively guides the formulator towards the blend of paint ingredients that delivers the right performance at the lowest overall cradle to grave environmental footprint. As an example, we compared two formulations for the same type of flat interior wall paint across the full range of environmental indicators defined in the CEPE Eco footprint tool [3]. One formulation uses universal TiO2 pigments designed for diverse paint applications, whereas the other uses TiO2 pigments specially developed for this application. Experimentally validated and externally peer reviewed results show that both paints meet the same quality requirements, but the paint with the specialized pigment enables reductions in the cradle-to-grave environmental footprint on the order of 20% across the board.

ABSTRACT. With the well-established criteria of cost, quality, delivery, and innovation for product and process design, elevation of the business case for sustainability can be a constant challenge for organizations. Life cycle inventory (LCI) may be a powerful tool to add a sustainability lens to an organization that uncovers triple bottom line (people, planet, profit) opportunity, adding value to criteria the business already prioritizes. At Kohler the term LCI is employed and not Life Cycle Assessment (LCA). An inventory of resource use and resulting emissions associated with products is more compatible with the language of business than the effect of this inventory on the environment. Kohler Co. began building product LCI models with unit operations detail in 2011. These models have provided justification for product and process improvement projects that in turn benefit next-generation LCI model results. This iterative process has grown organizational acceptance of LCI as a value-added tool and sustainable design as a necessary competency. With this presentation, the process of building a value-added LCI model will be briefly described, with emphasis on the steps necessary to include detail that allows for an actionable model. This will be followed with a demonstration of results within each life cycle stage for an example product. With each stage, the audience will be engaged via a text message-based polling application to offer opinions on the best opportunities to improve product and process sustainability. The real-time poll results will be followed with an explanation of how Kohler Co. interpreted the results and justified design changes. Kohler Co. recognizes that visibility of these LCI-inspired projects within the organization is critical to broader acceptance of this tool. Together with the individual projects that resulted from this effort, the methods by which Kohler communicates this story- both internally and externally- will be presented. To conclude, the effect of these changes on the overall product life cycle will be demonstrated with an updated LCI model. Remaining time in this session will again engage the audience for their own questions and comments on this process. Product and material samples will be used as visual aids.

ABSTRACT. GE believes that a flexible and customized approach to incorporating sustainability across its different business units is necessary in order to identify important innovation and value creation opportunities. As such, the Ecoassessment Center of Excellence (COE) has developed and applied a variety of life cycle tools and resources, including everything from qualitative assessments to basic screening to detailed life cycle assessment (LCA), which can be tailored for specific product or business applications to drive meaningful outcomes and enhance our leadership position. Over the past several years, GE’s Ecoassessment COE has applied these life cycle approaches to a variety of GE products and processes including gas and steam turbines, aircraft engine components, wind turbines, medical equipment, lighting, additive manufacturing, biopharmaceutical manufacturing, healthcare consumables packaging, thin film solar, aeroderivative gas engines, Jenbacher gas engines, micro LNG, smart meters, membrane ultrafiltration systems for water treatment, Durathon™ energy storage systems, appliances and appliances recycling, locomotives, biomass gasification, advanced metallurgy, jet fuel from bio-oils, and component remanufacturing.

These efforts have provided us with the opportunity to engage with a broad array of internal stakeholders, play a variety of roles, and understand a range of unique business needs. Accordingly, a key goal of the Ecoassessment COE’s engagement approach is to create value through better products, better value proposition for the customer, better competitive positioning, better line of sight to environmental issues and opportunities, better positioning with respect to regulatory trends, enhanced brand image, and more. The value proposition may be different for different business units, different product categories, customer segments, or market regions. This presentation will provide highlights of the strategies, tools, best practices, and accounts of our experiences for successful internal engagement within a large, diverse company.

ABSTRACT. This presentation will share the story of life cycle thinking and the evolution of the life cycle assessment (LCA) team at Eastman. At Eastman Chemical Company, we are constantly seeking new solutions to address complicated challenges in the world. As a leading specialty chemical company, we are at the cutting edge of innovative chemicals and technology development. Through the lens of innovation LCA and sustainability can be seen as key drivers for the evolution of the company’s offerings. Eastman’s experience with LCA’s began in 2008 when customer requests required completion of a large number of cradle-to-gate LCA studies. Now the initial investment is paying off, and the LCA team and life cycle thinking have become integrated into innovation at Eastman. Our LCA team made a switch from compliance to proactive innovation about a year ago, and we are currently executing our strategy. This shift in focus required directed effort on the part of the LCA team, and we devoted many meetings to determine who we are as a team and how LCA can create value for our company. Goals and actions which arose from our strategy development include

1. Identifying key stakeholders in the company 2. Developing and delivering presentations for internal and external audiences 3. Inviting external speakers to provide additional valuable perspectives 4. Creating a website and video clips about LCA to be shared internally and externally 5. Developing and following best practices for completion, documentation and communication of LCA studies Because of diligent networking and education, various key groups like business organizations, marketing managers, researchers, regulatory affairs and procurement arms of Eastman now understand life cycle assessment and have begun to apply it in their organizations. LCA studies inform product portfolio assessments that enable intelligent strategic decisions for new realities in a changing world. To support innovation the LCA team performs screening assessments to delineate potential advantages or shortcomings of product and technology concepts from a sustainability and energy efficiency perspective. Case examples will be shared in this presentation.

ABSTRACT. The City of Beaumont, Texas carbon footprint described by this paper will be used by city government officials as part of an effort to reduce operating costs consistent with lower operating budget needs. This is a screening footprint that will attempt to capture major contributors based on results of other city footprints and established protocols.

System boundaries for city footprints can be defined with the city government’s infrastructure as the focus, or more holistically to gain an understanding of the population and what impacts are important to the public. While the larger focus is more broadly appealing, the narrower focus (e.g., that specified by C40 for Carbon Disclosure Project reporting) is more in keeping with the business needs of a city and was the approach selected for this study.

The city has eliminated curb-side recycling as a cost reduction, while larger cities have been adding this. Results show how current impacts related to waste management would compare to those for recycling. The city operates a propane-fueled bus system but ridership is very low. Results show impacts from transportation and user ridership data to compare to conventional programs elsewhere. Building operation data (e.g., utility use) is compared to other cities to show whether other cities that have invested in improvements are getting those benefits.

One unique issue that has been investigated makes the presentation of these results especially interesting. Most carbon footprints do not consider the impacts of traffic idle time. This study includes data on traffic idling where a major road repair at a river bridge impacts traffic on a heavily congested east-west interstate highway that runs right past its downtown area. Traffic back-ups occur each afternoon for east-bound travelers and they last for many hours, bringing thousands of cars and cargo trucks to a stop or crawl. Impacts from traffic idling and low speed travel are compared to other aspects of city operations to gain better perspective on this anomaly. A portion of city workers use this bridge as part of their daily commute home from work. Possible mitigating actions are recommended. Idling impacts have not been shared elsewhere.

ABSTRACT. Food waste and yard trimmings accounted for 29.8% of municipal solids waste (MSW) discards in the United States in 2012, with just 4.8% of food waste recovered from disposal.[1] While source reduction and food donation are the preferred food waste management options, anaerobic digestion is an emerging management strategy that cities will likely employ as they pursue organics landfill diversion targets and requirements, such as Massachusetts’ recent commercial food waste disposal ban. The authors are working with the U.S. EPA to develop life-cycle energy and greenhouse gas (GHG) emission factors for anaerobic digestion of organics in EPA’s Waste Reduction Model (WARM).

WARM was developed to help solid waste planners and organizations track and voluntarily report GHG emissions reductions from several different waste management practices. The authors are developing an approach for modeling anaerobic digestion in WARM based on a literature review, stakeholder interviews, and adaptation of an existing model developed at North Carolina State University.[2] Anaerobic digestion produces two potentially valuable coproducts: biogas and digested liquids and solids (digestate). The boundaries of the anaerobic digestion energy and GHG emission factors in WARM will include all gate-to-gate processes at the digester and cradle-to-grave impacts from beneficial use and disposal of coproducts. The modeling approach addresses the effect of technology type and feedstock composition on coproducts yield, impacts from co-digestion at wastewater treatment plants, and impacts from different options for utilizing generated biogas and digestate.

Preliminary estimates indicate that the digester technology modeled is likely to have a minor impact on life-cycle emissions, while beneficial use and management of biogas and digestate is expected to have a larger impact on life-cycle energy and emissions. The authors are currently evaluating impacts from synthetic fertilizer use avoided by land application of digestate and electricity and heat generation from biogas. Previous studies have found that total GHG emissions from anaerobic digestion ranging from -47 to 29 kg CO2e/ww Mg of household organic waste.[3] The large values and ranges for these values indicate that further research is needed to identify potential life-cycle emissions from U.S. anaerobic digestion facilities.

The development of national average factors for anaerobic digestion in WARM will provide insight into the environmental impacts of organics diversion and beneficial use of coproducts. These emission factors will provide waste managers and policy-makers with a more complete perspective on the life-cycle impacts from different material management options.

[1] U.S. EPA. 2014. “Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and Figures for 2012.” United States Environmental Protection Agency. EPA-530-F-14-001. Retrieved from: http://www.epa.gov/solidwaste/nonhaz/municipal/pubs/2012_msw_fs.pdf. [2] Levis, J.W. & M.A. Barlaz. 2013. Anaerobic Digestion Process Model Documentation. Retrieved from: http://www4.ncsu.edu/~jwlevis/AD.pdf. Accessed: April 30, 2015. [3] Møller, J., A. Boldrin, and T.H. Christensen. 2009. Anaerobic digestion and digestate use: accounting of greenhouse gases and global warming contribution. Waste Management & Research: The Journal of the International Solid Wastes and Public Cleansing Association, ISWA, 27(8), 813–24. doi:10.1177/0734242X09344876

ABSTRACT. The recycling of materials is one essential part of today’s strategies to cover future commodity needs. For this resource-conserving approach new recycling treatments are developed constantly. New recycling ways need to be evaluated, to verify their economic and environmental benefit in comparison to the primary production. Due to the laboratory scale and the linked uncertainties, methods are crucial which enable a sound comparison of diverse material provision options.

Within the presented project, which was funded by the Gips-Schüle foundation, the recycling of electronic scrap was tested. An innovative approach named electrodynamic fragmentation was enhanced by Fraunhofer Institute for Building Physics (IBP) to that effect. Besides the process adaption, a further emphasize of the study was the identification of target materials in electronic scrap and the evaluation of their recovery potential from an environmental perspective. The ecological benefit was quantified by life cycle assessment (lca). Thereby one main methodical challenge consisted of the creation of comparability of diverse commodity sources. A generalization of the value chain of recycling was necessary as well as a survey of the requirements the secondary material has to meet to be comparable.

The presentation focuses on the methodical approaches to achieve comparability for commodity sources. The identified value chain of recycling and the linked quality gates are illustrated as well as exemplary environmental potentials of the recovery of target materials.

For the future provision of industry and society with crucial materials, recycling seems to be the logical consequence. In order to choose recycling procedures with the highest environmental benefit, a broad basis of information is needed and realistic comparability of data is vital. The presented study provides the methodical approach to achieve comparability and delivers insights in the environmental recycling potential of some target commodities. The study enables decision makers in politics and industry to justify their recycling decisions.

ABSTRACT. The recycling of material resources lies at the heart of the industrial ecology metaphor. The very notion of the industrial ecosystem is motivated by the idea that we should learn from natural ecosystems how to ‘close the loop’. Recycling is not just central to industrial ecology (IE), it is part of everyday life. Yet, while virtually no one questions the environmental rationale behind recycling, accurately quantifying its environmental benefits is not a trivial problem. Part of this issue are four common misconceptions about recycling that may lead to misguided actions and policies and could thus undermine recycling’s environmental potential. They are: 1) Recycling material multiple times is better than once, 2) Closed-loop recycling is better than open-loop recycling, 3) Given its inherent properties are unchanged, recycled material displaces primary material one to one, and 4) The distinction between closed and open loops is useful. This talk will explain why those four assertions are flawed, discuss the implications, and present an alternative set of principles to better harness the potential environmental benefits of closing material loops.

ABSTRACT. ECOBASE, is a public commissioned study which major goal is to provide the methodology, database and calculator for the development of the national life cycle inventories (LCI) for the food and construction sector in Chile. The following paper addresses the latter.

Following the global trend towards sustainable construction, the Chilean building industry has developed, in recent years, national building design standards for improving the environmental performance of buildings using objective criteria and third-party verification. However, while the operational energy and GHG emissions from buildings have become progressively studied, resource use assessments in the building supply chain are incipient. In this context, the National Sustainable Construction Secretariat commissioned the ECOBASE Construccion project which main goal is to elaborate a national environmental life cycle database for construction materials. In the future, these emerging inventories should allow for a more holistic environmental assessment of different building systems.

This study describes the process of developing the LCI for the five most used building product categories in the Chilean market: Concrete, Steel, Claybrick, Wood and Gypsum Plasterboard. LCI is done using both direct data from primary sources in the production processes; secondary data, from existing databases and general bibliography, which in conjunction enable the calculation of official national averages for the Chilean industry.

The database considers disaggregated LCI flows and the environmental impacts of each profile, for six midpoint impact categories: Global warming, respiratory effects, water scarcity index, mineral depletion, fossil fuel depletion and photo-chemical smog. These priority categories where defined through a stakeholder participation process with project principals and relevant actors of the construction industry in Chile. In addition, the basic flows that contribute to several of these categories are available through a public data base of emissions and pollutant registration administered by Ministry of the Environment (RETC) that includes information on the emissions to air and water, and the hazardous waste transported to treatment or final disposal of several national companies.

The final product of this project involves the implementation of an open access LCA calculator for non LCA-experts, empowering industry stakeholders- from government, companies and academia-with the capacity to incorporate LCA data into their management process. This is the first tool of its kind developed for non expert users in the construction industry to use LCA tools and data, thus it contributes to bridging the gap between scientific LCA knowledge and the general audience.

The following paper informs the LCI methodology used for this project, the data collection process, the calculation of the LCIA for sixteen products within the five product categories and the description of the LCA calculator for non LCA-experts.

ABSTRACT. The International Institute of Synthetic Rubber Producers (IISRP) wanted to conduct an industry average LCA study on four synthetic rubber products in order to help members identify the environmental impacts of their products and respond to customer inquiries. Across the globe, environmental information has been requested of member organizations by their customers on a more frequent basis.

This presentation will describe the process used to conduct this industry wide LCA study and an overview of the results. PRé conducted LCAs for four types of synthetic rubber for IISRP including Polybutadiene (BR) rubber, styrene-butadiene rubber (S-SBR), emulsion styrene-butadiene rubber (E-SBR) and styrene-butadiene styrene (SBS) rubber. PRé worked with participating companies to gather data on material and energy inputs and the associated emissions to the environment throughout the upstream supply chain of the products being studied. Data was supplied from 18 companies at 38 facilities across three geographic regions (North America, Europe, and Asia). The system boundaries of this project are “cradle to gate”, which includes raw materials and manufacturing, and excludes distribution to customers, use, and end of life.

Four metrics were analyzed including total energy demand, climate change, eutrophication and acidification. Four full life cycle assessment reports were created on the production weighted average product, which identify key drivers of environmental impacts for each of the four products.

Impact category Unit Elastomer A Elastomer B Elastomer C Elastomer D Total energy demand MJ 88.2 92.9 97.9 96.8 Climate change kg CO2 eq 2.54 3.13 3.66 3.70 Eutrophication kg N eq 1.79E-04 2.13E-04 2.18E-04 2.41E-04 Acidification kg SO2 eq 0.0082 0.0095 0.0106 0.0107

This project not only created an industry average life cycle assessment for four products, but also allowed companies to respond to customer requests for LCA data through the creation of data communication sheets containing life cycle inventories and emission factors for each product. This study provided insight into the main drivers of environmental impacts in the synthetic rubber supply chain based on an industry average product and how individual companies perform compared to other participants in the study.

ABSTRACT. The International Zinc Association (IZA) recently completed its life cycle assessment (LCA) for zinc concentrate and special high grade zinc. This global LCA includes primary data from 24 mines and 18 smelters, which cover 4.9 million metric tons of zinc concentrate and 3.4 million tons of special high-grade zinc, respectively. Collectively, the data and associated model account for the relevant production processes, including zinc ore mining and concentration, transportation of the zinc concentrate, and zinc concentrate smelting. This data was modeled in GaBi 6 and complemented with background data from the GaBi databases to create the cradle-to-gate LCA model.

This presentation will review the process by which the LCA model was created, the results from the study, and the challenges related to allocation and data gaps. In particular, allocation demands associated with different impact categories required resolution using innovative modeling techniques. Recommendations and lessons learned from this study will provide LCA practitioners insight into how to conduct large-scale, global LCAs and how to deal with the complex issues that arise in these projects.

ABSTRACT. The UNEP Shonan Guidance Principles are one important result of an international “Pellston” workshop held in 2011 in Shonan village near Tokyo, where about 50 well-known, experienced LCA scientists and practitioners agreed on interoperability and management principles for LCI databases. Aim of a recent project by SETAC and UNEP was to develop criteria that allow assessing the conformance of LCI databases with these Shonan Principles.

The criteria are now available in a draft mode, on a database and data set level, for system and unit process data sets. Some of the criteria are only informative, while others are seen as essential for Shonan-conformity. For these, there are minimum scores for Shonan conformity proposed. These criteria have been applied on four relevant European databases, for randomly selected data sets in these databases.

The criteria will be presented and their application will be demonstrated. The application shows that some of the criteria are surprisingly hard to meet by different databases, although they are reflecting the Shonan report and the broad, worldwide consensus reached therein. Problems arise often from very practical aspects that seem relatively easy to change.

In a conclusion, it will be shown how the criteria help to identify potential interoperability issues in databases, and thereby are one step towards better interoperable LCA databases. A potential future use and refinement will be discussed.

ABSTRACT. Shale gas and oil production is on the rise in the United States. While the increase in shale gas production is reducing the overall greenhouse gas emissions of the United States, because it is replacing coal usage, shale gas production is a water and energy intensive process.

This study estimates the life cycle water consumption and wastewater generation, and the life cycle greenhouse gas emissions from the production of Barnett shale gas in Texas. This life cycle assessment is done for a shale gas well from its construction to the end of life. The data for the Barnett wells is collected from literature review and publicly available natural gas extraction inventories. Similar studies have been done for the Marcellus shale play but there is little information available for the Barnett shale play. This data will be used to create a life cycle inventory for shale gas production using SimaPro software. The life cycle direct water quality pollution impacts will be assessed using the Environmental Protection Agency’s tool for the reduction and assessment of chemicals and other environmental impacts (TRACI). The water consumption index will be calculated using the Water Footprint - Hoekstra et al 2012 water scarcity method. Global warming potential will also be quantified using the TRACI model.

Our results will be reported as GHG emissions in kgCO2eq/MWh and water consumption in gal/MWh. Based on the results and life cycle assessments, wastewater treatment costs and management options will be proposed. The results will also provide a thorough understanding of the water consumption and greenhouse gas emissions from shale gas production in the Barnett shale play. These outcomes will help to estimate the impacts of the rapid growth in shale production on water availability in Texas. In addition, our results will inform discussions on the contribution of shale gas to greenhouse gas emissions reductions in the US.

ABSTRACT. In the light of local water scarcity concerns in regions across the world, it is important to understand the dynamics of regional water supply and demand. Water stress indices (WSIs) have been developed as quantitative indicators of water scarcity in different areas – they are typically estimated as a function of the water use and availability in any region. Application of these indices helps us understand water supply and demand risks for multiple users, including those in the agricultural, industrial, residential and commercial sectors. Previous studies have developed methodologies to calculate WSIs that were used to estimate characterization factors (CFs), in order to quantify environmental impacts of freshwater consumption within a life cycle assessment (LCA) framework. In these studies, global WSIs were based on data from publicly available databases and have been reported as annual averages for multiple watersheds. The resolutions used in these literature studies typically do not effectively differentiate between seasonal and permanent water scarcity. A recent study1 improves upon the temporal and spatial resolution of the water scarcity calculations used to estimate WSIs, and offers a more robust framework for risk assessment, with a case study focused on the Mississippi river basin. A physical hydrological model, the Soil and Water Assessment Tool (SWAT), was used to simulate water supply in the Mississippi river basin with high spatial and temporal resolution. The basin was divided into about 450 sub-basins for which water availability was simulated and aggregated to monthly and annual timescales time-scales. Input data to SWAT included weather, land use and soil characteristics, all from publicly available global data sets. The hydrological model was calibrated against observed monthly river discharge within sub-basins, and compared against observed evapotranspiration, with improved results compared to global models. The calibrated results were used to estimate monthly- and annually-averaged WSIs for the sub-basins. The results from this study suggest that global models previously used to estimate WSIs may not be able to rigorously capture spatial and temporal variability at the sub-basin scale. These uncertainties may have implications for LCAs that account for water impacts of supply chains at regional or global scales.

References [1] Scherer et al, Large-Scale Hydrological Modeling for Calculating Water Stress Indices: Implications of Improved Spatiotemporal Resolution, Surface-Groundwater Differentiation, and Uncertainty Characterization, Environmental Science & Technology, 2015

ABSTRACT. The need for consensus-developed and recommended methods for water use impact assessment is clear in order to perform a water scarcity footprint consistently with ISO 14046:2014 and the challenge was undertaken by the WULCA working group, of the UNEP-SETAC Life Cycle Initiative. Including method developers and experts from different fields, the group is developing consensus-based indicators to assess impacts from water use, complying with the requirements of the ISO document. This work presents the results of the working group on the consensus method development. The work was divided in 6 parts:1) Identification of the question that the indicator should answer, 2) Identification of the modelling choices and possible options, 3) Consensus findings on each of these modelling choices, 4) Building of the resulting indicator(s), 5) Testing of the resulting indicator(s) and 6) Final recommendation. In order to answer these questions, a series of three expert workshops were held on three different continents: in Zurich (Switzerland), San Francisco (USA) and Tsukuba (Japan), with a total of 48 experts participating. The group agreed that the indicator chosen should answer the following question: “What is the potential of depriving another user of water in this region?”, independently of whether the user is human or ecosystem. Consensus finding of these modelling choices led to three possible indicators: 1) Demand-to-Availability ratio (DTA), 2) DTA*(Area/Availability)0.34 and 3) UWworld/UW (with UW referring to unused water, availability minus demand). Following a first testing phase and criteria analysis, a preliminary recommendation is made for the latter of these indicators. It is agreed that the final result will consist of a single metric covering the entire globe, modelled at various temporal and spatial scales for application in LCA with different inventory datasets. The group is proposing the result of its work and new consensus-based indicator with the hope that it will be adopted widely and hence decrease disparity and confusion when it comes to applying the new ISO standard on water footprinting, by providing an internationally approved, robust and simple indicator for assessment of potential impacts from water consumption.

ABSTRACT. Water scarcity has led to increased efforts to reduce residential water consumption. One measure is in-building wastewater treatment and reuse of water for toilet flushing and cooling towers. This raises two questions: what are the life-cycle environmental impacts of in-building wastewater treatment and reuse and their major contributors in an urban setting and how do on-site treatment systems compare to a centralized municipal system.

In this study, the life-cycle energy consumption and air emissions of water consumed daily in a residential green high-rise building in the Northeastern US with and without on-site wastewater treatment and in-building reuse were assessed by the Water-Energy Sustainability Tool (WEST) and the Wastewater-Energy Sustainability Tool (WWEST). Developed at the University of California at Berkeley, WEST and WWEST combine process-based and input-output based life-cycle assessment of the water supply and wastewater infrastructure and their operation.

Due to diseconomies of scale, the life-cycle energy consumption and release of greenhouse gas emissions of the on-site wastewater treatment facility exceeded those of the centralized system. Life-cycle energy and greenhouse gas savings from replacing potable water with reuse water were not enough to offset the increased energy and greenhouse gas emissions of the on-site wastewater treatment system. The contribution of potable water treatment and supply was not significant in the life-cycle for either scenario. The largest contributor to the impacts for both scenarios was the energy consumed during the operational phase while the impact of the construction phase varied. For the centralized scenario, the construction phase performed within the same order of magnitude as the operational phase, suggesting that its impact may be overlooked. For the on-site reuse scenario, construction was less significant, which is a potential benefit for on-site reuse if the operational energy consumption can be decreased. The neighborhood scale and the effect of the region other than the Northeastern US are still being assessed. A limitation of the study is life-cycle energy consumption, greenhouse gas emissions and major air emissions were included in this assessment.

ABSTRACT. A life cycle perspective is critical to the invention and development of products that contribute to company and societal sustainability by having environmental benefits that clearly exceed the burdens to create them. Quick, qualitative, tools [1] can build awareness well but may be challenging for a company to compare projects across a portfolio. Tools based on company performance can provide good alignment and progress on company goals [2] but may change too slowly to provide focus for innovation.

Ideal tools or metrics to influence R&D are ones that are forward-looking, quantitative, and readily compared or totaled across a research portfolio. The approach we have taken at The Dow Chemical Company (Dow) has been to set a specific goal for “net positive impact” for innovation products, a life-cycle metric comparing benefits (primarily in the use phase) to the burdens (primarily in other life-cycle stages) [3]. This will be used to impact decisions on the company innovation portfolio. A key methodological issue is how to “discount” future benefits compared to current burdens. Discounting is a concept routinely used in companies for economic evaluation, but less so for potential environmental impacts. But it is an important concept to address to have effective use of the metric.

Dow’s commitment to this approach was announced on April 15, 2015. We will present our assessment and resolution of methodological issues and implementation challenges of the approach.

1. David A. Russell & Dawn L. Shiang, “Thinking about More Sustainable Products: Using an Efficient Tool for Sustainability Education, Innovation, and Project Management To Encourage Sustainability Thinking in a Multinational Corporation “ ACS Sustainable Chem. Eng., 2013, 1 (1), pp 2–7 http://pubs.acs.org/doi/abs/10.1021/sc300131e 2. Shawn Hunter & Anne Wallin, “The Sustainable Chemistry Index: Providing Life-Cycle Insight Across The Dow Chemical Company Product Portfolio” Proceedings of LCA XIV, San Francisco, October 2014. http://lcacenter.org/lcaxiv/final-presentations/1132.pdf 3. Mazor, Mike, Adam Muellerweiss, Rich Helling, Anastasia Behr “Bringing Life Cycle Thinking to Corporate Metrics´ LCA XII conference, Tacoma, WA, September 2012. http://lcacenter.org/lcaxii/final-presentations/627.pdf

ABSTRACT. One challenge that industry faces in product level Life Cycle Assessment is the lack of supplier specific Life Cycle Inventory data. In lieu of this data, publicly available industry average data or purchased data sets that are often based on public information are often used as proxies. The use of proxy data increases the uncertainty of the result and as industry pursues publication of those results in product literature and Environmental Product Declarations, the need for accuracy increases. This presentation explains the drivers at Interface for supplier specific LCI, different approaches to acquisition of the data, and the effect of increased data specificity on the results of some product level life cycle assessments. Additionally, the presentation will also share the supplier’s point of view and explain how Interface has collaborated with their suppliers to overcome common obstacles such as concerns over proprietary data, lack of technical knowledge, high costs and limited resources. Additionally, the session’s presenters will share success stories from Interface’s program, including how one supplier took the program a step further and became the first in the United States to publish an EPD for their product group.

ABSTRACT. 1. Transparency Transparency -- a common theme in the marketplace today – has many meanings, but increasingly is used to describe the push for disclosure of the chemical composition of products. This call for disclosure has resulted in a number of challenges, questions, and concerns impacting both the value chain and consumers. For example, what information is needed by product manufacturers to manage health and environmental considerations? What is the right balance between consumer interest in ingredient disclosure versus a system that fosters innovation in formulation and new chemistries by protecting research and development and property rights? What information do consumers truly need to make complete and informed choices? What is the best way to communicate to consumers about ingredients, both in terms of product safety and environmental impact?

2. Evaluation Tools Continued improvement of the health profile of products depends on an understanding of how decisions are made regarding the chemical composition/formulation of those products. Likewise, true sustainability depends on a keen understanding of environmental impacts across the entire life cycle of the product. And product improvement should also consider whether the physical safety and performance of the product are at least maintained if not improved. There are currently many tools available to help assist with health, safety, and environmental evaluations of products. But how can we better understand how these tools work, what underlying assumptions they make, and how they treat data inputs? If the science of sustainability requires sophisticated, powerful, and complete evaluation across disciplines, how can we know whether sustainability tools are likewise sophisticated, powerful, and complete? How can we advance the science and methodologies needed to support the next generation of tools? This session will focus on how existing tools evaluate the chemistries and processes used to evaluate products.

Results of two ACC research reports will be presented, which together offer a deeper understanding of available approaches – and tools – used to evaluate chemical hazard. The research, which included evaluation of the same series of selected chemicals through multiple tools, reveals that hazard classifications and rankings differ significantly – for the same chemicals – across various tools. The audience will gain a better understanding of how these tools work, which will inform ongoing discussion about ways to improve the scientific and technical basis for sustainability decision making.

3. Working with the Value Chain to Provide Solutions Product sustainability is with us to stay -- an evergreen challenge for the entire value chain. The sustainability discussion will continue to consider the role and value of ingredient disclosure, hazard assessment, exposure assessment, and alternatives assessment, all while equipping the value chain to develop innovative new products or continuing to improve existing ones. ACC is leading work with trade associations and others to explore development of the next generation of technical standards and certification systems for product assessment. A foundational part of this work is to help the value chain and consumers better understand the critical role that chemistry plays in engineering the products that make modern society possible. We are rethinking the ways we communicate about the value and benefits of chemistry, and how the safety and performance of products depends on chemistry. We are also finding new ways to explain the science behind chemical safety – hazard, exposure, and risk – to lay audiences. And we are finding new partners in the value chain to help with this important discussion as we all work together to move sustainability forward.

4. Learning Objectives • Understand the motivating factors behind the push for greater “transparency” in private sector sustainability standards and programs addressing product formulations, and the possible pros and cons for innovation and informed choice. • Understand the evaluatory framework used by existing hazard screening tools, and the consequences of these frameworks on the technical output of the tools. • Identify paths to develop next generation technically robust, science-based, sophisticated frameworks for product evaluation. • Share examples of communication and partnership strategies to improve understanding of the science behind product evaluation with the value chain.