Life Cycle Data Interoperability Improvements through Implementation of the Federal LCA Commons Elementary Flow List.

As a fundamental component of data for life cycle assessment models, elementary flows have been demonstrated to be a key requirement of life cycle assessment data interoperability. However, existing elementary flow lists have been found to lack sufficient structure to enable improved interoperability between life cycle data sources. The Federal Life Cycle Assessment Commons Elementary Flow List provides a novel framework and structure for elementary flows, but the actual improvement this list provides to the interoperability of life cycle data has not been tested. The interoperability of ten elementary flow lists, two life cycle assessment databases, three life cycle impact assessment methods, and five life cycle assessment software sources is assessed with and without use of the Federal Life Cycle Assessment Commons Elementary Flow List as an intermediary in flow mapping. This analysis showed that only 25% of comparisons between these sources resulted in greater than 50% of flows being capable of automatic name-to-name matching between lists. This indicates that there is a low level of interoperability when using sources with their original elementary flow nomenclature, and elementary flow mapping is required to use these sources in combination. The mapping capabilities of the Federal Life Cycle Assessment Commons Elementary Flow List to sources were reviewed and revealed a notable increase in name-to-name matches. Overall, this novel framework is found to increase life cycle data source interoperability.

Life cycle assessment of a rainwater harvesting system compared with an AC condensate harvesting system.

This study presents a life cycle assessment (LCA) of a rainwater harvesting (RWH) system and an air-conditioning condensate harvesting (ACH) system for non-potable water reuse. U.S. commercial buildings were reviewed to design rooftop RWH and ACH systems for one to multi-story buildings' non-potable water demand. A life cycle inventory was compiled from the U.S. EPA's database. Nine scenarios were analyzed, including baseline RWH system, ACH system, and combinations of the two systems adapted to 4-story and 19-story commercial buildings in San Francisco and a 4-story building in Washington, DC. Normalization of 11 life cycle impact assessment categories showed that RWH systems in 4-story buildings at both locations outperformed ACH systems (45-80% of ACH impacts) except equivalent in Evaporative Water Consumption. However, San Francisco's ACH system in 19-story building outperformed the RWH system (51-83% of RWH impacts) due to the larger volume of ACH collection, except equivalent in Evaporative Water Consumption. For all three buildings, the combined system preformed equivalently to the better-performing option (≤4-8% impact difference compared to the maximum system). Sensitivity analysis of the volume of water supply and building occupancy showed impact-specific results. Local climatic conditions, rainfall, humidity, water collections and demands are important when designing building-scale RWH and ACH systems. LCA models are transferrable to other locations with variable climatic conditions for decision-making when developing and implementing on-site non-potable water systems.

The creation, management, and use of data quality information for life cycle assessment.

PURPOSE: Despite growing access to data, questions of "best fit" data and the appropriate use of results in supporting decision making still plague the life cycle assessment (LCA) community. This discussion paper addresses revisions to assessing data quality captured in a new US Environmental Protection Agency guidance document as well as additional recommendations on data quality creation, management, and use in LCA databases and studies. APPROACH: Existing data quality systems and approaches in LCA were reviewed and tested. The evaluations resulted in a revision to a commonly used pedigree matrix, for which flow and process level data quality indicators are described, more clarity for scoring criteria, and further guidance on interpretation are given. DISCUSSION: Increased training for practitioners on data quality application and its limits are recommended. A multi-faceted approach to data quality assessment utilizing the pedigree method alongside uncertainty analysis in result interpretation is recommended. A method of data quality score aggregation is proposed and recommendations for usage of data quality scores in existing data are made to enable improved use of data quality scores in LCA results interpretation. Roles for data generators, data repositories, and data users are described in LCA data quality management. Guidance is provided on using data with data quality scores from other systems alongside data with scores from the new system. The new pedigree matrix and recommended data quality aggregation procedure can now be implemented in openLCA software. FUTURE WORK: Additional ways in which data quality assessment might be improved and expanded are described. Interoperability efforts in LCA data should focus on descriptors to enable user scoring of data quality rather than translation of existing scores. Developing and using data quality indicators for additional dimensions of LCA data, and automation of data quality scoring through metadata extraction and comparison to goal and scope are needed.

Critical review of elementary flows in LCA data.

PURPOSE: Elementary flows are essential components of data used for life cycle assessment. A standard list is not used across all sources, as data providers now manage these flows independently. Elementary flows must be consistent across a life cycle inventory for accurate inventory analysis and must correspond with impact methods for impact assessment. With the goal of achieving a global network of LCA databases, a critical review of elementary flow usage and management in LCA data sources was performed. METHODS: Flows were collected in a standard template from various life cycle inventory, impact method, and software sources. A typology of elementary flows was created to identify flows by types such as chemicals, minerals, land flows, etc. to facilitate differential analysis. Twelve criteria were defined to evaluate flows against principles of clarity, consistency, extensibility, translatability, and uniqueness. RESULTS AND DISCUSSION: Over 134,000 elementary flows from five LCI databases, three LCIA methods, and four LCA software tools were collected and evaluated from European, North American, and Asian Pacific LCA sources. The vast majority were typed as "Element or Compound" or "Group of Chemicals" with less than 10% coming from the other seven types Many lack important identifying information including context information (environmental compartments), directionality (LCIA methods generally do not provide this information), additional clarifiers such as CAS numbers and synonyms, unique identifiers (like UUIDs), and supporting metadata. Extensibility of flows is poor because patterns in flow naming are generally complex and inconsistent because user defined nomenclature is used. CONCLUSIONS: The current shortcomings in flow clarity, consistency, and extensibility are likely to make it more challenging for users to properly select and use elementary flows when creating LCA data and make translation/conversion between different reference lists challenging and loss of information will likely occur. RECOMMENDATIONS: We recommend the application of a typology to flow lists, use of unique identifiers and inclusion of clarifiers based on external references, setting an exclusive or inclusive nomenclature for flow context information that includes directionality and environmental compartment information, separating flowable names from context and unit information, linking inclusive taxonomies to create limited patterns for flowable names, and using an encoding schema that will prevent technical translation errors.

Mining Available Data from the United States Environmental Protection Agency to Support Rapid Life Cycle Inventory Modeling of Chemical Manufacturing.

Demands for quick and accurate life cycle assessments create a need for methods to rapidly generate reliable life cycle inventories (LCI). Data mining is a suitable tool for this purpose, especially given the large amount of available governmental data. These data are typically applied to LCIs on a case-by-case basis. As linked open data becomes more prevalent, it may be possible to automate LCI using data mining by establishing a reproducible approach for identifying, extracting, and processing the data. This work proposes a method for standardizing and eventually automating the discovery and use of publicly available data at the United States Environmental Protection Agency for chemical-manufacturing LCI. The method is developed using a case study of acetic acid. The data quality and gap analyses for the generated inventory found that the selected data sources can provide information with equal or better reliability and representativeness on air, water, hazardous waste, on-site energy usage, and production volumes but with key data gaps including material inputs, water usage, purchased electricity, and transportation requirements. A comparison of the generated LCI with existing data revealed that the data mining inventory is in reasonable agreement with existing data and may provide a more-comprehensive inventory of air emissions and water discharges. The case study highlighted challenges for current data management practices that must be overcome to successfully automate the method using semantic technology. Benefits of the method are that the openly available data can be compiled in a standardized and transparent approach that supports potential automation with flexibility to incorporate new data sources as needed.

Biocompatible lecithin-based microemulsions with rhamnolipid and sophorolipid biosurfactants: formulation and potential applications.

The objectives of this research are first to evaluate the hydrophilicity/hydrophobicity of sophorolipid biosurfactants relative to conventional synthetic surfactants and then to formulate and evaluate microemulsions of lecithin/rhamnolipid/sophorolipid biosurfactants with a range of oils (varying EACN values and oil types). We found that sophorolipid biosurfactants are more hydrophobic than sodium bis(2-ethyl) dihexyl sulfosuccinate (SBDHS), which is more hydrophobic than sodium dihexyl sulfosuccinate (SDHS) and rhamnolipid biosurfactant. Sophorolipid thus played an important role as the hydrophobic component in lecithin/rhamnolipid/sophorolipid biosurfactant formulation. This biosurfactant formulation was able to produce Winsor Type I, III and II microemulsions and the corresponding ultralow IFT for limonene, decane, isopropyl myristate and hexadecane. The phase behavior of this formulation with isopropyl myristate did not change significantly with changing temperature (10, 25, 40 degrees C) and electrolyte concentration (0.9% and 4.0% w/v), making it desirable for cosmetic and drug delivery applications. The hexadecane detergency performance of our biocompatible formulation was higher than that of a commercial liquid detergent at the same surfactant active concentrations. This paper thus shows the ability and robustness of mixed biosurfactant systems in formulating microemulsions for a range of oils and their potential applications.