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.

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.