Improving the reliability of chemical manufacturing life cycle inventory constructed using secondary data.

This study proposes methods to improve data mining workflows for modeling chemical manufacturing life cycle inventory. Secondary data sources can provide valuable information about environmental releases during chemical manufacturing. However, the often facility-level nature of the data challenges their utility for modeling specific processes and can impact the quality of the resulting inventory. First, a thorough data source analysis is performed to establish data quality scoring and create filtering rules to resolve data selection issues when source and species overlaps arise. A method is then introduced to develop context-based filter rules that leverage process metadata within data sources to improve how facility air releases are attributed to specific processes and increase the technological correlation and completeness of the inventory. Finally, a sanitization method is demonstrated to improve data quality by minimizing the exclusion of confidential business information (CBI). The viability of the methods is explored using case studies of cumene and sodium hydroxide production in the United States. The attribution of air releases using process context enables more sophisticated filtering to remove unnecessary flows from the inventory. The ability to sanitize and incorporate CBI is promising because it increases the sample size, and therefore representativeness, when constructing geographically averaged inventories. Future work will focus on expanding the application of context-based data filtering to other types and sources of environmental data.

Holistic Analysis of Urban Water Systems in the Greater Cincinnati Region: (1) Life Cycle Assessment and Cost Implications.

Urban water and wastewater utilities are striving to improve their environmental and economic performances due to multiple challenges such as increasingly stringent quality criterion, aging infrastructure, constraining financial burden, growing urban population, climate challenges and dwindling resources. Growing needs of holistic assessments of urban water systems are required to identify systems-level cross-domain solutions. This study evaluated the life cycle environmental and economic impacts of urban water and wastewater systems with two utilities in Greater Cincinnati region as a case study. The scope of this study includes the entire urban water and wastewater systems starting from raw water acquisition for drinking water to wastewater treatment and discharge. The detailed process-based life cycle models were developed based on the datasets provided by local water and wastewater utilities. The life cycle assessment indicated that the operation and maintenance of drinking water distribution was a dominating contributor for energy consumption (43%) and global warming potential (41%). Wastewater discharge from the wastewater treatment plant contributed to more than 80% of the total eutrophication potential. The cost analysis determined that labor and maintenance cost (19%) for wastewater collection, and electricity cost (13%) for drinking water distribution were major contributors. Electricity purchased by the utility was the driver for the majority of impact categories assessed with the exception of eutrophication, blue water use, and metal depletion. Infrastructure requirements had a negligible influence on impact results, contributing less than 3% to most categories, with the exception of metal depletion where it led to 68% of total burdens. Sensitivity analysis showed that the life cycle environmental results were more sensitive to the choice of the electricity mixes and electricity consumption than the rest of input parameters such as chemical dosages, and infrastructure life time. This is one of the first comprehensive studies of the whole urban water system using real case data. It elucidates a bigger picture of energy, resource and cost distributions in a typical urban centralized water system. Inherent to a modern city as large population centers, a significant expenditure has to be invested to provide water services function (moving water, treating water/wastewater) in order to avoid human and environmental health problems. This study provides insights for optimization potentials of overall treatment efficiency and can serve as a benchmark for communities considering adoption of alternative water systems.

Discrimination in a General Algebraic Setting.

Discriminating groups were introduced by G. Baumslag, A. Myasnikov, and V. Remeslennikov as an outgrowth of their theory of algebraic geometry over groups. Algebraic geometry over groups became the main method of attack on the solution of the celebrated Tarski conjectures. In this paper we explore the notion of discrimination in a general universal algebra context. As an application we provide a different proof of a theorem of Malcev on axiomatic classes of Ω-algebras.