(151b) Tracking Industrial Wastewater Transfers to Publicly Owned Treatment Works, a Data Engineering Approach
AIChE Annual Meeting
2022
2022 Annual Meeting
Sustainable Engineering Forum
Sustainable Management and Uses of Post-Consumer Materials and Waste
Monday, November 14, 2022 - 12:45pm to 1:00pm
A large amount of disparate data across several regulated public databases can support risk evaluation of chemicals found in industrial wastewater releases to POTWs. Gathering, curating, and analyzing information from agency repositories that differ in reporting standards and data formats are challenging and time-consuming approaches, especially for those who are not proficient in the many local, state, and federal regulatory entities. Also, U.S. EPAâs current risk assessment methods for chemicals at their EoL scenarios is a structured case-by-case systematic review process that gathers scientific information and models consistent with the best available science to identify, evaluate and integrate data for risk evaluations. However, using this approach to review several thousand chemicals covered by these databases makes the case-by-case review procedure resource and time-intensive.
Data engineering frameworks that can quickly collect and curate environmental release data from industrial EoL scenarios have been developed however, to this research teamâs knowledge, no such framework exists that includes EoL POTW environmental releases and exposure scenarios. This work proposes the design of a novel structured framework that can produce transparent, reproducible, and scientifically credible datasets from regulated public-access databases with the intent to track and estimate EoL chemical releases and potential occupational exposure in POTWs.
The framework evaluates environmental releases by collecting and storing various facility-reported datasets (e.g., TRI1, NEI2, Biennial Reports, DMR3, RCRA4, NPDES5, etc.), process units, and unit operations by applying chemical flow analysis (CFA) methods. Also, CFA can be used for collecting life-cycle inventory (LCI) and identifying potential exposure scenarios for chemicals of concern at an EoL stage. Through this framework, stakeholders can gather, manage, and convert raw data into usable information to identify whether a chemical substance presents an unreasonable risk to human or environmental health.
Furthermore, our framework supports worldwide efforts outlined by United Nations Millennial Goal #12 by providing a resource that can gather and assess chemical data that can be used to further improve environmentally sound chemical management.
The views expressed in this presentation abstract are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.