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BlueConduit and EPIC analyze patterns in EPA Lead and Copper Rule public comments

The upcoming release of EPA’s Lead and Copper Rule is top of mind for many in the drinking water industry. As part of its rule-making process, EPA received 80,000 public comments on its proposed rule. Using natural language processing (performing data science on textual data), BlueConduit, in collaboration with the Environmental Policy Innovation Center, explored the content and tone of those comments.

This provided an opportunity to understand what topics were important to stakeholder groups and how they communicated those messages as part of their submitted comments.

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Analyzing Public Comments Whitepaper

By employing the techniques of topic analysis and sentiment analysis, we were able to identify the principle themes of different types of comments and the speakers’ feeling (on a positive/negative spectrum). analyzing what different types of commenters had to say about the proposed regulations.

Findings

Machine learning found that service line replacement was a more frequent and detectable theme of public input than enhanced testing and sampling of drinking water.

Concern over children’s safety is a central theme in comments and attachments.

The analysis found little to no evidence that financial themes were central in both comments and attachments. Additionally, there was no evidence of negative sentiments related to “unrealistic” financial demands, suggesting that the federal government should not exaggerate cost considerations in its final rule, compared to the draft.

Topic analysis found detectable differences between different commenter types, but that those differences do not always correspond to differences of opinion.

The insights that this type of analysis highlights for the Proposed Lead and Copper Rule Revisions show the use of these tools for government agencies in processing large volume of comments. The full report offers a deeper exploration of those opportunities.

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About BlueConduit

BlueConduit originated the approach of using machine learning to predict lead service line materials and have been doing it longer than anyone else.

Our team has been helping local officials and their engineering partners identify and remove lead service lines since 2016.

We’ve now created our software platform to streamline this process for our utility and engineering partners.

BlueConduit

About BlueConduit

BlueConduit pioneered the predictive modeling approach to lead service line identification and replacement. Through BlueConduit data science, utilities, municipalities, government agencies, and consultants standardize, predict, report, and communicate key information about lead.