Evidence map›Paper›PMID 37588127›Full record

ArticleResources, conservation, and recycling2022

A data engineering approach for sustainable chemical end-of-life management.

Jose D Hernandez-Betancur, Mariano Martin, Gerardo J Ruiz-Mercado

Abstract read
In one paragraph

Article in Resources, conservation, and recycling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jose D Hernandez-BetancurOak Ridge Institute for Science and Education, hosted by Office of Research & Development, U.S. Environmental Protection Agency, Cincinnati, OH, 45268, USA.
Mariano MartinDepartment of Chemical Engineering, University of Salamanca, Plz. Caidos 1-5, Salamanca, 37008, Spain.
Gerardo J Ruiz-MercadoOffice of Research & Development, U.S. Environmental Protection Agency, 26 W Martin L. King Dr., Cincinnati, OH, 45268, USA.

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

The presence of chemicals causing significant adverse human health and environmental effects during end-of-life (EoL) stages is a challenge for implementing sustainable management efforts and transitioning towards a safer circular life cycle. Conducting chemical risk evaluation and exposure assessment of potential EoL scenarios can help understand the chemical EoL management chain for its safer utilization in a circular life-cycle environment. However, the first step is to track the chemical flows, estimate releases, and potential exposure pathways. Hence, this work proposes an EoL data engineering approach to perform chemical flow analysis and screening to support risk evaluation and exposure assessment for designing a safer circular life cycle of chemicals. This work uses publicly-available data to identify potential post-recycling scenarios (e.g., industrial processing/use operations), estimate inter-industry chemical transfers, and exposure pathways to chemicals of interest. A case study demonstration shows how the data engineering framework identifies, estimates, and tracks chemical flow transfers from EoL stage facilities (e.g., recycling and recovery) to upstream chemical life cycle stage facilities (e. g., manufacturing). Also, the proposed framework considers current regulatory constraints on closing the recycling loop operations and provides a range of values for the flow allocated to post-recycling uses associated with occupational exposure and fugitive air releases from EoL operations.

Indexed as

Chemical flow analysisCircular life cycleData pipelineEnd-of-life management chain

Identifiers

PMID37588127
PMCPMC10428185

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.