ArticleFuel (London, England)2022
Characterization of Compositional Variability in Petroleum Substances.
Article in Fuel (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed.
- Oil Characterization, Molecular Modeling and Process Simulation in Petroleum Research and Industry, Opportunities, Challenges and Perspectives.Molecules (Basel, Switzerland) · 2026Review
- Determination of the Weight Percent of Aromatic Compounds in a Heavy Fuel Oil by Using Flash Chromatography and Solid-phase Extraction Coupled With High-Temperature Two-Dimensional Gas Chromatography and Electron Ionization Time-of-Flight High-Resolution Mass Spectrometry.Journal of separation science · 2025Article
- Reference library for suspect screening of environmental toxicants using ion mobility spectrometry-mass spectrometry.Communications chemistry · 2025Article
- Evaluating Ion Mobility Data Acquisition, Calibration, and Processing for Small Molecules: A Cross-Platform Assessment of Drift Tube and Traveling Wave Methodologies.Journal of the American Society for Mass Spectrometry · 2025Article
- Article
- A Systematic Analysis of Read-Across Adaptations in Testing Proposal Evaluations by the European Chemicals Agency.bioRxiv : the preprint server for biology · 2024Article
- Machine Learning Methods for Endocrine Disrupting Potential Identification Based on Single-Cell Data.Chemical engineering science · 2023Article
- Application of Ion Mobility Spectrometry-Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples.Environmental toxicology and chemistry · 2023Article
- Article
- Analytical chemistry solutions to hazard evaluation of petroleum refining products.Regulatory toxicology and pharmacology : RTP · 2023Review
- Next Challenges for the Comprehensive Molecular Characterization of Complex Organic Mixtures in the Field of Sustainable Energy.Molecules (Basel, Switzerland) · 2022Review
- Temporal chemical composition changes in water below a crude oil slick irradiated with natural sunlight.Marine pollution bulletin · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
In the process of registration of substances of Unknown or Variable Composition, Complex Reaction Products or Biological Materials (UVCBs), information sufficient to enable substance identification must be provided. Substance identification for UVCBs formed through petroleum refining is particularly challenging due to their chemical complexity, as well as variability in refining process conditions and composition of the feedstocks. This study aimed to characterize compositional variability of petroleum UVCBs both within and across product categories. We utilized ion mobility spectrometry (IMS)-MS as a technique to evaluate detailed chemical composition of independent production cycle-derived samples of 6 petroleum products from 3 manufacturing categories (heavy aromatic, hydrotreated light paraffinic, and hydrotreated heavy paraffinic). Atmospheric pressure photoionization and drift tube IMS-MS were used to identify structurally related compounds and quantified between- and within-product variability. In addition, we determined both individual molecules and hydrocarbon blocks that were most variable in samples from different production cycles. We found that detailed chemical compositional data on petroleum UVCBs obtained from IMS-MS can provide the information necessary for hazard and risk characterization in terms of quantifying the variability of the products in a manufacturing category, as well as in subsequent production cycles of the same product.
Identifiers
What OpenQuestion holds
Registered trials
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.