Evidence map›Paper›PMID 40242284›Full record

ArticleACS ES&T air2025

Intercomparison of Three Continuous Monitoring Systems on Operating Oil and Gas Sites.

William S Daniels, Spencer G Kidd, Shuting Lydia Yang, Shannon Stokes, Arvind P Ravikumar, Dorit M Hammerling

Abstract read
In one paragraph

Article in ACS ES&T air, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

William S DanielsDepartment of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado 80401, United States.ORCID https://orcid.org/0000-0001-8752-5536
Spencer G KiddDepartment of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado 80401, United States.
Shuting Lydia YangDepartment of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, Texas 78712, United States.ORCID https://orcid.org/0000-0003-4214-2448
Shannon StokesCenter for Energy and Environmental Resources, The University of Texas at Austin, Austin, Texas 78712, United States.
Arvind P RavikumarDepartment of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, Texas 78712, United States.ORCID https://orcid.org/0000-0001-8385-6573
Dorit M HammerlingDepartment of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado 80401, United States.ORCID https://orcid.org/0000-0003-3583-3611

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We compare continuous monitoring systems (CMS) from three different vendors on six operating oil and gas sites in the Appalachian Basin using several months of data. We highlight similarities and differences between the three CMS solutions when deployed in the field and compare their output to concurrent top-down aerial measurements and to site-level bottom-up inventories. Furthermore, we compare vendor-provided emission rate estimates to estimates from an open-source quantification algorithm applied to the raw CMS concentration data. This experimental setup allows us to separate the effect of the sensor platform (i.e., sensor type and arrangement) from the quantification algorithm. We find that 1) localization and quantification estimates rarely agree between the three CMS solutions on short time scales (i.e., 30 min), but temporally aggregated emission rate distributions are similar between solutions, 2) differences in emission rate distributions are generally driven by the quantification algorithm, rather than the sensor platform, 3) agreement between CMS and aerial rate estimates varies by CMS solution but is close to parity when CMS estimates are averaged across solutions, and 4) similar sites with similar bottom-up inventories do not necessarily have similar emission characteristics. These results have important implications for developing measurement-informed inventories and for incorporating CMS-inferred emission characteristics into emission mitigation efforts.

Identifiers

PMID40242284
PMCPMC11997984

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Registered trials

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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.