Evidence map›Paper›PMID 42621971›Full record

ArticleACS ES&T air2026

Facility-Scale Detection and Quantification of Gas Flaring Using Imaging Spectrometers.

Jinsol Kim, Daniel H Cusworth, Bradley M Conrad, Riley M Duren

Abstract read
In one paragraph

Article in ACS ES&T air, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Jinsol KimCarbon Mapper Inc, Pasadena, California 91101, United States.ORCID https://orcid.org/0000-0002-7780-0685
Daniel H CusworthCarbon Mapper Inc, Pasadena, California 91101, United States.
Bradley M ConradCarbon Mapper Inc, Pasadena, California 91101, United States.ORCID https://orcid.org/0000-0003-3678-7434
Riley M DurenCarbon Mapper Inc, Pasadena, California 91101, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Globally, over 140 billion cubic meters of natural gas are flared each year, according to the VIIRS Nightfire (VNF) data product derived from satellite observations by the Visible Infrared Imaging Radiometer Suite (VIIRS), the most widely used instrument for global flare monitoring. Although VIIRS routinely tracks global flaring activity through nighttime observations, its coarse spatial resolution limits the ability to attribute flares to specific facilities or operators. Here, we present flare detection and quantification using high spatial resolution imaging spectrometers. We demonstrate that NASA's Earth Surface Mineral Dust Source Investigation (EMIT) is capable of detecting flares at individual flare stacks with a probability of detection (POD) comparable to that of VIIRS. We further attribute the detected flare stacks in the Permian Basin during 2023 to individual operators and evaluate EMIT's potential to estimate annual flared gas volumes at the operator level. We find good correspondence between the EMIT-observed radiant heat values and reported annual flared gas volume on the operator level. Despite limited temporal sampling relative to VIIRS, EMIT achieves accuracy comparable to VIIRS-based annual flaring estimates, while providing operator-level attribution. This highlights the value of high-resolution imaging spectrometers in regulatory and mitigation efforts by adding insights at the operator level that can complement existing VIIRS observations, enabling more comprehensive flare monitoring and analysis.

Indexed as

EMITfacility scaleflared gas volumesflaringimaging spectrometermethaneoil and gasoperator level

Identifiers

PMID42621971
PMCPMC13488275

What OpenQuestion holds

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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.