Methane Integrated Monitoring and Measurement System Design Article Swipe
Jake Zenker
,
Lekha Patel
,
Anneliese Lilje
,
Philip R. Miller
,
Joshua J. Whiting
,
Jennifer A. Lewis
,
Daniel Krofcheck
,
Kurtis Shuler
,
C. A. Amann
,
Andrew G. Glen
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.2172/2480126
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.2172/2480126
Methane (CH4), an abundant greenhouse gas, is the second largest contributor to global warming after carbon dioxide (CO2). In comparison to CO2, CH4 has a larger warming effect over a much shorter lifetime. While technologies to radically reduce global carbon dioxide emissions are materializing, rapid reductions in methane emissions are needed to limit near-term warming. Methane is primarily emitted as a byproduct from agricultural activities and energy extraction/utilization and is currently monitored via bottom-up (i.e., activity level) or top-down (via airborne or satellite retrievals) approaches. However, significant methane leaks remain undetected, and emission rates are challenging to characterize with current monitoring frameworks. In this report, we study methane leaks from oil and gas infrastructure using a tiered monitoring approach that combines bottom-up and top-down approaches in an integrated framework. We describe the individual advantages of bottom-up and top-down sensors in both stationary and mobile settings before characterizing how a fully integrated framework can improve predictions and uncertainties of potential leak locations and their emission rates. Further, we study the impact of different atmospheric (wind) conditions on integrated methane monitoring and develop a probabilistic approach to optimal sensor placement, thereby shortening detection times and improving monitoring capabilities. Last, we discuss how biogenic flux modeling can be used to improve assessment of background methane concentrations needed to fully assess the sensitivity of a tiered monitoring system.
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Metadata
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- en
- Landing Page
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- OpenAlex ID
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All OpenAlex metadata
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https://doi.org/10.2172/2480126Digital Object Identifier
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Methane Integrated Monitoring and Measurement System DesignWork title
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reportOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-10-01Full publication date if available
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Jake Zenker, Lekha Patel, Anneliese Lilje, Philip R. Miller, Joshua J. Whiting, Jennifer A. Lewis, Daniel Krofcheck, Kurtis Shuler, C. A. Amann, Andrew G. GlenList of authors in order
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https://doi.org/10.2172/2480126Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.osti.gov/biblio/2480126Direct OA link when available
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Computer science, Methane, Environmental science, Chemistry, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.and | 65, 68, 91, 111, 122, 136, 142, 155, 161, 179, 192 |
| abstract_inverted_index.are | 42, 49, 94 |
| abstract_inverted_index.can | 152, 203 |
| abstract_inverted_index.gas | 112 |
| abstract_inverted_index.has | 23 |
| abstract_inverted_index.how | 147, 199 |
| abstract_inverted_index.oil | 110 |
| abstract_inverted_index.the | 7, 131, 168, 217 |
| abstract_inverted_index.via | 72 |
| abstract_inverted_index.(via | 79 |
| abstract_inverted_index.both | 140 |
| abstract_inverted_index.flux | 201 |
| abstract_inverted_index.from | 62, 109 |
| abstract_inverted_index.gas, | 5 |
| abstract_inverted_index.leak | 159 |
| abstract_inverted_index.much | 30 |
| abstract_inverted_index.over | 28 |
| abstract_inverted_index.that | 119 |
| abstract_inverted_index.this | 103 |
| abstract_inverted_index.used | 205 |
| abstract_inverted_index.with | 98 |
| abstract_inverted_index.Last, | 196 |
| abstract_inverted_index.While | 33 |
| abstract_inverted_index.after | 14 |
| abstract_inverted_index.fully | 149, 215 |
| abstract_inverted_index.leaks | 88, 108 |
| abstract_inverted_index.limit | 52 |
| abstract_inverted_index.rapid | 44 |
| abstract_inverted_index.rates | 93 |
| abstract_inverted_index.study | 106, 167 |
| abstract_inverted_index.their | 162 |
| abstract_inverted_index.times | 191 |
| abstract_inverted_index.using | 114 |
| abstract_inverted_index.(i.e., | 74 |
| abstract_inverted_index.(wind) | 173 |
| abstract_inverted_index.assess | 216 |
| abstract_inverted_index.before | 145 |
| abstract_inverted_index.carbon | 15, 39 |
| abstract_inverted_index.effect | 27 |
| abstract_inverted_index.energy | 66 |
| abstract_inverted_index.global | 12, 38 |
| abstract_inverted_index.impact | 169 |
| abstract_inverted_index.larger | 25 |
| abstract_inverted_index.level) | 76 |
| abstract_inverted_index.mobile | 143 |
| abstract_inverted_index.needed | 50, 213 |
| abstract_inverted_index.rates. | 164 |
| abstract_inverted_index.reduce | 37 |
| abstract_inverted_index.remain | 89 |
| abstract_inverted_index.second | 8 |
| abstract_inverted_index.sensor | 186 |
| abstract_inverted_index.tiered | 116, 221 |
| abstract_inverted_index.Methane | 0, 55 |
| abstract_inverted_index.current | 99 |
| abstract_inverted_index.develop | 180 |
| abstract_inverted_index.dioxide | 16, 40 |
| abstract_inverted_index.discuss | 198 |
| abstract_inverted_index.emitted | 58 |
| abstract_inverted_index.improve | 153, 207 |
| abstract_inverted_index.largest | 9 |
| abstract_inverted_index.methane | 47, 87, 107, 177, 211 |
| abstract_inverted_index.optimal | 185 |
| abstract_inverted_index.report, | 104 |
| abstract_inverted_index.sensors | 138 |
| abstract_inverted_index.shorter | 31 |
| abstract_inverted_index.system. | 223 |
| abstract_inverted_index.thereby | 188 |
| abstract_inverted_index.warming | 13, 26 |
| abstract_inverted_index.Further, | 165 |
| abstract_inverted_index.However, | 85 |
| abstract_inverted_index.abundant | 3 |
| abstract_inverted_index.activity | 75 |
| abstract_inverted_index.airborne | 80 |
| abstract_inverted_index.approach | 118, 183 |
| abstract_inverted_index.biogenic | 200 |
| abstract_inverted_index.combines | 120 |
| abstract_inverted_index.describe | 130 |
| abstract_inverted_index.emission | 92, 163 |
| abstract_inverted_index.modeling | 202 |
| abstract_inverted_index.settings | 144 |
| abstract_inverted_index.top-down | 78, 123, 137 |
| abstract_inverted_index.warming. | 54 |
| abstract_inverted_index.bottom-up | 73, 121, 135 |
| abstract_inverted_index.byproduct | 61 |
| abstract_inverted_index.currently | 70 |
| abstract_inverted_index.detection | 190 |
| abstract_inverted_index.different | 171 |
| abstract_inverted_index.emissions | 41, 48 |
| abstract_inverted_index.framework | 151 |
| abstract_inverted_index.improving | 193 |
| abstract_inverted_index.lifetime. | 32 |
| abstract_inverted_index.locations | 160 |
| abstract_inverted_index.monitored | 71 |
| abstract_inverted_index.near-term | 53 |
| abstract_inverted_index.potential | 158 |
| abstract_inverted_index.primarily | 57 |
| abstract_inverted_index.radically | 36 |
| abstract_inverted_index.satellite | 82 |
| abstract_inverted_index.activities | 64 |
| abstract_inverted_index.advantages | 133 |
| abstract_inverted_index.approaches | 124 |
| abstract_inverted_index.assessment | 208 |
| abstract_inverted_index.background | 210 |
| abstract_inverted_index.comparison | 19 |
| abstract_inverted_index.conditions | 174 |
| abstract_inverted_index.framework. | 128 |
| abstract_inverted_index.greenhouse | 4 |
| abstract_inverted_index.individual | 132 |
| abstract_inverted_index.integrated | 127, 150, 176 |
| abstract_inverted_index.monitoring | 100, 117, 178, 194, 222 |
| abstract_inverted_index.placement, | 187 |
| abstract_inverted_index.reductions | 45 |
| abstract_inverted_index.shortening | 189 |
| abstract_inverted_index.stationary | 141 |
| abstract_inverted_index.approaches. | 84 |
| abstract_inverted_index.atmospheric | 172 |
| abstract_inverted_index.challenging | 95 |
| abstract_inverted_index.contributor | 10 |
| abstract_inverted_index.frameworks. | 101 |
| abstract_inverted_index.predictions | 154 |
| abstract_inverted_index.retrievals) | 83 |
| abstract_inverted_index.sensitivity | 218 |
| abstract_inverted_index.significant | 86 |
| abstract_inverted_index.undetected, | 90 |
| abstract_inverted_index.agricultural | 63 |
| abstract_inverted_index.characterize | 97 |
| abstract_inverted_index.technologies | 34 |
| abstract_inverted_index.capabilities. | 195 |
| abstract_inverted_index.probabilistic | 182 |
| abstract_inverted_index.uncertainties | 156 |
| abstract_inverted_index.characterizing | 146 |
| abstract_inverted_index.concentrations | 212 |
| abstract_inverted_index.infrastructure | 113 |
| abstract_inverted_index.materializing, | 43 |
| abstract_inverted_index.extraction/utilization | 67 |
| abstract_inverted_index.CH<sub>4</sub> | 22 |
| abstract_inverted_index.CO<sub>2</sub>, | 21 |
| abstract_inverted_index.(CH<sub>4</sub>), | 1 |
| abstract_inverted_index.(CO<sub>2</sub>). | 17 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 10 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.44999998807907104 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile |