{"id":158,"date":"2025-02-06T13:19:39","date_gmt":"2025-02-06T13:19:39","guid":{"rendered":"https:\/\/blog.fmi.fi\/coe-inverse\/?p=158"},"modified":"2026-01-29T05:04:40","modified_gmt":"2026-01-29T05:04:40","slug":"linear-integrated-mass-enhancement","status":"publish","type":"post","link":"https:\/\/blog.fmi.fi\/coe-inverse\/?p=158","title":{"rendered":"Linear Integrated Mass Enhancement"},"content":{"rendered":"\n<p>Our paper,&nbsp;<strong>\u201cLinear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations,\u201d<\/strong>&nbsp;has been published in&nbsp;<em>Remote Sensing of Environment<\/em>.<\/p>\n\n\n\n<p>In this paper, we propose a new methodology for plume inversion emission estimation termed&nbsp;<em>linear integrated mass enhancement (LIME)<\/em>. As the name implies, this approach is based on the integrated mass enhancement (IME) method and on the linear relationship between IME and the distance from the source. The proposed approach accounts for the information coming from different portions of the plume, and it can be seen as a \u201ccombination\u201d of the cross-sectional flux (CSF) method and IME. The method offers a straightforward way to estimate the source strength by determining the slope of the linear fit.<\/p>\n\n\n\n<p>We test the LIME approach with both real (OCO-3, S5P\/TROPOMI, Sentinel-2) and simulated (MicroHH, SMARTCARB) satellite data. We apply the method to the simulated carbon dioxide (CO<sub>2<\/sub>) observations for the upcoming CO2M mission over the Matimba and J\u00e4nschwalde power stations with known source rates. We use the OCO-3 data to estimate the CO<sub>2<\/sub>&nbsp;emissions originating from the Be\u0142chat\u00f3w power station in Poland (between 72 and 103&nbsp;ktCO<sub>2<\/sub>\/d). We also estimate the emissions from two methane (CH<sub>4<\/sub>) leaking sites in Algeria based on S5P\/TROPOMI (77 and 47&nbsp;tCH<sub>4<\/sub>\/h for two days) and Sentinel-2 (7.7&nbsp;tCH<sub>4<\/sub>\/h) observations. Finally, we apply the LIME method to the Sentinel-2 retrievals from a controlled CH<sub>4<\/sub>&nbsp;release in Arizona.<\/p>\n\n\n\n<p>Across all case studies, the LIME emission estimates are in agreement with the expected values. The LIME estimates are also aligned with the state-of-the-art IME emission estimates, which are calculated as byproducts in the LIME emission estimation process.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"446\" src=\"https:\/\/blog.fmi.fi\/coe-inverse\/wp-content\/uploads\/2025\/01\/kuva_abstract_uusi-1024x446.png\" alt=\"\" class=\"wp-image-159\" srcset=\"https:\/\/blog.fmi.fi\/coe-inverse\/wp-content\/uploads\/2025\/01\/kuva_abstract_uusi-1024x446.png 1024w, https:\/\/blog.fmi.fi\/coe-inverse\/wp-content\/uploads\/2025\/01\/kuva_abstract_uusi-300x131.png 300w, https:\/\/blog.fmi.fi\/coe-inverse\/wp-content\/uploads\/2025\/01\/kuva_abstract_uusi-768x334.png 768w, https:\/\/blog.fmi.fi\/coe-inverse\/wp-content\/uploads\/2025\/01\/kuva_abstract_uusi-1536x669.png 1536w, https:\/\/blog.fmi.fi\/coe-inverse\/wp-content\/uploads\/2025\/01\/kuva_abstract_uusi-2048x892.png 2048w, https:\/\/blog.fmi.fi\/coe-inverse\/wp-content\/uploads\/2025\/01\/kuva_abstract_uusi-1200x522.png 1200w\" sizes=\"(max-width: 709px) 85vw, (max-width: 909px) 67vw, (max-width: 1362px) 62vw, 840px\" \/><\/figure>\n\n\n\n<p><strong>Citation:<\/strong><br>Janne Hakkarainen, Iolanda Ialongo, Daniel J. Varon, Gerrit Kuhlmann, and Maarten C. Krol: Linear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations, <em>Remote Sensing of Environment<\/em>, Volume 319, 2025, <a href=\"https:\/\/doi.org\/10.1016\/j.rse.2025.114623\">https:\/\/doi.org\/10.1016\/j.rse.2025.114623<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Our paper,&nbsp;\u201cLinear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations,\u201d&nbsp;has been published in&nbsp;Remote Sensing of Environment. In this paper, we propose a new methodology for plume inversion emission estimation termed&nbsp;linear integrated mass enhancement (LIME). As the name implies, this approach is based on the integrated mass enhancement (IME) method &hellip; <a href=\"https:\/\/blog.fmi.fi\/coe-inverse\/?p=158\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Linear Integrated Mass Enhancement&#8221;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=\/wp\/v2\/posts\/158"}],"collection":[{"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=158"}],"version-history":[{"count":3,"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=\/wp\/v2\/posts\/158\/revisions"}],"predecessor-version":[{"id":163,"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=\/wp\/v2\/posts\/158\/revisions\/163"}],"wp:attachment":[{"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=158"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=158"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.fmi.fi\/coe-inverse\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=158"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}