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Temporal variation and grade categorization of methane emission from LNG fueling stations
Natural gas is increasingly seen as the fossil fuel of choice for China as it transitions to renewable sources. The significant development of China’s LNG vehicle application and fueling stations and the urgency of climate changes make it particularly important to quantify methane emission from LNG...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626451/ https://www.ncbi.nlm.nih.gov/pubmed/36319852 http://dx.doi.org/10.1038/s41598-022-23334-2 |
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author | Wang, Yifan Tang, Jianfeng Xie, Donglai Li, Fei Xue, Ming Zhao, Bo Yu, Xiao Wen, Xiaojin |
author_facet | Wang, Yifan Tang, Jianfeng Xie, Donglai Li, Fei Xue, Ming Zhao, Bo Yu, Xiao Wen, Xiaojin |
author_sort | Wang, Yifan |
collection | PubMed |
description | Natural gas is increasingly seen as the fossil fuel of choice for China as it transitions to renewable sources. The significant development of China’s LNG vehicle application and fueling stations and the urgency of climate changes make it particularly important to quantify methane emission from LNG stations, where the data are extremely rare. We carried out a pilot study on direct measurement and quantitative analysis of methane emission from five LNG fueling stations located in Shandong, China following the standard stationary EPA OTM 33A method. The measured methane emission of these five stations vary from 0.01 to 8.76 kg/h. The loss rates vary from 0.004 to 0.257%. We demonstrated that the emission from LNG stations consist of continuous and intermittent contents. The intermittent emission shows a strong temporal variation. If a station is only monitored for 20 min, it may either under-estimate or over-estimate the total emission. Both the distribution of emission events and total emission rates among different stations are highly skewed. We found that these LNG fueling station emission can be categorized into 3 grades, as low, medium and high, corresponding to emission rates below 0.1 kg/h; between 0.1 and 1 kg/h and above 1 kg/h, which can be characterized by the measured average methane concentration enhancement. |
format | Online Article Text |
id | pubmed-9626451 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96264512022-11-03 Temporal variation and grade categorization of methane emission from LNG fueling stations Wang, Yifan Tang, Jianfeng Xie, Donglai Li, Fei Xue, Ming Zhao, Bo Yu, Xiao Wen, Xiaojin Sci Rep Article Natural gas is increasingly seen as the fossil fuel of choice for China as it transitions to renewable sources. The significant development of China’s LNG vehicle application and fueling stations and the urgency of climate changes make it particularly important to quantify methane emission from LNG stations, where the data are extremely rare. We carried out a pilot study on direct measurement and quantitative analysis of methane emission from five LNG fueling stations located in Shandong, China following the standard stationary EPA OTM 33A method. The measured methane emission of these five stations vary from 0.01 to 8.76 kg/h. The loss rates vary from 0.004 to 0.257%. We demonstrated that the emission from LNG stations consist of continuous and intermittent contents. The intermittent emission shows a strong temporal variation. If a station is only monitored for 20 min, it may either under-estimate or over-estimate the total emission. Both the distribution of emission events and total emission rates among different stations are highly skewed. We found that these LNG fueling station emission can be categorized into 3 grades, as low, medium and high, corresponding to emission rates below 0.1 kg/h; between 0.1 and 1 kg/h and above 1 kg/h, which can be characterized by the measured average methane concentration enhancement. Nature Publishing Group UK 2022-11-01 /pmc/articles/PMC9626451/ /pubmed/36319852 http://dx.doi.org/10.1038/s41598-022-23334-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Yifan Tang, Jianfeng Xie, Donglai Li, Fei Xue, Ming Zhao, Bo Yu, Xiao Wen, Xiaojin Temporal variation and grade categorization of methane emission from LNG fueling stations |
title | Temporal variation and grade categorization of methane emission from LNG fueling stations |
title_full | Temporal variation and grade categorization of methane emission from LNG fueling stations |
title_fullStr | Temporal variation and grade categorization of methane emission from LNG fueling stations |
title_full_unstemmed | Temporal variation and grade categorization of methane emission from LNG fueling stations |
title_short | Temporal variation and grade categorization of methane emission from LNG fueling stations |
title_sort | temporal variation and grade categorization of methane emission from lng fueling stations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626451/ https://www.ncbi.nlm.nih.gov/pubmed/36319852 http://dx.doi.org/10.1038/s41598-022-23334-2 |
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