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利用对流层监测仪对陆上油气甲烷源进行全球观测覆盖。

Global observational coverage of onshore oil and gas methane sources with TROPOMI.

作者信息

Gao Mozhou, Xing Zhenyu, Vollrath Coleman, Hugenholtz Chris H, Barchyn Thomas E

机构信息

Centre for Smart Emissions Sensing Technologies, Department of Geography, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.

出版信息

Sci Rep. 2023 Oct 5;13(1):16759. doi: 10.1038/s41598-023-41914-8.

DOI:10.1038/s41598-023-41914-8
PMID:37798261
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10555993/
Abstract

Satellite observations have been used to measure methane (CH) emissions from the oil and gas (O&G) industry, particularly by revealing previously undocumented, very large emission events and basin-level emission estimates. However, most satellite systems use passive remote sensing to retrieve CH mixing ratios, which is sensitive to sunlight, earth surface properties, and atmospheric conditions. Accordingly, the reliability of satellites for routine CH emissions monitoring varies across the globe. To better understand the potentials and limitations of routine monitoring of CH emissions with satellites, we investigated the global observational coverage of the TROPOMI instrument onboard the Sentinel-5P satellite-the only satellite system currently with daily global coverage. A 0.1° × 0.1° gridded global map that indicates the average number of days with valid observations from TROPOMI for 2019-2021 was generated by following the measurement retrieval quality-assurance threshold (≥ 0.5). We found TROPOMI had promising observational coverage over dryland regions (maximum: 58.6%) but limited coverage over tropical regions and high latitudes (minimum: 0%). Cloud cover and solar zenith angle were the primary factors affecting observational coverage at high latitudes, while aerosol optical thickness was the primary factor over dryland regions. To further assess the country-level reliability of satellites for detecting and quantifying CH emissions from the onshore O&G sector, we extracted the average annual TROPOMI observational coverage (TOC) over onshore O&G infrastructure for 160 countries. Seven of the top-10 O&G-producing countries had an average annual TOC < 10% (< 36 days per year), which indicates the limited ability to routinely identify large emissions events, track their duration, and quantify emissions rates using inverse modelling. We further assessed the potential performance of the latter by combining TOC and the uncertainties from the global O&G inventory. Results indicate that the accuracy of emissions quantifications of onshore O&G sources using TROPOMI data and inverse modeling will be higher in countries located in dryland and mid-latitude regions and lower in tropical and high-latitude regions. Therefore, current passive-sensing satellites have low potential for frequent monitoring of large methane emissions from O&G sectors in countries located in tropical and high latitudes (e.g., Canada, Russia, Brazil, Norway, and Venezuela). Alternative methods should be considered for routine emissions monitoring in these regions.

摘要

卫星观测已被用于测量石油和天然气行业的甲烷(CH)排放,特别是通过揭示以前未记录的、非常大的排放事件和盆地级排放估计。然而,大多数卫星系统使用被动遥感来获取CH混合比,这对阳光、地球表面特性和大气条件敏感。因此,卫星用于常规CH排放监测的可靠性在全球范围内各不相同。为了更好地理解用卫星常规监测CH排放的潜力和局限性,我们研究了哨兵 - 5P卫星上搭载的TROPOMI仪器的全球观测覆盖范围,这是目前唯一具有每日全球覆盖的卫星系统。通过遵循测量检索质量保证阈值(≥0.5),生成了一张0.1°×0.1°的全球网格地图,该地图显示了2019 - 2021年TROPOMI有效观测的平均天数。我们发现TROPOMI在旱地地区有良好的观测覆盖范围(最大值:58.6%),但在热带地区和高纬度地区覆盖范围有限(最小值:0%)。云量和太阳天顶角是影响高纬度地区观测覆盖范围的主要因素,而气溶胶光学厚度是旱地地区的主要因素。为了进一步评估卫星在检测和量化陆上石油和天然气行业CH排放方面的国家层面可靠性,我们提取了160个国家陆上石油和天然气基础设施上TROPOMI的年均观测覆盖范围(TOC)。十大石油和天然气生产国中有七个年均TOC < 10%(每年< 36天),这表明使用反演模型常规识别大型排放事件、跟踪其持续时间和量化排放率的能力有限。我们通过结合TOC和全球石油和天然气清单的不确定性进一步评估了后者的潜在性能。结果表明,在旱地和中纬度地区的国家,使用TROPOMI数据和反演模型对陆上石油和天然气源进行排放量化的准确性较高,而在热带和高纬度地区较低。因此,当前的被动遥感卫星对热带和高纬度地区国家(如加拿大、俄罗斯、巴西、挪威和委内瑞拉)的石油和天然气行业大型甲烷排放进行频繁监测的潜力较低。在这些地区应考虑采用替代方法进行常规排放监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/ac89331e1d8c/41598_2023_41914_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/f724fe3f12c0/41598_2023_41914_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/6020330e81d0/41598_2023_41914_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/ddeb9414809e/41598_2023_41914_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/819c92af6617/41598_2023_41914_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/ac89331e1d8c/41598_2023_41914_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/f724fe3f12c0/41598_2023_41914_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/89a5e3fc675c/41598_2023_41914_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/6020330e81d0/41598_2023_41914_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/ddeb9414809e/41598_2023_41914_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/819c92af6617/41598_2023_41914_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd14/10555993/ac89331e1d8c/41598_2023_41914_Fig6_HTML.jpg

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