利用柱形和地面观测反演城市甲烷排放:一项OSSE研究

IF 3.4 2区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Jun Zhang, Jia Chen, Sanam Noreen Vardag, Haoyue Tang
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引用次数: 0

摘要

甲烷排放的规模、趋势和来源贡献仍然高度不确定,特别是在城市尺度上。在此,我们提出了一个观测系统模拟实验框架,以定量评估一个结合柱观测和地面观测的潜在测量网络,用于估算城市CH4排放。我们从多个角度对观测系统进行了评估,重点关注其估算月度和年际变化的能力,以及将排放归因于特定部门的能力。进行多元线性回归分析以确定后通量不确定性的来源。从2021年到2023年,假定甲烷排放量每年增加10%,以评估观测系统捕捉年际变化和趋势的能力。MUCCnet是世界上第一个拥有5个站点的永久性城市地面柱状温室气体网络,能够捕捉CH4排放的月和年际变化和趋势。仅使用muccnet进行的逆温排放估算存在很大的不确定性,可归因于农业部门的大量排放,而农业部门远离网络部署地点,或者由于气象条件的限制,观测范围有限。联合台网内的地面现场观测可以有效地降低这些不确定性。利用MUCCnet和地表原位网络的观测数据,利用两个平台之间的互补性,可以减少总CH4排放估算的不确定性。利用联合网络配置,可以以较低的不确定性检测CH4排放的年际变化和趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Inverse Estimation of Urban Methane Emissions Using Both Column and Surface Observations: An OSSE Study

Inverse Estimation of Urban Methane Emissions Using Both Column and Surface Observations: An OSSE Study

The magnitudes, trends, and source contributions of CH4 emissions are still highly uncertain, especially at an urban scale. Here, we present an observing system simulation experiment framework to quantitatively evaluate a potential measurement network that combines column and surface observations for estimating urban CH4 emissions. We evaluate the observing systems from multiple perspectives, focusing on their ability to estimate monthly and interannual variability, and to attribute emissions to specific sectors. A multivariate linear regression analysis was performed to identify the sources of uncertainties in the posterior fluxes. A 10% annual rise in CH4 emissions from 2021 to 2023 was assumed to evaluate the capability of the observing system to capture interannual variability and trends. We found that MUCCnet, the world's first permanent urban ground-based column greenhouse gas network with 5 stations, was able to capture the monthly and interannual variability and trends of CH4 emissions. The significant uncertainties in emission estimates from MUCCnet-only inversions can be attributed to strong emissions from the Agriculture sector, which are far from the network deployment sites, or to limited observation coverage due to meteorological conditions. Surface in situ observations within the joint network can effectively reduce these uncertainties. The uncertainties in total CH4 emission estimates can be reduced by using observations from MUCCnet and a surface in situ network, leveraging the complementarity between the two platforms. Using the joint network configuration, the interannual variability and trend of CH4 emissions can be detected with low uncertainties.

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来源期刊
Journal of Geophysical Research: Atmospheres
Journal of Geophysical Research: Atmospheres Earth and Planetary Sciences-Geophysics
CiteScore
7.30
自引率
11.40%
发文量
684
期刊介绍: JGR: Atmospheres publishes articles that advance and improve understanding of atmospheric properties and processes, including the interaction of the atmosphere with other components of the Earth system.
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