欧洲钢铁厂一氧化碳排放量天基估算与报告估算的比较

IF 5.2 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Atmospheric Chemistry and Physics Pub Date : 2024-06-19 DOI:10.5194/egusphere-2024-1561
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, Ilse Aben
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引用次数: 0

摘要

摘要。我们利用一氧化碳(CO)的卫星观测数据来估算欧洲大陆CO排放量最高的点源--欧洲综合钢铁厂的CO排放量。我们利用对流层监测仪器(TROPOMI)2019 年的观测数据,对 21 家工厂的排放量进行了分析反演估算。作为先前的排放量,我们使用了这些设施向欧洲污染物释放和转移登记册(E-PRTR)报告的数值。这些报告的排放量在估算方法上有所不同,包括测量和计算。通过天气研究与预测 (WRF) 模型,我们使用不同的传输设置执行了一系列模拟,以最好地复制每天和每个地点的观测排放羽流。将基于反演的排放估算值与 E-PRTR 报告进行比较,发现有九个工厂的估算值在不确定范围内一致。对于其余工厂,我们发现排放率普遍低于报告值。除少数低排放或沿海地点外,我们的后验排放估计值受到卫星观测的良好约束(90% 的工厂平均核敏感度高于 0.7)。我们发现我们的反演结果与我们使用横截面通量(CSF)方法估算的七个最强排放工厂的排放量之间存在一致性,这进一步增强了我们对反演估算结果的信心。最后,对于报告排放率年际变化较大或报告排放率与我们的后验估计值差异较大的四家工厂,我们将分析延伸至 2020 年。无论是观测到的一氧化碳浓度,还是我们的反演结果,都没有发现排放率发生强烈变化的证据。这说明了如何利用卫星来识别报告排放量中潜在的不确定性。
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Comparing space-based to reported carbon monoxide emission estimates for Europe’s iron & steel plants
Abstract. We use satellite observations of carbon monoxide (CO) to estimate CO emissions from European integrated iron & steel plants, the continent’s highest emitting CO point sources. We perform analytical inversions to estimate emissions from 21 individual plants using observations from the Tropospheric Monitoring Instrument (TROPOMI) for 2019. As prior emissions, we use values reported by the facilities to the European Pollutant Release and Transfer Register (E-PRTR). These reported emissions vary in estimation methodology, including both measurements and calculations. With the Weather Research and Forecasting (WRF) model, we perform an ensemble of simulations with different transport settings to best replicate the observed emission plumes for each day and site. Comparing the inversion-based emission estimates to the E-PRTR reports, nine of the plants agree within uncertainties. For the remaining plants, we generally find lower emission rates than reported. Our posterior emission estimates are well-constrained by the satellite observations (90 % of the plants have averaging kernel sensitivities above 0.7) except for a few low-emitting or coastal sites. We find agreement between our inversion results and emissions we estimate using the Cross-Sectional Flux (CSF) method for the seven strongest-emitting plants, building further confidence in the inversion estimates. Finally, for four plants with large year-to-year variability in reported emission rates or large differences between the reported emission rate and our posterior estimate, we extend our analysis to 2020. We find no evidence in either the observed carbon monoxide concentrations or our inversion results for strong changes in emission rates. This demonstrates how satellites can be used to identify potential uncertainties in reported emissions.
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来源期刊
Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics 地学-气象与大气科学
CiteScore
10.70
自引率
20.60%
发文量
702
审稿时长
6 months
期刊介绍: Atmospheric Chemistry and Physics (ACP) is a not-for-profit international scientific journal dedicated to the publication and public discussion of high-quality studies investigating the Earth''s atmosphere and the underlying chemical and physical processes. It covers the altitude range from the land and ocean surface up to the turbopause, including the troposphere, stratosphere, and mesosphere. The main subject areas comprise atmospheric modelling, field measurements, remote sensing, and laboratory studies of gases, aerosols, clouds and precipitation, isotopes, radiation, dynamics, biosphere interactions, and hydrosphere interactions. The journal scope is focused on studies with general implications for atmospheric science rather than investigations that are primarily of local or technical interest.
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