Abstract. Nitrogen oxides (NOx = NO + NO2) are air pollutants which are co-emitted with CO2 during high-temperature combustion processes. Monitoring NOx emissions is crucial for assessing air quality and for providing proxy estimates of CO2 emissions. Satellite observations, such as those from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5P satellite, provide global coverage at high temporal resolution. However, satellites measure only NO2, necessitating a conversion to NOx. Previous studies have applied a constant NO2-to-NOx conversion factor. In this paper, we develop a more realistic model for NO2-to-NOx conversion and apply it to TROPOMI data of 2020 and 2021. To achieve this, we analysed plume-resolving simulations from the MicroHH large-eddy simulation model with chemistry for the Bełchatów (PL), Jänschwalde (DE), Matimba (ZA) and Medupi (ZA) power plants, as well as a metallurgical plant in Lipetsk (RU). We used the cross-sectional flux method to calculate NO, NO2 and NOx line densities from simulated NO and NO2 columns and derived NO2-to-NOx conversion factors as a function of the time since emission. Since the method of converting NO2 to NOx presented in this paper assumes steady-state conditions and that the conversion factors can be modelled by a negative exponential function, we validated the conversion factors using the same MicroHH data. Finally, we applied the derived conversion factors to TROPOMI NO2 observations of the same sources. The validation of the NO2-to-NOx conversion factors shows that they can account for the NOx chemistry in plumes, in particular for the conversion between NO and NO2 near the source and for the chemical loss of NOx further downstream. When applying these time-since-emission-dependent conversion factors, biases in NOx emissions estimated from TROPOMI NO2 images are greatly reduced from between −50 % and −42 % to between only −9.5 % and −0.5 % in comparison with reported emissions. Single-overpass estimates can be quantified with an uncertainty of 20 %–27 %, while annual NOx emission estimates have uncertainties in the range of 4 %–21 % but are highly dependent on the number of successful retrievals. Although more simulations covering a wider range of meteorological and trace gas background conditions will be needed to generalise the approach, this study marks an important step towards a consistent, uniform, high-resolution and near-real-time estimation of NOx emissions – especially with regard to upcoming NO2-monitoring satellites such as Sentinel-4, Sentinel-5 and CO2M.

中文翻译：

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用于量化 NO2 卫星观测点源 NOx 排放的轻量级 NO2 到 NOx 转换模型


摘要。氮氧化物（NOx = NO + NO2）是在高温燃烧过程中与CO2共同排放的空气污染物。监测氮氧化物排放对于评估空气质量和提供二氧化碳排放量的代理估算至关重要。卫星观测，例如 Sentinel-5P 卫星上的对流层监测仪器 (TROPOMI) 的观测，可提供高时间分辨率的全球覆盖。然而，卫星仅测量二氧化氮，因此需要转换为氮氧化物。先前的研究应用了恒定的 NO2 至 NOx 转换因子。在本文中，我们开发了一个更真实的 NO2 到 NOx 转化模型，并将其应用于 2020 年和 2021 年的 TROPOMI 数据。为了实现这一目标，我们利用化学方法分析了 MicroHH 大涡模拟模型的烟羽解析模拟， Bełchatów (PL)、Jänschwalde (DE)、Matimba (ZA) 和 Medupi (ZA) 发电厂，以及利佩茨克 (RU) 的冶金厂。我们使用横截面通量方法从模拟的 NO 和 NO2 柱中计算 NO、NO2 和 NOx 线密度，并导出 NO2 到 NOx 的转换因子，作为排放后时间的函数。由于本文提出的将 NO2 转化为 NOx 的方法假设稳态条件，并且转换因子可以通过负指数函数建模，因此我们使用相同的 MicroHH 数据验证了转换因子。最后，我们将导出的转换因子应用于相同来源的 TROPOMI NO2 观测结果。 NO2 到 NOx 转换因子的验证表明，它们可以解释羽流中的 NOx 化学反应，特别是源头附近 NO 和 NO2 之间的转化以及下游 NOx 的化学损失。 当应用这些与排放时间相关的转换因子时，与报告的排放量相比，TROPOMI NO2 图像估计的氮氧化物排放量的偏差从 -50% 到 -42% 之间大大减少到仅 -9.5% 到 -0.5% 之间。单立交桥估算的量化不确定度为 20%–27%，而年度 NOx 排放估算的不确定度为 4%–2​​1%，但高度依赖于成功反演的数量。尽管需要进行更多涵盖更广泛的气象和微量气体背景条件的模拟来推广该方法，但这项研究标志着朝着一致、统一、高分辨率和近实时的氮氧化物排放估算迈出了重要一步——尤其是关于即将推出的 NO2 监测卫星，例如 Sentinel-4、Sentinel-5 和 CO2M。