Quantifying NO_x emissions in Egypt using TROPOMI observations

Abstract

Abstract. Urban areas and industrial facilities, which concentrate the majority of human activity and industrial production, are major sources of air pollutants, with serious implications for human health and global climate. For most of these pollutants, emission inventories are often highly uncertain, especially in developing countries. Spaceborne measurements from the TROPOMI instrument, on board the Sentinel-5 Precursor satellite, are used to retrieve nitrogen dioxide (NO2) column densities at high spatial resolution. Here, we use 2 years of TROPOMI retrievals to map nitrogen oxide (NOx = NO + NO2) emissions in Egypt with a top-down approach using the continuity equation in steady state. Emissions are expressed as the sum of a transport term and a sink term representing the three-body reaction comprising NO2 and hydroxyl radical (OH). This sink term requires information on the lifetime of NO2, which is calculated with the use of the CAMS near-real-time temperature and OH concentration fields. We compare this derived lifetime with the lifetime inferred from the fitting of NO2 line density profiles in large plumes with an exponentially modified Gaussian function. This comparison, which is conducted for different samples of NO2 patterns above the city of Riyadh, provides information on the reliability of the CAMS near-real-time OH concentration fields; it also provides some hint on the vertical levels that best represent typical pollution sources in industrial areas and megacities in the Middle East region. In Egypt, total emissions of NOx are dominated by the sink term, but they can be locally dominated by wind transport, especially along the Nile where human activities are concentrated. Megacities and industrial regions clearly appear as the largest sources of NOx emissions in the country. Our top-down model infers emissions with a marked annual variability. By looking at the spatial distribution of emissions at the scale of different cities with different industrial characteristics, it appears that this variability is consistent with national electricity consumption. We detect lower emissions on Fridays, which are inherent to the social norm of the country, and quantify the drop in emissions in 2020 due to the COVID-19 pandemic. Overall, our estimations of NOx emissions for Egypt are 7.0 % higher than the CAMS-GLOB-ANT_v4.2 inventory and significantly differ in terms of seasonality.

Ozone production over arid regions: insights into meteorological and chemical drivers

“…The seasonality of ozone production is now compared to variations in meteorological parameters during the summer and winter. Beginning with temperature (figures S11), hyper-arid and arid cities typically have higher summer temperatures than semi-arid cities, which increases energy demand for cooling [72,73]. Conversely, their winter temperatures are not as low as those in the semi-arid regions.…”

Nitrogen oxides emissions from selected cities in North America, Europe, and East Asia observed by TROPOMI before and after the COVID-19 pandemic

“…Despite the similarity between Eq. 1 and its counterpart in the flux divergence literature (Beirle et al, 2019(Beirle et al, , 2021Liu et al, 2021;Dix et al, 2022;de Foy and Schauer, 2022;Rey-Pommier et al, 2022;Veefkind et al, 2023), Eq. 1 accounts for the impacts from the horizontal divergence of wind and topography to the estimated emission, both of which are not included in the flux divergence equation and scale linearly with column amounts, Ω.…”

“…Substantial efforts among the research community have been devoted to characterizing the NO x emission responses in the early phase of the pandemic (Gkatzelis et al, 2021, and references therein). Satellite-observed NO 2 tropospheric column amounts have been used to infer COVID-induced NO x emission perturbations through chemical transport models (CTMs) (Miyazaki et al, 2020;Ding et al, 2020;Riess et al, 2022;Kang et al, 2022), fitting of plume dispersion or box models (Sun et al, 2021;Lange et al, 2022;Dammers et al, 2022;Xue et al, 2022;Godłowska et al, 2023;Zhang et al, 2023), and calculation of the divergence of horizontal NO 2 flux (the flux divergence approach hereafter, de Foy and Schauer, 2022; Dix et al, 2022;Rey-Pommier et al, 2022;Chen et al, 2023). Each approach comes with its own strengths and limitations.…”

Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique

“…com/world-cities/riyadh-population, last access: 29 March 2022), and strong point sources of NO x close to the metropolitan area, such as a cement plant and power plants. Moreover, Riyadh is remote from other sources and has favorable weather conditions for space-based measurements, such as low cloud cover and high surface albedo Rey-Pommier et al, 2022). The two typical wind regimes present in Riyadh favor the applicability of the windassigned anomaly method and are another reason for choosing this region for this work.…”