scholarly journals Quantifying NO<sub>x</sub> emissions in Egypt using TROPOMI observations

2022 ◽  
Author(s):  
Anthony Rey-Pommier ◽  
Frédéric Chevallier ◽  
Philippe Ciais ◽  
Grégoire Broquet ◽  
Theodoros Christoudias ◽  
...  

Abstract. Urban areas and industrial facilities, which concentrate most 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 observations from the TROPOMI instrument, onboard the Sentinel-5 Precursor satellite, are used to measure nitrogen dioxide (NO2) slant column densities with a high spatial resolution. Here, we use two years of TROPOMI retrievals to map nitrogen oxides (NOx = NO + NO2) emissions in Egypt with a top-down model based on 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 OH. This sink term requires information on the lifetime of NO2, which is calculated with the use of CAMS near-real-time temperature and hydroxyl radical (OH) concentration fields. The applicability of the OH concentration field is evaluated by comparing the lifetime it provides with the lifetime inferred from the fitting of NO2 line density profiles with an exponentially modified Gaussian function. This comparison, which is conducted for 39 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 the location of the most appropriate vertical level to represent typical pollution sources in industrial areas and megacities in the Middle East. In Egypt, total derived emissions of NOx are dominated by the sink term. However, 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 produces emissions whose annual variability is consistent with the national electricity consumption. It is also able to detect lower emissions on Fridays, which are inherent to the social norm of the country, and to quantify the drop in emissions due to the COVID-19 pandemic. Overall, our indications of NOx emissions for Egypt are found to be 25.0 % higher than the CAMS-GLOB-ANT_v4.2 inventory, but significantly differ in terms of seasonality.

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2893 ◽  
Author(s):  
Willem W. Verstraeten ◽  
Klaas Folkert Boersma ◽  
John Douros ◽  
Jason E. Williams ◽  
Henk Eskes ◽  
...  

Top-down estimates of surface NOX emissions were derived for 23 European cities based on the downwind plume decay of tropospheric nitrogen dioxide (NO2) columns from the LOTOS-EUROS (Long Term Ozone Simulation-European Ozone Simulation) chemistry transport model (CTM) and from Ozone Monitoring Instrument (OMI) satellite retrievals, averaged for the summertime period (April–September) during 2013. Here we show that the top-down NOX emissions derived from LOTOS-EUROS for European urban areas agree well with the bottom-up NOX emissions from the MACC-III inventory data (R2 = 0.88) driving the CTM demonstrating the potential of this method. OMI top-down NOX emissions over the 23 European cities are generally lower compared with the MACC-III emissions and their correlation is slightly lower (R2 = 0.79). The uncertainty on the derived NO2 lifetimes and NOX emissions are on average ~55% for OMI and ~63% for LOTOS-EUROS data. The downwind NO2 plume method applied on both LOTOS-EUROS and OMI tropospheric NO2 columns allows to estimate NOX emissions from urban areas, demonstrating that this is a useful method for real-time updates of urban NOX emissions with reasonable accuracy.


2020 ◽  
Author(s):  
Prakhar Misra ◽  
Masayuki Takigawa ◽  
Pradeep Khatri ◽  
Surendra Dhaka ◽  
A. Dimri ◽  
...  

Abstract COVID-19 induced restrictions resulted in a lowered fine aerosol particle and trace gas concentration across several urban places around the world, providing a natural opportunity to study effects of anthropogenic activities on emissions of air pollutants. Impact of sudden suspension of human activities on air pollution was analyzed by studying the change in satellite retrieved NO2 concentrations and top-down NOx emission over the urban and rural areas around Delhi. NO2 was chosen for being the most indicative of emission intensity due to its short lifetime of the order of a few hours in the planetary boundary layer. We present a robust temporal comparison of Ozone Monitoring Instrument (OMI) retrieved NO2 column density during the lockdown with the counterfactual baseline concentrations, extrapolated from the long-term trend and seasonal cycle components of NO2 using observations during 2015 to 2019. NO2 columns in the urban area of Delhi experienced an anomalous relative change ranging from 60.0% decline during the Phase 1 of lockdown (March 25-April 13, 2020) to 3.4% during the post-lockdown Phase 5. In contrast, we find no substantial reduction in NO2 concentrations over the rural areas. To clarify the quantitative impact of the lockdown measures, weekly top-down NOx emissions were estimated from TROPOspheric Monitoring Instrument (TROPOMI) retrieved NO2 by accounting for horizontal advection derived from the steady state continuity equation. NOx emissions from urban areas and power plants exhibited a mean decline of 72.19% and 53.4% respectively in Phase 1 compared to the pre-lockdown business-as-usual phase. Due to absence of confounding emission source activity during lockdown, emission estimates over urban areas and power-plants were validated with respective electricity generation reports and Google’s mobility reports. A higher anomaly in emission estimates suggests that comparison of only concentration change, without accounting for the dynamical and photochemical conditions, may mislead evaluation of lockdown impact. Our results are also useful for optimizing bottom-up emission inventories.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Prakhar Misra ◽  
Masayuki Takigawa ◽  
Pradeep Khatri ◽  
Surendra K. Dhaka ◽  
A. P. Dimri ◽  
...  

AbstractCOVID-19 related restrictions lowered particulate matter and trace gas concentrations across cities around the world, providing a natural opportunity to study effects of anthropogenic activities on emissions of air pollutants. In this paper, the impact of sudden suspension of human activities on air pollution was analyzed by studying the change in satellite retrieved NO2 concentrations and top-down NOx emission over the urban and rural areas around Delhi. NO2 was chosen for being the most indicative of emission intensity due to its short lifetime of the order of a few hours in the planetary boundary layer. We present a robust temporal comparison of Ozone Monitoring Instrument (OMI) retrieved NO2 column density during the lockdown with the counterfactual baseline concentrations, extrapolated from the long-term trend and seasonal cycle components of NO2 using observations during 2015 to 2019. NO2 concentration in the urban area of Delhi experienced an anomalous relative change ranging from 60.0% decline during the Phase 1 of lockdown (March 25–April 13, 2020) to 3.4% during the post-lockdown Phase 5. In contrast, we find no substantial reduction in NO2 concentrations over the rural areas. To segregate the impact of the lockdown from the meteorology, weekly top-down NOx emissions were estimated from high-resolution TROPOspheric Monitoring Instrument (TROPOMI) retrieved NO2 by accounting for horizontal advection derived from the steady state continuity equation. NOx emissions from urban Delhi and power plants exhibited a mean decline of 72.2% and 53.4% respectively in Phase 1 compared to the pre-lockdown business-as-usual phase. Emission estimates over urban areas and power-plants showed a good correlation with activity reports, suggesting the applicability of this approach for studying emission changes. A higher anomaly in emission estimates suggests that comparison of only concentration change, without accounting for the dynamical and photochemical conditions, may mislead evaluation of lockdown impact. Our results shall also have a broader impact for optimizing bottom-up emission inventories.


2012 ◽  
Vol 12 (5) ◽  
pp. 699-706 ◽  
Author(s):  
B. S. Marti ◽  
G. Bauser ◽  
F. Stauffer ◽  
U. Kuhlmann ◽  
H.-P. Kaiser ◽  
...  

Well field management in urban areas faces challenges such as pollution from old waste deposits and former industrial sites, pollution from chemical accidents along transport lines or in industry, or diffuse pollution from leaking sewers. One possibility to protect the drinking water of a well field is the maintenance of a hydraulic barrier between the potentially polluted and the clean water. An example is the Hardhof well field in Zurich, Switzerland. This paper presents the methodology for a simple and fast expert system (ES), applies it to the Hardhof well field, and compares its performance to the historical management method of the Hardhof well field. Although the ES is quite simplistic it considerably improves the water quality in the drinking water wells. The ES knowledge base is crucial for successful management application. Therefore, a periodic update of the knowledge base is suggested for the real-time application of the ES.


Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 657
Author(s):  
Aoki Takanose ◽  
Yoshiki Atsumi ◽  
Kanamu Takikawa ◽  
Junichi Meguro

Autonomous driving support systems and self-driving cars require the determination of reliable vehicle positions with high accuracy. The real time kinematic (RTK) algorithm with global navigation satellite system (GNSS) is generally employed to obtain highly accurate position information. Because RTK can estimate the fix solution, which is a centimeter-level positioning solution, it is also used as an indicator of the position reliability. However, in urban areas, the degradation of the GNSS signal environment poses a challenge. Multipath noise caused by surrounding tall buildings degrades the positioning accuracy. This leads to large errors in the fix solution, which is used as a measure of reliability. We propose a novel position reliability estimation method by considering two factors; one is that GNSS errors are more likely to occur in the height than in the plane direction; the other is that the height variation of the actual vehicle travel path is small compared to the amount of movement in the horizontal directions. Based on these considerations, we proposed a method to detect a reliable fix solution by estimating the height variation during driving. To verify the effectiveness of the proposed method, an evaluation test was conducted in an urban area of Tokyo. According to the evaluation test, a reliability judgment rate of 99% was achieved in an urban environment, and a plane accuracy of less than 0.3 m in RMS was achieved. The results indicate that the accuracy of the proposed method is higher than that of the conventional fix solution, demonstratingits effectiveness.


Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>


2018 ◽  
Vol 173 ◽  
pp. 142-156 ◽  
Author(s):  
Marco Trombetti ◽  
Philippe Thunis ◽  
Bertrand Bessagnet ◽  
Alain Clappier ◽  
Florian Couvidat ◽  
...  

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