Estimation of NOx, SO2 and HCHO emissions from the megacity of Lahore, Pakistan using car MAX-DOAS observations and comparison with regional model and TROPOMI satellite data

2020 ◽  
Author(s):  
Maria Razi ◽  
Steffen Dörner ◽  
Vinod Kumar ◽  
Sebastian Donner ◽  
Noor Ahmad ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Regional Model ◽  
Atmospheric Pollutants ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Strong Emission ◽  
Geometric Approximation ◽  
Vertical Column Density ◽  
The City ◽  
Measurement Campaigns

<p>Lahore, megacity of Pakistan with more than 11 million inhabitants is a strong emission source of atmospheric pollutants. We present results of a top-down emission procedure for NOx and SO<sub>2</sub> for Lahore, based on car multi-axis differential optical absorption spectroscopy (car-MAX-DOAS) observations. Additionally, the total flux of HCHO from the city is determined which can be seen as an indicator for VOC emissions. Results from two extensive campaigns, which took place in summer 2017 and spring 2018 will be presented. From the measured spectra, we retrieve the vertically integrated concentration (the so-called tropospheric vertical column density, VCD) of the trace gases along the driving route by using the so-called geometric approximation method. By combining these observations with ECMWF Re-Analysis wind data, the total fluxes of NO<sub>x</sub>, SO<sub>2</sub> and HCHO from the city of Lahore are estimated. From both measurement campaigns, we also analyzed the seasonal variability of the above-mentioned species.</p><p>Derived NOx and SO<sub>2</sub> emissions are compared to the bottom-up emission inventory EDGAR. Spatial disributions of the tropospheric NO<sub>2</sub> and SO<sub>2</sub> VCDs observed by car MAX-DOAS are compared with those simulated using a coupled regional-global model system (MECO(n)). We find that, the model is able to account for the spatial variablity but the VCDs are systematically underestimated by the regional model. Finally, derived NOx emissions are also compared to the emissions estimated from TROPOMI satellite observations.</p>

scholarly journals Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B

2014 ◽  
Vol 7 (3) ◽  
pp. 3021-3073 ◽  
Author(s):  
M. Grossi ◽  
P. Valks ◽  
D. Loyola ◽  
B. Aberle ◽  
S. Slijkhuis ◽  
...  
Keyword(s):  
Water Vapour ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Vertical Column ◽  
Data Set ◽  
Vertical Column Density ◽  
Data Processor ◽  
Climate Analysis ◽  
Total Column

Abstract. The knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors and perform an extensive inter-comparison and validation in order to estimate their absolute accuracy and long-term stability. We use the recently reprocessed data sets retrieved by the GOME-2 instruments aboard EUMETSAT's MetOp-A and MetOp-B satellites and generated by DLR in the framework of the O3M-SAF using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines H2O/O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. We evaluate the overall consistency between about 8 months measurements from the newer GOME-2 instrument on the MetOp-B platform with the GOME-2/MetOp-A data in the overlap period. Furthermore, we compare GOME-2 results with independent TCWV data from ECMWF and with SSMIS satellite measurements during the full period January 2007–August 2013 and we perform a validation against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project. We find global mean biases as small as ± 0.03 g cm−2 between GOME-2A and all other data sets. The combined SSM/I-MERIS sample is typically drier than the GOME-2 retrievals (−0.005 g cm−2), while on average GOME-2 data overestimate the SSMIS measurements by only 0.028 g cm−2. However, the size of some of these biases are seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, but are not as evident in the validation with the ECMWF and the SSM/I + MERIS data. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three independent data sets, especially for land areas, although some discrepancies over ocean and over land areas with high humidity and a relatively large surface albedo are also present.

scholarly journals Intercomparison of four airborne imaging DOAS systems for tropospheric NO<sub>2</sub> mapping – the AROMAPEX campaign

2019 ◽  
Vol 12 (1) ◽  
pp. 211-236 ◽  
Author(s):  
Frederik Tack ◽  
Alexis Merlaud ◽  
Andreas C. Meier ◽  
Tim Vlemmix ◽  
Thomas Ruhtz ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Wavelength Region ◽  
Correlation Coefficients ◽  
Horizontal Distribution ◽  
Primary Objective ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Vertical Column ◽  
Airborne Imaging ◽  
The City

Abstract. We present an intercomparison study of four airborne imaging DOAS instruments, dedicated to the retrieval and high-resolution mapping of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs). The AROMAPEX campaign took place in Berlin, Germany, in April 2016 with the primary objective to test and intercompare the performance of experimental airborne imagers. The imaging DOAS instruments were operated simultaneously from two manned aircraft, performing synchronised flights: APEX (VITO–BIRA-IASB) was operated from DLR's DO-228 D-CFFU aircraft at 6.2 km in altitude, while AirMAP (IUP-Bremen), SWING (BIRA-IASB), and SBI (TNO–TU Delft–KNMI) were operated from the FUB Cessna 207T D-EAFU at 3.1 km. Two synchronised flights took place on 21 April 2016. NO2 slant columns were retrieved by applying differential optical absorption spectroscopy (DOAS) in the visible wavelength region and converted to VCDs by the computation of appropriate air mass factors (AMFs). Finally, the NO2 VCDs were georeferenced and mapped at high spatial resolution. For the sake of harmonising the different data sets, efforts were made to agree on a common set of parameter settings, AMF look-up table, and gridding algorithm. The NO2 horizontal distribution, observed by the different DOAS imagers, shows very similar spatial patterns. The NO2 field is dominated by two large plumes related to industrial compounds, crossing the city from west to east. The major highways A100 and A113 are also identified as line sources of NO2. Retrieved NO2 VCDs range between 1×1015 molec cm−2 upwind of the city and 20×1015 molec cm−2 in the dominant plume, with a mean of 7.3±1.8×1015 molec cm−2 for the morning flight and between 1 and 23×1015 molec cm−2 with a mean of 6.0±1.4×1015 molec cm−2 for the afternoon flight. The mean NO2 VCD retrieval errors are in the range of 22 % to 36 % for all sensors. The four data sets are in good agreement with Pearson correlation coefficients better than 0.9, while the linear regression analyses show slopes close to unity and generally small intercepts.

scholarly journals High-resolution airborne imaging DOAS measurements of NO<sub>2</sub> above Bucharest during AROMAT

2017 ◽  
Vol 10 (5) ◽  
pp. 1831-1857 ◽  
Author(s):  
Andreas Carlos Meier ◽  
Anja Schönhardt ◽  
Tim Bösch ◽  
Andreas Richter ◽  
André Seyler ◽  
...  
Keyword(s):  
Surface Properties ◽  
Urban Areas ◽  
Strong Dependence ◽  
Horizontal Distribution ◽  
Optical Absorption Spectroscopy ◽  
Surface Reflectance ◽  
Emission Rates ◽  
Vertical Column ◽  
Airborne Imaging ◽  
The City

Abstract. In this study we report on airborne imaging DOAS measurements of NO2 from two flights performed in Bucharest during the AROMAT campaign (Airborne ROmanian Measurements of Aerosols and Trace gases) in September 2014. These measurements were performed with the Airborne imaging Differential Optical Absorption Spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP) and provide nearly gapless maps of column densities of NO2 below the aircraft with a high spatial resolution of better than 100 m. The air mass factors, which are needed to convert the measured differential slant column densities (dSCDs) to vertical column densities (VCDs), have a strong dependence on the surface reflectance, which has to be accounted for in the retrieval. This is especially important for measurements above urban areas, where the surface properties vary strongly. As the instrument is not radiometrically calibrated, we have developed a method to derive the surface reflectance from intensities measured by AirMAP. This method is based on radiative transfer calculation with SCIATRAN and a reference area for which the surface reflectance is known. While surface properties are clearly apparent in the NO2 dSCD results, this effect is successfully corrected for in the VCD results. Furthermore, we investigate the influence of aerosols on the retrieval for a variety of aerosol profiles that were measured in the context of the AROMAT campaigns. The results of two research flights are presented, which reveal distinct horizontal distribution patterns and strong spatial gradients of NO2 across the city. Pollution levels range from background values in the outskirts located upwind of the city to about 4  ×  1016 molec cm−2 in the polluted city center. Validation against two co-located mobile car-DOAS measurements yields good agreement between the datasets, with correlation coefficients of R =  0.94 and R =  0.85, respectively. Estimations on the NOx emission rate of Bucharest for the two flights yield emission rates of 15.1 ± 9.4 and 13.6 ± 8.4 mol s−1, respectively.

Quantification of Nitrogen Dioxide and Sulfur Dioxide emissions from Bucharest using a mobile-DOAS setup

2020 ◽  
Author(s):  
Sebastian Iancu
Keyword(s):  
Sulfur Dioxide ◽  
Nitrogen Dioxide ◽  
Human Life ◽  
Scattered Light ◽  
Fine Tuning ◽  
Atmospheric Composition ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Airborne Measurements ◽  
The City

&lt;p&gt;Atmospheric pollution has a well-known impact on the human life, thus observing the emissions of trace gases is an important part of monitoring the atmospheric composition. This paper aims to determine the vertical column densities (VCDs) of Nitrogen Dioxide (NO&lt;sub&gt;2&lt;/sub&gt;) and Sulfur Dioxide (SO&lt;sub&gt;2&lt;/sub&gt;). These quantities will be used to calculate emissions of these pollutants quantified using a ground based mobile remote sensing technique that relies on scattered light DOAS (Differential Optical Absorption Spectroscopy) measurements. This method will be implemented using the SWING (Small Whiskbroom Imager for atmospheric compositioN monitorinG). The instrument is designed to perform airborne measurements, but for the purpose of this paper it was adapted for ground-based use by the National Institute for Aerospace Research (INCAS) in Bucharest, Romania. The source aimed to be quantified is the city of Bucharest, specifically the total emissions generated by the traffic and industry within the city. The measurements will be performed during the Spring of 2020 between February and April. The experimental setup consists of the SWING that will be mounted on the roof of a car, which allows to perform measurements along the ring road of Bucharest. There will be presented results from several days of measurements from a total of 150 hours of driving in terms of differential slant column densities (DSCDs), vertical column densities (VCDs) and quantified emissions of NO&amp;#173;&lt;sub&gt;2&lt;/sub&gt; and SO&lt;sub&gt;2&lt;/sub&gt;. This study will also be used for the fine tuning of the SWING operational parameters for use on UAV platforms in future measurement campaigns.&lt;/p&gt;

scholarly journals Shipborne MAX-DOAS measurements for validation of TROPOMI NO<sub>2</sub> products

2020 ◽  
Vol 13 (3) ◽  
pp. 1413-1426 ◽  
Author(s):  
Ping Wang ◽  
Ankie Piters ◽  
Jos van Geffen ◽  
Olaf Tuinder ◽  
Piet Stammes ◽  
...  
Keyword(s):  
Column Density ◽  
Transport Model ◽  
Massively Parallel ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Chemistry Transport Model ◽  
The Pacific ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
Good Agreement

Abstract. Tropospheric NO2 and stratospheric NO2 vertical column densities are important TROPOspheric Monitoring Instrument (TROPOMI) data products. In order to validate the TROPOMI NO2 products, KNMI Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments have measured NO2 on ship cruises over the Atlantic and the Pacific oceans. The MAX-DOAS instruments have participated in five cruises on board RV Sonne (in 2017 and 2019) and RV Maria S. Merian (in 2018). The MAX-DOAS measurements were acquired over 7 months and spanned about 90∘ in latitude and 300∘ in longitude. During the cruises aerosol measurements from Microtops sun photometers were also taken. The MAX-DOAS measured stratospheric NO2 columns between 1.5×1015 and 3.5×1015 molec cm−2 and tropospheric NO2 up to 0.6×1015 molec cm−2. The MAX-DOAS stratospheric NO2 vertical column densities have been compared with TROPOMI stratospheric NO2 vertical column densities and the stratospheric NO2 vertical column densities simulated by the global chemistry Transport Model, version 5, Massively Parallel model (TM5-MP). Good correlation is found between the MAX-DOAS and TROPOMI and TM5 stratospheric NO2 vertical column densities, with a correlation coefficient of 0.93 or larger. The TROPOMI and TM5 stratospheric NO2 vertical column densities are about 0.4×1015 molec cm−2 (19 %) higher than the MAX-DOAS measurements. The TROPOMI tropospheric NO2 also has good agreement with the MAX-DOAS measurements. The tropospheric NO2 vertical column density is as low as 0.5×1015 molec cm−2 over remote oceans.

scholarly journals Rapid methods for inversion of MAXDOAS elevation profiles to surface-associated box concentrations, visibility, and heights: application to analysis of Arctic BrO events

2010 ◽  
Vol 3 (6) ◽  
pp. 4645-4674 ◽  
Author(s):  
D. Donohoue ◽  
D. Carlson ◽  
W. R. Simpson
Keyword(s):  
Column Density ◽  
Surface Concentration ◽  
Trace Gas ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Data Set ◽  
Profile Method ◽  
Remote Sensing Technique ◽  
Vertical Column Density ◽  
Gas Layer

Abstract. Multiple Axis Differential Optical Absorption Spectroscopy (MAXDOAS) is a remote sensing technique that measures surface-associated trace gas profiles using simple automated instrumentation that requires very low power and is deployable at remote sites. However, the analysis of MAXDOAS data is complex and often cannot be applied rapidly or consistently over long measurement periods. Here we present three transparent methods to analyze MAXDOAS data. The box profile method finds the best trace gas layer height and surface-associated vertical column density (VCD) to simultaneously fit oxygen collisional dimer (O4) and trace gas differential slant column density (dSCD) observations. The elevated viewing method estimates the surface-associated VCD from observations at high view elevations, such as 10° and 20°. The horizon viewing method estimates the surface concentration of a trace gas by using near-horizon view trace gas and O4 data. We apply these methods to a two-month data set and show that the methods retrieve information 80% of the time and provides a consistent time series. Surface-associated trace gas VCD observations by the elevated viewing method correlate (r2 > 0.93) with the box profile method with slopes within 15% of unity. Surface-associated concentration observations from the horizon viewing method correlate well (r2 > 0.90) with the box profile method and a slope within 4% of unity. Application of these retrieval methods to UV-absorbing trace gases other than BrO is straightforward, and application in other spectral regions is discussed. These methods provide rapid and comprehensive inversions of MAXDOAS spectral data that are useful during field campaigns, as well as, verification of more complex (e.g. optimal estimate inversion) methods.

scholarly journals Quantitative bias estimates for tropospheric NO<sub>2</sub> columns retrieved from SCIAMACHY, OMI, and GOME-2 using a common standard for East Asia

2012 ◽  
Vol 5 (10) ◽  
pp. 2403-2411 ◽  
Author(s):  
H. Irie ◽  
K. F. Boersma ◽  
Y. Kanaya ◽  
H. Takashima ◽  
X. Pan ◽  
...  
Keyword(s):  
Regression Line ◽  
Correlation Coefficients ◽  
Satellite Observation ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Vertical Column ◽  
Vertical Column Density ◽  
Satellite Sensors ◽  
Single Set ◽  
Japan And China

Abstract. For the intercomparison of tropospheric nitrogen dioxide (NO2) vertical column density (VCD) data from three different satellite sensors (SCIAMACHY, OMI, and GOME-2), we use a common standard to quantitatively evaluate the biases for the respective data sets. As the standard, a regression analysis using a single set of collocated ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations at several sites in Japan and China from 2006–2011 is adopted. Examinations of various spatial coincidence criteria indicates that the slope of the regression line can be influenced by the spatial distribution of NO2 over the area considered. While the slope varies systematically with the distance between the MAX-DOAS and satellite observation points around Tokyo in Japan, such a systematic dependence is not clearly seen and correlation coefficients are generally higher in comparisons at sites in China. On the basis of these results, we focus mainly on comparisons over China and estimate the biases in SCIAMACHY, OMI, and GOME-2 data (TM4NO2A and DOMINO version 2 products) against the MAX-DOAS observations to be −5 ± 14%, −10 ± 14%, and +1 ± 14%, respectively, which are all small and insignificant. We suggest that these small biases now allow for analyses combining these satellite data for air quality studies, which are more systematic and quantitative than previously possible.

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