scholarly journals The Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaigns

2020 ◽  
Author(s):  
Alexis Merlaud ◽  
Livio Belegante ◽  
Daniel-Eduard Constantin ◽  
Mirjam Den Hoed ◽  
Andreas Carlos Meier ◽  
...  
Keyword(s):  
Power Plants ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Trace Gases ◽  
Vertical Column ◽  
Airborne Measurements ◽  
Tropospheric No2 ◽  
Order Of Magnitude ◽  
Vertical Column Density ◽  
Optimal Target

Abstract. The Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaigns took place in Romania in September 2014 and August 2015. They focused on two sites: the Bucharest urban area and the power plants in the Jiu Valley. Their main objectives were to test recently developed airborne observation systems dedicated to air quality studies and to verify the concept of such campaigns in support of the validation of spaceborne atmospheric missions such as TROPOspheric Monitoring Instrument (TROPOMI)/Sentinel-5 Precursor (S5P). We show that tropospheric NO2 vertical column density (VCD) measurements using airborne mapping instruments are valuable for satellite validation. The signal to noise ratio of the airborne NO2 measurements is one order of magnitude higher than its spaceborne counterpart when the airborne measurements are averaged at the TROPOMI pixel scale. A significant source of comparison error appears to be the time variation of the NO2 VCDs during a flight, which we estimated at about 4 x 1015 molec cm-2 in the AROMAT conditions. Considering the random error of the TROPOMI tropospheric NO2 VCD (σ), the dynamic range of the NO2 VCDs field extends from detection limit up to 37σ (2.6 x 1016 molec cm-2) or 29σ (2 x 1016 molec cm-2) for Bucharest and the Jiu Valley, respectively. For the two areas, we simulate validation exercises of the TROPOMI tropospheric NO2 product using airborne measurements. These simulations indicate that we can closely approach the TROPOMI optimal target accuracy of 25 % by adding NO2 and aerosol profile information to the mapping data, which constrains the investigated accuracy within 28 %. In addition to NO2, we also measured significant amounts of SO2 in the Jiu Valley, as well as a hotspot of H2CO in the center of Bucharest. For these two species, we conclude that the best validation strategy would consist in deploying ground-based measurement systems at key locations which the AROMAT observations help identify.

scholarly journals Satellite validation strategy assessments based on the AROMAT campaigns

2020 ◽  
Vol 13 (10) ◽  
pp. 5513-5535 ◽  
Author(s):  
Alexis Merlaud ◽  
Livio Belegante ◽  
Daniel-Eduard Constantin ◽  
Mirjam Den Hoed ◽  
Andreas Carlos Meier ◽  
...  
Keyword(s):  
Power Plants ◽  
Dynamic Range ◽  
So2 Emissions ◽  
Large Power ◽  
Airborne Measurements ◽  
Satellite Validation ◽  
Tropospheric No2 ◽  
Comparison Error ◽  
Airborne Mapping ◽  
Validation Strategy

Abstract. The Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaigns took place in Romania in September 2014 and August 2015. They focused on two sites: the Bucharest urban area and large power plants in the Jiu Valley. The main objectives of the campaigns were to test recently developed airborne observation systems dedicated to air quality studies and to verify their applicability for the validation of space-borne atmospheric missions such as the TROPOspheric Monitoring Instrument (TROPOMI)/Sentinel-5 Precursor (S5P). We present the AROMAT campaigns from the perspective of findings related to the validation of tropospheric NO2, SO2, and H2CO. We also quantify the emissions of NOx and SO2 at both measurement sites. We show that tropospheric NO2 vertical column density (VCD) measurements using airborne mapping instruments are well suited for satellite validation in principle. The signal-to-noise ratio of the airborne NO2 measurements is an order of magnitude higher than its space-borne counterpart when the airborne measurements are averaged at the TROPOMI pixel scale. However, we show that the temporal variation of the NO2 VCDs during a flight might be a significant source of comparison error. Considering the random error of the TROPOMI tropospheric NO2 VCD (σ), the dynamic range of the NO2 VCDs field extends from detection limit up to 37 σ (2.6×1016 molec. cm−2) and 29 σ (2×1016 molec. cm−2) for Bucharest and the Jiu Valley, respectively. For both areas, we simulate validation exercises applied to the TROPOMI tropospheric NO2 product. These simulations indicate that a comparison error budget closely matching the TROPOMI optimal target accuracy of 25 % can be obtained by adding NO2 and aerosol profile information to the airborne mapping observations, which constrains the investigated accuracy to within 28 %. In addition to NO2, our study also addresses the measurements of SO2 emissions from power plants in the Jiu Valley and an urban hotspot of H2CO in the centre of Bucharest. For these two species, we conclude that the best validation strategy would consist of deploying ground-based measurement systems at well-identified locations.

scholarly journals Highly resolved global distribution of tropospheric NO<sub>2</sub> using GOME narrow swath mode data

2004 ◽  
Vol 4 (2) ◽  
pp. 1665-1689 ◽  
Author(s):  
S. Beirle ◽  
U. Platt ◽  
M. Wenig ◽  
T. Wagner
Keyword(s):  
Spatial Resolution ◽  
Power Plants ◽  
General Information ◽  
Global Distribution ◽  
Seasonal Effects ◽  
Standard Size ◽  
Vertical Column ◽  
Large Power ◽  
Tropospheric No2 ◽  
Long Time

Abstract. The Global Ozone Monitoring Experiment (GOME, since 1995) allows the retrieval of global total column densities of atmospheric trace gases, including NO2. Tropospheric vertical column densities (VCDs) are derived by estimating the stratospheric fraction from measurements over the remote ocean. Mean maps of tropospheric NO2 VCDs derived from GOME clearly allow to detect regions with enhanced industrial activity, but the standard spatial resolution of the GOME ground pixels (320×40 km2) is insufficient to resolve regional trace gas distributions or individual cities. Within the nominal GOME operation, every tenth day measurements in the so called narrow swath mode are executed with a much better spatial resolution (80×40 km2). Though the global coverage of these data is – due to the narrow swath – rather poor, the mean distribution over several years (1997–2001) allows to construct a much more detailed picture of the global NO2 distribution, especially if corrected for seasonal effects. It vividly illustrates the shortcomings of the standard size GOME pixels and reveals an unprecedented wealth of details in the global distribution of tropospheric NO2. Sharply localised spots of enhanced NO2 VCD can be associated directly to cities, large power plants, and heavy industry centers. The long time series of GOME data allows a quantitative comparison of the narrow swath mode data to the nominal resolution that holds general information on the dependency of NO2 VCDs on pixel size. This is important for new instruments like SCIAMACHY (launched March 2002 on ENVISAT) or OMI and GOME II (to be launched 2004 and 2005, respectively) with an improved spatial resolution.

scholarly journals Lockdowns Save People from Air Pollution: Evidence from Daily Global Tropospheric NO2 Satellite Data

2021 ◽  
Vol 13 (21) ◽  
pp. 11777
Author(s):  
Sunbin Yoo ◽  
Shunsuke Managi
Keyword(s):  
Air Pollution ◽  
Global Health ◽  
Satellite Data ◽  
Health Benefits ◽  
The United States ◽  
Vertical Column ◽  
Statistical Life ◽  
Policy Interventions ◽  
Tropospheric No2 ◽  
Vertical Column Density

Motivated by the global fear of the Coronavirus-19 (COVID-19) pandemic, we investigated whether lockdowns save people from air pollution, notably from Nitrogen Dioxide (NO2). Using daily satellite data from the National Aeronautics and Space Administration (NASA), we first found that the global NO2 tropospheric vertical column density (TVCD) decreased by 16.5% after the Coronavirus-19 (COVID-19) outbreak. Then, we calculated the global health benefits, as the monetized value of life, using the value of a statistical life (VSL). The total global health benefits were approximately 8.73 trillion USD, accounting for 10% of the global GDP; such benefits would be the largest in China, followed by the United States, Japan and Germany. Our results suggest that lockdowns may bring benefits to countries that policy interventions cannot easily bring, thus highlighting the importance of social distancing.

scholarly journals MAX-DOAS NO<sub>2</sub> observations over Guangzhou, China; ground-based and satellite comparisons

2018 ◽  
Vol 11 (4) ◽  
pp. 2239-2255 ◽  
Author(s):  
Theano Drosoglou ◽  
Maria Elissavet Koukouli ◽  
Natalia Kouremeti ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
...  
Keyword(s):  
Time Window ◽  
Correlation Coefficients ◽  
Urban Site ◽  
Reference Case ◽  
Vertical Column ◽  
Time Period ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
Satellite Sensors ◽  
Academy Of Sciences

Abstract. In this study, the tropospheric NO2 vertical column density (VCD) over an urban site in Guangzhou megacity in China is investigated by means of MAX-DOAS measurements during a campaign from late March 2015 to mid-March 2016. A MAX-DOAS system was deployed at the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences and operated there for about 1 year, during the spring and summer months. The tropospheric NO2 VCDs retrieved by the MAX-DOAS are presented and compared with space-borne observations from GOME-2/MetOp-A, GOME-2/MetOp-B and OMI/Aura satellite sensors. The comparisons reveal good agreement between satellite and MAX-DOAS observations over Guangzhou, with correlation coefficients ranging between 0.795 for GOME-2B and 0.996 for OMI. However, the tropospheric NO2 loadings are underestimated by the satellite sensors on average by 25.1, 10.3 and 5.7 %, respectively, for OMI, GOME-2A and GOME-2B. Our results indicate that GOME-2B retrievals are closer to those of the MAX-DOAS instrument due to the lower tropospheric NO2 concentrations during the days with valid GOME-2B observations. In addition, the effect of the main coincidence criteria is investigated, namely the cloud fraction (CF), the distance (d) between the satellite pixel center and the ground-based measurement site, as well as the time period within which the MAX-DOAS data are averaged around the satellite overpass time. The effect of CF and time window criteria is more profound on the selection of OMI overpass data, probably due to its smaller pixel size. The available data pairs are reduced to half and about one-third for CF  ≤  0.3 and CF  ≤  0.2, respectively, while, compared to larger CF thresholds, the correlation coefficient is improved to 0.996 from about 0.86, the slope value is very close to unity ( ∼  0.98) and the mean satellite underestimation is reduced to about half (from  ∼  7 to  ∼  3.5  ×  1015 molecules cm−2). On the other hand, the distance criterion affects mostly GOME-2B data selection, because GOME-2B pixels are quite evenly distributed among the different radii used in the sensitivity test. More specifically, the number of collocations is notably reduced when stricter radius limits are applied, the r value is improved from 0.795 (d ≤  50 km) to 0.953 (d ≤  20 km), and the absolute mean bias decreases about 6 times for d ≤  30 km compared to the reference case (d ≤  50 km).

MICRU effective cloud fractions for S-5P/TROPOMI

2020 ◽  
Author(s):  
Holger Sihler ◽  
Sreffen Beirle ◽  
Christian Borger ◽  
Thomas Wagner
Keyword(s):  
Spatial Resolution ◽  
Trace Gases ◽  
Input Parameter ◽  
Cloud Fraction ◽  
Vertical Column ◽  
Angle Scattering ◽  
Vertical Column Density ◽  
Reflectance Map ◽  
Small Cloud

&lt;pre class=&quot;western&quot; lang=&quot;en-GB&quot;&gt;&lt;span lang=&quot;en-GB&quot;&gt;We present results of effective cloud fractions retrieved from measurements of the TROPOspheric Monitoring Instrument (TROPOMI) using the Mainz Iterative Cloud Retrieval Utilities (MICRU) algorithm. Cloud fraction (CF) data is used to study the distribution of clouds in general. Furthermore, CF is a crucial input parameter for retrievals of tropospheric trace gases from satellite measurements in the UV/vis spectral region because CF errors may even dominate vertical column density (VCD) retrieval errors of tropospheric trace gases.&lt;/span&gt; &lt;span lang=&quot;en-GB&quot;&gt;The MICRU algorithm has been specifically developed to retrieve small cloud fractions (CF&lt;20%) at high accuracy in order to improve retrievals of tropospheric trace gases. Here, MICRU is applied to TROPOMI data offering a more than 100 times higher spatial resolution compared to GOME-2 (Global Ozone Monitoring Experiment-2), on which it was previously applied. Hence, MICRU CF can be used as an alternative to the operational CF product.&lt;/span&gt; &lt;span lang=&quot;en-GB&quot;&gt;The most important feature of MICRU is the derivation of the minimum reflectance map from the measurements themselves. The algorithm builds on the assumption that the surface is dark compared to clouds, and it is therefore limited to regions not permanently covered by clouds, ice or snow. In particular, the MICRU algorithm applies four parameters to constrain interferences with surface BRDF effects like sun glitter and shadowing. Our approach features a lower threshold map parameterised by time, viewing zenith angle, scattering angle, and reflection angle. &lt;/span&gt; &lt;span lang=&quot;en-GB&quot;&gt;We demonstrate that MICRU, compared to the operational cloud fraction algorithms OCRA and FRESCO, interferences less with viewing angle, solar glitter, and shore lines and, hence, significantly improves the determination of cloud fractions. Furthermore, CF features made visible by the unprecedented spatial resolution of TROPOMI are discussed.&lt;/span&gt;&lt;/pre&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 The Spatial–Temporal Variation of Tropospheric NO2 over China during 2005 to 2018

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 444 ◽  
Author(s):  
Chunjiao Wang ◽  
Ting Wang ◽  
Pucai Wang
Keyword(s):  
Eastern China ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
The North ◽  
Annual Range ◽  
Tropospheric No2 ◽  
Vertical Column Density ◽  
Long Term Trends ◽  
Increasing Trends ◽  
No2 Pollution

In recent years, new and strict air quality regulations have been implemented in China. Therefore, it is of great significance to evaluate the current air pollution situation and effectiveness of actions. In this study, Ozone Monitoring Instrument (OMI) satellite data were used to detect the spatiotemporal characteristics of tropospheric NO2 columns over China from 2005 to 2018, including spatial distribution, seasonal cycles and long-term trends. The averaged NO2 pollution is higher in southeastern China and lower in the northwest, which are well delineated by the Heihe–Tengchong line. Furthermore, the NO2 loadings are highest in the North China Plain, with vertical column density (VCD) exceeding 13 × 1015 molec cm−2. Regarding the seasonal cycle, the NO2 loadings in eastern China is highest in winter and lowest in summer, while the western region shows the opposite feature. The amplitude of annual range increase gradually from the south to the north. If the entire period of 2005–2018 is taken into account, China has experienced little change in NO2. In fact, however, there appears to be significant trends of an increase followed by a downward tendency, with the turning point in the year 2012. In the former episode of 2005–2012, increasing trends overwhelm nearly the whole nation, especially in the Jing–Jin–Tang region, Shandong Province, and Northern Henan and Southern Hebei combined regions, where the rising rates were as high as 1.0–1.8 × 1015 molec cm−2 year−1. In contrast, the latter episode of 2013–2018 features remarkable declines in NO2 columns over China. Particularly, the regions where the decreased degree was remarkable in 2013–2018 were consistent with the regions where the upward trend was obvious in 2005–2012. Overall, this upward–downward pattern is true for most parts of China. However, some of the largest metropolises, such as Beijing, Shanghai and Guangzhou, witnessed a continuous decrease in the NO2 amounts, indicating earlier and more stringent measures adopted in these areas. Finally, it can be concluded that China’s recent efforts to cut NO2 pollution are successful, especially in mega cities.

scholarly journals Novel application of satellite and in-situ measurements to map surface-level NO<sub>2</sub> in the Great Lakes region

2011 ◽  
Vol 11 (22) ◽  
pp. 11761-11775 ◽  
Author(s):  
C. J. Lee ◽  
J. R. Brook ◽  
G. J. Evans ◽  
R. V. Martin ◽  
C. Mihele
Keyword(s):  
Qualitative Data ◽  
Great Lakes Region ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Surface Level ◽  
Suburban Areas ◽  
The Us ◽  
Tropospheric No2 ◽  
Vertical Column Density

Abstract. Ozone Monitoring Instrument (OMI) tropospheric NO2 vertical column density data were used in conjunction with in-situ NO2 concentrations collected by permanently installed monitoring stations to infer 24 h surface-level NO2 concentrations at 0.1° (~11 km) resolution. The region examined included rural and suburban areas, and the highly industrialised area of Windsor, Ontario, which is situated directly across the US-Canada border from Detroit, MI. Photolytic NO2 monitors were collocated with standard NO2 monitors to provide qualitative data regarding NOz interference during the campaign. The accuracy of the OMI-inferred concentrations was tested using two-week integrative NO2 measurements collected with passive monitors at 18 locations, approximating a 15 km grid across the region, for 7 consecutive two-week periods. When compared with these passive results, satellite-inferred concentrations showed an 18% positive bias. The correlation of the passive monitor and OMI-inferred concentrations (R=0.69, n=115) was stronger than that for the passive monitor concentrations and OMI column densities (R=0.52), indicating that using a sparse network of monitoring sites to estimate concentrations improves the direct utility of the OMI observations. OMI-inferred concentrations were then calculated for four years to show an overall declining trend in surface NO2 concentrations in the region. Additionally, by separating OMI-inferred surface concentrations by wind direction, clear patterns in emissions and affected down-wind regions, in particular around the US-Canada border, were revealed.

scholarly journals NO2 Retrieval from the Environmental Trace Gases Monitoring Instrument (EMI): Preliminary Results and Intercomparison with OMI and TROPOMI

2019 ◽  
Vol 11 (24) ◽  
pp. 3017 ◽  
Author(s):  
Liangxiao Cheng ◽  
Jinhua Tao ◽  
Pieter Valks ◽  
Chao Yu ◽  
Song Liu ◽  
...  
Keyword(s):  
Daily Variation ◽  
Trace Gases ◽  
Absorption Spectrometry ◽  
Visible Spectral Range ◽  
Wide Field ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Tropospheric No2 ◽  
Daily Total ◽  
Good Agreement

Onboard the Chinese GaoFen-5 (GF5) satellite, the Environmental trace gases Monitoring Instrument (EMI) is a nadir-viewing wide-field spectrometer that was launched on May 9, 2018. EMI measures the back-scattered earthshine solar radiance in the ultraviolet and visible spectral range. By using the differential optical absorption spectrometry (DOAS) method and the EMI measurements in the VIS1 band (405–465 nm), we performed retrievals of NO2. Some first retrieval results of NO2 from EMI and a comparison with OMI and TROPOMI products are presented in this paper. The monthly mean total vertical column densities (VCD) of NO2 show similar spatial distributions to OMI and TROPOMI (r > 0.88) and their difference is less than 27%. A comparison of the daily total VCD shows that EMI could detect the NO2 patterns in good agreement with OMI (r = 0.93) and TROPOMI (r = 0.95). However, the slant column density (SCD) uncertainty (0.79 × 1015 molec cm−2) of the current EMI algorithm is relatively larger than OMI. The daily variation pattern of NO2 from EMI in Beijing in January 2019 is consistent with TROPOMI (r = 0.96). The spatial distribution correlation of the tropospheric NO2 VCD of EMI with OMI and TROPOMI is 0.88 and 0.89, respectively, but shows an overestimate compared to OMI (15%) and TROPOMI (23%), respectively. This study demonstrates the capability of using EMI for global NO2 monitoring.

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