NO2 Vertical Column Densities Research Articles

Propagation of NO2 originated in intense fires in the Paraná River Delta analyzed from satellite observations

Wildfires in the Paraná River Delta started to be a common situation in the year 2008 and during the first years of the 2020́s decade: 2020, 2021, 2022. These fires affected natural areas, primarily the islands within the delta, situated in front of Rosario city (32.95 °S, 60.67 °W, 25 meters above sea level (m.a.s.l.)), Argentina. They mostly occur during the period between June and September each year and are more intense when a strong La Niña event is present. The aim of this study is to examine the association between the propagation of high intensity nitrogen dioxide (NO2) plumes and the significant fire events that occurred in the Paraná River Delta from 6 to 17 September 2022. Satellite data of NO2 obtained from the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency (ESA) Sentinel-5 Precursor satellite, air mass forward trajectories performed with The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), Fire Radiative Power (FRP) data provided by Visible Infrared Imaging Radiometer Suite (VIIRS) on board The National Oceanic and Atmospheric Administration - 20 (NOAA-20) and Suomi National Polar-orbiting Partnership (S-NPP) satellites, Aerosol Optical Depth (AOD) from VIIRS S-NPP and Smoke Injection Height from Multi-Angle Implementation of Atmospheric Correction (MAIAC) Thermal Technique were employed. The trajectories followed by the air masses coming from the major fire sources locations nearby Rosario city and its surrounding area, were analyzed at altitudes of 20, 500, 1000, 1500 and 2000 m above ground level (AGL) in order to evaluate the impact of the NO2 clouds present in the atmosphere and carried by the winds, at different sites of Rosario and its adjacent region. The NO2 plumes has the potential to pose a significant health risk for this region, inhabited by an approximate population of one and a half million individuals. This risk is contingent upon the altitude where the highest levels of NO2 in the tropospheric column are found. Tropospheric vertical column densities (VCDs) of NO2 in the range of 4.68×1014 to 1.66×1016 molecules/cm2 were determined. The results indicate a robust correlation between elevated tropospheric NO2 VCD values and intense fires, as characterized by their FRP. Additionally, high tropospheric NO2 VCDs were observed to impact cities and towns located in close proximity to the fires. In particular, the unusually high tropospheric NO2 VCDs determined for the towns of Fighiera and Pueblo Esther, situated along the coast and near the Paraná River Delta, are noteworthy. This is uncommon considering they are small towns in rural areas that typically have good air quality. The results regarding FRP, provided by VIIRS on board NOAA-20 and S-NPP satellites, indicate that the fire characterization of hotspots during the considered period had a mean value in the range of 20.17-21.47 MW. On specific days (12, 13 and 16 September 2022), the cumulative (total) daily values were very high, ranging from 2000 to 10000 MW. Furthermore, on 12 and 13 September 2022, the smoke aerosols did not reach significant altitudes in the atmosphere, remaining within the range of 0 to 1500 m AGL. During the fire period, AOD values close to 1 were observed within the fire plume. Notably, Puerto San Martín (0.27), San Lorenzo (0.22), and Ibarlucea (0.20) recorded higher average AOD values compared to other sites. The remaining sites generally exhibited lower average AOD values, with a slight distinction between rural locations (Pueblo Esther: 0.14 and Fighiera: 0.14) and the city center of Rosario (0.09).

Revised estimates of NO2 reductions during the COVID-19 lockdowns using updated TROPOMI NO2 retrievals and model simulations

The TROPOspheric Monitoring Instrument (TROPOMI) observed unprecedented declines in NO2 vertical column densities (VCD) over the world's most densely populated cities during the 2020 COVID-19 lockdowns. These favorable changes in NO2 air quality were correlated with sharp reductions in traffic volume and economic activity during the lockdowns. In this comprehensive global study, we provide revised estimates of the declines in anthropogenic emissions for 36 megacities using a novel methodology for disentangling the anthropogenic emissions from the meteorological transport and natural variability. We further quantify the uncertainty associated with changes in the a priori profile shape information during the lockdowns due to reduced emissions. Satellite NO2 retrieval techniques calculate an air mass factor that requires a priori NO2 profile shape information representative of the local atmosphere. This information, which is typically obtained from a chemical transport model (CTM), was not available for the early studies. This study also accounts for the satellite sampling errors resulting from the selective sampling of non-cloudy scenes during the study period. For our analysis, we used CTM simulations that were generated with and without COVID-impacted emissions. We perform retrievals of tropospheric NO2 columns with the NASA NO2 algorithm, and then use observed and simulated data to disentangle the meteorological transport from the contribution due anthropogenic emissions. We found that the meteorological transport was most significant source of variability ranging between −35% and 22% of the change total tropospheric VCD. We also find that not accounting for changes in the a priori NO2 profile shape information during the lockdowns resulted in systematic retrieval errors that were up to 12% of the estimated decline, and the elimination of cloud contaminated scenes resulted in sampling errors that in general ranged between varied ±15%.

Evaluation of the first year of Pandora NO2 measurements over Beijing and application to satellite validation

Abstract. Nitrogen dioxide (NO2) is a highly photochemically reactive gas, has a lifetime of only a few hours, and at high concentrations is harmful to human beings. Therefore, it is important to monitor NO2 with high-precision, time-resolved instruments. To this end, a Pandora spectrometer has been installed on the roof of the laboratory building of the Aerospace Information Research Institute of the Chinese Academy of Sciences in the Olympic Park, Beijing, China. The concentrations of trace gases (including NO2, HCHO, O3) measured with Pandora are made available through the open-access Pandora database (https://data.pandonia-global-network.org/Beijing-RADI/Pandora171s1/, last access: 11 July 2023). In this paper, an overview is presented of the Pandora total and tropospheric NO2 vertical column densities (VCDs) and surface concentrations collected during the first year of operation, i.e., from August 2021 to July 2022. The data show that NO2 concentrations were high in the winter and low in the summer, with a diurnal cycle where the concentrations reached a minimum during the daytime. The concentrations were significantly lower during the 2022 Winter Olympics in Beijing, showing the effectiveness of the emission control measures during that period. The Pandora observations show that during northerly winds, clean air is transported to Beijing with low NO2 concentrations, whereas during southerly winds, pollution from surrounding areas is transported to Beijing and NO2 concentrations are high. The contribution of tropospheric NO2 to the total NO2 VCD varies significantly on daily to seasonal timescales; i.e., monthly averages vary between 50 % and 60 % in the winter and between 60 % and 70 % in the spring and autumn. A comparison of Pandora-measured surface concentrations with collocated in situ measurements using a Thermo Scientific 42i-TL analyzer shows that the Pandora data are low and that the relationship between Pandora-derived surface concentrations and in situ measurements is different for low and high NO2 concentrations. Explanations for these differences are offered in terms of measurement techniques and physical (transport) phenomena. The use of Pandora total and tropospheric NO2 VCDs for validation of collocated TROPOspheric Monitoring Instrument (TROPOMI) data, resampled to 100 m × 100 m, shows that although on average the TROPOMI VCDs are slightly lower, they are well within the expected error for TROPOMI of 0.5 Pmolec.cm-2 + (0.2 to 0.5) ⋅ VCDtrop (1 Pmolec.cm-2 = 1 × 1015 molec cm−2). The location of the Pandora instrument within a sub-orbital TROPOMI pixel of 3.5 km × 5.5 km may result in an error in the TROPOMI-derived tropospheric NO2 VCD between 0.223 and 0.282 Pmolec.cm-2, i.e., between 1.7 % and 2 %. In addition, the data also show that the Pandora observations at the Beijing-RADI site are representative of an area with a radius of 10 km.

Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources

Abstract. High-spatial-resolution NO2 vertical column densities (VCDs) were retrieved from airborne observations using the low-cost hyperspectral imaging sensor (HIS) at three industrial areas (i.e., Chungnam, Jecheon, and Pohang) in South Korea, where point sources (i.e., power plant, petrochemical complex, steel yard, and cement kiln) with significant NO2 emissions are located. An innovative and versatile approach for NO2 VCD retrieval, hereafter referred to as the modified wavelength pair (MWP) method, was developed to overcome the excessively variable radiometric and spectral characteristics of the HIS attributed to the absence of temperature control during the flight. The newly developed MWP method was designed to be insensitive to broadband spectral features, including the spectral dependency of surface and aerosol reflectivity, and can be applied to observations with relatively low spectral resolutions. Moreover, the MWP method can be implemented without requiring precise radiometric calibration of the instrument (i.e., HIS) by utilizing clean-pixel data for non-uniformity corrections and is also less sensitive to the optical properties of the instrument and offers computational cost competitiveness. In the experimental flights using the HIS, NO2 plumes emitted from steel yards were particularly conspicuous among the various NO2 point sources, with peak NO2 VCDs of 2.0 DU (Dobson unit) at Chungnam and 1.8 DU at Pohang. Typical NO2 VCD uncertainties ranged between 0.025–0.075 DU over the land surface and 0.10–0.15 DU over the ocean surface, and the discrepancy can be attributable to the lower signal-to-noise ratio over the ocean and higher sensitivity of the MWP method to surface reflectance uncertainties under low-albedo conditions. The NO2 VCDs retrieved from the HIS with the MWP method showed a good correlation with the collocated Tropospheric Monitoring Instrument (TROPOMI) data (r=0.73, mean absolute error equals 0.106 DU). However, the temporal disparities between the HIS frames and the TROPOMI overpass, their spatial mismatch, and their different observation geometries could limit the correlation. The comparison of TROPOMI and HIS NO2 VCDs further demonstrated that the satellite sub-grid variability could be intensified near the point sources, with more than a 3-fold increase in HIS NO2 VCD variability (e.g., difference between 25th and 75th quantiles) over the TROPOMI footprints with NO2 VCD values exceeding 0.8 DU compared to footprints with NO2 VCD values below 0.6 DU.

On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO2 in WRF-Chem – comparisons to in situ, satellite, and MAX-DOAS observations

Abstract. We present WRF-Chem simulations over central Europe with a spatial resolution of 3 km × 3 km and focus on nitrogen dioxide (NO2). A regional emission inventory issued by the German Environmental Agency, with a spatial resolution of 1 km × 1 km, is used as input. We demonstrate by comparison of five different model setups that significant improvements in model accuracy can be achieved by choosing the appropriate boundary layer scheme, increasing vertical mixing strength, and/or tuning the temporal modulation of the emission data (“temporal profiles”) driving the model. The model setup with improved vertical mixing is shown to produce the best results. Simulated NO2 surface concentrations are compared to measurements from a total of 275 in situ measurement stations in Germany, where the model was able to reproduce average noontime NO2 concentrations with a bias of ca. −3 % and R=0.74. The best agreement is achieved when correcting for the presumed NOy cross sensitivity of the molybdenum-based in situ measurements by computing an NOy correction factor from modelled peroxyacetyl nitrate (PAN) and nitric acid (HNO3) mixing ratios. A comparison between modelled NO2 vertical column densities (VCDs) and satellite observations from TROPOMI (TROPOspheric Monitoring Instrument) is conducted with averaging kernels taken into account. Simulations and satellite observations are shown to agree with a bias of +5.5 % and R=0.87 for monthly means. Lastly, simulated NO2 concentration profiles are compared to noontime NO2 profiles obtained from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at five locations in Europe. For stations within Germany, average biases of −25.3 % to +12.0 % were obtained. Outside of Germany, where lower-resolution emission data were used, biases of up to +50.7 % were observed. Overall, the study demonstrates the high sensitivity of modelled NO2 to the mixing processes in the boundary layer and the diurnal distribution of emissions.

TROPOMI NO2 Sentinel-5P data in the Community of Madrid: A detailed consistency analysis with in situ surface observations

Excess reactive nitrogen emissions from anthropogenic activities can negatively impact the natural environment. The sensor TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (Sentinel-5P) satellite is capable of providing data on tropospheric NO2 vertical column densities (VCDs). This work investigates NO2 data retrieved from TROPOMI to study the spatial and temporal patterns of NO2 pollution compared with surface-level concentration measurements in the Community of Madrid in 2022. A high linear correlation coefficient (r) was obtained by comparing daily Level-3 tropospheric TROPOMI NO2 data with ground-based data from air quality monitoring stations at satellite overpass time (r = 0.78). Since the overpasses of Sentinel-5P over the region consistently occur between 12:00 and 4:00 p.m. local time, a second correlation analysis was carried out by averaging all available data from both sources within that interval, resulting in an even higher coefficient (r = 0.81). Results showed a lower correlation at rural sites compared to urban and suburban sites. Examining the monthly and weekly variations of NO2 concentration from satellite data and in situ measurements, similar tendencies in NO2 concentration were observed from both sources. In agreement with previous studies, the cold months and weekdays exhibited higher NO2 concentrations. It was concluded that TROPOMI NO2 data and in situ measurements yield a strong correlation for the Community of Madrid target area, and TROPOMI data can be further investigated to propose pollution mitigation policies.

Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of NO2 and H2CO at Kinshasa and comparisons with TROPOMI observations

Abstract. We present a database of MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) ground-based observations of NO2 and H2CO tropospheric vertical column densities (VCDtropo) performed for the first time in the city of Kinshasa. These measurements were conducted between November 2019 and July 2021 and processed using the standardized inversion tools developed in the ESA FRM4DOAS (Fiducial Reference Measurements for Ground-Based DOAS Air-Quality Observations) project. The retrieved geophysical quantities are used to validate column observations from the TROPOspheric Monitoring Instrument (TROPOMI) over Kinshasa. In the validation, we experiment with three different comparison cases of increasing complexity. In the first case, a direct comparison between MAX-DOAS observations (hourly average of MAX-DOAS VCDtropo at overpass) and TROPOMI shows an underestimation of TROPOMI with a median bias of −38 % for NO2 and −39 % for H2CO based on monthly comparison. The second case takes into account the different vertical sensitivities of the two instruments and the a priori profile. We note significant changes in the median bias for both compounds: −12 % for NO2 and +11 % for H2CO. The third case builds on the second case by considering also the direction of sight of the MAX-DOAS. For this third case, we find a median bias of +44 % for NO2 and a median bias of +4 % for H2CO. However this case is impacted by low sampling and is considered less reliable. The findings from this study underscore the significance of employing a realistic a priori profile in TROPOMI column extraction, particularly within heavily polluted urban zones like Kinshasa. The investigation also highlights the necessity for prudence when integrating the MAX-DOAS line of sight due to the noise generated during subsampling and the limited horizontal sensitivity of MAX-DOAS observations. Importantly, the study further reveals the pronounced pollution levels of NO2, H2CO and aerosols in both the city of Kinshasa and its adjacent regions, underscoring the imperative for consistent monitoring and effective regulatory measures by local authorities.

Estimate of near-surface NO2 concentrations in Fenwei Plain, China, based on TROPOMI data and random forest model.

Nitrogen dioxide (NO2) concentration is a crucial indicator of ground-level air quality, and elevated concentrations can adversely affect human health and the atmospheric environment. In this study, we utilized Tropospheric Monitoring Instrument (TROPOMI) tropospheric NO2 vertical column density data (VCD) and multi-source geographic data to establish a random forest regression (RF) model that accurately estimates NO2 concentrations near the ground in the Fenwei Plain. The model addresses the inherent limitations of traditional ground-based monitoring and provides data support for analyzing regional pollution spatial and temporal characteristics. (1) The RF model based on TROPOMI and geographic data demonstrates high estimation accuracy, with monthly average RF model fit and validation coefficient of determination (R2) reaching 0.949 and 0.875, respectively. (2) A complex nonlinear relationship exists between near-surface NO2 concentration and multi-source geographic data. The RF model's estimations reveal clear seasonal and regional variations in near-surface NO2 concentration. Concentrations are generally highest in winter, followed by spring and autumn, and lowest in summer. The high NO2 concentrations are primarily mainly distributed in the plains and river valleys with low elevation and dense population density. The model estimation results also indicate that the estimated effect is better when the NO2 concentration fluctuates less and anthropogenic emission reduction measures significantly impact the NO2 concentration near the ground. (3) The population exposure risk results indicate that most cities in the Fenwei Plain face varying exposure risks. These findings offer valuable insights for regional NO2 pollution management.

Retrieval of Tropospheric NO2 Vertical Column Densities from Ground-Based MAX-DOAS Measurements in Lhasa, a City on the Tibetan Plateau

In order to investigate the abundance of and temporal variation in nitrogen dioxide (NO2) in the troposphere and validate the corresponding satellite products during a normal year and the lockdown period of coronavirus disease 2019 (COVID-19) in Lhasa, a city on the Tibetan Plateau (TP), ground-based remote-sensing measurements captured by applying multi-axis differential optical absorption spectroscopy (MAX-DOAS) were recorded from August 2021 to March 2023 at the Lhasa site (91.14°E, 29.66°N; 3552.5 m altitude). The NO2 differential slant column densities (dSCDs) were retrieved from the spectra of scattered solar light at different elevation angles. Then, the tropospheric NO2 vertical column densities (VCDs) were calculated with the geometric approximation method. Based on the retrieved tropospheric NO2 VCDs, we found that the pattern of monthly variation in tropospheric NO2 VCDs in Lhasa presented two peaks, one in winter and one around May. According to the monthly means of tropospheric NO2 VCDs during the COVID-19 lockdown, the NO2 background level in Lhasa was estimated to be 0.53 × 1015 molecules·cm−2. For diurnal variations in tropospheric NO2 VCDs, the morning and evening peaks disappeared during the COVID-19 lockdown period. The east–west direction (i.e., along the river valley) was the main path of NO2 transport and dispersion in Lhasa, but the tropospheric NO2 VCDs were little dependent on the wind direction or wind speed during the COVID-19 lockdown. The correlation coefficient of tropospheric NO2 VCDs was R = 0.33 (R = 0.43), with the averaged relative deviation of −28% (99%) for the TROPOMI (GEMS) relative to ground-based MAX-DOAS. The monthly deviations of tropospheric NO2 VCDs between ground-based MAX-DOAS and the satellite showed a dependence on NO2 abundance, with the maxima of the monthly positive deviations during the COVID-19 lockdown period. The GEMS could not capture the strong and systematic diurnal variation in tropospheric NO2 VCDs in the “normal” year well. During the COVID-19 lockdown, the GEMS (>2 × 1015 molecules·cm−2) overestimated the hourly levels measured by ground-based MAX-DOAS (<1.6 × 1015 molecules·cm−2). As a whole, these results are beneficial to understanding the influences of anthropogenic activities on NO2 background levels in Lhasa and to learning the accuracy of satellite products over the TP, with its high altitude and complex terrain.

Reliability Analysis Based on Air Quality Characteristics in East Asia Using Primary Data from the Test Operation of Geostationary Environment Monitoring Spectrometer (GEMS)

Air pollutants adversely affect human health, and thus a global improvement in air quality is urgent. A Geostationary Environment Monitoring Spectrometer (GEMS) was mounted on the geostationary Chollian 2B satellite in 2020 to observe the spatial distribution of air pollution, and sequential observations have been released since July 2022. The reliability of GEMS must be analyzed because it is the first payload on the geostationary Earth orbit satellite to observe trace gases. This study analyzed the initial results of GEMS observations such as the aerosol optical depth and vertical column densities (VCD) of ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO), and compared them with previous studies. The correlation coefficient of O3 ranged from 0.90 (Ozone Monitoring Instrument, OMI) to 0.97 (TROPOspheric Monitoring Instrument, TROPOMI), whereas that of NO2 ranged from 0.47 (winter, OMI and OMPS) to 0.83 (summer, TROPOMI). GEMS yielded a higher VCD of NO2 than that of OMI and TROPOMI. Based on the sources of O3 and NO2, GEMS observed the maximum VCD at a different time (3–4 h) to that of the ground observations. Overall, GEMS can make observations several times a day and is a potential tool for atmospheric environmental analysis.

A CNN-SVR model for NO2 profile prediction based on MAX-DOAS observations: The influence of Chinese New Year overlapping the 2020 COVID-19 lockdown on vertical distributions of tropospheric NO2 in Nanjing, China

In this study, a hybrid model, the convolutional neural network-support vector regression model, was adopted to achieve prediction of the NO2 profile in Nanjing from January 2019 to March 2021. Given the sudden decline in NO2 in February 2020, the contribution of the Coronavirus Disease-19 (COVID-19) lockdown, Chinese New Year (CNY), and meteorological conditions to the reduction of NO2 was evaluated. NO2 vertical column densities (VCDs) from January to March 2020 decreased by 59.05% and 32.81%, relative to the same period in 2019 and 2021, respectively. During the period of 2020 COVID-19, the average NO2 VCDs were 50.50% and 29.96% lower than those during the pre-lockdown and post-lockdown periods, respectively. The NO2 volume mixing ratios (VMRs) during the 2020 COVID-19 lockdown significantly decreased below 400 m. The NO2 VMRs under the different wind fields were significantly lower during the lockdown period than during the pre-lockdown period. This phenomenon could be attributed to the 2020 COVID-19 lockdown. The NO2 VMRs before and after the CNY were significantly lower in 2020 than in 2019 and 2021 in the same period, which further proves that the decrease in NO2 in February 2020 was attributed to the COVID-19 lockdown. Pollution source analysis of an NO2 pollution episode during the lockdown period showed that the polluted air mass in the Beijing-Tianjin-Hebei was transported southwards under the action of the north wind, and the subsequent unfavorable meteorological conditions (local wind speed of < 2.0 m/sec) resulted in the accumulation of pollutants.

First-time comparison between NO2 vertical columns from Geostationary Environmental Monitoring Spectrometer (GEMS) and Pandora measurements

Abstract. The Geostationary Environmental Monitoring Spectrometer (GEMS) is a UV-visible (UV-Vis) spectrometer on board the GEO-KOMPSAT-2B (Geostationary Korea Multi-Purpose Satellite 2B) satellite launched into a geostationary orbit in February 2020. To evaluate the GEMS NO2 total column data, a comparison was carried out using the NO2 vertical column density (VCD) that measured direct sunlight using the Pandora spectrometer system at four sites in Seosan, South Korea, from November 2020 to January 2021. Correlation coefficients between GEMS and Pandora NO2 data at four sites ranged from 0.35 to 0.48, with root mean square errors (RMSEs) from 4.7×1015 to 5.5×1015 molec. cm−2 for a cloud fraction (CF) &lt;0.7. Higher correlation coefficients of 0.62–0.78 with lower RMSEs from 3.3×1015 to 5.0×1015 molec. cm−2 were found with CF &lt;0.3, indicating the higher sensitivity of GEMS to atmospheric NO2 in less cloudy conditions. Overall, the GEMS NO2 total column data tended to be lower than the Pandora data, owing to differences in the representative spatial coverage, with a large negative bias under high CF conditions. With a correction for horizontal representativeness in the Pandora measurement coverage, correlation coefficients ranging from 0.69 to 0.81, with RMSEs from 3.2×1015 to 4.9×1015 molec. cm−2, were achieved for CF &lt;0.3, showing a better correlation with the correction than without the correction.

Long-term spatiotemporal variations in surface NO2 for Beijing reconstructed from surface data and satellite retrievals

Remote sensing data from the Ozone Monitoring Instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI) play important roles in estimating surface nitrogen dioxide (NO2), but few studies have compared their differences for application in surface NO2 reconstruction. This study aims to explore the effectiveness of incorporating the tropospheric NO2 vertical column density (VCD) from OMI and TROPOMI (hereafter referred to as OMI and TROPOMI, respectively, for conciseness) for deriving surface NO2 and to apply the resulting data to revisit the spatiotemporal variations in surface NO2 for Beijing over the 2005–2020 period during which there were significant reductions in nitrogen oxide emissions. In the OMI versus TROPOMI performance comparison, the cross-validation R2 values were 0.73 and 0.72, respectively, at 1 km resolution and 0.69 for both at 100 m resolution. The comparisons between satellite data sources indicate that even though TROPOMI has a finer resolution it does not improve upon OMI for deriving surface NO2 at 1 km resolution, especially for analyzing long-term trends. In light of the comparison results, we used a hybrid approach based on machine learning to derive the spatiotemporal distribution of surface NO2 during 2005–2020 based on OMI. We had novel, independent passive sampling data collected weekly from July to September of 2008 for hindcasting validation and found a spatiotemporal R2 of 0.46 (RMSE = 7.0 ppb). Regarding the long-term trend of surface NO2, the level in 2008 was obviously lower than that in 2007 and 2009, as expected, which was attributed to pollution restrictions during the Olympic Games. The NO2 level started to steadily decline from 2015 and fell below 2008's level after 2017. Based on OMI, a long-term and fine-resolution surface NO2 dataset was developed for Beijing to support future environmental management questions and epidemiological research.

Assessing the impact of urban form and urbanization process on tropospheric nitrogen dioxide pollution in the Yangtze River Delta, China

Optimizing urban form through urban planning and management policies can improve air quality and transition to demand-side control. Nitrogen dioxide (NO2) in the urban atmosphere, mainly emitted by anthropogenic sources such as industry and vehicles, is a key precursor of fine particles and ozone pollution. Both NO2 and its secondary pollutants pose health risks for humans. Here we assess the interactions between urban forms and airborne NO2 pollution in different cities with various stages of urbanization in the Yangtze River Delta (YRD) in China, by using the machine learning and geographical regression model. The results reveal a strong correlation between urban fragmentation and tropospheric NO2 vertical column density (TVCD) in YRD cities in 2020, particularly those with lower or higher levels of urbanization. The correlation coefficients (R2) between NO2 TVCD and the largest patch index (a metric of urban fragmentation) in different cities are greater than 0.8. For cities at other urbanization stages, population and road density are strongly correlated with NO2 TVCD, with an R2 larger than 0.61. This study highlights the interdependence among urbanization, urban forms, and air pollution, emphasizing the importance of customized urban landscape management strategies for mitigating urban air pollution.

Estimating surface-level nitrogen dioxide concentrations from Sentinel-5P/TROPOMI observations in Finland

In recent decades, satellite instruments have been providing observations of air pollutants such as nitrogen dioxide (NO2) with global coverage. Since late 2018, the TROPOspheric Monitoring Instrument (TROPOMI) on-board the Copernicus Sentinel-5 Precursor satellite has produced NO2 vertical column densities (VCDs) with the best spatial resolution (currently 5.5 × 3.5km2 at nadir). In this paper, we test and adapt two previously published methods to estimate surface-level NO2 concentrations from TROPOMI VCD retrievals in the specific conditions of Finland. Satellite-based estimates show good correlation with co-located surface NO2 measurements from the Finnish AQ network, although not accounting for the level of NO2 mixing within the boundary layer leads to underestimation. We also use a linear relation between in situ measurements and surface-level estimates to correct for the observed negative bias in the estimates. Finally, we use chemical transport model simulations to estimate the ratio of the annual mean surface concentrations to the values sampled according to TROPOMI observation times, and use it to correct our surface-level NO2 estimates for compatibility with annual limit values defined in AQ legislation.Overall, the results provide new information to complement traditional ground-based AQ measurements, especially over areas where the surface AQ networks are sparse, and to support national environmental authorities in air quality assessment and reporting.

NO2 emissions from oil refineries in the Mississippi Delta

Of the >17,943 thousand barrels per calendar day (bbl/d) of oil refining capacity located in the US, the Petroleum Administration for Defense District 3 (PADD-3) region has the largest number of refineries and accounts for >53 % (or 9607 tbbl/d) of all US oil refining capacity. Processing facilities in this area are mainly located on the Gulf of Mexico coast in Texas and Louisiana. This study selected a sub-region for analysis within the Mississippi River delta in the state of Louisiana between the cities of New Orleans and Baton Rouge. This region is characterized by intensive industrial activity connected with oil refining and related activities. The TROPOspheric Monitoring Instrument (TROPOMI) detected highly localized NO2 vertical column densities (VCDs) over the two largest US refineries in Baton Rouge (503,000 bbl/d) and Garyville (578,000 bbl/d). TROPOMI NO2 VCD over these stations were 100 μmol/m2 and 80 μmol/m2, respectively. A high correlation coefficient (r = 0.65, p < 0.05) was also found between TROPOMI NO2 and population density. Data from the National Emissions Inventory (NEI) showed high NOx emissions from refineries and other industries including coal-fired power generation, chemical, and aluminum processing plants. The results of the NO2 analysis are of practical interest for a comparative assessment of air pollution, as well as for the exchange of best practices in the field of low-waste fuel combustion technologies.

Background nitrogen dioxide (NO2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires

Abstract. Tropospheric nitrogen dioxide (NO2) measured from satellites has been widely used to track anthropogenic NOx emissions, but its retrieval and interpretation can be complicated by the free tropospheric NO2 background to which satellite measurements are particularly sensitive. Tropospheric NO2 vertical column densities (VCDs) from the spaceborne Ozone Monitoring Instrument (OMI) averaged over the contiguous US (CONUS) show no trend after 2009, despite sustained decreases in anthropogenic NOx emissions, implying an important and rising contribution from the free tropospheric background. Here, we use the GEOS-Chem chemical transport model applied to the simulation of OMI NO2 to better understand the sources and trends of background NO2 over CONUS. The previous model underestimate of the background is largely corrected by the consideration of aerosol nitrate photolysis, which increases the model NO2 VCDs by 13 % on an annual basis (25 % in spring) and also increases the air mass factor (AMF) to convert the tropospheric slant column densities (SCDs) inferred from the OMI spectra into VCDs by 7 % on an annual basis (11 % in spring). The increase in the AMF decreases the retrieved NO2 VCDs in the satellite observations, contributing to the improved agreement with the model. Accounting for the 2009–2017 increase in aircraft NOx emissions drives only a 1.4 % mean increase in NO2 VCDs over CONUS and a 2 % increase in the AMF, but the combination of decreasing surface NOx emissions and increasing aircraft emissions is expected to drive a 14 % increase in the AMF over the next decade that will be necessary to account for in the interpretation of satellite NO2 trends. Fire smoke identification with the National Oceanic and Atmospheric Administration (NOAA) Hazard Mapping System (HMS) indicates that wildfires contribute 1 %–8 % of OMI NO2 VCDs over the western US in June–September and that this contribution has been increasing since 2009, contributing to the flattening of OMI NO2 trends. Future analyses of NO2 trends from satellite data to infer trends in surface NOx emissions must critically consider the effects of a rising free tropospheric background due to increasing emissions from aircraft, fires, and possibly lightning.

A new insight into the vertical differences in NO2 heterogeneous reaction to produce HONO over inland and marginal seas

Abstract. Ship-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements were conducted along the marginal seas of China from 19 April to 16 May 2018 to measure the vertical profiles of aerosol, nitrogen dioxide (NO2), and nitrous acid (HONO). Along the cruise route, we found five hot spots with enhanced tropospheric NO2 vertical column densities (VCDs) in the Yangtze River Delta, Taiwan Strait, Guangzhou–Hong Kong–Macau Greater Bay Area, port of Zhanjiang, and port of Qingdao. Enhanced HONO concentrations could usually be observed under high-level aerosol and NO2 conditions, whereas the reverse was not always the case. To understand the impacts of relative humidity (RH), temperature, and aerosol on the heterogeneous reaction of NO2 to form HONO in different scenarios, the Chinese Academy of Meteorological Sciences (CAMS) and Southern University of Science and Technology (SUST) MAX-DOAS stations were selected as the inland and coastal cases, respectively. The RH turning points in CAMS and SUST cases were both ∼ 65 % (60 %–70 %), whereas two turning peaks (∼ 60 % and ∼ 85 %) of RH were found in the sea cases. As temperature increased, the HONO / NO2 ratio decreased with peak values appearing at ∼ 12.5∘C in CAMS, whereas the HONO / NO2 gradually increased and reached peak values at ∼ 31.5∘C in SUST. In the sea cases, when the temperature exceeded 18.0∘C, the HONO / NO2 ratio rose with increasing temperature and achieved its peak at ∼ 25.0∘C. This indicated that high temperature can contribute to the secondary formation of HONO in the sea atmosphere. In the inland cases, the correlation analysis between HONO and aerosol in the near-surface layer showed that the ground surface is more crucial to the formation of HONO via the heterogeneous reaction of NO2; however, in the coastal and sea cases, the aerosol surface contributed more. Furthermore, we discovered that the conversion rate of NO2 to HONO through heterogeneous reactions in the sea cases is larger than that in the inland cases in higher atmospheric layers (&gt; 600 m). Three typical events were selected to demonstrate three potential contributing factors of HONO production under marine conditions (i.e., transport, NO2 heterogeneous reaction, and unknown HONO source). This study elucidates the sea–land and vertical differences in the forming mechanism of HONO via the NO2 heterogeneous reaction and provides deep insights into tropospheric HONO distribution, transforming process, and environmental effects.

Mobile MAX-DOAS observations of tropospheric NO2 and HCHO during summer over the Three Rivers' Source region in China

Abstract. The tropospheric concentrations of nitrogen dioxide (NO2) and formaldehyde (HCHO) have high spatio-temporal variability, and in situ observations of these trace gases are still scarce, especially in remote background areas. We made four similar circling journeys of mobile multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in the Three Rivers' Source region over the Tibetan Plateau in summer (18–30 July) 2021 for the first time. The differential slant column densities (DSCDs) of NO2 and HCHO were retrieved from the measured spectra, with very weak absorptions along the driving routes. The tropospheric NO2 and HCHO vertical column densities (VCDs) were calculated from their DSCDs by the geometric approximation method, and they were further filtered to form reliable data sets by eliminating the influences of sunlight shelters and the vehicle's vibration and bumpiness. The observational data show that the tropospheric NO2 and HCHO VCDs decreased with the increasing altitude of the driving route, whose background levels ± standard deviations were 0.40 ± 1.13×1015 molec. cm−2 for NO2 and 2.27±1.66×1015 molec. cm−2 for HCHO in July 2021 over the Three Rivers' Source region. The NO2 VCDs show similar geographical distribution patterns between the different circling journeys, but the levels of the HCHO VCDs are different between the different circling journeys. The elevated NO2 VCDs along the driving routes usually corresponded to enhanced transport emissions from the towns crossed. However, the spatial distributions of the HCHO VCDs depended significantly on natural and meteorological conditions, such as surface temperature. By comparing TROPOMI satellite products and mobile MAX-DOAS results, we found that TROPOMI NO2 and HCHO VCDs have large positive offsets in the background atmosphere over the main area of the Three Rivers' Source. Our study provides valuable data sets and information of NO2 and HCHO over the Tibetan Plateau, benefitting the scientific community in investigating the spatio-temporal evolution of atmospheric composition in the background atmosphere at high altitudes, validating and improving the satellite products over mountain terrains, and evaluating the model's ability to simulate atmospheric chemistry over the Tibetan Plateau.

Temporal Variation of NO2 and O3 in Rome (Italy) from Pandora and In Situ Measurements

To assess the best measures for the improvement of air quality, it is crucial to investigate in situ and columnar pollution levels. In this study, ground-based measurements of nitrogen dioxide (NO2) and ozone (O3) collected in Rome (Italy) between 2017 and 2022 are analyzed. Pandora sun-spectrometers provided the time series of the NO2 vertical column density (VC-NO2), tropospheric column density (TC-NO2), near-surface concentration (SC-NO2), and the O3 vertical column density (VC-O3). In situ concentrations of NO2 and O3 are provided by an urban background air quality station. The results show a clear reduction of NO2 over the years, thanks to the recent ecological transition policies, with marked seasonal variability, observable both by columnar and in situ data. Otherwise, O3 does not show inter-annual variations, although a clear seasonal cycle is detectable. The results suggest that the variation of in situ O3 is mainly imputable to photochemical reactions while, in the VC-O3, it is triggered by the predominant contribution of stratospheric O3. The outcomes highlight the importance of co-located in situ and columnar measurements in urban environments to investigate physical and chemical processes driving air pollution and to design tailored climate change adaptation strategies.