Tropospheric Nitrogen Dioxide Research Articles

Spatiotemporal Distributions and Variations in Summertime Ozone Photochemical Production Regimes over Shanxi

Satellite-based formaldehyde（HCHO）columns and tropospheric nitrogen dioxide columns were observed using the Ozone Monitoring Instrument（OMI），and groundbased observations of ozone（O3）for May-August from 2013 to 2022 were connected to calculate the threshold values of the HCHO to NO2 ratio（FNR）in Shanxi Province. Then，the spatiotemporal distributions and variations in summertime ozone photochemical production regimes were analyzed. The results showed that：① The volatile organic compound（VOC） -sensitive regime area（FNR < 2.3）was obviously reduced，while the VOCs-NOx transitional regime（FNR between 2.3-4.1）area increased in the early years and then decreased， and NO x -sensitive regime area expanded significantly in summer from 2013 to 2022 over Shanxi Province. ② The increased summertime FNR during 2013 to 2019 was associated with the co-effect of increased HCHO columns and decreased tropospheric NO2 columns. The Shanxi Province was generally under an NOx regime since 2016，which reflected the remarkable effect of NO x emission reductions；however，there was a shift from a VOC-sensitive regime to a VOCs-NOx transitional regime，in which O3 pollution aggravation was widespread under the background of decreased NOx emissions. The decrease in O3 concentration during 2020 to 2022 followed the synergistical declines in HCHO columns and tropospheric NO2 columns. ③ The O3 weekend effects were reversed in Linfen and Yuncheng but were persistent in the other nine cities. Satellite-based weekend HCHO and NO2 levels were higher than those on weekdays in some cities of Shanxi Province，indicating that the O3 weekend effect was not only dependent on the changes of precursors emissions but was also closely related to O3 photochemical production sensitivity. The results indicated the necessity of simultaneous controls in NOx emissions and VOCs emissions for ozone abatement plans over Shanxi Province. In addition，Taiyuan，Yangquan，Yuncheng，and Jincheng should continue to promote reduction in NOx emissions.

Estimation of Near-surface Ozone Concentration in the Beijing-Tianjin-Hebei Region Based on XGBoost-LME Model

High spatiotemporal resolution data on near-surface ozone concentration distribution is of great significance for monitoring and controlling atmospheric ozone pollution and improving the living environment. Using TROPOMI-L3 NO2, HCHO products, and ERA5-land high-resolution data as estimation variables, an XGBoost-LME model was constructed to estimate the near-surface ozone concentration in the Beijing-Tianjin-Hebei Region. The results showed that： ① Through correlation analysis, surface 2 m temperature （T2M）, 2 m dewpoint temperature （D2M）, surface solar radiation downwards （SSRD）, tropospheric formaldehyde （HCHO）, and tropospheric nitrogen dioxide （NO2） were important factors affecting the near-surface ozone concentration in the Beijing-Tianjin-Hebei Region. Among them, T2M, SSRD, and D2M had strong correlations, with correlation coefficients of 0.82, 0.75, and 0.71, respectively. ② Compared with that of other models, the XGBoost-LME model had the best performance in terms of various indicators. The ten-fold cross-validation evaluation indicators R2, MAE, and RMSE were 0.951, 9.27 μg·m-3, and 13.49 μg·m-3, respectively. At the same time, the model performed well at different time scales. ③ In terms of time, there was a significant seasonal difference in near-surface ozone concentration in the Beijing-Tianjin-Hebei Region in 2019, with the concentration changing in the order of summer &gt; spring &gt; autumn &gt; winter. The monthly average ozone concentration in the region showed an inverted "V" trend, with a slight increase in September. The highest value occurred in July, whereas the lowest value occurred in December. In terms of spatial distribution, the near-surface ozone concentrations in the Beijing-Tianjin-Hebei Region during the months of February and March were generally at the same levels. In January, November, and December, there was a relatively insignificant trend of higher concentrations in the north and lower concentrations in the south. For the remaining months, the spatial distribution of near-surface ozone concentrations in this area predominantly exhibited a pattern of higher concentrations in the south and lower concentrations in the north. High-value areas were predominantly found in the plain regions of the southern part with lower altitudes, dense population, and higher industrial emissions； low-value areas, on the other hand, were primarily located in mountainous areas of the northern part with higher altitudes, sparse population, higher vegetation coverage, and lower industrial emissions.

Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001-2018).

Tropospheric nitrogen dioxide (NO2) poses a serious threat to the environmental quality and public health. Satellite NO2 observations have been continuously used to monitor NO2 variations and improve model performances. However, the accuracy of satellite NO2 retrieval depends on the knowledge of aerosol optical properties, in particular for urban agglomerations accompanied by significant changes in aerosol characteristics. In this study, we investigate the impacts of aerosol composition on tropospheric NO2 retrieval for an 18 year global data set from Global Ozone Monitoring Experiment (GOME)-series satellite sensors. With a focus on cloud-free scenes dominated by the presence of aerosols, individual aerosol composition affects the uncertainties of tropospheric NO2 columns through impacts on the aerosol loading amount, relative vertical distribution of aerosol and NO2, aerosol absorption properties, and surface albedo determination. Among aerosol compositions, secondary inorganic aerosol mostly dominates the NO2 uncertainty by up to 43.5% in urban agglomerations, while organic aerosols contribute significantly to the NO2 uncertainty by -8.9 to 37.3% during biomass burning seasons. The possible contrary influences from different aerosol species highlight the importance and complexity of aerosol correction on tropospheric NO2 retrieval and indicate the need for a full picture of aerosol properties. This is of particular importance for interpreting seasonal variations or long-term trends of tropospheric NO2 columns as well as for mitigating ozone and fine particulate matter pollution.

High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns

Abstract. Satellite-derived spatiotemporal patterns of nitrogen oxide (NOx) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NOx emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO2) retrievals. The accuracy of the coupled method is validated through application to synthetic NO2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = −0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R=0.88±0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = −0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.

The variability of NO2 concentrations over China based on satellite and influencing factors analysis during 2019–2021

The variation of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) indirectly reflects the difference in pollution emissions from industrial production and transportation. Accurately analyzing its pollution sources and driving factors plays an important role in energy conservation, emission reduction, and air pollution reduction. NO2 concentration products of Sentinel-5P (Sentinel-5 Precursor) TROPOMI (TROPOspheric Monitoring Instrument) from 2019 to 2021 and Aura OMI (Ozone Monitoring Instrument) from 2009 to 2021, combined with China’s main energy consumption, the growth value of the industry, Gross Domestic Product (GDP), and other data were used to analyze the influencing factors of NO2 variations. Firstly, NO2 tropospheric vertical column densities (NO2 TVCDs) of China increased by 14.72% and 3.26% in 2021 and 2020 compared with the 2019. The secondary and tertiary industry and the national energy consumption increased synchronously, which was highly related to the increase in NO2 TVCDs. Secondly, the impact of COVID-19 (coronavirus disease 2019) on China’s industrial production and residents was mainly concentrated in the first quarter of 2020, which leading to a decline in the annual average NO2 concentration in densely populated areas in 2020 compared to the same period in 2019. The industrial production scale and production capacity has gradually recovered since April 2020, and the NO2 concentration has gradually reached or exceeded the level of the same period of 2019. Finally, atmospheric pollution prevention and control measures played a positive role in the decline of NO2 of China.

Trans-boundary spatio-temporal analysis of Sentinel 5P tropospheric nitrogen dioxide and total carbon monoxide columns over Punjab and Haryana Regions with COVID-19 lockdown impact.

This study conducts a spatio-temporal analysis of tropospheric nitrogen dioxide (NO2) and total carbon monoxide (CO) concentrations in the Punjab and Haryana regions of India and Pakistan, using datasets from the Sentinel 5-Precursor (S5P) satellite. These regions, marked by diverse economic growth factors including population expansion, power generation, transportation, and agricultural practices, face similar challenges in atmospheric pollution, particularly evident in major urban centers like Delhi and Lahore, identified as pollution hotspots. The study also spotlights pollution associated with power plants. In urban areas, tropospheric NO2 levels are predominantly elevated due to vehicular emissions, whereas residential activities mainly contribute to CO pollution. However, precisely attributing urban CO sources is complex due to its longer atmospheric residence time and intricate circulation patterns. Notably, the burning of rice crop residue in November significantly exacerbates winter pollution episodes and smog, showing a more pronounced correlation with total CO than with tropospheric NO2 levels. The temporal analysis indicates that the months from October to December witness peak pollution, contrasted with the relatively cleaner period during the monsoon months of July to September. The severe pollution in the OND quarter is attributed to factors such as variations in boundary layer height and depletion of OH radicals. Furthermore, the study highlights the positive impact of the COVID-19 lockdown on air quality, with a significant decrease in NO2 concentrations during April, 2020 (Delhi: 59%, Lahore: 58%). However, the reduction in total CO columns was less significant. The study also correlates lockdown stringency with tropospheric NO2 columns (R2: 0.37 for Delhi, 0.25 for Lahore, 0.22 for Rawalpindi/Islamabad), acknowledging the influence of various meteorological and atmospheric variables. The research highlights the significant impact of crop residue burning on winter pollution levels, particularly on total CO concentrations. The study also shows the notable effect of the COVID-19 lockdown on air quality, significantly reducing NO2 levels. Additionally, it explores the correlation between lockdown stringency and tropospheric NO2 columns, considering various meteorological factors.

Predicting tropospheric nitrogen dioxide column density in South African municipalities using socio-environmental variables and Multiscale Geographically Weighted Regression.

Atmospheric nitrogen dioxide (NO2) pollution is a major health and social challenge in South African induced mainly by fossil fuel combustions for power generation, transportation and domestic biomass burning for indoor activities. The pollution level is moderated by various environmental and social factors, yet previous studies made use of limited factors or focussed on only industrialised regions ignoring the contributions in large parts of the country. There is a need to assess how socio-environmenral factors, which inherently exhibit variations across space, influence the pollution levels in South Africa. This study therefore aimed to predict annual tropospheric NO2 column density using socio-environmental variables that are widely proven in the literature as sources and sinks of pollution. The environmental variables used to predict NO2 included remotely sensed Enhanced Vegetation Index (EVI), Land Surface Temperature and Aerosol Optical Depth (AOD) while the social data, which were obtained from national household surveys, included energy sources data, settlement patterns, gender and age statistics aggregated at municipality scale. The prediction was accomplished by applying the Multiscale Geographically Weighted Regression that fine-tunes the spatial scale of each variable when building geographically localised relationships. The model returned an overall R2 of 0.92, indicating good predicting performance and the significance of the socio-environmental variables in estimating NO2 in South Africa. From the environmental variables, AOD had the most influence in increasing NO2 pollution while vegetation represented by EVI had the opposite effect of reducing the pollution level. Among the social variables, household electricity and wood usage had the most significant contributions to pollution. Communal residential arrangements significantly reduced NO2, while informal settlements showed the opposite effect. The female proportion was the most important demographic variable in reducing NO2. Age groups had mixed effects on NO2 pollution, with the mid-age group (20-29) being the most important contributor to NO2 emission. The findings of the current study provide evidence that NO2 pollution is explained by socio-economic variables that vary widely across space. This can be achieved reliably using the MGWR approach that produces strong models suited to each locality.

Assessment of tropospheric nitrogen dioxide (NO2) levels on the COVID-19 pandemic in Morocco

After being discovered in Wuhan, China towards the end of December, the novel infectious disease with human-to-human transmission (COVID-19) spread around the world and became a pandemic. Globally, there have been over 4 million 600,000 COVID-19 cases reported, and over 300,000 patients have passed away. Many of the pre-existing diseases that are impacted by long-term exposure to air pollution are also those that raise the risk of infection and mortality in individuals with COVID-19. Under the locking conditions, the current study investigates this correlation at the national Moroccan level. TROPOMI data from the Sentinel-5P satellite is utilized to map the distribution of NO2 in the troposphere. According to the findings, three administrative regions with the highest tropospheric NO2 concentrations harbored 60% of the COVID-19 infected cases. When viewed within the global context, these findings suggest that prolonged exposure to this contaminant may play a role in the infection, death, and dissemination of the COVID-19 virus.

To new heights by flying low: comparison of aircraft vertical NO2 profiles to model simulations and implications for TROPOMI NO2 retrievals

Abstract. The sensitivity of satellites to air pollution close to the sea surface is decreased by the scattering of light in the atmosphere and low sea surface albedo. To reliably retrieve tropospheric nitrogen dioxide (NO2) columns using the TROPOspheric Monitoring Instrument (TROPOMI), it is therefore necessary to have good a priori knowledge of the vertical distribution of NO2. In this study, we use an aircraft of the Royal Belgian Institute of Natural Sciences equipped with a sniffer sensor system to measure NOx (= NO + NO2), CO2 and SO2. This instrumentation enabled us to evaluate vertical profile shapes from several chemical transport models and to validate TROPOMI tropospheric NO2 columns over the polluted North Sea in the summer of 2021. The aircraft sensor observes multiple clear signatures of ship plumes from seconds after emission to multiple kilometers downwind. Besides that, our results show that the chemical transport model Transport Model 5, Massively Parallel version (TM5-MP), which is used in the retrieval of the operational TROPOMI NO2 data, tends to underestimate surface level pollution – especially under conditions without land outflow – while overestimating NO2 at higher levels over the study region. The higher horizontal resolution in the regional CAMS (Copernicus Atmosphere Monitoring Service) ensemble mean and the LOTOS-EUROS (Long Term Ozone Simulation European Operational Smog) model improves the surface level pollution estimates. However, the models still systematically overestimate NO2 levels at higher altitudes, indicating exaggerated vertical mixing and overall too much NO2 in the models over the North Sea. When replacing the TM5 a priori NO2 profiles with the aircraft-measured NO2 profiles in the air mass factor (AMF) calculation, we find smaller recalculated AMFs. Subsequently, the retrieved NO2 columns increase by 20 %, indicating a significant negative bias in the operational TROPOMI NO2 data product (up to v2.3.1) over the North Sea. This negative bias has important implications for estimating emissions over the sea. While TROPOMI NO2 negative biases caused by the TM5 a priori profiles have also been reported over land, the reduced vertical mixing and smaller surface albedo over sea make this issue especially relevant over sea and coastal regions.

Application of the Multi-Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0) for air quality research in Africa

Abstract. The Multi-Scale Infrastructure for Chemistry and Aerosols Version 0 (MUSICAv0) is a new community modeling infrastructure that enables the study of atmospheric composition and chemistry across all relevant scales. We develop a MUSICAv0 grid with Africa refinement (∼ 28 km × 28 km over Africa). We evaluate the MUSICAv0 simulation for 2017 with in situ observations and compare the model results to satellite products over Africa. A simulation from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), a regional model that is widely used in Africa studies, is also included in the analyses as a reference. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Both models underestimate carbon monoxide (CO) compared to in situ observations and satellite CO column retrievals from the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument. MUSICAv0 tends to overestimate ozone (O3), likely due to overestimated stratosphere-to-troposphere flux of ozone. Both models significantly underestimate fine particulate matter (PM2.5) at two surface sites in East Africa. The MUSICAv0 simulation agrees better with aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) and tropospheric nitrogen dioxide (NO2) column retrievals from the Ozone Monitoring Instrument (OMI) than WRF-Chem. MUSICAv0 has a consistently lower tropospheric formaldehyde (HCHO) column than OMI retrievals. Based on model–satellite discrepancies between MUSICAv0 and WRF-Chem and MOPITT CO, MODIS AOD, and OMI tropospheric NO2, we find that future field campaign(s) and more in situ observations in the East African region (5∘ S–5∘ N, 30–45∘ E) could substantially improve the predictive skill of atmospheric chemistry model(s). This suggested focus region exhibits the largest model–in situ observation discrepancies, as well as targets for high population density, land cover variability, and anthropogenic pollution sources.

Analysis of variation characteristics, transport paths, and influencing factors of atmospheric NO2 pollution in Western Europe.

Climate change and air pollution are one of the global environmental problems. It is significant to grasp the air pollution situation of Western Europe in recent 10 years for its or the global pollution control. Based on the OMI tropospheric nitrogen dioxide (NO2) column density data, the spatial and temporal distribution characteristics, variation trend, transmission path, and influencing factors of NO2 in 15 countries in Western Europe from 2011 to 2022 are discussed in this paper. Meanwhile, the annual average spatial and temporal distribution in 2023 is predicted by the random forest (RF) model. The results showed that (1) the 12-year spatial distribution map showed an increasing trend from southwest to northeast, with the border area of the Netherlands and Germany and Milan as two high-value areas, and the overall trend over time was that the high-concentration area gradually shrank, the low-concentration area gradually expanded, and the annual average concentration gradually decreased. (2) The inter-month trend presents a "U" shape, with the mean NO2 pollution ranking in winter > autumn > spring > summer. (3) Natural factors are one of the reasons affecting NO2; for instance, NO2 pollution has a strong positive correlation with the lifted index, relative humidity, and wind speed and a moderately strong negative correlation with precipitable water and air temperature. (4) Exogenous atmospheric transport is another important factor affecting the change of NO2 pollution in Western Europe. The HYSPLIT model is used to analyze the backward trajectory of Milan, Italy, and Nijmegen, Netherlands, in the four seasons of 2022. Both are mainly influenced by westerly airflows, and therefore, the transport effect in the atmosphere brings air pollutants from westerly regions in the atmosphere.

Temporal assessment of air quality in major cities in Nigeria using satellite data

This study evaluated the concentrations of tropospheric nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and Aerosol Index (AI) as well as different meteorological parameters, including atmospheric temperature (AT), relative humidity (RH), and wind speed (WS) in nine Nigerian cities: Aba, Benin, Ibadan, Kaduna, Kano, Lagos, Onitsha, Port Harcourt, and Umuahia. The role of socioeconomic activities on air pollution was also investigated using nighttime light radiance as a surrogate measure. Welch's one-way ANOVA test was performed for the variance study to evaluate the concentration dynamics of the selected tropospheric air pollutants and their association with nighttime light radiance. The mean concentration of CO and AI was highest in Kano, while that of O3 was the lowest. A similar pattern was also observed in the spatiotemporal transition of the selected pollutants and the nighttime light during the study period. Further, the correlation analysis revealed that AT is positively correlated with NO2 except in Aba and Benin cities, while it is positively correlated with CO and AI for all cities. The principal component analysis (PCA) revealed that O3 and RH have strong negative factor loadings, whereas CO, AI, and AT have strong positive factor loadings. This study will guide future researchers by associating the level of pollution with socioeconomic activities, especially during the absence of permanent air quality stations.

Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine

Since February 2022, the full-scale war in Ukraine has been strongly affecting society and economy in Ukraine and beyond. Satellite observations are crucial tools to objectively monitor and assess the impacts of the war. We combine satellite-based tropospheric nitrogen dioxide (NO2) and carbon dioxide (CO2) observations to detect and characterize changes in human activities, as both are linked to fossil fuel combustion processes. We show significantly reduced NO2 levels over the major Ukrainian cities, power plants and industrial areas: the NO2 concentrations in the second quarter of 2022 were 15–46% lower than the same quarter during the reference period 2018–2021, which is well below the typical year-to-year variability (5–15%). In the Ukrainian capital Kyiv, the NO2 tropospheric column monthly average in April 2022 was almost 60% smaller than 2019 and 2021, and about 40% smaller than 2020 (the period mostly affected by the COVID-19 restrictions). Such a decrease is consistent with the essential reduction in population and corresponding emissions from the transport and commercial/residential sectors over the major Ukrainian cities. The NO2 reductions observed in the industrial regions of eastern Ukraine reflect the decline in the Ukrainian industrial production during the war (40–50% lower than in 2021), especially from the metallurgic and chemical industry, which also led to a decrease in power demand and corresponding electricity production by thermal power plants (which was 35% lower in 2022 compared to 2021). Satellite observations of land properties and thermal anomalies indicate an anomalous distribution of fire detections along the front line, which are attributable to shelling or other intentional fires, rather than the typical homogeneously distributed fires related to crop harvesting. The results provide timely insights into the impacts of the ongoing war on the Ukrainian society and illustrate how the synergic use of satellite observations from multiple platforms can be useful in monitoring significant societal changes. Satellite-based observations can mitigate the lack of monitoring capability during war and conflicts and enable the fast assessment of sudden changes in air pollutants and other relevant parameters.

Rapid O3 assimilations – Part 2: Tropospheric O3 changes accompanied by declining NOx emissions in the USA and Europe in 2005–2020

Abstract. Tropospheric nitrogen dioxide (NO2) concentrations have declined dramatically over the United States (USA) and Europe in recent decades. Here we investigate the changes in surface and free-tropospheric O3 accompanied by NO2 changes over the USA and Europe in 2005–2020 by assimilating the Ozone Monitoring Instrument (OMI) and U.S. Air Quality System (AQS) and European AirBase network O3 observations. The assimilated O3 concentrations demonstrate good agreement with O3 observations. Surface O3 concentrations are 41.4, 39.5, and 39.5 ppb (parts per billion; USA) and 35.3, 32.0, and 31.6 ppb (Europe) and tropospheric O3 columns are 35.5, 37.0, and 36.8 DU (USA) and 32.8, 35.3, and 36.4 DU (Europe) in the simulations, assimilations, and observations, respectively. We find overestimated summertime surface O3 concentrations over the USA and Europe, which resulted in a surface O3 maximum in July–August in the simulations, which is in contrast to April in the observations. Furthermore, our analysis exhibits limited changes in surface O3 concentrations; i.e., they decreased by −6 % over the USA and increased by 1.5 % over Europe in 2005–2020. The surface observation-based assimilations suggest insignificant changes in tropospheric O3 columns, namely −3.0 % (USA) and 1.5 % (Europe) in 2005–2020. While the OMI-based assimilations exhibit larger decreases in tropospheric O3 columns, with −12.0 % (USA) and −15.0 % (Europe) in 2005–2020, the decreases mainly occurred in 2010–2014, corresponding to the reported slower decline in free-tropospheric NO2 since 2010. Our analysis thus suggests that there are limited impacts of the decline in local emissions on tropospheric O3 over the USA and Europe and advises more efforts to evaluate the possible contributions of natural sources and transport. The discrepancy in assimilated tropospheric O3 columns further indicates the possible uncertainties in the derived tropospheric O3 changes.

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.

Characteristics of Air Pollutant Distribution and Sources in the East China Sea and the Yellow Sea in Spring Based on Multiple Observation Methods

The composition of marine aerosol is quite complex, and its sources are diverse. Across the East China Sea (ECS) and the Yellow Sea (YS), multi-dimensional analysis of marine aerosols was conducted. The characteristics of carbonaceous aerosols and gaseous pollutants were explored through in situ ship-based observation, MERRA-2 reanalysis datasets and TROPOMI data from Sentinel-5P satellite. Black carbon (BC)’s average concentration is 1.35 ± 0.78 μg/m3, with high-value BC observed during the cruise. Through HYSPLIT trajectory analysis, sources of BC were from the northern Eurasian continent, the Shandong Peninsula, the ECS and Northwest Pacific Ocean (NWPO). The transport of marine sources like ship emissions cannot be ignored. According to the absorption Angstrom exponent (AAE), BC originates from biomass burning (BB) in the shortwave band (~370 nm) and from fossil fuel combustion in the longwave band (~660 nm). Organic carbon (OC), sulfate (SO42−) and BC report higher Angstrom exponent (AE) while dust and sea salt reveal lower AE, which can be utilized to classify the aerosols as being fine- or coarse-mode, respectively. OC has the highest AE (ECS: 1.98, YS: 2.01), indicating that anthropogenic activities could be a significant source. The process of biomass burning aerosol (BBA) mixed with sea salt could contribute to the decline in BBA’s AE. Ship emissions may affect the distribution of tropospheric nitrogen dioxide (NO2) in the ECS, especially during the COVID-19 pandemic. Tropospheric NO2 over the YS has the highest value (up to 12 × 1015 molec/cm2). Stratospheric NO2 has a ladder-like distribution from north to south, and the variation gradient was lower than that in the troposphere. Carbon monoxide (CO) accumulates in the south and east of the ECS and the east of the YS, while the variation over the eastern YS is relatively frequent. Seas near the Korean Peninsula have extremely high CO concentration (up to 1.35 × 1017 molec/cm2).

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.

Highly resolved mapping of NO2 vertical column densities from GeoTASO measurements over a megacity and industrial area during the KORUS-AQ campaign

Abstract. The Korea–United States Air Quality (KORUS-AQ) campaign is a joint study between the United States National Aeronautics and Space Administration (NASA) and the South Korea National Institute of Environmental Research (NIER) to monitor megacity and transboundary air pollution around the Korean Peninsula using airborne and ground-based measurements. Here, tropospheric nitrogen dioxide (NO2) slant column density (SCD) measurements were retrieved from Geostationary Trace and Aerosol Sensor Optimization (GeoTASO) L1B data during the KORUS-AQ campaign (2 May to 10 June 2016). The retrieved SCDs were converted to tropospheric vertical column densities using the air mass factor (AMF) obtained from a radiative transfer calculation with trace gas profiles and aerosol property inputs simulated with the Community Multiscale Air Quality (CMAQ) model and surface reflectance data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). For the first time, we examine highly resolved (250 m × 250 m resolution) tropospheric NO2 over the Seoul and Busan metropolitan regions and the industrial region of Anmyeon. We reveal that the maximum NO2 vertical column densities (VCDs) were 4.94×1016 and 1.46×1017 molec. cm−2 at 09:00 and 15:00 LT over Seoul, respectively, 6.86×1016 and 4.89×1016 molec. cm−2 in the morning and afternoon over Busan, respectively, and 1.64×1016 molec. cm−2 over Anmyeon. The VCDs retrieved from the GeoTASO airborne instrument were correlated with those obtained from the Ozone Monitoring Instrument (OMI) (r=0.48), NASA's Pandora Spectrometer System (r=0.91), and NO2 mixing ratios obtained from in situ measurements (r=0.07 in the morning, r=0.26 in the afternoon over the Seoul, and r&gt;0.56 over Busan). Based on our results, GeoTASO is useful for identifying NO2 hotspots and their spatial distribution in highly populated cities and industrial areas.

Changes in Tropospheric Nitrogen Dioxide Vertical Column Densities over Japan and Korea during the COVID-19 Using Pandora and MAX-DOAS

We investigated the impact of human activity during COVID-19 on the tropospheric nitrogen dioxide vertical column density (NO2 TropVCD) at three urban sites (Gwangju and Busan in Korea and Yokosuka in Japan) and one remote site (Cape Hedo in Japan) from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) and Pandora. Compared to the monthly mean NO2 TropVCD from 2015 to 2018 and in 2019, the values were lower in 2020 due to social distancing in Korea and Japan. High negative relative changes were observed from May to September (−30% to −18%) at the three urban sites; Cape Hedo, a remote site, did not show a significant difference in relative changes between previous years and 2020, suggesting that only anthropogenic emission sources decreased dramatically. In the case of Yokosuka, the 15-day moving average of the NO2 TropVCD exhibited a good relationship with transportation (R = 0.48) and industry (R = 0.54) mobility data. In contrast, the NO2 TropVCD at the Korean sites showed a moderate to low correlation with the industrial sector and insignificant correlations with transportation. The differences in correlations might be caused by the different social distancing policies in Korea (voluntary) and Japan (mandatory). By applying generalized boosted models to exclude meteorological and seasonal effects associated with NO2 TropVCD variations, we revealed that the decreasing trend from 2019 to 2020 was much steeper than that from 2015 to 2020 (a factor of two), and a significant change was identified in January 2020, when the first cases of COVID-19 were observed in both Korea and Japan. This result confirmed that the reduction in NO2 can be largely explained by the NOx emission reduction resulting from social distancing for COVID-19 rather than annual meteorological differences; however, in December 2020, NO2 recovered suddenly to its previous level due to an increase in human activities.

Response of tropospheric nitrogen dioxide variations based on Major Function Oriented Zones over eastern China during 2006–2021

Response of tropospheric nitrogen dioxide variations based on Major Function Oriented Zones over eastern China during 2006–2021