Comprehensive evaluations of diurnal NO2 measurements during DISCOVER-AQ 2011: effects of resolution-dependent representation of NO x emissions

Nitrogen oxides (NO _x =NO+NO₂) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO₂ are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO₂ concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment - 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore-Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO₂ observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO₂ (O₃) surface concentrations during night-time, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO₂ TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NO _x emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO₂ vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NO _x emissions in the National Emissions Inventory (NEI) 2011.

Environmental impact of COVID-19 led lockdown: A satellite data-based assessment of air quality in Indian megacities

The strategies to contain the spread of COVID-19 pandemic, including restricted human movement and economic activities, have shown positive impacts on the environment. Present research analysed the effects of COVID-19 led lockdown on air quality with special reference to major pollutants, namely nitrogen dioxide (NO₂), carbon monoxide (CO), sulphur dioxide (SO₂) and aerosol optical depth (AOD). The assessment has been conducted for megacities of India (Delhi, Mumbai, Bengaluru, Chennai and Kolkata) for four months, that is, March and April in 2019 and 2020 using Sentinel 5P and MCD19A2 data. A decrease in concentrations of air pollutants, specifically NO₂ and SO_2, has been observed during the lockdown period in all the cities; whereas CO and AOD have exhibited discrete pattern of spatio-temporal variation. Four megacities except Kolkata have revealed a positive correlation between NO₂ concentration and population density. The results conclude overall improvement in air quality during COVID-19 led lockdown. The current situation provides a unique opportunity to implement a structural economic change that could help us move towards a city with low emission economy. Realizing the achievable improvement of air quality, the study suggests further in-depth research on source attribution of individual pollutants to assess the prospect of emission reduction actions.

Evaluation of OMI NO2 Vertical Columns Using MAX-DOAS Observations over Mexico City

Nitrogen dioxide (NO2) is a gas pollutant that can be measured from space and several operational products are now available from instruments on-board of satellite-based platforms. There are still, however, many unknowns about the accuracy of these products under different viewing and surface conditions since ground-based observations are generally scarce. This is particularly the case of high-altitude sub-tropical megacities such as the Mexico City Metropolitan Area (MCMA). In this study, we use more than five years of data from four ground-based MAX-DOAS instruments distributed within the MCMA in order to evaluate the DOMINO product from the Ozone Monitoring Instrument (OMI) on board the Aura satellite. We compare OMI against each MAX-DOAS site independently using the vertical column densities (VCDs) reported by each instrument. The VCDs are also compared after smoothing the MAX-DOAS profiles with the a priori and the Averaging Kernels of the satellite product. We obtain an overall correlation coefficient (R) of 0.6 that does not improve significantly after the smoothing is applied. However, the slopes in the linear regressions for the individual sites improve when applying the smoothing from 0.36 to 0.62 at UNAM, from 0.26 to 0.49 at Acatlán, from 0.78 to 1.23 at Vallejo, and from 0.50 to 0.97 at the Cuautitlán station. The large differences observed between the OMI and MAX-DOAS VCDs are attributed to a reduced sensitivity of the satellite product near the surface and the large aerosol loading typically present within the mixed layer of the MCMA. This may also contribute to a slight overestimation of the VCDs from the MAX-DOAS measurements that presents a total error (random + systematic) of about 20%. As a result of this comparison, we find that OMI retrievals are on average 56% lower than the MAX-DOAS without any correction. The near-surface concentrations are estimated from the lowest layers of the MAX-DOAS retrievals and these compare well with surface measurements from in situ analyzers operated at the co-located air quality monitoring stations. The diurnal variability for each station is analyzed and discussed in relation to their location within the city.

TROPOMI NO2 Tropospheric Column Data: Regridding to 1 km Grid-Resolution and Assessment of their Consistency with In Situ Surface Observations

This work presents a regridding procedure applied to the nitrogen dioxide (NO2) tropospheric column data, derived from the Copernicus Sentinel 5 Precursor Tropospheric Monitoring Instrument (S5P/TROPOMI). The regridding has been performed to provide a better comparison with punctual surface observations. It will be demonstrated that TROPOMI NO2 tropospheric column data show improved consistency with in situ surface measurements once the satellite retrievals are scaled to 1 km spatial sampling. A geostatistical technique, i.e., the ordinary kriging, has been applied to improve the spatial distribution of Level 2 TROPOMI NO2 data, which is originally sparse and uneven because of gaps introduced by clouds, to a final spatial, regular, sampling of 1 km × 1 km. The analysis has been performed for two study areas, one in the North and the other in the South of Italy, and for May 2018-April 2020, which also covers the period January 2020-April 2020 of COVID-19 diffusion over the Po Valley. The higher spatial sampling NO2 dataset indicated as Level 3 data, allowed us to explore spatial and seasonal data variability, obtaining better information on NO2 sources. In this respect, it will be shown that NO2 concentrations in March 2020 have likely decreased as a consequence of the lockdown because of COVID-19, although the far warmest winter season ever recorded over Europe in 2020 has favored a general NO2 decrease in comparison to the 2019 winter. Moreover, the comparison between NO2 concentrations related to weekdays and weekend days allowed us to show the strong correlation of NO2 emissions with traffic and industrial activities. To assess the quality and capability of TROPOMI NO2 observations, we have studied their relationship and correlation with in situ NO2 concentrations measured at air quality monitoring stations. We have found that the correlation increases when we pass from Level 2 to Level 3 data, showing the importance of regridding the satellite data. In particular, correlation coefficients of Level 3 data, which range between 0.50–0.90 have been found with higher correlation applying to urban, polluted locations and/or cities.

Assessment of NO2 observations during DISCOVER-AQ and KORUS-AQ field campaigns

NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011-2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (> 312 km2).

Effects of local meteorology and aerosols on ozone and nitrogen dioxide retrievals from OMI and pandora spectrometers in Maryland, USA during DISCOVER-AQ 2011

An analysis is presented for both ground- and satellite-based retrievals of total column ozone and nitrogen dioxide levels from the Washington, D.C., and Baltimore, Maryland, metropolitan area during the NASA-sponsored July 2011 campaign of Deriving Information on Surface COnditions from Column and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Satellite retrievals of total column ozone and nitrogen dioxide from the Ozone Monitoring Instrument (OMI) on the Aura satellite are used, while Pandora spectrometers provide total column ozone and nitrogen dioxide amounts from the ground. We found that OMI and Pandora agree well (residuals within ±25 % for nitrogen dioxide, and ±4.5 % for ozone) for a majority of coincident observations during July 2011. Comparisons with surface nitrogen dioxide from a Teledyne API 200 EU NO_x Analyzer showed nitrogen dioxide diurnal variability that was consistent with measurements by Pandora. However, the wide OMI field of view, clouds, and aerosols affected retrievals on certain days, resulting in differences between Pandora and OMI of up to ±65 % for total column nitrogen dioxide, and ±23 % for total column ozone. As expected, significant cloud cover (cloud fraction >0.2) was the most important parameter affecting comparisons of ozone retrievals; however, small, passing cumulus clouds that do not coincide with a high (>0.2) cloud fraction, or low aerosol layers which cause significant backscatter near the ground affected the comparisons of total column nitrogen dioxide retrievals. Our results will impact post-processing satellite retrieval algorithms and quality control procedures.

Space-based constraints on spatial and temporal patterns of NO(x) emissions in California, 2005-2008

We describe ground and space-based measurements of spatial and temporal variation of NO(2) in four California metropolitan regions. The measurements of weekly cycles and trends over the years 2005-2008 observed both from the surface and from space are nearly identical to each other. Observed decreases in Los Angeles and the surrounding cities are 46% on weekends and 9%/year from 2005-2008. Similar decreases are observed in the San Francisco Bay area and in Sacramento. In the San Joaquin Valley cities of Fresno and Bakersfield weekend decreases are much smaller, only 27%, and the decreasing trend is only 4%/year. We describe evidence that the satellite observations provide a uniquely complete view of changes in spatial patterns over time. For example, we observe variations in the spatial pattern of weekday-weekend concentrations in the Los Angeles basin with much steeper weekend decreases at the eastern edge of the basin. We also observe that the spatial extent of high NO(2) in the San Joaquin Valley has not receded as much as it has for other regions in the state. Analysis of these measurements is used to describe observational constraints on temporal trends in emission sources in the different regions.