Ozone Monitoring Instrument Products Research Articles

Satellite-based estimates of daily NO2 exposure in urban agglomerations of China and application to spatio-temporal characteristics of hotspots

The analysis of the daily spatial patterns of near-surface Nitrogen dioxide (NO2) concentrations can assist decision makers mitigate this common air pollutant in urban areas. However, comparative analysis of NO2 estimates in different urban agglomerations of China is limited. In this study, a new linear mixed effect model (LME) with multi-source spatiotemporal data is proposed to estimate daily NO2 concentrations at high accuracy based on the land-use regression (LUR) model and Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) products. In addition, three models for NO2 concentration estimation were evaluated and compared in four Chinese urban agglomerations from 2018 to 2020, including the COVID-19 closed management period. Each model included a unique combination of methods and satellite NO2 products: ModelⅠ: LUR model with OMI products; Model Ⅱ: LUR model with TropOMI products; Model Ⅱ: LME model with TropOMI products. The results show that the LME model outperformed the LUR model in all four urban agglomerations as the average RMSE decreased by 16.09% due to the consideration of atmospheric dispersion random effects, and using TropOMI instead of OMI products can improve the accuracy. Based on our NO2 estimations, pollution hotspots were identified, and pollution anomalies during the COVID-19 period were explored for two periods; the lockdown and revenge pollution periods. The largest NO2 pollution difference between the hotspot and non-hotspot areas occurred in the second period, especially in the heavy industrial urban agglomerations.

An agricultural biomass burning episode in eastern China: Transport, optical properties, and impacts on regional air quality

AbstractAgricultural biomass burning (ABB) has been of particular concern due to its influence on air quality and atmospheric radiation, as it produces large amounts of gaseous and aerosol emissions. This paper presents an integrated observation of a significant ABB episode in Nanjing, China, during early June 2011, using combined ground‐based and satellite sensors (Moderate Resolution Imaging Spectroradiometer, Atmospheric Infrared Sounder, Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), and Ozone Monitoring Instrument products). The time‐height distribution, optical properties, sources and transport of smoke, and its impacts on air quality are investigated. Lidar profiles indicate that the smoke aerosols are confined to the planetary boundary layer (PBL) and have a depolarization ratio of less than 0.08. The aerosol optical depths increase from 0.5 to 3.0 at 500 nm, while the extinction‐related Angstrom exponent increases from 1.1 to 1.6 at the wavelength pair of 440–870 nm. The single‐scattering albedo becomes lower at 670–1020 nm following the ABB intrusion and particularly shows a decreasing tendency between wavelengths of 440 to 1020 nm. The absorption Angstrom exponent (0.7) is smaller than 1.0, which may indicate the aged smoke particles mixed or coated with the urban aerosols. Surface particular matter PM10 and PM2.5 show a dramatic increase, reaching hourly mean of 800 µg/m3 and 485 µg/m3, respectively, which results in a heavy air pollution event. The stagnant and high‐moisture weather provides favorable conditions for the aerosols to accumulate near the surface. Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) also illustrate that the large‐scale aerosols are primarily present in the PBL and transported to the ocean, but some dense smoke plumes are misclassified as cloud or polluted dust. By comparing with the observations, we found that the Weather Research and Forecasting–Chemistry model captured the accumulation and downwind transport of surface PM2.5 from 20:00 on 2 June to 10:00 on 3 June (phase 1) but showed a dramatic underestimate from 20:00 on 3–4 June (phase 2) when dense aerosols are present. Such a discrepancy in the model is associated with the improper vertical apportion of transported smoke and atmospheric diffusion conditions when comparing with the observed aerosol and wind profiles. In addition, the model simulations indicate that the transported smoke can contribute to 50–70% of the ground‐level PM2.5 in Nanjing.

Smithsonian Astrophysical Observatory Ozone Mapping and Profiler Suite (SAO OMPS) formaldehyde retrieval

Abstract. This paper presents our new formaldehyde (H2CO) retrievals, obtained from spectra recorded by the nadir instrument of the Ozone Mapping and Profiler Suite (OMPS) flown on board NASA's Suomi National Polar-orbiting Partnership (SUOMI-NPP) satellite. Our algorithm is similar to the one currently in place for the production of NASA's Ozone Monitoring Instrument (OMI) operational H2CO product. We are now able to produce a set of long-term data from two different instruments that share a similar concept and a similar retrieval approach. The ongoing overlap period between OMI and OMPS offers a perfect opportunity to study the consistency between both data sets. The different spatial and spectral resolution of the instruments is a source of discrepancy in the retrievals despite the similarity of the physic assumptions of the algorithm. We have concluded that the reduced spectral resolution of OMPS in comparison with OMI is not a significant obstacle in obtaining good-quality retrievals. Indeed, the improved signal-to-noise ratio of OMPS with respect to OMI helps to reduce the noise of the retrievals performed using OMPS spectra. However, the size of OMPS spatial pixels imposes a limitation in the capability to distinguish particular features of H2CO that are discernible with OMI. With root mean square (RMS) residuals ∼ 5 × 10−4 for individual pixels we estimate the detection limit to be about 7.5 × 1015 molecules cm−2. Total vertical column density (VCD) errors for individual pixels range between 40 % for pixels with high concentrations to 100 % or more for pixels with concentrations at or below the detection limit. We compare different OMI products (SAO OMI v3.0.2 and BIRA OMI v14) with our OMPS product using 1 year of data, between September 2012 and September 2013. The seasonality of the retrieved slant columns is captured similarly by all products but there are discrepancies in the values of the VCDs. The mean biases among the two OMI products and our OMPS product are 23 % between OMI SAO and OMPS SAO and 28 % between OMI BIRA and OMPS SAO for eight selected regions.

Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis

Abstract. A radiative transfer interface has been developed to simulate the UV aerosol index (AI) from the NASA Goddard Earth Observing System version 5 (GEOS-5) aerosol assimilated fields. The purpose of this work is to use the AI and aerosol absorption optical depth (AAOD) derived from the Ozone Monitoring Instrument (OMI) measurements as independent validation for the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Since AI is dependent on aerosol concentration, optical properties and altitude of the aerosol layer, we make use of complementary observations to fully diagnose the model, including AOD from the Multi-angle Imaging SpectroRadiometer (MISR), aerosol retrievals from the AErosol RObotic NETwork (AERONET) and attenuated backscatter coefficients from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission to ascertain potential misplacement of plume height by the model. By sampling dust, biomass burning and pollution events in 2007 we have compared model-produced AI and AAOD with the corresponding OMI products, identifying regions where the model representation of absorbing aerosols was deficient. As a result of this study over the Saharan dust region, we have obtained a new set of dust aerosol optical properties that retains consistency with the MODIS AOD data that were assimilated, while resulting in better agreement with aerosol absorption measurements from OMI. The analysis conducted over the southern African and South American biomass burning regions indicates that revising the spectrally dependent aerosol absorption properties in the near-UV region improves the modeled-observed AI comparisons. Finally, during a period where the Asian region was mainly dominated by anthropogenic aerosols, we have performed a qualitative analysis in which the specification of anthropogenic emissions in GEOS-5 is adjusted to provide insight into discrepancies observed in AI comparisons.

Validation of OMI total ozone retrievals from the SAO ozone profile algorithm and three operational algorithms with Brewer measurements

Abstract. The accuracy of total ozone computed from the Smithsonian Astrophysical Observatory (SAO) optimal estimation (OE) ozone profile algorithm (SOE) applied to the Ozone Monitoring Instrument (OMI) is assessed through comparisons with ground-based Brewer spectrometer measurements from 2005 to 2008. We also compare the three OMI operational ozone products, derived from the NASA Total Ozone Mapping Spectrometer (TOMS) algorithm, the KNMI (Royal Netherlands Meteorological Institute) differential optical absorption spectroscopy (DOAS) algorithm, and KNMI's Optimal Estimation (KOE) algorithm. The best agreement is observed between SAO and Brewer, with a mean difference of within 1% at most individual stations. The KNMI OE algorithm systematically overestimates Brewer total ozone by 2% at low and mid-latitudes and 5% at high latitudes while the TOMS and DOAS algorithms underestimate it by ~1.65% on average. Standard deviations of ~1.8% are calculated for both SOE and TOMS, but DOAS and KOE have higher values of 2.2% and 2.6%, respectively. The stability of the SOE algorithm is found to have insignificant dependence on viewing geometry, cloud parameters, or total ozone column. In comparison, the KOE–Brewer differences are significantly correlated with solar and viewing zenith angles and show significant deviations depending on cloud parameters and total ozone amount. The TOMS algorithm exhibits similar stability to SOE with respect to viewing geometry and total column ozone, but has stronger cloud parameter dependence. The dependence of DOAS on observational geometry and geophysical conditions is marginal compared to KOE, but is distinct compared to the SOE and TOMS algorithms. Comparisons of all four OMI products with Brewer show no apparent long-term drift, but seasonal features are evident, especially for KOE and TOMS. The substantial differences in the KOE vs. SOE algorithm performance cannot be sufficiently explained by the use of soft calibration (in SOE) and the use of different a priori error covariance matrices; however, other algorithm details cause fitting residuals larger by a factor of 2–3 for KOE.

Use of satellite erythemal UV products in analysing the global UV changes

Abstract. Long term changes in solar UV radiation affect global bio-geochemistry and climate. The satellite-based dataset of TOMS (Total Ozone Monitoring System) and OMI (Ozone Monitoring Instrument) of erythemal UV product was applied for the first time to estimate the long-term ultraviolet (UV) changes at the global scale. The analysis of the uncertainty related to the different input information is presented. OMI and GOME-2 (Global Ozone Monitoring Experiment-2) products were compared in order to analyse the differences in the global UV distribution and their effect on the linear trend estimation. The results showed that the differences in the inputs (mainly surface albedo and aerosol information) used in the retrieval, affect significantly the UV change calculation, pointing out the importance of using a consistent dataset when calculating long term UV changes. The areas where these differences played a major role were identified using global maps of monthly UV changes. Despite the uncertainties, significant positive UV changes (ranging from 0 to about 5 %/decade) were observed, with higher values in the Southern Hemisphere at mid-latitudes during spring-summer, where the largest ozone decrease was observed.

An emission source inversion model based on satellite data and its application in air quality forecasts

This paper aims at constructing an emission source inversion model using a variational processing method and adaptive nudging scheme for the Community Multiscale Air Quality Model (CMAQ) based on satellite data to investigate the applicability of high resolution OMI (Ozone Monitoring Instrument) column concentration data for air quality forecasts over the North China. The results show a reasonable consistency and good correlation between the spatial distributions of NO2 from surface and OMI satellite measurements in both winter and summer. Such OMI products may be used to implement integrated variational analysis based on observation data on the ground. With linear and variational corrections made, the spatial distribution of OMI NO2 clearly revealed more localized distributing characteristics of NO2 concentration. With such information, emission sources in the southwest and southeast of North China are found to have greater impacts on air quality in Beijing. When the retrieved emission source inventory based on high-resolution OMI NO2 data was used, the coupled Weather Research Forecasting CMAQ model (WRF-CMAQ) performed significantly better in forecasting NO2 concentration level and its tendency as reflected by the more consistencies between the NO2 concentrations from surface observation and model result. In conclusion, satellite data are particularly important for simulating NO2 concentrations on urban and street-block scale. High-resolution OMI NO2 data are applicable for inversing NOx emission source inventory, assessing the regional pollution status and pollution control strategy, and improving the model forecasting results on urban scale.

Satellite observations of recent power plant construction in Inner Mongolia, China

About 50% of the increase in China's NOx emissions since 2000 can be attributed to the construction of new power plants. We show that the newly added NOx emissions from new power plants in Inner Mongolia, China, were detected by the Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite. Increase rates of NO2 columns from OMI and NOx emissions from inventories are even in quantitative agreement in cases where new facilities are added to already‐developed regions. This study confirms that the OMI products are quite capable of identifying the construction of large new emitting facilities through detection of their NOx emissions.

Comparison of OMI ozone and UV irradiance data with ground-based measurements at two French sites

Abstract. Ozone Monitoring Instrument (OMI), launched in July 2004, is dedicated to the monitoring of the Earth's ozone, air quality and climate. OMI is the successor of the Total Ozone Mapping Spectrometer (TOMS) instruments and provides among other atmospheric and radiometric quantities the total column of ozone (TOC), the surface ultraviolet (UV) irradiance at several wavelengths, the erythemal dose rates and the erythemal daily doses. The main objective of this work is to compare OMI data with data from ground-based instruments in order to use OMI products (collection 2) for scientific studies. The Laboratoire d'Optique Atmosphérique (LOA) located in Villeneuve d'Ascq (VdA) in the north of France performs solar UV measurements using a spectroradiometer. The site of Briançon in the French Southern Alps is also equipped with a spectroradiometer operated by Interaction Rayonnement Solaire Atmosphère (IRSA). The OMI total ozone column data is obtained from the OMI-TOMS and OMI-DOAS algorithms. The comparison between the TOC retrieved with ground-based measurements and OMI-TOMS data shows good agreement at both sites for all sky conditions with a relative difference for most of points better than 5%. For OMI-DOAS data, the agreement is generally better than 7% and these data show a significant dependence on solar zenith angle. Comparisons of spectral UV on clear sky conditions are also satisfying with relative differences smaller than 10% except at solar zenith angles larger than 65°. On the contrary, results of comparisons of the erythemal dose rates and erythemal daily doses for clear sky show that OMI overestimates surface UV doses at VdA by about 15% and that on cloudy skies, the bias increases. At Briançon, such a bias is observed if data corresponding to snow-covered surface are excluded.

Tracking volcanic sulfur dioxide clouds for aviation hazard mitigation

Satellite measurements of volcanic sulfur dioxide (SO2) emissions can provide critical information for aviation hazard mitigation, particularly when ash detection techniques fail. Recent developments in space-based SO2 monitoring are discussed, focusing on daily, global ultraviolet (UV) measurements by the Ozone Monitoring Instrument (OMI) on NASA’s Aura satellite. OMI’s high sensitivity to SO2 permits long-range tracking of volcanic clouds in the upper troposphere and lower stratosphere (UTLS) and accurate mapping of their perimeters to facilitate avoidance. Examples from 2006 to 2007 include eruptions of Soufriere Hills (Montserrat), Rabaul (Papua New Guinea), Nyamuragira (DR Congo), and Jebel at Tair (Yemen). A tendency for some volcanic clouds to occupy the jet stream suggests an increased threat to aircraft that exploit this phenomenon. Synergy between NASA A-Train sensors such as OMI and the Atmospheric Infrared Sounder (AIRS) on the Aqua satellite can provide critical information on volcanic cloud altitude. OMI and AIRS SO2 data products are being produced in near real-time for distribution to Volcanic Ash Advisory Centers (VAACs) via a NOAA website. Operational issues arising from these improved SO2 measurements include the reliability of SO2 as proxy for co-erupted ash, the duration of VAAC advisories for long-lived volcanic clouds, and the potential effects of elevated concentrations of SO2 and sulfate aerosol in ash-poor clouds on aircraft and avionics (including cumulative effects after multiple inadvertent transits through dilute clouds). Further research is required in these areas. Aviation community assistance is sought through continued reporting of sulfurous odors or other indications of diffuse volcanic cloud encounters, in order to validate the satellite retrievals.