Aerosol satellite remote sensing

Aerosols are inportant for many processes in the atmosphere. Aerosols are a leading uncertainty in predicting global climate change, To a large extent this uncertainty is caused by a lack of knowledge on the occurrence and concentration of aerosols. On global scale, this information can only be obtained by satellite remote sensing. In this thesis three techniques satellite remote sensing are presented. One of these applies only over the ocean, the other two were primarily designed for use over land. These methods compute the spectral aerosol optical depth, which is the column integrated aerosol extinction coefficient along a vertical path through the atmosphere. The different retrieval methods were applied to data from the Along Track Scanning Radiometer 2 (ATSR-2), the Advanced Very High Resolution Radiometer (AVHRR) and the Global Ozone Monitoring Experiment (GOME). Comparisons with ground based and airbornemeasurements showed that the aerosol optical depth and its spectral behavior can accurately be determined using satellite remote sensing methods. Frequently, very high spatial gradients in the aerosol optical depth, typically a factor of two or three over less than a hundred kilomneters were observed. The aerosol optical depth determined using satellite remote sensing was compared to results from a chemical transport model. These comparisons show reasonable agreement, particularly in regard of the large assumptions in the method to derive the aerosol optical depth from the model results

Aerosol optical depth retrieval over land from two angle view satellite radiometry

Atmospheric aerosol particles play an important role in the Earth’s radiation balance. They are considered one of the largest uncertainties in today’s climate modelling. To a large extent, these uncertainties are caused by the lack of aerosol data on a global scale. Due to the short lifetimes of aerosols in the troposphere (hours to a week), and the many different sources with different spatial extents and emissions, the aerosol is highly variable in both space and time. Satellite remote sensing only can provide the global coverage and the spatial and temporal resolution to measure the inhomogeneous aerosol fields

A TROPOMI- and GLM-Based Estimate of NOx Production by Lightning over the U.S.

Lightning produces NO because the extreme temperatures (>20000 K) in lightning channels dissociate molecular O2 and molecular N2, which then combine to form NOx which quickly reacts with O3 to form NO2. Lightning is responsible for 10-15% of NOx emissions globally. This is 2 8 Tg N a-1 [Schumann and Huntrieser, 2007] or 100 to 400 mol per flash. Much of the uncertainty stems from limited knowledge of lightning NOx production per flash (LNOx PE) or per unit flash length. Most LNOx is injected into mid- and upper-troposphere where away from deep convection its lifetime is longer relative to lower troposphere NOx. NOx in this region enhances the concentrations of upper tropospheric NOy, OH, and O3 and contributes to positive radiative forcing by O3 and negative forcing by CH4. We have previously used OMI NO2 to obtain estimates of LNOx production per flash over the Gulf of Mexico (Pickering et al., 2016, JGR), in convective events during NASAs TC4 field program (Bucsela et al., 2010, JGR), and over broad regions of the tropics (Allen et al., 2019, JGR) and midlatitudes (Bucsela et al., 2019, JGR). In the latter studies, we obtained PE values of 170 100 mol flash and 180 100 mol flash, respectively

OMMYDCLD: a New A-train Cloud Product that Co-locates OMI and MODIS Cloud and Radiance Parameters onto the OMI Footprint

Clouds cover approximately 60% of the earth's surface. When obscuring the satellite's field of view (FOV), clouds complicate the retrieval of ozone, trace gases and aerosols from data collected by earth observing satellites. Cloud properties associated with optical thickness, cloud pressure, water phase, drop size distribution (DSD), cloud fraction, vertical and areal extent can also change significantly over short spatio-temporal scales. The radiative transfer models used to retrieve column estimates of atmospheric constituents typically do not account for all these properties and their variations. The OMI science team is preparing to release a new data product, OMMYDCLD, which combines the cloud information from sensors on board two earth observing satellites in the NASA A-Train: Aura/OMI and Aqua/MODIS. OMMYDCLD co-locates high resolution cloud and radiance information from MODIS onto the much larger OMI pixel and combines it with parameters derived from the two other OMI cloud products: OMCLDRR and OMCLDO2. The product includes histograms for MODIS scientific data sets (SDS) provided at 1 km resolution. The statistics of key data fields - such as effective particle radius, cloud optical thickness and cloud water path - are further separated into liquid and ice categories using the optical and IR phase information. OMMYDCLD offers users of OMI data cloud information that will be useful for carrying out OMI calibration work, multi-year studies of cloud vertical structure and in the identification and classification of multi-layer clouds

The Ozone Monitoring Instrument: Overview of 14 years in space

This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain

Nitrogen Oxide Emissions from U.S. Oil and Gas Production: Recent Trends and Source Attribution

U.S. oil and natural gas production volumes have grown by up to 100% in key production areas between January 2017 and August 2019. Here we show that recent trends are visible from space and can be attributed to drilling, production, and gas flaring activities. By using oil and gas activity data as predictors in a multivariate regression to satellite measurements of tropospheric NO2 columns, observed changes in NO2 over time could be attributed to NOx emissions associated with drilling, production and gas flaring for three select regions: the Permian, Bakken, and Eagle Ford basins. We find that drilling had been the dominant NOx source contributing around 80% before the downturn in drilling activity in 2015. Thereafter, NOx contributions from drilling activities and combined production and flaring activities are similar. Comparison of our topâ down source attribution with a bottomâ up fuelâ based oil and gas NOx emission inventory shows agreement within error margins.Plain Language SummaryU.S. oil and natural gas production volumes have grown by up to 100% in key production areas between January 2017 and August 2019. Here we show that recent trends are visible from space as increases in NO2, an air pollutant that is released from combustion engines associated with the oil and gas industry. For three select regions, the Permian (TX and NM), Bakken (ND), and Eagle Ford (TX) basins, we report that the trend in NO2 columns over time can be explained by a combination of drilling activity, production numbers, and flared gas volume, which allows us to quantify the contributions from these sources to the total NOx (= NO + NO2) emissions from these areas. We find that drilling had been the dominant NOx source contributing around 80% before the downturn in drilling activity in 2015. But now, NOx contributions from drilling activities and combined production and flaring activities are similar. Both Permian and Bakken oil and gas production volumes are at an allâ time high and if current growth rates continue in the Eagle Ford basin, maximum production volumes will be exceeded in about 1 year.Key PointsRecent increases in U.S. oil and gas production are seen from space as increased tropospheric NO2 columns and increased gas flaringChanges in NO2 over time can be attributed to oil and gas NOx emissions associated with drilling, production, and gas flaring activitiesTopâ down and bottomâ up source attributions agree that drilling and, to a lesser extent, production are the main sources of NOx emissionsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153757/1/grl60007_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153757/2/grl60007.pd

Validation of the TROPOMI/S5P aerosol layer height using EARLINET lidars

The purpose of this study is to investigate the ability of the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) to derive accurate geometrical features of lofted aerosol layers, selecting the Mediterranean Basin as the study area. Comparisons with ground-based correlative measurements constitute a key component in the validation of passive and active satellite aerosol products. For this purpose, we use ground-based observations from quality-controlled lidar stations reporting to the European Aerosol Research Lidar Network (EARLINET). An optimal methodology for validation purposes has been developed and applied using the EARLINET optical profiles and TROPOMI aerosol products, aiming at the in-depth evaluation of the TROPOMI aerosol layer height (ALH) product for the period 2018 to 2022 over the Mediterranean Basin. Seven EARLINET stations were chosen, taking into consideration their proximity to the sea, which provided 63 coincident aerosol cases for the satellite retrievals. In the following, we present the first validation results for the TROPOMI/S5P ALH using the optimized EARLINET lidar products employing the automated validation chain designed for this purpose. The quantitative validation at pixels over the selected EARLINET stations illustrates that the TROPOMI ALH product is consistent with the EARLINET lidar products, with a high correlation coefficient R=0.82 (R=0.51) and a mean bias of -0.51±0.77 km and -2.27±1.17 km over ocean and land, respectively. Overall, it appears that aerosol layer altitudes retrieved from TROPOMI are systematically lower than altitudes from the lidar retrievals. High-albedo scenes, as well as low-aerosol-load scenes, are the most challenging for the TROPOMI retrieval algorithm, and these results testify to the need to further investigate the underlying cause. This work provides a clear indication that the TROPOMI ALH product can under certain conditions achieve the required threshold accuracy and precision requirements of 1 km, especially when only ocean pixels are included in the comparison analysis. Furthermore, we describe and analyse three case studies in detail, one dust and two smoke episodes, in order to illustrate the strengths and limitations of the TROPOMI ALH product and demonstrate the presented validation methodology. The present analysis provides important additions to the existing validation studies that have been performed so far for the TROPOMI S5P ALH product, which were based only on satellite-to-satellite comparisons.</p

Air quality impacts of COVID-19 lockdown measures detected from space using high spatial resolution observations of multiple trace gases from Sentinel-5P/TROPOMI

The aim of this paper is to highlight how TROPOspheric Monitoring Instrument (TROPOMI) trace gas data can best be used and interpreted to understand event-based impacts on air quality from regional to city scales around the globe. For this study, we present the observed changes in the atmospheric column amounts of five trace gases (NO2, SO2, CO, HCHO, and CHOCHO) detected by the Sentinel-5P TROPOMI instrument and driven by reductions in anthropogenic emissions due to COVID-19 lockdown measures in 2020. We report clear COVID-19-related decreases in TROPOMI NO2 column amounts on all continents. For megacities, reductions in column amounts of tropospheric NO2 range between 14 % and 63 %. For China and India, supported by NO2 observations, where the primary source of anthropogenic SO2 is coal-fired power generation, we were able to detect sector-specific emission changes using the SO2 data. For HCHO and CHOCHO, we consistently observe anthropogenic changes in 2-week-averaged column amounts over China and India during the early phases of the lockdown periods. That these variations over such a short timescale are detectable from space is due to the high resolution and improved sensitivity of the TROPOMI instrument. For CO, we observe a small reduction over China, which is in concert with the other trace gas reductions observed during lockdown; however, large interannual differences prevent firm conclusions from being drawn. The joint analysis of COVID-19-lockdown-driven reductions in satellite-observed trace gas column amounts using the latest operational and scientific retrieval techniques for five species concomitantly is unprecedented. However, the meteorologically and seasonally driven variability of the five trace gases does not allow for drawing fully quantitative conclusions on the reduction in anthropogenic emissions based on TROPOMI observations alone. We anticipate that in future the combined use of inverse modeling techniques with the high spatial resolution data from S5P/TROPOMI for all observed trace gases presented here will yield a significantly improved sector-specific, space-based analysis of the impact of COVID-19 lockdown measures as compared to other existing satellite observations. Such analyses will further enhance the scientific impact and societal relevance of the TROPOMI mission