N. A. Krotkov

Air quality over the Canadian oil sands : a first assessment using satellite observations

Results from the first assessment of air quality over the Canadian oil sands–one of the largest industrial undertakings in human history–using satellite remote sensing observations of two pollutants, nitrogen dioxide (NO2) and sulfur dioxide (SO2), are presented. High-resolution maps were created that revealed distinct enhancements in both species over an area (roughly 30 km × 50 km) of intensive surface mining at scales of a few kilometers. The magnitude of these enhancements, quantified in terms of total mass, are comparable to the largest seen in Canada from individual sources. The rate of increase in NO2between 2005 and 2010 was assessed at 10.4 ± 3.5%/year and resulted from increases both in local values as well as the spatial extent of the enhancement. This is broadly consistent with both surface-measurement trends and increases in annual bitumen production. An increase in SO2 was also found, but given larger uncertainties, it is not statistically significant.

Scaling Relationship for NO2 Pollution and Urban Population Size: A Satellite Perspective

Concern is growing about the effects of urbanization on air pollution and health. Nitrogen dioxide (NO2) released primarily from combustion processes, such as traffic, is a short-lived atmospheric pollutant that serves as an air-quality indicator and is itself a health concern. We derive a global distribution of ground-level NO2 concentrations from tropospheric NO2 columns retrieved from the Ozone Monitoring Instrument (OMI). Local scaling factors from a three-dimensional chemistry-transport model (GEOS-Chem) are used to relate the OMI NO2 columns to ground-level concentrations. The OMI-derived surface NO2 data are significantly correlated (r = 0.69) with in situ surface measurements. We examine how the OMI-derived ground-level NO2 concentrations, OMI NO2 columns, and bottom-up NOx emission inventories relate to urban population. Emission hot spots, such as power plants, are excluded to focus on urban relationships. The correlation of surface NO2 with population is significant for the three countries and one continent examined here: United States (r = 0.71), Europe (r = 0.67), China (r = 0.69), and India (r = 0.59). Urban NO2 pollution, like other urban properties, is a power law scaling function of the population size: NO2 concentration increases proportional to population raised to an exponent. The value of the exponent varies by region from 0.36 for India to 0.66 for China, reflecting regional differences in industrial development and per capita emissions. It has been generally established that energy efficiency increases and, therefore, per capita NOx emissions decrease with urban population; here, we show how outdoor ambient NO2 concentrations depend upon urban population in different global regions.

Lifetimes and emissions of SO2 from point sources estimated from OMI

A new method to estimate sulfur dioxide (SO2) lifetimes and emissions from point sources using satellite measurements is described. The method is based on fitting satellite SO2 vertical column density to a three-dimensional parameterization as a function of the coordinates and wind speed. An effective lifetime (or, more accurately, decay time) and emission rate are then determined from the parameters of the fit. The method was applied to measurements from the Ozone Monitoring Instrument (OMI) processed with the new principal component analysis (PCA) algorithm in the vicinity of approximately 50 large U.S. near-point sources. The obtained results were then compared with available emission inventories. The correlation between estimated and reported emissions was about 0.91 with the estimated lifetimes between 4 and 12 h. It is demonstrated that individual sources with annual SO2 emissions as low as 30 kt yr−1 can produce a statistically significant signal in OMI data.

Sulfur dioxide vertical column DOAS retrievals from the Ozone Monitoring Instrument: Global observations and comparison to ground-based and satellite data

We present a new data set of sulfur dioxide (SO2) vertical columns from observations of the Ozone Monitoring Instrument (OMI)/AURA instrument between 2004 and 2013. The retrieval algorithm used is an advanced Differential Optical Absorption Spectroscopy (DOAS) scheme combined with radiative transfer calculation. It is developed in preparation for the operational processing of SO2 data product for the upcoming TROPOspheric Monitoring Instrument/Sentinel 5 Precursor mission. We evaluate the SO2 column results with those inferred from other satellite retrievals such as Infrared Atmospheric Sounding Interferometer and OMI (Linear Fit and Principal Component Analysis algorithms). A general good agreement between the different data sets is found for both volcanic and anthropogenic SO2 emission scenarios. We show that our algorithm produces SO2 columns with low noise and is able to provide accurate estimates of SO2. This conclusion is supported by important validation results over the heavily polluted site of Xianghe (China). Nearly 4 years of OMI and ground-based multiaxis DOAS SO2 columns are compared, and an excellent match is found. We also highlight the improved performance of the algorithm in capturing weak SO2 sources by detecting shipping SO2 emissions in long-term averaged data, an unreported measurement from space.

Global dry deposition of nitrogen dioxide and sulfur dioxide inferred from space‐based measurements

A method is developed to estimate global NO2 and SO2 dry deposition fluxes at high spatial resolution (0.1°×0.1°) using satellite measurements from the Ozone Monitoring Instrument (OMI) on the Aura satellite, in combination with simulations from the Goddard Earth Observing System chemical transport model (GEOS-Chem). These global maps for 2005–2007 provide a data set for use in examining global and regional budgets of deposition. In order to properly assess SO2 on a global scale, a method is developed to account for the geospatial character of background offsets in retrieved satellite columns. Globally, annual dry deposition to land estimated from OMI as NO2 contributes 1.5 ± 0.5 Tg of nitrogen and as SO2 contributes 13.7 ± 4.0 Tg of sulfur. Differences between OMI-inferred NO2 dry deposition fluxes and those of other models and observations vary from excellent agreement to an order of magnitude difference, with OMI typically on the low end of estimates. SO2 dry deposition fluxes compare well with in situ Clear Air Status and Trends Network-inferred flux over North America (slope = 0.98, r = 0.71). The most significant NO2 dry deposition flux to land per area occurs in the Pearl River Delta, China, at 13.9 kg N ha−1 yr−1, while SO2 dry deposition has a global maximum rate of 72.0 kg S ha−1 yr−1 to the east of Jinan in Chinas Shandong province. Dry deposition fluxes are explored in several urban areas, where NO2 contributes on average 9–36% and as much as 85% of total NOy dry deposition.

Revising the slant column density retrieval of nitrogen dioxide observed by the Ozone Monitoring Instrument

Abstract Nitrogen dioxide retrievals from the Aura/Ozone Monitoring Instrument (OMI) have been used extensively over the past decade, particularly in the study of tropospheric air quality. Recent comparisons of OMI NO2 with independent data sets and models suggested that the OMI values of slant column density (SCD) and stratospheric vertical column density (VCD) in both the NASA OMNO2 and Royal Netherlands Meteorological Institute DOMINO products are too large, by around 10–40%. We describe a substantially revised spectral fitting algorithm, optimized for the OMI visible light spectrometer channel. The most important changes comprise a flexible adjustment of the instrumental wavelength shifts combined with iterative removal of the ring spectral features; the multistep removal of instrumental noise; iterative, sequential estimates of SCDs of the trace gases in the 402–465 nm range. These changes reduce OMI SCD(NO2) by 10–35%, bringing them much closer to SCDs retrieved from independent measurements and models. The revised SCDs, submitted to the stratosphere‐troposphere separation algorithm, give tropospheric VCDs ∼10–15% smaller in polluted regions, and up to ∼30% smaller in unpolluted areas. Although the revised algorithm has been optimized specifically for the OMI NO2 retrieval, our approach could be more broadly applicable.

Extending the long‐term record of volcanic SO2 emissions with the Ozone Mapping and Profiler Suite nadir mapper

Uninterrupted, global space-based monitoring of volcanic sulfur dioxide (SO2) emissions is critical for climate modeling and aviation hazard mitigation. We report the first volcanic SO2 measurements using ultraviolet (UV) Ozone Mapping and Profiler Suite (OMPS) nadir mapper data. OMPS was launched on the Suomi National Polar-orbiting Partnership satellite in October 2011. We demonstrate the sensitivity of OMPS SO2 measurements by quantifying SO2 emissions from the modest eruption of Paluweh volcano (Indonesia) in February 2013 and tracking the dispersion of the volcanic SO2 cloud. The OMPS SO2 retrievals are validated using Ozone Monitoring Instrument and Atmospheric Infrared Sounder measurements. The results confirm the ability of OMPS to extend the long-term record of volcanic SO2 emissions based on UV satellite observations. We also show that the Paluweh volcanic SO2 reached the lower stratosphere, further demonstrating the impact of small tropical volcanic eruptions on stratospheric aerosol optical depth and climate.

High-resolution NO2 observations from the Airborne Compact Atmospheric Mapper: Retrieval and validation

Nitrogen dioxide (NO2) is a short-lived atmospheric pollutant that serves as an air quality indicator, and is itself a health concern. The Airborne Compact Atmospheric Mapper (ACAM) was flown on board the NASA UC-12 aircraft during the DISCOVER-AQ Maryland field campaign in July 2011. The instrument collected hyperspectral remote sensing measurements in the 304-910 nm range, allowing day-time observations of several tropospheric pollutants, including nitrogen dioxide (NO2), at an unprecedented spatial resolution of 1.5 × 1.1 km2. Retrievals of slant column abundance are based on the Differential Optical Absorption Spectroscopy (DOAS) method. For the Air Mass Factor (AMF) computations needed to convert these retrievals to vertical column abundance, we include high resolution information for the surface reflectivity by using bidirectional reflectance distribution function (BRDF) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We use high-resolution simulated vertical distributions of NO2 from the Community Multiscale Air Quality (CMAQ) and Global Modeling Initiative (GMI) models to account for the temporal variation in atmospheric NO2 to retrieve middle- and lower-tropospheric NO2 columns (NO2 below the aircraft). We compare NO2 derived from ACAM measurements with in-situ observations from NASAs P-3B research aircraft, total column observations from the ground-based Pandora spectrometers, and tropospheric column observations from the space-based OMI instrument. The high-resolution ACAM measurements not only give new insights into our understanding of atmospheric composition and chemistry through observation of sub-sampling variability in typical satellite and model resolutions, but they also provide opportunities for testing algorithm improvements for forthcoming geostationary air quality missions.

The GeoTASO airborne spectrometer project

The NASA ESTO-funded Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) development project demonstrates a reconfigurable multi-order airborne spectrometer and tests the performance of spectra separation and filtering on the sensor spectral measurements and subsequent trace gas and aerosol retrievals. The activities support mission risk reduction for the UV-Visible air quality measurements from geostationary orbit for the TEMPO and GEMS missions1 . The project helps advance the retrieval algorithm readiness through retrieval performance tests using scene data taken with varying sensor parameters. We report initial results of the project.

Using CATS near‐real‐time lidar observations to monitor and constrain volcanic sulfur dioxide (SO2) forecasts

An eruption of Italian volcano Mount Etna on 3 December 2015 produced fast-moving sulfur dioxide (SO2) and sulfate aerosol clouds that traveled across Asia and the Pacific Ocean, reaching North America in just 5 days. The Ozone Profiler and Mapping Suites Nadir Mapping UV spectrometer aboard the U.S. National Polar-orbiting Partnership satellite observed the horizontal transport of the SO2 cloud. Vertical profiles of the colocated volcanic sulfate aerosols were observed between 11.5 and 13.5 km by the new Cloud Aerosol Transport System (CATS) space-based lidar aboard the International Space Station. Backward trajectory analysis estimates the SO2 cloud altitude at 7–12 km. Eulerian model simulations of the SO2 cloud constrained by CATS measurements produced more accurate dispersion patterns compared to those initialized with the back trajectory height estimate. The near-real-time data processing capabilities of CATS are unique, and this work demonstrates the use of these observations to monitor and model volcanic clouds.