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Nickolay A Krotkov

Publications and source records attributed to Nickolay A Krotkov.

13 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Perturbations in Stratospheric Aerosol Evolution Due to the Water-Rich Plume of the 2022 Hunga-Tonga Eruption

The January 2022 Hunga Tonga-Hunga Ha'apai (HTHH) volcanic eruption injected a relatively small amount of SO2, but significantly more water into the stratosphere than previously seen in the modern satellite record. Here we show that the large amount of water resulted in large perturbations to stratospheric aerosol evolution. Our Community Earth System Model simulation reproduces the enhanced water vapor observed by the Microwave Limb Sounder at pressure levels between 10 and 50 hPa for three months. Compared with a simulation without a water injection, this additional source of water vapor increases OH, which halves the SO2 lifetime. Subsequent coagulation creates larger sulfate particles that double the stratospheric aerosol optical depth. A seasonal forecast of volcanic plume transport in the southern hemisphere indicates this eruption will greatly enhance the aerosol surface area and water vapor near the polar vortex until at least October 2022, suggesting that there will continue to be an impact of the HTHH eruption on the climate system.

Atmospheric science↗
NASA NTRS2022

Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations

The COVID-19 lockdown had a large impact on anthropogenic emissions of air pollutants and particularly on nitrogen dioxide (NO 2 ). While the overall NO 2 decline over some large cities is well-established, understanding the details remains a challenge since multiple source categories contribute. In this study, a new method of isolation of three components (background NO 2 , NO 2 from urban sources, and NO 2 from industrial point sources) is applied to estimate the impact of the COVID-19 lockdown on each of them. The approach is based on fitting satellite data by a statistical model with empirical plume dispersion functions driven by a meteorological reanalysis. Population density and surface elevation data as well as coordinates of industrial sources were used in the analysis. The tropospheric NO 2 vertical column density (VCD) values measured by the Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor over 261 urban areas for the period from 16 March to 15 June 2020 were compared with the average VCD values for the same period in 2018 and 2019. While the background NO 2 component remained almost unchanged, the urban NO 2 component declined by −18 % to −28 % over most regions. India, South America, and a part of Europe (particularly, Italy, France, and Spain) demonstrated a −40 % to −50 % urban emission decline. In contrast, the decline over urban areas in China, where the lockdown was over during the analysed period, was, on average, only -4.4± 8 %. Emissions from large industrial sources in the analysed urban areas varied greatly from region to region from -4.8 ± 6 % for China to -40 ± 10 % for India. Estimated changes in urban emissions are correlated with changes in Google mobility data (the correlation coefficient is 0.62) confirming that changes in traffic were one of the key elements in the decline in urban NO2 emissions. No correlation was found between changes in background NO2 and Google mobility data. On the global scale, the background and urban components were remarkably stable in 2018, 2019, and 2021, with averages of all analysed areas all being within ±2.5 % and suggesting that there were no substantial drifts or shifts in TROPOMI data. The 2020 data are clearly an outlier: in 2020, the mean background component for all analysed areas (without China) was -6.0 % ± 1.2 % and the mean urban component was -26.7 ± 2.6 % or 20σ below the baseline level from the other years.

COVID-19↗
NASA NTRS2022

EarthShine: Observing Our World as an Exoplanet from the Surface of the Moon

NASA’s return to the Moon coincides with explosive growth in exoplanet discovery. Missions are being formulated to search for habitable planets orbiting other stars, making this the ideal time to deploy an instrument suite to the lunar surface to help us recognize a habitable exoplanet when we see it. We present EarthShine, a technically mature, three-instrument suite to observe the whole Earth from the Moon as an exoplanet proxy. Earth Shine data will validate and improve models critical for designing missions to image and characterize exoplanets, thus informing observing strategies for flagship missions to directly image exoplanets. EarthShine will answer interconnected questions in Earth and lunar science, exoplanets, and astrobiology, related to the credo“ follow the water.” Earth Shine can take advantage of current NASA programs to conduct science from the Moon with low-cost, mature space hardware to reduce risk and assure success. Like the 1968 Apollo Earthrise image of our home planet, lonely in the black sky, the appeal of Earth Shine to a multidisciplinary array of researchers in Earth Science, Planetary Science, and astrophysics will maximize both its scientific impact and its impact on the general public.

EarthShine↗
NASA NTRS2022

Global Fine Scale Changes in Ambient NO2 During COVID-19 Lockdowns

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health(1–9) . A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-19(10–20). Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

Ground level NO2↗
NASA NTRS2020

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 data sets 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 actor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori pro-files) but mostly to OMI’s large footprint (>312 km2).

Nitrogen dioxide↗
NASA NTRS2019

Enhanced Capabilities of TROPOMI NO2: Estimating NOX from North American Cities and Power Plants

The TROPOspheric Monitoring Instrument (TROPOMI) is used to derive top-down NOXemissions for twolarge power plants and three megacities in North America. Wefirst re-process the vertical column NO2with an improved airmass factor to correct for a known systematic low bias in the operational retrieval near urban centers. For the two power plants,top-down NOXemissions agree to within 10% of the emissions reported by the power plants. We then derive top-down NOXemissions rates for New York City, Chicago, and Toronto, and compare them to projected bottom-up emissions inventories. Inthis analysis of 2018 NOXemissions, wefind a +22% overestimate for New York City, a−21% underestimate in Toronto, andgood agreement in Chicago in the projected bottom-up inventories when compared to the top-down emissions. Top-downNOXemissions also capture intraseasonal variability, such as the weekday versus weekend effect (emissions are +45% larger onweekdays versus weekends in Chicago). Finally, we demonstrate the enhanced capabilities of TROPOMI, which allow us toderive a NOXemissions rate for Chicago using a single overpass on July 7, 2018. The large signal-to-noise ratio of TROPOMI iswell-suited for estimating NOXemissions from relatively small sources and for sub-seasonal timeframes.

TROPOspheric Monitoring Instrument (TROPOMI)↗
NASA NTRS2019

A New Discrete Wavelength BUV Algorithm for Consistent Volcanic SO2 Retrievals from Multiple Satellite Missions

This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, and Lambertian effective reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) onboard NASA's Nimbus-7 satellite (N7/TOMS: 1978-1993) and from the current Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory (DSCOVR: 2015-) from the Earth-Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were assessed using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as the Ozone Monitoring Instrument (OMI) onboard NASA's Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) onboard NASA-NOAA Suomi National Polar Partnership (SNPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus-7/TOMS instrument, described in Sect. S1 of the Supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as the 1991 Pinatubo eruption. To estimate SO2 retrieval systematic uncertainties, we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.

Bradford L Fisher↗
NASA NTRS2019

Five Decades Observing Earth's Atmospheric Trace Gases Using Ultraviolet and Visible Backscatter Solar Radiation from Space

Over the last five decades, Earth’s atmosphere has been extensively monitored from space using different spectral ranges. Early efforts were directed at improving weather forecasts with the first meteorological satellites launched in the 1960s. Soon thereafter, the intersection between weather, climate and atmospheric chemistry led to the observation of atmospheric composition from space. During the 1970s the Nimbus satellite program started regular monitoring of ozone integrated columns and water vapor profiles using the Backscatter Ultraviolet Spectrometer, the Infrared Interferometer Spectrometer and the Satellite Infrared Spectrometer instruments. Five decades after these pioneer efforts, continuous progress in instrument design, and retrieval techniques allow researchers to monitor tropospheric concentrations of a wide range of species with implications for air quality, climate and weather. The time line of historic, present and future space-borne instruments measuring ultraviolet and visible backscattered solar radiation designed to quantify atmospheric trace gases is presented. We describe the instruments technological evolution and the basic concepts of retrieval theory. We include a review of algorithms developed for ozone, nitrogen dioxide, sulfur dioxide, formaldehyde, bromine monoxide, water vapor and glyoxal, a selection of studies using these algorithms, the challenges they face and how these challenges can be addressed. The paper ends by providing insights on the opportunities that new instruments will bring to the atmospheric chemistry, weather and air quality communities and how to address the pressing need for long-term, inter-calibrated data records necessary to monitor the response of the atmosphere to rapidly changing ecosystems.

Infrared Interferometer Spectrometer↗
NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-user Resources, Answers to Faqs, and Common Mistakes to Avoid

Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

remote sensing↗
NASA NTRSDate not supplied

Verification of TROPOMI NO2 Product Using OMI NO2 algorithm

We evaluated S5P TROPOspheric Monitoring Instrument (TROPOMI) operational nitrogen dioxide (NO2) product by comparing with the NO2 retrievals from Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite. We compared spatially matched NO2 vertical column density (VCD) data from OMI and TROPOMI to identify any discrepancies between the two operational products. We also applied OMI Air-Mass Factor (AMF) algorithm to TROPOMI Slant Column Density (SCD) data (v02.03.01) aiming to create long-term merged NO2 Earth Science Data Record (https://disc.gsfc.nasa.gov/datasets/TROPOMI_MINDS_NO2_1.1/summary ). The algorithm (version 4.0) uses new Geometry-dependent Lambertian Equivalent surface Reflectivity (GLER) product available for each TROPOMI pixel. GLER is pre-calculated using the vector linearized discrete ordinate radiative transfer (VLIDORT) model, which uses as input high-resolution bidirectional reflectance distribution function (BRDF) information from NASA's Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the wind-dependent Cox–Munk wave-facet slope distribution over water, the latter with a contribution from the water-leaving radiance based on MODIS gap-filled in-water chlorophyll-a data. The GLER data, combined with consistently retrieved cloud parameters, provide improved information for the calculation of the scattering weight profiles. Additional AMF improvements result from using high resolution (0.25o latitude x 0.25o longitude) a priori NO2 profile shapes and other auxiliary information from the Global Modeling Initiative (GMI) Replay simulation sampled using S5P orbital simulator. Our TROPOMI_MINDS_NO2 algorithm employs the stratosphere-troposphere separation scheme, de-striping, and surface snow/ice treatment consistently with the latest OMI NO2 re-processing (version 4). We evaluate the TROPOMI_MINDS_NO2 product by comparing with the S5P operational NO2 product as well as with independent NO2 observations from ground-based Pandora and aircraft observations. Our results indicate that the new TROPOMI_MINDS_NO2 retrievals are generally higher than the S5P operational NO2 product over polluted regions and show improved agreement with independent validation data.

TROPOMI↗
NASA NTRSDate not supplied

Comparing Satellite Measurements of Volcanic SO2 Mass from OMI, OMPS and TROPOMI

Sulfur dioxide (SO2) is a major air pollutant that contributes to acid rain and aerosol formation (e.g., sulfates), adversely affects the environment and human health, and explosive volcanic SO2 emissions can impact climate. The majority of SO2 emissions are related to anthropogenic processes (e.g., fossil fuel burning, metal ore smelting operations), although natural processes such as volcanic eruptions and degassing also play an important role as anthropogenic SO2 emissions continue to decline. Generally, the most interest in volcanoes occurs during major eruptions. We will focus on comparing volcanic SO2 outgassing that occurs on an almost daily basis from lesser known volcanoes using satellite data. At NASA’s Global Sulfur Dioxide Monitoring Home page (https://so2.gsfc.nasa.gov/), we have been posting daily SO2 maps from 40 volcanic and industrial regions around the world using measurements from three satellite instruments; the Ozone Monitoring Instrument (OMI) onboard NASA’s Earth Observing System Aura satellite, the Ozone Monitoring and Profiler Suite (OMPS) onboard the NASA-NOAA Suomi National Polar-orbiting Partnership (NPP) satellite, and the TROPOspheric Monitoring Instrument (TROPOMI) onboard the ESA/Copernicus Sentinel-5 Precursor satellite. These instruments in low Earth sun-synchronous polar orbits with 1:30-2:00 pm equator crossing local time provide daily SO2 maps at different spatial resolutions: 13 x 24 km2, 50 x 50 km2 and 5.5 x 3.5 km2 for OMI, OMPS and TROPOMI respectively. Data from OMI are available since October 2004 (partial coverage since 2008), from OMPS since 2012 and from TROPOMI since 2018. We will present comparative SO2 mass time-series (see Hunga-Tonga plot) and statistical analyses of recent eruptions that have data from all the instruments.

SO2↗
NASA NTRSDate not supplied

Has NO(2) in Metropolitan Areas Returned to Pre-COVID-19 Levels as Measured by OMI Satellite Data?

Nitrogen oxides (NOx = NO + NO2) are primarily emitted through the combustion of fossil fuels, such as automobiles and power plants. NOx can contribute to chemical reactions that produce ozone and fine particulate matter (PM2.5) pollution. Using tropospheric vertical column density (TVCD) NO2 data from satellite hyperspectral instruments, such as the Ozone Monitoring Instrument (OMI) on board NASA’s EOS Aura satellite, one can monitor changes in NO2 pollution during “black-swan” events, such as mobility restrictions during COVID-19 lockdowns. Our OMI team has created the Global Nitrogen Dioxide Monitoring Home Page (https://so2.gsfc.nasa.gov/no2/no2_index.html ) where we display NO2 TVCD time series, animated maps, and COVID-specific NO2 anomalies comparing to a pre-COVID five-year average for 317 cities and regions around the world. During the pandemic as a result of the widespread lockdowns, many areas saw low NO2 anomalies superimposed on the natural weather related NO2 changes, such as seasonal NO2 cycle. Has NO2 levels returned to pre-Covid-19 levels in large metropolitan areas? We analyze NO2 time series from March through September for the years 2020-2023 using as a reference the average NO2 from 2015-2019 for those months. We will present data from selected cities that represent all countries.

Keith D Evans↗