40 research outputs found

    Estimates of Power Plant NOx Emissions and Lifetimes from OMI NO2 Satellite Retrievals

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    Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons

    Airborne MAX-DOAS Measurements Over California: Testing the NASA OMI Tropospheric NO2 Product

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    Airborne Multi-AXis Differential Optical Absorption Spectroscopy (AMAX-DOAS) measurements of NO2 tropospheric vertical columns were performed over California for two months in summer 2010. The observations are compared to the NASA Ozone Monitoring Instrument (OMI) tropospheric vertical columns (data product v2.1) in two ways: (1) Median data were compared for the whole time period for selected boxes, and the agreement was found to be fair (R = 0.97, slope = 1.4 +/- 0.1, N= 10). (2) A comparison was performed on the mean of coincident AMAX-DOAS measurements within the area of the corresponding OMI pixels with the tropospheric NASA OMI NO2 assigned to that pixel. The effects of different data filters were assessed. Excellent agreement and a strong correlation (R = 0.85, slope = 1.05 +/- 0.09, N= 56) was found for (2) when the data were filtered to eliminate large pixels near the edge of the OMI orbit, the cloud radiance fraction was2 km, and a representative sample of the footprint was taken by the AMAX-DOAS instrument. The AMAX-DOAS and OMI data sets both show a reduction of NO2 tropospheric columns on weekends by 38 +/- 24% and 33 +/- 11%, respectively. The assumptions in the tropospheric satellite air mass factor simulations were tested using independent measurements of surface albedo, aerosol extinction, and NO2 profiles for Los Angeles for July 2010 indicating an uncertainty of 12%

    A Summary of OMI NO2 Data for Air Quality Applications

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    As a member of NASA's Air Quality Applied Sciences Team (AQAST), I will update air quality managers on the status of various NASA satellite datasets that are relevant for air quality applications. I will also present a new website that contains NASA Aura OMI nitrogen dioxide data and shows US city trends and comparisons to EPA surface monitor data. Since this is the final AQAST meeting, I will summarize my contributions to AQAST over the last five years

    Nitrogen Dioxide Trend over the United States: the View from the Ground, the View from Space

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    Emissions of nitrogen oxides (NOx) are decreasing over the US due to environmental policies and technological change. We use observations of tropospheric nitrogen dioxide (NO2) columns from the Ozone Monitoring Instrument (OMI) satellite instrument and surface NO2 in-situ measurements from the air quality system (AQS) to quantify the trends, and to establish the relationship between the trends in tropospheric column and surface concentration. Both observations show substantial downward trends from 2005 to 2013, with an average reduction of 35 percent according to OMI and 38 percent according to AQS. The annual reduction rates are largest in 2005-2009: -6.2 percent per year and -7 percent per year observed by OMI and AQS, respectively. We examine various factors affecting the estimated trend in OMI NO2 columns and in-situ NO2 observations. An improved understanding of trend offers valuable insights about effectiveness of emission reduction regulations on state and federal level

    The Observed Response of Ozone Monitoring Instrument (OMI) NO2 Columns to NOx Emission Controls on Power Plants in the United States: 2005-2011

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    We show that Aura Ozone Monitoring Instrument (OMI) nitrogen dioxide (NO2) tropospheric column data may be used to assess changes of the emissions of nitrogen oxides (NOx) from power plants in the United States, though careful interpretation of the data is necessary. There is a clear response for OMI NO2 data to NOx emission reductions from power plants associated with the implementation of mandated emission control devices (ECDs) over the OMI record (2005e2011). This response is scalar for all intents and purposes, whether the reduction is rapid or incremental over several years. However, it is variable among the power plants, even for those with the greatest absolute decrease in emissions. We document the primary causes of this variability, presenting case examples for specific power plants

    Interpreting summertime hourly variation of NO2 columns with implications for geostationary satellite applications

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    Accurate representation of the hourly variation in the NO2-column-to-surface relationship is essential for interpreting geostationary observations of NO2 columns. Previous research indicated inconsistencies in this hourly variation. This study employs the high-performance configuration of the GEOS-Chem model (GCHP) to analyze daytime hourly NO2 total columns and surface concentrations during summer. We use measurements from globally distributed Pandora sun photometers and aircraft observations over the United States. We correct Pandora total NO2 vertical columns for (1) hourly variations in effective temperature driven by vertically resolved contributions to the total column and (2) changes in local solar time along the Pandora line of sight. These corrections increase the total NO2 columns by 5–6 × 1014 molec. cm−2 at 09:00 and 18:00 across all sites. Fine-scale simulations from GHCP (∼12 km) reduce the normalized bias (NB) against Pandora total NO2 columns from 19 % to 10 % and against aircraft measurements from 25 % to 13 % in Maryland, Texas, and Colorado. Similar reductions are observed in NO2 columns over the eastern US (17 % to 9 %), the western US (22 % to 14 %), Europe (24 % to 15 %), and Asia (29 % to 21 %) when compared to 55 km simulations. Our analysis attributes the weaker hourly variability in the total NO2 column to (1) hourly variations in column effective temperature, (2) local solar time changes along the Pandora line of sight, and (3) differences in hourly NO2 variability from different atmospheric layers, with the lowest 500 m exhibiting greater variability, while the dominant residual column above 500 m exhibits weaker variability.</p

    The version 3 OMI NO2 standard product

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    We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2 /products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO2 slant column density (SCD) retrieval and (2) higher-resolution (1 degrees latitude and 1.25 degrees longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry-transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by similar to 10-40 %) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite- and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots

    Application of OMI Observations to a Space-Based Indicator of NOx and VOC Controls on Surface Ozone Formation

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    We investigated variations in the relative sensitivity of surface ozone formation in summer to precursor species concentrations of volatile organic compounds (VOCs) and nitrogen oxides (NOx) as inferred from the ratio of the tropospheric columns of formaldehyde to nitrogen dioxide (the "Ratio") from the Aura Ozone Monitoring Instrument (OMI). Our modeling study suggests that ozone formation decreases with reductions in VOCs at Ratios less than 1 and NOx at Ratios greater than 2; both NOx and VOC reductions may decrease ozone formation for Ratios between 1 and 2. Using this criteria. the OMI data indicate that ozone formation became: 1. more sensitive to NOx over most of the United States from 2005 to 2007 because of the substantial decrease in NOx emissions, primarily from stationary sources, and the concomitant decrease in the tropospheric column of NO2. and 2. more sensitive to NOx with increasing temperature, in part because emissions of highly reactive, biogenic isoprene increase with temperature, thus increasing the total VOC reactivity. In cities with relatively low isoprene emissions (e.g .. Chicago). the data clearly indicate that ozone formation became more sensitive to NOx from 2005 to 2007. In cities with relatively high isoprene emissions (e.g ., Atlanta), we found that the increase in the Ratio due to decreasing NOx emissions was not obvious as this signal was convolved with variations in the Ratio associated with the temperature dependence of isoprene emissions and, consequently, the formaldehyde concentration
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