scholarly journals Worldwide biogenic soil NO<sub>x</sub> emissions inferred from OMI NO<sub>2</sub> observations

2014 ◽  
Vol 14 (10) ◽  
pp. 14683-14724
Author(s):  
G. C. M. Vinken ◽  
K. F. Boersma ◽  
J. D. Maasakkers ◽  
M. Adon ◽  
R. V. Martin
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
A Priori ◽  
Nox Emission ◽  
Nox Emissions ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Tropospheric No2 ◽  
The Usa ◽  
Time Specific

Abstract. Biogenic NOx emissions from soils are a large natural source with substantial uncertainties in global bottom-up estimates (ranging from 4 to 27 Tg N yr−1). We reduce this range in emission estimates, and present a top-down soil NOx emission inventory for 2005 based on retrieved tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). We used a state-of-science soil NOx emission inventory (Hudman et al., 2012) as a priori in the GEOS-Chem chemistry transport model to identify 11 regions where tropospheric NO2 columns are dominated by soil NOx emissions. Strong correlations between soil NOx emissions and simulated NO2 columns indicated that spatial patterns in simulated NO2 columns in these regions indeed reflect the underlying soil NOx emissions. Subsequently, we used a mass-balance approach to constrain emissions for these 11 regions on all major continents using OMI observed and GEOS-Chem simulated tropospheric NO2 columns. We found that responses of simulated NO2 columns to changing NOx emissions were suppressed over low NOx regions, and accounted for these non-linearities in our inversion approach. In general, our approach suggests that emissions need to be increased in most regions. Our OMI top-down soil NOx inventory amounts to 10.0 Tg N for 2005 when only constraining the 11 regions, and 12.9 Tg N when extrapolating the constraints globally. Substantial regional differences exist (ranging from −40% to +90%), and globally our top-down inventory is 4–35% higher than the GEOS-Chem a priori (9.6 Tg N yr−1). We evaluated NO2 concentrations simulated with our new OMI top-down inventory against surface NO2 measurements from monitoring stations in Africa, the USA, and Europe. Although this comparison is complicated by several factors, we find an encouraging improved agreement when using the OMI top-down inventory compared to using the a priori inventory. To our knowledge, this study provides, for the first time, specific constraints on soil NOx emissions on all major continents using OMI NO2 columns. Our results rule out the high end of reported soil NOx emission estimates, and suggest that global emissions are most likely around 10–13 Tg N yr−1.

scholarly journals Worldwide biogenic soil NO<sub>x</sub> emissions inferred from OMI NO<sub>2</sub> observations

2014 ◽  
Vol 14 (18) ◽  
pp. 10363-10381 ◽  
Author(s):  
G. C. M. Vinken ◽  
K. F. Boersma ◽  
J. D. Maasakkers ◽  
M. Adon ◽  
R. V. Martin
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
A Priori ◽  
Nox Emission ◽  
Nox Emissions ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Tropospheric No2 ◽  
The Usa ◽  
Time Specific

Abstract. Biogenic NOx emissions from soils are a large natural source with substantial uncertainties in global bottom-up estimates (ranging from 4 to 15 Tg N yr−1). We reduce this range in emission estimates, and present a top-down soil NOx emission inventory for 2005 based on retrieved tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). We use a state-of-science soil NOx emission inventory (Hudman et al., 2012) as a priori in the GEOS-Chem chemistry transport model to identify 11 regions where tropospheric NO2 columns are dominated by soil NOx emissions. Strong correlations between soil NOx emissions and simulated NO2 columns indicate that spatial patterns in simulated NO2 columns in these regions indeed reflect the underlying soil NOx emissions. Subsequently, we use a mass-balance approach to constrain emissions for these 11 regions on all major continents using OMI observed and GEOS-Chem simulated tropospheric NO2 columns. We find that responses of simulated NO2 columns to changing NOx emissions are suppressed over low NOx regions, and account for these non-linearities in our inversion approach. In general, our approach suggests that emissions need to be increased in most regions. Our OMI top-down soil NOx inventory amounts to 10.0 Tg N for 2005 when only constraining the 11 regions, and 12.9 Tg N when extrapolating the constraints globally. Substantial regional differences exist (ranging from −40% to +90%), and globally our top-down inventory is 4–35% higher than the GEOS-Chem a priori (9.6 Tg N yr−1). We evaluate NO2 concentrations simulated with our new OMI top-down inventory against surface NO2 measurements from monitoring stations in Africa, the USA and Europe. Although this comparison is complicated by several factors, we find an encouraging improved agreement when using the OMI top-down inventory compared to using the a priori inventory. To our knowledge, this study provides, for the first time, specific constraints on soil NOx emissions on all major continents using OMI NO2 columns. Our results rule out the low end of reported soil NOx emission estimates, and suggest that global emissions are most likely around 12.9 ± 3.9 Tg N yr−1.

scholarly journals Top-Down NOX Emissions of European Cities Based on the Downwind Plume of Modelled and Space-Borne Tropospheric NO2 Columns

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2893 ◽  
Author(s):  
Willem W. Verstraeten ◽  
Klaas Folkert Boersma ◽  
John Douros ◽  
Jason E. Williams ◽  
Henk Eskes ◽  
...  
Keyword(s):  
Urban Areas ◽  
Transport Model ◽  
Nox Emissions ◽  
Inventory Data ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Chemistry Transport Model ◽  
European Cities ◽  
Tropospheric No2

Top-down estimates of surface NOX emissions were derived for 23 European cities based on the downwind plume decay of tropospheric nitrogen dioxide (NO2) columns from the LOTOS-EUROS (Long Term Ozone Simulation-European Ozone Simulation) chemistry transport model (CTM) and from Ozone Monitoring Instrument (OMI) satellite retrievals, averaged for the summertime period (April–September) during 2013. Here we show that the top-down NOX emissions derived from LOTOS-EUROS for European urban areas agree well with the bottom-up NOX emissions from the MACC-III inventory data (R2 = 0.88) driving the CTM demonstrating the potential of this method. OMI top-down NOX emissions over the 23 European cities are generally lower compared with the MACC-III emissions and their correlation is slightly lower (R2 = 0.79). The uncertainty on the derived NO2 lifetimes and NOX emissions are on average ~55% for OMI and ~63% for LOTOS-EUROS data. The downwind NO2 plume method applied on both LOTOS-EUROS and OMI tropospheric NO2 columns allows to estimate NOX emissions from urban areas, demonstrating that this is a useful method for real-time updates of urban NOX emissions with reasonable accuracy.

scholarly journals Growth in NOx emissions from power plants in China: bottom-up estimates and satellite observations

2012 ◽  
Vol 12 (10) ◽  
pp. 4429-4447 ◽  
Author(s):  
S. W. Wang ◽  
Q. Zhang ◽  
D. G. Streets ◽  
K. B. He ◽  
R. V. Martin ◽  
...  
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Emission Inventory ◽  
Transport Model ◽  
Nox Emission ◽  
Nox Emissions ◽  
Large Power ◽  
Power Plant Emissions ◽  
Tropospheric No2 ◽  
Plant Emissions

Abstract. Using OMI (Ozone Monitoring Instrument) tropospheric NO2 columns and a nested-grid 3-D global chemical transport model (GEOS-Chem), we investigated the growth in NOx emissions from coal-fired power plants and their contributions to the growth in NO2 columns in 2005–2007 in China. We first developed a unit-based power plant NOx emission inventory for 2005–2007 to support this investigation. The total capacities of coal-fired power generation have increased by 48.8% in 2005–2007, with 92.2% of the total capacity additions coming from generator units with size ≥300 MW. The annual NOx emissions from coal-fired power plants were estimated to be 8.11 Tg NO2 for 2005 and 9.58 Tg NO2 for 2007, respectively. The modeled summer average tropospheric NO2 columns were highly correlated (R2 = 0.79–0.82) with OMI measurements over grids dominated by power plant emissions, with only 7–14% low bias, lending support to the high accuracy of the unit-based power plant NOx emission inventory. The ratios of OMI-derived annual and summer average tropospheric NO2 columns between 2007 and 2005 indicated that most of the grids with significant NO2 increases were related to power plant construction activities. OMI had the capability to trace the changes of NOx emissions from individual large power plants in cases where there is less interference from other NOx sources. Scenario runs from GEOS-Chem model suggested that the new power plants contributed 18.5% and 10% to the annual average NO2 columns in 2007 in Inner Mongolia and North China, respectively. The massive new power plant NOx emissions significantly changed the local NO2 profiles, especially in less polluted areas. A sensitivity study found that changes of NO2 shape factors due to including new power plant emissions increased the summer average OMI tropospheric NO2 columns by 3.8–17.2% for six selected locations, indicating that the updated emission information could help to improve the satellite retrievals.

scholarly journals Evaluation of OMI operational standard NO<sub>2</sub> column retrievals using in situ and surface-based NO<sub>2</sub> observations

2014 ◽  
Vol 14 (10) ◽  
pp. 14519-14573 ◽  
Author(s):  
L. N. Lamsal ◽  
N. A. Krotkov ◽  
E. A. Celarier ◽  
W. H. Swartz ◽  
K. E. Pickering ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
In Situ Measurements ◽  
Nox Emission ◽  
Data Sets ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Bottom Up ◽  
Tropospheric No2

Abstract. We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.

scholarly journals Evaluation of OMI operational standard NO<sub>2</sub> column retrievals using in situ and surface-based NO<sub>2</sub> observations

2014 ◽  
Vol 14 (21) ◽  
pp. 11587-11609 ◽  
Author(s):  
L. N. Lamsal ◽  
N. A. Krotkov ◽  
E. A. Celarier ◽  
W. H. Swartz ◽  
K. E. Pickering ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
In Situ Measurements ◽  
Nox Emission ◽  
Data Sets ◽  
Ozone Monitoring Instrument ◽  
Validation Data ◽  
Bottom Up ◽  
Tropospheric No2

Abstract. We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in~situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.

scholarly journals Growth in NO<sub>x</sub> emissions from power plants in China: bottom-up estimates and satellite observations

2012 ◽  
Vol 12 (1) ◽  
pp. 45-91 ◽  
Author(s):  
S. W. Wang ◽  
Q. Zhang ◽  
D. G. Streets ◽  
K. B. He ◽  
R. V. Martin ◽  
...  
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Emission Inventory ◽  
Transport Model ◽  
Nox Emission ◽  
Nox Emissions ◽  
Large Power ◽  
Power Plant Emissions ◽  
Tropospheric No2 ◽  
Plant Emissions

Abstract. Using OMI (Ozone Monitoring Instrument) tropospheric NO2 columns and a nested-grid 3-D global chemical transport model (GEOS-Chem), we investigated the growth in NOx emissions from coal-fired power plants and their contributions to the growth in NO2 columns in 2005–2007 in China. We first developed a unit-based power plant NOx emission inventory for 2005–2007 to support this investigation. The total capacities of coal-fired power generation have increased by 48.8% in 2005–2007, with 92.2% of the total capacity additions coming from generator units with size ≥300 MW. The annual NOx emissions from coal-fired power plants were estimated to be 8.11 Tg NO2 for 2005 and 9.58 Tg NO2 for 2007, respectively. The modeled summer average tropospheric NO2 columns were highly correlated (R2 = 0.79–0.82) with OMI measurements over grids dominated by power plant emissions, with only 7–14% low bias, lending support to the high accuracy of the unit-based power plant NOx emission inventory. The ratios of OMI-derived annual and summer average tropospheric NO2 columns between 2007 and 2005 indicated that most of the grids with significant NO2 increases were related to power plant construction activities. OMI had the capability to trace the changes of NOx emissions from individual large power plants in cases where there is less interference from other NOx sources. Scenario runs from GEOS-Chem model suggested that the new power plants contributed 18.5% and 10% to the annual average NO2 columns in 2007 in Inner Mongolia and North China, respectively. The massive new power plant NOx emissions significantly changed the local NO2 profiles, especially in less polluted areas. A sensitivity study found that changes of NO2 shape factors due to including new power plant emissions increased the summer average OMI tropospheric NO2 columns by 3.8–17.2% for six selected locations, indicating that the updated emission information could help to improve the satellite retrievals.

scholarly journals New constraints on biogenic emissions using satellite-based estimates of carbon monoxide fluxes

2019 ◽  
Vol 19 (21) ◽  
pp. 13569-13579 ◽  
Author(s):  
Helen M. Worden ◽  
A. Anthony Bloom ◽  
John R. Worden ◽  
Zhe Jiang ◽  
Eloise A. Marais ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Transport Model ◽  
A Priori ◽  
Primary Source ◽  
Biogenic Emissions ◽  
Chemical Production ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Decadal Scale

Abstract. Biogenic non-methane volatile organic compounds (NMVOCs) emitted from vegetation are a primary source for the chemical production of carbon monoxide (CO) in the atmosphere, and these biogenic emissions account for about 18 % of the global CO burden. Partitioning CO fluxes to different source types in top-down inversion methods is challenging; typically a simple scaling of the posterior flux to prior flux values for fossil fuel, biogenic and biomass burning sources is used. Here we show top-down estimates of biogenic CO fluxes using a Bayesian inference approach, which explicitly accounts for both posterior and a priori CO flux uncertainties. This approach re-partitions CO fluxes following inversion of Measurements Of Pollution In The Troposphere (MOPITT) CO observations with the GEOS-Chem model, a global chemical transport model driven by assimilated meteorology from the NASA Goddard Earth Observing System (GEOS). We compare these results to the prior information for CO used to represent biogenic NMVOCs from GEOS-Chem, which uses the Model of Emissions of Gases and Aerosols from Nature (MEGAN) for biogenic emissions. We evaluate the a posteriori biogenic CO fluxes against top-down estimates of isoprene fluxes using Ozone Monitoring Instrument (OMI) formaldehyde observations. We find similar seasonality and spatial consistency in the posterior CO and top-down isoprene estimates globally. For the African savanna region, both top-down CO and isoprene seasonality vary significantly from the MEGAN a priori inventory. This method for estimating biogenic sources of CO will provide an independent constraint on modeled biogenic emissions and has the potential for diagnosing decadal-scale changes in emissions due to land-use change and climate variability.

scholarly journals Global NO<sub>x</sub> emission estimates derived from an assimilation of OMI tropospheric NO<sub>2</sub> columns

2011 ◽  
Vol 11 (12) ◽  
pp. 31523-31583 ◽  
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
A Priori ◽  
Eastern China ◽  
Nox Emissions ◽  
Chemical Transport Model ◽  
Background Error ◽  
Tropospheric No2 ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. A data assimilation system has been developed to estimate global nitrogen oxides (NOx) emissions using OMI tropospheric NO2 columns (DOMINO product) and a global chemical transport model (CTM), CHASER. The data assimilation system, based on an ensemble Kalman filter approach, was applied to optimize daily NOx emissions with a horizontal resolution of 2.8° during the years 2005 and 2006. The background error covariance estimated from the ensemble CTM forecasts explicitly represents non-direct relationships between the emissions and tropospheric columns caused by atmospheric transport and chemical processes. In comparison to the a priori emissions based on bottom-up inventories, the optimized emissions were higher over Eastern China, the Eastern United States, Southern Africa, and Central-Western Europe, suggesting that the anthropogenic emissions are mostly underestimated in the inventories. In addition, the seasonality of the estimated emissions differed from that of the a priori emission over several biomass burning regions, with a large increase over Southeast Asia in April and over South America in October. The data assimilation results were validated against independent data: SCIAMACHY tropospheric NO2 columns and vertical NO2 profiles obtained from aircraft and lidar measurements. The emission correction greatly improved the agreement between the simulated and observed NO2 fields; this implies that the data assimilation system efficiently derives NOx emissions from concentration observations. We also demonstrated that biases in the satellite retrieval and model settings used in the data assimilation largely affect the magnitude of estimated emissions. These dependences should be carefully considered for better understanding NOx sources from top-down approaches.

scholarly journals Effect of changing NO<sub><i>x</i></sub> lifetime on the seasonality and long-term trends of satellite-observed tropospheric NO<sub>2</sub> columns over China

2020 ◽  
Vol 20 (3) ◽  
pp. 1483-1495 ◽  
Author(s):  
Viral Shah ◽  
Daniel J. Jacob ◽  
Ke Li ◽  
Rachel F. Silvern ◽  
Shixian Zhai ◽  
...  
Keyword(s):  
Transport Model ◽  
Eastern China ◽  
Organic Nitrates ◽  
Nox Emissions ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Volatile Organic ◽  
Tropospheric No2 ◽  
Long Term Trends

Abstract. Satellite observations of tropospheric NO2 columns are extensively used to infer trends in anthropogenic emissions of nitrogen oxides (NOx≡NO+NO2), but this may be complicated by trends in NOx lifetime. Here we use 2004–2018 observations from the Ozone Monitoring Instrument (OMI) satellite-based instrument (QA4ECV and POMINO v2 retrievals) to examine the seasonality and trends of tropospheric NO2 columns over central–eastern China, and we interpret the results with the GEOS-Chem chemical transport model. The observations show a factor of 3 increase in NO2 columns from summer to winter, which we explain in GEOS-Chem as reflecting a longer NOx lifetime in winter than in summer (21 h versus 5.9 h in 2017). The 2005–2018 summer trends of OMI NO2 closely follow the trends in the Multi-resolution Emission Inventory for China (MEIC), with a rise over the 2005–2011 period and a 25 % decrease since. We find in GEOS-Chem no significant trend of the NOx lifetime in summer, supporting the emission trend reported by the MEIC. The winter trend of OMI NO2 is steeper than in summer over the entire period, which we attribute to a decrease in NOx lifetime at lower NOx emissions. Half of the NOx sink in winter is from N2O5 hydrolysis, which counterintuitively becomes more efficient as NOx emissions decrease due to less titration of ozone at night. The formation of organic nitrates also becomes an increasing sink of NOx as NOx emissions decrease but emissions of volatile organic compounds (VOCs) do not.

scholarly journals New Constraints on Biogenic Emissions using Satellite-Based Estimates of Carbon Monoxide Fluxes

2019 ◽  
Author(s):  
Helen M. Worden ◽  
A. Anthony Bloom ◽  
John R. Worden ◽  
Zhe Jiang ◽  
Eloise Marais ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Transport Model ◽  
A Priori ◽  
Primary Source ◽  
Biogenic Emissions ◽  
Chemical Production ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Decadal Scale

Abstract. Biogenic non-methane volatile organic compounds (NMVOCs) emitted from vegetation are a primary source for the chemical production of carbon monoxide (CO) in the atmosphere and these biogenic emissions account for about 18 % of the global CO burden. Partitioning CO fluxes to different source types in top-down inversion methods is challenging and typically a simple scaling of the posterior flux to prior flux values for fossil fuel, biogenic and biomass burning sources is used. Here we show top-down estimates of biogenic CO fluxes using a Bayesian inference approach, which explicitly accounts for both posterior and a priori CO flux uncertainties. This approach re-partitions CO fluxes following inversion of Measurements Of Pollution In The Troposphere (MOPITT) CO observations with the GEOS-Chem model, a global chemical transport model driven by assimilated meteorology from the NASA Goddard Earth Observing System (GEOS). We compare these results to the prior information for CO used to represent biogenic NMVOCs from GEOS-Chem, which uses the Model of Emissions of Gases and Aerosols from Nature (MEGAN) for biogenic emissions. We evaluate the a posteriori biogenic CO fluxes against top-down estimates of isoprene fluxes using Ozone Monitoring Instrument (OMI) formaldehyde observations. We find similar seasonality and spatial consistency in the posterior CO and top-down isoprene estimates globally. For the African savanna region, both top-down CO and isoprene seasonality vary significantly from the MEGAN apriori inventory. This method for estimating biogenic sources of CO will provide an independent constraint on modelled biogenic emissions and has the potential for diagnosing decadal-scale changes in emissions due to land-use change and climate variability.

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