European NOx emissions in WRF-Chem derived from OMI: Impacts on summertime surface ozone

Auke J. Visser*, K. Folkert Boersma, Laurens N. Ganzeveld, Maarten C. Krol

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

Ozone (O3) is a secondary air pollutant that negatively affects human and ecosystem health. Ozone simulations with regional air quality models suffer from unexplained biases over Europe, and uncertainties in the emissions of ozone precursor group nitrogen oxides (NOx= NO+NO) contribute to these biases. The goal of this study is to use NO2 column observations from the Ozone Monitoring Instrument (OMI) satellite sensor to infer top-down NOx emissions in the regional Weather Research and Forecasting model with coupled chemistry (WRF-Chem) and to evaluate the impact on simulated surface O3 with in situ observations. We first perform a simulation for July 2015 over Europe and evaluate its performance against in situ observations from the AirBase network. The spatial distribution of mean ozone concentrations is reproduced satisfactorily. However, the simulated maximum daily 8h ozone concentration (MDA8 O3) is underestimated (mean bias error of -14.2μgm-3), and its spread is too low. We subsequently derive satellite-constrained surface NOx emissions using a mass balance approach based on the relative difference between OMI and WRF-Chem NO2 columns. The method accounts for feedbacks through OH, NO2's dominant daytime oxidant. Our optimized European NOx emissions amount to 0.50TgN (for July 2015), which is 0.18TgN higher than the bottom-up emissions (which lacked agricultural soil NOx emissions). Much of the increases occur across Europe, in regions where agricultural soil NOx emissions dominate. Our best estimate of soil NOx emissions in July 2015 is 0.1TgN, much higher than the bottom-up 0.02TgN natural soil NOx emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). A simulation with satellite-updated NOx emissions reduces the systematic bias between WRF-Chem and OMI NO2 (slopeCombining double low line0.98, r2Combining double low line0.84) and reduces the low bias against independent surface NO2 measurements by 1.1μgm-3 (-56%). Following these NOx emission changes, daytime ozone is strongly affected, since NOx emission changes particularly affect daytime ozone formation. Monthly averaged simulated daytime ozone increases by 6.0μgm-3, and increases of >10μgm-3 are seen in regions with large emission increases. With respect to the initial simulation, MDA8 O3 has an improved spatial distribution, expressed by an increase in r2 from 0.40 to 0.53, and a decrease of the mean bias by 7.4μgm-3 (48%). Overall, our results highlight the dependence of surface ozone on its precursor NOx and demonstrate that simulations of surface ozone benefit from constraining surface NOx emissions by satellite NO2 column observations.

Original languageEnglish
Pages (from-to)11821-11841
Number of pages21
JournalAtmospheric Chemistry and Physics
Volume19
Issue number18
DOIs
Publication statusPublished - 24 Sep 2019

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ozone
monitoring
soil emission
agricultural emission
simulation
agricultural soil
spatial distribution
ecosystem health
satellite sensor
nitrogen oxides
oxidant
mass balance
air quality
aerosol
weather
gas

Cite this

@article{2e08affd151347f58457b655766be0a5,
title = "European NOx emissions in WRF-Chem derived from OMI: Impacts on summertime surface ozone",
abstract = "Ozone (O3) is a secondary air pollutant that negatively affects human and ecosystem health. Ozone simulations with regional air quality models suffer from unexplained biases over Europe, and uncertainties in the emissions of ozone precursor group nitrogen oxides (NOx= NO+NO) contribute to these biases. The goal of this study is to use NO2 column observations from the Ozone Monitoring Instrument (OMI) satellite sensor to infer top-down NOx emissions in the regional Weather Research and Forecasting model with coupled chemistry (WRF-Chem) and to evaluate the impact on simulated surface O3 with in situ observations. We first perform a simulation for July 2015 over Europe and evaluate its performance against in situ observations from the AirBase network. The spatial distribution of mean ozone concentrations is reproduced satisfactorily. However, the simulated maximum daily 8h ozone concentration (MDA8 O3) is underestimated (mean bias error of -14.2μgm-3), and its spread is too low. We subsequently derive satellite-constrained surface NOx emissions using a mass balance approach based on the relative difference between OMI and WRF-Chem NO2 columns. The method accounts for feedbacks through OH, NO2's dominant daytime oxidant. Our optimized European NOx emissions amount to 0.50TgN (for July 2015), which is 0.18TgN higher than the bottom-up emissions (which lacked agricultural soil NOx emissions). Much of the increases occur across Europe, in regions where agricultural soil NOx emissions dominate. Our best estimate of soil NOx emissions in July 2015 is 0.1TgN, much higher than the bottom-up 0.02TgN natural soil NOx emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). A simulation with satellite-updated NOx emissions reduces the systematic bias between WRF-Chem and OMI NO2 (slopeCombining double low line0.98, r2Combining double low line0.84) and reduces the low bias against independent surface NO2 measurements by 1.1μgm-3 (-56{\%}). Following these NOx emission changes, daytime ozone is strongly affected, since NOx emission changes particularly affect daytime ozone formation. Monthly averaged simulated daytime ozone increases by 6.0μgm-3, and increases of >10μgm-3 are seen in regions with large emission increases. With respect to the initial simulation, MDA8 O3 has an improved spatial distribution, expressed by an increase in r2 from 0.40 to 0.53, and a decrease of the mean bias by 7.4μgm-3 (48{\%}). Overall, our results highlight the dependence of surface ozone on its precursor NOx and demonstrate that simulations of surface ozone benefit from constraining surface NOx emissions by satellite NO2 column observations.",
author = "Visser, {Auke J.} and {Folkert Boersma}, K. and Ganzeveld, {Laurens N.} and Krol, {Maarten C.}",
year = "2019",
month = "9",
day = "24",
doi = "10.5194/acp-19-11821-2019",
language = "English",
volume = "19",
pages = "11821--11841",
journal = "Atmospheric Chemistry and Physics",
issn = "1680-7316",
publisher = "European Geosciences Union",
number = "18",

}

European NOx emissions in WRF-Chem derived from OMI: Impacts on summertime surface ozone. / Visser, Auke J.; Folkert Boersma, K.; Ganzeveld, Laurens N.; Krol, Maarten C.

In: Atmospheric Chemistry and Physics, Vol. 19, No. 18, 24.09.2019, p. 11821-11841.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - European NOx emissions in WRF-Chem derived from OMI: Impacts on summertime surface ozone

AU - Visser, Auke J.

AU - Folkert Boersma, K.

AU - Ganzeveld, Laurens N.

AU - Krol, Maarten C.

PY - 2019/9/24

Y1 - 2019/9/24

N2 - Ozone (O3) is a secondary air pollutant that negatively affects human and ecosystem health. Ozone simulations with regional air quality models suffer from unexplained biases over Europe, and uncertainties in the emissions of ozone precursor group nitrogen oxides (NOx= NO+NO) contribute to these biases. The goal of this study is to use NO2 column observations from the Ozone Monitoring Instrument (OMI) satellite sensor to infer top-down NOx emissions in the regional Weather Research and Forecasting model with coupled chemistry (WRF-Chem) and to evaluate the impact on simulated surface O3 with in situ observations. We first perform a simulation for July 2015 over Europe and evaluate its performance against in situ observations from the AirBase network. The spatial distribution of mean ozone concentrations is reproduced satisfactorily. However, the simulated maximum daily 8h ozone concentration (MDA8 O3) is underestimated (mean bias error of -14.2μgm-3), and its spread is too low. We subsequently derive satellite-constrained surface NOx emissions using a mass balance approach based on the relative difference between OMI and WRF-Chem NO2 columns. The method accounts for feedbacks through OH, NO2's dominant daytime oxidant. Our optimized European NOx emissions amount to 0.50TgN (for July 2015), which is 0.18TgN higher than the bottom-up emissions (which lacked agricultural soil NOx emissions). Much of the increases occur across Europe, in regions where agricultural soil NOx emissions dominate. Our best estimate of soil NOx emissions in July 2015 is 0.1TgN, much higher than the bottom-up 0.02TgN natural soil NOx emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). A simulation with satellite-updated NOx emissions reduces the systematic bias between WRF-Chem and OMI NO2 (slopeCombining double low line0.98, r2Combining double low line0.84) and reduces the low bias against independent surface NO2 measurements by 1.1μgm-3 (-56%). Following these NOx emission changes, daytime ozone is strongly affected, since NOx emission changes particularly affect daytime ozone formation. Monthly averaged simulated daytime ozone increases by 6.0μgm-3, and increases of >10μgm-3 are seen in regions with large emission increases. With respect to the initial simulation, MDA8 O3 has an improved spatial distribution, expressed by an increase in r2 from 0.40 to 0.53, and a decrease of the mean bias by 7.4μgm-3 (48%). Overall, our results highlight the dependence of surface ozone on its precursor NOx and demonstrate that simulations of surface ozone benefit from constraining surface NOx emissions by satellite NO2 column observations.

AB - Ozone (O3) is a secondary air pollutant that negatively affects human and ecosystem health. Ozone simulations with regional air quality models suffer from unexplained biases over Europe, and uncertainties in the emissions of ozone precursor group nitrogen oxides (NOx= NO+NO) contribute to these biases. The goal of this study is to use NO2 column observations from the Ozone Monitoring Instrument (OMI) satellite sensor to infer top-down NOx emissions in the regional Weather Research and Forecasting model with coupled chemistry (WRF-Chem) and to evaluate the impact on simulated surface O3 with in situ observations. We first perform a simulation for July 2015 over Europe and evaluate its performance against in situ observations from the AirBase network. The spatial distribution of mean ozone concentrations is reproduced satisfactorily. However, the simulated maximum daily 8h ozone concentration (MDA8 O3) is underestimated (mean bias error of -14.2μgm-3), and its spread is too low. We subsequently derive satellite-constrained surface NOx emissions using a mass balance approach based on the relative difference between OMI and WRF-Chem NO2 columns. The method accounts for feedbacks through OH, NO2's dominant daytime oxidant. Our optimized European NOx emissions amount to 0.50TgN (for July 2015), which is 0.18TgN higher than the bottom-up emissions (which lacked agricultural soil NOx emissions). Much of the increases occur across Europe, in regions where agricultural soil NOx emissions dominate. Our best estimate of soil NOx emissions in July 2015 is 0.1TgN, much higher than the bottom-up 0.02TgN natural soil NOx emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). A simulation with satellite-updated NOx emissions reduces the systematic bias between WRF-Chem and OMI NO2 (slopeCombining double low line0.98, r2Combining double low line0.84) and reduces the low bias against independent surface NO2 measurements by 1.1μgm-3 (-56%). Following these NOx emission changes, daytime ozone is strongly affected, since NOx emission changes particularly affect daytime ozone formation. Monthly averaged simulated daytime ozone increases by 6.0μgm-3, and increases of >10μgm-3 are seen in regions with large emission increases. With respect to the initial simulation, MDA8 O3 has an improved spatial distribution, expressed by an increase in r2 from 0.40 to 0.53, and a decrease of the mean bias by 7.4μgm-3 (48%). Overall, our results highlight the dependence of surface ozone on its precursor NOx and demonstrate that simulations of surface ozone benefit from constraining surface NOx emissions by satellite NO2 column observations.

U2 - 10.5194/acp-19-11821-2019

DO - 10.5194/acp-19-11821-2019

M3 - Article

VL - 19

SP - 11821

EP - 11841

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

SN - 1680-7316

IS - 18

ER -