scholarly journals Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs

2017 ◽  
Vol 17 (11) ◽  
pp. 7067-7081 ◽  
Author(s):  
Xueling Liu ◽  
Arthur P. Mizzi ◽  
Jeffrey L. Anderson ◽  
Inez Y. Fung ◽  
Ronald C. Cohen
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Weather Forecast ◽  
Forecast Errors ◽  
Nox Emissions ◽  
Chemical Transport Model ◽  
Model Framework ◽  
Simulation Experiments ◽  
High Space

Abstract. Observations of trace gases from space-based instruments offer the opportunity to constrain chemical and weather forecast and reanalysis models using the tools of data assimilation. In this study, observing system simulation experiments (OSSEs) are performed to investigate the potential of high space- and time-resolution column measurements as constraints on urban NOx emissions. The regional chemistry–meteorology assimilation system where meteorology and chemical variables are simultaneously assimilated is comprised of a chemical transport model, WRF-Chem, the Data Assimilation Research Testbed, and a geostationary observation simulator. We design OSSEs to investigate the sensitivity of emission inversions to the accuracy and uncertainty of the wind analyses and the emission updating scheme. We describe the overall model framework and some initial experiments that point out the first steps toward an optimal configuration for improving our understanding of NOx emissions by combining space-based measurements and data assimilation. Among the findings we describe is the dependence of errors in the estimated NOx emissions on the wind forecast errors, showing that wind vectors with a RMSE below 1 m s−1 allow inference of NOx emissions with a RMSE of less than 30 mol/(km2  ×  h) at the 3 km scale of the model we use. We demonstrate that our inference of emissions is more accurate when we simultaneously update both NOx emissions and NOx concentrations instead of solely updating emissions. Furthermore, based on our analyses, we recommend carrying out meteorology assimilations to stabilize NO2 transport from the initial wind errors before starting the emission assimilation. We show that wind uncertainties (calculated as a spread around a mean wind) are not important for estimating NOx emissions when the wind uncertainties are reduced below 1.5 m s−1. Finally, we present results assessing the role of separate vs. simultaneous chemical and meteorological assimilation in a model framework without covariance between the meteorology and chemistry.

scholarly journals Sulfate-nitrate-ammonium aerosols over China: response to 2000–2015 emission changes of sulfur dioxide, nitrogen oxides, and ammonia

2013 ◽  
Vol 13 (5) ◽  
pp. 2635-2652 ◽  
Author(s):  
Y. Wang ◽  
Q. Q. Zhang ◽  
K. He ◽  
Q. Zhang ◽  
L. Chai
Keyword(s):  
Emission Reduction ◽  
Transport Model ◽  
Critical Role ◽  
Sufficient Information ◽  
Nox Emissions ◽  
Chemical Transport Model ◽  
Dominant Component ◽  
Emission Changes ◽  
Emission Reduction Target

Abstract. We use a chemical transport model to examine the change of sulfate-nitrate-ammonium (SNA) aerosols over China due to anthropogenic emission changes of their precursors (SO2, NOx and NH3) from 2000 to 2015. From 2000 to 2006, annual mean SNA concentrations increased by about 60% over China as a result of the 60% and 80% increases in SO2 and NOx emissions. During this period, sulfate is the dominant component of SNA over South China (SC) and Sichuan Basin (SCB), while nitrate and sulfate contribute equally over North China (NC). Based on emission reduction targets in the 12th (2011–2015) Five-Year Plan (FYP), China's total SO2 and NOx emissions are projected to change by −16% and +16% from 2006 to 2015, respectively. The amount of NH3 emissions in 2015 is uncertain, given the lack of sufficient information on the past and present levels of NH3 emissions in China. With no change in NH3 emissions, SNA mass concentrations in 2015 will decrease over SCB and SC compared to their 2006 levels, but increase over NC where the magnitude of nitrate increase exceeds that of sulfate reduction. This suggests that the SO2 emission reduction target set by the 12th FYP, although effective in reducing SNA over SC and SCB, will not be successful over NC, for which NOx emission control needs to be strengthened. If NH3 emissions are allowed to keep their recent growth rate and increase by +16% from 2006 to 2015, the benefit of SO2 reduction will be completely offset over all of China due to the significant increase of nitrate, demonstrating the critical role of NH3 in regulating nitrate. The effective strategy to control SNA and hence PM2.5 pollution over China should thus be based on improving understanding of current NH3 emissions and putting more emphasis on controlling NH3 emissions in the future.

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 Sulfate-nitrate-ammonium aerosols over China: response to 2000–2015 emission changes of sulfur dioxide, nitrogen oxides, and ammonia

2012 ◽  
Vol 12 (9) ◽  
pp. 24243-24285 ◽  
Author(s):  
Y. Wang ◽  
Q. Q. Zhang ◽  
K. He ◽  
Q. Zhang ◽  
L. Chai
Keyword(s):  
Emission Reduction ◽  
Transport Model ◽  
Critical Role ◽  
Nox Emissions ◽  
Chemical Transport Model ◽  
So2 Emission ◽  
Dominant Component ◽  
Emission Changes ◽  
Emission Reduction Target

Abstract. We use a chemical transport model to examine the change of sulfate-nitrate-ammonium (SNA) aerosols over China due to anthropogenic emission changes of their precursors (SO2, NOx and NH3) from 2000 to 2015. From 2000 to 2006, annual mean SNA concentrations increased by about 60% over China as a result of the 60%~80% increases in SO2 and NOx emissions. During this period, sulfate is the dominant component of SNA over South China (SC) and Sichuan Basin (SCB), while nitrate makes equal contribution as sulfate over North China (NC). Based on emission reduction targets in the 12th (2011–2015) Five Year Plan (FYP), China's total SO2 and NOx emissions are projected to change by −16% and +16% from 2006 to 2015, respectively. However, the amount of NH3 emissions in 2015 is uncertain, given our finding that bottom-up inventories tend to overestimate China's ammonia emissions during the 2000–2006 period. With no change in NH3 emissions, SNA mass concentrations in 2015 will decrease over SCB and SC compared to their levels in 2006, but increase over NC where the magnitude of nitrate increase exceeds that of sulfate reduction. This suggests that the SO2 emission reduction target set by the 12th FYP, although effective in reducing SNA over SC and SCB, will not be successful over NC for which NOx emission control needs to be strengthened. If NH3 emissions are allowed to keep their recent growth rate and increase by +16% from 2006 to 2015, the benefit of SO2 reduction will be completely offset over all of China due to the significant increase of nitrate, demonstrating the critical role of NH3 in regulating nitrate. The effective strategy to control SNA and hence PM2.5 pollution over China should thus be based on improving understanding of current NH3 emissions and putting more emphasis on controlling NH3 emissions in the future.

scholarly journals Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Transport Model ◽  
Cost Model ◽  
Low Cost ◽  
Model Performance ◽  
Monitoring Network ◽  
Correlation Factor ◽  
Chemical Transport Model ◽  
High Quality

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

scholarly journals Changes in Power Plant NOx Emissions over Northwest Greece Using a Data Assimilation Technique

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 900
Author(s):  
Ioanna Skoulidou ◽  
Maria-Elissavet Koukouli ◽  
Arjo Segers ◽  
Astrid Manders ◽  
Dimitris Balis ◽  
...  
Keyword(s):  
Power Plant ◽  
Data Assimilation ◽  
Energy Production ◽  
Power Plants ◽  
Transport Model ◽  
A Priori ◽  
Filter Method ◽  
Nox Emissions ◽  
A Posteriori ◽  
Data Assimilation Technique

In this work, we investigate the ability of a data assimilation technique and space-borne observations to quantify and monitor changes in nitrogen oxides (NOx) emissions over Northwestern Greece for the summers of 2018 and 2019. In this region, four lignite-burning power plants are located. The data assimilation technique, based on the Ensemble Kalman Filter method, is employed to combine space-borne atmospheric observations from the high spatial resolution Sentinel-5 Precursor (S5P) Tropospheric Monitoring Instrument (TROPOMI) and simulations using the LOTOS-EUROS Chemical Transport model. The Copernicus Atmosphere Monitoring Service-Regional European emissions (CAMS-REG, version 4.2) inventory based on the year 2015 is used as the a priori emissions in the simulations. Surface measurements of nitrogen dioxide (NO2) from air quality stations operating in the region are compared with the model surface NO2 output using either the a priori (base run) or the a posteriori (assimilated run) NOx emissions. Relative to the a priori emissions, the assimilation suggests a strong decrease in concentrations for the station located near the largest power plant, by 80% in 2019 and by 67% in 2018. Concerning the estimated annual a posteriori NOx emissions, it was found that, for the pixels hosting the two largest power plants, the assimilated run results in emissions decreased by ~40–50% for 2018 compared to 2015, whereas a larger decrease, of ~70% for both power plants, was found for 2019, after assimilating the space-born observations. For the same power plants, the European Pollutant Release and Transfer Register (E-PRTR) reports decreased emissions in 2018 and 2019 compared to 2015 (−35% and −38% in 2018, −62% and −72% in 2019), in good agreement with the estimated emissions. We further compare the a posteriori emissions to the reported energy production of the power plants during the summer of 2018 and 2019. Mean decreases of about −35% and−63% in NOx emissions are estimated for the two larger power plants in summer of 2018 and 2019, respectively, which are supported by similar decreases in the reported energy production of the power plants (~−30% and −70%, respectively).

scholarly journals A new diagnostic for tropospheric ozone production

2017 ◽  
Author(s):  
Peter M. Edwards ◽  
Mathew J. Evans
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Transport Model ◽  
Chemical Transport ◽  
Ozone Production ◽  
Chemical Transport Model ◽  
Organic Species ◽  
Earth’S Climate ◽  
Oxidation Of Organics

Abstract. Tropospheric ozone is important for the Earth’s climate and air quality. It is produced during the oxidation of organics in the presence of nitrogen oxides. Due to the range of organic species emitted and the chain like nature of their oxidation, this chemistry is complex and understanding the role of different processes (emission, deposition, chemistry) is difficult. We demonstrate a new methodology for diagnosing ozone production based on the processing of bonds contained within emitted molecules, the fate of which is determined by the conservation of spin of the bonding electrons. Using this methodology to diagnose ozone production in the GEOS-Chem chemical transport model, we demonstrate its advantages over the standard diagnostic. We show that the number of bonds emitted, their chemistry and lifetime, and feedbacks on OH are all important in determining the ozone production within the model and its sensitivity to changes. This insight may allow future model-model comparisons to better identify the root causes of model differences.

scholarly journals A linear CO chemistry parameterization in a chemistry-transport model: evaluation and application to data assimilation

2010 ◽  
Vol 10 (13) ◽  
pp. 6097-6115 ◽  
Author(s):  
M. Claeyman ◽  
J.-L. Attié ◽  
L. El Amraoui ◽  
D. Cariolle ◽  
V.-H. Peuch ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Large Scale ◽  
Lower Stratosphere ◽  
Transport Model ◽  
Order Approximation ◽  
Chemical Transport Model ◽  
Long Run ◽  
Linear Scheme ◽  
Mean Differences ◽  
First Order Approximation

Abstract. This paper presents an evaluation of a new linear parameterization valid for the troposphere and the stratosphere, based on a first order approximation of the carbon monoxide (CO) continuity equation. This linear scheme (hereinafter noted LINCO) has been implemented in the 3-D Chemical Transport Model (CTM) MOCAGE (MOdèle de Chimie Atmospherique Grande Echelle). First, a one and a half years of LINCO simulation has been compared to output obtained from a detailed chemical scheme output. The mean differences between both schemes are about ±25 ppbv (part per billion by volume) or 15% in the troposphere and ±10 ppbv or 100% in the stratosphere. Second, LINCO has been compared to diverse observations from satellite instruments covering the troposphere (Measurements Of Pollution In The Troposphere: MOPITT) and the stratosphere (Microwave Limb Sounder: MLS) and also from aircraft (Measurements of ozone and water vapour by Airbus in-service aircraft: MOZAIC programme) mostly flying in the upper troposphere and lower stratosphere (UTLS). In the troposphere, the LINCO seasonal variations as well as the vertical and horizontal distributions are quite close to MOPITT CO observations. However, a bias of ~−40 ppbv is observed at 700 Pa between LINCO and MOPITT. In the stratosphere, MLS and LINCO present similar large-scale patterns, except over the poles where the CO concentration is underestimated by the model. In the UTLS, LINCO presents small biases less than 2% compared to independent MOZAIC profiles. Third, we assimilated MOPITT CO using a variational 3D-FGAT (First Guess at Appropriate Time) method in conjunction with MOCAGE for a long run of one and a half years. The data assimilation greatly improves the vertical CO distribution in the troposphere from 700 to 350 hPa compared to independent MOZAIC profiles. At 146 hPa, the assimilated CO distribution is also improved compared to MLS observations by reducing the bias up to a factor of 2 in the tropics. This study confirms that the linear scheme is able to simulate reasonably well the CO distribution in the troposphere and in the lower stratosphere. Therefore, the low computing cost of the linear scheme opens new perspectives to make free runs and CO data assimilation runs at high resolution and over periods of several years.

scholarly journals EnKF and 4D-Var data assimilation with chemical transport model BASCOE (version 05.06)

2016 ◽  
Vol 9 (8) ◽  
pp. 2893-2908 ◽  
Author(s):  
Sergey Skachko ◽  
Richard Ménard ◽  
Quentin Errera ◽  
Yves Christophe ◽  
Simon Chabrillat
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Chemical Transport ◽  
Error Variance ◽  
Model Error ◽  
Chemical Processes ◽  
Observation Error ◽  
Chemical Transport Model ◽  
Error Covariance ◽  
Chemical Tracer

Abstract. We compare two optimized chemical data assimilation systems, one based on the ensemble Kalman filter (EnKF) and the other based on four-dimensional variational (4D-Var) data assimilation, using a comprehensive stratospheric chemistry transport model (CTM). This work is an extension of the Belgian Assimilation System for Chemical ObsErvations (BASCOE), initially designed to work with a 4D-Var data assimilation. A strict comparison of both methods in the case of chemical tracer transport was done in a previous study and indicated that both methods provide essentially similar results. In the present work, we assimilate observations of ozone, HCl, HNO3, H2O and N2O from EOS Aura-MLS data into the BASCOE CTM with a full description of stratospheric chemistry. Two new issues related to the use of the full chemistry model with EnKF are taken into account. One issue is a large number of error variance parameters that need to be optimized. We estimate an observation error variance parameter as a function of pressure level for each observed species using the Desroziers method. For comparison purposes, we apply the same estimate procedure in the 4D-Var data assimilation, where both scale factors of the background and observation error covariance matrices are estimated using the Desroziers method. However, in EnKF the background error covariance is modelled using the full chemistry model and a model error term which is tuned using an adjustable parameter. We found that it is adequate to have the same value of this parameter based on the chemical tracer formulation that is applied for all observed species. This is an indication that the main source of model error in chemical transport model is due to the transport. The second issue in EnKF with comprehensive atmospheric chemistry models is the noise in the cross-covariance between species that occurs when species are weakly chemically related at the same location. These errors need to be filtered out in addition to a localization based on distance. The performance of two data assimilation methods was assessed through an 8-month long assimilation of limb sounding observations from EOS Aura MLS. This paper discusses the differences in results and their relation to stratospheric chemical processes. Generally speaking, EnKF and 4D-Var provide results of comparable quality but differ substantially in the presence of model error or observation biases. If the erroneous chemical modelling is associated with moderately fast chemical processes, but whose lifetimes are longer than the model time step, then EnKF performs better, while 4D-Var develops spurious increments in the chemically related species. If, however, the observation biases are significant, then 4D-Var is more robust and is able to reject erroneous observations while EnKF does not.

scholarly journals Organic nitrate chemistry and its implications for nitrogen budgets in an isoprene- and monoterpene-rich atmosphere: constraints from aircraft (SEAC<sup>4</sup>RS) and ground-based (SOAS) observations in the Southeast US

2016 ◽  
Vol 16 (9) ◽  
pp. 5969-5991 ◽  
Author(s):  
Jenny A. Fisher ◽  
Daniel J. Jacob ◽  
Katherine R. Travis ◽  
Patrick S. Kim ◽  
Eloise A. Marais ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Gas Phase ◽  
Transport Model ◽  
Oxidation Mechanism ◽  
Organic Nitrate ◽  
Organic Nitrates ◽  
Nox Emissions ◽  
Particle Phase ◽  
Chemical Transport Model ◽  
Southeast Us

Abstract. Formation of organic nitrates (RONO2) during oxidation of biogenic volatile organic compounds (BVOCs: isoprene, monoterpenes) is a significant loss pathway for atmospheric nitrogen oxide radicals (NOx), but the chemistry of RONO2 formation and degradation remains uncertain. Here we implement a new BVOC oxidation mechanism (including updated isoprene chemistry, new monoterpene chemistry, and particle uptake of RONO2) in the GEOS-Chem global chemical transport model with  ∼  25  ×  25 km2 resolution over North America. We evaluate the model using aircraft (SEAC4RS) and ground-based (SOAS) observations of NOx, BVOCs, and RONO2 from the Southeast US in summer 2013. The updated simulation successfully reproduces the concentrations of individual gas- and particle-phase RONO2 species measured during the campaigns. Gas-phase isoprene nitrates account for 25–50 % of observed RONO2 in surface air, and we find that another 10 % is contributed by gas-phase monoterpene nitrates. Observations in the free troposphere show an important contribution from long-lived nitrates derived from anthropogenic VOCs. During both campaigns, at least 10 % of observed boundary layer RONO2 were in the particle phase. We find that aerosol uptake followed by hydrolysis to HNO3 accounts for 60 % of simulated gas-phase RONO2 loss in the boundary layer. Other losses are 20 % by photolysis to recycle NOx and 15 % by dry deposition. RONO2 production accounts for 20 % of the net regional NOx sink in the Southeast US in summer, limited by the spatial segregation between BVOC and NOx emissions. This segregation implies that RONO2 production will remain a minor sink for NOx in the Southeast US in the future even as NOx emissions continue to decline.

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