scholarly journals Technical Note: Evaluation of simultaneous measurements of mesospheric OH, HO<sub>2</sub>, and O<sub>3</sub> under photochemical equilibrium assumption: Statistical approach

2017 ◽  
Author(s):  
Mikhail Yu. Kulikov ◽  
Anton A. Nechaev ◽  
Mikhail V. Belikovich ◽  
Tatiana S. Ermakova ◽  
Alexander M. Feigin
Keyword(s):  
Transport Model ◽  
Full Range ◽  
Lower Thermosphere ◽  
Technical Note ◽  
Primary Data ◽  
Chemical Transport Model ◽  
Air Concentration ◽  
Simultaneous Measurements ◽  
First Results ◽  
One Year

Abstract. The Technical Note presents a statistically correct approach to evaluating simultaneous measurements of several atmospheric components under the assumption of photochemical equilibrium. We consider simultaneous measurements of OH, HO2, and O3 at the altitudes of the mesosphere as a specific example and their daytime photochemical equilibrium as an evaluating relationship. A simplified algebraic equation relating local concentrations of these components in the 50–100 km altitude range has been derived. The parameters of the equation are air temperature, air concentration, local zenith angle, and the rates of 9 reactions. We have performed one-year simulation of the mesosphere and lower thermosphere using a 3D chemical-transport model. The simulation shows that the discrepancy between the calculated evolution of the components and the equilibrium value given by the equation does not exceed 3–4 % in the full range of altitudes independent of season or latitude. We have developed the technique of statistic Bayesian evaluation of simultaneous measurements of OH, HO2 and O3 based on the equilibrium equation taking into account the measurement error. The first results of application of the technique to MLS/Aura data are presented in this Technical Note. It has been found that the satellite data of HO2 distribution regularly demonstrates essentially lower altitudes of mesospheric maximum of this component. This has also been confirmed by offline retrieval of HO2 from the MLS primary data.

scholarly journals Technical note: Evaluation of the simultaneous measurements of mesospheric OH, HO<sub>2</sub>, and O<sub>3</sub> under a photochemical equilibrium assumption – a statistical approach

2018 ◽  
Vol 18 (10) ◽  
pp. 7453-7471 ◽  
Author(s):  
Mikhail Y. Kulikov ◽  
Anton A. Nechaev ◽  
Mikhail V. Belikovich ◽  
Tatiana S. Ermakova ◽  
Alexander M. Feigin
Keyword(s):  
Statistical Approach ◽  
Transport Model ◽  
Full Range ◽  
Lower Thermosphere ◽  
Technical Note ◽  
Chemical Transport Model ◽  
Simultaneous Measurements ◽  
First Results ◽  
Mesosphere And Lower Thermosphere ◽  
One Year

Abstract. This Technical Note presents a statistical approach to evaluating simultaneous measurements of several atmospheric components under the assumption of photochemical equilibrium. We consider simultaneous measurements of OH, HO2, and O3 at the altitudes of the mesosphere as a specific example and their daytime photochemical equilibrium as an evaluating relationship. A simplified algebraic equation relating local concentrations of these components in the 50–100 km altitude range has been derived. The parameters of the equation are temperature, neutral density, local zenith angle, and the rates of eight reactions. We have performed a one-year simulation of the mesosphere and lower thermosphere using a 3-D chemical-transport model. The simulation shows that the discrepancy between the calculated evolution of the components and the equilibrium value given by the equation does not exceed 3–4 % in the full range of altitudes independent of season or latitude. We have developed a statistical Bayesian evaluation technique for simultaneous measurements of OH, HO2, and O3 based on the equilibrium equation taking into account the measurement error. The first results of the application of the technique to MLS/Aura data (Microwave Limb Sounder) are presented in this Technical Note. It has been found that the satellite data of the HO2 distribution regularly demonstrate lower altitudes of this component's mesospheric maximum. This has also been confirmed by model HO2 distributions and comparison with offline retrieval of HO2 from the daily zonal means MLS radiance.

scholarly journals Multi-species inversion of CH<sub>4</sub>, CO and H<sub>2</sub> emissions from surface measurements

2009 ◽  
Vol 9 (14) ◽  
pp. 5281-5297 ◽  
Author(s):  
I. Pison ◽  
P. Bousquet ◽  
F. Chevallier ◽  
S. Szopa ◽  
D. Hauglustaine
Keyword(s):  
Transport Model ◽  
Regional Scale ◽  
Surface Concentration ◽  
Temporal Variations ◽  
Global Scale ◽  
Chemical Transport Model ◽  
Methyl Chloroform ◽  
Emission Fluxes ◽  
Surface Measurements ◽  
One Year

Abstract. In order to study the spatial and temporal variations of the emissions of greenhouse gases and of their precursors, we developed a data assimilation system and applied it to infer emissions of CH4, CO and H2 for one year. It is based on an atmospheric chemical transport model and on a simplified scheme for the oxidation chain of hydrocarbons, including methane, formaldehyde, carbon monoxide and molecular hydrogen together with methyl chloroform. The methodology is exposed and a first attempt at evaluating the inverted fluxes is made. Inversions of the emission fluxes of CO, CH4 and H2 and concentrations of HCHO and OH were performed for the year 2004, using surface concentration measurements of CO, CH4, H2 and CH3CCl3 as constraints. Independent data from ship and aircraft measurements and satellite retrievals are used to evaluate the results. The total emitted mass of CO is 30% higher after the inversion, due to increased fluxes by up to 35% in the Northern Hemisphere. The spatial distribution of emissions of CH4 is modified by a decrease of fluxes in boreal areas up to 60%. The comparison between mono- and multi-species inversions shows that the results are close at a global scale but may significantly differ at a regional scale because of the interactions between the various tracers during the inversion.

scholarly journals Technical note: Reanalysis of Aura MLS chemical observations

2019 ◽  
Vol 19 (21) ◽  
pp. 13647-13679 ◽  
Author(s):  
Quentin Errera ◽  
Simon Chabrillat ◽  
Yves Christophe ◽  
Jonas Debosscher ◽  
Daan Hubert ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Michelson Interferometer ◽  
Polar Vortex ◽  
Methyl Chloride ◽  
Technical Note ◽  
Chemical Transport Model ◽  
Stratospheric Polar Vortex ◽  
Upper Troposphere ◽  
Independent Observations

Abstract. This paper presents a reanalysis of the atmospheric chemical composition from the upper troposphere to the lower mesosphere from August 2004 to December 2017. This reanalysis is produced by the Belgian Assimilation System for Chemical ObsErvations (BASCOE) constrained by the chemical observations from the Microwave Limb Sounder (MLS) on board the Aura satellite. BASCOE is based on the ensemble Kalman filter (EnKF) method and includes a chemical transport model driven by the winds and temperature from the ERA-Interim meteorological reanalysis. The model resolution is 3.75∘ in longitude, 2.5∘ in latitude and 37 vertical levels from the surface to 0.1 hPa with 25 levels above 100 hPa. The outputs are provided every 6 h. This reanalysis is called BRAM2 for BASCOE Reanalysis of Aura MLS, version 2. Vertical profiles of eight species from MLS version 4 are assimilated and are evaluated in this paper: ozone (O3), water vapour (H2O), nitrous oxide (N2O), nitric acid (HNO3), hydrogen chloride (HCl), chlorine oxide (ClO), methyl chloride (CH3Cl) and carbon monoxide (CO). They are evaluated using independent observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and N2O observations from a different MLS radiometer than the one used to deliver the standard product and ozonesondes. The evaluation is carried out in four regions of interest where only selected species are evaluated. These regions are (1) the lower-stratospheric polar vortex where O3, H2O, N2O, HNO3, HCl and ClO are evaluated; (2) the upper-stratospheric–lower-mesospheric polar vortex where H2O, N2O, HNO3 and CO are evaluated; (3) the upper troposphere–lower stratosphere (UTLS) where O3, H2O, CO and CH3Cl are evaluated; and (4) the middle stratosphere where O3, H2O, N2O, HNO3, HCl, ClO and CH3Cl are evaluated. In general BRAM2 reproduces MLS observations within their uncertainties and agrees well with independent observations, with several limitations discussed in this paper (see the summary in Sect. 5.5). In particular, ozone is not assimilated at altitudes above (i.e. pressures lower than) 4 hPa due to a model bias that cannot be corrected by the assimilation. MLS ozone profiles display unphysical oscillations in the tropical UTLS, which are corrected by the assimilation, allowing a good agreement with ozonesondes. Moreover, in the upper troposphere, comparison of BRAM2 with MLS and independent observations suggests a positive bias in MLS O3 and a negative bias in MLS H2O. The reanalysis also reveals a drift in MLS N2O against independent observations, which highlights the potential use of BRAM2 to estimate biases between instruments. BRAM2 is publicly available and will be extended to assimilate MLS observations after 2017.

scholarly journals Characterisation of Central-African aerosol and trace-gas emissions based on MAX-DOAS measurements and model simulations over Bujumbura, Burundi

2017 ◽  
Author(s):  
Clio Gielen ◽  
François Hendrick ◽  
Gaia Pinardi ◽  
Isabelle De Smedt ◽  
Caroline Fayt ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Forest Fires ◽  
Transport Model ◽  
Central Africa ◽  
Optimal Estimation ◽  
Trace Gas ◽  
Chemical Transport Model ◽  
Radiative Power ◽  
First Results ◽  
The City

Abstract. We present MAX-DOAS measurements of NO2, HCHO, and aerosols performed in Central Africa, in the city of Bujumbura, Burundi (3.38° S, 29.3° E). A MAX-DOAS instrument has been operated at this location by BIRA-IASB since late 2013. Aerosol-extinction and trace-gas vertical profiles are retrieved by applying the optimal-estimation-based profiling tool bePRO to the measured O4, NO2 and HCHO slant-column densities. The MAX-DOAS vertical columns and profiles are used for investigating the diurnal and seasonal cycles of NO2, HCHO, and aerosols. Regarding the aerosols, the retrieved AODs are compared to co-located AERONET sun-photometer measurements for verification purposes, while in the case of NO2 and HCHO, the MAX-DOAS vertical columns and profiles are compared to GOME-2 and OMI satellite observations. To characterise the biomass-burning and biogenic emissions in the Bujumbura region, the trace gases and aerosol MAX-DOAS retrievals are used in combination with MODIS fire radiative-power values and the tropospheric 3D chemical transport model IMAGES, as well as simulations from the NOAA backward-trajectory model HYSPLIT. The first results show that the aerosol and HCHO seasonal variation is driven by the alternation of rain and dry periods, the latter being associated with intense biomass-burning agricultural activities and forest fires in the south/south-east and transport from this region to Bujumbura. In contrast, NO2 is seen to depend mainly on local emissions close to the city, due to the short lifetime of this species (typically 1–2 hours).

scholarly journals Technical note: Reanalysis of Aura MLS Chemical Observations

2019 ◽  
Author(s):  
Quentin Errera ◽  
Simon Chabrillat ◽  
Yves Christophe ◽  
Jonas Debosscher ◽  
Daan Hubert ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Michelson Interferometer ◽  
Polar Vortex ◽  
Methyl Chloride ◽  
Technical Note ◽  
Chemical Transport Model ◽  
Stratospheric Polar Vortex ◽  
Upper Troposphere ◽  
Independent Observations

Abstract. This paper presents a reanalysis of the atmospheric chemical composition from the upper troposphere to the lower mesosphere from August 2004 to December 2017. This reanalysis is produced by the Belgian Assimilation System for Chemical ObsErvations (BASCOE) constrained by the chemical observations from the Microwave Limb Sounder (MLS) onboard the Aura satellite. BASCOE is based on the Ensemble Kalman Filter (EnKF) method and includes a chemical transport model driven by the winds and temperature from the ERA-Interim meteorological reanalysis. The model resolution is 3.75° in longitude, 2.5° in latitude and 37 vertical levels from the surface to 0.1 hPa with 25 levels above 100 hPa. The outputs are provided every 6 hours. This reanalysis is called BRAM2 for BASCOE Reanalysis of Aura MLS, version 2. Vertical profiles of eight species from MLS version 4 are assimilated and are evaluated in this paper: ozone (O3), water vapour (H2O), nitrous oxide (N2O), nitric acid (HNO3), hydrogen chloride (HCl), chlorine oxide (ClO), methyl chloride (CH3Cl) and carbon monoxide (CO). They are evaluated using independent observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACEFTS), the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES), N2O observations from another MLS radiometer than the one used to deliver the standard product and ozonesondes. The evaluation is done in four regions of interest where only selected species are evaluated. These regions are (1) the lower stratospheric polar vortex where O3, H2O, N2O, HNO3, HCl and ClO are evaluated, (2) the upper stratospheric lower mesospheric polar vortex where H2O, N2O, HNO3 and CO are evaluated, (3) the tropical tropopause layer (TTL) where O3, H2O, CO and CH3Cl are evaluated and (4) the middle stratosphere where O3, H2O, N2O, HNO3, HCl, ClO and CH3Cl are evaluated. In general BRAM2 reproduces MLS observations within their uncertainties and agrees well with independent observations, with several limitations discussed in this paper (see the summary in Sect. 5.5). In particular, ozone is not assimilated at altitudes above (i.e. pressures lower than) 4 hPa due to a model bias that cannot be corrected by the assimilation. MLS ozone profiles display unphysical oscillations in the TTL which are corrected by the assimilation, allowing a good agreement with ozonesondes. Moreover, in the upper troposphere, comparison of BRAM2 with MLS and independent observations suggests a positive bias in MLS O3 and a negative bias in MLS H2O. The reanalysis also reveals a drift in MLS N2O against independent observations which highlights the potential use of BRAM2 to estimate biases between instruments. BRAM2 is publicly available and will be extended to assimilate MLS observations post 2017.

scholarly journals Sources and seasonality of atmospheric methanol based on tall tower measurements in the US Upper Midwest

2011 ◽  
Vol 11 (6) ◽  
pp. 17473-17505 ◽  
Author(s):  
L. Hu ◽  
M. J. Mohr ◽  
K. C. Wells ◽  
T. J. Griffis ◽  
D. Helmig ◽  
...  
Keyword(s):  
Transport Model ◽  
Early Summer ◽  
Emission Rates ◽  
University Of Minnesota ◽  
Chemical Transport Model ◽  
Upper Midwest ◽  
The Us ◽  
One Year ◽  
The University ◽  
Tall Tower

Abstract. We present over one year of continuous atmospheric methanol measurements from the University of Minnesota tall tower Trace Gas Observatory (KCMP tall tower; 244 m a.g.l.), and interpret the dataset in terms of constraints on regional methanol sources and seasonality. The seasonal cycle of methanol concentrations observed at the KCMP tall tower is generally similar to that simulated by a global 3-D chemical transport model (GEOS-Chem, driven with MEGANv2.0 biogenic emissions) except the seasonal peak occurs ~1 month earlier in the observations, apparently reflecting a model underestimate of emission rates for younger versus older leaves. Based on a source tracer approach, which we evaluate using GEOS-Chem and with multiple tracers, we estimate that anthropogenic emissions account for approximately 40 % of ambient methanol abundance during winter and 10 % during summer. During daytime in summer, methanol concentrations increase exponentially with temperature, reflecting the temperature sensitivity of the biogenic source, and the observed temperature dependence is statistically consistent with that in the model. Nevertheless, summertime concentrations are underestimated by on average 35 % in the model for this region. The seasonal importance of methanol as a source of formaldehyde (HCHO) and carbon monoxide (CO) is highest in spring through early summer, when biogenic methanol emissions are high but isoprene emissions are still relatively low. During that time observed methanol concentrations account for on average 20 % of the total CO and HCHO production rates as simulated by GEOS-Chem, compared to 12 % later in the summer and 12 % on an annual average basis. The biased seasonality in the model means that the photochemical role for methanol early in the growing season is presently underestimated.

scholarly journals Sources and seasonality of atmospheric methanol based on tall tower measurements in the US Upper Midwest

2011 ◽  
Vol 11 (21) ◽  
pp. 11145-11156 ◽  
Author(s):  
L. Hu ◽  
D. B. Millet ◽  
M. J. Mohr ◽  
K. C. Wells ◽  
T. J. Griffis ◽  
...  
Keyword(s):  
Transport Model ◽  
Early Summer ◽  
Emission Rates ◽  
University Of Minnesota ◽  
Chemical Transport Model ◽  
Upper Midwest ◽  
The Us ◽  
One Year ◽  
The University ◽  
Tall Tower

Abstract. We present over one year (January 2010–February 2011) of continuous atmospheric methanol measurements from the University of Minnesota tall tower Trace Gas Observatory (KCMP tall tower; 244 m a.g.l.), and interpret the dataset in terms of constraints on regional methanol sources and seasonality. The seasonal cycle of methanol concentrations observed at the KCMP tall tower is generally similar to that simulated by a global 3-D chemical transport model (GEOS-Chem, driven with MEGANv2.0 biogenic emissions) except the seasonal peak occurs ~1 month earlier in the observations, apparently reflecting a model underestimate of emission rates for younger versus older leaves. Based on a source tracer approach, which we evaluate using GEOS-Chem and with multiple tracers, we estimate that anthropogenic emissions account for approximately 40% of ambient methanol abundance during winter and 10% during summer. During daytime in summer, methanol concentrations increase exponentially with temperature, reflecting the temperature sensitivity of the biogenic source, and the observed temperature dependence is statistically consistent with that in the model. Nevertheless, summertime concentrations are underestimated by on average 35% in the model for this region. The seasonal importance of methanol as a source of formaldehyde (HCHO) and carbon monoxide (CO) is highest in spring through early summer, when biogenic methanol emissions are high but isoprene emissions are still relatively low. During that time observed methanol concentrations account for on average 20% of the total CO and HCHO production rates as simulated by GEOS-Chem, compared to 12% later in the summer and 12% on an annual average basis. The biased seasonality in the model means that the photochemical role for methanol early in the growing season is presently underestimated.

scholarly journals PMIF v1.0: an inversion system to estimate the potential of satellite observations to monitor fossil fuel CO<sub>2</sub> emissions over the globe

2020 ◽  
Author(s):  
Yilong Wang ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Franck Lespinas ◽  
Michael Buchwitz ◽  
...  
Keyword(s):  
Power Plants ◽  
Fossil Fuel ◽  
Transport Model ◽  
Time Windows ◽  
Full Range ◽  
European Space Agency ◽  
Relative Difference ◽  
Uncertainty Reduction ◽  
Horizontal Resolution ◽  
One Year

Abstract. This study assesses the potential of satellite imagery of vertically integrated columns of dry-air mole fractions of CO2 (XCO2) to constrain the emissions from cities and power plants (called emission clumps) over the whole globe during one year. The imagery is simulated for one imager of the Copernicus mission on Anthropogenic Carbon Dioxide Monitoring (CO2M) planned by the European Space Agency and the European Commission. The width of the swath of the CO2M instruments is about 300 km and the ground horizontal resolution is about 2 km resolution. A Plume Monitoring Inversion Framework (PMIF) is developed, relying on a Gaussian plume model to simulate the XCO2 plumes of each emission clump and on a combination of overlapping assimilation windows to solve for the inversion problem. The inversion solves for the 3 h mean emissions (during 8:30–11:30 local time) before satellite overpasses and for the mean emissions during other hours of the day (over the aggregation between 0:00–8:30 and 11:30–0:00) for each clump and for the 366 days of the year. Our analysis focuses on the derivation of the uncertainty in the inversion estimates (the “posterior uncertainty”) of the clump emissions. A comparison of the results obtained with PMIF and those from a previous study using a complex 3-D Eulerian transport model for a single city (Paris) shows that the PMIF system provides the correct order of magnitude for the uncertainty reduction of emission estimates (i.e. the relative difference between the prior and posterior uncertainties). Beyond the one or few large cities studied by previous studies, our results provide, for the first time, the global statistics of the uncertainty reduction of emissions for the full range of global clumps (differing in emission rate and spread, and distance from other major clumps) and meteorological conditions. We show that only the clumps with an annual emission budget higher than 2 MtC per year can potentially have their emissions between 8:30 and 11:30 constrained with a posterior uncertainty smaller than 20 % for more than 10 times within one year (ignoring the potential to cross or extrapolate information between 8:30–11:30 time windows on different days). The PMIF inversion results are also aggregated in time to investigate the potential of CO2M observations to constrain daily and annual emissions, relying on the extrapolation of information obtained for 8:30–11:30 time windows during days when clouds and aerosols do not mask the plumes, based on various assumptions regarding the temporal auto-correlations of the uncertainties in the emission estimates that are used as a prior knowledge in the Bayesian framework of PMIF. We show that the posterior uncertainties of daily and annual emissions are highly dependent on these temporal auto-correlations, stressing the need of systematic assessment of the sources of uncertainty in the spatiotemporally-resolved emission inventories used as prior estimates in the inversions. We highlight the difficulty to constrain global and national fossil fuel CO2 emissions with satellite XCO2 measurements only, and calls for integrated inversion systems that exploit multiple types of measurements.

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.

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