scholarly journals Simulation of variability in atmospheric carbon dioxide using a global coupled Eulerian – Lagrangian transport model

2011 ◽  
Vol 4 (2) ◽  
pp. 317-324 ◽  
Author(s):  
Y. Koyama ◽  
S. Maksyutov ◽  
H. Mukai ◽  
K. Thoning ◽  
P. Tans
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Dispersion Model ◽  
Regional Scale ◽  
Coupled Model ◽  
Particle Dispersion ◽  
Atmospheric Composition ◽  
Tracer Transport ◽  
Eulerian Model ◽  
Co2 Concentrations

Abstract. This study assesses the advantages of using a coupled atmospheric-tracer transport model, comprising a global Eulerian model and a global Lagrangian particle dispersion model, to improve the reproducibility of tracer-gas variations affected by the near-field surface emissions and transport around observation sites. The ability to resolve variability in atmospheric composition on an hourly time-scale and a spatial scale of several kilometers would be beneficial for analyzing data from continuous ground-based monitoring and from upcoming space-based observations. The coupled model yields an increase in the horizontal resolution of transport and fluxes, and has been tested in regional-scale studies of atmospheric chemistry. By applying the Lagrangian component to the global domain, we extend this approach to the global scale, thereby enabling computationally efficient global inverse modeling and data assimilation. To validate the coupled model, we compare model-simulated CO2 concentrations with continuous observations at three sites: two operated by the National Oceanic and Atmospheric Administration, USA, and one operated by the National Institute for Environmental Studies, Japan. As the goal of this study is limited to introducing the new modeling approach, we selected a transport simulation at these three sites to demonstrate how the model may perform at various geographical areas. The coupled model provides improved agreement between modeled and observed CO2 concentrations in comparison to the Eulerian model. In an area where variability in CO2 concentration is dominated by a fossil fuel signal, the correlation coefficient between modeled and observed concentrations increases by between 0.05 to 0.1 from the original values of 0.5–0.6 achieved with the Eulerian model.

scholarly journals Simulation of atmospheric carbon dioxide variability with a global coupled Eulerian-Lagrangian transport model

2010 ◽  
Vol 3 (4) ◽  
pp. 2051-2070
Author(s):  
Y. Koyama ◽  
S. Maksyutov ◽  
H. Mukai ◽  
K. Thoning ◽  
P. Tans
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Regional Scale ◽  
Coupled Model ◽  
Particle Dispersion ◽  
Atmospheric Composition ◽  
Small Subset ◽  
Tracer Transport ◽  
Eulerian Model ◽  
Co2 Concentrations

Abstract. This study assesses the advantages of using a coupled atmospheric-tracer transport model, comprising a global Eulerian model and a global Lagrangian particle dispersion model, for reproducibility of tracer gas variation affected by near field around observation sites. The ability to resolve variability in atmospheric composition on an hourly time scale and a spatial scale of several kilometers would be beneficial for analyzing data from continuous ground-based monitoring and upcoming space-based observations. The coupled model yields increased horizontal resolution of transport and fluxes, and has been tested in regional-scale studies of atmospheric chemistry. By applying the Lagrangian component to the global domain, we extend this approach to the global scale, thereby enabling global inverse modeling and data assimilation. To validate the coupled model, we compare model-simulated CO2 concentrations with continuous observations at two sites operated by the National Oceanic and Atmospheric Administration, USA and one site operated by National Institute for Environmental Studies, Japan. As the purpose of this study is limited to demonstration of the new modeling approach, we select a small subset of 3 sites to highlight use of the model in various geographical areas. To explore the capability of the coupled model in simulating synoptic-scale meteorological phenomena, we calculate the correlation coefficients and variance ratios between deseasonalized model-simulated and observed CO2 concentrations. Compared with the Eulerian model alone, the coupled model yields improved agreement between modeled and observed CO2 concentrations.

scholarly journals Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation

2016 ◽  
Vol 9 (2) ◽  
pp. 749-764 ◽  
Author(s):  
Dmitry A. Belikov ◽  
Shamil Maksyutov ◽  
Alexey Yaremchuk ◽  
Alexander Ganshin ◽  
Thomas Kaminski ◽  
...  
Keyword(s):  
Message Passing ◽  
Message Passing Interface ◽  
Automatic Differentiation ◽  
Transport Model ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Coupled Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Eulerian Model

Abstract. We present the development of the Adjoint of the Global Eulerian–Lagrangian Coupled Atmospheric (A-GELCA) model that consists of the National Institute for Environmental Studies (NIES) model as an Eulerian three-dimensional transport model (TM), and FLEXPART (FLEXible PARTicle dispersion model) as the Lagrangian Particle Dispersion Model (LPDM). The forward tangent linear and adjoint components of the Eulerian model were constructed directly from the original NIES TM code using an automatic differentiation tool known as TAF (Transformation of Algorithms in Fortran; http://www.FastOpt.com), with additional manual pre- and post-processing aimed at improving transparency and clarity of the code and optimizing the performance of the computing, including MPI (Message Passing Interface). The Lagrangian component did not require any code modification, as LPDMs are self-adjoint and track a significant number of particles backward in time in order to calculate the sensitivity of the observations to the neighboring emission areas. The constructed Eulerian adjoint was coupled with the Lagrangian component at a time boundary in the global domain. The simulations presented in this work were performed using the A-GELCA model in forward and adjoint modes. The forward simulation shows that the coupled model improves reproduction of the seasonal cycle and short-term variability of CO2. Mean bias and standard deviation for five of the six Siberian sites considered decrease roughly by 1 ppm when using the coupled model. The adjoint of the Eulerian model was shown, through several numerical tests, to be very accurate (within machine epsilon with mismatch around to ±6 e−14) compared to direct forward sensitivity calculations. The developed adjoint of the coupled model combines the flux conservation and stability of an Eulerian discrete adjoint formulation with the flexibility, accuracy, and high resolution of a Lagrangian backward trajectory formulation. A-GELCA will be incorporated into a variational inversion system designed to optimize surface fluxes of greenhouse gases.

scholarly journals Adjoint of the Global Eulerian–Lagrangian Coupled Atmospheric transport model (A-GELCA v1.0): development and validation

2015 ◽  
Vol 8 (7) ◽  
pp. 5983-6019
Author(s):  
D. A. Belikov ◽  
S. Maksyutov ◽  
A. Yaremchuk ◽  
A. Ganshin ◽  
T. Kaminski ◽  
...  
Keyword(s):  
Message Passing ◽  
Message Passing Interface ◽  
Automatic Differentiation ◽  
Transport Model ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Coupled Model ◽  
Particle Dispersion ◽  
Limiting Factors ◽  
Eulerian Model

Abstract. We present the development of the Adjoint of the Global Eulerian–Lagrangian Coupled Atmospheric (A-GELCA) model that consists of the National Institute for Environmental Studies (NIES) model as an Eulerian three-dimensional transport model (TM), and FLEXPART (FLEXible PARTicle dispersion model) as the Lagrangian plume diffusion model (LPDM). The tangent and adjoint components of the Eulerian model were constructed directly from the original NIES TM code using an automatic differentiation tool known as TAF (Transformation of Algorithms in Fortran; http://www.FastOpt.com), with additional manual pre- and post-processing aimed at improving the performance of the computing, including MPI (Message Passing Interface). As results, the adjoint of Eulerian model is discrete. Construction of the adjoint of the Lagrangian component did not require any code modification, as LPDMs are able to track a significant number of particles back in time and thereby calculate the sensitivity of observations to the neighboring emissions areas. Eulerian and Lagrangian adjoint components were coupled at the time boundary in the global domain.The results are verified using a series of test experiments. The forward simulation shown the coupled model is effective in reproducing the seasonal cycle and short-term variability of CO2 even in the case of multiple limiting factors, such as high uncertainty of fluxes and the low resolution of the Eulerian model. The adjoint model demonstrates the high accuracy compared to direct forward sensitivity calculations and fast performance. The developed adjoint of the coupled model combines the flux conservation and stability of an Eulerian discrete adjoint formulation with the flexibility, accuracy, and high resolution of a Lagrangian backward trajectory formulation.

scholarly journals A global coupled Eulerian-Lagrangian model and 1 × 1 km CO<sub>2</sub> surface flux dataset for high-resolution atmospheric CO<sub>2</sub> transport simulations

2011 ◽  
Vol 4 (3) ◽  
pp. 2047-2080 ◽  
Author(s):  
A. Ganshin ◽  
T. Oda ◽  
M. Saito ◽  
S. Maksyutov ◽  
V. Valsala ◽  
...  
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Transport Model ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Lagrangian Model ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e., a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.

scholarly journals Technical note: A high-resolution inverse modelling technique for estimating surface CO<sub>2</sub> fluxes based on the NIES-TM – FLEXPART coupled transport model and its adjoint

2020 ◽  
Author(s):  
Shamil Maksyutov ◽  
Tomohiro Oda ◽  
Makoto Saito ◽  
Rajesh Janardanan ◽  
Dmitry Belikov ◽  
...  
Keyword(s):  
High Resolution ◽  
Transport Model ◽  
Dispersion Model ◽  
Surface Flux ◽  
Particle Dispersion ◽  
Anthropogenic Emissions ◽  
Coupled Transport ◽  
Tracer Transport ◽  
Flux Corrections

Abstract. We developed a high-resolution surface flux inversion system based on the global Lagrangian–Eulerian coupled tracer transport model composed of National Institute for Environmental Studies Transport Model (NIES-TM) and FLEXible PARTicle dispersion model (FLEXPART). The inversion system is named NTFVAR (NIES-TM-FLEXPART-variational) as it applies variational optimisation to estimate surface fluxes. We tested the system by estimating optimized corrections to natural surface CO2 fluxes to achieve best fit to atmospheric CO2 data collected by the global in-situ network, as a necessary step towards capability of estimating anthropogenic CO2 emissions. We employ the Lagrangian particle dispersion model (LPDM) FLEXPART to calculate the surface flux footprints of CO2 observations at a 0.1° × 0.1° spatial resolution. The LPDM is coupled to a global atmospheric tracer transport model (NIES-TM). Our inversion technique uses an adjoint of the coupled transport model in an iterative optimization procedure. The flux error covariance operator is being implemented via implicit diffusion. Biweekly flux corrections to prior flux fields were estimated for the years 2010–2012 from in-situ CO2 data included in the Observation Package (ObsPack) dataset. High-resolution prior flux fields were prepared using Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) for fossil fuel combustion, Global Fire Assimilation System (GFAS) for biomass burning, the Vegetation Integrative SImulator for Trace gases (VISIT) model for terrestrial biosphere exchange and Ocean Tracer Transport Model (OTTM) for oceanic exchange. The terrestrial biospheric flux field was constructed using a vegetation mosaic map and separate simulation of CO2 fluxes at daily time step by the VISIT model for each vegetation type. The prior flux uncertainty for terrestrial biosphere was scaled proportionally to the monthly mean Gross Primary Production (GPP) by the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17 product. The inverse system calculates flux corrections to the prior fluxes in the form of a relatively smooth field multiplied by high-resolution patterns of the prior flux uncertainties for land and ocean, following the coastlines and vegetation productivity gradients. The resulting flux estimates improve fit to the observations at continuous observations sites, reproducing both the seasonal variation and short-term concentration variability, including high CO2 concentration events associated with anthropogenic emissions. The use of high-resolution atmospheric transport in global CO2 flux inversion has the advantage of better resolving the transport from the mix of the anthropogenic and biospheric sources in densely populated continental regions and shows potential for better separation between fluxes from terrestrial ecosystems and strong localised sources such as anthropogenic emissions and forest fires. Further improvements in the modelling system are needed as the posterior fit is better than that by the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker only for a fraction of the monitoring sites, mostly at coastal and island locations experiencing mix of background and local flux signals.

scholarly journals The CarboCount CH sites: characterization of a dense greenhouse gas observation network

2015 ◽  
Vol 15 (19) ◽  
pp. 11147-11164 ◽  
Author(s):  
B. Oney ◽  
S. Henne ◽  
N. Gruber ◽  
M. Leuenberger ◽  
I. Bamberger ◽  
...  
Keyword(s):  
Carbon Flux ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Regional Scale ◽  
Particle Dispersion ◽  
Observation Network ◽  
Simulated Surface ◽  
Swiss Plateau ◽  
Atmospheric Transport Model

Abstract. We describe a new rural network of four densely placed (< 100 km apart), continuous atmospheric carbon (CO2, CH4, and CO) measurement sites in north-central Switzerland and analyze its suitability for regional-scale (~ 100–500 km) carbon flux studies. We characterize each site for the period from March 2013 to February 2014 by analyzing surrounding land cover, observed local meteorology, and sensitivity to surface fluxes, as simulated with the Lagrangian particle dispersion model FLEXPART-COSMO (FLEXible PARTicle dispersion model-Consortium for Small-Scale Modeling). The Beromünster measurements are made on a tall tower (212 m) located on a gentle hill. At Beromünster, regional CO2 signals (measurement minus background) vary diurnally from −4 to +4 ppmv, on average, and are simulated to come from nearly the entire Swiss Plateau, where 50 % of surface influence is simulated to be within 130–260 km distance. The Früebüel site measurements are made 4 m above ground on the flank of a gently sloping mountain. Nearby (< 50 km) pasture and forest fluxes exert the most simulated surface influence, except during convective summertime days when the site is mainly influenced by the eastern Swiss Plateau, which results in summertime regional CO2 signals varying diurnally from −5 to +12 ppmv and elevated summer daytime CH4 signals (+30 ppbv above other sites). The Gimmiz site measurements are made on a small tower (32 m) in flat terrain. Here, strong summertime regional signals (−5 to +60 ppmv CO2) stem from large, nearby (< 50 km) crop and anthropogenic fluxes of the Seeland region, except during warm or windy days when simulated surface influence is of regional scale (< 250 km). The Lägern-Hochwacht measurements are made on a small tower (32 m) on top of the steep Lägern crest, where simulated surface influence is typically of regional scale (130–300 km) causing summertime regional signals to vary from −5 to +8 ppmv CO2. Here, considerable anthropogenic influence from the nearby industrialized region near Zurich causes the average wintertime regional CO2 signals to be 5 ppmv above the regional signals simultaneously measured at the Früebüel site. We find that the suitability of the data sets from our current observation network for regional carbon budgeting studies largely depends on the ability of the high-resolution (2 km) atmospheric transport model to correctly capture the temporal dynamics of the stratification of the lower atmosphere at the different sites. The current version of the atmospheric transport model captures these dynamics well, but it clearly reaches its limits at the sites in steep topography and at the sites that generally remain in the surface layer. Trace gas transport and inverse modeling studies will be necessary to determine the impact of these limitations on our ability to derive reliable regional-scale carbon flux estimates in the complex Swiss landscape.

scholarly journals European source and sink areas of CO<sub>2</sub> retrieved from Lagrangian transport model interpretation of combined O<sub>2</sub> and CO<sub>2</sub> measurements at the high alpine research station Jungfraujoch

2011 ◽  
Vol 11 (15) ◽  
pp. 8017-8036 ◽  
Author(s):  
C. Uglietti ◽  
M. Leuenberger ◽  
D. Brunner
Keyword(s):  
Transport Model ◽  
Dispersion Model ◽  
Seasonal Pattern ◽  
Particle Dispersion ◽  
Research Station ◽  
Co2 Uptake ◽  
Air Masses ◽  
Background Values ◽  
Co2 Concentrations ◽  
Source And Sink

Abstract. The University of Bern monitors carbon dioxide (CO2) and oxygen (O2) at the High Altitude Research Station Jungfraujoch since the year 2000 by means of flasks sampling and since 2005 using a continuous in situ measurement system. This study investigates the transport of CO2 and O2 towards Jungfraujoch using backward Lagrangian Particle Dispersion Model (LPDM) simulations and utilizes CO2 and O2 signatures to classify air masses. By investigating the simulated transport patterns associated with distinct CO2 concentrations it is possible to decipher different source and sink areas over Europe. The highest CO2 concentrations, for example, were observed in winter during pollution episodes when air was transported from Northeastern Europe towards the Alps, or during south Foehn events with rapid uplift of polluted air from Northern Italy, as demonstrated in two case studies. To study the importance of air-sea exchange for variations in O2 concentrations at Jungfraujoch the correlation between CO2 and APO (Atmospheric Potential Oxygen) deviations from a seasonally varying background was analyzed. Anomalously high APO concentrations were clearly associated with air masses originating from the Atlantic Ocean, whereas low APO concentrations were found in air masses advected either from the east from the Eurasian continent in summer, or from the Eastern Mediterranean in winter. Those air masses with low APO in summer were also strongly depleted in CO2 suggesting a combination of CO2 uptake by vegetation and O2 uptake by dry summer soils. Other subsets of points in the APO-CO2 scatter plot investigated with respect to air mass origin included CO2 and APO background values and points with regular APO but anomalous CO2 concentrations. Background values were associated with free tropospheric air masses with little contact with the boundary layer during the last few days, while high or low CO2 concentrations reflect the various levels of influence of anthropogenic emissions and the biosphere. The pronounced cycles of CO2 and O2 exchanges with the biosphere and the ocean cause clusters of points and lead to a seasonal pattern.

scholarly journals A global coupled Eulerian-Lagrangian model and 1 × 1 km CO<sub>2</sub> surface flux dataset for high-resolution atmospheric CO<sub>2</sub> transport simulations

2012 ◽  
Vol 5 (1) ◽  
pp. 231-243 ◽  
Author(s):  
A. Ganshin ◽  
T. Oda ◽  
M. Saito ◽  
S. Maksyutov ◽  
V. Valsala ◽  
...  
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Transport Model ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Lagrangian Model ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA), comprising a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e. a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.

scholarly journals Intercontinental transport of biomass burning pollutants over the Mediterranean Basin during the summer 2014 ChArMEx-GLAM airborne campaign

2017 ◽  
Author(s):  
Vanessa Brocchi ◽  
Gisèle Krysztofiak ◽  
Valéry Catoire ◽  
Jonathan Guth ◽  
Virginie Marécal ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Mediterranean Basin ◽  
Transport Model ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Transport Processes ◽  
Atmospheric Composition ◽  
Air Masses ◽  
The Mediterranean ◽  
The Mediterranean Basin

Abstract. The Gradient in Longitude of Atmospheric constituents above the Mediterranean basin (GLAM) campaign was set up in August 2014, as part of the Chemistry-Aerosol Mediterranean Experiment (ChArMEx) project. This campaign aimed at studying the chemical variability of gaseous pollutants and aerosols in the troposphere along a West-East transect above the Mediterranean Basin (MB). In the present work, we focus on two biomass burning events detected at 5.4 and 9.7 km altitude above sea level (asl) above Sardinia (from 39°12 N–9°15 E to 35°35 N–12°35 E and at 39°30 N–8°25 E, respectively). Concentration variations in trace gas carbon monoxide (CO) and aerosols were measured thanks to the standard instruments on-board the Falcon-20 aircraft operated by the Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE) and the Spectromètre InfraRouge In situ Toute Altitude (SPIRIT) developed by LPC2E. 20-day backward trajectories with Lagrangian particle dispersion model FLEXPART (FLEXible PARTicle) help understanding the transport processes and the origin of the emissions that contributed to these pollutions detected above Sardinia. Biomass burning emissions came (i) on 10 August from the Northern American continent with air masses transported during 5 days before arriving over the MB, and (ii) on 6 August from Siberia with air masses travelling during 12 days and enriched in fire emission products above Canada 5 days before arriving over the MB. In combination with the Global Fire Assimilation System (GFAS) inventory and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite fire locations, FLEXPART reproduces well the contribution of those fires to CO and aerosols enhancements under adjustments of the injection height to 10 km in both cases, and application of an amplification factor of 2.5 on CO GFAS emissions for the 10 August event. The chemistry transport model (CTM) MOCAGE is used as a complementary tool for the case of 6 August to confirm the origin of the emissions by tracing the CO global atmospheric composition reaching the MB. For this event, both models agree on the origin of air masses with CO concentrations simulated with MOCAGE lower than the observed ones, likely caused by the coarse model horizontal resolution that yields the dilution of the emissions and diffusion during transport. In combination with wind fields, the analysis of the transport of the air mass documented on 6 August suggests the subsidence of CO pollution from Siberia towards North America and then a transport to the MB via fast jet winds located at around 5.5 km in altitude.

The BIO-MAÏDO (Bio-physicochemistry of tropical clouds at Maïdo (La Réunion Island): processes and impacts on secondary organic aerosols formation) campaign

2020 ◽  
Author(s):  
Maud Leriche ◽  
Aurélie Colomb ◽  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Transport Model ◽  
Dispersion Model ◽  
Cloud Model ◽  
Particle Dispersion ◽  
Atmospheric Composition ◽  
Biogenic Volatile Organic Compounds ◽  
Volatile Organic ◽  
Orographic Clouds

&lt;p&gt;BIO-MA&amp;#207;DO is a French collaborative program founded by the ANR (Agence Nationale de La Recherche). BIO-MA&amp;#207;DO aims at better understanding the chemical and biological multiphasic mechanisms that control the Secondary Organic Aerosol (SOA) formation. The tropical environment of the Reunion Island represents an ideal site to study SOA formation: (1) numerous biogenic volatile organic compounds, precursors of SOA are emitted in huge amount and the high solar intensity flux and the temperature favors their chemical transformations; (2) due to the high occurrence of orographic clouds over this region, this site allows evaluating the influence of aqueous processes on SOA formation. The strategy adopted is based on an intensive field campaign over several sites with the objective to characterize sources of gases and aerosols and to evaluate multiphasic pathways controlling the formation and oxidation of SOA. This work is done in synergy with modeling investigations using a lagrangian particle dispersion model (FLEXPART), a 0D process cloud model (CLEPS) together with a 3D chemistry/transport model (Meso-NH).&lt;/p&gt;&lt;p&gt;The campaign took place from 13&lt;sup&gt;th&lt;/sup&gt; of March to 4&lt;sup&gt;th&lt;/sup&gt; of April 2019 at La R&amp;#233;union Island. The main objectives were to document the cloud cycle on the slope of the Ma&amp;#239;do, the boundary layer development and the chemical evolution of atmospheric composition (primary and secondary aerosols as well as gaseous precursors) along the slope up to the receptor site, the Ma&amp;#239;do observatory. For this reason, the campaign took place on five sites distributed on the slope from the Ma&amp;#239;do to the observatory. A innovative instrumentation was deployed: three PTR-MS, a tethered balloon, an instrumented mast measuring biogenic volatile organic compounds fluxes, a mobile mast with a cloud impactor, etc. Preliminary results from the campaign will be presented.&lt;/p&gt;

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