scholarly journals Grid-independent high-resolution dust emissions (v1.0) for chemical transport models: application to GEOS-Chem (12.5.0)

2021 ◽  
Vol 14 (7) ◽  
pp. 4249-4260
Author(s):  
Jun Meng ◽  
Randall V. Martin ◽  
Paul Ginoux ◽  
Melanie Hammer ◽  
Melissa P. Sulprizio ◽  
...  
Keyword(s):  
High Resolution ◽  
Transport Model ◽  
Dust Emission ◽  
Chemical Transport ◽  
Nonlinear Dependence ◽  
Transport Models ◽  
Dust Source ◽  
Dust Emissions ◽  
Chemical Transport Models ◽  
Emission Strength

Abstract. The nonlinear dependence of the dust saltation process on wind speed poses a challenge for models of varying resolutions. This challenge is of particular relevance for the next generation of chemical transport models with nimble capability for multiple resolutions. We develop and apply a method to harmonize dust emissions across simulations of different resolutions by generating offline grid-independent dust emissions driven by native high-resolution meteorological fields. We implement into the GEOS-Chem chemical transport model a high-resolution dust source function to generate updated offline dust emissions. These updated offline dust emissions based on high-resolution meteorological fields strengthen dust emissions over relatively weak dust source regions, such as in southern South America, southern Africa and the southwestern United States. Identification of an appropriate dust emission strength is facilitated by the resolution independence of offline emissions. We find that the performance of simulated aerosol optical depth (AOD) versus measurements from the AERONET network and satellite remote sensing improves significantly when using the updated offline dust emissions with the total global annual dust emission strength of 2000 Tg yr−1 rather than the standard online emissions in GEOS-Chem. The updated simulation also better represents in situ measurements from a global climatology. The offline high-resolution dust emissions are easily implemented in chemical transport models. The source code and global offline high-resolution dust emission inventory are publicly available.

scholarly journals Grid-independent High Resolution Dust Emissions (v1.0) for Chemical Transport Models: Application to GEOS-Chem (version 12.5.0)

2020 ◽  
Author(s):  
Jun Meng ◽  
Randall V. Martin ◽  
Paul Ginoux ◽  
Melanie Hammer ◽  
Melissa P. Sulprizio ◽  
...  
Keyword(s):  
High Resolution ◽  
Dust Emission ◽  
Chemical Transport ◽  
Data Availability ◽  
Nonlinear Dependence ◽  
Transport Models ◽  
Dust Source ◽  
Dust Emissions ◽  
Chemical Transport Models ◽  
Emission Strength

Abstract. The nonlinear dependence of the dust saltation process on wind speed poses a challenge for models of varying resolutions. This challenge is of particular relevance for the next generation of chemical transport models with nimble capability for multiple resolutions. We develop and apply a method to harmonize dust emissions across simulations of different resolutions by generating offline grid-independent dust emissions driven by native high-resolution meteorological fields. We implement into the GEOS-Chem chemical transport model a high-resolution dust source function to generate updated offline dust emissions. These updated offline dust emissions based on high-resolution meteorological fields can better resolve weak dust source regions, such as in southern South America, southern Africa, and the southwestern United States. Identification of an appropriate dust emission strength is facilitated by the resolution independence of offline emissions. We find that the performance of simulated aerosol optical depth (AOD) versus measurements from the AERONET network and satellite remote sensing improves significantly when using the updated offline dust emissions with the total global annual dust emission strength of 2,000 Tg yr−1 rather than the standard online emissions in GEOS-Chem. The offline high-resolution dust emissions are easily implemented in chemical transport models. The source code is available online through GitHub: https://github.com/Jun-Meng/geos-chem/tree/v11-01-Patches-UniCF-vegetation . The global offline high resolution dust emission inventory is freely available (see Code and Data Availability section).

scholarly journals Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

2018 ◽  
Author(s):  
Scott D. Chambers ◽  
Elise-Andree Guérette ◽  
Khalia Monk ◽  
Alan D. Griffiths ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Potential Health ◽  
Meteorological Model ◽  
Model Skill ◽  
Chemical Transport Models

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

scholarly journals On the ability of chemical transport models to simulate the vertical structure of the N<sub>2</sub>O, NO<sub>2</sub> and HNO<sub>3</sub> species in the mid-latitude stratosphere

2005 ◽  
Vol 5 (6) ◽  
pp. 12373-12401
Author(s):  
G. Berthet ◽  
N. Huret ◽  
F. Lefèvre ◽  
G. Moreau ◽  
C. Robert ◽  
...  
Keyword(s):  
Transport Model ◽  
Three Dimensional ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
One Dimensional ◽  
Chemical Transport Models ◽  
Dimensional Version ◽  
The Impact

Abstract. In this paper we study the impact of the modelling of N2O on the simulation of NO2 and HNO3 by comparing in situ vertical profiles measured at mid-latitudes with the results of the Reprobus 3-D CTM (Three-dimensional Chemical Transport Model) computed with the kinetic parameters from the JPL recommendation in 2002. The analysis of the measured in situ profile of N2O shows particular features indicating different air mass origins. The measured N2O, NO2 and HNO3 profiles are not satisfyingly reproduced by the CTM when computed using the current 6-hourly ECMWF operational analysis. Improving the simulation of N2O transport allows us to calculate quantities of NO2 and HNO3 in reasonable agreement with observations. This is achieved using 3-hourly winds obtained from ECMWF forecasts. The best agreement is obtained by constraining a one-dimensional version of the model with the observed N2O. This study shows that modelling the NOy partitioning with better accuracy relies at least on a correct simulation of N2O and thus of total NOy.

scholarly journals On the ability of chemical transport models to simulate the vertical structure of the N<sub>2</sub>O, NO<sub>2</sub> and HNO<sub>3</sub> species in the mid-latitude stratosphere

2006 ◽  
Vol 6 (6) ◽  
pp. 1599-1609 ◽  
Author(s):  
G. Berthet ◽  
N. Huret ◽  
F. Lefèvre ◽  
G. Moreau ◽  
C. Robert ◽  
...  
Keyword(s):  
Transport Model ◽  
Three Dimensional ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
One Dimensional ◽  
Chemical Transport Models ◽  
Dimensional Version ◽  
The Impact

Abstract. In this paper we study the impact of the modelling of N2O on the simulation of NO2 and HNO3 by comparing in situ vertical profiles measured at mid-latitudes with the results of the Reprobus 3-D CTM (Three-dimensional Chemical Transport Model) computed with the kinetic parameters from the JPL recommendation in 2002. The analysis of the measured in situ profile of N2O shows particular features indicating different air mass origins. The measured N2O, NO2 and HNO3 profiles are not satisfyingly reproduced by the CTM when computed using the current 6-hourly ECMWF operational analysis. Improving the simulation of N2O transport allows us to calculate quantities of NO2 and HNO3 in reasonable agreement with observations. This is achieved using 3-hourly winds obtained from ECMWF forecasts. The best agreement is obtained by constraining a one-dimensional version of the model with the observed N2O. This study shows that the modelling of the NOy partitioning with better accuracy relies at least on a correct simulation of N2O and thus of total NOy.

scholarly journals Analyzing experimental data and model parameters: implications for predictions of SOA using chemical transport models

2013 ◽  
Vol 13 (6) ◽  
pp. 15907-15947 ◽  
Author(s):  
K. C. Barsanti ◽  
A. G. Carlton ◽  
S. H. Chung
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Chemical Transport ◽  
Basis Set ◽  
Base Case ◽  
Model Parameters ◽  
Smog Chamber ◽  
Modeling Framework ◽  
Transport Models ◽  
Chemical Transport Models

Abstract. Despite the critical importance for air quality and climate predictions, accurate representation of secondary organic aerosol (SOA) formation remains elusive. An essential addition to the ongoing discussion of improving model predictions is an acknowledgement of the linkages between experimental conditions, parameter optimization and model output, as well as the linkage between empirically-derived partitioning parameters and the physicochemical properties of SOA they represent in models. In this work, advantages of the volatility basis set (VBS) modeling approach are exploited to develop parameters for use in the computationally-efficient and widely-used two product (2p) SOA modeling framework, standard in chemical transport models such as CMAQ (Community Multiscale Air Quality) and GEOS-Chem (Goddard Earth Observing System–Chemistry). Calculated SOA yields and mass loadings obtained using the newly-developed 2p-VBS parameters and existing 2p and VBS parameters are compared with observed yields and mass loadings from a comprehensive list of published smog chamber studies to determine a "best available" set of SOA modeling parameters. SOA and PM2.5 levels are simulated using CMAQv.4.7.1; results are compared for a base case (with default 2p CMAQ parameters) and two "best available" parameter cases chosen to illustrate the high- and low-NOx limits of biogenic SOA formation from monoterpenes. Comparisons of published smog chamber data with SOA yield predictions illustrate that: (1) SOA yields for naphthalene and cyclic and > C5 alkanes are not well represented using either newly developed (2p-VBS) or existing (2p and VBS) parameters for low-yield aromatics and lumped alkanes, respectively; and (2) for 4 of 7 volatile organic compound + oxidant systems, the 2p-VBS parameters better represent existing data. Using the "best available" parameters (combination of published 2p and newly derived 2p-VBS), predicted SOA mass and PM2.5 concentrations increase by up to 10–15% and 7%, respectively, for the high-NOx case and up to 215% (~ 3 μg m−3) and 55%, respectively, for the low-NOx case. The ability to robustly assign "best available" parameters, however, is limited due to insufficient data for photo-oxidation of diverse monoterpenes and sesquiterpenes under a variety of atmospherically relevant NOx conditions. These results are discussed in terms of implications for current chemical transport model simulations and recommendations are provided for future measurement and modeling efforts.

scholarly journals Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 25 ◽  
Author(s):  
Scott Chambers ◽  
Elise-Andree Guérette ◽  
Khalia Monk ◽  
Alan Griffiths ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Potential Health ◽  
Meteorological Model ◽  
Model Skill ◽  
Chemical Transport Models

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

scholarly journals Sensitivity of chemical transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

2015 ◽  
Vol 8 (11) ◽  
pp. 9589-9616
Author(s):  
S. Philip ◽  
R. V. Martin ◽  
C. A. Keller
Keyword(s):  
Spatial Resolution ◽  
Temporal Resolution ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Simulation Accuracy ◽  
Chemical Transport Models ◽  
Order Of Magnitude ◽  
Simulation Error

Abstract. Chemical transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemical transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to temporal resolution. Subsequently, we compare the tracers simulated with operator durations from 10 to 60 min as typically used by global chemical transport models, and identify the timesteps that optimize both computational expense and simulation accuracy. We found that longer transport timesteps increase concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production at longer transport timesteps. Longer chemical timesteps decrease sulfate and ammonium but increase nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by an order of magnitude from fine (5 min) to coarse (60 min) temporal resolution. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, ozone, carbon monoxide and secondary inorganic aerosols with a finer temporal or spatial resolution taken as truth. Simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) temporal resolution. Chemical timesteps twice that of the transport timestep offer more simulation accuracy per unit computation. However, simulation error from coarser spatial resolution generally exceeds that from longer timesteps; e.g. degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different temporal resolutions in offline chemical transport models. We encourage the chemical transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

scholarly journals Data Assimilation as a Tool to Improve Chemical Transport Models Performance in Developing Countries

2021 ◽  
Author(s):  
Santiago Lopez-Restrepo ◽  
Andrés Yarce Botero ◽  
Olga Lucia Quintero ◽  
Nicolás Pinel ◽  
Jhon Edinson Hinestroza ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Data Assimilation ◽  
Transport Model ◽  
Population Expansion ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Tropical Andes ◽  
Urban Centers ◽  
Transport Models ◽  
Chemical Transport Models

Particulate matter (PM) is one of the most problematic pollutants in urban air. The effects of PM on human health, associated especially with PM of ≤2.5μm in diameter, include asthma, lung cancer and cardiovascular disease. Consequently, major urban centers commonly monitor PM2.5 as part of their air quality management strategies. The Chemical Transport models allow for a permanent monitoring and prediction of pollutant behavior for all the regions of interest, different to the sensor network where the concentration is just available in specific points. In this chapter a data assimilation system for the LOTOS-EUROS chemical transport model has been implemented to improve the simulation and forecast of Particulate Matter in a densely populated urban valley of the tropical Andes. The Aburrá Valley in Colombia was used as a case study, given data availability and current environmental issues related to population expansion. Using different experiments and observations sources, we shown how the Data Assimilation can improve the model representation of pollutants.

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