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 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 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 Systematic bias in evaluating chemical transport models with maximum daily 8 h average (MDA8) surface ozone for air quality applications: a case study with GEOS-Chem v9.02

2019 ◽  
Vol 12 (8) ◽  
pp. 3641-3648 ◽  
Author(s):  
Katherine R. Travis ◽  
Daniel J. Jacob
Keyword(s):  
Air Quality ◽  
Mixed Layer ◽  
Diurnal Cycle ◽  
Surface Ozone ◽  
Chemical Transport ◽  
Systematic Bias ◽  
Transport Models ◽  
Ozone Deposition ◽  
Chemical Transport Models

Abstract. Chemical transport models frequently evaluate their simulation of surface ozone with observations of the maximum daily 8 h average (MDA8) concentration, which is the standard air quality policy metric. This requires successful simulation of the surface ozone diurnal cycle including nighttime depletion, but models often have difficulty simulating this diurnal cycle for a number of reasons, including (1) vertical grid structure in the surface layer, (2) timing of changes in mixed layer dynamics and ozone deposition velocity across the day–night transition, (3) poor representation of nighttime stratification, and (4) uncertainties in ozone nighttime deposition. We analyze the problem with the GEOS-Chem model, taking as a representative case study the Southeast US during the NASA SEAC4RS aircraft campaign in August–September 2013. The model is unbiased relative to the daytime mixed layer aircraft observations but has a mean +8 ppb bias at its lowest level (65 m) relative to MDA8 surface ozone observations. The bias can be corrected to +5 ppb by implicit sampling of the model at the 10 m altitude of the surface observations. The model does not capture frequent observed occurrences of <20 ppb MDA8 surface ozone on rainy days, possibly because of enhanced ozone deposition to wet surfaces that is unaccounted for. Restricting the surface ozone evaluation to dry days still shows inconsistencies with MDA8 ozone because of model errors in the ozone diurnal cycle. Restricting the evaluation to afternoon ozone completely removes the bias. We conclude that better representation of diurnal variations in mixed layer dynamics and ozone deposition velocities is needed in models to properly describe the diurnal cycle of ozone.

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 Systematic bias in evaluating chemical transport models with maximum daily 8-hour average (MDA8) surface ozone for air quality applications

2019 ◽  
Author(s):  
Katherine R. Travis ◽  
Daniel J. Jacob
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Surface Ozone ◽  
Chemical Transport ◽  
Systematic Bias ◽  
Transport Models ◽  
Chemical Transport Models ◽  
Aircraft Observations ◽  
Southeast Us ◽  
Quality Policy

Abstract. Chemical transport models typically evaluate their simulation of surface ozone with observations of the maximum daily 8-hour average (MDA8) concentration, which is the standard air quality policy metric. This requires successful simulation of the surface ozone diurnal cycle including nighttime depletion, but models are generally biased high at night because of difficulty in resolving the stratified conditions near the surface. We quantify the problem with the GEOS-Chem model for the Southeast US during the NASA SEAC4RS aircraft campaign in August–September 2013. The model is unbiased relative to the daytime mixed layer aircraft observations but has a +5 ppb bias relative to MDA8 surface ozone observations. The model also does not capture observed occurrences of

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.

Air quality forecasting system based on chemical transport models

2019 ◽  
Vol 4 ◽  
pp. 203-218
Author(s):  
I.N. Kusnetsova ◽  
◽  
I.U. Shalygina ◽  
M.I. Nahaev ◽  
U.V. Tkacheva ◽  
...  
Keyword(s):  
Air Quality ◽  
Chemical Transport ◽  
Transport Models ◽  
Chemical Transport Models ◽  
Forecasting System ◽  
Air Quality Forecasting

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.

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