Development and application of the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID)

Zhang, Yang

doi:10.1029/2003jd003501

Cited by 207 publications

(198 citation statements)

References 84 publications

(199 reference statements)

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“…Concerning the sensitivity to the aerosol module, only the sensitivity to the size distribution (number of sections) and the sensitivity to physical parameterizations (coagulation, whether condensation is solved assuming full equilibrium or using an hybrid scheme, cloud chemistry, heterogeneous reactions, and sea-salt emissions) are considered. However, there is also a sensitivity to numerical algorithms for simulation of condensation/evaporation for example as shown by Zhang et al (2004).…”

Section: Resultsmentioning

confidence: 99%

MICS Asia Phase II—Sensitivity to the aerosol module

Sartelet

Hayami

Sportisse

2008

Atmospheric Environment

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In the framework of the model inter-comparison study -Asia Phase II (MICS2), where eight models are compared over East Asia, this paper studies the influence of different parameterizations used in the aerosol module on the aerosol concentrations of sulfate and nitrate in PM 10 .An intracomparison of aerosol concentrations is done for March 2001 using different configurations of the aerosol module of one of the model used for the intercomparison. Single modifications of a reference setup for model configurations are performed and compared to a reference case. These modifications concern the size distribution, i.e. the number of sections, and physical processes, i.e. coagulation, condensation/evaporation, cloud chemistry, heterogeneous reactions and sea-salt emissions.Comparing monthly averaged concentrations at different stations, the importance of each parameterization is first assessed. It is found that sulfate concentrations are little sensitive to sea-salt emissions and to whether condensation is computed dynamically or by assuming thermodynamic equilibrium. Nitrate concentrations are little sensitive to cloud chemistry. However, a very high sensitivity to heterogeneous reactions is observed.Thereafter, the variability of the aerosol concentrations to the use of different chemistry transport models (CTMs) and the variability to the use of different parameterizations in the aerosol module are compared. For sulfate, the variability to the use of different parameterizations in the aerosol module is lower than the variability to the use of different CTMs. However, for nitrate, for monthly averaged concentrations averaged over four stations, these two variabilities have the same order of magnitude.

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Section: Resultsmentioning

confidence: 99%

MICS Asia Phase II—Sensitivity to the aerosol module

Sartelet

Hayami

Sportisse

2008

Atmospheric Environment

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“…MCA uses fixed boundaries and M 0 and M 3 are fully transferred to neighboring bins when the diameter D = (M 3 /M 0 ) 1/3 exceeds the boundaries, whereas LDM assumes that the intrasectional size distribution is linear in particle volume. The DMS-MCA methods are documented in detail in Jacobson [1997] and Zhang et al [2004] and the DMS-LDM in Simmel and Wurzler [2006].…”

Section: Simulation Settings and Definitions Of Termsmentioning

confidence: 99%

“…Methods I-III all use harmonic mean interpolation for coagulation and condensation rates. Method II (DMS-MCA-HM) employs the moving-center approach [Jacobson, 1997;Zhang et al, 2004] for condensational growth calculation, whereas Method III (DMS-LDM-HM) uses the linear discrete method (LDM) [Simmel and Wurzler, 2006;Zaveri et al, 2008] for condensational growth. MCA is employed for coagulation by the both Methods II and III.…”

Section: Simulation Settings and Definitions Of Termsmentioning

confidence: 99%

“…[51] MBHM uses the fixed bin boundary structure and the moving-center approach (MCA) [Jacobson, 1997], which is accurate and produces less numerical diffusion than other methods such as stationary bin structure (fixed volume in each bin), semi-Lagrangian, or Lagrangian techniques in condensational and coagulation growth simulations [Jacobson, 1997;Zhang et al, 2004]. In MBHM, when the number equivalent geometric mean diameter D g,i of bin i becomes larger or smaller than the boundary diameters D up,i or D lw,i , all three moments in the bin are transferred to the next bins i + 1 or i À 1.…”

Section: Computational Efficiency and Low Numerical Diffusionmentioning

confidence: 99%

“…[39] DMS methods are widely used for aerosol dynamics calculations in global-and regional-scale chemical transport models, which explicitly treat aerosol chemical, thermodynamical, and microphysical processes [e.g., Jacobson, 1997;Zhang et al, 2004;Zaveri et al, 2008]. While aerosol number and mass concentrations are preserved in DMS, surface area is not always preserved: When two groups of aerosols with different diameters (D i1 and D i2 ) meet in the same bin i after a dynamical process (condensation and coagulation) or transport (advection or diffusion) in a 3-D simulation, the moments of merged aerosols (D i ) in the bin of DMS will be…”

Section: Consistency In Aerosol Surface Area Modelingmentioning

confidence: 99%

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Modal Bin Hybrid Model: A surface area consistent, triple‐moment sectional method for use in process‐oriented modeling of atmospheric aerosols

2013

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[1] A triple-moment sectional (TMS) aerosol dynamics model, Modal Bin Hybrid Model (MBHM), has been developed. In addition to number and mass (volume), surface area is predicted (and preserved), which is important for aerosol processes and properties such as gas-to-particle mass transfer, heterogeneous reaction, and light extinction cross section. The performance of MBHM was evaluated against double-moment sectional (DMS) models with coarse (BIN4) to very fine (BIN256) size resolutions for simulating evolution of particles under simultaneously occurring nucleation, condensation, and coagulation processes (BINx resolution uses x sections to cover the 1 nm to 1 μm size range). Because MBHM gives a physically consistent form of the intrasectional distributions, errors and biases of MBHM at BIN4-8 resolution were almost equivalent to those of DMS at BIN16-32 resolution for various important variables such as the moments M k (k: 0, 2, 3), dM k /dt, and the number and volume of particles larger than a certain diameter. Another important feature of MBHM is that only a single bin is adequate to simulate full aerosol dynamics for particles whose size distribution can be approximated by a single lognormal mode. This flexibility is useful for process-oriented (multicategory and/or mixing state) modeling: Primary aerosols whose size parameters would not differ substantially in time and space can be expressed by a single or a small number of modes, whereas secondary aerosols whose size changes drastically from 1 to several hundred nanometers can be expressed by a number of modes. Added dimensions can be applied to MBHM to represent mixing state or photochemical age for aerosol mixing state studies.Citation: Kajino, M., R. C. Easter, and S. J. Ghan (2013), Modal Bin Hybrid Model: A surface area consistent, triplemoment sectional method for use in process-oriented modeling of atmospheric aerosols,

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Secondary organic aerosol model intercomparison based on secondary organic aerosol to odd oxygen ratio in Tokyo

et al. 2014

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Improvement of secondary organic aerosol (SOA) models is critical for accurate understanding of the behavior and sources of atmospheric aerosols. Over the last decade, a number of SOA production pathways were discovered, and several new SOA models have been developed. However, few comparative studies of the performances of the various SOA models have been conducted. In this study, simulation data obtained with five SOA models (two yield models, a volatility basis set (VBS) model, a mechanistic model, and a near-explicit model) were compared. The performances of the models were evaluated by comparison of the simulated data with observed ratios of the SOA concentration to odd oxygen concentration) in the Tokyo metropolitan area. In Tokyo, SOA concentrations have been shown to correlate well with O x concentrations; thus, Tokyo is an appropriate location for this intercomparison study. All five models showed similar results for the concentrations of gaseous species, including ozone, reactive nitrogen, hydroxy radicals, and volatile organic compounds. In contrast, the simulated SOA concentrations varied substantially among the five models. The VBS model reproduced the observed [SOA]/[O x ] ratio well, whereas the other four models substantially underestimated the ratio. The sensitivity of the ratio to various input parameters differed substantially among the models, as did the volatility distribution of SOA and the source contributions of SOA, suggesting that the choice of SOA model is critical for accurate assessment of the atmospheric behavior and sources of SOA.

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Development and application of the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID)

Cited by 207 publications

References 84 publications

MICS Asia Phase II—Sensitivity to the aerosol module

MICS Asia Phase II—Sensitivity to the aerosol module

Modal Bin Hybrid Model: A surface area consistent, triple‐moment sectional method for use in process‐oriented modeling of atmospheric aerosols

Secondary organic aerosol model intercomparison based on secondary organic aerosol to odd oxygen ratio in Tokyo

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