Nothing Special   »   [go: up one dir, main page]

Mathur et al., 2005 - Google Patents

Multiscale Air Quality Simulation Platform (MAQSIP): Initial applications and performance for tropospheric ozone and particulate matter

Mathur et al., 2005

View PDF @Full View
Document ID
10155515823530485895
Author
Mathur R
Shankar U
Hanna A
Odman M
McHenry J
Coats Jr C
Alapaty K
Xiu A
Arunachalam S
Olerud Jr D
Byun D
Schere K
Binkowski F
Ching J
Dennis R
Pierce T
Pleim J
Roselle S
Young J
Publication year
Publication venue
Journal of Geophysical Research: Atmospheres

External Links

Snippet

The performance of the Multiscale Air Quality Simulation Platform (MAQSIP) in simulating the regional distributions of tropospheric ozone and particulate matter (PM) is evaluated through comparisons of model results from three‐dimensional simulations against available …
Continue reading at agupubs.onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063—Operations research or analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0073—Control unit therefor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/26—Investigating or analysing materials by specific methods not covered by the preceding groups oils; viscous liquids; paints; inks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N1/00—Sampling; Preparing specimens for investigation
    • G01N1/02—Devices for withdrawing samples
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01W—METEOROLOGY
    • G01W1/00—Meteorology
    • G01W1/10—Devices for predicting weather conditions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"

Similar Documents

Publication Publication Date Title
Wang et al. Mesoscale modeling of Central American smoke transport to the United States: 1.“Top‐down” assessment of emission strength and diurnal variation impacts
Park et al. Natural and transboundary pollution influences on sulfate‐nitrate‐ammonium aerosols in the United States: Implications for policy
Pye et al. Effect of changes in climate and emissions on future sulfate‐nitrate‐ammonium aerosol levels in the United States
Riemer et al. Impact of the heterogeneous hydrolysis of N2O5 on chemistry and nitrate aerosol formation in the lower troposphere under photosmog conditions
Reddy et al. Estimates of global multicomponent aerosol optical depth and direct radiative perturbation in the Laboratoire de Météorologie Dynamique general circulation model
Tang et al. Impacts of aerosols and clouds on photolysis frequencies and photochemistry during TRACE‐P: 2. Three‐dimensional study using a regional chemical transport model
Bertschi et al. Long‐range transport of ozone, carbon monoxide, and aerosols to the NE Pacific troposphere during the summer of 2003: Observations of smoke plumes from Asian boreal fires
Lin et al. Global model simulation of summertime US ozone diurnal cycle and its sensitivity to PBL mixing, spatial resolution, and emissions
Yu et al. An assessment of the ability of three‐dimensional air quality models with current thermodynamic equilibrium models to predict aerosol NO3−
El-Harbawi Air quality modelling, simulation, and computational methods: a review
Yu et al. Evaluation of real‐time PM2. 5 forecasts and process analysis for PM2. 5 formation over the eastern United States using the Eta‐CMAQ forecast model during the 2004 ICARTT study
Brioude et al. Top‐down estimate of anthropogenic emission inventories and their interannual variability in Houston using a mesoscale inverse modeling technique
Sillman et al. Reactive mercury in the troposphere: Model formation and results for Florida, the northeastern United States, and the Atlantic Ocean
Riemer et al. Modeling aerosols on the mesoscale‐γ: Treatment of soot aerosol and its radiative effects
Chameides et al. Correlation between model‐calculated anthropogenic aerosols and satellite‐derived cloud optical depths: Indication of indirect effect?
Karydis et al. Evaluation of a three‐dimensional chemical transport model (PMCAMx) in the eastern United States for all four seasons
Liu et al. Uncertainties in global aerosol simulations: Assessment using three meteorological data sets
Zhang et al. Probing into regional ozone and particulate matter pollution in the United States: 1. A 1 year CMAQ simulation and evaluation using surface and satellite data
Kelly et al. Fine‐scale simulation of ammonium and nitrate over the South Coast Air Basin and San Joaquin Valley of California during CalNex‐2010
Tao et al. A summer simulation of biogenic contributions to ground‐level ozone over the continental United States
Mathur et al. Assessment of the wintertime performance of developmental particulate matter forecasts with the Eta‐Community Multiscale Air Quality modeling system
Jiang et al. Modeling the effects of VOC and NOx emission sources on ozone formation in Houston during the TexAQS 2000 field campaign
Tang et al. Effects of fire diurnal variation and plume rise on US air quality during FIREX‐AQ and WE‐CAN based on the Multi‐Scale Infrastructure for Chemistry and Aerosols (MUSICAv0)
Ukhov et al. Study of SO 2 Pollution in the Middle East Using MERRA‐2, CAMS Data Assimilation Products, and High‐Resolution WRF‐Chem Simulations
Staudt et al. Sources and chemistry of nitrogen oxides over the tropical Pacific