Implementing the Decoupled Direct Method for Sensitivity Analysis in a Particulate Matter Air Quality Model

2007 ◽  
Vol 41 (8) ◽  
pp. 2847-2854 ◽  
Author(s):  
Bonyoung Koo ◽  
Alan M. Dunker ◽  
Greg Yarwood
Keyword(s):  
Sensitivity Analysis ◽  
Particulate Matter ◽  
Air Quality ◽  
Direct Method ◽  
Air Quality Model ◽  
Quality Model

Comparison of Source Apportionment and Sensitivity Analysis in a Particulate Matter Air Quality Model

2009 ◽  
Vol 43 (17) ◽  
pp. 6669-6675 ◽  
Author(s):  
Bonyoung Koo ◽  
Gary M. Wilson ◽  
Ralph E. Morris ◽  
Alan M. Dunker ◽  
Greg Yarwood
Keyword(s):  
Sensitivity Analysis ◽  
Particulate Matter ◽  
Air Quality ◽  
Source Apportionment ◽  
Air Quality Model ◽  
Quality Model

scholarly journals Effect of the uncertainty in meteorology on air quality model predictions

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 625-646
Author(s):  
Zita Ferenczi ◽  
Emese Homolya ◽  
Krisztina Lázár ◽  
Anita Tóth
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Model System ◽  
Air Quality Model ◽  
Quality Model ◽  
Near Surface ◽  
The Impact

An operational air quality forecasting model system has been developed and provides daily forecasts of ozone, nitrogen oxides, and particulate matter for the area of Hungary and three big cites of the country (Budapest, Miskolc, and Pécs). The core of the model system is the CHIMERE off-line chemical transport model. The AROME numerical weather prediction model provides the gridded meteorological inputs for the chemical model calculations. The horizontal resolution of the AROME meteorological fields is consistent with the CHIMERE horizontal resolution. The individual forecasted concentrations for the following 2 days are displayed on a public website of the Hungarian Meteorological Service. It is essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input meteorological fields. The main aim of this research is to probe the response of an air quality model to its uncertain meteorological inputs. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. During the past decades, meteorological ensemble modeling has received extensive research and operational interest because of its ability to better characterize forecast uncertainty. One such ensemble forecast system is the one of the AROME model, which has an 11-member ensemble where each member is perturbed by initial and lateral boundary conditions. In this work we focus on wintertime particulate matter concentrations, since this pollutant is extremely sensitive to near-surface mixing processes. Selecting a number of extreme air pollution situations we will show what the impact of the meteorological uncertainty is on the simulated concentration fields using AROME ensemble members.

scholarly journals Development of the high-order decoupled direct method in three dimensions for particulate matter: enabling advanced sensitivity analysis in air quality models

2012 ◽  
Vol 5 (2) ◽  
pp. 355-368 ◽  
Author(s):  
W. Zhang ◽  
S. L. Capps ◽  
Y. Hu ◽  
A. Nenes ◽  
S. L. Napelenok ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Particulate Matter ◽  
Air Quality ◽  
Direct Method ◽  
Statistical Significance ◽  
Second Order ◽  
High Order ◽  
Three Dimensions ◽  
So2 Emissions ◽  
Aerosol Module

Abstract. The high-order decoupled direct method in three dimensions for particulate matter (HDDM-3D/PM) has been implemented in the Community Multiscale Air Quality (CMAQ) model to enable advanced sensitivity analysis. The major effort of this work is to develop high-order DDM sensitivity analysis of ISORROPIA, the inorganic aerosol module of CMAQ. A case-specific approach has been applied, and the sensitivities of activity coefficients and water content are explicitly computed. Stand-alone tests are performed for ISORROPIA by comparing the sensitivities (first- and second-order) computed by HDDM and the brute force (BF) approximations. Similar comparison has also been carried out for CMAQ sensitivities simulated using a week-long winter episode for a continental US domain. Second-order sensitivities of aerosol species (e.g., sulfate, nitrate, and ammonium) with respect to domain-wide SO2, NOx, and NH3 emissions show agreement with BF results, yet exhibit less noise in locations where BF results are demonstrably inaccurate. Second-order sensitivity analysis elucidates poorly understood nonlinear responses of secondary inorganic aerosols to their precursors and competing species. Adding second-order sensitivity terms to the Taylor series projection of the nitrate concentrations with a 50% reduction in domain-wide NOx or SO2 emissions rates improves the prediction with statistical significance.

Uncertainty in air quality model evaluation for particulate matter due to spatial variations in pollutant concentrations

2006 ◽  
Vol 40 ◽  
pp. 563-573 ◽  
Author(s):  
Sun-Kyoung Park ◽  
Charles Evan Cobb ◽  
Katherine Wade ◽  
James Mulholland ◽  
Yongtao Hu ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Model Evaluation ◽  
Spatial Variations ◽  
Air Quality Model ◽  
Quality Model ◽  
Pollutant Concentrations
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