The Impact of Nudging in the Meteorological Model for Retrospective Air Quality Simulations. Part I: Evaluation against National Observation Networks

2008 ◽  
Vol 47 (7) ◽  
pp. 1853-1867 ◽  
Author(s):  
Tanya L. Otte
Keyword(s):  
Air Quality ◽  
Meteorological Conditions ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
Meteorological Model ◽  
Model Simulations ◽  
Dynamic Analyses ◽  
The Impact ◽  
Over Time

Abstract It is common practice to use Newtonian relaxation, or nudging, throughout meteorological model simulations to create “dynamic analyses” that provide the characterization of the meteorological conditions for retrospective air quality model simulations. Given the impact that meteorological conditions have on air quality simulations, it has been assumed that the resultant air quality simulations would be more skillful by using dynamic analyses rather than meteorological forecasts to characterize the meteorological conditions, and that the statistical trends in the meteorological model fields are also reflected in the air quality model. This article, which is the first of two parts, demonstrates the impact of nudging in the meteorological model on retrospective air quality model simulations. Here, meteorological simulations are generated by the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) using both the traditional dynamic analysis approach and using forecasts for a summertime period. The resultant fields are then used to characterize the meteorological conditions for emissions processing and air quality simulations using the Community Multiscale Air Quality (CMAQ) Modeling System. As expected, on average, the near-surface meteorological fields show a significant degradation over time in the forecasts (when nudging is not used), while the dynamic analyses maintain nearly constant statistical scores in time. The use of nudged MM5 fields in CMAQ generally results in better skill scores for daily maximum 1-h ozone mixing ratio simulations. On average, the skill of the daily maximum 1-h ozone simulation deteriorates significantly over time when nonnudged MM5 fields are used in CMAQ. The daily maximum 1-h ozone mixing ratio also degrades over time in the CMAQ simulation that uses MM5 dynamic analyses, although to a much lesser degree, despite no aggregate loss of skill over time in the dynamic analyses themselves. These results affirm the advantage of using nudging in MM5 to create the meteorological characterization for CMAQ for retrospective simulations, and it is shown that MM5-based dynamic analyses are robust at the surface throughout 5.5-day simulations.

A procedure for inter-comparing the skill of regional-scale air quality model simulations of daily maximum 8-h ozone concentrations

2008 ◽  
Vol 42 (21) ◽  
pp. 5403-5412 ◽  
Author(s):  
John S. Irwin ◽  
Kevin Civerolo ◽  
Christian Hogrefe ◽  
Wyat Appel ◽  
Kristen Foley ◽  
...  
Keyword(s):  
Air Quality ◽  
Regional Scale ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
Model Simulations ◽  
Ozone Concentrations

scholarly journals Modeling the impact of chlorine emissions from coal combustion and prescribed waste incineration on tropospheric ozone formation in China

2017 ◽  
Author(s):  
Yiming Liu ◽  
Qi Fan ◽  
Xiaoyang Chen ◽  
Jun Zhao ◽  
Zhenhao Ling ◽  
...  
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Coal Combustion ◽  
Waste Incineration ◽  
Daily Maximum ◽  
Ozone Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Chlorine Radicals ◽  
The Impact

Abstract. Chlorine radicals can enhance atmospheric oxidation which potentially increase tropospheric ozone concentration. However, few studies have been done to quantify the impact of chlorine emissions on ozone formation in China due to lack of chlorine emission inventory used in air quality model with sufficient resolution. In this study, Anthropogenic Chlorine Emissions Inventory for China (ACEIC) was developed for the first time, including emissions of hydrogen chloride (HCl) and molecular chlorine (Cl2) from coal combustion and prescribed waste incineration (waste incineration plant). The HCl and Cl2 emissions from coal combustion in China in 2012 were estimated to be 232.9 and 9.4 Gg, respectively, while HCl emission from prescribed waste incineration was estimated to be 2.9 Gg. Spatially high chlorine emissions were found in the North China Plain, the Yangtze River Delta and the Sichuan Basin. Air quality model simulations with the Community Multiscale Air Quality (CMAQ) modeling system were performed for November 2011 and the modeling results derived with and without chlorine emissions were compared. The magnitude of the simulated HCl, Cl2 and ClNO2 agreed reasonably with the observation when anthropogenic chlorine emissions were included in the model. The inclusion of the ACEIC increased the concentration of fine particulate Cl−, leading to enhanced heterogeneous reactions between Cl− and N2O5 which resulted in the higher production of ClNO2. Photolysis of ClNO2 and Cl2 in the morning and the reaction of HCl with OH in the afternoon produced chlorine radicals which accelerated tropospheric oxidation. When anthropogenic chlorine emissions were included in the model, the monthly mean concentrations of fine particulate Cl−, daily maximum 1-h ClNO2 and Cl radicals were estimated to increase by up to about 2.0 μg m−3, 773 pptv and 1.5 × 103 molecule cm−3 in China, respectively. Meanwhile, the monthly mean daily maximum 1-h O3 concentration was found to increase by up to 2.2 ppbv (3.8 %), while the monthly mean NOx concentration decreased by up to 0.5 ppbv (6.1 %). The anthropogenic chlorine emissions potentially increased the 1-h O3 concentration by up to 7.7 ppbv in China. This study highlights the need for the inclusion of anthropogenic chlorine emission on air quality modeling and demonstrated its importance on tropospheric ozone formation.

scholarly journals Impact of a new condensed toluene mechanism on air quality model predictions in the US

2010 ◽  
Vol 3 (4) ◽  
pp. 2291-2314
Author(s):  
G. Sarwar ◽  
K. W. Appel ◽  
A. G. Carlton ◽  
R. Mathur ◽  
K. Schere ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Production Efficiency ◽  
Sensitivity Study ◽  
Chemical Mechanism ◽  
Ozone Production ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
Mixing Ratios

Abstract. A new condensed toluene mechanism is incorporated into the Community Multiscale Air Quality Modeling system. Model simulations are performed using the CB05 chemical mechanism containing the existing (base) and the new toluene mechanism for the western and eastern US for a summer month. With current estimates of tropospheric emission burden, the new toluene mechanism increases monthly mean daily maximum 8-h ozone by 1.0–3.0 ppbv in Los Angeles, Portland, Seattle, Chicago, Cleveland, northeastern US, and Detroit compared to that with the base toluene chemistry. It reduces model mean bias for ozone at elevated observed ozone mixing ratios. While the new mechanism increases predicted ozone, it does not enhance ozone production efficiency. Sensitivity study suggests that it can further enhance ozone if elevated toluene emissions are present. While changes in total fine particulate mass are small, predictions of in-cloud SOA increase substantially.

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.

The Impact of Nudging in the Meteorological Model for Retrospective Air Quality Simulations. Part II: Evaluating Collocated Meteorological and Air Quality Observations

2008 ◽  
Vol 47 (7) ◽  
pp. 1868-1887 ◽  
Author(s):  
Tanya L. Otte
Keyword(s):  
Air Quality ◽  
Dynamic Analysis ◽  
Air Quality Modeling ◽  
Shortwave Radiation ◽  
Error Patterns ◽  
Ozone Prediction ◽  
Quality Modeling ◽  
Dynamic Analyses ◽  
The Impact ◽  
Over Time

Abstract For air quality modeling, it is important that the meteorological fields that are derived from meteorological models reflect the best characterization of the atmosphere. It is well known that the accuracy and overall representation of the modeled meteorological fields can be improved for retrospective simulations by creating dynamic analyses in which Newtonian relaxation, or “nudging,” is used throughout the simulation period. This article, the second of two parts, provides additional insight into the value of using nudging-based data assimilation for dynamic analysis in the meteorological fields for air quality modeling. Meteorological simulations are generated by the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) using both the traditional dynamic analysis approach and forecasts for a summertime period. The resultant meteorological fields are then used for emissions processing and air quality simulations using the Community Multiscale Air Quality Modeling System (CMAQ). The predictions of surface and near-surface meteorological fields and ozone are compared with a small network of collocated meteorological and air quality observations. Comparisons of 2-m temperature, 10-m wind speed, and surface shortwave radiation show a significant degradation over time when nudging is not used, whereas the dynamic analyses maintain consistent statistical scores over time for those fields. Using nudging in MM5 to generate dynamic analyses, on average, leads to a CMAQ simulation of hourly ozone with smaller error. Domainwide error patterns in specific meteorological fields do not directly or systematically translate into error patterns in ozone prediction at these sites, regardless of whether nudging is used in MM5, but large broad-scale errors in shortwave radiation prediction by MM5 directly affect ozone prediction by CMAQ at specific sites.

scholarly journals Impact of a new condensed toluene mechanism on air quality model predictions in the US

2011 ◽  
Vol 4 (1) ◽  
pp. 183-193 ◽  
Author(s):  
G. Sarwar ◽  
K. W. Appel ◽  
A. G. Carlton ◽  
R. Mathur ◽  
K. Schere ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Production Efficiency ◽  
Sensitivity Study ◽  
Chemical Mechanism ◽  
Ozone Production ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
The Us

Abstract. A new condensed toluene mechanism is incorporated into the Community Multiscale Air Quality Modeling system. Model simulations are performed using the CB05 chemical mechanism containing the existing (base) and the new toluene mechanism for the western and eastern US for a summer month. With current estimates of tropospheric emission burden, the new toluene mechanism increases monthly mean daily maximum 8-h ozone by 1.0–3.0 ppbv in Los Angeles, Portland, Seattle, Chicago, Cleveland, northeastern US, and Detroit compared to that with the base toluene chemistry. It reduces model mean bias for ozone at elevated observed ozone concentrations. While the new mechanism increases predicted ozone, it does not enhance ozone production efficiency. A sensitivity study suggests that it can further enhance ozone if elevated toluene emissions are present. While it increases in-cloud secondary organic aerosol substantially, its impact on total fine particle mass concentration is small.

Downscaling EDGAR emissions to local emission sectors for Switzerland

2021 ◽  
Author(s):  
Jacinta Edebeli ◽  
Curdin Spirig ◽  
Julien Anet
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Measurement Data ◽  
Pilot Project ◽  
Air Quality Model ◽  
Quality Model ◽  
Emission Data ◽  
Traffic Pattern ◽  
Pollutant Concentrations ◽  
The Impact

<p>The fifth version of the Emission Database for Global Atmospheric Research (EDGAR 5.0) provides an impressive inventory of various pollutants. Pollutants from different emission sectors are available with daily, monthly and yearly temporal profiles at a high global resolution of 0.1°×0.1°. Although this resolution has been sufficient for regional air quality studies, the emissions appeared to be too coarse for local air quality studies in areas with complex topography. With Switzerland as a case study, we present our approach for downscaling EDGAR emission data to a much finer resolution of 0.02°×0.02° with the aim of modelling local air quality.</p><p>We downscaled the EDGAR emissions using a combination of GIS tools including QGIS, ArcGIS, and a series of python scripts. We obtained the surface coverage of different land use features within the defined EDGAR emission sectors from Open Street Map (OSM) using the <em>QuickOSM</em> tool in QGIS. With the calculated local surface area coverage of the emissions sectors, we downscaled the EDGAR inventory data within ArcGIS using a set of developed Arcpy script tools.</p><p>The outcome was a much finer resolved emission dataset which we fed into the WRF-CHEM air quality model within a pilot project. A comparison of the modelled pollutant concentrations using the two datasets (original EDGAR data and the downscaled data) shows an improved agreement between the downscaled dataset and the measurement data.</p><p>Studies investigating the impact of urbanization, land use change or traffic pattern on air quality may benefit from our downscaling solution, which, thanks to the global coverage of OSM, can be globally applied.</p>

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