Simulation Of Particulate Matter Distribution Over Iowa

Bulletin of The American Meteorological Society, 2004

2013

In order to better understand the characteristics of dust storm processes over the western United States, available dust storm events reported by media or recorded by NASA earth observatory are classified into four types based on the prevailing weather systems. Then these four types of dust storm events related to cold fronts, downbursts, tropical disturbances, and cyclogenesis and their selected typical representative events are examined to explore their identifiable characteristics based on in-situ and remote sensing measurements. We find that the key feature of cold front-induced dust storms is their rapid process with strong dust emissions. Events caused by rapid downbursts have the highest rates of emissions. Dust storms due to tropical disturbances show stronger air concentrations of dust and last longer than those caused by cold fronts and downbursts. Finally, dust storms caused by cyclogenesis last the longest. The analysis of particulate matter records also shows that the relative ratio of PM 10 (size less than 10 µm) values on dust storm-days to non-dust storm-days is a better indicator of event identification compared to previous established indicators. Moreover, aerosol optical depth (AOD) measurements from both in-situ and satellite datasets allow us to capture dust storm processes. We show that MODIS AOD retrieved from the deep blue data better identify dust storm-affected areas and the spatial extension of event intensity. Our analyses also show that the variability in mass concentrations during dust storm processes captured only by in-situ observations is consistent with the variability in AOD from stationary or satellite observations. The study finally indicates that the combination of in-situ and satellite observations is a better method to fill gaps in dust storm recordings.

Atmospheric Environment, 2010

Comparisons were made between three sets of meteorological fields used to support air quality predictions for the California Regional Particulate Air Quality Study (CRPAQS) winter episode from December 15, 2000 to January 6, 2001. The first set of fields was interpolated from observations using an objective analysis method. The second set of fields was generated using the WRF prognostic model without data assimilation. The third set of fields was generated using the WRF prognostic model with the fourdimensional data assimilation (FDDA) technique. The UCD/CIT air quality model was applied with each set of meteorological fields to predict the concentrations of airborne particulate matter and gaseous species in central California. The results show that the WRF model without data assimilation over-predicts surface wind speed by w30% on average and consequently yields under-predictions for all PM and gaseous species except sulfate (S(VI)) and ozone(O 3 ). The WRF model with FDDA improves the agreement between predicted and observed wind and temperature values and consequently yields improved predictions for all PM and gaseous species. Overall, diagnostic meteorological fields produced more accurate air quality predictions than either version of the WRF prognostic fields during this episode. Population-weighted average PM 2.5 exposure is 40% higher using diagnostic meteorological fields compared to prognostic meteorological fields created without data assimilation. These results suggest diagnostic meteorological fields based on a dense measurement network are the preferred choice for air quality model studies during stagnant periods in locations with complex topography.

Fourth Symposium on …, 2009

Fourth Symposium on Policy and Socio—Economic Research Symposium on Urban High Impact Weather Special Symposium on Measurements in the Urban Environment and Observations Eighth Conference on Coastal Atmospheric and Oceanic Prediction and Processes ...

1991

Journal of Applied Meteorology and Climatology, 2011

A radar-based climatology of 91 unique summertime (May 2000–August 2009) thunderstorm cases was examined over the Indianapolis, Indiana, urban area. The study hypothesis is that urban regions alter the intensity and composition/structure of approaching thunderstorms because of land surface heterogeneity. Storm characteristics were studied over the Indianapolis region and four peripheral rural counties approximately 120 km away from the urban center. Using radar imagery, the time of event, changes in storm structure (splitting, initiation, intensification, and dissipation), synoptic setting, orientation, and motion were studied. It was found that more than 60% of storms changed structure over the Indianapolis area as compared with only 25% over the rural regions. Furthermore, daytime convection was most likely to be affected, with 71% of storms changing structure as compared with only 42% at night. Analysis of radar imagery indicated that storms split closer to the upwind urban regio...

2012

Wind erosion is a dynamic physical process that leads to environmental degradation when strong winds blow on loose, dry, bare soils, creating dust events that can impact human health, visibility and air quality. Since 1932, more than two thousand dust event days were recorded at El Paso, averaging 25 per year. This research analyzes and models data on dust events in the El Paso/Juarez metropolitan area for better understanding of their effects. The meteorological characteristics of these events are analyzed for variables such as the frequency, visibility, and average wind speeds associated with convective and nonconvective events. These variables are further correlated with other parameters including particulate matter concentrations, relative humidity and associated precipitation to determine their relationships. Air transport pathways into El Paso during days with dust events (classified as convective and nonconvective in nature), as well as days in which dust was not reported, were created with the HYSPLIT model and statistically analyzed. During 2001-2005, dust events were recorded on 12% of all days; 55% of the events were synoptically-driven, while 45% of the events were convectively-driven. Analyses showed different airflow patterns during dusty days as compared to overall trajectories into El Paso. For synoptically-driven dust events, arriving air masses were strongly associated with a zone of known dust source areas west-southwest of the city, and trajectories were consistent with air parcels moving toward cyclones crossing or developing NE of the Chihuahuan Desert. For convective dust events, trajectories were correlated with air masses arriving from the south and southeast, consistent with monsoon moisture surges bringing thunderstorms. Finally, numerical modeling of weather on a dust event day was performed and analyzed using the Weather Research and Forecasting (WRF)-Chem model. The case study selected was Feb. 4, 2008, where very strong gusty winds across much of northern Mexico, eastern New Mexico and Northwest Texas generated widespread dense blowing dust in the afternoon on. WRF-Chem model results were correlated with TCEQ station data to evaluate the vii model's performance for dust storms. The results of these analyses improve the knowledge of how dust storms and airborne particulate matter behave in the El Paso, Texas/ Ciudad Juarez, Chihuahua region and can aid in improving the forecasts of these phenomena. viii

2007

An analysis of fine particulate data in eastern North Carolina was conducted to investigate the impact of the hog industry and its emissions of ammonia into the atmosphere. The fine particulate data are simulated using ISORROPIA, an equilibrium thermodynamic model that simulates the gas and aerosol equilibrium of inorganic atmospheric species. The observational data analyses show that the major constituents of fine particulate matter (PM 2.5) are organic carbon, elemental carbon, sulfate, nitrate, and ammonium. The observed PM 2.5 concentration is positively correlated with temperature but anticorrelated with wind speed. The correlation between PM 2.5 and wind direction at some locations suggests an impact of ammonia emissions from hog facilities on PM 2.5 formation. The modeled results are in good agreement with observations, with slightly better agreement at urban sites than at rural sites. The predicted total inorganic particulate matter (PM) concentrations are within 5% of the observed values under conditions with median initial total PM species concentrations, median relative humidity (RH), and median temperature. Ambient conditions with high PM precursor concentrations, low temperature, and high RH appear to favor the formation of secondary PM.

2000