One of the primary modes for pollutants to reach the human body is through their release into the atmosphere and dispersion in the nearby areas. This makes air emissions one of the important components of an environmental assessment. They are frequently of interest to the people living in the vicinity of the site. The analysis carried out in this research provides a framework for atmospheric dispersion modeling of air pollutants using AERMOD, the United States Environmental Protection Agency (US EPA) approved regulatory model, for modeling port related emissions. There are various sources of emissions from the ports, however for this study, emissions from roadways, small equipment, and marine related sources are considered. AERMOD was used to estimate ambient pollutant concentrations of selective criteria pollutants such as NOx, SO2, CO and PM10 from a hypothetical port.

Some of the air pollution regulations in the United States are based on an application of the National Ambient Air Quality Standards at the property line. Agricultural operations such as cotton gins, feed mills, and cattle feed yards may be inappropriately regulated by such regulations if the current methods of measuring and predicting the concentrations of regulated pollutants are used. The regulated particulate matter pollutants are those with aerodynamic equivalent diameters less than or equal to a nominal 10 and 2.5 micrometers (PM10 and PM2.5) respectively. The current Federal Reference Method PM10 and PM2.5 samplers exhibit oversampling errors when sampling dusts with particle size distributions similar to those of agricultural sources. These errors are due to the interaction of the performance characteristics of the sampler with the particle size distribution of the dust being sampled. The results of this work demonstrate the development of a new sampler that may be used to accurately sample total suspended particulate (TSP) concentrations. The particle size distribution of TSP samples can be obtained and used to more accurately determine PM10 and PM2.5 concentrations. The results of this work indicate that accurate measures of TSP can be taken on a low volume basis. This work also shows that the low volume samplers provide advantages in maintaining more consistent sampling flow rates, and more robust measurements of TSP concentrations in high dust concentrations. The EPA approved dispersion model most commonly used to estimate concentrations downwind from a stationary source is the Industrial Source Complex Short Term version 3 (ISCST3). ISCST3 is known to over-predict downwind concentrations from low level point sources. The results of this research show that the magnitude of these errors could be as much as 250%. A new approach to correcting these errors using the power law with P values as a function of stability class and downwind distance is demonstrated. Correcting the results of ISCST3 using this new approach results in an average estimated concentration reduction factor of 2.3.

Increasing vehicle dependence in the United States has resulted in substantial emissions of traffic-related air pollutants that contribute to the deterioration of urban air quality. Exposure to urban air pollutants trigger a number of public health concerns, including the potential of inequality of exposures and health effects among population subgroups. To better understand the impact of traffic-related pollutants on air quality, exposure, and exposure inequality, modeling methods that can appropriately characterize the spatiotemporally resolved concentration distributions of traffic-related pollutants need to be improved. These modeling methods can then be used to investigate the impacts of urban design and transportation management choices on air quality, pollution exposures, and related inequality. This work will address these needs with three objectives: 1) to improve modeling methods for investigating interactions between city and transportation design choices and air pollution exposures, 2) to characterize current exposures and the social distribution of exposures to traffic-related air pollutants for the case study area of Hillsborough County, Florida, and 3) to determine expected impacts of urban design and transportation management choices on air quality, air pollution exposures, and exposure inequality. To achieve these objectives, the impacts of a small-scale transportation management project, specifically the '95 Express' high occupancy toll lane project, on pollutant emissions and nearby air quality was investigated. Next, a modeling method capable of characterizing spatiotemporally resolved pollutant emissions, concentrations, and exposures was developed and applied to estimate the impact of traffic-related pollutants on exposure and exposure inequalities among several population subgroups in Hillsborough County, Florida. Finally, using these results as baseline, the impacts of sprawl and compact urban forms, as well as vehicle fleet electrification, on air quality, pollution exposure, and exposure inequality were explored. Major findings include slightly higher pollutant emissions, with the exception of hydrocarbons, due to the managed lane project. Results also show that ambient concentration contributions from on-road mobile sources are disproportionate to their emissions. Additionally, processes not captured by the CALPUFF model, such as atmospheric formation, contribute substantially to ambient concentration levels of the secondary pollutants such as acetaldehyde and formaldehyde. Exposure inequalities for NOx, 1,3-butadiene, and benzene air pollution were found for black, Hispanic, and low income (annual household income less than $20,000) subgroups at both short-term and long-term temporal scales, which is consistent with previous findings. Exposure disparities among the subgroups are complex, and sometimes reversed for acetaldehyde and formaldehyde, due primarily to their distinct concentration distributions. Compact urban form was found to result in lower average NOx and benzene concentrations, but higher exposure for all pollutants except for NOx when compared to sprawl urban form. Evidence suggests that exposure inequalities differ between sprawl and compact urban forms, and also differ by pollutants, but are generally consistent at both short and long-term temporal scales. In addition, vehicle fleet electrification was found to result in generally lower average pollutant concentrations and exposures, except for NOx. However, the elimination of on-road mobile source emissions does not substantially reduce exposure inequality. Results and findings from this work can be applied to assist transportation infrastructure and urban planning. In addition, method developed here can be applied elsewhere for better characterization of air pollution concentrations, exposure and related inequalities.

Šiame darbe atliekamas kietųjų dalelių dispersijos modeliavimas SILAM modeliu pernašos atmosferoje tyrimo tikslais, pateikiami modelio rezultatai, išvados. Lietuvoje yra sąlygos efektyviam modelio darbui bei poreikis modeliuoti ir prognozuoti atmosferos teršalų sklidimą, todėl šio darbo rezultatas ir darbo metu sukurta modelio nustatymo metodika galėtų būti plačiai naudojami praktikoje. Kol kas nėra gausios informacijos apie atmosferos taršos modeliavimą Lietuvos teritorijoje. Atliekami tik matavimai ir regioniniu bei valstybės mastu naudojami kaimyninių valstybių modeliavimo duomenys, o atskiros savivaldybės teršalų sklaidą atmosferoje modeliuoja mikro masto modeliais. Pagrindinis darbo tikslas: ištirti pagrindines kietųjų dalelių pernašos Lietuvos teritorijoje savybes naudojant SILAM modelį, parengtą kietųjų dalelių dispersijos modeliavimui ir prognozavimui Lietuvos teritorijoje bei kuo naujesnius ir kuo gausesnius duomenis iš Lietuvos institucijų (pavyzdžiui Lietuvos hidrometeorologijos tarnybos, Aplinkos ministerijos ir t.t.). Gauti rezultatai, išvados: 1. Pagal atliktų modeliavimų rezultatus matyti, kad pagrindinė kietųjų dalelių taršos dalis laikosi priežeminiuose troposferos sluoksniuose ir pernešama netoli (šis braižas verčia manyti, kad tai stambiosios frakcijos). Tuo tarpu į aukštesnius sluoksnius patenka keletą ir net keletą dešimčių kartų mažesnė kietųjų dalelių dalis, bet jos pernešamos toliau. 2. Pagal gautus duomenis galima teigti, kad modeliuojamuoju... [toliau žr. visą tekstą] / The main purpose of this diploma thesis “Particulate matter transport in the atmosphere research using SILAM model” (written by Adomas Mažeikis) is to use SILAM model to research the transport of local Particulate matter pollutants and those from neighboring countries too. Emission data was prepared by interpolating EMEP and Statistical Department provided data sets. Meteorological data was taken from Lithuanian HydroMeteorological Service HIRLAM installation. The setup of model was prepared and test runs were made (one of them is simulating fire in oil refinery "Mažeikių nafta"). The results of this thesis are large arrays of past (2007 October - 2008 April) PM10 dispersion data. Grads package was used to perform the analysis of data and these are the conclusions made after the analysis was finished: 1. SILAM model is accurate enough for researching country wide PM10 transport analysis. 2. Each and every model run needs individual setup for best performance. 3. SILAM is not user friendly application and there is a lack of documentation (User guide, Operational instructions and model technical descriptions are available but it does not describe the setup of model in details). 4. Users of SILAM should check model run logs. There is plenty of useful data in there though the format is not very usable. 5. Performed analysis of model run results shows that the biggest part of PM10 aerosol is in the lower levels of the troposphere and that part is transported up to 100km (this can... [to full text]

abstract: The Toledo Core Based Statistical Area (CBSA) presents an interesting case study for the new sulfur dioxide (SO2) one hour standard. Since no SO2 monitor within 75 miles to estimate the attainment status of the area, American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used in this study to predict potential problems associated with the newly revised standard. The Toledo CBSA is home to two oil refineries, a glass making industry, several coal fired lime kilns, and a sulfuric acid regeneration plant, The CBSA 3 has coal fired power plants within a 30 mile radius of its center. Additionally, Toledo is a major Great Lakes shipping port visited by both lake and ocean going vessels. As a transportation hub, the area is also traversed by several rail lines which feed four rail switching yards. Impacts of older generation freighters, or "steamers", utilizing high sulfur "Bunker C" fuel oil in the area is also an issue. With the unique challenges presented by an SO2 one hour standard, this study attempted to estimate potential problem areas in advance of any monitoring data being gathered. Based on the publicly available data as inputs, it appears that a significant risk of non-attainment may exist in the Toledo CBSA. However, future on-the-books controls and currently proposed regulatory actions appear to drive the risk below significance by 2015. Any designation as non-attainment should be self-correcting and without need for controls other than those used in these models. The outcomes of this screening study are intended for use as a basis for assessments for other mid-sized, industrial areas without SO2 monitors. The results may also be utilized by industries and planning groups within the Toledo CBSA to address potential issues in advance of monitoring system deployment to lower the risk of attaining long term or perpetual non-attainment status. / Dissertation/Thesis / M.S. Technology 2011

The performance of the AERMOD and ADMS dispersion models was tested using PM10 (thoracic dust) emissions from Rössing Uranium Mine open pit in Namibia. The performance of the two models was evaluated against the observations and also against each other using various statistical measures. The models were tested under different case scenarios (cases explained in chapter 4) with the aim of evaluating their performances as well as their inter model variability. The study was undertaken from the 13 July 2009 – 14 August 2009. The results from the study showed that the performance of ADMS was superior to that of AERMOD. In general, the performance of AERMOD was very poor and simulated extremely high concentration values. AERMOD performed even more poorly during calm conditions. ADMS performance was superior to AERMOD as was evident from the values of various performance statistical measures and a conclusion reached was that ADMS is likely to be a better model to use in cases where prolonged calm conditions are experienced. Copyright / Dissertation (MSc)--University of Pretoria, 2012. / Chemical Engineering / unrestricted

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Air quality has been a major environmental concern for many years. Recently the issue of airport emissions has presented growing concerns and is being studied in much more depth. Airport emissions come from a variety of point, line and area sources, making emissions modeling for airports very complex and more involved. Accurate air quality models, specific to airport needs, are required to properly analyze this complex array of air pollution sources created by airports. Accurate air quality models are needed to plan for increased growth of current airports and address concerns over proposed new ones. The Federal Aviation Administration's (FAA) Emissions and Dispersion Modeling System (EDMS) is a program that is the required model for assessing emissions from airport sources. This research used EDMS Version 4.21, which incorporates the EPA dispersion model AERMOD, to model detailed airport data and compare the model's predicted values to the actual measured carbon monoxide concentrations at 25 locations at a major U.S. airport. Statistics relating the model characteristics as well as trends are presented. In this way, a thorough investigation of the accuracy of the EDMS modeled values of carbon monoxide was possible. EDMS modeling included two scenarios, the first scenario referred to as practice detail included general airport information that a modeler could find from the airport being studied and the second scenario referred to as research detail utilized very detailed information from observer logs during a three day observation period. Each of the modeling scenarios was compared to the field measured data and to each other. These comparisons are important to insure the model is adequately describing emissions sources at airports. Data analysis of this study was disappointing since measured levels of CO were generally higher than modeled values. Since EDMS is continually changing and improving perhaps these results can help enhance future models.

There is a growing public concern that emissions of mobile source air toxics (MSATs) from motor vehicles may pose a threat to human health. At present, no state or federal agencies require dispersion modeling of these compounds, but many agencies are concerned about potential future requirements. Current air pollution professionals are familiar with Federal Highway Administration (FHWA) and U.S. Environmental Protection Agency (EPA) requirements for dispersion modeling to produce predicted concentrations for comparison with appropriate standards. This research examined a method in which the potential near-road concentrations of MSATs were calculated. It was believed that by assessing MSATs in much the same way that are used for other pollutants, the model and methods developed in this research could become a standard for those quantifying MSAT concentrations near-roadways. This dissertation reports on the results from short-term (1-hour) and long-term (annual average) MSATs dispersion modeling that has been conducted on seven intersections and seven freeway segments in the state of Florida. To accomplish the modeling, the CAL3QHC model was modified to handle individual MSAT emissions input data and to predict the concentrations of several MSATs around these roadway facilities. Additionally, since the CAL3MSAT model is DOS based and not user-friendly, time was invested to develop a Windows® graphical user interface (GUI). Real-world data (traffic volumes and site geometry) were gathered, worst-case meteorology was selected, mobile source emission factors (EFs) were obtained from MOVES2010a, and worst-case modeling was conducted. Based on a literature search, maximum acceptable concentrations (MACs) were proposed for comparison with the modeled results, for both a short-term (1-hour) averaging time and a long-term (1-year) averaging time. iv Results from this CAL3MSAT modeling study indicate that for all of the intersections and freeway segments, the worst-case 1-hour modeled concentrations of the MSATs were several orders of magnitude below the proposed short-term MACs. The worst-case 1-year modeled concentrations were of the same order of magnitude as the proposed long-term MACs. The 1-year concentrations were first developed by applying a persistence factor to the worst-case 1-hour concentrations. In the interest of comparing the predicted concentrations from the CAL3MSAT persistence factor approach to other dispersion models, two EPA regulatory models (CAL3QHCR and AERMOD) with the ability to account for yearly meteorology, traffic, and signal timing were used. Both hourly and annual MSAT concentrations were predicted at one large urban intersection and compared for the three different dispersion models. The shortterm 1-hour results from CAL3MSAT were higher than those predicted by the two other models due to the worst-case assumptions. Similarly, results indicate that the CAL3MSAT persistence factor approach predicted a worst-case annual average concentration on the same order of magnitude as the two other more refined models. This indicated that the CAL3MSAT model might be useful as a worst-case screening approach.

As U.S. landfills continue to grow in size, concerns about odorous gas emissions from landfills are increasing. For states that are expanding in population, such as Florida, odors from landfills are a major concern because new housing developments, needed to accommodate the rapid population growth, are creeping closer and closer to the existing landfills. As homes get closer to landfills, odor complaints are likely to become more frequent, causing landfill managers increased problems with public interactions. Odor buffer zones around landfills need to be established to give municipalities tools to help prevent the building of future homes too close to landfills. Using the latest air dispersion model, AERMOD, research predicted downwind odor concentrations from a Central Florida landfill. Accurate estimates of methane emissions throughout a Central Florida landfill were determined using a new technique developed as part of this research that uses hundreds of ambient air VOC measurements taken within a landfill, as receptors. Hundreds of point sources were placed on the landfill, and the standard Gaussian dispersion equations were solved by matrix inversion methods. The methane emission rates were then used as surrogates for odor emissions to predict downwind odor concentrations via AERMOD. By determining a critical zone around a landfill with regards to odor, stakeholders will be able to meet regulatory issues and assist their communities. Other beneficial uses from this research include: determination of existing gas collection system efficiencies, calculation of fugitive greenhouse gas emissions from municipal solid waste (MSW) landfills, and improved landfill gas management.