In order to meet the US EPA's National Ambient Air Quality Standards as set under the provisions of the Clean Air Act, states and regions throughout the United States are designing cap and trade programs aimed at reducing the emissions of the two dominant precursors for ozone, nitrogen oxides (NOx) and Volatile Organic Compounds (VOCs). While emission cap and trade programs are becoming more common, relatively few analyses have examined the air quality implications of moving emissions from one location to another (due to trading of emissions between facilities), from one sector to another (due to the use of technologies such as Plug-in Electric Hybrid Vehicles - PHEVs), and changing the temporal distribution of emissions (through emissions trading among facilities with different temporal profiles). This thesis will examine, in detail, the air quality implications of two emission cap and trade programs. The first program is a NOx trading program that covers Electricity Generating Units (EGUs) in the Northeastern United States. Results show that refining the temporal limits on this cap and trade program, by charging facilities more to emit NOx on days when ozone is most likely to form, has the potential to significantly reduce NOx emissions and ozone concentrations. Additionally, this research also shows that, for this region, the spatial redistribution of NOx emissions due to trading leads to greater ozone reductions than similar amounts of NOx emission reductions applied evenly across all facilities. Analyses also indicate that displacing emissions from the on-road mobile sector (vehicles) to the EGU sector through the use of PHEVs decreases ozone in most areas, but some highly localized areas show increases in ozone concentration. The second trading program examined in this thesis is limited to Houston, Texas, where a VOC trading program is focused on a sub-set of four Highly Reactive Volatile Organic Compounds (HRVOCs), which have been identified as having substantial ozone formation potential. Work presented in this thesis examined whether this trading program, in its current form or in an expanded form, could lead to air pollution hot spots, due to spatial reallocation of emissions. Results show that the program as currently designed is unlikely to lead to ozone hot spots, so no further spatial limitations are required for this program. Expanding the trading to include Other VOCs, fugitive emissions and chlorine emissions, based on reactivity weighted trading, is also unlikely to lead to the formation of ozone hot spots, and could create more flexibility in a trading market that is currently not very active. Based on these air quality modeling results, policy suggestions are provided that may increase participation in the trading market. These case studies demonstrate that use of detailed air analyses can provide improved designs for increasingly popular emission cap and trade programs, with improved understanding of the impacts of modifying spatial and temporal distributions of emissions. / text

published_or_final_version / Urban Studies / Master / Master of Social Sciences

Air pollution has changed from an urban environmental problem to a phenomenon spreading to state, country and even global scales. In response, a variety of regulations, standards, and policies have been enacted world-wide. Policy-making and development of efficient and effective control strategies requires understanding of air quality impacts from different sources, which are usually estimated using source-oriented air quality models and their corresponding uncertainties should be addressed. This thesis evaluates emission uncertainties and their impacts on air quality modeling (Models-3/Community Multiscale Air Quality Model (CMAQ)), with special attention to biomass burning. Impacts of uncertainties in ozone precursors (mainly NOX and VOC) emissions from different sources and regions on ozone formation and emission control efficiencies are evaluated using Monte Carlo methods. Instead of running CMAQ multiple of times, first and higher order ozone sensitivities calculated by Higher-order Decoupled Direct method in Three Dimensions (CMAQ-HDDM-3D) are employed to propagate emission uncertainties. Biomass burning is one of the major sources for PM2.5. Impacts of uncertainties in biomass burning emissions, including total amount, temporal and spatial characteristics, and speciation on air quality modeling are investigated to identify emission shortcomings. They are followed by estimation of seasonal PM2.5 source contributions over the southeastern US focusing on Georgia. Results show that prescribed forest fires are the largest individual biomass burning source. Forest fire emissions under different forest management practices and ensuing air quality impacts are further studied. Forest management practices considered here include different burning seasons, fire-return intervals (FRIs), and controlling emissions during smoldering. Finally, uncertainties in prescribed forest fire emissions are quantified by propagation of uncertainties in burned area, fuel consumption and emission factors, which are required inputs for emissions estimation and quantified by various fire behavior models and methods. In summary, this thesis has provided important insights regarding emission uncertainties and their impacts on air quality modeling.

Die ab dem 1.1.2010 geltenden erweiterten Luftqualitätsgrenzwerte stellen die Kom-munen vor allem in verkehrlich belasteten Gebieten vor Probleme. Zum einen haben die Kommunen sicherzustellen, dass die Immissionsgrenzwerte eingehalten werden, zum anderen stehen ihnen aber nur eine Reihe beschränkt wirkungsvoller Maßnahmen zur Verfügung. Wie können die (Groß-) Städte darauf reagieren? Zunächst kann festgehalten werden, dass der Verkehrsbereich zukünftig den Schwerpunkt von Maßnahmen zu Klimaschutz und Luftreinhaltung bilden muss. Die wesentlichen urbanen Problemfelder werden durch den Verkehr bestimmt; bei den relevanten Luftschadstoffen stellen Fahrzeuge mit Dieselmotoren die Hauptemittenten dar und zur Reduktion der CO2-Emissionen müssen alle Fahrzeuge deutlich mehr beitragen als bisher. In der Vergangenheit war die Reduktion von Verkehrsemissionen vorrangig als Frage der Weiterentwicklung der Fahrzeugtechnik interpretiert worden. Da die technischen Weiterentwicklungen allein für die Problemlösung nicht ausreichen, sind grundsätzliche Änderungen von Verkehrsverhalten und Verkehrssystemen unumgänglich. Eine Verbesserung der Raumordnung, weniger Zersiedelung, eine multifunktionale Stadt der kurzen Wege und ein anderes Mobilitätsverhalten der Bevölkerung weisen die höchsten Reduktionspotentiale auf, wirken aber vor allem langfristig. Eine Übersicht mit denkbaren Maßnahmengruppen zur Erreichung der Luftqualitäts- und Klimaschutzziele wurde erarbeitet, die zur Entwicklung spezifischer Pakete von Kommunen genutzt werden kann.

Die ab dem 1.1.2010 geltenden erweiterten Luftqualitätsgrenzwerte stellen die Kom-munen vor allem in verkehrlich belasteten Gebieten vor Probleme. Zum einen haben die Kommunen sicherzustellen, dass die Immissionsgrenzwerte eingehalten werden, zum anderen stehen ihnen aber nur eine Reihe beschränkt wirkungsvoller Maßnahmen zur Verfügung. Wie können die (Groß-) Städte darauf reagieren? Zunächst kann festgehalten werden, dass der Verkehrsbereich zukünftig den Schwerpunkt von Maßnahmen zu Klimaschutz und Luftreinhaltung bilden muss. Die wesentlichen urbanen Problemfelder werden durch den Verkehr bestimmt; bei den relevanten Luftschadstoffen stellen Fahrzeuge mit Dieselmotoren die Hauptemittenten dar und zur Reduktion der CO2-Emissionen müssen alle Fahrzeuge deutlich mehr beitragen als bisher. In der Vergangenheit war die Reduktion von Verkehrsemissionen vorrangig als Frage der Weiterentwicklung der Fahrzeugtechnik interpretiert worden. Da die technischen Weiterentwicklungen allein für die Problemlösung nicht ausreichen, sind grundsätzliche Änderungen von Verkehrsverhalten und Verkehrssystemen unumgänglich. Eine Verbesserung der Raumordnung, weniger Zersiedelung, eine multifunktionale Stadt der kurzen Wege und ein anderes Mobilitätsverhalten der Bevölkerung weisen die höchsten Reduktionspotentiale auf, wirken aber vor allem langfristig. Eine Übersicht mit denkbaren Maßnahmengruppen zur Erreichung der Luftqualitäts- und Klimaschutzziele wurde erarbeitet, die zur Entwicklung spezifischer Pakete von Kommunen genutzt werden kann.

No description available.

published_or_final_version / Environmental Management / Master / Master of Science in Environmental Management

Ambient and indoor air pollution is a major cause of premature mortality, and has been associated with more than three million preventative deaths per year worldwide. Most of these health impacts are from the effects from fine particulate matter. It is suspected that PM2.5 health effects vary by composition, which depends on the mixture of pollutants emitted by sources. This has led to efforts to estimate relationships between sources of PM2.5 and health effects. The health effects of PM2.5 may be preferentially dependent on specific species; however, recent work has suggested that health impacts may actually be caused by the net effect of the mixture of pollutants which make up PM2.5. Recently, there have been efforts to use source impacts from source apportionment (SA) studies as a proxy for these multipollutant effects. Source impacts can be quantified using both receptor and chemical transport models (RMs and CTMs), and have both advantages and limitations for their use in health studies. In this work, a technique is developed that reconciles differences between source apportionment (SA) models by ensemble-averaging source impacts results from several SA models. This method uses a two-step process to calculate the ensemble average. An initial ensemble average is used calculate new estimates of uncertainties for the individual SA methods that are used in the ensemble. Next, an updated ensemble average is calculated using the SA method uncertainties as weights. Finally, uncertainties of the ensemble average are calculated using propagation of errors that includes covariance terms. The ensemble technique is extended to include a Bayesian formulation of weights used in ensemble-averaging source impacts. In a Bayesian approach, probabilistic distributions of the parameters of interest are estimated using prior distributions, along with information from observed data. Ensemble averaging results in updated estimates of source impacts with lower uncertainties than individual SA methods. Overall uncertainties for ensemble-averaged source impacts were ~45 - 74%. The Bayesian approach also captures the expected seasonal variation of biomass burning and secondary impacts. Sensitivity analysis found that using non-informative prior weighting performed better than using weighting based on method-derived uncertainties. The Bayesian-based source impacts for biomass burning correlate better with observed levoglucosan (R2=0.66) and water soluble potassium (R2=0.63) than source impacts estimated using more traditional methods, and more closely agreed with observed total mass. Power spectra of the time series of biomass burning source impacts suggest that profiles/factors associated with this source have the greatest variability across methods and locations. A secondary focus of this work is to examine the impacts of biomass burning. First a field campaign was undertaken to measure emissions from prescribed fires. An emissions factor of 14±17 g PM2.5/kg fuel burned was determined. Water soluble organic carbon (WSOC) was highly correlated with potassium (K) (R2=.93) and levoglucosan (R2=0.98). Results using a biomass burning source profile derived from this work further indicate that source apportionment is sensitive to levels of potassium in biomass burning source profiles, underscoring the importance of quantifying local biomass burning source profiles. Second, the sensitivity of ambient PM2.5 to various fire and meteorological parameters in was examined using the method of principle components regression (PCR) to estimate sensitivity of PM2.5 to fire data and, observed and forecast meteorological parameters. PM2.5 showed significant sensitivity to PB, with a unit-based sensitivity of 3.2±1 µg m-3 PM2.5 per 1000 acres burned. PM2.5 had a negative sensitivity to dispersive parameters such as wind speed.

Ground level ozone is one of the most ubiquitous air pollutants in urban areas, and is generated by photochemical reactions of oxides of nitrogen (NOx) and volatile organic compounds (VOCs). The effectiveness of emission reduction strategies for ozone precursors is typically evaluated using gridded, photochemical air quality models. One of the underlying assumptions in these models is that industrial emissions are nearly constant, since many industrial facilities operate continuously at a constant rate of output. However, recent studies performed in the Houston-Galveston-Brazoria area indicate that some industrial emission sources exhibit high temporal emission variability that can lead to very rapid ozone formation, especially when emissions are composed of highly reactive volatile organic compounds. This work evaluates the impact of variable emissions from industrial sources on ground-level ozone formation in Houston area, utilizing a unique hourly emission inventory, known as the 2006 Special Inventory, created as a part of the second Texas Air Quality Study. Comparison of the hourly emissions inventory data with ambient measurements indicated that the impact of the variability of industrial source emissions on ozone can be significant. Photochemical modeling predictions showed that the variability in industrial emissions can lead to differences in local ozone concentrations of as much as 27 ppb at individual ozone monitor locations. The hourly emissions inventory revealed that industrial source emissions are highly variable in nature with diverse temporal patterns and stochastic behavior. Petrochemical and chemical manufacturing flares, which represent the majority of emissions in the 2006 Special Inventory, were grouped into categories based on industrial process, chemical composition of the flared gas, and the temporal patterns of their emissions. Stochastic models were developed for each categorization of flare emissions with the goal of simulating the characterized temporal emission variability. The stochastic models provide representative temporal profiles for flares in the petrochemical manufacturing and chemical manufacturing sectors, and as such serve as more comprehensive input for photochemical air quality modeling. / text

No description available.