Calcined coke is a high quality carbon material produced by calcining green petroleum coke. Calcining is the process of heating green petroleum coke in a kiln to remove excess moisture, extract all remaining hydrocarbons, and modify the crystalline structure of the coke into a denser, electrically conductive product. The final product, calcined coke, is primarily used to make carbon anodes for the aluminum industry and recarburizing agent for industries such as the steel industry. If not appropriately controlled, the calcining process could lead to excess production of particulate emissions from either handling or storing of raw coke, or from the stack emissions during the production of calcined coke. Though calcined coke has shown low hazard potential in human populations due to low volatile content, there remains some public health concern regarding the emissions from these facilities. This study is designed to evaluate the emissions of petroleum coke calcining facility and assess the public health concern from the processes engaged in the handling and storage of green coke as well as from the calcining process. The ambient air levels were measured from a calcining facility and compared with the standards promulgated by USEPA. The results showed that pollutant contribution from the facility, measured by monitoring carbon fraction of the emissions, was de-minimis. The current research also studied whether the exposure levels and health risks specified in various epidemiological studies correlate with the standards promulgated by USEPA to protect public health from petrochemical emissions.

Black carbon (BC) is the light-absorbing component of soot, a combustion-generated aerosol that warms the climate by absorbing solar radiation. Its impacts on climate depend on its microphysical properties, which are modified by atmospheric processes including condensation, coagulation and wet removal. State of the art climate models consider soot in a concentric core/shell configuration, with a BC core coated by nonrefractory material such as organics or sulphate. Within this model, thicker coatings enhance visible light absorption, but also wet removal efficiency, and these have opposing effects on the total amount of light absorbed over BC’s lifetime. How well the core/shell model can calculate Mass Absorption Coefficient (MAC, the ratio of absorption to BC mass) is uncertain, as real soot forms more complex (often fractal) shapes, and detailed optical models using these morphologies predict the core/shell model may under- or over-estimate MAC depending on the precise properties of the particles. Few reliable measurements of variations in ambient MAC are available, as most older measurement techniques suffer from systematic uncertainties. In this work, a Single Particle Soot Photometer (SP2) and PhotoAcoustic Soot Spectrometer (PASS) were used to measure BC mass concentration and absorption, and these instruments do not suffer from such uncertainties. The SP2 was also used to report core size and coating thickness distributions that are required to test state of the art climate models. Firstly, a method was developed to minimise bias in the measured coating thicknesses related to the limited detection range of the SP2. The sensitivity of this technique to the assumed density and refractive index of the BC core was also explored, and the most appropriate parameters to use with ambient measurements were determined. Core and shell distributions were measured in Pasadena, California under a range of different photochemical ages. These were then used to calculate MAC, which was compared to that measured using the SP2 and PASS. The measured and modelled MAC agreed within 10% at 532 nm, though this was dependent on the assumed refractive index of the BC core. Overall MAC increased by 15 –25% in around one third of a day of photochemical ageing. This is quite modest compared to some climate models, but not compared to the previous best estimate, which predicted MAC may increase by a factor of ~1.5 over BC’s lifetime. Core and coating distributions were also measured in Canadian boreal biomass burning plumes. A case study was presented comparing the properties of BC in three plumes, one of which had passed through a precipitating cloud. It was demonstrated that larger and more coated BC-containing particles were removed more efficiently, in agreement with previous thermodynamic theory. By calculating MAC using the measured core/shell distributions and comparing to measured scattering, it was demonstrated that the MAC and single-scattering albedo in the plumes were likely not significantly affected by the wet removal, as greater differences were observed between the two plumes not affected by precipitation.

Der anthropogene Klimaeinfluss hat zu global steigenden Temperaturen geführt. In der sich verändernden Arktis ist diese Erwärmung im Vergleich zum globalen Mittel verstärkt. Schwarzer Kohlenstoff (Black Carbon, BC) ist ein Aerosoltyp, der von besonderem Interesse ist, da er die Sonnenstrahlung besonders effizient absorbiert und dadurch zur Erwärmung der Atmosphäre beiträgt. BC entsteht bei unvollständiger Verbrennung fossiler Brennstoffe und bei Vegetationsbränden. Dies beinhaltet fossile Brennstoffe und Biomasse, etwa bei Vegetationsbränden. Ziel dieser Arbeit ist die Untersuchung der Quellen und des Transports von BC in die Arktis mittels globaler Modellierung und eine aktuelle Abschätzung dessen Wirkung auf den Strahlungshaushalt der Arktis. Hierzu wird das globale Aerosol-Klimamodell ECHAM-HAM verwendet. Eine umfassende Evaluierung des Models unter Verwendung von Beobachtungen der BC-Konzentrationen in der Arktis zeigt, dass BC vom Modell im allgemeinen realistisch reproduziert, in der oberen Troposphäre der Arktis jedoch überschätzt wird. Die häufigsten Unsicherheiten globaler Aerosol-Klimamodelle werden mit Sensitivitätsstudien angegangen: Der Unsicherheitsbereich der aus Annahmen über die BC-Quellen resultiert, wird durch eine Gegenüberstellung verschiedener Emmisionskonfigurationen quantifiziert. Zusätzlich werden die Unsicherheiten aufgrund der Parametrisierung der Nassdeposition abgeschätzt. Tagesaktuelle, satellitengestützte Emissionen von Vegetationsbränden sind entscheidend um die vertikale Verteilung von arktischem BC zu reproduzieren. Außerdem ermöglichen diese Emissionsdaten bessere zeitliche Korrelationen zwischen Beobachtungen und Modell. Eine neue Modellkonfiguration mit langsamerer Alterung und effizienterer Auswaschung von Aerosolen in Wolken führt zu einer realistischeren BC-Verteilung in der oberen arktischen Troposphäre. Der direkte Strahlungseffekt (DRE) des atmosphärischen BC in der Arktis >60°N beläuft sich auf einen Nettoenergiegewinn (solar und thermisch) am Oberrand der Atmosphäre (TOA) von +0,31 Watt pro Quadratmeter im Mittel der Jahre 2007 bis 2018, der des Schnee-Albedo-Effekts von BC auf einen Gewinn von +0,12 Watt pro Quadratmeter. Der effektive Strahlungseinfluss von BC auf die Arktis am TOA (der direkte Effekte und Aerosol-Wolken-Wechselwirkungen einschließt) wird im langjährigen Mittel auf -0,2 Watt pro Quadratmeter geschätzt. Diese Wechselwirkungen sind jedoch höchst unsicher. Verbesserte Emissionsannahmen erhöhen die modellierte arktische BC-Belastung um 25%, während sie durch die optimierte Aerosolmikrophysik und Nassdeposition um 10% verringert wird. Allerdings wirken sich beide Unsicherheitsfaktoren auf den DRE mit 22% bis 24% etwa gleichermaßen stark aus, dies zeigt die Wichtigkeit einer genauen Beschreibung der vertikalen Verteilung von BC im Modell. Diese Arbeit ermöglicht somit eine vollständigere Bewertung des DRE von BC in der Arktis. Neu entwickelte Modellerweiterungen und die angewandten Methoden bilden eine Grundlage für weitere Aerosol-Klima-Forschung auch außerhalb der Arktis. / The anthropogenic impact on climate has led to rising global temperatures. This warming is enhanced in the changing Arctic compared to the global mean. Black carbon (BC) is an aerosol type of particular interest, because it efficiently absorbs solar radiation and thus contributes to the atmospheric warming. BC is released into the atmosphere through incomplete combustion of fossil fuels and biomass including wildfires. The objective of this work is to investigate the sources and transport of BC to the Arctic using global modelling and to provide an up-to-date estimate of its effect on the radiation budget of the Arctic. For this purpose the global aerosol-climate model ECHAM-HAM is used. A comprehensive evaluation of the model using ground-based and airborne observations of BC concentrations in the Arctic shows that it is mostly able to realistically reproduce the observations, but produces an overestimation in the upper Arctic troposphere. The typical uncertainties of current aerosol-climate models are addressed with sensitivity studies: The range of uncertainty in the distribution and radiative effects of BC aerosol due to the assumptions on BC sources is quantified by comparing different emission setups. In addition, the uncertainties related to the wet deposition parametrisation are estimated. It is found that daily, satellite-based biomass combustion emissions are crucial for the reproduction of the vertical distribution of Arctic BC mass concentrations. Moreover, these emission data allow better temporal correlation between observations at Arctic stations and model. A new model configuration, developed in this study, with slower ageing and more efficient scavenging of aerosol in clouds leads to a more realistic BC distribution in the upper Arctic troposphere. The DRE of atmospheric BC in the Arctic (>60°N) amounts to a net energy gain (solar and thermal) at the TOA of +0.31 watt per square meter on average over the years 2007 to 2018, that of the BC-in-snow albedo effect to a gain of +0.12 watt per square meter. The effective radiative impact (direct effects plus rapid adjustments and aerosol-cloud interactions) of BC on the Arctic at top of the atmosphere (TOA) is estimated at -0.2 watt per square meter on the multi-year average. However, the aerosol-cloud radiation interactions are highly uncertain. Improved emission assumptions increase the modelled Arctic BC burden by 25%, while the optimised aerosol microphysics and wet deposition decrease it by 10%. However, both uncertainty factors affect the direct radiative effect (DRE) with 22% to 24% approximately equally, which shows the importance of an accurate description of the vertical distribution of BC in the model. This work thus allows a more complete assessment of the DRE of BC in the Arctic. The newly developed model extensions and methods applied provide a basis for further aerosol-climate research in the Arctic and elsewhere.

Atmospheric aerosol particles play an important role in global climate change, via direct and indirect radiative forcing. Elemental carbon (EC) and nitrate are important contributors to anthropogenic aerosol radiative forcing over Europe, since they strongly absorb and/or scatter solar radiation, respectively. However, the evaluation of their climate effects remains highly uncertain. Improvements on the simulation of particle number/mass size distribution (PSD) in modelling will help us to refine model assessments of climate change. The simulations were performed over Europe with a fully online-coupled regional air quality model (WRF-Chem) for the time period of September 10-20th, 2013. Measurements in the HOPE-Melpitz campaign and other datasets in Europe were adopted to evaluate the model uncertainties. The meteorological conditions were well reproduced by the simulations. However, a remarkable overestimation of coarse mode PSD was found in the simulations. The overestimation was mainly contributed by EC, sodium nitrate and sea salt (SSA), stemming from the inadequate emission of EC and SSA. The EC inventory overestimates EC point sources in Germany and the fractions of coarse mode EC emissions in Eastern Europe and Russia. Allocating too much EC emission into the coarse mode could shorten EC lifetime and reduce its long-range transport, thus partly (~20-40%) explaining the underestimation of EC in Germany, when air masses came from eastern direction in previous studies. Furthermore, WRF-Chem overestimated coarse mode SSA mass concentrations by factors of about 8-20 over northwestern and central Europe in this study, due to the shortcoming of its emission scheme. This could facilitate the coarse mode sodium nitrate formation and lead to ~140% overestimation of coarse mode nitrate. Under such circumstances, nitric acid was exhausted, and fine mode ammonium nitrate formation was inhibited. The overestimated SSA shaped the PSD of nitrate towards larger sizes, which might influence the optical properties, lifetime and climate effect of nitrate accordingly. A transport mechanism would broaden the influence of SSA on nitrate PSD to central Europe, where a considerable amount of nitrate precursors and ammonium nitrate is present.:Table of Contents List of Figures List of Tables Abbreviations 1. Introduction 1.1 Particle size distribution 1.2 Elemental carbon particle size distribution simulation 1.3 Chemical pathways for particulate nitrate 1.4 Influence of sea salt on nitrate particle mass size distribution 1.5 Objectives 2. Methodology 2.1. WRF-Chem model 2.1.1. General description 2.1.2. Model configuration 2.1.3 Anthropogenic source emissions 2.1.4 Natural source emissions 2.2 HOPE-Melpitz campaign 2.3 GUAN network over Germany 2.4 Other datasets 3. Results and Discussion 3.1 First publication 3.1.1 Evaluation of the size segregation of elemental carbon (EC) emission in Europe: influence on the simulation of EC long-range transportation 3.1.2 Supporting information 3.2 Second publication 3.2.1 Sea salt emission, transport and influence on size-segregated nitrate simulation: a case study in northwestern Europe by WRF-Chem 3.2.2 Supporting information 4. Summary and Conclusions 5. Outlook Appendix A Bibliography Acknowledgements

The health effects of particulate air pollution and the evaluation of mitigation efforts to address them have been focused in the past on measurements of bulk mass concentrations of aerosol particles (particulate matter or PM) at fixed locations instead of more traffic-related PM such as black carbon (BC). A more appropriate investigation of the spatial and temporal variabilities of these pollutants is necessary to effectively estimate realistic pedestrian exposure. In this work, three novel scientific contributions are presented with an overarching goal of quantifying the influence of environmental factors on the spatial and temporal distributions of BC and PM2.5 (all particles smaller than 2.5 micrometers) in urban areas. Mass concentrations of BC and PM2.5 were obtained with a mobile platform called the “aerosol backpack”. With this tool, strategic mobile measurement field campaigns were conducted at multiple sites in four countries to achieve the scientific objectives of this work. First, a concept was developed to optimize the mobile measurement strategy for obtaining high-quality data for scientific analyses including a traceable way to reconstruct and calculate PM2.5 mass concentrations from an optical particle size spectrometer. Second, an entire investigation was done on the field performance of the most widely-used portable absorption photometer for measuring BC mass concentrations, the AE51. Results show that these instruments are robust and reliable across different environments. Third, a statistical approach based on a Bayesian distributional model was developed and refined to suitably analyze mobile measurement datasets and extract reliable information. Through this model, the differences between the effects of human activities and other environmental factors on BC and PM2.5 have been quantified. These results quantitatively confirm that spatial and temporal characteristics related to human activities have stronger effects on the variability of the BC mass concentration than on the regulated PM2.5 – consequently, having more influence on pedestrian exposure. This study highlights the importance of high data quality for mobile measurements to make them useful in exposure assessment, particularly to pollutants that are highly variable in space. Finally, this study contributes to the growing evidence of the importance of including more traffic-related pollutants to monitor air quality in urban areas and create appropriate mitigation strategies to combat the adverse health effects of air pollution.:Table of Contents Bibliographic Description .................................................................................................. i Bibliografische Beschreibung ........................................................................................... ii 1. Introduction ................................................................................................................... 1 1.1 Black carbon ....................................................................................................... 2 1.2 Mobile measurements ........................................................................................ 5 1.3 Objectives ............................................................................................................... 6 2. Methodology ................................................................................................................. 9 2.1 TROPOS Aerosol backpack ................................................................................... 9 2.1.1 Instrumentation .............................................................................................. 10 2.2 Mobile measurement strategy ........................................................................... 12 2.3 Phase 1 – Pilot studies .......................................................................................... 12 2.3.1 MACE-2015, Manila Philippines (Master thesis) ......................................... 13 2.3.2 Saxony Soot Project 2016, Leipzig and Dresden, Germany .......................... 15 2.4 Phase 2 – Optimization of MM and quality assurance ......................................... 18 2.4.1 CARE-2017, Rome, Italy .............................................................................. 18 2.4.2 Other datasets ................................................................................................. 19 2.5 Phase 3 – Data analysis ......................................................................................... 20 2.5.1 Statistical model: lognormal distributional regression .................................. 21 3. Results and Discussion ............................................................................................... 27 3.1 First publication .................................................................................................... 27 3.1.1 Methodology for high-quality mobile measurement with focus on black carbon and particle mass concentrations ............................................................................ 27 3.2 Second publication ................................................................................................ 45 3.2.1 Performance of microAethalometers: Real-world field intercomparisons from multiple mobile measurement campaigns in different atmospheric environments 45 3.3 Third Publication .................................................................................................. 73 iv 3.3.1 Pedestrian exposure to black carbon and PM2.5 emissions in urban hotspots: New findings using mobile measurement techniques and flexible Bayesian regression models .................................................................................................... 73 4. Summary and Conclusions ....................................................................................... 101 5. Outlook ..................................................................................................................... 107 Appendix ....................................................................................................................... 109 A.1 Publications included in the Doctoral Thesis and Author’s contributions ......... 109 A.2 Other Publications as First Author and Co-author during PhD ......................... 111 A.3 PhD Committee .................................................................................................. 113 A.4 Supervision Committee ...................................................................................... 114 List of Figures ............................................................................................................... 115 List of Tables ................................................................................................................ 116 Abbreviations ................................................................................................................ 117 Bibliography ................................................................................................................. 119 Acknowledgement ........................................................................................................ 129 / Die gesundheitlichen Auswirkungen der Luftverschmutzung durch Feinstaub und die Bewertung von Maßnahmen zu ihrer Eindämmung konzentrierten sich bisher auf Messungen der Massenkonzentration von Aerosolpartikeln (PM; Particulate Matter) an festen Standorten und nicht auf verkehrsbedingte Aerosolpartikel wie z. B. Ruß (BC; Black Carbon). Eine zielgerichtete Untersuchung der räumlichen und zeitlichen Variabilität dieser Schadstoffe ist notwendig, um die realistische Exposition von Fußgängern effektiv abzuschätzen. In dieser Arbeit werden drei neue wissenschaftliche Ansätze mit dem übergreifenden Ziel vorgestellt, den Einfluss von Umweltfaktoren auf die räumliche und zeitliche Verteilung von BC und PM2,5 in städtischen Gebieten zu quantifizieren. Die Massenkonzentrationen von BC und PM2,5 (alle Partikel kleiner 2,5 Mikrometer) wurden mit einer mobilen Plattform, dem Aerosol-Rucksack, gemessen. Damit wurden strategische mobile Messkampagnen an mehreren Standorten in verschiedenen Ländern durchgeführt, um die wissenschaftlichen Ziele dieser Arbeit zu erreichen. Dazu wurde zunächst ein Konzept zur Optimierung der mobilen Messstrategie entwickelt, um qualitativ hochwertige Daten für wissenschaftliche Analysen zu erhalten, einschließlich einer nachvollziehbaren Methode zur Rekonstruktion und Berechnung von PM2.5-Massekonzentrationen aus Messungen mit einem optischen Partikelgrößenspektrometer. Zweitens wurde die Leistungsfähigkeit der am häufigsten verwendeten tragbaren Absorptionsphotometers zur Messung der BCMassekonzentration unter realistischen Bedingungen untersucht. Diese Ergebnisse zeigen, dass die verwendeten Geräte in den unterschiedlichsten Umgebungen robust und zuverlässig einsetzbar sind. Drittens wurde ein statistischer Ansatz entwickelt und angepasst, um mobile Messdatensätze in geeigneter Weise zu analysieren und weitere nützliche Informationen zu gewinnen. Mithilfe dieses Modells wurden die Unterschiede zwischen den Auswirkungen menschlicher Aktivitäten und anderer Umweltfaktoren auf BC und PM2,5 quantifiziert. Diese Ergebnisse bestätigen quantitativ, dass räumliche und zeitliche Merkmale im Zusammenhang mit menschlichen Aktivitäten stärkere Auswirkungen auf die Variabilität der BC-Massekonzentration haben als auf die regulierte PM2,5-Konzentration - und folglich auch einen größeren Einfluss auf die Exposition von Fußgängern. Diese Studie unterstreicht die Bedeutung hoher Datenqualität bei mobilen Messungen zur Expositionsabschätzung, insbesondere bei Schadstoffen, die räumlich sehr variabel sind. Insbesondere trägt diese Studie dazu bei, die Notwendigkeit hervorzuheben, in städtischen Gebieten mehr verkehrsbedingte Luftschadstoffe in die Überwachung der Luftqualität einzubeziehen. Darüber hinaus sollen geeignete Strategien, zur Bekämpfung der gesundheitsschädlichen Auswirkungen der Luftverschmutzung, entwickelt werden.:Table of Contents Bibliographic Description .................................................................................................. i Bibliografische Beschreibung ........................................................................................... ii 1. Introduction ................................................................................................................... 1 1.1 Black carbon ....................................................................................................... 2 1.2 Mobile measurements ........................................................................................ 5 1.3 Objectives ............................................................................................................... 6 2. Methodology ................................................................................................................. 9 2.1 TROPOS Aerosol backpack ................................................................................... 9 2.1.1 Instrumentation .............................................................................................. 10 2.2 Mobile measurement strategy ........................................................................... 12 2.3 Phase 1 – Pilot studies .......................................................................................... 12 2.3.1 MACE-2015, Manila Philippines (Master thesis) ......................................... 13 2.3.2 Saxony Soot Project 2016, Leipzig and Dresden, Germany .......................... 15 2.4 Phase 2 – Optimization of MM and quality assurance ......................................... 18 2.4.1 CARE-2017, Rome, Italy .............................................................................. 18 2.4.2 Other datasets ................................................................................................. 19 2.5 Phase 3 – Data analysis ......................................................................................... 20 2.5.1 Statistical model: lognormal distributional regression .................................. 21 3. Results and Discussion ............................................................................................... 27 3.1 First publication .................................................................................................... 27 3.1.1 Methodology for high-quality mobile measurement with focus on black carbon and particle mass concentrations ............................................................................ 27 3.2 Second publication ................................................................................................ 45 3.2.1 Performance of microAethalometers: Real-world field intercomparisons from multiple mobile measurement campaigns in different atmospheric environments 45 3.3 Third Publication .................................................................................................. 73 iv 3.3.1 Pedestrian exposure to black carbon and PM2.5 emissions in urban hotspots: New findings using mobile measurement techniques and flexible Bayesian regression models .................................................................................................... 73 4. Summary and Conclusions ....................................................................................... 101 5. Outlook ..................................................................................................................... 107 Appendix ....................................................................................................................... 109 A.1 Publications included in the Doctoral Thesis and Author’s contributions ......... 109 A.2 Other Publications as First Author and Co-author during PhD ......................... 111 A.3 PhD Committee .................................................................................................. 113 A.4 Supervision Committee ...................................................................................... 114 List of Figures ............................................................................................................... 115 List of Tables ................................................................................................................ 116 Abbreviations ................................................................................................................ 117 Bibliography ................................................................................................................. 119 Acknowledgement ........................................................................................................ 129

Durch die Verbrennung von Biomasse werden Partikel freigesetzt, die u.a. schwarzen Kohlenstoff enthalten. Dieser ist wesentlich für die Absorption der solaren Strahlung in der Atmosphäre verantwortlich. Um den Effekt der emmitierten Partikel auf den Strahlungshaushalt quantifizieren zu können, ist die Kenntnis der physikalischen und chemischen Eigenschaften dieser Partikel nötig. Diese sind aber nur zum Teil bekannt. Dieser Bericht beschreibt eine Methode, die optischen Eigenschaften solcher Partikel unter Verwendung bestimmter Annahmen zu berechnen. Auÿerdem wird ein erster Vergleich zwischen berechneten Größen und Messungen aus Laborfeuern durchgeführt. / Biomass burning is an important source for particles containing black carbon, which is known as a strong light absorbing substance. To quantify the effect of such emitted particles on the radiation budget, the knowledge of their physical and chemical properties is necessary. Until now these properties are only partly known. In the following we describe a possibility of calculating the optical properties of such particles using certain simplifications. Also a first comparison between the calculated values and measurements from lab experiments is shown.

No description available.

PM2.5 variability within the neighborhood scale has not been thoroughly studied for wood burning communities. High variability in near-field PM2.5 concentration may lead to harmful public exposure since monitoring does not occur on that scale. This study measures near-field PM2.5 variability by measuring black carbon (BC), a component of PM2.5, in a 1 km2 area located in Cambria, California. BC and meteorological data (when meteorological instruments were available) were measured over thirteen 12-hour intensive operation periods (IOPs) occurring over the winters of 2009 and 2010. Near-field BC variability was measured to understand the type of exposures found in communities where many homes are burning wood simultaneously within a small area. In addition, relationships between meteorological, geographical, and burning source characteristics and BC were observed as tools for understanding BC concentration. The computer air dispersion modeling programs, ISC-PRIME and ISCST3, were also evaluated for applicability to the near field. BC concentrations were measured using 1- to 2-minute resolution aethalometers and 12 hour resolution Personal Environmental Monitors (PEMs). On average, over all IOPs and sites, aethalometer and PEM BC averages were very similar, ranging between 200 and 250 ng/m3, or 4 and 5 µg/m3 for PM2.5, and standard deviations were often high. Averaging all BC measurements, aethalometer BC standard deviation values were 360 percent of the average BC concentration and PEM BC standard deviations were 120 percent the average BC concentration. The average standard deviation detected during each IOP was 190 percent of the average BC concentration for aethalometers and 79 percent of the average BC concentration for PEMs. The average standard deviation detected at each site was 220 percent of the average BC concentration for aethalometers and 76 percent of the average BC concentration for PEMs. The larger standard deviations measured by higher resolution aethalometers demonstrated that low resolution instruments, such as PEMs, are unable to detect high concentrations that may occur. In addition to examining BC variability, multiple linear regression analyses were conducted to determine the impact of meteorological variables and geographic and burning source characteristics on BC concentration and a weighted BC deviation function (BC standard deviation divided by average BC concentration). Time impacts, humidity, and wind speed, accounted for about 50 percent of variability in aethalometer average BC and BC deviation. However, because all model assumptions were not satisfied, improvements are needed. Regression models based on PEM BC found wind speed and direction to account for about 80 percent of average PEM BC variability and number of burning sources to account for about 30 percent of PEM BC deviation. Although PEM BC models accounted for a high percentage of BC variability, few data points were available for the PEM analyses and more IOPs are needed to determine their accuracy. When evaluating correlations between geographic and burning source characteristics and PEM BC concentrations, specific IOP and PEM sampling location explained almost 70 percent of variability in BC concentration, though model residuals suggested model bias. IOP likely explained variation in burning patterns and meteorology over each night while sampling location was likely a proxy for housing density, tree coverage, and/or elevation. Because all regression model assumptions could not be satisfied, the predictors were also observed graphically. Plotting BC concentration versus the number of burning sources suggested that number of burning sources may affect BC concentration in areas of low tree coverage and high housing density and in the case that the level of surrounding vegetation and structures are minimal. More data points will be needed to determine whether or not these relationships are significant. ISC-PRIME and ISCST3 modeling overall tended to under predict BC concentrations with average modeled-to-measured ratios averaging 0.25 and 0.15, for ISC-PRIME and ISCST3, respectively. Correction factors of 9.75 and 18.2 for ISC-PRIME and ISCST3, respectively, were determined to bring modeled BC concentrations closer to unity, but the range of ratios was still high. Both programs were unable to consistently capture BC variability in the area and more investigation will be needed to improve models. The results of the study indicate high BC variability exists on the near-field scale, but that the variability is not clearly explained by existing regression and air dispersion models. To prevent public exposure to harmful concentrations, more investigation will be needed to determine factors that largely influence pollutant variability on the neighborhood scale.

No description available.

No description available.