abstract: Dust storms known as 'haboobs' occur in the City of Tempe, AZ during the North American monsoon season. A haboob classification method based on meteorological and air quality measurements is described. There were from 3 to 20 haboob events per year over the period from 2005 to 2014. The calculated annual TSP (total suspended particulate) dry deposition during haboobs is estimated to contribute 74% of the total particulate mass deposited in Tempe, AZ. Dry deposition is compared with the aqueous chemistry of Tempe Town Lake. Water management and other factors may have a stronger impact on Tempe Town Lake chemistry than haboob dry-deposition. Haboobs alter the Polycyclic Aromatic Hydrocarbon (PAH) concentrations and distributions in Tempe, AZ. PAH isomer ratios suggest PM2.5 (particulate matter with aerodynamic diameters less than or equal to 2.5 μm) sources consistent with approximate thunderstorm outflow paths. The importance of the atmospheric aqueous phase, fogs and clouds, for the processing and removal of PAHs is not well known. A multiphase model was developed to determine the fate and lifetime of PAHs in fogs and clouds. The model employed literature values that describe the partitioning between three phases (aqueous, liquid organic, and gas), in situ PAH measurements, and experimental and estimated (photo)oxidation rates. At 25 °C, PAHs with two, three and four rings were predicted to be primarily gas phase (fraction in the gas phase xg > 90 %) while five- and six-ring PAHs partitioned significantly into droplets (xg < 60 %) with aqueous phase fractions of 1 to 6 % and liquid organic phase fractions of 31 to 91 %. The predicted atmospheric lifetimes of PAHs in the presence of fog or cloud droplets (< 5 hours) were significantly shorter than literature predictions of PAH wet and dry deposition lifetimes (1 to 14 days and 5 to 15 months respectively) and shorter than or equal to predicted PAH gas phase / particle phase atmospheric lifetimes (1 to 300 hours). The aqueous phase cannot be neglected as a PAH sink due to the large aqueous volume (vs. organic volume) and the relatively fast aqueous reactions. / Dissertation/Thesis / Doctoral Dissertation Chemistry 2016

Dallas is the third largest growing industrialized city in the state of Texas. the prevailing air quality here is highly influenced by the industrialization and particulate matter 2.5µm (PM2.5) has been found to be one of the main pollutants in this region. Exposure to PM2.5 in elevated levels could cause respiratory problems and other health issues, some of which could be fatal. the current study dealt with the quantification and analysis of the sources of emission of PM2.5 and an emission inventory for PM2.5 was assessed. 24-hour average samples of PM2.5 were collected at two monitoring sites under the Texas Commission on Environmental Quality (TCEQ) in Dallas, Dallas convention Centre (CAMS 312) and Dallas Hinton sites (CAMS 60). the data was collected from January 2003 to December 2009 and by using two positive matrix models PMF 2 and EPA PMF the PM2.5 source were identified. 9 sources were identified from CAMS 312 of which secondary sulfate (31% by PMF2 and 26% by EPA PMF) was found to be one of the major sources. Data from CAMS 60 enabled the identification of 8 sources by PMF2 and 9 by EPA PMF. These data also confirmed secondary sulfate (35% by PMF2 and 34% by EPA PMF) as the major source. to substantiate the sources identified, conditional probability function (CPF) was used. the influence of long range transport pollutants such as biomass burns from Mexico and Central America was found to be influencing the region of study and was assessed with the help of potential source contribution function (PSCF) analysis. Weekend/weekday and seasonal analyses were useful in understanding the behavioral pattern of pollutants. Also an inter comparison of the model results were performed and EPA PMF results was found to be more robust and accurate than PMF 2 results.

Indiana University-Purdue University Indianapolis (IUPUI) / This study looked at the time period of June through mid-October, 2013, based on the results of earlier studies that the strongest correlation between the PM2.5 and AOD data sets occurs during the summer and fall. Terra satellite data was used in this study due to availability of images for the geographic area of the state of Indiana during the time period of the study. PM2.5 measurements from 12 IDEM continuous monitoring sites, which were collected at noon local time, were compared with MODIS AOD data. Despite the limitations of useful data and smaller data sets, this study shows encouraging results, and illustrates that there is a relationship between remotely sensed MODIS AOD data and fine particulate matter (PM2.5) data collected from ground sensors within the geographic region of the state of Indiana. It is believed that this topic should be studied further and expanded upon.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第17794号 / エネ博第277号 / 新制||エネ||58(附属図書館) / 30601 / 京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻 / (主査)教授 東野 達, 教授 坂 志朗, 教授 米田 稔 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第19819号 / エネ博第325号 / 新制||エネ||65(附属図書館) / 32855 / 京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻 / (主査)教授 東野 達, 教授 坂 志朗, 准教授 亀田 貴之 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

Wildfires pose a significant and growing threat to human health. Current trends in climate change predict that wildfire occurrence and severity will increase in the near future, and therefore the adverse health effects associated with wildfire and its air quality effects are becoming increasingly relevant. Even with current efforts to stem future rises in temperature, wildfire activity will continue to increase due to lags in the climate system itself. Thus, in addition to the known increase in mortality, respiratory, and cardiovascular risks, there is a growing need to investigate other health outcomes associated with wildfire smoke exposure, especially their effect on pregnancy and birth outcomes. In order to provide a broad overview of the state of wildfire research on the topic of pregnancy and birth outcomes, this narrative review will summarize the existing literature on pregnancy and birth outcomes associated with wildfire smoke exposure, with consideration for the ambient air pollution literature that informs wildfire research. As research in this specific topic is still developing, a pattern of limitations to study designs is beginning to emerge, which will guide future research needs. Finally, practical considerations for implementing research findings into land management and public health policies that reduce wildfire exposure in order to mitigate the health risks associated with it will be explained.

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La pollution atmosphérique est le produit de fortes émissions de polluants (et de leurs précurseurs) et de conditions météorologiques défavorables. Les particules fines (PM2.5) sont l'un des polluants les plus dangereux pour la santé publique. L'exposition répétée ou prolongée à ces particules entraîne chaque année des maladies respiratoires et cardio-vasculaires chez les personnes exposées ainsi que des morts prématurées. L'évolution du climat dans les années à venir aura un impact sur des variables météorologiques (température, vents, précipitations, ...). Ces variables influencent à leur tour divers facteurs, qui affectent la qualité de l'air (émissions, lessivage par les précipitations, équilibre gaz/particule, ...). Si de nombreuses études ont déjà projeté l'effet du changement climatique sur les concentrations d'ozone, peu se sont intéressées à son effet sur les concentrations de particules fines, en particulier à l'échelle du continent européen. C'est ce que cette thèse se propose d'étudier. La circulation atmosphérique de grande échelle est étroitement liée aux variables météorologiques de surface. Par conséquent, il est attendu qu'elle ait également un impact sur les concentrations de PM2.5. Nous utilisons dans cette thèse une approche statistique pour estimer les concentrations futures de PM2.5 à partir d'observations présentes de PM2.5, de quelques variables météorologiques pertinentes et d'outils permettant de représenter cette circulation atmosphérique (régimes et types de temps). Le faible nombre d'observations journalières de PM2.5 et de ses composants en Europe nous a conduit à créer un jeu de données pseudo-observées à l'aide du modèle de qualité de l'air Polyphemus/Polair3D, puis à l'évaluer de façons opérationnelle et dynamique, afin de s'assurer que l'influence des variables météorologiques sur les concentrations de PM2.5 est reproduite de manière satisfaisante par le modèle. Cette évaluation dynamique d'un modèle de qualité de l'air est, à notre connaissance, la première menée à ce jour.Les projections de PM2.5 sur les périodes futures montrent une augmentation systématique des concentrations de PM2.5 au Royaume-Uni, dans le nord de la France, au Benelux et dans les Balkans, et une diminution dans le nord, l'est et le sud-est de l'Europe, en Italie et en Pologne. L'évolution de la fréquence des types de temps ne suffit pas toujours à expliquer l'évolution de ces concentrations entre les périodes historique et futures, car les relations entre circulation atmosphérique de grande échelle et types de temps, entre types de temps et variables météorologiques, et entre variables météorologiques et concentrations de PM2.5 sont amenées à évoluer dans le futur et contribuent à l'évolution des concentrations de PM2.5. L'approche statistique développée dans cette thèse est nouvelle pour l'estimation de l'impact du climat et du changement climatique sur les concentrations de PM2.5 en Europe. Malgré les incertitudes qui y sont associées, cette approche est facilement adaptable à différents modèles et scénarios, ainsi qu'à d'autres régions du monde et d'autres polluants. En utilisant des observations pour définir la relation polluant-météorologie, cette approche serait d'autant plus robuste / Air pollution is the result of high emissions of pollutants (and pollutant precursors) and unfavorable meteorological conditions. Fine particulate matter (PM2.5) is one of the pollutants of great concern for human health. Every year, a repeated or continuous exposure to such particles is responsible for respiratory and cardiovascular diseases among the concerned populations and leads to premature deaths. Climate change is expected to impact meteorological variables (temperature, wind, precipitation,...). Those variables will influence numerous factors, which will affect air quality (emissions, precipitation scavenging, gas/particle equilibrium,...). A large body of studies have already investigated the effects of climate change on ozone, whereas only a few have addressed its effects on PM2.5 concentrations, especially over Europe. This is the subject we investigate in this thesis. Large-scale circulation is closely linked to surface meteorological variables. Therefore, it is expected that it will impact PM2.5 concentrations too. In this thesis, we develop a statistical algorithm to estimate future PM2.5 concentrations from present PM2.5 observations, selected meteorological variables and tools to represent this circulation (weather regimes and weather types). The lack of daily observations of PM2.5 and its components over Europe prevents us to used observations. Consequently, we have created a pseudo-observed PM2.5 data set, by using the Polyphemus/Polair3D air quality Chemical-Transport Model. Both operational and dynamic evaluations were conducted against EMEP measurements, to ensure that the influence of meteorological variables on PM2.5 concentrations is correctly reproduced by the model. As far as we know, this dynamic evaluation of an air quality model with respect to meteorology is the first conducted to date.Future PM2.5 concentrations display an increase over the U.K., northern France, Benelux, and in the Balkans, and a decrease over northern, eastern, and southeastern Europe, Italy, and Poland compared to the historical period. The evolution of weather type frequencies is not sufficient to explain the PM2.5 changes. The relationships between the large-scale circulation and the weather types, between the weather types and meteorological variables, and between meteorological variables and PM2.5 concentrations evolve with future meteorological conditions and also contribute to PM2.5 changes. The statistical method developed in this thesis is a new approach to estimate the impact of climate and climate change on PM2.5 concentrations over Europe. Despite some uncertainties, this approach is easily applicable to different models and scenarios, as well as other geographical regions and other pollutants. Using observations to establish the pollutant-meteorology relationship would make this approach more robust