Several studies indicate that the cabin of buses is the micro-environment in urban public transport where commuters might be the most exposed to black carbon. Black carbon functions as an indicator of air pollution, which is shown to have harmful impacts on the human body and because it may lead to cancers, systemic inflammation, and cardiovascular diseases, it is listed as one of the top causes to premature deaths, globally. This makes it important to understand what mechanisms there are to the elevated levels of pollutants in urban buses, and by performing mobile in-cabin measurements of black carbon concentrations during 55 bus trips in the public transport system of Stockholm, this study have tried to assess the influences from using different types of fuel, self-contamination, meteorological conditions and driving factors. Although concentrations showed large variability both spatially and temporally, idling at intensely trafficked bus stops showed an average increase of concentrations by 42% compared to the overall average. The risk of allowing increased number of pollutants at bus stops increases with idling for longer time and having the doors open meanwhile.

Indiana University-Purdue University Indianapolis (IUPUI) / Rise in air pollution resulting in negative health externalities for humans has created an urgent need for cities and communities to monitor it regularly. At present we have insufficient ground passive and active monitoring networks in place which presents a huge challenge. Satellite imagery has been used extensively for such analysis, but its resolution and methodology present other challenges in estimating pollution burden. The objective of this study was to propose three low-cost methods to fill in the gaps that exist currently. First, EPA grade sensors were used in 11 cities across the U.S. to examine NO2. This is a simplistic way to assess the burden of air pollution in a region. However, this technique cannot be applied to fine scale analysis, which resulted in the next two components of this research study. Second, a citizen science network was established on the east side of Indianapolis, IN who hosted 32 Ogawa passive sensors to examine NO2 and O3 at a finer scale. These low-cost passive sensors, not requiring power, and very little maintenance, have historically tracked very closely with Federal Reference Monitors. Third, a low-cost PurpleAir PA-II-SD active sensors measuring PM2.5 were housed with the citizen scientists identified above. This data was uploaded via Wi-Fi and available via a crowd sourced site established by PurpleAir. These data sets were analyzed to examine the burden of air pollution. The second and third research studies enabled granular analyses utilizing citizen science, tree canopy data, and traffic data, thus accommodating some of the present limitations. Advancement in low-cost sensor technology, along with ease of use and maintenance, presents an opportunity for not just communities, but cities to take charge of some of these analyses to help them examine health equity impacts on their citizens because of air pollution.

京都大学 / 新制・課程博士 / 博士(地球環境学) / 甲第24153号 / 地環博第231号 / 新制||地環||44(附属図書館) / 京都大学大学院地球環境学舎地球環境学専攻 / (主査)教授 梶井 克純, 教授 高野 裕久, 准教授 田中 周平 / 学位規則第4条第1項該当 / Doctor of Global Environmental Studies / Kyoto University / DFAM

Spatial and temporal variations and factors affecting these variations in concentrations of measured parameters at two different groups of stations in Ankara are investigated in this study. The first group consists of three curbside stations that are under the direct influence of traffic emissions, on the other hand, the other group is composed of eight residential stations in which domestic heating is the main emission source. State of air quality in Ankara is determined through comparison with air quality data generated in other countries and available air quality standards. Based on this comparison, although air quality has improved in recent years, it is still not one of the clean cities around the world. Although measured concentrations of pollutants comply with standards in the Turkish Air Quality Regulation, further reduction in concentrations will be necessary, if EU directives become effective in the country. Relation between measured concentrations and meteorological parameters are also investigated. Wind speed and mixing height are the two parameters that are most closely related to measured concentrations at residential stations. However, at curbside stations concentrations are determined by emissions. Qualitative comparison of two groups of stations emphasizes the contribution of motor vehicle emissions on residential areas. Seasonal and diurnal variations of measured parameters and lower winter-to-summer ratio of SO2 indicate contribution of diesel vehicle emissions to SO2 levels at curbside stations. Contribution of traffic emissions are also observed in terms of well defined bimodal traffic pattern of SO2 and PM-10 at non-curbside stations. Seasonal and diurnal pollutant ratios are investigated to apportion different source types that are effective in each group of station. PM-to-SO2, NO-to-NO2, PM-10-to-NOX and SO2-to-NOX ratios are found to be good tracers for qualitative assessment of source groups, namely traffic and domestic heating. Different statistical methodologies are demonstrated to determine the source regions of pollutants with respect to wind direction. Air quality level of Ankara, instead of air quality level in each station, is determined in terms of daily API. One by one correlation between API and meteorological factors are investigated, maximum wind speed and daily thermic excursion is found to be the highest correlated variables. The relation between API and these variables is analyzed by multiple linear regression method and then air pollution forecast model highly correlated with API and meteorological variables is developed. The assimilative capacity of Ankara is calculated in terms of ventilation coefficient and found to be highest in summer and lowest in winter. In winter poor dispersion conditions favor the poor air quality in the city.

Chaque jour, 15% des Européens sont exposés à des niveaux moyens de bruit ou de polluants atmosphériquesdépassant les valeurs seuils fixées par la législation européenne. L’intensité de la pollution de chaque polluant et sarépartition à l’échelle d’une agglomération dépendent des capacités d’émission des sources, des phénomènes dedispersion, et de l’environnement urbain. Il en résulte une variabilité spatiale du niveau de multi-exposition qui resteencore largement méconnue. L’objectif de ce travail de thèse est d’identifier et de caractériser les situations de multiexpositionsur la ville de Besançon. Les niveaux sonores et les concentrations de plusieurs polluants atmosphériques denatures différentes (NO2, benzène, PM10 et PM2.5) ont été finement modélisés (2m x 2m). La compatibilité des modèlesa été maximisée par l’introduction d’inputs identiques dans les méthodologies de calcul Mithra-SIG pour le bruit, etCOPERT4/ADMS-urban pour les polluants. Dans un premier temps, l’impact de la définition du voisinage sur lesniveaux d’exposition a été exploré pour les deux pollutions. Douze indicateurs, présentant chacun une définitiondifférente de la zone d’exposition au voisinage du domicile, ont permis de quantifier les niveaux d'exposition autour des10865 bâtiments d’habitations bisontins. Les résultats obtenus mettent en évidence un impact significatif de ladéfinition de la zone d’exposition sur les niveaux. Les différentes définitions du voisinage conduisent à l'existence d'unbiais différentiel, dû à la prise en compte particulière des variables environnementales dans chacun des indicateurs. Cebiais se retrouve pour l'ensemble des polluants étudiés, bien que dans des proportions variables en fonction du polluant.Dans un second temps, l’étude des situations de multi-exposition bruit/NO2 a pu être réalisée. Les résultats obtenusindiquent l'existence d'une relation complexe et permettent de décrire les différentes situations de multi-expositionprésentes dans la ville. Ce travail de thèse constitue une des premières approches de ce type en France et permet demieux comprendre les relations existantes entre définition du voisinage, zones d'exposition, paramètresenvironnementaux et niveaux d'exposition. / Every day, 15% of the European population is exposed to average noise or air pollution levels exceeding theEuropean legal threshold. Levels and distribution of each pollutant across the city depend of individual sourcesemissions, dispersion phenomenon, and urban environment. Consequently, spatial variability of multi-exposure levelremains mostly unknown. The aim of this Ph. D. thesis is to identify and describe multi-exposure situations in the cityof Besançon. Environmental noise levels, and concentrations of several air pollutants (NO2, benzene, PM10 and PM2.5),have been modeled using a fine scale grid (2m x 2m). Model compatibility has been maximized by the use of commoninput into the calculation software Mithra-SIG (for noise) and COPERT4/ADMS-urban (for air pollutants). In a firsttime, impact of the neighborhood definition on exposure levels has been explored for both pollutions. Twelveindicators, each representing a different definition of the exposure area in the dwelling vicinity, have been used toquantify exposure levels around the 10 865 inhabitable building of Besançon. Obtained results show a significantimpact of the neighborhood definition on the exposure levels. Different neighborhood definitions lead to a differentialbias caused by a different accounting for environmental variables. This bias exists for all studied pollutant, but indifferent proportion depending on the pollutant. In a second time, situations of multi-exposure to noise and NO2 havebeen identified in the city. Results indicate a complex relation between pollutants and allow the description of severalmulti-exposure situations across the city. This work constitute one of the firsts approaches of this kind in France andallow a better understanding of the existing relations between neighborhood, exposure area, environmental parametersand exposure levels.