Rozprawy doktorskie na temat „Air pollution-Urban”

Understanding the determinants of childhood obesity has never been more urgent given the high levels across the world. It is increasingly recognized that the urban environment may affect childhood growth and obesity, and may provide important potential for community-level intervention. This thesis aimed to investigate how time trends in prevalence and incidence of overweight and obesity among children differ by sociodemographic characteristics, and to evaluate the association between the urban environment, especially on ambient air pollution, and childhood growth and obesity. This thesis used longitudinal data from primary care health records and from two cross-sectional studies in Catalonia, Spain. We observed an overall reduction over time in the prevalence of childhood obesity across Catalonia, but the prevalence increased over time among children from more deprived areas or with non-Spanish nationality, indicating increasing deprivation disparities. We observed that early-life exposure to air pollution was associated with a small increase of body mass index (BMI) growth during early postnatal growth and an increased risk of developing childhood obesity during childhood. These associations were stronger among children living in more deprived areas. Other urban factors such as population density were associated with increased BMI growth, whereas green spaces and land use mix were associated with decreased BMI growth. Finally, we observed that urban areas with higher levels of air pollution, noise and traffic, and lower levels of green spaces were associated with a higher odd of overweight and obesity in school-aged children (9-12 years). In conclusion, the findings of this thesis suggest that the urban environment, especially ambient air pollution, may have a small influence on childhood weight status from birth until mid-childhood. Socioeconomic status plays an important role in increasing inequalities of childhood obesity and in the association between the urban environment and childhood obesity.
Entendre els determinants de l’obesitat infantil no havia estat mai tan urgent, atès l’alta prevalença que hi ha arreu del món. Cada vegada hi ha més evidències que l’entorn urbà podria afectar l’obesitat infantil, i que pot aportar un potencial important per a la intervenció en l’àmbit comunitari. Aquesta tesi pretén investigar com les tendències temporals en prevalença i incidència del sobrepès i l’obesitat en infants difereix segons les característiques sociodemogràfiques; i, avaluar l’associació entre l’entorn urbà, especialment la contaminació atmosfèrica, i el creixement de l’infant i l’obesitat. Aquesta tesi ha fet servir dades longitudinals de registres electròniques de centres d’atenció primària i de dos estudis transversals en Catalunya (Espanya). S’ha observat una reducció, en general, en el transcurs del temps en la prevalença de sobrepès i obesitat infantil a Catalunya, però la prevalença incrementa al llarg del temps entre els infants de les àrees més desafavorides o els qui no tenen una nacionalitat espanyola, cosa que indica un increment de desigualtats. Hem observat en tres estudis diferents que l’exposició a la contaminació atmosfèrica en els primers anys de vida està associada a un petit increment del creixement de l’índex de massa corporal (IMC) durant el creixement postnatal, i que pot augmentar el risc de desenvolupar obesitat infantil durant l’etapa mitjana de la infància (de 6 a 14 anys). Aquestes associacions han estat més accentuades en infants que viuen en àrees desafavorides. Altres factors urbans, com ara la densitat de població, han estat associats a un increment del creixement de l’IMC, mentre que els espais verds i l’ús del sòl han estat associats a una disminució del creixement de l’IMC. Finalment, també s’ha percebut que les àrees urbans amb un nivell més alt de contaminació atmosfèrica, soroll i trànsit, i amb els nivells més baixos d’àrees verdes, tenien més probabilitats d’estar associades al sobrepès i a l’obesitat infantil durant la edat escolar (9-12 anys). En conclusió, els resultats d’aquesta tesi suggereixen que l’entorn urbà, especialment la contaminació atmosfèrica, poden tenir una petita influència en el pes infantil des del naixement fins a l’etapa mitjana de la infància. L’estatus socioeconòmic té un paper important a l’hora d’augmentar les desigualtats en l’obesitat infantil i en l’associació entre l’entorn urbà i aquesta obesitat.

Exposures to air pollution have adverse effects on health. Traditionally, epidemiological studies used monitoring data to investigate the relationship between air pollution and health. In recent decades, modelling tools have been developed to predict pollutant concentrations for population exposure assessments. Whilst gradual improvements have been made to these techniques, such as dispersion and land use regression (LUR), results have exhibited spatial inconsistencies at times. The processes involved are often time- and data- consuming, and outputs generally do not account for short-term variations in pollution. Improving model prediction capabilities can avoid exposure misclassifications, and provide better estimates for health risk assessment. The aim of this project is to increase the accuracy and efficiency of current exposure modelling techniques to capture spatial and temporal variability of urban air pollution. As part of this study, air pollution models were developed in a GIS framework for London for PM10, NOX and NO2, using dispersion, LUR, hybrid and Bayesian statistical methods. Predictors derived from traffic, land use, population datasets were incorporated in a geographical information system for modelling. For the first time, newly available city-wide datasets were used to extract enhanced geographical variables, including building height/ area, street canyon and detailed urban green space, which may have significant influence on pollution in local dispersion environment. Developed models were cross-validated and compared to concentrations obtained from routine monitoring network. LUR models were found to have higher prediction capabilities over other techniques, providing accurate explanations of spatial variability in urban air pollution. Significant improvements in model performance were seen with addition of buildings and street configuration variables, particularly for traffic-related pollutants. LUR require less computational demands than conventional dispersion methods; therefore can be easily applied over large urban areas. Introducing Bayesian statistical techniques has enabled spatio-temporal predictions which accounted uncertainties, allowing detection of pollution trends and episodes.

Thesis (Ph. D.)--Earth and Atmospheric Sciences, Georgia Institute of Technology, 2006.
Rodney J. Weber, Committee Chair ; Michael E. Chang, Committee Member ; Judith A. Curry, Committee Member ; Ellery Ingall, Committee Member ; Michael H. Bergin, Committee Member.

The research reported in this thesis describes: the prevalence of respiratory symptoms, COPD and cardiovascular problems in rural and urban adults taking account of all major confounding factors; and estimates of exposures, both indoor and outdoor, and assessment of the relationships between measured exposure and health outcomes. A cross-sectional study was conducted in an adult population (16+ years) in Nepal to compare the respiratory and cardiovascular risk of indoor air pollution in a rural population exposed to biomass smoke compared to an urban population using liquefied petroleum gas using an investigator-delivered questionnaire, lung function and blood pressure measurements.  Direct measures of indoor particular exposure (PM_2.5 and CO) and outdoor PM_2.5 were made with other relevant factors obtained by questionnaire. Direct measures of 24-hour indoor PM_2.5 were carried out in 245 rural and equal numbers of urban homes. Health outcomes were assessed in 846 rural and 802 urban dwellers.  The main risk factors studied were socio-economic status, smoking, fuel types, stove types, ventilation, BMI, income, ETS and cooking. The result suggests that cooking with biomass is associated with reduced lung function and thus a higher prevalence of COPD in the rural dwellers compared to the non-exposed urban dwellers.  No clear relationship between biomass smoke exposure and cardiovascular endpoints was found although reported cooking with biomass fuel was associated with higher blood pressure and chest pain.  Methodological issues including more invasive assessment of cardiovascular disease will in future studies be important in interpretation of this relationship.

Thesis (Ph. D.)--Ohio State University, 2004.
Title from first page of PDF file. Document formatted into pages; contains xvii, 248 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Jean-Michel Guldmann, Dept. of City and Regional Planning. Includes bibliographical references (p. 148-154).

Pattern recognition focuses on the recognition of pattern and regularities in data. In urban air pollution studies such as the study of the relationship between air pollutant concentration and meteorology data or atmospheric photochemistry, such as hydroxyl molecule loss in the atmosphere, pattern recognition is pertinent. This thesis presents various case studies where emission potential to atmosphere, concentration pattern in an air basin, extreme event pattern on a local or regional scale, patterns of the relationship between meteorological parameters and chemical parameter and atmospheric chemical loss processes have been explored. The thesis presents some new approaches to studying urban air pollution. The first study is a landfill gas emission potential study, where the composite signal has been analysed. The study proposes a new Monte Carlo permutation scheme to capture the composite landfill gas emission potential to the atmosphere. It also compares the new method with the traditional Fisher g statistics method. The second study reviews the existing methods for identifying extreme events of particulate matter on a local and regional scale and develops a new method based upon medcouple calculations of dispersion of data. This study also informs the relationship between local meteorology and extreme events using a new mathematical approach. The third study involves different pattern recognition techniques such as self organising maps, hierarchical and non-hierarchical clustering techniques, the receiver operating characte11stic curve method and a multivariate statistical approach to explore the pattern of air pollution on a regional scale. The fourth study involves applying soft modelling approaches such as block similarity measures, partial least square and principal component regression techniques to explore the relationship between meteorology and urban air pollution. This study applies a new kind of instrument known as an AQ mesh. So appropriate calibration approaches for studying these data have been followed. The fifth study is the measurement of total OH reactivity in a subtropical climatic region in the autumn season. Non-methane volatile organic carbon and different trace species contribution to OH reactivity have been assessed. This study involves the development of an instrument to generate the OH radical in a laboratory environment and kinetic study of the OH radical with volatile organic carbons and trace species in ambient air. An attempt has also been made in this study to calculate the potential "Criegee intermediate" by the ozonolysis of identified alkenes in the ambient air.

La circulation routière est une source majeure de pollution atmosphérique dans les zones urbaines. Les décideurs insistent pour qu’on leur propose de nouvelles solutions, y compris de nouvelles stratégies de management qui pourraient directement faire baisser les émissions de polluants. Pour évaluer les performances de ces stratégies, le calcul des émissions de pollution devrait tenir compte de la dynamique spatiale et temporelle du trafic. L’utilisation de capteurs traditionnels sur route (par exemple, capteurs inductifs ou boucles de comptage) pour collecter des données en temps réel est nécessaire mais pas suffisante en raison de leur coût de mise en oeuvre très élevé. Le fait que de telles technologies, pour des raisons pratiques, ne fournissent que des informations locales est un inconvénient. Certaines méthodes devraient ensuite être appliquées pour étendre cette information locale à une grande échelle. Ces méthodes souffrent actuellement des limites suivantes : (i) la relation entre les données manquantes et la précision de l’estimation ne peut être facilement déterminée et (ii) les calculs à grande échelle sont énormément coûteux, principalement lorsque les phénomènes de congestion sont considérés. Compte tenu d’une simulation microscopique du trafic couplée à un modèle d’émission, une approche innovante de ce problème est mise en oeuvre. Elle consiste à appliquer des techniques de sélection statistique qui permettent d’identifier les emplacements les plus pertinents pour estimer les émissions des véhicules du réseau à différentes échelles spatiales et temporelles. Ce travail explore l’utilisation de méthodes statistiques intelligentes et naïves, comme outil pour sélectionner l’information la plus pertinente sur le trafic et les émissions sur un réseau afin de déterminer les valeurs totales à plusieurs échelles. Ce travail met également en évidence quelques précautions à prendre en compte quand on calcul les émissions à large échelle à partir des données trafic et d’un modèle d’émission. L’utilisation des facteurs d’émission COPERT IV à différentes échelles spatio-temporelles induit un biais en fonction des conditions de circulation par rapport à l’échelle d’origine (cycles de conduite). Ce biais observé sur nos simulations a été quantifié en fonction des indicateurs de trafic (vitesse moyenne). Il a également été démontré qu’il avait une double origine : la convexité des fonctions d’émission et la covariance des variables de trafic
Road traffic is a major source of air pollution in urban areas. Policy makers are pushing for different solutions including new traffic management strategies that can directly lower pollutants emissions. To assess the performances of such strategies, the calculation of pollution emission should consider spatial and temporal dynamic of the traffic. The use of traditional on-road sensors (e.g. inductive sensors) for collecting real-time data is necessary but not sufficient because of their expensive cost of implementation. It is also a disadvantage that such technologies, for practical reasons, only provide local information. Some methods should then be applied to expand this local information to large spatial extent. These methods currently suffer from the following limitations: (i) the relationship between missing data and the estimation accuracy, both cannot be easily determined and (ii) the calculations on large area is computationally expensive in particular when time evolution is considered. Given a dynamic traffic simulation coupled with an emission model, a novel approach to this problem is taken by applying selection techniques that can identify the most relevant locations to estimate the network vehicle emissions in various spatial and temporal scales. This work explores the use of different statistical methods both naïve and smart, as tools for selecting the most relevant traffic and emission information on a network to determine the total values at any scale. This work also highlights some cautions when such traffic-emission coupled method is used to quantify emissions due the traffic. Using the COPERT IV emission functions at various spatial-temporal scales induces a bias depending on traffic conditions, in comparison to the original scale (driving cycles). This bias observed in our simulations, has been quantified in function of traffic indicators (mean speed). It also has been demonstrated to have a double origin: the emission functions’ convexity and the traffic variables covariance

The differential role that airborne particulate matter (PM) size fractions, sources, and components play in producing adverse health effects is not fully understood. Specific gaps include the role of PM generated by traffic and the effects of PMs generated by natural sources. Source specific air pollution epidemiological research still lacks integration in the risk assessment process, a fundamental tool to inform policy makers and the public about the current situation or the impact of future or past air pollution policies. This thesis addresses both these gaps. To explore the effects of PM from different sources, we investigated the association between different PM size fractions and mortality in Barcelona, Spain and used PM chemical composition data to help determine the different sources and components linked to toxicity. To illustrate that local air pollution risk assessments are useful tools in evidence-based public health, we estimated the health and economic benefits that would result from different scenario of improved air quality in the Barcelona metropolitan area and in two communities of Southern California. These case studies include new methods to integrate into the risk assessment process the recent epidemiological evidence related to the effects of traffic exposure.This thesis contributes to a better understanding of the link between particulate matter size fraction, sources, and components and health effects, and to improve air pollution health impact assessment methods. Both contributions have important implications for public health and air pollution public policy.
El papel diferencial en que las diferentes fracciones de partículas en suspensión en el aire (PMs), sus fuentes y componentes producen efectos adversos para la salud no está completamente entendido. Las lagunas actuales incluyen el papel de las PMs generadas por el tráfico y los efectos de las PMs generadas por fuentes naturales. La investigación epidemiológica relacionada con fuentes todavía falta ser integrada en el proceso de evaluación de impacto, una herramienta fundamental para informar a los tomadores de decisiones y el público sobre la situación actual o el impacto de futuras o pasadas políticas de contaminación atmosférica. Esta tesis trata estas áreas. Para explorar el papel de las PMs generadas por diferentes fuentes, se ha investigado la asociación entre diferentes fracciones de PMs y mortalidad en Barcelona (España) y se ha usado datos de composición química de PMs para identificar las fuentes y los componentes relacionados con la toxicidad. Para ilustrar que las evaluaciones de impacto a nivel local son herramientas útiles en salud pública, se ha estimado el beneficio en salud y económico que resultaría de diferentes escenarios de mejora de la calidad del aire en el área metropolitana de Barcelona y en dos comunidades de California del Sur. Estos estudios de casos incluyen nuevos métodos para integrar en las evaluaciones de impacto las nuevas evidencias epidemiológicas que relacionan la exposición al tráfico con los efectos en salud. Esta tesis contribuye a un mayor entendimiento del vínculo entre las fracciones de PM, sus fuentes y componentes y los efectos en salud así como a la mejora de los métodos de las evaluaciones de impacto. Estas contribuciones tienen importantes implicaciones para la salud pública y las políticas públicas de contaminación atmosférica.

Traffic-related air pollution is now a major concern. The Rio Earth Summit and the Government's commitment to Agenda 21 has led to Local Authorities taking responsibility to manage the growing number of vehicles and to reduce the impact of traffic on the environment. There is an urgent need to effectively monitor urban air quality at reasonable cost and to develop long and short term air pollution prediction models. The aim of the research described was to investigate relationships between traffic characteristics and kerbside air pollution concentrations. Initially, the only pollution monitoring equipment available was basic and required constant supervision. The traffic data was made available from the demand-responsive traffic signal control systems in Leicestershire and Nottinghamshire. However, it was found that the surveys were too short to produce statistically significant results, and no useful conclusions could be drawn. Subsequently, an automatic, remote kerbside monitoring system was developed specifically for this research. The data collected was analysed using multiple regression techniques in an attempt to obtain an empirical relationship which could be used to predict roadside pollution concentrations from traffic and meteorological data. However, the residual series were found to be autocorrelated, which meant that the statistical tests were invalid. It was then found to be possible to fit an accurate model to the data using time series analysis, but that it could not predict levels even in the short-term. Finally, a semi-empirical model was developed by estimating the proportion of vehicles passing a point in each operating mode (cruising, accelerating, decelerating and idling) and using real data to derive the coefficients. Unfortunately, it was again not possible to define a reliable predictive relationship. However, suggestions have been made about how this research could be progressed to achieve its aim.

Urban air quality has been a topic of major public concern and scientific research in recent years. Several theoretical and experimental studies have focused on the assessment of air quality within street canyons and other microenvironments (intersections, motorways, parking spaces, etc.), where population exposure to traffic-related pollutants is relatively high. The aim of this study was to develop a practical methodology for assessing traffic-related air pollution in urban streets, after testing available monitoring and modelling techniques. To meet this objective, a large amount of original air quality, meteorological and traffic data were collected during four intensive short-term and one long-term monitoring campaigns carried out in the region of Paris from December 1998 to December 2001. These campaigns covered three representative street canyon sites (Bd. Voltaire, Rue de Rennes, Av. Leclerc - PI. Basch) as well as a motorway service station (RN10 petrol station). Passive and active monitoring techniques were used to sample a wide range of inorganic (CO, NO X and Os) and organic gases (benzene, toluene, xylene, ethylbenzene, formaldehyde, acetaldehyde, etc.) at different heights and distances from the kerb. Indicative background measurements were also taken during the same sampling periods. Furthermore, relevant meteorological (synoptic and local) and traffic information was obtained on each site. The analysis of the data gave insights into the dispersion and transformation processes taking place within the streets. Channelling effects induced by parallel to the road axis winds gave rise to relatively high kerbside pollution levels. On the other hand, perpendicular synoptic winds generated air vortices within the canyons, which resulted in steep crossroad concentration gradients. In that case, higher pollution levels were observed on the leeward than on the windward side of the streets. A significant reduction of concentrations with height above the ground was also observed within two of the street canyons (Bd. Voltaire and Av. Leclerc). In all cases, roadside concentrations were several times higher than the corresponding urban background values. This spatial variability indicates a strong transport effect on the pollutant distribution within urban canyons, caused by the synoptic wind and influenced by the geometry of the street. That may have serious implications in terms of population exposure and compliance with air quality legislation. In this context, the siting of permanent monitoring equipment becomes crucial. A relationship between CO and benzene as well as an exponential expression linking pollutant concentrations at different heights within the canyons were empirically deduced. Five dispersion models of different levels of complexity (STREET-SRI, OSPM, AEOLIUS, CAR-International, and CALINE4) were used to calculate CO and benzene concentrations at the campaign sites. The Computational Fluid Dynamic code PHOENICS was also tested for one location. The comparison between observed and predicted values revealed the advantages and drawbacks of each model in association with the configuration of the street and the meteorological conditions. Furthermore, a sensitivity and uncertainty analysis involving three of the available models (STREET-SRI, OSPM and AEOLIUS) was carried out. OSPM was slightly modified in order to allow user access to certain internally coded parameters. An operational method combining multi-site sampling and dispersion modelling was finally proposed for assessing air quality in urban streets, taking into account the pronounced spatial and temporal variability of traffic-related air pollution, the modelling uncertainty, the practical constraints related to measurements and models, and the needs of decision makers. This methodology may find wider application in air quality management, urban and transport planning, and population exposure studies.

Atmospheric dispersion models are being increasingly used by local authorities in the United Kingdom as part of their urban air quality management programmes. Output from dispersion models now forms a vital part of any environmental impact assessment, road improvement or traffic management scheme or environmental health study. This study is centred primarily on Northampton, a county town in Southern England and is concerned with the limitations of meteorological data available to local authorities. The first part of the study investigates the variation in certain key meteorological parameters both within Northampton and between synoptic stations up to 70 kilometres away. The second part examines modelling outcomes using different sets of meteorological data and evaluates the performance of an urban dispersion model in relation to monitored air quality data. Special emphasis is placed on the use of cloud cover as a meteorological input variable. A small case study of monitoring and modelling work carried out in the London Borough of Richmond is also presented

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A ligação entre as zonas urbanas e as questões ambientais ficam mais próximas na medida em que cresce a conscientização global de conservar, melhorar e valorizar os serviços ambientais prestados pela natureza para a sustentabilidade da vida, dentro e fora da cidade. Cobertura vegetal (ou cobertura verde) está dentre as principais fontes de tais serviços. Uma vez que o processo de urbanização se mostra irreversível e os problemas ambientais urbanos se alastram em tamanho e extensão, a presença do verde está diretamente relacionada aos indicadores de qualidade de vida urbana. Como reflexo do processo de urbanização, a cidade de Belém perdeu uma grande porcentagem de seus ecossistemas naturais, de modo que este trabalho se concentrou em analisar alguns serviços ecossistêmicos—qualidade do ar, poluição do ar e regulação do clima - fornecidos pela qualidade e pela quantidade de cobertura vegetal local, considerando as alterações na distribuição espaço-temporal, em três distritos administrativos. Um marco teórico foi construído e analisado; a cobertura vegetal foi calculada, utilizando-se NDVI e Cobertura Vegetal Fracional em imagens do LANDSAT 5, ao longo de um período de 23 anos. A partir de uma proposta de escala mais detalhada de NDVI, análises quantitativas e qualitativas da cobertura verde evidenciaram perda significativa de cobertura muito densa, densa, moderada e aumento de áreas de pouca ou nenhuma vegetação. Ademais, lesão das áreas verdes sinalizou tendências de aumento da poluição do ar, da poluição sonora e da temperatura. A carência de dados relacionados ao meio ambiente não deixa dúvida sobre a urgência de investimento nos serviços ambientais provenientes da cobertura vegetal, para a sustentabilidade urbana em Belém, cujos cenários previstos são de drásticas perdas de área verde. Mais pesquisas e iniciativas de instituições públicas e privadas são necessárias para a contribuição aos serviços ambientais em Belém e, consequentemente, ao bem-estar público.
The ties between urban areas and environmental issues are growing as strong as the global awareness of the need to conserve, improve and valorize the ecosystem services provided by nature, in order to ensure the sustainability of life in and outside cities. Green vegetation coverage (or green areas) is one of the major sources of such services. Considering that there is no turning back on urbanization process, and the urban environmental problems are on the rise, the urban green areas should be among the elements that influence urban life quality. As a result of the urbanization process, the city of Belém has lost a great percentage of its natural ecosystems. This work focused at analyzing ecosystem services (air quality, air pollution and climate regulation) provided by local vegetation coverage quality and quantity, considering the spatial distribution and temporal changes on three administrative districts. A theoretical framework was built and assessed while vegetation coverage was calculated using NDVI and Fractional Vegetation Coverage on LANDSAT 5 imagery over a 23-year period. Owing to a more detailed scale, NDVI enabled conducting the quantitative and qualitative analyses of vegetation coverage, which showed significant loss of very dense, dense and moderate vegetation coverage and an increase in poor vegetation and bare soil areas. In addition, the study findings revealed increased noise pollution, decrease in air quality and increase in temperature, all resulting from changes in natural coverage. The significant lack of environmental data leaves no doubt about the urgency of investing on vegetation coverage for the urban sustainability in Belém, given that both actual and forecast scenarios indicate drastic green area losses. Hence, more research and both public and private initiatives are encouraged to contribute to the development of Belém ecosystems services and contribute to the enhancement of public well-being.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2007.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 176-189).
Limiting anthropogenic climate change over the next century will require controlling multiple substances. The Kyoto Protocol structure constrains the major greenhouse gases and allows trading among them, but there exist other possible regime architectures which may be more efficient. Tradeoffs between the market efficiency of all-inclusive policies and the benefits of policies targeted to the unique characteristics of each substance are investigated using an integrated assessment approach, using the MIT Emissions Prediction and Policy Analysis model, the Integrated Global Systems Model, and political analysis methods. The thesis explores three cases. The first case addresses stabilization, the ultimate objective of Article 2 of the UN Framework Convention on Climate Change. We highlight the implications of imprecision in the definition of stabilization, the importance of non-CO2 substances, and the problems of excessive focus on long-term targets. The results of the stabilization analysis suggest that methane reduction will be especially valuable because of its importance in low-cost mitigation policies that are effective on timescales up to three centuries. Therefore in the second case we examine methane, demonstrating that methane constraints alone can account for a 15% reduction in temperature rise over the 21st century.
(cont.) In contrast to conventional wisdom, we show that Global Warming Potential based trading between methane reductions and fossil CO2 reductions is flawed because of the differences in their atmospheric characteristics, the uncertainty in methane inventories, the negative interactions of CO2 constraints with underlying taxes, and higher political barriers to constraining CO2. The third case examines the benefits of increased policy coordination between air pollution constraints and climate policies. We calculate the direct effects of air pollution constraints to be less than 8% of temperature rise over the century, but ancillary reductions of GHGs lead to an additional 17% decrease. Furthermore, current policies have not had success coordinating air pollution constraints and CO2 constraints, potentially leading to a 20% welfare cost penalty resulting from separate implementation. Our results lead us to recommend enacting near term multinational CH4 constraints independently from CO2 policies as well as supporting air pollution policies in developing nations that include an emphasis on climate friendly projects.
by Marcus C. Sarofim.
Ph.D.

Air pollution is an emotive and complex issue, affecting materials, vegetation growth and human health. Given that over half the world's population live within urban areas and that those areas are often highly polluted, the ability to understand the patterns and magnitude of pollution at the small area (urban environment) level is increasingly important. Recent research has highlighted, in particular, the apparent relationship between traffic-related pollution and respiratory health, while the increasing prevalence of asthma, especially amongst children, has been widely attributed to exposure to traffic-related air pollution. The UK government has reacted to this growing concern by publishing the UK National Air Quality Strategy (DOE 1996) which forces all Local Authorities in England and Wales to review air quality in their area and designate any areas not expected to meet the 2005 air quality standards as Air Quality Management Areas (AQMAs), though what constitutes AQMAs and how to define them remains vague. Against this background, there is a growing need to understand the patterns and magnitude of urban air pollution and for improvements in pollution mapping methods. This thesis aims to contribute to this knowledge. The background to air pollution and related research has been examined within the first section of this report. A review of sampling methods was conducted, a sampling strategy devised and a number of surveys conducted to investigate both the spatial nature of air pollution and, more specifically, the dispersion of pollution with varying characteristics (distance to road, vehicle volume, height above ground level etc). The resultant data was analysed and a number of patterns identified. The ability of linear dispersion models to accurately predict air pollution was also considered. A variety of models were examined, ranging from the simplistic (e.g. DMRB) to the more complex (e.g. CALINE4) model. The model best able to predict pollution at specific sites was then used to predict concentrations over the entire urban area which were then compared to actual monitored data. The resultant analysis, indicated that the dispersion model is not a good method for predicting pollution concentrations at the small area level, and therefore an alternative method of mapping was investigated. Using the ARC/INFO geographical information system (GIS) a regression analysis approach was applied to the study area. A number of variables including altitude, landuse type, traffic volume and composition etc, were examined and their ability to predict air pollution tested using data on nitrogen dioxide from intensive field surveys. The study area was then transformed into a grid of 10m2, regression analysis was performed on each individual square and the results mapped. The monitored data was then intersected with the resultant map and monitored and modeled concentrations compared. Results of the analysis indicated that the regression analysis could explain up to 61 per cent of the variation in nitrogen dioxide concentrations and thus performed significantly better than the dispersion model method. The ease of application and transferability of the regression method means it has a wide range of applied and academic uses that are discussed in the final section.

While bicyclists and other active travelers obtain health benefits from increased physical activity, they also risk uptake of traffic-related air pollution. But pollution uptake by urban bicyclists is not well understood due to a lack of direct measurements and insufficient analysis of the determinants of exposure and ventilation (breathing). This knowledge gap impedes pollution-conscious transportation planning, design, and health impact assessment. The research presented in this dissertation generates new connections between transportation system characteristics and pollution uptake by bicyclists. The primary research questions are: 1) how do urban bicyclists' intake and uptake of air pollution vary with roadway and travel characteristics and 2) to what extent can transportation-related strategies reduce uptake. Breath biomarkers are used to measure absorbed doses of volatile organic compounds (VOCs). This research is the first application of breath biomarkers to travelers and the first uptake measurements of any pollutant to include roadway-level covariates. Novel methods to collect and integrate bicycle, rider, traffic, and environmental data are also introduced. Bicyclist exposure concentrations, exhaled breath concentrations, respiratory physiology, and travel characteristics were collected on a wide range of facilities in Portland, Oregon. High-resolution trajectory and pollution data were then integrated with roadway and traffic data. Models of exposure, ventilation, and uptake of VOCs were estimated from the on-road data. Important new quantifications in the models include the effects of average daily traffic (ADT) on multi-pollutant exposure, the lagged effect of on-road workload on ventilation, and the effects of exposure and ventilation on absorbed VOCs. Estimated models are applied to situations of interest to travelers and transportation professionals. Sample applications include the inhalation dose effects of road grade, cruising speed choice, stops, and detouring to parallel low-traffic facilities. In addition, dose-minimizing routing behavior is compared with revealed routing preferences in the literature. Finally, findings from this research and the literature are distilled so that they can be incorporated into bicycle network design guidelines.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico
Localizada no Sudeste brasileiro, a cidade de Ipatinga encontra-se inserida na Região Metropolitana do Vale do Aço, a qual é caracterizada pela predominância da atividade industrial siderúrgica, além da presença de uma das maiores frotas veiculares do país. Desenvolver métodos padronizados de biomonitoramento com espécies vegetais nativas pode ser uma opção economicamente viável para avaliar a qualidade do ar ao longo de grandes extensões de área urbana, o que geralmente não há como ser feito através do monitoramento instrumental devido ao seu alto custo. Neste sentido, o potencial para o monitoramento de partículas foi avaliado em Caesalpinia echinata e C. ferrea visando testar se o acúmulo de metais pelas plantas está relacionado a feições da superfície foliar. As plantas foram expostas em quatro locais urbanos por 90 dias. Uma estação- referência foi instalada no Parque Estadual do Rio Doce, a 30 km do município. Após o período experimental, avaliou-se o acúmulo de metais-traço pelas plantas. A rugosidade da superfície foliar foi investigada em dois níveis hierárquicos, através de análises de perfilometria e microscopia de força atômica. As ceras foram caracterizadas quimicamente através de CG-EM e por espectroscopia no infravermelho, e micromorfologicamente através de microscopia eletrônica de varredura. A espessura dos tecidos foliares foi avaliada em microscopia óptica. O acúmulo de partículas foi maior em C. echinata e se relacionou com uma menor rugosidade dada pelo tecido epidérmico (macrorrugosidade), menor rugosidade dada pela micromorfologia das ceras na forma de um filme fino (microrrugosidade) e com características químicas das ceras. As ceras dessa espécie possuem menores teores de hidrocarbonetos e éteres, o que lhes dá natureza polar. Essas características presumivelmente lhes conferem maior molhabilidade, o que geralmente está associado a um menor efeito auto-limpante e a um consequente aumento no acúmulo de partículas. Em contraste, C. ferrea acumulou menos material particulado (MP) mas apresentou um gradiente de respostas mais bem definido ao longo dos diferentes locais de exposição. Os locais foram um fator discriminante para a altura das células do tecido epidérmico, principalmente da face adaxial da folha, tendo este tecido este apresentado valores de espessura reduzidos nas estações urbanas. Os resultados sugerem o uso de C. echinata como bioacumuladora de MP e de C. ferrea como biosensora de poluição urbana.
In Southeastern Brazil, the city of Ipatinga is inserted in the Steel Valley Metropolitan Region, which is characterized by the predominance of steel industry, and also by the presence of one of the largest vehicle fleets in the country. Developing standardized biomonitoring methods with native plant species may be an economically viable option for assessing air quality across extensive urban areas, which usually cannot be achieved by instrumental monitoring due to cost issues. In this sense, the potential for biomonitoring airborne particles was evaluated in Caesalpinia echinata and C. ferrea aiming to test whether metal accumulation by the plants is related to leaf surface features. Plants were exposed in four urban sites for 90 days. A reference station was installed at Rio Doce State Park, 30 km away from the municipality. After the experimental period, plants were evaluated for trace-metal accumulation. Leaf surface roughness was evaluated in two hierarchical levels, through profilometry and atomic force microsocopy. Epicuticular waxes were characterized chemically through GC-MS and FTIR, and micromorphologically through scanning electron microscopy. Leaf tissue thickness was assessed through optical microscopy. Particle accumulation was higher in C. echinata, and was related to a lower roughness given by the epidermal tissue (macro- roughness), lower roughness given by the epicuticular wax deposition pattern (micro- roughness), the micromorphology of waxes in the form of a layer, and the wax chemical composition. The waxes of this species have lower amounts of hydrocarbons and ethers, conferring them a polar nature. These characteristics presumably render the leaf higher wettability, which is usually associated with decreased self-cleaning effect and a consequent increased particle accumulation. In contrast, C. ferrea showed reduced accumulation of particulate matter (PM), but a more well-defined response gradient across the exposure sites. Sites were a discriminant factor for cell height on the epidermal tissue, especially on the leaf adaxial surface, such tissue showing reduced thickness in plants exposed at the urban stations. The results suggest the use of C. echinata as a bioaccumulator of PM and C. ferrea as biosensor of urban pollution.

La contaminación ambiental es uno de los principales problemas que afecta a nuestro planeta. El crecimiento industrial y los aglomerados urbanos, entre otros, están contribuyendo a que dicho problema se diversifique y se cronifique. La presencia de contaminantes ambientales en niveles elevados afecta la salud humana, siendo la calidad del aire y los niveles de ruido ejemplos de factores que pueden causar efectos negativos en las personas tanto psicológicamente como fisiológicamente. Sin embargo, la ubiquidad de los microcomputadores, y el aumento de los sensores incorporados en nuestros smartphones, han hecho posible la aparición de nuevas estrategias para medir dicha contaminación. Así, el Mobile Crowdsensing se ha convertido en un nuevo paradigma mediante el cual los teléfonos inteligentes emergen como tecnología habilitadora, y cuya adopción generalizada proporciona un enorme potencial para su crecimiento, permitiendo operar a gran escala, y con unos costes asumibles para la sociedad. A través del crowdsensing, los teléfonos inteligentes pueden convertirse en unidades de detección flexibles y multiuso que, a través de los sensores integrados en dichos dispositivos, o combinados con nuevos sensores, permiten monitorizar regiones de interés con una buena granularidad tanto espacial como temporal. En esta tesis nos centramos en el diseño de soluciones de crowdsensing usando smartphones donde abordamos problemas de contaminación ambiental, específicamente del ruido y de la contaminación del aire. Con este objetivo, se estudian, en primer lugar, las propuestas de crowdsensing que han surgido en los últimos años. Los resultados de nuestro estudio demuestran que todavía hay mucha heterogeneidad en términos de tecnologías utilizadas y métodos de implementación, aunque los diseños modulares en el cliente y en el servidor parecen ser dominantes. Con respecto a la contaminación del aire, proponemos una arquitectura que permita medir la contaminación del aire, concretamente del ozono, dentro de entornos urbanos. Nuestra propuesta utiliza smartphones como centro de la arquitectura, siendo estos dispositivos los encargados de leer los datos de un sensor móvil externo, y de luego enviar dichos datos a un servidor central para su procesamiento y tratamiento. Los resultados obtenidos demuestran que la orientación del sensor y el período de muestreo, dentro de ciertos límites, tienen muy poca influencia en los datos capturados. Con respecto a la contaminación acústica, proponemos una arquitectura para medir los niveles de ruido en entornos urbanos basada en crowdsensing, y cuya característica principal es que no requiere intervención del usuario. En esta tesis detallamos aspectos tales como la calibración de los smartphones, la calidad de las medidas obtenidas, el instante de muestreo, el diseño del servidor, y la interacción cliente-servidor. Además, hemos validado nuestra solución en escenarios reales para demostrar el potencial de la solución alcanzada. Los resultados experimentales muestran que, con nuestra propuesta, es posible medir niveles de ruido en diferentes zonas urbanas o rurales con un grado de precisión comparable al de los dispositivos profesionales, todo ello sin requerir intervención del usuario, y con un consumo reducido en cuanto a recursos del sistema. En general, las diferentes contribuciones de esta tesis doctoral ofrecen un punto de partida para nuevos desarrollos, ofreciendo estrategias de calibración y algoritmos eficientes de cara a realizar medidas representativas. Además, una importante ventaja de nuestra propuesta es que puede ser implementada de forma directa tanto en instituciones públicas como no gubernamentales en poco tiempo, ya que utiliza tecnología accesible y soluciones basadas en código abierto.
La contaminació ambiental és un dels principals problemes que afecten el nostre planeta. El creixement industrial i els aglomerats urbans, entre altres, estan contribuint al fet que aquest problema es diversifique i es cronifique. La presència de contaminants ambientals en nivells elevats afecta la salut humana, sent la qualitat de l'aire i els nivells de soroll exemples de factors que poden causar efectes negatius en les persones, tant psicològicament com fisiològicament. No obstant això, la ubiqüitat de les microcomputadores i l'augment dels sensors incorporats als nostres telèfons intel·ligents han fet possible l'aparició de noves estratègies per a mesurar aquesta contaminació. Així, el mobile crowdsensing s'ha convertit en un nou paradigma mitjançant el qual els telèfons intel·ligents emergeixen com a tecnologia habilitadora, i l'adopció generalitzada d'aquest proporciona un enorme potencial per al seu creixement, ja que permet operar a gran escala i amb uns costos assumibles per a la societat. A través del crowdsensing, els telèfons intel·ligents poden convertir-se en unitats de detecció flexibles i multiús que, a través dels sensors integrats en els esmentats dispositius, o combinats amb nous sensors, permeten monitoritzar regions d'interès amb una bona granularitat, tant espacial com temporal. En aquesta tesi ens centrem en el disseny de solucions de crowdsensing usant telèfons intel·ligents, on abordem problemes de contaminació ambiental, específicament del soroll i de la contaminació de l'aire. Amb aquest objectiu, s'estudien, en primer lloc, les propostes de crowdsensing que han sorgit en els últims anys. Els resultats del nostre estudi demostren que encara hi ha molta heterogeneïtat en termes de tecnologies utilitzades i mètodes d'implementació, encara que els dissenys modulars en el client i en el servidor semblen ser dominants. Pel que fa a la contaminació de l'aire, proposem una arquitectura que permeta mesurar la contaminació d'aquest, concretament de l'ozó, dins d'entorns urbans. La nostra proposta utilitza telèfons intel·ligents com a centre de l'arquitectura, sent aquests dispositius els encarregats de llegir les dades d'un sensor mòbil extern, i d'enviar després aquestes dades a un servidor central per al seu processament i tractament. Els resultats obtinguts demostren que l'orientació del sensor i el període de mostratge, dins de certs límits, tenen molt poca influència en les dades capturades. Pel que fa a la contaminació acústica, proposem una arquitectura per a mesurar els nivells de soroll en entorns urbans basada en crowdsensing, i la característica principal de la qual és que no requereix intervenció de la persona usuària. En aquesta tesi detallem aspectes com ara el calibratge dels telèfons intel·ligents, la qualitat de les mesures obtingudes, l'instant de mostratge, el disseny del servidor i la interacció client-servidor. A més, hem validat la nostra solució en escenaris reals per a demostrar el potencial de la solució assolida. Els resultats experimentals mostren que, amb la nostra proposta, és possible mesurar nivells de soroll en diferents zones urbanes o rurals amb un grau de precisió comparable al dels dispositius professionals, tot això sense requerir intervenció de l'usuari o usuària, i amb un consum reduït quant a recursos del sistema. En general, les diferents contribucions d'aquesta tesi doctoral ofereixen un punt de partida per a nous desenvolupaments, i ofereixen estratègies de calibratge i algorismes eficients amb vista a realitzar mesures representatives. A més, un important avantatge de la nostra proposta és que pot ser implementada de forma directa tant en institucions públiques com no governamentals en poc de temps, ja que utilitza tecnologia accessible i solucions basades en el codi obert.
Environmental pollution is one of the main problems that affect our planet. Industrial growth and urban agglomerations, among others, are contributing to the diversification and chronification of this problem. The presence of environmental pollutants at high levels affect human health, with air quality and noise levels being examples of factors that can cause negative effects on people both psychologically and physiologically. Traditionally, environmental pollution is measured through monitoring centers, which are usually fixed and have a high cost. However, the ubiquity of microcomputers and the increase in the number of sensors embedded in our smartphones, have paved the way for the appearance of new strategies to measure such pollution. Thus, Mobile Crowdsensing has become a new paradigm through which smartphones emerge as an enabling technology, and whose widespread adoption provides enormous potential for growth, allowing large-scale operations, and with costs acceptable to our society. Through crowdsensing, smartphones can become flexible and multipurpose detection units that, through the sensors integrated into these devices, or combined with new sensors, allow monitoring regions of interest with good spatial and temporal granularity. In this thesis, we focus on the design of crowdsensing solutions using smartphones. We deal with environmental pollution problems, specifically noise and air pollution. With this objective, the crowdsensing proposals that have emerged in recent years are studied in the first place. The results of our study show that there is still a lot of heterogeneity in terms of technologies used and implementation methods, although modular designs at both client and server seem to be dominant. Concerning air pollution, we propose an architecture that allows measuring air pollution, specifically ozone, in urban environments. Our proposal uses smartphones as the center of the architecture, being these devices responsible for reading the data obtained by an external mobile sensor, and then sending such data to a central server for processing and analysis. In this proposal, several problems have been analyzed with regard to the orientation of the external sensor and the sampling time, and the proposed solution has been validated in real scenarios. The results obtained show that the orientation of the sensor and the sampling period, within certain limits, have very little influence on the captured data. Also, by comparing the heat maps generated by our solution with the data from the existing monitoring stations in the city of Valencia, we demonstrate that our approach is capable of providing greater data granularity. Concerning noise pollution, we propose an architecture to measure noise levels in urban environments based on crowdsensing, and whose main characteristic is that it does not require user intervention. In this thesis, we detail aspects such as the calibration of smartphones, the quality of the measurements obtained, the sampling instant, the server design, and the client-server interaction. Besides, we have validated our solution in real scenarios to demonstrate the potential of the proposed solution. Experimental results show that, with our proposal, it is possible to measure noise levels in different urban or rural areas with a degree of precision comparable to that of professional devices, all without requiring the intervention of the user, and with reduced consumption of system resources. In general, the different contributions of this doctoral thesis provide a starting point for new developments, offering efficient calibration strategies and algorithms to make representative measurements. Besides, a significant advantage of our proposal is that it can be implemented straightforwardly by both public and non-governmental institutions in a short time, as it relies on accessible technology and open source software
Zamora Mero, WJ. (2018). Crowdsensing solutions for urban pollution monitoring using smartphones [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/115483
TESIS

1.1\xWith the emphasis on particulate matter (PM) and persistent organic pollutants (POPs) from uncontrolled sources, this study focused on the ambient air pollution of e-waste recycling regions and the indoor air quality of urban areas in South China.;1.2\xIn the past decades, severe PM and POPs pollutions were recorded in e-waste recycling regions in China. Since the 2010s, more effective measures, stricter regulations and sophisticated dismantling technologies have been implemented in Guiyu and Qingyuan by local authorities. In this study, total suspended particles (TSP), fine particles (PM2.5), gas phase samples, and indoor settled dust were collected simultaneously in the primary recycling areas as well as reference sites in Guiyu and Qingyuan in August, 2013. The results showed that both PM, PCDD/Fs (polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans) , PBDEs (polybrominated diphenyl ethers) and PCBs (polychlorinated biphenyls) in ambient air showed significantly reduced levels in the regions, compared with the former corresponding reports. The changed source patterns of the POPs confirmed the environmental effects of the implementation of stricter regulation and advanced technologies in these years. Nevertheless, the remained uncontrolled e-waste recycling activities in Guiyu, including plastics recycling and circuit board baking, still made significant influence to the air environment and resulted in alarming levels of PCDD/Fs (0.73~2.43 pg I-TEQ/m3) in the recycling areas. While in Qingyuan, high environmental PCBs burden was observed both in informal (1737 pg/m3) and formal recycling areas (1075 pg/m3), which could attribute to the uncontrolled dismantling of PCB-contained transformers. The estimated non-cancer risk for children and adults in the recycling regions were 2.7~25.2 and 1.2~3.2, respectively, and moderate cancer risk were found for the residents living in the recycling regions of Guiyu and the vicinage of the formal recycing factory (CR>10-4). The unacceptable estimated risk for both children and adults suggested unsafe air environments in the two recycling regions.;1.4\xCollectively, our results suggest unsatisfactory air quality in both e-waste recycling regions and common urban areas. The air problems could both attribute to the uncontrolled sources of the related spaces. The obtained results firstly indicated that a long way to solve e-waste issues and more effective measures are needed to control the contaminants release and the exposure to the local residents. Secondly, indoor air quality standard for fine particulate matters as well as associated toxicants such as PAHs is urgently needed to guide common populations and communities.;1.5\xKeywords: Air pollution; E-waste recycling; Urban areas; Indoor air; Ambient air; PM2.5; Persistent organic pollutants; Health risk assessment

Master of Regional and Community Planning
Department of Landscape Architecture/Regional and Community Planning
Brent Chamberlain
Air pollution is a serious health and environmental problem. In fact, poor air quality has been linked to numerous diseases and is a significant public health issue related to urban planning. These problems can be clearly seen in urban Chinese cities, most recently with the first ever Red Alert in Beijing China in 2015. In 2015, director Chai Jing developed a documentary depicting the bad effects on health of air pollution in China. However, soon after the release of the film, it was banned. One important finding in the film was the misperception the Chinese people had about the kinds of pollution and the health impacts. Therefore, this study aims to investigate the extent to which Chinese people understand the causes of air pollution and their related health effects. Accordingly, a survey was produced and delivered via Chinese social medium. The survey had three objectives: study the perception of 1) Air quality and the source of air pollution, 2) Health effects if air pollution, and 3) Air pollution and Environmental policies. The results show that 44% Chinese people feel air quality is worse now than a year before, and 72% people feel air pollution has affected their health. One main finding in this study was that younger people took the survey more than older people, as perhaps because they may have started to have a family or become a family; this is significant because air pollution is harmful for children. The other main finding was that 52% people did not know a China Air Pollution and Prevention Law exists.

Rapid and unplanned urbanization has ushered in a variety of public health challenges, including exposure to traffic pollution and greater dependence on automobiles. Moreover, vulnerable population groups often bear the brunt of negative outcomes and are subject to disproportionate exposure and health effects. This makes it imperative for urban transportation engineers, land use planners, and public health professionals to work synergistically to understand both the relationship between urban design and population exposure to traffic pollution, and its social distribution. Researchers have started to pay close attention to this connection, mainly by conducting observational studies on the relationship between transportation, urban form, and air quality. However, research on this topic is still nascent. Further, most studies do not predict exposures under alternative urban design scenarios. Hence, to understand the relationship between urban design and population exposures, there is a need to build and apply integrated modeling tools that can predict exposures under alternative urban design scenarios. Within this context, the overarching goal of this dissertation is to understand how the transportation infrastructure of cities can be designed for improved urban air quality and mitigation of population exposure to traffic pollution. The study area is Hillsborough County, Florida, a sprawling region with limited transit availability and a diverse population along with a mix of urban, suburban, and rural areas. The rank of the county for sprawl and congestion metrics (i.e., yearly delay and travel time index) fall in the mid-range in comparison with other US urban regions. Thus, the study area may be representative of other US urban regions with medium sprawl and above-average congestion levels. Oxides of nitrogen (NOx), a surrogate for traffic pollution, is the focus pollutant. The Health Effects Institute’s report on traffic-related air pollution identifies NOx as a potential surrogate due to its relative ease of measurement and the abundance of epidemiologic studies that characterize exposures to NOx. Because exposures are dependent on the spatial and temporal distributions of both people and pollution, this study first sought to understand the importance of activity and travel patterns of individuals for exposure estimation. To estimate exposures, the 2009 National Household Travel Survey (NHTS) data containing daily individual activity records, ArcGIS-estimated shortest-time travel route profiles, and the annual-average diurnal cycle of NOx derived from hourly CALPUFF dispersion model results from 2002, were combined. Two exposure measures were estimated: activity-based exposure that considers the daily activity and travel patterns of individuals, and residence-based exposure that considers only the pollutant concentrations at the residences. Exposure estimation without inclusion of activity and travel patterns was found to slightly underestimate activity-based exposures on average. Additionally, disproportionately-high exposures were found for blacks, Hispanics, below poverty groups, urban residents, and people whose daily travel time is greater than one hour. Finally, urbanicity and travel time variables were found to be the strongest predictors of daily exposure. Following this, a modeling framework was developed to predict population exposure by integrating activity-based travel demand modeling (DaySim), dynamic traffic assignment simulation (MATSim), mobile-source emission estimation (EPA MOVES), and pollutant dispersion modeling (R LINE). This modeling framework was used to predict daily population and subgroup exposures by estimating the high-resolution spatial and temporal distributions of both pollution and individual activities for the year 2010. Persistent exposure inequalities were found at the population-level; blacks, Hispanics, active age groups (19-65 years), below-poverty and middle-income groups, urban residents, and individuals with daily travel times above one hour had higher estimated exposures than the population mean. These inequalities for blacks, Hispanics, and below-poverty non-white groups worsened at higher exposure levels. Use of low-resolution activity and pollution data as opposed to high-resolution data led to underestimation of exposures (by 10% on average). Finally, the integrated modeling framework was employed to understand the relationship between urban transportation and land use design, air quality, and population exposure. Three scenarios that are based on a combination of diesel-bus transit services and residential distribution were simulated. Specifically, the low-transit scenario used the 2040 base residential distribution and the 2010 bus services. The enhanced-transit scenario applied the 2040 bus services proposed for the county instead. The compact-growth scenario added an increase of residential density to this latter scenario. Specifically, about 37% of total households were redistributed from locations with low accessibility to jobs and transit to locations near employment and bus stops. Results indicate slight higher non-car travel mode shares in the enhanced-transit and compact-growth scenarios compared to the low-transit scenario (with a 7.1% increase for walking, 0.2% for bicycle, and 1.8% for transit for the compact-growth scenario versus the low-transit scenario). The enhanced-transit scenario resulted in slightly lower daily total travel distances and times compared with the low-transit scenario, but daily total emissions and winter mean concentration of NOx were higher, i.e., the increase in bus transit services did not induce sufficient shifts in travel mode to overcome the concomitant increase in diesel-bus emissions. The compact-growth scenario resulted in lower daily total travel distance (9%) and travel time (2.1%) and daily total emissions of NOx (11%) and its winter mean concentration (9%), compared with both the low-transit and enhanced-transit scenarios. Although the compact-growth scenario improved the air quality of the region on average, daily population mean exposure was higher compared with both the low-transit (29%) and enhanced-transit scenarios (25%). This is largely due to the redistribution of population to urban core locations that had higher pollutant levels. Overall, neither the bus-transit improvements nor residential compaction strategies alone were sufficient to mitigate population exposures. Combining them with transit that services both origins and destinations, uses clean fuel technologies, and separates major roadways from dense residential pockets may be needed for greater exposure reductions. Overall, this dissertation has implications for population exposure to traffic pollution and public health through transportation and land use interventions. Results presented here may be applicable to other study regions that have similar composite sprawl scores as the Tampa Bay area. Future studies should exploit spatially-and temporally-resolved data on human activities and travel, vehicular activities, and air quality for better characterization of population exposure. Engineers and planners should pay greater attention to integrated land use and transport planning; lone, disjointed, and ill-planned design interventions may exacerbate population exposure to air pollution. The integrated modeling framework presented here may be applied in a wide variety of urban contexts to further explore the nexus between travel demand, air quality, and exposures. However, before such an exercise is undertaken, a preliminary analysis should be conducted to assess the transferability of the framework. Policies that could be studied include mixed land use design, urban compaction with controlled sociodemographic distributions (to assess exposure inequality), and inclusion of additional types of transit and fuel technologies.

The control of atmospheric pollution in the urban environment has, in recent years, taken on important local, national and international significance. Legislation has been introduced in many countries to improve air quality in urban areas. Monitoring air pollution is an important part of understanding and improving air quality. Current standard methods of measuring air pollution only monitor at a single point in space which can lead to ambiguities when assessing air quality over an extended region, such as a city centre or a road intersection. Optical remote sensing techniques, such as long path Fourier transform absorption spectroscopy, overcome the limitations of point measurements by integrating over long paths and thus measuring the average ambient pollutant concentrations. A commercially available Fourier transform infrared (FTIR) spectrometer, together with custom built external optics has been used to make measurements of air pollution in Oxford city centre. It has been shown that it is possible to measure the concentrations of several pollutants simultaneously and in short measurement times. Issues relating to the performance of the spectrometer have been studied, their effects quantified and solutions proposed. Optimal estimation techniques have been applied to the analysis of the single beam spectra recorded by the FTIR spectrometer. This technique has previously only been applied to radiance and transmission spectra and so extensions were necessary. High resolution laboratory measurements of the absorption cross-sections of benzene and 1,3-butadiene have been made and the potential for detecting them in ambient urban air determined.

The resuspension of road dust has been recognised as a source of airborne particulate matter, but little information exists as to the strength of this source or to the factors affecting it, particularly in relation .to the United Kingdom This study has focused on determining emission rates for wind-induced road dust resuspension from a tarmac surface for a range of wind speeds, including an unsteady 'gusty' flow. A wind tunnel has been used to generate a boundary-layer flow above a tarmac surface. The flow generated has been compared to that occurring close to a tarmac airport runway and the two are found to be comparable. This has enabled realistic measurements of the resuspension of a tracer dust from the tarmac surface in the wind tunnel for a range of wind speeds. Full-scale measurements have also been made of the flow occurring very close to a tarmac surface during the passage a vehicle. Qualitatively similar gusts to those generated by a vehicle have been generated in a small wind tunnel and these gusts have been shown to significantly increase resuspension. The spatial and temporal variability of the road dust loading for a number of roads in Birmingham has been investigated throughout an entire year. The dust loading at all sites is found to be very stable suggesting that road dust resuspension is in equilibrium with dust deposition to the road surface. The average road dust loading for the roads studied was found to be O.16g m-2 • Using the results of this study a rough estimate of the annual wind-induced UK road dust emissions has been found as 1.9 kilotonnes. This figure does not include the considerable contribution to road dust emissions made by vehicle-induced resuspension.

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2004.
Includes bibliographical references (leaves 83-85).
(cont.) over time as pollution levels change. Using these new models, we valued the economic benefit of reduced air pollution due to the Clean Air Act regulations to be over $7 trillion from 1970 to 2000, or 2.1% of aggregate US economic welfare over the period. This does not include the benefits into the future (after 2000) from reduction in mortality due chronic exposure during these years. The economic benefit of those saved mortalities is another $7 trillion using a 3% discount rate. Another calculation is the remaining economic burden of unmitigated pollution levels (actual historical pollution). We estimate this to be approximately $9 trillion over the same period. The $9 trillion burden includes the early mortalities due to chronic exposure to PM before and during this period. While these economic benefits of air pollution regulation are large ($7 trillion), they are considerably less than the $27.6 trillion estimated in EPAs own analysis of the benefits of air pollution regulation. The main difference for our lower estimate is the stock-flow accounting of mortality due to chronic exposure. There are considerable uncertainties in these estimates both because of uncertainties in the relationship between air pollution exposure and the health effects, and in the assumptions needed to value these effects.
In the last 30 to 40 years, an increasing awareness of the link between urban air pollutant levels and negative health effects have led to numerous studies and policies that are targeted towards both understanding the linkage and mitigating its effects. In 1970, the Environmental Protection Agency (EPA) created the Clean Air Act directed at reducing harmful emissions that cause high pollution levels in urban areas. Ever since then, environmental economists and policy makers have attempted to better understand the economic impacts of these regulations through cost and benefit analysis. Towards that end, we have developed a methodology for fully integrating the health effects from exposure to air pollution into a computable general equilibrium economic model. This model represents the first attempt at fully incorporating the economic valuation of air pollution in an integrated economic model that has endogenously built-in consumer demand and preference curves to accurately represent the demand for air pollution health. This framework provides a way to consistently value effects with commonly used approaches for valuing costs of mitigation and to explore uncertainties in these estimates. Furthermore, we also describe a new stock and flow model to track the extra mortalities from chronic exposure to particulate matters. Past frameworks have assumed an immediate relationship between pollution levels and mortality levels. While this is true for mortality due to acute exposure, changes in mortalities from chronic exposure due to a change in pollution levels are only gradually realized and so the full effects on the economy are observed for many years. This new framework allows the tracking of total pollution in-take and its effect on mortality levels
by Trent Yang.
S.M.

Urban airborne particulate matter (PM) is known to increase morbidity and mortality due to cardiopulmonary diseases related to inflammatory processes and genotoxic effects. The aim of this thesis is to highlight the toxic and carcinogenic potential of airborne particulate matters collected during different seasons at a site that is located in the northern area of the city of Bologna by using alternative in vitro tests, such as the cell transformation assay with BALB/c 3T3 A31-1-1 and Bhas 42 cells. The purpose is also to evaluate the lifetime cancer risks associated with air inhalation in different sites (rural and urban), by using the relative potency of compounds belonging to the same chemical class (PAHs and nitro-PAHs) and the specific unit of carcinogenic risk. None of the organic or inorganic extracts of PM2.5 and PM1 induced a significant increase in the average number of transformed foci/plate or in the transformation frequency of BALB/c 3T3 A311-1 cells, whereas the results obtained by Bhas 42 cell transformation showed a significant increase in the average number of transformed foci/plate. All the analyzed organic extracts showed promoting effects in Bhas 42 cells. The application of the UR cancer risk to the transformed value of B(a)P equivalents in the winter– autumn campaigns leads to estimate an increase in the cancer risk similar to that defined in the literature (1 x 10-4 for exposure to 1 ng/m3). The calculated cancer risk was about one order of magnitude lower in the summer campaigns. In conclusion, the proposed approach, based on the integration of the data derived from in vitro testing and cancer risk assessment, could represent a reliable model for investigating environmental mixtures and predicting their effects on toxicological relevant endpoints.

Urban airborne particulate matter (PM) is known to increase morbidity and mortality due to cardiopulmonary diseases related to inflammatory processes and genotoxic effects. The aim of this thesis is to highlight the toxic and carcinogenic potential of airborne particulate matters collected during different seasons at a site that is located in the northern area of the city of Bologna by using alternative in vitro tests, such as the cell transformation assay with BALB/c 3T3 A31-1-1 and Bhas 42 cells. The purpose is also to evaluate the lifetime cancer risks associated with air inhalation in different sites (rural and urban), by using the relative potency of compounds belonging to the same chemical class (PAHs and nitro-PAHs) and the specific unit of carcinogenic risk. None of the organic or inorganic extracts of PM2.5 and PM1 induced a significant increase in the average number of transformed foci/plate or in the transformation frequency of BALB/c 3T3 A311-1 cells, whereas the results obtained by Bhas 42 cell transformation showed a significant increase in the average number of transformed foci/plate. All the analyzed organic extracts showed promoting effects in Bhas 42 cells. The application of the UR cancer risk to the transformed value of B(a)P equivalents in the winter– autumn campaigns leads to estimate an increase in the cancer risk similar to that defined in the literature (1 x 10-4 for exposure to 1 ng/m3). The calculated cancer risk was about one order of magnitude lower in the summer campaigns. In conclusion, the proposed approach, based on the integration of the data derived from in vitro testing and cancer risk assessment, could represent a reliable model for investigating environmental mixtures and predicting their effects on toxicological relevant endpoints.