Estimativa das emissões de monóxido de carbono por veículos automotivos na cidade de Campinas/SP utilizando o modelo CAL3QHCR

Air pollution is an environmental issue worldwide and frequently cause negative effects on population health and ecosystems on cities. The relationship between climate and atmospheric pollution can be used as a surrogate to the intensity of air pollution. The present and quantity of some gases can be used as indicators to air quality: particulate matter (PM), sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), and nitrogen dioxide (NO2). Among those gases, CO has its major source within the cities, where automobiles are the main emitter. But measure pollutant concentration are challenging, sometimes because the lack of good equipments due to high costs and of the large variability of models that varies in precision, way of measure and distribution of sellers. Modeling are useful when there are an intend to evaluate air pollution, its sources and evaluate scenarios. This work aims to use CAL3QHCR model developed by the U.S Environmental Protection Agency (EPA) to generate predictive surfaces of CO concentration distribution on a site within Campinas city, located in São Paulo state, Brazil. CAL3QHCR model use data urban automobile circulation to generate spatial results for CO distribution. We observed that the pollution concentration was lower on our modeling than the concentrations measured by Companhia Ambiental do Estado de São Paulo (CETESB), the main environmental company on the São Paulo state. Also the correlation between average estimates of our model and the measure by CETESB was weak, indicating that the model used on this study need to be or better parameterized, or the scale we measured of CO emissions need to be rescaled. Although the model failed to correlate to CETESB data, maybe one that explore the estimated emissions distributed within the sites to understand spatial distributions of CO on the regions. Also, the generated information can also be used to other studies, and come to be useful to explain heat island

Fenologia reprodutiva e distribuição espacial de Oeceoclades maculata (Lindl.) Lindl. (Orchidaceae) em Cerrado do município de Mogi Guaçu, São Paulo, Brasil

Oeceoclades aculate (Lindl.) Lindl., an invasive orchid, was analyzed as to its reproductive phenology and spatial distribution, correlation between abundance of mature and immature individuals, and verifying these with microclimate patterns in the Cerrado (savanna-like vegetation) of Mogi Guacu, Sao Paulo State, Brazil. For the reproductive phenology 100 plants were followed and the distribution pattern was identified by the Morisita Index (MI) and the Variance Ratio/Average (R) in 20 plots of 20x10m, reduced to 10x10m afterwards. The phenology presented seasonality, with flowering from November to February, fructification from February to June, and dehiscence from June to July. Mature and immature individuals aggregated and correlated to each other, indicating dependence between the ontogenetic stages. The luminosity was the preponderant microclimatic factor in the allocation of plants. Seasonal climatic changes and intensity of anthropogenic disturbances seem to be more important for the establishment of the species than microclimate.

Admissions due to pneumonia and biomass burning: a spatial approach

Objective: To identify spatial patterns in rates of admission for pneumonia among children and relate them to the number of fires reported in the state of Mato Grosso, Brazil. Methods: We conducted an ecological and exploratory study of data from the state of Mato Grosso for 2008 and 2009 on hospital admissions of children aged 0 to 4 years due to pneumonia and on fires in the same period. Admission rates were calculated and choropleth maps were plotted for rates and for fire outbreaks, Moran's I was calculated and the kernel estimator used to identify "hotspots." Data were analyzed using TerraView 3.3.1. Results: Fifteen thousand six hundred eighty-nine children were hospitalized (range zero to 2,315), and there were 161,785 fires (range 7 to 6,454). The average rate of admissions per 1,000 inhabitants was 2.89 (standard deviation [SD] = 5.18) and the number of fires per 1,000 inhabitants was 152.81 (SD = 199.91). Moran's I for the overall number of admissions was I = 0.02 (p = 0.26), the index for rate of admission was I = 0.02 (p = 0.21) and the index for the number of fires was I = 0.31 (p < 0.01). It proved possible to identify four municipalities with elevated rates of admissions for pneumonia. It was also possible to identify two regions with high admission densities. A clustering of fires was evident along what is known as the "arc of deforestation." Conclusions: This study identified municipalities in the state of Mato Grosso that require interventions to reduce rates of admission due to pneumonia and the number fires.

Tráfego veicular e mortalidade por doenças do aparelho circulatório em homens adultos

OBJETIVO: Analisar a associação entre indicadores de exposição à poluição por tráfego veicular e mortalidade por doenças do aparelho circulatório em homens adultos. MÉTODOS: Foram analisadas informações sobre vias e volume de tráfego no ano de 2007 fornecidas pela companhia de engenharia de tráfego local. Mortalidade por doenças do aparelho circulatório no ano de 2005 entre homens ≥ 40 anos foram obtidas do registro de mortalidade do Programa de Aprimoramento de Informações de Mortalidade do Município de São Paulo, SP. Dados socioeconômicos do Censo 2000 e informações sobre a localização dos serviços de saúde também foram coletados. A exposição foi avaliada pela densidade de vias e volume de tráfego para cada distrito administrativo. Foi calculada regressão (α = 5%) entre esses indicadores de exposição e as taxas de mortalidade padronizadas, ajustando os modelos para variáveis socioeconômicas, número de serviços de saúde nos distritos e autocorrelação espacial. RESULTADOS: A correlação entre densidade de vias e volume de tráfego foi modesta (r² = 0,28). Os distritos do centro apresentaram os maiores valores de densidade de vias. O modelo de regressão espacial de densidade de vias indicou associação com mortalidade por doenças do aparelho circulatório (p = 0,017). Não se observou associação no modelo de volume de tráfego. Em ambos os modelos – vias e volume de tráfego (veículos leves/pesados) – a variável socioeconômica foi estatisticamente signifi cante. CONCLUSÕES: A associação entre mortalidade por doenças do aparelho circulatório e densidade de vias converge com a literatura e encoraja a realização de mais estudos epidemiológicos em nível individual e com métodos mais acurados de avaliação da exposição.

Desigualdade social no adoecimento e morte por câncer de boca e orofaríngeo no Município de São Paulo, Brasil: 1997 a 2008

A ocupação do espaço geográfico é determinada historicamente pelo modelo socioeconômico e pelo dinamismo de suas relações sociais, políticas e ideológicas. O objetivo deste trabalho é avaliar a distribuição espacial e o efeito de indicadores socioeconômicos no adoecimento e morte por câncer de boca e orofaríngeo no Município de São Paulo, Brasil, no período de 1997 a 2008. Os dados foram coletados no Registro de Câncer de Base Populacional e no Programa de Aprimoramento das Informações de Mortalidade - PRO-AIM e georreferenciados pelos softwares Terraview e GeoDa. O referencial teórico para avaliação dos resultados foi baseado na teoria de Milton Santos. As taxas de incidência apresentaram um índice de autocorrelação Global de Moran de 0,226 e as taxas de mortalidade de 0,337. A Incidência de câncer de boca e orofaríngeo não apresenta um padrão espacial bem definido no Município de São Paulo, mas é bastante desigual no que se refere à Mortalidade, concentrando as suas menores taxas na área central, mais rica e economicamente menos desigual.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Urban forest health survey on Roznik in Ljubljana in 2013 by two methods

Urban forest health was surveyed on Roznik in Ljubljana (46.05141 N, 14.47797 E) in 2013 by two methods: ICP Forests and UFMO. ICP Forests is most commonly used monitoring programme in Europe - the International Co-operative Programme on the Assessment and Monitoring of Air Pollution Effects on Forests, which is based on systematic grid. UFMO method - Urban Forests Management Oriented method was developed in the frame of EMoNFUr Project - Establishing a monitoring network to assess lowland forest and urban plantations in Lombardy and urban forest in Slovenia (LIFE10 ENV/IT/000399). UFMO is based on non-linear transects (GPS tracks). ICP forests monitoring plots were established in July 2013 in the urban forest Roznik in Ljubljana .The 32 plots are located on sampling grid 500 × 500 m. The grid was down-scaled from the National Forest Monitoring survey, which bases on national sample grid 4 × 4 km. With the ICP forests method the following parameters for each tree within the 15 plots were gathered according to the ICP forests manual for Visual assessment of crown condition and damaging agents: tree species, percentage of defoliation, affected part of the tree, specification of affected part, location in crown, symptom, symptom specification, causal agents / factors, age of damage, damage extent, and damage extent on the trunk. With the UFMO method, the following parameters for each tree that needed sylviculture measure (felling, pruning, sanitary felling, thinning, etc.) were recorded: tree species, breast diameter, causal agent / damaging factor, GPS waypoint and GPS track. For overall picture in the urban forest health problems, also other biotic and abiotic damaging factors that did not require management action were recorded.

A Multiresolution Image Alignment Technique Based on Direct Methods for Pose Estimation of Aerial Vehicles

In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi-Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles' state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle's state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle's state for more than one minute, at real-time frame rates based, only on visual information.

Human Mobility, Exposure to the Built Environment, and Health

Thesis (Ph.D.)--University of Washington, 2016-06

Avaliação de sensores de baixo custo e de métodos de referência para a monitorização da qualidade do ar

A crescente urbanização global tem como consequência o aumento dos níveis de poluentes na atmosfera e a respetiva deterioração da qualidade do ar. O controlo da poluição atmosférica e monitorização da qualidade do ar são passos fundamentais para implementar estratégias de redução e estimular a consciência ambiental dos cidadãos. Com este intuito, existem várias técnicas e tecnologias que podem ser usadas para monitorizar a qualidade do ar. A utilização de microsensores surge como uma ferramenta inovadora para a monitorização da qualidade do ar. E, apesar dos desempenhos dos microsensores permitirem uma nova estratégia, resultando em respostas rápidas, baixos custos operacionais e eficiências elevadas, que não podem ser alcançados apenas com abordagens convencionais, ainda é necessário aprofundar o conhecimento a fim de integrar estas novas tecnologias, particularmente quanto à verificação do desempenho dos sensores comparativamente aos métodos de referência em campanhas experimentais. Esta dissertação, desenvolvida no Instituto do Ambidente e Desenvolvimento em forma de estágio, teve como objetivo a avaliação do desempenho de sensores de baixo custo comparativamente com os métodos de referência, tendo como base uma campanha de monitorização da qualidade do ar realizada no centro de Aveiro durante 2 semanas de outubro de 2014. De forma mais específica pretende-se perceber até que ponto se podem utilizar sensores de baixo custo que cumpram os requisitos especificados na legislação e as especificidades das normas, estabelecendo assim um protocolo de avaliação de microsensores. O trabalho realizado passou ainda pela caracterização da qualidade do ar no centro de Aveiro para o período da campanha de monitorização. A aplicação de microsensores eletroquímicos, MOS e OPC em paralelo com equipamento de referência neste estudo de campo permitiu avaliar a fiabilidade e a incerteza destas novas tecnologias de monitorização. Com este trabalho verificou-se que os microsensores eletroquímicos são mais precisos comparativamente aos microsensores baseados em óxidos metálicos, apresentando correlações fortes com os métodos de referência para diversos poluentes. Por sua vez, os resultados obtidos pelos contadores óticos de partículas foram satisfatórios, contudo poderiam ser melhorados quer pelo modo de amostragem, quer pelo método de tratamento de dados aplicado. Idealmente, os microsensores deveriam apresentar fortes correlações com o método de referência e elevada eficiência de recolha de dados. No entanto, foram identificados alguns problemas na eficiência de recolha de dados dos sensores que podem estar relacionados com a humidade relativa e temperaturas elevadas durante a campanha, falhas de comunicação intermitentes e, também, a instabilidade e reatividade causada por gases interferentes. Quando as limitações das tecnologias de sensores forem superadas e os procedimentos adequados de garantia e controlo de qualidade possam ser cumpridos, os sensores de baixo custo têm um grande potencial para permitir a monitorização da qualidade do ar com uma elevada cobertura espacial, sendo principalmente benéfico em áreas urbanas.

Avaliação de sensores de baixo custo e de métodos de referência para a monitorização da qualidade do ar

A crescente urbanização global tem como consequência o aumento dos níveis de poluentes na atmosfera e a respetiva deterioração da qualidade do ar. O controlo da poluição atmosférica e monitorização da qualidade do ar são passos fundamentais para implementar estratégias de redução e estimular a consciência ambiental dos cidadãos. Com este intuito, existem várias técnicas e tecnologias que podem ser usadas para monitorizar a qualidade do ar. A utilização de microsensores surge como uma ferramenta inovadora para a monitorização da qualidade do ar. E, apesar dos desempenhos dos microsensores permitirem uma nova estratégia, resultando em respostas rápidas, baixos custos operacionais e eficiências elevadas, que não podem ser alcançados apenas com abordagens convencionais, ainda é necessário aprofundar o conhecimento a fim de integrar estas novas tecnologias, particularmente quanto à verificação do desempenho dos sensores comparativamente aos métodos de referência em campanhas experimentais. Esta dissertação, desenvolvida no Instituto do Ambidente e Desenvolvimento em forma de estágio, teve como objetivo a avaliação do desempenho de sensores de baixo custo comparativamente com os métodos de referência, tendo como base uma campanha de monitorização da qualidade do ar realizada no centro de Aveiro durante 2 semanas de outubro de 2014. De forma mais específica pretende-se perceber até que ponto se podem utilizar sensores de baixo custo que cumpram os requisitos especificados na legislação e as especificidades das normas, estabelecendo assim um protocolo de avaliação de microsensores. O trabalho realizado passou ainda pela caracterização da qualidade do ar no centro de Aveiro para o período da campanha de monitorização. A aplicação de microsensores eletroquímicos, MOS e OPC em paralelo com equipamento de referência neste estudo de campo permitiu avaliar a fiabilidade e a incerteza destas novas tecnologias de monitorização. Com este trabalho verificou-se que os microsensores eletroquímicos são mais precisos comparativamente aos microsensores baseados em óxidos metálicos, apresentando correlações fortes com os métodos de referência para diversos poluentes. Por sua vez, os resultados obtidos pelos contadores óticos de partículas foram satisfatórios, contudo poderiam ser melhorados quer pelo modo de amostragem, quer pelo método de tratamento de dados aplicado. Idealmente, os microsensores deveriam apresentar fortes correlações com o método de referência e elevada eficiência de recolha de dados. No entanto, foram identificados alguns problemas na eficiência de recolha de dados dos sensores que podem estar relacionados com a humidade relativa e temperaturas elevadas durante a campanha, falhas de comunicação intermitentes e, também, a instabilidade e reatividade causada por gases interferentes. Quando as limitações das tecnologias de sensores forem superadas e os procedimentos adequados de garantia e controlo de qualidade possam ser cumpridos, os sensores de baixo custo têm um grande potencial para permitir a monitorização da qualidade do ar com uma elevada cobertura espacial, sendo principalmente benéfico em áreas urbanas.

Development of a particle number and particle mass emissions inventory for an urban fleet : a study in South-East Queensland

Motor vehicles are a major source of gaseous and particulate matter pollution in urban areas, particularly of ultrafine sized particles (diameters < 0.1 µm). Exposure to particulate matter has been found to be associated with serious health effects, including respiratory and cardiovascular disease, and mortality. Particle emissions generated by motor vehicles span a very broad size range (from around 0.003-10 µm) and are measured as different subsets of particle mass concentrations or particle number count. However, there exist scientific challenges in analysing and interpreting the large data sets on motor vehicle emission factors, and no understanding is available of the application of different particle metrics as a basis for air quality regulation. To date a comprehensive inventory covering the broad size range of particles emitted by motor vehicles, and which includes particle number, does not exist anywhere in the world. This thesis covers research related to four important and interrelated aspects pertaining to particulate matter generated by motor vehicle fleets. These include the derivation of suitable particle emission factors for use in transport modelling and health impact assessments; quantification of motor vehicle particle emission inventories; investigation of the particle characteristic modality within particle size distributions as a potential for developing air quality regulation; and review and synthesis of current knowledge on ultrafine particles as it relates to motor vehicles; and the application of these aspects to the quantification, control and management of motor vehicle particle emissions. In order to quantify emissions in terms of a comprehensive inventory, which covers the full size range of particles emitted by motor vehicle fleets, it was necessary to derive a suitable set of particle emission factors for different vehicle and road type combinations for particle number, particle volume, PM1, PM2.5 and PM1 (mass concentration of particles with aerodynamic diameters < 1 µm, < 2.5 µm and < 10 µm respectively). The very large data set of emission factors analysed in this study were sourced from measurement studies conducted in developed countries, and hence the derived set of emission factors are suitable for preparing inventories in other urban regions of the developed world. These emission factors are particularly useful for regions with a lack of measurement data to derive emission factors, or where experimental data are available but are of insufficient scope. The comprehensive particle emissions inventory presented in this thesis is the first published inventory of tailpipe particle emissions prepared for a motor vehicle fleet, and included the quantification of particle emissions covering the full size range of particles emitted by vehicles, based on measurement data. The inventory quantified particle emissions measured in terms of particle number and different particle mass size fractions. It was developed for the urban South-East Queensland fleet in Australia, and included testing the particle emission implications of future scenarios for different passenger and freight travel demand. The thesis also presents evidence of the usefulness of examining modality within particle size distributions as a basis for developing air quality regulations; and finds evidence to support the relevance of introducing a new PM1 mass ambient air quality standard for the majority of environments worldwide. The study found that a combination of PM1 and PM10 standards are likely to be a more discerning and suitable set of ambient air quality standards for controlling particles emitted from combustion and mechanically-generated sources, such as motor vehicles, than the current mass standards of PM2.5 and PM10. The study also reviewed and synthesized existing knowledge on ultrafine particles, with a specific focus on those originating from motor vehicles. It found that motor vehicles are significant contributors to both air pollution and ultrafine particles in urban areas, and that a standardized measurement procedure is not currently available for ultrafine particles. The review found discrepancies exist between outcomes of instrumentation used to measure ultrafine particles; that few data is available on ultrafine particle chemistry and composition, long term monitoring; characterization of their spatial and temporal distribution in urban areas; and that no inventories for particle number are available for motor vehicle fleets. This knowledge is critical for epidemiological studies and exposure-response assessment. Conclusions from this review included the recommendation that ultrafine particles in populated urban areas be considered a likely target for future air quality regulation based on particle number, due to their potential impacts on the environment. The research in this PhD thesis successfully integrated the elements needed to quantify and manage motor vehicle fleet emissions, and its novelty relates to the combining of expertise from two distinctly separate disciplines - from aerosol science and transport modelling. The new knowledge and concepts developed in this PhD research provide never before available data and methods which can be used to develop comprehensive, size-resolved inventories of motor vehicle particle emissions, and air quality regulations to control particle emissions to protect the health and well-being of current and future generations.

Estimating the effects of environmental exposures using a weighted mean of monitoring stations

The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.