Operational short term health impact assessment of air pollution modelling system over Europe

The last decade, scientific studies have indicated an association between air pollution to which people are exposed and wide range of adverse health outcomes. We have developed a tool which is based on a model (MM5-CMAQ) running over Europe with 50 km spatial resolution, based on EMEP annual emissions, to produce a short-term forecast of the impact on health. In order to estimate the mortality change (forecasted for the next 24 hours) we have chosen a log-linear (Poisson) regression form to estimate the concentration-response function. The parameters involved in the C-R function have been estimated based on epidemiological studies, which have been published. Finally, we have derived the relationship between concentration change and mortality change from the C-R function which is the final health impact function.

Variación espacial de la exposición a contaminación atmosférica en la ciudad de Valencia y su relación con un índice de privación

Objetivo: Evaluar la variación espacial de la exposición a dióxido de nitrógeno (NO2) en la ciudad de Valencia y su relación con la privación socioeconómica y la edad. Métodos: La población por sección censal (SC) procede del Instituto Nacional de Estadística. Los niveles de NO2 se midieron en 100 puntos del área de estudio, mediante captadores pasivos, en tres campañas entre 2002 y 2004. Se utilizó regresión por usos del suelo (LUR) para obtener el mapa de los niveles de NO2. Las predicciones del LUR se compararon con las proporcionadas por: a) el captador más cercano de la red de vigilancia, b) el captador pasivo más cercano, c) el conjunto de captadores en un entorno y d) kriging. Se asignaron niveles de contaminación para cada SC. Se analizó la relación entre los niveles de NO2, un índice de privación con cinco categorías y la edad (≥65 años). Resultados: El modelo LUR resultó el método más preciso. Más del 99% de la población superó los niveles de seguridad propuestos por la Organización Mundial de la Salud. Se encontró una relación inversa entre los niveles de NO2 y el índice de privación (β = –2,01 μg/m3 en el quintil de mayor privación respecto al de menor, IC95%: –3,07 a –0,95), y una relación directa con la edad (β = 0,12 μg/m3 por incremento en unidad porcentual de población ≥65 años, IC95%: 0,08 a 0,16). Conclusiones: El método permitió obtener mapas de contaminación y describir la relación entre niveles de NO2 y características sociodemográficas.

Traffic-Related PM2.5 Air Pollution and Schools in Proximity to Major Roadways in Shanghai, China

Thesis (Master's)--University of Washington, 2016-06

Methods for Confounding Adjustment and High-Dimensional Environmental Exposures

Thesis (Ph.D.)--University of Washington, 2016-08

Characterization of water-soluble organic compounds in bioaerosols by liquid chromatography and fluorescence spectroscopy

In the last decades, the effects of the air pollution have been increasing, especially in the case of the human health diseases. In order to overcome this problem, scientists have been studying the components of the air. As a part of water-soluble organic compounds, amino acids are present in the atmospheric environment as components of diverse living organisms which can be responsible for spreading diseases through the air. Liquid chromatography is one technique capable of distinguish the different amino acids from each other. In this work, aiming at separating the amino acids found in the aerosols samples collected in Aveiro, the ability of four columns (Mixed-Mode WAX-1, Mixed-Mode HILIC-1, Luna HILIC and Luna C18) to separate four amino acids (aspartic acid, lysine, glycine and tryptophan) and the way the interaction of the stationary phases of the columns with the analytes is influenced by organic solvent concentration and presence/concentration of the buffer, are being assessed. In the Mixed-Mode WAX-1 column, the chromatograms of the distinct amino acids revealed the separation was not efficient, since the retention times were very similar. In the case of lysine, in the elution with 80% (V/V) MeOH, the peaks appeared during the volume void. In the Mixed-Mode HILIC-1 column, the variation of the organic solvent concentration did not affect the elution of the four studied amino acids. Considering the Luna HILIC column, the retention times of the amino acids were too close to each other to ensure a separation among each other. Lastly, the Luna C18 column revealed to be useful to separate amino acids in a gradient mode, being the variation of the mobile phase composition in the organic solvent concentration (ACN). Luna C18 was the column used to separate the amino acids in the real samples and the mobile phase had acidified water and ACN. The gradient consisted in the following program: 0 – 2 min: 5% (V/V) ACN, 2 – 8 min: 5 – 2 % (V/V) ACN, 8 – 16 min: 2% (V/V) ACN, 16 – 20 min: 2 – 20 % (V/V) ACN, 20 – 35 min: 20 – 35 % (V/V) ACN. The aerosols samples were collected by using three passive samplers placed in two different locations in Aveiro and each sampler had two filters - one faced up and the other faced down. After the sampling, the water-soluble organic compounds was extracted by dissolution in ultra-pure water, sonication bath and filtration. The resulting filtered solutions were diluted in acidified water for the chromatographic separation. The results from liquid chromatography revealed the presence of the amino acids, although it was not possible to identify each one of them individually. The chromatograms and the fluorescence spectra showed the existence of some patterns: the samples that correspond to the up filters had more intense peaks and signals, revealing that the up filters collected more organic matter.

Urban Growth Analysis Using Spatial and Temporal Data

Urban growth identification, quantification, knowledge of rate and the trends of growth would help in regional planning for better infrastructure provision in environmentally sound way. This requires analysis of spatial and temporal data, which help in quantifying the trends of growth on spatial scale. Emerging technologies such as Remote Sensing, Geographic Information System (GIS) along with Global Positioning System (GPS) help in this regard. Remote sensing aids in the collection of temporal data and GIS helps in spatial analysis. This paper focuses on the analysis of urban growth pattern in the form of either radial or linear sprawl along the Bangalore - Mysore highway. Various GIS base layers such as builtup areas along the highway, road network, village boundary etc. were generated using collateral data such as the Survey of India toposheet, etc. Further, this analysis was complemented with the computation of Shannon's entropy, which helped in identifying prevalent sprawl zone, rate of growth and in delineating potential sprawl locations. The computation Shannon's entropy helped in delineating regions with dispersed and compact growth. This study reveals that the Bangalore North and South taluks contributed mainly to the sprawl with 559% increase in built-up area over a period of 28 years and high degree of dispersion. The Mysore and Srirangapatna region showed 128% change in built-up area and a high potential for sprawl with slightly high dispersion. The degree of sprawl was found to be directly proportional to the distances from the cities.

Numerical analysis of spatial evolution of the small signal gain in a chemical oxygen-iodine laser operating without primary buffer gas

A chemical oxygen iodine laser (COIL) that operates without primary buffer gas has become a new way of facilitating the compact integration of laser systems. To clarify the properties of spatial gain distribution, three-dimensional (3-D) computational fluid dynamics (CFD) technology was used to study the mixing and reactive flow in a COIL nozzle with an interleaving jet configuration in the supersonic section. The results show that the molecular iodine fraction in the secondary flow has a notable effect on the spatial distribution of the small signal gain. The rich iodine condition produces some negative gain regions along the jet trajectory, while the lean iodine condition slows down the development of the gain in the streamwise direction. It is also found that the new configuration of an interleaving jet helps form a reasonable gain field under appropriate operation conditions. (c) 2007 Elsevier Ltd. All rights reserved.

A GIS analysis of coastal development and trends in bottlenose dolphin strandings in Charleston, SC: implications for coastal marine spatial planning

Bottlenose dolphins (Tursiops truncatus) inhabit estuarine waters near Charleston, South Carolina (SC) feeding, nursing and socializing. While in these waters, dolphins are exposed to multiple direct and indirect threats such as anthropogenic impacts (egs. harassment with boat traffic and entanglements in fishing gear) and environmental degradation. Bottlenose dolphins are protected under the Marine Mammal Protection Act of 1972. Over the years, the percentage of strandings in the estuaries has increased in South Carolina and, specifically, recent stranding data shows an increase in strandings occurring in Charleston, SC near areas of residential development. During the same timeframe, Charleston experienced a shift in human population towards the coastline. These two trends, rise in estuarine dolphin strandings and shift in human population, have raised questions on whether the increase in strandings is a result of more detectable strandings being reported, or a true increase in stranding events. Using GIS, the trends in strandings were compared to residential growth, boat permits, fishing permits, and dock permits in Charleston County from 1994-2009. A simple linear regression analysis was performed to determine if there were any significant relationships between strandings, boat permits, commercial fishing permits, and crabpot permits. The results of this analysis show the stranding trend moves toward Charleston Harbor and adjacent rivers over time which suggests the increase in strandings is related to the strandings becoming more detectable. The statistical analysis shows that the factors that cause human interaction strandings such as boats, commercial fishing, and crabpot line entanglements are not significantly related to strandings further supporting the hypothesis that the increase in strandings are due to increased observations on the water as human coastal population increases and are not a natural phenomenon. This study has local and potentially regional marine spatial planning implications to protect coastal natural resources, such as the bottlenose dolphin, while balancing coastal development.

Report of the training in database and spatial analysis for Marine Protected Areas staff in Indonesia's BOBLME region, Medan, Indonesia, 30 June-4 July, 2015

Training included: Geographic Information System (GIS)concept and software; Global Positioning System (GPS); Ecological Gap Analysis and Marine Protected Area (MPA) design using Marine Reserve Design using Spatially Explicit Annealing (MARXAN); and cartography.

Dental caries and the nutritional status of preschool children: a spatial analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.