945 resultados para Air Pollution Reduction, Cardiorespitory Diseases, Energy Use Scenario, Health Benefit Analysis


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La planificación de la movilidad sostenible urbana es una tarea compleja que implica un alto grado de incertidumbre debido al horizonte de planificación a largo plazo, la amplia gama de paquetes de políticas posibles, la necesidad de una aplicación efectiva y eficiente, la gran escala geográfica, la necesidad de considerar objetivos económicos, sociales y ambientales, y la respuesta del viajero a los diferentes cursos de acción y su aceptabilidad política (Shiftan et al., 2003). Además, con las tendencias inevitables en motorización y urbanización, la demanda de terrenos y recursos de movilidad en las ciudades está aumentando dramáticamente. Como consecuencia de ello, los problemas de congestión de tráfico, deterioro ambiental, contaminación del aire, consumo de energía, desigualdades en la comunidad, etc. se hacen más y más críticos para la sociedad. Esta situación no es estable a largo plazo. Para enfrentarse a estos desafíos y conseguir un desarrollo sostenible, es necesario considerar una estrategia de planificación urbana a largo plazo, que aborde las necesarias implicaciones potencialmente importantes. Esta tesis contribuye a las herramientas de evaluación a largo plazo de la movilidad urbana estableciendo una metodología innovadora para el análisis y optimización de dos tipos de medidas de gestión de la demanda del transporte (TDM). La metodología nueva realizado se basa en la flexibilización de la toma de decisiones basadas en utilidad, integrando diversos mecanismos de decisión contrariedad‐anticipada y combinados utilidad‐contrariedad en un marco integral de planificación del transporte. La metodología propuesta incluye dos aspectos principales: 1) La construcción de escenarios con una o varias medidas TDM usando el método de encuesta que incorpora la teoría “regret”. La construcción de escenarios para este trabajo se hace para considerar específicamente la implementación de cada medida TDM en el marco temporal y marco espacial. Al final, se construyen 13 escenarios TDM en términos del más deseable, el más posible y el de menor grado de “regret” como resultado de una encuesta en dos rondas a expertos en el tema. 2) A continuación se procede al desarrollo de un marco de evaluación estratégica, basado en un Análisis Multicriterio de Toma de Decisiones (Multicriteria Decision Analysis, MCDA) y en un modelo “regret”. Este marco de evaluación se utiliza para comparar la contribución de los distintos escenarios TDM a la movilidad sostenible y para determinar el mejor escenario utilizando no sólo el valor objetivo de utilidad objetivo obtenido en el análisis orientado a utilidad MCDA, sino también el valor de “regret” que se calcula por medio del modelo “regret” MCDA. La función objetivo del MCDA se integra en un modelo de interacción de uso del suelo y transporte que se usa para optimizar y evaluar los impactos a largo plazo de los escenarios TDM previamente construidos. Un modelo de “regret”, llamado “referencedependent regret model (RDRM)” (modelo de contrariedad dependiente de referencias), se ha adaptado para analizar la contribución de cada escenario TDM desde un punto de vista subjetivo. La validación de la metodología se realiza mediante su aplicación a un caso de estudio en la provincia de Madrid. La metodología propuesta define pues un procedimiento técnico detallado para la evaluación de los impactos estratégicos de la aplicación de medidas de gestión de la demanda en el transporte, que se considera que constituye una herramienta de planificación útil, transparente y flexible, tanto para los planificadores como para los responsables de la gestión del transporte. Planning sustainable urban mobility is a complex task involving a high degree of uncertainty due to the long‐term planning horizon, the wide spectrum of potential policy packages, the need for effective and efficient implementation, the large geographical scale, the necessity to consider economic, social, and environmental goals, and the traveller’s response to the various action courses and their political acceptability (Shiftan et al., 2003). Moreover, with the inevitable trends on motorisation and urbanisation, the demand for land and mobility in cities is growing dramatically. Consequently, the problems of traffic congestion, environmental deterioration, air pollution, energy consumption, and community inequity etc., are becoming more and more critical for the society (EU, 2011). Certainly, this course is not sustainable in the long term. To address this challenge and achieve sustainable development, a long‐term perspective strategic urban plan, with its potentially important implications, should be established. This thesis contributes on assessing long‐term urban mobility by establishing an innovative methodology for optimizing and evaluating two types of transport demand management measures (TDM). The new methodology aims at relaxing the utility‐based decision‐making assumption by embedding anticipated‐regret and combined utilityregret decision mechanisms in an integrated transport planning framework. The proposed methodology includes two major aspects: 1) Construction of policy scenarios within a single measure or combined TDM policy‐packages using the survey method incorporating the regret theory. The purpose of building the TDM scenarios in this work is to address the specific implementation in terms of time frame and geographic scale for each TDM measure. Finally, 13 TDM scenarios are built in terms of the most desirable, the most expected and the least regret choice by means of the two‐round Delphi based survey. 2) Development of the combined utility‐regret analysis framework based on multicriteria decision analysis (MCDA). This assessment framework is used to compare the contribution of the TDM scenario towards sustainable mobility and to determine the best scenario considering not only the objective utility value obtained from the utilitybased MCDA, but also a regret value that is calculated via a regret‐based MCDA. The objective function of the utility‐based MCDA is integrated in a land use and transport interaction model and is used for optimizing and assessing the long term impacts of the constructed TDM scenarios. A regret based model, called referente dependent regret model (RDRM) is adapted to analyse the contribution of each TDM scenario in terms of a subjective point of view. The suggested methodology is implemented and validated in the case of Madrid. It defines a comprehensive technical procedure for assessing strategic effects of transport demand management measures, which can be useful, transparent and flexible planning tool both for planners and decision‐makers.

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Background: In recent years, Spain has implemented a number of air quality control measures that are expected to lead to a future reduction in fine particle concentrations and an ensuing positive impact on public health. Objectives: We aimed to assess the impact on mortality attributable to a reduction in fine particle levels in Spain in 2014 in relation to the estimated level for 2007. Methods: To estimate exposure, we constructed fine particle distribution models for Spain for 2007 (reference scenario) and 2014 (projected scenario) with a spatial resolution of 16x16 km2. In a second step, we used the concentration-response functions proposed by cohort studies carried out in Europe (European Study of Cohorts for Air Pollution Effects and Rome longitudinal cohort) and North America (American Cancer Society cohort, Harvard Six Cities study and Canadian national cohort) to calculate the number of attributable annual deaths corresponding to all causes, all non-accidental causes, ischemic heart disease and lung cancer among persons aged over 25 years (2005-2007 mortality rate data). We examined the effect of the Spanish demographic shift in our analysis using 2007 and 2012 population figures. Results: Our model suggested that there would be a mean overall reduction in fine particle levels of 1mg/m3 by 2014. Taking into account 2007 population data, between 8 and 15 all-cause deaths per 100,000 population could be postponed annually by the expected reduction in fine particle levels. For specific subgroups, estimates varied from 10 to 30 deaths for all non-accidental causes, from 1 to 5 for lung cancer, and from 2 to 6 for ischemic heart disease. The expected burden of preventable mortality would be even higher in the future due to the Spanish population growth. Taking into account the population older than 30 years in 2012, the absolute mortality impact estimate would increase approximately by 18%. Conclusions: Effective implementation of air quality measures in Spain, in a scenario with a short-term projection, would amount to an appreciable decline infine particle concentrations, and this, in turn, would lead to notable health-related benefits. Recent European cohort studies strengthen the evidence of an association between long-term exposure to fine particles and health effects, and could enhance the health impact quantification in Europe. Air quality models can contribute to improved assessment of air pollution health impact estimates, particularly in study areas without air pollution monitoring data.

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Transportation Department, Washington, D.C.

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Prepared for Illinois Dept. of Energy and and Natural Resources, Office of Research and Planning; principal investigators: Patricia Szczepanik Van Leeuwen, William H. Hallenbeck.

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Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of global warming. Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. In order to address these issues, the present thesis presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. However, even if hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations, the reduced engine load and the repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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Particle Pollution (PM) is a major problem in urban environments. There is serious health risks associated with exposure to PM. In addition, particulate matter also contributes to greenhouse effects and global warming. PM originates mainly from fuel combustion. In this paper, we attempt to study household energy use contributions to experienced levels of PM concentrations. We find that there is a strong positive association between household gasoline consumption and urban air pollution. Residential natural gas use is also associated with poor air quality.

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The objective of this work was to evaluate the effects of pollutants on the abundance and diversity of Collembola in urban soils. The research was carried out in three parks (Cişmigiu, Izvor and Unirea) in downtown Bucharest, where the intense car traffic accounts for 70% of the local air pollution. One site in particular (Cişmigiu park) was highly contaminated with Pb, Cd, Zn and Cu at about ten times the background levels of Pb. Collembola were sampled in 2006 (July, September, November) using the transect method: 2,475 individuals from 34 species of Collembola were collected from 210 samples of soil and litter. Numerical densities differed significantly between the studied sites.The influence of air pollutants on the springtail fauna was visible at the species richness diversity and soil pollution levels. Species richness was lowest in the most contaminated site (Cismigiu, 11 species), which presented an increase in springtails abundances, though. Some species may become resistant to pollution and occur in high numbers of individuals in polluted sites, which makes them a good bioindicator of pollutants.

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Exposure to nitrogen oxides (NOx) emitted by burning fossil fuels has been associated with respiratory diseases. We aimed to estimate the effects of NOx exposure on mortality owing to respiratory diseases in residents of Taubaté, São Paulo, Brazil, of all ages and both sexes. This time-series ecological study from August 1, 2011 to July 31, 2012 used information on deaths caused by respiratory diseases obtained from the Health Department of Taubaté. Estimated daily levels of pollutants (NOx, particulate matter, ozone, carbon monoxide) were obtained from the Centro de Previsão de Tempo e Estudos Climáticos Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System. These environmental variables were used to adjust the multipollutant model for apparent temperature. To estimate association between hospitalizations owing to asthma and air pollutants, generalized additive Poisson regression models were developed, with lags as much as 5 days. There were 385 deaths with a daily mean (±SD) of 1.05±1.03 (range: 0-5). Exposure to NOx was significantly associated with mortality owing to respiratory diseases: relative risk (RR)=1.035 (95% confidence interval [CI]: 1.008-1.063) for lag 2, RR=1.064 (95%CI: 1.017-1.112) lag 3, RR=1.055 (95%CI: 1.025-1.085) lag 4, and RR=1.042 (95%CI: 1.010-1.076) lag 5. A 3 µg/m3 reduction in NOx concentration resulted in a decrease of 10-18 percentage points in risk of death caused by respiratory diseases. Even at NOx concentrations below the acceptable standard, there is association with deaths caused by respiratory diseases.

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Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

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En el proceso de extracción de petróleo (crudo) deben realizarse tratamientos físicos y químicos en estaciones de recolección del hidrocarburo con el fin de garantizar su calidad antes de su entrega para el transporte y comercialización. Para la realización de esta actividad el personal operativo requerido (operadores) debe realizar diferentes actividades, tales como ronda operacional, verificación de sistemas de almacenamiento del crudo, agua residual del proceso e insumos químicos utilizados en su tratamiento y manipulación de facilidades en las estaciones de recolección, entre otras. Como resultados de las actividades rutinarias los operadores están expuestos a factores de riesgo químico asociados a gases y vapores orgánicos generados en los procesos de tratamiento del crudo. En el presente trabajo se realizaron mediciones de calidad de aire e higiene industrial en diferentes estaciones tratamiento de crudo, con el propósito de evaluar los niveles de exposición de los operadores a gases y vapores de hidrocarburos durante el proceso de tratamiento de crudo y dar respuesta a la siguiente pregunta: ¿existe relación entre la exposición ocupacional, las emisiones atmosféricas de gases (SO2, CO, H2S) y la percepción de afectación de la salud de los trabajadores que se encuentran expuestos durante la actividad laboral, en una empresa del sector de hidrocarburos? Se realizó un estudio de corte transversal, mediante la aplicación de cuestionarios sobre las condiciones de trabajo y de salud a 30 trabajadores que laboran en una estación de tratamiento de crudo de una compañía del sector de hidrocarburos. Los operadores objeto de estudio laboran en turnos rotativos, han estado vinculados con la compañía por más de dos años y tienen contrato directo, adicionalmente, se identificaron los factores de riesgos ambientales y ocupacionales para el grupo de trabajadores y se realizó una revisión de los informes de medición de higiene industrial y de calidad de aire de las estaciones donde labora el personal seleccionado con el fin de establecer si los resultados se relacionan. Los resultados obtenidos indican que el 100% de los trabajadores son de género masculino y se desempeñan en cargos de operadores, recorredores de pozos de crudo y supervisores. El 97% de los operadores tiene más de cuarenta años de edad y el 80% de los mismos ha laborado por más de 6 años en la compañía. Acerca de la percepción de los trabajadores sobre su estado de salud el 90% afirma que su salud es buena, el 97% respondió que no presenta problemas respiratorios, el 23% manifiesta que presenta trastornos dermatológicos y el 27% indican que presenta dolor de cabeza constante. De la revisión de los informes de calidad de aire disponibles se encontró que las mediciones de Dióxido de Azufre SO2, Monóxido de Carbono CO se encuentran dentro del rango definido como el de menor impacto para la salud humana. De los datos del informe se puede concluir que la calidad del aire es buena en el 100% de las áreas de influencia de las estaciones de tratamiento de crudo. Según los informes de higiene industrial el 34% de las instalaciones presenta concentraciones de Sulfuro de Hidrógeno (H2S) en el límite permisible para exposiciones crónicas en un promedio ponderado de tiempo (TLV-TWA) y el límite permisible para exposiciones agudas en un límite de exposición a corto plazo (TLV-STEL). Solo el 37% de los trabajadores objeto de este estudio percibe el riesgo por la exposición a factores de riesgo químicos y son claramente consientes que se encuentran expuestos a estos riesgos por la manipulación de productos químicos y exposición a sustancias químicas producto de sus actividades rutinarias, el 73% no percibe el riesgo de exposición por su actividad laboral. Se recomienda que la compañía fortalezca su esquema de vigilancia para generar alternativas que eleven los niveles de consciencia del riesgo del trabajador. Los factores de riesgo ambiental y ocupacional, de los gases y vapores generados se deben al proceso de tratamiento de crudo, están mutuamente relacionados dado que al generarse una emisión y/o escape no controlado como consecuencia se tiene una afectación directa al medio ambiente y a los trabajadores.

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How do resource booms affect human capital accumulation? We exploit time and spatial variation generated by the commodity boom across local governments in Peru to measure the effect of natural resources on human capital formation. We explore the effect of both mining production and tax revenues on test scores, finding a substantial and statistically significant effect for the latter. Transfers to local governments from mining tax revenues are linked to an increase in math test scores of around 0.23 standard deviations. We find that the hiring of permanent teachers as well as the increases in parental employment and improvements in health outcomes of adults and children are plausible mechanisms for such large effect on learning. These findings suggest that redistributive policies could facilitate the accumulation of human capital in resource abundant developing countries as a way to avoid the natural resources curse.