Numeric simulation of pollutant dispersion by a control-volume based on finite element method

The dispersion of pollutants in the environment is an issue of great interest as it directly affects air quality, mainly in large cities. Experimental and numerical tools have been used to predict the behavior of pollutant species dispersion in the atmosphere. A software has been developed based on the control-volume based on the finite element method in order to obtain two-dimensional simulations of Navier-Stokes equations and heat or mass transportation in regions with obstacles, varying position of the pollutant source. Numeric results of some applications were obtained and, whenever possible, compared with literature results showing satisfactory accordance. Copyright (C) 2010 John Wiley & Sons, Ltd.

Remote Sensing Detection of atmospheric pollutants using Lidar, Sodar and correlation with air quality data in an industrial area

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of São Paulo, in the city of Cubatão, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar. © 2011 SPIE.

A New and Simple Visual Technique Based on Indigo Dye for Determination of Ozone in Ambient Air

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Ambient levels of air pollution induce clinical worsening of blepharitis

Background: Even though air pollutants exposure is associated with changes in the ocular surface and tear film, its relationship to the clinical course of blepharitis, a common eyelid disease, had not yet been investigated. Our objective was to investigate the correlation between air pollution and acute manifestations of blepharitis. Method: We recorded all cases of changes in the eyelids and ocular surface, and rated clinical findings on a scale from zero (normal) to two (severe alterations). Daily values of carbon monoxide, particulate matter smaller than 10 mu m in diameter and nitrogen dioxide concentrations and meteorological variables (temperature and relative humidity) in the vicinity of the medical service were obtained. Specific linear regression models for each outcome were constructed including pollutants as independent variables (single pollutant models). Temperature and humidity were included as confounding variables. Results: increases of 28.8 mu g/m(3) in the concentration of particulate matter and 1.1 ppm in the concentration of CO were associated with increases in cases of blepharitis on the day of exposure (5 cases, 95% CI: 1-10 and 6 cases, 95% CI: 1-12, respectively). Conclusion: Exposure to usual air pollutants concentrations present in large cities affects, in a consistent manner, the eyes of residents contributing to the increasing incidence of diseases of the eyelid margin. (C) 2011 Elsevier Inc. All rights reserved.

Mechanical Alterations in airway smooth muscle after interaction with indoor pollutant – A mathematical model.

The viscoelasticity of mammalian lung is determined by the mechanical properties and structural regulation of the airway smooth muscle (ASM). The exposure to polluted air may deteriorate these properties with harmful consequences to individual health. Formaldehyde (FA) is an important indoor pollutant found among volatile organic compounds. This pollutant permeates through the smooth muscle tissue forming covalent bonds between proteins in the extracellular matrix and intracellular protein structure changing mechanical properties of ASM and inducing asthma symptoms, such as airway hyperresponsiveness, even at low concentrations. In the experimental scenario, the mechanical effect of FA is the stiffening of the tissue, but the mechanism behind this effect is not fully understood. Thus, the aim of this study is to reproduce the mechanical behavior of the ASM, such as contraction and stretching, under FA action or not. For this, it was created a two-dimensional viscoelastic network model based on Voronoi tessellation solved using Runge-Kutta method of fourth order. The equilibrium configuration was reached when the forces in different parts of the network were equal. This model simulates the mechanical behavior of ASM through of a network of dashpots and springs. This dashpot-spring mechanical coupling mimics the composition of the actomyosin machinery of ASM through the contraction of springs to a minimum length. We hypothesized that formation of covalent bonds, due to the FA action, can be represented in the model by a simple change in the elastic constant of the springs, while the action of methacholine (MCh) reduce the equilibrium length of the spring. A sigmoid curve of tension as a function of MCh doses was obtained, showing increased tension when the muscle strip was exposed to FA. Our simulations suggest that FA, at a concentration of 0.1 ppm, can affect the elastic properties of the smooth muscle ¯bers by a factor of 120%. We also analyze the dynamic mechanical properties, observing the viscous and elastic behavior of the network. Finally, the proposed model, although simple, incorporates the phenomenology of both MCh and FA and reproduces experimental results observed with in vitro exposure of smooth muscle to FA. Thus, this new mechanical approach incorporates several well know features of the contractile system of the cells in a tissue level model. The model can also be used in different biological scales.

Mechanical alterations in airway smooth muscle after interaction with indoor pollutant - A mathematical model

The viscoelasticity of mammalian lung is determined by the mechanical properties and structural regulation of the airway smooth muscle (ASM). The exposure to polluted air may deteriorate these properties with harmful consequences to individual health. Formaldehyde (FA) is an important indoor pollutant found among volatile organic compounds. This pollutant permeates through the smooth muscle tissue forming covalent bonds between proteins in the extracellular matrix and intracellular protein structure changing mechanical properties of ASM and inducing asthma symptoms, such as airway hyperresponsiveness, even at low concentrations. In the experimental scenario, the mechanical effect of FA is the stiffening of the tissue, but the mechanism behind this effect is not fully w1derstood. Thus, the aim of this study is to reproduce the mechanical behavior of the ASM, such as contraction and stretching, under FA action or not. For this, it was created a two-dimensional viscoelastic network model based on Voronoi tessellation solved using Runge-Kutta method of fourth order. The equilibrium configuration was reached when the forces in different parts of the network were equal. This model simulates the mechanical behavior of ASM through of a network of dashpots and springs. This dashpot-spring mechanical coupling mimics the composition of the actomyosin machinery of ASM through the contraction of springs to a minimum length. We hypothesized that formation of covalent bonds, due to the FA action, can be represented in the model by a simple change in the elastic constant of the springs, while the action of methacholinc (MCh) reduce the equilibrium length of the spring. A sigmoid curve of tension as a function of MCh doses was obtained, showing increased tension when the muscle strip was exposed to FA. Our simulations suggest that FA, at a concentration of 0.1 ppm, can affect the elastic properties of the smooth muscle fibers by a factor of 120%. We also analyze the dynamic mechanical properties, observing the viscous and elastic behavior of the network. Finally, the proposed model, although simple, ir1corporates the phenomenology of both MCh and FA and reproduces experirnental results observed with ir1 vitro exposure of smooth muscle to .FA. Thus, this new mechanical approach incorporates several well know features of the contractile system of the cells ir1 a tissue level model. The model can also be used in different biological scales.

Finite element simulation of a local scale air quality model over complex terrain

[EN]In this paper we propose a finite element method approach for modelling the air quality in a local scale over complex terrain. The area of interest is up to tens of kilometres and it includes pollutant sources. The proposed methodology involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. We apply our methodology to simulate a fictitious pollution episode in La Palma island (Canary Island, Spain)...

High-resolution simulation of stack pollutant emissions

[EN]A three-dimensional air pollution model for the short-term simulation of emission, transport and reaction of pollutants is presented. In the finite element simulation of these environmental processes over a complex terrain, a mesh generator capable of adapting itself to the topographic characteristics is essential, A local refinement of tetrahedra is used in order to capture the plume rise. Then a wind field is computed by using a mass-consistent model and perturbing its vertical component to introduce the plume rise effect. Finally, an Eulerian convection-diffusionreaction model is used to simulate the pollutant dispersion…

Three-dimensional finite element modelling of stack pollutant emissions

[EN]In this paper we propose a finite element method approach for modelling the air quality in a local scale over complex terrain. The area of interest is up to tens of kilometres and it includes pollutant sources. The proposed methodology involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. The methodology is used to simulate a fictitious pollution episode in La Palma island (Canary Island, Spain)…

Local scale finite element modelling of stack pollutant emissions

Congresos y conferencias

Application of innovative methods of source apportionment in air contamination assessment

In this work, new tools in atmospheric pollutant sampling and analysis were applied in order to go deeper in source apportionment study. The project was developed mainly by the study of atmospheric emission sources in a suburban area influenced by a municipal solid waste incinerator (MSWI), a medium-sized coastal tourist town and a motorway. Two main research lines were followed. For what concerns the first line, the potentiality of the use of PM samplers coupled with a wind select sensor was assessed. Results showed that they may be a valid support in source apportionment studies. However, meteorological and territorial conditions could strongly affect the results. Moreover, new markers were investigated, particularly focusing on the processes of biomass burning. OC revealed a good biomass combustion process indicator, as well as all determined organic compounds. Among metals, lead and aluminium are well related to the biomass combustion. Surprisingly PM was not enriched of potassium during bonfire event. The second research line consists on the application of Positive Matrix factorization (PMF), a new statistical tool in data analysis. This new technique was applied to datasets which refer to different time resolution data. PMF application to atmospheric deposition fluxes identified six main sources affecting the area. The incinerator’s relative contribution seemed to be negligible. PMF analysis was then applied to PM2.5 collected with samplers coupled with a wind select sensor. The higher number of determined environmental indicators allowed to obtain more detailed results on the sources affecting the area. Vehicular traffic revealed the source of greatest concern for the study area. Also in this case, incinerator’s relative contribution seemed to be negligible. Finally, the application of PMF analysis to hourly aerosol data demonstrated that the higher the temporal resolution of the data was, the more the source profiles were close to the real one.

Global modeling of pollutant transport and deposition from anthropogenic emission hot spots on global scale

Urban centers significantly contribute to anthropogenic air pollution, although they cover only a minor fraction of the Earth's land surface. Since the worldwide degree of urbanization is steadily increasing, the anthropogenic contribution to air pollution from urban centers is expected to become more substantial in future air quality assessments. The main objective of this thesis was to obtain a more profound insight in the dispersion and the deposition of aerosol particles from 46 individual major population centers (MPCs) as well as the regional and global influence on the atmospheric distribution of several aerosol types. For the first time, this was assessed in one model framework, for which the global model EMAC was applied with different representations of aerosol particles. First, in an approach with passive tracers and a setup in which the results depend only on the source location and the size and the solubility of the tracers, several metrics and a regional climate classification were used to quantify the major outflow pathways, both vertically and horizontally, and to compare the balance between pollution export away from and pollution build-up around the source points. Then in a more comprehensive approach, the anthropogenic emissions of key trace species were changed at the MPC locations to determine the cumulative impact of the MPC emissions on the atmospheric aerosol burdens of black carbon, particulate organic matter, sulfate, and nitrate. Ten different mono-modal passive aerosol tracers were continuously released at the same constant rate at each emission point. The results clearly showed that on average about five times more mass is advected quasi-horizontally at low levels than exported into the upper troposphere. The strength of the low-level export is mainly determined by the location of the source, while the vertical transport is mainly governed by the lifting potential and the solubility of the tracers. Similar to insoluble gas phase tracers, the low-level export of aerosol tracers is strongest at middle and high latitudes, while the regions of strongest vertical export differ between aerosol (temperate winter dry) and gas phase (tropics) tracers. The emitted mass fraction that is kept around MPCs is largest in regions where aerosol tracers have short lifetimes; this mass is also critical for assessing the impact on humans. However, the number of people who live in a strongly polluted region around urban centers depends more on the population density than on the size of the area which is affected by strong air pollution. Another major result was that fine aerosol particles (diameters smaller than 2.5 micrometer) from MPCs undergo substantial long-range transport, with about half of the emitted mass being deposited beyond 1000 km away from the source. In contrast to this diluted remote deposition, there are areas around the MPCs which experience high deposition rates, especially in regions which are frequently affected by heavy precipitation or are situated in poorly ventilated locations. Moreover, most MPC aerosol emissions are removed over land surfaces. In particular, forests experience more deposition from MPC pollutants than other land ecosystems. In addition, it was found that the generic treatment of aerosols has no substantial influence on the major conclusions drawn in this thesis. Moreover, in the more comprehensive approach, it was found that emissions of black carbon, particulate organic matter, sulfur dioxide, and nitrogen oxides from MPCs influence the atmospheric burden of various aerosol types very differently, with impacts generally being larger for secondary species, sulfate and nitrate, than for primary species, black carbon and particulate organic matter. While the changes in the burdens of sulfate, black carbon, and particulate organic matter show an almost linear response for changes in the emission strength, the formation of nitrate was found to be contingent upon many more factors, e.g., the abundance of sulfuric acid, than only upon the strength of the nitrogen oxide emissions. The generic tracer experiments were further extended to conduct the first risk assessment to obtain the cumulative risk of contamination from multiple nuclear reactor accidents on the global scale. For this, many factors had to be taken into account: the probability of major accidents, the cumulative deposition field of the radionuclide cesium-137, and a threshold value that defines contamination. By collecting the necessary data and after accounting for uncertainties, it was found that the risk is highest in western Europe, the eastern US, and in Japan, where on average contamination by major accidents is expected about every 50 years.

A prospective study of the impact of air pollution on respiratory symptoms and infections in infants

Rationale: There is increasing evidence that short-term exposure to air pollution has a detrimental effect on respiratory health, but data from healthy populations, particularly infants, are scarce. Objectives: To assess the association of air pollution with frequency and severity of respiratory symptoms and infections measured weekly in healthy infants. Methods: In a prospective birth cohort of 366 infants of unselected mothers, respiratory health was assessed weekly by telephone interviews during the first year of life (19,106 total observations). Daily mean levels of particulate matter (PM10), nitrogen dioxide (NO2), and ozone (O3) were obtained from local monitoring stations. We determined the association of the preceding week's pollutant levels with symptom scores and respiratory tract infections using a generalized additive mixed model with an autoregressive component. In addition, we assessed whether neonatal lung function influences this association and whether duration of infectious episodes differed between weeks with normal PM10 and weeks with elevated levels. Measurements and Main Results: We found a significant association between air pollution and respiratory symptoms, particularly in the week after respiratory tract infections (risk ratio, 1.13 [1.02-1.24] per 10 μg/m(3) PM10 levels) and in infants with premorbid lung function. During times of elevated PM10 (>33.3 μg/m(3)), duration of respiratory tract infections increased by 20% (95% confidence interval, 2-42%). Conclusions: Exposure to even moderate levels of air pollution was associated with increased respiratory symptoms in healthy infants. Particularly in infants with premorbid lung function and inflammation, air pollution contributed to longer duration of infectious episodes with a potentially large socioeconomic impact.

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (SO2) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of SO2 concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

Pollutant concentrations and Meteorological data classification by Neural Networks

This paper present an environmental contingency forecasting tool based on Neural Networks (NN). Forecasting tool analyzes every hour and daily Sulphur Dioxide (SO2) concentrations and Meteorological data time series. Pollutant concentrations and meteorological variables are self-organized applying a Self-organizing Map (SOM) NN in different classes. Classes are used in training phase of a General Regression Neural Network (GRNN) classifier to provide an air quality forecast. In this case a time series set obtained from Environmental Monitoring Network (EMN) of the city of Salamanca, Guanajuato, México is used. Results verify the potential of this method versus other statistical classification methods and also variables correlation is solved.