985 resultados para PM2. 5


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Field deployments of the Aerodyne Aerosol Mass Spectrometer (AMS) have significantly advanced real-time measurements and source apportionment of non-refractory particulate matter. However, the cost and complex maintenance requirements of the AMS make its deployment at sufficient sites to determine regional characteristics impractical. Furthermore, the negligible transmission efficiency of the AMS inlet for supermicron particles significantly limits the characterization of their chemical nature and contributing sources. In this study, we utilize the AMS to characterize the water-soluble organic fingerprint of ambient particles collected onto conventional quartz filters, which are routinely sampled at many air quality sites. The method was applied to 256 particulate matter (PM) filter samples (PM1, PM2:5, and PM10, i.e., PM with aerodynamic diameters smaller than 1, 2.5, and 10 μm, respectively), collected at 16 urban and rural sites during summer and winter. We show that the results obtained by the present technique compare well with those from co-located online measurements, e.g., AMS or Aerosol Chemical Speciation Monitor (ACSM). The bulk recoveries of organic aerosol (60–91 %) achieved using this technique, together with low detection limits (0.8 μg of organic aerosol on the analyzed filter fraction) allow its application to environmental samples. We will discuss the recovery variability of individual hydrocarbon ions, ions containing oxygen, and other ions. The performance of such data in source apportionment is assessed in comparison to ACSM data. Recoveries of organic components related to different sources as traffic, wood burning, and secondary organic aerosol are presented. This technique, while subjected to the limitations inherent to filter-based measurements (e.g., filter artifacts and limited time resolution) may be used to enhance the AMS capabilities in measuring size-fractionated, spatially resolved longterm data sets.

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The association between fine particulate matter air pollution (PM2.5) and cardiovascular disease (CVD) mortality was spatially analyzed for Harris County, Texas, at the census tract level. The objective was to assess how increased PM2.5 exposure related to CVD mortality in this area while controlling for race, income, education, and age. An estimated exposure raster was created for Harris County using Kriging to estimate the PM2.5 exposure at the census tract level. The PM2.5 exposure and the CVD mortality rates were analyzed in an Ordinary Least Squares (OLS) regression model and the residuals were subsequently assessed for spatial autocorrelation. Race, median household income, and age were all found to be significant (p<0.05) predictors in the model. This study found that for every one μg/m3 increase in PM2.5 exposure, holding age and education variables constant, an increase of 16.57 CVD deaths per 100,000 would be predicted for increased minimum exposure values and an increase of 14.47 CVD deaths per 100,000 would be predicted for increased maximum exposure values. This finding supports previous studies associating PM2.5 exposure with CVD mortality. This study further identified the areas of greatest PM2.5 exposure in Harris County as being the geographical locations of populations with the highest risk of CVD (i.e., predominantly older, low-income populations with a predominance of African Americans). The magnitude of the effect of PM2.5 exposure on CVD mortality rates in the study region indicates a need for further community-level studies in Harris County, and suggests that reducing excess PM2.5 exposure would reduce CVD mortality.^

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Objective: To assess the indoor environment of two different types of dental practices regarding VOCs, PM2.5, and ultrafine particulate concentrations and examine the relationship between specific dental activities and contaminant levels. Method: The indoor environments of two selected dental settings (private practice and community health center) will were assessed in regards to VOCs, PM 2.5, and ultrafine particulate concentrations, as well as other indoor air quality parameters (CO2, CO, temperature, and relative humidity). The sampling duration was four working days for each dental practice. Continuous monitoring and integrated sampling methods were used and number of occupants, frequency, type, and duration of dental procedures or activities recorded. Measurements were compared to indoor air quality standards and guidelines. Results: The private practice had higher CO2, CO, and most VOC concentrations than the community health center, but the community health center had higher PM2.5 and ultrafine PM concentrations. Concentrations of p-dichlorobenzene and PM2.5 exceeded some guidelines. Outdoor concentrations greatly influenced the indoor concentration. There were no significant differences in contaminant levels between the operatory and general area. Indoor concentrations during the working period were not always consistently higher than during the nonworking period. Peaks in particulate matter concentration occurred during root canal and composite procedures.^

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Exposure to air pollutants in urban locales has been associated with increased risk for chronic diseases including cardiovascular disease (CVD) and pulmonary diseases in epidemiological studies. The exact mechanism explaining how air pollution affects chronic disease is still unknown. However, oxidative stress and inflammatory pathways have been posited as likely mechanisms. ^ Data from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Mexican-American Cohort Study (2003-2009) were used to examine the following aims, respectively: 1) to evaluate the association between long-term exposure to ambient particulate matter (PM) (PM10 and PM2.5) and nitrogen oxides (NO x) and telomere length (TL) among approximately 1,000 participants within MESA; and 2) to evaluate the association between traffic-related air pollution with self-reported asthma, diabetes, and hypertension among Mexican-Americans in Houston, Texas. ^ Our results from MESA were inconsistent regarding associations between long-term exposure to air pollution and shorter telomere length based on whether the participants came from New York (NY) or Los Angeles (LA). Although not statistically significant, we observed a negative association between long-term air pollution exposure and mean telomere length for NY participants, which was consistent with our hypothesis. Positive (statistically insignificant) associations were observed for LA participants. It is possible that our findings were more influenced by both outcome and exposure misclassification than by the absence of a relationship between pollution and TL. Future studies are needed that include longitudinal measures of telomere length as well as focus on effects of specific constituents of PM and other pollutant exposures on changes in telomere length over time. ^ This research provides support that Mexican-American adults who live near a major roadway or in close proximity to a dense street network have a higher prevalence of asthma. There was a non-significant trend towards an increased prevalence of adult asthma with increasing residential traffic exposure especially for residents who lived three or more years at their baseline address. Even though the prevalence of asthma is low in the Mexican-origin population, it is the fastest growing minority group in the U.S. and we would expect a growing number of Mexican-Americans who suffer from asthma in the future. Future studies are needed to better characterize risks for asthma associated with air pollution in this population.^

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Few recent estimates of childhood asthma incidence exist in the literature, although the importance of incidence surveillance for understanding asthma risk factors has been recognized. Asthma prevalence, morbidity and mortality reports have repeatedly shown that low-income children are disproportionately impacted by the disease. The aim of this study was to demonstrate the utility of Medicaid claims data for providing statewide estimates of asthma incidence. Medicaid Analytic Extract (MAX) data for Texas children ages 0-17 enrolled in Medicaid between 2004 and 2007 were used to estimate incidence overall and by age group, gender, race and county of residence. A 13+ month period of continuous enrollment was required in order to distinguish incident from prevalent cases identified in the claims data. Age-adjusted incidence of asthma was 4.26/100 person-years during 2005-2007, higher than reported in other populations. Incidence rates decreased with age, were higher for males than females, differed by race, and tended to be higher in rural than urban areas. With this study, we were able to demonstrate the utility of MAX data for estimating asthma incidence, and create a dataset of incident cases to use in further analysis. ^ In subsequent analyses, we investigated a possible association between ambient air pollutants and incident asthma among Medicaid-enrolled children in Harris County Texas between 2005 and 2007. This population is at high risk for asthma, and living in an area with historically poor air quality. We used a time-stratified case-crossover design and conditional logistic regression to calculate odds ratios, adjusted for weather variables and aeroallergens, to assess the effect of increases in ozone, NO2 and PM2.5 concentrations on risk of developing asthma. Our results show that a 10 ppb increase in ozone was significantly associated with asthma during the warm season (May-October), with the strongest effect seen when a 6-day cumulative lag period was used to compute the exposure metric (OR=1.05, 95% CI, 1.02–1.08). Similar results were seen for NO2 and PM 2.5 (OR=1.07, 95% CI, 1.03–1.11 and OR=1.12, 95% CI, 1.03–1.22, respectively). PM2.5 also had significant effects in the cold season (November-April), 5-day cumulative lag: OR=1.11, 95% CI, 1.00–1.22. When compared with children in the lowest quartile of O3 exposure, the risk for children in the highest quartile was 20% higher. This study indicates that these pollutants are associated with newly-diagnosed childhood asthma in this low-income urban population, particularly during the summer months. ^

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This study represents a secondary analysis of the merging of emergency room visits and daily ozone and PM2.5. Although the adverse health effects of ozone and fine particulate matter have been documented in the literature, evidence regarding the health risks of these two pollutants in Harris County, Texas, is limited. Harris County (Houston) has sufficiently unique characteristics that analysis of these relationships in this setting and with the ozone and industry issues in Houston is informative. The objective of this study was to investigate the association between the joint exposure to ozone and fine particulate matter, and emergency room diagnoses of chronic obstructive pulmonary disease and cardiovascular disease in Harris County, Texas, from 2004 to 2009, with zero and one day lags. ^ The study variables were daily emergency room visits for Harris County, Texas, from 2004 to 2009, temperature, relative humidity, east wind component, north wind component, ozone, and fine particulate matter. Information about each patient's age, race, and gender was also included. The two dichotomous outcomes were emergency room visits diagnoses for chronic obstructive pulmonary disease and cardiovascular disease. Estimates of ozone and PM2.5 were interpolated using kriging, in which estimates of the two pollutants were predicted from monitoring data for every case residence zip code for every day of the six years, over 3 million estimates (one of each pollutant for each case in the database). ^ Logistic regressions were conducted to estimate odds ratios of the two outcomes. Three analyses were conducted: one for all records, another for visits during the four months of April and September of 2005 and 2009, and a third one for visits from zip codes that are close to PM2.5 monitoring stations (east area of Harris County). The last two analyses were designed to investigate special temporal and spatial characteristics of the associations. ^ The dataset included all ER visits surveyed by Safety Net from 2004 to 2009, exceeding 3 million visits for all causes. There were 95,765 COPD and 96,596 CVD cases during this six year period. A 1-μg/m3 increase in PM2.5 on the same day was associated with a 1.0% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses, a 0.4% increase in the odds of cardiovascular disease emergency room diagnoses, and a 0.2% increase in the odds of cardiovascular disease emergency room diagnoses on the following day. A 1-ppb increase in ozone was associated with a 0.1% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses on the same day. These four percentages add up to 1.7% of ER visits. That is, over the period of six years, one unit increase for both ozone and PM2.5 (joint increase), resulted in about 55,286 (3,252,102 * 0.017) extra ER visits for CVD or COPD, or 9,214 extra ER visits per year. ^ After adjustment for age, race, gender, day of the week, temperature, relative humidity, east wind component, north wind component, and wind speed, there were statistically significant associations between emergency room chronic obstructive pulmonary disease diagnosis in Harris County, Texas, with joint exposure to ozone and fine particulate matter for the same day; and between emergency room cardiovascular disease diagnosis and exposure to PM2.5 of the same day and the previous day. ^ Despite the small association between the two air pollutants and the health outcomes, this study points to important findings. Namely, the need to identify reasons for the increase of CVD and COPD ER visits over the course of the project, the statistical association between humidity (or whatever other variables for which it may serve as a surrogate) and CVD and COPD cases, and the confirmatory finding that males and blacks have higher odds for the two outcomes, as consistent with other studies. ^ An important finding of this research suggests that the number and distribution of PM2.5 monitors in Harris County - although not evenly spaced geographically—are adequate to detect significant association between exposure and the two outcomes. In addition, this study points to other potential factors that contribute to the rising incidence rates of CVD and COPD ER visits in Harris County such as population increases, patient history, life style, and other pollutants. Finally, results of validation, using a subset of the data demonstrate the robustness of the models.^

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From November 2004 to December 2007, size-segregated aerosol samples were collected all-year-round at Dome C (East Antarctica) by using PM10 and PM2.5 samplers, and multi-stage impactors. The data set obtained from the chemical analysis provided the longest and the most time-resolved record of sea spray aerosol (sea salt Na+) in inner Antarctica. Sea spray showed a sharp seasonal pattern. The highest values measured in winter (Apr-Nov) were about ten times larger than in summer (Dec-Mar). For the first time, a size-distribution seasonal pattern was also shown: in winter, sea spray particles are mainly submicrometric, while their summer size-mode is around 1-2 µm. Meteorological analysis on a synoptic scale allowed the definition of atmospheric conditions leading sea spray to Dome C. An extreme-value approach along with specific environmental based criteria was taken to yield stronger fingerprints linking atmospheric circulation (means and anomalies) to extreme sea spray events. Air mass back-trajectory analyses for some high sea spray events allowed the identification of two major air mass pathways, reflecting different size distributions: micrometric fractions for transport from the closer Indian-Pacific sector, and sub-micrometric particles for longer trajectories over the Antarctic Plateau. The seasonal pattern of the SO4**2- /Na+ ratio enabled the identification of few events depleted in sulphate, with respect to the seawater composition. By using methanesulphonic acid (MSA) profile to evaluate the biogenic SO4**2- contribution, a more reliable sea salt sulphate was calculated. In this way, few events (mainly in April and in September) were identified originating probably from the "frost flower" source. A comparison with daily-collected superficial snow samples revealed that there is a temporal shift between aerosol and snow sea spray trends. This feature could imply a more complex deposition processes of sea spray, involving significant contribution of wet and diamond dust deposition, but further work has to be carried out to rule out the effect of wind re-distribution and to have more statistic significance.

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The Spanish NGO "Alianza por la Solidaridad" has installed improved cookstoves in 3000 households during 2012 and 2013 to improve energy efficiency reducing fuelwood consumption and to improve in-door air quality. The type of cookstoves were Noflaye Jeeg and Noflaye Jaboot and were installed in the Cassamance Natural Subregion covering part of Senegal, The Gambia and Guinea-Bissau. The Technical University of Madrid (UPM) has conducted a field study on a sample of these households to assess the effect of improved cookstoves on kitchen air quality. Measurements of carbon monoxide (CO) and fine particle matter (PM2.5) were taken for 24-hr period before and after the installation of improved cook-stoves. The 24-hr mean CO concentrations were lower than the World Health Organization (WHO) guidelines for Guinea-Bissau but higher for Senegal and Gambia, even after the installation of improved cookstoves. As for PM2.5 concentrations, 24-hr mean were always higher than these guidelines. However, improved cookstoves produced significant reductions on 24-hr mean CO and PM2.5 concentrations in Senegal and for mean and maximum PM2.5 concentration on Gambia. Although this variability needs to be explained by further research to determine which other factors could affect indoor air pollution, the study provided a better understanding of the problem and envisaged alternatives to be implemented in fu-ture phases of the NGO project.

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The Spanish NGO "Alianza por la Solidaridad" has installed improved cookstoves in 3000 households during 2012 and 2013 to improve energy efficiency reducing fuelwood consumption and to improve indoor air quality. The type of cookstoves were Noflaye Jeeg and Noflaye Jaboot and were installed in the Cassamance Natural Subregion covering part of Senegal, The Gambia and Guinea-Bissau. The Technical University of Madrid (UPM) has conducted a field study on a sample of these households to assess the effect of improved cookstoves on kitchen air quality. Measurements of carbon monoxide (CO) and fine particle matter (PM2.5) were taken for 24-hr period before and after the installation of improved cookstoves. The 24-hr mean CO concentrations were lower than the World Health Organization (WHO) guidelines for Guinea-Bissau but higher for Senegal and Gambia, even after the installation of improved cookstoves. As for PM2.5 concentrations, 24-hr mean were always higher than these guidelines. However, improved cookstoves produced significant reductions on 24-hr mean CO and PM2.5 concentrations in Senegal and for mean and maximum PM2.5 concentration on Gambia. Although this variability needs to be explained by further research to determine which other factors could affect indoor air pollution, the study provided a better understanding of the problem and envisaged alternatives to be implemented in future phases of the NGO project.

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The present paper describes the advancement and evaluation of air quality-related impacts with the Atmospheric Evaluation and Research Integrated system for Spain (AERIS). In its current version, AERIS is able to provide estimates on the impacts of air quality over human health (PM2.5 and O3), crops and vegetation (O3). The modules that allow quantifying the before mentioned impacts were modeled by applying different approaches (mostly for the European context) present in scientific literature to the conditions of the Iberian Peninsula. This application was supported by reliable data sources, as well as by the good predictive capacity of AERIS for ambient concentrations. For validation purposes, the estimates of AERIS for impacts on human health (change in the statistical life expectancy-PM2.5) and vegetation (loss of wheat crops-O3) were compared against results from the SERCA project and GAINS estimates for two emission scenarios. In general, good results evidenced by reasonable correlation coefficients were obtained, therefore confirming the adequateness of the followed modeling approaches and the quality of AERIS predictions.

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La mejora de la calidad del aire es una tarea eminentemente interdisciplinaria. Dada la gran variedad de ciencias y partes involucradas, dicha mejora requiere de herramientas de evaluación simples y completamente integradas. La modelización para la evaluación integrada (integrated assessment modeling) ha demostrado ser una solución adecuada para la descripción de los sistemas de contaminación atmosférica puesto que considera cada una de las etapas involucradas: emisiones, química y dispersión atmosférica, impactos ambientales asociados y potencial de disminución. Varios modelos de evaluación integrada ya están disponibles a escala continental, cubriendo cada una de las etapas antesmencionadas, siendo el modelo GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) el más reconocido y usado en el contexto europeo de toma de decisiones medioambientales. Sin embargo, el manejo de la calidad del aire a escala nacional/regional dentro del marco de la evaluación integrada es deseable. Esto sin embargo, no se lleva a cabo de manera satisfactoria con modelos a escala europea debido a la falta de resolución espacial o de detalle en los datos auxiliares, principalmente los inventarios de emisión y los patrones meteorológicos, entre otros. El objetivo de esta tesis es presentar los desarrollos en el diseño y aplicación de un modelo de evaluación integrada especialmente concebido para España y Portugal. El modelo AERIS (Atmospheric Evaluation and Research Integrated system for Spain) es capaz de cuantificar perfiles de concentración para varios contaminantes (NO2, SO2, PM10, PM2,5, NH3 y O3), el depósito atmosférico de especies de azufre y nitrógeno así como sus impactos en cultivos, vegetación, ecosistemas y salud como respuesta a cambios porcentuales en las emisiones de sectores relevantes. La versión actual de AERIS considera 20 sectores de emisión, ya sea equivalentes a sectores individuales SNAP o macrosectores, cuya contribución a los niveles de calidad del aire, depósito e impactos han sido modelados a través de matrices fuentereceptor (SRMs). Estas matrices son constantes de proporcionalidad que relacionan cambios en emisiones con diferentes indicadores de calidad del aire y han sido obtenidas a través de parametrizaciones estadísticas de un modelo de calidad del aire (AQM). Para el caso concreto de AERIS, su modelo de calidad del aire “de origen” consistió en el modelo WRF para la meteorología y en el modelo CMAQ para los procesos químico-atmosféricos. La cuantificación del depósito atmosférico, de los impactos en ecosistemas, cultivos, vegetación y salud humana se ha realizado siguiendo las metodologías estándar establecidas bajo los marcos internacionales de negociación, tales como CLRTAP. La estructura de programación está basada en MATLAB®, permitiendo gran compatibilidad con software típico de escritorio comoMicrosoft Excel® o ArcGIS®. En relación con los niveles de calidad del aire, AERIS es capaz de proveer datos de media anual y media mensual, así como el 19o valor horario más alto paraNO2, el 25o valor horario y el 4o valor diario más altos para SO2, el 36o valor diario más alto para PM10, el 26o valor octohorario más alto, SOMO35 y AOT40 para O3. En relación al depósito atmosférico, el depósito acumulado anual por unidad de area de especies de nitrógeno oxidado y reducido al igual que de azufre pueden ser determinados. Cuando los valores anteriormente mencionados se relacionan con características del dominio modelado tales como uso de suelo, cubiertas vegetales y forestales, censos poblacionales o estudios epidemiológicos, un gran número de impactos puede ser calculado. Centrándose en los impactos a ecosistemas y suelos, AERIS es capaz de estimar las superaciones de cargas críticas y las superaciones medias acumuladas para especies de nitrógeno y azufre. Los daños a bosques se calculan como una superación de los niveles críticos de NO2 y SO2 establecidos. Además, AERIS es capaz de cuantificar daños causados por O3 y SO2 en vid, maíz, patata, arroz, girasol, tabaco, tomate, sandía y trigo. Los impactos en salud humana han sido modelados como consecuencia de la exposición a PM2,5 y O3 y cuantificados como pérdidas en la esperanza de vida estadística e indicadores de mortalidad prematura. La exactitud del modelo de evaluación integrada ha sido contrastada estadísticamente con los resultados obtenidos por el modelo de calidad del aire convencional, exhibiendo en la mayoría de los casos un buen nivel de correspondencia. Debido a que la cuantificación de los impactos no es llevada a cabo directamente por el modelo de calidad del aire, un análisis de credibilidad ha sido realizado mediante la comparación de los resultados de AERIS con los de GAINS para un escenario de emisiones determinado. El análisis reveló un buen nivel de correspondencia en las medias y en las distribuciones probabilísticas de los conjuntos de datos. Las pruebas de verificación que fueron aplicadas a AERIS sugieren que los resultados son suficientemente consistentes para ser considerados como razonables y realistas. En conclusión, la principal motivación para la creación del modelo fue el producir una herramienta confiable y a la vez simple para el soporte de las partes involucradas en la toma de decisiones, de cara a analizar diferentes escenarios “y si” con un bajo coste computacional. La interacción con políticos y otros actores dictó encontrar un compromiso entre la complejidad del modeladomedioambiental con el carácter conciso de las políticas, siendo esto algo que AERIS refleja en sus estructuras conceptual y computacional. Finalmente, cabe decir que AERIS ha sido creado para su uso exclusivo dentro de un marco de evaluación y de ninguna manera debe ser considerado como un sustituto de los modelos de calidad del aire ordinarios. ABSTRACT Improving air quality is an eminently inter-disciplinary task. The wide variety of sciences and stakeholders that are involved call for having simple yet fully-integrated and reliable evaluation tools available. Integrated AssessmentModeling has proved to be a suitable solution for the description of air pollution systems due to the fact that it considers each of the involved stages: emissions, atmospheric chemistry, dispersion, environmental impacts and abatement potentials. Some integrated assessment models are available at European scale that cover each of the before mentioned stages, being the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model the most recognized and widely-used within a European policy-making context. However, addressing air quality at the national/regional scale under an integrated assessment framework is desirable. To do so, European-scale models do not provide enough spatial resolution or detail in their ancillary data sources, mainly emission inventories and local meteorology patterns as well as associated results. The objective of this dissertation is to present the developments in the design and application of an Integrated Assessment Model especially conceived for Spain and Portugal. The Atmospheric Evaluation and Research Integrated system for Spain (AERIS) is able to quantify concentration profiles for several pollutants (NO2, SO2, PM10, PM2.5, NH3 and O3), the atmospheric deposition of sulfur and nitrogen species and their related impacts on crops, vegetation, ecosystems and health as a response to percentual changes in the emissions of relevant sectors. The current version of AERIS considers 20 emission sectors, either corresponding to individual SNAP sectors or macrosectors, whose contribution to air quality levels, deposition and impacts have been modeled through the use of source-receptor matrices (SRMs). Thesematrices are proportionality constants that relate emission changes with different air quality indicators and have been derived through statistical parameterizations of an air qualitymodeling system (AQM). For the concrete case of AERIS, its parent AQM relied on the WRF model for meteorology and on the CMAQ model for atmospheric chemical processes. The quantification of atmospheric deposition, impacts on ecosystems, crops, vegetation and human health has been carried out following the standard methodologies established under international negotiation frameworks such as CLRTAP. The programming structure isMATLAB ® -based, allowing great compatibility with typical software such as Microsoft Excel ® or ArcGIS ® Regarding air quality levels, AERIS is able to provide mean annual andmean monthly concentration values, as well as the indicators established in Directive 2008/50/EC, namely the 19th highest hourly value for NO2, the 25th highest daily value and the 4th highest hourly value for SO2, the 36th highest daily value of PM10, the 26th highest maximum 8-hour daily value, SOMO35 and AOT40 for O3. Regarding atmospheric deposition, the annual accumulated deposition per unit of area of species of oxidized and reduced nitrogen as well as sulfur can be estimated. When relating the before mentioned values with specific characteristics of the modeling domain such as land use, forest and crops covers, population counts and epidemiological studies, a wide array of impacts can be calculated. When focusing on impacts on ecosystems and soils, AERIS is able to estimate critical load exceedances and accumulated average exceedances for nitrogen and sulfur species. Damage on forests is estimated as an exceedance of established critical levels of NO2 and SO2. Additionally, AERIS is able to quantify damage caused by O3 and SO2 on grapes, maize, potato, rice, sunflower, tobacco, tomato, watermelon and wheat. Impacts on human health aremodeled as a consequence of exposure to PM2.5 and O3 and quantified as losses in statistical life expectancy and premature mortality indicators. The accuracy of the IAM has been tested by statistically contrasting the obtained results with those yielded by the conventional AQM, exhibiting in most cases a good agreement level. Due to the fact that impacts cannot be directly produced by the AQM, a credibility analysis was carried out for the outputs of AERIS for a given emission scenario by comparing them through probability tests against the performance of GAINS for the same scenario. This analysis revealed a good correspondence in the mean behavior and the probabilistic distributions of the datasets. The verification tests that were applied to AERIS suggest that results are consistent enough to be credited as reasonable and realistic. In conclusion, the main reason thatmotivated the creation of this model was to produce a reliable yet simple screening tool that would provide decision and policy making support for different “what-if” scenarios at a low computing cost. The interaction with politicians and other stakeholders dictated that reconciling the complexity of modeling with the conciseness of policies should be reflected by AERIS in both, its conceptual and computational structures. It should be noted however, that AERIS has been created under a policy-driven framework and by no means should be considered as a substitute of the ordinary AQM.

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This paper analyses the effects of policy making for air pollution abatement in Spain between 2000 and 2020 under an integrated assessment approach with the AERIS model for number of pollutants (NOx/NO2, PM10/PM2.5, O3, SO2, NH3 and VOC). The analysis of the effects of air pollution focused on different aspects: compliance with the European limit values of Directive 2008/50/EC for NO2 and PM10 for the Spanish air quality management areas; the evaluation of impacts caused by the deposition of atmospheric sulphur and nitrogen on ecosystems; the exceedance of critical levels of NO2 and SO2 in forest areas; the analysis of O3-induced crop damage for grapes, maize, potato, rice, tobacco, tomato, watermelon and wheat; health impacts caused by human exposure to O3 and PM2.5; and costs on society due to crop losses (O3), disability-related absence of work staff and damage to buildings and public property due to soot-related soiling (PM2.5). In general, air quality policy making has delivered improvements in air quality levels throughout Spain and has mitigated the severity of the impacts on ecosystems, health and vegetation in 2020 as target year. The findings of this work constitute an appropriate diagnosis for identifying improvement potentials for further mitigation for policy makers and stakeholders in Spain.

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Wildfires produce a significant release of gases and particles affecting climate and air quality. In the Mediterranean region, shrublands significantly contribute to burned areas and may show specific emission profiles. Our objective was to depict and quantify the primary-derived aerosols and precursors of secondary particulate species released during shrubland experimental fires, in which fire-line intensity values were equivalent to those of moderate shrubland wildfires, by using a number of different methodologies for the characterization of organic and inorganic compounds in both gas-phase and particulate-phase. Emissions of PM mass, particle number concentrations and organic and inorganic PMx components during flaming and smouldering phases were characterized in a field shrubland fire experiment. Our results revealed a clear prevalence of K+ and SO42- as inorganic ions released during the flaming-smouldering processes, accounting for 68 to 80% of the inorganic soluble fraction. During the residual-smouldering phases, in addition to K+ and SO42-, Ca2+ was found in significant amounts probably due the predominance of re-suspension processes (ashes and soil dust) over other emission sources during this stage. Concerning organic markers, the chromatograms were dominated by phenols, n-alkanals and n-alkanones, as well as by alcohol biomarkers in all the PMx fractions investigated. Levoglucosan was the most abundant degradation compound with maximum emission factors between 182 and 261 mg kg-1 in PM2.5 and PM10 respectively. However, levoglucosan was also observed in significant amounts in the gas-phase. The most representative organic volatile constituents in the smoke samples were alcohols, carbonyls, acids, monocyclic and bicyclic arenes, isoprenoids and alkanes compounds. The emission factors obtained in this study may contribute to the validation and improvement of national and international emission inventories of this intricate and diffuse emission source.

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