Hydrogen sulfide health effects and recommended air quality standard : prepared for the Illinois Institute for Environmental Quality /

Includes bibliographical references.

Revising the National Ambient Air Quality Standards: The integration of science and policy

Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^

Influence of the 23 October 2002 dust storm on the air quality of four Australian cities

Widespread drought and record maximum temperatures in eastern Australia produced a large dust storm on 23 October, 2002 which traversed a large proportion of eastern Australia and engulfed communities along a 2000 km stretch of coastline from south of Sydney ( NSW) to north of Mackay ( Queensland). This event provided an opportunity for a study of the impacts of rural dust upon the air quality of four Australian cities. A simple model is used to predict dust concentrations, dust deposition rates and particle size characteristics of the airborne dust in the cities. The total dust load of the plume was 3.35 to 4.85 million tones, and assuming a ( conservative) plume height of 1500 m, 62 - 90% of this dust load was deposited in-transit to the coast. It is conservatively estimated that 3.5, 12.0, 2.1 and 1.7 kilotonnes of dust were deposited during the event in Sydney, Brisbane, Gladstone and Mackay, respectively. In the South East Queensland region, this deposition is equivalent to 40% of the total annual TSP emissions for the region. The event increased TSP, PM10 and PM2.5 concentrations and reduced the visibility beyond the health and amenity guidelines in the four cities. For example, the 24-h average PM10 concentrations in Brisbane and Mackay, were 161 and 475 mu g m(-3) respectively, compared with the Australian national ambient air quality standard of 50 mu g m(-3). The 24-h average PM2.5 concentration in Brisbane was 42 mu g m(-3), compared with the national advisory standard of 25 mu g m(-3). These rural dusts significantly increased PM10/TSP ratios and decreased PM2.5/PM10 ratios, indicating that most of the particles were between PM2.5 and PM10.

'Herbal' but potentially hazardous: an analysis of the constituents and smoke emissions of tobacco-free waterpipe products and the air quality in the cafes where they are served

BACKGROUND: There are limited data on the composition and smoke emissions of 'herbal' shisha products and the air quality of establishments where they are smoked. METHODS: Three studies of 'herbal' shisha were conducted: (1) samples of 'herbal' shisha products were chemically analysed; (2) 'herbal' and tobacco shisha were burned in a waterpipe smoking machine and main and sidestream smoke analysed by standard methods and (3) the air quality of six waterpipe cafes was assessed by measurement of CO, particulate and nicotine vapour content. RESULTS: We found considerable variation in heavy metal content between the three products sampled, one being particularly high in lead, chromium, nickel and arsenic. A similar pattern emerged for polycyclic aromatic hydrocarbons. Smoke emission analyses indicated that toxic byproducts produced by the combustion of 'herbal' shisha were equivalent or greater than those produced by tobacco shisha. The results of our air quality assessment demonstrated that mean PM2.5 levels and CO content were significantly higher in waterpipe establishments compared to a casino where cigarette smoking was permitted. Nicotine vapour was detected in one of the waterpipe cafes. CONCLUSIONS: 'Herbal' shisha products tested contained toxic trace metals and PAHs levels equivalent to, or in excess of, that found in cigarettes. Their mainstream and sidestream smoke emissions contained carcinogens equivalent to, or in excess of, those of tobacco products. The content of the air in the waterpipe cafes tested was potentially hazardous. These data, in aggregate, suggest that smoking 'herbal' shisha may well be dangerous to health.

Calibration and validation of an air quality finite element model around an electric power plant in Gran Canaria island

[EN]This work presents the calibration and validation of an air quality finite element model applied to the surroundings of Jinamar electric power plant in Gran Canaria island (Spain). The model 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 main advantage of the model is the treatment of complex terrains that introduces an alternative to the standard implementation of current models. In addition, it improves the computational cost through the use of unstructured meshes...

A feasibility study for assessing building occupants' indoor air quality expectations compared to nationally recognized standards

Indoor Air Quality (IAQ) can have significant implications for health, productivity, job performance, and operating cost. Professional experience in the field of indoor air quality suggests that high expectations (better than nationally established standards) (American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE)) of workplace indoor air quality lead to increase air quality complaints. To determine whether there is a positive association between expectations and indoor air quality complaints, a one-time descriptive and analytical cross-sectional pilot study was conducted. Area Safety Liaisons (n = 330) at University of Texas Health Science Center – Houston were asked to answer a questionnaire regarding their expectations of four workplace indoor air quality indicators i.e., (temperature, relative humidity, carbon dioxide, and carbon monoxide) and if they experienced and reported indoor air quality problems. A chi-square test for independence was used to evaluate associations among the variables of interest. The response rate was 54% (n = 177). Results did not show significant associations between expectation and indoor air quality. However, a greater proportion of Area Safety Liaisons who expected indoor air quality indicators to be better than the established standard experienced greater indoor air quality problems. Similarly, a slightly higher proportion of Area Liaisons who expected indoor air quality indicators to be better than the standard reported greater indoor air quality complaints. ^ The findings indicated that a greater proportion of Area Safety Liaisons with high expectations (conditions that are beyond what is considered normal and acceptable by ASHRAE) experienced greater indoor air quality discomfort. This result suggests a positive association between high expectations and experienced and reported indoor air quality complaints. Future studies may be able to address whether the frequency of complaints and resulting investigations can be reduced through information and education about what are acceptable conditions.^

Assessment of urban parameterizations in the WRF model for air quality modelling purposes in Madrid (Spain)

This study aims to assess the performance or multi-layer canopy parameterizations implemented in the mesoscale WRF model in order to understand their potential contribution to improve the description of energy fluxes and wind fields in the Madrid city. It was found that the Building Energy Model (BEP+BEM) parameterization yielded better results than the bulk standard scheme implemented in the Noah LSM, but very close to those of the Building Energy Parameterization (BEP). The later was deemed as the best option since data requirements and CPU time were smaller. Two annual runs were made to feed the CMAQ chemical-transport model to assess the impact of this feature in routinely air quality modelling activities.

Development and implementation of an air quality integrated assessment modelling system for the Iberian Peninsula

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.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

Burn wood influence on outdoor air quality in a small village: Foros de Arrão, Portugal

One Plus Sequential Air Sampler—Partisol was placed in a small village (Foros de Arrão) in central Portugal to collect PM10 (particles with an aerodynamic diameter below 10 μm), during the winter period for 3 months (December 2009–March 2010). Particles masses were gravimetrically determined and the filters were analyzed by instrumental neutron activation analysis to assess their chemical composition. The water-soluble ion compositions of the collected particles were determined by Ion-exchange Chromatography. Principal component analysis was applied to the data set of chemical elements and soluble ions to assess the main sources of the air pollutants. The use of both analytical techniques provided information about elemental solubility, such as for potassium, which was important to differentiate sources.

Indoor air quality in primary schools

Clean air is a basic requirement of life. The Indoor Air Quality (IAQ) has been the object of several studies due to an increasing concern within the scientific community on the effects of indoor air quality upon health, especially as people tend to spend more time indoors than outdoors. The quality of air inside homes, offices, schools or other private and public buildings is an essential determinant of healthy life and people’s well-being. People can be exposed to contaminants by inhalation, ingestion and dermal contact. In the past, scientists have paid much attention to the study of exposure to outdoor air contaminants, because they have realised the seriousness of outdoor air pollution problems. However, each indoor microenvironment has unique characteristics, determined by the local outdoor air, specific building characteristics and indoor activities. Indeed, hazardous substances are emitted from buildings, construction materials and indoor equipment or due to human activities indoors.

Indoor air quality in Portuguese archives: a snapshot on exposure levels

Indoor air quality recently entered legislation in Portugal. Several parameters must be evaluated and kept within limits in order to obtain a certification for air quality and energy consumption. Certification parameters were analyzed in two Portuguese archives in order to assess indoor air quality both for people attending or working on these premises and for maintenance of a written heritage that must be retained for future generations. Carbon monoxide (CO) and carbon dioxide (CO2), formaldehyde, and fungal counts were kept within stipulated limits. Relative humidity (RH), volatile organic compounds (VOC), particulate matter (PM10), and ozone (O3) showed values above legislated levels and justified the implementation of corrective measures. In terms of conservation, studies on the limit values are still needed, but according to the available international guidelines, some of the analyzed parameters such as PM10, O3, and RH were also above desirable values. Corrective measures were proposed to these institutions. Although this study was only of a short duration, it proved valuable in assessing potential eventual problems and constitutes the first Portuguese indoor air quality assessment taking into consideration both aspects of an archive such as human health and heritage safekeeping.

Integration of biomonitoring and instrumental techniques to assess the air quality in an industrial area located in the coastal of Central Asturias, Spain

Throughout the world, epidemiological studies were established to examine the relationship between air pollution and mortality rates and adverse respiratory health effects. However, despite the years of discussion the correlation between adverse health effects and atmospheric pollution remains controversial, partly because these studies are frequently restricted to small and well-monitored areas. Monitoring air pollution is complex due to the large spatial and temporal variations of pollution phenomena, the high costs of recording instruments, and the low sampling density of a purely instrumental approach. Therefore, together with the traditional instrumental monitoring, bioindication techniques allow for the mapping of pollution effects over wide areas with a high sampling density. In this study, instrumental and biomonitoring techniques were integrated to support an epidemiological study that will be developed in an industrial area located in Gijon in the coastal of central Asturias, Spain. Three main objectives were proposed to (i) analyze temporal patterns of PM10 concentrations in order to apportion emissions sources, (ii) investigate spatial patterns of lichen conductivity to identify the impact of the studied industrial area in air quality, and (iii) establish relationships amongst lichen conductivity with some site-specific characteristics. Samples of the epiphytic lichen Parmelia sulcata were transplanted in a grid of 18 by 20 km with an industrial area in the center. Lichens were exposed for a 5-mo period starting in April 2010. After exposure, lichen samples were soaked in 18-MΩ water aimed at determination of water electrical conductivity and, consequently, lichen vitality and cell damage. A marked decreasing gradient of lichens conductivity relative to distance from the emitting sources was observed. Transplants from a sampling site proximal to the industrial area reached values 10-fold higher than levels far from it. This finding showed that lichens reacted physiologically in the polluted industrial area as evidenced by increased conductivity correlated to contamination level. The integration of temporal PM10 measurements and analysis of wind direction corroborated the importance of this industrialized region for air quality measurements and identified the relevance of traffic for the urban area.

Trace Elements in Ambient Air at Porto Metropolitan Area—Checking for Compliance with New European Union (Eu) Air Quality Standards

Because of the scientific evidence showing that arsenic (As), cadmium (Cd), and nickel (Ni) are human genotoxic carcinogens, the European Union (EU) recently set target values for metal concentration in ambient air (As: 6 ng/m3, Cd: 5 ng/m3, Ni: 20 ng/m3). The aim of our study was to determine the concentration levels of these trace elements in Porto Metropolitan Area (PMA) in order to assess whether compliance was occurring with these new EU air quality standards. Fine (PM2.5) and inhalable (PM10) air particles were collected from October 2011 to July 2012 at two different (urban and suburban) locations in PMA. Samples were analyzed for trace elements content by inductively coupled plasma–mass spectrometry (ICP-MS). The study focused on determination of differences in trace elements concentration between the two sites, and between PM2.5 and PM10, in order to gather information regarding emission sources. Except for chromium (Cr), the concentration of all trace elements was higher at the urban site. However, results for As, Cd, Ni, and lead (Pb) were well below the EU limit/target values (As: 1.49 ± 0.71 ng/m3; Cd: 1.67 ± 0.92 ng/m3; Ni: 3.43 ± 3.23 ng/m3; Pb: 17.1 ± 10.1 ng/m3) in the worst-case scenario. Arsenic, Cd, Ni, Pb, antimony (Sb), selenium (Se), vanadium (V), and zinc (Zn) were predominantly associated to PM2.5, indicating that anthropogenic sources such as industry and road traffic are the main source of these elements. High enrichment factors (EF > 100) were obtained for As, Cd, Pb, Sb, Se, and Zn, further confirming their anthropogenic origin.