Aplicação de regressão baseada no uso do solo para predizer a concentração de material particulado inalável no município de São Paulo, Brasil

O estudo teve por objetivo construir um modelo de regressão baseada no uso do solo para predizer a concentração material particulado inalável (MP10) no município de São Paulo, Brasil. O estudo se baseou na média de MP10 de 2007 de 9 estações de monitoramento. Obtiveram-se dados demográficos, viários e de uso do solo em círculos concêntricos de 250 a 1.000 m para compor o modelo. Calculou-se regressão linear simples para selecionar as variáveis mais robustas e sem colinearidade. Quatro variáveis entraram no modelo de regressão múltipla. Somente tráfego leve em círculos concêntricos <250 m permaneceu no modelo final, que explicou 63,8% da variância de MP10. Verificou-se que o método de regressão baseada no uso do solo é rápido, de fácil execução. Entretanto, este modelo se baseou em medições de MP10 de poucos locais.

Quantifying and modeling ecosystem services provided by urban greening in cities of the Southern Alps, N Italy

Population growth in urban areas is a world-wide phenomenon. According to a recent United Nations report, over half of the world now lives in cities. Numerous health and environmental issues arise from this unprecedented urbanization. Recent studies have demonstrated the effectiveness of urban green spaces and the role they play in improving both the aesthetics and the quality of life of its residents. In particular, urban green spaces provide ecosystem services such as: urban air quality improvement by removing pollutants that can cause serious health problems, carbon storage, carbon sequestration and climate regulation through shading and evapotranspiration. Furthermore, epidemiological studies with controlled age, sex, marital and socio-economic status, have provided evidence of a positive relationship between green space and the life expectancy of senior citizens. However, there is little information on the role of public green spaces in mid-sized cities in northern Italy. To address this need, a study was conducted to assess the ecosystem services of urban green spaces in the city of Bolzano, South Tyrol, Italy. In particular, we quantified the cooling effect of urban trees and the hourly amount of pollution removed by the urban forest. The information was gathered using field data collected through local hourly air pollution readings, tree inventory and simulation models. During the study we quantified pollution removal for ozone, nitrogen dioxide, carbon monoxide and particulate matter (<10 microns). We estimated the above ground carbon stored and annually sequestered by the urban forest. Results have been compared to transportation CO2 emissions to determine the CO2 offset potential of urban streetscapes. Furthermore, we assessed commonly used methods for estimating carbon stored and sequestered by urban trees in the city of Bolzano. We also quantified ecosystem disservices such as hourly urban forest volatile organic compound emissions.

Origin and variability of PM10 and atmospheric radiotracers at the WMO-GAW station of Mt. Cimone (1998-2011) and in the central Po Valley

Particulate matter is one of the main atmospheric pollutants, with a great chemical-environmental relevance. Improving knowledge of the sources of particulate matter and of their apportionment is needed to handle and fulfill the legislation regarding this pollutant, to support further development of air policy as well as air pollution management. Various instruments have been used to understand the sources of particulate matter and atmospheric radiotracers at the site of Mt. Cimone (44.18° N, 10.7° E, 2165 m asl), hosting a global WMO-GAW station. Thanks to its characteristics, this location is suitable investigate the regional and long-range transport of polluted air masses on the background Southern-Europe free-troposphere. In particular, PM10 data sampled at the station in the period 1998-2011 were analyzed in the framework of the main meteorological and territorial features. A receptor model based on back trajectories was applied to study the source regions of particulate matter. Simultaneous measurements of atmospheric radionuclides Pb-210 and Be-7 acquired together with PM10 have also been analysed to acquire a better understanding of vertical and horizontal transports able to affect atmospheric composition. Seasonal variations of atmospheric radiotracers have been studied both analysing the long-term time series acquired at the measurement site as well as by means of a state-of-the-art global 3-D chemistry and transport model. Advection patterns characterizing the circulation at the site have been identified by means of clusters of back-trajectories. Finally, the results of a source apportionment study of particulate matter carried on in a midsize town of the Po Valley (actually recognised as one of the most polluted European regions) are reported. An approach exploiting different techniques, and in particular different kinds of models, successfully achieved a characterization of the processes/sources of particulate matter at the two sites, and of atmospheric radiotracers at the site of Mt. Cimone.

Kinetic modeling and experiments on gas uptake and chemical transformation of organic aerosol in the atmosphere

Aerosolpartikel beeinflussen das Klima durch Streuung und Absorption von Strahlung sowie als Nukleations-Kerne für Wolkentröpfchen und Eiskristalle. Darüber hinaus haben Aerosole einen starken Einfluss auf die Luftverschmutzung und die öffentliche Gesundheit. Gas-Partikel-Wechselwirkunge sind wichtige Prozesse, weil sie die physikalischen und chemischen Eigenschaften von Aerosolen wie Toxizität, Reaktivität, Hygroskopizität und optische Eigenschaften beeinflussen. Durch einen Mangel an experimentellen Daten und universellen Modellformalismen sind jedoch die Mechanismen und die Kinetik der Gasaufnahme und der chemischen Transformation organischer Aerosolpartikel unzureichend erfasst. Sowohl die chemische Transformation als auch die negativen gesundheitlichen Auswirkungen von toxischen und allergenen Aerosolpartikeln, wie Ruß, polyzyklische aromatische Kohlenwasserstoffe (PAK) und Proteine, sind bislang nicht gut verstanden.rn Kinetische Fluss-Modelle für Aerosoloberflächen- und Partikelbulk-Chemie wurden auf Basis des Pöschl-Rudich-Ammann-Formalismus für Gas-Partikel-Wechselwirkungen entwickelt. Zunächst wurde das kinetische Doppelschicht-Oberflächenmodell K2-SURF entwickelt, welches den Abbau von PAK auf Aerosolpartikeln in Gegenwart von Ozon, Stickstoffdioxid, Wasserdampf, Hydroxyl- und Nitrat-Radikalen beschreibt. Kompetitive Adsorption und chemische Transformation der Oberfläche führen zu einer stark nicht-linearen Abhängigkeit der Ozon-Aufnahme bezüglich Gaszusammensetzung. Unter atmosphärischen Bedingungen reicht die chemische Lebensdauer von PAK von wenigen Minuten auf Ruß, über mehrere Stunden auf organischen und anorganischen Feststoffen bis hin zu Tagen auf flüssigen Partikeln. rn Anschließend wurde das kinetische Mehrschichtenmodell KM-SUB entwickelt um die chemische Transformation organischer Aerosolpartikel zu beschreiben. KM-SUB ist in der Lage, Transportprozesse und chemische Reaktionen an der Oberfläche und im Bulk von Aerosol-partikeln explizit aufzulösen. Es erforder im Gegensatz zu früheren Modellen keine vereinfachenden Annahmen über stationäre Zustände und radiale Durchmischung. In Kombination mit Literaturdaten und neuen experimentellen Ergebnissen wurde KM-SUB eingesetzt, um die Effekte von Grenzflächen- und Bulk-Transportprozessen auf die Ozonolyse und Nitrierung von Protein-Makromolekülen, Ölsäure, und verwandten organischen Ver¬bin-dungen aufzuklären. Die in dieser Studie entwickelten kinetischen Modelle sollen als Basis für die Entwicklung eines detaillierten Mechanismus für Aerosolchemie dienen sowie für das Herleiten von vereinfachten, jedoch realistischen Parametrisierungen für großskalige globale Atmosphären- und Klima-Modelle. rn Die in dieser Studie durchgeführten Experimente und Modellrechnungen liefern Beweise für die Bildung langlebiger reaktiver Sauerstoff-Intermediate (ROI) in der heterogenen Reaktion von Ozon mit Aerosolpartikeln. Die chemische Lebensdauer dieser Zwischenformen beträgt mehr als 100 s, deutlich länger als die Oberflächen-Verweilzeit von molekularem O3 (~10-9 s). Die ROIs erklären scheinbare Diskrepanzen zwischen früheren quantenmechanischen Berechnungen und kinetischen Experimenten. Sie spielen eine Schlüsselrolle in der chemischen Transformation sowie in den negativen Gesundheitseffekten von toxischen und allergenen Feinstaubkomponenten, wie Ruß, PAK und Proteine. ROIs sind vermutlich auch an der Zersetzung von Ozon auf mineralischem Staub und an der Bildung sowie am Wachstum von sekundären organischen Aerosolen beteiligt. Darüber hinaus bilden ROIs eine Verbindung zwischen atmosphärischen und biosphärischen Mehrphasenprozessen (chemische und biologische Alterung).rn Organische Verbindungen können als amorpher Feststoff oder in einem halbfesten Zustand vorliegen, der die Geschwindigkeit von heterogenen Reaktionenen und Mehrphasenprozessen in Aerosolen beeinflusst. Strömungsrohr-Experimente zeigen, dass die Ozonaufnahme und die oxidative Alterung von amorphen Proteinen durch Bulk-Diffusion kinetisch limitiert sind. Die reaktive Gasaufnahme zeigt eine deutliche Zunahme mit zunehmender Luftfeuchte, was durch eine Verringerung der Viskosität zu erklären ist, bedingt durch einen Phasenübergang der amorphen organischen Matrix von einem glasartigen zu einem halbfesten Zustand (feuchtigkeitsinduzierter Phasenübergang). Die chemische Lebensdauer reaktiver Verbindungen in organischen Partikeln kann von Sekunden bis zu Tagen ansteigen, da die Diffusionsrate in der halbfesten Phase bei niedriger Temperatur oder geringer Luftfeuchte um Größenordnungen absinken kann. Die Ergebnisse dieser Studie zeigen wie halbfeste Phasen die Auswirkung organischeer Aerosole auf Luftqualität, Gesundheit und Klima beeinflussen können. rn

Entwicklung und Anwendung von mobilen Messstrategien und Analysemethoden zur Untersuchung urbanen Aerosols

Seit Anbeginn der Menschheitsgeschichte beeinflussen die Menschen ihre Umwelt. Durch anthropogene Emissionen ändert sich die Zusammensetzung der Atmosphäre, was einen zunehmenden Einfluss unter anderem auf die Atmosphärenchemie, die Gesundheit von Mensch, Flora und Fauna und das Klima hat. Die steigende Anzahl riesiger, wachsender Metropolen geht einher mit einer räumlichen Konzentration der Emission von Luftschadstoffen, was vor allem einen Einfluss auf die Luftqualität der windabwärts gelegenen ruralen Regionen hat. In dieser Doktorarbeit wurde im Rahmen des MEGAPOLI-Projektes die Abluftfahne der Megastadt Paris unter Anwendung des mobilen Aerosolforschungslabors MoLa untersucht. Dieses ist mit modernen, zeitlich hochauflösenden Instrumenten zur Messung der chemischen Zusammensetzung und Größenverteilung der Aerosolpartikel sowie einiger Spurengase ausgestattet. Es wurden mobile Messstrategien entwickelt und angewendet, die besonders geeignet zur Charakterisierung urbaner Emissionen sind. Querschnittsmessfahrten durch die Abluftfahne und atmosphärische Hintergrundluftmassen erlaubten sowohl die Bestimmung der Struktur und Homogenität der Abluftfahne als auch die Berechnung des Beitrags der urbanen Emissionen zur Gesamtbelastung der Atmosphäre. Quasi-Lagrange’sche Radialmessfahrten dienten der Erkundung der räumlichen Erstreckung der Abluftfahne sowie auftretender Transformationsprozesse der advehierten Luftschadstoffe. In Kombination mit Modellierungen konnte die Struktur der Abluftfahne vertieft untersucht werden. Flexible stationäre Messungen ergänzten den Datensatz und ließen zudem Vergleichsmessungen mit anderen Messstationen zu. Die Daten einer ortsfesten Messstation wurden zusätzlich verwendet, um die Alterung des organischen Partikelanteils zu beschreiben. Die Analyse der mobilen Messdaten erforderte die Entwicklung einer neuen Methode zur Bereinigung des Datensatzes von lokalen Störeinflüssen. Des Weiteren wurden die Möglichkeiten, Grenzen und Fehler bei der Anwendung komplexer Analyseprogramme zur Berechnung des O/C-Verhältnisses der Partikel sowie der Klassifizierung der Aerosolorganik untersucht. Eine Validierung verschiedener Methoden zur Bestimmung der Luftmassenherkunft war für die Auswertung ebenfalls notwendig. Die detaillierte Untersuchung der Abluftfahne von Paris ergab, dass diese sich anhand der Erhöhung der Konzentrationen von Indikatoren für unprozessierte Luftverschmutzung im Vergleich zu Hintergrundwerten identifizieren lässt. Ihre eher homogene Struktur kann zumeist durch eine Gauß-Form im Querschnitt mit einem exponentiellen Abfall der unprozessierten Schadstoffkonzentrationen mit zunehmender Distanz zur Stadt beschrieben werden. Hierfür ist hauptsächlich die turbulente Vermischung mit Umgebungsluftmassen verantwortlich. Es konnte nachgewiesen werden, dass in der advehierten Abluftfahne eine deutliche Oxidation der Aerosolorganik im Sommer stattfindet; im Winter hingegen ließ sich dieser Prozess während der durchgeführten Messungen nicht beobachten. In beiden Jahreszeiten setzt sich die Abluftfahne hauptsächlich aus Ruß und organischen Partikelkomponenten im PM1-Größenbereich zusammen, wobei die Quellen Verkehr und Kochen sowie zusätzlich Heizen in der kalten Jahreszeit dominieren. Die PM1-Partikelmasse erhöhte sich durch die urbanen Emissionen im Vergleich zum Hintergrundwert im Sommer in der Abluftfahne im Mittel um 30% und im Winter um 10%. Besonders starke Erhöhungen ließen sich für Polyaromaten beobachten, wo im Sommer eine mittlere Zunahme von 194% und im Winter von 131% vorlag. Jahreszeitliche Unterschiede waren ebenso in der Größenverteilung der Partikel der Abluftfahne zu finden, wo im Winter im Gegensatz zum Sommer keine zusätzlichen nukleierten kleinen Partikel, sondern nur durch Kondensation und Koagulation angewachsene Partikel zwischen etwa 10nm und 200nm auftraten. Die Spurengaskonzentrationen unterschieden sich ebenfalls, da chemische Reaktionen temperatur- und mitunter strahlungsabhängig sind. Weitere Anwendungsmöglichkeiten des MoLa wurden bei einer Überführungsfahrt von Deutschland an die spanische Atlantikküste demonstriert, woraus eine Kartierung der Luftqualität entlang der Fahrtroute resultierte. Es zeigte sich, dass hauptsächlich urbane Ballungszentren von unprozessierten Luftschadstoffen betroffen sind, advehierte gealterte Substanzen jedoch jede Region beeinflussen können. Die Untersuchung der Luftqualität an Standorten mit unterschiedlicher Exposition bezüglich anthropogener Quellen erweiterte diese Aussage um einen Einblick in die Variation der Luftqualität, abhängig unter anderem von der Wetterlage und der Nähe zu Emissionsquellen. Damit konnte gezeigt werden, dass sich die entwickelten Messstrategien und Analysemethoden nicht nur zur Untersuchung der Abluftfahne einer Großstadt, sondern auch auf verschiedene andere wissenschaftliche und umweltmesstechnische Fragestellungen anwenden lassen.

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.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Reduced Bayesian Hierarchical Models: Estimating Health Effects of Simultaneous Exposure to Multiple Pollutants

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.

PM2.5-bound oxygenated PAHs, nitro-PAHs and parent-PAHs from the atmosphere of a Chinese megacity: seasonal variation, sources and cancer risk assessment

Polycyclic aromatic compounds (PACs) in air particulate matter contribute considerably to the health risk of air pollution. The objectives of this study were to assess the occurrence and variation in concentrations and sources of PM2.5-bound PACs [Oxygenated PAHs (OPAHs), nitro-PAHs and parent-PAHs] sampled from the atmosphere of a typical Chinese megacity (Xi'an), to study the influence of meteorological conditions on PACs and to estimate the lifetime excess cancer risk to the residents of Xi'an (from inhalation of PM2.5-bound PACs). To achieve these objectives, we sampled 24-h PM2.5 aerosols (once in every 6 days, from 5 July 2008 to 8 August 2009) from the atmosphere of Xi'an and measured the concentrations of PACs in them. The PM2.5-bound concentrations of Σcarbonyl-OPAHs, ∑ hydroxyl + carboxyl-OPAHs, Σnitro-PAHs and Σalkyl + parent-PAHs ranged between 5–22, 0.2–13, 0.3–7, and 7–387 ng m− 3, respectively, being markedly higher than in most western cities. This represented a range of 0.01–0.4% and 0.002–0.06% of the mass of organic C in PM2.5 and the total mass of PM2.5, respectively. The sums of the concentrations of each compound group had winter-to-summer ratios ranging from 3 to 8 and most individual OPAHs and nitro-PAHs had higher concentrations in winter than in summer, suggesting a dominant influence of emissions from household heating and winter meteorological conditions. Ambient temperature, air pressure, and wind speed explained a large part of the temporal variation in PACs concentrations. The lifetime excess cancer risk from inhalation (attributable to selected PAHs and nitro-PAHs) was six fold higher in winter (averaging 1450 persons per million residents of Xi'an) than in summer. Our results call for the development of emission control measures.

A Study of Radon in Air and Water in Maine Schools

The transfer coefficient of radon from water to air was investigated in schools. Kitchens, bathrooms and locker rooms were studied for seven schools in Maine. Simulations were done in water-use rooms where radon in air detectors were in place. Quantities measured were radon in water (270-24500 F) and air (0-80 q), volume of water used, emissivities (0.01-0.99) and ventilation rates (0.012-0.066A). Variation throughout the room of the radon concentration was found. Values calculated for the transfer coefficient for kitchens and baths were ranged from 9.6 x to 2.0 x The transfer coefficient was calculated using these parameters and was also measured using concentrations of radon in water and air. This provides a means by which radon in air can be estimated using the transfer coefficient and the concentration in the water in other schools and it can be used to estimate the dose caused by radon released from water use. This project was partially funded by the United States Environmental Protection Agency (grant #X828l2 101-0) and by the State of Maine (grant #10A500178). These are the first measurements of this type to be done in schools in the United States.

Hazardous air pollutants and childhood lymphohematopoietic cancer in Southeast Texas, 1995--2004

Southeast Texas, including Houston, has a large presence of industrial facilities and has been documented to have poorer air quality and significantly higher cancer rates than the remainder of Texas. Given citizens’ concerns in this 4th largest city in the U.S., Mayor Bill White recently partnered with the UT School of Public Health to determine methods to evaluate the health risks of hazardous air pollutants (HAPs). Sexton et al. (2007) published a report that strongly encouraged analytic studies linking these pollutants with health outcomes. In response, we set out to complete the following aims: 1. determine the optimal exposure assessment strategy to assess the association between childhood cancer rates and increased ambient levels of benzene and 1,3-butadiene (in an ecologic setting) and 2. evaluate whether census tracts with the highest levels of benzene or 1,3-butadiene have higher incidence of childhood lymphohematopoietic cancer compared with census tracts with the lowest levels of benzene or 1,3-butadiene, using Poisson regression. The first aim was achieved by evaluating the usefulness of four data sources: geographic information systems (GIS) to identify proximity to point sources of industrial air pollution, industrial emission data from the U.S. EPA’s Toxic Release Inventory (TRI), routine monitoring data from the U.S. EPA Air Quality System (AQS) from 1999-2000 and modeled ambient air levels from the U.S. EPA’s 1999 National Air Toxic Assessment Project (NATA) ASPEN model. Further, once these four data sources were evaluated, we narrowed them down to two: the routine monitoring data from the AQS for the years 1998-2000 and the 1999 U.S. EPA NATA ASPEN modeled data. We applied kriging (spatial interpolation) methodology to the monitoring data and compared the kriged values to the ASPEN modeled data. Our results indicated poor agreement between the two methods. Relative to the U.S. EPA ASPEN modeled estimates, relying on kriging to classify census tracts into exposure groups would have caused a great deal of misclassification. To address the second aim, we additionally obtained childhood lymphohematopoietic cancer data for 1995-2004 from the Texas Cancer Registry. The U.S. EPA ASPEN modeled data were used to estimate ambient levels of benzene and 1,3-butadiene in separate Poisson regression analyses. All data were analyzed at the census tract level. We found that census tracts with the highest benzene levels had elevated rates of all leukemia (rate ratio (RR) = 1.37; 95% confidence interval (CI), 1.05-1.78). Among census tracts with the highest 1,3-butadiene levels, we observed RRs of 1.40 (95% CI, 1.07-1.81) for all leukemia. We detected no associations between benzene or 1,3-butadiene levels and childhood lymphoma incidence. This study is the first to examine this association in Harris and surrounding counties in Texas and is among the first to correlate monitored levels of HAPs with childhood lymphohematopoietic cancer incidence, evaluating several analytic methods in an effort to determine the most appropriate approach to test this association. Despite recognized weakness of ecologic analyses, our analysis suggests an association between childhood leukemia and hazardous air pollution.^

The role of municipalities in air toxics regulation: The Houston experience

The federal regulatory regime for addressing airborne toxic pollutants functions fairly well in most of the country. However, it has proved deficient in addressing local risk issues, especially in urban areas with densely concentrated sources. The problem is especially pronounced in Houston, which is home to one of the world's biggest petrochemical complexes and a major port, both located near a large metropolitan center. Despite the fact that local government's role in regulating air toxics is typically quite limited, from 2004-2009, the City of Houston implemented a novel municipality-based air toxics reduction strategy. The initiatives ranged from voluntary agreements to litigation and legislation. This case study considers why the city chose the policy tools it did, how the tools performed relative to the designers' intentions, and how the debate among actors with conflicting values and goals shaped the policy landscape. The city's unconventional approach to controlling hazardous air pollution has not yet been examined rigorously. The case study was developed through reviews of publicly available documents and quasi-public documents obtained through public record requests, as well as interviews with key informants. The informants represented a range of experience and perspectives. They included current and former public officials at the city (including Mayor White), former Texas Commission on Environmental Quality staff, faculty at local universities, industry representatives, and environmental public health advocates. Some of the city's tools were successful in meeting their designers' intent, some were less successful. Ultimately, even those tools that did not achieve their stated purpose were nonetheless successful in bringing attention and resources to the air quality issue. Through a series of pleas and prods, the city managed to draw attention to the problem locally and get reluctant policymakers at higher levels of government to respond. This work demonstrates the potential for local government to overcome limitations in the federal regulatory regime for air toxics control, shifting the balance of local, state, and federal initiative. It also highlights the importance of flexible, cooperative strategies in local environmental protection.^

ANN and Fuzzy c-Means applied to environmental pollution prediction

Salamanca, situated in center of Mexico is among the cities which suffer most from the air pollution in Mexico. The vehicular park and the industry, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Sulphur Dioxide (SO2). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables and air pollutant concentrations of SO2. Before the prediction, Fuzzy c-Means and K-means clustering algorithms have been implemented in order to find relationship among pollutant and meteorological variables. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of SO2 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours.

Air quality modeling and mortality impact of fine particles reduction policies in Spain

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