The composition, concentration, and size of submicron aerosols were measured with a time resolution of five minutes by an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) at a rural location northwest of the Dallas-Fort Worth, TX, area for the month of June 2011. A TSI, Inc., Model AE51 aethalometer using an optical absorption technique also was deployed to measure black carbon (BC) concentrations. The total measured PM1 mass concentration ranged between 1.0 µg/m3 and 17.1 µg/m3, with a mean and standard deviation of 4.6± 2.7 µg/m3. Significant variability is observed in the time series of total PM1 and of all four HR-ToF-AMS species, particularly between June 21 and 25. The average aerosol composition was dominated by organic matter (52.1 ± 14.8%) and sulfate (28.8 ± 11.8%). Organic aerosol concentrations were positively correlated with tracers of combustion carbon monoxide (CO) and BC, the coefficients of determination were r2=064 and r2=0.48, respectively. Because of the large influence of organics on total aerosol concentration, organic data were analyzed in the context of ΔOA/ΔCO, which typically is used to investigate the relative importance of secondary organic aerosol. The average ∆OA/∆CO for the data used was 64.0 ± 26.9 µg/ (m3 ppmv), which is typical of an aged air mass. Other metrics of age include the ratio of OOAI (more oxidized) to total oxidized organic aerosol (OOA), the ratio of sulfate to total sulfur, the ratio of its oxidation products to isoprene, and the ratio of nitrogen oxides to total reactive nitrogen. All metrics point to aged air masses, but variations in these age matrices, particularly during one period of enhanced ΔOA/ΔCO, help elucidate the contributions of various precursors and processes to organic aerosols at the site.

Long and short-term exposure to particulate matter (PM) are linked to adverse heath endpoints. Evidence indicates that PM composition such as metals and organic carbon (OC) might drive the health effects. As airborne pollutants show significant intracity spatiotemporal variation, mobile sampling and distributed monitors are utilized to capture the variation pattern. The measurements are then fed to develop models to better characterize the relationship between exposure and health outcomes. Two sampling campaigns were conducted. One was sole mobile sampling in 2013 summer and winter in Pittsburgh, PA. Thirty-six sites were chosen based on three stratification variables: traffic density, proximity to point sources, and elevation. The other one was hybrid sampling network, incorporating a mobile sampling platform, 15 distributed monitors, and a supersite. We designed two case studies (transect and downtown), selected 14 neighborhoods (~1 km2), and conducted sampling in 2016 summer/fall and winter. Spatial variation of PM2.5 mass and composition was studied in the 2013 campaign. X-ray fluorescence (XRF) was used to analyze concentrations of 26 elements: Na, Mg, Al, Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb, Sr, Zr, Cd, Sb, and Pb. Trace elements had a broad range of concentrations from 0 to 300 ng/m3. Comparison of data from mobile sampling with stationary monitors showed reasonable agreement. We developed Land use regression (LUR) models to describe spatial variation of PM2.5, Si, S, Cl, K, Ca, Ti, Cr, Fe, Cu, and Zn. Independent variables included traffic influence, land-use type, and facility emissions. Models had an average R2 of 0.57 (SD = 0.16). Traffic related variables explained the most variability with an average R2 contribution of 0.20 (SD = 0.20). Overall, these results demonstrated significant intra-urban spatial variability of fine particle composition. Spatial variation of OC was based on the 2013 campaign as well. We collected organic carbon (OC) on quartz filters, quantified different OC components with thermaloptical analysis, and grouped them based on volatility in decreasing order (OC1, OC2, OC3, OC4, and pyrolyzed carbon (PC)). We compared our ambient OC concentrations (both gas and particle phase) to similar measurements from vehicle dynamometer tests, cooking emissions, biomass burning emissions, and a highway traffic tunnel. OC2 and OC3 loading on ambient filters showed a strong correlation with primary emissions while OC4 and PC were more spatially homogenous. While we tested our hypothesis of OC2 and OC3 as markers of fresh source exposure for Pittsburgh, the relationship seemed to hold at a national level. Land use regression (LUR) models were developed for the OC fractions, and models had an average R2 of 0.64 (SD = 0.09). We demonstrate that OC2 and OC3 can be useful markers for fresh emissions, OC4 is a secondary OC indicator, and PC represents both biomass burning and secondary aerosol. People with higher OC exposure are likely inhaling more fresh OC2 and OC3, since secondary OC4 and PC varies much less drastically in space or with local primary sources. With the 2016 hybrid sampling campaign, we addressed the intracity exposure patterns, as they could be more complex than intercity ones because of local traffic, restaurants, land use, and point sources. This network studied a wide range of pollutants (CO2, CO, NO2, PM1 mass and composition, and particle number PN). Mobile measurements and distributed monitors show good agreement. PN hotspots are strongly associated with restaurants and highway traffic. PN at sites with large local source impacts tends to have larger diurnal variation than daily variation, while CO in downtown center shows the opposite trend. PN exhibits the largest spatial and temporal variations. Spatial variation is generally larger than temporal variation among all five pollutants (CO2, NO2, CO, PN, and PM1). These findings provide quantitative comparison between spatial and temporal variation in different scales, and support the theoretical validity of developing long-term exposure models from short-term mobile measurement. A combined sampling network with mobile and distributed monitor could prove more valuable in studying intracity air pollution. In the 2016 hybrid sampling campaign, we also studied spatial variability of air pollution in the vicinity of monitors. Monitoring network is essential for protecting public health, though evaluation is needed to assess spatial representativeness of monitors in different environments. Mobile sampling was conducted repeatedly around 15 distributed monitors. Substantial short-range spatial variability was observed. Spatial variation was consistently larger than temporal variation for NO2 and CO at different sites. Ultrafine particles were highly dynamic both in space and time. PM1 was less spatially and temporally variable. Urban locations had more frequent episodic source plume events compared with background sites. Using a single monitor measurement to represent surrounding ~1 km2 areas could introduce an average daily exposure misclassification of 46 ppb (SD = 26) for CO (30% of regional background), 3 ppb (SD = 2) for NO2 (43% of background), 4007 #/cm3 (SD = 1909) for ultrafine particle number (64% of background), and 1.2 μg/m3 (SD = 1.0) for PM1 (13% of background). Exposure differences showed fair correlation with traditional land use covariates such as traffic and restaurant density, and the magnitude of misclassification could be even bigger for urban neighborhoods.

Different aspects of natural organic matter composition and cycling have been studied using solid-state 13C and 31P Nuclear Magnetic Resonance (NMR) spectroscopy. Depending on the specific study, complementary analytical techniques such as elemental, isotopic and molecular analyses have also been applied. Samples from a variety of environments were examined including ocean waters, marine sediments and atmospheric aerosols. Studies from all these environments illustrate differences in natural organic matter composition resulting from various factors such as sources, cycling mechanisms and redox conditions. In the marine water column, organic matter of two different size fractions (dissolved and particulate) is found to have distinctly different bulk chemical and isotopic compositions. Overall, this indicates that particulate organic matter does not form from the simple physical aggregation of dissolved organic matter, and dissolved organic matter is not the primary source for particulate organic matter. Comparison of carbon and phosphorus compositional changes with depth in the ocean within the dissolved and particulate fractions reveals differences in cycling mechanisms. In the marine water column, selective mineralization of specific carbon compounds such as carbohydrates and amino acids occurs relative other species such as lipids. Whereas for phosphorus, the relative proportion of the different functional groups are unvarying with depth. In marine sediments, NMR spectroscopy reveals P cycling for specific phases such as polyphosphates is a function of sediment redox conditions. In atmospheric aerosols 13C NMR spectroscopy shows differences in water-soluble organic carbon composition from urban versus biomass burning sources. Urban aerosols have higher aliphatic and lower aromatic compound contents relative to samples derived from biomass burning. The results of these studies provide new insights into carbon and phosphorus cycling in the environment and demonstrate the capabilities of solid-state NMR as a tool for investigating natural organic matter composition.

As altas concentrações de aerossol fino e ultrafino observadas na atmosfera de áreas urbanas possuem um importante papel no clima local e global, devido sua interação com a radiação solar e também pela característica de formação dos núcleos de condensação de nuvens (CCN). Essas altas concentrações de partículas são responsáveis pela poluição do ar, atualmente considerada como o principal problema ambiental para a saúde pública no mundo, sendo relacionada ao câncer, doenças respiratórias, cardiovasculares e o mal de Alzheimer. Nesse contexto, o presente trabalho almejou a caracterização e discriminação de fontes poluentes para o aerossol atmosférico da cidade de São Paulo, utilizando os isótopos de Pb, Zn e Cu simultaneamente. Além disso, nesse estudo também foi realizada a avaliação do efeito das fontes locais e remotas para a ativação do CCN na atmosfera dessa região. São Paulo é a maior cidade da Região Metropolitana de São Paulo (RMSP), que por sua vez é a maior megacidade da América do Sul, e está entre as dez maiores do mundo. Amostras de aerossol urbano foram coletadas no inverno de 2013 e verão de 2014 na cidade de São Paulo. Ao mesmo tempo foram coletadas, em São Paulo e Cubatão, amostras de fontes poluentes importantes para a RMSP, como aquelas relacionadas ao tráfego veicular (combustíveis, pneu, poeira de rua e aerossol de túnel), construção civil (cimento) e à área industrial de Cubatão (aerossol). Adicionalmente, foram medidas no inverno de 2014 a concentrações de CCN, a distribuição por tamanho e a concentração em número das partículas. As determinações das composições isotópicas de Pb, Zn e Cu foram realizadas com um novo procedimento analítico, desenvolvido para a separação sequencial e purificação desses elementos, a partir de uma mesma solubilização de amostra, seguida pelas análises por espectrometria de massas empregando MC-ICP-MS e TIMS. A validação da exatidão e precisão desse procedimento foi realizada pela análise de amostras de materiais de referência, aerossol e fontes poluentes. Com base nos dados isotópicos das fontes poluentes, o tráfego veicular foi diferenciado da área industrial de Cubatão utilizando as assinaturas isotópicas de Pb dessas fontes, que demonstraram grande reprodutibilidade quando comparadas com estudos anteriores. Adicionalmente, as assinaturas isotópicas da poeira de rua e dos pneus foram discriminadas das emissões veiculares em um diagrama \'delta\'66ZnJMC vs 206Pb/207Pb. As assinaturas isotópicas de Zn e Cu da poeira de rua, emissões veiculares e cimento foram discriminadas em um diagrama \'delta\'65CuNIST vs \'delta\'66ZnJMC. As contribuições das fontes para as composições isotópicas de Pb e Zn, determinadas no aerossol da cidade de São Paulo, foram quantificadas utilizando modelos de mistura ternária. Nesses modelos o tráfego veicular (57 a 66%) foi predominante, seguido pela fonte não-caracterizada (25 a 32%), que mostrou uma assinatura isotópica de Pb e Zn específica observada nas duas campanhas. A área industrial de Cubatão apresentou contribuições de 11 a 17%, enquanto a poeira de rua contribuiu em até 18% para as assinaturas de Pb e Zn no aerossol. No inverno de 2014, o tráfego veicular local, o sal marinho e a queima de biomassa foram identificadas nas amostras de aerossol por análises de PMF, trajetórias de massas de ar e pelo sistema lidar. Também foram observados eventos de formação de aerossol secundário em 35% dos dias de medição. A ativação de CCN foi menor durante o dia em relação ao período noturno, sendo esse padrão associado principalmente as emissões do tráfego veicular local. Comparando os dias com contribuições das fontes remotas, pôde-se concluir que o material particulado proveniente do tráfego veicular durante o dia mostrou o maior efeito nos parâmetros de ativação de CCN em comparação com as fontes remotas de sal marinho e queima de biomassa. / Fine and ultrafine aerosol particles in high concentrations found in the atmosphere of urban areas, play an important role in local and global climate through interaction with solar radiation and cloud condensation nuclei (CCN) formation. These high concentrations of particles are related to the air pollution, which is the major environmental problem to the public health in the world, related with cancer, cardiovascular, respiratory and Alzheimer diseases. In this context, this study reports the simultaneous use of Pb, Zn and Cu to characterize and discriminate pollutant sources of the atmospheric aerosol from São Paulo City and evaluate the effect of local and remote sources to CCN activation in the atmosphere of this area. São Paulo is the main city of Metropolitan Area of São Paulo (MASP), which is the largest megacity in South America and rank among the ten most populous in the world. Urban aerosol samples were collected during winter of 2013 and summer of 2014 in the São Paulo city. At the same time, samples of the main pollutant sources of MASP, were sampled in São Paulo and Cubatão, such as vehicular traffic (fuels, tyres, road dust and tunnel aerosol), construction (cement) and aerosol from Cubatão industrial area. In addition, CCN concentrations, particle number concentrations and size distributions were measured during the winter of 2014 in the same sampling site. The Pb, Zn and Cu isotopic composition were determined by a new analytical procedure, developed to sequential separation of these elements, using a unique sample dissolution, followed by mass spectrometry analysis by MC-ICP-MS and TIMS. Analytical procedure validation of Accuracy and precision was carried with reference materials, aerosol and pollutant source samples. Based on isotopic data obtained on the pollutant sources, vehicular traffic was differentiated from Cubatão industrial area, using Pb isotopic fingerprints of this sources, which showed long term reproducibility when compared with previous studies. In addition, road dust and tyre isotopic signatures were discriminated from vehicular emissions in a \'delta\'66ZnJMC vs 206Pb/207Pb four isotope plot. Interestingly, Zn and Cu isotopic fingerprints of road dust, vehicular emission and cement was distinguished in a \'delta\'65CuNIST vs \'delta\'66ZnJMC four isotope plot. In order to quantify contributions of sources to Pb and Zn isotopic compositions determined in aerosol from São Paulo city, ternary mixing models were performed. In these models, vehicular traffic accounted to the main contribution (57 to 66%), followed by non-characterized source (25 to 32%), with a specific Pb and Zn isotopic signature identified in aerosol during the two campaigns. Cubatão industrial area showed contributions of 11 to 17%, whereas road dust contributed 18% to Pb and Zn isotopes in aerosol. In the winter of 2014, local vehicular traffic, sea salt and biomass burning were identified in aerosol by PMF, air masses trajectories and lidar analysis. Some new particle formation (NPF) events were identified on 35% of the sampling days. CCN activation was lower during the daytime compared to nightime periods, a pattern that was found to be associated mainly with local road-traffic emissions. Comparing the days with remote sources events, we concluded that particulate matter from local vehicular emissions during the daytime have a greater effect on CCN activation parameters than that from sea salt and biomass burning remote sources.