Semiparametric Latent Variable Regression Models for Spatio-temporal Modeling of Mobile Source Particles in the Greater Boston Area

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separately

Microgram level radiocarbon (14C) determination on carbonaceous particles in ice

In climate research the interest on carbonaceous particles has increased over the last years because of their influence on the radiation balance of the earth. Nevertheless, there is a paucity of available data regarding their concentrations and sources in the past. Such data would be important for a better understanding of their effects and for estimating their influence on future climate. Here, a technique is described to extract carbonaceous particles from ice core samples with subsequent separation of the two main constituents into organic carbon (OC) and elemental carbon (EC) for analysis of their concentrations in the past. This is combined with further analysis of OC and EC 14C/12C ratios by accelerator mass spectrometry (AMS), what can be used for source apportionment studies of past emissions. We further present how 14C analysis of the OC fraction could be used in the future to date any ice core extracted from a high-elevation glacier. Described sample preparation steps to final analysis include the combustion of micrograms of water–insoluble carbonaceous particles, primary collected by filtration of melted ice samples, the graphitisation of the obtained CO2 to solid AMS target material and final AMS measurements. Possible fractionation processes were investigated for quality assurance. Procedural blanks were reproducible and resulted in carbon masses of 1.3 ± 0.6 μg OC and 0.3 ± 0.1 μg EC per filter. The determined fraction of modern carbon (fM) for the OC blank was 0.61 ± 0.13. The analysis of processed IAEA-C6 and IAEA-C7 reference material resulted in fM = 1.521 ± 0.011 and δ13C = −10.85 ± 0.19‰, and fM = 0.505 ± 0.011 and δ13C = −14.21 ± 0.19‰, respectively, in agreement with consensus values. Initial carbon contents were thereby recovered with an average yield of 93%.

Translocation of particles and inflammatory responses after exposure to fine particles and nanoparticles in an epithelial airway model

ABSTRACT: BACKGROUND: Experimental studies provide evidence that inhaled nanoparticles may translocate over the airspace epithelium and cause increased cellular inflammation. Little is known, however, about the dependence of particle size or material on translocation characteristics, inflammatory response and intracellular localization. RESULTS: Using a triple cell co-culture model of the human airway wall composed of epithelial cells, macrophages and dendritic cells we quantified the entering of fine (1 mum) and nano-sized (0.078 mum) polystyrene particles by laser scanning microscopy. The number distribution of particles within the cell types was significantly different between fine and nano-sized particles suggesting different translocation characteristics. Analysis of the intracellular localization of gold (0.025 mum) and titanium dioxide (0.02-0.03 mum) nanoparticles by energy filtering transmission electron microscopy showed differences in intracellular localization depending on particle composition. Titanium dioxide nanoparticles were detected as single particles without membranes as well as in membrane-bound agglomerations. Gold nanoparticles were found inside the cells as free particles only. The potential of the different particle types (different sizes and different materials) to induce a cellular response was determined by measurements of the tumour necrosis factor-alpha in the supernatants. We measured a 2-3 fold increase of tumour necrosis factor-alpha in the supernatants after applying 1 mum polystyrene particles, gold nanoparticles, but not with polystyrene and titanium dioxide nanoparticles. CONCLUSION: Quantitative laser scanning microscopy provided evidence that the translocation and entering characteristics of particles are size-dependent. Energy filtering transmission electron microscopy showed that the intracellular localization of nanoparticles depends on the particle material. Both particle size and material affect the cellular responses to particle exposure as measured by the generation of tumour necrosis factor-alpha.