Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA

Inhalation of airborne particulate matter (PM) is associated with a variety of adverse health outcomes. However, the relative toxicity of specific PM types—mixtures of particles of varying sizes, shapes, and chemical compositions—is not well understood. A major impediment has been the sparse distribution of surface sensors, especially those measuring speciated PM. Aerosol remote sensing from Earth orbit offers the opportunity to improve our understanding of the health risks associated with different particle types and sources. The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard NASA’s Terra satellite has demonstrated the value of near-simultaneous observations of backscattered sunlight from multiple view angles for remote sensing of aerosol abundances and particle properties over land. The Multi-Angle Imager for Aerosols (MAIA) instrument, currently in development, improves on MISR’s sensitivity to airborne particle composition by incorporating polarimetry and expanded spectral range. Spatiotemporal regression relationships generated using collocated surface monitor and chemical transport model data will be used to convert fractional aerosol optical depths retrieved from MAIA observations to near-surface PM_(10), PM_(2.5), and speciated PM_(2.5). Health scientists on the MAIA team will use the resulting exposure estimates over globally distributed target areas to investigate the association of particle species with population health effects

Diurnal and seasonal trends in the apparent density of ambient fine and coarse particles in Los Angeles

Diurnal and seasonal variations in the apparent density of ambient fine and coarse particulate matter (PM2.5 and CPM [PM2.5-10], respectively) were investigated in a location near downtown Los Angeles. The apparent densities, determined by particle mass-to-volume ratios, showed strong diurnal and seasonal variations, with higher values during the warm phase (June to August 2013) compared to cold phase (November 2012 to February 2013). PM2.5 apparent density showed minima during the morning and afternoon rush hours of the cold phase (1.20g cm(-3)), mainly due to the increased contribution of traffic-emitted soot particles, and highest values were found during the midday in the warm phase (2.38g cm(-3)). The lowest CPM apparent density was observed during the morning rush hours of the cold phase (1.41g cm(-3)), while highest in early afternoon during the warm phase (2.91g cm(-3)), most likely due to the increased wind-induced resuspension of road dust

Chemical characterization and source apportionment of indoor and outdoor fine particulate matter (PM2.5) in retirement communities of the Los Angeles Basin

Concurrent indoor and outdoor measurements of fine particulate matter (PM2.5) were conducted at three retirement homes in the Los Angeles Basin during two separate phases (cold and warm) between 2005 and 2006. Indoor-to-outdoor relationships of PM2.5 chemical constituents were determined and sources of indoor and outdoor PM2.5 were evaluated using a molecular marker-based chemical mass balance (MM-CMB) model. Indoor levels of elemental carbon (EC) along with metals and trace elements were found to be significantly affected by outdoor sources. EC, in particular, displayed very high indoor-to-outdoor (I/O) mass ratios accompanied by strong I/O correlations, illustrating the significant impact of outdoor sources on indoor levels of EC. Similarly, indoor levels of polycyclic aromatic hydrocarbons (PAHs), hopanes, and steranes were strongly correlated with their outdoor components and displayed I/O ratios close to unity. On the other hand, concentrations of n-alkanes and organic acids inside the retirement communities were dominated by indoor sources (e.g. food cooking and consumer products), as indicated by their I/O ratios, which exceeded unity. Source apportionment results revealed that vehicular emissions were the major contributor to both indoor and outdoor PM2.5, accounting for 39 and 46% of total mass, respectively. Moreover, the contribution of vehicular sources to indoor levels was generally comparable to its corresponding outdoor estimate. Other water-insoluble organic matter (other WIOM), which accounts for emissions from uncharacterized primary biogenic sources, displayed a wider range of contributions, varying from 2 to 73% of PM2.5, across all sites and phases of the study. Lastly, higher indoor than outdoor contribution of other water-soluble organic matter (other WSOM) was evident at some of the sites, suggesting the production of secondary aerosols as well as direct emissions from primary sources (including cleaning or other consumer products) at the indoor environments

Land use regression models for ultrafine particles, fine particles, and black carbon in Southern California

Exposure models are needed to evaluate health effects of long-term exposure to ambient ultrafine particles (UFP; <0.1 μm) and to disentangle their association from other pollutants, particularly PM2.5 (<2.5 μm). We developed land use regression (LUR) models to support UFP exposure assessment in the Los Angeles Ultrafines Study, a cohort in Southern California. We conducted a short-term measurement campaign in Los Angeles and parts of Riverside and Orange counties to measure UFP, PM2.5, and black carbon (BC), collecting three 30-minute average measurements at 215 sites across three seasons. We averaged concentrations for each site and evaluated geographic predictors including traffic intensity, distance to airports, land use, and population and building density by supervised stepwise selection to develop models. UFP and PM2.5 measurements (r = 0.001) and predictions (r = 0.05) were uncorrelated at the sites. UFP model explained variance was robust (R2 = 0.66) and 10-fold cross-validation indicated good performance (R2 = 0.59). Explained variation was moderate for PM2.5 (R2 = 0.47) and BC (R2 = 0.38). In the cohort, we predicted a 2.3-fold exposure contrast from the 5th to 95th percentiles for all three pollutants. The correlation between modeled UFP and PM2.5 at cohort residences was weak (r = 0.28), although higher than between measured levels. LUR models, particularly for UFP, were successfully developed and predicted reasonable exposure contrasts

Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA

Inhalation of airborne particulate matter (PM) is associated with a variety of adverse health outcomes. However, the relative toxicity of specific PM types-mixtures of particles of varying sizes, shapes, and chemical compositions-is not well understood. A major impediment has been the sparse distribution of surface sensors, especially those measuring speciated PM. Aerosol remote sensing from Earth orbit offers the opportunity to improve our understanding of the health risks associated with different particle types and sources. The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard NASA's Terra satellite has demonstrated the value of near-simultaneous observations of backscattered sunlight from multiple view angles for remote sensing of aerosol abundances and particle properties over land. The Multi-Angle Imager for Aerosols (MAIA) instrument, currently in development, improves on MISR's sensitivity to airborne particle composition by incorporating polarimetry and expanded spectral range. Spatiotemporal regression relationships generated using collocated surface monitor and chemical transport model data will be used to convert fractional aerosol optical depths retrieved from MAIA observations to near-surface PM10, PM2.5, and speciated PM2.5. Health scientists on the MAIA team will use the resulting exposure estimates over globally distributed target areas to investigate the association of particle species with population health effects. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]