Improving quantitative analysis of spark-induced breakdown spectroscopy: Multivariate calibration of metal particles using machine learning.

We have recently developed a low-cost spark-induced breakdown spectroscopy (SIBS) instrument for in-situ analysis of toxic metal aerosol particles that we call TARTA (toxic-metal aerosol real time analyzer). In this work, we applied machine learning methods to improve the quantitative analysis of elemental mass concentrations measured by this instrument. Specifically, we applied least absolute shrinkage and selection operator (LASSO), partial least squares (PLS) regression, principal component regression (PCR), and support vector regression (SVR) to develop multivariate calibration models for 13 metals (e.g., Cr, Cu, Mn, Fe, Zn, Co, Al, K, Be, Hg, Cd, Pb, and Ni), some of which are included on the US EPA hazardous air pollutants (HAPS) list. The calibration performance, adjusted coefficient of determination (R2) and normalized root mean square error (RMSE), and limit of detection (LOD) of the proposed models were compared to those of univariate calibration models for each analyte. Our results suggest that machine learning models tend to have better prediction accuracy and lower LODs than conventional univariate calibration, of which the LASSO approach performs the best with R2 > 0.8 and LODs of 40-170 ng m-3 at a sampling time of 30 min and a flow rate of 15 l min -1. We then assessed the applicability of the LASSO model for quantifying elemental concentrations in mixtures of these metals, serving as independent validation datasets. Ultimately, the LASSO model developed in this work is a very promising machine learning approach for quantifying mass concentration of metals in aerosol particles using TARTA.

The performance of an inexpensive spark-induced breakdown spectroscopy instrument for near real-time analysis of toxic metal particles.

To meet the demand for identifying and controlling toxic air contaminants in environmental justice communities, we have recently developed a cost-effective spark-induced breakdown spectroscopy (SIBS) instrument for detecting and quantifying toxic metal air pollutants. We characterized the detection limit and linearity of this SIBS instrument by analyzing nebulized elemental standard solutions. The experimental parameters affecting SIBS performance were optimized, including the time delay to observation, the distance between electrodes, and the ablation voltage. The instrument successfully detected Cr, Cu, Mn, Fe, Zn, Co, and Ni, with limits of detection ranged from 0.05 µg m-3 to 0.81 µg m-3 at a flow rate of 15 l min-1 and a 30 min sampling duration. Similar to other investigations using ion breakdown spectroscopy, we did not observe strong emissions lines for As, Sb, Se, Hg, Pb, and Cd, which were likely due to spectral overlap, matrix effects, and the limited detection range of the optical components. Overall, SIBS is a promising technique for field measurements of toxic metals for environmental justice, industrial and urban applications.

Chronic exposure to traffic-related air pollution reduces lipid mediators of linoleic acid and soluble epoxide hydrolase in serum of female rats.

Chronic exposure to traffic-related air pollution (TRAP) is known to promote systemic inflammation, which is thought to underlie respiratory, cardiovascular, metabolic and neurological disorders. It is not known whether chronic TRAP exposure dampens inflammation resolution, the homeostatic process for stopping inflammation and repairing damaged cells. In vivo, inflammation resolution is facilitated by bioactive lipid mediators known as oxylipins, which are derived from the oxidation of polyunsaturated fatty acids. To understand the effects of chronic TRAP exposure on lipid-mediated inflammation resolution pathways, we measured total (i.e. free+bound) pro-inflammatory and pro-resolving lipid mediators in serum of female rats exposed to TRAP or filtered air (FA) for 14 months. Compared to rats exposed to FA, TRAP-exposed rats showed a significant 36-48% reduction in fatty acid alcohols, specifically, 9-hydroxyoctadecadienoic acid (9-HODE), 11,12-dihydroxyeicosatetraenoic acid (11,12-DiHETE) and 16,17-dihydroxydocosapentaenoic acid (16, 17-DiHDPA). The decrease in fatty acid diols (11,12-DiHETE and 16, 17-DiHDPA) corresponded to a significant 34-39% reduction in the diol to epoxide ratio, a marker of soluble epoxide hydrolase activity; this enzyme is typically upregulated during inflammation. The findings demonstrate that 14 months exposure to TRAP reduced pro-inflammatory 9-HODE concentration and dampened soluble epoxide hydrolase activation, suggesting adaptive immune changes in lipid mediator pathways involved in inflammation resolution.

Comparative computational modeling of airflows and vapor dosimetry in the respiratory tracts of rat, monkey, and human.

Computational fluid dynamics (CFD) models are useful for predicting site-specific dosimetry of airborne materials in the respiratory tract and elucidating the importance of species differences in anatomy, physiology, and breathing patterns. We improved the imaging and model development methods to the point where CFD models for the rat, monkey, and human now encompass airways from the nose or mouth to the lung. A total of 1272, 2172, and 135 pulmonary airways representing 17±7, 19±9, or 9±2 airway generations were included in the rat, monkey and human models, respectively. A CFD/physiologically based pharmacokinetic model previously developed for acrolein was adapted for these anatomically correct extended airway models. Model parameters were obtained from the literature or measured directly. Airflow and acrolein uptake patterns were determined under steady-state inhalation conditions to provide direct comparisons with prior data and nasal-only simulations. Results confirmed that regional uptake was sensitive to airway geometry, airflow rates, acrolein concentrations, air:tissue partition coefficients, tissue thickness, and the maximum rate of metabolism. Nasal extraction efficiencies were predicted to be greatest in the rat, followed by the monkey, and then the human. For both nasal and oral breathing modes in humans, higher uptake rates were predicted for lower tracheobronchial tissues than either the rat or monkey. These extended airway models provide a unique foundation for comparing material transport and site-specific tissue uptake across a significantly greater range of conducting airways in the rat, monkey, and human than prior CFD models.

Susceptibility to inhaled flame-generated ultrafine soot in neonatal and adult rat lungs.

Over a quarter of the U.S. population is exposed to harmful levels of airborne particulate matter (PM) pollution, which has been linked to development and exacerbation of respiratory diseases leading to morbidity and mortality, especially in susceptible populations. Young children are especially susceptible to PM and can experience altered anatomic, physiologic, and biological responses. Current studies of ambient PM are confounded by the complex mixture of soot, metals, allergens, and organics present in the complex mixture as well as seasonal and temporal variance. We have developed a laboratory-based PM devoid of metals and allergens that can be replicated to study health effects of specific PM components in animal models. We exposed 7-day-old postnatal and adult rats to a single 6-h exposure of fuel-rich ultrafine premixed flame particles (PFPs) or filtered air. These particles are high in polycyclic aromatic hydrocarbons content. Pulmonary cytotoxicity, gene, and protein expression were evaluated at 2 and 24 h postexposure. Neonates were more susceptible to PFP, exhibiting increased lactate dehydrogenase activity in bronchoalveolar lavage fluid and ethidium homodimer-1 cellular staining in the lung in situ as an index of cytotoxicity. Basal gene expression between neonates and adults differed for a significant number of antioxidant, oxidative stress, and proliferation genes and was further altered by PFP exposure. PFP diminishes proliferation marker PCNA gene and protein expression in neonates but not adults. We conclude that neonates have an impaired ability to respond to environmental exposures that increases lung cytotoxicity and results in enhanced susceptibility to PFP, which may lead to abnormal airway growth.

High resolution lung airway cast segmentation with proper topology suitable for computational fluid dynamic simulations.

Developing detailed lung airway models is an important step towards understanding the respiratory system. While modern imaging and airway casting approaches have dramatically improved the potential detail of such models, challenges have arisen in image processing as the demand for greater detail pushes the image processing approaches to their limits. Airway segmentations with proper topology have neither loops nor invalid voxel-to-voxel connections. Here we describe a new technique for segmenting airways with proper topology and apply the approach to an image volume generated by magnetic resonance imaging of a silicone cast created from an excised monkey lung.