Associations of Air Pollution and Pediatric Asthma in Cleveland, Ohio.

Air pollution has been associated with poor health outcomes and continues to be a risk factor for respiratory health in children. While higher particulate matter (PM) levels are associated with increased frequency of symptoms, lower lung function, and increase airway inflammation from asthma, the precise composition of the particles that are more highly associated with poor health outcomes or healthcare utilization are not fully elucidated. PM is measured quantifiably by current air pollution monitoring systems. To better determine sources of PM and speciation of such sources, a particulate matter (PM) source apportionment study, the Cleveland Multiple Air Pollutant Study (CMAPS), was conducted in Cleveland, Ohio, in 2009-2010, which allowed more refined assessment of associations with health outcomes. This article presents an evaluation of short-term (daily) and long-term associations between motor vehicle and industrial air pollution components and pediatric asthma emergency department (ED) visits by evaluating two sets of air quality data with healthcare utilization for pediatric asthma. Exposure estimates were developed using land use regression models for long-term exposures for nitrogen dioxide (NO2) and coarse (i.e., with aerodynamic diameters between 2.5 and 10 µm) particulate matter (PM) and the US EPA Positive Matrix Factorization receptor model for short-term exposures to fine (<2.5 µm) and coarse PM components. Exposure metrics from these two approaches were used in asthma ED visit prevalence and time series analyses to investigate seasonal-averaged short- and long-term impacts of both motor vehicles and industry emissions. Increased pediatric asthma ED visits were found for LUR coarse PM and NO2 estimates, which were primarily contributed by motor vehicles. Consistent, statistically significant associations with pediatric asthma visits were observed, with short-term exposures to components of fine and coarse iron PM associated with steel production. Our study is the first to combine spatial and time series analysis of ED visits for asthma using the same periods and shows that PM related to motor vehicle emissions and iron/steel production are associated with increased pediatric asthma visits.

Primary Sources of Polycyclic Aromatic Hydrocarbons to Streambed Sediment in Great Lakes Tributaries Using Multiple Lines of Evidence.

Polycyclic aromatic hydrocarbons (PAHs) are among the most widespread and potentially toxic contaminants in Great Lakes (USA/Canada) tributaries. The sources of PAHs are numerous and diverse, and identifying the primary source(s) can be difficult. The present study used multiple lines of evidence to determine the likely sources of PAHs to surficial streambed sediments at 71 locations across 26 Great Lakes Basin watersheds. Profile correlations, principal component analysis, positive matrix factorization source-receptor modeling, and mass fractions analysis were used to identify potential PAH sources, and land-use analysis was used to relate streambed sediment PAH concentrations to different land uses. Based on the common conclusion of these analyses, coal-tar-sealed pavement was the most likely source of PAHs to the majority of the locations sampled. The potential PAH-related toxicity of streambed sediments to aquatic organisms was assessed by comparison of concentrations with sediment quality guidelines. The sum concentration of 16 US Environmental Protection Agency priority pollutant PAHs was 7.4-196 000 µg/kg, and the median was 2600 µg/kg. The threshold effect concentration was exceeded at 62% of sampling locations, and the probable effect concentration or the equilibrium partitioning sediment benchmark was exceeded at 41% of sampling locations. These results have important implications for watershed managers tasked with protecting and remediating aquatic habitats in the Great Lakes Basin. Environ Toxicol Chem 2020;39:1392-1408. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Source apportionment of polycyclic aromatic hydrocarbons (PAHs) in small craft harbor (SCH) surficial sediments in Nova Scotia, Canada.

Multiple source apportionment approaches were employed to investigate PAH sources which contribute to small craft harbor (SCH) sediments in Nova Scotia (NS), Canada. A total of 580 sediment samples were analyzed using PAH diagnostic ratios, Unmix Optimum receptor modeling, and by assessment of the composition of the PAH profile. PAH diagnostic ratios suggest PAHs are primarily of pyrogenic (thermal) origin, while UnmixO modeling identifies four individual sources which best describe surficial sediments and suggests contributions from both pyrogenic and petrogenic origins. These include coal combustion, automobile exhaust, and biomass incineration. PAH profile assessment determined an overwhelming contribution of high molecular weight PAHs, which exhibited a strong correlation with total PAH concentrations.

Unmix Optimum analysis of PAH sediment sources.

Unmix Optimum (UnmixO) was developed to analyze data, such as sediment PAH data, that were resistant to existing methods of multivariate analysis. Using a geometrical approach, UnmixO uses multiple advanced nonlinear optimization algorithms to find potential sources that obey non-negativity constraints while optimally fitting the data. UnmixO does not require specific knowledge of the uncertainties in the data and will work better for smaller data sets than other multivariate models. UnmixO was able to identify polycyclic aromatic hydrocarbon (PAH) contaminant sources contributing to sediment samples based on sample composition data with good diagnostic values. Results were compared to published EPA Chemical Mass Balance (CMB) sediment results from Lady Bird Lake (LBL) Austin, TX and 40 lakes (40LKS) across the U.S. A Chi-sum approach determined which UnmixO source profile best matched profiles used in CMB sediment studies; two coal tar (CT) sealcoat sources and a mixed combustion source contributed to the sediment PAHs. These results were consistent with CMB results for the LBL and 40LKS studies that estimated CT sealcoats contribute over 80% of PAHs to urban lakes. UnmixO results also showed that CT sealant's contribution to sediments decreased after the City of Austin ban in 2006.

Signal Decomposition of Conductivity Sensor Measurements on the Allegheny River, Pennsylvania.

Surface water conductivity measurements were used to evaluate the combined contribution of anions in western Pennsylvania from brines discharged by sources such as oil and gas wastewater treatment, coal-fired power plants, and coal mining activities. Conductivity sensor data were collected in the Allegheny River during a US Environmental Protection Agency and US Fish and Wildlife study that included seven sites covering 256 river km during the fall of 2012. Intermittent discharges, such as oil and gas wastewater, and continuous sources contributing to the conductivity were quantified using constrained and adaptive decomposition of time-series (CADETS) frequency analysis. CADETS was able to quantify the intermittent or short-term component of conductivity at sites where the intermittent fraction was 1 to 22% of the total conductivity. The demonstrated efficacy of the CADETS method for surface water quality analysis suggests it could be widely used to evaluate other water sensor data in rivers with both continuous and intermittent source impacts.

Airborne Observations of Reactive Inorganic Chlorine and Bromine Species in the Exhaust of Coal-Fired Power Plants.

We present airborne observations of gaseous reactive halogen species (HCl, Cl2, ClNO2, Br2,BrNO2, and BrCl), sulfur dioxide (SO2), and nonrefractory fine particulate chloride (pCl) and sulfate(pSO4) in power plant exhaust. Measurements were conducted during the Wintertime INvestigation of Transport, Emissions, and Reactivity campaign in February-March of 2015 aboard the NCAR-NSF C-130 aircraft. Fifty air mass encounters were identified in which SO2 levels were elevated ~5 ppb above ambient background levels and in proximity to operational power plants. Each encounter was attributed to one or more potential emission sources using a simple wind trajectory analysis. In case studies, we compare measured emission ratios to those reported in the 2011 National Emissions Inventory and present evidence of the conversion of HCl emitted from power plants to ClNO2. Taking into account possible chemical conversion downwind, there was general agreement between the observed and reported HCl: SO2 emission ratios. Reactive bromine species (Br2, BrNO2, and/or BrCl) were detected in the exhaust of some coal-fired power plants, likely related to the absence of wet flue gas desulfurization emission control technology. Levels of bromine species enhanced in some encounters exceeded those expected assuming all of the native bromide in coal was released to the atmosphere, though there was no reported use of bromide salts (as a way to reduce mercury emissions) during Wintertime INvestigation of Transport, Emissions, and Reactivity observations. These measurements represent the first ever in-flight observations of reactive gaseous chlorine and bromine containing compounds present in coal-fired power plant exhaust.

Chemical composition and source apportionment of size fractionated particulate matter in Cleveland, Ohio, USA.

The Cleveland airshed comprises a complex mixture of industrial source emissions that contribute to periods of non-attainment for fine particulate matter (PM2.5) and are associated with increased adverse health outcomes in the exposed population. Specific PM sources responsible for health effects however are not fully understood. Size-fractionated PM (coarse, fine, and ultrafine) samples were collected using a ChemVol sampler at an urban site (G.T. Craig (GTC)) and rural site (Chippewa Lake (CLM)) from July 2009 to June 2010, and then chemically analyzed. The resulting speciated PM data were apportioned by EPA positive matrix factorization to identify emission sources for each size fraction and location. For comparisons with the ChemVol results, PM samples were also collected with sequential dichotomous and passive samplers, and evaluated for source contributions to each sampling site. The ChemVol results showed that annual average concentrations of PM, elemental carbon, and inorganic elements in the coarse fraction at GTC were ∼2, ∼7, and ∼3 times higher than those at CLM, respectively, while the smaller size fractions at both sites showed similar annual average concentrations. Seasonal variations of secondary aerosols (e.g., high NO3- level in winter and high SO42- level in summer) were observed at both sites. Source apportionment results demonstrated that the PM samples at GTC and CLM were enriched with local industrial sources (e.g., steel plant and coal-fired power plant) but their contributions were influenced by meteorological conditions and the emission source's operation conditions. Taken together the year-long PM collection and data analysis provides valuable insights into the characteristics and sources of PM impacting the Cleveland airshed in both the urban center and the rural upwind background locations. These data will be used to classify the PM samples for toxicology studies to determine which PM sources, species, and size fractions are of greatest health concern.

The impact of commercially treated oil and gas produced water discharges on bromide concentrations and modeled brominated trihalomethane disinfection byproducts at two downstream municipal drinking water plants in the upper Allegheny River, Pennsylvania, USA.

In 2010, a dramatic increase in the levels of total trihalomethane (THM) and the relative proportion of brominated species was observed in finished water at several Pennsylvania water utilities (PDW) using the Allegheny River as their raw water supply. An increase in bromide (Br(-)) concentrations in the Allegheny River was implicated to be the cause of the elevated water disinfection byproducts. This study focused on quantifying the contribution of Br(-) from a commercial wastewater treatment facility (CWTF) that solely treats wastes from oil and gas producers and discharges into the upper reaches of the Allegheny River, and impacts on two downstream PDWs. In 2012, automated daily integrated samples were collected on the Allegheny River at six sites during three seasonal two-week sampling campaigns to characterize Br(-) concentrations and river dispersion characteristics during periods of high and low river discharges. The CWTF discharges resulted in significant increases in Br(-) compared to upstream baseline values in PDW raw drinking water intakes during periods of low river discharge. During high river discharge, the assimilative dilution capacity of the river resulted in lower absolute halide concentrations, but significant elevations Br(-) concentrations were still observed at the nearest downstream PDW intake over baseline river levels. On days with active CWTF effluent discharge the magnitude of bromide impact increased by 39 ppb (53%) and 7 ppb (22%) for low and high river discharge campaigns, respectively. Despite a declining trend in Allegheny River Br(-) (2009-2014), significant impacts from CWTF and coal-fired power plant discharges to Br(-) concentrations during the low river discharge regime at downstream PDW intakes was observed, resulting in small modeled increases in total THM (3%), and estimated positive shifts (41-47%) to more toxic brominated THM analogs. The lack of available coincident measurements of THM, precursors, and physical parameters limited the interpretation of historical trends.

Application of ICP-OES for evaluating energy extraction and production wastewater discharge impacts on surface waters in Western Pennsylvania.

Oil and gas extraction and coal-fired electrical power generating stations produce wastewaters that are treated and discharged to rivers in Western Pennsylvania with public drinking water system (PDWS) intakes. Inductively coupled plasma optical emission spectroscopy (ICP-OES) was used to quantify inorganic species in wastewater and river samples using a method based on EPA Method 200.7 rev4.4. A total of 53 emission lines from 30 elements (Al, As, B, Ba, Ca, Cd, Ce, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, P, Pb, S, Sb, Se, Si, Sn, Sr, Ti, Tl, V, and Zn) were investigated. Samples were prepared by microwave-assisted acid digestion using a mixture of 2% HNO3 and 0.5% HCl. Lower interferences and better detection characteristics resulted in selection of alternative wavelengths for Al, As, Sb, Mg, Mo, and Na. Radial view measurements offered accurate determinations of Al, Ba, K, Li, Na, and Sr in high-brine samples. Spike recovery studies and analyses of reference materials showed 80-105% recoveries for most analytes. This method was used to quantify species in samples with high to low brine concentrations with method detection limits a factor of 2 below the maximum contaminant limit concentrations of national drinking water standards. Elements B, Ca, K, Li, Mg, Na, and Sr were identified as potential tracers for the sources impacting PDWS intakes. Usability of the ICP-OES derived data for factor analytic model applications was also demonstrated.

Methods for estimating uncertainty in PMF solutions: examples with ambient air and water quality data and guidance on reporting PMF results.

The new version of EPA's positive matrix factorization (EPA PMF) software, 5.0, includes three error estimation (EE) methods for analyzing factor analytic solutions: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement (BS-DISP). These methods capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. To demonstrate the utility of the EE methods, results are presented for three data sets: (1) speciated PM2.5 data from a chemical speciation network (CSN) site in Sacramento, California (2003-2009); (2) trace metal, ammonia, and other species in water quality samples taken at an inline storage system (ISS) in Milwaukee, Wisconsin (2006); and (3) an organic aerosol data set from high-resolution aerosol mass spectrometer (HR-AMS) measurements in Las Vegas, Nevada (January 2008). We present an interpretation of EE diagnostics for these data sets, results from sensitivity tests of EE diagnostics using additional and fewer factors, and recommendations for reporting PMF results. BS-DISP and BS are found useful in understanding the uncertainty of factor profiles; they also suggest if the data are over-fitted by specifying too many factors. DISP diagnostics were consistently robust, indicating its use for understanding rotational uncertainty and as a first step in assessing a solution's viability. The uncertainty of each factor's identifying species is shown to be a useful gauge for evaluating multiple solutions, e.g., with a different number of factors.

Applicability of the environmental relative moldiness index for quantification of residential mold contamination in an air pollution health effects study.

The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) investigated the impact of exposure to traffic-related air pollution on the respiratory health of asthmatic children in Detroit, Michigan. Since indoor mold exposure may also contribute to asthma, floor dust samples were collected in participants homes (n = 112) to assess mold contamination using the Environmental Relative Moldiness Index (ERMI). The repeatability of the ERMI over time, as well as ERMI differences between rooms and dust collection methods, was evaluated for insights into the application of the ERMI metric. ERMI values for the standard settled floor dust samples had a mean ± standard deviation of 14.5 ± 7.9, indicating high levels of mold contamination. ERMI values for samples collected from the same home 1 to 7 months apart (n = 52) were consistent and without systematic bias. ERMI values for separate bedroom and living room samples were highly correlated (r = 0.69, n = 66). Vacuum bag dust ERMI values were lower than for floor dust but correlated (r = 0.58, n = 28). These results support the use of the ERMI to evaluate residential mold exposure as a confounder in air pollution health effects studies.

Source apportionment of ambient fine particulate matter in Dearborn, Michigan, using hourly resolved PM chemical composition data.

High time-resolution aerosol sampling was conducted for one month during July-August 2007 in Dearborn, MI, a non-attainment area for fine particulate matter (PM2.5) National Ambient Air Quality Standards (NAAQS). Measurements of more than 30 PM2.5 species were made using a suite of semi-continuous sampling and monitoring instruments. Dynamic variations in the sub-hourly concentrations of source 'marker' elements were observed when discrete plumes from local sources impacted the sampling site. Hourly averaged PM2.5 composition data for 639 samples were used to identify and apportion PM2.5 emission sources using the multivariate receptor modeling techniques EPA Positive Matrix Factorization (PMF) v4.2 and EPA Unmix v6.0. Source contribution estimates from PMF and Unmix were then evaluated using the Sustained Wind Instance Method (SWIM), which identified plausible source origins. Ten sources were identified by both PMF and Unmix: (1) secondary sulfate, (2) secondary nitrate characterized by a significant diurnal trend, (3) iron and steel production, (4) a potassium-rich factor attributable to iron/steel slag waste processing, (5) a cadmium-rich factor attributable to incineration, (6) an oil refinery characterized by La/Ce>1 specific to south wind, (7) oil combustion, (8) coal combustion, (9) motor vehicles, and (10) road dust enriched with organic carbon. While both models apportioned secondary sulfate, oil refinery, and oil combustion PM2.5 masses closely, the mobile and industrial source apportionments differed. Analyses were also carried out to help infer time-of-day variations in the contributions of local sources.

The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS): study design and methods.

The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) was designed to examine the relationship between near-roadway exposures to air pollutants and respiratory outcomes in a cohort of asthmatic children who live close to major roadways in Detroit, Michigan USA. From September 2010 to December 2012 a total of 139 children with asthma, ages 6-14, were enrolled in the study on the basis of the proximity of their home to major roadways that carried different amounts of diesel traffic. The goal of the study was to investigate the effects of traffic-associated exposures on adverse respiratory outcomes, biomolecular markers of inflammatory and oxidative stress, and how these exposures affect the frequency and severity of respiratory viral infections in a cohort of children with asthma. An integrated measurement and modeling approach was used to quantitatively estimate the contribution of traffic sources to near-roadway air pollution and evaluate predictive models for assessing the impact of near-roadway pollution on children's exposures. Two intensive field campaigns were conducted in Fall 2010 and Spring 2011 to measure a suite of air pollutants including PM2.5 mass and composition, oxides of nitrogen (NO and NO2), carbon monoxide, and black carbon indoors and outdoors of 25 participants' homes, at two area schools, and along a spatial transect adjacent to I-96, a major highway in Detroit. These data were used to evaluate and refine models to estimate air quality and exposures for each child on a daily basis for the health analyses. The study design and methods are described, and selected measurement results from the Fall 2010 field intensive are presented to illustrate the design and successful implementation of the study. These data provide evidence of roadway impacts and exposure variability between study participants that will be further explored for associations with the health measures.

Evaluation of land use regression models for nitrogen dioxide and benzene in Four US cities.

Spatial analysis studies have included the application of land use regression models (LURs) for health and air quality assessments. Recent LUR studies have collected nitrogen dioxide (NO(2)) and volatile organic compounds (VOCs) using passive samplers at urban air monitoring networks in El Paso and Dallas, TX, Detroit, MI, and Cleveland, OH to assess spatial variability and source influences. LURs were successfully developed to estimate pollutant concentrations throughout the study areas. Comparisons of development and predictive capabilities of LURs from these four cities are presented to address this issue of uniform application of LURs across study areas. Traffic and other urban variables were important predictors in the LURs although city-specific influences (such as border crossings) were also important. In addition, transferability of variables or LURs from one city to another may be problematic due to intercity differences and data availability or comparability. Thus, developing common predictors in future LURs may be difficult.

Single-particle SEM-EDX analysis of iron-containing coarse particulate matter in an urban environment: sources and distribution of iron within Cleveland, Ohio.

The physicochemical properties of coarse-mode, iron-containing particles and their temporal and spatial distributions are poorly understood. Single-particle analysis combining X-ray elemental mapping and computer-controlled scanning electron microscopy (CCSEM-EDX) of passively collected particles was used to investigate the physicochemical properties of iron-containing particles in Cleveland, OH, in summer 2008 (Aug-Sept), summer 2009 (July-Aug), and winter 2010 (Feb-March). The most abundant classes of iron-containing particles were iron oxide fly ash, mineral dust, NaCl-containing agglomerates (likely from road salt), and Ca-S containing agglomerates (likely from slag, a byproduct of steel production, or gypsum in road salt). The mass concentrations of anthropogenic fly ash particles were highest in the Flats region (downtown) and decreased with distance away from this region. The concentrations of fly ash in the Flats region were consistent with interannual changes in steel production. These particles were observed to be highly spherical in the Flats region, but less so after transport away from downtown. This change in morphology may be attributed to atmospheric processing. Overall, this work demonstrates that the method of passive collection with single-particle analysis by electron microscopy is a powerful tool to study spatial and temporal gradients in components of coarse particles. These gradients may correlate with human health effects associated with exposure to coarse-mode particulate matter.

Separating the air quality impact of a major highway and nearby sources by nonparametric trajectory analysis.

Nonparametric Trajectory Analysis (NTA), a receptor-oriented model, was used to assess the impact of local sources of air pollution at monitoring sites located adjacent to highway I-15 in Las Vegas, NV. Measurements of black carbon, carbon monoxide, nitrogen oxides, and sulfur dioxide concentrations were collected from December 2008 to December 2009. The purpose of the study was to determine the impact of the highway at three downwind monitoring stations using an upwind station to measure background concentrations. NTA was used to precisely determine the contribution of the highway to the average concentrations measured at the monitoring stations accounting for the spatially heterogeneous contributions of other local urban sources. NTA uses short time average concentrations, 5 min in this case, and constructed local back-trajectories from similarly short time average wind speed and direction to locate and quantify contributions from local source regions. Averaged over an entire year, the decrease of concentrations with distance from the highway was found to be consistent with previous studies. For this study, the NTA model is shown to be a reliable approach to quantify the impact of the highway on local air quality in an urban area with other local sources.

Scanning electron microanalysis and analytical challenges of mapping elements in urban atmospheric particles.

Elemental mapping with energy-dispersive X-ray spectroscopy (EDX) associated with scanning electron microscopy is highly useful for studying internally mixed atmospheric particles. Presented is a study of individual particles from urban airsheds and the analytical challenges in qualitatively determining the composition and origin of heterogeneous urban-air particles from high-resolution elemental maps. Coarse-mode particles were taken from samples collected in three U.S. cities: Atlanta, Los Angeles, and Seattle. Elemental maps distinguished particles with heterogeneously mixed phases from those with homogeneously mixed phases that also contained inclusions or surface adducts. Elemental mapping at low and high beam energies, along with imaging at an oblique angle helped to classify particles by origin. The impact of particle shape on X-ray microanalysis was demonstrated by having the beam enter the particle at ≥ 52° from normal. Potential misinterpretations of particle composition due to artifacts in the elemental maps were minimized by tilt imaging to reveal particle surface roughness and depth, mapping at low beam energies, noting the position of the EDX detector in the map field, and assessing differences in the mass absorption coefficients of the particle's major elements to anticipate X-ray self-absorption.

Application of EPA unmix and nonparametric wind regression on high time resolution trace elements and speciated mercury in Tampa, Florida aerosol.

Intensive ambient air sampling was conducted in Tampa, FL, during October and November of 2002. Fine particulate matter (PM(2.5)) was collected at 30 min resolution using the Semicontinuous Elements in Aerosol Sampler II (SEAS-II) and analyzed off-line for up to 45 trace elements by high-resolution ICPMS (HR-ICPMS). Divalent reactive gaseous mercury and particulate bound mercury were also measured semicontinuously (2 h). Application of the United States Environmental Protection Agency's (EPA) Unmix receptor model on the 30 min resolution trace metals data set identified eight possible sources: residual oil combustion, lead recycling, coal combustion, a Cd-rich source, biomass burning, marine aerosol, general industrial, and coarse dust contamination. The source contribution estimates from EPA Unmix were then run in a nonparametric wind regression (NWR) model, which convincingly identified plausible source origins. When the 30 min ambient concentrations of trace elements were time integrated (2 h) and combined with speciated mercury concentrations, the model identified only four sources, some of which appeared to be merged source profiles that were identified as separate sources by using the 30 min resolution data. This work demonstrates that source signatures that can be captured at 30 min resolution may be lost when sampling for longer durations.