Chemical composition and source apportionment of size fractionated particulate matter in Cleveland, Ohio, USA☆
Graphical abstract
Introduction
Cleveland is an industrial city in the Midwestern U.S. and is impacted by a combination of local and regional particulate matter (PM) sources including coal- and oil-fired power plants, integrated steel plants, non-ferrous metals smelting, manufacturing, motor vehicles, and secondary aerosols. The U.S. Environmental Protection Agency (U.S. EPA) National Ambient Air Quality Standard (NAAQS) for fine fraction PM (PM2.5) is persistently exceeded in Cleveland resulting in non-attainment status. Therefore, it is critical to understand the relative contribution of air emission sources to the Cleveland airshed in order to develop an effective state implementation plan (SIP) that is required by U.S. EPA to achieve air pollution standards. A number of health studies show positive relationships among PM sources, chemical composition, and adverse health outcomes (Mar et al., 2006, Seagrave et al., 2006, Pun et al., 2014, DeFranco et al., 2016). In particular, it has been reported that increased emergency department visits for asthma and respiratory illness in Cleveland were significantly associated with exposure to coarse (Schwartz et al., 1996, Mortimer et al., 2002, Jaffe et al., 2003) and fine fractions of PM (Kumar et al., 2013). However, the specific chemical components or physical characteristics of the ambient PM in the Cleveland area responsible for health outcomes are not well understood.
U.S. EPA conducted an intensive study of ambient air quality in the Cleveland airshed from August 2008 to October 2010 (referred to as the Cleveland Multiple Air Pollutant Study or CMAPS). As part of CMAPS two multi-site one-month intensive air pollution measurement campaigns (August 2009; February 2010), and a year-long measurement effort (July 2009 to June 2010) were conducted to investigate sources of air pollution and their relative contribution to observed PM2.5 concentrations in Cleveland (Norris et al., 2009). As part of the CMAPS intensive studies, it was demonstrated that the coarse fraction PM from central industrial sites in Cleveland had high spatial and temporal variability (or heterogeneity) in association with emissions from steel and cement production (Ault et al., 2012, Mukerjee et al., 2012, Sawvel et al., 2015). The year-long study was specifically designed to collect data on PM, precursor species, and associated air pollutants necessary for advanced air quality modeling analysis that is able to predict how source emissions and meteorology impact the ambient exposure of residents to multiple pollutants. To this end, we analyzed the year-long collection size-fractionated PM samples from urban and rural sites for a suite of chemical compounds that could identify and quantitatively apportion contributing sources through positive matrix factorization (PMF) analysis (Paatero and Tapper, 1993, Paatero and Tapper, 1994, Paatero, 1997).
Of the available contemporary receptor modeling approaches, the U.S. EPA PMF receptor model (Norris et al., 2014) is the most commonly used to characterize spatial/temporal variations in PM chemical compositions and to identify major PM sources in sampling sites. Pancras et al. (2013) analyzed hourly PM2.5 chemical composition data collected in Dearborn, Michigan, and used PMF to identify hazardous air pollution elements associated with local industrial sources. In addition to the standard single site PMF analysis, Sturtz et al. (2014) used a multisite PMF model approach to identify specific trace elements of coarse PM across multiple urban areas. This approach of combining measurements from multiple areas into a single model run allowed Sturtz et al. (2014) to identify and quantify locally specific source profiles, and also determine if the areas were affected by common sources. Finally, spatial/temporal variations and patterns of apportioned air pollution sources contributing to PM in urban and rural areas have been demonstrated (Hasheminassab et al., 2014), and applications of their source apportionment data to expand epidemiological health studies have been utilized. More details on PMF and the model's applicability to various kinds of environmental data for identifying air pollutants and predicting their atmospheric processing are described in a recent review article (Hopke, 2016).
The goal of this study was to identify and quantify the sources of size-fractionated PM in the Cleveland airshed using the U.S. EPA PMF receptor model to resolve the relative contribution from local anthropogenic sources. The year-long PM measurements at urban and rural sites of Cleveland were conducted with ChemVol and dichotomous samplers, and used to apportion specific local industrial sources contributing to the size-fractionated PM samples. Alongside these measurements, PM samples were also collected from a passive sampler and their potential sources were characterized by scanning electron microscopy coupled with energy-dispersive x-ray spectrometry (SEM-EDS). This study provides information on what sources are responsible for spatial and seasonal variability as well as for generating exposure metrics for subsequent epidemiology and toxicology investigations.
Section snippets
Cleveland Multiple Air Pollutant Study (CMAPS) study sites
Ambient size-fractionated PM samples in the Cleveland airshed were collected from G.T. Craig (GTC; 41° 29′ 31.35″ N, 81° 40′ 42.64″ W) an existing downtown air sampling site (Cuyahoga County, 2008 population in Cuyahoga County: ∼1,283,000 (US Census Bureau, 2008)) and Chippewa Lake (CLM; 41° 3′ 37.35″ N, 81° 55′ 26.17″ W) a rural predominantly upwind site (Medina County, 2008 population in Median County: ∼171,000 (US Census Bureau, 2008)) established as part of CMAPS to represent the regional
Chemical compositions of size-fractionated PM in the Cleveland airshed
Mass concentrations of size-fractionated PM measured by the ChemVol sampler at GTC and CLM from 07/28/2009 to 06/08/2010 are presented in Fig. 2 and Table S2. The average concentration of coarse PM during the sampling period at GTC was significantly higher than that of coarse PM at CLM (p < 0.001), however, there was no significant difference between the fine PM concentrations at GTC and CLM, indicating that air quality of GTC was highly associated with coarse PM resulting from mechanical
Discussion
CMAPS was a large scale integrated research study that involved investigators from many disciplines to investigate the sources responsible for observed PM concentrations, PM2.5 non-attainment status, and which sources in the Cleveland airshed may be associated with the observed negative health outcomes. Specifically, we conducted EPA PMF receptor modeling and SEM imaging analysis to evaluate how pollutant sources could impact exposures of residents. This is the first study to systematically
Conclusions
CMAPS was an integrated multidisciplinary and collaborative research project involving industry, academia, as well as federal, state, and local government agencies. The present study provides unique information on the spatial and temporal variability air pollution sources and their impact on size fractionated PM in the Cleveland airshed. Local industrial sources (e.g., steel production and coal combustion) were identified as major contributors to coarse PM in the urban area and relatively low
Acknowledgements
The authors would like to thank Drs. Stephen Gavett and Shaibal Mukerjee for careful review of this manuscript. This study was performed while Dr. Yong Ho Kim held a National Research Council Senior Research Associateship Award at the U.S. Environmental Protection Agency. The research described in this manuscript has been reviewed by the National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, and approved for publication. Approval does not signify
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This paper has been recommended for acceptance by Eddy Y. Zeng.
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Present address: Health and Environmental Impacts Division, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.