Source apportionment of fine particulate matter (PM2.5) at a rural Ohio River Valley site

Kim, Myoungwoo; Deshpande, Seemantini R.; Crist, Kevin

doi:10.1016/j.atmosenv.2007.07.061

Cited by 44 publications

(24 citation statements)

References 34 publications

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“…Dust storms in this area often impact El Paso in Texas and Ciudad Juarez in Mexico (Rivera et al, 2010(Rivera et al, , 2009Baddock et al, 2011). The Ohio River Valley (H) encompasses several states and is home to numerous coal-fired power plants, chemical plants and industrial facilities, leading to high levels of ambient particulates (Khosah et al, 2000;Anderson et al, 2004;Yatavelli et al, 2006;Kim et al, 2007). The Ohio River Valley has a higher average abundance of PM 2.5 than the rest of the East Coast.…”

Section: Key Features By Regionmentioning

confidence: 99%

Estimating the global abundance of ground level presence of particulate matter (PM2.5)

et al. 2014

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Abstract. With the increasing awareness of the health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground level airborne particulate matter with a diameter of 2.5 microns or less (PM 2.5). Here we use a suite of remote sensing and meteorological data products together with groundbased observations of particulate matter from 8,329 measurement sites in 55 countries taken 1997-2014 to train a machinelearning algorithm to estimate the daily distributions of PM 2.5 from 1997 to the present. In this first paper of a series, we present the methodology and global average results from this period and demonstrate that the new PM 2.5 data product can reliably represent global observations of PM 2.5 for epidemiological studies.

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Section: Key Features By Regionmentioning

confidence: 99%

Estimating the global abundance of ground level presence of particulate matter (PM2.5)

et al. 2014

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“…Source 4 in the current study was observed to be composed of higher mass fractions of secondary nitrates and sulphates, namely NO 3 − , NH 4 + and SO 4 2− . In source apportionment studies conducted by Kim et al, (2007) in Ohio, Raman and Hopke (2007) in New York and Tsai and Chen (2006) secondary nitrates, and the secondary sulfates have been identified as a major source of PM 2.5 in various source apportionment studies Ogulei et al, 2006). The current PMF analysis shows that secondary aerosols contributed to about 24.33%, 22.27% and 37.25% for PM 10 , PM 2.5 and PM 0.1 mass concentrations, respectively.…”

Section: Source Apportionmentmentioning

confidence: 99%

Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization

Gugamsetty

Han

Liu

et al. 2012

Aerosol Air Qual. Res.

203

117

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Ambient Particulate Matters (PM 10 , PM 2.5 and PM 0.1 ) were investigated at Shinjung station in New Taipei City, Taiwan. Samples were collected simultaneously using a dichotomous sampler (Andersen Model SA-241) and a MOUDI (MSP Model 110) over a 24-h period from May 2011 to November 2011 at Shinjung station. Samples were analyzed for metallic trace elements using ion coupled plasma mass spectroscopy (ICP-MS) and ionic compounds by ion chromatography (IC). The average concentrations of PM 10 , PM 2.5 and PM 0.1 were found to be 39.45 ± 11.58, 21.82 ± 7.50 and 1.42 ± 0.56 μg/m 3 , respectively. Based on the chemical information, positive matrix factorization (PMF) was used to identify PM sources. A total of five source types were identified, including soil dust, vehicle emissions, sea salt, industrial emissions and secondary aerosols, and their contributions were estimated using PMF. The crustal enrichment factors (EF) were calculated using Al as a reference for the trace metal species to identify the sources. Conditional probability functions (CPF) were computed using wind profiles and factor contributions. The results of CPF analysis were used to identify local point sources. The results suggest a competitive relationship between anthropogenic and natural source processes over the monitoring station.

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“…A study in the upper peninsula of Michigan conducted by Sheesley et al (2004) observed major contributions from SOA from both biogenic and anthropogenic volatile organic compound (VOC) oxidation in the summer. Studies across rural Illinois and Ohio found major atmospheric contributions from secondary sulfate, nitrate, and OC, consistent with aerosol aging during transport (Kim et al, 2005(Kim et al, , 2007Zhang et al, 2009), though these locations were much less forested than the more northern Great Lakes regions. Kundu and Stone (2014) measured composition and sources at rural locations in Iowa, identifying major PM mass contributions from biomass burning, combustion, and dust.…”

mentioning

confidence: 99%

“…Relatively few studies have chemically characterized atmospheric aerosols in the rural Great Lakes region of the United States (Sheesley et al, 2004;Kim et al, 2005Kim et al, , 2007Zhang et al, 2009;Jeong et al, 2011;Sjostedt et al, 2011;Kundu and Stone, 2014;Bullard et al, 2017). Except for the major metropolitan areas of Detroit (MI), Chicago (IL), Minneapolis (MN), and Milwaukee (WI), much of the land is characterized by rural agricultural areas and remote forests without significant anthropogenic emissions.…”

mentioning

confidence: 99%

Ubiquitous influence of wildfire emissions and secondary organic aerosol on summertime atmospheric aerosol in the forested Great Lakes region

et al. 2018

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Abstract. Long-range aerosol transport affects locations hundreds of kilometers from the point of emission, leading to distant particle sources influencing rural environments that have few major local sources. Source apportionment was conducted using real-time aerosol chemistry measurements made in July 2014 at the forested University of Michigan Biological Station near Pellston, Michigan, a site representative of the remote forested Great Lakes region. Size-resolved chemical composition of individual 0.5-2.0 µm particles was measured using an aerosol time-of-flight mass spectrometer (ATOFMS), and non-refractory aerosol mass less than 1 µm (PM 1 ) was measured with a high-resolution aerosol mass spectrometer (HR-AMS). The field site was influenced by air masses transporting Canadian wildfire emissions and urban pollution from Milwaukee and Chicago. During wildfireinfluenced periods, 0.5-2.0 µm particles were primarily aged biomass burning particles (88 % by number). These particles were heavily coated with secondary organic aerosol (SOA) formed during transport, with organics (average O/C ratio of 0.8) contributing 89 % of the PM 1 mass. During urban-influenced periods, organic carbon, elemental carbonorganic carbon, and aged biomass burning particles were identified, with inorganic secondary species (ammonium, sulfate, and nitrate) contributing 41 % of the PM 1 mass, indicative of atmospheric processing. With current models underpredicting organic carbon in this region and biomass burning being the largest combustion contributor to SOA by mass, these results highlight the importance for regional chemical transport models to accurately predict the impact of longrange transported particles on air quality in the upper Midwest, United States, particularly considering increasing intensity and frequency of Canadian wildfires.

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Source apportionment of fine particulate matter (PM2.5) at a rural Ohio River Valley site

Cited by 44 publications

References 34 publications

Estimating the global abundance of ground level presence of particulate matter (PM2.5)

Estimating the global abundance of ground level presence of particulate matter (PM2.5)

Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization

Ubiquitous influence of wildfire emissions and secondary organic aerosol on summertime atmospheric aerosol in the forested Great Lakes region

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