Modeling Source Contributions to Submicron Particle Number Concentrations Measured in Rochester, New York

Abstract

An advanced receptor model was used to elicit source information based on ambient submicron (0.01-0.47 µm) particle number concentrations, gaseous species, and meteorological variables measured at the New York State Department of Environmental Conservation central monitoring site in Rochester, NY. Four seasonal data sets (winter, spring, summer, and fall) were independently investigated. A total of ten different sources were identified, including two traffic factors, two nucleation factors, industrial emissions, residential/commercial heating, secondary nitrate, secondary sulfate, ozone-rich secondary aerosol, and regionally transported aerosol. The resolved sources were generally characterized by similar number modes for either winter, spring, summer or fall. The size distributions for nucleation were dominated by the smallest particles (<10-30 nm) that gradually grew to larger sizes as could be seen by observing the volume profiles. In addition, the nucleation factors were closely linked to traffic rush hours suggesting that cooling of tail-pipe emissions may have induced nucleation activity in the vicinity of the highways. Although the diurnal pattern of each of the two traffic factors closely followed traffic rush hour for Rochester, their size modes were different suggesting that these factors might represent local and remote emissions. Industrial emissions were dominated by emissions from coal-fired power plants that were located to the northwest of the sampling site. These facilities represent the largest point emission sources of SO 2 , and probably ultrafine (<0.1 µm) or submicron particles, in Rochester. Regionally transported material was characterized by accumulation mode particles. Air parcel back-trajectories showed transport of air masses from the industrial midwest.

Source Apportionment of Winter Submicron Prague Aerosols from Combined Particle Number Size Distribution and Gaseous Composition Data

“…Wet precipitation events preceded the high O 3 days. Precipitation events, led to reduction in fine particles and clear skies (last 5 days), high WS and T with frontal passage supports the assignment of F1 to be ozone-rich, similar to ozone-related factor observed by Ogulei et al (2007) in Rochester, NY.…”

Sources of sub-micrometre particles near a major international airport

“…SMPS data at 5 min resolution were used as the PMF input matrix. Uncertainties associated with SMPS data were estimated according to the empirical method proposed by Ogulei et al (2007). Uncertainty for the total variable (total particle number concentration; PNC) was set to 300 % of the PNC concentration and also marked as "weak" to avoid it driving the profiles.…”

Source apportionment of ultrafine and fine particle concentrations in Brisbane, Australia

“…The results obtained are scaled to the measured particle numbers by regression of the total number concentration against the obtained source contributions to determine a scaling constant, k s (Ogulei et al 2007a;Kim et al 2003a). …”

“…Similar analysis has also been conducted in Erfurt, Germany (Yue et al 2008). In addition, there have been other types of analyses including, the use of (i) gaseous, chemical (particulate matter composition), and particle size data together in the PMF analysis over short (Ogulei et al 2006b;Zhou et al 2005a;Thimmaiah et al 2009), or long (Ogulei et al 2007a;Kasumba et al 2009;Cuccia et al 2010) periods, (ii) chemical and particle size data in two separate PMF analyses followed by comparison of the outcomes (Gu et al 2011), (iii) elemental size distribution data (Han et al 2006;Mazzei et al 2007), (iv) aerodyne aerosol mass spectral data (Sun et al 2010), and (v) PMF results that are compared to the actual events observed during the sampling period (Ogulei et al 2007b). Numerous sources have been identified in these studies such as: nucleation, various motor vehicle sources, wood burning, and secondary particles.…”