Characterization of PM Using Multiple Site Data in a Heavily Industrialized Region of Turkey

Abstract

Source apportionment has most often been applied to a time series of data collected at a single site. However, in a complex airshed where there are multiple sources, it may be helpful to collect samples from multiple sites to ensure that some of them have low contributions from specific sources such that edges can be properly defined. In this study, samples were collected at multiple sites in the Aliaga region (38°40′-38°54′N and 26°50′-27°03′E) located in western Turkey on the coast of the Aegean Sea. This area contains a number of significant air pollution sources including five scrap iron-steel processing plants with electric arc furnaces (EAFs), several steel rolling mills, a petroleum refinery, a petrochemical complex, a natural gas-fired power plant, a fertilizer plant, ship breaking yards, coal storage and packaging, scrap storage and classification sites, large slag and scrap piles, heavy road traffic, very intense transportation activities including ferrous scrap trucks and busy ports used for product and raw material transportation. A total of 456 samples of PM 10 at six sampling sites and 88 samples of PM 2.5 at one site were collected for four seasons and the elemental composition was determined for 43 elements. The newest version of EPA PMF (V5.0) that has the capability of handling multiple site data was used for source apportionment. Eight factors were identified as iron-steel production from scrap (23.4%), resuspended and road dust (23.3%), crustal (20.5%), marine aerosol (14.4%), biomass and wood combustion (7.2%), salvage activities (4.7%), coal combustion (3.7%) and residual oil combustion (2.8%). The pattern of source contributions and conditional probability function analysis were consistent with the locations of the known sources. Thus, the multiple site data allowed for a comprehensive identification of the primary sources of PM in this region.

Source Apportionment of Airborne Dioxins, Furans, and Polycyclic Aromatic Hydrocarbons at a United States Forward Operating Air Base During the Iraq War

“…EPA PMF V5 has been given the capability of handling multiple site data and has been used in other such studies. 16 Assuming that different sites would be affected by the same set of potential sources and that such sources may differently influence the sites depending on wind speed and direction, it was possible to use spatial variability to provide a source resolution with less rotational ambiguities. 17,18 …”

“…16,19 Briefly, the CPF analyzes local source impacts from varying wind directions using the source contribution estimates from PMF coupled with time-resolved wind directions. 19 CPF essentially assesses the probability that a source contribution from a given wind direction exceeds a predetermined threshold criterion (e.g., concentrations >75th percentile, in this case).…”

“…Sources are likely to be located along the directions that have high conditional probability values and can triangulate on sources when multiple site data are available. 16,20 …”

An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan

“…Simply relying on two input files, sample species' concentration data and sample species' uncertainty data, the PMF solves the equation for each factor p, concurrently estimating the factor contributions (G) and the factor profiles (F). Sample species uncertainty can be derived from actual uncertainty data of analytical determination or be estimated through an equation-based approach from specific parameters, such as the detection limit (DL) of the measurement method [42][43][44].…”

Source Apportionment of Fine and Coarse Particulate Matter in Industrial Areas of Kaduna, Northern Nigeria

“…The approach of Polissar et al (1998) has been used to estimate the concentration values and their associated error estimates. Because of small number of samples collected at the NNPC site and prior work by Kara et al (2015) showing the value of multiple site data. Given an area with significant local sources, sampling from multiple locations such that a given source cannot easily impact both sites simultaneously provides edge points (Henry, 2003) and thus, additional resolution in the analysis.…”