Source apportionment of population representative samples of PM(2.5) in three European cities using structural equation modelling

Comparison of the sources and oxidative potential of PM2.5 during winter time in large cities in China and South Korea

Regional air pollution is rising in Northeast Asia due to increasing energy consumption resulting from a growing population and intensifying industrialization. This study analyzes the sources of air pollution using fine particulate matter (PM_2.5) sampling from the atmosphere over Korea and China. We then use this analysis to further investigate the relationship between organic compounds (source tracers) and the oxidative potential of PM_2.5. The PM_2.5 concentration during winter measured at a measurement stations in Korea showed no significant variation year-to-year. The PM_2.5 concentrations measured during winter at a site near Beijing, China were 62.45 μg/m³ in 2018 and 33.07 μg/m³ in 2020. The sources, as determined from PMF, were analyzed at a site in Korea, the sources as secondary nitrate (34.10 %), secondary sulfate (20.20 %), coal combustion (4.01 %), vehicle emission (8.55 %), cooking and biomass burning (18.39 %), dust (8.45 %), and SOA (6.29 %) were identified. At a site in China, secondary nitrate (17.54 %), secondary sulfate (12.03 %), coal combustion (15.53 %), vehicle emission (12.43 %), cooking and biomass burning (9.25 %), dust (26.40 %), secondary organic aerosol (6.82 %) were identified. Our results show secondary organic carbon had a positive association with oxidative potential in Korea while primary organic carbon presented higher correlation with oxidative potential in China. Further, the ECMWF Reanalysis v5 (ERA5) wind field during the high PM_2.5 events demonstrated airflow from the west coast of China resulting in high polar organic compounds at the Korean monitoring site. The results further support that aged PM_2.5, which contains secondary products, leads to increased oxidative potential. The results presented explain the high concentrations of secondary products and the impact on the biological activities of PM_2.5, supporting additional actions to address the impacts of long-range transport of PM_2.5.

PM2.5 exceedances and source appointment as inputs for an early warning system

Between June 2018 and April 2019, a sampling campaign was carried out to collect PM2.5, monitoring meteorological parameters and anthropogenic events in the Sartenejas Valley, Venezuela. We develop a logistic model for PM2.5 exceedances (≥ 12.5 µg m-3). Source appointment was done using elemental composition and morphology of PM by scanning electron microscopy coupled with energy dispersive spectroscopy (SEM-EDS). A proposal of an early warning system (EWS) for PM pollution episodes is presented. The logistic model has a holistic success rate of 94%, with forest fires and motor vehicle flows as significant variables. Source appointment analysis by occurrence of events showed that samples with higher concentrations of PM had carbon-rich particles and traces of K associated with biomass burning, as well as aluminosilicates and metallic elements associated with resuspension of soil dust by motor-vehicles. Quantitative source appointment analysis showed that soil dust, garbage burning/marine aerosols and wildfires are three majority sources of PM. An EWS for PM pollution episodes around the Sartenejas Valley is proposed considering the variables and elements mentioned.

PM2.5 source apportionment in a French urban coastal site under steelworks emission influences using constrained non-negative matrix factorization receptor model

The constrained weighted-non-negative matrix factorization (CW-NMF) hybrid receptor model was applied to study the influence of steelmaking activities on PM2.5 (particulate matter with equivalent aerodynamic diameter less than 2.5 μm) composition in Dunkerque, Northern France. Semi-diurnal PM2.5 samples were collected using a high volume sampler in winter 2010 and spring 2011 and were analyzed for trace metals, water-soluble ions, and total carbon using inductively coupled plasma--atomic emission spectrometry (ICP-AES), ICP--mass spectrometry (ICP-MS), ionic chromatography and micro elemental carbon analyzer. The elemental composition shows that NO3(-), SO4(2-), NH4(+) and total carbon are the main PM2.5 constituents. Trace metals data were interpreted using concentration roses and both influences of integrated steelworks and electric steel plant were evidenced. The distinction between the two sources is made possible by the use Zn/Fe and Zn/Mn diagnostic ratios. Moreover Rb/Cr, Pb/Cr and Cu/Cd combination ratio are proposed to distinguish the ISW-sintering stack from the ISW-fugitive emissions. The a priori knowledge on the influencing source was introduced in the CW-NMF to guide the calculation. Eleven source profiles with various contributions were identified: 8 are characteristics of coastal urban background site profiles and 3 are related to the steelmaking activities. Between them, secondary nitrates, secondary sulfates and combustion profiles give the highest contributions and account for 93% of the PM2.5 concentration. The steelwork facilities contribute in about 2% of the total PM2.5 concentration and appear to be the main source of Cr, Cu, Fe, Mn, Zn.

Contribution of polycyclic aromatic hydrocarbon (PAH) sources to the urban environment: A comparison of receptor models

The aim of this study was to evaluate the contribution of the main emission sources of PAHs associated with PM2.5, in an urban area of the Rio Grande do Sul state. Source apportionment was conducted using both the US EPA Positive Matrix Factorization (PMF) model and the Chemical Mass Balance (CMB) model. The two models were compared to analyze the source contributions similarities and differences, their advantages and disadvantages. PM2.5 samples were collected continuously over 24h using a stacked filter unit at 3 sampling sites of the urban area of the Rio Grande do Sul state every 15days between 2006 and 2008. Both models identified the main emission sources of PAHs in PM2.5: vehicle fleet (diesel and gasoline), coal combustion, wood burning, and dust. Results indicated similar source contribution amongst the sampling sites, as expected because of the proximity amongst the sampling sites, which are under the influence of the same pollutants emitting sources. Moreover, differences were observed in obtained sources contributions for the same data set of each sampling site. The PMF model attributed a slightly greater amount of PAHs to the gasoline and diesel sources, while diesel contributed more in the CMB results. The results were comparable with previous works of the region and in accordance with the characteristics of the study area. Comparison between these receptor models, which contain different physical constraints, is important for understanding better PAH emissions sources in order to reduce air pollution.

Elemental composition and oxidative properties of PM(2.5) in Estonia in relation to origin of air masses - results from the ECRHS II in Tartu

Fine particulate matter (PM(2.5)) was sampled at an urban background site in Tartu, Estonia over one-year period during the ECRHS II study. The elemental composition of 71 PM(2.5) samples was analyzed for different chemical elements using energy-dispersive X-ray fluorescence spectrometry (ED-XRF). The oxidative activity of 36 samples was assessed by measuring their ability to generate hydroxyl radicals in the presence of hydrogen peroxide. The origin of air masses was determined by computing 96-hour back trajectories of air masses with the HYSPLIT Model. The trajectories of air masses were divided into four sectors according to geographical patterns: "Russia," "Eastern Europe," "Western Europe," and "Scandinavia." During the study period, approximately 30% of air masses originated from "Scandinavia." The other three sectors had slightly lower values (between 18 and 22%). In spring, summer, and winter, higher total PM levels originated from air masses from continental areas, namely "Russia" and "Eastern Europe" (18.51+/-7.33 and 19.96+/-9.23microg m(-3), respectively). In autumn, the PM levels were highest in "Western Europe". High levels of Fe, Ti, and AlCaSi (Al, Ca, and Si) were also detected in air masses from the Eurasian continent. The oxidative properties were correlated to the origin of air masses. The OH values were approximately 1.5 times higher when air masses originated from the direction of "Eastern Europe" or "Russia." The origin of measured particles was evaluated using principal component factor analysis. When comparing the PM(2.5) elemental composition with seasonal variation, factor scores, and other studies, the factors represent: (1) combustion of biomass; (2) crustal dust; (3) traffic; and (4) power plants and industrial processes associated with oil burning. The total PM(2.5) is driven mainly by biomass and industrial combustion (63%) and other unidentified sources (23%). Other sources of PM, such as crustal dust and traffic, contribute a total of 13%.