Characteristics of PM2.5 carbonaceous aerosol in the Sihwa industrial area,Korea

In order to investigate the characteristics of carbonaceous fine aerosols, PM_2.5 particulate samples were collected in the Sihwa industrial complex area between February 1998 and 1999 and in Seoul between 31 May and 9 June 1999, respectively. The carbonaceous species were analyzed by the selective thermal manganese dioxide oxidation (TMO) method. In Sihwa, average OC and EC concentrations for the entire data set were measured to be 9.8 and 1.8 μg m⁻³, respectively. The OC concentrations were higher than those measured in other urban environments. The EC concentrations were lower than those of other urban environments. The OC/EC ratio measured at the Sihwa area was higher than those at other urban and rural environments. Backward trajectories of sampled air masses were performed to find out the sources of those higher OC/EC levels. Enrichment in the organic compounds during winter periods can be explained by the combination of primary local emissions from the industrial complex area and long-range transport of organic species from outside the Sihwa area. High OC values in June resulted from primary anthropogenic emissions and secondary organic aerosol formation rather than the atmospheric transport of organic compounds from the outside. In urban area of Seoul, the OC and EC concentrations in PM_2.5 during the summer were higher than those measured at other urban atmospheres. OC/EC ratios obtained in Seoul were lower than Sihwa. It can be concluded that carbonaceous species in Seoul were mainly emitted from primary anthropogenic sources.     

PM10 and PM2.5 source apportionment in the Barcelona Metropolitan area, Catalonia, Spain

Levels of total suspended particles, PM10, PM2.5 and PM1 were continuously monitored at an urban kerbside in the Metropolitan area of Barcelona from June 1999 to June 2000. The results show that hourly levels of PM2.5 and PM1 are consistent with the daily cycle of gaseous pollutants emitted by traffic, whereas TSP and PM10 do not follow the same trend, at least in the diurnal period. The PM2.5/PM10 ratio is dependent on the traffic emissions, whereas additional contribution sources for the >10 μm fraction must be taken into account in the diurnal period. Different PM10 and PM2.5 source apportionment techniques were compared. A methodology based on the chemical determination of 83% of both PM10 and PM2.5 masses allowed us to quantify the marine (4% in PM10 and <1% in PM2.5), crustal (26% in PM10 and 8% in PM2.5) and anthropogenic (54% in PM10 and 73% in PM2.5) loads. Peaks of crustal contribution to PM10 (up to 44% of the PM10 mass) were recorded under Saharan air mass intrusions. A different seasonal trend was observed for levels of sulphate and nitrate, probably as a consequence of the different thermodynamic behaviour of these PM species and the higher summer oxidation rate of SO₂.     

Seasonal variation of chemical composition and source apportionment of PM2.5 in Pune,India

Environmental Science and Pollution Research - Particulate matter with size less than or equal to 2.5&nbsp;μm (PM2.5) samples were collected from an urban site Pune, India, during April...     

Chemical Composition and Source Apportionment of PM25 Particles in the Sihwa Area,Korea

ABSTRACT

To investigate the chemical characteristics of fine particles in the Sihwa area, Korea, atmospheric aerosol samples were collected using a dichotomous PM₁₀ sampler and two URG PM_2.5 cyclone samplers during five intensive sampling periods between February 1998 and February 1999. The Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS), ion chromatograph (IC), and thermal manganese dioxide oxidation (TMO) methods were used to analyze the trace elements, ionic species, and carbonaceous species, respectively. Backward trajectory analysis, factor analysis, and a chemical mass balance (CMB) model were used to estimate quantitatively source contributions to PM_{2 5} particles collected in the Sihwa area.

The results of PM_2.5 source apportionment using the CMB7 receptor model showed that (NH₄)₂SO₄ was, on average, the major contributor to PM_2.5 particles, followed by nontraffic organic carbon (OC) emission, NH₄NO₃, agricultural waste burning, motor vehicle emission, road dust, waste incineration, marine aerosol, and others. Here, the nontraffic OC sources include primary anthropogenic OC emitted from the industrial complex zone, secondary OC, and organic species from distant sources. The source impact of waste incineration emission became significant when the dominant wind directions were from southwest and west sectors during the sampling periods. It was found that PM_2.5 particles in the Sihwa area were influenced mainly by both anthropogenic local sources and long-range transport and transformation of air pollutants.     

Chemical fingerprint and source apportionment of PM 2.5 in highly polluted events of southern Taiwan

To investigate the spatial distribution and diurnal variation of the chemical composition of PM2.5 pollution in an industrial city of southern Taiwan, 12-h PM2.5 was diurnally continuously collected simultaneously at the Kaoping Air Quality Zone (KAQZ) during one highly PM2.5-polluted episode. Water-soluble ions, metallic elements, carbonaceous contents, dicarboxylic acids, and anhydrosugars were analyzed to characterize the chemical fingerprint of PM2.5. Backward trajectory simulation and chemical mass balance (CMB) receptor modeling were applied to identify the potential sources of PM2.5 and their contributions. It showed that Chaozhou (rural area) accompanying the highest SORs and NORs suffered from the most severe PM2.5 pollution during the episode. Sulfate (SO42−) was probably formed by the atmospheric chemical reaction in the daytime, while NO3− processed at nighttime at the KAQZ. A homogeneous formation of NO3− occurred at Chaozhou. The concentrations of Zn, Pb, Fe, Cu, V, and Al, mainly emitted from anthropogenic sources, increased significantly at the KAQZ. The highest OC, SOC/OC, and DA/OCs at Daliao (industrial area) were attributed to the transformation of primary VOCs to secondary OC via photo-oxidation during the episode. Oxalic acid was mainly produced through photochemical reactions since a high correlation between oxalic acid and Ca2+ was observed at Nanzi (urban area) and Daliao during the episode. During the episode, PM2.5 mostly originated from local primary or secondary aerosol than long-range overseas transport. The dominant source was anthropogenic emissions, accounting for 67.1% and 70.4% of PM2.5 at Nanzi and Daliao, respectively. At Chaozhou, the contribution of anthropogenic emissions was the lowest (42.4%), but secondary aerosols had the highest contribution of 38.3% of PM2.5 among the three areas during the episode.     

Health risk assessment and source apportionment of PM2.5-bound toxic elements in the industrial city of Siheung,Korea

Environmental Science and Pollution Research - The emission sources and their health risks of fine particulate matter (PM2.5) in Siheung, Republic of Korea, were investigated as a middle-sized...     

Chemical characteristics of principal PM2.5 species in Chongju,South Korea

Fine particles were collected over four seasons from October 1995 to August 1996 to evaluate the chemical characteristics of principal PM_2.5 components in Chongju, South Korea. The annual mean concentrations of PM_2.5 (d_p⩽2.5 μm), sulfate, nitrate, ammonium, elemental carbon (EC) and organic carbon (OC) were 44.2, 8.22, 3.63, 2.84, 4.44 and 4.99 μg m⁻³, respectively. The sum of the species measured from this study accounted for 50–62% of the PM_2.5 mass. Sulfate was the most abundant species and constituted 13–23% of the PM_2.5 mass. The EC and OC accounted for 17–28% of PM_2.5. The correlation between OC and EC was strong, and the annual mean ratio of OC/EC was 1.12, suggesting that OC measured in the Chongju area may be emitted directly in particulate form as a primary aerosol.     

Analysis of the PM2.5 emission inventory and source apportionment in Jilin City,Northeast of China

Environmental Science and Pollution Research - This study collected and compiled statistical data on atmospheric pollution in Jilin City, China during 2013–2014, using models and methods to...     

Seasonal variations and source apportionment of atmospheric PM2.5-bound polycyclic aromatic hydrocarbons in a mixed multi-function area of Hangzhou,China

Environmental Science and Pollution Research - To reveal the seasonal variations and sources of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) during haze and non-haze episodes, daily PM2.5...     

Estimation of source apportionment and potential source locations of PM2.5 at a west coastal IMPROVE site

Particle composition data for PM_2.5 samples collected at Kalmiopsis Interagency Monitoring of Protected Visual Environments (IMPROVE) site in southwestern Oregon from March 2000 to May 2004 were analyzed to provide source identification and apportionment. A total of 493 samples were collected and 32 species were analyzed by particle induced X-ray emission, proton elastic scattering analysis, photon-induced X-ray fluorescence, ion chromatography, and thermal optical reflectance methods. Positive matrix factorization (PMF) was used to estimate the source profiles and their mass contributions. The PMF modeling identified nine sources. In the Kalmiopsis site, the average mass was apportioned to wood/field burning (38.4%), secondary sulfate (26.9%), airborne soil including Asian dust (8.6 %), secondary nitrate (7.6%), fresh sea salt (5.8%), OP-rich sulfate (4.9%), aged sea salt (4.5 %), gasoline vehicle (1.9%), and diesel emission (1.4%). The potential source contribution function (PSCF) was then used to help identify likely locations of the regional sources of pollution. The PSCF map for wood/field burning indicates there is a major potential source area in the Siskiyou County and eastern Oregon. The potential source locations for secondary sulfate are found in western Washington, northwestern Oregon, and the near shore Pacific Ocean where there are extensive shipping lanes. It was not possible to extract a profile directly attributable to ship emissions, but indications of their influence are seen in the secondary sulfate and aged sea salt compositions.     

One-year study of the elemental composition and source apportionment of PM10 aerosols in Florence, Italy

An extensive investigation was carried out for the characterisation of the air particulate composition in Florence. The aim was to determine the aerosol elemental concentrations, as well as to identify pollution sources. For our investigation, the external Particle-Induced X-Ray Emission-Particle-Induced gamma-Ray Emission beam facility of the Istituto Nazionale di Fisica Nucleare, Van de Graaff accelerator at the Physics Department of the Florence University was used. We report the results of the analysis of a long temporal series (approximately 1 yr) of PM10 particulate samples, collected on Millipore filters on a daily basis in three different sites (characterised by different urban settings). Daily concentrations of more than 20 elements were detected. The long sampling period (approximately 1 yr) allowed a comparison with the air quality recommended values and the identification of seasonal variations. Four main sources (traffic, oil-combustion, soil-dust, and wind transported sea-salt) were extracted with the help of Principal Component Analysis (PCA). An absolute PCA showed traffic to be the major source both in the high traffic site and in the urban background site.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

Health effects of PM2.5 constituents and source contributions in major metropolitan cities,South Korea

Ambient PM_2.5 is one of the major risk factors for human health, and is not fully explained solely by mass concentration. We examined the short-term associations of cause-specific mortality (i.e., all-cause, cardiovascular, and respiratory mortality) with the 15 chemical constituents and sources of PM_2.5 in four metropolitan cities of South Korea during 2014–2018. We found transition metals consistently showed significant associations with all-cause mortality, while the effects of other constituents varied across the cities and for cause of death. Carbonaceous components strongly affected the all-cause, cardiovascular, and respiratory mortality in Daejeon. Secondary inorganic aerosols, SO₄^2? and NH₄⁺, showed significant associations with respiratory mortality in Gwangju. We also found the sources from which species closely linked to mortality generally increased the relative mortality risks. Heavy metal markers from soil or industrial sources were significantly associated with mortality in all cities. However, several sources influenced mortality despite their marker species not being significantly associated with it. Secondary nitrate and secondary sulfate sources were linked to mortality in DJ. This could be attributed to the deep inland location, which might have facilitated formation of secondary inorganic aerosols. In addition, primary sources including mobile and coal combustion seemed to have acute impacts on respiratory mortality in Gwangju. Our findings suggest the necessity of positive matrix factorization (PMF)-based approaches for evaluating health effects of PM_2.5 while considering the spatial heterogeneity in the compositions and source contributions of PM_2.5.

     

PM2.5 source apportionment with organic markers in the Southeastern Aerosol Research and Characterization (SEARCH) study

Positive matrix factorization (PMF) and effective variance (EV) solutions to the chemical mass balance (CMB) were applied to PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) mass and chemically speciated measurements for samples taken from 2008 to 2010 at the Atlanta, Georgia, and Birmingham, Alabama, sites. Commonly measured PM_2.5 mass, elemental, ionic, and thermal carbon fraction concentrations were supplemented with detailed nonpolar organic speciation by thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS). Source contribution estimates were calculated for motor vehicle exhaust, biomass burning, cooking, coal-fired power plants, road dust, vegetative detritus, and secondary sulfates and nitrates for Atlanta. Similar sources were found for Birmingham, with the addition of an industrial source and the separation of biomass burning into open burning and residential wood combustion. EV-CMB results based on conventional species were qualitatively similar to those estimated by PMF-CMB. Secondary ammonium sulfate was the largest contributor, accounting for 27–38% of PM_2.5, followed by biomass burning (21–24%) and motor vehicle exhaust (9–24%) at both sites, with 4–6% of PM_2.5 attributed to coal-fired power plants by EV-CMB. Including organic compounds in the EV-CMB reduced the motor vehicle exhaust and biomass burning contributions at both sites, with a 13–23% deficit for PM_2.5 mass. The PMF-CMB solution showed mixing of sources within the derived factors, both with and without the addition of speciated organics, as is often the case with complex source mixtures such as those at these urban-scale sites. The nonpolar TD-GC/MS compounds can be obtained from existing filter samples and are a useful complement to the elements, ions, and carbon fractions. However, they should be supplemented with other methods, such as TD-GC/MS on derivitized samples, to obtain a wider range of polar compounds such as sterols, sugars, and organic acids. The PMF and EV solutions to the CMB equations are complementary to, rather than replacements for, each other, as comparisons of their results reveal uncertainties that are not otherwise evident.

Implications:?Organic markers can be measured on currently acquired PM_2.5 filter samples by thermal methods. These markers can complement element, ion, and carbon fraction measurements from long-term speciation networks. Applying the positive matrix factorization and effective variance solutions for the chemical mass balance equations provides useful information on the accuracy of the source contribution estimates. Nonpolar compounds need to be complemented with polar compounds to better apportion cooking and secondary organic aerosol contributors.     

Chemical characterization and source identification/apportionment of fine and coarse air particles in Thessaloniki,Greece

The distribution of air particulate mass and selected particle components (trace elements and polycyclic aromatic hydrocarbons (PAHs)) in the fine and the coarse size fractions was investigated at a traffic-impacted urban site in Thessaloniki, Greece. 76±6% on average of the total ambient aerosol mass was distributed in the fine size fraction. Fine-sized trace elemental fractions ranged between 51% for Fe and 95% for Zn, while those of PAHs were between 95% and 99%. A significant seasonal effect was observed for the size distribution of aerosol mass, with a shift to larger fine fractions in winter. Similar seasonal trend was exhibited by PAHs, whereas larger fine fractions in summer were shown by trace elements. The compositional signatures of fine and coarse particle fractions were compared to that of local paved-road dust. A strong correlation was found between coarse particles and road dust suggesting strong contribution of resuspended road dust to the coarse particles. A multivariate receptor model (multiple regression on absolute principal component scores) was applied on separate fine and coarse aerosol data for source identification and apportionment. Results demonstrated that the largest contribution to fine-sized aerosol is traffic (38%) followed by road dust (28%), while road dust clearly dominated the coarse size fraction (57%).     

Atmospheric concentrations of PM2.5 trace elements in the Seoul urban area of South Korea

Fine particles (PM2.5) were collected during all four seasons, from April 2001 to February 2002, in Seoul, South Korea, using an annular denuder system. Elemental compositions of ambient PM2.5 were analyzed using the proton-induced X-ray emission method. The greatest contributors (> or = 2%) to the PM2.5 mass were sulfur (S), silicon (Si), chlorine (Cl), aluminum (Al), and iron (Fe) in the spring; S in the summer; and S and Cl in the fall. S, Cl, and Si were the major elements in the winter. S was the most abundant species among the elements, ranging from 5.3 to 7.9%, followed by Si and Cl. From analysis of variance, PM2.5 mass, Al, Si, potassium, calcium, and Fe showed significant seasonal differences during the four seasons (p < 0.001). Enrichment factor (EF) analysis was carried out to identify the sources affecting the aerosol in the Seoul area. On the basis of the mean EF values, elemental S, copper, zinc, and lead may be emitted from anthropogenic sources (EF > 50). Elemental Al, Si, titanium, and Fe may be emitted from crustal sources (EF < 3). Additionally, a correlation analysis was carried out for source identification. The results of the correlation analysis were confirmed by the results of the EF analysis.     

Source apportionment of PM10 and PM2.5 in five Chilean cities using factor analysis

Chile is a fast-growing country with important industrial activities near urban areas. In this study, the mass and elemental concentrations of PM10 and PM2.5 were measured in five major Chilean urban areas. Samples of particles with diameter less than 10 microm (PM10) and 2.5 microm (PM2.5) were collected in 1998 in Iquique (northern Chile), Valparaiso, Vi?a del Mar, Rancagua (central Chile), and Temuco (southern Chile). Both PM10 and PM2.5 annual mean concentrations (PM10: 56.9-77.6 microg/m3; PM2.5: 22.4-42.6 microg/m3) were significantly higher than the corresponding European Union (EU) and U.S. Environmental Protection Agency (EPA) air quality standards. Moreover, the 24-hr PM10 and PM2.5 U.S. standards were exceeded infrequently for some of the cities (Rancagua and Valparaiso). Elements ranging from Mg to Pb were detected in the aerosol samples using X-ray fluorescence (XRF). For each of the five cities, factor analysis (FA) was applied to identify and quantify the sources of PM10 and PM2.5. The agreement between calculated and measured mass and elemental concentrations was excellent in most of the cities. Both natural and anthropogenic sources were resolved for all five cities. Soil and sea were the most important contributors to coarse particles (PM10-PM2.5), whereas their contributions to PM2.5 were negligible. Emissions from Cu smelters and oil refineries (and/or diesel combustion) were identified as important sources of PM2.5, particularly in the industrial cities of Rancagua, Valparaiso, and Vi?a del Mar. Finally, motor vehicles and wood burning were significant sources of both PM2.5 and PM10 in most of the cities (wood burning was not identified in Iquique).     

Source apportionment of particulate matter (PM2.5) in an urban area using dispersion,receptor and inverse modelling

Air pollution emission inventories are the basis for air quality assessment and management strategies. The quality of the inventories is of great importance since these data are essential for air pollution impact assessments using dispersion models. In this study, the quality of the emission inventory for fine particulates (PM_2.5) is assessed: first, using the calculated source contributions from a receptor model; second, using source apportionment from a dispersion model; and third, by applying a simple inverse modelling technique which utilises multiple linear regression of the dispersion model source contributions together with the observed PM_2.5 concentrations. For the receptor modelling the chemical composition of PM_2.5 filter samples from a measurement campaign performed between January 2004 and April 2005 are analysed. Positive matrix factorisation is applied as the receptor model to detect and quantify the various source contributions. For the same observational period and site, dispersion model calculations using the Air Quality Management system, AirQUIS, are performed. The results identify significant differences between the dispersion and receptor model source apportionment, particularly for wood burning and traffic induced suspension. For wood burning the receptor model calculations are lower, by a factor of 0.54, but for the traffic induced suspension they are higher, by a factor of 7.1. Inverse modelling, based on regression of the dispersion model source contributions and the PM_2.5 concentrations, indicates similar discrepancies in the emissions inventory. In order to assess if the differences found at the one site are generally applicable throughout Oslo, the individual source category emissions are rescaled according to the receptor modelling results. These adjusted PM_2.5 concentrations are compared with measurements at four independent stations to evaluate the updated inventory. Statistical analysis shows improvement in the estimated concentrations for PM_2.5 at all sites. Similarly, inverse modelling is applied at these independent sites and this confirms the validity of the receptor model results.     

Effects of soil dust episodes and mixed fuel sources on source apportionment of PM10 particles in Kuopio,Finland

A receptor modeling study was carried out in Kuopio, Finland, between January and April 1994. Near the center of town, the daily mean concentrations were measured for PM10, sulphur dioxide, carbon monoxide and Black Smoke. Elemental concentrations of PM10 samples for 38 days were analyzed by ICP-MS. The main sources and their contributions to the measured concentrations of PM10 particles were solved by receptor modeling using a factor analysis-multiple linear regression (FA-MLR) model. Because a dust episode was very strong during two sampling days, the FA analysis was strongly influenced by this episode and did not give main factors. The factor analysis, when the two episode days were omitted, gave credible factors related to the sources in the study area. The four major sources and their estimated contributions to the average PM10 concentration of 27.2 μg m^-3 were: soil and street dust 46–48%, heavy fuel oil burning 12–18%, traffic exhaust 10–14%, wood burning ca. 11% and unidentified sources 15–25%. However, during spring dust episode days, with maximum PM10 concentration of 150 μg m^-3, the main source of PM10 was soil.