Neutron activation analysis for identification of African mineral dust transport

A Gent stacked filter unit sampler was used to collect air particulate matter (APM) in separate coarse (PM_2.5–10) and fine (PM_2.5) size fractions, at a sub-urban site in Lisbon, Portugal. The sampling was done during the year 2001 and two daily samples were taken per week. The filters were analyzed for particulate mass by instrumental neutron activation analysis (INAA). The chemical analysis of APM levels and the study of the atmospheric dynamics by back-trajectories showed that most of the PM_2.5 and PM_2.5–10 peaks events were associated with air masses transport from the Saharan desert. High mineral load in ambient particulate matter levels were registered during the Saharan dust outbreaks. The accuracy of INAA to measure Fe, Sc and Sm was evaluated by NIST filter standards, revealing results with an agreement of ± 10%. This method constituted an important tool to identify these events.     

Extraction of arsenic species from airborne particulate filters—Application to an industrial area of Greece

In the present study, the extraction of the arsenic species arsenite (As(III)), arsenate (As(V)), monomethyarsonic (MMA) and dimethylarsinic acid (DMA) from airborne particulate filters was investigated and optimized. For this purpose, total suspended particulate matter as well as size fractionated aerosol samples were collected from the industrial area of Aspropyrgos, Greece, in glass fibre and polycarbonated filters, respectively. Among H₃PO₄ and HCl, tested in various concentrations, concentrated HCl was found to be the most effective extractant for arsenic from both polycarbonated and glass fibre filters, without provoking any arsenic species transformation. However, the quantitative extraction of arsenic species from glass fibre filters required the subsequent washing of the filters with ultrapure water after their leaching with concentrated HCl. The developed procedure was applied to airborne particulate filters for arsenic speciation in Aspropyrgos' atmosphere. The results showed an enrichment of As in the fine (PM_2.5) compared with the coarse (PM_10–2.5) fraction of airborne particulates, while As(V) was found to be the predominant arsenic species in all samples. Finally, As concentration in the PM₁₀ fraction, for the investigated area and time period from December 2004 to June 2006, was below the target value of 6 ng As m^− 3, referred in the Directive 2004/107 of European Union.     

Determination of chemical elements in airborne particulate matter collected at Lembang, Indonesia by particle induced X-ray emission

Monitoring the air quality in ambient air is an important step for assessing the air pollution level in one region and its impact to the human health. In this study, the determination of chemical elements concentrations in airborne particulate matter collected in suburban area of Lembang, Indonesia was carried out. Samples were collected using a Gent stacked filter unit sampler in two size fractions of <2.5 μm (fine) and 2.5–10 μm (coarse). Sampling was conducted twice a week for 24 h from January 2008 to June 2009 and 123 pairs of samples were collected. Black carbon was determined by reflectance and chemical elements analysis were performed using particle induced X-ray emission (PIXE). PIXE as one of ion beam analysis techniques is suitable for analyzing particulate matter for its multielemental analysis with good limits of detection. Results showed that none of daily concentrations of PM_2.5 and PM₁₀ exceeded the 24 h Indonesian NAAQS for PM_2.5 and PM₁₀. Chemical elements such as Mg, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Hg and Pb were determined and the correlation between these elements was reported in order to understand the anthropogenic sources of particulate matter.     

Elemental concentrations of aerosols near Portuguese power plants by INAA and PIXE

Mass and elemental concentrations in PM₁₀ and PM_2.5 — airborne particulate matter with an aerodynamic diameter below 10 μm and 2.5 μm, respectively — have been evaluated in mainland Portugal since 1993. The data herein refer to areas generally impacted by emissions from electrical power plants, either coal- or oil-fired, which are mostly large, state-of-the-art facilities. Background areas have been sampled as well, and results from one of them are given for comparison. Through the country, lead levels are well below the European enacted values, particularly since unleaded fuels became mandatory in the late 1990s. Nickel appears especially concentrated in PM_2.5 and, apart from extreme cases (rural sites, coal-fired plants), its levels are not significantly different from place to place. Highest values for arsenic and mercury have been found in the vicinity of the coal-fired plants. Cadmium data, if only available for metropolitan Lisbon, seems to confirm the trend for anthropogenic elements appearing mainly in fine particulates.     

Particle-size distribution of polycyclic aromatic hydrocarbons in urban air in southern Spain

The size distribution of polycyclic aromatic hydrocarbons (PAH) was determined for airborne particles from a large city with high vehicular traffic. The analytical method was optimised and validated using NIST standard reference material (SRM 1649a Urban Dust). The 16 priority PAH listed in the US-EPA were Soxhlet-extracted from filtered particulate matter and then fractionated using on-column chromatography. The aromatic fraction was quantified by gas chromatography-mass spectrometry. Real samples of particles collected in Seville (Spain) were analysed using the validated method. Values for the total concentration of PAH in the air, as well as the concentrations of each PAH in six particle-size ranges were obtained. Values of the PAH in TSP, PM₁₀, PM_2.5 and PM₁ were assessed.     

Bioaccessibility of selected trace metals in urban PM<Subscript>2.5</Subscript> and PM<Subscript>10</Subscript> samples: a model study

Bioaccessibility of trace metals originating from urban particulate matter was assessed in a worst case scenario to evaluate the uptake and thus the hazardous potential of these metals via gastric juice. Sampling was performed over a period of about two months at the Getreidemarkt in downtown Vienna. Concentrations of the assayed trace metals (Ti, Cr, Mn, Co, Ni, Cu, Zn, Mo, Ag, Cd, Sn, Sb, Tl and Pb) were determined in PM_2.5 and PM₁₀ samples by ICP-MS. The metal concentrations in sampled air were in the low picogram to high nanogram per cubic metre range. The concentrations in PM_2.5 samples were generally lower than those in PM₁₀ samples. The average daily intake of these metals by inhalation for a healthy adult was estimated to be in the range of <1 ng (Tl) to >1,000 ng (Zn). To estimate the accessibility of the inhaled and subsequently ingested metals (i.e. after lung clearance had taken place) in the size range from 2.5- to 10-μm aerodynamic equivalent diameter, a batch-extraction with synthetic gastric juice was performed. The data were used to calculate the bioaccessibility of the investigated trace metals. Extractable fractions ranged from 2.10% (Ti in PM_2.5) to 91.0% (Cd in PM_2.5), thus yielding bioaccessible fractions (PM_2.5–10) from 0.16 ng (Ag) to 178 ng (Cu).     

High time resolution observation and statistical analysis of atmospheric light extinction properties and the chemical speciation of fine particulates

In recent years, the visibility deterioration caused by regional fine particulate pollution becomes one of the crucial air pollution problems in the urban areas of our country. The rapid variation of visibility and fine particulates make it difficult to estimate the relationship between them precisely and accurately unless high time resolution observation data can be accessed. This study aims to fill this gap in the field of atmospheric science by establishing a formula using multiple linear regressions. Excellent fitting goodness (R ² = 0.913, n = 3167) was obtained using 10 min average of high-resolution real-time light scattering coefficients, light absorption coefficients, main chemical speciation concentration in PM₁ and some meteorological parameters from 17 Jan to 16 Feb, 2009. It shows that the average light extinction coefficient during the observation in the winter of Shenzhen was measured to be 290 ± 183 Mm^?1, consisting of 72% of light scattering and 21% of absorption. In terms of the percentage contribution of PM₁ chemical species to the total light extinction, the organic matter was estimated to be most with an average of 45%, followed by ammonium sulfate with an average of 24%. The contributions of black carbon and ammonium nitrate were 17% and 12%, respectively. Besides, the diurnal variation of light extinction was investigated as well in this study.     

Determination of Pesticides in the Respirable Fraction of Airborne Particulate Matter by High-performance Liquid Chromatography–Tandem Mass Spectrometry

Potential harmful effects of pesticides include risks to human health of workers involved in the wet spray application in cultivated areas. Inhalation exposure depends on several factors including pesticide concentrations in the respirable fraction of airborne particulate matter (PM₄). To ensure a high level of protection, the use of tractors with cabins provides protection against dust, aerosols, and vapors. Since tractors not providing maximum protection are still in use, PM₄ was sampled during spreading operations in agricultural fields inside and outside tractor cabins. Sample preparation technique based on accelerated solvent extraction and solid-phase extraction cleanup was optimized before analysis of nine pesticides in PM₄. Meptyldinocap, deltamethrin, myclobutanil, fluopyram, methoxyfenozide, dimethomorph, fluopicolide, cyflufenamid, and metrafenone were simultaneously determined by high-performance liquid chromatography–electrospray ionization–tandem mass spectrometry (HPLC–ESI–MS–MS). The results demonstrated the efficacy of the tractor cabs used in the sampling sites.     

Application of NAA to air particulate matter collected at thirteen sampling sites in eight Asian countries: A collaborative study

Air particulate matter (APM) samples (PM_2.5 and PM_10–2.5) were collected at 13 sampling points in 8 Asian countries and their chemical compositions were determined by using neutron activation analysis (NAA) with the k ₀-standardization method in addition to conventional comparative method of NAA. Analytical data showed that mass concentration and elemental composition of the APM collected are variable in terms of time and space, and are related to the characteristics of the sampling sites concerned. NAA was proved to be highly effective for the regional characterization of APM in chemical composition.     

Source identification and long-term monitoring of airborne particulate matter (PM<Subscript>2.5</Subscript>/PM<Subscript>10</Subscript>) in an urban region of Korea

Summary For the identification of air pollution sources, about 500 airborne particulate matter (PM_2.5and PM₁₀) samples were collected by using a Gent air sampler and a polycarbonate filter in an urban region in the middle of Korea from 2000 to 2003. The concentrations of 25 elements in the samples were measured by using instrumental neutron activation analysis (INAA). Receptor modeling was performed on the air monitoring data by using the positive matrix factorization (PMF2) method. According to this analysis, the existence of 6 to 10PMF factors, such as metal-alloy, oil combustion, diesel exhaust, coal combustion, gasoline exhaust, incinerator, Cu-smelter, biomass burning, sea-salt, and soil dust were identified.     

Characterization of the aeolian aerosol from Cape Verde by k 0-INAA and PIXE

Due to its location on West Coast of Africa, Cape Verde is highly influenced by Sahara Desert dust events being an optimum place to observe and study the African aeolian aerosol. During 2011, particulate matter with an aerodynamic diameter lower than 10 μm (PM₁₀) was sampled in Santiago Island and its chemical composition was evaluated by k ₀-instrumental neutron activation analysis (k ₀-INAA) and particle induced X-ray emission (PIXE). This study showed the existence of a seasonal intrusion of dust from Africa (that occurred from October to March) characterized by significant increases of PM₁₀, mineral elements and anthropogenic particles concentrations. In 2011, the PM₁₀ health-based air quality guidelines defined by WHO, EU and USEPA were exceeded. Cape Verde PM₁₀ composition was characterized essentially by high concentrations of elements originating from the soil (Ca, Ce, Co, Fe, K, Mg, Mn, Rb, S, Sc, Si, Sm, and Ti) and sea (Br, Cl, and Na); and low concentrations of anthropogenic elements (As, Cr, Cu, Ni, Pb, Sb, V, and Zn). k ₀-INAA and PIXE were fundamental tools for the determination of airborne chemical elements in Cape Verde. Their multi-elemental capabilities in association with low detection limits made it possible to determine the majority of the element concentrations of environmental interest.     

Assessment of the sources of the inorganic fraction of aerosol in a conurbation

Two intensive sampling campaigns for coarse (PM_2.5–10) and fine (PM_2.5) particulate matter were carried out in August 2003 and March 2004 in the multi-impacted centre of the Athens (Greece) conurbation. Receptor modelling by means of Positive Matrix Factorization was utilised in order to provide an insight to the poorly characterised sources of the chemically analysed inorganic fraction of the sampled aerosol mass. Using elemental concentrations, seven factors have been resolved for both fractions for August 2003. Combining elemental and ionic concentrations, nine factors were resolved in the coarse particulate matter and eight in the fine particulate matter for March 2004. The greatest contributors of primary origin are (re)suspended dust/soil and sea salt. Secondary aerosol contributions were resolved in the form of secondary sulphate, secondary nitrate as well as an aged sea salt factor which was characterised by the replacement of chloride with sulphate and, secondarily, nitrate. Furthermore, throughout sites and fractions, primary anthropogenic emissions were identified in a series of factors, including a Pb-rich profile, representing non-catalytic exhaust emissions, a Cu-Mo-Sb-rich profile representing brake emissions, a Zn-Ba-rich profile representing tyre-wear and heavy vehicle brakes, and, lastly, a V-Ni-rich factor representing industrial heavy oil-combustion. Local anthropogenic emissions predominated, outweighing long-range transport as it was suggested by the lack of direct relationship between changes in the wind speed and direction and species mass burdens, as well as factor contributions.     

Urinary levoglucosan as a biomarker for residential wood smoke exposure

As part of a randomised controlled residential intervention study, levoglucosan (LG) was investigated as a biomarker for wood smoke exposure. This study was conducted among 33 children living in homes that used wood stoves for residential heating. Indoor fine particulate matter (PM_2.5) concentrations and corresponding urine samples from participants were collected during pre- and a post-intervention winter sampling periods. Interventions included the installation of an air filtration unit and a wood stove change out. Homes and children assigned to a placebo filter served as the control condition. Results showed a strong reduction in indoor PM_2.5 among the air filter homes (≈58% reduction), whereas the wood stove change out homes did not have a significant PM_2.5 reduction from pre- to post-intervention observations. Children living in the air filter homes did not show a corresponding reduction in urinary LG concentrations. Further analysis did not show an association between overall changes in indoor PM_2.5 concentrations and changes in urinary LG concentrations. These findings suggest that urinary LG is not a reliable indicator of wood smoke exposure in residential wood heating settings.     

The analysis of seasonal air pollution pattern with application of neural networks

Air pollution monitoring includes measuring the concentrations of air contaminants such as nitrogen dioxide, sulfur dioxide, some polycyclic aromatic hydrocarbons(PAHs), suspended particulate matter (PM) and tar substances. The purpose of this study was to determine the possibility of using artificial neural networks for identification of any patterns occurring during heating and nonheating seasons. The samples included in the study were collected over a period of 5 years (1997–2001) in the area of the city of Gdansk and the levels of pollutants measured in the samples collected were used as inputs to two different types of neural networks: multilayer perceptron (MLP) and self-organizing map (SOM). The MLP was used as a tool to predict in what heating season a certain sample was collected, and the SOM was applied for mapping all samples to recognize any similarities between them. This study also presents the comparison between two projection methods—linear (principal component analysis, PCA) and nonlinear (SOM)—in extracting valuable information from multidimensional environmental data. In the research the MLP model with 13-12-1 topology was developed and successfully trained for classification of air samples from different seasons. The sensitivity analysis on the inputs to the MLP indicated benz[α]anthracene, benzo[α]pyrene, PM₁, SO₂, tar substances and PM₁₀ as the most distinctive variables, while PCA pointed to PAHs and PM₁.     

Determination of 1-nitropyrene in low volume ambient air samples by high-performance liquid chromatography with fluorescence detection

To measure the actual exposure of a person to 1-nitropyrene (1-NP) in airborne particulate matter, it is considered more accurate to collect air samples with a portable air sampler than to sample at a fixed location. However, because the portable samplers can sample only small volumes, a sensitive method is needed to analyze the compounds that are collected on a filter. Here we describe a high-performance liquid chromatographic (HPLC) method with fluorescence detection that is sensitive and precise enough for use with portable air samplers. The developed column-switching system successfully removed the interfering substances in the samples with only a simple pretreatment. To improve the precision of the measurement, deuterated 1-NP was used as an internal standard, and it eluted immediately prior to 1-NP with sufficient resolution (R_s, 1.50). The detection limit was 0.32 fmol/injection, and the calibration range was from 2 to 100 fmol. The proposed method was applied to determining 1-NP in fine airborne particulate matter (PM_2.5) at two sites with low pollution levels. 1-NP was detected in all samples at concentrations in the low fmol/m³ range. The proposed method has enough sensitivity and precision to determine 1-NP in the limited air volume of the portable sampler.     

Source apportionment of carbonaceous particulate matter during haze days in Shanghai based on the radiocarbon

To estimate the sources of carbonaceous particulate matter, ¹⁴C and biomass-burning marker (levoglucosan) were measured in the form of organic carbon (OC) and elemental carbon (EC) in PM_2.5 that was collected in five different functional districts of Shanghai during winter 2013. Spatial variations of the contemporary proportion among different districts were evident. The results of levoglucosan in Xujiahui (XH) and Chongming (CM) agreed well with those of ¹⁴C. The results indicate that environmental protection policies should vary for functional districts within the same city to account for their different sources of emissions.     

Local and non-local sources of airborne particulate pollution at Beijing

A new element tracer technique has firstly been established to estimate the contributions of mineral aerosols from both inside and outside Beijing. The ratio of Mg/Al in aerosol is a feasible element tracer to distinguish between the sources of inside and outside Beijing. Mineral aerosol, inorganic pollution aerosol mainly as sulfate and nitrate, and organic aerosol are the major components of airborne particulates in Beijing, of which mineral aerosol accounted for 32%–-67% of total suspended particles (TSP), 10% –70% of fine particles (PM2.5), and as high as 74% and 90% of TSP and PM_2.5, respectively, in dust storm. The sources from outside Beijing contributed 62% (38%–-86%) of the total mineral aerosols in TSP, 69% (52%–-90%) in PM₁₀, and 76% (59%–-93%) in PM_2.5 in spring, and 69% (52%–-83%), 79% (52%–-93%), and 45% (7% – 79%) in TSP, PM₁₀, and PM_2.5, respectively, in winter, while only ≈20% in summer and autumn. The sources from outside Beijing contributed as high as 97% during dust storm and were the dominant source of airborne particulates in Beijing. The contributions from outside Beijing in spring and winter are higher than those in summer, indicating clearly that it was related to the various meteorological factors.     

Determination of lead in fine particulates by slurry sampling electrothermal atomic absorption spectrometry

A simple method for determining lead in fine particulates (PM_2.5) by using electrothermal atomic absorption spectrometry (ETAAS) has been developed. Particulates collected on Nuclepore filter by using a dichotomous sampler were suspended in diluted nitric acid after ultrasonic agitation. The dislodging efficiency is nearly 100% after agitation for 5 min. In order to study the suspension behavior of PM_2.5 in solvents, a Brookhaven ZetaPlus Particle Size Analyzer was used to determine the particle size distribution and suspension behavior of air particulates in the solvent. The pre-digestion and modification effect of nitric acid would be discussed. Palladium was added as a chemical modifier and the temperature program of ETAAS was changed in order to improve the recovery. The slurry was introduced directly into a graphite tube for atomization. The metal content in the sample was determined by the standard addition method. In addition, a conventional acid digestion procedure was applied to verify the efficiency of the slurry sampling method. It offers a quick and efficient alternative method for heavy metal characterization in fine particulates. Received: 2 August 2000 / Revised: 25 October 2000 / Accepted: 28 October 2000     

Analysis of urban dust (PM<Subscript>2</Subscript>/PM<Subscript>10-2</Subscript>) in Daejeon city by instrumental neutron activation analysis

Summary As part of an air pollution monitoring study, airborne particulate matter (PM₂/PM_10-2) samples were collected from 2000 to 2003 at two sampling sites in an urban region, Daejeon, the middle of Korea. Mass concentrations of both fine and coarse fractions and that of the black carbon in the fine particles were measured using the Gent stacked filter unit sampler and the smoke stain reflectometer, respectively. In the collected samples the concentrations of 24 elements were analyzed using instrumental neutron activation analysis. Monitored data were investigated for their temporal trends under different environmental conditions and their seasonal correlation patterns. Crustal enrichment factors were also estimated to establish the contribution between anthropogenic and crustal origin. Patterns for airborne particle matter (APM) and elemental concentrations, seasonal variation of some marker elements were investigated. The results can be applied for the investigation of further air pollution sources and for the evaluation of air quality.     

Application of receptor models to airborne particulate matter

The human activities in their various aspects cause a change in the natural air quality. This change results more marked in very populated and in high industrialized areas. Some pollutants emitted are typical of a particular activity. Each source of pollution is identified by its profile in the composition of the emissions in the environment. Multivariate receptor models can be used in order to apportion pollutants to the different sources assessing the contribution of each source to the total pollution.This paper deals with the application of Absolute Principal Component Scores (APCS) receptor model to data obtained from the automatic network of air quality monitoring in the city of Bari (South Italy). The parameters monitored by automatic networks, as bihourly values, are PM₁₀, NO_x, CO, Benzene, Toluene, Xilene. The data shown in this paper concerning 1 month almost of sampling in different monitoring stations of Bari Municipality during the period of time from January 2005 to April 2006. Moreover preliminary results obtained applying the APCS model to daily PM_2.5 samples collected during SITECOS PRIN project are shown. The results concerning data collected in corso Cavour (Bari) during the month of October 2005.The results obtained by APCS receptor model seem to suggest a poor contribution of the “vehicular traffic source” and a relevant contribution of the “secondary particulate source” to particulate matter concentrations.