Elemental Composition Of Particulate Matter Research Articles

Size distribution and elemental composition of airborne particulate matter on four plant species in vertical greenery systems

Vertical greenery systems (VGSs) have been proven to greatly improve the urban thermal environment. However, their effect on the retention of airborne particulate matter (PM) in the road environment remains unclear. This study aimed to assess the quantity of size-segregated PMs on both the upper (adaxial) and lower (abaxial) leaf surfaces, the mass of size-segregated PMs on the leaf surface and within the leaf wax, as well as the elemental composition of PMs retained in leaf stomata of four plant species in VGSs in Guangzhou. The findings revealed that VGSs exhibited greater retention of fine (<2.5 μm) PMs when compared to coarse (2.5–10 μm) and large (>10 μm) PMs. Among the four species studied, Tradescantia spathacea exhibited the highest PM retention in VGSs. The number density of accumulated PMs on the upper and lower leaf surfaces of the four plant species of VGSs at three heights varied significantly with species, heights, and their interaction (P < 0.05). The greatest stomatal block rate by PM occurred at a height of 0.6 m, the range was 91.1%–98.0%. The composition of PMs retained by the leaves primarily consisted of common element of C, O, Ca, K, Mg, and Si, which likely originated from natural sources. Heavy metals (HMs) such as Cr and Cd may have originated from brakes, while Zn and Cu might be attributed to tire wear and exhaust emissions. Therefore, VGSs effectively retained a substantial quantity of airborne PM and contributed to the mitigation of urban air pollution issues.

Elemental Composition of Particulate Matter in the Euphotic and Benthic Boundary Layers of the Barents and Norwegian Seas

The increasing influence of Atlantic inflows in the Arctic Ocean in recent decades has had a potential impact on regional biogeochemical cycles of major and trace elements. The warm and salty Atlantic water, entering the Eurasian Basin through the Norwegian Sea margin and the Barents Sea, affects particle transport, sink, phyto-, and zooplankton community structure and could have far-reaching consequences for the marine ecosystems. This study discusses the elemental composition of suspended particulate matter and fluffy-layer suspended matter derived from samples collected in the Barents Sea and northern Norwegian Sea in August 2017. The mosaic distribution of SPM elemental composition is mainly determined by two factors: (i) The essential spatial variability of biological processes (primary production, abundance, and phytoplankton composition) and (ii) differences in the input of terrigenous sedimentary matter to the sea area from drainage sources (weak river runoff, melting of archipelago glaciers, etc.). The distribution of lithogenic, bioessential, and redox-sensitive groups of elements in the particulate matter was studied at full-depth profiles. Marine cycling of strontium in the Barents Sea is shown to be significantly affected by increasing coccolithophorid bloom, which is associated with Atlantic water. Mn, Cu, Cd, and Ba significantly enrich the suspended particulate matter of the benthic nepheloid layer relative to the fluffy layer particulate matter within the benthic boundary layer.

Particulate Matter and Trace Metal Retention Capacities of Six Tree Species: Implications for Improving Urban Air Quality

As effective filters for natural particulate matter (PM), plants play an important role in the reduction of PM, thus improving air quality. However, research on the relationship between leaf functional traits and PM retention capacity in different polluted environments remains limited. In this study, six tree species (Abies holophylla, Pinus tabuliformis, Juniperus chinensis, Populus berolinensis, Salix babylonica, Robinia pseudoacacia) in Shenyang city, China were selected as research objects to analyze their PM retention capacity in three different polluted environments (i.e., a busy road, an industrial area of the urban center, and a green space). Additionally, we determined the composition of trace elements associated with the different polluted environments; we also evaluated the impact of different polluted environments on leaf surface traits. The results showed that the actual amounts of PM and trace elements that accumulated on leaf surfaces differed considerably between pollution sites and plant species. The greatest accumulation of PM10 and PM2.5 deposited on the leaves of tested plants was at a traffic-related pollution site and the smallest accumulation was at a park site. There were significant differences in the PM10 and PM2.5 retention capacities of leaves among the different tree species (p &lt; 0.05), in the following order: Abies holophylla &gt; Pinus tabuliformis &gt; Juniperus chinensis &gt; Populus berolinensis &gt; Salix babylonica &gt; Robinia pseudoacacia. The average PM10 and PM2.5 accumulation amounts of Abies holophylla were 1.28–8.74 times higher than these of the other plants (p &lt; 0.05). Trace element analysis showed that the elemental composition of PM accumulated on leaf surfaces was location-dependent. In conclusion, a highly polluted environment can increase the average groove width, stomatal density, and roughness compared to a low-polluted environment. In contrast, the average value of contact angle is higher at low-pollution sites than at other sites. These results suggest that Abies holophylla is the most suitable greening tree species and that its widespread use could significantly reduce PM pollution in urban environments.

Assessment of plant species suitability in green walls based on API, heavy metal accumulation, and particulate matter capture capacity.

One of the most pressing issues confronting the civilized and modern world is air pollution. Particulate matter (PM) is a well-known pollutant that contributes significantly to urban air pollution and has numerous short- and long-term adverse effects on human health. One method of reducing air pollution is to create green spaces, mainly green walls, as a short-term solution. The current study investigated the ability of nine plant species to reduce traffic-related PM using a green wall system installed along a busy road in Mashhad, Iran. The main aims were (1) estimate the tolerance level of plant species on green walls to air pollution using the air pollution tolerance index (APTI); (2) assess the PM capture on the leaves of green wall species using scanning electron microscopy (SEM), energy dispersive X-ray (EDX) analysis, and accumulation of heavy metals using inductively coupled plasma (ICP); (3) select the most tolerance species for reducing air pollution using anticipated performance index (API). The plants' APTI values ranged from 5 to 12. The highest APTI value was found in Carpobrotus edulis and Rosmarinus officinalis, while Kochia prostrata had the lowest. Among the APTI constituents, leaf water content (R2 = 0.29) and ascorbic acid (R2 = 0.33) had a positive effect on APTI. According to SEM analysis, many PMs were adsorbed on the adaxial and abaxial leaf surfaces, as well as near the stomata of Lavandula angustifolia, C. edulis, Vinca minor, and Hylotelephium sp. Based on EDX analysis, carbon and oxygen formed the highest amount (more than 60%) of metals detected in the elemental composition of PM deposited on the leaves of all species. The Sedum reflexum had the highest Cr, Fe, Pb, and As accumulation. The concentrations of all heavy metals studied in green wall plants were higher than in the control sample. Furthermore, the C. edulis is the best plant for planting in industrial, urban areas of the city based on APTI, biological, economic, and social characteristics. It concludes that green walls composed primarily of plants with small leaves can significantly adsorb PM and accumulation of heavy metal.

Ultrafine particles, particle components and lung function at age 16years: The PIAMA birth cohort study.

Particulate matter (PM) air pollution exposure has been linked to lung function in adolescents, but little is known about the relevance of specific PM components and ultrafine particles (UFP). To investigate the associations of long-term exposure to PM elemental composition and UFP with lung function at age 16years. For 706 participants of a prospective Dutch birth cohort, we assessed associations of forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) at age 16 with average exposure to eight elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc) in PM2.5 and PM10, as well as UFP during the preceding years (age 13-16years) estimated by land-use regression models. After assessing associations for each pollutant individually using linear regression models with adjustment for potential confounders, independence of associations with different pollutants was assessed in two-pollutant models with PM mass and NO2, for which associations with lung function have been reported previously. We observed that for most PM elemental components higher exposure was associated with lower FEV1, especially PM10 sulfur [e.g. adjusted difference -2.23% (95% confidence interval (CI) -3.70 to -0.74%) per interquartile range (IQR) increase in PM10 sulfur]. The association with PM10 sulfur remained after adjusting for PM10 mass. Negative associations of exposure to UFP with both FEV1 and FVC were observed [-1.06% (95% CI: -2.08 to -0.03%) and -0.65% (95% CI: -1.53 to 0.23%), respectively per IQR increase in UFP], but did not persist in two-pollutant models with NO2 or PM2.5. Long-term exposure to sulfur in PM10 may result in lower FEV1 at age 16. There is no evidence for an independent effect of UFP exposure.

Particulate Matter Removal Ability of Ten Evergreen Trees Planted in Korea Urban Greening

Broad-leaved evergreen trees create urban forests for mitigation of climate warming and adsorption of particulate matter (PM). This study was performed to identify the species suitable for urban greening by examining the adsorption capacity of the evergreen species in urban areas in Korea, the adsorption points and the elemental composition of PM in the adsorbed tree. Leaf sampling was carried out four times (period of seven months from October 2017 to May 2018) and used after drying (period 28 to 37 days). Particulate matter (PM) was classified and measured according to size PM2.5 (0.2–2.5 μm), PM10 (2.5–10 μm), PM100 (10–100 μm). The total amount of PM adsorbed on the leaf surface was highest in Pinus densiflora (24.6 μg∙cm−2), followed by Quercus salicina (47.4 μg∙cm−2). The composition of PM adsorbed by P. densiflora is 4.0% PM2.5, 39.5% PM10 and 56.5% PM100, while those adsorbed by Q. salicina are evergreen at 25.7% PM2.5, 27.4% PM10 and 46.9% PM100. When the amount of PM adsorbed on the leaf was calculated by LAI, the species that adsorbed PM the most was P. densiflora, followed by Q. salicina, followed by Q. salicina in the wax layer, then P. densiflora. As a result of this study, the amount of PM adsorbed per unit area of leaves, and the amount of PM calculated by LAI, showed a simpler pattern. The hardwoods had a high adsorption rate of PM2.5. The adsorption ratio of ultra-fine PM2.5 by evergreen broad-leaved trees was greater than that of coniferous trees. Therefore, broad-leaved evergreens such as Q. salicina are considered very suitable as species for adsorbing PM in the city. PM2.5 has been shown to be adsorbed through the pores and leaves of trees, indicating that the plant plays an important role in alleviating PM in the atmosphere. As a result of analyzing the elemental components of PM accumulated on leaf leaves by scanning electron microscopy (SEM)/ energy dispersive x-ray spectroscopy (EDXS) analysis, it was composed of O, C, Si, and N, and was found to be mainly generated by human activities around the road. The results of this study provide basic data regarding the selection of evergreen species that can effectively remove aerial PM. It also highlights the importance of evergreen plants for managing PM pollution during the winter and provides insights into planning additional green infrastructure to improve urban air quality.

Assessment of the ability of roadside vegetation to remove particulate matter from the urban air.

The development of urbanised areas together with the growing transport infrastructure and traffic volume are the main cause of air quality deterioration due to the increasing concentrations of particulate matter. Dust pollution is a threat to human health. It can cause the development of lung, larynx or circulatory system cancer. Due to the ability to accumulate dust particles on the leaf surface, the contribution of trees in the process of phytoremediation of air pollution has started to be appreciated. An analysis of the elemental composition of particulate matter (PM) stored on the leaves surface was also carried out, which showed high average concentration of: C > O > Si > Fe (above 8wt.%). It was also observed single particles with a high concentration of heavy metals: Ti, Mn, Ba, Zn, Cr, Pb, Sn, Ni and REE (rare earth elements). The major origin of PM are vehicular emissions, soil and re-suspended road dust. This paper presents also a comparison of selected tree, shrub and vine species differing in their ability to accumulate particulate matter. It was experimentally determined the average leaf surface of individual plant species and established the amount of particulate matter with aerodynamic diameter between 10 and 100μm, 2.5 and 10μm, and 0.2 and 2.5μm deposited on the leaf surface and in waxes. Some species of vines (Parthenocissus quinquefolia), shrubs (Forsythia x intermediata) and coniferous trees, such as Betula pendula 'Youngii', Quercus rubra, Cratageus monogyna, Acer pseduoplatanus, Tilia cordata Mill. or Platanus orientalis turned out to be the most efficient in the process of phylloremediation.

Changes in the elemental composition of particulate matter in a speleotherapeutic cave

Atmosphere inside caves used for speleotherapy are microenvironments influenced by ventilation and human activities inside. In this context, particulate matter with an aerodynamic diameter from 15 nm to 10 μm was collected with an electrical low-pressure impactor ELPI+ in the Císařská Cave in the northern part of the Moravian Karst (Czech Republic) and 33 elements were determined with inductively coupled plasma tandem mass spectrometry (ICPMS/MS). To see the effect of ventilation, samples were collected with closed and opened entrances.Nucleation mode particles (particles with aerodynamic diameter less than 10 nm) were dominant in particle number concentrations at both cave ventilation regimes. Aitken mode particles (10–100 nm) differed in the content of sulphur, calcium, iron, chromium, magnesium and nickel for different ventilation regimes. Accumulation mode particles (100–1000 nm) consisted predominantly of sulphur and calcium, also chromium, copper, arsenic, molybdenum, selenium, cadmium and lead were mainly present in this particle size range. Coarse mode particles (larger than 1000 nm) contained predominantly calcium, in addition to common earth crust elements, originating by mechanical abrasion of cave floor.It is suggested that ventilation as well as children activities in the cave influence the elemental composition of particulate matter, which might have an impact on speleotherapy.

Investigating size-segregated sources of elemental composition of particulate matter in the South China Sea during the 2011 &amp;lt;i&amp;gt;Vasco&amp;lt;/i&amp;gt; cruise

Abstract. The South China Sea (SCS) is a receptor of numerous natural and anthropogenic aerosol species from throughout greater Asia. A combination of several developing countries, archipelagic and peninsular terrain, a strong Asian monsoon climate, and a host of multi-scale meteorological phenomena make the SCS one of the most complex aerosol–meteorological systems in the world. However, aside from the well-known biomass burning emissions from Indonesia and Borneo, the current understanding of aerosol sources is limited, especially in remote marine environments. In September 2011, a 2-week research cruise was conducted near Palawan, Philippines, to sample the remote SCS environment. Size-segregated aerosol data were collected using a Davis Rotating Uniform size-cut Monitor (DRUM) sampler and analyzed for concentrations of 28 elements measured via X-ray fluorescence (XRF). Positive matrix factorization (PMF) was performed separately on the coarse, fine, and ultrafine size ranges to determine possible sources and their contributions to the total elemental particulate matter mass. The PMF analysis resolved six sources across the three size ranges: biomass burning, oil combustion, soil dust, a crustal–marine mixed source, sea spray, and fly ash. Additionally, size distribution plots, time series plots, back trajectories and satellite data were used in interpreting factors. The multi-technique source apportionment revealed the presence of biogenic sources such as soil dust, sea spray, and a crustal–marine mixed source. Anthropogenic sources were also identified: biomass burning, oil combustion, and fly ash. Mass size distributions showed elevated aerosol concentrations towards the end of the sampling period, which coincided with a shift of air mass back trajectories to southern Kalimantan. Covariance between coarse-mode soil dust and fine-mode biomass burning aerosols were observed. Agreement between the PMF and the linear regression analyses indicates that the PMF solution is robust. While biomass burning is indeed a key source of aerosol, this study shows the presence of other important sources in the SCS. Identifying these sources is not only key for characterizing the chemical profile of the SCS but, by improving our picture of aerosol sources in the region, also a step forward in developing our understanding of aerosol–meteorology feedbacks in this complex environment.

Impact of elemental composition of particulate matter in the airshed of a University Farm on the local air quality

The impact of particulate matter on the ambient air quality of Landmark University Farm was assessed using deposition fluxes of Trace elements (TEs) in the airshed of the farm. Deposition gauges were employed to collect both dry and wet deposition samples of particulate matter between 2018 and 2019. Elemental compositions of particulates collected during the sampling period were analyzed using Energy Dispersive X-ray Fluorescence Spectroscopy (ED-XRF). The deposition fluxes of crustal and anthropogenic trace elements were also determined using standard methods. Results showed that in dry season, iron has the highest mean concentration (3283.61 mg/kg), while chromium has the lowest (0.023 mg/kg). On the other hand, in wet season, silicon and nickel have the highest and lowest mean concentrations of 159.34 mg/kg and 0.01 mg/kg respectively. Although the concentrations of these metals were higher in the dry season than wet season, there was no statistical significant difference between the mean concentrations of the elements measured in each season of the year (p > 0.05). The compositions of some of the elements in the particulate matters were found to be far above the recommended exposure limits prescribed by OSHA. The study concluded that the elemental composition of particulate matter in the airshed of the University Farm adversely impacts the ambient air quality of the Community.

Elemental Composition of Particulate Matter in the Southeastern Brazilian Ceramic Pole by Synchrotron Radiation X-ray Fluorescence Technique (SR-XRF)

In the present study, the elemental content of the particulate matter PM2.5 (particulate matter with diameters lower than 2.5 µm) and PM10 (particulate matter with diameters lower than 10 µm) of the Brazilian city of Rio Claro (SP) were analyzed by synchrotron radiation X-ray fluorescence (SR-XRF) in the Brazilian Synchrotron Light Laboratory (LNLS). A fractional sampling of particulate matter (PM) was carried out in two climatic periods (dry and rainy season). The elemental determination of PM2.5 and PM10 included the following elements: Si, S, Ca, K, Ti, Cr, Mn, Fe, Cu, and Zn. Elemental correlation studies, cluster analysis, principal component analysis and enrichment factor determination were performed in order to allow the distinction of the main sources of the emission of PM. The mean elementary contents, especially in PM10, were statistically different to each other between the sampling seasons and higher in dry than in rainy season. The cluster analysis indicated two groups as being the main constituting element groups for the composition of PM in Rio Claro. A major group originated by the resuspension of soil composed by the elements Si, Fe, Ca and K, and a second, minor group composed of S, Ti, Mn, Cu, Cr, and Zn, presumably influenced by vehicular emissions and the regions adjacent ceramic industries.

Use of the Neutron Activation Analysis, k0-standardized method, in the evaluation of the air quality in critical points of Belo Horizonte

Belo Horizonte, the capital of Minas Gerais, is one of the largest cities in Brazil. It is geographically centered on a region with intense mining and industrial activity and a fleet of more than 1.5 million vehicles. The numerous sources of atmospheric emissions of particulate matter in this capital and its vicinity offer a considerable risk to the degradation of air quality. In order to contribute with elemental composition of particulate matter, the Nuclear Technology Development Center / Brazilian Commission for Nuclear Energy, and the Department of Nuclear Engineering of the Federal University of Minas Gerais has developed a research based on environmental samples. This work aims to present the sampling methodology, the concentration values of sampled particulate matter preliminarily, the methodology of analysis of elemental concentration using the nuclear technique of neutron activation analysis, k0-standardized method, and interpreted through statistical techniques and values of the elemental concentrations more representative of the samplings carried out. The results pointed out the vehicle emissions as the major source that contributes to airborne particulate matter followed by soil resuspension.

Chemical and radioanalytical investigations of 106Ru-containing air filters from Vienna in fall 2017: searching for stable element anomalies

Related to the recent nuclear release of radioactive ruthenium isotopes in fall 2017, we analyzed air filters from Vienna for irregularities in the (stable) elemental composition of particulate matter from this period. Methods were SEM/EDXS and INAA. For comparison, a reference filter from 2007 and blank filters were used. The chemical fingerprint encompassed 28 elements. The results show no indication for a considerable change in the elemental composition of the suspended matter. For example, no anomalies in the abundance of platinum group elements were found. The results suggest that the release of 106Ru had not been accompanied by a release of detectable amounts of (activatable) stable elements.

On the Morphology and Composition of Particulate Matter in an Urban Environment.

Particulate matter (PM) plays a vital role in altering air quality, human health, and climate change. There are sparse data relevant to PM characteristics in urban environments of the Middle East, including Peshawar city in Pakistan. This work reports on the morphology and composition of PM in two size fractions (PM2.5 and PM10) during November 2016 in Peshawar. The 24 hous mass concentration of PM2.5 varied from 72 μg m-3 to 500 μg m-3 with an average value of 286 μg m-3. The 24 hours PM10 concentration varied from 300 μg m-3 to 1440 μg m-3 with an average of 638 μg m-3. The morphology, size, and elemental composition of PM were measured using Fourier Transform Infra Red (FT-IR) Spectroscopy and Scanning Electron Microscopy (SEM) with Energy Dispersive X-ray (EDX) Spectroscopy. The size of the analyzed particles by EDX ranged from 916 nm to 22 μm. Particles were classified into the following groups based on their elemental composition and morphology: silica (12%), aluminosilicates (23%), calcium rich (3%), chloride (2%), Fe/Ti oxides (3%), carbonaceous (49%), sulfate (5%), biogenic (3%). The major identified sources of PM are vehicular emissions, biomass burning, soil and re-suspended road dust, biological emissions, and construction activities in and around the vicinity of the sampling site.

Long-term exposure to ambient air pollution and incidence of brain tumor: the European Study of Cohorts for Air Pollution Effects (ESCAPE).

BackgroundEpidemiological evidence on the association between ambient air pollution and brain tumor risk is sparse and inconsistent.MethodsIn 12 cohorts from 6 European countries, individual estimates of annual mean air pollution levels at the baseline residence were estimated by standardized land-use regression models developed within the ESCAPE and TRANSPHORM projects: particulate matter (PM) ≤2.5, ≤10, and 2.5–10 μm in diameter (PM2.5, PM10, and PMcoarse), PM2.5 absorbance, nitrogen oxides (NO2 and NOx) and elemental composition of PM. We estimated cohort-specific associations of air pollutant concentrations and traffic intensity with total, malignant, and nonmalignant brain tumor, in separate Cox regression models, adjusting for risk factors, and pooled cohort-specific estimates using random-effects meta-analyses.ResultsOf 282194 subjects from 12 cohorts, 466 developed malignant brain tumors during 12 years of follow-up. Six of the cohorts also had data on nonmalignant brain tumor, where among 106786 subjects, 366 developed brain tumor: 176 nonmalignant and 190 malignant. We found a positive, statistically nonsignificant association between malignant brain tumor and PM2.5 absorbance (hazard ratio and 95% CI: 1.67; 0.89–3.14 per 10–5/m3), and weak positive or null associations with the other pollutants. Hazard ratio for PM2.5 absorbance (1.01; 0.38–2.71 per 10–5/m3) and all other pollutants were lower for nonmalignant than for malignant brain tumors.ConclusionWe found suggestive evidence of an association between long-term exposure to PM2.5 absorbance indicating traffic-related air pollution and malignant brain tumors, and no association with overall or nonmalignant brain tumors.

In-depth compositional analysis of water-soluble and -insoluble organic substances in fine (PM2.5) airborne particles using ultra-high-resolution 15T FT-ICR MS and GC×GC-TOFMS

Airborne particulate matter consisting of ionic species, salts, heavy metals and carbonaceous material is one of the most serious environmental pollutants owing to its impacts on the environment and human health. Although elemental and organic carbon compounds are known to be major components of aerosols, information on the elemental composition of particulate matter remains limited because of the broad range of compounds involved and the limits of analytical instruments. In this study, we investigated water-soluble and -insoluble organic compounds in fine (PM2.5) airborne particles collected during winter in Korea to better understand the elemental compositions and distributions of these compounds. To collect ultra-high-resolution mass profiles, we analyzed water-soluble and -insoluble organic compounds, extracted with water and dichloromethane, respectively, using an ultra-high-resolution 15 T Fourier transform ion cyclotron resonance (15T FT-ICR) mass spectrometer in positive ion mode (via both electrospray ionization [ESI] and atmospheric pressure photoionization [APPI] for water-extracts and via APPI for dichloromethane-extracts). In conjunction with the FT-ICR mass spectrometry (MS) data, subsequent two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) data were used to identify potentially hazardous organic components, such as polycyclic aromatic hydrocarbons. This analysis provided information on the sources of ambient particles collected during winter season and partial evidence of contributions to the acidity of organic content in PM2.5 particles. The compositional and structural features of water-soluble and -insoluble organic compounds from PM2.5 particles are important for understanding the potential impacts of aerosol-carried organic substances on human health and global ecosystems in future toxicological studies.

Prenatal exposure to outdoor airborne trace elements and cognitive and psychomotor development during childhood in four European birth cohorts

Introduction: Studies addressing exposure to elemental composition of particulate matter in outdoor air and neuropsychological development are sparse. We aimed to investigate the association of pre...

Particle Bound Metals at Major Intersections in an Urban Location and Source Identification Through Use of Metal Markers

Air quality monitoring for Kanpur in North India, an industrial city ranked among the top ten most polluted cities worldwide, was conducted in summer 2011. Airborne particulate matter (PM) sample from six locations were analyzed for metals. Source identification conducted using metals as source markers reveals probable sources of airborne particles being vehicular emissions, industrial, and railway activity. Findings were substantiated by investigating morphological characteristics and elemental composition of PM using SEM-EDX analysis at three major sites. In addition to confirmation of results by metal marker method, SEM-EDX analysis revealed presence of sulphur (S) which highlights influence of Panki Thermal Power Plant on air quality. The study shows that high levels of metals observed in airborne particles at major intersections may pose a significant cancer risk by exposure to toxics such as Cr, Pb and Ni.

Chemometrics in biomonitoring: Distribution and correlation of trace elements in tree leaves

The concentrations of 15 elements were measured in the leaf samples of Aesculus hippocastanum, Tilia spp., Betula pendula and Acer platanoides collected in May and September of 2014 from four different locations in Belgrade, Serbia. The objective was to assess the chemical characterization of leaf surface and in-wax fractions, as well as the leaf tissue element content, by analyzing untreated, washed with water and washed with chloroform leaf samples, respectively. The combined approach of self-organizing networks (SON) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) aided by Geometrical Analysis for Interactive Aid (GAIA) was used in the interpretation of multiple element loads on/in the tree leaves. The morphological characteristics of the leaf surfaces and the elemental composition of particulate matter (PM) deposited on tree leaves were studied by using scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) detector. The results showed that the amounts of retained and accumulated element concentrations depend on several parameters, such as chemical properties of the element and morphological properties of the leaves. Among the studied species, Tilia spp. was found to be the most effective in the accumulation of elements in leaf tissue (70% of the total element concentration), while A. hippocastanum had the lowest accumulation (54%). After water and chloroform washing, the highest percentages of removal were observed for Al, V, Cr, Cu, Zn, As, Cd and Sb (>40%). The PROMETHEE/SON ranking/classifying results were in accordance with the results obtained from the GAIA clustering techniques. The combination of the techniques enabled extraction of additional information from datasets. Therefore, the use of both the ranking and clustering methods could be a useful tool to be applied in biomonitoring studies of trace elements.

Spatial variation of PM elemental composition between and within 20 European study areas — Results of the ESCAPE project

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements.We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning.PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10.Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM.