Absolute Principal Component Analysis Research Articles

Metals and metalloids pollution levels, partitioning, and sources in the environmental compartments of a small urban catchment in Moscow megacity.

This study examines the contamination levels and sources of 32 metals and metalloids (MMs) in environmental compartments (roadside soil, road dust, and river suspended sediments) of a small urbanized river catchment located in Moscow megacity. MMs partitioning between particle size fractions (PM1000, PM1-10, and PM1) was analyzed by ICP-MS and ICP-AES methods. The pollution level of particle size fractions with MMs decreases in the following series: road dust>suspended sediments>soils. Absolute principal component analysis with multiple linear regression (PCA/APCS-MLR) shows that in both relatively coarse (PM1-10) and fine (PM1) fractions, traffic emissions are the primary contributors to pollution, whereas natural sources are dominant providers of chemical elements in bulk samples (PM1000). The predominance of fractions with a diameter over 10μm in all three studied compartments indicates that the mineral matrix of all compartments is formed predominantly by natural material. Across all compartments and their fractions, Sb, Cd, Zn, Mo, W, Sn, Cu, Pb, and Bi are consistently accumulated. PM1 and PM1-10 particles of road dust and suspended sediments also absorb Ni and Cr, suspended sediments retain Mn and As, and soils additionally accumulate As. Anthropogenic influence is more pronounced in PM1 and PM1-10 particles compared to bulk samples due to a large impact of industrial sources, traffic, construction activities, and waste storage. Polluted soils are an additional source of MMs to PM1 and PM1-10 of road dust and PM1-10 of suspended sediments, and road dust acts as a source of MMs to PM1-10 of soils.

Contamination assessment and source identification of metals and metalloids in submicron road dust (PM1) in Moscow Megacity.

The content of 39 metals and metalloids (MMs) in submicron road dust (PM1 fraction) was studied in the traffic zone, residential courtyards with parking lots, and on pedestrian roads in parks in Moscow. The geochemical profiles of PM1 vary slightly between different types of roads and courtyards but differ significantly from those in parks. In Moscow, compared to other cities worldwide, submicron road dust contains less As, Sb, Mo, Cr, Cd, Sn, Tl, Ca, Rb, La, Y, U, but more Cu, Zn, Co, Fe, Mn, Ti, Zr, Al, V. Relative to the upper continental crust, PM1 is highly enriched in Sb, Zn, Cd, Cu, W, Sn, Bi, Mo, Pb. In the courtyards, where contact between pollutants and the population is most frequent and occurs over an extended period, the level of PM1 pollution with MMs (from strong to extreme) is comparable to that on large roads. Source identification was conducted using correlations, elemental ratios, and absolute principal component analysis with multiple linear regression (APCA-MLR). In the traffic zone, non-exhaust and exhaust vehicle emissions contribute significantly to the MM concentrations in PM1 (especially for Bi, Sb, Sn, V, Fe, Cu, W, Mo); soil particles, abrasion of steel surfaces, industrial emissions, tire and road wear with carbonate dust resuspension contribute less. In the courtyards, the contribution of the road wear with carbonate dust resuspension and soil particles increases by up to 16% due to the poor condition of the road surface, frequent construction works, and large contact areas of roads with soils. In parks, the contribution of anthropogenic sources sharply decreases by 20-48% due to the increased soil resuspension rate. The spatial distribution pattern of MMs in submicron road dust should aid in the development of more effective road surface washing strategies, ultimately minimizing the risk to public health.

Preliminary Analysis of the Chemical Characteristics and Boron Sources of Surface Water and Groundwater in the Cherchen River Basin of Xinjiang

The climate of the Cherchen River Basin （CRB） is dry and rainless and the water resources are relatively scarce. Identifying the chemical characteristics and high boron sources of surface water and groundwater in the basin is important for the sustainable development and utilization of water resources and the protection of animals, plants, and human health. To preliminarily explore the chemical characteristics and the main sources of boron （B） in the CRB, a total of 46 groups of water samples （including six groups of river water and 40 groups of well water） were collected in 2023. The chemical characteristics of surface water and groundwater and the sources of boron in the CRB were preliminarily analyzed using a Piper diagram, Gibbs chart, correlation analysis, hydrogeochemical simulation, and absolute principal component analysis （PCA-APCS-MLR） and the contribution of different factors to boron and other chemical components was quantitatively evaluated. The results showed that the water resources in the CRB were weakly alkaline, with an average pH of 7.99. The groundwater was mostly brackish water and salt water and the anions and cations were mainly Cl- and Na+. Many types of water chemistry were present, among which the river water was mainly SO4·Cl-Na type and HCO3·SO4·Cl-Na type. The groundwater was mainly SO4·Cl-Na type. The average content of boron in river water in the area was 1.80 mg·L-1 and the over standard rate was 66.7%. The average content of boron in groundwater was 1.48 mg·L-1 and the exceeding standard rate was 45.0%. APCS-MLR receptor model analysis further revealed that the major sources of water chemical components and boron were leaching-enrichment, anthropogenic activity, and primary geological factors and unknown sources. The phenomenon of boron exceeding the standard in the water of the Cherchen River Basin was obvious, mainly due to agricultural activities （fertilizers and pesticides） and unknown sources. Isotope technology may further identify the main sources of boron in water.

Long-term exposure to several constituents and sources of PM2.5 is associated with incidence of upper aerodigestive tract cancers but not gastric cancer: Results from the large pooled European cohort of the ELAPSE project

It is unclear whether cancers of the upper aerodigestive tract (UADT) and gastric cancer are related to air pollution, due to few studies with inconsistent results. The effects of particulate matter (PM) may vary across locations due to different source contributions and related PM compositions, and it is not clear which PM constituents/sources are most relevant from a consideration of overall mass concentration alone. We therefore investigated the association of UADT and gastric cancers with PM2.5 elemental constituents and sources components indicative of different sources within a large multicentre population based epidemiological study.Cohorts with at least 10 cases per cohort led to ten and eight cohorts from five countries contributing to UADT- and gastric cancer analysis, respectively. Outcome ascertainment was based on cancer registry data or data of comparable quality.We assigned home address exposure to eight elemental constituents (Cu, Fe, K, Ni, S, Si, V and Zn) estimated from Europe-wide exposure models, and five source components identified by absolute principal component analysis (APCA). Cox regression models were run with age as time scale, stratified for sex and cohort and adjusted for relevant individual and neighbourhood level confounders.We observed 1139 UADT and 872 gastric cancer cases during a mean follow-up of 18.3 and 18.5 years, respectively. UADT cancer incidence was associated with all constituents except K in single element analyses. After adjustment for NO2, only Ni and V remained associated with UADT. Residual oil combustion and traffic source components were associated with UADT cancer persisting in the multiple source model. No associations were found for any of the elements or source components and gastric cancer incidence.Our results indicate an association of several PM constituents indicative of different sources with UADT but not gastric cancer incidence with the most robust evidence for traffic and residual oil combustion.

Residues, potential source and ecological risk assessment of polycyclic aromatic hydrocarbons (PAHs) in surface water of the East Liao River, Jilin Province, China

The environmental risks posed by polycyclic aromatic hydrocarbons (PAHs) and the diversity of their anthropogenic origins make them a global issue. Therefore, it is of utmost significance for protecting the aquatic environment and the growth of neighboring populations to identify their possible origins and ecological risk. Here, we detail the contamination profiles of 15 PAHs found in the East Liao River's surface waters in Jilin Province and use the receptor model Absolute Principal Component Analysis - Multiple Linear Regression (APCS-MLR) and diagnostic ratios method to identify the primary potential sources of pollution. Based on the natural hazard risk formation theory (NHRFT), an ecological risk assessment (ERA) model for PAHs in the East Liao River was developed. The method assesses the ecological risk status of PAHs by integrating the risk quotient (RQ) approach and the DPSIRM (driving force, pressure, state, impact, response, management) conceptual framework. Total concentrations in the surface water body were between 396.42 and 624.06 ng/L, with an average of 436.99 ng/L. The source research revealed that coal, biomass, and traffic emission sources are the most likely PAH contributors to the East Liao River. The ERA found that the majority of the sites' locations of the study were at low risk for PAHs in surface water bodies (30.7 % and 32.2 %, respectively), while only a tiny percentage of sites were at high or very high risk (1.8 % and 13.6 %). The study results provide theoretical support for the East Liao River's ecological, environmental protection, and policy formulation.

Contamination levels and source apportionment of potentially toxic elements in size-fractionated road dust of Moscow.

The distributions of potentially toxic elements (PTEs) among PM1, PM1-10, PM10-50, and PM50-1000 fractions of the road dust were studied in the western and eastern parts of Moscow, impacted mainly by the road transport and the industrial sector, respectively. The partitioning of PTEs in road dust can provide more precise information on pollution sources and its further interpretation regarding human health risks. The concentrations of PTEs were analyzed by mass and atomic emission inductively coupled plasma spectrometry. Differences in the results between the western and eastern parts of the city were caused by the dissimilarity between traffic and industrial emissions. The source apportionment of the PTEs was carried out using absolute principal component analysis with multiple linear regressions (PCA/APCS-MLR). The contribution from anthropogenic sources was significant to PM1 and PM1-10 particles. In coarser fractions (PM10-50, PM50-1000), it decreased due to the input with the wind-induced resuspension of soil and rock particles. In the eastern part of the city, the accumulation of PTEs (especially Mo, Sb, Cd, Sn, Bi, Co, and As) is the most active in PM1-10, while in the western part, it is most pronounced in PM1 (especially Pb, Cu, Cr, and W) which is associated with differences in the size of particles coming from traffic and industrial sources. In the eastern part of Moscow, in comparison with the western part, the contribution from industrial sources to the accumulation of PTEs in all particle size fractions was higher by 10-30%. In the western part of Moscow, the finest particles PM1 and PM1-10 demonstrate the trend of rising pollution levels with the increase in road size, while in the eastern part of the city, only coarse particles PM50-1000 show the same trend. In the fractions PM1 and PM1-10 of road dust, a significant contribution was made by anthropogenic sources; however, its role decreased in the coarse fractions-PM10-50 and especially in PM50-1000-due to the influence of roadside soils and their parent material.

A modified receptor model for source apportionment of sediment polycyclic aromatic hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) have become a serious threat to human health and ecological security due to their persistence and high toxicity. Lake sediments are in a relatively closed environment, so PAHs and other pollutants can be preserved for a long time. Accurate analysis of the sources of PAHs in sediments is an important prerequisite for PAH pollution control. However, the existing PAHs source resolution receptor model (the absolute principal component analysis - multilinear regression (APCA-MLR) and positive matrix factorization (PMF)) has many defects, such as great uncertainty in the process of matrix rotation. In this study, we collected sediment samples from Taihu Lake and tested their PAH content, and the existing receptor model was improved. High PAH contents were distributed in Meiliang Bay, Zhushan Bay, Gonghu Bay and areas close to the shore. "High-High" areas were distributed in Meiliang Bay, Gonghu Bay and areas close to the shore. "Low-Low" areas appeared in the central and southern parts of Taihu Lake. The results show that the improved positive matrix factorization partition computing (PMF-PC) model is significantly better than the APCA-MLR and PMF models in terms of both numerical simulation accuracy and the spatial distribution consistency of PAHs. The correlations (R2) between the measured and simulated values of low-molecular-weight PAHs (L-PAHs), high-molecular-weight PAHs (H-PAHs) and PAHs were 0.992, 0.989 and 0.993, respectively. The contributions of biomass sources, coal combustion sources and petroleum sources to PAHs in Taihu Lake sediments reached 16.7%, 31.7% and 51.6%, respectively. Fossil fuel sources were mainly concentrated in areas near the shore, and the contribution was lower in areas far from the shore. Although the algorithm still needs to be improved, the PMF-PC model may become a useful tool for the source apportionment of PAHs in sediments.

Health risk and source assessment of semi-volatile phenols, p-chloroaniline and plasticizers in plastic packaged (sachet) drinking water

The presence of U.S. EPA priority organic contaminants in drinking water poses a dire health risk on consumers. Packaged drinking water such as plastic sachet drinking water has significantly gained market in both developed and developing countries, especially, its dominance in the Ghanaian market. The treatment process, packaging, and storage of the sachet drinking water contribute to the levels of genotoxic semi-volatile phenols, p-chloroaniline, and plasticizers contamination in the drinking water. The study thus sought to investigate the levels of semi-volatile phenols, p-chloroaniline, and plasticizer contaminants in sachet drinking water on the Ghanaian market and the associated health risk of exposure. The study also investigated the possible sources of the contaminants. A total of thirty (30) different brands of sachet water on the Ghanaian market were studied. The samples were extracted in replicates (n = 3) using Solid Phase Extraction (SPE) cartridges and further analysed with GC–MS (SIM mode). The source apportionment was conducted using absolute principal component analysis coupled with multiple, linear regression (APCA-MLR) and automatic linear regression (APCA-MALR) modelling. The mean total levels for the phenols, p-chloroaniline, and plasticizers were between 210.2 and 18,914.9, 11.2 and 18,871.0, and 21.2 and 69,834.1 ng/L respectively. The cumulative non-cancer risk (hazard quotient) and cancer risk upon exposure were computed to range between 2.1 × 10−3 and 1.2 and 1.5 × 10−7 and 1.3 × 10−4 respectively. About 37% of the samples had elevated cancer risk (>10−6) which may contribute to the existing incidence, cause for concern. The five sources found for the contaminants were apportioned as “environmental background (major)”, “water treatment/disinfectant”, “plastic/plasticizers”, “storage and preservation”, and “residual inter-conversion/degradation sources”.

APORTE CUANTITATIVO DE LAS FUENTES DE PM10 Y PM2.5 EN SITIOS URBANOS DEL VALLE DEL MANTARO, PERÚ

Particulate matter (PM 10 and PM 2.5 ) is responsible for serious human health problems. Therefore, this study determines the quantitative contribution of the sources of both particles at main cities of Mantaro Valley, located in central Peru. The obtained data in the monthly monitoring campaign of urban sites of Jauja, Concepcion and Huancayo, from July 2007 to October 2008 are analyzed. A low-volume sampler (Partisol model) was used for monitoring. Elemental chemical composition was obtained by X-ray fluorescence, and principal component analysis with varimax rotation and absolute principal component analysis were applied. Chemical element groupings were contrasted with enrichment factor and hierarchical cluster analysis. The results showed that PM 10 and PM 2.5 were significantly higher in Huancayo (p < 0.05), urban area where the National Air Quality Standards for both particle sizes were exceeded. Natural and anthropogenic source tracers were determined. In total, five emission sources were detected for the urban sites of the Mantaro Valley: soil dust (Al, Ca, Si, Fe, Ti, Mn and K), biomass burning (Cl, Br, K), vehicles (Cu, Zn, Cl, Cr), fuel-oil (Ni) and smelting (Pb, Zn, As and Cu), being soil dust the main source of PM 10 and PM 2.5 .

Application of APCA-MLR receptor model for source apportionment of char and soot in sediments

Black carbon (char and soot) has attracted increasing attention due to its important role in the global carbon cycle, adsorption of pollutants (polycyclic aromatic hydrocarbons (PAHs) and heavy metals), climate effects and threats to human health. However, few studies have included source analysis of black carbon (char and soot). In this study, the levels of char, soot and PAHs in sediments of West Taihu Lake were assessed, and an absolute principal component analysis followed by multiple linear regression (APCA-MLR) receptor model was used to successfully analyze the material sources of char and soot, providing a new perspective and method for exploring the sources of char and soot. The contributions of coal combustion sources to char and soot are 62.0% and 43.2%, respectively, which are significantly higher than those of biomass combustion sources (13.7% and 19.8%). The contributions of oil combustion sources to char and soot are 24.3% and 37.0%, respectively. The contributions of coal, oil and biomass combustion to char and soot have similar spatial distributions: the coal combustion sources and biomass combustion sources are mainly affected by urban development, which is largely distributed in the northwest of the study area, whereas the oil combustion sources are mainly affected by automobile traffic and lake ports, which are mainly distributed in the west of the study area, and these effects decrease with an increase in offshore distance.

Characterisation and source apportionment of atmospheric organic and elemental carbon in an urban–rural fringe area of Taiyuan, China

Environmental contextCarbonaceous aerosols are major components of atmospheric fine-particulate material. We studied the characteristics and sources of carbonaceous aerosols in the urban–rural fringe area of Taiyuan, China, and found that pollutant levels were generally higher than in similar areas of northern China, and that vehicle emissions were the dominant source. The study highlights the importance of source analysis to help control pollution from particulate matter in the ambient air. AbstractThe concentrations of organic carbon (OC) and elemental carbon (EC) in fine particulate matter (PM2.5) were measured in 2017 at an urban–rural fringe area of Taiyuan. The annual average concentrations of PM2.5, OC and EC were 143±56, 13±8 and 10±6μgm−3 respectively, which were higher than those in most northern suburban and rural areas in China. Long-range transport and local resuspended dust caused by strong winds during the spring contributed strongly to PM2.5 mass concentrations. The OC and EC concentrations exhibited strong seasonal variations, with higher values in winter and spring, while poor correlations between OC and EC indicated the complexity of aerosol particle sources in winter and spring. Absolute principal component analysis (APCA) using eight carbon fractions was applied to determine the source contributions of total carbon (TC) in PM2.5. During winter, 61% of TC was attributed to mixed sources from coal combustion, biomass combustion and secondary organic carbon (SOC) formation, 23% to vehicle emissions, and 10% to regional origins. During spring, 57% of TC was attributed to vehicle exhaust, 18% to regional transport and SOC formation, and 13% to biomass burning. Comparative studies of hazy and non-hazy periods revealed the significance of SOC formation during hazy days.

Temporal variations of fine and coarse particulate matter sources in Jeddah, Saudi Arabia

ABSTRACTThis study provides the first comprehensive analysis of the seasonal variations and weekday/weekend differences in fine (aerodynamic diameter <2.5 μm; PM2.5) and coarse (aerodynamic diameter 2.5–10 μm; PM2.5–10) particulate matter mass concentrations, elemental constituents, and potential source origins in Jeddah, Saudi Arabia. Air quality samples were collected over 1 yr, from June 2011 to May 2012 at a frequency of three times per week, and analyzed. The average mass concentrations of PM2.5 (21.9 μg/m3) and PM10 (107.8 μg/m3) during the sampling period exceeded the recommended annual average levels by the World Health Organization (WHO) for PM2.5 (10 μg/m3) and PM10 (20 μg/m3), respectively. Similar to other Middle Eastern locales, PM2.5–10 is the prevailing mass component of atmospheric particulate matter at Jeddah, accounting for approximately 80% of the PM10 mass. Considerations of enrichment factors, absolute principal component analysis (APCA), concentration roses, and backward trajectories identified the following source categories for both PM2.5 and PM2.5–10: (1) soil/road dust, (2) incineration, and (3) traffic; and for PM2.5 only, (4) residual oil burning. Soil/road dust accounted for a major portion of both the PM2.5 (27%) and PM2.5–10 (77%) mass, and the largest source contributor for PM2.5 was from residual oil burning (63%). Temporal variations of PM2.5–10 and PM2.5 were observed, with the elevated concentration levels observed for mass during the spring (due to increased dust storm frequency) and on weekdays (due to increased traffic). The predominant role of windblown soil and road dust in both the PM2.5 and PM2.5–10 masses in this city may have implications regarding the toxicity of these particles versus those in the Western world where most PM health assessments have been made in the past. These results support the need for region-specific epidemiological investigations to be conducted and considered in future PM standard setting.Implications: Temporal variations of fine and coarse PM mass, elemental constituents, and sources were examined in Jeddah, Saudi Arabia, for the first time. The main source of PM2.5–10 is natural windblown soil and road dust, whereas the predominant source of PM2.5 is residual oil burning, generated from the port and oil refinery located west of the air sampler, suggesting that targeted emission controls could significantly improve the air quality in the city. The compositional differences point to a need for health effect studies to be conducted in this region, so as to directly assess the applicability of the existing guidelines to the Middle East air pollution.

Assessment of water quality and source apportionment in a typical urban river in China using multivariate statistical methods

Abstract Water quality in urban rivers is a product of the interactions of human activities and natural processes. To explore water quality characteristics and to assess the impacts of natural and anthropogenic processes on urban river systems, we used multivariate statistical techniques to analyse water quality of a typical urban river in eastern China. Cluster analysis grouped the sites into four clusters which were affected by wastewater treatment plant effluent, untreated domestic sewage, tributaries and shipping, respectively. Cluster analysis provided scientific basis for optimizing the monitoring scheme. Three latent factors obtained from principal component analysis/factor analysis were interpreted as wastewater treatment plant effluent, untreated domestic sewage and surface runoff. Absolute principal component analysis indicated that most of the total dissolved phosphorus, nitrite, total dissolved nitrogen, and total nitrogen, Na, K and Cl resulted from the wastewater treatment plant effluent, most of the ammonia, dissolved organic carbon, sulfate and Mg resulted from the surface runoff. The pollution control measures for nitrogen and phosphorus were proposed based on the source apportionment results. The present study showed that the multivariate statistical methods are effective to identify the main pollution sources, quantify their relative contributions and provide useful water management suggesitions in urban rivers.

Inorganic Chemical Composition of Fine Particulates in Medium-Sized Urban Areas: A Case Study of Brazilian Cities

The aim of this study was to characterize the inorganic chemical composition of fine inhalable atmospheric particulate matter (PM2.5) in medium-sized cities in Brazil. These cities account for a significant proportion of the population and are growing at rates above the national average, thereby demonstrating the importance of carefully analysing the possible impact of such growth on air quality over the coming decades. In 2013 and 2014, this study collected PM2.5 samples from sites in the cities of Londrina and Maringa in two seasons: winter and summer. The mean concentration of PM2.5 ranged from 4.4 µg m–3 and 3.7 µg m–3 during the summer to 10.3 µg m–3 and 8.0 µg m–3 in winter in Londrina and Maringa, respectively. The analysis of the major water-soluble ions, nitrate, sulphate and chloride, showed that they accounted for between 16.5% and 35.1% from the mass of PM2.5, with sulphate providing the greatest contribution in all the campaigns. The nitrate/sulphate ratios ranged from 0.2 and 0.6, which are similar to the figures cited in the literature for other regions of the world. Although the PM2.5 concentrations are much lower than those observed in Asia and in Sao Paulo the participation of ions (%) is very close to that observed in Asian cities and significantly higher than the values recorded in other areas of Brazil, possibly as a result of the increased influence of burning of biomass and waste. The metals Zn, Pb, Cu and Mn found in the samples from all campaigns indicate that, in general, mobile sources are the main contributor to PM2.5. The winter campaigns showed the highest concentrations of black carbon equivalent (BCe). Absolute principal component analysis and enrichment factor analysis indicate the contribution of vehicular emission sources and biomass and waste burning to the inorganic chemical composition of PM2.5.

Molecular Marker Study of Particulate Organic Matter in Southern Ontario Air.

To study the origins of airborne particulate organic matter in southern Ontario, molecular marker concentrations were studied at Hamilton, Simcoe, and York Gateway Tunnel, representing industrial, rural, and heavy traffic sites, respectively. Airborne particulate matter smaller than 10 μm in aerodynamic diameter was collected on quartz filters, and the collected samples were analyzed for total carbons, 5-6 ring PAHs, hopanes, n-alkanes (C20 to C34), and oxygenated aromatic compounds. Results showed that PAH concentrations at all three sites were highly correlated, indicating vehicular emissions as the major source. Meanwhile, in the scatter plots of α,β-hopane and trisnorhopane, concentrations displayed different trends for Hamilton and Simcoe. The slopes of the linear regressions for Hamilton and the tunnel were statistically the same, while the slope for Simcoe was significantly different from those. Comparison with literature values revealed that the trend observed at Simcoe was explained by the influence from coal combustion. We also found that the majority of oxygenated aromatic compounds at both sites were in the similar level, possibly implying secondary products contained in the southern Ontario air. Regardless of some discrepancies, absolute principal component analysis applied to the datasets could reproduce those findings.

A source apportionment of U.S. fine particulate matter air pollution

Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

Water-soluble organic compounds (WSOCMs) in PM2.5 and PM10 at a subtropical site of India

PM2.5 and PM10 samples collected at a suburban site of northeastern part of India have been analysed for particle mass, total carbon (TC), water-soluble total carbon (WSTC), water-soluble organic carbon (WSOC), water-soluble inorganic carbon (WSIC), organic acids (formic, acetic, proponoic and oxalic acids) along with inorganic ions (NO3−, SO42− and NH4−). Most of the PM10 consists of PM2.5 in the present site (ratio 54–74%). WSTC content in PM2.5 and PM10 corresponds to 21% and 16%, respectively, of their total particle masses. Thermo gravimetric analysis showed the presence of humic-like substances (16–22%) in particulate samples. Domestic heating and stagnant atmospheric conditions enhanced the levels of these carbonaceous compounds in PM2.5 and PM10 in winter. Qualitative estimation of various functional groups by Fourier transform infrared (FTIR) analysis indicates the presence of carboxylic, hydroxyl, aliphatic and aromatic hydrocarbons, amines and sulphurous compounds in these aerosols. Absolute principal component analysis applied on the aerosol data resolves four factors. These factors are associated with carbonaceous aerosols released from combustion of coal and wood, secondary inorganic and organic aerosols and water-soluble inorganic fraction

Elemental characterization and source identification of PM2.5 using multivariate analysis at the suburban site of North-East India

Aerosol samples for PM2.5 were collected at a suburban site of India during Jan 2007 to Jan 2008. The sampling site is exposed to different antropic source emissions like vehicular emission, wood burning, coal based industries and other industrial activities. The mass concentrations of PM2.5, major elements (Al, Si, P, S, Na, K, Ca, Ti, V, Cr, Mn, Fe, Te, Co, Ni, Cu, Zn, Cd, Sn, Sb, and Pb) and major ions (Cl−, NO3−, SO42−, and NH4+) were determined for winter and rainy seasons. Their levels were found higher than those of in various European and American cities, however, comparable to those of some Asian cities. Analysis of variance (ANOVA) showed significant seasonal variation for concentrations of PM2.5, NO3−, SO42− and most of the elements. This seasonal variation is due to enhanced heating activities and stagnant climatic conditions in winter and removal of pollutants by wet deposition in the rainy period. Source apportionment was undertaken using enrichment factor (EF), Spearman's correlation and absolute principal component analysis. A five-factor model for explaining the observed PM2.5 levels was found to provide realistic results. Evaluation of element abundance at site indicates different pollution levels. The source identification of this study shows that PM2.5 levels were influenced by not only local and industrial activities but also long range transport. Traffic induced crustal sources (38%); coal combustion (26%), industrial and vehicular emissions (19%), wood burning (9%) and secondary aerosol formation (8%) are the major contributors to PM2.5 levels in the city.

Characterisation and source apportionment of PM10 in an urban background site in Lecce

The analysis reported in this work has been performed to characterise PM10 concentration measured in an urban background site in Lecce (Apulia region, Italy). PM10 concentration and its inorganic chemical composition have been studied using three procedures: a qualitative analysis of the correlation coefficients between the different species and of the crustal enrichment factor; the cluster analysis (CA) and the principal component analysis (PCA). The results of the three procedures are in good agreement. The five groups identified by the CA correspond to the five principal components obtained with the PCA and they reflect the results qualitatively inferred using the two-species correlation coefficients. The CA results helped in putting in evidence a correlation between Ni, V and sulphate that was less evident in the PCA. The relative abundance of V is larger with wind from the N-NW directions where the main industrial sites of the region are located. This suggests the presence of anthropogenic inorganic secondary aerosol generated by a common source of V and SO2 that are likely the industrial releases and the ship emissions. The absolute PCA (APCA) allowed the quantitative apportionment of the five components observed: crustal matter (49.5%), secondary inorganic aerosol (24.1%), marine aerosol (6.3%), traffic (16.5%), and industrial (2.1%). Observed PM10 concentration clearly shows a seasonal pattern, opposite to the one observed in the northern and central Italy, with average PM10 larger in the warm season (spring and summer) with respect to the cold season as a consequence of the increase of crustal matter contribution likely due to the intrusion of African dust. These intrusions are more frequent in the warm season and have an influence on daily PM10 concentrations variable between 6% and 120% in this site. Correlation with meteorological data indicates that the more intense cases of intrusions of African dust happen with wind blowing from the SW direction. Average PM10 concentration decreases of about 23% during precipitation. The decrease is mainly due to the decrease in crustal matter contribution and secondary inorganic aerosol. The sum of the other three sources is almost not changing during precipitation.

Application of absolute principal component analysis to size distribution data: identification of particle origins

Abstract. Absolute principal component analysis can be applied, with suitable modifications, to atmospheric aerosol size distribution measurements. This method quickly and conveniently reduces the dimensionality of a data set. The resulting representation of the data is much simpler, but preserves virtually all the information present in the original measurements. Here we demonstrate how to combine the simplified size distribution data with trace gas measurements and meteorological data to determine the origins of the measured particulate matter using absolute principal component analysis. We have applied the analysis to four different sets of field measurements that were conducted at three sites in southern Ontario. Several common factors were observed at all the sites; these were identified as photochemically produced secondary aerosol particles, regional pollutants (including accumulation mode aerosol particles), and trace gas variations associated with boundary layer dynamics. Each site also exhibited a factor associated specifically with that site: local industrial emissions in Hamilton (urban site), processed nucleation mode particles at Simcoe (polluted rural site), and transported fine particles at Egbert (downwind from Toronto).