Source apportionment of PM(10) and PM(2.5) using positive matrix factorization and chemical mass balance in Izmir, Turkey

Air quality challenges in Central Asian urban areas: a PM2.5 source apportionment analysis in Dushanbe, Tajikistan

This work presents the first comprehensive assessment of PM pollution sources in Dushanbe, Tajikistan. A total of 138 PM2.5 samples were collected during 2015-2016 and 2018-2019 and were analyzed through gravimetric, ED-XRF, and multi-wavelength absorption techniques. The results show that PM2.5 concentrations were substantially higher than the European annual limit value and WHO Air Quality Guidelines annual average value, with an average of 90.9 ± 68.5 μg m-3. The PMF application identified eight sources of pollution that influenced PM2.5 concentration levels in the area. Coal burning (21.3%) and biomass burning (22.3%) were the dominant sources during the winter, while vehicular traffic (7.7%) contributed more during the warm season. Power plant emissions (17.5%) showed enhanced contributions during the warm months, likely due to high energy demand. Cement industry emissions (6.9%) exhibited significant contribution during the cold period of 2018-2019, while soil dust (11.3%) and secondary sulphates (11.5%) displayed increased contribution during the warm and cold months, respectively. Finally, waste burning (1.5%) displayed the lowest contribution, with no significant temporal variation. Our results highlight the significant impact of anthropogenic activities, and especially the use of coal burning for energy production (both in power plants and for residential heating), and the significant contribution of biomass burning during both warm and cold seasons.

Source identification and health risk assessment of PM2.5 in urban districts of Hanoi using PCA/APCS and UNMIX

Comparing results obtained by different models with different physical assumptions and constraints for source apportionment is important for better understanding the sources of pollutants. Source apportionment of PM2.5 measured at three sites located in inner urban districts of Hanoi was performed using two receptor models, UNMIX and principal component analysis with absolute principle component score (PCA/APCS). A total of 78 daily samples were collected consecutively during the dry and wet seasons in 2019 and 2020. The average PM2.5 concentration (66.26 µg/m3 ± 29.70 µg/m3 with a range from 23.57 to 169.04 µg/m3) observed in Hanoi metropolitan exceeded the National Ambient Air Quality standard QCVN 05:2013/BTNMT (50 µg/m3). Both UNMIX and PCA/APCS expressed comparable ability to reproduce measured PM2.5 concentrations. Additionally, both models identified similar potential sources of PM2.5 including traffic-related emissions, scrap metal recycling villages, crustal mixed with construction sources, coal combustion mixed with industry, and biomass burning. Both UNMIX and PCA/APCS confirmed that traffic-related emission was the most influential PM2.5 with a high percentage contribution of 59% and 55.97%, respectively. All the HQ and Cr values for both children and adults of toxic elements apportioned by both UNMIX and PCA/APCS in every source were within the acceptable range.

The role of large-scale atmospheric circulations on long-term variations of PM10 concentrations over Turkey

PM10 is widely identified as an important atmospheric pollutant posing a serious threat to human health and environment as well as it influences the climate system. To unearth the mechanism involved in its sources and circulation behavior in environment, this study focuses on the role of large-scale atmospheric circulation on the long-term variability of PM10 over Turkey by applying rotated empirical orthogonal functions (REOF) analysis. As a result of the implementation of REOF to the daily PM10 data for 80 air quality stations throughout the period 2010-2020, first REOF mode (REOF1 44.9% in winter, 43.2% in spring, 39.5% in summer and 31.6% in fall) for all the four seasons indicated the role of local emission sources on the variations of PM10, which show high PM10 values in different geographical regions. The results of the second mode (REOF2, 17.9% in winter, 14.0% in spring, 14.0% in summer and 16.3% in fall) indicate the role of large-scale atmospheric circulations on the values of PM10. From the REOF2 analysis and extracted synoptic composite maps, the strength of southerly winds and the presence of southwesterly winds at low levels are very important in transporting of dust pollutants from the Arabian Peninsula and Northern Africa, respectively, to the eastern (EAR) and southeastern (SEAR) regions of Turkey during winter. In spring, sand particles in the interior terrestrial part of the country are carried to the northern regions by the effect of large-scale southerly winds, which cause above-normal PM10 concentrations in the Black Sea region of Turkey. In summer, dust particles together with warm dry air intrusion to the eastern region of Turkey by strong easterly winds are sourced by Caspian Sea and result in high PM10 values. Our findings emphasize that the long-term variations in air quality over Turkey are affected secondary by the variations in the large-scale atmospheric circulations with primary contributions from the changes in local emission sources.

Traffic pollution tracers in the lymphatic system tissue of children-possible link to chronic tonsillitis development: pilot study

The origin of metal elements in tonsillar tissues of children patients was investigated in order to establish the link between environmental pollution and tonsilitis diagnosis. The children lived either in a polluted, industrial region (Moravian-Silesian Region, North-East Czechia) or a clean, predominantly agricultural region (South Bohemian Region, South-East Czechia). Simultaneously, the distance of the address of the patients to the closest main road was assessed. The elemental content of the present particulate matter in the tonsil samples, coming from indicated tonsillectomies, was analysed using scanning electron microscopy equipped with an X-ray microprobe. No significant association of the elemental composition and the region was found using both bivariate and multivariate methods; however, an association with the distance to the closest main road was found. The study presents a novel assessment of the tonsillar tissues and supports the link between environmental factors (traffic-related particulate pollution) and the onset of chronic, idiopathic diseases in children, which has been debated recently.

Understanding the Sources of Ambient Fine Particulate Matter (PM2.5) in Jeddah, Saudi Arabia

Urban air pollution is rapidly becoming a major environmental problem of public concern in several developing countries of the world. Jeddah, the second-largest city in Saudi Arabia, is subject to high air pollution that has severe implications for the health of the exposed population. Fine particulate matter (PM2.5) samples were collected for 24 h daily, during a 1-year campaign from 2013 to 2014. This study presents a detailed investigation of PM2.5 mass, chemical composition, and sources covering all four seasons of the year. Samples were analyzed for black carbon (BC), trace elements (TEs), and water-soluble ionic species (IS). The chemical compositions were statistically examined, and the temporal and seasonal patterns were characterized using descriptive analysis, correlation matrices, and elemental enrichment factor (EF). Source apportionment and source locations were performed on PM2.5 samples using the positive matrix factorization (PMF) model, elemental enrichment factor, and air-mass back trajectory analysis. The 24-h mean PM2.5 and BC concentrations ranged from 33.9 ± 9.1–58.8 ± 25 µg/m3 and 1.8 ± 0.4–2.4 ± 0.6 µg/m3, respectively. Atmospheric PM2.5 concentrations were well above the 24-h WHO guideline of 15 µg/m3, with overall results showing significant temporal and seasonal variability. EF defined two broad categories of TEs: anthropogenic (Ni, V, Cu, Zn, Cl, Pb, S, Lu, and Br), and earth-crust derived (Al, Si, Mg, K, Ca, Ti, Cr, Mn, Fe, and Sr). The five identified factors resulting from PMF were (1) fossil-fuels/oil combustion (45.3%), (2) vehicular emissions (19.1%), (3) soil/dust resuspension (15.6%), (4) industrial mixed dust (13.5%), and (5) sea-spray (6.5%). This study highlights the importance of focusing control strategies, not only on reducing PM concentration but also on the reduction of components of the PM as well, to effectively protect human health and the environment.

Exposure to particulate matter: a brief review with a focus on cardiovascular effects, children, and research conducted in Turkey

Exposure to environmental particulate matter (PM), outdoor air pollution in particular, has long been associated with adverse health effects. Today, PM has widely been accepted as a systemic toxicant showing adverse effects beyond the lungs. There are numerous studies, from those in vitro to epidemiological ones, suggesting various direct and indirect PM toxicity mechanisms associated with cardiovascular risks, including inflammatory responses, oxidative stress, changes in blood pressure, autonomic regulation of heart rate, suppression of endothelium-dependent vasodilation, thrombogenesis, myocardial infarction, and fibrinolysis. In addition to these and other health risks, considerations about air quality standards should include individual differences, lifestyle, and vulnerable populations such as children. Urban air pollution has been a major environmental issue for Turkey, and this review will also address current situation, research, and measures taken in our country.

Organic Molecular Marker from Regional Biomass Burning—Direct Application to Source Apportionment Model

To reduce fine particulate matter (PM2.5) level, the sources of PM2.5 in terms of the composition thereof needs to be identified. In this study, the experimental burning of ten types of biomass that are typically used in Republic of Korea, collected at the regional area were to investigate the indicated organic speciation and the results obtained therefrom were applied to the chemical mass balance (CMB) model for the study area. As a result, the organic molecular markers for the biomass burning were identified as they were varying according to chemical speciation of woods and herbaceous plants and depending upon the hard- and soft characteristics of specimens. Based on the source profile from biomass burning, major sources of PM2.5 in the study area of the present study appeared as sources of biomass burning, the secondary ions, secondary particulate matters, which is including long-distance transport, wherein the three sources occupied most over 84% of entire PM2.5. In regard to the subject area distinguished into residential area and on roads, the portion of the biomass burning appeared higher in residential area than on roads, whereas the generation from vehicles of gasoline engine and burning of meats in restaurants, etc. appeared higher on roads comparing to the residential area.

Levels and ecological and health risk assessment of PM2.5-bound heavy metals in the northern part of the Persian Gulf

Bushehr, a port along the northern part of the Persian Gulf, has repeatedly encountered dust storms in recent years but there is not been a comprehensive study on the PM_2.5 contents in this region. The present study reports the characteristics and health risks of atmospheric PM_2.5-bound heavy metals (HMs) in Bushehr from December 2016 to September 2017. A total of 46 samples were analyzed, and a high volume air sampler equipped with quartz fiber filters was used for sampling. Inductively coupled plasma optical emission spectroscopy (ICP-OES) was also used for HMs analyses. Risk assessment and hazard index (HI) of these metals were computed by using USEPA's exposure parameters. The results showed that the average 24-h mass concentration of PM_2.5 ranged from 22.09 to 292.45 μg/m³. The results also indicated that 95.65 and 82.61% of the samples were higher than WHO and EPA guidelines for 24-h PM_2.5. Also there was no statistically significant relationship between wind direction and PM_2.5.The average concentration levels of seven measured metals (Cd, Co, Cr, Fe, Ni, Pb, and V) in the PM_2.5 samples were in the range of 6.03 ng/m³ to 1335.94 ng/m³, and the order of their concentration was Fe > Ni > Pb > Cr > Cd > V > Co. Principal component analysis (PCA) showed that PM_2.5-bound heavy metals were categorized in three groups. The ecological risk level of calculated metals was very significant, and the major contribution of the ecological risk was related to Cd. The highest HQ in children and adults was related to Cr, and overall HI in children was higher than adults. Also the RI values of Cr in both groups of children and adults were indicated high risk of developing cancer in human.

Characteristics and Source Apportionment of Metallic Elements in PM2.5 at Urban and Suburban Sites in Beijing: Implication of Emission Reduction

To gain insights into the impacts of emission reduction measures on the characteristics and sources of trace elements during the 2014 Asia-Pacific Economic Cooperation (APEC) summit, PM2.5 samples were simultaneously collected from an urban site and a suburban site in Beijing from September 15th to November 12th, and fifteen metallic elements were analyzed, including five crustal elements (Mg, Al, K, Ca and Fe), nine trace metals (V, Cr, Mn, Co, Cu, Zn, Ag, Cd and Pb) and As. Most of the trace metals (V, Cr, Mn, As, Cd and Pb) decreased more than 40% due to the emission regulations during APEC, while the crustal elements decreased considerably (4–45%). Relative to the daytime, trace metals increased during the nighttime at both sites before the APEC summit, but no significant difference was observed during the APEC summit, suggesting suppressed emissions from anthropogenic activities. Five sources (dust, traffic exhaust, industrial sources, coal and oil combustion and biomass burning) were resolved using positive matrix factorization (PMF), which were collectively decreased by 30.7% at the urban site and 14.4% at the suburban site during the APEC summit. Coal and oil combustion regulations were the most effective for reducing the trace elements concentrations (urban site: 63.1%; suburban site: 52.0%), followed by measures to reduce traffic exhaust (52.8%) at the urban site and measures to reduce biomass burning (37.7%) at the suburban site. Our results signify that future control efforts of metallic elements in megacities like Beijing should prioritize coal and oil combustion, as well as traffic emissions.

Ambient air quality in the holy city of Makkah: A source apportionment with elemental enrichment factors (EFs) and factor analysis (PMF)

Air pollution remains a major global public health and environmental issue. We assessed the levels of PM_2.5 and delineated the major sources in Makkah, Saudi Arabia. Fine particulate matter (PM_2.5) sampling was performed from February 26, 2014-January 27, 2015 in four cycles/seasons. Samples were analyzed for black carbon (BC) and trace elements (TEs). PM_2.5 source apportionment was performed by computing enrichment factors (EFs) and positive matrix factorization (PMF). Backward-in time trajectories were used to assess the long-range transport. Significant seasonal variations in PM_2.5 were observed, Spring: 113 ± 67.1, Summer: 88.3 ± 36.4, Fall: 67.8 ± 24, and Winter: 67.6 ± 36.9 μg m^-3. The 24-h PM_2.5 exceeded the WHO (25 μg m^-3) and Saudi Arabia's (35 μg m^-3) guidelines, with an air quality index (AQI) of "unhealthy to hazardous" to human health. Most delta-C computations were below zero, indicating minor contributions from bio-mass burning. TEs were primarily Si, Ca, Fe, Al, S, K and Mg, suggesting major contributions from soil (Si, Ca, Fe, Al, Mg), and industrial and vehicular emissions (S, Ca, Al, Fe, K). EF defined two broad categories of TEs as: anthropogenic (Cu, Zn, Eu, Cl, Pb, S, Br and Lu), and earth-crust derived (Al, Si, Na, Mg, Rb, K, Zr, Ti, Fe, Mn, Sr, Y, Cr, Ga, Ca, Ni and Ce). Notably, all the anthropogenic TEs can be linked to industrial and vehicular emissions. PMF analysis defined four major sources as: vehicular emissions, 30.1%; industrial-mixed dust, 28.9%; soil/earth-crust, 24.7%; and fossil-fuels/oil combustion, 16.3%. Plots of wind trajectories indicated wind direction and regional transport as major influences on air pollution levels in Makkah. In collusion, anthropogenic emissions contributed >75% of the observed air pollution in Makkah. Developing strategies for reducing anthropogenic emissions are paramount to controlling particulate air pollution in this region.

Using an innovative flag element ratio approach to tracking potential sources of heavy metals on urban road surfaces

Heavy metals deposited on urban road surfaces can be washed-off by stormwater runoff, undermining stormwater reuse safety due to their high toxicity to ecological and human health. Heavy metals on urban road surfaces come from diverse sources and tracking these sources is essential to effectively manage stormwater and hence its reuse safety. This research study developed an innovative approach to tracking sources of heavy metals using data collected in Shenzhen, China. This approach developed was based on a "flag element ratio" theory, where each source generally corresponds to a specific ratio of targeted pollutants to the flag element. It is noted that Cr, Cu, Pb, Ni, and Zn on urban roads were 19.05 mg/kg to 152.01 mg/kg, 25.66 mg/kg to 310.75 mg/kg, 15.61 mg/kg to 220.35 mg/kg, 10.65 mg/kg to 100.28 mg/kg, and 138.14 mg/kg to 1047.05 mg/kg, respectively. Gasoline emission was the main source for Cr, Ni and Pb, while braking wear and tyre wear were the major sources of Cu and Zn, respectively. Furthermore, the rankings of sources of each heavy metal in terms of their contributions were obtained by using this approach. Vehicle exhaust was found as the main contributor for all the heavy metals on urban road surfaces. This highlighted that vehicle exhaust should be seriously considered in terms of controlling heavy metal pollution on urban road surfaces and hence resulting urban road stormwater runoff.

Chemical characteristics, source apportionment, and regional transport of marine fine particles toward offshore islands near the coastline of northwestern Taiwan Strait

This study aims to investigate the spatiotemporal variation, chemical composition, and source apportionment of marine fine particles (PM_2.5) as well as their regional transport toward the Matsu Islands located near the coastline of northwestern Taiwan Strait. Four offshore island sites located at the Matsu Islands were selected to conduct both regular and intensive sampling of marine PM_2.5. Water-soluble ionic species, metallic elements, and carbonaceous contents were then analyzed to characterize the chemical characteristics of marine PM_2.5. In order to identify the potential sources and their contributions to marine PM_2.5, chemical mass balance (CMB) receptor model was employed along with the backward trajectory simulation to resolve the source apportionment of marine PM_2.5 and to explore their transport routes in different seasons. The results showed that high PM_2.5 concentrations were commonly observed during the northeastern monsoon periods. Additionally, marine PM_2.5 concentration decreased from the west to the east with the highest PM_2.5 at the Nankang Island and the lowest PM_2.5 at the Donyin Island in all seasons, indicating an obvious concentration gradient of PM_2.5 transported from the continental areas to the offshore islands. In terms of chemical characteristics of PM_2.5, the most abundant water-soluble ions of PM_2.5 were secondary inorganic aerosols (SO₄^2-, NO₃^-, and NH₄⁺) which accounted for 55-81% of water-soluble ions and 29-52% of marine PM_2.5. The neutralization ratios of PM_2.5 were always less than unity, indicating that NH₄⁺ cannot solely neutralize nss-SO₄²⁺ and NO₃^- in marine PM_2.5 at the Matsu Islands. Although crustal elements (Al, Ca, Fe, K, and Mg) dominated the metallic content of marine PM_2.5, trace anthropogenic metals (Cd, As, Ni, and Cr) increased significantly during the northeastern monsoon periods, particularly in winter. Organic carbons (OCs) were always higher than elemental carbons (ECs), and the mass ratios of OC and EC were generally higher than 2.2 in all seasons, implying that PM_2.5 was likely to be aged particles. During the poor air quality periods, major air mass transport routes were the northern transport and the anti-cyclonic circulation routes. Source apportionment results indicated that fugitive soil dusts and secondary aerosols were the major sources of marine PM_2.5 at the Matsu Islands, while, in winter, biomass burning contributed up to 15% of marine PM_2.5. This study revealed that cross-boundary transport accounted for 66~84% of PM_2.5 at the Matsu Islands, suggesting that marine PM_2.5 at the Matsu Islands has been highly influenced by anthropogenic emissions from neighboring Fuzhou City as well as long-range transport from Northeast Asia.

Source apportionment studies on particulate matter (PM10 and PM2.5) in ambient air of urban Mangalore, India

Particulate matter (PM₁₀ and PM_2.5) samples were collected from six sites in urban Mangalore and the mass concentrations for PM₁₀ and PM_2.5 were measured using gravimetric technique. The measurements were found to exceed the national ambient air quality standards (NAAQS) limits, with the highest concentration of 231.5 μg/m³ for PM₁₀ particles at Town hall and 120.3 μg/m³ for PM_2.5 particles at KMC Attavar. The elemental analysis using inductively coupled plasma optical emission spectrophotometer (ICPOES) revealed twelve different elements (As, Ba, Cd, Cr, Cu, Fe, Mg, Mn, Mo, Ni, Sr and Zn) for PM₁₀ particles and nine different elements (Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Sr and Zn) for PM_2.5 particles. Similarly, ionic composition of these samples measured by ion chromatography (IC) divulged nine different ions (F^-, Cl^-, NO₃^-, PO₄^3-, SO₄^2-, Na⁺, K⁺, Mg²⁺ and Ca²⁺) for PM₁₀ particles and ten different ions (F^-, Cl^-, NO₃^-, PO₄^3-, SO₄^2-, Na⁺, NH₄⁺, K⁺, Mg²⁺ and Ca²⁺) for PM_2.5 particles. The source apportionment study of PM₁₀ and PM_2.5 for urban Mangalore in accordance with these six sample sites using chemical mass balance model (CMBv8.2) revealed nine and twelve predominant contributors for both PM₁₀ and PM_2.5, respectively. The highest contributor of PM₁₀ was found to be paved road dust followed by diesel and gasoline vehicle emissions. Correspondingly, PM_2.5 was found to be contributed mainly from two-wheeler vehicle emissions followed by four-wheeler and heavy vehicle emissions (diesel vehicles). The current study depicts that the PM₁₀ and PM_2.5 in ambient air of Mangalore region has 70% of its contribution from vehicular emissions (both exhaust and non-exhaust).

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

This study provides the first comprehensive analysis of the seasonal variations and weekday/weekend differences in fine (aerodynamic diameter <2.5 μm; PM_2.5) and coarse (aerodynamic diameter 2.5-10 μm; PM_2.5-10) 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 PM_2.5 (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 PM_2.5 (10 μg/m³) and PM₁₀ (20 μg/m³), respectively. Similar to other Middle Eastern locales, PM_2.5-10 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 PM_2.5 and PM_2.5-10: (1) soil/road dust, (2) incineration, and (3) traffic; and for PM_2.5 only, (4) residual oil burning. Soil/road dust accounted for a major portion of both the PM_2.5 (27%) and PM_2.5-10 (77%) mass, and the largest source contributor for PM_2.5 was from residual oil burning (63%). Temporal variations of PM_2.5-10 and PM_2.5 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 PM_2.5 and PM_2.5-10 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 PM_2.5-10 is natural windblown soil and road dust, whereas the predominant source of PM_2.5 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.

Source apportionment for fine particulate matter in a Chinese city using an improved gas-constrained method and comparison with multiple receptor models

PM_2.5 is one of the most studied atmospheric pollutants due to its adverse impacts on human health and welfare and the environment. An improved model (the chemical mass balance gas constraint-Iteration: CMBGC-Iteration) is proposed and applied to identify source categories and estimate source contributions of PM_2.5. The CMBGC-Iteration model uses the ratio of gases to PM as constraints and considers the uncertainties of source profiles and receptor datasets, which is crucial information for source apportionment. To apply this model, samples of PM_2.5 were collected at Tianjin, a megacity in northern China. The ambient PM_2.5 dataset, source information, and gas-to-particle ratios (such as SO₂/PM_2.5, CO/PM_2.5, and NOx/PM_2.5 ratios) were introduced into the CMBGC-Iteration to identify the potential sources and their contributions. Six source categories were identified by this model and the order based on their contributions to PM_2.5 was as follows: secondary sources (30%), crustal dust (25%), vehicle exhaust (16%), coal combustion (13%), SOC (7.6%), and cement dust (0.40%). In addition, the same dataset was also calculated by other receptor models (CMB, CMB-Iteration, CMB-GC, PMF, WALSPMF, and NCAPCA), and the results obtained were compared. Ensemble-average source impacts were calculated based on the seven source apportionment results: contributions of secondary sources (28%), crustal dust (20%), coal combustion (18%), vehicle exhaust (17%), SOC (11%), and cement dust (1.3%). The similar results of CMBGC-Iteration and ensemble method indicated that CMBGC-Iteration can produce relatively appropriate results.

A Global Perspective of Fine Particulate Matter Pollution and Its Health Effects

Fine particulate matter (PM) in the ambient air is implicated in a variety of human health issues throughout the globe. Regulation of fine PM in the atmosphere requires information on the dimension of the problem with respect to variations in concentrations and sources. To understand the current status of fine particles in the atmosphere and their potential harmful health effects in different regions of the world this review article was prepared based on peer-reviewed scientific papers, scientific reports, and database from government organizations published after the year 2000 to evaluate the global scenario of the PM_2.5 (particles <2.5 μm in aerodynamic diameter), its exceedance of national and international standards, sources, mechanism of toxicity, and harmful health effects of PM_2.5 and its components. PM_2.5 levels and exceedances of national and international standards were several times higher in Asian countries, while levels in Europe and USA were mostly well below the respective standards. Vehicular traffic has a significant influence on PM_2.5 levels in urban areas; followed by combustion activities (biomass, industrial, and waste burning) and road dust. In urban atmosphere, fine particles are mostly associated with different health effects with old aged people, pregnant women, and more so children being the most susceptible ones. Fine PM chemical constituents severely effect health due to their carcinogenic or mutagenic nature. Most of the research indicated an exceedance of fine PM level of the standards with a diverse array of health effects based on PM_2.5 chemical constituents. Emission reduction policies with epidemiological studies are needed to understand the benefits of sustainable control measures for fine PM mitigation.

Source apportionment and health risk assessment among specific age groups during haze and non-haze episodes in Kuala Lumpur, Malaysia

This study aims to determine PM_2.5 concentrations and their composition during haze and non-haze episodes in Kuala Lumpur. In order to investigate the origin of the measured air masses, the Numerical Atmospheric-dispersion Modelling Environment (NAME) and Global Fire Assimilation System (GFAS) were applied. Source apportionment of PM_2.5 was determined using Positive Matrix Factorization (PMF). The carcinogenic and non-carcinogenic health risks were estimated using the United State Environmental Protection Agency (USEPA) method. PM_2.5 samples were collected from the centre of the city using a high-volume air sampler (HVS). The results showed that the mean PM_2.5 concentrations collected during pre-haze, haze and post-haze periods were 24.5±12.0μgm^-3, 72.3±38.0μgm^-3 and 14.3±3.58μgm^-3, respectively. The highest concentration of PM_2.5 during haze episode was five times higher than World Health Organisation (WHO) guidelines. Inorganic compositions of PM_2.5, including trace elements and water soluble ions were determined using inductively coupled plasma-mass spectrometry (ICP-MS) and ion chromatography (IC), respectively. The major trace elements identified were K, Al, Ca, Mg and Fe which accounted for approximately 93%, 91% and 92% of the overall metals' portions recorded during pre-haze, haze and post-haze periods, respectively. For water-soluble ions, secondary inorganic aerosols (SO₄^2-, NO₃^- and NH₄⁺) contributed around 12%, 43% and 16% of the overall PM_2.5 mass during pre-haze, haze and post-haze periods, respectively. During haze periods, the predominant source identified using PMF was secondary inorganic aerosol (SIA) and biomass burning where the NAME simulations indicate the importance of fires in Sumatra, Indonesia. The main source during pre-haze and post-haze were mix SIA and road dust as well as mineral dust, respectively. The highest non-carcinogenic health risk during haze episode was estimated among the infant group (HI=1.06) while the highest carcinogenic health risk was estimated among the adult group (2.27×10^-5).

Source apportionment of size-fractionated particles during the 2013 Asian Youth Games and the 2014 Youth Olympic Games in Nanjing, China

In this study, samples of size-fractionated particulate matter were collected continuously using a 9-size interval cascade impactor at an urban site in Nanjing, before, during and after the Asian Youth Games (AYG), from July to September of 2013, and the Youth Olympic Games (YOG), from July to September of 2014. First, elemental concentrations, water-soluble ions including Cl^-, NO₃^-, SO₄^2-, NH₄⁺, K⁺, Na⁺ and Ca²⁺, organic carbon (OC) and elemental carbon (EC) were analysed. Then, the source apportionment of the fine and coarse particulate matter was carried out using the chemical mass balance (CMB) model. The average PM₁₀ concentrations were 90.4±20.0μg/m³ during the 2013 AYG and 70.6±25.3μg/m³ during the 2014 YOG. For PM_2.1, the average concentrations were 50.0±12.8μg/m³ in 2013 and 34.6±17.0μg/m³ in 2014. Investigations showed that the average concentrations of particles declined significantly from 2013 to 2014, and concentrations were at the lowest levels during the events. Results indicated that OC, EC, sulfate and crustal elements have significant monthly and size-based variations. The major components, including crustal elements, water-soluble ions and carbonaceous aerosol accounted for 75.3-91.9% of the total particulate mass concentrations during the sampling periods. Fugitive dust, coal combustion dust, iron dust, construction dust, soil dust, vehicle exhaust, secondary aerosols and sea salt have been classified as the main emissions in Nanjing. The source apportionment results indicate that the emissions from fugitive dust, which was the most abundance emission source during the 2013 AYG, contributed to 23.0% of the total particle mass. However, fugitive dust decreased to 6.2% of the total particle mass during the 2014 YOG. Construction dust (14.7% versus 7.8% for the AYG and the YOG, respectively) and secondary sulfate aerosol (9.3% versus 8.0% for the AYG and the YOG, respectively) showed the same trend as fugitive dust, suggesting that the mitigation measures of controlling particles from the paved roads, construction and industry worked more efficiently during the YOG.

Source identification and apportionment of PM2.5 and PM2.5-10 in iron and steel scrap smelting factory environment using PMF, PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM2.5 and PM2.5-10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m(3) for PM2.5 and 331.36, 190.01, and 184.60 μg/m(3) for PM2.5-10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM2.5-10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM2.5-10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.

Determination of heavy metals in the ambient atmosphere

Heavy metal determination in ambient air is an important task for environmental researchers because of their toxicity to human beings. Some heavy metals (hexavalent chromium (Cr), arsenic (As), cadmium (Cd) and nickel (Ni)) have been listed as carcinogens. Furthermore, heavy metals in the atmosphere can accumulate in various plants and animals and enter humans through the food chain. This article reviews the determination of heavy metals in the atmosphere in different areas of the world since 2006. The results showed that most researchers concentrated on toxic metals, such as Cr, Cd, Ni, As and lead. A few studies used plant materials as bio-monitors for the atmospheric levels of heavy metals. Some researchers found higher concentrations of heavy metals surrounding industrial areas compared with residential and/or commercial areas. Most studies reported the major sources of the particulate matter and heavy metals in the atmosphere to be industrial emissions, vehicular emissions and secondary aerosols.

Inter-annual variability of wintertime PM2.5 chemical composition in Xi'an, China: Evidences of changing source emissions

Chemical characteristics of PM2.5 in Xi'an in wintertime of 2006, 2008, and 2010 were investigated. Markers of OC2, EC1, and NO3(-)/SO4(2-) ratio were calculated to investigate the changes in PM2.5 emission sources over the 5-year period. Positive matrix factorization (PMF) model was used to identify and quantify the main sources of PM2.5 and their contributions. The results showed that coal combustion, motor vehicular emissions, fugitive dust, and secondary inorganic aerosol accounted for more than 80% of PM2.5 mass. The importance of these major sources to the PM2.5 mass varied yearly: coal combustion was the largest contributor (31.2% ± 5.2%), followed by secondary inorganic aerosol (20.9% ± 5.2%) and motor vehicular emissions (19.3% ± 4.8%) in 2006; the order was still coal combustion emissions (27.6% ± 3.4%), secondary inorganic aerosol (23.2% ± 6.9%), and motor vehicular emissions (20.9% ± 4.6%) in 2008; while coal combustion emission further decreased (24.1% ± 3.1%) with fugitive dust (19.4% ± 5.5%) increasing in 2010. The changes in PM2.5 chemical compositions and source contributions can be attributed to the social and economic developments in Xi'an, China, including energy structure adjustment, energy consumption, the expansion of civil vehicles, and the increase of urban construction activities.

Assessment of selected metals in the ambient air PM10 in urban sites of Bangkok (Thailand)

Estimating the atmospheric concentrations of PM10-bounded selected metals in urban air is crucial for evaluating adverse health impacts. In the current study, a combination of measurements and multivariate statistical tools was used to investigate the influence of anthropogenic activities on variations in the contents of 18 metals (i.e., Al, Sc, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Cd, Sb, Ba, La, Ce and Pb) in ambient air. The concentrations of PM10-bounded metals were measured simultaneously at eight air quality observatory sites during a half-year period at heavily trafficked roads and in urban residential zones in Bangkok, Thailand. Although the daily average concentrations of Al, V, Cr, Mn and Fe were almost equivalent to those of other urban cities around the world, the contents of the majority of the selected metals were much lower than the existing ambient air quality guidelines and standard limit values. The sequence of average values of selected metals followed the order of Al > Fe > Zn > Cu > Pb > Mn > Ba > V > Sb > Ni > As > Cr > Cd > Se > Ce > La > Co > Sc. The probability distribution function (PDF) plots showed sharp symmetrical bell-shaped curves in V and Cr, indicating that crustal emissions are the predominant sources of these two elements in PM10. The comparatively low coefficients of divergence (COD) that were found in the majority of samples highlight that site-specific effects are of minor importance. A principal component analysis (PCA) revealed that 37.74, 13.51 and 11.32 % of the total variances represent crustal emissions, vehicular exhausts and the wear and tear of brakes and tires, respectively.

Aerosol particulate matter in the Baltimore metropolitan area: Temporal variation over a six-year period

This study investigates the sources of fine particulate matter (aerodynamic diameter ≤2.5 μm; PM(2.5)) composition for the Baltimore, Maryland, metropolitan area, covering a 6-year period (2008-2013). Data obtained from the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) were used for the identification of eight chemical speciation clusters (factors), which, as a percentage of the average concentration, were identified as secondary sulfate (31.9%), secondary nitrate (14.3%), gasoline (17.4%), diesel (10.1%), soil (4.0%), biomass burning (11%), marine aerosol (4.1%), and industrial processing (7.2%). The results show predominant influence from vehicle emissions transiting major highways I-695 and I-95 located in the vicinity of the sampling site. Strong influence on PM2.5 mass from biomass burning was found in the first 2 years (2008-2009) due to particulate matter remnants from forest fire events in North Carolina and a strong contribution in 2013 that was due mainly to wood burning during winter. Sulfate, nitrate, soil, and marine aerosol fractions registered very low variability over the 6-year period analyzed. In addition, this study shows a significant reduction in particulate matter from industrial origins after a major industrial source in Baltimore shut down. The results obtained from Baltimore were compared with those from the Beltsville, Maryland, sampling station located 25 miles south of Baltimore for 2011 and 2012, where good agreement was found for most of the factors.

IMPLICATIONS

This paper presents the first long-term aerosol speciation analysis in a Mid-Atlantic United States metropolitan area, which is essential for the air quality management agencies in order to revise regulations and reduce human exposure to adverse air quality conditions. The results suggest that although a declining trend in the overall PM2.5 was observed, no significant tendency was observed in the identified sources besides exceptional events such as the impact of wildfires on local air quality and downward contribution from industrial fraction of PM(2.5) after the Steel Mill at Sparrows Point closure in 2012.

Particulate Matter deposition on Quercus ilex leaves in an industrial city of central Italy

A number of studies have focused on urban trees to understand their mitigation capacity of air pollution. In this study particulate matter (PM) deposition on Quercus ilex leaves was quantitatively analyzed in four districts of the City of Terni (Italy) for three periods of the year. Fine (between 0.2 and 2.5 μm) and Large (between 2.5 and 10 μm) PM fractions were analyzed. Mean PM deposition value on Quercus ilex leaves was 20.6 μg cm(-2). Variations in PM deposition correlated with distance to main roads and downwind position relatively to industrial area. Epicuticular waxes were measured and related to accumulated PM. For Fine PM deposited in waxes we observed a higher value (40% of total Fine PM) than Large PM (4% of total Large PM). Results from this study allow to increase our understanding about air pollution interactions with urban vegetation and could be hopefully taken into account when guidelines for local urban green management are realized.

Source apportionment of particulate matter in a large city of southeastern Po Valley (Bologna, Italy)

This study reports the results of an experimental research project carried out in Bologna, a midsize town in central Po valley, with the aim at characterizing local aerosol chemistry and tracking the main source emissions of airborne particulate matter. Chemical speciation based upon ions, trace elements, and carbonaceous matter is discussed on the basis of seasonal variation and enrichment factors. For the first time, source apportionment was achieved at this location using two widely used receptor models (principal component analysis/multi-linear regression analysis (PCA/MLRA) and positive matrix factorization (PMF)). Four main aerosol sources were identified by PCA/MLRA and interpreted as: resuspended particulate and a pseudo-marine factor (winter street management), both related to the coarse fraction, plus mixed combustions and secondary aerosol largely associated to traffic and long-lived species typical of the fine fraction. The PMF model resolved six main aerosol sources, interpreted as: mineral dust, road dust, traffic, secondary aerosol, biomass burning and again a pseudo-marine factor. Source apportionment results from both models are in good agreement providing a 30 and a 33% by weight respectively for PCA-MLRA and PMF for the coarse fraction and 70% (PCA-MLRA) and 67% (PMF) for the fine fraction. The episodic influence of Saharan dust transport on PM10 exceedances in Bologna was identified and discussed in term of meteorological framework, composition, and quantitative contribution.

Particulate matter from Saudi Arabia induces genes involved in inflammation, metabolic syndrome and atherosclerosis

Airborne particulate matter (PM) exposure is a major environmental health concern and is linked to metabolic disorders, such as cardiovascular diseases (CVD) and diabetes, which are on the rise in the Kingdom of Saudi Arabia. This study investigated changes in mouse lung gene expression produced by administration of PM10 collected from Jeddah, Saudi Arabia. FVB/N mice were exposed to 100 μg PM10 or water by aspiration and euthanized 24 h later. The bronchoalveolar lavage fluid (BALF) was collected and analyzed for neutrophil concentration and tumor necrosis factor (TNF)-α and interleukin (IL)-6 levels. RNA was extracted from lungs and whole transcript was analyzed using Affymetrix Mouse Gene 1.0 ST Array. Mice exposed to PM10 displayed an increase in neutrophil concentration and elevated TNF-α and IL-6 levels. Gene expression analysis revealed that mice exposed to PM10 displayed 202 genes that were significantly upregulated and 40 genes that were significantly downregulated. PM10 induced genes involved in inflammation, cholesterol and lipid metabolism, and atherosclerosis. This is the first study to demonstrate that Saudi Arabia PM10 increases in vivo expression of genes located in pathways associated with diseases involving metabolic syndrome and atherosclerosis.

Assessing pollution in Izmir Bay from rivers in western Turkey: heavy metals

Urban rivers having different catchment areas and properties are investigated in order to infer their heavy metal contribution to the Izmir Inner Bay. The concentrations of Cd, Cr, Cu, Ni, Pb, and Zn in the waters and sediments of these rivers were measured and compared with the limit values given in the Sediment Quality Guidelines and Screening Quick Reference Tables (SQuiRTs). Metal concentrations in the sediments were determined to be between 0.5 and 3.5 mg kg(-1), 10 to 221.5 mg kg(-1), 28 to 153.5 mg kg(-1), 13 to 103.5 mg kg(-1), 31.5 to 157 mg kg(-1), and 124 to 1065.5 mg kg(-1) for Cd, Cr, Cu, Ni, Pb, and Zn, respectively. Higher metal concentrations in river waters were observed in rainy seasons, and Cu and Zn were frequently found above the critical limits. The correlations between the concentrations in waters, sediments, and wash off fluxes of the river catchments were statistically investigated and evaluated. Strong correlations between Ni-Cr (r = 0.618, p < 0.01), Ni-Zn (r = 0.578, p < 0.01), and Zn-Pb (r = 0.590, p < 0.01) concentrations in water were found. The metal load entering the inner bay was found to be 28.2 tons per year. The fluxes (mg m(-2) per day) were generally high in large catchments with high annual flows, in regions with high runoff coefficients, and in areas hosting industrial activities. The strong correlations between the heavy metal fluxes suggest that the atmospheric pollution, which influences the whole city, may be the major source of these metals.

A holistic approach combining factor analysis, positive matrix factorization, and chemical mass balance applied to receptor modeling

Rapid urbanization and population growth resulted in severe deterioration of air quality in most of the major cities in India. Therefore, it is essential to ascertain the contribution of various sources of air pollution to enable us to determine effective control policies. The present work focuses on the holistic approach of combining factor analysis (FA), positive matrix factorization (PMF), and chemical mass balance (CMB) for receptor modeling in order to identify the sources and their contributions in air quality studies. Insight from the emission inventory was used to remove subjectivity in source identification. Each approach has its own limitations. Factor analysis can identify qualitatively a minimal set of important factors which can account for the variations in the measured data. This step uses information from emission inventory to qualitatively match source profiles with factor loadings. This signifies the identification of dominant sources through factors. PMF gives source profiles and source contributions from the entire receptor data matrix. The data from FA is applied for rank reduction in PMF. Whenever multiple solutions exist, emission inventory identifies source profiles uniquely, so that they have a physical relevance. CMB identifies the source contributions obtained from FA and PMF. The novel approach proposed here overcomes the limitations of the individual methods in a synergistic way. The adopted methodology is found valid for a synthetic data and also the data of field study.

Integrated chemical species analysis with source-receptor modeling results to characterize the effects of terrain and monsoon on ambient aerosols in a basin

This study integrated estimated oxidation ratio of sulfur (SOR) and oxidation ratio of nitrogen (NOR) with source-receptor modeling results to identify the effects of terrain and monsoons on ambient aerosols in an urban area (north basin) and a rural area (south basin) of the Taichung Basin. The estimated results indicate that the conversion of sulfur mainly occurs in fine particles (PM₂.₅), whereas the conversion of nitrogen occurs in approximately equal quantities of PM₂.₅ and coarse particles (PM₂.₅-₁₀). The results show a direct relationship for PM₂.₅ between the modeling results with SOR and NOR. The high PM₂.₅ SOR, NOR, and secondary aerosol values all occurred in the upwind area during both monsoons; this shows that the photochemical reaction and the terrain effect on the pollutant transmission were significant in the basin. Additionally, the urban heat island effect on the urban area and the valley effect on the rural area were significant. The results show that secondary aerosol in PM₂.₅-₁₀ contributed approximately 10 % during both monsoons, and the difference in the contribution from secondary aerosol between both areas was small. Vehicle exhaust emissions and wind-borne dust were two crucial PM2.5-10 contributors during both monsoons; their average contributions in both areas were higher than 34 and 32 %, respectively.

Concentrations and source apportionment of PM10 and associated major and trace elements in the Rhodes Island, Greece

Ambient concentrations of PM(10) and associated major and trace elements were measured over the cold and the warm season of 2007 at two sites located in the Rhodes Island (Greece), in Eastern Mediterranean, aimed at source apportionment by Chemical Mass Balance (CMB) receptor modeling. Source chemical profiles, necessary in CMB modeling, were obtained for a variety of emission sources that could possibly affect the study area, including sea spray, geological material, soot emissions from the nearby oil-fuelled thermal power plant, and other anthropogenic activities, such as vehicular traffic, residential oil combustion, wood burning, and uncontrolled open-air burning of agricultural biomass and municipal waste. Source apportionment of PM(10) and elemental components was carried out by employing an advanced CMB version, the Robotic Chemical Mass Balance model (RCMB). Vehicular emissions were found to be major PM(10) contributor accounting, on average, for 36.8% and 31.7% during the cold period, and for 40.9% and 39.2% in the warm period at the two sites, respectively. The second largest source of ambient PM(10), with minor seasonal variation, was secondary sulfates (mainly ammonium and calcium sulfates), with total average contribution around 16.5% and 18% at the two sites. Soil dust was also a remarkable source contributing around 22% in the warm period, whereas only around 10% in the cold season. Soot emitted from the thermal power plant was found to be negligible contributor to ambient PM(10) (<1%), however it appeared to appreciably contribute to the ambient V and Ni (11.3% and 5.1%, respectively) at one of the sites during the warm period, when electricity production is intensified. Trajectory analysis did not indicate any transport of Sahara dust; on the contrary, long range transport of soil dust from arid continental regions of Minor Asia and of biomass burning aerosol from the countries surrounding the Black Sea was considered possible.

Source Apportionment and Elemental Composition of PM2.5 and PM10 in Jeddah City, Saudi Arabia

This paper presents the first comprehensive investigation of PM2.5 and PM10 composition and sources in Saudi Arabia. We conducted a multi-week multiple sites sampling campaign in Jeddah between June and September, 2011, and analyzed samples by XRF. The overall mean mass concentration was 28.4 ± 25.4 μg/m³ for PM2.5 and 87.3 ± 47.3 μg/m³ for PM10, with significant temporal and spatial variability. The average ratio of PM2.5/PM10 was 0.33. Chemical composition data were modeled using factor analysis with varimax orthogonal rotation to determine five and four particle source categories contributing significant amount of for PM2.5 and PM10 mass, respectively. In both PM2.5 and PM10 sources were (1) heavy oil combustion characterized by high Ni and V; (2) resuspended soil characterized by high concentrations of Ca, Fe, Al, and Si; and (3) marine aerosol. The two other sources in PM2.5 were (4) Cu/Zn source; (5) traffic source identified by presence of Pb, Br, and Se; while in PM10 it was a mixed industrial source. To estimate the mass contributions of each individual source category, the CAPs mass concentration was regressed against the factor scores. Cumulatively, resuspended soil and oil combustion contributed 77 and 82% mass of PM2.5 and PM10, respectively.

Application of positive matrix factorization in characterization of PM(10) and PM(2.5) emission sources at urban roadside

The 24-h average coarse (PM(10)) and fine (PM(2.5)) fraction of airborne particulate matter (PM) samples were collected for winter, summer and monsoon seasons during November 2008-April 2009 at an busy roadside in Chennai city, India. Results showed that the 24-h average ambient PM(10) and PM(2.5) concentrations were significantly higher in winter and monsoon seasons than in summer season. The 24-h average PM(10) concentration of weekdays was significantly higher (12-30%) than weekends of winter and monsoon seasons. On weekends, the PM(2.5) concentration was found to slightly higher (4-15%) in monsoon and summer seasons. The chemical composition of PM(10) and PM(2.5) masses showed a high concentration in winter followed by monsoon and summer seasons. The U.S.EPA-PMF (positive matrix factorization) version 3 was applied to identify the source contribution of ambient PM(10) and PM(2.5) concentrations at the study area. Results indicated that marine aerosol (40.4% in PM(10) and 21.5% in PM(2.5)) and secondary PM (22.9% in PM(10) and 42.1% in PM(2.5)) were found to be the major source contributors at the study site followed by the motor vehicles (16% in PM(10) and 6% in PM(2.5)), biomass burning (0.7% in PM(10) and 14% in PM(2.5)), tire and brake wear (4.1% in PM(10) and 5.4% in PM(2.5)), soil (3.4% in PM(10) and 4.3% in PM(2.5)) and other sources (12.7% in PM(10) and 6.8% in PM(2.5)).

Effects of basin topography and monsoon conditions on transport and occurrence of atmospheric PCDD/Fs in the Taichung Basin

BACKGROUND, AIM, AND SCOPE

Topographical and meteorological factors, such as monsoons, can drastically affect ambient dioxin levels. In order to better understand these phenomena, four sampling lines (comprising 16 sampling sites) were selected in accordance with the topographical characteristics and the transport paths of the Taichung Basin.

MATERIALS AND METHODS

The ambient air samples were simultaneously collected according to US EPA TO-9A. Seventeen polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) were analyzed by a high-resolution gas chromatograph/high-resolution mass spectrometer.

RESULTS

Field measurements indicated that, during monsoons, PCDD/Fs concentrations varied from 128 to 4,230 fg m(-3). Two locations, the pass between two tablelands and the valley in front of a mountain, had the highest PCDD/Fs concentrations; those concentrations were about two to five times greater than the average concentration. There were 189 analyses of 11 kinds of PCDD/Fs emission sources used to develop emission fingerprints for a CMB8.2 simulation. Chemical mass balance (CMB8.2) model simulation with PCDD/Fs and surface wind field measurements were performed. Results of CMB8.2 modeling indicated that the major source of most sites was secondary copper smelting.

CONCLUSIONS

The CMB8.2 model indicated the effects of hills and river valleys on pollutant transport. Results indicated that secondary copper smelting must be controlled to reduce the ambient concentrations of PCDD/Fs in the Taichung Basin.

The use of olive tree (Olea europaea L.) leaves as a bioindicator for environmental pollution in the Province of Aydın, Turkey

INTRODUCTION

In this study, olive tree leaves, collected from 50 sampling sites throughout the Province of Aydın, Turkey, were used to estimate level of pollution by measuring Al, As, B, Ba, Ca, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, Sr, and Zn concentrations and calculating pollution factor (PF) values.

MATERIALS AND METHODS

After sample preparation, collected leaves were microwave digested, and extracts were analyzed by an inductively coupled plasma-mass spectrometer.

RESULTS AND DISCUSSION

The maximum PF values were ≥10 for a number of elements ranging from 11-13 (Al, As, Cr, Fe, Mn, Ni) to >100 for Cu, Li, and Na. Urban-rural and roadside-nonroadside concentration comparisons showed that some of the elements (As, Cu, and Pb) were at significantly higher levels on urban and/or roadside sampling sites.

SUMMARY AND CONCLUSION

Correlations and factor analysis showed that there may be common sources for some elements, which included several soil types and anthropogenic activities. Based on the results of the statistical source apportionment, possible sources were narrowed down with help of the constructed elemental concentration maps. In conclusion, utilization of olive tree leaves for biomonitoring and assessment of environmental pollution was shown to be possible in the Mediterranean region where they are indigenous and cultivated.

Receptor modeling of PM2.5, PM10 and TSP in different seasons and long-range transport analysis at a coastal site of Tianjin, China

Atmospheric particulate matter (PM(2.5), PM(10) and TSP) were sampled synchronously during three monitoring campaigns from June 2007 to February 2008 at a coastal site in TEDA of Tianjin, China. Chemical compositions including 19 elements, 6 water-solubility ions, organic and elemental carbon were determined. principle components analysis (PCA) and chemical mass balance modeling (CMB) were applied to determine the PM sources and their contributions with the assistance of NSS SO(4)(2)(-), the mass ratios of NO(3)(-) to SO(4)(2)(-) and OC to EC. Air mass backward trajectory model was compared with source apportionment results to evaluate the origin of PM. Results showed that NSS SO(4)(2)(-) values for PM(2.5) were 2147.38, 1701.26 and 239.80 ng/m(3) in summer, autumn and winter, reflecting the influence of sources from local emissions. Most of it was below zero in summer for PM(10) indicating the influence of sea salt. The ratios of NO(3)(-) to SO(4)(2)(-) was 0.19 for PM(2.5), 0.18 for PM(10) and 0.19 for TSP in winter indicating high amounts of coal consumed for heating purpose. Higher OC/EC values (mostly larger than 2.5) demonstrated that secondary organic aerosol was abundant at this site. The major sources were construction activities, road dust, vehicle emissions, marine aerosol, metal manufacturing, secondary sulfate aerosols, soil dust, biomass burning, some pharmaceutics industries and fuel-oil combustion according to PCA. Coal combustion, marine aerosol, vehicular emission and soil dust explained 5-31%, 1-13%, 13-44% and 3-46% for PM(2.5), PM(10) and TSP, respectively. Backward trajectory analysis showed air parcels originating from sea accounted for 39% in summer, while in autumn and winter the air parcels were mainly related to continental origin.

TSP, PM depositions, and trace elements in the vicinity of a cement plant and their source apportionments using chemical mass balance model in Izmir, Turkey

Total suspended particles mass concentrations (TSP) and bulk depositions of particulate matter (PM depositions) were measured around a cement plant located in the multi-impacted area to assess the affect of the plant on the ambient air in the vicinity in Izmir, Turkey. TSP samples were collected five times a month whereas PM depositions were sampled monthly at four sites between August 2003 and January 2004. The concentrations of Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, V, and Zn in TSP and PM depositions (except Cu) were reported. Chemical mass balance (CMB) receptor model with local source profiles was run in order to calculate the source contributions of the PM sources to the concentrations of TSP, PM depositions, and trace elements. Traffic was found to be the major contributor to TSP whereas PM depositions dominantly result from area sources including several stone quarries, concrete plants, lime kilns, and asphalt plants in the region. CMB model results indicate that the cement plant is a significant contributor to TSP, PM depositions, and trace elements, particularly Cd.

Air pollution forecasting in Ankara, Turkey using air pollution index and its relation to assimilative capacity of the atmosphere

Spatial and temporal variations in concentrations of CO, NO, NO(2), SO(2), and PM(10), measured between 1999 and 2000, at traffic-impacted and residential stations in Ankara were investigated. Air quality in residential areas was found to be influenced by traffic activities in the city. Pollutant ratios were proven to be reliable tracers to differentiate between different sources. Air pollution index (API) of the whole city was calculated to evaluate the level of air quality in Ankara. Multiple linear regression model was developed for forecasting API in Ankara. The correlation coefficients were found to be 0.79 and 0.63 for different time periods. The assimilative capacity of Ankara atmosphere was calculated in terms of ventilation coefficient (VC). The relation between API and VC was investigated and found that the air quality in Ankara was determined by meteorology rather than emissions.

Levels, chemical composition and sources of fine aerosol particles (PM1) in an area of the Mediterranean basin

Daily samples of fine aerosol particles (i.e., PM1, aerosol particles with an aerodynamic diameter less than 1.0mum) were collected in Tito Scalo - Southern Italy - from April 2006 to March 2007. Measurements were performed by means of a low-volume gravimetric sampler, and each PM1 sample was analyzed by means of Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) or Atomic Absorption Spectrometry (GFAAS and FAAS) techniques in order to determine its content in fourteen trace elements (Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Ti and Zn). During the period examined, PM1 daily concentrations ranged between 0.3microgm(-3) and 55microgm(-3) with a mean value of 8 microg m(-3), a standard deviation of 7microgm(-3) and a median value of 6microgm(-3). As far as PM1 chemical composition is concerned, the mean values of the trace element concentrations decreased in the following order: Ca>Fe>Al>Na>K>Cr>Mg>Pb>Ni approximately Ti approximately Zn>Cd approximately Cu>Mn. Principal Component Analysis (PCA) allowed the identification of three probable PM1 sources: industrial emissions, traffic and re-suspension of soil dust. Moreover, the results of a procedure applied to study the potential long-range transport contribution to PM1 chemical composition, showed that trace element concentrations do not seem to be affected by air mass origin and path. This was probably due to the strong impact of the local emission sources and the lack of the concentration measurements of some important elements and compounds that could better reveal the long-range transport influence on PM1 measurements at ground level.