Distant source contributions to PM10 profile evaluated by SOM based cluster analysis of air mass trajectory sets

This paper evaluates the effects of long-range transport patterns of air masses to the regional PM profile in a megacity, Istanbul, Turkey. Five-day hourly backward trajectories were obtained by the HYSPLIT model for selected episodic events in 2008. Self Organizing Maps (SOM), a very powerful classification tool, was used to cluster these trajectories. In total, eight cluster groups were obtained. All of the clusters were evaluated with respect to inhalable particulate matter (PM₁₀) concentrations observed in Istanbul for the arrival times of the trajectories. Istanbul is generally under the effect of trajectories in three clusters (1, 2 and 4) (52% of all pre-selected episodic events), which have higher mean concentration values than the mean value of all the samples. These clusters typically make significant PM contributions to Istanbul's air quality. PM loadings of the trajectories in these clusters were attributed to massive anthropogenic activity over all of Europe and southwestern air flow most likely carrying PM₁₀ atmospheric particles originating from the Saharan Desert and other global dust generation regions located in the northern part of Africa.     

Analysis of long-range transport influences on urban PM10 using two-stage atmospheric trajectory clusters

There is evidence that long-range transport of natural and/or anthropogenic particles can have a negative impact on urban air quality. Certain European cities may fail to comply with the currently implemented 24-h PM₁₀ limit value due to the additional impact of remote sources of particles, which are not controllable at local level. For that reason, reliable methodologies identifying long-range transport patterns and quantifying their contribution to urban PM₁₀ levels are required. In this study, a two-stage clustering methodology was developed and applied to back trajectories arriving in three European cities: Athens, Madrid and Birmingham, which experience large, moderate and small numbers of daily PM₁₀ episodes, respectively. The atmospheric trajectories used in this analysis were computed with HYSPLIT model (NOAA) for a 3-year period. The two-stage cluster analysis has the advantage of providing highly disaggregated trajectory clusters, which proved to correspond to significantly different PM₁₀ levels. In the case of Madrid and Birmingham, clusters of trajectories originating from North Africa and continental Europe, respectively, were strongly associated with the highest PM₁₀ levels recorded in selected monitoring stations. In Athens, long-range transport patterns and trans-boundary influences were less evident, which highlighted the more substantial impact of local emission sources. Finally, two simple statistical indexes were proposed for assessing PM₁₀ episodes associated with different clusters of trajectories. This study has established a practical methodology for examining the impact of long-range atmospheric transport on local air quality, without resorting to high resource-demanding source apportionment techniques.     

Fine particle measurements at two background sites in Korea between 1996 and 1997

Five intensive field measurements were carried out at two background sites in Korea; Kosan and Kangwha during spring, fall, and winters of 1996 and 1997 to investigate the characteristics of long-range transport of air pollutants in northeastern Asia. Fine particles (PM_2.5) were collected by low-volume samplers and the concentrations of major ions, organic and elemental carbons, and nitric acid were quantified. The concentrations of anthropogenic species in PM_2.5 measured at both sites were generally higher than those at other background areas, Nagano, Japan and San Nicolas Is., USA due to continental outflow of air pollutants, but lower than those at an urban background site, Qingdao, China. The major components of PM_2.5 were sulfate, organic carbon (OC), and ammonium for Kosan and sulfate, OC, ammonium, and nitrate for Kangwha. The major fractions of sulfate at both sites are non-sea-salts (nss) sulfate. Based on the relationship among major anthropogenic species, analysis of the nss sulfate to total nitrate molar ratios, and backward air parcel trajectories, it was found that fine particles measured at both sites during the measurement periods are mainly coming from China. At Kosan, the concentrations of anthropogenic species were higher when air parcels were coming from southern China than when air parcels were from northern China. At Kangwha, however, the differences of the concentrations were not statistically significant since most air parcels were from northern China and local effects are prominent.     

Chemical characteristics of long-range transport aerosol at background sites in Korea

In this study, background concentration sites of Deokjeok and Gosan, which were deemed suitable for monitoring the impact of long-range transported air pollutants, were selected. An investigation of the source types of pollutants, their locations, and relative quantitative contributions to the particulate concentrations at both sites using appropriate methodologies to make initial estimations was conducted. Episodic measurements of PM_2.5, PM₁₀, and size distribution, along with its ion and carbon components were performed from 2005 to 2007, and a comprehensive analysis of the results was conducted utilizing back trajectory analysis. As for frequency of wind direction, it was quite apparent that the two sites are heavily influenced by air masses originating from the eastern and northern regions of China. For PM_2.5 and PM₁₀, the mass concentrations from north and east China were higher than other cases, originating from the ocean. In the northerly-wind case, meteorological properties for Deokjeok and Gosan and the influence of carbon emissions from northwest Korea resulted in a changing of air mass properties during transport. As was the case with mass concentration, the highest contribution for ionic and carbon components of PM_2.5 and PM₁₀ for both sites appeared for the westerly wind case. A specially high relative contribution, greater than 1.4 times, was apparent in the secondary aerosol case because of a large influence of long-range transported pollutants from east China. Carbon components exhibited different behaviors for the northerly and westerly wind cases compared with secondary aerosol. The major reason for this discrepancy appears to be the carbon emissions from northwest Korea.     

A four-year size-segregated characterization study of particles PM10, PM2.5 and PM1 depending on air mass origin at Melpitz

PM₁₀ measurements were started in November 1992 at Melpitz site. The mean PM₁₀ concentration in 1993 was 38 μg m^?3 in the summer season (May until October) and about 44 μg m^?3 in the winter season (November until April). The mean PM₁₀ level decreased until 1999 and varies now in ranges from 20–34 μg m^?3 to 17–24 μg m^?3 (minimum and maximum mean values for 1999–2008) in winter and summer seasons, respectively. High volume filter samples of particles PM₁₀, PM_2.5 and PM₁ were characterized for mass, water-soluble ions, organic and elemental carbon from 2004 until 2008. The percentage of PM_2.5 in PM₁₀ varies between summer (71.6%) and winter seasons (81.9%). Mean concentrations of PM₁₀, PM_2.5 and PM₁ in Melpitz were 20, 15, and 13 μg m^?3 in 2004, 22, 18, and 13 μg m^?3 in 2005, 24, 19, and 12 μg m^?3 in 2006 and 22, 17, and 12 μg m^?3 in 2007, respectively. In the four winters the rural background concentration PM₁₀ at Melpitz exceeded the daily 50 μg m^?3 limit for Europe on 8, 8, 7 and 6 days, respectively.Findings for a simple two-sector-classification of the samples (May 2004 until April 2008) using 96-h backward trajectories for the identification of source regions are: Air masses were transported most of time (60%) from the western sector and secondly (17%) from the eastern sector. The lowest daily mean mass concentration PM₁₀ were found during western inflow in summer (17 μg m^?3) containing low amounts of sulphate (2.4 μg m^?3), nitrate (1.7 μg m^?3), ammonium (1.1 μg m^?3) and TC (3.7 μg m^?3). In opposite the highest mean mass concentration PM₁₀ was found during eastern inflow in winter (35 μg m^?3) with high amounts of sulphate (6.1 μg m^?3), nitrate (5.4 μg m^?3), ammonium (3.8 μg m^?3) and TC (9.4 μg m^?3). An estimation of secondary formed OC (SOA) shows 0.8–0.9 μg m^?3 for air masses from West and 2.1–2.2 μg m^?3 from East. The seasonal difference can be neglected.The half-hourly measurements of the particle mass concentration PM₁₀ evaluated as mean daily courses using a TEOM^® show low values (14–21 μg m^?3) in summer and winter for air masses transported from West and the highest concentrations (31–38 μg m^?3) in winter for air masses from East.The results demonstrate the influence of meteorological parameters on long-range transport, secondary particle mass formation and re-emission which modify mass concentration and composition of PM₁₀, PM_2.5 and PM₁. Melpitz site is located in the East of Germany faraway from strong local anthropogenic emissions (rural background). Therefore, this site is suitable for investigation of the influence of long-range transport of air pollution in continental air masses from the East with source regions inside and outside of the European Union.     

PM10 concentration levels at an urban and background site in Cyprus: The impact of urban sources and dust storms

Air quality in Cyprus is influenced by both local and transported pollution, including desert dust storms. We examined PM₁₀ concentration data collected in Nicosia (urban representative) from April 1, 1993, through December 11, 2008, and in Ayia Marina (rural background representative) from January 1, 1999, through December 31, 2008. Measurements were conducted using a Tapered Element Oscillating Micro-balance (TEOM). PM₁₀ concentrations, meteorological records, and satellite data were used to identify dust storm days. We investigated long-term trends using a Generalized Additive Model (GAM) after controlling for day of week, month, temperature, wind speed, and relative humidity. In Nicosia, annual PM₁₀ concentrations ranged from 50.4 to 63.8 μg/m³ and exceeded the EU annual standard limit enacted in 2005 of 40 μg/m³ every year. A large, statistically significant impact of urban sources (defined as the difference between urban and background levels) was seen in Nicosia over the period 2000–2008, and was highest during traffic hours, weekdays, cold months, and low wind conditions. Our estimate of the mean (standard error) contribution of urban sources to the daily ambient PM₁₀ was 24.0 (0.4) μg/m³. The study of yearly trends showed that PM₁₀ levels in Nicosia decreased from 59.4 μg/m³ in 1993 to 49.0 μg/m³ in 2008, probably in part as a result of traffic emission control policies in Cyprus. In Ayia Marina, annual concentrations ranged from 27.3 to 35.6 μg/m³, and no obvious time trends were observed. The levels measured at the Cyprus background site are comparable to background concentrations reported in other Eastern Mediterranean countries. Average daily PM₁₀ concentrations during desert dust storms were around 100 μg/m³ since 2000 and much higher in earlier years. Despite the large impact of dust storms and their increasing frequency over time, dust storms were responsible for a small fraction of the exceedances of the daily PM₁₀ limit.

ImplicationsThis paper examines PM₁₀ concentrations in Nicosia, Cyprus, from 1993 to 2008. The decrease in PM₁₀ levels in Nicosia suggests that the implementation of traffic emission control policies in Cyprus has been effective. However, particle levels still exceeded the European Union annual standard, and dust storms were responsible for a small fraction of the daily PM₁₀ limit exceedances. Other natural particles that are not assessed in this study, such as resuspended soil and sea salt, may be responsible in part for the high particle levels.     

Particle Size Distributions and Elemental Composition of Atmospheric Particulate Matter in Southern Italy

Abstract

Three 2-wk seasonal field campaigns were performed in 2003 and 2004 at a sampling site on the southern Tyrrhenian coast of Italy with the aim to investigate the dynamics and characteristics of particle-bound pollutants in the Mediterranean area. Fine (PM_2.5) and coarse particulate matter (PM_10–2.5) size fractions were collected by a manual dichotomous sampler on 37-mm Teflon filters over a 24-hr sampling period. On average, 70% of the total PM₁₀ (PM_2.5 + PM_10–2.5) mass was associated with the coarse fraction and 30% with the fine fraction during the three campaigns. The ambient concentrations of Pb, Ni, Cr, Zn, Mn, V, Cd, Fe, Cu, Ca, and Mg associated with both size fractions were determined by atomic absorption spec-trometry. Ambient concentrations showed differences in their absolute value, ranging from few ng · m^-3 to µg ?m^-3, as well as in their variability within the PM_2.5 and PM_10–2.5 size fractions. PM₁₀ levels were well below the European Union (EU) limit value during the study period with the exception of three events during the first campaign (fall) and five events during the third campaign (spring). Two main sources were identified as the major contributors including mineral dust, transported from North Africa, and sea spray from the Tyrrhenian Sea. Comparing the results with backward trajectories, calculated using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) and Total Ozone Mapping Spectrometer-National Aeronautics and Space Administration (TOMS-NASA) maps, it was observed that in central and eastern Europe, the Tyrrhenian Sea and North Africa were the major emission source regions that affected the temporal variations and daily averages of PM_2.5 and PM_10–2.5 concentrations.     

Air pollution “holiday effect” resulting from the Chinese New Year

Our study was an attempt to conduct a comprehensive and systematical examination of the holiday effect, defined as the difference in air pollutant concentrations between holiday and non-holiday periods. This holiday effect can be applied to other countries with similar national or cultural holidays. Hourly and daily surface measurements of six major air pollutants from thirteen air quality monitoring stations of the Taiwan Environmental Protection Administration during the Chinese New Year (CNY) and non-Chinese New Year (NCNY) periods were used. We documented evidence of a “holiday effect”, where air pollutant concentrations were significantly different between holidays (CNY) and non-holidays (NCNY), in the Taipei metropolitan area over the past thirteen years (1994–2006).The concentrations of NO_x, CO, NMHC, SO₂ and PM₁₀ were lower in the CNY than in the NCNY period, while the variation in the concentration of O₃ was reversed, which was mainly due to the NO titration effect. Similar differences in these six air pollutants between the CNY and NCNY periods were also found in the diurnal cycle and in the interannual variation. For the diurnal cycle, a common traffic-related double-peak variation was observed in the NCNY period, but not in the CNY period. Impacts of dust storms were also observed, especially on SO₂ and PM₁₀ in the CNY period. In the 13-year period of 1994–2006, decreasing trends of NO_x and CO in the NCNY period implied a possible reduction of local emissions. Increasing trends of SO₂ and PM₁₀ in the CNY period, on the other hand, indicated a possible enhancement of long-range transport. These two mechanisms weakened the holiday effect.     

Source Identification and Trends in Concentrations of Gaseous and Fine Particulate Principal Species in Seoul,South Korea

Abstract

Ambient measurements were made using two sets of annular denuder system during the four seasons (April 2001 to February 2002) and were then compared with the results during the period of 1996–1997 to estimate the trends and seasonal variations in concentrations of gaseous and fine particulate matter (PM_2.5) principal species. Annual averages of gaseous HNO₃ and NH₃ increased by 11% and 6%, respectively, compared with those of the previous study, whereas HONO and SO₂ decreased by 11% and 136%, respectively. The PM_2.5 concentration decreased by ～17%, 35% for SO₄ ^2?, and 29% for NH₄ ⁺, whereas NO₃ ^? increased by 21%. Organic carbon (OC) and elemental carbon (EC) were 12.8 and 5.98 μg/m^-3, accounting for ～26 and 12% of PM_2.5 concentration, respectively. The species studied accounted for 84% of PM_2.5 concentration, ranging from 76% in winter to 97% in summer.

Potential source contribution function (PSCF) analysis was used to identify possible source areas affecting air pollution levels at a receptor site in Seoul. High possible source areas in concentrations of PM_2.5, NO₃ ^?, SO₄ ^2?, NH₄ ⁺, and K⁺ were coastal cities of Liaoning province (possibly emissions from oil-fired boilers on ocean liners and fishing vessels and industrial emissions), inland areas of Heibei/Shandong provinces (the highest density areas of agricultural production and population) in China, and typical port cities (Mokpo, Yeosu, and Busan) of South Korea. In the PSCF map for OC, high possible source areas were also coastal cities of Liaoning province and inland areas of Heibei/Shandong provinces in China. In contrast, high possible source areas of EC were highlighted in the south of the Yellow Sea, indicating possible emissions from oil-fired boilers on large ships between South Korea and Southeast Asia. In summary, the PSCF results may suggest that air pollution levels in Seoul are affected considerably by long-range transport from external areas, such as the coastal zone in China and other cities in South Korea, as well as Seoul itself.     

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1–10 μm (PM_1–10) sources in a village, B?ezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM_1–10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM₁₀ and PM_1–10 within 2008–2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM_1–10 data across the multiple sites. PMF resolved seven sources of PM_1–10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM_1–10. The conditional probability function (CPF) helped to identified local sources of PM_1–10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).

Implications: This is the first application of PMF to highly time/size resolved PM data in Czech Republic. The coarse aerosol fraction, PM_1–10, was chosen with regard to industrial character of the region, sampling site near the coal strip mine and coal power stations. Contrary to expectation, source apportionment did not show dominance of emissions from the coal strip mine. The results will enable local authorities and state bodies responsible for air quality assessment to focus on sources most responsible for air pollution in this industrial region.

Supplemental Materials:?Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for (1) details of measurement campaigns; (2) CPF for each of the sources contributing to PM_1–10; (3) factors contribution to PM_1–10 resolved by PMF; (4) diurnal pattern of road dust, car brake factor in summer and winter; (5) trajectories during the marine aerosol episode in winter 2010; and (6) temporal temperature, concentration, and wind speed relationships during the summer 2008 campaign and winter 2010 campaign.     

Determination and analysis of PM10 source apportionment during episodes of air pollution in Central Eastern European urban areas: The case of wintertime 2006

Source apportionment of air pollution due to particulate matter with an aerodynamic diameter <10 μm (PM₁₀) was investigated in Central Eastern European urban areas. A combination of four methods was developed to distinguish long-range transport (LRT) and regional transport (RT) from local pollution (LP) sources as well as to discern the involvement of traffic or residential sources in LP. Sources of PM₁₀ events of pollution were determined in January 2006 in representative Polish cities using monitored air quality and meteorological data, backward air mass trajectories, correlation and principal component analysis (PCA). Daily patterns of PM₁₀ levels show that several peak episodes were registered in Poland; January 21–30th being the most polluted days. Air mass back-trajectory analysis shows that all cities were under the influence of LRT from North-eastern origins (Russia–Belarus–Ukraine), most were also under LRT from Southern origin (Slovakia, Czech Republic), and northern cities were under national RT influence. PCA analysis shows that ion-sums of secondary inorganic aerosols account for LRT pollution while arsenic and chromium represents markers of RT (industrial) and LP (residential) sources of PM₁₀, respectively. Determination of several ratios (REG/UB, REG/TRAF, TRAF/UB) calculated between PM₁₀ levels measured at regional background (REG); urban background (UB) and traffic (TRAF) monitoring sites shows that, with ratios REG/UB ≥ 0.57, PM₁₀ episodes in both Szczecin and Warsaw bore a marked RT origin. The lower REG/UB ≤ 0.35 in the Southern cities of Cracow and Zabrze indicates that LP was the main contributor to the observed episodes. Only PM₁₀ episodes in Southern-western Poland (Jelenia Góra) were clearly of LP origin as characterized, by the lowest REG/UB ratio (<0.2). The high TRAF/UB ratios obtained for all cities (close to 1) indicate that there was a great uniformity of PM levels on an urban scale owing to the meteorologically stagnant conditions. A high correlation between PM₁₀, NO₂ and CO confirms that traffic emission represented a common and an important LP source of urban pollution in most Polish cities during January 2006. On the other hand PM₁₀ which is also highly correlated with SO₂ in 4 cities out of 6, indicates that coal combustion through domestic heating or industrial activities was also an important LP source of PM₁₀. Finally, extremely unfavourable meteorological conditions caused by the influence of a Siberian high-pressure system were found to be associated with the occurrence of severe PM₁₀ episodes of pollution.     

Determination of air quality zones in Turkey

In this study, the particulate matter (with an aerodynamic diameter <10 μm; PM₁₀) profile of Turkey with data from the air quality monitoring stations located throughout the country was used. The number of stations (119) was reduced to 55 after a missing data treatment for statistical analyses. First, a classification method was developed based on ongoing national and international (European Commission directives) legislations to categorize air zones into six groups, from a “Very Clear Air Zone” to a “Polluted Air Zone.” Then, a Geographic Information System (GIS)-based interpolation technique and statistical analyses (correlation analysis and factor analysis) were used to generate PM₁₀ pollution profiles of the annual heating time and nonheating time periods. Finally, the coherent air pollution management zones of Turkey, based on air quality criteria and measured data using a GIS-based model supported by statistical analyses, were suggested. Based on the analysis, four hot spots were identified: (i) the eastern part of the Black Sea region; (ii) the northeastern part of inland Anatolia; (iii) the western part of Northeastern Anatolia; and (vi) the eastern part of Turkey. The possible reasons for the elevated PM₁₀ levels are discussed using topographic, climatologic, land use, and energy utilization parameters. Finally, the suggested air zones were compared with the administrative air zones, which were newly developed by the Turkish Ministry of Environment and Forestry, to evaluate the level of agreement between the two.

Implications: The evaluation of air quality profiles of specific regions is important in the development and/or application of an effective air quality management strategy. Factor analysis (FA), together with correlation analysis (CA), provides useful information to classify air pollution management areas over regional networks that have historical time-series air quality data. In this study, which relied on a FA- and CA-based methodology, the coherent air pollution management zones of Turkey after using a GIS-based model were suggested. Policy makers and scientist can use these suggested zones to construct better air quality management strategies.     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.     

Southeastward transport of Asian dust: Source,transport and its contributions to Taiwan

Atmospheric Aluminum measured in northern Taiwan from 2003 to 2006 is used as a dust tracer, from which dust concentrations are derived, and major Asian dust events are determined. The source locations for the major dust events are traced back and identified, and the processes leading to the southeastward transport of Asian dust is investigated. The derived dust concentrations are compared to the local PM₁₀ (particle with size less than 10 μm) concentrations, and the impacts of Asian dust on the air quality of Taiwan are quantified.According to the backward trajectory and dust observation analyses, most of the southeastward transport of major Asian dust events originate from Mongolia and Inner Mongolia in northern China, and only one out of 16 events is generated from western China. Modeling studies and weather analyses of dust events suggest that the southeastward transport of Asian dust is usually generated behind a surface front and transported downwind behind the associated upper level trough. The associated upper level trough is usually deep, in which the northwesterly wind behind the trough favors the southeastward transport of dust to lower latitudes. Dust transported to Taipei generally occur during periods of large-scale subsidence.Asian dust contributes about 15 μg m^?3 of aerosol particles to northern Taiwan during winter monsoon, which accounts for about 24–30% of the PM₁₀ concentrations to the northern Taiwan. The contributions of Asian dust are raised pronouncedly to about 60–70% during major dust events. The impacts of Asian dust on Taiwan's air quality are most substantial in December. The Asian dust impacts decrease in other months, but still remain at around 30% in the late winter to early spring.     

Identification of Sources Contributing to Mid-Atlantic Regional Aerosol

Abstract

Source types or source regions contributing to the concentration of atmospheric fine particles measured at Brigantine National Wildlife Refuge, NJ, were identified using a factor analysis model called Positive Matrix Factorization (PMF). Cluster analysis of backward air trajectories on days of high- and low-factor concentrations was used to link factors to potential source regions. Brigantine is a Class I visibility area with few local sources in the center of the eastern urban corridor and is therefore a good location to study Mid-Atlantic regional aerosol. Sulfate (expressed as ammonium sulfate) was the most abundant species, accounting for 49% of annual average fine mass. Organic compounds (22%; expressed as 1.4 × organic carbon) and ammonium nitrate (10%) were the next abundant species. Some evidence herein suggests that secondary organic aerosol formation is an important contributor to summertime regional aerosol.

Nine factors were identified that contributed to PM_2.5 mass concentrations: coal combustion factors (66%, summer and winter), sea salt factors (9%, fresh and aged), motor vehicle/mixed combustion (8%), diesel/Zn-Pb (6%), incinerator/industrial (5%), oil combustion (4%), and soil (2%). The aged sea salt concentrations were highest in springtime, when the land breeze-sea breeze cycle is strongest. Comparison of backward air trajectories of high- and low-concentration days suggests that Brigantine is surrounded by sources of oil combustion, motor vehicle/mixed combustion, and waste incinerator/industrial emissions that together account for 17% of PM_2.5 mass. The diesel/Zn-Pb factor was associated with sources north and west of Brigantine. Coal combustion factors were associated with coal-fired power plants west and southwest of the site. Particulate carbon was associated not only with oil combustion, motor vehicle/mixed combustion, waste incinerator/industrial, and diesel/Pb-Zn, but also with the coal combustion factors, perhaps through common transport.     

Physicochemical variations in atmospheric aerosols recorded at sea onboard the Atlantic–Mediterranean 2008 Scholar Ship cruise (Part I): Particle mass concentrations,size ratios,and main chemical components

We report on ambient atmospheric aerosols present at sea during the Atlantic–Mediterranean voyage of Oceanic II (The Scholar Ship) in spring 2008. A record was obtained of hourly PM₁₀, PM_2.5, and PM₁ particle size fraction concentrations and 24-h filter samples for chemical analysis which allowed for comparison between levels of crustal particles, sea spray, total carbon, and secondary inorganic aerosols. On-board monitoring was continuous from the equatorial Atlantic to the Straits of Gibraltar, across the Mediterranean to Istanbul, and back via Lisbon to the English Channel. Initially clean air in the open Atlantic registered PM₁₀ levels <10 μg m^?3 but became progressively polluted by increasingly coarse PM as the ship approached land. Away from major port cities, the main sources of atmospheric contamination identified were dust intrusions from North Africa (NAF), smoke plumes from biomass burning in sub-Saharan Africa and Russia, industrial sulphate clouds and other regional pollution sources transported from Europe, sea spray during rough seas, and plumes emanating from islands. Under dry NAF intrusions PM₁₀ daily mean levels averaged 40–60 μg m^?3 (30–40 μg m^?3 PM_2.5; c. 20 μg m^?3 PM₁), peaking briefly to >120 μg m^?3 (hourly mean) when the ship passed through curtains of higher dust concentrations amassed at the frontal edge of the dust cloud. PM₁/PM₁₀ ratios ranged from very low during desert dust intrusions (0.3–0.4) to very high during anthropogenic pollution plume events (0.8–1).     

Sources and processes affecting concentrations of PM10 and PM2.5 particulate matter in Birmingham (U.K.)

Hourly average concentrations of PM₁₀ and PM_2.5 have been measured simultaneously at a site within Birmingham U.K. between October 1994 and October 1995. Comparison of PM₁₀ and NO_x data with two other sites in the same city shows comparable summer and winter mean concentrations and highly significant inter-site correlations for both hourly and daily mean data. Over a four-month period samples were also collected for chemical analysis of sulphate, nitrate, chloride, ammonium and elemental and organic carbon. Analysis of the data indicates a marked difference between summer and winter periods. In the winter months PM_2.5 comprises about 80% of PM₁₀ and is strongly correlated with NO_x indicating the importance of road traffic as a source. In the summer months, coarse particles (PM₁₀−PM_2.5) account for almost 50% of PM₁₀ and the influence of resuspended surface dusts and soils and of secondary particulate matter is evident. The chemical analysis data are also consistent with three sources dominating the PM₁₀ composition: vehicle exhaust emissions, secondary ammonium salts and resuspended surface dusts. Coarse particles from resuspension showed a positive dependence on windspeed, whilst elemental carbon derived from road traffic exhibited a negative dependence.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): Analysis of Short-Term and Episodic Variations in PM2.5 Concentrations Using Hourly Air Monitoring Data

Abstract

One-hour average ambient concentrations of particulate matter (PM) with an aerodynamic diameter <2.5 μm (PM_2.5) were determined in Steubenville, OH, between June 2000 and May 2002 with a tapered element oscillating microbalance (TEOM). Hourly average gaseous copollutant [carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen oxide (NO_x), and ozone (O₃)] concentrations and meteorological conditions also were measured. Although 75% of the 14,682 hourly PM_2.5 concentrations measured during this period were ≤17 μg/m³, concentrations >65 μg/m³ were observed 76 times. On average, PM_2.5 concentrations at Steubenville exhibited a diurnal pattern of higher early morning concentrations and lower afternoon concentrations, similar to the diurnal profiles of CO and NO_x. This pattern was highly variable; however, PM_2.5 concentrations >65 μg/m³ were never observed during the mid-afternoon between 1:00 p.m. and 5:00 p.m. EST. Twenty-two episodes centered on one or more of these elevated concentrations were identified. Five episodes occurred during the months June through August; the maximum PM_2.5 concentration during these episodes was 76.6 μg/m³. Episodes occurring during climatologically cooler months often featured higher peak concentrations (five had maximum concentrations between 95.0 and 139.6 μg/m³), and many exhibited strong covariation between PM_2.5 and CO, NO_x, or SO₂. Case studies suggested that nocturnal surface-based temperature inversions were influential in driving high nighttime concentrations of these species during several cool season episodes, which typically had dramatically lower afternoon concentrations. These findings provide insights that may be useful in the development of PM_2.5 reduction strategies for Steubenville, and suggest that studies assessing possible health effects of PM_2.5 should carefully consider exposure issues related to the intraday timing of PM_2.5 episodes, as well as the potential for toxicological interactions among PM_2.5 and primary gaseous pollutants.     

Effect of local and long-range transport emissions on the elemental composition of PM10–2.5 and PM2.5 in Beirut

The elemental composition of PM_10−2.5 and PM_2.5 were studied in winter, summer, stormy and non-stormy dates during a period extending from February 2004 till January 2005, in a populated area of Beirut. Results of PIXE analysis and enrichment factor (E.F.) calculation, using Si as a reference of crustal material, showed that crustal elements (E.F.<10) like Si, Ca, K, Ti, Mn and Fe were more abundant in PM_10−2.5 while enriched elements (E.F.>10) like S, Cu, Zn and Pb predominated in PM_2.5. In PM_10−2.5, concentrations of crustal elements increased during stormy episodes, all time high Ca concentrations were due to the abundance of calcite and limestone rocks in Lebanon, and increased Cl levels correlated with marine air masses. In PM_2.5, sulfur concentrations were more prominent in the summer due to the enhancement of photochemical reactions. Sources of sulfur were attributed to local, sea-water and long-range transport from Eastern Europe, with the latter being the most predominate. Anthropogenic elements like Cu and Zn were generated from worn brakes and tires in high traffic density area and spikes of Pb were directly linked to a southerly wind originated from Egypt and/or Israel as determined by the air trajectory HYSPLIT model. In brief, elemental variations depended on the regional variability of the transport pattern and the different removal rates of aerosols.