In this paper, two backward air mass trajectory-based models (Potential Source Contribution Function PSCF and Concentration Weighted Trajectory CWT) were combined, aiming to identify sources and ...factors defining the load of PM in the city of Limassol (Cyprus). The study also focused on the determination of atmospheric pathways enriching the aerosol phase of four carcinogenic Polycyclic Aromatic Hydrocarbons (PAHs): Benzo(a)pyrene (BaP), Benzo(a)anthracene (BaA), Benzo(b)fluoranthene (BbF) and Benzo(k)fluoranthene (BkF), in PM10 mass. The analysis was performed on a 0.5°·0.5° resolution grid for the two-year period 2011–2012. During cold seasons, regional airflows triggered the accumulation of locally produced PM2.5, while the impact of dust plumes originated from deserts in NE Africa, Syria and the Middle East, was apparent on PM2.5 and principally on PMCOARSE levels. On the contrary, within warm seasons, weaker dust PMCOARSE contributions were detected in Limassol from areas in Egypt and Libya. Raised particulate-phase PAH concentrations in Limassol were clearly related to air parcels reaching Cyprus via continental areas. The use of outdated technologies for heating and transportation in Turkey and Syria, and fire events in central Turkey, are possible sources of exogenous PAHs throughout cold and warm period respectively. The influence of clean marine air masses dropped the levels of PAH compounds in all seasons.
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•During cold seasons, regional airflows entrapped locally produced PM2.5 in Cyprus.•The impact of dust from NE Africa and the Middle East was apparent on PMCOARSE.•Continental airflows increased particulate-phase PAHs in Limassol.•Clean marine air masses dropped the levels of PAH compounds in all seasons.•Possible PAH intrusions from fire events in Central Turkey were indicated.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The concentrations of particulate mercury (PHg) and other trace elements in PM2.5 and PM10 in the atmosphere were measured at the summit of Mount Tai during the time period of 15 June – 11 August ...2015. The average PHg concentrations were 83.33 ± 119.1 pg/m3 for PM2.5 and 174.92 ± 210.5 pg/m3 for PM10. Average concentrations for other trace elements, including Al, Ca, Fe, K, Mg, Na, Pb, As, Se, Cu, Cd, Cr, V, Mo, Co, Ag, Ba, Mn, Zn and Ni ranged from 0.06 ng/m3 (Ag) to 354.33 ng/m3 (Ca) in PM2.5 and 0.11 ng/m3 (Co) to 592.66 ng/m3 (Ca) in PM10. The average concentrations of PHg were higher than those at other domestic mountain sites and cities in other counties, lower than those at domestic city sites. Other trace elements showed concentrations lower than those at the domestic mountain sites. Due possibly to increased control of emissions and the proportion of new energy, the PHg and trace element concentrations decreased, but the PHg showed concentrations higher than those at the Mountain sites, this showed that the reasons was not only severely affected by anthropogenic emissions, but also associated with other sources. The concentration changed trend of the main trace elements indicated that PHg, trace elements and particle matters present positive correlation and fine particulate matter has a greater surface area which was conductive to adsorption of Hg and trace elements to particles. On June 19, June 27 and July 6, according to the peak of mercury and trace elements, we can predict the potential sources of these three days. The results of principal component analysis (PCA) suggested that, crustal dust, coal combustion, and vehicle emissions were the main emission sources of PHg and other trace elements in Mount Tai. The 24-h backward trajectories and potential source contribution function (PSCF) analysis revealed that air masses arriving at Mount Tai were mainly affected by Shandong province. Mount Tai was subjected to five main airflow trajectories. Clusters 1, 2, 3, and 5 represented four pathways for local and regional sources and cluster 4 originated long-distance transportation. Central Shandong was the main source regions of PHg, Pb, Se, As, Cu and Cd. Southeastern and northwestern Shandong province and northern Jiangsu province were the most polluted source regions of Mn, Zn, and Ni. The crustal elements Fe and Ca had similar distributions of potential source regions, suggested by the highest PSCF values in southeastern Shandong and northern Jiangsu.
•PHg characteristic was first determined in the high coal-fired area near Mount Tai.•The distributions of elements in PM2.5 and PM10 at high altitude were compared.•The transport pathways and potential source regions of risk elements were analyzed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Lead (Pb) in individual aerosol particles was measured using a single particle aerosol mass spectrometer at an urban site in Chengdu, a typical basin city of China, for four one-month periods in ...2016–2017 – one period for each season. The highest mass concentrations of particulate matter (PM) and gaseous species (CO, NO, NO2, and SO2) were observed in winter. Cluster analysis was applied to Pb-containing particles, and eight major classes were identified based on mass spectral features. The contribution of these classes to the total Pb-containing particles varied seasonally – for example, Pb-nitrate (PbNO3) particles showed a higher contribution in spring and winter (47%), while Pb-sulfate (PbSO4) particles exhibited a higher contribution in summer and autumn (14%–19%). The size range of particles also changed with seasons as a result of different sources and formation mechanisms under different climatic conditions. A weighted potential source contribution function (WPSCF) analysis suggested that the potential source areas of Pb-containing particles were mainly located to the northeast, east, southeast, and south of Chengdu, and their contribution intensity and coverage area significantly varied in the four seasons. Although almost all pollutants decreased during the Spring Festival holiday (SF) period, fireworks caused the most serious PM and SO2 pollution episodes during the whole study period. During the SF period, the contributions of industrial and traffic-related particles (Pb-organic + elemental carbon (PbOE) and PbNO3 particles) decreased, whereas those of Pb-chloride (PbCl), Pb-metal (PbM), and Pb-sulfate + nitrate (PbSN) particles increased due to fireworks. Results from this study may provide valuable information for a deeper understanding of Pb in particles and evaluation its impacts on atmospheric environment and human health.
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•Pb-containing particles were characterized by SPAMS in a basin city of China.•Contribution and size distribution of each particle class varied seasonally.•Potential source areas of Pb-containing particles were identified by WPSCF.•Fireworks caused serious air pollution and changes in particle composition.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Long-range transport (LRT) of air masses in East Asia and their impacts on marine PM2.5 were explored. Situated in the leeward region of East Asia, Taiwan Island marked by its elevated Central ...Mountain Range (CMR) separates air masses into two distinct air currents. This study aims to investigate the transport of PM2.5 from the north to the leeward region. Six transport routes (A-F) were identified and further classified them into three main channels (i.e. East, West, and South Channels) based on their transport routes and potential sources. Green Island (Site GR) and Hengchun Peninsula (Site HC) exhibited similarities in their transport routes, with Central China, North China, and Korean Peninsula being the major source regions of PM2.5, particularly during the Asian Northeastern Monsoons (ANMs). Dongsha Island (Site DS) was influenced by both Central China and coastal regions of East China, indicating Asian continental outflow (ACO) as the major source of PM2.5. The positive matrix factorization (PMF) analysis of PM2.5 resolved that soil dust, sea salts, biomass burning, ship emissions, and secondary aerosols were the major sources. Northerly Channels (i.e. East and West Channels) were primarily influenced by ship emissions and secondary aerosols, while South Channel was dominated by oceanic spray and soil dust. The results of W-PSCF and W-CWT analysis indicated that three remote sites experienced significant contributions from Central China in the highest PM2.5 concentration range (75–100%). In contrast, PM2.5 in the 0–25% and 25–50% ranges primarily originated from the open seas, with ship emissions being the prominent source. It suggested that northern regions with heavy industrialization and urbanization have impacts on high PM2.5 concentrations, while open seas are the main sources of low PM2.5 concentrations.
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•PM2.5 of West Channel had higher than East Channel, lowest levels in South Channel.•The contribution of CBT can be as high as 83.3 % during ANMs.•The PM2.5 chemical fingerprints differed strongly with the transport channels/routes.•The West Channel is most severely affected by ship emissions.•W-PSCF and W-CWT (50–100 %) indicates to a major source from coastal of East China.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
PM2.5 samples were collected daily at the Lin'an regional background station (LA) in Zhejiang, China during 2014–2015 and the major chemical components including organic carbon (OC), elemental carbon ...(EC) and water-soluble inorganic ions (WSII) were determined. Backward trajectory clustering and potential source contribution function (PSCF) were adopted for identifying the transport pathways and potential source regions of PM2.5 at LA. The annual mean concentration was 68.9 ± 28.3 μg m−3, indicating severe pollution in East China. Obvious seasonal variations were found, with highest level in winter and lowest in summer. Carbonaceous aerosols and WSII were the predominant compositions, accounting for 30.7% and 53.5% of PM2.5, respectively. Secondary inorganic ions (SO42−, NO3−, and NH4+) made a total contribution of 45.2% to PM2.5. Heterogeneous formation played a dominant role in SO42− formation and NH4+ formation promoted NO3− formation. Stationary sources played a more important role than mobile sources based on NO3−/SO42− ratio of 0.53. Aerosol environment at LA was ammonium-poor and SO42− was only neutralized sufficiently by NH4+ with the predominant production of (NH4)2SO4 in winter. Four major transport pathways of air masses at LA were found based on trajectory clustering. Air masses from the northwest Gobi areas passing over the heavily polluted regions in North and Central China had the highest levels of PM2.5, followed by the air masses from Central China. PSCF results suggested that surrounding areas in the Yangtze River Delta region were major regional origins of PM2.5 and its major components. Northern region was an important origin for carbonaceous components, and southwestern region was significant for secondary inorganic ions. This study helps understand PM2.5 characteristics, identify potential source regions and effectively control PM2.5 in East China.
•Chemical characteristics of PM2.5 at a background site in China were studied.•Heterogeneous chemistry dominated SO42− formation and NH4+ promoted NO3− formation.•Transport pathways of PM2.5 were identified based on trajectory clustering.•Sources regions of PM2.5 and its components were investigated by PSCF.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
It is important to estimate the effects of the long-range transport of atmospheric pollutants for efficient and effective strategies to control air quality. In this study, the contributions of ...trans-boundary transport to the mean concentrations of SO2, NO2, CO, and PM10 in Seoul, Korea from 2001 to 2014 were estimated based on the conditional potential source contribution function (CPSCF) method. Eastern China was found to be the major source of trans-boundary pollution in Seoul, but moderate sources were also located in northeastern China. The contribution of long-range transport from Japan was negligible. The spatial distributions of the potential source contribution function (PSCF) values of each pollutant showed reasonable consistency with their emission inventory and satellite products. The PSCF values of SO2 and PM10 from eastern China were higher than those of NO2 and CO. The mean concentrations of SO2, NO2, CO, and PM10 in Seoul for the period from 2001 to 2014 were 5.34, 37.0, and 619.1 ppb, and 57.4 4 μg/m3, respectively. The contributions of long-range transport to the mean concentrations of SO2, NO2, CO, and PM10 in Seoul were 0.74, 3.4, and 39.0 ppb, and 12.1 μg/m3, respectively, which are 14%, 9%, 6%, and 21% of the mean concentrations, respectively. The annual mean concentrations of SO2 and NO2 followed statistically significant increasing linear trends (0.5 and 1.6 ppb per decade, respectively), whereas the trends in the annual mean concentrations of CO and PM10 were statistically insignificant. The trends in the ratio of the increased concentrations associated with long-range transport to the annual mean concentrations of the pollutants were statistically insignificant. However, the results indicate that the trans-boundary transport of SO2, NO2, CO, and PM10 from eastern China consistently affected air quality in Seoul over the study period (2001–2014). Regionally, the effects of the long-range transport of pollutants from Beijing and Harbin-Changchun on air quality in Seoul have become more significant over this period.
•The long-range transports of pollutants to Seoul were analyzed from 2001 to 2014.•Long-range transport increase SO2, NO2, CO, PM10 concentration by 14%, 9%, 6%, 21%.•Transports from near Beijing and Harbin are becoming more significant recently.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Measurements of ambient speciated mercury (Hg) concentrations and Hg wet deposition were made at two urban sites (Bronx, NY and Rochester, NY) and one rural site (Potsdam, NY) in New York State in ...2013 and 2014 to: 1) determine the factors influencing Hg wet deposition concentrations, 2) identify the contribution of gaseous oxidized Hg (GOM) and particulate bound Hg (PBM) scavenging to Hg wet deposition concentrations, and 3) identify potential source areas associated with high concentration events. The Bronx had the highest mean gaseous elemental Hg (GEM) and GOM concentrations, Rochester had the highest mean PBM and the lowest GOM concentrations, and Potsdam had the lowest mean GEM and PBM concentrations. The annual volume weighted mean (VWM) Hg concentrations and Hg wet deposition fluxes in the Bronx, Rochester, and Potsdam were significantly different with mean values of 10.3 ± 8.16, 10.2 ± 9.06, and 5.07 ± 1.79 ngL−1 and 8.45 ± 0.64, 6.65 ± 0.21, and 5.25 ± 0.49 μg/m2 year−1, respectively. Hg wet deposition flux and precipitation depth were positively correlated at all three sites as were Hg concentration in precipitation and weekly GOM concentrations at the Bronx and Potsdam sites. Scavenging coefficients (SC) of 680, 630, 850 for GOM and 410, 320, and 410 for PBM at Bronx, Rochester, and Potsdam, respectively, suggest GOM is responsible for most of the scavenged Hg. Measured GOM and PBM concentrations were relatively constant before precipitation events and Hg concentrations in precipitation did not vary significantly during precipitation events implying the scavenging process mainly occurred in clouds. VWM Hg concentrations, monthly accumulated Hg flux, and SCs for GOM and PBM were higher at the urban sites and significantly different for non-snow and snow events. Local sources appeared more important at the rural site while regional sources affected high urban concentrations.
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•Speciated Hg depends on emissions, photochemical processes, and meteorology.•Scavenging of oxidized Hg was higher than particle-bound Hg at all 3 sites.•Similar GOM and PBM values pre and post-precipitation show cloud scavenging prevails.•Regional sources were important for urban Hg; local sources for the rural site.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Fine particle (PM2.5) samples were collected at Jinsha (JSH), a regional background China Atmosphere Watch Network (CAWNET) site in Central China from March 2012 to March 2013. The mass ...concentrations of water-soluble inorganic ions (WSIIs), organic carbon (OC) and elemental carbon (EC) in PM2.5 were measured. The average PM2.5 mass concentration was 48.7 ± 26.9 μg m−3, exceeding the Chinese National Ambient Air Quality Standards (NAAQS) (35 μg m−3), implying that PM2.5 is a pollutant of regional concern in Central China. The average concentrations of total WSIIs, OC and EC were 26.1 ± 18.8, 7.5 ± 3.5 and 0.7 ± 0.5 μg m−3, accounting for 53.5%, 15.1% and 1.5% of the PM2.5 concentrations at JSH, respectively. Clear seasonal variations in PM2.5 and the levels of its main chemical species were observed in the following order: winter > autumn > spring > summer. Backward air trajectory analysis and potential source contribution function (PSCF) analysis implied that the areas north and northeast of JSH contributed significantly to the levels of SO42−, NO3−, NH4+ and OC, while sandstorms originating from Mongolia and traveling across Northwest China may have contributed significantly to the levels of Na+, Ca2+, and Mg2+ in PM2.5 at JSH. Two pollution events, related to regional biomass burning and haze, respectively, were recorded at JSH during the sampling campaign.
•PM2.5 is a pollutant of regional concern in Central China.•Water-soluble inorganic ion, OC and EC in PM2.5 were measured.•Backward air trajectory analysis and PSCF analysis were used to identify potential source.•Two pollution events were recorded during the sampling campaign.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A hybrid source-receptor modeling process was assembled, to apportion and infer source locations of PM10 and PM2.5 in three heavily-impacted urban areas of Greece, during the warm period of 2011, and ...the cold period of 2012. The assembled process involved application of an advanced computational procedure, the so-called Robotic Chemical Mass Balance (RCMB) model. Source locations were inferred using two well-established probability functions: (a) the Conditional Probability Function (CPF), to correlate the output of RCMB with local wind directional data, and (b) the Potential Source Contribution Function (PSCF), to correlate the output of RCMB with 72h air-mass back-trajectories, arriving at the receptor sites, during sampling. Regarding CPF, a higher-level conditional probability function was defined as well, from the common locus of CPF sectors derived for neighboring receptor sites. With respect to PSCF, a non-parametric bootstrapping method was applied to discriminate the statistically significant values. RCMB modeling showed that resuspended dust is actually one of the main barriers for attaining the European Union (EU) limit values in Mediterranean urban agglomerations, where the drier climate favors build-up. The shift in the energy mix of Greece (caused by the economic recession) was also evidenced, since biomass burning was found to contribute more significantly to the sampling sites belonging to the coldest climatic zone, particularly during the cold period. The CPF analysis showed that short-range transport of anthropogenic emissions from urban traffic to urban background sites was very likely to have occurred, within all the examined urban agglomerations. The PSCF analysis confirmed that long-range transport of primary and/or secondary aerosols may indeed be possible, even from distances over 1000km away from study areas.
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•A hybrid source-receptor modeling process was assembled for SA of PM in Greece.•Dust resuspension was found to be a major source of PM.•Contributions from biomass burns corresponded to the shift in the energy mix.•Short-range transport was evidenced for traffic emissions and resuspended dust.•Secondary aerosols were estimated to have a travel distance over 1000km.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP