Variation of PM2.5 concentration in Hangzhou,China

This observational study investigates the variation of PM_2.5 concentration and its ratio against PM₁₀ concentration under different weather systems and pollution types. The study was conducted in Hangzhou on east China's Yangtze River Delta using data collected at seven ambient air quality monitoring stations around the metropolitan area between 2006 and 2008 and using weather information in the same period. Nine predominant weather systems affecting the city were classified through careful analysis of the 11-year surface and upper air weather charts from 1996 to 2006. Each observational day was then assigned to one of the nine weather systems. It was found that the PM_2.5 concentration varied greatly for different weather systems, with the highest PM_2.5 concentration associated with the post-cold-frontal system at 0.091 mg/m³ and the lowest PM_2.5 concentration with the easterlies system at 0.038 mg/m³, although the PM_2.5/PM₁₀ ratio remained consistently above 0.5 for all systems. The post-cold-frontal system typically occurs in autumn and winter while the easterlies system is more a summer phenomenon. Among all types of pollution, the highest PM_2.5 concentration of 0.117 mg/m³ coincided with the large-scale continuous pollution events, suggesting that this type of pollution was more conducive to the formation of secondary particulate matters. The ratio of PM_2.5/PM₁₀ was above 0.5 in non-pollution days and all pollution types but one under the influence of dust storms when the ratio decreased to 0.3 or less. The outcomes of this study could be used to develop a rudimental predictive model of PM_2.5 concentration based on weather system and pollution type.     

Local and long-range transport influences on PM2.5 at a cities-cluster in northern China,during summer 2008

Hourly PM_2.5 concentrations were observed simultaneously at a cities-cluster comprising 10 cities/towns in Hebei province in China from July 1 to 31, 2008. Among the 10 cities/towns, Baoding showed the highest average concentration level (161.57 μg/m³) and Yanjiao exhibited the lowest (99.35 μg/m³). These observed data were also studied using the joint potential source contribution function with 24-h and 72-h backward trajectories, to identify more clearly the local and countrywide-scale long-range transport sources. For the local sources, three important influential areas were found, whereas five important influential areas were defined for long-range transport sources. Spatial characteristics of PM_2.5 were determined by multivariate statistical analyses. Soil dust, coal combustion, and vehicle emissions might be the potential contributors in these areas. The results of a hierarchical cluster analysis for back trajectory endpoints and PM_2.5 concentrations datasets show that the spatial characteristics of PM_2.5 in the cities-cluster were influenced not only by local sources, but also by long-range transport sources. Different cities in the cities-cluster obtained different weighted contributions from local or long-range transport sources. Cangzhou, Shijiazhuang, and Baoding are near the source areas in the south of Hebei province, whereas Zhuozhou, Yangfang, Yanjiao, Xianghe, and Langfang are close to the sources areas near Beijing and Tianjin.     

Particulate pollution in an underground car park in Wuhan,China

Particulate matter (PM) pollution in an underground car park in Wuhan was investigated. Mass concentrations of PM₁₀ and PM_2.5 were obtained using gravimetric method. Selected metal elements, such as Fe, Mn, Zn, Pb, and Cu in PM₁₀ samples, were determined using atomic absorption spectrometer (AAS). Beta attenuation method was applied to observe the hourly variation of PM₁₀ levels. Results show that average PM₁₀ concentrations at the entrance and at the exit were 101.3 μg/m³ and 234.4 μg/m³, respectively, and average PM_2.5 concentrations at the entrance and at the exit were 47.7 μg/m³ and 62.7 μg/m³, respectively. PM pollution was worse at the exit than at the entrance. Hourly PM₁₀ concentration was weakly correlated with traffic flow. Regarding element concentrations, the most enriched element in PM₁₀ samples was Fe. Re-suspension of soil dust at the exit is an important source of PM₁₀.     

Impact of meteorological conditions on a nine-day particulate matter pollution event observed in December 2013, Shanghai,China

A severe particulate matter pollution event occurred in Shanghai from 1 to 9 December 2013. The mean hourly mass concentrations of PM_2.5 and PM₁₀ were 211.9 and 249.0 μg/m³, respectively. Reanalysis data, in situ, and remote-sensing measurements were used to examine the impacts of meteorological conditions on this event. It was found that the synoptic pattern of weak pressure, the reduced planetary boundary layer height, and the passage of two cold fronts were key factors causing the event. Four stages were identified during this event based on the evolution of its PM_2.5 levels and weather conditions. The highest concentration of PM_2.5 (602 μg/m³) was observed in stage 3. High PM_2.5 concentrations were closely associated with a low local ventilation index, with an average of 505 m²/s, as well as with the influx of pollutants from upstream, transported by the cold fronts.     

Aerosol observation in Fengtai area, Beijing

Measurements of aerosol number concentration and particulate matter with diameter less than 10 μm （PM10） mass concentrations of urban background aerosols were performed in Fengtai area, Beijing in 2006. Black carbon （BC） was collected simultaneously from the ground and analyzed to determine the particulate matter components. To satisfy the interest in continuous monitoring of temporal and spatial distribution of aerosols, the relationship between extinction coefficient （visibility） measured by lidar remote sensing and the aerosol number concentration measured from the ground was derived by using statistical method. Vertical particle number concentration profile within the planetary boundary layer could be inversed through the lidar data as well as the statistical relation.     

Characteristics of elemental carbon and organic carbon in PM10 during spring and autumn in Chongqing, China

PM10 （particulate matter with aerodynamic diameter less than 10 μm） samples were collected simultaneously at nine urban sites and one urban background site during two intensive observation campaigns in 2006. Concentrations of elemental carbon （EC） and organic carbon （OC） in PM10 were analyzed using an element analyzer. The characteristics regarding spatial and seasonal distribution patterns of OC and EC concentrations and their contributions to PM10 mass, as well as correlation between OC and EC, were investigated in detail. The average OC and EC concentrations for urban sites were 57.5 ± 20.8 and 8.3 ± 3.9 μg/m^3, respectively, both being around three times higher than those for urban background site. As a whole, EC concentrations did not show distinct seasonal variations, though OC concentrations were generally higher in autumn than in spring. For urban sites, total carbonaceous aerosol （TCA） accounted for 33.2% in spring and 35.0% in autumn of PM10 mass. The OC and EC concentrations were found significantly correlated to each other both in spring and in autumn, implying the existence of similar emission sources such as coal combustion. The OC/EC ratios generally exceeded 2.0, indicating the presence of secondary organic carbon （SOC）, whose estimated concentration for urban Chongqing was 26.7 and 39.4μg/m^3, accounting for 48.9 and 61.9% of the total OC observed in the samples, in spring and in autumn, respectively.     

Analysis of the causes of heavy aerosol pollution in Beijing,China: A case study with the WRF-Chem model

The causes and variability of a heavy haze episode in the Beijing region was analyzed. During the episode, the PM_2.5 concentration reached a peak value of 450 μg/kg on January 18, 2013 and rapidly decreased to 100 μg/kg on January 19, 2013, characterizing a large variability in a very short period. This strong variability provides a good opportunity to study the causes of the haze formation. The in situ measurements (including surface meteorological data and vertical structures of the winds, temperature, humidity, and planetary boundary layer (PBL)) together with a chemical/dynamical regional model (WRF-Chem) were used for the analysis. In order to understand the rapid variability of the PM_2.5 concentration in the episode, the correlation between the measured meteorological data (including wind speed, PBL height, relative humidity, etc.) and the measured particle concentration (PM_2.5 concentration) was studied. In addition, two sensitive model experiments were performed to study the effect of individual contribution from local emissions and regional surrounding emissions to the heavy haze formation. The results suggest that there were two major meteorological factors in controlling the variability of the PM_2.5 concentration, namely, surface wind speed and PBL height. During high wind periods, the horizontal transport of aerosol particles played an important role, and the heavy haze was formed when the wind speeds were very weak (less than 1 m/s). Under weak wind conditions, the horizontal transport of aerosol particles was also weak, and the vertical mixing of aerosol particles played an important role. As a result, the PBL height was a major factor in controlling the variability of the PM_2.5 concentration. Under the shallow PBL height, aerosol particles were strongly confined near the surface, producing a high surface PM_2.5 concentration. The sensitivity model study suggests that the local emissions (emissions from the Beijing region only) were the major cause for the heavy haze events. With only local emissions, the calculated peak value of the PM_2.5 concentration was 350 μg/kg, which accounted for 78% of the measured peak value (450 μg/kg). In contrast, without the local emissions, the calculated peak value of the PM_2.5 concentration was only 100 μg/kg, which accounted for 22% of the measured peak value.     

Real-time measurements of PM2.5, PM10–2.5, and BC in an urban street canyon

A continuous dichotomous beta gauge monitor was used to characterize the hourly content of PM_2.5, PM_10–2.5, and Black Carbon (BC) over a 12-month period in an urban street canyon of Hong Kong. Hourly vehicle counts for nine vehicle classes and meteorological data were also recorded. The average weekly cycles of PM_2.5, PM_10–2.5, and BC suggested that all species are related to traffic, with high concentrations on workdays and low concentrations over the weekends. PM_2.5 exhibited two comparable concentrations at 10:00–11:00 (63.4 μg/m³) and 17:00–18:00 (65.0 μg/m³) local time (LT) during workdays, corresponding to the hours when the numbers of diesel-fueled and gasoline-fueled vehicles were at their maximum levels: 3179 and 2907 h⁻¹, respectively. BC is emitted mainly by diesel-fueled vehicles and this showed the highest concentration (31.2 μg/m³) during the midday period (10:00–11:00 LT) on workdays. A poor correlation was found between PM_2.5 concentration and wind speed (R = 0.51, P-value > 0.001). In contrast, the concentration of PM_10–2.5 was found to depend upon wind speed and it increased with obvious statistical significance as wind speed increased (R = 0.98, P-value < 0.0001).     

Composition of carbohydrates,surfactants, major elements and anions in PM2.5 during the 2013 Southeast Asia high pollution episode in Malaysia

Haze episodes have become a major concern in Malaysia over the past few decades and have an increasingly important impact on the country each and every year. During haze episodes from biomass burning in Southeast Asia, particularly from Sumatra, Indonesia, particulate matter PM_2.5 is found to be one of the dangerous sources of airborne pollution and is known to seriously affect human health. This study determines the composition of carbohydrates (as levoglucosan), surfactants, major elements, and anions in PM_2.5 during a 2013 haze episode. PM_2.5 samples were collected from Universiti Kebangsaan Malaysia, Bangi, using a high volume sampler during a seven-day monitoring campaign during the peak of that year’s haze episode. PM_2.5 concentrations ranged between 14.52 and 160.93 μg/m³, exceeding the 2005 WHO air quality guidelines for PM_2.5 (25 μg/m³ for 24-h mean). The patterns for levoglucosan, surfactants, major elements, and anionic compositions were proportional to the PM_2.5 concentrations. Changes in PM_2.5 observed on days 3 and 4 were influenced by a combination of meteorological factors, which substantiate the theory that such factors play a pivotal role in haze episodes.     

An evaluation of mass,number concentration,chemical composition and types of particles in a cafeteria before and after the passage of an antismoking law

This study assessed air quality indicators before and after enactment of the Spanish anti-smoking law. Mass and number concentrations and the chemical composition of particles were evaluated. Microscopy analyses were also conducted. Real time concentrations of PM₁₀, PM_2.5, PM₁ and ultrafine particles were measured under ventilated and non-ventilated conditions and PM₁₀ samples were collected for detailed inorganic and organic chemical characterization. Before enactment of the law in 2010, tobacco smoke produced significant indoor ambient particulate matter pollution, with elevated particulate matter mass concentrations (PM₁₀ and PM₁ concentrations of 122–220 and 48–85 μg/m³, respectively) and ultrafine particle numbers (75,000 and 48,000 cm^–3 under ventilated and non-ventilated conditions, respectively). Typical tobacco smoke tracers including iso- and anteiso-alkanes and elements including La and Ce from the ignition of lighters were abundant. Additionally, several toxic substances derived from tobacco smoke, including Cd (3.1 ng/m³) and benzo[a]pyrene (1.0 ng/m³) were present at concentrations approximately 10 times greater than those measured after enactment of the anti-smoking law. The anti-smoking law significantly reduced exposure to potentially toxic compounds by approximately 90%. This law is expected to have a positive health impact, particularly for people who spend considerable time in affected environments, such as employees.     

Possible effects of climate change of wind on aerosol variation during winter in Shanghai,China

Several data sets were introduced to investigate the possible effects of climate-change-related variation of wind on aerosol concentration during winter in Shanghai, China. These data sets included the daily wind speed, wind direction, visibility, and precipitation from 1956 to 2010, hourly PM₁₀ concentration from 2008 to 2010, and the NCEP/NCAR reanalysis data of global atmospheric circulation from 1956 to 2010. The trend of aerosol concentration and its correlations with wind speed and wind direction in winter were analyzed. Results indicated that there was an increase in the number of haze days in winter of 2.1 days/decade. Aerosol concentration, represented by PM₁₀ in this study, was highly correlated to both wind speed and direction in winter. The PM₁₀ concentration increased as wind speed decreased, reaching maximum values under static wind conditions. The PM₁₀ concentration was relatively lower under easterly winds and higher under westerly winds. The analysis showed that weaker East Asia winter monsoons have resulted in a reduction of wind speed, increase in static wind frequency, and decline in the frequency of northerly winds since the 1980s. Moreover, the rapid expansion of urban construction in Shanghai has changed the underlying surface considerably, which has led to a reduction in wind speed. Finally, a wind factor was defined to estimate the combined effects of wind speed and wind direction on aerosol concentrations in Shanghai. The analysis of this factor indicated that changes in atmosphere circulation and urbanization have had important effects on the number of winter haze days in Shanghai.     

Source apportionment of PM10 in Delhi,India using PCA/APCS,UNMIX and PMF

Source apportionment of particulate matter (PM₁₀) measurements taken in Delhi, India between January 2013 and June 2014 was carried out using two receptor models, principal component analysis with absolute principal component scores (PCA/APCS) and UNMIX. The results were compared with previous estimates generated using the positive matrix factorization (PMF) receptor model to investigate each model’s source-apportioning capability. All models used the PM₁₀ chemical composition (organic carbon (OC), elemental carbon (EC), water soluble inorganic ions (WSIC), and trace elements) for source apportionment. The average PM₁₀ concentration during the study period was 249.7 ± 103.9 μg/m³ (range: 61.4–584.8 μg/m³). The UNMIX model resolved five sources (soil dust (SD), vehicular emissions (VE), secondary aerosols (SA), a mixed source of biomass burning (BB) and sea salt (SS), and industrial emissions (IE)). The PCA/APCS model also resolved five sources, two of which also included mixed sources (SD, VE, SD+SS, (SA+BB+SS) and IE). The PMF analysis differentiated seven individual sources (SD, VE, SA, BB, SS, IE, and fossil fuel combustion (FFC)). All models identified the main sources contributing to PM₁₀ emissions and reconfirmed that VE, SA, BB, and SD were the dominant contributors in Delhi.     

PM2.5 in an industrial district of Zhengzhou,China: Chemical composition and source apportionment

Zhengzhou is a developing city in China, that is heavily polluted by high levels of particulate matter. In this study, fine particulate matter (PM_2.5) was collected and analyzed for their chemical composition (soluble ions, elements, elemental carbon (EC) and organic carbon (OC)) in an industrial district of Zhengzhou in 2010. The average concentrations of PM_2.5 were 181, 122, 186 and 211 μg/m³ for spring, summer, autumn and winter, respectively, with an annual average of 175 μg/m³, far exceeding the PM_2.5 regulation of USA National Air Quality Standards (15 μg/m³). The dominant components of PM_2.5 in Zhengzhou were secondary ions (sulphate and nitrate) and carbon fractions. Soluble ions, total carbon and elements contributed 41%, 13% and 3% of PM_2.5 mass, respectively. Soil dust, secondary aerosol and coal combustion, each contributing about 26%, 24% and 23% of total PM_2.5 mass, were the major sources of PM_2.5, according to the result of positive matrix factorization analysis. A mixed source of biomass burning, oil combustion and incineration contributed 13% of PM_2.5. Fine particulate matter arising from vehicles and industry contributed about 10% and 4% of PM_2.5, respectively.     

Compositional characteristics and toxicological responses of human lung epithelial cells to inhalable particles (PM10) from ten typical biomass fuel combustions

As the primary component of haze, atmospheric inhalable particulate matters (PM₁₀) are highly detrimental to human health. Biomass combustion is one of China's most pivotal sources to aerosols pollution, inducing non-negligible emissions and uncertain risks. PM₁₀ samples directly from 10 representative biomass fuel combustion sources (2 groups covering the reality widely: straws of rice, wheat, corn, corncob, soybean, peanut, rape, sesame; and branches of pine, peach) were collected using the dilution channel sampler and analyzed for chemical compositions and in vitro cytotoxicity to human lung epithelial cell lines A549. The components of PM₁₀ are dominated by organic carbon (OC), followed by water-soluble K⁺ and Cl⁻, and rich in metals Fe, Zn, Cr, and Ni. Generally, PM₁₀ emitted from biomass fuel combustions can weaken the antioxidant capacity of cells, and straws emissions, especially rape and peanut straws, show stronger ability to further induce oxidative stress and inflammatory damage than fuelwoods, owing to the key toxic roles of Cr, Ni, and Co. Therefore, reducing the specific source emissions of PM₁₀ from crop straw combustions rich in heavy metals could be an effective oriented strategy to improve environmental air quality and control aerosols pollution precisely for protecting public health.     

Multiyear analyses of ground-level air contaminants over Paris metropolitan region using real-time observations and air mass backward trajectories

For the years 2008–2013, particles of diameter <10 and 2.5 μm (PM₁₀ and PM_2.5, respectively), NO_x, SO₂, and O₃ concentrations at urban, suburban, rural, and traffic sites in the Paris metropolitan area were analyzed. Strong spatial variability at traffic and rural sites and relatively uniform profiles at urban and suburban sites for PM₁₀, PM_2.5, and O₃ were observed. The O₃ weekend effect was induced by lower NO_x emissions during the weekend, and favored volatile organic compounds (VOCs)-limited atmospheric conditions. In conjunction with low ambient temperature, these conditions could also favor increased formation of secondary particulate nitrates in winter. Winter air pollution events were associated with multiple pollutants, whereas those observed in spring were caused by high PM₁₀ and PM_2.5 levels. Backward trajectory analyses showed the contribution of sources in Western and Central Europe on days with high PM₁₀, PM_2.5, and O₃, and a local/national component for NO_x and SO₂.     

Seasonal variations and sources of mass and chemical composition for PM10 aerosol in Hangzhou,China

Aerosol observation was conducted for four seasons from September 2001 to August 2002 at five sampling sites in Hangzhou, South China, on PM10 mass, 22 elements （Na, Mg, AI, Si, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As. Se, Br, Cd, Ba, and Pb）, 5 major ions （F^-, Cl^ , NO3^-, SO4^2- , and NH4^＋）, and organic and elemental carbon （OC and EC）, showing that PM10 mass ranged from 46.7 to 270.8 μg/m^3, with an annual average of 119.2 μg/m^3. Na, AI, Si, S, K, Ca, and Fe were the most abundant elements in PM10, most of S being in the form of SO4^2- . SO4^2-, NO3^-, and NH4^＋ were the major ions, which contributed to about 20% of the PM10 mass. The mean seasonal concentrations for SO4^2- , averaged over all sites, were found to be 18.0, 18.5, 24,Z and 21.4 μg/m^3, for spring, summer, autumn, and winter, respectively, while the corresponding loadings for NO3^- were 7.2, 4.7, 7.1, and 11.2 μg/m^3, and for NH4^＋ were 6.0, 5.9, 8.2, and 9.3 μg/m^3, in the form mostly of NH4NO3 in spring, autumn, and winter, and mostly of （NH4）2SO4 in summer. The low NO3^-/SO4^2- ratio found indicates coal combustion as the major source throughout the year. The mean annual concentrations of OC and EC in PM10 were found to be 21.4, and 4.1 μg/m^3, respectively. Material balance calculation indicated that fugitive dust, the secondary aerosol, and carbonaceous matter were the most abundant species in PM10 for the four seasons, as is characteristic for cities in South China.     

Observation and analysis of near-surface atmospheric aerosol optical properties in urban Beijing

Year-round measurements of the mass concentration and optical properties of fine aerosols (PM_2.5) from June 2009 to May 2010 at an urban site in Beijing were analyzed. The annual mean values of the PM_2.5 mass concentration, absorption coefficient (Ab), scattering coefficient (Sc) and single scattering albedo (SSA) at 525 nm were 67 ± 66 μg/m³, 64 ± 62 Mm⁻¹, 360 ± 405 Mm⁻¹ and 0.82 ± 0.09, respectively. The bulk mass absorption efficiency and scattering efficiency of the PM_2.5 at 525 nm were 0.78 m²/g and 5.55 m²/g, respectively. The Ab and Sc showed a similar diurnal variation with a maximum at night and a minimum in the afternoon, whereas SSA displayed an opposite diurnal pattern. Significant increases in the Ab and Sc were observed in pollution episodes caused by the accumulation of pollutants from both local and regional sources under unfavorable weather conditions. Aerosol loadings in dust events increased by several times in the spring, which had limited effects on the Ab and Sc due to the low absorption and scattering efficiency of dust particles. The frequency of haze days was the highest in autumn because of the high aerosol absorption and scattering under unfavorable weather conditions. The daily PM_2.5 concentration should be controlled to a level lower than 64 μg/m³ to prevent the occurrence of haze days according to its exponentially decreased relationship with visibility.     

Chemical characteristics and Pb isotopic compositions of PM2.5 in Nanchang,China

In mid-September 2013, PM_2.5 samples were collected at six sites in Nanchang, Jiangxi Province, China, to quantify nine water-soluble ions (Ca²⁺, Mg²⁺, K⁺, Na⁺, NH₄⁺, SO₄²⁻, Cl⁻, F⁻, NO₃⁻), 29 trace elements (Ba, Zn, Pb, Ni, Mo, Cr, Cu, Sr, Sb, Rb, Cd, Bi, Zr, V, Ga, Li, Y, Nb, W, Cs, Tl, Sc, Co, U, Hf, In, Re, Be, and Ta), and to characterize Pb isotopic ratios (²⁰⁷Pb/²⁰⁶Pb, ²⁰⁸Pb/²⁰⁶Pb, and ²⁰⁷Pb/²⁰⁴Pb) for identifying the main source(s) of Pb. The results showed that the average daily PM_2.5 concentration (53.16 ± 24.17) μg/m³ was within the secondary level of the Chinese ambient air quality standard. The combined concentrations of SO₄²⁻, NH₄⁺, and NO₃⁻ to total measured water-soluble ion concentrations in PM_2.5 ranged from 79.40% to 95.18%, indicating that anthropogenic sources were significant. Coal combustion and vehicle emissions were both contributors to PM_2.5 based on the NO₃⁻/SO₄²⁻ ratios. Wushu School experienced the lowest concentrations of PM_2.5 and most trace elements among the six sampling sites. Enrichment factor results showed that Tl, Cr, In, Cu, Zn, Pb, Bi, Ni, Sb, and Cd in PM_2.5 were affected by anthropogenic activities. Cluster analysis suggested that Cd, Sb, Pb, Re, Zn, Bi, Cs, Tl, Ga, and In were possibly related to coal combustion and vehicle exhaust, while Ni, Nb, Cr, and Mo may have originated from metal smelting. Pb isotopic tracing showed that coal dust, cement dust, road dust and construction dust were the major Pb sources in PM_2.5 in Nanchang. Combined, these sources contributed an average of 72.51% of the Pb measured, while vehicle exhaust accounted for 27.49% of Pb based on results from a binary Pb isotope mixed model.     

Effect of chemical composition of PM2.5 on visibility in Guangzhou,China, 2007 spring

The object of this study was to investigate the correlation of visibility with chemical composition of PM2.5 in Guangzhou. In April 2007, 28 PM2.5 samples were collected daily at the monitoring station of the South China Institute of Environmental Sciences （SCIES）, in urban Guangzhou. Water-soluble ionic species （CI^-, NO3^-, SO4^2-, NH4^＋, K^＋, Na^＋, Ca^2＋, and Mg^2＋） and carbonaceous contents （OC and EC） of the PM2.5 samples were determined to characterize their impact on visibility impairment. The results showed that sulfate was the dominant species that affected both light scattering and visibility. The average percentage contributions of the visibility-degrading species to light scattering coefficient were 40% for sulfate, 16% for nitrate, 22% for organics, and 22% for elemental carbon. Because of its foremost effect on visibility, sulfate reduction in PM2.5 would effectively improve the visibility of Guangzhou.     

Chemical characteristics of PM2.5 during haze episodes in the urban of Fuzhou,China

Atmospheric fine particles (PM_2.5) were collected in this study with middle volume samplers in Fuzhou, China, during both normal days and haze days in summer (September 2007) and winter (January 2008). The concentrations, distributions, and sources of polycyclic aromatic hydrocarbons (PAHs), organic carbon (OC), elemental carbon (EC), and water soluble inorganic ions (WSIIs) were determinated. The results showed that the concentrations of PM_2.5, PAHs, OC, EC, and WSIIs were in the orders of haze > normal and winter > summer. The dominant PAHs of PM_2.5 in Fuzhou were Fluo, Pyr, Chr, BbF, BkF, BaP, BghiP, and IcdP, which represented about 80.0% of the total PAHs during different sampling periods. The BaPeq concentrations of ∑PAHs were 0.78, 0.99, 1.22, and 2.43 ng/m³ in summer normal, summer haze, winter normal, and winter haze, respectively. Secondary pollutants (SO₄^2?, NO₃^?, NH₄⁺, and OC) were the major chemical compositions of PM_2.5, accounting for 69.0%, 55.1%, 63.4%, and 64.9% of PM_2.5 mass in summer normal, summer haze, winter normal, and winter haze, respectively. Correspondingly, secondary organic carbon (SOC) in Fuzhou accounted for 20.1%, 48.6%, 24.5%, and 50.5% of OC. The average values of nitrogen oxidation ratio (NOR) and sulfur oxidation ratio (SOR) were higher in haze days (0.08 and 0.27) than in normal days (0.05 and 0.22). Higher OC/EC ratios were also found in haze days (5.0) than in normal days (3.3). Correlation analysis demonstrated that visibility had positive correlations with wind speed, and negative correlations with relative humidity and major air pollutants. Overall, the enrichments of PM_2.5, OC, EC, SO₄^2?, and NO₃^? promoted haze formation. Furthermore, the diagnostic ratios of IcdP/(IcdP + BghiP), IcdP/BghiP, OC/EC, and NO₃^?/SO₄^2? indicated that vehicle exhaust and coal consumption were the main sources of pollutants in Fuzhou.