Analysis of a high PM10 episode observed at a coastal site nearby Shanghai, China

A high PM₁₀ episode observed at a coastal site nearby Shanghai during 18–19 January 2007 was analyzed in this study. The maximum hourly averaged PM₁₀ concentrations for the 2 days were 0.58 and 0.62 mg/m³, respectively. The meteorological condition during the episode was favorable for air pollution with large-scale stagnation. There was no dispersing effect by high wind, no scavenging function by precipitation, and no diluting process by clean marine air during the episode. The trajectories for 16–19 January all came from the northern region and kept in low levels, and during the episode peak time, from the morning of 18 to the morning of 19 January, trajectories all came from the northern inland areas and had passed over the coastal region of Jiangsu province before arriving at the site. The variation of the air pollution indexes (APIs) in the cities located in the upwind direction of the site during the episode days clearly shows a process of large-scale air pollution from north to south. The liner correlation coefficient for PM₁₀ and SO₂ concentrations is 0.774 during the episode, while for PM₁₀ and CO, it even reaches 0.995, which indicated that the high PM₁₀ was mainly emitted from the coal burning for domestic heating in winter. Therefore, the observed episode was caused by the transport of domestic heating pollutants accumulated in the boundary layer from northern continental areas.     

Differences in the Spatial Distribution and Chemical Composition of PM10 Between the UK and Poland

The Fine Resolution Atmospheric Multi-pollutant Exchange Model was used to calculate the spatial distribution and chemical composition of PM₁₀ concentrations for two geographically remote countries in Europe—the UK and Poland—for the year 2007. These countries are diverse in terms of pollutant emissions as well as climate conditions. Information on the contribution of natural and anthropogenic as well as national and imported particles in total PM₁₀ concentrations in both countries is presented. The paper shows that the modelled national annual average PM₁₀ concentrations, calculated for the entire country area, are similar for the UK and Poland and close to 12 μg m^?3. Secondary inorganic aerosols dominate the total PM₁₀ concentrations in Poland. Primary particulate matter has the greatest contribution to total PM₁₀ in the UK, with large contribution of base cations. Anthropogenic sources predominate (81 %) in total PM₁₀ concentrations in Poland, whereas natural prevail in the UK—hence, the future reduction of PM₁₀ air concentrations by emissions reduction could be more difficult in the UK than in Poland.     

RELEVANT ASPECTS OF AIR QUALITY IN OPORTO (PORTUGAL): PM10 AND O3

The air quality Framework Directive (FWD) and the correspondent Daughter Directives defined the new strategy for air quality management in Europe. In general, the new standards are more restrictive than those established by the previous legislation. In Portugal, some difficulties can be previewed to achieve those new standards. Thus, this paper aims at evaluating the impact of application of the FWD to Oporto Metropolitan Area in what concerns to the most critical air pollutants in the area (PM₁₀ and O₃). The specific objectives were: i) to analyse the concentration exceedances between 1999 and 2001; ii) to identify the main emission sources; iii) to evaluate the possibility of a new redistribution of the existing monitoring sites; iv) to contribute to the definition of a new strategy for air quality management. The results showed that; i) the standard values for PM₁₀ and O₃ were largely surpassed, possibly concluding that the FWD application implies a strong impact on the air quality management strategies; ii) the main emission sources (road traffic and the neighbour stationary sources localised upwind) affect all the Metropolitan area through intra-region pollutant transport; iii) it is safer maintaining the site localisation to avoid previewing exceedances through mathematical correlations; iv) the reduction of PM₁₀ and of ozone precursors must be performed considering new technologies for cleaner production and gaseous depuration, a rigorous urban and territory planning, the creation of an efficient public transport network and the definition of strict measures for car maintenance.     

Seasonal air quality profile of inorganic ionic composition of PM10 near Taj Mahal in Agra, India

Atmospheric aerosols and their impacts on the environment particularly on human health is an issue of significant public and governmental concern. Though studies on air quality related to total suspended particulate matter have done by various authors in India, yet respirable suspended particulate matter (PM₁₀) is not characterized so far particularly in a historical and world heritage city like Agra. This study presents seasonal variation in mass levels of PM₁₀ and its ionic composition. PM₁₀ samples were collected in the proximity of Taj Mahal and subjected to chemical analysis using ion chromatography technique. The preliminary findings reveal that the 24-h average of PM₁₀ mass level varies from 115 to 233, 155 to 321, and 33 to 178 μg/m³, respectively, in summer, winter, and rainy seasons indicating critical pollution situation. These values are very much higher than the National Ambient Air Quality Standards of 75 μg/m³ (prescribed by Central Pollution Control Board, India) in both of summer and winter seasons whereas quite near the permissible limits in rainy season. The equivalent ratios of NH₄ ⁺ to nonsea salt SO₄ ^2? and NO₃ ^? and ∑Cations to ∑Anios were found to be greater than unity indicating high source strength of ammonia and alkaline nature of aerosols. The study suggests the need for continuous and long-term systematical sampling and detailed physiochemical analysis of PM₁₀ and also to know the characteristics of PM in background areas for better understanding of the emission sources.     

Seasonal variation in ambient PM mass and number concentrations (case study: Tehran, Iran)

Tehran, the capital city of Iran, is an important industrial and commercial center. This city is one of the worst cities in the world in terms of air pollution, which is mostly due to mobile sources rather than stationary sources. Particulate matter (PM), which is a complex mixture of extremely small particles and liquid droplets, is considered as an important source of air pollution in Tehran. In this study, our objective was to study PM₁₀, PM_2.5, and PM_1.0 mass and number concentrations and find the correlations of these two parameters in the west-central parts of Tehran during two consecutive warm and cold seasons. The particles collected from five stations were analyzed for their mass and number simultaneously by a laser-based Grimm dust monitor. In general, it was found that the accumulation of the PM in this region is more in the cold season. PM₁₀ mass concentration increases almost twofold and PM_2.5 and PM_1.0 almost three times in this season. The mean number concentration of the particles (0.3–20 μm) was found to be almost 4.8 times in the cold season. It was also noticed that the average dimensions of the particles decrease in that season.     

Characteristics of ambient 1-min PM2.5 variation in Beijing

One-minute PM_2.5 concentration was obtained with LD-5C pocket microcomputer laser dust instrument from Dec. 15th, 2005 to Jan. 16th, 2006 and Mar. 17th to Apr. 28th, 2006 in Beijing. The concentration of SO₂, NO₂, O₃, CO, and PM₁₀ from Jan. 1st, 2001 to Dec. 31st, 2004 were obtained from the conversion of air pollution index. Results showed that all the pollutants showed cyclic characteristics. The longer yearly cycles was shown from SO₂, NO₂, O₃, CO, and PM₁₀, as the sampling time was 4-year long and daily collected. The shorter hourly and daily cycle was shown from 1-min PM_2.5, as the sampling time was about 1-month long and one collected at 1 min. The spectral density analysis confirmed this from the periodogram graphs. The longer yearly cycle (365, 180 days), the seasonal cycle (120, 60–90 days), and monthly cycle (21, 23, 27 days) of SO₂, NO₂, CO, O₃, and PM₁₀ were obviously shown. In addition, the shorter weekly cycle of 5–7 days is obviously shown, too. The shorter hourly cycle (8–12, 4–6, 3, 1–2 h, 20 min) of 1-min PM_2.5 was also indicated from spectral density analysis. Two major factors contribute the 1-min PM_2.5 cycles, i.e., the meteorological factors and source effects. Both the relative humidity and dew point showed consistent variation with PM_2.5, but the wind speed showed inverse variations with PM_2.5. Furthermore, the spectral density analysis of the meteorological factors (4–5, 2–2.5, 1–1.5 days, 12, 6–8, 3 h) may partially explain the cycles of PM_2.5. As for the sources effects, it can be shown from the strong dust storm of April 16–18th, 2006. PM_2.5 constantly increased tens and even hundreds of times high concentration within a few minutes due to the intensity of the dust sources.     

Human health damage caused by particulate matter PM10 and ozone in urban environments: the case of Athens, Greece

Studies conducted over the past decades have provided substantial evidence that both the long- and the short-term exposures to ozone and particulate matter are responsible for mortality and cardiopulmonary morbidity. This paper examines the relationship between exposure to ambient concentrations of ozone (O₃) and particulate matter with aerodynamic diameter of less than 10 μm (PM₁₀) and public health and provides the quantification of the burden of disease from PM₁₀ and O₃-related mortality and morbidity through a Life Cycle Impact Assessment focused on the greater area of Athens, Greece. Thus, characterizations factors (CFs) for human health damage are calculated in 17 sites in Athens, in terms of the annual marginal change in the disability-adjusted life years (DALYs) due to a marginal increase in the ambient concentrations. It is found that the PM₁₀ intake factors range between 1.25?×?10^?6 and 2.78?×?10^?6, suggesting that 1.25–2.78 μg of PM₁₀ are inhaled by the Athenian population per kg of PM₁₀ in the urban atmosphere. Mortality due to chronic exposure to PM₁₀ has a dominant contribution to years of life lost with values ranging between 6.2?×?10^?5 and 1.1?×?10^?4. On the other hand, the mortality caused by short-term exposure to O₃ is weaker with the CFs ranging between 1.58?×?10^?7?years of life lost in the urban/traffic areas and 4.71?×?10^?7?years in the suburbs. Finally, it is found that 9,000 DALYs are lost on average in Athens, corresponding to 0.0018 DALYs per person. This is equal to 0.135 DALYs per person over a lifetime of approximately 75 years, assuming constant emission rates for the whole period.     

杭州城区大气颗粒物污染特征及PM2.5潜在源区研究

基于2015年9月1日至2016年8月25日杭州城区观测点PM₁、PM_2.5、PM₁₀小时浓度数据进行分析,利用HYSPLIT模型、潜在源贡献因子（PSCF）方法和浓度权重轨迹（CWT）方法,探讨了杭州城区PM₁、PM_2.5、PM₁₀时间分布特征和PM_2.5潜在来源。结果表明：研究期间PM₁季节平均浓度表现为冬季 > 秋季、春季 > 夏季,PM_1~2.5、PM_2.5~10浓度则表现为冬季 > 春季 > 秋季 > 夏季;PM₁浓度日变化呈现明显的双峰现象,而PM_1~2.5和PM_2.5~10在同一时段均无明显浓度峰值;杭州城区PM_2.5受外源输送污染具有明显的季节性变化特征,夏季、秋季杭州城区PM_2.5的潜在源区主要是浙江北部、安徽东南部等,春季PM_2.5的潜在源区主要是浙江中部、江苏南部等,冬季PM_2.5的潜在源区主要是山东南部、江苏西南部、浙江北部、安徽南部、江西中部等地区。     

Indoor air quality modeling for PM10, PM2.5, and PM1.0 in naturally ventilated classrooms of an urban Indian school building

Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student??s health and performance as they spend a substantial amount of their time (6?C7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants?? health. The objectives of the present study are twofold, one, to measure the concentrations of PM₁₀ (<10  $\upmu $ m), PM_2.5 (<2.5  $\upmu $ m), and PM_1.0 (<1.0  $\upmu $ m) in naturally ventilated classrooms of a school building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM₁₀ (NVIAQM_pm10), PM_2.5 (NVIAQM_pm2.5), and PM_1.0 (NVIAQM_pm1.0) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO₂ concentrations have also been monitored during school hours. Predicted indoor PM₁₀ concentrations show poor correlations with observed indoor PM₁₀ concentrations (R ² = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM_pm2.5 and NVIAQM_pm1.0 results show good correlations with observed concentrations of PM_2.5 (R ² = 0.87 for weekdays and 0.9 for weekends) and PM_1.0 (R ² = 0.86 for weekdays and 0.87 for weekends). NVIAQM_pm10 shows the tendency to underpredict indoor PM₁₀ concentrations during weekdays as it does not take into account the occupant??s activities and its effects on the indoor concentrations during the class hours. Intense occupant??s activities cause resuspension or delayed deposition of PM₁₀. The model results further suggests conductance of experimental and physical simulation studies on dispersion of particulates indoors to investigate their resuspension and settling behavior due to occupant??s activities/movements. The models have been validated at three different classroom locations of the school site. Sensitivity analysis of the models has been performed by varying the values of mixing factor (k) and newly introduced parameter R _c. The results indicate that the change in values of k (0.33 to 1.00) does not significantly affect the model performance. However, change in value of R _c (0.001 to 0.500) significantly affects the model performance.     

Simulation of Urban-Scale Air Pollution Patterns in Luxembourg: Contributing Sources and Emission Scenarios

The aim of this study is to investigate the air pollution situation in an urban area in southwestern Luxembourg and to simulate annual NO₂ and PM₁₀ concentrations in response to changes in meteorological conditions and emissions using a Gaussian dispersion model. Simulations are carried out for the years 1998–2006. Emission scenarios related to road transport and nonindustrial combustion are performed in order to predict changes of air pollution levels. Road transport is by far the most important local emission source in the study area. Scenarios with more stringent emission standards for vehicles, less traffic, and fewer heavy-duty vehicles lead to reductions of NO_x and primary PM₁₀ emissions. As a result, the annual NO₂ concentrations are decreasing in most parts of the study area and are below the European annual limit value of 40 μg?m^?3. In contrast, a scenario with increased use of wood pellets for domestic heating shows an increase in urban PM₁₀ concentration. The year-to-year variability of meteorological conditions accounts for the same magnitude of absolute NO₂ and PM₁₀ concentration changes as the emission scenarios. The comparison with measurements located in the study area shows that the model is able to predict urban-scale annual average air pollution. The proposed application results show that the model can be appropriate for policy-driven air quality management and planning queries.     

Distribution of PM2.5 and PM10-2.5 in PM10 Fraction in Ambient Air Due to Vehicular Pollution in Kolkata Megacity

This research paper aims at establishing baseline PM₁₀ and PM_2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM_2.5) and coarser fractions (PM_10-2.5) to PM₁₀ fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM₁₀ concentration was 304 μg/m³, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM₁₀ concentration was due to fine fraction (PM_2.5) released by vehicular exhaust. The 24h average PM_2.5 concentration was found 179 μg/m³, which is exceeded USEPA and EU standards of 65 and 50 μg/m³ respectively for the winter. India does not have any PM_2.5 standards. The 24 h average PM_10-2.5 concentrations were found 126 μg/m³. The PM_2.5 constituted more than 59% of PM₁₀ and whereas PM₁₀-PM_2.5 fractions constituted 41% of PM₁₀. The correlation between PM₁₀ and PM_2.5 was found higher as PM_2.5 comprised major proportion of PM₁₀ fractions contributed by vehicular emissions.     

Motor Vehicle Contributions to Ambient PM10 and PM2.5 at Selected Urban Areas in the USA

A source apportionment study was carried out to estimate the contribution of motor vehicles to ambient particulate matter (PM) in selected urban areas in the USA. Measurements were performed at seven locations during the period September 7, 2000 through March 9, 2001. Measurements included integrated PM_2.5 and PM₁₀ concentrations and polycyclic aromatic hydrocarbons (PAHs). Ambient PM_2.5 and PM₁₀ were apportioned to their local sources using the chemical mass balance (CMB) receptor model and compared with results obtained using scanning electron microscopy (SEM). Results indicate that PM_2.5 components were mainly from combustion sources, including motor vehicles, and secondary species (nitrates and sulfates). PM₁₀ consisted mainly of geological material, in addition to emissions from combustion sources. The fractional contributions of motor vehicles to ambient PM were estimated to be in the range from 20 to 76% and from 35 to 92% for PM_2.5 and PM₁₀, respectively.     

渝东南典型城区冬季一次罕见的PM2.5污染过程及溯源分析

2020年12月底,以生态旅游业为主的重庆市渝东南地区出现了一次较为罕见的PM_2.5污染过程,持续时间长且污染程度重。以渝东南地区武隆区为例,应用污染特征雷达图、后向轨迹模型及潜在源污染贡献估算等方法分析了本次PM_2.5污染的特征及来源,结果表明：(1)在污染前期主要受扬尘、燃煤和机动车等污染排放影响,污染源直接排放贡献较大;中、后期污染受二次颗粒物影响显著,扬尘影响也较为明显。(2)污染期间的气流轨迹均为短距离输送,轨迹主要来自东北方向(65%)。(3)除自身污染排放贡献外,渝东北地区和主城都市区是武隆区PM_2.5污染的主要潜在源区,对武隆区传输贡献占比超50%。     

Using Archive Data to Investigate Trends in the Sources and Composition of Urban PM10 Particulate Matter: Application to Edinburgh (U.K.) Between 1992 and 1997

By extending the method of Stedman (1998), daily dataof atmospheric concentrations of gravimetricPM₁₀, black smoke (BS) and sulphate aerosol (SA)from national networks were analysed to determine thetrends in time of the contribution of different sources of particulate matter to total PM₁₀ measured in central Edinburgh. Since BS is an indicator of combustion-related primary sources of particulate matter, the quantity obtained by subtraction of daily BS from daily PM₁₀ is indicative of the contribution to total PM₁₀ from other primary sources and from secondary aerosol. This PM₁₀-BS statistic was regressed on SA, since SA is an indicator of variation in secondary aerosol source. For Edinburgh, SA is a considerably better indicator of PM₁₀-BS during summer than winter (reflecting the much greater photochemical generation of secondary aerosol in summer) and there is evidence that the contribution of other secondary aerosol (presumably nitrate aerosol) has increased relative to SA between 1992 and 1997. The concentration of non-combustion primary particulate material (marine aerosol, suspended dust) to PM₁₀ in Edinburgh has not changed over this period but is about twice that calculated as the U.K. national average. The increasing input to PM₁₀ from secondary aerosol sources at regional rather than urban scale has important implications for ensuring local air quality compliance. The method should have general applicability to other locations.     

Assessment of indoor and outdoor particulate air pollution at an urban background site in Iran

The relationship between indoor and outdoor particulate air pollution was investigated at an urban background site on the Payambar Azam Campus of Mazandaran University of Medical Sciences in Sari, Northern Iran. The concentration of particulate matter sized with a diameter less than 1 μm (PM_1.0), 2.5 μm (PM_2.5), and 10 μm (PM₁₀) was evaluated at 5 outdoor and 12 indoor locations. Indoor sites included classrooms, corridors, and office sites in four university buildings. Outdoor PM concentrations were characterized at five locations around the university campus. Indoor and outdoor PM measurements (1-min resolution) were conducted in parallel during weekday mornings and afternoons. No difference found between indoor PM₁₀ (50.1 ± 32.1 μg/m³) and outdoor PM₁₀ concentrations (46.5 ± 26.0 μg/m³), indoor PM_2.5 (22.6 ± 17.4 μg/m³) and outdoor PM_2.5 concentration (22.2 ± 15.4 μg/m³), or indoor PM_1.0 (14.5 ± 13.4 μg/m³) and outdoor mean PM_1.0 concentrations (14.2 ± 12.3 μg/m³). Despite these similar concentrations, no correlations were found between outdoor and indoor PM levels. The present findings are not only of importance for the potential health effects of particulate air pollution on people who spend their daytime over a period of several hours in closed and confined spaces located at a university campus but also can inform regulatory about the improvement of indoor air quality, especially in developing countries.     

不同气团来源对广州细颗粒物理化特性的影响

利用2006年7月广州细颗粒物质量浓度、数谱分布与化学组成的观测数据与气团后向轨迹聚类分析结果,系统分析了不同气团来源对广州细颗粒物理化特性的影响。观测期间,广州气团来源可分成来自远海、近海、西面陆地和北面陆地4种类型。细颗粒物总数浓度水平在4种类型中基本相当。当气团来自远海时,二次转化影响较小,PM2.5质量浓度较低,颗粒物数浓度从大到小依次为老化爱根核模态新鲜爱根核模态度积聚模态;受到海洋气团的影响,Cl-在PM2.5中比例为4种类型中最大。气团来自近海时,颗粒物二次生成与老化现象突出,数谱峰值出现在积聚模态,而其他类型出现在爱根核模态;SO2-4、OC与NO-3之和在PM2.5中的比例大于50%,为4种类型中最高。气团来自西面陆地和北面陆地时,细颗粒物受陆地传输老化气团和本地来源影响均较明显。来自北面陆地时,250 nm以上颗粒物数浓度明显升高,是PM2.5平均浓度远高于其他类型的直接原因之一。     

Effects of meteorological conditions on PM10 concentrations - A study in Macau

Review on the annual PM₁₀ concentrations over a 10-year period shows that Macau is subjected to severe fine particulate pollution. Investigations of its variation in monthly and daily time scales with the local meteorological records reveal further details. It is found that a distinct feature of the Asian monsoon climates, the changes of wind direction, mainly controls the general trend of PM₁₀ concentration in a year. The monsoon driven winter north-easterly winds bring upon Macau dry and particle enriched air masses leading to a higher concentration in that period while the summer south-westerly winds transport humid and cleaner air to the region leading to a lower PM₁₀ value. This distinct seasonal feature is further enhanced by the lower rainfall volume and frequency as well as mixing height in winter and their higher counterparts in summer. It is also found that the development of tropical cyclones near Macau could also impose episode like PM₁₀ concentration spikes due to the pre-typhoon induced stagnant air motion followed by the swing of wind direction to the northerly.     

Heavy metals in urban ambient PM10 and soil background in eight cities around China

The ambient PM₁₀ and background soil samples were collected and analyzed with ICP-AES in eight cities around China to investigate the levels of ten heavy metals (Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, and Pb). The mean concentrations of ten heavy metals in PM₁₀ of the eight cities of China followed the order of Zn?>?Pb?>?Mn?>?Cu?>?Ni?>?Cr?>?Co?>?V. The metals in the ambient PM₁₀ and soil were compared in each city to evaluate the heavy metal mass fraction from anthropogenic sources in ambient air. The CD values in these cities were all above 0.2, indicating that the ingredients spectrums of PM₁₀ and soil vary markedly. Most heavy metals were enriched in PM₁₀, except Fe and Ti. The results showed that almost all the cities suffer important heavy metal pollution from anthropogenic sources. The eight cities were also grouped according to their similarity in heavy metals of ambient PM₁₀ by cluster analysis to investigate the relationship between the heavy metals and the pollution sources of each city. The conclusion was that the eight cities were divided into three clusters which had similar industrial type and economy scale: the first cluster consisted of Shenzhen, Wuxi, and Guiyang; followed by Jinan and Zhengzhou as the second grouping; and the third group had Taiyuan, Urumqi, and Luoyang.     

南充市大气PM10与PM2.5排放清单及特征

以四川省南充市为研究区域,通过实地调研、现场测试及结合统计年鉴等获得数据,采用排放因子法计算南充市2014年大气PM_(10)、PM_(2.5)排放量并建立排放清单。结果表明,南充市2014年扬尘源、移动源、生物质燃烧源、化石燃料固定燃烧源、工艺过程源排放总量PM_(10)分别为85 187、1 777、9 175、2 417、3 519 t,PM_(2.5)分别为16 093、1 619、7 322、914、1 585 t,PM_(10)贡献率分别为83.5%、1.7%、9.0%、2.4%、3.4%,PM_(2.5)贡献率分别为58.4%、5.9%、26.6%、3.3%、5.8%。城市区域扬尘源、生物质燃烧源、移动源、化石燃料固定燃烧源、工艺过程源对PM_(10)贡献分别为60.0%、12.5%、6.3%、8.6%、12.5%,对PM_(2.5)贡献分别为41.8%、21.6%、14.4%、8.1%、14.1%。南充市2014年大气PM_(10)、PM_(2.5)排放源总量和贡献率以及区域空间分布特征均存在差异。     

Characterisation of PM10, PM2.5 and Benzene Soluble Organic Fraction of Particulate Matter in an Urban Area of Kolkata, India

In this study, the relationship between inhalable particulate (PM₁₀), fine particulate (PM_2.5), coarse particles (PM_{2.5 – 10}) and meteorological parameters such as temperature, relative humidity, solar radiation, wind speed were statistically analyzed and modelled for urban area of Kolkata during winter months of 2003–2004. Ambient air quality was monitored with a sampling frequency of twenty-four hours at three monitoring sites located near traffic intersections and in an industrial area. The monitoring sites were located 3–5 m above ground near highly trafficked and congested areas. The 24 h average PM₁₀ and PM_2.5 samples were collected using Thermo-Andersen high volume samplers and exposed filter papers were extracted and analysed for benzene soluble organic fraction. The ratios between PM_2.5 and PM₁₀ were found to be in the range of 0.6 to 0.92 and the highest ratio was found in the most polluted urban site. Statistical analysis has shown a strong positive correlation between PM₁₀ and PM_2.5 and inverse correlation was observed between particulate matter (PM₁₀ and PM_2.5) and wind speed. Statistical analysis of air quality data shows that PM₁₀ and PM_2.5 are showing poor correlation with temperature, relative humidity and solar radiation. Regression equations for PM₁₀ and PM_2.5 and meteorological parameters were developed. The organic fraction of particulate matter soluble in benzene is an indication of poly aromatic hydrocarbon (PAH) concentration present in particulate matter. The relationship between the benzene soluble organic fraction (BSOF) of inhalable particulate (PM₁₀) and fine particulate (PM_2.5) were analysed for urban area of Kolkata. Significant positive correlation was observed between benzene soluble organic fraction of PM₁₀ (BSM10) and benzene soluble organic fraction of PM_2.5 (BSM2.5). Regression equations for BSM10 and BSM2.5 were developed.