Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

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.     

青藏高原典型城市拉萨市大气颗粒物污染源成分谱建立研究与特征分析

系统研究建立高原典型城市拉萨市开放源(土壤风沙尘、道路扬尘、施工扬尘、采矿扬尘),移动源(机动车尾气尘),固定源(工业烟粉尘、生物质燃烧尘及餐饮油烟)共3类8种大气颗粒物(PM_(2.5)、PM_(10))污染源化学成分谱。研究结果表明:开放源以地壳类元素为主,自然背景特征明显;移动源源成分谱中元素碳含量明显高于其他城市,在PM_(2.5)、PM_(10)源谱中分别占60.15%、51.86%,有机碳含量也相对较高,均超过20%;固定源中,牛粪和松柏枝两类生物质燃烧污染源的有机碳含量显著高于其他组分,工业烟粉尘中Ca远高于其他组分,在PM_(2.5)、PM_(10)源谱中分别占21.32%、21.21%。移动源、固定源源成分谱均显示出高原城市的独特特征。     

Analysis of acidic components, heavy metals and PAHS of particulate in the Changwon–Masan area of Korea

This study is an analysis of the concentrations and components of heavy metals in PM_2.5 and the total suspended particulate (TSP) collected at a mechanical industrial complex (IC) site in Changwon and at a residential site in Masan, Korea. Particulate was collected during two sampling periods, from the late summer to the early fall and from the middle to late fall, at the IC site and one sampling period, from the middle fall to the early winter, at the residential site. PM_2.5 and TSP samples were taken by an annular denuder system and a hi-volume air sampler, respectively. The authors also identified the concentrations and components of heavy metals extracted from the PM_2.5 and TSP filters, the acidic components extracted from the PM_2.5 filters, and the polycyclic aromatic hydrocarbons (PAHs) extracted from polyurethane foam (PUF) plug. The average concentrations of the PM_2.5 collected at the IC and residential sites were very similar. Major sources of PM_2.5 at the study sites, however, were air emissions from vehicles and industry as well as emissions from residential heating and soil origins, respectively. The higher concentrations of the TSP at the IC site, as compared to those at the residential site, were due to either increased suspended dust from vehicle emissions or re-suspended road dust because of increased vehicle speeds near the IC site. Heavy metal concentrations in the TSPs were higher than those in the PM_2.5. The heavy metal concentrations in the PM_2.5 and TSP at the IC site with heavy traffic were substantially greater than those at the residential site. The concentrations of TSP and heavy metals and PAHs in PM during the period of the middle to late fall was much higher than those during the period of the late summer to early fall at the IC site. This is because of the difference in meteorological characteristics and energy uses between two periods. The residential site also showed higher concentrations of acidic anions while the IC site showed higher concentrations of acidic cation. Secondary aerosols or particulates, such as ammonium nitrate or ammonium nitrite, might have been important constituents of the PM_2.5 at the residential site. The PAHs in the TSP collected at the IC site was greatly affected by traffic and industry emissions consisting mostly of high molecular weight PAHs with two to four rings. PAHs in the TSP at the site, however, were affected by residential heating and air emissions from small chemical plants having higher concentrations of low molecular weight PAHs with five to six rings.     

Determination of road dust loadings and chemical characteristics using resuspension

The contribution of fugitive dust from traffic to air pollution can no longer be ignored in China. In order to obtain the road dust loadings and to understand the chemical characteristics of PM₁₀ and PM_2.5 from typical road dust, different paved roads in eight districts of Beijing were selected for dust collection during the four seasons of 2005. Ninety-eight samples from 28 roads were obtained. The samples were resuspended using equipment assembled to simulate the rising process of road dust caused by the wind or wheels in order to obtain the PM₁₀ and PM_2.5 filter samples. The average road dust loading was 3.82 g m^− 2, with the highest of 24.22 g m^− 2 being in Hutongs in the rural–urban continuum during winter. The road dust loadings on higher-grade roads were lower than those on lower-grade roads. Attention should be paid to the pollution in the rural–urban continuum areas. The sums of element abundances measured were 16.17% and 18.50% for PM₁₀ and PM_2.5 in road dust. The average abundances of OC and EC in PM₁₀ and PM_2.5 in road dust were 11.52%, 2.01% and 12.50%, 2.06%, respectively. The abundance of elements, water-soluble ions, and OC, EC in PM₁₀ and PM_2.5 resuspended from road dust did not change greatly with seasons and road types. The soil dust, construction dust, dust emitted from burning coal, vehicle exhaust, and deposition of particles in the air were the main sources of road dust in Beijing. Affected by the application of snow-melting agents in Beijing during winter, the amount of Cl⁻ and Na⁺ was much higher during that time than in the other seasons. This will have a certain influence on roads, bridges, vegetations, and groundwater.     

Estimation of air pollutant emission loads from construction and operational activities of a port and harbour in Mumbai, India

Port causes environmental and health concerns in coastal cities if its operation and development are not made environmentally compatible and sustainable. An emission inventory is necessary to assess the impact of port projects or growth in marine activity as well as to plan mitigation strategies. In this study, a detailed emission inventory of total suspended particulate (TSP) matter, respirable particulate matter (PM₁₀), sulphur dioxide (SO₂) and oxides of nitrogen (NO_x) for a port having operation and construction activities in parallel is compiled. The study has been done for 1 year. Results show that the maximum contribution of emission of air pollutants in the port area was from TSP (68.5%) and the minimum was from SO₂ (5.3%) to the total pollutants considered in this study. Total TSP emission from all activities of the port was 4,452 tyr^???1 and PM₁₀ emission was 903 tyr^???1 in the year 2006. Re-suspension of dust from paved roads was the major contributor of TSP and PM₁₀ in the road transport sector. Construction activities of the port had contributed 3.9% of TSP and 7.4% of PM₁₀ to total emission of particulate matter. Of the total particulate emissions from various port activities approximately 20% of TSP could be attributed to PM₁₀. The sectoral composition indicates that major contribution of SO₂ emission in the port was from maritime sector and major contribution of NO_x was from road transport sector.     

上海市浦东新区大气细颗粒物中重金属污染特征及来源解析

于2017年对浦东城区和郊区大气PM2.5中的重金属特征和来源进行了分析。结果表明,K、Fe、Na、Ca、Mg、Al等矿物元素为浦东新区PM2.5中含量最高的金属元素,其中K的年均值为297.3 ng/m^3。浦东城区的不同元素在季节变化上呈现较为不同的变化规律,郊区的金属元素值大部分呈现春季先逐月下降,在夏、秋季有起伏波动,在10月之后逐渐上升;沙尘+道路源+建筑扬尘、煤燃烧、工业排放、金属冶炼、船舶排放、海盐+垃圾焚烧+生物质燃烧为浦东城区PM2.5中重金属元素的6大类主要来源。其中沙尘+道路源+建筑扬尘对Ca的贡献率为82.7%,煤燃烧对As的贡献率为86.6%,工业排放对SO4^2-的贡献率达到65.9%,金属冶炼对Cr的贡献率为75.7%,船舶排放对V的贡献率为97.5%、海盐+垃圾焚烧+生物质燃烧对Cl^-的贡献率为93.0%。煤燃烧和金属冶炼主要来自于西部方向。船舶排放分布在长江口及其延伸带。浦东新区PM2.5中重金属元素的质量浓度与本地源排放强度、外界传输和大气扩散条件均有密切关系。     

道路绿化带影响大气颗粒物分布实测研究

以福州市西三环快速路某路段为实验靶区,利用微型环境检测仪采集路边细颗粒物(PM_2.5)、亚微米颗粒物(PM_1.0)和黑碳(BC)的空间分布样本,解析其在道路绿化带前后(绿化带前是指干道和辅道外边缘线位置,其他位置均视为绿化带后)的变化特征及原因。结果表明：(1)颗粒物浓度随着采样点远离干道而整体趋于递减,呈现BC>PM_2.5>PM_1.0的衰减率变化特征,且植被稠密的路边环境对应更大的颗粒物浓度降幅。(2)夏季绿化带后的颗粒物浓度降幅高于冬季,冬季绿化带后部分采样点的PM_1.0和PM_2.5浓度甚至有所抬升。在植被茂密的路边环境下,风自干道吹向绿化带情景的路边空气质量介于风自绿化带吹向干道情景和风平行于干道情景之间。(3)BC对交通变化的敏感性高于PM_2.5和PM_1.0,植被茂密的绿化带后的颗粒物浓度降幅会因交通强度的上升而增大。风自干道吹向绿化带时,绿化带对颗粒物的调节作用会随交通源强和季节的变化而不同...     

太原市大气颗粒物中重金属的污染特征及来源解析

为了解太原市采暖期大气颗粒物不同粒径中重金属的污染特征及其来源,于2012年10月—2013年2月对环境空气中颗粒物采样,用原子吸收分光光度法测定样品中Fe、Pb、Cu、Ni、Cr、Cd、Mn、Zn等8种元素的含量。结果表明,太原市采暖期重金属浓度从高到低依次为FePbMnZnCrCuNiCd。重金属Pb、Mn、Zn、Ni、Cd主要富集在PM2.5中;Cr主要富集在PM10中;Cu主要富集在PM5中;Fe主要在粒径大于2.5μm的粗粒子中富集。除Zn外,其他7种元素浓度均表现为灰霾期采暖期采暖前。通过主因子分析表明,太原市大气颗粒物中重金属主要来源于冶金、有机合成工业、燃煤、汽车尾气、土壤尘等。     

Dispersion model on PM 2.5 fugitive dust and trace metals levels in Kuwait Governorates

Frequent dust storms and recent environmental changes were found to affect the human health especially in residents of arid countries. Investigations on the PM_2.5 fugitive dust in six Kuwait Governorate areas using dispersion Gaussian plume modeling revealed significant relationship between low rate of pollutant emission, low wind velocity, and stable weather conditions’ matrix causing high rate of dust deposition in summer than in winter. The rate of dust deposition and trace metals levels in PM_2.5 were in the sequence of G-VI > G-I > G-II > G-V > G-III > G-IV. Trace metals were observed in the sequence of Al > Fe > Zn > Ni > Pb > Cd irrespective of the Governorate areas and the two seasons. The high rate of dust deposition and trace metals in PM_2.5 was reflected by the vast open area, wind velocity, and rapid industrialization besides natural and anthropogenic sources. A combination of air dispersion modeling and nephalometric and gravimetric studies of this kind not only determines the seasonal qualitative and quantitative analyses on the PM_2.5 dust deposition besides trace metals apportionment in six Kuwait Governorate areas, but also characterizes air pollution factors that could be used by environmentalist to deduce preventive measures.     

石家庄市大气颗粒物元素组分特征分析

为研究石家庄市大气颗粒物的污染特征及其来源,于2013年4—5月在主城6区分别采集TSP、PM10和PM2.5颗粒物样品,利用ICP-MS分析其中的22种元素浓度。结果表明,石家庄市城区Ca、Fe元素在各粒径颗粒物中含量都较高,PM2.5中的S、K含量较高,PM10和TSP中Mg、Al的浓度相对较高。颗粒物的主要来源为燃煤尘、道路尘和建筑尘,TSP、PM10和PM2.5具有较好的统计相关性和同源性。     

PM2.5 and PM10 Concentrations from the Qalabotjha Low-Smoke Fuels Macro-Scale Experiment in South Africa

This article presents results from the particulate monitoringcampaign conducted at Qalabotjha in South Africa during the winter of 1997. Combustion of D-grade domestic coal and low-smoke fuels were compared in a residential neighborhood to evaluate the extent of air quality improvement by switchinghousehold cooking and heating fuels.Comparisons are drawn between the gravimetric results from the two types of filter substrates (Teflon-membrane and quartz-fiber) as well as between the integrated and continuous samplers. It is demonstrated that the quartz-fiber filters reported 5 to 10% greater particulate mass than the Teflon-membrane filters, mainly due to the adsorption of organic gases onto the quartz-fiber filters. Due to heating of sampling stream to 50 °C in the TEOM continuous sampler and the high volatile content of the samples, approximately 15% of the particulate mass was lost during sampling.The USEPA 24-hr PM_2.5 and PM₁₀ National Ambient Air Quality Standards (NAAQS) of 65 g m^-3 and 150 g m^-3, respectively, were exceeded on several occasions during the 30-day field campaign. Average PMconcentrations are highest when D-grade domestic coal was used, and lowest between day 11 and day 20 of the experiment when a majority of the low-smoke fuels were phased in. Source impacts from residential coal combustion are also found to be influenced by changes in meteorology, especially wind velocity.PM_2.5 and PM₁₀ mass, elements, water-soluble cations (sodium, potassium, and ammonium), anions (chloride, nitrate, and sulfate), as well as organic and elemental carbonwere measured on 15 selected days during the field campaign. PM_2.5 constituted more than 85% of PM₁₀ at three Qalabotjha residential sites, and more than 70% of PM₁₀ at the gradient site in the adjacent community of Villiers. Carbonaceous aerosol is by far the most abundant component, accounting for more than half of PM mass at the three Qalabotjha sites, and for more than a third of PM mass at the gradient site. Secondary aerosols such as sulfate, nitrate,and ammonium are also significant, constituting 8 to 12% of PM mass at the three Qalabotjha sites and 15 to 20% at the Villiers gradient site.     

Demonstrating PM<Subscript>2.5</Subscript> and road-side dust pollution by heavy metals along Thika superhighway in Kenya,sub-Saharan Africa

This study assessed the level of heavy metal in roadside dust and PM_2.5 mass concentrations along Thika superhighway in Kenya. Thika superhighway is one of the busiest roads in Kenya, linking Thika town with Nairobi. Triplicate road dust samples collected from 12 locations were analysed for lead (Pb), chromium (Cr), cadmium (Cd), nickel (Ni), zinc (Zn), and copper (Cu) using atomic absorption spectrophotometry (AAS). PM_2.5 samples were collected on pre-weighed Teflon filters using a BGI personal sampler and the filters were then reweighed. The ranges of metal concentrations were 39–101 μg/g for Cu, 95–262 μg/g for Zn, 9–28 μg/g for Cd, 14–24 μg/g for Ni, 13–30 μg/g for Cr, and 20–80 μg/g for Pb. The concentrations of heavy metals were generally highly correlated, indicating a common anthropogenic source of the pollutants. The results showed that the majority of the measured heavy metals were above the background concentration, and in particular, Cd, Pb, and Zn levels indicated moderate to high contamination. Though not directly comparable due to different sampling timeframes (8 h in this study and 24 h for guideline values), PM_2.5 for all sites exceeds the daily WHO PM_2.5 guidelines of 25 μg/m³. This poses a health risk to people using and working close to Thika superhighway, for example, local residents, traffic police, street vendors, and people operating small businesses. PM_2.5 levels were higher for sites closer to Nairobi which could be attributed to increased vehicular traffic towards Nairobi from Thika. This study provides some evidence of the air pollution problem arising from vehicular traffic in developing parts of the world and gives an indication of the potential health impacts. It also highlights the need for source apportionment studies to determine contributions of anthropogenic emissions to air pollution, as well as long-term sampling studies that can be used to fully understand spatiotemporal patterns in air pollution within developing regions.     

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.     

省级高空间分辨率扬尘源排放清单研究

通过对浙江省统一开展部署和行动,现场调查收集全省7 507个施工工地、3 923个堆场以及不同等级公路和城市道路的真实活动水平数据,并基于点源地理信息和路网信息图层,采用排放系数法和ArcGIS工具构建了浙江省2015年3 km×3 km高空间分辨率扬尘源排放清单。结果表明,2015年浙江省扬尘源PM₁₀和PM_2.5的排放量分别为24.26×10⁴ t和6.00×10⁴ t,其中PM₁₀和PM_2.5排放贡献均主要为施工扬尘和道路扬尘,施工扬尘分别贡献37.7%和39.3%,道路扬尘分别贡献36.5%和39.1%。从城市空间分布来看,杭州市、宁波市、温州市、绍兴市扬尘排放总量居于全省前四,舟山市最低,而城市主城区排放量显著高于郊区。     

Ionic and heavy metal composition of respirable particulate in Madurai, India

Airborne particulate matter (PM₁₀) was collected for a period of 1 year at six locations in Madurai city, India. The chemical analyses on PM₁₀ samples were carried out for the estimation of heavy metals and ions using atomic absorption spectroscopy and ion chromatography respectively. The average PM₁₀ concentrations varied from 97.2 to 152.5 μg/m³, which were found to be below the Indian air quality standards. While industrial areas had the highest concentrations of heavy metals such as Fe, Zn and Cr and also the $\text{SO}_{4}^{2-}$ ions, traffic areas with relatively higher traffic densities in the city endured highest concentrations of Cd and the $\text{NO}_{3}^{-}$ ion. As gaseous pollutants serve as precursors of ionic particles in the atmospheric environment, gaseous pollution control is necessitated along with particulate with special reference to heavy metal and ion pollution abatement for the sustainable development of Madurai city.     

Influence of Meteorological Parameters on Particulates and Atmospheric Pollutants at Taichung Harbor Sampling Site

Atmospheric aerosol particles and metallic concentrations, ionic species were monitored at the Experimental harbor of Taichung sampling site in this study. This work attempted to characterize metallic elements and ionic species associated with meteorological conditions variation on atmospheric particulate matter in TSP, PM_2.5, PM_2.5–10. The concentration distribution trend between TSP, PM_2.5, PM_2.5–10 particle concentration at the TH (Taichung harbor) sampling site were also displayed in this study. Besides, the meteorological conditions variation of metallic elements (Fe, Mg, Cr, Cu, Zn, Mn and Pb) and ions species (Cl⁻, NO₃ ⁻, SO₄ ²⁻, NH₄ ⁺, Mg²⁺, Ca²⁺ and Na⁺) concentrations attached with those particulate were also analyzed in this study. On non-parametric (Spearman) correlation analysis, the results indicated that the meteorological conditions have high correlation at largest particulate concentrations for TSP at TH sampling site in this study. In addition, the temperature and relative humidity of meteorological conditions that played a key role to affect particulate matter (PM) and have higher correlations then other meteorological conditions such as wind speed and atmospheric pressure. The parameter temperature and relative humidity also have high correlations with atmospheric pollutants compared with those of the other meteorological variables (wind speed, atmospheric pressure and prevalent wind direction). In addition, relative statistical equations between pollutants and meteorological variables were also characterized in this study.     

蚌埠市夏季大气细颗粒物在线源解析

为了解蚌埠市环境空气中PM_(2.5)的来源,于2017年8月18日—9月18日,在百货大楼和高新区站点,利用单颗粒物气溶胶飞行时间质谱仪开展PM_(2.5)在线源解析。结果表明,百货大楼点位ρ(PM_(2.5))高于高新区点位,轻度污染比例(4.2%)明显高于高新区点位(0.8%),出现了中度污染(0.3%);SPAMS的PM_(2.5)质谱图显示百货大楼点位PM_(2.5)中K~+、Na~+特征明显,高新区点位HSO_4~-、NO_3~-、NO_2~-等无机信号较为明显;2个点位NO_3~-、NO_2~-、NH_4~+离子颗粒数占总颗粒数的百分比明显较高,且高新区点位NO_3~-、HSO_4~-离子数占比要明显高于百货大楼点位,燃料燃烧、工业工艺源、农田氮肥施用是其主要的人为污染源;2个点位PM_(2.5)成分主要为元素碳,分别占比42.4%,40.6%;污染时段,ρ(PM_(2.5))快速上升,除受本地机动车尾气源和燃煤源累积影响外,百货大楼点位扬尘源排放增加,高新区点位扬尘源和工业工艺排放源增加;2个点位机动车尾气源均为首要污染源,分别占比29.5%和30.9%,其次为燃煤源(24.3%和24.7%),扬尘源占比分别为22.9%和20.8%。     

Characterization of particulate matter and its related metal toxicity in an urban location in South West India

This study reports the quantification of the toxicity of particulate matter (PM)-bound metals and their possible associated risks to human health. For assessment of PM, 24-h samples of PM₁₀ and PM_2.5 were collected by Mini Vol-TAS sampler at an urban site of Pune. Samples were sequentially extracted with ultrapure water and concentrated HNO₃ and analyzed for “soluble” and “total” metals. Factor analysis identified the resuspension of road dust due to traffic, biomass burning, construction activities, and wind-blown dust as possible sources that played an important role for overall pollution throughout the year. Water-soluble proportion was found to be ≤20 % for Cr, Co, Fe, and Al; ≥50 % for Sr, Cd, Ca, and Zn; and a substantial proportion (～25–45 %) for Mn, Ba, K, Na, Ni, Mg, Cu, and Pb metals in PM₁₀. For PM_2.5, the water-soluble proportion was ≤20 % for Fe, Co, Ni, Cr, and Al, while Sr, K, and Cd were mostly soluble (>50 %) and Cu, Ba, Mn, Ca, Zn, Pb, Na, and Mg were substantially soluble (～25–45 %). In the present study, among the toxic metals, Cd and Pb show higher concentration in the soluble fraction and thus represent the higher bioavailability index and especially are harmful to the environment and exposed person. Risk calculations with a simple exposure assessment method showed that the cancer risks of the bioavailable fractions of Cr, Cd and Ni were greater than the standard goal.