Morphology,microstructure and chemical composition of single inhalable particles in Shanghai,China

The morphology, microstructure, and chemical composition of a variety of particles emitted from coal-fired power plants, steel plants, and vehicle exhausts, which are possible sources of particulate matter (PM) in the atmosphere, were investigated by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) and compared with particle samples collected from urban atmosphere to identify the best footprint or the suitable indicator relating the existence of studied particles and their possible emitters by the morphology, microstructure, and chemical composition of the particles. The investigation indicated that the particles from these three sources are different in morphology, microstructure, and chemical composition. Sphere aggregates were generally the most abundant components, with silicon and aluminum as major elements. The urban air particulate contained particles similar to those observed in the power plant, steel plant, and vehicle exhaust samples suggesting that all three sources are contributing to the pollution in the city.     

The composition of PM10 as collected by a conventional TEOM, a modified TEOM and a Partisol gravimetric monitor at a kerbside site in the North East of England

The composition of airborne particulate matter sampled by a conventional TEOM, an experimental modified TEOM, operated at a lower temperature but fitted with a drier to remove moisture and a Partisol, installed at a kerbside site in the North East of England, has been investigated. The results indicate that there is a seasonal variation in the composition of PM(10) as sampled by the three monitors, with chloride concentration being significantly higher in the winter. The Partisol was found to sample a higher mass of chloride and nitrate, however the differences between the monitors was only significant for chloride. Both TEOM's were found to sample a greater mass of sulphate, although the variability in the data collected meant that significance of the results was not proven statistically. The range of artifacts associated with PM(10) monitors is reviewed. Difficulties in the interpretation of results due to the variable nature of airborne particulate matter and the ability of filter based systems to accurately represent the composition of atmospheric particles are considered.     

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.     

A combined analysis to identify airborne PM10 sources

A two step procedure that combines an air dispersion model with a receptor model was used to identify the key sources that contribute to air levels of suspended particulate matter. The contribution to PM(10) concentrations measured at four monitoring sites in San Nicolas, Argentina, of the following sources, a thermal power plant, an integrated steel mill, motor vehicle exhaust fumes, and finally dust from paved and unpaved roads, have been analysed. Moreover, an air dispersion model was used to estimate the contribution of the thermal power plant, emissions of which have been described in depth by means of hourly fuel consumption and specific emission factors. The ratio "apportionment coefficient" was introduced to relate the contribution of this source to the measured 24 h PM(10) concentrations by analysing the frequency of occurrence of connecting winds between the power plant and each monitoring site. In San Nicolas 70% of the PM(10) sampled at three of the four monitoring sites could be attributed to the power plant in those scenarios where winds connected the facility's tall point sources with the sampling locations. The contribution to the measured PM(10) levels of the rest of the sources that are present in the analysed area was confirmed by way of receptor models. For this purpose, the multielemental composition of 41 samples was determined by Wavelength Dispersive X-ray Fluorescence analysis. In order to ascertain the underlying correlations between PM(10) samples and potential sources, Principal Component Analysis was performed on the standard matrix of composition profiles, which comprises the measured PM(10) samples being enlarged with the composition profiles of the potential contributing sources. The diagonalization of the covariance matrix was used as a screening procedure to differentiate the most likely contributing sources from those that were not significant.     

乌鲁木齐市冬季大气颗粒物PM_(10) 和PM_(2.5)污染水平及相关性研究

为研究乌鲁木齐市冬季采暖期间大气颗粒物污染特征,通过采样和在线监测二种手段分析了2015年1~2月大气颗粒物样品,采用重量法分析颗粒物质量浓度,并对其相关性进行分析。结果表明:依据《环境空气质量标准》(GB 3095-2012),采样期间乌鲁木齐市大气PM_(10) 和PM_(2.5)的日均质量浓度均超过了国家二级标准,颗粒物污染严重;PM_(10) 和PM_(2.5)存在显著相关性,PM_(2.5)和PM_(10) 浓度的比值均大于0.5,采暖期PM2.5对乌鲁木齐市大气颗粒物贡献显著。     

质谱直接测量法解析盐城市大气细颗粒物来源

为全面了解盐城市大气颗粒物的组成,摸清以PM2.5为首要污染物的来源,说清其化学组分和源贡献率,于2014年12月16日00:00—2014年12月21日09:00,利用在线单颗粒气溶胶质谱仪,对盐城市细颗粒物进行实时在线源解析。结果表明,盐城首要污染物为燃煤,占比为23.7%,其次是机动车尾气,占比为18.3%,第三位是扬尘,占总颗粒数的15.7%,生物质燃烧占比为14.8%位列第四,工业工艺源、二次无机源和其他源贡献率相对较小。     

Spatial and temporal variations in inhalable CuZnPb aerosols within the Mexico City pollution plume

We report on the CuPbZn content of PM10 and PM2.5 samples collected from three sites (urban T0, suburban T1 and rural T2) during the Mexico City MILAGRO campaign of March 2006. Daytime city centre concentrations of summation operator CuZnPb(PM10) were much higher (T0 > 450 ng m(-3)) than at the suburban site (T1 < 200 ng m(-3)). Rural site (T2) summation operator CuZnPb(PM10) concentrations exceeded 50 ng m(-3) when influenced by the megacity plume but dropped to 10 ng m(-3) during clean northerly winds. Nocturnal metal concentrations more than doubled at T0, as pollutants became trapped in the nightly inversion layer, but decreased at the rural site. Transient spikes in concentrations of different metals, e.g. a "copper event" at T0 (CuPM10 281 ng m(-3)) and "zinc event" at T1 (ZnPM10 1481 ng m(-3)) on the night of March 7-8, demonstrate how industrial pollution sources produce localised chemical inhomogeneities in the city atmosphere. Most metal aerosols are <2.5 microm and SEM study demonstrates the dominance of Fe, Ti, Ba, Cu, Pb and Zn (and lesser Sn, Mo, Sb, W, Ni, V, As, Bi) in metalliferous particles that have shapes including spherical condensates, efflorescent CuZnClS particles, cindery Zn, and Cu wire. Metal aerosol concentrations do not change in concert with PM10 mass, which is more influenced by wind resuspension than industrial emissions. Metalliferous particles can induce cell damage, and PM composition is probably more important than PM mass, with respect to negative health effects, so that better monitoring and control of industrial emissions would likely produce significant improvements in air quality.     

东北地区城市大气颗粒物中多环芳烃的污染特征

2008年4月至2009年1月期间,在东北三省(辽宁、吉林、黑龙江)设立30个观测点位,研究了东北城市大气颗粒物中PAHs的浓度水平、分布及来源.结果表明,不同季节14种PAHs总浓度的变化范围是16.3 ～712.1 ng/m3,呈冬季高、夏季低的季节变化特征；PAHs组成以4～5环化合物为主,3～4环化合物受温度的影响较大,表现出较强的季节波动；8个城市中抚顺和吉林PAHs污染最重,城市不同功能区中以工业区污染较重；燃煤和机动车尾气是区域PAHs的主要来源.     

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.     

Hydroxyl radical generation by electron paramagnetic resonance as a new method to monitor ambient particulate matter composition

Epidemiological studies have demonstrated the relationship between exposure to ambient particulate matter (PM) and health effects in those with cardiopulmonary diseases. The free radical generating activity of particles has been suggested as a unifying factor in the biological activity of PM in toxicological studies but so far has not been applied as a method for environmental monitoring of PM. The purpose of this study was to characterize hydroxyl radical (OH*) production by different size fractions of PM, to use as an alternative method for monitoring of PM composition and activity. We have developed a method, using electron paramagnetic resonance (EPR), to measure OH* radical formation in suspensions of particles in the presence of hydrogen peroxide and 5,5-dimethyl-1-pyrroline-N-oxide (DMPO) as a specific spin-trap. Samples of ambient particulate matter (PM) of different size fractions were collected from various sites on various filters. PM deposited on filters as well as suspensions in water retain its ability to generate OH* and this generation is determined by concentration of hydrogen peroxide and soluble metals. However, large variations in OH* radical formation and kinetics were found with different soluble metals and within metals (Fe, V) with different valencies. The method was applied to environmental monitoring in Hettstedt-Zerbst, situated in South-Eastern Germany, where it showed a relation to Cu-content of PM. The method was also applied in Duisburg, where the PMI fraction showed the highest DMPO-OH* generation but was not linked to particle counts. The method integrates metal bioavailability and reactivity and can provide a better understanding of the effect of small variations in mass concentrations on health.     

Molecular characterisation of organic material in air fine particles (PM10) using conventional and reactive pyrolysis-gas chromatography-mass spectrometry

Pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) was applied to study the composition of organic constituents in air particulate matter (PM10) collected inside an industrial area. A few milligrams of sampling filters containing air particles were pyrolysed at 700 degrees C directly (conventional) or after the addition of a derivatising reagent (tetramethylammonium hydroxide, TMAH, for pyrolysis-methylation; hexamethyldisilazane, HMDS, for pyrolysis-silylation). Py-GC-MS was also applied to synthetic polymers (poly(styrene-co-isoprene), polylimonene and polypinene) and vegetation samples (coniferous pollen, bark and resin) to identify markers indicative of possible precursors. Pyrolysates of PM10 showed the same suite of compounds in all the four seasons, dominated by hydrocarbons like styrene, limonene and clusters of isomeric alkenes with 14, 15 and 16 carbon atoms. Pyrolysis products of natural origin, including furaldehyde, benzeneacetonitrile, dehydroabietin and other diterpenoids were found, while no specific markers of synthetic rubbers were detected. The principal products released from reactive pyrolysis of PM10 were methyl or trimethylsilyl (TMS) derivatives of 1,6-anhydroglucose (levoglucosan), fatty acids, dehydroabietic acid and other resin acids along with hydroxy (di)carboxylic acids. Possible sources of the detected products (e.g. pine forest, biomass combustion) are discussed.     

Particle emission from heavy-duty engine fuelled with blended diesel and biodiesel

In this study, particulate matter (PM) were characterized from a place impacted by heavy-duty vehicles (Bus Station) fuelled with diesel/biodiesel fuel blend (B3) in the city of Londrina, Brazil. Sixteen priority polycyclic aromatic hydrocarbons (PAH) concentrations were analyzed in the samples by their association with atmospheric PM, mass size distributions and major ions (fluorite, chloride, bromide, nitrate, phosphate, sulfate, nitrite, oxalate; fumarate, formate, succinate and acetate; lithium, sodium, potassium, magnesium, calcium and ammonium). Results indicate that major ions represented 21.2% particulate matter mass. Nitrate, sulfate, and ammonium, respectively, presented the highest concentration levels, indicating that biodiesel may also be a significant source for these ions, especially nitrate. Dibenzo[a,h]anthracene and indeno[1,2,3,-cd]pyrene were the main PAH found, and a higher fraction of PAH particles was found in diameters lower than 0.25 μm in Londrina bus station. The fine and ultrafine particles were dominant among the PM evaluated, suggesting that biodiesel decreases the total PAH emission. However, it does also increase the fraction of fine and ultrafine particles when compared to diesel.     

Chemical Composition and Sources of PM10 and PM2.5 Aerosols in Guangzhou, China

Aerosol samples of PM10 and PM2.5 are collected in summertime at four monitoring sites in Guangzhou, China. The concentrations of organic and elemental carbons (OC/EC), inorganic ions, and elements in PM10 and PM2.5 are also quantified. Our study aims to: (1) characterize the particulate concentrations and associated chemical species in urban atmosphere (2) identify the potential sources and estimate their apportionment. The results show that average concentration of PM2.5 (97.54 μg m⁻³) in Guangzhou significantly exceeds the National Ambient Air Quality Standard (NAAQS) 24-h average of 65 μg m⁻³. OC, EC, Sulfate, ammonium, K, V, Ni, Cu, Zn, Pb, As, Cd and Se are mainly in PM2.5 fraction of particles, while chloride, nitrate, Na, Mg, Al, Fe, Ca, Ti and Mn are mainly in PM2.5-10 fraction. The major components such as sulfate, OC and EC account for about 70–90% of the particulate mass. Enrichment factors (EF) for elements are calculated to indicate that elements of anthropogenic origins (Zn, Pb, As, Se, V, Ni, Cu and Cd) are highly enriched with respect to crustal composition (Al, Fe, Ca, Ti and Mn). Ambient and source data are used in the multi-variable linearly regression analysis for source identification and apportionment, indicating that major sources and their apportionments of ambient particulate aerosols in Guangzhou are vehicle exhaust by 38.4% and coal combustion by 26.0%, respetively.     

克拉玛依市中心城区颗粒物中多环芳烃污染特征

在克拉玛依市中心城区布设4个采样点,在供暖期和非供暖期分别同步采集4个点位大气中不同粒径的颗粒物,采用HPLC进行分析并计算2个采样期内PM_(10)和PM_(2.5)中多环芳烃(PAHs)的浓度和种类。结果表明:中心城区供暖期PM_(10)中PAHs浓度为56.19 ng/m3,PM_(2.5)中PAHs浓度为48.85 ng/m3;中心城区非供暖期PM_(10)中PAHs浓度为18.86 ng/m~3,PM_(2.5)中PAHs浓度为14.53 ng/m~3。不同采样期PM_(10)和PM_(2.5)中PAHs浓度变化趋势相同,均为供暖期明显大于非供暖期。中心城区供暖期大气颗粒物吸附的PAHs以4环以下的组份为主,非供暖期则是5~6环的高环数组份偏多。分析结果表明克拉玛依市中心城区供暖期颗粒物中PAHs来源于燃煤排放叠加机动车排放,与中心城区集中供热锅炉关系密切;非供暖期则是以机动车排放污染为主。     

A Statistical Analysis of Particulate Data Sets for Jawaharlal Nehru Port and Surrounding Harbour Region in India

The concentrations of total suspended particulate matter (TSP) and particulate matter less than 10 microns (PM10) were measured at various locations in a Jawaharlal Nehru port and surrounding harbour region. Meteorological data was also collected to establish the correlation with air pollutant concentration. The results are analysed from the standpoint of monthly and seasonal variations, annual trends as well as meteorological effects. The monthly mean concentration of TSP was in the range of 88.2 to 199.3 microg m(-3). The maximum and minimum-recorded value of PM10 was 135.8 and 20.3 microg m(-3), respectively. The annual average concentration of PM10 was 66.1 microg m(-3). There are clear associations between TSP and PM10 data set at all the measured three sites with a correlation coefficient of 0.89, 0.69 and 0.81, respectively. PM10 data appears to be a constant fraction of the TSP data throughout the year, indicating common influences of meteorology and sources. Particle size analysis showed PM10 to be 47% of the total TSP concentration, which is lower than reported for industrial area and traffic junctions in Mumbai. Anthropogenic sources contribute significantly to the PM10 fraction in an industrial region, while contributions from natural sources are more in a port and harbour area. Statistical analysis of air quality data shows that TSP is strongly correlated with wind speed but weakly correlated with temperature. There appears to be a simple inverse relationship between TSP and wind speed data, indicating the dilution and transport by winds.     

TSP, PM depositions, and trace elements in the vicinity of a cement plant and their source apportionments using chemical mass balance model in Izmir, Turkey

Total suspended particles mass concentrations (TSP) and bulk depositions of particulate matter (PM depositions) were measured around a cement plant located in the multi-impacted area to assess the affect of the plant on the ambient air in the vicinity in Izmir, Turkey. TSP samples were collected five times a month whereas PM depositions were sampled monthly at four sites between August 2003 and January 2004. The concentrations of Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, V, and Zn in TSP and PM depositions (except Cu) were reported. Chemical mass balance (CMB) receptor model with local source profiles was run in order to calculate the source contributions of the PM sources to the concentrations of TSP, PM depositions, and trace elements. Traffic was found to be the major contributor to TSP whereas PM depositions dominantly result from area sources including several stone quarries, concrete plants, lime kilns, and asphalt plants in the region. CMB model results indicate that the cement plant is a significant contributor to TSP, PM depositions, and trace elements, particularly Cd.     

PM10 Concentration Measurements in Dublin City

Mass Concentration of ambient particulate matter with an aerodynamic diameter less than 10µm (PM10) are reported for the first time for a range of sites in Dublin City over a 6 month period from January 1st 1996 to June 30th 1996. PM10 gravimetric mass concentration measurements are made with low flow Partisol 2000 air samplers using an impaction type PM10 inlet and 47mm diameter glass fibre filters. In addition, much finer time resolution measurements (minimum sampling frequency of 30 minutes) are made using a tapered element oscillating microbalance (TEOM) PM10 mass monitor. These PM10 mass concentrations methods are also compared with mass concentration inferred using the standard black smoke method. Analysis of the ambient mass concentration data with reference to traffic density and meteorological influences are presented. Results for the first six months of 1996 show that the average PM10 values range from a high of 49 µg m-3 at the Dublin city centre site to 14 µg m-3 at one of the suburban sites. Intercomparison between PM10 and black smoke mass concentrations show that the relationship is site specific. Statistical analysis between PM10 levels and car traffic number show a positive correlation while a weak negative correlation is found between PM10 levels and rainfall amount, wind speed and air temperature.     

Concentration gradient patterns of aerosol particles near interstate highways in the Greater Cincinnati airshed

The objective of this study was to determine if there is an exposure gradient in particulate matter concentrations for people living near interstate highways, and to determine how far from the highway the gradient extends. Air samples were collected in a residential area of Greater Cincinnati in the vicinity of two major highways. The measurements were conducted at different distances from the highways by using ultrafine particle counters (measurement range: 0.02-1 microm), optical particle counters (0.3-20 microm), and PM2.5 Harvard Impactors (0.02-2.5 microm). The collected PM2.5 samples were analyzed for mass concentration, for elemental and organic carbon, and for elemental concentrations. The results show that the aerosol concentration gradient was most clearly seen in the particle number concentration measured by the ultrafine particle counters. The concentration of ultrafine particles decreased to half between the sampling points located at 50 m and 150 m downwind from the highway. Additionally, elemental analysis revealed a gradient in sulfur concentrations up to 400 m from the highway in a residential area that does not have major nearby industrial sources. This gradient was qualitatively attributed to the sulfate particle emissions from diesel engine exhausts, and was supported by the concentration data on several key elements indicative of traffic sources (road dust and diesel exhaust). As different particulate components gave different profiles of the diesel exposure gradient, these results indicate that no single element or component of diesel exhaust can be used as a surrogate for diesel exposure, but more comprehensive signature analysis is needed. This characterization is crucial especially when the exposure data are to be used in epidemiological studies.     

区域大气细颗粒物化学组分及来源年变化趋势

利用单颗粒气溶胶质谱仪(SPAMS)于2018年1月1日—2019年12月31日对上海市浦东新区环境空气PM_2.5开展高时间分辨化学成分监测。结果表明，2019年监测点空气质量总体优于2018年，AQI达标率由74.8%升高至86.6%。通过对PM_2.5成分分类，最终确定了8类颗粒物，相较于2018年，2019年富钾颗粒物升幅较为明显，左旋葡聚糖、重金属和元素碳有小幅增加，其余各组分相对减少。对PM_2.5排放源分类分析显示，机动车尾气源占比>25%，其中2018年3月、2018年7月、2019年2和3月贡献超过40%；二次无机源和燃煤源呈现一定的季节变化特点，整体秋冬季高于春夏季，2019年燃煤源占比较2018年下降了41%；工业排放源2018年5和10月、2019年1和5月占比相对较高，其余各月份占比相对较为稳定。     

南京市冬季大气颗粒态汞的分布特征

采集了南京市2012年冬季4个功能区的PM2．5、PM10、TSP样品，对不同粒径大气颗粒物中的颗粒态汞测试。结果表明，南京冬季大气颗粒物TSP中汞的质量浓度为49．26 pg/m3～257．14 pg/m3，平均质量浓度为161．27 pg/m3；PM10中汞的质量浓度为44．82 pg/m3～228．29 pg/m3，平均质量浓度为147．38 pg/m3；PM2．5中汞的质量浓度为35．98 pg/m3～178．58 pg/m3，平均质量浓度为104．10 pg/m3。不同功能区大气颗粒态汞质量浓度的分布趋势为：交通综合区＞旅游区＞住宿综合区＞商业区。大气颗粒态汞60％以上存在于可吸入肺的PM2．5中，细颗粒物富集汞的能力比粗颗粒物强。