Investigation of source locations and contributions using an integrated trajectory-source apportionment method with multiple time resolution data

Fine particulate matter (PM_2.5) and volatile organic compounds (VOCs) coexist in ambient air and contribute to adverse health effects in human populations. Thus, it is helpful to identify the contributions of air pollutants from different sources in order to design effective control strategies. Nevertheless, different sampling time schedules for VOCs and PM_2.5 result in difficulties for conventional receptor modeling. Additionally, a receptor model is unable to link the retrieved factors directly with actual source locations. To address these gaps, this study integrated back-trajectory data into an improved source apportionment model suitable for multiple time resolution data to estimate the locations of the regional transport-related factor. Within six potential source regions (PSRs) outlined by the above method, PSR 5 was suggested the primary one located near the industrial regions in the northeastern China. Constrained model results showed that the source contribution estimates with back trajectories passing over the PSRs were 3 and 9% of the selected VOCs and PM_2.5 mass, respectively.     

Air quality and elemental enrichment factors of aerosol particulate matter in Riyadh City, Saudi Arabia

Air particulate matter (PM) samples were collected from June 2006 to May 2007 for determination of chemical elements. PM samples were taken in two size fractions (PM_2.5 and PM₁₀) with MiniVolume air samplers on rooftops of various buildings (15–25 m above ground) in the city of Riyadh. The samples were subjected to X-ray fluorescence analysis to measure major (Na, Mg, Al, K, Ca, Si, P, S, and Fe) and trace elements (Mn, Ni, Cu, Zn, and Ba). The results showed that the PM concentrations were higher for PM₁₀ compared to PM_2.5, indicating that the major PM source was local dust. Also the spatial distribution with high PM concentrations was observed in the south and southeast of the city and the lowest levels were in the center and northeast of the city. This spatial distribution was attributed to different factors such as wind direction and velocity, emission from cement factories, and the presence of buildings, trees, and paved streets that reduce the amount of dust resuspended into the atmosphere. The air quality of the city was found to range from good to hazardous based on PM_2.5, and from good to very hazardous based on PM₁₀. The element-enrichment factors revealed two element groups according to their changing spatial behavior. The first group showed no significant spatial changes indicating they have the same common source. The second group (mainly S and Ni) exhibited significant changes as expected from anthropogenic inputs. The origin of S is possibly a combination of minerals (CaSO₄) and fossil fuel combustion. The source of Ni is probably from fossil fuel combustion.     

Chemical characterization and sources of PM2.5 at 12-h resolution in Guiyang,China

The increasing emission of primary and gaseous precursors of secondarily formed atmospheric particulate matter due to continuing industrial development and urbanization are leading to an increased public awareness of environmental issues and human health risks in China. As part of a pilot study, 12-h integrated fine fraction particulate matter (PM_2.5) filter samples were collected to chemically characterize and investigate the sources of ambient particulate matter in Guiyang City, Guizhou Province, southwestern China. Results showed that the 12-h integrated PM_2.5 concentrations exhibited a daytime average of 51 ± 22 µg m^?3 (mean ± standard deviation) with a range of 17–128 µg m^?3 and a nighttime average of 55 ± 32 µg m^?3 with a range of 4–186 µg m^?3. The 24-h integrated PM_2.5 concentrations varied from 15 to 157 µg m^?3, with a mean value of 53 ± 25 µg m^?3, which exceeded the 24-h PM_2.5 standard of 35 µg m^?3 set by USEPA, but was below the standard of 75 µg m^?3, set by China Ministry of Environmental Protection. Energy-dispersive X-ray fluorescence spectrometry (XRF) was applied to determine PM_2.5 chemical element concentrations. The order of concentrations of heavy metals in PM_2.5 were iron (Fe) > zinc (Zn) > manganese (Mn) > lead (Pb) > arsenic (As) > chromium (Cr). The total concentration of 18 chemical elements was 13 ± 2 µg m^?3, accounting for 25% in PM_2.5, which is comparable to other major cities in China, but much higher than cities outside of China.     

Geochemical features of aerosols in Santiago de Chile from time series analysis

Santiago, the capital of Chile, suffers from high air pollution levels, especially during winter. An extensive particulate matter (PM) monitoring and analysis program was conducted to quantify elemental concentrations of PM. Size-resolved PM samples (PM_2.5 and PM_10–2.5) from the La Paz and Las Condes stations in Santiago (2004–2005) were analyzed using ICP-MS. Most trace element concentrations (Cu, Pb, Zn, Mn, V, Sb, Pb and As) were higher during winter than during summer and were also higher at the La Paz station than at the Las Condes station. During the highest pollution events, As concentrations in PM_2.5 (16 ng m^?3) exceeded the annual average standard value (6 ng m^?3). A 10-year time series showed decreasing Pb and As concentrations and slightly increasing Zn, Cu and Mn concentrations. Concentrations of Cr and Ni remained relatively constant. The implementation of new public policies in 1998 may explain the decreasing concentrations of Pb and As. Enrichment factor (EF) calculations identified two principal groups: elements with EF < 10 (Mg, Y, Zr, U Sr, Ca, Ti, and V) and EF > 10 (Rb, K, Cs, Fe, P, Ba, Mn, Ni, Cr, Co, Zn, Sn, Pb, Cu, Mo, Cd, As, Ag, and Sb), which were related to natural and anthropogenic PM sources, respectively. Three main PM sources were identified using factor analysis: a natural source (crustal matter and marine aerosol), combustion and copper smelting. Three other sources were identified using rare earth elements: fluid catalytic crackers, oil-fired power production and catalytic converters.     

Coarse and fine particulates, Hg(p)-bound particulate concentrations and compositions study at Sha-Lu, central Taiwan

Ambient air and coarse, fine and particulate-bound mercury (Hg(p)) pollutants were collected and analyzed from March 17 to May 22 and September 3, 2009 to March 5, 2010 at a highway traffic site located in Sha-Lu, central Taiwan. This study has the following objectives: (1) to measure the coarse and fine particulates concentrations and the particulate-bound mercury Hg(p) which was attached to these particulate; (2) to determine the average Hg(p) compositions in coarse and fine particulates and (3) to compare the Hg(p) concentrations and compositions particulate in this study to the those obtained in other studies. The results obtained in this study indicated that the average ambient air PM_2.5, PM_2.5–10 and PM₁₀ were 18.79 ± 6.71, 11.22 ± 4.93 and 30.01 ± 10.27 μg/m³, respectively. The ranges of concentrations for Hg(p) in PM_2.5 were from 0.0016 to 0.0557 ng/m³, from 0.0006 to 0.0364 ng/m³ in PM_2.5–10 and from 0.0022 to 0.0862 ng/m³ in PM₁₀. In addition, the highest particle-bound mercury compositions in PM_2.5 were 16.85 ng/g and the lowest particle-bound mercury concentrations were 0.55 ng/g. The highest particle-bound mercury compositions in PM_2.5–10 were 13.88 ng/g and the lowest particle-bound mercury in PM_2.5–10 were 0.22 ng/g.     

Assessment of spatial variations of particulate matter (PM<Subscript>10</Subscript> and PM<Subscript>2.5</Subscript>) in Bahrain identified by air quality index (AQI)

The rapid urbanization, industrialization, modernization, and the frequent Middle Eastern dust storms have negatively impacted the ambient air quality in Bahrain. The objective of this study is to identify the most critical atmospheric air pollutants with emphasis on their potential risk to health based on calculated AQI (air quality index) values using EPA approach. The air quality datasets of particulate matters (PM₁₀ and PM_2.5), ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) were measured in January 2012 and August 2012 using five mobile air quality monitoring stations located at different governorates. The results of this study demonstrated that PM₁₀ and PM_2.5 are the most critical air pollutants in Bahrain with PM_2.5 prevailing during January 2012 and PM₁₀ prevailing during August 2012. The corresponding AQI categories were utilized to evaluate spatial variability of particulate matters in five governorates. The impact of meteorological factors such as ambient air temperature, wind speed, relative humidity, and total precipitation on ambient air quality were discussed. The analysis demonstrated that the highest PM₁₀ concentrations were observed in the Northern Governorate while the highest PM_2.5 concentrations were observed in the Capital, Central, and Northern Governorates during August 2012. It was observed that the levels of PM_2.5 pollution were higher within proximity of the industrial zone. The results suggested that the average PM_2.5/PM₁₀ ratio in August 2012 was lower than in January 2012 due to the Aeolian processes. This study concludes that higher wind speed, total precipitation, relative humidity rates, and lower ambient air temperature in January 2012 assisted with the dissipation of particulate matter thus lowering the pollution levels of both PM₁₀ and PM_2.5 in comparison to August 2012.     

Particulate matter source apportionment in Cairo: recent measurements and comparison with previous studies

This paper presents results of an atmospheric particulate matter (PM) monitoring and source apportionment study conducted during summer and fall 2010 in Cairo. These results are compared to those of similar studies in 1999 and 2002. Concentrations of PM_2.5 and PM₁₀ mass and their chemical constituents were determined and chemical mass balance modeling was conducted to estimate the source contributions to ambient PM. Emphasis was placed on characterizing the long-term trends in atmospheric lead (Pb) concentrations and their sources in Cairo. PM_2.5 and PM₁₀ concentrations were highest during fall 1999 at four of the five study sites. This was also the case for open (vegetative/trash) burning contributions, which showed a smaller increase during fall 2010. Burning of agricultural waste after the fall harvest continues to be a major source of PM in Cairo. Both PM_2.5 and PM₁₀ mass decreased dramatically at Shobra, an industrial site, from 1999 to 2010. A reduction of lead smelting has resulted in a decrease of ambient Pb concentrations of up to two orders of magnitude from 1999 to 2010 at Shobra, El-Zamalek, and El-Qualaly. From 1999 to 2010, the mobile source contribution has been relatively stable at most of the study sites. Future efforts to reduce ambient PM should focus on controlling emissions from motor vehicles and open burning and implementing mitigation strategies for reducing resuspended road and construction dust.     

The characteristics of air pollutants during different seasons in the urban area of Lanzhou,Northwest China

Based on data from ground-based air quality stations, space–time variations of six principal atmospheric pollutants, such as particulate matter (PM_2.5 and PM₁₀) and gas pollutants (SO₂, NO₂, СО, and O₃), obtained from January 1, 2014 to December 31, 2017 in the city of Lanzhou, have been studied. Average total concentrations of PM_2.5 and PM₁₀ were 53.2?±?26.91 and 124.54?±?82.33 µg/m³, respectively; however, the results showed that in 75.53% and 84.85% days, concentrations of these pollutants exceeded Chinese National Ambient Air Quality Standard and in 100% days exceeded World Health Organization guidelines standards. Daily mean values of aerosol optical depth and Ångström exponent based on data, received by satellite Moderate Resolution Imaging Spectroradiometer, show a broad range of values for aerosol optical depth (from 0.018 to 1.954) and Ångström exponent (from 0.003 to 1.8). Results of principal components analysis revealed three factor loadings. Thus, Factor 1 has the relevant loadings for PM_2.5, PM₁₀, CO, SO₂, and NO₂ (36%) and closely associated with transport emissions and industrial sources, which contribute to air pollution in Lanzhou. Factor 2 was heavily loaded with temperature and visibility (16.94%). Factor 3 consisted of relative humidity (14.11%). Cluster analysis revealed four subgroups: cluster 1 (PM_2.5, NO₂, SO₂), cluster 2 (CO), cluster 3 (PM₁₀) and cluster 4 (relative humidity, visibility, temperature, O₃, wind speed), which were compliant with results, obtained from principal components analysis. Positive correlation was found among all pollutants, other than O₃. According to processed backward trajectories obtained by Hybrid Single-Particle Lagrangian Integrated Trajectory model, it was found that movement of air masses occur from north, northwest, and west directions—the location of principal natural sources of aerosols.     

广州市大气颗粒物PM2.5显微形貌特征和来源解析

PM_2.5是近年来影响我国城市大气环境的首要污染物,其成因机制复杂。本文采用扫描电镜和ICP-MS研究了广州市大气颗粒物PM_2.5的显微形貌及其化学组成特征,并应用富集因子法进行源解析。结果表明,PM_2.5的颗粒形态以无定形态为主;主要物质表现为含Fe、Mg、Al、K、Na的硅酸盐组合,具有道路扬尘、建筑施工排放等一次粒子特征;单个无定形颗粒物能谱表现出硫酸盐+硝酸盐的组合特征,为汽车尾气所排放的前体污染气体NO_x和SO₂进入大气环境中,在特定的物理化学条件下通过成核作用发生相态改变所形成的二次粒子。PM_2.5中高度富集Cd、Se、Zn、Cu、Pb、As等重金属,异常富集的Br主要为当地普遍使用的阻燃剂十溴联苯醚和拆解电子垃圾所致,稀土元素的浓度在0.022~0.582 ng/m³之间,具有重稀土元素富集的特征。这些特征反映出广州市PM_2.5颗粒物的组成既有一次粒子,也有二次粒子,物质来源具有多重性。     

Assessment of air quality during 19th Common Wealth Games at Delhi, India

The 19th Common Wealth Games was organized at Delhi, India, during October 3 to 14, 2010, where more than 8,000 athletes from 71 Commonwealth Nations have participated. In order to give them better environment information for proper preparedness, mass concentrations of particulate matters below 10 microns (PM₁₀) and 2.5 microns (PM_2.5), black carbon (BC) particles and gaseous pollutants such as carbon monoxide (CO) and nitrogen oxide (NO) were monitored and displayed online for ten different locations around Delhi, including inside and outside the stadiums. This extensive information system for air quality has been set up for the period from September 24 to October 21, 2010, and data have been archived at 5-min interval for further research. During the study period, average concentration of PM₁₀ and PM_2.5 was observed to be 229.7 ± 85.5 and 112.1 ± 56.0 μg m^?3, respectively, which is far in excess of the corresponding annual averages, stipulated by the national ambient air quality standards. Significant large and positive correlation (r = 0.93) between PM₁₀ and PM_2.5 implies that variations in PM₁₀ mass are governed by the variations in PM_2.5 mass. The mass concentrations of PM_2.5 inside the stadium were found to be ~18 % lower than those outside; however, no large variations were observed in PM₁₀. Mean concentrations of BC, CO and NO for the observation period were 10.9 μg m^?3 (Min, 02 μg m^?3; Max, 31 μg m^?3), 1.83 ± 0.89 ppm (Min, 0.48 ppm; Max, 4.55 ppm) and 37.82 ppb (Min, 2.4 ppb; Max, 206.05 ppb), respectively. BC showed positive correlation (r = 0.73) with CO suggests unified source for both of them, mainly from combustion emissions. All the measured parameters, however, show a significant diurnal variation with enhanced peaks in the morning and late night hours and lower values during daytime.     

The emission and vertical flux of particulate matter <10 μm from a disturbed clay-crusted surface

Arid and semi‐arid environments are important sources for the atmospheric loading of PM₁₀ (particulate matter <10 μm), although the emission of this material is often limited by surface crusts. This study investigates the emission and vertical flux of PM₁₀ from a clay‐crusted playa, with and without saltating grains to abrade the surface. Using a portable field wind tunnel, it was found that, despite disturbance to the surface, the emission of PM₁₀ decays rapidly without abrasion. Only in the presence of saltating grains was PM₁₀ continuously liberated from the surface, such that the emission rate (the total amount of PM₁₀ emitted from the surface expressed as a horizontal flux) varied linearly with the saltation transport rate. Although the emission of PM₁₀ was found to depend on saltation abrasion, past studies have tended to focus on the relationship between the vertical flux of PM₁₀ (the amount of PM₁₀ being transported vertically through the boundary layer) and the shear velocity. In this study, the vertical flux of PM₁₀ was found to vary with the shear velocity to the power of 2·14. Although the vertical PM₁₀ flux is a proportion of the emission rate (the horizontal flux), no statistically significant relationship was observed between the emission rate and the shear velocity. The disparity of these results is explained by the lack of a consistent relationship between the shear velocity and the saltation transport rate in this supply‐limited environment. This suggests that the observed relationship between the vertical PM₁₀ flux and the shear velocity is a spurious correlation, resulting from the use of shear velocity to calculate the vertical dust flux. It is thus concluded that shear velocity is not an appropriate variable for emission modelling in supply‐limited environments and that improvements in dust emission modelling will only be realized if the abrasion process is the focus of a concerted research effort.     

Experimental and numerical analyses of particulate matter concentrations in underground subway station

The purpose of this paper was to perform the experimental and numerical analyses of PM₁₀ and PM_2.5 concentrations in Imam Khomeini (IKH) underground subway station in Tehran. The aim was to provide fundamental data in order to fulfill workers and passengers respiratory health necessities. Experimental measurements was done at three different locations (entrance, middle and exit) inside the platform and also outdoor ambient of the station. The Dust-Trak was applied to measure continuous PM_2.5 and PM₁₀ concentrations at a logging interval of 30 s. The measurements were recorded during rush hours (8:00 am–12:00 pm) for one week per each season from June 2015–June 2016.Moreover, computational fluid dynamic (CFD) simulation was done for the platform of the above station and the necessary boundary conditions were provided through field measurements. Those basic parameters which were considered for numerical analysis of particulate matters concentrations included air velocity, air pressure and turbulence. Furthermore, the piston effect caused by train movement inside the station provided natural ventilation in the platform. The results showed that seasonal measured PM_2.5 and PM₁₀ indoor concentrations had a variety range from 40–98 µg/m³ to 33–102 µg/m³, respectively, and were much higher than national indoor air quality standard levels. Meanwhile, PM_2.5 and PM₁₀ concentrations in the IKH underground subway station were approximately 2.5–2.9 times higher than those in outdoor ambient, respectively. Numerical simulation indicated that the predicted concentrations were underestimated by a factor of 8% in comparison with the measured ones.     

Temporal analysis of air pollution and its relationship with meteorological parameters in Bahrain, 2006–2012

The objective of this paper is to analyze temporal and seasonal trends of air pollution in Bahrain between 2006 and 2012 by utilizing datasets from five air quality monitoring stations. The non-parametric and robust Theil-Sen approach is employed to study quantitatively temporal variations of particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃). The calculated annual concentrations for PM₁₀ and PM_2.5 in Bahrain were substantially higher than recommended World Health Organization (WHO) guideline standards. Results showed increasing trends for PM₁₀, PM_2.5, and SO₂ whereas O₃ and its precursor NO₂ showed decreasing behavior. The general increase in air pollution trends is in agreement with prediction of air pollution models for Middle East region due to economic growth, industrialization, and urbanization. The significances of long-term trends were examined. Additional to actual (unadjusted) trends, meteorological adjusted (deseasonalized) trends and seasonal trends were quantified. The box-plot analysis visually illustrated monthly variations of key air pollutants. It showed that only PM₁₀ and PM_2.5 exhibited seasonal pattern, and their concentrations increased during summer and decreased during winter. The effects of ambient air temperature, relative humidity, wind speed, and rainfall on particulate matter (PM) concentrations were further investigated. The Spearman correlation coefficient results demonstrated significant negative correlation between relative humidity and PM concentrations (??0.595 for PM₁₀ and ??0.526 for PM_2.5) while significant positive correlation was observed between temperature and PM concentrations (0.420 for PM₁₀ and 0.482 for PM_2.5).     

A study of PM<Subscript>2.5</Subscript> and PM<Subscript>10</Subscript> concentrations in the atmosphere of large cities in Gansu Province,China, in summer period

Due to rapid economic growth of the country in the last 25 years, particulate matter (PM) has become a topic of great interest in China. The rapid development of industry has led to an increase in the haze created by pollution, as well as by high levels of urbanization. In 2012, the Chinese National Ambient Air Quality Standard (NAAQS) imposed ‘more strict’ regulation on the PM concentrations, i.e., 35 and 70 μg/m³ for annual PM_2.5 and PM₁₀ in average, respectively (Grade-II, GB3095-2012). The Pearson’s correlation coefficient was used to determine the linear relationship of pollution between pollution levels and weather conditions as well as the temporal and spatial variability among neighbouring cities. The goal of this paper was to investigate hourly mass concentration of PM_2.5 and PM₁₀ from June 1 to August 31, 2015 collected in the 11 largest cities of Gansu Province. This study has shown that the overall average concentrations of PM_2.5 and PM₁₀ in the study area were 26 and 66 μg/m³. In PM_2.5 episode days (when concentration was more than 75 μg/m³ for 24 hrs), the average concentrations of PM_2.5 was 2–3 times higher as compared to non-episode days. There were no observed clear differences during the weekday/weekend PM and other air pollutants (SO₂, NO₂, CO and O₃) in all the investigated cities.     

Elements’ Geochemical Characteristics of PM10 and PM2.5 in Beijing During Winter and Spring

From 2012 to 2013, heavy haze frequently hit Beijing in spring and winter. The fine atmospheric particulates can be inhaled by people, and remain in the respiratory tract and lung for quite a long time. The heavy metal elements in the particles are harmful, and even carcinogenic to human bodies. Therefore, it is necessary to master the geochemical characteristics and the temporal and spatial distribution of the heavy metal elements in atmospheric particles. The atmospheric particulates (TSP/PM₁₀/PM_2.5) were collected by using TH1500C intelligent medium volume (80~120 L/min) air samplers in the five functional areas and suburbs of Beijing, respectively in January 2013 (heating period) and April 2013 (non-heating period). The five functional areas were: building materials factory area, residential area, education area, business area and recreation area, each functional area having three sampling sites, and five in suburbs. The sampling height was 1.5 m above the ground and the distance of the sampling sites to roads exceeded 50 m so as to avoid excessive impact of vehicle exhaust emissions. These samples were analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), Inductively Coupled Plasma Optical Emission Spectrometer(ICP-OES)and Atomic Fluorescence Spectrometer (AFS), by which 21 elements including Al, Fe, Mn, As, Hg, Cd, Cr were tested. Based on the comparisons of the concentration and element content variation of atmospheric particulates of these functional areas in and after the heating period, the spatial distribution of atmospheric particulates and the influence of coal combustion on the concentration and composition of atmospheric particulates were revealed. The elements sources of atmospheric particulates were also discussed by computing the enrichment factor of the elements, providing a scientific basis for the air contaminant treatment in Beijing. The results showed that the total concentration of the 21 elements of PM₁₀ and PM_2.5 in the functional areas of Beijing in winter was higher than that in spring, the most marked among them being the business area. In winter, the concentration of pollution elements in the building materials factory area and the business area in Beijing was extremely high, and the residential area, education area, recreation area and suburbs where people live were much better, among which the education area was the best. The concentration change of particulates in suburbs was quite smaller in winter and spring than that of the urban area. It also showed that the concentrations of Cd, Cr, As and Hg in PM₁₀ increased by 233%,306%,298%,141%,respectively and the increase in PM_2.5 was 442%、309%、310%、256%, respectively. These abovementioned elements show a tendency to accumulate mainly in PM_2.5 whose concentrations in winter were significantly higher than those in spring. It indicates that coal heating during winter makes great contributions to the polluting elements in atmosphere and the main polluting particulates are Cd, As and Hg.     

北京市区春季交通源大气颗粒物污染水平及其影响因素

文中以PM_(2·5)和PM_(10)为研究对象,于2005年3月13日至19日前后6d的时间内,在成府路东口、前门2个地区设立采样点,研究分析了北京市春季交通源大气颗粒物的污染水平及其影响因素。研究表明:(1)PM_(2·5)和PM_(10)的质量浓度存在明显的日变化规律,在工作日所测得的PM_(2·5)和PM_(10)的质量浓度值要高于在周末所测得的质量浓度值;(2)PM_(2·5)和PM_(10)的质量浓度存在明显的时变化规律,在7:00~9:00,19:00~21:00和23:00之后,PM_(2·5)和PM_(10)的质量浓度分别达到三个峰值;(3)PM_(2·5)和PM_(10)的质量浓度随着温度的变化而存在明显的变化规律,PM_(2·5)和PM_(10)质量浓度的最大值与低温(0~5℃)有关,而PM_(2·5)和PM_(10)质量浓度的最小值在高温(11~15℃)时被观察到;(4)PM_(2·5)和PM_(10)的质量浓度的最大值与高湿度值(36%~46%)有关,而PM_(2·5)和PM_(10)质量浓度的最小值在低湿度值(11%~25%)时被观察到;(5)通过对成府路东口、前门采样点颗粒物浓度与风级比较,发现二者呈明显的反相关关系,由此可见,风力大小对特定区域的颗粒物浓度起决定性作用;(6)与国外一些城市的PM_(10)的污染水平相比,在北京成府路东口、前门所测得的PM_(10)的质量浓度都要比国外一些城市高,由此可见,汽车尾气仍是北京市区大气颗粒物的主要来源之一。     

北京市PM_(2.5)中主要重金属元素污染特征及季节变化分析

利用2005年4月18日—2008年9月27日北京市中国地质大学(东门)采样点的PM2.5质量浓度变化与重金属Cd、Pb、As、Cu及Zn等污染特征,结合最新发布的《环境空气质量标准》(GB3095—2012),初步分析了近4年时间里北京市单点PM2.5的污染水平及主要重金属污染元素的变化特征,得出了一些有意义的认识。2005年春季—2008年春季期间PM2.5质量浓度为13.1～171μg/m3之间变化,平均浓度为65.6μg/m3,超过最新环境空气质量标准制定的PM2.5年平均浓度限值35μg/m3,北京市PM2.5污染形势依然严峻。奥运会及残奥会期间PM2.5的24 h质量浓度平均值为40.7μg/m3,没有超标。北京市PM2.5中的重金属元素含量及富集特征随着不同年份不同季节差别较大,典型的城市污染元素As在冬季质量浓度最高。对比环境空气质量标准的参考浓度限值发现,As元素的质量浓度在研究期间的年均值均超过了年平均浓度参考限值0.006μg/m3。化学分析结果显示人为污染是PM2.5中Cu、Cd、Pb、Zn、As重金属污染的主要来源,其中As污染需要引起足够重视。研究结果对于北京市大气污染防治具有一定的借鉴意义。     

Ambient air quality of Kathmandu valley as reflected by atmospheric particulate matter concentrations (PM10)

This paper presents the analysis and interpretation of ambient particulate matter concentrations measured as PM₁₀ at a network of six air monitoring stations in Kathmandu valley during the years, 2003 through 2005. The purpose was to understand the pollution trends associated with different areas considering levels particulate matter concentrations representing the ambient air quality of Kathmandu valley. The study indicate that particulate concentrations (PM₁₀) measured are persistently higher at air sampling sites representing roadside areas compared to the background sites. The inter-station network variability with respect the particulate pollution suggests optimizing resources. The comparison of annual average PM₁₀ concentration observed at six air-monitoring sites in Kathmandu Valley with standard annual average concentration prescribed by World Health Organization as well as Europe Union indicates serious PM₁₀ pollution in Kathmandu valley.     

Spatio-temporal variations of respirable particles at residential areas located in the vicinity of opencast coal projects,India: a case study

The objective of the study is to investigate spatio-temporal variations of PM₁₀, PM_2.5, and PM₁ concentrations at seven residential sites, located in the vicinity of opencast coal projects, Basundhara Garjanbahal Area (BGA), India. Meteorological parameters such as wind speed, wind direction, relative humidity, and temperature were collected simultaneously with PM concentrations. Mean concentrations of PM₁₀ in the range 215 ± 169–526 ± 412 μg m^?3, PM_2.5 in the range of 91 ± 79–297 ± 107 μg m^?3, PM₁ in the range of 68 ± 60–247 ± 84 μg m^?3 were obtained. Coarse fractions (PM_2.5–10) varied from 27 to 58% whereas fine fractions (PM_1–2.5 and PM₁) varied in the range of 51–73%. PM_2.5 concentration was 41–74% of PM₁₀ concentration, PM₁ concentration was 31–62% of PM₁₀ concentration, and PM₁ concentration was 73–83% of PM_2.5 concentration. Role of meteorology on PM concentrations was assessed using correlation analysis. Linear relationships were established among PM concentrations using least square regression analysis. With the aid of principal component analysis, two components were drawn out of eight variables, which represent more than 75% of variance. The results indicated that major sources of air pollutants (PM₁₀, PM_2.5, PM₁, CO, CO₂) at the residential sites are road dust raised by vehicular movement, spillage of coal generated during transportation, spontaneous combustion of coal, and biomass burning in village area.     

Characterisation of aerosol from Santiago,Chile: an integrated PIXE–SEM–EDX study

Santiago de Chile is a big city with huge air quality problems, being one of the most polluted cities in the world. This is aggravated during winter by the topography and meteorological conditions of the city. Although public policies have been developed to minimise the atmospheric aerosol pollution, there is a lack of adequate knowledge and poor characterisation of these aerosols (in its PM_2.5 and PM₁₀ fractions). In this study we sampled atmospheric particles during winter in two distinct areas of Santiago: downtown (Teatinos Street) and in a more residential area (Macul). Major (Si, Al, Fe, Ca and K) and some trace element (S, Cl, Ti, P, Cr, Cu and Zn) compositions were obtained by proton-induced X-ray emission (PIXE). Morphological, type and chemical characterisation was also performed using scanning electron microscopy (SEM) coupled with an energy dispersive X-ray microanalysis system (SEM–EDX). Besides the carbon particles, the contribution of which can be quite important in the atmospheric aerosol, especially in downtown, unambiguously lithogenic (i.e. of geological origin) particles and elements are the second highest contributors. Enrichment factor calculation, together with particle identification and element correlation allow the origin of some elements and particles to be traced, revealing anthropogenic origins for some of them that are specific to the Santiago area.