奥运会及残奥会期间北京市区大气颗粒物污染特征及微观形貌类型

2008年8月和9月,北京市成功举办了第29届奥运会和第13届残奥会,对这段时间在北京市区(中国矿业大学校园综合楼五层,距奥运村3 km)采集的大气颗粒物的质量浓度和微观形貌类型进行了研究。结果表明:奥运会期间,北京市区大气PM10和PM2.5的日均质量浓度分别小于国家PM10二级标准(150μg/m3)和美国EPA的PM2.5二级标准(65μg/m3),12 h的质量浓度范围分别为7.64~81.63μg/m3和1.91~54.59μg/m3;残奥会期间,12 h的PM10质量浓度范围为33.83~106.36μg/m3,没有超标,PM2.5质量浓度变化范围为15.29~88.30μg/m3,其中出现了3 d超标天,分别为9月6日、7日和14日;从奥运期间PM2.5/PM10的比值(0.26~0.86,大部分值大于0.5)可以看出,奥运期间北京大气颗粒物以细粒子为主。与往年相比,颗粒物质量浓度出现大幅下降趋势。场发射扫描电镜观察显示,奥运会和残奥会期间样品的微观形貌类型主要有球形颗粒、烟尘集合体、不规则矿物和未知颗粒,其数量-粒径分布主要呈单峰分布,峰值均在0.1~0.2μm范围,其中球形颗粒明显占多数。各种分析数据均显示,残奥会期间样品比奥运会期间样品污染要严重。     

华北平原典型工业城市秋、冬季大气细颗粒物污染特征

济宁市是位于华北平原大气污染传输通道上的工业城市,为研究其秋、冬季细颗粒物(PM2.5)的污染特征,在市区的3个站点进行了PM2.5的同步滤膜采样。采样期为2018年10月15日至2019年1月31日,涵盖非采暖期和采暖期(自2019年11月15日始),共270个小流量滤膜样品。研究结果表明,济宁市秋、冬季PM2.5平均质量浓度为(98.9±48.8)μg/m³,采暖期PM2.5质量浓度(107.1±52.8)μg/m³显著高于非采暖期(77.4±27.8)μg/m³。PM2.5的化学组成以二次无机气溶胶、有机碳和元素碳为主,占比分别为52.4%、10.9%和7.5%。S、Cl、K、Ca、Fe和Si元素平均质量浓度之和占元素总平均质量浓度的78.8%,是PM2.5中的主要元素。采暖期PM2.5的主要化学组分质量浓度显著高于非采暖期。二次有机碳是有机碳的重要来源,占比78.9%。PM2.5中Zn和Pb的富集因子较高,说明燃煤及相关工业对PM2.5中重金属的贡献较为显著,ρ(NO3^?)/ρ(SO4^2?)比值分析表明,济宁市整体受流动源影响较大。本研究可为查明华北平原典型工业城市的PM2.5污染来源成因提供依据。     

北京市区春季燃烧源大气颗粒物的污染水平和影响因素

以大气中PM2.5和PM10为研究对象,于2005-03-13—25共7天的时间内,在中国地质大学(北京)测试楼顶、首钢焦化厂和首钢东门设立3个采样点进行采样监测。结果表明:PM2.5和PM10质量浓度的日变化呈现一定规律性,在不同时段PM2.5和PM10的质量浓度不尽相同,且变化较大,在特定时刻出现峰值,主要受污染源排放和气象因素的控制;PM2.5和PM10质量浓度随气温的升高而降低,这与高温有利于颗粒物扩散、低温容易形成逆温层有关;在一定的相对湿度范围内(以大气中水汽不发生重力沉降为界限),PM2.5和PM10质量浓度与相对湿度呈正相关关系;而当发生降水时,由于水滴的冲刷和附带作用,PM2.5和PM10质量浓度降低;PM2.5和PM10质量浓度与风级呈明显的负相关关系。通过北京市与国内8个省会城市的PM2.5和PM10质量浓度的对比,发现北京市PM2.5和PM10污染比较严重,PM2.5和PM10质量浓度分别超过了1996年中国制定的PM10排放标准和1997年美国EPA制定的PM2.5排放标准。     

安徽省大气颗粒物污染特征分析

对2016年全年颗粒物监测浓度数据进行统计分析,得到了安徽省颗粒物污染的空间分布、浓度和粒径,以及污染传输特征。结果表明,淮河以北、沿江和江淮之间、长江以南和皖南山区城市颗粒物污染随地理位置不同表现出明显的区域化特征,污染程度由北向南减轻,污染过程明显表现出由北向南逐步扩散传输的规律,污染程度越重,污染深入南方的范围越广,持续时间也越长。冬季污染较重的城市,上午出现明显的高浓度时段,全天变化为“双峰双谷”型。夏、秋季节夜间细颗粒物(PM2.5)浓度贡献比增加。PM2.5与PM10(可吸入颗粒物)质量浓度比值冬季最高,春季较低。污染重的城市冬季PM2.5占比高。     

榆林市城区春季环境空气中PM10与 PM2.5污染特征分析

分析榆林市城区春季环境空气污染特征,选取榆林市红石峡(J1)、环保监测大楼(J2)、实验中学(J3)、世纪广场(J4)4个大气自动监测点,分别进行 PM10与 PM2.5的分析。结果表明,与国内其他大中型城市相比,榆林市PM10、PM2.5为轻度污染,ρ( PM2.5)/ρ( PM10)小于50%,属于粗颗粒物污染型;4个监测点 PM10和 PM2.5的日均浓度变化趋势基本一致,呈波峰、波谷变化,但浓度在区域分布上表现略有差异;小时浓度均呈现较明显的双峰变化趋势,上午和夜间各出现一个峰,而下午浓度变得相对较低。     

贵阳城区大气污染物的时空变化和复合污染特征

选取贵阳市10个空气质量监测站发布的PM2.5、PM10、SO2、NO2、CO和O3实时浓度数据，通过时间序列分析法和插值法研究贵阳市大气污染物的时空变化和复合污染特征。结果表明:（1）贵阳市2014-2018年主要污染物PM2.5和PM10的年平均浓度逐渐下降，光化学污染物O3年平均浓度有所增加，空气质量逐渐转好，环境治理取得明显效果；（2）2018-2019自然年PM2.5、PM10、NO2和O3在春季污染最严重，SO2和CO在冬季污染最严重，反映出污染源、阶段性燃料燃烧和二次离子生成等因素对不同污染物的影响不同；（3）PM2.5和PM10日变化特征为“午峰晚峰”型，峰值发生的时间因季节而异，主要由不同季节人类作息的起止时间不同所致，O3日变化为单峰型，夜间O3浓度较低，从早晨8:00点开始随着太阳辐射的增大和温度的升高，在15:00-16:00点左右达到峰值；（4）PM2.5的空间分布呈现出部分郊区和工业区较高，市中心居民区较低的特征，指示城市建设向郊区推进。O3浓度呈现出市区低、郊区高的空间分布特征，反映郊区植被覆盖好，释放的天然源VOCs促进了O3生成；（5）主要污染物O3与颗粒物PM2.5和PM10在春季造成的复合污染最为严重，在夏季O3与PM10造成一定程度的复合污染，在秋冬季O3浓度最低，O3与颗粒物不产生复合污染；一天之内同一时刻O3与颗粒物不会产生叠加从而造成复合污染。      

超低排放燃煤电厂一次颗粒物和黑碳实时排放特征

燃煤电厂是大气一次污染物的重要排放源,其超低排放改造改变了大气颗粒物排放特征。为满足当前高时间分辨率排放清单构建的需要,燃煤电厂颗粒物实时排放质量浓度及关键组分比值亟需更新。本研究基于稀释通道采样系统,对某超低排放改造后的燃煤电厂开展实测,获得该燃煤电厂可吸入颗粒物(PM10)、细颗粒物(PM2.5)、超细颗粒物(PM1.0)和黑碳(BC)的实时排放质量浓度,更新各污染物排放因子,分析PM1.0/PM2.5、PM2.5/PM10和BC/PM2.5质量浓度比值(文中以上比值均为质量浓度比值)日变化。结果表明,上述污染物排放平均质量浓度分别为(5.0±6.0)mg/m^3、(5.0±5.9)mg/m^3、(4.9±5.9)mg/m^3和(36.6±28.3)μg/m^3;对应的排放因子分别为0.03 kg/t、0.03 kg/t、0.03 kg/t和0.2 mg/kg。该燃煤电厂颗粒物排放质量浓度表现出明显的日间变化,高值时段(20:30至次日10:30)PM2.5平均质量浓度是低值时段(10:30~20:30)的12.2倍,推测可能与不同时段的污染控制措施效率变动有关。作为不完全燃烧的产物,黑碳排放高值时段(06:00~12:00和14:30~19:00)的质量浓度是低值时段(00:00~05:00)相应值的1.5~2.4倍,推测与煤的添加和锅炉燃烧效率有关。颗粒物及组分质量浓度的日变化在构建高时间分辨率排放清单时需予以考虑。本研究实测所得PM2.5/PM10和BC/PM2.5比值分别为1.00±0.01和0.03±0.04,均远高于清单编制技术手册中推荐的燃煤电厂相应比值0.3和0.002,采用现有清单编制技术手册的相应比值可能低估了燃煤电厂细颗粒物和黑碳排放,需引起重视。     

砣矶岛国家大气背景站PM_(2.5)化学组成及季节变化特征

首次在位于渤海海峡中部的砣矶岛国家大气背景监测站连续采集大流量PM2.5样品,对2011年12月至2012年12月期间的65个样品进行了分析,包括质量浓度、有机碳、元素碳、水溶性离子、无机元素等。结果表明,砣矶岛PM2.5的年均质量浓度为54.6μg/m3(17.3~143.8μg/m3),超过国家空气质量标准(35μg/m3)。在季节变化上表现为春季与夏季高(平均浓度分别为73.6μg/m3与60.7μg/m3),分别受沙尘和山东半岛生物质燃烧的影响,而冬季最低(39.0μg/m3),与渤海地区冬季频降暴雪有关。PM2.5中24SO?、OM、3NO?、MMO是最主要的成分,分别占PM2.5质量的18.8%、16.5%、10.8%和9.4%,其次为4NH?(3.5%)和EC(3.3%)。砣矶岛PM2.5的组成较好地反映了颗粒物的主要来源及其季节变化特征,如:春季样品中Fe、Ca与Mg含量最高,与春季北方地区普遍受沙尘影响有关;夏季较高的K+浓度与OC/EC比值反映夏季风影响下山东半岛生物质燃烧对砣矶岛PM2.5的重要贡献;夏季24SO?与3NO?的异常浓度反映了二次气溶胶形成的普遍特征。此外,较高的Na+浓度与V/Ni比值表明海盐和船舶废气对砣矶岛PM2.5有一定影响。     

甘新城市大气挥发性有机物和颗粒物的污染特征及健康风险评估北大核心CSCD

基于质子转移反应质谱仪(PTR-MS)和颗粒物(PM)采集和分析技术,对我国西北甘肃省和新疆维吾尔自治区(甘新地区)十三个城市大气中的挥发性有机物(VOCs)、PM(PM10、PM2.5和PM1)及其组分(水溶性无机离子、碳质气溶胶和无机元素)进行了采样分析,阐明了甘新地区城市大气中VOCs和PM的污染特征和健康风险。研究表明:污染特征分析表明平均总VOCs(TVOCs)浓度为(41.84±7.56) ppbv(ppbv为十亿分之一的体积混合比),氧化性VOCs(OVOCs)是VOCs的重要组分,VOCs组分总浓度高于国内外其他城市,主要为甲醇的浓度较高,而芳香烃则低于其他城市。PM10、PM2.5和PM1的平均浓度分别为(139.39±32.63)μg·m-3、(77.66±25.39)μg·m-3和(44.76±17.59)μg·m-3,水溶性无机离子(WSIIs)是该地区PM的重要组分。健康风险评估表明该地区VOCs的非致癌风险显著,致癌风险处于可接受水平;PM中重金属的非致癌风险和致癌风险均显著。乙醛的非致癌风险和萘的致癌风险较高,Mn的非致癌风险和As的致癌风险较高,因此应加强乙醛、萘、Mn和As元素的管控,以减少大气污染对人体健康的危害。     

黑龙江省松嫩平原南部大气颗粒物地球化学特征及来源解析

研究采集了黑龙江松嫩平原南部28个夏季大气颗粒物样品,分析了不同粒径(TSP、PM10、PM2-5)样品中常量和微量元素含量,对元素浓度含量特征、元素间相关性和空间分布特征进行了分析,并使用富集系数法和因子分析法进行元素来源解析。研究表明：在PM10-100中富集的元素多在地壳中含量很高,重金属元素在PM2-5中高度富集,不同粒径大气颗粒物中各元素质量浓度整体水平为：大庆>绥化>哈尔滨>齐齐哈尔。富集因子分析表明：Fe、K、Ti、Mn、Co的富集因子小于1或非常接近1,Ca、Mg、Ni、Cr的富集因子大于1但仍小于10,Na、Zn、Cu、Cd、Pb、Se的富集因子大于10,表现出较为明显的人为来源特征。参照颗粒物不同源主要标识元素,对各元素进行主因子分析结果表明：松嫩平原南部大气可吸入颗粒物的主要来源是土壤扬尘,此外还有燃煤、垃圾焚烧、汽车尾气、碱尘大气传输、燃油和工业来源。     

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。     

煤矿区城市矿物气溶胶的SEM-EDX特征分析

采集煤矿区城市义马、平顶山、永城夏季大气PM₁₀样品,采用带能谱的扫描电镜(SEM-EDX)研究了PM₁₀中的矿物颗粒组成、成因及来源。结果表明,矿区矿物颗粒按化学成分共有5种主要类型,分别为"富Si"、"富Ca"、"富S"、"富K"、"富Cl"型。其中平顶山地区"富Si"颗粒占百分比最高(78%),矿物颗粒硫酸盐化程度小;永城地区硫酸盐化程度中等,几乎所有的"富Ca"碱性碳酸盐颗粒都硫酸盐化成石膏;义马地区矿物硫酸盐化程度最大,除石膏以外,还有一定量硫酸铵形成。永城和义马地区还出现了一定量的"富K"(12.7%)和"富Cl"(10.6%)颗粒,与秸秆焚烧活动有关。通过对3个矿区城市PM₁₀硫酸盐化程度对比可以发现,偏碱性的碳酸盐矿物、煤炭燃烧和秸秆焚烧燃烧释放出大量的酸性SO₂以及较高的空气湿度,均有利于硫酸盐化的进行,硫酸盐颗粒的形成对煤矿区城市的区域性气候具有一定影响。     

PM2.5降尘对大鼠的急性肺损伤及复合维生素B的干预作用研究

为探讨复合维生素B(叶酸、B_6和B_(12))能否抑制PM_(2.5)对大鼠的急性肺损伤作用,本研究将56只SD大鼠随机分成对照组、不同剂量(0. 4、2. 0、10. 0 mg/m L) PM_(2.5)染毒组和相应的复合维生素B干预组(0. 02 mg/m L叶酸、1 mg/m L维生素B6、0. 002 5 mg/m L维生素B12),取肺组织进行HE染色观察组织病理学形态变化并进行病理学评分;收集支气管肺泡灌洗液(BALF)测定总蛋白(TP)、乳酸脱氢酶(LDH)、碱性磷酸酶(AKP)、酸性磷酸酶(ACP)、丙二醛(MDA)、超氧化物歧化酶(SOD)和过氧化氢酶(CAT)的含量。结果显示,PM_(2.5)染毒能对大鼠肺组织造成不同程度的病理性损伤,复合维生素B能减缓此损伤;与对照组相比,低、中、高剂量的PM_(2.5)染毒大鼠可引起BALF中LDH、AKP、ACP、TP和MDA含量显著升高(P 0. 05),而SOD和CAT活性显著降低(P 0. 05),且TP和MDA含量随染毒剂量的增加而升高(P 0. 05),CAT活性随染毒剂量的增加而降低; 3个染毒剂量的复合维生素B干预组LDH、TP和MDA含量显著降低(P 0. 05),而SOD和CAT活性显著升高(P 0. 05); PM_(2.5)低、高剂量+复合维生素B组BALF中ACP含量显著降低(P 0. 05); PM_(2.5)中剂量+复合维生素B组BALF中ACP含量无显著改变;仅有PM_(2.5)低剂量+复合维生素B组AKP含量降低(P 0. 05),其余干预组AKP含量无显著变化。因此认为,PM_(2.5)降尘能打破机体的氧化-抗氧化平衡,造成大鼠急性肺损伤,而复合维生素B能减缓此损伤,对机体起到保护作用。     

Seasonal statistical analysis of the impact of meteorological factors on fine particle pollution in China in 2013–2017

Based on long-term PM_2.5 data observed at high temporal and spatial resolution, the relationships between PM_2.5, primary emission, and weather factors in China during four seasons were examined using statistical analysis. The results reveal that primary emission plays a decisive role in the spatial distribution and seasonal variability of PM_2.5, except in western China, where PM_2.5 is controlled by dust weather. In addition to the accumulation of primary emissions, unfavorable meteorological conditions for the diffusion of air pollution lead to the occurrence of PM_2.5 pollution. The significant dynamic factors affecting PM_2.5 concentration are surface wind speed, planet boundary layer height, and ventilation coefficient, especially in winter. The ventilation coefficient is inversely correlated with PM_2.5. Better ventilation is more favorable for the dilution and outflow of local PM_2.5. However, in spring and autumn, ventilation coefficient and PM_2.5 are positively correlated over the southern regions with low emission, indicating that ventilation also affects the inflow of PM_2.5 from outside the region. Wind shear, 850 hPa divergence, and vertical velocity have insignificant effects on the long-term variations in PM_2.5. The significant thermal factor is 850 hPa temperature in winter, except in the Pearl River Delta and Xinjiang regions. In spring, the influence of each thermal factor is weak. In summer, the influences of temperature and humidity are more significant than in spring. In autumn, the influence of humidity is relatively obvious, compared with other thermal factors. The correlation coefficients between multi-factors regressed and observed PM_2.5 concentrations pass the 95% confidence test, and are higher than that of single-factor regression over most regions. The observed data from December 2016 to February 2017 were chosen to test the regression equation. The test result reveals that the regression equation is effective for predicting PM_2.5 concentrations over regions with high primary emission.     

Water soluble components of PM10 Chongqing, China

The concentrations of water soluble ions (Na⁺, NH₄ ⁺, K⁺, Mg²⁺, Ca²⁺, NO₃ ^-, Cl^-, and SO ₄ ^2- ) in PM₁₀ samples collected on cellulose filters by a medium-volume cascade impactor were determined, which were obtained from three kinds of areas in Chongqing: industrial area (Jiulongpo district), commercial and residential area (Jiangbei district) and background area (Jinyun Mountain in the Beibei district). The results showed that except for the background site, the annual average values of PM₁₀ are 23% – 61% higher than the national air quality standard (GradeII) (0.1 mg/m³), even that the value of the control site is still 20% higher than American standard (0.05 mg/m³). This implied that serious pollution of fine particles occurred in Chongqing. Nine kinds of soluble ions in water of PM₁₀ were analyzed by ion chromatography (IC) and the annual average concentrations follow the order of [SO ₄ ^2- ] > [NO³ _-] > [Cl^-] > [F^-], and [Ca²⁺] > [NH₄ ⁺] > [K⁺] > [Na⁺] > [Mg²⁺]. Their values were different in these areas: the industrial area > the commercial and living area > the control area. As for NH_{4 +}, K⁺, Ca²⁺, NO₃ ^- and SO ₄ ^2- , their seasonal average concentrations show a similar variation trend: the values in spring and fall were higher than those in summer and winter. The seasonal average concentrations of [Cl^-], [F^-], [Na⁺] and [Mg²⁺] are much lower than those of other ions. However, the concentrations of [Na⁺] changed more greatly in different seasons than those of the other three ions. Correlation coefficients showed that the three areas have been polluted by coal smoke and dust to different extents, while some local resources of pollution should be taken into consideration as well.     

PM_(2.5)降尘诱导A549细胞G2/M期阻滞的机制研究

PM_(2.5)降尘作用于A549细胞后,MTT法检测细胞存活率,扫描电镜观察细胞形态,流式细胞术检测细胞周期改变,RT-PCR检测周期阻滞相关基因p53、p21、CDK1、c-myc和lncRNA H19的表达水平,Western-blot检测周期蛋白cyclin B1表达。通过转染H19 siRNA干扰H19的表达,RT-PCR检测其对p53、c-myc及CDK1表达的影响,以探讨PM2.5降尘诱导A549细胞周期阻滞的作用机制。结果显示,PM2.5降尘暴露可降低A549细胞存活率,随作用浓度及时间增加呈递减趋势,并可观察到细胞形态破坏,细胞膜表面吸附聚集大量粉尘颗粒。PM2.5作用于细胞24 h后,A549细胞增殖阻滞在G2/M期,周期阻滞相关基因p53、p21及H19表达增加,CDK1及cyclin B1表达降低。此外,转染H19 siRNA后成功干扰H19的表达,并调控CDK1表达进一步降低。综合以上结果,PM2.5降尘处理A549细胞后可通过激活p53及p21活性,抑制CDK1和cyclin B1表达水平,诱导G2/M期阻滞从而抑制细胞增殖。短期暴露于PM2.5后,lncRNA H19在染毒细胞中可能发挥特异性癌基因的作用,通过与p53及c-myc结合参与调控细胞周期,干扰H19低表达使细胞G2/M期阻滞更加明显。     

Lockdown during COVID-19 pandemic: A case study from Indian cities shows insignificant effects on persistent property of urban air quality

The influence of reduction in emissions on the inherent temporal characteristics of PM_2.5 and NO₂ concentration time series in six urban cities of India is assessed by computing the Hurst exponent using Detrended Fluctuation Analysis (DFA) during the lockdown period (March 24–April 20, 2020) and the corresponding period during the previous two years (i.e., 2018 and 2019). The analysis suggests the anticipated impact of confinement on the PM_2.5 and NO₂ concentration in urban cities, causing low concentrations. It is observed that the original PM_2.5 and NO₂ concentration time series is persistent but filtering the time series by fitting the autoregressive process of order 1 on the actual time series and subtracting it changes the persistence property significantly. It indicates the presence of linear correlations in the PM_2.5 and NO₂ concentrations. Hurst exponent of the PM_2.5 and NO₂ concentration during the lockdown period and previous two years shows that the inherent temporal characteristics of the short-term air pollutant concentrations (APCs) time series do not change even after withholding the emissions. The meteorological variations also do not change over the three time periods. The finding helps in developing the prediction models for future policy decisions to improve urban air quality across cities.     

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.     

Bedrock controls on the mineralogy and chemistry of PM<Subscript>10</Subscript> extracted from Australian desert sediments

Given the relevance of desert aerosols to environmental issues such as dust storms, climate change and human health effects, we provide a demonstration of how the bedrock geology of an arid area influences the mineralogy and geochemistry of even the finest particulate matter (i.e., the inhalable fraction <10 μm in size: PM₁₀). PM₁₀ samples extracted from desert sediments at geologically contrasting off-road sites in central and southeastern Australia (granitic, high grade metamorphic, quartzitic sandstone) were analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM), inductively coupled plasma atomic emission spectrometry (ICP-AES) and inductively coupled plasma mass spectrometry (ICP-MS). The “granitic” PM₁₀ are highly alkali feldspathic and illitic, with a wide range of accessory minerals including rutile (TiO₂), monazite [(Ce, La, Nd, Th, Y) PO₄], xenotime (YPO₄), apatite [Ca₅(PO₄)₃ (F, OH, Cl)], hematite (Fe₃O₄), zircon (ZrSiO₄) and thorite (ThSiO₄). This mineralogy is reflected in the geochemistry which shows notable enrichments in rare earth elements (REE) and most high field strength elements (both held in the accessory minerals), and higher than normal levels of low (<2.0) ionic potential elements (Na, K, Li, Cs, Rb: held in alkali feldspar and illite). The “metamorphic” resuspended PM₁₀ define a mineralogy clearly influenced by local exposures of pelitic and calc-silicate schists (sillimanite, muscovite, calcite, Ca-amphibole), a dominance of monazite over other REE-bearing phases, and a geochemistry distinguished by enrichments in alkaline earth metals (Ca, Mg, Ba, Sr) and depletion in heavy REE. The “quartzite” PM₁₀, derived from rocks already recycled by Precambrian erosion and sedimentary transport, show a sedimentologically mature mineralogy of mostly quartz and kaolinite, detrital accessory ilmenite, rutile, monazite and hematite, and the strongest geochemical depletion (especially K, Rb, Cs, Na, Ca, Mg, Ba).     

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.