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%。     

夏季桂林市大气PM_(2.5)化学组成和成分分布的质谱研究

选取桂林市5个代表性监测点,采用单颗粒气溶胶飞行时间质谱仪在线分析该市夏季大气PM_(2.5)的化学组成及化学成分分布。结果表明:5个监测点,80%的PM_(2.5)分布在0.2μm~1.0μm的小粒径范围,20%的PM_(2.5)分布在1.0μm~2.5μm大粒径范围;大气PM_(2.5)中离子成分包含Na~+、K~+、NH~+4、C2H3~+/Al~+、Fe~+、HSO~-_4、NO~-_3、NO~-_2、CNO~-、CN~-、SO~-_3、O~-和元素碳离子;PM_(2.5)中离子按成分特征可分为元素碳、有机碳、元素碳有机碳混合颗粒、富锰颗粒、富铁颗粒、富钾颗粒、矿物质、左旋葡聚糖以及其他金属等9类,各监测点元素碳占比均超过50%;元素碳与硫酸盐、铵盐、硝酸盐发生内混合的程度极高,其中各监测点元素碳与硫酸盐混合程度最高,均达到90%左右。     

西宁市典型开放源颗粒物粒径组成特征分析

采用BT-9300S激光粒度仪分析了西宁市道路尘、扬尘、土壤尘、建筑尘4种典型开放源的粒径组成。结果表明,4种类型尘中大粒径颗粒物占主导地位,粒径大于10 μm颗粒占到全部颗粒的73.80%以上,可吸入颗粒物的含量仅占7.06%～26.20%;建筑尘的细颗粒物含量最高,粒径小于2.5、1 μm的颗粒含量分别为8.36%±4.25%、2.42%±1.02%;道路尘的细颗粒物含量最低,粒径小于2.5、1 μm的颗粒含量分别为2.30%±0.94%、0.73%±0.28%;4种类型尘的体积平均直径、面积平均直径、中位直径分别在37.70～87.99 μm、8.50～23.53 μm、28.95～74.98 μm之间,其中道路尘的3种粒径参数最大,建筑尘最小;开放源颗粒物的粒度分布曲线主要呈头长尾短的不对称单峰分布,累积频率曲线为两段式,存在较为明显的拐点。     

合肥市春季大气PM10和PM2.5中碳组分的污染特征

选取桂林市5个代表性监测点，采用单颗粒气溶胶飞行时间质谱仪在线分析该市夏季大气PM2.5的化学组成及化学成分分布。结果表明： 5个监测点，＞80%的PM2.5分布在0.2 μm～1.0 μm的小粒径范围，＜20%的PM2.5分布在1.0 μm～2.5 μm大粒径范围； 大气PM2.5中离子成分包含Na+、K+、NH+4、C2H3+/Al+、Fe+、HSO-4、NO-3、NO-2、CNO-、CN-、SO-3、O-和元素碳离子； PM2.5中离子按成分特征可分为元素碳、有机碳、元素碳有机碳混合颗粒、富锰颗粒、富铁颗粒、富钾颗粒、矿物质、左旋葡聚糖以及其他金属等9类，各监测点元素碳占比均超过50%； 元素碳与硫酸盐、铵盐、硝酸盐发生内混合的程度极高，其中各监测点元素碳与硫酸盐混合程度最高，均达到90%左右。     

西安城北地区秋季PM_(2.5)中的矿尘颗粒污染特征

采用单颗粒气溶胶飞行时间质谱仪(Single Particle Aerosol Mass Spectrometer,SPAMS)对西安市大气矿尘颗粒物进行连续12 d在线分析,共采集到107 425个同时含有正负质谱信息的矿尘颗粒,矿尘颗粒物占PM_(2.5)样本数的8.44%。结果表明,矿尘颗粒物的正离子碎片成分以Na~+、K~+、Al~+、Ca~+、CaO~+、Fe~+为主,同时还含有Pb~+等,负离子碎片成分以NO~-_2和NO~-_3为主,另外还含有HSO~-_4、SiO~-_3、HSiO~-_3、H(NO_3)~-_2等。在西安市大气细颗粒物中,矿尘颗粒物中贡献较大的几类(如含钙、含铁、铁氧颗粒物等)大多是老化的成分。将观测阶段采集到的矿尘颗粒纳入本地污染源谱进行来源分析,其主要来源为扬尘源、工业源、燃煤源和汽车尾气源等。     

镇江市东部片区大气细颗粒物中水溶性离子在线监测成分特征研究

2019年1-6月之间利用MARGA离子在线分析仪在镇江东部地区对细颗粒物中主要水溶性离子组分NH_4~+,Na~+,K~+,Ca~(2+),Mg~(2+),Cl-,NO_3~-,SO_4~(2-)的在线监测,结果表明:细颗粒物中阴阳离子的当量浓度的频数分布趋势基本一致。通过相关性系数分析,NO_3~-和SO_4~(2-)存在显著相关性,表明与燃料燃烧有一定关系。Na~+和K~+存在显著相关性,生物质燃烧可能为其共同来源。Mg~(2+)和Ca~(2+)相关性也较强,表明可能来自于土壤扬尘。整体上镇江市东部地区点位受扬尘影响较小,受工业排放机动车尾气和燃料燃烧影响较大,说明因加强生产企业节能减排、超低排放,汽柴油车和燃料燃烧的管理。     

宜兴市细颗粒物化学特征和来源解析

通过在宜兴市3个监测站点对细颗粒物(PM_(2.5))开展不同季节采样,对样品做化学分析,结合化学质量平衡(CMB)模型解析PM_(2.5)来源贡献。结果表明,宜兴市PM_(2.5)年均质量浓度为37.5μg/m~3,冬季质量浓度最高,为53.1μg/m~3。PM_(2.5)主要化学成分为SO_4~(2-)、NO_3~-、OC、EC、NH_4~+、Cl~-、Ca、Na、Al。PM_(2.5)的主要排放源贡献为二次硫酸盐(21.0%)、二次有机气溶胶(14.9%)、二次硝酸盐(14.1%)和燃煤电厂(8.0%)。利用本地排放源清单进行二次来源解析,得到全年主要排放源贡献为工业(33.1%)、燃煤(23.1%)、移动源(17.6%)、扬尘(9.3%)和其他来源(16.9%)。减轻颗粒物污染,重点是控制工业生产、燃煤及机动车中的排放。     

重庆市主城区大气水溶性离子在线观测分析

2015年12月—2016年3月期间,利用在线气体与气溶胶成分监测仪(IGAC)在重庆市大气超级站开展连续观测分析,并捕捉到2次持续时间较长的空气重污染过程。对PM_(2.5)中9种水溶性离子及5种气态前体物的观测结果分析表明:NO_3~-、NH_4~+和SO_4~(2-)是重庆市主城区PM_(2.5)中主要的水溶性离子成分,其浓度均表现出明显的日变化特征,主要以(NH4)_2SO_4和NH_4NO_3的形式存在。NH_3和SO_2是最主要的气态污染物。2次重污染过程的水溶性离子组分有明显差异,细颗粒物累积型污染的NH_4~+、SO_4~(2-)、NO_3~-浓度高,二次转化十分明显;春节期间烟花爆竹集中燃放,Cl~-、K~+浓度高,主要属于一次排放;污染期间主要离子组分的同源性特征显著。     

张家口市沙尘天气过程气溶胶单颗粒特征研究

利用单颗粒气溶胶质谱仪对张家口市2015年春季的一次典型沙尘过程进行了监测,分析了沙尘过程对当地大气颗粒物成分的影响。结果表明,监测期间的颗粒物类型主要分为8种:矿物质(MD)、左旋葡聚糖(LEV)、元素碳(EC)、有机碳(OC)、混合碳(ECOC)、重金属(HM)、富钾(K)、其他(Other)。对比沙尘天气来临前、中、后3个时段,随着沙尘天气的来临,本地大气颗粒物成分发生较大变化,矿物质、左旋葡聚糖等成分含量升高,而有机碳、重金属等成分含量下降,其中矿物质在PM10峰值时段小时比例高达27.8%;沙尘天气期间,由于矿物质颗粒占比增加,使得总颗粒物的粒径分布向0.9μm以上的粗粒径段偏移;此外,沙尘天气期间的颗粒物各成分与二次组分的混合程度相较非沙尘天气时段的低,说明其老化程度相对较低。     

在线单颗粒气溶胶质谱在大气重金属铅污染事故中的应用研究

重金属铅由于其对人体健康的影响而广受关注。利用在线单颗粒气溶胶质谱仪对2012年发生在华南地区的一次金属铅污染事故中的含铅颗粒物的质谱特征、粒径分布及排放规律进行了分析。监测发现A、B两个监测点位的含铅颗粒物比例多在夜间或凌晨达到高峰,高峰时刻含铅颗粒物数浓度占比最高可达67%,对比广州市区、鹤山超级站的含铅颗粒物浓度占比,可知该地区含铅颗粒物的污染程度较高。两监测点位的含铅颗粒物质谱特征及粒径分布情况非常相似,可能存在相同的排放源或具有相同的形成机制。质谱中都均含有明显的铅、元素碳、硫、硫酸盐等信号,可能来自于燃煤源的排放。通过进一步对比分析燃煤烟气排放的含铅颗粒物质谱特征,判断其为燃煤源排放。     

2017年厦门金砖会晤期间PM2.5的化学特征及来源

为了探讨厦门金砖会晤期间的排放控制措施以及天气形势对大气颗粒物污染特征的影响,于2017年8月10日至9月10日对厦门气态污染物、细颗粒物(PM2.5)中的水溶性离子以及有机碳(OC)、元素碳(EC)等主要化学成分开展了高时间分辨率的在线监测。根据空气质量管控措施和天气形势将研究期分为6个阶段。管控前、管控期Ⅰ(非台风)和管控期Ⅱ(非台风) PM2.5质量浓度分别为(33. 12±9. 48)、(30. 30±17. 00)、(16. 01±4. 71)μg/m^3。管控期Ⅰ(台风)和管控期Ⅱ(台风) PM2.5质量浓度分别为(12. 40±3. 73)、(12. 45±3. 28)μg/m^3。结果表明:管控期Ⅰ(非台风)阶段受静稳天气的影响,管控效果削弱,PM2.5质量浓度下降幅度小;台风对颗粒物质量浓度下降的影响比管控更显著。管控初期,PM2.5中二次无机离子的质量浓度下降明显;台风对碳质组分质量浓度的影响不如无机组分显著。PMF源解析结果表明,二次无机源是PM2.5主要来源,随着管控措施的实行,扬尘源的贡献从21%降低到6%,而机动车源的贡献降幅不明显。台风期间SO4^2-、NO3^-、SO2、NO2以及硫酸盐氧化比值(SOR)均明显低于非台风期间,氮氧化比值(NOR)反而升高。台风和非台风期间NOR的日变化特征一致,NOR与阳离子的相关性分析结果表明,台风或高风速海风期间NOR与Na^+呈现很强的正相关性,说明海盐粒子可促进NO2非均相反应生成NO3-。     

Dynamics and origin of PM2.5 during a three-year sampling period in Beijing, China

Systematic sampling and analysis were performed to investigate the dynamics and the origin of suspended particulate matter smaller than 2.5 μm in diameter (PM(2.5)), in Beijing, China from 2005 to 2008. Identifying the source of PM(2.5) was the main goal of this project, which was funded by the German Research Foundation (DFG). The concentrations of 19 elements, black carbon (BC) and the total mass in 158 weekly PM(2.5) samples were measured. The statistical evaluation of the data from factor analysis (FA) identifies four main sources responsible for PM(2.5) in Beijing: (1) a combination of long-range transport geogenic soil particles, geogenic-like particles from construction sites and the anthropogenic emissions from steel factories; (2) road traffic, industry emissions and domestic heating; (3) local re-suspended soil particles; (4) re-suspended particles from refuse disposal/landfills and uncontrolled dumped waste. Special attention has been paid to seven high concentration "episodes", which were further analyzed by FA, enrichment factor analysis (EF), elemental signatures and backward-trajectory analysis. These results suggest that long-range transport soil particles contribute much to the high concentration of PM(2.5) during dust days. This is supported by mineral analysis which showed a clear imprint of component in PM(2.5). Furthermore, the ratios of Mg/Al have been proved to be a good signature to trace back different source areas. The Pb/Ti ratio allows the distinction between periods of predominant anthropogenic and geogenic sources during high concentration episodes. Backward-trajectory analysis clearly shows the origins of these episodes, which partly corroborate the FA and EF results. This study is only a small contribution to the understanding of the meteorological and source driven dynamics of PM(2.5) concentrations.     

乌鲁木齐市可吸入颗粒物水溶性离子特征及来源解析

采暖期时在乌鲁木齐市采集了环境空气中的可吸入颗粒物,对可吸入颗粒物质量浓度及8种水溶性离子的特征和来源进行了分析。结果表明,细粒子和粗粒子的月平均质量浓度分别是53.5～233.3μg/m3和38.9～60.9μg/m3;细粒子和粗粒子中水溶性离子主要由SO24-、NH4+和NO3-组成;粗粒子中NH4+与NO3-和SO24-的相关性分别是0.70和0.66,细粒子中NH4+与NO3-和SO24-的相关性分别是0.89和0.93,铵盐是乌鲁木齐可吸入颗粒物主要存在形式;煤烟尘是乌鲁木齐市采暖期可吸入颗粒物的主要来源。     

Assessment of particulate matter in the urban atmosphere: size distribution, metal composition and source characterization using principal component analysis

In this study, the size distribution of airborne particles and related heavy metals Co, Cd, Sn, Cu, Ni, Cr, Pb and V in two urban areas in Istanbul: Yenibosna and Goztepe, were examined. The different inhalable particles were collected by using a cascade impactor in eight size fractions (<0.4 μm, 0.4-0.7 μm, 1.1-2.1 μm, 2.1-3.3 μm, 3.3-4.7 μm, 4.7-5.8 μm, 5.8-9 μm and >9 μm) for six months at each station. Samples were collected on glass fiber filters and filters were extracted and analyzed using ICP-MS. Log-normal distributions showed that the particles collected at the Yenibosna site have a smaller size compared to the Goztepe samples and the size distribution of PM was represented the best by the tri-modal. The average total particle concentrations and standard deviations were obtained as 67.7 ± 17.0 μg m(-3) and 82.1 ± 21.2 μg m(-3), at the Yenibosna and G?ztepe sites, respectively. The higher metal rate in fine and medium coarse PM showed that the anthropogenic sources were the most significant pollutant source. Principal component analysis identified five components for PM namely traffic, road dust, coal and fuel oil combustion, and industrial.     

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.     

Traffic emission factors of ultrafine particles: effects from ambient air

Ultrafine particles have a significant detrimental effect on both human health and climate. In order to abate this problem, it is necessary to identify the sources of ultrafine particles. A parameterisation method is presented for estimating the levels of traffic-emitted ultrafine particles in terms of variables describing the ambient conditions. The method is versatile and could easily be applied to similar datasets in other environments. The data used were collected during a four-week period in February 2005, in Gothenburg, as part of the G?te-2005 campaign. The specific variables tested were temperature (T), relative humidity (RH), carbon monoxide concentration (CO), and the concentration of particles up to 10 μm diameter (PM(10)); all indicators are of importance for aerosol processes such as coagulation and gas-particle partitioning. These variables were selected because of their direct effect on aerosol processes (T and RH) or as proxies for aerosol surface area (CO and PM(10)) and because of their availability in local monitoring programmes, increasing the usability of the parameterization. Emission factors are presented for 10-100 nm particles (ultrafine particles; EF(ufp)), for 10-40 nm particles (EF(10-40)), and for 40-100 nm particles (EF(40-100)). For EF(40-100) no effect of ambient conditions was found. The emission factor equations are calculated based on an emission factor for NO(x) of 1 g km(-1), thus the particle emission factors are easily expressed in units of particles per gram of NO(x) emitted. For 10-100 nm particles the emission factor is EF(ufp) = 1.8×10(15)×(1 - 0.095×CO - 3.2×10(-3)×T) particles km(-1). Alternative equations for the EFs in terms of T and PM(10) concentration are also presented.     

Chemical compositions and sources of atmospheric PM10 in heating, non-heating and sand periods at a coal-based city in northeastern China

Mass concentrations and chemical components (18 elements, 9 ions, organic carbon [OC] and elemental carbon [EC]) in atmospheric PM(10) were measured at five sites in Fushun during heating, non-heating and sand periods in 2006-2007. PM(10) mass concentrations varied from 62.0 to 226.3 μg m(-3), with 21% of the total samples' mass concentrations exceeding the Chinese national secondary standard value of 150 μg m(-3), mainly concentrated in heating and sand periods. Crustal elements, trace elements, water-soluble ions, OC and EC represented 20-47%, 2-9%, 13-34%, 15-34% and 13-25% of the particulate matter mass concentrations, respectively. OC and crustal elements exhibited the highest mass percentages, at 27-34% and 30-47% during heating and sand period. Local agricultural residuals burning may contribute to EC and ion concentrations, as shown by ion temporal variation and OC and EC correlation analysis. Heavy metals (Cr, Ni, Zn, Cu and Mn) from coal combustion and industrial processes should be paid attention to in heating and sand periods. The anion/cation ratios exhibited their highest values for the background site with the influence of stationary sources on its upper wind direction during the sand period. Secondary organic carbon were 1.6-21.7, 1.5-23.0, 0.4-17.0, 0.2-33.0 and 0.2-21.1 μg m(-3), accounting for 20-77%, 44-88%, 4-77%, 8-69% and 4-73% of OC for the five sampling sites ZQ, DZ, XH, WH and SK, respectively. From the temporal and spatial variation analysis of major species, coal combustion, agricultural residual burning and industrial emission including dust re-suspended from raw material storage piles were important sources for atmospheric PM(10) in Fushun at heating, non-heating and sand periods, respectively. It was confirmed by principal component analysis that coal combustion, vehicle emission, industrial activities, soil dust, cement and construction dust and biomass burning were the main sources for PM(10) in this coal-based city.     

Aerosol size distribution and mass concentration measurements in various cities of Pakistan

During March and April 2010 aerosol inventories from four large cities in Pakistan were assessed in terms of particle size distributions (N), mass (M) concentrations, and particulate matter (PM) concentrations. These M and PM concentrations were obtained for Karachi, Lahore, Rawalpindi, and Peshawar from N concentrations using a native algorithm based on the Grimm model 1.109 dust monitor. The results have confirmed high N, M and PM concentrations in all four cities. They also revealed major contributions to the aerosol concentrations from the re-suspension of road dust, from sea salt aerosols, and from vehicular and industrial emissions. During the study period the 24 hour average PM(10) concentrations for three sites in Karachi were found to be 461 μg m(-3), 270 μg m(-3), and 88 μg m(-3), while the average values for Lahore, Rawalpindi and Peshawar were 198 μg m(-3), 448 μg m(-3), and 540 μg m(-3), respectively. The corresponding 24 hour average PM(2.5) concentrations were 185 μg m(-3), 151 μg m(-3), and 60 μg m(-3) for the three sites in Karachi, and 91 μg m(-3), 140 μg m(-3), and 160 μg m(-3) for Lahore, Rawalpindi and Peshawar, respectively. The low PM(2.5)/PM(10) ratios revealed a high proportion of coarser particles, which are likely to have originated from (a) traffic, (b) other combustion sources, and (c) the re-suspension of road dust. Our calculated 24 hour averaged PM(10) and PM(2.5) concentrations at all sampling points were between 2 and 10 times higher than the maximum PM concentrations recommended by the WHO guidelines. The aerosol samples collected were analyzed for crustal elements (Al, Fe, Si, Mg, Ca) and trace elements (B, Ba, Cr, Cu, K, Na, Mn, Ni, P, Pb, S, Sr, Cd, Ti, Zn and Zr). The averaged concentrations for crustal elements ranged from 1.02 ± 0.76 μg m(-3) for Si at the Sea View location in Karachi to 74.96 ± 7.39 μg m(-3) for Ca in Rawalpindi, and averaged concentrations for trace elements varied from 7.0 ± 0.75 ng m(-3) for B from the SUPARCO location in Karachi to 17.84 ± 0.30 μg m(-3) for Na at the M. A. Jinnah Road location, also in Karachi.     

Reducing dust exposure in indoor climbing gyms

As users of indoor climbing gyms are exposed to high concentrations (PM(10) up to 4000 μg m(-3); PM(2.5) up to 500 μg m(-3)) of hydrated magnesium carbonate hydroxide (magnesia alba), reduction strategies have to be developed. In the present paper, the influence of the use of different kinds of magnesia alba on dust concentrations is investigated. Mass concentrations, number concentrations and size distributions of particles in indoor climbing gyms were determined with an optical particle counter, a synchronized, hybrid ambient real-time particulate monitor and an electrical aerosol spectrometer. PM(10) obtained with these three different techniques generally agreed within 25%. Seven different situations of magnesia alba usage were studied under controlled climbing activities. The use of a suspension of magnesia alba in ethanol (liquid chalk) leads to similar low mass concentrations as the prohibition of magnesia alba. Thus, liquid chalk appears to be a low-budget option to reduce dust concentrations. Magnesia alba pressed into blocks, used as powder or sieved to 2-4 mm diameter, does not lead to significant reduction of the dust concentrations. The same is true for chalk balls (powder enclosed in a sack of porous mesh material). The promotion of this kind of magnesia alba as a means of exposure reduction (as seen in many climbing gyms) is not supported by our results. Particle number concentrations are not influenced by the different kinds of magnesia alba used. The particle size distributions show that the use of magnesia alba predominantly leads to emission of particles with diameters above 1 μm.