青岛市区春夏季大气能见度与颗粒物的关系

利用青岛市灰霾综合观测站2012年3月2日-2012年6月7日期间的监测数据,分析了青岛市区大气能见度与不同粒径颗粒物质量浓度的日变化特征,比较了各级别大气能见度下不同粒径颗粒物质量浓度及所占比例的相关性,研究了相对湿度对大气能见度和颗粒物质量浓度相关性的影响.结果表明,监测时段大气能见度与颗粒物质量浓度呈现较好的负相关,每天大气能见度最低值出现在早晨07:00--09:00;剔除相对湿度高于90％的前提下,PM2.5是影响大气能见度的主要因子,随着其在PM1o中所占比例上升,大气能见度级别不断下降,相关系数为-0.84;不同相对湿度区间下,PM2.5对大气能见度的影响最明显,其中,相对湿度为60％ ～ 70％,大气能见度与颗粒物质量浓度之间的相关性最好.     

Monitoring of ambient particles and heavy metals in a residential area of Seoul, Korea

In this study, ambient TSP, PM10, and PM2.5 in a residential area located in the northern part of Seoul were monitored every other month for 1 year from April 2005 to February 2006. The monthly average levels of TSP, PM10, and PM2.5 had ranges of 71∼158, 40∼106, and 28∼43 μg/m³, respectively. TSP and PM10 showed highest concentration in April; this seems to be due to Asian dust from China and/or Mongolia. However, the fine particle of PM2.5 showed a relatively constant level during the monitoring period. Heavy metals in PM 10 and PM2.5, such as Cr, As, Cd, Mn, Zn and Pb, were also analysed during the same period. The monthly average concentrations of heavy metal in PM2.5 were Cr:1.9∼22.7 ng/m³; As:0.9∼2.5 ng/m³; Cd: 0.6∼7 ng/m³; Mn:6.1∼22.6 ng/m³; Zn: 38.9∼204.8 ng/m³, and Pb: 21.6∼201.1 ng/m³. For the health risk assessment of heavy metals in ambient particles, excess cancer risks were calculated using IRIS unit risk. As a result, the excess cancer risks of chromium, cadmium, and arsenic were shown to be more than one per million based on the annual concentration of heavy metals, and chromium showed the highest excess cancer risk in ambient particles in Seoul.     

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。     

库尔勒市大气颗粒物污染特征与影响因素分析

针对库尔勒市PM 10、PM 2.5年均浓度超标现象,基于市区3个环境监测站2013—2017年的逐时观测数据,分析PM 10、PM 2.5污染特征、成因及其主要影响因素。结果表明:①2013—2017年库尔勒市PM 10年均浓度变化较大且无明显趋势,PM 2.5年均浓度整体呈下降趋势;②季节尺度上,库尔勒市PM 10在每年2—5月呈现高浓度,PM 2.5高浓度期则为10月至翌年5月;③城郊的开发区站PM 10浓度最高,老城区的州政府站PM 2.5浓度最高,在PM 10和PM 2.5的高浓度期空间差异尤其显著;④PM 10与风速显著正相关,来自塔克拉玛干沙漠的风蚀沙尘颗粒物是库尔勒地区颗粒污染物的主要来源;⑤库尔勒市PM 10主要为外源输入,PM 2.5则以城市内源为主,相对湿度、风速、风向、温度等气象条件是影响大气颗粒物浓度及分布的重要因素。     

一次连续在线观测分析天津市细颗粒物污染特征

根据2005年的5月17日—5月23日GR IMM(1.109#)谱分析仪在线观测结果考察天津市细颗粒物浓度和质量浓度特征。观测期间,天津市颗粒物数浓度平均值为1 124 cm-3,粒径分布为0.25μm~0.60μm,98.5%粒子的粒径0.65μm。同期PM10日均质量浓度值为204μg/m3,ρ(PM2.5)为104μg/m3,ρ(PM1.0)为82.9μg/m3。ρ(PM1.0)/ρ(PM2.5)超过80%,粒径1μm超细颗粒物为天津城市大气颗粒物的主要成分。     

Evaluation of the Impact of Long-range Transport and Aerosol Concentration Temporal Variations at the Eastern Coast of the Baltic Sea

Ambient particles vary greatly in their ability to affect visibility, climate and human health. The fine fraction of aerosol is responsible for greater and wider effects on human health; thus, investigation of this fraction is very important. Continuous measurements of PM2.5 (particulate matter below 2.5 μm in size) concentrations at the Preila monitoring station started in 2003. During a period of 2 years, the episodes of high daily and semi-hourly concentrations of PM2.5 were measured. These episodes did not depend on the season or time of day. The substantial role of long-range transport of pollutants to these increases in concentration was shown using chemical and statistical analysis. It was found that most of the severe episodes occurred when air masses came from a specific site besides it was established that air masses of different origin were characterized by different mixing layer depth. Lower mixing depth was observed in air masses characterized by higher observed concentrations at the measuring site and vice versa. PM2.5 concentrations showed diurnal and seasonal variations whose pattern reflected the regional origin of the aerosol. The regional pollution level was evaluated by the statistical analysis of PM2.5 concentrations. The background annual average of PM2.5 mass concentration for the eastern coast of the Baltic Sea was 15.1 ± 0.8 μg m⁻³.     

平顶山市大气PM10、PM2.5污染调查

于2003年12月-2004年11月对平顶山市城区大气PM10、PM2.5污染进行了调查.结果表明,2004年大气PM10、PM2.5质量浓度分别为0.031 mg/m3～0.862 mg/m3、0.019 mg/m3～0.438 mg/m3;年均值分别为0.174 mg/m3、0.114 mg/m3,超标0.74倍、6.60倍.PM10、PM2.5污染的季节变化趋势是以冬季、春季高,秋季次之,夏季最低,细颗粒(PM2.5)约占PM10 65%;As、Pb、Cd、S、Zn、Cu、Mn、Ca等元素是颗粒物中主要污染元素,易在PM2.5中富集.平顶山市大气颗粒物污染的主要来源有煤炭燃烧、汽车尾气、城市基础建设和有色金属冶炼行业.     

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。     

Investigation into presence of atmospheric particulate matter in Marikana, mining area in Rustenburg Town, South Africa

An investigation to find out presence of particulate matter in Marikana, a mining area in Rustenburg town, South Africa, was carried out in the months of August and November of 2008. Samples were collected for measurements of particulate matter (PM) of particle diameters of PM10, PM2.5, and PM1. After gravimetric analysis of daily measurements, it was found that PM10 concentration values ranged between 3 and 9 ??g/m³, PM2.5 concentration values ranged between 16 and 26 ??g/m³, and PM1 concentration values ranged between 14 and 18 ??g/m³ for the month of August 2008. For the month of November, it was found that PM10 concentration values ranged between 2 and 8 ??g/m³, PM2.5 concentration values ranged between 0 and 5 ??g/m³, and PM1 concentration values ranged between 4 and 15 ??g/m³. This study was undertaken as preliminary work having in mind that mining activities could be emitting high levels of particulate matter in the atmosphere which might be degrading the quality of the air. It was observed, however, that the daily particulate matter especially of PM10 emitted were quite low when compared to laid down International Air Quality Standards. The standards did not give guidelines for particulate matter of diameter 2.5 ??m. It was concluded that particulate matter came from three major sources: platinum mining, domestic biomass burning, and traffic emissions due to fuel burning.     

Evaluation of the diffusion size classifier (meDiSC) for the real-time measurement of particle size and number concentration of nanoaerosols in the range 20-700 nm

In the frame of assessing exposure to nanostructured particles, the aim of this work is to study the performance of a new device devoted to the real-time measurement of nanostructured aerosol: the meDiSC (Diffusion Size Classifier, Matter Engineering, Switzerland). This instrument is based on unipolar diffusion charging of particles which are then collected successively in diffusion and filtration stages. From currents measured in these stages, the instrument is capable of determining aerosol mean size and number concentration. These data were compared to reference measurements regarding monodisperse aerosols in a range from 20 to 700 nm; the relative biases were found unsatisfying. This led us to investigate the principle of the instrument. Consequently, the charging law of the diffusion charger was experimentally established, as well as the calibration curve allowing the determination of the mean size of the particles. The latter analysis was completed by a model based on diffusion theory. Our results indicate the possibility to improve the range of size measurement up to 350 nm. Measured particle size and number concentration were also used to calculate geometric surface-area concentration; the experimental data were compared to a reference calculated surface-area concentration. The results demonstrate the possibility to evaluate this parameter within acceptable uncertainty. In a second step, the meDiSC was challenged with polydisperse aerosols. It was observed that meDiSC overestimates particle size by a factor 1.7, while particle number concentrations are found within ±40% of the reference. The model applied to polydisperse aerosols indicates that polydispersity little influences particle size up to 300 nm while geometric standard deviation remains below 1.7.     

桂林市细颗粒物部分典型排放源的粒径谱及成分分析

采用在线单颗粒气溶胶质谱技术源解析方法,对桂林市PM2.5典型排放源的粒径和化学成分进行质谱分析,采集燃煤/燃气源、工业工艺源、扬尘源、油烟源4类共计7个典型排放源。结果表明,桂林市4类排放源细颗粒物的粒径分布为0.25~1.25μm,80%以上的细颗粒分布在0.2~1.0μm的小粒径范围,峰值约0.68μm。细颗粒物离子成分含有Na~+、Mg~+、K~+、NH~+4、Fe~+、Pb~+、Cd~+、V~+、Mn~+、Li~+、Al~+、Ca~+、Cu~+、Zn~+、Cr~+、CN~-、PO_3~-、NO_2~-、NO_3~-、Cl~-、SO_4~(2-)、SiO_3~-等成分,桂林市细颗粒物为元素碳、有机碳元素碳、有机碳、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。     

Dust exposure in indoor climbing halls

The use of hydrated magnesium carbonate hydroxide (magnesia alba) for drying the hands is a strong source for particulate matter in indoor climbing halls. Particle mass concentrations (PM10, PM2.5 and PM1) were measured with an optical particle counter in 9 indoor climbing halls and in 5 sports halls. Mean values for PM10 in indoor climbing halls are generally on the order of 200-500 microg m(-3). For periods of high activity, which last for several hours, PM10 values between 1000 and 4000 microg m(-3) were observed. PM(2.5) is on the order of 30-100 microg m(-3) and reaches values up to 500 microg m(-3), if many users are present. In sports halls, the mass concentrations are usually much lower (PM10 < 100 microg m(-3), PM2.5 < or = 20 microg m(-3)). However, for apparatus gymnastics (a sport in which magnesia alba is also used) similar dust concentrations as for indoor climbing were observed. The size distribution and the total particle number concentration (3.7 nm-10 microm electrical mobility diameter) were determined in one climbing hall by an electrical aerosol spectrometer. The highest number concentrations were between 8000 and 12 000 cm(-3), indicating that the use of magnesia alba is no strong source for ultrafine particles. Scanning electron microscopy and energy-dispersive X-ray microanalysis revealed that virtually all particles are hydrated magnesium carbonate hydroxide. In-situ experiments in an environmental scanning electron microscope showed that the particles do not dissolve at relative humidities up to 100%. Thus, it is concluded that solid particles of magnesia alba are airborne and have the potential to deposit in the human respiratory tract. The particle mass concentrations in indoor climbing halls are much higher than those reported for schools and reach, in many cases, levels which are observed for industrial occupations. The observed dust concentrations are below the current occupational exposure limits in Germany of 3 and 10 mg m(-3) for respirable and inhalable dust. However, the dust concentrations exceed the German guide lines for work places without use of hazardous substances. In addition, minimizing dust concentrations to technologically feasible values is required by the current German legislation. Therefore, substantial reduction of the dust concentration is required.     

Aspiration and sampling efficiencies of the TSP and louvered particulate matter inlets

An experimental system was developed for the rapid measurement of the aspiration/transfer efficiency of aerosol samplers in a wind tunnel. We attempted to measure the aspiration and particle transfer characteristics of two inlets commonly used for sampling airborne Particulate Matter (PM): the 'Total Suspended Particulate' or TSP inlet, and the louvered 'dichotomous sampler inlet' typically used in sampling PM10 or PM2.5. We were able to determine the fraction of the external aerosol that enters the inlet and is transferred through it, and hence is available for collection by a filter, or further size fractionation into PM10 or PM2.5. This 'sampling efficiency' was analysed as a function of dimensionless aerodynamic parameters in order to understand the factors governing inlet performance. We found that for the louvered inlet the sampling efficiency increases as the external wind increases. Under all conditions expected in practical use the louvered inlet aspirates sufficient PM to allow either PM10 or PM2.5 to be selected downstream. The TSP inlet's sampling efficiency decreases with increasing external wind, and the TSP inlet is likely to under-sample the coarse end of the PM10 fraction at moderate and high external winds. As this inlet is generally not used with a downstream size fractionator, changes in sampling efficiency directly affect the measured aerosol concentration. We also investigated whether it is possible to dimensionally scale the PM inlets to operate at either higher or lower flow rates, while preserving the same sampling characteristics as the current full-scale, 16.67 L min(-1) versions. In the case of the louvered inlet, our results indicate that scaling to lower flow rates is possible; scaling to higher flow rates was not tested. For the TSP sampler, the sampling efficiency changes if the sampler is scaled to operate at smaller or larger flow rates, leading to unreliable performance.     

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.     

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.     

Relationship between different size classes of particulate matter and meteorology in three European cities

Evidence on the correlation between particle mass and (ultrafine) particle number concentrations is limited. Winter- and spring-time measurements of urban background air pollution were performed in Amsterdam (The Netherlands), Erfurt (Germany) and Helsinki (Finland), within the framework of the EU funded ULTRA study. Daily average concentrations of ambient particulate matter with a 50% cut off of 2.5 microm (PM2.5), total particle number concentrations and particle number concentrations in different size classes were collected at fixed monitoring sites. The aim of this paper is to assess differences in particle concentrations in several size classes across cities, the correlation between different particle fractions and to assess the differential impact of meteorological factors on their concentrations. The medians of ultrafine particle number concentrations were similar across the three cities (range 15.1 x 10(3)-18.3 x 10(3) counts cm(-3)). Within the ultrafine particle fraction, the sub fraction (10-30 nm) made a higher contribution to particle number concentrations in Erfurt than in Helsinki and Amsterdam. Larger differences across the cities were found for PM2.5(range 11-17 microg m(-3)). PM2.5 and ultrafine particle concentrations were weakly (Amsterdam, Helsinki) to moderately (Erfurt) correlated. The inconsistent correlation for PM2.5 and ultrafine particle concentrations between the three cities was partly explained by the larger impact of more local sources from the city on ultrafine particle concentrations than on PM2.5, suggesting that the upwind or downwind location of the measuring site in regard to potential particle sources has to be considered. Also, relationship with wind direction and meteorological data differed, suggesting that particle number and particle mass are two separate indicators of airborne particulate matter. Both decreased with increasing wind speed, but ultrafine particle number counts consistently decreased with increasing relative humidity, whereas PM2.5 increased with increasing barometric pressure. Within the ultrafine particle mode, nucleation mode (10-30 nm) and Aitken mode (30-100 nm) had distinctly different relationships with accumulation mode particles and weather conditions. Since the composition of these particle fractions also differs, it is of interest to test in future epidemiological studies whether they have different health effects.     

Particulate matter concentration levels during intense haze event in an urban environment

This study assessed concentration levels of particulate matter (PM) in the ambient environment of Ilorin metropolis, Nigeria, during haze episodes. Meteorological data (wind speed and direction, rainfall data, sunshine data, relative humidity and temperature) were obtained. Aerocet 531S particle counter (MetOne Instruments, USA) was used to measure four mass concentration ranges of PM (PM_1.0, PM_2.5, PM₁₀ and the total suspended particles (TSP)) in 10 locations taking into consideration land use patterns. Surfer® version 8 (Golden Software LLC, USA) was used to model the spatial variation of particulate matter concentration levels using kriging interpolation griding method. Human exposure assessment was done using the total respiratory deposition dose (TRDD) estimates and statutory limit breach (SLB) approaches. The appearance of dominating weak southern atmospheric wind flow was observed as wind speed ranged from 0 to 6.811 m/s while solar radiation periods ranged from 0.3 to 3.5 h/day. The relative humidity of the metropolis ranged between 28 and 57%, while daily temperature was 15 to 36 °C. Highest concentration levels of PM measured were 73.4, 562.7, 7066.3 and 9907.8 μg/m³ for PM_1.0, PM_2.5, PM₁₀ and TSP, respectively. Very strong negative correlations existed between the PM concentration levels and microclimatic parameters. Spatial variation of the concentration level as modelled using Surfer® version 8 indicated that particulate concentration level increases from south to north. Concentration levels of PM for the 24-h averaging period were generally above the 24-h threshold limit value set by the regulatory agencies for all the locations.     

睢宁地区大气PM_(2.5)及气态污染物季节性变化特征

根据2014年全年实时在线观测数据,分析了徐州睢宁地区大气细颗粒物(PM_(2.5))和气态污染物(包括SO_2、CO、NO_x、O_3)质量浓度的季节性变化特征。结合后向轨迹模型,分析不同气团对该地区大气污染浓度的影响。PM_(2.5)与O_3值在夏季最低,呈显著相关,表明夏季PM_(2.5)主要受控于本地大气光化学活性。在冬季,除O_3外,PM_(2.5)、SO_2、CO、NO_x值最高,且大气颗粒物主要以细粒子为主。O_3在春季最高,并与远程传输的气团且经过我国东部污染源密集地区相对应。高浓度的PM_(2.5)主要与冬季缓慢移动的气团相对应,这可能将PM_(2.5)及其气态前体物传输至该地区进而加重大气污染程度。     

郑州市 PM2．5和 PM10质量浓度变化特征分析

根据郑州市2013年PM2．5和PM10颗粒物连续自动监测数据,对郑州市各国控站点的PM2．5和PM10的达标情况、变化趋势等进行探讨分析。结果表明：2013年郑州市PM10和PM2．5的年均质量浓度均超过了新标准规定的年均值二级标准限值。 PM10和PM2．5月均值峰值出现在1月和10月,谷值出现在8月,各月PM2．5的超标天数都大于PM10。PM10和PM2．5冬季的日均值浓度明显高于其他季节,呈双峰型,夜晚浓度整体高于白天;PM2．5春、夏、秋三季日变化呈单峰型,PM10夏季和秋季呈单峰型,春季呈双峰型。 PM2．5和PM10日均值有着非常显著的线性相关关系,PM2．5和PM10浓度的比值（p）10月最高。     

乌鲁木齐市2011年冬季PM2.5/PM10浓度特征分析

利用乌鲁木齐市PM2.5//PM10自动监测数据,分析PM2.5与PM10的浓度分布特征和时间变化规律。结果表明,按照《环境空气质量标准》(二次征求意见稿)的标准限值,乌鲁木齐市冬季PM2.5污染重于PM10。PM2.5浓度为0.164mg/m3,超过二级年标准限值的3.7倍,超标率为73.9%。PM2.5浓度日变化曲线昼高夜低,呈单峰型,峰值出现在13:00~14:00(北京时间)。PM10中PM2.5所占比例较高,PM2.5/PM10为0.79,相关分析和检验显示PM2.5与PM10的线性相关显著,相关系数为0.92。