PM1切割器性能测试系统的搭建与应用

为对PM_1切割器的性能进行准确评估,本文设计搭建了两套PM_1切割器性能测试系统.结果发现,多分散气溶胶测试系统发生的气溶胶稳定、均匀,符合对数正态分布;单分散气溶胶测试系统发生的气溶胶稳定,单分散性良好.采用上述两套系统对5种PM1旋风切割器进行了性能评价,结果表明,两套系统测试结果基本一致,5种旋风切割器的切割粒径D50均在(1.0±0.1)μm之间,sharp-cut和Stairmand两类结构设计的切割器几何标准偏差σg分别在1.2±0.1和1.4±0.1之间.     

标准气溶胶发生系统的建立与性能评估

针对气溶胶测量仪器校准和实验室气溶胶光学特性研究的需求,搭建了一套标准气溶胶发生系统,并对其性能开展了测试研究.系统采用恒定流量的雾化器产生气溶胶,经过扩散干燥管干燥以及电荷中和器带电中和后,产生标准气溶胶粒子.利用氯化钠样品对系统的性能进行了测试,结果表明,当样品溶液浓度增加时,系统雾化产生粒子的数浓度和粒径均随之增加;当载气气压增加,系统雾化产生粒子的数浓度随之增加,而粒径随之减小.在测试时间内,系统发生的多分散气溶胶粒子的几何平均粒径波动小于1%,总粒子数浓度波动小于2%,单分散气溶胶粒子数浓度的稳定性好于4%.     

天津市PM_(2.5)在线源解析成分特征谱库构建研究

根据天津市颗粒物源解析结果,选取扬尘、燃煤、机动车尾气、工业生产、生物质燃烧及餐饮油烟等典型PM_(2.5)排放源,利用单颗粒气溶胶质谱仪开展天津市PM_(2.5)在线源解析成分特征谱库的构建研究。应用自适应共振理论神经网络分类算法(ART-2a)对采集的数据进行分析,确定了天津市PM_(2.5)的成分谱特征。通过对PM_(2.5)源谱离线与在线组分测试结果的相关性分析,得出各类污染物在线源解析源谱具有较好的代表性,能够定性反映各类污染源的基本信息,可作为在线源解析受体样品进行匹配的依据使用。     

一种纳米气溶胶发生系统的设计及性能测试

气溶胶发生系统是校准大气颗粒物测量仪器、研究纳米颗粒物特性和开展烟雾箱模拟实验的必备仪器之一.针对现有气溶胶发生仪器稳定性差和不利于外场监测等缺点,本研究设计了一款新型纳米气溶胶发生系统(包括气溶胶发生器和扩散干燥管),并通过搭建实验系统对该仪器的工作性能进行了测试.在性能测试中使用氯化钠(NaCl)-水溶液和癸二酸二辛酯(DOS)-异丙醇溶液分别产生固态NaCl和液态DOS气溶胶,利用扫描电迁移率粒径谱仪测试生成气溶胶的粒径分布.测试结果表明,通过调节溶液浓度(0.01～0.50 g·L-1)和载气流量(1.64～3.67 L·min-1),生成不同大小(几何平均粒径:25～51nm)和不同数浓度(106～107个·cm-3)的气溶胶.对仪器稳定性能测试发现,在3 h的测试时间里生成的气溶胶几何平均粒径变化小于6%,数浓度变化小于12%.     

PM2.5旋风切割器的性能测试与模拟

切割器是PM_(2.5)采样器的关键部件,其性能的优劣将直接影响到采样结果的准确性,对其性能进行测试有助于评估PM_(2.5)采样器采样结果的准确性和可比性.因此,本研究选取两种应用广泛的BGI公司和URG公司生产的PM_(2.5)旋风切割器,分别采用多分散气溶胶和单分散气溶胶标定装置对其性能进行了测试.结果表明,两种装置的测试结果基本一致.BGI和URG切割器的切割粒径D50为(2.5±0.2)μm,能够满足环境空气PM_(2.5)采样要求(HJ 93-2013);BGI切割器的捕集效率几何标准偏差δg为1.2±0.1,满足要求;而URG切割器的δg超出规定范围.同时,本研究获得了切割器采样流量Q与D50的关系式,可通过该关系式改变切割器的Q获得所需的D50;为使BGI切割器的D50在规定的范围内,其流量偏差需限定在设计流量(即16.7 L·min-1)的-1.0%~16.7%之间,而URG切割器的流量偏差需限定在设计流量的-1.3%~16.2%之间.其次,获得了切割器流动雷诺数Ref与无量纲切割粒径D50/DC的关系式,利用该关系式可在保持设计流量不变的情况下,通过改变切割器的出口管尺寸,得到所需的D50.最后,获得了切割器Q与压力损失△P的关系式,采用5种模型对两种切割器的无量纲阻力系数KL进行模拟计算,并与测试计算结果进行比较,发现CasalMartinez模型、Coker模型和Demir模型更适用于BGI旋风切割器的△P预测,而ShepherdLapple模型和CasalMartinez模型更适用于URG旋风切割器的△P预测.     

基于观测的大气气溶胶散射吸湿增长因子模型研究 ——以2006 CAREBeijing加强观测为例

在2006年北京加强观测期间,以颗粒物－液体转换采集系统(PILS)测量的气溶胶各可溶性离子组分的质量浓度、颗粒物分级采样器(MOUDI)测量的各可溶性离子组分及有机碳(OC)、碳黑(EC)的分级质量谱分布为基础,对离子组分的可能存在形态进行判断,计算了化学组分质量浓度及各化学物种的粒径数谱浓度;利用Mie模型及各化学物种的密度、折射率、吸湿粒径增长因子等参数计算得到外混、内混的粒子群在干燥状态、不同相对湿度下的散射系数,最终计算得到不同化学组分外混、内混状态下的散射吸湿增长因子;将模型模拟的气溶胶散射吸湿增长因子与观测得到的该因子进行对比,发现模拟值与观测值能够在一定误差范围内吻合,实现了该因子的闭合实验.     

泉州郊区春节燃放烟花时段大气污染特征

研究了泉州郊区2009年春节燃放烟花期闯空气污染特征.采用在线监测和中流量采样器对该时段气溶胶进行了颗粒物实时监测和采集.目的是阐明泉州郊区燃放烟花期间大气中颗粒物、多环芳烃(PAHs)和水溶性离子的浓度及分布特征,探讨其污染物的来源.结果表明,除夕00:57-01:27为颗粒物浓度受燃放烟花影响最大时段,PM205和...     

南京北郊大气颗粒物的粒径分布及其影响因素分析

在南京北郊使用FA-3型9级采样器对2014年1~11月颗粒物的粒径分布进行了采样分析.首先将FA-3与中流量分级采样器(KC-120H)和环境保护局在线监测仪器的同期监测结果进行对比,数据相关系数均在0.95以上,对细粒子FA-3分别偏低13.9%和16.6%,而对PM_(10)偏高15.2%和13.3%,但采样偏差在大气采样可接受范围之内,说明其可以对大气颗粒物进行准确分级和采样.南京北郊颗粒物污染严重,PM_(1.1),PM_(2.1)和PM_(10)的年平均浓度分别为(65.6±37.6)、(91.0±54.7)和(168.0±87.0)μg·m-3,污染以细粒子为主,且大部分在1.1μm以下;颗粒物粒径呈双峰分布,峰值位于0.43~0.65μm和9~10μm粒径段;中值粒径为1.83μm,为积聚模态污染.颗粒物粒径分布在冬季细粒径段较高,春季粗粒径段较高,夏季细粒径段降低并不明显,粗粒径段明显低于其他季节;颗粒物浓度的昼夜变化在粗粒径段差异很小,在细粒径段基本表现出夜晚大于白天的特征.除了夏季,降水对各个粒径范围的颗粒物都有清除作用,且在细粒径段表现得更为明显;霾发生时随着霾等级的加重,0.43~2.1μm粒径段颗粒物浓度逐渐增加,该粒径段颗粒物质量浓度与能见度呈显著负相关.以相对湿度70%为界,颗粒物粒径分布发生了明显变化,湿度大于70%后,小于0.43μm粒径段颗粒物质量浓度显著降低,而0.43~2.1μm粒径段明显上升,颗粒物的吸湿增长应是主要原因.南京北郊的气团来源可以分为四类,其中西北方向快速输送的气团最为洁净,细粒径颗粒物浓度明显低于其它方向;本地和周边近距离输送的气团污染最重,粗细粒径颗粒物浓度都较高,其传输距离短,风速小,发生污染的概率最大,达到73.9%,对南京市的空气污染贡献较大.     

山西某电厂燃煤烟气SO_3与颗粒物排放特征

某330 MW电厂燃煤机组的污染物脱除设备(SCR脱硝塔、电除尘器、湿式电除尘器)进行了改造,并进行了污染物排放检测,得到SO_2、NO_x、颗粒物排放浓度分别为5.1,4.1,4.2 mg/m3,符合超低排放的标准。运用虚拟撞击采样器对湿式电除尘器进行了颗粒物分级浓度检测,得到PM_(2.5)、PM_(2.5~10)、PM_(>10)的脱除效率分别为83.29%、93.06%、96.51%,湿式电除尘器对PM_(2.5)脱除效果明显。对电除尘器进出口灰样进行元素分析和粒径分析,得到SO_3与颗粒物中碱性物质结合协同脱除效率为10.09%,粒径>13μm颗粒物在除尘器内部趋近于完全脱除。     

气溶胶粒度分布的在线测量实验研究

随着雾、霾等气溶胶引起环境问题的加剧,对大气气溶胶特性的研究也越来越深入。该文重点研究了光学粒径谱仪在气溶胶粒度分布在线测量上的应用。通过对比3款典型粒径谱仪的测量原理、测量范围、测量精度等特征,选用光学粒径谱仪系列(OPS)是比较适合在线测量自然环境下大气气溶胶粒度分布的。通过一系列对大气气溶胶中典型的固体和液体气溶胶的在线测量实验,发现更换HEPA过滤器对在线测量的结果有影响,而不同采样时长和不同通道区间不会影响OPS对大气气溶胶的在线测量。     

北京雾霾天大气颗粒物中微生物气溶胶的浓度及粒谱特征

于2013年1月8日~2013年2月4日雾霾频繁暴发期间,使用定量空气微生物采样器和气溶胶粒谱测试仪测试并比较了雾霾天和之后的清朗天气下细菌、真菌气溶胶浓度变化、粒谱分布及不同粒径大小颗粒物的数量浓度差异和粒谱分布特征.结果表明,采样周期内真菌气溶胶小于5μm的粒子(可吸入肺粒子)所占百分比显著高于细菌气溶胶小于5μm的粒子百分比.雾霾过后的晴朗天气下细菌、真菌气溶胶浓度高于雾霾天气时的浓度,而颗粒物浓度则相反.无论雾霾天或晴朗天微生物气溶胶的粒谱分布无显著差别,空气中的颗粒物以PM1.0占绝大多数.     

北京大气气溶胶表面无机组分的静态飞行时间二次离子质谱研究

采用特定的样品处理方式,利用静态飞行时间二次离子质谱(Static-TOF-SIMS)技术,对使用通用型大气污染物采样仪VAPS(URG-3000K)采集于非导电性的滤膜(聚碳酸酯滤膜)上的大气气溶胶细粒子(PM_2.5)与粗粒子(PM_2.5～10)的表面无机组分进行了探索性的比较分析.结果表明:大气气溶胶细粒子与粗粒子的表面无机组分组成特征具有明显的差异;气溶胶细粒子表面存在着大气中二次形成的亲水性化合物,会对其表面的疏水性/亲水性特征产生影响,从而影响其大气化学行为;气溶胶粗粒子表面存在氟化物,对生态环境和人体健康具有潜在的危害性,应该重视对气溶胶中氟污染的研究与控制;静态飞行时间二次离子质谱可以成为研究大气气溶胶表面化学组成特征的有利分析手段.      

上海霾与非霾期间大气颗粒物光学特性垂直分布特征和质量浓度对比研究

采用美国国家航空航天局的云-气溶胶激光雷达红外开拓者卫星搭载的正交极化云-气溶胶激光雷达数据产品,包括消光系数、光学厚度、总后向散射系数、体积退偏比和色比,结合地面监测的颗粒物质量浓度,分析上海大气相对湿度小于80%霾发生期间气溶胶光学属性的垂直分布特征和颗粒物质量浓度变化,并与非霾期间进行比较.结果表明:霾期间532 nm和1064 nm消光系数在垂直高度上(海拔:0~10 km)均大于非霾期间,且大多数霾期间颗粒物在整层大气的光学厚度大于非霾期间.在近地面,霾期间大气颗粒物散射能力大于非霾期间.各垂直高度层,霾与非霾期间小粒径和规则气溶胶占主导地位.霾期间近地面大粒径颗粒物在霾期间所占比例大于非霾期间;2.0~4.0 km高度层,霾和非霾期间细颗粒所占比例接近;4.0~10.0 km高度层,霾期间细颗粒气溶胶所占比例大于非霾期间.PM1、PM2.5和PM10质量浓度在霾期间均大于非霾期间,且霾期间细颗粒物所占比例明显增加.颗粒物质量浓度和比值PM1/PM2.5和PM2.5/PM10分别随霾污染程度的加重而升高.冬季颗粒物质量浓度最高,主要来自细颗粒物的贡献;而春季PM10质量浓度高于其它季节.     

珠三角地区利用PM2.5反演气溶胶数浓度谱方法

大气气溶胶数浓度谱分布(PNSD)对于大气辐射和光学计算至关重要,利用目前普遍观测的气溶胶质量浓度(PM_(2.5))来反演计算PNSD,能有效补充PNSD观测的不足,对于需要PNSD信息的研究工作如大气能见度计算等有重要的实用价值.本文利用2014年11月～2015年1月在广州城市站进行同期连续观测的干气溶胶粒子的PM_(2.5)、PNSD数据进行客观分析,建立了一种使用PM_(2.5)反演PNSD的方法,并评估了该方法的适用性.结果表明该反演算法具有较好地适用性和稳定性,对于积聚模态的PNSD反演效果较好,但对于PM_(2.5)高浓度的反演结果差异较大.该反演方法将为珠三角地区的大气能见度计算和应用提供有利的依据和支撑.     

Chemical characterization of size-resolved aerosols in four seasons and hazy days in the megacity Beijing of China

Size-resolved aerosol samples were collected by MOUDI in four seasons in 2007 in Beijing. The PM₁₀ and PM_1.8 mass concentrations were 166.0 ± 120.5 and 91.6 ± 69.7 μg/m³, respectively, throughout the measurement, with seasonal variation: nearly two times higher in autumn than in summer and spring. Serious fine particle pollution occurred in winter with the PM_1.8/PM₁₀ ratio of 0.63, which was higher than other seasons. The size distribution of PM showed obvious seasonal and diurnal variation, with a smaller fine mode peak in spring and in the daytime. OM (organic matter = 1.6 × OC (organic carbon)) and SIA (secondary inorganic aerosol) were major components of fine particles, while OM, SIA and Ca^2 + were major components in coarse particles. Moreover, secondary components, mainly SOA (secondary organic aerosol) and SIA, accounted for 46%–96% of each size bin in fine particles, which meant that secondary pollution existed all year. Sulfates and nitrates, primarily in the form of (NH₄)₂SO₄, NH₄NO₃, CaSO₄, Na₂SO₄ and K₂SO₄, calculated by the model ISORROPIA II, were major components of the solid phase in fine particles. The PM concentration and size distribution were similar in the four seasons on non-haze days, while large differences occurred on haze days, which indicated seasonal variation of PM concentration and size distribution were dominated by haze days. The SIA concentrations and fractions of nearly all size bins were higher on haze days than on non-haze days, which was attributed to heterogeneous aqueous reactions on haze days in the four seasons.     

Hydrocarbons in particulate samples from wildfire events in central Portugal in summer 2010

In summer 2010, twenty eight(14 PM_(2.5)samples plus 14 samples PM_(2.5–10)) smoke samples were collected during wildfires that occurred in central Portugal. A portable high-volume sampler was used to perform the sampling, on quartz fibre filters of coarse(PM_(2.5–10)) and fine(PM_(2.5)) smoke samples. The carbonaceous content(elemental and organic carbon) of particulate matter was analysed by a thermal–optical technique. Subsequently, the particulate samples were solvent extracted and fractionated by vacuum flash chromatography into three different classes of organic compounds(aliphatics, polycyclic aromatic hydrocarbons(PAHs) and carbonyl compounds). The organic speciation was performed by gas chromatography–mass spectrometry(GC–MS). Emissions were dominated by the fine particles, which represented around 92% of the PM_(10). A clear predominance of carbonaceous constituents was observed, with organic to elemental carbon(OC/EC)ratios ranging between 1.69 and 245 in both size fractions. The isoprenoid ketone6,10,14-trimethyl-2-pentadecanone, a tracer for secondary organic aerosol formation, was one of the dominant constituents in both fine and coarse particles. Retene was the most abundant compound in all samples. Good correlations were obtained between OC and both aliphatic and PAH compounds. Pyrogenic processes, thermal release of biogenic compounds and secondary processing accounted for 97% of the apportioned PM_(2.5)levels.     

Influence of different weather events on concentrations of particulate matter with different sizes in Lanzhou, China

The formation and development of weather events has a great impact on the diffusion, accumulation and transport of air pollutants, and causes great changes in the particulate pollution level. It is very important to study their influence on particulate pollution. Lanzhou is one of the most particulate-polluted cities in China and even in the world. Particulate matter (PM) including TSP, PM_>10, PM_2.5-10, PM_2.5 and PM_1.0 concentrations were simultaneously measured during 2005-2007 in Lanzhou to evaluate the influence of three kinds of weather events - dust, precipitation and cold front - on the concentrations of PM with different sizes and detect the temporal evolution. The main results are as follows: (1) the PM pollution in Lanzhou during dust events was very heavy and the rate of increase in the concentration of PM_2.5-10 was the highest of the five kinds of particles. During dust-storm events, the highest peaks of the concentrations of fine particles (PM_2.5 and PM_1.0) occurred 3 hr later than those of coarse particles (PM_>10 and PM_2.5-10). (2) The major effect of precipitation events on PM is wet scavenging. The scavenging rates of particles were closely associated with the kinds of precipitation events. The scavenging rates of TSP, PM_>10 and PM_2.5-10 by convective precipitation were several times as high as those caused by frontal precipitation for the same precipitation amount, the reason being the different formation mechanism and precipitation characteristics of the two kinds of precipitation. Moreover, there exists a limiting value for the scavenging rates of particles by precipitation. (3) The major effect of cold-front events on particles is clearance. However, during cold-front passages, the PM concentrations could sometimes rise first and decrease afterwards, which is the critical difference in the influence of cold fronts on the concentrations of particulate pollutants vs. gaseous pollutants.     

滨海城市气溶胶中颗粒态汞的分布特征

与气溶胶颗粒相结合的汞,即颗粒态汞,不仅对人体健康及生态环境产生一定的危害,而且在汞的生物地球化学过程扮演重要角色.以我国东南滨海城市厦门市为研究对象,采集郊区、居民区、旅游区、工业区和背景区四季(2008年10月～2009年8月)的PM2.5、PM10和TSP样品,基于塞曼原子吸收法的俄罗斯LumexRA-915+汞分析仪对大气不同粒径颗粒物中颗粒态汞进行了测试.结果表明,厦门市大气不同粒径颗粒物中汞的含量均表现为冬、春两季的浓度明显高于夏、秋两季;春、夏、秋、冬四季细颗粒物(PM2.5)中的含量分别为(51.46±19.28)、(42.41±12.74)、(38.38±6.08)和(127.23±33.70)pg/m3.不同粒径颗粒物中汞主要分布在PM2.5中,占到颗粒物态汞的42.48%～67.87%,表明细粒子富集汞的能力较强.不同功能区颗粒态汞的浓度分布趋势为背景区居民区旅游区工业区郊区,说明颗粒态汞浓度的空间分布特征与采样点的环境功能密切相关.总体而言,滨海城市大气颗粒态汞含量较低;PM2.5对颗粒态汞的富集明显高于PM10和TSP,表明对颗粒态汞的控制应集中在细颗粒物污染上.     

Local PM10 and PM2.5 emission inventories from agricultural tillage and harvest in northeastern China

Mineral particles or particulate matters(PMs) emitted during agricultural activities are major recurring sources of atmospheric aerosol loading.However,precise PM inventory from agricultural tillage and harvest in agricultural regions is challenged by infrequent local emission factor(EF) measurements.To understand PM emissions from these practices in northeastern China,we measured EFs of PM_(10) and PM_(2.5) from three field operations(i.e.,tilling,planting and harvesting) in major crop production(i.e.,corn and soybean),using portable real-time PM analyzers and weather station data.County-level PM_(10) and PM_(2.5) emissions from agricultural tillage and harvest were estimated,based on local EFs,crop areas and crop calendars.The EFs averaged(107 ± 27),(17 ± 5) and 26 mg/m~2 for field tilling,planting and harvesting under relatively dry conditions(i.e.,soil moisture 15%),respectively.The EFs of PM from field tillage and planting operations were negatively affected by topsoil moisture.The magnitude of PM_(10) and PM_(2.5) emissions from these three activities were estimated to be 35.1 and 9.8 kilotons/yr in northeastern China,respectively,of which Heilongjiang Province accounted for approximately45%.Spatiotemporal distribution showed that most PM_(10) emission occurred in April,May and October and were concentrated in the central regions of the northeastern plain,which is dominated by dryland crops.Further work is needed to estimate the contribution of agricultural dust emissions to regional air quality in northeastern China.     

北京市海坨山冬季不同污染过程下气溶胶化学组分及其潜在来源分析

为了探讨京津冀地区冬季背景大气中气溶胶化学组分特征及其来源分布,使用GRIMM 180、单颗粒黑碳光度计(SP2)和高分辨率飞行时间气溶胶质谱仪(HR-TOF-AMS)观测了海坨山2020年12月28日至2021年2月3日PM和化学组分,结合气象数据和HYSPLIT模式,计算了潜在源贡献因子(PSCF)和浓度权重轨迹(...