河北省涞水县大气颗粒物单颗粒分析表征及来源识别

为了解河北省涞水县颗粒物污染特征,采用单颗粒分析技术扫描电镜-X射线能谱法和气团后向轨迹分析技术对该县2015年3个典型污染时段〔即正常管控、严格管控（2015年阅兵期间）及发生严重颗粒物染污〕采集的7个大气颗粒物样品进行了分析表征和来源解析.共测量了1 506个粒径≥0.5 μm的单颗粒,其中粒径小于2.5 μm的颗粒占98%以上,测量结果揭示了细颗粒污染特征.结果表明:①碳质颗粒为主要颗粒物种类,其检出数目占比在90%以上.②非供暖期严格管控时段,当地居民日常生活产生的球形碳质颗粒检出数目占比最高.③非供暖期正常管控时段,机动车排放的碳质集合体颗粒检出数目占比最高,交通污染贡献最大.④供暖期球形碳质颗粒检出数目占比最高,含硫颗粒检出数目占比相对增加,燃煤的贡献最大.3个采样时段48 h气团后向轨迹分析结果表明,在空气质量良好、颗粒物污染水平较低的情况下,影响研究区域空气质量的主要是本地源;雾霾天气（处于严重颗粒物污染时段）时,西南方向外来源和本地源共同构成研究区域的颗粒物污染状态.      

Measurement and evaluation of acid air pollutants in Chicago using an annular denuder system

The cyclone/annular denuder/filter pack sampling system (ADS) was used to collect and evaluate ambient air pollutants in Chicago. Eighty-one 12-h samples, equally divided into day/night intervals, were collected from April 1990 to March 1991. The chemical species measured were HNO₃, HNO₂, SO₂ and NH₃ in the gas phase, and SO₄²⁻, NO₃⁻, NH₄⁺, and H⁺ in the particulate phase.The ADS data were collected simultaneously with PM10 samples. The particulate matter was analysed for elemental composition. These compositions were combined with the ADS observations and subjected to evaluation using a chemical mass balance receptor model (CMB). From the CMB analysis, the sum of the contributions from soil (15%), mobile (14%), incinerator (2%), coal (0.6%), steel (0.3%) and refinery (0.2%) was 32% of the PM10. NO₃⁻, which was not included in the fingerprints, represented an additional 9% of the PM10. Residual SO₄²⁻ and residual organic carbon, possibly formed in the atmosphere, represented an additional 22 and 20% of the PM10, respectively, leaving only 17% from other unidentified sources. From the standpoint of source contributions of sulfur and nitrogen compounds, coal combustion (23%) and refinery emissions (23%) are the major contributors of ambient sulfur (with 49% from unidentified sources). Mobile sources (87%) contributed most of the ambient nitrogen (with only 2% from unidentified sources).     

Characteristics of air particulate matter and their sources inurban and rural area of Beijing, China

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粤港澳地区大气中有机污染物初步研究

用Ｔｅｋｍａｒ多填层吸附管连接ＴＭＰ－１５００空气采样采集ＶＯＣｓ样,然后在Ｔｅｋｍａｒ６０３２／３０００吹扫捕集系统与ＧＣ／ＭＳＤ联用仪上分析,用ＴＨ－１０００Ｌ型大量采样器收集ＴＳＰ气溶胶样,ＴＳＰ滤膜经抽提分离后,烷径和芳烃进行ＧＣ／ＭＳＤ分析,了广州,香港和澳门地区大气 有机物和气溶胶可溶有机物的与成因。     

南京市可吸入颗粒物（PM10）来源解析研究

基于《南京市环境空气中可吸入颗粒物（PM10）源解析及控制对策研究》课题研究成果,课题于2004年-2005年间共采集了197个源和受体样品,每个样品分析测试了三类化学元素,采用化学质量平衡（CMB）模型解析南京市环境空气中可吸入颗粒物的来源,其中48%来源于扬尘、土壤尘等开放源类。研究认为扬尘等开放源类是南京市可吸入颗粒物污染的首要因素。     

青岛大气气溶胶中氨基化合物的分布特征

氨基化合物是大气气溶胶和雨水中常被检出的一类有机氮化合物,由于其可作为生物生长直接的氮源,因此可能对海洋生态系统产生直接作用.利用2008年1～12月在青岛采集的66个总悬浮颗粒物样品,采用邻苯二甲醛/N-乙酰-L-半胱氨酸柱前衍生高效液相色谱法,分析了其中溶解态(DAC)和颗粒态氨基化合物(PAC)的浓度.气溶胶中DAC浓度为2.4～40.9nmol·m-3,在春季最高,夏季次之,秋季、冬季最低.PAC浓度为0.7～76.1nmol·m-3,呈现春季冬季秋季夏季的变化趋势.不同季节氨基化合物的组成不同.依据气团的后向轨迹,气溶胶样品可分为受北方陆源、南方陆源和海洋源影响,DAC和PAC在受南方陆源影响的气溶胶中浓度最高,北方陆源次之,海洋源气溶胶中最低.不同来源的气溶胶中氨基化合物的组成不同,蛋白质类氨基化合物对总氨基化合物的贡献在海洋源气溶胶中最高,在南方源气溶胶中最低.     

Distribution of PCDDs,PCDFs and PCBs in the atmosphere

Air samples were collected through the summer season using quartz fiber filter (QMF) and polyurethane foam plugs (PUF) with high volume air sampler. The QMF and PUF samples were analyzed for polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs), chlordanes and DDE by high resolution gas chromatography with mass spectrometry (HRGC-MS). We have previously reported the concentrations of these compounds in urban air. In this study we present: (1) daily variability; (2) vapor/particulate ratio of these compounds. Daily variability of these compounds in ambient air was discussed with meteorological factors. The major parts of PCDDs and PCDFs exist in the particulate phase. Chlordanes, PCBs, and DDE exist in the vapor phase at 98%,96% and 95%, respectively.     

用同位素方法评估天津市汽油无铅化进程

用同位素技术研究和评估天津市汽油无铅化进程.采用稀酸浸出法处理天津市1994～2001年冬春季节123个玻璃纤维滤膜大气颗粒物样品,测量了大气铅浓度和同位素丰度比(²⁰⁶Pb/²⁰⁷Pb).结果表明,1994～2001年是我国汽油无铅化的重要时段,这期间大气颗粒物样品铅浓度有所下降,铅的同位素丰度比逐渐增加,表征了汽油无铅化进程中汽车尾气的贡献率减少,其他来源的贡献率上升.在汽油无铅化后,我国还应加强对铅污染的综合治理.     

Source profiles by unique ratios (SPUR) analysis: Determination of source profiles from receptor-site streaker samples

A streaker total filter particulate sampler was operated for three weeks at an urban site in Milan, Italy. The filters were analysed by Particle Induced X-ray Emission (PIXE), yielding hourly concentrations of 15 elements. The data are used to extract source elemental profiles using a new method, SPUR (Source Profiles by Unique Ratios). The SPUR technique is a combination of event identification using unique elemental ratios in sources, and correction for background events by identifying events of differing time constants in the time domain. The elemental ratios are identified in plots of log([S]/[T])vs[T], referred to as SPUR plots, where T is a (non-unique) tracer and [S] is an element establishing the unique ratio. Using the SPUR technique, eight distinct sources are identified and profiles established. The sources are: two metallurgical smelters, two crustal sources, a potassium-rich source, automotive, regional crustal and regional sulphur. Results are compared with source profiles derived from Absolute Principal Component Scores analysis. SPUR analysis demonstrates powerful capability for deriving source profiles from receptor samples, including having the capability of distinguishing between sources of similar composition without using a unique tracer element.     

北京夏季典型天气TSP组成和来源对比

于2005年7月选择分别受北方冷空气、海上高压和地方性山谷风影响的3个天气过程条件下,在北京市区和郊区采集了23个大气总悬浮颗粒物(TSP)样品,并采用扫描电镜-X射线能谱技术,根据单颗粒尺度、形貌、特征化学组成解析出各类源对颗粒数浓度的贡献.结果发现:有机/碳质颗粒(占总颗粒数的31.3%,下同)和矿物颗粒(占29.5%)为优势种类,二次源颗粒占10.6%,燃煤飞灰占7.2%,燃煤、机动车排放和建筑施工产生的3类颗粒占4.1%～6.5%.3种天气下颗粒组成特征鲜明,来源差别明显:①冷空气影响下空气质量最好,TSP样品中粒径小于1.0 μm和大于5.0 μm颗粒较多,一次源处于绝对主导地位(占90%);②海上高压控制天气下,粒径为1.0～2.5 μm的颗粒大幅度增加,有大量的次生粒子生成(占10%～20%);③地方性天气中颗粒质量浓度偏高,粒径小于1.0 μm和1.0～2.5 μm颗粒所占比例均较高,但有机/碳质颗粒比例减少, 其他次要种类颗粒增多.市区人为源颗粒的种类最多,对郊区影响明显.      

黄海近岸大气降水中磷溶解度及其影响因素

于2020年6~9月在黄海近岸城市青岛采集31场降水69个样品,分析其中总磷（TP）、溶解态总磷（DTP）及溶解态无机磷（DIP）和有机磷（DOP）,探讨P浓度和溶解度的变化特征及其影响因素.降水中TP浓度为（6.2±1.0）μg/L,DTP浓度为（3.8±0.6）μg/L,P溶解度为（64.8±18.0）%.DTP中以DIP为主,其贡献为（56.5±21.6）%.降水中TP和DTP与降水量呈负幂指数关系,TP清除指数大于DTP.降水量<10mm时,降水对气溶胶P的清除和稀释作用显著影响降水中P浓度,但降水量>40mm时,这种作用对P浓度的影响不大.降水对气溶胶P的清除作用以云下清除为主,占总清除效率的70%~85%.酸化作用显著促进降水中颗粒态P溶解,且无机P溶解效率高于有机P.对降雨量<5mm及>30mm降水,pH值是影响P溶解度的主要因素,降水量和气团来源对P溶解度也有一定影响.当pH值相近时,降水量越大,P溶解度越高;当pH值相近且降水量<5mm时,海洋源贡献越大,P溶解度越高.对降水量5~30mm的降水,P溶解度受到降水量、pH值及气团来源等因素的共同影响.     

基于化学分析和气象信息综合表征大气铅污染

对天津市1998年11月-1999年2月期间21个玻璃纤维滤膜大气颗粒物样品,采用稀酸浸出法溶解后,测量了ρ(Pb),w(Pb)和同位素丰度比206Pb/207Pb.采用IDAS软件对样品进行聚类分析,分组的结果表明,在不同的天气条件下,各种污染源排放的贡献也不同.48 h反向风迹图提供了大量详实的气象信息,结合ρ(TSP),ρ(Pb),w(Pb)和同位素丰度比的数据,可用于综合表征铅污染的状况.      

Understanding the sources and composition of the incremental excess of fine particles across multiple sampling locations in one air shed

Well-designed health studies and the development of effective regulatory policies need to rely on an understanding of the incremental differences in particulate matter concentrations and their sources. Although only a limited number of studies have been conducted to examine spatial differences in sources to particulate matter within an air shed, routine monitoring data can be used to better understand these differences. Measurements from the US EPA Chemical Speciation Network （CSN） collected between 2002-2008 were analyzed to demonstrate the utility of regulatory data across three sites located within 100 km of each other. Trends in concentrations, source contribution, and incremental excesses across three sites were investigated using the Positive Matrix Factorization model. Similar yearly trends in chemical composition were observed across all sites, however, excesses of organic matter and elemental carbon were observed in the urban center that originated from local emissions of mobile sources and biomass buming. Secondary sulfate and secondary nitrate constituted over half of the PM2.5 with no spatial differences observed across sites. For these components, the excess of emissions from industrial sources could be directly quantified. This study demonstrates that CSN data from multiple sites can be successfully used to derive consistent source profiles and source contributions for regional pollution, and that CSN data can be used to quantify incremental differences in source contributions of across these sites. The analysis strategy can be used in other regions of the world to take advantage of existing ambient particulate matter monitoring data to better the understanding of spatial differences in source contributions within a given air shed.     

基于质谱技术的在线大气颗粒物来源与污染过程解析研究——以江苏省淮安市为例

通过大气细颗粒物实时在线源解析技术(质谱直接测量法)采集录入淮安市市区部分特征污染源排放成分谱,对淮安市大气细颗粒物进行在线源解析,获取高时间分辨的颗粒物源解析结果,分析颗粒物来源、季度变化和重污染天气的污染过程,评估形成重污染过程的污染影响因子和影响程度,为区域大气污染综合整治提供重要目标指向,同时也为淮安环境空气PM2.5重度污染实时预警与监控、大气污染源减排方案评估、污染事件监控等提供有效的在线监测技术平台.     

青岛大气气溶胶中微量元素溶解度及影响因素

利用2012年12月在青岛采集的31个总悬浮颗粒物（TSP）样品,分析其中11种微量元素的总浓度和溶解态浓度,讨论了沙尘负载、气溶胶来源、酸过程及天气条件对微量元素溶解度的影响.结果表明,Fe和Al的溶解度<5%,Pb、Ba、Bi的为10%左右,Cu、V、Cd、Mn的为20%~30%,Zn和As的约为40%.随着沙尘负载量的增加,气溶胶中微量元素溶解度呈规律性递减.气团后向轨迹聚类分析和正矩阵因子分析（PMF）结果显示,受人为源影响的气溶胶中微量元素溶解度明显高于受沙尘源影响的,受二次生成源和海洋源影响的的气溶胶中微量元素溶解度明显高于受土壤源影响的.大气酸过程是造成这些差异的主要原因.相关性分析表明,SO₄^2-、NO₃^-和有机酸等酸组分均对微量元素溶解度有一定影响.霾天时气溶胶中微量元素溶解度明显低于雾天的,其原因为酸组分在较高的相对湿度下更能促进微量元素溶解度的提高.     

Vertical characteristics and source identification of PM10 in Tianjin

Ambient PM₁₀ (particulate matter with a diameter less than 10 μm) concentrations were measured on a 255 meter tower in Tianjin, China. The samples were collected at four vertical levels (10, 40, 120 and 220 m). Vertical characteristics for PM₁₀ samples were studied. The results showed that the concentrations of PM₁₀ and constituent species had a negative correlation with the sampling height. The highest concentrations of PM₁₀ and species were obtained at the 10 m level, and the lowest concentrations were measured at the 220 m level. For the fractions of species to total mass, SO₄^2- and NO₃^- had higher values (fraction) at greater height; while Ca had a higher fraction at lower height. Possible source categories for the PM₁₀ ambient dataset were identified by the principal component analysis method. The possible source categories included crustal dust, vehicles, cement dust, and incineration as well as secondary sulfate and nitrate sources. Analysis of meteorological factors on PM₁₀ concentrations indicated that wind speed and inversion may be the main factors contributing to different concentrations of PM₁₀ at different heights.     

Analysis of particulate organics in a forest atmosphere by thermodesorption GC/MS

Aerosol samples from a forest site were collected on glass fiber filters, and particulate bound organics were analyzed by a thermodesorption GC/MS procedure. A conventional GC injector was modified to enable the insertion of loaded filter samples without disarranging the GC-system. Seven commercial glass fiber filter types were tested for performance with regard to sampling and analysis requirements. Sixty-six substances were detected in aerosol samples, 40 organics, mainly n-alkanes, phthalic acid esters, fatty acids, fatty acid esters, n-alkane nitriles and polycyclic aromatic hydrocarbons (HCs) were identified. Comparative measurements of samples collected at an urban site and in flat showed only small differences for the ratio of the main constituents identified.     

南昌市PM2.5中结合氨基酸的浓度组成及来源

采集了春季南昌市城市和森林地区的大气PM_2.5样品及潜在大气氨基酸排放源（植物和土壤）样品,测定并分析了样品中结合氨基酸（CAAs）的浓度、组成及甘氨酸（Gly）的氮同位素值.结果表明,城市和森林地区PM_2.5中总CAAs的浓度分别为0.507~3.912和0.497~2.647nmol/m³.通过对PM_2.5中CAAs组成占比分析发现,城市和森林地区CAAs组成成分相似,其中Pro、Gly、Ala、Leu和His是PM_2.5中丰富的CAAs物种.结合Gly的氮同位素值可知,城市地区（+0.62‰~+22.67‰）和森林地区（+1.99‰~+23‰） PM_2.5中δ¹⁵N_C-Gly值表现出较大的变化范围.根据大气CAAs潜在排放源δ¹⁵N值清单,本研究中生物质燃烧、土壤源和植物源是PM_2.5中CAAs的主要来源.贝叶斯稳定同位素模型计算源分配结果表明生物质燃烧、土壤源和植物源对城市地区PM_2.5中CAAs的平均贡献为42%、40%和18%,对森林地区PM_2.5中CAAs的平均贡献为38%、38%和24%.     

南京北郊大气细粒子硝基苯酚类化合物污染特征与来源

硝基苯酚类化合物是大气中普遍存在的一类含氮有机物,也是大气吸光性有机物(即棕色碳)的重要组成部分,对气候变化、空气质量和人体健康都具有重要影响.自2019年3月至2020年1月于南京北郊地区采集了共265个大气细粒子(PM2.5)日样品,并利用超高效液相色谱质谱联用仪(UHPLC-MS)定量分析样品中的8种硝基苯酚类化...     

贵阳市一居民区大气颗粒态汞的污染状况

2004年4、7、8、11、12月采用微型捕集管-冷原子荧光光谱法对贵阳市一个居民区大气中的痕量颗粒态总汞(TPM)进行了测定。结果表明:TPM日均浓度范围是0.149~4.853 ng.m-3,平均值是1.091 ng.m-3,显著高于背景参考值1~86 pg.m-3;TPM浓度采暖期大于非采暖期,夜间通常大于白昼;TPM与大气气态总汞(TGM)可能具有同源性;燃煤、垃圾焚烧以及周边工厂排放的含尘烟气可能是居民区大气颗粒态汞的主要人为来源。