南京市冬季PM2.5中水溶性离子污染特征研究

基于城市超级站对2018年12月—2019年2月南京市在线水溶性离子污染特征进行研究。结果表明：监测期间水溶性无机离子(WSIs)质量浓度均值为45.7μg/m3,占PM2.5的67.8%,各离子排序为NO3-＞ SO42-＞NH4+＞Cl-＞K+＞Ca2+＞Na+＞Mg2+。二次离子（SNA）是PM2.5主要组分,大气气溶胶呈中性。各离子日变化存在差异,SNA变化趋势和WSIs基本一致。南京市冬季存在明显SO2和NO2向SO42-和NO3-二次转化;NO3-/SO42-均值为1.96,移动源增量大于固定源。通过相关性和三相聚类分析可知,SNA主要结合方式为(NH4)2SO4和NH4NO3。主成分分析表明,南京市冬季PM2.5中水溶性离子主要来源是二次转化,燃煤、生物质燃烧和土壤建筑扬尘也有贡献。     

典型矿业城市大气颗粒物水溶性离子分布特征

利用2014年7月和2015年1月在淮南市不同功能区采集的大气颗粒物样品，分析其水溶性离子时空和粒径分布特征。结果表明：夏季和冬季粗、细粒子中总水溶性离子质量浓度均值分别为（13.45±4.53）μg/m3、（27.81±17.65）μg/m3和（12.87±8.37）μg/m3、（85.08±35.41）μg/m3。淮南市大气颗粒物中主要的水溶性离子为Ca2+、NO-3和SO2-4。冬季各功能区PM2.5中总水溶性离子质量浓度普遍高于夏季。大气颗粒物中水溶性离子主要来源于土壤源、工业污染及二次转化，冬季二次污染源主要以流动源污染为主，而夏季流动源和固定源污染贡献接近。     

燃煤工业城市大气细颗粒物中水溶性无机离子的季节变化特征及来源解析——以邯郸市为例

为探究典型燃煤工业城市邯郸市的大气细颗粒物(PM2.5)污染水平及水溶性无机离子特征,于2016年1—12月采集了当地大气PM2.5样品,然后利用离子色谱法测得水溶性无机离子的组分,分析了不同季节水溶性无机离子随PM2.5的浓度变化特征。通过对PM2.5中的阴离子、阳离子进行分析发现,SO4^2-、NO3^-和NH4^+在春夏秋冬四季均为PM2.5中的主要离子成分,SO4^2-、NO3^-和NH4^+的浓度之和在春夏秋冬四季占各季节总的水溶性无机离子浓度的百分比分别为84.6%、77.4%、89.9%、62.5%。其中,在春季和冬季含量最高的3种离子分别是NO3^-、SO4^2-和NH4^+,夏季含量最高的3种离子分别是SO4^2-、NH4^+和NO3^-,而秋季含量最高的3种离子分别是NH4^+、SO4^2-和NO3^-。相关性分析发现,2016年春季、夏季和秋季PM2.5为酸性,冬季为碱性。SO4^2-、NO3^-、NH4^+浓度分析表明,冬季PM2.5中的一次建筑扬尘排放较多。通过主成分分析法得出,PM2.5中水溶性无机离子主要来源于二次转化和生物质燃烧。     

大同市大气颗粒物浓度与水溶性离子季度分布特征

为研究大同市大气颗粒物质量浓度与水溶性离子组成特征,于2013年2、7、9、12月,分别对大同市及其对照点庞泉沟国家大气背景点进行了PM2.5及PM10的采样,通过超声萃取-IC法测定了样品中的9种水溶性离子,结果表明,大同市大气颗粒物污染1、4季度重于2、3季度,PM2.5季度均值全年均未超标,PM10仅第1季度超标1.4倍,污染状况总体良好,PM2.5与PM10相关系数R为0.75,说明大同市颗粒物污染有较为相近的来源,且不同季节均以粗颗粒物为主;大同市PM2.5中水溶性离子浓度分布为SO2-4、NO-3、NH+4Cl-、Ca2+K+、Na+F-、Mg2+,PM10中Ca2+浓度仅次于SO2-4、NO-3,控制扬尘将有效降低PM10的浓度;PM2.5及PM10中的9种水溶性离子在不同季度的浓度与颗粒物浓度分布规律类似,1、4季度较高,2、3季度较低;由阴阳离子平衡计算结果可知,相关性方程的斜率K为1.045,表明大同市大气颗粒物中阳离子相对亏损,大气细粒子组分偏酸性。NO-3与SO2-4浓度比值均小于1,大同市以硫酸型污染为主,大气中的SO2-4主要来源于人类活动排放。     

北京市大气颗粒物的浓度水平和离子物种的化学形态

用离子色谱法测定了 1 998年 1 1月至 1 999年 2月期间的 2 4个总悬浮颗粒物 (TSP)样品中 NH+ 4、NO- 3、SO2 - 4和Na+ 质量浓度。研究结果表明 ,北京市冬季大气颗粒物中离子物种的化学形态可以分为三种情况 :污染严重时 ,离子物种以 H2 SO4 、NH4 HSO4 、Na NO3为主要存在形态 ,气溶胶酸性强 ;污染轻时 ,离子物种以 (NH4 ) 2 SO4 、Na NO3为主要存在形态 ,气溶胶呈弱酸性 ;中等污染时 ,离子物种以 (NH4 ) 2 SO4 、NH4 HSO4 、Na NO3几种化学形态存在 ,气溶胶呈中等酸性     

重庆市大气TSP中水溶性无机离子的化学特征

于2001至2002年在重庆市7个采样点采集了TSP,进行了水溶性无机离子分析。结果发现,SO42-离子浓度最高,其浓度范围为6.32~20.96μg/m3;Ca2 次之,其浓度范围0.78~7.47μg/m3;SO42-、NO3-和NH4 三种离子占TSP质量的8.05%~20.96%。Ca2 、K 与SO42-和NO3-都有很好的相关性,[NO3-]/[SO42-]比值较低(均值为0.4),说明重庆市区普遍使用含硫燃煤。SO42-浓度冬季最高,主要与冬季燃煤的消耗增大有关,NO3-季节明显,与NO3-的形成环境温度密切相关。水溶性无机离子质量浓度有较明显的区域差异,中心城区采样点离子质量浓度高于距离中心城区较远的采样点。     

南通市冬季PM2.5中水溶性离子污染特征

根据南通市2016和2017年冬季大气多参数站自动监测PM2.5数据和在线离子色谱分析仪Marga监测的PM2.5中水溶性离子数据,分析了南通市冬季PM2.5中水溶性离子污染特征。结果表明,南通市2016和2017年冬季,ρ(PM2.5)分别为58和54μg/m 3,均高出其年均值(14μg/m^3);ρ(水溶性离子)总占ρ(PM2.5)百分比分别为74.5%和74.3%;二次离子ρ(NO3^-、SO4^2-和NH4^+)占ρ(PM2.5)百分比分别为66.8%和66.6%;各水溶性离子占比大小依次为:NO3^-、SO4^2-、NH4^+、Cl^-、K^+、Na^+、Ca^2+、Mg^2+。对ρ(NO3^-)/ρ(SO 4^2-)分析表明,移动源已经成为南通市冬季的主要污染源,且呈逐年增强趋势。对氯氧化率和硫氧化率的分析表明,南通市冬季存在较明显的二次污染,SO2的转化程度大于NO2。除Na^+和Mg^2+外,其他离子与PM2.5均呈显著相关性,NO3^-、SO4^2-与NH4^+之间的相关系数最高,Cl^-与除Na^+外的所有阳离子均呈显著相关性。     

北京市大气PM10源解析研究

于2004年在北京市定陵、车公庄、古城、亦庄、房山和奥体中心6个采样点采集大气PM10环境样品,针对北京市颗粒物主要排放源采集土壤尘、建筑水泥尘、燃煤等污染源PM10样品,分别对其中的无机元素、离子、有机碳(OC)和元素碳(EC)进行测定。采用代表北京市颗粒物主要排放源PM10组分特征的成分谱,利用CMB受体模型对PM10来源进行解析。结果表明,PM10的最大来源为土壤尘,其它贡献源类依次为燃煤排放、机动车/燃油排放、二次粒子(SO42-、NO3-和NH4 )、建筑水泥尘。污染源贡献具有明显的季节变化,并存在一定的地域变化。     

采暖期大气颗粒物PM1.0和PM2.5中水溶性离子污染特征

为了解采暖期大气PM_(1.0)和PM_(2.5)中水溶性离子污染特征,采集哈尔滨市2014年11月至2015年3月采暖期PM_(1.0)和PM_(2.5)的样品,进而分析其中的水溶性离子(F-、Cl-、NO-3、SO2-4、Na+、NH+4、K+、Mg2+、Ca2+)的质量浓度。结果表明:PM_(1.0)和PM_(2.5)中的水溶性离子具有相同的变化趋势。采暖期间PM_(1.0)和PM_(2.5)中9种水溶性离子质量浓度总和分别为25.4~60.7μg/m~3和38.8~78.0μg/m~3。在PM_(1.0)和PM_(2.5)中NH+4、NO-3、SO2-4占比较高,而F-、Mg2+占比较低。PM_(1.0)和PM_(2.5)中9种水溶性离子质量浓度均为夜间大于白天。在PM_(1.0)和PM_(2.5)中,Mg2+和NH+4、F-和Cl-呈显著相关,说明它们来自相似的污染源,在PM_(1.0)中的K+和Ca2+显著相关,故它们受相似的污染源的影响。根据酸度与各离子的相关性,得出SO2-4和NH+4是控制大气颗粒物酸碱性的主要离子。另外,气象因素对PM_(1.0)和PM_(2.5)的浓度有影响。     

2019—2021年徐州市大气细颗粒物化学组成特征及来源解析

徐州市地处四省交界，大气污染物来源复杂，颗粒物污染在气象条件不利时较为显著。通过地面观测数据、颗粒物组分连续观测、源解析及轨迹溯源等方法，对徐州市2019—2021年颗粒物变化特征进行了全面分析，以定量解析各类污染源的贡献，识别对颗粒物贡献显著的化学成分。结果表明：PM_2.5各组分质量占比中二次无机盐和有机碳相对较高，其中二次无机盐SNA(SO■、NO^-₃、NH⁺₄)占比达到59.1%～62.7%;水溶性离子总浓度逐年降低，但Mg²⁺和Ca²⁺浓度2021年分别同比增加2%和12.5%,说明扬尘污染存在反弹。秋冬季水溶性离子明显较高，Cl^-浓度明显高于其他季节，表明徐州市秋冬季受移动源、燃煤源和二次有机气溶胶共同影响。PM_2.5中OC与EC质量浓度比为4.88～8.40,说明徐州市颗粒物受多源影响，柴油、汽油机动车尾气排放以及燃煤排放对颗粒物贡献较大。后向轨迹分析表明，污染严重的1月污染物主...     

Characterization and diurnal variation of size-resolved inorganic water-soluble ions at a rural background site

Water-soluble inorganic ions in aerosol samples have been studied. The sample collection took place during summer in 2003 at a European background site which is operating within the framework of the European Monitoring and Evaluation Program. Gent type PM10 stacked filter unit (SFU) samplers were operated in parallel on a day and night basis to collect particles in separate coarse (2.0-10 microm) and fine (<2.0 microm) size fractions. Particulate masses were measured gravimetrically; the filters from one of the SFU samplers were analyzed by particle-induced X-ray emission spectrometry (PIXE) and instrumental neutron activation analysis (INAA). Filters from the other SFU sampler were analyzed by ion chromatography (IC) for major inorganic anions (MSA-, NO2(-), NO3(-), Cl-, Br-, SO4(2-), oxalate) and cations (Na+, K+, NH4(+), Mg2+, Ca2+). The water-soluble inorganic ions measured were responsible for 44% and 16% of the total fine and coarse particulate mass, respectively. In the fine size fraction, the main ionic components were SO4(2-) and NH4(+) accounting for about 90% of fine ionic mass. In the coarse fraction the main ionic components were Ca2+ and NO3(-), followed by SO4(2-). Significant day and night difference in the mass concentrations was observed only for fine NO3(-). The molar ratios of fine NH4(+) to SO4(2-) indicated their complete neutralization to (NH4)2SO4. According to the cation-to-anion ratios the coarse particles were alkaline, while the fine particles were slightly acidic or neutral. By comparing the corresponding concentrations obtained from PIXE/INAA and IC, we determined the water-extractable part of the individual species. We also investigated the effect of long-range transported air masses on the local air concentrations, and we found that the air quality of this background monitoring station was affected by regional pollution sources.     

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-。     

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。     

Atmospheric aerosol concentration level and chemical characteristics of water-soluble ionic species in wintertime in Beijing,China

Total suspended particulate (TSP) samples were collected during wintertime from November 24, 1998 to February 12, 1999 in Beijing. Ionic species including Cl-, NO3(-), SO4(2-), Na+, NH4(+), K+, Mg2+ and Ca2+ were determined by Ion Chromatography (IC). The sum average concentration of all the determined ions accounted for 18.9% of the TSP concentration, and SO4(2-) appeared the dominant ion with an average concentration of 30.84 microg m(-3); the sum mass concentration of SO4(2-), NO3(-), Ca2+ and NH4(+) accounted for about 83.2% of all the eight ions measured. The study indicated that the chemical form of sulfate and ammonium varies with TSP concentration levels. During heavy pollution periods, the average TSP concentration was 0.66 mg m(-3), and the NH4(+)/SO4(2-) molar ratio was low (0.58). It indicated that sulfate may present as CaSO4 and (NH4)2SO4 x CaSO4 x 2H2O. When TSP concentration (average 0.186 mg m(-3)) was relatively low, the NH4(+)/SO4(2-) molar ratio was 1.94, close to the theoretical ratio of 2 of (NH4)2SO4. Under this condition (NH4)2SO4 is expected to exist as the major form of sulfate. When the TSP concentration level was medium (average 0.35 mg m(-3)), the NH4+/SO4(2-) molar ratio appeared an average value (1.27), (NH4)2SO4, (NH4)2SO4 x CaSO4 x 2H2O and CaSO4 are expected to be present in those aerosol particles. Meteorological conditions including wind speed and wind direction were related to the TSP concentration level.     

南通市PM2.5中水溶性离子季节分布特征

对南通市2016年12月-2018年10月大气污染季节分布特征进行了分析。结果表明,南通市ρ(PM2.5)和ρ(水溶性离子)为冬、春季高,夏、秋季低。春夏秋冬四季ρ(水溶性离子)占ρ(PM2.5)百分比分别为68.2%,70.6%,64.5%和74.5%,其中二次离子SNA(NO3-、SO42-和NH4+)占ρ(PM2.5)的百分比分别为63.1%,67.0%,59.3%和66.8%;ρ(NO3-)/ρ(SO42-)表明,移动源已成为南通市春、秋、冬季的主要污染源,四季均存在不同程度的二次转化,且SO2的转化率均大于NO2,NO2冬季转化率最大、夏季最小,SO2夏季转化率最大、秋季最小。南通市NO2转化为硝酸盐的主要形式是气相均相反应,非均相反应和均相反应对SO2转化为硫酸盐的贡献差异不大。     

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。     

Contemporary estimates of atmospheric nitrogen deposition to the watersheds of New York State, USA

Atmospheric inputs of reactive nitrogen (N) to ecosystems are a particular concern in the northeastern USA, including New York State, where rates of atmospheric N deposition are among the highest in the nation. We calculate the seasonal and annual spatial variations of contemporary inorganic atmospheric N deposition loading to multi-scale watersheds across New York State using numerous monitoring datasets of precipitation and ambient atmospheric N concentrations. Our models build upon and refine previous efforts estimating the spatial distribution of N deposition. Estimates of total inorganic wet deposition (NH4-N + NO3-N) across New York ranged from 4.7 to 10.5 kg ha(-1) yr(-1) under contemporary conditions (averaged 2002-2004), and both seasonal and annual predicted rates of inorganic N deposition (NH4-N, NO3-N, and total) fit relatively well with that of observed measurements. Our results suggest that "hot spots" of N deposition are, for the most part, spatially distributed according to geographic positions (i.e., relative location from sources and the Great Lakes system) and elevation. We also detect seasonal variations in deposition, showing that total wet atmospheric inorganic N deposition inputs to watersheds (extracted from the four-digit HUC calculations) are highest during the spring (mean = 2.4 kg ha(-1), stddev = 0.29) and lowest during the winter months (mean = 1.4 kg ha(-1), stddev = 0.23). Results also suggest that wet NO3(-) consistently comprises a slightly higher proportion of wet N deposition than wet NH4+ throughout watersheds of New York, ranging from 2.5 to 6.1 kg NO3-N ha(-1) yr(-1) compared to NH4+, which ranges from 2.2 to 4.4 kg NH4-N ha(-1) yr(-1).     

Ion chemistry and individual particle analysis of atmospheric aerosols over Mt. Bogda of eastern Tianshan Mountains, Central Asia

Aerosol samples were collected during the scientific expedition to Mt. Bogda in July-August, 2009. The major inorganic ions (Na(?+?), NH??, K(?+?), Mg(2?+?), Ca(2?+?), Cl(?-?), SO2??, and NO??) of the aerosols were determined by ion chromatography. SO2??, NO??, and Ca(2?+?) were the dominate ions, with the mean concentrations of 0.86, 0.56, and 0.28 μg m?3, respectively. These mean ion concentrations were generally comparable with the background conditions in remote site of Xinjiang, while much lower than those in ürümqi. Morphology and elemental compositions of 1,500 particles were determined by field emission scanning electron microscopy equipped with an energy dispersive X-ray spectrometer. Based on the morphology and elemental compositions, particles were classed into four major groups: soot (15.1%), fly ash (4.7%), mineral particles (78.9%), and little other matters (0.8% Fe-rich particles and 0.5% unrecognized particles). Presence of soot and fly ash particles indicated the influence of anthropogenic pollutions, while abundance mineral particles suggested that natural processes were the primary source of aerosols over this region, coinciding with the ionic analysis. Backward air mass trajectory analysis suggested that ürümqi may contribute some anthropogenic pollution to this region, while the arid and semi-arid regions of Central Asia were the primary source.