Source apportionment of single aerosol particles in the atmosphere of Shanghai city

A nuclear microprobe with high spatial resolution and high analyti- cal sensitivity was applied to analyze atmospheric aerosol at five monitoring sites in Shanghai city. Meantime, a new pattern recognition technique, which used the micro PIXE spectrum of a single aerosol particle as its fingerprint, was developed to identify the origin of the particle. The results showed that the major contributors to the at- mosphere pollution were soil dust (31.6%), building dust (30.8%), and the next were vehicle exhaust (13.7%), metallurgic industry excrements (5.6%), oil combustion (5%) and coal combustion (2.3%). Besides these, about 10% of the particles could not be identified. Based on the cluster analysis of these particles, they could be divided into eight groups. By inference, they might belong to some sub-pollution sources from soil dust, building dust and metallurgic industry excrements. Moreover, some new pollution sources from tyres and chemical plants were also revealed.

Source Apportionment of Ambient PM_(10) in the Urban Area of Longyan City,China:a Comparative Study Based on Chemical Mass Balance Model and Factor Analysis Method

In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples and various pollution sources which were collected in January 2010 in Longyan with inductivity coupled plasma-mass spectrometry（ICP-MS）.Then chemical mass balance（CMB） model and factor analysis（FA） method were applied to comparatively study the inorganic components in the sources and receptor samples.The results of factor analysis show that the major sources were road dust,waste incineration and mixed sources which contained automobile exhaust,soil dust/secondary dust and coal dust during the daytime in Longyan City,China.There are two major sources of pollution which are soil dust and mixture sources of automobile exhaust and secondary dust during the night in Longyan.The results of CMB show that the major sources are secondary dust,automobile exhaust and road dust during the daytime in Longyan.The major sources are secondary dust,soil dust and automobile exhaust during the night in Longyan.The results of the two methods are similar to each other and the results will guide us to plan to control the PM10 pollution sources in Longyan.

Source apportionment of PM_(2.5)using PMF combined online bulk and single-particle measurements:Contribution of fireworks and biomass burning

Fireworks(FW)could significantly worsen air quality in short term during celebrations.Due to similar tracers with biomass burning(BB),the fast and precise qualification of FW and BB is still challenging.In this study,online bulk and single-particle measurements were combined to investigate the contributions of FW and BB to the overall mass concentrations of PM_(2.5)and specific chemical species by positive matrix factorization(PMF)during the Chinese New Year in Hong Kong in February 2013.With combined information,fresh/aged FW(abundant ^(140)K_(2)NO_(3)^(+)and ^(213)K_(3)SO_(4)^(+)formed from ^(113)K_(2)Cl^(+)discharged by fresh FW)can be extracted from the fresh/aged BB sources,in addition to the Second Aerosol,Vehicles+Road Dust,and Sea Salt factors.The contributions of FW and BB were investigated during three high particle matter episodes influenced by the pollution transported from the Pearl River Delta region.The fresh BB/FW contributed 39.2%and 19.6%to PM_(2.5)during the Lunar Chinese New Year case.However,the contributions of aged FW/BB enhanced in the last two episodes due to the aging process,evidenced by high contributions from secondary aerosols.Generally,the fresh BB/FW showed more significant contributions to nitrate(35.1%and15.0%,respectively)compared with sulfate(25.1%and 5.9%,respectively)and OC(14.8%and11.1%,respectively)on average.In comparison,the aged FW contributed more to sulfate(13.4%).Overall,combining online bulk and single-particle measurement data can combine both instruments’advantages and provide a new perspective for applying source apportionment of aerosols using PMF.

Size distribution of chemical elements and their source apportionment in ambient coarse, fine, and ultrafine particles in Shanghai urban summer atmosphere

Ambient coarse particles （diameter 1.8-10 μm）, fine particles （diameter 0.1-1.8 μm）, and ultrafine particles （diameter 〈 0.1 μm） in the atmosphere of the city of Shanghai were sampled during the summer of 2008 （from Aug 27 to Sep 08）. Microscopic characterization of the particles was investigated by scanning electron microscopy coupled with energy dispersive X-ray spectroscopy （SEM/EDX）. Mass concentrations of Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Br, Rb, Sr, and Pb in the size-resolved particles were quantified by using synchrotron radiation X-ray fluorescence （SRXRF）. Source apportionment of the chemical elements was analyzed by means of an enrichment factor method. Our results showed that the average mass concentrations of coarse particles, fine particles and ultrafine particles in the summer air were 9.38 ± 2.18, 8.82 ± 3.52, and 2.02 ± 0.41 μg/m3, respectively. The mass percentage of the fine particles accounted for 51.47% in the total mass of PM10, indicating that fine particles are the major component in the Shanghai ambient particles. SEM/EDX results showed that the coarse particles were dominated by minerals, fine particles by soot aggregates and fly ashes, and ultrafine particles by soot particles and unidentified particles. SRXRF results demonstrated that crustal elements were mainly distributed in the coarse particles, while heavy metals were in higher proportions in the fine particles. Source apportionment revealed that Si, K, Ca, Fe, Mn, Rb, and Sr were from crustal sources, and S, Cl, Cu, Zn, As, Se, Br, and Pb from anthropogenic sources. Levels of P, V, Cr, and Ni in particles might be contributed from multi-sources, and need further investigation.

Chemical characterization and source apportionment of atmospheric submicron particles on the western coast of Taiwan Strait, China

Taiwan Strait is a special channel for subtropical East Asian Monsoon and its western coast is an important economic zone in China. In this study, a suburban site in the city of Xiamen on the western coast of Taiwan Strait was selected for fine aerosol study to improve the understanding of air pollution sources in this region. An Aerodyne high-resolution time-of-flight aerosol mass spectrometer（HR-To F-AMS） and an Aethalometer were deployed to measure fine aerosol composition with a time resolution of 5 min from May 1to 18, 2015. The average mass concentration of PM1 was 46.2 ± 26.3 μg/m^3 for the entire campaign. Organics（28.3%）, sulfate（24.9%）, and nitrate（20.6%） were the major components in the fine particles, followed by ammonium, black carbon（BC）, and chloride. Evolution of nitrate concentration and size distribution indicated that local NOx emissions played a key role in high fine particle pollution in Xiamen. In addition, organic nitrate was found to account for 9.0%–13.8% of the total measured nitrate. Positive Matrix Factorization（PMF）conducted with high-resolution organic mass spectra dataset differentiated the organic aerosol into three components, including a hydrocarbon-like organic aerosol（HOA） and two oxygenated organic aerosols（SV-OOA and LV-OOA）, which on average accounted for 27.6%,28.8%, and 43.6% of the total organic mass, respectively. The relationship between the mass concentration of submicron particle species and wind further confirmed that all major fine particle species were influenced by both strong local emissions in the southeastern area of Xiamen and regional transport through the Taiwan Strait.

Self-feedback LSTM regression model for real-time particle source apportionment

Atmospheric particulate matter pollution has attracted much wider attention globally.In recent years,the development of atmospheric particle collection techniques has put forwards new demands on the real-time source apportionments techniques.Such demands are summarized,in this paper,as how to set up new restraints in apportionment and how to develop a non-linear regression model to process complicated circumstances,such as the existence of secondary source and similar source.In this study,we firstly analyze the possible and potential restraints in single particle source apportionment,then propose a novel three-step self-feedback long short-term memory(SF-LSTM)network for approximating the source contribution.The proposed deep learning neural network includes three modules,as generation,scoring and refining,and regeneration modules.Benefited from the scoring modules,SF-LSTM implants four loss functions representing four restraints to be followed in the apportionment,meanwhile,the regeneration module calculates the source contribution in a non-linear way.The results show that the model outperforms the conventional regression methods in the overall performance of the four evaluation indicators(residual sum of squares,stability,sparsity,negativity)for the restraints.Additionally,in short time-resolution analyzing,SF-LSTM provides better results under the restraint of stability.

不同粒径和来源大气颗粒物暴露与孕妇子痫前期发生风险的关联研究

目的:探究不同粒径和来源的大气颗粒物暴露对孕妇子痫前期发生风险的影响。方法:从北京市某城区妇幼保健院收集2014—2018年的产前检查记录;监测同期气象数据和空气动力学直径5~560 nm的大气颗粒物数浓度(PNC),并应用正定矩阵因子分解法进行颗粒物的来源解析。采用Logistic回归分析大气颗粒物暴露与孕妇子痫前期发生风险的关联效应。结果:孕前3个月和孕早期暴露于空气动力学直径5~200 nm的颗粒物与孕妇子痫前期的发生存在正相关关系。孕前3个月的25~100 nm、100~200 nm粒径段的大气颗粒物暴露水平每增加四分位间距(IQR)浓度,子痫前期的发生风险分别增加36%[比值比(OR)=1.36,95%CI(1.04,1.76)]和40%[OR=1.40,95%CI(1.12,1.76)];孕早期5~25 nm和100~200 nm粒径段的大气颗粒物暴露水平每增加IQR浓度,子痫前期的发生风险分别增加46%[OR=1.46,95%CI(1.15,1.83)]和40%[OR=1.40,95%CI(1.08,1.82)]。子痫前期发生风险与孕前3个月和孕早期的大气核模态颗粒和汽油车排放颗粒暴露存在显著关联。结论:大气颗粒物,特别是交通来源的细小粒径颗粒物暴露可增加孕妇子痫前期的发生风险。

Comprehensive understanding on sources of high levels of fine particulate nitro-aromatic compounds at a coastal rural area in northern China

Nitro-aromatic compounds(NACs)are among the major components of brown carbon(BrC)in the atmosphere,causing negative impacts on regional climate,air quality,and ecological health.Due to the extensive origins,it is still a challenge to figure out the contributions and originating regions for different sources of atmospheric NACs.Here,field observations on fine particulate NACs were conducted at a coastal rural area in Qingdao,China in the winter of 2018 and 2019.The mean total concentrations of fine particulate nitro-aromatic compounds were 125.0±89.5 and 27.7±21.1 ng/m^(3)in the winter of 2018 and 2019,respectively.Among the measured eleven NACs,nitrophenols and nitrocatechols were the most abundant species.Variation characteristics and correlation analysis showed that humidity and anthropogenic primary emissions had significant influences on the NAC abundances.In this study,two tracing methods of the improved spatial concentration weighted trajectory(SCWT)model and the receptor model of positive matrix factorization(PMF)were combined to comprehensively understand the origins of NACs in fine particles at coastal Qingdao.Four major sources were identified,including coal combustion,biomass burning,vehicle exhaust,and secondary formation.Surprisingly,coal combustion was responsible for about half of the observed nitro-aromatic compounds,followed by biomass burning(~30%).The results by SCWT demonstrated that the coal combustion dominated NACs mainly originated from the Shandong peninsula and the areas to the north and southwest,while those dominated by biomass burning primarily came from local Qingdao and the areas to the west.

基于粒径谱仪的大气PM_(10)源解析方法研究与评估

本文尝试利用粒径分布数据建立一种新的大气颗粒物来源解析方法,为城市大气颗粒物解析和治理提供新思路。于2023年春季,利用大气颗粒物粒径监测仪对保定市、南阳市和鄂州市0.2、0.3、0.4、0.5、1.0、2.5、4、7和10μm共9个粒径段的颗粒物进行连续观测和来源解析,并通过沙尘过程和降雨过程对城市的粒径分布变化和解析结果进行分析和评估。结果表明:①观测期间保定市、南阳市和鄂州市总粒子数浓度平均值分别为851、755和782 cm^(−3),非沙尘期间分别为922、765和811 cm^(−3),与观测期间相比,非沙尘期间3个城市总粒子数浓度平均值均有所上升。②解析结果显示,非沙尘期间3个城市PM_(10)的首要贡献源均为扬尘源,其次依次为二次源、机动车源、固定燃烧源、工艺过程源和其他源。③在一次沙尘过程中,与沙尘前相比,3个城市在沙尘中各粒径段浓度变化均随粒径增长呈先降低再逐渐升高的特征,期间3个城市的扬尘源贡献率均显著增大。④保定市在一次降雨过程中,除PM_(2.5~4)外的其他粒径段整体表现为粒径越大浓度降幅越大的特征,其中PM_(2.5~4)可能受到湿沉降和颗粒物吸湿增长的双重影响降幅相对较小;降雨过程中扬尘源、固定燃烧源和机动车源贡献率均有所降低,其中扬尘源贡献率降幅最大。研究显示,建立的大气颗粒物粒径解析模型可以得到比较合理的PM_(10)源解析结果,有望应用于各地区大气污染治理工作中。

宜兴东南部区域春季大气细颗粒物在线源解析

为探讨宜兴东南部区域春季大气细颗粒物化学特征及来源,利用单颗粒气溶胶飞行时间质谱仪(SPAMS 0515)对其开展为期19天的在线监测。结果显示:主要污染源为扬尘源(39.4%)、二次无机源(25.7%),相较优良时段,污染时段下的二次无机源、扬尘源占比分别上升7.4个百分点和5.0个百分点。监测期间,3次PM_(2.5)浓度升高主要受到扬尘源的排放影响,1次PM_(2.5)浓度升高主要受到二次无机源的影响;早晚交通高峰期的机动车尾气源对PM_(2.5)浓度升高也有一定贡献。

天津市大气中多环芳烃衍生物污染特征和来源

为探究天津市大气中多环芳烃衍生物污染特征与来源,使用石英纤维滤膜(QFFs)和聚氨酯泡沫(PUFs)采集环境空气样品,并使用气相色谱-质谱法测定其浓度.结果表明,天津市大气中∑_(18)NPAHs在秋季和冬季平均浓度分别为840,894pg/m^(3),∑_(5)OPAHs在秋季和冬季平均浓度分别为8.08,9.36ng/m^(3),表现为冬季略大于秋季.大气中9N-ANT、2N-NAP、1N-NAP、2+3N-FLT、BZO和9-FO为主要的多环芳烃衍生物.PM_(2.5)中多环芳烃衍生物的浓度冬季大于秋季,在气相中则为秋季大于冬季.从昼夜差异来看,PM_(2.5)中,多环芳烃衍生物浓度的夜昼比在大部分采样天数都大于1,在秋季的气相和PM_(2.5)中,昼间二次形成的NPAHs较冬季高.基于特征比值法进行来源初析,发现天津秋冬季大气PM_(2.5)中NPAHs主要以一次排放为主,同时二次生成对NPAHs也有一定贡献,大气PM_(2.5)中NPAHs二次生成方式以与OH·催化反应生成为主.气粒分配特征表现为:多数化合物在冬季PM_(2.5)占比较秋季高,同时气相中多环芳烃衍生物占比秋季较冬季呈上升趋势.

太原市大气降尘化学组分及来源的粒径分布

2019年11月~2020年12月,从太原市8个监测站点采集的大气降尘样品,进行化学组分和粒径分析,研究了降尘化学组分及降尘来源的粒径分布特征.研究结果表明:首先,太原市降尘的粒径大小受地理位置影响显著,呈现南部粒径大,北部粒径小的特点,且呈现秋冬季粒径偏大的季节特点,这与太原市降尘污染源的时空分布有关.此外,不同粒径大小降尘的化学组分存在明显的时空差异,尤其是OC、SO_(4)^(2-)和无机元素Ca、Si和Fe等组分.源解析结果表明城市扬尘源对太原市各粒径大小降尘样品的贡献均较高(33.7%~37.5%).同时,建筑尘源(21.8%~31.6%)和钢铁工业源(5.1%~18.1%)对中粒径和粗粒径降尘具有显著贡献,燃煤源对细粒径降尘的影响也不可忽视(14.1%~22.6%).

曼谷城区总悬浮颗粒物的化学组成特征、来源解析及其人肺上皮细胞A549毒性

城市大气颗粒物暴露与人群健康不利效应密切相关,由于颗粒物来源广泛、组成复杂,其引致的健康毒性效应不尽相同。本研究旨在探查城市颗粒物的化学组成、来源及其对人体细胞的毒性效应。采集泰国曼谷城区一年的大气总悬浮颗粒物(TSP)样品,分析水溶性离子、微量金属元素、碳质组分及有机分子标志物含量,并利用正定矩阵因子(PMF)模型解析曼谷TSP来源;测定人肺上皮细胞A549暴露于TSP水萃取组分和有机萃取组分后细胞毒性的变化,包括细胞存活率、活性氧(ROS)生成、白细胞介素-8(IL-8)及细胞凋亡。结果表明,曼谷TSP浓度呈现干季高、湿季低的季节趋势,有机组分和水溶性离子是TSP的主要组分(>50%)。PMF模型解析结果显示,生物质燃烧(24.7%)、陆地化石燃料燃烧(21.1%)和土壤扬尘(20.6%)是干季内曼谷TSP质量浓度的主要贡献者,而湿季内曼谷TSP的主要来源为陆地化石燃料燃烧(29.5%)、生物质燃烧(16.6%)及海盐(16.0%)。曼谷TSP水萃取组分和有机萃取组分均可引起A549细胞毒性,其中TSP有机萃取组分暴露后的细胞具有更高的死亡率、ROS水平和凋亡率,而TSP水萃取组分暴露后的细胞则具有更高的IL-8水平,这种差异表明诱导胞内ROS(即氧化应激响应)和细胞死亡(细胞存活率与凋亡率)的主导活性组分与诱导IL-8的主导活性成分不同。

西南特殊地形区域大气降尘中矿物颗粒特征

为研究西南特殊地形区域大气降尘中矿物颗粒特征,于2021年9-10月在川西的康定市和马尔康市以及川南的攀枝花市采集了大气降尘样品,分析了大气降尘样品的化学组分和矿物相,并研究了区域气团迁移和降尘矿物颗粒来源,结果表明:川西降尘中有鲕粒状矿物,攀枝花降尘中大多为球状矿物,矿物相有方解石、石英和白云母等,攀枝花降尘中还有较高质量分数的赤铁矿;康定和马尔康降尘主要受生物质燃烧源和矿尘影响,城市气团主要受来自四川盆地的雅安气团影响,还受少量来自青藏高原和西北沙漠区气团影响,而攀枝花降尘主要受燃煤排放和移动排放源影响,城市气团主要受来自云南的气团影响。研究成果可为西南特殊地形区域精准控制大气污染提供技术支撑。

青岛沿海站点冬季不同污染条件下气溶胶的来源解析——基于单颗粒质谱分析

青岛位于京津冀的下风区,毗邻黄渤海,其大气污染受到陆地和海洋传输的影响,尤其在冬季来源较为复杂。本研究利用单颗粒气溶胶质谱仪于2019年12月在青岛奥帆中心采集913514个大气颗粒,并利用Art-2a算法将其分类,对青岛市大气气溶胶进行溯源和分析。其中富钾颗粒(K)、元素碳和有机碳混合颗粒物(ECOC)、有机碳颗粒物(OC)、多环芳烃颗粒物(PAH)、OCEC和富钾颗粒与有机碳元素碳混合颗粒(K_ECOC)等颗粒物多与生物质燃烧有关,其在总颗粒物中的占比高达49.2%;与工业排放有关的元素碳和富钾混合颗粒(EC_K)、富铁颗粒(Fe)和其他重金属(other_HM)颗粒物的占比为29.7%;与海洋排放相关的海盐颗粒和富钠颗粒物(Na_rich)占比为6.8%;另外有机胺(Amine,10.6%)受到了陆源和海洋源的共同影响。根据污染个例分析发现,青岛受到京津冀传输影响时,局地工业源EC_K的贡献从36.0%逐渐降至15.0%,较高的环境湿度促进了Amine在颗粒物上的二次生成;当受到高空输送影响时,以生物质燃烧颗粒为主导(70.5%);在海洋气团影响主导时,青岛受局地排放(EC_K,42.2%)和海洋气溶胶(7.7%)控制。

北京市大气细粒子的来源分析

细粒子 (空气动力学直径小于 2 5 μm的颗粒物 )污染是许多城市重要的大气环境问题 .从 1 999年至 2 0 0 0年对北京市细粒子展开了 4次采样和化学分析 ,有效采样天数为 40d .利用正定矩阵分解 (PMF)方法对细粒子的来源进行了分析 .化学成分包括EC(元素碳 )、有机物、SO2 - 4、F- 、Cl- 、Fe、Ca、K、Mg、Al、Na、Zn、Mn、Ti、Pb、Ba和P等 1 7种 .发现主要来源有 6类 :地面扬尘、建筑源、生物质燃烧、二次源、机动车排放和燃煤 .

因子分析法解析北京市大气颗粒物PM_(10)的来源

2004年10月份在北京市6个采样点采集了大气PM10样品,分析了大气颗粒物的质量浓度、元素组成、离子、有机碳(OC)和元素碳(EC)的浓度,并用因子分析模型对颗粒物的来源进行了研究。结果显示,北京市大气颗粒物的来源主要有6类:建筑水泥尘/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘、生物质燃烧尘和燃油尘。用模型计算得到的各源对PM10的贡献率分别为建筑水泥尘/机动车尾气尘/燃煤尘占36.57%、土壤风沙尘占16.07%、二次粒子尘占12.33%、工业粉尘占10.29%、生物质燃烧尘占6.07%、燃油尘占3.84%、其它占14.84%。其中建筑水泥/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘是大气颗粒物PM10的主要来源。实验表明,在缺少源成分谱时可以用因子分析模型来分析大气颗粒物的来源及其相对贡献。

北京冬季大气颗粒物数浓度的粒径分布特征及来源

监测北京市冬季远郊区（密云）、交通道路（北四环）和生活区（清华大学）采样点的CO,NO,NO2,SO2等浓度,同时监测大气细颗粒物（FPs,粒径为0.1-2.5μm）和超细颗粒物（UFPs,粒径〈0.1μm）的数浓度,利用正交矩阵因子（PMF）法对FPs和UFPs数浓度的粒径分布特征和来源进行了研究.结果表明：在远郊区采样点共有4个影响因子,其中主因子1,4可能与长距离运移有关,主因子2可能来自1 km外的村庄生活排放,主因子3为附近铁路机车排放;在交通道路采样点共有3个影响因子,其中主因子1,3可能均来自机动车排放,主因子2来自燃煤污染;在生活区采样点共有3个影响因子,其中,主因子1可能与机动车排放有关,主因子2,3可能均来自燃煤排放.

区域大气细粒子污染特征及快速来源解析

在广东大气超级站使用单颗粒气溶胶飞行时间质谱仪(SPAMS)等仪器开展综合观测,2013年12月共监测到两个污染过程,主要的化学成分为元素碳(EC),占总颗粒数的56.8%,其次为有机碳(OC)和重金属(HM),分别占总颗粒数的12.7%和10.1%.两个污染过程中,不同颗粒类别的变化趋势有差异,说明两个污染过程的污染特征有所不同.污染来源分析发现,监测期间主要受到机动车尾气源和燃煤源的影响,二者分别占24.8%和22%;其次为工业工艺源和生物质燃烧,分别占16.4%和10.3%.第一个污染过程中,工业工艺源是首要污染源,而随着颗粒物浓度的增高,燃煤和二次无机气溶胶的比例明显增加,说明此污染过程中受一次污染源(燃煤源和工业工艺源)和二次光化学反应的复合影响.而第二个污染过程中,机动车尾气为首要污染源,其次是燃煤和工业工艺源,整个过程中各源的比例较为稳定,说明该次污染过程主要由不利气象条件导致的污染物累积形成.

基于质子微探针研究的大气气溶胶单颗粒源解析

用高分辨率 ,高灵敏度的质子微探针对上海市人民公园大气气溶胶进行单颗粒源解析 .结果发现 ,上海市大气主要污染源为土壤扬尘、建筑扬尘、汽车尾气和钢铁工业尘 ,它们对大气环境贡献率之和为 80 %以上 .此外还发现约有 1 3%的颗粒物无法识别 ,通过对这些颗粒物进行聚类分析 ,初步确定它们分属于 2种不同污染源的亚类和一种新的未知的污染源 .