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The molecular compositions of organic components in winter PM2.5 samples from a typical urban area of Chongqing were analyzed by electrospray ionization coupled with ion mobility spectrometry-time of flight mass spectrometry (ESI-IMS-TOF-MS). Sulfur-containing organics (CHOS+CHNOS) were important components in organic aerosol, and their relative abundance accounted for more than 70% on average. IMS-derived collision cross section, collision-induced dissociation, and Kendrick mass defect analyses verified the presence of organosulfates (OSs). Molecular characterization results indicated that sulfur-containing organics were dominated by carbohydrate and lignin species and had higher oxidation degree in Chongqing urban area compared with other cities. Biogenic and anthropogenic precursors were important sources of sulfur-containing organics. The relationships between aerosol liquid water content, acidity and inorganic sulfate with sulfur-containing organics suggested that aqueous-phase chemistry and acid-catalyzed chemistry play important roles in the formation of sulfur-containing organics.

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使用电喷雾电离结合离子迁移谱-飞行时间质谱仪(ESI-IMS-TOF-MS)分析了重庆典型城区冬季PM2.5样品中有机物的分子组成.结果发现,含硫有机物(CHOS+CHNOS)是有机气溶胶中的重要成分,其平均相对丰度超过70%.IMS衍生的碰撞截面、碰撞诱导解离和肯德里克质量缺陷分析证明了有机硫酸酯(OSs)的存在.分子特征分析表明含硫有机物以碳水化合物和木质素为主,且相较于其他地区,具有较高的氧化程度.生物源和人为源前体物是其重要来源.气溶胶液态水含量、酸度和无机硫酸盐与含硫有机物的关系表明了水相化学和酸催化化学在含硫有机物的形成中起着重要的作用.

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* 责任作者,副教授,
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赵鑫泉(2000-),男,四川巴中人,重庆大学硕士研究生,主要从事大气中污染物质的分子特征及形成机制研究..

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赵鑫泉(2000-),男,四川巴中人,重庆大学硕士研究生,主要从事大气中污染物质的分子特征及形成机制研究..

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赵鑫泉(2000-),男,四川巴中人,重庆大学硕士研究生,主要从事大气中污染物质的分子特征及形成机制研究..

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点的颜色代表O/S比值,直线代表Zhang等[33]预测的OSs趋势线

, figureFileSmall=T4cXvnu71wk11A9zuNcabg==, figureFileBig=o3odPqsJh5IG7FE7FEmXzg==, tableContent=null), ArticleFig(id=1234106403942626139, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=EN, label=Fig.3, caption=Analytical results of C4H3O4S-, C5H7O6S- and corresponding dissociated fragments (-SO3和HSO4-), figureFileSmall=rB9+Fvyaxhuesew4GKaEtQ==, figureFileBig=Z6+C0IzeoKVQnv+axJ7Xwg==, tableContent=null), ArticleFig(id=1234106404102009708, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=CN, label=图3, caption=C4H3O4S-和C5H7O6S-以及对应解离碎片(-SO3和HSO4-)分析结果, figureFileSmall=rB9+Fvyaxhuesew4GKaEtQ==, figureFileBig=Z6+C0IzeoKVQnv+axJ7Xwg==, tableContent=null), ArticleFig(id=1234106404248810363, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=EN, label=Fig.4, caption=CH2-KMD plots of CHOS and CHNOS compounds, figureFileSmall=rgRWPjGV5W8ZFwG8xHdQOA==, figureFileBig=z1fcO0E3QUBByS9l1Vb2kw==, tableContent=null), ArticleFig(id=1234106404433359761, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=CN, label=图4, caption=CHOS和CHNOS化合物的CH2-KMD图, figureFileSmall=rgRWPjGV5W8ZFwG8xHdQOA==, figureFileBig=z1fcO0E3QUBByS9l1Vb2kw==, tableContent=null), ArticleFig(id=1234106404609520543, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=EN, label=Fig.5, caption=Elemental distributions of CHOS and CHNOS compounds, figureFileSmall=sl7+d0rum56Ct9fgqpyivA==, figureFileBig=6TKoyuVXwjeNt4tALZFYVA==, tableContent=null), ArticleFig(id=1234106406090109871, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=CN, label=图5, caption=CHOS和CHNOS化合物的元素分布, figureFileSmall=sl7+d0rum56Ct9fgqpyivA==, figureFileBig=6TKoyuVXwjeNt4tALZFYVA==, tableContent=null), ArticleFig(id=1234106406249493433, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=EN, label=Fig.6, caption=Peak signal intensity-weighted H/C and DBE, O/C and DBE/C for organics; Modified Van Krevelen diagrams for sulfur-containing organics, figureFileSmall=0r8+rijei+TwTMmGszL4sA==, figureFileBig=9V4G/vgfVyWCob351kUvzA==, tableContent=null), ArticleFig(id=1234106406408877006, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=CN, label=图6, caption=有机物峰信号强度加权H/C、DBE、O/C和DBE/C图及含硫有机物的修正Van Krevelen图

点的颜色代表有机物的O/S,大小代表有机物的相对丰度;A~F区域分别代表:多环芳香族、高度芳香族、高度不饱和、不饱和脂肪族、饱和和低氧化程度

, figureFileSmall=0r8+rijei+TwTMmGszL4sA==, figureFileBig=9V4G/vgfVyWCob351kUvzA==, tableContent=null), ArticleFig(id=1234106406614397913, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=EN, label=Fig.7, caption=Precursor diagrams of OSs and NOSs, figureFileSmall=co3zvqRtCAR7O98RCYHGEQ==, figureFileBig=I/b+rYTKeXI6ZLXXDmR/Mg==, tableContent=null), ArticleFig(id=1234106406790558697, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=CN, label=图7, caption=OSs和NOSs化合物的前体物图

表示线性烷烃OSs:CnH2n+1SO4或NOSs:CnH2nNO3SO4的趋势线;代表线性糖醇OSs:CnH2n+1OnSO4或NOSs:CnH2nOnNO3SO4的趋势线.(a)中I~V区域分别代表由异戊二烯/乙二醛、异戊二烯二聚体、单萜/长链烷烃/萘、倍半萜和苯衍生的OSs;(b)中A~C区域分别代表由异戊二烯、单萜/萘、倍半萜衍生的NOSs;点的大小代表含硫有机物的相对丰度

, figureFileSmall=co3zvqRtCAR7O98RCYHGEQ==, figureFileBig=I/b+rYTKeXI6ZLXXDmR/Mg==, tableContent=null), ArticleFig(id=1234106406907999220, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=EN, label=Fig.8, caption=Correlations between the relative abundance of sulfur-containing organics and atmospheric parameters; relationships between sulfur-containing compounds and ALWC with SO42- concentrations, figureFileSmall=10Q5F6SnP99gkUu5rBO+bw==, figureFileBig=WLa/GQVBK0reEBPWcGkjGg==, tableContent=null), ArticleFig(id=1234106407042216959, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=CN, label=图8, caption=含硫有机物与各参数间的相关性及含硫物种和ALWC与SO42-浓度之间的关系, figureFileSmall=10Q5F6SnP99gkUu5rBO+bw==, figureFileBig=WLa/GQVBK0reEBPWcGkjGg==, tableContent=null), ArticleFig(id=1234106407189016581, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=EN, label=Table 1, caption=

Distribution of sulfur-containing organic compounds in different categories (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
类别H/CO/CAICHOSCHNOS
脂质1.5~2.00~0.3-2.380.00
蛋白质/氨基糖1.5~2.20.3~0.67-11.6912.68
碳水化合物1.5~2.00.67~1.2-26.2727.35
不饱和烃0.7~1.00~0.1-0.000.00
木质素0.7~1.50.1~0.670~0.6732.7827.84
稠环芳烃0.2~0.70~0.670.67~1.670.000.00
单宁0.5~1.50.67~1.20~0.679.199.75
其他---17.6922.37
), ArticleFig(id=1234106407352594449, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106388285289227, language=CN, label=表1, caption=

含硫有机物的分类依据以及在不同类别中的分布(%)

, figureFileSmall=null, figureFileBig=null, tableContent=
类别H/CO/CAICHOSCHNOS
脂质1.5~2.00~0.3-2.380.00
蛋白质/氨基糖1.5~2.20.3~0.67-11.6912.68
碳水化合物1.5~2.00.67~1.2-26.2727.35
不饱和烃0.7~1.00~0.1-0.000.00
木质素0.7~1.50.1~0.670~0.6732.7827.84
稠环芳烃0.2~0.70~0.670.67~1.670.000.00
单宁0.5~1.50.67~1.20~0.679.199.75
其他---17.6922.37
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重庆典型城区PM2.5中含硫有机物的分子特征与成因
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赵鑫泉 1 , 宋洋 2 , 梁波 2 , 唐浩辉 1 , 王森华 1 , 陈静 1 , 田密 1, *
中国环境科学 | 大气污染与控制 2025,45(6): 2961-2973
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中国环境科学 | 大气污染与控制 2025, 45(6): 2961-2973
重庆典型城区PM2.5中含硫有机物的分子特征与成因
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赵鑫泉1 , 宋洋2, 梁波2, 唐浩辉1, 王森华1, 陈静1, 田密1, *
作者信息
  • 1.重庆大学环境与生态学院,重庆 400045
  • 2.重庆市计量质量检测研究院,重庆 401123
  • 赵鑫泉(2000-),男,四川巴中人,重庆大学硕士研究生,主要从事大气中污染物质的分子特征及形成机制研究..

通讯作者:

* 责任作者,副教授,
Molecular characteristics and impact factors of PM2.5-bound sulfur-containing organics in downtown Chongqing
Xin-quan ZHAO1 , Yang SONG2, Bo LIANG2, Hao-hui TANG1, Sen-hua WANG1, Jing CHEN1, Mi TIAN1, *
Affiliations
  • 1.College of Environment and Ecology, Chongqing University, Chongqing 400045, China
  • 2.Chongqing Academy of Metrology and Quality Inspection, Chongqing 401123, China
出版时间: 2025-06-20
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使用电喷雾电离结合离子迁移谱-飞行时间质谱仪(ESI-IMS-TOF-MS)分析了重庆典型城区冬季PM2.5样品中有机物的分子组成.结果发现,含硫有机物(CHOS+CHNOS)是有机气溶胶中的重要成分,其平均相对丰度超过70%.IMS衍生的碰撞截面、碰撞诱导解离和肯德里克质量缺陷分析证明了有机硫酸酯(OSs)的存在.分子特征分析表明含硫有机物以碳水化合物和木质素为主,且相较于其他地区,具有较高的氧化程度.生物源和人为源前体物是其重要来源.气溶胶液态水含量、酸度和无机硫酸盐与含硫有机物的关系表明了水相化学和酸催化化学在含硫有机物的形成中起着重要的作用.

有机气溶胶  /  离子迁移谱  /  含硫有机物  /  分子特征  /  影响因素

The molecular compositions of organic components in winter PM2.5 samples from a typical urban area of Chongqing were analyzed by electrospray ionization coupled with ion mobility spectrometry-time of flight mass spectrometry (ESI-IMS-TOF-MS). Sulfur-containing organics (CHOS+CHNOS) were important components in organic aerosol, and their relative abundance accounted for more than 70% on average. IMS-derived collision cross section, collision-induced dissociation, and Kendrick mass defect analyses verified the presence of organosulfates (OSs). Molecular characterization results indicated that sulfur-containing organics were dominated by carbohydrate and lignin species and had higher oxidation degree in Chongqing urban area compared with other cities. Biogenic and anthropogenic precursors were important sources of sulfur-containing organics. The relationships between aerosol liquid water content, acidity and inorganic sulfate with sulfur-containing organics suggested that aqueous-phase chemistry and acid-catalyzed chemistry play important roles in the formation of sulfur-containing organics.

organic aerosols  /  ion mobility spectrometry  /  sulfur-containing organics  /  molecular characteristics  /  influencing factors
赵鑫泉, 宋洋, 梁波, 唐浩辉, 王森华, 陈静, 田密. 重庆典型城区PM2.5中含硫有机物的分子特征与成因. 中国环境科学, 2025 , 45 (6) : 2961 -2973 .
Xin-quan ZHAO, Yang SONG, Bo LIANG, Hao-hui TANG, Sen-hua WANG, Jing CHEN, Mi TIAN. Molecular characteristics and impact factors of PM2.5-bound sulfur-containing organics in downtown Chongqing[J]. China Environmental Science, 2025 , 45 (6) : 2961 -2973 .
有机气溶胶(OA)是环境细颗粒物(PM2.5)的重要组成部分,约占PM2.5的20%~90%[1-3].近年来,PM2.5的化学组分发生了显著变化,有机物在PM2.5中的占比不断增加,成为大气气溶胶中越来越重要的组分[4].OA组成复杂且来源广泛,既可由自然或人为污染源直接排放,也可通过气态或颗粒态前体物在大气中经光化学或液相氧化生成[5-6].OA中的含硫有机物由于可以揭示污染物的来源、老化机制和转化过程而受到广泛关注[7].然而,由于含硫有机物复杂的分子特征和缺乏分析手段,对其组成、分子特征和成因的研究尚不完整.
含硫有机物作为大气OA的重要贡献者,广泛存在于世界各地的大气气溶胶中[8-9],对气溶胶的酸度、挥发性、吸湿性和光吸收等特征产生关键影响[10-11].含硫化合物既可由化石燃料和生物质燃烧直接排放,也可由人为源或生物源前体物与SO2、硫酸盐颗粒的非均相/多相反应形成[12-14].根据含硫有机物中的官能团,可将其分为有机硫酸酯(OSs),亚砜、有机磺酸盐和砜等,包含硝酸基团(-ONO2)的OSs又称为硝基有机硫酸酯(NOSs),其中OSs和NOSs被认为是最丰富的物种[15].研究表明[16-17],酸化硫酸盐气溶胶对生物源挥发性有机物的氧化产物(如异戊二烯环氧化物)的反应性吸收已被确定为OSs形成的重要途径.此外,野外观测和实验室研究都表明含硫有机物的形成受多种因素的影响,包括生物源/人为源挥发性有机物[18-19]、无机硫物种(如SO2和SO42-)[20]、大气氧化剂浓度[21]、气溶胶液态水含量(ALWC)[22]、气溶胶酸度[23]和相对湿度(RH)[24]等.然而目前对影响野外气溶胶中含硫有机物形成的主导因素的认识还较为缺乏,特别是对于有机硫酸酯.
重庆作为西南地区重要的特大城市之一,特殊的地形和气象条件对OA形成的影响可能有别于其他区域.尽管之前已有研究者使用单颗粒气溶胶质谱(SP-AMS)[25]和气溶胶化学形态监测仪(ACSM)[26]对重庆地区OA的化学成分和来源进行了表征,但目前对重庆地区OA的分子特征及其成因的认识还不足.离子迁移谱和高分辨质谱相结合可以提供离子质荷比和碰撞截面结构等信息[27-28],可为大气气溶胶中复杂混合物的分析提供重要手段.本研究使用电喷雾电离结合离子迁移谱-飞行时间质谱仪(ESI-IMS-TOF-MS)在分子水平上分析重庆城区冬季大气PM2.5样品中的有机物,阐明有机组分(特别是含硫有机物)在分子水平上的化学特征,识别含硫有机物中的有机硫酸酯,探讨影响含硫有机物形成的主要因素,旨在为城市大气气溶胶的控制提供参考.
采样点设置在重庆主城区某楼楼顶(29°34'N,106°28'E,海拔326m).该采样点主要受交通、居民区和商业区的影响,周边没有明显的工业活动.因此,该采样点处于典型的城市环境.PM2.5样品采集时间为2015年12月16日~2016年1月14日,每天持续采样23.5h.使用石英纤维滤膜(QFF, Whatman)和大气大流量采样器(TISCH)以1.03m3/ min的速率采集PM2.5样品.QFF在采样前已放置在450℃的马弗炉中煅烧5h,并用铝箔纸包好放入密封袋中备用.采样结束后样品用铝箔纸包好放入密封袋,随后放入-20℃冰箱保存等待分析.采样期间同时记录温度和相对湿度等气象参数.气态物种(SO2、O3和NO2)的浓度来自于环境监测站.
使用热光碳分析仪定量分析有机碳(OC)和元素碳(EC),使用离子色谱法定量分析水溶性无机离子(SO42-、NO3-和NH4+等),详细信息可参见前期研究[29].利用扩展气溶胶热力学模型II(EAIM-II)估算ALWC和气溶胶pH值(http://www.aim.env.uea.ac.uk/aim/aim.php).将水溶性无机离子浓度、气态前体物浓度、环境温度和相对湿度作为模型输入参数,模型可计算化学物质的平衡浓度,进而得到ALWC和气溶胶pH值.
为了分析PM2.5样品中有机成分的分子组成,将四分之一的滤膜样品放入烧杯中,用铝箔包裹遮光,用甲醇(HPLC级,Macklin)超声萃取30min,萃取液转移至棕色小瓶,氮吹浓缩至2mL后,用孔径为0.22μm的聚四氟乙烯(PTFE)过滤器过滤并浓缩至1mL.
使用ESI-IMS-TOF-MS对PM2.5中OA的分子组成进行表征.在ESI源负离子模式下获得OA的谱图.通过注射泵以1μL/min的流速注入样品.漂移管保持在恒温(60℃)和常压下,并在漂移区末端加入流速为1.2mL/min的逆流漂移气体(N2).离子迁移区电场强度为300~400V/cm,IMS高压设置为12000V.从漂移管中出来后,离子加合物通过压力真空界面聚焦到TOF-MS中,该界面包括两个四极杆(Q1和Q2),其中Q1的频率和振幅分别设置为1.5×106Hz和196V,Q2的频率和幅度分别设置为1.4×106Hz和250V.质荷比范围为0~800Th,每个数据集记录时间为2min.采用磷酸铵、十二烷基硫酸钠、牛磺胆酸钠水合物和Ultramark 1621进行校准质谱.质谱由Acquility(2.1.0)软件记录,并在Igor Pro(6.37,Wavemetrics)环境中使用Tofware软件(2.5.10)进行数据分析.
使用Tofware软件(2.5.10)对阈值为±1%的质谱峰进行计算并以尽量小的质量偏差进行分子式的分配.设定在负离子模式下使用12C,1H,16O,14N和32S五种元素,原子数分别限制在1~50,0~200,0~50,0~5和0~2.为了获得唯一的分子式,还限制了分子式的等效双键当量(DBE≥0)和元素比例(H/C≤3,O/C≤3,N/C≤0.5和S/C≤0.2).对于化学式CcHhNnOoSs,DBE的计算采用公式(1):
式中:chn分别为化学式中C、H和N原子个数.修正的芳香性指数(AI)的计算采用公式(2):
式中:chnos分别为化学式中C、H、N、O和S原子个数.
使用单因素方差分析或t检验评估数据组之间的差异.对两个参数进行相关性分析时,统计显著性水平设置为P<0.05.使用统计软件PASW Statistical 18(SPSS)进行统计分析和相关性分析.
在ESI-IMS-TOF-MS负离子模式下,本研究在重庆典型城区冬季PM2.5样品中识别出了1440种有机化合物,其中有62个物种广泛存在于大部分样品内,表明这些物种在重庆冬季持续存在.根据有机物的元素组成可将其分为4类:含碳氢氧化合物(CHO)、含碳氢氮氧化合物(CHNO)、含碳氢氧硫化合物(CHOS)及含碳氢氮氧硫化合物(CHNOS)(图1).
CHO化合物信号强度和分子数量在四类有机物中最小,分别占有机物总信号强度和分子数量的2.2%~10.3%和4.0%~12.6%.这些化合物可能是羰基化合物,含羧基化合物和有机酸等[30].CHNO化合物可能为有机硝酸酯或含氨基类化合物,其峰信号强度占总有机物的6.2%~42.1%,分子数量占5.1%~29.1%.含硫有机物(CHOS+CHNOS)的峰信号强度和分子数量对总有机分子的贡献在整个观测期间大多数时间内超过70%(平均为74.4%),其中CHOS化合物峰信号强度和分子数量的贡献分别为23.5%~38.5%和29.2%~49.0%,CHNOS化合物为26.2%~61.1%和22.8%~52.6%.需要注意的是由于电离效率和基质效应的潜在影响,分子式的峰信号强度和数量并不能直接反映物种的绝对浓度[8],即,含硫化合物在有机分子信号强度及分子数量中的高占比不能直接说明其对有机气溶胶的贡献,但其峰信号强度及占比的变化可以在一定程度上反应其在不同情形下的形成特征.
由IMS衍生的碰撞截面(CCS)作为电离分子稳定的理化参数,代表了特定离子与缓冲气体之间相互作用的有效面积,可作为识别未知化合物的额外证据[31].之前的研究报道称,相同化学类别的物质在CCS和荷质比(m/z)组成的二维空间中倾向于一条独特的趋势线[32].例如,羧酸、烷基硝酸酯和有机硫酸酯(OSs)显示出不同的CCS-m/z趋势线[33].如图2所示,观察到两条CHOS化合物的CCS-m/z趋势线,其中靠右的一条趋势线中的大多数CHOS化合物与Zhang等[33]预测的OSs趋势线较为接近,这表明这些CHOS化合物极大可能属于OSs类别.然而,由于野外大气气溶胶中的CHOS化合物往往非常复杂,可能具有多个官能团,因此表现出比预测的趋势线更宽的范围.
前期野外研究多采用CHOS化合物中氧原子数目与硫原子数目比值判断其是否属于OSs[34-36],即,当CHOS化合物的O/S<4时,其氧原子可能主要存在于羧基和羟基等官能团中,而当CHOS化合物具有高氧硫比(O/S≥4)时,其分子中的氧原子可能以-OSO3H基团的形式存在,CHOS化合物为OSs.图2显示,本研究中靠左的趋势线中大多数CHOS化合物的O/S<4,而靠右的趋势线中几乎所有CHOS化合物的O/S≥4,这进一步表明右侧趋势线中的CHOS化合物属于OSs,这也说明利用CCS-m/z趋势线与利用氧硫比识别OSs的结果较为一致.这些结果表明了CCS-m/z趋势线用于识别OSs的潜力.
碰撞诱导解离(CID)是一种质谱技术中常用的解离方法,它基于分子离子之间的碰撞将离子打碎成更小的碎片,可用于对复杂物质的鉴定、定量和检测分析[32-33].本研究中使用的仪器(IMS-CID-MS)能够在离子迁移分离之后而在质谱仪之前对上述母离子进行碰撞诱导解离.因此,解离碎片和母离子表现出相同的漂移时间.图3(a)表明,母离子C4H3O4S-在15V的CID电压下,其离子强度降低,并且产生了高信号强度的解离碎片HSO4-.当CID电压从15V增加到30V时,母离子C4H3O4S-的强度持续变弱,解离碎片HSO4-的强度有所降低,而进一步解离出的-SO3碎片强度增加.图3(b)中的母离子C5H7O6S-经过15和30V的CID电压后其解离碎片和母离子强度也表现出类似的现象.不同CID电压情况下,母离子(C4H3O4S-和C5H7O6S-)和解离碎片(-SO3和HSO4-)始终具有相同的漂移时间,因此母离子C4H3O4S-和C5H7O6S-中存在-OSO3H官能团,属于有机硫酸酯.这与图2中CCS-m/z结果可相互印证.C4H3O4S-和C5H7O6S-位于预测的OSs趋势线上,这也表明了C4H4O4S和C5H8O6S属于OSs,与CID分析结果一致.可见,CID的结果也为重庆地区PM2.5中有机硫酸酯的存在提供了重要的依据.
肯德里克质量缺陷(KMD)分析可以用于筛选获得的质谱数据,以便将复杂的有机混合物体系可视化,以识别同一系列的所有化合物[37].使用重复单元(RU=CH2)的标称质量(NMRU)和精确质量数(MRU)将化合物的质量(M)转换为肯德里克质量数(KM,KM=M ⋅ NMRU/MRU),然后根据标称肯德里克质量数(NKM)计算肯德里克质量缺陷(KMD,KMD=NKM-KM)[38].在KMD系统中,所有同系物都具有相同的KMD.图4标注了部分识别到的含硫化合物同系物,包括CnH2n-6O9S(n=9~19)、CnH2nO6S(n=2~8)、CnH2n-3NO9S(n=7~15)和CnH2n-1NO7S(n=5~10)等,这些同系物之间具有类似的结构,彼此之间仅差一个CH2基团.基于CCS-m/z结果,这些CHOS化合物均属于有机硫酸酯.此外,一些特殊分子在前期研究中也被识别为OSs.如C5H10O7S为CHOS化合物CnH2nO7S(n=4~9)系列中的化合物,研究表明该化合物是由异戊二烯衍生的有机硫酸酯[1839-40].又如,在CHNOS化合物的CnH2n-3NO7S(n=7~11)同系物中,包括相对丰度较高的C10H17NO7S化合物,该化合物先前已在实验室和野外研究中观察到,并被认为是由生物源前体物α-蒎烯和β-蒎烯等衍生的硝基有机硫酸酯,其氧原子由一个硫酸基团和硝酸酯基组成[3441].综上,这些结果证明了有机硫酸酯是重庆城区PM2.5中重要的有机组分.
根据分子式中的氧原子与硫原子数量比(O/S)可以将CHOS化合物分为不同的组别.如图5(a)所示,CHOS化合物主要为含有4~8个氧原子和1个硫原子的有机物,占CHOS化合物总强度的81.9%.绝大部分(92.7%)的CHOS化合物均属于OSs,这与广州[12](87%~95%)、上海[41](81%~84%)、和太原[42](91%~100%)等城市大气有机气溶胶中分布有大量有机硫酸酯的特点一致.此外,CHOS化合物中较多的O原子(O/S>4)表明可能存在额外的氧化基团(如羟基或羰基),特别是对于O/S≥9的CHOS化合物,这些化合物大多数高度氧化,并且可能与光化学老化反应有关[43].而对于O/S<4的CHOS化合物可能对应还原的含硫物种,如砜、亚砜和磺酸盐等[44].
根据不同的N和O原子数将CHNOS化合物分为19个不同的组别(图5(b)),包括NO2S1~NO12S1和N2O3S1、N2O6S1~N2O12S(NO12S1和N2O12S1表示氧原子数≥12).其中,只有一个N原子的CHNOS化合物占88.5%,包含两个N原子的CHNOS化合物占11.5%,这表明重庆典型城区大气有机气溶胶中大多数CHNOS化合物以一个N原子为主.CHNOS化合物主要分布在N1O4S1~N1O8S1亚组,占总CHNOS化合物丰度的67.2%.具有过量的氧原子(O/(4S+3N)≥1)的CHNOS化合物分子结构中可能存在-OSO3H和-NO3官能团,从而将其分类为硝基有机硫酸酯(NOSs)[34-36].本研究中属于NOSs的CHNOS化合物占比为44.0%,表明CHNOS化合物中的大多数N原子以还原态的形式或S原子以还原的含硫基团形式存在.本研究中NOSs的占比与上海[45](46%~67%)和西北关中盆地[30](20%~75%)大气颗粒物中NOSs的占比相近,但远低于大连[46](78%~ 96%),这可能归因于我国北方地区冬季供暖期间大量煤炭燃烧的直接排放[47].
通常采用有机物的H/C比和DBE来表征化合物的饱和程度,低H/C比和高DBE值表明高不饱和度结构的存在[48-49].图6(a)显示了CHOS和CHNOS在采样期的平均H/C为1.69和1.71,均高于CHO(1.40)和CHNO(1.42).而DBE值具有相反的趋势,CHOS和CHNOS化合物的DBE值分别为2.71和3.44,低于CHO(3.58)和CHNO(4.43).这说明相较于其他两类化合物,含硫化合物具有更低的不饱和度.在上海[49]、北京[50]和珠江三角洲[51]等地区也发现了类似的现象,即相较于CHO和CHNO化合物,CHOS和CHNOS化合物具有更高的H/C和更低的DBE.这些结果表明含硫有机物在大部分地区PM2.5中总是以低不饱和度的特征存在.有机物的O/C比通常被用于评估化合物的氧化程度.如图6(b)所示,CHOS和CHNOS化合物的O/C明显低于CHO和CHNO化合物,但CHOS和CHNOS化合物之间无明显区别.对比于上海[49](CHOS:0.50~0.71、CHNOS:0.50~0.88)、北京[50](CHOS:0.51、CHNOS:0.59)和珠江三角洲[51](CHOS:0.55、CHNOS:0.81)等地区发现,重庆典型城区含硫有机物具有更高的O/C,表明这些有机物可能经历了更强烈的氧化和老化过程.DBE与C原子数的比值(DBE/C)通常用作有机物的稠环芳香结构的判断标准,若该比值大于0.7,则认为化合物具有稠环芳香结构[52].从图中可以看出含硫化合物的DBE/C比基本上均小于0.7,说明含硫化合物主要以脂肪族的形式存在,这与合肥、石家庄[53]和长春[54]等城市地区中含硫化合物的结构相似.
采用Su等[44]开发的含硫有机物的分类方案对本研究中的CHOS和CHNOS化合物进行了分类.图6(c)和(d)中传统VK图中的O/C被(O-3S)/C或(O-3S-2N)/C所替代.由于与常见的含氧官能团(如羟基和羰基)相比,-OSO3和-ONO2官能团分别具有3和4个额外的氧原子,因此(O-3S)/C或(O-3S-2N)/C是用于表示CHOS或CHNOS化合物氧化程度更好的指标[36].根据含硫有机物的H/C和(O-3S)/C或(O-3S-2N)/C可以将修正VK图分为6个区域,从A~F分别为多环芳香族、高度芳香族、高度不饱和、不饱和脂肪族、饱和和低氧化程度.CHOS化合物主要集中在CDE这3个区域,分别占总CHOS化合物相对丰度的35.8%、28.1%和26.3%,其次是F区域,占8.5%.与之不同的是,CHNOS化合物在CDEF区域,分别占23.5%、36.0%、15.5%和25.1%.其中F区域占比相较于CHOS化合物增加了16.6%,表明CHNOS化合物中存在更多的低氧化程度的有机物,这与含硫有机物的元素分布结果一致,即CHNOS化合物中部分有机物中的N原子以还原态的形式或S原子以还原的含硫基团形式存在,而CHOS化合物大部分属于高氧化态的有机物.此外,含硫有机物几乎不存在于AB区域中,这与DBE/C的结果一致,即芳香族化合物可能对本研究中含硫有机物的贡献较低.
根据有机物的H/C、O/C和芳香性指数(AI)可以将化合物分为脂质、蛋白质/氨基糖、碳水化合物、不饱和烃、木质素、稠环芳烃和单宁七类[55].如表1所示,本研究样品中CHOS有机物主要为木质素和碳水化合物,分别占CHOS有机物总信号强度的32.8%和26.3%,其次是蛋白质/氨基糖,占11.7%,而单宁和脂质类占比最低,为9.2%和2.4%.与之相似的是,CHNOS化合物也以木质素(27.9%)和碳水化合物(27.4%)为主,蛋白质/氨基糖和单宁分别占12.7%和9.8%.两类含硫有机物均几乎不以脂质或者稠环芳烃存在.木质素作为植物的主要结构,可由生物质燃烧过程大量释放[47,49].碳水化合物作为生物体的关键组成部分,可以通过多种途径进入大气,例如生物质燃烧、土壤颗粒再悬浮、叶面风蚀、海浪等[56].
本研究进一步对OSs和NOSs可能的前体物进行了分析.根据Wang[57]和Lin等[34]对含硫有机物分子量和碳原子个数的关系研究,建立了“OSs和NOSs前体物图”,该图可以揭示大气PM2.5样品中有机硫酸酯的可能来源和分子结构,结果如图7所示,图中显示了由生物源/人为源前体物(包括异戊二烯/乙二醛、异戊二烯二聚体、单萜/长链烯烃/萘、倍半萜和苯)衍生的OSs和NOSs的分子特征,其中采用(O-3S)/C或(O-3S-2N)/C代替传统的O/C来表示含硫有机物中每个碳原子额外氧化基团的数量.如图7(a)所示,除了几种异戊二烯/乙二醛和苯衍生的OSs和部分非OSs外,大多数CHOS化合物都位于线性烷烃OSs和糖醇OSs间的“分子走廊”中,这也表明分子量和碳数的二维空间可以较好地表征复杂大气气溶胶中的OSs化合物的特征.本研究中CHOS化合物在五类区域中均存在,表明重庆城区OSs的前体物较为复杂.其中I(异戊二烯/乙二醛衍生的OSs)和Ⅲ(单萜/长链烷烃/萘衍生的OSs)区域中CHOS化合物占主导地位.I区域中的OSs位于2~5个碳原子数范围内并靠近糖醇OSs线,且具有高(O-3S)/C比,表明它们被高度氧化.位于I区域的C3H6O6S、C5H10O7S和C5H12O7S等已被证实为来自于生物源异戊二烯的有机硫酸酯[1858-59],并且以较高的相对丰度广泛存在于本研究PM2.5样品中.位于Ⅲ区域中的OSs碳原子数为7~11,(O-3S)/C比多数分布在0.18和0.75之间.其中C10H16O6S被认为是由β-蒎烯在酸性硫酸盐存在下的臭氧化反应所形成的OSs[60],C10H16O8S可通过十氢化萘经氧化后形成环氧化物,再酸催化开环形成[13],C11H14O7S是萘的甲基取代物同系物形成的OSs[61],这些OSs均位于Ⅲ区域,表明了OSs前体物的多样性.此外,倍半萜衍生的OSs在14~16个碳原子(IV)的范围内,(O-3S)/C比在0.18~0.36之间.由苯衍生的OSs(V)位于分子走廊之外,但靠近烷烃OSs线,碳数为6~9,(O-3S)/C较低.还有几种碳原子数超过5的由异戊二烯二聚体衍生的OSs(区域II),但对总OSs的贡献较低.
与OSs的前体物分类相似,根据NOSs的分子量和碳原子数特征可将其前体物分为A~C 3个不同的区域,分别代表由异戊二烯、单萜/萘和倍半萜衍生的NOSs(图7(b)).大多数CHNOS化合物都位于线性烷烃NOSs和糖醇NOSs之间的“分子走廊”内,但也有部分CHNOS化合物位于分子走廊之外,这些CHNOS化合物属于非NOSs,可能含有一个氨基(-NH2)或巯基(-SH),其氧化程度较低.位于A和C区域的NOSs较少,表明以异戊二烯和倍半萜为前体物衍生的NOSs对重庆城区PM2.5中的含硫有机物的贡献不大.部分CHNOS化合物位于B区域中,表明它们可能是由单萜/萘衍生的NOSs.位于B区域中的高丰度C10H17NO7S化合物已在实验室和野外研究中普遍观察到,并被认为是由前体物α-蒎烯和β-蒎烯等衍生的NOSs[18].需注意的是,仍有较多含硫有机物(特别是CHNOS物质)并未包括在已发现的前体物的区域中,这些物质大多属于含有高碳原子数的大分子,其来源可能更加复杂,后续还需更多研究对其来源进行识别.总体而言,以上结果表明,人为源和生物源前体物(特别是异戊二烯和单萜等)对重庆城区有机气溶胶中含硫有机物的形成起着关键的作用.
图8(a)所示,含硫有机物CHOS主要与ALWC和pH值呈显著负相关.CHOS化合物与ALWC呈显著中等程度负相关(r=-0.51,P<0.05),OSs与ALWC之间的负相关关系更为强烈(r=-0.68,P<0.05),这表明较高的液态水含量可能不利于CHOS化合物(特别是有机硫酸酯)的形成或积累.Flaud等[62]在烟雾舱实验中也发现了类似的现象,即相对湿度影响气溶胶液态水含量进而对有机硫酸盐形成的数量和产物分布有重要影响,在潮湿条件下形成的有机硫酸盐浓度明显低于干燥条件,且在潮湿条件下没有观察到高分子量的有机硫酸盐.ALWC对气溶胶中含硫有机物的影响较为复杂,一方面,较高的ALWC可能导致有机硫酸盐的水解或潮解[63-64];另一方面,ALWC可以通过影响极性物质的吸收,进而影响含硫有机物的形成[65].如有研究指出,较高的RH下ALWC增多,使得更多的气态SO2吸收到气溶胶液态水中,并与前体物(有机过氧化物/氢过氧化物、不饱和脂肪酸和羰基/羟基化合物等)反应,进而促进含硫有机物的生成[2466].本研究中CHOS化合物与ALWC的显著负相关及其与SO2浓度之间未发现显著性关系(r=-0.017,P>0.05)都表明,这两方面影响中,ALWC增加导致的有机硫酸盐水解增强可能是更主要的影响.
此外,含水量的增加会导致气溶胶酸度下降,离子强度变低,从而影响含硫有机物的形成[21,67].一些研究发现在高RH下,由异戊二烯衍生的有机硫酸盐形成减少,可能是由颗粒酸度下降和硫酸盐亲核试剂的稀释所导致[30,59].本研究发现含硫有机物与气溶胶pH值表现出显著的负相关关系(CHOS:r=-0.65, P<0.05;OSs:r=-0.69, P<0.05),表明高酸度对含硫有机物,特别是有机硫酸酯的生成具有促进作用.Wang等[68]对北京大气颗粒物有机硫酸盐的研究也发现在较高的气溶胶酸度下有机硫酸盐浓度升高,表明了酸催化化学对其形成的重要性.酸催化的环氧化物开环反应被认为是有机硫酸酯的重要形成途径,大气中的生物源挥发性有机物经光氧化反应后形成的环氧化物可与硫酸或硫酸盐气溶胶发生反应形成有机硫酸酯[8,18],在这个过程中气溶胶酸度被认为是其重要的影响因素.考虑到生物源有机物是本研究中有机硫酸酯的重要前体物(如第2.4节分析所示),这些结果表明酸催化生物源有机物(如异戊二烯和单萜)可能是重庆城区大气中有机硫酸酯的重要成因.
已有研究表明臭氧在有机硫酸盐的形成过程中起着重要的氧化剂作用[62,69-71].但由图8(a)可知,本研究中含硫有机物与臭氧并未表现出明显的相关性(CHOS:r=0.21, P>0.05;OSs:r=0.2, P>0.05).值得注意的是,在本研究中两类丰度较高的含硫有机物C5H10O6S和C8H10O4S与臭氧均表现出正相关性(C5H10O6S:r=0.37, P=0.066;C8H10O4S:r=0.44, P<0.05).C5H10O6S和C8H10O4S已被证明是在硫酸盐存在下由异戊二烯臭氧分解产物吸收到酸化硫酸盐气溶胶上形成的有机硫酸酯[13,58].因此这表明了臭氧对重庆城区部分有机硫酸酯形成的重要性.此外,C5H10O6S和C8H10O4S与SO2均表现为显著的正相关关系(C5H10O6S:r=0.46, P<0.05;C8H10O4S:r=0.51,P<0.05),这表明了SO2对于这些有机硫酸酯形成的重要作用[45].
无机硫酸盐在OSs形成过程中也有重要作用[72].本研究OSs的相对丰度与SO42-浓度之间无显著相关性,但高硫酸盐浓度时,OSs相对丰度较低(图8(b)),可能是由于两者的形成过程存在竞争关系[12],而高ALWC更有利于无机硫酸盐的形成与积累.此外,本研究中OSs/SO42-与SO42-浓度之间呈显著负相关(图8(c)),表明低硫酸盐情况下,更多的无机硫酸盐转化为有机硫酸酯[68].当SO42-浓度较高时(约15~30μg/m3),比值随SO42-浓度的变化变缓(图8(c)),表明SO42-过量不再是OSs形成的限制性因素.这与图8(b)的结果较为吻合,即低硫酸盐浓度时,OSs的相对丰度有随SO42-浓度的增加而增加的趋势.由于SO42-及其前体物SO2主要来自人为源,因此这些结果也表明了有机硫酸酯成因的复杂性,既受到生物排放有机物的影响,又受到人为源污染物的影响.
CHNOS化合物在大气中的形成机制和影响因素更为复杂.如图8(a)所示,CHNOS和NOSs化合物的相对丰度均与硫酸根的浓度表现出中等程度显著负相关关系(CHNOS:r=-0.48,P<0.05;NOSs:r=-0.59,P<0.05),这表明含氮的含硫有机物和硫酸根在形成过程中可能存在竞争关系[12].气溶胶酸度对CHNOS化合物(或NOSs)的影响与CHOS化合物相反,pH值增加有利于CHNOS化合物的形成,这可能与含氮基团的形成有关.在本研究样品中分布较广且丰度较高的C7H13NO7S和C10H17NO7S化合物与NO2和SO2均表现为正相关关系,特别是与SO2的相关性程度更强(C7H13NO7S:r=0.54,P<0.05;C10H17NO7S:r=0.72, P<0.05).其中,C10H17NO7S可能是由α-蒎烯在SO2和NOx存在下氧化形成[19,73].此外,它们与RH之间也呈负相关性,这可能是由于硝基(-ONO2)和硫酸盐官能团(-OSO3H)在较高的气溶胶含水量下更容易发生水解[74].
3.1 使用电喷雾电离结合离子迁移谱-飞行时间质谱仪对重庆典型城区冬季大气PM2.5样品中有机物进行了分子组成分析,结果显示含硫有机物是其主要组成成分,其中CHNOS和CHOS化合物的平均相对丰度分别为40.8%和33.4%.进一步采用IMS衍生的CCS、CID和KMD分析揭示了有机硫酸酯普遍存在于重庆城区大气气溶胶中.
3.2 对含硫有机物的分子特征分析表明重庆城区含硫有机物中有机硫酸酯占总CHOS化合物的92.7%,硝基有机硫酸酯占总CHNOS化合物的44.0%.含硫有机物主要为碳水化合物和木质素物种,并且对比于其他城市具有较高的O/C,可能经历了更强烈的氧化和老化过程.进一步对其前体物进行分析后发现重庆城区OSs和NOSs的前体物高度复杂,既受到生物排放有机物(特别是异戊二烯和单萜等)的影响,又受到人为源污染物的影响.
3.3 含硫有机物(特别是OSs)的形成主要受气溶胶液态水含量、酸度和无机硫酸盐的影响.ALWC的增加不仅可能会导致OSs的水解,还能降低气溶胶酸度,进而影响其生成或积累.高气溶胶酸度更有利于生物源前体物的酸催化形成OSs,而低酸度可能有利于含氮基团的形成,从而促进NOSs的形成.此外,低SO42-浓度可能更有利于无机硫酸盐向有机硝酸酯的转化.
  • 重庆市自然科学基金资助项目(cstc2020jcyj-msxmX0959)
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2025年第45卷第6期
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  • 接收时间:2024-11-27
  • 首发时间:2026-02-27
  • 出版时间:2025-06-20
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  • 收稿日期:2024-11-27
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重庆市自然科学基金资助项目(cstc2020jcyj-msxmX0959)
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    1.重庆大学环境与生态学院,重庆 400045
    2.重庆市计量质量检测研究院,重庆 401123

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2种不同金属材料的力学参数

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种数
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species
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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