2023, Vol. 44
水溶性有机物是大气气溶胶中的重要组成部分[1].有研究表明, 在气溶胶、雾和云水中的水溶性有机物(water-soluble organic matter, WSOM)存在具有羟基、羧基、羰基和硝基氧基的多环和单环结构, 称为类腐殖质物质[2], 其在大气气溶胶WSOM中的丰度相对稳定(9% ~72%)[3~5].类腐殖质物质(humic-like substances, HULIS)对大气环境具有重大影响, 可以作为云凝结核促进气溶胶的吸湿生长[6~8], 而WSOM中除去HULIS的高极性水溶性组分(HP-WSOM)也会对气溶胶的吸湿性产生影响[9~11].因此深入分析WSOM具体组分的污染特征对改善大气环境具有重要意义.
PM2.5被世界卫生组织(WHO)列为第一类致癌物, 其中部分组分可以被活化为亲电活性代谢产物, 进而增加或产生细胞内活性氧物种.HULIS上的氧化还原位点可以协助电子转移, 并导致呼吸沉积时ROS的过度产生和转化, 扰乱受影响细胞中的氧化还原平衡, 对身体健康产生影响[12~14].颗粒物中的过渡金属如Fe、Cu和Mn等也可通过Fenton反应诱导产生ROS[15].大气颗粒物(PM)暴露引起健康效应的潜在机制尚未被完全阐明, 目前公认的PM毒理学机制是诱导源自PM介导的细胞中ROS产生氧化应激[16~18].氧化应激一般通过OP来反映, 体外DCFH测定是测量OP最广泛使用的方法之一.DCFH是一种非荧光试剂, 氧化时会发出荧光.在辣根过氧化物酶(horseradish peroxidase, HRP)的存在下, 2′, 7′-二氯荧光素(2′, 7′-dichlorofluorescin, DCFH)可以迅速氧化成荧光化合物(the fluorescent dye 2′, 7′-dichlorofluorescein, DCF)[19], 因此DCFH可以用作检测氧化活性的荧光探针.先前的研究主要集中在PM2.5氧化电位的确定[20, 21], 但对不同极性的WSOM研究相对较少.
为了研究不同极性WSOM的污染特征和氧化潜势, 本研究采集西安市冬季PM2.5环境样品, 依次提取WSOM中的HULIS-n、HULIS-a和HP-WSOM.分析PM2.5水溶性离子组分、碳组分、三类WSOM的碳浓度和OP, 评估WSOM中各组分的氧化还原能力, 研究三类组分OP与各自浓度的相关性, 以期为西安市大气污染防治和健康效应评估提供数据支撑.
1 材料与方法 1.1 样品采集采样地点位于西安市西安交通大学教学二区楼顶, 采样器高于楼顶地面1.5 m, 采样头距离地面约为15 m.该场地为城市大气混合区域, 周围环绕着住宅区、学校校园以及主要的交通道路[22], 具有大气观测代表性.
采样时间为2019年11月20日至12月30日, 使用流量为1.13 m3 ·min-1的大容量采样器(HVS-PM2.5, Thermo-Anderson Inc.), 每天采样24 h(09:00至次日09:00).采样前将石英纤维过滤器(203 mm×254 mm, Whatman, QMA)在780℃预烘烤7 h.通过高精度(± 0.1 mg)微量天平(ME-5, Sartorius Inc., USA)将样品称重至少3次以确定PM2.5质量.装载样品的过滤器被包裹在预烘烤的铝箔中, 并在进一步分析之前储存在-20℃的冰箱中.采样期间同步收集现场空白, 并通过与PM2.5样品相同的程序进行保存和分析.
1.2 样品提取与分离取部分样品滤膜, 加入6 mL超纯水超声萃取30 min, 利用0.45 μm Teflon滤头过滤1~3次, 得到WSOM组分.利用0.01mol ·L-1的NaOH将WSOM的pH调节至7, 然后将其通过Oasis HLB柱(6 cm3, 200 mg; 水), 用2%(质量分数)的氨的甲醇溶液洗脱吸附物质, 这部分为中性的类腐殖质HULIS-n.将上一步柱子流出物收集并用1 mol ·L-1 HCl调节pH为2并通过另一个Oasis HLB柱, 用甲醇洗脱柱子上吸附的物质, 该物质为酸性类腐殖质HULIS-a.这一步骤的流出物被收集在另一个玻璃瓶中, 根据HLB柱的吸附机制, 这部分具有较高的极性, 为高极性水溶性有机物即HP-WSOM.将以上提取分离的三类WSOM利用氮气流完全干燥, 并用1 mL超纯水重新溶解.
1.3 化学分析水溶性离子组分通过Dionex-500型离子色谱仪(IC, Dionex-500, DionexCorp, Sunnyvale, California, United States)测定, 检测的离子种类包括Cl-、NO3-、SO42-、NH4+、Na+、K+、Ca2+和Mg2+共8种.分析的检出限小于0.05 mg ·L-1, 每组10个样品中选择一个样品进行2次分析以进行质量控制.有机碳(organic carbon, OC)和元素碳(elemental carbon, EC)使用美国DRI Model 2001A型热/光碳分析仪分析.HULIS和WSOM中的碳浓度由总有机碳(total organic carbon, TOC)分析仪(TOC-LCPH, Shimadzu, Kyoto, Japan)测定.空白膜与样品采用相同方法处理, 所有数据均已扣除空白值, 平行样复检的相对误差小于10%.
1.4 OP测量使用2′, 7′-二氯二氢荧光素-二乙酸酯(2′, 7′-dichlorofluorescein-diacetyl, DCFH-DA)(Sigma-Aldrich, Saint Louis, Missouri, US)测定ROS活性.将一定量三类WSOM提取物接种在96孔板中, 并添加Hanks平衡盐溶液缓冲液(pH=7.2)以保持相同的最终溶液体积.将DCFH-DA添加到样品中, 并在37℃黑暗中孵育10 min.孵育后, 立即使用酶标仪(Flex Station 3 Multi-Mode, Molecular Devices, Taiwan, China)在485/538 nm的激发/发射波长下分别测量0和30 min的荧光强度, 通过两个时刻的荧光强度表征样品ROS生成能力.
2 结果与讨论 2.1 冬季PM2.5的污染状况采样期间西安市ρ(PM2.5)范围为9.90~241.92 μg ·m-3, ρ(PM2.5)平均值为(80.70±49.21) μg ·m-3, 超过了《环境空气质量标准》(GB 3095-2012)的二级标准(75 μg ·m-3).采样期间霾天和非霾天的PM2.5日平均浓度如图 1所示, 其中霾天占观测期接近一半的天数.2019年12月28日为本观测期ρ(PM2.5)最高水平, 达241.92 μg ·m-3.霾天和非霾天ρ(PM2.5)平均值分别为(122.09±46.26) μg ·m-3和(48.71±17.08) μg ·m-3, 霾天的浓度是非霾天的2.51倍.
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图 1 采样期间PM2.5浓度分布 Fig. 1 Distribution of PM2.5 concentration during sampling period |
图 2显示了霾天和非霾天的PM2.5各组分占比, 包括有机物(organic matter, OM)、元素碳(elemental carbon, EC)、水溶性无机离子(Cl-、NO3-、SO42-、NH4+、Na+、K+、Ca2+和Mg2+)及其他未鉴别组分, 其中OM采用Turpin等[23]在2001年推荐的OM=1.6×OC进行估算.
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图 2 PM2.5中各组分的占比 Fig. 2 Proportion of each component in PM2.5 |
由图 2可知, 碳质物种和无机离子是PM2.5最大的组成部分, 这与以往的研究结果一致[24, 25].OC/EC常被用来判断大气二次污染的程度, 一般来说, OC/EC的值大于2时, 说明大气中存在二次有机碳(secondary organic carbon, SOC)[26], 比值越高表明大气中的二次污染越显著.本研究中, OC/EC的平均值为(4.45±1.27), 说明西安冬季PM2.5受到二次转化影响较大.图 2显示3种主要的次生无机离子(NO3-、SO42-和NH4+)的占比达PM2.5浓度的30%, 进一步表明西安市大气受到了较为严重的二次污染.NO3-/SO42-用来表征大气污染的源贡献, 由NO3-/SO42->1可知, 机动车排放对西安冬季大气颗粒物有较大贡献[27].已有研究表明, K+可以作为生物质燃烧的示踪剂[24, 28, 29].本研究中, 霾天和非霾天K+在阳离子中占比分别为8.85%和10.84%, 表明生物质燃烧对西安冬季大气污染有贡献.以上结果说明西安冬季PM2.5来源于二次生成、机动车排放和生物质燃烧等.
2.2 不同极性WSOM的浓度水平西安市PM2.5中ρ(WSOM)和ρ(HULIS)分别为(5.83±2.22) μg ·m-3和(4.62±1.89) μg ·m-3.与其他地区冬季的观测结果比较见表 1.本研究结果与广州2014-2015年冬季大气PM2.5中ρ(WSOM)[(5.8±2.6) μg ·m-3]和ρ(HULIS)[(3.5±1.6) μg ·m-3]水平相近[30].
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表 1 以往研究的WSOM和HULIS的浓度和比值对比 Table 1 Comparison of concentration and ratio of WSOM and HULIS in previous studies |
观测期间西安市区霾天ρ(WSOM)和ρ(HULIS)均值分别为(6.73±2.34) μg ·m-3和(5.54±1.93) μg ·m-3, 非霾天ρ(WSOM)和ρ(HULIS)均值分别为(5.11±1.87) μg ·m-3和(3.87±1.52) μg ·m-3.与上海2015年冬季霾天和非霾天大气PM2.5中的ρ(WSOM) [(7.05±3.54) μg ·m-3和(4.86±1.87) μg ·m-3]水平相差不大, 但西安市冬季HULIS浓度明显高于上海ρ(HULIS)[(1.96±1.06) μg ·m-3和(1.37±0.39) μg ·m-3][31], 这主要与各采样点的地理位置及污染源特征不同有关.西安周边冬季采暖使用煤和生物质燃烧排放大量污染物, 且西安地处关中盆地, 污染物不易扩散[32], 而上海属于沿海地区, 污染物可以在海风作用下被稀释[33, 34].
整个观测期, HULIS占WSOM的(78.81±10.50)%, 说明HULIS是WSOM的重要组成部分.考虑到霾天和非霾天PM2.5的来源和形成机制的不同, 本研究分别探讨WSOM和HULIS在不同环境条件下的浓度水平分布(图 3)及其各自占比情况(表 2).可以看出, 大气PM2.5中WSOM浓度霾天低于非霾天, 而HULIS/WSOM比值呈现出相反的结果, 即霾天高于非霾天, 说明霾天WSOM中存在更多的HULIS.
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图 3 采样期间HULIS和WSOM浓度分布 Fig. 3 Distribution of HULIS and WSOM concentration during sampling period |
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表 2 观测期间PM2.5中HULIS和WSOM占比/% Table 2 Proportion of HULIS and WSOM in PM2.5 during observation/% |
图 4显示了采样期间HULIS-a、HULIS-n和HP-WSOM的碳浓度变化, HULIS-a-C、HULIS-n-C和HP-WSOC分别表示3种物质的碳浓度. ρ(HULIS-a-C)范围为0.06~6.59 μg ·m-3, 平均值为(1.32±1.18) μg ·m-3, 霾天ρ(HULIS-a-C)平均值为(1.56±1.54) μg ·m-3, 是非霾天1.38倍; HULIS-n是WSOM中最疏水的部分, 占ρ(WSOM)的(56.43±12.44)%, 这与之前的研究结果一致[41]. ρ(HULIS-n-C)范围为1.21~5.73 μg ·m-3, 平均值为(3.29±1.45) μg ·m-3, 霾天和非霾天的ρ(HULIS-n-C)平均值分别为(3.98±1.38) μg ·m-3和(2.74±1.28) μg ·m-3; ρ(HP-WSOC)范围为0.06~3.00 μg ·m-3, 平均值为(1.22±0.73) μg ·m-3, 霾天平均值为(1.19±0.69) μg ·m-3, 非霾天平均值为(1.24±0.78) μg ·m-3.本研究结果明显高于Chen等[41]所研究的2011~2012年日本名古屋冬季样品的测定结果, 即：ρ(HULIS-a-C)、ρ(HULIS-n-C)和ρ(HP-WSOC)分别为(0.30±0.03)、(0.97±0.16)和(0.30±0.06) μg ·m-3, 可能与PM2.5来源差异有关.有研究表明, 与SO42-相比, HULIS和WSOM与NO3-相关性更显著[42, 43], 说明移动源排放的PM2.5中HULIS和WSOM高于固定源.2011~2012年日本名古屋大气PM2.5中SO42-浓度低于NO3-浓度[44], 即固定源排放占主导, 这与本研究相反, 因此其各组分水平偏低.
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图 4 整个采样期间HULIS-a、HULIS-n和HP-WSOM的碳浓度变化 Fig. 4 Changes in carbon concentration of HULIS-a, HULIS-n, and HP-WSOM during the whole sampling period |
进一步分析数据发现整个采样期间HULIS-a-C/WSOC为0.22, HULIS-n-C/WSOC为0.56, HP-WSOM-C/WSOC为0.21, 说明环境样本中HULIS-n为WSOM的主要组成.另外, 霾天呈现出HULIS-n-C>HULIS-a-C>HP-WSOC的特征, 而非霾天HULIS-n-C>HP-WSOC>HULIS-a-C, 霾天HULIS-n-C的分别是HULIS-a-C和HP-WSOC浓度的2.55倍和3.34倍, 非霾天分别为2.42倍和2.21倍.说明HULIS-n是西安市冬季霾天和非霾天大气WSOM的主要组分.
2.3 氧化潜势特征分析OPm表示单位质量组分所具有的氧化潜势, 它是PM固有OP的量度[25].OPv表示基于每单位吸入空气与PM2.5相关的氧化应激[26], 是个人在特定地点接触活性氧的指标[28].表 3显示了采样期间霾天和非霾天不同极性的WSOM组分的OPm和OPv.整个采样期间HULIS-a、HULIS-n和HP-WSOM的OPm分别为(55.94±61.88)、(24.49±9.66)和(79.63±45.24)nmol ·μg-1, OPv分别为(38.06±28.35)、(85.38±4.44)和(99.19±6.88)nmol ·m-3.霾天和非霾天OPm的规律均为HP-WSOM>HULIS-a>HULIS-n, 虽然HULIS-n浓度水平在HULIS-a和HP-WSOM之上, 但其OPm远小于HULIS-a和HP-WSOM, 这表明HULIS-n中与产生ROS能力相关的物质少于其他两个组分.霾天和非霾天的OPv均遵循HP-WSOM>HULIS-n>HULIS-a的规律, HP-WSOM的OPv最高, 而其浓度最低, 说明浓度较低的组分可能会引起更高的毒性, 这与前人研究的结果一致[30].以上差异可归因于与氧化还原活性化合物相关的不同化学成分和分子结构差异[31], 需要进一步地研究来探索WSOM不同极性组分的分子结构与其氧化活性之间的关系.
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表 3 霾天和非霾天的HULIS-a、HULIS-n和HP-WSOM的OPm和OPv Table 3 OPm and OPv of HULIS-a, HULIS-n, and HP-WSOM in haze and non-haze days |
霾天HP-WSOM的OPm高于非霾天, 而霾天HP-WSOM浓度低于非霾天, 说明各组分相关的OPm主要由组分自身性质而非浓度决定.除此之外, HULIS-a和HULIS-n霾天OPv略大于非霾天, 有研究表明HULIS样品在霾天比非霾天更能催化ROS的产生[17], 这就可以解释PM2.5升高HULIS物种OPv也升高的原因.而霾天HP-WSOM的OPv小于非霾天, 这可能与不同污染条件下HP-WSOM分子特征的差异有关.Ning等[45]报告称O3和温度会影响WSOM的分子特征, 进而增强其氧化能力.分析气象数据发现观测期间气温和O3浓度呈现出霾天[(1.96±3.39)℃; (14.11±4.80) μg ·m-3]低于非霾天[(2.73±2.01)℃; (19.28±9.76) μg ·m-3]的特征, 因此非霾天HP-WSOM相对于霾天具有更强的氧化潜力.总的来说, 各组分的氧化潜势与污染物浓度没有必然联系.
2.4 氧化潜势与不同极性WSOM的关系分析不同污染状况下HULIS-a、HULIS-n和HP-WSOM的碳浓度与OPm的相关性如图 5和图 6所示.可以看出, 无论是霾天还是非霾天, OPm与WSOM各组分碳浓度均呈负相关关系, 与前人的研究一致[46].这可能是因为随着各组分碳浓度升高, 不产生ROS的物质占比增加.Lin等[13]发现左旋葡聚糖、琥珀酸、苹果酸和草酸等有机物几乎没有ROS活性.虽然各组分浓度水平升高, 但其与ROS生成相关的组分比例下降, 因此整体的组分浓度与氧化潜势呈现负相关关系.
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图 5 霾天各组分OPm与组分碳浓度相关性 Fig. 5 Correlation between OPm and carbon concentration of each component in haze days |
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图 6 非霾天各组分OPm与组分碳浓度相关性 Fig. 6 Correlation between OPm and carbon concentration of each component in non-haze days |
霾天OPm与HULIS-n-C(R2=0.866 9)和HP-WSOC(R2=0.858 2)具有较高相关性, 说明高PM2.5浓度下, WSOM的氧化潜势主要由HULIS-n和HP-WSOC贡献.非霾天HULIS-a-C(R2=0.936 8)、HULIS-n-C(R2=0.866 2)、HP-WSOC(R2=0.927 6)均与OPm强相关, 说明低污染条件下, OPm对组分浓度有很强的依赖性, 除HULIS外, HP-WSOM对OP也有重要贡献.同时笔者发现随着PM2.5的升高, HULIS-a与OPm相关性减弱, 说明随着污染加重, HULIS-a中产生ROS的物质占比降低.
3 结论(1) 观测期间碳质物种和无机离子是西安冬季PM2.5样品主要组成部分.由OC/EC>2, NO3-/SO42->1以及K+在阳离子的高占比, 推测西安冬季市区PM2.5由机动车排放、二次污染和生物质燃烧共同贡献.
(2) HULIS是WSOM的重要组成部分, 霾天WSOM中HULIS占比更高, 霾天和非霾天HULIS-n碳浓度均高于HULIS-a和HP-WSOM.
(3) 组分产生ROS的能力与其组分碳浓度或是PM2.5污染水平并无绝对正相关关系, 较低的组分碳浓度可能会引起更高的毒性, 这主要由各组分自身性质决定.
(4) 整个采样期间OPm与WSOM的三类组分碳浓度呈负相关关系, 可能是由于组分中某些物质几乎无ROS生成能力, 但是其占比增大导致.霾天WSOM的氧化潜势主要由HULIS-n和HP-WSOM贡献, 非霾天OPm则由HULIS-a、HULIS-n和HP-WSOM共同决定.
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