水体中17种持久性和可迁移有机污染物的检测

高欲乾, 郭敏丽, 梁存珍, 关东, 刘鹏. 水体中17种持久性和可迁移有机污染物的检测[J]. 环境工程学报, 2023, 17(5): 1736-1746. doi: 10.12030/j.cjee.202301066
引用本文: 高欲乾, 郭敏丽, 梁存珍, 关东, 刘鹏. 水体中17种持久性和可迁移有机污染物的检测[J]. 环境工程学报, 2023, 17(5): 1736-1746. doi: 10.12030/j.cjee.202301066
GAO Yuqian, GUO Minli, LIANG Cunzhen, GUAN Dong, LIU Peng. Determination of 17 persistent and mobile organic contaminants (PMOCs) in water[J]. Chinese Journal of Environmental Engineering, 2023, 17(5): 1736-1746. doi: 10.12030/j.cjee.202301066
Citation: GAO Yuqian, GUO Minli, LIANG Cunzhen, GUAN Dong, LIU Peng. Determination of 17 persistent and mobile organic contaminants (PMOCs) in water[J]. Chinese Journal of Environmental Engineering, 2023, 17(5): 1736-1746. doi: 10.12030/j.cjee.202301066

水体中17种持久性和可迁移有机污染物的检测

    作者简介: 高欲乾 (1998—) ,男,硕士研究生,1073306604@qq.com
    通讯作者: 梁存珍(1973—),男,博士,副教授,liangcunzhen@bipt.edu.cn
  • 基金项目:
    第三次新疆综合科学考察资助项目 (2021xjkk1400)
  • 中图分类号: X832

Determination of 17 persistent and mobile organic contaminants (PMOCs) in water

    Corresponding author: LIANG Cunzhen, liangcunzhen@bipt.edu.cn
  • 摘要: 持久性和移动性有机污染物 (persistent and mobile organic contaminants, PMOCs) 在环境中降解缓慢,并且可以通过水体循环进行迁移。由于缺乏水体中PMOCs的高效富集和准确测定方法,导致关于PMOCs在水体中存在水平的可靠监测数据较少。通过优化固相萃取条件和高效液相色谱-串联质谱参数,建立了同时检测水中17种PMOCs的分析方法。采用HLB固相萃取柱对水样中的PMOCs进行富集,乙腈和含10 mmol·L−1乙酸铵的水溶液作为流动相进行梯度洗脱,PMOCs检出限为0.04~0.35 ng·L−1,定量限为0.13~1.16 ng·L−1,回收率为65.01%~98.65%。在北京潮白河、广东北江和河北滹沱河进行布点采样,并测定其PMOCs的质量浓度。实验结果表明:17种PMOCs在潮白河、北江和滹沱河中均有检出,其ƩPMOCs平均质量浓度分别为604.69、740.45和505.11 ng·L−1。潮白河地表水中安赛蜜、金刚烷胺和己内酰胺的质量浓度相对较高,分别高达261.75、143.84和153.71 ng·L−1。北江中安赛蜜、磷酸三 (2-氯丙基) 酯和己内酰胺的质量浓度相对较高,分别高达433.14、444.46和108.76 ng·L−1。滹沱河中金刚烷胺、己内酰胺和磷酸三 (2-氯丙基) 酯的质量浓度较高,分别高达218.10、101.14和222.60 ng·L−1。本研究结果可为地表水和地下水水体中PMOCs的检测评价提供参考。
  • 加载中
  • 图 1  流动相对PMOCs响应强度的影响

    Figure 1.  Influence of mobile phase on the response intensity of PMOCs

    图 2  流动相和流动相添加剂对PMOCs响应强度的影响

    Figure 2.  Influence of mobile phase and concentration of additive on the response intensity of PMOCs

    图 3  固相萃取柱对LC-MS/MS检测 PMOCs回收率的影响

    Figure 3.  Influence of LC-MS/MS SPE sorbent on the recoveries of PMOCs

    图 4  潮白河地表水和地下水中PMOCs的时空分布

    Figure 4.  Spatiotemporal variation of the PMOCs in the surface water and groundwater from Chaobai River

    表 1  17种PMOCs的LC-MS/MS优化参数

    Table 1.  The details of LC-MS/MS operating parameters of 17 PMOCs

    化合物出峰时间/min母离子 (m/z) 定量离子 (m/z) Q1/VCE/VQ3/V
    BDMA2.548135.7090.90/65.00/38.95−30−25/-35/-54−30/-25/-15
    DTG2.134239.70132.95/107.95/106.10−30−21/-22/-30−14/-21/-19
    TCPP7.152328.6099.00/174.85/252.95−23−23/-13/-9−19/-19/-29
    DPG2.145211.60119.00/76.95/94.00−29−22/-40/-21−22/-28/-18
    AMANT2.294151.70135.05/78.9/77.00−30−18/-35/-44−26/-28/-29
    BETMA2.293150.9092.05/91.00/65.10−30−21/-22/-38−17/-17/-24
    CAP2.592111.1079.95/95.85/81.001222/23/2030/17/29
    MTSC3.421111.9080.05/95.90/80.901122/24/1930/17/29
    PEA1.464111.1079.95/96.00/81.001123/23/1930/17/30
    MBSA2.053169.80106.05/63.85/79.001816/46/2718/23/30
    MS3.483111.1079.95/96.00/81.001224/23/2030/17/28
    ACE1.488162.0082.00/78.05/40.001113/29/2830/30/14
    XSA1.638185.2080.00/121.10/118.851230/22/2530/22/21
    SAC1.499182.0041.90/105.85/62.002036/21/2314/19/25
    AMPSA1.504206.00135.00/79.95/70.001422/29/2525/30/26
    TFMSA1.987149.0079.90/98.80/68.901623/23/3130/17/27
    BPS2.948249.00107.95/92.00/155.901730/36/2020/30/16
    化合物出峰时间/min母离子 (m/z) 定量离子 (m/z) Q1/VCE/VQ3/V
    BDMA2.548135.7090.90/65.00/38.95−30−25/-35/-54−30/-25/-15
    DTG2.134239.70132.95/107.95/106.10−30−21/-22/-30−14/-21/-19
    TCPP7.152328.6099.00/174.85/252.95−23−23/-13/-9−19/-19/-29
    DPG2.145211.60119.00/76.95/94.00−29−22/-40/-21−22/-28/-18
    AMANT2.294151.70135.05/78.9/77.00−30−18/-35/-44−26/-28/-29
    BETMA2.293150.9092.05/91.00/65.10−30−21/-22/-38−17/-17/-24
    CAP2.592111.1079.95/95.85/81.001222/23/2030/17/29
    MTSC3.421111.9080.05/95.90/80.901122/24/1930/17/29
    PEA1.464111.1079.95/96.00/81.001123/23/1930/17/30
    MBSA2.053169.80106.05/63.85/79.001816/46/2718/23/30
    MS3.483111.1079.95/96.00/81.001224/23/2030/17/28
    ACE1.488162.0082.00/78.05/40.001113/29/2830/30/14
    XSA1.638185.2080.00/121.10/118.851230/22/2530/22/21
    SAC1.499182.0041.90/105.85/62.002036/21/2314/19/25
    AMPSA1.504206.00135.00/79.95/70.001422/29/2525/30/26
    TFMSA1.987149.0079.90/98.80/68.901623/23/3130/17/27
    BPS2.948249.00107.95/92.00/155.901730/36/2020/30/16
    下载: 导出CSV

    表 2  17种PMOCs的回收率、相对标准偏差、线性相关系数及检测限

    Table 2.  Recovery rate, RSD, correlation coefficients, detection limit of 17 PMOCs

    化合物回收率/%RSD/%相关
    系数R2
    检出限/
    (ng·L-1)
    定量限/
    (ng·L-1)
    BDMA87.494.80.9980.090.29
    DTG98.658.80.9990.080.27
    TCPP80.217.10.9960.130.43
    DPG98.246.10.9980.210.69
    AMANT85.323.60.9950.120.39
    BETMA76.988.70.9990.180.59
    CAP65.055.10.9950.040.13
    MTSC74.404.90.9980.120.39
    PEA94.107.50.9980.150.49
    MBSA76.736.20.9940.311.02
    MS65.016.10.9950.110.36
    ACE86.585.40.9980.260.86
    XSA89.505.60.9930.351.16
    SAC83.217.60.9960.240.79
    AMPSA85.218.90.9950.331.09
    TFMSA82.997.70.9980.170.56
    BPS76.123.60.9960.160.53
    化合物回收率/%RSD/%相关
    系数R2
    检出限/
    (ng·L-1)
    定量限/
    (ng·L-1)
    BDMA87.494.80.9980.090.29
    DTG98.658.80.9990.080.27
    TCPP80.217.10.9960.130.43
    DPG98.246.10.9980.210.69
    AMANT85.323.60.9950.120.39
    BETMA76.988.70.9990.180.59
    CAP65.055.10.9950.040.13
    MTSC74.404.90.9980.120.39
    PEA94.107.50.9980.150.49
    MBSA76.736.20.9940.311.02
    MS65.016.10.9950.110.36
    ACE86.585.40.9980.260.86
    XSA89.505.60.9930.351.16
    SAC83.217.60.9960.240.79
    AMPSA85.218.90.9950.331.09
    TFMSA82.997.70.9980.170.56
    BPS76.123.60.9960.160.53
    下载: 导出CSV

    表 3  平水期17种PMOCs在10个采样点中的质量浓度

    Table 3.  Mass concentrations of 17 kinds of PMOCs in 10 sampling points in flat water period

    化合物地表水质量浓度 /(ng·L−1)地下水质量浓度 /(ng·L−1)
    S1S2S3S4S51#2#3#4#5#
    BDMA23.3211.2241.0322.6423.446.977.8414.5622.465.16
    DTG34.5612.8131.278.196.762.571.65ND6.315.22
    TCPP143.3428.7721.4717.6464.6421.7131.4735.85109.6945.61
    DPG68.79113.621.7032.4261.2231.79ND95.1136.722.98
    AMANT143.8464.69111.1768.9745.6625.3381.7060.4670.5868.84
    BETMA48.8230.7118.1562.5933.029.6716.118.0828.5311.88
    CAP101.8261.2681.1136.5673.2747.3639.6839.5851.7646.16
    MTSC64.8813.4146.9933.1160.5560.4959.7545.6619.9955.51
    PEA28.1152.847.4117.8945.4327.3414.9911.6128.176.66
    MBSA30.566.9880.5612.4314.6933.3640.1228.6410.8229.99
    MS69.7588.2910.3587.5764.7338.4927.8613.4924.5517.97
    ACE261.75137.1389.38113.1369.9450.2473.8732.2959.74168.11
    XSA79.4523.0935.3114.2934.5933.5139.8136.647.0565.09
    SAC63.7157.2153.4814.389.607.454.4ND6.026.63
    AMPSA25.3624.0863.29100.4879.6620.5920.5912.9015.1052.32
    TFMSA10.2914.353.1614.2618.6574.6520.6611.6210.3621.24
    BPS33.4120.5228.6326.362.0611.9111.49ND35.7632.53
    ƩPMOCs1 231.76760.94724.47682.91707.91503.43491.99446.49543.61641.91
      注:ND表示未检出。
    化合物地表水质量浓度 /(ng·L−1)地下水质量浓度 /(ng·L−1)
    S1S2S3S4S51#2#3#4#5#
    BDMA23.3211.2241.0322.6423.446.977.8414.5622.465.16
    DTG34.5612.8131.278.196.762.571.65ND6.315.22
    TCPP143.3428.7721.4717.6464.6421.7131.4735.85109.6945.61
    DPG68.79113.621.7032.4261.2231.79ND95.1136.722.98
    AMANT143.8464.69111.1768.9745.6625.3381.7060.4670.5868.84
    BETMA48.8230.7118.1562.5933.029.6716.118.0828.5311.88
    CAP101.8261.2681.1136.5673.2747.3639.6839.5851.7646.16
    MTSC64.8813.4146.9933.1160.5560.4959.7545.6619.9955.51
    PEA28.1152.847.4117.8945.4327.3414.9911.6128.176.66
    MBSA30.566.9880.5612.4314.6933.3640.1228.6410.8229.99
    MS69.7588.2910.3587.5764.7338.4927.8613.4924.5517.97
    ACE261.75137.1389.38113.1369.9450.2473.8732.2959.74168.11
    XSA79.4523.0935.3114.2934.5933.5139.8136.647.0565.09
    SAC63.7157.2153.4814.389.607.454.4ND6.026.63
    AMPSA25.3624.0863.29100.4879.6620.5920.5912.9015.1052.32
    TFMSA10.2914.353.1614.2618.6574.6520.6611.6210.3621.24
    BPS33.4120.5228.6326.362.0611.9111.49ND35.7632.53
    ƩPMOCs1 231.76760.94724.47682.91707.91503.43491.99446.49543.61641.91
      注:ND表示未检出。
    下载: 导出CSV

    表 4  丰水期17种PMOCs在10个采样点中的质量浓度

    Table 4.  Mass concentrations of 17 kinds of PMOCs in 10 sampling points in abundant water period

    化合物地表水质量浓度/(ng·L−1)地下水质量浓度/(ng·L−1)
    S1S2S3S4S51#2#3#4#5#
    BDMA71.2313.8122.8111.7729.8332.8714.079.2634.1214.96
    DTG17.103.2924.436.9713.671.711.13ND24.6512.34
    TCPP68.9436.6923.82118.88.1684.5314.9312.5610.6120.26
    DPG45.9143.9391.8579.2549.4915.8833.2715.1811.9424.58
    AMANT83.8471.1413.37102.1869.8822.4137.2328.2226.0534.21
    BETMA17.423.9411.6415.8026.4523.935.3919.0925.6149.03
    CAP153.7149.9452.4361.6072.0173.3557.1519.3873.88101.14
    MTSC23.5527.8430.1322.5520.0730.7522.6837.8460.3019.87
    PEA17.4210.267.5211.439.776.2410.573.5223.2523.30
    MBSA15.5648.1125.8242.7918.7633.4222.4138.515.0826.86
    MS79.7720.65ND3.7713.5338.6912.7971.9732.1120.62
    ACE128.7259.7898.0963.61135.9446.3254.7525.6142.4173.37
    XSA77.483.2544.163.617.7234.1630.9ND18.658.19
    SAC15.466.8212.9424.1619.164.021.76ND6.532.26
    AMPSA48.7018.2352.4231.0219.9313.7954.7216.0836.4210.20
    TFMSA17.099.218.2611.979.447.4311.483.1114.5520.74
    BPS13.1333.683.319.82ND2.4919.6810.811.412.17
    ƩPMOCs895.03460.57522.95621.08523.81471.99404.91311.12457.56464.11
      注:ND表示未检出。
    化合物地表水质量浓度/(ng·L−1)地下水质量浓度/(ng·L−1)
    S1S2S3S4S51#2#3#4#5#
    BDMA71.2313.8122.8111.7729.8332.8714.079.2634.1214.96
    DTG17.103.2924.436.9713.671.711.13ND24.6512.34
    TCPP68.9436.6923.82118.88.1684.5314.9312.5610.6120.26
    DPG45.9143.9391.8579.2549.4915.8833.2715.1811.9424.58
    AMANT83.8471.1413.37102.1869.8822.4137.2328.2226.0534.21
    BETMA17.423.9411.6415.8026.4523.935.3919.0925.6149.03
    CAP153.7149.9452.4361.6072.0173.3557.1519.3873.88101.14
    MTSC23.5527.8430.1322.5520.0730.7522.6837.8460.3019.87
    PEA17.4210.267.5211.439.776.2410.573.5223.2523.30
    MBSA15.5648.1125.8242.7918.7633.4222.4138.515.0826.86
    MS79.7720.65ND3.7713.5338.6912.7971.9732.1120.62
    ACE128.7259.7898.0963.61135.9446.3254.7525.6142.4173.37
    XSA77.483.2544.163.617.7234.1630.9ND18.658.19
    SAC15.466.8212.9424.1619.164.021.76ND6.532.26
    AMPSA48.7018.2352.4231.0219.9313.7954.7216.0836.4210.20
    TFMSA17.099.218.2611.979.447.4311.483.1114.5520.74
    BPS13.1333.683.319.82ND2.4919.6810.811.412.17
    ƩPMOCs895.03460.57522.95621.08523.81471.99404.91311.12457.56464.11
      注:ND表示未检出。
    下载: 导出CSV

    表 5  北江中PMOCs在10个采样点中的质量浓度

    Table 5.  Mass concentrations of 17 kinds of PMOCs in 10 sampling points in the Beijiang River ng·L−1

    化合物B01B02B03B04B05B06B07B08B09B10
    BDMA60.6581.7552.21105.4744.1860.4931.5354.7620.9139.72
    DTG21.4338.1521.6917.5111.977.979.194.1917.727.73
    TCPP444.46120.0637.8757.93152.7527.7317.7643.5025.2072.15
    DPG10.5823.4218.97114.193.3617.871.6531.8151.427.72
    AMANT55.8125.9310.4216.2210.8144.9918.8036.0748.2114.26
    BETMA23.9979.0669.5578.3127.4678.4232.2930.3462.8253.16
    CAP79.4499.7196.62198.7647.0941.6857.7649.6964.9678.87
    MTSC64.8446.4731.2821.3736.3530.7825.3229.0743.8233.06
    PEA6.167.375.097.424.235.927.535.9627.368.35
    MBSA38.1310.6328.4418.1047.2710.279.4632.2810.168.45
    MS17.1628.9618.747.4813.6820.9013.1512.2526.3617.62
    ACE433.14134.13127.4726.50217.8599.06270.24123.51233.3760.49
    XSA130.8538.7033.0526.7620.9384.6527.1524.4129.3423.86
    SAC31.7022.6515.9013.7414.096.195.657.329.354.54
    AMPSA20.4718.3441.1427.8635.0434.7129.2558.86111.4064.94
    TFMSA36.0917.654.6216.715.1416.416.7325.3724.747.14
    BPS1.311.283.416.652.090.831.160.9327.591.72
    ƩPMOCs1 476.21794.26616.47760.98694.29588.87564.62570.32834.73503.78
      注:ND表示未检出。
    化合物B01B02B03B04B05B06B07B08B09B10
    BDMA60.6581.7552.21105.4744.1860.4931.5354.7620.9139.72
    DTG21.4338.1521.6917.5111.977.979.194.1917.727.73
    TCPP444.46120.0637.8757.93152.7527.7317.7643.5025.2072.15
    DPG10.5823.4218.97114.193.3617.871.6531.8151.427.72
    AMANT55.8125.9310.4216.2210.8144.9918.8036.0748.2114.26
    BETMA23.9979.0669.5578.3127.4678.4232.2930.3462.8253.16
    CAP79.4499.7196.62198.7647.0941.6857.7649.6964.9678.87
    MTSC64.8446.4731.2821.3736.3530.7825.3229.0743.8233.06
    PEA6.167.375.097.424.235.927.535.9627.368.35
    MBSA38.1310.6328.4418.1047.2710.279.4632.2810.168.45
    MS17.1628.9618.747.4813.6820.9013.1512.2526.3617.62
    ACE433.14134.13127.4726.50217.8599.06270.24123.51233.3760.49
    XSA130.8538.7033.0526.7620.9384.6527.1524.4129.3423.86
    SAC31.7022.6515.9013.7414.096.195.657.329.354.54
    AMPSA20.4718.3441.1427.8635.0434.7129.2558.86111.4064.94
    TFMSA36.0917.654.6216.715.1416.416.7325.3724.747.14
    BPS1.311.283.416.652.090.831.160.9327.591.72
    ƩPMOCs1 476.21794.26616.47760.98694.29588.87564.62570.32834.73503.78
      注:ND表示未检出。
    下载: 导出CSV

    表 6  滹沱河中PMOCs在10个采样点中的质量浓度

    Table 6.  Mass concentrations of 17 kinds of PMOCs in 10 sampling points in the Hutuo River ng·L−1

    化合物H01H02H03H04H05H06H07H08H09H10
    BDMA11.1924.7471.3131.7860.3877.0328.3238.0852.4135.06
    DTG0.951.521.273.1313.4024.8049.033.854.849.29
    TCPP19.27222.6011.8221.1277.1343.6670.5220.4430.5120.53
    DPG2.043.4647.208.1835.0914.0722.0622.9294.9329.86
    AMANT4.3611.6314.159.72140.59218.10171.7824.6469.3613.86
    BETMA8.0719.189.483.8414.7854.5787.632.28159.8031.46
    CAP73.8814.3389.86141.1443.8038.7653.7146.2160.4173.35
    MTSC17.8910.286.514.7811.599.9523.3711.085.482.54
    PEA4.449.848.937.1611.816.837.484.864.053.69
    MBSA16.1919.5563.2029.954.0416.7625.1089.7363.4951.13
    MS2.0839.4232.0233.9613.879.1924.2340.8848.6918.46
    ACE61.976.4651.6118.3386.07241.1620.5024.686.899.67
    XSA12.672.565.117.2410.8843.0937.603.646.2811.35
    SACND9.131.053.9322.442.436.130.730.881.18
    AMPSA26.0455.7440.4526.1641.1211.3335.1317.3754.9260.66
    TFMSA3.099.198.036.2610.216.266.944.063.483.76
    BPSND1.161.051.145.356.124.461.314.231.36
    ƩPMOCs264.13460.79463.05357.82602.55824.11673.99356.76670.65377.21
      注:ND表示未检出。
    化合物H01H02H03H04H05H06H07H08H09H10
    BDMA11.1924.7471.3131.7860.3877.0328.3238.0852.4135.06
    DTG0.951.521.273.1313.4024.8049.033.854.849.29
    TCPP19.27222.6011.8221.1277.1343.6670.5220.4430.5120.53
    DPG2.043.4647.208.1835.0914.0722.0622.9294.9329.86
    AMANT4.3611.6314.159.72140.59218.10171.7824.6469.3613.86
    BETMA8.0719.189.483.8414.7854.5787.632.28159.8031.46
    CAP73.8814.3389.86141.1443.8038.7653.7146.2160.4173.35
    MTSC17.8910.286.514.7811.599.9523.3711.085.482.54
    PEA4.449.848.937.1611.816.837.484.864.053.69
    MBSA16.1919.5563.2029.954.0416.7625.1089.7363.4951.13
    MS2.0839.4232.0233.9613.879.1924.2340.8848.6918.46
    ACE61.976.4651.6118.3386.07241.1620.5024.686.899.67
    XSA12.672.565.117.2410.8843.0937.603.646.2811.35
    SACND9.131.053.9322.442.436.130.730.881.18
    AMPSA26.0455.7440.4526.1641.1211.3335.1317.3754.9260.66
    TFMSA3.099.198.036.2610.216.266.944.063.483.76
    BPSND1.161.051.145.356.124.461.314.231.36
    ƩPMOCs264.13460.79463.05357.82602.55824.11673.99356.76670.65377.21
      注:ND表示未检出。
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出版历程
  • 收稿日期:  2023-01-17
  • 录用日期:  2023-04-04
  • 刊出日期:  2023-05-10
高欲乾, 郭敏丽, 梁存珍, 关东, 刘鹏. 水体中17种持久性和可迁移有机污染物的检测[J]. 环境工程学报, 2023, 17(5): 1736-1746. doi: 10.12030/j.cjee.202301066
引用本文: 高欲乾, 郭敏丽, 梁存珍, 关东, 刘鹏. 水体中17种持久性和可迁移有机污染物的检测[J]. 环境工程学报, 2023, 17(5): 1736-1746. doi: 10.12030/j.cjee.202301066
GAO Yuqian, GUO Minli, LIANG Cunzhen, GUAN Dong, LIU Peng. Determination of 17 persistent and mobile organic contaminants (PMOCs) in water[J]. Chinese Journal of Environmental Engineering, 2023, 17(5): 1736-1746. doi: 10.12030/j.cjee.202301066
Citation: GAO Yuqian, GUO Minli, LIANG Cunzhen, GUAN Dong, LIU Peng. Determination of 17 persistent and mobile organic contaminants (PMOCs) in water[J]. Chinese Journal of Environmental Engineering, 2023, 17(5): 1736-1746. doi: 10.12030/j.cjee.202301066

水体中17种持久性和可迁移有机污染物的检测

    通讯作者: 梁存珍(1973—),男,博士,副教授,liangcunzhen@bipt.edu.cn
    作者简介: 高欲乾 (1998—) ,男,硕士研究生,1073306604@qq.com
  • 1. 北京石油化工学院环境工程系,北京 102617
  • 2. 北京市水科学技术研究院,北京 100048
  • 3. 北京市怀柔区水务局,北京 101400
基金项目:
第三次新疆综合科学考察资助项目 (2021xjkk1400)

摘要: 持久性和移动性有机污染物 (persistent and mobile organic contaminants, PMOCs) 在环境中降解缓慢,并且可以通过水体循环进行迁移。由于缺乏水体中PMOCs的高效富集和准确测定方法,导致关于PMOCs在水体中存在水平的可靠监测数据较少。通过优化固相萃取条件和高效液相色谱-串联质谱参数,建立了同时检测水中17种PMOCs的分析方法。采用HLB固相萃取柱对水样中的PMOCs进行富集,乙腈和含10 mmol·L−1乙酸铵的水溶液作为流动相进行梯度洗脱,PMOCs检出限为0.04~0.35 ng·L−1,定量限为0.13~1.16 ng·L−1,回收率为65.01%~98.65%。在北京潮白河、广东北江和河北滹沱河进行布点采样,并测定其PMOCs的质量浓度。实验结果表明:17种PMOCs在潮白河、北江和滹沱河中均有检出,其ƩPMOCs平均质量浓度分别为604.69、740.45和505.11 ng·L−1。潮白河地表水中安赛蜜、金刚烷胺和己内酰胺的质量浓度相对较高,分别高达261.75、143.84和153.71 ng·L−1。北江中安赛蜜、磷酸三 (2-氯丙基) 酯和己内酰胺的质量浓度相对较高,分别高达433.14、444.46和108.76 ng·L−1。滹沱河中金刚烷胺、己内酰胺和磷酸三 (2-氯丙基) 酯的质量浓度较高,分别高达218.10、101.14和222.60 ng·L−1。本研究结果可为地表水和地下水水体中PMOCs的检测评价提供参考。

English Abstract

  • 持久性和可迁移有机污染物 (persistent and mobile organic contaminants, PMOCs) 是一类人工合成的高极性有机污染物,具有在环境中降解缓慢,在水中有持久性和可迁移性的特点[1]。随着食品制造业、制药业和化工业的快速发展,越来越多的PMOCs随着生活污水和工业废水的排放进入天然水体[2]。目前,监管措施多集中在多氯联苯[3]、有机氯农药[4]这类具有环境持久性 (半衰期长达数年) 、迁移性、生物蓄积性、毒性的有机污染物 (persistent,bioaccumulative and toxic contaminants, PBT) [5],但其在水循环中迁移性较弱,趋向于在生物相和沉积物中会沉积或积聚[6]。PMOCs不仅具有PBT环境持久性的特点,还不容易吸附到土壤和沉积物的表面,在水循环中有很强的扩散能力,会影响到地表水和地下水水质,并最终威胁到饮用水源安全[7]

    目前,气相色谱-质谱联用法 (GC-MS) [8-9]和液相色谱-质谱联用法 (LC-MS) [10-11]是检测PMOCs的主要方法。其中,高效液相色谱-串联质谱技术 (HPLC-MS /MS) 凭借高灵敏度和高选择性的优势在检测极性有机物中更为常用。基于相关文献,本研究选择了17种极性高、环境排放潜力大、难降解的PMOCs作为研究对象,包括人工甜味剂、医药中间体、化工助剂等[12-13]。本研究对固相萃取条件和HPLC-MS/MS 参数进行优化,建立同时测定17种PMOCs的分析方法。在北京潮白河、广东北江和河北滹沱河进行布点采样,测定不同地区水样中的PMOCs的存在水平,旨在为我国水环境中新污染物的监管提供数据支撑。

    • 本研究共购买17种PMOCs标准品,2种人工甜味剂包括安赛蜜 (ACE) 和糖精 (SAC);5种医药中间体包括金刚烷胺 (AMANT)、4-甲基氨基硫脲 (MTSC)、N-氨乙基哌嗪 (PEA)、三氟甲烷磺酸 (TFMSA)、硫酸钾酯钠 (MS);10种化工助剂包括1,3-二邻甲苯基胍 (DTG)、二苯胍 (DPG)、苄基三甲基氯化铵 (BETMA)、己内酰胺 (CAP) 、N,N-二甲基苄胺 (BDMA) 、磷酸三 (2-氯丙基) 酯 (TCPP)、对甲苯黄酰胺 (MBSA) 、二甲苯磺酸钠 (XSA)、2-丙烯酰胺基-2-甲基丙磺酸盐 (AMPSA)、双酚S (BPS)。17种PMOCs标准品 (纯度>99%)、HPLC级甲醇、乙腈、甲酸、乙酸铵和0.45 μm玻璃纤维滤膜购自上海安谱公司,Oasis HLB、Oasis MCX和Envi-18固相萃取柱分别购自美国Waters公司和Supelco公司。用甲醇配制含有待测PMOCs 2 000 mg·L−1的单标储备溶液和混标储备液,根据需要进一步配制使用液。

    • 依据《地表水和污水监测技术规范》 (HJ/T 91—2002) [14]和《地下水环境监测技术规范》 (HJ 164-2020) [15]分别于2022年4月 (春季,平水期) 、2022年9月 (秋季,丰水期) 采集北京市潮白河地表水和地下水,地表水样品S1和S2取自潮白河上游,S3、S4和S5取自潮白河下游,采集深度为0~1 m;地下水样品1#和2#位于一期工程间歇受水区,3#、4#和5#位于一期工程常年受水区,采集深度为30 m。2022年4月,采集广东北江韶关至佛山段10个地表水样品,采集深度为0~1 m。2022年10月,采集河北滹沱河正定至无极段10个地表水样品,采集深度为0~1 m。每个样点采集水样3 L。

      水样采用SPE处理,具体流程为:用0.45 μm玻璃纤维滤膜过滤2 L水样,分别用5 mL乙腈、甲醇和超纯水活化固相萃取柱,2 L水样通过固相萃取柱富集,用10 mL的乙腈对固相萃取柱中的目标物进行洗脱处理,收集洗脱液,用无水硫酸钠脱水后经过旋转蒸发仪和氮吹仪浓缩至0.5 mL待测[16]

    • 高效液相色谱柱 (Inert Suatain C18 column,150 mm×4.6 mm,5 μm) ,进样体积10 μL,柱温40 ℃,用乙腈和含10 mmol·L−1乙酸铵的水溶液作为流动相进行梯度洗脱,0~9 min乙腈由40%升至80%,9~12 min乙腈由80%降至40%,12~15 min保持乙腈为40%平衡3 min,选用电喷雾离子源 (ESI) 和多反应监测模式 (MRM) ,雾化气和干燥器流速分别为3和15 L·min−1,去溶剂温度和加热区温度分别为250 ℃和400 ℃,17种PMOCs的质谱参数如表1 所示。

    • 在实验过程中利用超纯水进行空白基质加标实验 (混合溶液的浓度梯度为0、10、30、80、150、300 ng·L−1) ,基于加标回收率和5个平行样的相对标准偏差验证固相萃取前处理方法可靠性。方法检出限( LODs)和方法定量限( LOQs)分别以3倍信噪比 (S /N = 3) 和10倍信噪比 (S /N= 10) 进行计算。每批次样品均分析试剂空白;每分析一批样品至少做1个空白进行校正;仪器每12小时做1次溶剂空白,检查仪器的污染状况。

    • 实验优化了流动相水、甲醇和乙腈的组成和比例,BETMA和CAP的响应强度在甲醇-水体系下比乙腈-水体系高28.46%和8.58%,其余的15种PMOCs在乙腈-水体系下响应强度增大18.94%~76.84%,选择乙腈-水体系作为流动相。60%、70%、80%乙腈-水等度洗脱和经过反复优化的梯度洗脱结果如图1所示, 17种PMOCs在梯度洗脱条件下的响应强度最高。HPLC-MS/MS在正离子模式下,加甲酸可以提高其响应强度[17],而在负离子模式下加乙酸铵可以提高其响应强度[18]。实验研究了含10 mmol·L−1甲酸和10 mmol·L−1乙酸铵的水溶液作为无机相分别进行梯度洗脱的效果,实验结果如图2所示,发现含10 mmol·L−1甲酸的水溶液做无机相,正离子模式下的PMOCs响应强度提高了20.04%~53.37%,负离子模式下的PMOCs相应强度降低了6.97%~33.17%。采用含10 mmol·L−1乙酸铵的水溶液作为无机相,负离子模式下的PMOCs响应强度提高12.36%~259.64%,特别是响应强度较低的MBSA、XSA、SAC和AMPSA,增加10 mmol·L−1乙酸铵后,其响应强度提高了94.39%~259.27%。正离子模式下的4种PMOCs响应强度只降低8.77%~23.29%,因此,有机相选择乙腈,无机相选择含10 mmol·L−1乙酸铵的水溶液作为流动相进行检测。

    • 常用的固相萃取柱有Oasis WCX、Oasis HLB、Oasis MCX、Envi-18等[19]。HLB柱含有特定比例的亲水基和疏水基,使其适合提取多种极性的分析物[20]。MCX具有反相和阳离子交换双重保留性能,对碱性化合物有良好的保留能力[21]。Envi-18含碳量大于17%,是一种较为通用的固相萃取柱。比较了Envi-18、MCX和HLB对PMOCs的富集效果。3种固相萃取柱的富集效果如图3所示,HLB柱、MCX柱和Envi-18柱对PMOCs的萃取的回收率分别为76.14%~98.65%、45.03%~85.31%和41.69%~75.92%,故实验中水样固相萃取选择HLB柱。

    • 方法回收率、相对标准偏差 (RSD) 、相关系数R2、检出限 (LODs,S/N=3) 和定量限 (LOQs,S/N=10) ,结果如表2所示:17种PMOCs相关系数均大于0.99,方法检出限为0.04~0.35 ng·L−1,定量限为0.13~1.16 ng·L−1,回收率为65.01%~98.65%,RSD为3.6%~8.9%。MONTES等[22]采用混合模式固相萃取法-液相色谱-串联质谱法检测了西班牙地表水中23种PMOCs,该方法的检出限为0.02~18 ng·L−1,定量限为0.1~60 ng·L−1,回收率为60%~107%。干志伟等[23]采用固相萃取-液相色谱-串联质谱法同时测定水中7种人工甜味剂,该方法定量限为0.1~6 ng·L−1,回收率为82.4%~93.5%。上述方法的回收率与定量限与本研究方法相近。

    • 1) 北京潮白河地表水和地下水中PMOCs的检测。潮白河平水期和丰水期水样中PMOCs的检测结果如表3表4所示,17种PMOCs在地下水和地表水中均有检出,地表水质量浓度范围为ND~261.75 ng·L−1,地下水质量浓度范围为ND~109.69 ng·L−1。地表水中安赛蜜 (ACE) 、金刚烷胺 (AMANT) 和己内酰胺 (CAP) 的质量浓度相对较高,分别为59.78~261.75、13.37~143.84和36.56~153.71 ng·L−1。地下水中安赛蜜 (ACE)、金刚烷胺 (AMANT) 和磷酸三 (2-氯丙基) 酯 (TCPP) 的质量浓度相对较高,分别为25.61~168.11、22.41~70.58和10.61~109.69 ng·L−1。ACE是常用的人工甜味剂,广泛应用于食品、药物和个人护理品。ACE在污水处理厂中去除效果差,并且在环境中难以被吸附或降解[24-25]。AMANT是一种抗病毒药物,可直接或间接引起生物体神经损伤[26]。AMANT由于价格低廉,大量用于养殖业,在生物体中多以原药形式排入外界环境,对环境中的动植物等产生一定的影响[27]。CAP在化工领域的应用极为广泛,因其具有良好的水溶性且具有毒性,中国、美国、欧盟等均将其列入常规监测和优先监测的污染物名单[28]。TCPP作为增塑剂和阻燃剂在聚氨酯泡沫、PVC、纺织品中使用,相关研究表明TCPP具有神经毒性、内分泌干扰性、基因突变性和致癌等多种危害[29]

      17种PMOCs的时空分布如图4所示,2022年4月地表水ƩPMOCs的质量浓度范围为682.91~1 231.76 ng·L−1,地下水ƩPMOCs的质量浓度范围为446.49~641.91 ng·L−1;2020年9月地表水ƩPMOCs的质量浓度范围为522.95~895.02 ng·L−1,地下水ƩPMOCs的质量浓度范围为311.12~471.99 ng·L−1。PMOCs在地表水中的质量浓度高于地下水中的浓度,这可能是污染物在向地下水迁移的过程中,由于土壤的吸附作用、微生物的生物降解以及污染物在地下水中产生的弥散作用导致地下水中PMOCs的质量浓度减少[30-31] 。潮白河地表水上游S1样点PMOCs质量浓度明显高于地表水其它采样点。5个地下水样点中PMOCs质量浓度相差没有地表水明显,3#样点在减河和潮白河交汇处下游,减河补水稀释作用可能导致此点PMOCs质量浓度低于其它几个样点,4号和5号样点上游存在俸伯桥和彩虹桥排污口,可能导致PMOCs质量浓度有所上升。地表水和地下水在4月份 (平水期) 的PMOCs质量浓度高于9月份 (丰水期) 的PMOCs质量浓度。北京属于典型的暖温带半湿润半干旱季风气候,夏季高温多雨,冬季寒冷干燥,春、秋短促,9月份降水多于4月份,雨水稀释作用可能是9月份PMOCs质量浓度较低的原因。

      2) 广东北江地表水中PMOCs的检测。北江水样中PMOCs的检测结果见表5,17种PMOCs均有检出,其质量浓度范围为0.83~444.46 ng·L−1。ƩPMOCs质量浓度最高的采样点为 B01,其质量浓度为1 476.21 ng·L−1。北江中安赛蜜 (ACE) 、磷酸三 (2-氯丙基) 酯 (TCPP) 和己内酰胺 (CAP) 的质量浓度相对较高,分别为60.49~433.14、17.76~444.46和41.68~108.76 ng·L−1

      3) 河北滹沱河地表水中PMOCs的检测。河北滹沱河水样中PMOCs的检测结果见表6,17种PMOCs均有检出,其质量浓度范围为ND~218.10 ng·L−1。ƩPMOCs质量浓度最高的采样点为 H06,其质量浓度为824.11 ng·L−1。滹沱河中金刚烷胺 (AMANT) 、己内酰胺 (CAP) 和磷酸三 (2-氯丙基) 酯 (TCPP) 的质量浓度较高,分别为4.36~218.10、14.33~101.14和11.82~222.60 ng·L−1

      4) 国内外水体中PMOCs存在水平对比。17种PMOCs在潮白河、北江和滹沱河中均有检出,其ƩPMOCs平均质量浓度分别为604.69、740.45和505.11 ng·L−1,北江ƩPMOCs平均质量浓度高于潮白河和滹沱河,其原因可能是北江流域有许多的化工生产企业,而潮白河和滹沱河属于生态涵养区,PMOCs排放源较少。虽然国内关于水体中PMOCs作为一大类物质进行检测还没有相关的文献报道,但是部分研究人员对水体中一些属于PMOCs的物质进行了检测。

      桂建业等[24]采用离子色谱-串联质谱法在石家庄地表水中检测到安赛蜜 (ACE) 的质量浓度为32.2~955.1 ng·L−1,地下水中的质量浓度为5.9~92.5 ng·L−1。JIN等[32]采用超高效液相色谱-串联质谱法在太湖、辽河和浑河检测的双酚S (BPS) 质量浓度分别为0.28~37、0.22~52和0.61~46 ng·L−1。李栋等[33]采用液相色谱-质谱联用法在长江南京段水源水中检测到磷酸三 (2-氯丙基) 酯 (TCPP) 的质量浓度为6.02~318.23 ng·L−1。上述三种PMOCs检出质量浓度与本研究水体浓度相近。

      水体中PMOCs污染现状系统性的研究主要集中在欧洲。BUERGE等[34] 采用固相萃取法-液相色谱-串联质谱联用法检测到瑞士地表水中ACE质量浓度高达4 700 ng·L−1,地下水中ACE质量浓度为20~2 600 ng·L−1。MONTES等[22]采用混合模式固相萃取法-液相色谱-串联质谱法检测了西班牙地表水中PMOCs,其中糖精 (SAC) 质量浓度为77~7 707 ng·L−1,二甲苯磺酸钠 (XSA) 质量浓度为11~1 767 ng·L−1。SCHULZ等[35] 采用混合模式液相色谱-质谱联用法在德国、西班牙和荷兰各类水体中检出了43种典型PMOCs, 其中苄基三甲基氯化铵 (BETMA) 质量浓度高达400 ng·L−1。潮白河、北江和滹沱河地表水中SAC质量浓度分别为9.60~63.71、4.54~31.70和ND~22.44 ng·L−1,XSA质量浓度分别为14.29~79.45、20.93~130.85和3.64~43.09 ng·L−1,BETMA质量浓度分别为18.15~62.59、 23.99~79.06和2.28~159.80 ng·L−1。欧洲水体中ACE、SAC,XSA和BETMA质量浓度明显高于本研究水体中的浓度,其余PMOCs质量浓度与本研究结果相近。

    • 1) 采用HLB固相萃取柱对水样中17种PMOCs进行固相萃取,用乙腈和含10 mmol·L−1乙酸铵的水溶液作为流动相,该方法的准确度和精密度均可满足水体中PMOCs的检测分析要求,17种PMOCs的方法检出限为0.04~0.35 ng·L−1,定量限为0.13~1.16 ng·L−1,回收率为65.01%~98.65%。

      2) 17种PMOCs在潮白河、北江和滹沱河中均有检出,其ƩPMOCs平均质量浓度分别为604.69、740.45和505.11 ng·L−1,北江PMOCs的质量浓度高于潮白河和滹沱河。北京潮白河地表水中ACE、AMANT和CAP的质量浓度相对较高。广东北江中ACE、TCPP和CAP的质量浓度相对较高。石家庄滹沱河中AMANT、CAP和TCPP的质量浓度较高。北京潮白河地表水中PMOCs的质量浓度高于地下水中的质量浓度,地表水和地下水在平水期的PMOCs质量浓度高于丰水期的质量浓度。

    参考文献 (35)

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