凝胶渗透色谱净化-高效液相色谱荧光法检测生肉中15种多环芳烃

目的建立生肉中欧盟优控15种多环芳烃的检测方法。方法采用装有Bio-Beads S-X3填料的凝胶渗透色谱净化分离柱(300mm×20mm),收集16～43min流出组分,在线浓缩近干,1mL乙腈复溶,采用PAH C18反相键合固定相色谱柱(250mm×4.6mm,5μm)分离,水和乙腈梯度洗脱,高效液相色谱荧光检测器检测。结果 15种多环芳烃在0.2～20.0ng/mL质量浓度范围内[苯并(j)荧蒽:0.5～20.0ng/mL]线性良好(r>0.998),该方法检出限为0.04～0.49μg/kg,定量限为0.12～1.51μg/kg。在生鱼肉、鸡肉、猪肉和牛肉4种基质中分别添加3个水平混合标准溶液(0.5、2.0、10.0μg/kg),平均回收率为61.0%～101.7%,相对标准偏差(RSD)为0.4%～11.5%(n=6)。结论该方法能同时检测生肉中欧盟优控的15种多环芳烃,满足定量分析要求。     

应用高效液相色谱法测定谷物中15种多环芳烃

目的使用高效液相色谱法测定谷物中15种多环芳烃。方法样品加入乙腈振荡、超声提取、离心,转移上清液用氮气吹干,用乙腈溶解残渣后,过0. 45μm微孔滤膜,以乙腈—水作为流动相梯度洗脱,以Waters-PHAs专用柱分离,通过荧光检测器检测其中多环芳烃。结果该方法线性关系良好,RSD 0. 80%～7. 22%,样品加标回收率90. 0%～110%。结论该方法前处理简单、准确、灵敏度高、重现性好、成本低,可以用于谷物中15种多环芳烃的检测。     

高效液相色谱法测定血清中的9种多环芳烃

目的建立固相萃取—高效液相色谱同时测定血清中蒽、荧蒽、芘、苯并[a]蒽、苯并[b]荧蒽、苯并[k]荧蒽、苯并[a]芘、苯并[a,h]蒽和苯并[g,h,i]芘9种多环芳烃的高效液相色谱测定方法。方法样品经过C18固相萃取小柱富集、净化,以甲醇洗脱后,采用Waters Symmetry C18色谱柱,以乙腈为流动相A,高纯水为流动相B梯度淋洗,流速为1.0 ml/min,荧光检测器测定,检测波长为Ex=340nm,Em=425nm。结果在给定浓度范围内各多环芳烃的峰面积与浓度具有良好的线性关系。其线性范围为0.10～3.00ng/ml;相关系数为0.9941～0.9999;回收率为87.1%～113.4%;相对标准偏差为2.56%～12.7%;检出限为0.05～0.10ng/ml。结论该方法可用于血清中9种多环芳烃的同时测定。     

超高效液相色谱法同时测定植物油中15种多环芳烃

目的建立采用超高效液相色谱(UPLC)-荧光检测器(FLR)同时快速检测植物油中15种多环芳烃的方法。方法采用乙腈∶丙酮(1∶1)混合溶剂提取,先后使用Waters的Oasis HLB和Sep-Pak Florsil小柱净化,Waters PAH C18色谱柱(4.6mm×50 mm,3μm)分离,甲醇、乙腈和水进行梯度洗脱,柱温35℃,流速0.80 ml/min,进样量10μl;荧光检测器采用程序定时控制荧光检测波长变化,外标法定量。结果 15种多环芳烃9 min内完全分离,在2.0~200.0μg/L范围内,峰面积和质量浓度的线性关系良好(r≥0.9990),以高、中、低浓度(10、50和100μg/kg)作为不同的添加水平,平均加标回收率为75.8%~96.4%,RSD为3.42%~8.03%(n=5),检出限为0.025~0.8μg/kg,定量限为0.08,3.0μg/kg。结论该方法操作方便、分离效果好、线性范围宽,能满足植物油中15种多环芳烃的检测要求。     

高效液相色谱法测定空气中的16种多环芳烃

摘要:目的　建立一种前处理简单、灵敏度高、重现性好的空气中16种多环芳烃的检测方法。方法　采用高效液相色谱法,Ultimate PAH（250 mm×4.6 mm,5 μm）液相色谱柱分离,乙腈-水为流动相进行梯度洗脱,紫外检测器,荧光检测器检测,紫外检测波长230 nm,荧光检测波长248～305 nm。结果　测定结果具有良好的线性（R＝0.9990～0.9999）,保留时间的RSD为0.007%～0.017%（n＝9）,峰面积的RSD为0.08%～2.41%（n＝9）,样品加标回收率为63.21%～102.92%,16种多环芳烃同时测定的检出限分别为:萘:0.040 μg/ml、芴:0.020 μg/ml、苊:0.032 μg/ml、菲:0.020 μg/ml、蒽:0.024 μg/ml、荧蒽:0.020 μg/ml、芘:0.032 μg/ml、苯并（a）蒽:0.032 μg/ml、屈:0.008 μg/ml、苯并（b）荧蒽:0.016 μg/ml、苯并（k）荧蒽:0.020 μg/ml、苯并（a）芘:0.008 μg/ml、二苯并（a,h）蒽:0.016 μg/ml、苯并（g,h,i）苝:0.032 μg/ml、茚苯（1,2,3-cd）芘:0.020 μg/ml、苊烯:0.020 μg/ml。结论　该方法具有操作简便、快速、重复性好、灵敏度高等优点,可用于测定空气中的多环芳烃。     

搅拌棒吸附萃取-高效液相色谱法测定红茶中15种多环芳烃

目的建立基于搅拌棒吸附萃取(SBSE)结合高效液相色谱-荧光检测(HPLC-FLD)测定红茶中15种多环芳烃的简便方法。方法研究甲醇和NaCl添加量、提取时间、解吸步骤以及基质效应对样品富集效率的影响,并在优化参数下将搅拌棒置于10 ml红茶样品中以750 r/min转速室温下提取120 min,萃取完成后以160μl乙腈-水解析后上机。结果在优化的实验条件下,15种多环芳烃在1 ng/L～1 200 ng/L浓度内呈良好线性关系,相关系数(r)> 0.998,检出限(S/N=3)为0.1 ng/L～8.7 ng/L,定量限为0.4 ng/L～27.5 ng/L,平均回收率在24.9%～88.7%。结论该方法简便、准确、环保、灵敏度高、选择性好,可满足红茶样品中多组分痕量多环芳烃的测定要求,为多环芳烃的残留分析提供了新的技术平台。     

多环芳烃分子印迹柱-高效液相色谱法快速测定大气细颗粒物中16种多环芳烃

目的 建立一种基于多环芳烃分子印迹柱净化的高效液相色谱法,用于快速定量检测大气细颗粒物中16种多环芳烃。方法 采用乙腈作为提取剂,超声辅助提取,提取液经多环芳烃分子印迹柱净化,氮吹浓缩过滤后测定。结果 16种多环芳烃在1～40 ng/mL范围内呈现良好的线性关系,相关系数r>0.9996;在5.0、10.0和20.0 ng/mL三个加标水平下,回收率为77.13%～107.67%,相对标准偏差为0.15%～4.63%(n=7);方法的检出限为0.004～0.084 ng/m³,定量限为0.016～0.336 ng/m³。结论 使用本方法检测细颗粒物中16种多环芳烃,比单纯超声辅助提取法及HJ 647—2013《环境空气和废气气相和颗粒物中多环芳烃的测定高效液相色谱法》中索氏提取法结果更加准确,灵敏度更高,耗时更短。     

高效液相色谱法同时测定大气PM2.5中15种欧盟优控多环芳烃

目的 采用高效液相色谱-荧光检测技术,建立大气细颗粒物（PM2.5）中15种欧盟优控多环芳烃（EU - PAHs）的同时测定方法。方法 利用超声波辅助乙腈提取PM2.5样品中的EU - PAHs,经0.45 μm滤膜过滤,用Waters PAH色谱柱分离,用乙腈 - 水作流动相梯度洗脱,荧光检测器检测,峰面积标准曲线法定量。结果 方法线性范围为 0.30～84 ng/m3,相关系数均大于0.999,方法精密度为4.6%～10.2%,回收率83.2%～95.6%。结论 该方法灵敏度高,准确度高,线性范围宽,适用于大气PM2.5中15种欧盟优控多环芳烃的同时检测。     

液相色谱-荧光检测器法测定人体血清中16种多环芳烃

目的 建立高灵敏度的超高效液相色谱串联荧光检测器检测人体血清中16种痕量多环芳烃的分析方法。方法 200μl血清样品,加入400μl正己烷,涡旋振荡后高速离心分离,取上层有机相,重复萃取2次,合并萃取液,氮吹至近干,再复溶于100μl乙腈中。经PAH C₁₈色谱柱(5μm, 4.6 mm×150 mm),在甲醇-水为流动相下梯度洗脱,超高效液相色谱串联荧光检测器测定。结果 血清中的16种多环芳烃在0.20μg/L～5.00μg/L浓度内呈良好的线性关系,线性相关系数均>0.998。该方法,检出限为0.1μg/L;加标回收率为60.5%～96.0%,RSD为1.5%～7.6%。结论 该方法操作简便、生物样本用量少、检出限低,适用于人群中多种多环芳烃的监测。     

Determination of polycyclic aromatic hydrocarbons in the lung

Polycyclie aromatic hydrocarbons (PAHs) accumulated in human lung samples from men (n = 236) and women (n = 128) were determined by high-performance liquid chromatography (HPLC) to examine their association with lung cancer. The mean values for benzo[a]pyrene (BaP), benzo[k]fluoranthene (BkF), and benzo[g,h,i]perylene (BghiP) in lungs (ng/g dry lung) of Japanese autopsied patients were 0.54, 0.44, and 0.87, respectively. The modal values were 0.3, 0.3 and 0.5, respectively. Each of the PAH concentrations was highly correlated with the others (r > 0.83). PAH concentrations in the lungs showed age-related increases with low correlation-coefficient values. BaP, BkF and BghiP concentrations in lungs of various subgroups were in the following order: male > female; and lung cancer > all cancers > non-cancer among male not female group. Only BghiP concentration in the lungs of the male smoker group is significantly higher (P < 0.10) than that of the male non-smoker group. Even among non-smoker groups, PAH concentrations in the lungs of male group were significantly higher than those of female group. In the male population, excess exposure to PAHs together with fine carbon particles, such as tobacco smoke or diesel exhaust, correlated with increased prevalence of lung cancer.     

重庆市某区小学女生多环芳烃内暴露水平及其与青春发动时相的关系

目的建立同时测定尿中4种多环芳烃(PAHs)代谢物的检测方法,研究重庆市某区女童青春发动时相提前与体内多环芳烃暴露水平的关系。方法研究对象采用目的性抽样,对重庆市某区4所小学1~4年级女生进行一般情况的问卷调查、生长发育的体格检查、并收集尿液,采用高效液相色谱-质谱联用法(HPLC-MS)对样品中4种PAHs代谢物进行定性和定量检测。结果 4种PAHs代谢物标准曲线相关性高,方法检出限为0.1 ng/mL。研究共调查女童737名,青春发动时相提前组209人,正常组528人。尿液检测结果显示4种PAHs代谢物检出率为100%,4种代谢物的检出浓度范围分别为1-羟基芘0.01~4.77 ng/mL,2-羟基萘0.15~50.00ng/mL,2-羟基芴0.06~12.59 ng/mL及9-羟基菲0.29~23.17 ng/mL。青春发动时相提前组和正常组在2-羟基芴(Z=-1.996)和9-羟基菲(Z=-3.161)暴露水平上差异具有统计学意义(P<0.05),控制了肥胖因素后,青春发动时相提前组9-羟基菲(Z=-3.012)暴露水平仍高于正常组(P<0.05)。结论该方法适用于4种PAHs代谢物的同时检测,研究地区女童青春发育早期均有PAHs暴露,且PAHs暴露可能是女童青春发动时相提前的因素之一。     

Determination of polycyclic aromatic hydrocarbons in aquatic products by HPLC-fluorescence

This paper analyzed 12 polycyclic aromatic hydrocarbons (PAHs), benzo[a]pyrene, benzo[b]fluoranthene, benzo[k]fluoranthene, dibenzo[a,h]anthracene, benzo[g,h,i]perylene, fluoranthene, anthracene, benzo[a]anthracene, chrysene, fluorene, phenanthrene and pyrene, in aquatic products by using a fluorimetric-detection RP-HPLC method. The preliminary treatment procedure was based on microwave-assisted extraction and neutral Al₂O₃ solid phase purification, and a selective isolation of PAHs from aquatic samples was carried out. The isolated fractions of PAHs were determined by HPLC with fluorescence detection. The test results suggest that the detection limits for the PAHs were from 0.0048 ng/mL to 0.075 ng/mL based on a signal-to-noise ratio of 3:1. The recoveries were from 85.26 ± 5.12% to 104.63 ± 0.95%. This proposed method was successfully applied to 35 aquatic samples, in which variable levels of summed PAHs were detected, ranging from 0.0 to 57.76 μg/kg.     

PM2.5中16种多环芳烃的液相色谱-二极管阵列检测器测定方法研究

目的建立PM2.5中16种多环芳烃同时测定的液相色谱-二极管阵列检测器(PDA)分析方法。方法PM2.5中多环芳烃收集于玻纤滤膜,经乙腈超声提取,以乙腈-水为流动相梯度洗脱,经多环芳烃专用色谱柱分离,PDA检测器进行测定。结果 PM2.5中16种多环芳烃化合物在0.1～2.0μg/mL浓度范围内线性关系良好,相关系数在0.999 2～0.999 8,样品加标回收率为73.3%～108.6%,RSD为3.7%～5.3%。结论方法能满足PM2.5中16种多环芳烃类化合物的同时测定,方法快速简单,准确度和重复性较好,线性范围宽。     

Determination of polycyclic aromatic hydrocarbons in industrial harbor sediments by GC-MS

Analysis of the 16 polycyclic aromatic hydrocarbons (PAHs) of the US Environmental Protection Agency priority pollutant list was carried out in sediment samples of an industrial port in the southern Kaohsiung Harbor of Taiwan which is supposed to be extensively polluted by industrial wastewater discharges. The determination and quantification of PAHs in sediment samples were performed using gas chromatography coupled to mass spectrometry (GC-MS) with the aid of deuterated PAH internal standards and surrogate standards. The total concentrations of the 16 PAHs varied from 4,425 to 51,261 ng/g dw, with a mean concentration of 13,196 ng/g dw. The PAHs concentration is relatively high in the river mouth region, and gradually diminishes toward the harbor region. Diagnostic ratios showed that the possible source of PAHs in the industrial port area could be coal combustion. As compared with the US Sediment Quality Guidelines (SQGs), the various observed levels of PAHs exceeded the effects range median (ERM), and could thus cause acute biological damages. The results can be used for regular monitoring, and future pollution prevention and management should target the various industries in this region for reducing pollution.