聊城市冬季PM2.5中多环芳烃来源解析及健康风险评估

为研究聊城市冬季PM_(2. 5)中多环芳烃(PAHs)的浓度水平、来源及健康效应,于2017年1～2月对聊城市PM_(2. 5)中的14种PAHs进行分析,利用特征比值法和PCA-MLR模型对其来源及贡献率进行解析,并利用Ba P当量浓度(Ba Peq)和呼吸途径暴露PAHs引发癌症的风险(ILCR)模型进行健康风险评估.结果表明,聊城市冬季PM_(2. 5)中PAHs的平均质量浓度为(64. 89±48. 23) ng·m~(-3),其中Fla、Pyr和Chry的浓度最高,占比分别为15. 5%、12. 8%和12. 7%,且4环PAHs总质量浓度占比最高,春节前与烟火Ⅱ期比其他时期污染较重. PCA-MLR模型分析结果表明,聊城市冬季PM_(2. 5)中PAHs来源主要包括煤炭燃烧、生物质燃烧和机动车尾气.聊城市冬季TEQ平均值为(6. 37±4. 92) ng·m~(-3),ILCR模型评估结果表明,成人的ILCR值高于儿童,二者的ILCR值均处于风险阈值内(10-6～10-4),表明聊城市冬季PM_(2. 5)具有潜在致癌风险.     

我国焦化场地多环芳烃和重金属分布情况及生态风险评价

焦化是我国的重工行业,其生产过程中对生态环境造成的严重影响不容忽视.通过收集我国各个地区焦化行业场地的最新污染数据,试图从全国范围展开分析,反映我国焦化行业场地土壤的污染状况.运用质量基准法和毒性当量法对焦化土壤16种多环芳烃的生态风险进行了评价分析,运用地累积指数法和潜在生态风险评价法对8种重金属进行评价分析.结果表明,质量基准法计算我国各地区焦化场地土壤的M-ERM-Q值都大于1.51,为高生态风险,其中北方地区风险等级最高.根据荷兰土壤质量标准,毒性当量法表明,10种多环芳烃的总毒性当量均大于荷兰标准,其土壤呈现污染状态,且北方地区∑1oTEQ远大于荷兰标准,这与质量标准法的评估结果一致;地累积指数法得出Cd和Hg为焦化场地主要污染物,其余元素危害相对较小.潜在生态风险评价表明,各地区焦化场地污染较为严重,山西和河北地区焦化场地的重金属危害程度最为严重,达到重度污染水平.     

氯代烃污染场地生物自然衰减修复研究进展

随着监测自然衰减技术的不断发展和日趋成熟,其在氯代烃污染场地修复领域中的应用越来越广泛和深入。本文在简要回顾监测自然衰减技术来源和发展的基础上,围绕主导氯代烃去除的生物自然衰减过程,综合探究了影响监测自然衰减效率的污染物、生物和环境因素,概述了评估氯代烃污染场地自然衰减能力的实地监测和数值模拟手段,并基于室内模拟实验和场地实际应用现状,分析了其与强化衰减技术联合应用的发展趋势。今后需要在复合污染体系的自然衰减特征、生物降解调控机理研究、数值模拟及同位素分析等手段的应用等方面进一步深入研究,以期为氯代烃污染场地的绿色修复提供参考。     

Source apportionment of polycyclic aromatic hydrocarbons (PAHs) in a sediment core from Lake Dagze Co, Tibetan Plateau, China: Comparison of three receptor models

Receptor models are a useful tool for identifying sources of polycyclic aromatic hydrocarbons (PAHs) in multiple environmental media. In this study, three different receptor models (including the principal component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF), and Unmix models) were used to apportion the sources of 16 priority PAHs in a sediment core of Lake Dagze Co. The ∑PAHs (sum of all 16 measured PAHs) concentrations ranged from 51.89 to 132.82 ng/g with an average of 80.39 ng/g. The ∑PAHs were dominated by 2-3 ring PAHs, accounting for 80.12% on average, thereby indicating that they mainly originated from biomass and coal combustion and/or from long-range atmospheric transportation. The three models produced consistent source apportionment results. The greatest contributor to ∑PAHs was biomass combustion, followed by coal combustion, vehicle emissions, and petrogenic sources. Moreover, the temporal variation of the common sources was well-correlated among models. The multi-method comparison and evaluation results showed that all three models were useful tools for source apportionment of PAHs, with the PMF model providing better results than the PCA-MLR and Unmix models. The temporal trends of factor contributions were verified by PAHs with different ring numbers. Significant correlations were found between the simulated concentrations of each source factor and the PAHs with different ring numbers (P<0.01), except for the petrogenic source identified by the Unmix model (P>0.05). This study can provide useful information for further investigation of source apportionment of PAHs in the sediment cores.     

Toxic equivalency factor approach for risk assessment of polycyclic aromatic hydrocarbons

The toxic equivalency factor (TEF) method has been developed to evaluate structurally related compounds, sharing a common mechanism of action. Because certain polycyclic aromatic hydrocarbons (PAHs) appear to fit this requirement and are ubiquitous environmental contaminants, these compounds are TEF candidates. Toxicity is often expressed relative to benzo[a]pyrene (BaP), the reference standard (e.g., TEF = EC50_BaP/EC50_PAH). BaP‐like toxicity or toxic equivalents (TEQs) can then be calculated: TEQ = S(PAH _i × TEF _i ), where PAH _i and TEF _i are the concentration and TEF, respectively, for individual PAH congeners. Representative TEFs for PAHs were compiled from studies measuring carcinogenic potency and surrogate biomarkers. This review examines the application of TEFs to PAHs with established criteria (i.e., demonstrated need, defined chemical grouping, broad toxicological database, endpoint consistency, additivity, common mechanism of action, consensus). Although all criteria are not satisfied (e.g., endpoint inconsistency, nonadditivity) and more rigorous validation studies are needed, the TEF method is useful when limitations are recognized. Refinements of the method might include incorporation of pharmacokinetic factors and segregation of TEFs derived from mammalian vs. nonmammalian systems to increase endopoint consistency. Probabilistic analysis may also prove useful to assess the range of TEF values reported both within and between human health and ecological risk assessments.     

Enrichment and transfer of polycyclic aromatic hydrocarbons (PAHs) through dust aerosol generation from soil to the air

● Compositional patterns of PAHs in dust aerosol vary from soil during dust generation. ● The EF of PAH in dust aerosol is affected by soil texture and soil PAH concentration. ● The sizes of dust aerosol play an important role in the enrichment of HMW-PAHs. Polycyclic aromatic hydrocarbons (PAHs) are major organic pollutants in soil. It is known that they are released to the atmosphere by wind via dust aerosol generation. However, it remains unclear how these pollutants are transferred through the air/soil interface. In this study, dust aerosols were generated in the laboratory using soils (sandy loam and loam) with various physicochemical properties. The PAH concentrations of these soils and their generated dust aerosol were measured, showing that the enrichment factors (EFs) of PAHs were affected by soil texture, PAH contamination level, molecular weight of PAH species and aerosol sizes. The PAHs with higher EFs (6.24–123.35 in dust PM_2.5; 7.02–47.65 in dust PM₁₀) usually had high molecular weights with more than four aromatic rings. In addition, the positive correlation between EFs of PAHs and the total OC_aerosol content of dust aerosol in different particle sizes was also statistically significant (r = 0.440, P < 0.05). This work provides insights into the relationship between atmospheric PAHs and the contaminated soils and the transfer process of PAHs through the soil-air interface.     

居室玻璃表面有机质与多环芳烃分布规律研究

为探讨广州和香港市区玻璃表面薄膜上有机质和PAHs的分布特征,从2007年12月至2008年1月,利用低尘擦拭纸采集广州和香港室内外相对应的15对玻璃表面薄膜样品.结果表明,广州室内外有机质占表面薄膜重量的1.8%和1.1%,香港则分别为3.9%和1.6%.玻璃表面薄膜上Σ15PAHs浓度的最高值达到1430ng/m2,以菲,芴,荧蒽,芘等为主.室内外对比结果显示,主要以颗粒态形式存在的5~6环化合物室内外差别较大,广州室外比室内大约高1倍,而香港由于中央通风系统的过滤作用,其室外比室内高约5~10倍.根据有机质和PAHs浓度之间的相关性,认为室内外存在不同源强的有机质和PAHs来源,玻璃表面可能更有利于PAHs的光降解.     

淮河流域安徽段水系沉积物中多环芳烃的污染性状研究

应用气相色谱质谱联用仪测定淮河流域安徽段水系沉积物样品中萘、二氢苊、苊、芴、菲、蒽、荧蒽、芘、苯并[a]蒽、、苯并[a]芘和二苯并[a,h]蒽等12种多环芳烃的质量分数,并在此基础上分析沉积物中多环芳烃的区域分布、污染特征和来源。结果表明：研究区水系沉积物中多环芳烃有一定程度的富集,但与国内其他河流相比,样品中多环芳烃的质量分数不高;淮河南北岸支流沉积物中多环芳烃的含量差异比较明显,尤其是东淝河,含量明显低于淮北平原上的其它河流;淮河主干道和北岸支流沉积物中4环以上的多环芳烃含量较高,而南岸支流的淠河和东淝河沉积物中2～3环的多环芳烃平均含量明显高于其他环数;通过污染来源分析,沉积物中多环芳烃除与天然成岩过程有关外,大都是由有机物质的燃烧与热解引起的。     

红树林生态系统多环芳烃的污染研究进展

多环芳烃（PAHs）是一类广泛存在于天然环境中的持久性有机污染物,对生态环境和人类健康造成严重的潜在威胁。文章介绍了红树林生态系统PAHs污染的研究现状;总结了红树林生态系统PAHs的污染分布及其来源,以及PAHs污染胁迫对红树植物生长的影响;评述了红树植物对PAHs的直接吸收、红树林湿地微生物对PAHs的降解等研究;最后,对红树林生态系统PAHs污染的研究趋势进行了分析和展望,提出了今后可能的研究方向,主要包括：（1）综合应用多学科交叉研究典型PAHs在红树林生态系统中的环境行为;（2）结合双光子激光共焦扫描显微技术等原位研究手段,开展红树植物对典型PAHs的吸收、存赋形态、转运等相关研究;（3）结合激光诱导时间分辨荧光光谱测定系统,实现对现场红树林生态系统中PAHs等有机污染物的原位检测。     

山西晋中焦化基地多环芳烃排放对周边大田卷心菜的影响

饮食摄入是多环芳烃(PAHs)人体暴露的主要途径之一,探究PAHs污染对农产品安全和人体健康的影响具有重要意义。山西晋中拥有大型焦化企业,也是北方重要的大田蔬菜种植基地,当地PAHs污染的特征和影响具有相当的典型性。研究选取修文工业基地周边的大田蔬菜基地作为研究区域,分别采集大气(含气相和颗粒相)、菜地表土和卷心菜菜心样品,确定各类样品中母体PAHs的浓度水平、组成比例和分布特征。结果表明,蔬菜基地周边大气中母体PAHs的平均浓度为301 ng·m-3。大气母体PAHs主要存在于气相,低环(2~3环)组分占据优势。利用同分异构体特征比值和主成分分析对大气PAHs进行初步源解析,炼焦、燃煤和生物质燃烧、以及交通尾气排放是当地PAHs的主要排放源。菜地表土母体PAHs的中位数浓度为236ng·g-1,范围为130~703 ng·g-1,以中、高环(4~6环)组分为主,菜地表土母体PAHs浓度与土壤总有机碳(TOC)分数呈现显著正相关关系。当地大田种植卷心菜菜心的PAHs中位数浓度为12.9 ng·g-1,范围为0.9~47.6 ng·g-1,低环组分所占比例最大,其组分谱分布与大气相似。偏相关分析显示周边大气PAHs对卷心菜菜心PAHs的传输贡献要大于表土PAHs。