多环芳烃物理化学性质的确定及其在逸度模型和上海典型环境研究中的应用
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摘要
多环芳烃(polycyclic aromatic hydrocarbons, PAHs)因在环境中持久、广泛存在且具有明确致癌性而备受关注,相关研究很多。研究理论多基于其物理化学(或物化)性质,因此,欲探讨PAHs各种环境行为及归趋,特别是利用模型进行相关研究,准确、无偏且有热力学一致性的物化性质是基本、首要前提。然而,由于存在实验室内、实验室间和不同仪器、不同方法间的误差等因素,已发表的物化性质数据存在小分子量PAHs物化性质参数多但存在差异、大分子量PAHs相关参数较少甚至缺乏的问题。因此,论文从研究16种优先控制PAHs的物化性质参数出发,开展以下方面研究工作:
所研究的物化性质有:熔点Tm、熔解熵△Sfus、水溶解度SW、饱和蒸气压PL、辛醇-水分配系数KOW、辛醇-空气分配系数KOA以及空气-水分配系数KAW等。首先通过查阅大量文献,对实验数据进行判断和筛选,剔除偏离较多的、实验方法有误差的及超出环境温度范围过多的数据,汇编整理后统一为标准单位和液态下的性质,经线性回归或平均计算,得出298.15 K下文献获得值LDVs(literature derived values)。16种PAHs的物化性质显示出随分子量变化而递增或递减的线性规律,R2值均达到0.9以上。为使LDVs参数间达到热力学一致性并减小误差,引入最小方差调整程序,计算出的调整百分比呈随机分布,表明了LDVs的无偏性。调整后得到的FAVs(final adjusted values)可为随后PAHs的相关研究提供基础数据,还可做为关键输入参数应用于PAHs相关环境模型中,以提高模型研究的科学性、准确性和可比性。同时发现由于logKOW测定实验中存在水饱和辛醇相和辛醇饱和水相以及纯水相和纯辛醇相间分配的差异而产生的热力学偏差,根据三个分配系数LDVs线性关系先对logKOW(LDVs)进行修正,再进行最小方差调整计算,调整百分比减小且随机性更趋明显,这一修正使FAVs具有更好的热力学一致性和无偏性。
为判断模型计算的准确性,选取四种定量结构预测模型(QSPR):EPIWIN, SPARC online, COSMOtherm,pp-LFER,对各自计算出的PAHs物化性质进行最小方差调整,并以FAVs为参照进行比较分析,发现模型预测PAHs物化性质的精确性和热力学一致性比较好,但与FAVs存在不同程度偏差,准确性稍差;同时最小方差调整结果显示某些性质在正或负方向上规律偏差,表明模型计算存在一定的系统偏差。研究得出模型应用中需注意:①好的热力学一致性和线性回归不能代表一个QSPR模型的准确性;②模型计算结果与实验数据间相互检验是非常必要且有互相促进作用。
为验证物化性质对PAHs环境行为的影响,分别进行实验和模型验证,研究PAHs在上海典型环境中大气、土壤、植物叶片中及在Level III逸度模型中的分布和预测,对PAHs环境行为进行推断并分析物化性质的影响性。
大气PM10采样分析结果显示,2005～2006年上海某工业区PM10中PAHs平均浓度为132±83 ng/m3,焦化厂周边PM10中PAHs浓度高于其它采样点,显示出一定的行业特征,对照点浓度远低于工业区;环数分布规律相似,均以3,4,5环为主,2,6环较少;季节性变化呈现出秋冬高、春夏低的趋势,环数分布也有相应变化,体现了物化性质是温度函数的特性。表明除环境等因素影响外,PAHs的物化性质决定了其在环境中的分配行为和归趋。同时采用BaPE进行风险评估结果显示:工业区PM10的BaPE值明显高于其它采样点位。上海多个点位表层土壤中PAHs分析结果显示,工业区土壤的总PAHs浓度最高(焦化厂、氯碱厂、电厂分别为3258, 1873和994 ng/g),其次为徐家汇交通主干道和南京路(196和166 ng/g),对照点淀山湖的含量最低(10.7 ng/g)。温度影响结果显示:冬季PAHs检出浓度普遍高于夏季,冬季以2、3、4环PAHs为主,夏季则以3、4、5为主。温度对不同环数PAHs介质分配的影响与其饱和蒸气压有关。
采用特征比值法对上海环境数据进行的源分析结果显示:选定的工业区域大气PM10中PAHs污染主要来自工业排放,其次为交通和扬尘污染,总体表现为混合污染;表层土壤分析结果为煤炭燃烧和交通排放混合污染。对焦化厂炼焦路炉顶无组织排放废气中PM10特征比值法分析发现:焦化炉顶PM10计算结果与文献中工业排放和焦炉燃烧PM10结果非常接近。
为探明气态PAHs分配行为,选取四种上海常见植物(广玉兰、香樟、黄杨和法国梧桐)叶片,采集的相同外部环境下叶片分析结果表明:常绿树树叶对PAHs的富集能力随环境温度而变化,梧桐树叶内PAHs随叶片生长而一直增加,通常梧桐叶内PAHs浓度较常绿树叶内高,各自富集特征差异较大,这应为叶片特性和PAHs物化性质共同作用结果。对两种被动式采样技术SPMDs和XAD对大气中PAHs的富集研究发现,相同条件下XAD富集能力较SPMDs高出数倍,富集特征存在差异,这与采样器的物理特性及PAHs物化性质有关。
Level III逸度模型采用Beyer Environment中环境参数,输入论文所得16种PAHs的物化性质FAVs,结果显示:随分子量和苯环数增加,富集在土壤和沉积物中的PAHs浓度呈数量级增加,气相中则呈递减趋势;两相间迁移呈现规律性递增或递减变化,模型计算结果显示出低于上海实测结果的趋势;根据上海实测结果,对Beyer环境参数中大气和土壤输入量微调后两者差异有所减小。证实了Level III模型对区域有机物环境行为预测的指导意义。
Polycyclic aromatic hydrocarbons (PAHs) are well know persistent organic pollutants (POPs) and widely investigated by researchers around the world due to their notable carcinogenic, mutagenecity properties and persistency. The basic and key element of all these research work is their physical-chemical properties. So a set of recommended physical-chemical properties, with accurate and themodynamic consistency, is necessary. The thesis began with this topic and the following works were carried out as described below.
A complete set of thermodynamically consistent property data (vapor pressure, aqueous solubility, octanol solubility, octanol-water partition coefficient, octanol-air partition coefficient, and air-water partition coefficient) for sixteen PAHs (naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, indeno[1,2,3-c,d]pyrene, dibenzo(a,h)anthracene and benzo[g,h,i]perylene) was derived from measured data reported in the literature. First, literature derived values (LDVs) at 25°C for each property of 16 PAHs were obtained by averaging, regressing and extrapolating after changed to standard units and liquid state. Then the LDVs were adjusted to conform the thermodynamic relationships by a least square adjustment procedure. The influence of the mutual solubility of octanol and water on phase partitioning is taken into account in the adjustment of the KOW. Compared to other semi-volatile organic compounds, the LDVs for the PAHs display a high degree of thermodynamic consistency and require only minor adjustments. The LDVs and the adjusted values for all properties show highly linear regressions with molecular mass (R2 > 0.9). The final adjusted values (FAVs) were recommended for further research work related to PAHs.
In order to compare and assess the accuracy of result calculated by models, four popular quantitative structure-property relationship (QSPR) models were employed: SPARC online, EPIWIN, COSMOtherm and pp-LFER. There has none relative report about the accuracy of each model for predicting the properties of PAHs before though it is essential for further use. We defined the FAVs as criteria to judge the accurate of results from models. Discrepancy was found for every model despite of their precision and thermo-consistency. The comparison showed that the experimental data, adjustment procedure and thermodynamic consistency are all valuable factors in evaluating a QSPR method. The results showed that good precision and thermo-consistency cannot represent the accuracy of a model. The accuracy of xperimental data and result from model can test each other.
In order to verify the influence of properties on behavior and fate of 16 PAHs, environmental sample and a fugacity model were employed. The environmental fate of 16 PAHs were investigated by selecting air, soil and leaves samples in several typical function districts in Shanghai and in Level III model. The results showed that the average concentration of 16 PAHs in PM10 were 132±83 ng/m3 in two years. Samples from Cocking Chemical Plant had the highest PM10 concentration than others while samples from Dianshan lake are far lower than that from the industrial area. And 2,3,4-ring PAHs took predominant level in PM10 while 2,6-ring PAHs were seldom detected. In spit of the environmental factors, physical-chemical properties of compounds are the key point in determining their environmental fate. PAHs are obvious influenced by the change of temperature. Usually the higher PAHs concentrations in PM10 appeared in autumn to winter while the lower ones in spring to summer. This character also had intimate relationship with local weather as while as their physical chemical properties. And risk assessment of PM10 showed that BaPE were much higher in industrial district than rural area. Results from soil samples also showed that 16 PAHs in soil from industrial area (Cocking Chemical Plant,Chloro-alkaline Chemical Plant,Thermo Power Plant were 3258 ng/g, 1873 ng/g and 994 ng/g respectively) were higher than that from others, and the sample from Dianshan lake was still the lowest one (10.7 ng/g). At the same time, PAHs detected in winter were always higher than in summer. And the 2,3,4-ring PAHs took prevalent level in winter samples while 3,4,5-ring PAHs in summer samples. Six-ring PAHs had only less detected in soil samples. This distribution pattern was mainly determined by the vapor pressure of PAHs except for environmental factors.
Diagnositic ratio analysis showed that PAHs in PM10 mainly came from the industrial waste gas, followed by traffic discharge and dustfall of road. Diagnositic ratio result for soil samples illustrated that the coal burning and traffic were their mainly source. Analysis of PM10 sampled just aroud the funnel of CCP had almost identical results as the reported data in literatures.
Leaf samples from three evergreen species (southern magnolia, camphor tree, boxtree) and one deciduous species (phoenix tree) in Shanghai were sampled during 2005 to 2006. The results showed that there has big difference in accumulating capacity and tendency among these species. For the phoenix tree, the accumulation of PAHs increased with the growth of leaves till the leaves mature. PAHs in evergreen trees were variable with the change of temperature. Their accumulating capacities and tendencies were different among three evergreen species. Leaves from phoenix tree had higher capacity in intercepting and accumulating PAHs from air than evergreen species due to the character of leaf and properties of PAHs. Two passive sampler devices, SPMD and XAD, were employed to investigate their accumulating pattern and tendency of PAHs. The results showed that concentration of total 16 PAHs in XAD were 2 to 8 times than that in SPMD. This should be attributed to the character of SPMD and XAD and properties of PAHs.
A fugacity model– Level III model, invented by Prof. D. Mackay from Trent University, was employed to illustrate the fate of PAHs in environment and the function of their physical-chemical properties (FAVs). The results showed that the PAHs tended to be accumulated fast in organic phase with the increasing of molecular mass and benzene rings while decreased in gas phase. And the exchange between phases also increased or decreased regularly. Results from Level III model were lower than the experimental results in Shanghai. This discrepancy decreased after adjusted two input parameters of Beyer Environment. The comparison verified that Level III model can be used in predicating the fate of PAHs in some certain typical area. It can also be used in predicting the fate and tendency in environment for compounds with similar structure and molecular mass without related property data.
所研究的物化性质有:熔点Tm、熔解熵△Sfus、水溶解度SW、饱和蒸气压PL、辛醇-水分配系数KOW、辛醇-空气分配系数KOA以及空气-水分配系数KAW等。首先通过查阅大量文献,对实验数据进行判断和筛选,剔除偏离较多的、实验方法有误差的及超出环境温度范围过多的数据,汇编整理后统一为标准单位和液态下的性质,经线性回归或平均计算,得出298.15 K下文献获得值LDVs(literature derived values)。16种PAHs的物化性质显示出随分子量变化而递增或递减的线性规律,R2值均达到0.9以上。为使LDVs参数间达到热力学一致性并减小误差,引入最小方差调整程序,计算出的调整百分比呈随机分布,表明了LDVs的无偏性。调整后得到的FAVs(final adjusted values)可为随后PAHs的相关研究提供基础数据,还可做为关键输入参数应用于PAHs相关环境模型中,以提高模型研究的科学性、准确性和可比性。同时发现由于logKOW测定实验中存在水饱和辛醇相和辛醇饱和水相以及纯水相和纯辛醇相间分配的差异而产生的热力学偏差,根据三个分配系数LDVs线性关系先对logKOW(LDVs)进行修正,再进行最小方差调整计算,调整百分比减小且随机性更趋明显,这一修正使FAVs具有更好的热力学一致性和无偏性。
为判断模型计算的准确性,选取四种定量结构预测模型(QSPR):EPIWIN, SPARC online, COSMOtherm,pp-LFER,对各自计算出的PAHs物化性质进行最小方差调整,并以FAVs为参照进行比较分析,发现模型预测PAHs物化性质的精确性和热力学一致性比较好,但与FAVs存在不同程度偏差,准确性稍差;同时最小方差调整结果显示某些性质在正或负方向上规律偏差,表明模型计算存在一定的系统偏差。研究得出模型应用中需注意:①好的热力学一致性和线性回归不能代表一个QSPR模型的准确性;②模型计算结果与实验数据间相互检验是非常必要且有互相促进作用。
为验证物化性质对PAHs环境行为的影响,分别进行实验和模型验证,研究PAHs在上海典型环境中大气、土壤、植物叶片中及在Level III逸度模型中的分布和预测,对PAHs环境行为进行推断并分析物化性质的影响性。
大气PM10采样分析结果显示,2005～2006年上海某工业区PM10中PAHs平均浓度为132±83 ng/m3,焦化厂周边PM10中PAHs浓度高于其它采样点,显示出一定的行业特征,对照点浓度远低于工业区;环数分布规律相似,均以3,4,5环为主,2,6环较少;季节性变化呈现出秋冬高、春夏低的趋势,环数分布也有相应变化,体现了物化性质是温度函数的特性。表明除环境等因素影响外,PAHs的物化性质决定了其在环境中的分配行为和归趋。同时采用BaPE进行风险评估结果显示:工业区PM10的BaPE值明显高于其它采样点位。上海多个点位表层土壤中PAHs分析结果显示,工业区土壤的总PAHs浓度最高(焦化厂、氯碱厂、电厂分别为3258, 1873和994 ng/g),其次为徐家汇交通主干道和南京路(196和166 ng/g),对照点淀山湖的含量最低(10.7 ng/g)。温度影响结果显示:冬季PAHs检出浓度普遍高于夏季,冬季以2、3、4环PAHs为主,夏季则以3、4、5为主。温度对不同环数PAHs介质分配的影响与其饱和蒸气压有关。
采用特征比值法对上海环境数据进行的源分析结果显示:选定的工业区域大气PM10中PAHs污染主要来自工业排放,其次为交通和扬尘污染,总体表现为混合污染;表层土壤分析结果为煤炭燃烧和交通排放混合污染。对焦化厂炼焦路炉顶无组织排放废气中PM10特征比值法分析发现:焦化炉顶PM10计算结果与文献中工业排放和焦炉燃烧PM10结果非常接近。
为探明气态PAHs分配行为,选取四种上海常见植物(广玉兰、香樟、黄杨和法国梧桐)叶片,采集的相同外部环境下叶片分析结果表明:常绿树树叶对PAHs的富集能力随环境温度而变化,梧桐树叶内PAHs随叶片生长而一直增加,通常梧桐叶内PAHs浓度较常绿树叶内高,各自富集特征差异较大,这应为叶片特性和PAHs物化性质共同作用结果。对两种被动式采样技术SPMDs和XAD对大气中PAHs的富集研究发现,相同条件下XAD富集能力较SPMDs高出数倍,富集特征存在差异,这与采样器的物理特性及PAHs物化性质有关。
Level III逸度模型采用Beyer Environment中环境参数,输入论文所得16种PAHs的物化性质FAVs,结果显示:随分子量和苯环数增加,富集在土壤和沉积物中的PAHs浓度呈数量级增加,气相中则呈递减趋势;两相间迁移呈现规律性递增或递减变化,模型计算结果显示出低于上海实测结果的趋势;根据上海实测结果,对Beyer环境参数中大气和土壤输入量微调后两者差异有所减小。证实了Level III模型对区域有机物环境行为预测的指导意义。
Polycyclic aromatic hydrocarbons (PAHs) are well know persistent organic pollutants (POPs) and widely investigated by researchers around the world due to their notable carcinogenic, mutagenecity properties and persistency. The basic and key element of all these research work is their physical-chemical properties. So a set of recommended physical-chemical properties, with accurate and themodynamic consistency, is necessary. The thesis began with this topic and the following works were carried out as described below.
A complete set of thermodynamically consistent property data (vapor pressure, aqueous solubility, octanol solubility, octanol-water partition coefficient, octanol-air partition coefficient, and air-water partition coefficient) for sixteen PAHs (naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, indeno[1,2,3-c,d]pyrene, dibenzo(a,h)anthracene and benzo[g,h,i]perylene) was derived from measured data reported in the literature. First, literature derived values (LDVs) at 25°C for each property of 16 PAHs were obtained by averaging, regressing and extrapolating after changed to standard units and liquid state. Then the LDVs were adjusted to conform the thermodynamic relationships by a least square adjustment procedure. The influence of the mutual solubility of octanol and water on phase partitioning is taken into account in the adjustment of the KOW. Compared to other semi-volatile organic compounds, the LDVs for the PAHs display a high degree of thermodynamic consistency and require only minor adjustments. The LDVs and the adjusted values for all properties show highly linear regressions with molecular mass (R2 > 0.9). The final adjusted values (FAVs) were recommended for further research work related to PAHs.
In order to compare and assess the accuracy of result calculated by models, four popular quantitative structure-property relationship (QSPR) models were employed: SPARC online, EPIWIN, COSMOtherm and pp-LFER. There has none relative report about the accuracy of each model for predicting the properties of PAHs before though it is essential for further use. We defined the FAVs as criteria to judge the accurate of results from models. Discrepancy was found for every model despite of their precision and thermo-consistency. The comparison showed that the experimental data, adjustment procedure and thermodynamic consistency are all valuable factors in evaluating a QSPR method. The results showed that good precision and thermo-consistency cannot represent the accuracy of a model. The accuracy of xperimental data and result from model can test each other.
In order to verify the influence of properties on behavior and fate of 16 PAHs, environmental sample and a fugacity model were employed. The environmental fate of 16 PAHs were investigated by selecting air, soil and leaves samples in several typical function districts in Shanghai and in Level III model. The results showed that the average concentration of 16 PAHs in PM10 were 132±83 ng/m3 in two years. Samples from Cocking Chemical Plant had the highest PM10 concentration than others while samples from Dianshan lake are far lower than that from the industrial area. And 2,3,4-ring PAHs took predominant level in PM10 while 2,6-ring PAHs were seldom detected. In spit of the environmental factors, physical-chemical properties of compounds are the key point in determining their environmental fate. PAHs are obvious influenced by the change of temperature. Usually the higher PAHs concentrations in PM10 appeared in autumn to winter while the lower ones in spring to summer. This character also had intimate relationship with local weather as while as their physical chemical properties. And risk assessment of PM10 showed that BaPE were much higher in industrial district than rural area. Results from soil samples also showed that 16 PAHs in soil from industrial area (Cocking Chemical Plant,Chloro-alkaline Chemical Plant,Thermo Power Plant were 3258 ng/g, 1873 ng/g and 994 ng/g respectively) were higher than that from others, and the sample from Dianshan lake was still the lowest one (10.7 ng/g). At the same time, PAHs detected in winter were always higher than in summer. And the 2,3,4-ring PAHs took prevalent level in winter samples while 3,4,5-ring PAHs in summer samples. Six-ring PAHs had only less detected in soil samples. This distribution pattern was mainly determined by the vapor pressure of PAHs except for environmental factors.
Diagnositic ratio analysis showed that PAHs in PM10 mainly came from the industrial waste gas, followed by traffic discharge and dustfall of road. Diagnositic ratio result for soil samples illustrated that the coal burning and traffic were their mainly source. Analysis of PM10 sampled just aroud the funnel of CCP had almost identical results as the reported data in literatures.
Leaf samples from three evergreen species (southern magnolia, camphor tree, boxtree) and one deciduous species (phoenix tree) in Shanghai were sampled during 2005 to 2006. The results showed that there has big difference in accumulating capacity and tendency among these species. For the phoenix tree, the accumulation of PAHs increased with the growth of leaves till the leaves mature. PAHs in evergreen trees were variable with the change of temperature. Their accumulating capacities and tendencies were different among three evergreen species. Leaves from phoenix tree had higher capacity in intercepting and accumulating PAHs from air than evergreen species due to the character of leaf and properties of PAHs. Two passive sampler devices, SPMD and XAD, were employed to investigate their accumulating pattern and tendency of PAHs. The results showed that concentration of total 16 PAHs in XAD were 2 to 8 times than that in SPMD. This should be attributed to the character of SPMD and XAD and properties of PAHs.
A fugacity model– Level III model, invented by Prof. D. Mackay from Trent University, was employed to illustrate the fate of PAHs in environment and the function of their physical-chemical properties (FAVs). The results showed that the PAHs tended to be accumulated fast in organic phase with the increasing of molecular mass and benzene rings while decreased in gas phase. And the exchange between phases also increased or decreased regularly. Results from Level III model were lower than the experimental results in Shanghai. This discrepancy decreased after adjusted two input parameters of Beyer Environment. The comparison verified that Level III model can be used in predicating the fate of PAHs in some certain typical area. It can also be used in predicting the fate and tendency in environment for compounds with similar structure and molecular mass without related property data.
引文
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