广州大学城珠江水域多环芳烃的污染特征

利用GC-MS对广州大学城珠江水域的地表水及表层沉积物中多环芳烃(PAHs)的含量进行了分析。结果表明,广州大学城珠江水域及表层沉积物中均可检出PAHs,水体优控PAHs总量在1061.7~6577.8ng/L之间,沉积物中优控PAHs总量分布在896.1~7248ng/g之间。广州大学城珠江水域的PAHs属混合来源,主要有石油类产品的输入(漏油泄油)和化石燃料的燃烧(大气沉降)。     

沈阳市大气PM2.5中多环芳烃的污染特征及来源解析

采用气相色谱-质谱联用仪定量分析2016年沈阳市PM_(2.5)中16种多环芳烃(PAHs)的质量浓度,探讨其时空分布特征,并解析PAHs的来源。结果表明:沈阳市PAHs的平均质量浓度为71. 5 ng/m3,其中3环、4环PAHs分别占31. 3%和48. 8%;采暖期PAHs浓度明显高于非采暖期,中心城区高于周边。总毒性当量浓度平均值为8. 05 ng/m3。特征比值法和主成分分析法解析的PAHs来源基本一致,主要为燃烧源、石油挥发源和工业生产源,贡献率分别为70. 11%、14. 19%和10. 74%。     

我国生态环境中多环芳烃污染状况研究进展

综述了近年来我国大气、水、土壤环境和生态系统中多环芳烃（PAHs）污染状况研究进展，指出化石燃料及其衍生物的燃烧产物是PAHs的主要来源，虽然我国大部分地区生态环境中PAHs风险较低，但仍须关注其潜在的健康风险，提出多学科交叉研究典型PAHs在生态系统中的环境行为及原位修复技术等未来研究方向。     

石油化工园区周边土壤中多环芳烃的分布研究

采集锦州市石油六厂工业区、交通运输区及农业区土壤,采用高效液相色谱/质谱联用仪分析测定土样中16种PAHs的总含量(∑PAHs):工业区均值为386.19μg/kg、交通运输区均值为328.54μg/kg、农业区均值为192.64μg/kg;致癌性PAHs的总含量(∑PAHscare):工业区均值为147.97μg/kg、交通运输区均值为131.52μg/kg、农业区均值为73.83μg/kg;不同功能区PAHs成分组成规律基本一致,PAHs以3环和4环为主,土壤中PAHs成分比例规律为4环>3环>2环>5环>6环;无论是土壤中∑PAHs还是∑PAHscare含量规律,都为工业区>交通运输区>农业区。工业区石油类污染较为严重,交通运输区及农业区土壤中PAHs污染主要来源于化石燃料的燃烧及农业用品的施用。     

某大型化工企业周边居民区积尘中多环芳烃调查及健康风险评价

以江苏省某大型化工企业周边居民区为研究区域,调查企业主导风的下风向2 km范围内的居民区以及对照区积尘中多环芳烃(PAHs)含量,对16种PAHs污染分布和特征进行研究,并评估积尘PAHs通过暴露途径对人群健康风险。结果表明:居民区积尘中16种PAHs全部检出,污染区∑PAHs均值为2 294μg/kg,明显高于对照区145μg/kg;污染区7个测点中有6个测点苯并(a)芘出现超标,超标倍数为0. 17～2. 5倍;所测的16种PAHs化合物中蒽、荧蒽、芘、、苯并(b)荧蒽、苯并(k)荧蒽、苯并(a)芘浓度相对较高;通过PAHs主成分分析和特征比值判断,不完全燃烧源对积尘中PAHs贡献率达77. 4%,污染区PAHs来源呈现石油燃烧、煤燃烧以及石油源的复合污染特征,对照区PAHs主要来源为煤的不完全燃烧;以苯并(a)芘毒性等效浓度进行风险评估,污染区致癌风险值明显高于对照区,儿童摄入PAHs风险总体高于成人;对照区儿童和成人致癌风险均小于1×10~(-6),不存在致癌风险;污染区儿童和成人平均致癌风险值分别为3. 95×10~(-6)、2. 65×10~(-6),在可接受范围内,但存在潜在致癌风险。     

成都典型工业园多环芳烃污染源区识别及风险评估

筛选识别成都市多环芳烃（PAHs）污染重点源和区域，采集57个土壤样品，利用人体暴露风险模型对16种PAHs的健康风险进行评价。结果表明：青白江工业集中发展区与新都工业集中发展区连片区局部有PAHs潜在渗漏风险，污染源主要为工业企业和交通源，农业面源、生活污染源等不直接产生PAHs；土壤PAHs主要来源途径为企业VOCs排放与沉降、汽车尾气与大气中PAHs沉降、废矿物油泄漏入渗；PAHs主要离去途径为入渗地下水、冲淋径流进入地表水、植物吸收；智能设备制造、化工用地存在PAHs人体健康及环境生态风险。     

乌鲁木齐土壤中多环芳烃的污染特征及生态风险评价

在乌鲁木齐地区不同功能区采集28个表层土壤样品,对土壤中多环芳烃(PAHs)的污染特征进行研究,并运用正定矩阵因子分析法对其来源进行分析,采用苯并[a]芘的毒性当量浓度(TEQBa P)对PAHs的生态风险进行评价。研究显示,土壤中∑16 PAHs含量为331~15 799μg/kg,其平均值为(5 018±4 896)μg/kg(n=28),以3环、4环为主。∑16PAHs的浓度呈现出交通区工业区公园区农业区居民商业区的变化趋势;正定矩阵因子分析法表明,乌鲁木齐表层土壤中PAHs的主要来源及贡献分别为煤的燃烧(51.19%),汽油车燃烧(19.02%),柴油车燃烧(18.35%),机动车石油的泄漏(11.42%);53%的采样点TEQBa P值超过荷兰土壤标准目标参考值,主要集中在交通区和工业区。     

某石化化工行业聚集区室内外PM2.5中多环芳烃分布特征及来源

于非采暖季和采暖季分别采集某石化化工行业聚集城市中心城区室内外PM_(2.5)样品,采用高效液相色谱法分析PM_(2.5)上载带的16种PAHs,对其分布特征、来源以及室外PAHs污染对室内污染的贡献进行了初步探讨。结果表明,研究区域非采暖季和采暖季室外PM_(2.5)中ΣPAHs浓度日均值分别为36.3、294 ng/m~3,室内PM_(2.5)中ΣPAHs浓度分别为14.8、84.6 ng/m~3,均以4、5环PAHs为主;室内PAHs主要来自室外渗透污染,但同时明显存在室内排放源贡献;PAHs来源分析进一步证实研究区域PAHs主要来自煤炭、石油等不完全燃烧,采暖季煤炭燃烧源贡献更突出。     

典型区域土壤中多环芳烃的污染分布特征

以河南省3类典型工业区域为例,分析研究其土壤中多环芳烃类化合物的种类组成及含量分布特征,结果表明：3类典型工业区域周边土壤中均检出14种PAHs,其中萘、芘、艹屈 、苯并[a]蒽具有较高的检出水平;大型化工企业周边土壤中PAHs的检出率高于油田和工业园区;检出的14种PAHs的总质量比均值,大型化工企业明显高于油田和工业园区;3类典型工业区域土壤中PAHs测定值明显高于背景值,表明土壤已受到PAHs的影响;来源分析表明,PAHs的污染主要源自石油和燃料的燃烧.     

天津滨海新区黑潴河下游沉积物多环芳烃风险评价及环境基准值的比较

对黑潴河下游表层沉积物中16种多环芳烃(PAHs)的污染现状进行了调查研究。结果表明,表层沉积物中PAHs总量变化范围为41.2～129.3ng/g(平均值为83.7ng/g),PAHs的组成以5～6环PAHs组分为主。黑潴河下游沉积物中PAHs主要来源于周边地区化石燃料的高温燃烧。比较了基于不同方法建立的沉积物中PAHs环境基准值的差异,分析产生差异的原因,选择生态效应区间法对黑潴河沉积物中的PAHs进行了生态风险评价。黑潴河下游PAHs生态风险较小,属PAHs低生态风险河道。     

Estimating nutrient loadings using chemical mass balance approach

The river Hindon is one of the important tributaries of river Yamuna in western Uttar Pradesh (India) and carries pollution loads from various municipal and industrial units and surrounding agricultural areas. The main sources of pollution in the river include municipal wastes from Saharanpur, Muzaffarnagar and Ghaziabad urban areas and industrial effluents of sugar, pulp and paper, distilleries and other miscellaneous industries through tributaries as well as direct inputs. In this paper, chemical mass balance approach has been used to assess the contribution from non-point sources of pollution to the river. The river system has been divided into three stretches depending on the land use pattern. The contribution of point sources in the upper and lower stretches are 95 and 81% respectively of the total flow of the river while there is no point source input in the middle stretch. Mass balance calculations indicate that contribution of nitrate and phosphate from non-point sources amounts to 15.5 and 6.9% in the upper stretch and 13.1 and 16.6% in the lower stretch respectively. Observed differences in the load along the river may be attributed to uncharacterized sources of pollution due to agricultural activities, remobilization from or entrainment of contaminated bottom sediments, ground water contribution or a combination of these sources.     

云南省宣威市和富源县空气和土壤中多环芳烃污染水平研究

宣威市和富源县位于我国云南省东北部,是全世界肺癌发病率最高的地区之一。当地居民在不通风的房间内燃烧烟煤做饭或取暖造成了严重的室内空气污染。研究表明,长期暴露在燃煤造成的污染物中是导致两地居民肺癌持续高发的主要原因,多环芳烃是最可疑的致病因子之一。2008年1月,分别用聚胺脂泡沫和玻璃纤维滤膜采集了当地9个点位室内、室外空气中气相和颗粒物相中的多环芳烃,同时采集了对应点位的土壤样品。通过对样品的分析,考察了当地空气和土壤中多环芳烃的污染水平、特征以及来源。结果证明,当地空气和土壤中存在严重的多环芳烃污染,室内污染显著高于室外,然而随着当地工业的发展室外污染同样不可忽视,主成分分析结合比值法证明,当地室内外多环芳烃的主要污染源来自于煤炭的燃烧。对空气颗粒物和土壤中多环芳烃浓度进行了比较,对土壤中多环芳烃的来源进行了验证。     

福建省茶园土壤中多环芳烃的分布、来源分析及生态风险评价

利用高效液相色谱分析技术对福建省茶园土壤中16种多环芳烃进行了定量分析,结果表明,PAHs的总量在0.622~812.0μg/kg之间,平均值为48.4μg/kg。其组成以3环的为主,4环次之,主成分分析和PAHs特征参数分析发现,福建省茶园土壤中多环芳烃主要以燃油、木柴和煤燃烧来源为主,部分样点存在油类排放污染。生态风险评价结果显示,福建省茶园土壤中多环芳烃已具有不利生物影响效应。     

Composition and source apportionment of PAHs in sediments at river mouths and channel in Kaohsiung Harbor, Taiwan

Fifty-eight sediment samples were collected in 2009 from the bottom of river mouths near Kaohsiung Harbor (Taiwan) and the harbor channel for the analyses of polycyclic aromatic hydrocarbons (PAHs) using gas chromatography-mass spectrometry (GC-MS). Concentrations of total PAHs varied from 39 to 30,521 ng g(-1) (dry weight); samples collected from the mouths of Love River, Canon River, Jen-Gen River, and Salt River showed the highest PAHs concentrations. This indicates that the major sources of sediment PAHs come from those polluted urban rivers and the harbor channel. In samples collected from the Salt River mouth, approximately 43% of the PAHs are identified as PAHs with 2 or 3 rings. However, samples collected from other locations contain predominantly PAHs with 4 rings (32 to 42%) or 5 and 6 rings (36 to 44%). Emissions from traffic-related sources and waste incineration contribute to the majority of PAHs found in most channel and river mouth sediments. However, coal/oil combustion is the main cause of high concentrations of PAHs observed in the Salt River mouth sediments. Principal component analyses with multivariate linear regression (PCA/MLR) have been used to further quantify the source contributions, and the results show that the contributions of coal/oil combustion, traffic-related and waste incineration are 37%, 33% and 30%, respectively.     

Chemometric application in identifying sources of organic contaminants in Langat river basin

Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.     

入河排污口在总量控制中的作用

入河排污口在污染源与水环境间起桥梁作用,入河排污口的入河量是对水环境影响大小的最直接贡献值,作好入河排污口的监测工作,既可对污染源的排污起监督作用,也可得到某区域相对最为可靠的排污总量和河流纳污量,因此,入河排污口是目前总量管理的基础     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Surface water quality assessment of the Vatinsky Egan River catchment, West Siberia

Stream water chemistry were analyzed across Vatinsky Egan River Catchment (West Siberia). The objective of the study is to reveal the spatial and seasonal variations of the water quality and to assess the anthropogenic chemical inputs into the river system. Stream chemistry were monitored in 24 sampling sites for a period extended from January 2002 to December 2005. Spatial distribution of constituents in the Vatinsky Egan River basin indicated pollution from non-point sources associated with oil development. Data revealed that ion concentrations of river waters are usually negatively correlated with stream discharge. The major spatial variations of the hydrochemistry are related to the salinity. Chloride exhibited wide and high concentration range. A comparison with another rivers of West Siberia reveals that Vatinsky Egan River is the most saline and regional impacts further out in the watershed. The salinity of the river water increases substantially as it crosses Samotlor oil field. Many Cl(-) concentrations in the middle and lower parts of the catchment exceed the world average river values by one or more orders of magnitude. For 38% of sampling events, total petroleum hydrocarbons (TPH) concentrations were above the recommended water quality standards.     

Source apportionment of polycyclic aromatic hydrocarbons in the Dahuofang Reservoir, Northeast China

Polycyclic aromatic hydrocarbons (PAHs) in 24 surface sediments from the Dahuofang Reservoir (DHF), the largest man-made lake in Northeast China, were measured. The results showed that the concentrations of 16 US EPA priority PAHs in the sediments ranged from 323 to 912 ng/g dry weight with a mean concentration of 592?±?139 ng/g. The PAH source contributions were estimated based on positive matrix factorization model. The coal combustion contributed to 31 % of the measured PAHs, followed by residential emissions (22 %), biomass burning (21 %), and traffic-related emissions (10 %). Pyrogenic sources contributed ～84 % of anthropogenic PAHs to the sediments, indicating that energy consumption release was a predominant contribution of PAH pollution in DHF. Compared with the results from the urban atmospheric PAHs in the region, there was a low contribution from traffic-related emissions in the sediments possibly due to the low mobility of the traffic-related derived 5+6-ring PAHs and their rapid deposition close to the urban area.