环渤海渔港沉积物多环芳烃的污染特征和生态风险评价

2019年5-6月采集了环渤海20个渔港的沉积物样品,采用高效液相色谱紫外成光检测器串联方法对16种多环芳烃(PAHs)进行检测,分析了其分布和组成特征,采用比值法和正定矩阵因子模型法(PMF)对PAHs进行定量源解析,采用效应区间中低值法和中值商法评估其生态风险.10种PAHs的检出率达到100％,表明PAHs在沉积...     

受体模型应用于典型持久性有毒物质的来源解析研究进展

阐述了常用的受体模型化学质量平衡模型(CMB),正定矩阵因子分解模型(PMF)、因子分析/多元线型回归(FA/MLR)、绝对因子得分/多元线性回归(AFS/MLR)、非负约束的因子分析模型(FA-NNC)和同位素来源解析技术(CSRA)的方法和原理,总结了受体模型应用于三种典型持久性有毒物质(PTS)PAHs,PCDD/Fs和PCBs的来源解析研究进展,并对PTS类污染物来源解析的发展趋势和我国源解析研究亟待解决的问题进行展望.     

鞍山市冬季大气PM_(2.5)中多环芳烃的来源解析及毒性评价

2015年1月份采集鞍山市主城区共6个采样点的PM_(2.5)样品,并采集了固定源、移动源、开放源、生物质燃烧源、餐饮油烟等5类污染源,使用GC-MS进行16种多环芳烃(PAHs)质量浓度的分析,运用PMF法和毒性当量分别进行了来源解析和毒性评价.结果表明,鞍山市主城区冬季大气PM_(2.5)中ρ(PAHs)和ρ(BaP)较高,PAHs以3环、4环为主,占PAHs总浓度的82.56%;冬季大气中PAHs主要来源为煤烟尘、焦化尘、移动源、开放源、生物质燃烧源和其他污染源,其贡献率分别为27.8%、24.2%、18.1%、13.4%、4.7%和11.8%;毒性评价表明,鞍山市冬季PAHs的TEQ均值为33.51 ng·m~(-3),铁西三道街的毒性当量浓度最高.     

黄海近岸表层沉积物中多环芳烃来源解析

采集了黄海近岸(日照岚山海域)12个站位的表层沉积物样品,利用气相色谱-质谱仪(GC-MS)分析了样品中16种多环芳烃(PAHs)的含量,结果显示16种PAHs含量范围在76.384～7512.023 ng·g-1,平均值为2622.576 ng·g-1.低环PAHs组分所占比重较大,中高环PAHs相对较小.利用比值法定性解析PAHs的来源,初步判断PAHs可能来自燃煤、燃油、焦化、柴油泄漏等污染源.进一步引用相关源成分谱,应用化学质量平衡模型(CMB8.2)对PAHs的来源进行定最解析,拟合计算结果表明研究海域表层沉积物中PAHs的主要来源为燃煤源、燃油源(主要为柴油燃烧)和焦炉源,其相对贡献率分别为53.99%、25.57%和13.97%.     

南京市可吸入颗粒物中多环芳烃的源解析

采集南京市燃煤、焦化、机动车和烹调四种污染源样品,采用高效液相色谱仪测定其中的PAHs含量,建立四种源的成分谱.根据所得数据,运用化学质量平衡(CMB)受体模型对PM10中的PAHs进行源解析研究,以确定燃煤源、焦化源、交通源和烹调源对PM10中PAHs的贡献率.     

基于放射性碳分析的多环芳烃源解析:技术进展和准确性评估

化石燃料燃烧和生物质燃烧是污染物多环芳烃(polycyclic aromatic hydrocarbon,PAHs)的两大来源.放射性碳(14C)分析近年用于评估这两类源对环境中PAHs的相对贡献.此方法基于化石燃料和生物质的14C含量差异,即化石燃料不含14C,而生物质的14C浓度有一个较稳定值.14C的自然丰度极低(约10-12),因此检测PAHs这样的痕量污染物的14C含量一度极具挑战.1990年代中期,加速器质谱的技术突破使得对环境样品PAHs的14C分析具有实用价值.要准确测出PAHs的14C含量,须先从化学成分复杂的环境样品中分离出高纯度的PAHs.制备气相色谱因其出色的分离能力而成为目前环境样品PAHs14C分析必备的工具.本文意在简介基于14C分析的PAHs源解析的基本原理、技术进展,以及评估该方法获得的PAHs源解析结果的准确性.     

城市近郊型地下河水中多环芳烃分布规律与来源解析

利用气相色谱-质谱联用仪(GC-MS)对广西清水泉地下河水16种多环芳烃(PAHs)的含量进行了测定,研究地下河水中PAHs的组成、分布规律及主要来源,为城市近郊型地下河系统持久性污染物防治提供科学依据.结果表明,地下河水中∑PAHs浓度范围为162.13—224.99 ng·L-1,平均值为191.71 ng·L-1,PAHs以4环为主,占47.14%;地下河水中PAHs的含量自上游至下游逐渐增大,2—3环PAHs的百分比先升高后降低;PAHs来源解析表明,上游地区PAHs来源以草、木、煤燃烧源为主,中下游地区敢怀村附近PAHs来源为石油源,地下河出口处PAHs来源以石油源和燃烧源的混合源为主.     

城市化进程中天津市近郊区土壤多环芳烃的污染特征变化及健康风险

多环芳烃(PAHs)是城市主要污染物之一,对居民健康构成了巨大的威胁.然而,探讨城市化与区域PAHs污染特征及其健康风险的关系的研究却很少.基于正定矩阵因子分解(PMF)模型和终身累积癌症风险(ILCR)模型,本文对比了2008年和2012年天津市近郊地区土壤中PAHs的含量、组成、来源及其导致的生态风险.结果表明,土壤中PAHs的浓度增加了1倍,低分子量组分的比例由28.6%上升到34.8%,优势化合物由苯并(b)荧蒽、荧蒽和苯并(g,h,i)苝转变为菲、萘和荧蒽.土壤PAHs主要来源由2008年的燃煤源(51.3%)、机动车排放(23.1%)和生物质燃烧排放(14.5%)转变为2012年的燃煤源(41.0%)、机动车排放(28.4%)和石油源(22.3%),排放源的变化与区域工业能源结构调整以及居民日常生活习惯改变有着密切的关联.机动车排放源贡献率增加导致当地居民的土壤PAHs暴露风险上升,皮肤接触是主要的暴露途径,儿童是对暴露风险最敏感的亚群体.     

新疆阿勒泰地区土壤中多环芳烃含量水平及来源解析

为了研究新疆阿勒泰地区土壤多环芳烃(PAHs)污染状况,于2018年10月对阿勒泰地区表层土壤进行采样,共采集样品14个,采用气相色谱-质谱仪(GC-MS 7890A-5975MSD Agilent)测定土壤样品中16种优控PAHs含量,并对其组成、分布及来源情况进行解析。结果表明,阿勒泰地区表层土壤中∑_(16)PAHs含量介于3.48～103.81 ng·g~(-1)之间,平均含量为32.24 ng·g~(-1),PAHs组成以3、4环为主,其中,7种致癌PAHs总含量介于0.32～50.95 ng·g~(-1)之间,平均含量为11.20 ng·g~(-1)。研究区域土壤PAHs污染水平较低,且PAHs污染水平与海拔高度无显著相关性(r=-0.471,P=0.668)。同分异构体比值法分析结果表明阿勒泰地区土壤PAHs主要来源于化石燃料及生物质燃烧,机动车尾气排放对PAHs贡献较大。主成分分析-多元线性回归解析结果表明,阿勒泰地区土壤PAHs主要受交通源(62.8%)、焦炉和燃煤源(28.2%)以及生物质燃烧源(9.0%)3个污染源影响,与新疆2012年排放贡献源相比,交通源以及焦炉和燃煤源排放占比呈上升趋势。     

泰安市大气挥发性有机物污染特征及来源解析

2018年夏季对泰安市城区站点的挥发性有机物(VOCs)进行监测,研究了其污染特征、臭氧生成潜势(OFP)和特征污染物比值,利用PMF源解析模型对VOCs的来源进行了解析.结果 表明,观测期间泰安市VOCs体积分数平均值为(16.57±7.99)× 10-9,VOCs中浓度占比最高的为OVOCs(41.9％),其次为烷...     

PM<Subscript>2.5</Subscript> pollution from household solid fuel burning practices in Central India: 2. Application of receptor models for source apportionment

USEPA’s UNMIX, positive matrix factorization (PMF) and effective variance-chemical mass balance (EV-CMB) receptor models were applied to chemically speciated profiles of 125 indoor PM_2.5 measurements, sampled longitudinally during 2012–2013 in low-income group households of Central India which uses solid fuels for cooking practices. Three step source apportionment studies were carried out to generate more confident source characterization. Firstly, UNMIX6.0 extracted initial number of source factors, which were used to execute PMF5.0 to extract source-factor profiles in second step. Finally, factor analog locally derived source profiles were supplemented to EV-CMB8.2 with indoor receptor PM_2.5 chemical profile to evaluate source contribution estimates (SCEs). The results of combined use of three receptor models clearly describe that UNMIX and PMF are useful tool to extract types of source categories within small receptor dataset and EV-CMB can pick those locally derived source profiles for source apportionment which are analog to PMF-extracted source categories. The source apportionment results have also shown three fold higher relative contribution of solid fuel burning emissions to indoor PM_2.5 compared to those measurements reported for normal households with LPG stoves. The previously reported influential source marker species were found to be comparatively similar to those extracted from PMF fingerprint plots. The comparison between PMF and CMB SCEs results were also found to be qualitatively similar. The performance fit measures of all three receptor models were cross-verified and validated and support each other to gain confidence in source apportionment results.     

大气颗粒物上多环芳烃的识别和源解析的进展

本文对当前大气颗粒物上ＰＡＨｓ的识别和源解析的定量及定性和半定量的方法进行了综述，定性及半定量方法简便易行，但误差大；化学质量平衡法结果较准确具体，但ＰＡＨｓ会发生化学反应而降解，并且没有各种燃烧源较完整的ＰＡＨｓ成份谱，这已成为ＣＭＢ广泛推行的障碍；多元统计方法不考虑ＰＡＨｓ的降解，但要求数据量大，国内外的科学工作者用不同的方法和手段，使ＰＡＨｓ来源的识别和源解析工作有了一定进展。     

An interval dynamic multimedia fugacity (IDMF) model for environmental fate of PAHs and their source apportionment in a typical oilfield,China

An interval dynamic multimedia fugacity (IDMF) model with a new validation criterion of interval average logarithmic residual error (IALRE) was developed in this study. The environmental fate of polycyclic aromatic hydrocarbons (PAHs) and their source apportionment in a typical oilfield of China were simulated from 1985 to 2010. The PAH concentrations predicted by the model were in agreement with the measured concentrations, which were indicated by the IALREs calculated at 0.41, 0.63, 0.52, and 0.58 for air, water, soil, and sediment, respectively. The multimedia concentrations of Σ16 PAHs were 29.55, 39.22, 31.98, and 26.69 times greater in 2010 than those in 1985, and were higher than any other year modelled. Additionally, 87.82% of PAHs remained in the soil in 2010. PAH source emission into the soil was the major modelled source, whereas PAH degradation in the air was the major modelled loss pathway; the dominant transfer process between the adjacent compartments was atmospheric deposition from air to soil. It was demonstrated that high-temperature combustion was the major source of PAHs in the air and soil, whereas biomass and coal combustion were attributed to water and sediment compartments. The IDMF model was effective in the dynamic source apportionment of PAHs.     

徐州市城市大气中的PAHs来源解析

采用化学质量平衡模型（CMB）对徐州市大气颗粒物中的多环芳烃（PAHs）进行来源分析,从而来确定各个源对大气的PAHs贡献值。主要通过利用大流量采样器配置PM10切割头在冬季和夏季对不同功能区,即生活区、工业区和旅游区采样大气中的可吸入颗粒物（PM10）样品,并用高效液相色谱法（HPLC）重点分析和研究了美国环保局（EPA）列出的16种PHAS优先污染物。研究结果表明：徐州市PM10污染比较严重,PM10污染质量浓度水平冬季是（288.81μg·m-3）大于夏季（276.34μg·m-3）,特别是工业区,污染数值达到393.13μg·m-3。夏季的总PAHs质量浓度为22.89 ng·m-3,分别是生活区28.35 ng·m-3、工业区21.75 ng·m-3和旅游区18.58 ng·m-3。冬季的总PAHs质量浓度为306.29 ng·m-3,分别是工业区388.03 ng·m-3、生活区276.29 ng·m-3和旅游区254.28 ng·m-3。夏季和冬季情况下,旅游区的污染相对来说都是最低的PM10中多环芳烃的源解析结果为,煤烟尘污染源的全年贡献率为64.00%,冬季煤烟尘污染源的贡献率为66.51%,夏季煤烟尘污染源的贡献率为57.21%,说明煤烟尘是PM10中多环芳烃的主要贡献源,土壤尘次之,全年贡献率为24.90%,冬季为25.48%,夏季为28.97%,因此,扬尘和烟煤尘的污染是徐州市的PM10中PAHs的最主要来源。     

城市小集水区降雨径流污染来源解析

利用深圳市王家庄集水区的降雨径流水质监测数据,运用正定矩阵因子分解法（PMF）定量解析了单个城市小集水区降雨径流污染的主要来源。结果表明：研究区降雨径流的主要污染源为城市污水、管内沉积物和地表径流。其中城市污水以输出氨氮（NH3-N）和总氮（TN）为主,管内沉积物是化学需氧量（CODCr）、总磷（TP）和生化需氧量（BOD5）的主要来源,地表径流为固体悬浮物（SS）的主要来源。PMF模型可作为土地利用方式均一的单个城市小集水区降雨径流污染源解析的有效方法之一,主要污染源的廓线能否保持相对稳定是该模型在降雨径流污染源解析时的主要约束条件。     

Source apportionment of PM2.5 in Tangshan,China—Hybrid approaches for primary and secondary species apportionment

The new hybrid approaches for the source apportionment of PM_2.5 were proposed. The hybrid approach can be used for source apportionment of secondary species. The metallurgy industry was the biggest contribution source to PM_2.5 of Tangshan. In winter, the contribution from the coal-fired boilers was the largest one. The objective of this paper is to propose a hybrid approach for the source apportionment of primary and secondary species of PM_2.5 in the city of Tangshan. The receptor-based PMF (Positive Matrix Factorization) is integrated with the emission inventory (EI) to form the first hybrid method for the source apportionment of the primary species. The hybrid CAMx-PSAT-CP (Comprehensive Air Quality Model with Extensions – Particulate Source Apportionment Technology – Chemical Profile) approach is then proposed and used for the source apportionment of the secondary species. The PM_2.5 sources identified for Tangshan included the soil dust, the metallurgical industry, power plants, coal-fired boilers, vehicles, cement production, and other sources. It is indicated that the PM_2.5 pollution is a regional issue. Among all the identified sources, the metallurgy industry was the biggest contribution source to PM_2.5, followed by coal-fired boilers, vehicles and soil dust. The other-source category plays a crucial role for PM_2.5, particularly for the formation of secondary species and aerosols, and these other sources include non-specified sources such as agricultural activities, biomass combustion, residential emissions, etc. The source apportionment results could help the local authorities make sound policies and regulations to better protect the citizens from the local and regional PM_2.5 pollution. The study also highlights the strength of utilizing the proposed hybrid approaches in the identification of PM_2.5 sources. The techniques used in this study show considerable promise for further application to other regions as well as to identify other source categories of PM_2.5.     

基于统计方法的辽东湾沉积物中多环芳烃来源特征分析

为研究辽东湾表层沉积物中多环芳烃(PAHs)的来源特征,2014年5月采集了20个辽东湾海域表层沉积物样品,并利用气相色谱质谱联用仪对优先控制的16种PAHs进行测定,采用聚类分析、主成分分析-多元线性回归分析、异构体比值3种统计方法对辽东湾表层沉积物中PAHs来源特征进行了研究。结果表明,辽东湾表层沉积物中PAHs含量范围88.5~199.3 ng·g-1,平均值为(126.3±35.3)ng·g-1,其中,萘、菲和荧蒽是PAHs优势组分。通过统计分析结果表明,辽东湾北部表层沉积物中PAHs含量低于西南部,沉积物中PAHs的来源包括石油燃烧来源、煤炭、木材等生物质燃烧来源和石油来源,其中燃烧来源是主要来源,煤炭、木材等生物质燃烧来源占49.9%,石油燃烧来源和石油来源占50.1%。     

长江三角洲河网地区典型城镇街尘中多环芳烃的污染特征

街尘是一种重要的环境介质,其携带的污染物在城镇化过程中对河网地区的水环境构成了一定的威胁.为初步探讨长江三角洲河网地区典型街尘中多环芳烃(PAHs)的污染特征,以杭嘉湖平原河网地区饮用水水源河流上游典型小城镇的街尘为研究对象,对工业区、交通干道、旧居区、新居区和商业区5种土地利用类型的15个采样点进行街尘样品采集和粒径分级,测试街尘的密度、有机质含量以及16种U.S.EPA优控PAHs含量等指标.结果表明,粒径为<63、63～125、125～250和250～900μm街尘中总多环芳烃(∑PAHs)的平均含量分别为7261、5835、4660和2909μg·kg-1,粒径越小,PAHs含量越高,其生态风险越大.不同土地利用类型的街尘中PAHs的含量顺序依次为:工业区>交通干道>旧居区>新居区>商业区.街尘中PAHs和有机质含量存在显著正相关关系,且街尘粒径越小,有机质和PAHs的相关性越强.源解析结果表明,街尘中的PAHs多为燃烧源.     

Source apportionment studies for particulates (PM10) in Kozhikode,South Western India using a combined receptor model

In the present work, source apportionment studies were carried out for particulate matter – one among the significant pollutants as addressed by The National Ambient Air Quality Standards. Advantages and disadvantages of each receptor model were addressed using a combined receptor model which integrates Factor Analysis (FA), Positive Matrix Factorisation (PMF) and Chemical Mass Balance (CMB). Verification of the approach was done using sets of synthetic data as well as field data from Kozhikode. Sampling was carried out in National Institute of Technology, Calicut for a period of over 26 days with 24-hour sampling. The sampling gave an average PM concentration value in the range of 29.174–129.176 µg m^?3. Studies using field data revealed five dominant sources and their contributions obtained from CMB and PMF were compared. Soil dust (contribution from CMB: 18%; contribution from PMF: 16%), marine aerosol (17%; 25%), construction and aggregate processing (46%; 11%), garden waste combustion (18%; 45%), and vehicular exhaust (1%; 3%) were major contributors in the site under study. The outcomes of the study integrated with the support of local authorities and by the acceptance of residents can definitely curb the pollution levels in the site under the study.