苯并[α]芘对海洋微藻生长及细胞特征的影响

采用急性毒性实验方法,研究了苯并[α]芘(B[α]P)对3种海洋微藻生长和细胞特征的影响。结果表明,B[α]P对3种海洋微藻生长的抑制呈显著的时间-剂量效应,其96 h半数效应浓度依次为:湛江等鞭金藻17.00μg/L,塔溪堤等鞭金藻25.18μg/L,牟氏角毛藻83.06μg/L。高浓度B[α]P胁迫96 h后,3种海洋微藻细胞体积和细胞内容物颗粒均有增加,而藻细胞叶绿素含量却随着B[α]P浓度的增加而降低。这一研究说明,B[α]P对微藻细胞形态及光合能力均能造成明显影响,并可抑制藻细胞数量的增长。B[α]P对藻细胞的抑制作用存在种的差异性,相对来说,金藻类微藻对B[α]P更为敏感。     

宁波市PM2.5中碳组分的时空分布特征和二次有机碳估算

为了研究PM2.5中碳质组分的时空分布特征,于2012年12月至2013年10月4个季度典型时段在宁波市5个采样点采集环境大气中的PM2.5,分析了样品中有机碳(OC)和元素碳(EC)的质量浓度,并估算二次有机碳(SOC)对OC的贡献.结果表明:1宁波市PM2.5年均质量浓度为51.6μg·m-3,其中OC和EC的比例分别为17%和6%.反向轨迹模型的分析结果表明,来自内陆地区的区域传输可能是冬季和春季PM2.5浓度较高的主要原因.2OC/EC比值和OC与EC的相关性分析结果表明,夏季有大量SOC生成,而冬季则可能受华北地区燃煤供暖的显著影响.3用EC示踪法对宁波市的SOC进行了估算,结果表明宁波冬季和春季受到区域传输的显著影响,污染源较不稳定,不宜使用该估算方法.夏季和秋季的SOC质量浓度分别为2.5μg·m-3和2.3μg·m-3,占OC的42%和28%.     

太原市PM2.5中有机碳和元素碳的污染特征

采集了太原市4个点位冬季和夏季PM2.5样品,利用元素分析仪测定了PM2.5中有机碳(OC)和元素碳(EC)的质量浓度,并对碳气溶胶污染水平、时空分布、二次有机碳(SOC)以及OC和EC相关性等特征进行了分析.结果表明,太原市冬季有机碳(OC)、元素碳(EC)平均质量浓度为22.3μg·m-3和18.3μg·m-3,夏季OC、EC平均质量浓度为13.1μg·m-3和9.8μg·m-3,冬季和夏季总碳气溶胶(TCA)占PM2.5的比例分别为56.6%和36.5%;各点位OC和EC质量浓度均呈现冬季夏季的季节特征,冬季OC、EC浓度呈现出较好的均一性,夏季OC、EC质量浓度存在较明显的空间分布差异;太原市SOC污染较轻;冬季OC、EC相关性较强,夏季OC、EC相关性差.     

宁波市区冬季大气颗粒物及其主要组分的污染特征分析

为了更好地研究影响宁波市区环境空气质量的污染物变化特征,于2010年1月20—30日进行了加强监测。研究结果表明,宁波市区大气中PM₁₀和PM_2.5质量浓度较高,其中PM_2.5/PM₁₀为0.5~0.85。对PM₁₀和PM_2.5采样膜分析,水溶性粒子和含碳组分分别占PM₁₀和PM_2.5质量浓度的56.7%和66.9%,其中二次污染的水溶性离子SO₄^2-、NO₃^-和NH₄⁺是PM₁₀和PM_2.5中浓度较高的离子组分;PM_2.5样品中OC与EC的相关性较好,表明OC与EC的来源相对一致,可能主要来自机动车尾气的贡献;但PM₁₀样品中OC与EC的相关性较差,表明其来源相对复杂;其中SOC的浓度占OC的13%~35%,说明宁波市区冬季导致二次污染的光化学反应不活跃。     

PM2.5 chemical composition and health risks by inhalation near a chemical complex

Particulate matter (PM_2.5) samples were collected in the vicinity of an industrial chemical pole and analysed for organic and elemental carbon (OC and EC), 47 trace elements and around 150 organic constituents. On average, OC and EC accounted for 25.2% and 11.4% of the PM_2.5 mass, respectively. Organic compounds comprised polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, anhydrosugars, phenolics, aromatic ketones, glycerol derivatives, aliphatic alcohols, sterols, and carboxyl groups, including aromatic, carboxylic and dicarboxylic acids. Enrichment factors > 100 were obtained for Pb, Cd, Zn, Cu, Sn, B, Se, Bi, Sb and Mo, showing the contribution of industrial emissions and nearby major roads. Principal component analysis revealed that vehicle, industrial and biomass burning emissions accounted for 66%, 11% and 9%, respectively, of the total PM_2.5-bound PAHs. Some of the detected organic constituents are likely associated with plasticiser ingredients and thermal stabilisers used in the manufacture of PVC and other plastics in the industrial complex. Photooxidation products of both anthropogenic (e.g., toluene) and biogenic (e.g., isoprene and pinenes) precursors were also observed. It was estimated that biomass burning accounted for 13.8% of the PM_2.5 concentrations and that secondary OC represented 37.6% of the total OC. The lifetime cancer risk from inhalation exposure to PM_2.5-bound PAHs was found to be negligible, but it exceeded the threshold of 10⁻⁶ for metal(loi)s, mainly due to Cr and As.     

Contents and sources of DDT impurities in dicofol formulations in Turkey

Background, aim, and scope  Dicofol is widely used as a pesticide in agriculture applications. Since dicofol is mainly synthesized from dichlorodiphenyltrichlorethane (DDT), it contains DDT as an impurity. The European Community has forced Prohibition Directive 79/117/EEC to reduce DDT in dicofol formulations. Specifically, DDT content in a dicofol formulation cannot exceed 0.1%. The goal of this project was to determine the DDT content in dicofol formulations used in Turkey. Materials and methods  Samples of all the dicofol formulations in Turkey were collected to quantify DDT and DDT-related compounds. Four replicates were used for each sample. GC/MS/MS was used to analyze p,p′ and o,p′ isomers of DDT, DDD, and DDE. A HPLC was used to determine p,p′-Cl-DDT concentrations. Results  The total DDT content of the formulated dicofol was found between 0.3% and 14.3%. The concentration of p,p′-DDE ranged from 167 to 1,042 mg kg⁻¹ in dicofol samples. p,p′-DDT concentrations were found to be 32 to 183 mg kg⁻¹. The o,p’-DDT level ranged from 2 to 34 mg kg⁻¹ in the dicofol formulations analyzed. Discussion  It was estimated that 617.8 kg of DDT was released from dicofol. The main impurity was identified as p,p-Cl-DDT. Based on these results, dicofol serves as a continuing source of DDT contamination. Conclusions  All DDT concentrations in dicofol samples analyzed were higher than the permitted 0.1% level of Prohibition Directive 79/117/EEC. The reduction of dicofol is critical since it serves as a continual source of DDT contamination. Recommendations and perspectives  DDT has been found in soil, water, and air samples. Dicofol has been identified as a contributor to continued DDT contamination in soil and water. More studies are needed to ascertain the source of DDT in the air.     

Measurement of machinery safety level in the European market: A real case based on market surveillance data

This article aims to highlight the current status of compliance to Machinery Directive 98/37/EC (transposed to Spanish regulation as RD 56/1995, of 20th January) (a new directive numbered as 2006/42/EC [Directive 2006/42/EC of the European Parliament and of the Council of 17 may 2006 on machinery, and amending Directive 95/16/EC (recast). OJ L157/24-86, 9.6.2006.], that recasts and replaced 98/37/ED directive and its amendments, came into force on 29 June 2006; it will not be applied until 29th December 2009. European Member States have a lead-time of two years to adopt and publish the national laws and regulations transposing the provisions of the new Directive into national law. Latest 10th October, Spain transposed Machinery Directive 2006/42/EC to national regulation as Real Decreto 1644/2008 [Real Decreto 1644/2008, de 10 de octubre, por el que se establecen las normas para la comercialización y puesta en servicio de las máquinas. BOE 246/2008, de 11 octubre 2008. Páginas 40995–41030]) of a particular family of machinery (hand-held, medium and small-size, deeply introduced in the market, of low-medium cost), that any user, professional or non-professional, can acquire as first-hand in any of the sales points (whether or not experts in these kind of products).At the same time, it emphasises the most significant shortcomings and non-conformities found, after analyzing the results of five consecutive Campaigns of Control of Industrial Products performed by one of the labs (placed in Spain) involved in the market surveillance European Program.     

天津市区PM2.5中碳组分污染特征及来源分析

为研究天津市细颗粒中碳组分特征,于2006年8-12月连续采集PM25样品,分析其来源及浓度特征.结果表明,天津市区PM25、有机碳(OC)及元素碳(EC)浓度分别为165.90、23.90、5.50 μg/m3,3项浓度均为冬季最高.OC、EC、总碳在PM2.5中所占比例分别为14.31％、3.66％和18.14％,秋季在PM 2 5中所占比例最高,夏季最低.OC/EC平均值为4.21,按照秋、夏、冬呈递增的季节变化趋势.冬季二次有机碳污染较重,二次有机碳浓度(13.98 μg/m3)占OC比例为34.5％.因子分析表明,非采暖期汽油车对碳气溶胶作用显著,采暖期生物质燃烧、燃煤及汽油车排放贡献.     

成都冬季PM2.5化学组分污染特征及来源解析

2017年1月1~20日在成都地区分昼夜对PM_(2.5)进行连续膜样品采集,并在实验室测定了其主要化学组分(水溶性离子和碳质组分)的质量浓度.观测期间,PM_(2.5)的平均质量浓度为(127.1±59.9)μg·m~(-3);总水溶性离子的质量浓度为(56.5±25.7)μg·m~(-3),其中SO2-4、NO-3和NH+4是最主要的离子,质量浓度分别为(13.6±5.5)、(21.4±12.0)和(13.3±5.7)μg·m~(-3),一共占到了水溶性离子的85.6%;有机碳(OC)和元素碳(EC)的平均质量浓度分别为34.0μg·m~(-3)和6.1μg·m~(-3),分别占PM_(2.5)质量浓度的26.8%和4.8%.昼夜污染对比显示,PM_(2.5)白天和夜晚质量浓度分别为(120.4±56.4)μg·m~(-3)和(133.8±64.0)μg·m~(-3),夜间污染更为严重.SO2-4、NO-3和NH+4白天浓度高于夜间,这与白天光照促进了二次离子的形成有关;而Cl-、K+、OC和EC浓度夜间明显升高,可能是受夜间煤和生物质燃烧排放增加的影响.通过对近年来成都冬季PM_(2.5)化学组分的研究进行文献总结和比较后发现,SO2-4浓度显著降低,从2010年的50.6μg·m~(-3)降低到2017年的13.6μg·m~(-3);而NO-3浓度变化不大,维持在20μg·m~(-3)左右.PM_(2.5)中离子酸碱平衡分析表明,成都冬季PM_(2.5)由于NH+4的相对过剩而呈现出碱性,与以往呈偏酸性结果存在差异.对成都冬季NO-3/SO2-4的比值进行计算,NO-3/SO2-4平均值为1.57,表明移动源对PM_(2.5)污染影响更大.OC与EC的相关性表明,白天和夜间OC与EC的相关系数分别为0.82和0.90(P0.01),OC与EC来源具有一致性.SOC估算结果显示,白天和夜间SOC浓度分别为8.5μg·m~(-3)和11.9μg·m~(-3),占到OC的28.1%和31.8%.K+/EC平均值为0.31,并且K+与OC之间相关系数为0.87(P0.01),说明生物质燃烧对成都冬季碳质气溶胶有一定影响.主成分分析表明,成都冬季PM_(2.5)主要来源于燃烧源(燃煤、生物质燃烧等)、二次无机污染源以及土壤和扬尘源,其贡献率分别为32.8%、34.5%和21.5%.     

沈阳市冬季不同污染程度PM2.5中OC和EC污染特征

于2018年12月~2019年1月对沈阳市PM_2.5进行持续在线浓度监测,使用有机碳/元素碳分析仪对PM_2.5中有机碳（OC）和元素碳（EC）的质量浓度进行分析,研究了不同污染程度下PM_2.5及其碳组分的污染特征和来源.结果表明,沈阳地区冬季碳组分污染较为严重,不同污染程度下的总碳气溶胶（TCA）约占PM_2.5的36.3%~42.8%.中/重度污染天气下PM_2.5、OC和EC的平均质量浓度达到148.6,29.6,6.6μg/m³,是清洁天的3.1~3.3倍.PM_2.5、OC和EC的日变化均表现为早晚高、午后低,任一时刻其浓度均为中/重度污染>轻度污染>清洁天.不同污染程度下的OC/EC值均大于2,其中污染天比值分布在2.1~25.3区间内,表明燃煤和机动车尾气排放是污染天碳质气溶胶的主要来源.二次有机碳（SOC）随污染程度增加表现出升高趋势,清洁天、轻度污染和中/重度污染下其平均浓度依次为2.9,6.5,10.6μg/m³.后向轨迹聚类结果表明,沈阳地区冬季污染天主要受偏北和西北方向气团影响.