Response of the Ascorbate-Peroxidase of Selenastrum capricornutum to Copper and Lead in Stormwaters

The green alga Selenastrum capricornutum expresses a uniqueascorbate peroxidase, that responds to copper and lead. Attemptswere made to test if this peroxidase could be used to monitor thelevels of copper and lead in natural waters. When S.capricornutum was exposed to a stormwater sample, the specificactivity of the peroxidase in the cell extract was commensuratewith the combined copper and lead contents in the sample. Theperoxidase responses were also correlated with the 96 hr biomasstoxicity assay of S. capricornutum. However, unlike thebiomass toxicity assay, the peroxidase activity was not affectedby the anions in the samples. The use of this peroxidase can beused as a marker for testing heavy metal toxicity in the water.     

因子分析法解析北京市大气颗粒物PM10的来源

2004年10月份在北京市6个采样点采集了大气PM10样品,分析了大气颗粒物的质量浓度、元素组成、离子、有机碳(OC)和元素碳(EC)的浓度,并用因子分析模型对颗粒物的来源进行了研究。结果显示,北京市大气颗粒物的来源主要有6类:建筑水泥尘/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘、生物质燃烧尘和燃油尘。用模型计算得到的各源对PM10的贡献率分别为建筑水泥尘/机动车尾气尘/燃煤尘占36.57%、土壤风沙尘占16.07%、二次粒子尘占12.33%、工业粉尘占10.29%、生物质燃烧尘占6.07%、燃油尘占3.84%、其它占14.84%。其中建筑水泥/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘是大气颗粒物PM10的主要来源。实验表明,在缺少源成分谱时可以用因子分析模型来分析大气颗粒物的来源及其相对贡献。     

广州冬季霾天气大气PM2.5污染特征分析

收集了2005年12月至2006年2月的PM2.5浓度观测数据及同步气象数据,分析了冬季PM2.5质量浓度日变化趋势以及霾日期间PM2.5质量浓度日变化和小时变化趋势.结果发现,观测期间PM2.5日均值浓度为69μg/m3,霾日期间PM2.5日均值浓度为72μg/m3.冬季霾天气的发生频率为45%,霾天气过程最短持续2天,最长持续9天.较高的PM2.5浓度和较高的相对湿度及较小的风速是导致霾天气形成的主要原因.霾日期间PM2.5小时浓度变化趋势与人类活动周期和气象条件密切相关.     

The collection of PM10 for toxicological investigation: comparisons between different collecting devices

A positive correlation has been established between increased levels of airborne particulate pollution and adverse health effects, the toxicological mechanisms of which are poorly understood. For toxicologists to unambiguously determine thesemechanisms, truly representative samples of ambient PM₁₀ are required. This presents problems, as PM₁₀ collecting equipment commonly employed, such as the Tapered Element Oscillating Microbalance (TEOM®), heat the inflow toexclude moisture or use fibrous filters, resulting in a PM₁₀sample that may have undergone significant chemical change on thefilter surface or is contaminated by filter fibres. Other systems(i.e. Negretti and Partisol) can successfully collect PM₁₀ without chemical alteration or filter contamination. Comparativecollections from Port Talbot, S. Wales suggest that TEOMs and Negretti/Partisol systems collect different PM₁₀'s; the principle difference arising from the TEOM's heating chamber, which precipitates water-soluble ions and volatilises some organic components. This results in both the mass and compositionof the PM₁₀'s being altered. Particle size distributionsfor Negretti and Partisol collections highlighted differences mainly attributed to different flow rates. The results of thiswork demonstrate that simple correlations between PM₁₀ massand adverse health effects are problematic. Furthermore, elucidation of the complex fractionation and chemical changes indifferent collectors is necessary.     

固相萃取-气质联机测定水中嗅味物质2-甲基异茨醇和土霉素

分别利用固相萃取剂XAD-2树脂和C18SEP柱富集,二氯甲烷洗脱,固相萃取装置浓缩,通过气质联机(GC/MS)测定了水中土霉化合物MIB和Geosmin。该方法重现性好,相对标准偏差5.4%~7.0%,回收率80%~92%,MIB和Geosmin检出限分别为5ng/L和2ng/L。两种固相萃取剂对MIB和Geosmin吸附效率相当,吸附效率不受嗅味物质浓度影响,但当水溶液中其它有机质增多时,C18SPE的回收率明显下降。利用该方法对不同培养时间的放线菌代谢产物进行了测定,培养25天后代谢产物MIB和Geosmin的浓度达到200ng/L和130ng/L。     

镉─邻菲啰啉配合物吸附波的研究与应用

在ｐＨ３．３的盐酸－醋酸钠介质中．镉－邻菲啉配合物在－０．６５Ｖ（ｖＳ．ＳＣＥ）处产生一灵敏的吸附波，其二次导数波高与镉浓度在０．０００６～０．１ｍｇ／Ｌ范围内呈良好的线性关系，检出下限达０．０００３ｍｇ／Ｌ。极谱波性质的研究表明该波具有配合物吸附波的特征。方法已用于环境水样中微量错的测定，结果与其它方法吻合。     

南通市冬季PM2.5中水溶性离子污染特征

根据南通市2016和2017年冬季大气多参数站自动监测PM2.5数据和在线离子色谱分析仪Marga监测的PM2.5中水溶性离子数据,分析了南通市冬季PM2.5中水溶性离子污染特征。结果表明,南通市2016和2017年冬季,ρ(PM2.5)分别为58和54μg/m 3,均高出其年均值(14μg/m^3);ρ(水溶性离子)总占ρ(PM2.5)百分比分别为74.5%和74.3%;二次离子ρ(NO3^-、SO4^2-和NH4^+)占ρ(PM2.5)百分比分别为66.8%和66.6%;各水溶性离子占比大小依次为:NO3^-、SO4^2-、NH4^+、Cl^-、K^+、Na^+、Ca^2+、Mg^2+。对ρ(NO3^-)/ρ(SO 4^2-)分析表明,移动源已经成为南通市冬季的主要污染源,且呈逐年增强趋势。对氯氧化率和硫氧化率的分析表明,南通市冬季存在较明显的二次污染,SO2的转化程度大于NO2。除Na^+和Mg^2+外,其他离子与PM2.5均呈显著相关性,NO3^-、SO4^2-与NH4^+之间的相关系数最高,Cl^-与除Na^+外的所有阳离子均呈显著相关性。     

2017年上半年北京市及周边地区空气质量特征分析

依托北京市、廊坊市和保定市高密度的地面空气质量监测、气象要素监测以及PM_2.5化学组分监测和后向轨迹分析等手段，对2017年上半年三地的空气质量进行分析。研究发现：三地中北京市空气质量较好，保定市较差。分污染物来看，保定市SO₂浓度水平明显高于廊坊市和北京市，颗粒物PM₁₀和PM_2.5也呈现保定市最高、北京市最低的规律。从污染物日变化来看，CO、SO₂、NO₂、PM₁₀和PM_2.5呈双峰型分布，O₃呈单峰型分布。从区域整体分布规律来看，PM_2.5和SO₂呈现明显的"南高北低"特征。PM_2.5化学组分分析结果表明：1—4月燃煤对该区域空气质量的影响较大，5—6月机动车排放的影响更为凸显。后向轨迹分析结果表明：在2017年上半年到达北京市的气流中有24%来自于北京市南部，且这些气流多为低空传输，表明区域传输对于北京市空气质量具有一定的影响。     

Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 m(PM₁₀), sulfur dioxide (SO₂) and nitrogen oxides (NO_x) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM₁₀ from all the port activitieswere 872 and 221 t yr^-1, respectively. Annual average emissions of gaseous pollutants SO₂ and NO_xwere 56 and 397 t yr^-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr ^-1) was from paved roads, while the least (0.4 t yr^-1) was from bulk handling activity. The maximum PM₁₀ emission (123 t yr^-1) was from unpaved roads and minimum (0.2 t yr^-1) from bulk handling operations. Similarly the ratio of TSP and PM₁₀ emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM₁₀ from variousport activities. Good correlation was observed between TSP andPM₁₀ having regression coefficient >0.8.     

乌鲁木齐市新市区大气气溶胶中多环芳烃的GC/MS分析

采用气相色谱-质谱联用技术(GC/MS)分析测定了乌鲁木齐市新市区的大气气溶胶样品16种EPA优控多环芳烃(PAHs)的含量。通过索氏提取气溶胶样品,抽提物经硅胶层析柱分离,使用16种多环芳烃混合标准样品绘制标准曲线,以外标法对PAHs进行定量分析,并根据所得数据浅析了多环芳烃污染来源。结果表明,乌鲁木齐市新市区大气中由于汽车尾气排放和煤的燃烧造成的多环芳烃污染均存在。