广州地区秋冬季细颗粒物PM2.5化学组分分析

分析了广州地区2009年-2010年秋冬季节大气中PM2．5样品的水溶性离子、重金属元素、有机碳/元素碳（OC/EC）、多环芳烃质量浓度和粒径分布。初步掌握了广州地区秋冬季节大气中PM2．5的化学组分和特点,有机质（OM）是广州地区秋冬季PM2．5中最主要的成分,其次是硫酸根离子、硝酸根离子和铵根;PM2．5中有机碳和元素碳的空间分布特征相似,并受一次源排放影响;PM2．5中的重金属含量以铝、锌、铅相对较高,且城区高于城郊;PM2．5中17种多环芳烃、苯并（ a）芘（ BaP）的浓度均为城郊高于市区。     

大气中PM2.5污染现状、健康效应及其致炎症机制研究进展

空气细颗粒物(PM_(2.5))污染已成为影响人体健康的重要因素,其健康效应及致炎症机制已经受到人们的广泛关注。简述了PM_(2.5)国内外污染现状,从PM_(2.5)的质量浓度和组成成分2个方面系统地阐述了其对人体健康的危害,并重点从介导信号通路和介导细胞自噬2个方面对PM_(2.5)导致机体炎症反应的毒性机制进行了总结和讨论,为后续研究和控制PM_(2.5)对机体健康的危害提供科学参考。     

我国4个大城市空气PM_(2.5)、PM_(10)污染及其化学组成

报告了 1 995～ 1 996年在中国的广州、武汉、兰州、重庆 4大城市 8个采样点 PM2 .5 、PM2 .5～ 1 0 和 PM1 0 的监测结果。结果表明 ,1 995年 PM2 .5 年均值浓度为 57～ 1 60 μg/m3,比美国 1 997年颁布的标准值 (1 5μg/m3)高 2 .8～ 9.7倍。PM1 0 年日均值为 95～ 2 73μg/m3。除武汉市 1个对照点外 ,其余 7个监测点的 PM1 0 均超过我国空气质量二极标准 (1 0 0μg/m3)2 8%～ 1 73 % ,比美国标准 (50μg/m3)超过更多 ,说明污染是相当严重的。用 XRF分析了 PM2 .5 、PM2 .5～ 1 0 中 4 2种化学元素 ,结果表明 ,燃煤、燃油和其它工业污染的元素 As、Pb、Se、Zn、Cu、Cl、Br、S在这些颗粒物中有明显富集 ,特别是在PM2 .5 中的富集倍数达数十倍至数万倍 ,对人体健康有很大危害     

南京市PM2.5中金属元素污染特征及健康风险

监测分析了南京市浦口区典型工业区(2016年12月—2017年10月)PM 2.5中金属元素的浓度,分析了季节差异及来源,评价了健康风险。结果表明,PM 2.5年均值为61.24μg/m 3,全年有33.33%的天数超过《环境空气质量标准》(GB 3095—2012)的日均限值。绝大多数金属元素的平均值为:冬季>春季>秋季>夏季。As的全年平均值为(2.01±1.09)ng/m 3,较为接近我国环境标准限值。PM 2.5中金属元素主要来自工业排放、自然过程、金属冶炼及交通活动,Cr、Ni、As、Cd、Cu、Zn和Pb的富集性较高。健康风险评价结果显示,Mn的非致癌风险最高,所有金属对儿童和成人的总非致癌风险值为0.0884,低于安全阈值1;Cr(Ⅵ)的致癌风险最高,所有金属对儿童和成人的总致癌风险分别为6.23×10-7和2.49×10-6,均在可接受水平内。     

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。     

四城市空气粗、细颗粒物元素质量谱及富集特征

以武汉市 X荧光光谱分析数据为例 ,介绍了粗、细颗粒物中元素的质量谱及富集特征。并且 ,比较了广州、武汉、兰州、重庆四城市的污染元素及可能污染元素的某些富集特征     

一次连续在线观测分析天津市细颗粒物污染特征

根据2005年的5月17日—5月23日GR IMM(1.109#)谱分析仪在线观测结果考察天津市细颗粒物浓度和质量浓度特征。观测期间,天津市颗粒物数浓度平均值为1 124 cm-3,粒径分布为0.25μm~0.60μm,98.5%粒子的粒径0.65μm。同期PM10日均质量浓度值为204μg/m3,ρ(PM2.5)为104μg/m3,ρ(PM1.0)为82.9μg/m3。ρ(PM1.0)/ρ(PM2.5)超过80%,粒径1μm超细颗粒物为天津城市大气颗粒物的主要成分。     

上海浦东新区城区大气PM2.5中水溶性离子污染特征研究

为研究大气中细颗粒物(PM2.5)在中低浓度水平下的污染特征及来源,于2018-2020年在上海市浦东新区采用在线气体组分及气溶胶监测系统对大气ρ(PM2.5)及其水溶性离子的质量浓度进行了在线连续观测.结果表明,2018-2020年ρ(PM2 5)变化总体均呈现冬季较高,春、秋季其次,夏季较低的特征.PM2.5中水溶...     

2013-2018年北京市PM2.5污染波动特征研究

利用2013—2018年北京市大气污染物监测数据及气象条件等资料,分析了北京市PM_(2.5)污染波动变化趋势及其影响因素。结果表明,2013—2018年北京市空气质量呈现整体改善趋势,优良天数由2013年的176 d增加至2018年的227d;重污染天数显著减少,由2013年的58 d逐年递减至2018年的14 d。受污染源排放、特殊气候现象、气象条件等多因素影响,近6年北京市ρ(PM_(2.5))月均值呈现波动下降趋势,其中秋、冬季波动性更加突显。2014—2016年北京市秋冬季PM_(2.5)污染突出,其中2014年10月、2015年11—12月、2016年12月ρ(PM_(2.5))月均值均达到中度污染级别;而2017—2018年北京市秋、冬季ρ(PM_(2.5))月均值均处于优良水平。相关性分析结果显示,地面相对湿度、中层温度与大气污染物呈现较强的正相关性,中层北风频率、地面风速则呈现负相关性。基于上述气象条件及CO、SO_2和NO_2等气态污染物共同构建的拟合方程对ρ(PM_(2.5))估算结果较好,多站点的拟合值与实际值的相关系数为0.900～0.947,进一步说明气象条件及相关污染源排放对PM_(2.5)污染具有显著影响。     

上海市浦东新区大气细颗粒物中重金属污染特征及来源解析

于2017年对浦东城区和郊区大气PM2.5中的重金属特征和来源进行了分析。结果表明,K、Fe、Na、Ca、Mg、Al等矿物元素为浦东新区PM2.5中含量最高的金属元素,其中K的年均值为297.3 ng/m^3。浦东城区的不同元素在季节变化上呈现较为不同的变化规律,郊区的金属元素值大部分呈现春季先逐月下降,在夏、秋季有起伏波动,在10月之后逐渐上升;沙尘+道路源+建筑扬尘、煤燃烧、工业排放、金属冶炼、船舶排放、海盐+垃圾焚烧+生物质燃烧为浦东城区PM2.5中重金属元素的6大类主要来源。其中沙尘+道路源+建筑扬尘对Ca的贡献率为82.7%,煤燃烧对As的贡献率为86.6%,工业排放对SO4^2-的贡献率达到65.9%,金属冶炼对Cr的贡献率为75.7%,船舶排放对V的贡献率为97.5%、海盐+垃圾焚烧+生物质燃烧对Cl^-的贡献率为93.0%。煤燃烧和金属冶炼主要来自于西部方向。船舶排放分布在长江口及其延伸带。浦东新区PM2.5中重金属元素的质量浓度与本地源排放强度、外界传输和大气扩散条件均有密切关系。     

克拉玛依市大气PM2.5、PM10污染水平浅析

根据从2012年1月1日至2012年3月30日在同一个监测点取得的PM2.5和PM10监测数据,分析采暖期颗粒物污染水平特征。结果表明,PM2.5浓度和PM10浓度之间高度线性相关;克拉玛依市冬季空气环境中PM2.5是PM10中的主要组成成分;PM2.5浓度在一天内基本保持稳定,而PM10浓度在一天之中的变化幅度较大,峰值出现在中午上下班高峰期。     

乌鲁木齐市冬季重污染天气下PM_(2.5)中重金属污染特征及来源解析

通过乌鲁木齐市2013年2月5日至26日一次重污染天气过程中,在6个采样点位进行细颗粒物PM_(2.5)的采集,并对其中的13种重金属(Cu、Sr、Mo、Cd、Pb、V、Cr、Mn、Fe、Co、Ni、As、Hg)含量、Mull污染指数、空间分布以及溯源进行了分析。结果显示:采样期间乌鲁木齐市重金属浓度在0.23~178 ng/m~3之间,浓度水平排序PbMnCrFeAsVCuNiSrCdMoCoHg,其中Cd、Hg、Pb、Cr、As浓度均高于乌鲁木齐市背景值和国内外其他城市水平,且Mull污染指数处于较严重的污染水平;在重金属元素浓度的空间分布上,铁招和南公园点位重金属浓度较高,31中学和市监测站相对较低。     

重庆空气重点控制有毒物质筛选

借鉴国外经验 ,建立了适合重庆地区特点的空气重点控制有毒物质筛选体系 ,筛选原则、程序和方法 ,确定了有毒物质的评分标准和量化处理手段 ,取得了较好的效果。     

Atmospheric PAH concentrations in fine and coarse particles

Measurements of the urban air concentrations of PAHsassociated with PM2.5-fine and PM10-coarse particles inChicago on the campus of IIT were achieved using a UniversalAir Sampler. Short sampling time (12 hr) and high flowrates were used to measure the PAH concentrations in fineand coarse particles. Measured ambient concentrations ofPAHs were classified based on wind direction and backtrajectory calculations as Land and Lake samples.Differences in ambient concentrations of PAHs were observedbetween Land and Lake samples. Fine particle concentrationsvaried from 9.5 to 25.7 ng m^-3 and averaged18.2 ng m^-3 for the Land samples, while they ranged from4.2 to 31.5 ng m^-3 and averaged 13.4 ng m^-3 for the Lake samples. The measured PAH concentrationsin coarse particles varied from 6.2 to 22.1 ng m^-3 and averaged 12.9 ng m^-3 for the Land samples, andthey ranged from 2.4 to 13.0 ng m^-3 with an average value of 7.3 ng m^-3 for the Lake samples. The fine/coarse ratio of each individual PAH compound varied between1.3 and 2.7 for the Land samples; it varied between 1.6 and 4.2 for the Lake samples. There was an increase in the fine/coarse ratio of PAH as molecular weight of the compound increases for both Land and Lake samples.     

长沙市环境空气污染状况、原因分析和控制对策探讨

应用多年的环境监测数据,对长沙市环境空气污染状况、原因进行了较详细的分析和探讨.长沙市环境空气主要污染物是二氧化硫和尘类污染.并对上述两项污染物的控制提出了切实可行的方案.     

Spatial & temporal variations of PM10 and particle number concentrations in urban air

The size of particles in urban air varies over four orders of magnitude (from 0.001 μm to 10 μm in diameter). In many cities only particle mass concentrations (PM10, i.e. particles <10 μm diameter) is measured. In this paper we analyze how differences in emissions, background concentrations and meteorology affect the temporal and spatial distribution of PM10 and total particle number concentrations (PNC) based on measurements and dispersion modeling in Stockholm, Sweden. PNC at densely trafficked kerbside locations are dominated by ultrafine particles (<0.1 μm diameter) due to vehicle exhaust emissions as verified by high correlation with NOx. But PNC contribute only marginally to PM10, due to the small size of exhaust particles. Instead wear of the road surface is an important factor for the highest PM10 concentrations observed. In Stockholm, road wear increases drastically due to the use of studded tires and traction sand on streets during winter; up to 90% of the locally emitted PM10 may be due to road abrasion. PM10 emissions and concentrations, but not PNC, at kerbside are controlled by road moisture. Annual mean urban background PM10 levels are relatively uniformly distributed over the city, due to the importance of long range transport. For PNC local sources often dominate the concentrations resulting in large temporal and spatial gradients in the concentrations. Despite these differences in the origin of PM10 and PNC, the spatial gradients of annual mean concentrations due to local sources are of equal magnitude due to the common source, namely traffic. Thus, people in different areas experiencing a factor of 2 different annual PM10 exposure due to local sources will also experience a factor of 2 different exposure in terms of PNC. This implies that health impact studies based solely on spatial differences in annual exposure to PM10 may not separate differences in health effects due to ultrafine and coarse particles. On the other hand, health effect assessments based on time series exposure analysis of PM10 and PNC, should be able to observe differences in health effects of ultrafine particles versus coarse particles.     

突发性大气污染事故调查

对突发性大气污染事故带来的环境影响 ,进行大气污染物和生态环境监测调查 ,分析判断所受症状与污染物之间的对应关系 ,并对生态环境调查提出建议     

Assessment of air pollution from small scale industry

Air pollution due to small scale industries have been found tocause serious occupational health hazards and adverse effects on vegetation and heritage. The study for air pollution impactassessment for brick kiln industries was undertaken. The stackmonitoring exercise was carried out to estimate the pollution level of SPM, SO₂, and NO_x. The ambient air quality was also measured in the vicinity of brick kilns to assess the impact of stack emission on ground level concentration. Characterisation of SPM for toxic metals were studied. Modelling exercise was carried to predict the impact of emission of brick kiln on surrounding environment. To minimise the emission level and ground level concentration, airpollution mitigation measures are suggested.     

Distribution of PM2.5 and PM10-2.5 in PM10 Fraction in Ambient Air Due to Vehicular Pollution in Kolkata Megacity

This research paper aims at establishing baseline PM₁₀ and PM_2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM_2.5) and coarser fractions (PM_10-2.5) to PM₁₀ fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM₁₀ concentration was 304 μg/m³, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM₁₀ concentration was due to fine fraction (PM_2.5) released by vehicular exhaust. The 24h average PM_2.5 concentration was found 179 μg/m³, which is exceeded USEPA and EU standards of 65 and 50 μg/m³ respectively for the winter. India does not have any PM_2.5 standards. The 24 h average PM_10-2.5 concentrations were found 126 μg/m³. The PM_2.5 constituted more than 59% of PM₁₀ and whereas PM₁₀-PM_2.5 fractions constituted 41% of PM₁₀. The correlation between PM₁₀ and PM_2.5 was found higher as PM_2.5 comprised major proportion of PM₁₀ fractions contributed by vehicular emissions.