鞍山市环境空气颗粒物中重金属元素分布特征

研究了鞍山市环境空气中可吸入颗粒物(PM10和PM2.5)中重金属元素分布特征,结果表明鞍山市环境空气可吸入颗粒物中Zn、Pb、Al、Cu四种金属总和所占21种元素比例近85%。重金属元素在不同粒径颗粒物中的浓度水平有明显差别,更易富集在细颗粒物PM2.5上。     

PM<Subscript>10</Subscript> and Ultrafine Particles Counts In-Vehicle and On-Road in the Athens Area

This work presents the first results of a study concerning on-road and in-vehicle exposure to particulate matter in the area of Athens. PM₁₀ concentration measurements were conducted by TSI DustTrak, while driving along routes with different characteristics of traffic density, during September 2003–March 2004. Concurrent measurements of the ultrafine particles (UFPs) number concentration were also conducted, by condensation particle counter during part of the days. Pedestrian exposure to PM₁₀ and UFPs was also studied through stationary measurements on the kerbside of selected roads on November 2003 and February 2004. A major avenue, a heavy-trafficked road across a children hospital and two central roads, one in a residential and one in a commercial area were selected for measurement. The results indicate that every day commuters are exposed to significant concentration levels. Higher exposures were observed in heavy-trafficked areas and during rush hours. Mean PM₁₀ in-vehicle and on-road concentrations ranged from 30–320 μg/m³ and 70–285 μg/m³, respectively. The ultrafine particles number concentrations were in the range of 5.0 × 10⁴–17.3 × 10⁴ particles/cm³ in-vehicle and 3.1 × 10⁴–7.3 × 10⁴ particles/cm³ on the kerbside of a central residential road. Both PM₁₀ and UFPs concentrations presented repeated short-term peak exposures. The results clearly point out the importance of the road microenvironment (in-vehicle and on kerbside) for population exposure in urban areas.     

The sustainability of China's major mining cities

The aim of this paper is to identify principal factors controlling the Degree of Sustainable Development of Mineral Resources (DSDMR) of mining cities and then to measure their DSDMR and reveal their developing trends. To do this, 78 Chinese mining cities are used as an example. These cities are classified on a hierarchical level of the DSDMR in order to support decision-making of sustainable development. Six principal factors controlling the DSDMR are recognized using factor analysis. They are used to measure the DSDMR of the Chinese mining cities and their developing trends. The results show that in terms of the type of mineral resources, the DSDMR decreases from petroleum to multi-resources to non-metal to coal to metal cities. It decreases also from middle to old to young aged cities and from eastern to central to western cities in geographical location. In addition, large and very large cities have higher DSDMR values than middle- and small-sized cities. These Chinese mining cities are classified into six clusters by cluster analysis, which forms the basis for policy making.     

西安市环境空气PM2.5污染现状及对策初探

文章通过对西安市城市环境空气PM_2.5试点监测数据深入分析,初步摸清了区域PM_2.5污染水平及分布规律,提出了污染防治对策和建议,对现阶段的环境空气PM_2.5污染防治有着重要的参考价值。     

杭州市大气PM2.5和PM10污染特征及来源解析

2006年在杭州市两个环境受体点位采集不同季节大气中PM2.5和PM10样品,同时采集了多种颗粒物源类样品,分析了其质量浓度和多种化学成分,包括21种无机元素、5种无机水溶性离子以及有机碳和元素碳等,并据此构建了杭州市PM2.5和PM10的源与受体化学成分谱;用化学质量平衡(CMB)受体模型解析其来源。结果表明,杭州市PM2.5和PM10污染较严重,其年均浓度分别为77.5μg/m3和111.0μg/m3;各主要源类对PM2.5的贡献率依次为机动车尾气尘21.6%、硫酸盐18.8%、煤烟尘16.7%、燃油尘10.2%、硝酸盐9.9%、土壤尘8.2%、建筑水泥尘4.0%、海盐粒子1.5%。各主要源类对PM10贡献率依次为土壤尘17.0%、机动车尾气尘16.9%、硫酸盐14.3%、煤烟尘13.9%、硝酸盐粒8.2%、建筑水泥尘8.0%、燃油尘5.5%、海盐粒子3.4%、冶金尘3.2%。     

广州市灰霾期PM10的化学组成对能见度的影响

采集广州市大气可吸入颗粒物(PM10)样品,并分别对冬、夏两季灰霾和非灰霾期PM10中有机碳(OC)、元素碳(EC)和水溶性离子进行分析。广州市灰霾期大气PM10中的主要化学成分按质量浓度大小排序为OC>NO3->SO24->NH4+>EC(非灰霾期则依次为OC>SO24->EC>NH4+>NO3-),其质量浓度分别为非灰霾期的4.7、12.5、3.7、3.2和2.3倍。相关性分析表明,灰霾期总碳[TC(OC+EC)]及NO3-的质量浓度对大气能见度的降低起主要作用,而非灰霾期则主要是TC和SO24-。     

遵义市PM10中元素污染特征、来源与生态风险评价

采集2012年3月-2013年2月遵义市丁字口（市区点）、凤凰山（背景点）监测点的 PM10样品,并对 PM10中元素污染特征、来源和生态风险进行分析与评价。结果表明,遵义市 PM10质量浓度季节变化为：冬季＞春季＞秋季＞夏季,且市区点高于背景点,冬季超标率均为100％。PM10中 As、Pb、Hg、Mn质量浓度市区点高于背景点,且均为冬季最高。富集因子分析表明,Pb、As、Cd、Hg、Mn、Cu、Zn来自人为污染,生态危害顺序为：Cd＞Pb ＞As＞Cu ＞Zn ＞Ni ＞Cr,其中 Cd 的潜在生态危害为极强。     

空气自动监测中PM2.5与PM10 “倒挂”现象特征及原因

采用不同原理的自动监测仪器在不同季节同时测定PM2.5与PM10,对所得数据中的PM2.5与PM10"倒挂"现象进行分析。结果表明,当PM10采用振荡天平法时,PM2.5与PM10的"倒挂"率较高;冬季和夏季"倒挂"现象发生率明显高于其他季节;造成PM2.5与PM10"倒挂"的原因主要有监测过程中的随机误差,PM2.5与PM10的监测方法原理不同,监测方法之间存在显著差异等。     

2015年新疆阿克苏市沙尘污染与气象因素关系的分析

应用阿克苏市国家基准站及2个环保局监测站2015年大风沙尘天气过程前后PM10浓度变化及其与污染源、NECP全球再分析资料、风、监测站周边环境等关系进行分析.结果表明,阿克苏市春季沙尘天气的首要污染物均为PM10,PM10的变化曲线呈正态分布,春季中度及以上污染日均出现在污染日当日或次日.造成阿克苏市沙尘天气污染源分本地型、外来型以及二者共同影响型三种.本地型沙尘污染强度取决于北风风速大小及强风持续时间,PM10浓度变化与风速呈正相关.而外来型污染多发生在本地型沙尘天气之后,"东灌"冷空气裹挟沙尘进入南疆盆地,造成地面加压,浮尘天气造成PM10浓度增大,并持续数天.总结出沙尘天气污染预警的几个必要条件,后续在地区环保局、县局监测站建立的情况下,为分析阿克苏地区"八县一市"污染物与气象因素的关系提供借鉴,同时为实际的空气质量预警提供参考.     

河南省五城市环境空气PM_(10)手工标准方法与自动监测法比对分析

在焦作、安阳、开封、三门峡、信阳5个城市开展PM_(10)手工标准方法和自动监测法比对实验,并用相关性和相对偏差对比对结果进行分析和评价。结果表明:12015年5个城市采集的PM_(10)手工和自动监测值均具有良好的相关性。22015年5个城市采集的PM_(10)手工和自动监测值的相对偏差为-19.1%~9.68%;负偏差数据占总数据量的75%。3PM_(10)手工和自动监测值|RD|平均值在中浓度下最小,高浓度下最大,低浓度介于二者之间,说明在高浓度和低浓度时PM_(10)的监测数据质量尤其值得关注。