广州市空气可吸入性颗粒物的污染水平

报告了中美合作“广州市大气污染对儿童肺功能影响研究”课题可吸入性颗粒物的两年监测结果。用安德森双道采样器、Ｔｅｆｌｏｎ膜采集细颗粒物（＜２５μｍ,ＰＭ２５）和粗颗粒物（２５≤＜１０μｍ,ＰＭ２５１０）,两者之和为ＰＭ１０,每季度采１５天,每天采一个２４小时样品。结果表明,广州市城区大气可吸入性颗粒物的污染相当严重,尤其是细颗粒物（ＰＭ２５）的污染,应引起公众和政府有关部门的重视。     

环境空气PM_(2.5)和PM_(10)监测分析质量保证及其评价

为保证四城市ＰＭ２５和ＰＭ１０的监测数据准确,具有可比性,本研究规定了滤膜的选择、称量操作步骤的要求和滤膜称量的质控指标。研究结果表明,粗细颗粒物样品的采集和称量操作可行,监测数据准确、可靠,具有可比性。     

中国4城市空气颗粒物元素的因子分析

因子分析在研究空气颗粒物来源上得到了广泛的应用。本文应用最大方差旋转因子分析法对中国4城市空气中粗、细颗粒物元素的来源进行了分析。结果指出粗、细颗粒物因子大致可分为土壤源因子和工业污染源因子两大类。粗颗粒物主要来自土壤源,细颗粒物主要来自工业污染源,并指出土壤源因子对粗颗粒物的贡献大于对细颗粒物的贡献。     

兰州市气溶胶中金属与非金属元素的污染规律

通过对兰州市空气飘尘中粗、细颗粒物上化学元素的分布规律与特征的分析 ,指出了细颗粒物 (PM2 .5 )是一些有毒有害元素的主要携带者。这是可以在肺泡沉积 ,并能直接进入血液循环 ,对人体产生危害的重要部分     

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     

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。     

长江南京段近岸沉积物和土壤中重金属分布特征分析

通过测定沉积物和土壤中Cd、Pb、Cr、Zn、Cu、Ni 6种重金属元素的平均含量,计算其富集因子,分析长江南京段近岸沉积物和土壤中重金属的空间分布特征,结果表明,几种重金属在沉积物中的富集次序为:CdPbCr1NiCuZn,在土壤中为:CdZnCu1CrPbNi,除Zn和Cu外,其他几种金属在沉积物中的富集程度高于土壤,同时Cd的含量超过土壤环境质量三级标准。以Cd和Pb为例分析了重金属含量与沉积物粒级之间的关系,回归分析显示,Cd、Pb的含量与颗粒物的粒级呈显著的相关性,与细颗粒物的含量有密切关系,细颗粒携带的重金属,在长江水力分选作用下到达下游,成为沉积物中重金属的主要来源。     

环境空气中细颗粒物自动监测手工比对的质量控制

简述了国内、国际细颗粒物比对监测工作的概况,对南通市细颗粒物比对监测工作进行了分析,对目前细颗物比对监测过程中存在细颗粒物污染状况对数据有效性的影响,以及温、湿度对自动监测数据的影响等问题,提出了对策建议。     

2008年北京市PM_(10)的粒度分布分形维数变化特征

2007年11月-2008年10月间在北京市市中心和西北城区采集了不同季节的PM10样品,并借助扫描电子显微镜和图像分析软件对其进行粒度分布分形维数分析。结果表明,颗粒物中细颗粒物越多,粒度越细,则颗粒物粒度分布分形维数值越大。2008年西北城区的PM10的粒径分布分形维数较大,市中心的较小。市中心的粒度分布分形维数在1.95～2.59之间,各个季节的分形维数呈现冬季春季夏季秋季,西北城区的粒度分布分形维数在2.58～2.72,各个季节的分形维数呈现秋季夏季冬季春季,说明在市中区冬季PM10粒度较细,而在西北城区秋季的颗粒物偏细。与2005年同季相比,2008年的总体颗粒物和烟尘集合体的粒径分布分形维数较大,矿物颗粒的粒度分布分形维数较小,并且总分布的季节变化一致。2008奥运期间的PM10粒度分布分形维数在2.28～3.39之间变化,标志着颗粒物总体变细的趋势。     

株洲市某交通干道夏季细颗粒物分布特征及相关因素

2014年夏季采用扫描电迁移率粒径谱仪,选取株洲市某交通干道附近,对其环境细颗粒物进行连续测量,并统计干道的车流量。实验结果表明:环境中的细颗粒物数浓度呈双峰分布,峰值一般出现在9.47~17.5、98.2~121.9 nm粒径段,晴天和雨天不同粒径段的细颗粒物数浓度的波动性不一致,降水过程对细颗粒有一定的去除作用。结合所观测的机动车流量和所排放的细颗粒物粒径谱,分析其与细颗粒物浓度之间的关系,可初步判断该环境中爱根核模态的细颗粒物来源于机动车排放。     

克拉玛依市中心城区颗粒物中多环芳烃污染特征

在克拉玛依市中心城区布设4个采样点,在供暖期和非供暖期分别同步采集4个点位大气中不同粒径的颗粒物,采用HPLC进行分析并计算2个采样期内PM_(10)和PM_(2.5)中多环芳烃(PAHs)的浓度和种类。结果表明:中心城区供暖期PM_(10)中PAHs浓度为56.19 ng/m3,PM_(2.5)中PAHs浓度为48.85 ng/m3;中心城区非供暖期PM_(10)中PAHs浓度为18.86 ng/m~3,PM_(2.5)中PAHs浓度为14.53 ng/m~3。不同采样期PM_(10)和PM_(2.5)中PAHs浓度变化趋势相同,均为供暖期明显大于非供暖期。中心城区供暖期大气颗粒物吸附的PAHs以4环以下的组份为主,非供暖期则是5~6环的高环数组份偏多。分析结果表明克拉玛依市中心城区供暖期颗粒物中PAHs来源于燃煤排放叠加机动车排放,与中心城区集中供热锅炉关系密切;非供暖期则是以机动车排放污染为主。     

Particulate matter concentration in ambient air and its effects on lung functions among residents in the National Capital Region, India

The World Health Organization has estimated that air pollution is responsible for 1.4 % of all deaths and 0.8 % of disability-adjusted life years. NOIDA, located at the National Capital Region, India, was declared as one of the critically air-polluted areas by the Central Pollution Control Board of the Government of India. Studies on the relationship of reduction in lung functions of residents living in areas with higher concentrations of particulate matter (PM) in ambient air were inconclusive since the subjects of most of the studies are hospital admission cases. Very few studies, including one from India, have shown the relationship of PM concentration and its effects of lung functions in the same location. Hence, a cross-sectional study was undertaken to study the effect of particulate matter concentration in ambient air on the lung functions of residents living in a critically air-polluted area in India. PM concentrations in ambient air (PM_1, PM_2.5) were monitored at residential locations and identified locations with higher (NOIDA) and lower concentrations (Gurgaon). Lung function tests (FEV₁, PEFR) were conducted using a spirometer in 757 residents. Both air monitoring and lung function tests were conducted on the same day. Significant negative linear relationship exists between higher concentrations of PM₁ with reduced FEV₁ and increased concentrations of PM_2.5 with reduced PEFR and FEV₁. The study shows that reductions in lung functions (PEFR and FEV₁) can be attributed to higher particulate matter concentrations in ambient air. Decline in airflow obstruction in subjects exposed to high PM concentrations can be attributed to the fibrogenic response and associated airway wall remodeling. The study suggests the intervention of policy makers and stake holders to take necessary steps to reduce the emissions of PM concentrations, especially PM_1, PM_2.5, which can lead to serious respiratory health concerns in residents.     

Saharan dust contribution to PM₁₀, PM₂.₅ and PM₁ in urban and suburban areas of Rome: a comparison between single-particle SEM-EDS analysis and whole-sample PIXE analysis

From February 15th to April 15th 2009, a period characterised by two episodes of Saharan dust outbreaks in Italy, particulate matter (PM) samples were collected at two stations (urban and suburban) in Rome. Some samples were selected and analysed using the SEM-EDS technique to characterise PM, focussing especially on the mineral contribution. Samples were representative both of days affected by Saharan dust episodes and days without this contribution. Cluster analysis allowed the attribution of each of about 67,000 analysed particles to one of the seven main statistical groups based on their composition. Characteristics of the particulate components identified using SEM-EDS analysis were verified by PIXE analysis carried out on filters collected in a suburban area. Ultimately, the contribution of crustal particles was revealed to be consistently high, highlighting the importance of local and regional mineral contributions, as well as those of Saharan origin. Therefore, quantifying all mineral contributions to resuspended particulate could lead to significant reductions of the PM level also on days not influenced by Saharan dust, thus limiting conditions when PM?? daily limit value (DLV) established by European legislation is exceeded.     

Investigation into presence of atmospheric particulate matter in Marikana, mining area in Rustenburg Town, South Africa

An investigation to find out presence of particulate matter in Marikana, a mining area in Rustenburg town, South Africa, was carried out in the months of August and November of 2008. Samples were collected for measurements of particulate matter (PM) of particle diameters of PM10, PM2.5, and PM1. After gravimetric analysis of daily measurements, it was found that PM10 concentration values ranged between 3 and 9 ??g/m³, PM2.5 concentration values ranged between 16 and 26 ??g/m³, and PM1 concentration values ranged between 14 and 18 ??g/m³ for the month of August 2008. For the month of November, it was found that PM10 concentration values ranged between 2 and 8 ??g/m³, PM2.5 concentration values ranged between 0 and 5 ??g/m³, and PM1 concentration values ranged between 4 and 15 ??g/m³. This study was undertaken as preliminary work having in mind that mining activities could be emitting high levels of particulate matter in the atmosphere which might be degrading the quality of the air. It was observed, however, that the daily particulate matter especially of PM10 emitted were quite low when compared to laid down International Air Quality Standards. The standards did not give guidelines for particulate matter of diameter 2.5 ??m. It was concluded that particulate matter came from three major sources: platinum mining, domestic biomass burning, and traffic emissions due to fuel burning.     

Regulatory effects on particulate pollution in the early hours of Chinese New Year, 2015

Human activities are a key driver of air pollution, so it is hardly surprising that celebrations affect air quality. The use of fireworks contributes to high particulate concentrations in many parts of the world, with the Chinese Lunar New Year (spring festival) particularly noticeable, as firecrackers are traditionally used to drive off evil spirits. Fireworks lead to short-term peaks in the concentration of PM10, PM2.5 and SO₂. Regulatory actions that restrict the use of fireworks have been evident in China since the 1990s. This paper investigates the particulate concentrations in nine Chinese cities (Beijing, Chengdu, Chongqing, Tianjin, Xi’an, Nanjing, Shanghai, Guangzhou and Shenzhen, along with Hong Kong (a Special Administrative Region) and Taipei and Kaohsiung (Taiwan) with a particular focus on the celebrations of 2015. Extremely high concentrations of particulate matter were observed, with some sites revealing peak PM10 concentrations in excess of 1000 μg m^?3 in the early hours of the New Year. In Beijing, Tianjin and Chongqing, the activities caused high particulate matter concentrations at most sites throughout the city. These peaks in particulate load in the early hours of Chinese New Year do not appear to be closely related to meteorological parameters. However, in cities where fireworks appear to be better regulated, there are fewer sharp pollution peaks just after midnight, although lowered air quality can still be found in the outer parts of some cities, remote from regulatory pressures. A few cities seem to have been effective at reducing the impact of the celebrations on air quality, with Nanjing a recent example. An increasing focus on light displays and electric lanterns also seems to offer a sense of celebration with much reduced impacts on air quality.     

Hydroxyl radical generation by electron paramagnetic resonance as a new method to monitor ambient particulate matter composition

Epidemiological studies have demonstrated the relationship between exposure to ambient particulate matter (PM) and health effects in those with cardiopulmonary diseases. The free radical generating activity of particles has been suggested as a unifying factor in the biological activity of PM in toxicological studies but so far has not been applied as a method for environmental monitoring of PM. The purpose of this study was to characterize hydroxyl radical (OH*) production by different size fractions of PM, to use as an alternative method for monitoring of PM composition and activity. We have developed a method, using electron paramagnetic resonance (EPR), to measure OH* radical formation in suspensions of particles in the presence of hydrogen peroxide and 5,5-dimethyl-1-pyrroline-N-oxide (DMPO) as a specific spin-trap. Samples of ambient particulate matter (PM) of different size fractions were collected from various sites on various filters. PM deposited on filters as well as suspensions in water retain its ability to generate OH* and this generation is determined by concentration of hydrogen peroxide and soluble metals. However, large variations in OH* radical formation and kinetics were found with different soluble metals and within metals (Fe, V) with different valencies. The method was applied to environmental monitoring in Hettstedt-Zerbst, situated in South-Eastern Germany, where it showed a relation to Cu-content of PM. The method was also applied in Duisburg, where the PMI fraction showed the highest DMPO-OH* generation but was not linked to particle counts. The method integrates metal bioavailability and reactivity and can provide a better understanding of the effect of small variations in mass concentrations on health.     

灰霾天气不同粒径的颗粒物污染特征分析

利用宁波市北仑区PM10、PM2.5和PM1的监测数据及与之对应的能见度监测结果,对影响灰霾天的颗粒物的污染特征进行了系统研究,结果表明,颗粒物粒径对灰霾天的形成和能见度的影响程度差异明显,且3种粒径的颗粒物质量浓度与能见度之间线性关系密切。     

Monitoring of cotton dust and health risk assessment in small-scale weaving industry

The present study describes the estimation of particulate matter (cotton dust) with different sizes, i.e., PM(1.0), PM(2.5), PM(4.0), and PM(10.0 μm) in small-scale weaving industry (power looms) situated in district Hafizabad, Punjab, Pakistan, and the assessment of health problems of workers associated with these pollutants. A significant difference was found in PM(1.0), PM(2.5), PM(4.0), and PM(10.0) with reference to nine different sampling stations with p values <0.05. Multiple comparisons of particulate matter with respect to size, i.e. PM(1.0), PM(2.5), PM(4.0), and PM(10.0), depict that PM(1.0) differs significantly from PM(2.5), PM(4.0), and PM(10.0), with p values <0.05 and that PM(2.5) differs significantly from PM(1.0) and PM(10.0), with p values <0.05, whereas PM(2.5) differs non-significantly from PM(4.0), with a p value >0.05 in defined sampling stations on an average basis. Majority of the workers were facing several diseases due to interaction with particulate matter (cotton dust) during working hours. Flue, cough, eye, and skin infections were the most common diseases among workers caused by particulate matter (cotton dust).