Characteristics of Hazardous Airborne Dust Around an Indian Surface Coal Mining Area

Surface coal mining creates more air pollution problems with respect to dust than underground mining . An investigation was conducted to evaluate the characteristics of the airborne dust created by surface coal mining in the Jharia Coalfield. Work zone air quality monitoring was conducted at six locations, and ambient air quality monitoring was conducted at five locations, for a period of 1 year. Total suspended particulate matter (TSP) concentration was found to be as high as 3,723 μg/m³, respirable particulate matter (PM10) 780 μg/m³, and benzene soluble matter was up to 32% in TSP in work zone air. In ambient air, the average maximum level of TSP was 837 μg/m³, PM10 170 μg/m³ and benzene soluble matter was up to 30%. Particle size analysis of TSP revealed that they were more respirable in nature and the median diameter was around 20 μm. Work zone air was found to have higher levels of TSP, PM10 and benzene soluble materials than ambient air. Variations in weight percentages for different size particles are discussed on the basis of mining activities. Anionic concentration in TSP was also determined. This paper concludes that more stringent air quality standards should be adopted for coal mining areas and due consideration should be given on particle size distribution of the air-borne dust while designing control equipment.     

2008年春季呼和浩特沙尘天气与TSP和PM_(10)污染的关系

利用TSP和PM10逐时监测数据,对2008年春季呼和浩特市TSP和PM10浓度的变化及其在沙尘天气过程中的相关性进行了分析,结果表明:(1)2008年春季TSP和PM10浓度值多高于国家环境空气质量二级标准,沙尘天气是影响空气环境质量的主要诱因。(2)TSP和PM10浓度在沙尘暴发生当日及前后几天均会有不同程度的增加,且以沙尘天气发生当日浓度最大。TSP和PM10浓度3月份最低,4月份次之,5月份最高。(3)不同沙尘天气过程中,TSP和PM10浓度相差明显,且TSP与PM10/TSP值随沙尘天气强度的增加而增大,PM10在不同沙尘天气过程中均为主要组成成分。(4)沙尘天气过程中TSP与PM10呈线性相关。     

鞍山市TSP及PM10相关性分析研究

分别在冬季及夏季选取具有典型气候特性的天气,采集空气中TSP和PM10.根据采样前、后滤膜重量之差及采样标况体积,计算TSP质量浓度,分析了TSP和PM10在大气中污染状况,研究了TSP和PM10的相关性及PM10占TSP的比例,并得出结论:在冬、夏二季TSP和PM10的浓度值变化趋势非常相似,在冬季时TSP和PM10...     

TSP-PM10-PM2.5-2型中流量大气颗粒物采集系统的开发和应用

自行开发并研制了TSP-PM10-PM2.5-2型中流量TSP、PM10、PM2.5大气颗粒物采集系统,是目前中国唯一可以采集TSP、PM10、PM2.5样品并提供足够的样品量进行大气颗粒物化学成分分析的中流量大气颗粒物采集器.该系统精心设计和加工的限流孔可以保持完全固定的流量,保证切割粒径的稳定,减小采样的误差并方便操作.该系统已经成功地应用于20多个城市和地区大气颗粒物的监测和研究中,为研究大气颗粒物的污染状况和来源提供了有效的技术手段和支持.     

乌鲁木齐市冬季大气颗粒物PM_(10) 和PM_(2.5)污染水平及相关性研究

为研究乌鲁木齐市冬季采暖期间大气颗粒物污染特征,通过采样和在线监测二种手段分析了2015年1~2月大气颗粒物样品,采用重量法分析颗粒物质量浓度,并对其相关性进行分析。结果表明:依据《环境空气质量标准》(GB 3095-2012),采样期间乌鲁木齐市大气PM_(10) 和PM_(2.5)的日均质量浓度均超过了国家二级标准,颗粒物污染严重;PM_(10) 和PM_(2.5)存在显著相关性,PM_(2.5)和PM_(10) 浓度的比值均大于0.5,采暖期PM2.5对乌鲁木齐市大气颗粒物贡献显著。     

Multivariate Statistical Analysis of Meteorological and Air Pollution Data in the ‘Campo De Gibraltar’ Region, Spain

A complete statistical analysis of meteorological and air pollution data was carried out in the ‘Campo de Gibraltar’ region (in the South of Spain) from 1999 to 2002. This is a heavy industrialized area where, up to date, very few air pollution studies have been made. The main objectives of the study presented here have been the characterization of the meteorological and (gaseous and particulate) air pollution conditions in the area, and the relations between them. Multivariate statistical techniques, such as Principal Component Analysis (PCA), have been applied to the data. The results show that air quality in the area is highly dependent on meteorological conditions such as wind persistence and direction, dispersion capability of the atmosphere, and humidity content. On average, sulphur dioxide and nitrogen oxide air pollution, mainly caused by fuel-oil combustion and traffic, respectively, is not very high. However, an important number of exceedences of the limits established by the EU Directive 1999 for PM10 (particulate matter with a diameter less than 10 μm) have been observed in some points of the area. A significant percentage of these exceedences (about 22% on average) are likely caused by African dust intrusions, which usually take place from May to August. From gaseous and particulate air correlations, it seems that anthropogenic activities contribute with about 19% on average.     

南京市建筑扬尘排放清单研究

统计分析了2010年南京市各行政区建筑场地面积和工期,结合扬尘排放因子,建立了南京市建筑扬尘排放清单。研究表明,2010年南京市建筑扬尘TSP、PM10和PM2．5的排放量分别达2．53万t、1．40万t和0．95万t,占工业烟（粉）尘排放量的23％、13％和8．6％。郊区县建筑扬尘排放量较大,约占全市 TSP、PM10、PM2．5排放总量的72％;主城区排放强度较高。对不同建筑工程类型扬尘排放量估算表明,城市建设工程和市政工程是建筑扬尘的主要来源,城市建设工程中又以住宅类建设工程为主。对不同研究获得的建筑扬尘结果比较,发现扬尘排放因子选择和污染源活动水平统计是影响建筑扬尘结果的关键因素。     

库尔勒市大气颗粒物污染特征与影响因素分析

针对库尔勒市PM 10、PM 2.5年均浓度超标现象,基于市区3个环境监测站2013—2017年的逐时观测数据,分析PM 10、PM 2.5污染特征、成因及其主要影响因素。结果表明:①2013—2017年库尔勒市PM 10年均浓度变化较大且无明显趋势,PM 2.5年均浓度整体呈下降趋势;②季节尺度上,库尔勒市PM 10在每年2—5月呈现高浓度,PM 2.5高浓度期则为10月至翌年5月;③城郊的开发区站PM 10浓度最高,老城区的州政府站PM 2.5浓度最高,在PM 10和PM 2.5的高浓度期空间差异尤其显著;④PM 10与风速显著正相关,来自塔克拉玛干沙漠的风蚀沙尘颗粒物是库尔勒地区颗粒污染物的主要来源;⑤库尔勒市PM 10主要为外源输入,PM 2.5则以城市内源为主,相对湿度、风速、风向、温度等气象条件是影响大气颗粒物浓度及分布的重要因素。     

The Effect of Traction Sanding on Urban Suspended Particles in Finland

Springtime urban road dust forms one of the most serious problems regarding air pollution in Finland. The composition and origin of springtime dust was studied in southern Finland with two different methods. Suspended particles (PM10 and TSP) were collected with high volume particle samplers and particle deposition was collected with moss bags. The composition of the PM(1.5-10) fraction was studied using individual particle analysis with SEM/EDX. The deposition in the moss bags was analysed with ICP-MS. The results showed that during the study period, approximately 10% of both PM(1.5-10) particles and the deposition originated from sanding. Other sources in the springtime PM(1.5-10) were e.g. asphalt aggregate or soil and combustion processes. It can be concluded that sanding produced a relatively small amount of particulate matter under the investigated circumstances.     

Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

北京市主要PM10排放源成分谱分析

对北京市土壤尘、道路扬尘、城市扬尘、建筑施工尘、钢铁尘、煤烟尘等主要PM10无组织排放源和固定源进行采样、分析,建立相应的成分谱数据库,通过对其化学组分分析,确定各类PM10排放源的化学组分特征和标识元素。土壤尘、建筑施工扬尘、钢铁尘、煤烟尘PM10的标识元素分别为Si、Ca、Fe、Al,道路扬尘显示出明显的土壤尘、建筑施工尘和机动车污染的特征,城市扬尘成分谱与道路尘有很强的共线性,具有明显的道路扬尘特征。     

Monitoring of ambient particles and heavy metals in a residential area of Seoul, Korea

In this study, ambient TSP, PM10, and PM2.5 in a residential area located in the northern part of Seoul were monitored every other month for 1 year from April 2005 to February 2006. The monthly average levels of TSP, PM10, and PM2.5 had ranges of 71∼158, 40∼106, and 28∼43 μg/m³, respectively. TSP and PM10 showed highest concentration in April; this seems to be due to Asian dust from China and/or Mongolia. However, the fine particle of PM2.5 showed a relatively constant level during the monitoring period. Heavy metals in PM 10 and PM2.5, such as Cr, As, Cd, Mn, Zn and Pb, were also analysed during the same period. The monthly average concentrations of heavy metal in PM2.5 were Cr:1.9∼22.7 ng/m³; As:0.9∼2.5 ng/m³; Cd: 0.6∼7 ng/m³; Mn:6.1∼22.6 ng/m³; Zn: 38.9∼204.8 ng/m³, and Pb: 21.6∼201.1 ng/m³. For the health risk assessment of heavy metals in ambient particles, excess cancer risks were calculated using IRIS unit risk. As a result, the excess cancer risks of chromium, cadmium, and arsenic were shown to be more than one per million based on the annual concentration of heavy metals, and chromium showed the highest excess cancer risk in ambient particles in Seoul.     

辽宁省三城市大气颗粒物来源解析研究

针对辽宁省的沈阳、抚顺、葫芦岛三个城市的大气颗粒物来源,应用CMB化学质量平衡模型和二重源解析技术进行了定性和定量解析。识别各源类及其成分谱的特征,分析、比较大气颗粒物的时空分布特征,并计算三城市各源类在不同季节对城市大气颗粒物污染的贡献率,得到辽宁省城市大气颗粒物来源和季节分布特征的一般规律,说明城市扬尘、土壤风沙尘和煤烟尘是城市颗粒物的主要来源,应作为颗粒物污染治理的重点,而抚顺市特有的钢铁尘,葫芦岛市特有的锌尘等源类的污染也不容忽视。     

乌鲁木齐市可吸入颗粒物(PM10)与总悬浮颗粒物(TSP)的相关性规律浅析

通过对乌鲁木齐市的PM10和TSP数据的对比分析，找出PM10在TSP中所占比率（分担率）在采暖季和非采暖季的变化范围，从而使过去采集的TSP数据与PM10数据有一定的可比性，保证监测数据的连续可比。     

石家庄市大气颗粒物元素组分特征分析

为研究石家庄市大气颗粒物的污染特征及其来源,于2013年4—5月在主城6区分别采集TSP、PM10和PM2.5颗粒物样品,利用ICP-MS分析其中的22种元素浓度。结果表明,石家庄市城区Ca、Fe元素在各粒径颗粒物中含量都较高,PM2.5中的S、K含量较高,PM10和TSP中Mg、Al的浓度相对较高。颗粒物的主要来源为燃煤尘、道路尘和建筑尘,TSP、PM10和PM2.5具有较好的统计相关性和同源性。     

广州市PM_(10)与气象要素的关系分析

广州的PM10污染状况较为严重.PM10是大气颗粒物中对环境和人体健康危害最大的一类,PM10与医院就诊率、呼吸器官疾病发病率乃至死亡率等关系密切.PM10污染与气象条件关系密切,研究气象条件对PM10污染的影响,对改善城市空气质量条件有重要意义.文章利用2001～2004年广州市PM10和同期地面气象要素的监测资料,定量分析PM10与降雨量、相对湿度、平均温度和气压之间的关系:不同等级的降雨对PM10污染均有一定的清除作用;PM.0日平均质量浓度的改变量随着降雨量的增大而增大;1mm降雨量对PM10的清除能力按春、夏、秋、冬依次递增.春、夏、秋三个季节均为当日平均相对湿度低于季平均相对湿度时容易出现PM10污染天气,冬季则相反.春、秋两季均为当日平均气温在季平均值附近徘徊时,较易出现PM10污染,冬季则相反,夏季较少出现PM10污染.较高气压下PM10污染日的出现频率明显高于非污染日.     

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.     

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。     

平顶山市大气PM10、PM2.5污染调查

于2003年12月-2004年11月对平顶山市城区大气PM10、PM2.5污染进行了调查.结果表明,2004年大气PM10、PM2.5质量浓度分别为0.031 mg/m3～0.862 mg/m3、0.019 mg/m3～0.438 mg/m3;年均值分别为0.174 mg/m3、0.114 mg/m3,超标0.74倍、6.60倍.PM10、PM2.5污染的季节变化趋势是以冬季、春季高,秋季次之,夏季最低,细颗粒(PM2.5)约占PM10 65%;As、Pb、Cd、S、Zn、Cu、Mn、Ca等元素是颗粒物中主要污染元素,易在PM2.5中富集.平顶山市大气颗粒物污染的主要来源有煤炭燃烧、汽车尾气、城市基础建设和有色金属冶炼行业.     

Characteristics of aerosol types during large-scale transport of air pollution over the Yellow Sea region and at Cheongwon,Korea, in 2008

Episodes of large-scale transport of airborne dust and anthropogenic pollutant particles from different sources in the East Asian continent in 2008 were identified by National Oceanic and Atmospheric Administration satellite RGB (red, green, and blue)-composite images and the mass concentrations of ground level particulate matter. These particles were divided into dust, sea salt, smoke plume, and sulfate by an aerosol classification algorithm. To analyze the aerosol size distribution during large-scale transport of atmospheric aerosols, aerosol optical depth (AOD) and fine aerosol weighting (FW) of moderate imaging spectroradiometer aerosol products were used over the East Asian region. Six episodes of massive airborne dust particles, originating from sandstorms in northern China, Mongolia, and the Loess Plateau of China, were observed at Cheongwon. Classified dust aerosol types were distributed on a large-scale over the Yellow Sea region. The average PM10 and PM2.5 ratio to the total mass concentration TSP were 70% and 15%, respectively. However, the mass concentration of PM2.5 among TSP increased to as high as 23% in an episode where dust traveled in by way of an industrial area in eastern China. In the other five episodes of anthropogenic pollutant particles that flowed into the Korean Peninsula from eastern China, the anthropogenic pollutant particles were largely detected in the form of smoke over the Yellow Sea region. The average PM10 and PM2.5 ratios to TSP were 82% and 65%, respectively. The ratio of PM2.5 mass concentrations among TSP varied significantly depending on the origin and pathway of the airborne dust particles. The average AOD for the large-scale transport of anthropogenic pollutant particles in the East Asian region was measured to be 0.42 ± 0.17, which is higher in terms of the rate against atmospheric aerosols as compared with the AOD (0.36 ± 0.13) for airborne dust particles with sandstorms. In particular, the region ranging from eastern China, the Yellow Sea, and the Korean Peninsula to the Korea East Sea was characterized by high AOD distributions. In the episode of anthropogenic polluted aerosols, FW averaged 0.63 ± 0.16, a value higher than that in the episode of airborne dust particles (0.52 ± 0.13) with sandstorms, showing that fine anthropogenic pollutant particles contribute greatly to atmospheric aerosols in East Asia.