乌鲁木齐采暖期4种颗粒物质量浓度比对研究

本研究以乌鲁木齐工业区、交通区、生活区、风景对照区4个典型区域为研究对象,采集了采暖期大气颗粒物TSP、PM10、PM5、PM2.5,并对其进行质量浓度分析。结果表明:在采暖期大气中TSP的浓度范围为87.94~325.61ug/m3;PM10的浓度范围为76.69~299.21ug/m3;PM5的浓度范围为79.68~294.95ug/m3;在PM2.5的浓度范围为71.80~213.30ug/m3。总体来看,乌鲁木齐采暖期TSP、PM10、PM5、PM2.5的浓度存在一定的差异性,各组分浓度分布为工业区交通区生活区风景对照区,这与采样区受污染程度有关。     

兰州市大气颗粒物污染特征分析

对兰州市2011—2012年大气颗粒物污染状况进行了研究,在主导风向上设置采样点,分别连续监测PM10、TSP、风速、能见度。结果表明,兰州市颗粒物浓度的峰值出现在2—4月,TSP浓度最大值可达到2.465 mg/m3,PM10最大值可达到2.079 mg/m3;颗粒物污染的季节性强,以3、4月出现的频率最高,发生时间具有随机性;2012年兰州市全年颗粒物(PM10和TSP)平均小时浓度值低于2011年,沙尘天气发生频次较2011年有所降低,环境空气质量有所改善。     

冬季大气中PM_(10)和PM_(2.5)污染特征及形貌分析

2008年冬季采集大气中PM10和PM2.5样品,利用SPSS软件进行分析。结果表明,PM10质量浓度在92.87～384.7μg/m3之间,平均值为201.09μg/m3,超标率71.43%。PM2.5浓度跨度为57.27～230.21μg/m3,平均值为133.82μg/m3,超标率89.47%。PM10和PM2.5空间分布略有差异。PM2.5/PM10在29.10%～94.76%之间,均值为66.55%。PM2.5与PM10质量浓度之间有显著相关性,相关方程:PM2.5=0.7993×PM10-55.984(R2=0.9524,置信度为95%)。通过颗粒物形貌分析,初步判定冬季大气主要污染源为燃煤和机动车尾气排放。     

重庆市春季不同功能区PM10中多环芳烃的污染特征

2012年4月在重庆市4个不同功能区连续10 d同步采集了大气PM10环境样品,利用气相色谱-质谱法分析测定美国环保局16种优控多环芳烃(PAHs).结果显示,在重庆主城区PM10中检测到16种优控PAHs,总浓度(∑PAHs)范围为31.68～ 189.31 ng/m3,平均浓度为108.05 ng/m3.各个功能区大气PM10中PAHs总浓度存在明显差别:交通区(沙坪坝七中)154.47 ng/m3＞工业区(大渡口区政府)132.92 ng/m3＞居民区(南岸工商大学)105.58 ng/m3＞对照区(缙云山风景区)39.16 ng/m3.根据典型污染来源中PAHs的特征比值综合判断,重庆市春季大气中PM10主要来源于燃煤和交通污染的混合源.     

典型矿业城市大气颗粒物水溶性离子分布特征

利用2014年7月和2015年1月在淮南市不同功能区采集的大气颗粒物样品，分析其水溶性离子时空和粒径分布特征。结果表明：夏季和冬季粗、细粒子中总水溶性离子质量浓度均值分别为（13.45±4.53）μg/m3、（27.81±17.65）μg/m3和（12.87±8.37）μg/m3、（85.08±35.41）μg/m3。淮南市大气颗粒物中主要的水溶性离子为Ca2+、NO-3和SO2-4。冬季各功能区PM2.5中总水溶性离子质量浓度普遍高于夏季。大气颗粒物中水溶性离子主要来源于土壤源、工业污染及二次转化，冬季二次污染源主要以流动源污染为主，而夏季流动源和固定源污染贡献接近。     

石家庄市春节期间大气颗粒物有机碳和元素碳的变化特征

为研究石家庄市大气颗粒物的污染特征及其来源,于2013年2月6—19日春节期间在石家庄市采集大气颗粒物TSP、PM10、PM2.5样品,对其有机碳、元素碳进行分析测定。结果表明,石家庄TSP、PM10、PM2.5日平均质量浓度分别为389、330、245μg/m3,颗粒物污染严重;碳组分在颗粒物中占有较大比重,且随着粒径的减少,碳组分比重逐渐增加;存在不严重的次生有机碳污染;OC与EC的相关系数较高,说明两者有较为相似的污染源,主要为燃煤、机动车排放源。各种气象条件对PM2.5、OC、EC浓度和OC/EC的变化都有不同程度的影响。     

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.     

宁波和温州地区夏季大气中不同粒径颗粒物特征分析

对宁波地区北仑和奉化站、温州地区乐清站3个监测点夏季TSP、PM10、PM2.5和PM1.0进行监测,测试分析各种粒径颗粒物浓度水平和粒径分布特征,并通过化学质量平衡(CMB)受体模型对颗粒物进行源解析。监测结果显示,夏季宁波、温州地区TSP和PM10日均浓度为0.049～0.134mg/m3和0.025～0.084mg/m3,均未超过我国环境空气质量二级标准;PM2.5日均浓度为0.007～0.069mg/m3,按美国2006年EPA最新标准限值0.035mg/m3衡量,奉化、乐清、北仑站的超标天数占总监测天数的比例分别为75%、40%和37.5%。粒径分布统计结果显示,3个监测站点PM10占TSP的比例为48.78%～86.96%;PM2.5占TSP的比例为33.33%～72.46%;奉化和乐清监测点PM10中PM2.5和PM1.0的比例平均值在50%以上。源解析结果显示,夏季TSP主要来源于土壤尘,其次是建筑尘和煤烟尘,其贡献率分别为40.70%～55.49%、9.62%～13.64%和5.85%～17.28%。     

淮安市区大气中颗粒物PM_(10)、PM_(2.5)污染水平

通过对淮安市大气颗粒物中PM10、PM2．5的监测与污染水平分析，得出了淮安市区PM10与PM2．5浓度呈冬秋季高，夏春季低的特征。PM2.5和PM10的比值范围在0．62～0．65之间，即PM2．5在PM10以下颗粒物中所占比例大约为63％。     

宁波市颗粒物中多环芳烃浓度水平、分布及来源分析

讨论了2003年宁波市颗粒物中多环芳烃浓度水平、分布及来源,结果表明,PM10中PAHS占TSP中总量的83%,PM2.5中的PAHS占TSP总量的54%,颗粒物中多环芳烃主要存在于小于10μm的颗粒中。颗粒物中多环芳烃季节变化特征明显,夏季最低,冬季最高。汽车尾气对PM10中多环芳烃的贡献率达56%,汽车尾气是颗粒物中多环芳烃的主要来源。     

Size distribution and seasonal variations of particle-associated organochlorine pesticides in Jinan, China

The concentrations of organochlorine pesticides (OCPs) in atmospheric particulate matter in Jinan, China, over the period from July 2009 to June 2010, were determined to study their pollution levels, compositions, size distribution and seasonal variations. All target compounds except endosulfan sulfate were detected. The annual average concentration of ∑18 OCPs was 92 ± 82 pg m(-3). Total HCH, total endrin, aldrin, endosulfan compounds and total DDT compounds were the primary components, accounting for approximately 27%, 20%, 16%, 14% and 10% of total OCPs, respectively. The annual mean ng g(-1) concentrations of ∑18 OCPs in PM(2.5), PM(5), PM(10) and TSP were 481 ± 190, 433 ± 161, 414 ± 158 and 264 ± 193, respectively, indicating that most OCPs tend to be strongly absorbed by fine air particles which were strongly related to a potential health risk. Distinct seasonal trends were found in OCPs concentrations with high concentrations appearing in November and March whereas low concentrations appeared in the summer, which were significantly positively correlated with particulate mass concentrations and Air Pollution Index (API). The high OCPs levels could be attributed to the seasonal usage, long-range atmospheric transport as well as adverse meteorological conditions.     

A Statistical Analysis of Particulate Data Sets for Jawaharlal Nehru Port and Surrounding Harbour Region in India

The concentrations of total suspended particulate matter (TSP) and particulate matter less than 10 microns (PM10) were measured at various locations in a Jawaharlal Nehru port and surrounding harbour region. Meteorological data was also collected to establish the correlation with air pollutant concentration. The results are analysed from the standpoint of monthly and seasonal variations, annual trends as well as meteorological effects. The monthly mean concentration of TSP was in the range of 88.2 to 199.3 microg m(-3). The maximum and minimum-recorded value of PM10 was 135.8 and 20.3 microg m(-3), respectively. The annual average concentration of PM10 was 66.1 microg m(-3). There are clear associations between TSP and PM10 data set at all the measured three sites with a correlation coefficient of 0.89, 0.69 and 0.81, respectively. PM10 data appears to be a constant fraction of the TSP data throughout the year, indicating common influences of meteorology and sources. Particle size analysis showed PM10 to be 47% of the total TSP concentration, which is lower than reported for industrial area and traffic junctions in Mumbai. Anthropogenic sources contribute significantly to the PM10 fraction in an industrial region, while contributions from natural sources are more in a port and harbour area. Statistical analysis of air quality data shows that TSP is strongly correlated with wind speed but weakly correlated with temperature. There appears to be a simple inverse relationship between TSP and wind speed data, indicating the dilution and transport by winds.     

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.     

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.     

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。     

乌鲁木齐市可吸入颗粒物水溶性离子特征及来源解析

采暖期时在乌鲁木齐市采集了环境空气中的可吸入颗粒物,对可吸入颗粒物质量浓度及8种水溶性离子的特征和来源进行了分析。结果表明,细粒子和粗粒子的月平均质量浓度分别是53.5～233.3μg/m3和38.9～60.9μg/m3;细粒子和粗粒子中水溶性离子主要由SO24-、NH4+和NO3-组成;粗粒子中NH4+与NO3-和SO24-的相关性分别是0.70和0.66,细粒子中NH4+与NO3-和SO24-的相关性分别是0.89和0.93,铵盐是乌鲁木齐可吸入颗粒物主要存在形式;煤烟尘是乌鲁木齐市采暖期可吸入颗粒物的主要来源。     

Airborne particulate matter and BTEX in office environments

Total suspended particulate (TSP), PM(2.5) and BTEX were collected in nine offices in the province of Antwerp, Belgium. Both indoor and outdoor aerosol samples were analysed for their weight, elemental composition, and water-soluble fraction. Indoor TSP and PM(2.5) concentrations ranged from 7-31 microg m(-3) and 5-28 microg m(-3), with an average of 18 and 11 microg m(-3), respectively. Of all the elements analysed in indoor TSP, more than 95% was represented by Al, Si, K, Ca, Fe, Cl and S, accounting for 12% of the TSP by mass. The other elements showed significant enrichment relative to the earth's crust. The water-soluble ionic fraction accounted for almost 30% of the sampled indoor TSP by weight, and was enriched by anthropogenic activities. It was shown that the indoor PM levels varied among the offices, depending on the ventilation pattern, location, and occupation density of the office. Indoor BTEX levels ranged together from 5-47 microg m(-3) and were considerably higher than the corresponding outdoor levels. It was observed that some recently constructed and renovated buildings were clearly burdened with elevated levels for toluene, ethyl benzene, and xylenes, while outdoor air was found to be the main source for BTEX levels at the 'older' offices.     

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。     

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。