上海市城区典型居民住宅区PM2.5和PM10监测结果比较研究

在上海市环境空气质量连续自动监测网络中的一个城市居民住宅区监测点进行了为期一年的PM2.5和PM10的同步监测，监测结果表明：PM2.5和PM10日平均浓度之间的比值范围为0．194～0．889，月平均浓度之间的比值范围为0．420～0．667；冬季颗粒物中小粒径颗粒物PM2.5的比例较高，春季则较低；随着相对湿度的上升；颗粒物中小粒径颗粒物PM2.5的比例缓慢升高；比值变化的风向特征与监测点周围环境情况有关；PM2.5和PM10监测结果月均值之间和各月的日均值之间均线性相关，回归直线关系存在。     

燃煤电厂烟气颗粒物分级测定与分析

采用分级撞击采样器(DPI)对燃煤电厂烟气颗粒物测定并分析,试验表明,PM10、PM2.5及PM1在湿除出口/烟囱入口的质量浓度分别为0.26 mg/m3~1.47 mg/m3、0.22 mg/m3~1.29 mg/m3、0.17 mg/m3~1.00 mg/m3。分析可知,除尘器后烟气颗粒物PM10中主要是PM2.5,而PM2.5~10占比低于35%;烟气经湿法脱硫后,PM2.5~10的比例进一步大幅降低,经湿式除尘器后,PM2.5~10的占比变化很小,而PM1~2.5的占比大幅降低。监测结果表明,湿式除尘器对烟气颗粒物的脱除效果优于湿法脱硫,而随着颗粒物粒径的减小,2种脱除设备的脱除效率均出现降低。     

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。     

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.     

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。     

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。     

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。     

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.     

大连市区大气气溶胶的无机化学特征分析

通过对大连市的两个采样点从2002年4月至12月三个期间的气溶胶的三种粒径的采样分析,结果表明,大连市区气溶胶中PM10质量浓度约占TSP的50%,PM2.5质量浓度约占TSP的30%;8种可溶性离子在不同粒径气溶胶中所占的比例,随着粒径的减小而增大,冬季的SO42-、NO3-、NH4 在各种粒子中含量高于夏季,沙尘暴期间各种可溶性离子在不同粒径颗粒物中的含量较低;11种常见元素在细粒子中的含量比粗粒子中的含量高,春季各种粒子中的元素含量要高于冬季.     

西宁市典型开放源颗粒物粒径组成特征分析

采用BT-9300S激光粒度仪分析了西宁市道路尘、扬尘、土壤尘、建筑尘4种典型开放源的粒径组成。结果表明,4种类型尘中大粒径颗粒物占主导地位,粒径大于10 μm颗粒占到全部颗粒的73.80%以上,可吸入颗粒物的含量仅占7.06%～26.20%;建筑尘的细颗粒物含量最高,粒径小于2.5、1 μm的颗粒含量分别为8.36%±4.25%、2.42%±1.02%;道路尘的细颗粒物含量最低,粒径小于2.5、1 μm的颗粒含量分别为2.30%±0.94%、0.73%±0.28%;4种类型尘的体积平均直径、面积平均直径、中位直径分别在37.70～87.99 μm、8.50～23.53 μm、28.95～74.98 μm之间,其中道路尘的3种粒径参数最大,建筑尘最小;开放源颗粒物的粒度分布曲线主要呈头长尾短的不对称单峰分布,累积频率曲线为两段式,存在较为明显的拐点。     

桂林市细颗粒物部分典型排放源的粒径谱及成分分析

采用在线单颗粒气溶胶质谱技术源解析方法,对桂林市PM2.5典型排放源的粒径和化学成分进行质谱分析,采集燃煤/燃气源、工业工艺源、扬尘源、油烟源4类共计7个典型排放源。结果表明,桂林市4类排放源细颗粒物的粒径分布为0.25~1.25μm,80%以上的细颗粒分布在0.2~1.0μm的小粒径范围,峰值约0.68μm。细颗粒物离子成分含有Na~+、Mg~+、K~+、NH~+4、Fe~+、Pb~+、Cd~+、V~+、Mn~+、Li~+、Al~+、Ca~+、Cu~+、Zn~+、Cr~+、CN~-、PO_3~-、NO_2~-、NO_3~-、Cl~-、SO_4~(2-)、SiO_3~-等成分,桂林市细颗粒物为元素碳、有机碳元素碳、有机碳、富锰颗粒、富铁颗粒、富钾颗粒、矿物质、左旋葡聚糖以及其他金属等9类。     

南京市冬季大气颗粒态汞的分布特征

采集了南京市2012年冬季4个功能区的PM2．5、PM10、TSP样品，对不同粒径大气颗粒物中的颗粒态汞测试。结果表明，南京冬季大气颗粒物TSP中汞的质量浓度为49．26 pg/m3～257．14 pg/m3，平均质量浓度为161．27 pg/m3；PM10中汞的质量浓度为44．82 pg/m3～228．29 pg/m3，平均质量浓度为147．38 pg/m3；PM2．5中汞的质量浓度为35．98 pg/m3～178．58 pg/m3，平均质量浓度为104．10 pg/m3。不同功能区大气颗粒态汞质量浓度的分布趋势为：交通综合区＞旅游区＞住宿综合区＞商业区。大气颗粒态汞60％以上存在于可吸入肺的PM2．5中，细颗粒物富集汞的能力比粗颗粒物强。     

青岛市区春夏季大气能见度与颗粒物的关系

利用青岛市灰霾综合观测站2012年3月2日-2012年6月7日期间的监测数据,分析了青岛市区大气能见度与不同粒径颗粒物质量浓度的日变化特征,比较了各级别大气能见度下不同粒径颗粒物质量浓度及所占比例的相关性,研究了相对湿度对大气能见度和颗粒物质量浓度相关性的影响.结果表明,监测时段大气能见度与颗粒物质量浓度呈现较好的负相关,每天大气能见度最低值出现在早晨07:00--09:00;剔除相对湿度高于90％的前提下,PM2.5是影响大气能见度的主要因子,随着其在PM1o中所占比例上升,大气能见度级别不断下降,相关系数为-0.84;不同相对湿度区间下,PM2.5对大气能见度的影响最明显,其中,相对湿度为60％ ～ 70％,大气能见度与颗粒物质量浓度之间的相关性最好.     

沈阳市大气中PM2.5来源解析研究

通过2015年在沈阳市采集PM2.5样品及源类样品,分析样品的质量浓度和化学组成,用化学质量平衡(CMB)模型对该市PM2.5来源进行解析。结果表明:沈阳市大气中PM2.5浓度时空变化特征明显;各主要源类对沈阳市PM2.5的分担率依次为煤烟尘(28.03%)、二次无机离子(22.63%)、机动车尾气尘(17.27%)、城市扬尘(13.28%)、建筑尘(5.94%)、土壤风沙尘(5.82%)、道路尘(3.04%)、生物质燃烧尘(2.74%)和冶金尘(1.25%)。燃煤和机动车的有效控制既能降低本类源的贡献,也能降低二次无机离子,体现了多源类综合治理原则。     

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.     

Characterization of ionic composition of TSP and PM10 during the Middle Eastern Dust (MED) storms in Ahvaz, Iran

Because of the recent frequent observations of major dust storms in southwestern cities in Iran such as Ahvaz, and the importance of the ionic composition of particulate matters regarding their health effects, source apportionment, etc., the present work was conducted aiming at characterizing the ionic composition of total suspended particles (TSP) and particles on the order of ～10?μm or less (PM(10)) during dust storms in Ahvaz in April-September 2010. TSP and PM(10) samples were collected and their ionic compositions were determined using an ion chromatography. Mean concentrations of TSP and PM(10) were 1,481.5 and 1,072.9?μg/m(3), respectively. Particle concentrations during the Middle Eastern Dust (MED) days were up to four times higher than those in normal days. Ionic components contributed to only 9.5% and 11.3% of the total mass of TSP and PM(10), respectively. Crustal ions were most abundant during dust days, while secondary ions were dominant during non-dust days. Ca(2+)/Na(+) and Cl(-)/Na(+) ratios can be considered as the indicators for identification of the MED occurrence. It was found that possible chemical forms of NaCl, (NH(4))(2)SO(4), KCl, K(2)SO(4), CaCl(2), Ca(NO(3))(2), and CaSO(4) may exist in TSP. Correlation between the anionic and cationic components suggests slight anion and cation deficiencies in TSP and PM(10) samples, though the deficiencies were negligible.     

Source apportionment of PM10 and PM(2.5) at Tocopilla, Chile (22 degrees 05' S, 70 degrees 12' W)

Tocopilla is located on the coast of Northern Chile, within an arid region that extends from 30 degrees S to the border with Perú. The major industrial activities are related to the copper mining industry. A measurement campaign was conducted during March and April 2006 to determine ambient PM10 and PM(2.5) concentrations in the city. The results showed significantly higher PM10 concentrations in the southern part of the city (117 microg/m3) compared with 79 and 80 (microg/m3) in the central and northern sites. By contrast, ambient PM2.5 concentrations had a more uniform spatial distribution across the city, around 20 (microg/m3). In order to conduct a source apportionment, daily PM10 and PM(2.5) samples were analyzed for elements by XRF. EPA's Positive Matrix Factorization software was used to interpret the results of the chemical compositions. The major source contributing to PM(2.5) at sites 1, 2 and 3, respectively are: (a) sulfates, with approximately 50% of PM2.5 concentrations at the three sites; (b) fugitive emissions from fertilizer storage and handling, with 16%, 21% and 10%; (c) Coal and residual oil combustion, with 15%, 15% and 4%; (d) Sea salt, 5%, 6% and 16%; (e) Copper ore processing, 4%, 5% and 15%; and (f) a mixed dust source with 11%, 7% and 4%. Results for PM10--at sites 1, 2 and 3, respectively--show that the major contributors are: (a) sea salt source with 36%, 32% and 36% of the PM10 concentration; (b) copper processing emissions mixed with airborne soil dust with 6.6%, 11.5% and 41%; (c) sulfates with 31%, 31% and 12%; (d) a mixed dust source with 16%, 12% and 10%, and (e) the fertilizer stockpile emissions, with 11%, 14% and 2% of the PM10 concentration. The high natural background of PM10 implies that major reductions in anthropogenic emissions of PM10 and SO2 would be required to attain ambient air quality standards for PM10; those reductions would curb down ambient PM(2.5) concentrations as well.     

Particulate matter concentration levels during intense haze event in an urban environment

This study assessed concentration levels of particulate matter (PM) in the ambient environment of Ilorin metropolis, Nigeria, during haze episodes. Meteorological data (wind speed and direction, rainfall data, sunshine data, relative humidity and temperature) were obtained. Aerocet 531S particle counter (MetOne Instruments, USA) was used to measure four mass concentration ranges of PM (PM_1.0, PM_2.5, PM₁₀ and the total suspended particles (TSP)) in 10 locations taking into consideration land use patterns. Surfer® version 8 (Golden Software LLC, USA) was used to model the spatial variation of particulate matter concentration levels using kriging interpolation griding method. Human exposure assessment was done using the total respiratory deposition dose (TRDD) estimates and statutory limit breach (SLB) approaches. The appearance of dominating weak southern atmospheric wind flow was observed as wind speed ranged from 0 to 6.811 m/s while solar radiation periods ranged from 0.3 to 3.5 h/day. The relative humidity of the metropolis ranged between 28 and 57%, while daily temperature was 15 to 36 °C. Highest concentration levels of PM measured were 73.4, 562.7, 7066.3 and 9907.8 μg/m³ for PM_1.0, PM_2.5, PM₁₀ and TSP, respectively. Very strong negative correlations existed between the PM concentration levels and microclimatic parameters. Spatial variation of the concentration level as modelled using Surfer® version 8 indicated that particulate concentration level increases from south to north. Concentration levels of PM for the 24-h averaging period were generally above the 24-h threshold limit value set by the regulatory agencies for all the locations.     

Air Quality and Monitoring Strategy in the Helsinki Metropolitan Area, Finland

The Helsinki Metropolitan Area Council (YTV) is responsible for air quality monitoring in the Helsinki area. Air quality has been monitored periodically since the late 1950s. An automatic SO2 monitoring network was constructed in 1975 and TSP measurements were added in 1978. Since then the network has been expanded and currently five automatic multicomponent stations form the basis of the network monitoring SO2, NO, NO2, CO, PM10 and O3 concentrations. Manual TSP and PM10 measurements are also conducted. Mobile monitoring units are also being used as well as special measurement campaigns. The effects of air pollution on nature are studied in bioindicator monitoring. An air quality index is used in order to inform the public of the current air quality situation. Changes in air quality are reflected in monitoring strategy. SO2 concentrations have decreased in the past two decades. Annual averages in 1995 were at or below 5 µg/m3. Traffic is the major source for pollutants even though catalytic converters have lowered traffic emissions somewhat. The highest annual average NO2 concentration at an urban site was 49 µg/m3 in 1995, and there has been no clear change in NO2 levels. There has been a decreasing trend in CO concentrations. Maximum annual TSP and PM10 averages in 1995 were 92 and 32 µg/m3, respectively. The highest average lead concentration was 0.01 µg/m3. Elevated concentrations are experienced from time to time. During the spring daily TSP and PM10 concentrations can go up to around 300 and 150 µg/m3, respectively. This is caused by resuspension mainly due to street sanding. Also a major winter NO2 episode occurred in December 1995. The highest hourly NO2 concentrations reached 400 µg/m3.